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Should we judge phcs by only iphs guidelines or probe further?
Background: Indian Public Health Standards (IPHS) evaluates supply side compliance of Primary Health Centers (PHCs). Patient Satisfaction (PS) on the other hand, assesses the demand side. Objective: Examining the supply side compliance and relating it to PS in the domain of Reproductive Health (RH). Methods: Using multistage stratified sampling, six rural and three urban PHCs in sub-districts, Ramanagara and Channapatna, in District Ramanagara, state of Karnataka, India, were chosen. Information collected using IPHS proforma for PHCs was compared with PS questionnaire (PSQ 18) data, collected from 398 patients visiting these facilities. Results: Using descriptive and inferential analysis, sub-optimal compliance levels in ease of access, physical & human infrastructure, patient data and usage of untied funds was found. Existing behavioral compliance was found to be optimal. These findings were in alignment with PS findings. Conclusion: Results call for PHC capacity building, incentivization and a crucial need to look into PS side, before passing judgement about performance standard. 2020, Indian Association of Preventive and Social Medicine. All rights reserved. -
Are muslims incurring higher out-of-pocket expenditures than hindus in reproductive healthcare at sub-district levels in Karnataka?
Background and Objective: This study was undertaken to evaluate level of differences found in Out-of-pocket expenditures (OOPE) among Hindus and Muslims, OOPE being a sub-component while constructing reproductive health account (RHA) matrices for Ramanagara district, Karnataka. Method: Adopting multistage stratified sampling method, individual level data was collected using survey tools, catering to six dimensions of RH functions, taken from WHO Guide to produce RH Sub-Account. 517 Hindu and Muslim men and women meeting inclusion criteria of reproductive age (15-49) incurring RH expenditures in last one year were included followed later by only 382 uninsured individuals for hypothesis testing. Results: Muslims showing almost double OOPE in RH necessitated hypothesis testing of significant difference in OOPE, equating groups, post exclusion of insured individuals. Statistically significant difference was revealed in RH expenditures using Mann-Whitney U test. Interpretations and conclusions: Vicious cycle of disparity in education levels, lower income levels, negligible health coverage, strenuous work conditions, poor living standards, repeated RH contingencies leading to massive borrowing financed OOPE in RH continues. 2019, Indian Journal of Public Health Research and Development. All rights reserved. -
Intelligent Multi-modal Data Processing
A comprehensive review of the most recent applications of intelligent multi-modal data processing Intelligent Multi-Modal Data Processing contains a review of the most recent applications of data processing. The Editors and contributors noted experts on the topic offer a review of the new and challenging areas of multimedia data processing as well as state-of-the-art algorithms to solve the problems in an intelligent manner. The text provides a clear understanding of the real-life implementation of different statistical theories and explains how to implement various statistical theories. Intelligent Multi-Modal Data Processing is an authoritative guide for developing innovative research ideas for interdisciplinary research practices. Designed as a practical resource, the book contains tables to compare statistical analysis results of a novel technique to that of the state-of-the-art techniques and illustrations in the form of algorithms to establish a pre-processing and/or post-processing technique for model building. The book also contains images that show the efficiency of the algorithm on standard data set. This important book: Includes an in-depth analysis of the state-of-the-art applications of signal and data processing Contains contributions from noted experts in the field Offers information on hybrid differential evolution for optimal multilevel image thresholding Presents a fuzzy decision based multi-objective evolutionary method for video summarisation Written for students of technology and management, computer scientists and professionals in information technology, Intelligent Multi-Modal Data Processing brings together in one volume the range of multi-modal data processing. 2021 John Wiley & Sons Ltd. All rights reserved. -
Conclusion
Digital data produced through data-processing algorithms has fundamental advantages of transportability, proficiency, and accuracy; but on the other hand, the data thus produced brings in several redundancies. To solve this challenging problem with data transmission in network surroundings, research on information security and forensics provides efficient solutions that can shield the privacy, reliability, and accessibility of digital information from malicious intentions. Despite two decades of rigorous research, multicarrier communications still suffer from high complexity and low convergence, which have an immense practical impact. It is also more challenging to ensure proper transmission of multimodal data. Novel techniques have been proposed that can effectively abate these problems and provide good symbol error rate performance. The singularity expansion method provides a superior way to identify targets. This type of method may be useful for addressing contemporary problems faced by radar and antenna researchers. 2021 John Wiley & Sons Ltd. -
Introduction
