Miracle-dz/UniFAR-FTUs huggingface dataset:
Alcohol, Hospital Discharge, and Socioeconomic Risk Factors for Default from Multidrug Resistant Tuberculosis Treatment in Rural South Africa: A Retrospective Cohort Study

Background Default from multidrug-resistant tuberculosis (MDR-TB) treatment remains a major barrier to cure and epidemic control. We sought to identify patient risk factors for default from MDR-TB treatment and high-risk time periods for default in relation to hospitalization and transition to outpatient care. Methods We retrospectively analyzed a cohort of 225 patients who initiated MDR-TB treatment between 2007 through 2010 at a rural TB hospital in the Western Cape Province, South Africa. Results Fifty percent of patients were cured or completed treatment, 27% defaulted, 14% died, 4% failed treatment, and 5% transferred out. Recent alcohol use was common (63% of patients). In multivariable proportional hazards regression, older age (hazard ratio [HR]= 0.97 [95% confidence interval 0.94-0.99] per year of greater age), formal housing (HR=0.38 [0.19-0.78]), and steady employment (HR=0.41 [0.19-0.90]) were associated with decreased risk of default, while recent alcohol use (HR=2.1 [1.1-4.0]), recent drug use (HR=2.0 [1.0-3.6]), and Coloured (mixed ancestry) ethnicity (HR=2.3 [1.1-5.0]) were associated with increased risk of default (P<0.05). Defaults occurred throughout the first 18 months of the two-year treatment course but were especially frequent among alcohol users after discharge from the initial four-to-five-month in-hospital phase of treatment, with the highest default rates occurring among alcohol users within two months of discharge. Default rates during the first two months after discharge were also elevated for patients who received care from mobile clinics. Conclusions Among patients who were not cured or did not complete MDR-TB treatment, the majority defaulted from treatment. Younger, economically-unstable patients and alcohol and drug users were particularly at risk. For alcohol users as well as mobile-clinic patients, the early outpatient treatment phase is a high-risk period for default that could be targeted in efforts to increase treatment completion rates.
Using a fine-grained comparative evaluation technique to understand and design software visualization tools

Software Visualization can be defined as the use of graphical and textual formalisms to describe the execution of computer programs. A large amount of Software Visualization technology has been developed to support computer science education, using a range of interface techniques. Far less effort has been devoted to evaluating the technology. As a result, it is unclear how effective Software Visualization tools are, either for students or professional programmers. Even more worrying, it is doubtful whether lessons are being learnt in successive designs of Software Visualization tools, or whether the application of new technologies (e.g. 3D animation and the internet) has become the primary goal, rather than the true goal of making computer programs easier to understand. To counter this problem the study reported here used protocol analysis to develop a fine-grained account of user behaviour, identifying (i) information access from the display, (ii) the use of comprehension strategies, and (iii) misunderstandings of the visualization and execution. The results were able to motivate future deigns which in turn could be compared and improved. The approach is compared to other evaluation techniques which aim to inform design. Finally, the generalizability of the approach is considered.
Temporal Task Scheduling With Constrained Service Delay for Profit Maximization in Hybrid Clouds

As cloud computing is becoming growingly popular, consumers’ tasks around the world arrive in cloud data centers. A private cloud provider aims to achieve profit maximization by intelligently scheduling tasks while guaranteeing the service delay bound of delay-tolerant tasks. However, the aperiodicity of arrival tasks brings a challenging problem of how to dynamically schedule all arrival tasks given the fact that the capacity of a private cloud provider is limited. Previous works usually provide an admission control to intelligently refuse some of arrival tasks. Nevertheless, this will decrease the throughput of a private cloud, and cause revenue loss. This paper studies the problem of how to maximize the profit of a private cloud in hybrid clouds while guaranteeing the service delay bound of delay-tolerant tasks. We propose a profit maximization algorithm (PMA) to discover the temporal variation of prices in hybrid clouds. The temporal task scheduling provided by PMA can dynamically schedule all arrival tasks to execute in private and public clouds. The sub problem in each iteration of PMA is solved by the proposed hybrid heuristic optimization algorithm, simulated annealing particle swarm optimization (SAPSO). Besides, SAPSO is compared with existing baseline algorithms. Extensive simulation experiments demonstrate that the proposed method can greatly increase the throughput and the profit of a private cloud while guaranteeing the service delay bound.
Syntactic Processing in Left Prefrontal Cortex Is Independent of Lexical Meaning

