Miracle-dz/UniFAR-FTUs huggingface dataset:
Hierarchical I/O Scheduling for Collective I/O

The non-contiguous access pattern of many scientific applications results in a large number of I/O requests, which can seriously limit the data-access performance. Collective I/O has been widely used to address this issue. However, the performance of collective I/O could be dramatically degraded in today's high-performance computing system due to the increasing shuffle cost caused by highly concurrent data accesses. This situation tends to be even worse as many applications become more and more data intensive. Previous research has primarily focused on optimizing I/O access cost in collective I/O but largely ignored the shuffle cost involved. In this study, we propose a new hierarchical I/O scheduling (HIO) algorithm to address the increasing shuffle cost in collective I/O. The fundamental idea is to schedule applications' I/O requests based on a shuffle cost analysis to achieve the optimal overall performance, instead of achieving optimal I/O accesses only. The algorithm is currently evaluated with the MPICH2 andPVFS2. Both theoretical analysis and experimental tests show that the proposed hierarchical I/O scheduling has a potential in addressing the degraded performance issue of collective I/O with highly concurrent accesses.
Effect of Assessment Method on the Discrepancy between Judgments of Health Disorders People have and do not have: A Web Study

Three experiments on the World Wide Web asked subjects to rate the severity of common health disorders such as acne or arthritis. People who had a disorder (“Haves”) tended to rate it as less severe than people who did not have it (“Not-haves”). Two explanations of this Have versus Not-have discrepancy were rejected. By one account, people change their reference point when they rate a disorder that they have. More precise reference points would, on this account, reduce the discrepancy, but, if anything, the discrepancy was larger. By another account, people who do not have the disorder focus on attributes that are most affected by it, and the discrepancy should decrease when people make ratings on several attributes. Again, if anything, the discrepancy increased when ratings were on separate attributes (combined by a weighted average). The discrepancy varied in size and direction across disorders. Subjects also thought that they would be less affected than others.
Randomization in Laboratory Procedure Is Key to Obtaining Reproducible Microarray Results

The quality of gene expression microarray data has improved dramatically since the first arrays were introduced in the late 1990s. However, the reproducibility of data generated at multiple laboratory sites remains a matter of concern, especially for scientists who are attempting to combine and analyze data from public repositories. We have carried out a study in which a common set of RNA samples was assayed five times in four different laboratories using Affymetrix GeneChip arrays. We observed dramatic differences in the results across laboratories and identified batch effects in array processing as one of the primary causes for these differences. When batch processing of samples is confounded with experimental factors of interest it is not possible to separate their effects, and lists of differentially expressed genes may include many artifacts. This study demonstrates the substantial impact of sample processing on microarray analysis results and underscores the need for randomization in the laboratory as a means to avoid confounding of biological factors with procedural effects.
Holobody galleries: blending augmented and virtual reality displays of human anatomy

In this paper, we propose a novel way to illustrate human anatomy by combining virtual and augmented reality display technologies. Our intention is to create an anatomy gallery, which blends real world anatomy specimens, in the form of 3D printed models, with virtual reality scenes, and use augmented reality technology to seamlessly move between these different modalities. Hand gesture interfaces are used to navigate and interact with the elements displayed in VR and in real. The project introduced here serves as a first step towards a multi-user, distributed exploration environment to experience, teach and learn about human anatomy, physiology and kinesiology.
THE PARADOXICAL EFFECTS OF PURSUING POSITIVE EMOTION When and Why Wanting to Feel Happy Backfi res

