bluuebunny/crossref_metadata_2025 huggingface dataset:
Virtual and Augmented Reality Applied to the Perception of the Sound and Visual Garden
Authors: Hurtado Soler Amparo , Botella Nicolás Ana María , Martínez Gallego Silvia
Published: May 2022

The COVID-19 situation has encouraged the creation of ICT-based learning environments. Difficulties in performing activities in a garden setting can be overcome by using Virtual Reality (VR) and Augmented Reality (AR). The aim of this research is to evaluate the usefulness of VR and AR as an educational resource through contextualised sensory experiences in the garden. Eighty-seven trainee teachers took part, and a mixed methodology was used, for the analysis of the sound and visual elements of the garden and for reflection on the usefulness of VR and AR. An interpretive and inferential analysis of the AR-based compositions was carried out and of the drawings of the garden created by the participants after the virtual immersion. The results show a bucolic-pastoral vision of the garden with a predominance of natural elements and a human presence that is respectful of the natural environment. During the immersion, >90% of the participants indicated that the sensations were positive and were able to distinguish natural components from human and/or technological items. The role of VR and AR in enhancing the understanding of content is notable, being, at the same time, tool, resource and content, which reinforces the idea that they can favour the development of teaching and digital competences.
Multi-Site and Multi-Scale Unbalanced Ship Detection Based on CenterNet
Authors: Zhang Feihu , Hou Xujia
Published: May 2022

Object detection plays an essential role in the computer vision domain, especially the machine learning-based approach, which has developed rapidly in the past decades. However, the development of convolutional neural networks in the marine field is relatively slow, such as in ship classification and tracking. In this paper, ship detection is considered as a central point classification and regression task but discards the non-maximum suppression operation. We first improved the deep layer aggregation network to enhance the feature extraction capability of tiny targets, then reduced the number of parameters through the lightweight convolution module, and finally employed a unique activation function to enhance the nonlinearity of the model. By doing this, the improved network not only suits unbalanced sample ratios in classifying, but is more robust in scenarios where both the number and resolution of samples are unstable. Experimental results demonstrate that the proposed approach obtains outstanding performance and especially suits tiny object detection compared with current advanced methods. Furthermore, in contrast to the original CenterNet framework, the mAP of the proposed approach increased by 5.6%.
Segmentation of Echocardiography Based on Deep Learning Model
Authors: Huang Helin , Ge Zhenyi , Wang Hairui , Wu Jing , Hu Chunqiang , Li Nan , Wu Xiaomei , Pan Cuizhen
Published: May 2022

In order to achieve the classification of mitral regurgitation, a deep learning network VDS-UNET was designed to automatically segment the critical regions of echocardiography with three sections of apical two-chamber, apical three-chamber, and apical four-chamber. First, an expert-labeled dataset of 153 echocardiographic videos and 2183 images from 49 subjects was constructed. Then, the convolution layer in the VGG16 network was used to replace the contraction path in the original UNet network to extract image features, and depth supervision was added to the expansion path to achieve the segmentation of LA, LV, and MV. The results showed that the Dice coefficients of LA, LV, and MV were 0.935, 0.915, and 0.757, respectively. The proposed deep learning network can achieve simultaneous and accurate segmentation of LA, LV, and MV in multi-section echocardiography, laying a foundation for quantitative measurement of clinical parameters related to mitral regurgitation.
Target Location Method Based on Compressed Sensing in Hidden Semi Markov Model
Authors: Tian Xin , Wei Guoliang , Wang Jianhua
Published: May 2022

A compressive sensing-based target localization method based on hidden semi-Markov model (HsMM) is proposed to address problems like unpredictable data and the multipath effect of the Receive Signal Strength (RSS) in indoor localization. The method can achieve both coarse and precise positioning by combining HsMM and the compressive sensing algorithm. Firstly, the hidden semi-Markov model is introduced to complete the coarse positioning of the target, and a parameter training method is proposed; secondly, the Davies-Bouldin Index and the Calinski-Harabasz Index based on the Euclidean distance and on the proposed connection distance herein are introduced; then, on the basis of coarse positioning, a precise positioning method based on compressive sensing is proposed; in the compressive sensing method, Gaussian matrix is introduced and a selection method of two screening matrices of the deterministic matrix is proposed; finally, the performance of coarse positioning is verified by experimental data for Hidden Markov Model (HMM) and HsMM, respectively, and the performance of the compressive sensing algorithm based on the two screening matrices of Gaussian matrix and deterministic matrix is respectively verified; the effectiveness of the proposed algorithm is experimentally verified.
Developing Cybersecurity Systems Based on Machine Learning and Deep Learning Algorithms for Protecting Food Security Systems: Industrial Control Systems
Authors: Alkahtani Hasan , Aldhyani Theyazn H. H.
Published: May 2022

