Miracle-dz/UniFAR-FTUs huggingface dataset:
Book Review: Meta Analysis: A Review and A New View

From its inception in the social science literature, metaanalysis has become a popular methodology. One might even call it a minor industry. Some view it as the wave of the future, others consider it a disaster. But as with most extreme points of view, the truth probably lies somewhere in between. What is somewhat perplexing is why this topic has generated so much controversy. Surely comparable deficiencies exist in many other statistical procedures. Perhaps the name appears to be somewhat pretentious, all-encompassing, guaranteeing new insights. The name macro-analysis (in contrast to micro-analysis) might have been less provocative. One of the most commonly stated criticisms of metaanalysis is that it may assume away differences among studies and be insensitive to the pitfalls of combining studies. It is also noted that one cannot obtain good results from a collection of poor studies. These reasonable caveats might well be applied to all science. In spite of criticisms of particular methods of cumulation, the fact remains that science is cumulative. Even the "hardest" of sciences, such as physics, have produced numerous published determinations of physical constants such as those concerned with gravitational force, dating from experiments by Cavendish in 1798 to present-day research. Synthesis of past results is central to almost any research, and indeed, it is unthinkable to embark on any current research without regard for, and integration of, the past. One might argue that altogether too many papers quote previous work without much verification of the conclusions. As with almost any
Attachment and Growth of Human Rotaviruses RV-3 and S12/85 in Caco-2 Cells Depend on VP4

ABSTRACT Studies with human neonatal rotaviruses RV-3 and S12/85 and their reassortants showed that VP4 is a determinant of rotavirus attachment to and growth in Caco-2 cells. The binding of these viruses to MA104 and Caco-2 cells correlated with their growth ability. Virus sensitivity to trypsin and the VP4 fusion region may be implicated in these processes.
Elastic management of cluster-based services in the cloud

In this paper we analyze the deployment of generic clustered services on top of a virtualized infrastructure layer that combines a VM manager (the OpenNebula engine) and a cloud resource provider (Amazon EC2). The use of this virtualization layer between the service and the physical infrastructure extends the classical benefits of VM platforms to distributed infrastructures. Additionally, the integration of the cloud in this layer allows us to give additional capacity to the services using an external provider, thus complementing the local infrastructure without notice from the users or affecting the service workload. This flexible approach, which separates the resource provisioning from the service management, provides important benefits: elastic service capacity to adapt it to its dynamic workload; physical infrastructure partitioning to isolate it from other running services; and support for heterogeneous configurations tailored for each service class. The feasibility of the proposed approach is analyzed for two different clustered services: a classical computing cluster and a web server.
Adhesion-dependent protein tyrosine phosphorylation in neutrophils treated with tumor necrosis factor

Human neutrophils (PMN) respond to tumor necrosis factor (TNF) by releasing their granules, reorganizing their cytoskeleton, and massively secreting hydrogen peroxide. This response is dependent on adhesion to extracellular matrix proteins and expression of CD11b/CD18 integrins (Nathan, C., S. Srimal, C. Farber, E. Sanchez, L. Kabbash, A. Asch, J. Gailit, and S. D. Wright. 1989. J. Cell Biol. 109:1341-1349). We investigated the role of tyrosine phosphorylation in the response of PMN to TNF. PMN adherent to protein-coated surfaces but not suspended PMN showed tyrosine phosphorylation of several proteins (approximately 150, approximately 115, approximately 75, and approximately 65 kD) in response to TNF. Tyrosine phosphorylation was evident 5 min after addition of TNF and lasted at least 2 h. The tyrosine kinase inhibitors K252a, genistein and ST638 suppressed tyrosine phosphorylation and blocked hydrogen peroxide production in a reversible manner at low concentrations. Tyrosine kinase inhibitors also blocked the spreading of PMN in response to TNF. Dihydrocytochalasin B did not inhibit tyrosine phosphorylation, but in its presence phosphorylation was rapidly reversed. By immunocytochemistry, the majority of tyrosine phosphoproteins were localized to focal adhesions. Thus TNF-induced tyrosine phosphorylation depends on adhesion of PMN to extracellular matrix proteins, and participates in the transduction of the signals that direct the cells to spread on a biological surface and undergo a respiratory burst.
Centering Decisions in Hierarchical Linear Models: Implications for Research in Organizations

