bluuebunny/crossref_metadata_2025 huggingface dataset:
Liposomal Nanocarriers to Enhance Skin Delivery of Chemotherapeutics in Cancer Therapy
Authors: Liu Xiangli , Falconer Robert A.
Published: January 2025

Cancer chemotherapeutics administered to cancer patients via traditional oral or parenteral routes often encounter poor bioavailability and severe systemic side effects. Skin delivery is a promising alternative route with reduced side effects and improved therapeutic efficacy and has gained significant attention in recent years. With conventional or deformable liposomal nanocarriers as a skin permeation strategy, cancer chemotherapeutics can be delivered via skin route, offering an option for more efficient therapy. This review summarizes the recent advances in liposome nanocarrier efficacy to enhance the skin delivery of chemotherapeutics with a wide range of physicochemical properties (log Poct from −0.89 to 5.93, MW from 130 to 1415) in targeting local skin cancer, breast cancer, and tumor metastasis and delivering the drug to systemic circulation to treat distal cancers. The potential mechanisms of skin permeation enhancement by different type of liposomes are also discussed in this review.
The Drivers of Mesozoic Neoselachian Success and Resilience
Authors: Staggl Manuel Andreas , De Gracia Carlos , López-Romero Faviel A. , Stumpf Sebastian , Villalobos-Segura Eduardo , Benton Michael J. , Kriwet Jürgen
Published: January 2025

The modern diversity of sharks, skates, and rays (Neoselachii) is the result of various diversification and extinction events during the Mesozoic (252–66 Ma). However, the key drivers of their diversity patterns remain poorly understood despite all the progress that has been accomplished in recent years. Here, we show that the interplay of climatic- and tectonic-linked trajectories, resulting in a high shallow marine habitat availability and lower atmospheric CO2 concentration, were significant drivers and sustainers of Mesozoic neoselachian diversity. We show, for the first time, that higher atmospheric CO2 content negatively affected neoselachian diversity in the past. The recognized gradual faunal changes throughout the Mesozoic and the two major diversification events during the Jurassic and Cretaceous, respectively, ultimately cumulated in an all-time diversity high in the Palaeogene despite the events during the end-Cretaceous extinction event, highlighting their remarkable resilience and adaptability despite severe environmental challenges. We thus provide novel perspectives on the processes underlying neoselachian diversification since the Mesozoic that contribute importantly to a better understanding of the selective forces that have shaped the long-term evolution and diversification of neoselachians. Given their vital role in modern ecosystems, our results provide information about possible future trends in the face of the current climate crisis.
High-Throughput Microfluidic Production of Ultrasmall Lecithin Nanoliposomes for High-Efficacy Transdermal Delivery and Skin-Aging Treatment
Authors: Liang Xiao , Lu Chan , Zheng Fangqiao , Lan Zhengyi , Wang Haoji , Shafiq Muhammad , Pan Xinxin , Chen Hangrong , Ma Ming
Published: January 2025

Background: Liposome particles with smaller sizes could increase transdermal drug delivery efficacy for enhanced skin penetration. While microfluidic methods have enabled controlled liposome synthesis, achieving efficient production of ultrasmall nanoliposomes (NLPUS) with a size smaller than 40 nm yet remains an unmet challenge. Methods: In this study, we employed a helical-blade-strengthened co-flow focusing (HBSCF) device to efficiently synthesize NLPUS, which demonstrated superior skin permeation and retention. Results: Liposome formulation primarily contains unsaturated lecithin, which endows an unprecedented capacity to NLPUS to scavenge reactive oxygen species (ROS). Moreover, NLPUS can effectively encapsulate a broad spectrum of anti-aging agents, including coenzyme Q10 (CoQ10), while preserving its physical properties. In a photoaged skin model, topical application of CoQ10-loaded NLPUS (CoQ10@NLPUS) inhibited ultraviolet B (UVB)-induced matrix metalloproteinase-1 (MMP-1) production, and promoted collagen type I (Col-I) synthesis in skin cells, thereby effectively rejuvenating the photoaged skin. Conclusions: This study presents a straightforward and efficient method for the production of NLPUS, thereby offering a promising platform for transdermal delivery of diverse therapeutic agents.
Exploring Perception Types of Humanities Job Seekers in Employment Preparation: Implications for Career Guidance
Authors: Jang Je Hwa , Lee Song Yi
Published: January 2025

This study uses Q methodology to examine the perception types of humanities majors during their employment preparation process. With the rapid advancement of artificial intelligence (AI) and automation technologies, traditional career paths for humanities majors are shrinking, leading to intensified job mismatches, psychological anxiety, and social bias. The study identified four perception types: (1) Social Support for Career Challenges, which emphasises the need for emotional and institutional support to overcome career-related anxiety and biases, (2) Building Practical Career Skills, which focuses on enhancing employability through practical job experience and technical skill development, (3) Graduation-related Career Constraints, which highlights the limitations caused by academic graduation requirements, calling for structural reforms and expanded certification support, and (4) Proactive Job Preparation, which reflects active efforts to adapt to technological advancements and competitive job market demands by emphasising digital skill acquisition and practical education. We analyse each type’s characteristics and support needs, offering valuable insights into how to address these challenges. The findings provide policy implications for career guidance and employment support, aiming to improve the employment success rates and job stability of humanities graduates. By offering empirical evidence for tailored support programmes, this study contributes practical recommendations to prepare humanities majors for the evolving job market.
Integration of Finite Element Analysis and Machine Learning for Assessing the Spatial-Temporal Conditions of Reinforced Concrete
Authors: Duan Junyi , Yan Huaixiao , Tao Chengcheng , Wang Xingyu , Guan Shanyue , Zhang Yuxin
Published: January 2025

