Miracle-dz/UniFAR-FTUs huggingface dataset:
Early sensitivity of evoked potentials to surface and volumetric structure during the visual perception of three‐dimensional object shape

This study used event‐related potentials (ERPs) to elucidate how the human visual system processes three‐dimensional (3‐D) object shape structure. In particular, we examined whether the perceptual mechanisms that support the analysis of 3‐D shape are differentially sensitive to higher order surface and volumetric part structure. Observers performed a whole‐part novel object matching task in which part stimuli comprised sub‐regions of closed edge contour, surfaces or volumetric parts. Behavioural response latency data showed an advantage in matching surfaces and volumetric parts to whole objects over contours, but no difference between surfaces and volumes. ERPs were analysed using a convergence of approaches based on stimulus dependent amplitude modulations of evoked potentials, topographic segmentation, and spatial frequency oscillations. The results showed early differential perceptual processing of contours, surfaces, and volumetric part stimuli. This was first reliably observed over occipitoparietal electrodes during the N1 (140–200 ms) with a mean peak latency of 170 ms, and continued on subsequent P2 (220–260 ms) and N2 (260–320 ms) components. The differential sensitivity in perceptual processing during the N1 was accompanied by distinct microstate patterns that distinguished among contours, surfaces and volumes, and predominant theta band activity around 4–7 Hz over right occipitoparietal and orbitofrontal sites. These results provide the first evidence of early differential perceptual processing of higher order surface and volumetric shape structure within the first 200 ms of stimulus processing. The findings challenge theoretical models of object recognition that do not attribute functional significance to surface and volumetric object structure during visual perception.
Proteomic Analysis of Plasmodesmata From Populus Cell Suspension Cultures in Relation With Callose Biosynthesis

Plasmodesmata are channels that link adjacent cells in plant tissues through which molecular exchanges take place. They are involved in multiple processes vital to plant cells, such as responses to hormonal signaling or environmental challenges including osmotic stress, wounding and pathogen attack. Despite the importance of plasmodesmata, their proteome is not well-defined. Here, we have isolated fractions enriched in plasmodesmata from cell suspension cultures of Populus trichocarpa and identified 201 proteins that are enriched in these fractions, thereby providing further insight on the multiple functions of plasmodesmata. Proteomics analysis revealed an enrichment of proteins specifically involved in responses to stress, transport, metabolism and signal transduction. Consistent with the role of callose deposition and turnover in the closure and aperture of the plasmodesmata and our proteomic analysis, we demonstrate the enrichment of callose synthase activity in the plasmodesmata represented by several gene products. A new form of calcium-independent callose synthase activity was detected, in addition to the typical calcium-dependent enzyme activity, suggesting a role of calcium in the regulation of plasmodesmata through two forms of callose synthase activities. Our report provides the first proteomic investigation of the plasmodesmata from a tree species and the direct biochemical evidence for the occurrence of several forms of active callose synthases in these structures. Data are available via ProteomeXchange with identifier PXD010692.
Nudging Neural Conversational Model with Domain Knowledge

Neural conversation models are attractive because one can train a model directly on dialog examples with minimal labeling. With a small amount of data, however, they often fail to generalize over test data since they tend to capture spurious features instead of semantically meaningful domain knowledge. To address this issue, we propose a novel approach that allows any human teachers to transfer their domain knowledge to the conversation model in the form of natural language rules. We tested our method with three different dialog datasets. The improved performance across all domains demonstrates the efficacy of our proposed method.
Learning Where to Fixate on Foveated Images

