Miracle-dz/UniFAR-FTUs huggingface dataset:
Initiation of Waves in BZ Encapsulated Vesicles Using Light - Towards Design of Computing Architectures

A gas free analogue of the Belousov-Zhabotinsky reaction catalysed by ferroin and encapsulated in phospholipid stabilised vesicles is reported. A reaction mixture which exhibits spontaneous oscillation and excitation transfer between vesicles was formulated. By adjusting the reagent concentrations a quiescent state with fewer spontaneous oscillations was achieved. Using relatively low power laser sources of specific wavelengths (green 532nm and blue 405nm) it was shown that waves could be reproducibly initiated within the BZ vesicles. Furthermore, despite the reduced excitability of the system overall the initiated waves exhibited vesicle to vesicle transfer. It was possible to manipulate single vesicles and design simple circuits based on a 2D validation of collision based circuits. Therefore, we conclude that this BZ system exhibits promise for computing applications based on 3D networks of vesicles.
The mitogenomic phylogeny of the Elasmobranchii (Chondrichthyes)

Abstract Here we present a mitogenomic perspective on the evolution of sharks and rays, being a first glance on the complete mitochondrial history of such an old and diversified group of vertebrates. The Elasmobranchii is a diverse subclass of Chondrichthyes, or cartilaginous fish, with about 1200 species of ocean- and freshwater-dwelling fishes spread all over the world’s seas, including some of the ocean’s largest fishes. The group dates back about 400 million years near the Devonian–Silurian boundary, being nowadays represented by several derivative lineages, mainly related to Mesozoic forms. Although considered of ecological, commercial and conservation importance, the phylogeny of this old group is poorly studied and still under debate. Here we apply a molecular systematic approach on 82 complete mitochondrial genomes to investigate the phylogeny of the Elasmobranchii. By using maximum likelihood (ML) and Bayesian analyses, we found a clear separation within the shark clade between the Galeomorphii and the Squalomorphii, as well as sister taxa relationships between the Carcharhiniformes and the Lamniformes. Moreover, we found that Pristoidei clusters within the Rhinobatoidei, having been recovered as the sister taxon of the Rhinobatos genus in a clade which also includes the basal Zapteryx. Our results also reject the Hypnosqualea hypothesis, which proposes that the Batoidea should be placed within the Selachii.
Character segmentation in text line via convolutional neural network

In this paper, we propose a character segmentation method for the task of text recognition. Specifically, our method is designed for splitting the adhesive and incomplete line characters under complex backgrounds. On one hand, we propose to split a text line by training a binary Convolutional Neural Network (CNN) classifier which identifies character images containing a whole character and gap images centering at the middle of two characters. On the other hand, due to the insufficient number of labels in training data, we adopt a weakly supervised training strategy, i.e. P-N Learning, to iteratively update the CNN using the samples that violates the predefined P and N constraints. Experiments on various datasets verifies the effectiveness of our method.
Offset curve deformation from skeletal animation

Skin deformation based on an underlying skeleton is a critical part of the modern animation pipeline. Linear blend skinning is fast but suffers volume loss at a bend and “candy wrapper” pinching under twist. More complex methods using dual quaternions [Kavan et al. 2007] and bind-point offset from intermediate curves [Singh and Fiume 1998] are nearly as fast and reduce these artifacts, but dual quaternions are limited only to rigid transformations and bind-point techniques continue to suffer from offset distortion, which increases with distance from the bind point, causing uneven stretching and self-intersection on the inside of a bend when offsets exceed the radius of curvature.
File mapping Rule-based DBMS and Natural Language Processing

This paper describes the system of storage, extract and processing of information structured similarly to the natural language. For recursive inference the system uses the rules having the same representation, as the data. The environment of storage of information is provided with the File Mapping (SHM) mechanism of operating system. In the paper the main principles of construction of dynamic data structure and language for record of the inference rules are stated; the features of available implementation are considered and the description of the application realizing semantic information retrieval on the natural language is given.
Design of the robot intelligent interaction and teleoperation via multilayer-cross control communication framework

