Miracle-dz/UniFAR-FTUs huggingface dataset:
Photolytically Generated Aerosols in the Mesosphere and Thermosphere of Titan

Analysis of the Cassini Ultraviolet Imaging Spectrograph (UVIS) stellar and solar occultations at Titan to date include 12 species: N2 (nitrogen), CH4 (methane), C2H2 (acetylene), C2H4 (ethylene), C2H6 (ethane), C4H2 (diacetylene), C6H6 (benzene), C6N2 (dicyanodiacetylene), C2N 2 (cyanogen), HCN (hydrogen cyanide), HC3N (cyanoacetylene), and aerosols distinguished by a structureless continuum extinction (absorption plus scattering) of photons in the EUV. The introduction of aerosol particles, retaining the same refractive index properties as tholin with radius ~125 Å and using Mie theory, provides a satisfactory fit to the spectra. The derived vertical profile of aerosol density shows distinct structure, implying a reactive generation process reaching altitudes more than 1000 km above the surface. A photochemical model presented here provides a reference basis for examining the chemical and physical processes leading to the distinctive atmospheric opacity at Titan. We find that dicyanodiacetylene is condensable at ~650 km, where the atmospheric temperature minimum is located. This species is the simplest molecule identified to be condensable. Observations are needed to confirm the existence and production rates of dicyanodiacetylene.
The Semantic Network Model of Creativity: Analysis of Online Social Media Data

The central hypothesis of Semantic Network Model of Creativity is that creative people, who are exposed to more information that are both novel and useful, will have more interconnections between event schemas in their associations. The networks of event schemas in creative people’s minds were expected to be wider and denser than those in less creative people’s minds. Based on this theory, data from Chinese online social media, also known as “Weibo microblogging,” were analyzed. Each user’s score consisted of the metric of coverage, which represented the spread of the network, as well as the metric of density, which represented the interconnections among nodes in the network. The results showed that occupations had a significant effect on people’s creativity score. Academic scholars and writers in general had higher scores compared to other groups, such as entertainment celebrities and sport stars. The implications and limitations of this method of quantifying people’s creativity were discussed.
An efficient approach to rule redundancy reduction in hierarchical phrase-based translation

Hierarchical phrase-based machine translation model is a popular syntax model that makes use of the expressive power of synchronous context-free grammars (SCFG) to address the reordering problem in statistical machine translation. The model, however, generally suffers from a great amount of redundancy in the extracted translation rules. In this paper, we re-introduce the concept of rift into the rule extraction procedure to force the rules with reordering power to concentrate on where reordering has actually happened. Our approach brings a dramatic reduction in the training time and the number of the rules, with only minor sacrifice in translation quality.
Decentralized Opportunistic Access for D2D Underlaid Cellular Networks

In this paper, we propose a decentralized access control scheme for interference management in device-to-device (D2D) underlaid cellular networks. Our method combines signal-to-interference ratio (SIR)-aware link activation with cellular guard zones in a system, where D2D links opportunistically access the licensed cellular spectrum when the activation conditions are satisfied. Analytical expressions for the success/coverage probability of both cellular and D2D links are derived. We characterize the impact of the guard zone radius and the SIR threshold on the D2D potential throughput and cellular coverage. A tractable approach is proposed to find the SIR threshold and guard zone radius that maximize the potential throughput of the D2D communication while ensuring sufficient coverage probability for the cellular uplink users. Simulations validate the accuracy of our analytical results and show the performance gain of the proposed scheme compared to prior state-of-the-art solutions.
Correlations Higher Order Factor Structure Of A Self-Control Test : Evidence From Confirmatory Factor Analysis With

can be found at: Educational and Psychological Measurement Additional services and information for http://epm.sagepub. com/cgi/alerts Email Alerts: http://epm.sagepub. com/subscriptions Subscriptions: http://www.sagepub. com/journalsReprints.nav Reprints: http://www.sagepub. com/journalsPermissions.nav Permissions: http://epm.sagepub. com/cgi/content/refs/63/1/112 SAGE Journals Online and HighWire Press platforms): (this article cites 12 articles hosted on the Citations
Employment of MNEs in Japan: New Evidence

