bluuebunny/crossref_metadata_2025_split huggingface dataset:
Total Synthesis and Structural Reassignment of the Antitubercular Natural Product Evybactin
Authors: Lysenko Vladyslav , Son Sangkeun , Theriault Monique E. , Slingerland Cornelis J. , Hauk Glenn , Cleenewerk Laurence , Speer Alexander , Berger James M. , Lewis Kim , Martin Nathaniel I. 
Published: October 2024

AbstractThe escalating threat posed by antibiotic resistance is a global concern and underscores the need for new antibiotics. In this context, the recent discovery of evybactin, a nonribosomal depsipeptide antibiotic that selectively and potently inhibits the growth of M. tuberculosis, is particularly noteworthy. Here, we present the first total synthesis of this natural product, along with a revision of its assigned structure. Our studies revealed a disparity between the structure originally proposed for evybactin and its actual configuration. Specifically, the 3‐methylhistidine residue present in the evybactin core macrocycle was found to be of the d‐configuration rather than the previously assigned l‐His(Me). Having addressed this, we further optimized our solid‐phase synthetic route to provide access to evybactin on a multi‐hundred‐milligram scale. Access to such quantities will allow for more comprehensive studies with this promising antibiotic.
Enhancing Software‐Defined Networking With Dynamic Load Balancing and Fault Tolerance Using a Q‐Learning Approach
Authors: Jain Ankit Kumar , Kumari Pooja , Dhull Rajat , Jindal Krish , Raza Shahid 
Published: October 2024

ABSTRACTThe Software‐Defined Networking (SDN) paradigm represents a fundamental shift in networking by decoupling the control plane from the data plane in network devices. This architectural change offers numerous advantages, including network programmability and centralized management capabilities, which improve scalability and efficiency compared to conventional network architectures. However, the dynamic nature of network traffic presents overload challenges, both temporally and spatially, especially in multi‐controller SDN settings. To address these challenges, this paper presents an approach leveraging network traffic patterns for dynamic load balancing. The proposed framework optimizes migration strategies to reduce costs and enhance in‐packet request‐response rates. By exploiting load ratio variance across controllers, the architecture identifies optimal migration triplets, encompassing migration‐in and migration‐out domains by selecting a subset of switches. The architecture utilizes online Q‐learning technology to achieve optimal controller load balancing while minimizing associated expenses. The proposed approach ensures stability and scalability by imposing limits to maintain maximum efficiency and reduce migration conflicts. It iteratively converges to an optimal policy through a comprehensive set of simulations performed on switches under a wide range of load distribution situations. These results highlight the effectiveness and adaptability of the proposed methodology in addressing the intricacies present in dynamic network settings, encouraging further progress in the field of SDN technologies and their real‐world applications.
Job Scheduling in Hybrid Clouds With Privacy Constraints: A Deep Reinforcement Learning Approach
Authors: He Haoyang , Gu Yan , Liu Qingzhi , Wu Hao , Cheng Long 
Published: October 2024

ABSTRACTWith the proliferation of cloud computing and the escalating demand for extensive data processing capabilities, an increasing number of enterprises are embracing hybrid cloud solutions. However, as more businesses move toward hybrid clouds, the need for effective solutions to privacy and security concerns becomes increasingly important. Although current scheduling approaches for cloud computing have addressed privacy protection to some extent, few have adequately considered the unique challenges posed by hybrid clouds. To address this gap, we propose a novel approach for scheduling jobs in hybrid clouds that prioritizes privacy protection. Our approach, called PH‐DRL, leverages Deep Reinforcement Learning (DRL) to intelligently allocate jobs to virtual machines, optimizing both privacy and Quality of Service (QoS), while minimizing response time. We present the detailed implementation of our approach and our experimental results demonstrate the superior performance of PH‐DRL in terms of privacy protection compared to existing methods.
Current trends in micro‐supercapacitor devices
Authors: Paul Aparna , Murmu Naresh Chandra , Kuila Tapas 
Published: October 2024

