Miracle-dz/UniFAR-FTUs huggingface dataset:
ffi cient Classification with Conjunctive Features

This paper proposes a method that speeds up a classifier trained with many conjunctive features: combinations of (primitive) features. The key idea is to precompute as partial results the weights of primitive feature vectors that represent fundamental classification problems and appear frequently in the target task. A prefix tree (trie) compactly stores the primitive feature vectors with their weights, and it enables the classifier to find for a given feature vector its longest prefix feature vector whose weight has already been computed. Experimental results on base phrase chunking and dependency parsing demonstrated that our method speeded up the svm and llm classifiers by a factor of 1.8 to 10.6.
Optimisation of the detection sensitivity of plasmonic nanoantenna based sensors for mid-infrared spectroscopy

In this paper we report on the optimisation of the optical characteristics of 2D-arrays of plasmonic gold nanoantennas (NA) that can be used as high sensitivity mid-infrared spectroscopic sensor for the detection of chemical/biological substances by using the Surface Enhanced Infrared Absorption (SEIRA) technique. This approach allows to detect the presence of a substance adsorbed on the NA by measuring its optical absorption under the conditions for which the maximum of the reflectivity response of the 2D-array occurs at the same wavelength of the substance maximum absorption peak. In particular, by acting on the 2D-array periodicity, NA shape, size and thickness, numerical simulations of the 2D-array detection response, based on Finite Element Method (FEM), demonstrate that is possible to obtain an increase in the detection sensitivity of more than three orders of magnitude with respect to that one achievable if the same substance is deposited on an unstructured planar metal surface, independently from the wavelength at which the substance absorption occurs. Moreover, we present the results of an analysis of the dependence of the 2D-array maximum reflectivity and peak wavelength on the geometrical parameters characterising the NA and the 2D-array. © 2015 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of EUROSENSORS 2015.
The fundamental theorem of distributed storage systems revisited

The fundamental theorem of distributed storage systems characterizes the maximum file size that can be stored with certain assumptions on file retrieval and node repair. The result is composed of two parts, namely, the min-cut bound and that the bound can be achieved by linear network code with bounded field size. The derivation of the min-cut bound is reexamined and illuminated by making an implicit step explicit. Furthermore, a simple alternative proof for the achievability of the min-cut bound is presented, which is based on the construction of the generic storage code, a restricted form of generic network code. The proof techniques in this paper are expected to be extensible to other more complex models of distributed storage systems.
The computer simulation research on evolution of solidification microstructure

Phase-field method is the effective method to simulate microstructure as a kind of numerical computer simulation technology. On the basis of the free energy functional, the anisotropy is introduced into the phase-field model which applied to the solidification process, and the side-Branch competitive growth, ripen and solute micro-segregation in the free dendrite growth are realized. The simulation results show that the instability and morphology selection of dendrite are influenced by anisotropy strength. If the anisotropy coefficient is 0 or little, equiaxed dendrite will not bring. Under the same condition, the dendrite will grow faster with the increase of anisotropy coefficient. But if the anisotropy coefficient value (0.06) is over large, dendrite variation will appear, the simulation conclusion is consistent with theoretical predictions.
The Limits of Arbitrage and Stock Mispricing: Evidence from Decomposing the Market to Book Ratio

The purpose of this paper is to investigate the effect of the "limits of arbitrage" on securities mispricing. Specifically, I investigate the effect of the availability of substitutes and financial constraints on stock mispricing. In addition, this study investigates the difference in the limits of arbitrage, in the sense that it will lead to lower mispricing for these stocks, relative to non-S&P 500 stocks. I also examine if the lower mispricing can be attributed to their lower limits of arbitrage. Modern finance theory and efficient market hypothesis suggest that security prices, at equilibrium, should reflect their fundamental value. If the market price deviates from the intrinsic value, then a risk-free profit opportunity has emerged and arbitrageurs will eliminate mispricing and equilibrium is restored. This arbitrage process is characterized by large number of arbitrageurs which have infinite access to capital. However, a better description of reality is that there are few numbers of arbitrageurs to the extent that they are highly specialized; and they have limited access to capital. Under these condition arbitrage is no more a risk-free activity and can be limited by several factors such as arbitrage risk and transaction costs. Other factors that are discussed in the literature are availability of substitutes and financial constraints. The former arises as a result of the specialization of arbitrageurs in the market in which they operate, while the latter arises as a result of the separation between arbitrageurs and capital. In this dissertation, I develop a measure of the availability of substitutes that is based on the propensity scores obtained from propensity score matching technique. In addition, I use the absolute value of skewness of returns as a proxy of financial constraints. Previous studies used the limits of arbitrage framework to explain pricing puzzles such as the closed-end fund discounts. However, closed-end fund discounts are highly affected by uncertainty of managerial ability and agency problems. This study overcomes this problem by studying the effect of limits of arbitrage on publicly traded securities. The results show that there is a significant relationship between proxies of limits of arbitrage and firm specific mispricing. More importantly, empirical results indicate that stocks that have no close substitutes have higher mispricing. In addition, stocks that have high skewness show higher mispricing. Subsequent studies show that the S&P 500 stocks have different levels of liquidity, analysts’ coverage and volatility. These characteristics affect the ability of arbitrageurs to eliminate mispricing. Preliminary univariate tests show that S&P 500 stocks have, on average, lower mispricing and limits of arbitrage relative to non-S&P 500 stocks. In addition, the multivariate test shows that S&P 500 members have, on average, lower mispricing relative to non-S&P 500 stocks.
CLUSTERGEN: a statistical parametric synthesizer using trajectory modeling

