Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative spatial multiplexing for ad hoc networks with hybrid ARQ: system design and performance analysis

For a network where each node has multiple antennas, we propose a transmission mode and a cooperation protocol, with the aim of maximizing the network throughput. The distinctive feature of the work is that the focus in both the design and the evaluation is at the network level, rather than on a single link. To this end, we propose the use of spatial multiplexing and code division multiple access (CDMA) to increase the parallelism of transmissions in the network, thus improving throughput. Cooperation is also implemented by spatial multiplexing and CDMA, together with an adaptive hybrid automatic repeat request mechanism that adapts the retransmissions to the actual channel conditions. Spatial multiplexing allows frame-asynchronous transmissions and a flexible cooperation protocol that minimizes the signaling overhead. The resulting scheme is named layered coded cooperative system (LCCS). We propose an implementation of LCCS based on linear erasure packet codes, where cooperation is transparent to the receiver, and we assess the performance of LCCS both by analyzing a simple network with three nodes and by simulating a more complex network.
Myrica rubra Extracts Protect the Liver from CCl4-Induced Damage

The relationship between the expression of mitochondrial voltage-dependent anion channels (VDACs) and the protective effects of Myrica rubra Sieb. Et Zucc fruit extract (MCE) against carbon tetrachloride (CCl4)-induced liver damage was investigated. Pretreatment with 50 mg kg−1, 150 mg kg−1 or 450 mg kg−1 MCE significantly blocked the CCl4-induced increase in both serum aspartate aminotransferase (sAST) and serum alanine aminotransferase (sALT) levels in mice (P < .05 or .01 versus CCl4 group). Ultrastructural observations of decreased nuclear condensation, ameliorated mitochondrial fragmentation of the cristae and less lipid deposition by an electron microscope confirmed the hepatoprotection. The mitochondrial membrane potential dropped from −191.94 ± 8.84 mV to −132.06 ± 12.26 mV (P < .01) after the mice had been treated with CCl4. MCE attenuated CCl4-induced mitochondrial membrane potential dissipation in a dose-dependent manner. At a dose of 150 or 450 mg kg−1 of MCE, the mitochondrial membrane potentials were restored (P < .05). Pretreatment with MCE also prevented the elevation of intra-mitochondrial free calcium as observed in the liver of the CCl4-insulted mice (P < .01 versus CCl4 group). In addition, MCE treatment (50–450 mg kg−1) significantly increased both transcription and translation of VDAC inhibited by CCl4. The above data suggest that MCE mitigates the damage to liver mitochondria induced by CCl4, possibly through the regulation of mitochondrial VDAC, one of the most important proteins in the mitochondrial outer membrane.
Cellular Identity of a Novel Small Subunit rDNA Sequence Clade of Apicomplexans: Description of the Marine Parasite Rhytidocystis polygordiae n. sp. (Host: Polygordius sp., Polychaeta)

ABSTRACT. A new species of Rhytidocystis (Apicomplexa) is characterized from North American waters of the Atlantic Ocean using electron microscopy and phylogenetic analyses of small subunit (SSU) rDNA sequences. Rhytidocystis polygordiae n. sp. is a parasite of the polychaete Polygordius sp. and becomes the fourth described species within this genus. The trophozoites of R. polygordiae were relatively small oblong cells (L=35–55 μm; W=20–25 μm) and distinctive in possessing subterminal indentations at both ends of the cell. The surface of the trophozoites had six to eight longitudinal series of small transverse folds and several micropores arranged in short linear rows. The trophozoites of R. polygordiae were positioned beneath the brush border of the intestinal epithelium but appeared to reside between the epithelial cells within the extracellular matrix rather than within the cells. The trophozoites possessed a uniform distribution of paraglycogen granules, putative apicoplasts, mitochondria with tubular cristae, and a centrally positioned nucleus. The trophozoites were non‐motile and lacked a mucron and an apical complex. Intracellular sporozoites of R. polygordiae had a conoid, a few rhoptries, micronemes, dense granules, and a posteriorly positioned nucleus. Phylogenies inferred from SSU rDNA sequences demonstrated a close relationship between R. polygordiae and the poorly known parasite reported from the hemolymph of the giant clam Tridacna crocea. The rhytidocystid clade diverged early in the apicomplexan radiation and showed a weak affinity to a clade consisting of cryptosporidian parasites, monocystids, and neogregarines.
Teacher Awareness and Support for Learners with Learning Disabilities in Public Primary Schools in Trans-Nzoia County, Kenya

