Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved surveillance for surgical site infections after orthopedic implantation procedures: extending applications for automated data.

BACKGROUND Screening methods that use automated data may streamline surgical site infection (SSI) surveillance and improve the accuracy and comparability of data on SSIs. We evaluated the use of automated inpatient diagnosis codes and pharmacy data to identify SSIs after arthroplasty. METHODS This retrospective cohort study at 8 hospitals involved weighted, random samples of medical records from 2128 total hip arthroplasty (THA) procedures performed from 1 July 2002 through 30 June 2004, and 4194 total knee arthroplasty (TKA) procedures performed from 1 July 2003 through 30 June 2005. We compared routine surveillance with screening of inpatient pharmacy data and diagnoses codes followed by medical record review to confirm SSI status. RESULTS Records from 696 THA and 1009 TKA procedures were reviewed. The SSI rates were nearly double those determined by routine surveillance (1.32% [95% confidence interval, 0.83%-1.81%] vs. 0.75% for THA; 1.83% [95% confidence interval, 1.43%-2.23%] vs. 0.71% for TKA). An inpatient diagnosis code for infection within a year after the operation had substantially higher sensitivity (THA, 89%; TKA, 81%), compared with routine surveillance (THA, 56%; TKA, 39%). Adding antimicrobial exposure of 7 days after the procedure increased the sensitivity (THA, 93%; TKA, 86%). Record review confirmed SSIs after 51% of THAs and 55% of TKAs that met diagnosis code criteria and after 25% of THAs and 39% of TKAs that met antimicrobial exposure and/or diagnosis code criteria. CONCLUSIONS Focused surveillance among a subset of patients who met diagnosis code screening criteria with or without the addition of antimicrobial exposure-based screening was more sensitive than routine surveillance for detecting SSIs after arthroplasty and could be an efficient and readily standardized adjunct to traditional methods.
On comparison of intra line copy and intra string copy for HEVC screen content coding

Recently, Intra Line Copy (ILC) and Intra String Copy (ISC) have been introduced as effective means for screen content coding during the development of HEVC Screen Content Coding Extensions. Although conceptually sharing the same theoretical basis, which is essentially string matching, they differ from each other in a number of significant ways. This paper presents detailed comparisons between them with respect to their compression performance, runtime complexity and memory access bandwidth, in order to better understand their merits and faults. Experimental results indicate that they perform comparably to each other, with ILC generally performing better in coding mixed content and ISC better in coding pure screen content. When considering the impact on the memory access bandwidth and coding performance trade-offs, local search for ILC/ISC becomes more favorable than full-frame search in low-delay real-time applications.
N-Point Correlations in CDM and ΩCDM Simulations

Higher order statistics are investigated in Ω cold dark matter (CDM) universes by analyzing 500 h-1 Mpc high-resolution tree N-body simulations with both Ω=1 and Ω<1. The amplitudes of the N-point correlation functions are calculated from moments of counts-in-cells determined by a pair of new algorithms especially developed for large simulations. This approach enables massive oversampling with ≃109-1014 cells for accurate determination of factorial moments from up to 47 million particles in the scale range of 8 h-1 kpc-125 h-1 Mpc. Thorough investigation shows that there are three scale ranges in the simulations: ≥8 h-1 Mpc, a weakly nonlinear regime where perturbation theory applies with utmost precision; 1-8 h-1 Mpc, the nonlinear plateau; and finally ≤1 h-1 Mpc, a regime where dynamical discreteness effects dominate the higher order statistics. In the physically relevant range of 1-125 h-1 Mpc the results (1) confirm the validity of perturbation theory in the weakly nonlinear regime; (2) establish the existence of a plateau in the highly nonlinear regime similar to the one observed in scale-free simulations; (3) show extended perturbation theory to be an excellent approximation for the nonlinear regime; (4) find the time-dependence of the SN's to be negligible in both regimes; (5) in comparison with similar measurements in the Edinburgh-Durham Southern Galaxy Catalog survey, strongly support Ω<1 with no biasing; and (6) show that the formulae of Szapudi and Colombi provide a good approximation for errors on higher order statistics measured in N-body simulations.
A Process Calculus for Universal Concurrent Constraint Programming : Semantics , Logic and Application

