Miracle-dz/UniFAR-FTUs huggingface dataset:
Crystal Structure of Thrombin in a Self-inhibited Conformation*

The activating effect of Na+ on thrombin is allosteric and depends on the conformational transition from a low activity Na+-free (slow) form to a high activity Na+-bound (fast) form. The structures of these active forms have been solved. Recent structures of thrombin obtained in the absence of Na+ have also documented inactive conformations that presumably exist in equilibrium with the active slow form. The validity of these inactive slow form structures, however, is called into question by the presence of packing interactions involving the Na+ site and the active site regions. Here, we report a 1.87Å resolution structure of thrombin in the absence of inhibitors and salts with a single molecule in the asymmetric unit and devoid of significant packing interactions in regions involved in the allosteric slow → fast transition. The structure shows an unprecedented self-inhibited conformation where Trp-215 and Arg-221a relocate >10Å to occlude the active site and the primary specificity pocket, and the guanidinium group of Arg-187 penetrates the protein core to fill the empty Na+-binding site. The extreme mobility of Trp-215 was investigated further with the W215P mutation. Remarkably, the mutation significantly compromises cleavage of the anticoagulant protein C but has no effect on the hydrolysis of fibrinogen and PAR1. These findings demonstrate that thrombin may assume an inactive conformation in the absence of Na+ and that its procoagulant and anticoagulant activities are closely linked to the mobility of residue 215.
Cost effectiveness of an outpatient multidisciplinary pulmonary rehabilitation programme

BACKGROUND Pulmonary rehabilitation programmes improve the health of patients disabled by lung disease but their cost effectiveness is unproved. We undertook a cost/utility analysis in conjunction with a randomised controlled clinical trial of pulmonary rehabilitation versus standard care. METHODS Two hundred patients, mainly with chronic obstructive pulmonary disease, were randomly assigned to either an 18 visit, 6 week rehabilitation programme or standard medical management. The difference between the mean cost of 12 months of care for patients in the rehabilitation and control groups (incremental cost) and the difference between the two groups in quality adjusted life years (QALYs) gained (incremental utility) were determined. The ratio between incremental cost and utility (incremental cost/utility ratio) was calculated. RESULTS Each rehabilitation programme for up to 20 patients cost £12 120. The mean incremental cost of adding rehabilitation to standard care was £ –152 (95% CI –881 to 577) per patient, p=NS. The incremental utility of adding rehabilitation was 0.030 (95% CI 0.002 to 0.058) QALYs per patient, p=0.03. The point estimate of the incremental cost/utility ratio was therefore negative. The bootstrapping technique was used to model the distribution of cost/utility estimates possible from the data. A high likelihood of generating QALYs at negative or relatively low cost was indicated. The probability of the cost per QALY generated being below £0 was 0.64. CONCLUSIONS This outpatient pulmonary rehabilitation programme produces cost per QALY ratios within bounds considered to be cost effective and is likely to result in financial benefits to the health service.
Pull-based Real-Time Complex Event Detection in Multiple Data Streams - the PAN Approach

With the proliferation of embedded sensors, the number of data streams and the volume of streamed data has increased enormously. This has strongly influenced both our business and our private life and has brought forward a large variety of monitoring applications in different domains. In all these applications the analysis of data streams in real-time is essential. One of the main challenges in data stream analysis is the detection of complex events out of the raw streaming data. In this report, we present PAN, a generic middleware for distributed real-time complex event detection (CED) which is able to analyze multiple distributed data streams. In PAN, CED applications are defined as workflows and are executed by dedicated workers in a distributed way in a P2P network. These workers use pull-based publish/subscribe for communication. This allows to dynamically extend analysis workflows at run-time and to balance the load between workers. As a consequence, it makes PAN scalable not only in terms of the number of data streams as well as the number and the complexity of the analyses but also in terms of the number of clients that retrieve the analysis results. Evaluations based on an extended version of the ACM DEBS 2013 Grand Challenge scenario show the effectiveness and efficiency of PAN. This technical report is an extended version of our previous work [19] that has been published by Springer International Publishing in the Proceedings of the 16th IFIP WG 6.1 International Conference on Distributed Applications and Interoperable Systems (DAIS 2016). It add details on the inner workings of PAN, especially on the pull-based publish/subsribe interaction between workers.
Sequential selection of correlated ads by POMDPs

