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

Biogenic factors explain soil carbon in paired urban and natural ecosystems worldwide

12 páginas.- 4 figuras.- 49 referencia.- Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41558-023-01646-z .- Full-text access to a view-only version (Acceso a texto completo de sólo lectura en este enlace) https://rdcu.be/c8vZiUrban greenspaces support multiple nature-based services, many of which depend on the amount of soil carbon (C). Yet, the environmental drivers of soil C and its sensitivity to warming are still poorly understood globally. Here we use soil samples from 56 paired urban greenspaces and natural ecosystems worldwide and combine soil C concentration and size fractionation measures with metagenomics and warming incubations. We show that surface soils in urban and natural ecosystems sustain similar C concentrations that follow comparable negative relationships with temperature. Plant productivity’s contribution to explaining soil C was higher in natural ecosystems, while in urban ecosystems, the soil microbial biomass had the greatest explanatory power. Moreover, the soil microbiome supported a faster C mineralization rate with experimental warming in urban greenspaces compared with natural ecosystems. Consequently, urban management strategies should consider the soil microbiome to maintain soil C and related ecosystem services.This study was supported by a 2019 Leonardo Grant for Researchers and Cultural Creators, BBVA Foundation (URBANFUN), and by BES Grant Agreement No. LRB17\1019 (MUSGONET). M.D-B., P.G-P., J.D. and A.R. acknowledge support from TED2021-130908B-C41/AEI/10.13039/501100011033/ Unión Europea NextGenerationEU/PRTR. M.D.-B. also acknowledges support from the Spanish Ministry of Science and Innovation for the I + D + i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. M.D.-B. was also supported by a project of the Fondo Europeo de Desarrollo Regional (FEDER) and the Consejería de Transformación Económica, Industria, Conocimiento y Universidades of the Junta de Andalucía (FEDER Andalucía 2014-2020 Objetivo temático ‘01 - Refuerzo de la investigación, el desarrollo tecnológico y la innovación’) associated with the research project P20_00879 (ANDABIOMA). D.J.E. was supported by the Hermon Slade Foundation. J.P.V. thanks the Science and Engineering Research Board (SERB) (EEQ/2021/001083, SIR/2022/000626) and the Department of Science and Technology (DST), India (DST/INT/SL/P-31/2021) and Banaras Hindu Univeristy-IoE (6031)-incentive grant for financial assistance for research in plant-microbe interaction and soil microbiome. J.D. and A. Rodríguez acknowledge support from the FCT (2020.03670.CEECIND and SFRH/BDP/108913/2015, respectively), as well as from the MCTES, FSE, UE and the CFE (UIDB/04004/2021) research unit financed by FCT/MCTES through national funds (PIDDAC).Peer reviewe

The future digital work force: Robotic Process Automation (Rpa)

Robotic Process Automation (RPA) is a new wave of the future technologies. Robotic Process Automation is one of the most advanced technologies in the area of computers science, electronic and communications, mechanical engineering, and information technology. It is a combination of both hardware and software, networking and automation for doing things very simple. In this light, the research manuscript investigated the secondary data - which is available on google, academic and research databases. The investigation went for totally 6 months, i.e., 1-1-2018 to 30-6-2018. A very few empirical articles, white papers, blogs and were found RPA and came across to compose this research manuscript. This study is exploratory in nature because of the contemporary phenomenon. The keywords used in searching from the database were Robotic Process Automation, RPA, Robots, Artificial Intelligence, Blue Prism. The study finally discovered that Robots and Robotic Process Automation technologies are becoming compulsory as a part to do business operations in organizations across the globe. Robotic Process Automation can bring immediate value to the core business processes including employee payroll, employee status changes, new hire recruitment, and onboarding, accounts receivable and payable, invoice processing, inventory management, report creation, software installations, data migration, and vendor onboarding etc. to name a few applications. Besides, the Robotic Process Automation has abundant applications including healthcare and pharmaceuticals, financial services, outsourcing, retail, telecom, energy and utilities, real estate and FMCG and many more sectors. To put in the right place of RPA in business operations, their many allied technologies are working at the background level, artificial intelligence, machine learning, deep learning, data analytics, HR analytics, virtual reality (second life), home automation, blockchain technologies, 4D printing etc. Moreover, it covers the content of different start-ups companies and existing companies - their RPA applications used across the world. This manuscript will be a good guideline for the academicians, researchers, students, and practitioners to get an overall idea

