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Limited treatment options, long duration of treatment and associated toxicity adversely impact the physical and mental well-being of multidrug-resistant tuberculosis (MDR-TB) patients. Despite research advances in the microbiological and clinical aspects of MDR-TB, research on the psychosocial context of MDR-TB is limited and less understood. We searched the databases of PubMed, MEDLINE, Embase and Google Scholar to retrieve all published articles. The final manuscripts included in the review were those with a primary focus on psychosocial issues of MDR-TB patients. These were assessed and the information was thematically extracted on the study objective, methodology used, key findings, and their implications. Intervention studies were evaluated using components of the methodological and quality rating scale. Due to the limited number of studies and the multiple methodologies employed in the observational studies, we summarized these studies using a narrative approach, rather than conducting a formal meta-analysis. We used 'thematic synthesis' method for extracting qualitative evidences and systematically organised to broader descriptive themes. A total of 282 published articles were retrieved, of which 15 articles were chosen for full text review based on the inclusion criteria. Six were qualitative studies; one was a mixed methods study; and eight were quantitative studies. The included studies were divided into the following issues affecting MDR-TB patients: a) psychological issues b) social issues and economic issues c) psychosocial interventions. It was found that all studies have documented range of psychosocial and economic challenges experienced by MDR-TB patients. Depression, stigma, discrimination, side effects of the drugs causing psychological distress, and the financial constraints due to MDR-TB were some of the common issues reported in the studies. There were few intervention studies which addressed these psychosocial issues most of which were small pilot studies. There is dearth of large scale randomized psychosocial intervention studies that can be scaled up to strengthen management of MDR-TB patients which is crucial for the TB control programme. This review has captured the psychosocial and economic issues challenging MDR patients. However there is urgent need for feasible, innovative psychosocial and economic intervention studies that help to equip MDR-TB patients cope with their illness, improve treatment adherence, treatment outcomes and the overall quality of life of MDR-TB patients.

Pulmonary nodule is one of the lung diseases and its early diagnosis and treatment are essential to cure the patient. This paper introduces a deep learning framework to support the automated detection of lung nodules in computed tomography (CT) images. The proposed framework employs VGG-SegNet supported nodule mining and pre-trained DL-based classification to support automated lung nodule detection. The classification of lung CT images is implemented using the attained deep features, and then these features are serially concatenated with the handcrafted features, such as the Grey Level Co-Occurrence Matrix (GLCM), Local-Binary-Pattern (LBP) and Pyramid Histogram of Oriented Gradients (PHOG) to enhance the disease detection accuracy. The images used for experiments are collected from the LIDC-IDRI and Lung-PET-CT-Dx datasets. The experimental results attained show that the VGG19 architecture with concatenated deep and handcrafted features can achieve an accuracy of 97.83% with the SVM-RBF classifier.

Lane detection (LD) under different illumination conditions is a vital part of lane departure warning system and vehicle localization which are current trends in the future smart cities. Recently, vision-based methods are proposed to detect lane markers in different road situations including abnormal marker cases. However, an inclusive framework for driverless cars has not been introduced yet. In this work, a novel LD and tracking method is proposed for the autonomous vehicle in the IoT-based framework (IBF). The IBF consists of three modules which are vehicle board (VB), cloud module (CM), and the vehicle remote controller. The LD and tracking are carried out initially by the VB, and then, in case of any failure, the whole set of data is passed to CM to be processed and the results are sent to the VB to perform the appropriate action. If the CM detects a lane departure, then the autonomous vehicle is driven remotely and the VB would be restarted. In addition to the proposed framework, an illumination invariance method is presented to detect lane markers under different light conditions. The simulation results with real-life data demonstrate lane-keeping rates of 95.3% and 95.2% in tunnels and on highways, respectively. The approximate processing time of the proposed method is 31 ms/frame which fulfills the real-time requirements.

