Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic Games: A Tutorial

Game theory [1] is a formalism for the study of competitive interaction in the rich spectrum of relationships ranging between conflict and cooperation. Originally conceived as a mathematical foundation of economics, it proved its robustness by providing new techniques and insights in logic and set theory [15, 13], evolutionary and population biology [22], auction design and implementation, the design and study of the internet [19], analysis of cold war strategies, etc. Dynamic games are used to model competitive processes evolving over time. Stochastic transitions are used for abstraction in modelling or to formalize inherent uncertainty, leading to quantitative statistical analysis. Stochastic games are dynamic games with stochastic transitions. They enjoy rich and mature mathematical theory [11, 23] and a wide range of applications including economics, cell, population and evolutionary biology [26], queueing theory and performance evaluation, and quantitative temporal model checking [17, 8]. In this tutorial we explore the spectrum of competitive dynamic behavioural models ranging from Markov chains, to transition systems, to Markov decision processes [20], to 2-player and multi-player perfect-information and general stochastic games [11]. We also consider the spectrum of qualitative and quantitative objectives for the players contained in the class of Borel-measurable functions [16], and we survey most popular concrete choices: discounted and limiting-average objectives [20, 11] used in economics and performance evaluation, and omega-regular objectives [13] encompassing safety, liveness and fairness objectives used in temporal logic model checking. We present the general determinacy result for zero-sum stochastic games with Borel-measurable objectives due to Martin [16], as well as its many refinements for stochastic games with discounted, limiting-average, and omega-regular objectives [11, 6, 9, 17, 4, 28]. Then we survey algorithmic techniques for solving various classes of stochastic games and Markov decision processes, including value iteration and strategy improvement [20, 7], convex optimization [7, 27, 2] and graph-theoretic algorithms [3]. Special attention is given to algorithmic solutions of (perfect-information) omega-regular stochastic games [14, 3, 4] laying the foundation for automated quantitative temporal model checking. We also consider non-zero sum stochastic games. After defining the fundamental notion of a Nash equilibrium we survey recent results [24, 21, 5] on its existence in various classes of stochastic games as well as a few challenging open problems in the area. Then we present the quantitative mu-calculus [10, 17, 8] which is a very expressive, robust, and yet algorithmically feasible logical formalism for specification and automated quantitative analysis. We argue that the quantitative
Profiling Family Communication Standards

The current research undertook a U.S.-Japan cross-cultural comparison to explore the underlying structure of family communication standards (FCS), or beliefs about the “ideal” ways of family interactions. The main study (U.S. n = 311, Japanese n = 192), utilizing latent profile analysis, revealed that (a) there are three “FCS profiles” (laissezfaire, high-context, and open-affectionate), each of which represents distinct FCS endorsement patterns; (b) individuals with different FCS profiles have different levels of subjective well-being and family satisfaction, and moreover, such profile-level dynamics operate independently of the effects of individual FCS dimensions; and (c) FCS profile endorsement is undergirded by individualism-collectivism and horizontal-vertical orientation. A follow-up study found that FCS profiles entail unique family conflict strategies. These findings are discussed in terms of the hierarchical structure of human cognition and impact of standards on psychological, relational, and communicative phenomena. Limitations and future directions for the research on FCS are also discussed.
International Journal of Computer Science and Mobile Computing Active Appearance Model and Pca Based Face Recognition System

At present face recognition has wide area of applications such as security, law enforcement. Imaging conditions, Orientation, Pose and presence of occlusion are huge problems associated with face recognition. The performance of face recognition systems decreases due to these problems. Discriminant Analysis (LDA) or Principal Components Analysis (PCA) is used to get better recognition results. Human face contains relevant information that can extracted from face model developed by PCA technique. Principal Components Analysis method uses eigenface approach to describe face image variation. A face recognition technique that is robust to all situations is not available. Some techniques are better in case of illumination, some for pose problem and some for occlusion problem. This paper presents some algorithms for face recognition. We discuss how greater accuracy can be achieved by extracting features from the boundaries of the faces by using Active Shape Models and, the skin textures, using Active Appearance Models, originally proposed by Cootes and Talyor.
Differential heating/cooling chip joining method to prevent chip package interaction issue in large die with ultra low-k technology

