Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative Assessment of Intrinsic Regional Myocardial Deformation by Doppler Strain Rate Echocardiography in Humans: Validation Against Three-Dimensional Tagged Magnetic Resonance Imaging

Background—Tissue Doppler echocardiography–derived strain rate and strain measurements (SDE) are new quantitative indices of intrinsic cardiac deformation. The aim of this study was to validate and compare these new indices of regional cardiac function to measurements of 3-dimensional myocardial strain by tagged MRI. Methods and Results—The study population included 33 healthy volunteers, 17 patients with acute myocardial infarction, and 8 patients with suspected coronary artery disease who were studied during dobutamine stress echocardiography. Peak systolic myocardial velocities were measured by tissue Doppler echocardiography, peak systolic strain rates and strains by SDE, and strains by tagged MRI. In healthy individuals, longitudinal myocardial Doppler velocities decreased progressively from base to apex, whereas myocardial strain rates and strains were uniform in all segments. In patients with acute infarction, abnormal strains clearly identified dysfunctional areas. In infarcted regions, SDE showed 1.5±4.3% longitudinal stretching compared with −15.0±3.9% shortening in remote myocardium (P <0.001), and radial measurements showed −6.9±4.1% thinning and 14.3±5.0% thickening (P <0.001), respectively. During dobutamine infusion, longitudinal strains by SDE increased significantly from −13.5% to −23.8% (P <0.01) and radial strains increased from 13.1±3.1% to 29.3±11.5% (P <0.01). Comparisons between myocardial strains by SDE and tagged MRI in healthy individuals (n=11), in infarct patients (n=17), and during stress echo (n=4) showed excellent correlations (r =0.89 and r =0.96 for longitudinal and radial strains, respectively, P < 0.001). Conclusions—The present study demonstrates the ability of Doppler echocardiography to measure myocardial strains in a clinical setting. Myocardial strains by Doppler may represent a new powerful method for quantifying left ventricular function noninvasively in humans.
Semantic Innovation Management

Innovation within industrial environment can be viewed as a cyclic loop consisting of four distinct phases, i.e., recognition, initiation, implementation, and stabilization. Different information technology enabled innovation management tools supporting the lifecycle of innovation are classified as five layers, i.e., individual innovation, project innovation, collaborative innovation, distributed innovation, and semantic innovation. According the fact that the current state is evolving from distributed innovation to semantic innovation, this paper focus on the realization of Semantic Web technologies enabled semantic innovation. To explicitly and formally specify all the different perspectives of innovation related information, a shared ontology is proposed as the common language of innovation management, which describes the critical and minimal information about the innovation process in a holistic way. Then, a technical framework which employs the machine readable innovation ontology to actually improve innovation management inside an organization and among loosely coupled organizations is presented. Finally, some features of the semantic innovation are discussed.
Scaled solar tracks and isochrones in a large region of the Z-Y plane I. From the ZAMS to the TP-A

Context. In many astrophysical contexts, the helium content of stars may differ significantly from those usually assumed in evolution- ary calculations. Aims. In order to improve upon this situation, we have computed tracks and isochrones in the range of initial masses 0.15−20 Mfor a grid of 39 chemical compositions with the metal content Z between 0.0001 and 0.070 and helium content Y between 0.23 and 0.46. Methods. The Padova stellar evolution code has been implemented with updated physics. New synthetic TP-AGB models allow the extension of stellar models and isochrones until the end of the thermal pulses along the AGB. Software tools for the bidimensional interpolation (in Y and Z) of the tracks have been tuned. Results. This first paper presents tracks for low mass stars (from 0.15 to 2.5 M� ) with scaled-solar abundances and the corresponding isochrones from very old ages down to about 1 Gyr. Conclusions. Tracks and isochrones are made available in tabular form for the adopted grid of chemical compositions in the plane Z-Y. As soon as possible an interactive web interface will allow users to obtain isochrones of any chemical composition and also simulated stellar populations with different Y(Z) helium-to-metal enrichment laws.
Estimating the Secrecy-Rate of Physical Unclonable Functions with the Context-Tree Weighting Method

