Miracle-dz/UniFAR-FTUs huggingface dataset:
An elastic band model for Shape retrieval

In this paper, we present novel model to find the contour of an image in phases. The model was designed by modelling physical motion of a real elastic band. This is applied to top of any existing shape representation methods in order to offer additional information. The model makes us deal with global and local shape characteristics at once and results in robustness to distortion and noise on the retrieval system as it does not miss the detailed data. Dynamic time warping algorithm is employed to measure the similarity between shapes. We have experimented in MPEG-7-CE-Shape-1 part B image database and the results show that our model is robust to distortion, noise and images having complexities inside of the boundary.
How changes in consumer behaviour and retailing affect competence requirements for food producers and processors

This paper analyses the changing competence requirements which members of the food chain face in their pursuit of competitive advantage. Two groups of trends serve as point of departure: more dynamic and heterogeneous consumer demands, which can be analysed in terms of consumer demands for sensory, health, process and convenience qualities, and changing roles for retailers in the food chain. Based on these trends, it is argued that competencies which can increase producers' level of market orientation get increased weight in the attainment of competitive advantage, and three types of competencies are singled out as especially important: consumer understanding, relationship management, and new product development. The development of market-related competencies aimed at exploiting trends in consumer behaviour and retailing will also entail changing forms of cooperation among members of the value chain, which favour both new ways of adding value but also new ways of matching consumer heterogeneity with heterogeneity in agricultural raw materials.
Exploiting Dependency Context Gazetteers for Named Entity Recognition

Modern named entity recognition (NER) systems mostly employ a supervised machine learning approach that heavily depends on local contexts. While NER systems based on local contexts provide strong baseline performance, results of recent research have demonstrated that non-local contexts can further improve the performance of these systems. In this paper, we propose the use of a context gazetteer as a novel resource for improving NER with non-local information. A context gazetteer is a list of syntactic dependency contexts with which entity names co-occur. We build a context gazetteer from a large encyclopedic database because manually annotated data are often too few to extract rich and sophisticated context patterns. Moreover, each context is assigned with a confidence value to reflect its reliability. In experiments, we create a context gazetteer of gene names and apply it to a biomedical NER task. High confidence context patterns appear in various forms: some are similar to predicate–argument structures whereas some are in unexpected forms. The experimental results show that the context gazetteer improves both precision and recall over strong baseline models.
On f-wise Arc Forwarding Index and Wavelength Allocations in Faulty All-optical Hypercubes

Motivated by the wavelength division multiplexing in all-optical networks, we consider the problem of finding an optimal (with respect to the least possible number of wavelengths) set of ƒ+1 internally node disjoint dipaths connecting all pairs of distinct nodes in the binary r -dimensional hypercube, where 0 ≤ ƒ . This system of dipaths constitutes a routing protocol that remains functional in the presence of up to ƒ faults (of nodes and/or links). The problem of constructing such protocols for general networks was mentioned in [1]. We compute precise values of ƒ -wise arc forwarding indexes and give (describe dipaths and color them) nearly optimal all-to-all ƒ -fault tolerant protocols for the hypercube network. Our results generalize corresponding results from [1, 4, 14].
An Integrated Field-Effect Microdevice for Monitoring Membrane Transport in Xenopus laevis Oocytes via Lateral Proton Diffusion

An integrated microdevice for measuring proton-dependent membrane activity at the surface of Xenopus laevis oocytes is presented. By establishing a stable contact between the oocyte vitelline membrane and an ion-sensitive field-effect (ISFET) sensor inside a microperfusion channel, changes in surface pH that are hypothesized to result from facilitated proton lateral diffusion along the membrane were detected. The solute diffusion barrier created between the sensor and the active membrane area allowed detection of surface proton concentration free from interference of solutes in bulk solution. The proposed sensor mechanism was verified by heterologously expressing membrane transport proteins and recording changes in surface pH during application of the specific substrates. Experiments conducted on two families of phosphate-sodium cotransporters (SLC20 & SLC34) demonstrated that it is possible to detect phosphate transport for both electrogenic and electroneutral isoforms and distinguish between transport of different phosphate species. Furthermore, the transport activity of the proton/amino acid cotransporter PAT1 assayed using conventional whole cell electrophysiology correlated well with changes in surface pH, confirming the ability of the system to detect activity proportional to expression level.
Three-dimensional active shape model matching for left ventricle segmentation in cardiac CT

