bluuebunny/crossref_metadata_2025 huggingface dataset:
Co-Channel Interference Suppression for LTE Passive Radar Based on Spatial Feature Cognition
Authors: Wang Haitao , Lyu Xiaoyong , Liao Kefei
Published: December 2021

Passive radars based on long-term evolution (LTE) signals suffer from sever interferences. The interferences are not only from the base station used as the illuminator of opportunity (BS-IoO), but also from the other co-channel base stations (CCBS) working at the same frequency with the BS-IoO. Because the reference signals of the co-channel interferences are difficult to obtain, cancellation performance degrades seriously when traditional interference suppression methods are applied in LTE-based passive radar. This paper proposes a cascaded cancellation method based on the spatial spectrum cognition of interference. It consists of several cancellation loops. In each loop, the spatial spectrum of strong interferences is first recognized by using the cyclostationary characteristic of LTE signal and the compressed sensing technique. A clean reference signal of each interference is then reconstructed according to the spatial spectrum previously obtained. With the reference signal, the interferences are cancelled. At the end of each loop, the energy of the interference residual is estimated. If the interference residual is still strong, then the cancellation loop continues; otherwise it terminates. The proposed method can get good cancellation performance with a small-sized antenna array. Theoretical and simulation results demonstrate the effectiveness of the proposed method.
Architecture-Level Optimization on Digital Silicon Photomultipliers for Medical Imaging
Authors: Bandi Franco , Ilisie Victor , Vornicu Ion , Carmona-Galán Ricardo , Benlloch José M. , Rodríguez-Vázquez Ángel
Published: December 2021

Silicon photomultipliers (SiPMs) are arrays of single-photon avalanche diodes (SPADs) connected in parallel. Analog silicon photomultipliers are built in custom technologies optimized for detection efficiency. Digital silicon photomultipliers are built in CMOS technology. Although CMOS SPADs are less sensitive, they can incorporate additional functionality at the sensor plane, which is required in some applications for an accurate detection in terms of energy, timestamp, and spatial location. This additional circuitry comprises active quenching and recharge circuits, pulse combining and counting logic, and a time-to-digital converter. This, together with the disconnection of defective SPADs, results in a reduction of the light-sensitive area. In addition, the pile-up of pulses, in space and in time, translates into additional efficiency losses that are inherent to digital SiPMs. The design of digital SiPMs must include some sort of optimization of the pixel architecture in order to maximize sensitivity. In this paper, we identify the most relevant variables that determine the influence of SPAD yield, fill factor loss, and spatial and temporal pile-up in the photon detection efficiency. An optimum of 8% is found for different pixel sizes. The potential benefits of molecular imaging of these optimized and small-sized pixels with independent timestamping capabilities are also analyzed.
Attention Autoencoder for Generative Latent Representational Learning in Anomaly Detection
Authors: Oluwasanmi Ariyo , Aftab Muhammad Umar , Baagyere Edward , Qin Zhiguang , Ahmad Muhammad , Mazzara Manuel
Published: December 2021

Today, accurate and automated abnormality diagnosis and identification have become of paramount importance as they are involved in many critical and life-saving scenarios. To accomplish such frontiers, we propose three artificial intelligence models through the application of deep learning algorithms to analyze and detect anomalies in human heartbeat signals. The three proposed models include an attention autoencoder that maps input data to a lower-dimensional latent representation with maximum feature retention, and a reconstruction decoder with minimum remodeling loss. The autoencoder has an embedded attention module at the bottleneck to learn the salient activations of the encoded distribution. Additionally, a variational autoencoder (VAE) and a long short-term memory (LSTM) network is designed to learn the Gaussian distribution of the generative reconstruction and time-series sequential data analysis. The three proposed models displayed outstanding ability to detect anomalies on the evaluated five thousand electrocardiogram (ECG5000) signals with 99% accuracy and 99.3% precision score in detecting healthy heartbeats from patients with severe congestive heart failure.
Optical Fiber Bundle-Based High-Speed and Precise Micro-Scanning for Image High-Resolution Reconstruction
Authors: Jiang Jiali , Zhou Xin , Liu Jiaying , Pan Likang , Pan Ziting , Zou Fan , Li Ziqiang , Li Feng , Ma Xiaoyu , Geng Chao , Zuo Jing , Li Xinyang
Published: December 2021

