Miracle-dz/UniFAR-FTUs huggingface dataset:
Language Proficiency and Sustained Attention in Monolingual and Bilingual Children with and without Language Impairment

Background: The language profiles of children with language impairment (LI) and bilingual children can show partial, and possibly temporary, overlap. The current study examined the persistence of this overlap over time. Furthermore, we aimed to better understand why the language profiles of these two groups show resemblance, testing the hypothesis that the language difficulties of children with LI reflect a weakened ability to maintain attention to the stream of linguistic information. Consequent incomplete processing of language input may lead to delays that are similar to those originating from reductions in input frequency. Methods: Monolingual and bilingual children with and without LI (N = 128), aged 5–8 years old, participated in this study. Dutch receptive vocabulary and grammatical morphology were assessed at three waves. In addition, auditory and visual sustained attention were tested at wave 1. Mediation analyses were performed to examine relationships between LI, sustained attention, and language skills. Results: Children with LI and bilingual children were outperformed by their typically developing (TD) and monolingual peers, respectively, on vocabulary and morphology at all three waves. The vocabulary difference between monolinguals and bilinguals decreased over time. In addition, children with LI had weaker auditory and visual sustained attention skills relative to TD children, while no differences between monolinguals and bilinguals emerged. Auditory sustained attention mediated the effect of LI on vocabulary and morphology in both the monolingual and bilingual groups of children. Visual sustained attention only acted as a mediator in the bilingual group. Conclusion: The findings from the present study indicate that the overlap between the language profiles of children with LI and bilingual children is particularly large for vocabulary in early (pre)school years and reduces over time. Results furthermore suggest that the overlap may be explained by the weakened ability of children with LI to sustain their attention to auditory stimuli, interfering with how well incoming language is processed.
Hypnos: An ultra-low power sleep mode with SRAM data retention for embedded microcontrollers!

In heavily duty-cycled embedded systems, the energy consumed by the microcontroller in idle mode is often the bottleneck for battery lifetime. Existing solutions address this problem by placing the microcontroller in a low power (sleep) state when idle, and preserving application state either by retaining the data in-situ in SRAM, or by checkpointing it to FLASH. However, both these approaches have notable drawbacks. In-situ data retention requires the SRAM to remain powered in sleep mode, while checkpointing to FLASH involves significant energy and time overheads. This paper proposes a new ultra-low power sleep mode for micro-controllers that overcomes the limitations of both these ap- proaches. Our technique, HYPNOS, is based on the key observation that the on-chip SRAM in a microcontroller exhibits 100% data retention even at a much lower supply voltage (as much as 10x lower) than the typical operating voltage of the microcontroller. HYPNOS exploits this observation by performing extreme voltage scaling when the microcontroller is in sleep mode. We implement and evaluate HYPNOS for the TI MSP430G2452 microcontroller and show that the MCU draws only 26nA in the proposed sleep mode, which is 4× lower than any existing sleep mode that preserves SRAM contents. Further, we show that a complete wireless sensing system using HYPNOS only depletes battery capacity by 42.6nAh in an hour. By decreasing the average power consumption to such minuscule levels, HYPNOS takes a significant step forward in making perpetual systems a reality through the use of energy harvesting.
A Nonparametric Bayesian Approach to Uncovering Rat Hippocampal Population Codes During Spatial Navigation

Rodent hippocampal population codes represent important spatial information about the environment during navigation. Several computational methods have been developed to uncover the neural representation of spatial topology embedded in rodent hippocampal ensemble spike activity. Here we extend our previous work and propose a nonparametric Bayesian approach to infer rat hippocampal population codes during spatial navigation. To tackle the model selection problem, we leverage a nonparametric Bayesian model. Specifically, to analyze rat hippocampal ensemble spiking activity, we apply a hierarchical Dirichlet process-hidden Markov model (HDP-HMM) using two Bayesian inference methods, one based on Markov chain Monte Carlo (MCMC) and the other based on variational Bayes (VB). We demonstrate the effectiveness of our Bayesian approaches on recordings from a freely-behaving rat navigating in an open field environment. We find that MCMC-based inference with Hamiltonian Monte Carlo (HMC) hyperparameter sampling is flexible and efficient, and outperforms VB and MCMC approaches with hyperparameters set by empirical Bayes.
Genetics in primary care. Report on workshop of EC Concerted Action on Genetics Services in Europe (CAGSE) in association with the Royal College of GP Spring Meeting, Blackpool, UK, 28 April 1995.

