bluuebunny/crossref_metadata_2025_split huggingface dataset:
Personality difficulty: A useful addition to the literature on personality disturbance
Authors: Bangash Ayesha 
Published: October 2024

AbstractThe term personality difficulty has become part of the personality disorders and related traits section of the 11th Revision of the International Classification of Diseases. People with this condition make great use of health services as it can be associated with distress and poor social functioning. In the WHO guidebook, Clinical Descriptions and Diagnostic Requirements for ICD‐11 Mental, Behavioural and Neurodevelopmental Disorders (CDDR) (2024) personality difficulty is included to aid clinicians in diagnosing mental, behavioural and neurodevelopmental disorders. It is not a diagnosis but has a formal code (QE 50.7) as a ‘problem associated with interpersonal interactions’. The use of this subsyndromal condition is currently uncertain and, in some quarters, may be challenged, but it is an essential part of the dimensional classification of personality dysfunction and is likely to help in overcoming the stigma around personality issues.
CoNglyPred: Accurate Prediction of N‐Linked Glycosylation Sites Using ESM‐2 and Structural Features With Graph Network and Co‐Attention
Authors: Wang Hongmei , Zhao Long , Yu Ziyuan , Zeng Ximin , Shi Shaoping 
Published: October 2024

ABSTRACTN‐Linked glycosylation is crucial for various biological processes such as protein folding, immune response, and cellular transport. Traditional experimental methods for determining N‐linked glycosylation sites entail substantial time and labor investment, which has led to the development of computational approaches as a more efficient alternative. However, due to the limited availability of 3D structural data, existing prediction methods often struggle to fully utilize structural information and fall short in integrating sequence and structural information effectively. Motivated by the progress of protein pretrained language models (pLMs) and the breakthrough in protein structure prediction, we introduced a high‐accuracy model called CoNglyPred. Having compared various pLMs, we opt for the large‐scale pLM ESM‐2 to extract sequence embeddings, thus mitigating certain limitations associated with manual feature extraction. Meanwhile, our approach employs a graph transformer network to process the 3D protein structures predicted by AlphaFold2. The final graph output and ESM‐2 embedding are intricately integrated through a co‐attention mechanism. Among a series of comprehensive experiments on the independent test dataset, CoNglyPred outperforms state‐of‐the‐art models and demonstrates exceptional performance in case study. In addition, we are the first to report the uncertainty of N‐linked glycosylation predictors using expected calibration error and expected uncertainty calibration error.
Cromolyn sodium and masitinib combination inhibits fibroblast‐myofibroblast transition and exerts additive cell‐protective and antioxidant effects on a bleomycin‐induced in vitro fibrosis model
Authors: Göksu Azize Yasemin , Dirol Hulya , Kocanci Fatma Gonca 
Published: October 2024

AbstractIdiopathic pulmonary fibrosis (IPF) is a progressive and fatal fibrotic lung disease. While recent studies have suggested the potential efficacy of tyrosine kinase inhibitors in managing IPF, masitinib, a clinically used tyrosine kinase inhibitor, has not yet been investigated for its efficacy in fibrotic lung diseases. In a previous study on an in vitro neurodegenerative model, we demonstrated the synergistic antitoxic and antioxidant effects of masitinib combined with cromolyn sodium, an FDA‐approved mast cell stabilizer. This study aims to investigate the anti‐fibrotic and antioxidant effects of the masitinib‐cromolyn sodium combination in an in vitro model of pulmonary fibrosis. Fibroblast cell cultures treated with bleomycin and/or hydrogen peroxide (H2O2) were subjected to masitinib and/or cromolyn sodium, followed by assessments of cell viability, morphological and apoptotic nuclear changes, triple‐immunofluorescence labeling, and total oxidant/antioxidant capacities, besides ratio of Bax and Bcl‐2 mRNA expressions as an indication of apoptosis. The combined treatment of masitinib and cromolyn sodium effectively prevented the fibroblast myofibroblast transition, a hallmark of fibrosis, and significantly reduced bleomycin / H2O2‐induced apoptosis and oxidative stress. This study is the first to demonstrate the additive anti‐fibrotic, cell‐protective, and antioxidant effects of the masitinib‐cromolyn sodium combination in an in vitro fibrosis model, suggesting its potential as an innovative therapeutic approach for pulmonary fibrosis. Combination therapy may be more advantageous in that both drugs could be administered in lower doses, exerting less side effects, and at the same time providing diverse mechanisms of action simultaneously.
Effect of mitochondrial coenzyme‐Q10 precursor solanesol in gentamicin‐induced experimental nephrotoxicity: Evidence from restoration of ETC‐complexes and histopathological alterations
Authors: Sangwan Minakshi , Chaudhary Hema , Mehan Sidharth , Khan Zuber , Bahauddin Ammar A. , Alrehaili Bandar D. , Elbadawy Hossein M. , Almikhlafi Mohannad A. , Narula Acharan S. , Kalfin Reni , Wanas Hanna 
Published: October 2024

