Evaluating trends in groundwater quality of coastal alluvial aquifers of Eastern India for sustainable groundwater management.

Groundwater is a precious natural element which ensures global water, food, and environmental security in the twenty-first century. Systematic monitoring, sustainable utilization, preservation and remediation are critical aspects of efficient groundwater resource management. This study deals with the analysis of spatial variability and trend in groundwater chemistry as well as identification of possible contamination sources in a coastal alluvial basin of eastern India. Pre-monsoon season data of 14 groundwater-quality variables measured in 'leaky confined' and 'confined' aquifers were analyzed for ten years (2012-2021). Mann-Kendall (M-K) test with the Sen's Slope Estimator, Spearman Rank Order Correlation (SROC) and Innovative Trend Analysis (ITA) tests were employed to assess decadal (2012-2021) trends. The analysis of the results indicated that the 'critical' water-quality parameters exceeding the acceptable limits for drinking are TDS, EC, TH, pH, Mg2+, Na+, K+, Fe2+, HCO3-, Cl- and NO3-. Weak negative correlations between rainfall and groundwater elevation for both the aquifers reveal poor rainfall recharge into the aquifers. Therefore, a reduction in groundwater abstraction and augmentation of groundwater recharge is recommended. Trend analysis results indicated that the concentrations of TH, Mg2+ and Fe2+ exhibit significant increasing trends in the 'leaky confined aquifer'. In contrast, significant rising trends in TH, Mg2+, Na+, Fe2+, HCO3- and NO3- concentrations are identified in the 'confined aquifer'. Further, the SROC test could not detect the trends in groundwater quality in most blocks and for many parameters. On the other hand, the ITA test revealed significant trends in most of the parameters of the two aquifers in almost all the blocks. Trend magnitudes of the groundwater-quality parameters based on the Sen's Slope Estimator and the ITA test vary from -63.7 to 58.65 mg/L/year for TDS, -14 to 39.07 mg/L/year for TH, -1.49 to 4.83 mg/L/year for Mg2+, -7.14 to 22.96 mg/L/year for Na+, -0.32 to 0.44 mg/L/year for Fe2+, -8.33 to 20.75 mg/L/year for HCO3-, -26.52 to 31.01 mg/L/year for Cl- and 1.29 to 3.76 mg/L/year for NO3- over the study area. The results of M-K and ITA tests were found in agreement in all the blocks for both the aquifers. Groundwater contamination in both the aquifers can be attributed to weathering, geogenic processes, mineral dissolution, seawater intrusion, poor recharge pattern and injudicious anthropogenic activities. It is strongly recommended that concerned authorities urgently formulate efficient strategies for managing groundwater quality in the 'leaky confined' and 'confined' aquifers which serve as vital sources of drinking and irrigation water supplies in the study area.

Deep neural network to detect COVID-19: one architecture for both CT Scans and Chest X-rays.

Since December 2019, the novel COVID-19's spread rate is exponential, and AI-driven tools are used to prevent further spreading [1]. They can help predict, screen, and diagnose COVID-19 positive cases. Within this scope, imaging with Computed Tomography (CT) scans and Chest X-rays (CXRs) are widely used in mass triage situations. In the literature, AI-driven tools are limited to one data type either CT scan or CXR to detect COVID-19 positive cases. Integrating multiple data types could possibly provide more information in detecting anomaly patterns due to COVID-19. Therefore, in this paper, we engineered a Convolutional Neural Network (CNN) -tailored Deep Neural Network (DNN) that can collectively train/test both CT scans and CXRs. In our experiments, we achieved an overall accuracy of 96.28% (AUC = 0.9808 and false negative rate = 0.0208). Further, major existing DNNs provided coherent results while integrating CT scans and CXRs to detect COVID-19 positive cases.

Shallow Convolutional Neural Network for COVID-19 Outbreak Screening Using Chest X-rays.

