Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of VaR based on stable distribution

Value at risk is widely applied to estimated market risks. But it lacks a convincing technique capturing the observed phenomena in financial data such as heavy-tails, time –varying and short and long-range dependence. The stable distribution can deal with these problems well. The demonstrative research shows that VaR based on stable distribution can solve these problems better than the traditional normal distribution.
1 Bilu – Linial Stability

In this chapter, we survey recent research on instance stability and perturbation resilience. Many discrete optimization problems in machine learning, operations research, and other areas are NP-hard. For many of them, not only the exact but even a good approximate solution cannot be found efficiently in the worst case. At the same time, instances appearing in real life can often be solved exactly or almost exactly. This raises the following question:
Detection of cases of inflammatory rheumatic disorders: performance of a telephone questionnaire designed for use by patient interviewers

Objective: To assess the performance in the detection of cases of rheumatoid arthritis (RA) and the spondyloarthropathies (SpA) of a questionnaire suitable for use in telephone surveys conducted by patient interviewers. Methods: A questionnaire was designed with reference to the signs, symptoms, and epidemiological criteria for RA (ACR 1987) and SpA (ESSG 1991). Three groups of respondents were recruited from the rheumatology outpatient clinics of 10 university hospitals: 235 with RA, 175 with SpA, and 195 controls with other rheumatological disorders. All diagnoses were confirmed by a rheumatologist. Patient from self help groups and social organisations were trained by a polling company professional to conduct a standard telephone interview using the new questionnaire. Results: In an RA-control comparison, logistic regression showed that a set of five items, predominantly ACR criteria, were the most informative. Self reported diagnosis performed best (sensitivity 0.99, specificity 0.87). In an SpA-control comparison, a set of three items from the ESSG criteria were the most informative, with self reported diagnosis again performing best (sensitivity 0.85, specificity 0.96). Overall agreements with clinical diagnoses were 97.7% for RA and 94.4% SpA, dropping to 90.4% and 79.1%, respectively, when self reported diagnosis was excluded. Without self reported diagnosis, questions about peripheral joint and spinal pain made significant contributions to diagnostic performance. Conclusion: A questionnaire in plain language was developed for use in detecting cases of RA and SpA. It performed satisfactorily when administered by patient interviewers and is now available for epidemiological surveys of the general population.
The Impact of climate change on tourism and recreation

Tourism is one of the largest and fastest growing economic sectors. Tourism is obviously related to climate, as tourists prefer spending time outdoors and travel to enjoy the sun or landscape. It is therefore surprising that the tourism literature pays little attention to climate and climatic change and it is equally surprising that the climate change impact literature pays little attention to tourism. The number of studies on tourism and climate change is, however, starting to grow. This paper reviews this literature, discussing shortcomings and recent developments in global modeling of tourism flows are presented. The range of methods used and issues studied in the literature is large, and findings are correspondingly diverse. However, all studies agree that climate change matters to tourism and recreation. Future avenues of inquiry are also discussed.
Piezoelectric actuator design with micro positioning capability and it's practical implementation: Fuzzy approach

Due to the developments of precision industrial machineries, the microscale positioning ability for the relative apparatus requires small size and high accuracy, and the piezoelectric actuator is one of means has this feature hence piezoelectric actuator plays an important role in this field for its microscale movement ability. Unfortunately, the nonlinear hysteresis phenomenon of piezoelectric materials, and modeling uncertainties of piezoelectric actuators lead to control difficulties and strongly reduce the positioning accuracy of piezoelectric actuators. Based on the above reasons, a novel control design combined with feedback linearization, fuzzy modeling approximation, and robust control concept are proposed for dealing with the micrometer (μm) positioning problem of piezoelectric actuators. From the simulation results, it is obvious that our proposed control law yields the excellent control performance than the conventional control designs. Finally, this proposed method is practically performed for the verification of positioning performance. After the practical testing, the controlled piezoelectric actuator possesses a positioning accuracy of 1 μm.
LEPTIN AND EXERCISE IN OVERWEIGHT AND OBESE WOMEN

The invention relates to a circuit arrangement for operating at least one discharge lamp, the circuit arrangement having a half-bridge inverter (Q10, Q11) with a downstream load circuit (L1, C10, LP1, C11), at least one coupling capacitor (C11) which is connected to the load circuit (L1, C10, LP1, C11) and to the half-bridge inverter (Q10, Q11), and a drive device (A1) of the half-bridge inverter (Q10, Q11). According to the invention, the circuit arrangement has a reference voltage source (R13, R14) and a detector circuit (DE1) which detector circuit compares the voltage drop across the at least one coupling capacitor (C11) or the voltage drop, divided downwards by a voltage divider, across the at least one coupling capacitor (C11) with the reference voltage of the reference voltage source (R13, R14), and generates an output signal for driving the half-bridge inverter (Q10, Q11).
Data Resource Acquisition from People at Various Stages of Cognitive Decline – Design and Exploration Considerations

