Miracle-dz/UniFAR-FTUs huggingface dataset:
Author ' s personal copy Cautious cannibals : Behavioral responses of juvenile and adult blue crabs to the odor of injured conspeci fi cs

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t a r t i c l e i n f o Blue crabs are cannibalistic, and therefore the scent of injured conspecifics represents both a potential food cue, as well as an indicator of predation risk. We examined the response of blue crabs to conspecific odor alone, as well as in mixtures of attractive cues to determine how animals evaluate and respond to this odor. We explicitly manipulated risk-sensitivity based on either animal size (an indicator of susceptibility to predation) or hunger state (susceptibility to starvation) as ways to evaluate theories of risk-allocation, which suggest that decreases in predation risk, or increases in the risk of starvation, ought to result in diminished responses to sensory cues that signal predator presence or activity. Large and small blue crabs were challenged to locate the source of odor plumes consisting of the scent of injured conspecifics (risk cue), attractive food odors (attractive cue), or their mixture (conflicting cue). Neither large nor small blue crabs tracked aversive cues, but large blue crabs consistently tracked conflicting treatments to their source. Responses to conflicting and aversive treatments also involved diminished movement and reduced tracking speed relative to behaviors displayed in attractive plumes. Thus, even cannibalistic crabs seem to respond more prevalently to the apparent predation risk then to food reward, and risk-sensitive behaviors have a likely cost in terms of reduced food intake. Starved animals were more likely than unstarved animals to track conflicting plumes. Both the ontogenic shift and the response of starved animals support the notion that the cost of risk-aversive behaviors results in this strategy being allocated in proportion to the degree of potential risk. Since risk-aversive responses to chemical cues can produce strong effects in communities, the size-dependent nature of these responses in blue crabs may introduce considerable complexity in interactions between blue crabs, their predators, and their prey.
PAPR reduction for improving performance of OFDM system

Orthogonal frequency division multiplexing (OFDM) signals have a generic problem of high peak to average power ratio (PAPR) which is defined as the ratio of the peak power to the average power of the OFDM signal. The drawback of the high PAPR is that the dynamic range of the power amplifiers (PA) & digital-to-analog (D/A) converters required during the transmission and reception of the signal is higher. As a result, the total cost of the transceiver increases, with reduced efficiency. This paper includes an idea of the PAPR constraint, along with the implementation and analysis of some specific algorithms for PAPR reduction of the OFDM signals. All the PAPR reduction algorithms are implemented and tested in the OFDM transceiver designed using Matlab. Analyzing some specific algorithms, we propose a novel algorithm by combining the subcarrier phase adjustment and linear combination of the time domain OFDM signals. Simulation results for a OFDM system employing Quadrature Amplitude Shift Keying (QASK) symbols and Quadrature Amplitude Modulation (QAM) can achieve a PAPR reduction of 5 dB.
Fundamental Performance Limits for PLC Systems Impaired by Impulse Noise

In this paper, we provide insights on the ultimate performance limits, in terms of achievable information rate, for power line communication (PLC) systems impaired by impulse noise. In particular, we analyze single carrier (SC) and multiple carrier (MC) transmission systems employing quadrature amplitude modulation (QAM) formats. In order to compute the information rates of standard MC systems, we introduce a theoretically equivalent channel model which allows the exact computation of the information rate. This simplified channel model will be referred to as interleaved MC channel model. We show that the use of MC schemes leads to an unavoidable loss with respect to SC schemes. In order to validate our theoretical results, we analyze the bit error rate (BER) performance of SC and MC schemes through Monte Carlo simulations. Several trellis-coded modulation (TCM) and low-density parity-check (LDPC)-coded schemes are considered
Variable Effects of Climate on Forest Growth in Relation to Ecosystem State

Tree growth rings are applied in forest ecology to understand the relationship between climate and forest growth. To this end, individual trees considered sensitive to climate are sampled and the average effects of climate over a sample period are estimated. Forests are dynamic systems, the structure, composition, and health of which evolve over time. The relationship between climate and growth is likely to change in relation to fundamental shifts in a forest ecosystem. Identifying and understanding changes in the growth-climate relationship requires data from entire forests and models that estimate the effects of climate on forest growth as a function of ecosystem state. We develop a Bayesian hierarchical model that: allows the effects of climate to vary temporally using a state space framework; allows for error propagation across growth ring standardization steps; and, applies climate data at an appropriate spatial scale. The model is applied to tree ring data from northeastern Minnesota. Important climate variables are identified using Bayesian variable selection. Results indicate forest growth is most sensitive to the interactive effects of temperature and precipitation represented through water balance metrics. We observe changes in forest growth response to water balance variables over time with periods of increased sensitivity to water availability. Periods of increased sensitivity correspond to droughts and forest tent caterpillar outbreak years in which the structure and function of study forests change. Variation in the response of tree growth due to climatic extremes or disturbance events are not observable applying conventional dendrochronology models that estimate the average effects of climate on tree growth over time. Our results are one example of additional inferences made possible by using a Bayesian state space approach to model tree growth as a function of climate.
How does Europeanization affect CEE governance? Conditionality, diffusion and diversity

