bluuebunny/crossref_metadata_2025 huggingface dataset:
Initial Alterations of Fish Community Structure and Diversity Following Fishing Cessation in Qilu Lake, China
Authors: Zhu Tingbing , Hu Feifei , Gong Jinling , Liu Kairun , Guo Zhibin , Yang Deguo , Li Xuemei
Published: August 2024

The Qilu Lake is an eutrophic shallow lake located in Yunnan Province, China. An ecological fishery project was initiated in the lake from 2011 to 2021 to introduce filter-feeding fish species that feed on algae, with the aim of improving water quality. In January 2022, when the ecological fishery project expired, all fisheries-related activities (including fish stocking and fishing activities) ceased in the lake. To comprehensively evaluate the initial alterations in fish community structure and diversity resulting from the fishing cessation in the Qilu Lake, the present study conducted field surveys within the one year before the fishing cessation (referred to as BFC) and the one year after the fishing cessation (referred to as AFC). A total of twenty-one fish species were collected, including four native species. Four species were recorded in the lake for the first time, including Pelteobagrus fulvidraco, Pelteobagrus vachelli, Paramisgurnus dabryanus, and Hyporhamphus intermedius. The number of fish species decreased from 21 to 13 following the fishing cessation. The fishes collected in both BFC and AFC are mainly omnivorous-feeding and of bottom-dwelling habits. The mean size of the fishes in the AFC sample shows a significant decrease compared to those in BFC. After the fishing cessation, the Shannon–Wiener diversity index and Margalef richness index of the fish slightly declined. The fish community structure of the Qilu Lake exhibits a high degree of similarity to adjacent lakes in central Yunnan. Our study demonstrates a significant shift in the fish community of the Qilu Lake following the fishing cessation, one which may adversely impact the stability of the lake ecosystem. To enhance fish species diversity in the Qilu Lake, it is recommended that policies be implemented to promote the ecological fishery project and improve habitat restoration for native fish species, while also regulating fish community structure.
Complete Growth Inhibition of Pseudomonas aeruginosa by Organo-Selenium-Incorporated Urinary Catheter Material
Authors: Tran Phat L. , Presson Caroline L. , Kashem Md Nayeem Hasan , Li Wei , Reid Ted W. , de Riese Werner T. W.
Published: August 2024

To further investigate the inhibition of Pseudomonas aeruginosa’s in vitro growth and biofilm formation by an organo-selenium-incorporated polyurethane (PU) catheter material. P. aeruginosa, Staphylococcus aureus, and Candida albicans were incubated in vitro with organo-selenium and control polyurethane catheter materials in the presence of glutathione. Growth was evaluated by a colony-forming-unit (CFU) count and visualized with confocal laser scanning microscopy. Two different PU catheter materials were used. Using tin-catalyzed PU catheter material, complete inhibition of S. aureus was seen at 1% selenium (Se), whereas no inhibition was seen for P. aeruginosa at up to 3.0% Se. Whereas, using a thermoplastic PU catheter material, 1.5% Se and 2% Se organo-selenium caused several logs of growth inhibition of P. aeruginosa, and 2.5% selenium, incorporation showed complete inhibition (8 logs). Samples with lower than 1.5% selenium did not show adequate growth inhibition for P. aeruginosa. Similar in vitro growth inhibition was achieved against a multidrug-resistant C. albicans strain. It was concluded that optimal inhibition of P. aeruginosa in vitro growth and biofilm formation occurs with 2.5% selenium incorporated as organo-selenium in a thermoplastic PU catheter material. These results suggest that reduced incidence of CAUTIs (catheter associated urinary tract infections) with P. aeruginosa and other bacteria and fungi can be achieved by using organo-selenium-incorporated catheters.
Unveiling the High Diversity of Clones and Antimicrobial Resistance Genes in Escherichia coli Originating from ST10 across Different Ecological Niches
Authors: Machado Maxsueli Aparecida Moura , Panzenhagen Pedro , Lázaro Cesar , Rojas Miguel , Figueiredo Eduardo Eustáquio de Souza , Conte-Junior Carlos Adam
Published: August 2024

In this pioneering in silico study in Peru, we aimed to analyze Escherichia coli (E. coli) genomes for antimicrobial resistance genes (ARGs) diversity and virulence and for its mobilome. For this purpose, 469 assemblies from human, domestic, and wild animal hosts were investigated. Of these genomes, three were E. coli strains (pv05, pv06, and sf25) isolated from chickens in our previous study, characterized for antimicrobial susceptibility profile, and sequenced in this study. Three other genomes were included in our repertoire for having rare cgMLSTs. The phenotypic analysis for antimicrobial resistance revealed that pv05, pv06, and sf25 strains presented multidrug resistance to antibiotics belonging to at least three classes. Our in silico analysis indicated that many Peruvian genomes included resistance genes, mainly to the aminoglycoside class, ESBL-producing E. coli, sulfonamides, and tetracyclines. In addition, through Multi-locus Sequence Typing, we found more than 180 different STs, with ST10 being the most prevalent among the genomes. Pan-genome mapping revealed that, with new lineages, the repertoire of accessory genes in E. coli increased, especially genes related to resistance and persistence, which may be carried by plasmids. The results also demonstrated several genes related to adhesion, virulence, and pathogenesis, especially genes belonging to the high pathogenicity island (HPI) from Yersinia pestis, with a prevalence of 42.2% among the genomes. The complexity of the genetic profiles of resistance and virulence in our study highlights the adaptability of the pathogen to different environments and hosts. Therefore, our in silico analysis through genome sequencing enables tracking the epidemiology of E. coli from Peru and the future development of strategies to mitigate its survival.
Pattern of Expression of Genes Involved in Systemic Inflammation and Glutathione Metabolism Reveals Exacerbation of COPD
Authors: Oit-Wiscombe Ingrid , Virág László , Kilk Kalle , Soomets Ursel , Altraja Alan
Published: August 2024

