bluuebunny/crossref_metadata_2025_split huggingface dataset:
Skin adhesive as an adjunct in primary total joint arthroplasty of the lower limb: A retrospective cohort study
Authors: Vial Izziddine Ahmad Ali , Boutros Ihab 
Published: June 2024

Background:
Surgical site infection (SSI) after lower-limb total joint arthroplasty is a complication that is associated with increased morbidity and mortality. Numerous risk factors are known to be linked to SSI.

Patients and Methods:
The wound surveillance data of 408 patients who underwent either a hip or knee arthroplasty between March 1, 2016, and October 31, 2018, inclusive, were retrospectively reviewed at our institution, a big tertiary teaching hospital at Salford Royal Hospital (Manchester, United Kingdom). The patients had undergone a primary elective lower-limb arthroplasty. These patients were selected from the Sunrise electronic patient records. Inclusion criteria were more than 18 years of age.

Results:
Four hundred and eight patients were included in the study. The rate of SSI was 8.3% (34 patients). Body mass index (P = 0.00948) and use of skin adhesive (P = 0.0016) were associated with SSI. There were also some notable absences such as diabetes mellitus, use of immunosuppressive medication, wound leakage <48 h, and hypertension.

Conclusion:
The incidence of SSI was found to be very high compared to the incidence reported in the literature. The high statistical significance shows that the use of skin adhesive in wound closure considerably reduces SSI, and therefore, its use should be recommended.
PATIENT WITH PRIMARY OVARIAN FAILURE DUE TO INTERMEDIATE PREMUTATION OF THE FMR1 GENE USING TRANSDERMAL TESTOSTERONE IN IVF TREATMENT, CASE REPORT AND LITERATURE REVIEW
Authors: Mancilla Hernández Fernando , Lezama Ruvalcaba Jorge L. , Rodríguez Calderón Ricardo , Salazar López-Ortiz Carlos G. , Becerril Rodríguez Paola R. , Rodríguez Verduzco Julio C. 
Published: June 2024

Background Fragile X syndrome (FXS) is a condition of non-Mendelian nucleotide repeats, which is due to the loss of function of the FMR1 gene (Fragile X Mental Retardation 1); it is caused by the hypermethylation of the repetitions of CGG (cytosine-guanine-guanine triple), expanded adjacent to exon 1 of the FMR1 gene; this mutation affects more than 98% of people with SXF. Clinical Case 35-year-old patient. Consulted for primary infertility of 1 year of evolution, relevant biochemical studies were requested, among which he highlighted the result of Anti-Mullerian Hormone of 0.40 ng/mL. By age and diagnosis of low ovarian reserve, it is decided to perform FMR1 mutation analysis in search of the cause of the probable primary ovarian failure, resulting in a premutation with repetition of 49 CGG. It is decided to perform a cycle of controlled ovarian stimulation, with menotropins 300 IU every 24 hours + dydrogesterone 30mg orally to inhibit LH peak, as well as the use of transdermal testosterone 50 mg every 24 hours to improve the ovarian response, obtaining 2 MII oocytes, which are vitrified. It is decided to perform a 2nd cycle of ovarian stimulation with menotropins 300 Units + GnRH antagonist to be able to make embryo transfer. The use of 50mg of transdermal testosterone to improve the result, obtaining 4MII, a total of 6 MII oocytes for the two cycles, ICSI (intracytoplasmic sperm injection) is performed at the 6 oocytes of which 4 embryos were obtained in the blastocyst stage, transferring 1 embryo in fresh, and vitrifying 3, quantification of hCG beta-positive fraction is performed at 10 days post-transfer, obtaining a live newborn, male with a weight of 4,010 kg, Size: 58 cm without complications. Conclusions FMR1 premutation is associated with a risk of reduced ovarian function and premature ovarian failure with the early loss of fertility in 20% of carrier women due to the reduced number of follicles in the ovaries. Transdermal pretreatment of testosterone seems to increase pregnancy and the rates of live births in people considered deficient who undergo ovarian stimulation for IVF.
Features of rural development: modeling and forecasting of the main results
Authors: Быкова М.Л. 
Published: June 2024

