bluuebunny/crossref_metadata_2025 huggingface dataset:
Evolution of the Concept and Scientific Mapping of Sustainable Human Resource Management S-(HRM)
Authors: Giraldo-Giraldo Camilo , Rubio-Andrés Mercedes , Rave-Gómez Elkin Darío , Gutiérrez-Broncano Santiago
Published: January 2025

The objective of this study was to analyse the evolutionary field of sustainable human resource management (S-(HRM)) over four strategically chosen sub-periods in order to understand its behaviour in the period from 1991 to 2024. We started by conducting a comprehensive review of research articles related to our topic, aiming to produce a scientific, accurate, and well-argued result through quantitative and empirical research, incorporating both factorial and exploratory analyses. We began by carrying out an exhaustive review of different research articles related to our topic in order to generate a scientific, truthful and argumentative result, from quantitative and empirical research, in relation to a factorial and exploratory analysis. Regarding the analysis of the period between the years chosen for this research (1991–2024), we observe that the subject analysed has gradually evolved, with an increase in publications, as evidenced in the different graphs. In turn, the analysis of the most prominent themes for the sub-periods is illustrated by their classification in strategic diagrams and structured spheres quantified in the statistical software SciMAT v1.1.06, through keywords, which is the strategy best adapted to this type of research. The analysis (keywords) configures the most important concepts of the research field.
A Dynamic Monitoring Framework for Spring Low-Temperature Disasters Affecting Winter Wheat: Exploring Environmental Coercion and Mitigation Mechanisms
Authors: Li Meixuan , Huo Zhiguo , Mi Qianchuan , Zhang Lei , Yang Jianying , Zhang Fengyin , Kong Rui , Wang Yi , Huo Yuxin
Published: January 2025

The implementation of real-time dynamic monitoring of disaster formation and severity is essential for the timely adoption of disaster prevention and mitigation measures, which in turn minimizes disaster-related losses and safeguards agricultural production safety. This study establishes a low-temperature disaster (LTD) monitoring system based on machine learning algorithms, which primarily consists of a module for identifying types of disasters and a module for simulating the evolution of LTDs. This study firstly employed the KNN model combined with a piecewise function to determine the daily dynamic minimum critical temperature for low-temperature stress (LTS) experienced by winter wheat in the Huang-Huai-Hai (HHH) region after regreening, with the fitting model’s R2, RMSE, MAE, NRMSE, and MBE values being 0.95, 0.79, 0.53, 0.13, and 1.716 × 10−11, respectively. This model serves as the foundation for determining the process by which winter wheat is subjected to LTS. Subsequently, using the XGBoost algorithm to analyze the differences between spring frost and cold damage patterns, a model for identifying types of spring LTDs was developed. The validation accuracy of the model reached 86.67%. In the development of the module simulating the evolution of LTDs, the XGBoost algorithm was initially employed to construct the Low-Temperature Disaster Index (LTDI), facilitating the daily identification of LTD occurrences. Subsequently, the Low-Temperature Disaster Process Accumulation Index (LDPI) is utilized to quantify the severity of the disaster. Validation results indicate that 79.81% of the test set samples exhibit a severity level consistent with historical records. An analysis of the environmental stress-mitigation mechanisms of LTDs reveals that cooling induced by cold air passage and ground radiation are the primary stress mechanisms in the formation of LTDs. In contrast, the release of latent heat from water vapor upon cooling and the transfer of sensible heat from soil moisture serve as the principal mitigation mechanisms. In summary, the developed monitoring framework for LTDs, based on environmental patterns of LTD formation, demonstrates strong generalization capabilities in the HHH region, enabling daily dynamic assessments of the evolution and severity of LTDs.
Effects of Sericea Lespedeza Supplementation on Steers Grazing Wild-Type Endophyte-Infected Tall Fescue
Authors: Poudel Sanjok , Pent Gabriel J. , Fike John H. , Zeller Wayne E. , Davis Brittany E.
Published: January 2025

Condensed tannins (CTs) in certain leguminous forages can mitigate toxic alkaloid absorption linked to fescue toxicosis due to their high affinity towards various steroidal and protein-like alkaloids. However, their use as feed supplements remains underexplored. This study evaluated the impact of CT-rich sericea lespedeza (Lespedeza cuneata) pellets on the post-ingestive effects of fescue toxicosis. Twelve steers on wild-type endophyte-infected tall fescue pastures received either sericea lespedeza pellets (LES) or LES with polyethylene glycol (LPEG; negative control) for 12 weeks over three consecutive summers. Body weight, hair coat scores, temperatures (rectal and extremity), cortisol levels, and caudal artery lumen area were measured every four weeks. Steers fed LES showed trends toward higher ADG (p = 0.0999) and reduced hair retention (p = 0.0547) compared to those fed LPEG. Steers on LES also showed hotter tail skin temperatures (p = 0.0053) and cooler rectal temperatures (p < 0.0001) compared to those fed LPEG. LES-fed steers had a 21% larger caudal artery lumen area (p < 0.01), suggesting reduced vasoconstriction. Additionally, LES-fed steers tended to have lower hair cortisol (p = 0.0746), indicating reduced chronic stress. These results suggest that supplementation with CTs may alleviate the post-ingestive effects of fescue toxicosis, potentially by improving blood flow and reducing stress. However, further research is needed to determine whether CTs directly reduce alkaloid absorption, as well as to validate the long-term efficacy of CT supplementation.
Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch
Authors: Gulshin Igor , Makisha Nikolay
Published: January 2025

