Miracle-dz/UniFAR-FTUs huggingface dataset:
Seismic Assessment of Geothermal Potential - Concept and ApplicationCase Study of the German Continental Deep Drilling Site (KTB)

Geothermal reservoirs can embody safe, accessible and stable sources of renewable and environmentally friendly energy. In order to access and extract this energy, drilling of deep wells connected with vast financial investments is unavoidable. Thorough predrilling exploration followed by simulations of heat extraction can help to assess the site’s geothermal energy potential and thus lower the risk of possible financial losses. Extraction of heat enclosed in the deep rock can be simulated with a two-well geothermal system. Through one of the wells cool water is being injected into the reservoir, where it is heating up while travelling towards the production well. If certain conditions are fulfilled, water pumped to the surface carries the amount of energy sufficient for geothermal power production. With simulations of such geothermal systems it is possible to predict their profitability and sustainability. The extensive amount of scientific experiments performed during the Continental Deep Drilling Program (KTB) within the years 1985-1996 yielded a wide database of miscellaneous information concerning the continental crystalline crust. This and the fact that temperatures up to 265°C were measured in the KTB drill hole were the motives to choose the KTB site as case study representative for geothermal reservoirs located in crystalline environments.
Common Learning

Consider two agents who learn the value of an unknown parameter by observing a sequence of private signals. The signals are independent and identically distributed across time but not necessarily across agents. We show that that when each agent's signal space is finite, the agents will commonly learn its value, i.e., that the true value of the parameter will become approximate common-knowledge. In contrast, if the agents' observations come from a countably infinite signal space, then this contraction mapping property fails. We show by example that common learning can fail in this case.
Big Data Infrastructure for Active Situation Awareness on Social Network Services

Awareness computing aims at our final goal in computer science to simulate human's awareness and cognition. Awareness of social network knowledge in everyday life is actively enabled by big data society. In this paper, we investigate infrastructure for big data analytics for social network services, and propose TF-IDF calculation on big data infrastructure to be aware of social relations on social networks.
Informedia News-On Demand: Using Speech Recognition to Create a Digital Video Library

Abstract : In theory, speech recognition technology can make any spoken words in video or audio media usable for text indexing, search and retrieval. This article describes the News-on-Demand application created within the Informedia(TM) Digital Video Library project and discusses how speech recognition is used in transcript creation from video, alignment with closed-captioned transcripts, audio paragraph segmentation and a spoken query interface. Speech recognition accuracy varies dramatically depending on the quality and type of data used. Informal information retrieval tests show that reasonable recall and precision can be obtained with only moderate speech recognition accuracy.
Secrets of successful simulation projects

Describes how a simulation project should be performed in order to ensure a successful outcome. This involves skills in both simulation and project management. The paper concentrates on the process of performing a simulation project rather than specific methods required during the course of a project. An overview of a simulation project is given before discussing in more detail the four main phases of a project: problem definition, model building and testing, experimentation and project completion.
On the Discovery of Interesting Patterns in Association Rules

Many decision support systems, which utilize association rules for discovering interesting patterns, require the discovery of association rules that vary over time. Such rules describe complicated temporal patterns such as events that occur on the “first working day of every month. ” In this paper, we study the problem of discovering how association rules vary over time. In particular, we introduce the idea of using a calendar algebra to describe complicated temporal phenomena of interest to the user. We then present algorithms for discovering calendric association rules, which are association rules that follow the patterns set forth in the user supplied calendar expressions. We devise various optimizations that speed up the discovery of calendric association rules. We show, through an extensive series of experiments, that these optimization techniques provide performance benefits ranging from to over a less sophisticated algorithm.
Domain Representable Spaces Defined by Strictly Positive Induction

Recursive domain equations have natural solutions. In particular there are domains defined by strictly positive induction. The class of countably based domains gives a computability theory for possibly non-countably based topological spaces. A $ qcb_{0} $ space is a topological space characterized by its strong representability over domains. In this paper, we study strictly positive inductive definitions for $ qcb_{0} $ spaces by means of domain representations, i.e. we show that there exists a canonical fixed point of every strictly positive operation on $qcb_{0} $ spaces.
Biomimetic-based output feedback for attitude stabilization of a flapping-wing micro aerial vehicle

SUMMARY The paper deals with the development of a bounded control law for Flapping-wing Micro Aerial Vehicles that mimics a strategy adopted by animal flapping flyers to stabilize their orientation. The control consists on generating torques about the body's principal axes by means of a modulation of the wing angle amplitudes. It is known that flapping flyers orient their body without any numerical computation or estimation of their current attitude. Therefore, the proposed control law is computed using the direct measurements of onboard sensors mimicking animal sensitive organs, more specifically the halteres, legs sensilla, and magnetic sense. The technological equivalents of these biological sensors are three rate gyros, a tri-axis accelerometer, and a tri-axis magnetometer, respectively. Besides, the control signal is bounded to keep the wing angle amplitudes below the maximal values. Owing to its simplicity, this control law is suitable for applications where onboard computational resources are limited. The stability of the closed-loop system is proved based on Lyapunov analysis and averaging theory. The effectiveness of the proposed control law is shown in simulations. The robustness with respect to external disturbances is also shown emphasizing the importance and need of the bounded control.
Multilocus Genetic Risk Score Associates With Ischemic Stroke in Case–Control and Prospective Cohort Studies

