bluuebunny/crossref_metadata_2025 huggingface dataset:
Professional Development Analytics: A Smart Model for Industry 5.0
Authors: Tusquellas Natalia , Santiago Raúl , Palau Ramon
Published: February 2025

This paper presents a novel AI-driven conceptual smart model designed to help organizations enhance workforce professional development by upskilling and reskilling employees while fostering job satisfaction and staying competitive in their markets; this novel model is called Professional Development Analytics (PDA). The model’s main focus is to provide a new design model that concentrates on how artificial intelligence (AI) can optimize personalized training and how it can improve employees’ technical and soft skills, enabling companies to create their talent map at the same time. By compiling personnel data and their roles within the company, AI is able to create detailed and personalized profiles. In the next stage, this information is classified, analyzed, and used to enhance current skills while also predicting future training needs. These processes result in the creation of personalized learning paths, where AI recommends customized courses tailored to each employee’s unique needs. The system will be automatically fed and adjusted by means of the gathered data and continuous feedback from the employees and their supervisors. The proposed AI tools are powered by machine learning, deep learning, natural language processing, generative AI and data analytics. Our model aims to support learning and development departments by delivering precise, personalized training solutions that address employees’ unique needs, enabling skill development and professional growth through an automated and customized process.
Fine Identification of Landslide Acceleration Phase Using Time Logarithm Prediction Method Based on Arc Synthetic Aperture Radar Monitoring Data
Authors: Li Chong , Wang Liguan , Wang Jiaheng , Zhang Jun
Published: February 2025

In the field of slope landslide prevention and monitoring in open-pit mines, addressing the lag issues associated with the traditional GNSS inverse-velocity method, this study introduces a novel strategy that integrates high-spatiotemporal-resolution monitoring data from ArcSAR with a time log model for prediction. The key findings include the following: (1) This strategy utilizes the normal distribution characteristics of deformation velocities to set confidence intervals, accurately identifying the starting point of accelerated deformation. (2) Coupled with coordinate transformation, the time logarithm prediction method was constructed, unifying the units of measurement and resolving convergence issues in data fitting. (3) Empirical research conducted at the Kambove open-pit mine in the Democratic Republic of the Congo demonstrates that this method successfully predicts landslide times four hours in advance, with an error margin of only 0.18 h. This innovation offers robust technical support for slope landslide prevention and control in open-pit mines, enhancing safety standards and mitigating disaster losses.
Investigation of the Layered Effect on the Tensile Fracture Characteristics of Sandstone Using Intact and Pre-Cracked Brazilian Disk Specimens
Authors: Zhong Yuchen , Hao Qi , Liu Huini , Liu Xiling , Wang Lichang , Xie Qin
Published: February 2025

To investigate the stratification effect on rock splitting and Mode I fracture characteristics, standard Brazilian splitting disk specimens and straight-crack disk specimens were subjected to splitting loading tests, and a high-speed camera system and acoustic emission (AE) system were used to study the rocks’ mechanical properties, fracture parameters, and AE characteristics. The results demonstrate the following: (1) The tensile strength and fracture toughness of the layered rock exhibit significant stratification effects, gradually decreasing with the increase in the number of layers and the layer angle. (2) The different angles of the stratification planes lead to the diversity of failure modes in the disk specimens. (3) The S-value and the cumulative AE count curve of specimens without prefabricated cracks show two types of pattern during loading: fluctuating increase mode, and “gentle–steep” increase mode. (4) Layered rock specimens exhibit a low ratio of rise time to voltage amplitude (RA) value and high average frequency (AF) characteristics during fracture, and the shear failure mainly occurs during the stable propagation phase after the initiation of macroscopic cracks. (5) The fracture process zone (FPZ)’s length at the peak point of the specimens decreases exponentially with the increase in the number of layers, but this reduction does not go on indefinitely, and there exists a minimum value. Within the range of 0° to 60°, the FPZ length decreases linearly with increasing stratification angle.
EUR Prediction for Shale Gas Wells Based on the ROA-CatBoost-AM Model
Authors: He Weikang , Li Xizhe , Wan Yujin , Zhan Honming , Wan Nan , He Sijie , Lin Yaoqiang , Wang Longyi , Yu Wenxuan , Chen Liqing
Published: February 2025

Shale gas is a critical energy resource, and estimating its ultimate recoverable reserves (EUR) is a key indicator for evaluating the development potential and effectiveness of gas wells. To address the challenges in accurately predicting shale gas EUR, this study analyzed production data from 200 wells in the CN block. Sixteen potential factors influencing EUR were considered, and key geological, engineering, and production factors were identified using Spearman correlation analysis and mutual information methods to exclude highly linearly correlated variables. An attention mechanism was introduced to weight input features prior to model training, enhancing the interpretability of feature contributions. The hyperparameters of the model were optimized using the Rabbit Optimization Algorithm (ROA), and 10-fold cross-validation was employed to improve the stability and reliability of model evaluation, mitigating overfitting and bias. The performance of four machine learning models was compared, and the optimal model was selected. The results indicated that the ROA-CatBoost-AM model exhibited superior performance in both fitting accuracy and prediction effectiveness. This model was subsequently applied for EUR prediction and for identifying the primary factors controlling productivity, providing effective guidance for development practices. The dominant factors and production forecasts determined by the model offer valuable references for optimizing block development strategies.
GraphEPN: A Deep Learning Framework for B-Cell Epitope Prediction Leveraging Graph Neural Networks
Authors: Wang Feng , Dai Xiangwei , Shen Liyan , Chang Shan
Published: February 2025

