Miracle-dz/UniFAR-FTUs huggingface dataset:
Minor Criteria of Infectious Disease Society of America/American Thoracic Society for Severe Community-Acquired Pneumonia Can Predict Delayed Treatment Response

The purpose of this study was to investigate the clinical aspects of patients satisfying the Infectious Disease Society of America/American Thoracic Society (IDSA/ATS) minor severity criteria, focusing on their treatment response to empirical antibiotics. In total, 381 community-acquired pneumonia (CAP) patients who did not require mechanical ventilation or vasopressors at admission were enrolled, and 50 (13.1%) satisfied the minor severity criteria (i.e. , minor severe CAP [minor-SCAP]). The rates of new complication events and clinical treatment failure were significantly higher in the minor-SCAP group than in the control group (30.0% vs 2.1%, P < 0.001, and 42.0% vs 10.6%, P < 0.001, respectively), and the time to reach clinical stability was longer in the minor-SCAP group (8 days vs 3 days, P < 0.001). In a multivariate model, minor severity criteria (≥ 3) were significantly associated with treatment failure (odds ratio, 2.838; 95% confidence interval, 1.216 to 6.626), and for predicting treatment failure the value of the area under the receiver operating characteristic curve for minor criteria was 0.731, similar to other established scoring methods. The IDSA/ATS minor severity criteria can predict delayed treatment response and clinical treatment failure.
Quasi-ballistic carbon nanotube array transistors with current density exceeding Si and GaAs

Nearly ballistic carbon nanotube array transistors are realized with current densities outmatching conventional semiconductors. Carbon nanotubes (CNTs) are tantalizing candidates for semiconductor electronics because of their exceptional charge transport properties and one-dimensional electrostatics. Ballistic transport approaching the quantum conductance limit of 2G0 = 4e2/h has been achieved in field-effect transistors (FETs) containing one CNT. However, constraints in CNT sorting, processing, alignment, and contacts give rise to nonidealities when CNTs are implemented in densely packed parallel arrays such as those needed for technology, resulting in a conductance per CNT far from 2G0. The consequence has been that, whereas CNTs are ultimately expected to yield FETs that are more conductive than conventional semiconductors, CNTs, instead, have underperformed channel materials, such as Si, by sixfold or more. We report quasi-ballistic CNT array FETs at a density of 47 CNTs μm−1, fabricated through a combination of CNT purification, solution-based assembly, and CNT treatment. The conductance is as high as 0.46 G0 per CNT. In parallel, the conductance of the arrays reaches 1.7 mS μm−1, which is seven times higher than the previous state-of-the-art CNT array FETs made by other methods. The saturated on-state current density is as high as 900 μA μm−1 and is similar to or exceeds that of Si FETs when compared at and equivalent gate oxide thickness and at the same off-state current density. The on-state current density exceeds that of GaAs FETs as well. This breakthrough in CNT array performance is a critical advance toward the exploitation of CNTs in logic, high-speed communications, and other semiconductor electronics technologies.
Testing Core-Based Digital Systems : A Symbolic MethodologyF

One of the primary drawbacks of the core-based design paradigm is the limited knowledge of the internal structure and organization of the cores which is provided to the users. This problem is particularly critical from the point of view of testing, since it forces the designers to rely on the test patterns provided by the core vendors. As a solution that avoids the use of scan-based techniques, we present a test methodology which provides the following capabilities: Test generation for a system containing cores, and testability estimation and improvement of the system components. The methodology can be applied to designs consisting of an arbitrary interconnection of modules, some of which may be cores. Our approach relies on a fault model which allows the identiication of an accurate correspondence between functional and stuck-at sources of failure. In addition, a functional DfT technique reduces the design to a feedback-free interconnection eventually improving the testability of some modules. This provides an abstraction of the interconnection structure of the system, thus enabling its sim-pliication to a chain of three basic entities: The module under test, a controlling network, and an observing network. The whole methodology exploits the expressiveness of Binary Decision Diagrams for the storage and the manipulation of the system description. Some promising results, conducted on a reasonably complex core-based design, demonstrate the applicability of the proposed approach.
Collection-based sparse label propagation and its application on social group suggestion from photos