In language comprehension a syntactic representation is built up even when the input is semantically uninterpretable. We report data on brain activation during syntactic processing, from an experiment on the detection of grammatical errors in meaningless sentences. The experimental paradigm was such that the syntactic processing was distinguished from other cognitive and linguistic functions. The data reveal that in syntactic error detection an area of the left dorsolateral prefrontal cortex, adjacent to Broca's area, is specifically involved in the syntactic processing aspects, whereas other prefrontal areas subserve general error detection processes.
Supersense Tagger for Italian

In this paper we present the procedure we followed to develop the Italian Super Sense Tagger. In particular, we adapted the English SuperSense Tagger to the Italian Language by exploiting a parallel sense labeled corpus for training. As for English, the Italian tagger uses a fixed set of 26 semantic labels, called supersenses, achieving a slightly lower accuracy due to the lower quality of the Italian training data. Both taggers accomplish the same task of identifying entities and concepts belonging to a common set of ontological types. This parallelism allows us to define effective methodologies for a broad range of cross-language knowledge acquisition tasks
Robust Trajectory Tracking for Underactuated VTOL Aerial Vehicles: Extended for Adaptive Disturbance Compensation

Abstract This work proposes a feedback control strategy to let the dynamics of an under-actuated Vertical Take-Off and Landing (VTOL) aerial vehicle to track a desired trajectory thanks to an adaptive robust compensation of the aerodynamic disturbances. The novelty of the proposed approach consists in employing an aerodynamic disturbance observer derived using the NonLinear Geometric Approach and Radial Basis Functions (RBF). The obtained estimation is directly employed by a nonlinear robust feedback law which relies on a cascade control paradigm in which the attitude dynamics and the position dynamics of the vehicle play the role of the inner and of the outer loop, respectively. The robustness of the proposed approach is also demonstrated by means of simulation results in which the aerodynamic model of a multi-propeller aircraft is considered.
Functionally aberrant electrophysiological cortical connectivities in first episode medication-naive schizophrenics from three psychiatry centers

Functional dissociation between brain processes is widely hypothesized to account for aberrations of thought and emotions in schizophrenic patients. The typically small groups of analyzed schizophrenic patients yielded different neurophysiological findings, probably because small patient groups are likely to comprise different schizophrenia subtypes. We analyzed multichannel eyes-closed resting EEG from three small groups of acutely ill, first episode productive schizophrenic patients before start of medication (from three centers: Bern N = 9; Osaka N = 9; Berlin N = 12) and their controls. Low resolution brain electromagnetic tomography (LORETA) was used to compute intracortical source model-based lagged functional connectivity not biased by volume conduction effects between 19 cortical regions of interest (ROIs). The connectivities were compared between controls and patients of each group. Conjunction analysis determined six aberrant cortical functional connectivities that were the same in the three patient groups. Four of these six concerned the facilitating EEG alpha-1 frequency activity; they were decreased in the patients. Another two of these six connectivities concerned the inhibiting EEG delta frequency activity; they were increased in the patients. The principal orientation of the six aberrant cortical functional connectivities was sagittal; five of them involved both hemispheres. In sum, activity in the posterior brain areas of preprocessing functions and the anterior brain areas of evaluation and behavior control functions were compromised by either decreased coupled activation or increased coupled inhibition, common across schizophrenia subtypes in the three patient groups. These results of the analyzed three independent groups of schizophrenics support the concept of functional dissociation.
Multifunctional Micellar Nanomedicine for Cancer Therapy

Polymeric micelles are supramolecular, core-shell nanoparticles that offer considerable advantages for cancer diagnosis and therapy. Their relatively small size (10–100 nm), ability to solubilize hydrophobic drugs as well as imaging agents, and improved pharmacokinetics provide a useful bioengineering platform for cancer applications. Several polymeric micelle formulations are currently undergoing phase I/II clinical trials, which have shown improved antitumor efficacy and reduced systemic toxicity. This minireview will focus on recent advancements in the multifunctional design of micellar nanomedicine with tumor targeting, stimulated drug release, and cancer imaging capabilities. Such functionalization strategies result in enhanced micellar accumulation at tumor sites, higher drug bioavailability, as well as improved tumor diagnosis and visualization of therapy. Ultimately, integrated nanotherapeutic systems (e.g., theranostic nanomedicine) may prove essential to address the challenges of tumor heterogeneity and adaptive resistance to achieve efficacious treatment of cancer.
Deterministic Decentralized Search in Random Graphs

We study a general framework for decentralized search in random graphs. Our main focus is on deterministic memoryless search algorithms that use only local information to reach their destination in a bounded number of steps in expectation. This class includes (with small modifications) the search algorithms used in Kleinberg's pioneering work on long-range percolation graphs and hierarchical network models. We give a characterization of searchable graphs in this model, and use this characterization to prove a monotonicity property for searchability.
Using imputed genotype data in the joint score tests for genetic association and gene–environment interactions in case‐control studies

