Miracle-dz/UniFAR-FTUs huggingface dataset:
ECG Distortion Measures and their Effectiveness

Measurement of quality is of fundamental importance to electrocardiogram (ECG) signal processing applications. A number of distortion measures are used for ECG signal quality assessment. A simple and widely used distortion measure is the percentage root mean square difference (PRD). It is an attractive measure due to its simplicity and mathematical convenience. But PRD is not a good measure of the true compression error and results in poor diagnostic relevance. In this paper, we discuss the advantages and drawbacks of the objective distortion measures using different compressed signals. With extensive analysis it is shown that although some distortion measures correlate well with the subjective evaluation for distortions resulting from a given compression method, they may not be reliable for evaluation of some other compression distortions. It is also concluded that a distortion measure should be subjectively meaningful in order to correlate a large or small quantitative distortion measure with bad and good quality. This work attempts to evaluate the closeness of the objective quality measures with subjective measure and investigation may help to suggest a better quality criterion for optimizing rate-distortion algorithms. Experimental results show that wavelet energy based diagnostic distortion (WEDD) measure is significantly better than other measures. This measure is sensitive to ECG feature changes and insensitive to smoothing of low-level background noise.
The Processing of Attended and Predicted Sounds in Time

Neural responses to an attended event are typically enhanced relative to those from an unattended one (attention enhancement). Conversely, neural responses to a predicted event are typically reduced relative to those from an unpredicted one (prediction suppression). What remains to be established is what happens with attended and predicted events. To examine the interaction between attention and prediction, we combined two robust paradigms developed for studying attention and prediction effects on ERPs into an orthogonal design. Participants were presented with sounds in attended or unattended intervals with onsets that were either predicted by a moving visual cue or unpredicted (no cue was provided). We demonstrated an N1 enhancement effect for attended sounds and an N1 suppression effect for predicted sounds; furthermore, an interaction between these effects was found that emerged early in the N1 (50–95 msec), indicating that attention enhancement only occurred when the sound was unpredicted. This pattern of results can be explained by the precision of the predictive cue that reduces the need for attention selection in the attended and predicted condition.
2D-BayesPointer: An Implicit Moving Target Selection Technique Enabled by Human Performance Modeling

Interactive systems with dynamic content are becoming ubiquitous nowadays. However, it is challenging to select small and fast-moving targets in such environment. We present 2D-BayesPointer, a novel interaction technique to assist moving target selection in 2D space. Compared with previous techniques, our method provides implicit support without modifying the original interface design. Moreover, the algorithmic parameters are determined by probabilistic modeling of human performance in moving target selection tasks. The preliminary results from a pilot study have shown that this technique can significantly improve both selection speed and accuracy.
An Embodied Account of Early Executive-Function Development

The importance of executive functioning for later life outcomes, along with its potential to be positively affected by intervention programs, motivates the need to find early markers of executive functioning. In this study, 18-month-olds performed three executive-function tasks—involving simple inhibition, working memory, and more complex inhibition—and a motion-capture task assessing prospective motor control during reaching. We demonstrated that prospective motor control, as measured by the peak velocity of the first movement unit, is related to infants’ performance on simple-inhibition and working memory tasks. The current study provides evidence that motor control and executive functioning are intertwined early in life, which suggests an embodied perspective on executive-functioning development. We argue that executive functions and prospective motor control develop from a common source and a single motive: to control action. This is the first demonstration that low-level movement planning is related to higher-order executive control early in life.
Location-based channel estimation and pilot assignment for massive MIMO systems

In this paper, a location-based channel estimation algorithm is proposed for massive multi-input multi-output (MIMO) systems. By utilizing the property of the steering vector, a fast Fourier transform (FFT)-based post-processing is introduced after the conventional pilot-aided channel estimation. Under the condition that different users with the same pilot sequence have non-overlapping angle-of-arrivals (AOAs), the proposed channel estimation algorithm is capable of distinguishing these users effectively. To cooperate with the location-based channel estimation, a pilot assignment algorithm is also proposed to ensure that the users in different cells using the same pilot sequence have different AOAs at base station. The simulation results demonstrate that the proposed scheme can reduce the inter-cell interference caused by the reuse of the pilot sequence and thus improves the overall system performance significantly.
Enhancement of voltage and loss reduction in radial distribustion system with distributed generation

