bluuebunny/crossref_metadata_2025 huggingface dataset:
Glutamate’s Effects on the N-Methyl-D-Aspartate (NMDA) Receptor Ion Channel in Alzheimer’s Disease Brain: Challenges for PET Radiotracer Development for Imaging the NMDA Ion Channel
Authors: Shah Nehal M. , Ghazaryan Nane , Gonzaga Noresa L. , Paclibar Cayz G. , Biju Agnes P. , Liang Christopher , Mukherjee Jogeshwar
Published: December 2023

In an effort to further understand the challenges facing in vivo imaging probe development for the N-methyl-D-aspartate (NMDA) receptor ion channel, we have evaluated the effect of glutamate on the Alzheimer’s disease (AD) brain. Human post-mortem AD brain slices of the frontal cortex and anterior cingulate were incubated with [3H]MK-801 and adjacent sections were tested for Aβ and Tau. The binding of [3H]MK-801 was measured in the absence and presence of glutamate and glycine. Increased [3H]MK-801 binding in AD brains was observed at baseline and in the presence of glutamate, indicating a significant increase (>100%) in glutamate-induced NMDA ion channel activity in AD brains compared to cognitively normal brains. The glycine effect was lower, suggesting a decrease of the co-agonist effect of glutamate and glycine in the AD brain. Our preliminary findings suggest that the targeting of the NMDA ion channel as well as the glutamate site may be appropriate in the diagnosis and treatment of AD. However, the low baseline levels of [3H]MK-801 binding in the frontal cortex and anterior cingulate in the absence of glutamate and glycine indicate significant hurdles for in vivo imaging probe development and validation.
Personalised Medicine and the Potential Role of Electrospinning for Targeted Immunotherapeutics in Head and Neck Cancer
Authors: O’Meara Connor H. , Nguyen Thanh Vinh , Jafri Zuhayr , Boyer Michael , Shonka David C. , Khachigian Levon M.
Published: December 2023

Advanced head and neck cancer (HNC) is functionally and aesthetically destructive, and despite significant advances in therapy, overall survival is poor, financial toxicity is high, and treatment commonly exacerbates tissue damage. Although response and durability concerns remain, antibody-based immunotherapies have heralded a paradigm shift in systemic treatment. To overcome limitations associated with antibody-based immunotherapies, exploration into de novo and repurposed small molecule immunotherapies is expanding at a rapid rate. Small molecule immunotherapies also have the capacity for chelation to biodegradable, bioadherent, electrospun scaffolds. This article focuses on the novel concept of targeted, sustained release immunotherapies and their potential to improve outcomes in poorly accessible and risk for positive margin HNC cases.
Role of Effective Policy and Screening in Managing Pediatric Nutritional Insecurity as the Most Important Social Determinant of Health Influencing Health Outcomes
Authors: Verma Hema , Verma Arun , Bettag Jeffery , Kolli Sree , Kurashima Kento , Manithody Chandrashekhara , Jain Ajay
Published: December 2023

Social Determinants of Health (SDOH) impact nearly half of health outcomes, surpassing the influence of human behavior, clinical care, and the physical environment. SDOH has five domains: Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context. Any adversity arising out of these interlinked domains predominantly affects children due to their greater susceptibility, and the adverse outcomes may span generations. Unfavorable SDOH may cause food insecurity, malnutrition, unbalanced gut microbiome, acute and chronic illnesses, inadequate education, unemployment, and lower life expectancy. Systematic screening by health care workers and physicians utilizing currently available tools and questionnaires can identify children susceptible to adverse childhood experiences, but there is a deficiency with respect to streamlined approach and institutional support. Additionally, current ameliorating supplemental food programs fall short of pediatric nutritional requirements. We propose a nutrition-based Surveillance, Screening, Referral, and Reevaluation (SSRR) plan encompassing a holistic approach to SDOH with a core emphasis on food insecurity, coupled with standardizing outcome-based interventions. We also propose more inclusive use of Food Prescription Programs, tailored to individual children’s needs, with emphasis on education and access to healthy food.
The Potential Role of Moringa oleifera Lam. Leaf Proteins in Moringa Allergy by Functionally Activating Murine Bone Marrow-Derived Dendritic Cells and Inducing Their Differentiation toward a Th2-Polarizing Phenotype
Authors: Xi Chuyu , Li Wenjie , Liu Xiaoxue , Xie Jing , Li Shijun , Tian Yang , Song Shuang
Published: December 2023

