Miracle-dz/UniFAR-FTUs huggingface dataset:
Determining the number of messages transmitted for the temporary links in the case of ABT family techniques

Starting from the algorithm of asynchronous backtracking (ABT), a unifying framework for some of the asynchronous techniques has recently been suggested. Within this unifying frameworld several techniques have been derived, known as the ABT family. They differ in the way they store no goods, but they all use additional communication links between unconnected agents to detect obsolete information. A first way to remove obsolete information is to add new communication links to allow a nogood owner to determine whether this no good is obsolete or not. The second solution consists in temporary keeping the links. A new link remains until a fixed number of messages have been exchanged through it. After that, it is removed. There is no optimal value determined for that number of messages. This article investigates different values for the number of messages, values that are either statically determined (before the run) or dynamically during the runtime. A dynamical solution for determining the number of messages necessary for maintaining a connection is proposed, the experiments show a better efficiency in comparison with the standard Yokoo variant.
Accurate max-margin training for structured output spaces

Tsochantaridis et al. (2005) proposed two formulations for maximum margin training of structured spaces: margin scaling and slack scaling. While margin scaling has been extensively used since it requires the same kind of MAP inference as normal structured prediction, slack scaling is believed to be more accurate and better-behaved. We present an efficient variational approximation to the slack scaling method that solves its inference bottleneck while retaining its accuracy advantage over margin scaling. We further argue that existing scaling approaches do not separate the true labeling comprehensively while generating violating constraints. We propose a new max-margin trainer PosLearn that generates violators to ensure separation at each position of a decomposable loss function. Empirical results on real datasets illustrate that PosLearn can reduce test error by up to 25% over margin scaling and 10% over slack scaling. Further, PosLearn violators can be generated more efficiently than slack violators; for many structured tasks the time required is just twice that of MAP inference.
Development of the human interactive autonomy for the shared teleoperation of mobile robots

Manipulation complexity of teleoperation increases the necessity of shared autonomy. However, designing an autonomy while keeping in mind the environmental uncertainty is challenging. This paper proposes a human interactive autonomy for a shared teleoperation. The central concept is a novel methodology of combining the innate cognitive ability of a human operator to arrive at an accurate, and precise solution of an autonomous system for mobile robot shared teleoperation. The resulting system is more efficient and less fatigued than direct teleoperation. This combined approach transfers the human operator's intention, shaped by his cognition about remote environment, to the autonomous system. The intention information input from the operator helps autonomous system perform the given teleoperation tasks more efficiently. For initial feasibility and proof of concept, the intention information is provided to the autonomous system in the form of a path which is acquired by our proposed sketch method. Our novel proposed sketch method allows the operator to sketch the path on the visual feedback image of the remote environments and the information is then transmitted to the autonomous system. Experimental results provide the feasibility and effectiveness of proposed method against prevalent control methods.
Long-Lasting Improvements in Liver Fat and Metabolism Despite Body Weight Regain After Dietary Weight Loss

OBJECTIVE Weight loss reduces abdominal and intrahepatic fat, thereby improving metabolic and cardiovascular risk. Yet, many patients regain weight after successful diet-induced weight loss. Long-term changes in abdominal and liver fat, along with liver test results and insulin resistance, are not known. RESEARCH DESIGN AND METHODS We analyzed 50 overweight to obese subjects (46 ± 9 years of age; BMI, 32.5 ± 3.3 kg/m2; women, 77%) who had participated in a 6-month hypocaloric diet and were randomized to either reduced carbohydrates or reduced fat content. Before, directly after diet, and at an average of 24 (range, 17–36) months follow-up, we assessed body fat distribution by magnetic resonance imaging and markers of liver function and insulin resistance. RESULTS Body weight decreased with diet but had increased again at follow-up. Subjects also partially regained abdominal subcutaneous and visceral adipose tissue. In contrast, intrahepatic fat decreased with diet and remained reduced at follow-up (7.8 ± 9.8% [baseline], 4.5 ± 5.9% [6 months], and 4.7 ± 5.9% [follow-up]). Similar patterns were observed for markers of liver function, whole-body insulin sensitivity, and hepatic insulin resistance. Changes in intrahepatic fat und intrahepatic function were independent of macronutrient composition during intervention and were most effective in subjects with nonalcoholic fatty liver disease at baseline. CONCLUSIONS A 6-month hypocaloric diet induced improvements in hepatic fat, liver test results, and insulin resistance despite regaining of weight up to 2 years after the active intervention. Body weight and adiposity measurements may underestimate beneficial long-term effects of dietary interventions.
Strategyproof Classification under Constant Hypotheses: A Tale of Two Functions

