Evaluation of IPM modules for the management of fruit borer and fruit rot diseases in tomato, Lycopersicon esculentum Miller

Among, five IPM modules tested against tomato fruit borer and fruit rot on tomato, the IPM module (M3) consisting of use of pheromone traps (@ 12 traps/ha) just after transplanting the tomato crop , Lycopersicon esculentum Miller for monitoring the population of Helicoverpa armigera . followed by three foliar sprays commencing with a mixture of lamba-cyhalothrin 5EC @ 0.8ml/L(0.04%) and Dithane Z-78 (Zineb) @ 2.5g/L (0.25%) after 10 days of appearance of moths in the traps (after 30 days of transplanting) followed by spray with a mixture of Helicide (Ha NPV) 100 LE @ 0.5ml/L+ Indofil M-45 @ 2.5g/L (0.25%) + Gur (0.05%) + Tween 80 (0.05%) after 15 days of first spray followed by spray with a mixture of lamba-cyhalothrin 5EC @ 0.8ml/L(0.04%) and moximate (cymoxanil + mancozeb) @ 0.25% after 15 days of the second spray was found to be most effective in minimizing the infestation of fruit borer and fruit rot diseases with 50.00% and 63.45% reduction over control, respectively. This module was also found to be most economic resulting in highest marketable fruit yield (255.94q/ha) and maximum net returns (Rs.10.36) per rupee spent. The present findings are of immense utility as there will be reduction in number of sprays resulting in the cost of production of tomato crop

Digital health rehabilitation can improve access to care in spinal cord injury in the UK: A proposed solution

© 2020, University Library System, University of Pittsburgh. All rights reserved. Lack of specialist beds, inadequate finance and shortage of skilled staff make it difficult for Spinal Cord Injury Centres (SCICs) in the United Kingdom (UK) to admit all newly injured individuals. Length of stay of those admitted can be too brief. At discharge, follow-up care is sparse and inadequate. We therefore propose that specialist spinal units redefine their roles and act as catalysts to build capacity by enhancing expertise in the wider community. SCICs can devolve certain tasks locally to less specialised units with their support, training, and guidance. This Commentary further proposes that use of Digital Health Technologies, (i.e., to deploy telemedicine, telehealth, and telerehabilitation), can enhance rehabilitation opportunities. The authors set-forth their vision for a comprehensive web portal that will serve as a primary resource for evidence-based practice, information on guidelines, care pathways, and protocols of SCI management. At any stage during the acute management of SCI and following discharge, rehabilitation specialists could conduct remote consultation with persons with SCI and acute care specialists via the web portal, allowing timely access to specialist input and better clinical outcomes. The proposed portal would also provide information, advice and support to persons with SCI and their family members. The strategic use of digital health technologies has been shown to result in cost and time savings and increase positive outcomes

Prevalence of hepatitis C in patients with chronic kidney disease at a tertiary care hospital in north India: a retrospective analysis

Background: Hepatitis C and chronic kidney disease (CKD) both present an unsolved public health problem Hepatitis C virus (HCV) is easily transmitted in haemodialysis units and by kidney transplantation. HCV leads to increased mortality and morbidity due to cirrhosis and hepatocellular carcinoma, while accelerating the progression of CKD. The aim of the  study was to describe the demographic, clinical/biochemical profile and prevalence of patients with CKD who have HCV infection.Methods: This was a retrospective analysis of patients with CKD who presented to out/in patient department of medicine in a tertiary care center in Jammu from a period of Feb 2016 to Nov 2018. Detailed clinical history along with previous lab reports were noted and tests for HCV infection were conducted in all patients. Diagnosis of HCV was made via HCV RNA(RT PCR) and positive  Anti HCV IgG serology.Results: Total 67 patients were included with median age of 54 years (range 43-72 years) with majority 76.1% being males, and 71.6% within 41-60 years age group. 31.4% were HCV positive out of which 81% were males. 7 patients were found to have co-infection with HIV and HBsAg. Genotype 1 (72%) was found to be more common than Genotype 3. Ultrasonography and Upper GI endoscopy showcased 57% with dilated spleenoportal axis  and oesophageal varices respectively.Conclusions: Prevalence of HCV infection in CKD patients is high with genotype 1 being commonest. False negative Anti HCV antibody is common hence screening with HCV RNA is recommended. Strict universal precautions should be employed in hospitals and dialysis units to prevent transmission

Customized stiffness control strategy for a six-bar linkage-based gait rehabilitation robot

