bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation of Recyclable Magnetic Catalyst (Pd/PDA@Fe3O4) and the Catalytic Degradation of 4-Nitrophenol and Rhodamine B
Authors: Wang Wei , Liu Jiaqi , Shi Guang , Wu Shiqi , Zhang Shihan , Yuan Ruixia
Published: February 2025

A magnetic shell-structured nano-catalyst was prepared by self-polymerization of dopamine wrapped by ferric oxide as the carrier, which was loaded with palladium nanoparticles (Pd/PDA@Fe3O4). The presence of magnetic Fe3O4 made it easy for nanoscale palladium particles to recover and prevent the loss of palladium nanoparticles that is unavoidable in traditional usage and preparation procedures. The catalyst was characterized by X-ray diffraction, fourier transform infrared spectroscopy, scanning electron microscopy, thermal weight loss analysis, Raman spectroscopy, X-ray photo-electron spectroscopy, and magnetic properties analysis. The catalytic performance of the prepared catalyst was investigated taking 4-nitrophenol (10 mg/L) and rhodamine B (15 mg/L) as the target pollutants. The results showed that under the conditions of 35 °C, pH = 7 and a catalyst dosage of 3 mg, the catalytic reduction efficiency of 4-nitrophenol, rhodamine B, and the mixture of them all can reach 99%. The catalytic efficiency of Pd/PDA@Fe3O4 remained above 90% after being used 10 times. The shell structure of Fe3O4 made it possible and easy to recover and recycle the nanoscale palladium, which was a real problem in the usage of nano-catalysts. At the same time, the problem of separation and recovery of palladium nano-catalyst is solved by magnetism, which provides research ideas for the recycling and utilization of nano-materials.
CD6 in Human Disease
Authors: Gurrea-Rubio Mikel , Fox David A. , Castresana Javier S.
Published: February 2025

CD6 is a cell surface protein expressed by T cells, a subset of NK cells, a small population of B cells, and thymocytes. CD6 has multiple and complex functions due to its distinct functional epitopes that mediate interactions with several ligands including CD166 (ALCAM) and CD318 (CDCP1). An additional molecule, CD44, is being investigated as a potential new ligand of CD6. CD6 plays critical roles in lymphocyte activation, proliferation, and adhesion to antigen-presenting, epithelial, and cancer cells. CD6 is a risk gene for multiple autoimmune diseases, possibly related to its numerous roles in regulating CD4+T-cell responses. Additionally, CD6 is a potential target for cancer immunotherapy. Here, we dissect the role of CD6 in the pathogenesis of more than 15 diseases and discuss recent data supporting the use of CD6-targeted therapy in humans.
Leveraging Artificial Intelligence in Project Management: A Systematic Review of Applications, Challenges, and Future Directions
Authors: Adamantiadou Dorothea S. , Tsironis Loukas
Published: February 2025

This article presents a systematic literature review exploring the integration of Artificial Intelligence (AI) methodologies in project management (PM). Key applications include cost estimation, duration forecasting, and risk assessment, which are critical factors for project success. This review synthesizes findings from 97 peer-reviewed studies published between 2011 and 2024, using the PRISMA methodology to ensure rigor and transparency. AI techniques such as machine learning, deep learning, and hybrid models have exhibited their potential to enhance PM techniques across projects’ phases, including planning, execution, and monitoring. Decision trees are created to represent the application of AI methodologies in various PM stages and tasks to facilitate understanding and real-world implementation. Among these are hybrid AI models that enhance risk assessment, duration forecasting, and cost estimation, as well as categorization based on project phases to optimize AI integration. Despite these advancements, there are still gaps in addressing dynamic project environments, validating AI models with real-world data, and expanding research into underexplored phases like project closure.
Exploring the Role of AbaComplex in Managing Dysglycemia: Insights from a Randomized, Three-Arm, Placebo-Controlled Trial
Authors: Schiano Elisabetta , Guerra Fabrizia , Abate Federico , Piccinocchi Gaetano , Tenore Gian Carlo , Novellino Ettore
Published: February 2025

Background: Dysglycemia, characterized by abnormal blood glucose levels, is a critical factor in the development of type 2 diabetes mellitus (T2DM) and its related complications. Among the traditional approaches to managing glucose homeostasis, supplementation with natural antidiabetic molecules stands out. Among these, abscisic acid (ABA), a naturally occurring compound abundant in unripe fruits, has shown potential for improving insulin sensitivity and glucose uptake. This study examines the effects of AbaComplex (ABAc), a nutraceutical derived from thinned nectarines, on glycemic control in individuals with dysglycemia, both alone and in combination with trivalent chromium, known for its role in increasing insulin signal. Methods: A three-arm, randomized, placebo-controlled trial was conducted over 3 months with 120 participants assigned to one of three groups: ABAc alone, ABAc with trivalent chromium (ABAc-Cr), or a placebo. Results: The results showed significant improvements in glycemic control in both the ABAc and ABAc-Cr groups compared to the placebo. Specifically, glycated hemoglobin decreased by 6.6% in the ABAc group and 11.3% in the ABAc-Cr group, while the placebo group showed a 4.3% increase. Both treatment groups also exhibited significant reductions in fasting glucose, insulin levels, and HOMA-IR. Nonetheless, the SF-12 questionnaire revealed marked improvements in physical and mental health, with the ABAc group alone demonstrating slightly greater improvements in certain quality-of-life measures. Conclusions: Overall, these findings underscore the effectiveness of ABAc supplementation as a valuable approach for managing dysglycemic conditions and early-stage T2D.
Multi-View, Multi-Target Tracking in Low-Altitude Scenes with UAV Involvement
Authors: Wu Pengnian , Li Yixuan , Li Zhihao , Yang Xuqi , Xue Dong
Published: February 2025