Types of robot recently keeps evolving with various communication method used for the interaction between the robot and human operator. In recent years, various approaches of robot communication have been proposed and implemented on human-robot interaction. This paper introduces a framework design for robot intelligent interaction and teleoperation using multilayer-cross control communication. The framework's approach is using wireless environment with multiple communications which are used across heterogeneous type of devices and networks connections. This approach is applied using widely-used devices such as PC, PDA, Smartphone, or other computer-based devices in order to communicate with the robot and other component in the framework. The existing communication tools in those devices, such as Wireless LAN and Bluetooth, are utilized. In this approach, a computer acts as a middleware device that can be used to extend and expand the network capability and interaction distance between robot and human operator.
Effectiveness of second-generation light-emitting diode (LED) light curing units.

AIM The purpose of this study was to evaluate the effectiveness of three commercially available light emitting diode (LED) light curing units (LCU) (Elipar FreeLight--3M ESPE; UltraLume LED2--Ultradent; and Single V--BioArt) for polymerizing Z250-A3 composite (3M ESPE) using Knoop hardness, polymerization depth, and flexural strength properties. METHODS AND MATERIALS The XL 2500 (3M ESPE) LCU, which is a conventional halogen unit, was used as a control. In all cases the curing time was 20 seconds. Hardness was determined 24 hours after composite cure for 10 samples of 8 mm diameter and 2 mm height for each LCU tested. Samples were stored dry in a light-proof container prior to testing. The depth of cure of the composite was measured immediately after composite polymerization for each LCU using three samples 4 mm in diameter and 6 mm in height. Flexural strength was determined for five samples 24 hours after immersion in distilled water at 37 degrees C. Each sample measured 25 mm in length, 2 mm in width, and 2 mm in height for each LCU tested. CONCLUSION The results were treated statistically for comparison of the LCUs. In all cases the results obtained by LED LCUs were not different or were higher than a conventional halogen LCU. CLINICAL SIGNIFICANCE Second generation LED LCUs were as effective as/or more effective than a halogen LCU for polymerization of the used composite. The present study shows second generation LEDs have the potential to replace halogen LCUs.
Reproducibility and biological basis of in vivo T2* magnetic resonance imaging of liver metastasis of colorectal cancer

In this study, the reproducibility of T2* MR imaging in colorectal liver metastases was assessed and T2* values were correlated with the expression of the hypoxia‐related markers GLUT‐1 and CA‐IX as well as the relative vascular area, and the vessel density in resected tumors. The reproducibility of T2* was analyzed in 18 patients with in total 22 colorectal liver metastases using the Bland and Altman method for the 16th, 50th, and 84th percentile values. Immunohistochemical staining was performed on 17 resected tumors obtained from 16 patients. The median T2* of all liver metastases was 25.0 ± 5.6 ms vs. 23.0 ± 4.1 ms (median ± st.dev.) in normal liver. The coefficient of repeatability was 11.2 ms and the limits of agreement were −13.2 ms and 9.1 ms for median T2* values. On average, T2* showed fair reproducibility. No correlations between T2* values, hypoxia‐ and vascularity‐related markers were observed. Magn Reson Med, 70:1145–1152, 2013. © 2012 Wiley Periodicals, Inc.
Real-time hybrid ToF multi-camera rig fusion system for depth map enhancement

We present a full real-time implementation of a multilateral filtering system for depth sensor data fusion with 2-D data. For such a system to perform in real-time, it is necessary to have a real-time implementation of the filter, but also a real-time alignment of the data to be fused. To achieve an automatic data mapping, we express disparity as a function of the distance between the scene and the cameras, and simplify the matching procedure to a simple indexation procedure. Our experiments show that this implementation ensures the fusion of 3-D data and 2-D data in real-time and with high accuracy.
Stride Segmentation during Free Walk Movements Using Multi-Dimensional Subsequence Dynamic Time Warping on Inertial Sensor Data

