bluuebunny/crossref_metadata_2025 huggingface dataset:
The Association between Dietary Purine Intake and Mortality: Evidence from the CHNS Cohort Study
Authors: Yan Miaojia , Liu Yezhou , Wu Lichen , Liu Huimeng , Wang Yutong , Chen Fangyao , Pei Leilei , Zhao Yaling , Zeng Lingxia , Dang Shaonong , Yan Hong , Mi Baibing
Published: April 2022

Objectives: To investigate the association between dietary purine intake and mortality among Chinese adults. Methods: Based on data from the 2004–2015 China Health and Nutrition Survey (CHNS) and the corresponding edition of China Food Composition, the average purine intake per day (mg/day) from 2004 to 2011 was calculated, and the surveyed population was divided into five groups by quintiles. The outcome event and timepoint of concern were defined as death and time, respectively, as reported by family members, recorded until the 2015 survey. Cox proportional hazards regression was used to estimate the hazard ratios (HRs) with 95% confidence intervals (CIs) for death. The possibly nonlinear relationship between purine intake and mortality was examined with restricted cubic splines. Results: We included 17,755 subjects, and the average purine intake among them was 355.07 ± 145.32 mg/day. Purine intake was inversely associated with mortality (Ptrend < 0.001). Compared with the lowest quintiles of purine intake, the highest quintiles (HR = 0.60; 95% CI: 0.46, 0.77) showed a significant association with lower mortality. The negative association with mortality was mainly found in plant-derived purine (Ptrend = 0.001) and, weakly, in animal-derived purine (Ptrend = 0.052). In addition, a U-shaped relationship between purine intake and mortality was observed in males; however, there was no statistically significant dose–response relationship in females. Conclusion: Considering the low-purine-intake levels of the Chinese population, we observed a U-shaped relationship between purine intake and mortality in males, but purine intake may not relate to mortality in females. Future studies should investigate the causal relationship between purine intake and disease burden in China.
Partial Hydrolyzed Protein as a Protein Source for Infant Feeding: Do or Don’t?
Authors: Vandenplas Yvan , Ksiażyk Janusz , Luna Manuel Sanchez , Migacheva Natalia , Picaud Jean-Charles , Ramenghi Luca A. , Singhal Atul , Wabitsch Martin
Published: April 2022

Exclusive breastfeeding until the age of six months is the recommended feeding method for all infants. However, this is not possible for every infant. Therefore, a second choice of feeding, as close as possible to the gold standard, is needed. For historical reasons, this has been cow’s-milk-based feeding. This paper discusses if this second-choice feeding method should contain intact protein or partially hydrolyzed proteins. The limited data available indicates that mother’s milk is relatively rich in bioactive peptides. Whether partially hydrolyzed protein might be a protein source closer to human milk protein content than intact cow’s milk needs further research. However, more research on protein and bioactive peptides in mother’s milk should be a priority for future scientific development in this field. Results of such research will also provide an answer to the question of which option would be the best second choice for infant feeding if sufficient breast milk is not available.
Fabrication and In Vitro/Vivo Evaluation of Drug Nanocrystals Self-Stabilized Pickering Emulsion for Oral Delivery of Quercetin
Authors: Wang Zhe , Dai Bo , Tang Xiaohan , Che Zhihui , Hu Fei , Shen Chengying , Wu Wei , Shen Baode , Yuan Hailong
Published: April 2022

The aim of this study was to develop a new drug nanocrystals self-stabilized Pickering emulsion (NSSPE) for improving oral bioavailability of quercetin (QT). Quercetin nanocrystal (QT–NC) was fabricated by high pressure homogenization method, and QT–NSSPE was then prepared by ultrasound method with QT–NC as solid particle stabilizer and optimized by Box-Behnken design. The optimized QT–NSSPE was characterized by fluorescence microscope (FM), scanning electron micrograph (SEM), X-ray diffraction (XRD), and differential scanning calorimetry (DSC). The stability, in vitro release, and in vivo oral bioavailability of QT–NSSPE were also investigated. Results showed that the droplets of QT–NSSPE with the size of 10.29 ± 0.44 μm exhibited a core-shell structure consisting of a core of oil and a shell of QT–NC. QT–NSSPE has shown a great stability in droplets shape, size, creaming index, zeta potential, and QT content during 30 days storage at 4, 25, and 40 °C. In vitro release studies showed that QT–NSSPE performed a better dissolution behavior (65.88% within 24 h) as compared to QT–NC (50.71%) and QT coarse powder (20.15%). After oral administration, the AUC0–t of QT–NSSPE was increased by 2.76-times and 1.38 times compared with QT coarse powder and QT–NC. It could be concluded that NSSPE is a promising oral delivery system for improving the oral bioavailability of QT.
Overcoming Hypoxia-Induced Drug Resistance via Promotion of Drug Uptake and Reoxygenation by Acousto–Mechanical Oxygen Delivery
Authors: Ho Yi-Ju , Thao Dinh Thi , Yeh Chih-Kuang
Published: April 2022

