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Salinity is a major abiotic stress that negatively impacts plant health and soil microbiota. ACC (1-aminocyclopropane carboxylic acid) deaminase producing microorganisms act as natural stress busters that protect plants from different kinds of stresses. The study focused on the isolation of potent, indigenous, multi-trait ACC deaminase producers. The shortlisted ACC deaminase producers were checked for their ability to promote growth of Cajanus cajan, and mitigate stress under laboratory conditions followed by validation of their potency in naturally saline field conditions. Physiological stress markers were assessed to evaluate the impact of salinity in plants treated with ACC deaminase producer, compared to controls. Further, the contribution of ACC deaminase in stress mitigation was demonstrated by using a chemical inhibitor for ethylene biosynthesis. This study presents a polyphasic approach, transitioning from the rhizospheric soil to the laboratory to validation in the field, and puts forth a promising eco-friendly alternative for sustainable agriculture.

Plant–microbiome interactions are significant determinant for plant growth, fitness and productivity. Depending upon the specific habitat, plants' microbial communities are classified as the rhizo-, phyllo-, and endospheric regions. Understanding the plant microbiome interactions could provide an opportunity to develop strategies for sustainable agricultural practices. There is a necessity to decipher the complex structural and functional diversity within plant microbiomes to reveal its immense potential in agriculture. The plant microbiota harbors enormous microbial communities that defy analytical methodologies to study dynamics underlying plant microbiome interactions. Findings based on conventional approaches have ignored many beneficial microbial strains, which creates a serious gap in understanding the microbial communications along with the genetic adaptations, which favors their association with host plant. The new era of next generation sequencing techniques and modern cost-effective high-throughput molecular approaches can decipher microbial community composition and function. In this review, we have presented the overview of the various compartments of plants, approaches to allow the access to microbiome and factors that influence microbial community composition and function. Next, we summarize how plant microbiome interactions modulate host beneficial properties particularly nutrient acquisition and defense, along with future agricultural applications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at. 10.1007/s12298-021-00927-1.

Sustainable management practices are the need of the hour to counter the ever-deteriorating environmental conditions in agro-ecosystems. While bioinoculants have served as eco-friendly means to mitigate stresses, their survivability and competitiveness in field conditions have been a major challenge. The present study aimed to adopt a multi-generational approach to adapt the rhizospheric microbiome of Vigna radiata, a legume consumed worldwide, under salt stress. A multi-generational plant growth experiment was set-up with induced salinity stress, employing the rhizosphere of best-performing plants from the preceding generation as inoculum for the next generation. The plant health and mitigation of salinity stress by the adapted microbiome was analyzed using plant biometrics, bacterial diversity, and stress markers. Decreased levels of salt-induced stress markers, and simultaneous improvement in plant attributes were observed with the progression of the generations. The shifts in bacterial community were prominent upon inoculation of the adapted microbiome. The treatments with the adapted microbiome in the presence of salinity stress were closer to the control sets compared to salinity-stressed treatments, indicating the efficiency of the adapted microbiome towards mitigation of salinity stress. The study demonstrates the promising potential of such an eco-friendly, microbiome-based approach for plant growth promotion and mitigation of salinity stress.

