bluuebunny/crossref_metadata_2025 huggingface dataset:
Validity and Reliability of Smartphone App for Evaluating Postural Adjustments during Step Initiation
Authors: da Costa Moraes Anderson Antunes , Duarte Manuela Brito , Ferreira Eduardo Veloso , da Silva Almeida Gizele Cristina , da Rocha Santos Enzo Gabriel , Pinto Gustavo Henrique Lima , de Oliveira Paulo Rui , Amorim César Ferreira , Cabral André dos Santos , de Athayde Costa e Silva Anselmo , Souza Givago Silva , Callegari Bianca
Published: April 2022

The evaluation of anticipatory postural adjustments (APAs) requires high-cost and complex handling systems, only available at research laboratories. New alternative methods are being developed in this field, on the other hand, to solve this issue and allow applicability in clinic, sport and hospital environments. The objective of this study was to validate an app for mobile devices to measure the APAs during gait initiation by comparing the signals obtained from cell phones using the Momentum app with measurements made by a kinematic system. The center-of-mass accelerations of a total of 20 healthy subjects were measured by the above app, which read the inertial sensors of the smartphones, and by kinematics, with a reflective marker positioned on their lumbar spine. The subjects took a step forward after hearing a command from an experimenter. The variables of the anticipatory phase, prior to the heel-off and the step phase, were measured. In the anticipatory phase, the linear correlation of all variables measured by the two measurement techniques was significant and indicated a high correlation between the devices (APAonset: r = 0.95, p < 0.0001; APAamp: r = 0.71, p = 0.003, and PEAKtime: r = 0.95, p < 0.0001). The linear correlation between the two measurement techniques for the step phase variables measured by ques was also significant (STEPinterval: r = 0.56, p = 0.008; STEPpeak1: r = 0.79, p < 0.0001; and STEPpeak2: r = 0.64, p < 0.0001). The Bland–Altman graphs indicated agreement between instruments with similar behavior as well as subjects within confidence limits and low dispersion. Thus, using the Momentum cell phone application is valid for the assessment of APAs during gait initiation compared to the gold standard instrument (kinematics), proving to be a useful, less complex, and less costly alternative for the assessment of healthy individuals.
Self-Supervised Object Distance Estimation Using a Monocular Camera
Authors: Liang Hong , Ma Zizhen , Zhang Qian
Published: April 2022

Distance estimation using a monocular camera is one of the most classic tasks for computer vision. Current monocular distance estimating methods need a lot of data collection or they produce imprecise results. In this paper, we propose a network for both object detection and distance estimation. A network-based on ShuffleNet and YOLO is used to detect an object, and a self-supervised learning network is used to estimate distance. We calibrated the camera, and the calibrated parameters were integrated into the overall network. We also analyzed the parameter variation of the camera pose. Further, a multi-scale resolution is applied to improve estimation accuracy by enriching the expression ability of depth information. We validated the results of object detection and distance estimation on the KITTI dataset and demonstrated that our approach is efficient and accurate. Finally, we construct a dataset and conduct similar experiments to verify the generality of the network in other scenarios. The results show that our proposed methods outperform alternative approaches on object-specific distance estimation.
Microbial Acoustical Analyzer for Antibiotic Indication
Authors: Zaitsev Boris , Borodina Irina , Alsowaidi Ali , Karavaeva Olga , Teplykh Andrey , Guliy Olga
Published: April 2022

In this study, a compact acoustic analyzer for express analysis of antibiotics based on a piezoelectric resonator with a lateral electric field and combined with a computer was developed. The possibility of determining chloramphenicol in aqueous solutions in the concentration range of 0.5–15 μg/mL was shown. Bacterial cells that are sensitive to this antibiotic were used as a sensory element. The change in the electrical impedance modulus of the resonator upon addition of the antibiotic to the cell suspension served as an analytical signal. The analysis time did not exceed 4 min. The correlation of the experimental results of an acoustic sensor with the results obtained using the light phase-contrast microscopy and standard microbiological analysis was established. The compact biological analyzer demonstrated stability, reproducibility, and repeatability of results.
End-to-End Lip-Reading Open Cloud-Based Speech Architecture
Authors: Jeon Sanghun , Kim Mun Sang
Published: April 2022

Deep learning technology has encouraged research on noise-robust automatic speech recognition (ASR). The combination of cloud computing technologies and artificial intelligence has significantly improved the performance of open cloud-based speech recognition application programming interfaces (OCSR APIs). Noise-robust ASRs for application in different environments are being developed. This study proposes noise-robust OCSR APIs based on an end-to-end lip-reading architecture for practical applications in various environments. Several OCSR APIs, including Google, Microsoft, Amazon, and Naver, were evaluated using the Google Voice Command Dataset v2 to obtain the optimum performance. Based on performance, the Microsoft API was integrated with Google’s trained word2vec model to enhance the keywords with more complete semantic information. The extracted word vector was integrated with the proposed lip-reading architecture for audio-visual speech recognition. Three forms of convolutional neural networks (3D CNN, 3D dense connection CNN, and multilayer 3D CNN) were used in the proposed lip-reading architecture. Vectors extracted from API and vision were classified after concatenation. The proposed architecture enhanced the OCSR API average accuracy rate by 14.42% using standard ASR evaluation measures along with the signal-to-noise ratio. The proposed model exhibits improved performance in various noise settings, increasing the dependability of OCSR APIs for practical applications.
Clustering at the Disposal of Industry 4.0: Automatic Extraction of Plant Behaviors
Authors: Molinié Dylan , Madani Kurosh , Amarger Véronique
Published: April 2022

