THE CAPITAL STRUCTURE OF MANUFACTURING INDUSTRIES IN INDIA

This study examines the growth performance of the capital structure of Indian manufacturing industries over the period from 1981–82 to 2019–20, using secondary data sourced from the Annual Survey of Industries (ASI). The analysis covers the key principal characteristics, namely number of factories, fixed capital, working capital, invested capital, and depreciation, deflated to constant prices with 2011–12 base year. Methodologically, the study employs the semi-logarithmic in that log-quadratic trend models is obtained to estimate the overall growth trends, as well as a two-kink exponential model to capture the sub-period growth rates across the period of pre-reform (1981–82 to 1990–91), post-reform (1991–92 to 2000–01), and transformation (2001–02 to 2019–20) phases. The findings reveal that the pre-reform period was marked by negative and decelerated growth rate, reflecting regulatory rigidities and limited access to capital. However, the post-1991 liberalization reforms catalysed accelerated growth rate across all the capital structure indicators, with particularly sharp increases in fixed capital, invested capital, and depreciation in the transformation phase. Overall, the results highlight the sector’s transition from a period of sluggish and uneven growth to accelerated capital accumulation and financial strengthening in the post-reform era. The study underscores how liberalization policies improved access to finance and structural reforms significantly influenced the composition and growth of capital structure, thereby enhancing the long-term growth potential and sustainability of India’s manufacturing industries

Economic Scrutiny of Structural Change and Occupational Diversification in India – A Look at Post-Reform Period

Expansion and creation of employment opportunities have been the unstated objectives being followed since the early 1990s in India. After the emergence of new economic reforms, economic development has shown a growing trend, but employment growth during the period from 2012 - 2019 has drastically fallen in absolute numbers after the marginal improvement during the commencement of economic reforms. The people are moving towards low-productivity sectors and shoddier the quality of employment. The present study examines the recent trends of structural changes in economic development and occupational diversification in India and tries to identify the outcome and ineptitude of the ongoing vicious pattern of economic development and employment. The paper argues that the structural changes are bounded to output level only, there is no transformation of labours between the sectors that lead to more unemployment. The increasing share of unemployment having the intermediate and advanced education led to the increase of employment in the informal sector for their livelihood. India's inclusive growth will be impossible to achieve unless the informal sector's share of total employment does not reduc

Automatic Detection of User Abilities through the SmartAbility Framework

This paper presents a proposed smartphone application for the unique SmartAbility Framework that supports interaction with technology for people with reduced physical ability, through focusing on the actions that they can perform independently. The Framework is a culmination of knowledge obtained through previously conducted technology feasibility trials and controlled usability evaluations involving the user community. The Framework is an example of ability-based design that focuses on the abilities of users instead of their disabilities. The paper includes a summary of Versions 1 and 2 of the Framework, including the results of a two-phased validation approach, conducted at the UK Mobility Roadshow and via a focus group of domain experts. A holistic model developed by adapting the House of Quality (HoQ) matrix of the Quality Function Deployment (QFD) approach is also described. A systematic literature review of sensor technologies built into smart devices establishes the capabilities of sensors in the Android and iOS operating systems. The review defines a set of inclusion and exclusion criteria, as well as search terms used to elicit literature from online repositories. The key contribution is the mapping of ability-based sensor technologies onto the Framework, to enable the future implementation of a smartphone application. Through the exploitation of the SmartAbility application, the Framework will increase technology amongst people with reduced physical ability and provide a promotional tool for assistive technology manufacturers

Wear behaviour of cast aluminium silicon (Al-Si) alloy in dot 4 brake fluid

Abstract : The frictional sliding behaviour of cast Al-Si alloy was investigated with and without DOT 4 hydraulic brake fluid lubrication/environments. Cast Al-Si specimen was produced from wrought alloy and the specimen surface was metallurgically prepared. The as- cast product was characterized with aid of micro-hardness tester, the chemical composition was analysed by X-ray fluorescence (XRF), while X-ray diffraction (XRD) was used to identify phases present, microstructures and surface examinations were done on a high resolution metallurgical Optical Microscope. The properties of the polished and worn sample surfaces were examined by Scanning electron microscope (SEM) equipped with Energy dispersive X- ray (EDS) facilities. A 6mm diameter alumina ball under varying normal loads (3-10 N) was rubbed against the surface of the cast Al-Si coupon specimen. The dry and wet sliding wear behaviour was assessed based on the CoF-sliding time behaviour. From the results, the average CoF values of 0.9064 for dry and 0.2038 for wet contacts were obtained. Comparatively, 1.03E-06 and 4.21E-07 minimum wear intensities; and 467290 and 132170 wear resistances were obtained for dry and wet contacts respectively. Behaviour of cast Al-Si in DOT4 were compared with its performance in DOT3 regarding the hydraulic brake system application