Arsenic poisoning through groundwater is the world's greatest normal groundwater catastrophe which got an immense effect on worldwide general wellbeing. India is confronting the outcomes of arsenic poisoning in the zone of Ganga Brahmaputra alluvial plains. In Bihar out of 38 districts, 18 districts are exceptionally influenced with groundwater arsenic defilement. In the present study, we have assessed the current situation of arsenic exposure in Sabalpur village of Saran district of Bihar after reporting of breast, renal, skin and thyroid cancer cases from this village along with typical symptoms of arsenicosis. Such cancer patients were identified at our institute and were taken for the study. The present investigation deals with the quantification of arsenic in groundwater, hair and nail samples as well as the survey of entire village to know the overall health status of the village people. Altogether, 128 groundwater samples through handpumps, 128 human hair and nail samples respectively were collected from over 520 households. Using the Graphite Furnace Atomic Absorption Spectrophotometer (GF-AAS), all the samples were analysed. The investigation resulted that the 61% of the analysed samples particularly the groundwater had the arsenic levels more than the permissible limit of WHO (>10µg/L) with 244.20µg/L as the greatest arsenic contamination in one of the groundwater sample. The exposure effect of hair sample was worst as 88% of all the collected samples were having high arsenic levels more than the permissible limit (>0.2mg/Kg). In case of nails samples, 92% of the samples were having high arsenic concentration more than the permissible limit (>0.5mg/Kg). The health survey study uncovered the exceptionally chronic weakness status of the village populace as individuals were experiencing the issues like asthma, anaemia, hepatomegaly, diabetes, cardiac problem, skin fungal infections, breathlessness, mental disability, etc. Few cancer cases of renal, skin, breast and cervix were also found among the population of this village. The percentage of cancer cases in this village was 0.94% that is low but it would be an aggravated situation in the near future if people will continue drinking arsenic contaminated water. Therefore, a mitigation intervention was done in March 2020 by installing an arsenic filter plant. The health situation in the present scenario is hope to restore in the village in the coming years. However, motivation and awareness among the village population is still required.

Reportedly, 300 million people worldwide are affected by the consumption of arsenic contaminated groundwater. India prominently figures amongst them and the state of Bihar has shown an upsurge in cases affected by arsenic poisoning. Escalated arsenic content in blood, leaves 1 in every 100 human being highly vulnerable to being affected by the disease. Uncontrolled intake may lead to skin, kidney, liver, bladder, or lung related cancer but even indirect forms of cancer are showing up on a regular basis with abnormal arsenic levels as the probable cause. But despite the apparent relation, the etiology has not been understood clearly. Blood samples of 2000 confirmed cancer patients were collected from pathology department of our institute. For cross-sectional design, 200 blood samples of subjects free from cancer from arsenic free pockets of Patna urban agglomeration, were collected. Blood arsenic levels in carcinoma patients as compared to sarcomas, lymphomas and leukemia were found to be higher. The geospatial map correlates the blood arsenic with cancer types and the demographic area of Gangetic plains. Most of the cancer patients with high blood arsenic concentration were from the districts near the river Ganges. The raised blood arsenic concentration in the 2000 cancer patients strongly correlates the relationship of arsenic with cancer especially the carcinoma type which is more vulnerable. The average arsenic concentration in blood of the cancer patients in the Gangetic plains denotes the significant role of arsenic which is present in endemic proportions. Thus, the study significantly correlates and advocates a strong relation of the deleterious element with the disease. It also underlines the need to address the problem by deciphering the root cause of the elevated cancer incidences in the Gangetic basin of Bihar and its association with arsenic poisoning.

We demonstrate the current state-of-the-art of a web-based photovoltaic simulation platform, which is developed within the Solar Energy Research Institute of Singapore (SERIS). This platform shall allow us to (1) dynamically upload a variety of measurements from a measurement tool within our cleanroom into a user centric database, (2) dynamically upload and execute internally and externally developed computer programs to simulate such measurements, (3) compare simulation to measurement, using automated data fitting, (4) Test/deploy machine learning applications.Using calibrated computer simulations, a large number of "simulated measurement data" can be generated, as required for the computation extensive training of an artificial neural network. However, the deployment of the neural network (prediction in a "forward modelling" as well as in a "reverse modelling" direction) is fast. Thus, using artificial neural networks, predictions and optimizations deploying machine learning will be possible.