Cooperative visual tracking involving unmanned aerial vehicles (UAVs) in low-altitude environments is a dynamic and rapidly evolving domain. Existing models encounter challenges with targets, such as scale variation, appearance similarity, and frequent occlusions, which hinder the effective use of target information for cross-view identity association. To address these challenges, this study introduces a model for multi-view, multi-target tracking in low-altitude scenes involving UAVs (MVTL-UAV), an effective multi-target tracking model specifically designed for low-altitude scenarios involving UAVs. The proposed method is built upon existing end-to-end detection and tracking frameworks, introducing three innovative modules: loss reinforcement, coupled constraints, and coefficient improvement. Collectively, these advancements enhance the accuracy of cross-view target identity matching. Our method is trained using the DIVOTrack dataset, which comprises data collected from a single UAV and two handheld cameras. Empirical results indicate that our approach achieves a 2.19% improvement in cross-view matching accuracy (CVMA) and a 1.95% improvement in the cross-view ID F1 metric (CVIDF1) when compared to current state-of-the-art methodologies. Importantly, the model’s performance is improved without compromising computational efficiency, thereby enhancing its practical value in resource-constrained environments. As a result, our model demonstrates satisfactory performance in various low-altitude target tracking scenarios involving UAVs, establishing a new benchmark in this research area.
Using Investments in Solar Photovoltaics as Inflation Hedges
Authors: Sadat Seyyed Ali , Mittal Kashish , Pearce Joshua M.
Published: February 2025

Mainstream strategies for protecting wealth from inflation involve diversification into traditional assets like common stocks, gold, fixed-income securities, and real estate. However, a significant contributor to inflation has been the rising energy prices, which have been the main underlying cause of several past recessions and high inflation periods. Investments in distributed generation with solar photovoltaics (PV) present a promising opportunity to hedge against inflation, considering non-taxed profits from PV energy generation. To investigate that potential, this study quantifies the return on investment (ROI), internal rate of return (IRR), payback period, net present cost, and levelized cost of energy of PV by running Solar Alone Multi-Objective Advisor (SAMA) simulations on grid-connected PV systems across different regions with varying inflation scenarios. The case studies are San Diego, California; Boston, Massachusetts; Santiago, Chile; and Buenos Aires, Argentina. Historical inflation data are also imposed on San Diego to assess PV system potential in dynamic inflammatory conditions, while Boston and Santiago additionally analyze hybrid PV-battery systems to understand battery impacts under increasing inflation rates. Net metering credits vary by location. The results showed that PV could be used as an effective inflation hedge in any region where PV started economically and provided increasingly attractive returns as inflation increased, particularly when taxes were considered. The varying values of the ROI and IRR underscore the importance of region-specific financial planning and the need to consider inflation when evaluating the long-term viability of PV systems. Finally, more capital-intensive PV systems with battery storage can become profitable in an inflationary economy.
The Dynamics of the California Electric Grid Mix and Electric Vehicle Emission Factors
Authors: Zhang Xingrui , Martin Elliot , Shaheen Susan
Published: February 2025

Electric vehicle (EV) emissions occur when a vehicle is charged and are based on the mix of power sources used during that period. The rapid growth of solar and wind energy has introduced a high degree of variability in the emissions of the grid for both diurnal and annual periodicities. Growth in solar energy has been particularly prominent in California. Using grid mix data spanning April 2018 to April 2023 from the California Independent System Operator (CAISO) and power source emission factors, we evaluate the grid mix at 5 min intervals and estimate the emission factors based on the mix of power sources, the transmission losses, and the AC/DC conversion. We compare the emission factors derived from this analysis to other static factors that can be used for estimating EV emissions. We find that, when using Low Carbon Fuel Standard (LCFS) emission factors, the average emissions rate was 301 g CO2-e per kWh over five years. However, depending on the time of year, the maximum hourly grid emission factors in California can be between 50% and 300% higher than the minimum factors. This difference suggests that the accurate measurement of emissions from electric vehicles would be improved with better data characterizing energy by the time of day and year in which the vehicle was charged.
A Stability Assessment of Fault-Caprock Trapping Systems for CO2 Storage in Saline Aquifer Layers Using a Coupled THMC Model
Authors: Xie Mingying , Wang Shenghao , Feng Shasha , Xu Chao , Li Xisheng , Sun Xiaona , Ma Yueqiang , Gan Quan , Wang Tao
Published: February 2025

Deep saline aquifers provide significant potential for CO2 storage and are crucial in carbon capture, utilization, and storage (CCUS). However, ensuring the long-term safe storage of CO2 remains challenging due to the complexity of coupled thermal, hydrological, mechanical, and chemical (THMC) processes. This study is one of a few to incorporate fault-controlled reservoir structures in the Enping 15-1 oilfield to simulate the performance of CO2 geological storage. A systematic analysis of factors influencing CO2 storage safety, such as the trap area, aquifer layer thickness, caprock thickness, reservoir permeability, and reservoir porosity, was conducted. We identified the parameters with the most significant impact on storage performance and provided suitable values to enhance storage safety. The results show that a large trap area and aquifer thickness are critical for site selection. Low permeability and large caprock thickness prevent CO2 from escaping, which is important for long-term and stable storage. These findings contribute to developing site-specific guidelines for CO2 storage in faulted reservoirs.
Energy Storage as a Transmission Asset—Assessing the Multiple Uses of a Utility-Scale Battery Energy Storage System in Brazil
Authors: Ferreira Torres Pedro , Manito Alex R. A. , Figueiredo Gilberto , Almeida Marcelo P. , de Souza Almeida Neto José César , Cavalcante Renato L. , Vieira de Freitas Almeida da Silva Caio Cesar , Zilles Roberto
Published: February 2025

