We present a theory of thermal conduction in a transition metal dichalcogenide nanocomposite structure with rough interfaces that accounts for the anisotropic conductivities of the host, the insert and the interface regions. The host and insert conductivities are calculated using a semi ab-initio method. The effects of specularity in phonon interface scattering and the thermal boundary resistance is incorporated through linking a phonon wavevector dependent specular scattering parameter to the average height of surface inhomogeneities, and the conductivity of the composite is calculated by employing an extension of a modified effective medium approach. Our work for spherical inserts of WS The determination of key parameters of a nanocomposite structure that control its physical properties, such as thermal, electronic and optical characteristics, is essential for future technological advances. The calculation of the bulk properties of nanocomposites where a small fraction of insertions of one material are embedded within a matrix of a different material, perhaps with a boundary layer between the insertion and the matrix, is a long-standing problem. Effective medium approaches (EMAs) are a widely used method of calculating properties  the directional dependence of the matrix thermal conductivity or dielectric constant must be accounted for ,16,17. IHowever, the originally formulated mEMA  and its Transition metal dichalcogenides (TMDCs) such as MoS studies ,22,23 deulations  are useda is the radius of the spherical insert, An emEMA calculation for a system with anisotropic interface resistance is performed in two steps. Firstly we compute the effective thermal conductivity of the insert and the interface regions :(1)κ*=κinsor see  accountiWe then calculate the thermal conductivity of the effective medium equation : (2)κE=κf is the volume fraction of inserts, Here nsor see  accountiThe required values of o method , which wIn order to include the effects of specularity, we define a momentum dependent parameter h et al. , we writThe value of The effects of finite Scattering from the sample boundary itself is taken to be purely diffusive and unaffected by the specularity parameter. Minnich and Chen  include Next, we discuss the thermal boundary resistance. This is a challenging property to calculate with any accuracy, since the assumptions of the prevailing models are strictly valid only in the continuum limit and exclude the effects of inelastic scattering and other anharmonic processes  and in-plane (x) directions. In both directions it undergoes a rapid decrease as the temperature rises before saturating above 400 K.  of Ref. .Panel (b) of Results for f, as one would expect. The effect of decreasing  inserts a,b, whicWhy is the deviation from the diffuse result greater for smaller particles? Recall from Equation  that theFor practical purposes, the above conclusion should be qualified slightly. We can estimate from the lattice constant of WSf and higher thermal conductivities for larger f, whereas we would expect a Minnich-Chen calculation  to provWe have used an extension of a modified effective medium approach (mEMA) to study thermal conduction in a transition metal dichalcogenide nanocomposite structure with rough interfaces by accounting for the anisotropic conductivities of the host, the insert and the interface regions. The role of specularity in phonon-interface scattering and in thermal boundary resistance is incorporated by implementing a simple phenomenological model relating momentum-dependent specular scattering and surface roughness. In general, it is found that the effect of specular scattering due to interface roughness is more pronounced for inserts smaller than 100 nm in the vicinity of 300 K. In particular, from comparison with calculations carried out in the diffuse limit, for spherical WS


This paper introduces an X-ray reflective anode with a diamond heat buffer layer, so as to improve heat dissipation of micro-focus X-ray sources. This also aids in avoiding the destruction of the anode target surface caused by the accumulation of heat generated by the electron beam bombardment in the focal spot area. In addition to the description of the production process of the new reflective anode, this study focuses more on the research of the thermal conductivity and compounding ability. This paper also introduces a method that combines finite element analysis (FEA) in conjunction with thermal conductivity experiments, and subsequently demonstrates the credibility of this method. It was found that due to diamonds having a high thermal conductivity and melting point, high heat flux produced in the micro-focus spot region of the anode could be conducted and removed rapidly, which ensured the thermal stability of the anode. Experiments with the power parameters of the radiation source were also completed and showed an improvement in the power limit twice that of the original. In the field of X-ray imaging, the improvement of image resolution has always been a key point for research. According to the projection imaging principle, there is an inverse relationship ,2,3 betwBased on the high thermal conductivity (TC = 1500–2000 W/m K) ,13,14 of(1) Preparation of the Diamond Heat Buffer layerUsed for uniform homogeneity, low deposition temperatures, and slight influences on physical properties of the diamond, in this experiment, the PECVD   Surface Metallization of the Diamond Heat Buffer layerThe diamond heat buffer layer separated from the Mo slice as soon as it was taken off the PECVD instrument after preparation. Then the diamond sheet was bonded tightly to a copper substratum. It was difficult to weld the diamond heat buffer layer and the copper substratum together by conventional soldering or plating because of the poor wettability and reactivity  between (3) Soldering the Copper Substratum and the Diamond Heat Buffer layerA special proportion of solder alloy was used under vacuum within high temperature conditions to solder the metallized diamond heat buffer layer and the copper substratum together, leaving a 15-μm-thick solder layer. Melt solder, wetting both the copper surface and the diamond surface, was cooled down. A gradient temperature was adopted for the heating and cooling to prevent the solder layer from cracking and loosening which can result from the different thermal expansion coefficients of the materials.(4) Metal Plating (Tungsten) on the Other Diamond SurfaceAfter the soldering was completed, the next step in the production process was to apply a tungsten film on the other surface of the diamond sheet. Tungsten, with a high melting point, is used widely in X-ray anode production. In addition, magnetron sputtering, a good method to extensively deposit high quality films, was utilized for the surface treatment on the other side of the X-ray anode. A general tungsten slice was used as a target in the experiment and a 2.2-μm-thick tungsten film was deposited on the other surface of the diamond sheet.In this study, tests were conducted for determination of the key properties of the diamond composite anode produced, which included:(1) Test of Bonding Strength between LayersIt is necessary to test the inter-layer bonding strength, which may influence the diamond composite anode’s scattering and other properties. The test was completed directly by cross-section characterization and analysis. The layers consist of the tungsten film, the diamond heat buffer layer, the metallization layer, the solder layer and the copper substratum. Scanning electron microscopy (SEM)  was used(2) Test of Bulk Temperature in the Focal Spot RegionA multi-functional X-ray generator, which is capable of simulating various actual work conditions of X-ray sources such as power and focal spot size etc., was used to determine and compare the bulk temperature in the focal spot region for different kinds of anodes. Under the conditions of constant power, the generator successfully kept the focal spot in a circular shape and at a size of 20 μm, which is the reference standard spot size most widely used in actual micro-focus X-ray inspections. The diamond composite anode was compared with a conventional tungsten film anode in the bulk temperature in focal spot region.a. Test of Surface Temperature in Focal Spot RegionAt present, there is no efficient way to detect surface temperatures in focal spots of X-ray anodes. Therefore, the proposal in this paper was to measure the infrared radiation spectrum at the focal spot and indirectly calculate the temperature in the spot by combining spectral analysis and processing technology. This will be explained specifically in the following section:For focal spot temperature determination, it was difficult to precisely locate the X-ray focal spot on an anode because the spot size was near to that of the infrared detector’s individual pixel. Therefore, infrared imaging spectrographs capable of detecting wave bands in the range 900–2500 nm, as well as an infrared lens whose focus length was 300 mm, were adopted in this study to scan the anodes inside the X-ray generator and obtain the infrared images in which each pixel had a corresponding infrared spectral curve. That is, through analysis and calculation on the infrared spectral curves corresponding to effective pixels projected by a focal spot on the CCD (Charge Coupled Device) the temperature at a specific location of the focal spot was identified.b. Comparison of the Vertical Temperature Distribution of Each Layer in the Focal Spot RegionThe diamond composite anode is a reflective X-ray source, whose heat is mainly conducted in the vertical direction, but the infrared imaging spectrographic method mentioned above can only measure the temperature on the surface of tungsten film and cannot characterize the anode’s vertical temperature distribution . A super non-uniform vertical temperature distribution can cause stress or structure changes in the materials of the anode and then degrade the inter-layer bonding strength. At present, it is still impossible to determine the vertical heat distribution in the focal spot region of the micro-focus X-ray anode through experimental methods. Therefore, the finite element method (FEM), which is usually used in heat transfer analysis, was introduced in this study to determine the vertical temperature distribution of each layer in the focal spot region. FEM can solve the position data for the related nodes inside the complex anode through discrete processing using temperature and heat flux. This method can characterize the temperature and heat flux density trends from the surface of the focal spot to the surface of the copper substratum. Moreover, the ANSYS software program  ,26 used According to experimental conditions and the properties of the materials constituting the diamond composite anode, the heat transmission experimental procedure can be turned into a two-dimensional unsteady heat transfer model, as shown in Direction of Anode Internal Heat Transfer: the horizontal (surface) heat transfer refers to the thermal conduction from the center of the focal spot to edge of the anode, while vertical inter-layer heat transfer refers to that through layers of the diamond composite anode to its convection surface, which depends on natural cooling. Then, the finite element method was used to determine the surface temperature and the vertical heat distribution at the focal spot of the diamond composite anode by giving a particular initial and a boundary temperature value. Similarly, the vertical heat distribution of each layer in the focal spot region of three other kinds of anodes  were analyzed and compared.c. Comparison of Temperatures at the Power LimitThe power was adjusted but other parameters of the X-ray generator remained unchanged to compare the maximum temperature distribution in each layer of the four types of anodes. The procedure mentioned