Human tracking and traffic monitoring systems are required to build advanced intelligent, innovative mobility services. In this study, we introduce an IoT system based on low-cost hardware that has been installed on the campus of the University of Malaga, in Spain. The sensors gather smart wireless devices (Bluetooth and Wi-Fi) anonymous information and environmental noise level around them. This research studies the spatio-temporal behavior of people and noise pollution in the campus as a short-scale Smart City, i.e., a Smart Campus. Applying specific machine learning algorithms, we have analyzed two months of captured data (61 days). The main findings from the analysis show that most university community members move through the campus at similar hours, generating congestion problems. In addition, the campus suffers from acoustic pollution according to regulations; therefore, we conclude that the proposed system is useful for gathering helpful information for the university community members and managers. Thanks to its low cost, it can be easily extended and even used in other similar environments, allowing democratic access to Smart City services as an excellent added value. Today, it is a fact that most of the world’s population lives in cities. This high concentration of people and vehicles in specific geographic zones has amplified the importance of issues related to the mobility of the inhabitants and the transportation of goods. In this context, smart city initiatives have emerged ,2,3. One(a) traditional measurement on-road hardware  [(b) cameras, which are also expensive and the accuracy of the gathered data may depend on external factors as the meteorology [(c) floating cars [These intelligent systems that are applied to mobility challenges require gathering accurate traffic/mobility data continuously to operate, which is still a big challenge today. Essential valuable mobility data, such as the number of cars per street, the origin/destination (OD) matrices of the city, and pedestrian behavior, are scarce and difficult to obtain. Nowadays, the most common systems of obtaining this type of data only perform vehicle count or provide an estimate of the road traffic density in a given area; thus, the most widely used means of assessing mobility at present in our cities are: tectors) , which ieorology ; (c) floing cars .Moreover, the use of cameras to track the movement of vehicles and people requires the extraction and identification of vehicle license plates and a feature vector of the person’s face/body, respectively. These data are stored and processed in the system. As these data can be used directly to identify vehicles (and their drivers) and persons uniquely, it can lead to an invasion of user privacy and provoke General Data Protection Regulation (GDPR) issues.(a) the service used to exchange the GPS position consumes a substantial amount of energy [(b) the service generally shares private information with a third party, usually a private entity, that manages the service [In recent years, with the proliferation of smart mobile devices , another manner to obtain vehicles/pedestrians mobility information is by using the cellphone location information services ,11,12. TA promising alternative to gather vehicles/pedestrians mobility is the installation of sensors able to detect Bluetooth (BT) signals and identifying vehicles and pedestrians by the Media Access Control (MAC) hardware addresses of their smart devices . Thus, tThe main aim of this article is to propose a low-cost alternative to loop detectors, cameras, and GPS-based systems to gather vehicle/pedestrians’ mobility. Thus, a novel cyber-physical system is presented. Our system extends BT-detection-based sensors by also gathering Wi-Fi (IEEE 802.11 wireless-based) signals in order to mitigate the inaccuracy of BT detectors . The idehttps://www.uma.es/smart-campus (accessed on 30 June 2022). Smart campus initiatives aim to apply intelligent systems to provide advanced services to the university community members [Thus, using the proposed ad hoc cyber-physical system to track mobility, we deployed a wireless sensor network (WSN) at the campus of the University of Malaga to analyze its suitability. The installation of this infrastructure is part of the Smart-Campus initiative of the University of Malaga, see University of Malaga Smart-Campus website— members ,17,18.The remainder of this paper is organized as follows: This subsection further describes the main aims of the research published in this article, explains how the work is structured, and discusses the relevance of this article in the scope of the journal.To detail a new IoT cyber-physical system for vehicles and pedestrians’ movement tracking based on a previously presented IoT system that only counts the number of vehicles at a given point . The maiTo propose a case study to show the functionality of the cyber-physical system in the Smart Campus context. The case study analyzes vehicle/pedestrian mobility within the campus of the University of Malaga, although the use of the sensor can be easily adapted to be used on any other campus. This use case is relevant because high road traffic density situations and crowded (high-people density) areas cause discomfort to the university community members. In addition, it is important because since the COVID-19 pandemic is being experienced, university managers are trying to measure the occupation of enclosed spaces, such as classrooms, cafeterias, libraries, etc., and the movement of people; thus, it is possible to identify where (which areas) and when (at what times) are crowded. In this way, the university decision-makers can take the appropriate measures to mitigate the accumulation of people in order to avoid mass transmission of the virus among members of the university community.To evaluate the system’s ability to assess ambient noise and to discuss the importance of providing such information to university managers.The main aims of this article are:In order to further understand the main contributions of this work, the manuscript first introduces what data the sensors collect and how these data are collected and processed see ; second,The relevance of this article in the field of IoT for Smart Cities is that it presents a sensor-based cyber-physical system for tracking vehicles and people based on simple, modular, scalable, and low-cost hardware. In addition, on top of the tracking systems based on cameras, our approach has the advantage that it does not transmit or store private information such as vehicle license plates or images  of people, thus mitigating possible GDPR issues.Furthermore, an actual use case is presented at the University of Malaga (easily adaptable to other campuses or environments) that employs the proposed system in the context of Smart Campus to evaluate the movement of vehicles and people and to measure the noise within the university campus. University managers use the information provided by the system to assess road traffic, mobility of university community members, and environmental noise levels.(i) the random sampling is impracticable and it limits the representativeness of the results; (ii) the highly gathering costs; (iii) they are usefulness from obtaining real-time data.Researchers and Smart City practitioners have proposed different approaches to obtain information about the inhabitants’ mobility in different contexts and on various scales. Traditionally, this information has been obtained by different methods, such as collecting travel diaries and surveys . Even thThis study focuses on methods that rely on gathering wireless signals for monitoring mobility because they can obtain accurate real-time information, do not involve high installation costs, and are not road intrusive. The most promising approaches based on this idea use Wi-Fi, BT, and Radio Frequency Identification (RFID).RFID technologies have been applied principally for tracking humans in indoor environments . Its maiSeveral researchers have used BT and Wi-Fi signals (or beacons) to track spatiotemporal behavior in various domains and environments ,22; howeThe methodology of detecting and tracking devices (pedestrians and vehicles) using BT and Wi-Fi is very similar. It consists of continuously gathering wireless beacons using scanners installed at a set of given locations of interest. These scanners register every detection by storing the unique MAC address of the beacon’s source device and the precise detection time. This approach is based on the proximity principle , i.e., iBT scanners have been applied to study the tourists’ behavior in a city , to eval(i) The users usually tend to keep their device’s Wi-Fi turned on to increase the chance of connecting to any nearby Wi-Fi network; (ii) The BT discovery time is ten times longer than the Wi-Fi one; and (iii) The Wi-Fi communication range is much longer than the BT one, and therefore, devices that are farther are detected. The more extended communication range of the Wi-Fi connections is also a disadvantage when using these communication interfaces to monitor users. The accuracy of the tracking system is limited because the device is supposed to be located at the same point as the sensor; however, as it is not designed for short-range communications such as BT, the Wi-Fi device could be located at a given significant distance.Wi-Fi scan-based sensors have also been applied to extract features from a human’s spatio-temporal movement in different environments by using a similar approach to BT. The detection ratio of devices that uses Wi-Fi interfaces is more competitive (higher) than when scanning BT ,22. ThisThe main difference between our approach and other systems proposed in the literature is the combination of the data coming from the detection of BT and Wi-Fi signals and the level of sound noise. The combination of these data sources provides a global knowledge of the road traffic status and people density in a given point and their mobility: the system captures MAC addresses and noise data, converts it into aggregated information, and then builds knowledge out of it.Compared to on-road hardware : Our sensors consist of simple hardware devices, which are easy to find in the market, low-cost, and easy to install and maintain . The sensors consume low energy . In addition, our cyber-physical system detects vehicles and people. In general, on-road hardware gathers information only about vehicles.Compared to cameras: Our system does not transmit or store images or data of vehicle license plates or pedestrian faces/bodies; thus, it mitigates possible GDPR issues. Furthermore, the systems based on cameras apply high computationally cost algorithms to process the images and obtain the data. In contrast, our approach uses basic methods to extract the MAC addresses from the gathered packets/datagrams.Compared to tracking systems based on wireless signal detection: Our proposal improves the accuracy of the other ones in the literature because we decided to simultaneously capture the signal from the two types of network interface . Detecting both types of wireless signals improves the likelihood of detecting devices.Compared to all the other systems: In addition to the detection of the wireless device, our cyber-physical system gathers noise levels because there is a correlation between noise pollution and road traffic ; thus, tThus, the main advantages of the proposed system over the ones presented in the literature are:The IoT cyber-physical system proposed and applied in this article measures and evaluates vehicle/pedestrian mobility by detecting and tracking smart devices and gathering environmental noise. In order to detect smart devices, the system captures the Bluetooth and Wi-Fi signals produced by the smart devices’ wireless interfaces and extracts their MAC address. Moreover, the system processes the MAC address gathered data to track smart devices .This section details the data captured and the processes carried out by our sensors to detect smart devices, track movement, and measure environmental noise.The proposed sensors detect smart devices by extracting the information captured in the packets that the devices broadcast throughout their wireless interfaces (Bluetooth and Wi-Fi).In order to detect Bluetooth signals generated by smart