Moringa oleifera leaves are an inexpensive substitute for staple foods. Despite limited data, Moringa oleifera leaf protein (Mo-Pr) may be allergenic in BALB/c mice. In mouse models and allergic patients, dendritic cells (DCs) may be involved in food allergy. In addition, some allergens, including food allergens, can directly activate DCs and induce Th2 polarization. We investigated whether Mo-Pr can modulate the functional profile of murine bone marrow-derived dendritic cells (BMDCs) in vitro. BMDCs were obtained from mouse bone marrow cultured with granulocyte–macrophage colony-stimulating factor (GM-CSF) for 7 days and then treated with lipopolysaccharide (LPS) or Mo-Pr. BMDC phenotypes were evaluated via flow cytometry, cytokine production was assessed using ELISA, the expression of key genes was studied using qRT-PCR, the effects on T-cell differentiation were investigated using mixed lymphocyte reaction (MLR), and transcriptional changes in BMDCs were investigated using RNA-Seq. Mo-Pr-specific IgE was investigated in recipient serum after BMDC transfer. Mo-Pr treatment significantly induced BMDC maturation, increased the expression of CD80/86 and MHC II, resulted in the production of IL-12 and TNF-α, and induced T-cell differentiation. Mo-Pr treatment stimulated BMDCs’ expression of the Th2 promoters OX40L and TIM-4, induced the production of the Th2-type chemokines CCL22 and CCL17, and decreased the Th1/Th2 ratio in vitro. Healthy recipients of Mo-Pr-treated BMDCs produced Mo-Pr-specific IgE.
An Investigation of Severe Influenza Cases in Russia during the 2022–2023 Epidemic Season and an Analysis of HA-D222G/N Polymorphism in Newly Emerged and Dominant Clade 6B.1A.5a.2a A(H1N1)pdm09 Viruses
Authors: Kolosova Natalia P. , Boldyrev Nikita D. , Svyatchenko Svetlana V. , Danilenko Alexey V. , Goncharova Natalia I. , Shadrinova Kyunnei N. , Danilenko Elena I. , Onkhonova Galina S. , Kosenko Maksim N. , Antonets Maria E. , Susloparov Ivan M. , Ilyicheva Tatiana N. , Marchenko Vasily Y. , Ryzhikov Alexander B.
Published: December 2023

In Russia, during the COVID-19 pandemic, a decrease in influenza circulation was initially observed. Influenza circulation re-emerged with the dominance of new clades of A(H3N2) viruses in 2021–2022 and A(H1N1)pdm09 viruses in 2022–2023. In this study, we aimed to characterize influenza viruses during the 2022–2023 season in Russia, as well as investigate A(H1N1)pdm09 HA-D222G/N polymorphism associated with increased disease severity. PCR testing of 780 clinical specimens showed 72.2% of them to be positive for A(H1N1)pdm09, 2.8% for A(H3N2), and 25% for influenza B viruses. The majority of A(H1N1)pdm09 viruses analyzed belonged to the newly emerged 6B.1A.5a.2a clade. The intra-sample predominance of HA-D222G/N virus variants was observed in 29% of the specimens from A(H1N1)pdm09 fatal cases. The D222N polymorphic variant was registered more frequently than D222G. All the B/Victoria viruses analyzed belonged to the V1A.3a.2 clade. Several identified A(H3N2) viruses belonged to one of the four subclades (2a.1b, 2a.3a.1, 2a.3b, 2b) within the 3C.2a1b.2a.2 group. The majority of antigenically characterized viruses bore similarities to the corresponding 2022–2023 NH vaccine strains. Only one influenza A(H1N1)pdm09 virus showed reduced inhibition by neuraminidase inhibitors. None of the influenza viruses analyzed had genetic markers of reduced susceptibility to baloxavir.
Norovirus Epidemiology and Genotype Circulation during the COVID-19 Pandemic in Brazil, 2019–2022
Authors: Sarmento Sylvia Kahwage , de Andrade Juliana da Silva Ribeiro , Malta Fábio Correia , Fialho Alexandre Madi , Mello Mateus de Souza , Burlandy Fernanda Marcicano , Fumian Tulio Machado
Published: December 2023

Norovirus stands out as a leading cause of acute gastroenteritis (AGE) worldwide, affecting all age groups. In the present study, we investigated fecal samples from medically attended AGE patients received from nine Brazilian states, from 2019 to 2022, including the COVID-19 pandemic period. Norovirus GI and GII were detected and quantified using RT-qPCR, and norovirus-positive samples underwent genotyping through sequencing the ORF1/2 junction region. During the four-year period, norovirus prevalence was 37.2%, varying from 20.1% in 2020 to 55.4% in 2021. GII genotypes dominated, being detected in 92.9% of samples. GII-infected patients had significantly higher viral concentrations compared to GI-infected patients (median of 3.8 × 107 GC/g and 6.7 × 105 GC/g, respectively); and patients aged >12–24 months showed a higher median viral load (8 × 107 GC/g) compared to other age groups. Norovirus sequencing revealed 20 genotypes by phylogenetic analysis of RdRp and VP1 partial regions. GII.4 Sydney[P16] was the dominant genotype (57.3%), especially in 2019 and 2021, followed by GII.2[P16] (14.8%) and GII.6[P7] (6.3%). The intergenogroup recombinant genotype, GIX.1[GII.P15], was detected in five samples. Our study is the first to explore norovirus epidemiology and genotype distribution in Brazil during COVID-19, and contributes to understanding the epidemiological dynamics of norovirus and highlighting the importance of continuing to follow norovirus surveillance programs in Brazil.
Generation of Narrow Modes in Random Raman Fiber Laser Based on Multimode Fiber
Authors: Vatnik Ilya D. , Gorbunov Oleg A. , Churkin Dmitry V.
Published: December 2023

We present a new design of a random Raman fiber laser based on a graded-index multimode fiber as the media composing the cavity that allows the generation of narrow spectral lines. We carried out spectral measurements using an optical heterodyning technique by projecting multimode radiation onto the fundamental mode of a standard single-mode fiber. The measurements confirmed the presence of localized ultra-narrow short-lived modes. We measured the powers of the modes and found it to be significantly higher (up to 25 mW) compared with those in a random Raman laser based on a single-mode fiber (<2 mW), while preserving the same typical lifetimes of a few milliseconds.
Can the Firmness, Weight, and Size of Blueberry Fruit Be Enhanced through the Application of Low Amounts of Calcium to the Soil?
Authors: Hirzel Juan
Published: December 2023

