Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta‐analysis of flow modeling performances—to build a matching system between catchment complexity and model types

Hydrological models play a significant role in modelling river flow for decision making support in water resource management. In the past decades, many researchers have made a great deal of efforts in calibrating and validating various models, with each study being focused on one or two models. As a result, there is a lack of comparative analysis on the performance of those models to guide hydrologists to choose appropriate models for the individual climate and physical conditions. This paper describes a two‐level meta‐analysis to develop a matching system between catchment complexity (based on catchment significant features (CSFs)) and model types. The intention is to use the available CSF information for choosing the most suitable model type for a given catchment. In this study, the CSFs include the elements of climate, soil type, land cover and catchment scale. Specific choices of model types in small and medium catchments are further explored with all CSF information obtained. In particular, it is interesting to find that semi‐distributed models are the most suitable model type for catchments with the area over 3000 km2, regardless of other CSFs. The potential methodology for expanding the matching system between catchment complexity and model complexity is discussed. Copyright © 2014 John Wiley & Sons, Ltd.
Ratiometric Imaging of pH Probes 23

Measurement of intracellular pH can be readily accomplished using tools and methods described in this chapter. We present a discussion of technical considerations of various ratiometric pH-sensitive probes including dyes and genetically encoded sensors. These probes can be used to measure pH across physical scales from macroscopic whole-mount tissues down to organelles and subcellular domains. We describe protocols for loading pH-sensitive probes into single cells or tissues and discuss ratiometric image acquisition and analysis.
Compact Optimal Quadratic Spline Collocation Methods for Poisson and Helmholtz Problems : Formulation and Numerical Verification

Optimal quadratic spline collocation (QSC) methods are developed for the numerical solution of Helmholtz and Poisson problems in the unit square subject to various combinations of non–homogeneous Dirichlet and Neumann boundary conditions (BCs), and periodic BCs. These methods are constructed so that the collocation equations can be solved using a matrix decomposition algorithm involving only tridiagonal linear systems whereas existing optimal QSC methods require the solution of pentadiagonal systems. The results of numerical experiments demonstrate the expected global accuracy of the methods as well as superconvergence phenomena.
Effect of ascorbic acid on reduced glutathione level in arsenic-loaded isolated liver tissues of rat

Isolated liver tissues of rat were loaded with trivalent arsenic and were exposed in presence and absence of ascorbic acid. The amount of reduced glutathione (GSH) in normal liver tissue was 52.0 ± 0.2 mg/g protein. Addition of arsenic to the tissues reduced the amount of GSH to 11.5 ± 0.3 mg/g protein. But when the arsenic loaded liver tissues were incubated with ascorbic acid at the concentration of 20 mg/mL, the amount of GSH was 14.2 ± 0.1 mg/g protein. There was 22.6% increase of GSH level which was statistically significant (p<0.001) when compared with arsenic alone. This study suggests that ascorbic acid increased the GSH level in arsenic-treated rat's liver.
Deep Recurrent Neural Networks for Multiple Language Aspect-Based Sentiment Analysis of User Reviews

Deep Recurrent Neural Networks (RNNs) are powerful sequence models applicable to modeling natural language. In this work we study applicability of different RNN architectures including uniand bi-directional Elman and Long Short-Term Memory (LSTM) models to aspect-based sentiment analysis that includes aspect terms extraction and aspect term sentiment polarity prediction tasks. We show that single RNN architecture without manual feature-engineering can be trained to do all these subtasks on English and Russian datasets. For aspect-term extraction subtask our system outperforms strong Conditional Random Fields (CRF) baselines and obtains stateof-the-art performance on Russian dataset. For aspect terms polarity prediction our results are below top-performing systems but still good for many practical applications.
Corruption, Crime and Economic Growth

The relationship between corruption, crime and economic growth seems obvious to most people. Both crime and corruption increase uncertainty and the cost of doing business, so crime and corruption must discourage entrepreneurial activities that cause growth. However, the relationship between crime and growth and corruption and growth is much more complex than it first appears. Scholars studying corruption have theorized both how corruption can reduce growth but also how it can increase growth, for example, by avoiding bureaucratic delays. The results of crosscountry empirical literature on the effect of corruption on growth are mixed. Recently a new literature has emerged controlling for the quality of institutions to examine the effect of corruption on growth. In the next section of this chapter we review the existing literature on corruption and growth, highlight some of the shortcomings in the literature, and then report on some of the newer studies that examine the interaction of institutions, corruption and growth. We believe this final strand of literature provides the most accurate view of how corruption impacts growth. High levels of crime can undermine the security of property rights and confidence in the rule of law. Both property rights and the rule of law have been illustrated to be vital for longrun economic growth. However, although there is a large literature on the cost of crime, we find almost no crosscountry evidence on the impact of crime on growth rates. This is for good reason. What is a crime in one society may not be a crime in another society, making it difficult to meaningfully compare many crime statistics across countries. Furthermore, crime, interpreted literally as breaking of government laws, could actually be growth enhancing in countries that have laws that prohibit capitalist acts between consenting adults. We review some of the existing literature on crime as it relates to growth in the third section of this chapter and then develop some suggestions for future research on the impact of crime on growth. The final section contains conclusions.
Air Fraction and EGR Proportion Control for Dual Loop EGR Diesel Engines 1 Control de la facción de aire fresco y proporción de EGR en motores Diesel de doble circuito de EGR 2