Composite reinforcements are attracting attention in the reinforced concrete (RC) field for their high corrosion resistance, low thermal conductivity, and low electromagnetic interference behavior. However, compared to metallic reinforcements, composites are less ductile and may lead to brittle failure. Three-point flexural tests provide information on the mechanical behavior of metal- and composite-reinforced concrete beams with distinct crack patterns. The structural conditions and failure mechanisms can be defined based on stress change and crack propagation. This study employs finite element analysis (FEA) to simulate the mechanical responses of composite- and metal-reinforced concrete beans under three-point flexural tests and predict the crack propagation in the beams. Machine learning-based algorithms are trained using FEA data to assess the spatial–temporal conditions of the RC beams. The findings indicate that composite rebars provide better reinforcement than metallic rebars in terms of stress fields (30.27% less stress in composite rebars) and crack propagation (fewer cracks in composite RC beams), with the initiation of shear cracks and maximum von Mises stress in rebars being correlated. The findings highlight the effectiveness of the Random Forest Regression (RFR) algorithm (R2=0.96) in assessing RC beam conditions under flexural loads, offering insights for efficient industry applications.
Second Language Trajectories in Immigrant Children: Latent Class Growth Analysis
Authors: Troesch Larissa Maria , Torchetti Loredana , Hasler Sonja , Grob Alexander
Published: January 2025

The present study aims to investigate whether there are different second language trajectories among immigrant children and what influences these trajectories. This longitudinal study included 443 children all learning German as a second language (49.9% girls). On average, at T1, the children were 3;6; at T2, 4;9; at T3, 6;2; and at T4, 7;3 years old. Discontinuous piecewise latent class growth analysis revealed four classes: improvement to low-level proficiency, improvement to medium-level proficiency, improvement to high-level proficiency, and permanent high-level proficiency. Class membership was predicted by early childcare attendance, the duration of the parents’ residence in Switzerland, contact with German speakers, the child’s cognitive abilities, and the parental socioeconomic status.
Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China
Authors: Wang Lingyao , Wu Taofeng , Ren Fangrong
Published: January 2025

As new-energy vehicles (NEVs) gradually gain public attention, their carbon-reduction issues have become a focal point in academia. This study evaluates the carbon-reduction efficiency of NEVs in 21 Chinese provinces using an improved three-stage DEA model, analyzes spatial disparities with the Dagum Gini coefficient, and decomposes carbon-emission factors using the LMDI method. Results show that the overall carbon-reduction efficiency is low, with an average value of only 0.266. Significant differences exist in production- and consumption-stage efficiencies across regions. Shanxi Province performed the best, with efficiency scores of 1 in both stages, while the carbon-reduction stage showed the lowest efficiency, ranging between 0.2 and 0.3 in most regions. The central region exhibited the highest carbon-reduction efficiency, followed by the western and eastern regions, primarily influenced by intra-regional disparities. Energy intensity significantly suppresses carbon emissions, followed by energy structure, while economic development and population size positively contribute to carbon emissions. This study provides theoretical support for regional governments to formulate policies related to the NEV industry and offers practical guidance for its further development.
Thermal Insulation of Agricultural Buildings Using Different Biomass Materials
Authors: Mazur Kamila Ewelina , Wardal Witold Jan , Barwicki Jan , Tseyko Mikhail
Published: January 2025

The main goal of the article is to present the effectiveness of biomass as a thermal insulator and estimate the global potential for using biomass, considering the perspective of sustainable development and improving energy efficiency in agricultural building construction. The article presents two types of piggery construction: one using typical materials like concrete and the other using biomass-based materials. The evaluation is based on carbon footprint and embodied energy indicators. The model calculations developed in this article may be used in the future for life cycle assessment (LCA) analyses of specific construction solutions for rural livestock buildings. Two model variants for constructing a pigsty with different insulating materials were compared. The TB (Traditional Building) variant consisted of layers of (AAC) Autoclaved Aerated Concrete, glass wool, and brick. The second model variant, HB (Hempcrete Building), was made of concrete blocks with the addition of industrial hemp (Cannabis sativa L.) shives. Regarding footprint evaluation, bio-based materials often have a net-negative carbon footprint due to the sequestration effect. The results showed a significant difference in the carbon footprint of both TB and HB solutions—the carbon footprint of the HB variant was only 9.02% of that of the TB variant. The insulation properties of hempcrete were also compared to those of the most frequently used insulating materials in construction, such as glass wool and rock wool. The novelty of the study lies in analyzing the potential use of biomass for thermal insulation in livestock buildings, considering various raw materials, including their industrial properties and the ecological benefits resulting from their implementation. In addition, the authors focused on biomass thermal insulation from the perspective of sustainable development and improving energy efficiency in building construction. Our evaluation and selection of the best solutions are based on the indicators of embodied energy and carbon footprint.
25 Years of EU Forest Policy—An Analysis
Authors: Gordeeva Evgenia , Wolfslehner Bernhard , Weber Norbert
Published: January 2025

