Miracle-dz/UniFAR-FTUs huggingface dataset:
Animal and human models for sepsis

Several preclinical models for sepsis have been used in the last decades to successfully unravel the pathophysiologic processes during sepsis. Furthermore, these models for sepsis revealed promising immunomodulating agents for the treatment of sepsis. Nevertheless, several clinical trials evaluating the efficacy of these new anti-inflammatory agents in septic patients showed disappointing results. In this article the advantages and disadvantages of different models for sepsis are discussed. Most models for sepsis lack an infectious focus. Importantly, investigations studying the effects of several immunomodulating strategies have demonstrated strikingly opposite results when using models for sepsis lacking an infectious focus and when using models for sepsis with a more natural route of infection. These differences will be discussed in this article. In general, it is advised to use a combination of models to test a new therapeutic agent, before starting a clinical study evaluating this new therapy.
Group III Histidine Kinase Is a Positive Regulator of Hog1-Type Mitogen-Activated Protein Kinase in Filamentous Fungi

ABSTRACT We previously reported that the group III histidine kinase Dic1p in the maize pathogen Cochliobolus heterostrophus is involved in resistance to dicarboximide and phenylpyrrole fungicides and in osmotic adaptation. In addition, exposure to the phenylpyrrole fungicide fludioxonil led to improper activation of Hog1-type mitogen-activated protein kinases (MAPKs) in some phytopathogenic fungi, including C. heterostrophus. Here we report, for the first time, the relationship between the group III histidine kinase and Hog1-related MAPK: group III histidine kinase is a positive regulator of Hog1-related MAPK in filamentous fungi. The phosphorylation pattern of C. heterostrophus BmHog1p (Hog1-type MAPK) was analyzed in wild-type and dic1-deficient strains by Western blotting. In the wild-type strain, phosphorylated BmHog1p was detected after exposure to both iprodione and fludioxonil at a concentration of 1 μg/ml. In the dic1-deficient strains, phosphorylated BmHog1p was not detected after exposure to 10 μg/ml of the fungicides. In response to osmotic stress (0.4 M KCl), a trace of phosphorylated BmHog1p was found in the dic1-deficient strains, whereas the band representing active BmHog1p was clearly detected in the wild-type strain. Similar results were obtained for Neurospora crassa Os-2p MAPK phosphorylation in the mutant of the group III histidine kinase gene os-1. These results indicate that group III histidine kinase positively regulates the activation of Hog1-type MAPKs in filamentous fungi. Notably, the Hog1-type MAPKs were activated at high fungicide (100 μg/ml) and osmotic stress (0.8 M KCl) levels in the histidine kinase mutants of both fungi, suggesting that another signaling pathway activates Hog1-type MAPKs in these conditions.
Smile and Punishment

Are people who display a positive nonverbal expression treated more leniently after committing a transgression? The present study evaluated the effects of facial expression (positive vs. neutral), seriousness of transgression (serious vs. non-serious), sex of offender, and the decision-making unit (individuals vs. groups) on decisions about guilt, punishment, and the overall impressions formed of the target person. Subjects (N = 217) read descriptions of a severe or nonsevere transgression and were shown a photograph of the offender (male or female) displaying positive (smiling) or neutral nonverbal expression. They rated the target on 13 scales, and later they were asked to discuss the case as a group and to arrive at consensus judgments. Results showed that (a) smiling targets were treated more leniently, particularly when the transgression was a minor one, and (b) following a group discussion to consensus, judgments became more extreme than the initial individual judgments. These results are discussed in terms of their implications for nonverbal communication in real-life situations, and their relevance to current work on responsibility attribution and group-induced opinion shifts is considered.
Protein astrogliopathies in human neurodegenerative diseases and aging

