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"Singh, Rahul"
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Migration, gender and home economics in rural North India
\"This book critically examines the socio-economic impacts of out-migration on households and gender dynamics in rural northern India. The first of its kind, this study unearths, through detailed regional and demographical research, the ways in which economic and migratory trends of male family members in rural India in general, and hilly regions of Garhwal in particular, affect the wives, children, extended families, and agricultural lands that they have left behind. It offers vital research in how rural India's socio-economic formations and topographic characteristics can today more effectively contribute to the national and global economy with respect to migratory trends, gender dynamics, and home life. Furthermore, it investigates the collapse of agricultural and many other traditional economic activities without a corresponding creation of fresh economic opportunities. This volume moreover elucidates how male out-migration from rural to urban centres has greatly re-shaped kinship and economic structures at places of origin and consequently had a serious impact on the socio-psychological well- being of family members This volume will be of great value to scholars and researchers of development economics, agricultural economics, environment studies, sociology, social anthropology, population studies, gender and women's studies, social psychology, migration and diaspora studies, South Asian studies, and behavioral studies\"-- Provided by publisher.
Book
Intermittency in the not-so-smooth elastic turbulence
Elastic turbulence is the chaotic fluid motion resulting from elastic instabilities due to the addition of polymers in small concentrations at very small Reynolds (
Re
) numbers. Our direct numerical simulations show that elastic turbulence, though a low
Re
phenomenon, has more in common with classical, Newtonian turbulence than previously thought. In particular, we find power-law spectra for kinetic energy
E
(
k
) ~
k
−4
and polymeric energy
E
p
(
k
) ~
k
−3/2
, independent of the Deborah (De) number. This is further supported by calculation of scale-by-scale energy budget which shows a balance between the viscous term and the polymeric term in the momentum equation. In real space, as expected, the velocity field is smooth, i.e., the velocity difference across a length scale
r
,
δ
u
~
r
but, crucially, with a non-trivial sub-leading contribution
r
3/2
which we extract by using the second difference of velocity. The structure functions of second difference of velocity up to order 6 show clear evidence of intermittency/multifractality. We provide additional evidence in support of this intermittent nature by calculating moments of rate of dissipation of kinetic energy averaged over a ball of radius
r
,
ε
r
, from which we compute the multifractal spectrum.
Intermittency is the behavior of extreme fluctuations observed in the flow of a fluid that is often associated with high Reynolds numbers. Here, the authors report intermittency in elastic turbulence at the low Reynolds number and high Deborah number limit.
Journal Article
Intermittency, fluctuations and maximal chaos in an emergent universal state of active turbulence
The phenomenon of active turbulence, a complex organization of matter driven at the scale of its constituent agents, is puzzling. Specifically, the lack of scale-separation in low-Reynolds-number active flows breaks away from the familiar notions of the energy cascade and approximate scale-invariance of inertial turbulence. Here, using a generalized hydrodynamic model developed for bacterial turbulence, we provide compelling analytical and numerical evidence that, beyond a critical drive, active turbulence indeed attains universality akin to inertial turbulence. In this asymptotic state, the energy spectrum scales as k−3/2, reminiscent of some classes of inertial turbulence. The flow also exhibits spatio-temporal intermittency beyond the transition, as seen from non-Gaussian fluctuations in velocity differences. With these tell-tale fingerprints, active turbulence is placed closer in phenomenology to inertial turbulence than previously held. We show, however, that as a consequence of a finite range of scales, the degree of chaoticity and hence mixing efficiency saturates to a maximum in the asymptotic regime, unlike unbounded chaos in inertial turbulence. We conclude that active turbulence, depending on the level of drive, can switch between fundamentally distinct non-universal and universal states.Active fluids exhibit regimes with a complex spatio-temporal structure reminiscent of inertial turbulence. Now, inertial and active turbulence are theoretically shown to be closely related indeed.
Journal Article
Excitation signal optimization for minimizing fluctuations in knock out slow extraction
The synchrotron is a circular particle accelerator used for high energy physics experiments, material and life science, as well as hadron cancer therapy. After acceleration to the desired energies, particle beams are commonly extracted from the synchrotron using the method of resonant slow extraction. The goal is to deliver a steady particle flux—referred to as
spill
—to experiments and treatment facilities over the course of seconds while slowly emptying the storage ring. Any uncontrolled intensity fluctuations in the spill are detrimental to the efficiency of beam usage, as they lead to detector pileups or detector interlocks, hindering experiments and cancer treatment. Among the most widely used extraction scheme in medical facilities is the Radio Frequency Knock Out (RF-KO) driven resonant slow extraction, where the stored beam is transversely excited with a radio frequency (RF) field and the spill intensity is controlled by the excitation signal strength. This article presents particle dynamics simulations of the RF-KO system with the focus on finding effective mechanism for minimizing the intensity fluctuations while maintaining a good extraction efficiency and other advantages of KO extraction. An improved beam excitation signal which optimizes these main objectives is found, and is rigorously compared experimentally with other commonly applied techniques.
Journal Article
Scalable earthquake magnitude prediction using spatio-temporal data and model versioning
Earthquake magnitude prediction is critical for natural calamity prevention and mitigation, significantly reducing casualties and economic losses through timely warnings. This study introduces a novel approach by using spatio-temporal data from seismic records obtained from the Indian government seismology department and weather data sourced via VisualCrossing to predict earthquake magnitudes. By integrating environmental and seismic variables, the study explores their interrelationships to enhance predictive capabilities. The proposed framework incorporates a machine learning operations (MLOps)-driven pipeline using MLflow for automated data ingestion, preprocessing, model versioning, tracking, and deployment. This novel integration ensures adaptability to evolving datasets and facilitates dynamic model selection for optimal performance. Multiple machine learning algorithms, including Gradient Boosting, Light Gradient Boosting Machine (LightGBM), XGBoost, and Random Forest, are evaluated on dataset sizes of 20%, 35%, 65%, and 100%, with performance metrics such as Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, and
R
2
. The results reveal that Gradient Boosting performs optimally on smaller datasets, while LightGBM demonstrates superior accuracy with larger datasets, showcasing the pipeline’s flexibility and scalability. This research presents a scalable, robust, and resilient solution for earthquake magnitude prediction by combining diverse data sources with a dynamic and operational MLOps framework. The outcomes illustrate the potential of integrating advanced machine learning techniques with lifecycle management practices to enhance prediction accuracy and applicability in real-world seismic scenarios.
Journal Article
Analysis of associations between emotions and activities of drug users and their addiction recovery tendencies from social media posts using structural equation modeling
Background
Addiction to drugs and alcohol constitutes one of the significant factors underlying the decline in life expectancy in the US. Several context-specific reasons influence drug use and recovery. In particular emotional distress, physical pain, relationships, and self-development efforts are known to be some of the factors associated with addiction recovery. Unfortunately, many of these factors are not directly observable and quantifying, and assessing their impact can be difficult. Based on social media posts of users engaged in substance use and recovery on the forum Reddit, we employed two psycholinguistic tools, Linguistic Inquiry and Word Count and Empath and activities of substance users on various Reddit sub-forums to analyze behavior underlining addiction recovery and relapse. We then employed a statistical analysis technique called structural equation modeling to assess the effects of these latent factors on recovery and relapse.
Results
We found that both emotional distress and physical pain significantly influence addiction recovery behavior. Self-development activities and social relationships of the substance users were also found to enable recovery. Furthermore, within the context of self-development activities, those that were related to influencing the mental and physical well-being of substance users were found to be positively associated with addiction recovery. We also determined that lack of social activities and physical exercise can enable a relapse. Moreover, geography, especially life in rural areas, appears to have a greater correlation with addiction relapse.
Conclusions
The paper describes how observable variables can be extracted from social media and then be used to model important latent constructs that impact addiction recovery and relapse. We also report factors that impact self-induced addiction recovery and relapse. To the best of our knowledge, this paper represents the first use of structural equation modeling of social media data with the goal of analyzing factors influencing addiction recovery.
Journal Article
Spatiotemporal variation in fish species distribution and abundance in the Vaishav stream, Kashmir Himalaya–India
Exploring the intricate dynamics of aquatic ecosystems present study investigates the spatio-temporal variations in the ecological parameters of the fish community within the Vaishav stream, Kashmir Himalayas. Monthly field investigations were conducted at three distinct sites (SI, SII & SIII) throughout the four seasons (winter, spring, summer, autumn) from November 2019 to October 2020. The findings encompass a total of 630 specimens belonging to 11 fish species, three orders Cypriniformes , Siluriforms and Salmoniformes and four families including Cyprinidae , Nemachelidae , Siluridae and Salmonidae were reported from the study sites. Among collected specimens, Cypriniformes were dominant with nine species followed by order Siluriformes and Salmoniformes with one species each. Out of eleven fish species, six fish species belongs to family Cyprinidae , three to Nemachelidae , one to Siluridae and Salmonidae each. The analysis, employing non-metric multidimensional scaling (NMDS), Principal component analysis (PCA), Analysis of similarity (ANOSIM) and Per-mutational multivariate analysis of variance (PERMANOVA) on fish abundance data highlighted significant differences among the various sites but not across seasons. The results unveil a diverse occurrence and distribution pattern of fishes from upstream to downstream. Furthermore, diversity metrics confirm higher diversity index values downstream, indicating a more conducive environment for fish survival. Jaccard’s index reveals greater similarity in fish fauna between site-II and site-III than site-I and site-III in terms of overlap of fish species composition. The study concludes that anthropogenic activities in the stream catchment area have led to a reduction in fish diversity and abundance, with landscape features significantly influencing fish abundance in this unique Himalayan ecosystem.