To test the hypothesis that they serve as systemic biomarkers of chronic obstructive pulmonary disease (COPD), we profiled the mRNA expression of enzymes connected to systemic inflammation and GSH metabolism in peripheral blood mononuclear cells (PBMCs). These were taken from patients displaying acute exacerbation of COPD (AE-COPD) and stable COPD, and also from non-obstructive smokers and non-smokers. The expression of poly(ADP-ribose) polymerase-1 was increased, but that of histone deacetylase 2 was decreased in association with AE-COPD. The expression of modulatory subunit of glutamyl–cysteine ligase was higher and that of its catalytic subunit, together with the expression of dipeptidyl peptidase 4, was lower in COPD patients compared with non-obstructive smokers and non-smokers. Leukotriene A4 hydrolase saw increased expression in patients with COPD according to disease severity compared to non-obstructive individuals, whereas the expression of GSH peroxidase increased in non-obstructive smokers and COPD patients with the growing number of pack-years smoked. The results corroborate COPD and its acute exacerbation as a complex systemic disorder demonstrating distinct associations with the expression of enzymes linked to inflammation and the regulation of GSH metabolism.
Proximate Composition, Health Benefits, and Food Applications in Bakery Products of Purple-Fleshed Sweet Potato (Ipomoea batatas L.) and Its By-Products: A Comprehensive Review
Authors: Rosell María de los Ángeles , Quizhpe Jhazmin , Ayuso Pablo , Peñalver Rocío , Nieto Gema
Published: August 2024

Ipomoea batatas (L.) Lam is a dicotyledonous plant originally from tropical regions, with China and Spain acting as the main producers from outside and within the EU, respectively. The root, including only flesh, is the edible part, and the peel, leaves, stems, or shoots are considered by-products, which are generated due to being discarded in the field and during processing. Therefore, this study aimed to perform a comprehensive review of the nutritional value, phytochemical composition, and health-promoting activities of purple-fleshed sweet potato and its by-products, which lead to its potential applications in bakery products for the development of functional foods. The methodology is applied to the selected topic and is used to conduct the search, review abstracts and full texts, and discuss the results using different general databases. The studies suggested that purple-fleshed sweet potato parts are characterized by a high content of essential minerals and bioactive compounds, including anthocyanins belonging to the cyanidin or the peonidin type. The flesh and leaves are also high in phenolic compounds and carotenoids such as lutein and β-carotene. The high content of phenolic compounds and anthocyanins provides the purple-fleshed sweet potato with high antioxidant and anti-inflammatory power due to the modulation effect of the transcription factor Nrf2 and NF-kB translocation, which may lead to protection against hepatic and neurological disorders, among others. Furthermore, purple-fleshed sweet potato and its by-products can play a dual role in food applications due to its attractive color and wide range of biological activities which enhance its nutritional profile. As a result, it is essential to harness the potential of the purple-fleshed sweet potato and its by-products that are generated during its processing through an appropriate agro-industrial valorization system.
Eicosapentaenoic Acid (EPA) and Docosahexaenoic Acid (DHA) Ameliorate Heart Failure through Reductions in Oxidative Stress: A Systematic Review and Meta-Analysis
Authors: Seth Jayant , Sharma Sohat , Leong Cameron J. , Rabkin Simon W.
Published: August 2024

