bluuebunny/crossref_metadata_2025_split huggingface dataset:
The deterministic behaviour of earthquake rupture beginning
Authors: Colombelli Simona , Longobardi Valeria , Zollo Aldo 
Published: February 2024

Abstract
Earthquakes are among the most destructive natural hazards. The energy released by an earthquake can be quantified by its magnitude. However, predicting how much energy the earthquake will release before the end of its rupture process represents a challenging question in geohazards. The way earthquake ruptures grow and arrest determines the final event size: small-to-moderate ruptures evolve in few seconds with typical lengths of few kilometers, while large-to-huge events develop in tens of seconds or more, involving lengths of several hundred kilometers. If the rupture process starts in the same way for small and large earthquakes, no deterministic prediction of the final size is feasible, until the process has finished. On the contrary, if the source mechanism starts differently from its early beginning, real-time proxies can be measured on seismic waves to discriminate the final event size. Here we show that the initial ground displacement growth is differently for small and large earthquakes, based on the analysis of an unprecedented catalog of seismic waveforms from worldwide earthquakes. The result supports the hypothesis of early predictable event magnitude for a wide range of different size earthquakes in diverse geological settings. This study confirms that the measure of the initial growth of displacement can be used as a parameter for a fast magnitude estimation, making it feasible for future implementation in early warning systems.
Recurrent herbicide applications on wheat: impact on productivity, weed dynamics, and nutrient depletion
Authors: Shah Maksud Hasan , Islam Md Mazharul , Mandal Bikas , Mukherjee Dhiman , Garai Sandip , Jewel Zilhas Ahmed , Rahman Md. Saidur 
Published: February 2024

Abstract
Wheat fields with weeds are known to contribute significantly to nutrient depletion, which lowers grain yield and quality. Given the unpredictable affects of these intricate and dynamic mixes, the use of herbicide combos and successive applications poses challenges to current standards aimed at maintaining ecosystem health. Thus, a two-year field experiment was carried out with a focus on soil health in a mesocosm experiment to identify the best herbicides to control weeds and assess the phytotoxic effects of herbicide mixtures while adhering to a feasible application timeline for wheat production. In a randomized block design with four replications, this study includes nine treatments. Plots treated with pendimethalin 30% EC at 1.0 kg/ha and metribuzin 70% WP at 0.2 kg/ha demonstrated significantly reduced weed uptake of potassium (K), phosphorus (P), and nitrogen (N). This finding was statistically identical to plots treated with sulfosulfuron 75% + metsulfuron 5% WG at 32 g/ha and pendimethalin 30% EC at 1.0 kg/ha, resulting in manual weeding at 30 days after sowing (DAS). In addition, pendimethalin and metribuzin prove effective to control weeds, yet they exhibited great efficacy in increasing wheat grain and straw yields. Treatments with pendimethalin, metribuzin, and sulfosulfuron + metsulfuron revealed substantial increases in the concentrations of N, P, and K in wheat grains. As a result, wheat growers need to exercise caution whenever it comes to the phytotoxic effects and environmental ramifications of herbicides. As consequently, sulfosulfuron 75% + metsulfu-ron 5% WG at 32g/ha proved to be an effective and environmentally friendly choice that boosted both productivity and quality.
Limited net poleward movement amongst Australian reef species over a decade of climate extremes.
Authors: Fuchs Yann Herrera , Edgar Graham , Bates Amanda , Waldock Conor , Smith Rick Stuart 
Published: February 2024

Abstract

Warming seas are expected to drive marine life poleward. However, few systematic observations can confirm movement among entire communities at both warm and cool range edges. We analysed two continent-scale reef monitoring datasets to quantify changes in latitudinal range edges of 662 Australian shallow-water reef fishes and invertebrates over a decade punctuated by climate extremes. Temperate and tropical species both showed little net movement overall, with retreat often balancing expansion across the continent. Within regions, however, range edges shifted ~100 km per decade, on average, in the poleward or equatorward directions expected from warming or cooling seas following climate extremes. While some species responded rapidly to temperature change, we found little evidence for mass poleward drift. Previous studies based on extreme observations, rather than tracking all species through time, may have over-estimated the prevalence, magnitude and longevity of range shifts amongst marine taxa.
Applications of LLMs for Generating Cyber Security Exercise Scenarios
Authors: Yamin Muhammad Mudassar , Hashmi Ehtesham , Ullah Mohib , Katt Basel 
Published: February 2024

