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Diatoms are major players in the global carbon cycle, and their metabolism is affected by ocean conditions. Understanding the impact of changing inorganic nutrients in the oceans on diatoms is crucial, given the changes in global carbon dioxide levels. Here, we present a genome-scale metabolic model (iMK1961) for Cylindrotheca closterium, an in silico resource to understand uncharacterized metabolic functions in this ubiquitous diatom. iMK1961 represents the largest diatom metabolic model to date, comprising 1961 open reading frames and 6718 reactions. With iMK1961, we identified the metabolic response signature to cope with drastic changes in growth conditions. Comparing model predictions with Tara Oceans transcriptomics data unraveled C. closteriums metabolism in situ. Unexpectedly, the diatom only grows photoautotrophically in 21% of the sunlit ocean samples, while the majority of the samples indicate a mixotrophic (71%) or, in some cases, even a heterotrophic (8%) lifestyle in the light. Our findings highlight C. closteriums metabolic flexibility and its potential role in global carbon cycling.

The Virtual Special Issue (VSI) entitled "COVID-19 in Environment: Treatment, Infectivity, Monitoring, Estimation (TIME)" mainly brings together the different themes and perspectives related to wastewater epidemiology related to COVID-19. The issue further concentrates on the idea of the very much required scientific studies of the wastewater containing the SARS-CoV RNA; its contagious attributes if any; and the very important possibility of estimation and monitoring of patients based on the wastewater epidemiology. We have brought global perspectives related to the most suitable estimations methods based on SARS-COV-RNA data and development of an approach combining wastewater epidemiology and clinical diagnostic test could facilitate surveillance of public health system for informed decision making for better and effective treatment methods on one platform, thereby facilitating the expansion of the reach of these ideas and their audience. This VSI is going to act as an interface for microbiologists, environmental engineers, data scientists, civil engineers, remote-sensing experts, and modelers to integrate their findings on the aforementioned topics to etch out the probability of relative environmental risks and human health challenges. It has undergone an open call for papers and a rigorous peer-review process, where each submission has been evaluated by a panel of experts. In total, twenty-two articles could pass the test of external referees that represent the ongoing research and development activities in the topical research area of COVID-19 wastewater surveillance., QC 20240905

In aquatic environments, microplastics pose alarming threat to the environment since they actively convey hazardous contaminants and aggregate into biota. Although studies on microplastics in freshwater ecosystems have increased recently, there are still many concerns about the origins, sources, fate, and distribution of MPs. This thorough review includes 167 studies (2017–2024) with an aim to provide knowledge of the type, sources, and detection of microplastics in freshwater ecosystems, along with their consequences on aquatic species and human health. The main sources of microplastic in freshwater ecosystems include improperly disposed plastic trash, industrial raw materials, personal care items, and synthetic fabrics. Factors like retention time, flow rate, and seasonal variations influence their permanence in freshwater (FW) ecosystems, ultimately leading to their transport through river networks. The most hazardous polymers identified are PUR, PAN, PVC, Epoxy resin, and ABS. Previous studies have confirmed their ‘Trojan horse effect’ due to their ability to adorb drugs (e.g., acyclovir, atenolol, sulfamethoxazole, and ibuprofen), heavy metals (As, Cd), pesticides (difenoconazole, buprofezin, imidacloprid), antibiotic-resistant genes and microorganisms. Microplastics carrying above pollutants may possess carcinogenic properties and other health risks, considering their entry into the human body through FW-sourced water and food products. Currently, there is a lack of standardized protocols for the identification, assessment, and quantification of MPs in freshwater ecosystems. The common identification techniques are spectroscopy, Microscopy, mass spectroscopy, and novel methods like staining and AFM-IR spectroscopy. The multifaceted impact of microplastics on FW ecosystems, from contaminant transmission to human health, underscores the intricate interactions within this environmental challenge., QC 20240619

The integration of GitOps and Infrastructure as Code within the context of continuous integration and continuous delivery/deployment (CI/CD) pipelines represents a significant challenge in software and infrastructure deployment, particularly in public cloud environments. This thesis provides a comprehensive analysis and investigates how such integrations in Amazon Web Services can improve deployment efficiency, reliability in software and infrastructure delivery, and security while addressing the gaps in the existing Development and Operations (DevOps) practices. The problem is that, in public cloud platforms, the complexity of deploying infrastructure using automated pipelines often results in a lack of version control, inefficiency or security loopholes. GitOps concepts and Infrastructure as Code principles have facilitated ease of deployment for applications and infrastructure, but there is still room for improvement in understanding their effects when combined with automated pipelines. This gap delays the optimization of best practices in deployment strategies and the full potential of infrastructure deployment processes in the public cloud, making it an essential area for academic research. This thesis utilizes a systematic approach, implementing a controlled GitOps environment using GitLab and Amazon Web Services that integrate GitOps concepts and Infrastructure as Code principles with Development, Security and Operations (DevSecOps) practices. This thesis analyzes the effects of GitOps and Infrastructure as Code on deployment efficiency and reliability through automated pipelines built on GitLab and provides best practices for improving efficiency, reliability, and security. These findings offer significant insights for organizations to refine their software development and infrastructure deployment practices. Furthermore, this thesis provides practitioners with empirical evidence to guide the adoption of GitOps and Infrastructure as Code with automated pipel, Integrationen av GitOps och Infrastructure som kod inom ramen för kontinuerlig integration och kontinuerlig leverans/deployment (CI/CD) pipelines representerar en betydande utmaning i programvaru- och infrastrukturdistribution, särskilt i offentliga molnmiljöer. Den här avhandlingen ger en omfattande analys och undersöker hur sådana integrationer i Amazon Web Services kan förbättra implementeringseffektiviteten, tillförlitligheten i leverans av programvara och infrastruktur och säkerhet samtidigt som man åtgärdar luckorna i de befintliga utvecklings- och driftrutinerna (DevOps). Problemet är att i offentliga molnplattformar resulterar komplexiteten i att distribuera infrastruktur med hjälp av automatiserade pipelines ofta i brist på versionskontroll, ineffektivitet eller kryphål i säkerheten. GitOps-koncept och Infrastructure as Code-principer har underlättat installationen för applikationer och infrastruktur, men det finns fortfarande utrymme för förbättringar när det gäller att förstå deras effekter när de kombineras med automatiserade pipelines. Denna lucka fördröjer optimeringen av bästa praxis i distributionsstrategier och den fulla potentialen av infrastrukturimplementeringsprocesser i det offentliga molnet, vilket gör det till ett viktigt område för akademisk forskning. Detta examensarbete använder ett systematiskt tillvägagångssätt och implementerar en kontrollerad GitOps-miljö med hjälp av GitLab och Amazon Web Services som integrerar GitOps-koncept och infrastruktur som kodprinciper med utveckling, säkerhet och drift (DevSecOps) praxis. Den här avhandlingen analyserar effekterna av GitOps och Infrastructure som kod på implementeringseffektivitet och tillförlitlighet genom automatiserade pipelines byggda på GitLab och ger bästa praxis för att förbättra effektivitet, tillförlitlighet och säkerhet. Dessa resultat ger betydande insikter för organisationer att förfina sina metoder för programvaruutveckling och infrastrukturinstallation. Dessutom förser denna av