We propose an imaging method based on optical fiber bundle combined with micro-scanning technique for improving image quality without complex image reconstruction algorithms. In the proposed method, a piezoelectric-ceramic-chip is used as the micro-displacement driver of the optical fiber bundle, which has the advantages of small volume, fast response speed and high precision. The corresponding displacement of the optical fiber bundle can be generated by precise voltage controlling. An optical fiber bundle with core/cladding diameter 4/80 μm and hexagonal arrangement is used to scan the 1951 USAF target. The scanning step is 1 μm, which is equivalent to the diffraction limit resolution of the optical system. The corresponding information is recorded at high speed through photo-detectors and a high-resolution image is obtained by image stitching processing. The minimum distinguishable stripe width of the proposed imaging technique with piezoelectric-ceramic-chip driven micro-scanning is approximately 2.1 μm, which is 1 time higher than that of direct imaging with a CCD camera whose pixel size is close to the fiber core size. The experimental results indicate that the optical fiber bundle combined with piezoelectric-ceramic-chip driven micro-scanning is a high-speed and high-precision technique for high-resolution imaging.
A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls
Authors: Varone Giuseppe , Boulila Wadii , Lo Giudice Michele , Benjdira Bilel , Mammone Nadia , Ieracitano Cosimo , Dashtipour Kia , Neri Sabrina , Gasparini Sara , Morabito Francesco Carlo , Hussain Amir , Aguglia Umberto
Published: December 2021

Until now, clinicians are not able to evaluate the Psychogenic Non-Epileptic Seizures (PNES) from the rest-electroencephalography (EEG) readout. No EEG marker can help differentiate PNES cases from healthy subjects. In this paper, we have investigated the power spectrum density (PSD), in resting-state EEGs, to evaluate the abnormalities in PNES affected brains. Additionally, we have used functional connectivity tools, such as phase lag index (PLI), and graph-derived metrics to better observe the integration of distributed information of regular and synchronized multi-scale communication within and across inter-regional brain areas. We proved the utility of our method after enrolling a cohort study of 20 age- and gender-matched PNES and 19 healthy control (HC) subjects. In this work, three classification models, namely support vector machine (SVM), linear discriminant analysis (LDA), and Multilayer perceptron (MLP), have been employed to model the relationship between the functional connectivity features (rest-HC versus rest-PNES). The best performance for the discrimination of participants was obtained using the MLP classifier, reporting a precision of 85.73%, a recall of 86.57%, an F1-score of 78.98%, and, finally, an accuracy of 91.02%. In conclusion, our results hypothesized two main aspects. The first is an intrinsic organization of functional brain networks that reflects a dysfunctional level of integration across brain regions, which can provide new insights into the pathophysiological mechanisms of PNES. The second is that functional connectivity features and MLP could be a promising method to classify rest-EEG data of PNES form healthy controls subjects.
Shack-Hartmann Wavefront Sensing of Ultrashort Optical Vortices
Authors: Pandey Alok Kumar , Larrieu Tanguy , Dovillaire Guillaume , Kazamias Sophie , Guilbaud Olivier
Published: December 2021

Light beams carrying Orbital Angular Momentum (OAM), also known as optical vortices (OV), have led to fascinating new developments in fields ranging from quantum communication to novel light–matter interaction aspects. Even though several techniques have emerged to synthesize these structured-beams, their detection, in particular, single-shot amplitude, wavefront, and modal content characterization, remains a challenging task. Here, we report the single-shot amplitude, wavefront, and modal content characterization of ultrashort OV using a Shack-Hartmann wavefront sensor. These vortex beams are obtained using spiral phase plates (SPPs) that are frequently used for high-intensity applications. The reconstructed wavefronts display a helical structure compatible with the topological charge induced by the SPPs. We affirm the accuracy of the optical field reconstruction by the wavefront sensor through an excellent agreement between the numerically backpropagated and experimentally obtained intensity distribution at the waist. Consequently, through Laguerre–Gauss (LG) decomposition of the reconstructed fields, we reveal the radial and azimuthal mode composition of vortex beams under different conditions. The potential of our method is further illustrated by characterizing asymmetric Gaussian vortices carrying fractional average OAM, and a realtime topological charge measurement at a 10Hz repetition rate. These results can promote Shack-Hartmann wavefront sensing as a single-shot OV characterization tool.
Context-Aware Human Activity Recognition in Industrial Processes
Authors: Niemann Friedrich , Lüdtke Stefan , Bartelt Christian , ten Hompel Michael
Published: December 2021

The automatic, sensor-based assessment of human activities is highly relevant for production and logistics, to optimise the economics and ergonomics of these processes. One challenge for accurate activity recognition in these domains is the context-dependence of activities: Similar movements can correspond to different activities, depending on, e.g., the object handled or the location of the subject. In this paper, we propose to explicitly make use of such context information in an activity recognition model. Our first contribution is a publicly available, semantically annotated motion capturing dataset of subjects performing order picking and packaging activities, where context information is recorded explicitly. The second contribution is an activity recognition model that integrates movement data and context information. We empirically show that by using context information, activity recognition performance increases substantially. Additionally, we analyse which of the pieces of context information is most relevant for activity recognition. The insights provided by this paper can help others to design appropriate sensor set-ups in real warehouses for time management.
A Custom-Made Lower Limb Dynamometer for Assessing Ankle Joint Torque in Humans: Calibration and Measurement Procedures
Authors: Drăgoi Iulia Iovanca , Popescu Florina Georgeta , Petrița Teodor , Tatu Romulus Fabian , Bondor Cosmina Ioana , Tatu Carmen , Bowling Frank L. , Reeves Neil D. , Ionac Mihai
Published: December 2021