In this paper we are introducing work in progress towards the development of an infrastructure (i.e., design, methodology, creation and description) of linguistic and extra-linguistic data samples acquired from people diagnosed with subjective or mild cognitive impairment and healthy, age-matched controls. The data we are currently collecting consists of various types of modalities; i.e. audio-recorded spoken language samples; transcripts of the audio recordings (text) and eye tracking measurements. The integration of the extra-linguistic information with the linguistic phenotypes and measurements elicited from audio and text, will be used to extract, evaluate and model features to be used in machine learning experiments. In these experiments, classification models that will be trained, that will be able to learn from the whole or a subset of the data to make predictions on new data in order to test how well a differentiation between the afore-mentioned groups can be made. Features will be also correlated with measured outcomes from e.g. language-related scores, such as word fluency, in order to investigate whether there are relationships between various variables.
A feature selection method using fixed-point algorithm for DNA microarray gene expression data

As the performance of hardware is limited, the focus has been to develop objective, optimized and computationally efficient algorithms for a given task. To this extent, fixed-point and approximate algorithms have been developed and successfully applied in many areas of research. In this paper we propose a feature selection method based on fixed-point algorithm and show its application in the field of human cancer classification using DNA microarray gene expression data. In the fixed-point algorithm, we utilize between-class scatter matrix to compute the leading eigenvector. This eigenvector has been used to select genes. In the computation of the eigenvector, the eigenvalue decomposition of the scatter matrix is not required which significantly reduces its computational complexity and memory requirement.
Structural diversity and biological significance of lipoteichoic acid in Gram-positive bacteria: focusing on beneficial probiotic lactic acid bacteria

Bacterial cell surface molecules are at the forefront of host-bacterium interactions. Teichoic acids are observed only in Gram-positive bacteria, and they are one of the main cell surface components. Teichoic acids play important physiological roles and contribute to the bacterial interaction with their host. In particular, lipoteichoic acid (LTA) anchored to the cell membrane has attracted attention as a host immunomodulator. Chemical and biological characteristics of LTA from various bacteria have been described. However, most of the information concerns pathogenic bacteria, and information on beneficial bacteria, including probiotic lactic acid bacteria, is insufficient. LTA is structurally diverse. Strain-level structural diversity of LTA is suggested to underpin its immunomodulatory activities. Thus, the structural information on LTA in probiotics, in particular strain-associated diversity, is important for understanding its beneficial roles associated with the modulation of immune response. Continued accumulation of structural information is necessary to elucidate the detailed physiological roles and significance of LTA. In this review article, we summarize the current state of knowledge on LTA structure, in particular the structure of LTA from lactic acid bacteria. We also describe the significance of structural diversity and biological roles of LTA.
Location-Aware Cross-Tier Coordinated Multipoint Transmission in Two-Tier Cellular Networks

Multi-tier cellular networks are considered as an effective solution to enhance the coverage and data rate offered by cellular systems. In a multi-tier network, high power base stations (BSs) such as macro BSs are overlaid by lower power small cells such as femtocells and/or picocells. However, co-channel deployment of multiple tiers of BSs gives rise to the problem of cross-tier interference that significantly impacts the performance of wireless networks. Multicell cooperation techniques, such as coordinated multipoint (CoMP) transmission, have been proposed as a promising solution to mitigate the impact of the cross-tier interference in multi-tier networks. In this paper, we propose a novel scheme for Location-Aware Cross-Tier Cooperation (LA-CTC) between BSs in different tiers for downlink CoMP transmission in two-tier cellular networks. On one hand, the proposed scheme only uses CoMP transmission to enhance the performance of the users who suffer from high cross-tier interference due to the co-channel deployment of small cells such as picocells. On the other hand, users with good signal-to-interference-plus-noise ratio (SINR) conditions are served directly by a single BS from any of the two tiers. Thus, the data exchange between the cooperating BSs over the backhaul network can be reduced when compared to the traditional CoMP transmission scheme. We use tools from stochastic geometry to quantify the performance gains obtained by using the proposed scheme in terms of outage probability, achievable data rate, and load per BS. We compare the performance of the proposed scheme with that of other schemes in the literature such as the schemes which use cooperation to serve all users and schemes that use range expansion to offload users to the small cell tier.
WebCap: Inferring the user's interests based on a real-time implicit feedback

In the context of the personalized information retrieval, this paper presents WebCap, a smart web browser for inferring the user's interests based on a real time implicit feedback. WebCap aims to collect implicitly the relevant documents, during the user's search session by inference of the degree of interest based on a combination of some relevant implicit indicators. The main advantage of our approach is that it does not require any log file. Indeed, WebCap, a browser side tool, calculates the degree of interest in real time and decides if the web page is quite relevant to feed the search history dimension. Our experimental framework, with real users, shows that WebCap can collected implicitly 80% of the relevant documents compared to the explicit approach.
Cooperation in Dialogue and Discourse Structure