Industrial control systems (ICSs) for critical infrastructure are extensively utilized to provide the fundamental functions of society and are frequently employed in critical infrastructure. Therefore, security of these systems from cyberattacks is essential. Over the years, several proposals have been made for various types of cyberattack detection systems, with each concept using a distinct set of processes and methodologies. However, there is a substantial void in the literature regarding approaches for detecting cyberattacks in ICSs. Identifying cyberattacks in ICSs is the primary aim of this proposed research. Anomaly detection in ICSs based on an artificial intelligence algorithm is presented. The methodology is intended to serve as a guideline for future research in this area. On the one hand, machine learning includes logistic regression, k-nearest neighbors (KNN), linear discriminant analysis (LDA), and decision tree (DT) algorithms, deep learning long short-term memory (LSTM), and the convolution neural network and long short-term memory (CNN-LSTM) network to detect ICS malicious attacks. The proposed algorithms were examined using real ICS datasets from the industrial partners Necon Automation and International Islamic University Malaysia (IIUM). There were three types of attacks: man-in-the-middle (mitm) attack, web-server access attack, and telnet attack, as well as normal. The proposed system was developed in two stages: binary classification and multiclass classification. The binary classification detected the malware as normal or attacks and the multiclass classification was used for detecting all individual attacks. The KNN and DT algorithms achieved superior accuracy (100%) in binary classification and multiclass classification. Moreover, a sensitivity analysis method was presented to predict the error between the target and prediction values. The sensitivity analysis results showed that the KNN and DT algorithms achieved R2 = 100% in both stages. The obtained results were compared with existing systems; the proposed algorithms outperformed existing systems.
Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review
Authors: Luzi Giovanni , McHardy Christopher
Published: May 2022

Computational Fluid Dynamics (CFD) have been frequently applied to model the growth conditions in photobioreactors, which are affected in a complex way by multiple, interacting physical processes. We review common photobioreactor types and discuss the processes occurring therein as well as how these processes have been considered in previous CFD models. The analysis reveals that CFD models of photobioreactors do often not consider state-of-the-art modeling approaches. As a comprehensive photobioreactor model consists of several sub-models, we review the most relevant models for the simulation of fluid flows, light propagation, heat and mass transfer and growth kinetics as well as state-of-the-art models for turbulence and interphase forces, revealing their strength and deficiencies. In addition, we review the population balance equation, breakage and coalescence models and discretization methods since the predicted bubble size distribution critically depends on them. This comprehensive overview of the available models provides a unique toolbox for generating CFD models of photobioreactors. Directions future research should take are also discussed, mainly consisting of an extensive experimental validation of the single models for specific photobioreactor geometries, as well as more complete and sophisticated integrated models by virtue of the constant increase of the computational capacity.
Multi-Type Hydrocarbon Accumulation Mechanism in the Hari Sag, Yingen Ejinaqi Basin, China
Authors: Peng Biao , Zhang Lulu , Li Jianfeng , Chang Tiantian , Zhang Zheng
Published: May 2022

With the successful development of unconventional hydrocarbons, the production of unconventional hydrocarbons has increased rapidly. However, a single conventional or unconventional model is not suitable for the mechanism of hydrocarbon accumulation in a given basin or sag. Based on data from drilling, logging, and geophysical analysis, the hydrocarbon accumulation mechanism in the Hari sag in the Yingen-Ejinaqi basin, China, was analyzed. There are three sets of source rocks in the Hari sag: the K1y source rocks were evaluated as having excellent source rock potential with low thermal maturity and kerogen Type I-II1; the K1b2 source rocks were evaluated as having good source rock potential with mature to highly mature stages and kerogen Type II1-II2; and the K1b1 source rocks were evaluated as having moderate source rock potential with mature to highly mature stages and kerogen Type II1-II2. Reservoir types were found to be conventional sand reservoirs, unconventional carbonate-shale reservoirs, and volcanic rock reservoirs. There were two sets of fault-lithologic traps in the Hari sag, which conform to the intra-source continuous hydrocarbon accumulation model and the approaching-source discontinuous hydrocarbon accumulation model. The conclusions of this research provide guidance for exploring multi-type reservoirs and multi-type hydrocarbon accumulation models.
Comparison between Space Mapping and Direct FEA Optimizations for the Design of Halbach Array PM Motor
Authors: Pérez Ramón , Pelletier Alexandre , Grenier Jean-Michel , Cros Jérôme , Rancourt David , Freer Richard
Published: May 2022

Effective methods for the design of high-performance electrical machines must use optimization techniques and precise and fast physical models. Convergence, precision and speed of execution are important issues, in addition to the ability to explore the entire domain of solutions. The finite element method (FEM) presents a high accuracy in the results but with high computational costs. Analytical models, on the other hand, solve the problem quickly but compromise the accuracy of the results. This work shows a comparison between an optimization made with an analytical electromagnetic model and a direct optimization with finite element field calculation for the optimal design of a Halbach array permanent magnet synchronous motor (PMSM). In the case of the analytical model, it is necessary to use an iterative method of correcting the model to obtain a valid solution. This method is known as Space Mapping (SM) and the analytical model can be improved with a reduced number of iterations with the FEM. The results show a rapid convergence towards an optimal solution for the SM, with more than 78% reduction in computational cost compared to a Direct FEM optimization. Both solutions have only a difference of 3% on the power density, which indicates that FEM does not improve the results obtained by SM. This represents a great advantage that allows for the consideration of a large amount of designs to analyze the domain of solutions in more detail. This study also shows that SM is a powerful method to optimize the power density or torque density of electrical machines.
Fuzzy Bang-Bang Relay Control of a Rigid Rotor Supported by Active Magnetic Bearings
Authors: Nagi Farrukh Hafiz , Inayat-Hussain Jawaid Iqbal , Ahmed Syed Khaleel
Published: May 2022