This study investigates the operational efficiency of the lab-scale oxidation ditch (OD) functioning in simultaneous nitrification and denitrification modes, focusing on forecasting biochemical oxygen demand (BOD5) concentrations over a five-day horizon. This forecasting capability aims to optimize the operational regime of aeration tanks by adjusting the specific load on organic pollutants through active sludge dosage modulation. A comprehensive statistical analysis was conducted to identify trends and seasonality alongside significant correlations between the forecasted values and various time lags. A total of 20 time lags and the “month” feature were selected as significant predictors. These models employed include Multi-head Attention Gated Recurrent Unit (MAGRU), long short-term memory (LSTM), Autoregressive Integrated Moving Average–Long Short-Term Memory (ARIMA–LSTM), and Prophet and gradient boosting models: CatBoost and XGBoost. Evaluation metrics (Mean Squared Error (MSE), Mean Absolute Error (MAE), Symmetric Mean Absolute Percentage Error (SMAPE), and Coefficient of Determination (R2)) indicated similar performance across models, with ARIMA–LSTM yielding the best results. This architecture effectively captures short-term trends associated with the variability of incoming wastewater. The SMAPE score of 1.052% on test data demonstrates the model’s accuracy and highlights the potential of integrating artificial neural networks (ANN) and machine learning (ML) with mechanistic models for optimizing wastewater treatment processes. However, residual analysis revealed systematic overestimation, necessitating further exploration of significant predictors across various datasets to enhance forecasting quality.
Optimization Control of Sub-Synchronous Oscillations in Doubly Fed Generators with Wind Turbines Using the Genetic Algorithm
Authors: Zhang Xu , Xie Yuhan , Xie Qiman , Huang Hui , Gao Lintao , Ye Jun , Ma Shenbing
Published: January 2025

The sub-synchronous oscillation accident of large-scale doubly fed wind turbines connected to a grid through series compensation has caused a serious impact on the power system. By optimizing the parameters of the doubly fed wind turbines control system, the system impedance can be effectively improved to solve the problem of sub-synchronous oscillation. However, owing to the complexity of a grid-connected system of doubly fed generators connected to wind turbines and the influence of the time-varying oscillation characteristics of the system, it is often difficult to achieve a successful suppression. To solve this problem, this paper proposes an optimized additional damping method for the rotor- and grid-side controllers, which can achieve efficient suppression of the sub-synchronous oscillation. The parameters of the proposed additional damping method are optimized for all variable operation conditions using a genetic algorithm under the established frequency–domain impedance model. The detailed time–domain simulation model was constructed with the RTLAB platform to verify the proposed method. The experimental results show that the optimized control strategy can effectively and quickly suppress the sub-synchronous oscillation under different operating conditions, and the amplitude suppression rate reached 85.99%, which effectively improved the grid-connected stability of the wind turbines.
Influence of a Given Field of Temperature on the Blood Pressure Variation: Variational Analysis, Numerical Algorithms and Simulations
Authors: Stavre Ruxandra , Ciorogar Alexandra
Published: January 2025

This article presents a fluid–elastic structure interaction (FSI) problem when the temperature variation of the two media is also taken into account. We introduced the mathematical description of this interaction in a recent article. Our model includes the coupling between the fluid and the elastic medium equations and, in addition, the coupling with the temperature equations. The novelty of this approach is that we succeed in analyzing a complicated double-coupled problem that allows us to describe more complex physical phenomena both from the theoretical and numerical points of view. Since the main goal of this article is to analyze the influence of an exterior field of temperature on fluid pressure variations, the theoretical results obtained in our previous article are completed with qualitative properties concerning the fluid pressure, such as existence, regularity and uniqueness. Our study continues with approximation schemes: in order to improve the unknowns regularity, we introduce the pressure approximation by a sequence of viscoelastic pressure functions and we prove the weak convergence of this sequence to the pressure; then, we present a numerical approximation scheme with stability and convergence results and Uzawa’s algorithm. The last part of the article is devoted to numerical simulations that rely on the numerical schemes introduced and studied before and highlight some physical phenomena related to the considered problem.
Mechanics of Bio-Inspired Protective Scales
Authors: Pantano Antonio , Baiamonte Vincenzo
Published: January 2025

