bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Winter Wheat Yield Estimation Based on Near-Surface Hyperspectral and UAV Hyperspectral Remote Sensing Data
Authors: Feng Haikuan , Tao Huilin , Fan Yiguang , Liu Yang , Li Zhenhai , Yang Guijun , Zhao Chunjiang
Published: August 2022

Crop yields are important for food security and people’s living standards, and it is therefore very important to predict the yield in a timely manner. This study used different vegetation indices and red-edge parameters calculated based on the canopy reflectance obtained from near-surface hyperspectral data and UAV hyperspectral data and used the partial least squares regression (PLSR) and artificial neural network (ANN) methods to estimate the yield of winter wheat at different growth stages. Verification was performed based on these two types of hyperspectral remote sensing data and the yield was estimated using vegetation indices and a combination of vegetation indices and red-edge parameters as the modeling independent variables, respectively, using PLSR and ANN regression, respectively. The results showed that, for the same data source, the optimal vegetation index for estimating the yield was the same in all of the studied growth stages; however, the optimal red-edge parameters were different for different growth stages. Compared with using only the vegetation indices as the modeling factor to estimate yield, the combination of the vegetation indices and red-edge parameters obtained superior estimation results. Additionally, the accuracy of yield estimation was shown to be improved by using the PLSR and ANN methods, with the yield estimation model constructed using the PLSR method having a better prediction effect. Moreover, the yield prediction model obtained using the near-surface hyperspectral sensors had a higher fitting and accuracy than the model obtained using the UAV hyperspectral remote sensing data (the results were based on the specific growth stressors, N and water supply). This study shows that the use of a combination of vegetation indices and red-edge parameters achieved an improved yield estimation compared to the use of vegetation indices alone. In the future, the selection of suitable sensors and methods needs to be considered when constructing models to estimate crop yield.
Integration of Photogrammetric and Spectral Techniques for Advanced Drone-Based Bathymetry Retrieval Using a Deep Learning Approach
Authors: Alevizos Evangelos , Nicodemou Vassilis C. , Makris Alexandros , Oikonomidis Iason , Roussos Anastasios , Alexakis Dimitrios D.
Published: August 2022

Shallow bathymetry mapping using proximal sensing techniques is an active field of research that offers a new perspective in studying the seafloor. Drone-based imagery with centimeter resolution allows for bathymetry retrieval in unprecedented detail in areas with adequate water transparency. The majority of studies apply either spectral or photogrammetric techniques for deriving bathymetry from remotely sensed imagery. However, spectral methods require a certain amount of ground-truth depth data for model calibration, while photogrammetric methods cannot perform on texture-less seafloor types. The presented approach takes advantage of the interrelation of the two methods, in order to predict bathymetry in a more efficient way. Thus, we combine structure-from-motion (SfM) outputs along with band-ratios of radiometrically corrected drone images within a specially designed deep convolutional neural network (CNN) that outputs a reliable and robust bathymetry estimation. To achieve effective training of our deep learning system, we utilize interpolated uncrewed surface vehicle (USV) sonar measurements. We perform several predictions at three locations in the southern Mediterranean Sea, with varying seafloor types. Our results show low root-mean-square errors over all study areas (average RMSE ≅ 0.3 m), when the method was trained and tested on the same area each time. In addition, we obtain promising cross-validation performance across different study areas (average RMSE ≅ 0.9 m), which demonstrates the potential of our proposed approach in terms of generalization capabilities on unseen data. Furthermore, areas with mixed seafloor types are suitable for building a model that can be applied in similar locations where only drone data is available.
Coordinated Attitude Control of Spacecraft Formation Flying via Fixed-Time Estimators under a Directed Graph
Authors: Zhou Zhanjie , Wang Yan
Published: August 2022

This paper mainly studies the distributed fixed-time coordinated attitude tracking control problem of spacecraft formation with a dynamic leader spacecraft under directed communication topology. Follower spacecraft cannot communicate directly with the leader spacecraft; therefore, in order to enable them to obtain the target attitude information, a fixed-time state estimator that can be applied to directed graphs is designed. Based on the estimators, a distributed fixed-time attitude tracking control law is proposed. The settling time of the fixed-time algorithm is only related to the parameters of the control law and independent of the initial state; thus, the proposed control law can reduce the influence of the dynamic leader attitude on the spacecraft formation-coordinated attitude tracking control system. Moreover, external disturbances and spacecraft inertia uncertainty were also considered in the design of the control law. The stability of the system was verified by Lyapunov stability theory, and the effectiveness of the control law was verified by numerical simulation.
Smart Diagnostics: Combining Artificial Intelligence and In Vitro Diagnostics
Authors: McRae Michael P. , Rajsri Kritika S. , Alcorn Timothy M. , McDevitt John T.
Published: August 2022

