Miracle-dz/UniFAR-FTUs huggingface dataset:
Using codewords to protect database data from a class of software errors

Increasingly, for extensibility and performance, special-purpose application code is being integrated with database system code. Such application code has direct access to database system buffers and, as a result, the danger of data being corrupted due to inadvertent application writes is increased. Previously proposed hardware techniques to protect data from corruption required system calls, and their performance depended on the details of the hardware architecture. We investigate an alternative approach which uses codewords associated with regions of data to detect corruption and to prevent corrupted data from being used by subsequent transactions. We develop several such techniques which vary in the level of protection, space overhead, performance and impact on concurrency. These techniques are implemented in the Dali/spl acute/ main-memory storage manager, and the performance impact of each on normal processing is evaluated. Novel techniques are developed to recover when a transaction has read corrupted data caused by a bad write, and then gone on to write other data in the database. These techniques use limited and relatively low-cost logging of transaction reads to trace the corruption, and may also prove useful when resolving problems caused by incorrect data entry and other logical errors.
Gender Interaction in Teams: Experimental Evidence on Performance and Punishment Behavior

This paper reports results from a real-e ort experiment in which men and women are paired to form a two-member team and asked to execute a real-eff ort task. Each participant receives an equal share of the team's output. Workers who perform better than their partner can punish him/her by imposing a fi ne. We manipulate the teams' gender composition (man-man, man-woman, and woman-woman) to analyze whether an individual's performance and sanctioning behavior depends on his/her gender and the gender interaction within the team. The data show that, on average, men perform slightly better than women. A man's performance will deteriorate when paired with a woman, while a woman's performance will improve when paired with a woman. When underperforming, women are sanctioned more often and more heavily than men; if sanctioned, men tend to improve their performance, while women's performance does not change.
Jumping control for compliantly actuated multilegged robots

A feedback control to generate jumping motions for compliantly actuated multilegged robots is proposed. The method allows to specify the direction of the jumping motion. This is achieved by a constraint that defines a one-dimensional submanifold and a bang-bang control which generates a limit cycle on this submanifold. The approach is based on classical impedance control with the difference that the stiffness on the submanifold and the force to preserve a predefined nominal body configuration result from the intrinsic mechanical springs in the joints. Furthermore, we propose two controller implementations: the first implementation does not require to detect the contact state, while the second implementation requires contact state detection, but accounts in addition for Coulomb friction constraints. The controller is validated in simulation with a compliantly actuated quadruped.
Effects of Part- and Whole-Object Primes on Early MEG Responses to Mooney Faces and Houses

Results from neurophysiological experiments suggest that face recognition engages a sensitive mechanism that is reflected in increased amplitude and decreased latency of the MEG M170 response compared to non-face visual targets. Furthermore, whereas recognition of objects (e.g., houses) has been argued to be based on individual features (e.g., door, window), face recognition may depend more on holistic information. Here we analyzed priming effects of component and holistic primes on 20 participants' early MEG responses to two-tone (Mooney) images to determine whether face recognition in this context engages “featural” or “configural” processing. Although visually underspecified, the Mooney images in this study elicited M170 responses that replicate the typical face vs. house effect. However, we found a distinction between holistic vs. component primes that modulated this effect dependent upon compatibility (match) between the prime and target. The facilitatory effect of holistic faces and houses for Mooney faces and houses, respectively, suggests that both Mooney face and house recognition—both low spatial frequency stimuli—are based on holistic information.
Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques.
The Predictive Value of the NEO-FFI Items: Parsing the Nature of Social Anhedonia Using the Revised Social Anhedonia Scale and the ACIPS

The goal was to examine the nature of social anhedonia using two validated measures and study their relationship to scores on the NEO-Five Factor Inventory (NEO-FFI). Nearly 1,900 college-aged participants completed the Chapman Revised Social Anhedonia Scale (RSAS), Anticipatory and Consummatory Interpersonal Pleasure Scale (ACIPS), and the NEO-FFI. Although both the RSAS and ACIPS were associated with the NEO-FFI domains of Extraversion, Agreeableness, and Neuroticism, linear regression analyses revealed that the RSAS and ACIPS were differentially predicted by NEO-FFI item clusters. The RSAS scores were predicted by Sociability, Nonantagonistic Orientation, Positive Affect, and Activity item clusters. The ACIPS scores were predicted by Sociability, Prosocial Orientation, Activity, and Positive Affect item clusters in addition to gender. In summary, it appears that social anhedonia is multidimensional, associated with various personality domains encompassing social approach and withdrawal.
A Quantitative Estimate of Schema Abnormality in Socially Anxious and Non‐Anxious Individuals