A comparison between the most relevant forest-focused and forest-related EU policies from the time periods of the three EU forest(ry) strategies of 1998, 2013 and 2021 has revealed an overall rise in the number of forest-related policies that is mainly rooted in the environmental policy sector. Next to the increasing number of policies, a growing preference for regulations over directives as policy instruments was identified. New policy fields that have gained increasing importance over the last 25 years, most prominently climate, energy and bioeconomy policy, create and define additional demands on forests through their cross-cutting relations with other policy sectors. At the same time, multi-issue strategies that have recently been employed by the European Commission might turn out to be unable to solve the trade-offs that are produced by opposing policy goals.
TFNet: Transformer-Based Multi-Scale Feature Fusion Forest Fire Image Detection Network
Authors: Liu Hongying , Zhang Fuquan , Xu Yiqing , Wang Junling , Lu Hong , Wei Wei , Zhu Jun
Published: January 2025

Forest fires pose a severe threat to ecological environments and the safety of human lives and property, making real-time forest fire monitoring crucial. This study addresses challenges in forest fire image object detection, including small fire targets, sparse smoke, and difficulties in feature extraction, by proposing TFNet, a Transformer-based multi-scale feature fusion detection network. TFNet integrates several components: SRModule, CG-MSFF Encoder, Decoder and Head, and WIOU Loss. The SRModule employs a multi-branch structure to learn diverse feature representations of forest fire images, utilizing 1 × 1 convolutions to generate redundant feature maps and enhance feature diversity. The CG-MSFF Encoder introduces a context-guided attention mechanism combined with adaptive feature fusion (AFF), enabling effective multi-scale feature fusion by reweighting features across layers and extracting both local and global representations. The Decoder and Head refine the output by iteratively optimizing target queries using self- and cross-attention, improving detection accuracy. Additionally, the WIOU Loss assigns varying weights to the IoU metric for predicted versus ground truth boxes, thereby balancing positive and negative samples and improving localization accuracy. Experimental results on two publicly available datasets, D-Fire and M4SFWD, demonstrate that TFNet outperforms comparative models in terms of precision, recall, F1-Score, mAP50, and mAP50–95. Specifically, on the D-Fire dataset, TFNet achieved metrics of 81.6% precision, 74.8% recall, an F1-Score of 78.1%, mAP50 of 81.2%, and mAP50–95 of 46.8%. On the M4SFWD dataset, these metrics improved to 86.6% precision, 83.3% recall, an F1-Score of 84.9%, mAP50 of 89.2%, and mAP50–95 of 52.2%. The proposed TFNet offers technical support for developing efficient and practical forest fire monitoring systems.
An Amide-Carboxylic Acid Compound as Gel Structure Breaker to Improve the Rheology of Oil-Based Drilling Fluids
Authors: Zhang Yu , Lv Kaihe , Huang Xianbin , Li Zhe , Zhang Yang , Yuan Zhenhang
Published: January 2025

High-density oil-based drilling fluids (OBDFs) are widely used in drilling operations, but during their application, the viscosity of the fluid typically increases due to the enhancement of the solid-phase gel network structure. This can lead to issues such as impaired fluid circulation, increased blowout risks, and accelerated drill bit wear. In this study, a compound (OCD), synthesized from tall oil fatty acids, diethylene triamine, and maleic anhydride, was developed to disrupt the strong gel structure in high-density OBDFs, thereby reducing the viscosity of the OBDFs. Rheological properties, including viscosity, yield point, and gel strength, were tested to evaluate the viscosity-reducing effect of OCD on both laboratory-prepared and field high-density OBDFs. Additionally, the effects of OCD on electrical stability (ES), high-temperature high-pressure (HTHP) filtration loss, and solid-phase settling stability were also tested. Finally, the mechanism of OCD was analyzed through contact angle tests, particle size analysis, and microstructural observations. The experimental results demonstrated that OCD could effectively reduce the viscosity of various high-density OBDFs. Adding 2 wt% of OCD reduced the apparent viscosity of laboratory-prepared OBDFs by 20.4%, and reduced the apparent viscosity of field OBDFs with a density of 1.7 g/cm3 by 29.2%. Furthermore, OCD showed good compatibility with OBDFs, having negligible effects on HTHP filtration loss and ES, and maintained good viscosity-reducing performance even at 180 °C. Mechanistic studies revealed that OCD enhanced the hydrophobicity of the solid phase, reduced the particle size of solids, and prevented the formation of excessive network structures in the oil. Therefore, this study provides significant practical value for controlling the rheological performance of the gel system in OBDFs.
Analyzing Decadal Trends of Vegetation Cover in Djibouti Using Landsat and Open Data Cube
Authors: Wardle Julee , Phillips Zachary
Published: January 2025