Active magnetic bearings, which are open-loop and unstable, require a feedback control system to ensure stable operation of the rotating machines that they support. Proportional-integral-derivative (PID) controllers are widely used in field applications of these bearings for this purpose. PID controllers are designed to work effectively within the linear region of operation of the rotating machines. Due to the inherent nonlinearity of the active magnetic bearings, large unbalance forces that may occur in these machines result in nonlinear vibration responses. Therefore, the PID controller’s effectiveness to control the vibration of the rotating machines is considerably reduced when the unbalance forces in these machines become large. Other control strategies, such as the fuzzy logic and the sliding mode control schemes, are more apt to deal with the nonlinear responses of the rotating machines supported by active magnetic bearings. The present work proposes an integrated fuzzy bang-bang relay controller for a rigid rotor mounted on active magnetic bearings. The effectiveness of this controller to suppress rotor vibrations is examined numerically. Performance comparison of this controller with the conventional fuzzy logic and PD controllers are made for different initial conditions, rotor imbalance magnitudes, and rotor angular speeds. At extreme operating conditions due to large rotor unbalance forces, where the magnetic bearings are highly nonlinear, the proposed integrated fuzzy bang-bang relay controller proved to be more superior over the conventional fuzzy logic and PD controllers.
Dynamic Performance Evaluation of the Secondary Control in Islanded Microgrids Considering Frequency-Dependent Load Models
Authors: Rios Miguel Angel , Pérez-Londoño Sandra , Garcés Alejandro
Published: May 2022

Performance analysis is challenging in modern power distribution networks due to the increasing penetration of distributed energy resources (DERs) interfaced by voltage source converters (VSCs). Parameter uncertainty, black-box models of the components, and low inertia are some of the issues that must be addressed. The latter can represent high vulnerabilities to sudden load changes in a microgrid (MG). Additionally, the islanded operation represents a challenge for inverter-based (DERs), where secondary control must regulate the microgrid frequency and voltage to its nominal values. When a secondary control strategy is implemented, it is necessary to validate its performance under several conditions. Most existing research papers focus on the microgrid’s small-signal and transient stability. At the same time, little has been done on the influence of the load model on voltage stability. This type of analysis is required to ensure an adequate transition between the grid-connected and stand-alone modes. This paper provides a voltage stability analysis of a microgrid, considering secondary control based on receding horizon and frequency-dependent load models. Simulation results demonstrate the robust performance of the secondary control and validate the importance of considering or adapting voltage stability indices to ensure adequate microgrid performance.
Possible Pathways toward Carbon Neutrality in Thailand’s Electricity Sector by 2050 through the Introduction of H2 Blending in Natural Gas and Solar PV with BESS
Authors: Diewvilai Radhanon , Audomvongseree Kulyos
Published: May 2022

To avoid the potential adverse impacts of climate change from global warming, it is suggested that the target of net zero emissions should be reached by this mid-century. Thailand is aiming to achieve carbon neutrality by 2050. Since electricity generation is one of the largest producers of carbon dioxide emission, the associated emissions must be greatly reduced to achieve the targets mentioned above. Thus, new generation expansion plans must be well developed. This paper discusses the development of generation expansion plans considering Thailand’s latest policies along with enhancement of the existing multi-period linear programming model, allowing new electricity generation technologies having low emissions, e.g., solar PV with battery and hydrogen blending in natural gas, to be integrated into generation expansion planning. Then, four generation expansion plans with different levels of hydrogen blending in natural gas are proposed and discussed. It is found that Thailand can achieve carbon neutrality by 2050 by promoting more use of renewable energy altogether with trade-off between land for solar PV installation and amount of hydrogen blended in natural gas. The lesson learned from this study provides crucial information about possible pathways to achieve carbon neutrality in the electricity sector for policy makers in other countries.
A Self-Tuning LCC/SP System for Electric Vehicle Wireless Charging against Large Self- and Mutual Inductance Variations
Authors: Zhao Yiyan , Wei Xuezhe , Luo Zhichao , Xiong Meng , Dai Haifeng
Published: May 2022

An LCC/SP self-tuning wireless charging system is proposed herein for use in a wireless charging test bench. With different dislocations in addition to changes in the coil self-inductance and mutual inductance caused by different secondary magnetic shielding materials, the system can ensure that the high power factor of the primary side remains unchanged without changing the circuit topology. Based on this normalized detuning LCC/SP circuit model, a switch-controlled capacitor (SCC) self-tuning method based on PI control is proposed. The control scheme employs only two MOSFETs and capacitors, without WIFI communication or parameter identification. A 2 kW experimental device was set up in the laboratory, and experimental verification was carried out with large-scale dislocations and different secondary magnetic shielding materials. The experimental results confirm that the system can maintain a high power factor (>0.9) under a system mutual inductance variation of 47.7% and secondary coil self-inductance variation of 12%, and that it can be applied in electric vehicle wireless chargers or high-power wireless charger test benches.
Development of Fault Diagnosing System for Ice-Storage Air-Conditioning Systems
Authors: Tien Ching-Jui , Yang Chung-Yuen , Tsai Ming-Tang , Gow Hong-Jey
Published: May 2022

