bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unmanned air/ground vehicle survey following a radiological dispersal event
Authors: Munsie Timothy , Beckman Blake , Fawkes Ross , Shippen Alan B. , Fairbrother Blaine , Green Anna Rae 
Published: February 2024

AbstractThis paper presents the method and results of surveying a dispersed radioactive field using an unmanned air vehicle (UAV) and an unmanned ground vehicle (UGV). A 35 GBq of La material was distributed in a specific geometric
l‐polygon pattern measuring a 120 m  20 m longitudinal rectangle and an 80 m  10 m transverse rectangle. Two methods were used to determine the amount and distribution of the lanthanum over the polygon including 20 plywood coupons distributed over the area and a UGV equipped with a Kromek GR1® driving over the area. The aerial survey was conducted using an unmanned aerial vehicle UAV carrying the Kromek GR1® while flying a traditional grid pattern and circular pattern at different elevations and speeds over the area. The data collected by the UAV were further postprocessed using N‐Visage, a 3D radiation modeling method developed by Createc, to create a model of the ground activity. This model was compared with the reference data collected on the ground by the UGV and was found to be in agreement with 11%.
Nautilus: An autonomous surface vehicle with a multilayer software architecture for offshore inspection
Authors: Campos Daniel F. , Gonçalves Eduardo P. , Campos Hugo J. , Pereira Maria I. , Pinto Andry M. 
Published: February 2024

AbstractThe increasing adoption of robotic solutions for inspection tasks in challenging environments is becoming increasingly prevalent, particularly in the offshore wind energy industry. This trend is driven by the critical need to safeguard the integrity and operational efficiency of offshore infrastructure. Consequently, the design of inspection vehicles must comply with rigorous requirements established by the offshore Operation and Maintenance (O&M) industry. This work presents the design of an autonomous surface vehicle (ASV), named Nautilus, specifically tailored to withstand the demanding conditions of offshore O&M scenarios. The design encompasses both hardware and software architectures, ensuring Nautilus's robustness and adaptability to the harsh maritime environment. It presents a compact hull capable of operating in moderate sea states (wave height up to 2.5 m), with a modular hardware and software architecture that is easily adapted to the mission requirements. It has a perception payload and communication system for edge and real‐time computing, communicates with a Shore Control Center and allows beyond visual line‐of‐sight operations. The Nautilus software architecture aims to provide the necessary flexibility for different mission requirements to offer a unified software architecture for O&M operations. Nautilus's capabilities were validated through the professional testing process of the ATLANTIS Test Center, involving operations in both near‐real and real‐world environments. This validation process culminated in Nautilus's reaching a Technology Readiness Level 8 and became the first ASV to execute autonomous tasks at a floating offshore wind farm located in the Atlantic.
Designing of target‐specific N‐substituted tetrahydroquinoline derivatives as potent mTOR inhibitors via integrated structure‐guided computational approaches
Authors: Shaw Suman , Dey Rajdeep , Bhatt Hardik , Patel Bhumika , Patel Saumya , Dixit Nandan , Chaube Udit 
Published: February 2024

AbstractThere is a need to develop innovative, safe, and more effective treatment methods for lung cancer due to obstacles including resistance, side effects, and low bioavailability, among others related to present medicines. Our previous research findings gave some promising results of tetrahydroquinoline (THQ) derivatives as mTOR inhibitors for the treatment of lung cancer. The current research has employed certain integrated computational techniques to enhance the effectiveness of THQ derivatives. Various computational methods, like the generation of the pharmacophore model, virtual screening, and QSAR modeling were employed to achieve the goal, and their results were connected to develop novel THQ analogues. This study revealed that among 48 newly designed THQ derivatives, the compound UC_1 indicated the XP Gscore of −9.378 kcal/mol and also showed the key amino acid interactions with the mTOR protein viz. Gln2167, Val2240. Interestingly, compound UC_1 showed a better binding affinity with the mTOR protein compared to the clinical trial molecules viz. AZD‐8055 and AZD‐2014. The molecular dynamics simulations (100 ns) along with each output give a shred of strong evidence that the designed THQ derivative (UC_1) has all the required features in terms of inhibiting mTOR protein for the treatment of lung cancer.
iSKIN: Integrated application of machine learning and Mondrian conformal prediction to detect skin sensitizers in cosmetic raw materials
Authors: Kong Weikaixin , Zhu Jie , Shan Peipei , Ying Huiyan , Chen Tongyu , Zhang Bowen , Peng Chao , Wang Zihan , Wang Yifan , Huang Liting , Bi Suzhen , Ma Weining , Huang Zhuo , Zhu Sujie , Liu Xueyan , Li Chun 
Published: February 2024