Custom-made dynamometry was shown to objectively analyze human muscle strength around the ankle joint with accuracy, easy portability and low costs. This paper describes the full method of calibration and measurement setup and the measurement procedure when capturing ankle torque for establishing reliability of a portable custom-built electronic dynamometer. After considering the load cell offset voltage, the pivotal position was determined, and calibration with loads followed. Linear regression was used for calculating the proportionality constant between torque and measured voltage. Digital means were used for data collection and processing. Four healthy consenting participants were enrolled in the study. Three consecutive maximum voluntary isometric contractions of five seconds each were registered for both feet during plantar flexion/dorsiflexion, and ankle torque was then calculated for three ankle inclinations. A calibration procedure resulted, comprising determination of the pivotal axis and pedal constant. Using the obtained data, a measurement procedure was proposed. Obtained contraction time graphs led to easier filtering of the results. When calculating the interclass correlation, the portable apparatus demonstrated to be reliable when measuring ankle torque. When a custom-made dynamometer was used for capturing ankle torque, accuracy of the method was assured by a rigorous calibration and measurement protocol elaboration.
Validity of the Wrist-Worn Polar Vantage V2 to Measure Heart Rate and Heart Rate Variability at Rest
Authors: Nuuttila Olli-Pekka , Korhonen Elisa , Laukkanen Jari , Kyröläinen Heikki
Published: December 2021

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11344 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (mean bias −0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (mean bias 0.20 ms, p < 0.001) and nocturnal recordings (mean bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.
Multi-Channel Bioimpedance System for Detecting Vascular Tone in Human Limbs: An Approach
Authors: Hammoud Ahmad , Tikhomirov Alexey , Myasishcheva Galina , Shaheen Zein , Volkov Alexander , Briko Andrey , Shchukin Sergey
Published: December 2021

Vascular tone plays a vital role in regulating blood pressure and coronary circulation, and it determines the peripheral vascular resistance. Vascular tone is dually regulated by the perivascular nerves and the cells in the inside lining of blood vessels (endothelial cells). Only a few methods for measuring vascular tone are available. Because of this, determining vascular tone in different arteries of the human body and monitoring tone changes is a vital challenge. This work presents an approach for determining vascular tone in human extremities based on multi-channel bioimpedance measurements. Detailed steps for processing the bioimpedance signals and extracting the main parameters from them have been presented. A graphical interface has been designed and implemented to display the vascular tone type in all channels with the phase of breathing during each cardiac cycle. This study is a key step towards understanding the way vascular tone changes in the extremities and how the nervous system regulates these changes. Future studies based on records of healthy and diseased people will contribute to increasing the possibility of early diagnosis of cardiovascular diseases.
Environmental Durability of an Optical Fiber Cable Intended for Distributed Strain Measurements in Concrete Structures
Authors: Alj Ismail , Quiertant Marc , Khadour Aghiad , Grando Quentin , Benzarti Karim
Published: December 2021

The present study investigates the environmental durability of a distributed optical fiber sensing (DOFS) cable on the market, commonly used for distributed strain measurements in reinforced concrete structures. An extensive experimental program was conducted on different types of specimens (including samples of bare DOFS cable and plain concrete specimens instrumented with this DOFS cable) that were exposed to accelerated and natural ageing (NA) conditions for different periods of up to 18 months. The instrumentation of both concrete specimens consisted of DOFS cables embedded at the center of the specimens and bonded at the concrete surface, as these two configurations are commonly deployed in the field. In these configurations, the alkalinity of the surrounding cement medium and the outdoor conditions are the main factors potentially affecting the characteristics of the DOFS component materials and the integrity of the various interfaces, and hence impacting the strain transfer process between the host structure and the core optical fiber (OF). Therefore, immersion in an alkaline solution at an elevated temperature or freeze/thaw (F/T) and immersion/drying (I/D) cycles were chosen as accelerated ageing conditions, depending on the considered configuration. Mechanical characterizations by tensile and pull-out tests were then carried out on the exposed specimens to assess the evolution of the mechanical properties of individual component materials as well as the evolution of bond properties at various interfaces (internal interfaces of the DOFS cable, and interface between the cable and the host structure) during ageing. Complementary physico-chemical characterizations were also performed to better understand the underlying degradation processes. The experimental results highlight that immersion in the alkaline solution induced a significant and rapid decrease in the bond properties at internal interfaces of the DOFS cable and at the cable/concrete interface (in the case of the embedded cable configuration), which was assigned to chemical degradation at the surface of the cable coating in contact with the solution (hydrolysis and thermal degradation of the EVA copolymer component). Meanwhile, F/T and I/D cycles showed more limited effects on the mechanical properties of the component materials and interfaces in the case of the bonded cable configuration. A comparison with the same specimens exposed to outdoor NA suggested that the chosen accelerated ageing conditions may not be totally representative of actual service conditions, but provided indications for improving the ageing protocols in future research. In the last part, an analysis of the distributed strain profiles collected during pull-out tests on instrumented concrete specimens clearly illustrated the consequences of ageing processes on the strain response of the DOFS cable.
A Wearable Head Mounted Display Bio-Signals Pad System for Emotion Recognition
Authors: Wan Chunting , Chen Dongyi , Huang Zhiqi , Luo Xi
Published: December 2021