The Royal College ofGP Spring Meeting lasted three days with half of this time devoted to genetic topics. There were plenary talks by Walter Bodmer, Alex Markham, and Andrew Read and a well attended panel discussion on ethical issues arising from genetics. An EC Workshop on primary care genetics was organised as a satellite of the RCGP meeting. The success of this workshop led to an open conference on Primary Care Genetics at the Royal Society of Medicine in London on 18 November 1995 where the main points and conclusions were discussed by a large audience of general practitioners and others. The workshop was organised because molecular genetics, clinical genetics, and rising public expectations are creating increasing demands on healthcare systems. It appears unlikely that geneticists alone will be able to cope with the volume of work generated. Primary care based healthcare systems are recognised to be economical while primary care teams, where they exist, have long term "guardianship" of patients' interests. Primary care must work in partnership with specialist genetics centres in the development of effective and cost effective population genetic services. The workshop participants* were multidisciplinary including people from Britain, Germany, and The Netherlands working in primary care, multidisciplinary medical genetics, public health, and social sciences. Rodney Harris described the EC Concerted Action on Genetic Services (CAGSE) in the context of the different health care systems, multilingual and multicultural societies of Europe. ' CAGSE is reviewing and recommending improvements in genetics, including the involvement of primary care. The partnerst in CAGSE are leading medical geneticists, working with sociologists and others to produce for each country a detailed report using a standard
The Role of Coincidence-Detector Neurons in the Reliability and Precision of Subthreshold Signal Detection in Noise

Subthreshold signal detection is an important task for animal survival in complex environments, where noise increases both the external signal response and the spontaneous spiking of neurons. The mechanism by which neurons process the coding of signals is not well understood. Here, we propose that coincidence detection, one of the ways to describe the functionality of a single neural cell, can improve the reliability and the precision of signal detection through detection of presynaptic input synchrony. Using a simplified neuronal network model composed of dozens of integrate-and-fire neurons and a single coincidence-detector neuron, we show how the network reads out the subthreshold noisy signals reliably and precisely. We find suitable pairing parameters, the threshold and the detection time window of the coincidence-detector neuron, that optimize the precision and reliability of the neuron. Furthermore, it is observed that the refractory period induces an oscillation in the spontaneous firing, but the neuron can inhibit this activity and improve the reliability and precision further. In the case of intermediate intrinsic states of the input neuron, the network responds to the input more efficiently. These results present the critical link between spiking synchrony and noisy signal transfer, which is utilized in coincidence detection, resulting in enhancement of temporally sensitive coding scheme.
Toward an Architecture for Never-Ending Language Learning

We consider here the problem of building a never-ending language learner; that is, an intelligent computer agent that runs forever and that each day must (1) extract, or read, information from the web to populate a growing structured knowledge base, and (2) learn to perform this task better than on the previous day. In particular, we propose an approach and a set of design principles for such an agent, describe a partial implementation of such a system that has already learned to extract a knowledge base containing over 242,000 beliefs with an estimated precision of 74% after running for 67 days, and discuss lessons learned from this preliminary attempt to build a never-ending learning agent.
A multi-level representation of f0 using the continuous wavelet transform and the Discrete Cosine Transform

We propose a representation of f0 using the Continuous Wavelet Transform (CWT) and the Discrete Cosine Transform (DCT). The CWT decomposes the signal into various scales of selected frequencies, while the DCT compactly represents complex contours as a weighted sum of cosine functions. The proposed approach has the advantage of combining signal decomposition and higher-level representations, thus modeling low-frequencies at higher levels and high-frequencies at lower-levels. Objective results indicate that this representation improves f0 prediction over traditional short-term approaches. Subjective results show that improvements are seen over the typical MSD-HMM and are comparable to the recently proposed CWT-HMM, while using less parameters. These results are discussed and future lines of research are proposed.
MultiView: Multilevel video content representation and retrieval

In this article, several practical algorithms are proposed to support content-based video analysis, modeling, representation, summarization, indexing, and access. First, a multilevel video data- base model is given. One advantage of this model is that it provides a reasonable approach to bridging the gap between low-level rep- resentative features and high-level semantic concepts from a hu- man point of view. Second, several model-based video analysis techniques are proposed. In order to detect the video shots, we present a novel technique, which can adapt the threshold for scene cut detection to the activities of variant videos or even different video shots. A seeded region aggregation and temporal tracking technique is proposed for generating the semantic video objects. The semantic video scenes can then be generated from these extracted video access units (e.g., shots and objects) according to some domain knowledge. Third, in order to categorize video contents into a set of semantic clusters, an integrated video classification technique is de- veloped to support more efficient multilevel video representation, summarization, indexing, and access techniques. © 2001 SPIE and
Efficacy of In-Hospital Multidimensional Interventions of Secondary Prevention After Acute Coronary Syndrome: A Systematic Review and Meta-Analysis

