bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hemorrhagic stroke as a complication of Cerebral Malaria in a 26-year male: A Rare Case Report
Authors: Birhanu Anteneh Messele , Kebede Molla Asnake , Eshetu Misikr Alemu , Shash Erkyehun Pawlos , Berhanu Melaku Tsediew , Ahmed Elias Tabit , Negatie Hashim Meketa , Araya Haimanot 
Published: April 2024

Abstract

INTRODUCTION
Malaria continues to cause unacceptably high levels of disease and death despite increased global efforts and is still significant public health problem. African countries are disproportionately affected by malaria. The objective of this study was to describe a rare case of haemorrhagic stroke as a complication of malaria in a − 26-year-old male patient.
CASE PRESENTATION
A 26-year-old male from southwest Ethiopia presented with complaint of loss of consciousness (LOC) of 12 hours duration. He had fever, headache, vomiting, chills, rigors and shivering three days prior to the loss of consciousness. On physical examination, pulse rate 116 beats/min, blood pressure of 120/90mmHg, respiratory rate was 24 breaths/min, a temperature of 38.9 ◦C and oxygen saturation of 94%. Nervous system examination; stuporous with Glasgow Comma Scale (GCS) 10/15(M5, E3, V2). Blood film and RDT showed Mixed infection (P.F and P.V) and Non contrast CT finding of right cerebral parenchymal haemorrhage.
DISCUSSION and CONCLUSION:
The presented case demonstrated very rare case of a 26-year-old male patient who was diagnosed with left side hemiparesis secondary to haemorrhagic stroke caused by Cerebral Malaria should be considered as a very rare cause of stroke in a patient who presented with body weakness in malaria endemic areas and in individuals who had travel history to malaria endemic areas
Optimizing Nonlinear Variable Fractional Volta’s System Design with RBFNN-Enhanced Intelligence Computing Networks
Authors: Malik Muhammad Ghulam Abbas , Bashir Zia , Akhtar Muhammad Waseem , Awais Muhammad 
Published: April 2024

Abstract

The study of variable order differential operators has emerged as a powerful tool for effectively modeling nonlinear fractional differential equations and chaotic systems. In this research, we employ a nonlinear, flexible structure of radial basis function neural network (RBFNN) to model the convective flow of the generalized nonlinear Volta's system in the variable order fractional domain. The intricate physical parameters of the fractional-order system are first computed using a Variable Caputo-Fabrizio scheme, considering diverse stochastic scenarios of control constraints. Following this, we craft a parametric model using a Radial basis function neural network under various initial conditions and variable order of the generalized variable order Volta's system. We compute diverse manifestations of chaos within Volta's system using a dynamical neural network structure across different fractional order solutions. The phase portrait of the chaotic attractor demonstrates the chaotic behavior of the generalized variable order fractional Volta system through the Lyapunov exponent. We calculate time delay and embedded dimension using the Average Mutual Information (AMI) method to reconstruct the phase space for generalized variable order Volta's system. The proposed configuration of the Radial basis function neural network has been verified as an exceptionally effective tool for both soft computing and dynamics analysis of chaotic systems within the variable order fractional domain.
Educational Policy as Predictor of Computational Thinking: A Supervised Machine Learning Approach
Authors: Ezeamuzie Ndudi O. , Leung Jessica S. C. , Fung Dennis C.L. , Ezeamuzie Mercy N. 
Published: April 2024

Abstract

Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners’ factors, instructional strategies and learning environment. However, the influence of the wider community such as educational policies on computational thinking remains unclear.
Objectives: This study examines the impact of basic and technology-related educational policies on the development of computational thinking.
Methods: Using supervised machine learning, computational thinking achievements of 31,823 eighth graders across nine countries were analysed. Seven rule-based and tree-based classification models were generated and triangulated to determine how educational policies predicted students’ computational thinking.
Results and Conclusions: Predictions show that students have higher propensity to develop computational thinking skills when schools exercise full autonomy in governance and explicitly embed computational thinking in their curriculum. Plans to support students, teachers and schools with technology or introduce 1:1 computing have no discernible predicted influence on students’ computational thinking achievement.
Implications: Although predictions deduced from these attributes are not generalizable, traces of how educational policies affect computational thinking exist to articulate more fronts for future research on the influence of educational policies on computational thinking.
An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning
Authors: Zhu Lin , Li Bingxian , Tan Long 
Published: April 2024