This paper asks two questions. 1) Do multinational enterprises (MNEs) present different patterns of employment from domestic firms? 2) Do workers in MNEs face a higher risk of losing jobs? We distinguish two types of MNEs (i.e., Japanese MNEs and foreign-owned firms) and utilize firm-level data in Japan between 1995 and 2000. It was true that the net job destruction of Japanese MNEs was larger than those of foreign-owned firms and domestic firms. However, this negative employment growth is attributable not to rapid job destruction but to slow job creation. Second, workers in Japanese MNEs and foreign-owned firms did not face a higher risk of losing jobs than did those in domestic firms. This finding contradicts the findings of Barba Navaretti, Turrini, and Checchi (2003) but is consistent with the firm-specific skill hypothesis of Fukao and Otaki (1993). Japanese MNEs and foreign-owned firms might invest heavily in job training, which results in their lower employment volatility.
Influence of RNA structural stability on the RNA chaperone activity of the Escherichia coli protein StpA

Proteins with RNA chaperone activity are able to promote folding of RNA molecules by loosening their structure. This RNA unfolding activity is beneficial when resolving misfolded RNA conformations, but could be detrimental to RNAs with low thermodynamic stability. In order to test this idea, we constructed various RNAs with different structural stabilities derived from the thymidylate synthase (td) group I intron and measured the effect of StpA, an Escherichia coli protein with RNA chaperone activity, on their splicing activity in vivo and in vitro. While StpA promotes splicing of the wild-type td intron and of mutants with wild-type-like stability, splicing of mutants with a lower structural stability is reduced in the presence of StpA. In contrast, splicing of an intron mutant, which is not destabilized but which displays a reduced population of correctly folded RNAs, is promoted by StpA. The sensitivity of an RNA towards StpA correlates with its structural stability. By lowering the temperature to 25°C, a temperature at which the structure of these mutants becomes more stable, StpA is again able to stimulate splicing. These observations clearly suggest that the structural stability of an RNA determines whether the RNA chaperone activity of StpA is beneficial to folding.
Automated Symbolic Proofs of Observational Equivalence

Many cryptographic security definitions can be naturally formulated as observational equivalence properties. However, existing automated tools for verifying the observational equivalence of cryptographic protocols are limited: they do not handle protocols with mutable state and an unbounded number of sessions. We propose a novel definition of observational equivalence for multiset rewriting systems. We then extend the Tamarin prover, based on multiset rewriting, to prove the observational equivalence of protocols with mutable state, an unbounded number of sessions, and equational theories such as Diffie-Hellman exponentiation. We demonstrate its effectiveness on case studies, including a stateful TPM protocol.
Searching for an optimal sensor location in the identification of laminates' parameters

The aim of the paper is to find an optimal sensor location in order to perform an identification of laminates’ elastic constants. As a result the identification procedure can be more accurate and less time-consuming. Simple and hybrid (with laminas composed of different materials) laminates are considered. To collect data necessary for the identification procedure modal analysis methods are used. This attitude allows reducing the number of sensor points to one. Sensitivity analysis of the measurements to the variation of identified parameters is performed. Global optimization methods in form of Evolutionary Algorithm and Artificial Immune System are employed to perform the identification task. Commercial finite element method software is employed to solve the direct problem for laminates. Numerical examples showing the influence of the sensor point location on the identification results are attached.
A Simple Probabilistic Approach to Ranking Documents by Sentiment

The problem of determining the sentiment of documents has often been approached via highly human-structured or highly complex methods. These approaches have generally been constrained to dividing an input corpus into two categories, positive and negative. I present a simple and straightforward probabilistic algorithm that attempts to rank an entire corpus in increasingly-positive order of sentiment, which is a more useful output. The output can be easily reinterpreted to solve a two-category sentiment classification task, in which case the proposed algorithm performs nearly as well as existing approaches to that problem.
How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS

There has been a recent growth in the use of Bayesian methods in medical research. The main reasons for this are the development of computer intensive simulation based methods such as Markov chain Monte Carlo (MCMC), increases in computing power and the introduction of powerful software such as WinBUGS. This has enabled increasingly complex models to be fitted. The ability to fit these complex models has led to MCMC methods being used as a convenient tool by frequentists, who may have no desire to be fully Bayesian.
High-rate WiFi broadcasting in crowded scenarios via lightweight coordination of multiple access points