Climate change and rice production in Sri Lanka: short-run vs. long-run symmetric and asymmetric effects

This study explores climate change's symmetric and asymmetric impacts on rice production in Sri Lanka, a crucial sector for food security in the country. The analysis utilized Autoregressive Distributed Lag (ARDL) and Non-linear Autoregressive Distributed Lag (NARDL) models. This study analyses annual data from 1952 to 2022 to capture relationships among the study variables. The ARDL findings reveal that temperature and cultivated land area have a significant long-term effect on rice production. The NARDL model reveals that positive and negative changes in climate variables have asymmetrical long-term impacts. Positive changes in temperature and rainfall lead to a notable decline in rice yields in the long term. Negative rainfall changes create a significant beneficial effect on rice production in the long term. Cultivated land area shows a significant positive impact on rice yield in the long term. The results of symmetric and asymmetric climate change impact are essential for formulating agricultural climate adaptation policies, such as promoting climate resilience rice varieties, improving irrigation and water management, developing early warning systems that promote sustainability and enhance climate adaptation strategies, ensuring food security in Sri Lanka

Highly Asynchronous and Asymmetric Cleavage Divisions Accompany Early Transcriptional Activity in Pre-Blastula Medaka Embryos

In the initial phase of development of fish embryos, a prominent and critical event is the midblastula transition (MBT). Before MBT cell cycle is rapid, highly synchronous and zygotic gene transcription is turned off. Only during MBT the cell cycle desynchronizes and transcription is activated. Multiple mechanisms, primarily the nucleocytoplasmic ratio, are supposed to control MBT activation. Unexpectedly, we find in the small teleost fish medaka (Oryzias latipes) that at very early stages, well before midblastula, cell division becomes asynchronous and cell volumes diverge. Furthermore, zygotic transcription is extensively activated already after the 64-cell stage. Thus, at least in medaka, the transition from maternal to zygotic transcription is uncoupled from the midblastula stage and not solely controlled by the nucleocytoplasmic ratio

The Atlantic Bonito ( Sarda sarda,Bloch 1793) Transcriptome and Detection of Differential Expression during Larvae Development

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Tiling Histone H3 Lysine 4 and 27 Methylation in Zebrafish Using High-Density Microarrays

BACKGROUND: Uncovering epigenetic states by chromatin immunoprecipitation and microarray hybridization (ChIP-chip) has significantly contributed to the understanding of gene regulation at the genome-scale level. Many studies have been carried out in mice and humans; however limited high-resolution information exists to date for non-mammalian vertebrate species. PRINCIPAL FINDINGS: We report a 2.1-million feature high-resolution Nimblegen tiling microarray for ChIP-chip interrogations of epigenetic states in zebrafish (Danio rerio). The array covers 251 megabases of the genome at 92 base-pair resolution. It includes ∼15 kb of upstream regulatory sequences encompassing all RefSeq promoters, and over 5 kb in the 5' end of coding regions. We identify with high reproducibility, in a fibroblast cell line, promoters enriched in H3K4me3, H3K27me3 or co-enriched in both modifications. ChIP-qPCR and sequential ChIP experiments validate the ChIP-chip data and support the co-enrichment of trimethylated H3K4 and H3K27 on a subset of genes. H3K4me3- and/or H3K27me3-enriched genes are associated with distinct transcriptional status and are linked to distinct functional categories. CONCLUSIONS: We have designed and validated for the scientific community a comprehensive high-resolution tiling microarray for investigations of epigenetic states in zebrafish, a widely used developmental and disease model organism

Zebrafish Whole-Adult-Organism Chemogenomics for Large-Scale Predictive and Discovery Chemical Biology

The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly), is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated) aromatic hydrocarbons [P(H)AHs] and estrogenic compounds (ECs), we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR) and estrogen receptor (ER) agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology