bluuebunny/crossref_metadata_2025_split huggingface dataset:
Isolation and Whole Genome Sequence Analysis of Cow Mastitis Candida tropicalis
Authors: Fang Weile , Jiang Chenxi , Chen Shupeng , Guo Xiaoquan , Gao Xiaona , Liu Pei , Hu Guoliang , Li Guyue , Liu Ping 
Published: February 2024

Abstract

Candida tropicalis（C. tropicalis）is a zoonotic pathogen that is widespread in the environment and in recent years an increasing number of dairy cows have been infected with the fungus causing mastitis in cows. In this study, the pathogenic bacteria were isolated from the milk of cows with mastitis and their pathogenicity and drug resistance were investigated. Firstly, we identified pathogenic species through bacterial morphological isolation, then used genome sequencing technology to analyze and predict pathogenicity and drug resistance of pathogens, then verified the virulence of pathogens by infecting mice, and finally verified the drug resistance of pathogens through drug sensitivity tests and PCR technology. Our results show that the causative agent of mastitis in cows in this study is C. tropicalis, and genome sequencing analysis indicates that the organism is highly virulent and multi-drug resistant, and is capable of causing organ damage in mice. C. tropicalis is highly sensitive to nystatin and ketoconazole, moderately sensitive to amphotericin B and insensitive to itraconazole, gentamicin, penicillin and ciprofloxacin, and the present study screened for drug resistance genes such as ABC1, CDR1 and CDR2. In conclusion, the C. tropicalis in this study was highly pathogenic and multi-drug resistant. This study provides a theoretical basis for further screening of novel drug resistance genes in C. tropicalis and provides some reference for the selection of drugs for the treatment of fungal dairy mastitis.
A Clinical View on the Palliative Care Challenges for Oncology Patients
Authors: Moiseenko Raisa , Gordiichuk Prokip , Kondratenko Andrii , Kalachov Oleksii , Konysheva Anna , Gordiichuk Mykola , Pogorelov Oleksandr 
Published: February 2024

Abstract

Objectives. To improve the organization and delivery of palliative care for cancer patients based on the work analysis of the Cancer Center for the period from 2018 to 2023.
Methods. From 2018 to 2023, 69,110 patients were grouped as follows: 1st – 36,443 patients of II-III stage, II clinical group, which received complex drug treatment according to the protocol and recommendations of the NCCN (according to nosologies); 2nd - 24,296 patients of IV stage, II clinical group, who received only drug treatment according to these recommendations and the clinical protocol; 3rd – 8,371 patients in IV stage, IV clinical group that received palliative care. Group 3 was further divided into subgroups: a) 3,022 patients who received inpatient palliative care (hospice); b) 5349 patients who received outpatient care.
Results. Over the past two years, there has been a significant increase (p < 0.05) in the number of patients in all groups. In the structure of the second group, the preference of patients with localization of the mammary gland and organs of the abdominal cavity was determined - 14,938 patients (61.48%). The correlation of the contingent of patients who received palliative drug treatment with those who received palliative care was determined.
Conclusion. It is possible to foresee patients receiving inpatient or mobile palliative care. Since there is a clinical course during hospitalization for palliative care, it is possible to foresee a certain set of measures taking into account a specific nosology.
Prediction of weld strength of LTW of Natural plant-based fiber reinforced Polypropylene using RSM, ANN, and ANFIS - a comparative study
Authors: Kapuyanyika Munyaradzi , Ude Albert Uchenna , Chinnasamy Vivekanandhan 
Published: February 2024