We introduce the Universal Timed Concurrent Constraint Programming (utcc) process calculus; a generalisation of Timed Concurrent Constraint Programming. The utcc calculus allows for the specification of mobile behaviours in the sense of Milner’s π-calculus: Generation and communication of private links. We first endow utcc with an operational semantics and then with a symbolic semantics to deal with problematic operational aspects involving infinitely many substitutions and divergent internal computations. The novelty of the symbolic semantics is to use temporal constraints to represent finitely infinitely-many substitutions. We also show that utcc has a strong connection with Pnueli’s Temporal Logic. This connection can be used to prove reachability properties of utcc processes. As a compelling example, we use utcc to exhibit the secrecy flaw of the Needham-Schroeder security protocol.
The Metabolic Syndrome and ECG Detected Left Ventricular Hypertrophy – Influences from IGF-1 and IGF-Binding Protein-1

Background and Aims The metabolic syndrome (MetS) is associated with an increased risk for left ventricular hypertrophy (LVH) and cardiovascular mortality. The aim of this study was to investigate potential influences from insulin-like growth factor-1 (IGF-1) and IGF binding protein-1 (IGFBP-1) on the relationship between the MetS and LVH, also taking into account the role of physical activity (PA), use of oestrogen and gender. Methods and Results In a population-based cross-sectional study of 60-year-old men (n = 1822) and women (n = 2049) participants underwent physical examination and laboratory tests, including electrocardiography (ECG), and completed an extensive questionnaire. Women showed higher levels of IGFBP-1 than men (37.0 vs. 28.0 µg/l, p<0.001), and women with LVH had lower levels of IGFBP-1 than women without LVH (31.0 µg/l vs. 37.0 µg/l, p<0.001). Furthermore, women with low levels of IGFBP-1 had a significantly increased risk of having LVH (crude OR≈2.5). When stratifying for PA and oestrogen, respectively, a weaker association between IGFBP-1 and LVH was demonstrated in physically active men and women, compared to inactive individuals, as well as in women using oestrogen, compared to non-users. Conclusion In a representative sample of 60-year-old Swedish men and women, the main findings were higher levels of IGFBP-1 in women than in men; lower levels of IGFBP-1 in women with LVH, compared to women without LVH; and an increased risk of having LVH in women with low levels of IGFBP-1. The association between IGFBP-1 and LVH was diminished in physically active men and women, as well as in women using oestrogen.
Development of a Remote Therapy Tool for Childhood Apraxia of Speech

We present a multitier system for the remote administration of speech therapy to children with apraxia of speech. The system uses a client-server architecture model and facilitates task-oriented remote therapeutic training in both in-home and clinical settings. The system allows a speech language pathologist (SLP) to remotely assign speech production exercises to each child through a web interface and the child to practice these exercises in the form of a game on a mobile device. The mobile app records the child's utterances and streams them to a back-end server for automated scoring by a speech-analysis engine. The SLP can then review the individual recordings and the automated scores through a web interface, provide feedback to the child, and adapt the training program as needed. We have validated the system through a pilot study with children diagnosed with apraxia of speech, their parents, and SLPs. Here, we describe the overall client-server architecture, middleware tools used to build the system, speech-analysis tools for automatic scoring of utterances, and present results from a clinical study. Our results support the feasibility of the system as a complement to traditional face-to-face therapy through the use of mobile tools and automated speech analysis algorithms.
Resource allocation for scalable video broadcast in wireless cellular networks