This work aims to investigate the feasibility of employing multi-frequency bioimpedance analysis for hemodynamic assessment. Towards this, we aim to explore one of its implementations, electrical impedance spectroscopy (EIS), for estimating changes in radial artery diameter due to blood flow. Following from our previous investigations, here, we use a commercial device—the Quadra® Impedance Spectroscopy device—for impedance measurements of the forearm of three subjects under normal conditions and occluding the artery with a cuff. This was performed simultaneously with ultrasound measurements as a reference. The impedance spectra were measured over time, yielding waveforms reflecting changes due to blood flow. Contributions from the fat/muscle domains were accounted for using the occluded impedance response, resulting in arterial impedance. A modified relationship was approximated to calculate the diameter from the arterial impedance, which showed a similarity with ultrasound measurements. Comparison with the ultrasound measurements revealed differences in phase and amplitude, primarily due to the approximated relationship between impedance and diameter and neglecting the impedance phase analysis. This work shows the potential of EIS, with improvements, towards estimating blood flow-induced variation in arteries. Further analysis and improvements could help place this technology in mainstream clinical practice for hemodynamic monitoring.

Tissue phantoms are widely used as substitute materials for real tissue validation of various newly emerging biomedical technologies such as ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI). However, there is no specific recipe for fabricating skin-mimicking phantoms which can mimic both the mechanical and dielectric properties of human skin at lower frequency ranges. The objective of this paper is to present a variety of tissue-mimicking materials for filling this research gap in the lower frequency range from 20 Hz to 300 kHz. The starting point of our experiments is based on the oil-in-gelatin based tissue-mimicking materials (TMMs) that have shown to mimic the dielectric properties of human skin in higher frequency ranges. This paper examines the mechanical and dielectric performance of five major classes of tissue-mimicking materials (1) Oil-in-gelatin, (2) lignin and graphene nanopowder in gelatin, (3) gelatin and distilled water, (4) mixed oil in gelatin and distilled water, and (5) lignin in gelatin and distilled water. Mechanical and electrical testing was performed using compression testing and parallel plate method respectively. The effect of electrode polarization was considered in the measured data and the intrinsic impedance values were found to be following the Cole-Cole equation. The Young's modulus range of all tissue-mimicking materials was within the range of skin.

This work aims to compile various measurement and calibration techniques for Electroencephalogram (EEG). The objective is to provide an assessment of different components of an EEG and their significance in understanding different types of responses to stimuli. This review provides an overview of recommended electrode positions and lead systems for EEG with calibration and activation procedures. The different components of an EEG according to frequency bands – Gamma, Beta, Alpha, Theta and Delta have been discussed with emphasis on their interpretation and their role in several applications. The motivation behind this study is to provide a basic understanding of the composition of EEG, understanding the significance of each brain wave and the locations at which they are most prominent.

Localization plays a key role during autonomous operation of mobile robots in planetary exploration missions. It is a challenging task due to the uncertainty in the environment and limitations in communications. In this paper we discuss various technologies that can be considered for localization of robots in extraterrestrial environments and also analyze various methods that can be implemented using these technologies. After reviewing pros and cons of each method we finally suggest the best technique for localization considering the application of the robot.

This work presents a parametric electrical modelling of the electrical response of human forearm tissues through a simulation of Multi-frequency Electrical Bioimpedance analysis (MF-EBIA). The objective is to estimate an electrical equivalent representation for tissue response in terms of resistance and capacitance values for three tissue layers in the forearm – the fat, muscle and artery, using parametric fitting analysis. Following up from a simulation study of the human forearm model using Ansys® High Frequency Structure Simulator (HFSS), this work assumes an electrical model of the human forearm section for every tissue and calculates the electrical parameters. The tissue model was considered to be isotropic with regards to the dielectric properties and the consideration of blood flow was realised by taking three instances of radial artery diameter. The proposed model was validated by using the obtained values of model components to reproduce the overall response. The obtained values of resistance and capacitance for every tissue domain provide an insight into their significant contribution to the overall electrical response, which can be important while analysing their individual electrical behaviour and also helpful in various pre-experimental studies related to dielectric characterization of living tissues.

