Miracle-dz/UniFAR-FTUs huggingface dataset:
Repeated Game Based Cooperation Mechanism for Antenna Beam Resource Allocation in TDRSS

In the tracking and data relay satellite system, users compete for the limited inter-satellite link antenna beam (ILAB) resource by excessive resource requests. This can lead to serious user request conflicts and considerably degrade the QoS (quality of service) of the system. Since those selfish users have no incentive to cooperate in a one-shot resource request, in this paper we construct a cooperation mechanism to maximize users' payoffs and meanwhile to reduce the conflict relying on a repeated game framework. Moreover, an efficient punishment and forgiveness strategy is proposed to prevent any user from breaking the cooperation. Simulation results confirm that the proposed scheme can significantly improve the system's operation performance. Compared with the payoffs under the Nash equilibrium in the one-shot game which is the traditional scheme, our repeated ILAB resource allocation game can acquire 1.36 to 3.46 times gain in respect to 2 to 10 users, respectively.
Training Neural Machine Translation using Word Embedding-based Loss

In neural machine translation (NMT), the computational cost at the output layer increases with the size of the target-side vocabulary. Using a limited-size vocabulary instead may cause a significant decrease in translation quality. This trade-off is derived from a softmax-based loss function that handles in-dictionary words independently, in which word similarity is not considered. In this paper, we propose a novel NMT loss function that includes word similarity in forms of distances in a word embedding space. The proposed loss function encourages an NMT decoder to generate words close to their references in the embedding space; this helps the decoder to choose similar acceptable words when the actual best candidates are not included in the vocabulary due to its size limitation. In experiments using ASPEC Japanese-to-English and IWSLT17 English-to-French data sets, the proposed method showed improvements against a standard NMT baseline in both datasets; especially with IWSLT17 En-Fr, it achieved up to +1.72 in BLEU and +1.99 in METEOR. When the target-side vocabulary was very limited to 1,000 words, the proposed method demonstrated a substantial gain, +1.72 in METEOR with ASPEC Ja-En.
Use of linguistic forms mining in the link analysis of legal documents

This document employs a statistical approach in exploring language and extracting linguistic forms there contained, so as to identify the linguistic forms which are most frequently used in legal documents. Thus retrieved data, as the second part of this paper shows, can be used to research information, analyze references and links, trace pathways between correlating legal documents and establish the relevance of legal documents on the grounds of their mutual correlation. The retrieved data can further be utilized in various other manners. The methodology of this research and thus attained information form a good basis and act as input data for numerous further analyses.
Won by a Head: A Platform Comparison of Smart Object Linking in Virtual Environments

Mixed -reality platforms and toolkits are now more accessible than ever, bringing a renewed interest in interactive mixed-reality applications. However, more research is required to determine which available platforms are best suited for different situated tasks. This paper presents a user study that compares headworn and handheld platforms with a smart object linking task in interactive virtual environments. These platforms both have potential beneﬁts for supporting spatial interaction for uses situated in the spatial context of the objects being connected. Results show that the immersive, headworn platform has several beneﬁts over the handheld tablet, including better performance and user experience. Findings also show that semantic knowledge about a spatial environment can provide advantages over abstract object identiﬁers.
( Supplemental Material ) Appendix : Markov Modulated Gaussian Cox Processes for Semi-Stationary Intensity Modeling of Events Data

For convenience, we define the diagonal entries of Q such that Q has 0 row sums, i.e., Qii := − ∑ j 6=iQij . We often denote the initial state probabilities as a row vector π (i.e., π = [π1, . . . , πr]). Then, using the differential notations and denoting the infinitesimal time duration by dt, the following holds for all i, j = 1, . , r, P (X(t+ dt) = j|X(t) = i) = I{i=j} +Qijdt. (2) Hence the marginal state distribution conforms to the first-order linear ODE. More specifically, letting v(t) be the r-dim row vector of the state distribution at time t (i.e., [v(t)]i = p(X(t) = i)), we can rewrite (2) in a vector notation,
Epigenetic Modifiers Induce Bioactive Phenolic Metabolites in the Marine-Derived Fungus Penicillium brevicompactum

