Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of hydrological pathways on dissolved organic carbon fluxes in tropical streams

Abstract Water flow pathways and water balance are fundamental components for understanding the dynamics of C in the soil/water interface of small basins. The objective of this study was to describe the seasonal variations and estimate the annual balance of dissolved organic carbon (DOC) by comparing two tropical microbasins (preserved forest—PF and cacao plantation—CP). Twenty‐one weekly collections were conducted from September to December 2012 and from April to June 2013. The calculation of the partial balance considered precipitation (P) as inflow and the stream as outflow. The samples were filtered and analyzed using a TOC analyzer. Overall, the DOC was higher CP compared with FP. The behavior of both venues showed that rainy season caused an increase in concentrations in the overland flow (OF) and in the stream, and a decrease in the precipitation (P) and in the throughfall (T). In the CP, the outflow and the soil were chiefly responsible for the high DOC concentrations in the stream, when compared to the PF, which is the result of constant OM decomposition. Soil composition contributes to the control of DOC consumption in each type of soil. The balances were negative in both microbasins, although losses were higher in the AFS (agroforestry systems) when compared to the PF, especially during rainy seasons (−8.98 and −3.05 kg ha−1 year−1, CP and FP, respectively). Thus, the high annual loss of DOC in the CP of the microbasins during the rainy season indicates changes in ecosystem metabolism due to the vegetation cover and to the interactions with the soil.
A Negative Allosteric Modulator for α5 Subunit-Containing GABA Receptors Exerts a Rapid and Persistent Antidepressant-Like Action without the Side Effects of the NMDA Receptor Antagonist Ketamine in Mice

Abstract New antidepressant pharmacotherapies that provide rapid relief of depressive symptoms are needed. The NMDA receptor antagonist ketamine exerts rapid antidepressant actions in depressed patients but also side effects that complicate its clinical utility. Ketamine promotes excitatory synaptic strength, likely by producing high-frequency correlated activity in mood-relevant regions of the forebrain. Negative allosteric modulators of GABA-A receptors containing α5 subunits (α5 GABA-NAMs) should also promote high-frequency correlated electroencephalogram (EEG) activity and should therefore exert rapid antidepressant responses. Because α5 subunits display a restricted expression in the forebrain, we predicted that α5 GABA-NAMs would produce activation of principle neurons but exert fewer side effects than ketamine. We tested this hypothesis in male mice and observed that the α5 GABA-NAM MRK-016 exerted an antidepressant-like response in the forced swim test at 1 and 24 h after administration and an anti-anhedonic response after chronic stress in the female urine sniffing test (FUST). Like ketamine, MRK-016 produced a transient increase in EEG γ power, and both the increase in γ power and its antidepressant effects in the forced swim test were blocked by prior administration of the AMPA-type glutamate receptor antagonist 2,3-dioxo-6-nitro-1,2,3,4-tetrahydrobenzo[f]quinoxaline-7-sulfonamide (NBQX). Unlike ketamine, however, MRK-016 produced no impairment of rota-rod performance, no reduction of prepulse inhibition (PPI), no conditioned-place preference (CPP), and no change in locomotion. α5 GABA-NAMs, thus reproduce the rapid antidepressant-like actions of ketamine, perhaps via an AMPA receptor (AMPAR)-dependent increase in coherent neuronal activity, but display fewer potential negative side effects. These compounds thus demonstrate promise as clinically useful fast-acting antidepressants.
Extended Tidal Structure in Two Lyα-emitting Starburst Galaxies

We present new Very Large Array (VLA) C-configuration H I imaging of the Lyα-emitting starburst galaxies Tol 1924-416 and IRAS 08339+6517. The effective resolution probes neutral gas structures larger than 4.7 kpc in Tol 1924-416 and larger than 8.1 kpc in IRAS 08339+6517. Both systems are revealed to be tidally interacting: Tol 1924-416 with ESO 338-IG04B (6.′6 = 72 kpc minimum separation), and IRAS 08339+6517 with 2MASX J08380769+6508579 (2.′4 = 56 kpc minimum separation). The H I emission is extended in these systems, with tidal tails and debris between the target galaxies and their companions. Since Lyα emission has been detected from both of these primary systems, these observations suggest that the geometry of the interstellar medium is one of the factors affecting the escape fraction of Lyα emission from starburst environments. Furthermore, these observations argue for the importance of interactions in triggering massive star formation events.
The Role of Absorptive Capacity in the Usage of a Complex Information System: The Case of the Enterprise Information System

