bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel Mechanisms of Dodecyldimethylbenzalkonium Chloride in Antiviral
Authors: Igarashi Chisato , Kubo Shun , Hayase Atsuko , Mori Takuya , Nonomura Yoshimune , Sakai Takaya 
Published: November 2024

Abstract

The cationic surfactant, alkyldimetylbenzalkonium chloride (BAC), effectively inactivates enveloped viruses, but the underlying mechanism of action is poorly understood1. Therefore, this study attempted to elucidate the inactivation mechanism of BAC using actual viruses and characterize the state of BAC in water under the same conditions. Here, we show that at concentrations below the critical micelle concentration (CMC), partial membrane disruption by BAC monomers contributes to the inactivation mechanism. At concentrations above the CMC, solubilization of the envelope component also contributes to virus inactivation. Concentration-related differences in the inactivation mechanism were further evaluated based on the kinetic equation of the reaction, which showed that physicochemical studies are directly related to biochemistry. As enveloped viruses can be viewed as vesicles based on their structure2, the results of this study should enhance investigations of non-virus biological vesicles, such as exosomes and drug delivery systems3, 4, 5.
Seismic Hazard Assessment of the San Ramón Fault in Santiago, Chile
Authors: Dominguez Horacio , Heresi Pablo , Montalva Gonzalo 
Published: November 2024

Abstract

The Chilean seismic activity consists mainly of interface and inslab earthquakes caused by the subduction of the Nazca Plate beneath the South American Plate. Nonetheless, several shallow crust faults also contribute to the seismic hazard in the country. An example of such faults is the San Ramón Fault (SRF), an active shallow crust system located at the eastern border of Santiago, whose seismic activity has recently been discovered. The SRF has an average slip rate of 0.4 mm/year, and it has the potential to generate earthquakes with magnitudes up to [[EQUATION]]. Although previous studies have examined the seismic hazard posed by the fault, a probabilistic approach has not been undertaken. This research compares the seismic hazard posed by the subduction zone with that generated by the SRF in Santiago, using state-of-the-art models that represent their geometry and seismicity. We compute seismic hazard maps employing deterministic and probabilistic approaches to assess the influence of the SRF on the study zone. Resulting hazard maps from a deterministic analysis present areas where the intensities caused by an earthquake on the SRF are over three times greater than those from interface and inslab events. However, under a probabilistic approach, the hazard of the SRF is less than 3% that of the subduction zone, attributed to the fault's large return period. Finally, our results indicate that the influence of the SRF on Santiago's seismic hazard strongly depends on the intensity measure considered.
Large impacts of wildfires on soil thermal, hydrological and carbon dynamics in northern Eurasian forests from 2003 to 2016
Authors: Xu Yiming , Zhuang Qianlai , Zhao Bailu , Billmire Michael , Cook Christopher , Graham Jeremy , French Nancy HF , Prinn Ronald 
Published: November 2024

Abstract

We use a process-based biogeochemistry model to simulate the fire impacts on soil thermal and hydrological dynamics and carbon budget of forest ecosystems in Northern Eurasia during 2003–2016 based on satellite-derived burn severity data. We find that burn severity generally increases in this region during the study period. Simulations indicate that fires increase soil temperature by 0.2–0.5°C through removing the ground moss and surface soil organic matter, especially in Asian part of the region. Fires also increase water runoff by about 37 km3 yr− 1 through reducing post-fire evapotranspiration, leading to a higher regional river discharge. Fires remove 1.7 Pg C of ecosystem carbon through combustion emissions during this period and reduce net ecosystem production from 106.4 to 66.1 Tg C yr− 1. Fires lead the forest ecosystems to lose 2.3 Pg C, shifting the forests from a carbon sink to a source in this period. Our study highlights the importance of wildfires in affecting soil thermal and hydrological and carbon dynamics in boreal forests.
Amelioration of the Rheumatoid Arthritis Microenvironment Using Celastrol-Loaded Silver-Modified Ceria Nanoparticles for Enhanced Treatment
Authors: Zhang Xiaoru , Fu Xiaguo , Chen Wanying , Kang Xuejia , Chen Peng , Bo Yang , Liang Jianming , Zeng Feng 
Published: November 2024