Natural armors found in animals like fish and armadillos offer inspiration for designing protective systems that balance puncture resistance and flexibility. Although segmented armors have been used historically, modern applications are hindered by a limited understanding of their mechanics. This study addresses these challenges by presenting two novel bio-inspired scale structures with overlapping and staggered configurations, modeled after the elasmoid designs found in fish. Their shapes differ significantly from other artificial scales commonly described in the literature, which are typically flat. Instead, these scales feature a support that extends vertically from the substrate, transitioning into an inclined surface that serves as the protective component. Finite element method tests evaluated their performance in puncture resistance and flexibility. The results showed that one type of scale provided better puncture resistance, while the other type offered greater flexibility. These findings highlight how small geometric variations can significantly influence the balance between protection and flexibility. The results offer new insights into the mechanisms of natural armor and propose innovative designs for personal protective equipment, such as bulletproof vests, protective gloves, and fireproof systems. The finite element simulations employed to test the protective systems can also serve as valuable tools for the scientific community to assess and refine designs.
Integrating Experimental Analysis and Gradient Boosting for the Durability Assessment of Lime-Based Mortar in Acidic Environment
Authors: Taheri Ali , Azimi Nima , Oliveira Daniel V. , Tinoco Joaquim , Lourenço Paulo B.
Published: January 2025

This paper presents a comprehensive study of the mechanical properties of lime-based mortar in an acidic environment, employing both experimental analysis and machine learning to model techniques. Despite the extensive use of lime-based mortar in construction, particularly for the strengthening of structures as externally bonded materials, its behavior under acidic conditions remains poorly understood in the literature. This study aims to address this gap by investigating the mechanical performance of lime-based mortar under prolonged exposure to acidic environments, laying the groundwork for further research in this critical area. In the experimental phase, a commercial hydraulic lime-based mortar was subjected to varying environmental conditions, including acidic solution immersion with a pH of 3.0, distilled water immersion, and dry storage. Subsequently, the specimens were tested under flexure following exposure durations of 1000, 3000, and 5000 h. In the modeling phase, the extreme gradient boosting (XGBoost) algorithm was deployed to predict the mechanical properties of the lime-based mortar by 1000, 3000, and 5000 h of exposure. Using the experimental data, the machine learning models were trained to capture the complex relationships between the stress-displacement curve (as the output) and various environmental and mechanical properties, including density, corrosion, moisture, and exposure duration (as input features). The predictive models demonstrated remarkable accuracy and generalization (using a 4-fold cross-validation approach) capabilities (R2 = 0.984 and RMSE = 0.116, for testing dataset), offering a reliable tool for estimating the mortar’s behavior over extended periods in an acidic environment. The comparative analysis demonstrated that mortar samples exposed to an acidic environment reached peak values at 3000 h of exposure, followed by a decrease in the mechanical properties with prolonged acidic exposure. In contrast, specimens exposed to distilled water and dry conditions exhibited an earlier onset of strength increase, indicating different material responses under varying environmental conditions.
Effects of Substrate Biasing and Sulfur Annealing on the Surface of MoS2 Thin Films and TFT
Authors: Subramaniyam Sudharsanam , Bharatan Sudhakar , Muthusamy Sasikala , Sivaprakasam Sinthamani
Published: January 2025

In this work, we report the properties of molybdenum disulfide (MoS2) thin films deposited on the p-type silicon substrate using RF magnetron sputtering. The structural, vibrational and morphological properties of MoS2 thin films were investigated using the Raman spectroscopy, X-ray diffraction technique (XRD), atomic force microscope (AFM) and scanning electron microscope (SEM). Raman spectroscopy result showed the appearance of broad E12g and A1g Raman peaks even without DC biasing the substrate and becomes sharp and distinct when the substrate is DC biased at 60 V. Post-deposition annealing in sulfur ambient resulted in sharp and distinct Raman E12g and A1g peaks confirming the formation of MoS2 thin film and improved Mo-S bonding on the top surface. X-ray diffraction spectra of the samples validates the formation of MoS2 thin film with the appearance of [002] XRD peak, when the substrates are biased. Improved morphological effects with the reduction in nano-sized defects, advent of continuous film and low surface rms roughness value of 0.872 nm, were observed on samples deposited with substrate biasing and post sulfur annealing. A back-gated thin film transistor was fabricated with Al as source-drain contacts and MoS2 as the semiconducting channel. The fabricated transistor exhibited p-type transfer characteristics with threshold voltage of −3.8 V. As a result of annealing and ambient exposure, MoO3 fragments on the top of thinned MoS2 layer resulted in extraction of hole from MoS2, resulting in the p-type behavior in the fabricated thin film transistor. The combination of XRD analysis, Raman measurements and EDS data of the film confirmed MoO3 inclusions in the MoS2 thin film.
Incidence and Predictors of Acute Kidney Injury Following Advanced Ovarian Cancer Cytoreduction at a Tertiary UK Centre: An Exploratory Analysis and Insights from Explainable Artificial Intelligence
Authors: Ratcliffe Elizabeth , Devlin Ciara , Munot Sarika , Broadhead Timothy , Thangavelu Amudha , Quaranta Michela , Nugent David , Kalampokis Evangelos , De Jong Diederick , Laios Alexandros
Published: January 2025