Abstract

During Laser Transmission welding (LTW) of thermoplastics reinforced with natural fibers, the constituents of the composite materials affect the properties of the material which relates to the appropriate design of operating parameters for attaining good-quality welds. Material composition affects the amount of laser energy absorbed, thermal properties, and optical properties. All these attributes greatly influence the properties and quality of weld joints formed from the LTW process. Given the wide range of LTW operating parameters that are feasible for joining thermoplastics, it is important to understand the effect of each parameter on important weld attributes such as weld strength and weld width track in a specific parameter design space for a given composite material and be able to predict vital weld properties such as weld strength. In this research paper, the comparison of the predicted weld strength of the LTW of Pure Polypropylene as the transparent part joined to Polypropylene doped with 0.2wt% of carbon black and reinforced with 15wt% oak wood short fibers using an empirical model based on Response Surface Method (RSM) central composite design, Artificial Neural Network (ANN) model and Adaptive Neuro-Fuzzy Inference System (ANFIS) model was done. The coefficient of determination (R2) was (0.90), (0.93), and (0.99) for the RSM model, ANN model, and the ANFIS model respectively. All the prediction models exhibited acceptable mean absolute error percentage and root-mean-square error. The results suggested a good performance in predicting weld strength for the specified materials in the specified parameter design space in this study. ANFIS model was found to give the best performance followed by the ANN model and lastly the RSM model.
Critical influence of aggregate types on the compressive strength of concrete
Authors: Maruyama Ippei , Sugimoto Soi 
Published: February 2024

Abstract
Understanding the role of aggregates in the compressive strength of brittle composites is crucial for optimizing construction material usage. In this study, we employed the rigid-body-spring-network model to determine the compressive strengths of both coarse aggregate and mortar in concrete. Through uniaxial compression loading tests on concrete, considering Young’s modulus and compressive strength of the coarse aggregate as variables, we elucidated the mechanism by which the coarse aggregate’s physical properties influence concrete's compressive strength, illustrated using a straightforward diagram. When the coarse aggregate’s Young's modulus is lower than that of the mortar, the stress transfer path within the mortar bends and cracks more rapidly, significantly lowering strength. Conversely, if the coarse aggregate’s Young’s modulus exceeds that of the mortar, stress becomes concentrated in the aggregate. Considering these aspects, the compressive strength of concrete can be optimized by changing the properties of the mortar according to the properties of the aggregates.
A Study to Assess the Awareness Regarding Suicidal Behaviour of Adolescents Among Mothers of Selected Wards at Angadipuram Panchayat, With a View to Develop an Informational Booklet
Authors: TF Nadha , Thasnim Diya , Binu Dona , Fathima Faby , PK Farsha 
Published: February 2024

Abstract
Background The World Health Organization has defined “adolescents” as persons in the 10 to 19-year age group. Suicidal behaviour is increasingly becoming a phenomenon associated with young people and an important public health issue. However, there are very few studies evaluating impact of young peoples' attitudes towards suicide and suicidal behaviour. Due to the high prevalence of this issue in our society, we took up this study to throw some light upon ways to increase awareness among the mothers regarding suicidal behaviour of adolescents.
Methods Survey research design was adopted. We systematically collected needed information through administration of demographic performa and modified questionnaire to mothers of adolescents. The data was analysed using descriptive and inferential statistics.
Results From the study it was evident that majority of the sample, 89 (89%) were having very poor awareness, 9(9%) had poor awareness and remaining 2 (2%) had moderate awareness regarding suicidal behaviour of adolescents. The Chi- square value is less than table value 0.05 level of significance which reveals that there is a significant association between the awareness of mothers and number of children.
Conclusion Suicide is a major public health issue that warrants attention. It has been found to be one of the leading causes of death in adolescents and youth worldwide (American academy of Child and adolescent psychiatry, 2021, World Health Organization, 2021). Adolescence, being the initial founding years of life, is very critical. Any mental health issue in this phase of life should be taken seriously to prevent further progress in adulthood (Blakemore, 2019). India has the world’s largest adolescent population (approximately 253 million), and every 5th person in India is between 10 and 19 years of age (UNICEF INDIA, 2019).
Enhanced Antibacterial Activity and Structural Characterization of ZnO-Doped MgO Nanocomposites Synthesized via Sol-Gel Technique
Authors: Mohammad Ali M. , Fatah Salar K. , Majeed Mahmood H. , Mohammed Sirwa M. , Mohammed Sulaf M. 
Published: February 2024