For two centuries, the industrial sector has never stopped evolving. Since the dawn of the Fourth Industrial Revolution, commonly known as Industry 4.0, deep and accurate understandings of systems have become essential for real-time monitoring, prediction, and maintenance. In this paper, we propose a machine learning and data-driven methodology, based on data mining and clustering, for automatic identification and characterization of the different ways unknown systems can behave. It relies on the statistical property that a regular demeanor should be represented by many data with very close features; therefore, the most compact groups should be the regular behaviors. Based on the clusters, on the quantification of their intrinsic properties (size, span, density, neighborhood) and on the dynamic comparisons among each other, this methodology gave us some insight into the system’s demeanor, which can be valuable for the next steps of modeling and prediction stages. Applied to real Industry 4.0 data, this approach allowed us to extract some typical, real behaviors of the plant, while assuming no previous knowledge about the data. This methodology seems very promising, even though it is still in its infancy and that additional works will further develop it.
Surface Recombination and Space-Charge-Limited Photocurrent-Voltage (PC-V) Measurements in (Cd,Mn)Te Samples–Kinetics of Photocurrent (PC)
Authors: Mycielski Andrzej , Kochanowska Dominika M. , Wardak Aneta , Gościński Krzysztof , Szot Michał , Dobrowolski Witold , Janusz Gabriela , Górska Małgorzata , Janiak Łukasz , Czarnacki Wiesław , Świderski Łukasz , Iwanowska-Hanke Joanna , Moszyński Marek
Published: April 2022

Photocurrent-voltage characteristic (PC-V) is a method of determining the critical parameter in X-ray and gamma-ray detector plates, i.e., the carrier mobility-lifetime product, μτ. We show for the (Cd,Mn)Te samples that the measurement results depend strongly on the surface treatment and the space charge distribution. The PC-V characteristics obtained for ħω > Eg and ħω ~ Eg indicated that etching with 20% HCl caused an appearance of a significant concentration of very shallow surface traps at the (Cd,Mn)Te sample surface. These traps seriously changed the results of measurements of PC-V characteristics and PC kinetics. We also noticed a small contribution of holes to photoconductivity in the PC kinetics. The measurements of PC-V characteristics for ħω > Eg may test the detector plate surface quality.
New Frontier in Advanced Dentistry: CBCT, Intraoral Scanner, Sensors, and Artificial Intelligence in Dentistry
Authors: Kim Seong-Hun , Kim Ki Beom , Choo HyeRan
Published: April 2022

The advancement of science and technology has brought innovation in the dental field [...]
Green Synthesis of Phosphorescent Carbon Dots for Anticounterfeiting and Information Encryption
Authors: Cheng Mingming , Cao Lei , Guo Hanzhou , Dong Wenfei , Li Li
Published: April 2022

Room-temperature phosphorescent (RTP) carbon dots (CDs) have promising applications in bioimaging, anticounterfeiting, and information encryption owing to their long lifetimes and wide Stokes shifts. Numerous researchers are interested in developing highly bright RTP CDs using environmentally friendly and safe synthesis processes (e.g., natural raw materials and zero-pollution production pathways). In this study, we successfully synthesized RTP CDs using a hydrothermal process employing natural vitamins as a raw material, ethylenediamine as a passivator, and boric acid as a phosphorescent enhancer, which is referred to as phosphorescent CD (PCD). The PCDs exhibit both bright blue fluorescence emission and green RTP emission, with a phosphorescence lifetime as long as 293 ms and an excellent green afterglow visible to the naked eye for up to 7.0 s. The total quantum yield is 12.69%. The phosphorescence quantum yield (PQY) is up to 5.15%. Based on the RTP performance, PCDs have been successfully employed for anticounterfeiting and information protection applications. The results of this study provide a green strategy for the scalable synthesis of RTP materials, which is a practical method for the fabrication of RTP materials with high efficiency and long afterglow lifetimes.
SIW-Based Circularly Polarized Antenna Array for 60 GHz 5G Band: Feasibility Study
Authors: Spurek Jan , Raida Zbynek
Published: April 2022

At present, most millimeter wave 5G systems operate at frequencies ranging from 24 GHz to 39 GHz. Nevertheless, the new 5G release is going to increase the supported 5G spectrum into the 60 GHz band. In this communication, we discuss a methodology of converting a modular antenna array, which was originally designed for the 17 GHz unlicensed band, to the emerging 60 GHz 5G band. The antenna array is of a modular architecture, allowing a simple extension to a higher number of elements. The feeding structure is composed of substrate-integrated waveguides (SIW), allowing relatively simple and cheap manufacturing. As revealed by a sensitivity analysis, the frequency up-conversion significantly increases the need for precision of the used manufacturing technology. Subsequently, the structure is optimized to minimize the repercussions of manufacturing variations. The properties of the converted array are studied when equipped with parasitic patches to increase the axial ratio (AR) bandwidth.
Augmentation of Human Action Datasets with Suboptimal Warping and Representative Data Samples
Authors: Warchoł Dawid , Oszust Mariusz
Published: April 2022

