bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Factors Related to National Health Insurance Participation in Rungan Barat District
Authors: Wilson Wilson , Noor Zairin , Shadiqi Muhammad Abdan , Febriana Silvia Kristanti Tri , Ilmi Bahrul
Published: June 2024

Target of the 2020-2024 RPJMN is targeting NHI membership of 98%. The data shows that West Rungan District is the area with the lowest coverage in Gunung Mas Regency as 36.35% in 2022. The study purposed to analyze the factors related to National Health Insurance membership in West Rungan District. The study used an analytic survey method with a cross sectional design. The population of this research is the people who live in West Rungan District, Gunung Mas Regency with a sample of 109 people who were determined using non-probability sampling with accidental sampling technique. Data were taken from primary data using a questionnaire. Data were analyzed by chi square test and multiple logistic regression. The chi square test shows the p-value between family income (p=0.001 < α 0.05), level of knowledge (p=0.323 >α 0.05), level of education (p=0.062 >α 0.05), number of family members (p=0.751 >α 0.05) and registration procedures (p=1,000 >α 0.05) with JKN participation. The conclusion was that there was a relationship between family income and NHI membership in West Rungan District. There was no significant relationship between family income, level of knowledge, level of education, number of family members, and registration procedures and NHI membership. Logistic Regression Test shows that family income is the most dominant factor (OR=6.536) related to JKN participation in West Rungan District.
Evaluation of practices and attitudes of caregivers influencing adherence to seasonal malaria chemoprevention in children under five years of age: the case of Rural Embangweni, Mzimba District, Malawi
Authors: Salangwa Chisomo , Munthali Reston , Mfune Lusungu , Nyirenda Vegha Kaunga
Published: June 2024

This research aimed to investigate medication adherence to seasonal malaria chemoprevention (SMC) and to evaluate the caregivers’ behaviors and attitudes throughout the 2022 SMC campaign in Embangweni, Mzimba District. SMC aims to administer a three-day course of anti-malarial drugs periodically during the months when malaria risk is highest. However, SMC’s effectiveness relies on medication adherence, without which morbidity cannot be reduced. In this study, a random cluster sampling approach was employed to extract data from internal monitoring, with caregivers’ self-reports as the primary information. The caregivers’ adherence levels, beliefs, and behaviors were then assessed and analyzed using Bernard Vrijens’ taxonomy. In total, 95% of caregivers (n = 2,457) were knowledgeable about using drugs to prevent malaria at the outset of treatment when 93.0% of children (n = 2,299) received their initial dose. However, only 66% of caregivers (n = 2,457) indicated that the community health workers supervised the treatment directly. At the beginning of the treatment phase, 89.4% of the children (n = 2,127) took their medication on the second day and 80.2% (n = 2,295) took their medication on the third day. Caregivers cited “forgetting”, “lack of time”, and “absence of the mother” as the primary reasons for halting the three-day prescription. The results of this research indicated that caregivers demonstrated a high level of adherence in completing the entire three-day course of medication and ensuring SMC coverage. However, the survey also highlighted areas of improvement in some caregivers’ attitudes, practices, and knowledge concerning adherence to medication throughout the SMC initiative.
Condition Monitoring of Drill Bit for Manufacturing Sector Using Wavelet Analysis and Artificial Neural Network (ANN)
Authors: Rajakannu Amuthakkannan , KP Ramachandran , K Vijayalakshmi
Published: June 2024

Real time condition monitoring and precision health assessment system is a mandatory need for effective maintenance program in industrial sector. Rapid advancement in the information technology and other engineering technologies have invited more proactive attention from research and development in industrial sectors and particularly in condition monitoring of machines and related Industrial processes. In this work, the drill bit condition monitoring techniques have been developed based on the wavelet analysis and artificial neural network (ANN) as automatic drill bit fault detection and classification. An experimental work has been conducted to capture the vibration signals for analysis. In this experiment, the CNC drill machine is used with high carbon steel drill bit and mild steel material as work piece. The cutting condition parameters are kept constant and the wear level is changed. The Data Acquisition system (DAQ) with Lab VIEW software is used to capture the vibration signals for drill bit with different wear conditions. The captured vibrations data are analyzed using continuous wavelet transform (CWT) with Morlet wavelet and Daubechies wavelet as a prime function. In general, the CWT coefficient is used to generate the inputs features to ANN for automatic tool condition classification, with two outputs (0, 1) for healthy and (1, 0) for faulty. The results show the effectiveness of the combed WT and ANN for automatic classification of tool wear conditions with high success rate.
Transition Strategies from Monolithic to Microservices Architectures: A Domain-Driven Approach and Case Study
Authors: Seedat Momil , Abbas Qaisar , Ahmed Nadeem , Feroz Irum , Affefah Qureshi  , Amelio Alessia
Published: June 2024