Transmission flexibility is a key component of current power systems and demands a reconfiguration of alternatives to expand transmission infrastructure. This paper addresses the use of a Battery Energy Storage System (BESS) as an asset of the transmission system that provides increased transmission capacity. Furthermore, the BESS also supports operational procedures of the transmission system in the course of the re-establishment of normal operation during transients, which helps maintain the power quality requirements. A case study is presented to assess the additional capabilities that an operational 30 MW/60 MWh BESS primarily used to provide congestion relief in the state of São Paulo, Brazil, could provide to the power system. Based on a 5-year horizon transmission and generation expansion plans by local governing bodies, a set of four alternative applications for this BESS was proposed and studied, as follows: (1) increased operational flexibility under contingencies and maintenance, (2) islanded operation for increased reliability, (3) grid support during system restoration, and (4) increased hosting capacity for variable renewables. The results show that the BESS improves performance and power quality indexes while aiding the operation during contingencies.
An Overview of Solar Photovoltaic Power Smoothing Control Strategies Based on Energy Storage Technology
Authors: Mao Mingxuan , Tang Yuhao , Chen Jiahan , Ma Fuping , Li Ziran , Ma Hongyu , Sun Haojin , Yin Chengqi , Li Huanxin
Published: February 2025

Countries around the world are actively promoting the low-carbon transformation of the energy system, and renewable energy represented by solar photovoltaic (PV) power generation will occupy a greater proportion of the power system. The power of PV power generation is characterized by randomness and volatility, so an energy storage system (ESS) is needed for smooth control of fluctuating power to improve the quality of electric energy and the stability of the system. First of all, through the comparative analysis of various energy storage technologies, this paper finds that the battery-supercapacitor hybrid energy storage system (HESS) has both steady-state and dynamic response capabilities. Secondly, the power smoothing control strategy comprises centralized control strategies and distributed control strategies, corresponding control algorithms based on filter and optimization, and droop control strategy, respectively. This paper introduces them in turn and analyzes their advantages and disadvantages. Finally, according to the characteristics of the two control strategies, the analysis of the applicable scenarios is given, and it can guide future applications.
Novel Pathogenic Variant of the TRRAP Gene Detected in a Hungarian Family with Autosomal Dominant Non-Syndromic Hearing Loss
Authors: Nagy Nikoletta , Szalenko-Tőkés Ágnes , Pál Margit , Bokor Barbara Anna , Nagy Roland , Jarabin János András , Róvó László , Széll Márta
Published: February 2025

Autosomal dominant non-syndromic hearing loss (ADNSHL) is a genetically heterogenic condition. The transformation/transcription domain associated protein (TRRAP) gene has been recently associated with ADNSHL, and only four variants of the gene have so far been reported in this disease. Here, we report on a Hungarian ADNSHL family in which the affected individuals exhibited sensorineural hearing loss with similar clinical symptoms, including initial impaired high frequencies that subsequently affected speech and lower frequencies. Whole exome sequencing and screening of the shared genetic variants of the affected individuals was performed. Our results revealed a novel heterozygous missense variant (NM_001244580.2, c.5360A>G, p.Lys1787Arg) in the TRRAP gene. This variant is completely co-segregated with hearing impairment. It is present in a heterozygous form in the affected mother and daughter but not carried by any unaffected family members. This study highlights the importance of elucidating the germline genetic background of ADNSHL, which may help to predict individual risk and the risk of family members. This will improve prevention, screening, and therapeutic measures for each patient and hearing loss-prone families.
Evaluating the Role of Vitamin D in Prediabetes Management, Insights from RCTs in the MENA Region: A Comprehensive Systematic Review
Authors: Al-Hetar Mohammed A. M. Y. , Rusli Noradliyanti , Kamaruzzaman Mohd Amir , Al-Goshae Husni , Wan Ngah Wan Zurinah , Shah Shamsul Azhar , Al-Matary Abdullah Mohammed , Al-Hetar Qais Mohammed , Mohammed Senan Dhya’a Alhaq , A. Wahab Norasyikin
Published: February 2025

Background/Objectives: The association between vitamin D deficiency and prediabetes has been extensively investigated, yet the findings remain inconsistent, with limited data available on the MENA region. This systematic review aims to assess the relationship between vitamin D deficiency and prediabetes in the Middle East and North Africa (MENA) region, focusing specifically on randomized controlled trials (RCTs). Methods: A comprehensive literature search was performed across four databases, which were Ovid MEDLINE, Cochrane, Scopus, and PubMed. RCTs studies conducted on people with prediabetes aged 15 years and older who live in the MENA region, and receiving vitamin D supplementation were included in the study. Results: From 2194 studies identified from the literature search, only 51 studies were considered eligible for full-text review. Ultimately, seven articles were finalized for inclusion. The findings from these studies showed mixed results, where some studies indicated that vitamin D supplementation had no significant effect on these outcomes. The remaining reported improvements in insulin sensitivity and a reduced risk of progression to type 2 diabetes with vitamin D supplementation. Conclusions: This systematic review examines the complex and contradictory relationship between vitamin D deficiency and prediabetes in the MENA region. Due to the mixed pattern seen in the intervention of vitamin D to prevent the development of type 2 diabetes, further research is necessary to elucidate the underlying mechanisms and potential confounding factors specifically in population of the MENA region.
Stochastic Modelling of the COVID-19 Epidemic
Authors: Platen Eckhard
Published: February 2025

