Miracle-dz/UniFAR-FTUs huggingface dataset:
The Future of Systems Research

After 20 years in academia and the Silicon Valley, the new Provost of Stanford University calls for a shift in focus for systems research. Performance-long the centerpiece-needs to share the spotlight with availability, maintainability, and other qualities. Although performance increases over the past 15 years have been truly amazing, it will be hard to continue these trends by sticking to the basically evolutionary path that the research community is currently on. The author advocates a more evolutionary approach to systems problems and thinks the approach needs to be more integrated. Researchers need to think about hardware and software as a continuum, not as separate parts. He sees society on the threshold of a "post PC" era, in which computing is ubiquitous, and everyone will use information services and everyday utilities. When everyone starts using these systems, guess what? They expect them to work and to be easy to use. So this era will drive system design toward greater availability, maintainability, and scalability, which will require a real refocusing of current research directions.
Organization Context and Structure: An Abbreviated Replication.

The present study establishes the reliability and validity of short forms for the measurement of four previously established dimensions of organizations: two contextual-technology and dependence-and two structural-structuring of activities and concentration of authority-based on information obtained from the chief executive in an interview lasting about one hour. A replication study was carried out using the abbreviated measures on a sample of 40 organizations in the English Midlands. The findings supported the relationships previously found between context and structure. Structuring of activities was found to be primarily related to organization size and to a lesser extent to technology; concentration of authority was found to be related to dependence. A restudy using these measures on 14 organizations after a period of four to five years generally supported the hypothesis that forms of workflow bureaucracy show a trend over time in the direction of increased structuring of activities coupled with decreased concentration of authority.
Smart factory and education: An integrated automation concept

The introduction of cyber physical systems into production companies is highly changing working conditions and processes as well as business models. In practice a growing discrepancy between big and small respectively medium-sized companies can be observed. Bridging that gap a university smart factory is introduced to give that companies a platform to trial, educate employees and access consultancy. Realizing the smart factory a highly integrated, open and standardized automation concept is shown comprising single devices, production lines up to a higher automation system maintaining a community or business models.
An embedded platform for reliable applications over heterogeneous wireless networks

A variety of wireless access technologies provides todaypsilas users with pervasive access to critical content and applications. Guaranteeing a satisfactory quality of service requires reliable and ubiquitous delivery schemes that optimally use the available access technologies. This paper presents a novel architecture to support adaptive real-time data and multimedia applications over different wireless technologies. It addresses several issues associated with the satisfactory operation of applications running over heterogeneous networks. The system is validated using a real-life healthcare application capable of transmitting voice, video and medical data simultaneously. Experimental results are reported that demonstrate the viability of the approach.
From smartphone to virtual window

This paper presents a prototype of virtual transparency on a hand-held device. The prototype is restricted to such device with no additional material to show that a semblance of virtual transparency can be achieved with today's smartphones and has been designed be as simple as possible to use. The user's head is tracked using the front camera and the eyes co-ordinates are estimated from the head position. The area to be displayed is then computed from the these coordinates, an estimation of the distance head-phone and phone-scene, as well as the phone and lens specifications. It provides a realistic illusion of virtual transparency, not an geometrically accurate render of the scene, and still works in non-optimal situations (non-flat scene).
A simplified technique for custom made overdenture semi-precision attachments.

CONTEXT Overdentures are the choice of treatment for most of them, but the only snag is its cost. In India, the rural areas are still deprived of quality treatment. This manuscript is showcasing a study, which is a cheaper, but effective way to provide the best to the patient. AIMS The aim of this study was to develop a custom made system, which can be used as an alternative treatment for the management of patients who need overdentures. The primary objective of this study was to provide a cost-effective attachment with the best functional efficacy. MATERIALS AND METHODS The semi-precision attachments were made by using the conventional technique of preparation of post space. The patterns were prepared by using the pattern resin material and the rest of the male and female attachments were fabricated by using innovative methods fulfilling the criteria. RESULTS The attachments were successfully used in patients with remarkably good function and comfort. CONCLUSION It was a successful attempt to provide the specialized treatment in affordable cost. There is a need of innovative work to make the sophisticated systems more economical and readily available.
Mixed-Race Women and Epistemologies of Belonging

How is it that people know when they belong and to what they belong? This question, about the epistemology of belonging, carries a particular complexity for mixed-race women. How is it that mixed-race women create a sense of identifi cation with others? What are the unities and disjunctures? What can we understand about epistemologies of belonging through examining how mixed-race women create belonging? Through qualitative work based on the life stories of women of mixed heritage, in this paper I examine how the navigation of hybridity, as it is experienced in the lives of six “hybrid” mixedrace women, illuminates the complexities of identity construction and epistemologies of belonging. I use the term epistemology to signify the nature of knowledge, how we come to know things, in this case knowledge, or knowing, related to belonging. Belonging in human relations is connected to identity, both self-identifi cation and identifi cation with others. Stuart Hall argues that identities are constituted discursively. He states:
"Got to have faith!": The DEvOTION algorithm for delurking in social networks