Although cognitive theories of anxiety suggest that anxious individuals are characterized by abnormal threat‐relevant schemas, few empirical studies have estimated the nature of these cognitive structures using quantitative methods that lend themselves to inferential statistical analysis. In the present study, socially anxious (n = 55) and non‐anxious (n = 62) participants completed 3 Q‐Sort tasks to assess their knowledge of events that commonly occur in social or evaluative scenarios. Participants either sorted events according to how commonly they personally believe the events occur (i.e. “self” condition), or to how commonly they estimate that most people believe they occur (i.e. “other” condition). Participants' individual Q‐Sorts were correlated with mean sorts obtained from a normative sample to obtain an estimate of schema abnormality, with lower correlations representing greater levels of abnormality. Relative to non‐anxious participants, socially anxious participants' sorts were less strongly associated with sorts of the normative sample, particularly in the “self” condition, although secondary analyses suggest that some significant results might be explained, in part, by depression and experience with the scenarios. These results provide empirical support for the theoretical notion that threat‐relevant self‐schemas of anxious individuals are characterized by some degree of abnormality.
Creating Learning Centered Classrooms. What Does Learning Theory Have To Say? ERIC Digest.

Creating Learning Centered Classrooms. What Does Learning Theory Have To Say? ERIC Digest.2 WHAT THEORIES AND FRAMEWORKS ARE RELEVANT TO LEARNING IN.2 WHAT DO WE KNOW ABOUT COLLEGE STUDENTS' LEARNING? 3 WHAT PRACTICES PROMOTE LEARNING AMONG COLLEGE STUDENTS? 3 WHAT ADDITIONAL QUESTIONS MUST BE ANSWERED? 4 REFERENCES. 4
Influence of TiO2 Nanoparticles on Growth and Phenolic Compounds Production in Photosynthetic Microorganisms

The influence of titanium dioxide nanoparticles (pure anatase and 15% N doped anatase) on the growth of Chlorella vulgaris, Haematococcus pluvialis, and Arthrospira platensis was investigated. Results showed that pure anatase can lead to a significant growth inhibition of C. vulgaris and A. platensis (17.0 and 74.1%, resp.), while for H. pluvialis the nanoparticles do not cause a significant inhibition. Since in these stress conditions photosynthetic microorganisms can produce antioxidant compounds in order to prevent cell damages, we evaluated the polyphenols content either inside the cells or released in the medium. Although results did not show a significant difference in C. vulgaris, the phenolic concentrations of two other microorganisms were statistically affected by the presence of titanium dioxide. In particular, 15% N doped anatase resulted in a higher production of extracellular antioxidant compounds, reaching the concentration of 65.2 and 68.0 mg gDB −1 for H. pluvialis and A. platensis, respectively.
Integrating Machine Translation with Translation Memory: A Practical Approach

The purpose of this work is to show how machine translation can be integrated into professional translation environments using two possible workflows. In the first workflow we demonstrate the real-time, sentence-by-sentence use of both rule-based and statistical machine translation systems with translation memory programs. In the second workflow we present a way of applying machine translation to full translation projects beforehand. We also compare and discuss the efficiency of statistical and rule-based machine translation systems, and propose some ideas about how these systems could be combined with translation memory technologies into a unified translation application.
The Field behind the Screen: Using Netnography for Marketing Research in Online Communities

The author develops “netnography” as an online marketing research technique for providing consumer insight. Netnography is ethnography adapted to the study of online communities. As a method, netnography is faster, simpler, and less expensive than traditional ethnography and more naturalistic and unobtrusive than focus groups or interviews. It provides information on the symbolism, meanings, and consumption patterns of online consumer groups. The author provides guidelines that acknowledge the online environment, respect the inherent flexibility and openness of ethnography, and provide rigor and ethics in the conduct of marketing research. As an illustrative example, the author provides a netnography of an online coffee newsgroup and discusses its marketing implications.
The responses of neural stem cells to the level of GSK-3 depend on the tissue of origin