В статье рассматриваются особенности развития сельских территорий в современных условиях. Анализ сельскохозяйственной отрасли позволил сформулировать вывод об исключительной важности данного вида экономической деятельности в социально-экономическом росте территорий, поскольку развитие сельского хозяйства определяет уровень продуктовой безопасности государства. Рассмотрены изменения в базовых отраслях специализации сельского хозяйства, а также исследована важность инновационной составляющей в развитии отрасли. Проанализирована помесячная динамика изменения оборота по данному виду деятельности с 2017 г. На основании графического и статистического анализа имеющихся данных была построена экономико-математическая модель изменения показателя во времени с учетом сезонной и случайной компоненты. О значимости и возможности практического применения модели свидетельствуют рассчитанные значения F-критерия и средней процентной ошибки.
This article examines the features of rural development in modern conditions. The analysis of the agricultural sector given in the framework of the work allowed us to formulate a conclusion about the exceptional importance of this type of economic activity in the socio-economic growth of territories, since the development of agriculture determines the level of food security of the state. The changes in the basic branches of agricultural specialization were considered, as well as the importance of the innovative component in the development of the industry was studied. The work also analyzed the monthly dynamics of turnover changes for this type of activity for the period from 2017. Based on the graphical and statistical analysis of the available data, an economic and mathematical model of the change in the indicator over time was built, taking into account the seasonal and random components. The calculated values of the F-criterion and the average percentage error indicate the significance and the possibility of practical application of the model.
Analysis of existing marketing communication channels
Authors: Пальмов С.В. , Болдова Е.И. , Полоскова А.П. 
Published: June 2024

В статье рассматриваются существующие маркетинговые каналы коммуникаций, теоретические основы маркетинговых коммуникаций, их сущность, роль в продвижении. Дается анализ традиционных, цифровых маркетинговых каналов, а также интегрированных маркетинговых коммуникаций. Описываются факторы, влияющие на выбор каналов, оцениваются эффективность различных каналов, методы оптимизации бюджета.
The announcement: this article examines the existing marketing communication channels. Theoretical foundations of marketing communications, their essence, role in promotion, analysis of traditional marketing channels, analysis of digital marketing channels, the essence of integrated marketing communications. The factors influencing the choice of channels are analyzed, the effectiveness of various channels is evaluated, and budget optimization methods are used.
Directions for improving government support for freelancers
Authors: Ахмедова М.Р. , Перова А.Е. 
Published: June 2024

В статье проведен опрос российских фрилансеров на платформе Google Form, выявлены их основные профессии, процентов фрилансеров, не регистрирующих свою деятельность. Проанализированы основные причины нежелания фрилансеров регистрировать свою деятельность. Сделан вывод о влиянии экономической обстановки с начала проведения спецоперации на рынок фриланса.
The article conducted a survey of Russian freelancers on the Google Form platform, identified their main professions, percentages of freelancers who do not register their activities. The main reasons for the reluctance of freelancers to register their activities are analyzed. The conclusion is made about the impact of the economic situation since the beginning of the special operation on the freelance market.
Promoting Sustainable Green Infrastructure: Experimental and Numerical Investigation of Concrete Reinforced with Recycled Steel Fibers
Authors: Ahmad Izhar , Shokouhian Mehdi 
Published: June 2024