Foveation, the ability to sequentially acquire high-acuity regions of a scene viewed initially at low-acuity, is a key property of biological vision systems. In a computer vision system, foveation is also desired to increase data efficiency and derive task-relevant features. Yet, most existing deep learning models lack the ability to foveate. In this paper, we propose a deep reinforcement learning-based foveation model, DRIFT, and apply it to challenging fine-grained classification tasks. Training of DRIFT requires only image-level category labels and encourages fixations to contain discriminative information while maintaining data efficiency. Specifically, we formulate foveation as a sequential decision-making process and train a foveation actor network with a novel Deep Deterministic Policy Gradient by Conditioned Critic and Coaching (DDPGC3) algorithm. In addition, we propose to shape the reward to provide informative feedback after each fixation to better guide the RL training. We demonstrate the effectiveness of our method on five fine-grained classification benchmark datasets, and show that the proposed approach achieves state-of-the-art performance using an order-of-magnitude fewer pixels.
Sistemas Tutores Inteligentes que Detectam as Emoções dos Estudantes: um Mapeamento Sistemático

As emoções vivenciadas pelos estudantes podem influenciar negativamente ou positivamente o aprendizado. Dessa forma, a detecção das emoções dos estudantes por softwares educacionais, como Sistemas Tutores Afetivos (STAs), permite a esses sistemas fornecer uma resposta mais adequada com objetivo de maximizar o aprendizado. Esse artigo apresenta um mapeamento sistemático que foi conduzido com o objetivo de investigar os mecanismos de detecção das emoções empregados por STAs. No total, foram analisados 462 estudos na área. Dentre estes estudos, 84 deles estavam relacionados com STAs e apenas 40 deles satisfizeram os critérios de inclusão e exclusão definidos neste trabalho. Como resultado, verificou-se que a maioria dos estudos usa a análise das expressões faciais como fonte principal de reconhecimento da emoção do estudante, seguido de sinais fisiológicos, linguística e dados comportamentais. Embora existam vários mecanismos para a detecção da emoção do estudante, ainda há carência de estudos que expliquem a relação entre emoções e aprendizado, bem como quais caminhos devem ser seguidos utilizando estas emoções com o propósito de tornar o ensino e a aprendizagem mais efetivos.
All roads lead to Rome: Many ways to double spend your cryptocurrency

In 2008, Satoshi Nakamoto proposed an electronic cash system (bitcoin) that is completely realized by peer-to-peer technology. The core value of this scheme is that it proposes a solution based on Proof-of Work, so that the cash system can run in a peer-to-peer environment and be able to prevent double-spend attacks. Bitcoin has been developed for ten years, and since then countless digital currencies have been created. But the discussion of double-spend attacks seems to still concentrate on 51% Attacks. In fact, our research has found that there are many other way to achieve double-spend attacks. In this paper, by introducing a number of double-spend attack vulnerabilities that we have found in EOS, NEO and other large blockchain platforms, we summarized various reasons for causing double-spend attacks, and propose an efficient mitigation measure against them.
Detecting The Objects on The Road Using Modular Lightweight Network

This paper presents a modular lightweight network model for road objects detection, such as car, pedestrian and cyclist, especially when they are far away from the camera and their sizes are small. Great advances have been made for the deep networks, but small objects detection is still a challenging task. In order to solve this problem, majority of existing methods utilize complicated network or bigger image size, which generally leads to higher computation cost. The proposed network model is referred to as modular feature fusion detector (MFFD), using a fast and efficient network architecture for detecting small objects. The contribution lies in the following aspects: 1) Two base modules have been designed for efficient computation: Front module reduce the information loss from raw input images; Tinier module decrease model size and computation cost, while ensuring the detection accuracy. 2) By stacking the base modules, we design a context features fusion framework for multi-scale object detection. 3) The propose method is efficient in terms of model size and computation cost, which is applicable for resource limited devices, such as embedded systems for advanced driver assistance systems (ADAS). Comparisons with the state-of-the-arts on the challenging KITTI dataset reveal the superiority of the proposed method. Especially, 100 fps can be achieved on the embedded GPUs such as Jetson TX2.
Register in computational language research