Fungi usually contain gene clusters that are silent or cryptic under normal laboratory culture conditions. These cryptic genes could be expressed for a wide variety of bioactive compounds. One of the recent approaches to induce production of such cryptic fungal metabolites is to use histone deacetylases (HDACs) inhibitors. In the present study, the cultures of the marine-derived fungus Penicillium brevicompactum treated with nicotinamide and sodium butyrate were found to produce a lot of phenolic compounds. Nicotinamide treatment resulted in the isolation and identification of nine compounds 1–9. Sodium butyrate also enhanced the productivity of anthranilic acid (10) and ergosterol peroxide (11). The antioxidant as well as the antiproliferative activities of each metabolite were determined. Syringic acid (4), sinapic acid (5), and acetosyringone (6) exhibited potent in vitro free radical scavenging, (IC50 20 to 30 µg/mL) and antiproliferative activities (IC50 1.14 to 1.71 µM) against HepG2 cancer cell line. Furthermore, a pharmacophore model of the active compounds was generated to build up a structure-activity relationship.
Efficient Estimation of Inclusion Coefficient using HyperLogLog Sketches

Efficiently estimating the inclusion coefficient - the fraction of values of one column that are contained in another column - is useful for tasks such as data profiling and foreign-key detection. We present a new estimator, BML, for inclusion coefficient based on Hyperloglog sketches that results in significantly lower error compared to the state-of-the art approach that uses Bottom-k sketches. We evaluate the error of the BML estimator using experiments on industry benchmarks such as TPC-H and TPC-DS, and several real-world databases. As an independent contribution, we show how Hyperloglog sketches can be maintained incrementally with data deletions using only a constant amount of additional memory.
Alignment Analysis of Sequential Segmentation of Lexicons to Improve Automatic Cognate Detection

Ranking functions in information retrieval are often used in search engines to extract the relevant answers to the query. This paper makes use of this notion of information retrieval and applies onto the problem domain of cognate detection. The main contributions of this paper are: (1) positional tokenization, which incorporates the sequential notion; (2) graphical error modelling, which calculates the morphological shifts. The current research work only distinguishes whether a pair of words are cognates or not. However, we also study if we could predict a possible cognate from the given input. Our study shows that language modelling based retrieval functions with positional tokenization and error modelling tend to give better results than competing baselines.
Analyzing Uncivil Speech Provocation and Implicit Topics in Online Political News

Online news has made dissemination of information a faster and more efficient process. Additionally, the shift from a print medium to an online interface has enabled user interactions, creating a space to mutually understand the reader responses generated by the consumption of news articles. Intermittently, the positive environment is transformed into a hate-spewing contest, with the amount and target of incivility varying depending on the specific news website in question. In this paper, we develop methods to study the emergence of incivility within the reader communities in news sites. First, we create a dataset of political news articles and their reader comments from partisan news sites. Then, we train classifiers to predict different aspects of uncivil speech in comments. We apply these classifiers to predict whether a news article is likely to provoke a substantial portion of reader comments containing uncivil language by analyzing only the article's content. Finally, we devise a technique to "read between the lines" --- finding the topics of discussions that an article triggers among its readers without frequent, explicit mentions of these topics in its content.
Collision detection during planning for sheet metal bending by bounding volume hierarchy approaches

ABSTRACT Collision detection is a computationally intensive task within process planning for sheet metal bending. An efficient collision detection algorithm can greatly improve the speed of the process planning. In this work, relevant features are extracted first from STL format of the part and tool models. Next, the collision detection strategies for the sheet metal bending problem are investigated considering bounding volume hierarchies involving oriented-bounding box (OBB) and axis-aligned bounding box (AABB) methods. The approaches are explained using two example parts. By analysing the data for 10 different sheet metal parts, it is demonstrated that although OBB hierarchy is more efficient in terms of minimising the number of collision tests between part and tool models, AABB hierarchy is superior in terms of computation time. The collision detection method based on AABB can be integrated with the sheet metal bend planning to realise CAD–CAM integration.
Fiber-Based High-Energy Femtosecond Pulses Tunable From 920 to 1030 nm for Two-Photon Microscopy

We demonstrate a fiber-based femtosecond laser source, which can deliver 37 MHz, ~100 fs laser pulses tunable from 920 nm to 1030 nm with up to 10 nJ pulse energy. Pumped by an ultrafast Yb-doped fiber laser, a short piece of tapered photonic crystal fiber with lower dispersion was used to generate self-phase-modulation filtered for the tunable pulses. We believe that this new type of high-energy ultrafast fiber laser source can be an ideal solution for the two-photon fluorescence microscopy applications.
An asynchronous P system with branch and bound for solving the satisfiability problem

Membrane computing, which is a computational model based on cell activity, has considerable attention as one of new paradigms of computations. In the general membrane computing, computationally hard problems have been solved in a polynomial number of steps using an exponential number of membranes. However, reduction of the number of membranes must be considered to make P system more realistic model. In the paper, we propose an asynchronous P system with branch and bound, which is a well known optimization technique, to reduce the number of membranes. The proposed P system solves the satisfiability problem (SAT) with n variables and m clauses, and works in O ( m 2^ n )$ sequential steps or O ( mn ) parallel steps. In addition, the number of membranes used in the proposed P system is evaluated using a computational simulation. The experimental result shows validity and efficiency of the proposed P system.
A programmable ternary CPU using hybrid CMOS/memristor circuits