devices, the Bluetooth interface of the sensor is set to discovering mode ; thus, tAs Bluetooth communication range is limited and users of smart devices may disable the Bluetooth interface, the designed sensor gathers information from Wi-Fi signals in order to maximize the likelihood of detecting the devices. Smart devices that apply 802.11-based protocols continuously broadcast packets containing the MAC frame. The information encapsulated in the frame is useful for tasks such as control medium access, roaming support, and authentication . The Wi-Human tracking is carried out using the specialized wireless interfaces installed in our sensors. As presented before, the main idea is to capture valuable information that the smart devices broadcast through their Bluetooth or Wi-Fi communication interfaces to identify them individually. Our sensors extract MAC addresses from the wireless signals. The sensor’s location can be used as an approximation of the location of the detected device. Storing this information with the exact time when the device was detected (time stamp) allows the system to detect human flows.Sensor 1 to Sensor 3 in 10 min and 35 s.Device with MAC address F4:33:5F:F3:42:01, which has moved from the location of Sensor 3 to Sensor 1 crossing the location of Sensor 2 in 9 min and 15 s.Device with MAC address 00:25:96:FF:FE:12, which has moved from the location of Therefore, in our study, the movement of a given device from the location of the sensor equivalent sound pressure level, i.e., The noise level data are captured by using the accurate sound meter introduced in  of time . In our This section describes the main components of our cyber-physical system, which is deployed as a wireless sensor network (WSN) at the university campus. The main purpose of this system is to measure the spatio-temporal dynamics of the people throughout the campus and to evaluate the environmental noise. This section first illustrates the IoT devices used to take the data and second presents the global system operation.The design of our IoT devices is mainly focused on overcoming the high costs and the sensing limitations of the traditional road traffic data collectors . In ordeThe Raspberry Pi is a low-cost and credit-card-sized computer. It performs the required tasks for (1) individually identifying smart devices by detecting their wireless signals, (2) obtaining the sound data coming from the sound meter, (3) synchronizing the data by adding time stamps, (4) temporally storing and filtering the data, and (5) interacting with the server using wireless connectivity.BENE TECH GM1356, see BENE TECH website—http://www.benetechco.net/en/products/gm1356.html (accessed on 30 June 2022), which uses a USB interface to send the noise level values to the Raspberry Pi. This meter is able to measure noise levels in the range between 30 and 130 decibels (dB). The external wireless interfaces used in our sensor , and the Bluetooth ASUS USB-BT400, see ASUS website—https://www.asus.com/Networking-IoT-Servers/Adapters/All-series/USBBT400/ (accessed on 30 June 2022), adapters) have been selected taking into account that they can be used in monitor mode to extract the MAC addresses of the detected devices.The sound meter installed in our sensors is the Our IoT devices are connected to a WSN whose global architecture is shown in In order to carry out the transfer of data from the sensors to the data center, an architecture based on the client/server model was designed see b, A set An application protocol has been developed to determine the sensors’ status. This protocol defines a procedure in which each sensor sends a packet continuously (every minute) to the server, including information about its current status. In turn, the sensors are equipped with a self-protection method, which allows automatically restoring the sensor in case of failure.Finally, a server performs three main tasks in our data center: (1) storing the data in a database, (2) applying different methods to generate information and knowledge from the data, and (3) providing a web interface to visualize the key information.In this article, we have defined a use case to evaluate the IoT system proposed at the University of Malaga. Note that our system can be easily installed and adapted to be used over any other university campus or area.2. This infrastructure consists of ten sensors, as the ones introduced in In this study, we have made use of the infrastructure installed in the Campus of Teatinos of the University of Malaga, that covers an area of 0.71 KmThe dots marked with a circle are the four sensors that gathered the data used in this study. We have selected the data from these four sensors because they are the ones that have been operating longer, and therefore, they provided more data. The data analyzed cover two months (from 9 January to 9 March of 2019), i.e., the data evaluated were captured during 61 days.This article is focused on extracting information about the human movement behavior and the environmental noise generated through the campus. It is important to remark that, as the study takes place on a university campus, most human movements are carried out during working days (from Monday to Friday) and regular university school opening hours (from 8:00 h to 21:00 h); therefore, the analysis of the human spatio-temporal patterns (human flows) proposed here takes into account these periods of time.In order to improve the knowledge about the evolution of the environmental noise on the campus throughout the time, we analyzed the level of noise sensed by the four sensors studied.The proposed use case is relevant because the university managers at the University of Malaga are concerned about (a) the number of users in some specific university facilities  because crowded areas provoke discomfort; (b) the mobility of the university community members because traffic jams negatively affect the daily life of the university community members ; (c) the noise levels suffered by the university community members may negatively affect to the running of the classes and may provoke health issues.In addition, this use case is relevant because since the COVID-19 pandemic is being experienced, university managers are trying to measure the occupation of enclosed spaces such as classrooms, cafeterias, and libraries, in order to control the virus transmission among members of the university community.Therefore, the information provided by the IoT system proposed here can be used by the university managers to scale services and change their schedules to avoid overcrowding in facilities such as cafeterias or libraries. Moreover, the managers could select different opening and closing times for several schools to decrease the transit of people through the campus during similar hours. In turn, the managers could avoid placing classes in the noisiest areas of the campus so that students do not suffer from high noise levels.This section presents the experimental analysis carried out to evaluate the human movement and environmental noise at the campus.First, we discuss the number of smart devices detected by each sensor in order to evaluate affluence of people in a given area. Then, we analyze different spatio-temporal aspects of the tracked human flows by using our cyber-physical system. Finally, we study the environmental noise captured on the campus.In order to measure the number of smart devices identified by our sensors, the number of different MAC addresses captured by each sensor during a given period of time (in this case ten minutes) is evaluated. As the sensors detect no moving devices , a filtering pre-process of the data is applied in order to discard the MAC addresses of such static devices in further analyses.These results confirmed most smartphones have the Wi-Fi interface enabled but not Bluetooth one. In turn, the communication range of Wi-Fi communications is higher than Bluetooth communications. This allowed the sensors to detect more Wi-Fi devices (at longer distances), however, this may lead to have less accurate results since these devices may be very far from the sensor (that determines their location).Useful findings can be drawn about people’s behavior by analyzing the patterns of people flows into the buildings. In our study, our sensors are installed nearby the main doors of the buildings to gather data about people crossing throughout the campus streets, but also to provide the detection of the people entering or leaving the facilities. Thus, we evaluate the devices sensed by each sensor to extract affluence patterns. Late-night shift (every day from 0:00 h to 7:00 h): Device detection was almost negligible; therefore, there were hardly any people moving around in the different facilities/buildings on campus.Standard working days : The number of detected devices increased dramatically from 7:00 h. Three peaks were able to be observed in which the sensors detected more people. The most prominent is around 14:00 h in the afternoon. In turn, there were two detection peaks that were less pronounced, one around 9:00 h and another around 21:00 h. These peaks coincide with the times when students enter and leave their classes.Standard non-working days : It was a similar pattern to the one shown above , but far fewer people were detected. These days the buildings are mainly staffed by workers performing maintenance or research tasks.The results shown in As it was observed, in general, the flow into the buildings depends on the working and studying times at the university campus.The Mean day results in Focusing on the people affluence in the buildings, i.e., sensor ids in Sensor 3 and Sensor 4 were installed in office buildings used for administrative and research work. Thus, the affluence of students in these buildings was limited. For this reason, the number of sensed devices was lower than for the other two sensors. In addition, the location of these two sensors has to be taken into account to evaluate their results. They were installed on the walls of these buildings separated from the roads and the sidewalks (see the map in As working days (from Monday to Friday) represented the days with the highest people flow throughout the campus, this section analyzes the human spatio-temporal patterns (human flows) during these days. Thus, Four different movements or flows of humans (devices) were tracked. They are named: Flow A, movement from Sensor 2 to Sensor 3; Flow B, movement from Sensor 3 to Sensor 2; Flow C, movement from Sensor 3 to Sensor 4; Flow D, movement from Sensor 4 to Sensor 3.The bar diagrams in In general, the human tracking flows results are in line with the results about the number of detected devices presented in During the schools opening times , there were detection of a significant number of flows. although there were less evident increases during the end of school hours (14:00 h and 19:30 h).The high rise of human flows tracked during the schools opening times  and the less evident increases during the end of school hours (14:00 h and 19:30 h) is mainly due to a remarkable number of students that arrived in the morning staying at the campus until late afternoon (these students might be attending afternoon shift classes or visiting the libraries). Generally, these students eat in the university cafeterias on campus.In addition, our cyber-physical system allows the evaluation of the speed of the tracked flows. The average speed of the human flows gathered was 2.95 m/s (10.62 km/h), representing a relatively high pace for human walking. This is mainly due to the system not only tracking people walking but also people using vehicles to move through the campus, such as bicycles, motorcycles, and cars. Thus, the highest speed of a tracked flow was 13.1 m/s (47.2 km/h), which would correspond to a motor vehicle, such as a car.The insights provided by analyzing the sensed devices and the human flows tracked by our cyber-physical system directly assist the university managers. We have observed that choosing the same opening and closing hours for several university schools provoked high mobility of people at similar times, which may produce road congestion and overcrowding issues. The university managers could select different opening and closing times for several schools in order to decrease the transit