bluuebunny/crossref_metadata_2025 huggingface dataset:
Mission Re-Planning of Reusable Launch Vehicles Under Throttling Fault in the Recovery Flight Based on Controllable Set Analysis and a Deep Neural Network
Authors: Li Keshu , Zhang Wanqing , Yuan Han , Zhou Jing , Ma Ying
Published: February 2025

The frequent launches of reusable launch vehicles are currently the primary approach to support large-scale space transportation, necessitating high reliability in recovery flights. This paper proposes a mission re-planning scheme to address throttling faults, which significantly affect the feasibility of powered landing. To quantify the influence of throttling capability, the concept of “controllable set (CS)” is introduced. The CS is defined as the collection of all feasible initial states that can achieve a successful powered landing and is computed using polyhedron approximation and convex optimization. Based on the CS, the physical feasibility of a power landing problem under deviations from the nominal conditions can be evaluated probabilistically. Besides, a deep neural network (DNN) is constructed to enhance the computational efficiency of the CS analysis, thereby meeting the requirements for online applications. Finally, an effective re-planning scheme is proposed to deal with throttling faults in recovery flight. This is achieved by adjusting the designed angle of attack during the endo-atmosphere unpowered descent phase and selecting the associated optimal handover conditions to initiate the powered landing. The optimal re-planning parameters are determined through a comprehensive investigation of the design space, leveraging probability-based CS analysis and computationally efficient DNN predictions. Simulations verify the accuracy of the CS computation algorithm and the effectiveness of the re-planning scheme under different fault conditions. The results indicate high feasibility probabilities of 99.97%, 98.12%, and 78.52% for maximum throttling capabilities at 65%, 75%, and 85% of nominal thrust magnitude, respectively.
Passive Rotor Noise Reduction Through Axial and Angular Blade Spacing Modulation
Authors: Arystanbekov Chingiz , Zhakatayev Altay , Elhadidi Basman
Published: February 2025

This study investigates the aerodynamic and aeroacoustic performance of a novel two-stage two-bladed coaxial propeller that is axially and angularly spaced. Aerodynamic propulsive thrust and efficiency are validated and evaluated using a Reynolds-averaged Navier–Stokes computational fluid dynamics (CFD) model for the two-bladed APC27x13 propeller. Aeroacoustic assessment is conducted using a Ffowcs Williams–Hawkings integral model. A four-bladed coplanar APC27x13 propeller is simulated and considered as the baseline propeller. The CFD results suggest that changes in the rotor thrust for the coaxial blades are within 3% for propellers with 0.25D axial spacing (where D is the propeller diameter) and 30∘ angular spacing for the advance ratio of J=0.3–0.5. The aeroacoustic assessment for J=0.3 reveals that blades with 30∘ and 60∘ azimuthal spacing and 0.25D axial spacing significantly reduce noise compared to the baseline propeller. The reduction is attributed to the redistribution of tonal noise blade passing frequencies, resulting in a reduction in the A-weighted noise levels by up to 2 dBA. Additionally, the study accounts for the effect of the blade tip Mach number, concluding that a tip Mach number ranging between 0.7 and 0.9 is optimal for noise reduction in the 30∘ configuration. The results highlight the potential noise reduction benefits of uneven axial and angular blade spacing while maintaining similar aerodynamic performance.
Research on Flexible Job Shop Scheduling Method for Agricultural Equipment Considering Multi-Resource Constraints
Authors: Wei Zhangliang , Yu Zipeng , Niu Renzhong , Zhao Qilong , Li Zhigang
Published: February 2025

The agricultural equipment market has the characteristics of rapid demand changes and high demand for machine models, etc., so multi-variety, small-batch, and customized production methods have become the mainstream of agricultural machinery enterprises. The flexible job shop scheduling problem (FJSP) in the context of agricultural machinery and equipment manufacturing is addressed, which involves multiple resources including machines, workers, and automated guided vehicles (AGVs). The aim is to optimize two objectives: makespan and the maximum continuous working hours of all workers. To tackle this complex problem, a Multi-Objective Discrete Grey Wolf Optimization (MODGWO) algorithm is proposed. The MODGWO algorithm integrates a hybrid initialization strategy and a multi-neighborhood local search to effectively balance the exploration and exploitation capabilities. An encoding/decoding method and a method for initializing a mixed population are introduced, which includes an operation sequence vector, machine selection vector, worker selection vector, and AGV selection vector. The solution-updating mechanism is also designed to be discrete. The performance of the MODGWO algorithm is evaluated through comprehensive experiments using an extended version of the classic Brandimarte test case by randomly adding worker and AGV information. The experimental results demonstrate that MODGWO achieves better performance in identifying high-quality solutions compared to other competitive algorithms, especially for medium- and large-scale cases. The proposed algorithm contributes to the research on flexible job shop scheduling under multi-resource constraints, providing a novel solution approach that comprehensively considers both workers and AGVs. The research findings have practical implications for improving production efficiency and balancing multiple objectives in agricultural machinery and equipment manufacturing enterprises.
How the “Village Merger and Resettlement” Policy Reshapes Agricultural Carbon Emissions: An Analysis of Effects and Mechanisms from Chinese Rural Practices
Authors: Wang Yafei , Zhang Luyao , Yan Jing , Cheng Shiyuan , Liu Junnan , Zhong Min
Published: February 2025

