Miracle-dz/UniFAR-FTUs huggingface dataset:
Intercultural Competency: A Transformative Learning Process

Intercultural competency is an adaptive capacity based on an inclusive and integrative world view which allows participants to effectively accommodate the demands of living in a host culture. Resea cultural competency over the last 25 years has ted to focus on identifying characteristics of participants indicative of successful intercultural experiences. Little if any research has approached the concept of intercultural competency from a learning perspective tat is, how participants learn to become interculturally competent The field of adult eda offers transformative learning theory that seems to partially explain this process. This study had a two-fold purpose: (a) to delineate the learning process of intercultural competency, and (b) to explore the theory of perspective transformation as a possible explanation for the learning and changes participants experience. The design of the study was qualitative, involving in-depth interviews with 12 interculturally competent participants. Analysis of the data resulted in a model illustrating the learning process of becoming interculturally competent The second part of the study revealed that Mezirow'stheoryofperspectivetransformationpartiallyexplainstheleaningprocess of intercultural competency. While both models share similar properties, this research extends our understanding of the theory of perspective transformation, particularly in the area of critical reflection.
An open-source state-of-the-art toolbox for broadcast news diarization

This paper presents the LIUM open-source speaker diarization toolbox, mostly dedicated to broadcast news. This tool includes both Hierarchical Agglomerative Clustering using well-known measures such as BIC and CLR, and the new ILP clustering algorithm using i-vectors. Diarization systems are tested on the French evaluation data from ESTER, ETAPE and REPERE campaigns.
Maximum classification optimization-based active learning for image classification

Traditional multi-class image classification needs a large number of training samples for building a classifier model. However, it is very time-consuming and costly to obtain labels for a large number of training samples from human experts. Active learning is a feasible solution. This paper proposes a maximum classification optimization method (MCO) for actively selecting unlabeled images to acquire labels. It integrated the information of an unlabeled sample from different perspectives with two steps. It first chooses a subset of candidates, and then selects the best from these candidates. Our experimental results show that the maximum classification optimization method outperforms two popular exiting methods (entropy-based uncertainty and BvSB).
Malstone: towards a benchmark for analytics on large data clouds

Developing data mining algorithms that are suitable for cloud computing platforms is currently an active area of research, as is developing cloud computing platforms appropriate for data mining. Currently, the most common benchmark for cloud computing is the Terasort (and related) benchmarks. Although the Terasort Benchmark is quite useful, it was not designed for data mining per se. In this paper, we introduce a benchmark called MalStone that is specifically designed to measure the performance of cloud computing middleware that supports the type of data intensive computing common when building data mining models. We also introduce MalGen, which is a utility for generating data on clouds that can be used with MalStone.
Outcome of invasive infections outside the central nervous system caused by Streptococcus pneumoniae isolates nonsusceptible to ceftriaxone in children treated with beta-lactam antibiotics

Objective. To determine the outcome of children treated primarily with beta-lactam antibiotics for a systemic infection outside the central nervous system (CNS) caused by isolates of Streptococcus pneumoniae nonsusceptible to ceftriaxone (MIC ≥ 1.0 &mgr;g/ml). Design. Retrospective review of the medical records of children identified prospectively with invasive infections outside of the CNS caused by isolates of S. pneumoniae that were not susceptible to ceftriaxone between September, 1993, and August, 1999. A subset of this group treated primarily with beta-lactam antibiotics was analyzed for outcome. Patients. Infants and children with pneumococcal infections cared for at eight children’s hospitals. Results. Among 2100 patients with invasive infections outside the CNS caused by S. pneumoniae, 166 had isolates not susceptible to ceftriaxone. One hundred patients treated primarily with beta-lactam antibiotics were identified. From this group 71 and 14 children had bacteremia alone or with pneumonia, respectively, caused by strains with an MIC of 1.0 &mgr;g/ml. Bacteremia or pneumonia caused by isolates with a ceftriaxone MIC ≥ 2.0 &mgr;g/ml occurred in 6 and 5 children, respectively. Three children with septic arthritis and 1 with cellulitis had infections caused by strains with an MIC to ceftriaxone of 1.0 &mgr;g/ml. Most were treated with parenteral ceftriaxone, cefotaxime or cefuroxime for one or more doses followed by an oral antibiotic. All but one child were successfully treated. The failure occurred in a child with severe combined immune deficiency and bacteremia (MIC = 1.0 &mgr;g/ml) who remained febrile after a single dose of ceftriaxone followed by 12 days of cefprozil. Conclusion. Ceftriaxone, cefotaxime or cefuroxime are adequate to treat invasive infections outside the CNS caused by pneumococcal isolates with MICs up to 2.0 &mgr;g/ml, a concentration currently considered resistant for these antibiotics by National Committee for Clinical Laboratory Standards breakpoints.
Thinking about terrorism and just war

