A Decision Support System for Liver Diseases Prediction: Integrating Batch Processing, Rule-Based Event Detection and SPARQL Query

Liver diseases pose a significant global health burden, impacting a substantial number of individuals and exerting substantial economic and social consequences. Rising liver problems are considered a fatal disease in many countries, such as Egypt, Molda, etc. The objective of this study is to construct a predictive model for liver illness using Basic Formal Ontology (BFO) and detection rules derived from a decision tree algorithm. Based on these rules, events are detected through batch processing using the Apache Jena framework. Based on the event detected, queries can be directly processed using SPARQL. To make the ontology operational, these Decision Tree (DT) rules are converted into Semantic Web Rule Language (SWRL). Using this SWRL in the ontology for predicting different types of liver disease with the help of the Pellet and Drool inference engines in Protege Tools, a total of 615 records are taken from different liver diseases. After inferring the rules, the result can be generated for the patient according to the DT rules, and other patient-related details along with different precautionary suggestions can be obtained based on these results. Combining query results of batch processing and ontology-generated results can give more accurate suggestions for disease prevention and detection. This work aims to provide a comprehensive approach that is applicable for liver disease prediction, rich knowledge graph representation, and smart querying capabilities. The results show that combining RDF data, SWRL rules, and SPARQL queries for analysing and predicting liver disease can help medical professionals to learn more about liver diseases and make a Decision Support System (DSS) for health care

Classification of Physiological Signals for Emotion Recognition using IoT

Emotion recognition gains huge popularity now a days. Physiological signals provides an appropriate way to detect human emotion with the help of IoT. In this paper, a novel system is proposed which is capable of determining the emotional status using physiological parameters, including design specification and software implementation of the system. This system may have a vivid use in medicine (especially for emotionally challenged people), smart home etc. Various Physiological parameters to be measured includes, heart rate (HR), galvanic skin response (GSR), skin temperature etc. To construct the proposed system the measured physiological parameters were feed to the neural networks which further classify the data in various emotional states, mainly in anger, happy, sad, joy. This work recognized the correlation between human emotions and change in physiological parameters with respect to their emotion

Scope of cooperation between India & Germany in renewables with a focus on opportunities in the wind sector in India

In 2015, India set itself a very ambitious task of expanding its installed base of renewable energies by more than five times to 175 gigawatt (GW) within seven years (by 2022). It was envisioned that 60 GW would be contributed by wind power. In 2018, the objective was revised upwards to 227 GW in total and 67 GW for wind power. The country needed such challenging goals to ensure an early, universal, and 24x7 access to electricity for all citizens. However, India’s per capita electricity consumption remains one of the lowest in the world. The young, aspiring and increasing population in a growing economy naturally engages in social and economic activities. As a result, the demand for electricity is increasing fast. Finally, there is a pressing need to switch from fossil fuels to renewable, replenishable and locally available resources for ensuring better energy security, reducing financial burden of energy imports, and - most crucially - for reducing carbon emissions to best protect the environment from a disastrous climate change. Wind energy has emerged as a success story in India. Today, India is leading globally on the fourth position in terms of installed wind power capacity. As a mature and cost effective technology, wind power has rapidly gained market share. The resultant economies of scale have again helped lower the costs and allowed firms to intensify innovation activity. Nevertheless, a huge market potential remains untapped, even as capacity utilization in terms of actual power generation has substantial scope of improvement. Germany is a global lead market for wind power, and renewable energies in general. It has a proven base of technological prowess and it has co-shaped the development of this industry. However, a certain saturation is setting in, as good sites for onshore wind power become scarce. There is a strong case for the two countries and their enterprises to cooperate in this sector. This case includes commercial, technological, humanitarian and environmental reasons. While there is a strong untapped potential in India and other global markets for affordable and excellent wind power solutions, technological cooperation can help in achieving affordable excellence (“frugal innovations”). Bilateral cooperation can help in realising the sustainable development goals (SDGs) in India and other developing economies of Asia, Africa and South America, in the process leading to a better life for millions, if not billions, of people. Finally, the environment and the biodiversity of our planet is at stake. Many of our non-human cohabitants are as severally, if not worse, affected by the human-intensified climate change, which potentially may threaten the existence of life itself on the planet if left unchecked. This study proposes an “IDEA” framework for Indo-German bilateral cooperation in wind sector that encompasses all relevant stakeholder in the value chain. The acronym stands for “Invest, Develop, Establish and Apply”. If implemented, this framework can help in creating affordable, green excellence with a win-win-win component for the countries involved, for human welfare, and for the environment