This paper proposes a fault diagnosing system for the Ice-Storage Air-Conditioning System (ISACS) to supervise the operation conditions of the brine chillers. Combining the Radial Basis Function Network (RBFN) and Robust Quality Design (RQD), an Enhanced RBFN (ERBFN) is proposed to pursue fast and accurate fault diagnosis. The RQD method is used to adjust the parameters in the RBFN training stage to improve the searching ability, and good performance with a close spike tracking capability can be seen. The efficiency of the brine chiller in the ISACS was considered as the quality characteristics, the values measured by all instruments were considered as control factors, and noise factors were abnormal variable control factors in the system. ERBFN can improve the efficiency of the ISACS and prevent the equipment from being damaged without warning. ERBFN is used for fault diagnosis to ensure the ISACS performance is normal. Experimental results are provided to show the effectiveness of the proposed method. The new artificial neural network algorithm proposed in this paper was successfully applied to the fault diagnosis of ISACS. It not only provides a reference for enterprises but can also be applied to studies on other topics in the future.
Transcriptome Analysis of Response to Aluminum Stress in Pinus massoniana
Authors: Wang Ting , Hu Ying , Chen Hu , Tan Jianhui , Xu Huilan , Li Peng , Wu Dongshan , Jia Jie , Yang Zhangqi
Published: May 2022

Pinus massoniana is a vital kind of coniferous species rich in rosin. Aluminum stress is a severe problem for P. massoniana growth in acidic soil causing root poisoning. However, the molecular mechanisms of aluminum-responsive are still unclear. We performed a transcriptome analysis of the P. massoniana root in response to aluminum stress. Through WGCNA analysis, we identified 338 early and 743 late response genes to aluminum stress. Gene Ontology analysis found many critical functional pathways, such as carbohydrate binding, cellulase activity, and phenylalanine ammonia-lyase activity. In addition, KEGG analysis revealed a significant enrichment of phenylpropanoid biosynthesis pathways. Further analysis showed that the expression of lignin synthesis genes 4CL, CAD, and COMT were up-regulated, indicating that they may play a crucial role in the process of aluminum tolerance in P. massoniana roots. These results provide method support for studying the regulation mechanism of P. massoniana aluminum stress.
Defoliation-Induced Growth Reduction of Pinus sylvestris L. after a Prolonged Outbreak of Diprion pini L.—A Case Study from Eastern Finland
Authors: Blomqvist Minna , Lyytikäinen-Saarenmaa Päivi , Kosunen Maiju , Kantola Tuula , Holopainen Markus
Published: May 2022

The frequency and intensity of insect outbreaks have increased in boreal forests, along with associated impacts on the growth and economic losses of host trees. In Finland, the common pine sawfly (Diprion pini L.) is a serious pest, causing declines in health and growth responses of Scots pine (Pinus sylvestris L.). We focused on investigating the species’ defoliating impact on tree radial and volume growth and estimated the economic value of the declined growth. Managed P. sylvestris forests in our study area in eastern Finland have suffered from extended defoliation by D. pini for 15 years since 1999 at varying intensity levels. We classified 184 trees into four defoliation classes and compared annual growth, expressed as growth indices between the classes. We modelled tree volume, estimated economic loss, and compared those to a reference period preceding the initial outbreak. We found significant differences in growth indices between the defoliation classes. Growth losses of 4.2%, 20.8%, and 40.4% were obtained for the mild, moderate, and high defoliation classes, with related economic impacts of 51 €, 272 €, and 734 € per ha for 11 years, respectively. Growth was slightly enhanced in the lowest defoliation class. We suggest that growth-related economic loss caused by D. pini may be significant and depend on defoliation intensity and outbreak duration.
A Single Catalytic Endolysin Domain Plychap001: Characterization and Application to Control Vibrio parahaemolyticus and Its Biofilm Directly
Authors: Wang Luokai , Ju Xiaochen , Cong Yu , Lin Hong , Wang Jingxue
Published: May 2022