The need to manage the risks related to the COVID-19 epidemic in health, economics, finance, and insurance became obvious after its outbreak. As a basis for the respective quantitative methods, this paper models, in a novel manner, the dynamics of an epidemic via a four-dimensional stochastic differential equation. Crucial time-dependent input parameters include the reproduction number, the average number of externally and newly infected cases, and the average number of new vaccinations. The proposed model is driven by a single Brownian motion process. When fitted to COVID-19 data, it generates the observed features. It captures widely observed fluctuations in the number of newly infected cases. The fundamental probabilistic properties of the dynamics of an epidemic can be deduced from the proposed model. These can form the basis for successfully managing an epidemic and the related economic and financial risks. As a general tool for quantitative studies, a simulation algorithm is provided. A case study illustrates the model and discusses strategies for reopening an economy during an epidemic.
Adsorption and Dissociation of 2-Chlorophenols on the 2D ZnO Monolayer Decorated with Al Atoms: A DFT Study
Authors: Zong Zhengjun , Wang Changqing , Zhao Miaomiao , Chen Weiguang , Jia Yu
Published: February 2025

The stable adsorption configurations, electronic structures, and dissociation properties of 2-chlorophenol on pristine and Al-decorated ZnO monolayer are investigated using density functional theory (DFT). Our results indicate that the interaction between 2-chlorophenol and pristine ZnO monolayer is weak, while Al-modified ZnO monolayer can significantly enhance the adsorption of 2-chlorophenol. Therefore, compared to the pristine ZnO monolayer, the ZnO monolayer modified with Al is more sensitive to 2-chlorophenol molecules. Moreover, both pristine ZnO and Al decorated ZnO monolayers exhibit lower barriers for the dissociation of 2-chlorophenol molecules. These results provide a deeper understanding of the adsorption and dissociation performance of the ZnO monolayer for 2-chlorophenol molecules, which will contribute to the further application of ZnO in the fields of catalysts and gas sensing.
Study on the Transverse Properties of T800-Grade Unidirectional Carbon Fiber-Reinforced Polymers
Authors: Wang Hao , Zhong Xiang-Yu , Jia He , Zhang Lian-Wang , Liu Han-Song , Sun Ming-Chen , Liu Tian-Wei , Bao Jian-Wen , Bai Jiang-Bo , Ge Si-Cheng
Published: February 2025

This paper focuses on the transverse tensile and compressive mechanical properties of T800-grade unidirectional (UD) carbon fiber-reinforced polymers (CFRPs). Firstly, transverse tensile and compressive tests were conducted on UD composite laminates, yielding corresponding stress–strain curves. The results indicated that, for tension, the transverse tensile modulus, strength, and failure strain were 8.7 GPa, 64 MPa, and 0.74%, respectively, whereas for compression, these values were 8.4 GPa, 197.1 MPa, and 3.43%, respectively. The experimental curves indicated brittle failure under tensile loadings and significant plastic failure characteristics under compressive loading for the T800-grade composite. Subsequently, fractography experiments were performed to observe the fracture morphologies, revealing that tensile fractures were through-thickness cracks perpendicular to the loading direction, while compressive fractures were at a 52° angle to the loading direction. Finally, a micromechanical finite element method (FEM) was employed to simulate the tensile and compressive failure processes of the unidirectional composite, and the tensile and compressive properties were predicted. The simulation results showed that under both tensile and compressive loadings, interfacial elements failed first, causing stress concentration and damage to nearby resin elements. The damaged resin and interfacial elements expanded and connected, leading to ultimate failure. The predicted tensile stress–strain curve exhibited linear characteristics consistent with the experimental results in most regions but showed more pronounced nonlinearity before ultimate failure. The predicted compressive stress–strain curve aligned well with the experimental results in terms of nonlinearity. The predicted elastic modulus, failure strengths, and failure strains were in good agreement with the experimental results, with differences of 1.1% (tension modulus), 3.2% (tension strength), and 13.5% (tension failure strain), and 3.6% (compression modulus), −8.5% (compression strength), and −3.8% (compression failure strain). The final failure morphologies were in good accordance with the fractography experimental observations.
Control Law for Two-Process Flexible Manufacturing Systems Modeled Using Petri Nets
Authors: Yang Yang , Yang Junjun , Liang Na , Zhong Chunfu
Published: February 2025