The integration of GitOps and Infrastructure as Code within the context of continuous integration and continuous delivery/deployment (CI/CD) pipelines represents a significant challenge in software and infrastructure deployment, particularly in public cloud environments. This thesis provides a comprehensive analysis and investigates how such integrations in Amazon Web Services can improve deployment efficiency, reliability in software and infrastructure delivery, and security while addressing the gaps in the existing Development and Operations (DevOps) practices. The problem is that, in public cloud platforms, the complexity of deploying infrastructure using automated pipelines often results in a lack of version control, inefficiency or security loopholes. GitOps concepts and Infrastructure as Code principles have facilitated ease of deployment for applications and infrastructure, but there is still room for improvement in understanding their effects when combined with automated pipelines. This gap delays the optimization of best practices in deployment strategies and the full potential of infrastructure deployment processes in the public cloud, making it an essential area for academic research. This thesis utilizes a systematic approach, implementing a controlled GitOps environment using GitLab and Amazon Web Services that integrate GitOps concepts and Infrastructure as Code principles with Development, Security and Operations (DevSecOps) practices. This thesis analyzes the effects of GitOps and Infrastructure as Code on deployment efficiency and reliability through automated pipelines built on GitLab and provides best practices for improving efficiency, reliability, and security. These findings offer significant insights for organizations to refine their software development and infrastructure deployment practices. Furthermore, this thesis provides practitioners with empirical evidence to guide the adoption of GitOps and Infrastructure as Code with automated pipel, Integrationen av GitOps och Infrastructure som kod inom ramen för kontinuerlig integration och kontinuerlig leverans/deployment (CI/CD) pipelines representerar en betydande utmaning i programvaru- och infrastrukturdistribution, särskilt i offentliga molnmiljöer. Den här avhandlingen ger en omfattande analys och undersöker hur sådana integrationer i Amazon Web Services kan förbättra implementeringseffektiviteten, tillförlitligheten i leverans av programvara och infrastruktur och säkerhet samtidigt som man åtgärdar luckorna i de befintliga utvecklings- och driftrutinerna (DevOps). Problemet är att i offentliga molnplattformar resulterar komplexiteten i att distribuera infrastruktur med hjälp av automatiserade pipelines ofta i brist på versionskontroll, ineffektivitet eller kryphål i säkerheten. GitOps-koncept och Infrastructure as Code-principer har underlättat installationen för applikationer och infrastruktur, men det finns fortfarande utrymme för förbättringar när det gäller att förstå deras effekter när de kombineras med automatiserade pipelines. Denna lucka fördröjer optimeringen av bästa praxis i distributionsstrategier och den fulla potentialen av infrastrukturimplementeringsprocesser i det offentliga molnet, vilket gör det till ett viktigt område för akademisk forskning. Detta examensarbete använder ett systematiskt tillvägagångssätt och implementerar en kontrollerad GitOps-miljö med hjälp av GitLab och Amazon Web Services som integrerar GitOps-koncept och infrastruktur som kodprinciper med utveckling, säkerhet och drift (DevSecOps) praxis. Den här avhandlingen analyserar effekterna av GitOps och Infrastructure som kod på implementeringseffektivitet och tillförlitlighet genom automatiserade pipelines byggda på GitLab och ger bästa praxis för att förbättra effektivitet, tillförlitlighet och säkerhet. Dessa resultat ger betydande insikter för organisationer att förfina sina metoder för programvaruutveckling och infrastrukturinstallation. Dessutom förser denna av

The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and vari-ants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.

The current experiment was conducted during 2020-21 at the Microbiology Laboratory, CCS Haryana Agricultural University, Regional Research Station Bawal to examine the impact of bio-inoculants and chemicals seed priming on bael seed germination. There were 15 seed priming treatments i.e., control, IBA @ 100 ppm and 50 ppm for 24 hours, NAA @ 50 and 100 ppm for 24 hours, GA3 @ 50 and 100 ppm for 24 hours, KNO3 @ 1 per cent for 24 hours, Azotobacter (HT 54) for 30 minutes, Trichoderma viride for 30 minutes, Rhizobium (CK 16) for 30 minutes, PSB (P 36) for 30 minutes, hot water for 30 minutes, nitric acid for 3 minutes, sulphuric acid for 3 minutes. Among different seed priming treatments, shortest germination time (12.7 days) was recorded with sulphuric acid for 3 minutes in agar medium at 28 ⁰C under laboratory conditions and the highest germination percentage (83.3 %), dry weight per seedling (153.2 mg), seedling length (12.2 cm) and vigour index I (976) and II (12256) were observed when bael seeds primed with GA3 @ 100 ppm for 24 hours under laboratory conditions.

The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and vari-ants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.

Multi Agent Path Finding (MAPF) seeks the optimal set of paths for multiple agents from respective start to goal locations such that no paths conflict. We address the MAPF problem for a fleet of hybrid-fuel unmanned aerial vehicles which are subject to location-dependent noise restrictions. We solve this problem by searching a constraint tree for which the subproblem at each node is a set of shortest path problems subject to the noise and fuel constraints and conflict zone avoidance. A labeling algorithm is presented to solve this subproblem, including the conflict zones which are treated as dynamic obstacles. We present the experimental results of the algorithms for various graph sizes and number of agents., Comment: 6 pages, 7 figures

Leader election is one of the fundamental and well-studied problems in distributed computing. In this paper, we initiate the study of leader election using mobile agents. Suppose $n$ agents are positioned initially arbitrarily on the nodes of an arbitrary, anonymous, $n$-node, $m$-edge graph $G$. The agents relocate themselves autonomously on the nodes of $G$ and elect an agent as a leader such that the leader agent knows it is a leader and the other agents know they are not leaders. The objective is to minimize time and memory requirements. Following the literature, we consider the synchronous setting in which each agent performs its operations synchronously with others and hence the time complexity can be measured in rounds. The quest in this paper is to provide solutions without agents knowing any graph parameter, such as $n$, a priori. We first establish that, without agents knowing any graph parameter a priori, there exists a deterministic algorithm to elect an agent as a leader in $O(m)$ rounds with $O(n\log n)$ bits at each agent. Using this leader election result, we develop a deterministic algorithm for agents to construct a minimum spanning tree of $G$ in $O(m+n\log n)$ rounds using $O(n \log n)$ bits memory at each agent, without agents knowing any graph parameter a priori. Finally, using the same leader election result, we provide improved time/memory results for other fundamental distributed graph problems, namely, gathering, maximal independent set, and minimal dominating sets, removing the assumptions on agents knowing graph parameters a priori., Comment: 25 pages

The introduction and study of dispersing mobile robots across the nodes of an anonymous graph have recently gained traction and have been explored within various graph classes and settings. While optimal dispersion solution was established for {\em oriented} grids [Kshemkalyani et al., WALCOM 2020], a significant unresolved question pertains to whether achieving optimal dispersion is feasible on an {\em unoriented} grid. This paper investigates the dispersion problem on unoriented grids, considering both non-faulty and faulty robots. The challenge posed by unoriented grids lies in the absence of a clear sense of direction for a single robot moving between nodes, as opposed to the straightforward navigation of oriented grids. We present three deterministic algorithms tailored to our robot model. The first and second algorithms deal with the dispersion of faulty and non-faulty robots, ensuring both time and memory optimization in oriented and unoriented grids, respectively. Faulty robots that are prone to crashing at any time, causing permanent failure. In both settings, we achieve dispersion in $O(\sqrt{n})$ rounds while requiring $O(\log n)$ bits of memory per robot. The third algorithm tackles faulty robots prone to crash faults in an unoriented grid. In this scenario, our algorithm operates within $O(\sqrt{n} \log n)$ time and uses $O(\sqrt{n} \log n)$ bits of memory per robot. The robots need to know the value of $n$ for termination.