This paper focuses on the systematic mapping of monolithic applicationsto microservices architecture, a popular alternative in the software development industry.The research examines the advantages of microservices and the challenges organizationsencounter during the transition from monolithic systems. A case study of a financialapplication is presented, along with proposed techniques for identifying microserviceswithin monolithic systems using domain-driven development concepts.The study highlights the difficulties and benefits of migrating from monolithic to microservicesarchitecture, offering valuable insights for software architects and developers. Practicalimplications include a technique for identifying microservices on monolithic systemsusing domain-driven concepts and various communication protocols for service interaction.The findings suggest that this proposed technique can enhance work performanceand establish clear models, particularly for complex systems. However, it may have limitedeffectiveness in less complex systems. The paper contributes to the field of softwaredevelopment by providing practical solutions for companies considering a shift tomicroservices architecture and comparing the two architectural styles.
Enhancing IoT Security through Machine Learning-Driven Anomaly Detection
Authors: Usama Tahir  , Muhammad Kamran Abid  , Muhammad Fuzail  , Naeem Aslam
Published: June 2024

This is study emphasizes the growing cybersecurity situations arising from the increasing use of Internet of Things (IoT) devices. Paying the main attention to the development of IoT security, the work here deploys the machine learning-based anomaly detection and adaptive defense mechanisms as proactive methods to counteract existing plus future cyber threat sources. The visual serves to expound the rapid development of the Internet of Things, and it also highlights the importance of infrastructures with robust safety features to secure the connected devices. IoT security statement brings out the hidden threat and vulnerabilities of the IoT, in this context advanced security measures are for the rescue. The objectives concentrate on improving security of IoT via machine learning detection of anomalies, and bring introduction of defense mechanisms that are adaptive. We specify the data sources, preprocessing tasks, and Random Forest, Decision Tree, SVM, and Gradient Boosting algorithms selected for anomaly detection in the methodology section. The abnormity negotiation function and the self-adaptive defense procedures are combined in order to strengthen the information technology ecosystems which are capable of dynamic simplification. The results and discussion part hotelates the effectiveness of machine learning models selected, and indicates about accuracy, precision, and recall metrics. To state in the most significant matter, Gradient Boosting brings the greater precision of 89.34%. Table 3 below indicates the various models' effectiveness. It is proven that Gradient Boosting is the most powerful model among all. The discourse unfolds with account of the results, acknowledgment of the limitations, and discussion crucial obstacles encountered in the realization of the research. The conclusion reaffirms the importance of machine learning in IoT security implementation, thus building a robust system that can evolve to fight the ever-emerging cyber-attacks, keeping up with the progressive direction for securing IoT through the connected world.
The Integration and Management of Clean Energy In Microgrid using Blockchain
Authors: Ahmed Afshaar , Mohammad Noman Ali Khan  , Rizvi Huma Hasan , AHMED MANZAR , Shakil ahmed  , Fahad Ahmed Siddiqui
Published: June 2024

The environment pollution is one of the biggest issues in the world and with the passage of time this issue becoming more severe. The researchers are focusing on this issue from many years but there is still no control and it’s creating bad impacts on weather and health. The impact of issue can be seen in form of changes occurs in global temperature, weather and health. There are many factors that contribute to raise pollution such as CO2, and main sources are smog, smoke and heat generated with energy resources. The pollution must be control for clean and healthy environment. The energy generate from the coal, diesel and by burning fuel must be stop and clean energy resources must be used such as hydroelectricity, solar and wind energy in future. In this research paper, the main issues related to energy and its environmental impact and solution will be proposed. The Microgrid is new approach and reliable and decentralized control system, which can address many technical and non-technical issues related to present power system by using the blockchain.  A Simulink model of microgrid will be used for analyzing the result graphically.
Exploring Long-Range Order in Diblock Copolymers through Cell Dynamic Simulations
Authors: Muhammad Javed Iqbal  , Soomro Inayatullah , Mahar Mumtaz Hussain , Usama Gulzar
Published: June 2024

Soft materials have played an important role in the development of nanotechnology over the past decade. Diblock copolymer systems in these soft materials have opened up new avenues of research, introducing discoveries in experimental and theoretical research in the bulk and melt states. To this end, computer programming has advanced the simulation of soft materials through mathematical models that have enabled the prediction of novel ordered structures and morphologies from simulations on long-range order. Using this approach proved to be cost-effective and time-efficient. There are many mathematical models for predicting novel morphologies in diblock copolymer systems by computer simulation. Still, cell dynamic simulation (CDS) stands out for its efficiency and robustness in achieving long-range order. This paper presents a cell dynamic simulation model for predicting simulation results by examining flow, deformation and phase transitions within diblock copolymer systems in curvilinear coordinate systems. The paper insight into the interpretation, understanding, scope, and application of the partial differential equations involved in the model by presenting a block diagram of the CDS model with a modified algorithm. A numerically consistent CDS numerical scheme is developed. Laplacian is involved in the CDS model based on curvilinear geometries to solve regular and irregular system boundaries. Also, self-assembly, phase separation mechanism, predicted results and applications in diblock copolymer systems are highlighted. Finally, the results of the CDS model are also presented for comparison with other models.
Proteção de dados no Direito Administrativo Sancionador
Authors: Oliveira José Roberto Pimenta , Pires Mariana Ferreira da Cruz
Published: June 2024

