bluuebunny/crossref_metadata_2025 huggingface dataset:
Unraveling the Influence of Perceived Built Environment on Commute Mode Choice Based on Hybrid Choice Model
Authors: Lu Huan , Gan Hongcheng
Published: September 2024

To address the limitations of existing studies on the built environment and commute mode choice, which primarily focus on the objective and residential built environment, this study investigates how commuters’ perceptions of the built environment at their residences and workplaces influence their choice of commuting mode. First, six latent variables are proposed to characterize the perceived built environment. Then, commuters’ socio-economic and commuting characteristics are treated as exogenous variables. Subsequently, the influence of the perceived built environment on commute mode choice is analyzed using both a Multinomial Logit (MNL) model without latent variables and a Hybrid Choice Model (HCM) incorporating variables related to the perceived built environment. Finally, a case study conducted in Shanghai reveals that the goodness-of-fit value of the HCM improves by approximately 27.4% compared to that of the MNL, indicating that the perceived built environment plays a significant role in explaining commute mode choice. Furthermore, commuters’ socio-economic profiles, commuting characteristics, and perceptions of the built environment all significantly influence their commute mode choices. The perceived built environment at residences has a stronger impact on commute mode choice than that at workplaces. Among the various commute modes of driving, cycling, walking, and public transit, the perceived built environment most significantly influences public transit usage. Based on these findings, several policy implications are offered, providing decision-making support for urban planning and traffic management authorities.
Knowledge Embedding Relation Network for Small Data Defect Detection
Authors: Ruan Jinjia , He Jin , Tong Yao , Wang Yuchuan , Fang Yinghao , Qu Liang
Published: September 2024

In industrial vision, the lack of defect samples is one of the key constraints of depth vision quality inspection. This paper mainly studies defect detection under a small training set, trying to reduce the dependence of the model on defect samples by using normal samples. Therefore, we propose a Knowledge-Embedding Relational Network. We propose a Knowledge-Embedding Relational Network (KRN): firstly, unsupervised clustering and convolution features are used to model the knowledge of normal samples; at the same time, based on CNN feature extraction assisted by image segmentation, the conv feature is obtained from the backbone network; then, we build the relationship between knowledge and prediction samples through covariance, embed the knowledge, further mine the correlation using gram operation, normalize the power of the high-order features obtained by covariance, and finally send them to the prediction network. Our KRN has three attractive characteristics: (I) Knowledge Modeling uses the unsupervised clustering algorithm to statistically model the standard samples so as to reduce the dependence of the model on defect data. (II) Covariance-based Knowledge Embedding and the Gram Operation capture the second-order statistics of knowledge features and predicted image features to deeply mine the robust correlation. (III) Power Normalizing suppresses the burstiness of covariance module learning and the complexity of the feature space. KRN outperformed several advanced baselines in small training sets on the DAGM 2007, KSDD, and Steel datasets.
On the Control and Validation of the PARA-SILSROB Surgical Parallel Robot
Authors: Pisla Doina , Popa Calin , Pusca Alexandru , Ciocan Andra , Gherman Bogdan , Mois Emil , Cailean Andrei-Daniel , Vaida Calin , Radu Corina , Chablat Damien , Hajjar Nadim Al
Published: September 2024

This paper presents the development of the hardware and software architecture of a sixdegrees of freedom (DOF) parallel robot (PARA-SILSROB) by illustrating all the stages undertaken to achieve the experimental model of the robot. Based on the experimental model, the control architecture is also presented, which is primarily based on a master–slave control system through which the surgeon controls the robot using the master console composed of commercial peripheral components (two 3D Space Mouse devices, computer, and keyboard) integrated with the solution developed in this study and presented in this paper. The robot was developed also according to the surgical protocol and surgeon’s requirements, and for the functionality testing of the mechanical structure, two experimental stands were used. The first stand presented several surgical steps, such as manipulation, resection, and suture of experimental tissues (simulating real-life robot-assisted surgical maneuvers) using commercial instruments. The second stand presented a simulation of an esophagectomy for esophageal cancer and digestive reconstruction through a right intercostal approach. For this testing phase, the organs were created using 3D reconstruction, and their simplified models were 3D printed using PolyJet technology. Furthermore, the input trajectory generated using the master console was compared with the robot actuator’s movements and the obtained results were used for validation of the proposed robot control system.
Machine Learning Use Cases in the Frequency Symbolic Method of Linear Periodically Time-Variable Circuits Analysis
Authors: Shapovalov Yuriy , Mankovskyy Spartak , Bachyk Dariya , Piwowar Anna , Chruszczyk Łukasz , Grzechca Damian
Published: September 2024

This manuscript presents an analysis of machine learning (ML) usage in the Frequency Symbolic Method (FSM) to enhance the diagnosis of faults in parametric circuit analysis and optimization, with a particular focus on Linear Periodically Time-Variable (LPTV) systems. We put forth a few ML-based approaches for fault diagnosis (including anomaly detection), invisible feature detection, and the prediction of FSM output. These methodologies concentrate on identifying and diagnosing faults by evaluating particular ML techniques, extracting pertinent features, and determining the desired diagnostic outputs. The use cases of ML application considered in this paper demonstrate that machine learning can enhance fault detection and diagnosis, reduce human errors and identify previously unnoticed anomalies within the FSM framework. ML has never been used in FSM before, so the key aim of this paper is to consider possible use cases of AI application in FSM. Additionally, feature extraction, required as an input stage for the ML model, is proposed based on FSM peculiarities. This work can be considered a study of ML application in FSM.
A Method for Detecting the Yarn Roll’s Margin Based on VGG-UNet
Authors: Wang Junru , Zhao Xiong , Peng Laihu , Wang Honggeng
Published: September 2024

