Miracle-dz/UniFAR-FTUs huggingface dataset:
Preadaptation and post-introduction evolution facilitate the invasion of Phragmites australis in North America

Compared with non-invasive species, invasive plant species may benefit from certain advantageous traits, for example, higher photosynthesis capacity and resource/energy-use efficiency. These traits can be preadapted prior to introduction, but can also be acquired through evolution following introduction to the new range. Disentangling the origins of these advantageous traits is a fundamental and emerging question in invasion ecology. We conducted a multiple comparative experiment under identical environmental condition with the invasive haplotype M lineage of the wetland grass Phragmites australis and compared the ecophysiological traits of this invasive haplotype M in North America with those of the European ancestor and the conspecific North American native haplotype E lineage, P. australis ssp. americanus. The invasive haplotype M differed significantly from the native North American conspecific haplotype E in several ecophysiological and morphological traits, and the European haplotype M had a more efficient photosynthetic apparatus than the native North American P. australis ssp. americanus. Within the haplotype M lineage, the introduced North American P. australis exhibited different biomass allocation patterns and resource/energy-use strategies compared to its European ancestor group. A discriminant analysis of principal components separated the haplotype M and the haplotype E lineages completely along the first canonical axis, highly related to photosynthetic gas-exchange parameters, photosynthetic energy-use efficiency and payback time. The second canonical axis, highly related to photosynthetic nitrogen use efficiency and construction costs, significantly separated the introduced P. australis in North America from its European ancestor. Synthesis. We conclude that the European P. australis lineage was preadapted to be invasive prior to its introduction, and that the invasion in North America is further stimulated by rapid post-introduction evolution in several advantageous traits. The multicomparison approach used in this study could be an effective approach for distinguishing preadaptation and post-introduction evolution of invasive species. Further research is needed to link the observed changes in invasive traits to the genetic variation and the interaction with the environment.
2016 Ieee International Conference on Big Data (big Data) Scalable Dynamic Graph Summarization

—Large-scale dynamic graphs can be challenging to process and store, due to their size and the continuous change of communication patterns between nodes. In this work we address the problem of summarizing large-scale dynamic graphs, maintaining the evolution of their structure and the communication patterns. Our approach is based on grouping the nodes of the graph in supernodes according to their connectivity and communication patterns. The resulting summary graph preserves the information about the evolution of the graph within a time window. We propose two online, distributed, and tunable algorithms for summarizing this type of graphs. We apply our methods to several real-world and synthetic dynamic graphs, and we show that they scale well on the number of nodes and produce high-quality summaries.
Predictors of in-hospital mortality among patients with pulmonary tuberculosis: a protocol of systematic review and meta-analysis of observational studies

Introduction Tuberculosis (TB) continues to be a major public health issue worldwide, with 1.4 million deaths occurring annually. There is uncertainty regarding which factors are associated with in-hospital mortality among patients with pulmonary TB. This knowledge gap complicates efforts to identify and improve the management of those individuals with TB at greatest risk of death. The aim of this systematic review and meta-analysis is to establish predictors of in-hospital mortality among patients with pulmonary TB to enhance the evidence base for public policy. Methods and analysis Studies will be identified by a MEDLINE, EMBASE and Global Health search. Eligible studies will be cohort and case–control studies that report predictors or risk factors for in-hospital mortality among patients with pulmonary TB and an adjusted analysis to explore factors associated with in-hospital mortality. We will use the Grading of Recommendations Assessment, Development and Evaluation approach to summarise the findings of some reported predictors. Teams of 2 reviewers will screen the titles and abstracts of all citations identified in our search, independently and in duplicate, extract data, and assess scientific quality using standardised forms quality assessment and tools tailored. We will pool all factors that were assessed for an association with mortality that were reported by >1 study, and presented the OR and the associated 95% CI. When studies provided the measure of association as a relative risk (RR), we will convert the RR to OR using the formula provided by Wang. For binary data, we will calculate a pooled OR, with an associated 95% CI. Ethics and dissemination This study is based on published data, and therefore ethical approval is not a requirement. Findings will be disseminated through publication in peer-reviewed journals and conference presentations at relevant conferences. Trial registration number CRD42015025755.
Ocular dominance and temporal dynamics in the venetian blind effect

