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In the AI era, where everything is turning out to be smart and autonomous, using a manual door is problematic as it requires a human to lock and unlock every time someone wants to come in. Even it hampers the security of an individual as he may not know who is on the other side of the door, and may lead to serious crimes. To bridge the gap and make life easy, our team came up with an AI driven Smart Door that can be monitored with any device like a smartphone. In the system, there will be a webcam implanted on the door to detect anyone outside, and there will be solenoid motor to lock/unlock the door. Person waiting outside can be traced by the system, and if the person is added to the whitelist by the user, the door will open automatically and alert the user via message. If the person is stranger to the user, it will alert the user and ask him whether to let him in, and act accordingly. From our user's perspective, he will have a simple interactive interface with which he can monitor everything and give commands by speaking from anywhere. There would be use of databases for white guest and black guest marked by the user. If the guests are allowed, the door will be unlocked automatically. The project will add value to the security of the users and in turn to humanity.

Artificial Intelligence is now a rapidly growing sector which will emphasize the productivity of man according to their need. So, this is our virtual assistant where we implement a small portion of AI to make our daily life more enjoyable and also be more productive. Our virtual not only able to recognize the voice of its owner but also it can perform all the given information by its owner. In past years we have no sort of devices or things to communicate with the AI devices for that reason we need to implement some coding to a chip or specifically into an integrated circuit which has a less amount of memory and can't able to perform all the algorithms by its own so we make an AI algorithm using python which can able to recognize as simple as a human can understand others language in their mother tongues. Also we are in testing of the algorithm to make an automatic robotic toy car which have the facility of the virtual assistant and the user of that car can able give it any sort of instructions on how to perform any operations simply into there mother tongues also they shouldn't use English also otherwise they can use google translate tool to make the output in their mother tongue.

In this paper we propose a method to analyze the sentiments of a user on a particular topic on the basis of their tweets. This method breaks up the texts into words, remove all the unnecessary stop words and then using a dictionary determines the sentiments by grouping certain words together. Using Tokenization it first splits those tweets into smaller units and using lemmatization it reduces the infected words to meaningfulwords before comparing those with the dictionary elements. Our purpose is to establish perceptive links between tweets and public sentiment for a better understanding of the public opinion. In this paper we present two applications of this method: recognizing depression in tweets and recognizing mass opinion. In the first application we use certain keywords to search for tweets that tend towards depression and our program analyzes the exact sentiments of the tweet to confirm the existence of depression. In the second application, tweets regarding a certain topic are scraped and they are analyzed together to give a result that represents the public opinion.

This paper represents an IoT based wireless portable healthcare system which can continuously monitor patient's heart rate, body temperature, SpO2 and keep track of the steps without visiting the hospital at the emergency hour. These sensors are connected to a NodeMCU development board to read the vitals of the patient and the output displayed on the OLED display. All Data is synced from the device to the cloud using Wi-fi or SIM Card IoT module (in case Wi-Fi is not available). The data is stored in cloud storage for future references. It enables the medical records or anamnesis for the family members to monitor the real- time data 24/7 using mobile. The system allows physicians to immediate precautions and autogenerate prescription.

The efficient monitoring and early detection of viruses may provide essential information about the disease. In this work, we have highlighted the interaction between DNA and a two-dimensional (2D) metal...

In this digital era, face recognition system plays a vital role in almost every sector. Face recognition is one of the mostly used biometrics. It can used for security, authentication, identification, and has got many more advan- tages. Despite of having low accuracy when compared to iris recognition and fingerprint recognition, it is being widely used due to its contactless and non-invasive process. Furthermore, face recognition system can also be used for attendance marking in schools, colleges, offices, etc. This system aims to build a class attendance system which uses the concept of face recognition as existing manual attendance system is time consuming and problematic to maintain. And there may be chances of proxy attendance. Thus, the need for this system increases. Faces are detected and recognized from a camera placed inside the classroom.

Background: Even though RT-PCR tests are generally considered the gold standard for diagnosing SARS-CoV-2, they are not without flaws, and the likelihood of detecting an infection varies depending on when the test is performed. There is chance of false negative due to different pitfalls. So there is essential of correlation of radiological characteristics, abnormalities in biochemical tests and symptoms of suspected patient during COVID-19 epidemic. Case presentation: Herein, we report a 42-year-old male patient with high-grade fever, dry cough, headache and dizziness. He went for the RT-PCR test two times and reported negative. On the chest X-Ray, there was opacity on both lungs and referred to cancer-hospital for lung-cancer screening. The patient underwent chest-HRCT and laboratory tests for further evaluation and was identified as typical COVID-19 findings. Then the patient was isolated and treatment of given according to COVID-19 treatment guidelines Conclusion: It is concluded that a clinically symptomatic patient with typical chest HRCT and abnormal lab findings for COVID-19 should be considered as a COVID-19 patient and isolated even with two negative RT-PCR tests.

