Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Design of Image Operators that Detect Interest Points

This work describes how evolutionary computation can be used to synthesize low-level image operators that detect interesting points on digital images. Interest point detection is an essential part of many modern computer vision systems that solve tasks such as object recognition, stereo correspondence, and image indexing, to name but a few. The design of the specialized operators is posed as an optimization/search problem that is solved with genetic programming (GP), a strategy still mostly unexplored by the computer vision community. The proposed approach automatically synthesizes operators that are competitive with state-of-the-art designs, taking into account an operator's geometric stability and the global separability of detected points during fitness evaluation. The GP search space is defined using simple primitive operations that are commonly found in point detectors proposed by the vision community. The experiments described in this paper extend previous results (Trujillo and Olague, 2006a,b) by presenting 15 new operators that were synthesized through the GP-based search. Some of the synthesized operators can be regarded as improved manmade designs because they employ well-known image processing techniques and achieve highly competitive performance. On the other hand, since the GP search also generates what can be considered as unconventional operators for point detection, these results provide a new perspective to feature extraction research.
Reduced visual acuity in both eyes of monocularly deprived kittens following a short or long period of reverse occlusion

While there can be substantial recovery of vision during reverse occlusion in the deprived eye of kittens that have been monocularly deprived from birth, in many situations this visual improvement does not appear to be retained following the introduction of binocular visual input. This study examines the consequences of periods of reverse occlusion whose onset and duration would be thought to maximize the opportunity for good and permanent recovery of vision in the initially deprived eye. Twenty kittens were monocularly deprived from near birth to either 4, 5, or 6 weeks of age and then reverse occluded for periods that were either very brief (9–18 d) or very long (9–12 weeks). In the former situation, binocular visual experience was introduced when the visual cortex was most susceptible to environmental modification, which would be thought to maximize the opportunity for the eventual development of good vision in both eyes. On the other hand, the long periods of reverse occlusion might be expected to lead to a permanent recovery of vision in only the initially deprived eye, since binocular visual input would have been introduced at a time when the cortex was no longer very plastic. Surprisingly, the end result of both these extreme regimens of reverse occlusion was the same, namely, a severe bilateral amblyopia in which the acuity of both eyes was permanently reduced to levels that were as low as 1/10, but more typically between 1/3 and 1/4 of normal values. Contrast sensitivity functions measured on 2 of the cats that received a brief period of reverse occlusion revealed deficits in contrast sensitivity of about an order of magnitude at all spatial frequencies. These observations have important implications for the nature of the physiological and anatomical changes that occur in the visual cortex during reverse occlusion.
A general algorithm for word graph matrix decomposition

In automatic speech recognition, word graphs (lattices) are commonly used as an approximate representation of the complete word search space. Usually these word lattices are acyclic and have no a-priori structure. More recently a new class of normalized word lattices have been proposed. These word lattices (a.k.a. sausages) are very efficient (space) and they provide a normalization (chunking) of the lattice, by aligning words from all possible hypotheses. We propose a general framework for lattice chunking, the pivot algorithm. There are four important components of the pivot algorithm. First, the time information is not necessary but is beneficial for the overall performance. Second, the algorithm allows the definition of a predefined chunk structure of the final word lattice. Third, the algorithm operates on both weighted and unweighted lattices. Fourth, the labels on the graph are generic, and could be words as well as part of speech tags or parse tags. While the algorithm has applications to many tasks (e.g. parsing, named entity extraction) we present results on the performance of confidence scores for different large vocabulary speech recognition tasks. We compare the results of our algorithms against off-the-shelf methods and show significant improvements.
Redistribution of mannose-6-phosphate receptors induced by tunicamycin and chloroquine

