Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive, Transparent Frequency and Voltage Scaling of Communication Phases in MPI Programs

Although users of high-performance computing are most interested in raw performance, both energy and power consumption have become critical concerns. Some microprocessors allow frequency and voltage scaling, which enables a system to reduce CPU performance and power when the CPU is not on the critical path. When properly directed, such dynamic frequency and voltage scaling can produce significant energy savings with little performance penalty. This paper presents an MPI runtime system that dynamically reduces CPU performance during communication phases in MPI programs. It dynamically identifies such phases and, without profiling or training, selects the CPU frequency in order to minimize energy-delay product. All analysis and subsequent frequency and voltage scaling is within MPI and so is entirely transparent to the application. This means that the large number of existing MPI programs, as well as new ones being developed, can use our system without modification. Results show that the average reduction in energy-delay product over the NAS benchmark suite is 10% - the average energy reduction is 12% while the average execution time increase is only 2.1%
Improving PSO-based Multi-Objective Optimization using Crowding , Mutation and �-Dominance

In this paper, we propose a new Multi-Objective Particle Swarm Optimizer, which is based on Pareto dominance and the use of a crowding factor to filter out the list of available leaders. We also propose the use of different mutation (or turbulence) operators which act on different subdivisions of the swarm. Finally, the proposed approach also incorporates the -dominance concept to fix the size of the set of final solutions produced by the algorithm. Our approach is compared against five state-of-the-art algorithms, including three PSO-based approaches recently proposed. The results indicate that the proposed approach is highly competitive, being able to approximate the front even in cases where all the other PSO-based approaches fail.
Active Ownership

We analyze an extensive proprietary database of corporate social responsibility engagements with U.S. public companies from 1999-2009. Engagements address environmental, social, and governance concerns. Successful (unsuccessful) engagements are followed by positive (zero) abnormal returns. Companies with inferior governance and socially conscious institutional investors are more likely to be engaged. Success in engagements is more probable if the engaged firm has reputational concerns and higher capacity to implement changes. Collaboration among activists is instrumental in increasing the success rate of environmental/social engagements. After successful engagements, particularly on environmental/social issues, companies experience improved accounting performance and governance and increased institutional ownership.
Tsunami Arrival Detection with High Frequency (HF) Radar

Quantitative real-time observations of a tsunami have been limited to deep-water, pressure-sensor observations of changes in the sea surface elevation and observations of sea level fluctuations at the coast, which are essentially point measurements. Constrained by these data, models have been used for predictions and warning of the arrival of a tsunami, but to date no system exists for local detection of an actual incoming wave with a significant warning capability. Networks of coastal high frequency (HF)-radars are now routinely observing surface currents in many countries. We report here on an empirical method for the detection of the initial arrival of a tsunami, and demonstrate its use with results from data measured by fourteen HF radar sites in Japan and USA following the magnitude 9.0 earthquake off Sendai, Japan, on 11 March 2011. The distance offshore at which the tsunami can be detected, and hence the warning time provided, depends on the bathymetry: the wider the shallow continental shelf, the greater this time. We compare arrival times at the radars with those measured by neighboring tide gauges. Arrival times measured by the radars preceded those at neighboring tide gauges by an average of 19 min (Japan) and 15 min (USA) The initial water-height increase due to the tsunami as measured by the tide gauges was moderate, ranging from 0.3 to 2 m. Thus it appears possible to detect even moderate tsunamis using this method. Larger tsunamis could obviously be detected further from the coast. We find that tsunami arrival within the radar coverage area can be announced 8 min (i.e., twice the radar spectral time resolution) after its first appearance. This can provide advance warning of the tsunami approach to the coastline locations.
Negative Reciprocity and the Interaction of Emotions and Fairness Norms

This experimental study investigates how behavior changes after punishment for an unkind action. It also studies how fairness perceptions affect the reaction to punishment and whether this effect is consistent across repeated play and role experiences. A repeated version of the power-to-take game is used. In this game, the proposer can make a claim on the resources of a responder. Then, the responder can destroy any part of her own resources. The focus is on how proposers adjust their behavior depending on their fairness perceptions, their experienced emotions, and their interaction with responders. We find that fairness plays an important role in the behavior of proposers. Specifically, deviations from a perceived fairness norm trigger feelings of shame and guilt, which induce proposers to lower their claims. However, we also find that the perceived fairness norm varies considerably between individuals. Therefore, it is not the case that proposers who considered they were acting fairly were particularly nice to responders. Our results also show that the different types of individuals predicted by models of social preferences, can be traced among the subjects that played the same role in both periods, but fail to describe the behavior of subjects who switched from one role to the other.
Automatic extrinsic calibration of multiple laser range sensors with little overlap