Multimodal bio-signals acquisition based on wearable devices and using virtual reality (VR) as stimulus source are promising techniques in emotion recognition research field. Numerous studies have shown that emotional states can be better evoked through Immersive Virtual Environments (IVE). The main goal of this paper is to provide researchers with a system for emotion recognition in VR environments. In this paper, we present a wearable forehead bio-signals acquisition pad which is attached to Head-Mounted Displays (HMD), termed HMD Bio Pad. This system can simultaneously record emotion-related two-channel electroencephalography (EEG), one-channel electrodermal activity (EDA), photoplethysmograph (PPG) and skin temperature (SKT) signals. In addition, we develop a human-computer interaction (HCI) interface which researchers can carry out emotion recognition research using VR HMD as stimulus presentation device. To evaluate the performance of the proposed system, we conducted different experiments to validate the multimodal bio-signals quality, respectively. To validate EEG signal, we have assessed the performance in terms of EEG eyes-blink task and eyes-open and eyes-closed task. The EEG eyes-blink task indicates that the proposed system can achieve comparable EEG signal quality in comparison to the dedicated bio-signals measuring device. The eyes-open and eyes-closed task proves that the proposed system can efficiently record alpha rhythm. Then we used signal-to-noise ratio (SNR) and Skin Conductance Reaction (SCR) signal to validate the performance for EDA acquisition system. A filtered EDA signal, with a high mean SNR of 28.52 dB, is plotted on HCI interface. Moreover, the SCR signal related to stimulus response can be correctly extracted from EDA signal. The SKT acquisition system has been validated effectively by the temperature change experiment when subjects are in unpleasant emotion. The pulse rate (PR) estimated from PPG signal achieved the low mean average absolute error (AAE), which is 1.12 beats per minute (BPM) over 8 recordings. In summary, the proposed HMD Bio Pad offers a portable, comfortable and easy-to-wear device for recording bio-signals. The proposed system could contribute to emotion recognition research in VR environments.
Jamming Strategy Optimization through Dual Q-Learning Model against Adaptive Radar
Authors: Liu Hongdi , Zhang Hongtao , He Yuan , Sun Yong
Published: December 2021

Modern adaptive radars can switch work modes to perform various missions and simultaneously use pulse parameter agility in each mode to improve survivability, which leads to a multiplicative increase in the decision-making complexity and declining performance of the existing jamming methods. In this paper, a two-level jamming decision-making framework is developed, based on which a dual Q-learning (DQL) model is proposed to optimize the jamming strategy and a dynamic method for jamming effectiveness evaluation is designed to update the model. Specifically, the jamming procedure is modeled as a finite Markov decision process. On this basis, the high-dimensional jamming action space is disassembled into two low-dimensional subspaces containing jamming mode and pulse parameters respectively, then two specialized Q-learning models with interaction are built to obtain the optimal solution. Moreover, the jamming effectiveness is evaluated through indicator vector distance measuring to acquire the feedback for the DQL model, where indicators are dynamically weighted to adapt to the environment. The experiments demonstrate the advantage of the proposed method in learning radar joint strategy of mode switching and parameter agility, shown as improving the average jamming-to-signal radio (JSR) by 4.05% while reducing the convergence time by 34.94% compared with the normal Q-learning method.
Effect of Cone-Plate Clarifier Structure Parameters on Flocculation Efficiency
Authors: Zhang Yulong , Liu Peikun , Xiao Linjing , Chang Long , Yan Fangping , Jiang Lanyue
Published: December 2021