Lower limb rehabilitation robots based on linkage-based mechanisms have recently drawn significant attention in the field due to their numerous advantages. The control of previously proposed linkage-based gait rehabilitation robotic orthoses has been achieved using constant speed control without consideration for the interaction forces. However, such an approach can be harmful to people with stroke since the level of disability varies among individuals, and it may cause potential injuries when excessive force is applied by the robot. To overcome this limitation and improve the rehabilitation process, it is necessary to recognize the force exerted by the person during walking and adjust the robot's assistive torque accordingly, to provide synchronized motion. Thus, in this work, a human-cooperative approach based on a stiffness control strategy for the six-bar linkage-based gait rehabilitation robot is presented. The proposed methodology can serve as a solid foundation for developing a human-cooperative approach for linkage-based lower limb rehabilitation robotic orthoses. The control was validated and tested with eight healthy human subjects. As a result, customized robotic assistance with this mechanism can be provided during training to meet the individual needs of stroke patients, which can lead to increased engagement and contribution, thus improving treatment outcomes

Utilizing the intelligence edge framework for robotic upper limb rehabilitation in home

Robotic devices are gaining popularity for the physical rehabilitation of stroke survivors. Transition of these robotic systems from research labs to the clinical setting has been successful, however, providing robot-assisted rehabilitation in home settings remains to be achieved. In addition to ensure safety to the users, other important issues that need to be addressed are the real time monitoring of the installed instruments, remote supervision by a therapist, optimal data transmission and processing. The goal of this paper is to advance the current state of robot-assisted in-home rehabilitation. A state-of-the-art approach to implement a novel paradigm for home-based training of stroke survivors in the context of an upper limb rehabilitation robot system is presented in this paper. First, a cost effective and easy-to-wear upper limb robotic orthosis for home settings is introduced. Then, a framework of the internet of robotics things (IoRT) is discussed together with its implementation. Experimental results are included from a proof-of-concept study demonstrating that the means of absolute errors in predicting wrist, elbow and shoulder angles are 0.89180,2.67530 and 8.02580, respectively. These experimental results demonstrate the feasibility of a safe home-based training paradigm for stroke survivors. The proposed framework will help overcome the technological barriers, being relevant for IT experts in health-related domains and pave the way to setting up a telerehabilitation system increasing implementation of home-based robotic rehabilitation. The proposed novel framework includes: • A low-cost and easy to wear upper limb robotic orthosis which is suitable for use at home. • A paradigm of IoRT which is used in conjunction with the robotic orthosis for home-based rehabilitation. • A machine learning-based protocol which combines and analyse the data from robot sensors for efficient and quick decision making

A Technical Comparative Heart Disease Prediction Framework Using Boosting Ensemble Techniques

This paper addresses the global surge in heart disease prevalence and its impact on public health, stressing the need for accurate predictive models. The timely identification of individuals at risk of developing cardiovascular ailments is paramount for implementing preventive measures and timely interventions. The World Health Organization (WHO) reports that cardiovascular diseases, responsible for an alarming 17.9 million annual fatalities, constitute a significant 31% of the global mortality rate. The intricate clinical landscape, characterized by inherent variability and a complex interplay of factors, poses challenges for accurately diagnosing the severity of cardiac conditions and predicting their progression. Consequently, early identification emerges as a pivotal factor in the successful treatment of heart-related ailments. This research presents a comprehensive framework for the prediction of cardiovascular diseases, leveraging advanced boosting techniques and machine learning methodologies, including Cat boost, Random Forest, Gradient boosting, Light GBM, and Ada boost. Focusing on “Early Heart Disease Prediction using Boosting Techniques”, this paper aims to contribute to the development of robust models capable of reliably forecasting cardiovascular health risks. Model performance is rigorously assessed using a substantial dataset on heart illnesses from the UCI machine learning library. With 26 feature-based numerical and categorical variables, this dataset encompasses 8763 samples collected globally. The empirical findings highlight AdaBoost as the preeminent performer, achieving a notable accuracy of 95% and excelling in metrics such as negative predicted value (0.83), false positive rate (0.04), false negative rate (0.04), and false development rate (0.01). These results underscore AdaBoost’s superiority in predictive accuracy and overall performance compared to alternative algorithms, contributing valuable insights to the field of cardiovascular health prediction

Three-Stage Design Analysis and Multicriteria Optimization of a Parallel Ankle Rehabilitation Robot Using Genetic Algorithm