T he experience of positive emotion is generally associated with, and even leads to, positive outcomes (Fredrickson, Cohn, Coff ey, Pek, & Finkel, 2008; Lyubomirsky, King, & Diener, 2005; Seligman & Csikszentmihalyi, 2000). However, it is less clear what outcomes are associated with pursuing positive emotion. Exploring the correlates and eff ects of pursuing positive emotion is important and interesting for two reasons. First, many people want to feel positive emotion, and this goal is very important to them (Barrett, 1996; Diener, Sapyta, & Suh, 1998; Rusting & Larsen, 1995; Tamir & Ford, 2012a). Second, several lines of research suggest a surprising paradoxical eff ect: the more people pursue positive emotion, the less likely they are to experience positive outcomes, including well-being, psychological health, and feelings of happiness (Mauss, Savino, et al., 2011; Mauss, Tamir, Anderson, & Savino, 2011; Schooler, Ariely, & Loewenstein, 2003). Th is suggests that a common goal many people pursue—happiness—may lead to decreased well-being, psychological health, and happiness. Th is chapter reviews current fi ndings on the paradoxical eff ects of pursuing positive emotion, discusses possible mechanisms to explain these paradoxical eff ects, and suggests methods to avoid them. Th is chapter focuses on happiness as a commonly pursued and commonly studied positive emotion and explores three key mechanisms for the paradoxical eff ects of pursuing happiness. First, as people pursue happiness, they tend to set high standards for their happiness. Th is can cause discontent (and lowered happiness) when their current state falls short of those
Adaptive Cache and Concurrency Allocation on GPGPUs

Memory bandwidth is critical to GPGPU performance. Exploiting locality in caches can better utilize memory bandwidth. However, memory requests issued by excessive threads cause cache thrashing and saturate memory bandwidth, degrading performance. In this paper, we propose adaptive cache and concurrency allocation (CCA) to prevent cache thrashing and improve the utilization of bandwidth and computational resources, hence improving performance. According to locality and reuse distance of access patterns in GPGPU program, warps on a stream multiprocessor are dynamically divided into three groups: cached, bypassed, and waiting. The data cache accommodates the footprint of cached warps. Bypassed warps cannot allocate cache lines in the data cache to prevent cache thrashing, but are able to take advantage of available memory bandwidth and computational resource. Waiting warps are de-scheduled. Experimental results show that adaptive CCA can significant improve benchmark performance, with 80 percent harmonic mean IPC improvement over the baseline.
Exploring the Genetic Signature of Body Size in Yucatan Miniature Pig

Since being domesticated about 10,000–12,000 years ago, domestic pigs (Sus scrofa domesticus) have been selected for traits of economic importance, in particular large body size. However, Yucatan miniature pigs have been selected for small body size to withstand high temperature environment and for laboratory use. This renders the Yucatan miniature pig a valuable model for understanding the evolution of body size. We investigate the genetic signature for selection of body size in the Yucatan miniature pig. Phylogenetic distance of Yucatan miniature pig was compared to other large swine breeds (Yorkshire, Landrace, Duroc and wild boar). By estimating the XP-EHH statistic using re-sequencing data derived from 70 pigs, we were able to unravel the signatures of selection of body size. We found that both selections at the level of organism, and at the cellular level have occurred. Selection at the higher levels include feed intake, regulation of body weight and increase in mass while selection at the molecular level includes cell cycle and cell proliferation. Positively selected genes probed by XP-EHH may provide insight into the docile character and innate immunity as well as body size of Yucatan miniature pig.
USING SELF-EXPLANATION STRATEGY TO IMPROVE STUDENTS' UNDERSTANDING OF THE TO BE LEARNED MATERIAL

Abstrak : Teori belajar kognitif dan kostructivisme memiliki padangan yang berbeda dengan teori belajar tradisional. Anak didik tidak dipandang sebagai penerima informasi yang pasif, akan tetapi mereka secara aktif mengkonstruksi pengetahuan. S elf-explanation adalah strategi belajar yang mendukung asumsi pembelajaran tersebut dan merupakan kegiatan konstruktif yang mendukung terintegrasinya pengetahuan baru dengan pengetahuan awal anak didik dengan baik. Penggunaan strategi ini dapat membantu anak didik memiliki representasi pengetahuan yang komprehensif, menfasilitasi pemahaman yang mendalam terhadap materi yang dipelajari, dan kemudahan dalam pengaksesan kembali informasi yang telah di simpan dalam memori. Abstract : Cognitive and constructivism learning theory have different views with traditional learning theory. Students are not viewed as passive recipients of information, but they actively construct knowledge. Self-explanation is a learning strategy that supports this learning assumption, and it is a constructive activity that supports the integration of new knowledge with prior knowledge of students well. The use of this strategy can help students to have a comprehensive knowledge representation facilitating in-depth understanding of the material being studied, and the ease in accessing back the information that is stored in memory.
Charophytes: Evolutionary Giants and Emerging Model Organisms