Online advertising has become a key source of revenue for both web search engines and online publishers. For them, the ability of allocating right ads to right webpages is critical because any mismatched ads would not only harm web users' satisfactions but also lower the ad income. In this paper, we study how online publishers could optimally select ads to maximize their ad incomes over time. The conventional offline, content-based matching between webpages and ads is a fine start but cannot solve the problem completely because good matching does not necessarily lead to good payoff. Moreover, with the limited display impressions, we need to balance the need of selecting ads to learn true ad payoffs (exploration) with that of allocating ads to generate high immediate payoffs based on the current belief (exploitation). In this paper, we address the problem by employing Partially observable Markov decision processes (POMDPs) and discuss how to utilize the correlation of ads to improve the efficiency of the exploration and increase ad incomes in a long run. Our mathematical derivation shows that the belief states of correlated ads can be naturally updated using a formula similar to collaborative filtering. To test our model, a real world ad dataset from a major search engine is collected and categorized. Experimenting over the data, we provide an analyse of the effect of the underlying parameters, and demonstrate that our algorithms significantly outperform other strong baselines.
A Combined Method for Confidentiality, Integrity, Availability and Authentication (CMCIAA)

--- This paper introduces a single method that ensures the Confidentiality, Integrity, Availability and Authentication of the message to be transmitted. Message is encrypted by the latest symmetric encryption standard called AES (Advanced Encryption Standard). A new method for calculating MAC (Message Authentication Code) based on the shared secret key used in AES, is proposed that proves the message integrity and authentication. The proposed method consists of very simple steps, therefore would have lesser overhead and low complexity, as compared to the standard algorithms of calculating MAC. So this method can be used to achieve all the main goals of Cryptography by a single mean.
Enabling Effective Programming and Flexible Management of Efficient Body Sensor Network Applications

Wireless body sensor networks (BSNs) possess enormous potential for changing people's daily lives. They can enhance many human-centered application domains such as m-Health, sport and wellness, and human-centered applications that involve physical/virtual social interactions. However, there are still challenging issues that limit their wide diffusion in real life: primarily, the programming complexity of these systems, due to the lack of high-level software abstractions, and the hardware constraints of wearable devices. In contrast with low-level programming and general-purpose middleware, domain-specific frameworks are an emerging programming paradigm designed to fulfill the lack of suitable BSN programming support with proper abstraction layers. This paper analyzes the most important requirements for an effective BSN-specific software framework, enabling efficient signal-processing applications. Specifically, we present signal processing in node environment (SPINE), an open-source programming framework, designed to support rapid and flexible prototyping and management of BSN applications. We describe how SPINE efficiently addresses the identified requirements while providing performance analysis on the most common hardware/software sensor platforms. We also report a few high-impact BSN applications that have been entirely implemented using SPINE to demonstrate practical examples of its effectiveness and flexibility. This development experience has notably led to the definition of a SPINE-based design methodology for BSN applications. Finally, lessons learned from the development of such applications and from feedback received by the SPINE community are discussed.
Chronic inhibition of brain glycolysis initiates epileptogenesis