In the digital era, signal processing has found application in daily life from medical diagnosis to social networking. The digital domain has evolved as the preferred choice in communication system design due to its advantages over analog systems, such as high-speed transmission, improved quality, and effortless copying with high precision. The advancement of digital media brings new opportunities. The internet boom of this millennium has allowed digital data to move around the world in real time. Efficient segmentation, recognition, and analysis of multidimensional data such as hyperspectral images, medical imaging, data analysis in social media, and audio signals are still challenging issues. Digital data produced through data-processing algorithms has the fundamental advantages of transportability, proficiency, and accuracy of information content; but such data is also at significant risk because perfect illegal replicas can be made in unlimited numbers. 2021 John Wiley & Sons Ltd. -
A Novel Ridge Estimator for the Liu-Type Logistic Regression Model and Its Application to Demographic Data from Urban Slums in Karnataka
This study introduces new ridge estimators for the Liu-type logistic regression model which helps to improve the model performance if multicollinearity is present in the independent variables. Logistic regression is the regression that helps to model binary outcomes but it provides inaccurate and unstable regression coefficients in the presence of multicollinearity. As a result of this, the variance might increase and the predictive accuracy of the model gets reduced. To overcome this issue, the Liu-type logistic regression is used which uses ridge and Liu parameters to provide stable and accurate regression coefficients. Several ridge estimators are proposed in this study based on the Liu-type logistic model which can handle multicollinearity and give better predictive performance of the model. The proposed estimators have been tested on the demographic dataset from Urban Slums in Karnataka and through the empirical analysis it is observed that one among the new ridge estimators give the lowest Mean Square Error (MSE) when compared to the existing ridge estimators. The results show the usefulness of the new estimators to improve the performance of the model and also contribute to the betterment of the logistic regression techniques. This work highlights the critical need to handle multicollinearity in regression analysis and sets the path for researchers to further improve the estimators in the future. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Smart grid and energy management in smart cyber-physical systems (SCPS)
[No abstract available] -
Marital Arrangements and Womens Autonomy: The Narratives of Tibetan Women in Exile
There has been a shift from the previously dominant polyandrous marital arrangements to monogamous arrangements, upon exile, among the Tibetan refugees in India. This article attempts to examine the autonomy of Tibetan women in exile across polyandrous and monogamous marital arrangements through the lens of modernisation and feminist theoretical frameworks. A thematic narrative analysis of 30 Tibetan participants in both marital arrangements has helped in comparing womens autonomy in the domains of inheritance and division of property, household decision-making and with respect to childrens education and occupation. Even though modernising forces partially explain the shift from polyandry to monogamy, the narratives of women belonging to both the monogamous and polyandrous families lend support to the feminist framework suggesting the role of internalisation of social norms and self-abnegation as negatively affecting their autonomy. 2025 CWDS. -
Exploring the Power of Agency in Womens Non-farm Business Participation
The relationship between rural womens agency and their non-farm self-employment is explored. Using a sequential explanatory design and nationally representative India Human Development Survey data, it is shown that agency outcomes, such as household decision-making, freedom of movement and group memberships, are crucial for womens participation and their roles in non-farm businesses. Additionally, personal in-depth interviews with self-employed women in rural West Bengal and Karnataka reveal how they navigate and negotiate within business environments despite existing constraints. 2026, Economic and Political Weekly. All rights reserved. -
ON THE INDICES OF CERTAIN GRAPH PRODUCTS
Molecular descriptors are numerical graph invariants that are used to study the chemical structure of molecules. In this paper, we determine the upper bound of the Sombor index based on four operations involving the subdivision graph, semi-total point graph, semi-total line graph, and total graph related to the lexicographic and tensor product. The exact expressions of the first reformulated Zagreb index and the second hyper-Zagreb index of the tensor product are formulated on the basis of the four significant graphs. Further, the descriptors for certain standard graphs are obtained and the graphical comparison for the first reformulated Zagreb index has also been illustrated to understand the result better. 2025 University of Isfahan -
Bounds on Sombor index of graph operations
Operations in graph theory have a significant influence in the theoretical and application aspect of the domain. Topological indices serve as a crucial component in chemical graph theory linked with some molecular structure. Recently, Gutman initiated the study on the Sombor index. In this paper, the computation of some bounds for Sombor index of graph operation notably join, cartesian product, corona product, lexicographic product, tensor product and strong product is carried out. The computation has been utilized to determine the upper bounds of the index for the specified graph operations for some standard graphs like the path and cycle graphs. 2025 World Scientific Publishing Company. -
