Miracle-dz/UniFAR-FTUs huggingface dataset:
Xpert MTB/RIF and pulmonary tuberculosis: time to delve deeper?

I find out what the world needs, then proceed to invent it. Thomas Edison. If Edison, the world’s most prolific inventor, had to get around to creating a new diagnostic test for tuberculosis (TB), he would have considered himself pleased with the Xpert MTB/RIF test. Here is the new diagnostic test for TB that the physician in the developing world has been waiting for. It does two things, and does them both well. It diagnoses TB with a higher sensitivity than a sputum smear examination: a single Xpert MTB/RIF test diagnoses 98% of sputum smear positive cases and around 70% of smear-negative patients.1 More importantly, for the physician practicing in areas with a high prevalence of multi-drug resistant TB (MDR-TB), it diagnoses rifampicin resistance (a surrogate marker for MDR-TB) with around 98% sensitivity and specificity, thus identifying patients who need second-line drugs.2 That it does this with safety, speed and simplicity is what makes this test a ‘game changer’. 3 A result is obtained within 90 min, lopping off 6–8 weeks from the time that a traditional culture would take to diagnose MDR-TB. Called a ‘laboratory in a cartridge’, the test comprises of a cartridge-based system using an automated real-time, PCR-based assay with molecular beacon technology. The test, which is easy to learn, can be performed by a technician with 2 days of training. Robust enough to be performed in emergency departments and small laboratories in hospitals across the developing world, it poses substantially less of a biohazard risk and hence obviates the need for bio safety cabinets, which are anyway conspicuous by …
Using lattice of class and method dependence for change impact analysis of object oriented programs

Software change impact analysis (CIA) is a key technique to identify unpredicted and potential effects caused by software changes. In this paper, we propose a new CIA technique based on a compact and effective representation for object oriented programs, called lattice of class and method dependence (LoCMD). This novel representation can effectively capture the dependences between classes and methods. Based on the LoCMD, our CIA technique calculates a ranked list of potential impacted methods according to a metric, impact factor, which corresponds to the priority of these methods to be inspected. Initial case study validates the reasonability of our two assumptions, and demonstrates the effectiveness of our technique.
Effect of exposure to injection drugs or alcohol on antigen-specific immune responses in HIV and hepatitis C virus coinfection.

BACKGROUND Ongoing substance use is a potential confounder for immunological studies on hepatitis C virus (HCV), but there is little in the literature regarding the effects of injection drug use (IDU) or alcohol on HCV-specific immune responses. We wanted to determine whether IDU or alcohol affected immune responses in HCV-infected and human immunodeficiency virus (HIV)/HCV coinfected subjects. METHODS Eight-four subjects with HIV/HCV and 57 with HCV were classified as either injection drug users, drinkers, or nonusers based on questionnaire results. Immune responses were studied with enzyme-linked immunosorbent spot assay for interferon (IFN)- gamma , interleukin (IL)-10, and tumor necrosis factor (TNF)- alpha against HCV proteins Core, NS3, and NS5 and recall antigens. RESULTS Subjects with HIV/HCV, in aggregate, had significantly lower HCV-specific IFN- gamma and TNF- alpha responses than subjects with HCV. However, HIV/HCV injection drug users had HCV-specific IFN- gamma and IL-10 responses that were similar to those of HCV injection drug users and were significantly higher than in nonusers with HIV/HCV. Conversely, subjects who drank alcohol had similar immune responses to those who were abstinent, among both subjects with HIV/HCV and subjects with HCV. CONCLUSIONS Studies that examine IFN- gamma or IL-10 immune responses in HIV/HCV-coinfected or HCV-infected persons need to consider current IDU. Alcohol, at levels consumed in this cohort, does not appear to have as much of an effect on antigen-specific immune responses.
Ubiquitination and Proteasomal Degradation of the BRCA1 Tumor Suppressor Is Regulated during Cell Cycle Progression*