Organizational researchers are increasingly interested in model ing the multilevel nature of organizational data. Although most organi zational researchers have chosen to investigate these models using traditional Ordinary Least Squares approaches, hierarchical linear models (i.e., random coefficient models) recently have been receiving increased attention. One of the key questions in using hierarchical linear models is how a researcher chooses to scale the Level-1 indepen dent variables (e.g., raw metric, grand mean centering, group mean centering), because it directly influences the interpretation of both the level-1 and level-2 parameters. Several scaling options are reviewed and discussed in light of four paradigms of multilevellcross-level research in organizational science: incremental (i.e., group variables add incremental prediction to individual level outcomes over and above individual level predictors), mediational (i.e., the influence of group level variables on individual outcomes are mediated by individual perceptions), moderational (i.e., the relationship between two individ ual level variables is moderated by a group level variable), and sepa rate (i.e., separate within group and between group models). The paper concludes with modeling recommendations for each of these paradigms and discusses the importance of matching the paradigm under which one is operating to the appropriate modeling strategy.
Malware detection based on ontology

Malware in form of Internet worms, computer viruses, and Trojan horses poses a major threat to the security of networked systems. So how to describe the behavior knowledge of malware is an interesting and meaningful work. In recent years, different ontology technologies have been proposed to represent domain knowledge. In the study, we apply ontology techniques into the field of malware detection, and propose the malware detection method based on ontology. This method is based on the behavior of malicious code, and makes a knowledge representation of the malware behaviors from a variety of perspectives. We use the common behaviors of individuals to represent the behaviors of a malware family, and use the ontology reasoning mechanism to detect unknown malware samples. Experiments show that the method has high malicious code detection rate and low false alarm rate.
Special Issue Synthesis

As we observed at the outset of this issue, organizational scholars are increasingly concerned with various binds that appear to be endemic to organizational life. Some frame these conflicts as a sort of new trend or contemporary condition—an effect, for example, of complex social and economic developments related to globalization, hyper-competition, and the resulting explosion of new and hybrid organizational forms (e.g., Volberda, 1996). Some take up with these binds as an inevitable partner of social and organizational change; that is, paradox and contradiction necessarily accompany efforts to do things differently amid entrenched systems and habits (e.g., Stohl & Cheney, 2001). Other authors see such tensions as a longstanding hallmark of human organizing, obscured by the tendency of organization theorists and practitioners to emphasize rationality and order while neglecting the ongoing dialectic of control and resistance (e.g., Benson, 1977). Hence, from diverse perspectives and motives, organization theorists have begun to develop conceptual frames and typologies for comprehending the rich texture of organizational tension, such as that arising from conflicts among ideologies, structures, norms, goals, and practices. These theoretical developments represent a move to challenge assumptions that still pervade organization theory—that organizations and members are rational entities and actors, that goals are unidirectional and consistent, that good communication is ordered and clear, and so on (Burgelman, 1994; Eisenberg, 1984; Eisenberg & Witten, 1987; Miner, 1990; Mumby & Putnam, 1992). It is our contention that such a move takes a crucial step toward the development of organization theories that are at once complex and responsive to actual practice. For, we believe, scholarship that denies the powerful presence of tensions neglects the basic character of organizational life.
SuperNova: Super-peers based architecture for decentralized online social networks

