Miracle-dz/UniFAR-FTUs huggingface dataset:
Politics, power, and performativity in the newsroom: an ethnography of television journalism in Turkey

How do political divisions within the newsroom shape negotiations around news production? This article addresses this question by examining how Turkish journalists, in their discourse and practices, represent Kurds and Arabs when interpreting and discussing current events related to the Kurdish question and the Arab Spring. The study draws upon a year of ethnographic fieldwork, and interviews conducted in 2011 and 2012, in the newsrooms of two mainstream national television channels in Turkey. It reveals how journalists with opposing political beliefs perform their representational practices by continuously modifying them according to the opinions of managerial boards. In negotiations on the portrayal of Kurds and Arabs in news reports, journalists mask or modify ‘undesired’ aspects of their individual interpretations to fit them into a dominant news frame. However, they can also challenge that frame. Based upon the observation of such negotiations, this article advances a novel definition of journalistic performance as a purposeful, strategic, and staged form of symbolic communication: an essential tool for navigating ideological conflicts in the power structure of the newsroom.
Particle Filtering Approaches for Multiple Acoustic Source Detection and 2-D Direction of Arrival Estimation Using a Single Acoustic Vector Sensor

This paper considers the problem of tracking multiple acoustic sources using a single acoustic vector sensor (AVS). Firstly, a particle filtering (PF) approach is developed to track the direction of arrivals of fixed and known number of sources. Secondly, a more realistic tracking scenario which assumes that the number of acoustic sources is unknown and time-varying is considered. A random finite set (RFS) framework is employed to characterize the randomness of the state process, i.e., the dynamics of source motion and the number of active sources, as well as the measurement process. As deriving a closed-form solution for the multi-source probability density is difficult, a particle filtering approach is employed to arrive at a computationally tractable approximation of the RFS densities. The proposed RFS-PF algorithm is able to simultaneously detect and track multiple sources. Simulations under different tracking scenarios demonstrate the ability of the proposed approaches in tracking multiple acoustic sources.
Over-Generative Finite State Transducer N-Gram for Out-of-Vocabulary Word Recognition

Hybrid statistical grammars both at word and character levels can be used to perform open-vocabulary recognition. This is usually done by allowing the special symbol for unknown-word in the word-level grammar and dynamically replacing it by a (long) n-gramat character-level, as the full transducer does not fit in the memory of most current computers. We present a modification of a finite-state-transducer (fst) n-gram that enables the creation of a static transducer, i.e. when it is not possible to perform on-demand composition. By combining paths in the "LG" transducer (composition of lexicon and n-gram)making it over-generative with respect to the n-grams observed in the corpus, it is possible to reduce the number of actual occurrences of the character-level grammar, the resulting transducer fits the memory of practical machines. We evaluate this model for handwriting recognition using the RIMES and the IAM dabases. We study its effect on the vocabulary size and show that this model is competitive with state-of-the-art solutions.
Variance Sensitivity Analysis of Parameters for Pruning of a Multilayer Perceptron: Application to a Sawmill Supply Chain Simulation Model

Simulation is a useful tool for the evaluation of a Master Production/Distribution Schedule (MPS). The goal of this paper is to propose a new approach to designing a simulation model by reducing its complexity. According to the theory of constraints, a reduced model is built using bottlenecks and a neural network exclusively. This paper focuses on one step of the network model design: determining the structure of the network. This task may be performed by using the constructive or pruning approaches. The main contribution of this paper is twofold; it first proposes a new pruning algorithm based on an analysis of the variance of the sensitivity of all parameters of the network and then uses this algorithm to reduce the simulation model of a sawmill supply chain. In the first step, the proposed pruning algorithm is tested with two simulation examples and compared with three classical pruning algorithms fromthe literature. In the second step, these four algorithms are used to determine the optimal structure of the network used for the complexity-reduction design procedure of the simulation model of a sawmill supply chain.
Positive and Negative Affects Facilitate Insight Problem‐Solving in Different Ways: A Study with Implicit Hints

: This study investigates the in ﬂ uence of affective states on the use of implicit hints when solving insight problems. To examine this, two experiments were conducted, both with Duncker ’ s (1945) radiation problem as an insight problem. When primed with a hint, positive affect inhibited the number of incorrect solutions generated in Experiment 1 and increased the number of correct solutions in Experiment 2. In con-trast, negative affect enhanced the participants ’ performance regardless of the presence of hints across the two experiments. These results indicate that positive and negative affect facilitate insight problem-solving in different ways. It seems that positive affect implicitly prompts the acceptance of cues and broadens people ’ s search of a problem space, and negative affect encourages people to intensively focus on solving the insight task. The results suggest a resolution of a long-standing debate on the effec-tiveness of positive versus negative affect in solving a problem.
Platelet-Activating Factor Acetylhydrolase Activity Indicates Angiographic Coronary Artery Disease Independently of Systemic Inflammation and Other Risk Factors: The Ludwigshafen Risk and Cardiovascular Health Study