Networks of laser range finders are a popular tool for monitoring large cluttered areas and to track people. Whenever multiple scanners are used for this purpose, one major problem is how to determine the relative positions of all the scanners. In this paper, we present a novel approach to calibrate a network of multiple planar laser range finders scanning horizontally. To robustly deal with the potentially restricted overlap between the fields of view, our approach only requires a dynamic object, e.g., a person, moving through the observed area. We employ a RANSAC-like algorithm to find the correspondences between the measurements of the different laser range finders. Based on these correspondences we formulate a graph-based optimization problem to determine the maximum likelihood extrinsic parameters of the sensor network. Furthermore, we present a method to evaluate the consistency of the resulting calibration based on visibility constraints. Experiments on real and simulated data show that the proposed approach yields better results than techniques that only perform pairwise calibration.
Non-parametric reconstruction of the primordial power spectrum at horizon scales from WMAP data

We extend to large scales a method proposed in previous work that reconstructs non-parametrically the primordial power spectrum from cosmic microwave background data at high resolution. The improvement is necessary to account for the non-Gaussianity of the Wilkinson Microwave Anisotropy Probe (WMAP) likelihood primarily due to cosmic variance. We assume the concordance A cold dark matter (ACDM) cosmology, utilize a smoothing prior and perform Monte Carlo simulations around an initial power spectrum that is scale free and with spectral index n s = 0.97, very close to the concordance spectrum. The horizon scale for the model we are considering corresponds to the wavenumber k h = 4.52 x 10 -4 Mpc -1 . We find some evidence for the presence of features and we quantify the probabilities of exceeding the observed deviations in WMAP data with respect to the fiducial models. We detect the following marginal departures from a scale-free (spectral index n s = 0.97) initial spectrum: a cut-off at 0.0001 < k < 0.001 Mpc -1 at 79.5 per cent (92 per cent), a dip at 0.001 < k < 0.003 Mpc -1 at 87.2 per cent (98 per cent) and a bump at 0.003 < k < 0.004 Mpc -1 at 90.3 per cent (55.5 per cent) confidence level. These frequentist confidence levels are calculated by integrating over the distribution of the Monte Carlo reconstructions built around the fiducial models. The frequentist analysis finds the low-k cut-off of the estimated power spectrum to be about 2. 5σ away from the n s = 0.97 model, while in the Bayesian analysis the model is about 1. 5σ away from the estimated spectrum. (The a values are different for the two different methods.).
Cby1 promotes Ahi1 recruitment to a ring-shaped domain at the centriole–cilium interface and facilitates proper cilium formation and function

Cby1 localizes to centrioles and antagonizes canonical Wnt signaling. Cby1−/− mice have cystic kidneys, and Cby1 facilitates primary cilium formation and ciliary recruitment of Arl13b. Cby1 localizes to a distal centriolar domain with Ofd1 and Ahi1, and the amount of Ahi1 at the transition zone is reduced in Cby1−/− cells.
Nonspecific Effect of Stress on Brain Gray Matter Volume in Drug-naive Female Patients with First Depressive Episode

Background:This study aimed to observe the differences in brain gray matter volume in drug-naive female patients after the first episode of major depression with and without stressful life events (SLEs) before the onset of depression. Methods:Forty-three drug-naive female patients voluntarily participated in the present study after the first major depressive episode. The life event scale was used to evaluate the severity of the impact of SLEs during 6 months before the onset of the major depressive episode. High-field magnetic resonance imaging (MRI) scans were obtained, and the VBM and SPM8 software process were used to process and analyze the MRI. Results:Compared to that in patients without SLEs, the volume of brain gray matter was lower in the bilateral temporal lobe, right occipital lobe, and right limbic lobe in the SLE group. However, the gray matter volume did not differ significantly between the two groups after the application of false discovery rate (FDR) correction. Conclusions:Although the results of the present study suggest the absence of significant differences in brain gray matter volume between female drug-naive patients after the first episode of major depression with and without SLEs after FDR correction, the study provides useful information for exploring the definitive role of stress in the onset of depression.
Representing and Solving Influence Diagram in Multi-Criteria Decision Making: A Loopy Belief Propagation Method