The popularity of action recognition (AR) approaches and the need for improvement of their effectiveness require the generation of artificial samples addressing the nonlinearity of the time-space, scarcity of data points, or their variability. Therefore, in this paper, a novel approach to time series augmentation is proposed. The method improves the suboptimal warped time series generator algorithm (SPAWNER), introducing constraints based on identified AR-related problems with generated data points. Specifically, the proposed ARSPAWNER removes potential new time series that do not offer additional knowledge to the examples of a class or are created far from the occupied area. The constraints are based on statistics of time series of AR classes and their representative examples inferred with dynamic time warping barycentric averaging technique (DBA). The extensive experiments performed on eight AR datasets using three popular time series classifiers reveal the superiority of the introduced method over related approaches.
A Hidden Markov Ensemble Algorithm Design for Time Series Analysis
Authors: Lin Ting , Wang Miao , Yang Min , Yang Xu
Published: April 2022

With the exponential growth of data, solving classification or regression tasks by mining time series data has become a research hotspot. Commonly used methods include machine learning, artificial neural networks, and so on. However, these methods only extract the continuous or discrete features of sequences, which have the drawbacks of low information utilization, poor robustness, and computational complexity. To solve these problems, this paper innovatively uses Wasserstein distance instead of Kullback–Leibler divergence and uses it to construct an autoencoder to learn discrete features of time series. Then, a hidden Markov model is used to learn the continuous features of the sequence. Finally, stacking is used to ensemble the two models to obtain the final model. This paper experimentally verifies that the ensemble model has lower computational complexity and is close to state-of-the-art classification accuracy.
Monitoring of Serum Potassium and Calcium Levels in End-Stage Renal Disease Patients by ECG Depolarization Morphology Analysis
Authors: Bukhari Hassaan A. , Sánchez Carlos , Ruiz José Esteban , Potse Mark , Laguna Pablo , Pueyo Esther
Published: April 2022

Objective: Non-invasive estimation of serum potassium, [K+], and calcium, [Ca2+], can help to prevent life-threatening ventricular arrhythmias in patients with advanced renal disease, but current methods for estimation of electrolyte levels have limitations. We aimed to develop new markers based on the morphology of the QRS complex of the electrocardiogram (ECG). Methods: ECG recordings from 29 patients undergoing hemodialysis (HD) were processed. Mean warped QRS complexes were computed in two-minute windows at the start of an HD session, at the end of each HD hour and 48 h after it. We quantified QRS width, amplitude and the proposed QRS morphology-based markers that were computed by warping techniques. Reference [K+] and [Ca2+] were determined from blood samples acquired at the time points where the markers were estimated. Linear regression models were used to estimate electrolyte levels from the QRS markers individually and in combination with T wave morphology markers. Leave-one-out cross-validation was used to assess the performance of the estimators. Results: All markers, except for QRS width, strongly correlated with [K+] (median Pearson correlation coefficients, r, ranging from 0.81 to 0.87) and with [Ca2+] (r ranging from 0.61 to 0.76). QRS morphology markers showed very low sensitivity to heart rate (HR). Actual and estimated serum electrolyte levels differed, on average, by less than 0.035 mM (relative error of 0.018) for [K+] and 0.010 mM (relative error of 0.004) for [Ca2+] when patient-specific multivariable estimators combining QRS and T wave markers were used. Conclusion: QRS morphological markers allow non-invasive estimation of [K+] and [Ca2+] with low sensitivity to HR. The estimation performance is improved when multivariable models, including T wave markers, are considered. Significance: Markers based on the QRS complex of the ECG could contribute to non-invasive monitoring of serum electrolyte levels and arrhythmia risk prediction in patients with renal disease.
Wireless Power Transfer in Wirelessly Powered Sensor Networks: A Review of Recent Progress
Authors: Huda S. M. Asiful , Arafat Muhammad Yeasir , Moh Sangman
Published: April 2022

With the emergence of the Internet of Things (IoT), billions of wireless devices, including sensors and wearable devices, are evolving under the IoT technology. The limited battery life of the sensor nodes remains a crucial implementation challenge to enable such a revolution, primarily because traditional battery replacement requires enormous human effort. Wirelessly powered sensor networks (WPSNs), which would eliminate the need for regular battery replacement and improve the overall lifetime of sensor nodes, are the most promising solution to efficiently address the limited battery life of the sensor nodes. In this study, an in-depth survey is conducted on the wireless power transfer (WPT) techniques through which sensor devices can harvest energy to avoid frequent node failures. Following a general overview of WPSNs, three wireless power transfer models are demonstrated, and their respective enabling techniques are discussed in light of the existing literature. Moreover, the existing WPT techniques are comprehensively reviewed in terms of critical design parameters and performance factors. Subsequently, crucial key performance-enhancing techniques for WPT in WPSNs are discussed. Finally, several challenges and future directions are presented for motivating further research on WPSNs.
Comparison of Motion Analysis Systems in Tracking Upper Body Movement of Myoelectric Bypass Prosthesis Users
Authors: Wang Sophie L. , Civillico Gene , Niswander Wesley , Kontson Kimberly L.
Published: April 2022