The purpose of this study is to model the relationship between absorptive capacity and intention to use in the Enterprise Resource Planning (ERP) environment in Iran. This research is a correlation study where a field survey was employed for data collection. The unit of analysis is Iranian individuals who are ERP user in organizations using ERP systems. The questionnaires were sent to the selected organizations. Using a structural equation modeling analysis we tested the hypothesized relationship using AMOS version 16.0. The results indicate that all three absorptive capacity measures to be good predictors of intention to use. Absorptive capacity for applying was the strongest predictor followed by absorptive capacity for understanding and absorptive capacity for assimilating. When implementing complex information systems, managers must also look at the absorptive capacity of the users in order to successful implementation of the system and to ensure continued usage. Previous researchers have not looked at the role of absorptive capacity in system usage at the same rate as those related to technology acceptance research which only focuses on the ease of use and usefulness. Thus this research adds on to the existing literature where future researchers may want to expand on the factors that may influence absorptive capacity for further policy implications.
Sample-Specific SVM Learning for Person Re-identification

Person re-identification addresses the problem of matching people across disjoint camera views and extensive efforts have been made to seek either the robust feature representation or the discriminative matching metrics. However, most existing approaches focus on learning a fixed distance metric for all instance pairs, while ignoring the individuality of each person. In this paper, we formulate the person re-identification problem as an imbalanced classification problem and learn a classifier specifically for each pedestrian such that the matching model is highly tuned to the individual's appearance. To establish correspondence between feature space and classifier space, we propose a Least Square Semi-Coupled Dictionary Learning (LSSCDL) algorithm to learn a pair of dictionaries and a mapping function efficiently. Extensive experiments on a series of challenging databases demonstrate that the proposed algorithm performs favorably against the state-of-the-art approaches, especially on the rank-1 recognition rate.
Motion-based video retargeting with optimized crop-and-warp

We introduce a video retargeting method that achieves high-quality resizing to arbitrary aspect ratios for complex videos containing diverse camera and dynamic motions. Previous content-aware retargeting methods mostly concentrated on spatial considerations, attempting to preserve the shape of salient objects in each frame by removing or distorting homogeneous background content. However, sacrificeable space is fundamentally limited in video, since object motion makes foreground and background regions correlated, causing waving and squeezing artifacts. We solve the retargeting problem by explicitly employing motion information and by distributing distortion in both spatial and temporal dimensions. We combine novel cropping and warping operators, where the cropping removes temporally-recurring contents and the warping utilizes available homogeneous regions to mask deformations while preserving motion. Variational optimization allows to find the best balance between the two operations, enabling retargeting of challenging videos with complex motions, numerous prominent objects and arbitrary depth variability. Our method compares favorably with state-of-the-art retargeting systems, as demonstrated in the examples and widely supported by the conducted user study.
Organismal climatology: analyzing environmental variability at scales relevant to physiological stress

SUMMARY Predicting when, where and with what magnitude climate change is likely to affect the fitness, abundance and distribution of organisms and the functioning of ecosystems has emerged as a high priority for scientists and resource managers. However, even in cases where we have detailed knowledge of current species' range boundaries, we often do not understand what, if any, aspects of weather and climate act to set these limits. This shortcoming significantly curtails our capacity to predict potential future range shifts in response to climate change, especially since the factors that set range boundaries under those novel conditions may be different from those that set limits today. We quantitatively examine a nine-year time series of temperature records relevant to the body temperatures of intertidal mussels as measured using biomimetic sensors. Specifically, we explore how a ‘climatology’ of body temperatures, as opposed to long-term records of habitat-level parameters such as air and water temperatures, can be used to extrapolate meaningful spatial and temporal patterns of physiological stress. Using different metrics that correspond to various aspects of physiological stress (seasonal means, cumulative temperature and the return time of extremes) we show that these potential environmental stressors do not always occur in synchrony with one another. Our analysis also shows that patterns of animal temperature are not well correlated with simple, commonly used metrics such as air temperature. Detailed physiological studies can provide guidance to predicting the effects of global climate change on natural ecosystems but only if we concomitantly record, archive and model environmental signals at appropriate scales.
Special Issue on University Entrepreneurship and Technology Transfer: Selling University Technology: Patterns from MIT

Many research universities engage in efforts to license inventions developed by university-affiliated inventors. However, no systematic explanation of the conditions under which university inventions will be licensed or commercialized has been provided. Drawing on transaction cost economics, I provide a conceptual framework to explain which university inventions are most likely to be licensed, commercialized, and generate royalties, and who will undertake that commercialization. I test this framework on data on the 1,397 patents assigned to the Massachusetts Institute of Technology during the 1980-1996 period. The results showthat (1) university inventions are more likely to be licensed when patents are effective; (2) when patents are effective, university technology is generally licensed to noninventors; (3) when patents are effective, licensing back to inventors increases the likelihood of license termination and reduces the likelihood of invention commercialization; and (4) the effectiveness of patents increases royalties earned for inventions licensed to noninventors. The implications of these findings for innovation management and strategy, entrepreneurship, and university technology commercialization are discussed.
Blood Pressure, Sleep Quality and Fatigue in Shift Working Police Officers: Effects of a Twelve Hour Roster System on Cardiovascular and Sleep Health