The identification of the yarn roll’s margin represents a critical phase in the automated production of textiles. At present, conventional visual detection techniques are inadequate for accurately measuring, filtering out background noise, and generalizing the margin of the yarn roll. To address this issue, this study constructed a semantic segmentation dataset for the yarn roll and proposed a new method for detecting the margin of the yarn roll based on deep learning. By replacing the encoder component of the U-Net with the initial 13 convolutional layers of VGG16 and incorporating pre-trained weights, we constructed a VGG-UNet model that is well suited for yarn roll segmentation. A comparison of the results obtained on the test set revealed that the model achieved an average Intersection over Union (IoU) of 98.70%. Subsequently, the contour edge point set was obtained through the application of traditional image processing techniques, and contour fitting was performed. Finally, the actual yarn roll margin was calculated based on the relationship between pixel dimensions and actual dimensions. The experiments demonstrate that the margin of the yarn roll can be accurately measured with an error of less than 3 mm. This is particularly important in situations where the margin is narrow, as the detection accuracy remains high. This study provides significant technical support and a theoretical foundation for the automation of the textile industry.
Assessment of Fatigue Crack Growth Characteristics of Laminated Biaxial/Triaxial Hybrid Composite in Wind Turbine Blades
Authors: Kim Hak-Geun , Kang Ki-Weon
Published: September 2024

The composite blade is integral to megawatt-class wind turbines and frequently incurs interlaminar damages such as adhesive failures, cracks, and fractures, which may originate from manufacturing flaws or sustained external fatigue loads. Notably, adhesive joint failure in the spar–web and trailing edge (TE) represents a predominant damage mode. This study systematically explores the failure mechanism in these regions, using mode I fracture toughness tests for an in-depth, quantitative analysis of the adhesive joint’s fatigue crack growth characteristics. Additionally, we conducted extensive material and technical evaluations on specimen units, aiming to validate the reliability of techniques employed for wind blade damage modeling. A damage model, inspired by the NREL 5 MW wind generator’s composite blade structure, meticulously considers the interactions between the TE and spar–web. Utilizing the virtual crack closure technique (VCCT), this model effectively simulates crack growth dynamics in wind blade adhesive joints, while the extended finite element method (XFEM) aids in analyzing crack propagation trajectories under repetitive fatigue loading. By applying this integrated methodology, we successfully determined the lifespan of the spar–web adhesive joint under constant load amplitudes, providing crucial insights into the resilience and longevity of critical wind turbine components.
Numerical Study of Flow Separation Control over a Hump Airfoil Using a Novel Sweeping Jet Actuator
Authors: Zhao Tong , Bai Yalei
Published: September 2024

Sweeping jet (SWJ) actuators have become a hot research topic in flow control due to their larger sweep range and higher control efficiency. However, the linear relationship between frequency and velocity ratio (VR = Ujet/U∞) in the SWJ actuator makes it challenging to determine the dominant factor affecting the control effect. Decoupling the frequency and VR and determining the control mechanism of the SWJ actuator is, therefore, a difficult task. In this study, a novel type of SWJ actuator was designed using periodic synthetic jets instead of feedback channels. This achieved the implementation of different frequencies under the same VR, effectively decoupling frequency and VR. The SWJ actuator was then applied in flow separation control of a Hump airfoil, with F+ = f × c/U∞ = 0.375, F+ = 1, and F+ = 10 being the three forcing frequencies studied. Numerical results demonstrated that all three forcing frequencies displayed a control effect on flow separation. At VR = 1.8, the control effectiveness is optimal for F+ = 1, and as VR continues to increase, F+ = 10 becomes the optimal control frequency.
Quantitative Analysis of Sterols and Oxysterols in Foods by Gas Chromatography Coupled with Mass Spectrometry
Authors: Derewiaka Dorota , Pydyn Mateusz
Published: September 2024

The study aimed to determine the content of sterol oxidation products (oxysterols) in selected processed food products with the use of GC-MS. It is known that an excessively high consumption of cholesterol in foods can lead to atherosclerosis and coronary heart disease and may also promote the appearance of gallstones. Cholesterol oxidation products have mutagenic, angiotoxic and cytotoxic properties and can lead to the development of atherosclerosis and promote the occurrence of some cancers. The cholesterol content in the tested products ranged from 8.72 to 2007.11 mg/100 g fat, and plant sterols were determined in 5 out of 12 tested products and their content ranged from 5.88 to 380.8 mg/100 g fat. The studies showed the presence of sterol oxidation products in each analyzed product. The total oxysterol content ranged from 0.16 to 3.95 μg/g fat in pastry products and from 0.06 to 9.72 μg/g fat in meat products. Due to the presence of sterol oxidation products in all analyzed products, their content in food products should be monitored. The presented analytical method is a proper tool for the determination of sterol oxidation products in different food matrices.
Multiplexing Multi-Scale Features Network for Salient Target Detection
Authors: Liu Xiaoxuan , Peng Yanfei , Wang Gang , Wang Jing
Published: September 2024