Background and Purpose— Genome-wide association studies have revealed multiple common variants associated with known risk factors for ischemic stroke (IS). However, their aggregate effect on risk is uncertain. We aimed to generate a multilocus genetic risk score (GRS) for IS based on genome-wide association studies data from clinical-based samples and to establish its external validity in prospective population-based cohorts. Methods— Three thousand five hundred forty-eight clinic-based IS cases and 6399 controls from the Wellcome Trust Case Control Consortium 2 were used for derivation of the GRS. Subjects from the METASTROKE consortium served as a replication sample. The validation sample consisted of 22 751 participants from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. We selected variants that had reached genome-wide significance in previous association studies on established risk factors for IS. Results— A combined GRS for atrial fibrillation, coronary artery disease, hypertension, and systolic blood pressure significantly associated with IS both in the case–control samples and in the prospective population-based studies. Subjects in the top quintile of the combined GRS had >2-fold increased risk of IS compared with subjects in the lowest quintile. Addition of the combined GRS to a simple model based on sex significantly improved the prediction of IS in the combined clinic-based samples but not in the population-based studies, and there was no significant improvement in net reclassification. Conclusions— A multilocus GRS based on common variants for established cardiovascular risk factors was significantly associated with IS both in clinic-based samples and in the general population. However, the improvement in clinical risk prediction was found to be small.
Influencing Factors on Price Tolerance of Internet Customers

Price is a major motive that engages consumers in shopping websites, and although price tolerance has gained increasing attention for its importance on pricing strategy, related literature on e-commerce lacks a conceptual model probing into factors that influence customers’ price tolerance. This paper proposes an integrated conceptual model, and empirically tests the model using data collected from online customers. The findings show that perceived value is the most influential factor on price tolerance, and the remaining factors that influence price tolerance are in the sequence of customer satisfaction, commitment, and trust. By dividing customers into two groups according to their monthly shopping frequency, this study finds that the perceived value of the high-frequency shopping group does not have a significantly positive influence on commitment, and the customer satisfaction of the low-frequency shopping group does not have significantly positive influence on price tolerance. The findings of this research provide related shopping websites with meaningful suggestions and references on pricing strategies.
A newly isolated Chlorella sp. from desert sand crusts exhibits a unique resistance to excess light intensity.

We recently isolated a small green alga from a biological sand crust (BSC) in the NW Negev, Israel. Based on its 18S rRNA and rbcL genes, it is a close relative of Chlorella sorokiniana and of certain strains of C. vulgaris and C. variabilis, but differs substantially in many aspects from C. sorokiniana. Because the classification of Chlorellales is still not resolved, we designated this species as C. ohadii (Trebouxiophyceae) in honor of Professor Itzhak Ohad. Under controlled laboratory conditions, C. ohadii showed marked structural and photosynthetic performance changes, depending on the carbon source used during growth, as well as remarkable resistance to photoinhibition. CO2 -dependent O2 evolution was not affected even when exposed to a light intensity of 3500 μmole photons m(-2) s(-1) , over 1.5 times the maximal intensity reached at the BSC surface, whereas the variable fluorescence declined sharply. We briefly discuss the use of fluorescence to assess photosynthetic rate and the implications of this finding for the assessment of global BSCs activity.
Differences of Retinal Blood Flow Between Arteries and Veins Determined by Laser Speckle Flowgraphy in Healthy Subjects