above was followed for determination of the vertical and horizontal heat transfer of X-ray anodes at the focal spots.In The scanning distance across the anode surface was completed by an iterative approach where the distance was reduced approaching the focal spot region. In this way, surface temperature measurements of the anode reduced interference and improved measurement precision. The focal spot projected two effective pixels on the CCD, and the number was sufficient for temperature measurements at the anode’s focal spot. Then, by repeating measurements and calculations, the relationship between time (duration of electron beam bombardment) and surface temperature at the focal spot region was determined.The reliability of the finite element method was verified by surface temperature measurements in the focal spot region. This was completed by comparing the temperature value obtained using the method with that determined through experimental measurement.Surface temperature values obtained at different times by modeling and simulation and by experimental measurements are close and the average error does not exceed 9.2%. Hence, the finite element method used in this study is reliable. However, there are still two facts which can decrease the reliability: first, the simulation assumes an absolute vacuum, however in reality there is always a certain amount of oxygen trapped in the vacuum chamber which may react with the anode’s tungsten film and produce an oxide; and second, the soldering alloy used may not have uniform composition or contain impurities, resulting in slight value errors through the determination of the thermal conductivity and heat flux.To prove the superiority of the new diamond buffer layer anode in all conditions, two aspects, the temperature and heat flux of each layer, were analyzed. The equation is exclusively for one-dimensional vertical direction, where, q refers to the heat flux, T1 refers to the temperature at the center of the focal spot on the tungsten film, T2 refers to the temperature at the center on the surface of the copper substratum, λ refers to the thermal conductivity of the material, and δ refers to the thickness of the material. The equation indicates that when the temperature difference is similar and the thickness of the material is equal, the heat flux q, increases with the thermal conductivity λ. A larger q means there is more heat transferred from the tungsten film to the copper substratum and more heat is conducted away from the unit area. This is why this paper discusses nothing on changes of the heat flux onto the copper substratum of type (c). The tungsten film is thin and the heat flux onto the copper substratum barely changes.To summarize, the advantage of the new type of anode with a diamond heat buffer layer is that the bulk temperature in the focal spot region of the tungsten film and the temperature on the surface of the copper substratum are both much lower than those of the other types of anodes. This is because diamond is a kind of isotropic material with a polycrystalline structure, and its high interatomic bonding energy gives it a high melting point and a high thermal conductivity. Therefore, the diamond composite anode can rapidly dissipate heat transferred from the tungsten film vertically and horizontally and therefore prevent excessive heat buildup in the tungsten film.With the increase in the X-ray generator power, the temperature in each layer of an anode increases. It can be seen in (1)The inter-layer bonding results of the composite anode were smooth, and no obvious gap or crack was found in each layer. This showed that the diamond buffer layer and copper substratum can be combined by brazing.(2)For the problem of precise temperature measurement at the focal spot on the surface of an X-ray anode, an analytical measurement and processing method based on infrared radiation spectra was proposed in this paper. The highest temperature value corresponding to the spectral peak of the micro-focus area was calculated by the infrared radiation spectrum which measured in the relevant area indirectly. This method was specifically designed for small-focus area temperature measurements.(3)For the vertical temperature measurement through the cross section of an X-ray composite anode, a method based on finite element was presented in this paper, which was proven reliable by verifying the simulation result with experimental measurements that resulted in surface temperature determination of an anode.(4)Analysis of heat distribution at the focal spot region of four types of X-ray anodes with different structures demonstrated that the X-ray reflective anode with a diamond heat buffer layer has much higher thermal stability and its working power limit is twice that of other anodes.A new reflective tungsten X-ray anode with a diamond heat buffer layer was designed, and its inter-layer bonding strength, focal spot temperature limit and thermal stability were examined theoretically and experimentally. This composite anode improves the micro-focus area cooling environment by utilizing the high thermal conductivity of diamond material. Thus, the highly concentrated heat in the micro-focus area is buffered by diffusion and rapid transmission. The conclusions are as follows:


Mitigation policy is regarded as an effective strategy to achieve the purpose of building health resilience and reducing disaster risk with the current high frequency of environmental event occurrences. To enhance public acceptance of mitigation policy, the issue of decision-making behavior has been a concern of researchers and planners. In the past literature, qualitative measures employed to reveal the behavioral intention of hazard risk mitigation cause restricted outcomes due to the problem of sample representativeness and the fact that quantitative research is restricted to discuss the linear relationship between the two selected variables. The purpose of this article is to attempt to construct a Mitigation Policy Acceptance Model (MPAM) to analyze the behavioral intention of seismic risk mitigation strategies. Based on Dual Processing Theory, affective is conducted as the core variable for constructing two types of thinking processes, and the variables of risk perception, trust and responsibility are selected in MPAM from theories and past research. In this study, the mitigation policy of residential seismic strengthening, adapted in Yongkang District of Tainan, has been conducted as the case study. According to the results, the result of model fit test has confirmed the MPAM framework, and two thinking modes could be associated together when people face a risky decision-making process. The variable of affective is the most effective factor to influence each variable, and a direct effect on intention is also shown in this model. The results could provide suggestions in communication risk strategies for the government. Building city resilience has been a concern of governments in order to increase the capacity of spatial health systems through risk communication to reduce the negative impacts of shock on public health . The SenFrom the perspective of the subjectively expected utility model in Financial Decision Theory, people might be willing to support public policies for reducing the threat if decision-makers adhere to axioms of rationality. In other words, people could regard adoption behavior as an investment target and be willing to support it with considerations towards the cost and benefit. Some famous theoretical models such as the Health Belief Model (HBM) or Protection Motivation Theory (PMT) are grounded on a perspective of consequentialism for seeking the greatest effectiveness. In the process of rational consideration, the assumption is based on the complete information provided to make individual decisions. However, in general, the threat of environmental events could not be predicted completely. Recent natural hazards, such as earthquakes or hurricanes around the world, are consistent with the unpredicted threats from natural events. The uncertainty information may lead to susceptibility to the threat. As a result, people could rely on prior experience or life experience by making decisions through different considerations rather than a rational consideration process ,16. With the breakthrough of technological measurements, psychologists have confirmed a different type of consideration to be able to answer this problem of how to explain a risk decision-making process. Evans 2003)  combines03  combiThe successful implementation of environmental mitigation policy relies on strong public support. Research has been conducted to confirm the factors affecting public intention to adopt seismic mitigation policies by quantitative analysis, such as correlation analysis ,25, multThe aim of this study is to construct a new model, named Mitigation Policy Acceptance Model (MPAM), for analyzing the behavioral intention of mitigation policy acceptance. The theoretical framework of MPAM is based on the Dual Processing Theory. The variable affective is the critical driving factor for connecting the pathways and variables such as risk perception, trust and responsibility from past individual decision-making theories and literature are also selected in this model. The structural equation modeling (SEM) is employed as the methodology for (1) testing the availability of MPAM, (2) realizing the thinking process of decision making under risk, and (3) analyzing the structural relationship of each selected variable. The residential seismic strengthening strategy adopted in Yongkang District of Taiwan is conducted as the case study of seismic mitigation policy through questionnaire surveys. This article includes five parts: The framework of the new model in this study is based on the Dual Processing Theory for connecting the pathways of each latent variable in SEM. Three main concepts are shown in the framework of MPAM: (1) The variables, including risk perception, affective, and trust, are selected by past theories and the literature of policy acceptance and seismic preparedness to reveal the character of risky decision making with the intention of policy acceptance mitigation; (2) the variable affective is regarded as the core factor to connect each thinking process. In the rational thinking mode, affective may be regarded as the information required to change individual perception and attitude and has an indirect impact on behavioral intention. In the automatic thinking mode, affective may be the kind of feelings required to drive personal decisions and has a direct impact on behavioral intention; (3) structural relationship of pathways with two types of thinking processes, including rational thinking and automatic thinking, are formed by individual decision-making theories and psychological hypotheses. The former includes the Person Relative to Event (PrE) and the Affect-as-Information Theory. The latter contains the “Affect Heuristic” and “Risk as Feelings” hypotheses. The research hypotheses are outlined as follows and are represented in Hypothesis 1 (H1).The affective of seismic hazards may influence individual risk perception.Hypothesis 2 (H2).The affective of seismic hazards may influence the responsibility of seismic mitigation adoption.Hypothesis 3 (H3).The affective of seismic hazards may influence the trust of government information and policies.Hypothesis 4 (H4).The affective of seismic hazards may influence the acceptance intention for seismic mitigation policies.Hypothesis 5 (H5).The risk perception of seismic hazards may influence the responsibility of seismic mitigation adaption.Hypothesis 6 (H6).The trust of government information and policy may influence the acceptation intention for seismic mitigation policies.Hypothesis 7 (H7).The responsibility of seismic mitigation adaption may influence the acceptation intention for