of people during similar hours.As in The times with the lowest noise levels for the four sensors are the ones between midnight and 7:00 h, which coincides with the hours in which we sensed the lowest number of smart devices.The level of noise increases critically from 7:00 h. This increment depends on the type of the day: it is higher for working days than for no working days; however, these differences are less marked than in the data of the number of detected devices and human flows see .Sensor 1 and Sensor 4 results do not present significant differences regarding the different type of days or times. This is mainly because they are installed close to some continuous noise source.In this case, the patterns defined by the results in In order to evaluate the noise level depending on the sensor, we have applied a polynomial curve fitting to the points defined by the distribution of the noise level measures. Thus, we have obtained a curve that describes the noise evolution throughout the day. As it can be shown in According to the results in The university managers should consider these results and the benefit of maintaining an infrastructure of sensors to evaluate noise since noise pollution is a common unpleasant problem that negatively affects human behavior and health; thus, the European Commission adopted a directive in which the institutions are required to gather real-world data on noise exposure to promote local actions to mitigate possible issues .This study presents an IoT cyber-physical system based on a WSN installed at the Campus of Teatinos of the University of Malaga to capture human mobility through the campus and the environmental noise, which are two critical factors affecting the quality of life of the members of the university community. The design of the system allows expanding the sensors with new components to evaluate other metrics . Moreover, the whole methodology proposed here can be easily adapted to be used on any other campus. The main results show that accurate information can be captured.According to the evaluation of the data captured by our system over two months, the patterns of the collected data about the movement of people are very similar to the same noise levels measured. For example, the time that obtained the highest number of tracked human flows matches with the highest amount of measured noise, which corresponded to the regular university school starting hours. In turn, these patterns may be classified into two main groups: working days and not working days.Regarding the human movement, the data demonstrated that most students across the university community move through the campus at similar hours . This generates most of the congestion problems at the campus, but they could be mitigated by shifting the scholar schedules.The evaluation of the noise levels sensed resulted in the campus suffering from acoustic pollution according to the Malaga city council regulations since the noise levels are always higher than the ones set by this organism.The analyses presented in this study are helpful for the university managers since they pointed at critical aspects that could be improved to benefit the whole university community. It has been observed that most mobility through the campus occurs at similar times, which may produce road congestion and overcrowding issues. Moreover, it has been seen that university community members suffer from high acoustic pollution at the location of the sensors; thus, the university managers have to take measures to change the spatio-temporal behavior of the university community members  and to allow the community members to avoid areas of the campus with high noise levels.The main lines for future work are focused on four main aspects: first, proposing a scalability analysis to evaluate our cyber-physical system on other dimensions by including data from more sensors and longer times; second, applying machine learning and deep learning methods  to provide deep insights into the data and predictions; third, analyzing privacy issues and GDPR violations that the operation of our system may rise; forth, devising a website to offer information and knowledge about the university campus to the university community.


The numerical simulation of rocket engine thrust chambers is very challenging as several damaging phenomena, such as plasticity, low-cycle-fatigue (LCF) and creep occur during its service life. The possibility of simulating the thermostructural behavior of the engine, by means of non-linear finite element analyses, allows the engineers to guarantee the structural safety of the structure. This document reports the numerical simulations developed with the aim of predicting the thermostructural behaviour and the service life of the thrust chamber of a liquid-propellant rocket engine. The work represents a step ahead of previous researches by the authors, with particular reference to the addition of the Smith-Watson-Topper (SWT) fatigue criterion, and to the implementation of a sub-modelling technique, for a more accurate assessment of the most critical section of the component. It was found that the equivalent plastic strains in the most critical nodes obtained through the sub-modelling technique were about 20% lower than those calculated without sub-modelling. Consistently with experimental tests from literature conducted on similar geometries, the most critical areas resulted to be on the internal surface of the chamber. The analyses demonstrated that the LCF damaging contribution was significant, with a life prediction for the thrust chamber of about 3400 cycles. The investigation presented in this work was conducted within the frame of the HYPROB Program, a research project aimed at developing and implementing technologies for regeneratively-cooled liquid-propellant rocket engines, which use liquid methane and liquid oxygen. Since elevated thrust values are requested, rather high chamber pressures and heavy heat fluxes are predicted in the combustion chamber. Consequently, active cooling solutions are needed to maintain the adopted materials at suitably low temperatures, i.e., 500–800 K.From the thermo-mechanical point of view, the pressure inside the cooling channel must be higher than the pressure of the combustion gases in the thrust chamber causing, as a result, bending of the inner wall separating the hot gases from the coolant flow; furthermore, compressive hoop stresses arise in the inner wall since its thermal expansion is restrained by the external cold structure. The induced thermal stresses generally exceed the yield stress generating significant plastic deformations in the hot-gas side walls. The failure mechanisms of the thrust chamber have been investigated in several experimental campaigns. For instance, Hannum et al.  and QuenThe thrust chamber structure is composed by electrodeposited layers made of copper and nickel on the outside with a CuCrZr alloy element on the inside. A regenerative cooling system was adopted to remove heat from the inner structure of the thrust chamber, through a flux of methane in the axial cooling channels. Being a regenerative cooling system, the same cooling fluid is also injected as fuel into the combustion chamber. Elevated thermal gradients exist through the inner chamber wall (ligament) that separates the cooling channels from the hot gas. In this context, several efforts have been made to optimize the regenerative cooling channel. Xu et al.  establisFurthermore, several efforts have been made to study the thermal efficiency of the cooling system of regeneratively cooled thrust chambers by means of thermal and fluid-dynamic numerical investigations ,10.In general, the thermomechanical behavior of thrust chambers of liquid rocket engines is described by means of a model allowing for combined hardening (isotropic and kinematic hardening) and creep. Several works demonstrated that the best suited kinematic hardening models are the nonlinear ones, based on Armstrong and Frederick ,14,15,16Regarding the investigation of typical thrust chamber failure mechanisms, creep, Low-Cycle Fatigue (LCF) and ratcheting have been identified as the most likely causes of failure ,21,22,23A time step sensitivity analyses was conducted in order to better describe those phases where very steep temperature changes occur in very short time periods, i.e., during ignition and purging phases.A sub-modelling approach was implemented to transfer boundary conditions from a global coarse model to a local fine model  criterion using the commercial code Since the experimental testing activity for these applications can be very expensive, it is mandatory to minimize experiments by adopting high fidelity numerical models. Within this context, the accuracy of the numerical modelling obtained in a previous investigation by the authors  was imprThe rest of this paper can be summarized as it follows. A schematic of the rocket engine thrust chamber is reported in In this paper, plasticity was modelled by the von Mises yield criterion, Prandtl-Reuss flow rule, and both isotropic and non-linear Chaboche kinematic hardening laws. The combined time hardening creep model was selected to simulate primary and secondary creep effects . A cumulA one-way thermal-structural coupling was employed. Hence, the temperature field influences the strain/stress response, and not vice versa. Several papers from literature demonstrated that such an approximation provided accurate results ,27,28,29In this work a FEM-FEM submodelling approach was adopted but alternative schemes would be also possible, e.g., FEM-DBEM approaches ,31.The transient thermal behaviour of cooling channels was investigated by non linear FEM analyses, considering the dependence of material properties with temperature. More information about these aspects can be found in ,32.Inelastic behavior of the thrust chamber was modeled assuming a combined isotropic-kinematic hardening model; in particular, a multilinear isotropic hardening model and a nonlinear Chaboche equation were considered, whilst creep effect was modeled by a combined time hardening relationship; the corresponding parameters are summarized in Further details of the creep and plasticity hardening models adopted can be found in .f2N is the number of reversals to failure. Multiaxiality effects are also considered and a biaxiality ratio The Smith-Watson-Topper life equation always accounts for mean stress and is typically used for low cycle fatigue; it defines a damage parameter based on the product of the maximum stress of each cycle Because the maximum values of heat flux are expected in the throat region of the combustion chamber see , a localAs mentioned earlier, instead of assigning predefined boundary conditions on the cut surfaces of the throat area (as conducted in ), a sub-In general, sub-modelling approaches allow to restrict the mesh refinement to the zones where plastic strains are envisaged. In particular, FEM analyses on a global model with a coarse mesh and a local model with a fine mesh are sequentially conducted. The displacements on the interface between the global and local models, obtained by a FEM linear analysis of the global model, are transferred to the local nonlinear model as boundary conditions for each time step. In the current work, the number of cycles simulated in the global model were less than those simulated in the local model in order to save computation time, namely at a certain point the results of the global model were considered stabilized and identically applied to all the subsequent further simulated cycles on the local model. In addition, a sensitivity analysis on the required number of loading cycles to be simulated in the global model was conducted in order to minimize the computation time (see next Section).By considering the symmetry of structure, only a half-cooling channel was modeled  with relCuCrZr alloy, in the zone in contact with the hot gases and the coolant;a thin layer of electrodeposited oxygen-free high-thermal conductivity copper (OFHC Cu);a layer of electrodeposited nickel to afford adequate chamber stiffness.The combustion chamber was realized with three different materials, as shown in Pressures of the hot gases and of the cooling fluid were considered as uniform and equal to 5 and 12 MPa, respectively. The thermal