B-cell epitope prediction is crucial for advancing immunology, particularly in vaccine development and antibody-based therapies. Traditional experimental techniques are hindered by high costs, time consumption, and limited scalability, making them unsuitable for large-scale applications. Computational methods provide a promising alternative, enabling high-throughput screening and accurate predictions. However, existing computational approaches often struggle to capture the complexity of protein structures and intricate residue interactions, highlighting the need for more effective models. This study presents GraphEPN, a novel B-cell epitope prediction framework combining a vector quantized variational autoencoder (VQ-VAE) with a graph transformer. The pre-trained VQ-VAE captures both discrete representations of amino acid microenvironments and continuous structural embeddings, providing a comprehensive feature set for downstream tasks. The graph transformer further processes these features to model long-range dependencies and interactions. Experimental results demonstrate that GraphEPN outperforms existing methods across multiple datasets, achieving superior prediction accuracy and robustness. This approach underscores the significant potential for applications in immunodiagnostics and vaccine development, merging advanced deep learning-based representation learning with graph-based modeling.
Evaluating 3D-Printed Polylactic Acid (PLA)-Reinforced Materials: Mechanical Performance and Chemical Stability in Concrete Mediums
Authors: Csótár Hanna , Szalai Szabolcs , Kurhan Dmytro , Sysyn Mykola , Fischer Szabolcs
Published: February 2025

The optimization and evaluation of 3D-printed polylactic acid (PLA) materials for reinforcing concrete elements present a promising avenue for advancing sustainable construction methods. This study addresses the challenges associated with PLA’s dual nature—biodegradable yet mechanically limited for long-term applications—while leveraging its potential to enhance concrete reinforcement. The research identifies gaps in understanding PLA’s mechanical and chemical behavior in alkaline environments, particularly its interactions with concrete matrices. To bridge this gap, four distinct PLA variants (high-impact PLA, engineering PLA, electrical ESD PLA, and gypsum PLA) and ABS (acrylonitrile butadiene styrene) were subjected to dissolution tests in NaOH solutions (pH 12 and 12.55) and mechanical evaluation under three-point bending using digital image correlation (DIC) technology. Test specimens were prepared using optimized 3D printing strategies to ensure structural consistency and were embedded in concrete beams to analyze their reinforcement potential. Force–displacement data and GOM ARAMIS measurements revealed significant differences in mechanical responses, with peak loads ranging from 0.812 kN (high-impact PLA) to 1.021 kN (electrical ESD PLA). Notably, electrical ESD PLA exhibited post-failure load-bearing capacity, highlighting its reinforcement capability. Chemical dissolution tests revealed material-specific degradation patterns, with high-impact and Gypsum PLA showing accelerated surface changes and precipitation phenomena. Observations indicated white crystalline precipitates, likely lime (calcium hydroxide—Ca(OH)2), residue from the dissolution tests (sodium hydroxide—NaOH), or material-derived residues formed on and near PLA elements, suggesting potential chemical interactions. These findings underline the critical role of material selection and optimization in achieving effective PLA–concrete integration. While PLA’s environmental sustainability aligns with industry goals, its structural reliability under long-term exposure remains a challenge. The study concludes that electrical ESD PLA demonstrates the highest potential for application in reinforced concrete, provided its chemical stability is managed, as its peak value (1.021 kN) showed 25.7% higher load-bearing capacity than high-impact PLA (0.812 kN) and did not lose any of its structural stability in the dissolution tests. This work advances the understanding of PLA as a sustainable alternative in construction, offering insights for future material innovations and applications.
A Novel Strutless Double-Row Structure for Deep Excavation: Working Mechanism Study and Analysis
Authors: Jia Jinqing , Pan Xuegang
Published: February 2025

This paper presents a novel strut-free earth retaining wall system for excavation, referred to as the asymmetric double-row pile wall (ARPW) retaining system. This system comprises three key elements: front-row reinforced concrete piles, back-row walls, and connecting crossbeams at the top of the piles. This paper aims to analyze the deformation characteristics and mechanical behavior of the ARPW retaining system, double-row pile wall (DRPW) retaining system, and single-row pile wall (SPW) retaining system using both physical model tests and numerical simulations. The study reveals that, with reasonable row spacing, double-row structures exhibit substantially lower earth pressure and bending moments compared to SPW. Additionally, all double-row structures display reverse bending points. The optimal row spacing for DRPW and ARPW is within the ranges of 2D to 6D and 4D to 8D, respectively. ARPW outperforms DRPW by efficiently utilizing active zone friction force and soil weight force (Gs) to resist overturning moments, thereby resulting in improved anti-overturning capabilities, reduced deformations, lower internal forces, and enhanced stability. The study also presents a case study from the Jinzhonghe Avenue South Side Plot in Tianjin, demonstrating the practical application and effectiveness of the ARPW system in meeting stringent deformation requirements for deep foundation pits. These research findings provide valuable insights for practical engineering applications.
Nutritional Profile and Antioxidant Properties of Hemp (Cannabis sativa L.) Seed from Romania
Authors: Floareș Oarga Doris , Berbecea Adina , Obiștioiu Diana , Hulea Anca , Hotea Ionela , Buzna Ciprian , Sabo Luana Alexandra , Panda Anca Ofelia , Radulov Isidora
Published: February 2025

