bluuebunny/crossref_metadata_2025 huggingface dataset:
Study of some components of the influence and formation of blood flow in patients with “slow flow”
Authors: Gogilashvili Nino , Tsinamdzgvrishvili Bezhan , Momtselidze Nana , Jung Friedrich , Plantl Lukas , Urdulashvili Tamar , Mantskava Maia
Published: July 2024

BACKGROUND: “Slow flow” is one very important concept in modern fundamental and clinical biomedicine. Slow coronary flow is indicative of delayed filling of the terminal coronary artery vessels, occurring in the absence of significant coronary stenosis. This group patient of patients exhibits a high incidence of disability and represents a significant financial and material burden for the state and the healthcare system in general. OBJECTIVE: The primary objective of our study was to examine patients with slow coronary flow. METHODS: We studied the standard parameters recommended by the international health care system (electrocardiography (by Medica QRS-12, Germany), through the electrical activity of a patient’s heart by the electrical impulses (beating) of the heart; HC1(Germany); coagulogramma by Coatron M1 (Germany), troponin by AQT 90 (Germany); general blood test we used automatic human counting device HC1(Germany). Also, we investigate the original parameters (non-standard parameters, which we use in this pilot study) that we were first studied for this diagnosis and non-standard parameters. RESULTS: A general blood test showed that patients with slow flow had a higher blood leukocyte count than the control group, but the amount of hemoglobin was normal, the hematocrit was much higher than in the control group, and the platelet count was close to the lower limit of clinical standards. We obtained details of blood flow by coagulation situation, such as prothrombin time, prothrombin index, international normalized ratio, activated partial thromboplastin time, thrombin time, fibrinogen, and rheological properties such as index of erythrocyte aggregability, index of erythrocyte deformability, plasma viscosity, in silico blood rheological index. CONCLUSSION: Blood flow can be considered as a superposition of vortices with similar frequencies and wave vectors that change after bifurcations or other obstacles in the vascular network. These factors together determine the conditions for structuring the flow of moving blood. Disruption or alteration of these factors results in slow flow. It has been found that the speed of blood flow in the coronary arteries depends on changes in the number and function of red blood cells. Slow flow is directly influenced by the aggregation and deformation of red blood cells, their number, and plasma viscosity. Consequently, the rheological status plays a crucial role in determining blood flow and its velocity.
Optimal design of RBFNN equalizer based on modified forms of BOA
Authors: Acharya Badal , Parida Priyadarsan , Panda Ravi Narayan , Mohapatra Pradumya
Published: July 2024

The equalization of digital channels is widely recognized as a nonlinear classification problem. In such scenarios, utilizing networks that approximate nonlinear mappings can be highly advantageous. There has also been extensive research on equalizers based on Radial Basis Function Neural Networks (RBFNNs). This study introduces a training methodology centred on the Improved Butterfly Optimization Algorithm (IBOA) for channel equalization using RBFNN. This approach aims to optimize the performance of RBFNN equalizers by leveraging the IBOA algorithm for training. Previous literature primarily approached the equalization problem as an optimization challenge. In contrast, this study addresses it as a classification problem. This training approach exhibits substantial enhancements compared to conventional metaheuristic algorithms.
Handwritten digit and Roman string recognition using gated CNN with federated learning
Authors: K Sruthi , M Meianbu , S R Naveen , Krishna R Nidhish
Published: July 2024

Handwritten number recognition has been extensively studied in the fields of machine literacy and computer vision, with datasets like MNIST serving as benchmarks. However, handwritten Roman numeral recognition presents unique challenges due to the diverse forms and structures of Roman numerals. In this paper, we propose a novel approach that combines Federated Learning with advanced neural network architectures to tackle this challenge effectively. Our methodology involves data acquisition and preprocessing, including the normalization of handwritten number and Roman numeral images. We design a hybrid neural network architecture that integrates Gated Convolutional Neural Networks (CNNs) for pixel-level feature extraction and Bidirectional Gated Recurrent Units (BGRUs) for sequence modeling. This architecture is essential for handling the complexity of recognizing both image and sequence data. Federated Learning is incorporated into our approach to train the model across multiple decentralized devices or servers while preserving data privacy. This ensures that sensitive handwritten data remains secure throughout the training process. By allowing model updates to be computed locally and aggregated without sharing raw data, Federated Learning maintains privacy and security in distributed learning environments. During training, each device computes gradients based on its local data and shares only the model updates with the central server. The central server aggregates these updates to update the global model, which is then sent back to the participating devices for further refinement. This iterative process continues until the model converges, while metrics such as accuracy, precision, recall, and F1-score are used to evaluate the model’s performance on a separate test dataset. Our approach demonstrates promising results in accurately recognizing both handwritten integers and Roman numerals, even in the presence of noise and variability in writing styles. By combining Federated Learning with advanced neural network architectures, our approach not only achieves state-of-the-art performance but also ensures data privacy and security in distributed learning environments.
The MindMoves Trial: Cross-Sectional Analyses of Baseline Vascular Risk and Cognition in Older Women with Cardiovascular Disease
Authors: Halloway Shannon , Volgman Annabelle Santos , Barnes Lisa L. , Schoeny Michael E. , Wilbur JoEllen , Pressler Susan J. , Laddu Deepika , Phillips Shane A. , Vispute Sachin , Hall Gabriel , Shakya Shamatree , Goodyke Madison , Auger Claire , Cagin Kelly , Borgia Jeffrey A. , Arvanitakis Zoe A.
Published: July 2024

Background:

Vascular diseases, including atherosclerotic cardiovascular disease (ASCVD) and stroke, increase the risk of Alzheimer’s disease and cognitive impairment. Serum biomarkers, such as brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor (VEGF), and insulin-like growth factor 1 (IGF-1), may be indicators of cognitive health.