Abstract
In this study, nanocomposites of Mg1 − xZnxO (x = 0, 0.1, 0.2, and 0.3) were synthesized using the sol-gel technique. The structural, surface morphological, and antibacterial effects of pure MgO and MgO doped with ZnO were investigated. For structural and morphological evaluations, X-ray diffraction (XRD) and Field emission scanning electron microscopy (FE-SEM) were used. The Rietveld refinement software analysis of XRD data revealed that the phase fraction of MgO exhibits a direct and linear relationship with increasing zinc nitrate concentration. In contrast, the ZnO phase shows an inverse correlation. It was also observed that, as the concentration of ZnO increased, the crystal sizes of the MgO and ZnO phases decreased from 35.87 to 31.29 nm and 46.16 to 41.41 nm, respectively, while their lattice constants increased. The FE-SEM images demonstrated that the particle morphologies of all the samples were similar, with no discernible distinctions. In general, the particles exhibited a small spherical appearance, and their sizes ranged from 73.771 to 76 nm, with irregular agglomeration influenced by the concentration of ZnO. In addition, the synthesized MgO/ZnO nanocomposite exhibited a synergistic antibacterial effect, inhibiting the growth of both Gram-positive Staphylococcus aureus and gram-negative bacteria Escherichia coli. Notably, the rate of Gram-positive and Gram-negative bacterial growth inhibition increased as the concentration of ZnO in the MgO nanocomposite increased.
Light-tracing based surface deformation measurement strategy for large radio telescopes
Authors: Zhang Zihan , Yang Dejin , Ye Qian , Wang Na 
Published: February 2024

Abstract

With the increasing aperture as well as the observation frequency of radio telescopes in the current period, the deformation caused by time-varying loads such as temperature and wind has been emphasized. Existing methods for measuring deformations often fall short in meeting the demands of full attitude coverage, quasi real-time response, and high accuracy. This study introduces a novel geometric-optical measurement approach based on light-tracing. Diverging from traditional methods, this approach doesn't directly measure the surface deformation of the main reflector. Instead, it creates a more easily measurable variable and establishes a mapping relationship between this variable and the main reflector deformation. In this innovative scheme, multiple laser modules are strategically positioned on the main reflector, treating the sub reflector as a spot projection surface. When the panel is displaced, the spot on the projection surface will follow and be displaced. In practice, the main reflector deformation can be solved by recording the position change of the light spots on the projection surface and utilizing the inverse reconstruction model. Besides, effective strategies are proposed to improve the robustness of the scheme. Next, the accuracy and real-time performance of the proposed method are verified through simulations and experiments. Results indicate that the proposed approach presents a fresh perspective to enhance the efficiency and precision of deformation measurements for large-aperture antennas.
Reflexivity and positionality applied to medical practice: an experimental study on implicit gender bias with medical students in a Swiss university
Authors: Arena Francesca , Geiser Elisa , Auer Silva , Clair Carole , Schwarz Joëlle 
Published: February 2024

Abstract

Background
An array of evidence shows how the presence of implicit bias in clinical encounters can negatively impact provider-patient communication, quality of care and ultimately contribute to health inequities. Reflexive practice has been explored as an approach to identify and address implicit bias in healthcare providers, including medical students. At the Lausanne School of Medicine, a clinically integrated module was introduced in 2019 to raise students’ awareness of gender bias in medical practice using a reflexivity and positionality approach. The purpose of this study is to describe the gender bias that were identified by medical students, analysing their types, places and modes of emergence during a clinical encounter. It further explores how positionality supported students’ reflexion on the way in which social position modulates their relationship to patients.
Methods
As part of the teaching activity, medical students individually reflected on gender bias in a specific clinical encounter by answering questions in their electronic portfolio. The questionnaire included a section on positionality. We qualitatively analysed the students’ assignments, applying a thematic analysis framework (n = 76).
Results
Medical students identified and described gender biases occurring at different moments of the clinical encounter (anamnesis (i.e. patient history), physical exam, differential diagnosis, final management). They causally associated these biases with wider social phenomenon such as the gendered division of labour or stereotypes around sexuality and gender. Analysing how students reflected on how their position influenced their relationship with patients, we found that the suggested exercise revealed a major contradiction in the process of medical enculturation: the injunction to be neutral and objective erases the social and cultural context of patients and prevents an understanding of gender bias.
Conclusion
Gender bias are present in the different steps of a clinical consultation and are rooted in broader gendered social representations. We further conclude that the tension between a quest for objectivity and the reality of social encounters should be made explicit to students, because it is constitutive of medical practice.
Incorporating Template-based Contrastive Learning into cognitively inspired, low resource relation extraction
Authors: Zheng yandan , Luu Anh tuan 
Published: February 2024