AbstractRecently, efforts have been made to design miniaturized energy storage devices according to custom requirements. The application of micro‐electronic equipment has increased significantly in information technology and biotechnology. Microelectromechanical systems, nanoelectromechanical systems, maintenance‐free wireless sensor networks, implantable medical devices, micro‐robots, and integrating energy conversion devices require micropower sources in small dimensions. Conventional supercapacitor devices cannot fulfill such high‐power demand, but miniaturization within the microscale helps enhance the working efficiency due to the shortening of diffusion path length. Micro‐supercapacitors (MSCs) in the micron to centimeter dimension range integrated with circuits and microelectronic components have gained great interest due to their high‐power density, high‐frequency response, and long cycling stability. Research on the design and fabrication of MSCs has progressed enormously. Integrating MSCs with other electronic units helps to achieve a highly efficient self‐powered system. This review presents a critical summary of the recent progress of novel materials for MSCs, fabrication methods, advanced design, and challenges in the MSCs industry.
A modified matrix model captures the population dynamics for the primary vector of Lyme disease in North America
Authors: Foster John R. , LaDeau Shannon L. , Oggenfuss Kelly , Ostfeld Richard S. , Dietze Michael C. 
Published: October 2024

AbstractLyme disease, the most prevalent tick‐borne disease in North America, is caused by the bacterium Borrelia burgdorferi, and in the eastern and central United States, it is spread to humans by the black‐legged tick (Ixodes scapularis). Due to the complex, multiyear and multihost life cycle of this species, a matrix modeling approach is needed to effectively estimate subseasonal, multistage survival and transition dynamics in order to better understand and predict when population growth is high. Of the three questing tick life stages (larvae, nymphs, and adults), nymphs are most often associated with transmitting the bacteria to humans, and previous work suggests a mix of abiotic and biotic drivers are associated with nymph abundance. However, understanding tick population growth requires understanding mortality and transition probabilities for each stage and each stage may be individually and uniquely impacted by climate and host availability. A larval tick, for example, may experience warming temperatures differently than nymph or adults, because they are present on the landscape at different times. Here, we describe and validate a model that accounts for field sampling design and evaluates abiotic (temperature, relative humidity, precipitation) and biotic (host abundance) drivers of variation in tick population growth. To account for the drivers of subseasonal and interannual variability in demography, phenology, and population density, we built stage‐structured population models that account for variability in meteorology and host population abundance throughout the full tick lifecycle. Our model is fit and validated with 11 years of tick and host data from the northeastern United States. In this context, we found that a four‐stage model that includes unique transitions to and from a dormant, overwintering nymph state outperforms a model that only includes the three questing stages, and that incorporating the abundance of the predominant host species, Peromyscus leucopus, and weather variables improved predictions and model fit. Additionally, the model accurately predicted all three questing stages at sites different than where they were calibrated, showing that this model structure is generally transferable. Overall, this model lays a foundation for the real‐time iterative forecasting of tick populations needed to effectively protect public health.
Investigation of motion response suppression characteristics in floating platforms equipped with novel spiral side plates
Authors: Jing‐mei Yu , Chun‐long Bai 
Published: October 2024

AbstractTo enhance the stability of floating wind turbine platforms, this study combines the structural characteristics of helical side plates and proposes the installation of serrated helical side plates on Spar wind turbine platforms. Based on potential flow theory, the present study employs blade element momentum theory and radiation‐diffraction theory. Upon establishing a dynamic data link library, wind‐wave coupling was implemented, and the dynamic response characteristics of platforms with different helical side plates were compared. The results indicate that in the frequency domain analysis, the platform with serrated helical side plates demonstrates reduced sensitivity to waves, with a particularly notable increase in added mass in the heave direction, suggesting excellent hydrodynamic performance. In the time domain analysis, improvements in the platform's surge and heave stability performances were observed, measuring 10.99% and 10.64%, respectively, in extreme conditions. Owing to the unique features of the serrated structure, the tension in the mooring chains on the wave‐facing side is reduced, thereby effectively lowering the fatigue load on the mooring chains.
Gymnema lactiferum: A Review of Its Traditional Applications, Phytochemical Constituents, and Biological Properties
Authors: Weerasinghe D. M. K. P. , Brough L. , Everett D. W. , Rashidinejad A. 
Published: October 2024