In this study, a coal mine water flocculation system was established. A series of flocculation tests were carried out at different structural parameters (cylinder height, cone-plate insertion depth and cone-plate spacing) to better investigate the effect of the cone-plate clarifier on coal mine water treatment performance. Sixteen sampling points were set up in the system for data monitoring to generate the required data. The cone-plate clarifier was divided into five zones for flocculation analysis. The increased cylinder height facilitated the flocculation of particles in the micro flocculation zone and the settling of particles in the settlement zone. The chemicals used are polyaluminum chloride (PACl), Fe3O4 and polyacrylamide (PAM), corresponding to doses of 60 mg/L, 40 mg/L and 6 mg/L, respectively. Insufficient insertion depth of the cone-plate will cause the small flocs that have not been fully flocculated to enter the exit pipe zone directly through the cone-plate, while too much insertion depth will cause the large floc in the settlement zone to re-enter the exit pipe zone. The flocculation effect of small flocs increased as the cone-plate spacing decreased, which is consistent with the shallow pool theory. When the cone plate spacing was too narrow, the amount of fluid was reduced and the increase in fluid velocity reduced the flocculation effect. Curve fitting was conducted for Suspended solids(SS) and turbidity removal efficiency under each structural parameter to derive the variation of SS and turbidity removal efficiency under different structural parameters. The regression models of SS and turbidity removal efficiency on the cylinder height, cone-plate insertion depth and cone-plate spacing were established based on the curve fitting results, and the regression models were verified to be well fitted based on the comparison of experimental results. Finally, the optimal values of SS and turbidity removal efficiency were found based on the regression model. The flow rate of the cone-plate clarifier is 0.6 m3/h. The SS removal efficiency reached 96.82% when the cylinder height was 708 mm, the cone-plate insertion depth was 367 mm and the cone-plate spacing was 26 mm. The turbidity removal efficiency reached 86.75% when the cylinder height was 709 mm, the cone-plate insertion depth was 369 mm and the cone-plate spacing was 26 mm.
Making a Building Smart with a Co-Created and Continuously Evolving Enjoyable Service Entity—Insights from a Collaborative Study
Authors: Nuutinen Maaria , Kaasinen Eija , Hyvärinen Jaana , Mölsä Airi , Siltanen Sanni
Published: December 2021

Buildings shape cities as those cities grow from and nurture people living and working within the built environment. Thus, the conceptualization of smart building should be brought closer to the smart city initiatives that particularly target ensuring and enhancing the sustainability and quality of urban life. In this paper, we propose that a smart building should be interlinked with a smart city surrounding it; it should provide good experiences to its various occupants and it should be in an ongoing state of evolving as an ecosystem, wherein different stakeholders can join to co-produce, co-provide and co-consume services. Smart buildings require a versatile set of smart services based on digital solutions, solutions in the built environment and human activities. We conducted a multiphase collaborative study on new service opportunities guided by a Design Thinking approach. The approach brought people, technology, and business perspectives together and resulted in key service opportunities that have the potential to make the buildings smart and provide enjoyable experience to the occupants who support their living and working activities in smart cities. This paper provides the resulting practical implications as well as proposes future avenues for research.
Involvement and Multi-Sectoral Collaboration: Applying Principles of Health Promotion during the Implementation of Local Policies and Measures—A Case Study
Authors: Lillefjell Monica , Maass Ruca Elisa Katrin
Published: December 2021

Five principles for health promotion (HP) stand out in various forms, providing guidance for HP measures and policy implementation: (1) a broad and positive health concept, (2) participation and involvement of key stakeholders, (3) build action and action competence by involving and empowering target groups, (4) a setting perspective, and (5) equity in health. The purpose of this study is to describe, and critically discuss, how the five HP principles can be applied to structure collaboration processes for implementing HP measures in local communities. A case study methodology was applied when investigating how the HP principles guided actions and focus-of-attention throughout the process of implementing a local community HP measure. Of special importance was the broad involvement of stakeholders and the anchoring of overarching, as well as specific, HP goals in the municipal strategic documents to ensure political commitment, ownership, and adequate resources. Direction on how to apply or achieve the HP principles should be further explored, described, and brought into systematic day-to-day work for a better society-development.
Mother–Child Relationships in U.S. Latinx Families in Middle Childhood: Opportunities and Challenges in the 21st Century
Authors: Updegraff Kimberly A. , Umaña-Taylor Adriana J. , Son Daye , Cahill Karina M.
Published: December 2021

The 21st century has brought unique opportunities and challenges for parents, and this is particularly true for Latinx families, whose children comprise more than one-fourth of the school-age population in the U.S. today. Taking an ecological and strengths-based approach, the current study examined the role of mothers’ cultural assets (familism values, family cohesion) and challenges (economic hardship, ethnic–race-based discrimination) on children’s educational adjustment in middle childhood, as well as the indirect role of mother–child warmth and conflict in these associations. The sample included 173 Latinx mothers and their middle childhood offspring (i.e., 5th graders and younger sisters/brothers in the 1st through 4th grade). Mothers participated in home visits and phone interviews and teachers provided ratings of children’s educational adjustment (academic and socioemotional competence, aggressive/oppositional behaviors). Findings revealed family cohesion was indirectly linked to children’s educational adjustment via mother–child warmth and conflict, particularly for younger siblings. Discussion focuses on the culturally based strengths of Latinx families and highlights potential implications for family-based prevention in middle childhood.
A Narrative Review for a Machine Learning Application in Sports: An Example Based on Injury Forecasting in Soccer
Authors: Rossi Alessio , Pappalardo Luca , Cintia Paolo
Published: December 2021

