39 research outputs found
A dataset for Audio-Visual Sound Event Detection in Movies
Audio event detection is a widely studied audio processing task, with
applications ranging from self-driving cars to healthcare. In-the-wild datasets
such as Audioset have propelled research in this field. However, many efforts
typically involve manual annotation and verification, which is expensive to
perform at scale. Movies depict various real-life and fictional scenarios which
makes them a rich resource for mining a wide-range of audio events. In this
work, we present a dataset of audio events called Subtitle-Aligned Movie Sounds
(SAM-S). We use publicly-available closed-caption transcripts to automatically
mine over 110K audio events from 430 movies. We identify three dimensions to
categorize audio events: sound, source, quality, and present the steps involved
to produce a final taxonomy of 245 sounds. We discuss the choices involved in
generating the taxonomy, and also highlight the human-centered nature of sounds
in our dataset. We establish a baseline performance for audio-only sound
classification of 34.76% mean average precision and show that incorporating
visual information can further improve the performance by about 5%. Data and
code are made available for research at
https://github.com/usc-sail/mica-subtitle-aligned-movie-sound
Acute toxicity and behavioural responses of a freshwater mussel Lamellidens marginalis (Lamarck) to dimethoate exposure
Dimethoate is a commonly used organophosphate pesticide (OP) in agricultural practices, from where they reach into natural freshwater bodies through surface run-off, affecting the life of non-target aquatic organisms. Molluscs accumulate contaminants in their body tissues and thus are used as bio-indicator for evaluating water quality and habitat degradation. The mussels have great economic value, since they are consumed as food and have therapeutic significance. In this study 96h static acute toxicity test was carried out for dimethoate in freshwater mussel, Lamellidens marginalis. The mussels were exposed to 8 different concentrations of dimethoate (35.00, 37.00, 39.00, 41.00, 43.00, 45.00, 47.00, and 49.00 mg L-1) and control (00.00 mg L-1). The mortality data were subjected to EPA Probit analysis (version 1.5) statistical software based on Finney’s method. The 24, 48, 72 and 96h LC50 values of dimethoate for freshwater mussel were determined as 45.09, 40.52, 38.71 and 36.35 mg L-1 respectively. Mussels show behavioural responses during exposure by exhibiting increase in duration for shell closure, increase in mucus secretion and decrease in oxygen consumption
Characterization and Screening of Thermophilic Bacillus Strains for Developing Plant Growth Promoting Consortium From Hot Spring of Leh and Ladakh Region of India
In the present investigation, the main aim is to identify and characterize the potential drought tolerant plant growth promoting consortium for agricultural productivity. Three bacterial isolates were isolated from hot spring of Chumathang area of Leh district. Bacillus species (BHUJP-H1, BHUJP-H2, and BHUJP-H3) were done some biochemical tests including catalase, cellulase, amylase, indole-3-acetic acid, phosphate solubilisation, production of ammonia, siderophore, and hydrogen cyanide. Molecular characterization of isolates was done by 16S rDNA sequencing, e.g., Bacillus subtilis BHUJP-H1 (KU312403), Bacillus sp. BHUJP-H2 (KU312404) and B. licheniformis BHUJP-H3 (KU312405). The genetic diversity of the isolates was assessed by seven inter simple sequence repeat, all primer shows high polymorphism. The highest polymorphism efficiency and polymorphism information content showed by UBC-809 and UBC-836 which were 100% and 0.44 respectively, the lowest is by UBC-807 75% and 0.28 respectively. On an average 90.69% polymorphism efficiency and 0.40 polymorphism information contents obtained by used markers. The highest, 11.08 and the lowest, 4.50 effective multiplex ratios obtained for primer UBC-823 and UBC-807, on an average 7.99 effective multiplex ratio obtained. The highest, 4.89 and the lowest, 1.25 marker indexes obtained by UBC-836 and UBC-807 respectively and on an average 3.24 obtained. The UPGMA cluster analysis divided a population into two clusters I and II, in which BHUJP-H1 and BHUJP-H2 grouped under same while BHUJP-H3 grouped under another cluster. The treatment combination of Bacillus subtilis BHUJP-H1, B. subtilis BHUJP-H1+ B. licheniformis BHUJP-H3 and B. subtilis BHUJP-H1+ Bacillus sp. BHUJP-H2+ B. licheniformis BHUJP-H3 were recorded better combination for enhancing plant growth attributes of Vigna radiata as compared to control and others. The plant growth promoting consortium, e.g., Bacillus subtilis BHUJP-H1, Bacillus subtilis BHUJP-H1+ B. licheniformis BHUJP-H3 and B. subtilis BHUJP-H1+ Bacillus sp. BHUJP-H2+ B. licheniformis BHUJP-H3 can be further used as effective microbial inoculant for enhancing the production of mungbean in field conditions. Bacillus sp. BHUJP-H1 and Bacillus sp. BHUJP-H2 may use as drought tolerant plant growth promoting consortium for enhancing the sustainable agricultural productivity
Metabolomics-Driven Mining of Metabolite Resources:Applications and Prospects for Improving Vegetable Crops
