Zinc silicate phosphor: Insights of X-ray induced and temperature enabled luminescence.

The present investigation deals with the effect of calcination temperature on the structural and thermoluminescent (TL) properties of Zn2 SiO4 materials. For this study, Zn2 SiO4 was prepared via a simple hydrothermal route and calcinated at temperatures from 700°C to 1100°C in an air atmosphere. TL data of all Zn2 SiO4 samples showed two peaks at around 240°C and 330°C due to the formation of the luminescence centre during X-ray irradiation. More interestingly, the Zn2 SiO4 sample calcinated at 900°C exhibited a shift in the TL peak (282°C and 354°C) with an optimal TL intensity attributed to its good crystallinity with a well-defined hexagonal plate-like morphology. X-ray-irradiated Zn2 SiO4 samples calcinated at 900°C exhibited a high-temperature TL glow curve peak, suggesting that the present material could be used for high-temperature dosimetry applications.

Continuous Ambulatory Peritoneal Dialysis Peritonitis Guidelines - Consensus Statement of Peritoneal Dialysis Society of India - 2020.

Continuous ambulatory peritoneal dialysis (CAPD) related peritonitis is a major cause of technique failure, morbidity, and mortality in patients on CAPD. Its prevention and management is key to success of CAPD program. Due to variability in practice, microbiological trends and sensitivity towards antibiotics, there is a need for customized guidelines for management of CAPD related peritonitis (CAPDRP) in India. With this need, Peritoneal Dialysis Society of India (PDSI) organized a structured meeting to discuss various aspects of management of CAPDRP and formulated a consensus agreement which will help in management of patients with CAPDRP.

Analysis of tebuconazole residues in coconut water, kernel and leaves using LC-MS/MS.

A method was validated for determining tebuconazole residues in coconut water, kernel and leaves using Liquid chromatography-Mass spectrometry/Mass spectrometry (LC-MS/MS) with electro spray ionization in positive ion mode. Samples were extracted with acetonitrile and subsequent clean-up was done using dispersive solid phase extraction. Recovery ranged between 70 and 114.39 % and the RSD was between 0.64 and 10.24 %. Root feeding studies with tebuconazole @ 5 and 10 mL/100 mL of water/tree revealed the presence of tebuconazole residues in coconut leaves until three days after treatment but dissipated to below quantifiable limit on 5th day at single dose while the residues went below quantifiable limit after 10 days at double the dose. Residues were below quantifiable limit in coconut water and kernel until three days. Data obtained from the study were used for estimating the risks associated with the exposures to tebuconazole residues in coconut.

Factors Influencing Scales of Burden, Coping Mechanisms, and Quality of Life in Caregivers of Hemodialysis Patients in Andhra Pradesh, India.

BACKGROUND: Evaluation of factors influencing scales of burden, coping mechanisms, and quality of life (QOL) in caregivers of hemodialysis (HD) patients may lead to the revision of interventions aimed at the betterment of QOL of caregivers of HD patients. In this study, we investigated the influence of demographic, social, and clinical variables on burden, coping mechanisms, and QOL in caregivers of HD patients. METHODS: In this prospective study, 150 caregivers of HD patients were recruited. Assessment of burden, coping strategies, and QOL were made by the Zarit Burden Interview, Revised Ways of Coping, and Short Form-36 QOL. The role of age, gender, and social and clinical variables on these constructs was investigated using multivariate analysis of variance. RESULTS: The mean age was 43.86 ± 1.11 years. Males outnumbered females. Most were Hindu, married, primary school educated, unemployed, spouses, caring the patients, and suffering from chronic diseases for <5 years. In multivariate analysis of variance, effect of age on physical functioning (PF), general health (GH), and physical component summary (PCS) score (P < 0.01); gender on burden, distancing, seeking social support, role limitation due to emotional problem, and pain (P < 0.05); role limitations due to physical health, energy/fatigue (EF), emotional well-being, PCS, and mental component summary (MCS) score (P < 0.01); religion on PF (P < 0.05); marital status on burden and GH (P < 0.05); PF and PCS (P < 0.01); relationship of caregiver with the patient on PCS (P < 0.05); EF and MCS (P < 0.01); and presence of chronic diseases on GH and social functioning (P < 0.01) were observed. CONCLUSION: The role of demographic, social, and clinical variables should be taken into consideration while initiating therapies for reducing the burden and improving the QOL of caregivers.