Pine needles are the by-product from the pine forest and cause of wild forest fire. A batch type portable charring drum was evaluated for converting pine needles to char and product gas with an aim to produce good quality char on-site. Char and product gas were characterized for their suitability as biochar and compared with chars derived from electrically heated batch type tubular reactor. The maximum conversion efficiency was found to be 29.3% at 80% loading, 50 m3 h−1 air flow rate and 90-min gasification time. Elemental analysis showed the maximum carbon content of 76.5% in the derived char which was comparable to the char derived at 400 °C. Other chemical properties also resembled the char produced at 400 °C. For good quality char which can qualify as biochar as per the guideline of European Biochar Certificate, gasification time is needed to continue up to 120 min at 60% loading.

Bismuth(Bi)-based materials have gained considerable attention in recent decades for use in a diverse range of sustainable energy and environmental applications due to their low toxicity and eco-friendliness. Bi materials are widely employed in electrochemical energy storage and conversion devices, exhibiting excellent catalytic and non-catalytic performance, as well as CO

Abstract - Emotion can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Emotion Detection in text documents is essentially a content– based classification problem involving concepts from the domains of Natural Language Processing as well as Machine Learning. In this paper we are proposing a solution for emotion recognition based on textual data. The emotion expressed in a blog, review or any kind of textual content remains unused until the text is analyzed and the emotion is retrieved from the data. It is impossible to analyze the huge amount of data manually and gain information from it.

Purpose Tar in producer gas causes detrimental effects in downstream pipelines in gasifier based power generation system. Ni-supported char based catalysts have been proven to be effective and low-cost solution for cracking of tar. Use of simple method to make the catalyst with locally available biomaterial and its optimization can effectively solve this problem. Methods This paper includes efficacy of ex-situ catalytic cracking temperature, Ni-loading, particle size of char catalyst and catalyst bed depth on cracking efficiency. Producer gas generated from pigeonpea stalk pellets using a laboratory scale downdraft gasifier was passed through a hot catalyst bed in an ex-situ reactor. Taguchi method was used for de-compositional analysis of the variables affecting tar-cracking efficiency. Results Experiments showed increase in cracking efficiency with increasing temperature, Ni loading, bed depth and with decrease in particle size. Optimum values of operating parameters were 700 °C catalyst bed temperature, 0.3 M Ni loading, 5–10 mm particle size and 400 mm bed depth. Improvement in gas composition with the increase in Ni-loading was observed. Conclusion These findings confirmed that using pigeonpea stalk char supported with Ni, tar in producer gas can be decomposed to the tune of 84% at 600°C which can be easily achievable at the peripheral space of oxidation zone in a downdraft gasifier. With further increase in temperature to 700°C and using low size of 1–5 mm catalysts cracking efficiency can be achieved up to 93%. Catalytic cracking also improved the quality of producer gas.

– Based on the concept of Application programming interface (API).This project comprises of a package named "algokit" which contains several algorithms based on the category of searching, sorting, dynamic programming, tree traversals and swapping. Keeping in mind that different algorithms from the same category have its own benefit in time and space complexity, This project covers almost all the algorithms known and available from each category. This would give the user several options to choose the right algorithm for its code.An user just requires to import the package named AlgoKit and call the functions inside it for a smooth programming experience. One of the prime objectives of this project is to build a kit that serves the purpose of reducing the number of lines of code and also reduce the time taken to run the same code elsewhere. It is platform independent and can be used in any open source Java development environment.

Background: mRNA vaccines have a strong potential for a possible cancer therapy platform. They express tumor antigens in antigen-presenting cells (APCs) after immunization, facilitating innate/adaptive immune stimulation. Because of its high effectiveness, safe administration, rapid development potential, and cost-efficient manufacturing, the mRNA cancer vaccine surpasses other traditional vaccination platforms. Conclusion: Careful evaluation of promising mRNA vaccines to supervise as carriers of lipids for cancer patients needs to be done. In addition, a possible revaluation for optimal protection is required. However, the extent to which solid tumours might take a significant part of the vaccine doses is still unknown.