We propose methods to estimate the secrecy-rate of fuzzy sources (e.g. biometrics and physical unclonable functions (PUFs)) using context-tree weighting. In this paper we focus on PUFs. In order to show that our estimates are realistic we first generalize Maurer's (1993) result to the ergodic case. Then we focus on the fact that the entropy of a stationary two-dimensional structure is a limit of a series of conditional entropies, a result by Anastassiou and Sakrison (1982). We extend this result to the conditional entropy of one two-dimensional structure given another one. Finally we show that the general CTW-method approaches the source entropy also in the two-dimensional stationary case. We further extend this result to the two-dimensional conditional entropy. Based on the obtained results we do several measurements on (our) optical PUFs. These measurements allow us to conclude that a secrecy-rate of 0.3 bit/location is possible
Clustering-based data transmission algorithms for VANET

In recent years, vehicular ad-hoc network (VANET) has received considerable attention. In VANET, safety application and user Internet accessing related application are expected to be supported. However, the characteristics of VANET, including high-speed mobility, channel fading property, channel competition mechanism, and various quality of service (QoS) of user services, etc., pose challenges and difficulties on data transmission in VANET. In this paper, clustering-based scheme is applied for data transmission in VANET, a cluster head (CH) selection algorithm and a cluster switching algorithm for VANET are presented. The proposed CH selection algorithm jointly considers node degree, the available resource of candidate CHs and the velocity difference between candidate CHs and other cluster members (CMs) in a given cluster. The proposed optimal cluster switching scheme stresses the QoS requirements of both delay-sensitive service and throughput-sensitive service, through defining utility functions for accessing various clusters, the optimal destination cluster can be obtained. The numerical results demonstrate the efficiency of the proposed algorithms.
Long-Term Survival of AIDS Patients Treated with Only Traditional Chinese Medicine

Abstract Traditional Chinese herbal medicine (TCM) has been used in Chinese society for more than 5,000 years to treat diseases from inflammation to cancer. Here, we report the case of nine living AIDS patients in the age range of 51 to 67 who were treated with either a unique formula of TCM alone from 2001 to 2009 or the TCM from 2001 to 2006 and then switched to occasional antiretroviral therapy. Surprisingly, the viral loads of eight patients were at undetectable levels on June 28, 2016, while the remaining patient had a low viral load of 29 copies/ml. The CD4+ counts (170–592 cells/μl) and CD4+/CD8+ ratios (0.21–0.90) of the nine patients are excellent, contributing to their current good health. Thus, the case study suggests that the TCM has the potential to become a functional cure for HIV/AIDS.
Bridging the gap between structured requirements and object-oriented analysis and design

A very large part of the business world today still uses a traditional structured approach to requirements gathering. On the technology side, extensive development has been done in the area of object-oriented technologies that provides for productivity and quality through reusability, encourages team work and adopts a modular approach. Since the quality of the object-oriented applications has proven to be superior to the structured applications, especially in the area of maintenance, there has been a large demand for object-oriented applications. This leads to the situation where the requirements are structured, and the application needs to be object-oriented subject matter experts (SMEs), with their knowledge of the system modeled and analysts, with their knowledge of the object-oriented paradigm, need to work together and reorganize the information from the requirements analysis. This paper proposes and develops a methodology for the transition. Emphasis is placed on presenting the knowledge captured in the requirements specification. The proposed methodology extends the existing Classes-Responsibilities-Collaborators (CRC) method and is tailored to be simple and understandable to SMEs, requiring minimal amount of training, yet powerful enough to enable the participants to think through the model in an object-oriented fashion.
Polynomial and RBF Kernels as Marker Selection Tools-A Breast Cancer Case Study