This study evaluates the nutritional and phytochemical properties of six industrial hemp varieties from Romania. The proximate composition (proteins, lipids, ash, moisture, fiber, and carbohydrates), total polyphenol content (TPC), total flavonoid content (TFC), antioxidant activity (DPPH), and macro/microelements were analyzed. Two extraction methods were used: conventional and ultrasound-assisted extraction. The results showed a protein content of 20.92–25.39 g/100 g, lipid content 24.92–28.43 g/100 g, fiber 25.92–31.21 g/100 g, ash 4.71–6.38 g/100 g, moisture content 4.84–5.96 g/100 g, carbohydrates between 35.05 and 43.58 g/100 g, and energy value between 483.25 and 502.40 kcal/100 g. The TPC content varied between 732.36 and 1457.60 mgGAE/kg for conventional extraction methods and from 1003.48 to 1519.87 mg GAE/kg for ultrasound-assisted methods. The TFC content was 343.91–1013.40 mg QE/kg for conventional extraction methods and 511.92 to 1222.14 mg QE/kg for ultrasound-assisted methods. The results showed that the extraction method influenced the phytochemical compounds. Macroelements were dominated by potassium (5533.23 μg/g), magnesium (2616.34 μg/g), and calcium (1853.51 μg/g). Microelements showed the highest levels of iron (189.49 μg/g), followed by manganese (138.26 μg/g), zinc (75.25 μg/g), and copper (13.08 μg/g). Nickel and cadmium were found in trace amounts. Multivariate analysis (PCA) was used to correlate the data.
Nutritional and Biochemical Characterization of White and Brown Rice (Oryza sativa) Subjected to Different Pest Control Methods
Authors: Villamar-Aveiga Mónica del Rocío , Villamar-Aveiga Carla Verónica , Ortiz-Mata Jhonny Darwin , Valenzuela-Cobos Juan Diego
Published: February 2025

Rice is a vital component of the Ecuadorian diet and plays a significant role in global food security. Agricultural practices aimed at boosting production can, however, compromise grain quality. This study explores the effects of various pest control methods on the nutritional and biochemical quality of both white and brown rice. Compounds such as total phenolics (TPC), dietary fiber (TDF), gamma oryzanol, phytic acid (PA), antioxidant activity (AA), and the presence of heavy metals were analyzed. The research was carried out in Taura, Guayas Province, Ecuador, using a bifactorial experimental design with three replications. Statistical analysis included ANOVA and Tukey HDS tests (α = 0.05), complemented by PCA biplot analysis for comprehensive data exploration. The results highlight significant differences in all variables depending on the rice type (R), with brown rice exhibiting higher values. In terms of pest control type (C), only phytic acid showed significant variance, an effect also evident in the interaction (R × C). Cadmium (<0.30 mg/kg) and arsenic (<0.55 mg/kg) levels remained below national standards, with no significant differences across treatments. The biplot analysis revealed PA independence, with higher values in grains managed with biological control, whereas those under chemical control displayed slightly higher and varied values for other studied variables.
Suitability of CMIP6 Models Considering Statistical Downscaling Based on GloH2O and E-OBS Dataset in River Basin Districts of the Southeastern Baltic Sea Basin
Authors: Akstinas Vytautas , Gurjazkaitė Karolina , Meilutytė-Lukauskienė Diana , Jakimavičius Darius
Published: February 2025

Climate projections based on global climate models (GCMs) are generally subject to large uncertainties, as the models only reflect the local climate in the past to a limited extent. Statistical downscaling is the most cost-effective approach to identify the systematic biases of the GCMs from the past and eliminate them in the projections. This study seeks to evaluate the effectiveness of GCMs in capturing local climatic characteristics at the river basin district scale by applying gridded statistical downscaling techniques using global and regional datasets. The historical observational datasets E-OBS and GloH2O were selected to downscale the raw data of 17 GCMs from ~1° grid cells to 0.25° resolution. E-OBS is a regional dataset supported by a dense network of meteorological stations in Europe, while GloH2O is a global dataset covering all continents. The results show that the suitability of the GCMs varies depending on the selected parameter. The statistical downscaling revealed the advantages of the performance of E-OBS in representing local climate characteristics during the historical period and emphasized the crucial role of regional datasets for good climate depiction. Such an approach provides the possibility to assess the relative performance of GCMs based on the high-resolution observational and reanalysis datasets, while generating statistically downscaled datasets for the best ranked GCMs. The strategies used in this study can help to identify the most appropriate models to assemble the right ensemble of GCMs for specific studies.
Lipid-siRNA Conjugates Targeting High PD-L1 Expression as Potential Novel Immune Checkpoint Inhibitors
Authors: Tansou Rina , Kubo Takanori , Nishida Haruka , Nishimura Yoshio , Mihara Keichiro , Yanagihara Kazuyoshi , Seyama Toshio
Published: February 2025