and structural boundary conditions are shown in With regard to the purging and relaxation phases the heat transfer coefficients and bulk temperatures considered are summarized in The finite element model used for the thermal and structural analyses, chosen after conducting a grid convergence analysis in the previous work , is depian ignition transient phase with duration of 3 s, in which the activation of thermal loads occurs;a hot phase with duration of 100 s,a purging phase of 3 s duration, during which an injection of liquid oxygen is performed to eliminate any waste into the channels;a relaxation phase, lasting almost 4000 s, when only natural convection acts to recover the chamber temperature back to room temperature.Four sequential phases were considered to define each thermal–structural loading:Creep is activated in the ignition and hot phases where maximum temperature values are expected , with respect to the case where 10 global model loading cycles were simulated, resulted of only 1.1%. In such a way a 23% run time saving on the global model analyses was obtained.The main outcomes of the thermal–mechanical analyses carried out on the throat region are summarized here. With regard to ratcheting life prediction, the curve representing equivalent plastic strain versus number of cycles was extrapolated by means of a curve with the following expression:tion see b. As shation see ; in factncode DesignLife, which works in the post-processing phase, namely after the solution of the non-linear structural analyses, and processes the calculated stress and strain field adopting the SWT method. Then, an evaluation of the cumulative fatigue damage All the fatigue evaluations have been conducted using the commercial code  out see , by meanThe corresponding thrust chamber fatigue life Since the hysteresis curves for the following loading cycles tend to shrink, as highlighted in ncode Design Life theory guide [A very small non-proportional loading factor, equal to 0.002, was also estimated . This result is consistent with the results obtained in , where iry guide . On the This work presented the numerical modelling of the mechanical behavior of a liquid rocket engine thrust chamber through a global-local sub-modelling approach. The work represents an extension of a previous research activity by the authors. The sub-modelling approach was implemented so as to get an improvement on the accuracy of the stress-strain field evaluation in the critical positions, in turn allowing for a more accurate life prediction of the rocket engine.The thermomechanical load cycle was updated through the modelling of a relaxation phase after the purging-post cooling phase, thus simulating the slow cooling of the component when reaching the room temperature before the following ignition stage, thus correctly simulating repeated ground hot firing cycles. Further significant advances with respect to the previous work were obtained, from the more realistic boundary conditions computed with the sub-modelling approach, to a time step convergence study in the ignition and purging phases to better simulate all time instants with very high thermal gradients.The results demonstrated that the adoption of the predefined boundary conditions (no submodelling), as previously considered, slightly overestimated the chamber service life. The simulation of the relaxation phase allowed one to alleviate the thermal gradients and stresses, in turn having a beneficial effect on the fatigue life prediction. Low cycle fatigue analyses have demonstrated that multiaxiality effects are significant, whereas the loading can be assumed as proportional. Finally, both creep and ratcheting phenomena resulted to provide a negligible damage along the whole component life. Even though no experimental results are available (a campaign test is scheduled for the end of the year), the results illustrated in this work are consistent with those obtained with very similar geometries and boundary conditions ,23. FurtThe computation time requested to perform a thermostructural global-local analysis with 25 loading cycles was 16 h, using an Intel Xeon Gold processor  with 3 GHz and a RAM of 190 GB.


Precision spraying relies on the response of the spraying equipment to the features of the targeted canopy. PWM technology manages the flow rate using a set of electronically actuated solenoid valves to regulate flow rate at the nozzle level. Previous studies have found that PWM systems may deliver incorrect flow rates. The objective of the present study was to characterize the performance of a commercial blast sprayer modified with pulse-width-modulated nozzles under laboratory conditions, as a preliminary step before its further field validation. Four different duty cycles  and four different pressures  were combined to experimentally measure the flow rate of each nozzle. Results showed that the PWM nozzles mounted in the commercial blast sprayer, under static conditions, were capable of modulating flow rate according to the duty cycle. However, the reduction of flow rates for the tested duty cycles according to pressure was lower than the percentage expected. A good linear relation was found between the pressure registered by the control system feedback sensor and the pressure measured by a reference conventional manometer located after the pump. High-speed video recordings confirmed the accurate opening and closing of the nozzles according to the duty cycle; however, substantial pressure variations were found at nozzle level. Further research to establish the general suitability of PWM systems for regulating nozzle flow rates in blast sprayers without modifying the system pressure still remains to be addressed. It is generally assumed that the use of pesticides is necessary to ensure high crop yields providing enough food supply for people and high quality of food products . HoweverAdapting the spraying equipment to the canopy characteristics has been proposed, to reduce drift ,12. CompThe flow rate of spraying liquid at a given instant is determined by a general model that contains the desired spray volume, the calculation model and the decision model. Most existing spray volume models are based on the working area, the leaf wall height in relation to the tree height and planting row space, the leaf wall area according to the tree height and the tree row volume, assuming that the tree row is a cuboid canopy volume. Flow rate regulation can be achieved, for instance, by using PID-based pipeline adjustment and spray nozzle flow control with pulse width modulation of solenoid valves (PWM). PWM technology manages flow rates by varying the duty cycle  and usinIn order to assess pressure and droplet size uniformity in PWM technology, the authors in  carried In order to assess precision variable-rate spraying in greenhouses, the authors in  carried In this regard, the authors in  identifiThe objective of this paper is to characterize the performance of a commercial blast sprayer modified with pulse-width-modulated nozzles under laboratory conditions, testing the effects of duty cycles and pressure settings on flow rate and pressure at different circuit points. This experiment represents a preliminary step before the application of prescription maps featuring VRT actuation in vineyards and olive groves for sustainable spraying and efficient crop protection.A commercial air-blast trailed sprayer for olive orchards was evaluated under static conditions in a laboratory. Off-the-shelf hollow disc-cone nozzle bodies  were used with solenoid shut-off valves  for PWM control on each nozzle body, closing and opening each valve when the solenoid was energized at a 10 Hz frequency. The control system implemented in the sprayer was fed from two different power sources. On the one hand, a self-standing internal battery providing 12 V was used for computer-controlled components such as an onboard PC-104 computer, a data acquisition card , a 240 W voltage converter (12 VDC-24 VDC), a 14-inch touchscreen monitor that hosts the graphic user interface (GUI) and a GPS receiver . On the other hand, an external source was directly connected to the pulling tractor´s battery, providing 12 V and 30 A for powering the 16 solenoids of the sprayer. A pressure sensor  and a flow-rate sensor  were connected to the computer. The intelligent spraying system implemented in the commercial sprayer was designed to operate under two working modes: a manual mode to analyze the specific behavior of selected groups of nozzles and denominated sectors and an automatic mode to read a prescription map and apply the prescribed rates according to the sprayer position. Sectors 1 (right) and 2 (left) comprise the four nozzles of the central part of the arc, whereas sectors 3 (right) and 4 (left) include the two top and two bottom nozzles targeting the periphery of the canopies. The system measured the flow rate (L/min) in the main pipe before it was divided between the two sides (left and right), together with the pressure (kPa) at three specific points in the circuit . As the sprayer was symmetrically configured , only thq is the flow rate, k is the nozzle discharge coefficient and p is the pressure.According to the ANOVA analysis provided in According to The instantaneous pressure registered by the pressure sensor connected to the computer was compared to the pressure gauge value  read aftA simple regression model was built to correlate the sector 1 flow rate with the pressure estimates obtained from the two registering systems, i.e., the computer-connected electronic sensor and the pressure gauge. The best model and the linear model fitting are shown in p-value < 0.05). The regression equation is given in Equation (Based on Equation .(2)FlowThe instantaneous flow rate registered by an electronic flowmeter connected to the control computer was compared to the manually measured flow rates . A weak Based on the high-speed camera images of the nozzles at 50 percent DC, the durations of the duty cycles were accurately calculated by registering the initial and final time frames for the footage sections analyzed. In order to assess and understand the pressure variations at the nozzle location, the pressure measurements obtained by the three conventional manometers in Pulse-width-modulated solenoid-driven nozzles mounted in a commercial blast sprayer were capable of modulating the flow rate according to the duty cycle under static conditions, although several complexities arose in the laboratory experiments. As expected, the flow rates increased with system pressure and the extent of the DC from 25 percent to 100 percent, but this increment was lower than expected from theoretical estimations. Specifically, for 25 percent and 50 percent DC, the actual reduction in flow was 19 percent and 32 percent, respectively. In terms of monitoring the relevant parameters of the spraying system, the instantaneous measurement of pressure with a sensor connected to the main computer provided accurate registers, but the real-time measurements of flow rates with an in-line flowmeter gave unreliable results due to the severe oscillations in the flowmeter line induced by the pulsing nozzles. A better location and attenuation of the flow line measuring point would probably eliminate, or significantly reduce, the errors found in the real-time estimation of flow rates. In contrast, the nozzle actuation timing tracked by high-speed video recording was very precise, confirming the selected 10 Hz frequency and yielding time lapses very close to the required DC. An important pressure drop of 200 kPa was measured between the outlet of the pump (P1) and the beginning of the right nozzle arc (P3), which indicates the convenience of always distinguishing between system pressure and nozzle pressure for follow-on studies. This study showed the inaccuracies in flow-rate reduction according to the fixed duty cycle and the difficulties of measuring nozzle pressures at low DC, with the resulting consequences for stable flow rate regulation and droplet-size homogeneity. Overall, PWM-actuated nozzles offer an attractive pressure-flow control option for smart spraying, but there are still important technical challenges that need thorough analysis before the widespread adoption of this technology for orchards and specialty crops.