Metabolic abnormalities found in epileptogenic tissue provide considerable evidence of brain hypometabolism, while major risk factors for acquired epilepsy all share brain hypometabolism as one common outcome, suggesting that a breakdown of brain energy homeostasis may actually precede epileptogenesis. However, a causal link between deficient brain energy metabolism and epilepsy initiation has not been yet established. To address this issue we developed an in vivo model of chronic energy hypometabolism by daily intracerebroventricular (i.c.v.) injection of the nonmetabolizable glucose analog 2‐deoxy‐D‐glucose (2‐DG) and also investigated acute effects of 2‐DG on the cellular level. In hippocampal slices, acute glycolysis inhibition by 2‐DG (by about 35%) led to contrasting effects on the network: a downregulation of excitatory synaptic transmission together with a depolarization of neuronal resting potential and a decreased drive of inhibitory transmission. Therefore, the potential acute effect of 2‐DG on network excitability depends on the balance between these opposing pre‐ and postsynaptic changes. In vivo, we found that chronic 2‐DG i.c. v. application (estimated transient inhibition of brain glycolysis under 14%) for a period of 4 weeks induced epileptiform activity in initially healthy male rats. Our results suggest that chronic inhibition of brain energy metabolism, characteristics of the well‐established risk factors of acquired epilepsy, and specifically a reduction in glucose utilization (typically observed in epileptic patients) can initiate epileptogenesis. © 2017 Wiley Periodicals, Inc.
Nature versus Nurture in Shallow Convection

Abstract Tracers are used in a large-eddy simulation of shallow convection to show that stochastic entrainment (and not cloud-base properties) determines the fate of convecting parcels. The tracers are used to diagnose the correlations between a parcel’s state above the cloud base and both the parcel’s state at the cloud base and its entrainment history. The correlation with the cloud-base state goes to zero a few hundred meters above the cloud base. On the other hand, correlations between a parcel’s state and its net entrainment are large. Evidence is found that the entrainment events may be described as a stochastic Poisson process. A parcel model is constructed with stochastic entrainment that is able to replicate the mean and standard deviation of cloud properties. Turning off cloud-base variability has little effect on the results, which suggests that stochastic mass-flux models may be initialized with a single set of properties. The success of the stochastic parcel model suggests that it holds promi.
(−)-Epigallocatechin Gallate and Polyphenon E Inhibit Growth and Activation of the Epidermal Growth Factor Receptor and Human Epidermal Growth Factor Receptor-2 Signaling Pathways in Human Colon Cancer Cells

Purpose: (−)-Epigallocatechin gallate (EGCG) inhibits activation of the epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor-2 (HER2) and multiple downstream signaling pathways in cancer cell lines. In this study we compared the cellular and molecular effects of EGCG with a well-standardized decaffeinated green tea catechin mixture Polyphenon E (Poly E) on human colon cancer cell lines. Experimental Design and Results: Both EGCG and Poly E preferentially inhibited growth of the Caco2, HCT116, HT29, SW480, and SW837 colon cancer cells when compared with the FHC normal human fetal colon cell line. The EGFR and HER2 proteins were overexpressed and constitutively activated in all of the colon cancer cell lines when compared with the FHC cell line. Treatment of HT29 cells with EGCG or Poly E caused an increase of cells in G1 and induced apoptosis. Both EGCG and Poly E caused a decrease in the phosphorylated forms of EGFR and HER2 proteins, and subsequently caused a decrease in the phosphorylated forms of the extracellular signal-regulated kinase and Akt proteins. Similar effects of these compounds were seen when the cells were stimulated with transforming growth factor α. Reporter assays indicated that both EGCG and Poly E inhibited the transcriptional activity of the activator protein 1 (AP-1), c-fos, nuclear factor κB, and cyclin D1 promoters. The combination of only 1 μg/mL of epicatechin plus 10 μg/mL of EGCG displayed synergistic effects on growth inhibition and induction of apoptosis. Furthermore, when treatment was prolonged for 96 hours, 1 μg/mL of EGCG or Poly E was sufficient to inhibit growth, reduce activation of EGFR and HER2, and induce apoptosis. Conclusion: Our findings suggest that EGCG or Poly E may be useful in the chemoprevention and/or treatment of colon cancer. Poly E contains about 60% EGCG, yet pure EGCG and Poly E had similar potencies (expressed as μg/ml). Poly E may be preferable because it is easier to prepare and this mixture of catechins may exert synergistic effects.
Ex Vivo Isolation and Characterization of Cd4+Cd25+ T Cells with Regulatory Properties from Human Blood