The EU influences the development of governance in central and eastern Europe through its accession process in ways that go well beyond its official competences in the current member states. However, the EU's impact is diffused by the complexity of actor constellations involved. Moreover, it lacks the comprehensive institutional templates that would be needed to shape political institutions into an identifiably 'EU' mould. Instead, EU influence interacts with other pressures, both external and internal, becoming woven into domestic debates about institutional change. Accession conditions and negotiations privilege a relatively small group of central government officials over other political actors. The lack of involvement of parliamentarians and wider society in the accession process could, in turn, exacerbate the EU's own democratic deficit after enlargement.
Lip Analysis for Person recognition

The human face is an attractive biometric identifier and face recognition has certainly improved a lot since its beginnings some three decades ago, but still its application in real world has achieved limited success. In this doctoral dissertation we focus on a local feature of the human face namely the lip and analyse it for its relevance and influence on person recognition. In depth study is carried out with respect to various steps involved, such as detection, evaluation, normalization and the applications of the human lip motion. Initially we present a lip detection algorithm that is based on the fusion of two independent methods. The first method is based on edge detection and the second one on region segmentation, each having distinct characteristics and thus exhibit different strengths and weaknesses. We exploit these strengths by combining the two methods using fusion. Then we present results from extensive testing and evaluation of the detection algorithm on a realistic database. Next we give a comparison of the visual features of lip motion for their relevance to person recognition. For this purpose we extract various geometric and appearance based lip features and compare them using three feature selection measures; Minimal- Redundancy-Maximum-Relevance, Bhattacharya Distance and Mutual Information. Next we extract features which model the behavioural aspect of lip motion during speech and exploit them for person recognition. The behavioural features include static features, such as the normalized length of major/minor axis, coordinates of lip extrema points and dynamic features based on optical flow. These features are used to build client model by Gaussian Mixture Model (GMM) and finally the classification is achieved using a Bayesian decision rule. Recognition results are then presented on a text independent database specifically designed for testing behavioural features that require comparatively more data. Lastly we propose a temporal normalization method to compensate for variation caused by lip motion during speech. Given a group of videos for a person uttering the same sentence multiple times we study the lip motion in one of the videos and select certain key frames as synchronization frames. We then synchronize these frames from the first video with the remaining videos of the same person. Finally all the videos are normalized temporally by interpolation using lip morphing. For evaluation of our normalization algorithm we have devised a spatio-temporal person recognition algorithm that compares normalized and un-normalized videos.
Enumerating with constant delay the answers to a query

We survey recent results about enumerating with constant delay the answers to a query over a database. More precisely, we focus on the case when enumeration can be achieved with a preprocessing running in time linear in the size of the database, followed by an enumeration process outputting the answers one by one with constant time between any consecutive outputs. We survey classes of databases and classes of queries for which this is possible. We also mention related problems such as computing the number of answers or sampling the set of answers.
A survey on real time bidding advertising

Real-time bidding (RTB) is an emerging and promising business model for online computational advertising in the age of big data. Based on analysis of massive amounts of Cookie data generated by Internet users, RTB advertising has the potential of identifying in real-time the characteristic and interest of the target audience in each ad impression, automatically delivering best-matched ads, and optimizing their prices via auction-based programmatic buying scheme. RTB has significantly changed online advertising, evolving from the traditional pattern of “media buying” and “ad-slot buying” to “target-audience buying”, and is expected to be the standard business model for online advertising in the future. In this paper, we discussed the current market practice of RTB advertising, presented the key roles and typical business processes in RTB markets, and summarized the current research progresses in the existing literature. The aim of this paper is to provide useful reference and guidance for future works.
A Novel Method of Mutation Clustering Based on Domain Analysis