Machine learning techniques based on security management in smart cities using robots.

BACKGROUND: Nowadays, the growth of smart cities is enhanced gradually, which collects a lot of information and communication technologies that are used to maximize the quality of services. Even though the intelligent city concept provides a lot of valuable services, security management is still one of the major issues due to shared threats and activities. For overcoming the above problems, smart cities' security factors should be analyzed continuously to eliminate the unwanted activities that used to enhance the quality of the services. OBJECTIVES: To address the discussed problem, active machine learning techniques are used to predict the quality of services in the smart city manages security-related issues. In this work, a deep reinforcement learning concept is used to learn the features of smart cities; the learning concept understands the entire activities of the smart city. During this energetic city, information is gathered with the help of security robots called cobalt robots. The smart cities related to new incoming features are examined through the use of a modular neural network. RESULTS: The system successfully predicts the unwanted activity in intelligent cities by dividing the collected data into a smaller subset, which reduces the complexity and improves the overall security management process. The efficiency of the system is evaluated using experimental analysis. CONCLUSION: This exploratory study is conducted on the 200 obstacles are placed in the smart city, and the introduced DRL with MDNN approach attains maximum results on security maintains.

A novel method for segmenting brain tumor using modified watershed algorithm in MRI image with FPGA.

The goal of the segmentation of brain images is to separate the images in different non-compatible homogenous areas reflecting the numerous anatomical structures. Brain segmentation by magnetic resonance has numerous implications for diagnosing brain disorganizations such as Alzheimer's, Parkinson-related syndrome among others. However, it is not an simple job to automatically segment the MR image. The main motive of this study is to provide a better segmentation approach for the segment of the ROI (Region Of Interest) region from the MRI image by solving the issues that currently exist in the literary works. MRI segmentation is not a trivial task, because acquired MR images are imperfect and are often corrupted by noise and other image artifacts. The variety in technologies for image processing has contributed to the creation in numerous image segmentation techniques. That is because there is no universal approach, nor are all methods necessarily appropriate for a specific form of picture suitable for all pictures. Other approaches still use the gray level histogram, for example, while others integrate detailed spatial picture details for bleeding conditions. Some methods use statistical techniques, but some do incorporate existing information to enhance segmentation efficiency. Some methods utilize probabilistic or fuzzy methods. Yet there are certain inconveniences of all the current processes. Therefore, we have intended to propose a new segmentation approach for the ROI region segmentation. The proposed work comprised of three phases namely preprocessing, edge detection and segmentation. At first, the MRI images are extracted from the database and that each of the input images is enhanced by applying a high pass filter. After completing the preprocessing method, the enhanced canny edge detection (ECED) approach is used to enhance the image. After that, the images are given to the modified watershed segmentation (MWS) algorithm which separates the ROI part from MRI Image. The testing consequences demonstrate that the proposed system accomplishes to give the good result related to the available strategies. Xilinx Virtex-5 FPGA is used to implement in this paper.

Effect of Variables on Quality of Life among Caregivers of Patients Undergoing Peritoneal Dialysis.

BACKGROUND: Most of the studies carried out abroad showed the effect of one or two variables on the constructs of burden, coping strategies, and quality of life (QOL) but nil in India context. These constructs change by cultural factors. The evaluation of variables influencing these constructs may be helpful in fine tuning the interventions to reduce the burden and to improve the QOL of caregivers of patients undergoing peritoneal dialysis (PD). AIM: The aim of this study was to investigate the impact of demographic, social and clinical variables on burden, coping strategies, and QOL in caregivers of patients undergoing PD. MATERIALS AND METHODS: In this prospective study, we recruited 100 caregivers of patients undergoing PD and made assessment on burden, coping strategies, and QOL and evaluated the effect of demographic, social, and clinical variables on these constructs. RESULTS: None of the studied variables showed effect on burden and coping strategies. Age, gender, duration of caregiving, presence of chronic disease, and duration of the presence of chronic disease showed a significant effect on QOL. CONCLUSION: The impact of demographic and clinical variables on QOL suggests these variables should be given adequate attention while developing interventions for alleviating the burden and improving the QOL of caregivers of patients undergoing PD.

