However, the delivery of timely haptic feedback remains a challenge due to the stringent computation and communication requirements associated with haptic data transfer. Haptic delay disrupts the realism of the user experience and interferes with the quality of interaction. Research efforts have been devoted to studying the neural correlates of delayed sensory stimulation to better understand and thus mitigate the impact of delay. However, little is known about the functional neural networks that process haptic delay. This paper investigates the underlying neural networks associated with processing haptic delay in passive and active haptic interactions. Nineteen participants completed a visuo-haptic task using a computer screen and a haptic device while electroencephalography (EEG) data were being recorded. A combined approach based on phase locking value (PLV) functional connectivity and graph theory was used. To assay the effects of haptic delay on functional connectivity, we evaluate a global connectivity property through the small-worldness index and a local connectivity property through the nodal strength index. Results suggest that the brain exhibits significantly different network characteristics when a haptic delay is introduced. Haptic delay caused an increased manifestation of the small-worldness index in the delta and theta bands as well as an increased nodal strength index in the middle central region. Inter-regional connectivity analysis showed that the middle central region was significantly connected to the parietal and occipital regions as a result of haptic delay. These results are expected to indicate the detection of conflicting visuo-haptic information at the middle central region and their respective resolution and integration at the parietal and occipital regions.Haptic technologies enable users to physically interact with remote or virtual environments by applying force, vibration, or motion  Haptic technologies are becoming a vital component in human-machine communication to empower virtual and extended reality applications with multimodal and bilateral interactions  based neural marker of haptic delay, namely a significant modulation of the early negativity component of the ERP detected at FCz electrode  and graph theory.Assessing the impact of haptic delay on global and local connectivity patterns through examining the small-worldness index and the strength index, respectively, during passive and active visuo-haptic interactions.Identifying the frequency bands in which significant modulation of the connectivity pattern is observed due to the experience of haptic delay.Locating the cortical regions(s) that act as the hub of connectivity and capturing the functional connectivity between the hub and the other brain regions during the haptic delay experience.Toward this end, a visuo-haptic task is designed and participants are recruited to perform the task under passive and active haptic interactions. Haptic delay is introduced to evaluate its impact on the functional neural networks in action.Nineteen healthy subjects  were enrolled in the study. All participants were right-handed with normal or corrected-to-normal vision. None of the participants reported a history of neurological or psychiatric disorders. Participants below the age of 18 or left-handed with reported traumatic brain injuries, neural abnormalities, or muscle atrophy were excluded from the study. The study was conducted after obtaining approval of the experimental protocol from the New York University Abu Dhabi Institutional Review Board (IRB: #HRPP-2019-120). The study was carried out in full compliance with the ethical standards outlined in the Declaration of Helsinki, following its guidelines and regulations. Before enrolling in the study, each participant signed a written consent in accordance with the IRB ethics. All participants received monetary compensation upon completion of the task.Participants were introduced to the haptic-visual task in which they used a computer screen and a haptic device . A tennis ball and a racket were shown on the screen; the goal of the task was to bounce the ball using the racket, which is controlled by the stylus of the haptic device. Participants were asked to stay seated on a chair in front of the screen and were instructed to hold the stylus of the haptic device in their right hand. Participants had to perform two types of tasks, namely passive and active, under two haptic delay conditions (0 ms delay or synchronous and 220 ms delay). During the passive task, participants held the stylus passively and pressed the button on the stylus end to initiate a free fall of the ball toward the racket. During the active task, however, participants had to move the stylus actively and hit the stationary ball. In both scenarios, and upon the ball's visual collision with the racket, a discrete force feedback is delivered through the haptic device. While the haptic feedback was delivered instantly along with the visual collision in the no delay condition, it was delayed by 220 ms from the visual collision in the delay condition. The task was developed using the Unity game engine version 2018.4.5f1  and the Openhaptics Unity toolkit .Participants were trained to use the haptic device before the start of the experiment to maintain minimal body movement and thus avoid excessive motor EEG artifacts. In the active task, participants were asked to only move their wrists up or down while keeping both the elbow and the forearm rested on the table. EEG data were acquired from 64 active electrodes using an actiCHamp amplifier  and the Brain Vision Recorder software . The locations of the electrodes were selected based on the international 10–20 system where the online reference electrode was placed at (FCz) and the ground electrode was placed at the frontal pole (Fpz). The sampling rate was 1,000 Hz. The impedance at each electrode was maintained below 10 KΩ.EEG data were pre-processed using MATLAB release 2019b  and the EEGLAB toolbox (v14.1.2)  implemented as part of the CSD toolbox in Matlab (version 1.1)   - ϕj is the instantaneous phase difference between channel i and channel j in trial n at time t. To reduce the computational cost, trials were divided into windows of 50 ms duration with 50% overlap, where the phase values were averaged for each window prior to calculating PLVs as described in Niso et al. , theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–50 Hz). Filtered data are subsequently transformed to the time-frequency domain using Hilbert transform to obtain the phase information. The phase value is extracted for all the time-bins of each trial. Several studies emphasized the role of phase synchronization mechanisms in binding segregated brain regions  matrices of baseline-normalized PLVs. PLV matrices were analyzed using indices from graph theory  , also called node strength  and the weighted average characteristic path length (L) individually normalized with respect to the frequency bands and participants. A SW index that is larger than 1 indicates that the network possesses small-world properties  for a particular participant (p) and frequency band (f):Cj is the clustering coefficient for channel j, E is the number of channels, Li is the characteristic path length for combination i of pairs of channels, and Cp, f(t) and Lp, f(t) indices were obtained by dividing indices of the epoch to the mean of the epoch as described in Vecchio et al. , Lp, f(t), and SWp, f(t) are defined below:Cnorm is the normalized clustering coefficient, Lnorm is the normalized characteristic path length, SWnorm is the normalized small-worldenss index, t0 is the first time bin in the epoch, tn is the last time bin in the epoch, and TN is the total number of time bins in an epoch. Weighted indices of an epoch are obtained by averaging the indices over the epoch length to achieve a single index for every participant at each frequency band and can be realized by the equations below  is defined as the sum of links' weights connected to the node. The S index was subsequently calculated for the frequency bands that showed a statistically significant difference in the SWavg−norm index between the synchronous and delayed conditions. The index S is used to identify the highly connected nodes in a specific frequency band. We used the Brain Connectivity Toolbox for the graph theoretical analysis on this work, along with custom written MATLAB routines  is identified, a hub-seeded connectivity analysis can be performed to capture the functional connectivity between the hub and the other brain regions. By hub seeded, we mean that we focus on evaluating the connectivity between a single electrode (the hub) and the rest of the electrodes  over the five frequency bands. The normality of the SWavg−norm index distributions was tested using the Shapiro-Wilk test  method was used to correct for multiple comparisons across the five frequency bands by adjusting the raw p-values; we report the adjusted p-values in the manuscript.Distributions of Royston,  implemenRoyston, . The tesp < 0.05) were further analyzed using the S index. The S index which was calculated over the time-course of the epoch, was compared across the synchronous and delayed conditions. The statistical comparison of the S index was computed for the hub(s) of connectivity at the peak values of the index. This is motivated by the temporal difference of the peak values caused by haptic delay. Lastly, hub-seeded connectivity analysis is conducted. The time-course of the difference topography maps for the hub-seeded PLVs are obtained per condition. Channels that show significantly different connectivity between the synchronous and delay conditions are highlighted at every time bin. To limit type 1 error due to multiple comparisons of the 64 channels and 10 time bins, p-values were corrected using the FDR method. For all analyzes in the manuscript, the statistics are computed at the group level and the reported p-values are the adjusted values after considering the multiple comparison factor.Frequency bands that showed significant differences  only in the delta and theta bands. SWavg−norm index when the haptic delay is introduced. On the contrary, the SWavg−norm index showed no significant change upon the introduction of the haptic delay in the alpha, beta, or gamma bands. To better understand whether the change in the SWavg−norm index is motivated by an increase in the Cavg−norm index or a decrease in the Lavg−norm index, both indices were examined. The details of the statistical analysis results on the SWavg−norm, Cavg−norm and Lavg−norm indices are found in SWnorm index is further examined over the delta-theta bands and plotted in p-value < 0.05, tPND=[175 ms] and tPD = [350 ms], paired t-test). However, no significant difference was found over the peaks for the active task . As per SWavg−norm was higher on average for AD compared to the AND condition, but not over the peak values.The examination of the SWavg−norm index, namely, delta (1–4 Hz) and theta (4–8 Hz). The S index was computed for each channel (node) over the time-course of the epoch; S index topography for the four conditions . In the passive task, a high localized S index is observed in the middle central region centered around Cz. In the presence of delay, the high localized S index is temporally shifted and increased in magnitude. In the active task on the other hand, a high S index is observed over the frontal and ipsilateral parietal regions under the synchronous condition. In the presence of delay, however, a high localized S index is again observed over the middle central region. In all four conditions, the described activation fades out 700 ms after the onset. Since Cz is the center of the activation in the middle central region, the time-course of the S index at Cz is extracted and shown in S index peaks later and higher in the presence of delay (PD and AD conditions). The difference is statistically significant and observed over peak values .Consequently, further analysis was focused only on the bands that showed significant differences in the SW and S indices, respectively. Connectivity in the delta and theta bands was found to be impacted by haptic delay, and the mid-central region, centered around Cz, was found to be the hub of connectivity. Thus, the Cz-seeded connectivity is plotted in Both, the frequency bands and the hub of connectivity were identified through the SW index could be attributed to either an increase in the global clustering  or a decrease in the characteristic path length . The results in SW,C, and L) during the passive task compared to the active task. As reported in self-reporting research . Our results suggest that the brain exhibits significantly different network characteristics when a haptic delay is introduced. In particular, a significantly increased manifestation of the small-world topology in the theta and delta bands was observed when the haptic delay was introduced . An incr Vogels, , the senA delay in an expected haptic stimulus is hypothesized to elicit higher levels of attention when compared to synchronous stimulation. This is, in turn, functionally related to the ability of an individual to detect and respond to rapid and subtle changes in the environment, such as the presence, absence, or delay of an expected stimulus; this ability is known as the psychomotor speed Bigler, . In lighS index at the middle central region in the PND condition is delayed and amplified significantly upon the introduction of the haptic delay, as shown in S index is similar to reported findings indicating a relationship between tasks that involve conflict processing and a subsequent increase in the middle central theta-based connectivity  show reduced fronto-parietal EEG phase synchrony in the theta band . The patients/participants provided their written informed consent to participate in this study.ME and HA conceived the study. HA and WP designed the experimental protocol. HA conducted the experiment and analyzed the results. WP and ME reviewed the results. All authors contributed intellectually in writing and revising the manuscript.This research was funded by the New York University Abu Dhabi PhD Fellowship Program. This work is also supported in part by the NYUAD Center for Artificial Intelligence and Robotics, funded by Tamkeen under the Research Institute Award CG010.