Changes in gait patterns provide important information about individuals’ health. To perform sensor based gait analysis, it is crucial to develop methodologies to automatically segment single strides from continuous movement sequences. In this study we developed an algorithm based on time-invariant template matching to isolate strides from inertial sensor signals. Shoe-mounted gyroscopes and accelerometers were used to record gait data from 40 elderly controls, 15 patients with Parkinson’s disease and 15 geriatric patients. Each stride was manually labeled from a straight 40 m walk test and from a video monitored free walk sequence. A multi-dimensional subsequence Dynamic Time Warping (msDTW) approach was used to search for patterns matching a pre-defined stride template constructed from 25 elderly controls. F-measure of 98% (recall 98%, precision 98%) for 40 m walk tests and of 97% (recall 97%, precision 97%) for free walk tests were obtained for the three groups. Compared to conventional peak detection methods up to 15% F-measure improvement was shown. The msDTW proved to be robust for segmenting strides from both standardized gait tests and free walks. This approach may serve as a platform for individualized stride segmentation during activities of daily living.
Face Detection using Variance based Haar-Like feature and SVM

This paper proposes a new approach to perform the problem of real-time face detection. The proposed method combines primitive Haar-Like feature and variance value to construct a new feature, so-called Variance based Haar-Like feature. Face in image can be represented with a small quantity of features using this new feature. We used SVM instead of AdaBoost for training and classification. We made a database containing 5,000 face samples and 10,000 non-face samples extracted from real images for learning purposed. The 5,000 face samples contain many images which have many differences of light conditions. And experiments showed that face detection system using Variance based Haar-Like feature and SVM can be much more efficient than face detection system using primitive Haar-Like feature and AdaBoost. We tested our method on two Face databases and one Non-Face database. We have obtained 96.17% of correct detection rate on YaleB face database, which is higher 4.21% than that of using primitive Haar-Like feature and AdaBoost.
Influenza A(H1N1)v pandemic in the dialysis population: first wave results from an international survey

Abstract Background. After the first cases of influenza A(H1N1)v in Mexico and the USA became public, Fresenius Medical Care established a case-based reporting of cases for all of its dialysis clinics located in Europe, Middle East, Africa and Latin America. This paper aims to describe mortality rates of patients on dialysis and to assess the risk profiles. Methods. The survey was developed in Lotus Notes with a secure browser-based form. The form was open to 602 Fresenius Medical Care clinics located in Europe, Middle East, Africa and Latin America. Results. As of 3 September 2009, 306 cases have been reported by 85 clinics located in Argentina, Chile, Brazil, UK and Spain. The mean age was 52.7 ± 17.7 years. The majority of cases (70.6%) were from 20- to 44-year-old and 45- to 64-year-old subgroups. Moreover, 35.3% had no associated comorbidity, 20.3% had two and 4.6% three comorbidities, with heart disease being the most frequent. Fever was the most common symptom, present in 94.4% of the cases, followed by cough (78.8%) and muscle and joint pain (69.3%). Eighty-seven percent were treated with antiviral agents, the majority with oseltamivir. One hundred and three patients (34%) were admitted to hospital because of influenza. Pneumonia was reported for 69 cases, out of which 52 patients belonged to a high-risk group. Mortality rate of all the patients (confirmed, probable and suspected cases) was around 5%. Conclusion. End-stage renal disease patients should be included in first ranks of the priority list for the influenza A (H1N1)v vaccine, as already advocated by some healthcare authorities.
The synthesis of cloth objects

