Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional differences between two CRF-related diuretic hormone receptors in Drosophila

SUMMARY In Drosophila, two related G-protein-coupled receptors are members of the corticotropin releasing factor (CRF) receptor subfamily. We have previously reported that one of these receptors, encoded by CG8422 is a functional receptor for a diuretic hormone, DH44. Here, we report that the other CRF receptor subfamily member, encoded by CG12370, is also a receptor for the DH44 neuropeptide. The lines of evidence to support this identification include increases in cAMP levels due to CG12370 receptor activation and the recruitment of β-arrestin–GFP to the plasma membrane in response to DH44 application. We compared these features of the receptors DH44-R2 (encoded by CG12370) and DH44-R1 (encoded by CG8422) and found fundamental differences in signaling, association with the arrestins, and peptide sensitivity. We found that the sensitivity of DH44-R2 to the DH44 peptide is lower than that of DH44-R1, specifically an estimated EC50 of 7.98E-07 moll–1 for DH44 by DH44-R2 to an EC50 of 5.12E-09 moll–1 by DH44-R1 and found that previous reports on the sensitivity of the tubule to DH44 is in agreement with our measurements of DH44-R2 sensitivity. We employed a specific RNAi construct to selectively knock-down DH44-R2 expression and this led to heightened sensitivity to osmotic challenges. The functional characterization of this diuretic hormone receptor in Drosophila demonstrates a high degree of conservation of CRF-like signaling.
A Fuzzy Ordered Weighted Average (OWA) Approach to Result Merging for Metasearch Using the Analytical Network Process

A metasearch engine is a Information Retrieval (IR) tool that greatly expands the scope of Internet Search. Functionally a metasearch engine passes a query to multiple search engines and combines and re-ranks results returned by them in one merged list. Result Merging is a key component of metasearch and different techniques have been applied to solve the problem. In this paper we propose a model for result merging based on Saty's Analytical Network Process (ANP) and Yager's Ordered Weighted Average operator. We compare our results with four existing models for result merging, namely the Borda-Fuse, Weighted Borda-Fuse, Condorcet Fuse and the OWA model.
Information Models and Methods of the University's Scientific Knowledge Life Cycle Support

—The main aim of this work is to develop methods and technologies of the university’s scientiﬁc knowledge management. The paper examines the concept of knowledge management and life-cycle processes of the university’s scientiﬁc knowledge. Text Mining and Semantic Web technologies are used to develop the ontological information model and for information resources processing. The paper describes the developed information model of the university’s scientiﬁc knowledge, the methods of forming scientiﬁc proﬁles, and the concept of the university’s scientiﬁc knowledge semantic portal.
Real estate mutual funds: a style analysis

We find that the characteristics of real estate related securities are different from those of the general common equities. To help investors understand better the products offered by real estate mutual funds, we develop style descriptors that are specifically created for real estate related securities. Among the universe of real estate securities, we find real estate funds tilt toward large stocks and favor growth moderately over value. Growth managers outperform value mangers in this sector by 1.51% to 2.30% per year. However, there is evidence of shifts in the investment style among the funds. Our results help investors in evaluating real estate fund performance and making better asset allocation decisions. © 2007 Academy of Financial Services. All rights reserved. Jel classifications: G11; G12
Arterial Occlusive Lesions Recanalize More Frequently in Women Than in Men After Intravenous Tissue Plasminogen Activator Administration for Acute Stroke

Background and Purpose— Previous reports suggest that women achieve better outcome than men after intravenous thrombolysis for ischemic stroke. Coagulation and fibrinolysis differ between sexes. These findings prompted us to investigate possible gender differences in arterial recanalization after intravenous tissue plasminogen activator (IV tPA). Methods— We identified 100 consecutive patients who presented with acute ischemic stroke and received IV tPA within 6 hours of onset. Only patients with large artery anterior circulation strokes, as determined by MRI/MRA or CT/CTA before treatment, who had follow-up vascular study within 72 hour after treatment were included. We compared demographics, clinical features, admission medications, symptom-to-needle and treatment-to-repeat vascular imaging times, baseline National Institutes of Health Stroke Severity score, radiological and laboratory data, stroke mechanism, and outcome between the sexes. Results— 39 patients met all inclusion/exclusion criteria (22 men and 17 women). The recanalization rate was significantly higher in women (94% versus 59%; P=0.02). This difference remained statistically significant after excluding patients whose strokes were attributed to internal carotid artery occlusive lesions, and when the analysis was limited to those treated within 3 hours of stroke onset. All other confounding variables did not differ significantly between the sexes. Conclusions— In our cohort, vascular occlusive lesions were more likely to recanalize in women than men in response to IV tPA. These preliminary findings need to be validated in larger prospective studies.
A local neural classifier for the recognition of EEG patterns associated to mental tasks

