Miracle-dz/UniFAR-FTUs huggingface dataset:
AN ADAPTIVE BACKPROPAGATION NEURAL NETWORK FOR ARRHYTHMIA CLASSIFICATION USING R-R INTERVAL SIGNAL

Automatic detection and classification of cardiac arrhythmias with high accuracy and by using as little information as possible is highly useful in Holter monitoring of the high risk patients and in telemedicine applications where the amount of information which must be transmitted is an important issue. To this end, we have used an adaptive-learning-rate neural network for automatic classifi- cation of four types of cardiac arrhythmia. In doing so, we have employed a mix of linear, nonlinear, and chaotic features of the R-R interval signal to significantly reduce the required information needed for analysis, and substantially improve the accuracy, as compared to existing systems (both ECG-based and R-R interval- based). For normal sinus rhythm (NSR), premature ventricular contraction (PVC), ventricular fibrillation (VF), and atrial fibrillation (AF), the discrimination accu- racies of 99.59%, 99.32%, 99.73%, and 98.69% were obtained, respectively on the MIT-BIH database, which are superior to all existing classifiers.
Next Generation Sequencing Technologies: A Short Review

When the editorial board invited me to write this short review, I remembered my old dream since thirty years ago, is it possible for mankind to live without more health burden? Scientists can answer a lot of difficult questions like this one. The science is growing very fast and next generation sequencing technologies are currently the hottest topic in the field of human and animal genomics researches. In this mini review, I have highlighted some basic knowledge about next generation sequencing technologies and its value for human health.
β-catenin activity in late hypertrophic chondrocytes locally orchestrates osteoblastogenesis and osteoclastogenesis

Trabecular bone formation is the last step in endochondral ossification. This remodeling process of cartilage into bone involves blood vessel invasion and removal of hypertrophic chondrocytes (HTCs) by chondroclasts and osteoclasts. Periosteal- and chondrocyte-derived osteoprogenitors utilize the leftover mineralized HTC matrix as a scaffold for primary spongiosa formation. Here, we show genetically that β-catenin (encoded by Ctnnb1), a key component of the canonical Wnt pathway, orchestrates this remodeling process at multiple levels. Conditional inactivation or stabilization of β-catenin in HTCs by a Col10a1-Cre line locally modulated osteoclastogenesis by altering the Rankl:Opg ratio in HTCs. Lack of β-catenin resulted in a severe decrease of trabecular bone in the embryonic long bones. Gain of β-catenin activity interfered with removal of late HTCs and bone marrow formation, leading to a continuous mineralized hypertrophic core in the embryo and resulting in an osteopetrotic-like phenotype in adult mice. Furthermore, β-catenin activity in late HTCs is required for chondrocyte-derived osteoblastogenesis at the chondro-osseous junction. The latter contributes to the severe trabecular bone phenotype in mutants lacking β-catenin activity in HTCs. Summary: The conditional modulation of β-catenin activity in late hypertrophic chondrocytes locally regulates osteoclast differentiation and the transdifferentiation of chondrocytes into osteoblasts.
SIPPER: A flexible method to integrate heterogeneous data into a metabolic network

With the accumulation of available ‘omics’ data, developing automatic methods for integrating and analyzing them into a common context has become a key goal in bioinformatics. In this paper, we propose a general framework (called SIPPER) to integrate heterogeneous information from one or several external data sources into a metabolic network, and to perform an automatic, data-independent analysis. Our approach consists in including neighborhood/non-neighborhood information about proteins and genes into a metabolic network, via the admitted paradigm ‘gene produces enzyme(s)’. The integration of this neighborhood information uses a distance involving data about genomic location, or gene expression, or connectivity in a PPI network. It may also use any freely chosen notion of distance between genes or proteins. The resulting model is a new (so-called integrated) network. Its low weight paths are the reaction chains of the metabolic network that are catalyzed by groups of closely related enzymes (according to the information the user chooses to integrate). Consequently, integrating heterogeneous knowledge using SIPPER allows us to find associations between genes, enzymes and metabolic reaction chains involved together in the system behavior.
A Randomized Trial of a Cervical Pessary to Prevent Preterm Singleton Birth.

