Miracle-dz/UniFAR-FTUs huggingface dataset:
Pilot Study Combining Electrical Stimulation and a Dynamic Hand Orthosis for Functional Recovery in Chronic Stroke

OBJECTIVE. We investigated the effect of a combined neuromuscular electrical stimulation (ES) and dynamic hand orthosis (DHO) regimen with a group of people with chronic stroke to improve performance on specific daily tasks. METHOD. Four people with chronic stroke participated in an ES‐DHO regimen using the affected upper extremity 5×/wk for 6 wk. Outcome measures included grip strength, range of motion (ROM), and analysis of muscle activation‐deactivation during release of grasp through electromyography. Ability to perform specific daily living tasks was assessed using the Assessment of Motor and Process Skills (AMPS). RESULTS. Results suggested that improvements in strength, ROM, and grasp deactivation are possible with the combined ES‐DHO regimen. All participants' AMPS motor scores improved. CONCLUSIONS. An ES‐DHO regimen may improve motor skills needed for functional task performance in people with chronic stroke. Results should be interpreted cautiously because of the pilot nature of the study and the small sample size.
A Review and Meta-analysis of Colorectal Cancer Utilities

Objective. To perform a systematic review of utility weights for colorectal cancer (CRC) health states reported in the scientific literature and to determine the effects of disease factors, patient characteristics, and utility methods on utility values. Methods. We identified 26 articles written in English and published from January 1980 to January 2013, providing 351 unique utilities for CRC health states elicited from 6546 unique respondents. The CRC utility data were analyzed using linear mixed-effects models with CRC type, stage, time to or from initial care, utility measurement instrument, and administration method as independent variables. Results. In the base case model, the estimated utility for a patient with stage I to III CRC more than 1 year after surgery, rated using a self-administered time tradeoff instrument, was 0.90. Stage, time to or from initial care, and utility measurement instrument were associated with statistically significant utility differences ranging from −0.19 to 0.02. Utilities for patients with stage IV cancer were 0.19 lower (P < 0.001) than for those with stage I to III cancer. Utilities elicited at more than 1 year after surgery were 0.05 higher than those elicited at 3 months after surgery (P = 0.008). Estimates of differences between utility measurement instruments were sensitive to how repeated scores in the same patient group were treated, and other findings were sensitive to how the disease stage was modeled and method of administration. Conclusions. Variations in reported utilities are associated with factors such as cancer stage, time to or from initial care, and utility measurement instrument. More research is needed to study why apparently similar patients report different quality of life.
Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic

Abstract Background: MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. Methods: An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2. The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. Results: In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We demonstrate our proposed approach for a two-sample summary data MR analysis to estimate the causal effect of low-density lipoprotein on heart disease risk. A high value of IGX2 close to 1 indicates that dilution does not materially affect the standard MR-Egger analyses for these data. Conclusions: Care must be taken to assess the NOME assumption via the IGX2 statistic before implementing standard MR-Egger regression in the two-sample summary data context. If IGX2 is sufficiently low (less than 90%), inferences from the method should be interpreted with caution and adjustment methods considered.
Gene silencing in non‐model insects: Overcoming hurdles using symbiotic bacteria for trauma‐free sustainable delivery of RNA interference

Insight into animal biology and development provided by classical genetic analysis of the model organism Drosophila melanogaster was an incentive to develop advanced genetic tools for this insect. But genetic systems for the over one million other known insect species are largely undeveloped. With increasing information about insect genomes resulting from next generation sequencing, RNA interference is now the method of choice for reverse genetics, although it is constrained by the means of delivery of interfering RNA. A recent advance to ensure sustained delivery with minimal experimental intervention or trauma to the insect is to exploit commensal bacteria for symbiont‐mediated RNA interference. This technology not only offers an efficient means for RNA interference in insects in laboratory conditions, but also has potential for use in the control of human disease vectors, agricultural pests and pathogens of beneficial insects.
Functional Validation of Candidate Genes Detected by Genomic Feature Models

Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait variability to pinpoint loci that contribute to the quantitative trait. Because stringent genome-wide significance thresholds are applied to control the false positive rate, many true causal variants can remain undetected. To ameliorate this problem, many alternative approaches have been developed, such as genomic feature models (GFM). The GFM approach tests for association of set of genomic markers, and predicts genomic values from genomic data utilizing prior biological knowledge. We investigated to what degree the findings from GFM have biological relevance. We used the Drosophila Genetic Reference Panel to investigate locomotor activity, and applied genomic feature prediction models to identify gene ontology (GO) categories predictive of this phenotype. Next, we applied the covariance association test to partition the genomic variance of the predictive GO terms to the genes within these terms. We then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated with the magnitude of the phenotypic consequence of gene knockdown. This study provides evidence for five new candidate genes for locomotor activity, and provides support for the reliability of the GFM approach.
Evaluating Cluster Quality Using Modified Density Subspace Clustering Approach

Clustering of the time series data faced with curse of dimensionality, where real world data consist of many dimensions. Finding the clusters in feature space, subspace clustering is a growing task. Density based approach to identify clusters in dimensional point sets. Density subspace clustering is a method to detect the density-connected clusters in all subspaces of high dimensional data for clustering time series data streams Multidimensional data clustering evaluation can be done through a density-based approach. In this approach proposed, Density subspace clustering algorithm is used to find best cluster result from the dataset. Density subspace clustering algorithm selects the P set of attributes from the dataset. Then apply the density clustering for selected attributes from the dataset . From the resultant cluster calculate the intra and inter cluster distance. Measuring the similarity between data objects in sparse and high-dimensional data in the dataset, Plays a very important role in the success or failure of a clustering method. Evaluate the similarity between data points and consequently formulate new criterion functions for clustering . Improve the accuracy and evaluate the similarity between the data points in the clustering,. The proposed algorithm also concentrates the Density Divergence Problem (Outlier). Proposed system clustering results compared them with existing clustering algorithms in terms of the Execution time, Cluster Quality analysis. Experimental results show that proposed system improves clustering quality result, and less time than the existing clustering methods. Keywords— Density Subspace Clustering, Intra Cluster, Inter Cluster, Outlier, Hierarchical Clustering.
The plastid genome of some eustigmatophyte algae harbours a bacteria-derived six-gene cluster for biosynthesis of a novel secondary metabolite

Acquisition of genes by plastid genomes (plastomes) via horizontal gene transfer (HGT) seems to be a rare phenomenon. Here, we report an interesting case of HGT revealed by sequencing the plastomes of the eustigmatophyte algae Monodopsis sp. MarTras21 and Vischeria sp. CAUP Q 202. These plastomes proved to harbour a unique cluster of six genes, most probably acquired from a bacterium of the phylum Bacteroidetes, with homologues in various bacteria, typically organized in a conserved uncharacterized putative operon. Sequence analyses of the six proteins encoded by the operon yielded the following annotation for them: (i) a novel family without discernible homologues; (ii) a new family within the superfamily of metallo-dependent hydrolases; (iii) a novel subgroup of the UbiA superfamily of prenyl transferases; (iv) a new clade within the sugar phosphate cyclase superfamily; (v) a new family within the xylose isomerase-like superfamily; and (vi) a hydrolase for a phosphate moiety-containing substrate. We suggest that the operon encodes enzymes of a pathway synthesizing an isoprenoid–cyclitol-derived compound, possibly an antimicrobial or other protective substance. To the best of our knowledge, this is the first report of an expansion of the metabolic capacity of a plastid mediated by HGT into the plastid genome.
Share in the Commons: Coexistence between LTE Unlicensed and Wi-Fi

LTE Unlicensed extends LTE to unlicensed spectrum by aggregating unlicensed carriers with licensed ones through carrier aggregation or solely operating in unlicensed bands. It can create a unified network, increase network capacity, provide ubiquitous mobility, enhance user experience, and lower operational costs. However, to harvest these potential benefits, many technical challenges have to be addressed for LTE Unlicensed, including harmonious coexistence between LTE Unlicensed and other incumbent unlicensed systems, quality-of-service guarantee in unreliable unlicensed spectrum, as well as maintenance of ecosystem balance in unlicensed spectrum. In this article, we provide an overview of the current studies in LTE Unlicensed. In particular, we introduce regulation requirements and current standardization progress. We further outline three main challenges, describe possible deployment scenarios, and summarize technical solutions. The impact of LTE Unlicensed on the incumbent unlicensed systems is also examined by leveraging stochastic geometry, and finally, some potential research topics are identified.
Arterial stiffness and its relationship to clinic and ambulatory blood pressure: a longitudinal study in non-dialysis chronic kidney disease