seismic mitigation policies.To confirm the new model presented in this study, the behavioral intention of seismic mitigation policy acceptance of the survey area residents were realized through the questionnaire. The survey was conducted between 23 October and 20 December 2014. There were a total of 417 effective survey responses, and the effective response rate was 92.7%. The respondents to the survey were reminded of some notifications. Seismic hazards are defined as an over 6.0 magnitude earthquake. The measurement of each variable is listed in Risk perception is the recognized perceived loss in a specific environment  and the In fact, the variable of risk perception has been measured with various definitions. According to the classification by Pan in 2012 , five kiThe influence of affective has not been given attention when analyzing behavioral decisions in past research. In recent years, several research studies discussing public risk perception pointed out the relationship between affective and decision behavior . Joffe eTrust is a personal feature that could arouse positive expectation in a relative position ,53. JamePast research has confirmed the effect of responsibility on hazard adjustment adoption ,36. The In sum, the framework of MPAM has some advantages to analyze the decision-making process of environmental mitigation policies: (1) Two kinds of thinking processes constructing the whole model respond the characteristic of risky decision making under information uncertainty; (2) the selected variables reveal the topic of mitigation policies acceptance; (3) the hypnosis of the causal path is based on theoretical foundation from interdisciplinary research and theories to ensure the reliability and availability modeling; (4) affective is the key factor to observe how to make the decision through two thinking systems. These traits could be determined by SEM and are reexamined in the Discussion.Taiwan is located at the Circum-Pacific seismic zone. According to official statistics, there were 3197 over 4.0 magnitude quakes that occurred in Taiwan Island in the past two decades. The official Seismic institution has predicted that there is a high possibility of a large earthquake happening in the future in Yongkang City. An over 5.0 magnitude quake occurred in February of 2016, bringing hundreds of casualties resulting from building collapses. According to the official statistics, approximately 10 thousand building cannot bear a high magnitude quake because of their low seismic capabilities. In this context, the governments, through providing subsidies, attempted to encourage individual seismic house strengthening.2, χ2/DF, GFI, AGFI and RMSEA. All the statistic tests, besides the p-value, passed, and it seems to show that the framework of this model has a good fit. In general, the value of χ2 may change obviously when the sample number is large. The value of RMSEA is lower than 0.05, and shows the great fitness of MPAM. In other words, the structural framework of MPAM is conducted by the results of the statistic tests. The results of the model fit test are shown in In the effect analysis of SEM , the facAccording to the results of SEM, the MPAM based on the Dual Processing Theory concludes some findings. Firstly, two different thinking modes truly exist when facing a risk decision-making process. In the case of residential seismic strengthening strategies, people would analyze the whole situation and conditions when they need to spend lots of time and money. On the other hand, people may also determine the decision by the affect heuristic mode when facing a decision between risk and uncertainty. This confirms that a rational-behavior-based theory is not enough to explain the whole public decision-making process. Secondly, the selected variables of trust and responsibility have an impact on behavioral intention. These results confirm the importance of these two variables in the past literature, of whether people are willing to accept public policies with uncertainty or not. Thirdly, the variable of affective has direct and indirect effects on behavioral intention, revealing the fact that the importance of this core variable has a significant impact on both rational and automatic thinking modes.This study attempted to present a new model to realize the intention behavior when people faced risky decision-making. According to past psychological research, affective has been confirmed to have an influence on intention behavior ,31,36. TAccording to the results of SEM, some discussion about the relationships may be shown in the following context. From the results, Hypothesis 2 has a negative effect on the factor of responsibility. A different result which is inconsistent with the preview hypothesis is shown in this study ,43. AccoMAPM confirms two thinking process exist when people make decisions on environmental mitigation policies with uncertain information. People may have an intuitive feeling or rational thinking that affects their behavioral intention. Also, the pass of model fitness shows the reliability and availability of variable selections and causal structure in this model framework. In the past literature, many researchers have devoted themselves to conducting the effects of policy incentives or personal social characteristics on mitigation policy acceptances for enhancing the effectiveness of implementing policies. In fact, people may support public policies through quick-thinking rather than logistic and rational thinking process. The results are shown for the direct and indirect impacts of affective on the behavioral intention in the study area. In this case, governments should think how to release public anxiety and worries of uncertainty through effective risk communication for achieving a successful implementation and adaption. In sum, the framework of MAPM provides a different way to analyze public willingness of environmental mitigation policies, and it is helpful for governments to develop risk communication strategies.The study on exploring the process of whether people are determined to adopt mitigation policies has been a concern of governments with the high frequency of environmental hazards occurring in recent years. The re-emphasis is on mitigation, and preparedness in modern disaster risk-management arouses more importance in the characteristics of the dramatic consequences brought on by extremely hazardous events. In this study, MPAM-based Dual Processing Theory is proposed to reveal the structural interaction between the selected factors and mitigation policy acceptance to explain the thinking process of the public from automatic or rational systems as a response to seismic hazards. A case study area of Yongkang City in Taiwan is conducted to analyze the decision making process of residential seismic strengthening policy. The great model fitness (RMSEA < 0.05) is shown by the statistical tests, and the effect of affective is emphasized in the model of this article for explaining the structural decision process and has been confirmed by the results in this paper. The affective has a direct impact (0.221) and an indirect effect (0.005) on the intention. On the whole, MPAM shows the availability to analyze the decision-making process and confirms that people may support public policy through quick-thinking process rather than logistic consideration when facing uncertainty. The question why the past rational-based model could not completely explain the behavior of supporting public policies could be answered, even if it is helpful for people to reduce the losses and decrease the reduce the risk potential to life. In this study, a preliminary result of MPAM is shown for analyzing the individual decision-making process of residential seismic strengthening policy. The future work could apply MPAM in comparison with an existing theoretical model through different study areas or mitigation policies for realizing the potentiality and restriction of the new model. The results in the paper could suggest to the government how to make risk communication strategies for residents. It is believed that it could be helpful for enhancing health resilience and reducing the pressure of spatial health systems through reducing negative impacts of future environmental hazards.


The micromanipulation of micro objects is nowadays the focus of several investigations, specially in biomedical applications. Therefore, some manipulation tasks are required to be in aqueous environment and become more challenging because they depend upon observation and actuation methods that are compatible with MEMS Technology based micromanipulators. This paper describes how three grasping-releasing based tasks have been successfully applied to agarose micro beads whose average size is about 60  The development of the ability of manipulating micro objects has a high impact on several applications, such as biomedical operations and minimal invasive surgery, as only representative examples. About a hundred different microgrippers have been presented in literature ,2 for a In 2002 a microgripper has been built by combining silicon fingertips fabricated by a micro-machining process and conventional piezoelectric actuators . This miA superelastic alloy microgripper has been fabricated by electro-discharge machining and integrated with electromagnetic actuators and piezoelectric force sensors . For theCell biomechanics has been investigated by an integrated platform that combines both force sensing and actuation . To achiMEMS Technology based microgrippers have been used to grasp and release micro- and nano-particles ,8 or HeLA 3D structure, electroplated nickel fabricated, magnetically actuated micro-assembled microrobot prototype, with 1 mm overall size, has been used to test a multi-axis MEMS force and torque sensor . RecentlIn 1995 micro Physics has been applied to micromanipulation tasks and many interesting phenomena involved in the handling of micro objects were identified. Attractive forces have been modeled and experimental tests have been carried out . These rInteractive forces between micro objects and a microgripper surface have been studied also in 1998 . In partThe above mentioned progress suggested possible developments in surgery . MicroroMore examples of applications of MEMS to the development of biomedical instruments are available in literature ,24,25. FIn the present investigation agarose has been used to test the gripper capabilities. Agarose-based polymers are naturally inert and biocompatible materials whose mechanical properties are similar to those of soft tissues. They are also very suitable to be employed as carriers for various biomedical applications . FurtherAgarose-based micro beads are a well-established helping tool in the biomedical field for a variety of applications such as protein detection, DNA hybridization and in general as a mean to immobilize biomolecules in order to support reactions and to permit a faster molecular detection with higher sensitivity and lower reagent consumption, making it an ideal choice for microscaled lab-on-chip devices . More spThis paper describes an experimental campaign aiming at reporting three micromanipulation tasks that have been performed on micro beads having variable sizes, from 45 The grasping-releasing basic operations have been tested in and outside a water drop and then the following tasks have been successfully documented: (i) the extraction of a single micro bead from a drop; (ii) the insertion of a single micro bead into the drop; (iii) the grasping of a single micro bead inside a water drop.The experimental activities described in this paper much owe to the past years, during which a new microgripper has been developed by the team, from the early stage of concept design to the operational testing, through the following phases: design ,47,48, o methods  toward tThe described experiments consist of a