Miracle-dz/UniFAR-FTUs huggingface dataset:
Multimodal Video-based Apparent Personality Recognition Using Long Short-Term Memory and Convolutional Neural Networks

Personality computing and affective computing, where the recognition of personality traits is essential, have gained increasing interest and attention in many research areas recently. We propose a novel approach to recognize the Big Five personality traits of people from videos. Personality and emotion affect the speaking style, facial expressions, body movements, and linguistic factors in social contexts, and they are affected by environmental elements. We develop a multimodal system to recognize apparent personality based on various modalities such as the face, environment, audio, and transcription features. We use modality-specific neural networks that learn to recognize the traits independently and we obtain a final prediction of apparent personality with a feature-level fusion of these networks. We employ pre-trained deep convolutional neural networks such as ResNet and VGGish networks to extract high-level features and Long Short-Term Memory networks to integrate temporal information. We train the large model consisting of modality-specific subnetworks using a two-stage training process. We first train the subnetworks separately and then fine-tune the overall model using these trained networks. We evaluate the proposed method using ChaLearn First Impressions V2 challenge dataset. Our approach obtains the best overall"mean accuracy"score, averaged over five personality traits, compared to the state-of-the-art.
Contributions to the Formalization and Extraction of Generic Bases of Association Rules

In this thesis, a detailed study shows that closed itemsets and minimal generators play a key role for concisely representing both frequent itemsets and association rules. These itemsets structure the search space into equivalence classes such that each class gathers the itemsets appearing in the same subset aka objects or transactions of the given data. In this respect, we proposed lossless reductions of the minimal generator set thanks to a new substitution-based process. Our theoretical results are extended to the association rule framework in order to reduce as much as possible the number of retained rules without information loss. We then give a thorough formal study of the related inference mechanism allowing to derive all redundant association rules, starting from the retained ones. We also lead a thorough exploration of the disjunctive search space, where itemsets are characterized by their respective disjunctive supports, instead of the conjunctive ones. This exploration is motivated by the fact that, in some applications, such information brings richer knowledge to the end-users. To obtain a redundancy free representation of the disjunctive search space, an interesting solution consists in selecting a unique element to represent itemsets covering the same set of data. Two itemsets are equivalent if their respective items cover the same set of data. In this regard, we introduced a new operator dedicated to this task. In each induced equivalence class, minimal elements are called essential itemsets, while the largest one is called disjunctive closed itemset. The introduced operator is then at the roots of new concise representations of frequent itemsets. We also exploit the disjunctive search space to derive generalized association rules. These latter rules generalize classic ones to also offer disjunction and negation connectors between items, in addition to the conjunctive one.
Investigation of Blubber Thickness in a Gray Whale Using Ultrasonography

Eric A. Wahrenbrock and Gary F. Maruschak are members of the staff of the Anesthesia Laboratory of the School of Medicine, University of California, San Diego. La Jolla, CA 92037. Robert Eisner is a member of the staff of the Physiological Research Laboratory of Scripps Institution of Oceanography. L'niversitv of California. San Diego, P^O. Box 109. La Jolla, CA 92037. David W. Kenney was formerly a member of the staff of Sea World. Inc. San Diego. Calif. ; his present address is 14220 Poway Rd. Poway, CA 92064. W-V perfonucd rcspiiiilnry unci mcuiholic sliulics on two female gray whale calves. Allhongh one died 2 inonlhs after capture, the other thrived during a year'. f captivity, pennitting serial observations while growing, and weiglied in e.Kcess of 6.350 kg when released. They appeared to he of normal size and weight compared to whtdes in the wild. Relative increases in body length and weight, lung volume, minute ventilation, and metabolic rale were similar to those in terrestrial mammals, as was the growth efficiency. Lung volume and metabolic rate could be predicted with only partial success from the relationships of those variables to body weight proposed by Tenney and Kleiber, perhaps due to intniuturity in the whales. Compared to terrestrial mammals, tite ratio of tidal volume to resting lung volume in the wliule was large, while the ratio of wasted ventilation to tidal volume was small. We measured respiratory excursions of arterial Oi and CO2 tensions of 36 and 16 mm Hg, respectively, consonant with the relationships between respiratory rate, lung volume, tidal volume, and metabolic rate.
Repeated Transient Jets from a Warped Disk in the Symbiotic Prototype Z And: A Link to the Long-lasting Active Phase