Background/Objectives: The incidence of acute kidney injury (AKI) following advanced epithelial ovarian cancer (EOC) surgery has not been extensively studied. This study aimed to investigate the incidence of AKI and identify preoperative and intraoperative predictors in patients undergoing advanced EOC cytoreduction using both traditional statistics and Artificial Intelligence (AI) modelling. Methods: Retrospective data were collected for 134 patients with a suspected or confirmed diagnosis of advanced EOC (FIGO Stage III–IV) who underwent surgical cytoreduction between January 2021 and December 2022 at a UK tertiary referral centre. AKI was diagnosed according to the KDIGO criteria. Data on 22 patient variables were extracted, including age, Charlson Comorbidity Index (CCI), procedure length, surgical complexity, and length of hospital stay. Logistic regression analysis was used for feature selection to identify AKI predictors, and an extreme gradient boost (XGBoost) model was applied to all variables related to AKI events. Results: The incidence of postoperative AKI was 6.72% (n=9). Predictive factors for AKI included younger age (OR = 0.942, p=0.037), lower CCI (OR = 0.415, p=0.015), longer procedure duration (OR = 1.006, p=0.019), and greater surgical effort (OR = 1.427, p=0.007). Patients with perioperative AKI experienced a doubling in the length of hospital stay (p=0.008). Mortality rates were similar between patients with and without AKI. AI-driven algorithms highlighted the complexity of AKI prediction and provided individual risk profiles, enabling future stratification and prompting different frequencies of AKI monitoring following cytoreduction. Conclusions: Predicting AKI is a complex task. This study found a lower-than-expected incidence of AKI following advanced EOC cytoreductive surgery. AKI is linked to heightened surgical risk-taking, underscoring the need for improved guidelines focusing on postoperative monitoring for targeted patients. Artificial Intelligence offers the potential for personalized AKI prediction.
Prognostication of Brain-Metastasized Patients Receiving Subsequent Systemic Therapy: A Single-Center Long-Term Follow-Up
Authors: Vermassen Tijl , Van Parijs Charlotte , De Keukeleire Stijn , Vandecasteele Katrien , Rottey Sylvie
Published: January 2025

Background. Survival of patients with brain metastases (BMs) is poor. It has become clear that targeted therapy has an effect on BMs and patient’ prognosis. The question remains which patients benefit from additional systemic therapy. This assumption was evaluated in a large single-center cohort. Methods. Patients consecutively planned to undergo local radiotherapy for their BMs in 2006–2017 were selected (n = 200). Prognosis, using CERENAL, disease-specific graded prognostic assessment (DS-GPA), and Radiation Therapy Oncology Group recursive partitioning analysis (RTOG RPA), was evaluated. Results. Ninety-three (46.5%) patients received at least one additional line of systemic therapy subsequent to the diagnosis of their BMs. The median overall survival (OS) was 6.3 months. Having received subsequent systemic therapy resulted in a more favorable OS (10.4 versus 3.9 months). Interestingly, using dichotomized scores, CERENAL showed prognostic properties in all patients for disease-specific survival on multivariate analysis, whereas RTOG RPA and DS-GPA were not withheld in the model. Lastly, only having a favorable DS-GPA resulted in prolonged progression-free survival for first systemic therapy following BM diagnosis. Conclusions. Receiving subsequent systemic therapy has a profound influence on outcome in patients with BMs, indicating the effect of systemic therapy on BMs. Use of the CERENAL brain prognostic score shows potential for further prognostication of patients with more favorable outcomes.
Conjecture Mapping an Integrated steM Camp to Support Middle School Students’ STEM Identity and STEM Interest
Authors: Kudaisi Queshonda J. , Leonas-Cabrera Michael J.
Published: January 2025

This study reports on an integrated steM camp that aimed to improve middle school students’ STEM identity, interest in STEM careers, and interest in environmental issues. Conjecture mapping was used as a tool to design the camp and to investigate if, how, and why the program features influenced the mediating processes and if, how, and why the mediating processes influenced the program outcomes. This study is grounded in design-based research and uses data from observations, interviews, surveys, facilitator reflections, and a group interview to answer the research questions. The findings revealed that most of the program features facilitated the intended mediating processes, which in turn influenced the intended outcomes. We also found that participants’ interest in STEM careers, interest in environmental issues, and interest in STEM identity increased. The findings of this study and the revised conjecture map advance the field’s understanding of how to improve middle school students’ STEM-related outcomes through an integrated steM camp. The findings also speak to some of the challenges of this designed environment and provide recommendations to address those challenges.
Image–Text Person Re-Identification with Transformer-Based Modal Fusion
Authors: Li Xin , Guo Hubo , Zhang Meiling , Fu Bo
Published: January 2025

Existing person re-identification methods utilizing CLIP (Contrastive Language-Image Pre-training) mostly suffer from coarse-grained alignment issues. This is primarily due to the original design intention of the CLIP model, which aims at broad and global alignment between images and texts to support a wide range of image–text matching tasks. However, in the specific domain of person re-identification, local features and fine-grained information are equally important in addition to global features. This paper proposes an innovative modal fusion approach, aiming to precisely locate the most prominent pedestrian information in images by combining visual features extracted by the ResNet-50 model with text representations generated by a text encoder. This method leverages the cross-attention mechanism of the Transformer Decoder to enable text features to dynamically guide visual features, enhancing the ability to identify and locate the target pedestrian. Experiments conducted on four public datasets, namely MSMT17, Market1501, DukeMTMC, and Occluded-Duke, demonstrate that our method outperforms the baseline network by 5.4%, 2.7%, 2.6%, and 9.2% in mAP, and by 4.3%, 1.7%, 2.7%, and 11.8% in Rank-1, respectively. This method exhibits excellent performance and provides new research insights for the task of person re-identification.
ADCNet: Anomaly-Driven Cross-Modal Contrastive Network for Medical Report Generation
Authors: Liu Yuxue , Zhang Junsan , Liu Kai , Tan Lizhuang
Published: January 2025