Abstract

Traditional vehicular edge computing research usually ignores the mobility of vehicles, the dynamic variability of the vehicular edge environment, the large amount of real-time data required for vehicular edge computing, the limited resources of edge servers, and collaboration issues. In response to these challenges, this paper proposes an allocation and collaboration scheme of vehicle edge computing resources based on the Lyapunov function and Twin Delayed Deep Deterministic Policy Gradient (TD3). In this solution, this paper uses Digital Twin technology (DT) to simulate the vehicular edge environment. The edge server DT is used to simulate the vehicular edge environment under the edge server, and the base station DT is used to simulate the entire vehicular edge system environment. Based on the real-time data obtained from DT simulation, this paper defines the Lyapunov function to simplify the migration cost of vehicle tasks between servers into a multi-objective dynamic optimization problem. It solves the problem by applying the TD3 algorithm. Experimental results show that compared with other algorithms, this scheme can effectively optimize the allocation and collaboration of vehicular edge computing resources and reduce the delay and energy consumption caused by vehicle task processing.
Risk factors correlated to potentially inappropriate medications in the elderly
Authors: Zhu Xiaojuan , Zhang Feng , Zhao Yong , Zhang Wen , Zhang Yahui , Zhang Xi-yu , Li Hui-jie , Dong Yan , Liu Jia , Wang Jianchun 
Published: April 2024

Abstract

Backgroud
The prevalence of multimorbidity ( ≥2 chronic disorders in the same individual), polypharmacy ( ≥5 medications in the same individual) and potentially inappropriate medications (PIMs) in elderly patients was very high.
Methods
This is a cross-sectional analysis of 276 elderly patients aged ≥65 years old. PIMs was analyzed based on the Beers criteria (2019 edition) and Chinese criteria, patients were divided into non-PIMs, 1PIMs and ≥2 PIMs group based on both critieria. Logistic regression analysis wasconducted to investigate factors related to PIMs.
Results
The prevalence of multimorbidity was as high as 96.74% (n=267). 91.30% of patients (n=252) had polypharmacy. Determined by Beers and Chinese criteria, 40.22% (n=111) and 41.30% (n=114) of patients had 1 PIMs, 26.09% (n=72) and 13.77% (n=38) of patients had 2 or more PIMs. Based on Beers criteria, patients with PIMs had more prescribed medications compared to patients with non-PIMs (median [inter-quartile range, IQR]: 10[7–12] vs.7[5-9]), patients with 2 or more PIMs had significant more prescribed medications compared to patients with 1 PIMs (11[9.25-13] vs 8[7-11]); Similar results was found based on Chinese criteria. Further logistic regression analysis showed that the strongest predictor of PIMs was increased number of prescribed medications as determined by both Beers and Chinese criteria (P<0.001). Gender, number of diseases or age was not risk factor correlated to PIMs in our study.
Conclusion
PIMs in the elderly was very common, increased number of prescribed medications was the strongest predictor of PIMs.
Statistical Analysis and Effects of Radio Frequency Interference in GPS Signal Quality in Thailand
Authors: Sophan Somkit , Supnithi Pornchai , Myint Lin M. M. , Budtho Jirapoom , Saito Susumu 
Published: April 2024