In the present study, seven diverse biomasses of Indian origin were characterized and pyrolyzed at 450 °C to produce biochars. The biochars were thoroughly characterized using a variety of techniques to assure their potential energy and environmental and agricultural applications. Biochars derived from crop wastes with low lignin content, viz., rice husk biochar (RHB), rice straw biochar (RSB), maize stover biochar (MSB), and sugarcane biochar (SCB), possessed high ash content, high pH, and low fixed carbon making them suitable for soil amelioration. RSB, RHB, and MSB recorded high cation exchange capacity, making their potential utilization as liming material and removal of heavy metal contaminants. Elemental O/C ratios for all biochars, except maize stover biochar, were in the range of 0.27–0.32, which showed better stability and half-life period. Thermogravimetric analysis (TGA) was carried out to evaluate the thermal stability of biochars up to 900 °C, and the overall mass loss varied in the range of 16–27 wt%. Biochars from eucalyptus (EB), lantana (LB), and pine needle (PNB) were found to have high higher heating values (HHVs) (23–28 MJ/kg), higher fixed carbon, and lower ash content. Correlations were constructed between HHV of biochars and their volatile matter, ash, and fixed carbon content with high but negative correlation with ash content. Rice straw, rice husk, maize stover, and sugarcane trash were poor substrates, as the resultant biochars contained ≤ 60 wt% fixed carbon, high ash, and a relatively low HHV. It is shown that RHB, RSB, MSB, and SCB can be potential materials for soil amendment and plant nutrient, while PNB, LB, and EB are suitable for renewable solid fuel purpose.

Mathematical modelling has been a helpful resource for planning public health responses to COVID-19. However, there is a need to improve the accessibility of models built within country contexts in the Global South. Immediately following the overwhelming ‘second wave’ of COVID-19 in India, we developed a user-friendly, web-based modelling simulator in partnership with the public health experts and health administrators for subnational planning. The purpose was to help policy-makers and programme officials at the state and district levels, to construct model-based scenarios for a possible third wave. Here, we describe our experiences of developing and deploying the simulator and propose the following recommendations for future such initiatives: early preparation will be the key for pandemic management planning, including establishment of networks with potential simulator users. Ideally, this preparedness should be conducted during ‘peace time’, and coordinated by agencies such as WHO. Second, flexible modelling frameworks will be needed, to respond rapidly to future emergencies as the precise nature of any pandemic is impossible to predict. Modelling resources will, therefore, need to be rapidly adaptable to respond as soon as a novel pathogen emerges. Third, limitations of modelling must be communicated clearly and consistently to end users. Finally, systematic mechanisms are required for monitoring the use of models in decision making, which will help in providing modelling support to those local authorities who may benefit most from it. Overall, these lessons from India can be relevant for other countries in the South-Asian-Region, to incorporate modelling resources into their pandemic preparedness planning.

Electronic waste (e-waste) is the world's fastest-growing type of waste, with lighting accounting for 9% of the total. Light-emitting diodes (LEDs) are composed of the most concentrated critical elements (Ag and Au) and recovery of these metals could generate economic benefits and reduce the burdens of environmental pollution; nevertheless, the absence of information about their composition currently presents a challenge in recycling these metals with minimal prospects for recovery. This study assessed the distribution and variation of elemental concentrations of 16 different elements in three generations of LEDs (12 different LED units): sub-mounted-device (SMD #10), chip-on-board (COB #1), and positive-intrinsic-negative (PIN #1). The SMD LEDs contained a considerable amount of Au with a median average concentration of 1204 mg/kg (ranging from 323 - 3687 mg/kg), which was similar to that of COB (1550 mg/kg), but higher than that of PIN LED (175 mg/kg). Based on the total threshold limiting concentration (TTLC), the Cu levels (605,823 mg/kg) in the SMD package exceeded the regulatory limits (2500 mg/kg). Concentrations of the hazardous elements Cr (29 mg/kg), Pb (12 mg/kg), Cd (0.1 mg/kg), and As (1 mg/kg) in the LED packages were within the regulatory limits. To recycle precious metals and other technological metals, a well-organized and dedicated optimized assessment of the value of metals is required especially in accordance with the concept of criticality and recyclability. Two factors, i.e., a high resource index (RI) and technology index (TI), suggest the importance of waste to the economy and has a significant potential for recycling with less processing burdens. Present findings indicated that the COB and a few of the studied SMD LEDs (3020, 4014, 5630, and 7020), exhibit high criticality and recyclability. For the RI and TI index, the contribution of metals such as Cu, Fe, Al, and Au were dominant. These findings can serve as a reference for the development of a viable approach for the recycling and recovery of targeted metals from LED e-waste.