This paper describes a novel technique to control the air fraction in the intake of dual-loop exhaust gas recirculation (EGR) Diesel engines. This control strategy enables to efficiently regulate the air fraction while satisfying a desired EGR proportion (between low-pressure EGR and high-pressure EGR). Based on a modified physical model of the air fraction dynamics along the engine air-path, a linear parameter varying (LPV) linear quadratic regulator (LQR) control is designed to ensure the stability of the air fraction while minimizing a quadratic performance index. The controllability of the system, necessary for the LPV-LQR control design, is verified by defining a convex parameter set using a polytopic approach. The controller is evaluated under strong transient conditions using an engine model that has been experimentally validated as a reference.
Coherence analysis of EEG during cataplexy attacks in narcoleptic adult patients

Corresponding Author: F. İrsel Tezer E-mail: irseltezer@yahoo.com. tr ; irsel@hacettepe.edu. tr Submitted: 12 February 2018 Accepted: 28 May 2018 You may cite this article as: Erbil N, Tezer Fİ. Coherence analysis of EEG during cataplexy attacks in narcoleptic adult patients. Neurol Sci Neurophysiol 2018; 35(3): 119-126. Abstract Objective: Cataplexy is defined as episodes of sudden, transient loss of voluntary muscle tone usually triggered by positive emotional stimuli. Due to the triggering factors, involvement of emotion-processing structures such as the amygdala and limbic system was suggested. Although electrophysiologically hypersynchronous paroxysmal slow wave activities were reported during cataplexy attacks, the involved area was not clear. In this study we examined functional couplings by using coherence analysis to investigate electrophysiological data among the involved brain regions during cataplexy attacks in adult patients. Methods: Thirteen of our 31 patients with polysomnography recordings had type I narcolepsy. Seven emotionally triggered cataplectic attacks were recorded during monitoring in three patients. Spectral electroencephalography changes were analyzed and compared during whole attacks and interictal awakening periods with similar duration. The imaginary part of coherence for every electrode with other electrodes was also calculated respectively. Results: The coupling of slow waves increased in temporal regions during the attacks. Coherence between the right side of temporal regions and frontal areas increased in slower waves (<4 Hz). The coherence of other slow waves (4-7 Hz) was pronounced in the left temporal region with almost all over the cortex. Conclusion: Our electrophysiological findings related to the involvement of temporal and frontal lobes during cataplexy attacks supported previous neuroimaging and physiological reports. Further investigations to clarify the neural circuits involved in their manifestation should be considered in future.
Forward or Backward Looking? The Economic Discourse and the Observed Reality

Is academic research anticipating economic shake-ups or merely reflecting the past? Exploiting the corpus of articles published in the Journal of Economics and Statistics (Jahrbucher fur Nationalokonomie und Statistik) for the years 1949 to 2010, this pilot study proposes a quantitative framework for addressing these questions. The framework comprises two steps. First, methods from computational linguistics are used to identify relevant topics and their relative importance over time. In particular, Latent Dirichlet Analysis is applied to the corpus after some preparatory work. Second, for some of the topics which are closely related to specific economic indicators, the developments of topic weights and indicator values are confronted in dynamic regression and VAR models. The results indicate that for some topics of interest, the discourse in the journal leads developments in the real economy, while for other topics it is the other way round.
Different mechanisms of silicic acid leakage and their biogeochemical consequences

In the modern ocean, silicic acid is effectively trapped in the Southern Ocean. According to the silicic acid leakage hypothesis, a loosening of this trapping may have contributed to low atmospheric CO2 during glacial times. Using a model with dynamical feedbacks in ocean physics and biology, we explore three distinct mechanisms to loosen the trapping and trigger silicic acid leakage from the Southern Ocean: sea ice expansion, weaker winds, and iron addition. The basic idea of the iron addition mechanism was previously explored using a simple box model. Here we confirm the main results of the earlier work and demonstrate further that sea ice expansion and weaker southern westerlies can also trigger silicic acid leakage. The three mechanisms are not mutually exclusive, and their biogeochemical consequences are dissimilar in terms of the spatial patterns of Si:N uptake and the relative changes in opal and particulate organic carbon fluxes both in and outside the Southern Ocean. While it is not entirely clear how sea ice, winds, and iron deposition were different during the last glacial period compared to today, we examine the synergistic effects of these three triggers in one simulation. In this simulation, the combination of sea ice and iron reproduces the north-south dipole of productivity recorded in export production proxies, but effects of the iron perturbation seem to dominate the overall biogeochemical response.
Scale-Robust Localization Using General Object Landmarks