We are beginning a new era of Smart Diagnostics—integrated biosensors powered by recent innovations in embedded electronics, cloud computing, and artificial intelligence (AI). Universal and AI-based in vitro diagnostics (IVDs) have the potential to exponentially improve healthcare decision making in the coming years. This perspective covers current trends and challenges in translating Smart Diagnostics. We identify essential elements of Smart Diagnostics platforms through the lens of a clinically validated platform for digitizing biology and its ability to learn disease signatures. This platform for biochemical analyses uses a compact instrument to perform multiclass and multiplex measurements using fully integrated microfluidic cartridges compatible with the point of care. Image analysis digitizes biology by transforming fluorescence signals into inputs for learning disease/health signatures. The result is an intuitive Score reported to the patients and/or providers. This AI-linked universal diagnostic system has been validated through a series of large clinical studies and used to identify signatures for early disease detection and disease severity in several applications, including cardiovascular diseases, COVID-19, and oral cancer. The utility of this Smart Diagnostics platform may extend to multiple cell-based oncology tests via cross-reactive biomarkers spanning oral, colorectal, lung, bladder, esophageal, and cervical cancers, and is well-positioned to improve patient care, management, and outcomes through deployment of this resilient and scalable technology. Lastly, we provide a future perspective on the direction and trajectory of Smart Diagnostics and the transformative effects they will have on health care.
A Simulation Study to Assess the Factors of Influence on Mean and Median Frequency of sEMG Signals during Muscle Fatigue
Authors: Corvini Giovanni , Conforto Silvia
Published: August 2022

Mean and Median frequency are typically used for detecting and monitoring muscle fatigue. These parameters are extracted from power spectral density whose estimate can be obtained by several techniques, each one characterized by advantages and disadvantages. Previous works studied how the implementation settings can influence the performance of these techniques; nevertheless, the estimation results have never been fully evaluated when the power density spectrum is in a low-frequency zone, as happens to the surface electromyography (sEMG) spectrum during muscle fatigue. The latter is therefore the objective of this study that has compared the Welch and the autoregressive parametric approaches on synthetic sEMG signals simulating severe muscle fatigue. Moreover, the sensitivity of both the approaches to the observation duration and to the level of noise has been analyzed. Results showed that the mean frequency greatly depends on the noise level, and that for Signal to Noise Ratio (SNR) less than 10dB the errors make the estimate unacceptable. On the other hand, the error in calculating the median frequency is always in the range 2–10 Hz, so this parameter should be preferred in the tracking of muscle fatigue. Results show that the autoregressive model always outperforms the Welch technique, and that the 3rd order continuously produced accurate and precise estimates; consequently, the latter should be used when analyzing severe fatiguing contraction.
Dual-Scale Doppler Attention for Human Identification
Authors: Yoon Sunjae , Kim Dahyun , Hong Ji Woo , Kim Junyeong , Yoo Chang D.
Published: August 2022

This paper considers a Deep Convolutional Neural Network (DCNN) with an attention mechanism referred to as Dual-Scale Doppler Attention (DSDA) for human identification given a micro-Doppler (MD) signature induced as input. The MD signature includes unique gait characteristics by different sized body parts moving, as arms and legs move rapidly, while the torso moves slowly. Each person is identified based on his/her unique gait characteristic in the MD signature. DSDA provides attention at different time-frequency resolutions to cater to different MD components composed of both fast-varying and steady. Through this, DSDA can capture the unique gait characteristic of each person used for human identification. We demonstrate the validity of DSDA on a recently published benchmark dataset, IDRad. The empirical results show that the proposed DSDA outperforms previous methods, using a qualitative analysis interpretability on MD signatures.
Experimental Verification of the Impact of Radial Internal Clearance on a Bearing’s Dynamics
Authors: Ambrożkiewicz Bartłomiej , Syta Arkadiusz , Georgiadis Anthimos , Gassner Alexander , Meier Nicolas
Published: August 2022

This paper focuses on the influence of radial internal clearance on the dynamics of a rolling-element bearing. In the beginning, the 2—Degree of Freedom (DOF) model was studied, in which the clearance was treated as a bifurcation parameter. The derived nonlinear mathematical model is based on Hertzian contact theory and takes into consideration shape errors of rolling surfaces and eccentricity reflecting real operating conditions. The analysis showed characteristic dynamical behavior by specific clearance range, which reflects others in a low or high amplitude and can refer to the optimal clearance. The experimental validation was conducted with the use of a double row self-aligning ball bearing (SABB) NTN 2309SK in which the acceleration response was measured by various rotational velocities. The time series obtained from the mathematical model and the experiment were analyzed with the recurrence quantification analysis.
Experimental Study on Performance Enhancement of a Photovoltaic Module Incorporated with CPU Heat Pipe—A 5E Analysis
Authors: Praveenkumar Seepana , Gulakhmadov Aminjon , Agyekum Ephraim Bonah , T. Alwan Naseer , Velkin Vladimir Ivanovich , Sharipov Parviz , Safaraliev Murodbek , Chen Xi
Published: August 2022

