Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of intra-aortic balloon counterpulsation in a model of septic shock*

Background:Fluid refractory septic shock can develop into a hypodynamic cardiovascular state in both children and adults. Despite management of these patients with empirical inotropic therapy (with or without a vasodilator), mortality remains high. Objectives:The effect of cardiovascular support using intra-aortic balloon counterpulsation was investigated in a hypodynamic, mechanically ventilated canine sepsis model in which cardiovascular and pulmonary support were titrated based on treatment protocols. Methods:Each week, three animals (n = 33, 10–12 kg) were administered intrabronchial Staphylococcus aureus challenge and then randomized to receive intra-aortic balloon counterpulsation for 68 hrs or no intra-aortic balloon counterpulsation (control). Bacterial doses were increased over the study (4–8 × 109 cfu/kg) to assess the effects of intra-aortic balloon counterpulsation during sepsis with increasing risk of death. Main Results:Compared with lower bacterial doses (4–7 × 109 colony-forming units/kg), control animals challenged with the highest dose (8 × 109 colony-forming units/kg) had a greater risk of death (mortality rate 86% vs. 17%), with worse lung injury ([A − a]o2), and renal dysfunction (creatinine). These sicker animals required higher norepinephrine infusion rates to maintain blood pressure (and higher Fio2) and positive end-expiratory pressure levels to maintain oxygenation (p ≤ 0.04 for all). In animals receiving the highest bacterial dose, intra-aortic balloon counterpulsation improved survival time (23.4 ± 10 hrs longer; p = 0.003) and lowered norepinephrine requirements (0.43 ± 0.17 &mgr;g/kg/min; p = 0.002) and systemic vascular resistance index (1.44 ± 0.57 dynes/s/cm5/kg; p = 0.0001) compared with controls. Despite these beneficial effects, intra-aortic balloon counterpulsation was associated with an increase in blood urea nitrogen (p = 0.002) and creatinine (p = 0.12). In animals receiving lower doses of bacteria, intra-aortic balloon counterpulsation had no significant effects on survival or renal function. Conclusions:In a canine model of severe septic shock with a low cardiac index, intra-aortic balloon counterpulsation prolongs survival time and lowers vasopressor requirements.
Portable biomedical devices: a critical issue during telecare services design

Objectives. The selection of a portable biomedical device (PBD) is a key issue regarding telecare service design. The objective of this study is to investigate the accuracy parameters of a PBD under different settings and levels. Methods and materials. By using a commercial PBD, trials were performed in a referral cardiology center and on the Olympia Explorer of the Royal Olympia Cruises, and the Superfast XII of Superfast Ferries. Data were collected (February 2004 – June 2006) by performing: (1) ‘in hospital’ standalone trials; (2) ‘in hospital’ comparative trials; and (3) ‘on board’ trials. Semistructured interviews were also conducted with several subjects, their cardiologists and crewmembers. Results. We investigated the accuracy parameters, namely the data precision (DP), the peripheral modules reliability (PMR) and the data transmission quality (DTQ). Although the outcomes of the comparative trials, via a statistical method verifying the DP (more than 95%), the trials ‘on board’ and ‘in hospital’ revealed a number of critical variables for the PMR and DTQ parameters. Conclusion. Telecare services design has accuracy parameter investigation needs. These parameters should be investigated simultaneously, while a compromise between them can act as a driving force to the telecare services success. The compromise is achieved by a smooth fit between DP and PMR with this fit varying within settings and levels.
A Multifunctional Protease Inhibitor To Regulate Endolysosomal Function