Objective:

We examined whether vascular risk was associated with levels of cognition and serum biomarkers in older women with cardiovascular disease (CVD).

Methods:

Baseline data from a lifestyle trial in older women ( n = 253) with CVD (NCT04556305) were analyzed. Vascular risk scores were calculated for ASCVD (ASCVD risk estimator) and stroke (CHA2DS2-VASc) based on published criteria. Cognition-related serum biomarkers included BDNF, VEGF, and IGF-1. Cognition was based on a battery of neuropsychological tests that assessed episodic memory, semantic memory, working memory, and executive function. A series of separate linear regression models were used to evaluate associations of vascular risk scores with outcomes of cognition and serum biomarkers. All models were adjusted for age, education level, and racial and ethnic background.

Results:

In separate linear regression models, both ASCVD and CHA2DS2-VASc scores were inversely associated with semantic memory (β= –0.22, p = 0.007 and β= –0.15, p = 0.022, respectively), with no significant findings for the other cognitive domains. There were no significant associations between vascular risk scores and serum biomarkers.

Conclusions:

Future studies should prospectively examine associations between vascular risk and cognition in other populations and additionally consider other serum biomarkers that may be related to vascular risk and cognition.
Optimizing the Implementation of a Lifestyle Dementia Prevention Intervention for Older Patients in an Academic Healthcare System
Authors: Mace Ryan A. , Lyons Christopher , Cohen Joshua E. , Ritchie Christine , Bartels Stephen , Okereke Olivia I. , Hoeppner Bettina B. , Brewer Judson A. , Vranceanu Ana-Maria
Published: July 2024

Background:

Interventions that promote healthy lifestyles are critical for the prevention of Alzheimer’s disease and Alzheimer’s disease related dementias (AD/ADRD). However, knowledge of the best practices for implementing AD/ADRD prevention in healthcare settings remains limited.

Objective:

We aimed to qualitatively identify barriers and facilitators to implementing a clinical trial of a novel lifestyle intervention ( My Healthy Brain) in our medical center for older patients with subjective cognitive decline who are at-risk for AD/ADRD.

Methods:

We conducted focus groups with 26 healthcare professionals (e.g., physicians, psychology, nursing) from 5 clinics that treat older patients (e.g., memory care, psychiatry). Our qualitative analysis integrated two implementation frameworks to systematically capture barriers and facilitators to AD/ADRD prevention (Consolidated Framework for Implementation Science Research) that impact implementation outcomes of acceptability, appropriateness, and feasibility (Proctor’s framework).

Results:

We found widespread support for an RCT of My Healthy Brain and AD/ADRD prevention. Participants identified barriers related to patients (stigma, technological skills), providers (dismissiveness of “worried well,” doubting capacity for behavior change), clinics (limited time and resources), and the larger healthcare system (underemphasis on prevention). Implementation strategies guided by Expert Recommendations for Implementing Change (ERIC) included: developing tailored materials, training staff, obtaining buy-in from leadership, addressing stigmatized language and practices, identifying “champions,” and integrating with workflows and resources.

Conclusions:

The results will inform our recruitment, enrollment, and retention procedures to implement the first randomized clinical trial of My Healthy Brain. Our study provides a blueprint for addressing multi-level barriers to the implementation of AD/ADRD prevention for older patients in medical settings.
The Impact of Misaligned Perceived and Objective Fall Risk in Cognitively Impaired Older People
Authors: Taylor Morag E. , Kerckhaert Luuk , Close Jacqueline C.T. , van Schooten Kimberley S. , Lord Stephen R.
Published: July 2024

Background:

Cognitive impairment (CI) may impair the ability to accurately perceive physical capacity and fall risk.

Objective:

We investigated perceived (measured as concern about falls) and physiological fall risk in community-dwelling older people with CI, the characteristics of the aligned and misaligned groups and the impact of misaligned perceptions on falls.

Methods:

Participants ( n= 293) with mild-moderate CI were classified into four groups based on validated physiological and perceived fall risk assessments: 1) vigorous: low perceived and physiological fall risk; 2) anxious: high perceived and low physiological fall risk; 3) unaware: low perceived and high physiological fall risk; and 4) aware: high perceived and physiological fall risk. Groups were compared with respect to neuropsychological and physical function, activity and quality of life measures, and prospective falls (12-months).

Results:

The anxious (IRR = 1.70, 95% CI = 1.02–2.84), unaware (IRR = 2.00, 95% CI = 1.22–3.26), and aware (IRR = 2.53, 95% CI = 1.67–3.84) groups had significantly higher fall rates than the vigorous group but fall rates did not significantly differ among these groups. Compared with the vigorous group: the anxious group had higher depression scores and reduced mobility and quality of life; the unaware group had poorer global cognition, executive function and mobility and lower physical activity levels; and the aware group had an increased prevalence of multiple physical and cognitive fall risk factors.

