Miracle-dz/UniFAR-FTUs huggingface dataset:
A Computational Account of Basic Level and Typicality Effects

Cognitive psychology has uncovered two effects that have altered traditional views of human classification. Basic level effects suggest that humans prefer concepts at a particular level of generality, while typicality effects indicate that some instances of a class are more readily recognized as such than others. This paper describes a model of memory that accounts for basic level effects, typicality effects, and interactions between them. More generally, computer experiments lay the groundwork for a formal unification of basic level and typicality phenomena.
Connexin 43 impacts on mitochondrial potassium uptake

In cardiomyocytes, connexin 43 (Cx43) forms gap junctions and unopposed hemichannels at the plasma membrane, but the protein is also present at the inner membrane of subsarcolemmal mitochondria (SSM). Both inhibition and genetic ablation of Cx43 reduce ADP-stimulated complex 1 respiration. Since mitochondrial potassium influx impacts on oxygen consumption, we investigated whether or not inhibition or ablation of mitochondrial Cx43 alters mitochondrial potassium uptake. SSM were isolated from rat left ventricular myocardium and loaded with the potassium-sensitive dye PBFI (potassium-binding benzofuran isophthalate). Intramitochondrial potassium was replaced by tetraethylammonium. Mitochondria were incubated under control conditions or treated with 250 μM Gap19, a peptide that specifically inhibits Cx43-based hemichannels at plasma membranes. Subsequently, 140 mM KCl was added and the slope of the increase in PBFI fluorescence over time was calculated. The slope of the PBFI fluorescence of the control mitochondria was set to 100%. In the presence of Gap19, the mitochondrial potassium influx was reduced from 100 ± 11.6% in control mitochondria to 65.5 ± 10.7% (n = 6, p < 0.05). In addition to the pharmacological inhibition of Cx43, potassium influx was studied in mitochondria isolated from conditional Cx43 knockout mice. Here, the ablation of Cx43 was achieved by the injection of 4-hydroxytamoxifen (4-OHT; Cx43Cre-ER(T)/fl + 4-OHT). The mitochondria of the Cx43Cre-ER(T)/fl + 4-OHT mice contained 3 ± 1% Cx43 (n = 6) of that in control mitochondria (100 ± 11%, n = 8, p < 0.05). The ablation of Cx43 (n = 5) reduced the velocity of the potassium influx from 100 ± 11.2% in control mitochondria (n = 9) to 66.6 ± 5.5% (p < 0.05). Taken together, our data indicate that both pharmacological inhibition and genetic ablation of Cx43 reduce mitochondrial potassium influx.
Vortex generation by line plumes in a rotating stratified fluid

We present the results of an experimental investigation of the generation of coherent vortical structures by buoyant line plumes in rotating fluids. Both uniform and stratified ambients are considered. By combining the scalings describing turbulent plumes and geostrophically balanced vortices, we develop a simple model which predicts the scale of the coherent vortical structures in excellent accord with laboratory experiments. We examine the motion induced by a constant buoyancy flux per unit length B, released for a finite time ts, from a source of length L into a fluid rotating with angular speed Ω = f/2. When the plume discharges into a uniformly stratified environment characterized by a constant Brunt–Väisälä frequency, N>f, the fluid rises to its level of neutral buoyancy unaffected by the system rotation before intruding as a gravity current. Rotation has a strong impact on the subsequent dynamics: shear develops across the spreading neutral cloud which eventually goes unstable, breaking into a chain of anticyclonic lenticular vortices. The number of vortices n emerging from the instability of the neutral cloud, n = (0.65±0.1)Lf1/2/ (t1/2sB1/3), is independent of the ambient stratification, which serves only to prescribe the intrusion height and aspect ratio of the resulting vortex structures. The experiments indicate that the Prandtl ratio characterizing the geostrophic vortices is given by P = Nh/(fR) = 0.47±0.12; where h and R are, respectively, the half-height and radius of the vortices. The lenticular vortices may merge soon after formation, but are generally stable and persist until they are spun-down by viscous effects. When the fluid is homogeneous, the plume fluid rises until it impinges on a free surface. The nature of the flow depends critically on the relative magnitudes of the layer depth H and the rotational lengthscale Lf = B1/3/f. For H>10Lf, the ascent phase of the plume is influenced by the system rotation and the line plume breaks into a series of unstable anticylonic columns of characteristic radius (5.3±1.0)B1/3/f which typically interact and lose their coherence before surfacing. When H<10Lf, the system rotation does not influence the plume ascent, but does control the spreading of the gravity current at the free surface. In a manner analogous to that observed in the stratified ambient, shear develops across the surface current, which eventually becomes unstable and generates a series of anticyclonic surface eddies with characteristic radius (1.6±0.2)B1/3t1/3s /f2/3. These surface eddies are significantly more stable than their columnar counterparts, but less so than the lenticular eddies arising in the uniformly stratified ambient. The relevance of the study to the formation of coherent vortical structures by leads in the polar ocean and hydrothermal venting is discussed.
Localization of pedestrian area from hybrid camera system

