Miracle-dz/UniFAR-FTUs huggingface dataset:
Some Effects of Crosswind on the Lateral Dynamics of a Bicycle

The bicycle, being unstable at low speed and marginally stable at high speed, is sensitive to lateral perturbations. One of the major lateral perturbations is crosswind, which can lead to accidents and fatalities. Here we investigate the effect of crosswind on the lateral dynamics and control of the bicycle in a wide range of forward speeds and various crosswinds, by means of computer model analysis and simulation. A low dimensional bicycle model is used together with experimentally identified rider control parameters. The crosswind forces are obtained from a recent experimental study. Analysis and simulation show that crosswind decreases the stability of the bicycle and is clearly a safety issue.
Learning to communicate more efficiently in human-agent teams

We are developing software agents that can help support the work of human teams. In order to be useful, these agents must be able to adapt their behavior, learning over ti me how to better serve the human members of the teams. In previou s work, we have demonstrated how agents can use techniques fro m machine learning to improve the performance of agents that identify organisational policy contraints of coalition partners. We have also identified mechanisms that agents can use for plann i g the communication that supports team activities. In this paper we describe how to combine these lines of work, showing how agents can use learning to improve their performance, both t o identify more efficient communication patterns, and to construct communication policies more efficiently.
Boundary detection of black skin tumors using an adaptive radial-based approach

Melanoma diagnosis greatly relies on the observation of some characteristic features on skin tumors. Similarly, a computer- based diagnostic system has been designed to detect these features. However, specificity and sensitivity of features often rely on their location within the tumor. Locating the border of lesions is therefore of utmost importance. Segmentation of tumors is not easy because of high variability of coloration from one tumor to another and because of numerous 'artifacts' such as hairs, or skin lines. An adaptive and supervised approach was consequently chosen to segment lesions. Dermatologists were asked to hand-outline borders of lesions and, after an automatic selection of a point inside the tumor, radial intensity profiles were generated. The location of border was associated with each of them. A neural network was taught to predict border from these labeled profiles. Our approach has been found efficient and robust in such a way that human correction of automatic segmentation are most of the time insignificant. Features such as asymmetry of texture and inhomogeneity of colors can subsequently be observed and their clinical significance evaluated.
ORBITA : A case study in the analysis and reporting of clinical trials

Department of Statistics and Political Science, Columbia University, New York City, NY, United States (Andrew Gelman, professor); Clinical Epidemiology & Biostatistics, Murdoch Children’s Research Institute, Melbourne School of Population and Global Health and Department of Paediatrics, University of Melbourne, Melbourne, Australia (John Carlin, professor); Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, United States (Brahmajee K Nallamothu, professor);
Robust 3D point cloud registration based on bidirectional Maximum Correntropy Criterion

This paper presents a robust 3D point cloud registration algorithm based on bidirectional Maximum Correntropy Criterion (MCC). Comparing with traditional registration algorithm based on the mean square error (MSE), using the MCC is superior in dealing with complex registration problem with non-Gaussian noise and large outliers. Since the MCC is considered as a probability measure which weights the corresponding points for registration, the noisy points are penalized. Moreover, we propose to use bidirectional measures which can maximum the overlapping parts and avoid the registration result being trapped into a local minimum. Both of these strategies can better apply the information theory method to the point cloud registration problem, making the algorithm more robust. In the process of implementation, we integrate the fixed-point optimization technique based on the iterative closest point algorithm, resulting in the correspondence and transformation parameters that are solved iteratively. The comparison experiments under noisy conditions with related algorithms have demonstrated good performance of the proposed algorithm.
Toward Super-Polynomial Size Lower Bounds for Depth-Two Threshold Circuits

