Miracle-dz/UniFAR-FTUs huggingface dataset:
The Study Of Dynamic Relationship Between Trading Volume, Return and Volatility

The dynamic relationship between trading volume, return and volatility of CNX Nifty Index Future in NSE.The result shows that the relationship between trading volume and return irrespetive of price change is positive and significant . Furthermore evidence is found rejecting an asymetric relationship between return and trading volume,which is consistence with the findings of (Karpoff,1987) who states the evidence from futures market , where cost of taking long and short position is same. Granger causality test demonstrates that returns cause volume. Also we find a positive relationship between trading volume and volatility by using GARCH(1,1) model . The inclusion of volume as a proxy for information arrival in the condtional variance function helps in explaining the GARCH effect in lagged form than its contemporous form. So in a contemporous form volume may be a poor proxy for market micro level analysis.
Combining Vector Space Embeddings with Symbolic Logical Inference over Open-Domain Text

We have recently shown how to combine random walk inference over knowledge bases with vector space representations of surface forms, improving performance on knowledge base inference. In this paper, we formalize the connection of our prior work to logical inference rules, giving some general observations about meth-ods for incorporating vector space representations into symbolic logic systems. Additionally, we present some promising prelim-inary work that extends these techniques to learning open-domain relations for the purpose of answering multiple choice questions, achieving 67% accuracy on a small test set.
Car sequencing with constraint-based ACO

Hybrid methods for solving combinatorial optimization problems have become increasingly popular recently. The present paper is concerned with hybrids of ant colony optimization and constraint programming which are typically useful for problems with hard constraints. However, the original algorithm suffered from large CPU time requirements. It was shown that such an integration can be made efficient via a further hybridization with beam search resulting in CP-Beam-ACO. The original work suggested this in the context of job scheduling. We show here that this algorithm type is also effective on another problem class, namely the car sequencing. We consider an optimization version, where we aim to optimize the utilization rates across the sequence. Car sequencing is a notoriously difficult problem, because it is difficult to obtain good bounds via relaxations. We show that stochastic sampling provides superior results to well known lower bounds for this problem when combined with CP-Beam-ACO.
How do skilled and less-skilled spellers write text messages? A longitudinal study

The link between students' spelling level and their text-messaging practice gives rise to numerous questions from teachers, parents and the media. A corpus of 4524 text messages produced in daily-life situations by students in sixth and seventh grade n=19, 11-12 years of age was compiled. None of the participants had ever owned or used a mobile phone before the start of the study; their text messages were collected monthly over the course of a year. The comparison between the group with mobile phones and the control group without mobile phones n=30 showed no difference between the level of traditional writing at the beginning of the text-message collection and during the collection. The results showed that the correlation between the level of traditional spelling and the density of textisms was dependent upon the type of textisms consistent/breaking with traditional code, the type of spelling usage-based/rule-based, the grades in French class and the duration of text-messaging practice. On the whole, students who were skilled or less skilled in traditional writing at the beginning of the text-message collection remained respectively skilled or less skilled throughout the year, despite their text-messaging use density and type of textisms. The discussion of this study's academic implications tends towards a complementarity between traditional writing and text messaging.
Droplet Detachment Mechanism in a High-Speed Gaseous Microflow

This paper experimentally investigates the mechanism of water droplet detachment in a confined microchannel under highly inertial (10 < Re < 200) air flow conditions. Experimental observations show that as the Reynolds number of the continuous phase is increased, the droplet transitions from an elongated slug to a nearly uniform aspect ratio droplet. Supporting scaling arguments are then made that examine the relevant forces induced by the continuous phase on the droplet at the point of detachment. The inertial, viscous, and hydrodynamic pressure forces that result as the air flow is confined in the small gap between droplet and channel walls are compared to the surface tension force pinning the droplet at the injection site. The results indicate that the dominant detachment mechanism transitions from the hydrostatic pressure difference to inertial drag as the continuous phase velocity is increased.
Endangered Species Research Endang Species Res Killing for Conservation: the Need for Alternatives to Lethal Sampling of Apex Predatory Sharks

