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Investigating Key Contributors to Hospital Appointment No-Shows Using Explainable AI
The healthcare sector has suffered from wastage of resources and poor service delivery due to the significant impact of appointment no-shows. To address this issue, this paper uses explainable artificial intelligence (XAI) to identify major predictors of no-show behaviours among patients. Six machine learning models were developed and evaluated on this task using Area Under the Precision-Recall Curve (AUC-PR) and F1-score as metrics. Our experiment demonstrates that Support Vector Classifier and Multilayer Perceptron perform the best, with both scoring the same AUC-PR of 0.56, but different F1-scores of 0.91 and 0.92, respectively. We analysed the interpretability of the models using Local Interpretable Model-agnostic Explanation (LIME) and SHapley Additive exPlanations (SHAP). The outcome of the analyses demonstrates that predictors such as the patients' history of missed appointments, the waiting time from scheduling time to the appointments, patients' age, and existing medical conditions such as diabetes and hypertension are essential flags for no-show behaviours. Following the insights gained from the analyses, this paper recommends interventions for addressing the issue of medical appointment no-shows. 2024 IEEE. -
Parametric Study on Compaction Characteristics of Clay Sand Mixtures
The behaviour of fine-grained soils can be attributed to their mineral composition and the amount of fines present in them. The present study aims to determine the effect of mineral composition and quantity of fines on the Atterberg limits and compaction characteristics and to determine the correlation between them. Two types of fine-grained artificial soil mixtures were prepared in the laboratory representing kaolinitic and montmorillonitic mineral compositions.The amount of fines was varied at 10% intervals, from 50 to 100%. The Atterberg limits like liquid limit, plastic limit, shrinkage limit, and compaction characteristics like maximum dry density (MDD) and optimum moisture content (OMC) for two compaction energy levels, i.e. standard proctor (SP) and modified proctor (MP) tests, were determined. The correlations were developed between percentage fines and Atterberg limits and similarly between percentage fines, Atterberg limits, and compaction characteristics for artificial mix proportions. The developed correlations were used to predict the properties of natural soil samples, and the predicted and actual values are compared. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Text Summarization Techniques for Kannada Language
Text Summarization is summarizing the original text document into a shorter description. This short version should retain the meaning and information content of the original text document. A concise summary can help humans quickly understand a large original document better in a short time. Summarization can be used in many text documents, such as reviews of books, movies, newspaper articles, content, and huge documents. Text summarization is broadly classified into extractive Text Summarization (ETS) and Abstractive Text Summarization (ATS). Even though more research works are carried out using extractive methods, meaningful summaries can be attained using abstractive summary techniques, which are more complex. In Indian languages, very few works are carried out in abstract summarization, and there is a high need for research in this area. The paper aims to generate extractive and abstractive summaries of the text by using deep learning and extractive summaries and comparisons between them in the Kannada language. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Perception to Control: End-to-End Autonomous Driving Systems
End-to-end autonomous driving systems have garnered a lot of attention in recent years, and researchers have been exploring different ways to make them work. In this paper, we provide an overview of the field with a focus on the two main types of systems: those that use only RGB images and those that use a combination of multiple modalities. We review the literature in each area, highlighting the strengths and limitations of each approach. We also discuss the challenges of integrating these systems into a complete end-to-end autonomous driving pipeline, including issues related to perception, decision-making, and control. Lastly, we identify areas where more research is needed to make autonomous driving systems work better and be safer. Overall, this paper provides a comprehensive look at the current state-of-the-art in end-to-end autonomous driving, with a focus on the technical challenges and opportunities for future research. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Thermal optimisation through the stratified bioconvective jetflow of nanofluid