Recent years have seen several earnest initiatives from both academic researchers as well as open source communities to implement and deploy decentralized online social networks (DOSNs). The primary motivations for DOSNs are privacy and autonomy from big brotherly service providers. However decentralization introduces many challenges. One of the principal problems is to guarantee availability of data even when the data owner is not online, so that others can access the said data even when a node is offline or down. Intuitively this can be solved by replicating the data on other users' machines. Existing DOSN proposals try to solve this problem using heuristics which are agnostic to the various kinds of heterogeneity both in terms of end user resources as well as end user behaviors in such a system. In this paper, we argue that a pragmatic design needs to explicitly allow for and leverage on system heterogeneity, and provide incentives for the resource rich participants in the system to contribute such resources. To that end we introduce SuperNova - a super-peer based DOSN architecture. Super-peers can help (i) bootstrap new peers who are yet to have/find any friends by either providing them storage space, (ii) maintaining a directory of users, so that users can find friends in the network by name or interests, (iii) help peers find other peers to store their content in case they don't have adequate friends to do so, or if their friends are already overloaded. Users may want to become super-peers out of altruism (they want DOSNs to succeed), for the sake of the reputation (e.g., being an influential member for an interest based community) as well as potentially to monetize their special roles (e.g., run advertisements). While proposing the SuperNova architecture, we envision a dynamic system driven by incentives and reputation, however, investigation of such incentives and reputation, and its effect on determining peer behaviors is a subject of our future study. In this paper we instead investigate the efficacy of a super-peer based system at any time point (a snap-shot of the envisioned dynamic system), that is to say, we try to quantify the performance of SuperNova system given any (fixed) mix of peer population and strategies.
Implementing Novel IT Products in Small Size Organizations - Technology-driven Requirements Engineering

The growing popularity of new mobile information technology products influences enterprises to buy them without an appropriate evaluation of their usability. This situation is relatively new and conventional usagedriven requirements engineering approaches are not well suitable. The objective of our work is to propose a technology-driven requirements engineering approach where requirements are discovered not only from business needs but also from product features and properties. In particular we take into consideration small size organizations with a small number of business roles and activities.
Environment-adaptive interaction primitives for human-robot motor skill learning

In complex environments where robots are expected to co-operate with human partners, it is vital for the robot to consider properties of their collaborative activity in addition to the behavior of its partner. In this paper, we propose to learn such complex interactive skills by observing the demonstrations of a human-robot team with additional external attributes. We propose Environment-adaptive Interaction Primitives (EalPs) as an extension of Interaction Primitives. In cooperation tasks between human and robot with different environmental conditions, EalPs not only improve the predicted motor skills of robot within a brief observed human motion, but also obtain the generalization ability to adapt to new environmental conditions by learning the relationships between each condition and the corresponding motor skills from training samples. Our method is validated in the collaborative task of covering objects by plastic bag with a humanoid Baxter robot. To achieve the task successfully, the robot needs to coordinate itself to its partner while also considering information about the object to be covered.
Multi-View 3D Video Multicast for Broadband IP Networks

With the recent emergence of 3D-supported TVs, video service providers now face an opportunity to provide high resolution multi-view 3D videos over IP networks. One simple way to support efficient communications between a video server and multiple clients is to deliver each desired view in a multicast stream. Nevertheless, it is expected that significantly increased bandwidth will be required to support the transmission of all views in multi-view 3D videos. However, the recent emergence of a new video synthesis technique called Depth-Image-Based Rendering (DIBR) suggests that multi-view 3D video does not necessarily require the transmission of all views. Therefore, we formulate a new problem, named Multi-view and Multicast Delivery Selection Problem (MMDS), and design an algorithm, called MMDEA, to find the optimal solution. Simulation results manifest that using DIBR can effectively reduce bandwidth consumption by 35% compared to the original multicast delivery scheme.
Rice NTRC Is a High-Efficiency Redox System for Chloroplast Protection against Oxidative Damage[W]