Online social network services pose great opportunities and challenges for many research areas. In multimedia content analysis, automatic social group recommendation for images holds the promise to expand one's social network through media sharing. However, most existing techniques cannot generate satisfactory social group suggestions when the images are classified independently. In this article, we present novel methods to produce accurate suggestions of suitable social groups from a user's personal photo collection. First, an automatic clustering process is designed to estimate the group similarities, select the optimal number of clusters and categorize the social groups. Both visual content and textual annotations are integrated to generate initial predictions of the group categories for the images. Next, the relationship among images in a user's collection is modeled as a sparse graph. A collection-based sparse label propagation method is proposed to improve the group suggestions. Furthermore, the sparse graph-based collection model can be readily exploited to select the most influential and informative samples for active relevance feedback, which can be integrated with the label propagation process without the need for classifier retraining. The proposed methods have been tested on group suggestion tasks for real user collections and demonstrated superior performance over the state-of-the-art techniques.
Inhibitors of Human Immunodeficiency Virus Type 1 Reverse Transcriptase Target Distinct Phases of Early Reverse Transcription

ABSTRACT Early HIV-1 reverse transcription can be separated into initiation and elongation phases. Here we show, using PCR analysis of negative-strand strong-stop DNA [(−)ssDNA] synthesis in intact virus, that different reverse transcriptase (RT) inhibitors affect distinct phases of early natural endogenous reverse transcription (NERT). The effects of nevirapine on NERT were consistent with a mechanism of action including both specific and nonspecific binding events. The nonspecific component of this inhibition targeted the elongation reaction, whereas the specific effect seemed principally to be directed at very early events (initiation or the initiation-elongation switch). In contrast, foscarnet and the nucleoside analog ddATP inhibited both early and late (−)ssDNA synthesis in a similar manner. We also examined compounds that targeted other viral proteins and found that Ro24-7429 (a Tat antagonist) and rosmarinic acid (an integrase inhibitor) also directly inhibited RT. Our results indicate that NERT can be used to identify and evaluate compounds that directly target the reverse transcription complex.
Predicative fragments of Frege Arithmetic

Frege Arithmetic (FA) is the second-order theory whose sole non-logical axiom is Hume’s Principle, which says that the number of F s is identical to the number of Gs if and only if the F s and the Gs can be one-to-one correlated. According to Frege’s Theorem, FA and some natural definitions imply all of second-order Peano Arithmetic. This paper distinguishes two dimensions of impredicativity involved in FA—one having to do with Hume’s Principle, the other, with the underlying second-order logic—and investigates how much of Frege’s Theorem goes through in various partially predicative fragments of FA. Theorem 1 shows that almost everything goes through, the most important exception being the axiom that every natural number has a successor. Theorem 2 shows that the Successor Axiom cannot be proved in the theories that are predicative in either dimension.
Utility maximization in incomplete markets with default

We adress the maximization problem of expected utility from terminal wealth. The special feature of this paper is that we consider a financial market where the price process of risky assets can have a default time. Using dynamic programming, we characterize the value function with a backward stochastic differential equation and the optimal portfolio policies. We separately treat the cases of exponential, power and logarithmic utility.
Vivo Replication In Vitro and Neuroinvasion In Pseudorabies Virus Impairs Viral in Large Tegument Protein pUL 36 of the Ubiquitin-Specific Protease Contained Mutagenesis of the Active-Site Cysteine in

Published Ahead of Print 9 April 2008. 2008, 82(12):6009. DOI: 10.1128/JVI.00280-08. J. Virol. Mettenleiter Barbara G. Klupp, Jens P. Teifke and Thomas C. Sindy Böttcher, Christina Maresch, Harald Granzow, Vivo Replication In Vitro and Neuroinvasion In Pseudorabies Virus Impairs Viral in Large Tegument Protein pUL36 of the Ubiquitin-Specific Protease Contained Mutagenesis of the Active-Site Cysteine in
WASAR imaging based on message passing with structured sparse constraint: Approach and experiment