Abstract The carry propagation of arithmetic operations is one of the major shortcomings of common binary number encodings as the two’s complement. Signed-digit arithmetic allows the addition of two numbers without carry propagation and in asymptotically constant time in dependence of the word length, while at the same time requiring a digit representation with more than two states. With the advent of memristors, it has become possible to store multiple states within a single memory cell. This paper proposes an implementation of a general purpose CPU using signed-digit arithmetic by exploiting memristors in order to implement multi-value registers. The proposed model of the CPU is evaluated by the execution of various image processing algorithms. It is shown that a break-even point exists at which signed-digit algorithms outperform conventional binary arithmetic operations. Furthermore, simulation results prove that the memristor device lends itself to store signed-digit data efficiently. Graphical Abstract Measurement of memristors behavior to store multiple discrete values. Below 5 k the digit 1 is coded, between 5 and 12.5 k the digit 0, and above 12.5 k the digit 1.
Caloric restriction combined with exercise is effective in reducing adiposity and mitigating bone structural deterioration in obese rats

Weight reduction through caloric restriction (CR) or exercise can have opposite effects on bone. This study investigated the effects of comparable weight reduction through CR and/or exercise on body composition and bone structure in an obese rat model. Male 6‐week‐old rats were fed either a normal‐fat diet for 6 months or a high‐fat (HF) diet for 3 months and then started on different CR or exercise regimens for an additional 3 months. Compared to HF conditions, rats given HF diet plus CR at 8% (HF+8CR), HF diet plus CR at 16% (HF+16CR), or HF+8CR plus exercise (HF+Ex+8CR) had lower fat mass. In addition, HF+8CR rats had lower serum tartrate‐resistant acid phosphatase and bone volume/total volume at distal femur (P < 0.05), and HF+16CR rats had lower serum insulin growth factor 1, osteocalcin, tartrate‐resistant acid phosphatase, and bone volume/total volume at distal femur and 2nd lumbar vertebrae, compared to regimens that included exercise. These data indicate that while CR (e.g., HF+8CR) was detrimental to bone structure, combined with exercise CR (e.g., HF+Ex+8CR) was effective in decreasing adiposity and mitigating bone structural deterioration associated with weight reduction in obese rats.
Multi-Sentence Compression with Word Vertex-Labeled Graphs and Integer Linear Programming

Multi-Sentence Compression (MSC) aims to generate a short sentence with key information from a cluster of closely related sentences. MSC enables summarization and question-answering systems to generate outputs combining fully formed sentences from one or several documents. This paper describes a new Integer Linear Programming method for MSC using a vertex-labeled graph to select different keywords, and novel 3-gram scores to generate more informative sentences while maintaining their grammaticality. Our system is of good quality and outperforms the state-of-the-art for evaluations led on news dataset. We led both automatic and manual evaluations to determine the informativeness and the grammaticality of compressions for each dataset. Additional tests, which take advantage of the fact that the length of compressions can be modulated, still improve ROUGE scores with shorter output sentences.
Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy

Inspired by many applications of bipartite matching in online advertising and machine learning, we study a simple and natural iterative proportional allocation algorithm: Maintain a priority score βa for each node a ∈ A on one side of the bipartition, initialized as βa = 1. Iteratively allocate the nodes i ∈ I on the other side to eligible nodes in A in proportion of their priority scores. After each round, for each node a ∈ A, decrease or increase the score βa based on whether it is overor underallocated. Our first result is that this simple, distributed algorithm converges to a (1 − )-approximate fractional b-matching solution in O( logn 2 ) rounds. We also extend the proportional allocation algorithm and convergence results to the maximum weighted matching problem, and show that the algorithm can be naturally tuned to produce maximum matching with high entropy. High entropy, in turn, implies additional desirable properties of this matching, e.g., it satisfies certain diversity and fairness (aka anonymity) properties that are desirable in a variety of applications in online advertising and machine learning.
Pareto-Optimal Network Resource Deployment for Trade-Off between Number of Resources and Operation Risk