Hypoxia-induced drug resistance (HDR) is a critical issue in cancer therapy. The presence of hypoxic tumor cells impedes drug uptake and reduces the cytotoxicity of chemotherapeutic drugs, leading to HDR and increasing the probability of tumor recurrence and metastasis. Microbubbles, which are used as an ultrasound contrast agent and drug/gas carrier, can locally deliver drugs/gas and produce an acousto–mechanical effect to enhance cell permeability under ultrasound sonication. The present study applied oxygen-loaded microbubbles (OMBs) to evaluate the mechanisms of overcoming HDR via promotion of drug uptake and reoxygenation. A hypoxic mouse prostate tumor cell model was established by hypoxic incubation for 4 h. After OMB treatment, the permeability of HDR cells was enhanced by 23 ± 5% and doxorubicin uptake was increased by 11 ± 7%. The 61 ± 14% reoxygenation of HDR cells increased the cytotoxicity of doxorubicin from 18 ± 4% to 58 ± 6%. In combination treatment with OMB and doxorubicin, the relative contributions of uptake promotion and reoxygenation towards overcoming HDR were 11 ± 7% and 28 ± 10%, respectively. Our study demonstrated that reoxygenation of hypoxic conditions is a critical mechanism in the inhibition of HDR and enhancing the outcome of OMB treatment.
Total Internal Reflection Lens for Optical Wireless Receivers
Authors: Kirrbach René , Schneider Tobias , Stephan Mira , Noack Alexander , Faulwaßer Michael , Deicke Frank
Published: April 2022

This work considers the use of a freeform total internal reflection (TIR) lens for optical concentration and provides for the first time experimental results in the context of optical wireless communications (OWC). The lens is placed on a surface-mounted device (SMD) avalanche photodiode (APD) to minimize position tolerances and simplify assembly. The lens achieves a concentration ratio of go = 44.7 (16.5 dB) within the FOV center and exhibits an acceptance angle of ±5°. The TIR lens approach is validated by comparing eye diagrams and bit error ratios (BER) of a receiver with and without a TIR lens. For the measurements, non-return-to-zero (NRZ) on-off keying (OOK) signals are transmitted with a data rate of 1.289 Gbit/s.
A K-Means Clustered Routing Algorithm with Location and Energy Awareness for Underwater Wireless Sensor Networks
Authors: Li Luyao , Qiu Yang , Xu Jing
Published: April 2022

Data delivery in harsh underwater channels consumes a higher transmission power than that in terrestrial networks. However, due to the complexity of the underwater environment, the energy supply of the nodes in underwater wireless sensor networks is usually limited by their required laborious battery replacement. Thus, energy consumption is considered one of the key issues in underwater wireless optical communication. To minimize such consumption for underwater transmission nodes, much research interest has been found on K-Means technology in designing routing algorithms. However, these algorithms have not regarded the located site and the remaining energy of the underwater nodes simultaneously, which might affect their efficiency. In this paper, we propose a clustered routing algorithm, namely the location and energy-aware k-means clustered routing (LE-KCR) algorithm, which applies K-means technology regarding both the located site and the remaining energy of each node. In the proposed LE-KCR algorithm, both the located site and the remaining energy of a candidate cluster-head, as well as the distance between it and its sink node, are considered in cluster-head selection. In addition, given the inaccessibility of some nodes to the whole underwater sensor network resulting from the limited transmission range of their clusters, the dual-hop routing technique is adopted for the edge nodes. The simulation results indicate that the proposed LE-KCR algorithm remarkably reduces the energy consumption and the dead nodes when compared to the traditional low-energy adaptive clustering hierarchy (LEACH) protocol and the optimized LEACH protocol based on K-means clustering technology.
Facile Preparation of Hydrophobic PLA/PBE Micro-Nanofiber Fabrics via the Melt-Blown Process for High-Efficacy Oil/Water Separation
Authors: Li Han , Zhang Heng , Hu Jun-Jie , Wang Guo-Feng , Cui Jing-Qiang , Zhang Yi-Feng , Zhen Qi
Published: April 2022

Polylactic acid (PLA) micro-nanofiber fabrics with a large specific surface area and excellent biodegradability are commonly used in oil/water separation; however, challenges remain due to their poor mechanical properties. Herein, a thermoplastic polylactic acid/propylene-based elastomer (PLA/PBE) polymer was prepared by blending PLA with PBE. Then, PLA/PBE micro-nanofiber fabrics were successfully prepared using a melt-blown process. The results show that the PLA/PBE micro-nanofiber fabric has a three-dimensional porous structure, improving the thermal stability and fluidity of the PLA/PBE blended polymers. The PLA/PBE micro-nanofiber fabric demonstrated a significantly reduced average fiber diameter and an enhanced breaking strength. Moreover, the water contact angle of the prepared samples is 134°, which suggests a hydrophobic capacity. The oil absorption rate of the fabric can reach 10.34, demonstrating excellent oil/water separation performance. The successful preparation of PLA/PBE micro-nanofiber fabrics using our new method paves the way for the large-scale production of promising candidates for high-efficacy oil/water separation applications.
Study of Gas-to-Liquid Heat Pipe Heat Exchanger
Authors: Gupta Pratik Prakash , Senthilkumar Sundararaj , Kang Shung-Wen
Published: April 2022