Proteases constitute a major class of drug targets. Endosomal compartments harbor several protease families whose attenuation may be beneficial to a number of biological processes, including inflammation, cancer metastasis, antigen presentation, and parasite clearance. As a step toward the goal of generalized but targeted protease inhibition in the endocytic pathway, we describe here the synthesis, characterization, and cellular application of a novel multifunctional protease inhibitor. We show that pepstatin A, a potent but virtually insoluble inhibitor of cathepsins D and E, can be conjugated to a single site on cystatin C, a potent inhibitor of the papain-like cysteine proteases (PLCP) and of asparagine endopeptidease (AEP), to create a highly soluble compound capable of suppressing the activity of all 3 principal protease families found in endosomes and lysosomes. We demonstrate that this cystatin–pepstatin inhibitor (CPI) can be taken up by cells to modulate protease activity and affect biological responses.
Fast Keypoint Recognition Using Random Ferns

While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. In this paper, we show that formulating the problem in a naive Bayesian classification framework makes such preprocessing unnecessary and produces an algorithm that is simple, efficient, and robust. Furthermore, it scales well as the number of classes grows. To recognize the patches surrounding keypoints, our classifier uses hundreds of simple binary features and models class posterior probabilities. We make the problem computationally tractable by assuming independence between arbitrary sets of features. Even though this is not strictly true, we demonstrate that our classifier nevertheless performs remarkably well on image data sets containing very significant perspective changes.
A visual exploration algorithm using semantic cues that constructs image based hybrid maps

A vision based exploration algorithm that invokes semantic cues for constructing a hybrid map of images - a combination of semantic and topological maps is presented in this paper. At the top level the map is a graph of semantic constructs. Each node in the graph is a semantic construct or label such as a room or a corridor, the edge represented by a transition region such as a doorway that links the two semantic constructs. Each semantic node embeds within it a topological graph that constitutes the map at the middle level. The topological graph is a set of nodes, each node representing an image of the higher semantic construct. At the low level the topological graph embeds metric values and relations, where each node embeds the pose of the robot from which the image was taken and any two nodes in the graph are related by a transformation consisting of a rotation and translation. The exploration algorithm explores a semantic construct completely before moving or branching onto a new construct. Within each semantic construct it uses a local feature based exploration algorithm that uses a combination of local and global decisions to decide the next best place to move. During the process of exploring a semantic construct it identifies transition regions that serve as gateways to move from that construct to another. The exploration is deemed complete when all transition regions are marked visited. Loop detection happens at transition regions and graph relaxation techniques are used to close loops when detected to obtain a consistent metric embedding of the robot poses. Semantic constructs are labeled using a visual bag of words(VBOW) representation with a probabilistic SVM classifier.
Le contrôle budgétaire: recherche d'efficience ou recherche de légitimité ?

A partir de reponses collectees aupres de 246 controleurs de gestion ou directeurs administratifs ou financiers, cette recherche a pour objectif de preciser les raisons pour lesquelles les entreprises font du controle budgetaire. Deux cadres explicatifs sont mobilises : le cadre contingent et le cadre neo-institutionnel. Le cadre contingent propose d'expliquer l'adoption du controle budgetaire par une recherche de l'efficience. En effet, le controle budgetaire permet la « decentralisation par le controle », la direction par objectifs et la gestion par exception et constitue a ce titre un outil utile dans certains « environnement techniques ». Cinq variables sont utilisees pour qualifier l'« environnement technique » de l'organisation : l'incertitude de l'environnement, la complexite de la technologie, la decentralisation de l'organisation, le type de strategie et la taille. Pour les neo-institutionnels, le controle budgetaire n'a pas uniquement pour but d'ameliorer l'efficience de l'organisation. Il permet egalement de donner l'illusion de la rationalite aux acteurs internes et externes et de legitimer l'action de l'organisation. Il repond donc aux attentes de l'environnement institutionnel et social dans lequel se situe l'organisation. Cet environnement institutionnel est caracterise par l'appartenance a un groupe et les types de relations avec le groupe, le type d'actionnariat et l'orientation professionnelle du dirigeant. Les regressions lineaires multiples realisees montrent que le cadre neo-institutionnel a un pouvoir explicatif de la mise en place du controle budgetaire plus fort que le cadre contingent. Ceci permet de souligner le role de legitimation du controle budgetaire vis-a-vis des parties prenantes et d'envisager ce dispositif comme un mythe rationnel, c'est-a-dire comme une structure institutionnalisee qui donne l'illusion de la rationalite.
The Detection of Deception in Forensic Contexts: Reality monitoring and detection of deception