BACKGROUND Preterm birth is the leading cause of neonatal and infant death and of disability among survivors. It is unclear whether a pessary inserted around the cervix reduces the risk of preterm singleton birth. METHODS We conducted a multicenter, randomized, controlled trial comparing pessary placement with expectant management (control) in girls and women who were pregnant with singletons (singleton pregnancies) and who had a cervical length of 25 mm or less at 20 weeks 0 days to 24 weeks 6 days of gestation. Participants in either group who had a cervical length of 15 mm or less, at randomization or at subsequent visits, received treatment with vaginal progesterone. The primary outcome was spontaneous delivery before 34 weeks of gestation. RESULTS In an intention-to-treat analysis, there was no significant difference between the pessary group (465 participants) and the control group (467 participants) in the rate of spontaneous delivery before 34 weeks (12.0% and 10.8%, respectively; odds ratio in the pessary group, 1.12; 95% confidence interval, 0.75 to 1.69; P=0.57). There were no significant differences in the rates of perinatal death (3.2% in the pessary group and 2.4% in the control group, P=0.42), adverse neonatal outcome (6.7% and 5.7%, respectively; P=0.55), or neonatal special care (11.6% and 12.9%, respectively; P=0.59). The incidence of new or increased vaginal discharge was significantly higher in the pessary group than in the control group. CONCLUSIONS Among girls and women with singleton pregnancies who had a short cervix, a cervical pessary did not result in a lower rate of spontaneous early preterm delivery than the rate with expectant management. (Funded by the Fetal Medicine Foundation; Current Controlled Trials number, ISRCTN01096902.).
A Price Driven Hazard Approach to User Retention

Customer loyalty is crucial for internet services since retaining users of a service to ensure the staying time of the service is of significance for increasing revenue. It demands the retention of customers to be high enough to meet the needs for yielding profit for the internet servers. Besides, the growing of rich purchasing interaction feedback helps in uncovering the inner mechanism of purchasing intent of the customers. In this work, we exploit the rich interaction data of user to build a customers retention evaluation model focusing on the return time of a user to a product. Three aspects, namely the consilience between user and product, the sensitivity of the user to price and the external influence the user might receive, are promoted to effect the purchase intents, which are jointly modeled by a probability model based on Cox's proportional hazard approach. The hazard based model provides benefits in the dynamics in user retention and it can conveniently incorporate covariates in the model. Extensive experiments on real world purchasing data have demonstrated the superiority of the proposed model over state-of-the-art algorithms.
Circuit proposition for realization of approximated fractional order systems

This paper gives an effective alternative approach for circuit realization of a block containing a real zero and a pair of complex conjugate poles. The proposed approach is useful for analog realization of a class of integer order systems as well as fractional order systems (FOS) via integer order approximation. The proposed approach makes the system less sensitive to noise while the number of components used is a minimum. The method has been demonstrated by three examples of FOS via their integer approximation. Fractional order transfer functions have been approximated over a frequency range of (0.01-1000) rad/sec, and in all the three cases, the pair of complex conjugate poles and one of the real zeros of approximants have been realized through PSPICE simulation. For one example, the circuit has been implemented in hardware also. Experimental results are compared with PSPICE simulation results and theoretical results.
Under Consideration for Publication in J. Functional Programming a Predicative Analysis of Structural Recursion

We introduce a language based upon lambda calculus with products, coproducts and strictly positive inductive types that allows the definition of recursive terms. We present the implementation (foetus) of a syntactical check that ensures that all such terms are structurally recursive, i.e., recursive calls appear only with arguments structurally smaller than the input parameters of terms considered. To ensure the correctness of the termination checker, we show that all structurally recursive terms are normalizing with respect to a given operational semantics. To this end, we define a semantics on all types and a structural ordering on the values in this semantics and prove that all values are accessible with regard to this ordering. Finally, we point out how to do this proof predicatively using set based operators.
Enhancing shared RAID performance through online profiling

Enterprise storage systems are generally shared by multiple servers in a SAN environment. Our experiments as well as industry reports have shown that disk arrays show poor performance when multiple servers share one RAID due to resource contention as well as frequent disk head movements. We have studied IO performance characteristics of several shared storage settings of practical business operations. To avoid the IO contention, we propose a new dynamic data relocation technique on shared RAID storages, referred to as DROP, Dynamic data Relocation to Optimize Performance. DROP allocates/manages a group of cache data areas and relocates/drops the portion of hot data at a predefined sub array that is a physical partition on the top of the entire shared array. By analyzing profiling data to make each cache area owned by one server, we are able to determine optimal data relocation and partition of disks in the RAID to maximize large sequential block accesses on individual disks and at the same time maximize parallel accesses across disks in the array. As a result, DROP minimizes disk head movements in the array at run time giving rise to high IO performance. A prototype DROP has been implemented as a software module at the storage target controller. Extensive experiments have been carried out using real world IO workloads to evaluate the performance of the DROP implementation. Experimental results have shown that DROP improves shared IO performance greatly. The performance improvements in terms of average IO response time range from 20% to a factor 2.5 at no additional hardware cost.
Dialogues between nurses, patients with heart failure and their partners during a dyadic psychoeducational intervention: a qualitative study

