The Effect of Workplace Stretching Exercise on Reducing Musculoskeletal Complaints in Ndao Ikat Weaving Workers in Rote Ndao District

Musculoskeletal complaints in Ndao weaving workers are a problem of muscle disorders for weavers. As a result of this process is a long time and repeatedly will cause musculoskeletal complaints. Workplace Stretching Exercise is designed with the principle of muscle stretching, which is an attempt to extend muscle rest or relaxation. This activity will improve blood circulation so that it helps relax nervous tension and train muscles to be stronger so they don't get tired easily while working. This study aimed to analyze the effect of workplace stretching exercises on the reduction of musculoskeletal complaints in Ndao weaving workers in Rote Ndao Regency. This is a quantitative research with a pre-experimental design type one-group pretest-posttest design method. The population in this study were active weavers in Ikat Ndao weaving, Lobalain District as many as 40 weavers. The selected research sample has met the eligibility criteria for as many as 18 active weavers. The type of analysis test used is the paired sample t-test. The results showed that there was a difference in the level of musculoskeletal complaints before the intervention was in the moderate complaint category with a percentage of 77.8% and after the WSE intervention, the complaints decreased to the low complaint category with a percentage of 66.7% with a significant decrease in value of 19.39%. The results of the analysis show that there is an effect of Workplace Stretching Exercise on the reduction of musculoskeletal complaints in Ndao tie weaving workers, where there is a large difference in value (p = 0.007 ) ≤ (0.05), so it is expected that Ndao tie weaving workers will carry out Workplace Stretching Exercise activities every day in between weaving activities to reduce musculoskeletal complaints

The impact of different concentrations of a pyrethroid insecticide on the cyclic gas exchange cycles on bumble bees

contribution to session II Bumblebees and other bee specie

ECG-Based Detection of Early Myocardial Ischemia in a Computational Model: Impact of Additional Electrodes, Optimal Placement, and a New Feature for ST Deviation

In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 2-11% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold. © 2015 Axel Loewe et al

Characterization of complex fractionated atrial electrograms by sample entropy: An international multi-center study

Atrial fibrillation (AF) is the most commonly clinically-encountered arrhythmia. Catheter ablation of AF is mainly based on trigger elimination and modification of the AF substrate. Substrate mapping ablation of complex fractionated atrial electrograms (CFAEs) has emerged to be a promising technique. To improve substrate mapping based on CFAE analysis, automatic detection algorithms need to be developed in order to simplify and accelerate the ablation procedures. According to the latest studies, the level of fractionation has been shown to be promisingly well estimated from CFAE measured during radio frequency (RF) ablation of AF. The nature of CFAE is generally nonlinear and nonstationary, so the use of complexity measures is considered to be the appropriate technique for the analysis of AF records. This work proposes the use of sample entropy (SampEn), not only as a way to discern between non-fractionated and fractionated atrial electrograms (A-EGM), but also as a tool for characterizing the degree of A-EGM regularity, which is linked to changes in the AF substrate and to heart tissue damage. The use of SampEn combined with a blind parameter estimation optimization process enables the classification between CFAE and non-CFAE with statistical significance (p < 0:001), 0.89 area under the ROC, 86% specificity and 77% sensitivity over a mixed database of A-EGM combined from two independent CFAE signal databases, recorded during RF ablation of AF in two EU countries (542 signals in total). On the basis of the results obtained in this study, it can be suggested that the use of SampEn is suitable for real-time support during navigation of RF ablation of AF, as only 1.5 seconds of signal segments need to be analyzed

Atrial Flutter Mechanism Detection Using Directed Network Mapping

Atrial flutter (AFL) is a common atrial arrhythmia typically characterized by electrical activity propagating around specific anatomical regions. It is usually treated with catheter ablation. However, the identification of rotational activities is not straightforward, and requires an intense effort during the first phase of the electrophysiological (EP) study, i.e., the mapping phase, in which an anatomical 3D model is built and electrograms (EGMs) are recorded. In this study, we modeled the electrical propagation pattern of AFL (measured during mapping) using network theory (NT), a well-known field of research from the computer science domain. The main advantage of NT is the large number of available algorithms that can efficiently analyze the network. Using directed network mapping, we employed a cycle-finding algorithm to detect all cycles in the network, resembling the main propagation pattern of AFL. The method was tested on two subjects in sinus rhythm, six in an experimental model of in-silico simulations, and 10 subjects diagnosed with AFL who underwent a catheter ablation. The algorithm correctly detected the electrical propagation of both sinus rhythm cases and in-silico simulations. Regarding the AFL cases, arrhythmia mechanisms were either totally or partially identified in most of the cases (8 out of 10), i.e., cycles around the mitral valve, tricuspid valve and figure-of-eight reentries. The other two cases presented a poor mapping quality or a major complexity related to previous ablations, large areas of fibrotic tissue, etc. Directed network mapping represents an innovative tool that showed promising results in identifying AFL mechanisms in an automatic fashion. Further investigations are needed to assess the reliability of the method in different clinical scenarios