One of the mechanisms plants have developed for chloroplast protection against oxidative damage involves a 2-Cys peroxiredoxin, which has been proposed to be reduced by ferredoxin and plastid thioredoxins, Trx x and CDSP32, the FTR/Trx pathway. We show that rice (Oryza sativa) chloroplast NADPH THIOREDOXIN REDUCTASE (NTRC), with a thioredoxin domain, uses NADPH to reduce the chloroplast 2-Cys peroxiredoxin BAS1, which then reduces hydrogen peroxide. The presence of both NTR and Trx-like domains in a single polypeptide is absolutely required for the high catalytic efficiency of NTRC. An Arabidopsis thaliana knockout mutant for NTRC shows irregular mesophyll cell shape, abnormal chloroplast structure, and unbalanced BAS1 redox state, resulting in impaired photosynthesis rate under low light. Constitutive expression of wild-type NTRC in mutant transgenic lines rescued this phenotype. Moreover, prolonged darkness followed by light/dark incubation produced an increase in hydrogen peroxide and lipid peroxidation in leaves and accelerated senescence of NTRC-deficient plants. We propose that NTRC constitutes an alternative system for chloroplast protection against oxidative damage, using NADPH as the source of reducing power. Since no light-driven reduced ferredoxin is produced at night, the NTRC-BAS1 pathway may be a key detoxification system during darkness, with NADPH produced by the oxidative pentose phosphate pathway as the source of reducing power.
Cholesterol and Lipoprotein Levels as Predictors of Response to Interferon for Hepatitis C

TO THE EDITOR: Minuk and colleagues (1) suggest that serum cholesterol and low-density lipoprotein (LDL) cholesterol are predictors of response to interferon therapy for chronic hepatitis C. To test this finding, we retrospectively compared pretreatment serum cholesterol levels between responders and nonresponders among 63 patients who had participated in our randomized trial (2). As Minuk and colleagues indicated, responders had higher serum cholesterol levels than nonresponders (4.83 0.92 mmol/L [186.8 35.7 mg/dL] vs. 4.13 0.74 mmol/L [159.8 28.7 mg/dL]; P=0.003). However, a previous study reported a decrease in serum cholesterol and LDL cholesterol levels that was related to increasing severity of liver disease (3). According to the fibrosis grade on pretreatment liver histologic testing in our patients, serum cholesterol levels were significantly lower in patients with a pretreatment liver fibrosis grade of 1 or less (Knodell fibrosis score [4]) than in patients with a grade of 3 (4.52 0.83 mmol/L [174.6 32.0 mg/dL] vs. 3.80 0.62 mmol/L [147.0 24.1 mg/dL]; P=0.002). Pretreatment liver histologic characteristics are an important predictor of response to interferon. The significance of serum cholesterol levels as a predictor of this response may therefore be associated with pretreatment liver histologic features. Further studies are required to investigate the association among serum cholesterol and LDL cholesterol levels, liver histologic characteristics, and response to interferon.
An Automatic Software Decentralization Framework for Distributed Device Collaboration

Recently, many low-profile devices with RF communication features have been developed such as sensor network nodes and one-chip microcomputers. This caused a variety of gadgets join to the wireless network. However, in order to realize collaborations between these devices, generally we have to develop complicated distributed software. In this paper, we propose an automatic software decentralization method, which converts a stand-alone software program into distributed software programs. In order to execute the generated software on these low-profile devices, we employ the programming language nesC for a decentralization target. We also have implemented applications with real hardware devices to exemplify that the proposed method successfully improves the ease of development.
Financial risk‐taking on “Who Wants to Be a Millionaire”: A comparison between Austria, Germany, and Slovenia

The aim of the present study was to examine the impact of gender, age, education, and stake on financial risk‐taking in contestants on the television game show “Who Wants to Be a Millionaire. ” According to the existing literature on the impact of demographic parameters on financial risk‐taking, it was expected that women should take less risks than men in the low‐stake condition of the game, older contestants should take less risks than their younger counterparts, and contestants with an academic degree should take more risks than contestants without an academic degree. It was also expected that the tendency towards voluntarily quitting the game should increase with increasing stake. In order to test the generality of the obtained results, the study was conducted in three European countries: Austria, Germany, and Slovenia. The total sample comprised 416 Austrian, 331 German, and 199 Slovenian contestants on the television game show “Who Wants to Be a Millionaire. ” By means of meta‐analyses it was found th.
A Comparative Study of Magnetic-Activated Cell Sorting, Cytotoxicity and Preplating for the Purification of Human Myoblasts