Bioconvection is a fascinating phenomenon observed in various biological systems, where the motion of motile microorganisms generates fluid flow patterns. This article explores the occurrence and characteristics of bioconvection within the context of a jet flow. The study of bioconvection in jet flow involves the interaction between motile microorganisms and the fluid dynamics of the surrounding medium. Microorganisms such as bacteria and algae are known to exhibit directed swimming behavior, which can lead to the formation of dynamic flow structures. Investigating the mechanisms underlying bioconvection in jet flow requires a multidisciplinary approach encompassing fluid dynamics, microbial ecology, and mathematical modeling. Experimental techniques, such as microscopy and particle image velocimetry, along with computational simulations, are employed to analyze the complex interactions between microorganisms and the fluid flow. In this regard, a supportive mathematical model is designed using partial differential equations (PDEs) which are later transformed into ordinary differential equations using similarity transformations. The resulting system of equations is solved using the RKF-45 method and the outcomes are recorded in tables and graphs. The consideration of thermophoresis has shown a significant impact on the heat and mass transfer of the jet flow and both these profiles are observed to increase with thermophoresis. Meanwhile, the Schmidt number decrease their respective mass profiles. Furthermore, the porosity is found to create a drag force which tends to oppose the fluid flow. 2023 Taylor & Francis Group, LLC. -
Heat transfer optimisation through viscous ternary nanofluid flow over a stretching/shrinking thin needle
The current investigation interprets the flow and the thermal characteristics of the ternary nanofluid composed of MoS 2, ZnO, and SiO 2 spherical nanoparticles and water. The resulting nanofluid is (Formula presented.) where (Formula presented.) act as the base fluid which help in the flow and the nanoparticles contribute to enhancing the heat conductivity. The flow is assumed to occur across a thin needle whose surface is maintained at a higher temperature than the surroundings. The mathematical model is framed by incorporating radiation introduced by Rosseland in terms of partial differential equations (PDE). This system of equations governs the flow and thermal properties of fluid which are converted to a system of ordinary differential equations (ODE). The major outcomes of the study indicated that the increase in the amount of molybdenum disulfide enhanced the heat conducted by the nanofluid whereas it reduced the flow speed. The positive values of the heat source/sink parameter caused the heat conduction of the nanofluid to go high. 2023 The Author(s). Published with license by Taylor & Francis Group, LLC. -
X-Tract: Framework for Flexible Extraction of Features in Chest Radiographs for Disease Diagnosis Using Machine Learning
Various types of medical images are used as diagnostic tools for identifying pathologies in human bodies, and in this research, chest X-ray images are used as diagnostic tools. Several pre-built models are created by the participants of ImageNet competitions for non-medical images, and these models are also being used in medical image classification; for example, Khan et al. (Comput Methods Prog Biomed 196:105581, 2020) developed a model called Coronet and Narayan Das et al. (IRBM 1:16, 2020) proposed a deep transfer learning-based model. Instead of using the pre-built models, a different approach was taken to address this problem. A framework was created to extract the frequency and spatial domain-based features, along with the raw statistics of the images. The model proposed in this article using the SVM algorithm has reached accuracy levels ranging from 91% to 97% and sensitivity of 92% to 96% on various samples of test data of over 400 images. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
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Computational investigation into the solvent effect, electron distribution, reactivity profile, pharmacokinetic properties and anti-cancer action of Hemimycalin C
This work consists of DFT studies and biological evaluation of the marine alkaloid Hemimycalin C. The DFT calculations include energy minimisation, reactivity analysis of the frontier molecular orbitals, electronic transition studies (UV spectra generation), molecular electrostatic potential colour map analysis (MEP), and natural bond orbitals (NBO) studies. Non-linear optical (NLO) properties estimation is also performed to obtain the first-order hyperpolarizability, mean polarizability and dipole moment of Hemimycalin C. The solvent methanol emerges as the most interesting among the polar solvents employed in this study, as it impacts the properties of Hemimycalin C to a significant extent. Multiwfn software is used for topological analyses, which include the calculation of Reduced Density Gradient (RDG), Localised Orbital Locator (LOL) maps), and Electron Localisation Function (ELF). The computed ADMET profile indicates that the molecule is a potent lead (drug candidate) as the medicinal chemistry parameters are mostly within the optimal range. The Ramachandran plots are also computed to show the stability and quality of the target proteins, by computation of the permitted psi and phi angles. The complexes of the ligand are docked using AutoDock Tools against blood cancer receptors to obtain good binding affinity values. 2025 Elsevier B.V. -
