bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wind Speed Estimation and Power Generation Prediction Using A Hybrid Deep Multilayer Perceptron with Clonal Selective Optimisation
Authors: Kumar T. Vinoth 
Published: April 2024

Abstract

Wind energy is fast developing energy resource as it is renewable, pollution free and abundant. The nonlinear and fluctuation of wind are large demand for enhancing the reliability and accuracy of the power system that combines the wind speed. With an exact wind speed data, power system operators predict the power output for system planning and scheduling. Wind speed prediction is an essential factor in forecasting to attain the efficient wind power utilization. But the prediction time and accuracy performance were not improved using existing techniques. In order to address this problem, Deep Multilayer Perceptron Neural Network based Clonal Selective Optimization (DMLPNN-CSO) technique is introduced. The main objective of DMLPNN-CSO technique is to improve the performance of power generation prediction through wind speed estimation with higher accuracy based on mean air temperature, relative humidity and vapor pressure data. DMLPNN-CSO technique comprises two processes, namely deep multilayer perceptron neural network and clonal data selection algorithm. Initially in DMLPNN-CSO technique, wind turbine is considered as the input and given to the input layer in deep multilayer perceptron neural network. Wind turbine information is extracted and given to the hidden layer 1. In this layer, data preprocessing is performed through the median filter for removing unnecessary data. After that, the preprocessed data is given to the hidden layer 2 to estimate the wind speed. The estimated values are collected and get matched with the pre-stored values in the output layer by using softsign activation function. After estimation of wind speed, the optimal data gets selected by using clonal data selection algorithm for predicting the power generation. Clonal data selection algorithm performs the sorting, cloning and guassian mutation for finding the optimal value in power generation prediction. This in turn helps to improve prediction accuracy and reduce the time consumption. Experimental evaluation of proposed DMLPNN-CSO technique is carried out with respect to number of wind turbine data and data samples. The results showed that DMLPNN-CSO technique produces higher prediction accuracy and wind speed estimation rate when compared to state-of-the-art works.
Response to clozapine in treatment resistant schizophrenia related to alterations in regional cerebral blood flow
Authors: Sun Junyu , Zelaya Fernando , Sendt Kyra-Verena , McQueen Grant , Gillespie Amy , Lally John , Howes Oliver , Barker Gareth , McGuire Philip , MacCabe James , Egerton Alice 
Published: April 2024

Abstract

Neuroimaging studies indicate that in treatment resistant schizophrenia (TRS), alterations in regional cerebral blood flow (CBF) during clozapine treatment may vary according to the clinical response. To date, these studies have involved radiotracers. Here, we used arterial spin labelling (ASL) to compare CBF in participants with TRS (N=36) before starting treatment with clozapine and in healthy volunteers (N=16). We then compared CBF before and after 12 weeks of treatment with clozapine in TRS participants (N=24), in relation to changes in Positive and Negative Syndrome Scale for Schizophrenia (PANSS) scores over the treatment period. At baseline, global CBF and CBF in frontal, temporal, and parietal regions were lower in participants with TRS than in healthy volunteers. After covarying for global CBF and age, lower CBF in frontal, temporal, and parietal regions was still evident. In the TRS group, higher striatal CBF at baseline was associated with greater improvement in total and general symptoms, and higher hippocampal CBF was associated with greater improvement in total and positive symptoms. Over the course of treatment there were longitudinal decreases in CBF in the anterior cingulate cortex (ACC) and increases in the left postcentral area. Longitudinal reductions in CBF in the ACC and thalamus were associated with less improvement in negative (ACC), positive (thalamus), and total (thalamus) symptoms. These findings indicate that the effect of clozapine in people with TRS may be related to regional CBF, and that assessing CBF has the potential to help in the stratification of this group according to clozapine response.
The Bayesian Central Limit Theorem for Exponential Family Distributions: A Geometric Approach
Authors: Goehle Geoff 
Published: April 2024