Background-oriented schlieren (BOS) is a powerful technique for flow visualization. Nevertheless, the widespread dissemination of BOS is impeded by its dependence on scientific cameras, computing hardware, and dedicated analysis software. In this work, we aim to democratize BOS by providing a smartphone based scientific tool called "Pocket Schlieren". Pocket Schlieren enables users to directly capture, process, and visualize flow phenomena on their smartphones. The underlying algorithm incorporates consecutive frame subtraction (CFS) and optical flow (OF) techniques to compute the density gradients inside a flow. It performs on both engineered and natural background patterns. Using Pocket Schlieren, we successfully visualized the flow produced from a burning candle flame, butane lighter, hot soldering iron, room heater, water immersion heating rod, and a large outdoor butane flame. Pocket Schlieren promises to serve as a frugal yet potent instrument for scientific and educational purposes. We have made it publicly available at doi: 10.5281/zenodo.10949271., Comment: 24 pages, 6 figures, 4 Supplementary figures

Clostridium acetobutylicum is an anaerobic bacterium that is extensively studied for its ability to produce butanol. Over the past two decades, various genetic and metabolic engineering approaches have been used to investigate the physiology and regulation system of the biphasic metabolic pathway in this organism. However, there has been a relatively limited amount of research focused on the fermentation dynamics of C. acetobutylicum. In this study, we developed a pH-based phenomenological model to predict the fermentative production of butanol from glucose using C. acetobutylicum in a batch system. The model describes the relationship between the dynamics of growth and the production of desired metabolites and the extracellular pH of the media. Our model was found to be successful in predicting the fermentation dynamics of C. acetobutylicum, and the simulations were validated using experimental fermentation data. Furthermore, the proposed model has the potential to be extended to represent the dynamics of butanol production in other fermentation systems, such as fed-batch or continuous fermentation using single and multi-sugars.

Monkeypox disease (MPXD), a viral disease caused by the monkeypox virus (MPXV), is an emerging zoonotic disease endemic in some countries of Central and Western Africa but seldom reported outside the affected region. Since May 2022, MPXD has been reported at least in 74 countries globally, prompting the World Health Organization to declare the MPXD outbreak a Public Health Emergency of International Concern. As of July 24, 2022; 92 % (68/74) of the countries with reported MPXD cases had no historical MPXD case reports. From the One Health perspective, the spread of MPXV in the environment poses a risk not only to humans but also to small mammals and may, ultimately, spread to potent novel host populations. Wastewater-based surveillance (WBS) has been extensively utilized to monitor communicable diseases, particularly during the ongoing COVID-19 pandemic. It helped in monitoring infectious disease case-loads as well as specific viral variants circulating in communities. The detection of MPXV DNA in lesion materials (e.g. skin, vesicle fluid, crusts), skin rashes, and various body fluids, including respiratory and nasal secretions, saliva, urine, feces, and semen of infected individuals, supports the possibility of using WBS as an early proxy for the detection of MPXV infections. WBS of MPXV DNA can be used to monitor MPXV activity/trends in sewerage network areas even before detecting laboratory-confirmed clinical cases within a community. However, several factors affect the detection of MPXV in wastewater including, but not limited to, routes and duration time of virus shedding by infected individuals, infection rates in the relevant affected population, environmental persistence, the processes and analytical sensitivity of the used methods. Further research is needed to identify the key factors that impact the detection of MPXV biomarkers in wastewater and improve the utility of WBS of MPXV as an early warning and monitoring tool for safeguarding human health. In t, QC 20221116

Gamma-ray bursts (GRBs) can be classified with their linearly dependent parameters alongside the standard $T_{90}$ distribution. The Generalized linear mixture model(GLM) identifies the number of linear dependencies in a two-parameter space. Classically, GRBs are classified into two classes by the presence of bimodality in the histogram of T$_{90}$. However, additional classes and sub-classes of GRBs are fascinating topics to explore. In this work, we investigate the GRBs classes in the $ T_{90} {-}T_{50}$ plane using the Generalized Linear Models(GLM) for Fermi GBM and BATSE catalogs. This study shows five linear features for the Fermi GBM catalog and four linear features for the BATSE catalog, directing towards the possibility of more than two GRB classes., Comment: 8 figures, 1 table

Advancements in analytical techniques have resulted in much progress in understanding co-occurrence of environmental con-taminants. We focused on investigating the global pattern of arsenic (As) co-occurrence with inorganic and emerging con-taminants and then explained the governing factors driving the situation. Major co-occurring inorganic contaminants were found in three sets: i) U, F, Fe, Mn, Pb, & Zn; ii) Al, Mo, Cd, Sb, Br, I, and Se; and iii) Ag, Au, Cr, Cu, Hg, Th, V, Ga, and Ba. Co-occurrences were majorly governed by weathering, redox conditions, recharge/pumping, and surface leaching. Several places around the world started to exhibit As presence with contaminants of emerging concerns like pesticides, per-and polyfluoroalkyl sub-stances (PFAS), endocrine disrupting chemicals (EDCs), and others, that needs to be explored further at fundamentally deeper levels. This is probably one of the first attempts to correlate As co -occurrences with contaminants of emerging concern., QC 20230818

Avirulent halotolerant plant growth-promoting rhizobacteria (HPGPR) located on the roots' periphery can reduce abiotic stressors (such as salinity and drought), enhance plant productivity. Salinity poses a significant challenge for growing agricultural products, like rice, in the coastal regions. It is crucial to enhance production because of limited arable land and the high growth rate of the population. This study targeted to identify HPGPR from legume root nodules and assessed their effects on rice plants experiencing salt stress in coastal regions of Bangladesh. Based on the culture morphology, biochemical, salt, pH, and temperature tolerance traits, sixteen bacteria were isolated from the root nodules of leguminous plants (Common bean, Yardlong bean, Dhaincha, and Shameplant). All the bacterial strains can tolerate 3 % salt concentration, and capable to survive at the highest 45 °C temperature and pH 11 (without isolate 1). Three preeminent bacteria, Agrobacterium tumefaciens (B1), Bacillus subtilis (B2), and Lysinibacillus fusiformis (B3) were specified through morpho-biochemical and molecular (16S rRNA gene sequence) exploration for inoculation. To assess the plant growth-promoting activities, germination tests are applied where bacterial inoculation increased germination in saline and non-saline conditions. Control group (C) showed 89.47 % and bacterial treated groups (C + B1, C + B2, and C + B3) 95 %, 90 %, and 75 % germination after 2 days of inoculation. In (1 % NaCl) saline condition control group revealed 40 % whereas three groups with bacteria showed 60 %, 40 %, and 70 % germination after 3 days, which increased 70 %, 90 %, 85 %, and 95 % respectively after 4 days of inoculation. The HPGPR significantly improved plant development metrics such as root length, shoot length, fresh and arid biomass yield, chlorophyll content, etc. Our results suggest that the salt-resistant bacteria (Halotolerant) have a great potential role in recuperating plant growth an, QC 20230707

Biochar, a promising carbon-rich and carbon-negative material, can control water pollution, harness the synergy of sustainable development goals, and achieve circular economy. This study examined the performance feasibility of treating fluoride-contaminated surface and groundwater using raw and modified biochar synthesized from agricultural waste rice husk as problem-fixing renewable carbon-neutral material. Physicochemical characterizations of raw/modified biochars were investigated using FESEM-EDAX, FTIR, XRD, BET, CHSN, VSM, pHpzc, Zeta potential, and particle size analysis were analyzed to identify the surface morphology, functional groups, structural, and electrokinetic behavior. In fluoride (Fˉ) cycling, performance feasibility was tested at various governing factors, contact time (0–120 min), initial Fˉ levels (10–50 mg L−1), biochar dose (0.1–0.5 g L−1), pH (2–9), salt strengths (0–50 mM), temperatures (301–328 K), and various co-occurring ions. Results revealed that activated magnetic biochar (AMB) possessed higher adsorption capacity than raw biochar (RB) and activated biochar (AB) at pH 7. The results indicated that maximum Fˉ removal (98.13%) was achieved using AMB at pH 7 for 10 mg L−1. Electrostatic attraction, ion exchange, pore fillings, and surface complexation govern Fˉ removal mechanisms. Pseudo-second-order and Freundlich were the best fit kinetic and isotherm for Fˉ sorption, respectively. Increased biochar dose drives an increase in active sites due to Fˉ level gradient and mass transfer between biochar-fluoride interactions, which reported maximum mass transfer for AMB than RB and AB. Fluoride adsorption using AMB could be described through chemisorption processes at room temperature (301 K), though endothermic sorption follows the physisorption process. Fluoride removal efficiency reduced, from 67.70% to 53.23%, with increased salt concentrations from 0 to 50 mM NaCl solutions, respectively, due to increased hydrodynamic diameter. Biochar was, QC 20230706