This paper investigates the level of teacher awareness and its influence on support for learners with learning disabilities in public primary schools in Trans-Nzoia County. The study was based on concurrent triangulation research design. The social constructivism theory formed the theoretical foundation of the study. The target population for the research consisted of 4107 teachers from which 351 were selected as the study sample size. Stratified random sampling technique was used to select teachers. The study used questionnaire, interviews and focus group discussions to collect data from teachers. It emerged that 59.5% of teachers were moderately aware of pupils with learning disabilities in their schools. The results shows that there existed significant positive relationship (r=0.256 and p=0.028) between Teachers Awareness of LD in Trans-Nzoia county and effective inclusion of these learners in their schools. In recommendation, teachers need to look for opportunities for further training to increase their awareness on learning disabilities in schools. There is also need for teachers to work with parents to assist pupils with learning disability in primary schools . Key Words: Teacher, Awareness, Learning Disability, Support
Supportive Principals and Black Teacher Turnover: ESSA as an Opportunity to Improve Retention

In U.S. public schools, the shortage of teachers of African descent specifically, and teachers of color more generally, is a worsening problem that has severe, detrimental effects on students. This shortage of Black teachers is driven in part by high turnover, much of which is precipitated by the poor working conditions in their schools. In this study, I analyze data from a sample of approximately 1,600 Black teachers who participated in the Schools and Staffing Survey (SASS, 2007–2008). My findings about the role of supportive principals have implications for how state departments of education should use Every Student Succeeds Act funds.
Determinants of the educational use of digital learning materials: The mediating role of self- efficacy, perceived norm and attitude

Initiatives to stimulate the development and propag ation of open educational resources (OER) need a sufficiently large community that can be mob ilized to participate in this endeavour. Failure to achieve this could lead to underuse of O ER. In the context of the Wikiwijs initiative a large scale survey was undertaken amongst primary a nd secondary school teachers to explore possible determinants of the educational use of dig ital learning materials (DLMs). Basing on the Integrative Model of Behaviour Predic tion it was conjectured that self-efficacy, attitude and perceived norm would take a central ro le in explaining the intention to use DLMs. Several other predictors were added to the model as well whose effects were hypothesized to be mediated by the three central variables. All conjectured relationships were found using path analysis on survey data from 1484 teachers. Intention to DLMs was most strongly deter mined by self-efficacy, followed by
Question: Do Standardized Tests Measure General Cognitive Skills? Answer: No.

S tandardized tests purport to measure the cognitive abilities required for a variety of aca demic and nonacademic tasks. Thus, test scores determine such important outcomes as whether students will be admitted into cortege, what grade they will receive, and the academic track where they will be placed. Unfortunately, there have been few research attempts to validate the as sumption that standardized tests do, in fact, measure general cognitive skills. Consequently, researchers at the Midcontinent Regional Educational Labo ratory analyzed 6,942 items from the Stanford Achievement batteries (the Stanford Early School Achievement Battery, the Stanford Achievement Test, and the Stanford Test of Aca demic Skills) and the California Test of Basic Skills to identify the general cog nitive abilities tested and study their relationship to student performance (Marzano and Jesse 1987). General cognitive abilities were de fined as those mental processes used in academic tasks that intersect more than one academic discipline. This definition stems from a widely ac cepted theory that the human mind stores information in two primary PtaopafblySr May Megan Dull
A novel dependency-based evaluation metric for machine translation

Automatic evaluation measures such as BLEU (Papineni et al. (2002)) and NIST (Doddington (2002)) are indispensable in the development of Machine Translation (MT) systems, because they allow MT developers to conduct frequent, fast, and cost-effective evaluations of their evolving translation models. However, most of the automatic evaluation metrics rely on a comparison of word strings, measuring only the surface similarity of the candidate and reference translations, and will penalize any divergence. In effect,a candidate translation expressing the source meaning accurately and fluently will be given a low score if the lexical and syntactic choices it contains, even though perfectly legitimate, are not present in at least one of the references. Necessarily, this score would differ from a much more favourable human judgment that such a translation would receive. This thesis presents a method that automatically evaluates the quality of translation based on the labelled dependency structure of the sentence, rather than on its surface form. Dependencies abstract away from the some of the particulars of the surface string realization and provide a more "normalized" representation of (some) syntactic variants of a given sentence. The translation and reference files are analyzed by a treebank-based, probabilistic Lexical-Functional Grammar (LFG) parser (Cahill et al. (2004)) for English, which produces a set of dependency triples for each input. The translation set is compared to the reference set, and the number of matches is calculated, giving the precision, recall, and f-score for that particular translation. The use of WordNet synonyms and partial matching during the evaluation process allows for adequate treatment of lexical variation, while employing a number of best parses helps neutralize the noise introduced during the parsing stage. The dependency-based method is compared against a number of other popular MT evaluation metrics, including BLEU, NIST, GTM (Turian et al. (2003)), TER (Snover et al. (2006)), and METEOR (Banerjee and Lavie (2005)), in terms of segment- and system-level correlations with human judgments of fluency and adequacy. We also examine whether it shows bias towards statistical MT models. The comparison of the dependency-based method with other evaluation metrics is then extended to languages other than English: French, German, Spanish, and Japanese, where we apply our method to dependencies generated by Microsoft's NLPWin analyzer (Corston-Oliver and Dolan (1999); Heidorn (2000)) as well as, in the case of the Spanish data, those produced by the treebank-based, probabilistic LFG parser of Chrupa la and van Genabith (2006a,b).
Evidence generation for Dempster-Shafer fusion using feature extraction multiplicity and radial basis network

