Miracle-dz/UniFAR-FTUs huggingface dataset:
Clustering of Driving Encounter Scenarios Using Connected Vehicle Trajectories

Classification and analysis of driving behaviors offer in-depth knowledge to make an efficient decision for autonomous vehicles. This paper aims to cluster a wide range of driving encounter scenarios based only on multi-vehicle GPS trajectories. Towards this end, we propose a generic unsupervised learning framework comprising of two layers: feature representation layer and clustering layer. In the feature representation layer, we combine the deep autoencoders with a distance-based measure to map the sequential observations of driving encounters into a computationally tractable space, which quantifies the spatiotemporal interaction characteristics of two vehicles. The clustering algorithm is then applied to the extracted representations to cluster homogeneous driving encounters into groups. Our proposed generic framework is then evaluated using 2,568 naturalistic driving encounters. Experimental results show that our proposed generic framework incorporated with unsupervised learning can cluster multi-trajectory data into distinct groups. These clustering results could benefit the decision-making and design of autonomous vehicles.
Audio De-identification - a New Entity Recognition Task

Named Entity Recognition (NER) has been mostly studied in the context of written text. Specifically, NER is an important step in de-identification (de-ID) of medical records, many of which are recorded conversations between a patient and a doctor. In such recordings, audio spans with personal information should be redacted, similar to the redaction of sensitive character spans in de-ID for written text. The application of NER in the context of audio de-identification has yet to be fully investigated. To this end, we define the task of audio de-ID, in which audio spans with entity mentions should be detected. We then present our pipeline for this task, which involves Automatic Speech Recognition (ASR), NER on the transcript text, and text-to-audio alignment. Finally, we introduce a novel metric for audio de-ID and a new evaluation benchmark consisting of a large labeled segment of the Switchboard and Fisher audio datasets and detail our pipeline’s results on it.
Case Marking in Hindi as the Weaker Language

Does language dominance modulate knowledge of case marking in Hindi-speaking bilinguals? Hindi is a split ergative language with a rich morphological case system. Subjects of transitive perfective predicates are marked with ergative case (-ne). Human specific direct objects, indirect objects, and dative subjects are marked with the particle -ko. We compared knowledge of case marking in Hindi–English bilinguals with different dominance patterns: 23 balanced bilinguals and two groups of bilinguals with Hindi as their weaker language: 24 L2 learners of Hindi with age of acquisition (AoA) of Hindi in adulthood and 26 Hindi heritage speakers with AoA of Hindi since birth in oral production and acceptability judgments. The balanced bilinguals outperformed the English-dominant bilinguals; the L2 learners and the heritage speakers, who showed similar lower command of the Hindi case marking system, with the exception of -ko marking as a function of specificity with direct objects. We consider how dominant language transfer, AoA of Hindi, and input factors may explain the acquisition and knowledge of morphology in Hindi as the weaker language.
Introduced Prophysaon andersonii (J.G. Cooper, 1872) in Quebec, Canada: first record of Prophysaon (Gastropoda, Eupulmonata, Arionoidea) in eastern North America, confirmed by partial-COI gene sequence

We report for the first time the terrestrial slug Prophysaon andersonii (J.G. Cooper, 1872) from Quebec, Canada. Two specimens were collected in Parc national du Bic. The identification was determined by the external morphology and partial-COI gene sequence data. The genus Prophysaon is endemic to western North America, and the new record indisputably represents an introduction. No species of Prophysaon has, until now, been noticed in North America from outside its native range.
Scalable Kernel Density Estimation-based Local Outlier Detection over Large Data Streams

Local outlier techniques are known to be effective for detecting outliers in skewed data, where subsets of the data exhibit diverse distribution properties. However, existing methods are not well equipped to support modern high-velocity data streams due to the high complexity detection algorithms and their volatility to data updates. To tackle these shortcomings, we propose new local outlier semantics that leverage kernel density estimation (KDE) to effectively detect local outliers from streaming data. A strategy to continuously detect top-N KDE-based local outliers over streams is also designed, called KELOS – the ﬁrst linear time complexity streaming local outlier detection approach. The ﬁrst innovation of KELOS is the abstract kernel center-based KDE ( a KDE) model. a KDE accurately while efﬁciently estimates the data density at each point – essential ingredi-ent for local outlier detection. This is based on the observation that a cluster of points close to each other tend to have a similar inﬂuence on a target point’s density estimation when used as kernel centers. These points thus can be represented by one abstract kernel center. Next, the KELOS’s inlier pruning strategy early prunes points that have no chance to become top-N outliers. This empowers KELOS to skip the computation of the data density and then the outlier status for every data point. Together a KDE and the inlier pruning strategy eliminate the performance bottleneck of streaming local outlier detection. The experimental evaluation demonstrates that KELOS is up to 3 orders of magnitude faster than existing solutions, while still being highly effective in detecting local outliers from streaming data.
The Concerted Action of E2-2 and HEB Is Critical for Early Lymphoid Specification