This study is focused on the study and development of a gas-to-liquid heat pipe heat exchanger (HPHE) based on numerical and experimental analysis. Stainless steel heat pipes were installed inside the heat exchanger in the form of three equilateral triangles, staggered into a hexagonal configuration to simulate the waste heat recovery from hot exhaust gas to a water flow. The first main aim of this study was focused on 3D design and numerical analysis, which were used to create and calculate the effect of similar input conditions on the overall system. The system was tested for the overall heat transfer by measuring the temperature change in both fluids. The heat transfer and overall average temperature were used to calculate the effectiveness of the system. In the second part of this study, a test of the waste heat recovery was undertaken with this setup, using water as the cooling fluid. The study was conducted with different input velocities and temperatures of waste hot air, controlled simultaneously by the input fan and air heater, whereas the cooling water was kept at a steady state of 30 °C and 0.0156 kg/s at the input. The hot air velocity was controlled by fans with different inlet air velocities of 0.3 m/s, 0.5 m/s, and 0.7 m/s. Moreover, the temperature of the air was changed from 150 °C to 250 °C with a step of 25 °C. The increase in temperature and the velocity of air was directly proportional to the amount of heat transferred from the air to the cooling water, and the effectiveness was also found to be inversely proportional to both of the varying input parameters. The numerical study showed a maximum increase of 12% in the heat transfer. The output temperatures of hot and cold fluids showed maximum increases of 7 K and 3 K, respectively. The numerical system with such input parameters can be evaluated further to predict the behavior of changes in the design and parameters.
Freshly Milled Quartz Particles Obtained from River Sand as an Efficient Natural Demulsifier for Crude Oil Emulsions
Authors: Nadirov Kazim , Zhantasov Manap , Nadirova Zhanna , Otarbaev Nurlybek , Bimbetova Gulmira , Nadirov Rashid
Published: April 2022

Saline water necessarily contained in crude oil forms complex and stable water-in-oil (w/o) emulsions with oil. Due to the negative impact of this emulsion on the oil’s transportation and refining, special materials are added to help break the emulsion and separate water. Herein, a comparative study of the demulsifying ability concerning w/o emulsion of the original and freshly milled quartz (FMQ) particles isolated from river sand was carried out. The effect of quartz with a mesh size of 75 μm on reducing emulsion stability was investigated using rheological measurements, interfacial tension measurements, demulsification tests, as well as routine methods for characterizing solid and liquid materials. With the addition of 3 wt% FMQ, 97% demulsification efficiency was achieved after 100 min of settling, against 140 min for the original quartz. The role of milling quartz is to increase the ability of water to adhere and thus locally increase the pH value; this results in a reduction in the stability of the emulsion and its destruction. The prolonging effect of quartz milling lasted about 2.5–3.0 h, after which the demulsifying ability of milled quartz became comparable to that of the starting material.
Analytical Routes to Chaos and Controlling Chaos in Brushless DC Motors
Authors: Chang Shun-Chang
Published: April 2022

This study examines the dynamics in a brushless DC motor (BLDCM) and methods used to control potentially chaotic behavior or behavior similar to chaotic processes in these systems. Bifurcation diagrams revealed complex nonlinear behaviors over a range of parameter values. In the resulting bifurcation diagram, period-doubling bifurcation, period-three bifurcation, and chaotic behavior can clearly be seen. We used Lyapunov exponents and Lyapunov dimensions to show the occurrence of chaos in a BLDCM. We then used the state feedback method to control chaos behaviors in the same BLDCM. Numerical simulations show the feasibility of the suggested means. Analysis of robustness against parametric perturbation in a BLDCM was performed from the perspective of Lyapunov stability theory and by using numerical simulations. We believe that studying the nonlinear dynamics and controlling chaos in BLDCMs will help to advance the development of high-performance electric vehicles.
Treatment of Scrap Tire for Rubber and Carbon Black Recovery
Authors: Abdulrahman Alaa Sultan , Jabrail Fawzi Habeeb
Published: April 2022

In this study, a chemical dissolution treatment was used to recover rubber and carbon black (CB) from truck tire scrap, with gas oil acting as the solvent and 4-Hydroxy-TEMPO acting as the catalyst for the chemical reactions. Montmorillonite clay was used to separate the rubber solution from the CB and the other non-dissolved tire additives. The recovered rubber and CB were characterized together with the original scrap tire sample by XRD, SEM, BET and thermal analysis, as well as FTIR and 1H NMR spectral analyses. Characterization of the chemical structure of the recovered rubber showed that the main functional groups of styrene−butadiene rubber blend with natural rubber. The thermal behavior and crystalline structure of the recovered rubber, as well as its morphological images, showed that the properties of the rubber sample were acceptable and similar to natural rubber. The recovered CB characterizations showed that the sample after pyrolysis was a highly crystalline nanocomposite structure with a high specific surface area and scattered pores.
The Applicability of Time-Integrated Unit Stream Power for Estimating Bridge Pier Scour Using Noncontact Methods in a Gravel-Bed River
Authors: Hempel Laura A. , Malenda Helen F. , Fulton John W. , Henneberg Mark F. , Cederberg Jay R. , Moramarco Tommaso
Published: April 2022

