bluuebunny/crossref_metadata_2025 huggingface dataset:
The Management of Perinatal Borderline Personality Disorder
Authors: Sved Williams Anne , Hill Rebecca
Published: October 2023

Borderline personality disorder (BPD) is highly prevalent in clinical perinatal mental health settings, although there are few systematic programmes to identify BPD at this time. Retrospective studies show compromised birth outcomes for women with this condition, and several authors have highlighted a significant range of problem outcomes for offspring identifiable from early infancy through the adult years, including the intergenerational transfer of mental health problems from mother to child. A literature review identifies the varying prevalence rates found in non-clinical and clinical settings and the paucity of published studies on the management of perinatal BPD, in particular focused both on the mother and mother-infant relationships. A case study is presented to show both the potential benefits of inpatient mother-baby unit protocols and of specialised longer-term group therapy. Many knowledge gaps can be identified for further clinical research that could potentially benefit families with perinatal BPD, including systematic identification of perinatal BPD and intensive programmes that not only could perhaps improve birth outcomes but also provide skills to mothers to help with their emotional regulation and potentially improve mother-infant relationships and longer-term offspring developmental pathways.
The Levels of Leptin, Cystatin C, Neuropilin-1 and Tau Protein in Relation to Dietary Habits in Patients with Alzheimer’s Disease
Authors: Bogdan Sylwia , Puścion-Jakubik Anna , Klimiuk Katarzyna , Socha Katarzyna , Kochanowicz Jan , Gorodkiewicz Ewa
Published: October 2023

Alzheimer’s disease (AD) is the most common form of dementia in older people. Its prevalence is expected to increase, and therefore it poses a serious challenge to the healthcare system. The aim of the study was to assess the concentration of leptin, cystatin C, neuropilin-1 and tau protein, as well as the influence of dietary habits on these parameters, in a group of AD patients (n = 110) compared to 60 healthy people (n = 60). It has been shown that AD patients, compared to healthy people, are characterized by significantly higher median concentrations of leptin (9.97 vs. 3.08), cystatin c (1.53 vs. 0.56) and tau protein (8.46 vs. 4.19), but significantly lower median neuropilin-1 (69.94 vs. 167.28). Multiple regression analyses showed that leptin levels could be explained by dietary habits in 27%, cystatin C in 51%, neuropilin-1 in 41% and tau protein in 25% of cases. Modification of eating habits may contribute to improving the values of the discussed parameters.
Larval Wound Therapy: Possibilities and Potential Limitations—A Literature Review
Authors: Bazaliński Dariusz , Przybek-Mita Joanna , Pytlak Kamila , Kardyś Daria , Bazaliński Adrian , Kucharzewski Marek , Więch Paweł
Published: October 2023

Patient-centered care (PCC) is recognized as a standard in healthcare for determining high quality. Honoring patients’ values, experiences, needs, and preferences in devising, coordinating, and delivering care underscores the enhancement of the therapeutic rapport between patients and healthcare providers. Wound treatment involves a multi-stage process encompassing diagnostics and local wound dressing, which reduces the risk of infection through a coordinated interdisciplinary team. Within this team, nurses undertake specific professional functions and roles. The implementation of local therapy using innovative and scientifically substantiated methods may be hindered by a deficit of knowledge or inappropriate knowledge among staff and patients themselves. This study presents the challenges concerning the care of patients with chronic wounds treated using Lucilia sericata larvae, based on a review of the current scientific literature. A critical analysis of the literature spanning from 2002 to 2022 was conducted using the Medline, PubMed, Cochrane, and Termedia databases, employing keywords such as “maggot debridement therapy” in relation to acceptance and perception. As a result of the preliminary selection, 472 papers were identified, of which 12 publications were included in the development of this concept. The acquired data were organized and presented in the concluding section in the form of tables, accompanied by descriptions and references to individual studies. Negative psychological and somatic sensations were among the most prominent challenges among patients treated with Maggot Debridement Therapy (MDT). Pain related to peripheral ischemia or infection in this group of patients requires pain prophylaxis, including hyperalgesia and allodynia, in order to improve method tolerance. On the other hand, augmenting patients’ understanding of MDT diminishes negative emotions, reinforces positive behaviors, and mitigates anxiety levels. MDT constitutes an effective and safe method. Its widespread use for chronic wounds requires substantial knowledge among healthcare professionals and patient education, along with that of their caregivers, to develop a positive attitude.
Force–Velocity Relationship in Cycling and Arm Cranking: A Comparison of Men and Women
Authors: Heller Jan , Kinkorova Ivana , Vodicka Pavel , Nikolaidis Pantelis Theodoros , Balko Stefan
Published: October 2023