Maneuvering target imaging based on inverse synthetic aperture radar (ISAR) imaging has recently drawn significant attention. Among the many autofocusing technologies which are crucial in ISAR imaging, minimum-entropy-based autofocusing (MEA) is highly robust. However, traditional MEA is not suitable for terahertz (THz) ISAR imaging. For one thing, the iterative process in traditional MEA is too complicated to be utilized for THz-ISAR imaging with tremendous data. For another, THz wavelengths are very short and extremely sensitive to phase errors, so the compensation accuracy of the traditional MEA method can hardly meet the requirements of THz radar high-resolution imaging. Therefore, in this paper, the MEA algorithm based on the damped Newton method is proposed, which improves computational efficiency by approximating the first- and second-order partial derivatives of the image entropy function with respect to the phase errors, as well as by the fast Fourier transform (FFT). The search step size factor is introduced to ensure that the algorithm can converge along the declination direction of the entropy function and obtain the globally optimal ISAR image. The experimental results validated the efficiency of the proposed algorithm, which is promising in THz-ISAR imaging of maneuvering targets. Inverse synthetic aperture radar (ISAR) enables the image of noncooperative targets with high resolution without the restrictions of illumination and weather and has been widely applied in many military and civil fields, such as space surveillance, air control, missile defense, air defense, and so on ,2,3,4. UBecause ISAR imaging is mainly applied to image noncooperative moving targets , the prior information of the target cannot be obtained before imaging, so the image quality is mainly determined by the performance of the motion compensation of the radar echoes. The translational motion compensation is necessary for generating high-resolution THz-ISAR images. It is usually accomplished through two steps: range alignment and autofocusing. The accuracy requirement of range alignment is relative to the range resolution ,17, and Autofocusing methods can be generally divided into parametric and nonparametric methods . The parAnother type of nonparametric autofocusing algorithm takes the minimum entropy as global quality indices for an ISAR image and uses the phase error of each pulse as an unknown variable to perform an iterative search to improve the estimation precision of the phase errors caused by the translational motion, thus having better performances in imaging maneuvering targets . HoweverTaking the robustness, adaptability, and precision into consideration, damped-Newton-method-based MEA (DN-MEA) was proposed to meet the requirements of a large amount of data and high-resolution imaging of THz radar. The main contributions of this paper are as follows.(1)The proposed method did not need to model the trajectory of the target and had strong adaptability. The phase error of the target was estimated by minimizing the entropy of the ISAR image in each iteration.(2)Since the phase errors between pulses are independent of each other, the simplified Hessian matrix was used to improve the calculation efficiency. The variable step-size factor, introduced to avoid the entropy function falling into the local optimal solution, was decided by the golden section method , which e(3)A large number of experimental results based on the measured data of 0.32 THz radar verified the effectiveness and robustness of the proposed DN-MEA method.This paper is organized as follows: The equivalent diagram of ISAR translational motion is shown in We estimated the phase error caused by the target translational motion, and the effect of the target’s translational motion on the phase and ISAR image was investigated based on the geometry as illustrated in We applied the approximation in Equation (3): entropy  and enve entropy . The forlated as :(5)I∂EI′Because Combining Equations (11) and (12) with Equation (13), the itten as :(14)∂EI′The Hessian of Since the phase errors of the different pulses of ISAR are relatively independent, only the diagonal elements of the Hessian matrix were derived to simplify the calculation:The diagonal elements of the Hessian matrix Then, the iterative process of DN-MEA can be expressed ash method . In ordeIn this section, the performance of the proposed DN-MEA method was verified by using the measured data of a corner reflector and UAV. The imaging results were compared with those of the FP-MEA and N-MEA methods. Several SNR conditions were set to verify the robustness of the proposed algorithm.In the experiment, we chose a UAV and a corner reflector as the targets. During the radar observation, the corner reflector was led by the UAV to make irregular movements together; radar could track one of the targets in each experiment. The experimental scene is shown in c and The imaging THz radar system used in this paper was based on the frequency modulated continuous wave (FMCW) principle. The parameters of the THz radar system in the experiments are listed in To verify the reliability of the proposed DN-MEA algorithm, ISAR imaging of the corner reflector was carried out. Azimuth resolution and side lobe suppression were analyzed using azimuth profiles. The peak side lobe ratio (PSLR) is the measurement of the imaging radar system’s ability to identify a weak target from a nearby strong one. The integrated side lobe ratio (ISLR) characterizes the ability to detect weak targets in the neighborhood of bright targets. The PSLR and ISLR of the three methods are listed in In this section, we further tested the proposed algorithm using UAV data measured with THz radar. The optical image of the UAV is shown in Again, the FP-MEA algorithm and the N-MEA were used for comparison. The obtained UAV ISAR image is shown in Similarly, for the purpose of analyzing the azimuth resolution and side lobe suppression of the proposed algorithms, the azimuth profile was selected to compare the −3 dB width. For the convenience of illustration, the scattering point located at the lower left wing was selected as an example to intuitively analyze the focus performance with DN-MEA. In ISAR imaging, the influence of SNRs on imaging quality must be considered. An effective imaging algorithm under a low SNR is more meaningful for practical engineering applications. The SNR was defined after range alignment of the range profile, that is, the noise was added to Image contrast is similar to image entropy, which is widely used to estimate the focused quality of ISAR images. The image entropy is defined as Equation (8), and the image contrast is expressed as follows:The image entropy and contrast of the radar images shown in Taking the algorithm’s practicability robustness and accuracy into consideration, a terahertz autofocusing algorithm based on DN-MEA is proposed in this paper. Our method was quantitatively verified by a large number of experimental results based on the measured data of 0.32-THz radar.Future work can be considered in the following directions: (1) In this experiment, the phase noise of the target echo of the corner reflector as a reference signal was processed. Data-driven phase correction algorithms for terahertz radar systems are an attractive direction, and the proposed method can be considered for the application to correct nonlinear phase errors of terahertz radar systems. (2) In THz-ISAR imaging, the phase error caused by translational motion accounts for a large proportion, while the part of the phase error caused by rotational motion is only a small fraction. Consequently, in this study, only the compensation of the phase error caused by translational motion was considered. However, high-order phase errors caused by rotational motion may also affect the imaging quality, although it inevitably increases the complexity of the algorithm. Therefore, a joint approach of translational and rotational phase error corrections in the terahertz band is a considerable direction. (3) ISAR scaling enables the user to estimate the size of the target from the radar image. In this study, THz-ISAR images were scaled along range cells with a range resolution of In this paper, a minimum entropy autofocusing algorithm based on the damped Newton method was proposed to obtain well-focused and fast-converging ISAR images from a THz radar system with a large datum volume and high sampling rate. This method used the phase error of each pulse as an unknown variable to perform an iterative search. The search step size factor was introduced to ensure the stable decline of image entropy. It can be seen from the experimental results that a reasonable step-size parameter can make the ISAR image converge to a position close enough to the minimum entropy, so as to obtain a well-focused ISAR image. The variation curves of the image entropy functions of FP-MEA, the N-MEA, and DN-MEA with the number of iterations were analyzed for different SNR conditions. The results showed that the proposed method could still generate well-focused ISAR images, even when the SNR was as low as −10 dB, which verified the robustness of the method. Further research is planned to try to incorporate this method into other steps of THz-ISAR imaging.