Unit selection synthesis has shown itself to be capable of producing high quality natural sounding synthetic speech when constructed from large databases of well-recorded, well-labeled speech. However, the cost in time and expertise of building such voices is still too expensive and specialized to be able to build individual voices for everyone. The quality in unit selection synthesis is directly related to the quality and size of the database used. As we require our speech synthesizers to have more variation, style and emotion, for unit selection synthesis, much larger databases will be required. As an alternative, more recently we have started looking for parametric models for speech synthesis, that are still trained from databases of natural speech but are more robust to errors and allow for better modeling of variation. This paper presents the CLUSTERGEN synthesizer which is implemented within the Festival/FestVox voice building environment. As well as the basic technique, three methods of modeling dynamics in the signal are presented and compared: a simple point model, a basic trajectory model and a trajectory model with overlap and add. Index Terms: speech synthesis, statistical parametric synthesis, trajectory HMMs.
Report on the Design of Exchange-Traded Funds and Bond Funds – Implications for Fund Investors and Underlying Security Markets Under Stressful Conditions

“The subcommittee is charged with assessing the consequences of the increased presence of fixed income mutual funds and ETFs in these markets, including their current and possible future impacts on the liquidity and pricing of the underlying bonds under a variety of scenarios, as well as investor understanding of these products. Topics that may be considered include the interaction of fixed income prices and fund prices, including through the ETF arbitrage process, an assessment of the impact of redemptions from funds in stressed conditions, an assessment of the potential impact of the rebalancing process on underlying markets, whether funds help to diversify sources of fixed income liquidity, the role of index providers, and retail investor education. ”
POREI: patterns-oriented requirements elicitation integrated -- proposal of a metamodel patterns-oriented for integration of the requirement elicitation process

The requirements elicitation is essential to the success of software development projects. Many papers have been written that promulgate specific elicitation methods. However, none have yet modeled elicitation in a way that makes clear the critical role played by situational knowledge. This paper presents a unified model of the requirements elicitation process that emphasizes the applying the concepts of patterns as it transforms the current state of the business requirements and the situation to an improved understanding of the requirements and, potentially, a modified situation. One meta-model of requirements elicitation, selection of an appropriate elicitation technique, is also captured in the model. The values of this model are: (a) an improved understanding of elicitation helps analysts improve their elicitation efforts and (b) as we improve our ability to perform elicitation, we improve the likelihood that systems we create will meet their intended customers' needs. These patterns are elicited from coordination and transaction costs economics theories and they are validated through a wide variety of relevant situation.
The Air Traffic Flow Management Problem with Enroute Capacities