Background & objectives In the context of India's ongoing resurgence of COVID-19 (second wave since mid-February 2021, following the subsiding of the first wave in September 2020), there has been increasing speculation on the possibility of a future third wave of infection, posing a burden on the healthcare system. Using simple mathematical models of the transmission dynamics of SARS-CoV-2, this study examined the conditions under which a serious third wave could occur. Methods Using a deterministic, compartmental model of SARS-CoV-2 transmission, four potential mechanisms for a third wave were examined: (i) waning immunity restores previously exposed individuals to a susceptible state, (ii) emergence of a new viral variant that is capable of escaping immunity to previously circulating strains, (iii) emergence of a new viral variant that is more transmissible than the previously circulating strains, and (iv) release of current lockdowns affording fresh opportunities for transmission. Results Immune-mediated mechanisms (waning immunity, or viral evolution for immune escape) are unlikely to drive a severe third wave if acting on their own, unless such mechanisms lead to a complete loss of protection among those previously exposed. Likewise, a new, more transmissible variant would have to exceed a high threshold (R0>4.5) to cause a third wave on its own. However, plausible mechanisms for a third wave include: (i) a new variant that is more transmissible and at the same time capable of escaping prior immunity, and (ii) lockdowns that are highly effective in limiting transmission and subsequently released. In both cases, any third wave seems unlikely to be as severe as the second wave. Rapid scale-up of vaccination efforts could play an important role in mitigating these and future waves of the disease. Interpretation & conclusions This study demonstrates plausible mechanisms by which a substantial third wave could occur, while also illustrating that it is unlikely for any such resurgence to be as large as the second wave. Model projections are, however, subject to several uncertainties, and it remains important to scale up vaccination coverage to mitigate against any eventuality. Preparedness planning for any potential future wave will benefit by drawing upon the projected numbers based on the present modelling exercise.

Background The Coronavirus disease 2019 (COVID-19) pandemic poses a serious public health concern worldwide. Certain regions of the globe were severely affected in terms of prevalence and mortality than other. Although the cause for this pattern is not clearly understood, lessons learned from previous epidemics and emerging evidences suggest the major role of ecological factors like ambient air pollutants (AAP) and meteorological parameters in increased COVID-19 incidence. The present study aimed to understand the impact of these factors on SARS-CoV-2 transmission and their associated mortality in major cities of India. Methods This study used secondary AAP, meteorological and COVID-19 data from official websites for the period January-November 2020, which were divided into Pre-lockdown (January-March 2020), Phase I (April to June 2020) and Phase II (July to November 2020) in India. After comprehensive screening, five major cities that includes 48 CPCB monitoring stations collecting daily data of ambient temperature, particulate matter PM2.5 and 10 were analysed. Spearman and Kendall’s rank correlation test was performed to understand the association between SARS-CoV-2 transmission and AAP and, meteorological variables. Similarly, case fatality rate (CFR) was determined to compute the correlation between AAP and COVID-19 related morality. Results The level of air pollutants in major cities were significantly reduced during Phase I compared to Pre-lock down and increased upon Phase II in all the cities. During the Phase II in Delhi, the strong significant positive correlation was observed between the AAP and SARS-CoV-2 transmission. However, in Bengaluru, Hyderabad, Kolkata and Mumbai AAP levels were moderate and no correlation was noticed. The relation between AT and SARS-CoV-2 transmission was inconclusive as both positive and negative correlation observed. In addition, Delhi and Kolkata showed a positive association between long-term exposure to the AAP and COVID-19 CFR. Conclusion Our findings support the hypothesis that the particulate matter upon exceeding the satisfactory level serves as an important cofactor in increasing the risk of SARS-CoV-2 transmission and related mortality. These findings would help public health experts to understand the SARS-CoV-2 transmission against ecological variables in India and provides supporting evidence to healthcare policymakers and government agencies for formulating strategies to combat the COVID-19.

Pine needles are the waste of pine forest and produced in a substantial amount every year during the fall. If not extracted from forest bed, they cause a widespread forest fire. In this study, pine needles were converted to char at different temperatures using a screw type pyrolyzer with an aim to find out the effect of thermal stress on the properties of chars and their intended end uses. The chars were evaluated for intrinsic physico-chemical transformations in comparison with the raw pine needles. Differences between chars produced in three temperatures and the raw biomass were studied by thermogravimetric analysis. It was found that the char produced at higher temperature showed a superior profile of apparent activation energy as compared with the char from low temperature. Coats–Redfern kinetics was used to compare the activation energies of chars and raw biomass, which showed that the char obtained from higher temperature had better thermal stability. From this study it can be concluded that chars produced at low temperatures in the screw reactor are useful as source of fuel, whereas the char of higher temperature is suitable for soil application and preparation of activated char.