Influence of Autonomous Sensory Meridian Response on Relaxation States: An Experimental Study
Multiple studies have stated that autonomous sensory meridian response (ASMR) induces relaxation. ASMR is defined as a static tingling-like sensation across the scalp and back of the head, experienced by some people in response to specific audio and visual triggers like tapping, whispering, and slow hand movements. This study explores the relaxation states and the stress states on which ASMR videos have the highest impact. Data from 60 college students with a mean age of 22 years and a standard deviation of 1.12 were collected for this study, among which 30 were assigned to an experimental group and 30 were assigned to a control group single blindly. The relaxation states and stress states were measured using Smith Relaxation Scale Inventory (SRSI) for the pretest and Smith Relaxation Posttest Inventory (SRPI) for the posttest. The experimental group watched an ASMR video, and the control group watched a neutral video between the pretest and posttest. SPSS version 16 was used for data analysis. The result suggested a significant increase in sleepiness after watching the ASMR video (significant difference). 2021 International Society for Neurofeedback and Research. All rights reserved. -
Determining the Impact of Adapted Yoga Training on Physical Functioning in Students with Mild Intellectual Disability
Background. Individuals with mild intellectual disability (ID) often encounter challenges in physical functioning, impacting their overall well-being and quality of life. Traditional exercise programs may not always be accessible or effective for this population due to various barriers. Adapted yoga programs have emerged as a promising alternative, offering tailored interventions to address the unique needs of individuals with ID. Objectives. The study aimed to close this gap by examining the effect of a structured, modified yoga programme on factors related to physical functioning. Materials and methods. A total of 40 students with mild ID, aged between 11 and 15 years, were selected from Special Schools in Coimbatore, Tamil Nadu. A quasi-experimental design was used in this study. The participants were divided into an experimental group undergoing an 8-week adapted yoga program and a control group maintaining regular activities. Physical function parameters were assessed using standardized tests measuring cardiorespiratory endurance, muscular strength and endurance, flexibility, body composition, and balance. The adapted yoga program, conducted by qualified instructors, comprised 8 weeks of sessions, 5 days a week, each lasting 45 to 60 minutes. Statistical analyses confirmed the normal distribution of data and employed paired sample t-tests to assess pre-and post-test differences, with SPSS version 20.0 used for analysis, setting the significance level at 0.05. Results. After undergoing 8 weeks of adapted yoga training, the results showed a significant improvement in the upper body strength (p < 0.04), lower body strength (p < 0.001), core strength (p < 0.002), flexibility (p < 0.00), and static balance (p < 0.00). However, there was no significant difference in body fat and cardiorespiratory endurance between adapted yoga training. Conclusions. This study highlights the potential of adapted yoga programs as an intervention for improving physical functioning in students with mild ID. These findings indicate that the imlementation of adapted yoga can be a valuable and accessible intervention for enhancing physical functioning in this population. Yuvaraj, D., Dibakar, D., Prem, K. G., Aravindh, M., Ramesh, A. J., & Alphi, G. S., 2024. -
Hyperspectral Image Classification Using Denoised Stacked Auto Encoder-Based Restricted Boltzmann Machine Classifier
This paper proposes a novel solution using an improved Stacked Auto Encoder (SAE) to deal with the problem of parametric instability associated with the classification of hyperspectral images from an extensive training set. The improved SAE reduces classification errors and discrepancies present within the individual classes. The data augmentation process resolves such constraints, where several images are produced during training by adding noises with various noise levels over an input HSI image. Further, this helps in increasing the difference between multiple classes of a training set. The improved SAE classifies HSI images using the principle of Denoising via Restricted Boltzmann Machine (RBM). This model ambiguously operates on selected bands through various band selection models. Such pre-processing, i.e., band selection, enables the classifier to eliminate noise from these bands to produce higher accuracy results. The simulation is conducted in PyTorch to validate the proposed deep DSAE-RBM under different noisy environments with various noise levels. The simulation results show that the proposed deep DSAE-RBM achieves a maximal classification rate of 92.62% without noise and 77.47% in the presence of noise. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Responsible Service of Alcohol: An Evaluation of Policies and Practices of Five Star Hotels in Karnataka