ABSTRACTHumanity has a longstanding reliance on natural plants for medicinal purposes, and Gymnema lactiferum (G. lactiferum) has emerged as a medicinal plant with deep‐rooted traditional usage. Throughout history, this plant has been an integral part of traditional medical systems, demonstrating diverse therapeutic effects. Notably, among these effects is its ability to decrease blood glucose concentration in diabetic patients, impart cooling effects, serve as an anabolic and rehydrating agent, stimulate spermiogenesis, and exhibit wormicidal properties. Furthermore, G. lactiferum has been used in treating conditions such as hemorrhoids cancers, anorexia, and as a cardiac stimulant. The primary objective of this review is to comprehensively gather and critically assess research findings regarding the medicinal properties of G. lactiferum, specifically emphasizing the bioactive compounds responsible for these properties. Previous studies have documented the presence of various phytochemicals in G. lactiferum, which are associated with some biological activities, including antioxidative, anti‐hyperglycemic, cholesterol‐regulating, and anti‐inflammatory properties. Additionally, this review explores potential future applications for this plant. Beyond its medicinal significance, extracts derived from G. lactiferum demonstrate promise for future nutritional applications. This review highlights the potential use of G. lactiferum as an herbal medicine by critically assessing research on its medicinal value.
Exploring internet addiction during Covid‐19 pandemic: a comparative study considering psychological, social, familial and individual aspects in University students
Authors: Faramarzi Mahbobeh , Karim Bardia , Gholami Zeinab , Khoshkhou Fatemah , Shirazi Fatemeh , Soghli Negar , Parvaneh Munire , Shirafkan Hoda , Khorshidian Faezeh 
Published: October 2024

AbstractBackgroundInternet addiction causes a variety of social, interpersonal, psychological, and physical issues. We are confronting a worldwide crisis about internet addiction and its effects.ObjectivesUtilizing five questionnaires to survey university students during the COVID‐19 epidemic, the current study sought to evaluate internet addiction and associated risk variables.MethodsAt the University of Medical Sciences in North Iran, a cross‐sectional analytical investigation was carried out. The sample was done among 318 students, selected through the random cluster sampling method. Data collection was done during August and September 2021.ResultsBased on our findings, the prevalence of internet addiction was 28.9% (92/318). Our results revealed that women are at twice the twice the risk of internet addiction as men (p = 0.028). Students in the medicinal field (p = 0.043; students with a positive history of mental illness in the family) p = 0.001 (and students with a fear of COVID‐19) p = 0.002 (recognized in the risk of Internet addiction, thus depression) p < 0.001 (anxiety) p < 0.001 (somatization) p = 0.001 (and psychological distress) p < 0.001 are risk factors for internet addiction. Age, marital status, place of living, total social support, and use of Alcohol/cigarettes are not risk factors for internet addiction.ConclusionsThe findings suggest that university students with a fear of COVID‐19, depression, anxiety, somatization, psychological distress and a positive history of mental illness in the family, particularly medicinal field students, are at significant risk for Internet addiction.
Treatment response and clinical features of snakebite envenomation in Alborz province, Iran: A cross‐sectional study
Authors: Farajidana Hoorvash , Mosalamiaghili Seyedarad , Assadian Kasra , Jahangiri Soodeh , Masumzadegan Maryam , Sadeghi Farangis , Arani Lida shojaei 
Published: October 2024

AbstractBackgroundSnakebite envenomation is a significant yet neglected public health burden. Our aim was to investigate the clinical and demographic factors of snakebite envenomation, as well as the factors associated with its severity and response to treatment, in Alborz province, northern Iran.MethodsIn this cross‐sectional study, we included 50 patients diagnosed with snakebite envenomation, referring to the Poison Control Centre of Alborz University of Medical Sciences. The presenting signs and symptoms, demographic data, treatment dose, response to treatment, complications, laboratory findings, and snakebite severity scale (SSS) were collected.ResultsForty‐six patients (92%) were men, the total mean age was 31.7 ± 12.06 years, and mean SSS was 6.54 ± 3.39. The patients were admitted for a median of 2 days, and 11 patients needed ICU admissions. The majority of snakebites were in upper extremities (60%) and they mainly occurred in summer (56%). SSS was significantly associated with response to treatment, ICU admission, gastrointestinal adverse events, thrombocytopenia, and length of stay. Similarly, response to treatment was significantly related to the history of snakebite, ICU admission, gastrointestinal adverse events, thrombocytopenia, length of stay, and SSS.ConclusionGastrointestinal symptoms, higher severity scores, and longer hospital stays were associated with poor treatment response. Importantly, no mortality was observed in this cohort. Further research is needed to confirm these findings and optimize treatment strategies for snakebite management.
The integral role of high‐entropy alloys in advancing solid‐state hydrogen storage
Authors: Ding Zhao , Li Yuting , Jiang Han , Zhou Yang , Wan Haiyi , Qiu Junqi , Jiang Fangning , Tan Jun , Du Wenjia , Chen Yu'an , Shaw Leon L. , Pan Fusheng 
Published: October 2024