The problem of marker selection in DNA microarray experiment, due to the "curse of dimensionality", has been mostly addressed so far by linear approaches. Taking into account the fact that the domain of interest is a complex one, where non-linear interconnections and dependencies may also exist among the extremely large number of examined genes, we address the use of nonlinear tools to assess the problem. In this study, we propose to apply the kernel ability of Support Vector Machines in combination with Fisher's ratio as an alternative approach to assess the problem.
Recent advances in psychological therapies for eating disorders

Recent years have seen substantial consolidation and development of the evidence base for psychological therapies for eating disorders. This review summarises the key changes over that time period. Specific forms of cognitive behavioural therapy and family-based treatment have consolidated and extended their positions as treatments of choice despite the development of novel approaches. However, there is still a significant need for further development and testing to improve recovery rates, particularly in anorexia nervosa.
Evaluation of bonding between oxygen plasma treated polydimethyl siloxane and passivated silicon

Oxygen plasma treatment has been used extensively to bond polydimethyl siloxane to polydimethyl siloxane or glass in the rapid prototyping of microfluidic devices. This study aimed to improve the bonding quality of polydimethyl siloxane to passivated silicon using oxygen plasma treatment, and also to evaluate the bonding quality. Four types of passivated silicon were used: phosphosilicate glass, undoped silicate glass, silicon nitride and thermally grown silicon dioxide. Bonding strength was evaluated qualitatively and quantitatively using manual peel and mechanical shear tests respectively. Through peel tests we found that the lowering of plasma pressure from 500 to 30 mTorr and using a plasma power between 20 to 60 W helped to improve the bond quality for the first three types of passivation. Detailed analysis and discussion were conducted to explain the discrepancy between the bonding strength results and peeling results. Our results suggested that polydimethyl siloxane can be effectively bonded to passivated silicon, just as to polydimethyl siloxane or glass.
Ikoma Lyssavirus, Highly Divergent Novel Lyssavirus in an African Civet

Evidence in support of a novel lyssavirus was obtained from brain samples of an African civet in Tanzania. Results of phylogenetic analysis of nucleoprotein gene sequences from representative Lyssavirus species and this novel lyssavirus provided strong empirical evidence that this is a new lyssavirus species, designated Ikoma lyssavirus.
Integrative data mining: the new direction in bioinformatics

Biological research is becoming increasingly database driven, motivated, in part, by the advent of large-scale functional genomics and proteomics experiments such as those comprehensively measuring gene expression. These provide a wealth of information on each of the thousands of proteins encoded by a genome. Consequently, a challenge in bioinformatics is integrating databases to connect this disparate information as well as performing large-scale studies to collectively analyze many different data sets. This approach represents a paradigm shift away from traditional single-gene biology, and it often involves statistical analyses focusing on the occurrence of particular features (e.g., folds, functions, interactions, pseudogenes, or localization) in a large population of proteins. Moreover, the explicit application of machine learning techniques can be used to discover trends and patterns in the underlying data. In this article, we give several examples of these techniques in a genomic context: clustering methods to organize microarray expression data, support vector machines to predict protein function, Bayesian networks to predict subcellular localization, and decision trees to optimize target selection for high-throughput proteomics.
How to mix a density matrix

A given density matrix may be represented in many ways as a mixture of pure states. We show how any density matrix may be realized as a uniform ensemble. It has been conjectured that one may realize all probability distributions that are majorized by the vector of eigenvalues of the density matrix. We show that if the states in the ensemble are assumed to be distinct then this is not true, but a marginally weaker statement may still be true.
Liar Liar: Experimental Evidence of the Effect of Confirmation‐Reports on Dishonesty

We identify the effect of confirmation‐reports on dishonesty using data from an experiment where subjects are asked to roll a die and report its outcome using either a self‐report or confirmation‐report mechanism. We find that relative to self‐reports, confirmation‐reports have a positive effect on the share of subjects who report honestly. The effect on the magnitude of lies told depends greatly on the accuracy of the prefilled information on the confirmation‐report. We argue that these results are driven by changes in the intrinsic costs of lying induced by the confirmation report.
ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening

Breast cancer screening policies attempt to achieve timely diagnosis by regularly screening healthy women via various imaging tests. Various clinical decisions are needed to manage the screening process: selecting initial screening tests, interpreting test results, and deciding if further diagnostic tests are required. Current screening policies are guided by clinical practice guidelines (CPGs), which represent a “one-size-fits-all” approach, designed to work well (on average) for a population, and can only offer coarse expert-based patient stratification that is not rigorously validated through data. Since the risks and benefits of screening tests are functions of each patient's features,personalized screening policies tailored to the features of individuals are desirable. To address this issue, we developed ConfidentCare: a computer-aided clinical decision support system that learns a personalized screening policy from electronic health record (EHR) data. By a “personalized screening policy,” we mean a clustering of women's features, and a set of customized screening guidelines for each cluster. ConfidentCare operates by computing clusters of patients with similar features, then learning the “best” screening procedure for each cluster using a supervised learning algorithm. The algorithm ensures that the learned screening policy satisfies a predefined accuracy requirement with a high level of confidence for every cluster. By applying ConfidentCare to real-world data, we show that it outperforms the current CPGs in terms of cost efficiency and false positive rates: a reduction of 31% in the false positive rate can be achieved.
Remarks on One Arbitrated Quantum-signature Scheme

Zeng and Keitel proposed an arbitrated quantum signature scheme In 2002. Recently, Curty and Lutkenhaus pointed out that the protocol is not operationally specified. In a reply, Zeng gave more details of the scheme. The author also claimed that the scheme is suitable for unknown messages. In this letter, we remark that the invented scenario in the original scheme is artificial. This is because its security entirely depends on the presence of a trustworthy arbitrator. Moreover, the claim that the original scheme is suitable for unknown messages is not sound.
Ad-hoc Top-k Query Answering for Data Streams

A top-k query retrieves the k highest scoring tuples from a data set with respect to a scoring function defined on the attributes of a tuple. The efficient evaluation of top-k queries has been an active research topic and many different instantiations of the problem, in a variety of settings, have been studied. However, techniques developed for conventional, centralized or distributed databases are not directly applicable to highly dynamic environments and on-line applications, like data streams. Recently, techniques supporting top-k queries on data streams have been introduced. Such techniques are restrictive however, as they can only efficiently report top-k answers with respect to a pre-specified (as opposed to ad-hoc) set of queries. In this paper we introduce a novel geometric representation for the top-k query problem that allows us to raise this restriction. Utilizing notions of geometric arrangements, we design and analyze algorithms for incrementally maintaining a data set organized in an arrangement representation under streaming updates. We introduce query evaluation strategies that operate on top of an arrangement data structure that are able to guarantee efficient evaluation for ad-hoc queries. The performance of our core technique is augmented by incorporating tuple pruning strategies, minimizing the number of tuples that need to be stored and manipulated. This results in a main memory indexing technique supporting both efficient incremental updates and the evaluation of ad-hoc top-k queries. A thorough experimental study evaluates the efficiency of the proposed technique.
The Two-Component Regulatory System mtrAB Is Required for Morphotypic Multidrug Resistance in Mycobacterium avium