This paper proposes a novel and simple local neural classifier for the recognition of mental tasks from on-line spontaneous EEG signals. The proposed neural classifier recognizes three mental tasks from on-line spontaneous EEG signals. Correct recognition is around 70%. This modest rate is largely compensated by two properties, namely low percentage of wrong decisions (below 5%) and rapid responses (every 1/2 s). Interestingly, the neural classifier achieves this performance with a few units, normally just one per mental task. Also, since the subject and his/her personal interface learn simultaneously from each other, subjects master it rapidly (in a few days of moderate training). Finally, analysis of learned EEG patterns confirms that for a subject to operate satisfactorily a brain interface, the latter must fit the individual features of the former.
Use of the potential of satellite images in the detection of farmland mutation by urbanization

Planning and management of urban areas have become one of the highest priorities in both developed and developing countries. Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially farmland, have become a great challenge for sustainable urban development in Algeria. Therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. Remote sensing has proved to be a powerful tool for monitoring rapid land use changes. The goal of this paper is to investigate the potential of satellite imagery in the detection of the dynamics of land use changes in the city of Sidi Bel Abbes. For this purpose, a methodology based on the vegetation index was proposed for the identification of farmland mutation. Multispectral and multitemporal images from Landsat were used to realize a map of farmland mutation by the phenomenon of urbanization. The results indicate that there was a considerable land use conversion from farmland into built-up land in the study area from 1987 to 2002.
A NEW COST FUNCTION FOR DIRECTION-OF-ARRIVAL ESTIMATION OF MULTIPLE SOUND SOURCES USING TWO MICROPHONES Minh

In this paper, a new cost function for estimating the directionof-arrival (DOA) using two microphones is proposed. The proposed cost function is cross-correlation of two microphone signals after canceling a sound source at each microphone by steering the null. The signal cancellation mechanism resembles null bemaforming except a scaling factor. It is shown that the null beamformer effectively cancels early reflections as well as the direct part of a signal. Due to this property, the estimation is shifted from the true direction in a reverberant environment. Cancellation of signals provides robustness of estimation in multi-source environments. Theoretical investigation shows that local/global minima of the cost function correspond to directions of sound sources. Simulation results using real world recordings in a highly reverberant room demonstrates the effectiveness of the proposed cost function for multiple sound sources.
Domain Mapping for Volumetric Parameterization using Harmonic Functions

ABSTRACTVolumetric parameterization problem refers to parameterization of both the interior and boundary of a 3D model. It is a much harder problem compared to surface parameterization where a parametric representation is worked out only for the boundary of a 3D model (which is a surface). Volumetric parameterization is typically helpful in solving complicated geometric problems pertaining to shape matching, morphing, path planning of robots, and isogeometric analysis etc. A novel method is proposed in which a volume parameterization is developed by mapping a general non-convex (genus-0) domain to its topologically equivalent convex domain. In order to achieve a continuous and bijective mapping of a domain, first we use the harmonic function to establish a potential field over the domain. The gradients of the potential values are used to track the streamlines which originate from the boundary and converge to a single point, referred to as the shape center. Each streamline approaches the shape center at a .
Attention in Complex Environment of Brain Computer Interface

Introduction: E lectroencephalogram (EEG) power is related to human cognitive processing, but in a complex and non-linear way. Attention is one of such fundamental human cognitive processes. EEG power in alpha band is positively related to it, whereas EEG power in theta band simultaneously shows the inverse relation [1]. It has been reported in past studies that if EEG power in lower (8-10Hz) and upper alpha (10-12Hz) supressed than opposite holds true for theta (4-7.5Hz) in attentional process [2]. The main purpose of this study is to explore the hidden nature of attention while involving a video game with high attentional need. This game creates a scenario in which subjects need to pay attention on both of the game and designed task. The attentional changes like handling sequential and random targets in our daily life - one complex environment. Material and Method: EEG data were collected from 10 right-handed subjects (male; 24.5 years; AD: 500Hz; 32 electrodes; 1-50Hz). A visual match-three puzzle game was used in which stimuli presented randomly 6-8 times in each session (total 6 sessions; played approximately 90 minutes). Subject needed to increase attention for 10s when target appears. The score was given by calculating and quantifying alpha power recorded online from EEG during 10s [3]. For analysis, EEG data from 1s prior as a reference interval and 10s following the onset stimulus were segmented. A power spectrum time series was calculated using the fast Fourier transform (FFT) which was squared and averaged for individual frequency band to obtain a
From rotation to dis guration : Testing a dual-strategymodel for recognition of faces across view anglesDominique