Human papillomaviruses (HPVs) are circular, nonenveloped small double-stranded DNA viruses that infect stratified epithelium and can cause a number of life-threatening diseases. HPV is the central risk factor for developing cervical cancer and is estimated that approximately 98% of this disease is associated with oncogenic types of HPV. HPV infection leads to an estimated 266,000 cervical cancer deaths annually. Therefore, the objective of this study was to determine the prevalence of HPV infection and risk factors associated with cervical lesion among women attending the cervical cancer screening clinic at the Ethiopian Family Guidance Association, Addis Ababa. A cross-sectional study was conducted to determine the prevalence of HPV infection. Data were collected using a questionnaire and samples leftover from cervical screening were taken. The leftover swab was air dried and DNA was extracted and amplified by using a PCR. A total of 247 women were included in the study. The prevalence of HPV was 9.72% among the population studied. Of all participants, 27.13% were positive for cervical intraepithelial neoplasia-1 (CIN1). CIN1 positivity was found in half of HPV positive women. Among HPV positive women, half of them had started sexual intercourse at ages 12–17 years and 41.66% were women who gave birth at ages 12–17 years. The high prevalence of HPV and the CIN1 positive group were ages 36–57 and women with multiple sexual partners. The other groups with the highest CIN1 positive were 22.39% grade (9–12) and 20.9% primary (1–8) and uneducated women. Among HPV positive women, 83.33% had an abortion history and 80% miscarried in the first trimester. Among the CIN1 positives, 53.73% had more than two sexual partners. Among HPV positive women, half of them were users of contraception methods. In conclusion, the highest prevalence of HPV is among women who began sexual intercourse earlier and who gave birth at 12–17 years of age, have an abortion history, with MSP and oral contraceptive methods users. In addition to HPV, early pregnancy and sexual intercourse at 12–17 years of age, abortion, MSP, and oral hormonal contraceptives are factors in cervical cancer. Finally, most women do not have enough knowledge and awareness about cervical cancer and the risk factor.

A critical global policy question is how the environmental management interventions could be repurposed to meet the sustainable development goals and their target for food security, climate protection, and environmental sustainability. A common challenge facing food systems in developing countries is to improve agricultural productivity to ensure food security for all without increasing the emission of greenhouse gases (GHGs) from agriculture. Climate-smart agriculture (CSA) approaches help to reduce GHG emissions from agriculture and address the challenges of climate change (CC) and food insecurity. Yet, CSA lack understanding of the institutional arrangements and policy processes. This paper examines 38 aspects to assess the institutional and policy status for CC mitigation and adaptation and CSA in Nagaland, India. Furthermore, we use these aspects to develop a scale to measure the policy and institutional environment for mitigation and adaptation of CC and implementation of CSA. Nagaland is relatively in a better position in nine aspects, although it can improve. Methodologically, the scale developed in this paper and the identified factors can help study the institutional and policy status of a country, state, or region. We identify several implications for understanding CC and CSA institutions and policies for informing policy research and practice.

The single image dehazing is performed using atmospheric scattering model (ASM). The ASM is based on transmission and atmospheric light. Thus, accurate estimation of transmission is essential for quality single image dehazing. Single image dehazing is of prime focus in research nowadays. The proposed work presents a fast and accurate method for single image dehazing. The proposed method works in two folds; (i) An adaptive dehazing control factor is proposed to estimate accurate transmission, which is based on difference of maximum and minimum color channel of hazy image, and (ii) a mathematical model to compute probability of a pixel to be at short distance is presented, which is utilized to locate haziest region of the image to compute the value of atmospheric light. The proposed method obtains visually compelling results, and recovers the information content (such as structural similarity, color, and visibility) accurately. The computation speed and accuracy of the proposed method is proved using quantitative and qualitative comparison of results with state of the art dehazing methods.

The best biocontroller Bacillus subtilis produced silver nanoparticles (AgNPs) with a spherical form and a 62 nm size through green synthesis. Using UV-vis spectroscopy, PSA, and zeta potential analysis, scanning electron microscopy, and Fourier transform infrared spectroscopy, the properties of synthesized silver nanoparticles were determined. Silver nanoparticles were tested for their antifungicidal efficacy against the most virulent isolate of the Aspergillus flavus fungus, JAM-JKB-BHA-GG20, and among the 10 different treatments, the treatment T6 [PDA + 1 ml of NP (19: 1)] + Pathogen was shown to be extremely significant (82.53%). TG-51 and GG-22 were found to be the most sensitive groundnut varieties after 5 and 10 days of LC-MS QTOF infection when 25 different groundnut varieties were screened using the most toxic Aspergillus flavus isolate JAM- JKB-BHA-GG20, respectively. In this research, the most susceptible groundnut cultivar, designated GG-22, was tested. Because less aflatoxin (1651.15 g.kg -1 ) was observed, treatment T8 (Seed + Pathogen + 2 ml silver nanoparticles) was determined to be much more effective. The treated samples were examined by Inductively Coupled Plasma Mass Spectrometry for the detection of metal ions and the fungicide carbendazim. Ag particles (0.8 g/g -1 ) and the fungicide carbendazim (0.025 g/g -1 ) were found during Inductively Coupled Plasma Mass Spectrometry analysis below detectable levels. To protect plants against the invasion of fungal pathogens, environmentally friendly green silver nanoparticle antagonists with antifungal properties were able to prevent the synthesis of mycotoxin by up to 82.53%.