The “Village Merger and Resettlement” policy, as an adjustment of rural living arrangements and spatial organization, addresses the rural population outflow against the backdrop of global urbanization and industrialization. It has profound impacts on agricultural resource allocation, technological innovation, and carbon emissions, playing a significant role in achieving green and low-carbon development alongside high-quality agricultural advancement. This paper conducts an empirical analysis based on panel data from 30 provincial regions in China from 2001 to 2022 (excluding Tibet, Hong Kong, Macau, and Taiwan) to examine the impact of the “Village Merger and Resettlement” policy on agricultural carbon emissions. It explores the mediating effects of agricultural informatization and the integration of agricultural industries and analyzes the moderating roles of government environmental regulations and public environmental participation. The findings indicate that the “Village Merger and Resettlement” policy significantly suppresses agricultural carbon emissions, with the effects being more pronounced in major grain-producing areas, regions with flat terrain, convenient transportation, and higher levels of technology and labor, as well as on the east side of the Hu Huanyong Line, where the degree of agricultural industrial restructuring is lower and government policy enforcement is stronger. The mediation analysis reveals that the processes of agricultural informatization and industry integration both play positive transmission roles in the policy’s impact on reducing agricultural carbon emissions. The moderation analysis shows that compulsory government environmental regulations have a negative moderating effect on the policy’s carbon emission suppression, while public environmental participation has a positive moderating effect. Therefore, in implementing the “Village Merger and Resettlement” policy, it is necessary to tailor strategies to local conditions, make full use of agricultural informatization resources, reasonably plan the integration of agricultural industries, and accurately grasp the roles of environmental regulations to promote the positive effects on green, low-carbon, and high-quality agricultural development.
US Public Attitudes on Animal Welfare During a Disease Outbreak: Strengthening Animal Disaster Management, Pandemic Preparedness, and the Sustainability of US Agriculture
Authors: Anthony Raymond , Cerqueira Cerqueira
Published: February 2025

This study utilized quantitative methodology in a national online survey to investigate the US public’s beliefs and attitudes regarding human–animal conflicts during the COVID-19 pandemic, with a view to understanding their willingness to consider animals’ interests during a disease outbreak. Our results suggest that the norms regarding prioritizing animal welfare are closely linked to respondents’ sense of relationship with animals and that the development of plans and processes for animal disease management, an essential component of public health preparedness systems, should be informed by the value commitments and ethical motivations of a diverse range of the US public.
Optimized Phosphorus Application Enhances Canopy Photothermal Responses, Phosphorus Accumulation, and Yield in Summer Maize
Authors: Yang Qirui , Zhang Huiyu , Zhang Xiao , Geng Sainan , Zhang Yinjie , Miao Yuhong , Li Lantao , Wang Yilun
Published: February 2025

The improper application of phosphorus (P) fertilizers not only leads to resource wastage and environmental concerns but also disrupts the normal growth and yield formation of maize. This study aims to explore the effects of varying P application rates on the growth, yield, photothermal response characteristics, P accumulation dynamics, and P recovery efficiency (PRE) in summer maize, which provides a theoretical foundation for the efficient and scientific application of P fertilizers. Field experiments were conducted over two growing seasons (2021−2022) in Wen County, Henan Province, with P application rates set at 0, 30, 60, 90, and 120 kg·P2O5·ha−1. At maturity, maize yield and its components were quantified. During key growth stages—jointing, tasseling, silking, and grain filling—plant height, leaf area, Soil and Plant Analyzer Development (SPAD) value, the fraction of photosynthetically active radiation (FPAR), canopy temperature, acid phosphatase activity (ACP), and P accumulation were measured. The results indicated that maize grain yield initially increased with P application, peaking at an average increase of 7.92–15.88%, before decreasing. The optimal P application rates were determined to be 113 kg·P2O5·ha−1 and 68 kg·P2O5·ha−1, respectively. P application significantly lowered canopy temperature and leaf ACP activity while significantly increasing the SPAD value and FPAR at 90 kg·P2O5·ha−1. Logistic regression analysis of P accumulation revealed that increasing P rates enhanced the maximum (Vmax) and mean (Vmean) accumulation rates, as well as the total P accumulation. Moderate P application also improved P absorption in various plant tissues and promoted the transfer of P to the grains. However, PRE, partial factor productivity from P fertilizer (PPFP), and P agronomic efficiency (PAE) declined at higher P rates. In conclusion, P fertilization enhanced maize yield, promoted growth, improved P utilization, and optimized photothermal response characteristics across different growth stages. Based on these findings, the recommended P application rate for summer maize is between 70 and 110 kg·P2O5·ha−1.
The Potential Impact of Flower Characteristics and Pollen Viability of Four Industrial Hemp (Cannabis sativa L.) Grain Varieties on Cross-Pollination
Authors: Dingha Beatrice N. , Jackai Louis E. N.
Published: February 2025