Background— Secondary prevention programs for patients experiencing an acute coronary syndrome have been shown to be effective in the outpatient setting. The efficacy of in-hospital prevention interventions administered soon after acute cardiac events is unclear. We performed a systematic review and meta-analysis to determine whether in-hospital, patient-level interventions targeting multiple cardiovascular risk factors reduce all-cause mortality after an acute coronary syndrome. Methods and Results— Using a prespecified search strategy, we included controlled clinical trials and before-after studies of secondary prevention interventions with at least a patient-level component (ie, education, counseling, or patient-specific order sets) initiated in hospital with outcomes of mortality, readmission, or reinfarction rates in acute coronary syndrome patients. We classified the interventions as patient-level interventions with or without associated healthcare provider–level interventions and/or system-level interventions. Twenty-six studies met our inclusion criteria. The summary estimate of 14 studies revealed a relative risk of all-cause mortality of 0.79 (95% CI, 0.69 to 0.92; n=37′585) at 1 year. However, the apparent benefit depended on study design and level of intervention. The before-after studies suggested reduced mortality (relative risk [RR], 0.77; 95% CI, 0.66 to 0.90; n=3680 deaths), whereas the RR was 0.96 (95% CI, 0.64 to 1.44; n=99 deaths) among the controlled clinical trials. Only interventions including a provider- or system-level intervention suggested reduced mortality compared with patient-level–only interventions. Conclusions— The evidence for in-hospital, patient-level interventions for secondary prevention is promising but not definitive because only before-after studies suggest a significant reduction in mortality. Future research should formally test which components of interventions provide the greatest benefit.
Drug-induced hypersensitivity syndrome induced by clindamycin.

© 2013 The Authors. doi: 10.2340/00015555-1363 Journal Compilation © 2013 Acta Dermato-Venereologica. ISSN 0001-5555 Drug-induced hypersensitivity syndrome (DIHS), also known as drug rash with eosinophilia and systemic symptoms (DRESS), is a severe, adverse drug reaction characterized by skin rash, fever, lymphadenopathy, hepatitis and haematological abnormalities (1, 2). The presence of human herpes virus (HHV)-6 reactivation is considered to be a diagnostic criterion for DIHS but not for DRESS. The most common causative drugs are carbamazepine, phenytoin, phenobarbital, mexiletine, dapsone, salazosulphapyridine, minocycline and allopurinol (3). We report here a case of DIHS/DRESS caused by clindamycin, which was confirmed using the lymphocyte transformation test (LTT) and patch testing.
Human parieto–occipital visual cortex: lack of retinotopy and foveal magnification

We studied visual representation in the parietal cortex by recording whole-scalp neuromagnetic responses to luminance stimuli of varying eccentricities. The stimuli were semicircles (5.5 degrees in radius) presented at horizontal eccentricities from 0 degrees to 16 degrees, separately in the right and left hemifields. All stimuli evoked responses in the contralateral occipital and medial parietal areas. The waveforms and distributions of the occipital responses varied with stimulus side (left, right) and eccentricity, whereas the parietal responses were remarkably similar to all stimuli. The equivalent sources of the parietal signals clustered within 1 cm3 in the medial parieto–occipital sulcus and did not differ significantly between the stimuli. The strength of the parietal activation remained practically constant with increasing stimulus eccentricity, suggesting that the visual areas in the parieto–occipital sulcus lack the enhanced foveal representation typical of most other visual areas. This result strengthens our previous suggestion that the medial parieto–occipital sulcus is the human homologue of the monkey V6 complex, characterized by, for example, lack of retinotopy and the absence of relative foveal magnification.
Robust next release problem: handling uncertainty during optimization

Uncertainty is inevitable in real world requirement engineering. It has a significant impact on the feasibility of proposed solutions and thus brings risks to the software release plan. This paper proposes a multi-objective optimization technique, augmented with Monte-Carlo Simulation, that optimizes requirement choices for the three objectives of cost, revenue, and uncertainty. The paper reports the results of an empirical study over four data sets derived from a single real world data set. The results show that the robust optimal solutions obtained by our approach are conservative compared to their corresponding optimal solutions produced by traditional Multi-Objective Next Release Problem. We obtain a robustness improvement of at least 18% at a small cost (a maximum 0.0285 shift in the 2D Pareto-front in the unit space). Surprisingly we found that, though a requirement's cost is correlated with inclusion on the Pareto-front, a requirement's expected revenue is not.
Handbook of perception and human performance

