Miracle-dz/UniFAR-FTUs huggingface dataset:
Hepatitis C Virus Serologic and Virologic Tests and Clinical Diagnosis of HCV-Related Liver Disease

The use of serological and virological tests has become essential in the management of hepatitis C virus (HCV) infection in order to diagnose infection, guide treatment decisions and assess the virological response to antiviral therapy. Virological tools include serological assays for anti-HCV antibody detection and serological determination of the HCV genotype, and molecular assays that detect and quantify HCV RNA and determine the HCV genotype. Anti-HCV antibody testing and HCV RNA testing are used to diagnose acute and chronic hepatitis C. Only patients with detectable HCV RNA should be considered for pegylated interferon alfa and ribavirin therapy and the HCV genotype should be systematically determined before treatment, as it determines the indication, the duration of treatment, the dose of ribavirin and the virological monitoring procedure. HCV RNA monitoring during therapy is used to tailor treatment duration in HCV genotype 1 infection, and molecular assays are used to assess the end-of-treatment and, most importantly the sustained virological response, i.e. the endpoint of therapy.
A new method for preserving privacy in quantitative association rules using DSR approach with automated generation of membership function

Data mining is the process of extracting hidden patterns from data. With the explosion of data at a tremendous rate, data mining is essential to extract useful information. Association rule mining is a method of finding correlation relationships among large set of data items. A rule is characterized as sensitive if its disclosure risk is above a certain confidence value. Sensitive rules should not be disclosed to the public, as they can be used to infer sensitive data and provide an advantage for the business competitors. Techniques for hiding association rules are limited to binary items. But, real world data consists of quantitative values. In this paper, a method to hide fuzzy association rule is proposed, in which, the fuzzified data is mined using modified apriori algorithm in order to extract rules and identify sensitive rules. The sensitive rules are hidden by decreasing the support value of Right Hand Side (RHS) of the rule. A framework for automated generation of membership function is also proposed. Experimental results of the proposed approach demonstrate efficient information hiding with minimum side effects.
Constrained-MSER detection of retinal pathology

With the increase in age and diabetes-related eye diseases, there is a rising demand for systems which can efficiently screen and locate abnormalities in retinal images. In this paper, we propose a framework that utilizes a variant of the Maximally Stable Extremal Region method, termed C-MSER, to systematically detect various retinopathy pathologies such as microaneurysms, haemorrhages, hard exudates and soft exudates. Experiments on three real-world datasets show that C-MSER is effective for online screening of diabetic retinopathy.
Urinary Magnesium Excretion and Risk of Hypertension: The Prevention of Renal and Vascular End-Stage Disease Study

Observational studies on dietary or circulating magnesium and risk of hypertension have reported weak-to-modest inverse associations, but have lacked measures of actual dietary uptake. Urinary magnesium excretion, an indicator of intestinal magnesium absorption, may provide a better insight in this association. We examined 5511 participants aged 28 to 75 years free of hypertension in the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study, a prospective population–based cohort study. Circulating magnesium was measured in plasma and urinary magnesium in two 24-hour urine collections, both at baseline. Incident hypertension was defined as blood pressure ≥140 mm Hg systolic or ≥90 mm Hg diastolic, or initiation of antihypertensive medication. During a median follow-up of 7.6 years (interquartile range, 5.0–9.3 years), 1172 participants developed hypertension. The median urinary magnesium excretion was 3.8 mmol/24 hour (interquartile range, 2.9–4.8 mmol/24 hour). Urinary magnesium excretion was associated with risk of hypertension in an inverse log-linear fashion, and this association remained after adjustment for age, sex, body mass index, smoking status, alcohol intake, parental history of hypertension, and urinary excretion of sodium, potassium, and calcium. Each 1-unit increment in ln-transformed urinary magnesium excretion was associated with a 21% lower risk of hypertension after multivariable adjustment (adjusted hazard ratio, 0.79; 95% confidence interval, 0.71–0.88). No associations were observed between circulating magnesium and risk of hypertension. In conclusion, in this cohort of men and women, urinary magnesium excretion was inversely associated with risk of hypertension across the entire range of habitual dietary intake.
Circulating Leptin, Ghrelin, Glucose, Insulin, C-Peptide, GH, IGF-1, Cortisol, and Interleukin-6 Concentrations, and the Systemic Stress Response to Uncomplicated Surgical Injury