AbstractTo characterize the total retinal blood flow determined by laser speckle flowgraphy (LSFG) of healthy subjects.This prospective cross-sectional study was conducted at the Nagoya University Hospital. One hundred fifteen right eyes of 115 healthy subjects (mean age: 39.4 ± 16.1 years) were studied. The total blood flow in the retinal arteries and veins around the optic nerve head was measured separately using the total retinal flow index (TRFI), which represents blood flow volume. The lumen diameters of the retinal vessels determined by LSFG and by adaptive optics (AO) camera were compared. The images obtained by LSFG and AO camera were merged, and the distribution of the mean blur rates (MBRs), which represent the velocities of the erythrocytes, was evaluated on the images.The mean TRFI in veins (1812 ± 445, arbitral units) was significantly higher than that in arteries (1455 ± 348, arbitral units; P < 0.001). Linear regression analysis showed a significant correlation between the TRFI in the arteries and veins (P < 0.001). Linear regression analysis also showed a highly significant correlation between the diameters of arteries and veins determined by LSFG and by the AO camera (arteries, r = 0.94, P < 0.001; veins, r = 0.92, P < 0.001). The ratios of the lumen diameters determined by LSFG to that by AO camera was significant lower in arteries (0.068 ± 0.005, arbitral units) than in veins (0.074 ± 0.007, arbitral units) (P < 0.001). The MBRs of veins were homogeneous throughout the width of the lumen; however, the MBRs in the arteries were higher at the center and lower close to the walls of the lumen.The higher TRFIs in the veins than in the arteries indicate that there is a smaller volume of retinal blood flow in arteries than veins. However, the possibility remains that LSFG has inherent problem that the arterial lumen diameter determined by LSFG is smaller than actual one because of the characteristics of arteries. This would result in a smaller volume of retinal blood flow in the arteries than veins in LSFG.
Chemical Profile and Antioxidant Activity of the Oil from Peony Seeds (Paeonia suffruticosa Andr.)

Peony seed oil (PSO) is a novel vegetable oil developed from the seeds of Paeonia suffruticosa Andr. The present study aimed to make an overall investigation on the chemical profile and antioxidant activities of PSO for reasonable development and utilization of this new resource food. Chemical analysis revealed that PSO was characterized by an uncommon high portion of α-linolenic acid (>38%), fairly low ratio of n-6 to n-3 polyunsaturated fatty acids (0.69), and much higher content of γ-tocopherol than various conventional seed oils. In vitro assay indicated that PSO is a more potent scavenger of free radicals than extra virgin olive oil. Moderate intake of PSO exhibited obvious protection against various oxidative damages such as tetrachloromethane-induced acute liver injury in mice and diet-induced hyperlipidemia in rats. The changes in the key indicators of oxidative injury and fatty acid composition in the liver caused by PSO administration were measured, and the results demonstrated that antioxidant properties of PSO are closely related to their characteristic chemical composition. Consequently, the present study provided new evidence for the health implications of PSO, which deserves further development for medical and nutritional use against oxidative damages that are associated with various diseases.
Iterative non-sequential protein structural alignment.

Structural similarity between proteins gives us insights on the evolutionary relationship between proteins which have low sequence similarity. In this paper, we present a novel approach called STSA for non-sequential pair-wise structural alignment. Starting from an initial alignment, our approach iterates over a two-step process, a superposition step and an alignment step, until convergence. Given two superposed structures, we propose a novel greedy algorithm to construct both sequential and non-sequential alignments. The quality of STSA alignments is evident in the high agreement it has with the reference alignments in the challenging-to-align RPIC set. Moreover, on a dataset of 4410 protein pairs selected from the CATH database, STSA has a high sensitivity and high specificity values and is competitive with state-of-the-art alignment methods and gives longer alignments with lower rmsd. The STSA software along with the data sets will be made available on line at http://www.cs. rpi.edu/-zaki/software/STSA.
Distribution of p53 expression in tissue from 774 Danish ovarian tumour patients and its prognostic significance in ovarian carcinomas  

The clinical roles played by normal and altered p53 in cancer are under intensive investigation, but larger studies describing the pattern as well as the prognostic value are still needed. The aim of this study was, using tissue array (TA), to examine the overexpression of p53 protein in 774 epithelial ovarian tumour tissues from Danish women and to evaluate whether p53 tissue expression levels correlate with clinicopathological parameters and prognosis. The distribution of p53 expression levels at different stages of disease, in different histological subtypes, and the prognostic value of p53 tissue expression were examined. Overall, p53 was expressed in 24/189 (13%) low malignant potential ovarian tumours (LMP) and in 278/585 (48%) ovarian cancers (OC). No significant difference in frequency of p53 tissue expression in LMP tissue was noted with increasing tumour stage (p=0.98). By contrast, there was a significant increase in the frequency of p53 tissue expression in OC with increasing FIGO stage (p<0.00001). Multivariate Cox regression analysis found that less than 20% tissue expression of p53 was associated with longer OC disease‐specific survival. Tissue p53 expression may be of prognostic value in women with OC.
Coalition formation through motivation and trust

Cooperation is the fundamental underpinning of multi-agent systems, allowing agents to interact to achieve their goals. Where agents are self-interested, or potentially unreliable, there must be appropriate mechanisms to cope with the uncertainty that arises. In particular, agents must manage the risk associated with interacting with others who have different objectives, or who may fail to fulfil their commitments. Previous work has utilised the notions of motivation and trust in engendering successful cooperation between self-interested agents. Motivations provide a means for representing and reasoning about agents' overall objectives, and trust offers a mechanism for modelling and reasoning about reliability, honesty, veracity and so forth. This paper extends that work to address some of its limitations. In particular, we introduce the concept of a clan: a group of agents who trust each other and have similar objectives. Clan members treat each other favourably when making private decisions about cooperation, in order to gain mutual benefit. We describe mechanisms for agents to form, maintain, and dissolve clans in accordance with their self-interested nature, along with giving details of how clan membership influences individual decision making. Finally, through some simulation experiments we illustrate the effectiveness of clan formation in addressing some of the inherent problems with cooperation among self-interested agents.
Digital interventions for sustainable urban mobility: a pilot study