Study to Test and Operationalize Preventive Approaches for CKD of Undetermined Etiology in Andhra Pradesh, India.

INTRODUCTION: High prevalence of chronic kidney disease (CKD) not associated with known risk factors has been reported from coastal districts of Andhra Pradesh. The Study to Test and Operationalize Preventive Approaches for Chronic Kidney Disease of Undetermined Etiology in Andhra Pradesh (STOP CKDu AP) aims to ascertain the burden (prevalence and incidence) of CKD, the risk factor profile, and the community perceptions about the disease in the Uddanam area of Andhra Pradesh. METHODS: Study participants will be sampled from the Uddanam area using multistage cluster random sampling. Information will be collected on the demographic profile, occupational history, and presence of conventional as well as nonconventional risk factors. Glomerular filtration rate (GFR) will be estimated using the Chronic Kidney Disease Epidemiology Collaboration equation, and proteinuria will be measured. All abnormal values will be confirmed by repeat testing after 3 months. Cases of CKD not associated with identified etiologies will be identified. Biospecimens will be stored to explore future hypotheses. The entire cohort will be followed up every 6 months to determine the incidence of CKD and to identify risk factors for decline in kidney function. Qualitative studies will be performed to understand the community perceptions and expectations with respect to the interventions. IMPLICATIONS: CKD is an important public health challenge in low- and middle-income countries. This study will establish the prevalence and determine the incidence of CKD not associated with known risk factors in a reported high-burden region, and will provide insights to help design targeted health systems responses. The findings will contribute to the policy development to tackle CKD in the region and will permit international comparisons with other regions with similar high prevalence.

Characteristics of Burden, Coping Strategies, and Quality of Life: The Effect of Age, Gender, and Social Variables in Caregivers of Renal Transplanted Patients from Southern Andhra Pradesh, India.

BACKGROUND: Evaluation of burden, coping strategies, and quality of life (QOL) in caregivers may lead to specific interventions to reduce the burden among caregivers. METHODS: In this prospective study, characteristics of burden, coping strategies, and QOL in caregivers was investigated and also studied the effect of age, gender, and social variables on these concepts. RESULTS: Mean burden score of the caregivers was 28.66 ± 2.02. Thirty percent of caregivers had mild-to-moderate burden followed by moderate-to-severe burden (20%). Seeking social support was the dominant coping strategy used by the caregivers. Role limitations due to the physical health (RLDPH) and role limitations due to emotional problem (RLDEP) were compromised subscales of QOL. The mean score of RLDPH (P = 0.007) and RLDEP (P = 0.014) were found to be significantly higher in males than that of females. Marital status, education, type of relationship with the patient, religion, occupation, and duration of care giving showed significant effect on burden, coping strategies, and QOL. Lower emotional well-being (P = 0.003) and escape avoidance (P = 0.000) in males and lower physical component (PC) (P = 0.002) in females and lower PC (P = 0.000) and escape avoidance (P = 0.001) were found to be the significant predictors of burden in caregivers of renal transplanted patients. CONCLUSION: Predictors of burden and QOL subscales varies by gender. Social and clinical variables influence the QOL subscales. Gender- and social group-specific interventions rather than global interventions may reduce the burden of caregivers.

Controlled infusion of intravenous cardiac drugs using global optimization.

OBJECTIVES: The objective of the study is to develop an automatic drug infusion control system during cardiovascular surgery. MATERIALS AND METHODS: Based on the clinical drug dosage analysis, the modeling of cardiovascular system with baroreceptor model is mathematically modeled using compartmental approach, considering the relationship between the volume and flow rate of blood during each heartbeat. This model is then combined with drug modeling of noradrenaline and nitroglycerine by deriving the volume and drug mass concentration equations, based on pharmacokinetics and pharmacodynamics of the drugs. The closed-loop patient models are derived from the open-loop data obtained from the physiology-drug model with covariate as age. The proportional-integral controller is designed based on optimal values obtained from bacterial foraging-oriented particle swarm optimization algorithm. The controllers are implemented individually for each control variable such as aortic pressure and cardiac output (CO), irrespective of varying weights based on the relative gain array analysis which depicts the maximum influence of cardiac drugs on control variables. RESULTS: The physiology-drug model output responses are simulated using MATLAB. The controlled responses of aortic pressure and CO with infusion rate of cardiac drugs are obtained. The robustness of the controller is checked by introducing variations in cardiovascular model parameters. The efficiency of the controller during normal and abnormal conditions is compared using time domain analysis. CONCLUSIONS: The controller design was efficient and can be further improved by designing switching-based controllers.