Abstract

The Bernstein-von Mises theorem, also known as the Bayesian Central Limit Theorem (BCLT), states that under certain assumptions a posterior distribution can be approximated as a multivariate normal distribution as long as the number of pseudo-observations is large. We derive a form of the BCLT for the canonical conjugate prior of a regular exponential family distribution using the machinery of information geometry. Our approach applies the core approximation for the BCLT, Laplace's method, to the free-entropy (i.e., log-normalizer) of an exponential family distribution. Additionally, we formulate approximations for the Kullback-Leibler divergence and Fisher-Rao metric on the conjugate prior manifold in terms of corresponding quantities from the likelihood manifold. We also include an application to the categorical distribution and show that the free-entropy derived approximations are related to various series expansions of the gamma function and its derivatives. Furthermore, for the categorical distribution, the free-entropy approximation produces higher order expansions than the BCLT alone.
Frequency ,Characteristics And Risk Factors Of Malnutrition Among Children Under Five Years Old In Wad Medni
Authors: abdalla Arwa faisal mohammed , Jaber Mohammed Hammad 
Published: April 2024

Abstract

Background
Malnutrition is the most common nutritional disorder in developing countries and it remains one of the most common causes of morbidity and mortality among children worldwide. Childhood malnutrition is a multi-dimensional problem. An increase in household income is not sufficient to reduce childhood malnutrition if children are deprived of food security, education, access to water, sanitation and health services. However, due to regional variations in prevalence of acute malnutrition, it is important to explore the risk factors specific to the region, for designing and implementing public health interventions.
Objective
To assess the prevalence and risk factors of malnutrition among children under five years
Methods
A descriptive study enrolled 100 children under five years in Helat Hassan Health Centre, Wad-Medani, Gezira State during the period from November 2020 - March 2021. Data regarding children and families characteristics, nutritional history, health and medical history and anthropometric measurements were collected. Malnutrition was defined according to WHO guideline as -3SD of age specific BMI
Results
Among 100 children, 59(59%) males and 41(41%) females, their mean age was 33 ± 18 months. The frequency of malnutrition was 10% (n = 10) and underweighting was 18% (n = 18). Child's related risk factors associated with malnutrition were; children order above 4th (P. value = 0.000) and number of under 5 children in family above 3 children (P. value = 0.00). Family's related risk factors associated with malnutrition were; younger mother blow 30 years (P. value = 0.001), non-mother (relative) caregivers (P. value = 0.000), illiterate mothers (P. value = 0.046), employed mothers (P. value = 0.000), relative as income responsible (P. value = 0.009), lack of medical insurance (P. value = 0.047), lack of in-home source of water (P. value = 0.003), and low income blow 6,000 SDG (P. value = 0.000). Nutritional related risk factors associated with malnutrition were; lack of exclusive breastfeeding (P. value = 0.000), less than three meals per day (P. value = 0.021), lack of vegetables and fruits in daily nutrition (P. value = 0.006) and lack of milk and dietary products in daily nutrition (P. value = 0.000). Health related risk factors associated with malnutrition were; illness as cause of health care center visit (P. value = 0.018), anemia (P. value = 0.002), admission to hospital in last 2 months (P. value = 0.005), fever, cough, runny rose or chest infection in last 2 weeks (P. value = 0.032), chronic diarrhea (20.7%; P. value = 0.018) and history of malnutrition (P. value = 0.001).
Conclusion
The frequency of malnutrition is not neglectable in Helat Hassan Health Centre at Wad-Medani. Malnutrition was found to be multi-factorial and associated with child, family, nutritional and health related factors. Effective, efficient and equitable program and intervention should be designed to reduce child malnutrition
Exploring the Influence of Human Activities and COVID-19 Lockdown on Urban Air Quality in Rajasthan, India
Authors: Kumar Porush 
Published: April 2024