Neurodegenerative diseases are characterized by progressive dysfunction and loss of neurons associated with depositions of pathologically altered proteins showing hierarchical involvement of brain regions. The role of astrocytes in the pathogenesis of neurodegenerative diseases is explored as contributors to neuronal degeneration or neuroprotection pathways, and also as potential mediators of the transcellular spreading of disease‐associated proteins. Protein astrogliopathy (PAG), including deposition of amyloid‐β, prion protein, tau, α‐synuclein, and very rarely transactive response DNA‐binding protein 43 (TDP‐43) is not unprecedented or unusual in neurodegenerative diseases. Morphological characterization of PAG is considered, however, only for the neuropathological diagnosis and classification of tauopathies. Astrocytic tau pathology is seen in primary frontotemporal lobar degeneration (FTLD) associated with tau pathologies (FTLD‐Tau), and also in the form of aging‐related tau astrogliopathy (ARTAG). Importantly, ARTAG shares common features with primary FTLD‐Tau as well as with the astroglial tau pathologies that are thought to be hallmarks of a brain injury‐related tauopathy known as chronic traumatic encephalopathy (CTE). Supported by experimental observations, the morphological variability of PAG might reflect distinct pathogenic involvement of different astrocytic populations. PAG might indicate astrocytic contribution to spreading or clearance of disease‐associated proteins, however, this might lead to astrocytic dysfunction and eventually contribute to the degeneration of neurons. Here, we review recent advances in understanding ARTAG and other related forms of PAG.
TRANSLATING LEGAL SENTENCE BY SEGMENTATION AND RULE SELECTION

A legal text usually long and complicated, it has some characteristic that make it different from other daily use texts.Then, translating a legal text is generally considered to be difficult. This pa per introduces an approach to split a legal sentence based on its logical structure and presents selecting appropriate translation rules to improve phrase reordering of legal translation. We use a method which divides a English legal sentence based on its logical structure to segment the legal sentence. New features with rich linguistic and contextual information of split sentences are proposed to rule selection. We apply maximum entropy to combine rich linguistic and contextual information and integrate the features of split sentences into the legal translation, tree-based SMT system. We obtain improvements in performance for legal translation from English to Japanese over Moses and Moses -chart systems.
Experiencing Diversity, Conflict, and Emotions in Teams

Diversity in teams has been previously defined in terms of the nominal categories into which team members "fall". The core argument of this paper is that diversity is a subjective experience of social categories to which members "feel" they belong. These categories, or social identities, may become more or less salient in different contexts and at different times. We propose a model of diversity in teams that explains under what conditions these social identities become salient and how these social identities may influence appraisals of issues and events. These appraisals, in turn, can influence conflict and emotion. This dynamic view of diversity provides us with a better understanding of the "black box" -- the cognitive and affective processes that may help to explain behavior and subsequently team performance.
Fitting Surface of Free Form Objects using Optimized NURBS Patches Network with Evolutionary Strategies (mu + lambda) - ES

We propose an algorithm to produce a 3-D CAD model from a set of range data, based on non-uniform rational B-splines (NURBS) surface fitting technique. Our goal is to construct continuous geometric models, assuming that the topology of surface is unknown. In our approach, the triangulated surface is partitioned in quadrilateral patches, using Morse theory. The quadrilateral obtained mesh is regularized by means of the use of geodesic curves and B-splines to obtain a new adequate grid on which to draw NURBS surfaces. Such NURBS surfaces are optimized by means of evolutionary strategies. Further, the patches are smoothly joined guaranteeing continuity C 1 .
Alcohol Outcome Expectancies: Scale Construction and Predictive Utility in Higher Order Confirmatory Models

The goals of this research were to develop a scale to measure alcohol outcome expectancies that incorporated important features suggested by previous research; to examine the psychometric properties of the instrument, with particular attention to item discrimination; and to examine the relationship of positive and negative expectancy to self-reported alcohol use. In Study 1, a preliminary expectancy scale was constructed; factor analysis showed 2 general constructs representing positive and negative consequences of drinking. In Study 2, the scale was refined through tests of item discrimination and was used to predict alcohol use using structural equation modeling
Separating succinct non-interactive arguments from all falsifiable assumptions