Background—Platelet-activating factor acetylhydrolase (PAF-AH), also denoted as lipoprotein-associated phospholipase A2, is a lipoprotein-bound enzyme that is possibly involved in inflammation and atherosclerosis. This study investigates the relationship of PAF-AH activity to angiographic coronary artery disease (CAD), the use of cardiovascular drugs, and other established risk factors. Methods and Results—PAF-AH activity, lipoproteins, sensitive C-reactive protein (sCRP), fibrinogen, serum amyloid A, and white blood cell count were determined in 2454 subjects with angiographically confirmed CAD and in 694 control subjects. PAF-AH activity was highly correlated with LDL cholesterol (r=0.517), apolipoprotein B (r=0.644), and non-HDL cholesterol (r=0.648) but not with sCRP or fibrinogen. PAF-AH activity was lower in women than in men and was affected by the intake of lipid-lowering drugs (−12%; P<0.001), aspirin (−6%; P<0.001), &bgr;-blockers (−6%; P<0.001), and digitalis (+7%; P<0.001). Unlike sCRP, fibrinogen, and serum amyloid A, PAF-AH activity was not elevated in unstable angina, non–ST-elevation myocardial infarction, or ST-elevation myocardial infarction. When nonusers of lipid-lowering drugs were examined, PAF-AH activity was associated with the severity of CAD and the number of coronary vessels with significant stenoses. In individuals not taking lipid-lowering drugs and after adjustment for use of aspirin, &bgr;-blocker, and digitalis, the odds ratio for CAD associated with increasing PAF-AH activity was 1.39 (95% CI 1.26 to 1.54, P<0.001), a finding that was robust against further adjustments. Conclusions—PAF-AH activity is not an indicator of the systemic inflammation that accompanies acute coronary syndromes. PAF-AH activity is affected by a number of cardiovascular drugs; however, after such medication use was accounted for, PAF-AH activity was associated with angiographic CAD, complementary to sCRP and independently of established risk factors such as LDL cholesterol.
Automatic System to Remove Unpleasant Images Detected by Pupil-Size Changes

An automatic filtering system to classify individual unpleasant emotions represented by pupil-size changes was proposed. The support vector machines classifier was applied to single-trial data of pupil size and indicated the possibility of the correct judgment of individually unpleasant states immediately after looking at emotional pictures. The framework was then constructed to automatically filter the similar unpleasant information from a picture database, applying the bag of features scheme to search for similar images.
Characteristics and formation mechanism of continuous extreme hazes in China: a case study in autumn of 2014 in the North China Plain

Four extreme haze episodes occurred in October 2014 in the North China Plain (NCP). To clarify the formation mechanism of hazes in the autumn, observations were conducted in Beijing from 5 October to 2 November. The meteorological parameters, satellite data, chemical compositions and optical of aerosols were obtained. The hazes originated from NCP, developing in the and northeast directions, with the highest concentration of PM2.5 of 469 μg·m -3 in Beijing. NCP was dominated by a weak high pressure system during the haze episode, which resulted in low surface wind speed and relatively stagnant weather. Moreover, the wind slowed down around Beijing city. The secondary aerosols NO3 was always higher than that of SO4 2, which indicated the motor vehicles played a more important part in the hazes in October 2014, even though the oxidation rate from SO2 to SO4 2was faster than that of NOX to NO3 . Sudden increases of the concentrations of organic matter, Cl and BC (Black carbon) before each haze episode implied that regional transport of pollutants by biomass burning was important for haze formation during the autumn. A satellite map of fire points and the backward trajectories of the air masses also indicated this pollution source. The distinct decrease in the PBL (Planetary boundary layer) height during four haze episodes restrained the vertical dispersion of the air pollutants. Water vapor also played a vital role in the formation of hazes by accelerating the chemical transformation of secondary pollutants, leading to hygroscopic growth of aerosols and altering the thermal balance of the atmosphere.
Homogenization of a degenerate triple porosity model with thin fissures