This article aims, through a systematized and non-exhaustive exposition of the literature and legislation, to analyze the historical evolution of the right to data protection and its treatment within the scope of national and foreign Sanctioning Administrative Law. Thus, the present study was organized into four axes: the historical and sociological context of the role of information in contemporary society, the importance of studying Comparative Law in the context of data protection, the implementation and performance of the Autoridade Nacional de Proteção de Dados – ANPD and the adoption of the responsive regulation model by the Lei Geral de Proteção de Dados – LGPD. It was found that, in general, the right of data protection in Brazil is very young and, as a result, it seeks maturity and improvement in foreign legal systems, especially in the Member States of the European Union. The research methodology is qualitative, bibliographic and documentary. The research is descriptive and exploratory, aiming to develop ideas from information on the topic.
Study on the Mechanism of High-Pressure Cyclic Water Injection for Far-Wellbore Oil Extraction in Cracks-Caverns Reservoirs
Authors: Jiang Beibei , Zhang Guoqiang , Wang Dong , Liu Jiabo , Li Haitao , Luo Hongwen , Chen Yong , Liu Dong
Published: June 2024

When applying the high-pressure cyclic water injection technique in injection and production wells belonging to cracks-caverns reservoirs for huff and puff oil production, it is crucial to effectively judge the reservoir type, accurately calculate the reservoir parameters, and reasonably set the high-pressure water injection parameters, which can effectively solve the low recovery efficiency and rapid oil production decline of the injection and production wells due to the differences in cracks and caverns and its complexity in spatial development. However, the imperfection of the existing technical system, resulting in the inability to ensure the rationality and effectiveness of high-pressure cyclic water injection parameter settings, followed by the difficulty in evaluating oil increment of the injection and production wells after multiple rounds of water injection and oil production, greatly limit the deep application of this technique.

To solve this problem, we take the Tahe Oilfield (a typical cracks-caverns reservoir in China) as an example. First, we analyze the morphological characteristics of numerous high-pressure water injection indicating curves in Tahe Oilfield, and extract four typical indicating curves using differentiated classification. Second, based on the volume balance equations, we establish two mathematical models—the karst cavern mathematical model of water injection indicating curve and the cracks-caverns mathematical model of water injection indicating curve. Finally, by solving the two mathematic models and the correlation analysis of characteristic parameters belonging to the four extracted typical indicating curves, we can fulfill the reservoir types identification and quantitative calculation of the key reservoir parameters in the injection and production wells. Application of this technique in Well TH1021XX indicates that its far-wellbore crude oil reserves are 69.80×104 m3, its activation pressure of the interconnected fractures ranges from 6.25 MPa to 8.25 MPa, and the error between the actual accumulated oil production and its predictive value is less than 4% after four rounds of high-pressure water injection and oil production. Meanwhile, the error assessment results of numerous wells are all within 10%, which validates the effectiveness and practicality of the research findings in this article.
Rationalization of labor as a function of systemic economic thinking under the modern social and labor relations
Authors: Bogunov L. A.
Published: June 2024

Objective: to define the content of concepts that formalize the problem area of the modern social and labor relations (SLR) and to offer a solution to the problem of SLR regulation from the viewpoint of rationalization factor.

Methods: content analysis and systematization of scientific publications, including logical, comparative and contextual analysis; methods of dialectical cognition, system analysis and synthesis, SWOT-analysis, and modeling; structural and system-functional approach.

Results: based on the analysis of foreign and Russian publications on various aspects of the SLR definition and development, the author formulated the content of concepts reflecting the said phenomenon in the logic of changes, problems and solutions. The problem area of the modern SLR interpretation was outlined, within which the rationalization potential of the labor subjects activity is not differentiated, which makes it difficult both to formalize certain modern problem aspects and to formulate relevant corrective proposals. A solution was developed that takes into account the resource of economic thinking of individuals with bounded rationality; this allows supplementing the essential construction of the rationalization concept in the context of labor activity. Using the established theoretical and methodological toolkit, the author reveals the possibilities to improve the labor agents’ adaptability under the changes in SLR and to promote the constructive interaction of SLR subjects in general. The article shows potential directions of scientific search concerning the activity of labor actors as subjects of rationalization under the changes.