The concept of smart grid has taken a major initiative in future distribution system. The distributed generation (DG) has an important role in the context as a reliable source of power to meet the increasing load demand. By the integration of DG units which tremendously change structure and operation of distribution system. The proper allocation of DG units in distribution system is very important to ensure the quality of power provided to the end user. This paper address DG allocation and sizing problem in a radial distribution system where DG unit is treated as negative load(PQ bus). The location and size of DG is found by identifying a candidate bus based on loss sensitivity factor and direct search method. Different rating of DG units of unity PF, suitable of renewable energy sources like solar and Fuel cell is tested on a 15 bus radial distribution system using MATLAB programming at different locations. The results show that by proper allocation of DG helps to improve the voltage profile and reduce in real power loss in the network. The proposed method is also tested on anIEEE33bus system.
Effect of Chemical Surface Treatment on Flax-Reinforced Epoxy Composite

ABSTRACT The aim of this study is to examine the impact of surface modification on properties of flax fiber and flax-reinforced composites. For this purpose, acetic anhydride, sodium hydroxide, and silane were used to treat surface of the flax fiber. The effects of treatments on fiber were investigated by using contact angle, attenuated total reflectance-Fourier transform infrared, atomic force microscopy (AFM), and scanning electron microscopy (SEM). Contact angle and AFM results revealed that sodium hydroxide-treated flax fibers have higher adhesion force on the fiber surface. Particularly, NaOH treatment improved the mechanical properties of the epoxy matrix composite.
A Statistical Approach to Robust Video Temporal Segmentation

The problem of video ’cut’ detection remains largely an open problem, because of the wide nature of transitions that occur in a digital video. This paper describes a shot boundary detection technique which is an amalgamation of few statistical methods and measures, and robustly detects camera breaks in a full-motion video clip. The proposed algorithm incorporates a weighted histogram, an error-propagation technique for increased robustness, and a curve-fitting technique to extract partitions from the similarity curve for avoiding heuristically chosen threshold value. The algorithm has been validated on many video clips and is shown to give improved results.
Nutritional Characterization and Phenolic Profiling of Moringa oleifera Leaves Grown in Chad, Sahrawi Refugee Camps, and Haiti

Moringa oleifera is a plant that grows in tropical and subtropical areas of the world. Its leaves are rich of nutrients and bioactive compounds. However, several differences are reported in the literature. In this article we performed a nutritional characterization and a phenolic profiling of M. oleifera leaves grown in Chad, Sahrawi refugee camps, and Haiti. In addition, we investigated the presence of salicylic and ferulic acids, two phenolic acids with pharmacological activity, whose presence in M. oleifera leaves has been scarcely investigated so far. Several differences were observed among the samples. Nevertheless, the leaves were rich in protein, minerals, and β-carotene. Quercetin and kaempferol glycosides were the main phenolic compounds identified in the methanolic extracts. Finally, salicylic and ferulic acids were found in a concentration range of 0.14–0.33 and 6.61–9.69 mg/100 g, respectively. In conclusion, we observed some differences in terms of nutrients and phenolic compounds in M. oleifera leaves grown in different countries. Nevertheless, these leaves are a good and economical source of nutrients for tropical and sub-tropical countries. Furthermore, M. oleifera leaves are a source of flavonoids and phenolic acids, among which salicylic and ferulic acids, and therefore they could be used as nutraceutical and functional ingredients.
Nonlinear Counterpropagating Waves, Multisymplectic Geometry, and the Instability of Standing Waves

Standing waves are a fundamental class of solutions of nonlinear wave equations with a spatial reflection symmetry, and they routinely arise in optical and oceanographic applications. At the linear level they are composed of two synchronized counterpropagating periodic traveling waves. At the nonlinear level, they can be defined abstractly by their symmetry properties. In this paper, general aspects of the modulational instability of standing waves are considered. This problem has difficulties that do not arise in the modulational instability of traveling waves. Here we propose a new geometric formulation for the linear stability problem, based on embedding the standing wave in a four-parameter family of nonlinear counterpropagating waves. Multisymplectic geometry is shown to encode the stability properties in an essential way. At the weakly nonlinear level we obtain the surprising result that standing waves are modulationally unstable only if the component traveling waves are modulation unstable. Systems of nonlinear wave equations will be used for illustration, but general aspects will be presented, applicable to a wide range of Hamiltonian PDEs, including water waves.
Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization

This paper introduces a new algorithm for consensus optimization in a multi-agent network, where all agents collaboratively find a minimizer for the sum of their private functions. All decentralized algorithms rely on communications between adjacent nodes. One class of algorithms use communications between some or all pairs of adjacent agents at each iteration. Another class of algorithms uses a random walk incremental strategy, which sequentially activates a succession of agents. Existing incremental algorithms require diminishing step sizes to converge to the solution, and their convergence is slow. In this work, we propose a random walk algorithm that uses a fixed step size and converges faster to the solution than the existing random walk incremental algorithms. Our algorithm uses only one link to communicate the latest information from an agent to another. Since this style of communication mimics a man walking in a network, we call our algorithm Walkman. We establish convergence for convex and nonconvex objectives. For decentralized least squares, we derive a linear rate of convergence and obtain a better communication complexity than those of other decentralized algorithms. Numerical experiments verify our analysis results.
Pancreaticoduodenectomy: minimizing the learning curve.

Background Pancreaticoduodenectomy outcomes improve as surgeon experience increases. We analyzed the outcomes of pancreaticoduodenectomy for any improvements over time to assess the learning curve. Methods A retrospective study of patients undergoing consecutive pancreaticoduodenectomy by a single surgeon at the beginning of practice was performed. Operative factors and 90-day outcomes were examined and trends over the course of the 4-year time period were analyzed. Results Between July 2011 and June 2015, 124 patients underwent pancreaticoduodenectomy (including total pancreatectomy, n=17) by open (n=93) or a laparoscopic (n=31) approach. The median operative time was 305 minutes which significantly improved over time. The median blood loss and length of stay were 250 mL and 6 days respectively which did not change over time. The pancreatic fistula rate, total morbidity, major morbidity, and mortality, and readmission rate was 7.5%, 41.1%, 14.5%, 1.6%, and 15.3% respectively and did not change over time. Pancreaticoduodenectomy was performed most commonly for pancreatic adenocarcinoma (51.6%) with a negative margin rate of 91.1% which significantly improved over time. Conclusions The performance of pancreaticoduodenectomy improves as surgical experience is gained. However, a learning curve that impacts patient outcomes can be considerably diminished by appropriate training, high-volume practice/institution, proficient mentorship and experienced multidisciplinary team.
The influence of grafting on flow-induced crystallization and rheological properties of poly(ε-caprolactone)/cellulose nanocrystal nanocomposites

Abstract The influence of poly(ε-caprolactone) (PCL) grafts on the rheology and crystallization behavior of nanocomposites based on PCL and cellulose nanocrystals (CNC) both under quiescent and shear conditions is investigated. Under quiescent conditions, the grafted nanocrystals have high nucleation efficiencies. Under the influence of shear, the non-grafted nanocrystals were, however, more efficient in orienting the polymer chains and accelerating the flow-induced crystallization. The addition of large amounts of grafted material decreases the viscosity of the composites and thereby also the efficiency of shear-induced orientation. Graphical Abstract
Efficacy and Safety of Uninterrupted Low-Intensity Warfarin for Radiofrequency Catheter Ablation of Atrial Fibrillation in the Elderly

Background: No previous studies exist investigating the optimal intensity of uninterrupted anticoagulation with warfarin during radiofrequency catheter ablation (RFCA) for atrial fibrillation (AF) in the elderly. Objective: Evaluate the efficacy and safety of continuous low-intensity warfarin therapy throughout the periprocedural period of RFCA for AF in the elderly. Methods: This is a prospective randomized study. We enrolled AF patients (age ≥ 70 years) who underwent first-time RFCA for AF. Enrolled patients were randomized to group A and group B. The international normalized ratios before ablation were maintained at 1.5 to 2.0 and 2.0 to 2.5 in group A and B, respectively. Primary end points were periprocedural thromboembolic complications and major bleeding. Secondary end points included periprocedural asymptomatic cerebral emboli (ACE) and minor bleeding. Results: A total of 101 patients were enrolled in our study (group A: 52; group B: 49). Baseline characteristics were well balanced between the 2 groups. Only 1 patient suffered from stroke in group B. No major bleeding events occurred in either group. The incidence of new ACE lesions was comparable between the 2 groups (11.5% vs 8.2%, P = 0.82). Minor bleeding occurred in 1 of 52 (1.9%) patients in group A and in 5 of 49 (10.2%) patients in group B (P = 0.10). Conclusions: Uninterrupted low-intensity warfarin for RFCA of AF might be as effective as standard-intensity warfarin in preventing periprocedural thromboembolic complications and might be associated with fewer bleeding events in the elderly.
A parameterized timing-aware flip-flop merging algorithm for clock power reduction

