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Rainfall estimation is of paramount importance, pertaining to the plethora of stakeholders that place substantial reliance on it, particularly in the agricultural sector. Because of the dynamic character of rainfall, forecasting is challenging and byzantine. In this study, estimation of daily rainfall for an Assamese town, Silonijan located in the Karbi Anglong district of Assam India is conducted. The data used for this research are the openly available gridded products provided by the Indian Meteorological Department (IMD). The objective of this study is to estimate the potential of Artificially Intelligent (AI) techniques in rainfall estimation. This work aims to develop new methods of rainfall prediction by utilizing Deep Learning rather than typical statistical and machine learning approaches, which lack the accuracy depicted by modern hybrid Deep-Learning-based techniques. A hybrid Deep Learning model built by stacking a Gated Recurrent Unit and Bi-Directional Long Short-Term Memory (Bi LSTM) is proposed in this research. The predictions are computed as a result of a multivariate time series analysis problem. Dynamic elements of the environment, maximum and minimum temperatures are used as input parameters for the model, with daily rainfall serving as an output parameter. The data spans over several decades, ranging from January 1950–May 2020. Predictions for a period of 15 days of the month June 2020 are made. The developed model is validated using two robust quality evaluation criteria, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The MAE value of the proposed methodology is 6.97, and the RMSE value is 10.13. Furthermore, the presented model’s predictions are confirmed by looking at the actual rainfall received by the Silonijan over a 15-day period in June 2020. Upon comprehensive analysis, it is ascertained that the proposed artificial intelligence model provides a precise estimation of the average rainfall anticipated for the town of Silojinan during the month of June 2020. This deep learning-based research could aid in the accurate and timely forecast of rainfall in places prone to flooding or drought, thus helping in disaster management.

Landfill site selection in an urban area like National Capital Territory (NCT) of Delhi is a challenging task due to shortage of suitable land and other environmental, economic and social parameters. This study focusses on the utilisation of geographic information system, open-source libraries and remote sensing for identification of potential landfill sites in Delhi NCT. Multi-criteria decision analysis (MCDA) and other GIS-based approaches are used for analysing various natural parameters derived using remote sensing satellite data products. Resourcesat LISS-III and Sentinel-2 multispectral satellite data is used for deriving the required parametric layers. Zones in the vicinity of monuments, transport, canals, drainages, lineaments are avoided altogether. Results reveal overall, most suitable places for landfill site in study area is around 4.05 sq. km (0.27%), moderately suitable places are 14.68 sq. km (0.98%), least suitable places are 25.46 sq. km (1.71%) and not suitable places is 1,419.11 sq. km (95.62%).

IMPORTANCE: A clear dosing regimen for methotrexate in psoriasis is lacking, and this might lead to a suboptimal treatment. Because methotrexate is affordable and globally available, a uniform dosing regimen could potentially optimize the treatment of patients with psoriasis worldwide. OBJECTIVE: To reach international consensus among psoriasis experts on a uniform dosing regimen for treatment with methotrexate in adult and pediatric patients with psoriasis and identify potential future research topics. DESIGN, SETTING, AND PARTICIPANTS: Between September 2020 and March 2021, a survey study with a modified eDelphi procedure that was developed and distributed by the Amsterdam University Medical Center and completed by 180 participants worldwide (55 [30.6%] resided in non-Western countries) was conducted in 3 rounds. The proposals on which no consensus was reached were discussed in a conference meeting (June 2021). Participants voted on 21 proposals with a 9-point scale (1-3 disagree, 4-6 neither agree nor disagree, 7-9 agree) and were recruited through the Skin Inflammation and Psoriasis International Network and European Academy of Dermatology and Venereology in June 2020. Apart from being a dermatologist/dermatology resident, there were no specific criteria for participation in the survey. The participants worked mainly at a university hospital (97 [53.9%]) and were experienced in treating patients with psoriasis with methotrexate (163 [91.6%] had more than 10 years of experience). MAIN OUTCOMES AND MEASURES: In a survey with eDelphi procedure, we tried to reach consensus on 21 proposals. Consensus was defined as less than 15% voting disagree (1-3). For the consensus meeting, consensus was defined as less than 30% voting disagree. RESULTS: Of 251 participants, 180 (71.7%) completed all 3 survey rounds, and 58 participants (23.1%) joined the conference meeting. Consensus was achieved on 11 proposals in round 1, 3 proposals in round 2, and 2 proposals in round 3. In the consensus meeting, consensus was achieved on 4 proposals. More research is needed, especially for the proposals on folic acid and the dosing of methotrexate for treating subpopulations such as children and vulnerable patients. CONCLUSIONS AND RELEVANCE: In this eDelphi consensus study, consensus was reached on 20 of 21 proposals involving methotrexate dosing in patients with psoriasis. This consensus may potentially be used to harmonize the treatment with methotrexate in patients with psoriasis.