Abstract

This research provides a comprehensive analysis of the intricate relationships between human activities, air quality dynamics, and the impact of the COVID-19 lockdown in seven major cities of Rajasthan, India - Ajmer, Alwar, Jaipur, Jodhpur, Kota, Pali, and Udaipur. The study meticulously examines the fluctuations in concentrations of key pollutants (PM2.5, PM10, NO2, and SO2) from 2018 to 2022, covering pre-lockdown, lockdown, and post-lockdown phases. Significant reductions in air pollutant concentrations were observed during the lockdown period, attributed to decreased anthropogenic activities, notably vehicular emissions and industrial operations. However, post-lockdown, a rebound effect was observed, indicating the challenges in sustaining air quality improvements amid economic resurgence. Notable findings include substantial declines in PM2.5, PM10, NO2, and SO2 levels during the lockdown, followed by increases to varying degrees post-lockdown. The cities of Ajmer, Alwar, and Jaipur demonstrated divergent trends in pollutant concentrations, emphasizing the complex interplay between environmental factors and human behavior. This research contributes to the ongoing discourse on air quality management by providing insights into the impacts of temporary interventions, such as lockdowns, on urban air quality dynamics. The findings underscore the need for holistic approaches integrating environmental policies, industrial regulations, and public health initiatives to mitigate air pollution’s adverse effects and safeguard public health and environmental well-being in urban regions.
Tracing Alzheimer's Genetic Footprints: A Pioneering Longitudinal Study Using Artificial Intelligence to Unravel Mutation-Driven Risks and Progression in Virtual Patients; Part 2 – The APP, PSEN1 and PSEN2 mutations
Authors: Danter Wayne 
Published: April 2024

Abstract

Alzheimer’s Disease (AD), the most prevalent neurodegenerative disorder, presents complex challenges in early diagnosis and management. This study, leveraging the innovative aiHumanoid platform, explores the genetic underpinnings of AD through a longitudinal analysis of mutations in APP, PSEN1, and PSEN2 genes. Using virtual patient simulations that integrate extensive medical and genetic literature, we examined the influence of these mutations on disease progression and biomarker development from early childhood through advanced age. Our findings reveal distinct progression patterns associated with these genetic variants, highlighting their potential in identifying early biomarkers, and refining diagnostic strategies. This part of our research broadens our understanding by including a wider array of genetic factors, thereby enhancing the potential for personalized treatment approaches. Ethical considerations regarding the use of AI in research were carefully addressed to ensure responsible technology integration into healthcare settings. The insights gained emphasize the transformative potential of AI in advancing AD research, laying a groundwork for future innovations in diagnostic and therapeutic methodologies.
A study on the suitability of Groundwater from physicochemical water quality parameters and using Water Quality Index (WQI)
Authors: Ali Niaz , Ali Fraraz 
Published: April 2024

Abstract

In the realm of global groundwater quality, including the Sindh province of Pakistan, there exists a significant risk due to various factors such as population growth, urban development, over-exploitation of groundwater resources, and contamination from sewage and industrial effluents. This research focuses on assessing the groundwater quality in Taluka Dokri by analyzing its physicochemical parameters. Findings indicate that 2.56% of samples exceeded permissible limits for color and odor, while approximately 23% were deemed unsuitable for drinking based on taste. Furthermore, elevated concentrations of Ca, Mg, TH, TDS, EC, and Cl rendered 30.77%, 38.46%, 30.77%, 41%, 100%, and 38.46% of samples unfit for drinking, respectively. Utilizing the Water Quality Index (WQI), analysis revealed 10.3%, 66.67%, and 23% of samples to be slightly, moderately, and highly polluted, respectively. Specific areas such as UC Tatri, Baghi Bindi, and Wakro exhibited slight pollution, while UCs like New Badh, Old Badh, and Dokri City showed extreme pollution. Proper treatment is necessary before consuming groundwater in these areas to mitigate health risks.
Monthly streamflow forecasting based on meteorological data from a nearby station
Authors: Nohani Ebrahim , Karimipour Ahmadreza , Khazaei Solmaz , Haroni Hossein Zamani , Akhmatov Sheikh-Mansur , Yegorov Aleksandr , Zolfaghari Maryam , Hatamiafkoueieh Javad , Heddam Salim , Tiefenbacher John 
Published: April 2024

