Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential temporal expression of S100β in developing rat brain

Radial glial cells (RGs) originally considered to provide scaffold to the radially migrating neurons constitute a heterogeneous population of the regionally variable precursor cells that generate both neurons as well as glia depending upon the location and the timing of development. Hence specific immunohistochemical markers are required to specify their spatiotemporal location and fate in the neurogenic and gliogenic zones. We hypothesize S100β as a potential and unified marker for both primary and secondary progenitors. To achieve this, cryocut sections from rat brains of varied embryonic and postnatal ages were immunolabeled with a combination of antibodies, i.e., S100β + Nestin, Nestin + GFAP and S100β + GFAP. A large population of the primary and secondary progenitors, lining the VZ and SVZ, simultaneously co-expressed S100β and nestin establishing their progenitor nature. A downregulation of both S100β and nestin noticed by the end of the 1st postnatal week marks their differentiation towards neuronal or glial lineage. In view of the absence of co-expression of GFAP (glial fibrillary acidic protein) either with S100β or nestin, the suitability of accepting GFAP as an early marker of RG’s was eliminated. Thus the dynamic expression of S100β in both the neural stem cells (NSCs) and RGs during embryonic and early neonatal life is associated with its proliferative potential and migration of undifferentiated neuroblasts and astrocytes. Once they lose their potential for proliferation, the S100β expression is repressed with its reemergence in mature astrocytes. This study provides the first clear evidence of S100β expression throughout the period of neurogenesis and early gliogenesis, suggesting its suitability as a radial progenitor cell marker.
[Occurrence of Bacillus cereus in infants and young children foods in 8 provinces in China].

OBJECTIVE To investigate the contamination status of infants and young children foods by Bacillus cereus. METHODS 1716 food samples were collected from retail market in 8 provinces in China and examined for Bacillus cereus by the plate count method. RESULTS Bacillus cereus was isolated from 9.85% of all the samples (169/1716). 14.08% of the powered formula for infants and young children were contaminated with B. cereus as well as 6.01% of the ready-to-eat cereal-based complementary foods for infants and young children. Counts higher than 100 CFU/g were found in 18 samples of the powered formula (2.20%) and 10 samples of the ready-to-eat cereal-based complementary foods (1.11%). CONCLUSION Inspection and management of infants and young children foods should be enhanced to prevent Bacillus cereus infection.
Visual object analysis using regions and interest points

This dissertation research will explore region-based and interest points based image representations, two of the most-used image models for object detection, image classification, and visual search among other applications. We will analyze the relationship between both representations with the goal of proposing a new hybrid representation that takes advantage of the strengths and overcomes the weaknesses of both approaches. More specifically, we will focus on the gPb-owt-ucm segmentation algorithm and the SIFT local features since they are the most contrasted techniques in their respective fields. Furthermore, using an object retrieval benchmark, this dissertation research will analyze three basic questions: (i) the usefulness of an interest points hierarchy based on a contour strength signal, (ii) the influence of the context on both interest points location and description, and (iii) the analysis of regions as spatial support for bundling interest points.
p21 is required for atRA‐mediated growth inhibition of MEPM cells, which involves RAR

All‐trans retinoic acid (atRA), a metabolite of vitamin A, is essential for embryonic development. Thus the spatial and temporal dispersal of RA must be tightly controlled. Previous studies show that excessive atRA led to growth inhibition and p21 accumulation in mouse embryonic palatal mesenchymal (MEPM) cells. We reported here the identification of p21 as a required mediator during atRA‐induced growth inhibition. atRA caused a G1 arrest in the cell cycle with an increase in the proportion of cells in G0/G1 and a decrease in the proportion of cells in S phase. In addition to a marked effect on cell cycling, atRA also triggered DNA fragmentation, reflected by an increase of the fraction of cells in the sub‐G1 population. Western blot analysis revealed that atRA treatment led to an increase in p21 level and a decrease in cyclin D1 protein and Rb phosphorylation. Using luciferase assay with reporter gene regulated by p21 promoter, we showed that atRA increased the reporter activity in a dose‐dependent manner; and p21 siRNA blocked the growth inhibition by atRA, suggesting that p21 is required for atRA‐mediated growth inhibition. Moreover, the induction of p21 by atRA was partially attenuated when RAR was silenced with specific siRNA. atRA stimulated RARE‐driven reporter gene activity dose‐dependently. Using chromatin immunoprecipitation, we demonstrated that RAR protein could bind to the p21 promoter. Taken together, our results indicate p21 is responsible for atRA‐induced growth inhibition of MEPM cells and RAR plays a role during this process. J. Cell. Biochem. 104: 2185–2192, 2008. © 2008 Wiley‐Liss, Inc.
Hybrid Signcryption Schemes with Insider Security ( Extended Abstract )