Industrial hemp (Cannabis sativa L.) is primarily a dioecious plant, and monoecious varieties have been developed for high yield. Production practices vary for each variety, prompting the need for the present study to describe the floral characteristics and evaluate pollen quantity and viability of monoecious and dioecious hemp varieties. All four hemp varieties, Henola, CFX-2, Canda, and Joey, have five lanceolate anthers, basifixed to a threadlike filament. Anther length was significantly different among varieties, but not anther width. The longest length (0.38 ± 0.046 cm) was recorded in Henola, and the shortest (0.34 ± 0.043 cm) in CFX-2. Anther width ranged from 0.088 ± 0.0024 to 0.095 ± 0.0021 cm. Pollen grains were triporate and spheroidal in shape and size and differed significantly, with the largest in Joey (27.83 ± 0.78 μm) and Henola (27.489 ± 0.99 μm), and smallest in Canda (22.04 ± 0.56 μm). The number of pollen grains per flower differed significantly among varieties, ranging from 29,183 in Henola to 104,548 in Joey. Even though Henola recorded the lowest pollen number, it had the highest percentage (69.3%) of viable pollen after 24 h of storage 4 °C and Canda had the lowest (54%). Three weeks after storage at the same temperature, pollen viability decreased for all the hemp varieties and ranged from 52% to 58%. There was a moderate, positive and significant relationship (r = 0.496) between anther length and the number of pollen grains in Joey. The relationship in Henola was moderate and non-significant (r = 0.356), and it was weak and non-significant in Canda (r = 0.188) and in CFX-2 (r = 0.037). The findings from this study provide information for growers and researchers on hemp breeding and cultivation practices that may contribute to the prevention of cross-pollination.
Research Status and Progress of All-Position Narrow-Gap GMAW for Pipelines
Authors: Liu Wenji , Li Qing , Yue Jianfeng , Zhu Peng , Li Bing
Published: February 2025

During the all-position narrow-gap welding process of pipelines, welding defects tend to occur in non-flat welding positions, constraining the quality and efficiency of pipeline construction. This paper addresses the sidewall and interlayer lack of fusion defects that commonly arise in all-position pipeline welding. Based on the research achievements of scholars and engineering technicians at home and abroad in recent years, the paper summarizes the influence laws of droplet transfer characteristics, arc morphology, and molten pool behavior on weld seam formation under different welding positions during gas metal arc welding. Additionally, the paper explores strategies for optimizing weld bead formation, including optimizing welding process parameters, controlling the molten pool flow with an external magnetic field, and using laser–arc hybrid welding. The paper points out the development trends of all-position pipeline welding technology, providing technical guidance and problem-solving ideas for alleviating the flow of the molten pool and optimizing the formation of all-position weld seams in engineering practice. Furthermore, it offers direction for scientific research for relevant researchers.
Risk Assessment Considering the Spatiotemporal Evolution of Power Grid Anomalies Under Tropical Cyclones
Authors: Geng Chenlong , Chen Chunyu
Published: February 2025

The increasing frequency of tropical cyclones caused by global warming poses a serious threat to the safe operation of coastal power grids, making it urgent to develop methods for quantitatively assessing the risks of spatiotemporal grid anomalies. This paper proposes a risk assessment method for power grids under the influence of tropical cyclones, with a focus on the spatiotemporal evolution of grid failures. First, the abnormal impact of meteorological factors on power grid equipment is analyzed, revealing the time-varying characteristics of equipment failures. Next, by incorporating power flow redistribution, an abnormal evolution mechanism of the grid that considers the coupling effect of meteorological factors and power flow was established. Then, by identifying the abnormal propagation paths and corresponding quantitative risk assessment metrics, the evolution of system failures during tropical cyclones was analyzed, and the failure chains were evaluated for risk. Finally, simulations based on the IEEE 14 system were conducted to verify the effectiveness of the proposed method in modeling the evolution of grid anomalies and failure processes.
Retrospective Clinical Investigation into the Association Between Abnormal Blood Clotting, Oral Anticoagulant Therapy, and Medium-Term Mortality in a Cohort of COVID-19 Patients
Authors: Dinoi Giorgia , Togo Maria Vittoria , Guida Pietro , Deruvo Caterina , Samarelli Francesco , Imbrici Paola , Nicolotti Orazio , De Luca Annamaria , Mastroianni Franco , Liantonio Antonella , Altomare Cosimo Damiano
Published: February 2025

