Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of surface EMG signals using harmonic wavelet packet transform

In this paper, an efficient method based on the discrete harmonic wavelet packet transform (DHWPT) is presented to classify surface electromyographic (SEMG) signals. After the relative energy of SEMG signals in each frequency band had been extracted by the DHWPT, a genetic algorithm was utilized to select appropriate features in order to reduce the feature dimensionality. Then, the selected features were used as the input vectors to a neural network classifier to discriminate four types of prosthesis movements. Compared with other classification methods, the proposed method provided high classification accuracy in experimental research. In addition, this method could also save a lot of computational time because the DHWPT has a fast algorithm based on the fast Fourier transform for numerical implementation.
Body image distortions and muscle dysmorphia symptoms among Asian men : do exercise status and type matter?

Theoretical Framework: Body image distortions and muscle dysmorphia symptoms were assessed among 78 Asian men who engaged in regular resistance training, aerobic training or did not engage in either. Method: Body fat and muscularity were measured and participants also completed the Muscle Dysmorphia Disorder Inventory. Results: Resistance trained men selected a body shape ideal that was higher in muscularity and lower in body fat. Aerobically trained men also reported higher perceived current Body Fat even though their actual levels were close to their ideal. Conclusion: The results suggest that specificity in body image distortion (e.g., perceived current-ideal versus perceived current-actual) when examining body image distortions might reduce conflicting findings in extant research.
SketchSoup: Exploratory Ideation Using Design Sketches

A hallmark of early stage design is a number of quick‐and‐dirty sketches capturing design inspirations, model variations and alternate viewpoints of a visual concept. We present SketchSoup, a workflow that allows designers to explore the design space induced by such sketches. We take an unstructured collection of drawings as input, along with a small number of user‐provided correspondences as input. We register them using a multi‐image matching algorithm, and present them as a 2D interpolation space. By morphing sketches in this space, our approach produces plausible visualizations of shape and viewpoint variations despite the presence of sketch distortions that would prevent standard camera calibration and 3D reconstruction. In addition, our interpolated sketches can serve as inspiration for further drawings, which feed back into the design space as additional image inputs. SketchSoup thus fills a significant gap in the early ideation stage of conceptual design by allowing designers to make better informed choices before proceeding to more expensive 3D modelling and prototyping. From a technical standpoint, we describe an end‐to‐end system that judiciously combines and adapts various image processing techniques to the drawing domain—where the images are dominated not by colour, shading and texture, but by sketchy stroke contours.
Support vector machine with dynamic time-alignment kernel for speech recognition

A new class of Support Vector Machine (SVM) which is applicable to sequential-pattern recognition is developed by incorporating an idea of non-linear time alignment into the kernel. Since time-alignment operation of sequential pattern is embedded in the kernel evaluation, same algorithms with the original SVM for training and classiﬁcation can be employed without modiﬁcations. Furthermore, frame-wise evaluation of kernel in the proposed SVM (DTAK-SVM) enables frame-synchronous recognition of sequential pattern, which is suitable for continuous speech recognition. Preliminary experiments of speaker-dependent 6 voiced-consonants recognition demonstrated excellent recognition performance of more than 98% in correct classiﬁcation rate, whereas 93% by hidden Markov models (HMMs).
On semi-supervised clustering via multiobjective optimization

Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clustering, in particular, explicitly integrates both information about the data distribution and about class memberships into the clustering process. In this paper, the potential of a multiobjective formulation of the semi-supervised clustering problem is explored, and two evolutionary multiobjective approaches to the problem are outlined. Experimental results demonstrate practical performance benefits of this methodology, including an improved classification performance and an increased robustness towards annotation errors.
Efficient list decoding of punctured Reed-Muller codes