Background: Police officers have been reported to exhibit a high incidence of pathologies, which present prematurely in an otherwise healthy population. Shift work has also been associated with an increased risk of cardiovascular and sleep disorders, attributable to its propensity for circadian rhythm dysfunction. However, contention exists as to whether shift work has a direct effect upon blood pressure (BP) regulation. Methods: This cross-sectional study sought to determine changes in BP and associations with the overall sleep quality and fatigue in 206 general duties police officers (n = 140 males) of the New South Wales Police Force in Australia. The subjects’ BP was assessed before and after their twelve hour shift, during which time they also completed the Lifestyle Appraisal Questionnaire, Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale and Fatigue Severity Scale (FSS). Results: Poor sleep quality (PSQI) and fatigue severity (FSS) were found to predominate in the sample (69% and 51% respectively). Although there was no change in BP for male participants, female officers’ systolic blood pressure (SBP) was found to increase significantly across the shift (p < 0.001), but with no change found in females’ diastolic blood pressure (DBP). Finally, higher pre and post-shift SBP (r = −0.26, p = 0.001; r = −0.25, p = 0.001, respectively) and DBP (r = −0.26, p = 0.001; r = −0.26, p = 0.001, respectively) were significantly correlated with lower FSS scores after accounting for age, waist-hip ratio and lifestyle risk factors. Conclusions: Based on these preliminary findings, there was a significant increase in SBP of female police officers after shift work, while BP and fatigue levels in all police officers were strongly related. Moreover, the predominating poor sleep quality and impact of fatigue in this sample remain a concern. Further research is required to ensure the physiological welfare of police officers, while strategies must be implemented to manage the detrimental effects shift work may be having upon their cardiovascular and sleep health.
A Consumption CAPM with a Reference Level ¤ Ren

We study an intertemporal asset pricing model in which a representative consumer maximizes expected utility derived from both the ratio of his consumption to some reference level and this level itself. If the reference consumption level is assumed to be determined by past consumption levels, the model generalizes the usual habit formation speci ̄cations. When the reference level growth rate is correlated with the market portfolio return, the model mixes a consumption CAPM with habit formation together with the CAPM. It therefore provides, in an expected utility framework, a generalization of the non-expected utility model of Epstein and Zin (1989). The empirical tests of the model with aggregate consumption per capita result in estimating economically plausible values of the preference parameters, in contrast with the particular cases of the habit formation approach and the Epstein-Zin non-expected utility function. All tests with various speci ̄cations of the preferences con ̄rm that the reference level enters signi ̄cantly in the pricing kernel. JEL classi ̄cation: G12
Bootstrap Confidence Regions for the Intensity of a Poisson Point Process

Abstract Bootstrap methods are developed for constructing confidence regions for the intensity function of a nonstationary Poisson process. Several different resampling algorithms are suggested, ranging from resampling a Poisson process with intensity equal to that estimated nonparametrically from the data to resampling the data points themselves in the same manner that the bootstrap is used in problems involving independent and identically distributed observations. For each different bootstrap method, various percentile-t ways of constructing confidence bands are described. The effectiveness of these different approaches is demonstrated both theoretically and numerically, for real and simulated data. Issues such as bias correction are addressed.
What Doesn’t Get Measured Does Exist: Improving the Accuracy of Computer-Aided Text Analysis

Computer-aided text analysis (CATA) is a form of content analysis that enables the measurement of constructs by processing text into quantitative data based on the frequency of words. CATA has been proposed as a useful measurement approach with the potential to lead to important theoretical advancements. Ironically, while CATA has been offered to overcome some of the known deficiencies in existing measurement approaches, we have lagged behind in regard to assessing the technique’s measurement rigor. Our article addresses this knowledge gap and describes important implications for past as well as future research using CATA. First, we describe three sources of measurement error variance that are particularly relevant to studies using CATA: transient error, specific factor error, and algorithm error. Second, we describe and demonstrate how to calculate measurement error variance with the entrepreneurial orientation, market orientation, and organizational ambidexterity constructs, offering evidence that past substantive conclusions have been underestimated. Third, we offer best-practice recommendations and demonstrate how to reduce measurement error variance by refining existing CATA measures. In short, we demonstrate that although measurement error variance in CATA has not been measured thus far, it does exist and it affects substantive conclusions. Consequently, our article has implications for theory and practice, as well as how to assess and minimize measurement error in future CATA research with the goal of improving the accuracy of substantive conclusions.
Improved Variance Estimation for Fully Synthetic Datasets