Accurate pedestrian path prediction and motion estimation are important tasks in the intelligent vehicle domain. The model incorporates the pedestrian pose recognition and lateral speed, motion direction and spatial layout of the environment. Pedestrian poses are recognized according to the spatial body language ratio. The region of interest of detected human is used. Then the centroid of the body relative to its width and height is used to define the pedestrian pose. Motion trajectory is obtained by using point tracking on that centroid, and then motion direction and estimated velocity are determined. Spatial layout is determined by the location of pedestrian with respect to road boundary. Input vector pedestrian pose, motion direction and speed, and the distance from the road lane are used by linear dynamic system. Instead of combining a number of subjects in a single model that will have to deal with the stylistic variations, all the subjects are separately trained in individual models. These models will be then hierarchically separated according to their action. Then, its classification will constrain the models to use for the prediction. Hybrid camera system is performed. A perspective camera is used for pedestrian localization with respect to car speed. And then an omnidirectional camera is used to enlarge field of view of monocular camera. Pedestrians are tracked in 360 degree around the vehicle. Experimental results show that the system has path predictions accuracy with the largest mean errors, 25 cm, for bending trajectories.
Black hole area in Brans-Dicke theory.

We have shown that the dynamics of the scalar field $\phi (x)= ``G^{-1}(x)"$ in Brans-Dicke theories of gravity makes the surface area of the black hole horizon {\it oscillatory} during its dynamical evolution. It explicitly explains why the area theorem does not hold in Brans-Dicke theory. However, we show that there exists a certain non-decreasing quantity defined on the event horizon which is proportional to the black hole entropy for the case of stationary solutions in Brans-Dicke theory. Some numerical simulations have been demonstrated for Oppenheimer-Snyder collapse in Brans-Dicke theory.
The Dark Side of the Mushroom Spring Microbial Mat: Life in the Shadow of Chlorophototrophs. I. Microbial Diversity Based on 16S rRNA Gene Amplicons and Metagenomic Sequencing

Microbial-mat communities in the effluent channels of Octopus and Mushroom Springs within the Lower Geyser Basin at Yellowstone National Park have been studied for nearly 50 years. The emphasis has mostly focused on the chlorophototrophic bacterial organisms of the phyla Cyanobacteria and Chloroflexi. In contrast, the diversity and metabolic functions of the heterotrophic community in the microoxic/anoxic region of the mat are not well understood. In this study we analyzed the orange-colored undermat of the microbial community of Mushroom Spring using metagenomic and rRNA-amplicon (iTag) analyses. Our analyses disclosed a highly diverse community exhibiting a high degree of unevenness, strongly dominated by a single taxon, the filamentous anoxygenic phototroph, Roseiflexus spp. The second most abundant organisms belonged to the Thermotogae, which have been hypothesized to be a major source of H2 from fermentation that could enable photomixotrophic metabolism by Chloroflexus and Roseiflexus spp. Other abundant organisms include two members of the Armatimonadetes (OP10); Thermocrinis sp. ; and phototrophic and heterotrophic members of the Chloroflexi. Further, an Atribacteria (OP9/JS1) member; a sulfate-reducing Thermodesulfovibrio sp. ; a Planctomycetes member; a member of the EM3 group tentatively affiliated with the Thermotogae, as well as a putative member of the Arminicenantes (OP8) represented ≥1% of the reads. Archaea were not abundant in the iTag analysis, and no metagenomic bin representing an archaeon was identified. A high microdiversity of 16S rRNA gene sequences was identified for the dominant taxon, Roseiflexus spp. Previous studies demonstrated that highly similar Synechococcus variants in the upper layer of the mats represent ecological species populations with specific ecological adaptations. This study suggests that similar putative ecotypes specifically adapted to different niches occur within the undermat community, particularly for Roseiflexus spp.
Classification with minimax fast rates for classes of Bayes rules with sparse representation

We construct a classifier which attains the rate of convergence log n/n under sparsity and margin assumptions. An approach close to the one met in approximation theory for the estimation of function is used to obtain this result. The idea is to develop the Bayes rule in a fundamental system of L2([0, 1]d) made of indicator of dyadic sets and to assume that coefficients, equal to −1, 0 or 1, belong to a kind of L1−ball. This assumption can be seen as a sparsity assumption, in the sense that the proportion of coefficients non equal to zero decreases as ”frequency” grows. Finally, rates of convergence are obtained by using an usual trade-off between a bias term and a variance term.
Structured Discriminative Models for Sequential Data Classification