Research on eyewitness testimony has primarily focused on memory errors. In this chapter, the focus is not on eye-witness errors but on the application of Johnson and Raye's (1981) reality monitoring (RM) model to detection of deception. The central question is whether or not it is possible to discriminate truthful from deceptive statements on the basis of content aspects outlined by the RM theory. This approach is akin to Statement Validity Analysis, in particular the Criteria-Based Content Analysis (CBCA) component, which also has focused on qualitative differences between truthful and deceptive accounts (for reviews, see Ruby and Brigham, 1997; Sporer, 1983, 1997a, 1997b; Steller and Kohnken, 1989; Vrij, 2000, in press). Reality monitoring approach In a seminal paper, Johnson and Raye (1981) asked how people go about discriminating memories of externally derived (perceptual) experiences from memories of internally derived experiences. This process has been termed reality monitoring (RM). In a deception situation, a communicator constructs an event either from scratch or on the basis of similar experiences, thus reporting on a new current event, not a memory of a past event. According to RM theory, people rely on qualitative characteristics of memories to decide whether a memory is based on an actual experience or not. It is assumed that externally derived memories contain more references to sensory information (visual details, colours, sounds, odours, touch, taste), contextual information (about space and time), emotions and feelings, and semantic information.
A semantic-aware information system for multi-domain applications over service grids

Service-oriented Grid frameworks offer resources and facilities to support the design and execution of distributed applications in different domains, ranging from scientific applications and public computing projects to commercial and industrial applications. A critical issue in such a context is the management of the heterogeneity of resources and services offered by a Grid, including computers, data, and software tools provided by different organizations. This paper presents a general architecture of a service-oriented information system, which exploits the characteristics of a multi-domain and semantically enriched metadata model. The main objective of the information system is to uniformly manage service-oriented applications and basic resources by assuring metadata persistence through an XML distributed database, without merely relying on the functionalities of persistent Grid services. The information system has been implemented on the basic services of the WSRF-based Globus Toolkit 4 and its performance has been evaluated in a testbed.
Making context-sensitive points-to analysis with heap cloning practical for the real world

Context-sensitive pointer analysis algorithms with full "heapcloning" are powerful but are widely considered to be too expensive to include in production compilers. This paper shows, for the first time, that a context-sensitive, field-sensitive algorithm with fullheap cloning (by acyclic call paths) can indeed be both scalable and extremely fast in practice. Overall, the algorithm is able to analyze programs in the range of 100K-200K lines of C code in 1-3 seconds,takes less than 5% of the time it takes for GCC to compile the code (which includes no whole-program analysis), and scales well across five orders of magnitude of code size. It is also able to analyze the Linux kernel (about 355K linesof code) in 3.1 seconds. The paper describes the major algorithmic and engineering design choices that are required to achieve these results, including (a) using flow-insensitive and unification-basedanalysis, which are essential to avoid exponential behavior in practice;(b) sacrificing context-sensitivity within strongly connected components of the call graph; and (c) carefully eliminating several kinds of O(N2) behaviors (largely without affecting precision). The techniques used for (b) and (c) eliminated several major bottlenecks to scalability, and both are generalizable to other context-sensitive algorithms. We show that the engineering choices collectively reduce analysis time by factors of up to 10x-15xin our larger programs, and have found that the savings grow strongly with program size. Finally, we briefly summarize results demonstrating the precision of the analysis.
Shares, Pins, and Tweets