Feature extraction methods in pattern recognition tasks seek to transform data variables to abstract mathematical variables such that their scores (called features) reveal hidden data structure of high cognitive value. Various feature extraction methods process raw data from different perspectives. Some depend on statistical correlation or independence such as principal component analysis (PCA), independent component analysis (ICA), singular value decomposition (SVD) and linear discriminant analysis (LDA), and some others aim to model parametric representations such as partial-least-square regression (PLSR). These methods can be viewed as independent observers who generate different feature sets for describing the same data. In supervised pattern recognition problems, this viewpoint can be combined with a classifier function to generate independent sets of class likelihood. The latter can be interpreted as evidences for class identities assigned by independent expert systems consisted of feature extraction method and classifier function combinations. Having created such set of experts, one can employ an information fusion system that could predict class identities. Following this paradigm, we used above mentioned feature extraction methods paired with a radial basis network to generate evidences, and applied Dempster-Shafer (D-S) fusion for pattern classification in a number of benchmark data sets. It is found that DS fusion results in enhanced classification rates compared to results from individual expert systems.
Projected Gromov-Witten varieties in cominuscule spaces

A projected Gromov-Witten variety is the union of all rational curves of fixed degree that meet two opposite Schubert varieties in a homogeneous space X = G/P . When X is cominuscule we prove that the map from a related Gromov-Witten variety is cohomologically trivial. This implies that all (3 point, genus zero) K-theoretic Gromov-Witten invariants of X are determined by the projected Gromov-Witten varieties, which extends an earlier result of Knutson, Lam, and Speyer. Our proof uses that any projected Gromov-Witten variety in a cominuscule space is also a projected Richardson variety.
Using ecological niche-based modeling techniques to predict the establishment , abundance 1 and relative impacts of introduced species : application to the common carp ( Cyprinus carpio ) 2 3

25 In order to efficiently manage non-indigenous species (NIS) predictive tools are needed to 26 prioritize locations where they are likely to become established and where their impacts will be 27 most severe. While predicting the impact of a NIS has generally proved challenging, forecasting 28 its abundance patterns across potential recipient locations should serve as a useful surrogate 29 method of estimating the relative severity of the impacts to be expected. Yet such approaches have 30 rarely been applied in invasion biology. We used long-term monitoring data for lakes within the 31 state of Minnesota and artificial neural networks to model both the occurrence as well as the 32 abundance of a widespread aquatic NIS, common carp (Cyprinus carpio). We then tested the 33 ability of the resulting models to (i) interpolate to new sites within our main study region, (ii) 34 extrapolate to lakes in the neighboring state of South Dakota and (iii) assessed the relative 35 contribution of each variable to model predictions. Our models correctly identified over 83% of 36 sites where carp are either present or absent and explained 73% of the variation in carp abundance 37 for validation lakes in Minnesota (i.e. lakes not used to build the model). When extrapolated to 38 South Dakota, our models correctly classified carp occurrence in 79% of lakes and explained 32% 39 of the variation in carp abundance. Variables related to climate and water quality were found to be 40 the most important predictors of carp distribution. These results demonstrate that ecological niche-41 based modeling techniques can be used to forecast both the occurrence and abundance patterns of 42 invasive species at a regional scale. Models also yielded sensible predictions when extrapolated to 43 neighboring regions. Such predictions, when combined, should provide more useful estimates of 44 the overall risk posed by NIS on potential recipient systems. 45 46
Victim Evaluations of Face-to-Face Restorative Justice Conferences: A Quasi-Experimental Analysis