In near-field remote sensing, noncontact methods (radars) that measure stage and surface water velocity have the potential to supplement traditional bridge scour monitoring tools because they are safer to access and are less likely to be damaged compared with in-stream sensors. The objective of this study was to evaluate the use of radars for monitoring the hydraulic conditions that contribute to bridge–pier scour in gravel-bed channels. Measurements collected with a radar were also leveraged along with minimal field measurements to evaluate whether time-integrated stream power per unit area (Ω) was correlated with observed scour depth at a scour-critical bridge in Colorado. The results of this study showed that (1) there was close agreement between radar-based and U.S. Geological Survey streamgage-based measurements of stage and discharge, indicating that radars may be viable tools for monitoring flow conditions that lead to bridge pier scour; (2) Ω and pier scour depth were correlated, indicating that radar-derived Ω measurements may be used to estimate scour depth in real time and predict scour depth based on the measured trajectory of Ω. The approach presented in this study is intended to supplement, rather than replace, existing high-fidelity scour monitoring techniques and provide data quickly in information-poor areas.
The Potential of Sentinel-1A Data for Identification of Debris-Covered Alpine Glacier Based on Machine Learning Approach
Authors: Yao Guohui , Zhou Xiaobing , Ke Changqing , Drolma Lhakpa , Li Haidong
Published: April 2022

Microwave remote sensing is one of the main approaches to glacier monitoring. This paper provides a comparative analysis of how different types of radar information differ in identifying debris-covered alpine glaciers using machine learning algorithms. Based on Sentinel-1A data, three data suites were designed: A backscattering coefficient (BC)-based data suite, a polarization decomposition parameter (PDP)-based data suite, and an interference coherence coefficient (ICC)-based data suite. Four glaciers with very different orientations in different climatic zones of the Tibetan Plateau were selected and classified using an integrated machine learning classification approach. The results showed that: (1) The boosted trees and subspace k-nearest neighbor algorithms were optimal and robust; and (2) the PDP suite (63.41–99.57%) and BC suite (55.85–99.94%) both had good recognition accuracy for all glaciers; notably, the PDP suite exhibited better rock and debris recognition accuracy. We also analyzed the influence of the distribution of glacier surface aspect on the classification accuracy and found that the more asymmetric it was about the sensor orbital plane, the more difficult it was for the BC and PDP suites to recognize the glacier, and a large slope could further reduce the accuracy. Our results suggested that during the inventory or classification of large-scale debris-covered alpine glaciers, priority should be given to polarization decomposition features and elevation information, and it is best to divide the glaciers into multiple subregions based on the spatial relationship between glacier surface aspect and radar beams.
An Encoder–Decoder with a Residual Network for Fusing Hyperspectral and Panchromatic Remote Sensing Images
Authors: Zhao Rui , Du Shihong
Published: April 2022

For many urban studies it is necessary to obtain remote sensing images with high hyperspectral and spatial resolution by fusing the hyperspectral and panchromatic remote sensing images. In this article, we propose a deep learning model of an encoder–decoder with a residual network (EDRN) for remote sensing image fusion. First, we combined the hyperspectral and panchromatic remote sensing images to circumvent the independence of the hyperspectral and panchromatic image features. Second, we established an encoder–decoder network for extracting representative encoded and decoded deep features. Finally, we established residual networks between the encoder network and the decoder network to enhance the extracted deep features. We evaluated the proposed method on six groups of real-world hyperspectral and panchromatic image datasets, and the experimental results confirmed the superior performance of the proposed method versus six other methods.
An Overview of a Special Issue on Upcoming Positioning, Navigation, and Timing: GPS, GLONASS, Galileo and BeiDou
Authors: Hong Chang-Ki , Bae Tae-Suk , Kwon Jay Hyoun
Published: April 2022

In recent decades, global navigation satellite systems (GNSSs) have experienced significant changes [...]
Ground Contact Time Estimating Wearable Sensor to Measure Spatio-Temporal Aspects of Gait
Authors: Bernhart Severin , Kranzinger Stefan , Berger Alexander , Peternell Gerfried
Published: April 2022

Inpatient gait analysis is an essential part of rehabilitation for foot amputees and includes the ground contact time (GCT) difference of both legs as an essential component. Doctors communicate improvement advice to patients regarding their gait pattern based on a few steps taken at the doctor’s visit. A wearable sensor system, called Suralis, consisting of an inertial measurement unit (IMU) and a pressure measuring sock, including algorithms calculating GCT, is presented. Two data acquisitions were conducted to implement and validate initial contact (IC) and toe-off (TO) event detection algorithms as the basis for the GCT difference determination for able-bodied and prosthesis wearers. The results of the algorithms show a median GCT error of −51.7 ms (IMU) and 14.7 ms (sensor sock) compared to the ground truth and thus represent a suitable possibility for wearable gait analysis. The wearable system presented, therefore, enables a continuous feedback system for patients and, above all, a remote diagnosis of spatio-temporal aspects of gait behaviour based on reliable data collected in everyday life.
FPGA-Based Autonomous GPS-Disciplined Oscillatorsfor Wireless Sensor Network Nodes
Authors: Bui Toan Quang The , Elango Arul , Landry René Jr.
Published: April 2022

