Miracle-dz/UniFAR-FTUs huggingface dataset:
On the “Where” of Social Experiments: Selecting More Representative Samples to Inform Policy

Most social experiments are conducted in samples of sites that are not formally representative of the population of policy interest. These studies may produce impact estimates that are unbiased for the sample but biased for the population from which the sample was selected. Recent research has estimated the bias associated with nonrandom inclusion. Although some research has focused on solutions to the problem at the design stage or the analysis stage, research on ways to address this problem is still sparse. This paper provides four recommendations to help researchers obtain more representative samples in impact studies. The fundamental challenge is that, in most impact studies, sites are not required to participate if selected. Therefore, obtaining a sample that adequately represents the population of policy interest can be difficult, and the resulting impact estimates may suffer from external validity bias. The recommendations in this chapter address this challenge to help researchers obtain more representative samples when obtaining a perfectly representative sample is not possible. The recommendations, which are based on standard survey sampling methods, demonstrate that researchers can take practical steps to obtain impact estimates that are more generalizable from the study sample to the broader population of policy interest—and therefore more relevant for informing policy decisions.
CDIO concept in Challenge Based Learning

In this paper an implementation of Challenge Based Learning in Embedded Engineering as a part of CDIO Syllabus in Helsinki Metropolia University of Applied Sciences (UAS) is studied and described. CDIO Initiative is an educational framework for engineering education to integrate active learning methods as fundamental part of the syllabus. The Challenge Based Learning (CBL) method and its implementation described in this paper are based on a study of project based learning in engineering education started in academic year 2004 [1]. The project described in this paper is the 5th Challenge Based Learning project which took place during the spring semester of the academic year 2008--2009. The paper focuses on introducing Challenge Based Learning method and the implementation of the CBL project as one of the first steps in transformation to CDIO syllabus. Also a discussion of learning outcomes, required resources and the experiences of tutoring lecturers are included as well as some recommendations for arranging similar learning events.
Design Exploration for next Generation High-Performance Manycore On-chip Systems: Application to big.LITTLE Architectures

Next generation embedded systems will massively adopt on-chip many core architectures to provide both performance and energy-efficiency. This trend will definitely establish the convergence of embedded computing and high-performance computing. In such a context, one major design challenge will concern the choice of adequate architecture parameters given system requirements. Moreover, it will affect the way applications can suitably exploit architecture resources for an efficient execution. This paper deals with many core on-chip system design exploration by using via simulation. It presents an approach enabling one to study central design parameters in an accurate and cost-effective manner. This approach is illustrated through the design exploration for ARM big. LITTLE heterogeneous multicore technology in the gem5 framework.
Path planning based on Constrained Delaunay Triangulation

This paper proposes a path planning algorithm for determining an optimal path with respect to the costs of a dual graph on the Constrained Delaunay Triangulation (CDT) of an environment. The advantages of using triangles for environment expression are: less data storage required, available mature triangulation methods and consistent with a potential motion planning framework. First we represent the polygon environment as a planar straight line graph (PSLG) described as a collection of vertices and segments, and then we adopt the CDT to partition the environment into triangles. Then on this CDT of the environment, a dual graph is constructed following the target attractive principle in order to avoid the nonoptimal paths caused by the different geometric size of the triangles. Correspondingly, a path planning algorithm via A* search algorithm finds an optimal path on the real-time building dual graph. In addition, completeness and optimization analysis of the algorithm is given. The simulation results demonstrate the effectiveness and optimization of the algorithm.
A fast filter-bank for adaptive Fourier analysis

Adaptive Fourier analyzers have been developed for measuring periodic signals with unknown or changing fundamental frequency. Typical applications are vibration measurements and active noise control related to rotating machinery and calibration equipment that can avoid the changes of the line frequency by adaptation. Higher frequency applications have limitations since the computational complexity of these analyzers are relatively high as the number of the harmonic components to be measured (or suppressed) is usually above 50. In this paper based on the concept of transformed domain signal processing a fast filter-bank structure is proposed to reduce the computational complexity. The first step of the suggested solution is the application of the filter-bank version of the fast Fourier transform or any other fast transformations that converts input data into the transformed domain. These fast transformers operate as a single-input multiple-output filter-banks, however, they cannot be adapted since their efficiency is due to their special symmetry. As a second step the adaptation of the filter-bank is performed at the transformers' output by adapting a simple linear combiner to the fundamental frequency of the periodic signal to be processed.
Cooperative Data Analysis in Supply Chains Using Selective Information Disclosure

Many modern products (e. g., consumer electronics) consist of hundreds of complex parts sourced from a large number of suppliers. In such a setting, finding the source of certain properties, e. g. , the source of defects in the final product, becomes increasingly difficult. Data analysis methods can be used on information shared in modern supply chains. However, some information may be confidential since they touch proprietary production processes or trade secrets. Important principles of confidentiality are data minimization and that each participant has control over how much information is communicated with others, both of which makes data analysis more difficult. In this work, we investigate the effectiveness of strategies for selective information disclosure in order to perform cooperative data analysis in a supply chain. The goal is to minimize information exchange by only exchanging information which is needed for the analysis tasks at hand. The work is motivated by the growing demand for cross company data analysis, while simultaneously addressing confidentiality concerns. As an example, we apply a newly developed protocol with association mining techniques in an empirical simulation study to compare its effectiveness with complete information disclosure. The results show that the predictive performance is comparable while the amount of exchanged information is reduced significantly.
Convergence in Productivity Across Industries: Some Results for New Zealand and Australia

Abstract New Zealand shares a wealth of common interests and experiences with Australia. This has tempted some to assume that these economies form an ‘Economic Club’, in which one would expect to identify common aggregate trends and growth experiences. In this paper we present results that test, and generally reject, convergence in labour productivity across Australia and New Zealand, using both aggregate and disaggregate, industry‐level data. We find that only two industries satisfy our definition of Conditional Convergence (Agriculture, Forestry and Fishing and Cultural and Recreational Services), and that the Mining and Wholesale Trade industries have particularly important roles to play in explaining the measured divergence. Cointegration‐based tests reveal more stochastic trends governing Australian productivity than in New Zealand. The evidence suggests, therefore, that the underlying growth processes of the two economies are fundamentally different, thereby questioning the relevance of aggregate comparisons between them. New evidence using industry‐level data does not, therefore, resolve the aggregate‐level ‘non‐convergence puzzle’ identified here, and elsewhere.
C *-Extreme Points of the Generalized State Space of a Commutative C *-Algebra

The generalized state space of a commutative C *-algebra, denoted S H (C(X)), is the set of positive unital maps from C(X) to the algebra B(H) of bounded linear operators on a Hilbert space H. C *-convexity is one of several non-commutative analogs of convexity which have been discussed in this context. We show that a C *-extreme point of S H (C(X)) satisfies a certain spectral condition on the operators in the range of an associated measure, which is a positive operator-valued measure on X. We then show that C *-extreme maps from C(X) into K + , the C *-algebra generated by the compact and scalar operators, are multiplicative, generalizing a result of D. Farenick and P. Morenz. iii ACKNOWLEDGMENTS I would like to express my gratitude to the many people who have offered support and encouragement during my years as a graduate student. Particular thanks go to Sylvia Wiegand and Judy Walker, who initially (and persistently) encouraged me to return to graduate school. During the summer before starting my course work at UNL, David Pitts was exceptionally generous with his time and expertise as I labored to remember the mathematics I had managed to forget since completing my Master's degree some years earlier. In spite of that experience, he was kind enough to agree to supervise my work on this thesis; I could hardly have hoped for a more supportive and helpful advisor. Our many discussions have greatly contributed to the work presented here. I am also grateful to the members of my thesis committee: Allan Donsig and Mark Walker, whose suggestions and proofreading have improved the thesis, and Diandra Leslie-Pelecky, whose encouragement as I prepared for my oral comprehensive exam was particularly appreciated. There are many graduate students in the department whose friendship I enjoy and treasure ; among them are Teena Carroll and Kirsten Messer (the other two Musketeers), and my office mates Mu-Wan Huang and Ela Celikbas: grad school wouldn't have been the same without you! Cheryl Kane, my office mate during my years as a lecturer, is my friend, my colleague, and my hero. Special thanks are due my parents, who have supported my education from the very beginning and in every way imaginable. Finally, and most importantly, I thank my husband, John, who keeps me on an even keel, and our wonderful children Claire and John Jr., who give me a reason …
Per Klemm K-12 Escherichia coli Colony Morphology of Antigen 43 and Type 1 Fimbriae Determine