combination of basic maneuvers, such as grasping, handling and releasing, applied by the developed microgripper to agarose micro beads in an aqueous solution.After an in-depth study, Sepharose© CL-4B agarose-based micro beads were chosen for the proposed experiments. The micro-beads have diameters which span from The device under test (DUT) is a lumped compliance MEMS-Technology based system embedding two compliant hinges, namely, two Conjugate Surface Compliance Hinge (CSFH), that have been positioned in order to allow the two jaws to rotate around a fixed revolute axis. The mobile axes are activated by means of rotary comb drives that use electrostatic principle of actuation. Deep Reactive Ion Etching (DRIE) allowed the microsystem to achieve reasonable aspect ratios   embedding a digital camera was employed to monitor the experiment. An overall view of the entire experimental setup is represented in In The identification of the actual values of design, operational and control parameters is a fundamental issue for the success of the target task. Some values have been already identified by measurements or numerical simulations, some of them are introduced in the present paper, while some other parameters will be studied next year. For the sake of completeness, In the next section, the main phases necessary for the correct execution of the experiment are described: the preparation of the Sepharose CL-4B agarose-based micro beads in aqueous solution, the positioning of the water drop near the microgripper jaws, the grasping and release phases and the bead grasping.As a preliminary phase, the agarose micro beads underwent a coloring procedure by means of a blue food dye to be better distinguished and recognized from the aqueous solution. Blue food coloring E 132 was preferred more than other types of dyes in order not to alter the chemical structure and the features of the beads. The pre-colored beads were then diluted in deionized water. Consequently, droplets of the resulting solution were collected and placed on top of the spoon-shaped probe with the help of a syringe.Once the droplets have been positioned near the microgripper jaws, the grasping/releasing phases are performed by micro-positioning the device and then applying voltage by means of three tungsten probes electrically connected to the power supply circuit. The water drop containing the micro beads is sustained by a spoon-shaped metal probe that is guided by a micro-positioning guide.(i)the extraction of a single micro bead from a drop;(ii)the insertion of a single micro bead into the drop;(iii)the grasping of a single micro bead inside a water drop.In this section the results of three different micromanipulation tasks are reported:These three tasks have been performed by using a semiautomatic procedure that makes use of gross motion micro positioning probes to approach the drop with 3 degrees of freedom (DoF) motion and fine gripping motion provided by externally applied voltage.The experiments have been carried out at a speed that was low enough to exclude dynamic effects. The pictures in the three series have been taken at variable time intervals, with an average rate of 1 picture every 6 s. An average of one successful grasping every 4 attempts has been experienced during the tests. This success frequency can be improved by modifying agarose beads size and concentration, drop size, water evaporation and adhesion.Using the equipment described in the previous paragraph some attempts have been made in order to extract one single agarose bead from a single drop. a) to (z) a time ordered sequence of views of the operational field. The sequence is described by the following stages.a) to (g).First, the micro-gripper is set in its initial state  and the water drop is guided toward the gripping device by operating the spoon-shaped droplet host micro-positioning device, as shown in h) to (k).The jaws-tips are then inserted into the water drop, as shown in Figures from ; the bead centering in the monitored pane is made via direct observation, while the transverse centering is done by using the microscope focusing.l) to (o). The DUT is now in its grasping state.When a single micro bead is centered in the operating volume, the grasping phase is activated and the device is actuated by supplying a gradually increasing voltage from zero up to 24 V to the jaw-connected electrodes and keeping null the voltage on the ground electrode. This induces the gradual closure of the jaws and a successful bead grasping, as shown by frames from (p) to (s), until the bead is completely extracted, as in frame (t).The water solution is then moved away from the closed grip system, operating the spoon-shaped droplet host micro-positioning device, as shown by frames from (u).During removal motion, part of the residual water on the jaw-tips evaporates, as illustrated in v) to (z).Finally, a change in the bead dimension occurs due to evaporation phenomena. In fact, the passage from a wet to a dry environment implies a significant and progressive shrinking, as shown by frames from (The second task (ii) consists in an operation which is opposite to the first task: the insertion of a single micro bead into the water drop. Since there is no other way to insert an agarose micro bead between the microgripper jaws, this task could take place only after the first task (i) had been completed. Task (ii) was performed not more than a minute later than task (i) had completed.a) to (l).a).An agarose bead grasped by the device jaws is shown in b) and (c).The water drop progressively approaches the device, as illustrated by frames (d) and (e).The micro bead is successfully inserted in the drop of solution, as reported by frames (f) and (g): in this phase, the voltage applied to the device is decreased down to 0 V.The micro bead is then successfully released, as documented in h) to (l).Finally, the device is extracted again from the water solution, as reported in frames from : the grasping of a micro bead inside a water drop. This particular task is crucial to perform new ways for dynamic characterization of cells and other types of microstructures, paving the way for new experimental micromanipulation scenarios. In fact, this particular device could be used in the future for the static force, stiffness, viscous and dynamic characterization of more complex cells or micro-structures.a) to (n), show the main steps of this experiment.a) to (c).First, the agarose bead is progressively approached, as depicted by Figures from (d).Then, the jaws grasp one agarose bead as illustrated in frame (e) to (h) describe how the bead is squeezed.Frames from (i).After that, the bead is released and let to go (j) to (n), represents the extraction and removal of the jaw-tips from the drop.The final sequence of frames, from  extraction of a single Agarose micro bead from a drop; (ii) insertion of a single Agarose micro bead into a drop; (iii) grasping of a single Agarose micro bead inside a water drop. These tasks are basic operations that had not yet been tested for the new class of CSFH equipped microgrippers. The results are provided as frames sequences that demonstrate, in an objective and reproducible way, all the above described experimental phases.


In order to provide timely, reliable, and comprehensive data for the maintenance of highly stressed geometries in sheet-bulk metal forming tools, this article features a possible setup by combining a 3D measuring endoscope with a two-stage kinematic. The measurement principle is based on the projection of structured light, allowing time-effective measurements of larger areas. To obtain data of proper quality, several hundred measurements are performed which then have to be registered and finally merged into one single point cloud. Factors such as heavy, unwieldy specimens affecting precise alignment. The rotational axes are therefore possibly misaligned and the kinematics and the hand-eye transformation remain uncalibrated. By the use of computer-aided design (CAD) data, registration can be improved, allowing a detailed examination of local features like gear geometries while reducing the sensitivity to detect shape deviations. In the context of increasing automation and digitalization of integrated industrial manufacturing processes, monitoring and automated quality assurance are essential factors, strengthening the importance of new measurement approaches. Optical measurement techniques are contactless and can meet current and future emerging requirements like significantly reduced measuring times while increasing the resolution of the data ,2.Sheet-bulk metal forming is a newly emerging forming process, producing complex geometries due to a combination of deep drawing and bulk metal forming . PossiblThe measuring system was developed within the last years and is intended to perform measurements in geometries which would be unreachable for most common systems. This is done by using a small and flexible measuring head. The system is based on the fringe projection approach in order to quantify the condition of sheet-bulk metal forming tools in an industrial environment . An endoSince the in situ determination of deviations and the quantification of wear is limited to certain single features, representing the condition of the entire specimen, it is further necessary to precisely measure the entire geometry of each forming tool enabling comprehensive analysis. Due to the given geometrical constraints and the limited bending radii (∼20 cm) of the fibers, the workspace of the kinematics robot is restricted, leading to an offline inspection setup which shall be presented here. To guarantee comparable results for both principle tasks, it is important to use the same measurement system with identical optics.Based on this first industrial application, introducing a robust system for time-effective and automated full-field 3D measurements at high resolution, a multitude of possible applications and future research is conceivable. The given setup is expected to enable a much better characterization of abrasion and wear, leading to deeper process understanding and helps to optimize certain process parameters. Additionally, it provides the basis for in situ inspections by identifying highly stressed geometries.The approach is developed for measuring a specimen with multiple inside-lying geometries. Such a specimen is illustrated in By combining several hundred measurements from different poses, the approach given here is trying to obtain detailed point cloud data and could therefore potentially measure all features. Since the whole inspection process shall be automated and less time consuming, a multi-axis kinematic is appropriate for traveling to all desired poses. A particular focus is therefore given to the alignment of all measurements. Given the fact of heavy, unwieldy specimens, various challenges affect precise alignment based on positioning data. This is especially relevant when the rotational axes are slightly misaligned. Moreover, the kinematics and the hand-eye transformation remain uncalibrated in order to meet the requirements of rapid inspection.The experimental setup is designed to analyze the condition of sheet metal forming tools after certain cycles. The specimens are machined with high precision and reference geometry data is available. Therefore, the assumption was made that form deviations are negligibly small and computer-aided design (CAD) data based registration can be used to align the measured data. While this should allow a detailed examination of local features like gear geometries, it may reduce sensitivity to detect global deviations. The following sections aim at giving an overview of all crucial data processing algorithms and show first results.In The fringes, created by the DMD, are injected into an endoscopic fiber by the use of a microscope objective and a tube lens. The fiber itself is