Programmed death 1 ligand (PD-L1), an important immune checkpoint molecule, is mainly expressed on cancer cells and has been shown to exert an immunosuppressive effect on T-cell function by binding to programmed cell death 1 (PD-1) expressed on T-cells. Recently, immune checkpoint inhibitors using antibody drugs such as nivolumab and atezolizumab have attracted attention. However, clinical challenges, including limitations to the scope of their application, are yet to be addressed. In this study, we developed a novel immune checkpoint inhibitor that targets PD-L1 using lipid-siRNA conjugates (lipid-siPDL1s). The inhibitory effect of lipid-siPDL1s on PD-L1 expression was evaluated and found to strongly suppress mRNA expression. Notably, lipid-siPDL1s exerted a significantly stronger effect than unmodified siPDL1. Interestingly, lipid-siPDL1s strongly inhibited PD-L1 expression despite cancer cell stimulation by interferon-gamma, which induced the overexpression of PD-L1 genes. These results strongly suggest that lipid-siPDL1s could be used as novel immune checkpoint inhibitors.
Circulating Autoantibodies Against Vasoactive Biomarkers Related to Orthostatic Intolerance in Long COVID Patients Compared to No-Long-COVID Populations: A Case-Control Study
Authors: Han Emilie , Müller-Zlabinger Katrin , Hasimbegovic Ena , Poschenreithner Laura , Kastner Nina , Maleiner Babette , Hamzaraj Kevin , Spannbauer Andreas , Riesenhuber Martin , Vavrikova Anja , Domanig Antonia , Nitsche Christian , Lukovic Dominika , Zelniker Thomas A. , Gyöngyösi Mariann
Published: February 2025

Endothelial dysfunction mediated by elevated levels of autoantibodies against vasoactive peptides occurring after COVID-19 infection is proposed as a possible pathomechanism for orthostatic intolerance in long COVID patients. This case-control study comprised 100 long COVID patients from our prospective POSTCOV registry and three control groups, each consisting of 20 individuals (Asymptomatic post-COVID group; Healthy group = pan-negative for antispike protein of SARS-CoV-2; Vaccinated healthy group = no history of COVID-19 and vaccinated). Autoantibodies towards muscarinic acetylcholine receptor M3, endothelin type A receptor (ETAR), beta-2 adrenergic receptor (Beta-2 AR), angiotensin II receptor 1 and angiotensin 1-7 (Ang1-7) concentrations were measured by enzyme-linked immunosorbent assay in long COVID patients and controls. Orthostatic intolerance was defined as inappropriate sinus tachycardia, postural tachycardia, orthostatic hypotonia and other dysautonomia symptoms, such as dizziness or blurred vision (n = 38 long COVID patients). Autoantibody concentrations were compared with routine laboratory parameters and quality of life questionnaires (EQ-5D). The concentration of ETAR autoantibodies were significantly higher in long COVID, Asymptomatic and Vaccinated groups compared to the antispike protein pan-negative Healthy group. A trend towards higher plasma levels of Beta-2 AR and Ang1-7 was measured in long COVID patients, not related to presence of orthostatic intolerance. ETAR autoantibody concentration showed significant positive correlation with the EQ-5D item “Problems in performing usual activities”.
Novel Insights into Viewer-Centered Versus Stimulus-Centered Hemispatial Neglect: A Cross-Sectional Behavioral and Imaging Study of Acute Stroke
Authors: Raman Ashley , Faria Andreia V. , Colavito Michael , Hillis Argye E.
Published: February 2025

Background/Objectives: Hemispatial neglect is common after stroke but is often evaluated only after right hemisphere (RH) stroke. We sought to determine the prevalence of two types of neglect, viewer-centered neglect (VCN) and stimulus-centered neglect (SCN), after left hemisphere (LH) and RH strokes. Additionally, we identified lesion load in each vascular territory and areas of hypoperfusion, estimated with FLAIR hyperintense vessels (FVHs) that contribute to neglect. Methods: A series of 233 stroke patients (73 LH and 160 RH) were administered a task to detect VCN and SCN and received brain MRI within 5 days of onset. We used multivariable logistic regression to identify vascular territories where lesion load and/or hypoperfusion contributed to each type of neglect. Results: While VCN was more prevalent after RH stroke, SCN occurred at a similar rate after LH and RH stroke. In RH stroke, lesion load in the middle cerebral artery occipital region and anterior cerebral artery territory and age predicted left VCN, whereas parietal hypoperfusion independently predicted left SCN. In LH stroke, lesion load across regions and age predicted right VCN, while lesion load in posterior cerebral artery occipital and anterior cerebral artery regions, as well as age, predicted right SCN. The addition of information about hypoperfusion improved the prediction of both VCN and SCN. Conclusions: VCN and SCN are each common after RH stroke, and SCN is common after LH stroke. Each type of neglect is accounted for by distinct areas of infarct and hypoperfusion. Results will aid in the detection of neglect after stroke and may guide reperfusion interventions to improve neglect.
Interest and Transformative Experience as Predictors of Geoscience Academic and Career Choice
Authors: Manzanares Amanda D. , Pugh Kevin J.
Published: February 2025