As is already known, solar photovoltaic (PV) technology is a widely accepted technology for power generation worldwide. However, it is scientifically proven that its power output decreases with an increase in the temperature of the PV module. Such an important issue is controlled by adopting a number of cooling mechanisms for the PV module. The present experimental study assesses the effect of a fanless CPU heat pipe on the performance of a PV module. The experiment was conducted in June in real weather conditions in Yekaterinburg, Russian Federation. The comparative analysis of two PV panels (i.e., cooled, and uncooled) based on the electrical energy, exergy performance, economic, embodied energy and energy payback (5E) for the two systems is presented and discussed. The key results from the study are that the average temperature reduction from the cooling process is 6.72 °C. The average power for the cooled panel is 11.39 W against 9.73 W for the uncooled PV panel; this represents an increase of 1.66 W for the cooled module. Moreover, the average improvements in the electrical efficiency, and embodied energy recorded for a cooled PV panel 2.98%, and 438.52 kWh, respectively. Furthermore, the calculations of the levelized cost of energy (LCE) for the cooled PV panel indicate that it can range from 0.277–0.964 USD/kWh, while that for the uncooled PV panel also ranges from 0.205–0.698 USD/kWh based on the number of days of operation of the plant.
A Human Gait Tracking System Using Dual Foot-Mounted IMU and Multiple 2D LiDARs
Authors: Duong Huu Toan , Suh Young Soo
Published: August 2022

This paper proposes a human gait tracking system using a dual foot-mounted IMU and multiple 2D LiDARs. The combining system aims to overcome the disadvantages of each single sensor system (the short tracking range of the single 2D LiDAR and the drift errors of the IMU system). The LiDARs act as anchors to mitigate the errors of an inertial navigation algorithm. In our system, two 2D LiDARs are used. LiDAR 1 is placed around the starting point, and LiDAR 2 is placed at the ending point (in straight walking) or at the turning point (in rectangular path walking). Using the LiDAR 1, we can estimate the initial headings and positions of each IMU without any calibration process. We also propose a method to calibrate two LiDARs that are placed far apart. Then, the measurement from two LiDARs can be combined in a Kalman filter and the smoother algorithm to correct the two estimated feet trajectories. If straight walking is detected, we update the current stride heading and the foot position using the previous stride headings. Then, it is used as a measurement update in the Kalman filter. In the smoother algorithm, a step width constraint is used as a measurement update. We evaluate the stride length estimation through a straight walking experiment along a corridor. The root mean square errors compared with an optical tracking system are less than 3 cm. The performance of proposed method is also verified with a rectangular path walking experiment.
Sentiment Analysis and Emotion Recognition from Speech Using Universal Speech Representations
Authors: Atmaja Bagus Tris , Sasou Akira
Published: August 2022

The study of understanding sentiment and emotion in speech is a challenging task in human multimodal language. However, in certain cases, such as telephone calls, only audio data can be obtained. In this study, we independently evaluated sentiment analysis and emotion recognition from speech using recent self-supervised learning models—specifically, universal speech representations with speaker-aware pre-training models. Three different sizes of universal models were evaluated for three sentiment tasks and an emotion task. The evaluation revealed that the best results were obtained with two classes of sentiment analysis, based on both weighted and unweighted accuracy scores (81% and 73%). This binary classification with unimodal acoustic analysis also performed competitively compared to previous methods which used multimodal fusion. The models failed to make accurate predictionsin an emotion recognition task and in sentiment analysis tasks with higher numbers of classes. The unbalanced property of the datasets may also have contributed to the performance degradations observed in the six-class emotion, three-class sentiment, and seven-class sentiment tasks.
A High-Accuracy Calibration Method for a Telecentric Structured Light System
Authors: Chen Chao , Kong Ya , Wang Huaiwen , Zhang Zonghua
Published: August 2022

We propose a method for accurately calibrating a telecentric structured light system consisting of a camera attached to a bilateral telecentric lens and a pin-hole projector. The proposed method can be split into two parts: axial calibration and transverse calibration. The first part is used for building the relationship between phase and depth by means of a planar plate with ring markers on its surface at several different positions in the measuring volume. The second part is used for establishing the relationship between transverse coordinates and pixel positions with the depth offered by a translation stage and the extracted ring centers. Compared with existing methods that require projector calibration, the proposed method can avoid a propagation of the correspondence error between the camera imaging plane and projector imaging plane, thus increasing calibration accuracy. The calibrated telecentric structured light system is further used for three-dimensional (3D) reconstructions of a planar, a ruled surface, and complex surfaces. Experimental results demonstrate that the proposed system calibration method can be used for accurate 3D measurement.
Simulation of a Temperature-Compensated Voltage Sensor Based on Photonic Crystal Fiber Infiltrated with Liquid Crystal and Ethanol
Authors: Wang Wei-Lin , Liu Qiang , Liu Zhao-Yang , Wu Qiang , Fu Yong-Qing
Published: August 2022