This study was aimed at comparing the force–velocity relationship during cycling and arm cranking in males and females. Thirty-two male and twenty-two female healthy volunteers performed a force–velocity test on a cycle ergometer and a cranking ergometer in a randomly selected order. The theoretical values of the maximum force at zero speed (F0) and the maximum velocity at zero braking force (v0) for the lower and upper limbs were determined, and the maximum anaerobic power (Pmax) was calculated from the individual force–velocity relationship. The Pmax and F0 of the upper limbs related to the lower limbs correspond to 78.2 ± 14.3% and 80.1 ± 17.3% in men and 65.5 ± 12.5% and 74.5 ± 6.5% in women, respectively. The theoretical maximum velocity v0 of the upper limbs to the lower limbs attained 129.1 ± 29.0% in men and 127.4 ± 26.4% in women. The results of the study can serve as reference data for the force–velocity characteristics of the upper and lower limbs of male and female athletes. The results can be used both in training and rehabilitation programs, where the starting point is the objectification of possible strength deficits in various areas of the force–velocity characteristic spectrum of the muscles of the upper and lower limbs.
A Comprehensive Review of Floating Solar Plants and Potentials for Offshore Applications
Authors: Huang Guozhen , Tang Yichang , Chen Xi , Chen Mingsheng , Jiang Yanlin
Published: October 2023

Fossil fuel consumption has progressively increased alongside global population growth, representing the predominant energy consumption pattern for humanity. Unfortunately, this persistent reliance on fossil fuels has resulted in a substantial surge in pollution emissions, exerting a detrimental influence on the delicate ecological balance. Therefore, it is imperative to find new renewable energy sources to replace fossil fuels. Solar energy is a clean energy source and has become the most preferred option for human day-to-day needs. Since the construction of the world’s first floating photovoltaic power station, humanity has been continuously advancing the technology of power generation by floating photovoltaics. This review comprehensively elucidates the progression of offshore photovoltaic technology and illustrates the composition of the floating photovoltaic system. Each section meticulously contrasts the advantages and drawbacks of various photovoltaic systems. In addition, an in-depth analysis of the offshore photovoltaic application potentials is conducted based on fundamental theories, thereby offering valuable insights for future research. Finally, an encompassing summary of the potential challenges associated with deep-sea floating photovoltaic systems is presented.
Screening of Undaria pinnatifida (Laminariales, Phaeophyceae) Lipidic Extract as a New Potential Source of Antibacterial and Antioxidant Compounds
Authors: Stabili Loredana , Acquaviva Maria Immacolata , Cecere Ester , Gerardi Carmela , Petrocelli Antonella , Fanizzi Francesco Paolo , Angilè Federica , Rizzo Lucia
Published: October 2023

The lipidic extract of Undaria pinnatifida, one of the worst invasive species, was investigated for its potential exploitation in biotechnological applications. The antimicrobial activity of the lipidic extract in three different portions (blade, sporophyll, and holdfast) was assessed by using the Kirby–Bauer method, while the antioxidant activity was evaluated by the TEAC, ORAC, and Folin–Ciocalteu assays. NMR spectroscopy and thin-layer chromatography were employed for the chemical characterization. The extracts showed antibacterial activity against several of the tested Vibrio species: V. aestuarinus, V. fischeri, V. furnisii, V. inusitatus, V. litoralis, and V. mediterranei, including some pathogens for farmed fish. Intriguing antioxidant activity was recorded, with the highest value in the blade (126.907 ± 28.993 mmol Trolox equivalent/g TEAC). Free, saturated, unsaturated, and polyunsaturated fatty acids were highlighted by 1D and 2D NMR spectroscopy. The presence of ω-3 and ω-6 PUFAs indicates the importance of this algal species in the food industry. We suggest the employment of U. pinnatifida as source of new and safer therapeutic agents to control fish and shellfish diseases due to vibriosis, as well as a source of natural antioxidants that are useful for human health, considering the growing interest in the development of strategies for invasive seaweed control.
The Influence of Oscillatory Frequency on the Structural Breakup and Recovery of Coastal Mud
Authors: Gu Hengye , Wang Shaohua , Su Zhitong , Xia Yuezhang
Published: October 2023

The structural breakup and recovery of coastal mud are closely related to wave propagation, mud transportation, and coastal morphology evolution. Due to the influence of climate, topography, and other factors, the wave frequency in marine environments is more variable than fixed. To investigate the mud structural breakup and recovery process under oscillatory shear loads with different frequencies, a series of oscillatory rheological experiments of the coastal mud collected from the tidal flats of Zhairuoshan Island, Zhejiang province, China, were carried out. The results revealed that the structural breakup of coastal mud had a two-step transition process. The fluidization occurs more rapidly at higher frequencies, but the influence of frequency on the two yield stresses is limited. In addition, frequency has a complex effect on the structural recovery of coastal mud. The normalized equilibrium storage modulus (G∞′/G0′) does not change monotonically with frequency. Moreover, the viscosity quickly approaches equilibrium when a shear load is applied. After that, when a low-frequency load is applied, G∞′/G0′ is no longer related to the pre-shear duration. However, when a high-frequency load is applied, G∞′/G0′ of the mud sample pre-sheared for 500 s is significantly larger than that of the sample pre-sheared to the minimum viscosity. This study is anticipated to provide reference and supplementary test data for understanding the interaction between waves of different frequencies and muddy seabed.
A New Approach for Production Prediction in Onshore and Offshore Tight Oil Reservoir
Authors: Qiu Kaixuan , Fan Kaifeng , Chen Xiaolin , Lei Gang , Wei Shiming , Navik Rahul , Li Jia
Published: October 2023