In image synthesis, cloth objects such as clothes are most often modelled as textures mapped onto rigid surfaces. However, in order to represent such objects more realistically, their physical properties must be examined. This paper describes a method for modelling cloth material hanging in three dimensions when supported by any number of constraint points. The cloth synthesized with this model contains folds and appears more realistic than simple texture mapping. This paper also describes a method for rendering the cloth once its free-hanging shape has been determined.The computation of the surface of a free-hanging cloth is performed in two stages. The first stage approximates the shape of the surface which is interior to the constraint points, and the second stage performs a relaxation process on all points on the surface to arrive at a close approximation to its shape. The rendering of the surfaces is done using a ray-tracer which treats the surface as a mesh of line segments.
Neural Networks for Segmenting Neuronal Structures in EM Stacks

A pixel classifier is driving our winning approach to neural structure segmentation in electron microscopy images. Without explicit feature computation, the label of each pixel (membrane or nonmembrane) is predicted from raw pixel values in a square window centered on it. The classifier is a special type of feed-forward neural network trained by plain gradient descent. The input layer maps each window pixel to a neuron. It is followed by a succession of convolutional and maxpooling layers which preserve 2D information and extract features with increasing levels of abstraction. The output layer produces a calibrated probability for each class, and is subjected to very mild post-processing. The approach outperformed all other entries of the competition in all considered metrics: values for rand error, warping error and pixel error were 48 · 10−3, 434 · 10−6 and 60 · 10−3, respectively.
Controlling Racial Prejudice

The malleability of stereotyping matters in social psychology and in society. Previous work indicates rapid amygdala and cognitive responses to racial out-groups, leading some researchers to view these responses as inevitable. In this study, the methods of social-cognitive neuroscience were used to investigate how social goals control prejudiced responses. Participants viewed photographs of unfamiliar Black and White faces, under each of three social goals: social categorization (by age), social individuation (vegetable preference), and simple visual inspection (detecting a dot). One study recorded brain activity in the amygdala using functional magnetic resonance imaging, and another measured cognitive activation of stereotypes by lexical priming. Neither response to photos of the racial out-group was inevitable; instead, both responses depended on perceivers' current social-cognitive goal.
Impact of pay-for-performance on mortality in diabetes patients in Taiwan

Background:The impact of pay-for-performance (P4P) programs on long-term mortality for chronic illnesses, especially diabetes mellitus, has been rarely reported. Several studies described the favorable impact of P4P for diabetes mellitus on medical utilizations or intermediate outcomes. Therefore, this study aimed to investigate the impact of a P4P program on mortality in patients with type 2 diabetes. Methods:The P4P group in this population-based cohort study was 2090 individuals with a primary diagnosis of type 2 diabetes who had been newly enrolled in the P4P program of Taiwan between January 1, 2004 and December 31, 2004. Matched by 1:1 ratio, patients in the non-P4P group were selected by propensity score matching (PSM) for sex, age, the first year of diagnosis as diabetes, and 32 other potential confounding factors. Mean (SD) age was 60.91 (12.04) years when diabetes was first diagnosed and mean (SD) duration of diabetes was 4.3 (1.9) years at baseline. The time-dependent Cox regression model was used to explore the impact of P4P on all-cause mortality. Results:During a mean of 5.13 years (SD = 1.07 years) of follow-up, 206 and 263 subjects died in the P4P group and the non-P4P group, respectively. After adjusting for the potential confounding factors at baseline, survival was significantly longer in the P4P group than in the non-P4P group (hazard ratio, 0.76 [95% confidence interval, 0.64–0.92], P = 0.004, by log-rank test). This decrease in mortality is equivalent to one less death for every 37 patients who were treated in the P4P program for 5.13 years. In this study, the P4P program significantly increased the medical utilization of physician visits and diabetes-related examinations, improved the adherence of oral hypoglycemic drugs during the first 3 years and that of insulin during the second 3 years, and was negatively associated with risk of cancer and chronic kidney disease. In annual health expense, there was no significant difference between P4P and non-P4P groups, P = 0.430. Conclusions:As compared with control, pay-for-performance program significantly improved survival in patients with diabetes without increasing the medical cost. The P4P group had significantly lower risk of cancer and chronic kidney disease.
Active Learning with Monotonicity Constraints