ABSTRACT
Monthly streamflow forecasting is critical for improving water resource management. In this study, several base-classifier data-mining algorithms – conjunctive rule (CR), isotonic regression (ISOR), sequential minimal optimization regression (SMOR) – as well as several hybrid data-mining techniques – disjoint aggregating or dagging (DA)-CR, DA-ISOR, and DA-SMOR – that combine dagging with these algorithms were developed and applied to forecasting streamflow 3 and 12 months into the future (i.e., Qt+3 and Qt+12) based on meteorological data from a nearby station. Thirty years of data (from 1988 to 2018) that included precipitation, minimum relative humidity, maximum relative humidity, evaporation, hours of sunshine, maximum temperature, minimum temperature, wind speed, and streamflow were collected at the Kermanshah synoptic station were input to develop and evaluate several models. Varying combinations of the input data were tested to find the optimal set to employ. The models were validated and compared using several quantitative statistical indices. Though all satisfactorily predicted monthly streamflow, the hybrid models (DA-CR, DA-ISOR, and DA-SMOR) outperformed the base-classifier models (CR, ISOR, and SMOR), proving that dagging improved data-mining models significantly. Of the hybrid models, D-SMOR was the best. The models developed in this study are cost-effective tools for quick and accurate monthly streamflow forecasting.
Correlation between antenatal care (ANC) visits and caffeine beverage consumption habits with the incidence of anemia in third trimester pregnant women in Health Centers, Bantul Region
Authors: Widiyanti Anggi , Fatimah Fatimah , Dwiarini Muafiqoh 
Published: April 2024

<p><em>mother and baby. Efforts made by health workers to reduce the occurrence of anemia by conducting Antenatal Care (ANC) visits, and providing Communication, Information, and Motivation (KIM) and administering Fe tablets. Consumption of Fe tablets is better consumed using plain water because if Fe tablets are taken together with tea and coffee it can inhibit iron absorption.</em></p><p><strong><em>Objectives: </em></strong><em>Determine the relationship between Antenatal Care (ANC) visits and consumption habits of caffeinated drinks with the incidence of anemia in third trimester pregnant women at the Health Center in Bantul.</em></p><p><strong><em>Methods: </em></strong><em>This type of research uses quantitative research with a cross sectional approach. Sampling using simple random sampling and quota sampling with the number of respondents 180 pregnant women using predetermined characteristics. The research instrument used a questionnaire on the variable ANC visits and consumption habits of caffeinated drinks and used the KIA handbook on the variable incidence of anemia in pregnant women. The bivariate analysis technique uses the Kendal Tau test.</em></p><p><strong><em>Results: </em></strong><em>In the ANC visit variable, a p value = 0.029 (p &lt;0.05) was obtained, indicating that there is a relationship between Antenatal Care (ANC) visits and the incidence of anemia in third trimester pregnant women. In the habitual variable of caffeine consumption, the p-value = 0.004 (p &lt;0.05), indicating that there is a relationship between the habit of consuming caffeinated drinks and the incidence of anemia in third trimester pregnant women.</em></p><p><strong><em>Conclusions : </em></strong><em>There is a relationship between Antenatal Care (ANC) visits and the incidence of anemia and there is a relationship between the habit of consuming caffeinated drinks and the incidence of anemia in third trimester pregnant women at the Health Center in Bantul.</em></p>
Online Visibility and Scientific Relevance of Strabismus Research: Bibliometric Analysis
Authors: Stupnicki Aleksander , Suresh Basil , Jain Saurabh 
Published: April 2024

Background
Quality and accuracy of online scientific data are crucial, given that the internet and social media serve nowadays as primary sources of medical knowledge.