A simulated design for a temperature-compensated voltage sensor based on photonic crystal fiber (PCF) infiltrated with liquid crystal and ethanol is presented in this paper. The holes distributed across the transverse section of the PCF provide two channels for mode coupling between the liquid crystal or ethanol and the fiber core. The couplings are both calculated accurately and explored theoretically using the finite element method (FEM). The influence of voltage on the alignment of the liquid crystal molecules and confinement loss of the fiber mode are studied. Liquid crystal molecules rotate which changes its properties as the voltage changes. As the characteristics of the liquid crystal will be affected by temperature, therefore, we further fill using ethanol, which is merely sensitive to temperature, into one hole of the PCF to realize temperature compensation. The simulated results show that the sensitivity is up to 1.29977 nm/V with the temperature of 25 °C when the voltage ranges from 365 to 565 V. The standard deviation of the wavelength difference is less than 2 nm within the temperature adjustment from 25 to 50 °C for temperature compensation. The impacts of the construction parameters of the PCF on sensing performances of this voltage sensor are also analyzed in this paper.
A Novel High-Speed Resonant Frequency Tracking Method Using Transient Characteristics in a Piezoelectric Transducer
Authors: Moon Jeonghoon , Park Sungjun , Lim Sangkil
Published: August 2022

When driving the piezoelectric transducer (PT: piezo transducer), which is a key device, it is important for the ultrasonic system (using ultrasonic waves of 20 kHz or higher) to operate at a resonant frequency that can maximize the conversion of mechanical energy (vibration) from electrical energy. The resonant frequency of the PT changes during the actual operation according to the load fluctuations and environmental conditions. Therefore, to maintain a stable output in an ultrasonic system, it is essential to track the resonant frequency in a short time. In particular, fast resonant frequency tracking (RFT: resonant frequency tracking) is an important factor in the medical ultrasonic system, i.e., the system applied in this thesis. The reason is that in the case of a medical ultrasonic system, heat-induced skin necrosis, etc., may cause the procedure to be completed within a short period of time. Therefore, tracking the RFT time for maximum power transfer is an important factor; in this thesis, we propose a new high-speed RFT method. The proposed method finds the whole system resonance frequency by using the transient phenomenon (underdamped response characteristic) that appears in an impedance system, such as an ultrasonic generator, and uses this to derive the mechanical resonance frequency of the PT. To increase the accuracy of the proposed method, parameter fluctuations of the pressure of the PT, the equivalent circuit impedance analysis of the PT, and a MATLAB simulation were performed. Through this, the correlation between the resonance frequency of the ultrasonic system, including the LC filter with nonlinear characteristics and the mechanical resonance frequency of the PT, was analyzed. Based on the analyzed results, a method for tracking the mechanical resonance frequency that can transfer the maximum output to the PT is proposed in this thesis. Experiments show that using the proposed high-speed RFT method, the ultrasonic system can track the mechanical resonance frequency of the PT with high accuracy in a short time.
Season Match Loads of a Portuguese Under-23 Soccer Team: Differences between Different Starting Statuses throughout the Season and Specific Periods within the Season Using Global Positioning Systems
Authors: Barreira João , Nakamura Fábio Y. , Ferreira Ricardo , Pereira João , Aquino Rodrigo , Figueiredo Pedro
Published: August 2022

This study aimed to quantify the external match loads (EMLs) of a Portuguese u-23 soccer team, competing at the highest national level for the age group, comparing players with different starting status throughout a competitive season and specific blocks. Thirty-five outfield soccer players were split into three groups for the entire season analysis and for each 3-month block, based on the percentage of games played as a starter. The three groups consisted of “starters” (≥55% of the games as a starter), “fringe” (30–54%), and “non-starters” (<30%). EMLs were recorded using 10 Hz GPS technology throughout the whole season (26 matches). Differences (p < 0.05) were found for total distance (TD), exposure time, and the number of accelerations and decelerations between starters and non-starters throughout the season (d = 0.73 to 1.08), and within each block (d = 0.59 to 1.68). Differences were also found between starters and fringe players for the number of accelerations in Block 2 (p = 0.03; d = 0.69), and TD (p = 0.006; d = 1) and exposure time (p = 0.006; d = 0.95) in Block 3. Differences in the EML were almost always accompanied by large differences in game time. Our results highlight the differences in the EML of starters and non-starters, emphasizing the need for compensatory training, especially with players that obtain significantly less playing time, to prepare the players for match demands (e.g., high-intensity efforts such as sprinting, accelerations, and decelerations).
Modelling and Investigation of Energy Harvesting System Utilizing Magnetically Levitated Permanent Magnet
Authors: Bijak Joanna , Trawiński Tomasz , Szczygieł Marcin , Kowalik Zygmunt
Published: August 2022

The aim of this article is mathematical modelling and investigation of chosen parameters of a small energy harvesting system designed for energy harvesting from car tire mechanical vibrations to provide power supply for various sensors, e.g., in tire pressure monitoring system. The energy harvester consists of three permanent magnets inserted into a tube made from polyamide material. Comsol program has been used to calculate the force between the magnets, the stiffness of the magnetic spring, and the natural frequency of the system. MATLAB program has been used to simulate the movement of the moveable magnet to compare it with the measurements. Finally, the parameters of the mathematical model of the energy harvester were investigated and validated on a specially prepared laboratory test bench.
Mathematical Modeling of Efficiency Evaluation of Double-Pass Parallel Flow Solar Air Heater
Authors: Singh Varun Pratap , Jain Siddharth , Karn Ashish , Kumar Ashwani , Dwivedi Gaurav , Meena Chandan Swaroop , Cozzolino Raffaello
Published: August 2022