Proving super-polynomial size lower bounds for $\textsf{TC}^0$, the class of constant-depth, polynomial-size circuits of Majority gates, is a notorious open problem in complexity theory. A major frontier is to prove that $\textsf{NEXP}$ does not have poly-size $\textsf{THR} \circ \textsf{THR}$ circuit (depth-two circuits with linear threshold gates). In recent years, R. ~Williams proposed a program to prove circuit lower bounds via improved algorithms. In this paper, following Williams' framework, we show that the above frontier question can be resolved by devising slightly faster algorithms for several fundamental problems: 1. Shaving Logs for $\textsf{$\ell_2$-Furthest-Pair}$. An $n^2 \textrm{poly}(d) / \log^{\omega(1)} n$ time algorithm for $\textsf{$\ell_2$-Furthest-Pair}$ in $\mathbb{R}^d$ for polylogarithmic $d$ implies $\textsf{NEXP}$ has no polynomial size $\textsf{THR} \circ \textsf{THR}$ circuits. The same holds for Hopcroft's problem, $\textsf{Bichrom. -$\ell_2$-Closest-Pair}$ and Integer $\textsf{Max-IP}$. 2. Shaving Logs for Approximate $\textsf{Bichrom. -$\ell_2$-Closest-Pair}$. An $n^2 \textrm(d) / \log^{\omega(1)} n$ time algorithm for $(1+1/\log^{\omega(1)} n)$-approximation to $\textsf{Bichrom. -$\ell_2$-Closest-Pair}$ or $\textsf{Bichrom. -$\ell_1$-Closest-Pair}$ for polylogarithmic $d$ implies $\textsf{NEXP}$ has no polynomial size $\textsf{SYM}\circ\textsf{THR}$ circuits. 3. Shaving Logs for Modest Dimension Boolean $\textsf{Max-IP}$. An $n^2 / \log^{\omega(1)} n$ time algorithm for Bichromatic Maximum Inner Product with vector dimension $d = n^\epsilon$ for any small constant $\epsilon$ would imply $\textsf{NEXP}$ has no polynomial size $\textsf{THR} \circ \textsf{THR}$ circuits. Note there is an $n^2\textrm{polylog}(n)$ time algorithm via fast rectangle matrix multiplication. Our results build on two structure lemmas for threshold circuits.
Graph properties of DAG associahedra and related polytopes

A directed acyclic graph (DAG) can be thought of as encoding a set of conditional independence (CI) relations among random variables. Assuming we sample data from a probability distribution satisfying these CI relations, a fundamental problem in causal inference is to recover the edge-structure of the underlying DAG. An algorithm known as the greedy SP algorithm aims to recover the underlying DAG by walking along edges of a polytope known as the DAG associahedron. Hence, the edge-structure of the DAG associahedron plays an important role in understanding the complexity of the greedy SP algorithm. In this thesis, we study graph properties of the edge-graph of DAG associahedra, related polytopes, and their important subgraphs. The properties considered include diameter, radius and center. Our results on the diameter of DAG associahedra lead to a new causal inference algorithm with improved theoretical consistency guarantees and complexity bounds relative to the greedy SP algorithm.
Scheduling URLLC users with reliable latency guarantees

This paper studies Ultra-Reliable Low-Latency Communications (URLLC), an important service class of emerging 5G networks. In this class, multiple unreliable transmissions must be combined to achieve reliable latency: a user experiences a frame success when the entire L bits are received correctly within a deadline, and its latency performance is reliable when the frame success rate is above a threshold. When jointly serving multiple users, a natural URLLC scheduling question arises: given the uncertainty of the wireless channel, can we find a scheduling policy that allows all users to meet a target reliable latency objective? This is called the URLLC SLA Satisfaction (USS) problem. The USS problem is an infinite horizon constrained Markov Decision Process, for which, after establishing a convenient property, we are able to derive an optimal policy based on dynamic programming. Our policy suffers from the curse of dimensionality, hence for large instances we propose a class of knapsack-inspired computationally efficient — but not necessarily optimal — policies. We prove that every policy in that class becomes optimal in a fluid regime, where both the deadline and L scale to infinity, while our simulations show that the policies perform well even in small practical instances of the USS problem.
uOttawa at SemEval-2018 Task 1: Self-Attentive Hybrid GRU-Based Network