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In this study, we propose a specimen tube prototype and smart specimen transport box using radio frequency identification (RFID) and narrow band–Internet of Things (NB-IoT) technology to use in the Department of Laboratory Medicine, King Chulalongkorn Memorial Hospital. Our proposed method replaces the existing system, based on barcode technology, with shortage usage and low reliability. In addition, tube-tagged barcode has not eliminated the lost or incorrect delivery issues in many laboratories. In this solution, the passive RFID tag is attached to the surface of the specimen tube and stores information such as patient records, required tests, and receiver laboratory location. This information can be written and read multiple times using an RFID device. While delivering the specimen tubes via our proposed smart specimen transport box from one clinical laboratory to another, the NB-IoT attached to the box monitors the temperature and humidity values inside the box and tracks the box’s GPS location to check whether the box arrives at the destination. The environmental condition inside the specimen transport box is sent to the cloud and can be monitored by doctors. The experimental results have proven the innovation of our solution and opened a new dimension for integrating RFID and IoT technologies into the specimen logistic system in the hospital. Nowadays, radio frequency identification (RFID) and Internet of Things (IoT) technology play a fundamental role in the so-called automation factory or Industry 4.0 era, aiming to increase the level of automation of industrial processes. In the medical packaging and logistic domain, RFID has gradually become an attractive technology due to its distinctive features such as the low cost of RFID tags, the reuse of RFID tags, and the easiness of RFID tag’s deployment and within the items to be tracked ,7,8,9,10The motivation behind our work is to solve the existing specimen transport system and management problems at King Chulalongkorn Memorial Hospital. This hospital is one of the largest public hospitals in Bangkok, Thailand, with an in-patient capacity of over 1400 beds. The number of patients admitted in 2017 was 1.6 million outpatients and more than 5000 patients daily. Blood or other samples such as urine, feces, sputum, pus, skin, hair, and nails are collected from the patients as required by the doctors. Then, these specimens must be transported to the Central Laboratory, Department of Laboratory Medicine, for examination. Unfortunately, the document-based specimen transport system cannot handle a massive request for specimen delivery while minimizing human errors such as mislabeling specimens, losing tubes, or incorrect delivery. Furthermore, the Central Laboratory also receives the specimen tubes from other local hospitals since they do not have sufficient equipment for examination. This specimen tube is encased in the transport box with an appropriate temperature and humidity requirement during transportation. In addition, the Central Laboratory must be able to remotely monitor the temperature and humidity of the box and trace the box location to estimate the delivery time. Therefore, it is necessary to develop an alternative specimen transport system utilizing digital technologies to replace the document-based one for the King Chulalongkorn Memorial Hospital.The barcode solution for specimen tubes in the literature cannot be a solution to the above problems. The barcode technology requires reading data in the line-of-sight only one label at a time; hence, the specimen tube processing rate is much slower than RFID technology. In fact, the biggest drawback of the barcode approach is that the barcode falls short of usage because the printed code is easily damaged or washed out. Moreover, another requirement is that the tubes in the transfer box must be placed under suitable temperature and humidity conditions while being delivered from one laboratory to another.The multiple reading/writing RFID system is located at a laboratory for traceability and accounting for the specimen tubes during the delivery to hospital laboratories;The portable RFID reader attached to the transfer box to check the correct receiver laboratory for specimen tubes;The NB-IoT device for tracking the specimen box position and monitoring temperature, and humidity inside the box.Our work solves the above problems of specimen transport system at the King Chulalongkorn Memorial Hospital by introducing a smart specimen transport system using RFID and NB-IoT technologies. The passive RFID tags can be multiple-read and write information even under non-line-of-sight conditions. The tags are made with plastic so that they are waterproof and heatproof. Furthermore, an RFID tag can easily be attached to specimen tubes requiring sterilization. Additionally, the NB-IoT device for the specimen transport box monitors temperature and humidity values inside the box during transportation. Moreover, the GPS location is also reported to the cloud platform to estimate the delivery duration. By introducing the smart specimen transport system, our work also contributes to widening the innovative applications of RFID and IoT technologies used in the clinical laboratory environment. In conclusion, the key features of our proposed system are:The rest of the paper is organized as follows. RFID technology has been widely applied in worldwide management and logistics supply chains. There are two scenarios of RFID usage, namely under indoor and outdoor conditions ,16,17,18The authors in  implemenThe development of IoT technologies has create new spaces for the integration of RFID tags for outdoor usage ,26,27,28ive tags , which iive tags  which coIn our proposed system, the RFID tag does not include explicit data, thereby creating privacy for patient information. Only the sender laboratory can obtain the personal information of the patient by using the code of the patient. Furthermore, only the environment and GPS location of the box are uploaded to the cloud via the NB-IoT module. Those are effective solutions for protecting patient information during traveling.An RFID reader is one of the key components of our proposed system. The reader transmits radio electromagnetic waves to the medium. When the transponder enters the read range, the RFID tag’s internal antenna draws energy from the reader and sends it to IC, which generates a signal back to the system. The reader detects a backscatter and interpreted it to the readable information. Readers also use RF waves to write new information on the tag. Usually, the reader connects with the computer via a cable to display the detected tag information using middle-ware. Some have a built-in onboard antenna to detect the tag in the short-range, while some external support antennas can be used for greater ranges. We usee the Sparkfun simultaneous RFID reader—M6E nano board .The ultra high-frequency (UHF) RFID Antenna boasts a frequency range of 860–960 MHz with a gain of six dBi. This is the external antenna we use for our simultaneous RFID reader due to its high-quality features .The Arduino device has been widely used for fast prototyping in IoT applications. We use the Arduino Mega 2560 device for the signal processing of specimen boxes due to its low-cost, portable, high flash memory, with more serial pins for serial communication devices, and a variety of reference resources .The SHT10 sensor module was chosen to monitor both the temperature and humidity inside the transport box. It is a tiny, low power consumption device, and it is Arduino-compatible and easy to deploy. It precisely calculates the temperature and humidity values and interfaces with the Arduino device via I2C communication .GPS-EM506RE is a coin-sized module with a high-accuracy and low-power consumption device. It works stably with the Arduino device at 4800 baud rates under indoor and outdoor conditions .The AIS NB-IoT shield is chosen for our project because it is currently available on the market, license band, and is still releasing updated features timely . The shiIn order to illustrate how our smart specimen transport box proposed in this contribution works, an experiment at the laboratory and a pilot test were conducted at the Central Laboratory of the Department of Laboratory Medicine, Chulalongkorn hospital Bangkok, Thailand. The laboratory experiment aimed to determine the suitable number of specimen tubes in each specimen box so that the RFID system could successfully read the information. The pilot test evaluates the NB-IoT’s performance in indoor and outdoor environments. The results are represented in the following subsections.Currently, there are two options for the number of specimen tubes per transport box: 25 tubes and 50 tubes. The ice bag is necessary to transport the specimen tubes since it keeps them under cool conditions. However, the ice bag interferes with the RFID signal, as seen in the first experiment. Therefore, in the second experiment, the ice bag positions inside the box are varied to determine the appropriate position.The NB-IoT prototype is integrated inside the specimen transport box to determine the box’s temperature, humidity, and location, as shown in Furthermore, we developed a specimen tube destination indicator (STDI) device using the RFID reader attached to the transfer box with the onboard antenna. Each specimen tube must be delivered to a receiver’s clinical laboratory by recording the receiver laboratory’s GPS location to the RFID tag and following the check-in and check-out procedures, as shown in In the actual situation, a transfer box contains many specimen tubes belonging to different receiver laboratories. Thus, any specimen tubes may be misplaced in the wrong receiver laboratory. This STDI device indicates the destination of a specimen tube by checking the GPS location of the receiver laboratory and compared to the current GPS location of the transfer box. If the absolute error between these two GPS locations is less than 10 m, we assume that they are the same location. One LED will blink when the specimen tube near the STDI device is placed. The green LED will blink if the specimen tube arrives at the corrected receiver laboratory. If a specimen tube belonging to a different receiver lab is taken out, the red LED will blink as an incorrect delivery indicator.During transportation, the NB-IoT sends the temperature, humidity, and position data every minute to the Magellan Cloud. Therefore, the environmental conditions inside the transfer box and the location can be monitored. Additionally, the Magellan dashboard shows values in real-time during the box’s traveling, as shown in In this paper, we proposed the smart specimen transport box based on RFID and NB-IoT technologies to monitor the quality of the specimen tubes during traveling to accelerate the specimen accounting process and eliminate the lost specimens during delivery caused by employees. According to the experiments in the laboratory and pilot tests at Chulalongkorn hospital, our proposed system was represented as being practical. In addition, the passive RFID tag can be reused, which allows money to be saved. Such a system can be integrated into existing medical laboratory systems and open up new opportunities to eliminate the paper-based process and accelerate the medical information flow.Future work will be simplified by the use of software in our proposed system making it more convenient for doctors to use the applied machine learning models to optimize the route for delivering transfer boxes and specimen tubes to many laboratories utilizing the traffic information. Another future work is that of implementing our smart specimen transport system in real clinical laboratories to evaluate the efficiency of the nurse and physician aspects.