Accumulation of waste tires and their respective fast increase are posing a great threat to the environment. Recycled steel fiber (RSF) extracted from the waste tires can be used in reinforced concrete considering proper fiber content and aspect ratio. Current research study aims to investigate the influence of RSF content (0.5, 1.5 and 2.25%) on the mechanical properties such as compressive strength, split tensile and flexural strength of recycled steel fiber reinforced concrete (RSFRC). The study also focused on developing numerical models such as fracture-plastic constitutive models using ATENA to validate the experimental results. The study was further extended by developing a slab model as a bus pad to find the behavior of RSFRC bus pad in response to the service loads and soil stiffness. In Baltimore City, inadequate design of bus pads posed strength and serviceability problems and needed to be investigated. From the test results, it was found that RSFRC mixture containing 1.5% RSF exhibited optimized behavior. Test results showed that 28-day compressive, split tensile and flexural strength increased by 10.7, 39.3, and 10.4%, respectively for the RSFRC mixture containing 1.5% RSF as compared to the control mixture without RSF and other RSF containing mixtures. The Numerical model was developed and validated using experimental data. Various models of bus pads were then analyzed, focusing on their maximum load-bearing capacity and flexural toughness. It was observed that the maximum load-bearing capacity and flexural toughness of the bus pads increased with the use of RSFRC. These findings offer valuable insights for the construction industry, facilitating the efficient utilization of RSFRC in concrete applications.

Received: 16 March 2024 | Revised: 20 May 2024 | Accepted: 31 May 2024

Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.

Data Availability Statement
Data available on request from the corresponding author upon reasonable request.

Author Contribution Statement
Izhar Ahmad: Methodology, Software, Validation, Formal analysis, Investigation, Writing - original draft, Writing - review & editing, Visualization; Mehdi Shokouhian: Conceptualization, Methodology, Software, Resources, Writing - original draft, Writing - review & editing, Supervision, Project administration.
Chinese Cultural and Opera Stage Architectural Design for Urbanization Henan, China
Authors: Chen Chen , Arus Baharudin Bin Mohd 
Published: June 2024

Background and Purpose: Urbanization in Henan, China has rapidly transformed the landscape, posing challenges to preserving traditional cultural elements like Chinese cultural and opera stages. This study aimed to provide qualitative insights into integrating traditional cultural/opera architectural design with modern urban development in Henan. Methods: Semi-structured interviews were conducted with 10 Henan residents to gather perspectives and experiences. Interview data was thematically analysed. Findings: Residents highly valued traditional cultural/opera stage design, indicating strong cultural interconnectedness. However, challenges were identified including commercial pressure in development, implying difficulty balancing economic growth and cultural preservation. Community participation was mixed with some active engagement. Environmental sustainability concerns and financial/institutional capacity constraints highlighted the need for collaborative approaches. Conclusion and Implications: Traditional cultural elements retain deep meaning for Henan residents amidst rapid urbanization. Preserving these traditions while enabling modernization will require overcoming multiple complex challenges across commercial, environmental, social, and institutional dimensions. Findings indicate that collaborative, multi-stakeholder urban planning approaches are needed to integrate cultural preservation with sustainable growth in Chinese cities undergoing rapid development. Study insights on resident perspectives and challenges can inform policies and frameworks to effectively balance economic, environmental, and cultural priorities.
Creating and Managing Green Residential Interior Design in Baotou Inner Mongolia, China
Authors: Yongxia Cao , Nasi Nadia Binti Mohd 
Published: June 2024

Purpose/Background: As sustainability garners global attention, exploring green design in residential interiors is significant. This study examined the creation and management of green residential design in Baotou, China. Environmentally conscious interior design can improve residential satisfaction, health, and conservation. Methods: A qualitative approach involved semi-structured interviews with Baotou residents to gain insights into experiences with and perceptions of green residential design. Detailed interviews explored specific sustainable features residents valued along with challenges faced. Interview transcripts were systematically coded and subjected to rigorous thematic analysis. Findings: Analysis highlighted the rationale for implementing green elements in Baotou and their impacts on residential communities, individual wellbeing, and the environment. Findings offer concrete implications for stakeholders including architects, designers, and property managers seeking to create eco-conscious interiors. Conclusions: Dynamic policies on green design pose constraints to consistent implementation, impacting the feasibility of proposed decorative solutions. Still, findings demonstrate clear connections between sustainable features and increased residential quality, which can inform environmentally friendly urban development. Ongoing legal analysis and community consultation is critically needed to adapt strategies while meeting residents' needs.
The Effect of Organizational Virtuousness on Employees’ Innovative Behavior: The Role of Moderating and Mediating Variables
Authors: Sabti Yousif Mousa , Hisnawi Salih M AL , AlMousawi Kawthar Mowaffak Jaber , Radhi Aeshah Hasan 
Published: June 2024