The distribution of Man-6-P receptors was determined by immunoperoxidase cytochemistry in Clone 9 hepatocytes cultured in the presence or absence of tunicamycin and chloroquine, agents that perturb lysosomal enzyme sorting and lead to their secretion. In control (untreated) cells, receptors were localized in cis Golgi cisternae, coated vesicles, and in endosomes or lysosomes. After tunicamycin treatment, receptors were found in coated vesicles lined up along the cis cisternae but were not detected in endosomes or lysosomes. After chloroquine treatment, receptors were localized in large vacuolated endosomes or lysosomes but were not usually detected in Golgi cisternae or in coated vesicles. These results demonstrate a redistribution of receptors along the normal Man-6-P-dependent sorting pathway after these treatments. In ligand-deficient (tunicamycin-treated) cells, immunoreactive receptors accumulate at the presumptive sorting site in the cis Golgi and are depleted from endosomes and lysosomes. When the intralysosomal pH is increased (by chloroquine treatment) preventing ligand-receptor dissociation, receptors accumulate at the presumptive delivery site (lysosomes and endosomes) and are depleted from the cis Golgi region. The findings also suggest that (a) ligand binding triggers movement of the receptor to endosomes or lysosomes, and (b) ligand dissociation triggers their movement back to the cis Golgi region.
Scaling up Pattern Induction for Web Relation Extraction through Frequent Itemset Mining

In this paper, we address the problem of extracting relational information from the Web at a large scale. In particular we present a bootstrapping approach to relation extraction which starts with a few seed tuples of the target relation and induces patterns which can be used to extract further tuples. Our contribution in this paper lies in the formulation of the pattern induction task as a well-known machine learning problem, i.e. the one of determining frequent itemsets on the basis of a set of transactions representing patterns. The formulation of the extraction problem as the task of mining frequent itemsets is not only elegant, but also speeds up the pattern induction step considerably with respect to previous implementations of the bootstrapping procedure. We evaluate our approach in terms of standard measures with respect to seven datasets of varying size and complexity. In particular, by analyzing the extraction rate (extracted tuples per time) we show that our approach reduces the pattern induction complexity from quadratic to linear (in the size of the occurrences to be generalized), while mantaining extraction quality at similar (or even marginally better) levels.
Efficient Heuristic Approach with Improved Time Complexity for Qos-Aware Service Composition

Service-Oriented Architecture enables the composition of loosely coupled services provided with varying Quality of Service (QoS) levels. Given a composition, finding the set of services that optimizes some QoS attributes under given QoS constraints has been shown to be NP-hard. Therefore, heuristic algorithms are widely used, finding acceptable solutions in polynomial time. Still the time complexity of such algorithms can be prohibitive for real-time use, especially if the algorithms are required to run until they find near-optimal solutions. Thus, we propose a heuristic approach based on Hill-Climbing that makes effective use of an initial bias computed with Linear Programming, and works on a reduced search space. In our evaluation, we show that our approach finds near-optimal solutions and achieves a low time complexity.
Taste for Competition and the Gender Gap Among Young Business Professionals

Using an incentivized measure of test for competition, this paper investigates whether this taste explains subsequent gender differences in earnings and industry choice in a sample of high-ability MBA graduates. We find that “competitive” individuals earn 9% more than their less competitive counterparts do. Moreover, gender differences in taste for competition explain around 10% of the overall gender gap. We also find that competitive individuals are more likely to work in high-paying industries nine years later, which suggests that the relation between taste for competition and earnings persists in the long run. Lastly, we find that the effect of taste for competition emerges over time when MBAs and firms interact with each other.
DCS: An Efficient Distributed-Certificate-Service Scheme for Vehicular Networks

In this paper, we propose an efficient distributed-certificate-service (DCS) scheme for vehicular networks. The proposed scheme offers flexible interoperability for certificate service in heterogeneous administrative authorities and an efficient way for any onboard units (OBUs) to update its certificate from the available infrastructure roadside units (RSUs) in a timely manner. In addition, the DCS scheme introduces an aggregate batch-verification technique for authenticating certificate-based signatures, which significantly decreases the verification overhead. Security analysis and performance evaluation demonstrate that the DCS scheme can reduce the complexity of certificate management and achieve excellent security and efficiency for vehicular communications.
Rhodopsin kinetics in the cat retina

