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Role of Machine Learning in the Analysis of Mental Health Data: An Empirical Approach
As funding for mental health research has grown, so too has the body of knowledge about how best to address and alleviate issues related to mental health. However, there is still a lack of certainty and clarity on the precise causes of mental diseases. Discovery of new drugs, analysis of radiological data, forecasting of disease outbreaks, and the diagnosis of illnesses are just some of the medical applications of machine learning algorithms. Machine learning algorithms are commonly used to sift through the mountains of medical data. Since their performance has improved to the point where it can be relied upon, they are now used to aid in medical diagnosis. To assess and address the issues with mental health, numerous new approaches and algorithms had been devised. There are still a lot of issues that can be resolved. So the main purpose of this study is to examine the effectiveness of machine learning in mental health problems. For fulfilling this purpose, this study is descriptive in nature. Primary data is collected with the help of interview method in which 50 individuals suffering from mental illness were asked to answers some questions. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Cold spray deposition of hydroxyapatite powder onto magnesium substrates for biomaterial applications
A simple, modified, cold spray process was developed in which hydroxyapatite powder was coated onto pure magnesium substrates preheated to 350 or 550C and ground to either 240 or 2000 grit surface roughness, with stand-off distances of 20 or 40 mm. The procedure was repeated five and 10 times. The hydroxyapatite coatings did not show any phase changes. Atomic force microscopy revealed a uniform coating topography, and scanning electron microscopy revealed good bonding between the coated layers and the substrates. As the p values were < 0.05, all factors except the number of sprays were considered to be significant. The response optimiser indicated that a 22.7 mm stand-off distance, a 649.2 grit surface roughness and a 496C substrate heating temperature produced good hydroxyapatite coatings of 46.3 ?m thickness, 436.5 MPa nanohardness and 43.9 GPa elastic modulus. The modified cold spray technique with substrate heating showed promising results in terms of product coating thickness and mechanical properties. 2015 Institute of Materials, Minerals and Mining. -
Optimization of multiple responses using overlaid contour plot and steepest methods analysis on hydroxyapatite coated magnesium via cold spray deposition
In this work, sequential optimization strategy based statistical design was employed to enhance the mechanical properties of hydroxyapatite coatings onto a pure magnesium substrate using a cold spray technique. A fractional factorial design (24-1) was applied to elucidate the process parameters that significantly affected the mechanical properties of the coating samples. Standoff distance, surface roughness, and substrate heating temperature were identified as important process parameters affecting thickness, nanohardness, and the elastic modulus of the coating sample. The overlaid method analysis was employed to determine tradeoff optimal values from multiple regressive equations. Then, finally, steepest method analysis was used to reconfirm and relocate the optimal domain from which the factor levels for maximum mechanical properties of the coating were determined at 49.77mm standoff distance, 926.4grit surface roughness, and 456C substrate heating temperature, which can accommodate the optimum requirements for the cold spray process with a coating of 49.77?m thickness, 462.61MPa nanohardness, and 45.69GPa elastic modulus. Scanning electron microscopy revealed that a short standoff distance, high surface roughness, and high substrate temperatures improved the bond between the coated layers and substrates. 2015 Elsevier B.V. -
Tourism and Hospitality in Asia: Crisis, Resilience and Recovery
This book analyses the ways in which crises, including COVID-19, can be managed within the tourism and hospitality industries in Asia, in ways that support the future of these industries and help to make them more resilient. This book supports efforts to develop a new direction for the tourism and hospitality industry by considering their development holistically in the context of sustainable development. Going further, this book highlights actions to make the tourism system more resilient to external shocks and crises. Readers of this book will get insights into the economic, social, technological, and environmental implications of crises on the tourism and hospitality industry in Asia, including issues within the food and beverage industry in the Asian post-COVID-19 period. This book has three major objectives: to explore the crisis context of Asian tourism and hospitality, to present multiple cases from countries in Asia, and finally to envisage the paths to make the Asian tourism system more resilient, through the discussion of new trends and issues emerging following the pandemic. This book examines the economic, social, environmental, and technological implications of crises on the Asian tourism and hospitality industry and discusses the various ways of managing these crises more efficiently, contributing new knowledge to the industry. In its wider context, this book covers tourism management, crisis management, and destination management. At the more micro level, themes explored include tourism economics, marketing management, hospitality management, food and beverage management and tourism technology. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Conclusion