Video broadcast services have become increasingly popular on packet-based wireless networks, such as 1xEV-DO and HSDPA which support high data rate. In this paper we propose a resource allocation algorithm for scalable video broadcast over such wireless networks. Our algorithm allocates time slots among the video layers of a scalable video and applies adaptive modulation and coding (AMC) to each video layer to maximize the sum of utilities for heterogeneous users with varying QoS requirements. It also considers competing video sessions and allocates time slots among them according to user preferences. Additionally, its polynomial time-complexity allows for online resource allocation that is necessary for real-time video services. Simulation experiments show that our algorithm outperforms a single-layer video broadcast with fixed modulation and coding (FMC), used in broadcast and multicast services (BCMCS) in the CDMA2000 system, and produce a near-optimal allocation.
Motion editing with spacetime constraints

In this paper, we present a method for editing a pre-existing motion such that it meets new needs yet preserves as much of the original quality as possible. Our approach enables the user to interactively position characters using direct manipulation. A spacetime constraints solver finds these positions while considering the entire motion. This paper discusses the three central challenges of creating such an approach: defining a constraint formulation that is rich enough to be effective, yet simple enough to afford fast solution; providing a solver that is fast enough to solve the constraint problems at interactive rates; and creating an interface that allows users to specify and visualize changes to entire motions. We present examples with a prototype system that permits interactive motion editing for articulated 3D characters on personal computers. I.3. 7 [Computer Graphics]: Three-Dimensional Graphics and Realism – Animation; I.3. 6 [Computer Graphics]: Methodology and Techniques Interaction Techniques; G.1. 6 [Numerical Analysis]: Optimization. Spacetime Constraints, Motion Displacement Mapping.
A discrete wavelet transform based robust watermarking for copyright protection

Digital watermarking is a simple and effective way to provide copyright protection. This paper proposes a robust and blind watermarking scheme for static images. It utilizes discrete wavelet transform and applies three coding methods according to the different characteristics of band coefficients: lattice code based on the communication principle, modification of insignificant coefficients based on the just-noticeable distortion of the human visual model, and quantization index modulation based on singular value decomposition. Together, these methods embed a watermark while maintaining image fidelity. The experimental results prove that the proposed method is robust against frequency-based and time domain geometric attacks.
A second order sigma delta modulator using semi&#8211;uniform quantizer with 81dB dynamic range at 32x OSR

In this paper a new type of nonuniform quantizer, semi-uniform quantizer, is introduced. A k-bit semi-uniform quantizer uses the thresholds defined by a (k+1)-bit uniform quantizer and arranges them in such a way that small-amplitude inputs will be quantized by small quantization steps and vice versa. Under the condition that there is no DC offset at the modulator input, the use of semi-uniform quantizer achieves about 1-bit higher dynamic range compared with using a conventional quantizer, while the hardware complexity of the quantizers is the same. The measurement results of a prototype chip in 0. 35µm CMOS process confirm the simulation results. At 32x oversampling ratio the 2nd order modulator achieves 81dB dynamic range, 56.3dB peak SNDR with a 3-bit semi-uniform quantizer. With a 3-bit uniform quantizer the dynamic range is 73dB and the peak SNDR is 52.6dB.
Electroacoustic Stimulation with Cochlear Implants for Deafness Treatment

Background: Cochlear implant is an electronic hearing aid surgically inserted into the inner ear that, unlike a conventional hearing aid, picks up sound waves and transforms it into an electrical impulse that directly stimulates the cochlear nerve. Objective: This study aims to describe the profile and outcomes of patients submitted to hybrid cochlear implant in the in a tertiary hospital in the last three years. Methods: It was conducted a clinical study including 8 patients implanted with the brand MED-EL FLEX EAS in a tertiary hospital in the last three years. Results: It was observed an improvement in all tonal thresholds after the activation of the cochlear implant. Conclusion: The hybrid cochlear implant was successful procedure, with an improvement of tonal thresholds after the activation of cochlear implants.
Gliotoxin production in Aspergillus fumigatus contributes to host-specific differences in virulence.