Scientific novelty: the article develops the concept of labor rationalization as a function of systemic economic thinking, which allows compensating for limited rationality and thus increasing constructive interaction of SLR subjects.

Practical significance: the provisions developed in the article can be used in research work when considering the issues of SLR and labor rationalization and in educational activities from the viewpoint of the established competence model.
Features of industrial policy implementation in the modern Russian economy
Authors: Nizamutdinov I. K.
Published: June 2024

Objective: in the modern economic system under globalization, effective industrial policy is one of the basic conditions for ensuring sustainable economic development in the context of multipolar economic systems formation and development. The tools of industrial policy implementation form the conditions for the advanced development of both national and regional economies. The study objective is to identify the key features of industrial development of the national economic system under globalization, as well as the basic tools for the effective industrial policy implementation in the Russian economy.

Methods: when considering the features and factors of industrial development and the tools for the effective industrial policy implementation, we used such methods as system and historical analysis, comparison and identification of the key features of industrial policy implementation and transformation tools in the modern Russian economy.

Results: based on the analysis of the world experience of industrial policy implementation along the main models of industrial development, the advantages and disadvantages of each respective model of industrial policy were determined; within the framework of the innovative model of industrial development, the indicators for assessing the effectiveness of industrial policy were systematized, as well as the peculiarities of the formation of the innovative environment of industrial development; the peculiarities of industrial policy implementation in the Russian economic system under globalization were revealed, the basic tools for the effective industrial policy implementation were structured.

Scientific novelty: based on the analysis of industrial development processes and scientific approaches to industrial development and implementation of industrial policy, the peculiarities of using the industrial policy tools in the Russian economic system were revealed in the framework of combination and transformation of tools of innovative and importsubstituting models of industrial policy implementation; the contradiction was identified in the changing role of the state in the implementation of effective industrial policy in the modern economy under globalization (in recent decades, the trend of the weakening role of the state in developed economies is replaced by the need to strengthen the state to ensure effective innovation process and industrial development); the tools for the industrial policy implementation in the modern economic system were systematized based on the analysis of world experience.

Practical significance: the results of the study of industrial policy tools in the modern economy, taking into account the regional aspect, can be used to establish mechanisms for the innovation process implementation and import substitution in the modern Russian economy based on the adjustment of the tools used and the industrial policy implementation methods, in order to form and implement the programs of sustainable industrial development at the federal and regional levels.
Digitalization of educational organizations as a product- and process-innovation in the data economy: managerial and methodological aspects
Authors: Shinkevich A. I. , Shaimieva E. Sh. , Gumerova G. I.
Published: June 2024

Objective: to reveal the essence of educational organizations’ digitalization as the implementation of product- and processinnovations in their innovation activity from the managerial viewpoint, including (here) innovation statistics in the data economy. The research tasks were: to formulate the essence of educational organizations’ digitalization as product- and process-innovations in their innovation activity in the digital economy based on the analysis of scientific works; to identify product- and process-innovations as a result of educational organizations’ digitalization; to form tools of educational organizations’ digitalization in the context of product- and process-innovations in the form of methodological material.

Methods: analysis, synthesis, classification. The study object is the processes of educational organizations’ digitalization as an integral part of their innovative activity under the fourth industrial revolution. The study subject matter is product- and process-innovations implemented in the process of educational organizations’ digitalization.

Results: the paper identifies product- and process-innovations as a result of educational organizations’ digitalization, compiles a list of them, while taking into account the processes of virtualization of assets, management and platformization in the internal and external environments of an educational organization. The concept of “digitalization of educational organizations” was clarified: it is a set of processes of virtualization and platformization, considered as an integral part of the innovative activity of educational organizations, which results in product- and process-innovations. Recommendations for experts in the field of educational organizations’ digitalization were developed, in terms of normative and legal regulation of the process under study, its organization, methodological support and achievement of the educational system’s technological sovereignty based on the introduction of product- and process-innovations.

Scientific novelty: consists in revealing the essence of an educational organization’s digitalization as part of its innovative activity, while distinguishing the product- and process-innovations in theoretical and practical virtualization and platformization of the issue.

Practical significance: the study results can be used to form strategies for managing product- and process-innovations arising during digitalization of educational organizations and to collect statistical information on the innovation activity of educational organizations in the digital economy.
Information support for corruption counteraction
Authors: Gorshenkov A. G. , Gorshenkov G. G. , Gorshenkov G. N.
Published: June 2024

Objective: to systematize knowledge about the information and criminological implications of the legal regulation in combating corruption and to develop proposals for the optimization of its legal means.

Methods: a set of scientific cognition methods, including universal and formal-logical methods, primarily formal-legal, modeling, and idealization; a retrospective approach to studying the formation and development of interrelated criminological and political scientific trends, which facilitated the obtaining of this study results. The main scientific tool used was the analytical method.