Both energy conservation and the use of renewable resources are necessary due to the global increase in energy demand. A useful technique for energy storage, when renewable energy sources are available, is a thermochemical energy storage system that relies on the interaction of gases with solids. From this vantage point, hydrogen offers a sustainable and regenerative response to this pressing issue. In line with that, herein, the operation of a novel two‐stage hydrogen‐based thermochemical energy storage system (TS‐H‐TCES) is proposed to attain a higher energy density and is analyzed with the help of the thermodynamic cycle. The proposed system operates at 298, 373, 403, and 423 K as atmospheric temperature (Tatm), waste heat input temperature (Tm), storage temperature (Ts), and upgraded/enhanced heat output temperature (Th), respectively. For the given operating temperature, the thermodynamic performance of TS‐H‐TCES is evaluated using experimentally measured pressure–concentration isotherms of LaNi4.7Al0.3, LaNi4.6Al0.4, and MmNi4.6Al0.4. The maximum coefficient of performance, second law efficiency (ηII), and thermal energy storage density are found to be 0.67, 0.70, and 220.98 kJ kg−1, respectively. The impact of operating temperatures on system performance is also investigated, which is important in choosing the best temperature range for a certain application. The proposed two‐stage thermochemical energy storage (TES) system can be operated using a combination of low‐ and high‐pressure metal hydrides (MH). The operating temperature can be varied based on the selection of MH. Herein, LaNi4.7Al0.3, LaNi4.6Al0.4and MmNi4.6Al0.4are used with operating temperatures of 298, 373, 403, and 423 K.

This review presents the detailed account of factors leading to cancer and design strategy for the synthesis of benzimidazole derivatives as anticancer agents. The recent survey for cancer treatment in Cancer facts and figures 2017 American Chemical Society has shown progressive development in fighting cancer. Researchers all over the world in both developed and developing countries are in a continuous effort to tackle this serious concern. Benzimidazole and its derivatives showed a broad range of biological activities due to their resemblance with naturally occurring nitrogenous base i.e. purine. The review discussed benzimidazole derivatives showing anticancer properties through a different mechanism viz. intercalation, alkylating agents, topoisomerases, DHFR enzymes, and tubulin inhibitors. Benzimidazole derivatives act through a different mechanism and the substituents reported from the earlier and recent research articles are prerequisites for the synthesis of targeted based benzimidazole derivatives as anticancer agents. The review focuses on an easy comparison of the substituent essential for potency and selectivity through SAR presented in figures. This will further provide a better outlook or fulfills the challenges faced in the development of novel benzimidazole derivatives as anticancer.

BackgroundBacterial infections account for a significant proportion of neonatal and infant mortality globally. We aimed to identify predictors of death in infants with probable serious bacterial infection (PSBI) defined as signs/symptoms of possible serious bacterial infection along with baseline C-reactive protein (CRP) ≥12 mg/l.MethodsWe did a secondary analysis using the data collected from 700 infants with PSBI who participated in a randomized controlled trial in India in which zinc or placebo was given in addition to the standard antibiotics. Logistic regression was used to estimate the associations between relevant variables and death within 21 days.ResultsThose infants who were fed cow’s milk or formula before the illness episode had 3.7-fold (95% confidence interval (CI) 1.5–9.3) and 5.3-fold (95% CI 2.0–13.6) higher odds of death, respectively. Lethargy (odds ratio (OR) 2.4, 95% CI 1.1–5.4) and CRP (OR 1.9, 95% CI 1.1–3.3) were also independent predictors of death. In the model including only clinical features, female gender (OR 2.25, 95% CI 1.0–5.0), abdominal distention (3.7, 95% CI 1.1–12.3), and bulging fontanelle (5.8, 95% CI 1.1–30.5) were also independent predictors for death.ConclusionFormula or cow milk feeding prior to the illness, lethargy at the time of presentation, and high serum CRP levels predicted death in infants with PSBI.