The visual system can use small disparities between the stimuli seen by each eye as a binocular cue for depth. Geometric disparities are the most commonly used cue for stereopsis, but disparities in contrast and luminance can also lead to the perception of depth and both can cancel perceived depth from a geometric disparity. Humans are able to perceive changes in depth from contrast disparities at frequencies up to approximately 1.4 Hz, whereas changes in depth from geometric disparities are visible at frequencies above 5 Hz (Dobias, 2008). This dissertation is divided into two parts. The first part (experiments 1 & 2) explores the dynamics of canceling the perceived depth from a geometric disparity using a contrast or a luminance disparity. The second part (experiments 3-5) explores the role of individual differences in the dynamics of perceived depth from contrast, luminance, and geometric disparities. Dobias (2008) and results in experiments 3 & 4 show that the probability of reporting depth from contrast and luminance disparities diminish at frequencies much lower than from a geometric disparity (critical frequency). A generalized difference model (simple low-pass filter), does not account for the data from experiment 1. However, a gated generalized difference model, which applies low-pass filtering to the amplitude of the modulation but not its rate of change, does account for the data. Results from part two show that the frequency at which depth changes from contrast and luminance disparities (experiment 3) differs from the frequency at which depth is no longer visible for a geometric disparity (experiment 4), that the frequency can differ depending on which eye views the changing stimulus (experiments 3 & 4), and that either visual masking or eye movements are likely not causing the decrease at lower frequencies for contrast and luminance disparities (experiment 5). The finding that results from part one follow the gated model, and the differences depending on which eye views the dynamic stimulus found in part two, suggest that the visual system processes depth from contrast and luminance disparities much differently from what would be expected based on our typical understanding of depth perception.
Verifying the ecological model of peer aggression on Croatian students

Using the ecological approach, the goal of this study was to determine the predictors of physical and verbal peer aggressive behavior. The participants were 880 school students from the fifth to eighth grade (48% boys and 52% girls) and the same number of parents (19% fathers and 61% mothers) as well as 107 teachers. The main analysis was performed using multivariate–multilevel modeling. The following significant predictors of physical peer aggression were obtained: Boys, a greater degree of impulsivity, more parental punishment, poorer school success, more time spent with the media, and the perception of great neighborhood dangerousness. For verbal peer aggression, the significant predictors were: A greater degree of impulsivity, lower level of affective empathy, more parental punishment, lack of parental supervision, lesser peer acceptance, large differences in family income, more time spent with the media, and the perception of great neighborhood dangerousness. A moderating effect of neighborhood dangerousness and parental supervision was found. The results were interpreted within Bronfenbrenner’s ecological model.
M Introduction to Generalized Linear Odels I. Motivation Ii. Basic Glm Setup and Assumptions Iii. Goodness of Fit and Comparing Models Overview

In this lecture we extend the ideas of linear regression to the more general idea of a generalized linear model (GLM). The essence of linear models is that the response variable is continuous and normally distributed: here we relax these assumptions and consider cases where the response variable is non-normal and in particular has a discrete distribution. Although these models are more general than linear models, nearly all of the techniques for testing hypotheses regarding the regression coefficients, and checking the assumptions of the model apply directly to a glm. In addition, a linear model is simply a special type of a generalised linear model and thus all of the discussion below applies equally to linear models. In Lecture 1 we saw that a typical statistical model can be expressed as an equation that equates the mean(s) of the response variable(s) to some function of a linear combination of the explanatory variables: [ ])] ; ([) (1 1 0 β η β β β η X LC X X x X Y E p p = + + + = = L , (1) In equation (1), the form of the function η() is known, as are Y and X (the latter for a particular choice of explanatory variables). However, the parameters of the model, , are not known and must be estimated. The simple linear model is a special case of the above in which the function η() is the identity function. 1 0 p β β β β K = Generalized linear models extend the ideas underlying the simple linear model () 2 2 2 1 1 0 , ~ , ] | [ σ µ β β β β N Y X X X X Y E p p + + + + = L (2) where the Y are independent, to the following more general situations: i 1. Response variables can follow distributions other than the Normal distribution. They can be discrete, or logical (one of two categories). 2. The relationship between the response and the explanatory variables does not have to take on the simple linear form above. GLMs are based on the exponential family of distributions that shares many of the desirable statistical properties of the Normal distribution. Consider a single random variable Y whose probability distribution depends only on a single parameter. The distribution of Y belongs to the exponential family if it …
A practical split‐window algorithm for retrieving land‐surface temperature from MODIS data