This paper proposes a multiplexing multi-scale features network (MMF-Network) for salient target detection to tackle the issue of incomplete detection structures when identifying salient targets across different scales. The network, based on encoder–decoder architecture, integrates a multi-scale aggregation module and a multi-scale visual interaction module. Initially, a multi-scale aggregation module is constructed, which, despite potentially introducing a small amount of noise, significantly enhances the high-level semantic and geometric information of features. Subsequently, SimAM is employed to emphasize feature information, thereby highlighting the significant target. A multi-scale visual interaction module is designed to enable compatibility between low-resolution and high-resolution feature maps, with dilated convolutions utilized to expand the receptive field of high-resolution feature maps. Finally, the proposed MMF-Network is tested on three datasets: DUTS-Te, HUK-IS, and PSCAL-S, achieving scores of 0.887, 0.811, and 0.031 in terms of its F-value SSIM and MA, respectively. The experimental results demonstrate that the MMF-Network exhibits a superior performance in salient target detection.
Research on the Impact of Flexible Working Hours on Reducing Traffic Delays in the City
Authors: Kalašová Alica , Paľo Jozef , Černický Ľubomír , Čulík Kristián
Published: September 2024

Nowadays, traffic congestion poses a significant problem in urban areas, affecting daily life. The imbalance between supply and demand causes overloading. Intersections are critical nodes in urban transport networks, and their design has a substantial impact on traffic safety and efficiency. Microscopic traffic flow models, which describe vehicle maneuvers and traffic patterns, are widely used for optimal design and performance evaluation of transportation facilities. This article focuses on traffic modeling at intersections using the Aimsun software. The examined intersections are located in Topoľčany, Slovakia, where a 13-h traffic survey was conducted on Tovarnická Street. In addition to the current situation, simulations were performed for scenarios distributing 10% and 20% of peak traffic intensity over longer periods, with overall quality levels determined. This article highlights the importance of researching intersection throughput and the need for capacity assessment in planning any construction that affects traffic in the area.
Stair Design and User Interaction
Authors: Koutamanis Alexander
Published: September 2024

Stairs are among the key elements in architectural composition, both aesthetically and spatially. They are also one of the main innovations in architecture and building, allowing pedestrians to bridge considerable height differences with relative efficiency. It is, therefore, surprising that, in spite of all stair regulations in building codes, stairs are responsible for a huge number of accidents—second only to motorcars. The extent of safety failures suggests that user interaction with stairs is poorly understood by designers and policy makers. This is not unrelated to the lack of research into the design and use of stairs. Templer’s seminal work is the exception, but it dates from 1992, and since then, little has been done to understand the relation between architectural design and stair performance, including safety. The paper reviews the literature on stairs in multiple domains and proposes that to redress poor stair performance, research and practice should build on affordance-based analyses of stair climbability, which establish a clear connection between the form of a stair and the perception of both action possibilities and dangers by all kinds of users. By doing so, affordances establish a comprehensive and consistent framework for the analysis of architectural designs, which utilizes both domain and psychological knowledge, including as a foundation for computational applications.
The Use of Fuzzy Modelling Based on Expert Knowledge to Determine Poland’s Energy Security Index Taking into Account Political Conditions
Authors: Joostberens Jarosław , Rybak Aurelia , Rybak Aleksandra
Published: September 2024

This article presents the results of research on the energy security index in Poland. Since the development of renewable energy sources forced by the transformation of the national energy system will require an increased supply of rare earth elements, the level of demand for these metals was taken into account when determining the energy security index. Furthermore, the development of renewable energy sources in Poland will directly depend on the volume of energy demand and, as the events of previous years have shown, on political and legal conditions, especially in the case of wind energy. Since some of these factors are qualitative, it was impossible to use a quantitative method. Therefore, fuzzy sets were used. Fuzzy modelling is based on expert knowledge. Using this method, the authors created three alternative scenarios for the development of Poland’s energy security index: pessimistic, optimistic, and the most probable.
Cohen–Grossberg Neural Network Delay Models with Fractional Derivatives with Respect to Another Function—Theoretical Bounds of the Solutions
Authors: Agarwal Ravi , Hristova Snezhana , O’Regan Donal
Published: September 2024

The Cohen–Grossberg neural network is studied in the case when the dynamics of the neurons is modeled by a Riemann–Liouville fractional derivative with respect to another function and an appropriate initial condition is set up. Some inequalities about both the quadratic function and the absolute values functions and their fractional derivatives with respect to another function are proved and they are based on an appropriate modification of the Razumikhin method. These inequalities are applied to obtain the bounds of the norms of any solution of the model. In particular, we apply the squared norm and the absolute values norms. These bounds depend significantly on the function applied in the fractional derivative. We study the asymptotic behavior of the solutions of the model. In the case when the function applied in the fractional derivative is increasing without any bound, the norms of the solution of the model approach zero. In the case when the applied function in the fractional derivative is equal to the current time, the studied problem reduces to the model with the classical Riemann–Liouville fractional derivative and the obtained results gives us sufficient conditions for asymptotic behavior of the solutions for the corresponding model. In the case when the function applied in the fractional derivative is bounded, we obtain a finite bound for the solutions of the model. This bound depends on the initial function and the solution does not approach zero. An example is given illustrating the theoretical results.
On the Connection between Nelson’s Stochastic Quantum Mechanics and Nottale’s Theory of Scale Relativity
Authors: Chavanis Pierre-Henri
Published: September 2024

In this paper, we review and compare the stochastic quantum mechanics of Nelson and the scale relativity theory of Nottale. We consider both nonrelativistic and relativistic frameworks and include the electromagnetic field. These theories propose a derivation of the Schrödinger and Klein–Gordon equations from microscopic processes. We show their formal equivalence. Specifically, we show that the real and imaginary parts of the complex Lorentz equation in Nottale’s theory are equivalent to the Nelson equations, which are themselves equivalent to the Madelung and de Broglie hydrodynamical representations of the Schrödinger and Klein–Gordon equations, respectively. We discuss the different physical interpretations of the Nelson and Nottale theories and stress their strengths and weaknesses. We mention potential applications of these theories to dark matter.
NaBH4-Poly(Ethylene Oxide) Composite Electrolyte for All-Solid-State Na-Ion Batteries
Authors: Luo Xiaoxuan , Aguey-Zinsou Kondo-Francois
Published: September 2024

A disordered sodium borohydride (NaBH4) environment to facilitate Na+ mobility was achieved by partially hydrolyzing NaBH4 and this significantly improved Na+ ionic conductivity to 10−3 S cm−1 at 75 °C. The reaction rate of NaBH4 self-hydrolysis, however, is determined by several parameters, including the reaction temperature, the molar ratio between NaBH4 and H2O, and the pH value; but these factors are hard to control. In this paper, poly(ethylene oxide) (PEO), capable of retaining H2O through hydrogen bonding, was used in an attempt to better control the amount of H2O available for NaBH4 self-hydrolysis. This strategy led to the ionic conductivity of 1.6 × 10−3 S cm−1 at 45 °C with a Na+ transference number of 0.54. The amorphous nature of the PEO matrix in hydrolyzed NaBH4 is also believed to provide a conduction path for fast Na+ conduction.
A Data-Centric Approach to Understanding the 2020 U.S. Presidential Election
Authors: Srinivasan Satish Mahadevan , Paat Yok-Fong
Published: September 2024

The application of analytics on Twitter feeds is a very popular field for research. A tweet with a 280-character limitation can reveal a wealth of information on how individuals express their sentiments and emotions within their network or community. Upon collecting, cleaning, and mining tweets from different individuals on a particular topic, we can capture not only the sentiments and emotions of an individual but also the sentiments and emotions expressed by a larger group. Using the well-known Lexicon-based NRC classifier, we classified nearly seven million tweets across seven battleground states in the U.S. to understand the emotions and sentiments expressed by U.S. citizens toward the 2020 presidential candidates. We used the emotions and sentiments expressed within these tweets as proxies for their votes and predicted the swing directions of each battleground state. When compared to the outcome of the 2020 presidential candidates, we were able to accurately predict the swing directions of four battleground states (Arizona, Michigan, Texas, and North Carolina), thus revealing the potential of this approach in predicting future election outcomes. The week-by-week analysis of the tweets using the NRC classifier corroborated well with the various political events that took place before the election, making it possible to understand the dynamics of the emotions and sentiments of the supporters in each camp. These research strategies and evidence-based insights may be translated into real-world settings and practical interventions to improve election outcomes.
Sentiment Informed Sentence BERT-Ensemble Algorithm for Depression Detection
Authors: Ogunleye Bayode , Sharma Hemlata , Shobayo Olamilekan
Published: September 2024

The World Health Organisation (WHO) revealed approximately 280 million people in the world suffer from depression. Yet, existing studies on early-stage depression detection using machine learning (ML) techniques are limited. Prior studies have applied a single stand-alone algorithm, which is unable to deal with data complexities, prone to overfitting, and limited in generalization. To this end, our paper examined the performance of several ML algorithms for early-stage depression detection using two benchmark social media datasets (D1 and D2). More specifically, we incorporated sentiment indicators to improve our model performance. Our experimental results showed that sentence bidirectional encoder representations from transformers (SBERT) numerical vectors fitted into the stacking ensemble model achieved comparable F1 scores of 69% in the dataset (D1) and 76% in the dataset (D2). Our findings suggest that utilizing sentiment indicators as an additional feature for depression detection yields an improved model performance, and thus, we recommend the development of a depressive term corpus for future work.
Grape Varieties for Sparkling Wine Production in Santa Catarina, Brazil: A Study of Phenology, Production, Chemical Composition, and Sensory Evaluation
Authors: Canossa Adrielen Tamiris , Würz Douglas André , Brighenti Alberto Fontanella , Rufato Daiana Petry , Rufato Leo
Published: September 2024