The use of discriminative models for structured classification tasks, such as automatic speech recognition is becoming increasingly popular. The major contribution of this first-year work is we proposed a large margin structured log-linear model for noise robust continuous ASR. An important aspect of log-linear models is the form of the features. The features used in our structured log linear model are derived from generative kernels. This provides an elegant way of combining generative and discriminative models to handle time-varying data. Additionally, since the features are based on the generative models, model-based compensation can be easily performed for noise robustness. Third, the designed joint feature space can be decomposed at the arc level. This allows efficient decoding and training with lattices, which is important for any larger vocabulary extensions. Previous work in this area is extended in two important directions. First, instead of using CML training which is commonly used for discriminative models, this paper describes efficient large margin training based on lattices. Second, efficient lattice-based classification of continuous data is also performed incorporating a joint feature space. Depending on the nature of the joint feature-space and labels, we have proved that this form of model is closely related to structured SVMs and Multi-class SVMs. The model is evaluated on a noise corrupted continuous digit task: AURORA 2.0. Results on the AURORA 2 demonstrate that modelling the structure information yields significant improvements. Current joint features are constructed based on the “most likely” alignment which is given by Viterbi likelihood. An exponential mixture model is proposed as a latent variable extension of structured log linear model. A new joint large margin training framework is proposed for this model which allows both discriminative and generative parameters can be estimated together in a large margin fashion with optimal alignments. An augmented Viterbi searching algorithm is also proposed for efficient training and decoding. The implementation of these extensions will be a part of future work.
Practical Attacks on NFC Enabled Cell Phones

Near Field Communication (NFC) technology enables devices to communicate wirelessly within proximity distance. These NFC devices are often embedded into smart posters that offer the ability to exchange small files, photos and contact details. The Nokia 6212 Classic is currently the most popular NFC phone. It allows users to easily exchange digital objects using the NFC interface. To do so, two phones should be within the proximity coupling distance of 5 cm. This paper shows that the NFC feature that invokes a Bluetooth connection without user consent can be abused to surreptitiously install malicious software on the phone. This results in a serious vulnerability when smart posters start installing malicious software or spreading viruses.
Indonesian Students’ Acquisition of English Address Terms: A Case Study in a University in the United Kingdom

This study explored on how the transfer of Indonesian Address Terms (ATs) influenced the production of English ATs and in what ways Indonesian students accommodated the acquisition of the English ATs during the study abroad. This study focused on the five participants who were recruited through the purposive sampling. Designed to capture the participants’ experiences, this study employed a qualitative case study approach. The written discourse completion test and semi-structured interviews were employed to look at the pragmatic transfer and the acquisition of the address terms. The findings indicated that students’ home cultures of showing politeness by addressing people through contextual variables were challenged under the local cultures which view the equality and casual direct addressing as politeness. Participants were also found to show salient efforts to accommodate the English ATs in multifaceted ways. These efforts shed light to the teaching of English ATs in classroom. Implications to teaching English ATs in classroom in Indonesia are also discussed.
Mapping the sequences of potential guanine quadruplex motifs

The knowledge that potential guanine quadruplex sequences (PQs) are non-randomly distributed in relation to genomic features is now well established. However, this is for a general potential quadruplex motif which is characterized by short runs of guanine separated by loop regions, regardless of the nature of the loop sequence. There have been no studies to date which map the distribution of PQs in terms of primary sequence or which categorize PQs. To this end, we have generated clusters of PQ sequence groups of various sizes and various degrees of similarity for the non-template strand of introns in the human genome. We started with 86 697 sequences, and successively merged them into groups based on sequence similarity, carrying out 66 clustering cycles before convergence. We have demonstrated here that by using complete linkage hierarchical agglomerative clustering such PQ sequence categorization can be achieved. Our results give an insight into sequence diversity and categories of PQ sequences which occur in human intronic regions. We also highlight a number of clusters for which interesting relationships among their members were immediately evident and other clusters whose members seem unrelated, illustrating, we believe, a distinct role for different sequence types.
A review of research on cost of quality models and best practices

This article presents a survey of published literature about various quality costing approaches and reports of their success in order to provide a better understanding of cost of quality (CoQ) methods. Even though the literature review shows an interest by the academic community, a CoQ approach is not utilized in most quality management programs. Nevertheless, evidence is presented which shows that companies that do adopt a CoQ concept are successful in reducing quality costs and improving quality for their customers. The survey shows that the method most commonly implemented is the classical prevention-appraisal-failure (P-A-F) model; however, other quality cost models are used with success as well. The selected CoQ model must suit the situation, the environment, the purpose and the needs of the company in order to have a chance to become a successful systematic tool in a quality management program.
Interprocedural dependence analysis and parallelization