This paper presents a practical split‐window algorithm utilized to retrieve land‐surface temperature (LST) from Moderate‐resolution Imaging Spectroradiometer (MODIS) data, which involves two essential parameters (transmittance and emissivity), and a new method to simplify Planck function has been proposed. The method for linearization of Planck function, how to obtain atmosphere transmittance from MODIS near‐infrared (NIR) bands and the method for estimating of emissivity of ground are discussed with details. Sensitivity analysis of the algorithm has been performed for the evaluation of probable LST estimation error due to the possible errors in water content and emissivity. Analysis indicates that the algorithm is not sensitive to these two parameters. Especially, the average LST error is changed between 0.19–1.1°C when the water content error in the simulation standard atmosphere changes between −80 and 130%. We confirm the conclusion by retrieving LST from MODIS image data through changing retrieval water content error. Two methods have been used to validate the proposed algorithm. Results from validation and comparison using the standard atmospheric simulation and the comparison with the MODIS LST product demonstrate the applicability of the algorithm. Validation with standard atmospheric simulation indicates that this algorithm can achieve the average accuracy of this algorithm is about 0.32°C in LST retrieval for the case without error in both transmittance and emissivity estimations. The accuracy of this algorithm is about 0.37°C and 0.49°C respectively when the transmittance is computed from the simulation water content by exponent fit and linear fit respectively.
Employee indifference and inaction against abusive supervision

Purpose The purpose of this paper is to investigate how part-time waiters perceive and respond to abusive supervision by the owner-manager of a small restaurant. Design/methodology/approach An ethnographic approach was used to collect data. One of the authors worked as a participant observer for three months. In addition, 13 interviews and three focus group discussions were conducted. Findings Data analysis showed how neutral identification based on a primary identity—liu xu sheng (overseas student)—overshadows employees’ occupational identity (waiter), which helps waiters to cope with abusive supervision. Originality/value Development and application of the concept of neutral organizational identification orientation encourages emotional suppression and reframing, leading to waiters’ indifference and acquiescence in abusive supervision. Implications are drawn for theory and the practice of managing part-time and temporary workers.
Stress-induced changes in cerebral metabolites, hippocampal volume, and cell proliferation are prevented by antidepressant treatment with tianeptine

Stress-induced structural remodeling in the adult hippocampus, involving debranching and shortening of dendrites and suppression of neurogenesis, provides a cellular basis for understanding the impairment of neural plasticity in the human hippocampus in depressive illness. Accordingly, reversal of structural remodeling may be a desirable goal for antidepressant therapy. The present study investigated the effect of tianeptine, a modified tricyclic antidepressant, in the chronic psychosocial stress model of adult male tree shrews (Tupaia belangeri), a model with high validity for research on the pathophysiology of major depression. Animals were subjected to a 7-day period of psychosocial stress to elicit stress-induced endocrine and central nervous alterations before the onset of daily oral administration of tianeptine (50 mg/kg). The psychosocial stress continued throughout the treatment period of 28 days. Brain metabolite concentrations were determined in vivo by proton magnetic resonance spectroscopy, cell proliferation in the dentate gyrus was quantified by using BrdUrd immunohistochemistry, and hippocampal volume was measured post mortem. Chronic psychosocial stress significantly decreased in vivo concentrations of N-acetyl-aspartate (−13%), creatine and phosphocreatine (−15%), and choline-containing compounds (−13%). The proliferation rate of the granule precursor cells in the dentate gyrus was reduced (−33%). These stress effects were prevented by the simultaneous administration of tianeptine yielding normal values. In stressed animals treated with tianeptine, hippocampal volume increased above the small decrease produced by stress alone. These findings provide a cellular and neurochemical basis for evaluating antidepressant treatments with regard to possible reversal of structural changes in brain that have been reported in depressive disorders.
Probabilistic communication optimizations and parallelization for distributed-memory systems

In high-performance systems execution time is of crucial importance justifying advanced optimization techniques. Traditionally, optimization is based on static program analysis. The quality of program optimizations, however, can be substantially improved by utilizing runtime information. Probabilistic data-flow frameworks compute the probability with what data-flow facts may hold at some program point based on representative profile runs. Advanced optimizations can use this information in order to produce highly efficient code. In this paper we introduce a novel optimization technique in the context of High Performance Fortran (HPF) that is based on probabilistic data-flow information. We consider statically undefined attributes which play an important role for parallelization and compute for those attributes the probabilities to hold some specific value during runtime. For the most probable attribute values highly-optimized, specialized code is generated. In this way significantly better performance results can be achieved. The implementation of our optimization is done in the context of VFC, a source-to-source parallelizing compiler for HPF/F90.
Comparison of target-controlled infusion of sufentanil and remifentanil in blunting hemodynamic response to tracheal intubation