In the last decade, the number of studies about machine learning algorithms applied to sports, e.g., injury forecasting and athlete performance prediction, have rapidly increased. Due to the number of works and experiments already present in the state-of-the-art regarding machine-learning techniques in sport science, the aim of this narrative review is to provide a guideline describing a correct approach for training, validating, and testing machine learning models to predict events in sports science. The main contribution of this narrative review is to highlight any possible strengths and limitations during all the stages of model development, i.e., training, validation, testing, and interpretation, in order to limit possible errors that could induce misleading results. In particular, this paper shows an example about injury forecaster that provides a description of all the features that could be used to predict injuries, all the possible pre-processing approaches for time series analysis, how to correctly split the dataset to train and test the predictive models, and the importance to explain the decision-making approach of the white and black box models.
A Systemic View of Future Mobility Scenario Impacts on and Their Implications for City Organizational LCA: The Case of Autonomous Driving in Vienna
Authors: Cremer Alexander , Müller Katrin , Finkbeiner Matthias
Published: December 2021

Autonomous vehicles (AV) are expected to significantly reshape urban mobility. Whether advancements at vehicle level also translate into positive environmental outcomes at city level is still uncertain. We investigate under which conditions a city could enable low emission AV mobility and what challenges are to be expected along the way from an environmental point of view. We build upon our recent environmental performance study of Vienna and combine city organizational life cycle assessment (city-OLCA) with AV transport models from literature for three AV use cases: an own AV, a shared AV, and a shared AV ride service. Most cases lower Vienna’s passenger capacity (by up to 28%) and increase motorized road traffic by a maximum of 49% (own AVs). Traffic relief is observed for shared AVs (−40%) if accompanied by a conventional car ban. This case reduces transport related GHG emissions compared to both Vienna’s current baseline (−60%) and a future electrified transportation system (−4.2%). These transformations have also shifted emission responsibility to the public level. While Vienna’s total GHG emissions could be reduced by 12%, the city’s emission responsibility increases from 25% to 32%. Efficient mass transit, the electrification of the mobility sector and grid decarbonization are key to reducing transport emissions in Vienna. The direction of GHG emission development will be determined by the extent to which these conditions are promoted. AV mobility probably will not be a main contributor.
Prediction Power of Logistic Regression (LR) and Multi-Layer Perceptron (MLP) Models in Exploring Driving Forces of Urban Expansion to Be Sustainable in Estonia
Authors: Mozaffaree Pour Najmeh , Oja Tõnu
Published: December 2021

Estonia mainly experienced urban expansion after regaining independence in 1991. Employing the CORINE Land Cover dataset to analyze the dynamic changes in land use/land cover (LULC) in Estonia over 28 years revealed that urban land increased by 33.96% in Harju County and by 19.50% in Tartu County. Therefore, after three decades of LULC changes, the large number of shifts from agricultural and forest land to urban ones in an unplanned manner have become of great concern. To this end, understanding how LULC change contributes to urban expansion will provide helpful information for policy-making in LULC and help make better decisions for future transitions in urban expansion orientation and plan for more sustainable cities. Many different factors govern urban expansion; however, physical and proximity factors play a significant role in explaining the spatial complexity of this phenomenon in Estonia. In this research, it was claimed that urban expansion was affected by the 12 proximity driving forces. In this regard, we applied LR and MLP neural network models to investigate the prediction power of these models and find the influential factors driving urban expansion in two Estonian counties. Using LR determined that the independent variables “distance from main roads (X7)”, “distance from the core of main cities of Tallinn and Tartu land (X2)”, and “distance from water land (X11)” had a higher negative correlation with urban expansion in both counties. Indeed, this investigation requires thinking towards constructing a balance between urban expansion and its driving forces in the long term in the way of sustainability. Using the MLP model determined that the “distance from existing residential areas (X10)” in Harju County and the “distance from the core of Tartu (X2)” in Tartu County were the most influential driving forces. The LR model showed the prediction power of these variables to be 37% for Harju County and 45% for Tartu County. In comparison, the MLP model predicted nearly 80% of variability by independent variables for Harju County and approximately 50% for Tartu County, expressing the greater power of independent variables. Therefore, applying these two models helped us better understand the causative nature of urban expansion in Harju County and Tartu County in Estonia, which requires more spatial planning regulation to ensure sustainability.
Heavy Metal Contamination of Natural Foods Is a Serious Health Issue: A Review
Authors: Munir Naveed , Jahangeer Muhammad , Bouyahya Abdelhakim , El Omari Nasreddine , Ghchime Rokia , Balahbib Abdelaali , Aboulaghras Sara , Mahmood Zahed , Akram Muhammad , Ali Shah Syed Muhammad , Mikolaychik Ivan N. , Derkho Marina , Rebezov Maksim , Venkidasamy Baskar , Thiruvengadam Muthu , Shariati Mohammad Ali
Published: December 2021