BACKGROUND Gliotoxin is a epipolythiodioxopiperazine toxin that is made by the filamentous fungus Aspergillus fumigatus. Gliotoxin has a wide range of effects on metazoan cells in culture, including induction of apoptosis through inhibition of Nf-kappaB, and inhibition of superoxide production by phagocytes. These activities have led to the proposal that gliotoxin contributes to pathogenesis during invasive aspergillosis. We tested this hypothesis by creating isogenic strains of gliotoxin-producing and nonproducing strains. METHODS We deleted gliP, the gene that encodes the nonribosomal peptide synthetase GliP. GliP catalyzes the first biosynthetic step in the synthesis of gliotoxin. We then tested for gliotoxin production and virulence in different animal models. RESULTS Deletion of gliP resulted in strains that were wild type for growth, but they did not synthesize gliotoxin. Transformation of gliP deletion mutants with a full copy of gliP restored gliotoxin production. The gliP deletion strain had attenuated virulence in nonneutropenic mice immunosuppressed with corticosteroids, but had normal virulence in neutropenic mice. It also had reduced virulence in a Drosophila melanogaster model. CONCLUSIONS Gliotoxin only contributes to the virulence of A. fumigatus in nonneutropenic mice and in fruit flies with functional phagocytes. These results suggest that the principal targets of gliotoxin are neutrophils or other phagocytes.
CAR Approach for the Internet of Things

In this paper, we propose a novel context-aware routing (CAR) approach that uses the cloud as an extra level of data-request processing to improve the network performance in terms of data delivery. Data delivery in the Internet of Things depends heavily on numerous factors, such as the amount of data, end-to-end in-network delay, and setup time. The CAR approach is significantly improving the current request-response model, especially while the exchanged in-network data amount increases and data are sent from source to destination in a peer-to-peer fashion. What we are trying to show in this paper, in particular, is the benefits of having a central context-aware server (in the cloud) in improving the end-user experience. Hence, the proposed CAR approach is a typical candidate for data-intensive cloud-based applications. It considers source and destination requirements in terms of data size, delay, link capacity, and available applications on the operating devices as well. Extensive simulations are performed, and achieved results show the efficiency of our approach against other competitive approaches in terms of in-network delay and packet delivery ratio.
Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation

Estimation of density derivatives is a versatile tool in statistical data analysis. A naive approach is to first estimate the density and then compute its derivative. However, such a two-step approach does not work well because a good density estimator does not necessarily mean a good density-derivative estimator. In this paper, we give a direct method to approximate the density derivative without estimating the density itself. Our proposed estimator allows analytic and computationally efficient approximation of multi-dimensional high-order density derivatives, with the ability that all hyper-parameters can be chosen objectively by cross-validation. We further show that the proposed density-derivative estimator is useful in improving the accuracy of non-parametric KL-divergence estimation via metric learning. The practical superiority of the proposed method is experimentally demonstrated in change detection and feature selection.
Joint Energy and Spectrum Cooperation for Cellular Communication Systems

Powered by renewable energy sources, cellular communication systems usually have different wireless traffic loads and available resources over time. To match their traffics, it is beneficial for two neighboring systems to cooperate in resource sharing when one is excessive in one resource (e.g., spectrum), while the other is sufficient in another (e.g., energy). In this paper, we propose a joint energy and spectrum cooperation scheme between different cellular systems to reduce their operational costs. When the two systems are fully cooperative in nature (e.g., belonging to the same entity), we formulate the cooperation problem as a convex optimization problem to minimize their weighted sum cost and obtain the optimal solution in closed form. We also study another partially cooperative scenario where the two systems have their own interests. We show that the two systems seek for partial cooperation as long as they find inter-system complementarity between the energy and spectrum resources. Under the partial cooperation conditions, we propose a distributed algorithm for the two systems to gradually and simultaneously reduce their costs from the non-cooperative benchmark to the Pareto optimum. This distributed algorithm also has proportional fair cost reduction by reducing each system's cost proportionally over iterations. Finally, we provide numerical results to validate the convergence of the distributed algorithm to the Pareto optimality and compare the centralized and distributed cost reduction approaches for fully and partially cooperative scenarios.
Problem solving analysis of course scheduling using graph coloring technique based on bee colony algorithm: Parameter of lecturer priority as soft constraint in Electrical Engineering Department of Sepuluh Nopember Institute of Technology

