bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing Brain Tumor Recognition with Ensemble support Vector-based Local Coati Algorithm and CNN Feature Extraction
Authors: Sumithra A. , M Joe Prathap P , A Karthikeyan , S Dhanasekaran . 
Published: January 2024

Abstract
Nowadays, brain tumor (BT) recognition has become a common phenomenon in the healthcare industry. In the medical system,BT identification and classification can take a significant part in the diagnostics and considerations of the patients. BT is characterized as an abnormal mass of tissue in which the cells proliferate unexpectedly with no control over cell proliferation. In recent years, improvements in machine learning (ML), particularly deep learning (DL) procedures, have shown significant potential for mechanizing and improving these undertakings by utilizing medical imaging information. Also, we examine the difficulties and probabilities in this field, including information shortage, model interpretability, and moral contemplations. To overcome these challenges Ensemble support Vector-based Local Coati (ESV-LC) Algorithm is employed to identify and classify the brain tumor disease in the patients. For optimal classification, the features need to be extracted and this can be achieved by employing the Convolutional Neural network (CNN). To accurately classify BT, Ensemble Support Vector Machine (ESVM) is involved, which enhances classification performance, and hyperparameter tuning is performed through Local Search Coati Optimization. The Brain Tumor Image Dataset and Figshare Brain Tumor dataset are utilized for BT classification and identification. The performance metrics like Accuracy, Precision, Sensitivity, Specificity, and F1-score are to be evaluated, where the accuracy achieves the value of 98.3%, sensitivity of 97.6%, precision of 97.7%, specificity of 98.1%, and F1-score of 96.7% respectively.
Adaptation to mercury stress by nitrogen-fixing bacteria is driven by horizontal gene transfer and enhanced gene expression of the Mer operon
Authors: Paape Timothy , Bhat Aditi , Sharma Reena , Desigan Kumaran , Lucas M. Mercedes , Mishra Ankita , Bowers Robert M. , Woyke Tanja , Epstein Brendan , Tiffin Peter 
Published: January 2024

Abstract
Background: Mercury (Hg) is highly toxic and has the potential to cause severe health problems for humans and foraging animals when transported into edible plant parts. Soil rhizobia that form symbiosis with legumes may possess mechanisms to prevent heavy metal translocation from roots to shoots in plants by exporting metals from nodules or compartmentalizing metal ions inside nodules. We sequenced the genomes of Sinorhizobium medicae and Rhizobium leguminosarum with high variation in Hg-tolerance to identify differences between low and high Hg-tolerant strains. While independent mercury reductase A (merA) genes are prevalent in a-proteobacteria, Mer operons are rare and often vary in their gene organization.
Results: Our analyses identified multiple structurally conserved merA homologs in the genomes of S. medicae, but only the strains that possessed a Mer operon exhibited hypertolerance to Hg. RNAseq analysis revealed nearly all genes in the Mer operon were significantly up-regulated in response to Hg stress in free-living conditions and in nodules. In both free-living and nodule environments, we found the Hg-tolerant strains with a Mer operon exhibited the fewest number of differentially expressed genes (DEGs) in the genome, indicating a rapid and efficient detoxification of Hg2+ from the cells that reduced general stress responses to the Hg-treatment. Expression changes in S. medicae while inside of nodules showed that both rhizobia strain and host-plant tolerance affected the number of DEGs. Aside from Mer operon genes, nif genes which are involved in nitrogenase activity in S. medicae showed significant up-regulation in the most Hg-tolerant strain while inside the most Hg-accumulating host-plant, indicating a genotype-by-genotype interaction that influences nitrogen-fixation under stress conditions. Transfer of the Mer operon to low-tolerant strains resulted in an immediate increase in Hg tolerance, indicating that the operon is solely necessary to confer hypertolerance to Hg, despite paralogous merA genes present elsewhere in the genome.
Conclusions: Mercury reductase operons (Mer) have not been previously reported in nitrogen-fixing rhizobia. This study demonstrates a pivotal role of the Mer operon in effective mercury detoxification and hypertolerance in nitrogen-fixing rhizobia. This finding has major implications not only for soil bioremediation, but also host plants growing in mercury contaminated soils.
Research on a capacitive particle analysis smoke detector
Authors: Wang Boqiang , Zhao Xuzeng , Zhang Yiyong , Song Zigang , Wang Zhuogang 
Published: January 2024