Heavy metals play an important role in the homeostasis of living cells. However, these elements induce several adverse environmental effects and toxicities, and therefore seriously affect living cells and organisms. In recent years, some heavy metal pollutants have been reported to cause harmful effects on crop quality, and thus affect both food security and human health. For example, chromium, cadmium, copper, lead, and mercury were detected in natural foods. Evidence suggests that these elements are environmental contaminants in natural foods. Consequently, this review highlights the risks of heavy metal contamination of the soil and food crops, and their impact on human health. The data were retrieved from different databases such as Science Direct, PubMed, Google scholar, and the Directory of Open Access Journals. Results show that vegetable and fruit crops grown in polluted soil accumulate higher levels of heavy metals than crops grown in unpolluted soil. Moreover, heavy metals in water, air, and soil can reduce the benefits of eating fruits and vegetables. A healthy diet requires a rational consumption of foods. Physical, chemical, and biological processes have been developed to reduce heavy metal concentration and bioavailability to reduce heavy metal aggregation in the ecosystem. However, mechanisms by which these heavy metals exhibit their action on human health are not well elucidated. In addition, the positive and negative effects of heavy metals are not very well established, suggesting the need for further investigation.
Does Urbanization Increase the Risk of Emerging Infectious Diseases in China? A Spatial Econometric Analysis
Authors: Feng Xiuju , Liu Shutong , Wang Chuanrong , Sriboonjit Jittaporn , Liu Jianxu , Sriboonchitta Songsak
Published: December 2021

The current COVID-19 pandemic has inspired more and more discussion about the relationship between urbanization and emerging infectious diseases (EID). This paper aims to examine the spatial effect of urbanization on EID incidence, such as hepatitis, syphilis and gonorrhea in China. Taking into account geographical and economic factors, the estimation results of the Spatial Error Model (SEM) show that urbanization has increased the risks of EID transmission from 2003 to 2019 in China. The spatial effects of urbanization are slightly different due to different types of infectious diseases, with a larger effect on syphilis comparing with hepatitis and gonorrhea. The regional heterogeneity test shows that the impact of urbanization on EID in eastern China is stronger than that in the Midwest especially when considering spatial correlation. Policy implications that include health must be integrated into urban planning, attaching more importance to ecological construction, improving regional joint prevention and control mechanisms, and more attention being paid to vulnerable groups. Considering the frequent occurrence of COVID-19 among cities in China, we emphasize the importance of enhancing the coordinated anti-crisis capacity of urban clusters and highlight the leading role of central cities.
Feasibility Assessment of Hybrid Solar Photovoltaic-Biogas Generator Based Charging Station: A Case of Easy Bike and Auto Rickshaw Scenario in a Developing Nation
Authors: Podder Amit Kumer , Supti Sayma Afroza , Islam Sayemul , Malvoni Maria , Jayakumar Arunkumar , Deb Sanchari , Kumar Nallapaneni Manoj
Published: December 2021

The popularity of electric vehicles (EVs) is increasing day by day in the modern world. The charging of EVs from grid-connected charging stations causes a considerable power crisis in the grid. Integrating renewable energy resources (RESs) with conventional energy sources in the power grid is now considered feasible to reduce peak power demand and the inevitable emission effect. Hence, this paper presents an energy solution for EV charging with two RESs, namely, solar photovoltaic (PV) and biogas. HOMER software is utilized to analyze the potency and functionality of solar PV and biogas-based EV charging stations. The proposed system consists of a solar PV system, two biogas engine generators, and a bidirectional converter with battery storage. The variation of different costs, such as net present cost (NPC), initial cost, and cost of energy (COE) for different solar PV systems (3 kW, 4.5 kW, 6 kW, and 9 kW), are analyzed in HOMER software. The 4.5 kW solar PV system is finally selected as the NPC, initial cost, and COE are $93,530, $19,735, and $0.181, respectively, which is efficient. The system’s lifetime is 25 years, where an initial 12 years is required to overcome the system cost, and the remaining 13 years will provide financial benefits. The study also illustrates the effect of solar irradiance, biomass, and the change in the load of the energy management system. The techno–economic analysis shows that the proposed scheme can be an effective energy solution. The emission of greenhouse gases (GHGs), such as CO2, CO, SO2, and NOX, is reduced considerably compared to other existing techniques. The study is expected to be beneficial in renewables-based EV charging systems with techno–economic and environmental feasibility.
The Effect of Loneliness in Psychological and Behavioral Profile among High School Students in Spain
Authors: Martín-Rodríguez Alexandra , Tornero-Aguilera Jose Francisco , López-Pérez Pedro Javier , Clemente-Suárez Vicente Javier
Published: December 2021