Rapid technological advances have accelerated offshore and onshore tight oil extraction to meet growing energy demand. Reliable tools to carry out production prediction are essential for development of unconventional reservoirs. The existed tri-linear analytical solutions are verified to be versatile enough to capture fundamental flow mechanisms and make accurate production predictions. However, these solutions are obtained in Laplace space with the Laplace transform and numerical inversion, which may lead to uncertainty in the solution. In this paper, a general analytical solution is derived in real-time space through integral transform and average pressure substitution. Namely, the partial differential equations describing subsurface fluid flow are firstly triple-integrated and then the obtained volume average pressure are replaced with the rate-dependent expressions. Furthermore, the ordinary differential equations related to oil rate are solved analytically in real-time space. To validate our model, this derived solution is verified against two numerical models constructed with two typical physical configurations. The great match indicates the accuracy and applicability of the analytical solution. According to the developed workflow, two field cases including offshore and onshore tight oilfield data are selected for history matching and production prediction. This new approach not only makes the obtained solution more simplified, but also helps field engineers diagnose flow patterns more quickly to better optimize production schemes.
Predicting 90-Day Prognosis in Ischemic Stroke Patients Post Thrombolysis Using Machine Learning
Authors: Abujaber Ahmad A. , Albalkhi Ibrahem , Imam Yahia , Nashwan Abdulqadir J. , Yaseen Said , Akhtar Naveed , Alkhawaldeh Ibraheem M.
Published: October 2023

(1) Objective: This study aimed to construct a machine learning model for predicting the prognosis of ischemic stroke patients who underwent thrombolysis, assessed through the modified Rankin Scale (mRS) score 90 days after discharge. (2) Methods: Data were sourced from Qatar’s stroke registry covering January 2014 to June 2022. A total of 723 patients with ischemic stroke who had received thrombolysis were included. Clinical variables were examined, encompassing demographics, stroke severity indices, comorbidities, laboratory results, admission vital signs, and hospital-acquired complications. The predictive capabilities of five distinct machine learning models were rigorously evaluated using a comprehensive set of metrics. The SHAP analysis was deployed to uncover the most influential predictors. (3) Results: The Support Vector Machine (SVM) model emerged as the standout performer, achieving an area under the curve (AUC) of 0.72. Key determinants of patient outcomes included stroke severity at admission; admission systolic and diastolic blood pressure; baseline comorbidities, notably hypertension (HTN) and coronary artery disease (CAD); stroke subtype, particularly strokes of undetermined origin (SUO); and hospital-acquired urinary tract infections (UTIs). (4) Conclusions: Machine learning can improve early prognosis prediction in ischemic stroke, especially after thrombolysis. The SVM model is a promising tool for empowering clinicians to create individualized treatment plans. Despite limitations, this study contributes to our knowledge and encourages future research to integrate more comprehensive data. Ultimately, it offers a pathway to improve personalized stroke care and enhance the quality of life for stroke survivors.
Bayesian Sequential Design for Identifying and Ranking Effective Patient Subgroups in Precision Medicine in the Case of Counting Outcome Data with Inflated Zeros
Authors: Vinnat Valentin , Annane Djillali , Chevret Sylvie
Published: October 2023

Precision medicine is revolutionizing health care, particularly by addressing patient variability due to different biological profiles. As traditional treatments may not always be appropriate for certain patient subsets, the rise of biomarker-stratified clinical trials has driven the need for innovative methods. We introduced a Bayesian sequential scheme to evaluate therapeutic interventions in an intensive care unit setting, focusing on complex endpoints characterized by an excess of zeros and right truncation. By using a zero-inflated truncated Poisson model, we efficiently addressed this data complexity. The posterior distribution of rankings and the surface under the cumulative ranking curve (SUCRA) approach provided a comprehensive ranking of the subgroups studied. Different subsets of subgroups were evaluated depending on the availability of biomarker data. Interim analyses, accounting for early stopping for efficacy, were an integral aspect of our design. The simulation study demonstrated a high proportion of correct identification of the subgroup which is the most predictive of the treatment effect, as well as satisfactory false positive and true positive rates. As the role of personalized medicine grows, especially in the intensive care setting, it is critical to have designs that can manage complicated endpoints and that can control for decision error. Our method seems promising in this challenging context.
Optimal Allocation of Territorial Space in the Minjiang River Basin Based on a Double Optimization Simulation Model
Authors: Wang Ge , Zhou Ziqi , Xia Jianguo , Ou Dinghua , Fei Jianbo , Gong Shunya , Xiang Yuxiao
Published: October 2023

The unequal distribution of territorial space resources stands out as a leading cause of the human–land contradictions and environmental degradation. These issues are especially pronounced in the Minjiang River Basin, which exhibits significant regional disparities. In pursuit of solutions to these pressing problems and the identification of sustainable developmental pathways, this study presents an innovative territorial space double optimization simulation model. This model integrates quantity structure optimization and distribution pattern optimization, in order to comprehensively consider the optimization of territorial space allocation and build a new territorial space pattern for the Minjiang River Basin in 2030. On this basis, we employed the Patch-generating Land Use Simulation (PLUS) model and scenario analysis method to design the double optimization scenario and natural development scenario. By comparing these two scenarios, and calculating the ecological benefits (EB), economic benefits (ECB), carbon storage (CS), and comprehensive benefits (CB) achieved in different scenarios, the validity of the double optimization model was fully verified. The results indicated that: ① the loss of sub-ecological space (PeS) under the natural development scenario was significantly larger than that under the double optimization scenario, and the loss should be mainly attributed to the large expansion of production space (PS) and living space (LS); ② the area of ecological space (ES) has reduced since 2020, but less area was lost and the retention rate was higher under the double optimization scenario; ③ the natural development scenario made the research region gain more ECB, but it also resulted in the loss of more EB and CS, whereas the Minjiang River Basin under the double optimization scenario was able to effectively balance the relationship among the three, thus achieving the best CB. The research findings provide strong scientific support for alleviating the human–land contradictions, protecting the ecological security in the basin, and promoting the sustainable development of the region.
Physics-Informed Machine Learning—An Emerging Trend in Tribology
Authors: Marian Max , Tremmel Stephan
Published: October 2023

Physics-informed machine learning (PIML) has gained significant attention in various scientific fields and is now emerging in the area of tribology. By integrating physics-based knowledge into machine learning models, PIML offers a powerful tool for understanding and optimizing phenomena related to friction, wear, and lubrication. Traditional machine learning approaches often rely solely on data-driven techniques, lacking the incorporation of fundamental physics. However, PIML approaches, for example, Physics-Informed Neural Networks (PINNs), leverage the known physical laws and equations to guide the learning process, leading to more accurate, interpretable and transferable models. PIML can be applied to various tribological tasks, such as the prediction of lubrication conditions in hydrodynamic contacts or the prediction of wear or damages in tribo-technical systems. This review primarily aims to introduce and highlight some of the recent advances of employing PIML in tribological research, thus providing a foundation and inspiration for researchers and R&D engineers in the search of artificial intelligence (AI) and machine learning (ML) approaches and strategies for their respective problems and challenges. Furthermore, we consider this review to be of interest for data scientists and AI/ML experts seeking potential areas of applications for their novel and cutting-edge approaches and methods.
Innovative Insights on the Thin Square Plate Large Deflection Problem
Authors: Hakim Gilad , Abramovich Haim
Published: October 2023

Thin plates subjected to transverse load and undergoing large deflections have been widely studied and published in the literature. However, there is still a lack of information and understanding about the membrane stresses created under large deflections and their associated Airy stress function, as displayed in the well-known von Kármán equations set. The present study aims at providing explicit expressions for the membrane stresses, the deflections, and the Airy stress function for a general square plate area vertically uniformly loaded to reach large deflection state. This was obtained by using the results of a high-fidelity finite element analysis applied on a lateral loaded simply supported thin square plate, which are then casted to yield approximate Fourier series expressions for the membrane stresses, deflections, and the Airy stress function. The stress map figures provide a good understanding of the critical points on the plate, while the explicit mathematical expressions enabled the calculation of deflections and stresses for the entire plate area. Among other interesting findings, the presence of relatively high tensile and compressive membrane stresses existing near the plate edges was revealed, which might lead to potential failure hazards. The derivatives of the deflections and the Airy stress function enabled the validation of the large deflections von Kármán equations set for the investigated case, and it turned out that the generated expressions for the stresses and the lateral deflection based on a high-fidelity finite element model satisfy the second equation with a good accuracy, while the first one remains to further be investigated. Moreover, using the generated explicit equations, the load influence on the deflections and stresses was also analyzed to yield general novel expressions for the medium and very large deflections states. To generalize the investigated case, the stresses and the deflections were non-dimensionalized so they can be used for any material and plate dimensions.
Precision Face Milling of Maraging Steel 350: An Experimental Investigation and Optimization Using Different Machine Learning Techniques
Authors: Abbas Adel T. , Helmy Mohamed O. , Al-Abduljabbar Abdulhamid A. , Soliman Mahmoud S. , Hasan Ali S. , Elkaseer Ahmed
Published: October 2023

Maraging steel, characterized by its superior strength-to-weight ratio, wear resistance, and pressure tolerance, is a material of choice in critical applications, including aerospace and automotive components. However, the machining of this material presents significant challenges due to its inherent properties. This study comprehensively examines the impacts of face milling variables on maraging steel’s surface quality, cutting temperature, energy consumption, and material removal rate (MRR). An experimental analysis was conducted, and the gathered data were utilized for training and testing five machine learning (ML) models: support vector machine (SVM), K-nearest neighbor (KNN), artificial neural network (ANN), random forest, and XGBoost. Each model aimed to predict the outcomes of different machining parameters efficiently. XGBoost emerged as the most effective, delivering an impressive 98% prediction accuracy across small datasets. The study extended into applying a genetic algorithm (GA) for optimizing XGBoost’s hyperparameters, further enhancing the model’s predictive accuracy. The GA was instrumental in multi-objective optimization, considering various responses, including surface roughness and energy consumption. The optimization process evaluated different weighting methods, including equal weights and weights derived from the analytic hierarchy process (AHP) based on expert insights. The findings indicate that the refined XGBoost model, augmented by GA-optimized hyperparameters, provides highly accurate predictions for machining parameters. This outcome holds significant implications for industries engaged in the machining of maraging steel, offering a pathway to optimized operational efficiency, reduced costs, and enhanced product quality amid the material’s machining challenges.
EHB Gear-Drive Symmetric Dead-Zone Finite-Time Adaptive Control
Authors: Wang Shuai , Cao Qinghua , Ma Fukuo , Wu Jian
Published: October 2023

Intelligent driving vehicles require more accurate and stable braking control. Electrohydraulic braking (EHB) systems can better adapt to the development of autonomous driving technology. The gear transmission system plays a crucial role in EHB deceleration and torque increase mechanisms. However, its dead-zone nonlinearity poses challenges for EHB control. To address the position-control problem in the EHB gear transmission system, we propose a finite-time adaptive control method for the symmetrical dead zone. This approach combines adaptive control theory with finite-time control theory and designs parameter-updating laws for the unknown parameters in the system. Boundary estimates are introduced into the parameter-update laws and control laws to compensate for unknown disturbances. By adjusting the relevant parameters, the convergence rate can be improved, ensuring that errors converge within a specified range within a limited time. After modifying the parameter-updating laws and control laws, all closed-loop signals remain bounded. Finally, we validate the proposed control strategy through simulation and hardware-in-the-loop (HIL) testing. The results demonstrate that the control strategy developed in this study achieves high tracking accuracy and stability even in the presence of dead zones, unknown parameters, and unknown interferences in the EHB gear-drive servo system.
On the Double-Zero Bifurcation of Jerk Systems
Authors: Lăzureanu Cristian
Published: October 2023

In this paper, we construct approximate normal forms of the double-zero bifurcation for a two-parameter jerk system exhibiting a non-degenerate fold bifurcation. More precisely, using smooth invertible variable transformations and smooth invertible parameter changes, we obtain normal forms that are also jerk systems. In addition, we discuss some of their parametric portraits.
A Fractional-Order Memristive Two-Neuron-Based Hopfield Neuron Network: Dynamical Analysis and Application for Image Encryption
Authors: Venkatesh Jayaraman , Pchelintsev Alexander N. , Karthikeyan Anitha , Parastesh Fatemeh , Jafari Sajad
Published: October 2023

This paper presents a study on a memristive two-neuron-based Hopfield neural network with fractional-order derivatives. The equilibrium points of the system are identified, and their stability is analyzed. Bifurcation diagrams are obtained by varying the magnetic induction strength and the fractional-order derivative, revealing significant changes in the system dynamics. It is observed that lower fractional orders result in an extended bistability region. Also, chaos is only observed for larger magnetic strengths and fractional orders. Additionally, the application of the fractional-order model for image encryption is explored. The results demonstrate that the encryption based on the fractional model is efficient with high key sensitivity. It leads to an encrypted image with high entropy, neglectable correlation coefficient, and uniform distribution. Furthermore, the encryption system shows resistance to differential attacks, cropping attacks, and noise pollution. The Peak Signal-to-Noise Ratio (PSNR) calculations indicate that using a fractional derivative yields a higher PSNR compared to an integer derivative.
Strong Differential Subordinations and Superordinations for Riemann–Liouville Fractional Integral of Extended q-Hypergeometric Function
Authors: Alb Lupaş Alina , Oros Georgia Irina
Published: October 2023

The notions of strong differential subordination and its dual, strong differential superordination, have been introduced as extensions of the classical differential subordination and superordination concepts, respectively. The dual theories have developed nicely, and important results have been obtained involving different types of operators and certain hypergeometric functions. In this paper, quantum calculus and fractional calculus aspects are added to the study. The well-known q-hypergeometric function is given a form extended to fit the study concerning previously introduced classes of functions specific to strong differential subordination and superordination theories. Riemann–Liouville fractional integral of extended q-hypergeometric function is defined here, and it is involved in the investigation of strong differential subordinations and superordinations. The best dominants and the best subordinants are provided in the theorems that are proved for the strong differential subordinations and superordinations, respectively. For particular functions considered due to their remarkable geometric properties as best dominant or best subordinant, interesting corollaries are stated. The study is concluded by connecting the results obtained using the dual theories through sandwich-type theorems and corollaries.
A Comprehensive Study on Advancement in Hybrid Contraction and Graphical Analysis of £-Fuzzy Fixed Points with Application
Authors: Rashid Maliha , Azam Akbar , Dar Fatima , Ali Faryad , Al-Kadhi Mohammed A.
Published: October 2023

Hybrid contractions serve as a flexible and versatile framework for establishing fixed-point Theorems and analyzing the convergence of iterative algorithms. This paper demonstrates the adapted form of the admissible hybrid fuzzy Z-contraction in the perspective of £-fuzzy set-valued maps for extended ♭-metric spaces. Sufficient criteria for obtaining £-fuzzy fixed points for this contraction have been established. In addition, the hypotheses of its main result are endorsed by some nontrivial supportive examples featuring graphical illustrations. Consequently, the concept of graphical extended ♭-metric spaces is introduced and a £-fuzzy fixed point result in the context of newly defined space is derived. Illustrative examples, incorporating relevant graphs, are provided with the support of a computer simulation to validate the established results, enhancing the understanding of the underlying notions and investigations. The concepts presented here not only considerably improve, enrich, and extend a number of well-known pre-existing fixed-point results but also assemble and merge several ones in the corresponding domain.
Low-Resource Language Processing Using Improved Deep Learning with Hunter–Prey Optimization Algorithm
Authors: Al-Wesabi Fahd N. , Alshahrani Hala J. , Osman Azza Elneil , Abd Elhameed Elmouez Samir
Published: October 2023