a combination of multiple flexible glass fiber cores, combined to a fiber bundle in a common cladding. The fiber in use features 100,000 individual fiber cores (pixels) at a diameter of 1.7 mm and a length of 1 m and is supplied by Fujikura Ltd. . The fiber is connected to a measuring head where the pattern is projected onto the specimen by using a gradient-index (GRIN) rod lens . Due to the small apertures of the fiber, the light source has to feature a comparatively small chip diameter, in order to reduce the loss of light. The maximum optical power output (white projector image), measured in focus, is approximately 5.8 mW [Depending on the reflectance characteristics of the specimen, typical exposure times range from 10 to 50 ms. Since technical surface geometries exhibit highly varying reflectivity, the dynamic range of the sensor can be enhanced by combining differently exposed images to a high dynamic range image. Usually, eight different projection patterns are required to perform a measurement.Different measuring head configurations have emerged throughout the development, each optimized for a certain set of requirements. This section provides an overview of the different types and shall outline each individual scope of application. The measuring head, using two liquid lenses, offers a good compromise between maximum focus and depth of field. Since two liquid lenses add ten more optic interfaces to the optical system, a loss of approximately 50 to 55% optical power was measured in focus. Other drawbacks include the need for a time-effective autofocus, the electrical control setup, the much more extensive calibration and the larger physical size of the measuring head itself.The specimen requires a depth of field of approximately 2.5 mm compare c which iOptical properties of the technical surfaceWorking distance, field curvature and depth of field (DOF) of the opticsSize and form of the specimenOrientation between measuring head and the specimenStray light and light scatteringTo quantify the accuracy of a single measurement, several external factors affecting the results should be taken into account:The evident limitation of triangulation-based optical measurement approaches is given by the optical properties of the specimen. If the optical beam path is not unambiguously reconstructable, a measurement cannot be performed. This applies particularly to  transparent surfaces. However, specular reflection can also be considered as a problem. By the use of HDR-imaging, a measurement can be performed in the highlight spot as long as the specimen does not feature structures causing multi reflections. Particularly due to the involute tooth flanks in combination with the fine surface properties of the specimen, it would be impossible to triangulate useful results. To overcome this, anti-glossy spray is applied. This leads to changes of the geometric form of the specimen and shall later be evaluated.As mentioned in The flowchart, given in At first, a rough initial transformation The alpha coordinate system is placed at the center of rotation. By using the radial position data of the stage Equation . VerticaBefore starting the registration operation, a denoising algorithm is applied, removing separately scattered points. The algorithm is based on the work of  and compAfter pre-aligning, the denoised and downsampled measured data is registered to the alpha data. To enhance performance, only features which exist in the measured point cloud shall be taken into account. The current transformation Equation ) of the After having aligned the first measurement with the alpha point cloud, the progress is repeated, starting with trimming and resampling of the next alpha geometries, based on the current rigid body transformation Equation , the curThe process of stitching and merging combines two registered point clouds with each other by removing points, mainly in the overlapping area. This procedure is repeated for all data sets. Currently, this is done by using the Computer Vision System Toolbox which is part of Matlab, supplied by The MathWorks Inc. .s.The process of merging is illustrated in Equation ). The siThe final deviation map is then calculated, based on the distance metric presented in P and X from both point clouds, a rigid transformation is computed. The goal behind this is, as shown in The determination of the initial transformation is the only operation requiring user input. By selecting corresponding point sets P and X according to Equation . The correspondence between camera and projector is determined by sinusoidal patterns being shifted through the scene. As can be seen in By merging all measured point clouds, captured from different perspectives, bigger holes in certain point clouds can be filled. The trimming threshold influences the results and conclusions of the inspection process. A more aggressive threshold leads to a decrease of the measurement uncertainty while reducing data density at areas of bad illumination. The determination of the threshold value should therefore always be done in accordance with the individual geometrical characteristics and possible wear of each specimen.In order to calculate a deviation and to apply a registration algorithm, an alpha point cloud must be created from a common CAD file. The algorithms are optimized for the In order to enhance performance and to ensure that the registration algorithm guarantees comparable results for all given measurements with the same set of parameters see , the refThe first step is to trim all vertices and corresponding faces beyond the gear geometries. This is done by applying a radial threshold (50 mm) to the data. To create additional point cloud data, points on each polygon have to be sampled. The total number of sampling points for each polygon is calculated by comparing the area of each polygon with the total area of all polygons and the number of required samples. Since these polygons are triangles, the surface area in 3D space is given by the half cross product formula.A method for generating unbiased random points with respect to the surface area was introduced by  and has A to the opposing edge P. The sampling of 100,000 points lasted for about half a second. It has been experimentally proven to be important to generate uniformly distributed random numbers. Otherwise, this approach does not produce useful results and sampled points seem to accumulate in one edge of each triangle.By generating the two random numbers p between two point clouds p is ranging from 1 (City block distance) to ∞ (Chebychev distance). For By the use of a proper distance metric, a point to point distance between two point clouds can be calculated. The Minkowksi distance of order The metric is also used for the registration of each point cloud by combining the approach based on the Euclidean distance with a rigid affine transformation to define the mean-squares objective function: R the rotation matrix and Let  simplex . More re simplex ,17.In this case, the iterative closest points (ICP) algorithm from the computer vision system toolbox  provides an additional stop criterion. In combination with good initial values, the algorithm aborts the calculation based on these termination criteria in most cases. A typical registration operation takes <10 s by calculating 5 iterations on the average. In order to make assessments with regard to indications of possible defects, the point cloud from The arithmetic average is 0.0356 mm with a standard deviation of 0.0188 mm. The greater measurement uncertainty is presumably caused by averaging (due to merging) all minor misalignments throughout all 588 measurements.A robust system for time-effective and automated full-field 3D measurements at high resolution for industrial applications has been introduced. The compact and flexible design of the 3D measuring endoscope, based on the endoscopic fringe projection approach, can be used to measure the shape of geometries which remain out of reach for traditional tactile or other measurement principles. In this application, several hundred single measurements were performed to scan all features of a rotationally symmetric forming tool. Much better stitching can be achieved by using a CAD based registration approach. This is especially relevant when the rotational axes are slightly misaligned and the kinematics and the hand-eye transformation remain uncalibrated and therefore the positing data of the stages cannot be used to precisely stitch all point clouds. Against the background of rapid inspection and heavy and unwieldy specimen, requiring extremely precise alignment, this approach can be considered reasonable. By utilizing and resampling CAD data, the registration can successfully stitch all measured data and calculate the overall deviation. The registration approach shifts the focus in favor of a very detailed examination of local features like gear geometries while reducing the sensitivity to detect shape deviations which should be taken into consideration.To reduce fragmentation at the back edges, the number of vertical measuring positions should be enlarged. The fragmentation at the side edges is probably caused by the arrangement of the camera and projector optics at the measuring head. A clear improvement could be achieved by adding another projector into the system, arranged on the other side of the camera.Furthermore, this setup is supposed to enable a much better characterization of abrasion and wear. This can be used to optimize the threshold level, introduced in Since the original geometrical properties of the specimen are not known exactly, the measurement uncertainty cannot be concluded. A potentially significant source of deviation is given by the layer of applied anti-glossy spray which presumably leads to a more or less constant deviation offset. Nevertheless, despite this first approach, it is expected that future potential damage of the specimen can be identified and measured reliably. A detailed assessment of the systems performance and sensitivity to identify various defects should be made shortly after enough data has been collected and the system has proven to be is suitable for permanent use in various industrial applications.This initial approach is providing scope for further improvements. It is supposed, that higher uncertainty in contrast to one ideal single measurement appears to be connected to the registration and the merging operation. Whereas the error susceptibility of the registration seems difficult to reduce, merging could be significantly improved. Instead of combining the points in each voxel the filter should keep only the points of good condition in future developments. Therefore, the same map which was originally used to mask each point cloud see  could beMeasuring and all data processing took about 3 h, which can be significantly accelerated. At first by parallelizing point cloud computation and measurement. Despite GPU support, the most time-consuming step is calculating the final point-wise deviation based on the smallest Euclidean distance of the alpha and measured point cloud. To increase performance, additional voxel filters shall be applied. An alternative approach would be the transformation of both point clouds into cylinder coordinates and the rearrangement of every axial layer in order of ascending angle. Each layer can then be resampled by interpolation according to a given grid. Finally, all points can be projected onto a plane. By subtracting both images , the deviation can be calculated. According to a first assessment, a deviation can be calculated within seconds while harboring minor interpolation errors.A more precise approach would be the calculation of the deviation based on a point-plane metric by using the polygon data stored in the alpha mesh. This metric could also be used for the registration algorithm superseding the alpha point cloud resampling step.