AbstractAnimal experiments traditionally identify sensitizers in cosmetic materials. However, with growing concerns over animal ethics and bans on such experiments globally, alternative methods like machine learning are gaining prominence for their efficiency and cost‐effectiveness. In this study, to develop a robust sensitizer detector model, we first constructed benchmark data sets using data from previous studies and a public database, then 589 sensitizers and 831 nonsensitizers were collected. In addition, a graph‐based autoencoder and Mondrian conformal prediction (MCP) were combined to build a robust sensitizer detector, iSKIN. In the independent test set, the Matthews correlation coefficient (MCC) and the area under the receiver operating characteristic curve (ROCAUC) values of the iSKIN model without MCP were 0.472 and 0.804, respectively, which are higher than those of the three baseline models. When setting the significance level in MCP at 0.7, the MCC and ROCAUC values of iSKIN could achieve 0.753 and 0.927, respectively. Regrouping experiments proved that the MCP method is robust in the improvement of model performance. Through key structure analysis, seven key substructures in sensitizers were identified to guide cosmetic material design. Notably, long chains with halogen atoms and phenyl groups with two chlorine atoms at ortho‐positions were potential sensitizers. Finally, a user‐friendly web tool (http://www.iskin.work/) of the iSKIN model was deployed to be used by other researchers. In summary, the proposed iSKIN model has achieved state‐of‐the‐art performance so far, which can contribute to the safety evaluation of cosmetic raw materials and provide a reference for the chemical structure design of these materials.
Tarsis: An effective automata‐based abstract domain for string analysis
Authors: Negrini Luca , Arceri Vincenzo , Cortesi Agostino , Ferrara Pietro 
Published: February 2024

AbstractIn this paper, we introduce Tarsis, a new abstract domain based on the abstract interpretation theory that approximates string values through finite state automata. The main novelty of Tarsis is that it works over an alphabet of strings instead of single characters. On the one hand, such an approach requires a more complex and refined definition of the lattice operators and of the abstract semantics of string operators. On the other hand, it is in position to obtain strictly more precise results than state‐of‐the‐art approaches. We compare Tarsis both with simpler domains and with the standard automata model, targeting case studies containing standard yet challenging string manipulations. The performance gain w.r.t. the standard automata model is also assessed, measuring the speed‐up gained by Tarsis. Experiments confirm that Tarsis can obtain precise results without incurring in excessive computational costs.
Enhancing Natural Rubber Composites with Spent Coffee Ground: Physical Properties, Odor Absorption, and Processing
Authors: Somdee Patcharapon , Prasoetsopha Natkrita , Detsunhnoen Saksan , Matnok Suchat , Ansari Manauwar Ali 
Published: February 2024

AbstractThis research aims to enhance natural rubber (NR) properties by incorporating spent coffee grounds (SCGs). Scanning electron microscope (SEM) reveals well‐dispersed SCG particles in the NR matrix without interaction. Shore A hardness notably increases by up to 49.90 (19% higher than unmodified), but tensile and tear strength decline with higher SCG levels. Optimal tear strength occurs at 10 phr of SCG due to uniform dispersion. The 300% modulus remains unchanged. The odor of composites (CO2 absorption) sees a 69.2% increase at 25 phr, while odor absorption efficiency peaks at 2%. Additionally, unmodified SCG affects scorch time (2.12%–23.40% increase from 1 to 20 phr) and cure time (3.12% to 76.82% improvement from 1 to 20 phr). These findings showcase improved hardness, enhanced CO2 absorption capacity, and effective odor control. Additionally, this study sheds light on the influence of SCG on processing times, contributing valuable insights for eco‐friendly applications.
RETRACTED: Development of the ARDS‐derived gene panel for lung adenocarcinoma prognosis stratification and experiment validation of CCL20 expression
Authors: Fang Jingjing , Shi Chaolu , Huang Qin , Huang Lei , Wang Xinnian , Yan Biqing 
Published: February 2024

AbstractAcute respiratory distress syndrome (ARDS) is a life‐threatening condition characterized by lung inflammation and high mortality rates. Lung cancer, specifically lung adenocarcinoma (LUAD), is a major cause of cancer‐related deaths worldwide. Patients with LUAD, particularly those undergoing chemotherapy, are more likely to develop ARDS. ARDS inflicts major malfunctioning in the immune system. We suspected a certain shared pathogenic mechanism between these diseases. This study analyzed 503 LUAD patients from the TCGA‐LUAD cohort as the training set, 85 LUAD cases from the GSE30219 cohort as the validation set, and 24 RNA‐seq samples from ARDS mice model and control groups in the GSE2411 cohort. The differentially expressed genes (DEGs) of ARDS were analyzed using the limma package and screened by Cox and Lasso analysis. ssGSEA and xCell algorithms were utilized for immune landscaping. RT‐qPCR analysis was used to determine the mRNA levels of key genes in both the LPS‐induced ARDS model and human LUAD cell lines. We identified DEGs between ARDS and control groups, which were highly associated with cytokine production and leukocyte migration. A prognosis model for LUAD patients was developed based on the expressions of the key genes in the ARDS‐derived DEGs, including FMO3, IL1R2, CCL20, CFTR, and GADD45G. A satisfactory efficacy was observed in both the training and validation cohorts. The model demonstrated increased effectiveness in predicting the intratumor immune profile and mutation status of LUAD. Moreover, we utilized LPS to induce the ARDS model, which resulted in elevated expressions of IL1R2 and CCL20. Additionally, CCL20 was upregulated in cancerous LUAD cell lines. We developed an ARDS‐based model for stratifying LUAD prognosis. CCL20 was found to be elevated in both the ARDS model and LUAD, suggesting a shared underlying mechanism of these two diseases.
Three Strategies for Supporting Elementary Writers through the Practice of Sharing
Authors: Lewis Bethany P. 
Published: February 2024

AbstractAlthough orally sharing and discussing written compositions has been shown to benefit elementary students, it can be challenging to entwine this additional pedagogy with an already full literacy instructional period. This article acknowledges these challenges and outlines three evidence‐based instructional modifications to encourage active sharing in literacy classrooms to support developing writers. The three strategies are (1) The “Single Share,” (2) “The Sticky and the Sticker,” and (3) “The Borrow.” The benefits of each strategy are discussed within the elementary literacy context, and insight into the successful implementation of each pedagogical approach is provided for educators.
Metagenomic analysis unravels novel taxonomic differences in the uterine microbiome between healthy mares and mares with endometritis
Authors: Virendra Aeknath , Gulavane Sarita U. , Ahmed Zulfikar A. , Reddy Ravi , Chaudhari Ravindra J. , Gaikwad Sandeep M. , Shelar Raju R. , Ingole Shailesh D. , Thorat Varsha D. , Khanam Afroza , Khan Firdous A. 
Published: February 2024