Genome‐wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene–environment interactions. We focus on case‐control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene–environment independence in the underlying population. As increasingly large‐scale GWAS are being performed through consortia effort where it is preferable to share only summary‐level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta‐analysis of “one‐step” maximum‐likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type‐I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene–environment interactions under the assumption of gene–environment independence. Methods are made available for public use through CGEN R software package.
Practical Work Function Tuning Based on Physical and Chemical Nature of Interfacial Impurity in Ni-FUSI/SiON and HfSiON Systems

The paper demonstrates large effective work function (Phieff) modulation towards Si band-edges based on physical and chemical nature of interfacial impurities at Ni-FUSI/SiON and HfSiON interfaces. The authors clarify the influence of Ni-silicide phase on the Phieff modulation with dopant segregation. Phieff of 4.14 eV is obtained with a combination of phosphorous ion implantation last (IIL) doping and newly developed low temperature NiSi2 formation process. The paper also proposed the realistic Phieff modulation with Al-segregation at Ni-FUSI/HfSiON using IIL-doping process
Automatic Structures — Recent Results and Open Questions

Regular languages are languages recognised by finite automata; automatic structures are a generalisation of regular languages where one also uses automatic relations (which are relations recognised by synchronous finite automata) and automatic functions (which are functions whose graph is an automatic relation). Functions and relations first-order definable from other automatic functions and relations are again automatic. Automatic functions coincide with the functions computed by position-faithful one-tape Turing machines in linear time. This survey addresses recent results and open questions on topics related to automatic structures: How difficult is the isomorphism problem for various types of automatic structures? Which groups are automatic? When are automatic groups Abelian or orderable? How can one overcome some of the limitations to represent rings and fields by weakening the automaticity requirements of a structure?
Hierarchical dialogue optimization using semi-Markov decision processes

This paper addresses the problem of dialogue optimization on large search spaces. For such a purpose, in this paper we propose to learn dialogue strategies using multiple Semi-Markov Decision Processes and hierarchical reinforcement learning. This approach factorizes state variables and actions in order to learn a hierarchy of policies. Our experiments are based on a simulated flight booking dialogue system and compare flat versus hierarchical reinforcement learning. Experimental results show that the proposed approach produced a dramatic search space reduction (99.36%), and converged four orders of magnitude faster than flat reinforcement learning with a very small loss in optimality (on average 0.3 system turns). Results also report that the learnt policies outperformed a hand-crafted one under three different conditions of ASR confidence levels. This approach is appealing to dialogue optimization due to faster learning, reusable subsolutions, and scalability to larger problems. Index Terms: Spoken dialogue systems, semi-Markov decision processes, hierarchical reinforcement learning.
Pointing gesture prediction using minimum-jerk model in human-robot interaction

A pointing gesture has an important role in human-human interaction. From our observation, we predict a pointing target before finishing the gesture in human-human communication. This paper, thus, proposes a method for a robot to predict human pointing gesture using the minimum-jerk model. Analytically, the final position of a wrist can be obtained by detecting the first acceleration peak, which corresponds to first 21\% of the entire gesture. We implemented and evaluated the method with a desktop size robot named Robovie-W. The result showed that our method improves naturalness and smoothness.
HIV-1 DNA decay dynamics in blood during more than a decade of suppressive antiretroviral therapy.

BACKGROUND Human immunodeficiency virus type 1 (HIV-1) DNA dynamics during long-term antiretroviral therapy (ART) are not defined. METHODS Blood mononuclear cells obtained during 7-12 years of effective ART were assayed for total HIV-1 DNA and 2-long terminal repeat (LTR) circles by quantitative polymerase chain reaction (qPCR). Slopes of HIV-1 DNA were estimated by participant-specific linear regressions. Plasma was assayed for residual viremia (HIV-1 RNA) by qPCR. RESULTS Thirty participants were studied. HIV-1 DNA decreased significantly from years 0-1 and 1-4 of ART with median decay slopes of -0.86 (interquartile range, -1.05, -0.59) and -0.11 (-0.17, -0.06) log10(copies/10(6) CD4+ T-cells)/year, respectively (P < .001). Decay was not significant for years 4-7 (-0.02 [-0.06, 0.02]; P = .09) or after year 7 of ART (-0.006 [-0.030, 0.015]; P = .17). All participants had detectable HIV-1 DNA after 10 years (median 439 copies/10(6) CD4+ T-cells; range: 7-2074). Pre-ART HIV-1 DNA levels were positively associated with pre-ART HIV-1 RNA levels (Spearman = 0.71, P < .001) and with HIV-1 DNA at years 4, 7, and 10 on ART (Spearman ≥ 0.75, P < .001). No associations were found (P ≥ .25) between HIV-1 DNA slopes or levels and % activated CD8+ T-cells (average during years 1-4) or residual viremia (n = 18). 2-LTR circles were detected pre-ART in 20/29 and in 8/30 participants at last follow-up. CONCLUSIONS Decay of HIV-1 DNA in blood is rapid in the first year after ART initiation (86% decline), slows during years 1-4 (23% decline/year), and subsequently plateaus. HIV-1 DNA decay is not associated with the levels of CD8+ T-cell activation or persistent viremia. The determinants of stable HIV-1 DNA persistence require further elucidation. Clinical Trials Registration. NCT00001137.
Static slicing of threaded programs