Journal Article
Advances in therapeutic and managemental approaches of bovine mastitis: a comprehensive review
Mastitis (intramammary inflammation) caused by infectious pathogens is still considered a devastating condition of dairy animals affecting animal welfare as well as economically incurring huge losses to the dairy industry by means of decreased production performance and increased culling rates. Bovine mastitis is the inflammation of the mammary glands/udder of bovines, caused by bacterial pathogens, in most cases. Routine diagnosis is based on clinical and subclinical forms of the disease. This underlines the significance of early and rapid identification/detection of etiological agents at the farm level, for which several diagnostic techniques have been developed. Therapeutic regimens such as antibiotics, immunotherapy, bacteriocins, bacteriophages, antimicrobial peptides, probiotics, stem cell therapy, native secretory factors, nutritional, dry cow and lactation therapy, genetic selection, herbs, and nanoparticle technology-based therapy have been evaluated for their efficacy in the treatment of mastitis. Even though several strategies have been developed over the years for the purpose of managing both clinical and subclinical forms of mastitis, all of them lacked the efficacy to eliminate the associated etiological agent when used as a monotherapy. Further, research has to be directed towards the development of new therapeutic agents/techniques that can both replace conventional techniques and also solve the problem of emerging antibiotic resistance. The objective of the present review is to describe the etiological agents, pathogenesis, and diagnosis in brief along with an extensive discussion on the advances in the treatment and management of mastitis, which would help safeguard the health of dairy animals.
Journal Article
Cyanobacteria : an emerging source for drug discovery
The c group of Gram-negative gliding bacteria, has a long history of cosmopolitan occurrence. It has great biodiversity despite the absence of sexual reproduction. This wide biodiversity may be reflected in the wide spectrum of its secondary metabolites. These cyanobacterial secondary metabolites are biosynthesized by a variety of routes, notably by non-ribosomal peptide synthetase or polyketide synthetase systems, and show a wide range of biological activities including anticancer, antibacterial, antiviral and protease inhibition activities. This high degree of chemical diversity in cyanobacterial secondary metabolites may thus constitute a prolific source of new entities leading to the development of new pharmaceuticals.
Journal Article
Pollutants and Water Management
POLLUTANTS AND WATER MANAGEMENT
Pollutants and Water Management: Resources, Strategies and Scarcity delivers a balanced and comprehensive look at recent trends in the management of polluted water resources. Covering the latest practical and theoretical aspects of polluted water management, the distinguished academics and authors emphasize indigenous practices of water resource management, the scarcity of clean water, and the future of the water system in the context of an increasing urbanization and globalization.
The book details the management of contaminated water sites, including heavy metal contaminations in surface and subsurface water sources. It details a variety of industrial activities that typically pollute water, such as those involving crude oils and dyes. In its discussion of recent trends in abatement strategies, Pollutants and Water Management includes an exploration of the application of microorganisms, like bacteria, actinomycetes, fungi, and cyanobacteria, for the management of environmental contaminants.
Readers will also discover a wide variety of other topics on the conservation of water sources including:
* The role of government and the public in the management of water resource pollution
* The causes of river system pollution and potential future scenarios in the abatement of river pollution
* Microbial degradation of organic pollutants in various water bodies
* The advancement in membrane technology used in water treatment processes
* Lead contamination in groundwater and recent trends in abatement strategies for it
* Highly polluting industries and their effects on surrounding water resources
Perfect for graduate and postgraduate students and researchers whose focus is on recent trends in abatement strategies for pollutants and the application of microorganisms for the management of environmental contaminants, Pollutants and Water Management: Resources, Strategies and Scarcity also has a place in the libraries of environmentalists whose work involves the management and conservation of polluted sites.
eBook