The Reed-Muller (RM) code encoding $n$-variate degree-$d$ polynomials over $\mathbb{F}_q$ for $d < q$ has relative distance $1-d/q$ and can be list decoded from a $1-O(\sqrt{d/q})$ fraction of errors. In this work, for $d \ll q$, we give a length-efficient puncturing of such codes which (almost) retains the distance and list decodability properties of the Reed-Muller code, but has much better rate. Specificially, when $q \gtrsim d^2/\epsilon^2$, we given an explicit rate $\Omega_d(\epsilon)$ puncturing of Reed-Muller codes which have relative distance at least $(1-\epsilon)$ and efficient list decoding up to $(1-\sqrt{\epsilon})$ error fraction. This almost matches the performance of random puncturings which work with the weaker field size requirement $q \gtrsim d/\epsilon^2$. We can also improve the field size requirement to the optimal (up to constant factors) $q \gtrsim d/\epsilon$, at the expense of a worse list decoding radius of $1-\epsilon^{1/3}$ and rate $\Omega_d(\epsilon^2)$. The first of the above trade-offs is obtained by substituting for the variables functions with carefully chosen pole orders from an algebraic function field; this leads to a puncturing for which the RM code is a subcode of a certain algebraic-geometric code (which is known to be efficiently list decodable). The second trade-off is obtained by concatenating this construction with a Reed-Solomon based multiplication friendly pair, and using the list recovery property of algebraic-geometric codes.
Motivators and Barriers to Recruiting Prior Service Members in the IRR

Given the reliance of military recruiting efforts on prior service enlistments, it is imperative that motivators and barriers to prior service recruiting receive greater research attention. This research applied the theory of planned behavior ( Ajzen, 1991, 2001) to predict prior service members’ intentions to join the Reserve, thereby advancing research beyond post hoc evaluation of existing recruitment strategies. Results indicated that prior service members in the Individual Ready Reserve were more likely to intend to join the Reserve if they held positive attitudes toward the Reserve and felt that alternative careers compared negatively against military service. Commitment mediated the relationship between satisfaction and Reserve intentions and perceived social support had a greater effect on Reserve intentions when influence of relevant others was high.
A Flexible Architecture for a Push-based P2P Database

Originally developed for file sharing, P2P concepts are predestinated to realize information sharing in a more general way. Combined with the well known concept of loosely coupled multidatabases they provide a promising fundament for sharing data and metadata across autonomous and heterogenous data sources. The Digame architecture allows each participating data source to decide autonomously, which kind of information to share. Data and schema updates on these shares are propagated actively to subscribing peers, without having to be managed by a central authority. Each peer is now able to maintain a replica of all the data demanded locally, regardless of where the data is stored originally. In this context we have identified several link patterns, indispensable for understanding and designing an information grid.
Barcelona Economics Working Paper Series Multiple Filtering Devices for the Estimation of Cyclical Dsge Models Multiple …ltering Devices for the Estimation of Cyclical Dsge Models

We propose a method to estimate time invariant cyclical DSGE models using the information provided by a variety of …lters. We treat data …ltered with alternative procedures as contaminated proxies of the relevant model-based quantities and estimate structural and non-structural parameters jointly using a signal extraction approach. We employ simulated data to illustrate the properties of the procedure and compare our conclusions with those obtained when just one …lter is used. We revisit the role of money in the transmission of monetary business cycles.
The Cattle are "Ghanaians" but the Herders are Strangers: Farmer ⴀ૰-ȁHerder Conflicts, Expulsion Policy, and Pastoralist Question in Agogo, Ghana

The phenomenon of farmer ⴀ૰-ȁherders conflict across West Africa has prompted management strategies by several governments across the subcontinent. One of the conflict resolution mechanisms has been the policy of expulsion, which the Ghanaian state adopted as a response to incessant conflict between the settled agriculturalists and migrating Fulani herders. This paper focuses on migration and conflict as well as the intrigues and politics of expulsion of Fulani pastoralist from Agogo town in Ghana since 2009. There are multiple factors responsible for the migration of Fulani herders to Agogo area that are linked to climate change. We also examine the social and political factors triggering the expulsion as well as agitation to expel the Fulani. Counter to this we examine the Fulani reactions towards this development. Through this we also critique the policy of expulsion as a means of dealing with the pastoralist question. By means of a critical assessment of the conflict we offer strategies for policy and reconciliation.
Identifying Time-Varying Neuromuscular Response: A Recursive Least-Squares Algorithm with Pseudoinverse