Current literature lacks a comparative analysis of different motion capture systems for tracking upper limb (UL) movement as individuals perform standard tasks. To better understand the performance of various motion capture systems in quantifying UL movement in the prosthesis user population, this study compares joint angles derived from three systems that vary in cost and motion capture mechanisms: a marker-based system (Vicon), an inertial measurement unit system (Xsens), and a markerless system (Kinect). Ten healthy participants (5F/5M; 29.6 ± 7.1 years) were trained with a TouchBionic i-Limb Ultra myoelectric terminal device mounted on a bypass prosthetic device. Participants were simultaneously recorded with all systems as they performed standardized tasks. Root mean square error and bias values for degrees of freedom in the right elbow, shoulder, neck, and torso were calculated. The IMU system yielded more accurate kinematics for shoulder, neck, and torso angles while the markerless system performed better for the elbow angles. By evaluating the ability of each system to capture kinematic changes of simulated upper limb prosthesis users during a variety of standardized tasks, this study provides insight into the advantages and limitations of using different motion capture technologies for upper limb functional assessment.
Movement Quality Parameters during Gait Assessed by a Single Accelerometer in Subjects with Osteoarthritis and Following Total Joint Arthroplasty
Authors: Emmerzaal Jill , Corten Kristoff , van der Straaten Rob , De Baets Liesbet , Van Rossom Sam , Timmermans Annick , Jonkers Ilse , Vanwanseele Benedicte
Published: April 2022

This study’s aim is threefold: (I) Evaluate movement quality parameters of gait in people with hip or knee osteoarthritis (OA) compared to asymptomatic controls from a single trunk-worn 3D accelerometer. (II) Evaluate the sensitivity of these parameters to capture changes at 6-weeks, 3-, 6-, and 12-months following total knee arthroplasty (TKA). (III) Investigate whether observed changes in movement quality from 6-weeks and 12-months post-TKA relates to changes in patient-reported outcome measures (PROMs). We invited 20 asymptomatic controls, 20 people with hip OA, 18 people pre- and post-TKA to our movement lap. They wore a single trunk-worn accelerometer and walked at a self-selected speed. Movement quality parameters (symmetry, complexity, smoothness, and dynamic stability) were calculated from the 3D acceleration signal. Between groups and between timepoints comparisons were made, and changes in movement quality were correlated with PROMs. We found significant differences in symmetry and stability in both OA groups. Post-TKA, most parameters reflected an initial decrease in movement quality at 6-weeks post-TKA, which mostly normalised 6-months post-TKA. Finally, improved movement quality relates to improvements in PROMs. Thus, a single accelerometer can characterise movement quality in both OA groups and post-TKA. The correlation shows the potential to monitor movement quality in a clinical setting to inform objective, data-driven personalised rehabilitation.
Applications of Laser-Induced Fluorescence in Medicine
Authors: Kwaśny Mirosław , Bombalska Aneta
Published: April 2022

Fluorescence is the most sensitive spectroscopic method of analysis and fluorescence methods. However, classical analysis requires sampling. There are new needs for real-time analyses of biological materials, without the need for sampling. This article presents examples of proprietary applications of laser-induced fluorescence (LIF) in medicine with such methods. A classic example is the analysis of photosensitizers using the photodynamic treatment method (PDT). The level and kinetics of accumulation and excretion of sensitizers in the body are examined, as well as the optimal exposure time after the application of compounds. The LIF method is also used to analyze endogenous fluorophores; it has been used to detect neoplasms, e.g., lung cancer or gynecological and dermatological diseases. Furthermore, it is used for the diagnosis of early stages of tooth decay or detection of fungi. The article will present the construction of sensors based on the LIF method—fiber laser spectrometers and investigated fluorescence spectra in individual applications. Examples of fluorescence imaging, e.g., dermatological, and dental diagnostics and measuring systems will be presented. The advantage of the method is it has greater sensitivity and easily detects lesions early compared to the methods used in observing the material in reflected light.
iArm: Design an Educational Robotic Arm Kit for Inspiring Students’ Computational Thinking
Authors: Zeng Chengze , Zhou Hong , Ye Weiwei , Gu Xiaoqing
Published: April 2022

Educational robotics is an effective carrier of information technology education, making its way into classrooms. However, the design of the educational robotic arm kit and the study on the effect of robotic arms on students’ thinking literacy remain to be completed. In this paper, iArm, a 6-DOF robotic arm consisting of a drive chassis, an arm body, and end tools, is presented. Its auxiliary modules, including the vision module and conveyor belt, and the curriculum targeting students’ computational thinking are also developed to refine the current educational robotic arm kit. Furthermore, to explore the effectiveness of the iArm kit, thirteen high school students participated in the semester-long curriculum, completed assigned projects, and filled out the pre-test and post-test scales. By formative and summative evaluation, the result shows that the iArm kit effectively enhanced students’ computational thinking.
Health Habits and Wearable Activity Tracker Devices: Analytical Cross-Sectional Study
Authors: Tricás-Vidal Héctor José , Lucha-López María Orosia , Hidalgo-García César , Vidal-Peracho María Concepción , Monti-Ballano Sofía , Tricás-Moreno José Miguel
Published: April 2022