AbstractBackgroundThe application of high throughput technologies has enabled unravelling of unique differences between healthy mares and mares with endometritis at transcriptomic and proteomic levels. However, differences in the uterine microbiome are yet to be investigated.ObjectivesThe present study was aimed at evaluating the differences in uterine microbiome between healthy mares and mares with endometritis.MethodsLow‐volume lavage (LVL) samples were collected from the uterus of 30 mares classified into healthy (n = 15) and endometritis (n = 15) based on their reproductive history, intrauterine fluid accumulation, gross appearance of LVL samples, endometrial cytology and bacterial culture. The samples were subjected to 16S rRNA sequencing.ResultsNotable differences in the uterine microbiome were observed between healthy mares and mares with endometritis at various taxonomic levels. In healthy mares, the most abundant phylum, class, order and family were Firmicutes, Bacilli, Bacillales and Paenibacillaceae, respectively. In contrast, the most abundant corresponding taxonomic levels in mares with endometritis were Proteobacteria, Gammaproteobacteria, Enterobacterales and Enterobacteriaceae, respectively. At the genus level, Brevibacillus and Paenibacillus were more abundant in healthy mares, whereas Escherichia, Salmonella and Klebsiella were more abundant in mares with endometritis. In healthy mares, Brevibacillus brevis was the most abundant species, followed by Brevibacillus choshinensis and Paenibacillus sp JDR‐2. However, in mares with endometritis, Escherichia coli was the most abundant species, followed by Salmonella enterica and Klebsiella pneumoniae.ConclusionsThese results confirmed the previously reported presence of a uterine microbiome in healthy mares and helped unravel some alterations that occur in mares with endometritis. The findings can potentially help formulate new approaches to prevent or treat equine endometritis.
Antibiotic resistance and virulence profiles of Proteus mirabilis isolated from broiler chickens at abattoir in South Africa
Authors: Ramatla Tsepo , Ramaili Taole , Lekota Kgaugelo , Mileng Kealeboga , Ndou Rendani , Mphuthi Malekoba , Khasapane Ntelekwane , Syakalima Michelo , Thekisoe Oriel 
Published: February 2024

AbstractBackgroundProteus mirabilis has been identified as an important zoonotic pathogen, causing several illnesses such as diarrhoea, keratitis and urinary tract infections.ObjectiveThis study assessed the prevalence of P. mirabilis in broiler chickens, its antibiotic resistance (AR) patterns, ESBL‐producing P. mirabilis and the presence of virulence genes.MethodsA total of 26 isolates were confirmed as P. mirabilis from 480 pooled broiler chicken faecal samples by polymerase chain reaction (PCR). The disk diffusion method was used to evaluate the antibacterial susceptibility test, while nine virulence genes and 26 AR genes were also screened by PCR.ResultsAll 26 P. mirabilis isolates harboured the ireA (siderophore receptors), ptA, and zapA (proteases), ucaA, pmfA, atfA, and mrpA (fimbriae), hlyA and hpmA (haemolysins) virulence genes. The P. mirabilis isolates were resistant to ciprofloxacin (62%) and levofloxacin (54%), while 8 (30.7%) of the isolates were classified as multidrug resistant (MDR). PCR analysis identified the blaCTX‐M gene (62%), blaTEM (58%) and blaCTX‐M‐2 (38%). Further screening for AMR genes identified mcr‐1, cat1, cat2, qnrA, qnrD and mecA, 12%, 19%, 12%, 54%, 27% and 8%, respectively for P. mirabilis isolates. The prevalence of the integron integrase intI1 and intI2 genes was 43% and 4%, respectively.ConclusionsThe rise of ciprofloxacin and levofloxacin resistance, as well as MDR strains, is a public health threat that points to a challenge in the treatment of infections caused by these zoonotic bacteria. Furthermore, because ESBL‐producing P. mirabilis has the potential to spread to humans, the presence of blaCTX‐M‐producing P. mirabilis in broilers should be kept under control. This is the first study undertaken to isolate P. mirabilis from chicken faecal samples and investigate its antibiotic resistance status as well as virulence profiles in South Africa.
The prevalence of adhesion and biofilm genes in Staphylococcus aureus isolates from bovine mastitis: A comprehensive meta‐analysis
Authors: Sharifi Aram , Mahmoudi Peyman , Sobhani Keyvan 
Published: February 2024