We consider the following setting: a decision maker must make a decision based on reported data points with binary labels. Subsets of data points are controlled by different selfish agents, which might misreport the labels in order to sway the decision in their favor. We design mechanisms (both deterministic and randomized) that reach an approximately optimal decision and are strategyproof, i.e., agents are best off when they tell the truth. We then recast our results into a classical machine learning classification framework, where the decision maker must make a decision (choose between the constant positive hypothesis and the constant negative hypothesis) based only on a sampled subset of the agents' points.
Minimal fuzzy memberships and rules using hierarchical genetic algorithms

A new scheme to obtain optimal fuzzy subsets and rules is proposed. The method is derived from the use of genetic algorithms, where the genes of the chromosome are classified into two different types. These genes can be arranged in a hierarchical form, where one type of gene controls the other. The effectiveness of this genetic formulation enables the fuzzy subsets and rules to be optimally reduced and, yet, the system performance is well maintained. In this paper, the details of formulation of the genetic structure are given. The required procedures for coding the fuzzy membership function and rules into the chromosome are also described. To justify this approach to fuzzy logic design, the proposed scheme is applied to control a constant water pressure pumping system. The obtained results, as well as the associated final fuzzy subsets, are included in this paper. Because of its simplicity, the method could lead to a potentially low-cost fuzzy logic implementation.
Dual-VCC 8T-bitcell SRAM array in 22nm tri-gate CMOS for energy-efficient operation across wide dynamic voltage range

A 14KB 8T-bitcell SRAM array is demonstrated in 22nm tri-gate CMOS with fine-grain dual-V<sub>CC</sub> assist techniques. V<sub>MIN</sub> limiting 8T-bitcell nodes are boosted selectively during read and write to improve overall chip-V<sub>MIN</sub>. Measurements show 130-270mV lower V<sub>MIN</sub> with 27-46% lower power at 0.4-1.6GHz for varying amounts of boosting, array activity and voltage regulator efficiency.
Reinventing delivery and childbirth in Brazil: back to the future.

The demonstrations that took the streets in Bra-zil in June 2013 brought health care to the cen-ter of public debate. The protests exposed the limits of the Brazilian Unified National Health System (SUS): despite expanding care cover-age enormously, it is unable to assure service quality and suffers from chronic underfunding and management shortcomings. Moreover, the model of health care financing accentuates social inequalities. The poorer majority finds difficulty enjoying the universal right to public health ser-vices stipulated in the 1988
Re-Examination of Thickness-Resonance- Frequency Formula for Structural Integrity Appraisal and Damage Diagnosis

This study examines rationale of correction factor β in the formula of thickness resonant frequency, fundamental to the thickness estimation of impact-echo (IE) approach in nondestructive testing (NDT) for integrity appraisal and damage diagnosis of infrastructure systems. It shows the role of the factor in the formula from the perspective of testing equipment setup, wave propagation, and resonant frequency identification, much broader than what was first introduced empirically for shape correction of a structure under test. Emphasis is laid in wave-based interpretation of resonant frequency, typically obtained from traditional fast Fourier transform (FFT) data analysis of IE recordings. Since the FFT data analysis provides average, not true, characteristic of resonant frequency shown in the nonstationary IE recordings, it typically distorts the thickness estimation from the formula if the correction factor is not used. An adaptive time-frequency data analysis termed Hilbert–Huang transform (HHT) is then introduced to overcome the shortage of FFT analysis in identifying the resonant frequency from noise-added IE recordings. With FFT and HHT analyses of five data sets of sample IE recordings from sound and damaged concrete structures and comparison with referenced ones, this study reveals that the proposed IE approach with HHT data analysis not only eliminates the subjective use of correction factor in the formula, but it also improves greatly the accuracy in the thickness estimation.
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems

Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type of operators for creating new individuals, specifically, hypothesis generation, which learns rules indicating subareas in the search space that likely contain the optimum, and hypothesis instantiation, which populates these subspaces with new individuals. This paper briefly describes the newest and most advanced implementation of learnable evolution, LEM3, its novel features, and results from its comparison with a conventional, Darwinian-type evolutionary computation program (EA), a cultural evolution algorithm (CA), and the estimation of distribution algorithm (EDA) on selected function optimization problems (with the number of variables varying up to 1000). In every experiment, LEM3 outperformed the compared programs in terms of the evolution length (the number of fitness evaluations needed to achieved a desired solution), sometimes more than by one order of magnitude.
Analysis of Generalized Pattern Searches

This paper contains a new convergence analysis for the Lewis and Torczon generalized pattern search (GPS) class of methods for unconstrained and linearly constrained optimization. This analysis is motivated by a desire to understand the successful behavior of the algorithm under hypotheses that are satisfied by many practical problems. Specifically, even if the objective function is discontinuous or extended-valued, the methods find a limit point with some minimizing properties. Simple examples show that the strength of the optimality conditions at a limit point depends not only on the algorithm, but also on the directions it uses and on the smoothness of the objective at the limit point in question. The contribution of this paper is to provide a simple convergence analysis that supplies detail about the relation of optimality conditions to objective smoothness properties and to the defining directions for the algorithm, and it gives previous results as corollaries.
Effect of azithromycin maintenance treatment on infectious exacerbations among patients with non-cystic fibrosis bronchiectasis: the BAT randomized controlled trial.

IMPORTANCE Macrolide antibiotics have been shown beneficial in cystic fibrosis (CF) and diffuse panbronchiolitis, and earlier findings also suggest a benefit in non-CF bronchiectasis. OBJECTIVE To determine the efficacy of macrolide maintenance treatment for adults with non-CF bronchiectasis. DESIGN, SETTING, AND PARTICIPANTS The BAT (Bronchiectasis and Long-term Azithromycin Treatment) study, a randomized, double-blind, placebo-controlled trial conducted between April 2008 and September 2010 in 14 hospitals in The Netherlands among 83 outpatients with non-CF bronchiectasis and 3 or more lower respiratory tract infections in the preceding year. INTERVENTIONS Azithromycin (250 mg daily) or placebo for 12 months. MAIN OUTCOME MEASURES Number of infectious exacerbations during 12 months of treatment. Secondary end points included lung function, sputum bacteriology, inflammatory markers, adverse effects, symptom scores, and quality of life. RESULTS Forty-three participants (52%) received azithromycin and 40 (48%) received placebo and were included in the modified intention-to-treat analysis. At end of study, the median number of exacerbations in the azithromycin group was 0 (interquartile range [IQR], 0-1), compared with 2 (IQR, 1-3) in the placebo group (P < .001). Thirty-two (80%) placebo-treated vs 20 (46%) azithromycin-treated individuals had at least 1 exacerbation (hazard ratio, 0.29 [95% CI, 0.16-0.51]). In a mixed-model analysis, change in forced expiratory volume in the first second of expiration (percent of predicted) over time differed between groups (F1,78.8 = 4.085, P = .047), with an increase of 1.03% per 3 months in the azithromycin group and a decrease of 0.10% per 3 months in the placebo group. Gastrointestinal adverse effects occurred in 40% of patients in the azithromycin group and in 5% in the placebo group (relative risk, 7.44 [95% CI, 0.97-56.88] for abdominal pain and 8.36 [95% CI, 1.10-63.15] for diarrhea) but without need for discontinuation of study treatment. A macrolide resistance rate of 88% was noted in azithromycin-treated individuals, compared with 26% in the placebo group. CONCLUSIONS AND RELEVANCE Among adults with non-CF bronchiectasis, the daily use of azithromycin for 12 months compared with placebo resulted in a lower rate of infectious exacerbations. This could result in better quality of life and might influence survival, although effects on antibiotic resistance need to be considered. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00415350.
A novel role of ImmE7 in the autoregulatory expression of the ColE7 operon and identification of possible RNase active sites in the crystal structure of dimeric ImmE7