In modern integrated circuits, the clock power contributes a dominant part of the chip power. Clock power can be reduced effectively by utilizing multi-bit flip-flops. In this paper, a parameterized timing-aware flip-flop merging algorithm is proposed for clock power reduction. The single-bit flip-flops are merged into multi-bit flip-flops after placement & optimization and before clock network synthesis with consideration of function information, scan chain information, distance and timing constraints. The algorithm can be configured with different parameters, such as the bit-number of MBFF, the setup timing margin and the distance margin. Experimental results under an industrial design show that compared with the basic design without MBFF, the design with 2-bit, 4-bit, 6-bit, and 8-bit MBFFs can save 7.5%, 12%, 11.8% and 11.1% total power consumption respectively. Using MBFF4 to replace 1-bit FFs is the best choice for the design optimization, which achieves minimum area and total power consumption. We also compare the designs with MBFF4 replacement under five different setup timing margins and distance margins. Without violating any timing constraint, it is better to set the setup timing margin as small as possible to achieve best power optimization. The distance margin (I00μm, 30μm) is the best choice for this industry design to achieve minimum power consumption.
New Conditional Sampling Strategies for Speeded-Up RANSAC

RANSAC (Random Sample Consensus) [2] is a popular algorithm in computer vision for fitting a model to data points contaminated with many gross outliers. Traditionally many small hypothesis sets are chosen randomly; these are used to generate models and the model consistent with most data points is selected. Instead we propose that each hypothesis set chosen is the one most likely to be correct, conditional on the knowledge of those that have failed to lead to a good model. We present two algorithms, BaySAC and SimSAC, to choose this most likely hypothesis set. A common use for RANSAC is for estimating the essential matrix describing the relative position of two cameras, which can be computed from stereo matches between two images. Given a set of these stereo correspondences the classic RANSAC sampling algorithm selects random subsets of five points, and for each subset computes all possible essential matrices. Each essential matrix is checked against all correspondences until one compatible with a large number of correspondences is found. RANSAC for essential matrix estimation can be a costly part of realtime Visual Navigation schemes because of the large number of hypothesis sets that must be tried before finding one uncontaminated by outliers. This number may be reduced considerably if outlier probabilities can be estimated, e.g. from stereo correspondence match strengths. PROSAC (Progressive Sample Consensus) [1] ranks data points by prior probability then selects subsets in (approximate) order of prior likelihood. Alternatively Guided-MLESAC [3] selects random subsets where each data-point is selected with probability in proportion to its prior inlier likelihood. These sampling methods fail to take into account is the information gained by testing hypothesis sets and finding them to be contaminated by outliers, unlike the two methods proposed here which are based on the following observation: a hypothesis set leading to a model consistent with few data points probably contains one or more outliers (the alternative possibility is that it contains a degenerate configuration of inliers). Hypothesis sets with one or more data points in common with this set are also now less likely, as they are likely to include the same outlier(s). Ideally at each time we will choose one of the hypothesis set that is most likely to contain no outliers based on the prior probabilities and the history of contaminated samples. This strategy minimises the number of hypotheses that must be tested before finding one consisting entirely of inliers. Unfortunately a closed-form solution for this posterior probability is algebraically intractable. Instead we present two methods of approximating this probability, both of which are shown to work well in practice.
Wide bandgap semiconductor radiation detectors for extreme environments

Wide bandgap semiconductor photodiodes were investigated for their suitability as radiation detectors for high temperature applications (≥ 20 °C), through measurements, calculations of key parameters of the devices, and relating the results back to the material, geometry of the detectors, environment under which the detectors were investigated, and previously published work. Three families of photodiodes were examined. 4H-SiC vertical Schottky UV photodiodes with Ni2Si interdigitated contacts were characterised for their response under dark and UV illumination. Electrical characterisation up to 120 °C and room temperature responsivity measurements (210 nm to 380 nm) suggested that the devices could operate at low UV light intensities, even at high visible and IR backgrounds without the use of filters, and at high temperatures. 4H-SiC Schottky photodiode detector arrays with planar thin NiSi contacts were investigated for X-ray (≤ 35 keV) detection and photon counting spectroscopy at 33 °C. The electrical characterisation of the devices up to 140 °C and subsequent analysis suggested that the devices are likely to operate as high temperature X-ray spectrometers. Results characterising GaAs p+-i-n+ mesa photodiode detectors for their room temperature visible and near infrared responsivity (580 nm to 870 nm), as well as their high temperature (≤ 60 °C) X-ray detection performance (at 5.9 keV) are presented. GaAs p+-i-n+ mesa photodiodes were also shown to be suitable for β- particle (electron) spectroscopy and X-ray fluorescence spectroscopy (≤ 21 keV) at 33 °C. The X-ray and electron spectroscopic measurements were supported by a comprehensive treatment of the noise components in charge sensitive preamplifiers. Calculations showed the potential benefits of using a SiC, rather than Si, JFET as the input transistor of such a preamplifier operating at high temperatures. The spectroscopic measurements, using both the 4H-SiC and GaAs photodiodes, are presented along with noise analysis to detangle the different noise components present in the reported spectrometers, identify the dominant source of noise, and suggest potential improvements for future spectrometers using the reported devices.