The apparition of adaptive immunity in Gnathostomata correlates with the expansion of the E-protein family to encompass E2-2, HEB and E2A. Within the family, E2-2 and HEB are more closely evolutionarily related but their concerted action in hematopoiesis remains to be explored. Here we show that the combined disruption of E2-2 and HEB results in failure to express the early lymphoid program in CLPs and a near complete block in B-cell development. In the thymus, ETPs were reduced and T-cell development perturbed, resulting in reduced CD4 T- and increased γδ T-cell numbers. In contrast, HSCs, erythro-myeloid progenitors and innate immune cells were unaffected showing that E2-2 and HEB are dispensable for the ancestral hematopoietic lineages. Taken together, this E-protein dependence suggests that the appearance of the full Gnathostomata E-protein repertoire was critical to reinforce the gene regulatory circuits that drove the emergence and expansion of the lineages constituting humoral immunity.
Detection and Quantification of Engineered Proanthocyanidins in Transgenic Plants

Proanthocyanidins (PAs) are oligomeric plant natural products mostly derived from epicatechin and/or catechin monomers. In studies aimed at engineering PAs into plant tissues that do not naturally make these compounds, we have expressed PA biosynthetic and regulatory genes in tobacco, alfalfa (Medicago sativa) and the model legume Medicago truncatula. Because engineered tannins may be produced in small quantities and it is often necessary to screen many independent plant lines, we have developed an improved, highly sensitive method to quantify and determine the composition of oligomeric PAs in plant extracts. The method involves normal-phase HPLC separation of semi-purified PAs followed by post-column reaction with the PA-specific reagent DMACA (dimethylaminocinnamaldehyde). This procedure allows for accurate and sensitive quantification of individual oligomeric PAs and, unlike currently used methods, does not require exhaustive sample preparation and clean-up. Compositional data are shown for genetically engineered PAs in tobacco and alfalfa.
How Important are Social Relations for Happiness? Empirical Evidence from Turkey

In this study, we examine how effective are social relations in determining the happiness of an individual by utilizing the life satisfaction survey micro data set (2017)provided by the Turkey Statistical Institute. According to the results of the logistic regression method, women seem to be happier than men, and married people are more satisfied than unmarried. Employees in the public sector appear to be less happy than those in the private sector. Also, health seems to have a positive effect on individual happiness. We find that people who are satisfied with their job, and those who are satisfied with their earnings are also happier. Satisfaction with social life (such as entertainment, cultural, and sporting activities) increases the happiness of individuals, and having more free time makes people happier. Satisfaction with relatives and satisfaction with relationships with people related to work-life were also included in the analysis as factors affecting the happiness of an individual positively. The survey also gives information on about the degree of individuals’ satisfaction with their relationships with neighbors and friends, but these factors do not seem to affect the happiness of individuals.
Effectiveness School-Based Educational Interventions in Preventing Smoking in Iranian Adolescents: A Systematic Review

Background: Adolescence is considered as a momentous period for initiating risky behaviors. Adolescents do not have an accurate understanding of the perilous consequences of their behavior due to being self-centered. They are likely to discover risky situations, which increases their capacity for danger. The purpose of this systematic review study is to evaluate the school-based educational interventions to increase self-efficacy in preventing smoking in Iranian adolescents. Materials and Methods: In this systematic review, all experimental and quasi-experimental studies from January 2000 to April 2019 in Iran, were searched from Web of Science, Scopus, ProQuest, Cochrane Library, and Medline (via PubMed) as English databases and SID, IRCT, Magiran and Irondoc as Iranian databases. Keywords were selected based on the Mesh and include: "adolescent, teenager, student, smoking, cigarette, education and Iran" combined with the Boolean OR and AND operators. Two reviewers studied the full text of the articles and their main findings were extracted and categorized. Quality assessment of studies was checked and verified by two authors independently based on Cochrane tool. Results: In this systematic review, 6 studies with 964 adolescents that met the inclusion criteria were included in the study; 5 of them were published in English and 1 in Persian. Different methods of school education, including lectures, film presentations, group discussions, question and answer sessions and role playing were used in these studies. Conclusion: According to the results of this study, education of adolescents in the school environment is effective in increasing self-efficacy skills as a preventive measure of smoking in adolescents.
Building Extraction from High-Resolution Remote Sensing Images Based on GrabCut with Automatic Selection of Foreground and Background Samples