This study investigates the eeect of distinctive marks on the recognition of unfamiliar faces across view angles. Subjects were asked to memorize a set of target faces, half of which had distinctive marks. Recognition was assessed by presenting the target faces, either in the same orientation, or after 90 degrees rotation, mixed with an equal number of distractors. Results show that the eeect of distinctive marks depends on the view presented during learning. When a frontal view was learned, as predicted by the Valentin, Abdi, Edelman, and Posamentier (in press) dual-strategy model, distinctive marks improve recognition performance in the 90-degree condition but not in the 0-degree condition. However, when a proole view was learned, distinctive marks have no eeect on recognition performance, even in the 90-degree condition where a frontal view is tested.
MOTC: An Interactive Aid for Multidimensional Hypothesis Generation

The paper reports on conceptual development in the areas of database mining and knowledge discovery in databases (KDD). Our efforts have also led to a prototype implementation, called MOTC, for exploring hypothesis space in large and complex data sets. Our KDD conceptual development rests on two main principles. First, we use the crosstab representation for working with qualitative data. This is by now standard in on-line analytical processing (OLAP) applications, and we reaffirm it with additional reasons. Second, and innovatively, we use prediction analysis as a measure of goodness for hypotheses. Prediction analysis is an established statistical technique for analysis of associations among qualitative variables. It generalizes and subsumes a large number of other such measures of association, depending on specific assumptions the user is willing to make. As such, it provides a very useful framework for exploring hypothesis space in a KDD context. The paper illustrates these points with an extensive discussion of MOTC.
Social Capital, Racial Context, and Incarcerations in the American States

This article examines the differential effects of social capital on policy equity in state outcomes. Specifically, it explores the relationship between social capital and incarceration rates in the American states paying particular attention to racial disparities in incarceration rates. Building on work by Hero, I present a theoretical explanation and empirical support for how social capital operates differently under different racial contexts. I argue that social capital enhances social empathy in homogeneous contexts and social controls in diverse contexts. Using state-level longitudinal data on the contiguous states, I find that social capital is positively associated with incarcerations, but only for African Americans. Furthermore, the effects of social capital appear to be conditional on racial context where this relationship is stronger as minority group size increases.
Online Incremental Face Recognition System Using Eigenface Feature and Neural Classifier

Understanding how people process and recognize faces has been a challenging problem in the field of object recognition for a long time. Many approaches have been proposed to simulate the human process, in which various adaptive mechanisms are introduced such as neural networks, genetic algorithms, and support vector machines (Jain et al., 1999). However, an ultimate solution for this is still being pursued. One of the difficulties in the face recognition tasks is to enhance the robustness over the spatial and temporal variations of human faces. That is, even for the same person, captured images of human faces have full of variety due to lighting conditions, emotional expression, wearing glasses, make-up, and so forth. And the face features could be changed slowly and sometimes drastically over time due to some temporal factors such as growth, aging, and health conditions. When building a face recognition system, taking all the above variations into consideration in advance is unrealistic and maybe impossible. A remedy for this is to make a recognition system evolve so as to make up its misclassification on its own. In order to construct such an adaptive face recognition system, so-called incremental learning should be embedded into the system because it enables the system to conduct learning and classification on an ongoing basis. One challenging problem for this type of learning is to resolve so-called “plasticity and stability dilemma” (Carpenter & Grossberg, 1988). Thus, a system is required to improve its performance without deteriorating classification accuracy for previously trained face images. On the other hand, feature extraction plays an essential role in pattern recognition because the extraction of appropriate features results in high generalization performance and fast learning. In this sense, incremental learning should be considered not only for a classifier but also for the feature extraction part. As far as we know, however, many incremental learning algorithms are aiming for classifiers. As for the incremental learning for feature extraction, Incremental Principal Component Analysis (IPCA) (e.g., Oja & Karhunen, 1985; Sanger, 1989; Weng et al., 2003; Zhao et al., 2006) and Incremental Linear Discriminant Analysis (Pang et al., 2005; Weng & Hwang, 2007) have been proposed so far. Hall and Martin (1998) proposed a method to update eigen-features (e.g., eigen-faces) incrementally based on eigenvalue decomposition. Ozawa et al. (2004) extended this IPCA algorithm such that an eigen-axis was augmented based on the accumulation ratio to control the dimensionality of an eigenspace easily. O pe n A cc es s D at ab as e w w w . in te ch w eb . o rg
Action observation treatment: a novel tool in neurorehabilitation