AbstractHigh‐entropy alloys (HEAs) have emerged as a groundbreaking class of materials poised to revolutionize solid‐state hydrogen storage technology. This comprehensive review delves into the intricate interplay between the unique compositional and structural attributes of HEAs and their remarkable hydrogen storage performance. By meticulously exploring the design strategies and synthesis techniques, encompassing experimental procedures, thermodynamic calculations, and machine learning approaches, this work illuminates the vast potential of HEAs in surmounting the challenges faced by conventional hydrogen storage materials. The review underscores the pivotal role of HEAs' diverse elemental landscape and phase dynamics in tailoring their hydrogen storage properties. It elucidates the complex mechanisms governing hydrogen absorption, diffusion, and desorption within these novel alloys, offering insights into enhancing their reversibility, cycling stability, and safety characteristics. Moreover, it highlights the transformative impact of advanced characterization techniques and computational modeling in unraveling the structure–property relationships and guiding the rational design of high‐performance HEAs for hydrogen storage applications. By bridging the gap between fundamental science and practical implementation, this review sets the stage for the development of next‐generation solid‐state hydrogen storage solutions. It identifies key research directions and strategies to accelerate the deployment of HEAs in hydrogen storage systems, including the optimization of synthesis routes, the integration of multiscale characterization, and the harnessing of data‐driven approaches. Ultimately, this comprehensive analysis serves as a roadmap for the scientific community, paving the way for the widespread adoption of HEAs as a disruptive technology in the pursuit of sustainable and efficient hydrogen storage for a clean energy future.
SPAG4 enhances mitochondrial respiration and aerobic glycolysis in colorectal cancer cells by activating the PI3K/Akt signaling pathway
Authors: Zhou Jiehao , Sun Haobo , Zhou Hang , Liu Ying 
Published: October 2024

AbstractAerobic glycolysis plays a pivotal role in the progression of tumors. Previously, a glycolysis‐associated prognostic model in CRC was constructed and the glycolysis‐related gene SPAG4 was discovered to be upregulated in CRC and was correlated with adverse prognosis. To date, however, no study has elucidated the specific role of SPAG4 in the development of CRC. In our study, CRC cells were transfected with si‐SPAG4 or OE‐SPAG4 to evaluate the influence of SPAG4 silencing or overexpression on CRC cell malignant behaviors. CRC cell proliferation and metastasis were detected via CCK‐8, colony formation, and Transwell assays. The oxygen consumption rate and extracellular acidification rate of CRC cells were determined by using an XF24 extracellular flux analyzer. The expression of SPAG4, key mitochondrial markers (NDUFA1, SDHB, ATP5A, and PGC‐1α), key enzymes involved in glycolysis (GLUT1, HK2, LDHA, PKM2, and PFK1), and PI3K/Akt pathway‐molecules and downstream transcription factor HIF‐1α was assessed by RT‐qPCR and western blot analysis. SPAG4 expression in CRC and normal tissue samples was tested through immunohistochemical staining. Finally, SPAG4‐overexpressed CRC cells were treated with LY294002 to validate the inhibition of PI3K/Akt pathway on CRC cell malignant phenotypes. Our results showed that SPAG4 was upregulated in CRC cells and tissues, and high expression SPAG4 predicted shorter overall survival time. SPAG4 knockdown inhibited while SPAG4 overexpression enhanced CRC cell proliferation, migration, invasion, mitochondrial respiration, and aerobic glycolysis. Overexpressing SPAG4 elevated p‐PI3K, p‐Akt, p‐mTOR, and HIF‐1α protein levels, which were restored after LY294002 treatment. Furthermore, LY294002 abolished the promotion of SPAG4 overexpression on CRC malignant phenotypes. Collectively, SPAG4 plays an oncogenic role in CRC by promoting mitochondrial respiration and aerobic glycolysis through activating the PI3K/Akt signaling. These findings suggest that inhibition of SPAG4‐mediated glucose metabolism may represent a potential strategy for the clinical treatment of CRC.
Explanatory Factors of the Accounting Choices for Investments Under IAS 27 of Listed European Union Entities
Authors: Ribeiro Maria , Gomes Dos Santos Paula , Albuquerque Fábio 
Published: October 2024