This study investigates decadal trends in vegetation cover in Djibouti from 1990 to 2020, addressing challenges related to its arid climate and limited resources. Using Digital Earth Africa’s Open Data Cube and thirty years of Landsat imagery, change detection algorithms, and statistical analysis, this research explores vegetation dynamics at various spatial and temporal scales. Studies on change detection have advanced the field through exploring Landsat time series and diverse algorithms, but face limitations in handling data inconsistencies, integrating methods, and addressing practical and socio-environmental challenges. The results, obtained through change detection using NDVI differencing and Welch’s t-test, reveal significant trends in vegetation across Djibouti’s administrative and countrywide levels. Results show significant countrywide vegetative loss from 1990 to 2010, but recovery from 2010 to 2020, as evidenced by Welch’s t-test results. This disproved the Null Hypothesis of no trend and confirmed significant trends across all regions and resolutions analyzed. The findings provide important information for policymakers, land managers, and conservationists, providing awareness into patterns of Djibouti’s vegetation trends in the face of future climate change. The use of Open Data Cube and cloud computing enhances research capacity, allowing for the rapid and repeated analysis of larger time periods and geographical regions.
Masculinity in Caregiving: Impact on Quality of Life and Self-Stigma in Caregivers of People with Multiple Sclerosis
Authors: Alvarez-Roldan Arturo , Bravo-González Félix
Published: January 2025

Background/Objectives: This study aims to examine the impact of the caregiving role on quality of life, perceived burden, gender dissonance, and self-stigma among male caregivers of individuals with multiple sclerosis (MS) in Andalusia, Spain. Methods: A total of 44 male caregivers participated, completing questionnaires on sociodemographic and functional characteristics of the persons with MS (PwMS) they cared for. Measures included the Caregiving Tasks in Multiple Sclerosis Scale (CTiMSS), the Zarit Burden Interview (ZBI), quality of life (WHOQOL-BREF), gender perception, and self-stigma. Data analysis employed ANOVA and regression analyses to assess the relationship between perceived burden and quality of life. Results: Male caregivers experienced significant burden, particularly in instrumental and social–practical caregiving tasks, with a mean score of 23.9 on the ZBI. Perceived burden was inversely related to quality of life, notably impacting physical and psychological health. Sixteen percent of caregivers reported cognitive self-stigma, though without affective or behavioral manifestations. Gender dissonance was observed, as men often perceived certain caregiving tasks as feminine; however, many integrated this role within their masculine identity. Conclusions: Male caregivers of PwMS face the dual burden of caregiving demands and traditional gender expectations. While gender dissonance and low levels of self-stigma were observed, most caregivers adapted by integrating caregiving into their identity. These findings highlight the need for tailored interventions to address their unique challenges and enhance their well-being.
Exploring Human–AI Dynamics in Enhancing Workplace Health and Safety: A Narrative Review
Authors: Fiegler-Rudol Jakub , Lau Karolina , Mroczek Alina , Kasperczyk Janusz
Published: January 2025

Background: Artificial intelligence (AI) is revolutionizing occupational health and safety (OHS) by addressing workplace hazards and enhancing employee well-being. This review explores the broader context of increasing automation and digitalization, focusing on the role of human–AI interaction in improving workplace health, safety, and productivity while considering associated challenges. Methods: A narrative review methodology was employed, involving a comprehensive literature search in PubMed, Embase, and Scopus for studies published within the last 25 years. After screening for relevance and eligibility, a total of 52 articles were included in the final analysis. These publications examined various AI applications in OHS, such as wearable technologies, predictive analytics, and ergonomic tools, with a focus on their contributions and limitations. Results: Key findings demonstrate that AI enhances hazard detection, enables real-time monitoring, and improves training through immersive simulations, significantly contributing to safer and more efficient workplaces. However, challenges such as data privacy concerns, algorithmic biases, and reduced worker autonomy were identified as significant barriers to broader AI adoption in OHS. Conclusions: AI holds great promise in transforming OHS practices, but its integration requires ethical frameworks and human-centric collaboration models to ensure transparency, equity, and worker empowerment. Addressing these challenges will allow workplaces to harness the full potential of AI in creating safer, healthier, and more sustainable environments.
5′-UTR G-Quadruplex-Mediated Translation Regulation in Eukaryotes: Current Understanding and Methodological Challenges
Authors: Kamzeeva Polina N. , Alferova Vera A. , Korshun Vladimir A. , Varizhuk Anna M. , Aralov Andrey V.
Published: January 2025