Abstract
Smoke detectors face the challenges of increasing accuracy, sensitivity, and high reliability in complex use environments to ensure the timeliness, accuracy, and reliability of very early fire detection. The improvement and innovation of the principle and algorithm for smoke particle concentration detection provide opportunities for improving the performance of the detector. This study represents a new refinement of the smoke concentration detection principle based on capacitive detection of cell structures, and detection signals are processed by a multiscale smoke particle concentration detection algorithm to calculate smoke concentration. Through experiments, it was found that the detector provides effective detection of smoke particle concentrations ranging from 0 to 10% obs/m; moreover, when the detection accuracy is greater than a certain number of parts per million (PPM), the sensitivity of the detector can reach the PPM level; furthermore, the detector can detect smoke particle concentrations higher than the PPM level accuracy even in an environment with a certain concentration of petroliferous and dust particles of different sizes.
The suspension control method for a 3DOF electromagnetic levitation suspended train
Authors: Yi Liu , Guo-qing Liu , Fang-heng Jiu , Long Zhang , Jin-fa Deng , Yuan-hao Zhao , Hao Shen 
Published: January 2024

Abstract
Most of the running wheels on existing suspension trains use rubber wheels. However, the wear and tear of rubber tires after long-term operation can affect the safety of train operation, and frequent replacement will increase operational costs. To address the above issues, a new suspended structure for maglev trains based on electromagnetic levitation was designed, and this new suspension method was investigated. Firstly, the dynamic characteristics of the bogie structure were modeled and analyzed in the Cartesian coordinate system, and a decoupling control algorithm was designed to independently control the steering attitude angle and the suspension height. Secondly, to address the issue of model inaccuracy caused by simplification in the dynamic modeling process, a fuzzy sliding mode control strategy was introduced. In order to verify the suppression effect of fuzzy sliding mode control on system oscillation, a fuzzy sliding mode control model and a sliding mode control simulation model were set up. The simulation results showed that compared with traditional sliding mode control, fuzzy sliding mode control can greatly suppress oscillation phenomena.Finally, the correctness of suspension control strategy was verified through the construction of a scaled experimental model of the new suspended maglev train based on electromagnetic levitation.
Ninja Turtles: high mobility and successful passage through common barriers to movement in a semi-terrestrial freshwater turtle
Authors: Dowling James M , Nordberg Eric J , Bower Deborah S 
Published: January 2024

Abstract
Anthropogenic landscape change due to urbanisation, agriculture and resource extraction inevitably results in linear barriers within the landscape. Artificial linear structures such as roads, fences, levees, and dams limit the movement of some species and further fragment residual habitat. In this study, we investigated the ability of Eastern long-necked turtles (Chelodina longicollis) to cross various terrestrial obstacles commonly encountered in their habitat. We tested two types of fences (chicken wire and exclusion fencing) commonly used in agricultural systems and three sizes of rocks (gravel, gabion, and large boulders) often used for road construction, erosion control, and waterway stabilisation. We examined the success rates of turtles in crossing obstacles, the effect of fatigue on crossing attempts, and the impact of individual boldness on movement behaviour. Turtles displayed high success rates in crossing gravel (85.4%), gabion (86%), boulders (73.3%) and hinged joint exclusion fencing (94.7%). Chicken wire style wire netting had no successful crossings (0%) despite 276 attempts. A significant fatigue effect was observed throughout the experiment, with turtles making an average of 3.94 (± 4.93 SE) fewer attempts at the end of the experiment (day eighteen) as opposed to day one. Bolder turtles were faster at crossing obstacles, however, boldness had no bearing on obstacle-crossing success. These results highlight the need for thoughtful selection of waterway and wetland infrastructure and the fatiguing impact of constant exposure to anthropogenic barriers for wildlife.
Preparation and Characterization of a Latent Reactive Organo-phosphor us-nitrogen Flame Retardant and its Applications in Polylactic acid Syst ems
Authors: 罗 越峰 , 温 桦浩 , 陈 卓玉 , 廖 正福 
Published: January 2024