Conclusions:

Fall rates were increased in participants who had increased perceived and/or physiological fall risk. Contrasting fall risk patterns were evident in those who under- and over-estimated their fall risk. Understanding these characteristics will help guide fall risk assessment and prevention strategies in community-dwelling older people with CI.
A Decade of Protecting Progress: Ethics Review
Authors: Rosen Allyson C. , Lavacot James A. , Klee Victoria , Luria Yuval , Rumbaugh Malia
Published: July 2024

Ethics Review began a decade ago with a mission to identify ethical concerns that hold back innovation and to promote solutions that would move the field forward. Over this time, blood biomarkers for brain pathology and medications that treat that pathology promise to transform research and care. A central problem is that the evidence needed to guide test interpretation and practice is accumulating and there are unanswered questions. At the same time, people living with and at risk for dementia want access to their test results and involvement in their care. We promote dialog among diverse people across many institutions through collaboration with the Advisory Group on Risk Evidence Education for Dementia (AGREEDementia.org). Over the years Ethics Review continues to publish these dialogs and solutions to overcome the paralysis of indecision and ethical concerns.
Quantitative muscle MRI in sporadic inclusion body myositis (sIBM): A prospective cohort study
Authors: Schlaffke Lara , Rehmann Robert , Froeling Martijn , Güttsches Anne-Katrin , Vorgerd Matthias , Enax-Krumova Elena , Forsting Johannes
Published: July 2024

Background:

Sporadic inclusion body myositis (sIBM) is the predominant idiopathic inflammatory myopathy (IIM) in older people. Limitations of classical clinical assessments have been discussed as possible explanations for failed clinical trials, underlining the need for more sensitive outcome measures. Quantitative muscle MRI (qMRI) is a promising candidate for evaluating and monitoring sIBM.

Objective:

Longitudinal assessment of qMRI in sIBM patients.

Methods:

We evaluated fifteen lower extremity muscles of 12 sIBM patients (5 females, mean age 69.6, BMI 27.8) and 12 healthy age- and gender-matched controls. Seven patients and matched controls underwent a follow-up evaluation after one year. Clinical assessment included testing for muscle strength with Quick Motor Function Measure (QMFM), IBM functional rating scale (IBM-FRS), and gait analysis (6-minute walking distance). 3T-MRI scans of the lower extremities were performed, including a Dixon-based sequence, T2 mapping and Diffusion Tensor Imaging. The qMRI-values fat-fraction (FF), water T2 relaxation time (wT2), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity ( λ1), and radial diffusivity (RD) were analysed.

Results:

Compared to healthy controls, significant differences for all qMRI parameters averaged over all muscles were found in sIBM using a MANOVA ( p < 0.001). In low-fat muscles (FF < 10%), a significant increase of wT2 and FA with an accompanying decrease of MD, λ1, and RD was observed ( p≤0.020). The highest correlation with clinical assessments was found for wT2 values in thigh muscles ( r≤–0.634). Significant changes of FF (+3.0%), wT2 (+0.6 ms), MD (–0.04 10-3mm2/s), λ1 (–0.05 10-3mm2/s), and RD (–0.03 10-3mm2/s) were observed in the longitudinal evaluation of sIBM patients ( p≤0.001). FA showed no significant change ( p = 0.242).

Conclusion:

qMRI metrics correlate with clinical findings and can reflect different ongoing pathophysiological mechanisms. While wT2 is an emerging marker of disease activity, the role of diffusion metrics, possibly reflecting changes in fibre size and intracellular deposits, remains subject to further investigations.
Considerations on How to Prevent Parkinson’s Disease Through Exercise
Authors: Oosterhof Thomas H. , Darweesh Sirwan K.L. , Bloem Bastiaan R. , de Vries Nienke M.
Published: July 2024

The increasing prevalence of people with Parkinson’s disease (PD) necessitates a high priority for finding interventions to delay or even prevent the onset of PD. There is converging evidence that exercise may exert disease-modifying effects in people with clinically manifest PD, but whether exercise also has a preventive effect or is able to modify the progression of the pathology in the prodromal phase of PD is unclear. Here we provide some considerations on the design of trials that aim to prevent PD through exercise. First, we discuss the who could benefit from exercise, and potential exercise-related risks. Second, we discuss what specific components of exercise mediate the putative disease-modifying effects. Third, we address how methodological challenges such as blinding, adherence and remote monitoring could be handled and how we can measure the efficacy of exercise as modifier of the course of prodromal PD. We hope that these considerations help in designing exercise prevention trials for persons at risk of developing PD.
The blessing of dimensionality
Authors: Fanizzi Nicola , d’Amato Claudia
Published: July 2024

The paper surveys ongoing research on hyperdimensional computing and vector symbolic architectures which represent an alternative approach to neural computing with various advantages and interesting specific properties: transparency, error tolerance, sustainability. In particular, it can be demonstrated that hyperdimensional patterns are well-suited for the encoding of complex knowledge structures. Consequently, the related architectures offer perspectives for the development of innovative neurosymbolic models with a closer correspondence to cognitive processes in human brains. We revisit the fundamentals of hyperdimensional representations and examine some recent applications of related methods for analogical reasoning and learning tasks, with a particular focus on knowledge graphs. We then propose potential extensions and delineate prospective avenues for future investigations.
Burden in caregivers of patients with acquired brain injury: Influence of family role and gender
Authors: Corallo Francesco , Maggio Maria Grazia , Bonanno Lilla , De Luca Rosaria , Cardile Davide , Cappadona Irene , Todaro Antonino , Calabrò Rocco Salvatore
Published: July 2024