Dengue virus (DENV) is an enveloped, single-stranded RNA virus, a member of the Flaviviridae family (which causes Dengue fever), and an arthropod-transmitted human viral infection. Bangladesh is well known for having some of Asia’s most vulnerable Dengue outbreaks, with climate change, its location, and it’s dense population serving as the main contributors. For speculation about DENV outbreak characteristics, it is crucial to determine how meteorological factors correlate with the number of cases. This study used five time series models to observe the trend and forecast Dengue cases. Current data-based research has also applied four statistical models to test the relationship between Dengue-positive cases and meteorological parameters. Datasets were used from NASA for meteorological parameters, and daily DENV cases were obtained from the Directorate General of Health Service (DGHS) open-access websites. During the study period, the mean of DENV cases was 882.26 ± 3993.18, ranging between a minimum of 0 to a maximum of 52,636 daily confirmed cases. The Spearman’s rank correlation coefficient between climatic variables and Dengue incidence indicated that no substantial relationship exists between daily Dengue cases and wind speed, temperature, and surface pressure (Spearman’s rho; r = −0.007, p > 0.05; r = 0.085, p > 0.05; and r = −0.086, p > 0.05, respectively). Still, a significant relationship exists between daily Dengue cases and dew point, relative humidity, and rainfall (r = 0.158, p < 0.05; r = 0.175, p < 0.05; and r = 0.138, p < 0.05, respectively). Using the ARIMAX and GA models, the relationship for Dengue cases with wind speed is −666.50 [95% CI: −1711.86 to 378.86] and −953.05 [−2403.46 to 497.36], respectively. A similar negative relation between Dengue cases and wind speed was also determined in the GLM model (IRR = 0.98). Dew point and surface pressure also represented a negative correlation in both ARIMAX and GA models, respectively, QC 20230705

Fluoride (F-) contamination in water is a global health concern, threatening the well-being of millions. This study investigated the role of ZnCl2/FeCl3-rice husk-modified biochar (Zn-BC and Zn/Fe-BC) in treating F--contaminated surface and groundwater under the influence of varying solution chemistry, co-existing ions, and biochar-amended through column transport experiments. Modified biochar showed maximum F- adsorp-tion, 99.01% and 91.90% using Zn/Fe-BC and Zn-BC, respectively, than 85.87% using raw biochar (R-BC). Raw/modified biochars were characterized with FESEM-EDAX, FTIR, XRD, particle size, surface area, electro-kinetic potential, and point of zero charge analyses. Langmuir and pseudo-second-order kinetic could explain that F--biochar interactions are dominated by chemisorption at ambient temperature while physisorption at higher temperatures. The influence of salt concentrations and co-occurring ions reduced F- sorption using Zn/Fe-BC. Increased salt strengths led to reduced electrophoretic mobility of biochar particles, i.e., biochar-biochar particles attract each other and increase the hydrodynamic diameter, which ultimately reduces the active sites on biochar for F- adsorption. Co-transport and deposition of biochar and F- in saturated porous media revealed lower mobility of biochar, and maximum F- adsorption was observed at 10 mM salt strength. Biochar transport is governed by electrostatic interactions, whereas F- transport mainly occurs through chemisorption. In rural areas, hand pumps and tube wells are generally used as source of potable water for drinking and cooking purposes; thus, biochar-mediated sand columns can be utilized for defluoridation. Thus, Zn/Fe-BC can be utilized as a potential bio-adsorbent for F--contaminated natural surface and groundwater with optimum preparation and treatment costs., QC 20230412

Presently, owing to the rapid development of industrialization and urbanization activities, a huge quantity of wastewater is generated that contain toxic chemical and heavy metals, imposing higher environmental jeopardies and affecting the life of living well-being and the economy of the counties, if not treated appropriately. Subsequently, the advancement in sustainable cost-effective wastewater treatment technology has attracted more attention from policymakers, legislators, and scientific communities. Therefore, the current review intends to highlight the recent development and applications of biochars and/or green nanoparticles (NPs) produced from agricultural waste via green routes in removing the refractory pollutants from water and wastewater. This review also highlights the contemporary application and mechanism of biochar-supported advanced oxidation processes (AOPs) for the removal of organic pollutants in water and wastewater. Although, the fabrication and application of agriculture waste-derived biochar and NPs are considered a greener approach, nevertheless, before scaling up production and application, its toxicological and life-cycle challenges must be taken into account. Furthermore, future efforts should be carried out towards process engineering to enhance the performance of green catalysts to improve the economy of the process. © 2022 Elsevier B.V.

Presently, owing to the rapid development of industrialization and urbanization activities, a huge quantity of wastewater is generated that contain toxic chemical and heavy metals, imposing higher environmental jeopardies and affecting the life of living well-being and the economy of the counties, if not treated appropriately. Subsequently, the advancement in sustainable cost-effective wastewater treatment technology has attracted more attention from policymakers, legislators, and scientific communities. Therefore, the current review intends to highlight the recent development and applications of biochars and/or green nanoparticles (NPs) produced from agricultural waste via green routes in removing the refractory pollutants from water and wastewater. This review also highlights the contemporary application and mechanism of biochar-supported advanced oxidation processes (AOPs) for the removal of organic pollutants in water and wastewater. Although, the fabrication and application of agriculture waste-derived biochar and NPs are considered a greener approach, nevertheless, before scaling up production and application, its toxicological and life-cycle challenges must be taken into account. Furthermore, future efforts should be carried out towards process engineering to enhance the performance of green catalysts to improve the economy of the process. © 2022 Elsevier B.V.

Presently, owing to the rapid development of industrialization and urbanization activities, a huge quantity of wastewater is generated that contain toxic chemical and heavy metals, imposing higher environmental jeopardies and affecting the life of living well-being and the economy of the counties, if not treated appropriately. Subsequently, the advancement in sustainable cost-effective wastewater treatment technology has attracted more attention from policymakers, legislators, and scientific communities. Therefore, the current review intends to highlight the recent development and applications of biochars and/or green nanoparticles (NPs) produced from agricultural waste via green routes in removing the refractory pollutants from water and wastewater. This review also highlights the contemporary application and mechanism of biochar-supported advanced oxidation processes (AOPs) for the removal of organic pollutants in water and wastewater. Although, the fabrication and application of agriculture waste-derived biochar and NPs are considered a greener approach, nevertheless, before scaling up production and application, its toxicological and life-cycle challenges must be taken into account. Furthermore, future efforts should be carried out towards process engineering to enhance the performance of green catalysts to improve the economy of the process. © 2022 Elsevier B.V.