The Future Digital Work Force: Robotic Process Automation (RPA)

Abstract The Robotic Process Automation (RPA) is a new wave of the future technologies. Robotic Process Automation is one of the most advanced technologies in the area of computers science, electronic and communications, mechanical engineering and information technology. It is a combination of both hardware and software, networking and automation for doing things very simple. In this light, the research manuscript investigated the secondary data - which is available in google, academic and research databases. The investigation went for totally 6 months, i.e., 1-1-2018 to 30-6-2018. A very few empirical articles, white papers, blogs and were found RPA and came across to compose this research manuscript. This study is exploratory in nature because of the contemporary phenomenon. The keywords used in searching of the database were Robotic Process Automation, RPA, Robots, Artificial Intelligence, Blue Prism. The study finally discovered that Robots and Robotic Process Automation technologies are becoming compulsory as a part to do business operations in the organizations across the globe. Robotic Process Automation can bring immediate value to the core business processes including employee payroll, employee status changes, new hire recruitment and on boarding, accounts receivable and payable, invoice processing, inventory management, report creation, software installations, data migration, and vendor on boarding etc. to name a few applications. Besides, the Robotic Process Automation has abundant applications including healthcare and pharmaceuticals, financial services, outsourcing, retail, telecom, energy and utilities, real estate and FMCG and many more sectors. To put in the right place of RPA in business operations, their many allied technologies are working at the background level, artificial intelligence, machine learning, deep learning, data analytics, HR analytics, virtual reality (second life), home automation, blockchain technologies, 4D printing etc. Moreover, it covers the content of different start-ups companies and existing companies - their RPA applications used across the world. This manuscript will be a good guideline for the academicians, researchers, students, and practitioners to get an overall idea

Biotechnological Interventions in Tomato (<i>Solanum lycopersicum</i>) for Drought Stress Tolerance: Achievements and Future Prospects

Tomato production is severely affected by abiotic stresses (drought, flood, heat, and salt) and causes approximately 70% loss in yield depending on severity and duration of the stress. Drought is the most destructive abiotic stress and tomato is very sensitive to the drought stress, as cultivated tomato lack novel gene(s) for drought stress tolerance. Only 20% of agricultural land worldwide is irrigated, and only 14.51% of that is well-irrigated, while the rest is rain fed. This scenario makes drought very frequent, which restricts the genetically predetermined yield. Primarily, drought disturbs tomato plant physiology by altering plant–water relation and reactive oxygen species (ROS) generation. Many wild tomato species have drought tolerance gene(s); however, their exploitation is very difficult because of high genetic distance and pre- and post-transcriptional barriers for embryo development. To overcome these issues, biotechnological methods, including transgenic technology and CRISPR-Cas, are used to enhance drought tolerance in tomato. Transgenic technology permitted the exploitation of non-host gene/s. On the other hand, CRISPR-Cas9 technology facilitated the editing of host tomato gene(s) for drought stress tolerance. The present review provides updated information on biotechnological intervention in tomato for drought stress management and sustainable agriculture

Overview of the HASOC subtrack at FIRE 2021: Hate speech and offensive content identification in English and Indo-Aryan languages and conversational hate speech

This is an accepted manuscript of a paper published by ACM in the proceedings of FIRE 2021: Forum for Information Retrieval Evaluation on 13/12/2021, available online: https://doi.org/10.1145/3503162.3503176 The accepted manuscript of the publication may differ from the final published version.The HASOC track is dedicated to the evaluation of technology for finding Offensive Language and Hate Speech. HASOC is creating a multilingual data corpus mainly for English and under-resourced languages(Hindi and Marathi). This paper presents one HASOC subtrack with two tasks. In 2021, we organized the classification task for English, Hindi, and Marathi. The first task consists of two classification tasks; Subtask 1A consists of a binary and fine-grained classification into offensive and non-offensive tweets. Subtask 1B asks to classify the tweets into Hate, Profane and offensive. Task 2 consists of identifying tweets given additional context in the form of the preceding conversion. During the shared task, 65 teams have submitted 652 runs. This overview paper briefly presents the task descriptions, the data and the results obtained from the participant's submission.Published versio