High-altitude and cold climate regions such as São Joaquim, in Santa Catarina, Brazil, a recent wine-growing region, are characterized by wines with pronounced acidity, ideal for sparkling wine production. The cultivars with potential for producing sparkling wines in this region were unknown. This research evaluates quality sparkling wines from Ribolla Gialla, Riesling Renano, Solaris, Sangiovese, Canaiolo Nero, Chardonnay, and Pinot Noir. The study considered the phenological, productive, and qualitative performance of these varieties in the 2017/2018 and 2018/2019 seasons. Ribolla Gialla, Riesling Renano, and Sangiovese, with later bud break and better productive aspects, are the best viticultural adaptations for the region. Riesling Renano maintains higher acidity. Sparkling wines from Solaris, Chardonnay, and Ribolla Gialla showed the most balanced chemical parameters. Sangiovese produced sparkling wine with the highest aroma intensity and toasted notes. Considering phenological, productive, and qualitative parameters, Riesling Renano, Ribolla Gialla, and Sangiovese are the most promising varieties for sparkling wine production in São Joaquim. Quality sparkling wines can be produced in this region using varieties different from those traditionally used in Brazil, enhancing the diversity of Brazilian viticulture.
African Cultivated, Wild and Weedy Rice (Oryza spp.): Anticipating Further Genomic Studies
Authors: Kehinde Babatunde O. , Xie Lingjuan , Song Beng-Kah , Zheng Xiaoming , Fan Longjiang
Published: September 2024

Rice is a staple crop in sub-Saharan Africa, and it is mostly produced by Asian cultivars of Oryza sativa that were introduced to the continent around the fifteenth or sixteenth century. O. glaberrima, the native African rice, has also been planted due to its valuable traits of insect and drought tolerance. Due to competition and resistance evolution, weedy rice has evolved from O. sativa and O. glaberrima, posing an increasing threat to rice production. This paper provides an overview of current knowledge on the introduction and domestication history of cultivated rice in Africa, as well as the genetic properties of African weedy rice that invades paddy fields. Recent developments in genome sequencing have made it possible to uncover findings about O. glaberrima’s population structure, stress resilience genes, and domestication bottleneck. Future rice genomic research in Africa should prioritize producing more high-quality reference genomes, quantifying the impact of crop–wild hybridization, elucidating weed adaptation mechanisms through resequencing, and establishing a connection between genomic variation and stress tolerance phenotypes to accelerate breeding efforts.
The Role of Claudins in the Pathogenesis of Dextran Sulfate Sodium-Induced Experimental Colitis: The Effects of Nobiletin
Authors: Al-Failakawi Asmaa , Al-Jarallah Aishah , Rao Muddanna , Khan Islam
Published: September 2024

Background: The pathogenesis of inflammatory bowel diseases such as ulcerative colitis and Crohn’s disease is not well understood. This study investigated the roles and regulation of the claudin-1, -2, -3, and -4 isoforms in the pathogenesis of ulcerative colitis, and the potential therapeutic effects of nobiletin. Methods: Colitis was induced in rats by administering dextran sulfate sodium [DSS] in drinking water for seven days. Animals were treated daily with nobiletin [oral, 60 mg/Kg body weight] and studied in four groups, C [non-colitis control], D [DSS-induced colitis], CN [nobiletin-treated non-colitis control], and DN [nobiletin-treated DSS-induced colitis]. On day seven, the animals were sacrificed, and colonic tissues were collected and analyzed. Results: Both macroscopic and microscopic findings suggest the progression of colitis. In the inflamed colon, claudin-1 and -4 proteins were decreased, claudin-2 increased, while the claudin-3 protein remained unchanged. Except for claudin-1, these changes were not paralleled by mRNA expression, indicating a complex regulatory mechanism. Uniform β-actin expression along with consistent quality and yield of total RNA indicated selectivity of these changes. Nobiletin treatment reversed these changes. Conclusions: Altered expression of the claudin isoforms -1, -2, and -4 disrupts tight junctions, exposing the lamina propria to microflora, leading to electrolyte disturbance and the development of ulcerative colitis. Nobiletin with its anti-inflammatory properties may be useful in IBD.
Ankle Stability and Dynamic Single-Leg Balance in Collegiate Jumping Athletes versus Non-Athletes
Authors: Garza Grant , Harrison Braden , O’Meara Tim , Potts Zachary , Hung You-jou
Published: September 2024

The purpose of this study was to compare ankle stability and dynamic single-leg balance between jumping athletes and non-athletes, and to examine the correlation between ankle stability and dynamic single-leg balance. Thirty-eight jumping athletes and thirty-seven non-athletes participated in this study. The Cumberland Ankle Instability Tool (CAIT) was used to assess ankle stability. The Y-Balance Test (YBT) was used to examine single-leg balance in the anterior (AN), posteromedial (PM), and posterolateral (PL) directions. The results show that 42.11% of jumping athletes and 21.62% of non-athletes exhibited chronic ankle instability (CAI) in their examined leg. In addition, jumping athletes exhibited significantly worse ankle stability than non-athletes (p = 0.038). The two groups showed no significant difference in the YBT scores in all directions (p = 0.113 AN, 0.567 PM, 0.542 PL). Very low correlations were found between the CAIT and the YBT scores in all directions (r < 0.107). In conclusion, single-leg jumping athletes experienced a higher prevalence of CAI and significantly worse ankle stability than non-athletes. However, the results of the YBT did not correlate strongly with the CAIT scores, suggesting an inability to predict dynamic single-leg balance deficits based on perceived ankle stability alone in this population.
The Impact of Fatigue in Foot-Stabilizing Muscles on Foot Pronation during Gait and a Comparison of Static and Dynamic Navicular Drop Assessments
Authors: Becker Stephan , Göddel Robin , Dindorf Carlo , Littig David , Fröhlich Michael , Ludwig Oliver
Published: September 2024