Massachusetts Institute of Technology, Cambridge, Massachusetts (Received August 1994; revision received October 1995; accepted May 1996) Throughout the United States and Europe, demand for airport use has been increasing rapidly, while airport capacity has been stagnating. Over the last ten years the number of passengers has increased by more than 50 percent and is expected to continue increasing at this rate. Acute congestion in many major airports has been the unfortunate result. For U.S. airlines, the expected yearly cost of the resulting delays is currently estimated at $3 billion. In order to put this number in perspective, the total reported losses of all U.S. airlines amounted to approximately $2 billion in 1991 and $2.5 billion in 1990. Furthermore, every day 700 to 1100 flights are delayed by 15 minutes or more. European airlines are in a similar plight. Optimally controlling the flow of aircraft either by adjusting their release times into the network (ground-holding) or their speed once they are airborne is a cost effective method to reduce the impact of congestion on the air traffic system. This paper makes the following contributions: (a) we build a model that takes into account the capacities of the National Airspace System (NAS) as well as the capacities at the airports, and we show that the resulting formulation is rather strong as some of the proposed inequalities are facet defining for the convex hull of solutions; (b) we address the complexity of the problem; (c) we extend that model to account for several variations of the basic problem, most notably, how to reroute flights and how to handle banks in the hub and spoke system; (d) we show that by relaxing some of our constraints we obtain a previously addressed problem and that the LP relaxation bound of our formulation is at least as strong when compared to all others proposed in the literature for this problem; and (e) we solve large scale, realistic size problems with several thousand flights.
Promoter hypermethylation in progesterone receptor-A ( PGR-A ) and PGR-B gene decreased its mRNA expression in ovarian endometriosis

The pathophysiology of endometriosis is not fully understood. It is believed that Progesterone Receptors (PGRs) play an important rule in the development of the disease. PGRs are expressed in human endometrial stromal. Reduction level of PGRs is related to the molecular basis of progesterone resistance in endometriosis. The aim of this study was to evaluate the association between methylation level of PGR-A and PGR-B gene and its mRNA expression in ovarian endometriosis. We used endometriotic tissues from 20 patients, aged 20-35 years, compared to endometrial tissues obtained from 20 normal women, age-matched to endometriosis group, who underwent micro-curettage to evaluate methylation status and mRNA expression of PGR-A and PGR-B gene. Methylation status of both PGRs was analyzed using MSP, and mRNA expression was investigated using qPCR. Methylation level of PGR-A (10,84%) and PGR-B (98,72%) in ovarian endometriosis were significantly different compared to control. The mRNA expression of PGR-A and PGR-B in ovarian endometriotic tissues significantly decreased by 2.35 and 6.37 folds compared to the normal endometrial tissues. Hypermethylation of PGR-B gene was correlated to mRNA expression, while methylation level of PGR-A had no correlation to mRNA expression. Promoter regions of PGR-A and -B genes in ovarian endometriosis are hypermethylated compared to controls. These hypermethylationmay reduce their expressions, hence might contribute to pathogenesis of endometriosis. Clinical article (J Int Dent Med Res 2019; 12(1):242-246 )
Symbolic models of networked control systems: A feedback refinement relation approach

Networked control systems (NCS) have attracted many researchers' attention in the past few years due to their flexibility and wide range of industrial applications. In this work, we address the controller synthesis problem for NCS with sophisticated closed-loop objectives, e.g. temporal logic requirements. Specifically, we consider controller synthesis schemes based on symbolic models, also known as finite abstractions. We present a methodology to construct symbolic models for NCS using a recently introduced notion of feedback refinement relations. The symbolic models for the NCS, which incorporate several network non-idealities, can be directly obtained from the symbolic model of the plant. The constructed symbolic models can be then leveraged to algorithmically synthesize controllers while enforcing complex specifications, e.g. those given by linear temporal logic (LTL) formulae. We illustrate the effectiveness of the proposed results by constructing symbolic models of several NCS using that of the plants within them.
Super Resolution in MRI : How far can we go ?

Super Resolution (SR) in MRI has been described as a techniqu e that allows an increase of resolution without a loss in the Signal to Noise Ratio (SNR), essentiall y providing “free” resolution. This study explores this claim and investigates the limits to SR in the presence of noi se. We show that the amplification of noise due to the SR algorithm can outweigh the signal benefit, leading to SNR r eductions that could counter the motivation for using the SR approach. Thresholds for successful SR approaches ar e determined through simulation, which are lower than used previously in the literature. We also assess the initia l resolving power of different slice profile shapes, without any further post-processing, and show that for rectangular slice profiles, it can be far higher than the slice width suggests. This finding has practical implications for struc tural MRI and could be used to provide “free” SNR.
A Review of Sequential Supervised Learning

Sequential supervised learning problems arise in many applications. After a definition of this learning task, we give out a set of evaluation criteria to the sequential supervised learning algorithms, some leading ones of which are described in this paper and evaluated based on the given criteria. In this paper, we show how these sequential supervised learning algorithms evolve from one to another based on the analysis of their limitations and advantages. We also try to give some intuitions to design novel sequential learning algorithms by showing how the existing ones are motivated by the corresponding traditional supervised learning algorithms. Some open problems in this area are discussed at the end.
Asynchronous Distributed Optimization Via Randomized Dual Proximal Gradient