We consider the problem of modelling the flow of a slightly compressible fluid in a periodic fractured medium assuming that the fissures are thin with respect to the block size. As a starting point we used a formulation applied to a system comprising a fractured porous medium made of blocks and fractures separated by a thin layer which is considered as an interface. The inter-relationship between these three characteristics comprise the triple porosity model. The microscopic model consists of the usual equation describing Darcy flow with the permeability being highly discontinuous. Over the matrix domain, the permeability is scaled by $(\varepsilon \delta)^2$, where $\varepsilon$ is the size of a typical porous block, with $\delta$ representing the relative size of the fracture. We then consider a model with Robin type transmission conditions: a jump of the density across the interface block-fracture is taken into account and proportional to the flux by the mean of a function $(\varepsilon\delta)^{-\gamma}$, where $\gamma$ is a parameter. Using two-scale convergence, we get homogenized models which govern the global behaviour of the flow as $\varepsilon$ and $\delta$ tend to zero. The resulting homogenized problem is a dual-porosity type model that contains a term representing memory effects for $\gamma\le 1$, and it is a single porosity model with effective coefficients for $\gamma >1$.
Coorganized with LUISS ) FACTORS INFLUENCING THE DYNAMICS OF BROKERAGE POSITIONS IN CLUSTERS . EVIDENCE FROM THE SPANISH FOODSTUFF INDUSTRY

Shifting away from traditional approaches orientated towards the analysis of the benefits associated with brokerage, this paper provides valuable insights on the dynamics of this network position providing opportunities to innovate. Using fine grain micro data collected in a foodstuff Spanish cluster, the evolution of five different brokerage profiles is analysed in depth. Particularly, we observe how firm-level characteristics (status, former mediating experience and external openness), and their interactions may generate changes in the different brokerage roles over a period of time. Findings endorse our expectations mainly based on the social capital and network approaches. Status and previous mediating experience facilitate the creation of partnerships, fostering brokerage. Conversely, interaction effects demote brokerage activity at the intra-cluster level, suggesting the selective nature of broker? s relational behaviour.
Patterns of success: first-year student success in multiple domains

ABSTRACT The goal of this study was to examine differences in university success between first-year students by analyzing three domains simultaneously: students’ academic achievement, critical thinking disposition, and social–emotional adjustment to university life. Participants were 307 students who completed an online questionnaire. Latent class cluster analysis revealed three patterns of success: (1) average-achieving well-adjusted students (64%), (2) high-achieving average-adjusted students (14%), and (3) low-achieving low-adjusted students (22%). Follow-up ANCOVAs indicated that low-achieving low-adjusted students most strongly experienced that their social life hindered their study, whereas average-achieving high-adjusted students experienced the least interference from their study on their social life. These results indicated that student success is a multi-domain concept, with subgroups of first-year students showing specific patterns of success. The results of this study help to understand the feasibility of and tensions between domains of student success and provide suggestions for universities to adjust their support to specific student needs.
Nerve growth factor-induced differentiation of PC12 cells: evaluation of changes in RNA and DNA metabolism

The relationship between both DNA and RNA metabolism and the nerve growth factor (betaNGF)-induced differentiation of PC12 cells was investigated. Cells remained in log phase growth for 4 days after exposure to betaNGF. DNA synthesis was similarly unaffected by betaNGF during this time. Thereafter, a gradual decrease in DNA synthesis was observed. In contrast, as many as 40% of the cells display neurites after 4 days exposure to betaNGF. The implication, that cells which have begun to differentiate morphologically may still synthesize DNA, was confirmed using autoradiography. The cellular RNA concentration was elevated significantly within 1 day of exposure to betaNGF and continued to increase for up to 6 days. Dose-response analysis revealed that this increase in cellular RNA, both rRNA and tRNA, closely correlates with the size and number of neurites per cell rather than with the cell's capacity to grow a neurite per se. A parallel rise in the cellular protein concentration was observed also. It was concluded, therefore, that (1) cessation of cell division is not a prerequisite for the initiation of the morphological differentiation of these cells and (2) the elevation of the cellular RNA content influences some quantitative aspects of neurite outgrowth.
Low-complexity standard-compatible robust and scalable video streaming over lossy/variable bandwidth networks

We propose a robust and scalable transmission scheme based on multiple description coding (MDC). Each description is encoded using a standard video codec such as MPEG-2 or H.264. This scheme provides equal or better robustness with respect to other solutions such as forward error correction (FEC), at lower system complexity; also, it provides scalability by selectively dropping descriptions.
Optimization of Starch Composite Edible Coating Formulation on Fresh-Cut “Fuji” Apple through Surface Tension, Wettability and FTIR Spectroscopy

Fresh-cut “Fuji” apples are easily oxidised and deteriorated. Therefore, starch composite edible coating formulation were formulated to extend its life span. In this study, the effect of different amount of carboxymethyl cellulose (CMC) (1, 2, 3 and 4% (w/v)), glycerol (1, 2, 3 and 4% (v/v)) and turmeric oil (TO) (50, 175 and 300ppm) were evaluated through surface tension and wettability analysis. Furthermore, the molecular interaction between raw materials of the edible coating film were analysed through FTIR analysis. The results showed that formulation using 2% (w/v) CMC and 2% (v/v) glycerol were the best amount to formulate composite edible coating. Meanwhile, the range of turmeric oil were 50, 175 and 300ppm suitable to be used for further analysis on fresh-cut “Fuji” apples as it does not exceed the general rule of surface tension. The findings for intermolecular reaction of raw materials revealed that there were interactions occurred when citric acid (CA), glycerol and CMC were added; further enhanced functionality of the starch. Besides that, FTIR showed that the functional group in turmeric oil that acts as an active compound to inhibit the oxidation process and microbial activities were present in the edible coating film.
Pattern and microbiological characteristics of diabetic foot ulcers in a Nigerian tertiary hospital