Background: Individuals may exhibit altered foot pronation during gait when fatigue sets in. Therefore, a more evidence-based understanding of these fatigue-induced changes may be helpful for future gait analysis and return-to-play tests since fatigue can provide new insights that might explain a person’s complaints. Methods: A total of 25 healthy individuals (12♂, 13♀; 24.3 ± 2.7 years; 174.9 ± 9.09 cm; 70 ± 14.2 kg; BMI: 22.7 ± 2.8) participated in this controlled non-randomized study of unilateral fatigue of the right foot’s stabilizing muscles with regard to the pronation of the foot, measured by navicular drop (ND) in static (statND; standing) and dynamic (dynND; walking) states. The left foot served as the control. Surface electromyography was used to verify fatigue. Results: While the statND did not change, the dynND increased significantly by 1.44 ± 2.1 mm (=22.3%) after the foot-stabilizing muscles experienced fatigue. No correlation was found between the statND and dynND. Conclusions: Muscular fatigue can affect foot pronation. The dynND appears to be more representative of the loads in everyday life, whereby most studies use the statND.
Targeted Antimicrobial Therapies: A Solution to Overcoming Antimicrobial Resistance in Humans
Authors: Zai Muhammad Jawad , Cheesman Matthew James , Cock Ian Edwin
Published: September 2024

Overuse or misuse of broad-spectrum antibiotics increases the risk of the emergence of antibiotic-resistant bacteria, which increases the possibility of antimicrobial-resistant (AMR) bacterial infections, and subsequently raises healthcare costs. The excessive use of broad-spectrum antibiotics has also been linked to increased death rates, whilst the benefits that they offer against antibiotic-resistant bacterial pathogens are minimal. Patients infected with antibiotic-resistant bacterial pathogens frequently receive inadequate antimicrobial therapies due to a lack of effective options than those with non-resistant infections, resulting in poor health outcomes and longer recovery times, especially among patients who are critically ill. Broad-spectrum antibiotics also disturb the gut microbiome, which is increasingly recognized as a regulator of immune health. This study offers insights into the use of targeted antimicrobial therapies for bacterial infections, focusing on strategies that mitigate the risk of antibiotic resistance and unwanted side effects associated with the use of broad-spectrum antibiotics. We focus on identifying the genotype and phenotype of bacterial pathogens and then using either nanoparticle-based, vaccine-based, bacteriophage-based, monoclonal antibody-based, and CRISPR-based targeted therapies to directly kill those pathogens and reduce collateral damage. Furthermore, the mechanisms of action of these targeted therapies and their advantages and disadvantages are discussed.
Efficacy of an Innovative Poly-Component Formulation in Counteracting Human Dermal Fibroblast Aging by Influencing Oxidative and Inflammatory Pathways
Authors: Augello Francesca Rosaria , Lombardi Francesca , Ciafarone Alessia , Ciummo Valeria , Altamura Serena , Giuliani Maurizio , Cinque Benedetta , Palumbo Paola
Published: September 2024

Skin aging is characterized by reactive oxygen species (ROS) accumulation, principal players in triggering events associated with aging. Our recent data on the ability of an innovative poly-component formulation (KARISMA Rh Collagen® FACE: K formulation) to suppress the biomolecular events associated with oxidative stress-induced aging prompted us to deepen the mechanisms underlying the observed effects on aged human dermal fibroblasts (HDFs). Here, we evaluated K’s ability to perform a direct free radical-scavenging action and modulate anti-oxidant systems by counteracting the inflammatory process in an H2O2-induced cellular senescence model. Standard methods were used to measure scavenging capacity and enzymatic anti-oxidant system activities. Nuclear factor E2-related factor 2 (Nrf2) and nuclear factor kappa-B (NF-κB) levels were analyzed by Western blot. We assessed pro-inflammatory cytokines, matrix metalloproteinases (MMPs), and advanced glycation end-products (AGEs). Our results show that K counteracted stress-induced aging in a dose-dependent manner by exerting a direct scavenging action and increasing anti-oxidant systems, such as superoxide dismutase (SOD) and catalase (CAT) up to control values. These findings could be associated with increased phospho-Nrf2 (p-Nrf2) expression, generally reduced in aged HDFs following exposure to different concentrations of K formulation. Moreover, K formulation caused a reduction of pro-inflammatory cytokines, interleukin-1β and -6, MMP-1 and -9, and AGE levels, events related to a downregulation of p-NF-κB level. The results indicate that K formulation re-established the normal physiology of HDFs by reducing p-NF-κB expression and restoring Nrf2 activation, thus supporting its efficacious reparative and regenerative action in treating skin aging.
Mother–Daughter Vessel Operation and Maintenance Routing Optimization for Offshore Wind Farms Using Restructuring Particle Swarm Optimization
Authors: Qi Yuanhang , Luo Haoyu , Huang Gewen , Hou Peng , Jin Rongsen , Luo Yuhui
Published: September 2024