Effectiveness of haptic guidance systems depends on how humans adapt their neuromuscular response to the force feedback. A quantitative insight into adaptation of neuromuscular response can be obtained by identifying neuromuscular dynamics. Since humans are likely to vary their neuromuscular response during realistic control scenarios, there is a need for methods that can identify time-varying neuromuscular dynamics. In this work an identification method is developed which estimates the impulse response of time-varying neuromuscular system by using a Recursive Least Squares (RLS) method. The proposed method extends the commonly used RLS-based method by employing the pseudo inverse operator instead of the inverse operator. This results in improved robustness to external noise. The method was validated in a human in-the-loop experiment. The neuromuscular estimates given by the proposed method were more accurate than those obtained with the commonly used RLS-based method.
Evaluation of an Ultra-Wideband Propagation Channel

This paper describes the results of an ultrawideband (UWB) propagation study in which arrays of propagation measurements were made. After a description of the propagation measurement technique, an approach to the spatial and temporal decomposition of an array of measurements into wavefronts impinging on the receiving array is presented. Based on a modification of the CLEAN algorithm, this approach provides estimates of time-of-arrival, angle of arrival, and waveform shape. This technique is applied to 14 arrays of indoor propagation measurements made in an office/laboratory building. Statistical description of the results is presented, based on a clustering model for multipath effects. The parameters of these statistical models are compared to results derived for narrowband signal propagation in the indoor environment. I. Ultra-Wideband Radio An ultra-wideband (UWB) radio signal is one whose fractional bandwidth (i.e., its 3 dB bandwidth divided its center frequency) is large, typically over 0.25. Such signals are generated by driving an antenna with very short electrical pulses (on the order of a few nanoseconds to fractions of a nanosecond in duration). Hence these radio systems often are referred to as short-pulse or impulse radio systems. Typically the radiated pulse signals are generated without the use of local oscillators or mixers. The antennas in UWB systems are significant pulseshaping filters. In addition, many environments provide a wealth of resolvable multipath. As a result, the received signal often bears little resemblance to the signal driving the transmitter’s antenna. If the result of an impulse transmission in free space is a received waveform p(t), then in a typical environment, a typical multipath model for the signal r(t) received over an indoor propagation channel is
Every-2-week darbepoetin alfa is comparable to rHuEPO in treating chemotherapy-induced anemia. Results of a combined analysis.

The safety and efficacy of darbepoetin alfa (Aranesp) at 3.0 microg/kg administered every 2 weeks and recombinant human erythropoietin (rHuEPO) given as 40,000 U weekly or 150 U/kg three times weekly were evaluated by pooling data from three darbepoetin alfa clinical studies. All studies enrolled anemic (hemoglobin < or = 11.0 g/dL) patients receiving multicycle chemotherapy. Open-label study drug was administered by subcutaneous injection. Hemoglobin concentrations, red blood cell transfusion requirements, and standard safety parameters were evaluated. Of 260 patients who received darbepoetin alfa at 3.0 microg/kg every 2 weeks and 115 patients who received rHuEPO three times weekly or once weekly, hematopoietic response (change in hemoglobin from baseline of > or = 2 g/dL or hemoglobin concentration of > or = 12 g/dL) was achieved in 71% (95% confidence interval [CI] = 65%-78%) of patients who received darbepoetin alfa every 2 weeks, comparable to the response in patients who received rHuEPO (71%; 95% CI = 61%-81%). The mean increase in hemoglobin concentration over 13 weeks was also similar: 1.48 g/dL (95% CI = 1.28-1.68 g/dL) for darbepoetin alfa and 1.31 g/dL (95% CI = 0.97-1.64 g/dL) for rHuEPO. The proportion of patients in the darbepoetin alfa group requiring transfusions was lower (7%; 95% CI = 4%-11%) than that in the rHuEPO group (14%; 95% CI = 8%-22%). Darbepoetin alfa every 2 weeks was well tolerated with a safety profile comparable to that of rHuEPO. In conclusion, darbepoetin alfa at a dose of 3.0 microg/kg given every 2 weeks safely increases hemoglobin concentration to the same extent as rHuEPO.
Treatment of myasthenia gravis exacerbation with intravenous immunoglobulin: a randomized double-blind clinical trial.