Abstract

Background From an unstructured text, Relation Extraction (RE) predicts semantic relationships between pairs of entities. The process of labeling tokens and phrases can be very expensive and require a great deal of time and effort. The Low-Resource Relation Extraction (LRE) problem comes into being, is challenging since there are only a limited number of annotated sentences available. Recent research has focused on minimizing the cross-entropy loss between pseudo labels and ground truth or on using external knowledge to make annotations for unlabeled data. Existing methods, however, fail to take into account the semantics of relation types and the information hidden within different relation groups.
Method By drawing inspiration from the process of human interpretation of unstructured documents, we introduce Template-based Contrastive Learning (TempCL). Through the use of template, we limit the model's attention to the semantic information that is contained in a relation. Then we employ a constrastive learning strategy using both group-wise and instance-wise perspectives to leverage shared semantic information within the same relation type to achieve a more coherent semantic representation. Particularly, the proposed group-wise contrastive learning minimizes the discrepancy between the template and original sentences in the same label group and maximizes the difference between those from separate label groups under limited annotation settings.
Results Our experiment results on two public datasets show that our model TempCL achieves state-of-the-art results for low resource relation extraction in comparison to baselines. The relative error reductions range from 0.68 to 1.32%.
Conclusion Our model encourages the feature to be aligned with both the original and template sentences. Using two contrastive losses, we exploit shared semantic information underlying sentences (both original and template) that have the same relation type. We demonstrate that our method reduces the noise caused by tokens that are unrelated and constrains the model's attention to the tokens that are related.
Individual level surrogacy of MRI T2 lesion information for future disease severity: a methodological discussion and application to recent MS Phase II and III trials
Authors: Buchka Stefan , Joachim Havla , Begüm Irmak Ön , Rehms Raphael , Mansmann Ulrich 
Published: February 2024

Abstract

Background:
Individual-level surrogacy (ILS) describes settings where individual-patient information on a biomarker captures information on future patient-relevant clinical outcomes. For persons with relapsing-remitting multiple sclerosis (PwRRMS), whether the number of new or newly enlarged hyperintense lesions in T2 magnetic resonance images (MRI) or the T2 lesions’ volume can act as ILS for disability progression and disease activity is of interest. However, ILS of new T2 lesions for individual PwRRMS has not yet been demonstrated, although new T2 lesions already serve as a primary outcome parameter for pivotal trials.
Methods:
Our synthesis used individual-patient data from ten randomized controlled trials (n = 5673 PwRRMS). Longitudinal data on either the number or volume of new T2 lesions were analyzed as potential ILS for disability progression measured by the expanded disability status scale (EDSS) and disease activity shown by clinical relapses. ILS metrics were calculated: R2A) for the Meta-analytic (MA) and LRF (likelihood reduction factor) for the information theoretic (IT) approach. A simulation study elucidates the approaches’ potential to detect ILS and provides the basis to interpret the results derived from the trial data.
Results:
The simulation study demonstrates good performance for the IT approach. MA algorithms work well when applied to continuous data. When applied to counting data, the results may numerically be unstable. However, transformations of the counting data allow successful calculations with methods for Gaussian data. Analyses following IT methodology provide in all trial-based settings reliable results on ILS and identified two studies with weak ILS for the combination of T2 Volume and EDSS (LRF = 0.21, CI95%: 0.16 – 0.26; LRF = 0.28, CI95%: 0.23 – 0.34).
Conclusion:
The simulation study showed robust and sensitive results for IT and MA when not applied to counting data outcomes-based ILS strategies. The high potential of these algorithms to detect ILS strengthens the interpretation of our findings. Within most arms of ten pivotal MS trials, ILS measures were close to zero. Evidence on the surrogacy of T2 lesion measures and disease progression and activity as a general principle could not be generated. More research using proper designs and methodology is needed.
Assessing the influence of the modifiable areal unit problem on Bayesian disease mapping in Queensland, Australia
Authors: Jahan Farzana , Haque Shovanur , Hogg James , Price Aiden , Hassan Conor , Areed Wala , Thompson Helen , Cameron Jessica , Cramb Susanna 
Published: February 2024