Fully synthetic datasets, i.e. datasets that only contain simulated values, arguably provide a very high level of data protection. Since all values are simulated reidentification is almost impossible. This makes the approach especially attractive for the release of very sensitive data such as medical records. However, the established variance estimate for fully synthetic datasets has two major drawbacks. First, it can be positively biased, where the bias is a function of the sampling rate of the original data. Second, it can become negative. In this paper I illustrate the negative effects of these drawbacks on the estimation of the variance and propose an alternative variance estimate that shows less variability, is always unbiased, and can never be negative. This variance estimate is closely related to the variance estimate for partially synthetic datasets.
Computing in Distributed Systems in the Presence of Benign Failures

In this work, we question these two basic principles of fault-tolerant distributed computing that have gained the status of dogmas, and show that it is both possible and worthy to renounce them in the context of benign failures: we present a computational model, suitable for systems with benign failures, which is based only on the notion of transmission failure. The new idea in our model is to study round-based computations and abstract away the implementation of the communication exchange between processes, be it shared memory, message-passing, or any other mechanism. In the whole paper, we call “messages” the pieces of information that are exchanged, whatever the medium of communication is. In each round, a process emits messages to the other processes, waits to receive messages from some processes, and then computes a new state. Every message received at some round must have been sent at that round. Consequently, any message missed at a round is definitely discarded. Using the terminology of Elrad and Francez [14], a round is a communication-closed layer. Most of the fault-tolerant distributed algorithms that have been designed for synchronous systems, or for partially synchronous or asynchronous ones, are structured in rounds (e.g., [12, 1, 13, 9, 4]). However, concerning impossibility results (lower bounds, non-solvability, . . . ), round-based computational models have been considered almost always for synchronous systems. The reason for that lies in the fact that it is an open question whether round-based models are equivalent to the ones in which late messages are not discarded. To the best of our knowledge, Dwork, Lynch, and Stockmeyer [13] were the first to define a round-based model for non synchronous computing. More precisely, they generalized the classical round-based computational model for synchronous systems to a large class of partially synchronous systems. Then Gafni [16] extended the round-based model to any type of systems. The basic idea in his model is to capture the properties of the communication mechanisms and of the system guarantees as a whole by a single module that is called Round-by-Round Failure Detector (for short RRFD) module. More precisely, at each round r and for each process p, the module provides a set of suspected processes from which p will
Comments on GP-ASG-RS-0001 implementation analysis OBD-CoCo-06

This document summarises the feedback of the On-Board Detection Working Group to the preliminary requirement analysis reported in GP-ASG-RS-0001[Ast03b]. The group expresses questions, comments and concerns regarding the implementation of a modified scheme which deviates significantly from the baseline provided as input. Its preoccupations are connected to the fulfilling of the scientific requirements, as expressed in [Hø03], and to associated development risks.
Random Walks on Graphs for Salient Object Detection in Images

We formulate the problem of salient object detection in images as an automatic labeling problem on the vertices of a weighted graph. The seed (labeled) nodes are first detected using Markov random walks performed on two different graphs that represent the image. While the global properties of the image are computed from the random walk on a complete graph, the local properties are computed from a sparse k-regular graph. The most salient node is selected as the one which is globally most isolated but falls on a locally compact object. A few background nodes and salient nodes are further identified based upon the random walk based hitting time to the most salient node. The salient nodes and the background nodes will constitute the labeled nodes. A new graph representation of the image that represents the saliency between nodes more accurately, the “pop-out graph” model, is computed further based upon the knowledge of the labeled salient and background nodes. A semisupervised learning technique is used to determine the labels of the unlabeled nodes by optimizing a smoothness objective label function on the newly created “pop-out graph” model along with some weighted soft constraints on the labeled nodes.
Rabies Virus-Induced Membrane Fusion Pathway

Fusion of rabies virus with membranes is triggered at low pH and is mediated by the viral glycoprotein (G). The rabies virus-induced fusion pathway was studied by investigating the effects of exogenous lipids having various dynamic molecular shapes on the fusion process. Inverted cone-shaped lysophosphatidylcholines (LPCs) blocked fusion at a stage subsequent to fusion peptide insertion into the target membrane. Consistent with the stalk-hypothesis, LPC with shorter alkyl chains inhibited fusion at lower membrane concentrations and this inhibition was compensated by the presence of oleic acid. However, under suboptimal fusion conditions, short chain LPCs, which were translocated in the inner leaflet of the membranes, considerably reduced the lag time preceding membrane merging, resulting in faster kinetics of fusion. This indicated that the rate limiting step for fusion is the formation of a fusion pore in a diaphragm of restricted hemifusion. The previously described cold-stabilized prefusion complex was also characterized. This intermediate is at a well-advanced stage of the fusion process when the hemifusion diaphragm is destabilized, but lipid mixing is still restricted, probably by a ring-like complex of glycoproteins. I provide evidence that this state has a dynamic character and that its lipid organization can reverse back to two lipid bilayers.