INTRODUCTION Through growing public awareness of the threats facing wildlife and the widespread exposure of 'green' issues , the public, press, scientists, and politicians alike are 'jumping on the conservation bandwagon' and arguing for protection of many threatened species. There are numerous lines of evidence that top oceanic predators, especially large predatory sharks (hereafter TOPS sensu Jacques 2010), are experiencing varying degrees of population decline is mounting debate as to whether lethal sampling of TOPS is justified for obtaining scientific data. Recently, this controversial issue was objectively tackled by Heupel & Simpfendorfer (2010). In their paper, the authors concluded that with respect to sharks: …Although lethal sampling comes at a cost to a population, especially for threatened species, the conservation benefits from well-designed studies provide essential data that cannot be collected currently in any other way… (p. 1212) Life history data (diet, reproductive status, age and growth, mortality) are critical for developing effective conservation strategies for sharks, and Heupel & Simpfendorfer (2010) argued that lethal sampling presently remains the most effective and accurate means of gathering these data. To meet such challenges, many scientists have relied on fishery-derived specimens, but have needed to supplement those data with fishery-independent sampling (e.g. Piercy et al. 2010). In many terrestrial predators, marine mammals, and even some ABSTRACT: Top oceanic predators, especially large predatory sharks (TOPS), appear to be experiencing varying degrees of population declines. Life history data (e.g. diet, reproductive status, age and growth, mortality) are critical for developing effective conservation strategies for TOPS. Presently, lethal sampling remains the most effective and accurate means of gathering these data. To meet such challenges, many scientists have utilized specimens obtained from recreational and commercial fisheries, but have needed to supplement those data with fishery-independent sampling. However, there is growing public and scientific debate as to whether lethal sampling of TOPS is justified for obtaining conservation data. Here we describe the development and use of non-lethal alternatives for collecting data on (1) trophodynamics; (2) maturity state and fecundity; and (3) growth and mortality rates necessary to enact conservation measures for threatened or even data-deficient TOPS. fishes, accepted non-lethal alternatives exist for obtaining life history and demographic data; however, at present , comparable alternatives are not yet widely used to study TOPS. Ethical, political, and emotional issues aside, lethal sampling does provide a variety of valuable biological and ecological data that cannot be otherwise achieved (Heupel & …
To Misreport or not to report? The Case of the Italian Survey on Household Income and Wealth

The objective of the paper is to adjust for the bias due to unit nonresponse and measurement error in survey estimates of total household financial wealth. Sample surveys are a useful source of information on household wealth. Yet, survey estimates are affected by nonsampling errors. In particular, when it comes to household wealth, unit nonresponse and measurement error can severely bias the estimates. Using the Italian Survey on Household Income and Wealth, we exploit the available auxiliary information in order to assess the magnitude of such a bias. We find evidence that for this kind of surveys, nonsampling errors are a major issue to deal with, possibly more serious than sampling errors. Moreover, in the case of SHIW the potential bias due to measurement error seems to outweigh by far that induced by nonresponse.
Patients' representations of their end-stage renal disease: relation with mortality.

BACKGROUND Self-regulation theory explains how patients' illness perceptions influence self-management behaviour (e.g. via adherence to treatment). Following these assumptions, we explored whether illness perceptions of ESRD-patients are related to mortality rates. METHODS Illness perceptions of 182 patients participating in the NECOSAD-2 study in the period between December 2004 and June 2005 were assessed. Cox proportional hazard models were used to estimate whether subsequent all-cause mortality could be attributed to illness perception dimensions. RESULTS One-third of the participants had died at the end of the follow-up. Mortality rates were higher among patients who believed that their treatment was less effective in controlling their disease (perceived treatment control; RR = 0.71, P = 0.028). This effect remained stable after adjusting for sociodemographic and clinical variables (RR = 0.65, P = 0.015). CONCLUSIONS If we consider risk factors for mortality, we tend to rely on clinical parameters rather than on patients' representations of their illness. Nevertheless, results from the current exploration may suggest that addressing patients' personal beliefs regarding the effectiveness of treatment can provide a powerful tool for predicting and perhaps even enhancing survival.
Iterative Computation of FIR MIMO MMSE-DFE With Flexible Complexity-Performance Tradeoff

In recent years, single-carrier (SC) communication for intersymbol interference (ISI) channels has enjoyed a revived interest. Its principal advantage over the multi-carrier scheme is its lower peak-to-average power ratio (PAPR). In this paper, we propose a new fast iterative algorithm to obtain the optimal finite impulse response (FIR) minimum-mean-square-error decision feedback equalizer (MMSE-DFE) for multiple-input multiple-output (MIMO) SC communication systems over ISI channels based on the QR decomposition of an augmented Toeplitz channel matrix. The proposed algorithm is not only computationally efficient but also very frugal in its memory usage. The algorithm applies to MIMO systems with any number of transmitting and receiving antennas, either balanced or unbalanced. The iterative nature of the proposed algorithm enables a flexible choice of Nf, the length of the feedforward filter (FFF), which leads to a controllable trade-off between complexity and performance. A conversion from time-domain equalization (TDE) to a hybrid DFE (HDFE) can be used to achieve lower complexity when Nf becomes large. Complexity analysis suggests a significant improvement over the prior art of TDE.
Giffen Behavior: Theory and Evidence