Inflammation and nutritional status assessment by malnutrition inflammation score and its outcome in pre-dialysis chronic kidney disease patients.

BACKGROUND: Malnutrition-inflammation complex syndrome (MICS), hyperhomocysteinemia, calcium and phosphate levels derangement have been predicted as important contributing factors for the progression of cardiovascular burden. Among patients with earlier stage of CKD, hypoalbuminaemia and inflammation deliberated as non-traditional cardiovascular risk factors, which add more burden to circulatory disease, mortality and rapid advancement to CKD stage 5. AIM: The aim of the study is to evaluate inflammation and nutritional status of CKD patients not on dialysis using Malnutrition inflammation score (MIS) and to verify the association with mortality in the follow-up period. METHODS AND MATERIAL: In this prospective cohort study 129 (66 males, 63 females) pre-dialysis CKD patients enrolled between June 2013 to August 2014 and censored until March 2017. Malnutrition and Inflammation assessed using Malnutrition inflammation score. Blood urea nitrogen, serum creatinine, albumin, Interleukin - 6, highly sensitive C reactive protein (hsCRP), total cholesterol and anthropometric data were analyzed. RESULTS: The Malnutrition inflammation score in pre-dialysis CKD patients ranged from 0 to 18 with the median score of two. During 36 or more months of follow-up, there were 30 (23.2%) deaths, 35 (27%) patients initiated on hemodialysis, one (0.7%) patient was initiated on peritoneal dialysis, two (1.4%) patients underwent renal transplantation and two (1.4%) patients were lost for follow-up. In this study, 33% had varying degree of malnutrition and inflammation. Patients who had MIS ≥7 had significant increase in IL-6 (p = 0.003) and HsCRP levels (p < 0.001) when compared with other tertiles of MIS. ROC curve analysis of MIS showed 56.5% sensitivity and 81% specificity in predicting death rate (AUC 0.709; 95% CI 0.604-0.815, p < 0.001). Kaplan-Meier survival analysis showed MIS ≥7 had a strong association (log rank test, p < 0.001) with mortality during 36 and more months of follow-up time. In unadjusted analyses, MIS (HR 1.140; 95% CI 1.054-1.233; p < 0.05) and HsCRP (HR 2.369; 95% CI 1.779-3.154; p < 0.001) found to be predictors of mortality. MIS and HsCRP remained predictors of mortality even after adjustments. CONCLUSIONS: This study shows MIS is an important factor that determines mortality in pre-dialysis CKD patients during 36 and more months of follow-up time. Patients with MIS ≥7 have high risk for mortality and needs close monitoring. In clinical setting application of MIS has a greater utilization in pre-dialysis CKD patients. Further research with longitudinal assessment of MIS and its association with outcomes are warranted. Pre-dialysis CKD patients should be assessed for their nutritional status and inflammation using MIS regularly to prevent malnutrition and its associated complications through appropriate medical and nutritional intervention.

A clinical and electrophysiological study of peripheral neuropathies in peritoneal dialysis patients: Our experience from rural South India.