To investigate the influencing range and optimize values of different operational and system parameters on the double-pass parallel flow solar air heater’s (DPPFSAH) thermal, effective, and exergetic efficiencies, an iterative method was used to analyze the governing energy equations using a theoretical model written in MATLAB based on the Nusselt number (Nu) and friction factor (f) correlations developed in the work performed earlier. A comparison between double-pass and single-pass SAHs for mathematical and experimental outcomes was conducted, and the results were found to be fairly consistent. According to the thermo-hydraulic performance indicators, similar to single-pass SAHs, perforated multi-V rib-roughened DPPFSAHs achieve optimum thermal performance for lower Reynolds numbers, which does not change much as the Reynolds number increases above 18,000. This finding can be taken into account when designing any DPPFSAH.
The Effect of Green Self-Identity on Perceived Image, Warm Glow and Willingness to Purchase: A New Generation’s Perspective towards Eco-Friendly Restaurants
Authors: Mahasuweerachai Patcharaporn , Suttikun Chompoonut
Published: August 2022

Compared to other generations, Generation Z (Gen Z) tend to be more concerned with environmental problems, prefer healthier food options, and are willing to pay premium prices for eco-friendly food products. Until now, however, this market segment had not been the focus of any sustainability research in the restaurant context. The present study fills this gap while exploring if green self-identity (one’s alignment with environmental concerns) influences perceptions of green restaurants (one’s perceived image of green restaurants) and warm glow feeling (one’s good feeling from patronizing green restaurants), which in turn affect willingness to pay. Data was collected from 388 Gen Z participants through a questionnaire survey, and covariance-based structural equation modeling (CB-SEM) was used to examine the study’s model. The results indicate warm glow is generated when individuals with green self-identity acknowledge restaurants are using green practices, which in turn influences their willingness to pay at green restaurants. Additionally, the findings of this study advance the theoretical viewpoints for social exchange theory (SET), identity theory, and green consumption in the restaurant industry. For practical implementation, restaurateurs can improve their businesses by developing their green image, initiating green design, and incorporating eco-friendly activities to enhance patrons’ dining experience.
Green Credit Financing and Emission Reduction Decisions in a Retailer-Dominated Supply Chain with Capital Constraint
Authors: Ji Jingna , Tang Dengli , Huang Jiansheng
Published: August 2022

In the context of low-carbon transformation, many small and medium-sized suppliers face financial difficulties. How to encourage and motivate capital-constrained suppliers to implement low-carbon strategies has become an important problem. There is a lack of quantitative research on green financing problems in the supply chain, especially considering the bank’s green credit financing (GCF) with discounted interest rates related to a low-carbon level. This paper formulates a Stackelberg game model to analyze the green financing and emission reduction decisions of a retailer-dominated supply chain consisting of one capital-constrained supplier and one capital-sufficient retailer. The retailer’s environmental purchasing requirement is considered. The result shows that the retailer’s procurement requirement cannot always motivate the capital-constrained supplier to improve their emission reduction rate. The mixed credit mode, which includes the bank’s GCF and the retailer’s partial prepayment, can help relieve the financing pressure of the capital-constrained supplier. It is found that the GCF at a discounted interest rate can effectively improve the supplier’s emission reduction enthusiasm. This paper tries to provide some meaningful insights for the government and supply chain members when making sustainable strategies.
Developing Capacities to Lead Change for Sustainability: A Quasi-Experimental Study of Simulation-Based Learning
Authors: Chatpinyakoop Chatchai , Hallinger Philip , Showanasai Parinya
Published: August 2022

Education for sustainability should be capable of developing citizens with the mindset and skills to meet the complex sustainability challenges faced in the 21st century. Although educators have advocated for the use of simulations and serious games in education for sustainability, there is need for experimental research that tests the effects of these active learning methods on learner knowledge, skills, and attitudes. This empirical study aimed to fill this gap by examining the effectiveness of the Leading Change for Sustainability—Business, an online computer simulation that challenges learners to transform a company’s capacity to achieve a triple bottom-line of sustainability goals. This article reports the results of a quasi-experimental study that was designed to assess change in knowledge and attitudes of 87 students studying in a Master of Management program in Thailand. The research found that learning with the Leading Change for Sustainability—Business simulation resulted in large, significant change in knowledge of sustainability and change management concepts, as well as in the sustainability mindset of students. The successful use of this simulation in a “fully online instructional environment” not only offers support for the use of this simulation in educating for sustainability, but also for the broader potential of simulations in online learning during the post-COVID-19 era.
A Human Defecation Prediction Method Based on Multi-Domain Features and Improved Support Vector Machine
Authors: Li Lin , Ke Yuwei , Zhang Tie , Zhao Jun , Huang Zequan
Published: August 2022