Background/Objectives: People affected by COVID-19 are exposed to abnormal clotting and endothelial dysfunction, which may trigger thromboembolic events. This study aimed at retrospectively investigating whether oral anticoagulant therapy (OAT), encompassing either direct oral anticoagulants (DOACs), mainly apixaban, or the vitamin K antagonist (VKA) warfarin, could have impacted medium-term mortality in a cohort of SARS-CoV-2 patients. Methods: Among 1238 COVID-19 patients, hospitalized from 17 March 2020 to 15 June 2021, 247 survivors and 247 deceased within 90 days from hospitalization were matched 1:1 based on age, sex, and intensive care unit (ICU) admission within three days. Conditional logistic regression was used to estimate associations by means of odds ratio (OR) with a 95% confidence interval (CI). Results: A univariate regression analysis suggested that OAT, no differently from subcutaneous low-molecular-weight heparins (LMWHs) during hospitalization, has no significant impact (p value > 0.05) on medium-term mortality. A multivariate analysis, limited to baseline variables (i.e., comorbidities and pharmacotherapies at hospital admission) showing significant association (p < 0.05) to mortality in a univariate analysis, revealed that, compared to patients living at 90 days from hospitalization, deceased patients had cancer histories (OR 1.75, CI 1.06–2.90, p = 0.029) or suffered from asthma (OR 2.25, CI 1.13–4.47, p = 0.021). In contrast, heart failure (HF), atrial fibrillation (AF), arteriopathy, chronic obstructive pulmonary disease (COPD), and kidney failure (KF), which, in a univariate analysis, were found to be associated with the endpoint (p < 0.05), lost significance in a multivariate analysis. Therapy at admission with aldosterone antagonists also appeared to be associated with medium-term mortality (OR 2.49, CI 1.52–4.08, p < 0.001); whereas, vitamin D supplementation during hospitalization appeared to be beneficial. Although not conclusive, a search into the Eudravigilance database, combined with consulting a digital predictive platform (PLATO, polypharmacology platform prediction), suggested potential off-target activities, which might contribute to increasing the severity of SARS-CoV-2 infection. Conclusions: This retrospective clinical study furnished evidences of the impact of OAT, comorbidities and other pharmacological treatments on COVID-19 clinical course.
DeepWalk-Based Graph Embeddings for miRNA–Disease Association Prediction Using Deep Neural Network
Authors: Ha Jihwan
Published: February 2025

Background: In recent years, micro ribonucleic acids (miRNAs) have been recognized as key regulators in numerous biological processes, particularly in the development and progression of diseases. As a result, extensive research has focused on uncovering the critical involvement of miRNAs in disease mechanisms to better comprehend the underlying causes of human diseases. Despite these efforts, relying solely on biological experiments to identify miRNA-disease associations is both time-consuming and costly, making it an impractical approach for large-scale studies. Methods: In this paper, we propose a novel DeepWalk-based graph embedding method for predicting miRNA–disease association (DWMDA). Using DeepWalk, we extracted meaningful low-dimensional vectors from the miRNA and disease networks. Then, we applied a deep neural network to identify miRNA–disease associations using the low-dimensional vectors of miRNAs and diseases extracted via DeepWalk. Results: An ablation study was conducted to assess the proposed graph embedding modules. Furthermore, DWMDA demonstrates exceptional performance in two major cancer case studies (breast and lung), with results based on statistically robust measures, further emphasizing its reliability as a method for identifying associations between miRNAs and diseases. Conclusions: We expect that our model will not only facilitate the accurate prediction of disease-associated miRNAs but also serve as a generalizable framework for exploring interactions among various biological entities.
Study on the Impact of Design Parameters of Photovoltaic Combined Vacuum Glazing (PVCVG) on the Energy Consumption of Buildings in Lhasa
Authors: Zhong Luyang , Wu Dan , Zhang Bo , Chen Lixing , Xie Yibing , Zhang Yingzi , Liang Xinchun
Published: February 2025

The synergistic active-passive utilization of solar energy in buildings plays an important role in achieving nearly zero-energy buildings. Building-integrated photovoltaic (BIPV) is a crucial initiative to reduce heating energy consumption, especially in cold climate zones with abundant solar radiation. However, few studies have examined the impact of design parameters of photovoltaic combined vacuum glazing (PVCVG) on building energy efficiency in Lhasa. This study assessed the energy performance of several typical windows and PVCVG with various Window-to-Wall Ratio (WWR) design conditions and investigated how the WWR and orientation of PVCVG influence energy consumption using DesignBuilder7.0 software. The findings indicate that PVCVG exhibits great energy-saving potential in Lhasa, with both orientation and WWR of PVCVG substantially affecting energy consumption. Specifically, when the south-facing WWR exceeds 40%, the energy generated by the three kinds of PV windows can meet the building’s requirements. The optimal orientation for PVCVG is southward, followed by east and west orientations. PVCVG reaches optimal energy satisfaction when the south WWR is 85%. This study is expected to provide useful information for improving energy use efficiency in cold climate zones with abundant solar radiation and promoting sustainable building development.
The Role of Perineuronal Nets in Physiology and Disease: Insights from Recent Studies
Authors: Auer Sophia , Schicht Martin , Hoffmann Lucas , Budday Silvia , Frischknecht Renato , Blümcke Ingmar , Paulsen Friedrich
Published: February 2025

Perineuronal nets (PNNs) are specialized extracellular matrix structures that predominantly surround inhibitory neurons in the central nervous system (CNS). They have been identified as crucial regulators of synaptic plasticity and neuronal excitability. This literature review aims to summarize the current state of knowledge about PNNs, their molecular composition and structure, as well as their functional roles and involvement in neurological diseases. Furthermore, future directions in PNN research are proposed, and the therapeutic potential of targeting PNNs to develop novel treatment options for various neurological disorders is explored. This review emphasizes the importance of PNNs in CNS physiology and pathology and underscores the need for further research in this area.
Sex Differences in Circulating Inflammatory, Immune, and Tissue Growth Markers Associated with Fabry Disease-Related Cardiomyopathy
Authors: Ivanova Margarita M. , Dao Julia , Friedman Andrew , Kasaci Neil , Goker-Alpan Ozlem
Published: February 2025