Among radiological imaging data, Chest X-rays (CXRs) are of great use in observing COVID-19 manifestations. For mass screening, using CXRs, a computationally efficient AI-driven tool is the must to detect COVID-19-positive cases from non-COVID ones. For this purpose, we proposed a light-weight Convolutional Neural Network (CNN)-tailored shallow architecture that can automatically detect COVID-19-positive cases using CXRs, with no false negatives. The shallow CNN-tailored architecture was designed with fewer parameters as compared to other deep learning models. The shallow CNN-tailored architecture was validated using 321 COVID-19-positive CXRs. In addition to COVID-19-positive cases, another set of non-COVID-19 5856 cases (publicly available, source: Kaggle) was taken into account, consisting of normal, viral, and bacterial pneumonia cases. In our experimental tests, to avoid possible bias, 5-fold cross-validation was followed, and both balanced and imbalanced datasets were used. The proposed model achieved the highest possible accuracy of 99.69%, sensitivity of 1.0, where AUC was 0.9995. Furthermore, the reported false positive rate was only 0.0015 for 5856 COVID-19-negative cases. Our results stated that the proposed CNN could possibly be used for mass screening. Using the exact same set of CXR collection, the current results were better than other deep learning models and major state-of-the-art works.

α,ß-Didehydrosuberoylanilide hydroxamic acid (DDSAHA) as precursor and possible analogue of the anticancer drug SAHA.

An alternate synthetic route to the important anticancer drug suberoylanilide hydroxamic acid (SAHA) from its α,ß-didehydro derivative is described. The didehydro derivative is obtained through a cross metathesis reaction between a suitable terminal alkene and N-benzyloxyacrylamide. Some of the didehydro derivatives of SAHA were preliminarily evaluated for anticancer activity towards HeLa cells. The administration of the analogues caused a significant decrease in the proliferation of HeLa cells. Furthermore, one of the analogues showed a maximum cytotoxicity with a minimum GI50 value of 2.5 µg/mL and the generation of reactive oxygen species (ROS) as some apoptotic features.

Effect of free energy barrier on pattern transition in 2D diffusion limited aggregation morphology of electrodeposited copper.

Fractal like morphology is a very interesting feature during electrodeposition of metals and shows pattern transition with changes in deposition conditions. In this article, we have explained the thermal effects in the two dimensional DLA morphology on the basis of thermal free energy and another free energy barrier resulting from the electric field. The results obtained from free energy hypothesis are consistent with experiments showing the transition voltage for electrodeposition of copper ions to be around 6 V.

Cross metathesis-mediated synthesis of hydroxamic acid derivatives.

An alternative synthesis of α,ß-unsaturated hydroxamates via cross metathesis between a class-I olefin and N-benzyloxyacrylamide is reported. The reaction proceeds better in the presence of Grubbs' second generation catalyst within short time and in good yields (57-85%) with a range of substrates. Subsequent hydrogenation of each of the CM products delivers the title compounds in moderate to very good yield (70-89%). An important demonstration of the protocol is the preparation of the unusual amino acid component of the bioactive cyclic peptide Chap-31.

Ag(I)-Catalyzed Domino Cyclization-Addition Sequence with Simultaneous Carbonyl and Alkyne Activation as a Route to 2,2'-Disubstituted Bisindolylarylmethanes.

An efficient synthesis of symmetrical 3, 3'-bisindolylarylmethanes with various substituents on the indole moiety has been developed by Ag(I)-catalyzed cycloisomerization and an deoxygenative addition sequence on o-alkynylanilines and aryl aldehydes. Ag(I) is proposed to activate alkyne unit and carbonyl moiety simultaneously leading to a domino first 5-endo-dig indole annulation, addition to C═O, second indole annulation, and its dehydroxylative addition.

Prevalence of Psychiatric Morbidity Among Undergraduate Students of a Dental College in West Bengal.