We propose a novel attentive hybrid GRU-based network (SAHGN), which we used at SemEval-2018 Task 1: Affect in Tweets. Our network has two main characteristics, 1) has the ability to internally optimize its feature representation using attention mechanisms, and 2) provides a hybrid representation using a character level Convolutional Neural Network (CNN), as well as a self-attentive word-level encoder. The key advantage of our model is its ability to signify the relevant and important information that enables self-optimization. Results are reported on the valence intensity regression task.
Eye behaviour as a hazard perception measure

Hazard perception during driving is essential in detecting and avoiding traffic incidents. In this study, eye movement analysis is used to measure the driver's hazard perception while engaged in different traffic scenarios on Australian roads. Participants were asked to observe recordings of four different traffic scenarios and react to hazards by clicking the mouse. The aim of this study is to examine three hypotheses; (1) the relationship between driver's experience and hazard identification, (2) the use of pupil dilation as a measure of hazard perception, and (3) the ability of gaze fixation points to determine the driver's perception of the hazard. The results show that eye movement dynamics and change in pupil diameter can provide good measures of the drivers' hazard perception and prediction.
Demographic expansion and genetic load of the halophyte model plant Eutrema salsugineum

The halophyte model plant Eutrema salsugineum (Brassicaceae) disjunctly occurs in temperate to subarctic Asia and North America. This vast, yet extremely discontinuous distribution constitutes an ideal system to examine long‐distance dispersal and the ensuing accumulation of deleterious mutations as expected in expanding populations of selfing plants. In this study, we resequenced individuals from 23 populations across the range of E. salsugineum. Our population genomic data indicate that E. salsugineum migrated “out of the Altai region” at least three times to colonize northern China, northeast Russia and western China. It then expanded its distribution into North America independently from northeast Russia and northern China, respectively. The species colonized northern China around 33.7 thousand years ago (kya) and underwent a considerable expansion in range size approximately 7–8 kya. The western China lineage is likely a hybrid derivative of the northern China and Altai lineages, originating approximately 25–30 kya. Deleterious alleles accumulated in a stepwise manner from (a) Altai to northern China and North America and (b) Altai to northeast Russia and North America. In summary, E. salsugineum dispersed from Asia to North America and deleterious mutations accumulated in a stepwise manner during the expansion of the species’ distribution.
Single-Prolonged Stress: A Review of Two Decades of Progress in a Rodent Model of Post-traumatic Stress Disorder

Post-traumatic stress disorder (PTSD) is a common, costly, and often debilitating psychiatric condition. However, the biological mechanisms underlying this disease are still largely unknown or poorly understood. Considerable evidence indicates that PTSD results from dysfunction in highly-conserved brain systems involved in stress, anxiety, fear, and reward. Pre-clinical models of traumatic stress exposure are critical in defining the neurobiological mechanisms of PTSD, which will ultimately aid in the development of new treatments for PTSD. Single prolonged stress (SPS) is a pre-clinical model that displays behavioral, molecular, and physiological alterations that recapitulate many of the same alterations observed in PTSD, illustrating its validity and giving it utility as a model for investigating post-traumatic adaptations and pre-trauma risk and protective factors. In this manuscript, we review the present state of research using the SPS model, with the goals of (1) describing the utility of the SPS model as a tool for investigating post-trauma adaptations, (2) relating findings using the SPS model to findings in patients with PTSD, and (3) indicating research gaps and strategies to address them in order to improve our understanding of the pathophysiology of PTSD.
What can Automated Planning do for Intelligent Tutoring Systems ?

In this paper, we build on the latest in automated planning techniques to develop a generalized framework for courseindependent design of Intelligent Tutoring Systems (ITSs). This is meant to provide targeted and personalized assistance to students, in order to meet the demands of the increasing class size, as well as help instructors who can use higher level specifications to design courses without having to worry about building the course-specific tutoring assistance. Thus the aim of this paper is to demonstrate what automated planning can bring to the table for the design of courseindependent ITS features. We will illustrate these capabilities in Dragoon, an ITS deployed at Arizona State University.
UNAM at SemEval-2018 Task 10: Unsupervised Semantic Discriminative Attribute Identification in Neural Word Embedding Cones