This paper presents results from a pilot study aimed to explore the design of behavior change interventions for sustainable urban mobility. Eight participants were provided with a mobile app deploying a novel combination of goal-setting, self-monitoring, rewards and sharing features in order to observe, over a month period, relevant changes in their transport choices and habits. The digital intervention produced an increase of sustainable transport choices of 14% and contributed to raise participants' environmental awareness, particularly regarding the
A new species of Dalla from Mexico (Lepidoptera: Hesperiidae).

Dalla steinhauseri , new species , is described from three males collected by John Kemner in Oaxaca, Mexico, during May 1990, the elevation varying from 1860-2700m. The closest related species to D. steinhauseri is D. bubobon (Dyar, 1921), known from two males: the holotype from Guerreo, Mexico (Muller Collection, USNM), and a male labelled southern Mexico, Townsend (Carnegie Museum, Pittsburgh). This species differs from D. steinhauseri in color pattern, maculation, size and morphology of the male genitalia.
Truthful randomized mechanisms for combinatorial auctions

We design two computationally-efficient incentive-compatible mechanisms for combinatorial auctions with general bidder preferences. Both mechanisms are randomized, and are incentive-compatible in the universal sense. This is in contrast to recent previous work that only addresses the weaker notion of incentive compatibility in expectation. The first mechanism obtains an O(√m)-approximation of the optimal social welfare for arbitrary bidder valuations -- this is the best approximation possible in polynomial time. The second one obtains an O(log2 m)-approximation for a subclass of bidder valuations that includes all submodular bidders. This improves over the best previously obtained incentive-compatible mechanism for this class which only provides an O(√ m)-approximation.
The effects of process variables on the weld deposit area in submerged arc welds

The results of bead-on-plate submerged arc welding experiments are presented to determine the effects of process variables on the weld deposit area at a constant heat input of 2kj/mm. It is found that the deposit area is a function of the welding current, welding voltage, welding speed, electrode polarity, electrode diameter and electrode extension. In general, welds made using direct current electrode negative (DCEN) polarity, a small-diameter electrode, long electrode extension, high welding current, low welding voltage and high welding speed have large deposit areas. The weld deposit area is, however, not affected significantly by the power source or the flux type used in this investigation.
Fast Inversion of Chebyshevvvandermonde Matrices 1

This paper contains two fast algorithms for inversion of ChebyshevvVander-monde matrices of the rst and second kind. They are based on special representations of the Bezoutians of Chebyshev polynomials of both kinds. The paper also contains the results of numerical experiments which show that the algorithms proposed here are not only much faster, but also more stable than other algorithms available. It is also eecient to use the above two algorithms for solving ChebyshevvVandermode systems of equations with preprocessing. 0 Introduction In this paper we consider polynomial Vandermonde matrix of the form V P t = 2 6 6 6 6 4
Navigation of a non-holonomic mobile robot with a memory of omnidirectional images

This paper extends our vision based navigation framework proposed in (2) to the entire class of central cameras (conventional and catadioptric cameras). During an off-line learning step, the robot performs paths which are sampled and stored as a set of ordered key images acquired by an embedded camera. The robot is then controlled by a vision-based control law along a visual route which joins the current image to the target image in the visual memory. We propose here to use an omnidirectional camera which significantly improves the localisation and navigation steps thanks to its large field o f view. Simulations as well as real experimental results with an indoor robot illustrate the validity of the presented framework. I. I NTRODUCTION
Dictionary-Based Face and Person Recognition From Unconstrained Video

To recognize people in unconstrained video, one has to explore the identity information in multiple frames and the accompanying dynamic signature. These identity cues include face, body, and motion. Our approach is based on video-dictionaries for face and body. Video-dictionaries are a generalization of sparse representation and dictionaries for still images. We design the video-dictionaries to implicitly encode temporal, pose, and illumination information. In addition, our video-dictionaries are learned for both face and body, which enables the algorithm to encode both identity cues. To increase the ability of our algorithm to learn nonlinearities, we further apply kernel methods for learning the dictionaries. We demonstrate our method on the Multiple Biometric Grand Challenge, Face and Ocular Challenge Series, Honda/UCSD, and UMD data sets that consist of unconstrained video sequences. Our experimental results on these four data sets compare favorably with those published in the literature. We show that fusing face and body identity cues can improve performance over face alone.