Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Sirolimus-Eluting Stents on Outcome in Diabetic Patients: A SIRIUS (SIRolImUS-coated Bx Velocity balloon-expandable stent in the treatment of patients with de novo coronary artery lesions) Substudy

Background—Randomized clinical trials have shown that a sirolimus-eluting stent significantly reduces restenosis after percutaneous coronary revascularization. Diabetic patients are known to have a higher risk of restenosis compared with nondiabetic patients. The purpose of this analysis was to determine the impact of sirolimus-eluting stents on outcomes of diabetic compared with nondiabetic patients. Methods and Results—The SIRIUS (SIRolImUS-coated Bx Velocity balloon-expandable stent in the treatment of patients with de novo coronary artery lesions) trial is a randomized, double-blind study that compared sirolimus-eluting and bare metal stent implantation in 1058 patients with de novo native coronary artery lesions. Diabetes mellitus was present in 279 (26%) patients (diabetes mellitus group, 131 patients received sirolimus-eluting stents and 148 patients received bare metal stents) and was absent in 778 patients (no–diabetes mellitus group, 402 patients received sirolimus-eluting stents and 376 patients received bare metal stents). At 270 days, target lesion revascularization was reduced in diabetic patients from 22.3% with bare metal stents to 6.9% with sirolimus-eluting stents (P <0.001) and in nondiabetic patients from 14.1% to 2.99% (P <0.001), respectively. Major adverse cardiac events were reduced in diabetic patients from 25% with bare metal stents to 9.2% with sirolimus-eluting stents (P <0.001) and from 16.5% to 6.5% (P <0.001) in nondiabetic patients, respectively. Conclusions—Implantation of sirolimus-eluting stents compared with bare metal stents in de novo coronary lesions reduces major adverse cardiac events in patients with and without diabetes mellitus. However, among patients receiving sirolimus-eluting stents, there remains a trend toward a higher frequency of repeat intervention in diabetic patients compared with nondiabetic patients, particularly in the insulin-requiring patients.
Knot concordance and Heegaard Floer homology invariants in branched covers

By studying the Heegaard Floer homology of the preimage of a knot K in S^3 inside its double branched cover, we develop simple obstructions to K having finite order in the classical smooth concordance group. As an application, we prove that all 2-bridge knots of crossing number at most 12 for which the smooth concordance order was previously unknown have infinite smooth concordance order.
Optimal Continuous Order Quantity (s, S) Policies - The 45-Degrees Algorithm

The most recent optimization algorithm for (s,S) order policies with continuous demand was developed by Federgruen and Zipkin (1985). This was also the first efficient algorithm, which uses policy iteration instead of discretization. Zheng and Federgruen (1991) developed an even more efficient algorithm for computing discrete order quantity (s,S) inventory policies. Since the continuous case prohibits enumeration, this algorithm does not apply to continuous order quantity systems. In this paper an efficient algorithm for continuous order quantity (s,S) policies is developed. A marginal cost approach is used for determining the optimal s. Furthermore, we construct two aid functions (generated by the optimality conditions for s and S), and exploiting their special properties a simple and efficient algorithm is obtained. The algorithm converges monotonically, such that at every iteration a policy improvement is obtained. Since every iteration finds a local minimum of the expected average cost, the number of iterations is at most N, where N
A Multi-Agent Approach to Arabic Handwritten Text Segmentation

The segmentation of individual words into characters is a vital process in handwritten character recognition systems. In this paper, a novel approach is proposed to segment handwritten Arabic text (words). We consider the “Naskh” font style. The segmentation algorithm employs seven agents in order to detect regions where segmentation is illegal. Feature points (end points) are extracted from the remaining regions of the word-image. Initially, the middle of every two successive end points is considered as a candidate segmentation point based on a set of rules. The experimental results are very promising as we achieved a success rate of 86%.
The dynamics of discourse situations

The effects of utterances such as cue phrases, keep-turn markers, and grounding signals cannot be characterized as changes to a shared record of the propositions under discussed: the simplest (and arguably most natural) way of characterizing the meaning of these utterances is in terms of a theory in which the conversational score is seen as a record of the discourse situation, or at least of the speech acts that have been performed. The problem then becomes to explain how discourse entities are accessible. We consider three hypotheses about the dynamics of a speech act-based theory of the conversational score, and argue that they could be implemented with relatively minor modifications to the technical tools already introduced in theories such as Compositional DRT.
Automated Detection and Evaluation of Swallowing Using a Combined EMG/Bioimpedance Measurement System