Active phases of some symbiotic binaries survive for a long time, from years to decades. The accretion process onto a white dwarf (WD) sustaining long-lasting activity, and sometimes leading to collimated ejection, is not well understood. We present the repeated emergence of highly collimated outflows (jets) from the symbiotic prototype Z And during its 2008 and 2009–10 outbursts and suggest their link to the current long-lasting (from 2000) active phase. We monitored Z And with high-resolution spectroscopy, multicolor UBVRC—and high time resolution—photometry. The well-pronounced bipolar jets were ejected again during the 2009–10 outburst together with the simultaneous emergence of the rapid photometric variability (Δm ≈ 0.06 mag) on the timescale of hours, showing similar properties as those during the 2006 outburst. These phenomena and the measured disk–jets connection could be caused by the radiation-induced warping of the inner disk due to a significant increase of the burning WD luminosity. Ejection of transient jets by Z And around outburst maxima signals a transient accretion at rates above the upper limit of the stable hydrogen burning on the WD surface, and thus proves the nature of Z And-type outbursts. The enhanced accretion through the disk warping, supplemented by the accretion from the giant’s wind, can keep a high luminosity of the WD for a long time, until depletion of the disk. In this way, the jets provide a link to long-lasting active phases of Z And.
Clinal Variation in Flowering Time and Vernalisation Requirement across a 3000-M Altitudinal Range in Perennial Arabidopsis kamchatica Ssp.Kamchatica and Annual Lowland Subspecies Kawasakiana

Clines in ecologically important traits across environmental gradients provide evidence of historical natural selection. Among the many adaptive traits that are relevant in natural habitats, flowering timing is a primary determinant of a plant’s lifetime fitness. In a laboratory experiment, we studied the divergence in flowering time and vernalisation requirement among 38 populations of two Arabidopsis subspecies: perennial A. kamchatica ssp. kamchatica across an altitudinal gradient from 30 to nearly 3000 m in the Japanese Alps, and its annual lowland subspecies, kawasakiana. Flowering time with vernalisation was not different and flowering time without vernalisation was slightly different between the subspecies; however, the altitude of the source populations was the dominant determinant of the variation in these traits for the species as a whole. The flowering time increased linearly and the effect of vernalisation to shorten the flowering time increased non-linearly with increasing altitude of the source population. Low-altitude populations of ssp. kamchatica from laboratory-collected seeds showed a stronger response to vernalisation than field-collected seeds, suggesting an effect of the maternal environment. By replicating the altitudinal gradient and explicitly accounting for the maternal effect, our results clearly suggest the existence of genetically based clinal patterns that provide signs of adaptive evolution. Early flowering is probably advantageous to completing reproduction before the hot summer at low altitudes. In ssp. kamchatica, which is perennial and can reproduce even if it does not flower in its first year, the strong vernalisation requirement may delay the first reproduction at high altitudes, where the growing season is short.
What Values Are and How They Are Structured

This chapter summarizes what we know about value—SWB relations and identifies some of what we do not know but would like to know. We first discuss the nature of values and the structured system they form. We draw on the ten values in the Schwartz (1992) theory that form a circular motivational continuum. We note three theoretical perspectives on relations of values to SWB. The first perspective seeks to explain direct relations between values and SWB. A second generation of direct relations research explains variation in relations across samples by pointing to societal-level moderators. The second perspective examines the congruence (or similarity) between people’s values and the values prevailing in their environment as a determinant of SWB. The third perspective sees the attainment of valued goals as the source of SWB. We present these perspectives and the literature based on them, and note ideas for future research throughout.
Fast Safety Assessment and Correction Framework for Maintenance Work Zones