Endolysins are enzymes used by bacteriophages to cleave the host cell wall in the final stages of the lytic cycle. As such, they are considered promising antibacterial agents for controlling and combating multidrug-resistant (MDR) bacteria. However, the application of endolysins targeting Gram-negative bacteria is greatly hindered by the outer membrane on these bacteria. Lysqdvp001, an endolysin with modular structure, has been reported as one of the most efficient endolysins against the Gram-negative bacterium Vibrio parahaemolyticus. In this study, Plychap001, the truncated recombinant catalytic domain of Lysqdvp001, was demonstrated to exhibit a direct and efficient bactericidal activity against broad spectrum of V. parahaemolyticus strains. Plychap001 was shown to be highly stable and retain high bactericidal activity at high temperatures, over a wide pH range, and at high NaCl concentrations. Plychap001 also exhibited a synergistic lytic effect with EDTA. Additionally, Plychap001 was found to efficiently degrade and eliminate V. parahaemolyticus biofilms on polystyrene surfaces. Our study establishes Plychap001 as a promising method for controlling V. parahaemolyticus in the food industry.
Lactic Acid Bacteria—Ensuring a Safe, Healthy Food Supply for Humankind since the Dawn of Our Civilization
Authors: Dapkevicius Maria L. N. E.
Published: May 2022

Lactic acid bacteria (LAB) are part of the microbiota that inhabit several environmental niches, including foods and the gastrointestinal tract of animals and humans [...]
Development of Healthy Vegan Bonbons Enriched with Lyophilized Peach Powder
Authors: Mihaylova Dasha , Popova Aneta , Goranova Zhivka , Doykina Pavlina
Published: May 2022

Changing nutritional demands, in combination with the global trend for snacking, sets a goal for preparing food products for direct consumption with certain beneficial properties. This study was designed to investigate the quality characteristics of raw vegan bonbons enriched with lyophilized peach powder. Three types of formulations were prepared in which 10%, 20%, and 30% of lyophilized peach powder were, respectively, added. The newly developed vegan products were characterized in terms of their physical (moisture, ash, color, water activity), microbiological, and nutritional characteristics. Their antioxidant activity, flavonoid, and phenolic content were also evaluated. Considering the content of the bonbons, the reported health claims indicate that they are sources of fiber, with no added sugar, and contain naturally occurring sugars. The color measurements demonstrated similarity in the values. This study showed that there is significant potential in the production of healthy snacks for direct consumption, with beneficial properties.
Antioxidant, Antihypertensive, Hypoglycaemic and Nootropic Activity of a Polyphenolic Extract from the Halophyte Ice Plant (Mesembryanthemum crystallinum)
Authors: Calvo Marta María , Martín-Diana Ana Belén , Rico Daniel , López-Caballero María Elvira , Martínez-Álvarez Oscar
Published: May 2022

This study aims to determine the potential antioxidant, antihypertensive, hypoglycaemic and nootropic activity of a purified polyphenolic extract from the halophyte ice plant (Mesembryanthemum crystallinum). The ice plant extract showed good antioxidant activity measured by DPPH, ORAC, TEAC, FRAP and ferrous ion chelating activity. Moreover, the extract showed potent ACE, DPP-IV and PEP-inhibitory activity (90.5%, 98.6% and 73.1%, respectively, at a final concentration of 1 mg/mL). The extract was fractionated and the fraction with the highest content of total phenolic compounds showed the highest bioactivity, suggesting that polyphenols could be mainly responsible for the abovementioned activities. The tentative polyphenol identification by HPLC-ESI-QTOF-MS in this fraction revealed that flavones (>65%) are the major group, with apigenin (38%) predominating, followed by diosmin (17.7%) and luteolin (11.9%). They could presumably be the main elements responsible for the enzymatic inhibition activity. Additionally, 4-hydroxybenzoic acid, p-coumaric acid and a hydroxycinnamic acid derivative (2-O-(p-cumaroyl)-l-malic acid) were found in the extract. To our knowledge, this is the first time that some of these activities have been reported for halophyte extracts.
A New Fifth-Order Finite Difference Compact Reconstruction Unequal-Sized WENO Scheme for Fractional Differential Equations
Authors: Zhang Yan , Zhu Jun
Published: May 2022

This paper designs a new finite difference compact reconstruction unequal-sized weighted essentially nonoscillatory scheme (CRUS-WENO) for solving fractional differential equations containing the fractional Laplacian operator. This new CRUS-WENO scheme uses stencils of different sizes to achieve fifth-order accuracy in smooth regions and maintain nonoscillatory properties near discontinuities. The fractional Laplacian operator of order β(0<β<1) is split into the integral part and the first derivative term. Using the Gauss–Jacobi quadrature method to solve the integral part of the fractional Laplacian operators, a new finite difference CRUS-WENO scheme is presented to discretize the first derivative term of the fractional equation. This new CRUS-WENO scheme has the advantages of a narrower large stencil and high spectral resolution. In addition, the linear weights of the new CRUS-WENO scheme can be any positive numbers whose sum is one, which greatly reduces the calculation cost. Some numerical examples are given to show the effectiveness and feasibility of this new CRUS-WENO scheme in solving fractional equations containing the fractional Laplacian operator.
Identification and Regulatory Network Analysis of Genes Related to Reproductive Performance in the Hypothalamus and Pituitary of Angus Cattle
Authors: Huang Yuwen , Yuan Chenfeng , Zhao Yun , Li Chunjin , Cao Maosheng , Li Haobang , Zhao Zijiao , Sun Ao , Basang Wangdui , Zhu Yanbin , Chen Lu , He Fang , Huan Cheng , Zhang Boqi , Iqbal Tariq , Wei Yamen , Fan Wenjing , Yi Kangle , Zhou Xu
Published: May 2022

