bluuebunny/crossref_metadata_2025_split huggingface dataset:
Eucalyptol (1, 8-cineole), a monoterpene oxide with potential for protecting soybean crops against insect pests and phytopathogenic fungi
Authors: Wagner Leandro Sebastian , Sequín Christian Javier , Perusset Sergio Andrés , Fernández Estrella Natalín , Pretti Joaquín , Campos-Soldini María Paula 
Published: February 2024

Abstract

Soybean (Glycine max), a pivotal global agricultural crop, faces significant economic losses from pests and phytopathogenic fungi. To address this, farmers often resort to synthetic pesticides, posing potential risks to health and the environment. In this context, eucalyptol stands out in agriculture for its toxicity to various insects and fungi, with minimal environmental and human health impacts. This study aimed to i) assess the insecticidal activity of eucalyptol against Spodoptera frugiperda JE Smith (Lepidoptera: Noctuidae) and Epicauta atomaria Germar (Coleoptera: Meloidae), and its fungicidal activity against Cercospora kikuchii, Cercospora sojina, and Sclerotium rolfsii; and ii) explore the potential phytotoxic effect of eucalyptol on non-target soybean plants. Eucalyptol demonstrated good fumigant insecticidal activity against S. frugiperda 1st instar larvae (LC50 = 26.9 µL/L air) and E. atomaria adults (LC50 = 34.6 µL/L air), along with moderate fungicidal activity against C. kikuchii and C. sojina (mycelial inhibition halo diameters of 6.0 ± 0.0 mm and 10.0 ± 2.5 mm, respectively, at a concentration of 5 µL/disk). Importantly, eucalyptol exhibited no phytotoxic effects on soybeans. Its potential as a biopesticide for soybean crops, replacing synthetic alternatives, shows promise, though further studies are needed.
Preoperative serum prealbumin levels in predicting postoperative complications and survival in malignant bowel obstruction surgery
Authors: Weng Zongqi , Lai Jinhong , Wang Kangmei , Chen Zishan , Chen Hongbin , Yu Hongxi , Chen Xianqiang , Lin Yuyuan , Lin Mengxin , Pan Jie 
Published: February 2024

Abstract
Purpose This study aims to assess the predictive value of preoperative prealbumin (PA) concentration in cases of Malignant bowel obstruction (MBO) for postoperative complications and long-term survival.
Methods Single-factor and multi-factor logistic regression analyses were performed to identify independent risk factors for severe complications and infectious complications. Simultaneously, single-factor and multi-factor Cox regression analyses were employed to identify independent risk factors for overall survival (OS), and corresponding nomograms were created. Kaplan-Meier survival curves were generated for grouped data with statistically significant differences. The area under the curve (AUC) was compared to assess the testing efficiency of different nutritional indicators for postoperative severe complications.
Results There was a statistically significant difference in the comparison of overall complications and infectious complications between the two groups in different CD grades (p＜0.001). Specifically, the incidence of CD≥3 in the super-low PA group was higher (p＜0.001), and a gradual increase in the severity of overall and infectious complications postoperatively was observed with decreasing PA levels (p＜0.001). PA (p<0.001) and intestinal stent placement (p=0.015) were identified as independent influencing factors for early postoperative severe complications (CD≥3), while PA was an independent influencing factor for postoperative infectious complications (p<0.001). PA, gender, surgical approach, TNM staging, and postoperative chemotherapy were identified as independent predictors of overall survival (OS). Compared to indicators like FPR and AFP, PA demonstrated the highest testing efficiency (AUC=0.888).
Conclusion Preoperative PA has significant predictive value for early postoperative complications and overall survival in MBO,providing new insights into perioperative nutritional intervention and surgical approach selection for MBO patients.
HFTDAO: Hybrid Fuzzy-based Tasmanian Devil Arithmetic Optimization for Trust worthy Data Communication in the WSN
Authors: R Uma Mageswari , TF Michael Raj , M Gowthul Alam M , S Jerald Nirmal Kumar 
Published: February 2024