AbstractBackgroundMastitis poses significant challenges to the dairy industry, resulting in economic losses and increased veterinary expenses. Staphylococcus aureus is a common cause of bovine mastitis, relying on efficient adhesion and biofilm formation for infection.ObjectivesThis study aimed to employ meta‐analysis to investigate the occurrence of adhesion and biofilm genes in S. aureus associated with bovine mastitis, as documented in previous studies.MethodsThis meta‐analysis was done according to Preferred Reporting Items for Systematic Reviews and Meta‐Analyses, examined 22 eligible articles and revealed varying prevalence rates of adhesion and biofilm genes in S. aureus isolates from bovine mastitis.ResultsAmong the genes, clfB showed the highest prevalence (p‐estimate = 0.905), followed by fnbA (p‐estimate = 0.689) and fnbB (p‐estimate = 0.502). The icaA and icaD genes also showed a relatively high prevalence (p‐estimate = 0.694 and 0.814, respectively). Conversely, the biofilm‐associated proteins gene had the lowest prevalence (p‐estimate = 0.043). Subgroup analyses based on mastitis types and publication years revealed no significant differences in gene prevalence. Insufficient data hindered the analysis of fib, sasG , eno and bbp genes.ConclusionThis study provides valuable insights for managing S. aureus‐induced bovine mastitis. Additionally, larger‐scale research, particularly on less‐studied genes, is necessary to comprehend the molecular roles of adhesion and biofilm genes in S. aureus‐induced bovine mastitis.
Exploring the artistic dimensions of soils in the vadose zone
Authors: Wessolek Gerd , Toland Alexandra 
Published: February 2024

AbstractThe rise of industrialized agriculture, coupled with a global demographic shift toward urbanization, has marginalized every‐day connections between individuals and soils. This societal shift has led to a decline in the appreciation of and cultural identity with soils. Amid a broader movement aimed at fostering soil awareness and environmental action, many artists and designers have been instrumental in bringing soils to the cultural mainstream, figuring their esthetic, social, political, and ecological dimensions. Contemporary artists place great importance on the underlying idea of animating soils through artistic practice, often transcending the physical artifact itself to assign agency to soils and the myriad beings that occupy them. Artists harness a multitude of media to articulate human‐soil relationships. From the early environmental art movements of the 1960s and 1970s to contemporary works centered on urban and industrial brownfields, soils’ multifaceted roles in CO2 transformation, water and nutrient cycling, agriculture, and as living bodies buffering against pollution have become ground for public discourse. What could this mean for the vadose zone in terms of reflecting on material flows in porous media beyond understandings of soil physics? In this paper, we draw on over 20 years of experience in studying the portrayal of soil in various arts genres to deliberate the potential of creative thinking about and thinking with the vadose zone.
A review of battery state of charge estimation and management systems: Models and future prospective
Authors: Hussein Hossam M. , Aghmadi Ahmed , Abdelrahman Mahmoud S. , Rafin S M Sajjad Hossain , Mohammed Osama 
Published: February 2024

AbstractBatteries are considered critical elements in most applications nowadays due to their power and energy density features. However, uncontrolled charging and discharging will negatively affect their functions and might result in a catastrophic failure of their applications. Hence, a battery management system (BMS) is mandated for their proper operation. One of the critical elements of any BMS is the state of charge (SoC) estimation process, which highly determines the needed action to maintain the battery's health and efficiency. Several methods were used to estimate the Lithium‐ion batteries (LIBs) SoC, depending on the LIBs model or any other suitable technique. This article provides a critical review of the existing SoC estimation approaches and the main LIB models with their pros and cons, their possibility to integrate with each other's for precise estimation results, and the applicability of these techniques in electric vehicles and utility applications with the commonly used standards and codes in these sectors. Moreover, this study will also explore a future framework for integrating digital twins (DTs) with BMSs for improved and advanced management. Based on this comprehensive review, it can be concluded that merging the model‐based estimation techniques with the data‐driven approaches with their promising development to determine the dynamic patterns inside the battery can efficiently achieve precise estimation results while reducing the complexity of these models. This integration will align also with the integration of digital twin technology to provide complete and accurate supervision for the BMSs.This article is categorized under:
Emerging Technologies > Energy Storage
Emerging Technologies > Digitalization
Energy and Power Systems > Distributed Generation