Networking and socializing has been a human practice since ancient times and alcohol has been the social lubricant ??yesterday, today and also tomorrow. While we cannot trace its origin to a particular culture or civilization, its role and impact has been recorded in ancient texts and literature across cultures. A person can get drunk for a few rupees or spend a few lakhs for the same. It is consumed across social classes- by a daily wage worker to a business tycoon. The only thing differentiating the two being the price he has paid for the drink and the glass he is having it from. Even though the price and glass differs the effect it has on a person is more or less the same. This research and study is based on the belief that alcohol in itself is not the major cause of all the issues and troubles it is blamed for, but it is the nature and manner in which it is treated, consumed and served. This study is based on the latter aspect, ????the service of alcohol???. As mentioned in the previous paragraph, alcohol is a social lubricant and bars and restaurants have always been a popular place for socializing. The people who deal with the sale and service of alcoholic beverages along with the management and owners have a moral responsibility to ensure that alcohol is both served and consumed responsibly. This practice of Responsible Beverage Service or Responsible Service of Alcohol might look simple and easy on paper but to practice it, is a different story! It involves the support and approval of all the stakeholders. The owner and management on their part have to compromise on the earnings from the extra sale alcohol. The server has the additional responsibility of checking that his customers are not getting intoxicated and that he is following all the rules and regulations associated with alcohol service and above all the consumers too have to support and accept responsible service practices by the establishment. This study has looked into the practice of Responsible Beverage Service followed in the bars and restaurants in five star hotels, in the state of Karnataka. The initial study involved a review on early research and study on Responsible Beverage Service, Its impact on controlling alcohol abuse and intoxication, Responsible Beverage Service practices and various other dimensions and issues associated with Responsible Service of Alcohol. VII This research has focused on both the consumer as well as the server???s perspective on Responsible Beverage Service. The primary data for the study was collected from both consumers and hotels through a structured questionnaire, followed by data analysis using the appropriate tool. The findings give an insight and understanding into the acceptance of responsible beverage service in the state. What works and what needs to be improved? The practices which has the most impact in controlling alcohol abuse and answers to other questions associated with the study. -
Human Resource Management in Digital India
The business entities of today are aware of the vital role played by technological interventions in value creation. HR technological interventions are no exceptions either. These interventions are aligned to business goals and help businesses achieve their bottom lines. Nevertheless, some business owners are apprehensive about the way forward while adopting technology. This chapter focuses on the various technologies that aid HR functions, its implementation framework keeping in perspective the key apprehensions, considerations and competency requirements. The chapter highlights few Indian organizations that have adopted it. The findings show that emphasis is laid on business value creation for stakeholders due to HR technology adoption. 2023 by World Scientific Publishing Co. Pte. Ltd. All right reserved. -
DFT, spectroscopic studies, NBO, NLO and Fukui functional analysis of 1-(1-(2,4-difluorophenyl)-2-(1H-1,2,4-triazol-1-yl)ethylidene) thiosemicarbazide
A novel triazole derivative 1-(1-(2,4-difluorophenyl)-2-(1H-1,2,4-triazol-1-yl)ethylidene) thiosemicarbazide was synthesized and subjected to density functional theory (DFT) studies employing B3LYP/6-31+G(d,p) basis set. Characterization was done by FT-IR, Raman, mass, 1H NMR and 13C NMR spectroscopic analyses. The stability of the molecule was evaluated from NBO studies. Delocalization of electron charge density and hyper-conjugative interactions were accountable for the stability of the molecule. The dipole moment (?), mean polarizabilty (??) and first order hyperpolarizability (?) of the molecule were calculated. Molecular electrostatic potential studies, HOMO-LUMO and thermodynamic properties were also determined. HOMO and LUMO energies were experimentally determined by Cyclic Voltammetry. 2018 Elsevier B.V. -