Numerous devices in distributed wireless sensor arrays require a high-accuracy timing reference. Although the GPS-disciplined oscillators have been developed for decades, the hardware design still has performance limitations. In this context, we present the hardware implementation for a GPS-disciplined oscillator with an automatic adaptive drift correction algorithm, which is implemented in a low-cost, high-speed field-programmable gate array (FPGA) device. The system design and the hardware implementation are presented to demonstrate the advantages of the proposed oscillator. To verify this oscillator in real-time applications, we tested the device in multiple environments and compared it to state-of-the-art designs. The experimental results showed that our proposed device has a low cost and high performance. This device can achieve less than 80 ns and 356 ns in 1PPS signal drift in the indoor environment test and the outdoor environment test, respectively, after 24 h of working without a GPS signal.
Space-Air-Ground Integrated 6G Wireless Communication Networks: A Review of Antenna Technologies and Application Scenarios
Authors: Dicandia Francesco Alessio , Fonseca Nelson J. G. , Bacco Manlio , Mugnaini Sara , Genovesi Simone
Published: April 2022

A review of technological solutions and advances in the framework of a Vertical Heterogeneous Network (VHetNet) integrating satellite, airborne and terrestrial networks is presented. The disruptive features and challenges offered by a fruitful cooperation among these segments within a ubiquitous and seamless wireless connectivity are described. The available technologies and the key research directions for achieving global wireless coverage by considering all these layers are thoroughly discussed. Emphasis is placed on the available antenna systems in satellite, airborne and ground layers by highlighting strengths and weakness and by providing some interesting trends in research. A summary of the most suitable applicative scenarios for future 6G wireless communications are finally illustrated.
Long-Range Underwater Communication Based on Time Reversal Processing Using Various Diversity Methods
Authors: Kim Donghyeon , Kim Jeasoo , Hahn Jooyoung
Published: April 2022

Time reversal processing (TRP) exploits signal diversity methods, namely, spatial, temporal, beam, and frequency, to mitigate the distortion caused by multipath time delay. Using the same experimental data, this study compares the performance of communication utilizing TRP based on various diversity methods. In October 2018, the biomimetic long-range acoustic communication experiment 2018 (BLAC18) was conducted in the East Sea, east of Pohang, Korea. During the experiment, communication signals modulated by binary phase-shift keying were transmitted over a range of 60 km, and a vertical line array of 16 elements (with an aperture of ∼42 m) was utilized. The BLAC18 analysis showed that the performance of each diversity method depends on the order of diversity. When the order of diversity was one, the beam diversity method with the beamformed signal yielded the best performance. For the maximum order of diversity, however, the spatial diversity method delivered the best performance, owing to the high channel variability and large number of receivers.
False Data Injection Detection for Phasor Measurement Units
Authors: Almasabi Saleh , Alsuwian Turki , Awais Muhammad , Irfan Muhammad , Jalalah Mohammed , Aljafari Belqasem , Harraz Farid A.
Published: April 2022

Cyber-threats are becoming a big concern due to the potential severe consequences of such threats is false data injection (FDI) attacks where the measures data is manipulated such that the detection is unfeasible using traditional approaches. This work focuses on detecting FDIs for phasor measurement units where compromising one unit is sufficient for launching such attacks. In the proposed approach, moving averages and correlation are used along with machine learning algorithms to detect such attacks. The proposed approach is tested and validated using the IEEE 14-bus and the IEEE 30-bus test systems. The proposed performance was sufficient for detecting the location and attack instances under different scenarios and circumstances.
D-CEWS: DEVS-Based Cyber-Electronic Warfare M&S Framework for Enhanced Communication Effectiveness Analysis in Battlefield
Authors: Seo Sang , Han Sangwoo , Kim Dohoon
Published: April 2022

Currently, in the field of military modernization, tactical networks using advanced unmanned aerial vehicle systems, such as drones, place an emphasis on proactively preventing operational limiting factors produced by cyber-electronic warfare threats and responding to them. This characteristic has recently been highlighted as a key concern in the functioning of modern network-based combat systems in research on combat effect analysis. In this paper, a novel discrete-event-system-specification-based cyber-electronic warfare M&S (D-CEWS) was first proposed as an integrated framework for analyzing communication effects and engagement effects on cyber-electronic warfare threats and related countermeasures that may occur within drones. Accordingly, for the first time, based on communication metrics in tactical ad hoc networks, an analysis was conducted on the engagement effect of blue forces by major wireless threats, such as multi-layered jamming, routing attacks, and network worms. In addition, the correlations and response logics between competitive agents were also analyzed in order to recognize the efficiency of mutual engagements between them based on the communication system incapacitation scenarios for diverse wireless threats. As a result, the damage effect by the cyber-electronic warfare threat, which could not be considered in the existing military M&S, could be calculated according to the PDR (packet delivery ratio) and related malicious pool rate change in the combat area, and the relevance with various threats by a quantifiable mission attribute given to swarming drones could also be additionally secured.
Markerless 3D Skeleton Tracking Algorithm by Merging Multiple Inaccurate Skeleton Data from Multiple RGB-D Sensors
Authors: Lee Sang-hyub , Lee Deok-Won , Jun Kooksung , Lee Wonjun , Kim Mun Sang
Published: April 2022