Introduction. Developing an automated diagnostic and therapeutic instrument for treating swallowing disorders requires procedures able to reliably detect and evaluate a swallow. We tested a two-stage detection procedure based on a combined electromyography/bioimpedance (EMBI) measurement system. EMBI is able to detect swallows and distinguish them from similar movements in healthy test subjects. Study Design. The study was planned and conducted as a case-control study (EA 1/019/10, and EA1/160/09, EA1/161/09). Method. The study looked at differences in swallowing parameters in general and in the event of penetration during swallows in healthy subjects and in patients with an oropharyngeal swallowing disorder. A two-stage automated swallow detection procedure which used electromyography (EMG) and bioimpedance (BI) to reliably detect swallows was developed. Results. Statistically significant differences between healthy subjects and patients with a swallowing disorder were found in swallowing parameters previously used to distinguish between swallowing and head movements. Our two-stage algorithm was able to reliably detect swallows (sensitivity = 96.1%, specificity = 97.1%) on the basis of these differences. Discussion. Using a two-stage detection procedure, the EMBI measurement procedure is able to detect and evaluate swallows automatically and reliably. The two procedures (EMBI + swallow detection) could in future form the basis for automated diagnosis and treatment (stimulation) of swallowing disorders.
A K-Means Based Clustering Approach for Finding Faulty Modules in Open Source Software Systems

Prediction of fault-prone modules provides one way to support software quality engineering. Clustering is used to determine the intrinsic grouping in a set of unlabeled data. Among various clustering techniques available in literature K-Means clustering approach is most widely being used. This paper introduces K-Means based Clustering approach for software finding the fault proneness of the Object-Oriented systems. The contribution of this paper is that it has used Metric values of JEdit open source software for generation of the rules for the categorization of software modules in the categories of Faulty and non faulty modules and thereafter empirically validation is performed. The results are measured in terms of accuracy of prediction, probability of Detection and Probability of False Alarms. Keywords—K-Means, Software Fault, Classification, Object Oriented Metrics.
The Efficacy and Safety of Chemotherapy in Patients With Nonsmall Cell Lung Cancer and Interstitial Lung Disease

AbstractChemotherapy plays a critical and venturous role against the co-morbidity of nonsmall cell lung cancer and interstitial lung disease (NSCLC–ILD). We performed a Bayesian meta-analysis and systematic review to evaluate the safety and efficacy of the chemotherapy in NSCLC–ILD patients.EMBASE, PubMed, the Cochrane Central Register of Controlled Trials, and clinicaltrials.gov (up to January 2015). We included all study designs except case reports, all studies with NSCLC–ILD patients and all the possible chemotherapy regimens.Quality was assessed by a components approach. We derived summary estimates using Bayesian method through WinBUGS (version 1.4.3, MRC Biostatistics Unit, Cambridge, UK). Seven studies involving 251 patients with NSCLC–ILD were included in the meta-analysis. The treatment response (complete remission, 0; [partial remission, 39.1%; 95% credible interval [CrI], 32.6–45.7]; [stable disease, 36%; 95% CrI, 29.6–42.2]; [PD, 15.4%; 95% CrI, 11.3–19.8]; [nonevaluable, 6.4%; 95% CrI, 2.7–10.1]; [overall response rate, 41.3%; 95% CrI, 35.3–47.4]; [disease control rate, 77.7%; 95% CrI, 72.2–82.7]) were comparable to that of patients with NSCLC alone; the survival outcomes (median overall survival, median progression-free survival, and 1-year survival rate) were slightly worse, especially the lower 1-year survival rate. Platinum-based doublets as first-line chemotherapy may be related to higher incidence of acute exacerbation-ILD in first line chemotherapy (AE, 8.47%; 95% CrI, 5.04–12.6). The data selection bias and small patient number make the meta-analysis of treatment response and conclusions generated from these data inaccurate.The present meta-analysis suggests that chemotherapy might be an effective therapy for patients with NSCLC–ILD, but it might be associated with higher incidence of acute exacerbation.
When is Noise Not Noise - A Microstructure Estimate of Realized Volatility

This paper studies the joint distribution of tick by tick returns and durations between trades. Returns are decomposed into changes in full information prices and microstructure noise, but the noise is modeled in accordance with various models of market microstructure allowing rich correlation structures both with the efficient price and over time. The full information price has time varying volatility which depends upon the arrival time of trades. The paper aims at three contributions: First, the noise is modeled to allow asymmetric information, inventory and order processing costs, and delayed quote setting. Second, the response to the trade arrival times allows trade durations to be informative on future volatility. Third, the estimated state space models can act as a laboratory to examine various non-parametric approaches to realized volatility estimation. Both simulated and actual data can be compared across methods and the accuracy and efficiency assessed as long as the parameteric model is viewed as a sufficiently accurate representation. We apply the above model to 10 NYSE stock transactions data series with varying transaction rates. It appears that contemporaneous duration has little effect on the volatility per trade after conditioning on the past, which means average per second volatility is inversely related to the duration between trades. Microstructure noise is found to be informative about the unobserved efficient price, and the informational component explains 45% of the total variation of the microstructure noise.
The Principles of Biomedical Scientific Writing: Results