This paper presents the results of an experimental investigation which was carried out with the purpose of assessing the performance-related properties of an emulsion-based cold-recycled mixture to be employed as a sustainable solution for the surface finishing of unpaved rural roads. This mixture contained significant quantities of recycled components , and its composition was fine-tuned by following an innovative mix design procedure. Properties of these mixtures were studied by means of laboratory tests which considered key parameters, such as flowability, indirect tensile stiffness modulus, indirect tensile strength, moisture susceptibility and resistance to permanent deformation. It was found that, by means of the proposed mix design procedure, optimal dosages of the recycled components can be identified, thereby ensuring the achievement of the desired properties in terms of high workability and adequate stiffness and strength. Construction and maintenance operations of road pavements, both of primary and secondary infrastructures, require large volumes of selected granular materials, which entails the excavation and use of considerable quantities of natural resources . The groReclaimed asphalt (RA), which comes from the milling of existing asphalt pavements and is formed by aggregate clusters coated by aged bituminous binders, is widely used as an alternative component in the construction of flexible pavements ,11,12,13One of the most cost-effective and environmental-friendly modes of employment of RA is represented by cold-recycling, in which RA is combined with asphalt emulsion or foamed bitumen to create a stable and durable paving mixture . AlthougMineral sludge (MS), obtained by the industrial washing to which aggregates are subjected in crushing plants, may also be considered as a possible alternative material to be used in pavement construction . This isMost of the studies presented in the literature are focused on the reuse of waste materials and by-products in major infrastructures, although secondary roads, including those constituting the rural road network, may represent a more fruitful and cost-effective application for recycling processes .The majority of the Italian rural road network is constituted by unpaved gravel roads, referred to as low-type surfaces due to the low traffic volumes to which they are normally subjected . Their bDespite the low traffic volumes to which they are subjected, rural roads may be affected by several distresses which compromise their serviceability. In particular, they are especially sensitive to water drainage which is a key factor in controlling long-term durability through the prevention of surface erosion and saturation of the subgrade. Since maintenance operations may be quite frequent for the restoration of surface evenness and for the repair of localized potholes and ruts, in some cases it could be appropriate, although not necessarily cost-effective, to proceed with the application of a surface finishing bituminous-bound protective layer .In this paper, a sustainable and cost-effective solution for the surface finishing of unpaved rural roads is proposed. An emulsion-based cold-recycled mixture (CRM) containing large quantities of RA and MS was conceived of and thereafter fine-tuned by following an innovative mix design procedure. Optimal composition was identified with the purpose of guaranteeing high workability (to reduce compaction efforts) and adequate stiffness and strength (to limit the frequency of maintenance operations). In order to maximize environmental benefits and to reduce the economic impact of the suggested solution, it was considered appropriate to avoid the use of any hydraulic binder (such as Portland cement) .Workability was assessed by performing flowability tests on loose mixtures and by analyzing compaction curves obtained by making use of the gyratory shear compactor. Compacted specimens of the investigated CRMs were then subjected to indirect tensile stiffness modulus tests and to indirect tensile strength tests, and moisture susceptibility was evaluated by referring to the indirect tensile strength ratio. Additional tests were carried out on laboratory-compacted slabs of the optimal CRMs for the assessment of their resistance to permanent deformation.a) as per the corresponding EN standards [Components employed for the formation of the aggregate skeleton of the investigated cold-recycled mixtures (CRMs) were reclaimed asphalt , siliceous sand  and mineral sludge (MS). All components were subjected to the preliminary determination of particle size distribution and apparent density  and hadmax is the maximum diameter of aggregate particles in the mixture  equal to 100%); Dmin is the minimum diameter of aggregate particles in the mixture ; and q is the so-called distribution modulus, which may vary between 0 and 1 and defines the balance of coarse and fine aggregates within the aggregate skeleton .The aim of achieving an acceptable level of workability of the investigated CRMs suggested the adoption of an approach which is similar to that normally referred to in the design of self-compacting cementitious mixtures ,47,48,57From a conceptual viewpoint, it was assumed that mechanical properties (such as stiffness and strength) are mainly attributable to the stone-to-stone contact occurring between the coarse RA particles bound by the bituminous residue of the emulsion (which provides some degree of shear resistance), and flowability properties are mainly controlled by MS and added water. Thus, several trial mixtures were prepared by changing the value of the distribution modulus q and the RA content.The compositions of the aggregate skeletons of CRMs included in the present study are shown in As mentioned in the Introduction, to ease laying and compaction procedures, special attention was paid to the workability features of the investigated mixtures.Since the total fluid phase (%FP)—given by the contributions of bituminous emulsion (%E) and added water (%W)—lubricates particle-to-particle contacts, and therefore enhances the workability of CRMs , it was Based on preliminary results obtained on trial CRMs, the dosage of the bituminous emulsion, expressed with respect to the total weight of the dry components of the lithic skeleton, was chosen to be 4% and kept constant throughout the experimental investigation.All mixtures were manually prepared and mixed by adopting a protocol which entailed the following steps: (i) preliminary mixing of RA and bituminous emulsion to completely cover RA particles, (ii) addition of sludge, sand and water, (iii) continuous mixing of the resulting blend until the achievement of a homogeneous material.The time elapsed between mixing and compaction was carefully controlled and kept constant—30 min—during which, a clear transition of the color of the mixture from brown to black was observed, thereby revealing the initiation of the breaking process of the emulsion.The experimental program included laboratory tests on loose mixtures for the evaluation of the flowability characteristics and volumetric and mechanical characterization tests carried out on laboratory-compacted specimens.Flowability tests were performed according to ASTM D6103 . As presx of the specimen was recorded after each gyration to evaluate the progressive degree of compaction Cx (which represents the complement to 100 times the void content of the sample) by making use of Equation (2):geo,x represents the geometric density of the sample at the generic gyration x and ρm is the maximum density measured on loose blends with the pycnometer method. ρgeo,x was calculated as the ratio between the mass of the sample and the volume of a cylinder of 150 mm diameter and height hx [x as a function of the number of gyrations recorded during the compaction process. For each mixture, a total of eight specimens were compacted. Volumetric properties were then calculated in terms of geometrical void content [Cylindrical specimens (150 mm diameter) were prepared by making use of a gyratory shear compactor  with a feight hx ,64. Dens content .After compaction, in order to mimic long-term conditions reached in the field, test specimens were subjected to a curing procedure in a forced draft oven kept at 40 °C for 72 h.Compacted specimens were then divided into two subsets, with approximately the same average height and average bulk density, named “dry subset” and “wet subset”. The dry subset was subjected to the assessment of stiffness modulus and indirect tensile strength, and the wet subset was conditioned in water for the evaluation of indirect tensile strength ratio.According to EN 12697-26 Annex C , stiffnedry and ITSwet. The wet-subset was preventively soaked in a water bath at 20 °C