We all can agree at one point: the COVID-19 pandemic has had a massive and unanticipated impact on all the lives of all tourists. The global tourism and hospitalityindustry has been heavily damaged, but the societal impact cannot be overlooked. Consumer behavior, and ultimately consumer spending, has been and will continue to change, and company planning must adapt to these new realities. The major findings of this edited book in the contexts of tourism, destination recovery and crisis management thus have value for the industry and for researchers seeking to understand these changes. Chapter 1 analyses evolution of tourism and hospitality during times of crisis and how these businesses might rebound. Academics in the field of tourism and hospitality can use this collection to understand the most recent studies on crises and recovery. The impact of the COVID-19 crisis on tourism and hospitality was examined in several published pieces. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Introduction
[No abstract available] -
Comparative Analysis of The Internet of Things (IOT) in the Health Sector
The Internet of Things (IoT) technology is still the main target of the discussion since it now has a significant influence on the healthcare industry. The majority of researchers who use technologies are professors and specialists. It aids in obtaining accurate study results so that rural areas may utilize technologies as well. It offers appropriate financial gains that are substantial. Services at a reasonable cost. Today, it is crucial to advance both the therapy and pharmaceutical sectors of medicine. The level of technology aids in conducting appropriate investigation appropriate solutions. The IoT is being utilized to improve the wearable electronic technologies that are applied to provide smart healthcare services in several different methods. They can survive as a result of it. According to research, IOT in the administration of wheelchairs, mobile healthcare solutions, as well as other variables has favourably affected the improvement of healthcare services. 2023 IEEE. -
Rethinking growth for long-term welfare: A case for circular economy transition in the tourism sector in Nepal
The construct of Circular Economy (CE) is emerging as an alternate to the existing linear "extraction-use-disposal" economic model. CE concept emphasises the significance of sustaining the value of resources like materials and products within the economy, lessening waste generation, thereby enhancing sustainability. The pandemic crisis has offered a rare prospect to pause and ruminate on crucial anxieties about the future prospects of the tourism industry, together with issues related to overall resilience, undesirable environmental and social impacts, opportunities, and risks amidst the emerging sustainability challenges. Over-tourism, GHG emissions and biosphere degradation problems will not automatically recede post-pandemic when the 'normalcy' returns. Principally, these challenges have to be dynamically addressed so as to rebuild a tourism industry that is economically and environmentally sustainable and more resilient. This paper aims to understand the need and implications of the shift of the tourism industry to the circular economy model. An attempt is made to examine the prospect of Nepal transitioning into a CE so that there is a well-balanced and restorative accomplishment from economic and environmental standpoints. 2024 Nova Science Publishers, Inc. All rights reserved. -
Interpretable Breast Cancer Risk Stratification Using Statistical Feature Engineering on Thermal Images
This research solves the black box problem of AI implementation in imaging by introducing a transparent, statistically grounded approach to breast cancer risk stratification via infrared thermography without compromising performance. Using the public DMR-IR dataset, statistical feature engineering was applied to training data by extracting first- and second-order statistical features. After ensuring non-normality with a Shapiro-Wilk test, feature significance was established with the Mann-Whitney U test. LASSO regularization selected the five most predictive features: mean, standard deviation, kurtosis, correlation, and energy. To counteract class imbalance, SMOTE was applied, and two machine learning modelslogistic regression and random forest (classifier)were trained on the balanced data and then evaluated on an unseen test dataset. Reporting an AUC of 0.98 over logistic regressions 0.96 reflects stringent statistical feature engineering and great generalization, creating a strong and interpretable model for breast cancer diagnosis in thermal images, and instills more clinical confidence in AI-based diagnostic systems. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Control of NOx from a DI diesel engine with hot EGR and ethanol fumigation: An experimental investigation
Oxides of nitrogen (NOx) are one of the major hazardous pollutants from diesel engine emission. Various control technologies exist for its control but each technique has advantages and disadvantages. At present, there is no single optimal technique that can control NOx without other side effects. Technologies available for NOx reductions either cause fuel penalty or increase other polluting emissions. Exhaust Gas Recirculation is an effective technique in controlling oxides of nitrogen in diesel engines but do not become attractive at higher loads and higher percentage of recirculated gas as combustion tends to deteriorate at higher loads leading to reduced engine thermal efficiency and increased hydrocarbon and smoke emission. Ethanol is an established alternate fuel used in diesel engine either as a blend or fumigated using a separate injector. Experiments were conducted on a single cylinder diesel engine to examine the effect of EGR temperature on NOx and other emission constituents. Hot EGR gave better results up to 30% EGR rate but EGR cooling was found better in terms of NOx reductions and efficiency. It was found that NOx reductions up to 88% was possible but at the cost of about 18% loss in thermal efficiency. This inconvenience of fuel penalty caused by Exhaust Gas Recirculation can be overcome by applying ethanol fumigation. The findings of experimental results for this combined technique are presented in this paper. With this combined technique, apart from reducing the oxides of nitrogen, engine power and efficiency approaches to that of only diesel combustion condition with improvements in smoke, hydrocarbon and carbon monoxide emissions. 2013 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg. -