The mechanisms initiating, regulating and sustaining the systemic stress response to a surgical injury have not all been identified yet. Recent studies point to the adipose tissue as a major endocrine system, the hormones of which in- fluence energy homeostasis, glucose and lipid metabolism, vascular homeostasis, and immune response. Essential ele- ments of this control system are leptin and ghrelin. The purpose of the present study was to compare the patterns of leptin and ghrelin secretion in different perioperative periods in patients undergoing elective cholecystectomy, and to relate the changes in circulating leptin or ghrelin to concomitantly occurring changes in glucose, insulin, C-peptide, growth hor- mone (GH), insulin-like growth factor (IGF)-1, total cortisol, free cortisol index, and interleukin-6, and other clinical pa- rameters. Thirty patients were included in the study. Blood was sampled at seven time points between one hour prior to the induction of anesthesia (first observation) to approximately 24 hours later. Both leptin and ghrelin displayed a parallel decrease in concentrations from baseline in the intra-and postoperative periods, with a parallel return to baseline on the morning of the first postoperative day. However, at each perioperative period the leptin trend was not associated with that of other substances(including ghrelin). Likewise, the ghrelin time trend was independent of other study variables (includ- ing leptin). What triggers this response remains unknown but this study implies that it is unlikely to be the hypothalamic- pituitary-adrenocortical, GH/IGF-1, or glucose homeostatic axis, or proinflammatory cytokines.
Inference on Functionals Under First Order Degeneracy

This paper presents a unified second order asymptotic framework for conducting inference on parameters of the form $\phi(\theta_0)$, where $\theta_0$ is unknown but can be estimated by $\hat\theta_n$, and $\phi$ is a known map that admits null first order derivative at $\theta_0$. For a large number of examples in the literature, the second order Delta method reveals a nondegenerate weak limit for the plug-in estimator $\phi(\hat\theta_n)$. We show, however, that the `standard' bootstrap is consistent if and only if the second order derivative $\phi_{\theta_0}''=0$ under regularity conditions, i.e., the standard bootstrap is inconsistent if $\phi_{\theta_0}''\neq 0$, and provides degenerate limits unhelpful for inference otherwise. We thus identify a source of bootstrap failures distinct from that in Fang and Santos (2018) because the problem (of consistently bootstrapping a \textit{nondegenerate} limit) persists even if $\phi$ is differentiable. We show that the correction procedure in Babu (1984) can be extended to our general setup. Alternatively, a modified bootstrap is proposed when the map is \textit{in addition} second order nondifferentiable. Both are shown to provide local size control under some conditions. As an illustration, we develop a test of common conditional heteroskedastic (CH) features, a setting with both degeneracy and nondifferentiability -- the latter is because the Jacobian matrix is degenerate at zero and we allow the existence of multiple common CH features.
Medical Image Segmentation with Improved Gradient Vector Flow

In this study, we discover some deficiencies of GVF and GGVF Snake such as it can not capture boundaries like "U" and "S" completely because of the counteraction of some external forces and the influence of the local minimum external forces. Based on analyzing force distribution rules of gradient vector flow, a standard is introduced to distinguish every control point is true or false. An additional control force is added to GVF Snake model. The direction of control force is gained by tracking the force field and the motion of snake control points. Experimentation proves that the new GVF Snake model can solve the problem that GVF and GGVF Snake model can not detect the boundaries like "U" and "S" and the new algorithm can improve GVF snake model's ability to capture thin boundary indentation like the boundary of brain image.
Classifying NMF components based on vector similarity for speech and music separation