The “results section” of a scientific paper provides the results related to all measurements and outcomes that have been posted earlier in the materials and methods section. This section consists of text, figures, and tables presenting detailed data and facts without interpretation and discussion. Results may be presented in chronological order, general to specific order, most to least important order, or may be organized according to the topic/study groups or experiment/measured parameters. The primary content of this section includes the most relevant results that correspond to the central question stated in the introduction section, whether they support the hypothesis or not. Findings related to secondary outcomes and subgroup analyses may be reported in this section. All results should be presented in a clear, concise, and sensible manner. In this review, we discuss the function, content, and organization of the “results section,” as well as the principles and the most common tips for the writing of this section.
Une recherche-action participative au soutien à domicile : vers des pratiques ergothérapiques axées sur la participation sociale des aînés

Background. Occupational therapists who provide community-based services are well positioned to foster older adults’ social participation. However, community occupational therapists rarely address social participation and require support to change their practice. Purpose. This study initiated a remodelling of community occupational therapy services by: (1) selecting practices fostering older adults’ social participation, and (2) identifying factors that could influence their integration. Method. A community-based participatory research study was conducted in a large Canadian city. Four focus group meetings and seven individual interviews were held with 28 key informants. Findings. A continuum of emerging practices was identified, including personalized, group-based and community-based interventions. Potential enablers of these practices included clinical support, better communication and user involvement. Organizational and systemic barriers were related to the institutional culture and performance indicators. Implications. These results point to innovative ways to foster older adults’ social participation and identify potential enablers and barriers influencing their integration.
Feasible Offset and Optimal Offset for General Single-Layer Channel Routing

This paper provides an efficient method to find all feasible offsets for a given separation in a very large-scale integration (VLSI) channel-routing problem in one layer. The previous literature considers this task only for problems with no single-sided nets. When single-sided nets are included, the worst-case solution time increases from $\Theta(n)$ to $\Omega(n^2)$, where $n$ is the number of nets. But if the number of columns $c$ is $O(n)$, the problem can be solved in time $O(n^{1.5}\lgn)$, which improves upon a "naive" $O(cn)$ approach. As a corollary of this result, the same time bound suffices to find the optimal offset (the one that minimizes separation). Better running times result when there are no two-sided nets or all single-sided nets are on one side of the channel. This paper also gives improvements upon the naive approach for $c\neq O(n)$, including an algorithm with running time independent of $c$. An interesting algorithmic aspect of the paper is a connection to discrete convolution.
On Analysis Error Covariances in Variational Data Assimilation

The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function (analysis). The equation for the analysis error is derived through the errors of the input data (background and observation errors). This equation is used to show that in a nonlinear case the analysis error covariance operator can be approximated by the inverse Hessian of an auxiliary data assimilation problem which involves the tangent linear model constraints. The inverse Hessian is constructed by the quasi-Newton BFGS algorithm when solving the auxiliary data assimilation problem. A fully nonlinear ensemble procedure is developed to verify the accuracy of the proposed algorithm. Numerical examples are presented.
Volume measurement based tensor completion

This paper presents a new tensor completion method named minimum volume constraint tensor completion. Unlike the nuclear norm penalization based methods, our method extends the conception of the matrix volume to the tensor volume, and uses the volume measurement as the penalization to address the tensor completion problem. The alternating direction method of multipliers (ADMM) algorithm is then employed to solve the optimization problem of the proposed model. Experimental results on several popular databases show superior performance of our method compared to the nuclear norm penalization based methods in terms of the accuracy and robustness.
A cross layered approach to improve energy efficiency of underwater wireless sensor network

Underwater Wireless Sensor Network (UWSN) environments have some very specific characteristics which introduce many challenges. Due to lack of sunlight as well as harsh conditions of underwater environment it is very difficult to change batteries and maintain power supply in underwater sensor nodes while in terrestrial WSN, managing power is easy due to ease of changing batteries and even a node can be changed as it is not as costly as an underwater sensor node. Moreover, in terrestrial WSN, solar power can also be utilized. Also in UWSN, often the transmission range required is more compared to terrestrial WSN as UWSNs are very sparse, which also results in more power consumption. Thus our focus is to improve the energy efficiency of UWSN. One of the way to improve energy efficiency is using cross layered approach. We have proposed a cross layered approach, cross layered VBF (CL-VBF), in which the routing layer is able to carry out power management along with the MAC layer. We evaluate our proposed approach with respect to overall energy consumption, per node energy consumption, average per node energy consumption, total end-to-end delivery and packet-delivery ratio by varying number of nodes, transmission range and packet size. We find that the newly designed CL-VBF achieves higher efficiency in energy consumption compared to VBF but has a low packet delivery ratio.
Simultaneous Reconnection Surgery Technique of Routing With Machine Learning-Based Acceleration