The BRCA1 tumor suppressor and the BARD1 protein form a stable heterodimeric complex that can catalyze the formation of polyubiquitin chains. Expression of BRCA1 fluctuates in a cell cycle-dependent manner, such that low steady-state levels of BRCA1 gene products are found in resting cells and early G1 cycling cells and high levels in S and G2 phase cells. Although transcriptional activation of the BRCA1 gene can account for induction of BRCA1 expression at the G1/S transition, the mechanisms by which BRCA1 is down-regulated during cell cycle progression have not been addressed. Here we show that the steady-state levels of BRCA1 protein remain elevated throughout mitosis but begin to decline at the M/G1 transition. This decline in BRCA1 levels coincides with the appearance of proteasome-sensitive ubiquitin conjugates of BRCA1 at the onset of G1. Formation of these conjugates occurs throughout G1 and S, but not in cells arrested in prometaphase by nocodazole. The proteasome-sensitive ubiquitin conjugates of BRCA1 appear to be distinct from BRCA1 autoubiquitination products and are probably catalyzed by the action of other cellular E3 ligases. Interestingly, co-expression of BARD1 inhibits the formation of these conjugates, suggesting that BARD1 serves to stabilize BRCA1 expression in part by reducing proteasome-sensitive ubiquitination of BRCA1 polypeptides. In summary, these data indicate that the cell cycle-dependent pattern of BRCA1 expression is determined in part by ubiquitin-dependent proteasomal degradation.
From von neumann, John Atanasoff and ABC to Neuromorphic computation and the NeuCube spatio-temporal data machine

During the 1940s John Atanasoff with the help of one of his students Clifford E. Berry, in Iowa State College, created the ABC (Atanasoff-Berry Computer) that was the first electronic digital computer. The ABC computer was not a general-purpose one, but still, it was the first to implement three of the most important ideas used in computers nowadays: binary data representation; using electronics instead of mechanical switches and wheels; using a Von Neumann architecture, where the memory and the computations are separated. A new computational paradigm, named as Neuromorphic, utilises the above two principles, but instead of the Von Neumann principle, it integrates the memory and the computation in a single module a spiking neural network (SNN) structure. The paper first reviews the need for neuromorphic systems and describes the principle differences from the traditional von Neumann architecture and then presents the NeuCube neuromorphic evolving spatio-temporal data machine for learning, recognising and understanding of spatio and spectro-temporal data using neuromorphic principles. This is the one of its kind artificial intelligence system that can be directly ported on the neuromorphic hardware chips. A limited version of the NeuCube software implementation is available from http://www.kedri. aut.ac. nz/neucube/.
High and Mighty: Implicit Associations between Space and Social Status

Figurative language and our perceptuo-motor experiences frequently associate social status with physical space. In three experiments we examine the source and extent of these associations by testing whether people implicitly associate abstract social status indicators with concrete representations of spatial topography (level versus mountainous land) and relatively abstract representations of cardinal direction (south and north). Experiment 1 demonstrates speeded performance during an implicit association test (Greenwald et al., 1998) when average social status is paired with level topography and high status with mountainous topography. Experiments 2 and 3 demonstrate a similar effect but with relatively abstract representations of cardinal direction (south and north), with speeded performance when average and powerful social status are paired with south and north coordinate space, respectively. Abstract concepts of social status are perceived and understood in an inherently spatial world, resulting in powerful associations between abstract social concepts and concrete and abstract notions of physical axes. These associations may prove influential in guiding daily judgments and actions.
Do Housekeeping Genes Exist?