Abstract

Rheumatoid arthritis (RA) is characterized by elevated levels of reactive oxygen species (ROS) and a persistent inflammatory microenvironment dominated by pro-inflammatory M1 macrophages, both of which contribute to disease progression. To address these pathological features, we developed a core-shell nanoplatform consisting of silver-modified ceria nanoparticles (Ag-CeNP-PEG) loaded with celastrol (Cel), termed Ag-CeNP@Cel. This nanoplatform significantly enhances the water solubility of Cel and reduces its hepato-renal toxicity by enabling passive accumulation in inflamed joints through the extravasation through leaky vasculature and subsequent inflammatory cell-mediated sequestration (ELVIS) effect. The Ag-CeNP-PEG platform synergistically combines with Cel to scavenge excess ROS and reprogram pro-inflammatory M1 macrophages into anti-inflammatory M2 macrophages, thereby mitigating inflammatory responses and improving the rheumatoid arthritis microenvironment (RAM). Ag-CeNP@Cel exhibited robust therapeutic efficacy and safety in preclinical models, presenting an innovative approach to RA treatment by integrating ROS elimination with macrophage modulation to ameliorate inflammatory microenvironment. This study underscores the potential of Ag-CeNP@Cel as a promising therapeutic strategy for RA management.
Real-time traffic light detection based on lightweight improved RT-DETR
Authors: Tang Chaoli , Li Yun , Wang Lei , Li Wenyan 
Published: November 2024

Abstract

Traffic light detection demands high real-time performance and a lightweight design, existing methods often encounter issues such as detection delays and limited computational resources. Therefore, reducing computational overhead and increasing detection speed, while maintaining accuracy, becomes a critical challenge. To tackle these, this paper proposes GAD-DETR, an enhanced RT-DETR-based network. First, inspired by the approach of GhostNet to minimize computational redundancy and integrate reparameterized convolution (RepConv), the GRELAN module is developed to restructure the backbone network which significantly decreases model size and parameters while enhancing detection speed. To improve the recognition of small objects, whose features tend to be diluted as the network deepens, ADown is introduced to replace standard convolution for downsampling, enhancing small-object detection capability. Finally, a lightweight feature fusion module, DGSFM, is designed to further reduce computational costs and enhance efficiency. Experimental results indicate that GAD-DETR achieves a detection precision of 95.9%, with a model size reduction of 50.3%, and parameter and computation reductions of 50.8% and 51.2%, respectively. FPS increases from 76.7 to 117.8, demonstrating that the proposed algorithm achieves lightweight, real-time traffic light detection.
Factors of Staying in Abusive Emotional Relationships of Iranian Girls: A Qualitative Study
Authors: Ghasemi Farzane , Namdarpour Fahimeh , Gorji Yousef 
Published: November 2024

Abstract

Background
Emotional relationships constitute an important part of the lives of most young people and can be important aspects of identity, a source of intimacy, emotional security, and social status for them. However, these relationships may sometimes lead to traumatic relationships and debilitating symptoms. Despite the unpleasantness of these relationships, some girls cannot leave such relationships. Therefore, the present study aimed to investigate the factors that cause Iranian female students to remain in abusive emotional relationships.
Methods
This research was conducted via the content analysis method. The participants were 9 Iranian girls aged 20–30 years and 10 counselors and psychologists, and the sampling was purposeful. The interviews were conducted in person and recorded. Then, they were transcribed verbatim, and the data were named in semantic units that were similar to each other under a subcategory. Finally, several subcategories were placed in a main category that has a higher degree of abstraction and is called the theme. To validate the findings, the Lincoln and Guba method was used, and for a more in-depth examination, the categories were examined via MaxQuda software version 2020.
Results
The results of the interviews led to the emergence of three main categories and seven subcategories: family factors (strict and permissive parenting, the clinical symptoms of parents, and the ability to reconstruct relationships with parents), individual factors (attachment-related needs and identity confusion) and social factors (peer pressure).
Conclusions
in general, a lack of psychological security in the family, excessive strictness, and neglect of emotional needs, whether real or perceived, and social pressures can affect abusive emotional relationships. Therefore, it is necessary to prioritize the implementation of supportive, educational, and counseling programs to prevent and reduce harm in educational centers, counseling centers, and the mental health policy system.
Khayyam Offline Persian Handwriting Dataset
Authors: Jafarzadeh Pourya , Choobdar Padideh , Safarzadeh Vahid Mohammadi 
Published: November 2024