Summary Neural stem cells (NSCs) can be obtained from a variety of sources, but not all NSCs exhibit the same characteristics. We have examined how the level of glycogen synthase kinase-3 activity regulates NSCs obtained from different sources: the mouse embryonic striatum, embryonic hippocampus, and mouse ES cells. Growth of striatal NSCs is enhanced by mild inhibition of GSK-3 but not by strong inhibition that is accompanied by Wnt/TCF transcriptional activation. In contrast, the growth of hippocampal NSCs is enhanced by both mild inhibition of GSK-3 as well as stronger inhibition. Active Wnt/TCF signaling, which occurs normally in the embryonic hippocampus, is required for growth of neural stem and progenitor cells. In the embryonic striatal germinal zone, however, TCF signaling is normally absent and its activation inhibits growth of NSCs from this region. Using a genetic model for progressive loss of GSK-3, we find that primitive ES cell-derived NSCs resemble striatal NSCs. That is, partial loss of GSK-3 alleles leads to an increase in NSCs while complete ablation of GSK-3, and activation of TCF-signaling, leads to their decline. Furthermore, expression of dominant negative TCF-4 in the GSK-3-null background was effective in blocking expression of Wnt-response genes and was also able to rescue neuronal gene expression. These results reveal that GSK-3 regulates NSCs by divergent pathways depending on the tissue of origin. The responses of these neural precursor cells may be contingent on baseline Wnt/TCF signaling occurring in a particular tissue.
Sensing the sensor web

The maturity of pervasive computing and Wireless Sensor Networks (WSNs) enables the development of smart environments in many scenarios, including surveillance and environmental monitoring. Extensive research efforts are being undertaken in sensor perception, data capture, management and interpretation. Such developments are a prerequisite for paradigms such as pervasive sensing and crowd-sourcing services. For mobile users, the issues of dynamic sensor discovery, data interpretation and visualization must be addressed if such services are to be realized in practice. This paper explores the genesis of a generic framework for heterogeneous sensor access and data visualization in remote contexts.
D-RES: Correct transitive distributed service sharing

With the growth of complexity in the embedded domain, the use of distributed systems to support multiple realtime applications has become commonplace. These applications may share processor and network resources, and real-time scheduling policies can guarantee that these applications do not interfere with each other's ability to meet their temporal constraints. We believe that these applications should also be able to transparently share services and chains of services, without the coupling that such sharing typically implies. To solve this problem, we propose D-RES, a resource management system that guarantees temporal isolation between service-sharing applications in a distributed system. D-RES transparently tracks which application uses which service, billing the correct application even in case of nested service calls. We implemented D-RES, and demonstrate its ability to isolate service-sharing applications even in case of overload.
Harvest Pressure on Coastal Atlantic Cod (Gadus morhua) from Recreational Fishing Relative to Commercial Fishing Assessed from Tag-Recovery Data

Marine recreational fishing is a popular outdoor activity. However, knowledge about the magnitude of recreational catches relative to commercial catches in coastal fisheries is generally sparse. Coastal Atlantic cod (Gadus morhua) is a target species for recreational fishers in the North Atlantic. In Norway, recreational fishers are allowed to use a variety of traps and nets as well as long-line and rod and line when fishing for cod. From 2005 to 2013, 9729 cod (mean size: 40 cm, range: 15–93 cm) were tagged and released in coastal Skagerrak, southeast Norway. Both high-reward (NOK 500) and low-reward tags (NOK 50) were used in this study. Because some harvested fish (even those posting high-reward tags) may go unreported by fishers, reporting rates were estimated from mark-recovery models that incorporate detection parameters in their structure, in addition to survival and mortality estimates. During 2005 to 2013, a total of 1707 tagged cod were recovered and reported by fishers. We estimate the overall annual survival to be 33% (SE 1.5). Recreational rod and line fishing were responsible for 33.7% (SE 2.4) of total mortality, followed by commercial fisheries (15.1% SE 0.8) and recreational fixed gear (6.8% SE 0.4). Natural mortality was 44.4% (SE 2.5) of total mortality. Our findings suggest that recreational fishing—rod and line fishing in particular—is responsible for a substantial part of fishing mortality exerted on coastal cod in southern Norway.
Ontogeny of Cloned Cattle to Lactation

Abstract Central to the success of large animal cloning is the production of healthy animals that can provide products for human health, food, and other animal agriculture applications. We report development of cloned cattle derived from 34 genetically unique, nonembryonic cell lines using nuclear transfer performed between 1 January 1998 and 29 February 2000. Nearly 25% (535/2170) of the recipients receiving reconstructed embryos initiated pregnancy. Overall, 19.8% (106/535) of the initiated pregnancies resulted in live births, while 77% (82/106) of these cattle clones remain healthy and productive today. Although a wide variation in birth weight of clone calves was observed, their growth rates, reproductive performance, and lactation characteristics are similar to that found in noncloned dairy cattle. Our data represent the most comprehensive information on cattle derived from nuclear transfer procedures and indicate that this emerging reproductive technology offers unique opportunities to meet critical needs in both human health care and agriculture.
Asynchronous and reliable on-demand media broadcast