Site‐specific cleavage of mRNA has been identified in vivo for the polycistronic colicin E7 operon (ColE7), which occurs between G and A nucleotides located at the Asp52 codon (GAT) of the immunity gene (ceiE7). In vitro, this specific cleavage occurs only in the presence of the ceiE7 gene product (ImmE7). The crystal structure of dimeric ImmE7 has been determined at 1.8 Å resolution by X‐ray crystallographic analysis. We found that several residues located at the interface of dimeric ImmE7 bear surprising resemblance to the active sites of some RNases. These results suggest that dimeric ImmE7 may possess a novel RNase activity that cleaves its own mRNA at a specific site and thus autoregulates translational expression of the downstream celE7 gene as well as degradation of the upstream ceaE7 mRNA.
Dissociative symptoms reflect levels of tumor necrosis factor alpha in patients with unipolar depression

Recent evidence indicates that the nature of interactions between the nervous system and immune system is important in the pathogenesis of depression. Specifically, alterations in pro-inflammatory cytokines have been related to the development of several psychological and neurobiological manifestations of depressive disorder, as well as to stress exposure. A number of findings point to tumor necrosis factor alpha (TNF-α) as one of the central factors in these processes. Accordingly, in the present study, we test the hypothesis that specific influences of chronic stressors related to traumatic stress and dissociation are related to alterations in TNF-α levels. We performed psychometric measurement of depression (Beck Depression Inventory [BDI]-II), traumatic stress symptoms (Trauma Symptom Checklist [TSC]-40), and psychological and somatoform dissociation (Dissociative Experiences Scale [DES] and Somatoform Dissociation Questionnaire [SDQ]-20, respectively), and immunochemical measure of serum TNF-α in 66 inpatients with unipolar depression (mean age 43.1 ± 7.3 years). The results show that TNF-α is significantly related to DES (Spearman R=−0.42, P<0.01), SDQ-20 (Spearman R=−0.38, P<0.01), and TSC-40 (Spearman R=−0.41, P<0.01), but not to BDI-II. Results of the present study suggest that TNF-α levels are related to dissociative symptoms and stress exposure in depressed patients.
RNA methyltransferases involved in 5′ cap biosynthesis

In eukaryotes and viruses that infect them, the 5′ end of mRNA molecules, and also many other functionally important RNAs, are modified to form a so-called cap structure that is important for interactions of these RNAs with many nuclear and cytoplasmic proteins. The RNA cap has multiple roles in gene expression, including enhancement of RNA stability, splicing, nucleocytoplasmic transport, and translation initiation. Apart from guanosine addition to the 5′ end in the most typical cap structure common to transcripts produced by RNA polymerase II (in particular mRNA), essentially all cap modifications are due to methylation. The complexity of the cap structure and its formation can range from just a single methylation of the unprocessed 5′ end of the primary transcript, as in mammalian U6 and 7SK, mouse B2, and plant U3 RNAs, to an elaborate m7Gpppm6,6AmpAmpCmpm3Um structure at the 5′ end of processed RNA in trypanosomes, which are formed by as many as 8 methylation reactions. While all enzymes responsible for methylation of the cap structure characterized to date were found to belong to the same evolutionarily related and structurally similar Rossmann Fold Methyltransferase superfamily, that uses the same methyl group donor, S-adenosylmethionine; the enzymes also exhibit interesting differences that are responsible for their distinct functions. This review focuses on the evolutionary classification of enzymes responsible for cap methylation in RNA, with a focus on the sequence relationships and structural similarities and dissimilarities that provide the basis for understanding the mechanism of biosynthesis of different caps in cellular and viral RNAs. Particular attention is paid to the similarities and differences between methyltransferases from human cells and from human pathogens that may be helpful in the development of antiviral and antiparasitic drugs.
Testing the intermediate disturbance hypothesis: response of fouling communities to various levels of emersion intensity