In global routing, both timing and routability are critical criteria to measure the performance of a design. However, these two objectives naturally conflict with each other during routing. In this paper, we propose reconnection approaches to fix timing. We first formulated a quadratic program (QP), which adjusts routing topologies of all the nets by only reconnecting critical sinks and takes congestion into consideration to tradeoff timing and routability objectives. A machine learning (ML)-based technique is applied to accelerate our algorithm, which offers a fast and effective way to solve the problem. By exploring more reconnection candidates, we then formulated a QP to reconnect any sink of a net and utilized a multilabel classifier to accelerate the process. The experimental results on ICCAD 2015 benchmarks show that our algorithms can achieve timing improvement with no significant degradation in routability and wirelength. With ML-based acceleration, our results can be obtained in almost negligible runtime.
Flow Permissions for Android

This paper proposes Flow Permissions, an extension to the Android permission mechanism. Unlike the existing permission mechanism our permission mechanism contains semantic information based on information flows. Flow Permissions allow users to examine and grant explicit information flows within an application (e.g., a permission for reading the phone number and sending it over the network) as well as implicit information flows across multiple applications (e.g., a permission for reading the phone number and sending it to another application already installed on the user's phone). Our goal with Flow Permissions is to provide visibility into the holistic behavior of the applications installed on a user's phone. Our evaluation compares our approach to dynamic flow tracking techniques; our results with 600 popular applications and 1,200 malicious applications show that our approach is practical and effective in deriving Flow Permissions statically.
Approach towards V M management for green computing

Energy conservation is a key concern in computing systems because it can bring several benefits such as reducing operating costs, increasing system reliability. To provide cloud services, more and more large-scale data centers containing thousands of computing nodes are built, which results in consuming terrific amount of energy with huge cost. Existing Energy-Aware Scheduling Algorithms developed for energy reductions in multiple VM system are competent but lacking the ability of guaranteeing system schedulability. Thus an efficient task scheduling algorithm required for tasks which will be also energy efficient, energy utilization of hosts on which multiple VMs are running can be reduced by scheduling task allotment to VMs, while taking care of deadline, execution time of each task and VMs availability.
Semantic Diff: a tool for summarizing the effects of modifications

Describes a tool that takes two versions of a procedure and generates a report summarizing the semantic differences between them. Unlike existing tools based on comparison of program dependence graphs, our tool expresses its results in terms of the observable input-output behaviour of the procedure, rather than its syntactic structure. And because the analysis is truly semantic, it requires no prior matching of syntactic components, and generates fewer spurious differences, so that meaning-preserving transformations (such as renaming local variables) are correctly determined to have no visible effect. A preliminary experiment on modifications applied to the code of a large real-time system suggests that the approach is practical. <<ETX>>
Variational Data Structures: Exploring Tradeoffs in Computing with Variability

Variation is everywhere, and in the construction and analysis of customizable software it is paramount. In this context, there arises a need for variational data structures for efficiently representing and computing with related variants of an underlying data type. So far, variational data structures have been explored and developed ad hoc. This paper is a first attempt and a call to action for systematic and foundational research in this area. Research on variational data structures will benefit not only customizable software, but many other application domains that must cope with variability. In this paper, we show how support for variation can be understood as a general and orthogonal property of data types, data structures, and algorithms. We begin a systematic exploration of basic variational data structures, exploring the tradeoffs among different implementations. Finally, we retrospectively analyze the design decisions in our own previous work where we have independently encountered problems requiring variational data structures.
Navigation in the presence of humans

Robot navigation in the presence of humans raises new issues for motion planning and control since the humans safety and comfort must be taken explicitly into account. We claim that a human-aware motion planner must not only elaborate safe robot paths, but also plan good, socially acceptable and legible paths. Our aim is to build a planner that takes explicitly into account the human partner by reasoning about his accessibility, his vision field and potential shared motions. This paper focuses on a navigation planner that takes into account the humans existence explicitly. This planner is part of a human-aware motion and manipulation planning and control system that we aim to develop in order to achieve motion and manipulation tasks in a collaborative way with the human. We are conducting research in a multidisciplinary perspective, (1) running user studies and (2) developing an algorithmic framework able to integrate knowledge acquired through the trials. We illustrate here a first step by implementing a human-friendly approach motion by the robot