Shlomo Argamon is Professor of Computer Science and Director of the Master of Data Science Program at the Illinois Institute of Technology (USA). In this article, he reflects on the current and potential relationship between register and the field of computational linguistics. He applies his expertise in computational linguistics and machine learning to a variety of problems in natural language processing. These include stylistic variation, forensic linguistics, authorship attribution, and biomedical informatics. He is particularly interested in the linguistic structures used by speakers and writers, including linguistic choices that are influenced by social variables such as age, gender, and register, as well as linguistic choices that are unique or distinctive to the style of individual authors. Argamon has been a pioneer in computational linguistics and NLP research in his efforts to account for and explore register variation. His computational linguistic research on register draws inspiration from Systemic Functional Linguistics, Biber’s multi-dimensional approach to register variation, as well as his own extensive experience accounting for variation within and across text types and authors. Argamon has applied computational methods to text classification and description across registers – including blogs, academic disciplines, and news writing – as well as the interaction between register and other social variables, such as age and gender. His cutting-edge research in these areas is certain to have a lasting impact on the future of computational linguistics and NLP.
Toward Worldview Pluralism in Psychology

Human beings are powerfully shaped—and divided—by their worldviews, or beliefs about ultimate questions. Implicitly or explicitly, we carry with us beliefs about the nature of reality (ontology), about right and wrong (ethics), and about how we come to know the world (epistemology). The doubly challenging thing about these beliefs is they are not only inherently contested, but there is also no worldview-neutral way to determine which ontology, ethic, or epistemology we should adopt. Neither, as I hope to show, is it possible to live our lives—including our lives as psychologists —in a worldview-neutral way. Although our discipline emerged in the 19th century with the promise of a method-wrought worldview-neutrality, this promise has not been fulfi lled. Indeed, this volume has argued that worldviews are powerfully transmitted through our sociocultural practices such as training (Chapter 2 ), our psychotherapy (Chapter 3 ), our research (Chapter 4 ), and our study of culture (Chapter 5 ). The remaining question is: what shall we do about this? This chapter will argue for what may alternatively be called worldview pluralism or worldview diversity. Though the widely used term viewpoint diversity 1 is helpful, the notion of worldview diversity hopes to expand the contemporary conversation beyond the current focus on political or moral viewpoints, and include the differing ontological and epistemological assumptions that psychologists believe. By employing the notion of pluralism , we intend to take advantage of the twofold meaning of the term. The first sense of the term has to do with the simple reality that psychologists are not entirely monolithic in their worldviews. The second sense Toward Worldview Pluralism in Psychology
Apprentissage progressif en analyse discriminante

L'analyse discriminante affecte une unite statistique a un groupe selon une regle de decision obtenue a partir d'un echantillon d'apprentissage. Cette procedure suppose que les conditions d'utilisation restent celles de l'apprentissage, ce qui n'est pas toujours garanti. Sous des hypotheses assez larges, il est cependant possible de faire face a une derive inconnue des conditions experimentales. Nous introduisons pour cela une analyse convenablement modifiee qui complete l'apprentissage initial par un controle progressif des conditions d'utilisation. Un exemple reel permet de montrer la mise en oeuvre concrete de la methode ainsi que son efficacite.
Space Management in Private Domestic Buildings: Comparing Elderly Age Groups in Hong Kong