This paper presents a nonnegative matrix factorization (NMF) components classification algorithm for single-channel speech and music separation. Music only and music-speech mixture segments are firstly classified from the audio stream via audio segmentation technique. Then NMF is applied for signal decomposition. The basis matrix of the NMF output of music only segments provides the prior knowledge of music component in the mixture signal. NMF components, i.e. basis and gain vectors of the mixture signal are classified into speech and music based on the vector similarity between each basis vector and the priori music basis matrix. A set of SNR-dependent thresholding coefficients are empirically determined for the classification. The separated speech and music signals are reconstructed from the respectively classified NMF components. Experimental results show the effectiveness of the proposed method for speech and music separation, and its superior performance over the traditional NMF-based separation methods.
Tumor Recognition in Wireless Capsule Endoscopy Images

This paper implementation of simple algorithm for detection of tumor in endoscopy images. Tumor is an uncontrolled growth of tissues in any part of the body. Tumors are of different types and they have different characteristics and different treatment. The wireless capsule endoscopy (WCE) image is visually examined by the physician for detection and diagnosis of gastrointestinal (GI) tract tumor. However this method of detection resists the accurate determination of tumor. To avoid that, this project uses computer aided method for segmentation (detection) of endoscopy tumor based on the combination of algorithms. This method allows the segmentation of tumor tissue with accuracy and reproducibility comparable to manual segmentation. In addition, it also reduces the time for analysis. At the end of the process the tumor is extracted from the gastrointestinal tract image. The wireless capsule endoscopy images, are extracted by gray level co-occurrence matrix (GLCM) & principal component analysis (PCA) and wavelet transform (DWT) which are characterize multi resolution property of images. After performing, the probabilistic neural network (PNN) based feature selection classify the type of tumor.
Polymer-free sirolimus- and probucol-eluting versus new generation zotarolimus-eluting stents in coronary artery disease: the Intracoronary Stenting and Angiographic Results: Test Efficacy of Sirolimus- and Probucol-Eluting versus Zotarolimus-eluting Stents (ISAR-TEST 5) trial.

BACKGROUND Durable polymer coatings have been implicated in mid- and long-term adverse events after drug-eluting stent implantation. A polymer-free dual-drug sirolimus- and probucol-eluting stent and a new generation permanent polymer zotarolimus-eluting stent are recently developed technologies demonstrating encouraging results. METHODS AND RESULTS In a clinical trial with minimal exclusion criteria, we randomly assigned 3002 patients to treatment with sirolimus- and probucol-eluting stents versus zotarolimus-eluting stents. The trial was designed to demonstrate noninferiority of the sirolimus- and probucol-eluting stents. The primary end point was the combined incidence of cardiac death, target-vessel-related myocardial infarction, or target-lesion revascularization at 1-year follow-up. Follow-up angiography was scheduled at 6 to 8 months. The sirolimus- and probucol-eluting stent was noninferior to the zotarolimus-eluting stent in terms of occurrence of the primary end point (13.1% versus 13.5%, respectively, P(noninferiority)=0.006; hazard ratio=0.97, 95% confidence interval, 0.78 to 1.19; P(superiority)=0.74). The incidence of definite/probable stent thrombosis was low in both groups (1.1% versus 1.2%, respectively; hazard ratio=0.91 [95% confidence interval, 0.45 to 1.84], P=0.80). With regard to angiographic efficacy, there were no differences between the sirolimus- and probucol-eluting stent and the zotarolimus-eluting stent in terms of either in-segment binary angiographic restenosis (13.3% versus 13.4% respectively; P=0.95) or in-stent late luminal loss (0.31±0.58 mm versus 0.29±0.56 mm, respectively; P=0.46). CONCLUSION In this large-scale study powered for clinical end points, a polymer-free sirolimus- and probucol-eluting stent was noninferior to a new generation durable polymer-based zotarolimus-eluting stent out to 12 months. CLINICAL TRIAL REGISTRATION http://www.clinicaltrials. gov. Unique identifier NCT 00598533.
The Effectiveness of Group Cognitive Behavioral Therapy in Treating Obsessive-Compulsive Disorder in Women with Multiple Sclerosis (MS): A randomized double-blind controlled trial