RNA G-quadruplexes (rG4s) in 5′-UTRs represent complex regulatory elements capable of both inhibiting and activating mRNA translation through diverse mechanisms in eukaryotes. This review analyzes the evolution of our understanding of 5′-UTR rG4-mediated translation regulation, from early discoveries of simple translation inhibitors to the current recognition of their multifaceted regulatory roles. We discuss canonical and non-canonical rG4 structures, their interactions with regulatory proteins, including helicases and FMRP, and their function in both cap-dependent and IRES-mediated translation. Special attention is given to the synergistic effects between rG4s and upstream open reading frames (uORFs), stress-responsive translation regulation, and their role in repeat-associated non-AUG (RAN) translation linked to neurodegenerative diseases. We critically evaluate methodological challenges in the field, including limitations of current detection methods, reporter system artifacts, and the necessity to verify rG4 presence in endogenous transcripts. Recent technological advances, including genome editing and high-throughput sequencing approaches, have revealed that rG4 effects are more complex and context-dependent than initially thought. This review highlights the importance of developing more robust methodologies for studying rG4s at endogenous levels and carefully reevaluating previously identified targets, while emphasizing their potential as therapeutic targets in various diseases.
Early Anti-Drug Antibodies Predict Adalimumab Response in Juvenile Idiopathic Arthritis
Authors: Huang Bo-Han , Hsu Jr-Lin , Huang Hsin-Yi , Huang Jing-Long , Yeh Kuo-Wei , Chen Li-Chen , Lee Wen-I , Yao Tsung-Chieh , Ou Liang-Shiou , Lin Syh-Jae , Su Kuan-Wen , Wu Chao-Yi
Published: January 2025

Adalimumab, a TNF-alpha inhibitor, is approved to treat juvenile idiopathic arthritis (JIA), helping control disease activity and reduce flare frequency. This study aims to investigate predictors of treatment response, including anti-drug antibodies. We reviewed 65 JIA patients (mean age 10.47 ± 3.90 years; 61.5% male) receiving adalimumab for an average of 2.64 ± 0.56 years, with demographics, laboratory parameters, therapeutic regimens, and treatment outcomes recorded. Disease status was evaluated using the Wallace criteria up to 36 months post-treatment initiation, and anti-adalimumab antibody levels were measured after 6 months of treatment. Enthesitis-related arthritis was the most common subtype (64.6%). Inactive disease status was achieved by 83.1% of patients, with 59.3% experiencing relapse. Detectable anti-adalimumab antibody at six months (p = 0.023) and temporomandibular joint (TMJ) involvement (p = 0.038) identified those less likely to achieve inactive disease. An antibody level cutoff of 7.426 ng/mL best predicted response (AUC = 0.808; p = 0.008), while high anti-adalimumab antibody levels after treatment (p = 0.032) and an injection intervals over two weeks (p = 0.042) were predictors of future flares. Our results highlight that the presence of anti-adalimumab antibodies six months after treatment is a risk factor for poor response to adalimumab therapy.
Retinal Pigment Epithelium Under Oxidative Stress: Chaperoning Autophagy and Beyond
Authors: Markitantova Yuliya , Simirskii Vladimir
Published: January 2025

The structural and functional integrity of the retinal pigment epithelium (RPE) plays a key role in the normal functioning of the visual system. RPE cells are characterized by an efficient system of photoreceptor outer segment phagocytosis, high metabolic activity, and risk of oxidative damage. RPE dysfunction is a common pathological feature in various retinal diseases. Dysregulation of RPE cell proteostasis and redox homeostasis is accompanied by increased reactive oxygen species generation during the impairment of phagocytosis, lysosomal and mitochondrial failure, and an accumulation of waste lipidic and protein aggregates. They are the inducers of RPE dysfunction and can trigger specific pathways of cell death. Autophagy serves as important mechanism in the endogenous defense system, controlling RPE homeostasis and survival under normal conditions and cellular responses under stress conditions through the degradation of intracellular components. Impairment of the autophagy process itself can result in cell death. In this review, we summarize the classical types of oxidative stress-induced autophagy in the RPE with an emphasis on autophagy mediated by molecular chaperones. Heat shock proteins, which represent hubs connecting the life supporting pathways of RPE cells, play a special role in these mechanisms. Regulation of oxidative stress-counteracting autophagy is an essential strategy for protecting the RPE against pathological damage when preventing retinal degenerative disease progression.
Multidrug Resistance-Associated Proteins 3 and 5 Play a Role in the Hepatic Transport of Mercuric Conjugates of Glutathione
Authors: Galiciolli Maria Eduarda Andrade , Joshee Lucy , Oliveira Cláudia S. , Barkin Jennifer L. , Bridges Christy C.
Published: January 2025

Multidrug resistance proteins (MRPs) are transporters for metabolic waste and xenobiotics and are known to export a wide range of substances from renal tubular cells. This study aimed to define and characterize the transport of mercuric conjugates of glutathione (GSH-Hg-GSH) in inside-out membrane vesicles containing MRP3 and MPR5. The functionality of the MRP3 and MRP5 vesicles was confirmed by measuring the uptake of [3H]-estradiol and 5-6-carboxy-2′,7′-dichloro-fluorescein (CDCF) over time (at 1, 5, 15, and 30 min). The uptake of GSH-Hg-GSH, containing radioactive mercury ([203Hg]), was measured in each set of membrane vesicles over time, and the findings suggest that GSH-Hg-GSH is a substrate of MRP3 and MRP5. The saturation kinetics were also analyzed by measuring the uptake of 10 µM GSH-[203Hg]-GSH in the presence of 25, 50, or 100 µM unlabeled GSH-Hg-GSH for 5 min at 37 °C. The transport of GSH-Hg-GSH by MRP3 (Vmax = 25.6 µM; Km = 2.8 µM) and MRP5 (Vmax = 32.9 µM; Km = 4.9 µM) was saturable. These findings are the first to show that MRP3 and MRP5 are capable of mediating the export of any form of mercury.
Historical Roots of Heritage Horticulture in the Southern Coastal Plain of Israel
Authors: Zohar Motti , Ben-Bassat Yuval , Bar-Oz Guy
Published: January 2025