Private domestic (PD) buildings in Hong Kong involve mass housing estates provided by developers; these estates feature clusters of high-rise buildings. Although building regulations are followed by the construction professionals in the industry, there are no specific guidelines relating to space management (SM) for elderly people living in PD buildings in Hong Kong. Elderly people may need extra space for their daily life, due to their physical disabilities. This directly affects their affordability for renting and/or purchasing an apartment that meets their needs. To understand the potential cost of housing for the elderly, this study aimed to identify the importance of key SM items in PD buildings for elderly people belonging to different age groups. A questionnaire survey was conducted among elderly people, of different age groups, living in PD buildings; data from a total of 89 respondents were purposively collected. This study identified 11 SM items, including distances between rooms, the size of various rooms, the width of doors, turning spaces at doors, and indoor barrier-free access. The results of the statistical analysis indicated a significant difference among the different age groups with respect to the respondents’ satisfaction with the distances between rooms in their PD buildings; there was no significant difference among the different age groups with respect to their satisfaction with the size of their rooms. This may be because the energy needed for walking declines in later life. In addition, the satisfaction of the different age groups with the size of their rooms and the indoor barrier-free designs of their unit flats was lower than their satisfaction with the distances between their rooms. Therefore, construction professionals are urged to seriously consider the distances between rooms inside the unit flats for elderly people, in order to reduce the housing costs of the occupants.
Un modelo numérico para la dinámica de vigas de pared delgada fracturadas por fatiga: Aplicación a la identificación de daños

En este trabajo se presenta un modelo teorico para el analisis dinamico de vigas abiertas de pared delgada con presencia de dano por fatiga. El modelo resulta aplicable a vigas construidas con material metalico o laminado compuesto (para configuraciones ortotropas o simetricos balanceados). Tal teoria, implementada mediante una formulacion de elementos finitos, es utilizada para la identificacion de fallas por fatiga a partir de medicion directa de la respuesta forzada estacionaria. Para ello la diferencia cuadratica entre valores teoricos y experimentales de amplitudes de vibracion constituye la funcion objetivo a minimizar para determinar los parametros asociados al dano. Para realizar este procedimiento de optimizacion se hace uso de un metodo evolutivo. La precision del modelo se valida mediante comparacion de los resultados obtenidos con sus correspondientes provenientes de un modelo numerico de elementos lamina.
Simulated Arctic atmospheric feedbacks associated with late summer sea ice anomalies

The coupled regional climate model HIRHAM‐NAOSIM is used to investigate feedbacks between September sea ice anomalies in the Arctic and atmospheric conditions in autumn and the subsequent winter. A six‐member ensemble of simulations spanning the period 1949–2008 is analyzed. The results show that negative Arctic sea ice anomalies are associated with increased heat and moisture fluxes, decreased static stability, increased lower tropospheric moisture, and modified baroclinicity, synoptic activity, and atmospheric large‐scale circulation. The circulation changes in the following winter display meridionalized flow but are not fully characteristic of a negative Arctic Oscillation pattern, though they do support cold winter temperatures in northern Eurasia. Internally generated climate variability causes significant uncertainty in the simulated circulation changes due to sea ice‐atmosphere interactions. The simulated atmospheric feedback patterns depend strongly on the position and strength of the regional sea ice anomalies and on the analyzed time period. The strongest atmospheric feedbacks are related to sea ice anomalies in the Beaufort Sea. This work suggests that there are complex feedback mechanisms that support a statistical link between reduced September sea ice and Arctic winter circulation. However, the feedbacks depend on regional and decadal variations in the coupled atmosphere‐ocean‐sea ice system.
A Reconfigurable Buck, Boost, and Buck-Boost Converter: Unified Model and Robust Controller

The need for reconfigurable, high power density, and low-cost configurations of DC-DC power electronic converters (PEC) in areas such as the transport electrification and the use of renewable energy has spread out the requirement to incorporate in a single circuit several topologies, which generally result in an increment of complexity about the modeling, control, and stability analyses. In this paper, a reconfigurable topology is presented which can be applied in alterative/changing power conversion scenarios and consists of a reconfigurable Buck, Boost, and Buck-Boost DC-DC converter (RBBC). A unified averaged model of the RBBC is obtained, a robust controller is designed through a polytopic representation, and a Lyapunov based switched stability analysis of the closed-loop system is presented. The reported RBBC provides a wide range of voltage operation, theoretically from to volts with a single power source. Robust stability, even under arbitrarily fast (bounded) parameter variations and reconfiguration changes, is reported including numerical and experimental results. The main advantages of the converter and the robust controller proposed are simple design, robustness against abrupt changes in the parameters, and low cost.
Personalized Medicine for Severe Asthma: How Far Have We Achieved?