This paper compares the volume of news articles per section in newspapers and social media platforms. To this end, two weeks of news articles were retrieved by querying the public Application Programming Interfaces (APIs) of The New York Times and The Guardian and the diffusion of each article on social media platforms Twitter, Facebook, Google+, Delicious, Pinterest, and StumbleUpon, was tracked. The results show significant differences in the topics emphasized by newspaper editors and social media users. While users of social media platforms favor opinion pieces, along with national, local, and world news, in sharp contrast the decision of news editors emphasized sports and the economy, but also entertainment and celebrity news. Common to social networking sites is the prevalence of items about arts, technology, and opinion pieces. Niche social networks like StumbleUpon and Delicious presented a greater volume of articles about science and technology, while Pinterest is mostly dedicated to fashion, arts, lifestyle, and entertainment. Twitter is the only social network to have presented a statistically significant correlation with the distribution of news items per section by The Guardian and The New York Times. The results of this study provide a bridge between journalism and audience research and present evidence of the differences between readership in social and legacy media.
Development of an e-Learning Recommender System Using Discrete Choice Models and Bayesian Theory: A Pilot Case in the Shipping Industry

The field of e-learning and self-learning has rapidly evolved during the past decade mainly because of major advances in telecommunications and information technologies, in particular the widespread use of web and mobile applications. Furthermore, the work environment conditions in most industries have become extremely demanding and competitive; therefore various forms of life-long learning appear to play an important role for employees’ career development, as well as for companies’ productivity improvement and human resources’ efficiency. The flexibility, and cost effectiveness that e-learning offers is very significant, in most cases.
Ambivalence and cognitive heuristics for dealing with ambiguity in complex social worlds

Abstract Based on our approach to complex dynamic systems, ambiguity of heuristics is a necessary tool to deal with objective ambiguity and complexity of the real world. I discuss various aspects of ambivalence of heuristics aimed to (a) decrease and (b) increase uncertainty in complex social worlds. Different kinds of asymmetry, paradoxes and contradictions in the creation and use of heuristics for diagnosis, prognosis, and control in social worlds are considered in such socially meaningful areas as stimulation and inhibition of others' development, translation of knowledge and masteries vs. keeping secrecy and ignorance, evaluation of humans' potential to create novelty, etc. Ambiguity of developmental paths related to objective uncertainty of real world, and to ambiguity of the heuristics used in main human activities is discussed.
Conditional poliovirus mutants made by random deletion mutagenesis of infectious cDNA

Small deletions were introduced into DNA plasmids bearing cDNA copies of Mahoney type 1 poliovirus RNA. The procedure used was similar to that of P. Hearing and T. Shenk (J. Mol. Biol. 167:809-822, 1983), with modifications designed to introduce only one lesion randomly into each DNA molecule. Methods to map small deletions in either large DNA or RNA molecules were employed. Two poliovirus mutants, VP1-101 and VP1-102, were selected from mutagenized populations on the basis of their host range phenotype, showing a large reduction in the relative numbers of plaques on CV1 and HeLa cells compared with wild-type virus. The deletions borne by the mutant genomes were mapped to the region encoding the amino terminus of VP1. That these lesions were responsible for the mutant phenotypes was substantiated by reintroduction of the sequenced lesions into a wild-type poliovirus cDNA by deoxyoligonucleotide-directed mutagenesis. The deletion of nucleotides encoding amino acids 8 and 9 of VP1 was responsible for the VP1-101 phenotype; the VP1-102 defect was caused by the deletion of the sequences encoding the first four amino acids of VP1. The peptide sequence at the VP1-VP3 proteolytic cleavage site was altered from glutamine-glycine to glutamine-methionine in VP1-102; this apparently did not alter the proteolytic cleavage pattern. The biochemical defects resulting from these mutations are discussed in the accompanying report.
Influence Activation Model: A New Perspective in Social Influence Analysis and Social Network Evolution