We presents a wide angle synthetic aperture radar (WASAR) imaging method based on the message passing with structured sparsity constraint. The motivation of this paper aims to improve the imaging performance and to explore the potential ofWASAR with the angle dependent scattering behavior of target. Intuitively, it can be inferred from studies of scattering persistence that the angle dependent scattering behavior possess underlying structure. We impose a generalized structure constraint on WASAR imaging problem and present a message passing based method. The proposed method exhibits good balance of accuracy and efficient in retrieving the scattering map on different viewing angle. The results of experiment demonstrate the effectiveness.
Aligning Coupled Manifolds for Face Hallucination

Many learning-based super-resolution methods are based on the manifold assumption, which claims that point-pairs from the low-resolution representation manifold (LRM) and the corresponding high-resolution representation manifold (HRM) possess similar local geometry. However, the manifold assumption does not hold well on the original coupled manifolds (i.e., LRM and HRM) due to the nonisometric one-to-multiple mappings from low-resolution (LR) image patches to high-resolution (HR) ones. To overcome this limitation, we propose a solution from the perspective of manifold alignment. In this context, we perform alignment by learning two explicit mappings which project the point-pairs from the original coupled manifolds into the embeddings of the common manifold (CM). For the task of SR reconstruction, we treat HRM as target manifold and employ the manifold regularization to guarantee that the local geometry of CM is more consistent with that of HRM than LRM is. After alignment, we carry out the SR reconstruction based on neighbor embedding between the new couple of the CM and the target HRM. Besides, we extend our method by aligning the multiple coupled subsets instead of the whole coupled manifolds to address the issue of the global nonlinearity. Experimental results on face image super-resolution verify the effectiveness of our method.
Classification of Daily Life Activities by Decision Level Fusion of Inertial Sensor Data

The fusion of inertial sensor data is heavily used for the classification of daily life activities. The knowledge about the performed daily life activities is mandatory to give physically inactive people feedback about their individual quality of life. In this paper, four inertial sensors were placed on wrist, chest, hip and ankle of 19 subjects, which had to perform seven daily life activities. Each sensor node separately performed preprocessing, feature extraction and classification. In the final step, the classifier decisions of the sensor nodes were fused and a single activity was predicted by majority voting. The proposed classification system obtained an overall mean classification rate of 93.9 % and was robust against defect sensors. The system allows an easy integration of new sensors without retraining of the complete system, which is an advantage over commonly used feature level fusion approaches.
Planar Millimeter-Wave Antennas: A Comparative Study

The paper describes the design and the experimental verification of three types of wideband antennas. Attention is turned to the bow-tie antenna, the Vivaldi antenna and the spiral antenna designed for the operation at millimeter waves. Bandwidth, input impedance, gain, and directivity pattern are the investigated parameters. Antennas are compared considering computer simulations in CST Microwave Studio and measured data.
Dissecting packet loss in mobile broadband networks from the edge

This paper demonstrates that end-to-end active measurements can give invaluable insights into the nature and characteristics of packet loss in cellular networks. We conduct a large-scale measurement study of packet loss in four UMTS networks. The study is based on active measurements from hundreds of measurement nodes over a period of one year. We find that a significant fraction of loss occurs during pathological and normal Radio Resource Control (RRC) state transitions. The remaining loss exhibits pronounced diurnal patterns and shows a relatively strong correlation between geographically diverse measurement nodes. Our results indicate that the causes of a significant part of the remaining loss lie beyond the radio access network.
Philosophy of Language in the Twentieth Century