Fabry disease (FD) is a lysosomal disorder due to alpha-galactosidase-A enzyme deficiency, accumulation of globotriaosylceramide (Gb3) and globotriaosylsphingosine (lyso-Gb3) which lead to proinflammatory effects. Males develop progressive hypertrophic cardiomyopathy (HCM) followed by fibrosis; females develop nonconcentric hypertrophy and/or early fibrosis. The inflammatory response to Gb3/lyso-Gb-3 accumulation is one of the suggested pathogenic mechanisms in FD cardiomyopathy when the secretion of inflammatory and transforming growth factors with infiltration of lymphocytes and macrophages into tissue promotes cardiofibrosis. This study aims to evaluate inflammation-driving cytokines and cardio-hypertrophic remodeling biomarkers contributing to sex-specific HCM progression. Biomarkers were studied in 20 healthy subjects and 45 FD patients. IL-2, IL-10, TNF-α, and IFN-γ were elevated in all patients, while IL-1α, MCP-1, and TNFR2 showed sex-specific differences. The increased cytokines were associated with the NF-kB pathway in FD males with HCM, revealing a correlation between MCP-1, IFN-γ, VEGF, GM-CSF, IL-10, and IL-2. In female patients, the impaired TNFα/TNFR2/TGFβ cluster with correlations to MCP-1, VEGF, GM-CSF, and IL-1α was observed. The activation of cytokines and the NF-kB pathway indicates significant inflammation during HCM remodeling in FD males. The TNFα/TNFR2/TGFβ signaling cluster may explain early fibrosis in females with FD cardiomyopathy. Sex-specific inflammatory responses in FD influence the severity and progression of HCM.
Molecular Mechanisms Underlying Heart Failure and Their Therapeutic Potential
Authors: Fonseka Oveena , Gare Sanskruti Ravindra , Chen Xinyi , Zhang Jiayan , Alatawi Nasser Hawimel , Ross Claire , Liu Wei
Published: February 2025

Heart failure (HF) is a prominent fatal cardiovascular disorder afflicting 3.4% of the adult population despite the advancement of treatment options. Therefore, a better understanding of the pathogenesis of HF is essential for exploring novel therapeutic strategies. Hypertrophy and fibrosis are significant characteristics of pathological cardiac remodeling, contributing to HF. The mechanisms involved in the development of cardiac remodeling and consequent HF are multifactorial, and in this review, the key underlying mechanisms are discussed. These have been divided into the following categories thusly: (i) mitochondrial dysfunction, including defective dynamics, energy production, and oxidative stress; (ii) cardiac lipotoxicity; (iii) maladaptive endoplasmic reticulum (ER) stress; (iv) impaired autophagy; (v) cardiac inflammatory responses; (vi) programmed cell death, including apoptosis, pyroptosis, and ferroptosis; (vii) endothelial dysfunction; and (viii) defective cardiac contractility. Preclinical data suggest that there is merit in targeting the identified pathways; however, their clinical implications and outcomes regarding treating HF need further investigation in the future. Herein, we introduce the molecular mechanisms pivotal in the onset and progression of HF, as well as compounds targeting the related mechanisms and their therapeutic potential in preventing or rescuing HF. This, therefore, offers an avenue for the design and discovery of novel therapies for the treatment of HF.
A Numerical Simulation Study on the Tensile Properties of Welds in Laser-Arc Hybrid Welding of Q355 Medium-Thick Plates
Authors: Tan Diao , Cao Li , Sun Wenlei
Published: February 2025

Laser-arc hybrid welding was applied to Q355 medium-thick steel plates to improve weld tensile properties, with experimental verification comparing welds to the base material. Numerical simulations identified optimal process parameters, analyzing the effects of heat source distance, welding speed, laser power, and arc power on temperature field distribution and molten pool morphology. Heat source distance had the greatest influence, followed by welding speed, laser power, and arc power. Maintaining a peak welding temperature of 900–1000 K refined the weld grain structure, enhancing the tensile performance. Under optimal parameters (laser power: 800 W, arc power: 1200 W, wire distance: 5 mm, welding speed: 15 mm/s), the weld achieved a 77% elongation rate compared to the base material’s 73% at a loading rate of 0.5 mm/min, demonstrating superior tensile properties. These results comply with the Code for Welding of Steel Structures. SEM analysis showed uniform, deep dimples in both the weld and base material, indicating a dense structure, excellent plasticity, and strong fracture resistance. This study offers theoretical and experimental insights for optimizing laser-arc hybrid welding processes.
Dual Relief: How Atopic Dermatitis Treatments Affect Alopecia Areata—A Small Retrospective Cohort Study
Authors: Brănișteanu Daciana Elena , Huțanu Antonia-Elena , Brănișteanu Daniel Constantin , Colac-Boțoc Cristina , Ciobanu Roxana Paraschiva , Munteanu Cătălina-Anca , Colac Alin Gabriel , Brănișteanu George , Onu-Brănișteanu Cătălina , Manolache Nicuța , Toader Mihaela-Paula , Porumb-Andrese Elena
Published: February 2025