Wearable activity trackers are electronic devices that facilitate self-monitoring of information related to health. The purpose of this study was to examine the use of tracker devices to record daily activity (calories) and its associations with gender, generation, BMI, and physical activity behavior of United States of America resident adults; a cross-sectional study in 892 subjects recruited to participate in an anonymous online survey was performed. Being female increased the odds of using a tracker device by 2.3 times. Having low cardiovascular disease mortality risk related to time spent sitting increased the odds for using a tracker device by 2.7 times, and having medium risk 1.9 times, with respect to having high risk. For every 1-point increase in BMI, the odds for using a tracker device increased by 5.2%. Conclusions: Subjects who had ever used any tracker device had a higher BMI. The use of tracker devices was related to lower cardiovascular disease mortality risk related to sitting time. The amount of physical activity and the time spent walking were not associated with the usage of tracker devices. It is possible that the user of tracker devices should be supported by professionals to implement deep change in health habits.
Machine-Learning-Based Noninvasive In Vivo Estimation of HbA1c Using Photoplethysmography Signals
Authors: Kwon Tae-Ho , Kim Ki-Doo
Published: April 2022

Glycated hemoglobin (HbA1c) is an important factor in monitoring diabetes. Since the glycated hemoglobin value reflects the average blood glucose level over 3 months, it is not affected by exercise or food intake immediately prior to measurement. Thus, it is used as the most basic measure of evaluating blood-glucose control over a certain period and predicting the occurrence of long-term complications due to diabetes. However, as the existing measurement methods are invasive, there is a burden on the measurement subject who has to endure increased blood gathering and exposure to the risk of secondary infections. To overcome this problem, we propose a machine-learning-based noninvasive estimation method in this study using photoplethysmography (PPG) signals. First, the development of the device used to acquire the PPG signals is described in detail. Thereafter, discriminative and effective features are extracted from the acquired PPG signals using the device, and a machine-learning algorithm is used to estimate the glycated hemoglobin value from the extracted features. Finally, the performance of the proposed method is evaluated by comparison with existing model-based methods.
Ultra-Wideband Narrow Wall Waveguide-to-Microstrip Transition Using Overlapped Patches
Authors: Zhou Ivan , Robert Jordi Romeu
Published: April 2022

An ultrawideband rectangular waveguide to microstrip line transition operating at the whole LMDS and Ka band is presented. The transition is based on exciting three overlapped transversal patches that radiate into the narrow wall of the waveguide, making the design feasible to be used in λg/2 spaced phased arrays. Both top-side and bottom-side versions were designed and compared to show their differences. They were validated by means of a manufactured back-to-back (B2B) configuration, with a measured fractional bandwidth of 21.2% (top-side) and 23% (bottom-side). The maximum single transition measured insertion losses were 0.67 dB (top-side) and 0.85 dB (bottom-side) in the whole band of operation.
Sensitivity Analysis of Sidelobes of the Lowest Order Cladding Mode of Long Period Fiber Gratings at Turn Around Point
Authors: Dey Tanoy Kumar , Tombelli Sara , Roy Arpan , Biswas Palas , Giannetti Ambra , Basumallick Nandini , Baldini Francesco , Bandyopadhyay Somnath , Trono Cosimo
Published: April 2022

A new methodology to enhance the sensitivity of a long period fiber grating sensor (LPFG) at the Turn Around Point (TAP) is here presented. The LPFG sensor has been fabricated by etching the fiber up to 20.4 µm, until the sidelobes of dispersed LP0,2 cladding mode appeared near TAP in aqueous medium. The dual peak sensitivity of the sidelobes was found to be 16,044 nm/SRIU (surrounding refractive index units) in the RI range from 1.333 to 1.3335.
Effects of Automation and Fatigue on Drivers from Various Age Groups
Authors: Arefnezhad Sadegh , Eichberger Arno , Koglbauer Ioana Victoria
Published: April 2022

This study explores how drivers are affected by automation when driving in rested and fatigued conditions. Eighty-nine drivers (45 females, 44 males) aged between 20 and 85 years attended driving experiments on separate days, once in a rested and once in a fatigued condition, in a counterbalanced order. The results show an overall effect of automation to significantly reduce drivers’ workload and effort. The automation had different effects, depending on the drivers’ conditions. Differences between the manual and automated mode were larger for the perceived time pressure and effort in the fatigued condition as compared to the rested condition. Frustration was higher during manual driving when fatigued, but also higher during automated driving when rested. Subjective fatigue and the percentage of eye closure (PERCLOS) were higher in the automated mode compared to manual driving mode. PERCLOS differences between the automated and manual mode were higher in the fatigued condition than in the rested condition. There was a significant interaction effect of age and automation on drivers’ PERCLOS. These results are important for the development of driver-centered automation because they show different benefits for drivers of different ages, depending on their condition (fatigued or rested).
XBeats: A Real-Time Electrocardiogram Monitoring and Analysis System
Authors: Badr Ahmed , Badawi Abeer , Rashwan Abdulmonem , Elgazzar Khalid
Published: April 2022