Manual quantitative analysis of cardiac left ventricular function using multi-slice CT is labor intensive because of the large datasets. We present an automatic, robust and intrinsically three-dimensional segmentation method for cardiac CT images, based on 3D Active Shape Models (ASMs). ASMs describe shape and shape variations over a population as a mean shape and a number of eigenvariations, which can be extracted by e.g. Principal Component Analysis (PCA). During the iterative ASM matching process, the shape deformation is restricted within statistically plausible constraints (±3σ). Our approach has two novel aspects: the 3D-ASM application to volume data of arbitrary planar orientation, and the application to image data from another modality than which was used to train the model, without the necessity of retraining it. The 3D-ASM was trained on MR data and quantitatively evaluated on 17 multi-slice cardiac CT data sets, with respect to calculated LV volume (blood pool plus myocardium) and endocardial volume. In all cases, model matching was convergent and final results showed a good model performance. Bland-Altman analysis however, showed that bloodpool volume was slightly underestimated and LV volume was slightly overestimated by the model. Nevertheless, these errors remain within clinically acceptable margins. Based on this evaluation, we conclude that our 3D-ASM combines robustness with clinically acceptable accuracy. Without retraining for cardiac CT, we could adapt a model trained on cardiac MR data sets for application in cardiac CT volumes, demonstrating the flexibility and feasibility of our matching approach. Causes for the systematic errors are edge detection, model constraints, or image data reconstruction. For all these categories, solutions are discussed.
Exploring the behaviour of long gamma-ray bursts with intrinsic afterglow correlations

In these proceedings, we summarise the exploration so far of the relationship between the afterglow luminosity (measured at rest frame 200s; log L200s) and average afterglow decay rate (measured from rest frame 200s onwards, α>200s) of long duration Gamma-ray Bursts (GRBs), first reported in the optical/UV light curves of GRB afterglows. We show that this correlation is also present in the X-ray afterglows of GRBs as observed by Swift-XRT. We explore how the parameters of the correlation observed in both the X-ray and optical/UV light curves relate to each other and the prompt emission phase and whether these correlations are consistent with predictions of the standard afterglow model. We find that the observed correlations are consistent with a common underlying physical mechanism producing GRBs and their afterglows regardless of the detailed temporal behaviour. However, a basic afterglow model has difficulty explaining all the observed correlations. This leads us to briefly discuss alternative more complex models.
DIC in variable selection

Model comparison is discussed from an information theoretic point of view. In particular the posterior predictive entropy is related to the target yielding DIC and modifications thereof. The adequacy of criteria for posterior predictive model comparison is also investigated depending on the comparison to be made. In particular variable selection as a special problem of model choice is formalized in different ways according to whether the comparison is a comparison across models or within an encompassing model and whether a joint or conditional sampling scheme is applied. DIC has been devised for comparisons across models. Its use in variable selection and that of other criteria is illustrated for a simulated data set.
ID : OOPS-103 The Link Structure of Java Classes

Several works in literature have analyzed the link structure of programs in relation with software engineering: it has been observed that the programming standards caused a small-world and power-law network to emerge among classes in object-oriented programming. The need for coherent design and the coding conventions introduce regular patterns in the link structure of code. In this work, we study the social network naturally emerging from unrelated software projects. We studied the links present among Java classes coming from different contexts. In this case, any observable patterns come from social behaviors , rather than software engineering practices. In our analysis too, we could observe a regular social network , structured according to a power-law distribution. Out of this finding, we propose a way of ranking classes, and we present our prototype search engine for Java classes.
Enhancing Students’ Level of Critical Thinking through Interaction in Problem Based Learning and Computer Supported Collaborative Learning Environment

— The purpose of this study is to investigate the potential impact of PBL-CSCL learning environment on students’ leve l of critical thinking skills and cognitive performance. This study will be carried out in ten weeks among 37 students who enrolled in Programming Language Concepts and Paradigms course. The independent variable of this study is the pattern of interaction types while the two assessment techniques which are the students’ critical thinking skills and cognitive performance are the dependent variables. The study seeks to identify the best pattern of interaction that occurs in the PBL-CSCL learning environment that helps to maximize students’ critical thinking skills and cognitive performance. Further investigation involves in finding if there correlation between students’ level of critical thinking and subject specific cognitive performance with types of interaction occurs during learning. This is a quantitative research design that involves the use of quantitative and qualitative data and adopts one group pre-test and post-test design. The findings of the study will help instructors in understanding students’ preference of interaction types in a real world learning activities in order to enhance their critical thinking and cognitive performance.
Hypergraph-oriented 3D reconstruction, interpretation and analysis of air flows