Lurkers are silent members of a social network (SN) who gain benefit from others' information without significantly giving back to the community. The study of lurking behaviors in SNs is nonetheless important, since these users acquire knowledge from the community, and as such they are social capital holders. Within this view, a major goal is to delurk such users, i.e., to encourage them to more actively be involved in the SN. Despite delurking strategies have been conceptualized in social science and human-computer interaction research, no computational approach has been so far defined to turn lurkers into active participants in the SN. In this work we fill this gap by presenting a delurking-oriented targeted influence maximization problem under the linear threshold (LT) model. We define a novel objective function, in terms of the lurking scores associated with the nodes in the final active set, and we show it is monotone and submodular. We provide an approximate solution by developing a greedy algorithm, named DEvOTION, which computes a k-node set that maximizes the value of the delurking-capital-based objective function, for a given minimum lurking score threshold. Results on SN datasets of different sizes have demonstrated the significance of our delurking approach via LT-based targeted influence maximization.
The crystal structure of Neisseria gonorrhoeae PriB reveals mechanistic differences among bacterial DNA replication restart pathways

Reactivation of repaired DNA replication forks is essential for complete duplication of bacterial genomes. However, not all bacteria encode homologs of the well-studied Escherichia coli DNA replication restart primosome proteins, suggesting that there might be distinct mechanistic differences among DNA replication restart pathways in diverse bacteria. Since reactivation of repaired DNA replication forks requires coordinated DNA and protein binding by DNA replication restart primosome proteins, we determined the crystal structure of Neisseria gonorrhoeae PriB at 2.7 Å resolution and investigated its ability to physically interact with DNA and PriA helicase. Comparison of the crystal structures of PriB from N. gonorrhoeae and E. coli reveals a well-conserved homodimeric structure consisting of two oligosaccharide/oligonucleotide-binding (OB) folds. In spite of their overall structural similarity, there is significant species variation in the type and distribution of surface amino acid residues. This correlates with striking differences in the affinity with which each PriB homolog binds single-stranded DNA and PriA helicase. These results provide evidence that mechanisms of DNA replication restart are not identical across diverse species and that these pathways have likely become specialized to meet the needs of individual organisms.
Global Estimates for High-Spatial-Resolution Clear-Sky Land Surface Upwelling Longwave Radiation From MODIS Data

Surface upwelling longwave radiation (LWUP) is a vital component in calculating the Earth's surface radiation budget. Under the general framework of the hybrid method, we developed linear and dynamic learning neural network (DLNN) models for estimating the global 1-km instantaneous clear-sky LWUP from the top-of-atmosphere radiance of Moderate Resolution Imaging Spectroradiometer thermal infrared channels 29, 31, and 32. Extensive radiative transfer simulations were conducted to produce a large number of representative samples, from which the linear model and DLNN model were derived. These two hybrid models were evaluated using ground measurements collected at 19 sites from three networks (SURFRAD, ASRCOP, and GAME-AAN). According to the validation results, the linear model was more accurate than the DLNN model, with a bias and root-mean-square error (RMSE) of -0.31 W/m2 and 19.92 W/m2 obtained by averaging the mean bias and RMSE for the three networks. Additionally, the computational efficiency of the linear model was much higher than that of the DLNN model. We also compared our linear model to a hybrid method developed by a previous study and found ours to perform better.
Fast Inexact Implicitly Restarted Arnoldi Method for Generalized Eigenvalue Problems with Spectral Transformation

We study an inexact implicitly restarted Arnoldi (IRA) method for computing a few eigenpairs of generalized non-Hermitian eigenvalue problems with spectral transformation, where in each Arnoldi step (outer iteration) the matrix-vector product involving the transformed operator is performed by iterative solution (inner iteration) of the corresponding linear system of equations. We provide new perspectives and analysis of two major strategies that help reduce the inner iteration cost: a special type of preconditioner with „tuning,” and gradually relaxed tolerances for the solution of the linear systems. We study a new tuning strategy constructed from vectors in both previous and current IRA cycles, and we show how tuning is used in a new two-phase algorithm to greatly reduce inner iteration counts. We give an upper bound of the allowable tolerances of the linear systems and propose an alternative estimate of the tolerances. In addition, the inner iteration cost can be further reduced through the use of subs.
Watt-level wireless power transfer based on stacked flex circuit technology