AbstractNephrotoxicity occurs when the body is exposed to certain drugs or toxins. When kidney damage occurs, the kidney fails to eliminate excess urine and waste. Solanesol (C45H74O) is a tri‐sesquiterpenoid alcohol first isolated from tobacco, and it is widely distributed in plants of the Solanaceae family. Solanesol (SNL) is an intermediate in the synthesis of coenzyme Q10 (CoQ10), an antioxidant which protects nerve cells. This study investigated the protective effect of SNL at doses of 30 and 60 mg/kg in gentamicin‐induced nephrotoxicity in Wistar albino rats. Animals were distributed into six groups and administered 100 mg/kg gentamicin‐intraperitoneal injection for 14 days. Biochemical assessments were performed on kidney homogenate, blood, and serum. Treatment with SNL was shown as lower serum levels of creatinine, blood urea nitrogen (BUN), thiobarbituric acid reactive substances (TBARS), and Tumor necrosis factor alpha)TNF‐α ((p < .001). It also restored reduced glutathione (GSH) and mitochondrial complex enzymatic activity as protective measures against gentamicin‐induced nephrotoxicity. SNL were shown to reduce inflammation and oxidative stress markers (p < .001). Histological findings furtherly augmented the protective effects of SNL. Long‐term SNL therapy also restored mitochondrial electron transport chain complex enzymes, such as complex‐I (p < .001). In conclusion, these findings suggest that SNL can represent a protective therapeutic option for drug‐induced nephrotoxicity, a long‐term adverse effect of aminoglycoside antibiotics such as gentamicin.
PBPK modeling: What is the role of CYP3A4 expression in the gastrointestinal tract to accurately predict first‐pass metabolism?
Authors: Henriot Justine , Dallmann André , Dupuis François , Perrier Jérémy , Frechen Sebastian 
Published: October 2024

AbstractGastrointestinal first‐pass metabolism plays an important role in bioavailability and in drug–drug interactions. Physiologically‐based pharmacokinetic (PBPK) modeling is a powerful tool to integrate these processes mechanistically. However, a correct bottom‐up prediction of GI first‐pass metabolism is challenging and depends on various model parameters like the level of enzyme expression and the basolateral intestinal mucosa permeability (Pmucosa). This work aimed to investigate if cytochrome P450 (CYP) 3A4 expression could help predict the first‐pass effect using PBPK modeling or whether additional factors like Pmucosa do play additional roles using PBPK modeling. To this end, a systematic review of the absolute CYP3A expression in the human gastrointestinal tract and liver was conducted. The resulting CYP3A4 expression profile and two previously published profiles were applied to PBPK models of seven CYP3A4 substrates (alfentanil, alprazolam, felodipine, midazolam, sildenafil, triazolam, and verapamil) built‐in PK‐Sim®. For each compound, it was assessed whether first‐pass metabolism could be adequately predicted based on the integrated CYP3A4 expression profile alone or whether an optimization of Pmucosa was required. Evaluation criteria were the precision of the predicted interstudy bioavailabilities and area under the concentration–time curves. It was found that none of the expression profiles provided upfront an adequate description of the extent of GI metabolism and that optimization of Pmucosa as a compound‐specific parameter improved the prediction of most models. Our findings indicate that a pure bottom‐up prediction of gastrointestinal first‐pass metabolism is currently not possible and that compound‐specific features like Pmucosa must be considered as well.
AI‐driven adaptive learning for sustainable educational transformation
Authors: Strielkowski Wadim , Grebennikova Veronika , Lisovskiy Alexander , Rakhimova Guzalbegim , Vasileva Tatiana 
Published: October 2024