Background: The firmness, weight, and size of blueberries are vital for commercial success of this crop. Fertilization is a key agronomic management practice that affects fruit quality, where calcium (Ca) plays a critical role. This study aimed to assess the impact of low levels of soil-dosed Ca in carboxylic acid form on fruit size, weight, firmness, and residual soil fertility. Methods: The study focused on two varieties of blueberries, Duke and Legacy, over two consecutive growing seasons on three commercial farms located in south-central Chile. This study consisted of five treatments, ranging from 0 to 4.0 kg Ca per hectare. Results: The highest firmness values observed for Duke were between 164 and 186 g mm−1, with size values ranging from 15.7 to 16.9 mm, and weight observations ranging from 1.60 to 1.76 g. On the other hand, Legacy showed firmness values between 163 and 173 g mm−1, with size values ranging from 16.2 to 17.2 mm, and weight observations ranging from 2.01 to 2.40 g. Conclusion: The application of low Ca rates to the soil did not impact the size, weight, or firmness of ‘Duke’ and ‘Legacy’ blueberries. There was a positive correlation between the Ca soil application and the concentration of exchangeable Ca.
Study on Dynamic Fermentation of Oat Silage Assisted by Exogenous Fibrolytic Enzymes
Authors: Liu Wei , Du Shuai , Sun Lin , Wang Zhijun , Ge Gentu , Jia Yushan
Published: December 2023

Based on the low content of water-soluble carbohydrate (WSC) and lactic acid bacteria (LAB) attachment in oat raw materials, we assumed that the neutral detergent fiber (NDF) content of oat can be reduced by adding cellulase or xylanase. The concentration of metabolizable sugars will be increased, which will assist the oat’s bacterial community in fermentation and obtain a better quality of oat silage. After wilting the oat, it was treated as follows: (1) distributed water (CK); (2) silages inoculated with xylanase (X); and (3) silages inoculated with cellulase (C), ensiling for 3, 7, 14, 30, and 60 days. Cellulase and xylanase treatments both alter the fermentation and nutritional quality of ensiled oat, resulting in lower NDF, acid detergent fiber (ADF), cellulose, and hemicellulose contents, increased lactic acid and acetic acid contents, and a significant decrease in ensiling environment pH. The bacterial community undergoes significant changes with cellulase and xylanase treatments, with a significant increase in Lactobacillus abundance in the C_14, X_30, C_30, X_60, and C_60 treatment groups, while Weissella abundance gradually decreases with longer ensiling times. Two exogenous fibrolytic enzymes also alter the bacterial diversity of ensiled oat, with different bacterial species and abundances observed in different treatment groups. Ensiled oat treated with cellulase and xylanase experiences significant changes in its own bacterial community, particularly in the abundance of Lactobacillus. These changes result in improved fermentation and nutritional quality of oat, but the higher metabolism levels observed after 60 days of ensiling with cellulase treatment may lead to energy loss.
Effects of Planting Density and Nitrogen Fertilization on the Growth of Forage Rice in Reclaimed and General Paddy Fields
Authors: Jang Yeongmi , Sharavdorj Khulan , Ahn Youngjik , Cho Jinwoong
Published: December 2023

The purpose of this study is to identify the different effects exerted by planting density and nitrogen fertilization on high-salinity reclaimed paddy fields (RPF) and general paddy fields (GPFs), and to find the amount of fertilization and the planting density suitable for the growth of forage rice in each paddy field. Nitrogen fertilization with high-salt and low-salt soils, an untreated control plot, treatment with 200 kg/ha, 300 kg/ha, and 400 kg/ha, and planting densities of 30 cm × 10 cm and 30 cm × 16 cm, growth, and feed values were investigated. In both experimental locations, there was no significant change in the soil due to N treatment, but in the case of RPF, electrical conductivity (EC) decreased significantly from more than 5 dS/m to up to 2.87 dS/m during the yellow ripe stage due to the influence of floods and concentrated precipitation in the fields. In all soils, as both the amount of N treatment and the planting density increased, there was a proportional relationship in which the number of tillers and the dry weight also increased, with the occurrence of lodging also being increased. The dry weight, as expected, was 1.5 times higher at a planting distance of 10 cm, rather than 16 cm. In addition, in both locations, the N treatment led to an increase in the dry weight, but when N treatment reached 400 kg/ha (2.0), the dry weight decreased instead. Moreover, although there was no clear difference in feed value according to N treatment, in RPF, the neutral detergent fiber (NDF) was higher than 60%, the relative feed value (RFV) was less than 98, and the total digestible nutrient (TDN) was also low, confirming that the quality of rice was higher in GPF.
Biopolymers as a Potential Alternative for the Retention of Pollutants from Vinasse: An In Silico Approach
Authors: Aristizabal Yesid , Ciro Yhors , Liscano Yamil , Salamanca Constain H. , Oñate-Garzón Jose
Published: December 2023