Dealing with dialogues requires developing different levels of interpretation. An intention-based analysis must take into account discourse conventions and communication phenomena which shall result in coherent cooperative dialogues. The realisation of such a system is possible by distributing the tasks to independent agents. We show that the collaboration of these agents is possible by building and using a dialogue representation whose structure and content integrate the results of the different agents. The structure is dynamically built and is based on an intentional analysis. But to go further than only a plan-based approach, the basic units are communicative intentions and exchanges are finely structured. Thus the structure can also be used to handle conversational obligations. Since comprehension problems affect the form of a dialogue, a decomposition in precise units also allows reasoning on the structure itself to evaluate the progress of a dialogue and to detect communication problems.
Synchronous Changes of Cortical Thickness and Corresponding White Matter Microstructure During Brain Development Accessed by Diffusion MRI Tractography from Parcellated Cortex

Cortical thickness (CT) changes during normal brain development is associated with complicated cellular and molecular processes including synaptic pruning and apoptosis. In parallel, the microstructural enhancement of developmental white matter (WM) axons with their neuronal bodies in the cerebral cortex has been widely reported with measurements of metrics derived from diffusion tensor imaging (DTI), especially fractional anisotropy (FA). We hypothesized that the changes of CT and microstructural enhancement of corresponding axons are highly interacted during development. DTI and T1-weighted images of 50 healthy children and adolescents between the ages of 7 and 25 years were acquired. With the parcellated cortical gyri transformed from T1-weighted images to DTI space as the tractography seeds, probabilistic tracking was performed to delineate the WM fibers traced from specific parcellated cortical regions. CT was measured at certain cortical regions and FA was measured from the WM fibers traced from same cortical regions. The CT of all frontal cortical gyri, including Brodmann areas 4, 6, 8, 9, 10, 11, 44, 45, 46, and 47, decreased significantly and heterogeneously; concurrently, significant, and heterogeneous increases of FA of WM traced from corresponding regions were found. We further revealed significant correlation between the slopes of the CT decrease and the slopes of corresponding WM FA increase in all frontal cortical gyri, suggesting coherent cortical pruning and corresponding WM microstructural enhancement. Such correlation was not found in cortical regions other than frontal cortex. The molecular and cellular mechanisms of these synchronous changes may be associated with overlapping signaling pathways of axonal guidance, synaptic pruning, neuronal apoptosis, and more prevalent interstitial neurons in the prefrontal cortex. Revealing the coherence of cortical and WM structural changes during development may open a new window for understanding the underlying mechanisms of developing brain circuits and structural abnormality associated with mental disorders.
Noise mitigated compressed sensing

Recently, compressed sensing (CS) is of major interest in the area of communication and measurement. CS technique is a subtle mathematical application in practice, which facilitates the signal acquisition and signal processing dramatically. It consists of the two phases: signal projection and signal recovery. Regarding the signal recovery often it is an l1 optimization process in terms of a sparse regularized least squares. In this work, we introduce the noise-mitigated least squares (NMLS) to improve the CS signal recovery performance in case of suboptimal regularization parameter λ. Both theory and empirical results show that NMLS is a promising method over state-of the-art standard regularized CS procedures.
Gene-Tracer: Algorithm Tracing Genes Modification from Ancestors through Offsprings

ABSTRACT Genes acquire many changes and modifications during evolution producing many orthologous and paralogous . One of the main challenges for biologist is tracing back the origin of modified genes in the genomes of various organisms. Tracing genes modifications and developments from the ancestors to offsprings is however a massive task for biologists. Thus, computer programs can help biologists tracking down those changes through sequence alignment. In this paper, we present an algorithm, called Gene Tracer and based on sequence alignment, that given two ancestor sequences and their offspring one, tracks down genes modification in the ancestor sequences and finds related parts of each ancestor in the offspring one. Keywords: Pairwise local alignment; Tracing genes modifications algorithm , Gene Tracer . Availability http://www.bitrides. com/bio-sat/index.php 1. INTRODUCTION alignment method to compare is local alignment [1]During biological evolution, genes acquire many changes and modifications. One of the main challenges for biologists is tracing back the origin of modified genes in the genomes of various organisms. Some of these modifications are desirable while others are notorious. Tracing genes modifications from ancestors to offsprings is, however, a massive task which needs computer programs to help biologists tracking down those changes. In the medical field, such programs will help out in tracing mutated heritable genes responsible for heritable diseases. In this paper, we present an algorithm, called
Measuring the Impact of Staple Strength-Enhancing Technologies on Australian Wool Producer Profits: A Duality-Based Approach