BACKGROUND: Acquired brain injuries (ABI) represent neurological disorders that can arise after traumatic and non-traumatic events. In addition to the physical, emotional and cognitive challenges that patients face, these injuries can bring changes in the life of the patient and his or her family. OBJECTIVE: This study aims to understand how the occurrence of an ABI condition can disrupt and reshape family functioning by examining certain dimensions such as role in the family, gender and age, which may have a major influence on family dynamics. METHODS: We enrolled 86 caregivers of patients with ABI. Two experienced psychologists examined family functioning with Olso’s Family Adaptability and Cohesion Rating Scale (FACES IV). RESULTS: The correlation between groups by generics showed a significant difference only for flexibility (p = 0.05). Specifically, flexibility was greater in male caregivers, particularly in sons. Most of the constructs defining family functioning, such as communication, remained unchanged despite the ABI event. CONCLUSION: This study provides an in-depth understanding of how families face the challenges posed by the ABI and the role caregivers play within the system.
Identifying best fall-related balance factors and robotic-assisted gait training attributes in 105 post-stroke patients using clinical machine learning models
Authors: Kim Heejun , Shin Jiwon , Kim Yunhwan , Lee Yongseok , You Joshua (Sung) H.
Published: July 2024

BACKGROUND: Despite the promising effects of robot-assisted gait training (RAGT) on balance and gait in post-stroke rehabilitation, the optimal predictors of fall-related balance and effective RAGT attributes remain unclear in post-stroke patients at a high risk of fall. OBJECTIVE: We aimed to determine the most accurate clinical machine learning (ML) algorithm for predicting fall-related balance factors and identifying RAGT attributes. METHODS: We applied five ML algorithms— logistic regression, random forest, decision tree, support vector machine (SVM), and extreme gradient boosting (XGboost)— to a dataset of 105 post-stroke patients undergoing RAGT. The variables included the Berg Balance Scale score, walking speed, steps, hip and knee active torques, functional ambulation categories, Fugl– Meyer assessment (FMA), the Korean version of the Modified Barthel Index, and fall history. RESULTS: The random forest algorithm excelled (receiver operating characteristic area under the curve; AUC = 0.91) in predicting balance improvement, outperforming the SVM (AUC = 0.76) and XGboost (AUC = 0.71). Key determinants identified were knee active torque, age, step count, number of RAGT sessions, FMA, and hip torque. CONCLUSION: The random forest algorithm was the best prediction model for identifying fall-related balance and RAGT determinants, highlighting the importance of key factors for successful RAGT outcome performance in fall-related balance improvement.
Effect of virtual cardiac rehabilitation during the COVID-19 pandemic on health-related quality of life of older adults with cardiac problems
Authors: Wlazlik-Supernak Alexandra , Margey Ronan , O’Neill Emer , Timmons Suzanne , O’Shea Emma
Published: July 2024

BACKGROUND: In March 2020, on the recommendation of the Chief Medical Officer, routine elective hospital medical activity was suspended and a national ‘stay at home order’ was implemented for a period of 16 weeks in response to the global COVID-19 pandemic. Most hospitals suspended their Cardiac Rehabilitation services. Many older adults did not receive the medical help they needed. This will have an impact on their health-related quality of life (HRQoL) now and thereafter. OBJECTIVE: Explore the effect of Virtual Cardiac Rehabilitation VCR delivered during Covid-19 Pandemics on the overall health-related quality of life (HRQoL) of older adults with cardiac problems. METHODS: A retrospective study design was used. Rand-36 scores in a population of older adults aged 60+ who participated in VCR between March 2020 and September 2021 were compared pre- and post-program. Convenience sampling method was used and only those who gave informed written consent for data use were included. SPSS version 27 was used to analyze data using descriptive statistics. RESULTS: Significant increases in median post-VCR scores, compared to pre-VCR scores (p < 0.001) were shown in the Physical domain from (95% CI 307.5–342.5). Mental health domain from (95% CI 301.5–340.5). There was statistically highly significant difference in scores in Chester Step Test METs pre- post VCR 16% (p < 0.001). There were no significant differences found in patients’ perception of Physical Function, Role Limit (Emotional) and Energy/Fatigue (p > 0.05). CONCLUSIONS: VCR delivered during Covid-19 Pandemic, had positive effect on the overall HRQoL of older adults with cardiac problems. VCR offered as an option in CR may potentially improve completion rate and facilitate behavioral modifications.
The prognostic significance and immune characteristics of bone morphogenetic proteins (BMPs) family: A pan-cancer multi-omics analysis
Authors: Chen Changsheng , Zhang Yu , Lin Yuda , Shen Chong , Zhang Zhe , Wu Zhouliang , Qie Yunkai , Zhao Gangjian , Hu Hailong
Published: July 2024

BACKGROUND: Bone morphogenetic proteins (BMPs) are a group of cancer-related proteins vital for development and progression of certain cancer types. Nevertheless, function of BMP family in pan-cancer was not detailedly researched. OBJECTIVE: Investigating expression pattern and prognostic value of the BMPs family (BMP1-8A and BMP8B) expression across multiple cancer types. METHODS: Our research integrated multi-omics data for exploring potential associations between BMPs expression and prognosis, clinicopathological characteristics, copy number or somatic mutations, immune characteristics, tumor microenvironment (TME), tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint genes and drug sensitivity in The Cancer Genome Atlas (TCGA) tumors. Furthermore, association of BMPs expression and immunotherapy effectiveness was investigated in some confirmatory cohorts (GSE111636, GSE78220, GSE67501, GSE176307, IMvigor210 and mRNA sequencing data from currently undergoing TRUCE01 clinical research included), and biological function and potential signaling pathways of BMPs in bladder cancer (BCa) was explored via Gene Set Enrichment Analysis (GSEA). Eventually, immune infiltration analysis was done via BMPs expression, copy number or somatic mutations in BCa, as well as validation of the expression levels by reverse transcription-quantitative PCR and western blot, and in vitro functional experiments of BMP8A. RESULTS: Discoveries displayed BMPs expression was related to prognosis, clinicopathological characteristics, mutations, TME, TMB, MSI and immune checkpoint genes of TCGA tumors. Anticancer drug sensitivity analysis displayed BMPs were associated with various drug sensitivities. What’s more, it was discovered that expression level of certain BMP family members related to objective response to immunotherapy. By GSEA, we discovered multiple immune-associated functions and pathways were enriched. Immune infiltration analysis on BCa also displayed significant associations among BMPs copy number variations, mutation status and infiltration level of diverse immune cells. Furthermore, differential expression validation and in vitro phenotypic experiment indicated that BMP8A significantly promoted BCa cell proliferation, migration and invasion. CONCLUSIONS: Current results confirmed significance of both BMPs expression and genomic alteration in the prognosis and treatment of diverse cancer types, and suggested that BMPs may be vital for BCa and can possibly be utilized as biomarkers for immunotherapy.
Architectural design of national evidence based medicine information system based on electronic health record
Authors: Fragidis Leonidas , Tsamoglou Sofia , Kosmidis Kosmas , Aggelidis Vassilios
Published: July 2024