Abstract

This study proposes a novel approach leveraging Large Language Models (LLMs) to generate dynamic and complex adaptable cybersecu-rity exercise scenarios. Motivated by Turing’s sem-inal exploration into machine cognition, which questions the ability of machines to mimic human thought and intelligence. By exploiting the generative potential of LLMs, our methodology simulates a wide range of cyber threats, both known and novel, thereby enhancing cybersecurity training and awareness. This approach transforms the potential for ’hal-lucination’ inherent in LLMs into a potential advantage , enabling the creation of complex exercise scenarios that push the boundaries of traditional cybersecurity training. The innovation lies in the sophisticated application of AI, aiming to advance the preparedness of security professionals against diverse cyber threats. The scenarios generated through this method were subject to meticulous testing and a rigorous evaluation process involving GPT models and expert review to ensure their realism and applicability. Furthermore, the prompts provided to the LLMs were meticulously designed to adopt a Retrieval-Augmented Generation (RAG) approach, enriching the complexity and relevance of the scenarios. This incorporation of RAG, alongside the inspiration drawn from Tur-ing’s exploration of machine intelligence, showcases an advanced application of AI in cybersecurity training , reflecting a deep understanding of how machines can augment our capabilities to anticipate and mitigate cyber threats.
Impact of the COVID-19 pandemic on depressive disorder among young adults in the United States: Analysis of the Behavioral Risk Factor Surveillance System data, 2018-2022
Authors: Chowdhury Suman Kanti , Mansuri Fahad , Xing Zailing , Beltrame Anna , Chandra Kanika , Kirby Russell S. 
Published: February 2024

Abstract

Purpose: Depressive disorder during early adulthood has been a rising public health concern, potentially further compounded by the COVID-19 pandemic. Using nationally representative large survey samples, this study addressed the knowledge gaps in how COVID-19 affected depressive disorder among U.S. young adults.
Methods: The analysis included 348,994 U.S. non-institutionalized young adults aged 18-34 years from the Behavioral Risk Factor Surveillance System for 2018-2022. Changes in the prevalence of diagnosed depressive disorder before and during COVID-19 were assessed by weighted bi-variate analysis using Rao-Scott Chi-Square test, with multivariable logistic regression models fitted to assess the magnitude of depressive disorder before and during COVID-19.
Results: Overall, the prevalence of depressive disorder increased by 13.7% (p<0.001) from 20.5% before COVID-19 to 23.3% during COVID-19. Adjusted for sociodemographic and lifestyle factors, the odds of depressive disorder during COVID-19 as compared to before COVID-19 were highest for females (OR: 1.35, 95% CI: 1.29-1.40), aged 18-24 years (OR: 1.34, 95% CI: 1.27-1.41), other races (OR: 1.46, 95% CI: 1.31-1.62), attended college or technical school (OR: 1.33, 95% CI: 1.26-1.40), employed (OR: 1.32, 95% CI: 1.27-1.37), and married (OR: 1.32, 95% CI: 1.24-1.40).
Conclusion: The study findings revealed the importance of recognizing and understanding the most affected groups of young adults during a pandemic like COVID-19, providing essential insights for developing targeted interventions and policies.
Conversion Chemoradiotherapy Combined with nab-paclitaxel plus Cisplatin in Patients with Locally Advanced Borderline-Resectable or Unresectable Esophageal Squamous Cell Carcinoma: a Phase Ⅰ/Ⅱ Prospective Cohort Study
Authors: Yu Nuo , Chen Xiankai , Li Jiao , Kang Xiaozheng , Wang Zhen , Zhang Ruixiang , Qin Jianjun , Li Yong , Zheng Qingfeng , Feng Guojie , Deng Lei , Zhang Tao , Wang Wenqing , Liu Wenyang , Wang Jianyang , Feng Qinfu , Lv Jima , Zhou Zongmei , Xiao Zefen , Bi Nan , Li Yin , Wang Xin 
Published: February 2024