Background/Objectives: Atopic dermatitis (AD) and alopecia areata (AA) frequently coexist due to shared immune-mediated mechanisms. Treatments targeting AD, including Janus kinase (JAK) inhibitors and dupilumab, may impact AA outcomes in unpredictable ways. This study aims to evaluate the effects of advanced therapies on patients with concurrent AD and AA to inform treatment strategies. Methods: A retrospective cohort study was conducted on six patients diagnosed with both AD and AA. Treatments included systemic corticosteroids, dupilumab, and JAK inhibitors (baricitinib and upadacitinib). Outcomes were assessed at six months using the Severity of Alopecia Tool (SALT), Dermatology Life Quality Index (DLQI), and Scoring Atopic Dermatitis (SCORAD) scores. Results: Patients receiving JAK inhibitors showed significant improvements in AD and AA outcomes, with mean reductions of 95.65% in SALT scores, 91.03% in DLQI scores, and 89.57% in SCORAD scores. Dupilumab was associated with the onset or worsening of AA in two patients. Systemic corticosteroids provided short-term benefits but are unsuitable for long-term management due to safety concerns. Conclusions: JAK inhibitors are effective for managing concurrent AD and AA, offering substantial improvements in disease control and quality of life. However, dupilumab requires cautious use in patients with these comorbid conditions. Personalized treatment strategies, informed by patient-specific factors, are essential for optimizing outcomes and minimizing risks. Further research is needed to identify predictive markers and refine therapeutic approaches for this challenging population.
Evaluating the Simple View of Reading Model: Longitudinal Testing and Applicability to the Swedish Language
Authors: Nordström Thomas , Fälth Linda , Danielsson Henrik
Published: February 2025

This study investigates the empirical validity of the simple view of reading model in a semi-transparent language, Swedish, by using a large amount of reading test data from 11,791 students. Data were collected during the primary grades (year 1–3), which allowed us to test two aspects of the model: how much reading comprehension variance can be accounted for by decoding and language comprehension across primary grades (nine test occasions in total), and how decoding and language comprehension contribute to reading comprehension at each test occasion (three test occasions per grade). By using a latent variable framework, our findings indicated that nearly all reading comprehension variance was accounted for by decoding and language comprehension across each test occasion. Both decoding and language comprehension contributed to reading comprehension at all grades. While decoding contributed the most to reading comprehension variance at the first test occasions (grade 1), language comprehension became equally important in the middle of second grade. At the end of third grade, language comprehension outperformed decoding. This study shows that the simple view of reading model is highly usable for yet another semi-transparent language, which has practical implications for how to assess reading skills and, ultimately of how to inform reading instruction for beginner readers.
The Implications of Long-Term Local Climate Change for the Energy Performance of an nZEB Residential Building in Volos, Greece
Authors: Stamatellou Antiopi-Malvina , Stamatelos Tassos
Published: February 2025

The construction of nearly zero-emission buildings in Europe and internationally has become mandatory by legislation. In parallel with these developments, the non-reversible increase in ambient temperatures stresses the buildings’ energy systems during the summer months with extreme temperatures, with their severity varying according to the local microclimate. These phenomena result in an increase in the summer cooling loads. Thus, the HVAC system’s performance during summer needs more careful study, especially for the residential sector and wherever the night cooling effect is no longer capable of releasing the stress. In the present work, the impact of climate change on a residential building’s energy performance is studied through energy simulations. The effect of the future increases in the intensity and duration of summer heat waves is assessed by exploiting the long-term forecasting capabilities of a transformer neural network model, trained by existing meteorological data for the period 2007–2023. Based on the forecasted climatic conditions for 2030 and 2040 produced in this way, the projected effects on the system’s energy performance are assessed. The long-term forecast was aided by 43 years of ambient temperature data for Europe, available through the ERA5 Copernicus program datasets. The respective predictions of the building’s HVAC electricity consumption during future summer heat wave episodes of long durations point to the necessity of special measures to keep the internal grid’s autonomy and reduce unwanted interactions with the external grid. Moreover, further improvements in nZEB building design for improved summer energy performance would be critical to the success of this policy during the next two decades.
The State of Health Estimation of Retired Lithium-Ion Batteries Using a Multi-Input Metabolic Gated Recurrent Unit
Authors: He Yu , Pattanadech Norasage , Sukemoke Kasiean , Pan Minling , Chen Lin
Published: February 2025