Low-resource language (LRL) processing refers to the development of natural language processing (NLP) techniques and tools for languages with limited linguistic resources and data. These languages often lack well-annotated datasets and pre-training methods, making traditional approaches less effective. Sentiment analysis (SA), which involves identifying the emotional tone or sentiment expressed in text, poses unique challenges for LRLs due to the scarcity of labelled sentiment data and linguistic intricacies. NLP tasks like SA, powered by machine learning (ML) techniques, can generalize effectively when trained on suitable datasets. Recent advancements in computational power and parallelized graphical processing units have significantly increased the popularity of deep learning (DL) approaches built on artificial neural network (ANN) architectures. With this in mind, this manuscript describes the design of an LRL Processing technique that makes use of Improved Deep Learning with Hunter–Prey Optimization (LRLP-IDLHPO). The LRLP-IDLHPO technique enables the detection and classification of different kinds of sentiments present in LRL data. To accomplish this, the presented LRLP-IDLHPO technique initially pre-processes these data to improve their usability. Subsequently, the LRLP-IDLHPO approach applies the SentiBERT approach for word embedding purposes. For the sentiment classification process, the Element-Wise–Attention GRU network (EWAG-GRU) algorithm is used, which is an enhanced version of the recurrent neural network. The EWAG-GRU model is capable of processing temporal features and includes an attention strategy. Finally, the performance of the EWAG-GRU model can be boosted by adding the HPO algorithm for use in the hyperparameter tuning process. A widespread simulation analysis was performed to validate the superior results derived from using the LRLP-IDLHPO approach. The extensive results indicate the significant superiority of the performance of the LRLP-IDLHPO technique compared to the state-of-the-art approaches described in the literature.
Relating Antimicrobial Resistance and Virulence in Surface-Water E. coli
Authors: LaMontagne Connor D. , Christenson Elizabeth C. , Rogers Anna T. , Jacob Megan E. , Stewart Jill R.
Published: October 2023

The role of the environment in the emergence and spread of antimicrobial resistance (AMR) is being increasingly recognized, raising questions about the public health risks associated with environmental AMR. Yet, little is known about pathogenicity among resistant bacteria in environmental systems. Existing studies on the association between AMR and virulence are contradictory, as fitness costs and genetic co-occurrence can be opposing influences. Using Escherichia coli isolated from surface waters in eastern North Carolina, we compared virulence gene prevalence between isolates resistant and susceptible to antibiotics. We also compared the prevalence of isolates from sub-watersheds with or without commercial hog operations (CHOs). Isolates that had previously been evaluated for phenotypic AMR were paired by matching isolates resistant to any tested antibiotic with fully susceptible isolates from the same sample date and site, forming 87 pairs. These 174 isolates were evaluated by conventional PCR for seven virulence genes (bfp, fimH, cnf-1, STa (estA), EAST-1 (astA), eae, and hlyA). One gene, fimH, was found in 93.1% of isolates. Excluding fimH, at least one virulence gene was detected in 24.7% of isolates. Significant negative associations were found between resistance to at least one antibiotic and presence of at least one virulence gene, tetracycline resistance and presence of a virulence gene, resistance and STa presence, and tetracycline resistance and STa presence. No significant associations were found between CHO presence and virulence, though some sub-significant associations merit further study. This work builds our understanding of factors controlling AMR dissemination through the environment and potential health risks.
Isolation, Characterization and Genomic Analysis of a Novel Jumbo Phage, AerS_266, That Infects Aeromonas salmonicida
Authors: Morozova Vera , Babkin Igor , Kozlova Yuliya , Tikunov Artem , Ushakova Tatiana , Bardasheva Alevtina , Fedorets Valeria , Zhirakovskaya Elena , Tikunova Nina
Published: October 2023

Aeromonas salmonicida is the causative agent of septicemia in fish, and it is associated with significant economic losses in the aquaculture industry. While piscine Aeromonas infections are mainly treated with antibiotics, the emergence of resistance in bacterial populations requires the development of alternative methods of treatment. The use of phages can be one of them. A novel A. salmonicida jumbo phage, AerS_266, was isolated and characterized. This phage infects only mesophilic A. salmonicida strains and demonstrates a slow lytic life cycle. Its genome contains 243,674 bp and 253 putative genes: 84 encode proteins with predicted functions, and 3 correspond to tRNAs. Genes encoding two multisubunit RNA polymerases, chimallin and PhuZ, were identified, and AerS_266 was thus defined as a phiKZ-like phage. While similar phages with genomes >200 kb specific to Aeromonas hydrophila and Aeromonas veronii have been previously described, AerS_266 is the first phiKZ-like phage found to infect A. salmonicida.
Variations in the Relative Abundance of Gut Bacteria Correlate with Lipid Profiles in Healthy Adults
Authors: Kalnina Ineta , Gudra Dita , Silamikelis Ivars , Viksne Kristine , Roga Ance , Skinderskis Edmunds , Fridmanis Davids , Klovins Janis
Published: October 2023