The enormous success of advanced wireless devices is pushing the demand for higher wireless data rates. The industry is satisfying this increasing demand by densely deploying large numbers of access points (APs). Unfortunately, unicast rates, especially in crowded scenarios, remain very low due to severe interference and time-sharing. However, one may take advantage of the broadcasting nature of wireless transmissions to offer high multicast rates. Motivated by this, we present coordinated broadcasting (Co-BCast), a system which coordinates multiple APs to provide participants of big events with high multicast rates that can support multiple high definition video streams. Co-BCast requires no complicated time or frequency synchronization and no instantaneous channel state information. Yet, despite the time and frequency offsets among concurrent transmitters, the aggregate signal from the coordinated APs offers uniform coverage and high SINR to all users. We explore the challenges of such asynchronous transmissions through theoretical analysis and wireless experiments on software defined radio (SDR) testbeds. We use a number of PHY techniques to address those challenges and implement our coordination scheme on top of an 802.11 reference design. Both wireless experiments and large-scale simulations demonstrate that Co-BCast can achieve multicast rates in the order of 100Mbps even in the most crowded scenarios. These rates are orders of magnitude higher than the unicast and multicast rates achieved by uncoordinated transmissions.
Development of a clinical data warehouse

There is increasing worldwide awareness that bionics and artificial intelligence will play an important role in microbial analysis. An intelligent data-warehouse system consisting of an odour generation mechanism, rapid volatile delivery and recovery system, and a classifier system based on neural networks and genetic algorithms have been applied as part of a microbial analysis. The microbiological warehouse environment has, also adopted the concept of fusion of multiple classifiers dedicated to specific feature parameters. The experimental results confirm the soundness of the presented methods.
Variable Metrics in Evolutionary Computation

This thesis considers variable metrics in the context of stochastic, function-value free optimization in continuous search spaces. We argue that the choice of a (variable) metric or equivalently the choice of a coordinate system can be decoupled from the underlying optimization procedure. An adaptive encoding procedure is presented, that is in principle applicable to any optimization procedure, and is proved to recover the covariance matrix adaptation evolution strategy (CMA-ES) when applied to a simple isotropic evolution strategy with step-size adaptation. The proof suggests that adaptive encoding should be able to improve the performance of many stochastic optimization algorithms in particular on ill-conditioned, non-separable objective functions.
Supersymmetric M-theory compactifications with fluxes on seven-manifolds and G-structures

We consider Minkowski compactifications of M-theory on generic seven-dimensional manifolds. After analyzing the conditions on the four-form flux, we establish a set of relations between the components of the intrinsic torsion of the internal manifold and the components of the four-form flux needed for preserving supersymmetry. The existence of two nowhere vanishing vectors on any seven-manifold with G2 structure plays a crucial role in our analysis, leading to the possibility of four-dimensional compactifications with = 1 and = 2 supersymmetry.
Dynamic Pricing for Vertically Differentiated Products

This paper studies the seller’s optimal pricing policies for a family of substitute perishable products. The seller aims to maximize her expected cumulative revenues over a finite selling horizon. At each demand epoch, the arriving customer observes the set of substitute products with positive inventory together with their prices. Based on this information as well as the customer’s own budget constraint, he either buys one of the available products, or leaves the system without making any purchase. We propose a choice model where a fixed ranking of the products is decided by the quality-price combination. We show the monotonicity property of the optimal prices with respect to quality, inventory and time-to-go. We derive the distribution-free pricing methodology and obtain the robust bounds on the price increment through the first-order Taylor approximation. Our work also sheds light on the assortment design in terms of choosing the breadth of the product quality range as well as the number of products in the assortment.
Target Selectivity of Feedforward Inhibition by Striatal Fast-Spiking Interneurons

The striatal microcircuitry consists of a vast majority of projection neurons, the medium spiny neurons (MSNs), and a small yet diverse population of interneurons. To understand how activity is orchestrated within the striatum, it is essential to unravel the functional connectivity between the different neuronal types. Fast-spiking (FS) interneurons provide feedforward inhibition to both direct and indirect pathway MSNs and are important in sculpting their output to downstream basal ganglia nuclei. FS interneurons are also interconnected with each other via electrical and chemical synapses; however, whether and how they inhibit other striatal interneuron types remains unknown. In this study we combined multineuron whole-cell recordings with optogenetics to determine the target selectivity of feedforward inhibition by striatal FS interneurons. Using transgenic and viral approaches we directed expression of channelrhodopsin 2 (ChR2) to FS interneurons to study their connectivity within the mouse striatal microcircuit. Optogenetic stimulation of ChR2-expressing FS interneurons generated strong and reliable GABAA-dependent synaptic inputs in MSNs. In sharp contrast, simultaneously recorded neighboring cholinergic interneurons did not receive any synaptic inputs from photostimulated FS cells, and a minority of low-threshold spiking (LTS) interneurons responded weakly. We further tested the synaptic connectivity between FS and LTS interneurons using paired recordings, which showed only sparse connectivity. Our results show that striatal FS interneurons form a feedforward inhibitory circuit that is target selective, inhibiting projection neurons while avoiding cholinergic interneurons and sparsely contacting LTS interneurons, thus supporting independent modulation of MSN activity by the different types of striatal interneurons.
Design and analysis of novel dynamic latched comparator with reduced kickback noise for high-speed ADCs