ABSTRACTThe concept of static flood inundation extent libraries and their utilisation to anticipate the extent of inundation to alert and evacuate the population likely to get affected has been suggested by many researchers in different prototype studies. Actual implementation of the concept for a nation like India demands an automated practical operational software framework for systematic organisation, retrieval and visualisation of flood inundation extent libraries in a Geographic Information System (GIS) environment. Implementation of a software framework in a Web GIS environment facilitates decision-makers to access the inundation library with a functionality to overlay other spatial layers for proper situation assessment and decision-making. Utilisation of an open source software library for developing the software framework reduces the overall project cost and its re-distribution. The present work addresses the development of an automated operational framework for one of the chronically flood affected states in India (Bihar) using open source libraries for updating libraries, cataloguing, database organisation, retrieval of data and visualisation of flood extent. The developed framework first reads and arranges the flood forecast information followed by database organisation for identifying the corresponding inundation extent and other related layers available in the library for visualisation.

Environmental crises, land degradation, declining factor productivity, and farm profitability questioned the sustainability of linear economy-based existing agricultural production systems. Hence, there is a dire need to design and develop circular economy-based production systems to meet the twin objectives of environmental sustainability and food security. Therefore, the productive capacity, natural resource conserving ability, and biomass recycling potential of four intensified maize-based systems viz.Maize (Zea mays) + sweet potato (Ipomoea batatas)-wheat, maize + colocasia (Colocasia esculenta)-wheat, maize + turmeric (Curcuma longa), and maize + ginger (Zingiber officinale) were tested consecutively for three years (2020, 2021 and 22) in a fixed plot manner at Dehradun, Indian Himalayan region against the existing sole maize-wheat systems. The result showed that the maize + sweet potato-wheat system significantly reduced runoff loss (166.3 mm) over the sole maize-wheat system. The highest through fall (68.12 %) and the lowest stem flow (23.54 %) were recorded with sole maize. On the contrary, the maize + sweet potato system has the highest stem flow (36.15 %) and the lowest through fall. Similarly, the maize + sweet potato system had 5.6 times lesser soil erosion and 0.77 t ha−1higher maize productivity over the sole maize-wheat system. Furthermore, the maize + sweet potato system recorded significantly higher soil moisture (19.3%), infiltration rate (0.95 cm h−1), and organic carbon (0.78%) over the rest of the systems. The maize + sweet potato system also recycled the highest nitrogen (299.2 kg ha−1), phosphorus, (31.0 kg ha−1), and potassium (276.2 kg ha−1) into the soil system. Hence, it can be inferred that concurrent cultivation of sweet potato, with maize, is a soil-supportive, resource-conserving, and productive production model and can be recommended for achieving the circular economy targets in the Indian Himalayas.

•This work presents a state-of-the-art review of the passive solar stills.•The single-basin cascade solar system is still the most appropriate design.•Tubular stills with wicks are the most suitable design for industrial purposes.•Multiple-basin and multiple-slope passive solar still shows 85 percent yield productivity.•It is more efficient to use a hemispherical condenser cover type solar still as opposed to a hemispherical basin type solar still.

Serious bacterial infections are a major cause of death in early infancy in developing countries. Inexpensive and accessible interventions that can add to the effect of standard antibiotic treatment could reduce infant mortality. We measured the effect of zinc as an adjunct to antibiotics in infants with probable serious bacterial infection.

Thirty patients (20 males, 10 females) with widespread alopecia areata (25 extensive alopecia areata, 5 alopecia areata) for a mean period of 4.2 years were included in the study. All patients above 12 years were administered 5 mg dexamethasone oral pulse on two consecutive days every week. Three children (<12 years) received 2.5 mg to 3.5 mg dexamethasone oral biweekly pulse. Patients who had received treatment for a minimum period of 12 weeks were evaluated for terminal hair growth. Complete to excellent (75–95%) hair growth was observed in 16 (63.3%) patients. Growth was good (50–74%) in 2 cases and poor (<50%) in 3 (10%) cases. Six (20%) patients has no growth of terminal hair. Complete to excellent growth of hair was obtained after a mean period of 5.35 months (range 3–10 months). Relapse occurred in one case each after three and six months but hair regrew with re‐treatment.