Vinasse, a waste from the bioethanol industry, presents a crucial environmental challenge due to its high organic matter content, which is difficult to biodegrade. Currently, no sustainable alternatives are available for treating the amount of vinasse generated. Conversely, biopolymers such as cellulose, carboxymethylcellulose, and chitosan are emerging as an interesting alternative for vinasse control due to their flocculating capacity against several organic compounds. This study seeks to determine the thermodynamic behavior of in silico interactions among three biopolymers (cellulose, carboxymethylcellulose, and chitosan) regarding 15 organic compounds found in vinasse. For this, the Particle Mesh Ewald (PME) method was used in association with the Verlet cutoff scheme, wherein the Gibbs free energy (ΔG) was calculated over a 50 ns simulation period. The findings revealed that cellulose showed a strong affinity for flavonoids like cyanidin, with a maximum free energy of −84 kJ/mol and a minimum of −55 kJ/mol observed with phenolic acids and other flavonoids. In contrast, chitosan displayed the highest interactions with phenolic acids, such as gallic acid, reaching −590 kJ/mol. However, with 3-methoxy-4-hydroxyphenyl glycol (MHPG), it reached an energy of −70 kJ/mol. The interaction energy for flavonoid ranged from −105 to −96 kJ/mol. Finally, carboxymethylcellulose (CMC) demonstrated an interaction energy with isoquercetin of −238 kJ/mol, while interactions with other flavonoids were almost negligible. Alternatively, CMC exhibited an interaction energy of −124 kJ/mol with MHPG, while it was less favorable with other phenolic acids with minimal interactions. These results suggest that there are favorable interactions for the interfacial sorption of vinasse contaminants onto biopolymers, indicating their potential for use in the removal of contaminants from the effluents of the bioethanol industry.
Gas Permeability through Polyimides: Unraveling the Influence of Free Volume, Intersegmental Distance and Glass Transition Temperature
Authors: Torres Alba , Soto Cenit , Carmona Javier , Comesaña-Gandara Bibiana , de la Viuda Mónica , Palacio Laura , Prádanos Pedro , Simorte María Teresa , Sanz Inmaculada , Muñoz Raúl , Tena Alberto , Hernández Antonio
Published: December 2023

The relationships between gas permeability and free volume fraction, intersegmental distance, and glass transition temperature, are investigated. They are analyzed for He, CO2, O2, CH4, and N2 gases and for five similar polyimides with a wide range of permeabilities, from very low to extremely high ones. It has been established here that there is an exponential relationship between permeability and the free volume fraction, and between permeability and the most probable intersegmental distance as measured by WAXS; in both cases, with an exponential coefficient that depends on the kinetic gas diameter as a quadratic polynomial and with a preexponential positive constant. Moreover, it has been proven that the intersegmental distance increases linearly with the free volume fraction. Finally, it has been established that the free volume fraction increases with the glass transition temperature for the polymers tested, and that they depend on each other in an approximate linear way.
Numerical Simulation Study of Pressure-Driven Water Injection and Optimization Development Schemes for Low-Permeability Reservoirs in the G Block of Daqing Oilfield
Authors: Wang Biao , Zhao Yanjie , Tian Yajie , Kong Cuilong , Ye Qinyou , Zhao Sicong , Li Zihao , Suo Yu
Published: December 2023

Pressure-driven water injection technology shows significant potential in addressing the key challenges of low-permeability oil reservoirs, improving water flooding development efficiency. Grounded in FDEM theory, this study establishes fluid matrix constitutive equations and employs FDEM to resolve rock stress–strain fields. A numerical simulation method for pressure-driven water injection in low-permeability reservoirs is developed to study the impact of different well pattern densities. The results indicate that the 90° horizontal well pattern using the five-spot method yields optimal outcomes, with approximately 32.32% higher cumulative liquid production than vertical well patterns. The 45° horizontal well pattern with the reversed nine-spot method also performs well, with about 30% higher cumulative liquid production than single-row vertical wells. Pressure-driven water injection improves matrix oil–water permeability and expands water flooding coverage. Based on the pressure gradient distribution driven by different well patterns, an evaluation method for the inter-well utilization capacity and its effectiveness was established. This method quantitatively assesses the reservoir depletion under various horizontal well encryption schemes. For research on timing of water injection in pressure-driven water flooding. Compared to pressure-driven water injection after 90 days, there is increased cumulative oil production after 40 days, emphasizing the importance of early pressure maintenance for higher cumulative oil production and enhanced recovery rates in low-permeability reservoir development. These findings provide crucial theoretical and practical support.
Modeling and Analysis of Distributed Control Systems: Proposal of a Methodology
Authors: Tkáčik Milan , Jadlovský Ján , Jadlovská Slávka , Jadlovská Anna , Tkáčik Tomáš
Published: December 2023

A Distributed Control System is a concept of Network Control Systems whose applications range from industrial control systems to the control of large physical experiments such as the ALICE experiment at CERN. The design phase of the Distributed Control Systems implementation brings several challenges, such as predicting the throughput and response of the system in terms of data-flow. These parameters have a significant impact on the operation of the Distributed Control System, and it is necessary to consider them when determining the distribution of software/hardware resources within the system. This distribution is often determined experimentally, which may be a difficult, iterative process. This paper proposes a methodology for modeling Distributed Control Systems using a combination of Finite-State Automata and Petri nets, where the resulting model can be used to determine the system’s throughput and response before its final implementation. The proposed methodology is demonstrated and verified on two scenarios concerning the respective areas of ALICE detector control system and mobile robotics, using the MATLAB/Simulink implementation of created models. The methodology makes it possible to validate various distributions of resources without the need for changes to the physical system, and therefore to determine the appropriate structure of the Distributed Control System.
Numerical Prediction of Refrigerant Oil Two-Phase Flow from Scroll Compressor Discharge to the Suction Side via Back Pressure Chamber
Authors: Stevanovic Vladimir D. , Petrovic Milan M. , Cucuz Stojan , Milivojevic Sanja , Ilic Milica
Published: December 2023