A novel dynamic latched comparator with reduced kickback noise for high-speed ADCs is presented. Dynamic latched comparators suffer from kickback noise. Especially the common-mode kickback noise becomes even more critical in applications with asymmetric input. By using common source input transistors and a decoupling mechanism the novel dynamic latched comparator produces much lower common-mode kickback noise, while the differential kickback noise is also significantly reduced. The simulated results show that the proposed comparator not only produces less than one third of the common-mode kickback noise of other typical dynamic latched comparators, but also settles faster.
On the way to solve lighting problems in underwater imaging

A major obstacle to processing images of the ocean floor comes from the absorption and scattering effects of the light in the aquatic environment. Due to the absorption of the natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion, and, as the vehicle moves, induce shadows in the scene. For this reason, the first step towards application of standard computer vision techniques to underwater imaging requires dealing first with these lighting problems. This paper analyses and compares existing methodologies to deal with low-contrast, nonuniform illumination in underwater image sequences. The reviewed techniques include: (i) study of the illumination-reflectance model, (ii) local histogram equalization, (iii) homomorphic filtering, and, (iv) subtraction of the illumination field. Several experiments on real data have been conducted to compare the different approaches.
The wobbly table: Increased social presence via subtle incidental movement of a real-virtual table

While performing everyday interactions, we often incidentally touch and move objects in subtle ways. These objects are not necessarily directly related to the task at hand, and the movement of an object might even be entirely unintentional. If another person is touching the object at the same time, the movement can transfer through the object and be experienced - however subtly - by the other person. For example, when one person hands a drink to another, at some point both individuals will be touching the glass, and consequently exerting small (often unnoticed) forces on the other person. Despite the frequency of such subtle incidental movements of shared objects in everyday interactions, few have examined how these movements affect human-virtual human (VH) interaction. We ran an experiment to assess how presence and social presence are affected when a person experiences subtle, incidental movement through a shared real-virtual object. We constructed a real-virtual room with a table that spanned the boundary between the real and virtual environments. The participant was seated on the real side of the table, which visually extended into the virtual world via a projection screen, and the VH was seated on the virtual side of the table. The two interacted by playing a game of “Twenty Questions,” where one player asked the other a series of 20 yes/no questions to deduce what object the other player was thinking about. During the game, the “wobbly” group of subjects experienced subtle incidental movements of the real-virtual table: the entire real-virtual table tilted slightly away/toward the subject when the virtual/real human leaned on it. The control group also played the same game, except the table did not wobble. Results indicate that the wobbly group had higher presence and social presence with the virtual human in general, with statistically significant increases in presence, co-presence, and attentional allocation. We present the experiment and results, and discuss some potential implications for virtual human systems and some potential future studies.
Unsupervised Brain Computer Interface Based on Intersubject Information and Online Adaptation

Conventional brain computer interfaces rely on a guided calibration procedure to address the problem of considerable variations in electroencephalography (EEG) across human subjects. This calibration, however, implies inconvenience to the end users. In this paper, we propose an online-adaptive-learning method to address this problem for P300-based brain computer interfaces. By automatically capturing subject-specific EEG characteristics during online operation, this method allows a new user to start operating a P300-based brain-computer interface without guided (supervised) calibration. The basic principle is to first learn a generic model termed subject-independent model offline from EEG of a pool of subjects to capture common P300 characteristics. For a new user, a new model termed subject-specific model is then adapted online based on EEG recorded from the new subject and the corresponding labels predicted by either the subject-independent model or the adapted subject-specific model, depending on a confidence score. To verify the proposed method, a study involving 10 healthy subjects is carried out and positive results are obtained. For instance, after 2-4 min online adaptation (spelling of 10-20 characters), the accuracy of the adapted model converges to that of a fully trained supervised subject-specific model.