The deadlock control problem in flexible manufacturing systems (FMSs) has received much attention in recent years. The formalism of the Petri net is employed to effectively model, analyze, and control deadlocks in an FMS case study. There are many kinds of deadlock prevention strategies based on the Petri net approach, where computational complexity is a major problem that needs to be considered. Based on the Petri net theory, this paper focuses on the two special subclasses in the S3PR net, namely the dual-process S3PR and the dual-process US3PR, in a bid to prevent deadlocks in an FMS. The relationship between the net structural characteristics and the deadlocks reached was analyzed, and then a regular method of adding controllers for these two models was proposed to reduce computational complexity.
Screening of Potential Angiotensin-Converting Enzyme-Inhibitory Peptides in Squid (Todarodes pacificus) Skin Hydrolysates: Preliminary Study of Its Mechanism of Inhibition
Authors: Li Mingyuan , Liang Qianqian , Zhang Yurui , Jiang Xin , Gu Yuan , Song Xin , Wang Xichang , Shi Wenzheng
Published: February 2025

Background: Hypertension has been identified as a significant risk factor for cardiovascular disease. Given the prevalence of the adverse effects of angiotensin-converting enzyme-inhibitory (ACEI) drugs, natural and effective alternatives to these medications need to be identified. Methods: An investigative study was conducted to assess the ACEI capacity and structural characteristics of enzymatic hydrolysates with varying molecular weights derived from squid skin. The amino acid sequences of the enzymatic digests were analyzed via Nano LC-MS/MS and screened for peptides with ACEI activity using an in silico analysis. Furthermore, molecular docking was employed to investigate the interaction between potential ACEI peptides and ACE. Results: TPSH-V (MW < 1 kDa) exhibited the highest rate of ACEI, a property attributable to its substantial hydrophobic amino acid content. Additionally, TPSH-V exhibited high temperature and pH stability, indicative of regular ordering in its secondary structure. The binding modes of four potential novel ACEI peptides to ACE were predicted via molecular docking with the sequences of FHGLPAK, IIAPPERKY, RGLPAYE, and VPSDVEF, all of which can bind to the ACE active site via hydrogen bonding, with FHGLPAK, RGLPAYE, and VPSDVEF being able to coordinate with Zn2+. Conclusions: Squid skin constitutes a viable resource for the production of ACEI peptides.
Unveiling Irreversible β-Relaxations in Metallic Glasses via Electrical Resistivity
Authors: Chen Jianyu , Ren Shuai , Chen Zhe , Dong Jie , Zhu Lixing , Zhan Yangguang , Wang Wenxue , Zeng Shenghao , Xiao Jing , Liang Xiong , Ma Jiang
Published: February 2025

Dynamic relaxations play an important role in understanding the nature of glass. The conventional methods to explore dynamic relaxations rely on the measurement of mechanical and thermic properties, while new methods that may provide a new perspective to probe dynamic relaxation are desperately required. Here, we show that the β-relaxation of metallic glasses (MGs) can be unveiled by electrical resistivity (ER). Irreversible β-relaxation leads to an increment in electrical resistivity, which can be fitted by the Kohlrausch–Williams–Watts equation well. In contrast, the ER results of the initialized sample only exhibit a negligible change during annealing, which indicates that the reversible β-relaxation change cannot be manifested by ER testing. This work provides the ER measurement as a new means to explore the dynamic relaxation of MGs, which may offer a new insight into the understanding of β-relaxation in glass materials.
Therapeutic Strategies to Modulate Gut Microbial Health: Approaches for Chronic Metabolic Disorder Management
Authors: Rondanelli Mariangela , Borromeo Sara , Cavioni Alessandro , Gasparri Clara , Gattone Ilaria , Genovese Elisa , Lazzarotti Alessandro , Minonne Leonardo , Moroni Alessia , Patelli Zaira , Razza Claudia , Sivieri Claudia , Valentini Eugenio Marzio , Barrile Gaetan Claude
Published: February 2025

Numerous recent studies have suggested that the composition of the intestinal microbiota can trigger metabolic disorders, such as diabetes, prediabetes, obesity, metabolic syndrome, sarcopenia, dyslipidemia, hyperhomocysteinemia, and non-alcoholic fatty liver disease. Since then, considerable effort has been made to understand the link between the composition of intestinal microbiota and metabolic disorders, as well as the role of probiotics in the modulation of the intestinal microbiota. The aim of this review was to summarize the reviews and individual articles on the state of the art regarding ideal therapy with probiotics and prebiotics in order to obtain the reversion of dysbiosis (alteration in microbiota) to eubiosis during metabolic diseases, such as diabetes, prediabetes, obesity, hyperhomocysteinemia, dyslipidemia, sarcopenia, and non-alcoholic fatty liver diseases. This review includes 245 eligible studies. In conclusion, a condition of dysbiosis, or in general, alteration of the intestinal microbiota, could be implicated in the development of metabolic disorders through different mechanisms, mainly linked to the release of pro-inflammatory factors. Several studies have already demonstrated the potential of using probiotics and prebiotics in the treatment of this condition, detecting significant improvements in the specific symptoms of metabolic diseases. These findings reinforce the hypothesis that a condition of dysbiosis can lead to a generalized inflammatory picture with negative consequences on different organs and systems. Moreover, this review confirms that the beneficial effects of probiotics on metabolic diseases are promising, but more research is needed to determine the optimal probiotic strains, doses, and administration forms for specific metabolic conditions.
Correction: Olugbodi et al. Silver Nanoparticles Stimulates Spermatogenesis Impairments and Hematological Alterations in Testis and Epididymis of Male Rats. Molecules 2020, 25, 1063
Authors: Olugbodi Janet Olayemi , David Oladipupo , Oketa Ene Naomi , Lawal Bashir , Okoli Bamidele Joseph , Mtunzi Fanyana
Published: February 2025