Background Both arterial stiffness and systolic blood pressure (BP) are established cardiovascular risk factors, yet little is known about their interrelationship in chronic kidney disease (CKD). The goal of this prospective study was to describe the trajectory of aortic pulse wave velocity (PWV) and BP and to compare the longitudinal interrelationship of BP (clinic and 24 h ambulatory recording) with the PWV. Methods Clinic BP was taken in two ways: at the time of the measurement of the PWV (Clinic-S) and as an average of triplicate measurements on three separate occasions within 1 week (Clinic-M). 24 h ambulatory BP was measured using a validated monitor and PWV was measured in the aorta using an echo-Doppler technique. Results Among 255 veterans with CKD followed for over up to 4 years, the rate of change of log PWV was inversely related to the baseline PWV; the trajectories were variable among individuals and the net population change was no different from zero. In contrast, systolic BP significantly increased, but linearly, and a strong relationship was seen between cross-sectional and longitudinal changes in Clinic-M systolic BP and log PWV. In contrast, a longitudinal relationship between Clinic-S and log PWV was absent. In the case of 24-h ambulatory BP, a strong cross-sectional change was seen between awake and 24 h systolic BP but not between sleep BP and log PWV. Conclusion In conclusion, among people with CKD, the PWV changes over time and is inversely related to the baseline PWV. An average of clinic BP measurements taken over three visits, but not single measurements, are useful to assess the PWV and its change over time. Differences exist between ambulatory BP monitoring recording during the sleep and awake states in their ability to predict the PWV. Taken together, these data support the view that among those with CKD not on dialysis, targeting clinic BP taken on multiple occasions using a standardized methodology or daytime ambulatory systolic BP may slow the progression of arterial damage.
The bullwhip effect under count time series: The case of first order integer auto-regressive demand processes

The impact of fast moving items, modeled by auto-regressive moving average (ARMA) type processes, on the bullwhip effect is well known. However, slow moving items that can be modeled using integer ARMA processes have received little attention. Herein, we measure the impact of bullwhip effect under a first order integer auto-regressive, INAR(1), demand process. We consider a simple two-stage supply chain consisting of a retailer and a manufacturer. We assume that the retailer employs a base stock inventory policy when the demand is forecasted using a minimum mean squared error method. We investigate the impact of the INAR(1) demand process parameter, , and the replenishment lead time, L, on the bullwhip effect generated by the order-up-to replenishment policy. We show that the bullwhip effect is increasing with the lead-time L.
Sympathoinhibitory Effect of Radiofrequency Renal Denervation in Spontaneously Hypertensive Rats With Established Hypertension.

BACKGROUND Radiofrequency ablation of the renal arteries (RF-ABL) has been shown to decrease blood pressure (BP) in drug-resistant hypertensive patients who receive antihypertensive drug therapy. However, there remain questions regarding how RF-ABL influences BP independent of drug therapy and whether complete renal denervation is necessary to maximally lower BP. To study these questions, we examined the cardiovascular, sympathetic, and renal effects produced by RF-ABL of the proximal renal arteries in spontaneously hypertensive rats (SHR) with established hypertension. METHODS SHR were instrumented (telemetry) for measurement of systolic/diastolic BP (SBP/DBP). Rats then underwent Sham-ABL or RF-ABL adjacent to the renal ostium and BP was recorded for 8 weeks. Changes in sympathetic activity, 24-hour water/sodium excretion, and levels of urinary angiotensinogen (AGT), plasma renin activity, and kidney renin content (KRC) were measured in SHR. RESULTS Compared with Sham-ABL, RF-ABL produced a sustained decrease in BP. At 8 weeks, SBP/DBP was 171±6/115±3 and 183±4/129±3mm Hg for RF-ABL and Sham-ABL SHR, respectively. Correlating with the reduction in BP, RF-ABL significantly decreased the low frequency/total and low frequency/high frequency of BP variability and attenuated the hypotensive response to chlorisondamine. Kidney norepinephrine levels were markedly decreased at 8 weeks in RF-ABL vs. Sham-ABL SHR. There were no group differences in 24-hour sodium/water excretion or urinary AGT excretion rate (6 weeks) or plasma renin activity or KRC (8 weeks). In other studies, concurrent RF-ABL plus surgical denervation initially decreased BP to a greater level than RF-ABL alone, but thereafter the reduction in BP between groups was not different. CONCLUSIONS In hypertensive SHR, bilateral RF-ABL of the proximal renal arteries produced a sustained decease in sympathetic activity and BP without changes in sodium/water excretion or activity of the systemic/renal renin-angiotensin system.
Mobility Difficulties, Physical Activity, and All-cause Mortality Risk in a Nationally representative Sample of Older Adults