One major goal of face-to-face restorative justice (RJ) is to help heal the psychological harm suffered by crime victims (Braithwaite, 2002). Substantial evidence from randomized controlled trials (RCTs) has shown that this can be accomplished (Strang, 2002) and more trials are underway (Sherman & Strang, 2004). These outcomes are even more clearly, if less rigorously, demonstrated through retrospective interviews of victims about their feelings before and after RJ took place. We review the responses of victims (N= 210) who participated in trials in Canberra (Australia) and in London, Thames Valley, and Northumbria (UK). Despite substantial variations in offense types, social contexts, nation and race, before-after changes revealed by qualitative and quantitative data are all in the same beneficial direction.
Finite element simulation of optical modes in VCSELs

An important ingredient of VCSEL device simulation is the solution of the optical model. Challenges are the multiscale structure of realistic devices with thin layers in the Bragg mirror and active zone on the one hand and large total resonator volumes on the other hand. In order to compute the resonating modes and frequencies, Maxwell eigenvalue problems have to be solved on these geometries. Thereby, also layered infinite exterior domains have to be respected. In commercial simulation packages the optical problem is often restricted to geometries with cylindrical symmetry or even only simplified 1D material stacks are considered. However, with increasing complexity of devices and novel design ideas like inclusion of photonic crystal structures, full 3D modeling of VCSELs becomes very important. In our contribution we present the finite element method for computation of the optical resonance modes and corresponding far fields in VCSELs. We investigate realistic 3D devices and quantify numerical effort and accuracy.
Hand Gesture Recognition Based on HU Moments in Interaction of Virtual Reality

Hand gesture recognition is the key technology to realize interaction of virtual reality. The accuracy and stability of the current hand gesture methods are still unsatisfactory due to various reasons. In YCbCr color space, the distribution of skin color has a good clustering. The paper uses skin detection in YCbCr color space for hand regional image, and proposes a hand gesture recognition method based on HU moments which have invariance property of translation, rotation and size. By extracting HU moments of the hand contour, this paper applies support vector machine (SVM) method to achieve the real-time hand gesture recognition. Experiments prove that the proposed method has very good precision and stability in virtual reality interaction.
EMBODIED SYSTEM LIFE

System life is concerned with societies of living beings, i.e. humans, animals, plants, and artifacts, i.e. computers, robots, machines in general, software, and virtual creatures. In this position paper we will focus on the functions of embodiment. It turns out that in addition to the fact that embodied systems are physical entities, there are important consequences of embodiment for category learning, concept acquisition, cognition, and communication. We will present a number of case studies that illustrate the concept of embodiment. We will then outline a research program designed to investigate the principles underlying system life, and present a theoretical framework. We will conclude by speculating about how to achieve higher levels of intelligence.
Causal Quantum Gravity

I discuss some issues of perturbative quantum gravity, namely of a theory of self-interacting massless spin-2 quantum gauge fields, the gravitons, on flat space-time, in the framework of causal perturbation theory. The central aspects of this approach lie in the construction of the scattering matrix by means of causality and Poincare covariance and in the analysis of the gauge structure of the theory. For this purpose, two main tools will be used: the Epstein-Glaser inductive and causal construction of the perturbation series for the scattering matrix and the concept of perturbative operator quantum gauge invariance borrowed from non-Abelian quantum gauge theories. The first method deals with the ultraviolet problem of quantum gravity and the second one ensures gauge invariance at the quantum level, formulated by means of a gauge charge, in each order of perturbation theory. The gauge charge leads to a characterization of the physical subspace of the graviton Fock space. Aspects of quantum gravity coupled to scalar matter fields are also discussed.
AUTOMATIC FEATURE MATCHING BETWEEN DIGITAL IMAGES AND 2 D REPRESENTATIONS OF A 3 D LASER SCANNER POINT CLOUD

The geometric referencing of digital image data and 3D point clouds e.g. given by a terrestrial laser scanner is the prerequisite for different levels of integrated data interpretation such as point cloud or mesh model texture colourisation for visualisation purposes, interactive object modelling by monoplotting-like procedures or automatic point cloud interpretation. Therein, the characteristics of laser scanner data and camera data can be regarded as complementary, so that these data are suitable for a combined interpretation. A precondition for the geometric referencing between laser scanner data and digital images and consequently for an integrated use of both data sets is the extraction of corresponding features. With a set of corresponding features the orientation of the image to the point cloud can be obtained by spatial resection. With regard to a high automation level the paper presents an approach for finding correspondences between features extracted from laser scanner data and digital images automatically. The basic idea of the presented approach is to use the SIFT operator to detect corresponding points in the camera image and an intensity image of the laser scanner data. Determining correspondences consists of four steps: Detection of salient characteristics, description of the features, matching of the descriptions in both images and evaluation of correct matches. RANSAC is used to find sets of consistent matches. The approach is validated with a data set taken from a baroque building in Dresden. * Corresponding author.