Results: a range of attributes was developed which characterizes the anti-corruption system and the information spectrum of its infrastructure related to three main types of activities: criminological, political, and managerial. Some of these attributes, which characterize the outlines of the emerging “support” concept in the considered system of functioning, were conceptualized and to a certain extent categorized. This, in turn, allowed defining the contours of the emerging system of instrumental knowledge that optimizes the scientific principle implementation in the political management of the anti-corruption system.

Scientific novelty: the article presents the idea of conceptualizing scientific provisions regarding the information support of anti-corruption efforts, the mechanism of which has not established yet. In this regard, the authors considers the concepts in the technological area of the anti-corruption management system to be promising. Among them is the idea to introduce such legal mechanisms as criminological monitoring and criminological expertise, a type of which is implemented in the anti-corruption expertise. The article novelty also consists in an additional area of research, which is special preventive for corruption offenses, studied for their effectiveness and ability to ensure criminological security.

Practical significance: the theoretical provisions developed in this study are designed to form scientific and criminological criticism in the professional legal consciousness, aimed at decision-making, selecting and implementing means and application technologies in the field of combating corruption.
Study on the Characteristics of Single Tank Leakage Explosion Accidents in Tank Farm
Authors: Oyang Dihua , Song Mengyao , Li Yanyan , Shi Hongxing , Qin Xiaowen
Published: June 2024

To quantitatively evaluate the consequences of a chain-detonation accident from a single tank leak in a tank farm, this paper simulates a leak-detonation accident based on the computational fluid dynamics (CFD) model with three different arrangements of field, one-way and L-shape distribution, and evaluates its impact on personnel and buildings. It combines the diffusion of combustible gases with subsequent deflagration due to accidental ignition. The diffusion behavior of the leaking gas with the wind is predicted and the danger zone created within the tank area is evaluated. Subsequently, a deflagration scenario due to the ignition of the flammable gas is simulated predicting the overpressure and high-temperature deflagration loads. Finally, the impact of a leaked gas deflagration on other tanks and personnel in the tank farm was evaluated. The hazardous area resulting from the diffusion of the leaking gas is mainly located on the right of the leaking tank. The hazards posed by different distribution arrangements of tank types also differed. The minimum radius to ensure safety under deflagration overpressure is 11.97 m. The present work is conducive to the determination of the safe distance between individual tanks in the new tank farm and the formulation of the safety protection.
Molecular phylogenetic relationships based on chloroplast genomes of Zingiberaceae crops: Insights into evolution and adaptation to extreme environments
Authors: Lu Tian , Zhang Guiyu , Xiang Niyan , Yu Xiaolei , Gao Xiaoman , Liu Shuwen , Zhao Yuemei , Zhang Rongxiang , Yuan Tao
Published: June 2024

In this study, we performed a comparative analysis of 11 newly and 110 published data from the Zingiberaceae family, including their structure, codon usage, nucleotide polymorphisms, divergence time, and selection pressures. Our findings revealed a conserved structure across Zingiberaceae species' chloroplast genomes, with no significant expansion or contraction observed during diversification. We identified four regions within protein-coding genes (atpH, rpl32, ndhA, and ycf1) and one intergenic region (psac-ndhE) prone to mutations, which could serve as valuable molecular markers for phylogeography and population genetics studies. Additionally, our analysis indicated that natural selection predominantly influences codon usage in Zingiberaceae chloroplast genes. Phylogenetic analysis supported the division of Zingiberaceae into two subfamilies. Our results confirmed that Globba is more closely related to Curcuma than to Hedychium, while Hedychium is more closely related to Pommereschea-Rhynchanthus than to Cautleya. Divergence time estimations revealed two rapid divergences in Zingiberoideae species, possibly influenced by rapid uplift of the Tibetan Plateau and a cooling event in the Late Miocene caused by a decrease in CO2 levels. Ancestral range reconstruction results support that Zingiberaceae species originated in Africa during the Cretaceous, and subsequently spread to Southeast Asia and India. Most protein-coding genes in Zingiberaceae undergo negative selection, except for the ycf2 gene. Furthermore, we identified two positively selected genes (matK and ndhB) in high-altitude Roscoea species, potentially crucial for their adaptation to highland environments. In summary, our study provided new perspectives for studying the intricate phylogenetic relationships and their adaptive evolution within the Zingibeaceae family.
Role of Multiple Stressors in Planned Adaptation to Climate Change in Semi-Arid Region in India
Authors: Mehta Pradeep Kumar
Published: June 2024