Abstract
In this study, an organophosphorus-nitrogen compound with latent reactive flame retardant properties(LROPN) were prepared by a facile method using 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide(DOPO), 4,4 ′-diphenylmethane diisocyanate(MDI) and ethanol as raw materials. The structure of the resulted compound were characterized by infrared spectroscopy (FTIR) and nuclear magnetic resonance (1H-NMR). The performances of LROPN used for Polylactic acid (PLA) were investigatd by the technologies of vertical combustion (UL-94) and limiting oxygen index (LOI) test. The results showed that adding LROPN into PLA matrix could significantly improve the flame retardancy of PLA. The LROPN addition of 8(wt)% could reach UL-94 V0 level, and the LOI increased from 19.5% to more than 26%. The TG-FTIR spetra of LROPN indicated that LROPN can deblock at around temperature of 180oC, which indicating LROPN have latent reactivity. The TG-DTA data showed that the maximum weight lost peak LROPN/PLA systems occured at temperature around 363 oC, and the amount of the residue carbon reached 3.93% when the content of LROPN was 8(wt)%. The scanning electron microscopy(SEM) morphologies showed that the addition of LROPN helped to reduce the melt driping of LROPN/PLA systems. The mechanism of flame retardant was investiated based on the TG-FTIR spetra of LROPN, the TG-DTA data of LROPN/PLA systems, and SEM morphologies of residue carbon. The flame retardancy mechanism of LROPN included the combination of free radical suppression and inert gas in the gas phase, and the barrier effect of coke residue in the condensed phase.
Italian Medical professionals Practices, Attitudes and Knowledge in Travel medicine (IMPAKT): a national survey protocol
Authors: Baglivo Francesco , De Angelis Luigi , Vannini Federico , Agostini Antonello , Todaro Antonio , Torri Eleonora , Lopez Giulio Alberto Gianolio , Fui Margherita , Tomasi Alberto , Rizzo Caterina 
Published: January 2024

Abstract
Introduction:
The evolving global health landscape highlights the importance of travel medicine, making it necessary for healthcare professionals to understand the epidemiologic profiles among varied traveler populations and keep themselves updated in this rapidly changing field.
However, in Italy, travel medicine clinics have significant gaps in resource allocation, staff training, and infrastructure. This is the protocol of a cross-sectional study that aims to create and validate a questionnaire to assess the knowledge, attitudes, and practices of healthcare professionals in travel medicine in Italy. The final goal is to provide a tool to evaluate the state of travel medicine, guide training initiatives, and monitor trends over time.
Methods:
The study population consists of healthcare professionals who practice travel medicine in Italy. The questionnaire will be developed by adapting an existing English survey and conducting a scoping review to align the questionnaire with contemporary scientific discourse. The validation process includes face validity, content validity, and expert evaluation. The sample size, determined through power analysis, ranges from 218 to 278 participants. The questionnaire will undergo a pilot test on a smaller sample size (10% of the total) to identify and address any issues. Statistical analysis will include central tendency and dispersion measures, categorical summaries, group comparisons, and regressions.
This research received ethical approval and informed consent will be collected from all participants.
Discussion:
This cross-sectional study will guide strategic planning and targeting training and awareness activities in areas deemed most critical or lacking.
The study's structured approach and periodic assessments will facilitate the identification of educational gaps, the dissemination of best practices, and the overall improvement of healthcare services for travelers in Italy.
Safety and Feasibility of Hippocampal Sparing Cranial Radiation in Acute Lymphoblastic Leukaemia Patients- A prospective study
Authors: Yadala Ambedkar , Mukherji Ashutosh , Neelakandan Vijayaprabhu , Karunanithi Arivazhagan. , Dubashi Biswajit , Menon Vikas , Elumalai Thiraviyam , Bharathi Deepak , Loganathan Vignesh , Gundapuneedi Bhargav Shreeram 
Published: January 2024