Bayesian network is a graphical model that encodes probabilistic relationships among variables of interest. When used in conjunction with statistical techniques, the graphical model has several advantages for data mining. Influence diagrams provide a compact technique to represent problems of decision making especially multi-criteria decision making (MCDM) under uncertainty. As a number of nodes in the network increases, computing exact solutions and making optimal decision becomes computationally intractable. Approximate solution becomes more efficient in term of the performance of execution and the storage space. Loopy belief propagation is the alternative way for approximate solution and is presented in this paper. A solution is approximated where high-probability actions under the policy have a high utility. Actions are then selected which have a high probability under the approximating policy. The loopy belief propagation method is shown to compare favorably to exact methods.
Model Formulation: Generic Data Modeling for Clinical Rrepositories

OBJECTIVE To construct a large-scale clinical repository that accurately captures a detailed understanding of the data vital to the process of health care and that provides highly efficient access to patient information for the users of a clinical information system. DESIGN Conventional approaches to data modeling encourage the development of a highly specific data schema in order to capture as much information as possible about a given domain. In contrast, current database technology functions most effectively for clinical databases when a generic data schema is used. The technique of "generic data modeling" is presented as a method of reconciling these opposing views of clinical data, using formal operations to transform a detailed schema into a generic one. RESULTS A complex schema consisting of hundreds of entities and representing a rich set of constraints about the patient care domain is transformed into a generic schema consisting of roughly two dozen tables. The resulting database design is efficient for patient-oriented queries and is highly flexible in adapting to the changing information needs of a health care institution, particularly changes involving the collection of new data elements. CONCLUSION Conventional approaches to data modeling can be used to develop rich, complex models of clinical data that are useful for understanding and managing the process of patient care. Generic data modeling techniques can successfully transform a detailed design into an efficient generic design that is flexible enough to meet the needs of an operational clinical information system.
Modeling and Analysis of Capillary Force Interaction for Common AFM Tip Shapes

This paper presents an analytical method to calculate the capillary force between AFM tip and the sample surface. For this purpose, several tip/substrate interactions including sphere/substrate, cone/substrate, truncated cone/substrate and two-sphere/substrate interactions are considered. Both equal and non-equal contact angles for liquid/solid interfaces are examined. Analytical models based on the energy method, for the capillary force between AFM tip and sample surface are developed and the efficiency of these models is investigated. Furthermore, the effect of several important parameters such as humidity, tip surface distance, tip geometry and contact angles on the meniscus force is studied. Experimental measurements confirm the precision and accuracy of the proposed models.
Emotion Detection in the Loop from Brain Signals and Facial Images

In this project, we intended to develop techniques for multimodal emotion detection, one modality being brain signals via fNIRS, the second modality being face video and the third modality being the scalp EEG signals. EEG and fNIRS provided us with an “internal” look at the emotion generation processes, while video sequence gave us an “external” look on the “same” phenomenon. Fusions of fNIRS with video and of EEG with fNIRS were considered. Fusion of all three modalities was not considered due to the extensive noise on the EEG signals caused by facial muscle movements, which are required for emotion detection from video sequences. Besides the techniques mentioned above, peripheral signals, namely, respiration, cardiac rate, and galvanic skin resistance were also measured from the subjects during “fNIRS + EEG” recordings. These signals provided us with extra information about the emotional state of the subjects. The critical point in the success of this project was to be able to build a “good” database. Good data acquisition means synchronous data and requires the definition of some specific experimental protocols for emotions elicitation. Thus, we devoted much of our time to data acquisition throughout the workshop, which resulted in a large enough database for making the first analyses. Results presented in this report should be considered as preliminary. However, they are promising enough to extend the scope of the research.
A primal-dual randomized algorithm for weighted paging