ABSTRACT Clinical isolates of the opportunistic pathogen Mycobacterium avium complex (MAC) undergo a reversible switch between red and white colony morphotypes on agar plates containing the lipoprotein stain Congo red. Compared to their isogenic red counterparts, white morphotypic variants are more virulent and more resistant to multiple antibiotics. This report shows that the two-component regulatory system mtrAB is required for the red-to-white switch as well as for other morphotypic switches of MAC. A mutant with a transposon insertion in the histidine protein kinase gene mtrB was isolated from a morphotypically white parent clone. The mutant resembled a naturally occurring red morphotypic variant in that it stained with Congo red, was sensitive to multiple antibiotics, and was permeable by a fluorescent DNA stain. However, it differed from a red variant in that it could not switch to the white or transparent morphotype, and it could not survive intracellularly within macrophage-like cells. Transcomplementation with a cloned wild-type mtrB gene restored to the mutant the ability to form impermeable, drug-resistant white and transparent variants. Quantitative reverse transcriptase PCR showed that mtrB was required for the normal expression of cell surface Mce proteins, some of which are up-regulated in the red-to-white switch. The results indicate that mtrAB functions in regulating the composition and permeability of mycobacterial cell walls and plays a role in the reversible colony type switches of MAC.
The sexual lives of breast cancer patients: Coping with changes associated with treatment

Objective: To clarify how breast cancer patients undergoing post-surgical hormone therapy cope with changes in their sexual lives and support themselves and their partners during these changes. Methods: Participants were 37 breast cancer patients undergoing post-surgical hormone therapy and attending mammary outpatient clinics. In-depth interviews and grounded theory were used to collect and analyze data, respectively. Results: First, sexual life was divided into four groups: “No complaint” regarding sexual activity, “Slight discord”, “Handicapped in meeting a life partner” and “Uninterested” in sexual activity. Sexual life during surgical-hormone therapy did not change significantly from sexual life before breast cancer. Second, meanings of sexual activity for breast cancer patients were divided into five, “Regaining femininity”, “Confirming love”, “Sharing pleasure”, “Response to partner’s higher desire” and “Procreation”. They differed by group. Third, coping strategies were divided into six, “Virtuous cycle to confirm love and regain lost femininity”, “Struggle to avoid relationship crisis”, “Reconfirmation of partner’s affection by his abstinence”, “Attempt to recover the sexual activity they hope for”, “Pursuing children or assuaging partner’s desire by other means” and “Difficulty making a partner continue to have sexual activity”. Conclusions: Nurses should screen breast cancer patients for changes in their sexual lives and to ascertain what sexual activity means to patients, and support them in selecting appropriate coping methods.
Parallel Computational Tree Logic

In the present paper we introduce a parallel version of the Computation Tree Logic. Here we distinguish between asynchronous and synchronous semantics. For both cases we investigate the computational complexity of the satisfiabi lity as well as the model checking problem. Satisfiability is shown t o be EXPTIME-complete whereas it does not matter which of the two semantics are considered. For model checking we prove a PSPACE-completeness result for the synchronous case, and s how P-completeness for the asynchronous case. Further we exhib it several interesting properties of both semantics.
Neural mechanisms underlying the effects of face-based affective signals on memory for faces: a tentative model

In our daily lives, we form some impressions of other people. Although those impressions are affected by many factors, face-based affective signals such as facial expression, facial attractiveness, or trustworthiness are important. Previous psychological studies have demonstrated the impact of facial impressions on remembering other people, but little is known about the neural mechanisms underlying this psychological process. The purpose of this article is to review recent functional MRI (fMRI) studies to investigate the effects of face-based affective signals including facial expression, facial attractiveness, and trustworthiness on memory for faces, and to propose a tentative concept for understanding this affective-cognitive interaction. On the basis of the aforementioned research, three brain regions are potentially involved in the processing of face-based affective signals. The first candidate is the amygdala, where activity is generally modulated by both affectively positive and negative signals from faces. Activity in the orbitofrontal cortex (OFC), as the second candidate, increases as a function of perceived positive signals from faces; whereas activity in the insular cortex, as the third candidate, reflects a function of face-based negative signals. In addition, neuroscientific studies have reported that the three regions are functionally connected to the memory-related hippocampal regions. These findings suggest that the effects of face-based affective signals on memory for faces could be modulated by interactions between the regions associated with the processing of face-based affective signals and the hippocampus as a memory-related region.