Oil lubricates the contact between the orbiting and stationary scroll in the refrigerant scroll compressor, while the sealing between the scrolls is achieved through the refrigerant vapour pressure in the sealed back pressure chamber. The back pressure should be adjusted using the refrigerant oil two-phase flow from the oil separator at the compressor discharge to the back pressure chamber and the refrigerant oil flow from the back pressure chamber to the compressor suction side. Both of the flows are conducted through connecting tubes with corresponding high-pressure and low-pressure nozzles with small diameters. Models for predicting the refrigerant oil critical and subcritical flows through the nozzles were developed and applied in enable the prediction of the back pressure. The models are original, because the slip between the oil and the refrigerant as well as the refrigerant solubility in the oil are taken into account. The critical flow model is validated against the experimental data that are available in the literature. The back pressure is predicted by equating the mass flow rates of refrigerant and oil two-phase mixtures through the high- and low-pressure nozzles. The results show that the critical flow takes place through the high-pressure nozzle, while the subcritical flow through the low-pressure nozzle can also exist in cases with a small pressure difference between the back pressure chamber and the compressor suction side. The refrigerant solubility in the oil has a small influence on the critical and subcritical refrigerant oil mixture mass flow rates, while the influence on the back pressure is more pronounced.
Residual Life Prediction of Rolling Bearings Based on a CEEMDAN Algorithm Fused with CNN–Attention-Based Bidirectional LSTM Modeling
Authors: Zhang Xinggang , Yang Jianzhong , Yang Ximing
Published: December 2023

This paper presents a methodology for predicting the remaining usability of rolling bearings. The method combines a fully adaptive ensemble empirical modal decomposition of noise (CEEMDAN), convolutional neural network (CNN), and attention bidirectional long short-term memory network (ABiLSTM). Firstly, a finite number of intrinsic mode functions (IMFs) are obtained from breaking down the initial vibration signals using CEEMDAN. The IMFs are further screened by combining the correlation criterion and the craggy criterion. Then, time-frequency domain features, which are extracted from the screened IMFs, are reconstructed into a feature set. The SPT is recognized through some features, like the root mean square (RMS), variance, and kurtosis. Secondly, the deterioration character of rolling bearings was extracted using CNN and used to train the ABiLSTM network. Based on the output of the ABiLSTM network, it forecasts how long rolling bearings will last during use. Finally, the XJTU-SY rolling bearing dataset validated the validity of the suggested rolling bearing remaining life prediction method. We compare our algorithm with other algorithms, such as GRU, LSTM, and CNN–BiLSTM, in which the accuracy of MAE, MSE, RMSE, MAPE, and R2_score is significantly improved. Thus, the results of the validation experiments demonstrate that our proposed algorithm has excellent prediction accuracy.
Online Media, Civic Engagement, and the Prevention of Religious Radicalism: Together for an Inclusive Future (A View of Empirical Evidence)
Authors: Tkácová Hedviga , Slivka Daniel
Published: December 2023

The current increase in religiously motivated radicalism is a serious social problem in various countries. Through our qualitative research, which was based on the knowledge and experience of experts recorded during the focus group interview, it was possible to identify the most frequent causes of religious radicalism in Slovakia today. The Slovak Republic, a small post-communist country in the region of Eastern Europe, served as an empirical example for research purposes. Following the research findings, a second research objective was set, namely to present the possibilities and contribution of citizen journalism that can play a key role in tracking, documenting and sharing cases of religious radicalism. The research presents the causes of religious radicalism and the optimal possibilities of citizen journalism, which would adequately respond to contemporary religious radicalism with the use of online media. The activities of “people’s journalists” appear not only as a trigger for public debate that takes place on social media, blogs, and independent journalistic platforms but also as a necessary voice calling for accountability and transparency of solutions concerning religious radicalism, which is inherently complex and a multifactorial process, often leading to extremism. This study attempts to answer the question of why civic engagement using online media is important in this issue.
An Interpretable Digital Twin for Self-Aware Industrial Machines
Authors: Vilar-Dias João L. , Junior Adelson Santos S. , Lima-Neto Fernando B.
Published: December 2023

This paper presents a proposed three-step methodology designed to enhance the performance and efficiency of industrial systems by integrating Digital Twins with particle swarm optimization (PSO) algorithms while prioritizing interpretability. Digital Twins are becoming increasingly prevalent due to their capability to offer a comprehensive virtual representation of physical systems, thus facilitating detailed simulations and optimizations. Concurrently, PSO has demonstrated its effectiveness for real-time parameter estimation, especially in identifying both standard and unknown components that influence the dynamics of a system. Our methodology, as exemplified through DC Motor and Hydraulic Actuator simulations, underscores the potential of Digital Twins to augment the self-awareness of industrial machines. The results indicate that our approach can proficiently optimize system parameters in real-time and unveil previously unknown components, thereby enhancing the adaptive capacities of the Digital Twin. While the reliance on accurate data to develop Digital Twin models is a notable consideration, the proposed methodology serves as a promising framework for advancing the efficiency of industrial applications. It further extends its relevance to fault detection and system control. Central to our approach is the emphasis on interpretability, ensuring a more transparent understanding and effective usability of such systems.
A WaveGAN Approach for mmWave-Based FANET Topology Optimization
Authors: Odat Enas , Ghazzai Hakim , Alsharoa Ahmad
Published: December 2023