The objective was to study the prevalence, clinical features, electrophysiological features, and severity of peripheral neuropathy in chronic kidney disease (CKD) patients on peritoneal dialysis (PD) and effect of the presence of diabetes mellitus (DM). Between May 2015 and December 2016, 100 CKD patients on PD were assessed. The prevalence of peripheral neuropathy was 65% based on clinical symptoms and 92% based on electrophysiological parameters. The mean age was 55.7 ± 10.9 years. About 64% were male. Twelve patients (12%) had motor weakness, 64 patients (64%) had positive symptoms and 60 patients (60%) had negative symptoms. Autonomic symptoms were seen in 14 patients (14%). Definite damage was seen in 68 patients (68%), early damage was seen in 16 patients (16%). In PD patients with DM (n = 50), 50 patients (100%) had definite damage. In PD patients without DM (n = 50), 18 patients (36%) had definite damage, 16 patients (32%) had early damage. In CKD patients on PD, patients aged >50 years (definite damage in 75.7%) showed more severe peripheral neuropathy when compared to patients aged ≤50 years (definite damage in 53%). Most common nerves involved in the present study were median motor nerve, sural nerve, ulnar sensory nerve, common peroneal nerve, posterior tibial nerve followed by the median sensory nerve. Peripheral neuropathy is common in CKD patients on PD, with higher prevalence and severity in elderly females and diabetics. Rationale management of diabetes in CKD patients on PD probably lowers the prevalence and severity of peripheral neuropathy.

Carbamylated Hemoglobin can Differentiate Acute Kidney Injury from Chronic Kidney Disease.

Carbamylated hemoglobin (CarHb) was found to have a potential role in the differentiation of patients with acute kidney injury (AKI) from chronic kidney disease (CKD). This study was aimed at the evaluation of the diagnostic performance and usefulness of CarHb in the differentiation of AKI from CKD. Forty patients with renal disease and twenty age- and sex-matched healthy controls were included in the study. Urea, creatinine, Hb, and CarHb were measured in all the subjects. Patients with AKI and CKD were found to have significantly increased levels of CarHb when compared to controls (P < 0.05 for both groups). Patients with CKD had significantly increased levels of CarHb when compared to patients with AKI (P < 0.05). CarHb showed significant positive correlation with urea in patients with renal disease (r = 0.776, P < 0.0001). Significant area under curve (AUC = 0.840, P < 0.0001) was obtained for CarHb and a cut-off value of 98.33 µg VH/g Hb resulted with the best combination of 85% sensitivity and 75% specificity. CarHb may provide clinical utility since patients with AKI and CKD have similar clinical presentation usually. A cut-off value of 98.33 µg VH/g Hb has been found to be useful to differentiate AKI from CKDs.

Polymeric nanocomposites for the removal of Acid red 52 dye from aqueous solutions: Synthesis, characterization, kinetic and isotherm studies.

Polymeric nanocomposites polyaniline-polyvinylpyrrolidone (PAPV) and polyaniline-polyvinylpyrrolidone-neodymium/zinc oxide (PAPV-NZO) were synthesized for the effective dye removal through adsorption process. Neodymium doped zinc oxide (NZO) with various proportions of neodymium were prepared by chemical co-precipitation method and incorporated into the copolymer matrix via oxidative polymerization technique. NZO nanoparticles were characterized by X-ray diffraction (XRD) and the morphological features, and functional group linkages of the PAPV-NZO were confirmed by scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR) analyses. Acid red 52 dye was chosen as a synthetic toxic effluent to study the removal efficiency of the nanocomposites with different parameters viz. time, concentration, adsorbent dosage and pH. The studies were performed under visible light irradiation and the residual dye concentration was analyzed by UV-visible spectrophotometer. PAPV-NZO exhibited greater dye removal rate than PAPV due to the incorporation of NZO that enhanced the conducting nature, stability and surface area of PAPV-NZO. The optimum concentration of the dye and the adsorbent dosage of the PAPV-NZO were determined to be 80 ppm and 50 mg, respectively. At acidic condition of pH 2, the removal capacity of PAPV-NZO was found 99.6%. Kinetic and isotherm models have been studied on the optimum parameters to investigate the nature of the adsorption process. The process followed pseudo second order kinetics and was best suited to the Langmuir model. The maximum dye adsorption capacity of PAPV-NZO was estimated to be 159.36 mg g-1. From the results, it can be assured that the PAPV-NZO can be effectively used for the removal of dye pollutants in water.

Quantitative trait loci mapping for stomatal traits in interspecific hybrids of Eucalyptus.