A differential heating/cooling chip join method was developed for Pb-free flip chip packaging of ultra low-k (ULK) technology Si chips on organic substrates to prevent Chip-Package Interaction (CPI) - related damage upon chip joining. A chip was mounted to a bonder head and a substrate was located on a base plate and they were held at different elevated temperatures during the bonding process. The temperature difference between the Si chip and the organic substrate during assembly provides a substantially matched thermal expansion and minimizes stress induced by coefficient of thermal expansion (CTE) mismatch. From the modeling study, it was confirmed that chip warpage, Controlled Collapse Chip Connection (C4) stresses/strains, and ULK stresses decreased significantly by differential heating/cooling chip join method, with further improvement noted as the substrate temperature was decreased during the bonding process. X-ray, scanning electron microscope (SEM) and C-mode scanning acoustic microscope (C-SAM) were used to examine the defects after flip chip assembly. Noncontact white light reflectometry was also used to measure the warpage shape of the assembled silicon chip and the organic substrate. Observation under C-SAM indicated that fractures in the ULK layers were dramatically reduced by the differential heating/cooling chip joining process compared to the conventional reflow process. Non-destructive X-ray images indicated there were no solder bridging in any area of the chip interconnects. The experimental results showed that the differential heating/cooling chip join process can effectively reduce fractures in the ULK layers and prevent C4 bump bridging in a large die package with low-K dielectric constant device integration and high Ag content solder bumps.
A safe and robust path following planner for wheeled robots

This paper addresses the problem of planning a path following, robust with respect to small localization errors, allowing a mobile robot to reach safely its goal. A path planning method dealing with uncertainties is proposed where both uncertainty in localization and in control of a nonholonomic mobile robot are managed. The safeness of this method is due to the combination of the planning phase and the navigation phase by using the same localization and control processes. The localization process realized the multisensor fusion of data provided by a ring of telemetric sensors in combination with a dead-reckoning system. The robustness is due to a stabilizing controller on which the system remains stable when estimated values are used for feedback instead of exact ones. By determining a compact attractive domain bounding the regulation error, we dynamically compute a security margin during the path planning. This security margin ensures the safeness of the planned path.
Graph Branch Algorithm: An Optimum Tree Search Method for Scored Dependency Graph with Arc Co-Occurrence Constraints

Preference Dependency Grammar (PDG) is a framework for the morphological, syntactic and semantic analysis of natural language sentences.PDG gives packed shared data structures for encompassing the various ambiguities in each levels of sentence analysis with preference scores and a method for calculating the most plausible interpretation of a sentence.This paper proposes the Graph Branch Algorithm for computing the optimum dependency tree (the most plausible interpretation of a sentence) from a scored dependency forest which is a packed shared data structure encompassing all possible dependency trees (interpretations) of a sentence.The graph branch algorithm adopts the branch and bound principle for managing arbitrary arc co-occurrence constraints including the single valence occupation constraint which is a basic semantic constraint in PDG.This paper also reports the experiment using English texts showing the computational complexity and behavior of the graph branch algorithm.
Temperature Dependence of Macroscopic L‐Type Calcium Channel Currents in Single Guinea Pig Ventricular Myocytes

Calcium Channels and Temperature. Introduction: Lowering temperature greatly reduces calcium influx through calcium channels. Studies on a number of tissues demonstrate that the peak inward current, ICa exhibits Q10 values ranging from 1.8 to 3.5; however, it remains unclear which component(s) of calcium channel gating may give rise to this large temperature sensitivity. Components of gating that may affect channel availability include phosphorylation and changes in [Ca2+)i, processes that vary in pertinence depending on the channel examined. This study addresses this problem by examining the temperature sensitivity (from 34° to 14°C) of cardiac ICa under control conditions, during attenuation or activation of protein kinase A (PKA) activity, and when intracellular [Ca2+] has been elevated.
Transcription Factor Bcl11b Controls Effector and Memory CD8 T cell Fate Decision and Function during Poxvirus Infection

CD8+ T cells play an important role in host resistance to many viral infections, but the underlying transcriptional mechanisms governing their differentiation and functionality remain poorly defined. By using a highly virulent systemic and respiratory poxvirus infection in mice, we show that the transcription factor Bcl11b provides a dual trigger that sustains the clonal expansion of virus-specific effector CD8+ T cells, while simultaneously suppressing the expression of surface markers associated with short-lived effector cell (SLEC) differentiation. Additionally, we demonstrate that Bcl11b supports the acquisition of memory precursor effector cell (MPEC) phenotype and, thus, its absence causes near complete loss of lymphoid and lung-resident memory cells. Interestingly, despite having normal levels of T-bet and Eomesodermin, Bcl11b-deficient CD8+ T cells failed to execute effector differentiation needed for anti-viral cytokine production and degranulation, suggesting a non-redundant role of Bcl11b in regulation of this program. Thus, Bcl11b is a critical player in fate decision of SLECs and MPECs, as well as effector function and memory formation.
DIY Bertin Matrix

In this paper, we relate the iterative fabrication of a physical Bertin Matrix. Jacques Bertin designed and refined such devices over 10 years (1970–1980) and five iterations of what he called Dominos 1–5. For the purpose of an exhibit dedicated to Bertin's work during VIS 2014 in Paris, we designed an improved version of such device by leveraging modern fabrication possibilities and in particular a laser cutter. We describe the process, iterations and improvements of our matrix, and report lessons we learnt.
A virtual environment and model of the eye for surgical simulation

