Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-efficient Trust-based aggregation in wireless sensor networks

Wireless sensor networks (WSNs) are often deployed in unattended and noise-prone environments and suffer from energy constraints that limit the quality and quantity of data transmission. Every decision made based on the low quality and low quantity data may have drastic consequence. Therefore, ensuring high quality of sensor data and preserving energy resources of the sensor nodes go hand in hand. In this paper, we propose ETA that is an Energy-efficient Trust based data aggregation aims to achieve reliable and energy-efficient data transmission and aggregation. We use the concept of functional reputation and trust as a means to reach reliability. Functional reputation is used to select nodes that best satisfy the criteria to be an aggregator on the basis of the quality of the node. To find out the best path from every sensor node to the aggregator we take into account the link availability and residual energy of the nodes over the path. Simulation results show that even though ETA introduces some delays, overall it outperforms the other approaches in terms of reliability and lifetime.
Nuclei extraction from histopathological images using a marked point process approach

Morphology of cell nuclei is a central aspect in many histopathological studies, in particular in breast cancer grading. Therefore, the automatic detection and extraction of cell nuclei from microscopic images obtained from cancer tissue slides is one of the most important problems in digital histopathology. We propose to tackle the problem using a model based on marked point processes (MPP), a methodology for extraction of multiple objects from images. The advantage of MPP based models is their ability to take into account the geometry of objects; and the information about their spatial repartition in the image. Previously, the MPP models have been applied for the extraction of objects of simple geometrical shapes. For histological grading, a morphological criterion known as nuclear pleomorphism corresponding to fine morphological differences between the nuclei is assessed by pathologists. Therefore, the accurate delineation of nuclei became an issue of even greater importance than optimal nuclei detection. Recently, the MPP framework has been defined on the space of arbitrarily-shaped objects allowing more accurate extraction of complex-shaped objects. The nuclei often appear joint or even overlap in histopathological images. The model still allows to extract them as individual joint or overlapping objects without discarding the overlapping parts and therefore without significant loss in delineation precision. We aim to compare the MPP model with two state-of-the-art methods selected from a comprehensive review of the available methods. The experiments are performed using a database of H&E stained breast cancer images covering a wide range of histological grades.
Density estimation optimizations for global illumination

Density estimation on the tangent plane (DETP) is a density estimation technique for global illumination. This technique is based on Photon Maps and provides increased accuracy when the surfaces are not locally smooth or continuous. However, the performance of the technique is limited by the large number of ray-disc intersections needed. Some optimizations which increase the performance of DETP have been devised. The first optimization works by creating a set of candidate rays for each radiance calculation. The second optimization uses spatial indexing of the discs around the radiance calculation points. An analytical study of the order of complexity of the algorithms, as well as an heuristic study of the calculation time for the different values of the parameters involved, has been performed. Some rules are given in order to identify the most suitable optimization for a given radiance calculation.
Hardware accelerator for real-time image resizing

An accurate, hardware efficient and fast image rescaling unit is a crucial part of any real-time image processing system. Although there are a number of image scaling algorithms existing in the literature but Bicubic and Bilinear interpolation algorithms are most widely used. In the recent years, numerous algorithms have been proposed that aim to bridge the gap between these two standard algorithms, by attempting to provide high image quality of the former while maintaining the computational simplicity of the latter. This paper proposes a novel image resizing algorithm which uses a four-part piecewise linear function that closely mimics the behavior of the bicubic kernel, and thus provides high quality resized images comparable to Bicubic interpolation while having a much lower computational cost. An optimized architecture is proposed to implement this algorithm which features a high re-use of hardware units for coefficient generation so that the hardware cost is comparable to that of bilinear interpolation. The architecture and algorithm have been designed in tandem so as to meet the real-time requirements of applications such as automated video surveillance, requiring minimal hardware use without compromising on image quality.
I Thought This Was a Study on Math Games: Attribute Modification in Children’s Interactions with Mathematics Apps

Technology is an increasingly important component of education. Children’s mathematical interactions with technology have become a focus of mathematics education research, but less research has investigated constructs that contribute to these mathematical interactions. Attributes of children and technology play a key role in mathematical interactions and both children and technology can modify attributes during these interactions. Grounded in the Artifact-Centric Activity Theory and linked to recent developments in research on technology in mathematics education, this qualitative study extended an earlier exploratory study to investigate attribute modification. In particular, this study examined patterns of attribute modification evident during fifth grade students’ mathematical interactions with two mathematics virtual manipulative touchscreen tablet apps. Results included three categories related to attribute modification: (1) reactive attribute modification (linear progression or repeated repetition); (2) unperceived attributes and opportunities for proactive modification; and (3) proactive modification (seeking equilibrium, seeking disequilibrium, or seeking equilibrium and disequilibrium). Findings have implications for designers, teachers, and researchers of educational technology.
Effect of Chitosan on Hyperglycemia Associated Impaired Renal Function in Streptozotocin-Diabetic Rats