Medical report generation has made significant progress in recent years. However, generated reports still suffer from issues such as poor readability, incomplete and inaccurate descriptions of lesions, and challenges in capturing fine-grained abnormalities. The primary obstacles include low image resolution, poor contrast, and substantial cross-modal discrepancies between visual and textual features. To address these challenges, we propose an Anomaly-Driven Cross-Modal Contrastive Network (ADCNet), which aims to enhance the quality and accuracy of medical report generation through effective cross-modal feature fusion and alignment. First, we design an anomaly-aware cross-modal feature fusion (ACFF) module that introduces an anomaly embedding vector to guide the extraction and generation of anomaly-related features from visual representations. This process enhances the capability of visual features to capture lesion-related abnormalities and improves the performance of feature fusion. Second, we propose a fine-grained regional feature alignment (FRFA) module, which dynamically filters visual and textual features to suppress irrelevant information and background noise. This module computes cross-modal relevance to align fine-grained regional features, ensuring improved semantic consistency between images and generated reports. The experimental results from the IU X-Ray and MIMIC-CXR datasets demonstrate that the proposed ADCNet method significantly outperforms existing approaches. Specifically, ADCNet achieves notable improvements in natural language generation metrics, as well as the accuracy, completeness, and fluency of medical report generation.
Benchmarking Hyper-Breakpoints for Efficient Virtual Machine Introspection
Authors: Beierlieb Lukas , Schmitz Alexander , Springer Raphael , Dietrich Christian , Iffländer Lukas
Published: January 2025

Virtual Machine Introspection (VMI) is a powerful technology used to detect and analyze malicious software inside Virtual Machines (VMs) from outside. Asynchronously accessing the VM’s memory can be insufficient for efficiently monitoring what is happening inside of a VM. Active VMI introduces breakpoints to intercept VM execution at relevant points. Especially for frequently visited breakpoints, and even more so for production systems, it is crucial to keep their performance overhead as low as possible. In this paper, we provide a systematization of existing VMI breakpoint implementation variants, propose workloads to quantify the different performance penalties of breakpoints, and implement them in the benchmarking application bpbench. We used this benchmark to measure that, on an Intel Core i5 7300U, SmartVMI’s breakpoints take around 81 µs to handle, and keeping the breakpoint invisible costs an additional 21 µs per read access. The availability of bpbench facilitates the comparison of disparate breakpoint mechanisms and their performance optimization with immediate feedback.
Renewable Energy Policies in the USA: A Comparative Study of Selected States
Authors: Fache Anna , Bhat Mahadev G. , Troxler Tiffany G.
Published: January 2025

Policies concerning renewable energy transition are the primary responsibilities of individual states in the United States. This article aims to provide a comprehensive evaluation of state-level renewable energy policies, focusing on identifying key factors driving successful energy transitions and offering actionable insights for policymakers. The research investigates: What are the critical indicators and strategies contributing to an effective renewable energy transition at the state level? To ensure meaningful comparisons, states were selected based on top and bottom performance across various energy parameters, including renewable energy share, solar and wind capacity, electricity costs, and policy adoption (RPS, EERS, and net metering). A rubric, structured around environmental, institutional, social, and techno-economic criteria, was developed to measure policy effectiveness across 15 indicators. Scores for each state were weighted based on their contextual relevance, determined through consultations with energy professionals and the adaptation of existing weighting frameworks. Washington state emerges as the frontrunner, achieving the highest scores for both weighted and unweighted transition performance, closely followed by California. Conversely, Kentucky, Texas, and Florida exhibit the lowest scores. A correlation analysis reveals relationships among performance indicators, such as the impact of stakeholder diversity on energy equity and the link between policy integration and energy demand. This study provides a roadmap for prioritizing renewable policy integration, showing how technology and policy drivers collectively influence the rate of energy transitions. It offers essential insights for shaping state-level renewable energy policies, fostering partnerships, and steering states toward a greener and more resilient energy future.
From Vineyard to Brewery: A Review of Grape Pomace Characterization and Its Potential Use to Produce Low-Alcohol Beverages
Authors: Telini Bianca de Paula , Villa Lorenza Corti , Vainstein Marilene Henning , Lopes Fernanda Cortez
Published: January 2025