An argument system for NP is succinct, if its communication complexity is polylogarithmic the instance and witness sizes. The seminal works of Kilian '92 and Micali '94 show that such arguments can be constructed under standard cryptographic hardness assumptions with four rounds of interaction, and that they be made non-interactive in the random-oracle model. However, we currently do not have any construction of succinct non-interactive arguments (SNARGs) in the standard model with a proof of security under any simple cryptographic assumption. In this work, we give a broad black-box separation result, showing that black-box reductions cannot be used to prove the security of any SNARG construction based on any falsifiable cryptographic assumption. This includes essentially all common assumptions used in cryptography (one-way functions, trapdoor permutations, DDH, RSA, LWE etc.). More generally, we say that an assumption is falsifiable if it can be modeled as an interactive game between an adversary and an efficient challenger that can efficiently decide if the adversary won the game. This is similar, in spirit, to the notion of falsifiability of Naor '03, and captures the fact that we can efficiently check if an adversarial strategy breaks the assumption. Our separation result also extends to designated verifier SNARGs, where the verifier needs a trapdoor associated with the CRS to verify arguments, and slightly succinct SNARGs, whose size is only required to be sublinear in the statement and witness size.
Phosphate-Responsive Promoter of a Pichia pastoris Sodium Phosphate Symporter

ABSTRACT To develop a functional phosphate-regulated promoter in Pichia pastoris, a phosphate-responsive gene, PHO89, which encodes a putative sodium (Na+)-coupled phosphate symporter, was isolated. Sequencing analyses revealed a 1,731-bp open reading frame encoding a 576-amino-acid polypeptide with 12 putative transmembrane domains. The properties of the PHO89 promoter (PPHO89) were investigated using a bacterial lipase gene as a reporter in 5-liter jar fermentation experiments. PPHO89 was tightly regulated by phosphate and was highly activated when the cells were grown in a phosphate-limited external environment. Compared to translation elongation factor 1α and the glyceraldehyde-3-phosphate dehydrogenase promoter, PPHO89 exhibited strong transcriptional activity with higher specific productivity (amount of lipase produced/cell/h). Furthermore, a cost-effective and simple PPHO89-based fermentation process was developed for industrial application. These results demonstrate the potential for efficient use of PPHO89 for controlled production of recombinant proteins in P. pastoris.
The effect of depth jumps and weight training on leg strength and vertical jump

Abstract In recent years, a method of plyometrics (exercises that cause a rapid lengthening of a muscle prior to contraction) called depth jumping has become a part of the training routine of many athletes. Two experiments are described in which the effectiveness of the exercises is examined. In Experiment 1, undergraduate students in beginning weight training classes trained with three different jumping programs: (1) maximum vertical jumps, (2) 0.3 m depth jumps, and (3) 0.75 m and 1.10 m depth jumps. In addition, all groups also lifted weights. In Experiment 2, a weight training class and the volleyball team at Brigham Young University-Hawaii were divided into two groups. One group lifted weights and performed 0.75 and 1.10 m depth jumps. The other group only lifted weights. In Experiment 1, the three training programs resulted in increases in one repetition maximum (1 RM) squat strength, isometric knee extension strength, and in vertical jump; however, there were no significant differences between trea.
LTE-Advanced: Heterogeneous networks

Long-Term Evolution (LTE) allows operators to use new and wider spectrum and complements 3G networks with higher data rates, lower latency and a flat IP-based architecture. To further improve broadband user experience in a ubiquitous and cost effective manner, 3GPP has been working on various aspects in the framework of LTE Advanced. Since radio link performance is approaching theoretical limits with 3G enhancements and LTE, the next performance leap in wireless networks will come from the network topology. LTE Advanced is about improving spectral efficiency per unit area. Using a mix of macro, pico, femto and relay base-stations, heterogeneous networks enable flexible and low-cost deployments and provide a uniform broadband experience to users anywhere in the network. This paper discusses the need for an alternative deployment model or topology using heterogeneous networks. To enhance the performance of these networks, advanced techniques are described which are needed to manage and control interference and deliver the full benefits of such networks. Range extension allows more user terminals to benefit directly from low-power base-stations such as picos, femtos, and relays. Adaptive inter-cell interference coordination provides smart resource allocation amongst interfering cells and improves inter-cell fairness in a heterogeneous network. In addition, the performance gains with heterogeneous networks using an example macro/pico network are shown.
High-Gain S-band Patch Antenna System for Earth-Observation CubeSat Satellites