Abstract
Introduction:Acute lymphoblastic leukemia (ALL) constitutes a significant portion of pediatric malignancies, with CNS relapse posing a considerable threat to patient outcomes. While prophylactic cranial irradiation (PCI) has been utilized to mitigate CNS relapse, it is associated with neurocognitive side effects. This study explores the feasibility and safety of using Volumetric Arc Therapy (VMAT) with hippocampal sparing during cranial radiation therapy for ALL patients, aiming to reduce these side effects.
Methods:This prospective observational study included pediatric and young adult ALL patients in remission. Hippocampal sparing was achieved using VMAT, and neurocognitive assessments were performed at baseline, 6 months, 1 year, and, to a limited extent, 4 years post-treatment.
Results:VMAT enabled precise hippocampal sparing with minimal dose impact on the hippocampus. There were no observed brain relapses among the patients in this study. Neurocognitive assessments demonstrated an maintained IQ scores over time, with no decline in neurocognitive funtions
Conclusion:This study highlights the potential of VMAT with hippocampal sparing as a promising approach to cranial radiation therapy for ALL patients in reducing the risk of neurocognitive side effects. The absence of brain relapses is encouraging, although larger studies are needed for conclusive evidence. The preservation of neurocognitive function may be attributed to the reduced radiation dose to the hippocampal region.
Lump-Type and Bell-shaped Solitons to the (2+1)-Dimensional ExtendedKadomtsev-Petviashvili Dynamical Equation Under Generaland Positive Quadratic Polynomial Functions
Authors: Aliyu Aliyu Isa , Ozsahin Dilber Uzun 
Published: January 2024

Abstract
In this article, we investigate lump-type solutions of the new integrable time-dependent coefficient (2+1)-dimensional Kadomtsev-Petviashvili equation by employing the Hirota bilinear technique and a suitable ansatz. This equation models the propagation of small-amplitude surface waves in large channels or straits with slowly varying width, depth, and non-vanishing vorticity. Utilizing the Bell’s polynomials approach, we successfully derive the bilinear form of the equation. Initially, we identify a general form of the quadratic function solution for the bilinear form and subsequently expand it as the sum of squares of linear functions satisfying specific conditions. Notably, we obtain two lump-type and a bell-shaped soliton solutions of the equation, which, to our knowledge, are reported for the first time in the literature. We discuss and represent the physical interpretation of the results graphically.
Does Economic Freedom Matter in Tax Evasion? Empirical Evidence from Asian Countries
Authors: Rashid Md. Harun Ur , Islam Azharul 
Published: January 2024

Abstract
The heterogeneity of Asian governance—stemming from poor administration and tax evasion—affects the business climate, which in turn, causes underinvestment and low tax-to-GDP ratios in the private sector. Due to a dearth of research on tax evasion in Asian countries, this study aims to investigate the relationship between economic freedom and tax evasion. To this end, this study draws upon the socioeconomic theory and applies a variety of econometric methods to analyze data comprising 414 observations from 23 Asian countries between 2001 and 2018. The empirical analysis revealed that the rate of tax evasion is negatively correlated with the level of economic freedom. More specifically, higher government integrity, lower fiscal freedom (tax rate), higher monetary freedom, and investment freedom significantly reduce tax evasion. The findings suggest that Asian governments undertake a robust corporate governance strategy to promote economic freedom and enable stockholders to protect their rights and influence the decision-making process of taxpayers in a bid to reduce tax evasion to a significant level. Moreover, the findings offer valuable insights to governments, tax authorities, and researchers in the formulation of economic policies geared at reducing tax evasion.
JEL Classification: H26, O17, A14
Predictive Modeling of ETO Across Iranian Climates: An ANN and Hybrid Approach
Authors: Bidabadi Misagh , Mashal Mahmoud , Azadegan Behzad , Bidabadi Maedeh 
Published: January 2024