This study reconstructs the agricultural landscape of the southern coastal plain of late Ottoman and British Mandatory Palestine (today southwestern Israel) utilizing late 19th and early 20th century cartographic materials and aerial photographs. Immense human effort and ingenuity were required to maintain sustainable agricultural on the fringes of the desert. Given today’s increasingly severe climate crisis, the lessons drawn from these historical agricultural practices have particular resonance. The agricultural land use described in this work extended into the coastal dunes of the region where the shallow water table was exploited to create complex agricultural systems that enabled the growth of citrus trees, grapes, and other crops for export and trade. Aerial photos and maps reveal the critical aspects of this region’s neglected agricultural history. The stability and resilience of these systems, some of which are still in existence 76 years or more after they were abandoned, as seen in the survey conducted for this study, point to the importance of understanding and preserving this chapter of the region’s agricultural heritage. The unique varieties of fruit trees adapted to the local climate of the western Negev still have significant economic value and are threatened with extinction from rapid urban encroachment. The remnants of this tradition serve as historical testimony of a bygone agricultural era which was replaced by mechanized monoculture. The discussion centers on the ways n which the study of heritage agriculture in rapidly changing areas can contribute to the broader field of historical geography by reconstructing landscapes that preserve the knowledge and societal patterns of behavior of past communities for future generations.
Numerical Fatigue Analysis of Dissimilar Lap Joints Fabricated by Dimple Spot Welding for Automotive Application
Authors: Livieri Paolo , Bortolan Michele
Published: January 2025

This paper presents a numerical analysis of dimple spot welding (DSW) as an innovative joining technique for dissimilar materials, namely steel and aluminium alloys. Employing a finite element (FE) model, the study simulates the fatigue performance of DSW joints, considering crucial factors such as contact friction and cyclic loading conditions. While various numerical models are proposed, the simulation incorporating friction and fatigue loading appears to offer the highest accuracy. The research highlights that the fatigue behaviour of DSW joints can be effectively investigated through the non-local theory of the implicit gradient approach by utilising the fatigue curve of arc-welded structures composed of steel or aluminium alloys. Specifically, simulations incorporating friction and fatigue loading demonstrate that the steel spot weld does not represent the weakest point within the joints.
Automatic Text Simplification for Lithuanian: Transforming Administrative Texts into Plain Language
Authors: Mandravickaitė Justina , Rimkienė Eglė , Kapkan Danguolė Kotryna , Kalinauskaitė Danguolė , Čenys Antanas , Krilavičius Tomas
Published: January 2025

In this study, we present the results of experiments on text simplification for the Lithuanian language, where we aim to simplify administrative-style texts to the Plain Language level. We selected mT5, mBART, and LT-Llama-2 as the foundational models and fine-tuned them for the text simplification task. Additionally, we evaluated ChatGPT for this purpose. Also, we conducted a comprehensive assessment of the simplification results provided by these models both quantitatively and qualitatively. The results demonstrated that mBART was the most effective model for simplifying Lithuanian administrative text, achieving the highest scores across all the evaluation metrics. A qualitative evaluation of the simplified sentences complemented our quantitative findings. Attention analysis provided insights into model decisions, highlighting strengths in lexical and syntactic simplifications but revealing challenges with longer, complex sentences. Our findings contribute to advancing text simplification for lesser-resourced languages, with practical applications for more effective communication between institutions and the general public, which is the goal of Plain Language.
The Isolation and Identification of Pseudoalteromonas sp. H27, a Bacterial Strain Pathogenic to Crassostrea gigas
Authors: Qin Heyang , Jiang Junyi , Jing Zhikai , Wang Jiayu , Xu Shuang , Chen Rongwei , Wang Bo , Huo Zhongming , Fang Lei
Published: January 2025

Bacterial infection is frequently observed in disease outbreaks of aquatic animals, making it of significance to isolate and identify the bacterial pathogens. In this study, diseased individuals of Crassostrea gigas were sampled from the nearshore area in Zhanjiang, Guangdong in May 2023. Culturable bacteria were isolated from the diseased tissue and a pathogenic strain labeled as H27 was screened through a hemolysis test and bacterial challenge experiments. Morphological characterization, 16S rRNA gene sequence-based molecular identification and biochemical tests showed that strain H27 belonged to the genus of Pseudoalteromonas, a dominant genus in the diseased tissue of C. gigas revealed by bacterial community structure analysis. The clinical signs originally observed in naturally diseased C. gigas were reproduced in strain H27-challenged adults, both with the red mantle and adductor. Histopathological analysis was further performed on the diseased tissues of the latter, which showed a significantly increased accumulation of pigment granules in the cytoplasm of the diseased mantle as well as enlarged muscle fiber distances in the diseased adductor. In addition, strain H27 was re-isolated from tissues of the moribund C. gigas after bacterial challenge, indicating the fulfillment of Koch’s postulate. Our results help to enrich the knowledge of C. gigas diseases, possibly contributing to disease prevention and control.
Comparison of Changes in Sterol Content of Nuts After Roasting Using Conventional and Microwave Methods and After Storage
Authors: Kulik Klaudia , Waszkiewicz-Robak Bożena
Published: January 2025