Abstract

Wireless sensor networks (WSN) play a significant role in various applications as a communication framework in the field of the Internet of things (IoT). Secure data communication over unsteady wireless connections becomes the main concern in WSN. In order to assure reliable and secure data delivery, numerous research works use authentication-based opportunistic routing protocols. However, it is identified that opportunistic routing protocols are more susceptible to cyber security attacks; particularly, Denial of service (DoS) attacks which causes network failures by disrupting the normal operation of the wireless network. Therefore, in this paper, we propose a novel trust-based routing protocol to safeguard the network from DoS attacks by providing better reliability and authenticity to the wireless channels. The proposed hybrid fuzzy-based Tasmanian devil arithmetic optimization (HFTDAO) algorithm analyzes the historic data information of wireless links and selects the optimal routing channel based on link trust. The novelty of the HFTDAO algorithm is, it utilizes the exploration ability of the Tasmanian devil algorithm and the exploitation ability of arithmetic optimization to enhance the searching ability of the algorithm; the exploring behavior is mechanically shifted among them by means of the tendency factor. In contrast to existing routing protocols, the proposed trust-based opportunistic routing protocol enhances the effectiveness of data delivery. The utilization of mutual authentication algorithm avoids invalid or unreliable data communication directed by DoS attacks and thus provides better data integrity. Also, the verification scheme performed before data delivery speeds up the isolation process of the DoS attack. The efficiency of the proposed model is compared with the existing techniques in terms of different performance metrics such as using different performance measures including PDR (Packet Delivery Ratio), the number of verifications, end-to-end latency, and control packet overhead. When compared to other approaches, the proposed HFTDAO algorithm has a very high throughput value, DoS attack identification rate, and packet delivery ratio.
Candiduria in The Patients Visiting at Kathmandu Model Hospital, Nepal
Authors: Shrestha Santosh , Bhandari Nirajan , Gopali Bipin , Pandey Bibek , Thapa Pushkar , Shrestha Basudha , Amatya Niroj Man 
Published: February 2024

Abstract
The effective management of Candiduria depends upon proper identification of Candida species and their antifungal susceptibility test. Therefore, this cross-sectional study is conducted to assess the occurrence of different Candida species in urine and to determine their antifungal susceptibility pattern from productive age group 15-65. The isolation and identification of Candida species from clean catch midstream urine were done by culturing on Sabouraud Dextrose Agar with chloramphenicol followed by germ tube test, sugar fermentation test, chlamydospore production test, and further differentiated by using CHROM agar. The antifungal susceptibility test was done on Muller Hinton Agar with 2% glucose and 0.5 µg/mL methylene blue, and result interpretation was done as recommended to CLSI guidelines (M 44-A2). From 586 urine samples, 45 Candida species were isolated in which the predominant one is C. parapsilosis (14, 31.1%) followed by C. albicans (12, 26.6%). The antifungal susceptibility test showed that fluconazole resistant (29.41%) was comparatively more than voriconazole (21.87%). Since non albicans Candida are emerging pathogen and its antifungal resistant pattern is hiking, it is crucial to incorporate fungus identification in routine testing and identify their antifungal susceptibility pattern to ensure effective treatment and monitor for any antifungal resistance.
Characteristics and outcomes of ECMO cannula-related infections: a European multicenter retrospective study
Authors: Ortuno Sofia , Massart Nicolas , Vidal Charles , de Montmollin Etienne , Bouglé Adrien , Nesseler Nicolas , Bidar Frank , Assouline Benjamin , Masi Paul , Henri Samuel , Hraiech Sami , Rozé Hadrien , Manicone Francesca , Luyt Charles-Edouard 
Published: February 2024