Reimagining Healthcare: The South African PPP Revolution
Publicprivate partnerships (PPPs) are rapidly being recognized as transformative methods for improving healthcare delivery and funding, particularly in resource-constrained environments. Global and national policy frameworks, supported by organizations such as the African Development Bank (AfDB) and the World Health Organization (WHO), emphasize the potential for PPPs to fill significant gaps in healthcare infrastructure and service delivery. Countries across Africa, notably South Africa, Kenya, Nigeria, and Rwanda, have put in place national PPP frameworks that formalize partnerships in healthcare, focusing on risk sharing, accountability, and sustainability. South Africas National Treasury PPP Unit is a regional pioneer in promoting PPP development that balances private-sector innovation with governmental control. Such frameworks allow PPPs to mobilize private resources, enhance public spending efficiency, and provide access to high-quality healthcare, particularly in marginalized communities. Despite positive developments, PPPs in African healthcare confront hurdles due to fragmented legal frameworks and low institutional capacity to manage complicated contracts. The AfDBs 20212031 PPP strategic framework seeks to fill these gaps by providing African States with resources to establish enabling environments and prepare viable healthcare projects for the market. Diverse models in South Africa and other countries, such as Kenyas Managed Equipment Services (MES) and Ghanas BuildOperateTransfer (BOT) programs, show how adaptable PPPs can improve healthcare finance and delivery. However, current regulatory frameworks are complicated and often disconnected, emphasizing the need for unifying legal standards to assure transparency and accountability. This chapter highlights the insights that present a strong PPP model adapted to healthcare financing. It highlights the necessity of transparent systems, good risk management, and combining publicprivate expertise to handle current healthcare concerns. PPPs can improve healthcare accessibility and quality, increase patient satisfaction, and strengthen healthcare systems by promoting improved governance, policy consistency, and capacity building. Strategically honed, PPPs can drive long-term breakthroughs, positioning healthcare systems better to address the changing demands of African communities and beyond. 2026 selection and editorial matter, Wasswa Shafik, Adel Ben Youssef, Chithirai Pon Selvan and Pushan Kumar Dutta; individual chapters, the contributors. -
Integrating Simple Temporal Attention for Improved Video Summarization
Simple Temporal Attention (STA) in video summarization can improve deep learning model performance while tackling complexity and multi-view dependency problems. Many of the current models are too complex and dependent on multi-view setups to be scalable in single-camera settings. The suggested STA mechanism reduces model complexity without sacrificing accuracy, making it easier to recognize important moments in videos. To further increase the efficacy of summarization, a spatio-temporal mechanism is also introduced to capture crucial dynamics between video frames. The approach is evaluated on two benchmark datasets, UCF50 and TVSum, demonstrating significant improvements in model performance. This study provides a scalable solution for video summarization by highlighting the useful advantages of integrating STA for producing succinct and informative video summaries through a comparison of different deep learning. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
GUI-Based Percentage Analysis forCuring Breast Cancer Survivors
The modeling approach is increasing the intensity of research in all the domains. The present paper deals with predictive modeling and probabilities. Data analysis is a technique used to transform, reconstruct, and revise some information that is an essential step to achieve the goal or the end result. The present study involves the usage of logistic regression technique for data analysis. Various domain-specific methods pertaining to science, business, etc., are available for data analysis which plays a key role in decision-making and model building. The significance of this analysis is to get the percentage of the survival of patients with advanced breast cancer. 2020, Springer Nature Singapore Pte Ltd. -
Analysis of the pooled effect of compression ratio and injection timing variation on conventional diesel engine powered with nano doped biodiesel blend
This research aims to explore how incorporating nanoparticles into a biodiesel-diesel blend influences the performance, combustion, and emission characteristics of a diesel engine under varying conditions, including compression ratios, engine loads, and injection timings. The biodiesel and nanoparticles considered for this investigation are mahua biodiesel and Titanium oxide nanoparticles (TiO2), respectively. The experimental fuel is formulated by blending diesel and mahua biodiesel with the addition of titanium oxide nanoparticles. In this study, compression ratio is varied from 17.5 to 18, whereas fuel injection timing of 20, 23, and 25 BTDCs along with engine load variation of 20%, 40%, 60%, 80%, and 100% are considered. The experimentation utilized a single-cylinder diesel engine equipped with a variable compression ratio (VCR) feature and a power output of 3.5kW. The results indicate that the maximum brake thermal efficiency was achieved at a compression ratio of 18 and a fuel injection timing of 20 before Top Dead Center. For the same setting, the nanoparticle-enriched biodiesel-diesel blend exhibited the lowest levels of CO and HC emissions among all test runs, with reductions of 45.34% and 40%, respectively, compared to standard diesel operation. The Author(s) 2025. -