ABSTRACTThis study aims to analyze the explanatory factors of the accounting choices for investments of entities with securities traded on regulated markets from the European Union (EU) under International Accounting Standards (IAS) 27—Separate Financial Statements (SFS). According to IAS 27, investments in their scope can be accounted for by using the cost, equity method, or fair value, which represents alternative accounting methods commonly known in the literature as accounting choices. To identify the factors that may explain the accounting choices for investments under IAS 27, a logistic regression model is used. The research covers listed entities from 19 out of the 21 EU countries where IAS 27 is required or permitted. The findings highlight that the entities’ size and investment weight likely explain the adoption of the cost method, conversely to the size of the board of directors, which negatively explains its use. Accounting choices for investments under SFS are not yet explored in the literature. Moreover, this research also proposes further explanatory factors in the scope of the literature on accounting choices. This paper can potentially benefit a diverse set of stakeholders, namely the accounting standard‐setters, as they can draw attention to the comparability issues from the use of accounting choices, which may mitigate the financial information usefulness for decision‐making. Furthermore, auditors, supervisors, as well as investors and other users, can have a more comprehensive perspective of the reasons behind the method chosen by entities for accounting for their financial investments.
Alignment rod and gap measurement methods achieve comparable alignment correction in opening wedge high tibial osteotomy for varus osteoarthritic knees
Authors: Onishi Shintaro , Kim Youngji , Nakayama Hiroshi , Jacquet Christophe , Mabrouk Ahmed , Ollivier Matthieu 
Published: October 2024

AbstractPurposeTo compare clinical and radiological outcomes of medial opening wedge high tibial osteotomy (MOWHTO) using two different alignment methods: the alignment rod (AR) versus the gap measurement (GM) method. The primary outcome was to report the surgical accuracy of coronal plane corrections in each method.MethodsPatients who underwent MOWHTO with either AR or GM method between 2014 and 2022 at a single institution, with a minimum of 2 years of follow‐up, were included. The opening gap was gradually spread with an AR under fluoroscopic control in the AR group, whereas the osteotomy site was opened to the value of the measured gap distance in addition to the thickness of the bone saw in the GM group. Radiological assessment of geometric characteristics included hip–knee–ankle angle (HKA), medial proximal tibial angle (MPTA), mechanical lateral distal femoral angle and joint line convergence angle. Surgical accuracy, which is the deviation (Δ) between the intended and achieved correction, was compared between both methods. Clinical outcomes were assessed using the Knee Injury and Osteoarthritis Outcome Scores.ResultsA total of 110 patients (n = 110 knees) with a mean age of 54.1 ± 8.4 years were included in the study. Radiological parameters were significantly improved as reflected by HKA correction from 171.6° ± 2.0° to 181.1° ± 2.6° in the AR group and from 171.0° ± 2.3° to 181.1° ± 2.8° in the GM group at 2 years (Intergroup n.s). There was no significant intergroup difference for all radiological parameters and clinical outcomes. There was no intergroup difference in the surgical accuracy as evaluated by Δvalues and absolute Δvalues of both HKA and MPTA (n.s).ConclusionsComparable correction accuracy was achieved in MOWHTO using either the AR or GM method. The GM method is simple and reliable in achieving the intended correction in MOWHTO.Level of EvidenceⅢ retrospective comparative study.