Three hundred and fifty six patients (234 males, 122 females) with alopecia areata were classified according to Ikeda's classification. The common type of alopecia areata was most frequently seen in 239 (67.13%) patients, followed by atopic in 60 (16.85%), prehypertensive in 48 (13.4%), and autoimmune/endocrine in 9 (2.52%) patients. Severe alopecia did not occur with a higher frequency in atopic or endocrine/autoimmune alopecia areata than in the common type (p>0.05). Prehypertensive alopecia areata had the lowest frequency of severe alopecia in the present study. The odds for developing severe alopecia were highest (2.6) when onset was before 16 years of age, followed by female sex (2.12), atopy (0.86), autoimmune/endocrine (0.53), and prehypertensive (0.28) types. Alopecia areata should be broadly classified as childhood (<16 years) and adult onset with subtypes of atopic, autoimmune/endocrine, and common type under both. The prehypertensive type should be combined with the common type of alopecia areata.

•Densities and speeds of sound values of investigated mixtures have been measured.•V23E, V123Eand(κSE)23, (κSE)123of the studied mixtures have been estimated by employing the measured data.•The calculated data have been analyzed in terms of Graph and PFP theories.•The V23E, V123Eand(κSE)23, (κSE)123values predicted by Graph theory compare well with experimental values.

•ρ, u, CPmdata of mixtures have been reported in the range (293.15–308.15) K.•VmE, κSEand CPmEdata have been estimated using measured data.•VmE, κSEand CPmEvalues tested in terms of Graph theory.•Estimated VmE, κSEand CPmEvalues are comparable with experimental values.

•Densities, ρ123and speed of sound, u123values of ternary mixtures have been measured at 4 temperatures.•The experiemntal data have been utilized to determine V123Eand (κSE)123data of mixtures.•The calculated data have been analyzed in terms of graph theory.•The V123Eand (κSE)123values predicted by graph theory compare well with experimental values.

We report on our systematic and detailed study of fabrication and characterization of polycarbonate thin-film optical waveguides. Various waveguide properties, such as refractive index, optical loss, waveguide thickness, dispersion as a function of temperature of waveguides and substrates, and the effect of thickness gradient on optical guiding losses, have been reported. A comparative study of the properties of waveguides fabricated with dioxane and tetrahydrofuran as solvents is also presented.

IntroductionNeisseria gonorrhoeaemultiantigen sequence typing (NG-MAST) is a highly discriminatory technique for assessing the genetic diversity of N. gonorrhoeae(NG) and has also been put forward as a tool for predicting specific antimicrobial resistance (AMR) phenotypes. In light of the above, the present study was undertaken to investigate the molecular epidemiology of NG in India and to examine if it can be used as a means for predicting AMR.MethodsA total of 204 consecutive NG isolates collected between April 2010 - October 2013 were investigated. Antimicrobial susceptibility testing was done using disc diffusion method and E test and the results interpreted using the breakpoint criteria of CDS technique. NG-MAST was performed as described previously. WHO N. gonorrhoeaereference strains F, G, K-P were used as controls. Association between NG-MAST sequence type (ST) and antimicrobial susceptibility was probed using χ2and fisher’s exact tests.ResultsRates of resistance to classical antibiotics were high. Decreased susceptibility (DS) to ceftriaxone (MIC 0.032–0.25 µg/ml) was seen in 7.3% while azithromycin resistance (MIC ≥1 µg/ml) in 2.5% isolates. A total of 202 NG isolates were assigned into 108 different STs while 2 were not typable, The high genetic diversity arose from the allelic combination of 80 porand 44 tbpBalleles and the overall mean genetic distance was 85.5 (SE 4.6) nucleotide differences. Out of 108 STs, 84 (77.8%) were novel. The majority of STs (75.9%, 82 of 108) were represented by singletons, whereas the remaining STs included between 2 and 38 isolates. The most common STs were ST6058 (n=38, 18.8%), ST2990 (n=6, 2.9%), ST6069, ST9775, ST9783, ST9875 (n=5, 2.5% each). There was a significant association between ST6058 and resistance to penicillin (p=0.00) and tetracycline (p=0.00) and ST6069 and ST 6083 and DS to ceftriaxone (p=0.00 and p=0.01 respectively). ConclusionThe present study highlights a heterogeneous gonococcal population in India. Our data, although on a limited number of NG isolates, testify to an association between genotype and AMR phenotype.