In this paper we report an unsupervised method aimed to identify whether an attribute is discriminative for two words (which are treated as concepts, in our particular case). To this end, we use geometrically inspired vector operations underlying unsupervised decision functions. These decision functions operate on state-of-the-art neural word embeddings of the attribute and the concepts. The main idea can be described as follows: if attribute q discriminates concept a from concept b, then q is excluded from the feature set shared by these two concepts: the intersection. That is, the membership q\in (a\cap b) does not hold. As a,b,q are represented with neural word embeddings, we tested vector operations allowing us to measure membership, i.e. fuzzy set operations (t-norm, for fuzzy intersection, and t-conorm, for fuzzy union) and the similarity between q and the convex cone described by a and b.
Protein phase separation provides long-term memory of transient spatial stimuli

Protein/RNA clusters arise frequently in spatially-regulated biological processes, from the asymmetric distribution of P granules and PAR proteins in developing embryos to localized receptor oligomers in migratory cells. This co-occurrence suggests that protein clusters might possess intrinsic properties that make them a useful substrate for spatial regulation. Here, we demonstrate that protein droplets show a robust form of spatial memory, maintaining the spatial pattern of an inhibitor of droplet formation long after it has been removed. Despite this persistence, droplets can be highly dynamic, continuously exchanging monomers with the diffuse phase. We investigate the principles of biophysical spatial memory in three contexts: a computational model of phase separation; a novel optogenetic system where light can drive rapid, localized dissociation of liquid-like protein droplets; and membrane-localized signal transduction from clusters of receptor tyrosine kinases. Our results suggest that the persistent polarization underlying many cellular and developmental processes could arise through a simple biophysical process, without any additional requirement for biochemical positive and negative feedback loops. Highlights We introduce PixELLs, an optogenetic system for protein droplet disassembly. Modeling and experiments demonstrate long-term memory of local droplet dissociation. Droplets ‘remember’ spatial stimuli in nuclei, the cytosol and on cell membranes. FGFR-optoDroplets convert transient local inputs to persistent cytoskeletal responses.
Geographic Clustering of Polygenic Scores at Different Stages of the Life Course

We interrogate state-level clustering of polygenic scores at different points in the life course and variation in the association of mean polygenic scores in a respondent’s state of birth with corresponding phenotypes. The polygenic scores for height and smoking show the most state-level clustering (2 to 4 percent) with relatively little clustering observed for the other scores. However, even the small amounts of observed clustering are potentially meaningful. The state-mean polygenic score for educational attainment is strongly associated with an individual’s educational attainment net of that person’s polygenic score. The ecological clustering of polygenic scores may denote a new environmental factor in gene-environment research. We conclude by discussing possible mechanisms that underlie this association and the implications of our findings for social and genetic research.
Effects of Subclinical Mastitis on Serum Estradiol and Tumour Necrosis Factor Alpha Levels During Estrus in Dairy Cows

The effect of subclinical mastitis on serum estradiol and tumor necrosis factor alpha (TNF-α) levels during oestrus and subsequent fertility was investigated in dairy cows. 40 cows were divided into two groups as healthy control (n=20) and subclinical mastitis (n=20), according to the results of California Mastitis Test (CMT) and bacteriological isolation and identification. Cows were synchronised with a standart 7 day Ovsynch protocol. Following prostaglandin F2alpha (PGF2α) administration, cows were examined with trans-rectal ultrasonography at 24, 36 and 48th h, dominant follicle diameters were recorded and blood samples were collected. Sixteen h after the second gonadotrophinreleasing hormone (GnRH) administration, cows were inseminated and a final examination of ovaries were performed and dominant follicle diameters were recorded. estradiol and TNF-α concentrations were analysed with ELISA in serum samples. No significant differences were found between the follicular diameters and growth patterns (P>0.05) of the two groups while estradiol concentations were significantly higher in the subclinical mastitis group than the control group at 24 and 48 h after PGF2α injection (P=0.017 and P=0.036 respectively). Also TNF-α levels were significantly higher in cows with subclinical mastitis than the control group (P=0.03). Positive correlations were observed between estradiol and TNF-α levels, in both groups (Control Group: R=0.512, P=0.021; Subclinical Mastitis Group: R=0.826, P<0.001). Overall pregnancy rate was higher in the control group (40%) than the subclinical mastitis (25%) group however the difference was not statistically significant (P>0.05). In conclusion estradiol and TNF-α concentrations were found higher in cows with subclinical mastitis during estrus and this data may be due to a luteal insufficiency during the initiation of synchronization, however further studies are required.
Dynamic Hedge Fund Portfolio Construction