Abstract: Background: Maintaining blood pressure (BP) and heart rate (HR) after laryngoscopy and tracheal intubation has always been a concern in injured patients. Opioids can attenuate or stop an increase in these two parameters if administered with proper doses or targets in target-controlled infusion (TCI). Remifentanil and sufentanil are widely used for this purpose because their cardiac side effects are low and, especially in traumatic patients, they are tolerated well. A comparison of the benefits and limitations of these two opioids in TCI is much needed. A literature review in electronic data bases revealed few results. Methods: 40 normotensive patients were enrolled to this randomized clinical trial study. After BIS guided anesthesia with a target-controlled propofol infusion and muscle relaxation with cisatracurium, remifentanil and sufentanil were infused using TCI with 2 and 0.2 ng.ml-1 targets respectively. BP and HR were recorded for five data points and compared with Fischer's exact test. Results: Systolic, mean and diastolic arterial pressure and HR in different points of the study remained below baseline values but were out of control in some cases, however the out-of-control values showed significant difference between the two groups only for heart rate changes. The relative risk for producing out-of-control changes with remifentanil compared to sufentanil is significantly more than 1 for HR decrease. Conclusions: Sufentanil produced more common pre-intubation hypotension than remifentanil in propofol anesthetized patients but this hypotension disappeared sooner than remifentanil after tracheal intubation. Both opioids prevent an increase in BP and HR after tracheal intubation but the side effects (hypotension and bradycardia) may be a cause for concern (IRCT138710011361N3).
Image denoising via collaborative support-agnostic recovery

In this paper, we propose a novel patch-based image denoising algorithm using collaborative support-agnostic sparse reconstruction. In the proposed collaborative scheme, similar patches are assumed to share the same support taps. For sparse reconstruction, the likelihood of a tap being active in a patch is computed and refined through a collaboration process with other similar patches in the similarity group. This provides a very good patch support estimation, hence enhancing the quality of image restoration. Performance comparisons with state-of-the-art algorithms, in terms of PSNR and SSIM, demonstrate the superiority of the proposed algorithm.
Targeting immune checkpoints in unresectable metastatic cutaneous melanoma: a systematic review and meta‐analysis of anti‐CTLA‐4 and anti‐PD‐1 agents trials

Anti‐cytotoxic T lymphocyte‐associated antigen‐4 (CTLA‐4) and anti‐programmed cell death‐1 (PD‐1) inhibitors have been shown to significantly improve survival in patients with metastatic cutaneous melanoma. However, there was some heterogeneity as well as some variation in the degree of benefit across studies. We reviewed randomized trials and performed a meta‐analysis to determine the efficacy and safety of immune checkpoint inhibitors in comparison with conventional regimens. Eligible studies were limited to randomized controlled trials comparing anti‐CTLA‐4 or anti‐PD‐1 inhibitors to chemotherapy or vaccination treatment in adult patients with unresectable cutaneous metastatic melanoma. Progression‐free survival (PFS) rate at 6 months was 28.5% versus 17.7% (RR: 0.84, 95% CI: 0.76–0.93), overall survival (OS) rate at 1 year was 51.2% versus 38.8% (RR: 0.72, 95% CI: 0.59–0.88), and overall response rate (ORR) at 6 months was 29.6% versus 17.7% (RR: 0.85, 95% CI: 0.76–0.95) favoring immune check point inhibitors over chemotherapies or vaccination. Immune check point inhibitors were associated with more frequent immune‐related adverse events at 13.7% versus 2.4% of treated patients (RR: 6.74, 95% CI: 4.65–9.75). Subgroup analyses demonstrated significant PFS (RR: 0.92 vs. 0.74, P < 0.00001) and ORR (RR: 0.95 vs. 0.76, P = 0.0004) improvement with anti‐PD‐1 treatment compared to anti‐CTLA‐4 when each of them was compared to control treatments. Collectively, these results demonstrate that immune checkpoint inhibitors have superior outcomes compared to conventional chemotherapies or vaccination, and support the results of recent randomized trials that showed superior outcomes with anti‐PD‐1 agents over ipilimumab in unresectable metastatic cutaneous melanoma patients.
A MT-NT-MILP combined method for gross error detection and data reconciliation

Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. In this paper, a MT-NT-MILP (MNM)combined method is developed for gross error detection and data reconciliation for industrial application. An improved MT-NT method is proposed in order to generate gross error candidates before data rectification. Candidates are used in the MILP objective function to improve the efficiency by reducing the number of binary variables. Simulation results show that the method is effective especially in a large-scale problem.
Energy/throughput trade-off in a fully asynchronous NoC for GALS-based MPSoC architectures

In this paper we evaluate the compromising effect of energy saving and throughput degradation on a fully asynchronous NoC architecture with regards to the dynamic voltage scaling guidelines. The investigated fully asynchronous NoC architecture is suitable for GALS-based MPSoCs architectures. The introduced architecture is simulated in 90nm CMOS technology with accurate Spice simulations, where the energy/throughput trade-off is reported and analyzed. Our results indicate that, although lower power may also be achieved by dynamic throughput scaling, this technique yields negligible energy saving for our asynchronous NoC. Therefore, we suggest a dynamic voltage scaling for this architecture which can save 40% energy at the expense of 13% throughput degradation.