In many applications of data mining it is known beforehand that the response variable should be increasing (or decreasing) in the attributes. We propose two algorithms to exploit such monotonicity constraints for active learning in ordinal classification in two different settings. The basis of our approach is the observation that if the class label of an object is given, then the monotonicity constraints may allow the labels of other objects to be inferred. For instance, from knowing that loan applicant a is rejected, it can be concluded that all applicants that score worse than a on all criteria should be rejected as well. We propose two heuristics to select good query points. These heuristics make a selection based on a point’s potential to determine the labels of other points. The algorithms, each implemented with the proposed heuristics, are evaluated on artificial and real data sets to study their performance. We conclude that exploitation of monotonicity constraints can be very beneficial in active learning.
Vasovagal syncope.

BACKGROUND Vasovagal syncope is the most common type of syncope and is one of the most difficult types to manage. PURPOSE This article reviews the status of mechanisms, diagnosis, and management of vasovagal syncope. DATA SOURCES MEDLINE search for English-language and German-language articles on vasovagal syncope published up to June 1999. STUDY SELECTION Case reports and series, clinical trials, research investigations, and review articles from peer-reviewed journals. DATA EXTRACTION Findings were summarized and discussed individually. Summaries were made in table format. Statistical analysis of combined data was inappropriate because of differences among studies in patient selection, testing, and follow-up. DATA SYNTHESIS The population of patients with vasovagal syncope is highly heterogeneous. Triggers of vasovagal syncope are likely to be protean, and many potential central and peripheral triggers have been identified. The specific mechanisms underlying the interactions among decreased preload, sympathetic and parasympathetic modulation, vasodilation, and cardioinhibition remain unknown. Tilt-table testing is a widely used diagnostic tool. The test results should be interpreted in the context of patients' clinical presentations and with an understanding of the sensitivity and specificity of the test. Assessment of therapeutic outcomes has been difficult, primarily because of patient heterogeneity, the large number of pharmacologic agents available for therapy, and the sporadic nature of the syndrome complex. CONCLUSIONS Vasovagal syncope is a common clinical syndrome that has complex and variable mechanisms and is difficult to manage. Advancements are being made in laboratory investigations of its triggering mechanisms. Randomized, controlled trials of pharmacologic and nonpharmacologic interventions are needed. Mechanism-targeted therapeutic trials may improve clinical outcomes.
Low complexity V-BLAST for massive MIMO

In an uplink massive multiple-input-multiple-output deployment with distributed single-antenna users and a large base-station array, we consider several combinations of receivers using linear combiners (maximum ratio combining (MRC) and zero forcing (ZF)) in conjunction with Vertical Bell Laboratories Layered Space Time (V-BLAST). We show that the performance loss of MRC relative to ZF can be removed in certain situations through the use of V-BLAST. Furthermore, we develop a low complexity ordering scheme which results in a V-BLAST scheme with MRC which has much less complexity than a single ZF linear combiner. An analysis of the signal-to-interference-and-noise-ratio at each stage of the V-BLAST approach is also given to support the findings of the proposed technique.
Video Assist: a customizable tool for analyzing video data

Analyzing real world events captured in video is often a very time consuming and labor intensive process. The paper describes Video Assist, a software tool designed to assist encoding and analyzing actions recorded on video tape. It presents the design rationales underlying its features such as: customizable objects and their attributes, their integration with an outliner and time line diagrams, their directly manipulable interface, and its mechanism for supporting consistent labeling. It reports on the use of this tool in analyzing a software review process meeting recorded on video tape. Using this example, it illustrates how Video Assist implements the phases and the operations of ESDA (Exploratory Sequential Data Analysis) and how they can dramatically simplify the process of analyzing the sequential data in video. It concludes by discussing the current limitations of the tool and the plans for future extension.