COVID-19: Trend analysis for market arrival of green gram in India
The unprecedented crisis hovering over the world due to Covid-19 pandemic has structurally impacted every sector of the world economy. This paper attempts to study the impact of ongoing pandemic in the agricultural sector specific to pulses in India. This paper finds that there is a significantly negative impact of Covid-19 on the pulses market. The market arrival of pulses has declined in the recent period while market demand for pulses has increased, therefore, there exists a supply side shortage for pulses in the domestic economy of India. This paper suggests that Government of India (Agriculture Department) urgently needs to deal with this shortage in supply of domestic pulses in "mandis" (agricultural markets). In this paper market arrival for pulses particularly green gram (Moong whole) has been forecasted for the next few months in Indian Agricultural Markets with the forecasting techniques such as Auto Regressive Integrated Moving Average (ARIMA) model and Artificial Neural Network (ANN) technique for pre and during pandemic period by using the arrival data in agriculture markets of India from Agmarknet. The results of this study using ARIMA models and ANNs have been compared to obtain the final conclusions with higher visibility in forecasting performance, which shows that there will be a sharp decline in market arrival with an average arrival of 494 quintals per day which can be maximized up to 623 quintals per day by stimulating the modal price at maximum possible point. Therefore, the urgent need of upscaling the technical efficiency of the farmers in different agro-climatic zones is needed to meet the domestic demand with domestic supply. 2020 DAV College. All rights reserved. -
Gut microbes: The miniscule laborers in the human body
Our physical and mental being largely depends on our dietary intake and the manipulations done on food by the gut bacterial flora in the digestive tract. Scientists have discovered a lot of previously unknown facts about the gut microbiota. They have been found to play a role in manifold processes, such as digestion, nutrient conversion, absorption, detoxification, and so on. In fact, people who consume plant-based and animal-based diets will have separate array of gut microbes. The composition of these microbiota will drastically change during a switch to a new diet. Deficiencies of adequate beneficial gut bacterial flora have been associated with many ailments. As there are billions of such microbes in our body, the number of bacterial genes could far outnumber the human genes in our body. The role of gut microbes in the proper functioning of the human digestive and nervous systems and its implications will be discussed in this chapter. 2018 Elsevier Inc. All rights reserved. -
Nanomedicine: Insight analysis of emerging biomedical research and developments
The field of nanomedicine has undergone a revolution owing to the specific optical, electrical, and mechanical behaviors of nanomaterials that are extensively utilized for the detection of biomolecules, improved therapeutics, and imaging of diseased tissues. Different cells have their own unique markers which can be detected by specific nanomaterials which in turn can be used to target micro levels of medicine in precision medicine. Most of the advances in nanomedicine will have effects on the healthcare delivery systems. More works have focused on screening procedures that have better sensitivity and specificity for disease detection, which in turn will greatly improve diagnostic and prognostic domains, thereby reducing healthcare costs. Nanomedicine has the advantages of facilitating early disease detection, quantification of tumor cells and toxicmolecules, delivery of drugs to specific cells like the tumor cells etc. This chapter deals with research and development in nanomedicine which has been a top priority in most of the developed countries, with a view to optimize factors like dose response, efficacy, targeting ability, safety and bioavailability. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. All rights reserved. -
Multifaceted Anticancer Potential of Trigonella foenum-graecum
The past decade saw a revolution in the discovery of genetic and epigenetic factors paving way for various types of cancers. With a better understanding of the causes, comes a chance of wider possibility of targeting the root causes of cancer. Nature is a storehouse of natural anticancer molecules, many yet to be explored. Trigonella foenumgraecum (fenugreek) is one such plant, having a huge potential for modulating prophylactic and therapeutic aspects of cancer. Cuisines world over make uses of this legume in multiple ways. This small herb has been found to be loaded with many secondary metabolites like diosgenin, coumarin, trigonelline and so on that reduce inflammation, promote apoptosis, act as antioxidants, regulates cell proliferation, etc., thereby reducing the effects of various hallmarks of cancer. Components of T. foenum-graecum extracts have been found to be effective in alleviating both solid tumours and blood cancers. The milieu of phytochemicals present in T. foenum-graecum has already been shown to have antimicrobial, antioxidant and neuroprotective properties by several studies done in different parts of the world. The current chapter attempts to have a comprehensive look at the potential of various bioactive principles in Trigonella foenum-graecum to be used for the prevention and treatment of cancer. In today's global scenario, where cancer incidences are alarmingly rising, such natural remedies would indeed go a long way in preventing various types of cancer and imparting a better quality of life. 2021 Nova Science Publishers, Inc.