This work presents XBeats, a novel platform for real-time electrocardiogram monitoring and analysis that uses edge computing and machine learning for early anomaly detection. The platform encompasses a data acquisition ECG patch with 12 leads to collect heart signals, perform on-chip processing, and transmit the data to healthcare providers in real-time for further analysis. The ECG patch provides a dynamically configurable selection of the active ECG leads that could be transmitted to the backend monitoring system. The selection ranges from a single ECG lead to a complete 12-lead ECG testing configuration. XBeats implements a lightweight binary classifier for early anomaly detection to reduce the time to action should abnormal heart conditions occur. This initial detection phase is performed on the edge (i.e., the device paired with the patch) and alerts can be configured to notify designated healthcare providers. Further deep analysis can be performed on the full fidelity 12-lead data sent to the backend. A fully functional prototype of the XBeats has been implemented to demonstrate the feasibly and usability of the proposed system. Performance evaluation shows that XBeats can achieve up to 95.30% detection accuracy for abnormal conditions, while maintaining a high data acquisition rate of up to 441 samples per second. Moreover, the analytical results of the energy consumption profile show that the ECG patch provides up to 37 h of continuous 12-lead ECG streaming.
The Birthplace Effect in 14–18-Year-Old Athletes Participating in Competitive Individual and Team Sports
Authors: Maayan Zohar , Lidor Ronnie , Arnon Michal
Published: April 2022

The birthplace (the place where an athlete was born) effect (BPE) has been found to be one of the environmental variables associated with early talent development and the achievement of a high level of proficiency in sport. The purpose of the current study is twofold: (1) to calculate the BPE in 14–18-year-old athletes who participated in individual and team sports and (2) examine how coaches perceived this effect. The participants were 1397 athletes (390 females and 1007 males) who competed in 5 individual (gymnastics, judo, swimming, tennis, and track and field) and 5 team (basketball, soccer, team handball, volleyball, and water polo) sports, as well as 147 coaches who provided their preliminary thoughts about the BPE. Data analyses revealed that although the BPE was not found to be associated with cities of a similar size, it was observed that growing up in cities of small and medium sizes was more beneficial than growing up in towns or cities of other sizes. Most of the coaches believed that certain characteristics of the place or city where the athlete grew up (e.g., proximity to sport facilities) could contribute positively to the athlete’s development. We discuss how the BPE data can aid policymakers in developing a sport policy associated with early phases of talent development.
Improving Women’s Opportunities to Succeed in the Workplace: Addressing Workplace Policies in Support of Menstrual Health and Hygiene in Two Kenyan Factories
Authors: Fry Whitney , Njagi Joan W. , Houck Frances , Avni Michal , Krishna Aditi
Published: April 2022

Women globally experience challenges managing their periods, especially those living in environments that do not support adequate menstrual health and hygiene (MHH). For working women, these challenges may have critical implications for their health, well-being, and economic outcomes (e.g., earnings). As part of a larger initiative that sought to understand the relationship between MHH and women’s economic empowerment, a policy analysis was conducted in two workplaces in Kenya to identify policy changes that would better support menstruating employees’ MHH needs. Policy analysis findings were synthesized with relevant baseline research findings from the same study to generate policy recommendations for participating companies. Key findings revealed limitations in hiring and induction processes, employee classification, representation and voice, toilet access, sick leave, and supervisor codes of conduct, all of which affected menstruating employees. Recommendations included updating supervisor codes of conduct, increasing women’s representation in union committees, and strengthening employee induction processes. Priority areas for policy changes were shared with companies’ leadership, alongside technical assistance for implementation. Insight from two private-sector workplaces in Kenya offers guidance on how to identify relevant policy gaps and institutionalize policies and practices that promote adequate workplace MHH in pursuit of women’s economic empowerment and improved business outcomes.
A Theoretical Analysis of Managerial Growth in the Context of Organizational Change
Authors: Kolbergytė Aušra , Dromantaitė Aistė
Published: April 2022

In analyzing the theoretical literature on managerial growth in the context of organizational change, an absence of research has been observed, especially that which comprehensively analyzes growth prospects and opportunities at the micro (individual), meso (group), and macro (organizational) levels, which considers organizational, social, emotional, and spiritual aspects. Therefore, one of the outstanding problems of this research was to select the relevant scientific literature to synthesize the theory and create a conceptual theoretical model based on it. The aim of this paper is to explore the context and preconditions for managerial growth during an organizational change at different levels and aspects of organizations. Therefore, six theoretical approaches from the fields of management, psychology, and education were chosen (Hiatt, Kotter, Kübler-Ross, Goleman, Mezirow, and Marcia). Conclusions provide insights into the context, aims, and directions of managerial growth within organizational change. First, the context of organizational change is understood as an educational environment that creates incentives for managerial growth at the macro, meso, and micro levels and encompasses the development of personal and professional skills and the conscious evolution of inner perceptions related to work. Second, managerial growth in the context of organizational change is targeted toward three objectives at the organizational, group, and individual levels: productivity, connection, and self-realization. Third, managerial growth in the context of organizational change is directed toward three dimensions: (1) the strategic-operational dimension overlaps with the development of leadership skills to ensure successful change implementation in the organization; (2) the social-emotional dimension overlaps with the development of psychosocial skills, enabling coping with challenges through relationships and an emotionally supportive workplace environment; and (3) the perceptual-spiritual dimension overlaps with the development of personal maturity and professional motivation, disclosing authentic performance during organizational change. These findings become a framework for further research but also provide practical guidelines for managers, HR specialists, and organizational leaders.
Emotional and Social Engagement in the English Language Classroom for Higher Education Students in the COVID-19 Online Context
Authors: Mihai Mihaela , Albert Carmen N. , Mihai Valentin C. , Dumitras Diana E.
Published: April 2022