The difficulty of defecation seriously affects the quality of life of the bedridden elderly. To solve the problem that it is difficult to know the defecation time of the bedridden elderly, this paper proposed a human pre-defecation prediction method based on multi-domain features and improved support vector machine (SVM) using bowel sound as the original signal. The method includes three stages: multi-domain features extraction, feature optimization, and defecation prediction. In the stage of multi-domain features extraction, statistical analysis, fast Fourier transform (FFT), and wavelet packet transform are used to extract feature information in the time domain, frequency domain, and time-frequency domain. The symmetry of the bowel sound signal in the time domain, frequency domain, and time-frequency domain will change when the human has the urge to defecate. In the feature optimization stage, the Fisher Score (FS) algorithm is introduced to select meaningful and sensitive features according to the importance of each feature, aiming to remove redundant information and improve computational efficiency. In the stage of defecation prediction, SVM is optimized by the gray wolf optimization (GWO) algorithm to realize human defecation prediction. Finally, experimental analysis of the bowel sound data collected during the study is carried out. The experimental result shows that the proposed method could achieve an accuracy of 92.86% in defecation prediction, which proves the effectiveness of the proposed method.
Indoxyl Sulfate Alters the Humoral Response of the ChAdOx1 COVID-19 Vaccine in Hemodialysis Patients
Authors: Hou Yi-Chou , Wu Chia-Lin , Lu Kuo-Cheng , Kuo Ko-Lin
Published: August 2022

Background and aims: Vaccination for severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) is strongly recommended. The efficacy of SARS-CoV-2 vaccine for patients with end-stage renal disease is low. Indoxyl sulfate (IS) is a representative protein bound uremic toxin arousing immune dysfunction in CKD patients. It is unknown whether IS impairs the efficacy of vaccines for SARS-CoV-2. Materials and Methods: From 1 June 2021, to 31 December 2021, hemodialysis patients (n = 358) and a control group (n = 59) were eligible to receive the first dose of the ChAdOx1 COVID-19 vaccine. Titer measurements indicative of the humoral response (anti-S1 IgG and surrogate virus neutralization test (sVNT) results) and indoxyl sulfate concentration measurement were performed 4 weeks after ChAdOx1 vaccine injection. Results: The serum concentrations of anti-S1 IgG were 272 ± 1726 AU/mL and 2111 ± 4424 AU/mL in hemodialysis patients and control group (p < 0.05), respectively. The sVNT values were 26.8 ± 21.1% and 54.0 ± 20.2% in the hemodialysis and control groups (p < 0.05), respectively. There was a decreasing trend for the anti-S1 IgG titer from the lowest to highest quartile of IS (p < 0.001). The patients with higher concentrations of IS had lower sVNT (p for trend < 0.001). Conclusion: Hemodialysis patients had weaker humoral immunity after the first dose of the ChAdOx1 vaccine. Higher concentration of IS altered the development of anti-S1 antibodies and sVNT-measured neutralization.
Siltation of Small Water Reservoir under Climate Change: A Case Study from Forested Mountain Landscape of Western Carpathians, Slovakia
Authors: Juško Vladimír , Sedmák Róbert , Kúdela Patrik
Published: August 2022

The effectiveness of small reservoirs in a mountain landscape continuously decreases over time due to the gradual siltation. We examined two hypotheses about the enhanced siltation rate and the constant relative contribution of unpaved roads to the siltation of a small water reservoir in the period 1990–2014, with pronounced climate change, compared to the reference period 1970–1989. Analysis was based on deposit volumes extracted from the reservoir in 1989 and detected at the reservoir bottom in 2014. The geographical information systems, image analysis and universal soil loss equation were applied to model the soil erosion according to the two sources—catchment area and roads—to study siltation processes in depth. Despite expectations, rates of siltation were almost unchanged in compared periods. The positive changes in vegetation cover (the forest expansion and changes in forest management practices) offset the enlarged rain erosivity. On the other hand, road erosion increased by 41% from 1990 and became twice as much a contributor to sediments compared to 1970–1989. The intensity of erosion from roads was from 13 to 29 times greater than from other areas. Therefore, proper maintenance of road networks could rapidly decrease reservoir siltation. Moreover, we recommend continuous cover forestry as a critical measure for central Europe’s forested regions to prevent growing erosion pressures.
Estimating Energy Efficient Design Parameters for Trash Racks at Low Head Hydropower Stations
Authors: Latif Muhammad Ahsan , Sarwar Muhammad Kaleem , Farooq Rashid , Shaukat Nadeem , Ali Shoaib , Hashmi Abrar , Tariq Muhammad Atiq Ur Rehman
Published: August 2022