Recruitment and retention of students in STEM fields continues to be a challenge. Existing models of recruitment and retention emphasize the role of domain interest and identity. In the current research, we investigated the role of transformative experience combined with domain interest/identity in predicting academic and career choice. Transformative experiences represent a form of deep engagement in which students actively apply school learning in their everyday lives and find value in doing so. We looked specifically at academic and career choice, i.e., available educational paths and various career options, in the field of geoscience, as the geosciences currently struggle to attract and retain majors, resulting in a lack of professionals to fill these jobs. We collected survey data from students (n = 60) at three U.S. universities, and used hierarchical multiple regression to investigate self-efficacy, pre-geoscience interest/identity, transformative experience, and post-geoscience interest/identity as predictors of geoscience academic and career choice. The full regression model explained 69% of the variance in geoscience academic/career choice. Further, stepwise regression analysis revealed that post-geoscience interest/identity fully mediated the relations between the other significant predictors (pre-geoscience interest/identity and transformative experience) and geoscience academic/career choice.
The Identification and Prioritization of the Factors Affecting Corporate Social Responsibility Implementation in the Construction Industry—The Perspective of Developing Countries
Authors: Ran Yunxia , Ali Azlan Shah , Shen Liyin , Salleh Hafez Bin , Zhu Mingli , Li Kaiyi , Wang Rui , Cao Yu
Published: February 2025

Corporate social responsibility (CSR) has become a vital component in addressing environmental, social, and economic challenges. In the context of the construction industry, due to the widespread presence of irresponsible practices, CSR implementation studies have gained significant attention, particularly in developing countries. This study consists of a systematic literature review of 58 articles published between 2018 and 2024, seeking to explore the internal and external factors affecting CSR implementation in emerging construction nations. The analysis employs the PESTEL framework, which refers to external impact factors, including political, economic, social, technological, environmental, and legal aspects. Additionally, the SWOT framework is utilized to identify the strength, weaknesses, opportunities, and threats. The Analytic Hierarchy Process (AHP) is then applied to prioritize the identified factors. The results demonstrate that institutional pressures and economic progress are the most influential external opportunities. Internal weaknesses, including subcontracting and quality challenges and financial constraints of SMEs, are significant barriers. This study contributes to the CSR literature by integrating external macro-environmental factors and internal organizational dynamics, offering a strategic and actionable framework for the advancement of CSR implementation in the construction industries of developing countries.
Recent Advances in Mesothelioma Treatment: Immunotherapy, Advanced Cell Therapy, and Other Innovative Therapeutic Modalities
Authors: Suraya Ratoe , Nagano Tatsuya , Tachihara Motoko
Published: February 2025

Mesothelioma is a highly malignant condition arising from the pleura and peritoneum that is closely related to asbestos exposure. The prognosis for this condition has traditionally been poor due to the difficulty physicians have faced in diagnosing and treating this disease, even in its early phase. Fortunately, recent advances in both the molecular understanding of the development of this disease and innovative and novel treatment modalities have accelerated the discovery of new ways to treat mesothelioma. In this review, we first summarize the mechanism of mesothelioma pathophysiology and then relate it to emerging treatment modalities. These include immunotherapy or immune checkpoint inhibitors (ICIs), molecular targeted therapies, and cell-based therapies (such as CAR-T cells or dendritic cells). The scientific basis for the utilization of these treatment modalities, alongside the current clinical evidence for each option, will be explored in detail later on. The hope is that this review can elucidate how these emerging therapeutic options work clinically to help accelerate further developments in novel mesothelioma treatment modalities.
Correction: Singh et al. Stat3 Inhibitors TTI-101 and SH5-07 Suppress Bladder Cancer Cell Survival in 3D Tumor Models. Cells 2024, 13, 1463
Authors: Singh Surya P. , Pathuri Gopal , Asch Adam S. , Rao Chinthalapally V. , Madka Venkateshwar
Published: February 2025

In the original publication [...]
The Emerging Role of the Histone H2AK13/15 Ubiquitination: Mechanisms of Writing, Reading, and Erasing in DNA Damage Repair and Disease
Authors: Shu Qi , Liu Yun , Ai Huasong
Published: February 2025

Histone modifications serve as molecular switches controlling critical cellular processes. The ubiquitination of histone H2A at lysines 13 and 15 (H2AK13/15ub) is a crucial epigenetic modification that coordinates DNA repair and genome stability during the DNA damage response (DDR). This epigenetic mark is dynamically regulated by three functional protein groups: “writer” enzymes (e.g., E3 ubiquitin ligase RNF168 that catalyzes H2AK13/15ub formation), “reader” proteins (including 53BP1 and BRCA1-BARD1 that recognize the mark to guide DNA repair), and “eraser” deubiquitinases (such as USP3 and USP16 that remove the modification). Dysregulation of the precisely coordinated network of H2AK13/15ub is strongly associated with various diseases, including RIDDLE syndrome, neurodegenerative disorders, immune deficiencies, and breast cancer. This review systematically analyzes the dynamic regulation of H2AK13/15ub in DDR and explores its therapeutic potential for disease intervention.
Adsorption and Decomposition Mechanisms of Vapor Growth Carbon Fiber on SiO2 in Non-Catalytic Conditions: A First-Principles Study
Authors: Ma Chen , Zeng Fanguang , Yang Shenbo
Published: February 2025