Static program slicing is an established method for analyzing sequential programs, especially for program understanding, debugging and testing. Until now, there was no slicing method for threaded programs which handles interference correctly. We present such a method which also calculates more precise static slices. This paper extends the well known structures of the control flow graph and the program dependencc graph for threaded programs with interference. This new technique does not require serialization of threaded programs.
Generalized semi-infinite programming: numerical aspects

Generalized semi-infinite optimization problems (GSIP) are considered. It is investigated how the numerical methods for standard semi-infinite programming (SIP) can be extended to GSIP. Newton methods can be extended immediately. For discretization methods the situation is more complicated. These difficulties are discussed and convergence results for a discretization- and an exchange method are derived under fairly general assumptions on GSIP. The question is answered under which conditions GSIP represents a convex problem.
Sweet Sorghum and Nitrogen Fertilizer Application – A Review

Sweet sorghum is similar to the grain sorghum in every respect but with the added feature of accumulating sugar in its stalk, just like sugarcane, which has given the crop the ability to qualify as an energy crop. There has been a growing trend in the global interest in renewable energy sources as a result of the ever growing concern for the environment. In order to meet the increasing demand for energy crops, there is the need to boost their productivity, especially through optimum agronomic management practices. Nitrogen fertilizer is an important nutrient in crop productivity which has widely been reported to affect the productivity of sweet sorghum. The required application rates have been found to vary across seasons and location, and are also affected by the factors of the climate, soil type and genotype. Studies have however shown that the nitrogen fertilizer rate in the range of 60 and 120 kg N ha -1 would result in optimum productivity depending on the location, the soil type and the native N of the soil determined through soil test.
Viral Replication and Innate Host Responses in Primary Human Alveolar Epithelial Cells and Alveolar Macrophages Infected with Influenza H5N1 and H1N1 Viruses

ABSTRACT Highly pathogenic influenza H5N1 virus continues to pose a threat to public health. Although the mechanisms underlying the pathogenesis of the H5N1 virus have not been fully defined, it has been suggested that cytokine dysregulation plays an important role. As the human respiratory epithelium is the primary target cell for influenza viruses, elucidating the viral tropism and innate immune responses of influenza H5N1 virus in the alveolar epithelium may help us to understand the pathogenesis of the severe pneumonia associated with H5N1 disease. Here we used primary cultures of differentiated human alveolar type II cells, alveolar type I-like cells, and alveolar macrophages isolated from the same individual to investigate viral replication competence and host innate immune responses to influenza H5N1 (A/HK/483/97) and H1N1 (A/HK/54/98) virus infection. The viral replication kinetics and cytokine and chemokine responses were compared by quantitative PCR (qPCR) and enzyme-linked immunosorbent assay (ELISA). We demonstrated that influenza H1N1 and H5N1 viruses replicated productively in type II cells and type I-like cells although with different kinetics. The H5N1 virus replicated productively in alveolar macrophages, whereas the H1N1 virus led to an abortive infection. The H5N1 virus was a more potent inducer of proinflammatory cytokines and chemokines than the H1N1 virus in all cell types. However, higher levels of cytokine expression were observed for peripheral blood monocyte-derived macrophages than for alveolar macrophages in response to H5N1 virus infection. Our findings provide important insights into the viral tropisms and host responses of different cell types found in the lung and are relevant to an understanding of the pathogenesis of severe human influenza disease.
Blockchain as a privacy enabler: an odometer fraud prevention system

Giving people ownership of the data they produce becomes more and more important in times of ever-growing capabilities to collect and analyze data of individuals. In light of this challenge, we show how blockchain technology can enable privacy by presenting an odometer fraud prevention system. It records mileage and GPS data of cars and secures that on the blockchain, which strongly hinders odometer fraud. Our users own and control their data while at the same time data integrity is ensured. This facilitates the certification of that data. We discuss the advantages of this approach compared to current systems and also highlight limitations of our architecture and the use of blockchain technology.