Presently, owing to the rapid development of industrialization and urbanization activities, a huge quantity of wastewater is generated that contain toxic chemical and heavy metals, imposing higher environmental jeopardies and affecting the life of living well-being and the economy of the counties, if not treated appropriately. Subsequently, the advancement in sustainable cost-effective wastewater treatment technology has attracted more attention from policymakers, legislators, and scientific communities. Therefore, the current review intends to highlight the recent development and applications of biochars and/or green nanoparticles (NPs) produced from agricultural waste via green routes in removing the refractory pollutants from water and wastewater. This review also highlights the contemporary application and mechanism of biochar-supported advanced oxidation processes (AOPs) for the removal of organic pollutants in water and wastewater. Although, the fabrication and application of agriculture waste-derived biochar and NPs are considered a greener approach, nevertheless, before scaling up production and application, its toxicological and life-cycle challenges must be taken into account. Furthermore, future efforts should be carried out towards process engineering to enhance the performance of green catalysts to improve the economy of the process. © 2022 Elsevier B.V.

Presently, owing to the rapid development of industrialization and urbanization activities, a huge quantity of wastewater is generated that contain toxic chemical and heavy metals, imposing higher environmental jeopardies and affecting the life of living well-being and the economy of the counties, if not treated appropriately. Subsequently, the advancement in sustainable cost-effective wastewater treatment technology has attracted more attention from policymakers, legislators, and scientific communities. Therefore, the current review intends to highlight the recent development and applications of biochars and/or green nanoparticles (NPs) produced from agricultural waste via green routes in removing the refractory pollutants from water and wastewater. This review also highlights the contemporary application and mechanism of biochar-supported advanced oxidation processes (AOPs) for the removal of organic pollutants in water and wastewater. Although, the fabrication and application of agriculture waste-derived biochar and NPs are considered a greener approach, nevertheless, before scaling up production and application, its toxicological and life-cycle challenges must be taken into account. Furthermore, future efforts should be carried out towards process engineering to enhance the performance of green catalysts to improve the economy of the process. © 2022 Elsevier B.V.

Biofortification is a global-scale agricultural approach that can improve human nutrition. Agronomic biofortification is viewed as a quick-fix and supplemental approach. Agronomic biofortification, especially foliar application, is highly effective for zinc and iron. A field experiment on agronomic biofortification of zinc and iron micronutrients in mango cv. Kesar was carried out in 2016-2017 at the Regional Horticultural Research Station, ASPEE College of Horticulture and Forestry, Navsari Agricultural University, Navsari (Gujarat). The experiment was arranged in a completely randomized design (CRD) with three replications containing 9 treatments. The results show that foliar application of ZnSO4 and FeSO4 (0.5% each) resulted in higher N (48.73 mg/100 g) and K (94.17 mg/100 g) in the pulp and P (0.056%) in the peel of mango. The iron (Fe) and zinc (Zn) contents in pulp and peel were highest in treatment T9 (0.50% FeSO4 + 0.50% ZnSO4), which was on par with those in treatment T8 (0.50% FeSO4 + 0.25% ZnSO4).

Experimental and theoretical methods, additional STM images, and calculated results.

The development of functional organic molecules requires structures of increasing size and complexity, which are typically obtained by the covalent coupling of smaller building blocks. Herein, with the aid of high-resolution scanning tunneling microscopy/spectroscopy and density functional theory, the coupling of a sterically demanded pentacene derivative on Au(111) into fused dimers connected by non-benzenoid rings was studied. The diradical character of the products was tuned according to the coupling section. In particular, the antiaromaticity of cyclobutadiene as the coupling motif and its position within the structure play a decisive role in shifting the natural orbital occupancies toward a stronger diradical electronic character. Understanding these structure–property relations is desirable not only for fundamental reasons but also for designing new complex and functional molecular structures.

We report the orbital decay rate of the high mass X-ray binary GX 301$-$2 from an analysis of its long-term X-ray light curves and pulsed flux histories from CGRO/BATSE, RXTE/ASM, Swift/BAT, Fermi/GBM and MAXI by timing the pre-periastron flares over a span of almost 30 years. The time of arrival of the pre-periastron flares exhibits an energy dependence (hard lag) and the orbital period decay was estimated after correcting for it. This method of orbital decay estimation is unaffected by the fluctuations in the spin rate of the X-ray pulsar associated with variations in the mass accretion rate. The resulting $\dot P_\textrm{orb}$ $=-(1.98\pm0.28)\times10^{-6}$ s s$^{-1}$ indicates a rapid evolution timescale of $|P_\textrm{orb}/\dot P_\textrm{orb}|\sim 0.6\times10^{5}$ yr, making it the high mass X-ray binary with the fastest orbital decay. Our estimate of $\dot P_\mathrm{orb}$ is off by a factor of $\sim2$ from the previously reported value of $-(3.7\pm0.5)\times10^{-6}$ s s$^{-1}$ estimated from pulsar TOA analysis. We discuss various possible mechanisms that could drive this rapid orbital decay and also suggest that GX 301$-$2 is a prospective Thorne-\.{Z}ytkow candidate., Comment: 11 pages, 6 figures, Accepted for publication in Monthly Notices of the Royal Astronomical Society

Irrigation has a major role to play in the productivity of winter maize. Precise information about the quantity and quality of irrigation water is the key for higher productivity of winter maize. In the present study attempt has been made to asses the impact of different depth of irrigation water on crop yield and biomass of winter maize using FAO-Aquacrop Model. In the first case crop yield and biomass was simulated for irrigation water depth varied from 20 mm to 80 mm, keeping the irrigation water quality constant. Similarly, in another case the optimum irrigation depth was kept constant and irrigation water quality varied from 1 to 10 ds/m. The simulated crop yield and biomass increases up to 40 cm depth of irrigation water application for all three seasons. When a similar comparison was made for 30 cm depth of irrigation water application the simulated yield reduction was only 0.79%, 2.2% and 2.4 % for the year 2016-17, 2017-18 and 2018-19 respectively. The analysis suggested that this yield reduction can easily be compromised for saving 10 cm of irrigation water. This study indicated that 30 cm depth of irrigation water is optimum for Winter maize in BurhiGandak river basin of North Bihar In case of deficit irrigation of 20 cm depth of irrigation water application the simulated yield reduced by 14.4 %, 25.4 % and 11.4 % for the year 2016-17, 2017-18 and 2018-19 respectively. Assessment of response of different quality irrigation water on simulated crop yield and biomass of winter maize using FAO-Aquacrop model suggests that simulated yield was found maximum with 1 ds/m. The reduction in simulated yield with 10 ds/m water quality was observed maximum with a value of 41.3 %, 44.4 % and 38.4 % respectively for the year 2016-17, 2017-18 and 2018-19. FAO-Aquacrop model can be used as an important tool for efficient planning of irrigation water under diminishing water supply and deteriorating water quality.

The COVID-19 (coronavirus disease 2019) pandemic's steady condition coupled with predominance of emerging contaminants in the environment and its synergistic implications in recent times has stoked interest in combating medical emergencies in this dynamic environment. In this context, high concentrations of pharmaceutical and personal care products (PPCPs), microplastics (MPs), antimicrobial resistance (AMR), and soaring coinfecting microbes, tied with potential endocrine disruptive (ED) are critical environmental concerns that requires a detailed documentation and analysis. During the pandemic, the identification, enumeration, and assessment of potential hazards of PPCPs and MPs and (used as anti-COVID-19 agents/applications) in aquatic habitats have been attempted globally. Albeit receding threats in the magnitude of COVID-19 infections, both these pollutants have still posed serious consequences to aquatic ecosystems and the very health and hygiene of the population in the vicinity. The surge in the contaminants post-COVID also renders them to be potent vectors to harbor and amplify AMR. Pertinently, the present work attempts to critically review such instances to understand the underlying mechanism, interactions swaying the current health of our environment during this post-COVID-19 era. During this juncture, although prevention of diseases, patient care, and self-hygiene have taken precedence, nevertheless antimicrobial stewardship (AMS) efforts have been overlooked. Unnecessary usage of PPCPs and plastics during the pandemic has resulted in increased emerging contaminants (i.e., active pharmaceutical ingredients and MPs) in various environmental matrices. It was also noticed that among COVID-19 patients, while the bacterial co-infection prevalence was 0.2-51%, the fungi, viral, protozoan and helminth were 0.3-49, 1-22, 2-15, 0.4-15% respectively, rendering them resistant to residual PPCPs. There are inevitable chances of ED effects from PPCPs and MPs applied p

In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1-2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions.