for 24 h before testing [Indirect tensile strength (ITS) was determined according to EN 12697-23  at a dis testing .ITS and indirect tensile strength ratio (ITSR) were calculated as follows (Equations (4) and (5)):In the case of the CRMs identified as optimal, slabs  were prepared by means of a large-size roller compactor, operating according to EN 12697-33 [i is the measured proportional rut depth on the i-th load application, mij is the local deformation at the jth location after application of the i-th load, m0j is the zero-point condition and h is the average initial slab thickness. Two replicates were carried out for each CRM and average values were considered in the analysis.On compacted slabs, the evaluation of the resistance to permanent deformation  was performed. Thus, wheel tracking tests were performed in accordance with EN 12697-22 . The adoResults obtained from flowability tests showed a particular behavior common to all investigated mixtures, as indicated in For very low water dosages, all CRMs showed a behavior similar to that of unbound granular mixtures, characterized by the absence of any significant cohesion between aggregate particles. By gradually increasing the water content, apparent cohesion of the mixtures began to be mobilized, leading to a progressive reduction in the spread diameter until the transition to a different behavior, indicated as self-molding. In this condition, the mixtures reached a level of cohesion which was sufficient to maintain the cylindrical shape without any spreading. This behavior, graphically described by a diameter equal to the internal diameter of the spread cylinder, occurred as long as the water content did not induce segregation phenomena, which caused the uncontrolled increase in spreading.Based on the observations provided above, the self-molding region was considered as a characteristic feature of the workability and compactability of CRMs, and its range of water contents was considered as the range of target fluid phase contents to be explored in the further phases of the investigation.Results of flowability tests obtained for the four considered CRMs are plotted in It can be observed that the self-molding regions of the investigated CRMs changed as functions of the compositions of their solid skeletons. In particular, it was found to be strongly dependent upon the amount of MS, which, based on its composition, can be considered as a water-absorbing fraction. The lower the MS dosage, the lower the amount of water required to achieve this behavior.For each mixture, both water contents listed in Average densification curves of investigated CRMs are summarized in By analyzing the data plotted in Moreover, it was noticed that differences between mixtures with the same aggregate skeleton but with different fluid phases were quite small in the case of CRM_1, CRM_2 and CRM_3, characterized by limited extension of the self-molding region  and by greater amounts of RA particles. On the contrary, mixture CRM_0 revealed more pronounced variations in the densification curves due to the wider range of the self-molding region  and a larger amount of fine particles.The volumetric properties of the compacted specimens, expressed in terms of geometric air void content, are presented in Despite the high variability highlighted by the data dispersion bars, a characteristic trend could be defined as a function of the fluid phase percentage and of the solid skeleton composition. In particular, consistently with the observations made from the densification curves, the CRMs characterized by the highest values of the percentage of total fluid phase showed the highest void contents, and the reduction of MS content was found to lead to higher compaction levels.Stiffness moduli were measured at 20 °C on compacted specimens after curing. Average values obtained for each CRM are reported in Both CRM_0 mixtures failed during the application of conditioning load pulses, revealing poor mechanical behavior due to the weak stone-to-stone contact created between RA particles as a consequence of the higher dosages of the finer fractions (MS and SS). On the contrary, the increase in the RA fraction, together with the reductions in the MS and SS dosages, let to the creation of tougher internal structures with enhanced stiffness, of the order of 1300 MPa, of the same order of magnitude of more conventional cold-recycled mixtures . As exped) and wet (ITSw) conditions, together with the corresponding indirect tensile strength ratio (ITSR) values, are reported in w values could not be determined.Results of indirect tensile strength tests, performed in dry  provided improved stone-to-stone contact, thereby enhancing strength. The highest values of ITS, in both dry and wet conditions, were recorded for the CRM_3 mixtures, which were characterized by the highest RA dosage (75%) considered in the investigation. Both dry and wet ITS values showed that CRMs with lower void contents exhibited higher resistance to loading as a consequence of their denser structure.ITSR results confirmed the enhanced mechanical properties provided by the combined effect of high RA dosage and low void content, which translated into improved water durability properties. However, it should be underlined that the obtained ITSR values were quite low, revealing drawbacks related to the moisture sensitivity of CRM mixtures, probably associated with their limited degree of compaction. This specific outcome of the investigation will be addressed in more detail in future investigations, before any full-scale implementation.Results gathered from volumetric and mechanical tests performed on the investigated CRMs led to considering the CRM_3 mixtures as the optimal ones, due to their high stiffness and strength.Thus, further tests were performed on compacted slabs to assess resistance to permanent deformation. Slabs were compacted by means of a roller compactor to achieve the same geometric density of the corresponding gyratory-compacted specimens and were thereafter subjected to wheel tracking tests (performed at 20 °C).The tendency of the CRMs to accumulate permanent deformation is graphically represented in Both CRMs showed similar and satisfactory anti-rutting behavior as a consequence of their high stiffness and low voids content. Visual inspection of the slabs at the end of the tests revealed the absence of cracks, raveling or particle loss, thereby confirming that mixtures of the considered type may constitute a valuable solution for the surface finishing of unpaved rural roads.In this paper, it was shown that reclaimed asphalt (RA) and mineral sludge (MS) obtained from the production of aggregates can be successfully employed for the creation of cold-recycled mixtures (CRMs) to be employed as a sustainable solution for the surface finishing of unpaved rural roads. These mixtures are constituted by large quantities of recycled components (RA and MS) combined with small amounts of silica sand, bituminous emulsion and added water. Mix design was carried out according to an innovative procedure, by means of which optimal composition was identified by considering flowability, stiffness and strength.From flowability tests, three different behaviors were observed as a function of the percentage of fluid phase, indicated as “cohesionless”, “self-molding” and “segregation”.The “self-molding” region was considered to represent the target condition to achieve in order to obtain CRMs characterized by satisfactory workability and compactability.High values of the percentage of fluid phase and of the MS dosage resulted in high volumes of voids, indicating that these composition parameters need to be carefully controlled in order to achieve a satisfactory compaction level.It was found that the mechanical properties of CRMs were mainly influenced by the RA content: its increase, together with reductions in the MS and SS dosages, led to the formation of tough internal structures with enhanced stiffness and strength.The CRM identified as optimal during the investigation showed a satisfactory performance in terms of resistance to permanent deformation.As a result of their limited degree of compaction, all CRMs exhibited significant moisture sensitivity.The main findings of the study can be summarized as follows:Notwithstanding the fact that the obtained experimental results are considered to be extremely encouraging, further investigations will be carried out to refine the mix design methodology and to improve the performance properties of CRMs in terms of their moisture sensitivity. Field trials will be consequently planned to optimize the production and laying technology of these innovative mixtures, and to analyze their actual behavior when subjected to traffic loading.