In this study, the authors employed first-principles calculations to investigate the adsorption and decomposition processes involved in non-catalytic growth of vapor-growth carbon fiber (VGCF) using a non-catalytic growth method. The adsorption and decomposition mechanisms of methane and its decomposition products on the substrate were investigated with the adsorption energy, transition state analysis, and projected density of states (PDOS). The results indicated that the surface adsorption difficulty for CH4 and its decomposition products followed the following order: H > CH4 ≈ CH3 > CH2 > CH > C. The adsorption energy analysis indicates that the adsorption of CH4, CH3, and H is classified as physical adsorption, whereas the adsorption of CH2, CH, and C is classified as chemical adsorption. Adsorption of all particles is exothermic and adsorption can occur. The transition state calculations indicate that the decomposition of CH4 is the rate-determining step in the decomposition reaction. PDOS analysis not only verified the results of adsorption energy analysis but also investigated the effect of adsorption particles. This work is helpful for advancing the application of non-catalytic growth processes to the synthesis of VGCF and enhancing the understanding of the mechanisms governing non-catalytic VGCF formation.
Klebsiella variicola Infection in a Second Trimester Twin Pregnancy: An Underreported Cause of Chorioamnionitis
Authors: Bonasoni Maria Paola , Ferretti Alice , Blasi Immacolata , Comitini Giuseppina , Aguzzoli Lorenzo , Bardaro Marcellino , Russello Giuseppe , Carretto Edoardo
Published: February 2025

Background and Clinical Significance: Klebisella variicola belongs to the Klebsiella pneumoniae complex. It is a Gram-negative, facultative anaerobic, and nonmotile bacillus, mainly isolated in plants. However, as an emerging human pathogen, it has been isolated in immunocompromised patients with urinary tract infections, pneumonia, and bacteremia. K. variicola infection in pregnancy, responsible for acute chorioamnionitis, has never been reported. Case Presentation: We present a case of a twin pregnancy at 17 + 5 weeks in which chorioamnionitis and fetal inflammatory responses such as funisitis and chorionic vasculitis were due to an ascending infection of K. variicola. The pathogen was isolated postmortem in fetal blood and tissues and the placenta using MALDI-ToF mass spectrometry (MALDI-ToF MS). The accuracy of this microbiological diagnosis sheds further light on the epidemiology and virulence of K. variicola in the prenatal setting. Conclusions: In the case of miscarriage, microbiological investigations on the fetus should always be recommended to identify the exact microorganism in order to target the medical treatment and manage subsequent pregnancies.
Salivary Cortisol as a Biomarker for Assessing Fear and Anxiety in Patients with Molar–Incisor Hypomineralization
Authors: Contac Laura-Roxana , Pop Silvia Izabella , Dobreanu Minodora , Oprica Madalina , Voidazan Septimiu , Bica Cristina Ioana
Published: February 2025

Background/Objectives: Molar–incisor hypomineralization (MIH) is a prevalent dental condition characterized by hypomineralized enamel affecting the first permanent molars and incisors. It leads to visible enamel opacities, with varying severity. Children with MIH often experience dental hypersensitivity, which can result in increased dental fear and anxiety, complicating dental treatment. Salivary cortisol, a well-established biomarker of stress, has been used to assess stress levels in various pediatric conditions but has not been extensively studied in MIH. This study aimed to assess salivary cortisol levels as a stress biomarker in children with MIH and compare them to those in children without MIH. Methods: Sixty children aged 5–9 years were divided into two groups: 31 with MIH and 29 healthy controls. Salivary cortisol levels were measured using ELISA, and statistical analysis was performed using IBM SPSS software, version 23 The Mann–Whitney test was used for group comparison, and the Kruskal–Wallis test evaluated the correlation between MIH severity and cortisol levels. Results: Children with MIH showed significantly higher mean cortisol levels (2.63 ng/mL) compared to controls (0.96 ng/mL), with a p-value of 0.0001. A progressive increase in cortisol levels was observed with the severity of MIH, with the highest levels recorded in grade 3 (4.38 ng/mL), in contrast to grade 0 (0.95 ng/mL), with a p-value of 0.001. Conclusions: Salivary cortisol levels are significantly higher in children with MIH, suggesting that MIH-related stress may contribute to dental anxiety and hypersensitivity. These findings highlight the importance of stress management in pediatric dental care.
Research on Super-Twisted Sliding Mode Anti-Disturbance of UAV-Mounted Optoelectronic Platform Based on Predictive Adaptive Law
Authors: Li Jinzhao , Li Xiantao , Wang Lu , Zhang Shitao , Zhao Zhigang , Yang Zongyuan
Published: February 2025