The area of dependence analysis has served as grounds for fruitful research as well as practical implementation. Compilers and tools that utilize dependence information can generate code that takes advantage of parallel resources and storage hierarchies on modern architectures. Here, we offer some historical background on the context and thinking that fostered our 1986 paper. We also attempt to summarize the direction research in this area has taken since the paper's appearance.We present a method that combines a deep analysis of program dependences with a broad analysis of the interaction among procedures. The method is more efficient than existing methods: we reduce many tests, performed separately by existing methods, to a single test. The method is more precise than existing methods with respect to references to multi-dimensional arrays and dependence information hidden by procedure calls. The method is more general than existing methods: we accommodate potentially aliased variables and structures of differing shapes that share storage. We accomplish the above through a unified approach that integrates subscript analysis with aliasing and interprocedural information.
A tutorial on (co)algebras and (co)induction

Algebraic structures which are generated by a collection of constructors| like natural numbers (generated by a zero and a successor) or nite lists and trees| are of well-established importance in computer science. Formally, they are initial algebras. Induction is used both as a deenition principle, and as a proof principle for such structures. But there are also important dual \coalgebraic" structures, which do not come equipped with constructor operations but with what are sometimes called \destructor" operations (also called observers, accessors, transition maps, or mutators). Spaces of innnite data (including, for example, innnite lists, and non-well-founded sets) are generally of this kind. In general, dynamical systems with a hidden, black-box state space, to which a user only has limited access via speciied (observer or mutator) operations, are coalgebras of various kinds. Such coalgebraic systems are common in computer science. And \coinduction" is the appropriate technique in this coalgebraic context, again both as a deenition principle and as a proof principle. The latter involves bisimulations. It is the aim of this tutorial to provide a brief introduction to this relatively new eld of coalgebra.
Improving Jump Point Search

We give online and offline optimisation techniques to improve the performance of Jump Point Search (JPS): a recent and very effective symmetry-breaking algorithm that speeds up pathfinding in computer games. First, we give a new and more efficient procedure for online symmetry breaking by manipulating "blocks'' of nodes at a single time rather than individual nodes. Second, we give a new offline pre-processing technique that can identify jump points apriori in order to further speed up pathfinding search. Third, we enhance the pruning rules of JPS, allowing it to ignore many nodes that must otherwise be expanded. On three benchmark domains taken from real computer games we show that our enhancements can improve JPS performance by anywhere from several factors to over one order of magnitude. We also compare our approaches with SUB: a very recent state-of-the-art offline pathfinding algorithm. We show that our improvements are competitive with this approach and often faster.
A New Algorithm for Human Face Detection Using Skin Color Tone

Human face recognition systems have gained a considerable attention during last decade due to its vast applications in the field of computer and advantages over previous biometric methods. There are many applications with respect to security, sensitivity and secrecy. Face detection is the most important and first step of recognition system. This paper introduces a new approach to face detection systems using the skin color of a subject. This system can detect a face regardless of the background of the picture, which is an important phase for face identification. The images used in this system are color images which give additional information about the images than the gray images provide. In face detection, the two respective classes are the "face area" and the "non-face area". This new approach to face detection is based on color tone values specially defined for skin area detection within the image frame. This system first resizes the image, and then separates it into its component R, G, and B bands. These bands are transformed into another color space which is YCbCr space and then into YC'bC'r space (the skin color tone). The morphological process is implemented on the presented image to make it more accurate. At last, the projection face area is taken by this system to determine the face area. Experimental results show that the proposed algorithm is good enough to localize a human face in an image with an accuracy of 92.69%.
Learning Medical Diagnosis Models from Multiple Experts

Building classification models from clinical data often requires labeling examples by human experts. However, it is difficult to obtain a perfect set of labels everyone agrees on because medical data are typically very complicated and it is quite common that different experts have different opinions on the same patient data. A solution that has been recently explored by the research community is learning from multiple experts/annotators. The objective of learning from multiple experts is to model different characteristics of the human experts and combine them to obtain a consensus model. In this work, we study and develop a new probabilistic approach for learning classification models from labels provided by multiple experts. Our method explicitly models and incorporates three characteristics of annotators into the learning process: their specific prediction model, consistency and bias. We show that in addition to building a superior classification model, our method also helps to model behavior of annotators. We applied the proposed method to learn different characteristics of Physicians labeling clinical records for Heparin Induced Thrombocytopenia (HIT) and combine them in order to obtain a final classifier.