This paper provides the first real-world evidence of Giffen behavior, i.e., upward sloping demand. Subsidizing the prices of dietary staples for extremely poor households in two provinces of China, we find strong evidence of Giffen behavior for rice in Hunan, and weaker evidence for wheat in Gansu. The data provide new insight into the consumption behavior of the poor, who act as though maximizing utility subject to subsistence concerns, with both demand and calorie elasticities depending significantly, and non-linearly, on the severity of their poverty. Understanding this heterogeneity is important for the effective design of welfare programs for the poor.
An Anomaly Detection Model Based on One-Class SVM to Detect Network Intrusions

Intrusion detection occupies a decision position in solving the network security problems. Support Vector Machines (SVMs) are one of the widely used intrusion detection techniques. However, the commonly used two-class SVM algorithms are facing difficulties of constructing the training dataset. That is because in many real application scenarios, normal connection records are easy to be obtained, but attack records are not so. We propose an anomaly detection model based on One-class SVM to detect network intrusions. The one-class SVM adopts only normal network connection records as the training dataset. But after being trained, it is able to recognize normal from various attacks. This just meets the requirements of the anomaly detection. Experimental results on KDDCUP99 dataset show that compared to Probabilistic Neural Network (PNN) and C-SVM, our anomaly detection model based on One-class SVM achieves higher detection rates and yields average better performance in terms of precision, recall and F-value.
Improved Recommendations Based on Trust Relationships in Social Networks

In order to alleviate the pressure of information overload and enhance consumer satisfaction, personalization recommendation has become increasingly popular in recent years. As a result, various approaches for recommendation have been proposed in the past few years. However, traditional recommendation methods are still troubled with typical issues such as cold start, sparsity, and low accuracy. To address these problems, this paper proposed an improved recommendation method based on trust relationships in social networks to improve the performance of recommendations. In particular, we define trust relationship afresh and consider several representative factors in the formalization of trust relationships. To verify the proposed approach comprehensively, this paper conducted experiments in three ways. The experimental results show that our proposed approach leads to a substantial increase in prediction accuracy and is very helpful in dealing with cold start and sparsity.
A survey of geocast routing protocols

Geocasting is the delivery of a message to nodes within a geographical region. With geocast, new services and applications are feasible, such as finding friends who are nearby, geographic advertising, and accident or wrong-way driver warning on a motorway. In this article we present a survey on geocast routing protocols. The protocols mainly differ in whether they are based on flooding, directed flooding, or on routing without flooding, and whether they are suitable for ad hoc networks or for infrastructure networks. Based on these criteria we propose a classification of geocast protocols. Our protocol comparison includes message and memory complexity, robustness, and the ability to deliver geocast packets in partially partitioned networks. Finally, we present simulations to compare the approaches based on flooding, directed flooding, and routing without flooding.
Scope of negation detection in sentiment analysis

An important part of information-gathering behaviour has always been to find out what other people think and whether they have favourable (positive) or unfavourable (negative) opinions about the subject. This survey studies the role of negation in an opinion-oriented information-seeking system. We investigate the problem of determining the polarity of sentiments in movie reviews when negation words, such as not and hardly occur in the sentences. We examine how different negation scopes (window sizes) affect the classification accuracy. We used term frequencies to evaluate the discrimination capacity of our system with different window sizes. The results show that there is no significant difference in classification accuracy when different window sizes have been applied. However, negation detection helped to identify more opinion or sentiment carrying expressions. We conclude that traditional negation detection methods are inadequate for the task of sentiment analysis in this domain and that progress is to be made by exploiting information about how opinions are expressed implicitly.
Secure and robust clustering for quantized target tracking in wireless sensor networks

We consider the problem of secure and robust clustering for quantized target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose a new method for jointly activating the best group of candidate sensors that participate in data aggregation, detecting the malicious sensors and estimating the target position. Firstly, we select the appropriate group in order to balance the energy dissipation and to provide the required data of the target in the WSN. This selection is also based on the transmission power between a sensor node and a cluster head. Secondly, we detect the malicious sensor nodes based on the information relevance of their measurements. Then, we estimate the target position using quantized variational filtering (QVF) algorithm. The selection of the candidate sensors group is based on multi-criteria function, which is computed by using the predicted target position provided by the QVF algorithm, while the malicious sensor nodes detection is based on Kullback-Leibler distance between the current target position distribution and the predicted sensor observation. The performance of the proposed method is validated by simulation results in target tracking for WSN.
Essays in liquidity