Background Obsessive-compulsive disorder (OCD) is one of the most prevalent psychiatric disorders and can cause problems for individuals in all aspects of life, including social and personal dimensions. Objective To study the effect of group cognitive-behavioral therapy on the reduction of OCD symptoms in female participants with multiple sclerosis (MS). Methods This double-blind randomized control trial was conducted from May 2012 to December 2014. The participants included 75 patients with MS who suffered from OCD and were referred to the Loghman Hakim and Imam Khomeini hospitals in Tehran, Iran. Thirty participants had been diagnosed through Yale-Brown Obsessive-Compulsive Symptoms (Y-BOCS). The participants were randomly divided into an experimental group (n=15) and a control group (n=15). Eleven sessions of cognitive-behavioral therapy were provided for the experimental group. Patients in the control group continued with their normal living. Hypotheses were tested using an analysis of covariance (ANCOVA). Results A significant reduction was found in the experimental group’s obsessive-compulsive symptoms after cognitive-behavioral therapy (p<0.001). In addition, mean scores for participants in the experimental group were significantly lower than for those in the control group (p=0.000). Conclusion It can be inferred that cognitive-behavioral therapy could considerably reduce OCD symptoms in women with MS. The application of this method by therapists, especially Iranian clinicians, is recommended.
Wave Field Synthesis: From research to applications

Wave Field Synthesis can dramatically increase the quality of sound reproduction. To create new virtual rooms with realistic ambience within any listening space, new ideas for room simulation and virtual acoustics are needed. The work originally started at Delft Technical University (TU Delft) is now continued at a number of research locations. The paper will introduce the basic techniques, show the requirements for a number of real world applications and give an overview of current research topics. The applications scenarios include cinemas, concert halls and all kinds of music performances (indoor and outdoor).
Improving the throughput of the AES algorithm with multicore processors

AES, Advanced Encryption Standard, can be considered the most widely used modern symmetric key encryption standard. To encrypt/decrypt a file using the AES algorithm, the file must undergo a set of complex computational steps. Therefore a software implementation of AES algorithm would be slow and consume large amount of time to complete. The immense increase of both stored and transferred data in the recent years had made this problem even more daunting when the need to encrypt/decrypt such data arises. As a solution to this problem, in this paper, we present an extensive study of enhancing the throughput of AES encryption algorithm by utilizing the state of the art multicore architectures. We take a sequential program that implements the AES algorithm and convert the same to run on multicore architectures with minimum effort. We implement two different parallel programmes, one with the fork system call in Linux and the other with the pthreads, the POSIX standard for threads. Later, we ran both the versions of the parallel programs on different multicore architectures and compared and analysed the throughputs between the implementations and among different architectures. The pthreads implementation outperformed in all the experiments we conducted and the best throughput obtained is around 7Gbps on a 32-core processor (the largest number of cores we had) with the pthreads implementation.
Analysis of Cancellation Error for Successive Interference Cancellation with Imperfect Channel Estimation