Central Pattern Generators (CPGs) form the neural basis of the observed rhythmic behaviors for locomotion in legged animals. The CPG dynamics organized into networks allow the emergence of complex locomotor behaviors. In this work, we take this inspiration for developing walking behaviors in multi-legged robots. We present novel DeepCPG policies that embed CPGs as a layer in a larger neural network and facilitate end-to-end learning of locomotion behaviors in deep reinforcement learning (DRL) setup. We demonstrate the effectiveness of this approach on physics engine-based insectoid robots. We show that, compared to traditional approaches, DeepCPG policies allow sample-efficient end-to-end learning of effective locomotion strategies even in the case of high-dimensional sensor spaces (vision). We scale the DeepCPG policies using a modular robot configuration and multi-agent DRL. Our results suggest that gradual complexification with embedded priors of these policies in a modular fashion could achieve non-trivial sensor and motor integration on a robot platform. These results also indicate the efficacy of bootstrapping more complex intelligent systems from simpler ones based on biological principles. Finally, we present the experimental results for a proof-of-concept insectoid robot system for which DeepCPG learned policies initially using the simulation engine and these were afterwards transferred to real-world robots without any additional fine-tuning., Comment: Preprint of paper accepted for publication in IEEE Transaction On Cognitive and Developmental Systems

In this paper, we investigate the leader election problem in diameter-two networks. Recently, Chatterjee et al. [DC 2020] studied the leader election in diameter-two networks. They presented a $O(\log n)$-round deterministic {implicit} leader election algorithm which incurs optimal $O(n\log n)$ messages, but a drawback of their algorithm is that it requires knowledge of $n$. An important question -- whether it is possible to remove the assumption on the knowledge of $n$ was left open in their paper. Another interesting open question raised in their paper is whether {\em explicit} leader election can be solved in $\tilde{O}(n)$ messages deterministically. In this paper, we give an affirmative answer to them. Further, we solve the {\em broadcast problem}, another fundamental problem in distributed computing, deterministically in diameter-two networks with $\tilde{O}(n)$ messages and $\tilde{O}(1)$ rounds without the knowledge of $n$. In fact, we address all the open questions raised by Chatterjee et al. for the deterministic leader election problem in diameter-two networks. To the best of our knowledge, this is the first $\tilde{O}(n)$ deterministic result for the explicit leader election in the diameter-two networks, that too without the knowledge of $n$., Comment: arXiv admin note: text overlap with arXiv:1809.00273 by other authors

Medical wastes include all solid and liquid wastes that are produced during the treatment, diagnosis, and immunisation of animals and humans. A significant proportion of medical waste is infectious, hazardous, radioactive, and contains potentially toxic elements (PTEs) (i.e., heavy metal (loids)). PTEs, including arsenic (As), cadmium (Cd), lead (Pb) and mercury (Hg), are mostly present in plastic, syringes, rubber, adhesive plaster, battery wastes of medical facilities in elemental form, as well as oxides, chlorides, and sulfates. Incineration and sterilisation are the most common technologies adopted for the safe management and disposal of medical wastes, which are primarily aimed at eliminating deadly pathogens. The ash materials derived from the incineration of hazardous medical wastes are generally disposed of in landfills after the solidification/stabilisation (S/S) process. In contrast, the ash materials derived from nonhazardous wastes are applied to the soil as a source of nutrients and soil amendment. The release of PTEs from medical waste ash material from landfill sites and soil application can result in ecotoxicity. The present study is a review paper that aims to critically review the dynamisms of PTEs in various environmental media after medical waste disposal, the environmental and health implications of their poor management, and the common misconceptions regarding medical waste.

We are considering the geometric amoebot model where a set of $n$ amoebots is placed on the triangular grid. An amoebot is able to send information to its neighbors, and to move via expansions and contractions. Since amoebots and information can only travel node by node, most problems have a natural lower bound of $\Omega(D)$ where $D$ denotes the diameter of the structure. Inspired by the nervous and muscular system, Feldmann et al. have proposed the reconfigurable circuit extension and the joint movement extension of the amoebot model with the goal of breaking this lower bound. In the joint movement extension, the way amoebots move is altered. Amoebots become able to push and pull other amoebots. Feldmann et al. demonstrated the power of joint movements by transforming a line of amoebots into a rhombus within $O(\log n)$ rounds. However, they left the details of the extension open. The goal of this paper is therefore to formalize and extend the joint movement extension. In order to provide a proof of concept for the extension, we consider two fundamental problems of modular robot systems: shape formation and locomotion. We approach these problems by defining meta-modules of rhombical and hexagonal shape, respectively. The meta-modules are capable of movement primitives like sliding, rotating, and tunneling. This allows us to simulate shape formation algorithms of various modular robot systems. Finally, we construct three amoebot structures capable of locomotion by rolling, crawling, and walking, respectively.

This century's most serious catastrophe, COVID-19, has been dubbed "the most life-threatening disaster ever". Asthmatic persons are even more prone to COVID-19's complex interplay with the underlying inflammatory condition. In order to protect themselves against COVID-19, asthmatic patients must be very vigilant in their usage of therapeutic techniques and drugs (e.g., bronchodilators, 5-lipoxygenase inhibitors), which may be accessed to deal with mild, moderate, and severe COVID-19 indications. People with asthma may have more severe COVID-19 symptoms, which may lead to a worsening of their condition. Several cytokines were found to be elevated in the bronchial tracts of patients with acute instances of COVID-19, suggesting that this ailment may aggravate asthma episodes by increasing inflammation. The intensity of COVID-19 symptoms is lessened in patients with asthma who have superior levels of T-cells. Several antibiotics, antivirals, antipyretics, and anti-inflammatory drugs have been suggested to suppress COVID-19 symptoms in asthmatic persons. Furthermore, smokers are more likely to have aggravated repercussions in COVID-19 infection. Being hospitalized to critical care due to COVID-19, needing mechanical breathing, and suffering from serious health repercussions, are all possible outcomes for someone who has previously smoked. Smoking damages airways and alveoli, which significantly raises the risk of COVID-19-related health complications. Patients with a previous record of smoking are predisposed to severe COVID-19 disease symptoms that essentially require a combination of bronchodilators, mucolytics, antivirals, and antimuscarinic drugs, to cope with the situation. The present review discusses the care and management of asthmatic and smoker patients in COVID-19 infection.

This study demonstrates two sustainable processes to produce electroactive biochars and their application in electroactive constructed wetlands (CWs) for providing a circular route for biomass utilization and technology up-gradation for wastewater treatment along with electricity generation. With the use of Canna indica biomass generated in CWs operation, the current study produced two different biochars that differ in their physico-(electro)chemical properties related to the preparation method used. This study used plasma based processing to produce ultrafast biochar (PB) within a few minutes resulting in more crystalline biochar with high electrical conductivity compared to the amorphous biochar material produced by using the drum kiln processed biochar (KB) method. These biochars were used in developing electroactive constructed wetlands coupled with microbial fuel cells (CW-MFC) and were operated in batch mode together with commercial granular graphite (GG) substrate-based CW-MFC as control. PB was developed from high-temperature plasma processing in 6.0 min, whereas KB was prepared in bulk amount from semi-controlled combustion process in kiln method and took 3–4 days before final biochar preparation. Electrical conductivity (EC) of the biochar and GG material were found to be in the order of PB > GG > KB, indicating PB as a highly conductive material that assisted in microbial electron transfer. Accordingly, the highest current and power densities of 628 mA m-3 and 126 mW m-3, respectively, were also achieved with PB. The COD removal of 72.42 ± 2.61 %,72.32 ± 2.98 % and 59.91 ± 3.21 % was found in CW-MFC-GG, CW-MFC-KB and CW-MFC-PB microcosms, respectively.