A computationally efficient method of three-dimensional (3-D) localization of underwater acoustic sources using an acoustic vector sensor (AVS) array is presented in this paper. Noise is modeled as a Gaussian mixture (GM), and an expectation maximization (EM) algorithm is used to estimate all the unknown parameters. The proposed method consists of an initialization stage followed by iterative updates which converge in a small number of iterations. Performance of the proposed method is better than that of existing methods, and performance of the AVS array is much better than that of the acoustic pressure sensor (APS) array.

Background: In the present times, arsenic poisoning contamination in the ground water has caused lots of health-related problems in the village population residing in middle Gangetic plain. In Bihar, about 16 districts have been reported to be affected with arsenic poisoning. For the ground water and health assessment, Simri village of Buxar district was undertaken which is a flood plain region of river Ganga. Methods: In this study, 322 water samples were collected for arsenic estimation, and their results were analyzed. Furthermore, the correlation between arsenic contamination in ground water with depth and its distance from river Ganga were analyzed. Results are presented as mean ± standard deviation and total variation present in a set of data was analyzed through one-way analysis of variance. The difference among mean values has been analyzed by applying Dunnett′s test. The criterion for statistical significance was set at P < 0.05. Results: This study shows novel findings ever done in this area. Halwa Patti and Doodhi Patti strips were the most affected strips with high-arsenic concentration in hand pumps. Furthermore, a correlation between the arsenic concentration with the depth of the hand pumps and the distance from the river Ganga was also a significant study. Conclusions: The present study concludes that in Simri village there is high contamination of arsenic in ground water in all the strips. Such a huge population is at very high risk leading the village on the verge of causing health hazards among them. Therefore, an immediate strategy is required to combat the present problem.

Background: Refractive error is the most common cause of blindness which can be corrected easily using simple modality like spectacles but because of ignorance, stigmas and cost related issues it is underutilized. Aims & Objective: Study to assess the psychosocial aspects of refractive error and effectiveness of health education in correcting stigmas related to spectacle use in high-school students of rural India. Material and Methods: This was a cross sectional study in which total of 255 high school students from a school near Bhopal were included. The responses were recorded on a pre-designed and pre-tested questionnaire. The health education was provided to all the participants and they were reassessed after one month using same questionnaire. The researcher used the STATA version 12.1 for data entry and analysis. Results: Amongst total of 255 students, 165 were males and 90 were females. During initial phase most of the respondents believed that common reasons for low vision were nutritional deficiency (68%) and bad eye care (56%). The respondents refused to use spectacles at all if needed as spectacles are cosmetically unacceptable (62%) , fear of rejection from opposite sex (54%) and likely teasing from colleagues (36%).Following health education there were statistically significant changes in the knowledge, attitude and care seeking behaviour of spectacle use. Only two parameters i.e. cosmetic acceptance of spectacles and that traditional methods were more than spectacles did not changed significantly. Conclusion: Prevalent stigmas regarding spectacle use among students of rural India were effectively corrected with health education.

This paper provides an efficient approach for text-independent speaker identification using a fused Mel feature sets and Gaussian Mixture Modeling (GMM). The individual Gaussian components of a GMM are shown to represent some speaker specific spectral shapes that are effective for modeling speaker identity. Two different set of features which are complement to each, other, Mel Frequency Cepstral Coefficient (MFCC) and Inverted Mel Frequency Cepstral Coefficient (MFCC) features are obtained for each speaker and are trained using Expectation Maximization algorithm. Two GMM models; one for MFCC feature sets, other one for IMFCC feature sets are created. During testing phase, the likelihood of unknown speaker's features with each of the GMM models is determined. By using a weighted sum of these likelihood values, a fused score is created for each speaker and speaker with maximum score is the identified speaker. The performance of this fusion GMM system is evaluated using a part of the TIMIT database consisting of 120 speakers and a maximum identification efficiency of 93.88% is achieved.