Gout is a crystal deposition disorder caused due to the deposition of monosodium urate crystals in joints and other tissues secondary to hyperuricemia. Podagra is the term for gout of the first metatarsophalangeal joint.In our case report, a 30-year-old male patient came to our OPD with complaints of swelling over the first metatarsophalangeal joint for one year, which was insidious in onset, localized, and had a sudden increase in size over the past three months. The patient also complained of an inability to properly wear his shoe. A plain radiograph was done, which was suggestive of an expansile lesion with the destruction of the first metatarsophalangeal joint and the erosion of the joint surface extending to the head of the first metatarsal and the proximal phalanx of the great toe. Lab investigations revealed a serum uric acid level of 10.2 mg/dl and an acid phosphatase level of 8.92 U/L.Excision of the lesion was done and a frozen section biopsy was sent intra-operatively which confirmed the presence of monosodium urate crystals. A fibular strut graft was taken to fill the defect using a square nail passing through the first metatarsophalangeal joint and a Kirschner wire was added to the interphalangeal joint to maintain the stability of the reduction. The foot was immobilized for six weeks following which the Kirschner wire was removed and range-of-motion exercises started. There was no residual deformity, and the patient responded well to the treatment. The term "gout" is used to describe a diverse group of conditions affecting only humans, usually secondary to hyperuricemia . Uric acClinically, most patients who have an increased uric acid level are asymptomatic and no treatment is needed. The patient may have a history of alcohol consumption, specifically beer, and a purine-rich diet. Patients with co-morbidities like hypertension and hyperlipidemia are more susceptible to developing symptoms. The patient usually seeks medical attention with complaints of a red hot swollen joint, most commonly at the base of the great toe . Joint aTreatment is necessary for only symptomatic patients with daily activities affected due to the disease. Urate-lowering medications like Allopurinol, Probenecid, and the most recent Topiroxostat can be used to lower serum uric acid levels -7.A 30-year-old male patient came to our OPD with swelling over the first metatarsophalangeal joint for one year, which was insidious in onset, localized, and had increased in size over the past three months as shown in Figure The patient had difficulty wearing his footwear due to the swelling. The patient had no history of similar complaints in the past. A plain radiograph of the foot was done, which revealed an expansile, lytic lesion eroding the first metatarsophalangeal joint as shown in Figure Blood investigations showed an increased serum urate level of 10.2 mg/dL and an increased acid phosphatase level of 8.92 U/L. Excision of the lesion was done with the patient under spinal anesthesia using a dorsomedial approach, and a frozen section biopsy was taken and immediately sent for histopathological examination. The histopathological examination revealed the presence of monosodium urate crystals thereby confirming the diagnosis of gout as shown in Figure The defect of the first metatarsophalangeal joint post-excision was measured, and a fibular strut graft of similar length was harvested using the lateral approach for the fibula. The gap was filled using the graft, which was held in place using a square nail passed through the proximal phalanx into the metatarsal. An additional Kirschner wire was passed to stabilize the inter-phalangeal joint as shown in Figure Routine closure was done and a below-knee slab was given postoperatively to immobilize the joint. A postoperative radiograph was taken as shown in Figure Another radiograph was taken at six weeks' time, which showed signs of union as shown in Figure Podagra is the term used for gout of the first metatarsophalangeal joint. Tophus deposition in the joint is a common finding in gout, however, destruction of articular cartilage and surrounding bony erosion is rarely seen. The radiographic picture may suggest a neoplastic growth, especially a giant cell tumor being the most likely differential diagnosis. Thus, histopathological examination is of utmost importance in the diagnosis of these cases.The majority of the cases of podagra are treated conservatively with uricosuric drugs and often respond well to it. Surgical management is rarely indicated in the presence of bony erosions and cartilage damage.In elderly patients with podagra, arthrodesis of the first metatarsophalangeal joint is a well-known treatment option . ArthrosIn our case, the patient was a young male with an expansile lesion eroding the head of the first metatarsal and the base of the first proximal phalanx of the great toe; preservation of the joint was not an option. Hence, the removal of tophi and reconstruction of the defect with a fibular strut graft was done with the aim to provide a painless joint that does not hinder the daily activities of the patient.The Masquelet technique is a well-known method of reconstruction of the first metatarsophalangeal joint using a fibular strut graft in cases of osteomyelitis . A similPodagra is a well-known clinical feature of gout with tophi deposition in the first metatarsophalangeal joint. However, a lytic lesion along with the erosion of the adjacent bone is a rarely-seen complication of the disease. Hence, the removal of tophi and reconstruction of the joint is necessary to provide a pain-free and weight-bearing first metatarsophalangeal joint.


In this paper, we analyze the construction of cross-media collaborative filtering neural network model to design an in-depth model for fast video click-through rate projection based on cross-media collaborative filtering neural network. In this paper, by directly extracting the image features, behavioral features, and audio features of short videos as video feature representation, more video information is considered than other models. The experimental results show that the model incorporating multimodal elements improves AUC performance metrics compared to those without multimodal features. In this paper, we take advantage of recurrent neural networks in processing sequence information and incorporate them into the deep-width model to make up for the lack of capability of the original deep-width model in learning the dependencies between user sequence data and propose a deep-width model based on attention mechanism to model users' historical behaviors and explore the influence of different historical behaviors of users on current behaviors using the attention mechanism. Data augmentation techniques are used to deal with cases where the length of user behavior sequences is too short. This paper uses the input layer and top connection when introducing historical behavior sequences. The models commonly used in recent years are selected for comparison, and the experimental results show that the proposed model improves in AUC, accuracy, and log loss metrics. In recent years, deep learning has achieved great success in computer vision. Deep convolutional neural networks, built to mimic the neural mechanisms of the human visual cortex, can mine the underlying features of images and are widely used in image classification and recognition . Deep leNowadays, recommendation systems are used in e-commerce platforms, blogs, movie sites, personalized music software, social networking sites, etc. Each area and venue has its recommendation characteristics . With thThe vast amount of user-generated content, video uploads, and updates makes the number of resources in the network grow exponentially, which brings the problem of “information overload” and “information explosion.” Collaborative filtering techniques can be classified into Memory-based CF and Model-based CF based on whether they are modeled using machine learning ideas. The matrix decomposition method of model-based collaborative filtering is popular because it is easy to implement and expand in multiple perspectives in neural networks. It is challenging to dig out valuable information for users and platforms from the vast amount of short video data and help temporary video platforms distribute and attract traffic, directly affecting the platform's revenue and users' experience . Click-tO(n3), which is not suitable for large data operations. Later, Ge et al. proposed the Funk SVD method, which no longer decomposes the matrix into three matrices but reduces the computational complexity by decomposing the matrix into two matrices and letting the new matrix obtained by matrix multiplication of these two matrices have a reduced error with the original matrix , which is, of course, easily achieved by a probabilistic function, such as a logistic function as the activation function of the prediction layer. Based on the above parameter settings, the likelihood function is given here: The image feature is essential in video content analysis, often used in target detection, scene recognition, and other fields. It is derived by segmenting the video into frames and extracted by CNN for video frames.SECk NCF prediction model learning: According to the pointwise loss method based on single-category prediction proposed in the NCF article, taking 1 indicates the presence of user-item interaction and 0 the other way around. Therefore, we need to limit the final output prediction value (5)Motivation for using convolutional neural networksk ∗ K dimensional vector, consistent with the approach in NCF. However, MLP is theoretically able to fit arbitrary approximation functions. This requires a large amount of experimental data to drive the results; however, real-life data are primarily sparse and leads to suboptimal outcomes. On the other hand, using MLP often requires a larger vector dimension K and a deeper network hierarchy, but this also leads to problems such as the parameters of the network becoming inaccessible, large, and complex for real machines to process at high speed. These problems can be solved very well using convolutional networks. Conversely, convolutional networks are very good at handling local feature relationships. The number of feature maps or kernels can determine how many correlations exist between regional dimensions, thus generating wealthy inter-dimensional interaction information. On the other hand, existing neural network frameworks can use the parallel computing power of CPUs or GPUs for convolutional networks to achieve high-speed processing, making such models realistic and feasible.The hidden layer can also use MLP (by flattening the tracklayer). Still, it loses the dimensional pairwise and locally tightly connected nature of the track. Note that after Flat, the tracklayer is transformed into a From a theoretical analysis, we know that convolutional networks are used for local feature extraction on the one hand and focus on specific valuable parts of local features on the other hand, which are then passed to the upper layers of the network. This means that each layer of the convolutional network deliberately “filters out” some of the information to leave the most valuable part for prediction. The reason for performing dimensionality reduction is that processing and analyzing high-dimensional features require a lot of computational resources and even generate dimensional disasters, so it is essential to represent the original high-dimensional feature vector with a low-dimensional feature vector. However, as analyzed in the previous section, the entire prediction model requires backpropagation of the target loss to train the user and item vectors, i.e., the values of the feature maps are derived from the loss gradient of the target function . This maN frames from the video and then using the N frames as the input to the 3D convolutional network. This paper uses the C3D network for extraction after pretraining on the Sport-1M dataset, which helps the model identify the behavioral categories in short videos. In the experiments, this paper selected the output of the penultimate fully connected layer as the behavioral video features with 4096 