Loneliness is a distressing feeling that can be a barrier to a student’s development and affect their mental health. This research aimed to analyse the effects of loneliness on psychological and behavioral factors among students aged 12–19 years in Spain. Loneliness, experiential avoidance, psychological inflexibility, physical activity, mobile phone use, and smoke habits were analysed in a sample of 110 men and 122 women assigned into two groups depending on their loneliness levels: higher loneliness group (HLG) and lower loneliness group (LLG). Results showed that experimental avoidance and psychological inflexibility were related with loneliness (r = 0.471; p = 0.000). Experiential avoidance and psychological inflexibility were higher in HLG than LLG. Regarding the use of mobile phones and smoking habits, LLG presented significantly higher values than HLG. Higher age correlated with lower loneliness values (r = −0.155; p = 0.017). The present research found how students with higher loneliness presented higher experiential avoidance and psychological inflexibility and lower age, use of mobile phone, and smoking habits. These findings reveal the importance of considering multiple social behaviours when examining adolescent mental health factors.
Assessment of Management Competencies According to Coherence with Managers’ Personalities
Authors: Birknerová Zuzana , Uher Ivan
Published: December 2021

The objective of our investigation was to verify a questionnaire’s suitability in identifying managerial competencies concerning managers’ personality characteristics. Methods: For the content validity of the questionnaire assessment of managerial competencies (AMC23), we investigated its coherence with the appraisal of the management style methodology, i.e., managerial grid (MG), with correlation analysis. The existence of statistically significant relationships between the assessment of managerial competencies and managers’ personality characteristics was determined using Pearson’s correlation coefficient concerning the BIG-5 model. Results: In total, 573 managers participated in this study. Our examination concludes that motivational competencies correlated positively with the compromise and cooperative style; performance competencies with the competitive and cooperative style; and social competencies with the cooperative, adaptive, and compromise style. Not least, target competencies positively correlated with the competitive and cooperative style. Further, neuroticism negatively correlated with social managerial competence, extraversion, and openness to experience, which positively correlated with motivational and target competence. Friendliness was positively associated with social competence, and diligentness positively correlated with motivational, performance, and target competence. Conclusion: We determined significant correlations between managerial competencies (AMC23) and managerial style (MG). Our findings might have implications for further investigation and the development of more comprehensive instruments to assess managerial competencies in connection with managers’ personalities. We point out the need for further research to verify, improve, and constitute a model that further elucidates and explains managerial competencies.
Sustainable Management of the Electrical-Energy–Water–Food Nexus Using Robust Optimization
Authors: Hassas Morteza Ahangari , Kalantari Navid Taghizadegan , Mohammadi-Ivatloo Behnam , Safari Amin
Published: December 2021

The significance of the security of electrical energy, water, and food resources in the future, which are inextricably connected, has led to increasing attention to this important issue in studies. This is an issue inattention to which can have irreparable consequences in the future. One of the sectors where electrical energy, water, and food are very closely associated is agriculture. Undoubtedly, the ability to properly manage electrical energy, hydropower, and food resources that have many uncertainties brings about the development of agriculture on the one hand and the optimal allocation of electrical energy, water, and land resources on the other. Thus, while reaching the highest economic profit, the greenhouse gas emissions reach the minimum possible value too. In this study, via robust optimization and by precisely considering the existing uncertainties, a model was developed for the optimal allocation of electrical energy, water, and land resources for a region in the north of China. In addition to acknowledging the close relationship between electrical energy, water, and food sources, the results show the method’s effectiveness for sustainable management in agriculture.
An Extension of the Exit Choice Model: Considering the Variance in the Perspectives of Evacuees When Interacting with the Spread of Fire
Authors: Shuaib Mohammed Mahmod
Published: December 2021

Understanding evacuees’ responses to dynamic environmental changes, during an emergency evacuation, is of great importance in determining which aspects are ideal and which aspects should be eliminated or corrected. Evacuees differ in their ability to continually plan escape routes and adapt the routes chosen when they become unsafe owing to moving sources of threat. This is because they have different views and perspectives. The perspectives of evacuees are stochastic and are characterized by a high degree of uncertainty and complexity. To reduce the complexity and control of uncertainty, a model is proposed that can test for variant stochastic representations of evacuees’ perspectives. Two extremely realistic perspectives—the most ideal and the least ideal—are proposed to reasonably limit the range of variance. The success of achieving optimal evacuation is tested when different tendencies towards extreme perspectives are adopted. It is concluded that data toward the most ideal perspectives are capable of demonstrating safer evacuation by reducing the number of simulated burnt agents. This study enables crowd managers and fire safety researchers to test guidance systems as well as configuration of buildings using different perspectives of evacuees.