Mutation testing is an effective but operational expensive technique. There exists much improvement to help mutation testing become a wide-used testing technique. The main objective is to reduce the number of mutants and test cases to be executed. The simplified mutant set can still approximate the adequacy. Many new techniques are put forward continuously. One of them is called mutation clustering. It integrates data clustering and mutation analysis, such that both mutant set and test set can be reduced dramatically. This paper revisions the extant mutation clustering. The goal is to provide a method which can guide clustering mutants statically before test case generation. And then the simplified mutant set is used to generate a test set. We hypothesize that such a test set can kill the original mutant set approximately. The cost of mutation testing will further decreases, because only a small test set needs to be generated and executed. A case study shows the encouraging result to support our hypothesis.
Development of a Pipeline Monitoring System by Bio-mimetic Robots

To explore pipelines is one of various bio-mimetic robot applications. The robot may work in common buildings such as between ceilings and ducts, in addition to complicated and massive pipeline systems of large industrial plants. The bio-mimetic robot finds any troubled area or malfunction and then reports its data. Importantly, it can not only prepare for but also react to any abnormal routes in the pipeline. The pipeline monitoring tasks require special types of mobile robots. For an effective movement along a pipeline, the movement of the robot will be similar to that of insects or crawling animals. During its movement along the pipelines, a pipeline monitoring robot has an important task of finding the shapes of the approaching path on the pipes. In this paper we propose an effective solution to the pipeline pattern recognition, based on the fuzzy classification rules for the measured IR distance data. Keywords—Bio-mimetic robots, Plant pipes monitoring, Pipe pattern recognition.
Zur Verwendung von Regressionsmodellen im Rahmen von finanzwirtschaftlichen Ereignisstudien [On application of regression models in event studies on financial markets]

In this paper an event study is conducted to detect price reactions on dividend announcements using data from the Austrian stock market. We use the Market Model and the Market Model with Dummies to describe the return generating process. To identify the significance of abnormal returns we apply parametric as well as non-parametric tests (modified rang test and bootstrap). Announced dividend increases induce stock prices to rise, whereas dividend decreases lead to shrinking prices.
Price-based quality-of-service control framework for two-class network services

This paper presents a price-based quality-of-service (QoS) control framework for two-class network services, in which circuit-switched and packet-switched services are defined as "premium service class" and "best-effort service class," respectively. Given the service model, a customer may decide to use the other class as a perfect or an imperfect substitute when he or she perceives the higher utility of the class. Given the framework, fixed-point problems are solved numerically to investigate how static pricing can be used to control the demand and the QoS of each class. The rationale behind this is as follows: For a network service provider to determine the optimal prices that maximize its total revenue, the interactions between the QoS-dependent demand and the demand-dependent QoS should be thoroughly analyzed. To test the robustness of the proposed model, simulations were performed with gradually increasing customer demands or network workloads. The simulation results show that even with substantial demands or workloads, self-adjustment mechanism of the model works and it is feasible to obtain fixed points in equilibrium. This paper also presents a numerical example of guaranteeing the QoS statistically in the short term-that is, through the implementation of pricing strategies.
The Shattered Document approach to adaptive hypertext. Design and evaluation

We address the problem of improving, automatically, the usability of a large online document. We propose an adaptive hypertext approach, based on splitting the document into components smaller than the page or screen, called noogramicles, and creating each page as a new assemblage of noogramicles each time it is accessed. The adaptation comes from learning the navigation patterns of the usors authors and readers, and is manifested in the assemblage of pages. We test this model across a number of configurations, including chance and non-adaptive systems. We evaluate our model through simulation. We have designed a simulator based on established findings about the behaviour of hypertext users. We have realised a quantitative evaluation based on hypertext usability measures adapted to the problem: session size, session cost.
Effects of Hepatocyte CD14 Upregulation during Cholestasis on Endotoxin Sensitivity

Cholestasis is frequently related to endotoxemia and inflammatory response. Our previous investigation revealed a significant increase in plasma endotoxin and CD14 levels during biliary atresia. We therefore propose that lipopolysacharides (LPS) may stimulate CD14 production in liver cells and promote the removal of endotoxins. The aims of this study are to test the hypothesis that CD14 is upregulated by LPS and investigate the pathophysiological role of CD14 production during cholestasis. Using Western blotting, qRT-PCR, and promoter activity assay, we demonstrated that LPS was associated with a significant increase in CD14 and MD2 protein and mRNA expression and CD14 promoter activity in C9 rat hepatocytes but not in the HSC-T6 hepatic stellate cell line in vitro. To correlate CD14 expression and endotoxin sensitivity, in vivo biliary LPS administration was performed on rats two weeks after they were subjected to bile duct ligation (BDL) or a sham operation. CD14 expression and endotoxin levels were found to significantly increase after LPS administration in BDL rats. These returned to basal levels after 24 h. In contrast, although endotoxin levels were increased in sham-operated rats given LPS, no increase in CD14 expression was observed. However, mortality within 24 h was more frequent in the BDL animals than in the sham-operated group. In conclusion, cholestasis and LPS stimulation were here found to upregulate hepatic CD14 expression, which may have led to increased endotoxin sensitivity and host proinflammatory reactions, causing organ failure and death in BDL rats.
Long-term expression of two interacting motor pattern-generating networks in the stomatogastric system of freely behaving lobster.