In this study, we explored the gene expression patterns of the pituitary gland and hypothalamus of Angus cows at different growth and developmental stages by deep sequencing and we identified genes that affect bovine reproductive performance to provide new ideas for improving bovine fertility in production practice. We selected three 6-month-old (weaning period), three 18-month-old (first mating period), and three 30-month-old (early postpartum) Angus cattle. The physiological status of the cows in each group was the same, and their body conformations were similar. After quality control of the sequencing, the transcriptome analyses of 18 samples yielded 129.18 GB of clean data. We detected 13,280 and 13,318 expressed genes in the pituitary gland and hypothalamus, respectively, and screened 35 and 50 differentially expressed genes (DEGs) for each, respectively. The differentially expressed genes in both tissues were mainly engaged in metabolism, lipid synthesis, and immune-related pathways in the 18-month-old cows as compared with the 6-month-old cows. The 30-month-old cows presented more regulated reproductive behavior, and pituitary CAMK4 was the main factor regulating the reproductive behavior during this period via the pathways for calcium signaling, longevity, oxytocin, and aldosterone synthesis and secretion. A variant calling analysis also was performed. The SNP inversions and conversions in each sample were counted according to the different base substitution methods. In all samples, most base substitutions were represented by substitutions between bases A and G, and the probability of base conversion exceeded 70%, far exceeding the transversion. Heterozygous SNP sites exceeded 37.68%.
Exploring the Core Genes of Schizophrenia Based on Bioinformatics Analysis
Authors: Feng Shunkang , Sun Ping , Qu Chunhui , Wu Xiaohui , Yang Lu , Yang Tao , Wang Shuo , Fang Yiru , Chen Jun
Published: May 2022

Schizophrenia is a clinical syndrome composed of a group of symptoms involving many obstacles such as perception, thinking, emotion, behavior, and the disharmony of mental activities. Schizophrenia is one of the top ten causes of disability globally, accounting for about 1% of the global population. Previous studies have shown that schizophrenia has solid genetic characteristics. However, the diagnosis of schizophrenia mainly depends on symptomatic manifestations, and no gene can be used as a clear diagnostic marker at present. This study explored the hub genes of schizophrenia by bioinformatics analysis. Three datasets were selected and downloaded from the GEO database (GSE53987, GSE21138, and GSE27383). GEO2R, NCBI’s online analysis tool, is used to screen out significant gene expression differences. The genes were functionally enriched by GO and KEGG enrichment analysis. On this basis, the hub genes were explored through Cytoscape software, and the immune infiltration analysis and diagnostic value of the screened hub genes were judged. Finally, four hub genes (NFKBIA, CDKN1A, BTG2, GADD45B) were screened. There was a significant correlation between two hub genes (NFKBIA, BTG2) and resting memory CD4 T cells. The ROC curve results showed that all four hub genes had diagnostic value.
Patient Judgement of Change with Elective Surgery Correlates with Patient Reported Outcomes and Quality of Life
Authors: Morris Meg E. , Atkinson Victoria , Woods Jeffrey , Myles Paul S. , Hodge Anita , Jones Cathy H. , Lloyd Damien , Rovtar Vincent , Clifford Amanda M. , Brusco Natasha K.
Published: May 2022

Obtaining pre-surgery PROM measures is not always feasible. The aim of this study was to examine if self-reports of change following elective surgery correlate with change scores from a validated PROM (15-item Quality of Recovery (QoR-15)). This cross-sectional study across 29 hospitals enrolled elective surgery patients. PROMs were collected one-week pre-surgery, as well as one- and four-weeks post-surgery via an electronic survey. We examined associations between patient “judgement of change” at one and four-weeks after surgery and the actual pre-to post-surgery PROM change scores. A total of 4177 surveys were received. The correlation between patient judgement of change, and the actual change score was moderately strong at one-week (n = 247, rs = 0.512, p < 0.001), yet low at four-weeks (n = 241, rs = 0.340, p < 0.001). Patient judgement was aligned to the direction of the PROM change score from pre- to post-surgery. We also examined the correlation between the QoR-15 (quality of recovery) and the EQ-5D-5L (QOL). There was a moderately strong positive correlation between the two PROMs (n = 356, rs = 0.666, p < 0.001), indicating that change in quality of recovery was related to change in QOL. These findings support the use of a single “judgement of change” recall question post-surgery.
Individual Stress Burden and Mental Health in Health Care Workers during the COVID-19 Pandemic: Moderating and Mediating Effects of Resilience
Authors: Schmuck Jonas , Hiebel Nina , Kriegsmann-Rabe Milena , Schneider Juliane , Matthias Julia-Katharina , Erim Yesim , Morawa Eva , Jerg-Bretzke Lucia , Beschoner Petra , Albus Christian , Weidner Kerstin , Radbruch Lukas , Hauschildt Eberhard , Geiser Franziska
Published: May 2022