The question of constructing a hybrid signcryption scheme with outside security was considered by Dent [7]. That paper also demonstrated that the basic hybrid construction formalised by Cramer and Shoup [5, 9] is incapable of producing a signcryption scheme with insider security. This paper provides a paradigm for constructing signcryption schemes with insider security based on the ideas of hybrid cryptography.
Replicated Studies: Building a Body of Knowledge about Software Reading Techniques

An empirical approach to software process improvement calls for guiding process development based on empirical study of software technologies. This approach helps direct the evolution of new technologies, by studying the problems developers have applying the technology in practice, and validates mature technologies, by providing indication of the expected benefit and the conditions under which they apply. So, a variety of different empirical studies are necessary for a given technology over time, with evolving goals and hypotheses.Thus, what we as a field know about a software development technology is never based on a single study; rather, a "body of knowledge" must be accumulated out of many individuals studies. Multiple studies also help mitigate the weaknesses inherent in any empirical study by requiring the confirmation or refutation of the original findings by means of independent replications, which can address the original threats to validity although they will invariably suffer from threats of their own.Since formal methods for abstracting results from independent studies (such as meta-analysis) have not proven feasible, we advocate a more informal approach to building up such bodies of knowledge. In this approach, replication is used to run families of studies theft are designed a priori to be related. Because new studies are based upon the designs of existing ones, it becomes easier to identify the context variables that change from one study to another. By comparing and contrasting the results of studies in the same family, researchers can reason about which context variables have changed and hypothesize what their likely effects on the outcome have been. As more studies become part of the family, hypotheses can be refined, or supported with more confidence by additional data. By using this informal approach, we can work toward producing a robust description of a technology's effects, specifying hypotheses at varying levels of confidence.In this chapter, we first present a more detailed discussion of various types of replications and why they are necessary for allowing the variation of important factors in a controlled way to study their effects on the technology. For each type of replication identified, we provide an example of this informal approach and how it has been used in the evolution of a particular software development technology, software reading techniques. We present a brief description of each set of replications, focusing on the lessons learned about the reading technology based on the results of the original study and the replication together. We will also discuss what we learned about the technologies from the entire series of studies, as well as what we learned about reading techniques in general. We will indicate which of these lessons were due directly to the process of replication and could not have been learned through a single study. Based on these examples, this chapter concludes with lessons learned about replicating studies.
Neuroticism explains unwanted variance in Implicit Association Tests of personality: possible evidence for an affective valence confound

Meta-analytic data highlight the value of the Implicit Association Test (IAT) as an indirect measure of personality. Based on evidence suggesting that confounding factors such as cognitive abilities contribute to the IAT effect, this study provides a first investigation of whether basic personality traits explain unwanted variance in the IAT. In a gender-balanced sample of 204 volunteers, the Big-Five dimensions were assessed via self-report, peer-report, and IAT. By means of structural equation modeling (SEM), latent Big-Five personality factors (based on self- and peer-report) were estimated and their predictive value for unwanted variance in the IAT was examined. In a first analysis, unwanted variance was defined in the sense of method-specific variance which may result from differences in task demands between the two IAT block conditions and which can be mirrored by the absolute size of the IAT effects. In a second analysis, unwanted variance was examined in a broader sense defined as those systematic variance components in the raw IAT scores that are not explained by the latent implicit personality factors. In contrast to the absolute IAT scores, this also considers biases associated with the direction of IAT effects (i.e., whether they are positive or negative in sign), biases that might result, for example, from the IAT's stimulus or category features. None of the explicit Big-Five factors was predictive for method-specific variance in the IATs (first analysis). However, when considering unwanted variance that goes beyond pure method-specific variance (second analysis), a substantial effect of neuroticism occurred that may have been driven by the affective valence of IAT attribute categories and the facilitated processing of negative stimuli, typically associated with neuroticism. The findings thus point to the necessity of using attribute category labels and stimuli of similar affective valence in personality IATs to avoid confounding due to recoding.
Drilling into complex 3D models with gimlenses

Complex 3D virtual scenes such as CAD models of airplanes and representations of the human body are notoriously hard to visualize. Those models are made of many parts, pieces and layers of varying size, that partially occlude or even fully surround one another. We introduce Gimlenses, a multi-view, detail-in-context visualization technique that enables users to navigate complex 3D models by interactively drilling holes into their outer layers to reveal objects that are buried, possibly deep, into the scene. Those holes get constantly adjusted so as to guarantee the visibility of objects of interest from the parent view. Gimlenses can be cascaded and constrained with respect to one another, providing synchronized, complementary viewpoints on the scene. Gimlenses enable users to quickly identify elements of interest, get detailed views of those elements, relate them, and put them in a broader spatial context.
Adaptive resolution of mainlobe and sidelobe detections using model order determination