The searching of human housekeeping (HK) genes has been a long quest since the emergence of transcriptomics, and is instrumental for us to understand the structure of genome and the fundamentals of biological processes. The resolved genes are frequently used in evolution studies and as normalization standards in quantitative gene-expression analysis. Within the past 20 years, more than a dozen HK-gene studies have been conducted, yet none of them sampled human tissues completely. We believe an integration of these results will help remove false positive genes owing to the inadequate sampling. Surprisingly, we only find one common gene across 15 examined HK-gene datasets comprising 187 different tissue and cell types. Our subsequent analyses suggest that it might not be appropriate to rigidly define HK genes as expressed in all tissue types that have diverse developmental, physiological, and pathological states. It might be beneficial to use more robustly identified HK functions for filtering criteria, in which the representing genes can be a subset of genome. These genes are not necessarily the same, and perhaps need not to be the same, everywhere in our body.
Counterfeit Object-oriented Programming: On the Difficulty of Preventing Code Reuse Attacks in C++ Applications

Code reuse attacks such as return-oriented programming (ROP) have become prevalent techniques to exploit memory corruption vulnerabilities in software programs. A variety of corresponding defenses has been proposed, of which some have already been successfully bypassed -- and the arms race continues. In this paper, we perform a systematic assessment of recently proposed CFI solutions and other defenses against code reuse attacks in the context of C++. We demonstrate that many of these defenses that do not consider object-oriented C++ semantics precisely can be generically bypassed in practice. Our novel attack technique, denoted as counterfeit object-oriented programming (COOP), induces malicious program behavior by only invoking chains of existing C++ virtual functions in a program through corresponding existing call sites. COOP is Turing complete in realistic attack scenarios and we show its viability by developing sophisticated, real-world exploits for Internet Explorer 10 on Windows and Fire fox 36 on Linux. Moreover, we show that even recently proposed defenses (CPS, T-VIP, vfGuard, and VTint) that specifically target C++ are vulnerable to COOP. We observe that constructing defenses resilient to COOP that do not require access to source code seems to be challenging. We believe that our investigation and results are helpful contributions to the design and implementation of future defenses against control flow hijacking attacks.
Detecting change and emergence for multiword expressions

This work looks at a temporal aspect of multiword expressions (MWEs), namely that the behaviour of a given n-gram and its status as a MWE change over time. We propose a model in which context words have particular probabilities given a usage choice for an n-gram, and those usage choices have time dependent probabilities, and we put forward an expectationmaximisation technique for estimating the parameters from data with no annotation of usage choice. For a range of MWE usages of recent coinage, we evaluate whether the technique is able to detect the emerging usage.
The Influence of Wireless Self-Monitoring Program on the Relationship Between Patient Activation and Health Behaviors, Medication Adherence, and Blood Pressure Levels in Hypertensive Patients: A Substudy of a Randomized Controlled Trial

Objective: Alcohol consumption has an important effect on coronary atherosclerotic heart disease (CAD). Acetaldehyde dehydrogenase 2 (ALDH2) is a key enzyme in alcohol metabolism. A G-to-A missense mutation of ALDH2 gene, rs671, which causes a Glu > Lys (504) substitution, was performed to detect the association with CAD and other relative diseases, but the results were not conclusive. The purpose of the present study was to determine whether this locus confers significant susceptibility to myocardial infarction and stroke in a Chinese population. Design and Method: We conducted two case–control association studies (one cohort of 2325 myocardial infarction patients and 2620 unrelated controls, another cohort of 3960 stroke patients and 3654 controls)from the Chinese population. Genotyping of the rs671 SNP was performed by the TaqMan Real Time PCR method. Results: We found that rs671 (G allele) was significantly associated with myocardial infarction (odds ratio 1.21, 95% CI: 1.088–1.337, p = 0.00027, additive model), and logistic regression result indicated that the polymorphism was not associated with alcohol consumption and other risk factors. However, rs671 (G allele) showed a protective effect on stroke patients without drinking (odds ratio 0.82, 95%CI: 0.741–0.908, p = 0.00033, additive model), and no relationship observed between SNP and stroke in patients with drinking. Conclusions: Our results indicate that, in the Chinese population, the ALDH2 variant rs671 is a risk factor of myocardial infarction but a protective factor of stroke without alcohol consumption. The role and pathway of ALDH2 involving in these diseases need more researches.
Estimating a State-Space Model from Point Process Observations