The performance of millimeter wave (mmWave) line-of-sight multiple input multiple output (LOS MIMO) systems using hybrid arrays of planar subarrays was studied. We characterized the achievable maximum spatial multiplexing gain for such LOS MIMO systems by the measures of spectral efficiency and effective degree of freedom (EDoF). By proposing a joint plane-wave and spherical-wave-based general 3D channel model, we derived the optimal design parameters in the analog domain, i.e., the optimal subarray separation products, and analyzed their sensitivity on the system performance. We also gave analytical eigenvalue expressions of the equivalent LOS MIMO channel matrix, which are applicable to the case of a non-optimal design, as well as the upper and lower bounds of the EDoF for system performance evaluation. A piecewise uniform quantization codebook was further designed for quantizing phase shifter values in practical applications. The numerical and simulation results show that planar subarrays are superior to traditional arrays in terms of spectral efficiency and EDoF in Ricean fading channels because they are more robust to the change in the communication distance and the deviation from the optimal design. The use of hybrid arrays of planar subarrays effectively removes the limitation of mmWave LOS MIMO systems using traditional arrays, through which, the conventional Rayleigh distance criterion has to be satisfied to achieve the optimal performance. With the ever increasing demand for data traffic, network throughput and wireless devices, traditional microwave frequency bands have been unable to satisfy the requirements of a fast-growing system capacity and spectral efficiency . TherefoUnlike the traditional MIMO channels in dense scattering environments, mmWave channels are usually characterized as sparse scattering, and thus go against conventional spatial multiplexing ,9. SinceR should be equal to or less than the so-called Rayleigh distance, i.e., V the maximum number of antennas between the transceiver and In LOS channels, the reflective paths do not exist or their power can be ignored, which results in a higher probability of an insufficient rank in the MIMO channel matrix. However, a well-designed antenna array can still be used to obtain a high-rank channel matrix and higher spatial multiplexing gain in a pure LOS environment . ReferenAlthough LOS MIMO has been considered to be able to achieve spatial multiplexing, the conventional full digital array LOS MIMO technology is infeasible for use in aerial platforms as the antenna spacing would have to be adjusted according to the communication distance, which is ever-changing. The inflexible adjustment is likely to cause a serious performance loss of spatial multiplexing when the Rayleigh distance criterion cannot be satisfied. To reduce the optimal antenna spacing for achieving full spatial multiplexing, the investigation in  added a Considering the power consumption and system complexity, radio frequency (RF) analog beamformer/combiners are typically implemented using phase shifters. The phase shifters are controlled digitally, and a finite number of values is usually selected subject to the quantization bits. Various quantization codebook designs or phase shifter structures have been investigated in mmWave MIMO systems ,25,26. TIn this paper, we studied the performance of mmWave LOS MIMO systems employing hybrid arrays of planar subarrays in terms of the spectral efficiency and effective degree of freedom (EDoF), where the EDoF represents the achievable maximum system spatial multiplexing gain. We propose a joint plane-wave and spherical-wave-based general 3D channel model for the LOS MIMO channel, which allows for a non-parallel orientation of hybrid arrays to be employed at the transceiver. The performance in terms of the spectral efficiency and EDoF using hybrid arrays of planar subarrays was analyzed and compared with that of the traditional digital arrays for different deviation factors and Ricean fading channels. The numerical and simulation results show that using the proposed planar subarray structure can still achieve an almost optimal performance even though the parameter design deviates from the Rayleigh distance criterion in a relatively wide range. The main contributions can be summarized as follows.Based on the proposed 3D channel model, the optimal subarray separation products in the vertical and horizontal directions were derived for maximizing the spectral efficiency and EDoF, respectively, and an analysis of the sensitivity to the non-optimal design was performed by means of deviation factors.The theoretical expressions for the eigenvalues of an equivalent LOS MIMO channel matrix were derived as a function of deviation factors, in both cases of optimal and non-optimal designs. The upper and lower bounds of the EDoF are also given.The piecewise uniform quantization codebooks for the phase angles in the beamformer and combiner were designed for LOS MIMO systems, which enables the results to be applied in practical systems with quantized RF phase shifters. Analytical expressions for spectral efficiency using the designed codebooks were also derived. The numerical results demonstrate that the designed codebooks outperform the beamsteering codebook in  using thThe remainder of this paper is organized as follows. a; The following notations are used throughout this paper. Consider a point-to-point LOS MIMO communication system where the hybrid arrays with planar subarrays are used in the transceiver, respectively. As shown in channels ,28. n∈CMkth eigenvalue of matrix Assuming that the channel state information is perfectly known at the receiver and equal power transmission is used, the spectral efficiency of the system can be expressed as (2)SE=loThe MIMO system can achieve the optimal performance only when its channel is equivalent to multiple independent single input single output (SISO) subchannels. Therefore, we characterize the achievable spatial multiplexing gain of the system by maximizing the EDoF as ,30(4)EDN, a 3 dB increase in SNR leads to an approximate increase in U bits/s/Hz in spectral efficiency [From (2) and (4), we can see that the spectral efficiency and EDoF are not only determined by the eigenvalue ficiency . The worficiency  revealedK represents the ratio between the power of the two components. In this paper, we focused on the pure LOS channel in an MIMO system, which indicates that A Ricean channel matrix can be modeled as the sum of an LOS component and an NLOS component in ,32. Assushown in , when thd for simplicity. The transmit arrays are placed on the R represents the horizontal communication distance between the bottom of the transceiver arrays. As in [As illustrated in s. As in ,35, due tth transmitting antenna element and the rth receiving antenna element andnth transmit subarray and that in the mth receive subarray. In this paper, we took the antenna element located at the origin of the coordinate axis in the first subarray as the reference element. nth transmit subarray (to the mth receive subarray), respectively. Therefore, an element of the channel matrix itten as (8)lr,t=As a result, the channel matrix nth transmit subarray and the mth receive subarray are written asnth transmit subarray (the mth receive subarray) to be directed towards the direction represented by the angles , (13) and (14), the orthogonality requires thatSince Substituting (9) into (16), we can obtainM is smaller than N. In general, the optimal subarray separation products for planar subarrays can be given byThere are infinite solutions for In order to investigate the sensitivity of LOS MIMO systems with planar subarrays to the deviations from the optimal planar subarray design in (19), we introduced the deviation factors, defined as the ratio of the optimal subarray separation product to the actual subarray separation product,From (2) and (4), we can see that the system spectral efficiency and EDoF depend on the eigenvalues of nth transmit subarray (the mth receive subarray) satisfies (When the main beam direction of the Substituting (9) into (22), we can rewrite We find that the eigenvalues of Then, the eigenvalues can be found asIt is shown in (4) that the EDoF is determined by the distribution of eigenvalues of U independent SISO subchannels. In this case, When the subarray separations at the transceiver satisfy (19), i.e., When the separations between adjacent subarrays are zero, i.e., The continuous and complete phase angle information is usually assumed to be available at the transceiver for RF phase shifter configuration. However, the phase shifters for the analog beamformer/combiner are implemented by discrete phase shifts due to the constraints on the RF hardware in a practical system, and thus the analog beamforming/combining vectors can only take specific values selected from the given quantization codebooks, as they can be easily implemented at a low cost in practical applications, though the spectral efficiency may be lower than that without quantization.Most of the existing quantization codebooks are designed for traditional MIMO with rich scattering channels, and yet they are not applicable to LOS MIMO channels with few scatterers. According to the introduced channel model, we designed beamsteering codebooks In the following, we characterize the effect of quantization bits on the spectral efficiency. Without a loss of generality, we assume that the elevation and azimuth angles of transmitted and received signals are evenly distributed in For ease of illustration, we assume that the phase shifters for phase angles Their integral primitive functions are represented as K is also provided for comparison.cheme in , where 2In this section, we present the numerical and simulation results to evaluate the LOS MIMO system performance using hybrid arrays with planar subarrays at the transceiver. Unless stated otherwise, we considered hybrid arrays with K. It is shown from this figure that the EDoF becomes increasingly dependent on K. It is also interesting to note that the EDoF using planar subarrays is almost independent of K when In R for different carrier frequencies. It can be seen that the EDoF decreases with increasing R, but it falls more slowly using planar subarrays than traditional arrays. The EDoF of the former is always higher than that of the latter. These indicate that the use of planar subarrays not only reduces the sensitivity of EDoF to the change in R, but also achieves a higher EDoF under the same conditions compared to traditional arrays in LOS MIMO systems. We can also see that the system EDoF using planar subarrays is also less sensitive to the change in carrier frequency compared to using traditional arrays.m. Through a comprehensive analysis of the above two figures, it can be observed that the system spectral efficiency achieves the maximum value when Based on the introduced joint plane-wave and spherical-wave 3D channel model for hybrid arrays with planar subarrays, we investigated the spatial multiplexing performance of mmWave LOS MIMO systems and derived the optimal subarray separation products in the vertical and horizontal directions with respect to maximizing the spectral efficiency and EDoF. It is shown that the subarray separation products can be represented as a function of the communication distance, carrier wavelength, the number of subarrays and the angles of the array placement. Compared to traditional arrays, a planar subarray structure can not only achieve a higher EDoF but can also be more robust to the change in the communication distance and the NLOS components. Therefore, using the planar subarray structure can remove the limitation that the optimal performance is achieved only when the Rayleigh distance criterion is satisfied for traditional arrays. It is also found that the influence of the carrier frequency on the system EDoF in planar subarrays is lower than that in traditional arrays. With the designed quantization codebooks, it was found that, when the dimension of arrays is doubled, the number of quantization bits of each phase angle needs to be increased by one to maintain the performance. In future work, the considered system models can be extended to a multi-user case for more general applications by exploiting the user separation in the angular domain. How to further develop the joint optimal design approaches for analog–digital hybrid beamforming, e.g., exploiting the iterative method in  for mult