Abstract

Handwriting analysis is still an important application in machine learning. A basic requirement for any handwriting recognition application is the availability of comprehensive datasets. Standard labelled datasets play a significant role in training and evaluating learning algorithms. In this paper, we present the Khayyam dataset as another large unconstrained handwriting dataset for elements (words, sentences, letters, digits) of the Persian language. We intentionally concentrated on collecting Persian word samples which are rare in the currently available datasets. Khayyam's dataset contains 44000 words, 60000 letters, and 6000 digits. Moreover, the forms were filled out by 400 native Persian writers. To show the applicability of the dataset, machine learning algorithms are trained on the digits, letters, and word data and results are reported. This dataset is available for research and academic use.
ECDet: Efficient oriented object detection on the aerial imagewith cross-layer attention
Authors: Lyu Xueqiang , Tian Lianghai , Teng Shangzhi 
Published: November 2024

Abstract

With advancements in horizontal object detection models, oriented object detection models have also made significant strides. Yet existing rotated object detectors often struggle to maintain high accuracy while processing high-resolution remote sensing images in real-time. To address these challenges, we propose a new lightweight model specifically for oriented object detection, named the Efficient Cross-layer attention Detector (ECDet). ECDet integrates several efficient modules, including an Efficient Reparameterized Transformer-like backbone (ERepViT) to reduce computational costs, and the Efficient Cross-Layer Fusion Neck (CLF-Neck), a lightweight alternative to traditional pyramid networks for feature fusion with attention mechanism. Additionally, we introduce the Lightweight Task Interaction Decoupled (LTID) head, which enhances task-specific performance by providing more detailed, task-aligned information for classification and regression with minimal computational cost. Furthermore, an ensemble loss combined with the Phase Shifting Coder (PSC) mitigates the angle discontinuity issue in regression-based methods. Evaluations on the DOTA and HRSC datasets show that ECDet runs 32% faster than RTMDet-S with higher accuracy, demonstrating its strong potential for practical application.
Character Recognition for Greek Squeezes
Authors: Howe Nicholas R. , Chang Feiran , Falbo Isabella , Brown Tajhini , Hershkowitz Aaron 
Published: November 2024

Abstract

Squeezes are three-dimensional paper impressions made of stone inscriptions, which have to date received relatively less study than many other forms of historical documents. This paper reports on experiments in text recognition, working with a collection of approximately 30,000 squeezes originally collected from museums and archaeological sites in classical Greece. It explores a number of complementary strategies for character recognition in this medium, with the aim of establishing a strong benchmark in performance. Of the methods studied here, the best achieves a character error rate of 14%.
Aircraft responses to volcanic ash advisories during volcanic eruptions
Authors: DELBREL Juliette , BURTON Mike , ENGWELL Samantha , ESSE Benjamin , HAYER Catherine 
Published: November 2024

Abstract

Volcanic eruptions can inject ash into the atmosphere, which is then advected by meteorological winds, potentially affecting large volumes of airspace. Volcanic Ash Advisory Centres (VAACs) issue volcanic ash advisories (VAAs) when an airspace is likely to contain ash above a concentration threshold. Much research has been done to improve operational ash forecasts of volcanic ash location in the atmosphere, but until now behaviour of aircraft around erupting volcanoes and those for which VAAs have been issued, and the impact these responses have on flight schedules and diverted aircraft’s fuel consumption, has not been closely examined. Here, we investigate real-world responses by commercial aircraft to volcanic activity as reported in VAAs, using publicly available flight trajectory data during several ash-rich eruptions in periods of heightened eruptive activity in 2022 and 2023 at Etna, Sakurajima, Marapi, Sheveluch, Klyuchevskoy and Ubinas volcanoes. We examine a range of geographic locations and eruption sizes. Flight trajectories during periods when VAAs were active are compared with flight trajectories during normal, ash-free periods. We find that aircraft adopt a range of strategies to avoid ash, largely avoiding the indicated air space affected by ash. We also find that, in general, by avoiding ash aircraft also avoided volcanic SO2 plumes. Our results confirm that the greater the volume of air affected by volcanic ash the greater the deviation of aircraft from their typical flight paths. Rerouted aircraft may travel significantly further distances to avoid ash, which results in longer air travel time and delays, suggesting greater fuel consumption and carbon emissions. Further long-term systematic studies of the impact of volcanic eruptions on flight routes and timing would be helpful in determining the amount of ash-related aircraft disruption, as air traffic is likely to grow in the coming years, and VAAC advisory strategies also evolve.
A Scalable Machine Learning Strategy for Resource Allocation Database
Authors: Manhary Fady Nashat , Mohamed Marghny H , Farouk Mamdouh 
Published: November 2024