The gut microbiome is a versatile system regulating numerous aspects of host metabolism. Among other traits, variations in the composition of gut microbial communities are related to blood lipid patterns and hyperlipidaemia, yet inconsistent association patterns exist. This study aims to assess the relationships between the composition of the gut microbiome and variations in lipid profiles among healthy adults. This study used data and samples from 23 adult participants of a previously conducted dietary intervention study. Circulating lipid measurements and whole-metagenome sequences of the gut microbiome were derived from 180 blood and faecal samples collected from eight visits distributed across an 11-week study. Lipid-related variables explained approximately 4.5% of the variation in gut microbiome compositions, with higher effects observed for total cholesterol and high-density lipoproteins. Species from the genera Odoribacter, Anaerostipes, and Parabacteroides correlated with increased serum lipid levels, whereas probiotic species like Akkermansia muciniphila were more abundant among participants with healthier blood lipid profiles. An inverse correlation with serum cholesterol was also observed for Massilistercora timonensis, a player in regulating lipid turnover. The observed correlation patterns add to the growing evidence supporting the role of the gut microbiome as an essential regulator of host lipid metabolism.
Unveiling Hidden Risks: Intentional Molecular Screening for Sexually Transmitted Infections and Vaginosis Pathogens in Patients Who Have Been Exclusively Tested for Human Papillomavirus Genotyping
Authors: Hernández-Rosas Fabiola , Rey-Barrera Manuel , Hernández-Barajas Flavio , Rangel-Soto Claudia , García-González Mariana Socorro , Franco-González Shumeyker Susmith , de León-Bautista Mercedes Piedad
Published: October 2023

Human papillomavirus (HPV) is the most prevalent sexually transmitted infection (STI) worldwide, with popular screening methods including the Papanicolaou test and HPV genotyping. However, in clinical practice, coinfections with other pathogens are often underestimated. Therefore, our study aims to describe the prevalence of STIs and vaginosis in urogenital samples from patients who had been tested exclusively for HPV genotyping. Methods: This analytical, prospective, cross-sectional study included 408 males and females. Eligible participants had positive and negative HPV genotyping test results and agreed to early detection or had HPV antecedents. They provided the same urogenital samples used for HPV detection and, through our multiplex in-house PCR assay, we screened for Candida spp., Ureaplasma spp., Trichomonas vaginalis, Neisseria gonorrhoeae, Chlamydia trachomatis, herpes simplex virus 1 and 2 (HSV), Mycoplasma spp., molluscum contagiosum virus (MCV), Treponema pallidum, Haemophilus spp., Staphylococcus aureus, and Klebsiella spp. The subsequent statistical analysis aimed to reveal correlations between HPV genotypes and the identified pathogens. Results: Of the participants, 72.1% (n = 294) tested positive for HPV genotypes. HR-HPV (high-risk HPV) genotypes comprised 51 (8.1%), 66 (7.1%), and 58 (6.1%). Haemophilus spp., Ureaplasma spp., Candida spp., Staphylococcus aureus, and Mycoplasma spp. frequently co-occurred with HPV infection (p < 0.05). Gender-based variations were notorious for Ureaplasma spp., Mycoplasma spp., and MCV (p < 0.05). Coinfections were prevalent (43.9%), with a positive HPV result elevating the risk for Trichomonas vaginalis, Mycoplasma spp., Staphylococcus aureus, HSV, and MCV (OR > 1, p < 0.05). HPV 16 correlated with HSV and Ureaplasma spp., while HPV 6 was linked with HSV and MCV (p < 0.05). Conclusions: This screening strategy uncovered significant coinfections and associations between HPV genotypes and pathogens, underscoring the importance of routine screening to explore clinical implications in urogenital health.
Exploring the Appeal of Car-Borne Central Control Platforms Based on Driving Experience
Authors: Lin Chih-Kuan , Chen Chien-Hsiung , Shen Kai-Shuan
Published: October 2023

This study explored drivers’ emotion-based impressions of car-borne central control platforms (CBCCPs) for personal-use vehicles. Thus, this preference-based study examined experts’ and drivers’ opinions regarding the appeal of CBCCPs from the perspective of Miryoku engineering. To this end, this study analyzed data via the EGM (evaluation grid method (EGM) and quantification theory type I. Results: Drivers’ preferences for specific CBCCP design characteristics were categorized into the factors “legible”, convenient”, and “tasteful”, which comprised the core of the EGM semantic hierarchical diagram. In addition, the importance of CBCCPs’ appeal factors and characteristics was assessed through quantification theory type I. The findings of this study provide valuable insights for designers, manufacturers, and researchers interested in the design of CBCCPs. Additionally, the results of this study can contribute to research on applied psychology, human–computer interactions, and car interface design.
GluN2A and GluN2B N-Methyl-D-Aspartate Receptor (NMDARs) Subunits: Their Roles and Therapeutic Antagonists in Neurological Diseases
Authors: Ladagu Amany Digal , Olopade Funmilayo Eniola , Adejare Adeboye , Olopade James Olukayode
Published: October 2023