dimensions. The audio in the video also contains rich information, even information that cannot be captured visually, such as the surrounding environment and emotion. Mel Frequency Cepstral Coefficients (MFCC) is a typical representation of audio features obtained by first converting the audio signal to Mel frequency and then performing cepstral analysis . Z-score normalization is a linear transformation of the original data so that the result falls between . Z-score normalization transforms the actual data distribution into a data distribution with mean 0 and variance 1. Analyzed from the perspective of gradient descent, the normalized data can find the optimal solution more easily with the same learning rate. The logistic regression model mainly relies on the manual construction of valuable features, and then after the linear transformation of the features, the values are mapped between  by the sigmoid function as the predicted values of the click-through rate.The overall structure of the click-through rate prediction model is designed, which is obtained by combining GRU improvements with the DIN model. The model consists of a three-layer network structure. The first layer is the Embedding Layer, which is used for data preprocessing; the second layer is the Interest Evolution Layer, which is used for mining the interest behind the user's historical behavior and learning its evolution process; the third layer is the CTR Prediction Layer, which is used for understanding the third layer is the CTR Prediction Layer, which is used to learn higher-order combinations of features and obtain click-through rate prediction values. The interest evolution layer is the key to processing user behavior data and is the innovation of the MMIE model. The network structure of the click-through rate prediction model is shown in x = T, where vi represents the feature vector of the ith behavior of the video in the user behavior sequence, H represents the length of the user behavior sequence, vi = T means the ith video contains image features, behavior features, and audio features; the features of the target video are va = T, and other features are represented as vc. The embedding layer needs to learn the mapping matrix Wj =  ∈ RD×K, which means the mapping matrix of class j elements, D represents the dimensionality of the original features, and Kj represents the dimensionality of the mapped features. Then, after the embedding layerec, the original behavioral sequence features are noted ase = T = , and the post-embedding features of other features are pointed out as ec. The user behavioral sequence needs to go through the interest evolution layer to mine the user interest representation behind it, and the formula can express its operation process: The recommendation system is not only applied to e-commerce platforms but also blogs, movie sites, personalized music software, social networking sites, and other platform sites all use the recommendation system to varying degrees, and each area and platform has its recommendation features.The model's input includes user behavior sequence, target video, and other features . Suppose the elements of the user behavior sequence are represented as After the construction of Transmedia Technology, Big Data Knowledge Graph de is completed; the original lengthy text data can be vividly visualized with the help of knowledge graph technology. Based on the proposed BERT-BLSTM-CRF-based entity identification algorithm and BGRU-ATTENTION-based entity relationship extraction algorithm, the time series dimension is introduced to extend our database by automatically acquiring the latest data daily to achieve the dynamic portrait of science and technology resources . The mosK users like the target user are formed into identical user groups based on the computer user similarity. The items of general interest from similar user groups are used to find the potential content of interest unknown to the target user.Content-based collaborative filtering algorithm (Item CF) extracts the features to be concerned from the filtered objects, uses their features to calculate the similarity, and then uses the preferences of different users to generate a recommendation list. The content-based collaborative filtering algorithm is popular in personalization applications. It calculates similarity based on the popularity of two items or contents, recommends similar items or contents for users to explore their potential associations, is insensitive to the addition of new content, and expands the data at will. A typical example of the model is the Conv NCF, whose convolutional layer uses a complete convolutional neural network with a convolutional kernel size of 2 × 2 and a step size of 2 until the final feature map (the topmost feature map) is mapped to a value, and then the vector composed of all the convolutional feature maps  is fed into the prediction layer. The recommendation of a user-based collaborative filtering algorithm is based on the similarity between users to find the group of users like the target users. In this similar group of users, items unknown to the target users but generally liked are recommended to the target users. Calculating the inter-user similarity can be implemented using Jaccard's formula, where the user's interest in the item is used as a behavioral indicator to calculate the inter-user similarity. We use Kera's to implement our model. We randomly select a training sample from the training set as the validation set for super parameter conditioning and then make predictions on the test set. We sample 4 negative sample instances for each positive sample instance by default . For a rFor MLP and Neu MF, we use the same structural configuration as in the NCF article and verify the effect of different embedding sizes. Finally, we find that the best performance is achieved for MLP with embedding size 64 in all three datasets. In contrast, the best results are achieved for both the MLP and GMF sides of Neu MF with Embedding. The best results were obtained for both the MLP and GMF sides of Neu MF with an embedding size of 64. We also tested the Neu MF pretrained with MLP and found no significant change in performance, i.e., no significant improvement. We also used BPR for personalized ranking on these three datasets. Deep learning algorithms are compute-intensive and storage-intensive. Deep convolutional neural networks enhance their expressive power by increasing their depth, trading time, and space for more advanced abstract features. Still, we do not report the experimental results of the BPR algorithm because all three datasets are too sparse to make the BPR algorithm perform poorly. The social network's extensive data search system includes a social network cross-media information real-time collection module, national security event cross-media feature extraction and search module, and social network content and user feature analysis module. Social network cross-media information real-time collection module: collects cross-media data from microblogs, saves the collected raw data from documenting database, synchronizes it to Elasticsearch regularly, and builds index. National security event cross-media feature extraction and search module: feature extraction of social network cross-media information, the introduction of irrelevant information filtering function of social network national security event, and semantic expansion search function of social network cross-media in the social network national security search system.The experiments in this paper are run on a Linux server with 4 graphics cards (GPUs); the GPU model is TeslaK20m. All models are implemented using python 3.5 and Tensorflow 1.4. The size of Embedding was set to 128 for all models; the batch size was set to 32, the learning rate was 0.1 and gradually decreased to 0.01. Sequence segments were segmented at 30-minute intervals, and each piece was restricted to contain the five most recent behaviors, while only the ten most recent subsequences were used. Behaviors that exceeded the limit were discarded, and vice versa were made up. The performance of the MMIE and SDIN models was investigated for different sequence lengths . The comI, i.e., I is only used for the learning of inter-segment interest table and not for the teaching of higher-order cross features; SDIN-SII model, i.e., inter-segment interest features are removed from the SDIN model H, i.e., the learning of inter-segment interest evolution process is missing. This subsection still uses the contribution degree to measure the effectiveness of each component. All components contribute positively to the SDIN model. The inter-segment interest feature has the highest contribution to the model with a gift of 1.42%, indicating a temporal relationship between segment interest differences. Learning the temporal relationship in user interest is the key to improving the model's prediction accuracy. The comparison test results of different components are shown in The SDIN model achieves the best experimental results from the comparative exploratory analysis with other models. The SDIN model is a combination of several components, so this subsection examines the contribution of each element of the SDIN model to the final experimental performance. This subsection analyzes the contribution of each aspect of the SDIN model using the structural exclusion method. The attention mechanism is removed from the SDIN model. The average pooling operation is used instead of the attention mechanism, i.e., the model cannot achieve the adaptive generation of user interest representation in the face of different target items; the skin-II model, i.e., the intra-segment interest feature is removed from the SDIN model SDIN and SDIN&FM models perform better than other models on both datasets, e.g., the SDIN model has a 1.28% higher AUC value than the MMIE model on the short video dataset. And comparing the models implemented based on the same sequential segmentation idea, the SDIN model has a 1.1% higher AUC value than the HRNN model. Since the SDIN model also adds an attention mechanism compared with HRNN, the SDIN model is still 0.88% higher in the Arnett model comparison, indicating that the self-attention tool is more vital than RNN in modeling sequential data. And comparing the SDIN&FM model with the SDIN model, it can be found that the SDIN&FM model performs 0.11% higher than SDIN; however, the improvement of the experimental results is not significant, but it still indicates that the lower-order crossover features contribute to the effect of the model. Perhaps, other ways of combining lower-order crossover features should be used.The rise of short video platforms has enriched people's entertainment life. Still, the ensuing massive number of short videos hinders users from accurately accessing the video content they are interested in. As an essential part of solving this problem, click-through rate estimation has received much attention from relevant research institutions and major companies. This paper proposes a cross-media collaborative filtering neural network model based on Deep FM for fast video click-through rate estimation. We use an RNN structure to process users' historical behaviors and data augmentation to process the training data. This paper proposes a short video click-through rate prediction model (MMIE) based on multimodal features and interest evolution. By analyzing the business scenarios in the fast video domain, this paper improves the structural unit of GRU by directly extracting short video multimodal features as video content representation and using attention mechanism in the processing of user behavior sequence features so that it can learn user interest evolution process with focus and improve the accuracy of click-through rate prediction. Experiments are conducted on the MMIE model, thus demonstrating the feasibility and effectiveness of the proposed model at the data level. The experimental results show that the MMIE model presented in this paper works best. In addition, many experiments are conducted on the way different features are combined, and the experiments show that the more elements are fused, the higher the accuracy rate the model can achieve.