Injuries sustained due to attacks from explosive weapons are multiple in number, complex in nature, and not well characterised. Blast may cause damage to the human body by the direct effect of overpressure, penetration by highly energised fragments, and blunt trauma by violent displacements of the body. The ability to reproduce the injuries of such insults in a well-controlled fashion is essential in order to understand fully the unique mechanism by which they occur, and design better treatment and protection strategies to alleviate the resulting poor long-term outcomes. This paper reports a range of experimental platforms that have been developed for different blast injury models, their working mechanism, and main applications. These platforms include the shock tube, split-Hopkinson bars, the gas gun, drop towers and bespoke underbody blast simulators. A range of experimental platforms is essential to recreate the various injury mechanisms due to an explosion.The versatility of experimental devices ensures their adaptability to specific in vivo, ex vivo, and in vitro experimental models of blast injury.Ensuring that the boundary conditions of the sample tested are appropriate and biofidelic is key for validation of computational simulations and for replicating specific blast scenarios and injury mechanisms.The relevance, design, fabrication and translation of these experimental platforms requires a wide range of expertise and is dependent on interdisciplinary collaboration between science, engineering, and medicine.et alet alModern conflict and terrorist attempts in civilian settings have seen an ever-increasing use of explosive devices as the weapon of choice. At the same time, medical treatment at the point of wounding and beyond has reached unprecedented levels of efficacy, resulting in an increased number of survivors with severe injuries.Historically, blast injuries have been categorised mainly based on how the physical aspects of the explosion act in causing the injury.To understand blast injury in depth, it is important to decouple the various injury mechanisms and to recreate time-dependent effects of blast in well-controlled laboratory environments. An explosion is a dynamic process that evolves with time. Detonations can compress the surrounding media to hundreds of kilobar inside the fire ball; the pressure quickly drops to a few tens of bar just outside the fire ball and exponentially decays to the ambient pressure with distance.Due to this complicated nature of explosions, the resulting trauma is usually due to multiple types of injury mechanism, rendering the design of protective strategies and of ongoing casualty care rather challenging. Research studies on blast injury require experimental capability outside the loading range that most conventional machines can offer and with a versatile tunability for individual parameters of the simulated blast. This paper presents and discusses the development and application of a range of platforms that can satisfy the dynamic conditions of blast loading, and focuses on platforms developed in the Royal British Legion Centre for Blast Injury Studies (CBIS) at Imperial College London.The shock tube is a conventional apparatus for generating the pressure profile of the blast wave as it is transmitted away from the fire ball region of the explosion. The CBIS shock tube is a stainless steel, 3.8 m long, air-driven system with 59±1 mm internal bore . The syset al used a platform where only the left limb of the rodent specimen was exposed to the blast wave to avoid unwanted complication in other body parts.et alAt the target end, the system can be adapted to study the effect of blast loading on biological specimens such as in vitro cell cultures, ex vivo tissues/organs, and in vivo whole animal models . EftaxioThe SHPB is a versatile, mechanical loading apparatus used to generate loadings over time durations from hundreds of microseconds up to one millisecond, therefore achieving strain rates in the hundreds and thousands per second. A conventional SHPB system consists of an arrangement in series of two long, cylindrical bars called the input bar (IB) and the output bar (OB) between which the sample of interest is sandwiched . A projeet alBased on a modified SHPB apparatus, Sory The platform has also been used to examine the effects of blast-relevant mechanical insults on the stimulation of osteogenesis in periosteum-derived mesenchymal stromal cells (PO MSCs) encapsulated in a 3D scaffold.A 32-millimetre-bore gas-gun system has been developed to investigate secondary blast-injury mechanisms .19 The gTo adapt the system for studies with fragment-simulating projectiles (FSPs) whose dimensions are usually much smaller than the gas-gun bore, the sabot is designed with an aluminium front plate, which can accommodate FSPs of desired shapes and sizes. A sabot stripper construction is installed at the entrance to the target chamber to halt the sabot while allowing the FSP to continue towards the target. Additional safety layers of wood, rubber, and steel are padded at the back of the target chamber to annihilate any remaining kinetic energy of the FSP if it passes through the sample.et alThis gas-gun system is currently used to investigate the penetration of blast fragments into soft tissue simulants and the tibia. Studies by Nguyen The Gardner impact test, commonly known as drop-weight impact test, is characterised by the vertical dropping of an impactor of variable mass, striking a specimen at the base of the tower. This platform can be used to study injuries by blunt impact, characterise tissue at high strain rates, as well as to investigate the performance of protective equipment under impact loading. The impact energy is determined as a function of the drop height and drop mass. Three CBIS drop towers are of similar design  but vary−1.WebsterAnUBIS has been developed to replicate the loading applied to occupants’ lower limbs in underbody blast (UBB).et alAnUBIS has been used in conjunction with postmortem human specimens (PMHSs) and instrumented anthropometric test devices (ATDs) to estimate the probability of injury as well as to assess the performance of protective equipment. Using both PHMSs and the Hybrid-III ATD, Grigoriadis Although AnUBIS is able to recreate the lower limb musculoskeletal injuries caused by UBB, the system (and others like it) uses cadaveric tissue. While this is arguably biofidelic anatomically, it is not reliable for recreation of internal organ injuries, which are important for prediction of mortality in UBB.The Rig for in vivo Underbody Loading (RivUL) is a modified gas gun that fires a polycarbonate projectile vertically along a 1 m honed barrel . The proAdditional equipment, including high-speed photography, allow measurement of the biomechanical response of the animal to the loading. Injuries noted in our initial rat model include haemoperitoneum from extensive liver laceration and parenchymal lung haemorrhage. These injuries are sustained from whole-body vertical acceleration without secondary impact. Such injuries may be analogous to those described in human incidents of UBB.Experimental platforms that can simulate blast loading mechanisms to the human body have been developed recently due the extensive use of explosive weapons in the last decade and the resulting need to understand the pathophysiology of blast injury. Various groups worldwide have adapted existing or created new experimental platforms to study blast injury. This paper presented a collection of platforms developed and used in CBIS to study primary, secondary and tertiary blast-injury mechanisms. The exemplar applications presented here are by no means exhaustive. Furthermore, the versatility of the designs ensures the ease of adapting the platforms to study blast injury to various parts of the body, as well as to characterise the efficacy of protective devices. For example, the shock tube can be fitted with an expansion chamber to study traumatic brain injury, where a bigger area in the sample needs to be exposed. Future adaptations of such platforms need to address the combined effects of primary and secondary blast, as injuries such as traumatic amputation or pelvic-floor rupture are a result of both primary and secondary blast mechanisms, although the contribution of each to the resulting injury is unknown.Moreover, the well-controlled boundary conditions and injury outcomes produced from these experimental platforms offer a test bed for validation of computational simulations of blast injury. Computational simulations offer a great alternative to difficult physical experiments and a means for running a multitude of virtual tests. For example, a finite-element model of a lower-limb ATD with combat boots was developed to simulate the injuries in UBB, validated against the experiments in AnUBIS.As the threat posed by the use of explosive devices persists, the combined efforts of an interdisciplinary research structure are required to understand blast injury fully and to contribute to the improvement in its treatment, protection and rehabilitation.


One key issue in the post-genomic era is how to systematically describe the associations between small molecule transcripts or translations inside cells. With the rapid development of high-throughput “omics” technologies, the achieved ability to detect and characterize molecules with other molecule targets opens the possibility of investigating the relationships between different molecules from a global perspective. In this article, a molecular association network (MAN) is constructed and comprehensively analyzed by integrating the associations among miRNA, lncRNA, protein, drug, and disease, in which any kind of potential associations can be predicted. More specifically, each node in MAN can be represented as a vector by combining two kinds of information including the attribute of the node itself  and the behavior of the node in the complex network (associations with other nodes). A random forest classifier is trained to classify and predict new interactions or associations between biomolecules. In the experiment, the proposed method achieved a superb performance with an area under curve (AUC) of 0.9735 under a five-fold cross-validation, which showed that the proposed method could provide new insight for exploration of the molecular mechanisms of disease and valuable clues for disease treatment. There are many types of biomolecules inside living cells that form multiple associated regulatory networks as pathways or direct participants to maintain a wide variety of life activities and key functions ,2,3. ForIn recent years, several computational methods based on public data sets have been put forward successively and was carried on in practice to guide and support manual experiments . These pIn this study, we present a model to predict the relationship between any small molecules in a cell based on the node attribute and node behavior through a more systematic and comprehensive view. The complex associations network of biomolecules  using associations between lncRNA, miRNA, disease, drug, and protein. We hope that this work will inspire more research on representational learning on biological networks.In order to systematically and holistically establish the molecular association network, known associations between biological molecule transcripts , diseases and drugs were downloaded from multiple databases. The details of the final experimental data obtained after performing the inclusion of identifier unification, de-redundancy, simplification, and deletion of the irrelevant items are shown in the following After aggregating the above database, we separately classified the different nodes to get the final statistics as shown in the following The sequences of miRNA, lncRNA, and protein are downloaded from miRbase , NONCODEThe Medical Subject Headings (MeSH) is a comprehensive searchable control vocabulary, which is organized by the National Library of Medicine furnished a rigorous index for journal articles and books in the life sciences. The top-level categories in the MeSH descriptor hierarchy are: Anatomy (A), Organisms (B), Diseases (C), Chemicals Drugs (D), and so on. In this system, each disease can be represented by a directed acyclic graph (DAG) generated through its MeSH, accurately and objectively describe its own characteristics. The details to describe the disease with DAG is as follows: DAG(D) = , E(D)), N(D) is the set of points that contains all the diseases in the DAG(D). E(D) is the set of edges that contains all relationships between nodes in the DAG(D). An example of the disease Astrocytoma’s DAG is as follows in D, the contribution of any ancestral disease t to disease D is as the formula:For the diseases that are included in MeSH, the semantic similarity that is calculated by means of DAG can be chosen to represent the disease according to the previous literature . The semD to