BACKGROUND The optimal dose of intravenous immunoglobulin (IVIG) in acute exacerbation of myasthenia gravis remains unknown. Increasing the treatment duration might provide added efficacy. OBJECTIVE To determine the optimal dose of IVIG for treating myasthenia gravis exacerbation. DESIGN Randomized double-blind placebo-controlled multicenter trial designed to demonstrate superiority of the 2 g/kg dose over the 1 g/kg dose of IVIG, conducted between November 13, 1996, and October 26, 2002. PARTICIPANTS One hundred seventy-three patients aged 15 to 85 years with acute exacerbation of myasthenia gravis. INTERVENTION Participants were randomly assigned to receive 1 g/kg of IVIG on day 1 and placebo on day 2 (group 1) vs 1 g/kg of IVIG on 2 consecutive days (group 2). MAIN OUTCOME MEASURE Improvement in the myasthenic muscular score after 2 weeks. RESULTS The mean improvements in the myasthenic muscular scores after 2 weeks were 15.49 points (95% confidence interval, 12.09-18.90 points) in group 1 and 19.33 points (95% confidence interval, 15.82-22.85 points) in group 2. However, the difference between the 2 groups was not significant (effect size, 3.84 [95% confidence interval, -1.03 to 8.71]; P = .12). CONCLUSION This trial found no significant superiority of 2 g/kg over 1 g/kg of IVIG in the treatment of myasthenia gravis exacerbation.
Association of FK506 binding protein 5 (FKBP5) gene rs4713916 polymorphism with mood disorders: a meta-analysis

Background: Several studies have investigated the association of FKBP5 gene polymorphisms with mood disorders, but findings are not always consistent. The aim of our study was to assess the association of FKBP5 gene polymorphisms with mood disorders using a meta-analysis. Methods: Data were collected from the following electronic databases: PubMed, Elsevier Science Direct, Cochrane Library, Chinese Biomedical Literature Database, China National Knowledge Infrastructure and Wanfang, with the last report up to March 2010. Meta-analysis was performed in a fixed/random effect model. Results: We identified six studies using search, and one study was excluded because of unavailable data. One study contained data on two different ethnicities and we treated them independently. Thus, six separate studies (2655 cases and 3593 controls) were included in the meta-analysis. Meta-analysis was performed for three FKBP5 gene polymorphisms (rs1360780, rs3800373 and rs4713916) in overall and Caucasian populations. We did not detect any association of FKBP5 gene rs1360780 and rs3800373 polymorphisms with mood disorders (p > 0.05). However, a significant association of FKBP5 gene rs4713916 polymorphism with mood disorders was found, and the heterozygous individual (GA genotype) was more susceptible to mood disorders in comparison to homozygous analogues (GG or AA genotype) [overall: GA vs. GG: OR (odds ratio) = 1.20, 95% CI (confidence interval) = 1.03–1.40, p = 0.02; GA vs. AA: OR = 1.44, 95% CI = 1.09–1.90, p = 0.009; Caucasian: GA vs. GG: OR = 1.22, 95% CI = 1.04–1.44, p = 0.01; GA vs. AA: OR = 1.43, 95% CI = 1.09–1.89, p = 0.01]. Conclusion: This meta-analysis shows that mood disorders are associated with FKBP5 gene rs4713916 polymorphism, but not with rs1360780 and rs3800373.
Latina Transgender Women’s Interactions with Law Enforcement in Los Angeles County