As the capacity of individual offshore wind turbines increases, prolonged downtime (due to maintenance or faults) will result in significant economic losses. This necessitates enhancing the efficiency of vessel operation and maintenance (O&M) to reduce O&M costs. Existing research mostly focuses on planning O&M schemes for individual vessels. However, there exists a research gap in the scientific scheduling for state-of-the-art O&M vessels. To bridge this gap, this paper considers the use of an advanced O&M vessel in the O&M process, taking into account the downtime costs associated with wind turbine maintenance and repair incidents. A mathematical model is constructed with the objective of minimizing overall O&M expenditure. Building upon this formulation, this paper introduces a novel restructuring particle swarm optimization which is tailed with a bespoke encoding and decoding strategy, designed to yield an optimized solution that aligns with the intricate demands of the problem at hand. The simulation results indicate that the proposed method can achieve significant savings of 28.85% in O&M costs. The outcomes demonstrate the algorithm’s proficiency in tackling the model efficiently and effectively.
Stapled Peptides: An Innovative and Ultimate Future Drug Offering a Highly Powerful and Potent Therapeutic Alternative
Authors: Kim Do-Hee , Kang Sung-Min
Published: September 2024

Peptide-based therapeutics have traditionally faced challenges, including instability in the bloodstream and limited cell membrane permeability. However, recent advancements in α-helix stapled peptide modification techniques have rekindled interest in their efficacy. Notably, these developments ensure a highly effective method for improving peptide stability and enhancing cell membrane penetration. Particularly in the realm of antimicrobial peptides (AMPs), the application of stapled peptide techniques has significantly increased peptide stability and has been successfully applied to many peptides. Furthermore, constraining the secondary structure of peptides has also been proven to enhance their biological activity. In this review, the entire process through which hydrocarbon-stapled antimicrobial peptides attain improved drug-like properties is examined. First, the essential secondary structural elements required for their activity as drugs are validated, specific residues are identified using alanine scanning, and stapling techniques are strategically incorporated at precise locations. Additionally, the mechanisms by which these structure-based stapled peptides function as AMPs are explored, providing a comprehensive and engaging discussion.
The Assessment of Methyl Methanesulfonate Absorption by Amphipods from the Environment Using Lux-Biosensors
Authors: Novoyatlova Uliana S. , Kudryavtseva Anna A. , Bazhenov Sergey V. , Utkina Anna A. , Fomin Vadim V. , Nevmyanov Shamil A. , Zhoshibekova Bagila S. , Fedyaeva Maria A. , Kolobov Mikhail Y. , Manukhov Ilya V.
Published: September 2024

The ability of aquatic mesofauna representatives involved in trophic chains to sorb and accumulate toxicants is important for understanding the functioning of aquatic ecosystems and for fishing industry. This study investigated the capacity of marine amphipod Gammarus oceanicus and freshwater amphipods Eulimnogammarus vittatus and Gammarus lacustris to absorb the DNA-alkylating agent methyl methanesulfonate (MMS). The presence of alkylating agents in the environment and in the tissues of the amphipods was determined using whole-cell lux-biosensor Escherichia coli MG1655 pAlkA-lux, in which the luxCDABE genes from Photorhabdus luminescens, enabling the luminescence of the cell culture, are controlled by the PalkA promoter of DNA glycosylase. It was shown that within one day of incubation in water containing MMS at a concentration above 10 μM, the amphipods absorbed the toxicant and their tissues produce more alkylation damage to biosensor cells than the surrounding water. Concentrations of MMS above 1 mM in the environment caused the death of the amphipods before the toxicant could be significantly concentrated in their tissues. The sensitivity and the capacity to absorb MMS were found to be approximately the same for the marine amphipod G. oceanicus and the freshwater amphipods E. vittatus and G. lacustris.
Mitochondrial Labeling with Mulberrin-Cy3: A New Fluorescent Probe for Live Cell Visualization
Authors: Yuan Gangxiang , Luo Yiwei , Qian Peng , He Ningjia
Published: September 2024

Mitochondria, crucial intracellular organelles, are central to energy metabolism, signal transduction, apoptosis, calcium homeostasis, and a myriad of other biological processes, making them a focal point in diverse research fields. The capacity to fluorescently label and visually track mitochondria is crucial for understanding their biological roles. We present mulberrin-Cy3, a novel small molecule fluorescent probe that selectively labels mitochondria in animal cells, including cancer cells, with relative ease. This protocol details the synthesis of mulberrin-Cy3 and its use for visualizing mitochondria in living cells. The synthesis is straightforward and time-efficient, and the labeling method is more accessible than traditional approaches, providing a cost-effective option for mitochondrial visualization at room temperature. The labeling is rapid, with effective labeling achieved within 5 min of incubation. The fluorescent signal is stable and brighter, offering a significant advantage over existing methods. Mulberrin-Cy3 represents a promising mitochondrial labeling compound, providing researchers with a novel experimental tool to explore the complex biological functions of mitochondria. This innovation has the potential to significantly advance our comprehension of mitochondrial dynamics and their role in cellular health and disease.
Simultaneous Production of Biogas and Electricity from Anaerobic Digestion of Pine Needles: Sustainable Energy and Waste Management
Authors: Sharma Deepak , Mahajan Rishi , Baghel Vikas , Bansal Saurabh , Ahuja Vishal , Goel Gunjan
Published: September 2024