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Neuropalliative Care Needs Checklist for Motor Neuron Disease and Parkinson's Disease: A Biopsychosocial Approach
Objectives: Neurodegenerative disorders necessitate comprehensive palliative care due to their progressive and irreversible nature. Limited studies have explored the comprehensive assessment needs of this population. This present study is designed to develop a checklist for evaluating the palliative care needs of individuals with motor neuron disease (MND) and Parkinson's disease (PD). Materials and Methods: The checklist was created through an extensive literature review and discussions with stakeholders in neuropalliative. Feedback from six field experts led to the finalisation of the checklist, which comprised 53 items addressing the unique biopsychosocial needs of MND and PD. Sixty patient-caregiver dyads receiving treatment in a tertiary referral care centre for neurology in south India completed the checklist. Results: People with MND had more identified needs with speech, swallowing, and communication, while people with PD reported needs in managing tremors, reduced movements, and subjective feelings of stiffness. People denying the severity of the illness was found to be a major psychosocial issue. The checklist addresses the dearth of specific tools for assessing palliative care needs in neurodegenerative disorders, particularly MND and PD. By incorporating disease-specific and generic items, the checklist offers a broad assessment of patients' multidimensional needs. Conclusion: This study contributes to the area of neuropalliative care by developing the neuropalliative care needs checklist (NPCNC) as a valuable tool for assessing the needs of individuals with neurodegenerative diseases. Future research should focus on refining and validating the NPCNC with larger and more diverse groups, applicability in different contexts, and investigating its sensitivity to changes over time. 2024 Published by Scientific Scholar on behalf of Indian Journal of Palliative Care. -
Computational screening of natural compounds from Salvia plebeia R. Br. for inhibition of SARS-CoV-2 main protease
The novel Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) has emerged to be the reason behind the COVID-19 pandemic. It was discovered in Wuhan, China and then began spreading around the world, impacting the health of millions. Efforts for treatment have been hampered as there are no antiviral drugs that are effective against this virus. In the present study, we have explored the phytochemical constituents of Salvia plebeia R. Br., in terms of its binding affinity by targeting COVID-19 main protease (Mpro) using computational analysis. Molecular docking analysis was performed using PyRx software. The ADMET and drug-likeness properties of the top 10 compounds showing binding affinity greater than or equal to ? 8.0kcal/mol were analysed using pkCSM and DruLiTo, respectively. Based on the docking studies, it was confirmed that Rutin and Plebeiosides B were the most potent inhibitors of the main protease of SARS-CoV-2 with the best binding affinities of ? 9.1kcal/mol and ? 8.9kcal/mol, respectively. Further, the two compounds were analysed by studying their biological activity using the PASS webserver. Molecular dynamics simulation analysis was performed for the selected proteinligand complexes to confirm their stability at 300ns. MM-PBSA provided the basis for analyzing the affinity of the phytochemicals towards Mpro by calculating the binding energy, and secondary structure analysis indicated the stability of protease structure when it is bound to Rutin and Plebeiosides B. Altogether, the study identifies Rutin and Plebeiosides B to be potent Mpro inhibitors of SARS-CoV-2. Graphic abstract: [Figure not available: see fulltext.] 2021, Society for Plant Research. -
The evolution of currency: A comparative study of the barter system and cryptocurrency
The barter system, the oldest form of exchange dating back to human civilization, involves directly exchanging goods and services without using money. However, it comes with limitations, such as the requirement for a double coincidence of wants, difficulties in valuing goods and services, and the absence of a store of value. Over time, various forms of money emerged to overcome these limitations. Commodity money, like gold and silver, gained value due to their rarity and intrinsic worth. Later, fiat currencies were introduced, backed by trust rather than physical commodities. In contrast, cryptocurrency, a new digital currency not issued by any central authority, relies on blockchain technology for secure and anonymous transactions. This paper traces the evolution of currency from medieval times to the present digital era and explores the differences between the barter system, fiat currency, and cryptocurrency. It also delves into the potential of cryptocurrency to revolutionize our perception of money. 2024, IGI Global. All rights reserved.