Objective
This study aims to analyze the relationship between scientific relevance and online visibility of strabismus research to answer the following questions: (1) Are the most popular strabismus papers scientifically relevant? (2) Are the most high-impact strabismus studies shared enough online?

Methods
The Altmetric Attention Score (AAS) was used as a proxy for online visibility, whereas citations and the journal’s impact factor (IF) served as a metric for scientific relevance. Using “strabismus” as a keyword, 100 papers with the highest AAS and 100 papers with the highest number of citations were identified. Statistical analyses, including the Spearman rank test, linear regression, and factor analysis, were performed to assess the relationship between AAS, citations, a journal’s IF, and mentions across 18 individual Web 2.0 platforms.

Results
A weak, positive, statistically significant correlation was observed between normalized AAS and normalized citations (P<.001; r=0.27) for papers with high visibility. Only Twitter mentions and Mendeley readers correlated significantly with normalized citations (P=.02 and P<.001, respectively) and IF (P=.04 and P=.009, respectively), with Twitter being the strongest significant predictor of citation numbers (r=0.53). For high-impact papers, no correlation was found between normalized citations and normalized AAS (P=.12) or the IF of the journal (P=.55).

Conclusions
While clinical relevance influences online attention, most high-impact research related to strabismus is not sufficiently shared on the web. Therefore, researchers should make a greater effort to share high-impact papers related to strabismus on online media platforms to improve accessibility and quality of evidence-based knowledge for patients.
A Digital Microintervention Supporting Evidence-Based Parenting Skills: Development Study Using the Agile Scrum Methodology
Authors: Hodson Nathan , Woods Peter , Sobolev Michael , Giacco Domenico 
Published: April 2024

Background
Conduct disorder increases risks of educational dropout, future mental illness, and incarceration if untreated. First-line treatment of conduct disorder involves evidence-based parenting skills programs. Time-outs, a frequent tool in these programs, can be effective at improving behavior, and recent apps have been developed to aid this process. However, these apps promote the use of time-outs in inconsistent or developmentally inappropriate ways, potentially worsening behavior problems. Digital microinterventions like these apps could guide parents through high-quality time-outs in the moment, but current time-out apps lack features promoting adherence to the evidence-based best practice. Agile scrum is a respected approach in the software development industry.

Objective
We aimed to explore the feasibility of using the agile scrum approach to build a digital microintervention to help parents deliver an evidence-based time-out.

Methods
The agile scrum methodology was used. Four sprints were conducted. Figma software was used for app design and wireframing. Insights from 42 expert stakeholders were used during 3 sprint reviews. We consulted experts who were identified from councils around the Midlands region of the United Kingdom and charities through personal contacts and a snowballing approach.

Results
Over 4 development sprints from August 2022 to March 2023, the app was iteratively designed and refined based on consultation with a diverse group of 42 experts who shared their knowledge about the content of common parenting programs and the challenges parents commonly face. Modifications made throughout the process resulted in significant app enhancements, including tailored timer algorithms and enhanced readability, as well as an onboarding zone, mindfulness module, and pictorial information to increase inclusivity. By the end of the fourth sprint, the app was deemed ready for home use by stakeholders, demonstrating the effectiveness of our agile scrum development approach.

Conclusions
We developed an app to support parents to use the evidence-based time-out technique. We recommend the agile scrum approach to create mobile health apps. Our experience highlights the valuable role that frontline health and social care professionals, particularly those working with vulnerable families, can play as experts in scrum reviews. There is a need for research to both evaluate the impact of digital microinterventions on child behavioral change and also create digital microinterventions that cater to non–English speakers and individuals who participate in parenting programs in settings outside the United Kingdom.