Wool tenderness is a significant problem in Australia, especially in areas where sheep graze under highly seasonal conditions. In this study, a duality-based modeling framework is implemented to assess the economic impact of staple strength-enhancing research on the profits of Australian woolgrowers. Within this framework, a normalized quadratic profit function is specified and estimated. The model is based on a number of fundamental characteristics of the Australian wool industry and the staple-strength enhancing technology being assessed. The model consists of a system of equations that are specified in terms of effective, rather than actual, prices. The interrelationships between the netputs are allowed for in the model in a manner that is consistent with the theoretical restrictions that arise as a result of assuming profit maximization, ensuring that the welfare calculations are unambiguous.
Performance modeling in industry: a case study on storage virtualization

In software engineering, performance and the integration of performance analysis methodologies gain increasing importance, especially for complex systems. Well-developed methods and tools can predict non-functional performance properties like response time or resource utilization in early design stages, thus promising time and cost savings. However, as performance modeling and performance prediction is still a young research area, the methods are not yet well-established and in wide-spread industrial use. This work is a case study of the applicability of the Palladio Component Model as a performance prediction method in an industrial environment. We model and analyze different design alternatives for storage virtualization on an IBM* system. The model calibration, validation and evaluation is based on data measured on a System z9* as a proof of concept. The results show that performance predictions can identify performance bottlenecks and evaluate design alternatives in early stages of system development. The experiences gained were that performance modeling helps to understand and analyze a system. Hence, this case study substantiates that performance modeling is applicable in industry and a valuable method for evaluating design decisions.
The development of a multi-posture sensing system

Wearable devices are being used in an expanding range of daily life applications, automatically recording data for extraction and analysis. This paper develops a real time wearable multi-posture sensing system, using six tri-axial accelerometers to detect four frequent posture types to provide the user with realtime, longitudinal posture monitoring for therapeutic purposes.
Political Uncertainty and Investment: Causal Evidence from U.S. Gubernatorial Elections

I examine the link between political uncertainty and firm investment using U.S. gubernatorial elections as a source of plausibly exogenous variation in uncertainty. Investment declines 5% before all elections and up to 15% for subsamples of firms particularly susceptible to political uncertainty. I use term limits as an instrumental variable (IV) for election closeness. Because close elections are related to economic downturns, I find that the effect of close elections on investment is understated by more than half by ordinary least squares (OLS). Post-election rebounds in investment depend on whether an incumbent is re-elected. Finally, I provide evidence that firms delay equity and debt issuances tied to investments before elections.
ARHGEF7 (BETA-PIX) Acts as Guanine Nucleotide Exchange Factor for Leucine-Rich Repeat Kinase 2

Background Mutations within the leucine-rich repeat kinase 2 (LRRK2) gene are a common cause of familial and sporadic Parkinson's disease. The multidomain protein LRRK2 exhibits overall low GTPase and kinase activity in vitro. Methodology/Principal Findings Here, we show that the rho guanine nucleotide exchange factor ARHGEF7 and the small GTPase CDC42 are interacting with LRRK2 in vitro and in vivo. GTPase activity of full-length LRRK2 increases in the presence of recombinant ARHGEF7. Interestingly, LRRK2 phosphorylates ARHGEF7 in vitro at previously unknown phosphorylation sites. We provide evidence that ARHGEF7 might act as a guanine nucleotide exchange factor for LRRK2 and that R1441C mutant LRRK2 with reduced GTP hydrolysis activity also shows reduced binding to ARHGEF7. Conclusions/Significance Downstream effects of phosphorylation of ARHGEF7 through LRRK2 could be (i) a feedback control mechanism for LRRK2 activity as well as (ii) an impact of LRRK2 on actin cytoskeleton regulation. A newly identified familial mutation N1437S, localized within the GTPase domain of LRRK2, further underlines the importance of the GTPase domain of LRRK2 in Parkinson's disease pathogenesis.
ADOPTION AND USE OF SOCIAL COMPUTING : A USER-SYSTEM FIT MODEL AND EMPIRICAL STUDY

Social computing, or Web 2.0, is receiving growing attention both in academic research and in practice. Evidence suggests that a rich set of motives entice individuals to use Web 2.0. However, traditional models of IT acceptance generally do not account for these motives, and thus are not particularly adequate to explain the adoption and use of Web 2.0. Indeed, a central construct in many of these models, the ‘usefulness’ construct, exclusively focuses on performance needs. This study makes an effort to provide an improved understanding of Web 2.0 usage by offering two contributions. First, the study reconceptualizes ‘usefulness’ into ‘needs-supplies fit’, a formative construct that taps into a wide spectrum of needs. Second, relying on person-environment fit as its theoretical lens, the study develops and tests a model of user system fit that offers a complementary perspective to current models in further understanding of Web 2.0 use.