Visual localization under large changes in scale is an important capability in many robotic mapping applications, such as localizing at low altitudes in maps built at high altitudes, or performing loop closure over long distances. Existing approaches, however, are robust only up to about a 3x difference in scale between map and query images. We propose a novel combination of deep-learning-based object features and state-of-the-art SIFT point-features that yields improved robustness to scale change. This technique is training-free and class-agnostic, and in principle can be deployed in any environment out-of-the-box. We evaluate the proposed technique on the KITTI Odometry benchmark and on a novel dataset of outdoor images exhibiting changes in visual scale of 7×and greater, which we have released to the public. Our technique consistently outperforms localization using either SIFT features or the proposed object features alone, achieving both greater accuracy and much lower failure rates under large changes in scale.
The Relationship Between Coping Style, Depression and Stages of Change in Cardiac Rehabilitation Patients

Counseling Association by Dr. Garry R. Walz and Dr. Jeanne C. Bleuer of Counseling Outfitters, LLC. Its purpose is to provide a means of capturing the ideas, information and experiences generated by the annual ACA Conference and selected ACA Division Conferences. Papers on a program or practice that has been validated through research or experience may also be submitted. This digital collection of peer-reviewed articles is authored by counselors, for counselors. VISTAS Online contains the full text of over 500 proprietary counseling articles published from 2004 to present.
Snapshot-based navigation for the guidance of UAS

This paper presents a bio-inspired homing strategy applied to the guidance of rotorcraft unmanned aerial systems (UAS). In this approach, a sequence of panoramic snapshots is stored to build a visual route between the home and the goal locations. Navigation back to the initial location consists in reaching each of the memorised snapshot positions, by performing successive local homing steps. For that purpose, a snapshot-based method is used to estimate the rotorcraft’s 3D position and velocity in real-time. This algorithm provides a simple, yet efficient means for describing a visual route, and enabling 3D navigation of a smallsize quadrotor in unknown outdoor environments. Results from closed-loop flight experiments are presented to evaluate the performance of our approach.
Classification of Shoeprint Images Using Directional Filterbanks

With the abundance of evidence data collected from scenes of crime (SoC), shoeprint (or soleprint) traces usually constitute one of the hardest types of evidence for a criminal to remove before leaving the SoC. Traditional approaches to shoeprint representations attempt to classify shoeprint images based on a number of possible patterns. Such approaches are difficult to implement in an automatic fashion without the intervention of a forensic specialist. In this paper, the authors propose a fully-automated system to assist forensic specialists in rapidly classifying a shoeprint image found in a scene of crime (SoC). The proposed multiresolution-based system uses directional filter banks (DFBs) to capture both local and global details in a shoeprint in a compact representation called ShoeHash. Experimental results based on forensic shoeprint databases of more than 1000 images are presented to validate the effectiveness of the proposed system in extracting shoeprint features and achieving good performance.
Characterization of the Salmonella bacteriophage vB

The bacteriophage vB_SenS-Ent1 (Ent1) is a member of the family Siphoviridae of tailed bacteriophages and infects a broad range of serovars of the enteric pathogen Salmonella enterica. The virion particle is composed of an icosahedral head 64 nm in diameter and a flexible, non-contractile tail of 116 8.5 nm possessing terminal fibres. The adsorption rate constant at 37 6C is 6.73 10 ml min. Latent and eclipse periods are 25 and 20 min, respectively, and the burst size is 35 progeny particles per cell after 35 min at 37 6C. Sequencing revealed a circularly permuted, 42 391 bp dsDNA genome containing 58 ORFs organized into four major transcriptional units. Comparisons with the genome sequences of other bacteriophages revealed a high level of nucleotide sequence identity and shared orthologous proteins with the Salmonella phages SETP3, SE2 and KS7 (SS3e) and the Escherichia phages K1G, K1H, K1ind1 and K1ind3.
The Herschel-ATLAS Data Release 1 Paper II: Multi-wavelength counterparts to submillimetre sources