Low-cost Zinc Oxide Nanorods Modified Paper Substrate for Biodiagnostics

Many of the point-of-care hand-held devices are based on the detection of very low concentrations of some specific protein biomarker in a blood or biofluid sample. There is an often need to preconcentrate by a few orders of magnitudes the analyte prior to measurement on the sensing area of the test to enhance the detection sensitivity for these miniaturized devices. Protein preconcentration is one of the major challenges in biosensing with miniaturized devices as enhancement of detection sensitivity for highly diluted analytes is critical and required for its better performance. Besides preconcentration, blood-plasma separation is another major challenge in biodiagnostics. The conventional blood-plasma separation involves centrifugation, which generally enables very efficient and fast results. But in case of point-of-care miniature devices it is necessary to have an integrated miniature blood-plasma separation system to reduce the number of sample preparation steps and quick diagnosis. Substantially-reduced total cost of ownership and usage are being seen as increasingly necessary to ensure affordable healthcare for a growing world population. In this context paper-based devices are gaining popularity as they are inexpensive, easy to fabricate and to modify, and once used, easy to dispose as they easily burn and are biodegradable. Paper has inherent capillary force created by the network of cellulose therefore, no external driving force or systems are required for fluid transport. Paper also provides a good support for growing nanostructures by providing a template for orientation and nucleation sites. The work presented in this thesis involves, modification of paper with ZnO nanostructures to increase the available surface area for protein capture, biofunctionalization of nanostructures-modified paper. Emphasis is given on developing a protocol for protein preconcentration using the nanorods modified paper as a substrate and its confirmation by surface plasmon resonance, which also provided an opportunity to explore SPR studies on the ZnO nanorods modified gold chip. In addition to this passive separation of blood cells from plasma with the 1-D ZnO nanostructures modified paper as a substrate is also explored.<br

Forecasting COVID- 19 cases using Statistical Models and Ontology-based Semantic Modelling: A real time data analytics approach

SARS-COV-19 is the most prominent issue which many countries face today. The frequent changes in infections, recovered and deaths represents the dynamic nature of this pandemic. It is very crucial to predict the spreading rate of this virus for accurate decision making against fighting with the situation of getting infected through the virus, tracking and controlling the virus transmission in the community. We develop a prediction model using statistical time series models such as SARIMA and FBProphet to monitor the daily active, recovered and death cases of COVID-19 accurately. Then with the help of various details across each individual patient (like height, weight, gender etc.), we designed a set of rules using Semantic Web Rule Language and some mathematical models for dealing with COVID19 infected cases on an individual basis. After combining all the models, a COVID-19 Ontology is developed and performs various queries using SPARQL query on designed Ontology which accumulate the risk factors, provide appropriate diagnosis, precautions and preventive suggestions for COVID Patients. After comparing the performance of SARIMA and FBProphet, it is observed that the SARIMA model performs better in forecasting of COVID cases. On individual basis COVID case prediction, approx. 497 individual samples have been tested and classified into five different levels of COVID classes such as Having COVID, No COVID, High Risk COVID case, Medium to High Risk case, and Control needed case

A Scoping Review of Technology Applications in Evidence-Based Programs for Child Maltreatment Pre- and Post-COVID-19

Introduction: Evidence-based programs (EBP) are the hallmark recommendation to address sequelae among children who have experienced child maltreatment. During the COVID-19 pandemic, many of these programs adopted existing or novel digital tools to assist with uninterrupted access to services for youth. However, it is unclear how the use of technology changed pre- to post-COVID-19, and whether technological adaptations affected youth engagement and outcomes. Purpose: The aim of this scoping review is to better understand the use of technology across EBPs prior to and following the pandemic, and its impact on youth outcomes. Methods: Articles were included if they examined EBPs for youth experiencing child maltreatment as determined by the California Evidence-Based Clearinghouse, used or evaluated technological adaptations in the program of interest, were in English, and were published between 2000-2023. We searched four academic databases, including Psychology and Behavioral Sciences Collection, Psych Articles, PsychInfo, and PubMed. We included grey literature in our findings. Reference lists of articles of select articles were also reviewed. An initial search has yielded 1452 articles. Preliminary findings suggest 7 peer reviewed articles meeting inclusion criteria. Two additional articles evaluated parent-child dyadic outcomes. Among currently identified articles, two uses of technology were noted: 1) Virtual delivery of programs (n=7) and 2) tools for engagement for children (n=2). Significant decreases in mental health symptomology and increases in engagement and retention were noted among applicable interventions using technology. No programs were identified that evaluated COVID-19 specific technology augmentations. However, the search is currently ongoing. Results will be updated at the time of presentation. Conclusion: Preliminary findings support effectiveness of the use of technology with EBPs to improve programmatic delivery and outcomes among children. Importantly, and although ongoing, this search reveals few articles evaluating the use of technology among programs post-COVID, suggesting the need to rigorously evaluate digital tools