A novel S-band circularly polarized patch antenna system suited for earth-observing CubeSats is presented. The antenna consists of four rectangular patches properly excited in order to have the maximum gain in the boresight direction and produce circular polarization. The antenna has a compact size, and its geometry and characteristics are compatible with any CubeSat standard structure. A 57-mm-wide square window allows to accommodate imaging system optics in its center leading to a very compact overall system. A prototype of the designed antenna system has been used to validate simulation results that showed a gain of 7.3 dBi. Experimental measurements confirm that the antenna achieves good impedance match at the desired frequency of 2450 MHz, a directivity of 8.3 dBi, and 60° 3-dB beamwidth, in good agreement with the simulation results.
A Novel Approach for Retrieving Tree Leaf Area from Ground-Based LiDAR

Leaf area is an important plant canopy structure parameter with important ecological significance. Light detection and ranging technology (LiDAR) with the application of a terrestrial laser scanner (TLS) is an appealing method for accurately estimating leaf area; however, the actual utility of this scanner depends largely on the efficacy of point cloud data (PCD) analysis. In this paper, we present a novel method for quantifying total leaf area within each tree canopy from PCD. Firstly, the shape, normal vector distribution and structure tensor of PCD features were combined with the semi-supervised support vector machine (SVM) method to separate various tree organs, i.e., branches and leaves. In addition, the moving least squares (MLS) method was adopted to remove ghost points caused by the shaking of leaves in the wind during the scanning process. Secondly, each target tree was scanned using two patterns, i.e., one scan and three scans around the canopy, to reduce the occlusion effect. Specific layer subdivision strategies according to the acquisition ranges of the scanners were designed to separate the canopy into several layers. Thirdly, 10% of the PCD was randomly chosen as an analytic dataset (ADS). For the ADS, an innovative triangulation algorithm with an assembly threshold was designed to transform these discrete scanning points into leaf surfaces and estimate the fractions of each foliage surface covered by the laser pulses. Then, a novel ratio of the point number to leaf area in each layer was defined and combined with the total number of scanned points to retrieve the total area of the leaves in the canopy. The quantified total leaf area of each tree was validated using laborious measurements with a LAI-2200 Plant Canopy Analyser and an LI-3000C Portable Area Meter. The results showed that the individual tree leaf area was accurately reproduced using our method from three registered scans, with a relative deviation of less than 10%. Nevertheless, estimations from only one scan resulted in a deviation of >25% in the retrieved individual tree leaf area due to the occlusion effect. Indeed, this study provides a novel connection between leaf area estimates and scanning sensor configuration and supplies an interesting method for estimating leaf area based on PCD.
A New Approach for Retaining Mercury in Energy Generation Processes: Regenerable Carbonaceous Sorbents

The energy production processes from fossil fuels represent the first anthropogenic source of mercury emissions in Europe and the second in the world. Among the different possibilities that can be posed to reduce these emissions, this work focuses on the use of regenerable sorbents based on gold nanoparticles dispersed on activated carbon foam. The use of regenerable sorbents would not only allow the objective of reducing mercury emissions, but also avoiding the generation of new toxic wastes. The results showed a retention efficiency of 100% and a retention capacity close to 600 µg·g−1 over several cycles of regeneration. Moreover, acid gases did not poison the support. It was observed that mercury capture in this simulated oxy-combustion atmosphere was a consequence of two mechanisms: (1) the amalgamation of elemental mercury and elemental gold and (2) the oxidation of elemental mercury in the presence of HCl, with the subsequent retention of the oxidized mercury on the surface of the activated carbon foam. The nanodispersion of gold on such supports involves a high initial investment. However, this would be counterbalanced by the remarkable regeneration capacity of the sorbent and the possibility of recovering all the materials used.
The rate of functional recovery from acute IOP elevation.