Since 2001 a new urge to moralize the use of violence as an instrument of state policy has appeared in liberal democracies. The American idea of a War against Terror, and the European notion of confronting a global terrorist threat, have together merged with a discourse on humanitarian military action: the political/moral ‘responsibility to protect’ is no longer to be confined to one's own citizens. Renewed interest among academics in ‘just war’ theory, the tradition that seeks to humanize war through law, reflects this development. This article questions the assumption that there is an essential difference between war (civilized violence) and terrorism (barbaric violence). It argues that their similarity appears more clearly if we set intentions aside—such as the deliberate or accidental killing of ‘innocents’—and focus instead on three main facts: (a) modern war strategies and technologies are uniquely destructive, (b) armed hostilities increasingly occupy a single space of violence in which war and peace are not clearly demarcated, and (c) the law of war does not provide a set of ‘civilizing’ rules but a language for legal/moral argument in which the use of punitive violence is itself a central semantic element.
Inclusion formation and neuronal cell death through neuron-to-neuron transmission of α-synuclein

Neuronal accumulation of α-synuclein and Lewy body formation are characteristic to many neurodegenerative diseases, including Parkinson's disease (PD). This Lewy pathology appears to spread throughout the brain as the disease progresses. Furthermore, recent studies showed the occurrence of Lewy pathology in neurons grafted into the brains of PD patients, suggesting the spread of pathology from the host tissues to the grafts. The mechanism underlying this propagation is unknown. Here, we show that α-synuclein is transmitted via endocytosis to neighboring neurons and neuronal precursor cells, forming Lewy-like inclusions. Moreover, α-synuclein was transmitted from the affected neurons to engrafted neuronal precursor cells in a transgenic model of PD-like pathology. Failure of the protein quality control systems, especially lysosomes, promoted the accumulation of transmitted α-synuclein and inclusion formation. Cells exposed to neuron-derived α-synuclein showed signs of apoptosis, such as nuclear fragmentation and caspase 3 activation, both in vitro and in vivo. These findings demonstrate the cell-to-cell transmission of α-synuclein aggregates and provide critical insights into the mechanism of pathological progression in PD and other proteinopathies.
Convolutional Neural Networks for Subsurface Electrical Properties Estimation

The estimation of electromagnetic properties of soil is a crucial step in the determination of volumetric water content (VWC). Several techniques are available for estimating VWC; however, these approaches are often time-consuming, complex, and costly. In this paper, we have developed a method for solving inverse scattering problems by utilizing a Convolutional Neural Network (CNN). This CNN takes Reflection coefficients as input and predicts soil parameters such as permittivity, conductivity, and thickness of layered soil. Our results demonstrate the effectiveness of the proposed model in accurately predicting soil parameters.
The Yeast Rab GTPase Ypt1 Modulates Unfolded Protein Response Dynamics by Regulating the Stability of HAC1 RNA