Associations Between Child Maltreatment Intake Call Rates and COVID-19 Vaccinations and Outcomes in Georgia

Child maltreatment (CM) is a significant public health problem. Parents, the primary perpetrators of CM may experience several risk factors and may engage in high-risk behaviors increasing likelihood of CM. However, there is a dearth of knowledge on health behaviors, such as vaccination uptake, among this at-risk population. This study explores the relationships between child maltreatment intake call rates from 2019-2022 and COVID-19 vaccination, infection, and mortality rates by county in the state of Georgia. Child maltreatment intake call data were obtained from the Division of Family and Children Services (DFCS) for each year from 2019-2022. Independent linear regression models were conducted to model the associations between intake calls and cumulative vaccination, morbidity, and mortality rates. 2019-2022 COVID-19 data were obtained from the Georgia Department of Public Health. County child maltreatment intake call rates were arranged by quartiles. Using 2019 data, unadjusted models indicated a 21% predicted lower COVID-19 vaccination rate (p\u3c .001), 6% higher infection rate (p\u3c .001), and 81% higher COVID-19 mortality rate (p\u3c .001) in counties with the highest quartiles of CM relative to the lowest. Upon adjusting for % Black, % Female, % rural, high school graduation, unemployment, median household income, and poor mental and physical health days, there was an 8% (p\u3c.001) lower vaccination rate, 16% (p\u3c.001) higher infection rate, and 16% (p\u3c .001) higher mortality rate. Analyses for 2020-21 data are in process and will be discussed. Interim findings suggest significant associations between intake calls with predictive lower vaccination rates, and higher morbidity and mortality rates in 2019 at the pandemic onset. Similar results are anticipated for 2020-2022 data. These novel results may have direct implications for related health outcomes among parents and youth. Implications for evidence-based parenting programs and future directions will be discussed

Loss of keratin 8 phosphorylation leads to increased tumor progression and correlates with clinico-pathological parameters of OSCC patients.

BACKGROUND: Keratins are cytoplasmic intermediate filament proteins expressed in tissue specific and differentiation dependent manner. Keratins 8 and 18 (K8 and K18) are predominantly expressed in simple epithelial tissues and perform both mechanical and regulatory functions. Aberrant expression of K8 and K18 is associated with neoplastic progression, invasion and poor prognosis in human oral squamous cell carcinomas (OSCCs). K8 and K18 undergo several post-translational modifications including phosphorylation, which are known to regulate their functions in various cellular processes. Although, K8 and K18 phosphorylation is known to regulate cell cycle, cell growth and apoptosis, its significance in cell migration and/or neoplastic progression is largely unknown. In the present study we have investigated the role of K8 phosphorylation in cell migration and/or neoplastic progression in OSCC. METHODOLOGY AND PRINCIPAL FINDINGS: To understand the role of K8 phosphorylation in neoplastic progression of OSCC, shRNA-resistant K8 phospho-mutants of Ser73 and Ser431 were overexpressed in K8-knockdown human AW13516 cells (derived from SCC of tongue; generated previously). Wound healing assays and tumor growth in NOD-SCID mice were performed to analyze the cell motility and tumorigenicity respectively in overexpressed clones. The overexpressed K8 phospho-mutants clones showed significant increase in cell migration and tumorigenicity as compared with K8 wild type clones. Furthermore, loss of K8 Ser73 and Ser431 phosphorylation was also observed in human OSCC tissues analyzed by immunohistochemistry, where their dephosphorylation significantly correlated with size, lymph node metastasis and stage of the tumor. CONCLUSION AND SIGNIFICANCE: Our results provide first evidence of a potential role of K8 phosphorylation in cell migration and/or tumorigenicity in OSCC. Moreover, correlation studies of K8 dephosphorylation with clinico-pathological parameters of OSCC patients also suggest its possible use in prognostication of human OSCC