New approaches and practices to improve photocatalytic efficiency of materials for remediation of organic and inorganic pollutant has become a top priority. We have developed a graphene-oxide based ternary composite Ag/TiO2/rGO as a green catalyst, and the photocatalytic oxidation and reduction efficiency of the catalyst was thoroughly evaluated for Cr(VI) and tetracycline (TC) remediation in water as potential contaminants. The results suggested that the electronic coupleing system exhibits excellent photocatalytic activity, mainly due to affecting light absorption and higher e−/h+ separation efficiency. The photocatalytic activity of the silver-deposited graphene-supported silver and titanium dioxide was 4.3 and 2.5 times for Cr (VI) and TC remediation, respectively. Furthermore, the service life of the photocatalyst was also evaluated within five recycling studies, indicating that the efficiency of the obtained photocatalyst was maintained above 80%. Electron paramagnetic resonance spectroscopy and the addition of free radical scavengers confirmed that e− act as reducing agents and may be the key (O2·−) to the degradation process. The photocatalytic mechanism was proposed based on the studies obtained. Green catalysts based on graphene-based ternary composites developed in this work can provide effective and economic remediation at higher scale and offer practical application of photo catalysis technology.

A uniformly distributed mesoporous silica nanospheres has been successfully synthesized. Silica nanospheres have been loaded with different content of Fe2O3 nanoparticles synthesized by the sol-gel process followed by calcination to form the Fe2O3 supported on silica nanospheres composite. The as-synthesized photocatalyst has been characterized for crystal structure, morphology, stability, surface area and also surface composition was determined. The photocatalytic oxidation ability of the composite photocatalyst was evaluated by degrading aqueous solutions of Methylene Blue and Congo red dyes under visible light having intense absorption in the wavelength range between 550 and 560 nm. The prime significance of silica is to act as catalyst support for uniform distribution of hematite particles for enhanced catalytic reactivity. Highest degradation has been achieved with 20 wt % loading of hematite nanoparticles indicating the less agglomeration and availability of more catalytic sites. Furthermore, colorless organic pollutants 2-chlorophenol and 2, 4-dichlorophenol have been degraded with high efficiency in the presence of H2O2 oxidizer. The scavenger experiments confirmed that hydroxyl radicals are the majorly participating species in this catalytic system. The composite system also shows good recyclability of the materials and advocates the promising nature of the designed system for multiple hazardous environmental contaminants.

Levofloxacin—a fluoroquinolone antibiotic—is a potential wastewater contaminant generated by pharmaceutical industries. Novel one-dimensional disilver dimolybdate (Ag2Mo2O7) structures were developed to form a heterojunction with thin nanosheets of MoS2 on the surface of Ag2Mo2O7. A photocatalyst was used for the efficient removal of levofloxacin under visible light. The processing of the Ag2Mo2O7 structures was optimized by altering the hydrothermal duration with structural analysis using Rietveld refinement. An enhanced catalytic activity for levofloxacin degradation (efficiency of 97%) was observed with 30 wt% MoS2/Ag2Mo2O7, following first-order kinetics. The superior activity is ascribed to the well-aligned and favorable band positions, which allowed efficient charge transfer between the photogenerated charge carriers. The direct Z-scheme led to the photogeneration of a large number of electrons at the MoS2 surface. An investigation with radical scavengers indicated that superoxide radicals played a significant role in the degradation process, which was confirmed by electron spin resonance spectral measurements. Detailed parametric studies were performed, and the reaction mechanism was examined, providing an insight into the development of such hybrid microcomposites for the removal of hazardous pharmaceuticals from the environment.

We carry out an experimental study of the granular surface flow of nearly monodisperse glass beads on a conical heap formed on a rough circular disc by a narrow stream of the particles from a hopper, with the pouring point displaced from the centre of the disc. During the growth phase, an axisymmetric heap is formed, which grows either by periodic avalanches or by non-periodic avalanches that occur randomly over the azimuthal location of the heap, depending on the operating conditions and system properties. The dynamics of heap growth is characterized by the variation of the heap height, angle of repose and the angular velocity of the periodic avalanche with time, for different mass flow rates from the hopper. When the base of the heap reaches the edge of the disc closest to the pouring point, the heap stops growing and a steady surface flow of particles is developed on the heap surface, with particles flowing over the edge of the disc into a collection tray. The geometry is a unique example of a granular flow on an erodible bed without any bounding side walls. The corresponding steady state geometry of the asymmetric heap is characterized by means of surface contours and angles of repose. The streamwise and transverse surface velocities are measured using high-speed video photography and image analysis for different mass flow rates. The flowing layer thickness is measured by immersing a coated needle in the flow at different positions on the mid-line of the flow. The surface angle of the flowing layer is found to be significantly smaller than the angle of repose and to be independent of the mass flow rate. The velocity profiles at different streamwise positions for different mass flow rates are found to be geometrically similar and are well described by Gaussian functions. The flowing layer thickness is calculated from a model using the measured surface velocities. The predicted values match the measured values quite well.