This paper presents the development and performance evaluation of a methodology for distinguishing between mainlobe and sidelobe detections that arise in adaptive radar systems operating in adverse environments. Various adaptive detection test statistics such as the adaptive matched filter (AMF), the generalized likelihood ratio test (GLRT) and adaptive coherence estimate (ACE), and combinations of these, have been previously analyzed with respect to their sidelobe rejection capabilities. In contrast to these methods, which are based on detecting a single target with known direction and Doppler, the present method uses model order determination techniques applied to the AMF or GLRT data observed over the range of unknown angle and Doppler parameters. The determination of model order, i.e., the number of signals present in the data, is made by using least-squares model fit error residuals and applying the Akaike information criterion. Comprehensive computer simulation results are presented which demonstrate substantial improvement in sidelobe rejection performance compared to previous methods.
Content Analysis of Information Exchange in Online Auctions

The literature on internet auctions focuses largely on the problem of information asymmetry and the steps taken to address the adverse selection problem. The central question for researchers is the issue of increasing efficiency of exchange through appropriate auction design mechanisms. Typically, the focus has been on either pre-transactional information (product descriptions, seller reputation, etc.) or post-transactional information (experience reviews). In this paper, we study the nature of information exchanged between auction participants while an auction is in progress. We examined 295 auctions of used cars that occurred over a two week period in a popular online auction site. By classifying the contents of this exchange into various categories, we analyze their effect on auction outcomes. Our models indicate that there is a significant role that such information can play in determining auction outcomes.
Urban Erosion Potential Risk Mapping with GIS

With increased regulatory focus on eroded sediment and its bound pollutants, methods are needed to predict areas with high erosive potential (EP) in urbanized areas. Using EP to prioritize urban areas for maintenance, implementation of Stormwater Control Measures (SCMs), stream restoration or monitoring is crucial. This study utilizes commonly available geospatial layers in conjunction with a computational procedure for prioritizing the contribution of site specific- and transport-erosion to compute relative EP risk throughout a target urban watershed. Factors that contribute to erosion were evaluated: local cell slope, soil erodibility, land cover, runoff volume, distance and slope to nearest stormwater conveyance point along a surface flow travel path. A case study of the developed methodology was performed on a 1.6 square kilometer urban watershed in Blacksburg, VA, to generate EP risk maps. Results of the study indicate areas of erosive potential within the target watershed and provide a methodology for creating erosion potential risk maps for use by MS4 planners, engineers and other individuals that manage erosion control programs.
Foundations of data-aware process analysis: a database theory perspective

In this work we survey the research on foundations of data-aware (business) processes that has been carried out in the database theory community. We show that this community has indeed developed over the years a multi-faceted culture of merging data and processes. We argue that it is this community that should lay the foundations to solve, at least from the point of view of formal analysis, the dichotomy between data and processes still persisting in business process management.
A Software Defined Wireless Networking for Efficient Communication in Smart Cities

Smart cities represent a rich dynamic environment where multiple wireless mobile devices interconnect to each other to communicate and share their data. The growing demand and the diverse traffic patterns of these smart devices place an increasing strain on the wireless networks. Routing data among wireless routers becomes a challenging issue as traditional routing algorithms, which are based on the Ad-Hoc and LAN flavors, cannot fulfill the requirements of distributed communications in Smart Cities. The routing decisions are taken based on local knowledge of a wireless router about each of its neighbors to reflect a partial visibility of the network. Such a local visibility limits the ability of managing the huge number of wireless smart devices in Smart Cities. An attractive and more realistic alternative is the Software Defined Networking (SDN), which offers a centralized up-to-date view of the entire network by refactoring the wireless protocols into control and forwarding decisions. However, many challenges must first be overcome to realize this potential. Accordingly, this paper outlines important challenging issues for building efficient wireless communication in smart cities. In particular, we describe a novel network architecture that integrates SDN and the Wireless Mesh Networks (WMNs) to address these issues. Our approach proposes a novel way of performing network virtualization, routing and traffic engineering in SDN-based WMNs in smart cities thereby improving the performance and the flexibility of the network.
Posterior Matching for Gaussian Broadcast Channels with Feedback

In this paper, the posterior matching scheme proposed by Shayevits and Feder is extended to the Gaussian broadcast channel with feedback, and the error probabilities and achievable rate region are derived for this coding strategy by using the iterated random function theory. A variant of the Ozarow-Leung code for the general two-user broadcast channel with feedback can be realized as a special case of our coding scheme. Furthermore, for the symmetric Gaussian broadcast channel with feedback, our coding scheme achieves the linear-feedback sum-capacity like the LQG code and outperforms the Kramer code.
A Role for Non-Rapid-Eye-Movement Sleep Homeostasis in Perceptual Learning