The paper introduces a new air flow analysis approach based on particle tracking velocimetry (PTV). One of the special features of the proposed method is that after the tracer particles are detected, matching and tracking are jointly conducted. To this end, we introduce an interpretation module based on a directed hypergraph for 3D curve reconstruction. At first, the 2D inter-frame locations are localised and used for the extraction and calculation of 3D keypoints. Through 3D keypoints, which are evaluated by the hypergraph together with the time information in several steps, reverse curve matching for path selection can be reconstructed and the resulting trajectories visualised. In contrast to the preceding works, our approach tries to describe the measuring data by 3D trajectories directly instead of estimating 2D trajectories first and then matching afterwards. A higher precision can be achieved also with complicated trajectories. A certain independence of the reflections and lighting conditions is reached by the interpretation. Moreover, the path of particles can also be reconstructed with the minimum number of 3D keypoints under consideration of the path energy minimisation.
Examining discrepancies between actual and desired communal coping with type 2 diabetes

Correspondence Erin D. Basinger, Department of Communication Studies, University of North Carolina, Colvard 5021, 9201 University City Blvd., Charlotte, NC 28223. Email: ebasinge@uncc.edu Present address: NUS Business School, National University of Singapore, Singapore Type 2 diabetes has deleterious physiological, psychological, and relational effects both on people living with diabetes (PLWD) and on their family members. We employed the communal coping model to investigate whether coping alongside family members was advantageous. Specifically, PLWD (n = 213) and family members of PLWD (n = 208) completed an online survey assessing their coping responses and a variety of diabetesrelated outcomes (i.e., depressive symptoms, relationship satisfaction, and self-care). Generally, results indicated that more communal coping was beneficial. However, a second goal of this study was to examine discrepancies between levels of actual communal coping and desired communal coping, and the findings from these analyses add nuance to the generally held belief that more communal coping is always better.
A novel approach using WAAVES coder for the EEG signal compression

In this paper, we propose a new approach to compress Electroencephalogram (EEG) signals using the WAAVES compression algorithm and Independent Component Analyses (ICA). Firstly, ICA is applied to the 1D-EEG signals as a preprocessing stage to uncorrelate signals. Then, the output of the ICA is scaled and reformatted into a 2D-matrix to be compressed as an image using the WAAVES coder. This scheme gives a better compression ratio and a better Percentage Root-Mean-Squared Difference (PRD). Our work increases the compression efficiency (CR = 36.60) while reserving the EEG signal diagnostic quality (PRD=4.73).
Standardization of lactation means of somatic cell scores for calculation of genetic evaluations.

Sample day records of means of somatic cell scores were analyzed to develop adjustments to standardize records for length of lactation. Estimates for effect of DIM were from a model that included random lactation and cow effects for lactations to date of 753,929 Holsteins and 21,842 Jerseys calving in Pennsylvania or Wisconsin from 1987 to 1991. Lactation, cow, and residual variances were estimated using REML. Lactation and cow variances relative to a phenotypic variance of 1.00 were . 57 and . 31, respectively, for Holsteins and . 52 and . 35, respectively, for Jerseys. Estimates of effect of DIM were used to compute additive adjustments. Final lactation mean of somatic cell score at < or = 305 DIM for 1,857,532 Holsteins and 113,998 Jerseys from all participating states were standardized for lactation length and analyzed to determine the national effects of calving age and the regional effects of calving month. Multiplicative adjustments were developed for calving age and additive adjustments for calving month. Sample day records of lactation means of somatic cell scores were used to estimate weights based on number of somatic cell sample days to account for the lower accuracy of short records for genetic evaluation.
ROAMS: Rover Analysis, Modeling and Simulation Software

In this paper, we present the development of ROAMS software for red-time simulation of mobile robotic vehicles. The purpose for the simulation is to provide a virtual testing ground for various subsystems and components of the robotic vehicle, which include a mechanical subsystem, an electrical subsystem, internal and external sensors, on-board control software. Using the DARTS/DSHELL framework, the real-time simulator can be applied to both operator-inthe-loop and off-line simulation. Its flexibility can accommodate the simulator to different levels of sophistication for various tasks in system engineering, software engineering, and for research scientists, maintenance and operation technicians. However, to achieve ”real-time” in simulation of complex physical systems is a non-trivial task. Efforts have been made to build the Rocky 7 rover model for efficient and stable simulation. Currently, the rover model is comprised of its mechanical, electrical, and sensor subsystems, and connected with the on-board software. With additional terrain models, we developed solution techniques that permit real-time simulation of the rover traversing Mars-like terrain on workstations. Further integration of ROAMS with a planning subsystem is also discussed in this paper. kl;remt/cs
Quantum cryptography in noisy channels