The objectives of this study were to explore the role that eicosapentaenoic acid (EPA) and/or docosahexaenoic acid (DHA) plays in heart failure (HF), highlighting the potential connection to oxidative stress pathways. Following PRISMA guidelines, we conducted electronic searches of the literature in MEDLINE and EMBASE focusing on serum EPA and/or DHA and EPA and/or DHA supplementation in adult patients with heart failure or who had heart failure as an outcome of this study. We screened 254 studies, encompassing RCTs, observational studies, and cohort studies that examined HF outcomes in relation to either serum concentrations or dietary supplementation of EPA and/or DHA. The exclusion criteria were pediatric patients, non-HF studies, abstracts, editorials, case reports, and reviews. Eleven studies met our criteria. In meta-analyses, high serum concentrations of DHA were associated with a lower rate of heart failure with a hazard ratio of 0.74 (CI = 0.59–0.94). High serum concentrations of EPA also were associated with an overall reduction in major adverse cardiovascular events with a hazard ratio of 0.60 (CI = 0.46–0.77). EPA and DHA, or n3-PUFA administration, were associated with an increased LVEF with a mean difference of 1.55 (CI = 0.07–3.03)%. A potential explanation for these findings is the ability of EPA and DHA to inhibit pathways by which oxidative stress damages the heart or impairs cardiac systolic or diastolic function producing heart failure. Specifically, EPA may lower oxidative stress within the heart by reducing the concentration of reactive oxygen species (ROS) within cardiac tissue by (i) upregulating nuclear factor erythroid 2-related factor 2 (Nrf2), which increases the expression of antioxidant enzyme activity, including heme oxygenase-1, thioredoxin reductase 1, ferritin light chain, ferritin heavy chain, and manganese superoxide dismutase (SOD), (ii) increasing the expression of copper–zinc superoxide dismutase (MnSOD) and glutathione peroxidase, (iii) targeting Free Fatty Acid Receptor 4 (Ffar4), (iv) upregulating expression of heme-oxygenase-1, (v) lowering arachidonic acid levels, and (vi) inhibiting the RhoA/ROCK signaling pathway. DHA may lower oxidative stress within the heart by (i) reducing levels of mitochondrial-fission-related protein DRP-1(ser-63), (ii) promoting the incorporation of cardiolipin within the mitochondrial membrane, (iii) reducing myocardial fibrosis, which leads to diastolic heart failure, (iv) reducing the expression of genes such as Appa, Myh7, and Agtr1α, and (v) reducing inflammatory cytokines such as IL-6, TNF-α. In conclusion, EPA and/or DHA have the potential to improve heart failure, perhaps mediated by their ability to modulate oxidative stress.
Evaluating Activation Functions in GAN Models for Virtual Inpainting: A Path to Architectural Heritage Restoration
Authors: Maitin Ana M. , Nogales Alberto , Delgado-Martos Emilio , Intra Sidola Giovanni , Pesqueira-Calvo Carlos , Furnieles Gabriel , García-Tejedor Álvaro J.
Published: August 2024

Computer vision has advanced much in recent years. Several tasks, such as image recognition, classification, or image restoration, are regularly solved with applications using artificial intelligence techniques. Image restoration comprises different use cases such as style transferring, improvement of quality resolution, or completing missing parts. The latter is also known as image inpainting, virtual image inpainting in this case, which consists of reconstructing missing regions or elements. This paper explores how to evaluate the performance of a deep learning method to do virtual image inpainting to reconstruct missing architectonical elements in images of ruined Greek temples to measure the performance of different activation functions. Unlike a previous study related to this work, a direct reconstruction process without segmented images was used. Then, two evaluation methods are presented: the objective one (mathematical metrics) and an expert (visual perception) evaluation to measure the performance of the different approaches. Results conclude that ReLU outperforms other activation functions, while Mish and Leaky ReLU perform poorly, and Swish’s professional evaluations highlight a gap between mathematical metrics and human visual perception.
Research on Predictive Auxiliary Diagnosis Method for Gastric Cancer Based on Non-Invasive Indicator Detection
Authors: Zhang Xia , Zhang Mao , Wei Gang , Wang Jia
Published: August 2024

Chronic atrophic gastritis is a serious health issue beyond the stomach health problems that affect normal life. This study aimed to explore the influencing factors related to chronic atrophic gastritis (CAG) using non-invasive indicators and establish an optimal prediction model to aid in the clinical diagnosis of CAG. Electronic medical record data from 20,615 patients with CAG were analyzed, including routine blood tests, liver function tests, and coagulation tests. The logistic regression algorithm revealed that age, hematocrit, and platelet distribution width were significant influences suggesting chronic atrophic gastritis in the Chongqing population (p < 0.05), with an area under the curve (AUC) of 0.879. The predictive model constructed based on the Random Forest algorithm exhibited an accuracy of 83.15%, precision of 97.38%, recall of 77.36%, and an F1-score of 70.86%, outperforming the models constructed using XGBoost, KNN, and SVC algorithms in a comprehensive comparison. The prediction model derived from this study serves as a valuable tool for future studies and can aid in the prediction and screening of chronic atrophic gastritis.
Trends and Future Directions in the Sports Performance of Deaf and Hard-of-Hearing Athletes: A Systematic Review
Authors: Gaweł Eliza , Soto-Rey Javier , Zwierzchowska Anna , Perez-Tejero Javier
Published: August 2024