Purpose To determine the pattern and bacteriological characteristics of diabetic foot ulcers in patients attending a tertiary health care facility. Method 160 Patients with Diabetes Mellitus foot syndrome were recruited, out of which 52 had diabetic foot ulcers. Relevant clinical, biochemical, and microbiological evaluations were carried out on the subjects. Data analysis was done using SPSS version 20. p value was set at <0.05. Results 52 (32.5%) out of 160 subjects with Diabetes Mellitus Foot Syndrome (DMFS) had diabetic foot ulcers. Poor glycaemic control (mean HbA1c = 9.2 (2.7) %), and abuse of antibiotics (76.9%) characterized the subjects. Foot ulcers mainly involved the right lower limb and followed spontaneous blister formation (50%). Microbiological culture pattern was polymicrobial (71.2%); predominantly anaerobic organisms (53.3%). Gram positive and negative aerobic isolates yielded high sensitivity to common quinolones (76% – 87.8%). The gram positive and negative anaerobic isolates were highly sensitive to Clindamycin and Metronidazole respectively (80.2% – 97.8%). High sensitivity (>80%) yield for gram negative anaerobes was recorded for Imipinem and Ampicillin/Sulbactam. Conclusion Diabetic foot ulcers (DFU) contribute about one-third of DMFS. The bacteriological isolates from these ulcers are mainly polymicrobial with high sensitivity to common antibiotics. The need for appropriate use of antibiotics should be advocated among the patients.
GPU-powered Bat Algorithm for the parameter estimation of biochemical kinetic values

The emergent behavior of biochemical systems can be investigated by means of mathematical modeling and computational analyses, which usually require the automatic inference of the unknown values of the model's parameters. This problem, known as Parameter Estimation (PE), is usually tackled with bio-inspired meta-heuristics for global optimization, most notably Particle Swarm Optimization (PSO). In this work we assess the performances of PSO and Bat Algorithm with differential operator and Lévy flights trajectories (DLBA). In particular, we compared these meta-heuristics for the PE using two biochemical models: the expression of genes in prokaryotes and the heat shock response in eukaryotes. In our tests, we also evaluated the impact on PE of different strategies for the initial positioning of individuals within the search space. Our results show that DLBA achieves comparable results with respect to PSO, but it converges to better results when a uniform initialization is employed. Since every iteration of DLBA requires three fitness evaluations for each bat, the whole methodology is built around a GPU-powered biochemical simulator (cupSODA) which is able to parallelize the process. We show that the acceleration achieved with cupSODA strongly reduces the running time, with an empirical 61× speedup that has been obtained comparing a Nvidia GeForce Titan GTX with respect to a CPU Intel Core i7-4790K. Moreover, we show that DLBA always outperforms PSO with respect to the computational time required to execute the optimization process.
Graphical Models and Belief Propagation-hierarchy for Optimal Physics-Constrained Network Flows

In this manuscript we review new ideas and first results on application of the Graphical Models approach, originated from Statistical Physics, Information Theory, Computer Science and Machine Learning, to optimization problems of network flow type with additional constraints related to the physics of the flow. We illustrate the general concepts on a number of enabling examples from power system and natural gas transmission (continental scale) and distribution (district scale) systems.
Design and implementation of wiki content transformations and refactorings

The organic growth of wikis requires constant attention by contributors who are willing to patrol the wiki and improve its content structure. However, most wikis still only offer textual editing and even wikis which offer WYSIWYG editing do not assist the user in restructuring the wiki. Therefore, "gardening" a wiki is a tedious and error-prone task. One of the main obstacles to assisted restructuring of wikis is the underlying content model which prohibits automatic transformations of the content. Most wikis use either a purely textual representation of content or rely on the representational HTML format. To allow rigorous definitions of transformations we use and extend a Wiki Object Model. With the Wiki Object Model installed we present a catalog of transformations and refactorings that helps users to easily and consistently evolve the content and structure of a wiki. Furthermore we propose XSLT as language for transformation specification and provide working examples of selected transformations to demonstrate that the Wiki Object Model and the transformation framework are well designed. We believe that our contribution significantly simplifies wiki "gardening" by introducing the means of effortless restructuring of articles and groups of articles. It furthermore provides an easily extensible foundation for wiki content transformations.