Abstract

The radio frequency interference (RFI) in global navigation satellite system (GNSS) signals has recently received much attention in the GNSS community because of frequent jamming issues. The carrier-to-noise density ratio (C/N0) is one of the common parameters to indicate the signal quality. In this work, we aim to analyze the occurrences of local RFI effects in areas surrounding the Suvarnabhumi International Airport as well as remote areas. Specifically, the percentage of RFI levels and raw C/N0 values are analyzed based on the modified RFI detection. The estimated RFI values are created from the raw C/N0 data, followed by the RFI levels generated by the empirical data. We validate the modified RFI detection by using the GNSS reference stations at the urban, suburban, and outside the capital city in Thailand. The user positioning errors with the high (severe) RFI levels are investigated based on the single point positioning (SPP) and real-time kinematics (RTK). From the experimental simulations, the high RFI levels at the urban are higher than those at the suburban. As expected, the statistical analysis covering COVID-19 (2019 to 2023) shows that the high RFI levels in June 2023 (post COVID-19) are more than those in June 2020 and 2021 (lockdown COVID-19) about twofold. Additionally, the SPP and RTK errors with the medium/high RFI levels have the error spikes in the centimeter to meter levels. The RTK performance with the fixed status can be affected and then returned to the float status as well.
Serum CHI3L1 levels predict overall survival of hepatocellular carcinoma patients after hepatectomy
Authors: Jiang Yanji , Gong Wenfeng , Liu Yingchun , Zhou Zihan , Liang Xiumei , Lin Qiuling , Qiu Moqin , Lin Biaoyang , Qiu Xiaoqiang , Yu Hongping 
Published: April 2024

Abstract

Objective
The Chitinase 3-like protein 1 (CHI3L1) is currently used as a biomarker for the diagnosis of liver fibrosis. However, its prognostic value for hepatocellular carcinoma (HCC) patients remains controversial. In this study, we aimed to investigate the prognostic value of the CHI3L1 in HCC patients after hepatectomy.
Methods
In total, 754 HCC patients who underwent curative hepatectomy between January 2017 to August 2021 were retrospectively recruited. The probability of overall survival (OS) was evaluated by the Kaplan-Meier method and compared between groups using the log-rank test. Cox proportional hazard regression analysis was used to determine the independent prognostic factors. A prognostic nomogram was constructed for further examine the clinical utility of CHI3L1 in HCC.
Results
Kaplan-Meier analysis revealed that elevated serum CHI3L1 levels were associated with worse overall survival of HCC patients. Multivariate Cox regression analysis showed that the high-CHI3L1 group (≥198.94 ng/ml) was associated with a shorter survival time compared with that in the low-CHI3L1 group (< 198.94 ng/ml) after adjustment for potential confounding factors (HR =1.43, 95% CI = 1.05-1.94, P = 0.024). Additionally, the nomogram had sufficient calibration and discriminatory power in the training cohort, with C-indexes of 0.723 (95% CI: 0.673-0.772). The validation cohort showed similar results. Finally, we demonstrated that the AUC of the nomogram was 0.752 (95% CI: 0.683-0.821), which had better predictive ability than AFP (AUC: 0.644, 95% CI: 0.577-0.711).
Conclusion
Our results confirmed that the CHI3L1 could serve as an independent predictor for OS in HCC patients after hepatectomy, thus helping clinicians to develop individualized treatment and follow-up plans for the HCC patients. Further confirmation is needed due to the study limitations.
Bladder endometeriosis with recurrent urinary tract infection as a rare case report
Authors: Alabdullah Hadi , Alhamid Ahmad , Belal Malek , Alhadla Ahmad , Yasin Mohamad 
Published: April 2024

Abstract
Background
About 1% of women with endometriosis have urological endometriosis, which is an uncommon condition.The patient may be asymptomatic clinically or exhibit symptoms such as dysmenorrhea, irregular or heavy periods, and pelvic, lower abdominal, or back pain. During the prolonged diagnostic process, the patient is often misdiagnosed with urinary tract infection or interstitial cystitis.
Case presentation:
We present a case of a 37-year-old female patient who presented with varied symptoms including irregular menstrual cycles, dyspareunia, blood in the urine during menstruation, and sometimes unrelated to menstruation.
Conclusion
Enhancing awareness regarding the potential connection between Caesarean scar and bladder endometriosis is crucial.
Grandmothers’ breastfeeding knowledge, attitudes, maternal support perception, and breastfeeding practice: A prospective cohort survey
Authors: Wu Jing-Ling , Zhang Xiao-Yun , Jiang Xiumin 
Published: April 2024