Eucalyptus is an important industrial species with tolerance to drought and salt stress. Genetic improvement activities including quantitative trait loci (QTL) mapping for pulping and adventitious rooting traits are in progress, but no information is available on the genomic regions on adaptive traits such as stomatal characteristics. In this study, an interspecific cross between Eucalyptus tereticornis and E. grandis was generated for the development of genetic map and QTL identification for stomatal traits. Simple sequence repeats (SSRs), inter-simple sequence repeats (ISSRs) and sequence related amplified polymorphism (SRAP)markers were used for genotyping the F1 individuals. Parent-specific geneticmaps (female, 1023.56 cM;male, 1049.64cM) and consensus map (1049.4 cM) were developed. QTL analysis was carried out to identify the chromosomal regions affecting stomatal density, area and pore length in adaxial and abaxial leaf surface. Seven QTLs were identified with phenotypic variation of 11.36 to 27.30% for stomatal density, area and pore length. Correlation of stomatal traits when combined with growth and wood properties would have greater implications for generation of stress tolerant eucalypt hybrids with higher productivity and adaptability.

Synthesis of novel Dy3+ activated Ba2 CaZn2 Si6 O17 phosphors for white light-emitting diodes.

Dysprosium ion (Dy3+ ) activated Ba2 CaZn2 Si6 O17 phosphors were synthesized using high temperature solid-state reaction method. Powder X-ray diffraction (PXRD) analysis confirmed the phase formation of the as-prepared phosphors. Scanning electron microscopy (SEM) analysis disclosed an agglomeration of particles with an irregular morphology. Under 350 nm excitation, the emission spectrum of Dy3+ ions showed bands at 481 nm (blue), 577 nm (yellow) and 674 nm (red). The influence of the Dy3+ concentration on its emission intensity was investigated. The optimum concentration of Dy3+ ions in the Ba2 CaZn2 Si6 O17 :Dy3+ phosphors were found to be x = 0.06. The critical energy transfer distance was calculated. The fluorescence lifetime was also determined for Ba2 CaZn2 Si6 O17 :0.06Dy3+ . The Commission International deI'Eclairage (CIE) chromaticity coordinates of the phosphor were calculated to be x = 0.304, y = 0.382. The activation energy for the thermal quenching was calculated to be 0.168 eV. These results indicated that the Ba2 CaZn2 Si6 O17 :Dy3+ phosphor might be a potential candidate for near ultraviolet (NUV)-based white light-emitting diodes.

A Clinical and Electrophysiological Study of Peripheral Neuropathies in Predialysis Chronic Kidney Disease Patients and Relation of Severity of Peripheral Neuropathy with Degree of Renal Failure.

OBJECTIVE: To study the prevalence, clinical features, electrophysiological features, and severity of peripheral neuropathy in predialysis chronic kidney disease (CKD) patients with respect to severity of renal failure and presence of diabetes mellitus. MATERIALS AND METHODS: Between May 2015 and December 2016, 200 predialysis CKD patients were assessed prospectively. RESULTS: The prevalence of peripheral neuropathy in predialysis CKD patients in the present study was 45% based on clinical symptoms and 90% electrophysiologically. Mean age of 200 predialysis CKD patients who participated in the study was 53.2 ± 13.2 years. One hundred and thirty-six (68%) patients were male and 64 (32%) patients were female. Mean duration of disease was 2.2 ± 1.6 years. Nearly 45% patients of patients had asymptomatic peripheral neuropathy in the present study, which was more common in mild-to-moderate renal failure group. One hundred twenty-six patients (63%) had definite damage and 54 patients (27%) had early damage. In mild-to-moderate renal failure (n = 100) and severe renal failure patients (n = 100), 88% and 92% had significant peripheral neuropathy, respectively. Most common nerves involved were sural nerve, median sensory nerve, and ulnar sensory nerve. Diabetic patients (97%) showed more severe and high prevalence of peripheral neuropathy when compared to nondiabetic patients (83%). Most common patterns were pure axonal sensorimotor neuropathy and mixed sensorimotor neuropathy. CONCLUSION: Peripheral neuropathy is common in predialysis patients, prevalence and severity of which increases as renal failure worsens. Predialysis patients with diabetes show higher prevalence and severity of peripheral neuropathy when compared with nondiabetics.