Abstract

Efficiently responding to dynamic application demands in cloud environments is crucial for meeting service level agreements (SLAs) and optimizing resource costs. Traditional auto-scaling approaches often struggle with predefined rules, making it challenging to devise optimal adaptation strategies. This paper introduces a proactive strategy that leverages the robust capabilities of long short-term memory (LSTM) for precise request prediction, complemented by the intelligent decision-making power of multi-agent reinforcement learning (MARL) to determine optimal actions for scaling virtual machines.
In this proposed methodology, the LSTM accurately predicts the number of requests in the next time step, effectively adapting to dynamic traffic changes. The integration of MARL enhances the adaptability and efficiency of the auto-scaling process by enabling virtual machines to make informed decisions based on real time states.
This study asserts that applying MARL as a fundamental component of the auto-scaling strategy is a promising and effective solution. The synergy between LSTM and MARL based Ape-X not only enhances predictive accuracy but also empowers virtual machines to make proactive decisions, making it a valuable approach for meeting SLAs and optimizing resource utilization in dynamic cloud environments.
Data-Driven De Novo Design of Super-Adhesive Hydrogels
Authors: Gong Jian Ping , Liao Hongguang , Hu Sheng , Yang Hu , Wang Lei , Tanaka Shinya , Takigawa Ichigaku , Li Wei , Fan Hailong 
Published: November 2024

Abstract

Data-driven methodologies have revolutionized the discovery and prediction of new hard materials, such as crystal structures and high-entropy alloys1-5. However, their application to soft materials remains challenging due to the inherent complexity of their structure–property relationships6-8. Here, we present a comprehensive data-driven approach that integrates data mining, experimentation, and machine learning to develop high-performance adhesive hydrogels from scratch, tailored for demanding underwater environments. By leveraging protein databases, we devised a descriptor strategy to statistically replicate protein sequence patterns via ideal random copolymerization, enabling targeted hydrogel design and dataset construction. Using machine learning, we optimized hydrogel formulations even with a small dataset, achieving unprecedented adhesive performance. These super-adhesive hydrogels demonstrate immense potential across diverse applications, from biomedical engineering to deep-sea exploration, marking a significant advancement in the data-driven innovation for soft materials.
The prevalence and risk factors of upper gastrointestinal problems: An analysis from the perspective of community pharmacies
Authors: Venugopal Jayalakshmi , Govindaswamy Swathy , Karnan Deepika , Dhilipkumar S. 
Published: November 2024