Abstract

Objective
The study aimed to scan the status of grandmothers’ breastfeeding knowledge and attitudes, explore the relationship between grandmothers’ knowledge, attitudes, and the mother's breastfeeding support perception, and further study whether those factors have a direct impact on breastfeeding practices.
Methods
A quantitative, prospective cohort study was set in an obstetrics and gynecology specialist hospital. 310 mother-grandmother dyads completed structured questionnaires, and 282 mothers were followed up to 6 weeks postpartum to investigate breastfeeding practice.
Results
The grandmother’s breastfeeding knowledge score was 9.32 (SD = 2.33). The grandmothers’ breastfeeding attitude score were 62.03 (SD = 4.46) at a positive level. The mother’s perception of the grandmother’s support score was 27.77 (SD = 3.40) at a positive level. There were positive correlations among grandmothers’ breastfeeding knowledge, grandmothers’ breastfeeding attitudes, and mothers’ perception of breastfeeding support of grandmothers. Mother's breastfeeding plan (P = 0.02), mother's perceived breastfeeding support (P = 0.04), grandmother's education level (P < 0.01), and attitude towards breastfeeding (P < 0.01) were independent influencing factors of breastfeeding practice.
Conclusion
Grandmothers' breastfeeding knowledge and attitudes and mothers' breastfeeding support perceptions of grandmothers were positive, but there is a vast scope for betterment. Healthcare professionals must identify the factors that impact breastfeeding practice and create interventions to improve it.
Constitutive Artificial Neural Network espoused Plant Leaf Disease Detection
Authors: Kanagaraj Kaavya , Kulandaivel Madhumitha , Shajin F. H. , Prabhakaran Salini 
Published: April 2024

Abstract

The emergence of new diseases on plant leaves poses a substantial threat to global food safety and agricultural productivity. To mitigate this risk, accurate and swift detection of plant illnesses is crucial, reducing unnecessary expenses and minimizing financial losses and environmental damage. This study proposes a method called Plant Leaf Disease Detection with a Constitutive Artificial Neural Network (PLDD-CANN) to provide advancements in deep learning. The approach begins by gathering data from the Plant Village dataset and subjecting it to pre-processing techniques. This includes noise removal and image enhancement using a Variational Marginalized Particle Filter (AVMPF). Next, an Adaptive Convex Clustering (ACC) method is employed for image segmentation, followed by feature extraction using Fast Fourier and Continuous Wavelet (FFCWT) transforms. Finally, a Constitutive Artificial Neural Network (CANN) is utilized to categorize the input image to one of several categories, including healthy and various disease types like Yellow Leaf Curl Virus, Septoria Leaf Spot, Two-Spotted Spider Mite, Bacterial Spot, Target Spot, Leaf Mold, Mosaic Virus, Early Blight, and Late Blight. Then, the proposed technique is simulated using Python under several performance metrics including precision, f1-score, error rate accuracy, sensitivity, specificity and ROC. The proposed PLDD-CANN method provides 26.75%, 25.83% and 27.46% higher accuracy comparing with existing methods an enhanced CNN technique for plant leaves disease diagnosis in tomato (CNN-PLDD), A Novel Approach for Plant Leaf Disease Predictions with Recurrent Neural Network RNN Classification Method (RNN-PLDD), Detection of tomato leaf diseases for agro-based industries (FRCNN-PLDD) respectively.
Challenges Experienced by Nursing Students in the Clinical Learning Environment: A Cross-sectional Study in Hospitals within Koforidua, Eastern Region of Ghana
Authors: Quayson Ebenezer , Okyere-Boateng Hannah , Boafo Emmanuella , Acquah Comfort Akua , Kyei Patience 
Published: April 2024