This paper presents the design, simulation, fabrication, and experimental characterization of a multi-layer spiral inductor that acts as the receiver coil for watt-level wireless power transfer. The inductor was designed with multiple vertical laminations where 88-μm-thick copper coils were separated by 25-μm-thick Kapton films using a flexible PCB fabrication technique. This Cu-Kapton approach has the potential for lower-cost coil fabrication than relatively expensive Litz-wire winding techniques. Varying turn widths were implemented to account for proximity effects and maximize the coil current distribution uniformity inside the coil windings at a given frequency, as validated by two-dimensional electromagnetic simulations. The multi-layer design incorporating lamination of four layers together with width variation exhibited a Q-factor improvement of 150% in comparison to the single-layer inductor. It was measured to have an inductance of 17 μH and a Q-factor of 50 at 300 kHz with an outer diameter of 5 cm. With a Litz-wire inductor as the transmitter coil for wireless power transfer, a load power of 7 Watts was transferred at 300 kHz over a distance of 5 cm and 5 Watts over 10 cm, two times the coil diameter, achieving an overall efficiency (defined as the ratio of the received load power to the total input power to the driving circuitry) of 46% and 23% respectively. In comparison, a manually-wound Litz-wire receiver coil with same characteristics under similar conditions demonstrated an overall efficiency of 58% and 39% at one and two-diameter distances, respectively.
Ad Reactions Over Time: Capturing Changes in the Real World

Using a naturally occurring situation as a quasi-experiment, this article contrasts measures of attitude toward advertisements for groups of subjects with different potential levels of exposure to repeated airings of the ads during a four-month TV campaign. These measures were taken after several different periods of delay following subjects' exposure to the ads. The results indicate that even with all of the confounding variables that exist in a natural viewing environment, subjects' evaluations of the ads decline as levels of potential exposure increase, though those evaluations return to their initial levels after an eight-month period of no exposure. A striking result, however, is that two different measures of attitude toward the ad show very different patterns over time. The article also presents exploratory evidence on the role of the initial likeability of the ad.
RGB-D Based 3D-Object Recognition by LLC Using Depth Spatial Pyramid

Recently, high-accuracy RGB-D cameras are commertially available, which are capable of providing high quality three dimension information (color and depth). In this paper, we propose an object recognition method where the techniques of object recognition in 2D are extended to 3D. Recent image classification systems mainly consist of the following three parts: feature extraction using scaleinvariant feature transform (SIFT), coding scheme using bag-of-features (BoF) and pooling process using spatial pyramid matching (SPM) [1]. The SPM is also regarded as an extension of BoF, which partitions the image into hierarchical spatial sub-regions and computes histograms of local features from each sub-region. This spatial pyramid restricted by position has shown very promising performance on many image classification tasks. These techniques used for 2D images are applied to 3D object recognition without any changes so far. For that reason, even though the depth information captures the overall shape of an object, conventional methods use depth information only to extract the local feature. In our proposed approach, the overall object shape is captured by the depth spatial pyramid based on depth information. In more detail, multiple features within each subregion of the depth spatial pyramid are pooled. As a result, the feature representation including the depth topological information is constructed. We use not only SIFT, but also histograms of oriented normal vectors (HONV [2]) for the depth image, which are originally designed to capture local geometric characteristics. We also adopt localityconstrained linear coding (LLC [4]), which utilizes local constraints to project each descriptor into its local-coordinate system.
Fast airborne aerosol size and chemistry measurements with the high resolution aerosol mass spectrometer during the MILAGRO Campaign

The concentration, size, and composition of non-refractory submicron aerosol (NR-PM1) was measured over Mexico City and central Mexico with a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) onboard the NSF/NCAR C-130 aircraft as part of the MILAGRO field campaign. This was the first aircraft deployment of the HR-ToF-AMS, in which the instrument performed very well, and provided 12 s data. The aerosol mass from the AMS correlates strongly with other aerosol measurements on board the aircraft. Organic aerosol (OA) species dominate the NR-PM1 mass. OA correlates strongly with CO and HCN indicating that pollution (mostly secondary OA, SOA) and biomass burning (BB) are the main OA sources. The OA to CO ratio indicates a typical value for aged air of around 80 ? g m? 3 (STP) ppm? 1. This is within the range observed in outflow from the Northeastern US, which could be due to a compensating effect between higher BB but lower biogenic VOC emissions during this study. The O/C atomic ratio for OA is calculated from the HR mass spectra and shows a clear increase with photochemical age, as SOA forms rapidly and quickly overwhelms primary urban OA, consistent with Volkamer et al. (2006) and Kleinman et al. (2007b). BB OA is marked by signals at m/z 60 and 73, and also by a signal enhancement at large m/z indicative of larger molecules or more resistance to fragmentation. The main inorganic components show different spatial patterns and size distributions. Sulfate is regional in nature with clear volcanic and petrochemical/power plant sources, while the urban area is not a major source for this species. Nitrate is enhanced significantly in the urban area and immediate outflow, and is strongly correlated with CO indicating a strong urban source. The importance of nitrate decreases with distance from the city likely due to evaporation. BB does not appear to be a strong source of nitrate despite its high emissions of nitrogen oxides, presumably due to low ammonia emissions. NR-chloride often correlates with HCN indicating a fire source, although other sources likely contribute as well. This is the first aircraft study of the regional evolution of aerosol chemistry from a tropical megacity.
Automatic Genre Classification in Web Pages Applied to Web Comments