Written by well-known specialists, here is a comprehensive handbook on human perception and performance. Volume one covers theory and methods; basic visual processes; auditory, kinesthetic, cutaneous, and vestibular senses; and space and motion perception. Volume two treats information processing, perceptual organization and cognition, and human performance. Organized to facilitate reference usefulness, these volumes provide substantial cross-referencing and extensive use of illustrations. In addition, a substantial amount of tutorial material is provided, with several hundred pages devoted to the elucidation of the conceptual and methodological underpinnings of the more substantive chapters. Figure legends are extremely detailed to enhance their reference usefulness without having to search accompanying text for relevant coverage.
Spin-it

Spinning tops and yo-yos have long fascinated cultures around the world with their unexpected, graceful motions that seemingly elude gravity. We present an algorithm to generate designs for spinning objects by optimizing rotational dynamics properties. As input, the user provides a solid 3D model and a desired axis of rotation. Our approach then modifies the mass distribution such that the principal directions of the moment of inertia align with the target rotation frame. We augment the model by creating voids inside its volume, with interior fill represented by an adaptive multi-resolution voxelization. The discrete voxel fill values are optimized using a continuous, nonlinear formulation. Further, we optimize for rotational stability by maximizing the dominant principal moment. We extend our technique to incorporate deformation and multiple materials for cases where internal voids alone are insufficient. Our method is well-suited for a variety of 3D printed models, ranging from characters to abstract shapes. We demonstrate tops and yo-yos that spin surprisingly stably despite their asymmetric appearance.
Exact Learning of Lightweight Description Logic Ontologies

We study learning of description logic TBoxes in Angluin et al.'s framework of exact learning via queries. We admit entailment queries ("is a given subsumption entailed by the target TBox? ") and equivalence queries ("is a given TBox equivalent to the target TBox? "), assuming that the signature and logic of the target TBox are known. We present three main results: (1) TBoxes formulated in DL-Lite with role inclusions and composite concepts on the right-hand side of concept inclusions can be learned in polynomial time; (2) EL TBoxes with only concept names on the right-hand side of concept inclusions can be learned in polynomial time; and (3) EL TBoxes cannot be learned in polynomial time. It follows that non-polynomial time learnability of EL TBoxes is caused by the interaction between existential restrictions on the right- and left-hand sides of concept inclusions. We also show that neither entailment nor equivalence queries alone are sufficient in cases (1) and (2) above.
Lack of Association between PTPN22 Gene +1858 C>T Polymorphism and Susceptibility to Generalized Vitiligo in a Turkish Population

Background Vitiligo is an autoimmune polygenic disorder characterized by loss of pigmentation due to melanocyte destruction. The PTPN22 gene +1858 C>T single nucleotide polymorphism (rs2476601) has been shown to be associated with various autoimmune disorders. Objective The aim of this study was to investigate whether the PTPN22 gene +1858 C>T single nucleotide polymorphism is associated with susceptibility to generalized vitiligo in a Turkish population. Methods One hundred and seven patients with generalized vitiligo, and one hundred and twelve gender-, age-, and ethnic-matched controls were enrolled in the study. Genotyping was done by polymerase chain reaction-restriction fragment length polymorphism. Results The PTPN22 +1858 C>T genotype and allele frequencies of the generalized vitiligo patients did not differ significantly from those of healthy controls. Conclusion We found no association between the PTPN22 +1858 C>T gene polymorphism and vitiligo susceptibility in Turkish generalized-vitiligo patients.
Duplicate detection in consumer photography and news video

Consumers often make more than one photograph of the same scene, creating non-identical duplicates and near duplicates. In Kodak's consumer photography database, on average, 19% of the images, per roll, fall into this category. Automatic detection of duplicates, therefore, is extremely useful in applications that help users organize their image collections. We introduce the challenging problem of non-identical duplicate image detection in consumer photography, describe STELLA (a novel interactive personal image collection organization system), and give an overview of our novel framework for detecting duplicate and near duplicate consumer photographs and news videos.
Online Learning of Assignments that Maximize Submodular Functions

Which ads should we display in sponsored search in order to maximize our revenue? How should we dynamically rank information sources to maximize value of information? These applications exhibit strong diminishing returns: Selection of redundant ads and information sources decreases their marginal utility. We show that these and other problems can be formalized as repeatedly selecting an assignment of items to positions to maximize a sequence of monotone submodular functions that arrive one by one. We present an efficient algorithm for this general problem and analyze it in the no-regret model. Our algorithm possesses strong theoretical guarantees, such as a performance ratio that converges to the optimal constant of 1-1/e. We empirically evaluate our algorithm on two real-world online optimization problems on the web: ad allocation with submodular utilities, and dynamically ranking blogs to detect information cascades.