Chitosan capsuleismanufactured by Green World Natural Solutions International Limited, U.S.A. As a food supplement, it is indicated in the management of obesity and hyperglycemia. To investigate the effects of Chitosan capsule on hyperglycemia mediated renal alteration in streptozotocin-induced diabetic rats. Twenty male Wistar albino rats (130-150 g) were divided into five groups comprising normal control, diabetic control and diabetic treated with 150 mg/kg body weight chitosan, 300 mg/kg body weight chitosan or 6 IU/kg body weight insulin. Diabetes was induced by a single intraperitonial injection of 65 mg/kg body weight streptozotocin prior to the commencement of treatment. After four weeks of treatment, the 24-hour fasting urine and blood samples of rats were collected for biochemical assays. The pancreas and liver were harvested for histological assessments and the kidney hypertrophy index was determined. Treatment with the two doses of chitosan significantly ( p <0.05) reduced the blood glucose levels, creatinine clearance and urine volume but significantly (p < 0.05) increased urinary urea levels compared to the diabetic control. Only the animals treated with the higher dose of chitosan (300 mg/kg body weight) showed a significant ( p <0.05) decrease in plasma urea. Kidney hypertrophy index of the chitosan treated groups was reduced but not significantly compared to the diabetic control. The results obtained in this study revealed that treatment with chitosan capsule could correct diabetic hyperglycemia, polyuria and ameliorate glomerular hyperfiltration observed in the early stages of diabetic nephropathy, thereby improving renal function.
Barriers to uptake of prevention of mother-to-child transmission of HIV services among mothers of vertically infected HIV-seropositive infants in Makurdi, Nigeria

Background Perinatal transmission of human immunodeficiency virus (HIV) continues in Nigeria because of the poor use of prevention of mother-to-child transmission of HIV (PMTCT) services. This study reports on the barriers preventing mothers of vertically infected HIV-seropositive infants to use the PMTCT services at the Federal Medical Centre, Makurdi, Nigeria. Methods This is a descriptive study conducted between January and April, 2014. A quantitative survey was applied to detect barriers along the PMTCT services cascade among 52 mothers of vertically infected HIV-seropositive infants. This includes 22 women who attended antenatal care at the Federal Medical Centre (designated as Group A mothers) and 30 women who did not receive any form of PMTCT service (Group B mothers). The study was supplemented with a focused group discussion involving 12 discussants from the two groups. Results In the quantitative assessment: among the Group A mothers, falling asleep was the most common reason (n=22, 100%) for missing therapeutic/prophylactic antiretroviral medicine; financial constraint (n=22, 100%) was the most common reason for antenatal care visit defaults; and a lot of the mothers (n=11, 50.0%) did not give nevirapine to their newborns because they delivered at home. Among Group B mothers, unawareness of HIV-seropositive status was the most common reason (n=28, 93.3%) given for not accessing PMTCT services. In the qualitative study: noninvolvement of male partners, stigma and discrimination experienced by HIV-seropositive mothers, financial constraints in couples, involvement of traditional birth attendants in antenatal care and delivery of HIV-infected women, unawareness of HIV-seropositive status by pregnant women, poor health system, and the lack of funding for PMTCT services at private and rural health facilities were the major barriers preventing the use of PMTCT services. Conclusion In order to reduce the missed opportunities for PMTCT interventions in Makurdi and by extension the Benue State it represents in Nigeria, strong political and financial commitments are needed to overcome the identified barriers.
Public information exposure detection: Helping users understand their web footprints

To help users better understand the potential risks associated with publishing data publicly, as well as the quantity and sensitivity of information that can be obtained by combining data from various online sources, we introduce a novel information exposure detection framework that generates and analyzes the Web footprints users leave across the social Web. Web footprints are the traces of one's online social activities represented by a set of attributes that are known or can be inferred with a high probability by an adversary who has basic information about a user from his/her public profiles. Our framework employs new probabilistic operators, novel pattern-based attribute extraction from text, and a population-based inference engine to generate Web footprints. Using a Web footprint, the framework then quantifies a user's level of information exposure relative to others with similar traits, as well as with regard to others in the population. Evaluation over public profiles from multiple sites (Google+, LinkeIn, FourSquare, and Twitter) shows that the proposed framework effectively detects and quantifies information exposure using a small amount of initial knowledge.
Robustness Analysis using FMEA and BBN - Case Study for a Web-based Application