We investigate the problem of population transfer in a two-states system driven by an external electromagnetic field featuring a few cycles, until the extreme limit of two or one cycle. Taking the physical constraint of zero-area total field into account, we determine strategies leading to ultrahigh-fidelity population transfer despite the failure of the rotating wave approximation. We specifically implement adiabatic passage based on adiabatic Floquet theory for a number of cycles as low as 2.5 cycles, finding and making the dynamics follow an adiabatic trajectory connecting the initial and targeted states. Nonadiabatic strategies with shaped or chirped pulses, extending the  Quantum (or coherent) control aims at developing methods for manipulating quantum dynamical processes at the atomic or molecular scale by shaped external electromagnetic fields ,2. It caUltrashort laser pulses that last only a few optical cycles have been transformative tools for studying and manipulating light–matter interactions . They alultrahigh-fidelity population transfer  . We alsoe method . The late method . The fore method . We achiAfter having defined the model in We consider the two-level system One can exhibit an instantaneous relative phase ted area :(5)∫titfIn the frame of the Floquet theory  written with the time-dependent phase Adiabatic passage through the (one-photon) resonance, using a pulsed (symmetric) Rabi frequency duration  , will allow a population transfer by adiabatic passage of a single Floquet eigenstate that will connect state ate time . We denoTo achieve population transfer, we apply the strategy of parallel adiabatic passage, where the adiabatic dynamics follows a level line requency ,40,41. Ishown in ,41 that In the situation of small number of cycles Considering We have obtained the most extreme situation with a low number of cycles Decreasing the number of cycles degrades the fidelity because one cannot satisfy a sufficiently large In this section and the next ones, one studies few-cycle pulses driving the dynamics in nonadiabatic regimes and analyzes how one can control the population transfer, in particular with ultrahigh fidelity.We introduce the notion of few-cycle generalized If one considers a single field In the resonant situation, ribed in , which cribed in  in the lHowever, in both situations, Our goal in the following consists in determining strategies of pulse shaping inducing ultrahigh fidelity in a We consider here the situation In this strategy, still with The effective Hamiltonian (16) with a single-mode field More generally, we can show that the phase can take the following forma priori large, we orient the search around the three strategies investigated in We provide the numerical results of a more systematic optimization procedure for the population transfer problem as described in In order to target and validate this strategy, we impose the resonance, Adding more modes, as proposed in the next subsection, will allow one to explore a different strategy to achieve the same complete transfer result.We now consider the resonant case ther see , with a One finally considers the situation with a nonzero detuning and a low number of cycles, For Optimization for the case In both cases, In this paper, we have explored quantum control with a few-cycle pulse implementing and generalizing two standard strategies, adiabatic Floquet theory and We have implemented a generalization of In a future work, we will explore the control in a multilevel system since the broadening of the spectrum induced by the small number of cycles is expected to impact significantly excited states. The present study will serve as an important exploratory work that will guide the strategies with the clear advantage of limiting the parameters landscape compared to blind optimal control strategies. More specifically, we will use the few-cycle-pulse adiabatic Floquet theory, including multistate effects, such as rotational and vibrational states in molecules (similarly to Ref. ), but be


The power demand from gas turbines in electrical grids is becoming more dynamic due to the rising demand for power generation from renewable energy sources. Therefore, including the transient data in the fault diagnostic process is important when the steady-state data are limited and if some component faults are more observable in the transient condition than in the steady-state condition. This study analyses the transient behaviour of a three-shaft industrial gas turbine engine in clean and degraded conditions with consideration of the secondary air system and variable inlet guide vane effects. Different gas path faults are simulated to demonstrate how magnified the transient measurement deviations are compared with the steady-state measurement deviations. The results show that some of the key measurement deviations are considerably higher in the transient mode than in the steady state. This confirms the importance of considering transient measurements for early fault detection and more accurate diagnostic solutions. The gas turbine is a complex system that requires extensive effort to examine its performance and behaviour under different operating settings. It has been widely used in power generation and propulsion . PredictGas turbine performance prediction models primarily rely on gas path measurements obtained under steady-state operating conditions, but it is crucial to use a transient measurement for the real-time assessment of compressor surge margin . TransieReal-time fault diagnosis is growing into a key topic of research in gas turbine engine condition monitoring due to the significant impact of an unexpected failure. In this regard, transient models are essential complements to steady-state models in order to have more effective and accurate diagnostic solutions. Based on actual geometry and control logic, Poorya et al.  created For predicting the transient performance of gas turbines, Djordje et al.  developeTo assure real-time monitoring of gas turbine performance, Jingchao et al.  presenteSangjo  suggesteAfter a comprehensive review, compared with the steady state, the literature on transient analysis is limited. The available transient studies focused on single- and double-shaft configurations. Moreover, the practical system response of transient loads ramping down with physical faults for three shaft-gas turbine configurations has not been investigated. From the diagnostic perspective, it is also important to demonstrate how magnified fault-induced measurement deviations are in transient conditions compared with steady-state conditions. This study aims to address the aforementioned gaps. Before initiating the transient simulation, the performance model has been developed using commercial software ,39, takiA three-shaft gas turbine engine, shown in The gas turbine performance model has been developed by numerous researchers using various techniques. The most accurate way to evaluate gas turbine performance is to calculate enthalpies and entropies at several gas path points. This approach is very powerful as it considers the deviation of specific heat due to the inlet conditions such as ambient temperature, ambient pressure, and humidity . Design The off-design model was built after the cycle design point calculations were successfully developed. The ability of an engine to operate in all operating circumstances, including the design point, is known as “off-design.” The two main factors are engine load and ambient state change. For example, the environment may change significantly from winter to summer, which has a significant impact on engine performance. Adapting the target engine’s design point to the standard compressor and turbine map using the scaling approach is the first stage in the off-design simulations. Each of the five component maps has a design point that was scaled systematically. The Newton-Raphson iterative technique is used in component matching; it is the second stage of off-design, to ensure compatibility with mass flow and work ,43. In tThe design-point performance model was developed after several iterations. The developed model was validated with the engine datasheet. The secondary air system and some engineering judgements based on published papers have been used. First, all known parameters were filled into the design point input window, and the simulation was initiated to see the model on the first attempt. Since getting an accurate model on the first simulation attempt is unlikely, the optimization task was conducted until the model output results matched the engine datasheet.Even though surge likely occurs in the compressor and choking likely occurs in the turbine, Finally, the design parameters from the gas turbine product datasheet were compared with the output of the design point model, as shown in The off-design model was created and validated using manufacturer data after the component maps were scaled and the cycle design point was correlated. The variable inlet guide vane schedule is shown in The off-design model was used to generate data after incorporating the power output versus ambient temperature and VIGV scheduling into the software. The generated data were then compared with the validation data. The validation data and the model that produces the efficiency versus ambient temperature and power output versus ambient temperature were closely matched. At each operational point, the power output versus ambient temperature error from the validation data was 0.02%, while a 4.05% error was found for the efficiency versus ambient temperature output data, as shown in In transient simulation, only a few input variables are required if the scope is performance. The polar moment of inertia is the fundamental difference between transient simulation and steady-state. The rest of the additional details on the transient input page describe a conventional proportional–integral differential control system. The actual transient simulation begins with steady-state operation, which has been calculated as a single cycle. The transient behaviour of a gas turbine engine can be simulated based on fuel flow rate versus time control, power output versus time control, and spool speed versus time control. In this study, power output versus time control was used, and a practical power ramp-down rate that was found in the research paper  was usedIn practice, the transient operating point of the gas turbine is achieved by modulating the fuel flow rate. In turn, a control system compares the generated power output with the demanded power output based on the signals provided by the sensors. Any discrepancy between the demanded power and generated power leads to either acceleration or deceleration. The commercial software that we used in this study uses a very simple controller named Proportional Integral Derivative (PID). The PID controller increases or decreases the fuel flow rate to maintain the demanded power. The PID uses the spool speed as input to navigate the fuel flow rate. Generally, a Proportional Integral Derivative (PID) controller works by controlling an output to bring a process value to a desired set point. The PID controller is continuously monitoring the error value and, using this value, calculating the proportional, integral, and derivative values. The controller then adds these three values together to create the output. In a PID controller, there is a term called “gain”. It is the term used for the multiplication factor. By adjusting the gain settings or multiplication factor of the proportional, integral, and derivative, the user can control how much effect the PID controller has on the output and how the controller will react to different changes in the process value. Each of the terms, proportional (P), integral (I) and derivative (D) will be calculated to get the output. The proportional term is calculated by multiplying the P-gain by the error. The purpose of the proportional is to have a large immediate reaction on the output to bring the process value close to the set point. Due to the limitation of the P-controller, where there is always an offset between the process variable and setpoint, an integral term is needed, which provides the necessary action to eliminate the steady-state error. It integrates the error over a period of time until the error value reaches zero. It holds the value for the final control device at which error becomes zero. The last one is the derivative term that creates an output signal proportional to the rate of change of the error signal. The derivative term looks ahead to see what the error will be in the future and contributes to the controller’s output accordingly. That brings us to a term called “controller tuning”.The commercial software that we used in this study uses Equations (1)–(3) to express Proportional Integral Derivative (PID). The fuel acceleration or deceleration is caused by any difference between the generated and required power. That means the fuel flow will be either increasing or decreasing based on the discrepancies between the actual and desired power output values.The performance of the gas turbine components, especially the compressor and turbine, is essential to the engine’s overall performance because of its vulnerability to various internal and external deterioration factors. A lack of lubricating oil may be the primary factor in mechanical problems, which also include misalignment, imbalance, cracks, and bearing failures. Performance-related problems such as dust and fouling in compressors, corrosion, erosion, inappropriate combustion, increased clearance around blade tips, domestic object damage (DOD), and thermal distortion are the second cause of gas turbine deterioration. There are two types of gas turbine performance degradation: temporary (recoverable by washing) and permanent (non-recoverable by washing). Temporary degradation can be recovered during engine overhaul and operation; however, permanent degradation requires replacement. Temporary degradation is caused by fouling, erosion, corrosion, and blade tip clearance. The most common causes of gas turbine performance drops are fouling and erosion . FoulingFollowing the validation of the design point and off-design gas turbine performance models in this study, the next task was to implant physical faults such as fouling and erosion to investigate their effect on the gas turbine’s performance at steady state and transient state. While introducing physical faults into the model, the relationship between physical faults and performance parameter deviation shown in The deviation of gas path measurement when erosion occurs at 100% fault severity with load variation at transient operation is shown in This study clearly shows that physical faults such as fouling and erosion can be detected much earlier in a transient simulation than in a steady state. It is also observed that the effect of fouling and erosion on steady-state gas turbine performance differs a little from the transient mode of gas turbine performance. It is observed that the deviation is somehow higher in the transient mode than in the steady-state mode of simulation. In most cases, as the load increases, the deviation of the performance parameter and measurement parameter increases. However, because of component matching discrepancies, in some cases, the deviation of the gas path and performance parameters are not linear with the load ramp rate. The simulation result shows that fouling has a significant effect on the upstream components more than the downstream components, and the health status of the upstream components is very critical to the entire performance of the gas turbine. The maximum isentropic efficiency deviation due to fouling and erosion occurs in the low-pressure compressor more than in other components. The fuel flow rate is raised when fouling and erosion occur at each component and at each power ramp rate. The reason is that when physical faults are injected by manipulating flow capacity and isentropic efficiency at power output versus ambient temperature scheduling, the values of the output flow capacity and isentropic efficiency will be reduced significantly more than the amount reduced to simulate the physical faults. This is because more fuel must be delivered to maintain the power output. The increase in heat at constant power causes decreases in component efficiency and overall gas turbine efficiency as well. Generally, in this paper, three-shaft gas turbine transient performance gained the focus. The deviation of component isentropic efficiency and gas path measurement parameters under transient mode are discussed following the plots. The results will be very helpful while developing a fault detection, isolation, and identification model. The authors suggest that future research could look into the start-up performance of three-shaft gas turbines, which is beyond the scope of this study. Furthermore, the combined effect of physical faults in a transient state remains an unexplored problem for researchers to investigate.