N-methyl-D-aspartate receptors (NMDARs) are ion channels that respond to the neurotransmitter glutamate, playing a crucial role in the permeability of calcium ions and excitatory neurotransmission in the central nervous system (CNS). Composed of various subunits, NMDARs are predominantly formed by two obligatory GluN1 subunits (with eight splice variants) along with regulatory subunits GluN2 (GluN2A-2D) and GluN3 (GluN3A-B). They are widely distributed throughout the CNS and are involved in essential functions such as synaptic transmission, learning, memory, plasticity, and excitotoxicity. The presence of GluN2A and GluN2B subunits is particularly important for cognitive processes and has been strongly implicated in neurodegenerative diseases like Parkinson’s disease and Alzheimer’s disease. Understanding the roles of GluN2A and GluN2B NMDARs in neuropathologies provides valuable insights into the underlying causes and complexities of major nervous system disorders. This knowledge is vital for the development of selective antagonists targeting GluN2A and GluN2B subunits using pharmacological and molecular methods. Such antagonists represent a promising class of NMDA receptor inhibitors that have the potential to be developed into neuroprotective drugs with optimal therapeutic profiles.
Tolerance-Aided Interference Degradation for Optical OFDM in Power-Constrained Systems
Authors: Gao Yan , Lian Jie
Published: October 2023

Optical wireless communications (OWCs) are power-efficient for providing short-range and high-speed data transmission. In this paper, we propose an interference degradation algorithm for power-constrained OWC systems when using orthogonal frequency division multiplexing (OFDM). In this algorithm, we introduce a decision tolerance at the receiver that can be optimally designed to reduce interference caused by peak power clipping distortion and decrease additive noise collected by the photodetectors. Although the recently proposed clipping-enhanced optical OFDM (CEO-OFDM) can transmit clipped information through extra signal frames, reconstructing the received signal introduces more noise. Using the proposed decision tolerance, we can determine whether the signals in the extra frame are required for data reconstruction. By optimally choosing the decision tolerance, the bit error rate (BER) performance is enhanced compared to those of DCO, ACO, and CEO-OFDM. Additionally, the proposed algorithm offers a wider dynamic modulation index range than DCO, ACO, and CEO-OFDM at the same BER. Using the tested parameters, the proposed algorithm with 64-QAM achieves a similar best BER performance as DCO, ACO, and CEO-OFDM using 32-QAM. Therefore, the proposed algorithm achieves a higher data rate than those of the other compared techniques.
Genome-Wide Association Studies of Biluochun Tea Plant Populations in Dongting Mountain and Comprehensive Identification of Candidate Genes Associated with Core Agronomic Traits by Four Analysis Models
Authors: Lei Xiaogang , Li Haoyu , Li Pingping , Zhang Huan , Han Zhaolan , Yang Bin , Duan Yu , Njeri Ndombi Salome , Yang Daqiang , Zheng Junhua , Ma Yuanchun , Zhu Xujun , Fang Wanping
Published: October 2023

The elite germplasm resources are key to the beautiful appearance and pleasant flavor of Biluochun tea. We collected and measured the agronomic traits of 95 tea plants to reveal the trait diversity and breeding value of Biluochun tea plant populations. The results revealed that the agronomic traits of Biluochun tea plant populations were diverse and had high breeding value. Additionally, we resequenced these tea plant populations to reveal genetic diversity, population structure, and selection pressure. The Biluochun tea plant populations contained two groups and were least affected by natural selection based on the results of population structure and selection pressure. More importantly, four non-synonymous single nucleotide polymorphisms (nsSNPs) and candidate genes associated with (−)-gallocatechin gallate (GCG), (−)-gallocatechin (GC), and caffeine (CAF) were detected using at least two GWAS models. The results will promote the development and application of molecular markers and the utilization of elite germplasm from Biluochun populations.
Fusarium Head Blight Infection Induced Responses of Six Winter Wheat Varieties in Ascorbate–Glutathione Pathway, Photosynthetic Efficiency and Stress Hormones
Authors: Sunic Katarina , Brkljacic Lidija , Vukovic Rosemary , Katanic Zorana , Salopek-Sondi Branka , Spanic Valentina
Published: October 2023

Fusarium head blight (FHB) is one of the most studied fungal diseases of wheat, causing massive grain yield and quality losses. This study aimed to extend previous studies on the physiological and biochemical responses of winter wheat to FHB stress in a controlled environment by focusing on the ascorbate-glutathione pathway (AsA-GSH), photosynthetic efficiency, and stress hormone levels, thus providing insight into the possible interactions of different defense mechanisms during infection. The activity of AsA-GSH metabolism was increased in FHB resistant varieties, maintaining the redox state of spikes, and consequently preserving functional photosystem II. Furthermore, carotenoids (Car) were shown to be the major pigments in the photosystem assembly, as they decreased in FHB-stressed spikes of resistant and moderately resistant varieties, compared to controls. Car are also the substrate for the synthesis of abscisic acid (ABA), which acts as a fungal effector and its elevated content leads to increased FHB susceptibility in inoculated spikes. The results of this study contributed to the knowledge of FHB resistance mechanisms and can be used to improve the breeding of FHB resistant varieties, which is considered to be the most effective control measure.