In the original publication [...]
Finely-Tuned Bis(imino)pyridylcobalt Complexes Enhance Ethylene Polymerization: The Role of Bulky and Halogen Substituents
Authors: Ogbe Elizabeth , Ma Yanping , Wang Yizhou , Gao Jiahao , Sun Yang , Sun Wen-Hua
Published: February 2025

The bis(imino)pyridylcobalt complexes have been finely tuned through using the aniline derivative bearing a meta-chloro substituent, besides its ortho- and para-di(4-fluorophenyl)methyl and ortho-methyl substituents for the series of 2-[1-(3-chloro-4,6-bis((di(4-fluorophenyl)methyl)-2-methylphenylimino)ethyl]-6-[1-(arylimino)ethyl]pyridylcobalt(II) chlorides (2,6-Me2Ph, Co1; 2,6-Et2Ph, Co2; 2,6-iPr2Ph, Co3; 2,4,6-Me3Ph, Co4; and 2,6-Et2-4-MePh, Co5). The compounds were characterized using elemental analysis, 1H/13C NMR, FT-IR spectroscopy, and the single-crystal X-ray diffraction used in confirming the molecular structures of Co1, Co2, Co4, and Co5. The newly synthesized precatalysts, maintaining steric influences with the addition of an electron-withdrawing meta-chloro group, achieved higher activities along with better thermal stability, and controlled molecular weights of polyethylenes obtained. Upon activation with either MAO or MMAO, all catalysts exhibited remarkable activity for ethylene polymerization, for example, 9.2 × 106 g mol−1 h−1 by Co1 at 70 °C with 30 min and 18.0 × 106 g mol−1 h−1 by Co4 with the first 5 min. Co4 demonstrated exceptionally thermal stability with the peak activity of 8.9 × 106 g mol−1 h−1 at 70 °C and slightly decreased to 7.2 × 106 g mol−1 h−1 at 80 °C, and even maintained an activity of 1.6 × 106 g mol−1 h−1 at 100 °C. More importantly, all resultant polyethylenes were characterized as having vinyl-terminal and high-linear feature along with narrow dispersity; the molecular weights could be adapted in the ranges from 6.4 to 50.0 kg mol−1. In comparison with previous cobalt analogs, the current system performed better thermal stability and polymerization efficiency. Therefore, such robust complex catalysts are potentially considered for the polyethylene industry.
Tailoring Polyamide66 Mechanical Performance: A Strategy for Condensed Phase Structure Optimization Through Hydrogen Bond Reorganization
Authors: Wang Wen-Yan , He Pan , Peng Ting , Zhang Shuai , Li Guang-Zhao , Nie Min , Han Rui
Published: February 2025

Polymers are widely used in various industries due to their unique properties, but their mechanical strength often falls short compared to other materials. This has spurred extensive research into enhancing their mechanical performance through condensed phase structure regulation. This study investigates the enhancement of mechanical properties in polyamide 66 (PA66) through the introduction of arylamide-based materials (TMB-5) during the melt-spinning process. TMB-5, possessing amide groups like PA66, can reorganize intermolecular hydrogen bonds within PA66, thereby facilitating molecular movement and reducing chain entanglement during fiber formation. Consequently, the synergistic effect of TMB-5 and the stretching field leads to enhanced crystallization and molecular and lamellae orientation in PA66 fibers without post-drawing, resulting in a significant increase in tensile strength and modulus. This work not only offers a novel strategy for adjusting polymer mechanical performance but also sheds light on the importance of molecular interactions in governing polymer properties.
The Associations of Vitamin D Status and Lifestyle Behaviors with General Obesity and Metabolically Unhealthy Obesity in Chinese Children and Adolescents
Authors: Liu Fangqu , Li Yan , Liang Chanhua , Kong Bingxuan , Zhang Qian , Yin Xingzhu , Wu Bangfu , Xiong Jingfan , Yao Ping , Tang Yuhan , Li Yanyan
Published: February 2025

Background: Vitamin D and lifestyle behaviors are closely related to children’s health. However, current research on the combined influences of vitamin D and adherence to 24-Hour Movement Guidelines (24-HMG) on childhood obesity remains scarce. Our study aimed to examine individual and joint associations of vitamin D status and the number of recommendations for adhering to 24-HMG with obesity among Chinese children and adolescents. Methods: In this cross-sectional study, a total of 4625 participants from Shenzhen, China, were recruited. Vitamin D status was classified into two categories: adequacy and inadequacy. The 24-HMG was obtained from a validated questionnaire, including moderate-to-vigorous physical activity, screen time, and sleep duration. General obesity and metabolically unhealthy obesity (MUO) were the outcomes of this study. The logistic regression model was performed to examine the associations between vitamin D status, the number of guidelines met, and obesity. Results: Vitamin D inadequacy was associated with increased odds of general obesity and MUO, with adjusted odds ratios (95% CIs) of 1.551 (1.080–2.226) and 2.205 (1.319–3.686). Meeting 2–3 recommendations of 24-HMG was associated with decreased odds of general obesity, with adjusted odds ratios (95% CIs) of 0.777 (0.626–0.965). Compared with the vitamin D adequacy/meeting 2–3 guidelines group, the vitamin D inadequacy/meeting 0–1 guideline group was positively related to general obesity (adjusted odd ratio, 1.826 [95% CI: 1.167–2.857]) and MUO (2.160, 1.175–3.972). In addition, the population-attributable fractions of vitamin D inadequacy or/and meeting 0–1 guideline were 28.4% (95% CI: 2.5–54.4%) for general obesity and 42.3% (95% CI: 11.5–73.1%) for MUO. Conclusions: Our findings displayed that the combined associations of vitamin D inadequacy and meeting 0–1 recommendations of 24-HMG were linked to high odds of general obesity and MUO, respectively. Understanding these relationships could provide a theoretical basis for effective preventive strategies and interventions for childhood obesity.
Research on the Quality of Composite Pipe Components in Fluid-Powered Projectile-Assisted Injection Molding
Authors: Kuang Tangqing , Kong Chuixin , Liu Hesheng , Yang Fan
Published: February 2025