It has been known for years that rodents harbor a unique population of CD4+CD25+ “professional” regulatory/suppressor T cells that is crucial for the prevention of spontaneous autoimmune diseases. Here we demonstrate that CD4+CD25+CD45RO+ T cells (mean 6% of CD4+ T cells) are present in the blood of adult healthy volunteers. In contrast to previous reports, these CD4+CD25+ T cells do not constitute conventional memory cells but rather regulatory cells exhibiting properties identical to their rodent counterparts. Cytotoxic T lymphocyte–associated antigen (CTLA)-4 (CD152), for example, which is essential for the in vivo suppressive activity of CD4+CD25+ T cells, was constitutively expressed, and remained strongly upregulated after stimulation. The cells were nonproliferative to stimulation via their T cell receptor for antigen, but the anergic state was partially reversed by interleukin (IL)-2 and IL-15. Upon stimulation with allogeneic (but not syngeneic) mature dendritic cells or platebound anti-CD3 plus anti-CD28 the CD4+CD25+ T cells released IL-10, and in coculture experiments suppressed the activation and proliferation of CD4+ and CD8+ T cells. Suppression proved IL-10 independent, yet contact dependent as in the mouse. The identification of regulatory CD4+CD25+ T cells has important implications for the study of tolerance in man, notably in the context of autoimmunity, transplantation, and cancer.
Eliciting Information from Experts on the Likelihood of Rapid Climate Change

The threat of so‐called rapid or abrupt climate change has generated considerable public interest because of its potentially significant impacts. The collapse of the North Atlantic Thermohaline Circulation or the West Antarctic Ice Sheet, for example, would have potentially catastrophic effects on temperatures and sea level, respectively. But how likely are such extreme climatic changes? Is it possible actually to estimate likelihoods? This article reviews the societal demand for the likelihoods of rapid or abrupt climate change, and different methods for estimating likelihoods: past experience, model simulation, or through the elicitation of expert judgments. The article describes a survey to estimate the likelihoods of two characterizations of rapid climate change, and explores the issues associated with such surveys and the value of information produced. The surveys were based on key scientists chosen for their expertise in the climate science of abrupt climate change. Most survey respondents ascribed low likelihoods to rapid climate change, due either to the collapse of the Thermohaline Circulation or increased positive feedbacks. In each case one assessment was an order of magnitude higher than the others. We explore a high rate of refusal to participate in this expert survey: many scientists prefer to rely on output from future climate model simulations.
Applications of Adjoint Modelling in Chemical Composition: Studies of Tropospheric Ozone at Middle and High Northern Latitudes

Applications of Adjoint Modelling in Chemical Composition: Studies of Tropospheric Ozone at Middle and High Northern Latitudes Thomas William Walker Doctor of Philosophy Graduate Department of Physics University of Toronto 2014 Ozone is integral to tropospheric chemistry, and understanding the processes controlling its distribution is important in climate and air pollution contexts. The GEOS-Chem global chemical transport model and its adjoint are used to interpret the impacts of midlatitude precursor emissions and atmospheric transport on the tropospheric ozone distribution at middle and high northern latitudes. In the Arctic, the model reproduces seasonal cycles of peroxyacetyl nitrate (PAN) and ozone measured at the surface, and observed ozone abundances in the summer free troposphere. Source attribution analysis suggests that local photochemical production, ≤ 0.25 ppbv/day, driven by PAN decomposition, accounts for more than 50% of ozone in the summertime Arctic boundary layer. In the mid-troposphere, photochemical production accounts for 30–40% of ozone, while ozone transported from midlatitudes contributes 25–35%. Adjoint sensitivity studies link summertime ozone production to anthropogenic, biomass burning, soil, and lightning emissions between 50◦N–70◦N. Over Alert, Nunavut, the sensitivity of mid-tropospheric ozone to lightning emissions sometimes exceeds that to anthropogenic emissions. Over the eastern U.S., numerous models overestimate ozone in the summertime boundary layer. An inversion analysis, using the GEOS-Chem four-dimensional variational data assimilation system, optimizes emissions of NOx and isoprene. Inversion
Hierarchical Reasoning with Distributed Vector Representations