Vegetable crops possess a prominent nutri-metabolite pool that not only contributes to the crop performance in the fields, but also offers nutritional security for humans. In the pursuit of identifying, quantifying and functionally characterizing the cellular metabolome pool, biomolecule separation technologies, data acquisition platforms, chemical libraries, bioinformatics tools, databases and visualization techniques have come to play significant role. High-throughput metabolomics unravels structurally diverse nutrition-rich metabolites and their entangled interactions in vegetable plants. It has helped to link identified phytometabolites with unique phenotypic traits, nutri-functional characters, defense mechanisms and crop productivity. In this study, we explore mining diverse metabolites, localizing cellular metabolic pathways, classifying functional biomolecules and establishing linkages between metabolic fluxes and genomic regulations, using comprehensive metabolomics deciphers of the plant’s performance in the environment. We discuss exemplary reports covering the implications of metabolomics, addressing metabolic changes in vegetable plants during crop domestication, stage-dependent growth, fruit development, nutri-metabolic capabilities, climatic impacts, plant-microbe-pest interactions and anthropogenic activities. Efforts leading to identify biomarker metabolites, candidate proteins and the genes responsible for plant health, defense mechanisms and nutri-rich crop produce are documented. With the insights on metabolite-QTL (mQTL) driven genetic architecture, molecular breeding in vegetable crops can be revolutionized for developing better nutritional capabilities, improved tolerance against diseases/pests and enhanced climate resilience in plants
Structural and functional characteristics and expression profile of the 20S proteasome gene family in Sorghum under abiotic stress
The 26S proteasome is a molecular machine that catalyzes and degrades protein intracellularly with the help of its core complex called 20S proteasome. The 20S proteasomes degrade and cleave denatured, cytotoxic, damaged, and unwanted proteins via proteolysis and impart biotic and abiotic stress tolerance in model plants. This study identified 20 genes, namely, 10 SbPA and 10 SbPB that encode for α- and β-subunits of the 20S proteasome in Sorghum bicolor (L.) Moench (2n= 20). These genes have been found distributed on the 1st, 2nd, 3rd, 4th, 5th, 7th, and 10th chromosomes. These sorghum genes were orthologous to corresponding rice. Phylogenetic analysis clustered these genes into seven clades, each with one of the seven α-subunits (1 to 7) and one of the seven β-subunits (1 to 7). In silico gene expression analysis suggested that nine genes were involved in abiotic stress response (cold, drought, and abscisic acid hormone). The expression of these proteasomal genes was studied in shoots and roots exposed to different abiotic stresses (cold, drought, and abscisic acid) by quantitative real-time polymerase chain reaction. A significant increase in the relative fold expression of SbPBA1, SbPAA1, SbPBG1, SbPBE1, and SbPAG1 genes under ABA and drought stress provides an insight into its involvement in abiotic stress. No expression was observed for cold stress of these genes indicating their non-involvement. It is believed that additional investigation into the SbPA/SbPB genes would aid in the creation of S. bicolor cultivars that are resistant to climate change
Phylogenomic analysis of 20S proteasome gene family reveals stress-responsive patterns in rapeseed (Brassica napus L.)
The core particle represents the catalytic portions of the 26S proteasomal complex. The genes encoding a- and b-subunits play a crucial role in protecting plants against various environmental stresses by controlling the quality of newly produced proteins. The 20S proteasome gene family has already been reported in model plants such as Arabidopsis and rice; however, they have not been studied in oilseed crops such as rapeseed (Brassica napus L.). In the present study, we identified 20S proteasome genes for a- (PA) and b-subunits (PB) in B. napus through systematically performed gene structure analysis, chromosomal location, conserved motif, phylogenetic relationship, and expression patterns. A total of 82 genes, comprising 35 BnPA and 47 BnPB of the 20S proteasome, were revealed in the B. napus genome. These genes were distributed on all 20 chromosomes of B. napus and most of these genes were duplicated on homoeologous chromosomes. The BnPA (a1-7) and BnPB (b1-7) genes were phylogenetically placed into seven clades. The pattern of expression of all the BnPA and BnPB genes was also studied using RNA-seq datasets under biotic and abiotic stress conditions. Out of 82 BnPA/PB genes, three exhibited high expression under abiotic stresses, whereas two genes were overexpressed in response to biotic stresses at both the seedling and flowering stages. Moreover, an additional eighteen genes were expressed under normal conditions. Overall, the current findings developed our understanding of the organization of the 20S proteasome genes in B. napus and provided specific BnPA/PB genes for further functional research in response to abiotic and biotic stresses
Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic