Miracle-dz/UniFAR-FTUs huggingface dataset:
Variation in aggregation propensities among ALS-associated variants of SOD1: Correlation to human disease

To date, 146 different mutations in superoxide dismutase 1 (SOD1) have been identified in patients with familial amyotrophic lateral sclerosis (ALS). The mean age of disease onset in patients inheriting mutations in SOD1 is 45–47 years of age. However, although the length of disease duration is highly variable, there are examples of consistent disease durations associated with specific mutations (e. g. A4V, less than 2 years). In the present study, we have used a large set of data from SOD1-associated ALS pedigrees to identify correlations between disease features and biochemical/biophysical properties of more than 30 different variants of mutant SOD1. Using a reliable cell culture assay, we show that all ALS-associated mutations in SOD1 increase the inherent aggregation propensity of the protein. However, the relative propensity to do so varied considerably among mutants. We were not able to explain the variation in aggregation rates by differences in known protein properties such as enzyme activity, protein thermostability, mutation position or degree of change in protein charge. Similarly, we were not able to explain variability in the duration of disease in SOD1-associated ALS pedigrees by these properties. However, we find that the majority of pedigrees in which patients exhibit reproducibly short disease durations are associated with mutations that show a high inherent propensity to induce aggregation of SOD1.
Determination of Thermophysical Properties of Si/SiGe Superlattices with a Pump-Probe Technique

A Time Domain Thermo-Reflectance technique (TDTR) is used for the non-destructive evaluation of thermal and acoustic properties of Si/SiGe superlattices (SL) at room temperature. In particular, this technique allows the determination of the SL cross-plan thermal conductivity, the thermal boundary resistance at the interface between the metallic film and the SL, and the longitudinal sound velocity inside the SL. We discuss the effect of both transducer thickness and pump power on the measurements and then on values of the extracted thermophysical properties of the superlattice.
Hybrid group adaptive memoryless algorithm for collision resolution in passive tags

Readers in radio frequency identification systems are in dire need of an anti-collision algorithm for identifying tags in the interrogation zone by consuming the most minimum time. Electing a good anti collision algorithm, in general is made based on the deployment area. Existing algorithms suggested in the last 3 decades are currently domain specific. Many algorithms produce remarkable results in stable environment but fail to produce even half when tags are mobile. The proposed methodology, in this paper is designed to be adopted in any environment without any major change to tag's hardware requirements. Instead of looking at “the glass being half empty” in a tag collision, the proposed algorithm takes full advantage of reducing the number of collisions, hence forth, when a collision is experienced in the previous slot. The reader intelligently constructs a probable query to reduce the transaction of bits among tags and readers. The proposed algorithm also uses a different clustering procedure to seclude a single tag. Performance evaluation shows that HGAMA performs well when other hybrid anti collision algorithms is compared.
Applying higher strength combinatorial criteria to test case prioritization : a case study

Faults in software systems often occur due to interactions between parameters. Several studies show that faults are caused by 2-way through 6-way interactions of parameters. In the context of test suite prioritization, we have studied prioritization by 2-way interwindow interaction coverage and found that this criteria is effective at finding faults quickly in the test execution cycle. However, since faults may be caused by interactions between more than 2 parameters, in this paper, we provide a greedy algorithm for test suite prioritization by n-way combinatorial coverage of inter-window interactions. While greedy algorithms that generate Combinatorial Interaction Test suites enumerate and track the coverage of all possible t-tuples and constraints, we have noticed that our user-session-based test suites often do not contain every possible t-tuple and we can take advantage of this in our algorithm by only storing t-tuples that appear in the test suite. Our empirical study shows both time and memory usage associated with our algorithm for 3-way inter-window parameter-value interaction coverage. Further, we conduct an empirical study where we compare 2-way and 3-way combinatorial coverage of inter-window parameter interactions in terms of the rate of fault detection for a web application called Schoolmate and a user-sessionbased test suite. Our results show that the rate of fault detection
Efficient Structural Query Evaluation over Social Data

With the rapid increase of social media, more and more users generate data on social application platforms, such as Facebook, Twitter and Sina Weibo(weibo.com). Current platforms, however, only provides keyword-based search function on social data, which is far from enough to satisfy users' query requirement in the view point of both structure and content aspects. The traditional structural join algorithms, which obtain results by matching both structure and content, do not work very well for social data. The challenges include (1) the size of social data is huge, (2) the online social applications require real time response. It is necessary to study the structural query on social data in order to meet the above requirements. This paper proposes the Post Dewey, a new numbering schema which is the structural summation of an element tag to reduce search space. A novel structural join algorithm, Post Structure Join (PSJ), was presented to address the limitation of the stack based algorithms, as a supplement strategy for structural joins. PSJ improves the overall performance by reducing the input size at the cost of losing some join efficiency. The approach is validated on real dataset crawled and extracted from Sina Weibo. The experimental results demonstrate the effectiveness of PSJ by comparing with the state-of-the-art structural join algorithms.
Teaching Entrepreneurship to Undergraduates

Contents: Foreword by Allan Gibb Introduction Part I: Scoping the Issues 1. Your Teaching Philosophy 2. Entrepreneurship Education 3. The Ontological Dilemma Part II: The Nature of Our Students 4. The Reasonable Adventurer 5. Student Diversity 6. The Learning Environment 7. The Resource Profile Part III: Being Entrepreneurial 8. The Art of Selling 9. Evaluating Ideas 10. Business Plans Part IV: Towards an Ecology of Learning 11. Accounting for Interaction Appendices References Index
Digital Government: Technology and Public Sector Performance

Few developments have had broader consequences for the public sector than the introduction of the Internet and digital technology. In this book, Darrell West discusses how new technology is altering governmental performance, the political process, and democracy itself by improving government responsiveness and increasing information available to citizens.Using multiple methods--case studies, content analysis of over 17,000 government Web sites, public and bureaucrat opinion survey data, an e-mail responsiveness test, budget data, and aggregate analysis--the author presents the most comprehensive study of electronic government ever undertaken. Among other topics, he looks at how much change has taken place in the public sector, what determines the speed and breadth of e-government adoption, and what the consequences of digital technology are for the public sector.Written in a clear and analytical manner, this book outlines the variety of factors that have restricted the ability of policy makers to make effective use of new technology. Although digital government offers the potential for revolutionary change, social, political, and economic forces constrain the scope of transformation and prevent government officials from realizing the full benefits of interactive technology.
Epigenetic Programming of Stress Responses through Variations in Maternal Care

Abstract: Early life experiences shape an individual's physical and mental health across the lifespan. Not surprisingly, an upbringing that is associated with adversity can produce detrimental effects on health. A central theme that arises from studies in human and nonhuman species is that the effects of adversity are mediated by the interactions between a mother and her young. In this review we describe some of the long‐term effects of maternal care on the offspring and we focus on the impact of naturally occurring variations in the behavior of female rats. Of particular interest are mothers that engage in high or low amounts of licking/grooming (LG) and arched‐back nursing (ABN) of their pups, but do so within the normal range for this species. Such variations in LG‐ABN can alter the function of the hypothalamic‐pituitary‐adrenal (HPA) axis, and cognitive and emotional development by directly affecting the underlying neural mechanisms. At the heart of these mechanisms is gene expression. By studying the hippocampal glucocorticoid receptor gene, we have identified that maternal care regulates its expression by changing two processes: the acetylation of histones H3‐K9, and the methylation of the NGFI‐A consensus sequence on the exon 17 promoter. Sustained “maternal effects” appear elsewhere in biology, including plants, insects, and lizards, and may have evolved to program advantages in the environments that the offspring will likely face as adults. Given the importance of early life and parent‐child interactions to later behavior, prevention and intervention programs should target this critical phase of development.
Do fiscal deficits cause current account deficits in the Pacific Island countries? A case study of Fiji

Pacific island countries have been experiencing budget deficits and deficits in their external accounts for some time in the past few years. Fiji is no exception. It has been experiencing current account deficits in its balance of payments since the late 1990s, despite the emergence of a boom in remittances. The deficits have become increasingly more pronounced since 2001 due to gradual decline in the country’s traditional exports of sugar and sharp fall in the exports of garments, due to expiry of the Multifibre Agreement, and decline in the exports of gold following operational problems. On the other hand, the surge in imports of capital goods and machinery for building and construction industry was mainly due to expansionary fiscal policies since 2001, which revived the economy as well. Additionally, a steep rise in private sector credit in the postcoup years of 2000 ensued, contributing to the further widening of current account deficit. This paper seeks to investigate whether the popular twin deficit hypothesis holds good in the case of Fiji.
Optimal Taxation of Human Capital and Credit Constraints

We study optimal linear income taxation in a model with heterogeneous agents where earnings potentials are endogenously determined through human capital accumulation. Agents differ in initial conditions and ability to learn. Capital market imperfections prevent poor agents to invest optimally in human capital. We show that optimal linear tax rates on human capital are positive, even in absence of redistributive preferences of the government. A more progressive tax system has efficiency gains because credit constraints are relaxed. Numerical calculations show that optimal linear tax rates are significantly increased when capital market imperfections are present.
Repair Expenses, Selling Contracts and House Prices

This paper examines the impact of repair expenses on the selling price of a house. Using data from settlement statements, we investigate the frequency and extent to which performance of major repairs is part of the sales contract. We find that most homes are restored to a "normally maintained" state each time the home changes hands, and that the cost of bringing the home to this condition is included as part of house selling price. This implies it may be unnecessary to measure maintenance levels when using transaction data to study components of house price or to construct house price indexes.
The use of preliminary data in econometric forecasting: an application with the Bank of Italy Quarterly Model

This paper considers forecasting by econometric and time series models using preliminary (or provisional) data. The standard practice is to ignore the distinction between provisional and final data. We call the forecasts that ignore such a distinction naive forecasts, which are generated as projections from a correctly specified model using the most recent estimates of the unobserved final figures. It is first shown that in dynamic models a multistepahead naive forecast can achieve a lower mean square error than a single-step-ahead one, intuitively because it is less affected by the measurement noise embedded in the preliminary observations. The best forecasts are obtained by combining, in an optimal way, the information provided by the model with the new information contained in the preliminary data. This can be done in the state space framework, as suggested in the literature. Here we consider two simple methods to combine, in general suboptimally, the two sources of information: modifying the forecast initial conditions via standard regressions and using intercept corrections. The issues are explored with reference to the Italian national accounts data and the Bank of Italy Quarterly Econometric Model (BIQM). A series of simulation experiments with the model show that these methods are quite effective in reducing the extra volatility of prediction due to the use of preliminary data.
Profile Extraction from Mean Profile for Automatic Text Categorization

With overwhelming growth of information technology, better organization of documents is required for easy access of information. Hence the need for text categorization becomes critical. Many researchers have turned their attention towards text categorization. Text categorization is the automated assignment of predefined categories to the text documents based on document contents. We proposed an automatic text categorization approach that uses profiles for categorization of text documents. A new similarity method has been used for measuring similarity between profiles and documents. We have explored different ways of profile creation and concluded that the increase in distance between profiles improves the classifier performance. Our classifier has an improved performance when compared with similar kind of text categorization methods
RANS/LES methodology for supersonic transverse jet interactions with approach flow

This work discusses some ongoing efforts towards the simulation of supersonic transverse jet interactions using LES. The code numerics feature a higher-order scheme with a "resurrected" limiting approach by the Jameson's dissipation scheme for dealing with shocks and other discontinuities. The methodology involves generating a "realistic" turbulent boundary layer using the "recycling-rescaling" approach that leads up to the transverse jet. A series of numerical experiments with increasing complexity are preformed to validate this methodology before attempting the transverse jet. The main goal of the effort is to be able to understand the complex physics involved and eventually be able to predict pressure fluctuation levels in such flows.
National Board Certified Teachers' Perspectives on Using Measures of Student Learning for Teacher Evaluation

Abstract This article examines the perspectives of 20 National Board Certified Teachers on the use of measures of student learning for teacher evaluation. An analysis of responses from four focus groups reveals concern about the validity and efficiency of current measures of student progress, and “gaming” of the systems to ensure positive evaluations. Classroom assessment measures designed by teachers—such as tests, quizzes, and portfolios—are discussed as a promising alternative to the use of large-scale testing.
Observation of growing correlation length as an indicator for critical point behavior prior to large earthquakes

We test the critical point concept for earthquakes in terms of the spatial correlation length. A system near a critical point is associated with a diverging correlation length following a power law time-to-failure relation. We estimate the correlation length directly from an earthquake catalog using single-link cluster analysis. Therefore we assume that the distribution of moderate earthquakes reflects the state of the regional stress field. The parameters of the analysis are determined by an optimization procedure, and the results are tested against a Poisson process with realistic distributions of epicenters, magnitudes, and aftershocks. A systematic analysis of all earthquakes with M≥6.5 in California since 1952 is conducted. In fact, we observe growing correlation lengths in most cases. The null hypothesis that this behavior can be found in random data is rejected with a confidence level of more than 99%. Furthermore, we find a scaling relation log R∼0.7M (log〈ξmax〉 ∼ 0.5M), between the mainshock magnitude M and the critical region R (the correlation length 〈ξmax〉 before the mainshock), which is in good agreement with theoretical values.
Evolutionary Theory Has Arrived in the Human Behavioral Sciences—But Not The Structure of Higher Education

Evolutionary theory has been restricted to the biological sciences and avoided for most human-related subjects for most of the 20 century. This situation is rapidly changing, resulting in a mismatch between current research and the structure of higher education. Using the journal Behavioral and Brain Sciences as a microcosm, I show that a large fraction of target articles are written from an evolutionary perspective across a diversity of subject areas. Since BBS is one of the premier journals in the human behavioral sciences, this demonstrates that the evolutionary perspective is not fringe science (as often portrayed), or future science, but has already arrived. Nevertheless, a survey sent to the authors of these articles reveals that a) most did not receive formal evolutionary training during their own higher education and acquired their expertise on their own; b) many feel isolated within their own departments and universities, despite being at the forefront of research nationally and internationally; and c) most estimate that the situation at their current institution is little different for today’s graduate students than when they were graduate students. In short, a major theoretical perspective in the human behavioral sciences is not yet reflected in the structure of higher education.
Pancreatic B-cell function is altered by oxidative stress induced by acute hyperglycaemia

Aims Type 2 diabetes is preceded by a symptom‐free period of impaired glucose tolerance (IGT). Pancreatic B‐cell function decreases as glucose intolerance develops. In many patients with IGT, fasting blood glucose is within normal limits and hyperglycaemia occurs only postprandially. We examined whether pancreatic B‐cell function changes during acute hyperglycaemia induced by oral glucose loading.
Using Imperfect Information in Online Social Systems: Applications and Measures of Betweenness

Online social software systems enable individuals to build representations of their network of social ties, and such information can be used for the analysis of network structure and the position of individuals in the network. However, social ties representing relationships as “friendship” have intensity or strength as an intrinsic, essential feature, and this needs to be taken into account in network models. This paper reports on fuzzy techniques that deal with imprecise information on the strength of social ties, and provides an extended model of brokerage that accounts for such imprecise information.
Modeling, filtering and optimization for AFM arrays

In this paper, we present new tools and results developed for Arrays of Microsystems and especially for Atomic Force Microscope (AFM) array design. For modeling, we developed a two-scale model of cantilever arrays in elastodynamics. A robust optimization toolbox is interfaced to aid for design before the microfabrication process. A model based algorithm of static state estimation using measurement of mechanical displacements by interferometry is stated. Quantization of interferometry data processing is analyzed for FPGA implementation. A robust H∞ filtering problem of the coupled cantilevers is solved for time-invariant system with random noise effects. Our solution allows semi-decentralized computing based on functional calculus that can be implemented by networks of distributed electronic circuits as shown in a previous paper.
Adaptation of bimanual assembly tasks using iterative learning framework

The paper deals with the adaptation of bimanual assembly tasks. First, the desired policy is shown by human demonstration using kinesthetic guidance, where both trajectories and interaction forces are captured. Captured entities are portioned to absolute and relative coordinates. During the execution, small discrepancies in object geometry as well as the influence of an imperfect control can result in large contact forces. Force control can diminish the above mentioned problems only to some extent. Therefore, we propose a framework that iteratively modifies the original demonstrated trajectory in order to increase the performance of the typical assembly tasks. The approach is validated on bimanual peg in a hole task using two KUKA LWR robots.
Localization of inositol 1,4,5-trisphosphate receptor-like protein in plasmalemmal caveolae

Activation of various receptors by extracellular ligands induces an influx of Ca2+ through the plasma membrane, but its molecular mechanism remains elusive and seems variable in different cell types. In the present study, we utilized mAbs generated against the cerebellar type I inositol 1,4,5-trisphosphate (InsP3) receptor and performed immunocytochemical and immunochemical experiments to examine its localization in several non-neuronal cells. By immunogold electron microscopy of ultrathin frozen sections as well as permeabilized tissue specimens, we found that a mAb to the type I InsP3 receptor (mAb 4C11) labels the plasma membrane of the endothelium, smooth muscle cell and keratinocyte in vivo. Interestingly, the labeling with the antibody was confined to caveolae, smooth vesicular inpocketings of the plasma membrane. The reactive protein, with an M(r) of 240,000 by SDS-PAGE, could be biotinylated with a membrane-impermeable reagent, sulfo-NHS- biotin, in intact cultured endothelial cells, and recovered by streptavidin-agarose beads, which result further confirmed its presence on the cell surface. The present findings indicate that a protein structurally homologous to the type I InsP3 receptor is localized in the caveolar structure of the plasma membrane and might be involved in the Ca2+ influx.