The production of low-alcohol beverages is an important world trend due to concerns about health and well-being. The use of agro-industrial residues, such as grape pomace, to produce bioactive and diverse beverages is highly acceptable to consumers. It is an eco-friendly approach that contributes to sustainability and a circular economy. This mini review highlights the composition of grape pomace and its emerging role as a fermentation substrate, emphasizing its potential to contribute to sustainable beverage innovation. In addition, we discussed using non-conventional yeasts to produce beer with different aromas, flavors, and low alcoholic content, as well as the possibility of using a vast diversity of substrates during fermentation, including grape pomace. Different yeasts and substrates bring new opportunities to the market for brewery industries and other products.
Fixed/Preassigned Time Synchronization of Impulsive Fractional-Order Reaction–Diffusion Bidirectional Associative Memory (BAM) Neural Networks
Authors: Mahemuti Rouzimaimaiti , Abdurahman Abdujelil , Muhammadhaji Ahmadjan
Published: January 2025

This study delves into the synchronization issues of the impulsive fractional-order, mainly the Caputo derivative of the order between 0 and 1, bidirectional associative memory (BAM) neural networks incorporating the diffusion term at a fixed time (FXT) and a predefined time (PDT). Initially, this study presents certain characteristics of fractional-order calculus and several lemmas pertaining to the stability of general impulsive nonlinear systems, specifically focusing on FXT and PDT stability. Subsequently, we utilize a novel controller and Lyapunov functions to establish new sufficient criteria for achieving FXT and PDT synchronizations. Finally, a numerical simulation is presented to ascertain the theoretical dependency.
The Relationship of the Pathogenic Variant rs721048 in the Intron of the EHBP1 Gene with the Development of Prostate Cancer and Colorectal Cancer in the Kazakh Population
Authors: Romanova Marina , Abdikerim Saltanat , Dauyey Kaisar , Gassanov Ziyo , Baltayev Nurlan , Satymbayev Shyngys , Zhunussova Aigul , Kaidarova Dilyara , Zhunussova Gulnur
Published: January 2025

Background: Prostate cancer (PC) is one of the most common oncological diseases among men. Up to 20% of PC cases are associated with hereditary risks or syndromes. The impact of common variants, particularly EHBP1 c.1185+30064G>A rs721048, on developing PC and other malignancies remains unclear. There are also no data on the frequency of this variant in the Kazakh population or its association with PC, nor its potential connection with other malignancies, particularly colorectal cancer (CRC). Methods: We utilized the TruSight Cancer Sequencing Panel to assess pathological genomic variants in 72 male patients with histologically verified aggressive PC and 119 patients of Kazakh nationality with histologically confirmed CRC compared to the control group. Results: A variant in the intron of the EHBP1 gene c.1185+30064G>A rs721048 was identified in 18 patients (25%) out of 72 with PC, while in the control group of 41 healthy males, the rs721048 variant was found in only 4 (9.8%) individuals. In the CRC group, rs721048 was detected in 17 cases (14.2%) and eight control individuals (10%). Conclusions: The frequency of the EHBP1 c.1185+30064G>A rs721048 variant in the PC group was significantly higher (p < 0.05) than in healthy males of Kazakh nationality. Identifying EHBP1 c.1185+30064G>A among the male population of Kazakhstan will help form the high-risk groups for PC to prevent the development of malignant neoplasms. The presence of rs721048 was not significantly associated with the risk of developing CRC in our study.
Real-World Outcomes of Anti-CD19 Chimeric Antigen Receptor (CAR) T-Cell Therapy for Third-Line Relapsed or Refractory Diffuse Large B-Cell Lymphoma: A Single-Center Study
Authors: Sridhar Aishwarya , Gunning Thomas S. , Della Pia Alexandra , Zhang Xiaopei , Ahn Jaeil , Sinclaire Brittany , Lukasik Brittany , Cho Christina , Donato Michele L. , Kaur Sukhdeep , Suh Hyung C. , Leslie Lori A. , Feldman Tatyana A. , Goy Andre H. , Ip Andrew
Published: January 2025

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common diagnosed aggressive B-cell lymphoma, with poor outcomes in those who experience relapsed or refractory (R/R) disease. Landmark clinical trials have demonstrated the efficacy and safety of anti-CD19 chimeric antigen receptor (CAR) T-cell therapy for patients with R/R DLBCL, though further exploration of real-world outcomes (RWOs) and safety data is warranted. Methods: A retrospective chart review was performed to collect patient and disease characteristics from patients with R/R DLBCL receiving CAR T-cell therapy for third-line treatment or beyond at the John Theurer Cancer Center as the standard of care. Results: We report on 82 patients with R/R DLBCL that successfully completed an infusion of an anti-CD19 CAR T-cell product at our institution. Best overall and complete response rates were 74.4% (95% CI, 64.9 to 83.8) and 67.1% (95% CI, 56.9 to 77.2), respectively. From the time of CAR T-cell infusion, median PFS was 26.5 months (95% CI, 8.6 months could not be estimated) and OS was not reached. Subgroup analyses revealed no statistical differences in outcomes by use of bridging therapy, Karnofsky performance status, transformed DLBCL status, and the type of CAR T-cell product used for this study. CAR T-cell therapy was well tolerated, with 58 patients (70.7%) experiencing cytokine-release syndrome and 17 patients (20.7%) experiencing immune effector cell-associated neurotoxicity syndrome. Conclusions: These results of RWOs in third-line patients with R/R DLBCL receiving anti-CD19 CAR T-cell therapy are comparable or superior to prior clinical trials and studies of RWOs, validating the strong efficacy and manageable toxicities of CAR T-cell therapy.
Autosomal Dominant Polycystic Kidney Disease Inflammation Biomarkers in the Tolvaptan Era
Authors: Lapão Tânia , Barata Rui , Jorge Cristina , Flores Carlos , Calado Joaquim
Published: January 2025