Although cultured myoblast transplantation has been extensively studied as a gene complementation approach to muscular dystrophy treatment, clinical success has still been limited. The inability to adequately isolate and purify myoblasts presents a major limitation to the production of sufficient myoblasts for engrafting purposes. This study attempted to purify myoblasts from primary culture by magnetic-activated cell sorting (MACS), complement-mediated cytotoxicity, and a preplating technique. As a result of positive myoblasts selection by MACS, the average percentage of myoblasts in mixed culture was increased from 30.0% to 41.7%. We observed both myoblast lysis and fibroblast lysis after complement-mediated cytotoxicity. Enrichment of myoblasts in mixed culture was found to increase to 83.1% by using the preplating technique. In addition, higher purification (92.8%) was achieved by following the preplating technique with MACS. Thus, preplating in combination with magnetic-activated cell sorting allows for a rapid and effective isolation of myoblasts from human muscle tissue.
Distinguishing Target From Distractor in Stroop, Picture–Word, and Word–Word Interference Tasks

Lexical selection—both during reading aloud and speech production—involves selecting an intended word, while ignoring irrelevant lexical activation. This process has been studied by the use of interference tasks. Examples are the Stroop task, where participants ignore the written color word and name the color of the ink, picture–word interference tasks, where participants name a picture while ignoring a super-imposed written word, or word–word interference (WWI) tasks, where two words are presented and the participants need to respond to only one, based on an pre-determined visual feature (e.g., color, position). Here, we focus on the WWI task: it is theoretically impossible for existing models to explain how the cognitive system can respond to one stimulus and block the other, when they are presented by the same modality (i.e., they are both words). We describe a solution that can explain performance on the WWI task: drawing on the literature on visual attention, we propose that the system creates an object file for each perceived object, which is continuously updated with increasingly complete information about the stimulus, such as the task-relevant visual feature. Such a model can account for performance on all three tasks.
Eigenvalues and expansion of regular graphs

The spectral method is the best currently known technique to prove lower bounds on expansion. Ramanujan graphs, which have asymptotically optimal second eigenvalue, are the best-known explicit expanders. The spectral method yielded a lower bound of <italic>k</italic>/4 on the expansion of linear-sized subsets of <italic>k</italic>-regular Ramanujan graphs. We improve the lower bound on the expansion of Ramanujan graphs to approximately <italic>k</italic>/2. Moreover, we construct a family of <italic>k</italic>-regular graphs with asymptotically optimal second eigenvalue and linear expansion equal to <italic>k</italic>/2. This shows that <italic>k</italic>/2 is the best bound one can obtain using the second eigenvalue method. We also show an upper bound of roughly <inline-equation> <f> 1+<rad><rcd>k-1</rcd></rad></f> </inline-equation> on the average degree of linear-sized induced subgraphs of Ramanujan graphs. This compares positively with the classical bound <inline-equation> <f> 2<rad><rcd>k-1</rcd></rad></f> </inline-equation>. As a byproduct, we obtain improved results on random walks on expanders and construct selection networks (respectively, extrovert graphs) of smaller size (respectively, degree) than was previously known.
Buck DC-DC converter control using invariant sets techniques

This paper presents an invariant sets technique for feedback law synthesis, in order to control a Buck DC-DC converter. For the linear discrete-time system affected by perturbations and constraints, the proposed method gives the best feedback gain in terms of finding the maximal invariant ellipsoid. As a result of this technique, the maximal ellipsoid is derived but with degraded closed loop performances. In order to assure satisfactory transients the concept of pole placement in LMI regions is introduced. This approach is finally validated in simulation considering the aforementioned converter.