The unfolded protein response (UPR) is a conserved mechanism that mitigates accumulation of unfolded proteins in the ER. The yeast UPR is subject to intricate post-transcriptional regulation, involving recruitment of the RNA encoding the Hac1 transcription factor to the ER and its unconventional splicing. To investigate the mechanisms underlying regulation of the UPR, we screened the yeast proteome for proteins that specifically interact with HAC1 RNA. Protein microarray experiments revealed that HAC1 interacts specifically with small ras GTPases of the Ypt family. We characterized the interaction of HAC1 RNA with one of these proteins, the yeast Rab1 homolog Ypt1. We found that Ypt1 protein specifically associated in vivo with unspliced HAC1 RNA. This association was disrupted by conditions that impaired protein folding in the ER and induced the UPR. Also, the Ypt1-HAC1 interaction depended on IRE1 and ADA5, the two genes critical for UPR activation. Decreasing expression of the Ypt1 protein resulted in a reduced rate of HAC1 RNA decay, leading to significantly increased levels of both unspliced and spliced HAC1 RNA, and delayed attenuation of the UPR, when ER stress was relieved. Our findings establish that Ypt1 contributes to regulation of UPR signaling dynamics by promoting the decay of HAC1 RNA, suggesting a potential regulatory mechanism for linking vesicle trafficking to the UPR and ER homeostasis.
Anticipating and Incorporating Stakeholder Feedback when Developing Value-Added Models

State and local education agencies across the United States are increasingly adopting rigorous teacher evaluation systems. Most systems formally incorporate teacher performance as measured by student test-score growth, sometimes by state mandate. An important consideration that will influence the long-term persistence and efficacy of these systems is stakeholder buy-in, including buy-in from teachers. In this study we document common questions from teachers about value-added measures and provide research-based responses to these questions. The questions come from teachers in Baltimore City Public Schools, who are evaluated using a combined measure of which value-added is one component. We focus on teacher questions about value-added because value-added generates the most concern from teachers. We also connect teacher concerns about value-added to other components of the evaluation system, such as classroom observations, although at present these other components epaa aape
A Concept-Centered Approach to Noun-Compound Interpretation

A noun-compound is a compressed proposition that requires an audience to recover the implicit relationship between two concepts that are expressed as nouns. Listeners recover this relationship by considering the most typical relations afforded by each concept. These relational possibilities are evident at a linguistic level in the syntagmatic patterns that connect nouns to the verbal actions that act upon, or are facilitated by, these nouns. We present a model of noun-compound interpretation that first learns the relational possibilities for individual nouns from corpora, and which then uses these to hypothesize about the most likely relationship that underpins a noun compound.
Nectandrin B Activates Endothelial Nitric-Oxide Synthase Phosphorylation in Endothelial Cells: Role of the AMP-Activated Protein Kinase/Estrogen Receptor α/Phosphatidylinositol 3-kinase/Akt Pathway

We revealed previously that nectandrin B isolated from Myristica fragrans (nutmeg, Myristicaceae) functions as a potent AMP-activated protein kinase (AMPK) activator and showed its antiobesity effect. In this study, we investigated whether nectandrin B affects phosphorylation of endothelial nitric-oxide synthase (eNOS) in human endothelial cells. Nectandrin B increased the phosphorylation of eNOS and nitric oxide (NO) production in a concentration-dependent manner and maximal effect was found at 10 μg/ml. Nectandrin B activates AMPK, presumably via Ca2+/calmodulin kinase II activation and nectandrin B-stimulated eNOS phosphorylation was reversed by AMPK inhibition. Both the enzyme activity of phosphatidylinositol 3-kinase (PI3K) and the estrogen receptor (ER)-dependent reporter gene transcription were enhanced by nectandrin B. ERα inhibition by specific antagonist or small interfering siRNA (siRNA) suppressed nectandrin B-mediated eNOS phosphorylation. Moreover, AMPK inhibition significantly reversed the activation of ER-dependent transcription and PI3K activation in response to nectandrin B. Nectandrin B evoked endothelium-dependent relaxation in rat aortic rings, and this was blocked by inhibition of AMPK, ER, or PI3K. These results suggest that potent AMPK activator nectandrin B enhances NO production via eNOS phosphorylation in endothelial cells and ERα-dependent PI3K activity is required.
Neuro-mimetic navigation systems: A computational model of the rat Hippocampus