A widely used signal processing paradigm is the state-space model. The state-space model is defined by two equations: an observation equation that describes how the hidden state or latent process is observed and a state equation that defines the evolution of the process through time. Inspired by neurophysiology experiments in which neural spiking activity is induced by an implicit (latent) stimulus, we develop an algorithm to estimate a state-space model observed through point process measurements. We represent the latent process modulating the neural spiking activity as a gaussian autoregressive model driven by an external stimulus. Given the latent process, neural spiking activity is characterized as a general point process defined by its conditional intensity function. We develop an approximate expectation-maximization (EM) algorithm to estimate the unobservable state-space process, its parameters, and the parameters of the point process. The EM algorithm combines a point process recursive nonlinear filter algorithm, the fixed interval smoothing algorithm, and the state-space covariance algorithm to compute the complete data log likelihood efficiently. We use a Kolmogorov-Smirnov test based on the time-rescaling theorem to evaluate agreement between the model and point process data. We illustrate the model with two simulated data examples: an ensemble of Poisson neurons driven by a common stimulus and a single neuron whose conditional intensity function is approximated as a local Bernoulli process.
Intercode translation : Words and music in opera

Abstract: Opera is a synchronization of different media of artistic expression, with a dual emphasis on music and drama. Operatic scholarship has voiced different views on the fusion of verbal and musical discourse, the two extremes being logocentrism and musicocentrism. The interlingual translation of the verbal subtext is a complex enterprise subject to multiple constraints. By focusing on its intricacies in some detail (the anatomy of the human vocal apparatus, high/low pitches, stress, prosodic and intonational patterns, rhyme, etc., together determining the singability of the libretto), I hope that the discussion will shed light on the manifold problems involved in opera translation. The theoretical remarks are exemplified in an analysis of selected passages from Das Rheingold, by Richard Wagner.Resume: L'opera est une synchronisation de differents moyens d'expression artistique avec un double accent sur la musique et le drame. Les etudes scientifiques sur l'opera ont exprime differents points de vue sur la fusion du discours verbal et musical; les conceptions extremes ont ete le logocentrisme et le musicocentrisme. La traduction interlinguale du subtexte verbal represente une tâche complexe soumise a des contraintes multiples. En mettant l'accent sur la complexite de cette tâche, en ce qui concerne les details tels que l'anatomie de l'appareil vocal humain, les tons hauts et bas, l'accent tonique, les structures de la prosodie et de l'intonation, la rime, etc., tout ce qui ensemble determine la qualite "chantable " du livret, nous esperons par la presente discussion mettre en lumiere la complexite des problemes inherente a la traduction en matiere d'opera. Pour illustrer et verifier ces remarques nous prenons comme exemple d'analyse Das Rheingold, de Richard Wagner.
The Logic of Hypothesis Generation in Kinetic Modeling of System Biology

In the past decades a lot of researches have been conducted to investigate pathways in order to increase the understanding of the mechanisms responsible for diseases and thus to find new treatments. One strategy to achieve this goal would be to inhibit or to trigger a part of the pathway that produces the disease. A strategy would be to first identify the pathway whose activity contributes to the disease and then look for drugs that inhibit or trigger the pathway acting on its internal components and reactions.
Strategies for Evaluating and Targeting Pragmatic Behaviors in Young Children

Reprint requests: Dr. Creaghead, University of Cincinnati, Cincinnati, OH 10379. ~t is well recognized by researchers and clinicians in the areas of child language acquisition and disorders that thorough evaluation of pragmatic skills requires observation in naturalistic settings (Lund and Duchan, 1983; Prutting, 1982; Spradlin and Siegel, 1982). There are several factors that dictate that this should be so.
Graph-based Clustering of Synonym Senses for German Particle Verbs

In this paper, we address the automatic induction of synonym paraphrases for the empirically challenging class of German particle verbs. Similarly to Cocos and Callison-Burch (2016), we incorporate a graph-based clustering approach for word sense discrimination into an existing paraphrase extraction system, (i) to improve the precision of synonym identification and ranking, and (ii) to enlarge the diversity of synonym senses. Our approach significantly improves over the standard system, but does not outperform an extended baseline integrating a simple distributional similarity measure.
A Crossover-Imaged Clustering Algorithm with Bottom-up Tree