BACKGROUND: The global implementation of Electronic Health Records has significantly enhanced the quality of medical care and the overall delivery of public health services. The incorporation of Evidence-Based Medicine offers numerous benefits and enhances the efficacy of decision-making in areas such as prevention, prognosis, diagnosis, and therapeutic approaches. OBJECTIVE: The objective of this paper is to propose an architectural design of an Evidence-Based Medicine information system based on the Electronic Health Record, taking into account the existing and future level of interoperability of health information systems in Greece. METHODS: A study of the suggested evidence-based medicine architectures found in the existing literature was conducted. Moreover, the interoperability architecture of health information systems in Greece was analyzed. The architecture design reviewed by specialized personnel and their recommendations were incorporated into the final design of the proposed architecture. RESULTS: The proposed integrated architecture of an Evidence-Based Medicine system based on the Electronic Health Record integrates and utilizes citizens’ health data while leveraging the existing knowledge available in the literature. CONCLUSIONS: Taking into consideration the recently established National Interoperability Framework, which aligns with the European Interoperability Framework, the proposed realistic architectural approach contributes to improving the quality of healthcare provided through the ability to make safe, timely and accurate decisions by physicians.
A hybrid model for the classification of Autism Spectrum Disorder using Mu rhythm in EEG
Authors: Radhakrishnan Menaka , Ramamurthy Karthik , Shanmugam Saranya , Prasanna Gaurav , S Vignesh , Y Surya , Won Daehan
Published: July 2024

BACKGROUND: Autism Spectrum Disorder (ASD) is a condition with social interaction, communication, and behavioral difficulties. Diagnostic methods mostly rely on subjective evaluations and can lack objectivity. In this research Machine learning (ML) and deep learning (DL) techniques are used to enhance ASD classification. OBJECTIVE: This study focuses on improving ASD and TD classification accuracy with a minimal number of EEG channels. ML and DL models are used with EEG data, including Mu Rhythm from the Sensory Motor Cortex (SMC) for classification. METHODS: Non-linear features in time and frequency domains are extracted and ML models are applied for classification. The EEG 1D data is transformed into images using Independent Component Analysis-Second Order Blind Identification (ICA-SOBI), Spectrogram, and Continuous Wavelet Transform (CWT). RESULTS: Stacking Classifier employed with non-linear features yields precision, recall, F1-score, and accuracy rates of 78%, 79%, 78%, and 78% respectively. Including entropy and fuzzy entropy features further improves accuracy to 81.4%. In addition, DL models, employing SOBI, CWT, and spectrogram plots, achieve precision, recall, F1-score, and accuracy of 75%, 75%, 74%, and 75% respectively. The hybrid model, which combined deep learning features from spectrogram and CWT with machine learning, exhibits prominent improvement, attained precision, recall, F1-score, and accuracy of 94%, 94%, 94%, and 94% respectively. Incorporating entropy and fuzzy entropy features further improved the accuracy to 96.9%. CONCLUSIONS: This study underscores the potential of ML and DL techniques in improving the classification of ASD and TD individuals, particularly when utilizing a minimal set of EEG channels.
Development of an efficient novel method for coronary artery disease prediction using machine learning and deep learning techniques
Authors: Mansoor C.M.M. , Chettri Sarat Kumar , Naleer H.M.M.
Published: July 2024

BACKGROUND: Heart disease is a severe health issue that results in high fatality rates worldwide. Identifying cardiovascular diseases such as coronary artery disease (CAD) and heart attacks through repetitive clinical data analysis is a significant task. Detecting heart disease in its early stages can save lives. The most lethal cardiovascular condition is CAD, which develops over time due to plaque buildup in coronary arteries, causing incomplete blood flow obstruction. Machine Learning (ML) is progressively used in the medical sector to detect CAD disease. OBJECTIVE: The primary aim of this work is to deliver a state-of-the-art approach to enhancing CAD prediction accuracy by using a DL algorithm in a classification context. METHODS: A unique ML technique is proposed in this study to predict CAD disease accurately using a deep learning algorithm in a classification context. An ensemble voting classifier classification model is developed based on various methods such as Naïve Bayes (NB), Logistic Regression (LR), Decision Tree (DT), XGBoost, Random Forest (RF), Convolutional Neural Network (CNN), Support Vector Machine (SVM), K Nearest Neighbor (KNN), Bidirectional LSTM and Long Short-Term Memory (LSTM). The performance of the ensemble models and a novel model are compared in this study. The Alizadeh Sani dataset, which consists of a random sample of 216 cases with CAD, is used in this study. Synthetic Minority Over Sampling Technique (SMOTE) is used to address the issue of imbalanced datasets, and the Chi-square test is used for feature selection optimization. Performance is assessed using various assessment methodologies, such as confusion matrix, accuracy, recall, precision, f1-score, and auc-roc. RESULTS: When a novel algorithm achieves the highest accuracy relative to other algorithms, it demonstrates its effectiveness in several ways, including superior performance, robustness, generalization capability, efficiency, innovative approaches, and benchmarking against baselines. These characteristics collectively contribute to establishing the novel algorithm as a promising solution for addressing the target problem in machine learning and related fields. CONCLUSION: Implementing the novel model in this study significantly improved performance, achieving a prediction accuracy rate of 92% in the detection of CAD. These findings are competitive and on par with the top outcomes among other methods.
The relationship between sleep quality and fear of COVID-19, anxiety, personality traits in working women
Authors: Keskin Gülseren , Gümüşsoy Süreyya , Taşdemir Yiğitoğlu Gülay
Published: July 2024