Abstract

Background: To evaluate the efficacy and safety of nab-paclitaxel plus cisplatin as the regimen of conversional chemoradiotherapy (cCRT) in locally advanced borderline resectable or unresectable esophageal squamous cell carcinoma (ESCC).
Methods: Patients with locally advanced ESCC (cT3-4, Nany, M0-1, M1 was limited to lymph node metastasis in the supraclavicular area) were enrolled. All the patients received the cCRT of nab-paclitaxel plus cisplatin. After the cCRT, those resectable patients received esophagectomy; those unresectable patients continued to receive the definitive chemoradiotherapy (dCRT). The locoregional control (LRC), overall survival (OS), event-free survival (EFS), distant metastasis free survival (DMFS), pathological complete response (pCR), R0 resection rate, adverse events (AEs) and postoperative complications were calculated.
Results: 45 patients with ESCC treated from October 2019 to May 2021 were finally included. The median follow-up time was 30.3 months. The LRC, OS, EFS, DMFS at 1and 2 years were 81.5%, 86.6%, 64.3%, 73.2% and 72.4%, 68.8%, 44.8%, 52.7% respectively. 21 patients (46.7%) received conversional chemoradiotherapy plus surgery (cCRT+S). The pCR rate and R0 resection rate were 47.6% and 84.0%. The LRC rate at 1 and 2 years were 95.0%, 87.1% in cCRT+S patitents and 69.3%, 58.7% in dCRT patients respectively (HR, 5.14; 95%CI, 1.10-23.94; P = 0.021). The toxicities during chemoradiotherapy were tolerated, and the most common grade 3-4 toxicitiy was radiation esophagitis (15.6%). The most common postoperative complication was pleural effusion (38.1%) and no grade ≥ Ⅲb complications were observed.
Conclusion: nab-paclitaxel plus cisplatin are safe as the regimen of conversional chemoradiotherapy of ESCC.
Trial registration number: NCT04278287
Trial registration date: 2020-2-20
RETRACTED: Ultrasound-Assisted Synthesis of Novel 4-Oxo-Chromen-Dihydropyridine Derivatives by a One-Pot Fusion and Multicomponent Reaction under Environmentally Friendly Conditions
Authors: Potnuru Raju , Mamidi Gopi , Lagudu Devi , Bankuru Jyothi , Saripalli Tirumala Santhoshkumar , Mahammad Jameel 
Published: February 2024

Abstract
The authors have requested that this preprint be removed from Research Square.
E-selectin combined with soluble CD44 as predictors of acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation
Authors: YANG Li , WANG Wei , CHENG Zhi , LONG Fei , SUN Ming , LU Wenjie , Qi Shanshan , XIONG Hao 
Published: February 2024

Abstract

Background Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is the mainly curable treatment options in children with high-risk malignancies, bone marrow failure diseases and inherited metabolic diseases. Acute graft-versus-host disease (aGVHD) accompanied with series of serious complications are the most severe obstacle of allo-HSCT because the early and accurate diagnostic markers and effective treatment are still lacked. Non-organ-specific injury induced activated endothelial cells and tissue integrity biomarkers may have higher specificity for the occurrence and development of aGVHD. Methods The blood from 52 pediatric patients who underwent allo-HSCT including 16 recipients with aGVHD and 36 recipients without aGVHD were collected to check the level of adhesion molecules. The vitro experiments, transwell experiments, and aGVHD mouse model are used to verify the effects of E-selectin in the occurrence and development of aGVHD. Results We found that E-selectin secreted by endothelial cells was remarkably increased while the level of soluble CD44, a widely distributed tissue structure molecule, was significantly decreased in aGVHD patients. The level of E-selectin was negatively correlated with the soluble CD44 and associated with the severity of the aGVHD. After that, the vitro experiments suggested the elevated E-selectin could recruit immune cells that result in a series of inflammatory response and tissue injury. The aGVHD mouse model revealed that the level of E-selectin in the intestine occurred aGVHD was obviously increased than that without aGVHD. The expression level of CD44 in organs was related to the incidence of organ aGVHD. More importantly, the area under the ROC curve (AUC) of E-selectin and CD44 can reach 0.85 indicating that these two parameters have strong prediction ability of aGVHD. Conclusions E-selectin and CD44 could play an important role in the occurrence and development of aGVHD. E-selectin combined with soluble CD44 could act as efficient biomarkers for the diagnosis of aGVHD.
Growing meat on vegetables: plants with natural biomimetic micro-patterns as edible meat-engineering scaffolds
Authors: Du Yanan , Liu Ye , Deng Yulin , Han Jianyong , Wang Tiantian , Zhang Yongqian , Wu Zhaozhao , Yang Yuchen , Jin Yuhong , Zhang Rui , Lai Yuming 
Published: February 2024