With the increasing adoption of lithium-ion batteries in energy storage systems, accurately monitoring the State of Health (SoH) of retired batteries has become a pivotal technology for ensuring their safe utilization and maximizing their economic value. In response to this need, this paper presents a highly efficient estimation model based on the multi-input metabolic gated recurrent unit (MM-GRU). The model leverages constant-current charging time, charging current area, and the 1800 s voltage drop as input features and dynamically updates these features through a metabolic mechanism. It requires only four cycles of historical data to reliably predict the SoH of subsequent cycles. Experimental validation conducted on retired Samsung and Panasonic battery cells and packs under constant-current and dynamic operating conditions demonstrates that the MM-GRU model effectively tracks SoH degradation trajectories, achieving a root mean square error of less than 1.2% and a mean absolute error of less than 1%. Compared to traditional machine learning algorithms such as SVM, BPNN, and GRU, the MM-GRU model delivers superior estimation accuracy and generalization performance. The findings suggest that the MM-GRU model not only significantly enhances the breadth and precision of SoH monitoring for retired batteries but also offers robust technical support for their safe deployment and asset optimization in energy storage systems.
Estimation of Forest Aboveground Biomass in North China Based on Landsat Data and Stand Features
Authors: Song Cheng , Li Zechen , Dai Yingcheng , Liu Tian , Li Jianjun
Published: February 2025

The forests in China’s temperate semi-arid region play a significant role in water conservation, carbon storage, and biodiversity protection. An accurate estimation of their aboveground biomass (AGB) is crucial for assessing key ecological characteristics, such as forest carbon storage capacity, biodiversity, and ecological productivity. This provides a scientific basis for forest resource management and ecological conservation in this region. In this study, we extract 17 features related to the dominant species (Larix gmelinii and Betula platyphylla), including 7 vegetation indices derived from remote sensing data, 14 indices from 7 satellite bands, and 3 forest site characteristics. We then analyze the correlations between the AGB and these features. We compare the performance of AGB estimation models using linear regression (LR), polynomial regression (PR), ridge regression (RR), Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and random forest regression (RFR). The results show that for Larix gmelinii, the Landsat 8 bands TM4 and TM7 have a greater degree of correlation with the AGB than the other features, while for Betula platyphylla, bands TM3 and TM4 show a greater degree of correlation with the AGB, and elevation has a weaker correlation with the AGB. Although the linear regression (LR) demonstrates certain advantages for AGB estimation, particularly when the AGB values range from 40 to 70 t/ha, the RFR outperforms in overall performance, with estimation accuracies reaching 85% for Betula platyphylla and 89% for Larix gmelinii. This study reveals that both the species and environmental characteristics may significantly influence the selection of the remote sensing features for AGB estimation, and the choice of algorithm for model optimization is critical. This study innovatively extracts the features related to the dominant species in temperate forests, analyses their relationships with environmental factors, and optimizes the AGB estimation model using advanced regression techniques, offering a method that can be applied to other forest regions as well.
Congenital Anomalies of the Kidney and Urinary Tract in Down Syndrome: Prevalence, Phenotypes, Genetics and Clinical Management
Authors: Leskur Mirela , Leskur Dario , Marijan Sandra , Minarik Luka , Lozić Bernarda
Published: February 2025

Down syndrome (DS), the most common survivable autosomal aneuploidy, is associated with a high prevalence of congenital anomalies of the kidney and urinary tract (CAKUT), significantly increasing the risk of chronic kidney disease (CKD). This review examines the diversity of CAKUT phenotypes reported in individuals with DS, focusing on anomalies affecting the kidney, ureter, bladder, and urethra. According to available literature, hydronephrosis is the most common renal anomaly, often secondary to other CAKUT phenotypes, followed by renal hypoplasia and glomerulocystic disease. Furthermore, obstructive uropathies are also frequent but usually lack detailed characterization in the literature. Key features of CAKUT in DS, including reduced kidney size, renal cystic diseases, acquired glomerulopathies, reduced nephron number, and immature glomeruli heighten the risk of CKD. Also, early detection of lower urinary tract dysfunction (LUTD) is critical to prevent progressive upper urinary tract damage and CKD. Despite the prevalence of CAKUT in DS, reported between 0.22% and 21.16%, there is a lack of standardized diagnostic criteria, consistent terminology, and extended follow-up studies. Systematic screening from infancy, including regular renal monitoring via urinalysis and ultrasound, plays a critical role in the timely diagnosis and intervention of CAKUT. To further enhance diagnostic accuracy and develop effective therapeutic strategies, increased awareness and focused research into the genetic factors underlying these anomalies are essential. Moreover, a multidisciplinary approach is indispensable for managing CAKUT and its associated complications, ultimately ensuring better long-term outcomes and an improved quality of life for individuals with DS.
Analysis of Transcriptome Differences Between Subcutaneous and Intramuscular Adipose Tissue of Tibetan Pigs
Authors: Li Xinming , Huang Qiuyan , Meng Fanming , Hong Chun , Li Baohong , Yang Yecheng , Qu Zixiao , Wu Junda , Li Fei , Xin Haiyun , Hu Bin , Wu Jie , Hu Chuanhuo , Zhu Xiangxing , Tang Dongsheng , Du Zongliang , Wang Sutian
Published: February 2025