We propose a bio-inspired approach to autonomous navigation based on some of the components that rats use for navigation. A spatial model of the environment is constructed by unsupervised Hebbian learning. The representation consists of a population of localized overlapping place elds, modeling place cell activity in the rat Hippocampus. Place elds are established by extracting spatio-temporal properties of the environment from visual sensory inputs. Visual ambiguities are resolved by means of path integration. Reinforcement learning is applied to use place cell activity for goal-oriented navigation. Experimental results obtained with a mobile Khepera robot are presented.
Quantifying the Fermi paradox in the local Solar neighborhood

The Fermi paradox highlights the dichotomy between the lack of physical contact with other civilizations and the expectation that technological civilizations are assumed likely to evolve in many locations in the Milky Way galaxy, given the large number of planetary systems within this galaxy. Work by Landis and others has modeled this question in terms of percolation theory and cellular automata, using this method to parametrize our ignorance about possible other civilizations as a function of the probability of one system to colonize another, and the maximum number of systems reachable from each starting location (i.e. the degree in the network used for percolation). These models used a fixed lattice of sites to represent a stellar region, so the degree of all sites were identical. In this paper, the question is examined again, but instead of using a pre-determined lattice, the actual physical positions of all known star systems within 40 parsecs of the Solar System are used as percolation sites; in addition, the number of sites accessible for further colonization from a given system is determined by a choice of maximum distance such efforts can travel across. The resulting simulations show that extraterrestrial colonization efforts may reach the Solar System, but only for certain values of the maximum travel distance and probability of an occupied system further colonizing other systems. Indeed, large numbers of systems may be colonized with either vessels that lack insufficient travel distance to reach the Solar System or else have a colonization probability where they are statistically unlikely to reach us.
Characteristics of Blood Vessel Wall Deformation with Porous Wall Conditions in an Aortic Arch

Abstract Blood vessels have been modeled as non-porous structures that are permeable to solutes mixed in the blood. However, the use of non-physiological boundary conditions in numerical simulations that assume atmospheric pressure at the outlet does not illustrate the actual structural physics involved. The presence of pores in the wall influences wall deformation characteristics, which may increase the risk of rupture in specific conditions. In addition, the formation of secondary flows in a curved blood vessel may add complications to the structural behavior of the vessel walls. These reservations can be addressed by a fluid structure interaction-based numerical simulation of a three-dimensional aortic arch with increased physiological velocity and pressure waveforms. The curvature radius of the arch was 30 mm with a uniform aorta diameter of 25 mm. A one-way coupling method was used between physics of porous media flow and structural mechanics. A comparison of results with a non-porous model revealed that the approximated porous model was more prone to hypertension and rupture. Similarly, the secondary flows found to be an important indicator for the vascular compliance that forced the outer aortic region to experience the largest deformation. Consequently, it is very important to use actual physiological situations of the blood vessels to reach a diagnostic solution.
A Cascaded Linear Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging

We propose a cascaded linear model for joint Chinese word segmentation and partof-speech tagging. With a character-based perceptron as the core, combined with realvalued features such as language models, the cascaded model is able to efficiently utilize knowledge sources that are inconvenient to incorporate into the perceptron directly. Experiments show that the cascaded model achieves improved accuracies on both segmentation only and joint segmentation and part-of-speech tagging. On the Penn Chinese Treebank 5.0, we obtain an error reduction of 18.5% on segmentation and 12% on joint segmentation and part-of-speech tagging over the perceptron-only baseline.
Isokinetic Leg Strength and Power in Collegiate Rodeo Athletes