We provide a complete proof of the security of quantum cryptography against any eavesdropping attack including coherent measurements even in the presence of noise. Polarization-based cryptographic schemes are shown to be equivalent to EPR-based schemes. We also show that the performance of a noisy channel approaches that of a noiseless one as the error rate tends to zero. (i.e., the secrecy capacity $C_s (\epsilon) \to C_s (0)$ as $\epsilon \to 0$. ) One implication of our results is that one can {\it double} the efficiency of a most well-known quantum cryptographic scheme proposed by Bennett and Brassard simply by assigning vastly different probabilities to the two conjugate bases.
Reproductive effort transiently reduces antioxidant capacity in a wild bird

Oxidative stress has been suggested as a proximate cost of reproduction and hence as a major constraint in the evolution of life histories, and it is therefore thought that antioxidants alleviate the effects of reproductive effort on oxidative stress. Furthermore, carotenoid-based ornaments have been proposed to mirror male ability to resist oxidative stress. Using a full-factorial experimental design in a natural population of great tits Parus major, we manipulated brood size and supplemented the male parent with either carotenoids or a placebo. We then assessed antioxidant capacity via a measure of whole blood resistance to a free radical attack during the nestling rearing period. Males of enlarged broods showed impaired antioxidant capacity 5 days after the brood size manipulation. However, 13 days after manipulation, they had their antioxidant capacity restored, an effect that may be due to the development of compensatory antioxidant mechanisms or due to reduced investment in the current reproduction in favor of future survival and reproduction. Carotenoid supplementation did not affect male antioxidant capacity nor was the interaction with the brood manipulation significant. Males with stronger carotenoid-based plumage colors did not show higher antioxidant capacity 5 days after the brood size manipulation, but after 13 days, the relationship was highly significant. This study on a natural population shows that larger brood size can induce a transient decrease in antioxidant capacity. It also supports the hypothesis that carotenoid-based plumage may signal male ability to resist oxidative stress, particularly during the energetically demanding nestling rearing period. Key words: antioxidant capacity, brood size manipulation, carotenoid-based coloration, carotenoids, oxidative stress, sexual selection. [Behav Ecol]
The Orphan Nuclear Receptor TLX Is an Enhancer of STAT1-Mediated Transcription and Immunity to Toxoplasma gondii

The protozoan parasite, Toxoplasma, like many intracellular pathogens, suppresses interferon gamma (IFN-γ)-induced signal transducer and activator of transcription 1 (STAT1) activity. We exploited this well-defined host–pathogen interaction as the basis for a high-throughput screen, identifying nine transcription factors that enhance STAT1 function in the nucleus, including the orphan nuclear hormone receptor TLX. Expression profiling revealed that upon IFN-γ treatment TLX enhances the output of a subset of IFN-γ target genes, which we found is dependent on TLX binding at those loci. Moreover, infection of TLX deficient mice with the intracellular parasite Toxoplasma results in impaired production of the STAT1-dependent cytokine interleukin-12 by dendritic cells and increased parasite burden in the brain during chronic infection. These results demonstrate a previously unrecognized role for this orphan nuclear hormone receptor in regulating STAT1 signaling and host defense and reveal that STAT1 activity can be modulated in a context-specific manner by such “modifiers. ”
Trait Mindfulness: A Multifaceted Evaluation

Scant studies have addressed the relations of an array of variables related to trait mindfulness in the context of a single investigation. We tested 800 (67.9% females, 31.3% males, .6% other, and .3% missing) undergraduate participants to evaluate three hypotheses: (a) increased positive affect, extraversion, openness, agreeableness, conscientiousness, acceptance, mysticism, transliminality, emotion regulation, and resilience would be related to increased trait mindfulness; (b) decreased negative affect, neuroticism, trait anxiety, behavioral avoidance, depression, and psychopathy would be associated with increased trait mindfulness; and (c) emotion regulation and resilience would demonstrate the strongest relations with trait mindfulness. All variables correlated significantly with trait mindfulness in the hypothesized directions, except for mysticism. Regression analyses revealed that emotion regulation, resilience, neuroticism, openness, conscientiousness, and behavioral avoidance all uniquely related to trait mindfulness. Enhanced emotion regulation and resilience alone accounted for more than 50% of variance in trait mindfulness.