Objectives To investigate the impact of targeted vaccination strategies on morbidity and mortality due to COVID-19, as well as on the incidence of SARS-CoV-2, in India. Design Mathematical modelling. Settings Indian epidemic of COVID-19 and vulnerable population. Data sources Country specific and age-segregated pattern of social contact, case fatality rate and demographic data obtained from peer-reviewed literature and public domain. Model An age-structured dynamical model describing SARS-CoV-2 transmission in India incorporating uncertainty in natural history parameters was constructed. Interventions Comparison of different vaccine strategies by targeting priority groups such as key workers including health care professionals, individuals with comorbidities (24 – 60 year), and all above 60. Main outcome measures Incidence reduction and averted deaths in different scenarios, assuming that the current restrictions are fully lifted as vaccination is implemented. Results The priority groups together account for about 18% of India’s population. An infection preventing vaccine with 60% efficacy covering all these groups would reduce peak symptomatic incidence by 20.6% (95% uncertainty intervals (CrI) 16.7 - 25.4), and cumulative mortality by 29.7% (95% CrI 25.8-33.8). A similar vaccine with ability to prevent symptoms (but not infection) will reduce peak incidence of symptomatic cases by 10.4% (95% CrI 8.4 – 13.0), and cumulative mortality by 32.9% (95% CrI 28.6 - 37.3). In the event of insufficient vaccine supply to cover all priority groups, model projections suggest that after keyworkers, vaccine strategy should prioritise all who are > 60, and subsequently individuals with comorbidities. In settings with weakest transmission, such as sparsely-populated rural areas, those with comorbidities should be prioritised after keyworkers. Conclusions An appropriately targeted vaccination strategy would witness substantial mitigation of impact of COVID-19 in a country like India with wide heterogenity. ‘Smart vaccination’, based on public health considerations, rather than mass vaccination, appears prudent. Strengths and limitation of this study The model in this study is informed by age-dependent risk factors for SARS-CoV-2 infection among contacts, and is stratified by co-morbidities (diabetes and/or hypertension), and vaccination status. Data on mortality and large-scale contact tracing from within India, and the recent national sero-survey results were used, which constituted a major strength of this investigation. Distinguishing between ‘infection’ and ‘symptomatic disease ‘ preventing vaccines, the model was simulated under a range of scenarios for the basic reproduction number (R0). Should they have been available, real life country-specific data on excess risks of deaths due to comorbidities would have added strength to the presented model. Key priority group-specific data on social mixing and potential associated transmission was not available, and remained as a limitation.

In this work, two-dimensional Bi

The net arable land area is declining worldwide rapidly due to soil erosion, drought, loss of soil organic carbon, and other forms of degradation. Intense rainfall, cultivation along steep slopes, unscientific land-use changes, shifting cultivation, soil acidity, and nutrient mining in hills and mountains make agriculture unsustainable and less profitable. Hills and mountain ecosystems of the Eastern Himalayan Region (EHR) are further prone to the impact of climate change posing a serious threat to agricultural production and the environment. Increasing soil carbon reserves contributes to multiple ecosystem services, improves soil nutrient and water-holding capacities, and advances climate-resilient agriculture. Thus, carbon sequestration is increasingly becoming an important aspect of farming among researchers in the region. The EHR predominantly practices shifting cultivation that degrades the ecosystem and promotes land degradation and biodiversity loss. Leaching of exchangeable bases is highly favored due to excess rainfall which in turn creates an acidic soil accounting for >84% of the region. Application of lime to raise the soil acidity for the cultivation of crops did not get adequate acceptance among the farming community due to multiple issues such as cost involvement, non-availability in time and place, and transportation issues. The application of biochar as soil amendments is widely known to improve soil’s physical, chemical, and biological properties. Biochar has also emerged as a potential candidate for long-term carbon sequestration due to its inbuilt structure and higher stability. Shift from traditional “slash and burn” culture to “slash and char” might lead to the sequestration of carbon from the atmosphere. Around 0.21 Pg of carbon (12% of the total anthropogenic carbon emissions by land-use change) can be sequestered in the soil if the traditional “slash and burnt” practice is converted to “slash and char”. The objective of this review is to provide detailed information about the role of biochar in altering the soil properties for sustaining agriculture and carbon sequestration, especially for hills and mountain ecosystems.