AbstractThis paper scrutinizes how adaptive learning technologies and artificial intelligence (AI) are transforming today's education by making it personalized, accessible, and efficient as well as leading people to accepting, addressing, and mitigating sustainable development. Recently, education witnessed a remarkable technological surge driven by various advances in technology, which can be demonstrated by the increase of the number of scientific publications on this topic from just 1 in 1990 to 636 in 2023. Ongoing digitalization and technological revolution in education together with the novel approach to respect each student's unique learning style and abilities paved the way for adaptive learning technologies represented by the innovative tools that personalize educational experiences to cater to individual learners. All of that contributes to preparing more educated and informed citizens, drives innovation, and supports economic growth necessary for achieving a sustainable future. Our bibliographic study employs VOSviewer to conduct a bibliometric analysis of a total number of 3518 selected publications using the keywords “adaptive learning” and “AI” (represented by articles, proceeding papers, and book chapters) indexed in the Web of Science (WoS) database from 1990 to 2024. Our results demonstrate that recent technological changes played a key role in transforming adaptive learning, which was rather reinforced by the “digital surge” in education brought about by the COVID‐19 pandemic. Our findings can be useful for further development in the field of adaptive education where they can be employed by the relevant stakeholders and policymakers as well as by the scholars and researchers.
Stepwise Curing Induced All‐Stretchable Thermoelectric Generator of High Power Density
Authors: Kim Daegun , Kim Myeong‐Eun , Kim Hoimin , Lee Jaehoon , Lee Jiyun , Lee Hansol , Lee Dongki , Lee Nae‐Eung , Kang Boseok 
Published: October 2024

AbstractIn this study, a wearable and highly stretchable organic thermoelectric (TE) generator with a notable power density is developed. A highly stretchable and solution‐processable TE/electrode pattern is realized by stepwise‐curing elastomeric and conducting network. Significant advances in the TE or electrical properties are obtained for these stretchable patterns through post‐activation treatment, which creates long‐range charge transport pathways without degrading pre‐established elastomeric networks. The TE and electrode patterns are solution‐processed to a stretchable template, so that all‐stretchable TE generator is realized. The fabricated TE generator maintains 90% of its maximum TE power output at 40% stretching stress and shows a stable TE power output after 200 stretching cycles. The TE generator maintains its stretchability in highly densified patterns, as the highly stretchable TE/electrode patterns enable good stretchability with little aid of the stretchable template. So, the TE generator has a high power density of 0.32 nW cm−2 K−2, one of the highest values among stretchable TE generators to date.
Laser‐Induced Solid‐Phase Strategy to Synthesize Single‐Atomic Lithiophilic Sites Enabled Dendrite‐Free Lithium Deposition on Graphene Matrix
Authors: Gao ShuaiYu , Li Lin , Wu Yingbin , Lu Chunlan 
Published: October 2024

AbstractThe introduction of metal Single‐atom (SA) to construct lithium‐philic active sites shows the ability to guide uniform lithium deposition and improve the stability of lithium hosts. Nevertheless, the development of facile and expedient methods for synthesizing SA remains a considerable challenge. Herein, The SA metal loaded on graphene (Bi@LrGO) is designed by laser‐induced solid‐phase strategy. The bismuth salts simultaneously decompose under the high local temperature and in the reductive atmosphere induced by laser to form SA metal. Simultaneously, graphene oxide (GO) nanosheets absorb photon energy to be reduced/graphitized into graphene, which serves as anchoring sites for Bismuth Sing‐atom (Bi SA) immobilization. The SA metals, supported on the graphene not only provide sufficient lithiophilic sites but also significantly increase the adsorption energy (−2.11 eV) with lithium atoms, promote the uniform nucleation and deposition of lithium, and inhibit the growth of lithium dendrites. Additionally, the layered structure of the graphene film adapts to the volume change during the repeated lithium plating/stripping process. Therefore, the symmetrical battery‐based Li deposited on Bi@LrGO (Bi@LrGO@Li) achieves an ultra‐long stable cycle life of ≈2400 h at 1 mA cm−2. In particular, a full cell with LiFePO4 cathode provides a good capacity retention of 81.2% at 4 C after 600 cycles.
Overcoming Bacteriophage Contamination in Bioprocessing: Strategies and Applications
Authors: Zou Xuan , Mo Ziran , Wang Lianrong , Chen Shi , Lee Sang Yup 
Published: October 2024