The aim of this systematic review was twofold: to identify the main trends and issues that are being addressed by researchers in the context of physical fitness and sports performance in deaf and hard-of-hearing (D/HH) athletes and to indicate the needs and future directions that should be implemented in the training process of athletes with hearing impairments. The methodology of this systematic review was planned according to PRISMA guidelines. A search of electronic databases (PubMed, EBSCO, Scopus) was conducted to identify all studies on physical fitness, sports performance and participation, and D/HH athletes from 2003 to 2024. In total, 87 full-text articles were assessed to determine eligibility, while 34 studies met the inclusion criteria and were subjected to detailed analysis and assessment of their methodological quality. The presented systematic review indicates evidence that D/HH athletes are characterized by a similar or higher level in selected motor abilities compared to hearing athletes. Moreover, it seems that hearing impairment is not a barrier in the development of an athlete’s physical fitness, including aerobic capacity, muscular strength and power or speed of reaction. Furthermore, inclusion in sports participation and specific tools (i.e., communication aids) appear to be crucial factors for performance enhancement.
Simulation on Operating Overvoltage of Dropping Pantograph Based on Pantograph–Catenary Arc and Variable Capacitance Model
Authors: Jiang Dazuo , Zou Huanqing , Guo Yike , Tian Fuqiang , Liu Hongqi , Yin Yufeng
Published: August 2024

When the electric locomotive pantograph is dropping, the interruption of pantograph catenary contact causes electromagnetic oscillation and arcing. The frequent arc burning that occurs due to charge accumulation results in the amplitude of overvoltage increasing gradually, posing a threat to locomotive high-voltage equipment. However, the physical mechanisms and characteristics of overvoltage are still unclear. This paper proposes a simulation model of operating overvoltage due to a dropping pantograph based on the pantograph–catenary arc and variable capacitance. Distributed RLC electromagnetic oscillation is considered, which allows the real-time calculation of arc resistance and capacitance. Under the same working conditions, the error between the simulation and test results is less than 4.0%, which proves the credibility of the model. The variation law of overvoltage under different dropping speeds or catenary phases was investigated, which shows the max amplitude is 298.20 kV and steepness is 2096.80 kV/μs at 0.30 m/s speed. The waveform shows the characteristics of high amplitude and high steepness, similar to very fast transient overvoltage (VFTO). There is a sinusoidal relationship between the catenary phase and overvoltage amplitude. The closer the catenary phase to 90°, the higher the overvoltage amplitude. The research has important guiding significance for the overvoltage formation mechanism of a traction power supply system and the insulation coordination design of high-voltage equipment.
Research on Agricultural Product Price Prediction Based on Improved PSO-GA
Authors: Li Yunhong , Zhang Tianyi , Yu Xintong , Sun Feihu , Liu Pingzeng , Zhu Ke
Published: August 2024

The accurate prediction of scallion prices can not only optimize supply chain management and help related practitioners and consumers to make more reasonable purchasing decisions, but also provide guidance for farmers’ planting choices, thus enhancing market efficiency and promoting the sustainable development of the whole industry. This study adopts the idea of decomposition–denoising–aggregation, using three decomposition and denoising techniques combined with three single prediction models to form a base model. Various base models are divided into different combinations based on whether the computational structure is the same or not, and the optimal weights of the combinations are determined by using the improved particle swarm optimization–genetic algorithm (PSO-GA) optimization algorithm in different combinations. The experimental results show that the scallion price in Shandong Province from 2014 to 2023 shows an overall upward trend, and there is a cyclical and seasonal fluctuation pattern of “high in winter and low in summer”; the semi-heterogeneous-PSO-GA model reduces the MAPE by 49.03% and improves the directional accuracy by 41.52%, compared to the optimal single prediction model, ARIMA. In summary, the combined model has the most accurate prediction and strong robustness, which can provide ideas and references for the difficult problem of determining the optimal weights of the combined model in the field of predicting the prices of agricultural products.
Comparative Analysis of Neuromuscular Activation Patterns Associated with Force between Semi-Professional Female Soccer Players with Previous Anterior Cruciate Ligament Surgery and Healthy Players in Thigh Musculature Related to Valgus Collapse
Authors: Ferrández-Laliena Loreto , Sánchez-Rodríguez Rocío , Vicente-Pina Lucía , Lucha-López María Orosia , Ambrus Mira , Hidalgo-García César , Monti-Ballano Sofía , Tricás-Moreno José Miguel
Published: August 2024

This study investigates electromyography activation and force development differences in key lower limb muscles between female football players with previous anterior cruciate ligament injuries compared with healthy players. Twenty-two semi-professional players were divided into ACL-injured (n = 11) and non-injured groups (n = 11). Participants underwent maximal voluntary isometric contractions while electromyography activation, peak and average, and peak torque of force were measured. Results indicated significant differences in electromyography activation patterns between anterior cruciate ligament players and non-injured players, particularly in biceps femoris and gluteus maximus muscles. These differences were also evident when comparing between limbs within anterior cruciate ligament players. Interestingly, both groups exhibited similar peak torque of force during maximal contractions, suggesting a compensatory neuromuscular strategy that supports a return to sport based on kinetic and kinematic factors. However, these findings underscore persistent muscle integration imbalances potentially contributing to the high rate of anterior cruciate ligament reinjury. In conclusion, this study highlights the importance of evaluating electromyography activation alongside force development in understanding neuromuscular adaptations post anterior cruciate ligament injury. These insights emphasize the need for comprehensive rehabilitation strategies that address muscle imbalance to mitigate the risk of recurrent anterior cruciate ligament injuries in female football players.
Adaptive Truncation Threshold Determination for Multimode Fiber Single-Pixel Imaging
Authors: Xiang Yangyang , Li Junhui , Lan Mingying , Yang Le , Hu Xingzhuo , Ma Jianxin , Gao Li
Published: August 2024