A framework is proposed to assess the safety of maintenance work zones in a timely manner, show whether there are safety hazards, whether adjustments need to be made and how to adjust it. By means of advanced data acquisition technologies such as multi video detection and portable device based naturalistic driving, the microscopic vehicle behaviour data can be collected. Based on this data, a method for expressing and displaying the distribution of unsafe vehicle behaviour is used to show whether safety hazards exist. Using Vissim, the impacts of the length and speed limit of the warning area, the length and type of the upstream transition area and the length of the work area of the maintenance work zone on the distribution of unsafe vehicle behaviour are simulated to establish the safety correction matrix, which can tell maintenance departments the direction of adjustment when safety hazards exist in maintenance work zones.
A two-dimensional propensity score matching method for longitudinal quasi-experimental studies: A focus on travel behavior and the built environment

The lack of longitudinal studies of the relationship between the built environment and travel behavior has been widely discussed in the literature. This paper discusses how standard propensity score matching estimators can be extended to enable such studies by pairing observations across two dimensions: longitudinal and cross-sectional. Researchers mimic randomized controlled trials and match observations in both dimensions to find synthetic control groups that are similar to the treatment group and to match subjects across before- and after-treatment periods. We call this a two-dimensional propensity score matching method. This method demonstrates superior performance for improving treatment effect estimation based on Monte Carlo evidence. A near-term opportunity for such matching is identifying the treatment effect of transportation infrastructure on travel behavior.
Sparse inversion for derivative of log determinant

Algorithms for Gaussian process, marginal likelihood methods or restricted maximum likelihood methods often require derivatives of log determinant terms. These log determinants are usually parametric with variance parameters of the underlying statistical models. This paper demonstrates that, when the underlying matrix is sparse, how to take the advantage of sparse inversion---selected inversion which share the same sparsity as the original matrix---to accelerate evaluating the derivative of log determinant.
Quantum Computation Toolbox for Decoherence‐Free Qubits Using Multi‐Band Alkali Atoms

Protocols for designing and manipulating qubits with ultracold alkali atoms in 3D optical lattices are introduced. These qubits are formed from two‐atom spin superposition states that create a decoherence‐free subspace immune to stray magnetic fields, dramatically improving coherence times while still enjoying the single‐site addressability and Feshbach resonance control of state‐of‐the‐art alkali atom systems. The protocol requires no continuous driving or spin‐dependent potentials, and instead relies upon the population of a higher motional band to realize naturally tunable in‐site exchange and cross‐site superexchange interactions. As a proof‐of‐principle example of their utility for entanglement generation for quantum computation, it is shown that the cross‐site superexchange interactions can be used to engineer 1D cluster states. Explicit protocols for experimental preparation and manipulation of the qubits are also discussed, as well as methods for measuring more complex quantities such as out‐of‐time‐ordered correlation functions (OTOCs).
Technical Report: Co-learning of geometry and semantics for online 3D mapping

This paper is a technical report about our submission for the ECCV 2018 3DRMS Workshop Challenge on Semantic 3D Reconstruction \cite{Tylecek2018rms}. In this paper, we address 3D semantic reconstruction for autonomous navigation using co-learning of depth map and semantic segmentation. The core of our pipeline is a deep multi-task neural network which tightly refines depth and also produces accurate semantic segmentation maps. Its inputs are an image and a raw depth map produced from a pair of images by standard stereo vision. The resulting semantic 3D point clouds are then merged in order to create a consistent 3D mesh, in turn used to produce dense semantic 3D reconstruction maps. The performances of each step of the proposed method are evaluated on the dataset and multiple tasks of the 3DRMS Challenge, and repeatedly surpass state-of-the-art approaches.
Biofiltration, growth and body composition of oyster Crassostrea rhizophorae in effluents from shrimp Litopenaeus vannamei