Colony morphology has been used as an important identification and characterization criterion in bacteriology for many decades. However, the molecular mechanisms underlying the appearance of different colony types have been given little attention. The synthesis of O antigen is defunct in Escherichia coli K-12, and colonies should accordingly only appear to be rough. However, previous reports have noted the presence of different interchangeable colony morphology types. In this study we have addressed the influence of two phase-variable surface structures, antigen 43 and type 1 fimbriae, on colony morphology. Due to differential expression of these structures, four different colony phenotypes could be distinguished. By creating and studying defined mutants of the respective loci, i.e., flu and fim, we conclude that the presence or absence of the corresponding gene products on the cells correlates with the observed colony morphology forms. Interestingly, the habitat specificity of bacteria under static liquid conditions seems to correlate with the colony phenotypes. In nature bacteria often grow as colonies on surfaces. Observation of colony development and morphology has for many years been an important tool for identification and characterization of bacteria because individual species often form colonies of characteristic size and appearance. However, even when a pure bacterial culture is plated out, different morphological colony types often arise. Traditionally, the colony morphology of Escherichia coli is identified as either a rough or a smooth form. The two forms are readily distinguished, as the colonies of the former are rough, flat, and irregular and colonies of the latter are smooth, high, and circular. E. coli K-12 strains are rough, their lipopolysaccharide having a complete core but no O antigen due to the insertion of an IS5 element in the rfb gene cluster controlling O antigen biosynthesis (23). Only extremely rarely are K-12 strains able to revert to the smooth form, as this requires the integrity of the rfb gene cluster to be restored. Nonetheless, K-12 strains have been observed to exhibit different interchangeable colony types. Diderichsen (7) partially identified a mechanism controlling the colony morphology of K-12 strains. The observed phenotypes were somewhat similar to the ones seen for rough and smooth strains, but the strains frequently switched between the two. To distinguish these from the rough and smooth phenotypes related to lipopolysaccharide status, the rough, flat, and irregular variant was designated frizzy, or form 1, and the smooth, convex, circular variant was designated glossy, or form 2 …
Applications of Discrete and Continuous Network Theory to Linear Population Models

The well-established methods of network construction and analysis are adapted to the problem of modeling single populations. A major advantage of the resulting approach is that it allows explicit incorporation of key processes in the life cycle of the organism being modeled, with feedback loops providing economy of representation where they are allowed. Thus, network structures provide heuristic vehicles by which population models can be de- veloped and modified. When a model is linear and has parameters that do not vary with time, a characteristic dynamic function can be derived by inspection from a simple transform of the network representation. The zeros of the function can be found (analytically or by commonly available numerical methods) and used directly to deduce the modeled population's dominant growth pattern and its propensity to sustain oscillations. In addition, under certain conditions (i.e., that the network model not contain both time delays and integrators), a straightforward method (partial fraction expansion) is available for deduction of the modeled population's specific responses to a variety of perturbations.
Coded BER minimization for MIMO multicarrier systems with imperfect channel estimates

Linear transmitter designs that minimize the MSE or the uncoded BER do not guarantee good bit error performance when any channel correction code is introduced. As an alternative, the cutoff rate, that has been considered for a long time as the practical bound on the performance that could be achieved by finite length channel codes, can provide a good performance not for an specific channel code but for the average over the ensemble of codes with block length N. This work presents a robust power allocation strategy that maximizes the cut-off rate using partial channel state information (CSI) at the transmitter. A Bayesian formulation is used to design an optimal transmitter when CSI is noisy. A closed-form solution for the transmitter design is obtained. In addition, the design adapts to the CSI quality, providing an algorithm that tends to the open-loop design when no CSI is available at the transmitter (i.e., the same power is allocated across all antennas and subcarriers).
Negative Tests and the Efficiency of Medical Care: What Determines Heterogeneity in Imaging Behavior?

We develop a model of the efficiency of medical testing based on rates of negative CT scans for pulmonary embolism. The model is estimated using a 20% sample of Medicare claims from 2000- 2009. We document enormous across-doctor heterogeneity in testing decisions conditional on patient risk and show it explains the negative relationship between physicians' testing frequencies and test yields. Physicians in high spending regions test more low-risk patients. Under calibration assumptions, 84% of doctors test even when costs exceed expected benefits. Furthermore, doctors do not apply observables to target testing to the highest risk patients, substantially reducing simulated test yields.
Competences memory map: A model for the representation of competences applied in education

A skill is a basic unit for cognitive processing that allows the use of concepts. A competence is the result of the application of a skill on a concept. Competences and their development play a central role in most educational and training programs. This paper presents a new formal model for the representation of competences in persons and machines, called Competences Memory Map, an extension of Memory Map [17], a model capable of representing skills and competences in an integrated, simple and flexible way. Competences Memory Map is a formal model described with set theory, handled with concept algebra, and computationally implementable. The formal description of algebraic and algorithmic operations over the model, as well as case studies demonstrate that Competences Memory Map model properties hold as expected in dealing with complex real structures.
Target Detection and Recognition through Contour Matching