Physical network resource deployment to meet future traffic growth is a significant issue for network operators because it has a significant impact on the overall performance of next-generation networks. In this paper, we propose an effective design method of physical network resource deployment by considering an adequate trade-off between the number of additional physical network resources, Q, and operation risk in both the pipe and the hose traffic models. Operation risk, which includes complex network design and misconfiguration of network components, is a significant issue in practical network operation because it increases the capital expenditure and operating expenses, in addition to preventing the provision of stable commercial services. We focus on reducing the number of links with additional capacity, Nu, as the first step to reduce operation risk. Numerical evaluations are performed to compare our method with a benchmark method that minimizes the number of physical network resources. Thus, our method is shown to be able to provide Pareto-optimal solutions that can reduce Nu significantly with a slight increase in Q. For example, Nu is reduced by 50% and 40% while increasing Q by 20% and only 2% in the pipe model and the hose model, respectively.
Recognising Assumption Violations in Autonomous Systems Verification

When applying formal verification to a system that interacts with the real world we must use a model of the environment. This model represents an abstraction of the actual environment, but is necessarily incomplete and hence presents an issue for system verification. If the actual environment matches the model, then the verification is correct; however, if the environment falls outside the abstraction captured by the model, then we cannot guarantee that the system is well-behaved. A solution to this problem consists in exploiting the model of the environment for statically verifying the system's behaviour and, if the verification succeeds, using it also for validating the model against the real environment via runtime verification. The paper reports on a demonstration of the feasibility of this approach using the Agent Java PathFinder model checker. Trace expressions are used to model the environment for both static formal verification and runtime verification.
The Interommatidial Bristle Variability of Diptera

Insects of the order ​Diptera​ are a popular biological model for understanding morphological trait evolution. One area of particular interest is the development of the compound eyes. While the development of ommatidia and photoreceptors has been thoroughly studied in this case, little attention has been paid to the interommatidial bristles (IOBs) present on the eyes of some dipteran families. A preliminary survey suggested that these bristles exhibit high variability among IOB families on multiple taxonomic levels and are not uniformly present or absent in any suborder of the ​Diptera​. To confirm this observation, I conducted a literature search to quantify how many dipteran families uniformly possessed IOBs, lack IOBs, or include species with both trait states. This effort revealed a slight bias towards lack of IOBs in the Diptera. Parsimony and maximum likelihood ancestral state reconstructions showed that IOBs are likely to have been present on the eyes of early dipteran​ ​ancestors, despite the bias towards lack of IOBs in the extant families. The absence of IOBs is therefore speculated to be the result of frequent evolutionary losses. Finally, the comparison with the 371 other previously studied traits suggests that IOBs have experienced the highest number of loss events among known fly traits
SmartPlot : Visualization Tool for Aircraft Probabilistic Damage Tolerance Analysis

SmartPlot is an application that reads and plots the files produced by SMART|DT (SMall Aircraft Risk Technology Damage Tolerance) probabilistic damage tolerance software. SmartPlot provides users with features such as selecting the data to be plotted, comparing results from multiple executions, and exporting plots as vector graphics in Portable Document Format. This application is based on a Finite State Machine (FSM) that automatically detects the characteristics of the file to be plotted. SmartPlot is written in Java, uses free software, and can be distributed as a Java ARchive (JAR) file that will run on any machine with Java Runtime Environment (JRE) 8.
Early Phonological Systematization in Children with Williams Syndrome: A Longitudinal Study

This longitudinal study looks at the systematic phonological development of children with Williams syndrome during the first three years of life. Williams syndrome is a genetic condition that impairs both cognitive and language abilities in those affected. It is commonly researched by linguists and speech pathologists alike because its phenotype provides a unique example of the interaction between cognitive impairment and language development. In this case study, four children’s first words were examined through the transcription of 30-minute-long play sessions to gain a better understanding of how children with Williams syndrome acquire phonological patterns. These transcripts were then analyzed using a customized battery of routines created and calculated in the Phon acoustic analysis software. It was found that some of these children did appear to be using patterned structures or ‘templates’ (Vihman, 2016) to produce their initial words. However, idiosyncrasies of language acquisition also were present in the data, as it was also found that not all participants appeared to be using defined templatic structures when vocalizing early word forms. By discussing how these children were or were not evidencing phonological systematization, these case studies can be added to the current literature to further understand not only how phonology is acquired, but how linguistic skills emerge in children with Williams syndrome.
On the Stylized Fact of the Firm Size Distribution

Due to truncated datasets and flawed statistical methods, the firm size distribution (FSD) does not yet have its undisputed stylized fact. Using comprehensive data on Belgian private firms, this paper proposes to estimate and test a new parametric distribution, called Generalized Pareto with cutoff (GPwC), and compare it to the commonly used Pareto and lognormal distributions. Our statistical test and graphical representations show that the GPwC is the best approximation of the entire Belgian FSD. This suggests that such a distribution is generated by a stochastic model that varies with firm size.