The integration of dynamic Flying Ad hoc Networks (FANETs) and millimeter Wave (mmWave) technology can offer a promising solution for numerous data-intensive applications, as it enables the establishment of a robust flying infrastructure with significant data transmission capabilities. However, to enable effective mmWave communication within this dynamic network, it is essential to precisely align the steerable antennas mounted on Unmanned Aerial Vehicles (UAVs) with their corresponding peer units. Therefore, it is important to design a novel approach that can quickly determine an optimized alignment and network topology. In this paper, we propose a Generative Adversarial Network (GAN)-based approach, called WaveGAN, for FANET topology optimization aiming to maximize the network throughput by selecting the communication paths with the best channel conditions. The proposed approach consists of a WaveGAN model followed by a beam search. The former learns how to generate optimized network topologies from a supervised dataset, while the latter adjusts the generated topologies to meet the structure requirements of the mmWave-based FANET. The simulation results show that the proposed approach is able to quickly find FANET topologies with a very small optimality gap for different network sizes.
Semi-Supervised Clustering-Based DANA Algorithm for Data Gathering and Disease Detection in Healthcare Wireless Sensor Networks (WSN)
Authors: Sinha Anurag , Aljrees Turki , Pandey Saroj Kumar , Kumar Ankit , Banerjee Pallab , Kumar Biresh , Singh Kamred Udham , Singh Teekam , Jha Pooja
Published: December 2023

Wireless sensor networks (WSNs) have emerged as a promising technology in healthcare, enabling continuous patient monitoring and early disease detection. This study introduces an innovative approach to WSN data collection tailored for disease detection through signal processing in healthcare scenarios. The proposed strategy leverages the DANA (data aggregation using neighborhood analysis) algorithm and a semi-supervised clustering-based model to enhance the precision and effectiveness of data collection in healthcare WSNs. The DANA algorithm optimizes energy consumption and prolongs sensor node lifetimes by dynamically adjusting communication routes based on the network’s real-time conditions. Additionally, the semi-supervised clustering model utilizes both labeled and unlabeled data to create a more robust and adaptable clustering technique. Through extensive simulations and practical deployments, our experimental assessments demonstrate the remarkable efficacy of the proposed method and model. We conducted a comparative analysis of data collection efficiency, energy utilization, and disease detection accuracy against conventional techniques, revealing significant improvements in data quality, energy efficiency, and rapid disease diagnosis. This combined approach of the DANA algorithm and the semi-supervised clustering-based model offers healthcare WSNs a compelling solution to enhance responsiveness and reliability in disease diagnosis through signal processing. This research contributes to the advancement of healthcare monitoring systems by offering a promising avenue for early diagnosis and improved patient care, ultimately transforming the landscape of healthcare through enhanced signal processing capabilities.
In Situ Synthesis of Highly Fluorescent, Phosphorus-Doping Carbon-Dot-Functionalized, Dendritic Silica Nanoparticles Applied for Multi-Component Lateral Flow Immunoassay
Authors: Hu Jia-Xuan , Ding Shou-Nian
Published: December 2023

The sensitivity of fluorescent lateral flow immunoassay (LFIA) test strips is compromised by the low fluorescence intensity of the signaling molecules. In this study, we synthesized novel phosphorus-doped carbon-dot-based dendritic mesoporous silica nanoparticles (DMSNs-BCDs) with a quantum yield as high as 93.7% to break this bottleneck. Meanwhile, the in situ growth method increased the loading capacity of carbon dots on dendritic mesoporous silica, effectively enhancing the fluorescence intensity of the composite nanospheres. Applied DMSNs-BCDs in LFIA can not only semi-quantitatively detect a single component in a short time frame (procalcitonin (PCT), within 15 min) but also detect the dual components with a low limit of detection (LOD) (carbohydrate antigen 199 (CA199) LOD: 1 U/mL; alpha-fetoprotein (AFP) LOD: 0.01 ng/mL). And the LOD of PCT detection (0.01 ng/mL) is lower by 1.7 orders of magnitude compared to conventional colloidal gold strips. For CA199, the LOD is reduced by a factor of four compared to LFIA using gold nanoparticles as substrates, and for AFP, the LOD is lowered by two orders of magnitude compared to colloidal gold LFIA. Furthermore, the coefficients of variation (CV) for intra-assay and inter-assay measurements are both less than 11%.
Enhancing Early Risk Detection for Reduced Earning Capacity: The Development of the padaCura App
Authors: Weißmann Regina , Grimmel-Bruhns Annette , Busacker Corinna , Loth Fanny
Published: December 2023