In this paper we consider distributed optimization problems in which the cost function is separable, i.e., a sum of possibly non-smooth functions all sharing a common variable, and can be split into a strongly convex term and a convex one. The second term is typically used to encode constraints or to regularize the solution. We propose a class of distributed optimization algorithms based on proximal gradient methods applied to the dual problem. We show that, by choosing suitable primal variable copies, the dual problem is itself separable when written in terms of conjugate functions, and the dual variables can be stacked into non-overlapping blocks associated to the computing nodes. We first show that a weighted proximal gradient on the dual function leads to a synchronous distributed algorithm with local dual proximal gradient updates at each node. Then, as main paper contribution, we develop asynchronous versions of the algorithm in which the node updates are triggered by local timers without any global iteration counter. The algorithms are shown to be proper randomized block-coordinate proximal gradient updates on the dual function.
Effects of Droplet-Vitrification Cryopreservation Based on Physiological and Antioxidant Enzyme Activities of Brassidium Shooting Star Orchid

Protocorm-like bodies (PLBs) of Brassidium Shooting Star orchid were successfully cryopreserved using droplet-vitrification method. Vitrification based cryopreservation protocol is comprised of preculture, osmoprotection, cryoprotection, cooling, rewarming, and growth recovery and each and every step contributes to the achievement of successful cryopreservation. In order to reveal the lethal and nonlethal damage produced by cryopreservation, histological observation, scanning electron microscopy (SEM), and biochemical analysis were carried out in both cryopreserved and noncryopreserved PLBs of Brassidium Shooting Star orchid comparing with the control PLBs stock culture. Histological and scanning electron microscopy analyses displayed structural changes in cryopreserved PLBs due to the impact of cryoinjury during exposure to liquid nitrogen. Total soluble protein significantly increased throughout the dehydration process and the highest value was achieved when PLBs were stored in liquid nitrogen. Ascorbate peroxidase (APX) and catalase (CAT) showed the highest enzyme activities in both dehydration and cryostorage treatments indicating that stress level of PLBs was high during these stages.
Joint Allocation of Transmit Power Levels and Degrees of Freedom to Links in a Wireless Network

In this paper, we study a wireless network that has constant or slow-varying data rate requirements. The transmitters transmit to multiple receivers. The allocation of degrees of freedom (orthogonal codes, spectrum or time-slots) is based on a weight vector that is associated with each transmitter. The weight vector will specify how the degrees of freedom should be shared between the receivers associated with the transmitter. This model applies not only to the downlink of a cellular network, but also to more general wireless networks, including multi-hop networks. We devise two distributed algorithms in order to determine the minimal power allocation for the transmitters that will meet the data rate requirement between each transmitter-receiver pair. The main feature of our algorithms is that they can be executed at each transmitter independently with local information
Higher Neural Functions and Behavior Human frontoparietal cortex represents behaviorally relevant target status based on abstract object features X

Henderson M, Serences JT. Human frontoparietal cortex represents behaviorally relevant target status based on abstract object features. J Neurophysiol 121: 1410–1427, 2019. First published February 13, 2019; doi:10.1152/jn.00015. 2019. —Searching for items that are useful given current goals, or “target” recognition, requires observers to flexibly attend to certain object properties at the expense of others. This could involve focusing on the identity of an object while ignoring identity-preserving transformations such as changes in viewpoint or focusing on its current viewpoint while ignoring its identity. To effectively filter out variation due to the irrelevant dimension, performing either type of task is likely to require highlevel, abstract search templates. Past work has found target recognition signals in areas of ventral visual cortex and in subregions of parietal and frontal cortex. However, target status in these tasks is typically associated with the identity of an object, rather than identityorthogonal properties such as object viewpoint. In this study, we used a task that required subjects to identify novel object stimuli as targets according to either identity or viewpoint, each of which was not predictable from low-level properties such as shape. We performed functional MRI in human subjects of both sexes and measured the strength of target-match signals in areas of visual, parietal, and frontal cortex. Our multivariate analyses suggest that the multiple-demand (MD) network, including subregions of parietal and frontal cortex, encodes information about an object’s status as a target in the relevant dimension only, across changes in the irrelevant dimension. Furthermore, there was more target-related information in MD regions on correct compared with incorrect trials, suggesting a strong link between MD target signals and behavior.