BACKGROUND: Stresses of medical course affects the academic performance as well as physical and psychological health of the students negatively. In the present day scenario every one of us has vulnerability to have psychiatric morbidity. Like other young adults, undergraduate dental students are similarly vulnerable to turmoil due to academic and social stresses, which often hamper the educational achievement. Early detection and treatment of psychological morbidities shorten the suffering leading to less social impairment in long term. AIM: The aim of this study was to assess the psychiatric morbidity of dental students and the factors affecting their mental health. SETTINGS AND DESIGN: This cross sectional, descriptive and correlation study was conducted in North Bengal Dental College, a rural dental college of West Bengal, India. MATERIALS AND METHODS: The study sample consisted of a total of 89 dental students. The student enrollment was done by "simple random sampling method". The semi-structured proforma and the General Health Questionnaire (GHQ)-28 were used to collect data and to assess the psychiatric morbidity. STATISTICAL ANALYSIS: Pearson's correlation followed by multivariate linear regression analysis was done to assess the effect of academic achievement, positive and negative event on the GHQ total score. RESULTS: The overall mean GHQ total score in the study population was 5.33, with a SD of 4.85 which was above the cutoff (>4) score. Karl Pearson correlation co-efficient r-values for GHQ total score with 'academic achievement' and 'negative events' score were 0.718 and 0.628 respectively and p-values were 0.001 and 0.001. CONCLUSION: The poor academic performance and negative events had strong impact on psychological morbidity of dental students. The findings of our study can't be generalized for all undergraduate dental student due to small sample size and non inclusion of many other variables.

Prevalence of psychiatric co-morbidity among patients attending dental OPD and the role of consultation-liaison psychiatry in dental practice in a tertiary care general hospital.

BACKGROUND: Psychiatric co-morbidities are frequent among patients attending dental OPD, some of which go unrecognized and hence untreated. AIMS: The present study has been carried out to detect the psychiatric co-morbidities among dental patients and determine the scope of consultation-liaison (C-L) psychiatry in a rural teaching hospital regarding comprehensive management of the patients. SETTINGS AND DESIGN: This cross-sectional, descriptive type study was conducted in a multi-speciality tertiary care teaching hospital in the northern part of West Bengal, India. MATERIALS AND METHODS: One hundred patients attending the dental OPD were randomly included in the study and every patient was consecutively referred to psychiatry department for assessment, during the period from 1(st) November 2013 to 30(th) April 2014. All referred patients were clinically examined and psychiatric co-morbidity was assessed by the help of General Health Questionnaire (GHQ)-28 and Mental Status Examination. STATISTICAL ANALYSIS USED: The data were subjected to statistical package for social sciences (SPSS), version 16, and statistically analyzed using Cross tab and Chi test. P <0.05 was considered to be statistically significant. RESULTS: The commonest dental illness was dental caries (22%). More than two-third of the patients had psychiatric co-morbidity according to GHQ-28 total score. Sixty-eight patients were diagnosed to have mental disorder on mental status examination. Somatoform disorder (25%) was the commonest type of mental disorder, followed by mixed anxiety and depression (14%). CONCLUSIONS: This study has pointed the need for psychological examination of patients visiting dental specialty with unexplained physical symptoms. Such patients can be identified and treated, provided a psychiatric consultation service exists.

Comparative evaluation of different forms of calcium hydroxide in apexification.

BACKGROUND: One out of every two children sustains a dental injury most often between 8 and 10 years of age. Majority of these teeth subsequently become non-vital and most often with immature apex. Management of these teeth is an enormous challenge for lack of apical stop. Calcium hydroxide in various formulations has maximum literature support in favor of successful apexification or induced apical closure. AIM: The aim of the following study is to determine the efficacy of calcium hydroxide in a different formulation to induce apexification. MATERIALS AND METHODS: The present study was undertaken on 51 children of 8-10 years of age (both sexes) at Dr. R Ahmed Dental College and Hospital from April 2006 to March 2007. All children had one or two maxillary permanent central incisor (s), non-vital and apices open. In all the cases, apexification was attempted with either calcium hydroxide mixed with sterile distilled water, or calcium hydroxide plus iodoform in methyl cellulose base, or calcium hydroxide plus iodoform in polysilicone oil base. The success of apexification was determined on the basis of clinical and radiographic criteria. RESULTS: In the pre-operative asymptomatic cases (72.55%), failure occurred in only 5.45% cases and pre-operative symptomatic cases failure rate was as high as 35.71%. Success rate was 94.6% in cases with narrow open apices, whereas 64.28% in wide open apices. In cases with pre-existing apical radiolucencies, successful apexification occurred in 63.63% and success rate was 92.5% in the cases without pre-existing apical radiolucencies. Average time consumed for apexification was minimum with calcium hydroxide plus iodoform in polysilicone oil base. CONCLUSION: The overall success rate observed to be 86.27%, which is in close proximity to the findings of most of the previous studies across the globe.