Time pressure and quality issues represent important challenges for those who develop web-based systems. The ability to analyze a system’s quality and implement improvements early in the development life cycle is of great practical important. For our study we have considered robustness as a critical quality issue. Our objective is to propose a general framework for conducting robustness analysis of web-based systems at an early stage of software development, providing a tool for evaluating failure impact severity and supporting trade-off decisions during the development process. The framework makes use of Jacobson’s analysis method to decompose a system in its functional components, Failure Modes and Effects Analysis to identify all failure modes that characterize each component, and Bayesian Belief networks to deal with failure causeeffect relationships and evaluate the uncertainty of their impact.
Greybody factors in a rotating black-hole background: Fermions and gauge bosons

We study the emission of fermion and gauge boson degrees of freedom on the brane by a rotating higher-dimensional black hole. Using matching techniques, for the near-horizon and far-field regime solutions, we solve analytically the corresponding field equations of motion. From this, we derive analytical results for the absorption probabilities and Hawking radiation emission rates, in the low-energy and low-rotation case, for both species of fields. We produce plots of these, comparing them to existing exact numerical results with very good agreement. We also study the total absorption cross-section and demonstrate that, as in the non-rotating case, it has a different behaviour for fermions and gauge bosons in the low-energy limit, while it follows a universal behaviour – reaching a constant, spin-independent, asymptotic value – in the high-energy regime.
A new Hierarchical Pattern Recognition method using Mirroring Neural Networks

this paper, we develop a hierarchical classifier (an inverted tree-like structure) consisting of an organized set of "blocks" each of which is actually a module that performs a feature extraction and an associated classification. We build each of such blocks by coupling a Mirroring Neural Network (MNN) with a clustering (algorithm) wherein the functions of the MNN are automatic data reduction and feature extraction which precedes an unsupervised classification. We then device an algorithm which we name as a "Tandem Algorithm" for the self-supervised learning of the MNN and an ensuing process of unsupervised pattern classification so that an ensemble of samples presented to the hierarchical classifier is classified and then sub-classified automatically. This tandem process is a two step process (feature extraction/data reduction and classification), implemented at each block (module) and can be extended level by level in the hierarchical architecture. The proposed procedure is practically demonstrated using 2 example cases where in a collage of images consisting of faces, flowers and furniture are classified and sub classified automatically. We expect that this kind of architecture will be very useful in the development of efficient and powerful self-learning machines in the future.
Efficient reconstruction from frame-based multiple descriptions

Redundant bases or frames are a promising technique for multiple description signal coding. Frames can provide sufficient redundancy for recovery in case of coefficient losses due, for instance, to packet transmission errors. In this paper, we consider the problem of dual frame computation in the context of finite impulse response (FIR) analysis and synthesis filterbanks. In particular, we propose an algorithm for dual frame computation which recovers the missing frame coefficients, followed by synthesis with the original filterbank. It is shown that the algorithm operates locally and allows for reduced complexity and low-delay reconstruction of the original signal. The case of excessive losses and incomplete bases is also considered. Experiments are provided to evaluate the algorithm performance and test its applicability in practical contexts.
High-frequency dependence of channel noise in short-channel RF MOSFETs

Using a two-dimensional (2-D) Green's function technique, similar to Shockley's impedance field technique, simulation results of the drain i/sub d/ and gate induced i/sub g/ channel noise are presented for an nMOS transistor as a function of frequency. The simulation results show that for frequencies much lower than the cutoff frequency of the transistor f/sub t/ the correlation factor (i.e., i~/sub g~/i~*/sub d~///spl radic/i/sub g//sup -2/i/sub g//sup -2/) between the drain and gate channel noise is equal to approximately 0.4j. For frequencies near the f/sub t/ of the device the correlation factor approximately equals 0.3j. For f/f/sub t//spl sim/0.3, the contribution of the gate induced noise compared to the drain noise was found to be on the order of 1% (i.e., i/sub g//sup -2//i/sub d//sup -2/(f/sub t//f)/sup 2/).
On limits of sequences of holomorphic functions

We study functions which are the pointwise limit of a sequence of holomorphic functions. In one complex variable this is a classical topic, though we offer some new points of view and new results. Some novel results for solutions of elliptic equations will be treated. In several complex variables the question seems to be new, and we explore some new avenues.
Impact of therapeutic drug monitoring of antiretroviral drugs in routine clinical management of patients infected with human immunodeficiency virus and related health care costs: a real-life study in a large cohort of patients