Abstract

Cultured meat needs edible bio-scaffolds that provide not only an appropriate growth milieu for muscle and adipose cells, but also biomimetic microstructures to sculpt tissue architecture. Current meat-engineering technologies struggle to achieve scalable cell production, efficient cell differentiation, and tissue maturation in one single culture system. Here we propose a simple strategy to transform common vegetables into muscle- and adipose-engineering scaffolds, without undergoing conventional plant decellularization. We selected vegetables with natural anisotropic and isotropic topology mimicking muscle and adipose tissue microstructures respectively. We further adjusted vegetable stiffness by autoclaving to emulate the mechanical characteristics of animal tissues. Our selected anisotropic Chinese chive and Shiitake mushroom stem supported the scalable expansion of murine myoblasts and porcine myosatellite cells, and improved cell alignment and subsequent myogenesis. We also chose loofah with isotropic topology to construct lipid-containing fat tissues. Our cultured muscle and fat tissues can be assembled into meat stuffing or layered meat chips. Our results highlight naturally micro-patterned vegetables, without needing decellularization, as promising meat-engineering scaffolds. These edible biomaterials are simple to fabricate, low-cost, and possess tissue-mimicking topology and stiffness. Vegetable scaffolds may see broad applications in the bio-fabrication of meat analogs, muscle-powered robots, and transplantable tissue patches.
High Quality Mask Generation Using HardRegion Refinement in Object-based Instance Segmentation
Authors: Huang Shiliang , Liao Bingyan , Wang Yayun , Yin Jun , Xiang Zhiyu , Lin Jun 
Published: February 2024

Abstract

Existing object-based instance segmentation methods have made remarkable achievements recently. However, the conventional methods ignorethe inhomogeneity of the segmentation difficulty in the spatial dimension in different regions of instances. In this paper, we propose theHard Region Refinement (HRR) method to explicitly model easy andhard regions adaptively for high-quality instance masks generating.Our insight is that different regions of an instance should be treatedunequally on account of their different complexity. This approach decomposes the instance prediction into coarse prototype mask estimation andmultiple fine-grained hard mask prediction. To supervise the regionsat high resolution, Region-DCT (R-DCT) loss is proposed for theefficient region learning. We have carried out extensive exploratoryexperiments on the COCO and Cityscapes datasets. The experimental results demonstrate the superiority of our proposed method.
Peloid-based cosmeutics is effective in the treatment of acnotic skin - prospective study from Montenegro
Authors: Potpara Zorica , Pantovic Snezana , Zecevic Antoaneta Adzic 
Published: February 2024

Abstract
Introduction: Among skin diseases, acne represents a special therapeutic challenge because it affects the younger population and significantly affects the quality of life.The chemical composition and biological profile of peloid from Ulcinj (Montenegro) was the subject of our previous research, and the combination of that peloid and medicinal plant tinctures made Peloderm, whose effectiveness in the treatment of acne is tested in this study.
Materials and Methods: A prospective study included 140 subjects diagnosed with acne. They were divided in two groups: Peloderm-treated cohort and Emuslion-treated cohort. The FDA-IGA scale was used to monitor the effectiveness of the treatment.Eighteen-months follow up protocol was applied.
Results: There were significant differences within the examined groups, namely in part of previous antibiotic therapy, body mass index, alcohol consumption and the presence of stress.FDA-IGA score decreases in both cohorts, but more significantly in Peloderm-cohort. Final FDA-IGA score is significantly lower in Peloderm-cohort.
Discussion and Conclusion: Despite official guidelines not recognizing cosmeuticals in acne treatment, Peloderm showed promising results. The formulation's assumed mechanisms of action include reduced sebum secretion, antimicrobial, and anti-inflammatory effects, attributed to peloid and medicinal plant ingredients. Further research are needed.
Experimental validation of solar parabolic trough collector model for industrial process heat application
Authors: Akello Philip O. O. , Saoke Churchil O. , Kamau Joseph N. , Ndeda Jared. O. H. 
Published: February 2024