With increasing challenges related to climate change, farmers living in harsh climatic conditions are experiencing an adverse impact on their livelihoods. Farmers need to respond to climate change in a more planned than reactive way to reduce their vulnerability to future climate changes. However, farmers confront with a range of multiple stressors, including climatic and non-climatic. The current study examines the role of non-climatic stressors on farmers' typology of adaptation. The study is conducted in an agriculturally dominated semi-arid region in India. The study includes a primary survey that encompasses 665 farmers. To ensure representation from each block, a proportionate stratified random sampling technique was applied in the selection process. Employing a mixed method approach, which combines quantitative and qualitative tools, the study reveals that farmers generally perceive climate change and attempt to adjust or adapt to changes in environmental conditions in various ways. However, in Nuh, only a few farmers are adopting planned measures to deal with climate change. The adoption of planned strategies is facilitated by access to formal credit, and affiliation with local organizations, while it is hindered by the incidence of non-climatic stressors. The existing non-climatic stressors play a critical role in farmers' adaptability to climate risks, constraining how farmers respond to climate change. There is a need to account for both climatic and non-climatic factors while planning and designing appropriate adaptation strategies.
Anti-glomerular basement membrane disease secondary with invasive C. albicans pneumonia: A case report and review
Authors: Zheng Xinchun , Chen Huili , He Pengyuan , Zhong Ruihua , Xia Jinyu , Li Chunna
Published: June 2024

Background
Anti-glomerular basement membrane (anti-GBM) disease is an autoimmune disorder that specifically affects the kidneys and lungs with the presence of autoantibodies targeting the GBM, causing rapid glomerulonephritis and alveolar hemorrhage due to damage to the capillary bed. The anti-GBM disease secondary with pulmonary Candida albicans infection has been rarely documented.
Case presentation:
A 58-year-old male suspected of tuberculosis presented to our hospital with cough and hemoptysis that progressed to acute respiratory failure and acute renal failure. He was finally diagnosed with invasive C. albicans pneumonia by detection of C. albicans with sputum culture and metagenomic next-generation sequencing (mNGS) in bronchoalveolar lavage fluid (BALF). Diagnosis of anti-GBM disease was confirmed based on positive serum anti-GBM autoantibody levels and diffuse linear spherical IgG deposition along the glomerular capillary walls observed during renal biopsy. After receiving antifungal therapy, plasmapheresis, hemodialysis, corticosteroid shock therapy and cyclophosphamide, the patient achieved a favorable prognosis after discharge.
Conclusion
Our report highlight the association between invasive C. albicans pneumonia and anti-GBM disease, which has not been reported to the best of our knowledge. Our findings suggest that evaluating anti-GBM antibody levels and conducting renal biopsies in elderly patients presenting with hemoptysis and acute renal failure may facilitate the identification of such cases. It is crucial for intensive care unit personnel to be knowledgeable about this syndrome, as initiating appropriate treatment promptly can significantly reduce mortality rates.
The Effect of Number of Doses of Sulphadoxine-pyrimethamine for Intermittent Preventive Therapy on Pregnancy Outcome Among Parturients Delivering at Lautech Teaching Hospital, Ogbomoso. A Prospective Cross-sectional Study
Authors: MURITALA WAKEEL OKANLAWON , ATANDA Oluseyi O.A , OWONIKOKO Kola Musliudin , SULEIMAN Sherifat T , ADESOPE Taibat Pejuola , Adeniji Adetunji Oladeni
Published: June 2024

Background
Malaria infection during pregnancy is associated with adverse maternal and foetal outcomes especially in sub-Saharan Africa. Sulphadoxine Pyrimethamine (SP) is commonly used for intermittent preventive therapy (IPT) against malaria in pregnancy. However, development of resistance to SP has been linked to reduction in its effectiveness. WHO recommends uptake of SP at each scheduled antenatal care (ANC) visit at least four weekly apart, but the effects of number of doses of SP on pregnancy outcomes still require comprehensive review.
Methodology: Study Type:
Prospective Cross-sectional Study. Participants were recruited during booking clinic. IPT-SPs were administered to participants in ANC under directly observed therapy (DOT) at least four weekly apart and recorded in the ANC case note and they were followed up till delivery. Data obtained was analysed using Statistical Product and Service Solutions (SPSS) version 21
Results
A total of two hundred and ten (210) participants were recruited into the study, 192 (91.43%) participants completed the study. The median number of doses of IPT-SP received by the study participants is three (3) doses. Increasing number of doses of IPT-SP was significantly associated with reduction in LBW (P < 0.001), symptomatic maternal malaria episode (p = 0.028), maternal anaemia in 3rd trimester (p < 0.001) and at delivery (p < 0.001) (most significantly in primigravida) and non-significant reduction in preterm delivery (p = 0.1). There was no significant difference in the proportion of women reporting adverse drug reactions among the number of doses (p = 0.395).
Conclusion
Four or more doses of IPT with SP was considerably more effective in reducing symptomatic malaria, maternal and neonatal anaemia, low birth weight and premature delivery than 2-dose regimen even in this area with low SP resistance and highly seasonal malaria and the extra dose of SP was well tolerated.
Recommendation:
Pregnant women should be encouraged to receive four or more doses of IPT-SP in pregnancy.
Risk of Acute Kidney Injury Following Repeated Contrast-enhanced Computed Tomography and Angiography in Trauma Patients
Authors: Wang Yu-Hao , Wu Yu-Tung , Cheng Chi-Tung , Fu Chih-Yuan , Liao Chien-Hung , Chen Huan-Wu , Hsieh Chi-Hsun
Published: June 2024