This objective of the study is to assess the association between OV and IB. Furthermore, the study scrutinizes the mediating effect of thriving between OV and IB. Moreover, this study also examines the moderating effect of CSE between thriving and IB. A quantitative also cross sectional design was used. Data was collected from to test the proposed 509 respondents from high-tech construction and manufacturing industries of Iraq. The findings shown that OV has a positive association with innovative behavior. The mediation result also was significant. The findings shown that CSE weakened the association between thriving and IB. In the end, theoretical and practices implications was discussed with future recommendation.
Development and Validation of an Ensemble Learning Risk Model for Sepsis After Abdominal Surgery
Authors: Shu Xin , Li Yujie , Zhu Yiziting , Yang Zhiyong , Liu Xiang , Hu Xiaoyan , Yang Chunyong , Zhao Lei , Zhu Tao , Chen Yuwen , Yi Bin 
Published: June 2024

IntroductionThough the importance raised attention, the clinical applications of methods for screening high-risk patients of sepsis after abdominal surgery were restricted. Therefore, we aimed to develop and validate models to screening high-risk patients of sepsis after abdominal surgery based on machine learning with routine variables.Material and methodsThe whole dataset was composed of three representative academic hospitals in China and Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Routine clinical variables were implemented for model development. Boruta was applied for feature selection. Afterwards, ensemble learning and other eight conventional algorithms were used for model fitting and validation based on all features and selected features. The area under curves of the receiver operating characteristic curves (ROCAUCs), sensitivity, specificity, F1 score, accuracy, Net reclassification index (NRI), integrated discrimination improvement (IDI), Decision Curve Analysis (DCA), and calibration curves were used for model evaluation.ResultsA total of 955 patients undergoing abdominal surgery were finally analyzed (sepsis:285, non-sepsis:670). After feature selection, the ensemble learning model constructed by integrating k-Nearest Neighbor (KNN) and Support Vector Machine (SVM), yielded the ROCAUC of 0.892(0.841-0.944), the accuracy of 85.0% on the test data, and the ROCAUC of 0.782(0.727-0.838), the accuracy of 68.1% on the validation data, which performed best. Albumin, ASA score, Neutrophil-lymphocyte ratio, age, and glucose were the top features associated with postoperative sepsis by KNN and SVM.ConclusionsWe developed a new and potential generalizable model to preoperatively screening the high-risk patients of sepsis after abdominal surgery with the advantages of a representative training cohort and routine variables.
Analysis of workshop safety and productivity improvement in an engineering workshop
Authors: Igbokwe Nkemkonam Chidiebube  , Ibekwe Chukwuemeka John  , Echetabu Chinecherem Perpetual  , Kalu Chijioke Andrew  , Mba Wilfred Chukwuemeka  
Published: June 2024