Introduction: In human beings Rakta dhatu is given utmost importance as the  diseases pertaining to Rakta is more in incidence. Kamala issuch a disease where in the Rakta dhatu is vitiated primarily by Pitta dosha. Indulgences with  pittaprakopaka nidana independently or after pitta pradhana vyadhis such as  Pandu are considered as nidana for Kamala. Based on samprapti, it is  manifested in two forms, Kostha Shaka Ashrita Kamala and Shaka Ashrita  Kamala. Clinically they were mainly characterized by Haridra Netra, Twak,  Nakha, Mootra and differentiated by Shweta varcha and Raktapeeta varcha respectively. Objective: - To understand the concept of the Kamala w.s.r Jaundice.  Material & method-Data collected from various ayurvedic & modern textbook  like Charak Samhita with Ayurved Dipika Commentary, Sushruta Samhita with Nibandhsangraha commentary, Ashtang Hriday with commentaries  Sarvangasundara, Relevant articles published in various national and  internationaljournals, Discussion: - In Ayurvedic literature kamala is described as pittaj nantmaja and  raktapradoshaj vyadhi. The aggravated pitta dosh impairs the blood and tissue of the liver and blocksthe channelsof the liver. Thus, pitta isthrown back into blood leading to discoloration of eyes and skin. Conclusion: - The Kamala would be point out to a disease condition in which hunger and appetitefor food are diminished.

Cancer is a deadly genetic disease with diverse aspects of complexity, including cancer immune evasion, treatment resistance, and recurrence requiring optimized treatment to be cured. Molecular studies have revealed that tumors are profoundly heterogeneous in nature, leading to the complexity of cancer progression that is ultimately linked to its genetic machinery. It is important to note that patients with the same types of cancer respond differently to cancer treatments, indicating the need for patient-specific treatment options. This requires an in-depth genomic study of the patient's tumors to fully understand the driving factors of cancer for effective targeted therapy. Precision oncology has evolved as a form of cancer therapy focused on genetic profiling of tumors to identify molecular alterations involved in cancer development for tailored individualized treatment of the disease. Whole genome sequencing, tumor and cell-free DNA profiling, transcriptomics, proteomics and exploration of the cancer immune system form the basis of this field of cancer research and treatment. This article aims to briefly explain the foundations and frontiers of precision oncology in the context of ongoing technological advancements in related fields of study in to assess its scope and importance in achieving effective cure against cancer.

Tweakable Enciphering Scheme (TES) is a length preserving scheme which provides confidentiality and admissible integrity. XCB (Extended Code Book) is a TES which was introduced in 2004. In 2007, it was modified and security bound was provided. Later, these two versions were referred to as XCBv1 and XCBv2 respectively. XCBv2 was proposed as the IEEE-std 1619.2 2010 for encryption of sector oriented storage media. In 2013, first time Security bound of XCBv1 was given and XCBv2's security bound was enhanced. A constant of $2^{22}$ appears in the security bounds of the XCBv1 and XCBv2. We showed that this constant of $2^{22}$ can be reduced to $2^{5}$. Further, we modified the XCB (MXCB) scheme such that it gives better security bound compared to the present XCB scheme. We also analyzed some weak keys attack on XCB and a type of TES known as HCTR (proposed in 2005). We performed distinguishing attack and the hash key recovery attack on HCTR. Next, we analyzed the dependency of the two different keys in HCTR., Comment: M.Tech Dissertation. Indian Statistical Institute, Kolkata, July 2018

This paper studies the message complexity of authenticated Byzantine agreement (BA) in synchronous, fully-connected distributed networks under an honest majority. We focus on the so-called {\em implicit} Byzantine agreement problem where each node starts with an input value and at the end a non-empty subset of the honest nodes should agree on a common input value by satisfying the BA properties (i.e., there can be undecided nodes). We show that a sublinear (in $n$, number of nodes) message complexity BA protocol under honest majority is possible in the standard PKI model when the nodes have access to an unbiased global coin and hash function. In particular, we present a randomized Byzantine agreement algorithm which, with high probability achieves implicit agreement, uses $\tilde{O}(\sqrt{n})$ messages, and runs in $\tilde{O}(1)$ rounds while tolerating $(1/2 - \epsilon)n$ Byzantine nodes for any fixed $\epsilon > 0$, the notation $\Tilde{O}$ hides a $O(\polylog{n})$ factor. The algorithm requires standard cryptographic setup PKI and hash function with a static Byzantine adversary. The algorithm works in the CONGEST model and each node does not need to know the identity of its neighbors, i.e., works in the $KT_0$ model. The message complexity (and also the time complexity) of our algorithm is optimal up to a $\polylog n$ factor, as we show a $\Omega(\sqrt{n})$ lower bound on the message complexity.

The ongoing COVID-19 pandemic increases the consumption of antimicrobial substances (ABS) due to the unavailability of approved vaccine(s). To assess the effect of imprudent consumption of ABS during the COVID-19 pandemic, we compare the 2020 prevalence of antidrug resistance (ADR) of Escherichia coli (E. coli) with a similar survey carried out in 2018 in Ahmedabad, India using SARS-CoV-2 gene detection as a marker of ABS usage. We found a significant ADR increase for in 2020 compared to 2018 in ambient water bodies, harbouring a higher incidence of ADR E.Coli towards non-fluoroquinolone drugs. Effective SARS-CoV-2 genome copies were found to be associated with the ADR prevalence. The prevalence of ADR depends on the efficiency of WWTPs (Wastewater Treatment Plants) and the catchment area in its vicinity. In year 2018 study, prevalence of ADR was discretely distributed, and the maximum ADR prevalence recorded was ~60%; against the current homogenous ADR increase, and up to 85% of maximum ADR among the incubated E.coli isolated from the river (Sabarmati) and lake (Chandola and Kankaria) samples. Furthermore, wastewater treatment plants showed less increase in comparison to the ambient waters, which eventually imply that although SARS-CoV-2 genes and faecal pollution may be diluted in the ambient waters, as indicated by low Ct-value and E.coli count, the danger of related aftermath like ADR increase cannot be nullified. Also, Non-fluoroquinolone drugs exhibited overall more resistance than the quinolone drugs. Overall, this is probably the first ever study that traces the COVID-19 pandemic imprints on the prevalence of antidrug resistance (ADR) through wastewater surveillance and hints at monitoring escalation of other environmental health parameters. This study will make public and policyholders concerned about the optimum use of antibiotics during any kind of treatment.