The bleaching and regeneration of rhodopsin in the living cat retina was studied by means of fundus reflectometry. Bleaching was effected by continuous light exposures of 1 min or 20 min, and the changes in retinal absorbance were measured at 29 wavelengths. For all of the conditions studied (fractional bleaches of from 65 to 100%), the regeneration of rhodopsin to its prebleach levels required greater than 60 min in darkness. After the 1-min exposures, the difference spectra recorded during the first 10 min of dark adaptation were dominated by photoproduct absorption, and rhodopsin regeneration kinetics were obscured by these intermediate processes. Extending the bleaching duration to 20 min gave the products of photolysis an opportunity to dissipate, and it was possible to follow the regenerative process over its full time-course. It was not possible, however, to fit these data with the simple exponential function predicted by first-order reaction kinetics. Other possible mechanisms were considered and are presented in the text. Nevertheless, the kinetics of regeneration compared favorably with the temporal changes in log sensitivity determined electrophysiologically by other investigators. Based on the bleaching curve for cat rhodopsin, the photosensitivity was determined and found to approximate closely the value obtained for human rhodopsin; i.e., the energy Ec required to bleach 1-e-1 of the available rhodopsin was 7.09 log scotopic troland-seconds (corrected for the optics of the cat eye), as compared with approximately 7.0 in man.
Endothelial Progenitor Cells in Tumor Angiogenesis: Another Brick in the Wall

Until 15 years ago, vasculogenesis, the formation of new blood vessels from undifferentiated cells, was thought to occur only during embryonic development. The discovery of circulating cells that are able to promote vascular regeneration and repair—the so-called endothelial progenitor cells (EPCs)—changed that, and EPCs have since been studied extensively. It is already known that EPCs include many subtypes of cells that play a variety of roles in promoting vascular growth. Some EPCs are destined to differentiate into endothelial cells, whereas others are capable of promoting and sustaining angiogenesis through paracrine mechanisms. Vasculogenesis and angiogenesis might constitute complementary mechanisms for postnatal neovascularization, and EPCs could be at the core of this process. Although the formation of new blood vessels from preexisting vasculature plays a beneficial role in many physiological processes, such as wound healing, it also contributes to tumor growth and metastasis. However, many aspects of the role played by EPCs in tumor angiogenesis remain unclear. This review aims to address the main aspects of EPCs differentiation and certain characteristics of their main function, especially in tumor angiogenesis, as well as the potential clinical applications.
Call Off the Dog(ma): M1/M2 Polarization Is Concurrent following Traumatic Brain Injury

Following the primary mechanical impact, traumatic brain injury (TBI) induces the simultaneous production of a variety of pro- and anti-inflammatory molecular mediators. Given the variety of cell types and their requisite expression of cognate receptors this creates a highly complex inflammatory milieu. Increasingly in neurotrauma research there has been an effort to define injury-induced inflammatory responses within the context of in vitro defined macrophage polarization phenotypes, known as “M1” and “M2”. Herein, we expand upon our previous work in a rodent model of TBI to show that the categorization of inflammatory response cannot be so easily delineated using this nomenclature. Specifically, we show that TBI elicited a wide spectrum of concurrent expression responses within both pro- and anti-inflammatory arms. Moreover, we show that the cells principally responsible for the production of these inflammatory mediators, microglia/macrophages, simultaneously express both “M1” and “M2” phenotypic markers. Overall, these data align with recent reports suggesting that microglia/macrophages cannot adequately switch to a polarized “M1-only” or “M2-only” phenotype, but display a mixed phenotype due to the complex signaling events surrounding them.
Accretion-powered Stellar Winds as a Solution to the Stellar Angular Momentum Problem