The objective of this study was to use oyster as biofilter to improve the quality of effluent from shrimp farming and to assess its growth performance and body composition. It was distributed 1,080 oysters into lanterns in fiberglass tanks (170 L) in a completely randomized design with three treatments (0, 60 and 120 oysters) and six replicates. It was used the effluent from the sedimentation tank. It was measured weekly: temperature, salinity, dissolved oxygen and pH, and it was analyzed ammonia-N, nitrite-N, nitrate-N, orthophosphate-P, suspended solids and chlorophyll-α of the input effluent. The control tanks (without oysters) were more efficient at removing ammonia-N, nitrite-N, nitrate-N and orthophosphate-P. The tanks containing oysters were more efficient at removing suspended solids and chlorophyll-α. Stocking density influenced the height growth of oysters, but not width. Wet and daily weight, condition and yield index were not affected by stocking density, and a significant increase in comparison to the initials values was observed. Body composition was not affected by stocking density, and a significant difference (p 0.05). Under the conditions evaluated, the oyster Crassostrea rhizophorae improves water quality and presents growth rates and body composition similar to those obtained in traditional crops.
The role of endogenous molecules in modulating pain through TRPV 1

Pain is a physiological response to a noxious stimulus that decreases the quality of life of people who suffer from it. Research aimed at finding new therapeutic targets for the This article is protected by copyright. All rights reserved. A cc ep te d A rti cl e 3 treatment of several maladies including pain has led to the discovery of numerous molecular regulators of ion channels in primary afferent nociceptive neurons. Among these receptors is TRPV1, a member of the Transient Receptor Potential (TRP) family of ion channels. TRPV1 is a calcium permeable channel, which is activated or modulated by diverse exogenous noxious stimuli such as high temperatures, changes in pH, irritant and pungent compounds and by selected molecules released during tissue damage and inflammatory processes. During the last decade the number of endogenous regulators of TRPV1’s activity has increased to include lipids that can negatively regulate TRPV1, as is the case for cholesterol and PIP2 while, in contrast, other lipids produced in response to tissue injury and ischemic processes are known to positively regulate TRPV1. Among the latter, lysophosphatidic acid activates TRPV1 while amines such as N-acylethanolamines and N-acyl-dopamines can sensitize or directly activate TRPV1. It has also been found that nucleotides such as ATP act as mediators of chemically induced nociception and pain and gases, such as hydrogen sulphide and nitric oxide, lead to TRPV1 activation. Finally, the products of lipoxygenases and omega-3 fatty acids among other molecules such as divalent cations have also been shown to endogenously regulate TRPV1 activity. Here we provide a comprehensive review of endogenous small molecules that regulate the function of TRPV1. Acting through mechanisms that lead to sensitization and desensitization of TRPV1, these molecules regulate pathways involved in pain and nociception. Understanding how these compounds modify TRPV1 activity will allow us to comprehend how some pathologies are associated with its deregulation. This article is protected by copyright. All rights reserved. A cc ep te d A rti cl e
Low-Profile Polarization-Adjustable Ring Slot Antenna for Millimeterwave Applications

In this paper, a dual-port antenna with polarization adjustability is proposed for millimeter-wave applications. The loading effect of four ring slots stimulates a hybrid mode in the cylindrical cavity that generates eight magnetic monopoles with high gain in boresight. Through controlling the phase difference between the two ports, six types of polarization can be demonstrated. Simulation results in 28 GHz show a maximum gain of 13 dBi, 10% bandwidth, and a good cross-polarization level in all polarization states. Distinct features including low-profile, low-cost, single-layer, and simple feeding network make the antenna a suitable candidate for upcoming millimeter-wave and 5G applications.
AN EFFICIENT AUTHENTICATION PROTOCOL USING ZERO KNOWLEDGE PROPERTY AND PAIRING ON ELLIPTIC CURVES

