Effect of exercise on diastasis recti abdominis among the primiparous women: a quasi-experimental study

Background: Diastatis recti abdominis (DRA) occurs most commonly in pregnant women owing to weakness of the abdominal musculature resulting from maternal hormone influences and increased stretch of the rectus abdominis induced by the expanding uterus. As there are musculoskeletal complications following DRA, there is a need to implement DRA corrective exercises in preventing or treating DRA following child birth. The objective of the study was to investigate the effects of Diastasis rectus abdominis corrective exercises in reducing DRA among the primiparous women.Methods: Primiparous women who had DRA of more than 2 finger width at their umbilical level or a bulging rectus abdominis on contraction following a vaginal delivery (VD) or cesarean section (LSCS) were included as per the inclusion and exclusion criteria.Results: Fifty four and forty two women in the VD and LSCS group respectively participated in the study. Among them only 12 and 9 women from each group respectively performed the DRA corrective exercises for 6 weeks. There was a significant improvement in the reduction of DRA within the groups at p 0.05 which indicated that both the groups showed the same level of improvement.Conclusions: DRA corrective exercises performed by the primiparous women with DRA in their postpartum period immediately following ND or a month after the LSCS for 6 weeks were found to be effective in reducing DRA

ASSESSMENT OF SERUM LIPID PROFILE IN HYPERTENSIVE PATIENTS: A CASE-CONTROL STUDY

Background: Hypertension and dyslipidemia are strongly associated with each other, and they are the most common risk factors for the development of the cardiovascular disease. Aim: Compare the serum lipid profile values among hypertensive patients and non-hypertensive individuals. Method: 30 patients with Hypertension and 30 age-matched non-hypertensive controls were included in the study. From the serum, total cholesterol levels were estimated by enzymatic (CHOD-PAP) colorimetric method, triglyceride by enzymatic (GPO-PAP) method, HDL-cholesterol and LDL-cholesterol were estimated using precipitant and Friedewald formula, by using commercially available reagent kits. Lipid profiles were compared with controls. Results: The mean values of total cholesterol were significantly more in Hypertensives-202.93 ± 28.44 and normotensives-178.76 ± 37.21, P<0.006. The mean values of triglycerides were significantly more in Hypertensives-139.8 ± 18.72 and normotensives-125.8± 12.34, P<0.001. The mean values of LDL-Cholesterol were significantly more in Hypertensives-141.63 ± 11.59 and normotensives-127.83 ± 14.65, P<0.0001. Conclusions: As Dyslipidemia is associated with Hypertension, serum lipid profile may be useful in the identification of patients at risk of Hypertension. Hypertensive patients need the measurement of blood pressure and lipid profile at regular intervals to prevent Cardiovascular diseases. Keywords: Cholesterol; Cardiovascular Diseases; Hypertension; Triglycerides; Dyslipidemia

ASSESSMENT OF SERUM LIPID PROFILE IN HYPERTENSIVE PATIENTS: A CASE-CONTROL STUDY

Background: Hypertension and dyslipidemia are strongly associated with each other, and they are the most common risk factors for the development of the cardiovascular disease. Aim: Compare the serum lipid profile values among hypertensive patients and non-hypertensive individuals. Method: 30 patients with Hypertension and 30 age-matched non-hypertensive controls were included in the study. From the serum, total cholesterol levels were estimated by enzymatic (CHOD-PAP) colorimetric method, triglyceride by enzymatic (GPO-PAP) method, HDL-cholesterol and LDL-cholesterol were estimated using precipitant and Friedewald formula, by using commercially available reagent kits. Lipid profiles were compared with controls. Results: The mean values of total cholesterol were significantly more in Hypertensives-202.93 ± 28.44 and normotensives-178.76 ± 37.21, P<0.006. The mean values of triglycerides were significantly more in Hypertensives-139.8 ± 18.72 and normotensives-125.8± 12.34, P<0.001. The mean values of LDL-Cholesterol were significantly more in Hypertensives-141.63 ± 11.59 and normotensives-127.83 ± 14.65, P<0.0001. Conclusions: As Dyslipidemia is associated with Hypertension, serum lipid profile may be useful in the identification of patients at risk of Hypertension. Hypertensive patients need the measurement of blood pressure and lipid profile at regular intervals to prevent Cardiovascular diseases. Keywords: Cholesterol; Cardiovascular Diseases; Hypertension; Triglycerides; Dyslipidemia

Robust parameters for automatic segmentation of speech

Automatic segmentation of speech ir on important problem that is useful in speed recognition, synthesis and coding. We explore in this paper: the robust parameter set, weightingfunction and distance measure for reliable segmentation of noisy speech. It is found that the MFCC parometers, successful in speech recognition. holds the best promise far robust segmentation also. We also explored a variery of symmetric and asymmetric weighting lifter, from which it is found that a symmetric lifter of the form $1+{Asin^{1/2}}{(\pi n/L)}$, ${0}\leq{n}\leq{L-1}$, for MFCC dimension L, is most effective. With regard to distance measure. the direct $L_2$ norm is found adequate