We compare the angular momentum extracted by a wind from a pre-main-sequence star to the torques arising from the interaction between the star and its Keplerian accretion disk. We find that the wind alone can counteract the spin-up torque from mass accretion, solving the mystery of why accreting pre-main-sequence stars are observed to spin at less than 10% of breakup speed, provided that the mass outflow rate in the stellar winds is ~10% of the accretion rate. We suggest that such massive winds will be driven by some fraction ϵ of the accretion power. For observationally constrained typical parameters of classical T Tauri stars, ϵ needs to be between a few and a few tens of percent. In this scenario, efficient braking of the star will terminate simultaneously with accretion, as is usually assumed to explain the rotation velocities of stars in young clusters.
Targets and Candidate Agents for Type 2 Diabetes Treatment with Computational Bioinformatics Approach

We sought to explore the molecular mechanism of type 2 diabetes (T2D) and identify potential drug targets and candidate agents for T2D treatment. The differentially expressed genes (DEGs) were assessed between human pancreatic islets with T2D and normal islets. The dysfunctional pathways, the potential transcription factor, and microRNA targets were analyzed by bioinformatics methods. Moreover, a group of bioactive small molecules were identified based on the connectivity map database. The pathways of Eicosanoid Synthesis, TGF-beta signaling pathway, Prostaglandin Synthesis and Regulation, and Integrated Pancreatic Cancer Pathway were found to be significantly dysregulated in the progression of T2D. The genes of ZADH2 (zinc binding alcohol dehydrogenase domain containing 2), BTBD3 (BTB (POZ) domain containing 3), Cul3-based ligases, LTBP1 (latent-transforming growth factor beta binding protein 1), PDGFRA (alpha-type platelet-derived growth factor receptor), and FST (follistatin) were determined to be significant nodes regulated by potential transcription factors and microRNAs. Besides, two small molecules (sanguinarine and DL-thiorphan) were identified to be capable of reverse T2D. In the present study, a systematic understanding for the mechanism underlying T2D development was provided with biological informatics methods. The significant nodes and bioactive small molecules may be drug targets and candidate agents for T2D treatment.
Coaches', athletes' and parents' perceptions of fun in youth sports : assumptions about learning and implications for practice

Children often say fun is the primary reason they play youth sports (e.g., Ewing & Seefeldt, 1990; Wankel & Sefton, 1989). Yet there is relatively little information about specific characteristics that increase children's fun in youth sport. Onehundred forty-seven participants (11 coaches, 19 parents, and 117 children) completed concept maps (Novak & Gowan, 1984) and 17 participants (3 coaches, 5 parents, and 9 children) were interviewed to explore perceptions about what enhances and detracts from children's fun during youth sport experiences in practice and competition. Although participants had differences in their views, all groups seemed to accept assumptions about the apparent conflict between skill development and fun. Results suggested the "core assumption" was that "drills are boring" and "games (both in practice and for competition) are fun. " Consequently, the conceptual framework from Teaching Games for Understanding (Bunker & Thorpe, 1982) is offered as a means to help coaches enhance children's fun in youth sport.
Modulation of β-Adrenergic Receptors in the Ventromedial Hypothalamus Influences Counterregulatory Responses to Hypoglycemia