BACKGROUND: Disasters such as the COVID-19 pandemic have serious traumatic effects on people, who may experience sleep problems, anxiety, and fear in the face of such a stressor. OBJECTIVE: This study is conducted to examine the relationship between sleep quality and fear of COVID-19, anxiety, and personality traits in working women. METHOD: This research was a descriptive study between June to August 2021. The study was conducted with 425 participants. The Pittsburgh Sleep Quality Index, COVID-19 Fear Scale, Beck Anxiety Scale, and the revised Eysenck Personality Questionnaire-Short Form were applied to the participants. T-test, ANOVA, and Pearson correlation analysis, were used. RESULTS: In the study, it was found that the total average score of the Fear of COVID-19 Scale was 18.83±5.5, while the score of sleep quality was 5.40±3.3 and the anxiety score was 14.01±12.4. On the other hand, the score of Extraversion was determined as 3.73±1.7, Neuroticism was 3.79±1.8, and Psychoticism was 1.97±1 in the study. Moreover, a statistically significant positive correlation was found between sleep quality and fear of COVID-19, anxiety, and neuroticism in working women (p < 0.05). CONCLUSION: Sleep quality, sleep latency, sleep disturbance; daytime dysfunction, use of sleep medication, sleep duration, sleep latency with anxiety; sleep latency, sleep quality, daytime dysfunction, sleep duration were found to be linked to neuroticism, and use of sleep medication and sleep duration were found to be linked to psychoticism. It was concluded that there was a relationship between sleep quality and fear of COVID-19, anxiety, and personality traits in working women.
What does corporate environmental citizenship really mean?
Authors: Lee Chin Tay , Lee Chee Tay
Published: July 2024

BACKGROUND: Corporate environmental citizenship receives little scholarly attention and the definitions remain unclear due to past studies defining corporate environmental citizenship in different perspectives. OBJECTIVE: The aim of this paper is to clarify the conceptualization of corporate environmental citizenship. It also proposes a plausible and useful definition for corporate environmental citizenship. METHODS: Previous environmental related studies are selected based on their relevance to the definitions. The selected studies then are examined to propose the new definition of corporate environmental citizenship. The online databases being utilized are ScienceDirect, Emerald, Taylor and Francis and Ebscohost. RESULTS: The new definition of corporate environmental citizenship is proposed: managerial recognition on the importance of environmental issues and integrating the environmental concerns into the organizational process. CONCLUSIONS: This study hopes to provoke more discussions about the definitions of corporate environmental citizenship as corporate environmental citizenship’s definition has attracted very little attention so far. This paper provides useful understanding for managers regarding the roles of corporate environmental citizenship. This is important as they strive to excel in the business performance in the highly competitive market. This in turn facilitates them to focus their business strategies.
Design of a multi-carrier X-ray source for communication with energy modulation information
Authors: Gao Youtao , Wu Yixiang , Li Shijia , Hei Daqian , Tang Yajun
Published: July 2024

X-ray communication is a kind of space communication technology which uses X-ray as information carrier. In order to improve the information transmission capacity, communication rate and anti-interference ability of X-ray communication, we proposes to design a novel multi-target X-ray source. The source is composed of a fast switching module of light channels based on FPGA technology and four photoelectric X-ray tubes with different target materials: Cr, Fe, Ni, and Cu. Using Geant4 software, we determined the optimal target thickness for each material, which enabled us to fully leverage the characteristic X-rays for multi-channel signal modulation transmission. Moreover, using CST software for particle trajectory simulation and optimization of the electron beam revealed that at a tube voltage of 20 kV, the focus area measures approximately 1.2 mm×1.2 mm. The simulations show that four kinds of spectra with high distinctiveness can be generated from the Cr, Fe, Ni, and Cu targets. Within a single modulation period, these spectra can be combined in various ways to create 16 different X-ray spectra signals, thereby increasing the number of communication elements and enhancing the information transmission rate.
Analisis Kadar Tumor Necrosis Factor-Alfa (Tnf-Alpha) Pada Pasien Tuberkulosis Dengan Diabetes Melitus Dan Pasien Tuberkulosis Tanpa Diabetes Melitus Di RSP UNHAS Makassar
Authors: Narto Sunarto , Restami Dewi Nita
Published: July 2024