Skeleton data, which is often used in the HCI field, is a data structure that can efficiently express human poses and gestures because it consists of 3D positions of joints. The advancement of RGB-D sensors, such as Kinect sensors, enabled the easy capture of skeleton data from depth or RGB images. However, when tracking a target with a single sensor, there is an occlusion problem causing the quality of invisible joints to be randomly degraded. As a result, multiple sensors should be used to reliably track a target in all directions over a wide range. In this paper, we proposed a new method for combining multiple inaccurate skeleton data sets obtained from multiple sensors that capture a target from different angles into a single accurate skeleton data. The proposed algorithm uses density-based spatial clustering of applications with noise (DBSCAN) to prevent noise-added inaccurate joint candidates from participating in the merging process. After merging with the inlier candidates, we used Kalman filter to denoise the tremble error of the joint’s movement. We evaluated the proposed algorithm’s performance using the best view as the ground truth. In addition, the results of different sizes for the DBSCAN searching area were analyzed. By applying the proposed algorithm, the joint position accuracy of the merged skeleton improved as the number of sensors increased. Furthermore, highest performance was shown when the searching area of DBSCAN was 10 cm.
Automated Mobile Hot Mist Generator: A Quest for Effectiveness in Fruit Horticulture
Authors: Khort Dmitriy , Kutyrev Alexey , Kiktev Nikolay , Hutsol Taras , Glowacki Szymon , Kuboń Maciej , Nurek Tomasz , Rud Anatolii , Gródek-Szostak Zofia
Published: April 2022

The study relates to the use of automated plant protection systems in agriculture. The article presents a proprietary automated mobile platform with an aerosol generator of hot mist. Furthermore, the cause of the loss of a chemical preparation in the spraying of plant protection products on the tree crown was determined in the course of field research. A statistical analysis of the results of experiment was carried out and the effect of droplet size on leaf coating density was determined. The manuscript presents a diagram of the degree of penetration of the working solution as it drops into the crown of the tree, as well as a cross-sectional graph of the permeability of the spray from the projection of the fruit tree crown. The most effective modes of operation of the automated mobile platform for spraying plant protection products with a mist generator aggregate were established. Analysis of the results shows that the device meets the spraying requirements of the procedure for spraying plant protection products. The novelty of this research lies in the optimal modes identified by movement of the developed automated mobile platform and the parameters of plant treatment with protective equipment when using a hot mist generator. The following mode parameters were established: the speed of the automated platform was 3.4 km/h, the distance to the crown of the tree was 1.34 m, and the flow rate of the working fluid was 44.1 L/h. Average fuel consumption was 2.5 L/h. Effective aerosol penetration reduced the amount of working fluid used by up to 50 times.
Motion Artifacts Correction from Single-Channel EEG and fNIRS Signals Using Novel Wavelet Packet Decomposition in Combination with Canonical Correlation Analysis
Authors: Hossain Md Shafayet , Chowdhury Muhammad E. H. , Reaz Mamun Bin Ibne , Ali Sawal Hamid Md , Bakar Ahmad Ashrif A. , Kiranyaz Serkan , Khandakar Amith , Alhatou Mohammed , Habib Rumana , Hossain Muhammad Maqsud
Published: April 2022

The electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals, highly non-stationary in nature, greatly suffers from motion artifacts while recorded using wearable sensors. Since successful detection of various neurological and neuromuscular disorders is greatly dependent upon clean EEG and fNIRS signals, it is a matter of utmost importance to remove/reduce motion artifacts from EEG and fNIRS signals using reliable and robust methods. In this regard, this paper proposes two robust methods: (i) Wavelet packet decomposition (WPD) and (ii) WPD in combination with canonical correlation analysis (WPD-CCA), for motion artifact correction from single-channel EEG and fNIRS signals. The efficacy of these proposed techniques is tested using a benchmark dataset and the performance of the proposed methods is measured using two well-established performance matrices: (i) difference in the signal to noise ratio ( ) and (ii) percentage reduction in motion artifacts ( ). The proposed WPD-based single-stage motion artifacts correction technique produces the highest average  (29.44 dB) when db2 wavelet packet is incorporated whereas the greatest average  (53.48%) is obtained using db1 wavelet packet for all the available 23 EEG recordings. Our proposed two-stage motion artifacts correction technique, i.e., the WPD-CCA method utilizing db1 wavelet packet has shown the best denoising performance producing an average  and  values of 30.76 dB and 59.51%, respectively, for all the EEG recordings. On the other hand, for the available 16 fNIRS recordings, the two-stage motion artifacts removal technique, i.e., WPD-CCA has produced the best average  (16.55 dB, utilizing db1 wavelet packet) and largest average  (41.40%, using fk8 wavelet packet). The highest average  and  using single-stage artifacts removal techniques (WPD) are found as 16.11 dB and 26.40%, respectively, for all the fNIRS signals using fk4 wavelet packet. In both EEG and fNIRS modalities, the percentage reduction in motion artifacts increases by 11.28% and 56.82%, respectively when two-stage WPD-CCA techniques are employed in comparison with the single-stage WPD method. In addition, the average  also increases when WPD-CCA techniques are used instead of single-stage WPD for both EEG and fNIRS signals. The increment in both  and  values is a clear indication that two-stage WPD-CCA performs relatively better compared to single-stage WPD. The results reported using the proposed methods outperform most of the existing state-of-the-art techniques.
Olympic Cycle Comparison of the Nutritional and Cardiovascular Health Status of an Elite-Level Female Swimmer: Case Study Report from Slovenia
Authors: Jakše Boštjan , Lipošek Silvester , Zenić Nataša , Šajber Dorica
Published: April 2022