Background This study sought to determine the association between levels of physical activity and mobility difficulties and time to death while accounting for the effect of several confounders. We also examined the possible interaction between them and how various daily-life mobility difficulties could predict all-cause mortality. Methods A nationally representative sample of 2,074 noninstitutionalized adults aged 60 years and older was analyzed. Vital status over a 3-year follow-up period was ascertained through national registers or by asking participants' relatives. Kaplan-Meier survival curves were stratified by levels of physical activity and mobility difficulties. Unadjusted and adjusted Cox proportional hazards regression models (by age, gender, marital status, years of education, multimorbidity, tobacco and alcohol consumption, depression, and memory function) were calculated, and interactions between the predictors and the covariates were explored. Results There was a dose-gradient effect of physical activity on time to death, with high levels associated with a 51% lower risk of dying, compared with moderate physical activity. Each unit increase in mobility functioning was associated with a 2% drop in mortality. Difficulties in standing for long periods, getting where one wants to go or extending arms to reach objects, were also found to be strong predictors of all-cause mortality. Conclusions Our results confirm the importance of older adults practicing moderate-to-vigorous physical activity. The assessment of self-reported difficulties in daily-life mobility activities, such as standing for long periods or not being able to move around, could be used in health settings as a screening for mortality risk.
Study On The Wettability And Self-cleaning OfButterfly Wing Surfaces

Many biological surfaces are hydrophobic because of their complicated composition and surface microstructure. Butterflies were selected to study their characteristics by Confocal Light Microscopy, Scanning Electron Microscopy and Contact Angle measurement. The contact angle of the water droplets on the butterfly wings surface consistently measured to be more than 140o. The dust on the surface can be easily cleaned by moving spherical droplets when the inclining angle is larger than 3°. It can be concluded that the butterfly wing’s surface possess a water-repellent, self-cleaning, or “Lotus-effect” characteristic. Contact angle measurement of the wings’ surface with and without squamas showed that the water-repellent characteristics are a consequence of the microstructure of the squamas. Each water droplet (diameter 2-3 mm) covers 3050 squamas each with a size of 40x80 microns. The regular riblets with a width of 1000-1500 nm are clearly observed on single squama. Such a nano-structure
Multimodal obstacle detection in unstructured environments with conditional random fields

Reliable obstacle detection and classification in rough and unstructured terrain such as agricultural fields or orchards remains a challenging problem. These environments involve large variations in both geometry and appearance, challenging perception systems that rely on only a single sensor modality. Geometrically, tall grass, fallen leaves, or terrain roughness can mistakenly be perceived as nontraversable or might even obscure actual obstacles. Likewise, traversable grass or dirt roads and obstacles such as trees and bushes might be visually ambiguous. In this paper, we combine appearance‐ and geometry‐based detection methods by probabilistically fusing lidar and camera sensing with semantic segmentation using a conditional random field. We apply a state‐of‐the‐art multimodal fusion algorithm from the scene analysis domain and adjust it for obstacle detection in agriculture with moving ground vehicles. This involves explicitly handling sparse point cloud data and exploiting both spatial, temporal, and multimodal links between corresponding 2D and 3D regions. The proposed method was evaluated on a diverse data set, comprising a dairy paddock and different orchards gathered with a perception research robot in Australia. Results showed that for a two‐class classification problem (ground and nonground), only the camera leveraged from information provided by the other modality with an increase in the mean classification score of 0.5%. However, as more classes were introduced (ground, sky, vegetation, and object), both modalities complemented each other with improvements of 1.4% in 2D and 7.9% in 3D. Finally, introducing temporal links between successive frames resulted in improvements of 0.2% in 2D and 1.5% in 3D.
TOTAL: TRNG on-the-fly testing for attack detection using Lightweight hardware

We present a design methodology for embedded tests of entropy sources. These tests are necessary to detect attacks and failures of true random number generators. The central idea of this work is to use an empirical design methodology consisting of two phases: collecting the data under attack and finding a useful statistical feature. In this work we focus on statistical features that are implementable in lightweight hardware. This is the first paper to address the design of on-the-fly tests based on the attack effects. The presented design methodology is illustrated with 2 examples: an elementary ring-oscillator based TRNG and a carry-chain based TRNG. The effectiveness of the tests was confirmed on FPGA prototypes.