This review focuses on a novel rehabilitation approach known as action observation treatment (AOT). It is now a well-accepted notion in neurophysiology that the observation of actions performed by others activates in the perceiver the same neural structures responsible for the actual execution of those same actions. Areas endowed with this action observation–action execution matching mechanism are defined as the mirror neuron system. AOT exploits this neurophysiological mechanism for the recovery of motor impairment. During one typical session, patients observe a daily action and afterwards execute it in context. So far, this approach has been successfully applied in the rehabilitation of upper limb motor functions in chronic stroke patients, in motor recovery of Parkinson's disease patients, including those presenting with freezing of gait, and in children with cerebral palsy. Interestingly, this approach also improved lower limb motor functions in post-surgical orthopaedic patients. AOT is well grounded in basic neuroscience, thus representing a valid model of translational medicine in the field of neurorehabilitation. Moreover, the results concerning its effectiveness have been collected in randomized controlled studies, thus being an example of evidence-based clinical practice.
Energy-efficiency indicators for e-services

Great strides have been made to increase the energy efficiency of hardware, data center facilities, and network infrastructure. These Green IT initiatives aim to reduce energy-loss in the supply chain from energy grid to computing devices. However, the demand for computation comes from software applications that perform business services. Therefore, to measure and improve efficiency for entire systems, energy-efficiency indicators are needed at the level of services. We have designed an initial set of indicators for energy-efficiency of e-services and we have tested them on two e-government services of the Dutch national government. We explain how these indicators serve as a starting point for energy-optimization initiatives, supported by appropriate contractual agreements between service owners and suppliers.
Experiences from Replicating a Case Study to Investigate Reproducibility of Software Development

1. INTRODUCTION Frequent changes in technology and continuously increasing demands from software customers means that software development is largely a creative process. Nevertheless, a fundamental question for software engineering in general, and for empirical software engineering in particular, is the reproducibility of software development: which aspects of a software development process and product are reproducible and which parts depend on the creativity of developers? A priori, it is not obvious that such separation into creative and reproducible aspects can be made, but if that were possible, we could focus software process, technologies, and empirical studies on the reproducible parts without restricting the creativity of developers. Therefore, this question is worthy of extensive investigation. The precise definition of reproducibility varies across disciplines, but it is often closely related to the definitions of repeatability. In an encyclopaedia of philosophy of science [Tetens 2004], reproducibility is described as the repeatability of the process of establishing a fact, or of the conditions under which the same fact can be observed. In natural science, reproducibility is often related closely to the repeatability of experimental conditions and results. See Anda et al. [2009] for a more comprehensive discussion of the concept of reproducibility in software engineering. The question of reproducibility can be asked for various levels of project granularity: from low-level atomic activities of developer actions to outcomes of entire projects, and for small elements of software such as a class or a function to large-scale software systems such as middleware in apache.org, Gnome UI, or even entire ecosystem of applications tied to the MS Windows platform, or event to entire Internet. The question of reproducibility is important for practitioners because it underlies the fundamental questions that have had the attention of software researchers for years, such as, to what extent software development effort and software quality can be predicted. Furthermore, this question is important from a scientific point of view since an understanding of what it means for a phenomenon to be reproducible is a prerequisite if software engineering (SE) phenomena are to be investigated using the scientific method and, hence, if SE is to become a mature industry. Scientific inquiry and mature engineering industries are recognized by reproducibility. The predominant focus in the empirical software engineering literature on research methods in general and replications in particular is experiment, see, for example [Wohlin et al. 1999] [Miller 2005] or [Shull et al. 2008]. Although the …
Run-timeScalingof MicroarchitectureResourcesin aProcessor for Energy Savings

In thispaperwepresenta strategyfor run-timeprofiling to optimizetheconfigurationof a microprocessordynamicallysoas to savepowerwith minimumperformancepenalty. Theconfigurationof theprocessoris changedat run-timeto attain the optimalenergyconsumptionfor theprogram.Experimentson somebenchmarkprogramsshowgoodsavingsin total energy consumption; wehaveobserveda decreaseof upto25%in energy/cycleandup to 10%in energy per instruction.Our proposedapproach can be usedfor energy-aware computingin eitherportableapplicationsor in desktopenvironmentswhere powerdensityis becominga concern.Thisapproach canalso be incorporatedin larger powermanagementstrategies like ACPI.
THE MDL PRINCIPLE , PENALIZED LIKELIHOODS , AND STATISTICAL RISK

We determine, for both countable and uncountable collections of functions, informationtheoretic conditions on a penalty pen(f) such that the optimizer f̂ of the penalized log likelihood criterion log 1/likelihood(f) + pen(f) has statistical risk not more than the index of resolvability corresponding to the accuracy of the optimizer of the expected value of the criterion. If F is the linear span of a dictionary of functions, traditional description-length penalties are based on the number of non-zero terms of candidate fits (the `0 norm of the coefficients) as we review. We specialize our general conclusions to show the `1 norm of the coefficients times a suitable multiplier λ is also an information-theoretically valid penalty.