PURPOSE To evaluate the recovery of retinal function after acute IOP elevation. METHODS The electroretinogram (ERG) was measured before, during, and after IOP increased to 50 and 70 mm Hg at different durations in anesthetized, dark-adapted rats (n = 5-7). Signals were collected for dim and bright flashes (-4.95 and 1.0 log cd . s/m(2)) and analyzed in terms of the photoreceptoral (P3), postreceptoral (P2), and inner retinal (negative scotopic threshold response [nSTR]) responses. Parameters (treatment/baseline, %) were compared across time by using repeated-measures ANOVA and t-tests. The rate of recovery was quantified with a logistic function and compared by bootstrap. RESULTS IOP spikes induce greater loss (P < 0.01) and slower recovery (P < 0.001) in the nSTR compared with the P2 and P3 responses. IOP spikes having common integral (pressure x duration, 2100 mm Hg x minutes) for insult gave significantly greater P2 and nSTR dysfunction at the higher pressure (70 vs. 50 mm Hg, nSTR reduced to -2.5% +/- 0.5% vs. 20.3% +/- 6.5%, P < 0.05). The higher pressure also produced significantly slower nSTR recovery (50% recovery time [t(0.5)] 70 vs. 50 mm Hg: 33.1 vs. 21.7 minutes; P < 0.05). At a given IOP (70 mm Hg), t(0.5) showed a linear relationship with duration (15 vs. 30 vs. 60 minutes' exposure: t(0.5) 16.7 vs. 33.1 vs. 63.2 minutes; P < 0.05) and integral. CONCLUSIONS Ganglion cell function recovers slower than the outer retina after IOP insult, with peak IOP being the principle determinant of functional loss and recovery. For a fixed pressure, functional recovery is linearly related to exposure.
An Algorithm for Emulsion Stability Simulations: Account of Flocculation, Coalescence, Surfactant Adsorption and the Process of Ostwald Ripening

The first algorithm for Emulsion Stability Simulations (ESS) was presented at the V Conferencia Iberoamericana sobre Equilibrio de Fases y Diseño de Procesos [Luis, J.; García-Sucre, M. ; Urbina-Villalba, G. Brownian Dynamics Simulation of Emulsion Stability In: Equifase 99. Libro de Actas, 1st Ed., Tojo J., Arce, A. , Eds.; Solucion’s: Vigo, Spain, 1999; Volume 2, pp. 364–369]. The former version of the program consisted on a minor modification of the Brownian Dynamics algorithm to account for the coalescence of drops. The present version of the program contains elaborate routines for time-dependent surfactant adsorption, average diffusion constants, and Ostwald ripening.
Gene Regulatory Networks from Multifactorial Perturbations Using Graphical Lasso: Application to the DREAM4 Challenge

A major challenge in the field of systems biology consists of predicting gene regulatory networks based on different training data. Within the DREAM4 initiative, we took part in the multifactorial sub-challenge that aimed to predict gene regulatory networks of size 100 from training data consisting of steady-state levels obtained after applying multifactorial perturbations to the original in silico network. Due to the static character of the challenge data, we tackled the problem via a sparse Gaussian Markov Random Field, which relates network topology with the covariance inverse generated by the gene measurements. As for the computations, we used the Graphical Lasso algorithm which provided a large range of candidate network topologies. The main task was to select the optimal network topology and for that, different model selection criteria were explored. The selected networks were compared with the golden standards and the results ranked using the scoring metrics applied in the challenge, giving a better insight in our submission and the way to improve it. Our approach provides an easy statistical and computational framework to infer gene regulatory networks that is suitable for large networks, even if the number of the observations (perturbations) is greater than the number of variables (genes).