Successive interference cancellation (SIC) is a technique, which can increase the capacity of a DS-CDMA system. Increase in capacity has been shown to approach theoretical limits for an AWGN channel [1]. For a practical channel from the viewpoint of cellular systems, significant increase in capacity using SIC has been shown in [2] even in the presence of estimation errors up to 50%. This capacity increase in [2] is maximized if the statistics of cancellation error is known. In this paper, cancellation error for SIC for the system model proposed in [2] has been analyzed mathematically and verified through simulation for an Additive White Gaussian Channel (AWGN) an also for a fading channel. The results have shown that statistics of cancellation error in SIC has a zero mean with standard deviation and probability density function dependent on the channel statistics. The knowledge and insight gained about cancellation error statistics provide better power allocation schemes required for a typical system using SIC. The results can be used to model the estimation of fractional cancellation error for each user. It is shown in [2] that the knowledge of fractional cancellation error is important for optimum power allocation scheme in a system employing SIC. The results also suggest that better power control schemes, used in 3G systems in the uplink, can reduce the estimation error and thus provide greater capacity enhancements relative to systems not employing SIC.
A distributed quasi-orthogonal space time block code for cooperative communication with information exchange errors for decode-and-forward relay networks

In this paper, we design the full-rate full-diversity quasi-orthogonal space time block code (QOSTBC) matrix for decode-and-forward (DAF) relay networks with four independent single-antenna source nodes, a single-antenna destination node and a single receive four-trans mit-antenna relay node. In this scheme, we consider the channel states between the four users to select the elements of the DQOSTBC matrix to be decode and forward (DAF) or amplify and forward (AAF) types. Thus the proposed scheme is a DQOSTBC matrix with embedded adaptive DAF/AAF elements, based on the source-to-source channel coefficient is above or below a threshold. By the simulation results, the proposed DQOSTBC with adaptive DAF/AAF matrix elements is approximately 7dB better than the traditional DQOSTBC (all matrix elements are fixed to DAF type, by Li et. al.) at 10-4 bit error rate (BER) because the traditional DQOSTBC loses full diversity due to information exchange errors.
An ALC(D)-based combination of temporal constraints and spatial constraints suitable for continuous (spatial) change

We present a family of spatio-temporal theories suitable for continuous spatial change in general, and for continuous motion of spatial scenes in particular. The family is obtained by spatio-temporalising the well-known ALC(D) family of Description Logics (DLs) with a concrete domain D, as follows, where TCSPs denotes "Temporal Constraint Satisfaction Problems", a well-known constraint-based framework: (1) temporalisation of the roles, so that they consist of TCSP constraints (specifically, of an adaptation of TCSP constraints to interval variables); and (2) spatialisation of the concrete domain D: the concrete domain is now $D_x$, and is generated by a spatial Relation Algebra (RA) $x$, in the style of the Region-Connection Calculus RCC8. We assume durative truth (i.e., holding during a durative interval). We also assume the homogeneity property (if a truth holds during a given interval, it holds during all of its subintervals). Among other things, these assumptions raise the "conflicting" problem of overlapping truths, which the work solves with the use of a specific partition of the 13 atomic relations of Allen's interval algebra.
Paper for the Annual Meeting of the Fluids Engineering Division of the Korean Society of Mechanical Engineers , April , 1997 . SOME CURRENT ADVANCES IN CAVITATION RESEARCH

Several recent experimental and allalytical investigations of cavitating flows have revealed new phenomena which clearly affect how we should view cavitation growth arid collapse and the strategies used t o ameliorate its adverse effects. On the scale of individual bubbles it is now clear that the dynamics and acoustics of single bubbles are severely affected by the distortion of the bubble by the flow. This distortion depends on the typical dimension and velocity of the flow (as well as the Reynolds number) and therefore the distortion effects are very important in the process of scaling results up from the model t o the prototype. The first part of the lecture will discuss the implications of these new observations for the classic problem of scale-up. Another recent revelation is the importantance of the interactions between bubbles in determining the coherent motions, dynamic and acoustic, of a cloud of cavitation bubbles. The second part of the lecture focusses on these cloud cavitation effects. It is shown that the collapse of a cloud of cavitating bubbles involves the formation of a bubbly shock wave and it is suggested that the focussing of these shock waves is responsible for the enhanced noise and damage in cloud cavitation. The paper describes experiments and calculations conducted to investigate these phenomena in greater detail as part of an attempt to find ways of ameliorating the most destructive effects associate with cloud cavitation.