Introduction: The COVID-19 pandemic generated a significant burden on the German health care system, affecting the mental health of health care workers (HCW) in particular. Resilience may serve as an essential protective factor for individuals’ well-being. Objective: Our objective was to identify demographic and work-related correlates of individual resilience and to investigate the association between pandemic-related stress, resilience and mental health using different resilience models. Methods: Our sample comprised 1034 German HCW in different medical professions who completed an online survey from 20 April to 1 July 2020. Resilience was assessed using the Resilience Scale-5 (RS-5). The pandemic-related self-reported stress burden was captured by a single item, while depression and anxiety symptoms were measured with the PHQ-2 and GAD-2, respectively. Additionally, various sociodemographic and work-related factors were assessed. Results: Overall, we found high levels of resilience in the sample compared to a German sample before the pandemic, which were significantly associated only with the older age of participants and having children in both univariate and multivariate analyses. Regarding mechanisms of resilience, moderation analysis revealed that low individual resilience and high pandemic-related stress burden independently contributed to both anxiety and depression symptoms while resilience additionally moderated the relationship between stress burden and anxiety symptoms. The link between self-reported stress burden and mental health symptoms was also partially mediated by individual resilience. Conclusion: Taken together, the findings based on the present sample during the COVID-19 pandemic suggest that resilience plays a central role in the mental health of healthcare workers and that resilience-building interventions should be expanded, especially with a focus on younger employees.
Formative Assessment to Improve Cancer Screenings in American Indian Men: Native Patient Navigator and mHealth Texting
Authors: Batai Ken , Sanderson Priscilla R. , Joshweseoma Lori , Burhansstipanov Linda , Russell Dana , Joshweseoma Lloyd , Hsu Chiu-Hsieh
Published: May 2022

Cancer screening rates among American Indian men remain low, without programs specifically designed for men. This paper describes the Community-Based Participatory Research processes and assessment of cancer screening behavior and the appropriateness of the mHealth approach for Hopi men’s promotion of cancer screenings. This Community-Based Participatory Research included a partnership with H.O.P.I. (Hopi Office of Prevention and Intervention) Cancer Support Services and the Hopi Community Advisory Committee. Cellular phone usage was assessed among male participants in a wellness program utilizing text messaging. Community surveys were conducted with Hopi men (50 years of age or older). The survey revealed colorectal cancer screening rate increased from 51% in 2012 to 71% in 2018, while prostate cancer screening rate had not changed (35% in 2012 and 37% in 2018). Past cancer screening was associated with having additional cancer screening. A cellular phone was commonly used by Hopi men, but not for healthcare or wellness. Cellular phone ownership increased odds of prostate cancer screening in the unadjusted model (OR 9.00, 95% CI: 1.11–73.07), but not in the adjusted model. Cellular phones may be applied for health promotion among Hopi men, but use of cellular phones to improve cancer screening participation needs further investigation.
Effects of 8-Week In-Season Contrast Strength Training Program on Measures of Athletic Performance and Lower-Limb Asymmetry in Male Youth Volleyball Players
Authors: Mesfar Abdeltif , Hammami Raouf , Selmi Walid , Gaied-Chortane Sabri , Duncan Michael , Bowman Thomas G. , Nobari Hadi , van den Tillaar Roland
Published: May 2022

Strength training using high and lower load such as contrast training (CST) seems to be beneficial as it addresses larger adaptive reserves in youth athletes. Therefore, the aim of this study was to investigate the effects of CST on dynamic balance (composite score during dynamic balance test (CS-YBT)), one repetition maximum lower-limb back squat (1RM), jumping performance (single-leg hop (SLH) or countermovement jump height (CMJ)), lower-limb asymmetry (predicted from the single-leg jump performance between two legs [ILA]) in elite youth male volleyball players. Thirty-one male youth volleyball players aged 14 years were randomly assigned to a CST group (n = 16) or a control group (n = 15). The tests were performed before and after 8 weeks of training. Significant group × time interactions was observed for CS-YBT [p < 0.001, ηp2 = 0.70], 1RM [p < 0.001, ηp2 = 0.95], SLH with right and left leg [p < 0.001, ηp2 = 0.69 and 0.51], CMJ [p < 0.001, ηp2 = 0.47]), whilst it was not notable in ILA [p < 0.294]. Post hoc tests showed that CST group demonstrated greater improvement in all of the dependent variables from medium to large effect size (for all p < 0.001). As a result, 8 weeks of CST twice a week can be an effective and efficient training along with volleyball training to improve skill-related fitness measures, except for lower-limb asymmetry in young volleyball players.
Assessing the Sustainability of Long-Term Care Insurance Systems Based on a Policy–Population–Economy Complex System: The Case Study of China
Authors: Peng Rong , Deng Xueqin , Xia Yinghua , Wu Bei
Published: May 2022