Crossing numbers of complete bipartite graphs and complete graphs
The crossing number of a graph is the smallest number of two edge crossings over all planar representations of the graph. In this paper, we investigate the crossing numbers of complete bipartite and complete graphs. Further, we identify optimal drawings and present results on crossing numbers of these classes of graphs. In addition, Zarankiewicz's conjecture on complete bipartite graphs and Guy's conjecture on complete graphs are verified to be true. 2018 Sanjith Hebbar, Tabitha Agnes Mangam. -
GPR based subsurface geotechnical exploration
The Seismic refraction technique (SRT) and Electrical resistivity technique (ERT) have long been in use in geotechnical exploration. A relatively recent technique is Ground penetrating radar (GPR). The study presented in this paper is on GPR-aided geotechnical subsurface exploration. The usual method of exploration is drilling, which gives much-needed site-specific information, but is expensive and restricted to a few point locations. The possibilities of non-invasive investigation offered by GPR make it useful for supplementing geotechnical investigations. The present work describes GPR survey at a construction site in Mumbai. The objective was to derive subsurface logs from GPR signals. Conventionally, subsurface logging is done using boreholes. First, the extracted soil and rock samples are examined visually. Second, additional information such as Core recovery ratios (CRR), Rock quality designation (RQD) and Standard penetration test (SPT) N values are collected and strata are demarcated. In comparison, the amplitude variations of GPR signals may not correspond directly to variations of these physical properties with depth. However, the study shows that fairly good correlations do exist with the subsurface stratification and transformed signals. -
Classification Framework for Fraud Detection Using Hidden Markov Model
Machine learning is described as a computer program that learns from experience E with regard to some task T and some performance measure P, if its performance on T improves with E as measured by P. Suppose we have a credit card fraud detection which watches which transactions we mark as fraud or not, and on the basis, it knows how to filter better fraudulent transactions then, E is watching your transactions is fraud or not, T is classifying your transactions as fraud or not, P is number of transactions correctly differentiated as spam or not spam. Machine learning has two types: supervised learning and unsupervised learning. Supervised learning is the type of machine learning where machine is provided with input mapped with its output, and these inputs and outputs are used to make a machine learn a particular function from the trained dataset. There are two branches of supervised learning, i.e., classification and regression. In unsupervised learning, we do not supervise model instead we allow machine to work on its own to discover information. Clustering is type of unsupervised learning. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Enhancement of tensile strength and elastic modulus using bio-waste based carbon nanospheres doped polymer nanocomposites
The Carbon Nano Spheres (CNS) derived from areca nuts were synthesized from pyrolysis process and were used as fillers for fabrication of polymer nano composite materials. The filler materials are loaded in 0.05%, 0.1% and 0.5% loading percentages. The optimum sample was subjected to heat treatment. The tensile strength, elastic modulus and % of elongation were investigated for all samples. The Scanning Electron Microscope (SEM) images revealed the morphological features of optimum samples and hence the uniform dispersion of CNS in polymer matrix. The 0.1% samples showed 10% improvement in Ultimate Tensile Strength (UTS) and 24% improvement in Elastic modulus compared to bare epoxy material. When 0.1% samplewas subjected to heat treatment under 200C the UTS improved by 23%. Hence, CNS reinforced composite materials exhibited unique properties like high strength, less weight and low cost making them suitable for various structural applications such as aerospace, automotive, construction, and electronics industries. The Polymer Society, Taipei 2024. -
Biogenic synthesis of Pd-nanoparticles using Areca Nut Husk Extract: a greener approach to access ?-keto imides and stilbenes
An eco-friendly green method for a one-step synthesis of palladium nanoparticles and their synthetic utility are reported. Phytochemicals like amines, alcohols, and phenols present in the Areca Nut Husk extract facilitate the reduction of Pd(ii) to Pd(0). The phytochemicals serve as stabilising agents and ligands for palladium reduction and the need for an external ligand is avoided. The Field Emission Scanning Electron Microscopy and Transmission Electron Microscopy of newly synthesized palladium nanoparticles revealed a spherical morphology. The catalytic activity of the nanoparticles was tested for 1,2-difunctionalization of ynamides, Heck coupling, denitrogenative coupling of phenylhydrazine and C-H arylation of indole. Moreover, catalyst recyclability, control experiments, mechanistic elucidation, and gram-scale synthesis are elaborated. The Royal Society of Chemistry and the Centre National de la Recherche Scientifique 2021. -