The grid-based clustering algorithms are efficient with low computation time, but the size of the predefined grids and the threshold of the significant cells are seriously influenced their effects. The ADCC [1] and ACICA+ [2] are two new grid-based clustering algorithms. The ADCC algorithm uses axis-shifted strategy and cell clustering twice to reduce the influences of the size of the cells and inherits the advantage with the low time complexity. And the ACICA+ uses the crossover image of significant cells and just only one cell clustering. But the extension of original significant cell in one crossover image is not easy to find what else clusters it belongs to. The crossover-imaged clustering algorithm with bottom-up tree architecture, called CIC-BTA, is proposed to use bottom-up tree architecture to have the same results. The main idea of CIC-BTA algorithm is to use the bottom-up tree architecture to link the significant cells to be the pre-clusters and combine pre-clusters into one by using semi-significant cells The final set of clusters is the result.
Retinex in Matlab

ial gital ce, on. al 003 Abstract. Many different descriptions of Retinex methods of lightness computation exist. We provide concise MATLABTM implementations of two of the spatial techniques of making pixel comparisons. The code is presented, along with test results on several images and a discussion of the results. We also discuss the calibration of input images and the postRetinex processing required to display the output images. © 2004 SPIE and IS&T. [DOI: 10.1117/1.1636761]
A Human Ecological Model of Spirit at Work

An empirically grounded, human ecological model of spirit at work specifying antecedent conditions and outcomes of spirit at work is presented. Spirit at work is a distinct state characterized by profound feelings of wellbeing, a belief that one is engaged in meaningful work, a connection to others and common purpose, a connection to something larger than self, and it has a transcendent nature. Four distinct paths to spirit at work are identified: always there, coming together, transformative event, and contextually sensitive. These paths are affected by individual factors (personality characteristics and personal actions) and contextual factors (organizational characteristics and transformative life events) that contribute to the experience of spirit at work. This model posits that personality, personal actions, and organizational characteristics are interconnected and operate to foster or impede an individual's spirit at work. Spirit at work appears to counteract disenchantment and disengagement at work and results in positive outcomes for employees, consumers, and organizations.
Microscopic image analysis for quantitative measurement and feature identification of normal and cancerous colonic mucosa

The development of an automated algorithm for the categorization of normal and cancerous colon mucosa is reported. Six features based on texture analysis were studied. They were derived using the co-occurrence matrix and were angular second moment, entropy, contrast, inverse difference moment, dissimilarity, and correlation. Optical density was also studied. Forty-four normal images and 58 cancerous images from sections of the colon were analyzed. These two groups were split equally into two subgroups: one set was used for supervised training and the other to test the classification algorithm. A stepwise selection procedure showed that correlation and entropy were the features that discriminated most strongly between normal and cancerous tissue (P<0.0001). A parametric linear-discriminate function was used to determine the classification rule. For the training set, a sensitivity and specificity of 93.1% and 81.8%, respectively, were achieved, with an overall accuracy of 88.2%. These results mere confirmed with the test set, with a sensitivity and specificity of 93.1% and 86.4%, respectively, and an overall accuracy of 90.2%.
A new method for extracting interface state and border trap densities in high-k/III-V MOSFETs

Increased CMOS performance requires the introduction of alternative materials as substrate and gate dielectrics. III-V materials and in particular InGaAs can provide superior electron mobility compared to classic Si substrates. However, such substrate materials have non-optimal dielectric-semiconductor interfaces that can drastically reduce the device performance. Techniques for the extraction of interface and border trap profiles are required for the characterization and optimization of these materials. In this paper we present a new procedure relying on a physical charge-transport model including trap assisted tunneling, lattice relaxation and trap assisted generation and recombination of minority carriers. The procedure allows the extraction of interface and border trap densities from capacitance voltage characteristics measured at different frequencies. The technique is applied to characterize InGaAs MOSFETs Al2O3/ZrO2 stacks of different thicknesses and fabricated with different annealing conditions.