Purpose The antifolate drug methotrexate (MTX) was introduced into clinical practice about 60 years ago and remains an important component of different acute lymphoblastic leukemia (ALL) treatment protocols. It acts by inhibiting several enzymes in the folate pathway, thereby resulting in the disruption of folate homeostasis. To date, treatment regimens have not been personalized despite there being experimental evidence that gene polymorphisms of folate metabolizing enzymes affect MTX response. The aim of this review was to evaluate the influence of genetic polymorphisms of the enzymes involved in the MTX pathway on ALL treatment outcomes and identify factors underlining the failure to personalize MTX therapy. Methods We conducted a literature search in PUBMED and Goggle scholar using the following key words: methotrexate, polymorphism, acute lymphoblastic leukemia, pharmacogenetics, pharmacogenomics and personalized mediciner. Results The reasons for the failure to personalize MTX therapy may be due to (1) most studies involving single-center, small-sized cohorts, (2) differences in MTX dose across different protocols, (3) failure to consider minimal residual disease as a risk factor for post-induction treatment, (4) differences in outcome criteria between studies and (5) failure to consider the folate levels of a patient before initiation of MTX therapy. Although high-throughput techniques allow the mapping of thousands of genetic polymorphisms in a single run, it remains a major challenge to dissect out folate-metabolizing enzymes which have a high impact on the efficacy and toxicity of MTX and which, therefore, could be the targets for intervention. Conclusions Prospective pharmacogenetic studies which consider all of the above-mentioned factors should be undertaken to facilitate the design of personalized MTX treatment for ALL patients.

Single image dehazing (SID) solves the atmospheric scattering model (ATSM). The ill-defined nature of the SID makes it a challenging problem. The transmission is the prime parameter of ATSM. Hence, accurate transmission is essential for quality of SID. The existing methods of SID estimate the transmission based on priors with strong assumptions (such as dark channel prior). These methods do not recover original colors, structure and visibility due to wrong transmission under invalidity of these assumptions. Therefor, the difference channel (DCH) is proposed to estimate accurate transmission. The DCH non-linearly translates the minimum channel of hazy image into minimum channel of haze-free image, which is used to compute the value of transmission. The DCH is based on an observation that difference of maximum and minimum color channel of the hazy image is negatively correlated with depth. The proposed method is able to recover the details from hazy image in the form of structure, edges, corners, colors and visibility due to the DCH. The accuracy and robustness of the proposed method is proved by comparing the results with known dehazing methods based on qualitative and quantitative analysis using benchmark data sets.

COVID-19 has inundated the entire world disrupting the lives of millions of people. The pandemic has stressed the healthcare system of India impacting the psychological status and functioning of health care workers. The aim of this study is to determine the burnout levels and factors associated with the risk of psychological distress among healthcare workers (HCW) engaged in the management of COVID 19 in India. A cross-sectional study was conducted from 1 September 2020 to 30 November 2020 by telephonic interviews using a web-based Google form. Health facilities and community centres from 12 cities located in 10 states were selected for data collection. Data on socio-demographic and occupation-related variables like age, sex, type of family, income, type of occupation, hours of work and income were obtained was obtained from 967 participants, including doctors, nurses, ambulance drivers, emergency response teams, lab personnel, and others directly involved in COVID 19 patient care. Levels of psychological distress was assessed by the General health Questionnaire -GHQ-5 and levels of burnout was assessed using the ICMR-NIOH Burnout questionnaire. Multivariable logistic regression analysis was performed to identify factors associated with the risk of psychological distress. The third quartile values of the three subscales of burnout viz EE, DP and PA were used to identify burnout profiles of the healthcare workers. Overall, 52.9% of the participants had the risk of psychological distress that needed further evaluation. Risk of psychological distress was significantly associated with longer hours of work (≥ 8 hours a day) (AOR = 2.38, 95% CI(1.66-3.41), income≥20000(AOR = 1.74, 95% CI, (1.16-2.6); screening of COVID-19 patients (AOR = 1.63 95% CI (1.09-2.46), contact tracing (AOR = 2.05, 95% CI (1.1-3.81), High Emotional exhaustion score (EE ≥16) (AOR = 4.41 95% CI (3.14-6.28) and High Depersonalisation score (DP≥7) (AOR = 1.79, 95% CI (1.28-2.51)). About 4.7% of the HCWs were overextended (EE>18); 6.5% were disengaged (DP>8) and 9.7% HCWs were showing signs of burnout (high on all three dimensions). The study has identified key factors that could have been likely triggers for psychological distress among healthcare workers who were engaged in management of COVID cases in India. The study also demonstrates the use of GHQ-5 and ICMR-NIOH Burnout questionnaire as important tools to identify persons at risk of psychological distress and occurrence of burnout symptoms respectively. The findings provide useful guide to planning interventions to mitigate mental health problems among HCW in future epidemic/pandemic scenarios in the country.