Monitoring the many aspects that are crucial to an athlete’s performance progress is vital for further training planning and for the development of performance and the sport. We evaluated a four-year change (2018 vs. 2022) in the current nutritional and cardiovascular health status of the most successful elite-level female swimmer in Slovenia. Body composition and dietary intake were assessed using dual-energy X-ray absorptiometry and a standardized food questionnaire. The concentration of blood lipids, blood pressure, and serum micronutrients (B12, 25(OH)D), potassium, calcium, phosphorus, magnesium, and iron) were measured. The four-year comparison showed an improved body composition status (i.e., increased body mass and decreased body fat (percentage and mass), increased lean soft tissue and total bone mineral density (BMD) (i.e., significantly decreased BMD of a left femoral neck and increased BMD of a spine and head)). We also measured an improvement in the cardiovascular health status of some markers (i.e., decreased total cholesterol, triglycerides, and blood pressure but increased low-density lipoprotein cholesterol), most likely due to the differences in assessed dietary intake (i.e., lower carbohydrate intake, higher total and saturated fat intake, and lower sodium intake). Notably, nutrient intakes that are generally of concern (eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), vitamin B12 and D, calcium, iron, and zinc (except for fiber intake)) were all within recommended ranges. However, the athlete’s vitamin K and potassium intake were not adequate. Furthermore, in 2018, the athlete did not consume dietary supplements, while she now regularly uses several dietary supplements, including EPA and DHA omega-3, vitamin D, multivitamins, carbohydrate powder, and sports drink. Moreover, from the micronutrient serum, only iron levels deviated from the reference values (37 μmol/L vs. 10.7–28.6 μmol/L). The presented screening example using valid, sensitive, and affordable methods and with rapid organizational implementation may be a viable format for regular monitoring.
Cooling the City? A Scientometric Study on Urban Green and Blue Infrastructure and Climate Change-Induced Public Health Effects
Authors: Capari Leo , Wilfing Harald , Exner Andreas , Höflehner Thomas , Haluza Daniela
Published: April 2022

Climate change causes global effects on multiple levels. The anthropogenic input of greenhouse gases increases the atmospheric mean temperature. It furthermore leads to a higher probability of extreme weather events (e.g., heat waves, floods) and thus strongly impacts the habitats of humans, animals, and plants. Against this background, research and innovation activities are increasingly focusing on potential health-related aspects and feasible adaptation and mitigation strategies. Progressing urbanization and demographic change paired with the climate change-induced heat island effect exposes humans living in urban habitats to increasing health risks. By employing scientometric methods, this scoping study provides a systematic bird’s eye view on the epistemic landscapes of climate change, its health-related effects, and possible technological and nature-based interventions and strategies in order to make urban areas climate proof. Based on a literature corpus consisting of 2614 research articles collected in SCOPUS, we applied network-based analysis and visualization techniques to map the different scientific communities, discourses and their interrelations. From a public health perspective, the results demonstrate the range of either direct or indirect health effects of climate change. Furthermore, the results indicate that a public health-related scientific discourse is converging with an urban planning and building science driven discourse oriented towards urban blue and green infrastructure. We conclude that this development might mirror the socio-political demand to tackle emerging climate change-induced challenges by transgressing disciplinary boundaries.
Novel Evolutionary-Optimized Neural Network for Predicting Fresh Concrete Slump
Authors: Safayenikoo Hamed , Khajehzadeh Mohammad , Nehdi Moncef L.
Published: April 2022