Automatic Web comment detection could signiﬁcantly facilitate information retrieval systems, e.g., a focused Web crawler. In this paper, we propose a text genre clas-siﬁer for Web text segments as intermediate step for Web comment detection in Web pages. Different feature types and clas-siﬁers are analyzed for this purpose. We compare the two-level approach to state-of-the-art techniques operating on the whole Web page text and show that accuracy can be improved signiﬁcantly. Finally, we illustrate the applicability for information retrieval systems by evaluating our approach on Web pages achieved by a Web crawler. 1
SPAWNN: A Toolkit for SPatial Analysis With Self‐Organizing Neural Networks

This article introduces the SPAWNN toolkit, an innovative toolkit for spatial analysis with self‐organizing neural networks, which is published as free and open‐source software (http://www.spawnn.org). It extends existing toolkits in three important ways. First, the SPAWNN toolkit distinguishes between self‐organizing neural networks and spatial context models with which the networks can be combined to incorporate spatial dependence and provides implementations for both. This distinction maintains modularity and enables a multitude of useful combinations for analyzing spatial data with self‐organizing neural networks. Second, SPAWNN interactively links different self‐organizing networks and data visualizations in an intuitive manner to facilitate explorative data analysis. Third, it implements cutting‐edge clustering algorithms for identifying clusters in the trained networks. Toolkits such as SPAWNN are particularly needed when researchers and practitioners are confronted with large amounts of complex and high‐dimensional data. The computational performance of the implemented algorithms is empirically demonstrated using high‐dimensional synthetic data sets, while the practical functionality highlighting the distinctive features of the toolkit is illustrated with a case study using socioeconomic data of the city of Philadelphia, Pennsylvania.
Description Description: Functions for Modelling Dispersion in Glm

February 15, 2013 Type Package Title Evaluating the genetic differentiation between populations based on Gst and D values. Version 0.8-5 Date 2012-02-26 Author Alexander Jueterbock, Philipp Kraemer, Gabriele Gerlach and Jana Deppermann Maintainer Alexander Jueterbock, <Alexander-Jueterbock@web.de> Depends R (>= 2.8.0) Description This package allows to calculate the fixation index Gst (Nei, 1973) and the differentiation index D (Jost, 2008) pairwise between or averaged over several populations. P-values, stating the significance of differentiation, and 95 percent confidence intervals can be estimated using bootstrap resamplings. In the case that more than two populations are compared pairwise, the p-values are adjusted by bonferroni correction and in several other ways due to the multiple comparison from one data set. License GPL (>= 2) Repository CRAN Date/Publication 2012-02-26 16:32:32 NeedsCompilation no
A Biologically Inspired Memory in a Multi-agent Based Robotic Architecture

We describe a biologically inspired memory in a multi-agent based robotic architecture. In this approach, memory and pattern recognition are intertwined to form a cognitive memory that is used for recognition of objects in a robotics environment. This memory is implemented in a multiple agent behavior based blackboard architecture as an object recognition agent. The agent performance is tested against a standard dataset with satisfactory results. The system is currently installed in a mobile robotic platform where its capabilities and applications are explored.
Effects of Phenolic Compounds of Fermented Thai Indigenous Plants on Oxidative Stress in Streptozotocin-Induced Diabetic Rats

We investigated the effects of antioxidant activity of fermentation product (FP) of five Thai indigenous products on oxidative stress in Wistar rats with streptozotocin (STZ)-induced diabetes type II. The rats were fed with placebo and with the FP (2 and 6 mL/kg body weight/day) for 6 weeks. Rutin, pyrogallol and gallic acid were main compounds found in the FP. Plasma glucose levels in diabetic rats receiving the higher dose of the FP increased less when compared to the diabetic control group as well as the group receiving the lower FP dose (13.1%, 29%, and 21.1%), respectively. A significant dose-dependent decrease in plasma levels of thiobarbituric acid reactive substance (P < .05) was observed. In addition, the doses of 2 and 6 mL FP/kg/day decreased the levels of erythrocyte ROS in diabetic rats during the experiment, but no difference was observed when compared to the untreated diabetic rat group. Results imply that FP decreased the diabetes-associated oxidative stress to a large extent through the inhibition of lipid peroxidation. The FP also improved the abnormal glucose metabolism slightly but the difference was not statistically significant. Thus, FP may be a potential therapeutic agent by reducing injury caused by oxidative stress associated with diabetes.