Background The prevention of tuberculosis (TB) is key for accelerating current, slow declines in TB burden. The 2018 World Health Organization (WHO) guidelines on eligibility for preventive therapy to treat latent TB infection (LTBI) include people living with human immunodeficiency virus (PLHIV), household contacts of TB patients including children, and those with clinical conditions including silicosis, dialysis, transplantation, etc. and other country-specific groups. We aimed to estimate the potential impact of full implementation of these guidelines in the WHO South-East Asian (SEA) Region, which bears the largest burden of TB and LTBI amongst the WHO regions. Methods We developed mathematical models of TB transmission dynamics, calibrated individually to each of the 11 countries in the region. We modelled preventive therapy in the absence of other TB interventions. As an alternative comparator, reflecting ongoing developments in TB control in the region, we also simulated improvements in the treatment cascade for active TB, including private sector engagement and intensified case-finding. Relative to both scenarios, for each country in the region, we projected TB cases and deaths averted between 2020 and 2030, by full uptake of preventive therapy, defined as comprehensive coverage amongst eligible populations as per WHO guidelines, and assuming outcomes consistent with clinical trials. We also performed sensitivity analysis to illustrate impact under less-than-optimal conditions. Results At the regional level, full uptake of preventive therapy amongst identified risk groups would reduce annual incidence rates in 2030 by 8.30% (95% CrI 6.48–10.83) relative to 2015, in the absence of any additional interventions. If implemented against a backdrop of improved TB treatment cascades, preventive therapy would achieve an incremental 6.93 percentage points (95% CrI 5.81–8.51) of reduction in annual incidence rates, compared to 2015. At the regional level, the numbers of individuals with latent TB infection that need to be treated to avert 1 TB case is 64 (95% CrI 55–74). Sensitivity analysis illustrates that results for impact are roughly proportional to ‘effective coverage’ (the product of actual coverage and effectiveness of the regimen). Conclusions Full implementation of WHO guidelines is important for ending TB in the SEA Region. Although future strategies will need to be expanded to the population level, to achieve large declines in TB incidence, the uptake of current tools can offer a valuable step in this direction.

The authors have withdrawn this manuscript because the source data was last updated at the end of March, and hence the authors believe that the results derived and conclusions drawn in the manuscript may not hold true now. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

India's lockdown against SARS-CoV-2, if lifted without any other mitigations in place, could risk a second wave of infection. A test-and-isolate strategy, using PCR diagnostic tests, could help to minimise the impact of this second wave. Meanwhile, population-level serological surveillance can provide valuable insights into the level of immunity in the population. Using a mathematical model, consistent with an Indian megacity, we examined how seroprevalence data could guide a test-and-isolate strategy, for lifting a lockdown. For example, if seroprevalence is 20% of the population, we show that a testing strategy needs to identify symptomatic cases within 5 - 8 days of symptom onset, in order to prevent a resurgent wave from overwhelming hospital capacity in the city. This estimate is robust to uncertainty in the effectiveness of the lockdown, as well as in immune protection against reinfection. To set these results in their economic context, we estimate that the weekly cost of such a PCR-based testing programme would be less than 2.1% of the weekly economic loss due to the lockdown. Our results illustrate how PCR-based testing and serological surveillance can be combined to design evidence-based policies, for lifting lockdowns in Indian cities and elsewhere.

In recent years, environmental pollution is a major global concern and adversely affecting human health and the economy. The environmental properties of soil are exceptionally complex, which makes the remediation and treatment more challenging and expensive. In this aspect, sustainable materials (biomaterials, biochar, and composites) present an effective and efficient remediation solution. Exactly, biochar and its relative composites can achieve novel properties with addition of metal oxides, surface agents, and nano-material. The present review study provides quantitative analysis and addresses the advantages of using biochar composites relative with pure biochar. The synthesis of Nano-metal assisted biochar, properties and utilization in improving soil properties as well as heavy metal removal are reviewed. Specific attention has been paid to the impacts of biochar and its composite on soil fundamental properties such as pH, cation exchange efficiency, bulk density, porosity, water retention capability, soil organic matter (SOM) and redox reactions. Significant emphasis is focused on soil remediation, in particular, the elimination of heavy metals utilizing biochar-based composites. Further research is urged to verify the proposed mechanisms involved biochar composites-microbial interactions and heavy metal remediation considering short term and long term efficiency for improvement. HighlightsProgress in development, synthesis methods, and application of biochar-based composites in the soil are studied.The impact mechanisms of biochar composites on essential soil properties have been studied.Biochar-based composites have a significant effect on bulk density and water retention capacity.Biochar-based composites were found to be better than pristine biochar in soil heavy metal remediation.The potential use of biochar-based composites in different soil heavy metal remediation prospected. Progress in development, synthesis methods, and application of biochar-based composites in the soil are studied. The impact mechanisms of biochar composites on essential soil properties have been studied. Biochar-based composites have a significant effect on bulk density and water retention capacity. Biochar-based composites were found to be better than pristine biochar in soil heavy metal remediation. The potential use of biochar-based composites in different soil heavy metal remediation prospected.