Trash racks are usually composed of an array of bars installed in a hydropower scheme to safeguard the turbines by collecting water-borne detritus. However, current design approaches for the design of trash racks focus on structural criteria. A little attention renders the proper evaluation of hydraulic criteria, which causes a significant hydraulic head loss in low head hydropower schemes with an integral intake. This study investigates the head loss through trash racks by employing computational fluid dynamics (CFD) for several design combinations. A three-dimensional model of trash racks using fractional area/volume obstacle representation (FAVOR) method in FLOW-3D is set up to define the effects of the meshing on the geometry and several simulations are carried out considering various approach velocities and different bar spacings, inclination angles, and blockage ratios. The results indicate that head loss increases with an increase in approach velocity, the inclination angle of the rack with channel bed, and blockage ratio. It is noticed that a clear spacing between vertical bars greater than or equal to 0.075 m has a minimum head loss before it becomes significantly high for lower spacing. In addition, the head loss coefficient increases for screen angles greater than 60°, which can be considered as an optimal parameter for design purpose.
Evaluation of Wind and Wave Estimates from CMEMS Reanalysis for Brazil’s Offshore Energy Resource Assessment
Authors: Freitas Ismael Guidson Farias de , Gomes Helber Barros , Peña Malaquias , Mitsopoulos Panagiotis , Nova Thayna Silva Vila , Silva Kécia Maria Roberto da , Calheiros Alan James Peixoto
Published: August 2022

This study aims to evaluate wind speed and significant wave height data from the Copernicus Marine Environment Monitoring Service (CMEMS) reanalysis using buoy measurements for offshore energy application off the east coast of Brazil. Such analysis has become important, since reanalysis datasets can be fundamental tools in identifying regions with wind energy potential that are suitable for the installation of offshore farms. Two sets of reanalysis were used: wind speed (with spatial resolution of 0.25° and temporal resolution of 6 h) and significant wave height (with spatial resolution of 0.2° and temporal resolution of 3 h). For validation, seven MetOcean buoys were selected. In the statistical validation, Pearson’s correlation, coefficient of determination (R2), slope of the straight line, root mean square error (RMSE), mean square error (MSE), probability density function (PDF), mean and standard deviation were calculated. In the evaluation of offshore wind energy resources, the calculation of energy density was performed. The results showed correlations above 0.70 for wind speed and above 0.91 for significant wave height, and additionally, the RMSE values showed maximums of 2.31 m/s for wind speed and 0.28 cm for significant wave height. In the PDF comparison of buoy data and reanalysis, similarities were observed, mainly in the PDF parameters. The energy density presented values consistent with other studies (352–461 W/m²). The results show that the reanalysis data can be applicable in studies focusing on offshore wind potential.
Relationship between the level of specific IgG to neurolep¬tics and the content of autoantibodies to dopamine recep¬tors, dopamine and acetylcholine receptors in patients with schizophrenia
Authors:   FSBEI HE Stavropol State Medical University of the Ministry of Health of the Russian Federation, Stavropol, Baturina M. V. , Boev O. I. ,   FSBEI HE Stavropol State Medical University of the Ministry of Health of the Russian Federation, Stavropol, Kharitonova Y. P. ,   FSBEI HE Stavropol State Medical University of the Ministry of Health of the Russian Federation, Stavropol, Yarovitsky V. B. ,   FSBEI HE Stavropol State Medical University of the Ministry of Health of the Russian Federation, Stavropol, Shikin Yu. M. ,   FSBEI HE Stavropol State Medical University of the Ministry of Health of the Russian Federation, Stavropol, Grudinin O. A. ,   FSBEI HE Stavropol State Medical University of the Ministry of Health of the Russian Federation, Stavropol
Published: August 2022

The purpose of the research was to study the levels of autoantibodies (AAB) to dopamine receptors of type 2 (DR2), to dopamine and acetylcholine receptors in the blood of patients with schizophrenia and to identify the relationship between the content of specific antibodies (IgG) to neuroleptics and the amount of autoantibodies.
Study of autoimmune mechanisms of neuroleptics action
Authors:   FSBEI HE Stavropol State Medical University of the Ministry of Health of the Russian Federation, Stavropol, Baturina M. V. , Beyer E. V. ,   FSBEI HE Stavropol State Medical University of the Ministry of Health of the Russian Federation, Stavropol
Published: August 2022

The authors set a goal to evaluate the severity of haloperidol catalepsy depending on the level of autoantibodies to dopamine receptors and dopamine in laboratory rats that were subjected to long-term administration of neuroleptics.
Assessment of the drug interaction potential of antihypertensive and anti-inflammatory drugs based on metabolism data involving the cytochrome P450 system
Authors:   MarGU, Belov A. E.
Published: August 2022

The author of the work sets the goal of personalizing the pharmacotherapy of patients receiving antihypertensive and anti-inflammatory therapy based on the metabolic profile of drugs.
El uso de las tics como herramientas estratégicas de la comunicación empresarial
Authors: Burau Grain Edgar Emiliano , Ruperti Cañarte Sussy Aracely , Pin Carvajal Jacqueline Del Rocío
Published: August 2022

Las Tecnologías de la Información y la Comunicación (TICs) son un conjunto de herramientas que permiten el avance de las diversas instituciones, empresas, gobiernos y todo tipo de organizaciones.  Conforme la globalización avanza, esta herramienta permite la transformación de información eficazmente, y tener dicha información disponible tanto en un tiempo como en un determinado y ayudar a tomar decisiones de suma importancia. En sí, la tecnología forma parte valiosa para las organizaciones, empleados y personas en general. En este texto se destacará el empleo de las TICs como herramientas estratégicas de comunicación empresarial. Para ello se partirá de la base de que engloban más del concepto de ser meros instrumentos, sino que constituyen una consecución de la interacción generada por las personas a través de la correcta estructuración de la información. De ahí su importancia y valía para las empresas y organizaciones.
Análisis de intereses lectores: una mirada al programa de vinculación “Manabí crece leyendo”
Authors: Navarro Cedeño Viviana , Joza Vera María Fernanda , García Cabrera Verónica
Published: August 2022