Comparison of acid and alkaline hydrogen-bromine fuel cell systems

The Conference abstracts' website is located at https://ecs.confex.com/ecs/224/webprogram/Paper20002.htmlSession - Vanadium Redox Systems 2 and Other Redox Systems 1: abstract no. 1674The hydrogen bromine (H2-Br2) fuel cell system is an attractive system for electrical energy storage because of its high round-trip conversion efficiency, high power density capability, and anticipated low costs. The hydrogen-bromine fuel cell system can be operated in the acid or alkaline modes. The charge and discharge electrode reactions in an acid H2-Br2 fuel cell system are as follows …postprin

Effectiveness of guided self-help in decreasing expressed emotion in family caregivers of people diagnosed with depression in Thailand: a randomised controlled trial

Background: High expressed emotion (EE) can extend the duration of illness and precipitate relapse; however, little evidence-based information is available to assist family caregivers of individuals with depression. In the present exploratory study, we examined the effectiveness of a cognitive behaviour therapy (CBT) based guided self-help (GSH) manual in decreasing EE in caregivers of people with depression, in Thailand. Method: A parallel group randomised controlled trial was conducted, following CONSORT guidelines, with 54 caregivers who were allocated equally to GSH or control group (standard outpatient department support). In addition, both groups were contacted weekly by telephone. EE was assessed, using the Family Questionnaire (FQ), at baseline, post-test (Week 8) and follow-up (Week 12). Results: FQ scores at baseline indicated that both groups had similar, though moderately high level of EE. However, between baseline and post-test EE scores decreased markedly in the intervention group, but in contrast, they increased slightly in the control group. Between post-test and follow-up, little change took place in the EE scores of either group. Overall, the intervention group recipients of GSH showed a significant decrease in EE whereas the control group recipients of standard outpatient department support reported a slight increase in EE. Conclusion: These findings provide preliminary evidence that GSH is beneficial in reducing EE in caregivers, which is advantageous to family members with depression and caregivers. The approach may be used as an adjunct to the limited outpatient department support given to caregivers by mental health professionals and, perhaps, to caregivers who do not attend these departments

Robust on-line diagnosis tool for the early accident detection in nuclear power plants

© 2019 Any loss of coolant accident mitigation strategy is necessarily bound by the promptness of the break detection as well as the accuracy of its diagnosis. The availability of on-line monitoring tools is then crucial for enhancing safety of nuclear facilities. The requirements of robustness and short latency implied by the necessity for fast and effective actions are undermined by the challenges associated with break prediction during transients. This study presents a novel approach to tackle the challenges associated with the on-line diagnostics of loss of coolant accidents and the limitations of the current state of the art. Based on the combination of a set of artificial neural network architectures through the use of Bayesian statistics, it allows to robustly absorb different sources of uncertainty without requiring their explicit characterization in input. It provides the quantification of the output confidence bounds but also enhances of the model response accuracy. The implemented methodology allows to relax the need for model selection as well as to limit the demand for user-defined analysis parameters. A numerical case-study entailing a 220 MWe heavy-water reactor is analysed in order to test the efficiency of the developed computational tool

Robustness Analysis of DCE-MRI-Derived Radiomic Features in Breast Masses: Assessing Quantization Levels and Segmentation Agreement

Featured Application The use of highly robust radiomic features is fundamental to reduce intrinsic dependencies and to provide reliable predictive models. This work presents a study on breast tumor DCE-MRI considering the radiomic feature robustness against the quantization settings and segmentation methods. Machine learning models based on radiomic features allow us to obtain biomarkers that are capable of modeling the disease and that are able to support the clinical routine. Recent studies have shown that it is fundamental that the computed features are robust and reproducible. Although several initiatives to standardize the definition and extraction process of biomarkers are ongoing, there is a lack of comprehensive guidelines. Therefore, no standardized procedures are available for ROI selection, feature extraction, and processing, with the risk of undermining the effective use of radiomic models in clinical routine. In this study, we aim to assess the impact that the different segmentation methods and the quantization level (defined by means of the number of bins used in the feature-extraction phase) may have on the robustness of the radiomic features. In particular, the robustness of texture features extracted by PyRadiomics, and belonging to five categories-GLCM, GLRLM, GLSZM, GLDM, and NGTDM-was evaluated using the intra-class correlation coefficient (ICC) and mean differences between segmentation raters. In addition to the robustness of each single feature, an overall index for each feature category was quantified. The analysis showed that the level of quantization (i.e., the 'bincount' parameter) plays a key role in defining robust features: in fact, in our study focused on a dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) dataset of 111 breast masses, sets with cardinality varying between 34 and 43 robust features were obtained with 'binCount' values equal to 256 and 32, respectively. Moreover, both manual segmentation methods demonstrated good reliability and agreement, while automated segmentation achieved lower ICC values. Considering the dependence on the quantization level, taking into account only the intersection subset among all the values of 'binCount' could be the best selection strategy. Among radiomic feature categories, GLCM, GLRLM, and GLDM showed the best overall robustness with varying segmentation methods

A Study of Alkaline-Based H2-Br2 and H2-I2 Reversible Fuel Cells

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