Purpose
This study investigates the risk of contrast-associated acute kidney injury (CA-AKI) in trauma patients, focusing on the impact of cumulative contrast medium doses.
Methods
A retrospective review was conducted at a level 1 trauma center (2019–2021). The study included patients who underwent intravascular contrast-enhanced (Omnipaque 350 mg I/ml) examinations for torso trauma within 7 days post-injury. The total contrast medium volume within 7 days was calculated. AKI was defined using the KDIGO grading system based on creatinine data. Multivariate logistic regression (MLR) identified AKI risk factors.
Results
Among the 264 patients, 7.2% (19/264) developed AKI, with 3.4% (9/264) classified as KDIGO stage 3. Approximately 42.8% of patients underwent at least two contrast-enhanced examinations. The mean total contrast medium given was 129.5mL (range 80-410ml). Multiple logistic regression (MLR) analysis identified four independent risk factors for AKI: diabetes mellitus, initial eGFR < 30, use of inotropic agents, and contrast medium exposure. The odds ratio of AKI increased by 2.92 (95% CI 1.30–6.53) for every 100ml increase in contrast dose. And the contrast volume exposure only plays important role in severe trauma patients (ISS ≥ 25). Moreover, when correlated with eGFR, the contrast medium exposure volume demonstrated better predictive ability for AKI, with a best cut-off value of Contrast volume to eGFR ratio > 1.86.
Conclusion
While repetitive contrast-enhanced examinations are sometimes inevitable, it does come with costs. The CA-AKI risk increases as the amount of contrast medium accumulates in trauma patients who requires repetitive examinations.
Fuzzy PID Control for Trajectory Correction Based on Motor Current Variation
Authors: Ying Weiqiang , Zhang Lingyan , Yao Cheng , Luo Shijian , Ying Fangtian
Published: June 2024

In this study, an attempt was made to interpolate linear models to approximate an entire nonlinear system, based on the traditional theory of fuzzy PID control. This approach considered the discrepancies between current detection and linear modeling, in conjunction with variations in motor current and the laws governing trajectory motion. The difference at a specific operating point between the obtained linear model and the actual nonlinear system was integrated into the linear system. Subsequently, a fuzzy controller was introduced for hall data within the cascade PID controller loop to synthesize a state feedback controller. Thereafter, variations in motor current were managed through fuzzy PID control. The theory, initially based on a single-wheel ramp scenario, was generalized to adapt to operational control on a general bump ramp. This method demonstrated satisfactory tracking responses upon testing.
The paper also discusses the application of PID control in linear systems and how intelligent control, through its nonlinear approximation capabilities, addresses complex issues. However, the algorithms of intelligent control are often computationally intensive and structurally complex, making them impractical for real-world applications. In light of the nonlinear characteristics of certain systems, where accurate mathematical models are unattainable, the features of nonlinear PID control are advantageous for systems with low model accuracy. This scheme exhibits robust anti-interference capabilities and effectively enhances system control precision. Nevertheless, it has been noted to have a slower tracking speed for input signals.
To evaluate the efficacy of fuzzy control, a tool capable of real-time positioning of the mobile robot was employed. The optimization design of the fuzzy PID controller was based on variations in motor current. Under different conditions, tests and observations were conducted, and the proposed fuzzy control method provided a favorable tracking response. The actual test outcomes were also effective, offering a novel perspective for the control of path stability.
High Expression of ARHGEF5 Predicts Unfavorable Prognosis in Acute Myeloid Leukemia
Authors: Xu Haitao , Chen Dangui , Lu Jia , Zhong Long
Published: June 2024