Abstract
Purpose
Only few data regarding epidemiology and management of ECMO cannula-related infections (CRIs) exist. The aim of our study was to describe their epidemiology and prognosis, and to evaluate factors associated with outcome.
Methods
We performed a multicenter retrospective study in 12 European ICUs, including patients with CRI, defined as a clinical suspicion plus a positive bacterial sample of ECMO-cannulation site. Primary objective was to describe CRI characteristics and outcomes. Secondary objectives were to evaluate the rates of infection recurrence, their risk factors, and to evaluate the impact of antimicrobial treatment duration on outcome.
Results
During the study period, 124 patients with CRI (78 having concomitant positive blood culture with the same pathogen) were included. Pathogens responsible for infections were predominantly Enterobacteriaceae, coagulase-negative Staphylococcus and Enterococcusspp., and 40% of episodes were polymicrobial. Rates of infection recurrence was 24% and ICU-mortality rate was 50%. Whereas veno-venous ECMO (as compared to veno-arterial ECMO), and therefore ECMO duration was associated with infection recurrence, characteristics of CRI and its management (and in particular duration of antimicrobial treatment) were not associated with recurrence. Patients with antibiotic course ≤8 days had similar infection recurrence rate and outcomes (including mortality) than patients with prolonged (>8 days) antibiotic course.
Conclusion
CRIs are frequently associated with BSI and frequently polymicrobial. Main risk factor of infection recurrence is ECMO duration. Duration of antimicrobial treatment for CRI ≤8 days is not associated with an increased risk of recurrence or death, as compared to longer treatment.
A Multi-Objective Approach for Optimizing IoT Applications Offloading in Fog-Cloud Environments with NSGA-II
Authors: mokni ibtissem , Yassa Sonia 
Published: February 2024

Abstract
Internet of Things (IoT) applications have gained widespread adoption across diverse sectors such as healthcare, smart agriculture, smart cities, transportation, and water management, leading to a substantial generation of Big Data. To efficiently process this voluminous data, there is a pressing need for a platform capable of handling large quantities. However, real-time applications face challenges in cloud processing due to high latency. Fog computing, serving as a complementary infrastructure to the cloud, emerges as a viable solution by facilitating task processing, networking, and data storage in cloud data centers accessible to mobile users.
Task offloading emerges as a promising fog computing solution to overcome resource constraints in IoT applications. This involves the execution of part or all of mobile applications in the cloud, aiming to enhance execution time and reduce energy consumption. Our research concentrates on optimizing the IoT task offloading problem within heterogeneous environments, considering conflicting constraints. This optimization challenge is formulated as a multi-objective problem, emphasizing energy consumption and latency Quality of Service (QoS) metrics. Our proposed solution, named Tof-NSGAII, is tailored to respect the finite resources of fog computing by adeptly balancing workloads and meeting the latency requirements of IoT tasks.
We have adapted the widely employed meta-heuristic, the non-dominant sorting genetic algorithm (NSGA-II), to generate a set of non-dominated multi-objective task offloading optimization solutions, considering both energy consumption and latency. Experimental results showcase the efficacy of Tof-NSGAII in generating task offloading solutions that judiciously distribute executed tasks between fog and cloud computing environments based on their specific requirements. Additionally, the generated non-dominated solutions demonstrate optimality in terms of energy consumption, boasting an average energy reduction of 12.18\% compared to alternative approaches. Notably, our approach introduces only a marginal increase in latency, amounting to 0.38\%, a difference that can be considered negligible.
Relationship between the Menstrual Cycle and Sexual Activity: Maybe Women Do Not Lose Estrus
Authors: Tarlacı Sultan , Koyuncu Safiye Ayça , Şan Oğuzhan 
Published: February 2024

Abstract
The menstrual cycle and women sexuality have long been an area of ​​research to understand both evolutionary and hormonal influences. This study examined the relationship between menstrual cycle and libido in women with regular menstrual cycles. Two different studies were conducted for this purpose. In the first study, 489 women were surveyed and asked about the day of their menstrual cycle and their libido and sexual activities on the day of the survey. In the second study, 25 women provided a daily diary throughout their one menstrual cycle, and their daily libido scores, whether they masturbated, and rate of initiating sexual activity with their partner were determined. All data were analyzed before and after ovulation and sub-analyses made for periods close to ovulation. We found in both studies were that sexual libido and its behavioral reflections increased before and immediately after ovulation. However, the findings also reveal the complexity of the menstrual cycle and women sexuality.
Dermal papilla cell-derived exosomes promote hair follicle regeneration during wound healing by activating Wnt/β‐catenin signaling pathway
Authors: Shang Yage , Li Mengyang , Zhang Lixia , Han Chao , Shen Kuo , Wang Kejia , Li Yan , Zhang Yue , Luo Liang , Jia Yanhui , Guo Kai , Cai Weixia , Zhang Jian , Wang Xujie , Wang Hongtao , Hu Dahai 
Published: February 2024