BACKGROUND & OBJECTIVES: Coronavirus disease 2019 (COVID-19) has raised urgent questions about containment and mitigation, particularly in countries where the virus has not yet established human-to-human transmission. The objectives of this study were to find out if it was possible to prevent, or delay, the local outbreaks of COVID-19 through restrictions on travel from abroad and if the virus has already established in-country transmission, to what extent would its impact be mitigated through quarantine of symptomatic patients? METHODS: These questions were addressed in the context of India, using simple mathematical models of infectious disease transmission. While there remained important uncertainties in the natural history of COVID-19, using hypothetical epidemic curves, some key findings were illustrated that appeared insensitive to model assumptions, as well as highlighting critical data gaps. RESULTS: It was assumed that symptomatic quarantine would identify and quarantine 50 per cent of symptomatic individuals within three days of developing symptoms. In an optimistic scenario of the basic reproduction number (R0) being 1.5, and asymptomatic infections lacking any infectiousness, such measures would reduce the cumulative incidence by 62 per cent. In the pessimistic scenario of R0=4, and asymptomatic infections being half as infectious as symptomatic, this projected impact falls to two per cent. INTERPRETATION & CONCLUSIONS: Port-of-entry-based entry screening of travellers with suggestive clinical features and from COVID-19-affected countries, would achieve modest delays in the introduction of the virus into the community. Acting alone, however, such measures would be insufficient to delay the outbreak by weeks or longer. Once the virus establishes transmission within the community, quarantine of symptomatics may have a meaningful impact on disease burden. Model projections are subject to substantial uncertainty and can be further refined as more is understood about the natural history of infection of this novel virus. As a public health measure, health system and community preparedness would be critical to control any impending spread of COVID-19 in the country.

Minimization of Leidenfrost effect is the main controlling step for achieving high heat transfer rate in a quenching process. Hence, in the current experimental study, by using oil-in-water emulsion spray as a coolant, the Leidenfrost effect has been tried to eliminate or significantly minimize and this can be achieved by the partial vapour condensation by the low specific heat contained oil present in the evaporating emulsion droplets. Different types of emulsion are considered in the investigation for the identification of appropriate combination. The characteristic of each emulsion is identified by analyzing the images taken by confocal microscope, Leica microscope and ESEM. In addition to the above, the thermo-physical properties controlling the thermal mechanism defining from the behaviour at the interface are also measured. The quenching experiments reveal that the heat removal rate (1.44 MW/m2) is the maximum for 800 ppm SDS + 30 ml kerosene emulsion among all the coolants due to the insignificant difference in properties at the interface of oil and water and the maximum condensation of produced vapour because of absorption of heat by the oil droplet present in the emulsion. However, vegetable oil-in-water emulsion depicts the minimum heat removal rate in comparison with pure water and other type of emulsions. The analysis of droplet impact mapping and boiling phenomena corroborate the findings of spray cooling.

The requirement for enhanced, less expensive, and eco-friendly nanocomposites as an adsorbent is highly preferred for removal of heavy metals and in the major applications of environmental remediat...

The purpose of this study was to optimize the pyrolysis conditions to obtain maximum bio-oil yield from pine needles using a screw pyrolyzer for utilizing this abundantly available ligno-cellulosic biomass from pine forest as an alternate source of fuel. Pyrolysis was conducted in a pilot scale single screw reactor. Process parameters such as pyrolysis temperature, biomass particle size, solid residence time and gas flow rate were optimized by employing Taguchi’s L9 Orthogonal Array. Chemical characterization of bio-oil was conducted using gas chromatographic/mass spectroscopy (GC/MS) analysis. Fuel properties of bio-oil and biochar were determined using ASTM standard methods. Composition of product gas was determined by gas chromatography and higher heating value (HHV) was calculated theoretically. Results revealed that bio-oil yield was primarily influenced by pyrolysis temperature and biomass particle size. The optimum conditions for maximum bio-oil yield were—pyrolysis temperature of 500 °C, particle size of 1.25–2.0 mm, solid residence time of 15 min and N2 gas flow rate of 30 l h− 1(Gas flow velocity ∼ 0.33 m min−1). A maximum bio-oil yield of 28.98% was achieved at optimum conditions. Optimized conditions found in this experiment can be employed to continuous pyrolysis of pine needles for production of higher grade energy products like bio-oil, biochar and product gas through screw reactor.