Objectives To describe nurses’ documentation of the content in a psychoeducational intervention inspired by Stuifbergen’s model addressing cognitive, supportive and behavioural needs of patient–partner dyads affected by heart failure. Design A descriptive qualitative design was used analysing nurses’ documentation in a dialogue guide based on a health promotion model. Settings The dialogue guide was used during three nurse-led sessions at two heart failure clinics in Sweden with patients affected with heart failure and their partners during the years 2005–2008. Participants The dialogue guides from 71 patient–partner dyads were analysed using direct deductive content analyses. Patients’ mean age was 69 years and 31% were female, partners’ mean age was 67 years and 69% were female. Results The findings supported the conceptual health promotion model and identified barriers, recourses and self-efficacy described by the dyads within each category. Conclusion The dyads described that during the sessions, they had gained enhanced knowledge and greater confidence to handle their life situation and expressed that they needed psychoeducational support during the whole illness trajectory. The results may guide and help to improve content and quality when caring for patients affected with heart failure and their partners and also when designing new interventions. Trial registration number NCT02398799; Post-results.
Distributed and Autonomous Resource and Power Allocation for Wireless Networks

In this paper, a distributed and autonomous technique for resource and power allocation in orthogonal frequency division multiple access (OFDMA) femto-cellular networks is presented. Here, resource blocks (RBs) and their corresponding transmit powers are assigned to the user(s) in each cell individually without explicit coordination between femto-base stations (FBSs). The “allocatability” of each resource is determined utilising only locally available information of the following quantities: ; the required rate of the user; : the quality (i.e., strength) of the desired signal; : the frequency-selective fading on each RB; and : the level of interference incident on each RB. Using a fuzzy logic system, the time-averaged values of each of these inputs are combined to determine which RBs are most suitable to be allocated in a particular cell, i.e., which resources can be allocated such that the user requested rate(s) in that cell are satisfied. Fuzzy logic presents a completely novel, low-complexity methodology for inter-cell interference coordination (ICIC). A comprehensive study of this system in a femtocell environment is performed, yielding system performance improvements in terms of throughput, energy efficiency and coverage over state-of-the-art ICIC techniques.
Eurographics/acm Siggraph Symposium on Computer Animation (2006) Segment-based Human Motion Compression

As more and more human motion data are becoming widely used to animate computer graphics figures in many applications, the growing need for compact storage and fast transmission makes it imperative to compress motion data. We propose a data-driven method for efficient compression of human motion sequences by exploiting both spatial and temporal coherences of the data. We first segment a motion sequence into subsequences such that the poses within a subsequence lie near a low dimensional linear space. We then compress each segment using principal component analysis. Our method achieves further compression by storing only the key frames' projections to the principal component space and interpolating the other frames in-between via spline functions. The experimental results show that our method can achieve significant compression rate with low reconstruction errors.
Recovering traceability links between requirements and source code in the same series of software products

If traceability links between requirements and source code are not clarified when conducting maintenance and enhancements for the same series of software products, engineers cannot immediately find the correction location in the source code for requirement changes. However, manually recovering links in a large group of products requires significant costs and some links may be overlooked. Here, we propose a semi-automatic method to recover traceability links between requirements and source code in the same series of large software products. In order to support differences in representation between requirements and source code, we recover links by using the configuration management log as an intermediary. We refine the links by classifying requirements and code elements in terms of whether they are common or specific to the products. As a result of applying our method to real products that have 60KLOC, we have recovered valid traceability links within a reasonable amount of time. Automatic parts have taken 13 minutes 36 seconds, and non-automatic parts have taken about 3 hours, with a recall of 76.2% and a precision of 94.1%. Moreover, we recovered some links that were unknown to engineers. By recovering traceability links, software reusability will be improved, and software product line introduction will be facilitated.
Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models

We propose maximum likelihood estimation for learning Gaussian graphical models with a Gaussian (l22) prior on the parameters. This is in contrast to the commonly used Laplace (l1) prior for encouraging sparseness. We show that our optimization problem leads to a Riccati matrix equation, which has a closed form solution. We propose an efficient algorithm that performs a singular value decomposition of the training data. Our algorithm is O(NT2)-time and O(NT)-space for N variables and T samples. Our method is tailored to high-dimensional problems (N ≫ T), in which sparseness promoting methods become intractable. Furthermore, instead of obtaining a single solution for a specific regularization parameter, our algorithm finds the whole solution path. We show that the method has logarithmic sample complexity under the spiked covariance model. We also propose sparsification of the dense solution with provable performance guarantees. We provide techniques for using our learnt models, such as removing unimportant variables, computing likelihoods and conditional distributions. Finally, we show promising results in several gene expressions datasets.
Grid resource allocation and task scheduling for resource intensive applications