itself is 1 and the contribution of other nodes to D will be attenuated due to D:i and j can be calculated by the following formula:Similar to the Jaccard similarity coefficient, the semantic similarity between the diseases The smiles of drugs were downloaded from DrugBank and then transformed into the corresponding Morgan molecular fingerprint by the python package.h and the decoder that reconstructs an approximation x̂ from the hidden representation h.In order to reduce noise and normalize attribute information to a uniform dimension, a stacked autoencoder was employed to obtain a suitable subspace from the original feature space. Stacked Autoencoder (SAE) can be divided into two parts: The encoder that encodes the input data into corresponding representation In the entire biomolecular network, each node can be represented by the node intrinsic attributes and behavior. The attributes of the node itself can be the sequence of ncRNA, protein, the semantics of the disease, and the molecular fingerprint of the drug. The node behavior can be considered as a representation of the relationship between nodes. More specifically, in this work, we chose a method of network embedding called LINE  to globai, j), the probability of “context” For large-scale networks, some existing network representation learning algorithms require complex computational complexity. Recently, some methods of large-scale networks either use indirect methods to reduce computational complexity or lack an explicit objective function . LINE defines two similarity relationships, including the first-order proximity and the second-order proximity. The first-order similarity is defined as the node connection relationship  in the network, and the second-order similarity is defined as the common neighbor node  of the nodes that are not directly connected as a supplement to the first-order similarity. In this work, we used the network representation model LINE to learn how to represent the relationships between each node and other nodes in the entire network. In this way, an undirected edge can be considered as two directed edges with opposite directions and equal weights. The second-order proximity assumes that vertices sharing many connections to other vertices are similar to each other. For each directed edge , sensitivity (Sen.), specificity (Spec.), precision (Prec.), and Matthews Correlation Coefficient (MCC) were utilized to evaluate the proposed model more comprehensively and fairly. As shown in As mentioned above, each node in the biomolecular network within the cell can be represented by two kinds of information including attribute information and behavior information. In order to evaluate the impact of each type of information on the final classification effect, we respectively utilized the information of attribute, the information of behavior and the combination of the above two to represent the node under the extensive evaluation criteria in five-fold cross validation. As shown in In order to evaluate the performance of the classifier, we compared random forest with Adaboost, logistic regression, naïve Bayes, and XGBoost under five cross-validation in various evaluation criteria. Under the control variable method, the various settings of the experiment are the same except the classifier, which makes the comparison of experimental results fairer and more credible. The results are shown in In order to compare with traditional methods that focus on single or isolated objects, the lncRNA-disease association prediction was chosen to perform this comparison experiment because of the serious lack of node attribute information. After processing the data, 1263 independent lncRNA-disease association pairs were obtained including 345 different lncRNAs and 295 different diseases. The sequence of each lncRNA was determined when the experimental materials were collected. However, among all diseases associated with lncRNA, only 76 of 295 diseases were able to obtain attribute information by constructing DAG to produce similarity with other diseases. The pairs, which include both two kinds of information only took possession of 259 in 1263 associations.We tried to analyze the flow of information in the molecular association network (MAN) based on a specific miRNA, lncRNA, and protein, which makes the model more interpretable. Two pairs of lncRNA–miRNA interactions were selected to perform this experiment. Firstly, each lncRNA and miRNA-associated protein was queried and aggregated. Then the obtained proteins were constructed into a PPI network. LncRNA and miRNA were directly connected and therefore were each other’s first-order neighbors. The process of a message transmission through the PPI network as an intermediary makes lncRNA and miRNA each other’s high-order neighbors, although the intersection of the second-order neighbors was not large, but the third-order neighbors and their associations were very rich. The specific lncRNA–miRNA interactions and associated proteins are shown in the following Accumulating evidence demonstrated the superiority of link prediction based on massive data through machine learning models, which not only served as an addition to manual experiments, but also provided researchers with an overall and macro insight into the interactions between intracellular molecules. In this article, we proposed a novel framework based on five different kinds of nodes and nine different kinds of relationships to detect any potential associations between arbitrary research objects in the whole network. Each node could be represented as a vector by two kinds of information including node attribute and node behavior. For attribute information, ncRNA and protein could be encoded into 64-dimensional vectors by the method of k-mer, in which each feature represents the normalized frequency of the corresponding 3-mer appearing in the RNA or protein sequence. The characteristics of the disease and the drug could be represented by their own semantic and molecular structure and transformed into 64-dimensional vectors through the function of feature selection and transformation in SAE. For behavior information, the relationships of each node with others could be abstracted by the network embedding method LINE. Combined with the above two kinds of feature, each node could be represented by a 128-dimensional vector and random forest classifier was chosen to carry out prediction tasks. The experimental results showed that our method could achieve outstanding performance. The construction of the molecular association network (MAN) in human cells, offers a new systematic view on understanding complex life activities and diseases.


The paper presents a method for recognizing sequences of static letters of the Polish finger alphabet using the point cloud descriptors: viewpoint feature histogram, eigenvalues-based descriptors, ensemble of shape functions, and global radius-based surface descriptor. Each sequence is understood as quick highly coarticulated motions, and the classification is performed by networks of hidden Markov models trained by transitions between postures corresponding to particular letters. Three kinds of the left-to-right Markov models of the transitions, two networks of the transition models—independent and dependent on a dictionary—as well as various combinations of point cloud descriptors are examined on a publicly available dataset of 4200 executions (registered as depth map sequences) prepared by the authors. The hand shape representation proposed in our method can also be applied for recognition of hand postures in single frames. We confirmed this using a known, challenging American finger alphabet dataset with about 60,000 depth images. Recognition of static hand posture sequences is a natural and relevant expansion of static hand posture recognition. Changing one hand shape to another, e.g., by performing two finger alphabet letters represented by different static hand postures, introduces motion of the hand that is not the part of a gesture itself. Recognition of static hand posture sequences is often compared to recognition of speech, which consists of phoneme sequences. However, in the case of hand gestures, the recognition problem is more difficult because there are no silence models, which are present in audio signals.Recognition of static hand postures in single images, point clouds or skeletons is a common problem. Researchers have addressed this issue using different algorithms ,4,5,6,7.In this work, we present an approach to recognition of Polish finger alphabet letter sequences using 3D data in the form of point clouds. Three-dimensional data have several advantages over data formats used in the mentioned works. One of the advantages is the possibility of hand segmentation based on depth that can be more accurate than methods relying solely on color information. Another advantage is the representation of objects using features based on the surface geometry in addition to the standard 2D shape features. Moreover, 3D cameras using time-of-flight technology work correctly under poor lighting conditions or even in absolute dark. Additionally, users performing gestures are not required to wear any gloves or to keep their hands very close to the camera, as is the case with Leap Motion cameras. In addition to the listed advantages, the main motivation for using 3D data is the good results obtained for the recognition of static hand postures in single images with representative datasets ,17,18.For gesture classification, we used hidden Markov models and the strategy exploiting motion related to transitions between letters. Our feature set was calculated using the point cloud descriptors: viewpoint feature histogram (VFH) , eigenvaProposition of combining VFH, ESF, GRSD, and eigenvalues-based point cloud descriptors to build hand shape representations;Experimental selection of the best descriptor combination and the best structure of hidden Markov models representing the hand shape sequences forming transitions between the pairs of letters;Experimental verification of two recognition methods: Dependent and independent from the dictionary of continuous fingerspelled expressions (acronyms);Experimental verification of the suitability of the proposed hand shape representation to recognition of hand postures in single frames by using a known, challenging American finger alphabet dataset with about 60,000 depth images;Providing the dataset and the details of the proposed method  of continuous fingerspelled expressions including a set of transitions between the pairs of letters).The novelty of the paper is the study of recognition of finger alphabet letter sequences based on models of transitions between the letters built using point clouds and point cloud descriptors. The main contributions are:The remaining part of the paper is organized as follows. This section presents the outline and the details of the proposed method.In this paper, we understand fingerspelling as quick highly coarticulated motions, not as the careful articulations of isolated signs. For recognition, we used the strategy exploiting motion related to transitions between the letters. The transition is called the sequence of hand shapes that appear between two consecutive letters see .We modeled such sequences by hidden Markov models; thus, each pair of consecutive letters considered in this study is represented by such a model, prepared using the training data. Multi-letter expressions  were modeled as networks of the transition models.Hand segmentation (based on depth map);Building the point cloud of the hand, downsampling of the cloud, determining its bounding box, and decomposing the bounding box into smaller cells;Extraction of features based on point cloud descriptors;Recognition using hidden Markov models (after performing steps 1–3 for each frame of the video related to an expression being recognized).The proposed recognition algorithm consists of the following main steps:Steps 1–3 were implemented using the OpenCV 2.4.9  and the i-th The hand segmentation method was proposed in our previous work . It begierode and dilate from OpenCV library can be used. Then, small gaps within the arm region are filled if they are not larger than the rectangular structuring element of size To remove defects resulting from measurement errors of a camera, morphological operations should be performed on GaussianBlur can be used. With such calculated M containing every local maximum not smaller than 85% of the m to m. As a central hand point M, for which the difference The next step of the hand segmentation is the selection of the central hand point. To this end, we applied the Gaussian filter on After the calculation of the hand center, the palm region of the hand is roughly estimated by the largest circle that can be fitted on it. Let us denote the circle with the center y coordinate is less than The last segmentation step is the rejection of the pixels