Background/Objectives: Fat deposition traits in pigs directly influence pork flavor, tenderness, and juiciness and are closely linked to overall pork quality. The Tibetan pig, an indigenous breed in China, not only possesses a high intramuscular fat content but also exhibits a unique fat metabolism pattern due to long-term adaptation to harsh environments. This makes it an excellent genetic and physiological model for investigating fat deposition characteristics. Adipose tissue from different body regions displays varying morphologies, cytokines, and adipokines. This study aimed to examine adipose tissue deposition characteristics in different parts of Tibetan pigs and provide additional data to explore the underlying mechanisms of differential fat deposition. Methods: Our research identified significant differences in the morphology and gene expression patterns between subcutaneous fat (abdominal fat [AF] and back fat [BF]) and intramuscular fat (IMF) in Tibetan pigs. Results: Histological observations revealed that subcutaneous fat cells were significantly larger in area and diameter compared to IMF cells. The transcriptomic analysis further identified differentially expressed genes (DEGs) between subcutaneous fat and IMF, with a total of 65 DEGs in BF vs. IMF and 347 DEGs in AF vs. IMF, including 25 DEGs common to both comparisons. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that these genes were significantly associated with lipid metabolism-related signaling pathways, such as the Wnt, mTOR, and PI3K-Akt signaling pathways. Several DEGs, including DDAH1, ADRA1B, SLCO3A1, and THBS3, may be linked to the differences in fat deposition in different parts of Tibetan pigs, thereby affecting meat quality and nutritional value. Conclusions: These findings provide new insights into the unique fat distribution and deposition characteristics of Tibetan pigs and establish a foundation for breeding strategies aimed at improving pork quality.
Outcomes of Treating Tuberculosis Patients with Drug-Resistant Tuberculosis, Human Immunodeficiency Virus, and Nutritional Status: The Combined Impact of Triple Challenges in Rural Eastern Cape
Authors: Dlatu Ntandazo , Faye Lindiwe M. , Apalata Teke
Published: February 2025

Background: Treatment outcomes are critical measures of TB treatment success, especially in resource-limited settings where tuberculosis remains a major public health issue. This study evaluated the treatment outcomes of patients with drug-resistant tuberculosis (DR-TB), co-infected with human immunodeficiency virus (HIV), and the impact of nutritional status, as measured by body mass index (BMI), on these outcomes in rural areas of the Olivier Reginald Tambo District Municipality, Eastern Cape, South Africa. Methods: A retrospective review of 360 patient files from four TB clinics and one referral hospital was conducted between January 2018 and December 2020. Data collected included patient demographics, clinical characteristics, BMI (categorized as underweight, normal, overweight, or obese), HIV status, DR-TB type, and treatment outcomes. Statistical analyses assessed the association between BMI categories, HIV status, and treatment outcomes. A scatter plot was used to illustrate BMI trends as a continuous variable in relation to age, enabling an analysis of BMI distribution across different age groups. Additionally, bar charts were utilized to explore categorical relationships and patterns in BMI across these groups. Results: The majority of patients were co-infected with HIV and had DR-TB, with rifampicin-resistant TB (RR-TB) and multidrug-resistant TB (MDR-TB) being the most prevalent forms. Treatment outcomes varied significantly by BMI category. Underweight patients had the lowest cure rates (23.2%), highlighting the adverse impact of malnutrition on DR-TB treatment success. Patients with normal BMI demonstrated higher cure rates (34.7%), while overweight and obese patients had moderate outcomes. HIV co-infection further reduced cure rates, with co-infected individuals showing poorer outcomes than HIV-negative patients. Gender disparities were also observed, with females achieving higher cure rates (39.1%) compared to males (31.4%). Weak trends linked BMI and DR-TB type, such as a higher prevalence of normal BMI among RR-TB cases. Conclusion: This study underscores the significant influence of nutritional status on DR-TB treatment outcomes, particularly among patients co-infected with HIV. Underweight patients face the greatest risk of poor outcomes, emphasizing the need for nutritional support as a critical component of DR-TB management. Comprehensive HIV care and gender-specific interventions are also essential to address disparities in treatment success. Tailored strategies focusing on these aspects can significantly enhance outcomes in high-burden, resource-limited settings.
Nanotherapy of Glioblastoma—Where Hope Grows
Authors: Grzegorzewski Jan , Michalak Maciej , Wołoszczuk Maria , Bulicz Magdalena , Majchrzak-Celińska Aleksandra
Published: February 2025

Localization in the central nervous system, diffuse growth, the presence of stem cells, and numerous resistance mechanisms, all make glioblastoma (GBM) an incurable tumor. The standard treatment of GBM consisting of surgery; radio- and chemotherapy with temozolomide provides insufficient therapeutic benefit and needs to be updated with effective modern solutions. One of the most promising and intensively explored therapeutic approaches against GBM is the use of nanotherapy. The first, and so far only, nanoparticle-based therapy approved for GBM treatment is NanoThermTM. It is based on iron oxide nanoparticles and the thermal ablation of the tumor with a magnetic field. Numerous other types of nanotherapies are being evaluated, including polymer and lipid-based nanoformulations, nanodiscs, dendrimers, and metallic, silica, or bioderived nanoparticles, among others. The advantages of these nanoscale drug carriers include improved penetration across the blood–brain barrier, targeted drug delivery, biocompatibility, and lower systemic toxicity, while major problems with their implementation involve scaling up their production and high costs. Nevertheless, taking all the impressive benefits of nanotherapies into consideration, it seems obvious that the combined effort of the scientific world will need to be taken to tackle these challenges and implement these novel therapies into clinics, giving hope that the battle against GBM can finally be won.