Due to long-term wear and attitude disturbance caused by shafting friction and other factors, the model parameters of the UAV-mounted optoelectronic platform are transformed, and the control accuracy and robustness of the platform are reduced. The traditional approach involves utilizing disturbance observers to observe disturbance values and subsequently reduce their impact on the system. However, when there is significant uncertainty in the model parameters, the application of this method is constrained. Therefore, a super-twisted sliding mode control based on predictive adaptive law (SSMC + PAL) (SSMPAL) is proposed. Firstly, to adapt to the impact of changes in platform structural parameters on the system and mitigate speed fluctuations, a predictive adaptive law is devised. Subsequently, a super-twisted sliding mode controller(SSMC) was developed, whose high-order performance effectively mitigates the chattering phenomenon associated with traditional sliding mode control strategies and minimizes the impact of observation errors stemming from significant model parameter uncertainties on system control accuracy. The convergence and robustness of the designed control strategy are proven using Lyapunov’s theorem. Finally, the effectiveness of the algorithm is verified using an actual UAV-mounted optoelectronic platform. The step response test results indicate that, compared to the disturbance observer control strategy, this method reduces the overshoot by 7.8% and significantly shortens the response time and transition process, demonstrating its superior dynamic response capability. Subsequent anti-disturbance and robustness tests further highlight the superiority of SSMPAL over disturbance observers in terms of anti-disturbance ability and stability, highlighting its significant engineering application value.
Preliminary Study on Enhancing Literacy Skills Through Intervention Targeting Inhibitory Control, Cognitive Flexibility, Working Memory, and Attentional Control
Authors: Castillo-Segura Marta , Carbonero-Martín Miguel Á. , Martín-Antón Luis J.
Published: February 2025

(1) Background: It is important to understand how inhibition, cognitive flexibility, working memory, and attentional control impact reading and writing skills to identify areas for intervention and create effective intervention programs. This pilot study explores the connection between these abilities and academic performance in children aged 6 to 8 using a design with control and experimental groups. (2) Methods: Both groups were assessed pre- and post-intervention using the Color and Word Test, Copy Test of a Complex Figure, Behavior Rating Inventory of Executive Function-2, and Literacy Analysis Test. (3) Results: The results showed significant enhancements in inhibition, cognitive flexibility, and working memory in the experimental group, underscoring the importance of executive functioning in the proper development of literacy. However, no significant differences were observed in reading or writing skills between the two groups, although the experimental group showed improvements in the correlations of all studied variables after the intervention. (4) Conclusions: These findings indicate that improving executive functions may be essential for enhancing literacy skills in children of this age group, being important both for research and for educational practice, emphasizing the importance of including executive function when developing intervention strategies to enhance reading and writing skills.
Successful Educational Actions for Sustainable Development: A Systematic Review of Training for Employability Development of Vulnerable Groups
Authors: Grau-del-Valle Carolina , Llinares-Insa Lucía Inmaculada , García-Raga Laura , Roca-Campos Esther
Published: February 2025

Successful Education Actions (SEAs) have proven to be key to generating opportunities for vulnerable groups. Building a sustainable future requires ensuring inclusive education that addresses inequalities and fosters social cohesion, aspects that SEAs promote by addressing educational and occupational inclusion. Recent studies underline the effects of SEAs on education and social cohesion. However, their impact on employability development has been insufficiently explored. Therefore, this study presents a systematic review that explores how SEAs contribute to the development of transversal competences that improve the employability of people in vulnerable situations, impacting on three dimensions: individual characteristics, personal circumstances, and contextual factors. PRISMA2020 methodology was used, and 30 empirical articles were analysed. After analysis, the results show that the high social and educational expectations, participation, quality relationships, community engagement, and co-creation promoted by SEAs have a significant impact on the employability of participants. These factors can contribute to more sustainable cities by fostering inclusive and lasting employability. The study systematises the positive effects of SEAs on employability and proposes optimal educational strategies that facilitate informed decisions for managers and policy makers.
Spatial and Temporal Climate Change Vulnerability Assessment in the West Bank, Palestine
Authors: Alawna Sandy , Garcia Xavier
Published: February 2025

Climate change is widely recognized as an inevitable phenomenon, with the Mediterranean region expected to experience some of the most severe impacts. Countries in this region, including Palestine, are already observing significant effects on key sectors such as agriculture, water resources, industry, and health. Consequently, there is a need for multidimensional analyses of vulnerability. This study applied a Climate Change Vulnerability (CCV) index to assess spatial and temporal changes in vulnerability across different governorates in the West Bank, Palestine. Climate change vulnerability maps for the West Bank were developed using Geographic Information System (GIS) tools and Analytical Hierarchy Process (AHP) matrices, incorporating various indicators across categories such as Health, Socio-demographic, Agriculture, Service, Housing, and Economic components. The findings indicate that socio-demographic factors contribute significantly to the West Bank’s overall vulnerability to climate change. Although the overall vulnerability has decreased over time, the developed maps reveal that 76% of the West Bank’s population resides in areas classified as highly vulnerable to climate change impacts. In contrast, 10% of the population lives in areas classified as low to very low in terms of vulnerability, including the governorates of Tubas, Salfit, Qalqiliya, and Jericho and Al-Aghwar. These results are invaluable for policymakers, offering guidance on selecting appropriate mitigation and adaptation measures, particularly in highly vulnerable areas, to reduce the impacts of climate change across the region.
Biological Characteristics of the Scale Insect Matsucoccus sinensis (Hemiptera: Coccoidae), a Pest Damaging the Chinese Red Pine Forests
Authors: Li Danchun , Liu Jinqian , Yang Jing , Qi Hao , Lin Yuan , Lei Wei , Zhang Wenyu , Shaarawy Nehal , Dewer Youssef , Shang Suqin , Fu Zuolin
Published: February 2025