Tuberkulosis merupakan penyakit infeksi bakteri menahun yang disebabkan oleh Mycobakterium tuberculosis, atu basil tahan asam yang ditularkan melalui udara sedangkan Diabetes Melitus adalah penyakit metabolik yang di tandai dengan tingginya kadar glukosa darah (hyperglikemia) sebagai akibat dari kekurangan sekresi insulin, gangguan aktifitas insulina atau keduanya, Hubungan antara keduanya telah terbukti. Diabetes melitus merupakan faktor risiko TB dan dapat mempengaruhi keberadaan penyakit serta respon terhadap pengobatan. Selain itu, TB dapat menyebabkan intoleransi glukosa dan memperburuk kontrol glikemik pada penderita DM. Tumor Necrosis Factor Alfa (TNF-Alfa) adalah sitokin yang diproduksi terutama oleh monosit atau makrofag, juga diproduksi oleh sel mast, sel endotel, jaringan saraf dan sel limfosit seperti limfosit T dan B dan sel natural killer (NK). Tujuan dari penelitian ini adalah untuk mengetahui hubungan kadar Tumor Necrosis Factor-Alfa (TNF-Alfa) pada pasien tuberkulosis dengan diabetes melitus dan pasien tuberkulosis tanpa diabetes melitus. Sampel yang digunakan yaitu sampel pasien TB dengan DM dan pasien TB tanpa DM sebanyak 24 responden yang menandakan adanya hubungan kadar Tumor Necrosis Factor-Alfa (TNF-Alfa) pada pasien tuberkulosis dengan diabetes melitus dan pasien tuberkulosis tanpa diabetes melitus. Hasil penelitian ini adalah tidak terdapat hubungan kadar TNF-Alfa antara pasien tuberkulosis dengan diabetes melitus dan pasien tuberkulosis tanpa diabetes melitus.
Kata Kunci : Tuberkulosis Paru, TNF-Alfa
Deteksi Gen Resistensi Karbapenemase Dan Metallo-Β-Lactamase Pada Acinetobacter Baumannii
Authors: Zuchrullah Mukhtasyam , Nurdin Erpi
Published: July 2024

Peningkatan resistensi terhadap antibiotik golongan karbapenem merupakan salah satu fenomena yang harus diwaspadai. Acinetobacter baumannii merupakan salah satu bakteri penyebab infeksi berat yang didapatkan di rumah sakit. Penelitian ini bertujuan untuk mendeteksi gen intrinsik dan gen yang membawa resistensi obat golongan karbapenem terhadap A. baumannii. Penelitian ini dilaksanakan di Laboratorium HUM-RC RSPTN Universitas Hasanuddin Makassar. Desain penelitian ini adalah deskriptif eksperimental laboratorium dengan jumlah sampel 50 isolat yang didapatkan dengan cara total sampling yang dikumpulkan dari RSUP Wahidin Sudirohusodo Makassar. Data yang dianalisis adalah hasil karakteristik isolat, uji sensitivitas dengan menggunakan Vitek-2, uji genotipe gen intrinsik OXA-51 dan blaIMP-1 dengan menggunakan Polymerase Chain Reaction. Hasil penelitian menunjukkan bahwa dari total 50 isolat A. baumannii, ditemukan paling banyak pada sampel sputum sejumlah 30 isolat (60%). Dari total 50 sampel uji sensitivitas antibiotik, isolat A. baumanni paling banyak resisten terhadap meropenem 14 isolat (28%) kemudian imipenem 9 isolat (18%), dan Doripenem 9 isolat (18%). Gen intrinsik OXA-51 ditemukan pada semua isolat sampel sedangkan hanya satu isolat dari A. baumannii yang mampu memproduksi enzim metallo-β-Lactamase (MBL) dan membawa gen blaIMP-1 yaitu pada sampel urine yang seluruhnya resisten terhadap ketiga golongan obat karbapenem.
Kata Kunci : Acinetobacter baumannii, Karbapenem, MBL, Polymerase Chain Reaction
Evaluasi Penyimpanan Vaksin Pada Puskesmas Kabupaten Maros, Sulawesi Selatan
Authors: Paluseri Andi , Nurul Mufliha Andi Naura , Hendrarti Wahyu , Lukman Muslimin  , Guntur Muhammad
Published: July 2024

Evaluation of Storing Vaccines at the Community Health Center in Maros Regency, South Sulawesi
Vaccines are a biological preparation whose storage requires special attention because they are compassionate. Improper storage and distribution of vaccines will reduce the quality of the vaccine so that its effectiveness will also decrease or even not be effective at all. This study aims to determine the description of vaccine storage at the Community Health Center, Regency of Maros, South Sulawesi. This research is a qualitative descriptive study conducted at 14 Community Health Centers in April - June 2022. Data was collected using direct interview techniques with vaccine officials and direct observation at vaccine storage areas. The research results show that the storage system meets the minimum requirements, although several aspects still do not meet the criteria due to a lack of storage facilities. Vaccines include vaccine solvent and vaccine layout in a refrigerator equipped with a generator, not exposed to direct sunlight, and in a room with sufficient air circulation. There are vaccine vial monitors (VVM) in conditions A and B. Incoming and outgoing vaccines are reported and recorded on the stock card. Likewise, the COVID-19 vaccine is also stored under reasonable control. So, it can be concluded that the vaccine storage system at 14 community health centers in the district. Maros has fulfilled the requirements of the Ministry of Health, Republic of Indonesia, No. 12 in 2017.
Vaksin merupakan salah satu sediaan biologi yang penyimpanannya membutuhkan perhatian khusus karena sangat sensitif. Penyimpanan dan pendistribusian vaksin yang tidak tepat akan menurunkan mutu vaksin sehingga efektivitasnya juga menurun bahkan tidak berkhasiat sama sekali. Penelitian ini bertujuan untuk mengetahui gambaran penyimpanan vaksin di Puskesmas Kab. Maros, Sulawesi Selatan. Penelitian ini bersifat deskriptif kualitatif yang dilakukan terhadap 14 puskesmas pada bulan April hingga Juni 2022. Data dikumpulkan dengan teknik wawancara langsung pada petugas penanggung jawab vaksin dan melakukan observasi langsung pada tempat penyimpanan vaksin. Hasil penelitian menunjukkan bahwa sistem penyimpanan sudah memenuhi syarat minimal walaupun masih ada beberapa aspek yang tidak terpenuhi kriteria karena kurangnya fasilitas penyimpanan. Vaksin termasuk pelarut vaksin dan tata letak vaksin di dalam refrigerator yang dilengkapi dengan generator (genset), tidak terkena sinar matahari langsung, dan ruangan yang memiliki sirkulasi udara yang cukup. Terdapat vaccine vial monitor (VVM) yang berada dalam kondisi A dan B. Vaksin yang masuk maupun keluar terlapor dan tercatat pada kartu stok. Begitu pula dengan vaksin covid-19 juga tersimpan dengan kontrol yang baik pula. Sehingga dapat disimpulkan sistem penyimpanan vaksin pada 14 Puskesmas di Kab. Maros telah memenuhi syarat PerMenKes No. 12 tahun 2017.
Usia Pengguna Kontrasepsi Depo Medroksi Progesteron Asetat (DMPA) Terhadap Peningkatan Berat Badan Akseptor Keluarga Berencana Di Puskesmas Pekkae Kabupaten Barru
Authors: Husain Hastuti , Nazar Putri Awalia , Marhaeni Marhaeni , Subriah Subriah
Published: July 2024