What drives the propensity for the social network dynamics? Social influence is believed to drive both off-line and on-line human behavior, however it has not been considered as a driver of social network evolution. Our analysis suggest that, while the network structure affects the spread of influence in social networks, the network is in turn shaped by social influence activity (i.e., the process of social influence wherein one person's attitudes and behaviors affect another's). To that end, we develop a novel model of network evolution where the dynamics of network follow the mechanism of influence propagation, which are not captured by the existing network evolution models. Our experiments confirm the predictions of our model and demonstrate the important role that social influence can play in the process of network evolution. As well exploring the reason of social network evolution, different genres of social influence have been spotted having different effects on the network dynamics. These findings and methods are essential to both our understanding of the mechanisms that drive network evolution and our knowledge of the role of social influence in shaping the network structure.
American Individualisms: Child Rearing and Social Class in Three Neighborhoods

Introduction* Ethnographic Method& Context * American Individualism& Social Class Revisited * Queens Ethnoconceptions of the Child's Self * Queenston Hard Protective Individualism vs. Kelley Hard Projective Individualism * Individualism& Ethnoconceptions of the Child's Self in Parkside * Queenston& Kelley Preschools * Parkside Preschools * Balancing Psychologized Individualism with Societal Constraints& Uncovering the True Self
Based on Multi-features and Clustering Ensemble Method for Automatic Malware Categorization

Automatic malware categorization plays an important role in combating the current large volume of malware and aiding the corresponding forensics. Generally, there are lot of sample information could be extracted with the static tools and dynamic sandbox for malware analysis. Combine these obtained features effectively for further analysis would provides us a better understanding. On the other hand, most current works on malware analysis are based on single category of machine learning algorithm to categorize samples. However, different clustering algorithms have their own strengths and weaknesses. And then, how to combine the merits of the multiple categories of features and algorithms to further improve the analysis result is very critical. In this paper, we propose a novel scalable malware analysis framework to exploit the complementary nature of different features and algorithms to optimally integrate their results. By using the concept of clustering ensemble, our system combines partitions from individual category of feature and algorithm to obtain better quality and robustness. Our system composed of the following three parts: (1) extract multiple categories of static and dynamic features; (2) use the k-means and hierarchical clustering algorithms to construct the base clustering; (3) proposed an efficient method based on mixture model clustering ensemble to conduct an effective clustering analysis. We have evaluated our method on two malware datasets, namely the Microsoft malware dataset and our own malware dataset which contained 10868 and 53760 samples respectively. Our experiment results show that our method could categorize malware with better quality and robustness. Also, our method has certain advantages in the system run time and memory consumption compared with the state-of-the art malware analysis works
A Well-Connected and Conserved Nucleoplasmic Helicase Is Required for Production of Box C/D and H/ACA snoRNAs and Localization of snoRNP Proteins

ABSTRACT Biogenesis of small nucleolar RNA-protein complexes (snoRNPs) consists of synthesis of the snoRNA and protein components, snoRNP assembly, and localization to the nucleolus. Recently, two nucleoplasmic proteins from mice were observed to bind to a model box C/D snoRNA in vitro, suggesting that they function at an early stage in snoRNP biogenesis. Both proteins have been described in other contexts. The proteins, called p50 and p55 in the snoRNA binding study, are highly conserved and related to each other. Both have Walker A and B motifs characteristic of ATP- and GTP-binding and nucleoside triphosphate-hydrolyzing domains, and the mammalian orthologs have DNA helicase activity in vitro. Here, we report that theSaccharomyces cerevisiae ortholog of p50 (Rvb2, Tih2p, and other names) is required for production of C/D snoRNAs in vivo and, surprisingly, H/ACA snoRNAs as well. Point mutations in the Walker A and B motifs cause temperature-sensitive or lethal growth phenotypes and severe defects in snoRNA accumulation. Notably, depletion of p50 (called Rvb2 in this study) also impairs localization of C/D and H/ACA core snoRNP proteins Nop1p and Gar1p, suggesting a defect(s) in snoRNP assembly or trafficking to the nucleolus. Findings from other studies link Rvb2 orthologs with chromatin remodeling and transcription. Taken together, the present results indicate that Rvb2 is involved in an early stage of snoRNP biogenesis and may play a role in coupling snoRNA synthesis with snoRNP assembly and localization.