This article proposes a new building extraction method from high-resolution remote sensing images, based on GrabCut, which can automatically select foreground and background samples under the constraints of building elevation contour lines. First the image is rotated according to the direction of pixel displacement calculated by the rational function Model. Second, the Canny operator, combined with morphology and the Hough transform, is used to extract the building's elevation contour lines. Third, seed points and interesting points of the building are selected under the constraint of the contour line and the geodesic distance. Then foreground and background samples are obtained according to these points. Fourth, GrabCut and geometric features are used to carry out image segmentation and extract buildings. Finally, WorldView satellite images are used to verify the proposed method. Experimental results show that the average accuracy can reach 86.34%, which is 15.12% higher than other building extraction methods.
Computational Methods Used to Explore Transport Events in Biological Systems

Transport of various molecules facilitated with membrane proteins is necessary for maintaining homeostasis in living cells. In humans, dysfunction of these proteins leads to many diseases. Thus, understanding how the membrane proteins function may help using them as therapeutic targets. To successfully investigate the mechanistic aspects of transport, the choice of appropriate methods is crucial. We review the computational methods that have proven most effective in investigating transport events, specifically, deterministic time-dependent classical molecular dynamics and its enhanced sampling variants, as well as methods based on Brownian dynamics. We describe technical aspects of these methods and examples of their novel variants or combinations that have been recently and successfully applied in the transport studies. We also discuss the difficulties related to these methods and provide possible solutions to avoid them.
A case-control study of paternal and maternal age as risk factors in mood disorders

Abstract Objective: Advanced parental age might constitute a risk factor for various disorders. We tested whether this concerns also mood disorder patients. Methods: The study included 314 subjects (42 bipolar-BD patients; 21 manics and 21 depressives, 68 unipolar-UD, and 204 normal controls-NC). Analysis of Covariance (ANCOVA) and the calculation of the Relative Risk (RR) and the Odds Ratio (OR) were used for the analysis. Results: Paternal age differed between NC and UD patients (29.42 ± 6.07 vs. 32.12 ± 5.54; p = .01) and manics (29.42 ± 6.07 vs. 35.00 ± 5.75; p = .001) and maternal age between NC and manics (25.46 ± 4.52 vs. 31.43 ± 4.75; p < .001) and manic and UD (31.43 ± 4.75 vs. 26.75 ± 6.03; p = .002). The RR and OR values suggested that advanced parental age constitutes a risk factor for the development of mood disorders. Conclusions: In a non-dose dependent and gender-independent, advanced parental age constitutes a risk factor for the development of BD with index episode of mania (probably manic predominant polarity); only advanced paternal age constitutes a risk factor for the development of UD and BD with index episode of depression (probably depressive predominant polarity). This is the first study suggesting differential effect of advanced parental age depending on predominant polarity of BD.
Combining Model and Parameter Uncertainty in Bayesian Neural Networks

Bayesian neural networks (BNNs) have recently regained a significant amount of attention in the deep learning community due to the development of scalable approximate Bayesian inference techniques. There are several advantages of using Bayesian approach: Parameter and prediction uncertainty become easily available, facilitating rigid statistical analysis. Furthermore, prior knowledge can be incorporated. However so far there have been no scalable techniques capable of combining both model (structural) and parameter uncertainty. In this paper we introduce the concept of model uncertainty in BNNs and hence make inference in the joint space of models and parameters. Moreover, we suggest an adaptation of a scalable variational inference approach with reparametrization of marginal inclusion probabilities to incorporate the model space constraints. Finally, we show that incorporating model uncertainty via Bayesian model averaging and Bayesian model selection allows to drastically sparsify the structure of BNNs.
The Effects of Knowledge Assets and Path Dependence in Innovations on Firm Value in the Korean Semiconductor Industry

This study investigated whether firms’ knowledge assets and path dependence in their innovations affect firm value. For the analysis, I used 37 firms in the semiconductor industry in Korea. These firms were listed on the Korea Stock Exchange and the Korea Securities Dealers Association Automated Quotation as of 2010 and through 2015. The dependent variable was measured by return on assets as firm value, and the ordinary least squares estimation was used. The results showed that a firm’s knowledge assets have a positive effect on firm value. In addition, when a firm creates new knowledge, if the firm follows path dependence by using its own knowledge, it has a positive effect on firm value. By contrast, when a firm conducts innovations using knowledge created by other firms, it has no effect on the value of the firm. Additionally, I found that technological innovation based on knowledge assets and path dependence has a positive effect on firm value in the short term but has no effect in the medium term. Thus, firms need to continue their innovation to maintain their competitive advantage and to use their existing knowledge in innovation in order to have high performance.
Developmental Dyscalculia in Adults

Abstract. Developmental dyscalculia (DD) is a chronic condition that poses not only a barrier to employment and socio-emotional wellbeing but that also persists into adulthood. Thus, understanding the neuro-cognitive foundations of DD is relevant for both children and adults with DD. However, so far the vast majority of scientific research endeavours has been dedicated to the study of DD in children only. Consequently, our current understanding of DD in adulthood is rather patchy. The main aim of the present review is to summarize the scientific findings on DD in adults by focusing on its cognitive manifestations and neural substrates in adults. For instance, research on DD in adulthood suggests that – beyond an outstanding deficiency in number processing – the processing of non-numerical magnitudes and domain-general skills seem to be also impaired in adults suffering from persistent DD. A secondary aim of this review is to delineate future lines of research that will provide us with a more elaborate understanding of the neurocognitive underpinnings of DD in adults (thus fostering the development of sensitive diagnostic marker tasks), and to formulate potential intervention areas targeting deficiencies frequently characterizing DD in adults.
On the Complexity of the k-Level in Arrangements of Pseudoplanes

A classical open problem in combinatorial geometry is to obtain tight asymptotic bounds on the maximum number of k-level vertices in an arrangement of n hyperplanes in d dimensions (vertices with exactly k of the hyperplanes passing below them). This is a dual version of the k-set problem, which, in a primal setting, seeks bounds for the maximum number of k-sets determined by n points in d dimensions, where a k-set is a subset of size k that can be separated from its complement by a hyperplane. The k-set problem is still wide open even in the plane, with a substantial gap between the best known upper and lower bounds. The gap gets larger as the dimension grows. In three dimensions, the best known upper bound is O(nk^(3/2)). In its dual version, the problem can be generalized by replacing hyperplanes by other families of surfaces (or curves in the planes). Reasonably sharp bounds have been obtained for curves in the plane, but the known upper bounds are rather weak for more general surfaces, already in three dimensions, except for the case of triangles. The best known general bound, due to Chan is O(n^2.997), for families of surfaces that satisfy certain (fairly weak) properties. In this paper we consider the case of pseudoplanes in 3 dimensions (defined in detail in the introduction), and establish the upper bound O(nk^(5/3)) for the number of k-level vertices in an arrangement of n pseudoplanes. The bound is obtained by establishing suitable (and nontrivial) extensions of dual versions of classical tools that have been used in studying the primal k-set problem, such as the Lova'sz Lemma and the Crossing Lemma.
Exploring In-Service TEYL Teachers’ Assessment Literacy: Implication For Continuing Professional Development

Assessment is central and holds essential role in language learning from which the result of the teaching and learning are derived. It shows that the ability of language teachers in assessing their students is crucial. This study explored the assessment literacy of in-service TEYL teachers in Bogor by employing narrative case study. The subjects of the study were 19 English teachers around Bogor. In collecting the data, CALI (Classroom Assessment Literacy Inventory) and FGD (Focus Group Discussion) were employed. The data gathered from CALI were then scored and analyzed, and FGD data were coded based on the assessment literacy standards from which conclusion were derived. The findings reveal that teachers have poor level of assessment literacy. Consequently, teachers must update themselves by conducting continuing professional development. HIGHLIGHTS: Assessing Young Learners is complicated and challenging for Indonesian teachers because of the demand of the Curriculum 2013. Assessment literacy is central in English language learning from which teachers can assess their students and communicate the results to the stakeholder. Continuing Professional Development is an important action that can be done by teachers to increase their assessment literacy.
High-Gain Circular Patch Antenna and Array With Introduction of Multiple Shorting Pins

This article proposes gain-enhanced circular patch antenna and array with introduction of multiple shorting pins. The antenna consists of a circular patch and several shorting pins. Equivalent inductance is brought to the patch after introducing shorting pins. Thus, resonance of the patch shifts at higher frequency. Compared to a conventional circular patch without any pins, radiation area of the proposed patch is enlarged given the same resonance frequency, hence leads to gain enhancement. The number of pins introduced to a circular patch can be set freely due to its symmetrical feature. Moreover, surface current is restricted within a small area around the center of the patch after introducing multiple pins, leading to more concentrated radiation. An equivalent circuit model is built for the proposed antenna. Layout and number optimization rules for introducing shorting pins are formulated. With these rules, gain of a circular patch can be maximized for the applications under certain size restrictions. A prototype operating at 5.8 GHz is designed and fabricated. Furthermore, a 2*2 array based on the gain-enhanced circular patch elements is implemented. In the measurements, high gain, high efficiency, and narrowed half-power beamwidth of the patch antenna and the array are observed.