In the Twentieth Century, Logic and Philosophy of Language are two of the few areas of philosophy in which philosophers made indisputable progress. For example, even now many of the foremost living ethicists present their theories as somewhat more explicit versions of the ideas of Kant, Mill, or Aristotle. In contrast, it would be patently absurd for a contemporary philosopher of language or logician to think of herself as working in the shadow of any figure who died before the Twentieth Century began. Advances in these disciplines make even the most unaccomplished of its practitioners vastly more sophisticated than Kant. There were previous periods in which the problems of language and logic were studied extensively (e.g. the medieval period). But from the perspective of the progress made in the last 120 years, previous work is at most a source of interesting data or occasional insight. All systematic theorizing about content that meets contemporary standards of rigor has been done subsequently. The advances Philosophy of Language has made in the Twentieth Century are of course the result of the remarkable progress made in logic. Few other philosophical disciplines gained as much from the developments in logic as the Philosophy of Language. In the course of presenting the first formal system in the Begriffsscrift, Gottlob Frege developed a formal language. Subsequently, logicians provided rigorous semantics for formal languages, in order to define truth in a model, and thereby characterize logical consequence. Such rigor was required in order to enable logicians to carry out semantic proofs about formal systems in a formal system, thereby providing semantics with the same benefits as increased formalization had provided for other branches of mathematics. It was but a short step to treating natural languages as more complex versions of formal languages, and then applying to the study of natural language the techniques developed by logicians interested in proving semantic results about formal theories. Increased formalization has yielded dividends in the Philosophy of Language similar to those in mathematics. It has enabled philosophers to provide better and more fruitful definitions and distinctions. Progress in Philosophy of Language and logic has positively affected neighboring disciplines such as metaphysics and meta-ethics. Because of this, some philosophers have thought that Philosophy of Language was some kind of " first philosophy " , as Descartes viewed what we would now call " epistemology ". But the fact that Philosophy of Language has …
Beowulf-Class Computer System at MSU-IIT

Beowulf class computer system is a type of parallel or distributed system, which consists of interconnected commodity-of-the shelf (COTS) personal computers working together as a single integrated computing resource [2,3]. A certain computational task could be divided among the computers that can result to faster execution of the task [2,11]. At MSU-IIT, we built a four-node Beowulf system. The MSU-IIT Beowulf system has been utilized in the study of molecular structures, using GAMESS [5] and GROMACS [6], and parallel computing education. An ongoing research is done to use CERNLIB, ROOT [12], JSF [7] and LCLIB [8] in the cluster environment. These software are used for high energy physics simulations for the Joint Linear Collider (JLC).
EndoS and SpeB from Streptococcus pyogenes Inhibit Immunoglobulin-Mediated Opsonophagocytosis

ABSTRACT The human pathogen Streptococcus pyogenes primarily infects the upper respiratory tract and skin, but occasionally it disseminates and causes severe invasive disease with high mortality. This study revealed that the activity of extracellular EndoS, which hydrolyzes the functionally important N-linked oligosaccharides on opsonizing immunoglobulin G (IgG), contributes to increased survival of S. pyogenes in human blood ex vivo. The inability to kill the bacteria is due to reduced binding of IgG to Fc receptors and impaired classical pathway-mediated activation of complement. In addition, the activity of extracellular SpeB, which cleaves IgG into Fc and Fab fragments, also increases bacterial survival. This suggests that S. pyogenes expresses two enzymes, EndoS and SpeB, which modulate IgG by different mechanisms in order to evade the adaptive immune system.
Pôles de compétitivité, transferts de connaissances et dynamiques territoriales : une analyse du pôle Systematic Paris-Région