Acute myeloid leukemia (AML) represents a hematological neoplasm that is defined by high heterogeneity. Therefore, identifying new molecular markers for predicting the prognosis and optimizing therapeutic interventions for patients suffering from AML is crucial. Although an increase in Rho guanine nucleotide exchange factor 5 (ARHGEF5) expression level was observed in multiple cancer types, its involvement in AML remains unexplored. We obtained data on the gene expression of patients by accessing "the Cancer Genome Atlas (TCGA)" database to determine ARHGEF5 and AML correlation. Next, a Wilcoxon rank-sum test was conducted for comparing ARHGEF5 expression in patients with AML and normal samples. Additionally, we determined the correlation between ARHGEF5 and patient survival through the Kaplan-Meier (K-M) method as well as Cox regression analysis (CRA). Moreover, a nomogram was constructed using CRA for the prediction of the ARHGEF5 effect on patient prognosis. Next, we determined the pathway and function enriched by ARHGEF5-related genes as well as the association between ARHGEF5 and immune cells using the GO and KEGG pathway enrichment, protein-protein interaction network, and single sample gene set enrichment analyses. The findings indicate a significant ARHGEF5 overexpression in various cancers, including AML, compared to normal samples. Furthermore, the results demonstrated a significant association between ARHGEF5 overexpression and poor prognosis of 151 patients suffering from AML, patients with age ≤ 60, patients harboring mutations in NPM1, FLT3 mutation-positive, and patients harboring wild-type RAS (P < 0.05). CRA showed that an increase in ARHGEF5 expression level could independently predict the patient's prognosis. The nomogram prognostic model was constructed by incorporating the age and cytogenetics risk of patients. Further, we identified 412 differentially expressed genes (DEGs) between the groups with high and low expression of ARHGEF5. Specifically, 216 of these DEGs were observed to be overexpressed, while 196 were suppressed. ARHGEF5 overexpression could be a biomarker for predicting unfavorable outcomes among patients with AML. In addition, these DEGs and pathways could clarify the mechanisms behind AML onset and progression.
Exploring the Long-Term Efficacy and Surgical Outcomes of Sural Neurovascular Flap Applications in Distal Lower Limb Wound Reconstruction: A Single-Center Retrospective Study
Authors: Bangura Mohamed , He Li An , Zeng Tend , Chirima Tadiwa , Tran Sy-Trung , Wan Xiang , Jin Yong Li , Wang Minglu , Luo Huasong
Published: June 2024

Background The sural neurovascular flap has been effectively used to reconstruct complex tibial and soft tissue defects caused by severe trauma, promoting successful wound repair and healing. Proactive management is essential in minimizing postoperative complications and achieving optimal outcomes. Methods Our institution's ethics committee approved this retrospective study which involved 47 participants. Informed consent was obtained from all subjects. Data collected included demographic details, injury mechanisms and sites, mode, and size of soft tissue defects, complications, cosmetic outcomes, and functional outcomes of the lower limb and ankle. All flaps were performed by a single surgeon, with follow-up from January 2012 to February 2018. Result The study observed minor complications, primarily superficial necrosis. Over 95% of flaps survived, and less than 5% required reoperations due to superficial necrosis. Patient satisfaction was high, with over 50% achieving excellent cosmetic results and over 40% good cosmetic results. Conclusion Sural neurovascular flap applications show significant promise in reconstructing distal lower limb wounds. Our findings highlight the procedure's efficacy, demonstrated by high patient satisfaction, excellent cosmetic outcomes, and favorable functional results. Critical factors for success include meticulous patient selection, thorough debridement, and careful planning to mitigate risks and optimize outcomes.
Polypyrrole-decorated carbonized cotton fabric derived at air atmosphere for tunable electromagnetic interference shielding performance and highly fire safety
Authors: Lu JiaYu , Yu Jin , Jiang Ziqing , Zhang Yan , Zhang Hao , Yu Yihao , Qi Dongming
Published: June 2024

With the escalating prevalence of electromagnetic radiation pollution, flexible electromagnetic interference (EMI) shielding materials hold immense potential for widespread application. Carbonized fabric possesses notable advantages such as flexibility, excellent electrical conductivity, and chemical stability. However, their traditional preparation process is characterized by high energy consumption, intricate atmospheric conditions, and prolonged duration. This study introduces a novel approach of incorporating intumescent flame retardant into cotton fabric, aiming to facilitate rapid carbonization in an air atmosphere. Remarkably, this innovative approach leads to a remarkable total EMI shielding effectiveness (SET) of 17.55 dB within just 5 min of carbonization at 900°C in an air atmosphere. Moreover, in order to enhance the shielding effect, we conducted in-situ growth of polypyrrole (PPy) on the prepared carbonized fabric. With a deposition time of 120 min, the sheet resistance remarkably decreased to only 11.85 Ω/sq, resulting in an impressive SET value of 28.22 dB that effectively shields up to 99.9% of electromagnetic waves (EMW). Moreover, the SET of IFR-C-PPy-60 min can be enhanced to 51.84 dB by stacking 4 layers, enabling the attenuation of 99.999% of EMW. The IFR-C-PPy also exhibits excellent fire safety. This study presents a novel approach for rapid and large-scale fabrication of highly efficient EMI shielding conductive carbonized cotton fabric, offering potential applications in flexible electronic devices.