Abstract
Background Spatial data are often aggregated by area to protect the confidentiality of individuals and aid the calculation of pertinent risks and rates. However, the analysis of spatially aggregated data is susceptible to the modifiable areal unit problem (MAUP), which arises when inference varies with boundary or aggregation changes. While the impact of the MAUP has been examined previously, typically these studies have focused on well-populated areas. Understanding how the MAUP behaves when data are sparse is particularly important for countries with less populated areas, such as Australia. This study aims to assess different geographical regions' vulnerability to the MAUP when data are relatively sparse to inform researchers' choice of aggregation level for fitting spatial models.
Methods To understand the impact of the MAUP in Queensland, Australia, the present study investigates inference from simulated lung cancer incidence data using the five levels of spatial aggregation defined by the Australian Statistical Geography Standard. To this end, Bayesian spatial BYM models with and without covariates were fitted.
Results and Conclusion The MAUP impacted inference in the analysis of cancer counts for data aggregated to coarsest areal structures. However, area structures with moderate resolution were not greatly impacted by the MAUP, and offer advantages in terms of data sparsity, computational intensity and availability of data sets.
Income taxation and regional growth: DID evidence from an income tax treatment in Italy
Authors: Bosco Bruno Paolo , Bosco Carlo Federico , Maranzano Paolo 
Published: February 2024

Abstract

This paper offers some fresh empirical evidence about the relation between income taxation and regional growth-related variables. Using the Italian regional income tax treatment of 2007 as a quasi-natural tax experiment, we present various panel data DID estimates of how income per capita and other variables related to economic growth, including labour supply, consumption, and VAT certificates, respond to exogenous income tax changes. Results show that the extensive negative adjustments of response variables measuring supply of labour services offered by taxpayers affected by the treatment is statistically significant, rapid, and strong but not long-time lasting and that treated families reduce in a similar manner their consumption with respect to families in the control (untreated) regions. Analogous adjustment responses characterise the growth of per-capita regional GDP response to tax changes. The estimated aggregate effects are further compared with the spatial-temporal patterns observed for every response variable. Policy issues are also discussed.
JEL codes: C10, C18, C21 H2, E2, E32, E62, C23, C26
LPBSA: Enhancing Optimization Efficiency through Learner Performance-based Behavior and Simulated Annealing
Authors: Hamad Dana Rasul , Rashid Tarik A. 
Published: February 2024

Abstract
This study introduces the LPBSA, an advanced optimization algorithm that combines Learner Performance-based Behavior (LPB) and Simulated Annealing (SA) in a hybrid approach. Emphasizing metaheuristics, the LPBSA addresses and mitigates the challenges associated with traditional LPB methodologies, enhancing convergence, robustness, and adaptability in solving complex optimization problems. Through extensive evaluations using benchmark test functions, the LPBSA demonstrates superior performance compared to LPB and competes favorably with established algorithms such as PSO, FDO, LEO, and GA. Real-world applications underscore the algorithm's promise, with LPBSA outperforming the LEO algorithm in two tested scenarios. Based on the study results many test function results such as TF5 by recording (4.76762333) and some other test functions provided in the result section prove that LPBSA outperforms popular algorithms. This research highlights the efficacy of a hybrid approach in the ongoing evolution of optimization algorithms, showcasing the LPBSA's capacity to navigate diverse optimization landscapes and contribute significantly to addressing intricate optimization challenges.