Thirty rodeo athletes (ages 20.8 ±2.1 yrs) had handgrip strength and isokinetic knee extension/flexion strength and power determined preseason. Male athletes were assigned to groups by event: roughstock riders (RS) (n = 10), steer wrestlers (SW) (n = 3), and ropers (RP) (n = 7). Females were assigned to the barrel racing group (BL) (n = 10). The SW group weighed significantly more (89.7 ±7.3 kg) than the other groups. The male athletes had significantly greater grip strength and knee extension/flexion strength and power at 30° and 180° · s–1 compared to the female group (BL). The SW group had greater 30° · s–1 peak knee extension/flexion strength in the right (93.3 ±5.3/71.3 ±5.2 lbs) and left (95.8 ±5.4/76.2 ±8.9 kg) legs compared to the RS and RP groups. However, these differences were not statistically significant. Similarly, the SW group had greater knee extension/flexion power at 180° · s–1 in the right (356 ±24.3/284.1 ±56.3 watts) and left (407.1 ±26.5/292 ±62.3 watts) legs compared to RS and RP groups. These results suggest that rodeo athletes have similar leg strength to endurance athletes but are not as strong as power athletes. Rodeo athletes may need to place greater emphasis on offseason training of leg strength and power to prevent injury and improve in-season training.
The role of red cell distribution width in the prognosis of patients with gastric cancer.

BACKGROUND Although the red cell distribution width (RDW) has been reported as a reliable predictor of prognosis in several types of cancer, to our knowledge the prognostic value of RDW in gastric carcinoma has not been studied, so far. OBJECTIVE We aimed to investigate the role of red cell distribution width (RDW) in predicting prognosis in gastric cancer patients. METHODS All gastric cancer patients who underwent curative surgery (n= 172, 110M/62F) over a five-year study period were evaluated. Data on demographics, preoperative RDW levels, tumor characteristics (early stage: I and II, advanced stage: IIIA-B-C), disease-free (DFS) and overall survival (OS) were retrospectively reviewed. Patients were classified as high RDW group (RDW ≥ 16, n= 62) or low RDW group (RDW < 16, n= 110). RESULTS Overall mortality and postoperative 60-day mortality in both groups were 55% and 14%, respectively. A borderline significant association between RDW (0.063) and mortality was noted. Preoperative RDW levels were significantly higher in patients with short-term mortality (17.9 ± 4.3 vs. 16 ± 3.2, p= 0.015). In high RDW group, the incidence of advanced gastric cancer was significantly higher (75 vs. 51%, p= 0.002), whereas DFS (0.035) and OS (p= 0.04) were lower. CONCLUSION The frequency of advanced cancer was high in patients with high RDWvalues. High RDW values were strongly associated with short-term mortality although only a borderline relationship with overall survival was observed.
Pharmacological Modulation of the Short-Lasting Effects of Antagonistic Direct Current-Stimulation Over the Human Motor Cortex

Combined administration of transcranial direct current-stimulation (tDCS) with either pergolide (PER) or d-cycloserine (d-CYC) can prolong the excitability-diminishing effects of cathodal, or the excitability enhancing effect of anodal stimulation for up to 24 h poststimulation. However, it remains unclear whether the potentiation of the observed aftereffects is dominated just by the polarity and duration of the stimulation, or the dual application of combined stimulation and drug administration. The present study looks at whether the aftereffects of oral administration of PER (a D1/D2 agonist) or d-CYC (a partial NMDA receptor agonist), in conjunction with the short-duration antagonistic application of tDCS (either 5 min cathodal followed immediately by 5 min anodal or vice versa), that alone only induces short-lasting aftereffects, can modulate cortical excitability in healthy human subjects, as revealed by a single-pulse MEP (motor-evoked-potential) paradigm. Results indicate that the antagonistic application of tDCS induces short-term neuroplastic aftereffects that are dependent upon the order of the application of short-duration stimulation. The administration of d-CYC resulted in a marked inhibition of cortical excitability under the application of tDCS in both stimulation orders. Intake of PER resulted in an increase in cortical excitability in both stimulation orientations, but was non-significant compared to the placebo condition. These results indicate that the aftereffects of tDCS are dependent upon the order of stimulation applied, and also demonstrate the prolongation of tDCS aftereffects when combined with the administration of CNS active drugs.