With the approval of tolvaptan as the first specific medicine for the treatment of rapidly progressive Autosomal Dominant Polycystic Kidney Disease (ADPKD), biomarker discovery has gained renewed interest as it is widely recognized that these will be crucial in clinical decision-making, serving as either prognostic or predictive tools. Since the marketing authorization was first issued in 2015 for ADPKD, tolvaptan has remained the sole pharmacological compound specifically targeting the disease. For ADPKD patients it is an invaluable medicine for retarding disease progression. Although the field of overall biomarker discovery and validation has been detailed in several publications, the role of inflammation remains largely overlooked in ADPKD. The current work aims to provide the reader with an updated review of inflammation biomarkers research in ADPKD, highlighting the role of urinary MCP-1 (monocyte chemoattractant protein-1) as the most promising tool.
Involvement of the SIX10 Gene in the Pathogenicity of Fusarium oxysporum Formae Speciales in Strawberries
Authors: Yang Wenbo , Ma Tianling , Liang Dong , Zhang Chuanqing
Published: January 2025

Strawberries are planted globally as an important crop. Fusarium oxysporum f. sp. fragariae (Fof), a haploid mitosporic, pathogenic fungus with obvious host specificity, is responsible for an economically devastating soil-borne disease seriously threatening strawberry. Fusarium oxysporum is distributed in soils worldwide and causes vascular wilt and root rot disease in over 100 plant species. However, the formae speciales of F. oxysporum commonly have a very narrow host range, often restricted to a single host plant species. We isolated and identified pathogenic F. oxysporum from diseased strawberry samples collected from different provinces in China. Further analysis showed that among the 55 F. oxysporum isolates, only 70.91% belonged to Fof, and the remaining 29.09% were named Fo. The mycelial growth of Fof was faster than that of Fo at 20, 30, and 35 °C. The sporulation ability of Fof was weaker than that of Fo, and Fof presented a significantly higher germination rate under high temperatures. Fof and Fo from strawberry were not pathogenic to tomato or cucumber plants, and Fof showed significantly higher pathogenicity on strawberry than Fo. To explore the pathogenic mechanism of Fof, we knocked out SIX10 in Fof. The mycelial growth rate of ΔFofSIX10 was significantly slower than that of the wild type, but there were no significant differences in spore production. The pathogenicity of ΔFofSIX10 to strawberry was significantly weakened, showing decreased severity of symptoms, indicated by root and crown rot, and wilt. Our research provides a basis for understanding the interaction between F. oxysporum and the host strawberry and the occurrence and management of Fusarium disease on strawberry.
Investigation of Biotransformation Pathways in a Chimeric Mouse with a Humanized Liver
Authors: Karlsson Isabella B. , Ekdahl Anja , Etchingham-Coll Hugh , Li Xue-Qing , Ericsson Cecilia , Ahlqvist Marie , Samuelsson Kristin
Published: January 2025

Xenobiotics, including drugs, undergo metabolism to facilitate detoxification and excretion. Predicting a compound’s metabolic fate before clinical trials is crucial for efficacy and safety. The existing methods rely on in vitro systems and in vivo animal testing. In vitro systems do not replicate the complexity of in vivo systems, and differences in biotransformation pathways between humans and nonclinical species may occur; thus, accurate predictions of human-specific drug metabolism are not always achieved. The aim of this study was to evaluate whether a chimeric mouse with a humanized liver, specifically the PXB-mouse, can mimic human metabolic profiles. PXB-mice have livers engrafted with up to 95% human hepatocytes. The biotransformation of 12 different small-molecule drugs were evaluated in PXB-mice (through analysis of blood and urine) and compared with the metabolism by hepatocytes from humans and mice and, when available, literature reports on human in vivo metabolism. The detected metabolites included major Phase I and II transitions, such as hydroxylation, and N- and O-dealkylation and glucuronidation. The metabolic patterns of the PXB-mice closely matched human in vivo data. It is also worth noting that the human hepatocytes formed most of the circulating metabolites, indicating that hepatocytes provide reliable predictions of human metabolic pathways. Thus, for drugs with human biotransformation pathways that are not observed in nonclinical species, the PXB-mouse model can be valuable in predicting human-specific metabolism.
Early Prediction of Fetal Macrosomia Through Maternal Lipid Profiles
Authors: Chagovets Vitaliy , Frankevich Natalia , Starodubtseva Natalia , Tokareva Alisa , Derbentseva Elena , Yuryev Sergey , Kutzenko Anastasia , Sukhikh Gennady , Frankevich Vladimir
Published: January 2025