This paper describes the design analysis and optimization of a novel 3-degrees of freedom (DOF) wearable parallel robot developed for ankle rehabilitation treatments. To address the challenges arising from the use of a parallel mechanism, flexible actuators, and the constraints imposed by the ankle rehabilitation treatment, a complete robot design analysis is performed. Three design stages of the robot, namely, kinematic design, actuation design, and structural design are identified and investigated, and, in the process, six important performance objectives are identified which are vital to achieve design goals. Initially, the optimization is performed by considering only a single objective. Further analysis revealed that some of these objectives are conflicting, and hence these are required to be simultaneously optimized. To investigate a further improvement in the optimal values of design objectives, a preference-based approach and evolutionary-algorithm-based nondominated sorting algorithm (NSGA II) are adapted to the present design optimization problem. Results from NSGA II are compared with the results obtained from the single objective optimization and preference-based optimization approaches. It is found that NSGA II is able to provide better design solutions and is adequate to optimize all of the objective functions concurrently. Finally, a fuzzy-based ranking method has been devised and implemented in order to select the final design solution from the set of nondominated solutions obtained through NSGA II. The proposed design analysis of parallel robots together with the multiobjective optimization and subsequent fuzzy-based ranking can be generalized with modest efforts for the development of all of the classes of parallel robots

An empirical investigation on the deployment of Operational excellence in SMEs

Purpose: This study investigates the quantitative aspect of the various strains of Operational excellence (OE) and “Competitive-potential (CP)” in the SME sector. It has five steps, i.e., identifying the key performance constructs of OE and their hypothesized relationship pattern from literature, validating these constructs through factor analysis, formalizing their empirical relationships by structural-equation-modeling (SEM), path analysis of performance constructs with the empirical results, and lastly proposing a framework for OE deployment in SMEs. Design/methodology/approach: Data for the deployment scores of Operational excellence procedures (OEPs) were collected through a structured questionnaire survey. Nine hundred participants from a stratified random sample were approached for the survey, and 473 responses were received. Sample stratification was based on Gender, Education, Experience, Position, Department, and Industry. Respondents had 5 to 30 years of experience managing manufacturing operations, holding the Manager position and above. Findings: The path analysis of the structural model provides unique insights into OE’s practical aspects in SMEs (Small and Medium Enterprises). Such as Contractual-conformance and Process-efficiency play pivotal roles as both have a significant positive impact on CP. Supplier efficacy, Consistency, and Product-excellence do not improve CP unless mediated by Contractual-conformance or Process-efficiency. Research limitations/implications: The study provides important implications for academia, policymakers, and managers. The study identifies and validates the operational excellence key performance practices and proposes a framework for manufacturing organizations. SME managers can follow the framework to develop effective operational excellence strategies to help them achieve their organizational goals. Additionally, the study emphasizes the need for continuous culture in SMEs, which will help to support operational excellence deployment. Overall, the implications presented in the study will help SMEs to enhance their competitiveness and operational performance. Originality/value: The study explores the empirical investigation of the operational excellence deployment in SMEs. The study uses a mixed method approach for research design, including qualitative and quantitative approaches, and uses SEM to test the proposed framework. Validation of OE’s six key performance constructs and establishing their empirical relation is an attempt to advance the Operations excellence theory. Unlike large enterprises, SMEs demonstrate an incohesive response to the practices pertaining to Supplier efficacy, Consistency, and Product-excellence. This unique response pattern requires special treatment, which is incorporated into the proposed framework

Comparative proteomic analyses of avirulent, virulent and clinical strains of mycobacterium tuberculosis identify strain-specific patterns

Mycobacterium tuberculosis is an adaptable intracellular pathogen, existing in both dormant as well as active disease-causing states. Here, we report systematic proteomic analyses of four strains, H37Ra, H37Rv and clinical isolates BND and JAL, to determine the differences in protein expression patterns that contribute to their virulence and drug resistance. Resolution of lysates of the four strains by liquid chromatography, coupled to mass spectrometry analysis, identified a total of 2161 protein groups covering ∼54% of the predicted M. tuberculosis proteome. Label-free quantification analysis of the data revealed 257 differentially expressed protein groups. The differentially expressed protein groups could be classified into seven K-means cluster bins, which broadly delineated strain-specific variations. Analysis of the data for possible mechanisms responsible for drug resistance phenotype of JAL suggested that it could be due to a combination of overexpression of proteins implicated in drug resistance and the other factors. Expression pattern analyses of transcription factors and their downstream targets demonstrated substantial differential modulation in JAL, suggesting a complex regulatory mechanism. Results showed distinct variations in the protein expression patterns of Esx and mce1 operon proteins in JAL and BND strains, respectively. Abrogating higher levels of ESAT6, an important Esx protein known to be critical for virulence, in the JAL strain diminished its virulence, although it had marginal impact on the other strains. Taken together, this study reveals that strain-specific variations in protein expression patterns have a meaningful impact on the biology of the pathogen