In Germany, 1.7 million individuals received reduced earning capacity pensions in 2020, but reintegrating them into the labor market remains challenging. For individuals who have a reduced earning capacity, this often leads to adverse consequences (e.g., low quality of life, poverty, social stigma). The project ‘Cooperation for prevention, fitness and health in the job center (KOPF22)’ focuses on early risk detection and prevention strategies for clients of the job center (who are recipients of Citizen’s Income) as they face various challenges in maintaining their ability to work. The padaCura App, a key component of the project, assesses the risk of reduced earning capacity using an ICF-based questionnaire. It offers immediate feedback reports to clients, categorizing their risk levels and suggesting actions in plain language with visual aids. Since the project emphasizes the client’s autonomy and voluntary participation, clients decide how to proceed with their results. If they decide to cooperate with the job center, then several offers for prevention and intervention measures can be used to increase employability. The first evaluations of the app and the questionnaire demonstrate its effectiveness in differentiating between employable persons and incapacitated individuals. Future developments should focus on enhancing the result reports to include more targeted interventions and on collaboration between employment support resources and healthcare systems to meet clients’ needs.
Plyometric Training’s Effects on Young Male Karatekas’ Jump, Change of Direction, and Inter-Limb Asymmetry
Authors: Moreno-Azze Alejandro , Prad-Lucas Estela , Fandos Soñén David , Pradas de la Fuente Francisco , Falcón-Miguel David
Published: December 2023

This study analysed the effects of performing a plyometric training programme on different types of jumping and specific changes of direction, and their respective asymmetries in karatekas. Twenty male karatekas (age 19 ± 4 years) were distributed in two groups, the control group (CG) and the experimental group (EG). The EG group (n = 10) performed a 6-week intervention of unilateral plyometric training, performing countermovement jumps (CMJ), drop jumps (DJ), and long jumps (SH). The tests performed at the beginning and at the end of the intervention were a unilateral and bilateral countermovement jump test (CMJ), single-leg hop test (SH), single-leg side-hop test (SSH), triple hop test (TH), and change of direction in a karate position test (MKUKS). The EG group obtained improvements in the CMJ with the stronger (p = 0.01; ES = 0.39) and weaker leg (p = 0.01; ES = 0.59), in the SH with the weaker leg (p = 0.01; ES = 0.45), in the SSH with the weaker leg (p = 0.03; ES = 0.33), in the MKUKS (p = 0.00; ES = 0.98), and improved the asymmetries obtained in the TH (p = 0.02; ES = −0.85). The GC group obtained significant differences in the CMJ with the stronger (p = 0.03; ES = 0.46) and weaker leg (p = 0.00; ES = 0.69), in the bilateral CMJ (p = 0.02; ES = 0.24), in the SH with the weaker leg (p = 0.00; ES = 0.34), in the TH with the stronger (p = 0.00; ES = −0.15) and weaker leg (p = 0.01; ES = 0.09), and in the MKUKS test (p = 0.04; ES = −0.94). A between-group analysis showed improvements of the EG over the GC in the TH with the stronger leg (p = 0.02; ES = 1.05). Performing plyometric training provides improvements in jumping, mainly in horizontal jumps, reducing inter-limb asymmetries in repetitive jumps.
Expression of Concern: Lin et al. A Perception Study for Unit Charts in the Context of Large-Magnitude Data Representation. Symmetry 2023, 15, 219
Authors:   Symmetry Editorial Office
Published: December 2023

With this notice, the Symmetry Editorial Office states its awareness of concerns regarding the availability and validity of the data as well as the overall findings of the published manuscript [...]
Pre-Trained Transformer-Based Models for Text Classification Using Low-Resourced Ewe Language
Authors: Agbesi Victor Kwaku , Chen Wenyu , Yussif Sophyani Banaamwini , Hossin Md Altab , Ukwuoma Chiagoziem C. , Kuadey Noble A. , Agbesi Colin Collinson , Abdel Samee Nagwan , Jamjoom Mona M. , Al-antari Mugahed A.
Published: December 2023

Despite a few attempts to automatically crawl Ewe text from online news portals and magazines, the African Ewe language remains underdeveloped despite its rich morphology and complex "unique" structure. This is due to the poor quality, unbalanced, and religious-based nature of the crawled Ewe texts, thus making it challenging to preprocess and perform any NLP task with current transformer-based language models. In this study, we present a well-preprocessed Ewe dataset for low-resource text classification to the research community. Additionally, we have developed an Ewe-based word embedding to leverage the low-resource semantic representation. Finally, we have fine-tuned seven transformer-based models, namely BERT-based (cased and uncased), DistilBERT-based (cased and uncased), RoBERTa, DistilRoBERTa, and DeBERTa, using the preprocessed Ewe dataset that we have proposed. Extensive experiments indicate that the fine-tuned BERT-base-cased model outperforms all baseline models with an accuracy of 0.972, precision of 0.969, recall of 0.970, loss score of 0.021, and an F1-score of 0.970. This performance demonstrates the model’s ability to comprehend the low-resourced Ewe semantic representation compared to all other models, thus setting the fine-tuned BERT-based model as the benchmark for the proposed Ewe dataset.
Identification of the Key Genes Involved in Proline-Mediated Modification of Cell Wall Components in Rice Seedlings under Trivalent Chromium Exposure
Authors: Ullah Abid , Lin Yu-Juan , Zhang Hua , Yu Xiao-Zhang
Published: December 2023