The prevalence of fetal macrosomia is steadily increasing worldwide, reaching up to 20%. Fetal macrosomia complicates pregnancy and delivery. Current prediction strategies are inaccurate, and most patients with fetal macrosomia go into labor with an “unknown status”. The aim of this study was to develop a system for predicting fetal macrosomia based on the lipid profiles of pregnant women’s blood serum. In total, 110 patients were included in this study: 30 patients had gestational diabetes mellitus (GDM) and 80 did not. During the observation, blood samples were collected at three time points: in the first trimester (11–13 weeks of pregnancy), in the second trimester (24–26 weeks), and in the third trimester (30–32 weeks). Lipids were detected by flow injection analysis with mass spectrometry. Lipid profiles of pregnant women were discriminated by orthogonal projection on latent structure discriminant analysis (OPLS-DA) in all three trimesters. The developed OPLS-DA models allowed for the prediction of the occurrence of fetal macrosomia during pregnancy. Three sets of models were developed: models independent of GDM status with a sensitivity of 0.85 and specificity of 0.91, models for patients with positive GDM status with a sensitivity of 0.91 and specificity of 0.96, and models for patients with negative GDM status with a sensitivity of 0.93 and specificity of 0.92. Phosphatidylcholines and sphingomyelins were the most important discriminative features. These lipid groups probably play an important role in the pathogenesis of fetal macrosomia and may serve as laboratory markers of this pregnancy complication.
Shaping the Future of Higher Education: A Technology Usage Study on Generative AI Innovations
Authors: Pang Weina , Wei Zhe
Published: January 2025

Generative Artificial Intelligence (GAI) is rapidly reshaping the landscape of higher education, offering innovative solutions to enhance student engagement, personalize learning experiences, and improve academic performance prediction. This study provides an in-depth exploration of GAI applications in educational contexts, drawing insights from 67 case studies meticulously selected from over 300 papers presented at the AIED 2024 conference. The research focuses on eight key themes from student engagement and behavior analysis to the integration of generative models into educational tools. These case studies illustrate the potential of GAI to optimize teaching practices, enhance student support systems, and provide tailored interventions that address individual learning needs. However, this study also highlights challenges such as scalability, the need for balanced and diverse datasets, and ethical concerns regarding data privacy and bias. Further, it emphasizes the importance of improving model accuracy, transparency, and real-world applicability in educational settings. The findings underscore the need for continued research to refine GAI technologies, ensuring they are scalable, adaptable, and equitable, ultimately enhancing the effectiveness and inclusivity of AI-driven educational tools across diverse higher education environments. It should be noted that this study primarily draws from papers presented at the AIED 2024 conference, which may limit global representativeness and introduce thematic biases. Future studies are encouraged to include broader datasets from diverse conferences and journals to ensure a more comprehensive understanding of GAI applications in higher education.
Exercise Pulmonary Hypertension and Beyond: Insights in Exercise Pathophysiology in Pulmonary Arterial Hypertension (PAH) from Invasive Cardiopulmonary Exercise Testing
Authors: Tarras Elizabeth S. , Singh Inderjit , Kreiger Joan , Joseph Phillip
Published: January 2025

Pulmonary arterial hypertension (PAH) is a rare, progressive disease of the pulmonary vasculature that is associated with pulmonary vascular remodeling and right heart failure. While there have been recent advances both in understanding pathobiology and in diagnosis and therapeutic options, PAH remains a disease with significant delays in diagnosis and high morbidity and mortality. Information from invasive cardiopulmonary exercise testing (iCPET) presents an important opportunity to evaluate the dynamic interactions within and between the right heart circulatory system and the skeletal muscle during different loading conditions to enhance early diagnosis, phenotype disease subtypes, and personalize treatment in PAH given the shortcomings of contemporary diagnostic and therapeutic approaches. The purpose of this review is to present the current applications of iCPET in PAH and to discuss future applications of the testing methodology.
Novel Reconstructive Technique for Lower Eyelid Defects: Marginal Approach for Releasing the Lid with Closure Handling Technique (MARCH Technique)
Authors: March De Ribot Anna , Ortiz-Pérez Santiago , March De Ribot Francesc
Published: January 2025

Background: This study introduces a novel surgical approach, the Marginal Approach for Releasing the lid with Closure Handling technique (MARCH technique), a single-step sparing tissue technique, for the reconstruction of medium to large full-thickness lower eyelid defects and its outcomes. Methods: The research considers a single-centre case series with a description of the MARCH technique. Patients with a full-thickness medium to large lower eyelid defect underwent this technique, which combines inferior cantholysis, splitting of lamellae and island or advancement flaps. Demographic data, lid defect size, histology and postoperative outcomes were collected. Results: The surgical procedure was performed in fifteen patients (nine males and six females). The mean age was 73.9 years (range 48–95 years old). Local anaesthesia was used in 86.7% of cases. The mean defect size was 68.7% (range 50% to 79%) of the lid length. All patients presented good results with no significant complications. Conclusions: The MARCH technique seems to be an excellent first-line approach in reconstructing medium to large full-thickness lower eyelid defects. Its single-step approach, tissue-sparing and minimally aggressive nature and ability to potentially guide eyelash positioning and restore the lacrimal system with a more anatomical position make it a promising option. Enrolling more patients and a longer follow-up would provide a better assessment.