Evolution of grid has drawn attention from various resource intensive applications addressing domains of bio-informatics, astrology and multimedia, to name a few. Image analysis applications in both bio-sciences and astrophysics are explicitly built in modular fashion to exploit the potential offered by grid. In this paper, we present a framework for resource allocation and task scheduling, MARS (management architecture for resource services), which efficiently allocates resources for such resource intensive applications which can be represented as task interaction graph (TIG), while keeping makespan as minimum as the current state of resources in grid allows. Simulation experiments with MARS show a considerable improvement in job completion time and host utilization over traditional resource management and scheduling algorithms for grid
Biodegradable hydrogels and nanocomposite polymers: Synthesis and characterization for biomedical applications

OF DISSERTATION BIODEGRADABLE HYDROGELS AND NANOCOMPOSITE POLYMERS: SYNTHESIS AND CHARACTERIZATION FOR BIOMEDICAL APPLICATIONS Hydrogels are popular materials for biological applications since they exhibit properties like that of natural soft tissue and have tunable properties. Biodegradable hydrogels provide an added advantage in that they degrade in an aqueous environment thereby avoiding the need for removal after the useful lifetime. In this work, we investigated poly(β-amino ester) (PBAE) biodegradable hydrogel systems. To begin, the factors affecting the macromer synthesis procedure were studied to optimize the reproducibility of the resulting hydrogels made and create new methods of tuning the properties. Hydrogel behavior was then tuned by altering the hydrophilic/hydrophobic balance of the chemicals used in the synthesis to develop systems with linear and twophase degradation profiles. The goal of the research was to better understand methods of controlling hydrogel properties to develop systems for several biomedical applications. Several systems with a range of properties were synthesized, and their in vitro behavior was characterized (degradation, mechanical properties, cellular response, etc.). From these studies, materials were chosen to serve as porogen materials and an outer matrix material to create a composite scaffold for tissue engineering. In most cases, a porous three dimensional scaffold is ideal for cellular growth and infiltration. In this work, a composite with a slow degrading outer matrix PBAE with fast degrading PBAE microparticles was created. First, a procedure for developing porogen particles of controlled size from a fast-degrading hydrogel material was developed. Porogen particles were then entrapped in the outer hydrogel matrix during polymerization. The resulting composite systems were degraded and the viability of these systems as tissue engineering scaffolds was studied. In a second area of work, two polymer systems, one PBAE hydrogel and one solgel material were altered through the addition of iron oxide nanoparticles to create materials with remote controlled properties. Iron oxide nanoparticles have the ability to heat in an alternating magnetic field due to the relaxation processes. The incorporation of these nanoscale heating sources into thermosensitive polymer systems allowed remote actuation of the physical properties. These materials would be ideal for use in applications where the system can be changed externally such as in remote controlled drug delivery.
A new compensation framework for LQ control over lossy networks

In this paper we study the compensation problem of LQ control over lossy networks under TCP-like protocols. The system we consider is discrete, linear, and time-invariant. Firstly, a general framework for static compensation is proposed. Secondly, using dynamic programming and optimization method we are able to get governing equations for the controller and the compensator gains that are optimized. Under the new framework, the two popular compensators: zero-input and hold-input appear to be special cases of the proposed one, and the issue as to why none of the above two commonly adopted compensation strategies can be claimed to be better than the other is to a great extent clarified. An iterative algorithm is also presented to solve the governing equations for the optimal gains obtained in the paper. Following that we provide two numerical examples to validate the new approach.
Writing Fault-Tolerant Applications Using Resilient X 10 Kiyokuni Kawachiya

X10 is a programming language that internally supports distributed computing. X10 applications can run over multiple “places” (computing nodes), and perform distributed computing by changing the execution place using “at” statements. However, in a conventional X10 environment, when a node that handles a place fails, the entire processing of that X10 application is aborted. To address this problem, we have been extending X10 to “Resilient X10”, where a node failure is reported as a DeadPlaceException and the execution can continue using the remaining nodes. In this paper, we explain how to construct fault-tolerant distributed applications using Resilient X10 functions. Three basic methods are introduced to handle the node failures: (a) Ignore failures and use the results from the remaining nodes, (b) Reassign the failed node’s work to the remaining nodes, or (c) Restore the computation from a periodic snapshot. We also describe a fault-tolerant extension of the existing distributed X10 library DistArray. These modifications to add fault tolerance were very small, and the modified code can still run on standard X10 as long as node failure does not occur. The impacts on execution performance caused by the modifications are also evaluated.