Accurate prediction of fresh concrete slumps is a complex non-linear problem that depends on several parameters including time, temperature, and shear history. It is also affected by the mixture design and various concrete ingredients. This study investigates the efficiency of three novel integrative approaches for predicting this parameter. To this end, the vortex search algorithm (VSA), multi-verse optimizer (MVO), and shuffled complex evolution (SCE) are used to optimize the configuration of multi-layer perceptron (MLP) neural network. The optimal complexity of each model was appraised via sensitivity analysis. Various statistical metrics revealed that the accuracy of the MLP was increased after coupling it with the above metaheuristic algorithms. Based on the obtained results, the prediction error of the MLP was decreased by up to 17%, 10%, and 33% after applying the VSA, MVO, and SCE, respectively. Moreover, the SCE emerged as the fastest optimizer. Accordingly, the novel explicit formulation of the SCE-MLP was introduced as a capable model for the practical estimation of fresh concrete slump, which can assist in project planning and management.
Individual Momentary Experiences of Neighborhood Public Spaces: Results of a Virtual Environment Based Stated Preference Experiment
Authors: Zhao Yuwen , van den Berg Pauline E. W. , Ossokina Ioulia V. , Arentze Theo A.
Published: April 2022

Although it has become increasingly recognized that the spatial design of public space plays an important role in the perceived quality of the built environment by users, there is still little known about the influences of specific attributes on individuals’ experiences. Therefore, this study aims at (1) identifying the factors underlying momentary experiences in public space given both cognitive (satisfaction) and affective (emotion) responses and (2) understanding the experiences as a function of green and design attributes and analyzing the heterogeneity in preferences. To achieve the research goals, this study innovatively introduced an online video-based stated preference experiment. A national sample of 316 individuals from the Netherlands were invited to complete the experiment. The results of a factor analysis indicate that the momentary experiences of the environments presented can be reduced to a single preference dimension capturing the cognitive as well as affective elements of experiences. The results of a latent class regression analysis furthermore show that there is substantial heterogeneity on how attributes are experienced. Three classes emerge which differ in terms of satisfaction with life and satisfaction with availability of green in the current living environment on dwelling, neighborhood, and city level. Presence of trees, vertical green on façades, and grass surfaces were found to be most important for individuals’ experiences generally. The paper provides a new understanding of how spatial attributes in neighborhood public spaces can influence individuals’ momentary experiences. For cities pursuing both greenification and densification, this study offers quantitative evidence to support the selection of design attributes of neighborhood public spaces which can evoke positive experiences.
Optimization of Water and Energy Spatial Patterns in the Cascade Pump Station Irrigation District
Authors: Bai Chen , Yao Lixiao , Wang Cheng , Zhao Yongxuan , Peng Weien
Published: April 2022

Cascade pump station irrigation districts (CPSIDs) consume large quantities of water and energy. Water- and energy-saving results and income increases are guaranteed under the sustainable development of the CPSID. The CPSID is divided into several sub-districts based on the elevation difference of topography and pump station distributions. The spatial patterns of crops and irrigation technologies can be changed by adjusting crop planting structures and developing drip irrigation in each sub-district. Its optimization will change the spatial patterns of irrigation water and energy consumption to achieve water- and energy-saving results, increase income, and provide an ecological advantage. To obtain the optimal spatial patterns of water and energy in the CPSID, a multi-objective linear programming model of minimum irrigation water consumption, minimum energy consumption, and highest crop output value was established. This model was applied to the Jingdian Phase I Irrigation District in northwest China, and an optimal scheme of water and energy spatial patterns was obtained. Compared with the present situation, the optimal scheme could save water by 26.18%, save energy by 29.38%, and increase income by 29.55%. The increased investment in the drip irrigation project would lead to reduced irrigation water and energy consumption and increased crop output value. The research results provide a scientific basis for the sustainable development of agriculture and ecological environment protection in the CPSID.
Assessing the Benefit of Adopting ERP Technology and Practicing Green Supply Chain Management toward Operational Performance: An Evidence from Indonesia
Authors: Santoso Ruben Wahyu , Siagian Hotlan , Tarigan Zeplin Jiwa Husada , Jie Ferry
Published: April 2022

The recent concern on the environmental protection and COVID-19 issue is increasingly affecting the manufacturing industry. This research assessing the benefit of adopting ERP technology and practicing green supply chain management toward operational performance in manufacturing industry. The study is essential to provide insight for the manufacturing industry regarding the consequences and benefits of practicing the green supply chain and adopting ERP technology amid the current constraints of the environmental protection issue and the COVID-19 pandemic. The study has surveyed 122 companies domiciled in Indonesia. Data collection used a questionnaire designed with a seven-point Likert scale. Questionnaire created in Google form, printed and distributed using social media and postal mail. Data analysis used SmartPLS software version 3.0. The result revealed that ERP adoption enables green purchasing, production, distribution, and operational performance. Furthermore, operating performance is directly affected by green purchasing and green production. However, operating performance was not supported by green distribution. In addition, ERP adoption indirectly improves operational performance through green purchasing and green production. But ERP adoption did not affect operational performance through green distribution. This result provides essential insight for the manager in the manufacturing industry that adopting ERP in the era of the COVID-19 pandemic and practicing environmental protection such as green purchasing, green production enhances operational performance. In summary, the result of this study encourages the practitioner to adopt environmental protection in running their business since it benefits the company. While there are very few studies examining the relationship between ERP adoption, green supply chain practices, and operational performance, this study is essential in terms of exploring the mediating role of green supply chain practices on the effect of ERP adoption on operational performance. Thus, these research findings could enrich the current research in the supply chain management context.