Charophytes are the group of green algae whose ancestral lineage gave rise to land plants in what resulted in a profoundly transformative event in the natural history of the planet. Extant charophytes exhibit many features that are similar to those found in land plants and their relatively simple phenotypes make them efficacious organisms for the study of many fundamental biological phenomena. Several taxa including Micrasterias, Penium, Chara, and Coleochaete are valuable model organisms for the study of cell biology, development, physiology and ecology of plants. New and rapidly expanding molecular studies are increasing the use of charophytes that in turn, will dramatically enhance our understanding of the evolution of plants and the adaptations that allowed for survival on land. The Frontiers in Plant Science series on “Charophytes” provides an assortment of new research reports and reviews on charophytes and their emerging significance as model plants.
Mobile robot localization using an electronic compass for corridor environment

This paper proposes a simple method for localization using an electronic compass. Electronic compasses are often used to detect the heading of mobile robots. However, electronic compasses have one drawback when used inside a building: they can easily be disturbed by electromagnetic sources (e.g., power lines) or large ferro-magnetic structures (e.g., bookshelves). However, this paper introduces another indoor application of electronic compasses. We take advantage of the magnetic field disturbances by using them as distinctive place recognition signatures. We first gather information about the changing heading as our robot travels along the hallway outside the lab, and then store this information. As the robot traverses the hallway, it gathers the information from the electronic compass and matches it with the pre-stored data. If a match is found, the robot can determine its current position. We use a sequential least-squares approximation approach for matching the signature. The simulation results will show that the robot can distinguish its location by using these signatures.
Prognostic value of circulating chromogranin A levels in acute coronary syndromes

Aims To determine whether circulating levels of chromogranin A (CgA) provide prognostic information independently of conventional risk markers in acute coronary syndromes (ACSs). Methods and results We measured circulating CgA levels on day 1 in 1268 patients (median age 67 years, 70% male) with ACS admitted to a single coronary care unit of a Scandinavian teaching hospital. The merit of CgA as a biomarker was evaluated after adjusting for conventional cardiovascular risk factors. During a median follow-up of 92 months, 389 patients (31%) died. The baseline CgA concentration was strongly associated with increased long-term mortality [hazard ratio per 1 standard deviation increase in logarithmically transformed CgA level: 1.57 (1.44–1.70), P < 0.001], heart failure hospitalizations [1.54 (1.35–1.76), P < 0.001], and recurrent myocardial infarction (MI) [1.27 (1.10–1.47), P < 0.001], but not stroke. After adjustment for conventional cardiovascular risk markers, the association remained significant for mortality [hazard ratio 1.28 (1.15–1.42), P < 0.001] and heart failure hospitalization [hazard ratio 1.24 (1.04–1.47), P = 0.02], but not recurrent MI. Conclusion CgA is an independent predictor of long-term mortality and heart failure hospitalizations across the spectrum of ACSs and provides incremental prognostic information to conventional cardiovascular risk markers.
A model of multi-scale perceptual organization in information graphics

We propose a new method for assessing the perceptual organization of information graphics, based on the premise that the visual structure of an image should match the structure of the data it is intended to convey. The core of our method is a new formal model of one type of perceptual structure, based on classical machine vision techniques for analyzing an image at multiple resolutions. The model takes as input an arbitrary grayscale image and returns a lattice structure describing the visual organization of the image. We show how this model captures several aspects of traditional design aesthetics, and we describe a software tool that implements the model to help designers analyze and refine visual displays. Our emphasis here is on demonstrating the model's potential as a design aid rather than as a description of human perception, but given its initial promise we propose a variety of ways in which the model could be extended and validated.
Advertising's Role in Capitalist Markets: What Do We Know and Where Do We Go from Here?