Although China launched long-term care insurance (LTCI) pilot program in 2016, there are great challenges associated with developing a sustainable LTCI system due to limited financial resources and a rapid increase in the aging population. This study constructed an LTCI policy–population–economics (PPE) system to assess the sustainability of the LTCI system in China. Based on the latest 76 LTCI policy documents published between 2016 and 2021, this study evaluated the strength of LTCI policy modeling in 14 pilot cities by constructing a policy modeling consistency (PMC) index containing 9 main variables and 36 sub-variables. The coupling coordination model was used to evaluate the interaction between LTCI policy, population aging, and economic development. The results showed that the PMC index ranged from 0.527 to 0.850. The policy strength of Qingdao, Nantong, and Shanghai was the highest (PMC > 0.8). Anqing, Qiqihaer, Chongqing, and Chengdu had the lowest level of policy strength (PMC < 0.6). The main policy weaknesses were the coverage of the LTCI, the sources of funds, the scope of care services, and benefit eligibility. The coupling coordination degree of PPE systems varied from 0.429 to 0.921, with a mean of 0.651. Shanghai, Nantong, and Suzhou had the highest level of coordination. The coordination between subsystems of PPE in most pilot cities (12 of 14 cities) was at a basic or low level. The findings from this study concluded that the coordination within the PPE system should be improved to develop a sustainable LTCI system. To improve the coordination of the PPE system, it is suggested that the country should maintain sustainable economic growth and modify LTCI policies based on demographic transitions and economic development.
Improvements for Therapeutic Intervention from the Use of Web Applications and Machine Learning Techniques in Different Affectations in Children Aged 0–6 Years
Authors: Sáiz-Manzanares María Consuelo , Marticorena-Sánchez Raúl , Arnaiz-González Álvar
Published: May 2022

Technological advances together with machine learning techniques give health science disciplines tools that can improve the accuracy of evaluation and diagnosis. The objectives of this study were: (1) to design a web application based on cloud technology (eEarlyCare-T) for creating personalized therapeutic intervention programs for children aged 0–6 years old; (2) to carry out a pilot study to test the usability of the eEarlyCare-T application in therapeutic intervention programs. We performed a pilot study with 23 children aged between 3 and 6 years old who presented a variety of developmental problems. In the data analysis, we used machine learning techniques of supervised learning (prediction) and unsupervised learning (clustering). Three clusters were found in terms of functional development in the 11 areas of development. Based on these groupings, various personalized therapeutic intervention plans were designed. The variable with most predictive value for functional development was the users’ developmental age (predicted 75% of the development in the various areas). The use of web applications together with machine learning techniques facilitates the analysis of functional development in young children and the proposal of personalized intervention programs.
A Phenomenological Investigation into Cyberbullying as Experienced by People Identifying as Transgender or Gender Diverse
Authors: Evelyn Sophie , Clancy Elizabeth M. , Klettke Bianca , Tatnell Ruth
Published: May 2022

Cyberbullying can present a serious risk for adolescents and young adults, with severe effects on victims including adverse mental health outcomes and increased risk of suicide. Transgender and gender diverse (TGD) individuals are significantly more likely to experience cyberbullying. However, little is presently known about the lived cyberbullying experiences of TGD adults despite the prevalence of cyberbullying experienced by the TGD community. TGD participants (n = 66, M = 24 years) were recruited through snowball sampling and completed an online questionnaire as part of a larger study, which included qualitative questions regarding cyberbullying. Participants reported that cyberbullying was experienced predominantly on social media sites and was largely anonymous. The content was often physically and sexually threatening and heavily transphobic. Additionally, some cyberbullying experienced by TGD individuals was perpetrated by other TGD individuals and focused on the identity policing and gatekeeping of TGD spaces. Participants reported cyberbullying evoked negative emotions, and they often responded by either arguing with or blocking the perpetrators, thereby demonstrating resilience. Some participants sought social support in response to cyberbullying, which acted as a protective factor. Findings reveal specific harms associated with cyberbullying as experienced by TGD individuals and highlight the need for further research and targeted support.
Relationship between Dietary Behaviors and Physical Activity and the Components of Metabolic Syndrome: A Case-Control Study
Authors: Godala Małgorzata , Krzyżak Michalina , Maślach Dominik , Gaszyńska Ewelina
Published: May 2022

Poor diet and low physical activity play an important role in the etiopathogenesis of metabolic syndrome. The aim of this study was to analyze the association between nutrient intake, groups of food products and physical exercise undertaken and the components of metabolic syndrome (MS). The study included 330 patients with MS, and the control group comprised of 270 subjects without MS. The food intake was assessed using 24-h dietary recall, and a 13-item Food Frequency Questionnaire. To assess nutrition knowledge, a Beliefs and Eating Habits Questionnaire was used. The level of physical activity was assessed using the International Physical Activity Questionnaire. Three patterns of behavior were identified: Prudent-Active, Western-Sedentary, and NotPrudent-notWestern-lowActive. In the Prudent-Active group, as compared to the NotPrudent-notWestern-lowActive subjects, the risk of central obesity, hypertension, hypertriglyceridemia, low HDL cholesterol and hyperglycemia occurrence was lower. There was also a lower proportion of patients with MS. As compared to the NotPrudent-notWestern-lowActive subjects, in the Prudent-Active group there was more than a two times higher chance of subjects with a high level of nutrition knowledge. Western diets have been proven to exert a detrimental effect on the components of MS. When designing intervention programs, education of patients with MS on dietary habits and physical activity should be considered.