Abstract

Background: Community pharmacists are often the first choice for individuals seeking advice with upper gastrointestinal issues since they are easily accessible. However, it is essential to highlight that most nations do not have "triage" systems that allow community pharmacists to help patients with gastrointestinal issues. One reason for this is the need for more available patient pharmacoepidemiologic data.
Aim and Objectives: This study investigated the prevalence, clinical characteristics, risk factors, and symptoms of patients with upper gastrointestinal problems who visit community pharmacists for medical advice or to obtain OTC medication.
Materials and Methods: This observational study, which included 731 participants, was carried out over six months at 12 randomly chosen community pharmacies in southern India. Data on the participants' sociodemographic and clinical characteristics were gathered and examined using IBM SPSS software version 29.0.
Results: A total of 731 patients participated in the research. The mean age was 36.0±13.7 years with male predominance (54.9%). The mean BMI was 20.8±4.4 kg/m2. Coffee was the most commonly consumed beverage (22.3%). Of the participants, 64% had been experiencing symptoms for the previous three months. Of them, 76.3% did not seek medical guidance to treat the symptoms. Heartburn, reported by 40.2% of participants, is the most prevalent symptom. The overall prevalence of UGI problems was 8.3%.
Conclusion: The study's results highlight the significance of dietary and lifestyle changes as common risk factors for UGI symptoms, particularly for younger people who often use community pharmacies. Since community pharmacists are directly involved in treating UGI symptoms, it is essential to integrate regular training for them and harmonize their professional guiding approach. These findings can inform healthcare practices and improve patient management of UGI symptoms, potentially reducing the burden on the healthcare system.
ЗНАЧЕНИЕ КЕЛЬНСКОГО ПРОИСХОЖДЕНИЯВ СТАНОВЛЕНИИ ВНЕШНЕПОЛИТИЧЕСКИХВЗГЛЯДОВ КАНЦЛЕРА АДЕНАУЭРА
Authors:  А.  Сорокин 
Published: November 2024

В статье рассматривается проблема влияния кёльнского происхождения на внешнюю политику Аденауэра. Определяется значение данного фактора для западной интеграции, антисоветского курса, германского вопроса.
The article considers the problem of the Cologne origin influence on Adenauer's foreign policy. The value of this factor for the western integration, an anti-Soviet course, the German question is defined.
«ЛОВУШКА» НА ПУТИ ИЗУЧЕНИЯ РАННЕГО ЭТНОГЕНЕЗА МОЛДАВАН: ПО СЛЕДАМ ИССЛЕДОВАНИЙ СОВЕТСКИХ УЧЕНЫХ
Authors: М.Ц. АРЗАКАНЯН , А.А. ГЕРЦЕН , Е.Г. ПАСКАРЬ 
Published: November 2024

Статья посвящена проблеме изучения раннего этногенеза молдаван. Авторы показывают, какую лепту в историографию вопроса в свое время внесли труды советских исследователей — историков, этнографов, археологов, лингвистов, работавших в Кишинёве и в Москве.
The article is devoted to the problem of studying the early ethnogenesis of Moldavians. The authors show what contribution to the historiography of the issue at the time was made by the works of Soviet researchers — historians, ethnographers, archaeologists, linguists who worked in Kishinev and Moscow.
РИМЛЯНЕ И ПРОВИНЦИАЛЫ: ПРОБЛЕМА ОТВЕТСТВЕННОСТИ ЗА ТЕХ, КОГО ПОКОРИЛИ
Authors: В.О. НИКИШИН 
Published: November 2024

Статья посвящена теме взаимодействия Рима и провинций в период Поздней республики. В частности, автор рассматривает вопросы управления и коррупции. Материал источников убеждает нас в том, что управление провинциями в конце эпохи Республики было не столько государственным, сколько частным делом представителей римской правящей элиты, наделённых, в сущности, неограниченными властными полномочиями. Такая ситуация порождала, с одной стороны, практически полное бесправие провинциалов, а с другой — разнообразные злоупотребления, произвол и беззакония со стороны римских должностных лиц и публиканов. Главная проблема в отношениях Рима с провинциями заключалась в отсутствии чувства ответственности за судьбы покорённых народов. Это чувство появилось у римской правящей элиты лишь в самом конце эпохи Республики.
This article is devoted to the theme of interaction between Rome and provinces during the period of the Late Republic. Particularly the author considers issues of government and corruption. The material of our historical sources convinces us that the provincial government in the end of the epoch of the Republic was not so much public case as private one, which was realized by the representatives of the Roman ruling class, who in fact were endowed by unlimited powers. Such situation generated, on the one hand, practically absolute powerlessness of provincials and different abusements, arbitrariness and lawlessness, which were made by the Roman officials and publicans, on the other. The main problem in the sphere of relations between Rome and its provinces was rooted in the absence of the sense of responsibility for the fates of conquered peoples. Such a sense emerged inside the Roman ruling class only in the very end of the epoch of the Republic.