We discuss wireless broadcasting of multimedia streams within a framework that allows asynchronous media access. Receivers subscribe at any time to the ongoing broadcast session, but are still able to display the media stream from the beginning. A fully scalable broadcasting scheme is presented where the media stream is appropriately segmented, and segments are protected by fountain codes. Erasure-based decoding as well as soft decoding is discussed. Asynchronous data reception and full reliability are achieved at the same time. Depending on its receiving conditions, the receiver adapts its initial playout delay to guarantee high reliability of successful playout
A decomposition storage model

This report examines the relative advantages of a storage model based on decomposition (of community view relations into binary relations containing a surrogate and one attribute) over conventional n-ary storage models There seems to be a general consensus among the database community that the n-ary approach is better This conclusion is usually based on a consideration of only one or two dimensions of a database system The purpose of this report is not to claim that decomposition is better Instead, we claim that the consensus opinion is not well founded and that neither is clearly better until a closer analysis is made along the many dimensions of a database system The purpose of this report is to move further in both scope and depth toward such an analysis We examine such dimensions as simplicity, generality, storage requirements, update performance and retrieval performance
Use of Time- and Frequency-Domain Approaches for Damage Detection in Civil Engineering Structures

The aim of this paper is to apply both time- and frequency-domain-based approaches on real-life civil engineering structures and to assess their capability for damage detection. The methodology is based on Principal Component Analysis of the Hankel matrix built from output-only measurements and of Frequency Response Functions. Damage detection is performed using the concept of subspace angles between a current (possibly damaged state) and a reference (undamaged) state. The first structure is the Champangshiehl Bridge located in Luxembourg. Several damage levels were intentionally created by cutting a growing number of prestressed tendons and vibration data were acquired by the University of Luxembourg for each damaged state. The second example consists in reinforced and prestressed concrete panels. Successive damages were introduced in the panels by loading heavy weights and by cutting steel wires. The illustrations show different consequences in damage identification by the considered techniques.
How Much Noise in Text is too Much : A Study in Automatic Document Classification Submitted for Blind Review

Noise is a stark reality in real life data. Especially in the domain of text analytics it has a significant impact as data cleaning forms a very large part (upto 80% time) of the data processing cycle. Noisy unstructured text is common in informal settings such as on-line chat, SMS, email, newsgroups and blogs, automatically transcribed text from speech data, and automatically recognized text from printed or handwritten material. Gigabytes of such data is being generated everyday on the Internet, in contact centers, and on mobile phones. Researchers have looked at various text mining issues such as pre-processing and cleaning noisy text, information extraction, rule learning, and classification for noisy text. This paper focuses on the issues faced by automatic text classifiers in analyzing noisy documents coming from various sources. The goal of this paper is to bring out and study the effect of different kinds of noise on automatic text classification. Does the nature of such text warrant moving beyond traditional text classification techniques? We present detailed experimental results on simulated noise on benchmark datasets viz. Reuters-21578 and 20-newsgroups. We also present interesting results on real life noisy datasets from various contact center domains.
To agent-based simulation from System Dynamics

Agent-based simulation (ABS) is a recent modeling technique that is being widely used in modeling complex social systems. Forrester's System Dynamics (SD) is another longstanding technique for modeling social systems. Several classical models of systems, such as the Kermack-McKendrick model of epidemiology, the Lotka-Volterra equations for modeling predator-prey relationships, and the Bass model for innovation diffusion are formulated as systems of differential equations and have corresponding System Dynamics representations as difference equations. The ABS and SD modeling approaches take fundamentally different perspectives when modeling a system, which can be characterized as bottom-up (ABS) versus top-down (SD). Yet many systems can be equivalently modeled by either approach. In this paper, we present a formal specification for SD and ABS models, use the specification to derive equivalent ABS representations, and present an example of an SIR epidemic model having SD and ABS counterparts.
Integer Multiplication with Overflow Detection or Saturation

High-speed multiplication is frequently used in general-purpose and application-specific computer systems. These systems often support integer multiplication, where two n-bit integers are multiplied to produce a 2n-bit product. To prevent growth in word length, processors typically return the n least significant bits of the product and a flag that indicates whether or not overflow has occurred. Alternatively, some processors saturate results that overflow to the most positive or most negative representable number. This paper presents efficient methods for performing unsigned or two's complement integer multiplication with overflow detection or saturation. These methods have significantly less area and delay than conventional methods for integer multiplication with overflow detection or saturation.