In the weighted paging problem there is a weight (cost) for fetching each page into the cache. We design a randomized O(log k) -competitive online algorithm for the weighted paging problem, where k is the cache size. This is the first randomized o(k)-competitive algorithm and its competitiveness matches the known lower bound on the problem. More generally, we design an O(log(k/(k - h + I)))-competitive online algorithm for the version of the. problem where, the online algorithm has-cache size k and the online algorithm has cache size h les k. Weighted paging is a special case (weighted star metric) of the well known k-server problem for which it is a major open question whether randomization can be useful in obtaining sub-linear competitive algorithms. Therefore, abstracting and extending the insights from paging is a key step in the resolution of the k-server problem. Our solution for the weighted paging problem is based on a two-step approach. In the first step we obtain an O(log k)-competitive fractional algorithm which is based on a novel online primal-dual approach. In the second step we. obtain a randomized algorithm by rounding online the fractional solution to an actual distribution on integral cache, solutions. We conclude with a randomized O(log N)-competitive algorithm for the well studied Metrical Task System problem (MTS) on a metric defined by a weighted star on N leaves, improving upon a previous O(log2 N)-competitive algorithm of Blum et al. [9].
Agent-Based User and Task Modelling for Seamless Information Access via Personal Digital Assistants

The paper describes a case study of how a combination of techniques, such as agent technologies, user, task and context modeling can be used to adapt a distributed application for mobile users with Personal Digital Assistants (PDAs) and support seamless connection and access to a centralized information system in areas of disconnection. In a domain where users have typical tasks and information needs related to these tasks it is possible, by keeping track of the users' current context (time and location through the user schedule) and a user class stereotype task model, to predict the user tasks and their information needs and to adapt both the functionality and the presentation information provided by the application. Two types of adaptation are important in a domain where there is no reliable connection: hiding from the user the disconnection and ensuring consistency of the data, which is added, deleted or modified by the user on her device during periods of disconnection. The case study’s target domain is the Saskatoon District Health Division, where homecare workers provided with iPaq PDAs equipped with CDPD cards retrieve patient information from centralized information system, make notifications for schedule changes and add new data into the information system, e.g. file reports. The prototype has been evaluated in a simulated environment with the goal to see if it provides seamless connection and access to data in conditions of disconnection.
Title: Complex Transcriptional Regulation and Independent Evolution of Fungal-like Traits 1 in a Relative of Animals 2 3

21 Cell-type specification through differential genome regulation is a hallmark of complex 22 multicellularity. However, it remains unclear how this process evolved during the transition from 23 unicellular to multicellular organisms. To address this question, we investigated transcriptional 24 dynamics in the ichthyosporean Creolimax fragrantissima, a relative of animals that undergoes 25 coenocytic development. We find that Creolimax utilizes dynamic regulation of alternative 26 splicing, long inter-genic non-coding RNAs and co-regulated gene modules associated with 27 animal multicellularity in a cell-type specific manner. Moreover, our study suggests that the 28 different cell types of the three closest animal relatives (ichthyosporeans, filastereans and 29 choanoflagellates) are the product of lineage-specific innovations. Additionally, a proteomic 30 survey of the secretome reveals adaptations to a fungal-like lifestyle. In summary, the diversity of 31 cell types among protistan relatives of animals and their complex genome regulation demonstrates 32 that the last unicellular ancestor of animals was already capable of elaborate specification of cell 33 types.
Leisure motivation of people with physical and visual disabilities in Ghana

Abstract Leisure motivation is central to the provision of leisure services especially to marginalised groups such as disabled people who may have different interests from non-disabled people. Using cross-sectional data from 536 people with physical and visual disabilities, this study assessed the leisure motivations of disabled people in Ghana. The findings suggest that the motivations of people with visual and physical disabilities were fourfold, namely competence mastery, social, intellectual, and stimulus avoidance. The influence of social motivation varied across marital status and household size, while stimulus avoidance varied by type of disability, sex, and employment status. Competence mastery and intellectual motivation varied across sex and income levels. It was concluded that the leisure motivations of disabled people in this study are based on their personal circumstances; they are heterogeneous. The study recommends that research on leisure motivation should be conducted with reference to specific context and interpreted in relation to the individual’s circumstances.
An analogue of the Chowla-Selberg formula for several automorphic L-functions

In this paper, we will give a certain formula for the Riemann zeta function that expresses the Riemann zeta function by an infinte series consisting of $K$-Bessel functions. Such an infinite series expression can be regarded as an analogue of the Chowla-Selberg formula. Roughly speaking, the Chowla-Selberg formula is the formula that expresses the Epstein zeta-function by an infinite series consisting of $K$-Bessel functions. In addition, we also give certain analogues of the Chowla-Selberg formula for Dirichlet $L$-functions and $L$-functions associated with holomorphic cusp forms. Moreover, we introduce a two variable function which is analogous to the real analytic Eisenstein series and give a certain limit formula for this one. Such a limit formula can be regarded as an analogue of Kronecker's limit formula.