Les poles de competitivite, labellises en 2005 par le gouvernement francais, ont pour vocation de soutenirdes projets collaboratifs de Recherche et Developpement (R&D). Ils ont pour originalite de conduire demultiples organisations (entreprises, universites, laboratoires de recherche, etc.) proches geographiquementa cooperer afin de faire emerger des innovations. La proximite geographique est-elle pour autant unecondition necessaire a la bonne coordination des activites d'innovation dans les poles de competitivite ? Cette these se propose d'approfondir la comprehension des dynamiques collaboratives dans les projets deR&D, en particulier en placant la focale sur les formes non-spatiales des proximites (institutionnelle,organisationnelle, cognitive et sociale). Notre terrain d'enquete est le pole de competitivite Systematic Paris-Region sur la periode 2005-2015. Nous proposons d'analyser les dynamiques territoriales du pole, a partirde l'etude de l'evolution spatiale des cooperations, ainsi que de l'evolution du positionnement desorganisations dans les reseaux collaboratifs de R&D. Ces etudes representent la construction et l'analyse deplus de quatre millions de donnees. Elles mobilisent les concepts et methodes de la theorie des reseaux,ainsi que de l'analyse en composantes principales (ACP). Aussi, la realisation de 57 entretiens aupres deresponsables scientifiques et techniques, ainsi que de 3 entretiens aupres de membres salaries du pole decompetitivite, nous permet d'eclaircir les dynamiques de proximite a l'oeuvre dans les projets collaboratifs dupole Systematic Paris-Region.
Polarized electrons from high-gradient guns

To take advantage of the lower emittance associated with extraction fields >> 10 MV/m, a number of technological hurdles must be overcome before photocathodes appropriate for generating polarized electrons can be utilized in high-gradient guns. Both rf guns and very fast ultra-high gradient ({ge} 1 GV/m) diode guns are anticipated. The known problems--some of which may be more than just technical--are delineated, and the present status of relevant research is reviewed.
Comparative Analysis of 4-bit Multipliers Using Low Power Adder Cells

Multiplier is the most commonly used circuit in the digital devices. Multiplication is one of the basic functions used in digital signal processing. Most high performance DSP systems rely on hardware multiplication to achieve high data throughput. There are various types of multipliers available depending upon the application in which they are used. Full Adder is the main block of power dissipation in multiplier. So reducing the power dissipation of full adder ultimately reduces the power dissipation of multiplier. In this paper 4-bit multipliers based on Gate Diffusion Input (GDI) adder cells are compared using EDA Tanner (Evaluation version), simulations are based on 180nm CMOS technology.
A Wireless Mobile Robots Deployment Approach for Maximising the Coverage of Important Locations in Disaster Rescues

This paper addresses the wireless mobile robot deployment problem in disaster rescues, which aims to maximise the coverage of important locations of an ad hoc network through deploying wireless mobile robots of the network at suitable locations. Nowadays, most of current approaches deploy wireless mobile robots to cover important locations in disaster environments based on greedy algorithms. Due to the myopia of greedy algorithms, these approaches can only maximise the coverage of important locations of each wireless mobile robot rather than all of them in an ad hoc network. To this end, two mathematical programming-based wireless mobile robot deployment approaches are proposed in this paper. The proposed approaches can create the optimal deployment locations for all wireless mobile robots in an ad hoc network. The experimental results demonstrate that wireless mobile robots in the proposed approaches can cover more important locations than that of in greedy algorithm-based approaches in most disaster environments.
Metric Learning Driven Multi-Task Structured Output Optimization for Robust Keypoint Tracking

As an important and challenging problem in computer vision and graphics, keypoint-based object tracking is typically formulated in a spatio-temporal statistical learning framework. However, most existing keypoint trackers are incapable of effectively modeling and balancing the following three aspects in a simultaneous manner: temporal model coherence across frames, spatial model consistency within frames, and discriminative feature construction. To address this issue, we propose a robust keypoint tracker based on spatio-temporal multi-task structured output optimization driven by discriminative metric learning. Consequently, temporal model coherence is characterized by multi-task structured keypoint model learning over several adjacent frames, while spatial model consistency is modeled by solving a geometric verification based structured learning problem. Discriminative feature construction is enabled by metric learning to ensure the intra-class compactness and inter-class separability. Finally, the above three modules are simultaneously optimized in a joint learning scheme. Experimental results have demonstrated the effectiveness of our tracker.