In recent times, previous studies have reported the manipulation of tools by rats and degus in controlled experimental settings. However, a previous study reported that only one out of eight experimentally naïve rats could manipulate a rake-shaped tool according to the position of a food reward without prior experience of obtaining the reward with the tool before the test. The present study aimed to improve the training of rats and investigate rodents’ ability to manipulate tools according to food position. Stricter criteria were employed when training the rats to promote the rats’ monitoring of their own tool manipulation. Additional training was introduced to give them the opportunity to learn that the reward moved closer to them by pulling an object connected to the reward. The present study showed that only one of eight rats could manipulate a tool according to the position of the reward without prior experience of obtaining the reward with the tool or perceiving that part of the tool came in contact with the reward, as the previous study showed. The change in training did not enhance the rats’ tool-manipulation ability according to the food position. These procedures should be conducted in a wider variety of animals to investigate whether the training in motion control can promote the subjects’ effective tool-use behavior. Macaca fuscata): Callithrix jacchus): Cacatua goffiniana) spontaneously manufactured a stick tool from a European larch and used it to rake food beyond its reach, but the other two cockatoos did not use tools to obtain the food  (Octodon degus)  ,b, 2021 n degus)  in contrn degus) . In thisn degus) . In contn degus) , reporten degus) . Thus, in degus) , particuThe test mentioned above, where the rake was placed at the center and the food reward placed on either the left or right side of the rake, followed the food-obtaining training. The present study aimed to improve the training techniques applied in A raking tool was used for the behavioral task for rats in the present study because the previous studies have reported that degus and rats could use rake-shaped tools ,b, 2021,SD = 6.93). During training and testing, rats were maintained at around 85% of their free feeding weight. However, all rats could gain approximately 10 g/month. The animal room was maintained under a 12-h light/dark cycle (light phase: 8:00–20:00). All training and testing sessions were conducted during the light phase. All procedures and treatments were approved by the Doshisha University Animal Experiment Committee (protocol number: A17051), and were conducted in accordance with guidelines established by the Doshisha University Ethics Review Committee.Eight experimentally naïve three-month-old male Brown-Norway rats  were individually housed in wire cages. On the last day of free feeding, the rats weighed an average of 273.38 g  of the experimental board was divided into the area to the left (Areas 1–10) and right (Areas 12–21) of the rake handle, with Area 11 at the center , 4. The For the rake-manipulation training, the daily success rates were calculated by dividing the number of trials in which each rat moved the rake laterally within the criterion range within 60 s  by the total number of trials .In the thread-pulling training, the average thread-pulling rates per session were calculated for the threads with and without a reward separately. The thread-pulling rates were calculated by dividing the number of trials in which each rat pulled the thread (with or without a reward) to the position in which the reward or knot entered in the box  by the total number of trials in each thread condition . A two-way analysis of variance (ANOVA) was performed with thread type and session as within-subject factors, followed by simple main effect analyses. In addition, the average thread-contacting rates per session were calculated for the threads with a reward and threads without a reward separately. The thread-contacting rates were calculated by dividing the number of trials in which the rat touched the rake with its paws or mouth within 60 s  by the total number of trials in thread condition . A two-way ANOVA was performed with thread type and session as within-subject factors followed by simple main effect analyses.The success rate was also calculated for each rat in the positional discrimination test by determining whether the rats manipulated the rake toward the reward (in the correct-direction) or not (in the incorrect-direction), and comparing the number of trials in which the rake was moved in either direction . The correct-direction rate was calculated by dividing the number of trials in which each rat manipulated the rake toward the reward  by those in which the rat manipulated the rake in either direction. The correct-direction trials included trials in which the rat manipulated the rake in the correct-direction but failed to obtain the reward. Using binomial tests, the number of correct- and incorrect-direction trials was compared for each rat. In the binomial tests, the null hypothesis was that the correct-direction rate was 50%. In addition, data analysis showed whether each rat manipulated the rake in the correct-direction from the beginning of the session in the test. The daily sessions  were divided into eight blocks to calculate the average correct-direction rate of rake manipulation, with each block consisting of five trials. Trials 31–35 in one rat (BN58) and Trials 26–40 in another (BN59) were excluded from this analysis because the individuals never pulled the rake in these trials.Ipsilateral trials were calculated for each rat to analyze the relationship between the position of the rats’ noses and the correct-direction rates in the positional discrimination test. The number of ipsilateral and contralateral trials was compared for each rat using two-tailed binomial tests.Results from the rake-pulling, rake-manipulation, and thread-pulling training are described in n. s., BN64: p < 0.01, binomial tests, The success rates in the positional discrimination test were low in all the rats  could manipulate the rake in the direction of the reward by chance. Only this rat may have had a behavioral tendency to manipulate the rake in the direction of the reward for some reason . It would not be possible that the other seven rats could not manipulate the rake in the correct-direction because, due to their low visual acuity, they could not identify the position of the reward presented on the experimental board . In the Sapajus libidinosus)  . In addiThe changes that the present study made to the experimental procedures used in https://osf.io/3x8tz/?view_only=f5c4b90614bd496e8ba6ddd3ed26207a.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: The animal study was reviewed and approved by Doshisha University Animal Experiment Committee.AN designed and performed the experiments, made the experimental apparatus, analyzed the data, wrote the manuscript, and prepared the figures.The author declares 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.


Some people experience post-traumatic growth (PTG), entailing positive changes such as a greater appreciation of life following traumatic events. We examined PTG in the context of the negative consequences of the COVID-19 pandemic, notably working from home and social distancing. We aimed to assess whether distinct sub-groups (profiles) of individuals experiencing PTG could be identified by how they appraised and coped with the COVID-19 pandemic.For this cross-sectional study, we used convenience sampling. In total, 951 participants from the general population completed an online questionnaire with items focusing on primary and secondary appraisal, positive reappraisal, rumination, and coping flexibility. For the latent profile analysis, we selected a sample of 392 individuals who had experienced moderate degrees of pandemic-related PTG, reporting at least two of the 10 positive changes in the PTG Inventory-Short Form.We identified two distinct profiles among people experiencing PTG. The first was characterised by low levels of primary appraisal and stressfulness and higher levels of secondary appraisal , increased coping flexibility and greater use of positive reappraisal. The second was characterised by higher levels of stressfulness and primary appraisal  and greater use of rumination.The two sub-groups evidently appraised and coped with the COVID-19 pandemic differently. Therefore, future research should account for these different profiles of people experiencing PTG. During or after traumatic events, individuals may experience not only negative psychological outcomes, such as depressive symptoms, but also positive changes relating to their personal strength, spiritual beliefs, interpersonal relationships, life priorities and goals and appreciation of life , 2004. TSeveral theories have attempted to explain the development of PTG. According to Previous studies investigated the characteristics proposed by One reason for findings of mostly small effect sizes and contrasting results may be that these associations were studied at the group level, whereas there may be individual differences in the predictors of PTG. For instance, it could be argued that for some individuals, the experience of PTG may be the result of ruminative thoughts, whereas for others, a greater perceived impact of the event on their lives could be more strongly associated with PTG. When the results are aggregated at the level of the entire sample, individual-level effects may average out, resulting in small effect sizes or mixed results.Therefore, rather than examining predictors of PTG at the overall group level, we used a different approach and examined whether there are distinct sub-groups (profiles) of individuals experiencing PTG. An individual-centered approach can be used to identify whether there are individual differences regarding predictors of PTG, thereby indicating that there are multiple pathways for experiencing PTG. We examined such individual PTG profiles in the context of the COVID-19 pandemic. Applying existing theory on PTG  and prevWith respect to the pandemic, recent research indicates that COVID-19 has had a major psychological impact on many people . Only a The only requirement for participation in the study was the ability to speak the Dutch language and living in the Netherlands; no other inclusion or exclusion criteria were used. Of the 1,133 participants who opened the online survey, 182 participants were excluded because they only clicked on the survey link, or they did not fill in the sections on demographic information or informed consent. In total, 951 individuals filled in the questionnaire at the baseline measurement at the beginning of the pandemic between 19 April 202 and 21 May 2020; of these participants, 684 completed the questionnaire, and 267 partially completed the questionnaire.To be able to study PTG and address the research questions, we selected individuals reporting positive changes, using the PTGI-SF. As no clear cutoff exists for the PTGI-SF, we decided to use a cutoff based on the number of changes participants reported. First, we defined a positive change by a score of 3 or higher on an individual item, which indicates the participant experienced the change at least to a moderate degree. Second, a cutoff with higher scores used as an indicator of PTG was based on reporting a change on at least two of the 10 items. We believe this is a relevant indicator of the presence of PTG, while at the same time keeping a sample size with sufficient power. This cutoff yields a sample size of at least 300 participants which is recommended for latent profile analysis . As we rvia convenience sampling, which may have induced bias affecting the generalisation of the