AbstractBacteriophage contamination has a devastating impact on the viability of bacterial hosts and can significantly reduce the productivity of bioprocesses in biotechnological industries. The consequences range from widespread fermentation failure to substantial economic losses, highlighting the urgent need for effective countermeasures. Conventional prevention methods, which focus primarily on the physical removal of bacteriophages from equipment, bioprocess units, and the environment, have proven ineffective in preventing phage entry and contamination. The coevolutionary dynamics between phages and their bacterial hosts have spurred the development of a diverse repertoire of antiviral defense mechanisms within microbial communities. These naturally occurring defense strategies can be harnessed through genetic engineering to convert phage‐sensitive hosts into robust, phage‐resistant cell factories, providing a strategic approach to mitigate the threats posed by bacteriophages to industrial bacterial processes. In this review, an overview of the various defense strategies and immune systems that curb the propagation of bacteriophages and highlight their applications in fermentation bioprocesses to combat phage contamination is provided. Additionally, the tactics employed by phages to circumvent these defense strategies are also discussed, as preventing the emergence of phage escape mutants is a key component of effective contamination management.
Follicular conjunctivitis in a Border Collie dog caused by Thelazia callipaeda
Authors: Terziev Georgi , Nizamov Nikola , Kirkova Zvezdelina 
Published: October 2024

AbstractA case of chronic bilateral follicular conjunctivitis in a 5‐year‐old male Border Collie, caused by Thelazia callipaeda infection, is described. Due to the acknowledged sensitivity of Collies to macrocyclic lactones, the treatment with these antiparasitic drugs was contraindicated. Mechanical removal of parasites and alternative treatment with local antibacterial and anti‐inflammatory drugs were performed. One month following the therapy, the control ophthalmological exam did not show any pathological changes in the patient's conjunctiva, the cornea and other eye tissues.
Long Combination Vehicles Reverse Strategies Based on Articulation Angle Gradient
Authors: Ge Zhaohui , Bruzelius Fredrik , Jacobson Bengt 
Published: October 2024

AbstractTo guide the development of driver assistant systems and fully automated solutions for reversing long combination vehicles (LCVs), the principles for reversing LCVs are investigated using the articulation angle gradient. The widely used Steady-state Circling Limitation (SSCL) in reversing LCVs has two main drawbacks: it restricts vehicles from operating with large articulation angles crucial for tight spaces and lacks a well-defined feasible range. Two new reverse principles are introduced that can provide better insight. The first principle extends SSCL to include more extreme articulation angles for single-articulated vehicles. It also addresses the necessity of considering articulation gradients when developing the continuous reverse limitation for multi-articulated vehicles. The second principle introduces limited distance reversing for vehicles that no longer meet the first principle’s requirements, providing additional vehicle ending poses useful for tasks like loading and coupling.
A Comparative Study of Discomfort Using Electrical and Friction Braking at Low Speed Driving
Authors: Deylaghian Samira , Jonasson Mats , Piiroinen Petri T. 
Published: October 2024