Truncated singular value decomposition (TSVD) is a popular recovery algorithm for multimode fiber single-pixel imaging (MMF-SPI), and it uses truncation thresholds to suppress noise influences. However, due to the sensitivity of MMF relative to stochastic disturbances, the threshold requires frequent re-determination as noise levels dynamically fluctuate. In response, we design an adaptive truncation threshold determination (ATTD) method for TSVD-based MMF-SPI in disturbed environments. Simulations and experiments reveal that ATTD approaches the performance of ideal clairvoyant benchmarks, and it corresponds to the best possible image recovery under certain noise levels and surpasses both traditional truncation threshold determination methods with less computation—fixed threshold and Stein’s unbiased risk estimator (SURE)—specifically under high noise levels. Moreover, target insensitivity is demonstrated via numerical simulations, and the robustness of the self-contained parameters is explored. Finally, we also compare and discuss the performance of TSVD-based MMF-SPI, which uses ATTD, and machine learning-based MMF-SPI, which uses diffusion models, to provide a comprehensive understanding of ATTD.
Multicenter Analysis of Emergency Patient Severity through Local Model Evaluation Client Selection: Optimizing Client Selection Based on Local Model Evaluation
Authors: Kim Yong-gyom , Yang SeMo , Lee KangYoon
Published: August 2024

In multi-institutional emergency room settings, the early identification of high-risk patients is crucial for effective severity management. This necessitates the development of advanced models capable of accurately predicting patient severity based on initial conditions. However, collecting and analyzing large-scale data for high-performance predictive models is challenging due to privacy and data security concerns in integrating data from multiple emergency rooms. To address this, our work applies federated learning (FL) techniques, maintaining privacy without centralizing data. Medical data, which are often non-independent and identically distributed (non-IID), pose challenges for existing FL, where random client selection can impact overall FL performance. Therefore, we introduce a new client selection mechanism based on local model evaluation (LMECS), enhancing performance and practicality. This approach shows that the proposed FL model can achieve comparable performance to centralized models and maintain data privacy. The execution time was reduced by up to 27% compared to the existing FL algorithm. In addition, compared to the average performance of local models without FL, our LMECS improved the AUC by 2% and achieved up to 23% performance improvement compared to the existing FL algorithm. This work presents the potential for effective patient severity management in multi-institutional emergency rooms using FL without data movement, offering an innovative approach that satisfies both medical data privacy and efficient utilization.
A Study on the Factors Controlling the Kinematics of a Reactivated and Slow-Moving Landslide in the Eastern Liguria Region (NW Italy) through the Integration of Automatic Geotechnical Sensors
Authors: Pepe Giacomo , Musante Barbara , Rizzi Giovanni , Viola Greta , Vigo Andrea , Ghirotto Alessandro , Armadillo Egidio , Cevasco Andrea
Published: August 2024

This paper deals with the investigation of factors influencing the movement patterns of a reactivated slow-moving landslide situated in the eastern Liguria region (NW Italy) through the analysis of extensive ground-based hydrological and geotechnical monitoring data. Subsurface horizontal displacement and pore water pressure data were acquired simultaneously by means of automatic sensors positioned at pre-existing and localized failure zones. The joint examination of field measurements enabled us to explore the connections between rain, pore water pressure, and displacements. The results of continuous displacement monitoring showed that the landslide kinematics involved phases of extremely slow movements alternated with periods of relative inactivity. Both stages occurred prevalently at seasonal scale displaying similar durations. The slow-motion phases took place at relatively constant pore water pressure and were ascribed to mechanisms of viscous shear displacements along failure surfaces. Inactive phases entailed no significant deformations, mostly corresponding to prolonged dry periods. The two motion patterns were interrupted by episodic sharp deformations triggered by delayed (preparation periods from 4 to 11 days) rainfall-induced pore water pressure peaks, which were ascribed to sliding mechanisms taking place through rigid-plastic frictional behaviour. During these deformation events, hysteresis relationships between pore water pressure and displacement were found, revealing far more complex hydro-mechanical behaviour.
A Stock Market Decision-Making Framework Based on CMR-DQN
Authors: Chen Xun , Wang Qin , Hu Chao , Wang Chengqi
Published: August 2024

In the dynamic and uncertain stock market, precise forecasting and decision-making are crucial for profitability. Traditional deep neural networks (DNN) often struggle with capturing long-term dependencies and multi-scale features in complex financial time series data. To address these challenges, we introduce CMR-DQN, an innovative framework that integrates discrete wavelet transform (DWT) for multi-scale data analysis, temporal convolutional network (TCN) for extracting deep temporal features, and a GRU–LSTM–Attention mechanism to enhance the model’s focus and memory. Additionally, CMR-DQN employs the Rainbow DQN reinforcement learning strategy to learn optimal trading strategies in a simulated environment. CMR-DQN significantly improved the total return rate on six selected stocks, with increases ranging from 20.37% to 55.32%. It also demonstrated substantial improvements over the baseline model in terms of Sharpe ratio and maximum drawdown, indicating increased excess returns per unit of total risk and reduced investment risk. These results underscore the efficiency and effectiveness of CMR-DQN in handling multi-scale time series data and optimizing stock market decisions.
Investigation of a Method for Identifying Unbalanced States in Multi-Disk Rotor Systems: Analysis of Axis Motion Trajectory Features
Authors: Peng Jianjun , Dong En , Yang Fang , Sun Yuxiang , Zhong Zhidan
Published: August 2024