In this paper, we provide further evidence on the use of multivariate conditional volatility models in hedge fund risk measurement and portfolio allocation, using monthly hedge fund index return data for the period 1990 to 2009. Building on Giamouridis and Vrontos (2007), we consider a broad set of multivariate GARCH models as well as the simpler exponentially weighted moving average (EWMA) estimator of RiskMetrics (1996). We find that while multivariate GARCH models provide some improvement in portfolio performance over static models, they are generally dominated by the EWMA model. In particular, in addition to providing better risk-adjusted performance, the EWMA model leads to dynamic allocation strategies that have substantially lower turnover and could therefore be expected to involve lower transaction costs. Moreover, we show that these results are robust across low-volatility and high-volatility sub-periods.
The Alexa Meaning Representation Language

This paper introduces a meaning representation for spoken language understanding. The Alexa meaning representation language (AMRL), unlike previous approaches, which factor spoken utterances into domains, provides a common representation for how people communicate in spoken language. AMRL is a rooted graph, links to a large-scale ontology, supports cross-domain queries, fine-grained types, complex utterances and composition. A spoken language dataset has been collected for Alexa, which contains ∼20k examples across eight domains. A version of this meaning representation was released to developers at a trade show in 2016.
Draft genome of a high value tropical timber tree, Teak (Tectona grandis L. f): insights into SSR diversity, phylogeny and conservation

Abstract Teak (Tectona grandis L. f.) is one of the precious bench mark tropical hardwood having qualities of durability, strength and visual pleasantries. Natural teak populations harbour a variety of characteristics that determine their economic, ecological and environmental importance. Sequencing of whole nuclear genome of teak provides a platform for functional analyses and development of genomic tools in applied tree improvement. A draft genome of 317 Mb was assembled at 151× coverage and annotated 36, 172 protein-coding genes. Approximately about 11.18% of the genome was repetitive. Microsatellites or simple sequence repeats (SSRs) are undoubtedly the most informative markers in genotyping, genetics and applied breeding applications. We generated 182,712 SSRs at the whole genome level, of which, 170,574 perfect SSRs were found; 16,252 perfect SSRs showed in silico polymorphisms across six genotypes suggesting their promising use in genetic conservation and tree improvement programmes. Genomic SSR markers developed in this study have high potential in advancing conservation and management of teak genetic resources. Phylogenetic studies confirmed the taxonomic position of the genus Tectona within the family Lamiaceae. Interestingly, estimation of divergence time inferred that the Miocene origin of the Tectona genus to be around 21.4508 million years ago.
Writing Across the Curriculum: Reliability Testing of a Standardized Rubric.

BACKGROUND Rubrics positively affect student academic performance; however, accuracy and consistency of the rubric and its use is imperative. The researchers in this study developed a standardized rubric for use across an undergraduate nursing curriculum, then evaluated the interrater reliability and general usability of the tool. METHOD Faculty raters graded papers using the standardized rubric, submitted their independent scoring for interrater reliability analyses, then participated in a focus group discussion regarding rubric use experience. RESULTS Quantitative analysis of the data showed a high interrater reliability (α = .998). Content analysis of transcription revealed several positive themes: Consistency, Emphasis on Writing Ability, and Ability to Use the Rubric as a Teaching Tool. Areas for improvement included use of value words and difficulty with point allocation. CONCLUSION Investigators recommend effective faculty orientation for rubric use and future work in developing a rubric to assess reflective writing. [J Nurs Educ. 2018;57(6):366-370. ].