Slow-wave activity (SWA; EEG power density in the 0.75–4.5 Hz range) in non-rapid-eye-movement (NREM) sleep is the primary marker of sleep homeostasis and thought to reflect sleep need. But it is unknown whether the generation of SWA itself serves a fundamental function. Previously, SWA has been implicated in brain plasticity and learning, yet the evidence for a causal role remains correlative. Here, we used acoustic slow-wave suppression to test whether overnight improvement in visual texture discrimination, a form of perceptual learning, directly depends on SWA during sleep. Two groups of subjects were trained on a texture discrimination task (TDT) after baseline sleep, and were tested 24 h later, after a 4 h experimental (EX) sleep episode (with or without SWA suppression), and again after a night of recovery sleep. In the suppression group, SWA during EX sleep was reduced by 30% compared with the control group, whereas total sleep time and REM sleep were not affected. Texture discrimination improved after EX sleep in the control group but not in the suppression group. Moreover, overnight improvement in TDT performance correlated with EEG power density during NREM sleep in the frequency range of SWA (maximum r = 0.75 at 0.75–1.0 Hz) over brain areas involved in TDT learning. We conclude that SWA is an important determinant of sleep-dependent gains in perceptual performance, a finding that directly implicates processes of sleep homeostasis in learning.
Factors influencing the adoption of and business case for Cloud computing in the public sector

Cloud adoption in the public sector is taking off slowly, which is perceived as a problem. Models of factors influencing cloud adoption are derived for better understanding using literature and results obtained via desk research and surveys by the Cloud for Europe project. We conclude that several factors require further research, such as the culture in countries, climate, legislation, economics and politics, IT staff shortage and feelings of uncertainty, fear and impatience. Adoption factors have impact on the business case for cloud computing. Hence a business case template to compare cloud scenarios with zero scenarios is developed. We recommend to use the risk-adjusted balance between benefits and costs to decide on cloud adoption instead of focussing only on the benefits of cloud computing. Although this makes the business case for adoption of cloud computing less favourable, it provides a more realistic picture leading to sustainable decisions on cloud adoption.
The beryllium hollow-body solar sail: exploration of the Sun's gravitational focus and the inner Oort Cloud

Spacecraft kinematics, peak perihelion temperature and space environment effects during solar-radiation-pressure acceleration for a beryllium hollow-body interstellar solar sail inflated with hydrogen fill gas are investigated. We demonstrate that diffusion is alleviated by an on-board fill gas reserve and electrostatic pressure can be alleviated by increasing perihelion distance. For a 0.1 AU perihelion, a 937 m radius sail with a sail mass of 150 kg and a payload mass of 150 kg, perihelion sail temperature is about 1000 K, peak acceleration is about 0.6 g, and solar-system exit velocity is about 400 km/s. After sail deployments, the craft reaches the 200 AU heliopause in 2.5 years, the Sun's inner gravitational focus at 550 AU in about 6.5 years and 2,550 AU in 30 years. The Be hollow-body sail could be applied in the post 2040 time frame to verify general relativity predictions regarding the Sun's inner gravitational focus and to explore particles and fields in the Sun's inner Oort Comet Cloud.
Structural analysis of high-field-side RF antennas during a disruption on the Advanced Divertor eXperiment (ADX)

The Advanced Divertor and RF tokamak eXperiment (ADX) is a compact, high-field device proposed by the MIT Plasma Science and Fusion Center and collaborators [1], which will address critical gaps in world fusion research on the pathway to fusion energy. In addition to developing and testing new divertor concepts at reactor level magnetic field strengths and power densities, ADX will test new antenna concepts for Lower Hybrid Current Drive (LHCD) and Ion Cyclotron Range of Frequency (ICRF) heating systems. In particular, ADX will be purpose-built to allow antennas to be positioned on the high magnetic field side of the torus, i.e., on the inner wall. With antennas placed at this location, plasma-wall interactions are greatly reduced and favorable RF wave physics projects to dramatic improvements in current drive efficiency and current profile control as well as very effective scenarios for RF heating and flow drive [2][3][4]. Initial designs for a high field side LHCD and ICRF antennas have been completed and are analyzed to determine the loads induced during a full-current plasma disruption. While locating antennas at the inner wall is beneficial from an RF standpoint, it exposes them to a higher toroidal field which, when combined with the eddy currents caused by a disrupting plasma, will lead to higher loads. Using COMSOL Multiphysics [5], a model of the ADX vessel and coils is created to predict the magnetic fields, eddy currents and loads acting on the antennas during a disruption. Structural models are then run to predict the stresses and to provide guidance for design improvement, such as determining where structural reinforcements may be necessary.