The operational state of a rotor system directly affects its working efficiency, and the axis trajectory can accurately characterize this state. Therefore, a method for extracting axis motion trajectory characteristics based on distance sequence representation is established. First, the axis trajectory sample signal is constructed from the original vibration displacement signal. Singular value decomposition (SVD) is performed on the sample signal to obtain effective components, resulting in a purified and denoised axis motion trajectory signal. Next, the axis motion trajectory signal is centralized and normalized. Feature extraction is then performed on the axis motion trajectory signal. Based on the different curvatures of various regions in the axis motion trajectory graph, data points are adaptively selected. The distances between the selected data points and a unique fixed point are calculated in the two-dimensional plane, resulting in a feature signal that characterizes the axis motion trajectory graph. This completes the extraction of the axis motion trajectory characteristics. Different rotational speeds, additional weights, and changes in rotor arrangement types are applied to a multi-disk rotor test rig to obtain measured data for various unbalanced states, validating this method. The results show that this method effectively characterizes the axis motion trajectory with strong generality.
Evaluation of In Vitro Antihypertensive and Anti-Inflammatory Properties of Dairy By-Products
Authors: Dalaka Eleni , Stefos Georgios C. , Politis Ioannis , Theodorou Georgios
Published: August 2024

Sweet whey (SW) and yogurt acid whey (YAW) are dairy by-products of the cheese-making process and Greek-style yogurt production, respectively. Both of them are considered pollutants with huge volumes of SW and YAW produced due to the growing demand for dairy products worldwide. Moreover, whey-derived peptides, resulting from fermentation as well as from further hydrolysis during digestion, have been associated with various biological activities. In the present study, the angiotensin-converting enzyme (ACE)-inhibitory activity of 48 SW samples and 33 YAW samples from bovine, ovine, caprine, and ovine/caprine milk obtained were evaluated. Additionally, the SW and YAW digestates and two of their fractions (smaller than 10 kDa, SW-D-P10 and YAW-D-P10, and smaller than 3 kDa, SW-D-P3 and YAW-D-P3), which were obtained after in vitro digestion and subsequent ultrafiltration, were also subjected to evaluation. Our data indicated that the D-P10 and D-P3 fractions exhibited higher ACE-inhibitory activity compared to the corresponding values before digestion. The ACE-inhibitory capacity after in vitro digestion was higher for the ovine SW samples compared to their bovine and caprine counterparts. The effect of the D-P3 fraction on the inhibition of nitric oxide (NO) production and the expression of a selected panel of immune-response-related genes in LPS-stimulated RAW 264.7 macrophages was also evaluated. Fractions from both dairy by-products inhibited NO production in LPS-stimulated RAW 264.7 cells. Especially, ovine SW-D-P3 showed a strong NO inhibitory activity and suppressed inducible nitric oxide synthase (Nos2) mRNA levels. However, YAW-D-P3 could not trigger neither the gene expression of inflammatory macrophage mediators Nos2 and cyclooxygenase-2 (Ptgs2) nor tumor necrosis factor-α (Tnf) and interleukin 6 (Il6) in LPS-stimulated murine macrophages regardless of animal origin. These findings suggest that in vitro digestion could enhance the production of ACE-inhibitory peptides in both dairy by-products, while SW from ovine origin displays higher potential as an anti-inflammatory agent, effectively preventing excessive NO production.
A Novel Battery-Supplied AFE EEG Circuit Capable of Muscle Movement Artifact Suppression
Authors: Delis Athanasios , Tsavdaridis George , Tsanakas Panayiotis
Published: August 2024

In this study, the fundamentals of electroencephalography signals, their categorization into frequency sub-bands, the circuitry used for their acquisition, and the impact of noise interference on signal acquisition are examined. Additionally, design specifications for medical-grade and research-grade EEG circuits and a comprehensive analysis of various analog front-end architectures for electroencephalograph (EEG) circuit design are presented. Three distinct selected case studies are examined in terms of comparative evaluation with generic EEG circuit design templates. Moreover, a novel one-channel battery-supplied EEG analog front-end circuit designed to address the requirements of usage protocols containing strong compound muscle movements is introduced. Furthermore, a realistic input signal generator circuit is proposed that models the human body and the electromagnetic interference from its surroundings. Experimental simulations are conducted in 50 Hz and 60 Hz electrical grid environments to evaluate the performance of the novel design. The results demonstrate the efficacy of the proposed system, particularly in terms of bandwidth, portability, Common Mode Rejection Ratio, gain, suppression of muscle movement artifacts, electrostatic discharge and leakage current protection. Conclusively, the novel design is cost-effective and suitable for both commercial and research single-channel EEG applications. It can be easily incorporated in Brain–Computer Interfaces and neurofeedback training systems.
A Similarity Clustering Deformation Prediction Model Based on GNSS/Accelerometer Time-Frequency Analysis
Authors: Han Houzeng , Li Rongheng , Xu Tao , Du Meng , Ma Wenxuan , Wu He
Published: August 2024