Background Highly active antiretroviral therapy (HAART) has reduced morbidity and mortality in patients infected with human immunodeficiency virus (HIV). Studies have documented high interindividual variability in the pharmacokinetics of antiretroviral drugs, which may impair the success of HAART if not managed properly. Therapeutic drug monitoring (TDM) is a useful diagnostic tool that helps clinicians to optimize drug doses so that drug concentrations associated with the highest therapeutic efficacy are obtained with a reduced risk of concentration-dependent adverse effects. The aim of this study was to assess whether use of TDM improves clinical outcomes and cost of illness. Methods A retrospective cohort study was conducted at L Sacco University Hospital in Milan, Italy, in HIV-infected patients aged ≥18 years with at least one prescription of antiretroviral drugs for which TDM was applied. The inclusion period was from January 2010 to December 2011, with a follow-up period of up to 12 months. Laboratory and administrative databases were analyzed and matched with each other. Results The cohort consisted of 5,347 patients (3,861 males and 1,486 females) of mean age 43.9±12.5 years. We found that TDM had been used in 143 of these patients, among whom adherence with therapy was significantly higher than among those in whom TDM had not been used (94% versus 78%). In TDM-controlled patients, the mean length of HIV-related hospitalization stay and mean cost of hospitalization were significantly reduced with respect to those observed in the group in which TDM had not been used (7.21 days versus 29.47 days and €293 versus €688, respectively). Conclusion Inclusion of TDM as part of routine clinical optimization of drug dosing in HIV-infected patients is associated with higher adherence to therapy, reduced length of hospitalization stay, and reduced cost of illness.
Non-contact detection of surface waves in concrete using an air-coupled sensor

This research investigates air-coupled sensors used for non-contact NDT of concrete structures. An air-coupled sensor detects propagating leaky surface waves generated by a point impact event applied on the concrete surface. Compared to conventional body waves, leaky surface waves can be easily detected by the sensor due to the large out-of-plane motion of the waves. The computed velocity of the sensed leaky waves indicates the nature of the wave: Rayleigh surface waves are generated in the thick wall and Lamb waves in the thin slab. The study shows the potential of this sensing method for rapid inspection of concrete structures.
P2P Traffic Identification Based on Host and Flow Behaviour Characteristics

Abstract Peer-to-Peer (P2P) networks have been widely applied in file sharing, streaming media, instant messaging and other fields, which have attracted large attention. At the same time P2P networks traffic worsens the congestion of a network significantly. In order to better manage and control P2P traffic, it is important to identify P2P traffic accurately. In this paper we propose a novel P2P identification scheme, based on the host and flow behaviour characteristics of P2P traffic. First we determine if a host takes part in a P2P application by matching its behaviour with some predefined host level behaviour rules. Subsequently, we refine the identification by comparing the statistical features of each flow in the host with several flow feature profiles. The experiments on real world network data prove that this method is quite efficient to identify P2P traffic. The classification accuracy achieves 93.9 % and 96.3 % in terms of flows and bytes respectively.
Taylor Spatial Frame Fixation in Patients With Multiple Traumatic Injuries: Study of 57 Long-Bone Fractures

Objective: To evaluate the Taylor spatial frame (TSF) for primary and definitive fixation of lower limb long-bone fractures in patients with multiple traumatic injuries. Design: Retrospective. Setting: Level I trauma center. Patients: Consecutive series of 52 patients, 57 fractures (25 femoral and 32 tibial), treated between 2005 and 2009. Forty-nine fractures (86%) were open. Injury Severity Score ≥16 for all patients. Intervention: Fifty-four fractures (95%) underwent definitive fixation with the TSF and 3 were treated primarily within 48 hours of injury. In 22 cases (39%), fractures were acutely reduced with the TSF, fixed to bone and the struts in sliding mode without further adjustment, and in 35 cases (61%), the total residual deformity correction program was undertaken. Main Outcome Measure: Clinical and radiological. Results: Complete union was obtained in 52 fractures (91%) without additional surgery at an average of 29 weeks. Four nonunions and 1 delayed union occurred. Results based on Association for the Study and Application of the Method of Ilizarov criteria: 74% excellent, 16% good, 4% fair, and 7% poor for bone outcomes and 35% excellent, 47% good, and 18% fair for functional outcomes. Eighty-eight percent of patients returned to preinjury work activities. Conclusions: Primary and definitive fixation with the TSF is effective. Advantages include continuity of device until union, reduced risk of infection, early mobilization, restoration of primary defect caused by bone loss, easy and accurate application, convertibility and versatility compared with a monolateral fixator, and improved union rate and range of motion for lower extremity long-bone fractures in patients with multiple traumatic injuries. Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.
Hadronic axion model in gauge-mediated supersymmetry breaking

Abstract A simple hadronic axion model is proposed in the framework of gauge-mediated supersymmetry breaking. Dynamics of Peccei-Quinn symmetry breaking is governed by supersymmetry breaking effects and the Peccei-Quinn breaking scale fPQ is inversely proportional to the gravitino mass. The gravitino mass range which corresponds to the axion window fPQ≃109 GeV – 1013 GeV lies in the region predicted by gauge-mediated supersymmetry breaking models. The model is also shown to be cosmologically viable.