The aim of this study was to determine the influence of the nut roasting process (conventional and microwave methods) and long-term storage (12 months) on phytosterol content and stability. This study was conducted using hazelnuts (Corylus avellana), common walnuts (Juglans regia L.), and shelled peanuts (Arachis hypogaea L.). Two roasting methods were examined: conventional (temp. 170 °C, roasting time 10–20 min.) and microwave (temp. 60 °C, pressure 40 hPa, roasting time 140–180 s). In the studied nuts (raw, roasted and stored), five main types of phytosterols were identified: campesterol, stigmasterol, ß-sitosterol, delta 5-avenasterol and cycloartenol. It was shown that the microwave roasting method caused a two-fold decrease in sterol loss compared with conventional roasting. Moreover, the long-term storage of roasted walnuts using the microwave method showed double the amount of sterols preserved compared with those roasted using the conventional method. The amount of ß-sitosterol, which was the most stable during roasting, depended more on storage duration than on roasting process. The cycloartenol content in the roasted nuts did not depend on storage duration. The sterols present in nuts, raw or roasted using either method, transform more during the first 6 months of storage.
Chemical Analyses and Therapeutic Properties of Plant Extracts
Authors: Opara Elizabeth I. , White Kenneth N. , Uvere Peter Orji
Published: January 2025

It has been almost 20 years since the World Health Organization (WHO) established the International Regulatory Co-operation for Herbal Medicines (IRCH), as part of a WHO Traditional Medicine Strategy [...]
Chemical Bonding in Three-Membered Ring Systems
Authors: Strasser Nina , Sax Alexander F.
Published: January 2025

The formation of the four 3-ring systems c-(CH2)3−k(SiH2)k (k=0: cyclopropane, k=1: silirane, k=2: disilirane, k=3: cyclotrisilane) by addition of methylene and silylene to the double bond in ethene, disilene, and silaethene, as well as the elimination of the carbene analogs from the 3-rings, was studied with CAS(4,4) wave functions in both C2v and Cs symmetry. To reveal the charge and spin redistribution during these reactions the CAS(4,4) wave functions were analyzed using the orthogonal valence bond method (OVB). The potential energy curves, different internal coordinates, and the results of the OVB analysis show that, frequently, the addition and elimination reactions follow different minimum energy paths, because they are indeed diabatic reactions. In these cases, there are no energy barriers corresponding to saddle points on the potential energy surfaces but the energy increases during one diabatic reaction until, at a certain point, the system jumps to the other diabatic state and, in the following, the energy decreases. This happens for reactions in C2v symmetry; as soon as the system can change to the lower symmetry, the diabatic states combine to an adiabatic one and the reaction follows a single minimum energy path.
Edible Coatings for Ready-to-Eat Products: Critical Review of Recent Studies, Sustainable Packaging Perspectives, Challenges and Emerging Trends
Authors: Bremenkamp Ina , Sousa Gallagher Maria José
Published: January 2025

If edible coatings are proven to control deterioration reactions by preventing chemical reactions, why aren’t they more widely used in industry applications, especially in the ready-to-eat food sector? This sector is a growing and emerging market and is interesting to diverse consumer groups. The potential of edible coatings as an innovative approach for more eco-friendly packaging systems should be further investigated. This article reviews the state-of-the-art developments of edible coatings for chilled RTE (ready-to-eat) food products as an area of growing interest and innovation, with a focus on sustainability, functionality, and costs. It discusses challenges associated with the use of edible coatings as eco-friendly packaging system in RTE food sector, including compatibility with food products, processing, shelf-life, storage conditions, cost, and regulatory requirements, and emerging trends, including biodegradable and eco-friendly coatings, shelf-life extension, active and intelligent coatings, and customization and personalization opportunities. Overall, while edible coatings offer many potential benefits in the RTE food sector, there are several challenges that must be addressed to ensure their successful implementation. Research and development efforts are needed to optimize the performance and stability of coatings while ensuring compliance with regulatory requirements and addressing cost concerns. The potential of edible coatings as eco-friendly packaging system should be further studied to highlight the full potential of edible coatings.
Real-Time Turning Movement, Queue Length, and Traffic Density Estimation and Prediction Using Vehicle Trajectory and Stationary Sensor Data
Authors: Shafik Amr K. , Rakha Hesham A.
Published: January 2025