Composite pipe fittings with an outer layer of 20% long glass fiber-reinforced polypropylene (LGFR-PP) and an inner layer of polypropylene (PP) were prepared via water-powered projectile-assisted co-injection molding short-shot (W-PACIM-S), water-powered projectile-assisted co-injection molding overflow (W-PACIM-O), gas-powered projectile-assisted co-injection molding short-shot (G-PACIM-S), and gas-powered projectile-assisted co-injection molding overflow (G-PACIM-O)techniques. The effects of different injection molding processes on the wall thickness, inner surface roughness, glass fiber orientation, and pressure resistance of pipe fittings were studied to evaluate the quality of the pipe fittings formed by each process. Compared with the short-shot method, the overflow method results in pipes with thinner walls in each layer, a more uniform distribution, smoother inner wall surfaces, and better orientation of glass fibers along the axial direction in the near boundary layer, resulting in better pressure resistance. Under the same injection method, the difference in fluid medium did not significantly change the trend of wall thickness variation in each layer. However, compared with gas, high-pressure water improves the uniformity of the pipe wall thickness and inner wall quality. In addition, the introduction of the warhead is more conducive to improving the degree of glass fiber orientation of the pipe fittings, and the thickness of the residual wall thickness of the pipe fittings has a great influence on the pressure resistance of the pipe fittings.
A Study on the Preparation of Environmentally Friendly High-Performance Natural Rubber Using the Interaction Mechanism of Alkaline Protease and Calcium Ions
Authors: Dai Tuo , Li Yun , Huang Honghai , Ding Li , Li Jianwei , Geng Haoran , Song Yazhong , Zhao Tao , Zhao Liguang , Gui Hongxing
Published: February 2025

Natural rubber (NR) is a material with a wide range of industrial and commercial applications, including agriculture, defense, transportation, and domestic use. However, the mechanical properties of natural rubber treated by traditional acid coagulation are limited, which restricts its application in high-end products. Furthermore, the wastewater generated also causes soil acidification. Consequently, there is a necessity to investigate new coagulation methods to enhance the comprehensive performance of natural rubber and reduce environmental pollution. In this work, a novel method for the preparation of environmentally friendly high-performance natural rubber by alkaline protease/calcium chloride coagulation of natural rubber (AC-NR) is reported. The research demonstrates that the products of protein cleavage by alkaline protease together with calcium ions can greatly enhance the cross-linking between rubber particles, form the network structure of natural rubber well. Furthermore, increasing the pH at the isoelectric point of the discharged wastewater reduces the impact on soil acidification. In comparison with those from conventional acid coagulation of natural rubber (A-NR), the tensile strength of AC-NR was increased by 7.9 MPa, the tear strength was increased by 5.3 kN/m, the final temperature rise was lowered by 6.5 °C, and abrasion performance was improved. This study demonstrates that by utilizing the collaborative impact of alkaline protease and calcium chloride on the rubber molecular chain during the coagulation process of natural rubber, environmentally friendly high-performance natural rubber with excellent mechanical properties and reduced environmental pollution can be prepared without the necessity for chemical modification or cumbersome processes, which is conducive to the green development and high-quality pursuit of NR materials.
YOLO-AMM: A Real-Time Classroom Behavior Detection Algorithm Based on Multi-Dimensional Feature Optimization
Authors: Cao Yi , Cao Qian , Qian Chengshan , Chen Deji
Published: February 2025

Classroom behavior detection is a key task in constructing intelligent educational environments. However, the existing models are still deficient in detail feature capture capability, multi-layer feature correlation, and multi-scale target adaptability, making it challenging to realize high-precision real-time detection in complex scenes. This paper proposes an improved classroom behavior detection algorithm, YOLO-AMM, to solve these problems. Firstly, we constructed the Adaptive Efficient Feature Fusion (AEFF) module to enhance the fusion of semantic information between different features and improve the model’s ability to capture detailed features. Then, we designed a Multi-dimensional Feature Flow Network (MFFN), which fuses multi-dimensional features and enhances the correlation information between features through the multi-scale feature aggregation module and contextual information diffusion mechanism. Finally, we proposed a Multi-Scale Perception and Fusion Detection Head (MSPF-Head), which significantly improves the adaptability of the head to different scale targets by introducing multi-scale feature perception, feature interaction, and fusion mechanisms. The experimental results showed that compared with the YOLOv8n model, YOLO-AMM improved the mAP0.5 and mAP0.5-0.95 by 3.1% and 4.0%, significantly improving the detection accuracy. Meanwhile, YOLO-AMM increased the detection speed (FPS) by 12.9 frames per second to 169.1 frames per second, which meets the requirement for real-time detection of classroom behavior.
Artificial Intelligence and Deep Learning in Sensors and Applications: 2nd Edition
Authors: Hsieh Yu-Heng , Yuan Shyan-Ming
Published: February 2025