Derivatives markets can quickly become illiquid in periods of high uncertainty. Neither the source of this illiquidity nor its implications are well understood. First, this thesis shows that hedgers' trades have an adverse impact on the futures price creating effectively an endogenous transaction cost increasing in times of uncertainty and acting as the source of illiquidity in these markets. Second, illiquidity is shown to strengthen the wealth effect, which has been proven to be too weak empirically to explain the behavior of prices. The wealth effect is the mechanism through which changes in investors' wealth impact their attitude towards risk. As investors lose wealth, they become more risk averse and ask for a higher compensation to hold a risky asset thereby decreasing its price. Third, illiquidity is shown to potentially explain the shape of the implied volatility function not only as a function of moneyness but also of the options' volume or open interest. These results are derived from models, where producers maximize their expected utility derived from their profits. They seek to hedge the uncertain price at which they will sell their product in the future. They can use futures or put options to reduce this price risk but must pay speculators, defined as having no position in the underlying asset, a premium. This premium disappears normally as trades are assumed to be too small to matter and the risk of trading perfectly shared. Both of these assumptions are relaxed to derive the illiquidity transaction costs and its implications.
A novel SSIM index for image quality assessment using a new luminance adaptation effect model in pixel intensity domain

The Structural SIMilarity (SSIM) is one of the most prominent image quality assessment (IQA) methods due to its high prediction performance and wide applicability for image quality optimization problems. To reflect the luminance adaptation (LA) characteristic of human visual system (HVS), SSIM is modelled to have high consistency with Weber's law. However, it inevitably has some intrinsic faults that wrongly incorporate the LA effect into SSIM. In this paper, we firstly analyze that Weber's law in the conventional SSIM index cannot precisely reflect the LA effect due to two reasons: (i) it is reported that Weber's law model is not able to precisely be fitted in the measured experimental results for the LA effect; (ii) SSIM is calculated with pixel intensity values, but Weber's law is applied for luminance values which have non-linear relations with the pixel intensity values. To solve this problem, we first theoretically derive a new LA effect model in pixel intensity domain using a Gamma correction function and a power-law model. We then devise a weight function for the LA effect, called LA-based local weight function (LALF) which allows the proposed LA effect model to be precisely incorporated into SSIM index. To verify the effectiveness of the proposed LALF-based SSIM, we perform comprehensive experiments on four large IQA databases. Experimental results show that the proposed LALF helps performance improvement of the SSIM index.
Interpreting the transmissibility of the avian influenza A(H7N9) infection from 2013 to 2015 in Zhejiang Province, China

SUMMARY Three epidemic waves of human influenza A(H7N9) were documented in several different provinces in China between 2013 and 2015. With limited understanding of the potential for human-to-human transmission, it was difficult to implement control measures efficiently or to inform the public adequately about the application of interventions. In this study, the human-to-human transmission rate for the epidemics that occurred between 2013 and 2015 in Zhejiang Province, China, was analysed. The reproduction number (R), a key indicator of transmission intensity, was estimated by fitting the number of infections from poultry to humans and from humans to humans into a mathematical model. The posterior mean R for human-to-human transmission was estimated to be 0·27, with a 95% credible interval of 0·14–0·44 for the first wave, whereas the posterior mean Rs decreased to 0·15 in the second and third waves. Overall, these estimates indicate that a human H7N9 pandemic is unlikely to occur in Zhejiang. The reductions in the viral transmissibility and the number of poultry-transmitted infections after the first epidemic may be attributable to the various intervention measures taken, including changes in the extent of closures of live poultry markets.
Classical Supersymmetric Mechanics

Abstract We analyse a supersymmetric mechanical model derived from (1+1)-dimensional field theory with Yukawa interaction, assuming that all physical variables take their values in a Grassmann algebra B . Utilizing the symmetries of the model we demonstrate how for a certain class of potentials the equations of motion can be solved completely for any B . In a second approach we suppose that the Grassmann algebra is finitely generated, decompose the dynamical variables into real components, and devise a layer-by-layer strategy to solve the equations of motion for arbitrary potential. We examine the possible types of motion for both bosonic and fermionic quantities and show how symmetries relate the former to the latter in a geometrical way. In particular, we investigate oscillatory motion, applying results of Floquet theory, in order to elucidate the role that energy variations of the lower order quantities play in determining the quantities of higher order in B .