This paper is the second in a pair of articles presenting data release 1 (DR1) of the Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS), the largest single open-time key project carried out with the Herschel Space Observatory. The H-ATLAS is a wide-area imaging survey carried out in five photometric bands at 100, 160, 250, 350 and 500$\mu$m covering a total area of 600deg$^2$. In this paper we describe the identification of optical counterparts to submillimetre sources in DR1, comprising an area of 161 deg$^2$ over three equatorial fields of roughly 12$^\circ$x4.5$^\circ$ centred at 9$^h$, 12$^h$ and 14.5$^h$ respectively. Of all the H-ATLAS fields, the equatorial regions benefit from the greatest overlap with current multi-wavelength surveys spanning ultraviolet (UV) to mid-infrared regimes, as well as extensive spectroscopic coverage. We use a likelihood-ratio technique to identify SDSS counterparts at r<22.4 for 250-$\mu$m-selected sources detected at $\geq$ 4$\sigma$ ($\approx$28mJy). We find `reliable' counterparts (reliability R$\geq$0.8) for 44,835 sources (39 per cent), with an estimated completeness of 73.0 per cent and contamination rate of 4.7 per cent. Using redshifts and multi-wavelength photometry from GAMA and other public catalogues, we show that H-ATLAS-selected galaxies at $z<0.5$ span a wide range of optical colours, total infrared (IR) luminosities, and IR/UV ratios, with no strong disposition towards mid-IR-classified AGN in comparison with optical selection. The data described herein, together with all maps and catalogues described in the companion paper (Valiante et al. 2016), are available from the H-ATLAS website at www.h-atlas.org.
N ov 2 00 7 Deterministic distributed dense coding with stabilizer states

We consider the possibility of using stabilizer states to perform deterministic dense coding among multiple senders and a single receiver. In the model we studied, the utilized stabilizer state is partitioned into several subsystems and then each subsystem is held by a distinct party. We present a sufficient condition for a stabilizer state to be useful for deterministic distributed dense coding with respect to a given partition plan. The corresponding protocol is also constructed. Furthermore, we propose a method to partially solve a more general problem of finding the set of achievable alphabet sizes for an arbitrary stabilizer state with respect to an arbitrary partition plan. Finally, our work provides a new perspective from the stabilizer formalism to view the standard dense coding protocol and also unifies several previous results in a single framework.
Exploring new possible targets in Methamphetamine exposure

Methamphetamine (METH) is a highly addictive psychostimulant drug and one of the most abused worldwide. Drug addiction is considered a chronic and relapsing brain disease associated to severe systemic disorders, which raises relevant socio-economic and public health concerns. Although addicted individuals usually present severe pathophysiological conditions, addiction treatment is currently scant and the mechanisms by which addiction develops are still elusive. Therefore it is essential to explore these processes in order to find new possible therapeutic targets. METH in particular, leads to long-term dysfunction of dopaminergic and glutamatergic neurons, glial impairment and high oxidative stress. Interestingly, exposure to psychostimulants also affects neuronal morphology, increasing neurite length and dendritic spine density in several brain regions. To explore this issue, we conducted an RNAseq analysis from both soma and neurite fraction of cultured hippocampal neurons, which revealed differential expression patterns in numerous genes in METH exposed neurons. In a first step, we have selected genes differentially expressed in the soma, related to metabolism, cell signaling, cell cycle or transcription/transduction. We selected 5 genes that were likely to be related to neuroinflammation and neuron/glia interplay: Optineurin (Optn), Olfactomedin 4 (Olfm4), RAS guanyl releasing protein 1 (Rasgrp1), RelB Proto-Oncogene (RelB) and Early B-cell factor 3 (Ebf3). We conducted RT-qPCR to validate the expression of the selected candidates, and confirmed that upon exposure to METH the Olfm4 mRNA expression levels were significantly increased in primary cultures of hippocampal neurons. Protein expression was evaluated through western blot and immunocytochemistry, revealing that Olfm4 protein levels are decreased. Olfm4 is known to interact with integrins and metalloproteinases and has been linked to inflammatory processes. We have also analysed METH influence in inflammatory factors expression through RT-qPCR, but found no evidence of increased expression of neuroinflammatory factors. Moreover, we have assessed METH effect on extracellular matrix related proteins (Cldn5, ZO-1, MMP2, Src and RhoA) by western blot, immunocytochemistry, zymography and FRET assays. We show that METH does not affect Cldn5 or ZO-1 expression. Also, METH exposure does not appear to significantly affect MMP2 activity in neuronal cells, leading however to an increase in Src activation, while decreasing RhoA activation. Interestingly, Src activation appears to decrease when Olfm4 is knocked down. Overall, we did not observe an effect of METH in the expression of extracellular matrix related proteins in neuronal cells, nor evidence of its contribution for the neuroinflammatory process described for METH in humans and in vivo models. However, we x FCUP Exploring new possible targets in Methamphetamine exposure might have uncovered a new pathway, involving Src activation and consequent RhoA inactivation, which may contribute to the METH-induced neuronal morphological alterations.