Abstract
Evapotranspiration is an essential component of the hydraulic cycle and is a crucial topic for water resource management. This study focuses on modeling daily reference crop evapotranspiration using an artificial neural network and a genetic algorithm in three stations: Ahvaz (dry climate), Saghez (semi-humid and dry climate), and Sardasht (humid climate). The study uses daily meteorological data from 2011 to 2020, including temperature, humidity, sunshine hours, and wind speed. The PMO-56 method is chosen as the modeling objective. The modeling process is investigated under various data scarcity conditions to determine the superior model in each scenario. The comparison of results between different models is based on Root Mean Squared Error (RMSE) and correlation coefficient (R). The results show that the best outcomes are achieved using four input parameters and the whale optimization algorithm approach. Also, ANN-WOA31, ANN-WOA21, and ANN-WOA11 models had the highest estimates in the Ahvaz station in different input conditions. ANN-WOA31, ANN-WOA24, and ANN-WOA11 models were the best in the Saghez station, and ANN-WOA33, ANN-WOA21, and ANN-WOA11 models performed best in Sardasht station with different input combinations. Furthermore, it is observed that with only the temperature parameter and using either an artificial neural network, genetic algorithm, or whale optimization algorithm method, good results can be obtained in all three stations. Following this, humidity and solar radiation can significantly influence the results, while wind speed alone does not substantially impact. Additionally, in all cases, the whale optimization algorithm consistently outperforms the other models in producing better results.
Comparative Effect of Chemotherapy and Non-chemotherapy Treatments on the Survival of Breast Cancer Patients at Different Stages: A SEER Cross-Sectional Based Study
Authors: Kaindal Sonia , B Venkataramana 
Published: January 2024

Abstract
The primary cause of fatalities due to cancer in women is breast cancer. The research’s objective is to determine the comparative effect of chemotherapy and non-chemotherapy on breast cancer outcomes observed in patients at different stages. The study aimed to clarify the potential differences in treatment effectiveness depending on the cancer stage. A total of 446,806 cancer patients were contained in the data set. Between 2011 and 2015 years 316,557 cancer patients were found. Chi-square tests were conducted to analyze statistical differences in demographic characteristics and clinical results between chemotherapy and non-chemotherapy patients. Kaplan-Meier analysis and log-rank tests are used to evaluate the results of different types of treatment. Multiple Cox regression was used to compare the overall and specific survival. In the model, the relationship between the patient’s marital status, age, race, tumor type, ER, PR, HER2, nodes, and primary locations have significantly influenced the overall survival rate (OS) and the specific survival rate (BCSS) for breast cancer in contrast to mastectomy. Chemotherapy significantly lowers the death rate in both overall survival (OS) and breast cancer-specific survival (BCSS) (HR=0.719, 95 percent CI=0.696-0.743; OS: HR=0.519, 95 percent CI=0.507-0.532, p<0.001). We observed that married patients receiving chemotherapy have significantly improved survival, highlighting the potential impact of marriage on prognosis. Analysis used secondary data available from the Surveillance, Epidemiology, and End Results (SEER) database.
Application of computer vision based light sensing image processing in industrial heritage landscape regeneration design
Authors: Huang Xuan , Li Wanying 
Published: January 2024

Abstract

Industrial heritage is an important relic of human civilization, with significant historical, cultural, and social value. However, due to the frequent abandonment and neglect of industrial heritage, it gradually crumbles and disappears. Therefore, it is crucial to design and protect industrial heritage through regeneration. This article proposes a visualization technology based on computer vision algorithms for the application of industrial heritage landscape regeneration design. This method mainly includes four steps: image acquisition, image processing, visualization, and design feedback. Firstly, high-precision image acquisition devices such as drones are used to obtain high-definition images of industrial heritage, and then computer vision algorithms are used for image processing to extract key features and spatial information of industrial heritage. Next, visualization technology is used to display the processed images and data for designers to carry out landscape regeneration design. Finally, through design feedback, we continuously optimize and improve the design scheme to achieve efficient, accurate, and refined industrial heritage landscape regeneration design. The research results of this article indicate that visualization technology based on computer vision algorithms can effectively improve the efficiency and accuracy of industrial heritage landscape regeneration design.