Abstract

Nursing students have a crucial role to play in healthcare services while they are in training. It is an essential step in their professional practice preparation. Unfortunately, nursing students often experience obstacles such as bullying behavior which makes some of them drop out of nursing education, regardless of their geographic location. With the increasing brain drain of nurses in Ghana, the nurse-patient ratio is likely to rise further if the phenomenon is not given attention. Therefore, it is crucial to thoroughly evaluate nursing students' bad experiences in the clinical learning environment for a remedy. Hence, the researchers aim to analyze the obstacles faced by nursing students during their clinical attachments in hospitals located in Koforidua, Ghana's Eastern Region. A cross-sectional survey was conducted using a convenient sampling technique to select 130 nursing students from specific clinical learning environments. The study found that male nursing students (OR = 3.27 [95% CI: 1.67–4.88], p < 0.01), nursing students who are married (OR=-0.89 [95% CI: -2.57-0.80], p = 0.30), and Muslim nursing students (OR=-0.68 [95% CI: -2.27-0.41], p = 0.17) were more likely to be dissatisfied with their clinical learning environment compared to female, unmarried, and Christian nursing students, respectively. Male nursing students, Muslim nursing students, married nursing students, and nursing students who were relatively old were more likely to drop out of nursing school due to their intolerance of bullying and disrespect in the clinical environment, which led to dissatisfaction with their clinical experience.
Thermal effects and ephaptic entrainment in Hodgkin-Huxley model
Authors: Sousa Matheus Phellipe Brasil , Cunha Gabriel Moreno , Corso Gilberto , Lima Gustavo Zampier dos Santos 
Published: April 2024

Abstract

The brain is understood as an intricate biological system composed of multiple elements. It is susceptible to diverse physical and chemical influences, including temperature. The literature widely explores the conditions that affect synapses in the context of cellular communications. However, the understanding of how brain global physical conditions can modulate ephaptic communication remains limited, because the still poorly understood nature of ephapticity. This study proposes an adaptation of the Hodgkin and Huxley model, HH-E, to investigate the effects of ephaptic entrainment in response to thermal changes. The analysis focus on two distinct neuronal regimes: subthreshold and suprathreshold. In the subthreshold regime, the circular statistic is used to show the phase differences dependence on temperature. In the suprathreshold regime, the Population Vector and the Inter-Spike Interval are used to estimate phase preferences and changes in the spiking pattern. Temperature affects positively the HH-E model spiking frequency. At high temperatures the HH-E model collapses and no more spiking are observed. Moreover, temperature difference improves the anti-phase between spikes and the ephaptic external signal. In the suprathreshold regime, the ephaptic entrainment is influenced by temperature, specially at low frequencies. Finally, this study reveals the susceptibility of ephaptic entrainment to temperature variations in both subthreshold and suprathreshold regimes and discusses the importance of ephaptic communication in pathological contexts in which temperature play an important role in neural physiology, such as inflammatory processes, fever and epileptic seizures.
Heinrich Rickert and the Specifics of the Methodology of Historical Knowledge (on the 160th Anniversary of His Birth)
Authors: Синицын О.В. 
Published: April 2024

В статье характеризуется теоретико-методологическая концепция Генриха Риккерта, одного из ярких представителей «критической философии истории», основная проблематика которой была связана с вопросами возможностей и границ исторического познания. Главное внимание при этом было уделено защите научности истории, что базировалось на принципах методологического различения индивидуализирующих и генерализирующих наук. Эпистемология Риккерта строилась на критике теории отражения и противопоставлении обобщающего метода естественных наук, связанных с объектами, не имеющими ценностей и идеографического метода наук о культуре, имеющих дело с объектами, связанными с ценностями, что и обусловливает особенности исторических наук и специфику исторического познания.
The article characterizes the theoretical and methodological conception of Heinrich Rickert, one of the prominent representatives of the “critical philosophy of history”. The main attention is paid to protecting the scientific nature of history, which was based on the principles of methodological distinction between individualizing and generalizing sciences. Rickert's epistemology was based on criticism of the theory of reflection and opposition of the generalizing method of natural sciences, associated with objects that do not have values, and the ideographic method of cultural sciences, dealing with objects associated with values, which determines the features of the historical sciences and the specifics of historical knowledge. To reveal the diversity of all values, it is necessary to turn, according to Rickert, to the science that studies culture as reality, revealing all its richness, diversity, and uniqueness.