Connell¹s intermediate disturbance hypothesis (IDH) postulates that diversity peaks at an intermediate level of disturbance frequency or intensity. To test the validity of this concept for the species-poor marine hard-bottom community of the Western Baltic, we chose an in situ experimental approach. Undisturbed fouling communities of 2 different successional stages, 3 and 12 mo old, were submitted to various levels of emersion intensities, defined as time spans of continuous exposure to the air d-1. Disturbance levels ranged from 0.25 h up to 12 h of daily exposure. The study on 3 mo old communities was repeated in 2 subsequent years, 1999 and 2000. Species richness, evenness and diversity (Shannon index) were recorded to measure the effect of intensity treatments on community structure. The IDH was confirmed in the first year, when diversity was found to peak at intermediate disturbances. However, for communities of both successional stages, diversity-disturbance relationships were U-shaped or not significant in the second year. This ambiguous picture basically confirms the validity of the mechanisms proposed by the IDH, but shows that their forcing can be masked by fluctuations in environmental parameters, such as climatic conditions. An extension of the model is proposed, that considers diversity enhancement under extreme conditions due to a disturbance-induced change in community structure. Furthermore we discuss a conceptual linkage of the IDH to the multiple stable-state hypothesis. Finally, we found community stability not to be positively correlated with community age and complexity.
uPAR regulates bronchial epithelial repair in vitro and is elevated in asthmatic epithelium

Background The asthma-associated gene urokinase plasminogen activator receptor (uPAR) may be involved in epithelial repair and airway remodelling. These processes are not adequately targeted by existing asthma therapies. A fuller understanding of the pathways involved in remodelling may lead to development of new therapeutic opportunities. uPAR expression in the lung epithelium of normal subjects and patients with asthma was investigated and the contribution of uPAR to epithelial wound repair in vitro was studied using primary bronchial epithelial cells (NHBECs). Methods Bronchial biopsy sections from normal subjects and patients with asthma were immunostained for uPAR. NHBECs were used in a scratch wound model to investigate the contribution of the plasminogen pathway to repair. The pathway was targeted via blocking of the interaction between urokinase plasminogen activator (uPA) and uPAR and overexpression of uPAR. The rate of wound closure and activation of intracellular signalling pathways and matrix metalloproteinases (MMPs) were measured. Results uPAR expression was significantly increased in the bronchial epithelium of patients with asthma compared with controls. uPAR expression was increased during wound repair in monolayer and air-liquid interface-differentiated NHBEC models. Blocking the uPA–uPAR interaction led to attenuated wound repair via changes in Erk1/2, Akt and p38MAPK signalling. Cells engineered to have raised levels of uPAR showed attenuated repair via sequestration of uPA by soluble uPAR. Conclusions The uPAR pathway is required for efficient epithelial wound repair. Increased uPAR expression, as seen in the bronchial epithelium of patients with asthma, leads to attenuated wound repair which may contribute to the development and progression of airway remodelling in asthma. This pathway may therefore represent a potential novel therapeutic target for the treatment of asthma.
Heuristic cryptanalysis of classical and modern ciphers

Block cipher algorithms are commonly used to secure confidential information in everyday user applications. However, it is quite common for ignorant users to use familiar dictionary words as their personal passwords. This research examines the effects of weakly chosen password-keys on the security of block ciphers. A new hybrid optimization heuristic cryptanalytic attack (tabu search and genetic algorithm) is used to conduct an intelligent key-search attack on classical ciphers and modern ciphers. The algorithm chosen to represent modern block ciphers is the advanced encryption standard (AES) algorithm. AES is an algebraic product cipher which combines elements of substitution and transposition. Therefore, the primarily aims of this paper is to study the effects of an optimization heuristic cryptanalytic attack on block cipher.