An anatomically detailed 3-D computer graphic model of the eye and surrounding face within a virtual environment has been implemented for use in a surgical simulator. The simulator forms part of a teleoperated micro-surgical robotic system being developed for eye surgery. The model has been designed to both visually and mechanically simulate features of the human eye by coupling computer graphic realism with finite element analysis. The paper gives an overview of the system with emphasis on the graphical modelling techniques and a computationally efficient framework for representing anatomical details of the eye and for finite element analysis of the mechanical properties. Examples of realistic images coupled to large deformation finite element model of the cornea are presented. These images can be rendered sufficiently fast for the virtual reality application.
Type Classification of Semi-Structured Documents

Semi-structured documents (e.g. journal art,icles, electronic mail, television programs, mail order catalogs, . .) a.re often not explicitly typed; the only available t,ype information is the implicit structure. An explicit t,ype, however, is needed in order to a.pply objectoriented technology, like type-specific methods. In this paper, we present a.n experimental vector space cla.ssifier for determining the type of semi-structured documents. Our goal was to design a. high-performa.nce classifier in t,erms of accuracy (recall and precision), speed, and extensibility.
Angiotensin-converting enzyme (ACE) I/D genotype and renal ACE gene expression.

BACKGROUND The angiotensin-converting enzyme (ACE) I/D genotype affects serum ACE levels and the onset and progression of renal disease, but little is known about the mechanism. We investigated a possible association between the ACE I/D genotype and renal ACE mRNA levels in healthy subjects. METHODS Renal biopsy samples were obtained from 50 healthy kidney donors. The ACE I/D genotype was determined by polymerase chain reaction (PCR). Renal ACE mRNA quantification was performed by competitive RNA-PCR. In situ hybridization (ISH) for ACE mRNA on renal biopsy specimens was also performed. RESULTS The number of ACE transcripts in 100 ng of total RNA was significantly (P < 0.01) lower in subjects with II genotype (5.6 +/- 5.3 x 10(5), N = 20) compared with those with the ID (17.9 +/- 13.6 x 10(5), N = 23) or the DD genotype (36.9 +/- 14.6 x 10(5), N = 7) in healthy donors. The ISH studies showed that both tubular and glomerular ACE mRNA expressions were weak in subjects with the II genotype, intermediate in subjects with ID genotype, and strong in subjects with DD genotype. CONCLUSIONS It is suggested that renal ACE gene expression is associated with the ACE I/D genotype in healthy Japanese subjects.
Travel delay in a large wireless ad hoc network

An analysis based on Brownian Motion, including the effect of packet losses, packet retransmission and the over-head delay incurred after each time-out, is used to derive closed form expressions for the average travel time of a packet from its source to a fixed destination. An iterative algorithm is proposed to compute the time it takes for a packet to reach a moving destination node. The value of the optimum time-out interval that minimises average travel time is illustrated with numerical examples.
Bell theorem without inequalities for two spinless particles.

We use the Greenberger-Horne-Zeilinger [in Bell's Theorem, Quantum Theory, and Conceptions of the Universe, edited by M. Kafatos (Kluwer Academic, Dordrecht, 1989)] approach to present three demonstrations of the failure of Einstein-Podolsky-Rosen (EPR) [Phys. Rev. 47, 777 (1935)] local realism for the case of two spinless particles in a two-particle interferometer. The original EPR assumptions of locality and reality do not suffice for this. First, we use the EPR assumptions of locality and reality to establish that in a two-particle interferometer, the path taken by each particle is an element of reality
A MoLC＋MoM-based G0 distribution parameter estimation method with application to synthetic aperture radar target detection

The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.
Statistical and Semantic Features to Measure Sentence Similarity in Portuguese

A sentence similarity measure is an important field for different applications of text mining. In recent literature, it is possible to find several similarity measures between sentences in English; however, it lacks measures for Portuguese. In addition, one of the main issues to assess sentence similarity is to identify word meaning. In this context, this work aims to present a new approach to measure the similarity between sentences written in Portuguese using statistical and deep learning features to overcome the meaning problems. The results showed that our method obtained better results when compared to the measures proposed in ASSIN 2016 competition.
(–)-(1R,2R)-3-(3-Dimethylamino-1-ethyl-2-methyl-propyl)-phenol Hydrochloride (Tapentadol HCl): a Novel μ-Opioid Receptor Agonist/Norepinephrine Reuptake Inhibitor with Broad-Spectrum Analgesic Properties