Chromium (Cr) toxicity exerts a detrimental effect on various physiological, biochemical, and molecular attributes of plants including the structure and functions of cell walls. On the other hand, the exogenous application of proline (Pro) is a beneficial strategy to overcome Cr toxicity. Therefore, it is a novel strategy to find the key genes associated with cell wall composition in rice under trivalent Cr with/without Pro application. A total of 203 genes were activated in the four cell wall biosynthesis pathways under chromium stress, namely cellulose (60), hemicellulose (57), lignin (35), and pectin (51). Based on the expression abundance of microarrays, the number of differentially expressed genes, and the expression level of genes, the lignin pathway was a crucial pathway in response to Cr treatments, followed by the cellulose pathway. Through the estimation of gene expression variation factors between ‘Cr’ and ‘Cr+Pro’ treatments, OsUGP1, OsBGLU24, OsBGLU29, OsBGLU33, OsBMY1, and OsBMY2 in the cellulose pathway; OsXTH9, OsXTH10, OsXTH16, OsGAUT3, OsGAUT19, OsGAUT28, OsXTH1, OsGAUT12, and OsGAUT21 in the hemicellulose pathway; OsPAL3, OsPAL3, OsPOX1, and OsPRX77 in the lignin pathway; and OsPME25, OsPGL27, OsPME26, OsPGL9, and OsPLL12 in the pectin pathway are the key genes involved in cell wall modification during Cr exposure with exogenous Pro application. The Pro-mediated activation of these genes could be crucial players in modifying the cell wall structure and composition of rice plants under Cr stress, which needs to be further clarified.
Characterization of a Panel of Monoclonal Antibodies Targeting the F-Protein of the Respiratory Syncytial Virus (RSV) for the Typing of Contemporary Circulating Strains
Authors: Krivitskaya Vera , Petrova Ekaterina , Sorokin Evgeniy , Tsareva Tatyana , Sverlova Maria , Komissarova Kseniia , Sominina Anna , Danilenko Daria
Published: December 2023

Respiratory syncytial virus (RSV) is the most common cause of upper and lower respiratory tract infections in infants and young children. Virus-specific monoclonal antibodies (mAbs) can be used for diagnosis, prophylaxis, and research of RSV pathogenesis. A panel of 16 anti-RSV mAbs was obtained from mice immunized by RSV strain Long. Half of them had virus-neutralizing activity. According to Western blot all of these mAbs effectively bound native oligomeric (homodimeric and homotrimeric) forms of the RSV fusion (F) protein. Only five of the mAbs interacted with the monomeric form, and only one of these possessed neutralizing activity. None of these mAbs, nor the commercial humanized neutralizing mAb palivizumab, reacted with the denaturated F protein. Thus, interaction of all these mAbs with F protein had clear conformational dependence. Competitive ELISA and neutralization assays allowed the identification of nine antigenic target sites for the interaction of mAb with the F protein. Five partially overlapping sites may represent a complex spatial structure of one antigenic determinant, including one neutralizing and four non-neutralizing epitopes. Four sites (three neutralizing and one non-neutralizing) were found to be distinct. As a result of virus cultivation RSV–A, strain Long, in the presence of a large amount of one of the neutralizing mAbs, an escape mutant with a substitution, N240S, in the F protein, was obtained. Thus, it was shown for the first time that position 240 is critical for the protective effect of an anti-RSV antibody. To assess the ability of these mAbs to interact with modern RSV strains circulating in St. Petersburg (Russia) between 2014 and 2022, 73 RSV-A and 22 RSV-B isolates were analyzed. Six mAbs were directed to conserved epitopes of the F protein as they interacted most efficiently with both RSV subtypes in a fixed cell-ELISA and could be used for diagnostic assays detecting RSV.
Correlates of Depression in ART Adherence among Youths in Lilongwe, Malawi
Authors: Msefula Mary Carolyne , Umar Eric
Published: December 2023

Despite collaborative efforts to improve mental health services among youths living with HIV (YLHIVs) aged 15–24, evidence shows that many suffer from depression. We established the correlates of depression and how it affects ART adherence. Structured questionnaires, a Patient Health Questionnaire 9 depression scale assessment, in-depth interviews, and Electronic Medical Record reviews were conducted at the Lighthouse Trust Martin Preus Centre (MPC) ART clinic in Lilongwe from April 2021 to October 2022. A total of 303 YLHIVs aged 15–24 were on ART, and 7 key informants were recruited. Bivariate and multivariate logistic regression analyses were performed using STATA V14.1. A thematic content analysis was used for qualitative data. Forty-six per cent of recruits were male, and fifty-four per cent were female. Seventy-one per cent were aged 20–24, and twenty-nine per cent were aged 15–19. Twenty-three per cent of the YLHIVs had depression symptoms, of whom seventy-nine per cent were aged 20–24 years. Twenty-two per cent had an unsuppressed viral load (non-adherent). Sixty-seven per cent of non-adherent participants were aged 20–24. There was no factor associated with ART non-adherence. Source of income (p = 0.003), alcohol consumption (p = 0.010), and sexual behaviour (p = 0.014) were associated with depression. Sexual behaviour was statistically significantly associated with depression (p = 0.024. The themes were a lack of basic needs, a lack of privacy, psychological trauma, incomplete disclosure, a shortage of psychosocial providers, and a knowledge deficit of ART providers to screen for depression. This study shows that depression is considerably high among YLHIVs in Malawi and linked to ART non-adherence. Strengthening mental health training for providers and routinely screening YLHIVs for depression would help in the early identification and management of depression, thereby improving ART adherence.