ABSTRACT Advertising is a rich, multidimensional phenomenon that has been studied in several disciplines. This research has led to an emerging body of findings and some potential generalizations. Even then, misconceptions about advertising persist, and important aspects of the phenomenon have not been adequately researched. Despite advertising's apparent weakness it is essential for free markets.
A Preliminary Experiment of Tweet Filtering by Back Propagation

It happens that one you are following in Twitter has several aspects in his personality. Suppose we are so attracted by his bright aspect that we are following his tweets. Then we have to endure dirty tweets from his dark side. In attempt to construct Twitter client software that filters out dirty tweets (from our point of view), we trained neural networks of different depths by the standard back propagation algorithm and tested if they can tell preferable tweets from dirty ones. The result says that the shallow network having only two hidden layers and more than 32 and 64 units per layer achieves over 96% and 97% of accuracy, respectively.
Making Mosquito Taxonomy Useful: A Stable Classification of Tribe Aedini that Balances Utility with Current Knowledge of Evolutionary Relationships

The tribe Aedini (Family Culicidae) contains approximately one-quarter of the known species of mosquitoes, including vectors of deadly or debilitating disease agents. This tribe contains the genus Aedes, which is one of the three most familiar genera of mosquitoes. During the past decade, Aedini has been the focus of a series of extensive morphology-based phylogenetic studies published by Reinert, Harbach, and Kitching (RH&K). Those authors created 74 new, elevated or resurrected genera from what had been the single genus Aedes, almost tripling the number of genera in the entire family Culicidae. The proposed classification is based on subjective assessments of the “number and nature of the characters that support the branches” subtending particular monophyletic groups in the results of cladistic analyses of a large set of morphological characters of representative species. To gauge the stability of RH&K’s generic groupings we reanalyzed their data with unweighted parsimony jackknife and maximum-parsimony analyses, with and without ordering 14 of the characters as in RH&K. We found that their phylogeny was largely weakly supported and their taxonomic rankings failed priority and other useful taxon-naming criteria. Consequently, we propose simplified aedine generic designations that 1) restore a classification system that is useful for the operational community; 2) enhance the ability of taxonomists to accurately place new species into genera; 3) maintain the progress toward a natural classification based on monophyletic groups of species; and 4) correct the current classification system that is subject to instability as new species are described and existing species more thoroughly defined. We do not challenge the phylogenetic hypotheses generated by the above-mentioned series of morphological studies. However, we reduce the ranks of the genera and subgenera of RH&K to subgenera or informal species groups, respectively, to preserve stability as new data become available.
Behavioral Study of UNIX Commands in a Faulty Environment

In this paper we propose the use of two approaches to tackle the detection and comprehension of how a faulty environment affects process behavior. We model processes as state-transition models with associated transition probabilities. The study employs SWIFI (Software Implemented Fault Injection) in commonly used UNIX tools to analyze behavioral changes. The approaches complement each other as one allows the detection of dissimilar behaviors and the other the analysis of how relationships among process states evolve over time. Obtained results are promising, as they allow a clear characterization of process execution in a normal and a faulty environment.
RHM2 Is Involved in Mucilage Pectin Synthesis and Is Required for the Development of the Seed Coat in Arabidopsis