Abstract

Hair follicle (HF) regeneration after skin injury remains a major clinical challenge. Dermal papilla cell-derived exosomes (DPC-Exos) have great potential to induce HF neogenesis. However, the role and mechanism of DPC-Exos in HF regeneration during wound healing are still unclear. In this study, the effect of DPC-Exos on fibroblasts in wound healing was explored for the first time. We found that DPC-Exos could promote the proliferation and migration of fibroblasts, and more importantly, enhance the hair-inducing capacity of fibroblasts. The fibroblasts treated with DPC-Exos could induce HF neogenesis in nude mice when combined with neonatal mice epidermal cells. In addition, the results of in vivo experiments showed that DPC-Exos could accelerate wound re-epithelialization, and promote HF regeneration. The expression levels of Wnt pathway transcription factor β-catenin and Lef1 were elevated in fibroblasts and the dermis of skin wounds after DPC-Exos treatment. Taken together, this study proved that DPC-Exos could promote HF regeneration during wound healing by activating fibroblasts and the Wnt/β-catenin signaling pathway, suggesting that DPC-Exos might be a promising therapeutic strategy for skin wound regenerative healing.
A Permutaion Importance Based feature selection method and Deep Learning Model to Detect Phishing Websites
Authors: Zaimi Rania , Hafidi Mohamed , Mahnane Lamia 
Published: February 2024

Abstract
Phishing attacks pose a significant and escalating threat to cybersecurity in recent times. This deceptive scam aims to trick naive users, luring them into visiting harmful websites and sharing sensitive information, including credentials, credit card numbers, and passwords. Consequently, cybercriminals exploit this data for their own gain. As the sophistication and maliciousness of phishing continue to evolve, researchers are earnestly developing multiple anti-phishing solutions in the literature. Among these solutions, those based on deep learning models have gained substantial attention in recent years. This study proposes an intelligent, deep-learning-based mechanism to detect phishing URLs. The proposed system is based on the permutation importance method (PIM) to select the most relevant URL features, and the Smote-Tomek link method to solve the problem of an unbalanced dataset. In addition, four DL models—CNN, LSTM, and two hybrid models (CNN-LSTM and LSTM-CNN)—are tested to identify the more suitable detection model for the phishing field. The experimental results demonstrate the successful functioning of the proposed phishing detection mechanism. It is observed that the proposed mechanism achieved an accuracy ranging from 93.36% to 96.43% without feature selection and data balance across two variants of datasets and different DL classifiers. It also achieved an accuracy ranging from 94.12% to 96.88% with feature selection and data balance. Finally, our phishing detection mechanism is implemented as web application to enhance its usability for web users.
Evaluating the Effect of Bias Correction Methods in Regional Climate Model Outputs for Rainfall- Runoff Modeling In Katar Watershed Ethiopia
Authors: Yersaw Babur Tesfaye , Chane Mulusew Bezabih 
Published: February 2024

Abstract

Identifying a suitable bias correction method is important to provide reliable inputs for evaluation of climate change impact. This study evaluates five precipitation bias correction methods (BCM) and three temperature BCM for Katar catchment. The BCMs were evaluated using several statistical measures such as, bias (PBIAS), root mean squared error (RMSE), mean absolute error (MAE), coefficient of variation (CV), personal correlation coefficient (R2), and relative volume error (RVE). The annual rainfall bias of the models varies between 7.5% and 257.93% suggesting overestimation. The result showed that the methods used to correct bias improve the RCM-simulated rainfall and temperature to a certain degree in terms of frequency and time series based statics. The raw RCM- simulated precipitation overestimates the wet month observed precipitation in all RCM- outputs. All bias correction methods reduce the overestimation of the raw RCM-simulated precipitation in all models. From the result ECDF performed better than the other bias correction methods based on the corrected annual, monthly, and daily rainfall comparison followed by PT, DM, LOCI, and LS. The temperature bias-correction method's effect was insignificant. The performance of raw RCM precipitation and temperature for stream flow was very poor with a value of NSE (0.2), R2 (0.37), RVE (25.69), and MAE (8.17) but the performance was improved by the application of BCM. The ECDF combined with the DM shows the best performance in stream flow simulation with NSE (0.63), R2 (0.64), RVE (-0.43), and MAE (4.78).
Uranium Electrodeposition at Boron-Doped Diamond Electrodes
Authors: Acevedo-González Alexis J. , Peña-Duarte Armando , Lagle Richard M , Drabo Mebougna , Jones Andrew C. , Cabrera Carlos R 
Published: February 2024