El objetivo de la investigación fue predecir el interés por la lectura en la provincia de Manabí, el presente estudio es de tipo cuantitativo basado en cuestionarios y test, aplicados a los estudiantes de Educación General Básica de las Unidades Educativas Andrés de Vera, 12 de Marzo y Rafael María Mendoza de la ciudad de Portoviejo acogidas desde el 16 de Abril en el albergue número uno “Andrés de Vera”. Estos educandos fueron parte importante del Programa Educativo “Manabí Crece Leyendo”. A raíz del terremoto estas instituciones se alojaron en una sola localidad, evento que marcó la vida de los todos los portovejenses, sobre todo de los más pequeños. Detrás de este suceso las autoridades y docentes de la Universidad Técnica de Manabí, junto con los estudiantes de la Escuela de Bibliotecología y Ciencias de la Información, deciden implementar una serie de actividades para fomentar y desarrollar capacidades lectoras en los niños; por medio de la pintura y la narración de leyendas manabitas, se logró desarrollar en los niños nuevos aprendizajes y experiencias para motivar el interés por la lectura. Se obtuvieron resultados favorables, mediante la aplicación de un test de escala de apreciación de las habilidades para predecir el interés por la lectura, y potenciar planes de fomento de la lectura más eficaces.
O JORNAL NA ESCOLA E A EDUCOMUNICAÇÃO
Authors: Zorzenon Rodrigues Dulce Mirian Mirian
Published: August 2022

O JORNAL NA ESCOLA E A EDUCOMUNICAÇÃO
Population Size Estimation of People Who Use Illicit Drugs and Alcohol in Iran (2015-2016)
Authors: Rastegari Azam , Baneshi Mohammad Reza , Hajebi Ahmad , Noroozi Alireza , Karamouzian Mohammad , Shokoohi Mostafa , Mirzazadeh Ali , Khojasteh Bojnourdi Toktam , Nasiri Naser , Haji Maghsoudi Saiedeh , Haghdoost Ali Akbar , Sharifi Hamid
Published: August 2022

Background: Estimating the number of people using illicit drugs and alcohol is necessary for informing health policy and programming. However, it is often challenging to reliably estimate the size of these marginalized populations through direct methods. In this study, we estimated the population size of these groups using the indirect Network Scale-Up (NSU) method in Iran from 2015 to 2016. Methods: Using a self-administered questionnaire, we asked 15 124 individuals (54% men) about the number of people they know who used different types of drugs at least once in the past 12 months. Prevalence estimates were reported per 100 000 population. The uncertainty level (UL) was calculated using the bootstrap method. Results: The average age of the respondents was 33 years old, and 35.1% of them were unmarried. The most common drugs and their prevalence were as follows: opium (2534 [95% UL: 2467-2598]), hashish (849 [95% UL: 811-886]), stimulants (methamphetamine, ecstasy pills, cocaine, and Ritalin) (842 [95% UL: 802-879]), heroin/crack (578 [95% UL: 550-607]), and drug injection (459 [95% UL: 438-484]). Additionally, we estimated the prevalence of alcohol use as 2797 (95% UL: 2731-2861). On average, substance use was 5.23 times more prevalent among men than women. Opium use was more prevalent among individuals aged >50 years old. Moreover, alcohol use was more prevalent among participants between 18 and 30 years old (5164 per 100 000 population). Conclusion: Although opium continues to be the most prevalent illicit drug in Iran, the patterns of illicit drug use are heterogeneous among different age groups, genders, and provinces. Age-gender specific and culturally appropriate interventions are warranted to meet the needs of people in different subgroups.
Three Approaches to Improve a Practical Guide on EvidenceInformed Deliberative Processes for Health Benefit Package Design Comment on "Evidence-Informed Deliberative Processes for Health Benefit Package Design – Part II: A Practical Guide"
Authors: Guzman Javier
Published: August 2022

As countries around the world seek to deliver universal health coverage, they must prioritize which services to pay for with public funds, to whom, and at what cost. Countries are increasingly using health technology assessment (HTA) to identify which interventions provide the best value for money and merit inclusion in their health benefit packages (HBPs)—the explicit lists of health services provided using public funds. Oortwijn et al understand the importance of providing practical guidance on the foundation of HBP design, and their article, "Evidence-Informed Deliberative Processes for Health Benefit Package Design – Part II: A Practical Guide," provides recommendations for HTA bodies to improve the legitimacy of their decision-making by incorporating four elements in their HBP procedures: stakeholder involvement, evidence-informed evaluation, transparency, and appeal. This article proposes three approaches to enhance the value of the guide: moving from structure to compliance and performance, prioritizing key issues of legitimacy within HBP processes, and acknowledging potential the costs and risks associated with the use of this framework.