To date, very few researchers have explored transgender women’s interactions with law enforcement agencies and officers. Addressing this research gap, this study examines the interactions of Latina transgender women with law enforcement. The investigators conducted semi-structured interviews of 220 low-income Latina transgender women recruited from a variety of community-based organizations and sources across Los Angeles County, California. The findings lend support to the conclusion that transgender women, and especially transgender women of colour, are common victims of verbal harassment, physical assault, and sexual assault perpetrated by law enforcement officers. The findings also lend support to the propositions that many transgender women perceive their personal interactions with law enforcement officers negatively, and view reports of crime against them as mishandled or ignored. The findings are discussed in light of the implications for law enforcement’s interactions with transgender women and transgender communities of colour in particular.
Joint Smoothing, Tracking, and Forecasting Based on Continuous-Time Target Trajectory Fitting

We present a continuous time state estimation framework that unifies traditionally individual tasks of smoothing, tracking, and forecasting (STF), for a class of targets subject to smooth motion processes, e.g., the target moves with nearly constant acceleration or affected by insignificant noises. Fundamentally different from the conventional Markov transition formulation, the state process is modeled by a continuous trajectory function of time (FoT) and the STF problem is formulated as an online data fitting problem with the goal of finding the trajectory FoT that best fits the observations in a sliding time-window. Then, the state of the target, whether the past (namely, smoothing), the current (filtering) or the near-future (forecasting), can be inferred from the FoT. Our framework releases stringent statistical modeling of the target motion in real time, and is applicable to a broad range of real world targets of significance such as passenger aircraft and ships which move on scheduled, (segmented) smooth paths but little statistical knowledge is given about their real time movement and even about the sensors. In addition, the proposed STF framework inherits the advantages of data fitting for accommodating arbitrary sensor revisit time, target maneuvering and missed detection. The proposed method is compared with state of the art estimators in scenarios of either maneuvering or non-maneuvering target.
Segmentation and Classification of Cine-MR Images Using Fully Convolutional Networks and Handcrafted Features

Three-dimensional cine-MRI is of crucial importance for assessing the cardiac function. Features that describe the anatomy and function of cardiac structures (e.g. Left Ventricle (LV), Right Ventricle (RV), and Myocardium(MC)) are known to have significant diagnostic value and can be computed from 3D cine-MR images. However, these features require precise segmentation of cardiac structures. Among the fully automated segmentation methods, Fully Convolutional Networks (FCN) with Skip Connections have shown robustness in medical segmentation problems. In this study, we develop a complete pipeline for classification of subjects with cardiac conditions based on 3D cine-MRI. For the segmentation task, we develop a 2D FCN and introduce Parallel Paths (PP) as a way to exploit the 3D information of the cine-MR image. For the classification task, 125 features were extracted from the segmented structures, describing their anatomy and function. Next, a two-stage pipeline for feature selection using the LASSO method is developed. A subset of 20 features is selected for classification. Each subject is classified using an ensemble of Logistic Regression, Multi-Layer Perceptron, and Support Vector Machine classifiers through majority voting. The Dice Coefficient for segmentation was 0.95+-0.03, 0.89+-0.13, and 0.90+-0.03 for LV, RV, and MC respectively. The 8-fold cross validation accuracy for the classification task was 95.05% and 92.77% based on ground truth and the proposed methods segmentations respectively. The results show that the PPs increase the segmentation accuracy, by exploiting the spatial relations. Moreover, the classification algorithm and the features showed discriminability while keeping the sensitivity to segmentation error as low as possible.