Structural monitoring is crucial for assessing structural health, and high-precision deformation prediction can provide early warnings for safety monitoring. To address the issue of low prediction accuracy caused by the non-stationary and nonlinear characteristics of deformation sequences, this paper proposes a similarity clustering (SC) deformation prediction model based on GNSS/accelerometer time-frequency analysis. First, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm is used to decompose the original monitoring data, and the time-frequency characteristic correlations of the deformation data are established. Then, similarity clustering is conducted for the monitoring sub-sequences based on their frequency domain characteristics, and clustered sequences are combined subsequently. Finally, the Long Short-Term Memory (LSTM) model is used to separately predict GNSS displacement and acceleration with clustered time series, and the overall deformation displacement is reconstructed based on the predicted GNSS displacement and acceleration-derived displacement. A shake table simulation experiment was conducted to validate the feasibility and performance of the proposed CEEMDAN-SC-LSTM model. A duration of 5 s displacement prediction is analyzed after 153 s of monitoring data training. The results demonstrate that the root mean square error (RMSE) of predicted displacement is 0.011 m with the proposed model, which achieves an improvement of 64.45% and 61.51% in comparison to the CEEMDAN-LSTM and LSTM models, respectively. The acceleration predictions also show an improvement of 96.49% and 95.58%, respectively, the RMSE of the predicted acceleration-reconstructed displacement is less than 1 mm, with a reconstruction similarity of over 99%. The overall displacement reconstruction similarity can reach over 95%.
Soldiers and Prisoners in Motion in Mesopotamian Iconography during the Early Bronze Age
Authors: Couturaud Barbara
Published: August 2024

Military images of the ancient Near East during the Early Bronze Age are characterized by one of their main features: the serial reproduction of soldiers and prisoners, side by side, the former clearly identifiable by the visual signs of power they bear and the latter by their humiliation. These images are usually and almost naturally conceived as the ideological prerogative of city-states in conflict for territorial domination or as signs of visual identity intended to reinforce the powers that be. However, the end of the Early Bronze Age is marked by the hegemony of the Akkadian dynasty and the iconographic changes that it generated. While strongly maintaining the military iconographic theme in its visual discourse, it broke with the motif of static parades of prisoners and introduced many details intended to clearly identify the protagonists, the enemies, or the environment of the battles. It could represent a transition from a discourse based on evocative repetition in order to present an ideal to one founded on detailed narration in order to assert the authenticity of an event. This paper investigates the phenomenon of repetition through soldiers and prisoners on images. Analyzing the message lying behind the series of hindered prisoners and battalions of soldiers also underlines the way the change of iconographic discourse during the Akkadian period can be understood, particularly given that the power of the Akkadian dynasty mainly rested on its military victories.
Assessment of Radon Concentration and Health Hazards in Natural Spring Water of a Sub-Himalayan District
Authors: Sajid Ayesha , Anjum Mavia , Younis Hannan , Salouci Moustafa , Mehboob Khurram , Haj Ismail Abd
Published: August 2024

The objective of this study was to evaluate the extent of radon contamination in twenty-six drinking water samples from natural springs were collected from Dhirkot Azad Kashmir, along with four bottled mineral water samples. Radon gas escapes from the earth’s crust due to uranium ores and diffuses into the atmosphere. This study assessed the levels of radon concentration, the yearly effective radiation dose, and carcinogenic risk from radon exposure in drinking water samples. The radon concentration varied from 0.28 to 30.25 Bq/L. The mean radon concentration of all samples was found to be 7.86 ± 2.3 Bq/L. The radon concentrations in bottled drinking water were found to be lower than those in natural springs. The statistical and GIS analyses included the use of interpolation and Pearson’s correlation matrix. Seven samples had radon concentration that surpassed the standard limit established by the US-EPA, which is 11 Bq/L. The average annual effective dose from inhalation and ingestion was found to be lower than the value (0.1 mSv/y) provided by the WHO, but for some natural spring water samples, it exceeded the risk limit. The cancer risk revealed that 40% of the samples had an elevated lifetime cancer risk from radon exposure. Overall, the majority of the results obtained aligned with the worldwide guidelines established by the US-EPA. However, there were a few instances where the limits were exceeded, and constant monitoring is recommended. This study establishes a baseline for radon concentration in the area and provides a basis for future studies.
Fox’s H-Functions: A Gentle Introduction to Astrophysical Thermonuclear Functions
Authors: Haubold Hans J. , Kumar Dilip , Kabeer Ashik A.
Published: August 2024