Rhythmic movements of the gastric mill and pyloric regions of the crustacean foregut are controlled by two stomatogastric neuronal networks that have been intensively studied in vitro. By using electromyographic recordings from the European lobster, Homarus gammarus, we have monitored simultaneously the motor activity of pyloric and gastric mill muscles for </=3 mo in intact and freely behaving animals. Both pyloric and gastric mill networks are almost continuously active in vivo regardless of the presence of food. In unfed resting animals kept under "natural-like" conditions, the pyloric network expresses the typical triphasic pattern seen in vitro but at considerably slower cycle periods (2. 5-3.5 s instead of 1-1.5 s). Gastric mill activity occurs at mean cycle periods of 20-50 s compared with 5-10 s in vitro but may suddenly stop for up to tens of minutes, then restart without any apparent behavioral reason. When conjointly active, the two networks express a strict coupling that involves certain but not all motor neurons of the pyloric network. The posterior pyloric constrictor muscles, innervated by a total of 8 pyloric (PY) motor neurons, are influenced by the onset of each gastric mill medial gastric/lateral gastric(MG/LG) neuron powerstroke burst, and for one cycle, PY neuron bursts may attain >300% of their mean duration. However, the duration of activity in the lateral pyloric constrictor muscle, innervated by the unique lateral pyloric (LP) motor neuron, remains unaffected by this perturbation. During this period after gastric perturbation, LP neuron and PY neurons thus express opposite burst-to-period relationships in that LP neuron burst duration is independent of the ongoing cycle period, whereas PY neuron burst duration changes with period length. In vitro the same type of gastro-pyloric interaction is observed, indicating that it is not dependent on sensory inputs. Moreover, this interaction is intrinsic to the stomatogastric ganglion itself because the relationship between the two networks persists after suppression of descending inputs to the ganglion. Intracellular recordings reveal that this gastro-pyloric interaction originates from the gastric MG and LG neurons of the gastric network, which inhibit the pyloric pacemaker ensemble. As a consequence, the pyloric PY neurons, which are inhibited by the pyloric dilator (PD) neurons of the pyloric pacemaker group, extend their activity during the time that PD neuron is held silent. Moreover, there is evidence for a pyloro-gastric interaction, apparently rectifying, from the pyloric pacemakers back to the gastric MG/LG neuron group.
Forecasting and information sharing in supply chains under ARMA demand

This article considers the problem of determining the value of information sharing in a multi-stage supply chain in which the retailer faces AutoRegressive Moving Average (ARMA) demand, all players use a myopic order-up-to policy, and information sharing can only occur between adjacent players in the chain. It is shown that an upstream supply chain player can determine whether information sharing is of any value directly from the parameters of the model for the adjacent downstream player's order. This can be done by examining the location of the roots of the moving average polynomial of the model for the downstream player's order. If at least one of these roots is inside the unit circle or if the polynomial is applied to a lagged set of the downstream player's shocks, there is value of information sharing for the upstream player. It is also shown that under credible assumptions, neither player k−1's order nor player k's demand is necessarily an ARMA process with respect to the relevant shocks. It is shown that demand activity propagates in general to a process that is called quasi-ARMA, or QUARMA, in which the most recent shock(s) may be absent. It is shown that the typical player faces QUARMA demand and places orders that are also QUARMA. Thus, the demand propagation model is QUARMA in–QUARMA out. The presented analysis hence reverses and sharpens several previous results in the literature involving information sharing and also opens up many questions for future research.
4D light field segmentation with spatial and angular consistencies

In this paper, we describe a supervised four-dimensional (4D) light field segmentation method that uses a graph-cut algorithm. Since 4D light field data has implicit depth information and contains redundancy, it differs from simple 4D hyper-volume. In order to preserve redundancy, we define two neighboring ray types (spatial and angular) in light field data. To obtain higher segmentation accuracy, we also design a learning-based likelihood, called objectness, which utilizes appearance and disparity cues. We show the effectiveness of our method via numerical evaluation and some light field editing applications using both synthetic and real-world light fields.