In the initial pandemic phase, effluents from wastewater treatment facilities were reported mostly free from Severe Acute Respiratory Coronavirus 2 (SARS-CoV-2) RNA, and thus conventional wastewater treatments were generally considered effective. However, there is a lack of first-hand data on i) comparative efficacy of various treatment processes for SARS-CoV-2 RNA removal; and ii) temporal variations in the removal efficacy of a given treatment process in the backdrop of active COVID-19 cases. This work provides a comparative account of the removal efficacy of conventional activated sludge (CAS) and root zone treatments (RZT) based on weekly wastewater surveillance data, consisting of forty-four samples, during a two-month period. The average genome concentration was higher in the inlets of CAS-based wastewater treatment plant in the Sargasan ward (1.25 x 103 copies/ L), than that of RZT plant (7.07 x 102 copies/ L) in an academic institution campus of Gandhinagar, Gujarat, India. ORF 1ab and S genes appeared to be more sensitive to treatment i.e., significantly reduced (p <0.05) than N genes (p>0.05). CAS treatment exhibited better RNA removal efficacy (p=0.014) than RZT (p=0.032). Multivariate analyses suggested that the effective genome concentration should be calculated based on the presence/absence of multiple genes. The present study stresses that treated effluents are not always free from SARS-CoV-2 RNA, and the removal efficacy of a given WWTPs is prone to exhibit temporal variability owing to variations in active COVID-19 cases in the vicinity and genetic material accumulation over time. Disinfection seems less effective than the adsorption and coagulation processes for SARS-CoV-2 removal. Results stress the need for further research on mechanistic insight on SARS-CoV-2 removal through various treatment processes taking solid-liquid partitioning into account.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel member of the Coronaviridae family, has been identified as the etiologic agent of an ongoing pandemic of severe pneumonia known as COVID-19.(1) To date there have been millions of cases of COVID-19 diagnosed in 184 countries with case fatality rates ranging from 1.8% in Germany to 12.5% in Italy.(2) Limited diagnostic testing capacity and asymptomatic and oligosymptomatic infections result in significant uncertainty in the estimated extent of SARS-CoV-2 infection.(3) Recent reports have documented that infection with SARS-CoV-2 is accompanied by persistent shedding of virus RNA in feces in 27%(4) to 89% of patients at densities from 0.8 to 7.5 log10 gene copies per gram.(5) The presence of SARS-CoV-2 RNA in feces raises the potential to survey sewage for virus RNA to inform epidemiological monitoring of COVID-19, which we refer to as wastewater-based epidemiology (WBE),(6) but is also known as environmental surveillance.(7) Several studies have reported the detection of SARS-CoV-2 RNA in wastewater in the early stages of local outbreaks, further supporting the technical viability of WBE.(8−10) WBE could be especially informative given that asymptomatic and oligosymptomatic infections are unlikely to be detected during clinical surveillance. In such instances, WBE can be used to determine the burden of undiagnosed infections at the population level, which is critical to refining estimates of case-fatality rates. Additionally, wastewater offers an aggregate sample from an entire community that is more easily accessible than pooled clinical samples.(11) Along with clinical data and other technological approaches, such as contact tracing, WBE could provide critical monitoring of SARS-CoV-2 transmission within a community including the beginning, tapering, or re-emergence of an epidemic (Figure 1). This approach mirrors previous efforts in environmental monitoring, for example poliovirus RNA, to inform

In this study, the neuroprotective potential of arbutin (100 µmol L–1) pre-treatment and post-treatment against oxygen/glucose deprivation (OGD) and reoxygenation (R) induced ischemic injury in cultured rat cortical neurons was explored. The OGD (60 min) and reoxygenation (24 h) treatment significantly (p < 0.001) compromised the antioxidant defence in cultured neurons. Subsequently, an increase (p < 0.001) in lipid peroxidation and inflammatory cytokines (tumour necrosis factor-α and nuclear factor kappa-B) declined neuron survival. In pre- and post-condition experiments, treatment with arbutin enhanced both survival (p < 0.01) and integrity (p < 0.05) of cultured neurons. Results showed that arbutin protects (p < 0.05) against peroxidative changes, inflammation, and enhanced the antioxidant activity (e.g., glutathione, superoxide dismutase and catalase) in cultured neurons subjected to OGD/R. It can be inferred that arbutin could protect against ischemic injuries and stroke. The anti-ischemic activity of arbutin can arrest post-stroke damage to the brain.

Wastewater-based epidemiology offers a time- and cost-effective way to monitor SARS-CoV-2 spread in communities and therefore represents a complement to clinical testing. WBE applicability has been demonstrated in a number of cases over short-term periods as a method for tracking the prevalence of SARS-CoV-2 and an early-warning tool for predicting outbreaks in the population. This study reports SARS-CoV-2 viral loads from wastewater treatment plants (WWTPs) and hospitals over a 6-month period (June to December 2020). Results show that the overall range of viral load in positive tested samples was between 1.2 × 103 and 3.5 × 106 gene copies/l, unveiling that secondary-treated wastewaters mirrored the viral load of influents. The interpretation suggests that the viral titers found in three out of four WWTPs were associated to clinical COVID-19 surveillance indicators preceding 2-7 days the rise of reported clinical cases. The median wastewater detection rate of SARS-CoV-2 was one out of 14,300 reported new cases. Preliminary model estimates of prevalence ranged from 0.02 to 4.6% for the studied period. This comprehensive statistical and epidemiological analysis demonstrates that the applied wastewater-based approach to COVID-19 surveillance is in general consistent and feasible, although there is room for improvements.

Purpose of Review Fine particulate matter (PM2.5) and ground-level ozone (O3) pose a significant risk to human health. The World Health Organization (WHO) has recently revised healthy thresholds for both pollutants. The formation and evolution of PM2.5 and O3 are however governed by complex physical and multiphase chemical processes, and therefore, it is extremely challenging to mitigate both pollutants simultaneously. Here, we review mechanisms and discuss the science-informed pathways for effective and simultaneous mitigation of PM2.5 and O3. Recent Findings Global warming has led to a general increase in biogenic emissions, which can enhance the formation of O3 and secondary organic aerosols. Reductions in anthropogenic emissions during the COVID-19 lockdown reduced PM2.5; however, O3 was enhanced in several polluted regions. This was attributed to more intense sunlight due to low aerosol loading and non-linear response of O3 to NOx. Such contrasting physical and chemical interactions hinder the formulation of a clear roadmap for clean air over such regions. Summary Atmospheric chemistry including the role of biogenic emissions, aerosol-radiation interactions, boundary layer, and regional-scale transport are the key aspects that need to be carefully considered in the formulation of mitigation pathways. Therefore, a thorough understanding of the chemical effects of the emission reductions, changes in photolytic rates and boundary layer due to perturbation of solar radiation, and the effect of meteorological/seasonal changes are needed on a regional basis. Statistical emulators and machine learning approaches can aid the cumbersome process of multi-sector multi-species source attribution.

Post monsoonal agricultural Crop Residue Burning (CRB) over northwestern India is believed to severely affect the air quality of the megacity of Delhi. However, the mechanistic understanding remains elusive. Long-term satellite observations (2007–2020) of aerosol properties during CRB season (Oct 20th to Nov 20th) indicate a distinct airshed of CRB plume transport from Northwestern India (source region) to greater Delhi (downwind region). Theoretically, the smoke concentration should disperse downwind, and the CRB-associated PM2.5 enhancement over Northern India should be inversely proportional to the distance from the CRB source region. However, the in-situ PM2.5 observations illustrate that smoke-associated enhancement in PM2.5 over greater Delhi (downwind region) is disproportionately large compared to the source region. In this study, we examine satellite, radiosonde, and ground-based observations along with reanalysis data to provide robust evidence that aerosol- boundary layer - PM2.5 associations via semi-direct effect can explain the above heterogeneity. Vertically resolved satellite observations indicate that as the emitted CRB-smoke plumes travel downwind, a portion of the transported smoke plume injected relatively at a higher altitude leads to the formation of an elevated smoke layer over greater Delhi. These elevated smoke layers tend to suppress the mixing height via inducing strong temperature inversion, thereby severely constraining the daytime dilution effect of shallow boundary layers. Along with direct advection of smoke particles, enhanced accumulation of local urban emissions due to these semi-direct impacts can lead to the observed disproportionate PM2.5 enhancements over Delhi during CRB haze periods. Thus, control of the local anthropogenic emissions could bring relief during the extreme haze episodes over Delhi.