results. At the beginning of the questionnaire, respondents had to give their consent for their responses to be used anonymously in the analysis.The study was ethically approved by the Medical Ethics Review Board of the University Medical Center Groningen . We used baseline measurements obtained from an ongoing longitudinal study on the psychological impact of the COVID-19 pandemic in areas such as well-being, coping strategies, PTG and mindfulness. This study was initiated during the first lockdown in the Netherlands that occurred between 19 April 2020 and 21 May 2020. Various researchers from the Department of Health Psychology at the UMCG invited the general public through Facebook and LinkedIn to participate in the online survey using the Qualtrics software. Followers within their networks could then share the invitations on their own pages. Thus, participants were recruited The following measurements, expressed in the Dutch language, were obtained.PTG was measured using a validated, abbreviated Dutch version of the PTG Inventory-Short Form PTGI-SF; . This inThe items of primary appraisal (perceived impact and stressfulness) and secondary appraisal were based on the SARS Appraisal Inventory SAI; . The EngA single item was used to measure secondary appraisal; the respondent was asked whether they believed that they were capable of coping with the consequences of the COVID-19 pandemic. Like perceived impact and stressfulness, this item was based on the SAI, which assesses an individual’s confidence in coping with the impact of SARS on multiple life domains. Respondents rated the item using a 5-point Likert scale ranging from 0 (not being capable of coping with the consequences) to 4 (being very capable of coping with the consequences of the COVID-19 pandemic).Positive reappraisal was measured with four items derived from the validated Cognitive Emotion Regulation Questionnaire CERQ; . For exaCoping flexibility was measured with the validated versatility scale of the coping flexibility questionnaire COFLEX; . This scWe included sex, age, marital status, education and living situation as socio-demographic characteristics in the study. Respondents could also indicate whether they had children and whether they have a chronic physical illness. Furthermore, they could indicate their employment situation. In case they indicated that they were engaged in wage labour, they could indicate their work situation .Respondents could indicate whether or not they believed that they belonged to the COVID-19 risk group. Furthermore, participants could indicate whether they ever perceived COVID-19 like symptoms (either tested or not) or not.Visual inspection of scatter plots of pairs of the included variables revealed no extreme outliers. Therefore, no respondents were omitted from the subsequent analyses. Additionally, the scatter plots revealed no clear profile structure in the data.Prior to the analysis, the variables were standardised to enable a comparison of the scores for the variables within and between the profiles. To investigate the characteristics of individuals experiencing PTG, we performed a latent profile analysis on the following variables: sex, age, belonging to the risk group, perceived impact, stressfulness, secondary appraisal, coping strategies  and coping flexibility. There were computation issues for the dichotomous variables sex and belonging to the risk group because most participants were female and did not belong to the risk group, resulting in unequal groups. Therefore, separate analyses were performed for each category to explore whether the profiles in each category were similar as they were for the whole group. Because similar results were found for each sex and for belonging (or not) to the risk group, we excluded these categorical variables in the analysis to make the computation and interpretation of the results easier.The analysis was performed using the ‘tidyLPA’ package in the RStudio software. As there is no consensus on a single fit index for determining the number of profiles, we used the recommendations of Subsequently, in the chosen final model, the smallest profile should be larger than 5% of the sample  and entrAdditionally, to test the robustness of the results, we repeated the analyses for a select sample with cutoff points for experiencing one or more positive changes and three or more positive changes to a moderate degree on the PTGI-SF. As no accepted cutoff point for PTG exists, we performed this sensitivity analysis to assess whether the results were in line with the main results and specifically whether profile means were similar.The sample comprised individuals who had experienced at least two positive changes to a moderate degree with reference to the PTGI-SF. Individuals who perceived positive changes had significantly higher scores on positive reappraisal than those who experienced less than two positive changes. Contrary, individuals experiencing at least two positive changes did not differ in terms of their ages, primary appraisals (perceived impact and stressfulness) and secondary appraisals, rumination and coping flexibility compared with those who experienced less than two positive changes to a moderate degree.r = 0.58) and moderately positive in relation to rumination (r = 0.32). Secondary appraisal was moderately negatively correlated with stressfulness (r = −0.42), whereas correlations with coping flexibility (r = 0.38) and reappraisal (r = 0.35) were positive. Finally, stressfulness was moderately positively correlated with rumination (r = 0.41), whereas PTG was moderately positively correlated to positive reappraisal (r = 0.43).The two-profile model also seemed appropriate on the basis of our interpretation of the profiles. The two profiles were reproduced in all of the other profile models. Notably, models containing more profiles included additional profiles that were less clearly identifiable than the two dominant profiles. For example, these models were characterised by scores close to the means for all variables or with minor differences compared with those for the two dominant profiles. Considering all of the criteria, the two-profile model appeared to be superior to the one-profile model and was selected as the final model, with, respectively, 238 individuals (60.7%) in profile 1 and 154 individuals in profile 2 (39.3%).Previous studies have overlooked the possibility that people reporting PTG after confrontation with stressful circumstances may differ from each other and show a different profile. Our findings in the context of the COVID-19 pandemic suggest that there are two distinct sub-groups (profiles) of individuals reporting PTG, which differ in terms of their appraisals and coping strategies and, to a lesser extent, age. The so-called resilient group (61% of the sample) perceived a relatively low impact of the pandemic and associated stress on their lives. They were confident in dealing with the COVID-19 pandemic, used more flexible and adaptive coping strategies  and belonged to older age groups than the stressed group. The so-called stressed group (39% of the sample) evidenced the opposite profile, perceiving a relatively high and stressful impact of the COVID-19 pandemic, feeling less confident in dealing with COVID-19 and being more likely to ruminate as a way of coping with stressful situations. They also belonged to younger age groups.Although the current study did not examine predictors/correlates of PTG, the identification of two distinct profiles within the group of individuals experiencing PTG suggests that there may be different pathways for experiencing PTG. The findings relating to these two groups may explain why previous studies found inconsistent or weak correlates of PTG at the group level. For example, a previous meta-analysis and recent studies indicated that stress predicted PTG inaccurately with a small effect size . Our resThe stressed group that we identified seems more in line with theory stating that PTG is a result of the individual’s struggle and a process of rumination in the aftermath of stressful circumstances . AccordiInterestingly, we also found a group reporting PTG that perceived the pandemic to have had a low impact on their lives. Members of this group felt confident, were flexible in their coping strategies and made little use of rumination (the resilient group). Even though PTG is widely theorised to occur when an impact or stress associated with an event is experienced, in practice, this may not always be the case. This finding is in line with those of previous studies, which have shown that PTG has been reported by people with and without experiencing a traumatic event and therefore not having necessarily experienced feelings of stress and the impact of the event . AnotherBecause of the cross-sectional design we could not be sure to what extent the appraisals and coping factors are apparent later in time. Given that our study was conducted at an early stage of the pandemic, longitudinal research is needed to determine whether the two groups continued to be discernible at later stages of the pandemic. Quantitative research could reveal to what extent the two profiles are differentially associated with levels of PTG over time and whether or not the two identified profiles were stable over time. Further research is needed to gain a better understanding of the differences between the two groups of people reporting PTG and to evaluate the theoretical assumptions underlying the interpretations for the groups. This could be done using a qualitative study design that includes interviews conducted with individuals belonging to either group.From a clinical perspective, more research entailing a person-centred approach is required to study the predictors of PTG. If the finding that individuals experience PTG for different reasons or because of different processes is validated, then interventions could be designed based on a person-centred approach aimed at increasing PTG and helping individuals to find meaning after experiencing a traumatic or stressful event.One strength of the study was the novel application of multiple variables within the widely used statistical approach to examine sub-groups of individuals reporting PTG. Furthermore, the variables considered in the study were strongly based on PTG theory. The results revealed one group that was in conformity with theory; in addition, a new pattern of characteristics of people experiencing PTG that has not yet been theorised was also identified. Moreover, the analysis had sufficient power as the sample, comprising more than 300 individuals, was the recommended size . HoweverAnother limitation related to external validity. The sample comprised predominantly well-educated women. Therefore, the results cannot simply be generalised to other populations. The underrepresentation of male participants and individuals of lower education status may be a result of using convenience sampling . EarlierPrevious studies have examined predictors of PTG, such as appraisals and coping strategies, at the group level. In the process, individual or sub-group effects were averaged out, leading to contradictory results. We found that individuals experiencing PTG differed in how they appraised and coped with the impact of the COVID-19 pandemic on their lives. This finding suggests that there are different pathways leading to the experience of PTG.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Medical Ethics Review Board of the University Medical Center Groningen. The patients/participants provided their written informed consent to participate in this study.DMB drafted the manuscript, carried out data collection and performed data analysis. ES helped carrying out data collection, provided conceptual guidance and helped to draft the manuscript. WP participated in data analysis and helped to draft the manuscript. MS provided conceptual guidance and helped to draft the manuscript. AR provided conceptual guidance and helped to draft the manuscript. All authors read and approved the final manuscript.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.