OBJECTIVE Norepinephrine is locally released into the ventromedial hypothalamus (VMH), a key brain glucose-sensing region in the response to hypoglycemia. As a result, this neurotransmitter may play a role in modulating counterregulatory responses. This study examines whether norepinephrine acts to promote glucose counterregulation via specific VMH β-adrenergic receptors (BAR). RESEARCH DESIGN AND METHODS Awake male Sprague-Dawley rats received, via implanted guide cannulae, bilateral VMH microinjections of 1) artificial extracellular fluid, 2) B2AR agonist, or 3) B2AR antagonist. Subsequently, a hyperinsulinemic-hypoglycemic clamp study was performed. The same protocol was also used to assess the effect of VMH delivery of a selective B1AR or B3AR antagonist. RESULTS Despite similar insulin and glucose concentrations during the clamp, activation of B2AR in the VMH significantly lowered by 32% (P < 0.01), whereas VMH B2AR blockade raised by 27% exogenous glucose requirements during hypoglycemia (P < 0.05) compared with the control study. These changes were associated with alternations in counterregulatory hormone release. Epinephrine responses throughout hypoglycemia were significantly increased by 50% when the B2AR agonist was delivered to the VMH (P < 0.01) and suppressed by 32% with the B2AR antagonist (P < 0.05). The glucagon response was also increased by B2AR activation by 63% (P < 0.01). Neither blockade of VMH B1AR nor B3AR suppressed counterregulatory responses to hypoglycemia. Indeed, the B1AR antagonist increased rather than decreased epinephrine release (P < 0.05). CONCLUSIONS Local catecholamine release into the VMH enhances counterregulatory responses to hypoglycemia via stimulation of B2AR. These observations suggest that B2AR agonists might have therapeutic benefit in diabetic patients with defective glucose counterregulation.
Link Failure Recovery over Very Large Arbitrary Networks: The Case of Coding

Network coding-based link failure recovery techniques provide near-hitless recovery and offer high capacity efficiency. Diversity coding is the first technique to incorporate coding in this field and is easy to implement over small arbitrary networks. However, its capacity efficiency is restricted by its systematic coding and high design complexity even though its design complexity is lower than the other coding-based recovery techniques. Alternative techniques mitigate some of these limitations, but they are difficult to implement over arbitrary networks. In this paper, we propose a simple column generation-based design algorithm and a novel advanced diversity coding technique to achieve near-hitless recovery over arbitrary networks. The design framework consists of two parts: a main problem and subproblem. Main problem is realized with Linear Programming (LP) and Integer Linear Programming (ILP), whereas the subproblem can be realized with different methods. The simulation results suggest that both the novel coding structure and the novel design algorithm lead to higher capacity efficiency for near-hitless recovery. The novel design algorithm simplifies the capacity placement problem which enables implementing diversity coding-based techniques on very large arbitrary networks.
Categories and word meanings are not single entities in the mind

But the idea that categories and word meanings are single mental entities can also have a distributed connectionist interpretation. In distributed connectionist models an entity is not represented by a single network unit as in localist connectionist models. However, categories or word meanings can be considered as corresponding to some particular pattern of activation on an ensemble of network units and therefore still interpreted as single entities. Categories and word meanings tend to be interpreted as single entities that are activated in the mind when an individual categorizes the world or uses language. We argue that this view is mistaken. Connectionist simulations of populations of neural networks that live and reproduce in an environment show that categories and word meanings are open and changing collections of activation patterns in the network’s internal units rather than single activation patterns.
Factors of academic procrastination: The role of perfectionism, anxiety and depression

This study investigated dimensions of perfectionism, anxiety, and depression as factors of academic procrastination. Our main research interest was to examine the role of specific dimensions of perfectionism as moderators in the relationship between anxiety and depression and academic procrastination. Four scales were administered on the sample of 403 students: perfectionism scale FMPS, academic procrastination scale APS-SI, depression scale CESD and anxiety scale STAI-X2. The results showed significant positive relationships between maladaptive dimensions of perfectionism, anxiety, depression, and academic procrastination. In addition, results showed significant negative associations between adaptive dimensions of perfectionism and academic procrastination. Certain dimensions of perfectionism, anxiety, and depression proved to be significant predictors of academic procrastination. The dimensions of perfectionism and academic procrastination were also significantly related to anxiety and depression, which both predicted academic procrastination. The relationship between anxiety levels and academic procrastination was moderated by personal standards (as adaptive dimension of perfectionism), while the relationship between depression levels and academic procrastination was moderated by the maladaptive dimension of parents’ expectations.