We demonstrate that distributed vector representations are capable of hierarchical reasoning by summing sets of vectors representing hyponyms (subordinate concepts) to yield a vector that resembles the associated hypernym (superordinate concept). These distributed vector representations constitute a potentially neurally plausible model while demonstrating a high level of performance in many different cognitive tasks. Experiments were run using DVRS, a word embedding system designed for the Sigma cognitive architecture, and Word2Vec, a state-of-the-art word embedding system. These results contribute to a growing body of work demonstrating the various tasks on which distributed vector representations perform competently.
Developments in the Measurement of Subjective Well-Being

Direct reports of subjective well-being may have a useful role in the measurement of consumer preferences and social welfare, if they can be done in a credible way. Can well-being be measured by a subjective survey, even approximately? In this paper, we discuss research on how individuals' responses to subjective well-being questions vary with their circumstances and other factors. We will argue that it is fruitful to distinguish among different conceptions of utility rather than presume to measure a single, unifying concept that motivates all human choices and registers all relevant feelings and experiences. While various measures of well-being are useful for some purposes, it is important to recognize that subjective well-being measures features of individuals' perceptions of their experiences, not their utility as economists typically conceive of it. Those perceptions are a more accurate gauge of actual feelings if they are reported closer to the time of, and in direct reference to, the actual experience. We conclude by proposing the U- index, a misery index of sorts, which measures the proportion of time that people spend in an unpleasant state, and has the virtue of not requiring a cardinal conception of individuals' feelings.
Spoken document retrieval using both word-based and syllable-based document spaces with latent semantic indexing

In this paper, we propose a spoken document retrieval method using vector space models in multiple document spaces. First we construct multiple document vector spaces, one of which is based on continuous-word speech recognition results and the other on continuous-syllable speech recognition results. Query expansion is also applied to the word-based document space. We proposed to apply latent semantic indexing (LSI) not only to the word-based space but also to the syllable-based space, to reduce dimensionality of the spaces using implicitly defined semantics. Finally, we combine the distances and compare the distance between the query and the available documents in various spaces to rank the documents. In this procedure, we propose to model the document by hyperplane. To evaluate our proposed method, we conducted spoken document retrieval experiments using the NTCIR-9 SpokenDoc data set. The results showed that using the combination of the distances, and using LSI on the syllable-based document space, improved retrieval performance.
Automata: from logics to algorithms

We review, in a unified framework, translations from five different logics—monadic second-order logic of one and two successors (S1S and S2S), linear-time temporal logic (LTL), computation tree logic (CTL), and modal µ-calculus (MC)—into appropriate models of finite-state automata on infinite words or infinite trees. Together with emptiness-testing algorithms for these models of automata, this yields decision procedures for these logics. The translations are presented in a modular fashion and in a way such that optimal complexity bounds for satisfiability, conformance (model checking), and realizability are obtained for all logics.
Half in Love with Easeful Death: The Meaning of Chronic Suicidality in Borderline Personality Disorder

&NA; Chronic suicidality is a central feature of borderline personality disorder. While suicidal thoughts and attempts are highly prevalent in borderline patients, completion is relatively unpredictable. Self‐cutting seems to function as a means of affective regulation. In borderline personality disorder, suicidality performs a set of psychological functions and can sometimes become “a way of life. ” Strategies developed for acutely suicidal patients may not be effective in chronic suicidality. Since there is no evidence that hospitalization prevents completion, an ambulatory approach to the management of chronically suicidal patients may be most useful.