There is increasing pharmacogenetic literature on the heterogeneity in the treatment responses to different anti-asthma drugs including inhaled corticosteroid (ICS), which are indicated for patients with moderate-to-severe asthma. A number of genetic targets including STIP1, CRHR1, CYP3A4, GLCCI1, T gene and FBXL7 are potential pharmacogenetic biomarkers for predicting patients’ response to ICS. Knowledge on predictive variants in these genes allows for the genotyping and selection of patients with severe asthma for personalized treatment with high-dose ICS treatment. There is an emerging trend to unravel genetic variants that predict treatment responses among patients with different asthma endotypes. Some patients with severe asthma are refractory to maintenance corticosteroids, and several biological agents targeting type 2 helper T lymphocyte pathway offer hope of optimizing their disease control. The efficacy of subcutaneous pitrakinra is dependent on patients’ IL4R status. Nonetheless, such pharmacogenetic effect has not been investigated for other biological agents such as mepolizumab. The adoption of a personalized pharmacogenetic approach to health care delivery facilitates the optimal use of novel, expensive and potentially toxic therapies in patients with severe asthma. Asthma is characterized by airway inflammation, and is caused by complex interactions between many genetic and environmental factors. Anti-inflammatory therapies such as inhaled corticosteroid (ICS) are therefore an integral component of asthma pharmacotherapy under different international guidelines. There is substantial inter-individual variability in patients’ response to anti-asthma treatments. According to Global Initiative for Asthma guideline, patients with severe controlled asthma require maintenance oral corticosteroid or anti-immunoglobulin E treatments. A number of biologic agents have recently been shown to be treatment alternatives for these patients. Pharmacogenetic approach facilitates personalized medicine by differentiating treatment responders from nonresponders, whereby substantially reducing the economic burden of asthma. Candidate gene and pathway-based pharmacogenetic methods have identified a number of candidate genes and their functional variants, but largerscale pharmacogenomics has drawn more and more attention over the past decade. Our group has previously discussed the genetic targets for bronchodilator responses to β2-agonists and leukotriene modifiers. This editorial focused on recent advances in the pharmacogenetics of ICS and the novel biological agents as treatment modalities for patients with severe asthma.
Proposal to reclassify [ Sphingomonas ] xenophaga

The sphingomonad group contains bacterial isolates that are quite diverse in terms of their phylogenetic, ecological and physiological properties. Thus, the genus Sphingomonaswas divided into four distinct genera, Sphingomonas sensu stricto, Sphingobium, Novosphingobium and Sphingopyxis on the basis of 16S rRNA gene sequence phylogenetic analysis, signature nucleotides, fatty acid profiles and polyamine patterns and this classification is currently widely accepted. In this study, a complete analysis of the 16S rRNA gene sequences of all the members of the group of sphingomonads encompassed in the genera Sphingomonas sensu stricto, Sphingobium, Novosphingobium and Sphingopyxis was inferred by using tree-making algorithms. [Sphingomonas] xenophaga DSM 6383 was found to form a distinct clade with the members of the genus Sphingobium, whereas [Sphingomonas] taejonensis DSM 15583 forms a clade with the members of the genus Sphingopyxis. The respective positions of these strains were also supported by the data for signature nucleotides, 2-hydroxy fatty acid profiles, polyamine patterns and the nitrate reduction properties of the strains. We therefore propose the reclassification of [Sphingomonas] xenophaga and [Sphingomonas] taejonensis as Sphingobium xenophagum comb. nov. (type strain DSM 6383=CIP 107206) and Sphingopyxis taejonensis comb. nov. (type strain DSM 15583=KCTC 2884=KCCM 41068), respectively.