The COVID-19 pandemic has led to perspective shifts in the approach of English language classrooms in the online higher education context. The current empirical study aims to understand the behaviour of 394 university students enrolled in agricultural, veterinary, and overall life science programmes in one of the main Romanian universities while learning English as a Foreign Language (EFL) and English for Specific Purposes (ESP) in terms of their classroom engagement during the 2020–2021 academic year. Following the application of an online questionnaire, a principal component analysis (PCA) was undertaken to determine the factors that determine students’ engagement (predominantly emotional and social), while learning EFL and ESP in the online system during the COVID-19 pandemic. Furthermore, the PCA results were used to identify clusters of students expressing similar behaviours towards the English learning process. Two clusters were identified: Cluster 1 consisted of moderately engaged students, and Cluster 2 consisted of highly engaged students. The clusters differed by the anxiety students express during class, the perception of the online system, the level of involvement and enjoyment, as well as class environment and dynamics, with the second cluster being the only one revealing a difference between the face-to-face and online experience. This study on students’ behaviours, attitudes, and preferences places students in the centre of the process of foreign language teaching and learning, as their enjoyment and engagement lead to a less stressful environment, especially during challenging times, and ultimately to long-term language proficiency and sustainable educational development.
Feasibility of Bio-Coal Production from Hydrothermal Carbonization (HTC) Technology Using Food Waste in Malaysia
Authors: Singh Ajit , Gill Andrew , Lim David Lian Keong , Kasmaruddin Agustina , Miri Taghi , Chakrabarty Anita , Chai Hui Hui , Selvarajoo Anurita , Massawe Festo , Abakr Yousif Abdalla , Mateva Kumbirai Ivyne , Ng Wendy Pei Qin , Serifi Olga , Mackenzie Claudia , Mohamad Mardawani , Kang Hooi-Siang , Goh Pei Sean , Lim Jun Wei , Chan Yi Jing
Published: April 2022

The alarming rise of food waste all over the world due to population and economic growth must be tackled with better waste management and treatment methods. The current practice of landfilling has been scientifically proven to adversely impact environmental and societal health. A relatively new technology called hydrothermal carbonization (HTC) has the potential to solve this problem. It takes in high-moisture-content material, like food waste, and converts it into bio-coal with a heating value similar to normal coal. The present study explored the feasibility of HTC technology and bio-coal production in Malaysia. An in-depth study via desk research was conducted by implementing Porter’s five forces analysis to evaluate the feasibility of the bio-coal production project. A survey involving 215 respondents from different households that represent the average demography of Malaysia was also conducted to understand the behaviors and attitudes of different households towards food waste. The present study found that a typical Malaysian household disposes mostly of meal leftovers, with an average of 926 g of food waste per day. In addition, the 3 highest food categories that were disposed of were rice or noodles or pasta (13.0%), vegetables (12.2%) and curry and soup (10.1%). Meal leftovers such as curry and soup are high in moisture content, which is suitable for HTC. The survey on household waste provided adequate information to support the availability of a sufficient quantity of food waste in the country to sustain the raw material for the bio-coal project in Malaysia. Furthermore, a consumer survey involving seven industrial firms was conducted to determine the potential buyers of bio-coal. The responses from the industrial firms show that a bio-alternative for coal is important, and they are willing to transition to greener technologies. However, five out of seven firms stated that the main hurdle in adopting bio-coal is the high cost of production and incompatibility with existing industrial processes. Finally, interviews were conducted with key players in the industry to evaluate the adoptability of bio-coal into the wider market. The findings from the desk research and the primary research show that the outlook for bio-coal in the market is quite positive. In the long run, HTC is certainly profitable, but for immediate benefits, adequate government support and policy in favour of the use of HTC bio-coal in power plants are required.
Extractive Waste as a Resource: Quartz, Feldspars, and Rare Earth Elements from Gneiss Quarries of the Verbano-Cusio-Ossola Province (Piedmont, Northern Italy)
Authors: Cavallo Alessandro , Dino Giovanna Antonella
Published: April 2022