In the era of rapidly advancing technologies, the integration of artificial intelligence (AI) and deep learning (DL) with sensor technologies is providing novel solutions across diverse fields, from healthcare [...]
Detection of Flexible Pavement Surface Cracks in Coastal Regions Using Deep Learning and 2D/3D Images
Authors: Sanchez Carlos , Wang Feng , Bai Yongsheng , Gong Haitao
Published: February 2025

Pavement surface distresses are analyzed by transportation agencies to determine section performance across their pavement networks. To efficiently collect and evaluate thousands of lane-miles, automated processes utilizing image-capturing techniques and detection algorithms are applied to perform these tasks. However, the precision of this novel technology often leads to inaccuracies that must be verified by pavement engineers. Developments in artificial intelligence and machine learning (AI/ML) can aid in the progress of more robust and precise detection algorithms. Deep learning models are efficient for visual distress identification of pavement. With the use of 2D/3D pavement images, surface distress analysis can help train models to efficiently detect and classify surface distresses that may be caused by traffic loading, weather, aging, and other environmental factors. The formation of these distresses is developing at a higher rate in coastal regions, where extreme weather phenomena are more frequent and intensive. This study aims to develop a YOLOv5 model with 2D/3D images collected in the states of Louisiana, Mississippi, and Texas in the U.S. to establish a library of data on pavement sections near the Gulf of Mexico. Images with a resolution of 4096 × 2048 are annotated by utilizing bounding boxes based on a class list of nine distress and non-distress objects. Along with emphasis on efforts to detect cracks in the presence of background noise on asphalt pavements, six scenarios for augmentation were made to evaluate the model’s performance based on flip probability in the horizontal and vertical directions. The YOLOv5 models are able to detect defined distresses consistently, with the highest mAP50 scores ranging from 0.437 to 0.462 throughout the training scenarios.
STar-DETR: A Lightweight Real-Time Detection Transformer for Space Targets in Optical Sensor Systems
Authors: Xiao Yao , Guo Yang , Pang Qinghao , Yang Xu , Zhao Zhengxu , Yin Xianlong
Published: February 2025

Optical sensor systems are essential for space target detection. However, previous studies have prioritized detection accuracy over model efficiency, limiting their deployment on resource-constrained sensors. To address this issue, we propose the lightweight space target real-time detection transformer (STar-DETR), which achieves a balance between model efficiency and detection accuracy. First, the improved MobileNetv4 (IMNv4) backbone network is developed to significantly reduce the model’s parameters and computational complexity. Second, group shuffle convolution (GSConv) is incorporated into the efficient hybrid encoder, which reduces convolution parameters while facilitating information exchange between channels. Subsequently, the dynamic depthwise shuffle transformer (DDST) feature fusion module is introduced to emphasize the trajectory formed by space target exposure. Finally, the minimum points distance scylla intersection over union (MPDSIoU) loss function is developed to enhance regression accuracy and expedite model convergence. A space target dataset is constructed, integrating offline and online data augmentation techniques to improve robustness under diverse sensing conditions. The proposed STar-DETR model achieves an AP0.5:0.95 of 89.9%, successfully detecting dim and discontinuous streak space targets. Its parameter count and computational complexity are reduced by 64.8% and 41.8%, respectively, highlighting its lightweight design and providing a valuable reference for space target detection in resource-constrained optical sensors.
The COVID Shift: Comparing Hybrid Telehealth to In-Person Group Therapy for Incarcerated Women Survivors of Sexual Violence Victimization
Authors: Bridges Ana J. , Fradley Marley F. , Mapes Ayla R. , Ledesma Roselee J. , Allen Emily L. , Karlsson Marie E. , Zielinski Melissa J.
Published: February 2025

Incarcerated women report extremely high rates of lifetime sexual violence victimization. Survivors Healing from Abuse: Recovery through Exposure (SHARE) is an exposure-based group therapy specifically designed for incarcerated women survivors of sexual violence. SHARE has been continuously delivered in a women’s prison for more than 12 years. However, like many prisons during the COVID-19 pandemic, the prison ceased all in-person programming between March 2020 and July 2021. In response, the SHARE treatment team pivoted to a hybrid telehealth delivery model (i.e., group participants gathering in a facility group room and therapists joining via video, displayed on a computer screen within the group room). Given the lack of evidence for hybrid telehealth in carceral settings, and specifically for group therapy for sexual trauma, the current study compared ratings on internalizing symptoms (Brief Symptom Inventory-18 or BSI-18), posttraumatic stress symptoms (Posttraumatic Checklist-5 or PCL-5), and group cohesion ratings (Inclusion of Self in Other scale, or IOS) for participants who received SHARE in person (n = 21) or through hybrid telehealth (n = 19). The results demonstrated that participants of in-person and hybrid telehealth SHARE groups reported similar significant reductions in BSI-18 (15.21 in person vs. 16.00 in hybrid telehealth) and PCL-5 (30.78 in person vs. 26.40 in hybrid telehealth) scores pre- to post-treatment and comparable IOS ratings (5.06 in person vs. 5.31 in hybrid telehealth). The findings suggest hybrid telehealth is an effective and feasible treatment modality for meeting the need for trauma-focused therapy in prisons. Future studies examining the effectiveness and implementation of trauma-focused hybrid telehealth groups in prisons are warranted.