AbstractIn this study, we conduct an analysis of the longitudinal dynamics of a vehicle model in an incline, with a specific focus on its behavior, at low speeds, when starting and stopping. The model is minimal, yet an effective representation of a vehicle that includes the effects of springs and dampers as well as friction and electric braking models, which allows for easy analysis into their interplay at low speed. One important feature that this early study shows is how the acceleration and jerk is affected by static and dynamic friction coefficients in different driving situations. Our study further demonstrates the interplay between the electric and friction braking systems and the differences in oscillatory motion they generate. Such insights are vital if we want to improve vehicle control at low speeds and suggest ways to reduce problems like excessive acceleration and jerk. Additionally, our findings could also provide valuable insights when developing active friction braking systems.
A Study on Giant Magnetostrictive Actuator Used in Active Noise Control System for Ultra-compact Electric Vehicles (Analytical Consideration on Output Performance of the Actuator)
Authors: Kato Taro , Naganuma Ryusei , Bando Koki , Kobayashi Ikkei , Kuroda Jumpei , Uchino Daigo , Ogawa Kazuki , Ikeda Keigo , Endo Ayato , Liu Xiaojun , Kato Hideaki , Narita Takayoshi , Furui Mitsuaki 
Published: October 2024

AbstractThe interiors of ultra-compact electric vehicles (EVs) can be uncomfortable owing to the noise caused by the road and wind. To address this issue, we propose an active noise control (ANC) system that uses a giant magnetostrictive actuator. The proposed system allows estimating ride comfort by analyzing the biological information of passengers and controlling the interior acoustic environment. The proposed ANC system employs wall-surface vibrations generated by a giant magnetostrictive actuator. We analytically investigated the thrust characteristics of giant magnetostrictive materials deformed by a magnetic field through electromagnetic field analysis. The results showed that the effect of thrust on frequency changes depends on the characteristics of the giant magnetostrictive material.
Collision Prediction for a Mining Collision Avoidance System
Authors: van Aswegen J. C. , Hamersma H. A. , Els P. S. 
Published: October 2024

AbstractAccidents caused by wheeled mining machines contribute to approximately 30% of injuries and fatalities in the global mining industry. Wheeled mining machines have limited driver assist features when compared to the passenger vehicle market and are typically limited to collision avoidance by braking. These products are often subject to false positive interventions leading to production losses, increased wear, and resistance to adopt the technology by end users. This study proposes a sampling-based method to expand the collision avoidance by braking approach to include steering. The sampling method is based on the vehicle’s kinematics and the application of a Gaussian distribution to the steering rate to determine the probability of a collision occurring. Initial results indicate that the inclusion of steering rate on the collision prediction model may increase the operator’s situational awareness, leading to fewer false positives.
Enhancing Electric Vehicle Remaining Range Prediction Through Machine Learning
Authors: Kim Byunggun , Kim Haeyoun 
Published: October 2024

AbstractMany automakers are announcing electric vehicle (EV) models in response to environmental regulations. However, charging times still exceed those of traditional internal combustion engine vehicles. Moreover, the supply of electric vehicle charging stations has not kept pace with the rapid expansion of electric vehicle adoption. This incongruity raises ongoing concerns for drivers regarding Distance To Empty (DTE) or remaining range. However, accurate DTE prediction faces challenges due to various factors. Therefore, predicting effective remaining range is attracting researchers’ attention. However, most algorithms are based on long-term historical driving data, which presents limitations in a shared vehicle scenario with frequently changing drivers. To address these challenges, this paper introduces a novel algorithm employing machine learning to classify driving styles and predict remaining range. This approach can integrate expected future road information and current driving conditions, offering a solution to the uncertainties associated with traditional methods.
Indoor Test-Rig to Measure the Lateral Characteristics of Bicycle Tyres
Authors: Dell’Orto Gabriele , Mastinu Giampiero 
Published: October 2024

AbstractTyre characteristics can strongly affect bicycle dynamics, therefore the overall bicycle performances. However, it may be hard to measure lateral characteristics with low uncertainty. Proper test-rigs are needed to obtain reliable tyre parameters, to be used then for modelling. The paper presents VeTyT, acronym of “Velo Tyre Testing”, a new test-rig specifically developed for bicycle tyres at the Department of Mechanical Engineering of Politecnico di Milano. It is the first test-rig for bicycle tyres in compliance with the standard ISO 9001-2015. We also present the results of an experimental campaign conducted on a road racing bicycle tyre. In particular, the impact of rim stiffness is relevant to tyre characteristics, leading to a 13% increase in cornering stiffness under the same test conditions.