Abstract

The uranium electrodeposition process on a boron-doped diamond electrode (BDD) surface at varying potentials as a means of environmental uranium remediation has been studied. The chronoamperometry technique was employed for the electrodeposition process, applying potentials ranging from − 0.60V to -2.00V vs. the reversible hydrogen electrode (RHE). A 2mM uranyl acetate dihydrate (UO2(C2H3O2)2·2H2O) solution in 0.1M KClO4 served as a model uranyl ion (UO22+) source. Analysis using scanning electron microscopy, energy-dispersive X-ray fluorescence spectroscopy, and atomic force microscopy (AFM) confirmed the presence of uranium and the formation of a thin layer on the electrode surface. Roughness measurements obtained through AFM analysis at different applied potentials vs. RHE were compared before and after uranium electrodeposition at BDD electrodes. Additionally, the identification of various uranium oxides resulting from the electrodeposition procedures was conducted using X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy. These analyses revealed the presence of UO2, UO3, and U3O8 on the BDD electrode surface due to the electrochemical deposition process, with a notable proportion of U3O8 observed. Ultimately, the optimal potential for efficient U6+ remediation from aqueous media and the formation of a uniform thin layer conducive to nuclear technology development was determined to be -1.75V vs. RHE.
Governance and the Relationship between Corruption and FDI in Africa: A Threshold regression analysis
Authors: Lakha Bianca , Oyenubi Adeola , Fadiran David , Naik Nimisha 
Published: February 2024

Abstract

Research on the institutional environment, corruption, and FDI highlights an important facilitating relationship between these factors. Competing views on the effect of corruption on FDI vis-à-vis the grabbing hand vs. the helping hand hypotheses has been examined in the literature. It has also been suggested that both hypotheses can co-exist under the assumption that the FDI-corruption relationship depends on the level of institutions. This study revisits this relationship for 34 African countries over the 2005 to 2019 period using the dynamic panel threshold model, which allows for an endogenous threshold variable. In the past, studies that have examined this relationship using a threshold regression approach are either not based exclusively on African countries (where the implication of this relationship is more salient) or use a threshold regression that assumes exogeneity of the threshold variable. This study examines the facilitating nature of various governance measures – political stability, government effectiveness, rule of law and regulatory quality – on the corruption-FDI relationship. The results indicate significant threshold effects. It also shows that while the grabbing hand hypothesis is consistent with the data irrespective of the institutional proxy used, the helping hand hypothesis is sensitive to the choice of governance. These results agree with the strand of literature in support of a weak helping hand hypothesis.
JEL classification: C33, E22, F21, K42, P37
Topological alterations in white matter anatomical networks in cervical dystonia
Authors: Zhang Jiana , Luo Yuhan , Zhong Linchang , Liu Huiming , Yang Zhengkun , Weng Ai , Zhang Yue , Zhang Weixi , Yan Zhicong , Xu Jinping , Liu Gang , Ou Zilin , Peng Kangqiang 
Published: February 2024

Abstract
Background
Accumulating neuroimaging evidence indicates that patients with cervical dystonia (CD) have changes in the cortico-subcortical white matter (WM) bundle. However, whether these patients’ WM structural networks undergo reorganization remains largely unclear. We aimed to investigate topological changes in large-scale WM structural networks in patients with CD compared to healthy controls (HCs), and explore the network changes associated with clinical manifestations.
Methods
Diffusion tensor imaging (DTI) was conducted in 30 patients with CD and 30 HCs, and WM network construction was based on the BNA-246 atlas and deterministic tractography. Based on the graph theoretical analysis, global and local topological properties were calculated and compared between patients with CD and HCs. In addition, the relationship between abnormal topological properties and clinical characteristics was analyzed.
Results
Compared with HCs, patients with CD showed changes in network segregation and resilience, characterized by increased local efficiency and assortativity, respectively. In addition, a significant decrease of network strength was also found in CD patients relative to HCs. No significant correlations were found between altered network properties and clinical characteristics in patients with CD.
Conclusion
Our findings show that extensive reorganization of the large-scale WM structural network exists in patients with CD. However, this reorganization is attributed to dystonia-specific abnormalities or hyperkinetic movements that need further identification.