Many factor affected schedule arrangement. The factors made the problem more complicated. This research purposed to analyze and to implement problem solving of course scheduling in university. The problem was modeled using graph coloring technique and bee colony algorithm was used as coloring algorithm. First, the course scheduling problem in university was described. Some of solution precondition that might be fulfilled (hard constraint) and not to be fulfilled (soft constraint) would be determined. Next, reconstruction of conflict course graph was done. The reconstruction process was done together with room assembly process. Hence, the graph that was formed has included room candidates. The research also gave lecturer problem solving with priority as a soft constraint parameter. From testing result, this technique succeed to obtain the proper solution with course percentage that could be assembled at time slot up to 100% and violation to lecturer priority is 5.83% for 206 course data, and the amount of lecturer that had priority status is 30% from 89 lecturers. Comparison was done to previous research and conventional technique; this technique gave ability to solution placement at time slot that much better.
Speech Operated System using DSP: A Review

Speech is the most basic, common and efficient for m of communication method for people to interact with each other. Today, speech technologies are commercially available for an unlimited but interesting ran ge of tasks. These technologies enable machines to respond correctly and reliably to human voices, and provide usef ul and valuable services. This paper gives an overview of implementation of speech recognition using Digital Signal Processor (DSP) and comparison between DSPs used in.
Detecting driver inattention by rough iconic classification

The paper proposes an original method, derived from basic face recognition and classification research, which is a good candidate for an effective automotive application. The proposed approach exploits a single b/w camera, positioned in front of the driver, and a very efficient classification strategy, based on neural network classifiers. A peculiar feature of the work is the adoption of iconic data reduction, avoiding specific and time-consuming feature-based approaches. Though at an initial development stage, the method proved to be fast and robust compared to state of the art techniques; experimental results show real-time response and mean weighted accuracy near to 93%. The method requires a simple training procedure which can be certainly improved for real applications; moreover it can be easily integrated with techniques for automatic face-recognition of the driver.
Exploitation on the Knowledge Transfer of the Time-Cost Optimization

The converting of tacit knowledge is the key of enterprise knowledge management. It facilitates the knowledge transferring between the contractor and subcontractors. Based on the difficulties in the process of knowledge transfer, this paper has focused on the manifesting the implicit knowledge by using the comparisons method. This paper emphatically introduces a series of institutional innovations including adjusting for optimized expenses curve, redrawing the net diagram and redefine total costs. It is also shown that the interests’ mechanism is the solid foundation in the process of manifesting. In addition, other countermeasure and safeguard measure were provided.
Is Microfinance a ‘Magic Bullet’ for Women’s Empowerment? Analysis of Findings from South Asia

Opinions on the impact of microfinance have been divided between those who see it as a "magic bullet" for women's empowerment and others who are dismissive of its abilities as a cure-all panacea for development. This paper seeks to examine the empirical evidence on the impact of microfinance with respect to poverty reduction and empowerment of poor women. It becomes apparent that while access to financial services can and does make vital contributions to the economic productivity and social well-being of poor women and their households, it does not "automatically" empower women, just as with other interventions, such as education, political quotas, etc, that seek to bring about a radical structural transformation that true empowerment entails. These other interventions simply constitute different entry points into this larger project, each with the potential for social transformation, but each is contingent on context, commitment and capacity if this potential is to become a reality.
Analyzing empirical data from a reverse engineering project

This study reports the analysis of data collected during the execution of a reverse engineering process in a real environment. Essentially, the analysis assessed productivity aspects. The experience showed the need for automatic tools which can be adapted to the context the process is performed in and the possibility of anchoring the effort required for the reverse engineering to the desired product quality.