Needed for cosmological and stellar nucleosynthesis, we are studying the closed-form analytic evaluation of thermonuclear reaction rates. In this context, we undertake a comprehensive analysis of three largely distinct velocity distributions, namely the Maxwell–Boltzmann distribution, the pathway distribution, and the Mittag-Leffler distribution. Moreover, a natural generalization of the Maxwell–Boltzmann velocity distribution is discussed. Furthermore, an explicit evaluation of the reaction rate integral in the high-energy cut-off case is carried out. Generalized special functions of mathematical physics like Meijer’s G-function and Fox’s H-functions and their utilization in mathematical physics are the prime focus of this paper.
Interactive Cascaded Network for Prostate Cancer Segmentation from Multimodality MRI with Automated Quality Assessment
Authors: Kou Weixuan , Rey Cristian , Marshall Harry , Chiu Bernard
Published: August 2024

The accurate segmentation of prostate cancer (PCa) from multiparametric MRI is crucial in clinical practice for guiding biopsy and treatment planning. Existing automated methods often lack the necessary accuracy and robustness in localizing PCa, whereas interactive segmentation methods, although more accurate, require user intervention on each input image, thereby limiting the cost-effectiveness of the segmentation workflow. Our innovative framework addresses the limitations of current methods by combining a coarse segmentation network, a rejection network, and an interactive deep network known as Segment Anything Model (SAM). The coarse segmentation network automatically generates initial segmentation results, which are evaluated by the rejection network to estimate their quality. Low-quality results are flagged for user interaction, with the user providing a region of interest (ROI) enclosing the lesions, whereas for high-quality results, ROIs were cropped from the automatic segmentation. Both manually and automatically defined ROIs are fed into SAM to produce the final fine segmentation. This approach significantly reduces the annotation burden and achieves substantial improvements by flagging approximately 20% of the images with the lowest quality scores for manual annotation. With only half of the images manually annotated, the final segmentation accuracy is statistically indistinguishable from that achieved using full manual annotation. Although this paper focuses on prostate lesion segmentation from multimodality MRI, the framework can be adapted to other medical image segmentation applications to improve segmentation efficiency while maintaining high accuracy standards.
ClpL Chaperone as a Possible Component of the Disaggregase Activity of Limosilactobacillus fermentum U-21
Authors: Al Ebrahim Rahaf N. , Alekseeva Maria G. , Bazhenov Sergey V. , Fomin Vadim V. , Mavletova Dilara A. , Nesterov Andrey A. , Poluektova Elena U. , Danilenko Valeriy N. , Manukhov Ilya V.
Published: August 2024

The L. fermentum U-21 strain, known for secreting chaperones into the extracellular milieu, emerges as a promising candidate for the development of novel therapeutics termed disaggregases for Parkinson’s disease. Our study focuses on characterizing the secreted protein encoded by the C0965_000195 locus in the genome of this strain. Through sequence analysis and structural predictions, the protein encoded by C0965_000195 is identified as ClpL, homologs of which are known for their chaperone functions. The chaperone activity of ClpL from L. fermentum U-21 is investigated in vivo by assessing the refolding of luciferases with varying thermostabilities from Aliivibrio fischeri and Photorhabdus luminescens within Escherichia coli cells. The results indicate that the clpL gene from L. fermentum U-21 can compensate for the absence of the clpB gene, enhancing the refolding capacity of thermodenatured proteins in clpB-deficient cells. In vitro experiments demonstrate that both spent culture medium containing proteins secreted by L. fermentum U-21 cells, including ClpL, and purified heterologically expressed ClpL partially prevent the thermodenaturation of luciferases. The findings suggest that the ClpL protein from L. fermentum U-21, exhibiting disaggregase properties against aggregating proteins, may represent a key component contributing to the pharmabiotic attributes of this strain.
Novel Therapeutic Horizons: SNCA Targeting in Parkinson’s Disease
Authors: Caramiello Alessio Maria , Pirota Valentina
Published: August 2024

Alpha-synuclein (αSyn) aggregates are the primary component of Lewy bodies, which are pathological hallmarks of Parkinson’s disease (PD). The toxicity of αSyn seems to increase with its elevated expression during injury, suggesting that therapeutic approaches focused on reducing αSyn burden in neurons could be beneficial. Additionally, studies have shown higher levels of SNCA mRNA in the midbrain tissues and substantia nigra dopaminergic neurons of sporadic PD post-mortem brains compared to controls. Therefore, the regulation of SNCA expression and inhibition of αSyn synthesis could play an important role in the pathogenesis of injury, resulting in an effective treatment approach for PD. In this context, we summarized the most recent and innovative strategies proposed that exploit the targeting of SNCA to regulate translation and efficiently knock down cytoplasmatic levels of αSyn. Significant progress has been made in developing antisense technologies for treating PD in recent years, with a focus on antisense oligonucleotides and short-interfering RNAs, which achieve high specificity towards the desired target. To provide a more exhaustive picture of this research field, we also reported less common but highly innovative strategies, including small molecules, designed to specifically bind 5′-untranslated regions and, targeting secondary nucleic acid structures present in the SNCA gene, whose formation can be modulated, acting as a transcription and translation control. To fully describe the efficiency of the reported strategies, the effect of αSyn reduction on cellular viability and dopamine homeostasis was also considered.