SUMMARY This report presents a combinatorial approach to the detection and recognition of instancesof a parameterized target contour model in grey-level images.Targetdetectionisformulatedasanoptimizationproblem. Theobjectivefunctionmeasuresthe evidentialsupportforany particularprojectionof the parametrized target contourmodelonto the input image. A combinatorial algorithm is used to ﬁnd a set of parameters whichprovide a good (though not necessarily optimal) interpretation of the image in terms of themodel.Target classiﬁcation can be performed through comparison of the parameters of the best ﬁtwith those of the prototypes in a data base. The contour matching algorithm can thereforebe used as a basis for a scale- and pose-invariant target recognition system.The results of a preliminary test, using a genetic algorithm to ﬁnd the best match betweena contour model and the image, demonstrate the feasibility of the approach.The EUCLID (EUropean Cooperation for the Long term In Defence) CALMA (Combina-torial Algorithms for Military Applications) RTP (Research and Technology Project) 6.4project has the main objective to investigate the relevance of various existing algorithmicoptimizationtechniquestotheactualsolutionof complexcombinatorialproblemsarisinginmilitary applications. The target detection algorithm presented here may serve as a testbedfor this purpose. The application of (hybrids of) a range of combinatorial optimizationtechniques in the context of this algorithm may serve to gain a better understanding of thesemethods.
The PTB interacting protein raver1 regulates α‐tropomyosin alternative splicing

Regulated switching of the mutually exclusive exons 2 and 3 of α‐tropomyosin (TM) involves repression of exon 3 in smooth muscle cells. Polypyrimidine tract‐binding protein (PTB) is necessary but not sufficient for regulation of TM splicing. Raver1 was identified in two‐hybrid screens by its interactions with the cytoskeletal proteins actinin and vinculin, and was also found to interact with PTB. Consistent with these interactions raver1 can be localized in either the nucleus or cytoplasm. Here we show that raver1 is able to promote the smooth muscle‐specific alternative splicing of TM by enhancing PTB‐mediated repression of exon 3. This activity of raver1 is dependent upon characterized PTB‐binding regulatory elements and upon a region of raver1 necessary for interaction with PTB. Heterologous recruitment of raver1, or just its C‐terminus, induced very high levels of exon 3 skipping, bypassing the usual need for PTB binding sites downstream of exon 3. This suggests a novel mechanism for PTB‐mediated splicing repression involving recruitment of raver1 as a potent splicing co‐repressor.
Septin ring assembly involves cycles of GTP loading and hydrolysis by Cdc42p

At the beginning of the budding yeast cell cycle, the GTPase Cdc42p promotes the assembly of a ring of septins at the site of future bud emergence. Here, we present an analysis of cdc42 mutants that display specific defects in septin organization, which identifies an important role for GTP hydrolysis by Cdc42p in the assembly of the septin ring. The mutants show defects in basal or stimulated GTP hydrolysis, and the septin misorganization is suppressed by overexpression of a Cdc42p GTPase-activating protein (GAP). Other mutants known to affect GTP hydrolysis by Cdc42p also caused septin misorganization, as did deletion of Cdc42p GAPs. In performing its roles in actin polarization and transcriptional activation, GTP-Cdc42p is thought to function by activating and/or recruiting effectors to the site of polarization. Excess accumulation of GTP-Cdc42p due to a defect in GTP hydrolysis by the septin-specific alleles might cause unphysiological activation of effectors, interfering with septin assembly. However, the recessive and dose-sensitive genetic behavior of the septin-specific cdc42 mutants is inconsistent with the septin defect stemming from a dominant interference of this type. Instead, we suggest that assembly of the septin ring involves repeated cycles of GTP loading and GTP hydrolysis by Cdc42p. These results suggest that a single GTPase, Cdc42p, can act either as a ras-like GTP-dependent “switch” to turn on effectors or as an EF-Tu–like “assembly factor” using the GTPase cycle to assemble a macromolecular structure.
Immunophenotype of Normal and Myelomatous Plasma-Cell Subsets

Plasma cells (PCs) are essentially characterized by the co-expression of CD138 and CD38, which allows their identification in flow cytometry in bone marrow (BM), peripheral blood, or cell suspensions from tissues. These terminally differentiated B-cells may lose the expression of surface CD19 and that of CD20 while retaining CD27. When malignant, they can gain a number of other markers such as CD28, CD33, CD56, or CD117 and lose CD27. Moreover, since each PC is only able to produce a single type of immunoglobulins (Igs), they display isotypic restriction and clonal malignant PCs can be further characterized by their homogeneous expression of either kappa or lambda light chains. In multiple myeloma (MM), such PC clones produce the Ig identified in plasma as an abnormal peak. In the BM where they essentially accumulate, these PCs may however display various immunophenotypes. The latter were explored in a two-way approach. Firstly, the various subsets delineated by the selective or common expression of CD19 together with combined CD56/CD28 were explored in normal and MM BM. Then, other aberrant markers’ expression was investigated, i.e., CD20, CD27, CD33, CD56, CD117. These data were compared to literature information. They underline the vast heterogeneity of MM PCs possibly accounting for the various answers to therapy of MM patients.