Navigating green synthesized metal-based nanoparticles as anti-inflammatory agent Comprehensive review
The biosynthesis of nanomaterials is a vast and expanding field of study due to their applications in a variety of fields, particularly the pharmaceutical and biomedical fields. Various synthetic routes, including physical and chemical methods, have been developed in order to generate metal nanoparticles (NPs) with definite shapes and sizes. In this review, focused on the recent advancements in the green synthetic methods for the generation of silver, zinc and copper NPs with simple and eco-friendly approaches and the potential of the biosynthesized metal and metal oxide NPs as alternative and therapeutic agent for the treatment of inflammatory diseases. Inflammation is a body's own defense mechanism that can become chronic inflammation affecting healthy cells. Owning to the size-based advantages of NPs which can mitigate in theses medical conditions and serve as anti-inflammatory drugs. The factors influencing their physicochemical properties, toxicity, biocompatibility and mode of action to formulate an effective nanomedicine in the treatment of inflammation. 2024 Elsevier B.V. -
Titanium based dual behavioral magnetic nanocomposite for ipso-hydroxylation and selective oxidation reactions under white light
A new titanium-based magnetic nanocomposite was prepared using facile method. The characterization of the prepared nanocomposite by various analytical techniques confirmed the successful coating of TiO2 on to the magnetic surface. A vital role of the prepared nanocomposite as photocatalyst for the selective oxidation of benzyl alcohols to their corresponding aldehydes and ipso-hydroxylation of aryl boronic acids under the illumination of tailor-made set up employing white light was demonstrated. The nanocatalyst was recycled and it retained excellent catalytic activity towards both the reactions upto several cycles demonstrating the excellent heterogeneous nature and possible application in the industries ensuring the sustainability. 2024 Elsevier B.V. -
Magnetically retractable tea extract stabilized palladium nanoparticles for denitrogenative cross-coupling of aryl bromides with arylhydrazines under green conditions: An alternate route for the biaryls synthesis
Novel palladium based magnetic nanocatalyst was synthesized by the co-precipitation method and coated with silica and tea extract as stabilizing agent. Palladation onto the prepared nanocomposite was done to get ION-SiO2/TE-Pd(0) catalyst. Our study is one of the limited number of studies reported for the catalytic denitrogenative coupling of arylbromide and arylhydrazine. This led to the construction of important substituted biaryls bearing various substituents with 8292% yields. The synthesized nanocatalyst was characterized using structural and morphological characterization techniques. It was also observed that only 2 mol% of ION-SiO2/TE-Pd(0) catalyst was sufficient for the catalysis and reusable upto six cycles. 2024 The Authors -
Furaldehyde-based magnetic supported palladium nanoparticles as an efficient heterogeneous catalyst for Mizoroki-Heck cross-coupling reaction
A novel palladium functionalised magnetic nanocatalyst (Fe3O4@SiO2-FA-Pd) was prepared using silica-coated iron oxide and furaldehyde Schiff base as a supported material. FT-IR, VSM, TEM, FESEM, XPS, EDAX and TGA were used to analyse the morphological structure and chemical composition of Fe3O4@SiO2-FA-Pd NPs. Thus, the prepared Fe3O4@SiO2-FA-Pd NPs as a magnetic nanocatalyst were used in the Mizoroki-Heck reaction of arylbromide and terminal alkenes, exhibiting effective catalysis with good yields. The magnetic nanocatalyst can be reused up to 6 times without significantly losing catalytic activity and is easily separable from the reaction mixture. This new catalytic system has significant and potentially useful applications in the pharmaceutical industry. 2024 The Royal Society of Chemistry. -
Palladium immobilized on guanidine functionalized magnetic nanoparticles: a highly effective and recoverable catalyst for ultrasound aided Suzuki-Miyaura cross-coupling reactions
We designed and prepared a palladium catalyst that can be magnetically recyclable by anchoring guanidine moiety on the surface of Fe3O4 nanoparticles, named Fe3O4@SiO2-TCT-Gua-Pd. It was established to be a potent catalyst for the Suzuki-Miyaura cross-coupling reaction (SMCR) in the EtOH/H2O system under ultrasonic conditions. FT-IR spectroscopy, field-emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX) microanalysis, vibration sample magnetometry (VSM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), and inductively coupled plasma atomic emission spectrometry (ICP-AES) analyses were used to characterize the structure of the Fe3O4@SiO2-TCT-Gua-Pd nanoctalyst. The Fe3O4@SiO2-TCT-Gua-Pd catalyst produced favorable coupled products with excellent yields and was harmonious with various aryl halides and aryl boronic acids. The stability, low palladium leaching, and heterogeneous nature of the nanocatalyst were confirmed by a hot-filtration test. The palladium nanocatalyst could be easily recovered by magnetic field separation and recycled at least 6 times in a row without noticeable loss in its catalytic activity. 2023 The Royal Society of Chemistry.