Kontrasepsi yang paling banyak diminati dan populer di kalangan perempuan yaitu depo medroksi progesteron asetat (DMPA) karena dianggap praktis dan mudah didapatkan di tempat pelayanan kesehatan. Tujuan penelitian untuk mengetahui pengaruh usia dan peningkatan berat badan terhadap penggunaan kontrasepsi DMPA di Puskesmas Pekkae. Metode penelitian bersifat survey analitik, dengan pendekatan cross sectional. Populasi pada penelitian ini adalah semua akseptor KB Puskesmas Pekkae sebanyak 909 akseptor dan sampel akseptor yang menggunakan DMPA sebanyak 62 akseptor.Penelitian dilakukan bulan Februari-Juni 2021 menggunakan format pengumpulan data. Dianalisis secara bivariat menggunakan uji Chi-square α = 0,05.
Hasil analisisi univariat menunjukkan bahwa sebanyak 56 orang (90,3%) akseptor mengalami peningkatan berat badan dan hanya 6 orang (9,7%) akseptor yang berat badannya tidak naik.Dan berdasarkan kelompok umur dalam katagori aman secara reproduktif sebesar 59 orang (95,2%) akseptor,hanya ada 2 orang(3,2%) akseptor yang termasuk katagori risiko tinggi untuk umur kurang <20 tahun dan juga satu orang akseptor dengan katagori risiko tinggi untuk >35 tahun (1,6%). Hasil analisis bivariat menunjukkan bahwa umur (Pvalue=1,000) dan peningkatan berat badan (Pvalue= p=0,000).Kesimpulan bahwa tidak pengaruh yang signifikan umur penggunan alat kontraspesi DMPA terhadap peningkatan berat badan akseptor KB dan penggunaan alat kontrasepsi DMPA berpengaruh secara signifikan terhadap  peningkatan berat badan akseptor KB. Disarankan bagi petugas kesehatan untuk pemahaman terhadap akseptor DMPA tanpa membedakan umur untuk belajar mengatur pola makan sehingga berat badan dapat terkontrol.
Kata Kunci : Berat badan, Kontrasepsi, Usia
Kombinasi Jus Jambu Biji dan Kapsul Daun Kelor Mengurangi Kejadian Anemia Pada Remaja Putri di SMA Negeri 6 Maros
Authors: Prasetyo Wahdania Putri , B Suriani , Amin Wirawati , Sonda Maria , Sabur Fitriati
Published: July 2024

Anemia merupakan sebuah kondisi saat kadar didalam sel darah merah (protein) pembawa oksigen berada di bawah normal karena kurangnya zat besi, yang menyebabkan penurunan hemoglobin dan rendahnya kadar ferritin. Anemia dapat dicegah dengan cara nonfarmakologis. Salah satu metode alternatif untuk mengobati anemia adalah dengan mengonsumsi buah Contohnya dengan mengonsumsi jambu biji dan daun kelor. Tujuan dari penelitian ini adalah Untuk mengetahui efektivitas pemberian kombinasi jus jambu biji dan kapsul daun kelor dalam mengurangi kejadian anemia pada remaja putri.Jenis penelitian ini adalah penelitian kuantitatif dengan menggunakan Quashi Eksperimental dengan rancangan pre and post test without control. Metode pengambilan sampel yang digunakan adalah Purposive sampling dengan jumlah sampel sebanyak 17 responden. Analisis data dilakukan menggunakan uji non-parametrik wilcoxon.Hasil penelitian diperoleh bahwa Terdapat pengaruh yang signifikan antara kombinasi jus jambu biji dan kapsul daun kelor dalam mengurangi kejadian anemia pada remaja putri kelas 11 MIPA SMA Negeri 6 Maros. Dan dapat simpulkan bahwa Kombinasi jus jambu biji dan kapsul daun kelor efektif dalam meningkatkan kadar Hb pada remaja putri.Selanjutnya diharapkan agar dapat memperhatikan pentingnya mengonsumsi buah dalam menjaga kadar Hb dalam tubuh.