Power scarcity and pollution can be overcome with the use of green energy forms like ethanol, biogas, electricity, hydrogen, etc., especially energy produced from renewable and industrial feedstocks. In hilly areas, pine needles are the most abundant biomass that has a low possibility of valorization due to high lignin content. On the other hand, anaerobic digestion (AD) of lignin and animal waste has low biogas yield due to poor conductivity. This study focuses on the simultaneous production of biogas and electricity through the co-digestion of cow dung and pine needles. The digester was initially established and stabilized in the lab to ensure a continuous supply of inoculum throughout the experiment. The optimization process involved the determination of an ideal cow dung-to-water ratio and selecting the appropriate conductive material that can enhance the energy generation from the feedstock. Afterward, both batch and continuous anaerobic digestion experiments were conducted. The results revealed that the addition of powdered graphite (5 mM), activated charcoal (15 mM), and biochar (25 mM) exhibited maximum voltage of 0.71 ± 0.013 V, 0.56 ± 0.013 V, and 0.49 ± 0.011 V on the 30th, 25th and 20th day of AD, respectively. The batch experiment showed that 5 mM graphite powder enhanced electron transfer in the AD process and generated a voltage of 0.77 ± 0.014 V on the 30th day, indicating an increase of ~1.5-fold as compared to the control (0.56 ± 0.019 V). The results from the continuous AD process showed that the digester with cow dung, pine needle, and a conductive material in combination exhibited the maximum voltage of 0.76 ± 0.012 V on the 21st day of AD, while the digester with cow dung only exhibited a maximum voltage of 0.62 ± 0.015 V on the 22nd day of AD, representing a 1.3-fold increase over the control. Furthermore, the current work used discarded plastic items and electrodes from spent batteries to emphasize waste management and aid in attaining sustainable energy and development goals.
Coanda Effect Displayed in a Giant Intracranial Aneurysm
Authors: Toader Corneliu , Rădoi Petrinel Mugurel , Aljboor Ghaith Saleh R. , Glavan Luca-Andrei , Covache-Busuioc Razvan-Adrian , Ilie Milena-Monica , Ciurea Alexandru Vlad
Published: September 2024

The Coanda effect is a fluid dynamics phenomenon in which a fluid jet adheres to a convex or flat surface. This effect occurs when a liquid or gas jet emerging from an orifice clings to an adjacent surface and entrains the surrounding fluid, creating a lower-pressure region along its path that maintains its attachment to the surface. The Coanda effect accounts for the behavior of blood flow in the fetal right atrium and the dispersion of eccentric mitral regurgitation jets along atrial walls. This series of interesting images depicting a large 4 × 3.75 cm saccular intracranial aneurysm suggests that the Coanda effect may play a role in the pathophysiology of intracranial aneurysms and could be an underlying factor in their formation, progression, or rupture.
Takotsubo Syndrome or Peripartum Cardiomyopathy? Depends on Who You Are Talking to
Authors: Falola Abigail O. , Razvi Naveed , Gada Ruta , Thompson David R. , Martin Colin R.
Published: September 2024

Takotsubo syndrome (otherwise known as broken-heart syndrome or left ventricular apical ballooning) is a rare cause of reversible heart failure that predominantly affects postmenopausal women. It was first described by Japanese researchers in the 1990s and has become established as a differential for heart failure following a physically or psychologically stressful event. This was popularised by a spike in cases following natural disasters in Japan. As the recognition of takotsubo syndrome in the differential diagnosis for sudden, onset heart failure in a previously healthy individual has grown, so has the discussion concerning takotsubo in the peripartum period. Peripartum cardiomyopathy is a rare cause of reversible heart failure in the latter weeks of pregnancy and the postpartum period. Morbidity and mortality for both cardiomyopathies can be highly variable, ranging from complete recovery of cardiac function to life threatening arrhythmias and even death. This rapid review highlights the similarities between both cardiomyopathies and challenges the hitherto assumption that both takotsubo and peripartum cardiomyopathies are distinct entities that can easily be distinguished from one another. The implications of this are significant within the context of the behavioural aspects of diagnosis, treatment, and outcome.
Shaping Student Relationships: The Role of Personality in Early Childhood Pre-Service Teachers
Authors: Ata Seda , Kimzan İlayda
Published: September 2024

The purpose of this explanatory sequential mixed-methods study is to explain teacher–student relationships in preschool classrooms in terms of the child’s temperament and the pre-service preschool teachers’ personalities. The study was conducted using a sequential exploratory mixed-methods design. Since both quantitative and qualitative data were obtained, sampling was carried out in two stages: quantitative random stratified sampling, and qualitative purposive sampling. Quantitative data were obtained from 126 pre-service teachers. The qualitative study group consisted of 18 pre-service teachers. Quantitative data were collected using the Student–Teacher Relationship Scale-Short Form, the Short Temperament Scale for Children (STSC), and the Five Factor Personality Inventory (FPI). Qualitative data were obtained from interviews with 18 teachers. The findings revealed that the student–teacher relationship can be explained by adult and child characteristics. In addition, pre-service teachers’ perceptions of the student–teacher relationship are explained by adult characteristics much more than pre-service teachers’ perceptions.