The systematic introduction to zero knowledge proof protocol has important theoretical guidance and practical significance on attracting more scholars involved in research as well as expanding application fields. Zero-knowledge proofs were first conceived in 1985 by Shafi Golwasser, Silvio Micalli and Charles Rackoff in a draft of the knowledge complexity of interactive proof systems. The goal of the present paper is to introduce a new identity based scheme which is a combination of zero-knowledge interactive proof and weil pairing on elliptic curves. The concept of weil pairing was first introduced by Andre Weil in 1940. It plays an important role in the theoretical study of the arithmetic of elliptic curves and Abelian varieties. It has also recently become extremely useful in cryptologic constructions related to these objects.
Size-based, seasonal, and multidirectional movements of an estuarine fish species in a habitat mosaic

To improve understanding of uni- versus multidirectional movement, seasonal dynamics, and the role of body size in tropical and sub-tropical nursery habitat, we conducted a 4 yr study on 1917 tagged juvenile common snook Centropomus undecimalis in 4 mangrove creeks. We detected 86% of individuals marked with autonomous passive integrated transponder (PIT) tag antennae. Marked fish were divided into 2 size classes (SC) for analysis: SC1 (approxi- mately age-0) and SC2 (approximately age-1). A higher percentage of SC2 than SC1 snook migrated, SC2 made longer movements, and the 10 d probability of migration was 2.4-fold higher in SC2 than SC1. For both size classes, migration probabilities varied seasonally, with lowest rates in the coldest months. Furthermore, migration events during fall and winter tended to be tempo- rary movements, while migration in spring and summer was more often permanent. Increased catch proportion of late-stage SC1 and early-stage SC2 individuals outside the creeks in spring/ summer temporally aligns with increased permanent migration, suggesting a large-scale seasonal movement away from the study creeks. During this potential seasonal transition to alternative habitats, increased mortality at the end of the first year, as implied by proportionally fewer SC1 than SC2 individuals returning to the creeks in the following year, may act as an early population bottleneck. Alternatively, some individuals may lack fidelity and instead move to habitat not studied here. This work suggests that movement from nursery habitat can be bidirectional, size depend- ent, and seasonally dependent, and that the studied habitat functions as part of a habitat mosaic.
Improving Generalization of Transformer for Speech Recognition with Parallel Schedule Sampling and Relative Positional Embedding

Transformer showed promising results in many sequence to sequence transformation tasks recently. It utilizes a number of feed-forward self-attention layers in the encoder and decoder to replace recurrent neural networks (RNN) in attention-based encoder decoder (AED). Self-attention layer learns temporal dependence by incorporating sinusoidal positional embedding of tokens in sequences for parallel computing. Quicker iteration speed in training than sequential operation of RNN can be obtained. The deeper layer of transformer also makes it perform better than RNN-based AED. However, this parallelization makes it hard to apply schedule sampling training. Self-attention with sinusoidal positional embedding may also cause performance degradations for longer sequence that has similar acoustic or semantic information at different positions. To address these problems, we propose to use parallel schedule sampling (PSS) and relative positional embedding (RPE) to help transformer generalize to unseen data. Our proposed methods achieve 7% relative improvement for short utterances and 30% absolute gains for long utterances on a 10,000-hour ASR task.
Scenarios and Recommendations for Ethical Interpretive AI

Artificially intelligent systems, given a set of non-trivial ethical rules to follow, will inevitably be faced with scenarios which call into question the scope of those rules. In such cases, human reasoners typically will engage in interpretive reasoning, where interpretive arguments are used to support or attack claims that some rule should be understood a certain way. Artificially intelligent reasoners, however, currently lack the ability to carry out human-like interpretive reasoning, and we argue that bridging this gulf is of tremendous importance to human-centered AI. In order to better understand how future artificial reasoners capable of human-like interpretive reasoning must be developed, we have collected a dataset of ethical rules, scenarios designed to invoke interpretive reasoning, and interpretations of those scenarios. We perform a qualitative analysis of our dataset, and summarize our findings in the form of practical recommendations.