(–)-(1R,2R)-3-(3-Dimethylamino-1-ethyl-2-methyl-propyl)-phenol hydrochloride (tapentadol HCl) is a novel μ-opioid receptor (MOR) agonist (Ki = 0.1 μM; relative efficacy compared with morphine 88% in a [35S]guanosine 5′-3-O-(thio)triphosphate binding assay) and NE reuptake inhibitor (Ki = 0.5 μM for synaptosomal reuptake inhibition). In vivo intracerebral microdialysis showed that tapentadol, in contrast to morphine, produces large increases in extracellular levels of NE (+450% at 10 mg/kg i.p.). Tapentadol exhibited analgesic effects in a wide range of animal models of acute and chronic pain [hot plate, tail-flick, writhing, Randall-Selitto, mustard oil colitis, chronic constriction injury (CCI), and spinal nerve ligation (SNL)], with ED50 values ranging from 8.2 to 13 mg/kg after i.p. administration in rats. Despite a 50-fold lower binding affinity to MOR, the analgesic potency of tapentadol was only two to three times lower than that of morphine, suggesting that the dual mode of action of tapentadol may result in an opiate-sparing effect. A role of NE in the analgesic efficacy of tapentadol was directly demonstrated in the SNL model, where the analgesic effect of tapentadol was strongly reduced by the α2-adrenoceptor antagonist yohimbine but only moderately attenuated by the MOR antagonist naloxone, whereas the opposite was seen for morphine. Tolerance development to the analgesic effect of tapentadol in the CCI model was twice as slow as that of morphine. It is suggested that the broad analgesic profile of tapentadol and its relative resistance to tolerance development may be due to a dual mode of action consisting of both MOR activation and NE reuptake inhibition.
First-Take-All: Temporal Order-Preserving Hashing for 3D Action Videos

With the prevalence of the commodity depth cameras, the new paradigm of user interfaces based on 3D motion capturing and recognition have dramatically changed the way of interactions between human and computers. Human action recognition, as one of the key components in these devices, plays an important role to guarantee the quality of user experience. Although the model-driven methods have achieved huge success, they cannot provide a scalable solution for efficiently storing, retrieving and recognizing actions in the large-scale applications. These models are also vulnerable to the temporal translation and warping, as well as the variations in motion scales and execution rates. To address these challenges, we propose to treat the 3D human action recognition as a video-level hashing problem and propose a novel First-Take-All (FTA) Hashing algorithm capable of hashing the entire video into hash codes of fixed length. We demonstrate that this FTA algorithm produces a compact representation of the video invariant to the above mentioned variations, through which action recognition can be solved by an efficient nearest neighbor search by the Hamming distance between the FTA hash codes. Experiments on the public 3D human action datasets shows that the FTA algorithm can reach a recognition accuracy higher than 80%, with about 15 bits per frame considering there are 65 frames per video over the datasets.
Effective Delay Control in Online Network Coding

Motivated by streaming applications with stringent delay constraints, we consider the design of online network coding algorithms with timely delivery guarantees. Assuming that the sender is providing the same data to multiple receivers over independent packet erasure channels, we focus on the case of perfect feedback and heterogeneous erasure probabilities. Based on a general analytical framework for evaluating the decoding delay, we show that existing ARQ schemes fail to ensure that receivers with weak channels are able to recover from packet losses within reasonable time. To overcome this problem, we re-define the encoding rules in order to break the chains of linear combinations that cannot be decoded after one of the packets is lost. Our results show that sending uncoded packets at key times ensures that all the receivers are able to meet specific delay requirements with very high probability.
Tachycardia and convulsions induced by accidental intravascular ropivacaine injection during sciatic block

Ropivacaine, a recently introduced local anesthetic of the amide family ( 1 ), seems to show less toxicity than bupivacaine (2–4 ). Nevertheless, both neurologic and cardiovascular toxicities are possible. Six cases of ropivacaine‐induced convulsions have previously been reported (5–10 ), of which three cases also showed cardiovascular toxicity. In three cases, total plasma concentrations were measured ( Table 1 ).
The High-Velocity Outflow of PG 1211+143 May Not Be That Fast

We analyze the X-ray spectrum of the quasar PG 1211+143 observed with the CCD and grating spectrometers on board XMM-Newton. Using an ion-by-ion fitting model, we find an outflow component of about 3000 km s-1, which includes absorption lines of K and L shell ions of the astrophysically abundant elements. We also identify and include in our model broad (FWHM = 6000 km s-1) emission lines from H-like ions of C, N, O, and Ne, and He-like ions of O, Ne, and Mg. The outflow velocity we find is an alternative interpretation of the data and is in contrast with the ultra high velocity of ~24,000 km s-1 reported previously for this object. Nevertheless, we cannot completely rule out the presence of a high-velocity component due to the poor signal-to-noise ratio of the data.