CVAR-Seg: An Automated Signal Segmentation Pipeline for Conduction Velocity and Amplitude Restitution

Background: Rate-varying S1S2 stimulation protocols can be used for restitution studies to characterize atrial substrate, ionic remodeling, and atrial fibrillation risk. Clinical restitution studies with numerous patients create large amounts of these data. Thus, an automated pipeline to evaluate clinically acquired S1S2 stimulation protocol data necessitates consistent, robust, reproducible, and precise evaluation of local activation times, electrogram amplitude, and conduction velocity. Here, we present the CVAR-Seg pipeline, developed focusing on three challenges: (i) No previous knowledge of the stimulation parameters is available, thus, arbitrary protocols are supported. (ii) The pipeline remains robust under different noise conditions. (iii) The pipeline supports segmentation of atrial activities in close temporal proximity to the stimulation artifact, which is challenging due to larger amplitude and slope of the stimulus compared to the atrial activity. Methods and Results: The S1 basic cycle length was estimated by time interval detection. Stimulation time windows were segmented by detecting synchronous peaks in different channels surpassing an amplitude threshold and identifying time intervals between detected stimuli. Elimination of the stimulation artifact by a matched filter allowed detection of local activation times in temporal proximity. A non-linear signal energy operator was used to segment periods of atrial activity. Geodesic and Euclidean inter electrode distances allowed approximation of conduction velocity. The automatic segmentation performance of the CVAR-Seg pipeline was evaluated on 37 synthetic datasets with decreasing signal-to-noise ratios. Noise was modeled by reconstructing the frequency spectrum of clinical noise. The pipeline retained a median local activation time error below a single sample (1 ms) for signal-to-noise ratios as low as 0 dB representing a high clinical noise level. As a proof of concept, the pipeline was tested on a CARTO case of a paroxysmal atrial fibrillation patient and yielded plausible restitution curves for conduction speed and amplitude. Conclusion: The proposed openly available CVAR-Seg pipeline promises fast, fully automated, robust, and accurate evaluations of atrial signals even with low signal-to-noise ratios. This is achieved by solving the proximity problem of stimulation and atrial activity to enable standardized evaluation without introducing human bias for large data sets

Is digital cognitive behavioural therapy for insomnia effective in treating sub-threshold insomnia: A pilot RCT

Objective/Background: CBT for insomnia (CBT-I) is useful for many. It is currently unknown if those with sub-threshold insomnia also benefit. Here we assessed whether CBT-I is both feasible and acceptable in participants with sub-threshold insomnia. The primary aims were to evaluate participation rates and treatment acceptability, and to establish an effect size for symptom improvement. Patients/Methods: A total of 199 female participants (Mage 20 ± 5 years) took part. Following baseline assessments, participants were randomly allocated to either a 6-week digital CBT-I intervention or a 6-week session control group receiving puzzles. Additional assessments were performed 3-weeks, 6-weeks, and 6-months later. Results: Participation in each survey wave did not differ between the groups (ps > .140), though adherence to weekly tasks was lower in the CBT-I group, p = .02. Treatment acceptability was high (M (SD) = 33.61 (4.82), range 6 – 42). The CBT-I group showed greater improvement in insomnia symptoms at the end of the intervention compared to the control group (p = .013, d = 0.42), with significant variation in outcome (M = 4.69, SD = 5.41). Sub-threshold participants showed a similar pattern of results, whilst those meeting insomnia criteria showed a smaller between-group difference. CBT-I led to improvements in anxiety, paranoia and perceived stress between baseline and end of intervention. Changes in insomnia symptoms were mediated by cognitions about sleep and somatic pre-sleep arousal. Conclusions: CBT-I provides a benefit even in sub-threshold insomnia. CBT-I may be useful as an early preventative intervention to tackle sleep problems before they manifest as chronic insomnia

Different patterns of labour market integration by migration motivation in Europe: the role of host country human capital

We study whether individual decisions to invest in the host country, namely obtaining equivalent qualifications, improving language skills, or naturalisation explain differences in labour market integration between migrants depending on their initial motivation. We use cross-national European data from the 2008 ad-hoc module of the Labour Force Survey to analyse migrant gaps in labour market participation, employment, occupational status and precarious employment. We find that different rates of and returns to host country human capital explain a substantial part of the improvements in labour market outcomes with years of residence, particularly for non-economic migrants who experience faster growth on average