Abstract
This study presents experimental performance and model analysis of a parabolic trough collector (PTC) system designed for industrial heating applications. Thus, a prototype of a PTC with 1.81m2 reflective aperture area, 90o rim angle and a concentration ratio of 14.41 is presented. The reflector is made of 2m2 anodized aluminium mirror with high light reflectance value of 0.95. The re-ceiver, or heat collection element (HCE), is a 2m long tube made from SUS304 (SS304) stainless steel, which is enclosed within an external layer of borosilicate glass envelope. The receiver exhibits an exceptionally high surface absorptance of 0.96 and transmittance value of 0.92. The tracking system is based on a universal sensory solar tracker controller designed to be used with permanent magnet DC motors, and with high tracking accuracy and great electrical ca-pabilities. Initially, a simulation model of the PTC is developed using System Advisor Model (SAM) software. Then, a PTC prototype sys-tem test setup is established under outdoor weather conditions at Kimuka, in Kajiado, Kenya (latitude 1.418426°S and longitude 36.59749°E), to validate the model using experimental and meteoro-logical data measured under clear-sky condition and cloudy weather. The deviations between experimental and simulation results on the clear-sky day are 5.6% for useful heat gain, 1.89% for optical effi-ciency, and 1.42% with RMSE of 0.20% for instantaneous thermal efficiency, respectively, demonstrating good agreement. For the cloudy day, the observed deviations between experimental findings and simulation results are 9.8% for useful heat gain, 1.05% for opti-cal efficiency, 3.32% with RMSE of 0.57% for instantaneous thermal efficiency, respectively, also indicating a satisfactory level of agree-ment. Based on these results, SAM simulation model can be consid-ered as effective in forecasting the thermal and optical performance of PTCs across various operational scenarios in Kenya. At the same time, the cost of the PTC is about US$185/m2 of aperture area, and lies within a competitive range in comparison to competitors in the market.
Crime Status Prediction Using Ensemble Learning
Authors: Jain Sanjay , Singh Prashant 
Published: February 2024

Abstract
This work focuses on crime status prediction through an ensemble methodology applied to extensive datasets obtained from catalog.data.gov, specifically targeting Los Angeles crime incidents since 2020. The research methodology comprises meticulous data collection, rigorous preprocessing, exploratory data analysis, model selection, and comprehensive model evaluation. Initial challenges included data inaccuracies and privacy-preserving measures in location data, necessitating thorough cleaning and transformation processes. Exploratory data analysis revealed crucial insights, including the 'Status' attribute's limited correlation, crime code distributions, areawise crime counts, and temporal patterns. To address class imbalance within 'Status', the synthetic minority oversampling technique (SMOTE) was applied to balance the dataset. Model evaluation highlighted the superiority of random forest models employing 10 and 20 decision trees, alongside KNN, which demonstrated consistent high accuracy, balanced precision-recall trade-offs, and notable F1 scores in crime status prediction.
Guide to Developing Case-based Attack Scenarios and Establishing Defense Strategies for Cybersecurity Exercise in ICS Environment
Authors: Kim Donghyun , Jeon Seungho , Kim Kwangsoo , Kang Jaesik , Lee Seungwoon , Seo Jung Taek 
Published: February 2024

Abstract

Critical infrastructure mostly performs its role through an industrial control system (ICS). Organizations that operate security-related facilities often conduct adversarial simulation exercises between the so-called red team, which carries out attacks, and the blue team, which is responsible for defense. For the exercise to be effective, adversarial activities should include clearly delineated attack scenarios and corresponding defensive activities. Although government agencies and organizations in each country recognize the importance of exercises and propose various guidelines and practices, there still needs to be systematic guides for deriving cyberattack scenarios or defense strategies. This paper proposes a guide for establishing realistic attack scenarios and defense strategies for cybersecurity exercises in ICS environments. The proposed guide is largely divided into attack scenario generation and defensive strategy derivation. Attack scenario generation is further divided into four steps: generating attack references, deriving attack sequence, mapping threat information, and mapping vulnerable implementation patterns. Deriving a defensive strategy consists of two steps parallel to developing an attack scenario: deriving containment and eradication. Through a case study, we showed that a clear exercise plan could be established from the proposed guide. Additionally, we discuss some possible uses and limitations of our proposal.