The growing demand for raw materials requires the optimization of extractive processes and innovative approaches, such as the recovery of quarrying and processing waste. Waste materials from gneiss (ranging from blocks up to residual sludge) used as dimension stone (Beola and Serizzo from Piedmont, northern Italy) were characterized for chemistry, mineralogy, and petrography: quartz and feldspars (plagioclase and K-feldspar) are the most abundant minerals, followed by micas (biotite and minor muscovite) and traces of chlorite and epidote (allanite). Quartz and feldspars could be reused in the industrial minerals sector, especially in the ceramics industry; depending on the purity requirements of the raw materials, some mica separation treatments may be required. The most critical issues relate to the small grain size and the relative abundance of mica in some commercial varieties. The presence of allanite opens new possibilities for the recovery of rare earth elements (REE, critical raw materials).
A Novel GIS-Based Modeling Approach for Evaluating Aquifer Susceptibility to Anthropogenic Contamination
Authors: Jenifer M. Annie , Jha Madan Kumar
Published: April 2022

Population growth, increasing urbanization and industrialization, mismanagement, and climate change are accountable for the rising depletion and pollution of groundwater worldwide. Consequently, water security, food security, and environmental security are in jeopardy, leading to a severe concern for the sustainable water supply on the Earth. The contamination of groundwater, a complex and hidden resource, is difficult to detect and treat. Therefore, it is essential to evaluate aquifer’s propensity for contamination to protect this precious resource. In this paper, a novel approach integrating the GWQI (Groundwater Quality Index), AVI (Aquifer Vulnerability Index), and geospatial modeling is proposed to explore aquifer susceptibility to contamination, applied to an unconfined aquifer. The Groundwater Quality Index (GWQI) was developed by the conventional method and the Analytic Hierarchy Process (AHP), whereas the Aquifer Vulnerability Index (AVI) was developed using a modified DRASTIC model. It was found that the spherical semi-variogram along with simple Kriging is suitable for interpolating concentrations of groundwater quality parameters. Geospatial modeling indicated that the AHP-based GWQI map is more accurate than the conventional method. The integration of the best GWQI and AVI resulted in an Aquifer Susceptibility Index (ASI) map, which revealed that >80% of the study area falls under ‘severe’ to ‘very severe’ susceptible zones, while about 20% of the area falls under ‘moderate’ or ‘minimum’ susceptible zones. The validation results confirmed that the developed ASI map is reliable. The ASI map can serve as a useful tool for planners and decision makers to devise sustainable aquifer management programs to protect vital groundwater resources from contamination and ensure a safe and reliable water supply under climate change.
Qualitative and Quantitative Characterization of Municipal Waste in Uncontrolled Dumpsites and Landfills Using Integrated Remote Sensing, Geological and Geophysical Data: A Case Study
Authors: Abou El-Magd Islam , Attwa Mohamed , El Bastawesy Mohammed , Gad Ahmed , Henaish Ahmed , Zamzam Sara
Published: April 2022

The conducted research offers an environmental assessment of municipal waste (MW) using remote sensing (RS), geological, and geophysical datasets. As a test site, the present study aims to characterize one of the largest uncontrolled dumpsites in Egypt. RS data analysis indicates that high temperature values are concentrated at the MW and landfill site allocations as a result of the decomposition process, leading to fire risks. Moreover, the geological and structural data draw attention to the structural-controlled old topography role on MW distributions. Consequently, the dumpsite MW has larger surface quantities near the downthrows of the mapped faults. For MW characterization, geophysical data are acquired to produce2D/3D resistivity models. Because MW has the ability to become soft clay, the municipal organic waste and landfill leachate resistivities are lower than that of municipal solid waste and sandy soils. The geophysical inversion results indicate that the maximum thickness of MW calibrating with the drilled borehole data is 60 m. Furthermore, the estimated MW dumpsite volume is about 42.32 MCM. Accordingly, the MW can be characterized in an accurate qualitative and quantitative manner. Our findings, therefore, help the efforts of uncontrolled dumpsite development and thus contribute to sustainability plans.
Vulnerability Assessment of Pacific Whiteleg Shrimp (Penaeus vannamei) Farms and Vendors in Davao, Philippines Using FishVool
Authors: Macusi Edison D. , Albarido Nitcel Aymie , Clapano Misael B. , Santos Mudjekeewis D.
Published: April 2022

The impacts of climate change on shrimp aquaculture can vary widely and can have environmental and socioeconomic consequences. This study assessed the vulnerability to climate change impacts of selected small-scale shrimp farms of Penaeus vannamei and shrimpfish market vendors in the Davao region, the Philippines, using a modified Fisheries Vulnerability Assessment Tool (FishVool). Shrimp farmers and vendors were interviewed using two separate semi-structured questionnaires. A total of thirty-nine (n = 39) shrimp farmers and forty-eight (n = 48) market vendors from various market areas within the region were interviewed. Data regarding exposure (E), sensitivity (S), and adaptive capacity (AC) were collected following the FishVool parameters with modifications. Results revealed that the overall climate change vulnerability of the shrimp farmers was medium (M), where both exposure and adaptive capacity were low (L) while sensitivity was medium (M). In addition, the shrimp market vulnerability of the various sites examined revealed medium (M) scores for markets in Pantukan, Mabini, Tagum, Maco, Lupon, Davao City, and Digos, and high (H) vulnerability scores for the markets in Panabo and Sta Cruz. Overall, the study provided a better understanding of shrimp farming in relation to climate change impacts and vulnerability and provided information for future shrimp farm management, marketing, and climate change adaptation in the region.