The Chinese red pine, Pinus tabulaeformis, is one of the most important evergreen conifer trees in China. It is widely planted in southern Gansu Province and is commonly used for garden trees, hedges, windbreaks, and soil and water conservation. However, Matsucoccus sinensis, a scale insect, has become a major pest of the P. tabulaeformis forests, and its life history and biological characteristics remain unknown. In this study, we investigated the biological characteristics, male cocoon emergence, adult mating period, and egg developmental period of M. sinensis, providing valuable insights for its prevention and control. We conducted continuous observation of the different developmental stages of M. sinensis, both in the laboratory and in P. tabulaeformis fields. The least squares method was used to calculate the egg developmental period of M. sinensis. Our results showed that the scale insect is a monophagous species with one generation occurring per year. The second-instar nymphs overwinter on the needles in the medium shell and reproduce sexually, without parthenogenesis. Male M. sinensis adults reach their peak appearance at the end of April in the study region. The peak emergence of male cocoons occurred between 2:00 AM and 4:00 AM, and the adult mating period lasted from 11:00 AM to 13:00 PM. The larvae of M. sinensis attack the needles of P. tabulaeformis. The nymphs crawled and moved to the inner base of the needles, with first- to third-instar nymphs fixing themselves to the needles to feed. The effective accumulated temperature and starting temperatures for the development of M. sinensis eggs were found to be 86.1 °C and 3.5 °C, respectively. Overall, understanding the biology and life history of M. sinensis is essential for identifying key developmental stages and determining the optimal timing for pest control, ultimately aiding in the development of targeted management strategies to protect P. tabulaeformis forests from this emerging pest.
Lactic Acid Bacteria Diversity in Fermented Foods as Potential Bio-Resources Contributing to Alleviate Malnutrition in Developing Countries: Nigeria as a Case Study
Authors: Adesemoye Elizabeth T. , Sanni Abiodun I. , Spano Giuseppe , Capozzi Vittorio , Fragasso Mariagiovanna
Published: February 2025

Fermented products represent ecological niches for developing microorganisms of interest as bio-resources for improving human well-being. Lactic acid bacteria (LAB) are frequently associated with food fermentations and represent relevant biotechnological resources for enhancing the overall quality of foods and beverages. Among the other potential applications, LAB isolated from traditional fermented foods can play a significant role in addressing malnutrition in developing countries, positively modulating the finished products’ nutritional quality. Nigeria represents an excellent model region to explore this topic as (i) it is a country where the magnitude of phenomena associated with malnutrition is high; (ii) there is a significant effort linked to the achievement of Sustainable Development Goals (SDGs) of the Food and Agriculture Organization (FAO) of the United Nations (UN); and (iii) there is an interesting diversity of traditional fermented foods and beverages. In nations such as Nigeria, fermented foods are integral to infant and young child nutrition, often serving as complementary foods. This review proposes a detailed overview of traditional Nigerian fermented products, including ogi, gari, fufu, lafun, kunu-zaki, masa, wara, kobele, abacha, pito, and burukutu. An overview of the microbial diversity associated with these matrices is also provided, considering a specific focus on LAB responsible for the spontaneous fermentation of various Nigerian foods. We underlined the potential of different LAB species/stains to produce vitamins naturally, particularly B-group vitamins, suggesting strategies that can be followed for in situ biofortification, enhancing the nutritional value of fermented products. In general, the review, summarizing data on microbial diversity presented in principal traditional fermented foods and beverages in Nigeria, supports future studies to exploit the potential of LAB species/strains from fermented foods to combat micronutrient deficiencies in developing countries, such as Nigeria, with the objective to mitigate hidden hunger and alleviate malnutrition in vulnerable populations.
Fractal Geometry: Surface Characterization of Printing Paper
Authors: Lee Yong Ju , Kim Geon-Woo , Lee Tai-Ju , Kim Hyoung Jin
Published: February 2025

This study investigates the surface characteristics of printing papers using fractal geometry, focusing on surface roughness and surface friction as independent properties. The fractal dimension (FD) was analyzed using the power spectral density method, which provided a more distinct characterization of paper surfaces compared to the variogram method. Surface roughness and friction were measured using a stylus-based contact profilometer, and mean absolute deviation (MAD) parameters, such as the mean absolute deviation of surface roughness (RMAD) and friction, were calculated to capture surface variability. The results revealed that while conventional parameters, such as roughness average (Ra) and the average coefficient of friction, are highly sensitive to measurement conditions, MAD-based parameters demonstrate greater robustness and stability. For instance, the regression equation for RMAD vs. Ra showed a strong correlation, with an R² value close to 1.0. However, the slopes were significantly less than one. Furthermore, FD exhibited weak correlations with surface roughness and friction, with R² values of 0.342 and 0.016, respectively, highlighting its unique ability to characterize autocorrelation or complexity of surface. Additionally, the effects of coating on paper surfaces were evaluated, revealing reduced flocculation of surface profiles but a 5% increase in FD, indicating enhanced surface complexity. These findings underscore the complementary role of FD in providing a comprehensive understanding of surface properties, with potential applications in quality control and the design of paper products.