This paper introduces a two-stage adaptive Kalman filter algorithm to estimate and predict traffic states required for real-time traffic signal control. Leveraging probe vehicle trajectory and upstream detector data, turning movement (TM) counts in the vicinity of signalized intersections are estimated in the first stage, while the upstream approach density and queue sizes are estimated in the second stage. The proposed approach is evaluated using drone-collected and simulated data from a four-legged signalized intersection in Orlando, Florida. The performance of the two-stage approach is quantified relative to the baseline estimation without a Kalman filter. The results show that the Kalman filter is effective in enhancing traffic state estimates at various market penetration levels, where the filter both improves the estimation accuracy over the baseline case and provides reliable state predictions. In the first stage, the standard deviation (SD) in TM estimates improves by up to 50% compared to the estimates provided by the sole use of probe vehicle headings. The proposed approach also provides predictions with a minimal SD of 92.8 veh/h at a 5% level of market penetration. In the second stage, the proposed queue size estimation method results in an enhancement to the queue size estimation of up to 32.8% compared to the estimates obtained from the baseline approach. In addition, the estimated traffic density is enhanced by up to 18.5%. The proposed two-stage approach demonstrates the capability of providing reliable turning movement predictions across varying levels of market penetration. This highlights the readiness of this approach for practical application in real-time traffic signal control systems.
Robust Distribution-Aware Ensemble Learning for Multi-Sensor Systems
Authors: Goodarzi Payman , Schauer Julian , Schütze Andreas
Published: January 2025

Detecting distribution and domain shifts is critical in decision-sensitive applications, such as industrial monitoring systems. This paper introduces a novel, robust multi-sensor ensemble framework that integrates principles of automated machine learning (AutoML) to address the challenges of domain shifts and variability in sensor data. By leveraging diverse model architectures, hyperparameters (HPs), and decision aggregation strategies, the proposed framework enhances adaptability to unnoticed distribution shifts. The method effectively handles tasks with various data properties, such as the number of sensors, data length, and information domains. Additionally, the integration of HP optimization and model selection significantly reduces the training cost of ensemble models. Extensive evaluations on five publicly available datasets demonstrate the effectiveness of the proposed framework in both targeted supervised tasks and unsupervised distribution shift detection. The proposed method significantly improves common evaluation metrics compared to single-model baselines. Across the selected datasets, the framework achieves near-perfect test accuracy for classification tasks, leveraging the AutoML approach. Additionally, it effectively identifies distribution shifts in the same scenarios, with an average AUROC of 90% and an FPR95 of 20%. This study represents a practical step toward a distribution-aware front-end approach for addressing challenges in industrial applications under real-world scenarios using AutoML, highlighting the novelty of the method.
Post-Wildfire Mobilization of Organic Carbon
Authors: Numan Travis , Lokesh Srinidhi , Shahriar Abrar , Timilsina Anil , Lard Myron L. , Clark Justin , Raeofy Yasaman , Zhao Qian , Poulson Simon R. , Verburg Paul S. , Richardson Jocelyn A. , Cook Robert L. , Samburova Vera , Yang Yu
Published: January 2025

Wildfires significantly alter watershed functions, particularly the mobilization of organic carbon (OC). This study investigated OC mobility and the physicochemical characteristics of wildfire-impacted soils and ashes from the northern California and Nevada fires (Dixie, Beckworth, Caldor). Organic carbon in wildfire-derived ashes (9.2–57.3 mg/g) generally exceeded levels in the background soils (4.3–24.4 mg/g), except at the Dixie fire sites. The mobile OC fraction varied from 0.0093 to 0.029 in ashes and 0.010 to 0.065 in soils, though no consistent trend was observed between the ashes and soils. Notably, the ash samples displayed lower OC mobility compared with the soils beneath them. A negative correlation was found between the mobile OC fraction and bulk OC content. Wildfire increased the total amount of mobile OC substantially by 5.2–574% compared to the background soils. Electron paramagnetic resonance (EPR) spectra confirmed the presence of environmentally persistent free radicals (EPFRs), which correlated with observed redox reactivity. Additionally, X-ray absorption near edge structure (XANES) and X-ray fluorescence (XRF) imaging revealed that Fe(II) oxidation in soils beneath the ashes may have enhanced the OC mobility, likely driven by pyrogenic carbon and free radicals. These findings enhance our understanding of post-wildfire OC mobilization and the impact of ash–soil physicochemical properties on watershed health.
Artificial Intelligence and the Energy Transition
Authors: Kyriakarakos George
Published: January 2025

In recent years, the energy sector has entered a decisive phase of transformation, driven by mounting concerns regarding climate change and the recognized need to transition toward sustainable energy systems [...]
Evolutionary Mechanisms of the Emergence of the Variants of Concern of SARS-CoV-2
Authors: Rouzine Igor M.
Published: January 2025

The evolutionary origin of the variants of concern (VOCs) of SARS-CoV-2, characterized by a large number of new substitutions and strong changes in virulence and transmission rate, is intensely debated. The leading explanation in the literature is a chronic infection in immunocompromised individuals, where the virus evolves before returning into the main population. The present article reviews less-investigated hypotheses of VOC emergence with transmission between acutely infected hosts, with a focus on the mathematical models of stochastic evolution that have proved to be useful for other viruses, such as HIV and influenza virus. The central message is that understanding the acting factors of VOC evolution requires the framework of stochastic multi-locus evolution models, and that alternative hypotheses can be effectively verified by fitting results of computer simulation to empirical data.