Ultrafast laser ablation is widely used as a versatile method for accurate micro-machining of polymers, glasses and metals for a variety of industrial and biomedical applications. We report on the use of a novel process parameter, the modulation of the laser pulse energy during the multi-scan texturing of surfaces. We show that this new and straightforward control method allows us to attain higher and lower roughness ( Alteration of metal surfaces induced by laser irradiation was very soon observed after the invention of the laser . The morFemtosecond lasers have also been employed to control the surface roughness with the generation of laser-induced micro- and nano-structures, such as microbumps and nanojets , microspLikewise, researchers have investigated more advanced laser-tuning parameters, such as the laser spot spatial energy distribution with, e.g., top-hat beams . MoreoveThe control of the roughness has direct consequences on the local wettability, with the possibility of achieving hydrophobic or hydrophilic surfaces ,37,38,39In this report, we present a novel and straightforward method to control the final surface roughness by altering the pulse energy during multi-scanning irradiation, which has not yet been discussed in the literature to the best of our knowledge. Unlike conventional laser processing, where a constant fluence was employed during the process, here we showcase that controlling the energy level within the multi-pulse irradiation sequence permits the control of the surface’s final roughness with a nearly unchanged ablation efficiency.Although the variation of the pulse energy was manually carried out between successive scan passes in this proof-of-concept report, the control of the pulse energy during laser processing can be easily automated by tuning the laser’s built-in external acousto-optic modulator; hence, a direct adaptation to industrial processing applications is straightforward.A classic high-overlap raster scan pattern of 20 scans using uniform laser pulse energy was compared to the same scan pattern, with the pulse energy varying linearly between the scans with either an increasing or decreasing trend and the overall energy deposition being identical. The surface roughness after irradiation was subsequently evaluated for each case. This parametric study was conducted on four materials: stainless steel, titanium, brass and silver. The surface topography of the irradiated surfaces was analyzed using confocal microscopy. Single-static shots at the three different conditions were equally achieved and characterized with atomic force microscopy (AFM) and scanning electron microscopy (SEM).The presence of regular LIPSS at the bottom of the ablation region was noticed in the case of decreasing energy configuration. Topographic parameters as the roughness This paper is structured in the following way: The schematic diagram of the experimental setup for laser ablation of metallic workpieces is shown in f-theta objective.The linearly polarized gaussian beam from the fs laser was magnified through a beam expander (BE) and then sent through a galvo scanner  and focused on the surface of a metallic workpiece through a 100 mm 2), measured using a Beamage-4M camera . For all micro-machined surface areas, a constant number of pulses per unit area were deposited on the metal surface using the common raster scanning method . The vaface see c. The vaterature .Literally, the area see d 48]. I. ISdr isline see e. In othThese parameters have been extracted from surface topography measurements performed with the aforementioned confocal microscope. The measurements of the roughness parameter The roughness of the stainless steel and titanium samples exhibits a clear trend, with the maximum value noticed with the increasing energy distribution  and the minimum one with the case of decreasing energy . In the case of brass, whose initial roughness is significantly higher than the other samples, the trend is found to be similar to the previous cases, but the values vary in a much smaller range (0.884–0.691 µm). In the case of silver, the trend is somewhat different. The roughness with increasing energy gradient is slightly lower than in the case of uniform energy  and a slight drop to 0.521 µm is observed in the case of decreasing energy. Thus, these results demonstrate that the use of the energy gradients permits better control of the final roughness. Noteworthy, the case of brass shows a situation where the femtosecond laser irradiation with decreasing energy distribution even permits the reduction of the surface roughness as compared with its initial value. Concerning the skewness In the cases of brass and silver, no detectable trend has been found concerning the eaks see e, this qRR in mm3/min can be calculated following 3 and AE in µm3/µJ can be deduced from 3, By measuring the depth of the ablated surfaces (averaged between three repeated measurements), the removal rate This shows that it is possible to control the surface roughness without compromising the ablation efficiency. Further validation of this result has been studied from ablation rate curves of the investigated materials found in the literature . The exp2 is obtained for a material by simply multiplying The choice of the fitting equation was carried out to obtain the best fitting performance. The lasers used in these studies were relatively similar to the one employed here, lying in the infrared region with sub-picosecond pulse durations. In order to compare these static shot experimental data with our results, we have evaluated the number of pulses per area spot to be on as in  and the As can be seen in 2 implies ablation regimes of low-removal efficiencies, e.g., when the laser fluence is very close to the threshold or very far from the optimal ablation fluence. Thus, it is slightly less efficient than a constant energy irradiation at a peak fluence which is close to the optimum ablation value.However, in a first approximation, these results appear to be coherent. Moreover, simple static ablation models are often used to discuss milling experiments in good agreement . OverallLastly, we tried to isolate the effects of the gradients from those of the scanning on metallic surfaces by investigating the static impacts at a micrometric scale by sending 20 laser pulses with and without the energy gradient sequence. The low number of 20 pulses was chosen in order to obtain relatively superficial impacts to ease the micrometric characterization.2), as observed in [Thus, an analysis of the static shots on a stainless steel sample has been performed with SEM and AFM, as depicted in erved in .2 of this study. Conversely, in the case of decreasing energy distribution (2.In the case of increasing energy distribution (For this reason, a regular pattern of LIPSS has been formed in this case . This reIn the decreasing energy sequence, hypothetically, the ablation sparsely occurs on the irradiation region, thus smoothing out the rough surface left by the previous pulses of higher energy. While scanning (such as in A new approach for controlling the post-irradiation roughness of several metal workpieces by changing the laser energy during multi-scan irradiation has been presented. To the best of our knowledge, this method has not been discussed before in the previous literature, where instead, common approaches with uniform energy have been used. Pulse overlaps of 86% and a scan speed of 36.4 mm/s have been used for the experiments at 10 kHz of pulse repetition rate. The experiments showed the same trend for all the cases: the highest value of roughness has been obtained with an increasing pulse energy distribution, and the lowest one with the case of decreasing energy. Therefore, in some cases, it is more convenient to use energy gradients rather than the usual uniform energy irradiation, depending on the need to achieve higher or lower roughness. Likewise, an increasing energy distribution is evidently indicated for achieving a higher roughness compared with the case of uniform energy and a decreasing one for a lower roughness formation. Additional topographic parameters, such as the developed interfacial area ratio, the skewness and the ablation efficiency of the processed surfaces, have been investigated as well in this work. It has also been demonstrated that the ablation efficiency does not significantly change between uniform energy and energy gradients, which means that the ablation efficiency has not deteriorated from one case to another. Lastly, a static analysis has been performed with static shots to analyze the impact of the energy distributions on the topography of the steel surface at a micrometric scale by using an SEM/AFM tool. The irradiated steel surface exhibits a chaotic topography in the cases of uniform and increasing energy distributions of energy, whereas a smoother surface with LIPSS presence is observed in the decreasing energy case, in harmony with the aforementioned roughness trend observed in the scanning study. The outcomes shown in this work open new possibilities for roughness control in industrial and biomedical applications where tuning the surface topography is of utmost importance for achieving desired surface properties, such as hydrophobicity, self-cleaning, anti-bacterial effects and so on.