Pectins are major components of primary plant cell walls and the seed mucilage of Arabidopsis. Despite progress in the structural elucidation of pectins, only very few enzymes participating in or regulating their synthesis have been identified. A first candidate gene involved in the synthesis of pectinaceous rhamnogalacturonan I is RHM2, a putative plant ortholog to NDP-rhamnose biosynthetic enzymes in bacteria. Expression studies with a promoter β-glucuronidase construct and reverse transcription PCR data show that RHM2 is expressed ubiquitously. Rhm2 T-DNA insertion mutant lines were identified using a reverse genetics approach. Analysis of the rhm2 seeds by various staining methods and chemical analysis of the mucilage revealed a strong reduction of rhamnogalacturonan I in the mucilage and a decrease of its molecular weight. In addition, scanning electron microscopy of the seed surface indicated a distorted testa morphology, illustrating not only a structural but also a developmental role for RGI or rhamnose metabolism in proper testa formation.
Harnessing Mobile Multiple Access Efficiency with Location Input

Benefiting from the abundant sensor hints of current mobile devices, their location information has become pervasively available and easy to access. As smartphones and tablets have become recently the main access devices of 802.11-based WLAN, location information provides large opportunity to improve the performance of underlying wireless communication. This paper presents CO-MAP (Co-Occurrence MAP) which leverages the position of devices to handle exposed and hidden terminal problems in mobile WLANs so as to improve the multiple access efficiency. With the location information, CO-MAP rapidly builds a co-occurrence map showing which two links can occur concurrently. Meanwhile, it selects the best settings of frame transmissions based on a novel analytical network model when hidden terminals are distinguished. CO-MAP improves the goodputs of both downlinks and uplinks in instant and distributed manner. Our implementation on a testbed of 6 laptops demonstrates that CO-MAP can accurately detect potential hidden and exposed interferers, and provide a large gain of goodput for both exposed terminal and hidden terminal scenarios. The simulation results of large scale networks on NS-2 also suggest that imperfect position hints can still bring substantial improvement on the multiple access efficiency.
Determination of the Number of Principal Directions in a Biologically Plausible PCA Model

Adaptively determining an appropriate number of principal directions for principal component analysis (PCA) neural networks is an important problem to address when one uses PCA neural networks for online feature extraction. In this letter, inspired from biological neural networks, a single-layer neural network model with lateral connections is proposed which uses an improved generalized Hebbian algorithm (GHA) to address this problem. In the proposed model, the number of principal directions can be adaptively determined to approximate the intrinsic dimensionality of the given data set so that the dimensionality of the data set can be reduced to approach the intrinsic dimensionality to any required precision through the network
Practical Guidelines for Ultrasound-Guided Core Needle Biopsy of Soft-Tissue Lesions: Transformation from Beginner to Specialist

Ultrasound-guided core needle biopsy (US-CNB) is an important step in the diagnosis of musculoskeletal soft-tissue lesions. To maximize efficacy and minimize the complications of US-CNB, it is critical to collaborate with a multidisciplinary team and to understand the particular considerations of US-CNB for these lesions. The purpose of this article is to provide a systematic review and step-by-step tips for using US-CNB to diagnose musculoskeletal soft-tissue lesions.
Research on a novel MAS for decision making method

The use of multiple intelligent agents in the decision support systems has become common. However, there are many questions in this field, such as the consensus of the agents and the method on choosing the best decision. In order to solve these problems, this paper provides a method, which uses the fuzzy aggregation operator to aggregate the opinions of the agents, ranks the alterative with the fuzzy preference relations, and then chooses the best alternative. This approach can be widely used in many fields.
Frame-Weighted Bayes Factor Scoring for Speaker Verification

In this paper, the Bayes factor is considered as a replacement verification criterion to the likelihood-ratio test in the context of GMM-based speaker verification. An advantage of this Bayesian method is that it allows for the incorporation of prior information and uncertainty of parameter estimates into the scoring process, complementing the Bayesian adaptation used in training. A development of Bayes factors for GMMs is presented based on incremental adaptation that is well-suited to inclusion in existing GMM-UBM systems. This method is extended to include the weighting of test frames to account for their statistical dependencies. Experiments on the 1999 NIST Speaker Recognition Evaluation corpus demonstrate improved performance over expected log-likelihood ratio scoring. These findings are supported with results from a modified version of the NIST Extended Data corpus of 2003.