corresponding to the forearm. For this purpose, each non-zero pixel of This method was designed for recognition of static postures in single point clouds (or depth images). For some hand postures, the circle can be fitted in a wrist region instead of palm, which leads to incorrect segmentation. Therefore, the algorithm is slightly modified to increase its effectiveness in posture sequence recognition. The modification includes checking whether the distance between the circle center H of hand pixels belonging to binary image H contains a pixel of the same coordinates. Therefore, the resulting point cloud consists only of points belonging to the hand, without forearm and isolated objects. The coordinates of cloud points: After the hand segmentation, depth maps have to be converted into the point cloud format. To this aim, we defined the set software   The resulting point cloud is redundantly dense. There is no need for such a large number of points to calculate representative features. Therefore, the cloud has to be downsampled in order to reduce the number of points and to speed up the process of feature calculation. This operation is performed by creating a 3D voxel grid over the input point cloud data. Each point situated within each voxel (3D cuboid) is approximated by its centroid. For this purpose, the PCL class ous work  turned oIn our method, the bounding box, defined as the smallest possible axis aligned cuboid that entirely embraces the point cloud of the segmented hand, is determined before feature calculation. To increase the distinctiveness of calculated hand features, we divided the bounding boxes into several cuboidal cells of equal sizes. Our feature vectors consist of features calculated for each cell. The experiments performed in our previous works ,17 showeTo calculate hand features, we used the following descriptors: viewpoint feature histogram, ensemble of shape functions, global radius-based surface descriptor, and eigenvalues-based descriptors.x axis directed to the left, the vertical y axis facing up, and the z axis coinciding with the optical axis of the camera and turned towards the observed objects. VFH consists of a surface shape component and a viewpoint direction component which is not used in our work, since it does not provide information useful in posture classification. The surface shape component has a form of four histograms describing distributions of the four parameters d, d means the distance between a point and the cloud centroid. The remaining parameters are angles computed based on an estimation of the vector normal to the surface at a given point and the average of such vectors for all points of the cloud hooked at the centroid [The viewpoint feature histogram is a global descriptor of a point cloud considered as a set of 3D points in a clockwise coordinate system with the horizontal centroid .The ensemble of shape functions is a combination of three functions describing the following properties of a point cloud: Distances, areas, and angles formed by connecting three randomly selected points. These values are placed in three histograms: IN, OUT, and MIXED, depending on whether the line connecting the points lies entirely inside the surface, entirely outside it, or both .The global radius-based surface descriptor calculates the radial relationships between the neighboring points. For each pair of point and its neighbor, the descriptor calculates the distance between them and the difference between surface normals computed at these points. Based on this information, a sphere is defined, which is then used for the surface categorization. This process assigns one of several categories to each point and creates histograms based on the transitions between the categories ,28.We used modified versions of ESF and GRSD descriptors. The modifications were proposed in our previous work . The maiL, planarity P, scattering S, omnivariance O, anisotropy A, change of curvature C, and eigenentropy E.Eigenvalues-based descriptors are computed as follows. The 3D covariance matrix is constructed for a given 3D point cloud. Since the matrix is symmetric and positive–semidefinite, its three eigenvalues  of 3D points of the considered point cloud. For justification of Equation , one ESF2 histogram, denoted in original work as http://vision.kia.prz.edu.pl. The implementation of VFH descriptor is available in the PCL library.We proposed to represent the calculated histograms of each histogram-based descriptor (VFH and ESF2) by their means and standard deviations. The features of GRSD-C and eigenvalues-based descriptors are not histograms but single values, and therefore, there is no need to calculate their mean and standard deviation. The results of our previous work on recognition of static hand gestures ,18 justiThe classification of posture sequences is carried out using hidden Markov models (HMMs). HMMs are useful for modeling the temporal structure and statistical properties of signals. They also find wide applications in gesture recognition . A hiddIn the proposed recognition method, we used HMMs that represent transitions between particular alphabet letters (two-element combination of letters without repetition). Such an approach allows to exploit not only shape information of the hand showing particular letters, but also the motion related to transitions between letters. For this purpose, we considered three left-to-right models, also known as Bakis models see :B1—in whThe number of states, also called emitting states, because they generate observations, was set experimentally see . For eveIn this Section, we describe the prepared dataset and list the recognized acronyms. Then, we describe the performed experiments and present their results.http://vision.kia.prz.edu.pl.We verified our method on a dataset recorded by three people . The gestures were recorded using a Kinect 2.0 camera with Kinect for Windows SDK 2.0 . It is aIn the first stage of experiments, the posture sequences were classified without knowledge of the considered words (the acronym dictionary was not used). For this purpose, we used a structure of connected transition models in which the first letter from each transition is equal to the second letter from the previous transition see . For exaAt this stage, each testing sequence was classified using models trained by all the sequences from the training set . Because of the used HMM structure, in which words are created from the letter transitions, each letter, with the exception of the first and last one, was recognized twice. Therefore, each letter with even index, with the exception of the last letter, had to be deleted from the resulting sequences. For example, the sequence of the correctly recognized acronym NATO was initially identified as NAATTO. Deletion of the second and fourth letter yields the original sequence: NATO.The recognition rate of the algorithm independent from the acronym dictionary was calculated using a method described by Kim et al. —the rateWe chose this form of letter recognition rate because, in the case of a standard word recognition rate, the results seem to be significantly underestimated if only the single letters in the whole sequence are incorrectly recognized, inserted or omitted. In such cases, the standard word recognition rate yields the 100% error rate. The rate of correctly recognized letters results in a smaller error, depending on the length of the word. It is worth noting that when a recognized word is quite different (in terms of Levenshtein distance) than the original word, the rate of correctly recognized letters yields the error greater than 100%. Therefore, in such cases, the results can be less favorable than those of the standard word recognition rate.We observed that the optimal number of states depended on the model type. Therefore, we performed recognition tests separately for models E (eigenentropy), and observed improvement of the results up to 5.5%, depending on the person from the testing set. Then, we tried adding the other best eigenvalues-based descriptor and observed that O, despite being the second best, does not work well when combined with other descriptors. Finally, we chose the most effective subset of FS1: The first (E), the third (C), the fourth (L), and the fifth (S) best eigenvalues-based descriptor. The results of the aforementioned experiments are presented in d), ESF2. Thus, the complete feature vector representing a video frame contains We decided to choose the optimal set of eigenvalues-based descriptors since we did not use them in our previous works with posture recognition in single images. To this aim, we performed tests with the feature set consisting of all the eigenvalues-based descriptors (further marked by FS1) and the feature set consisting of all the remaining descriptors mentioned in hand see c.In The most misclassifications were related to visually similar letters, such as S mistaken for O and N mistaken for P. These mistakes are common in the case of posture recognition in single images. Other frequent mistakes were related to letters N and A as well as inserting additional, single letters at various positions of a sequence despite recognizing other letters correctly .In the second stage of experiments, the posture sequences were classified by the method using a dictionary of acronyms from the testing set. Each testing sequence was classified using models trained by all the sequences from the training set. For this purpose, we used a structure of connected models containing only the connections corresponding to the classified acronyms see . The claRecognition rates of this method are presented in In the third stage of experiments, we performed leave-one-person-out tests see  for the The most frequent misclassification was incorrect recognition of acronym CEA in the case of person I and II. Most often, it was mistaken for PAP, PLN (person I), and RP (person II). The reason for this error could be a characteristic motion of thumb and index finger towards each other that can be observed in each of these acronyms. This motion is more visible in gestures performed by person I and II than by person III. Moreover, acronym NCN shown by person II was incorrectly recognized multiple times as NBP and RP. This can be partially explained by the difficulty in distinguishing between the similar letters N and P previously observed in the method independent from the acronym dictionary.The difference between mean recognition rates of tests presented in T containing transitions recorded by person I, II, and III using the method dependent on the acronym dictionary  and speed of fingerspelling. Hand segmentation and feature extraction of a single point cloud took approximately 55 ms on a PC with Intel Core i7-4710HQ, 2.5 GHz CPU, and 16 GB RAM, 800 MHz. Classification time of a single sequence was 10–13 ms. It depended on the number of states in HMM models .E,C,L,S) obtained in the experiments from The previous experiments were focussed on the fingerspelling considered as quick highly coarticulated motions. However, our hand shape representation method can also be applied for recognition of hand postures in single frames, but in this case, the classifier has to be replaced. In this subsection, we present experimental results of our method with SVM (support vector machine)  as a claFor these experiments, we used a publicly available American finger alphabet dataset . It is aThe results, presented in In the paper, we presented a method for recognition of static hand posture sequences in a form of fingerspelled letters of the Polish finger alphabet. The method works with 3D data in a form of point clouds. As classification features, we used point cloud descriptors: VFH, eigenvalues-based descriptors, and modified versions of ESF and GRSD. The hand shape representation based on such an approach can be applied both for the recognition of hand postures in single frames, which we confirmed on a challenging American finger alphabet dataset, and for the recognition of fingerspelling considered as quick highly coarticulated motions. In the second case, our method is based on a hidden Markov models classifier with the models trained by transitions between postures corresponding to two consecutive letters. We considered three transition models (We used our own dataset, consisting of training data in the form of transitions between letters and testing data in the form of acronyms. Using our own, publicly accessible dataset, we achieved high recognition rates for the method dependent on the acronym dictionary. The results obtained for the method independent from the acronym dictionary are promising; however, the problem of letter sequence classification without a dictionary still remains challenging and can be a subject for future work. Another future study topic may be expanding the recognition method by adding the possibility to recognize not only static but also dynamic letters of the finger alphabet.