This study carries out an analysis of workshop safety and productivity improvement in an engineering workshop in a University setting. The problem stems from observations made during students’ workshop practicals, where concerns regarding fatigue, pain and low productivity were noted. To address these issues, a mixed-methods approach was employed, including surveys, interviews, and observation checklists, to gather data from 367 engineering students. Demographic analysis revealed that a significant proportion of respondents were final year students (58%), with varying levels of workshop usage. Findings also showed that there is a mixed view among students regarding the workshop environment. While a majority perceive the workshop as organised and efficient (58.1% agree), concerns exist regarding cleanliness (only 35.5% agree) and tool accessibility (only 32.3% agree). Safety perceptions reveal that while most students (83.9%) reported never experiencing musculoskeletal injuries, only 48.3% feel confident in the workshop’s safety. Furthermore, productivity challenges are evident, with a significant number of students (45.2%) finding it difficult to complete project in the workshop. Based on these findings, recommendations are proposed to address identified concerns, including improvements in workshop organization, maintenance, safety measures, and productivity enhancements, implementing these recommendations can contribute to creating a safer, more efficient, and student-friendly workshop environment.
Keywords: Workshop Safety, Productivity Improvement, Engineering Students, Engineering Workshop.
The role of Blockchain technology in enhancing transparency and trust in green finance markets
Authors: Ezekiel Onyekachukwu Udeh  , Prisca Amajuoyi  , Kudirat Bukola Adeusi  , Anwulika Ogechukwu Scott  
Published: June 2024

This study explores the transformative potential of blockchain technology in green finance, aiming to assess how it enhances transparency, efficiency, and trust within the sector. Employing a systematic literature review and content analysis, the research scrutinizes peer-reviewed journals, industry reports, and case studies to elucidate blockchain's impact on sustainable financial practices. The methodology focuses on identifying the benefits, challenges, and strategic implications of blockchain applications in green finance, guided by specific inclusion and exclusion criteria to ensure the relevance and quality of the literature analyzed. Key findings reveal that blockchain technology significantly contributes to the transparency and efficiency of green finance mechanisms, such as green bonds and sustainability-linked loans, by providing immutable, transparent, and secure transaction records. This technological integration fosters trust among stakeholders, including investors, regulators, and beneficiaries, and addresses traditional challenges faced by green finance, such as lack of transparency and high transaction costs. The study underscores blockchain's role as a catalyst for change in the future of green finance, advocating for the development of supportive regulatory frameworks and international collaboration to fully harness its potential. Finally, the research offers strategic recommendations for enhancing transparency and trust in green finance through blockchain technology and identifies areas for future research, including the exploration of emerging technologies and the socio-economic implications of blockchain in sustainable finance. This study contributes to the ongoing discourse on leveraging blockchain technology to advance environmental sustainability goals within the financial sector.
Keywords: Blockchain Technology, Green Finance, Transparency and Trust, Sustainable Financial Practices.
Addressing class imbalance in soil movement predictions
Authors: Kumar Praveen , Priyanka Priyanka , Uday Kala Venkata , Dutt Varun 
Published: June 2024

Abstract. Landslides threaten human life and infrastructure, resulting in fatalities and economic losses. Monitoring stations provide valuable data for predicting soil movement, which is crucial in mitigating this threat. Accurately predicting soil movement from monitoring data is challenging due to its complexity and inherent class imbalance. This study proposes developing machine learning (ML) models with oversampling techniques to address the class imbalance issue and develop a robust soil movement prediction system. The dataset, comprising 2 years (2019–2021) of monitoring data from a landslide in Uttarakhand, has a 70:30 ratio of training and testing data. To tackle the class imbalance problem, various oversampling techniques, including the synthetic minority oversampling technique (SMOTE), K-means SMOTE, borderline-SMOTE, and adaptive SMOTE (ADASYN), were applied to the training dataset. Several ML models, namely random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), adaptive boosting (AdaBoost), category boosting (CatBoost), long short-term memory (LSTM), multilayer perceptron (MLP), and a dynamic ensemble, were trained and compared for soil movement prediction. A 5-fold cross-validation method was applied to optimize the ML models on the training data, and the models were tested on the testing set. Among these ML models, the dynamic ensemble model with K-means SMOTE performed the best in testing, with an accuracy, precision, and recall rate of 0.995, 0.995, and 0.995, respectively, and an F1 score of 0.995. Additionally, models without oversampling exhibited poor performance in training and testing, highlighting the importance of incorporating oversampling techniques to enhance predictive capabilities.