Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing semi-supervised document clustering with feature supervision

Traditional semi-supervised clustering uses only limited user supervision in the form of labeled instances and pairwise instance constraints to aid unsupervised clustering. However, user supervision can also be provided in alternative forms for document clustering, such as labeling a feature by indicating whether it discriminates among clusters. This paper thus fills this void by enhancing traditional semi-supervised clustering with feature supervision which asks the user to label discriminating features during labeling the instance or pairwise instance constraints. Various types of semi-supervised clustering algorithms were explored with feature supervision. Our experimental results on several real-world datasets demonstrate that augmenting the instance-level supervision with feature-level supervision can significantly improve document clustering performance.
An RBF–Galerkin approach to the time-dependent Schrödinger equation

The time-dependent Schrodinger equation (TDSE) models the quantum nature of molecular processes. Numerical simulations based on the TDSE help in understanding and predicting the outcome of chemical reactions. This thesis is dedicated to the derivation and analysis of efficient and reliable simulation tools for the TDSE, with a particular focus on models for the interaction of molecules with time-dependent electromagnetic fields.Various time propagators are compared for this setting and an efficient fourth-order commutator-free Magnus-Lanczos propagator is derived. For the Lanczos method, several communication-reducing variants are studied for an implementation on clusters of multi-core processors. Global error estimation for the Magnus propagator is devised using a posteriori error estimation theory. In doing so, the self-adjointness of the linear Schrodinger equation is exploited to avoid solving an adjoint equation. Efficiency and effectiveness of the estimate are demonstrated for both bounded and unbounded states. The temporal approximation is combined with adaptive spectral elements in space. Lagrange elements based on Gauss-Lobatto nodes are employed to avoid nondiagonal mass matrices and ill-conditioning at high order. A matrix-free implementation for the evaluation of the spectral element operators is presented. The framework uses hybrid parallelism and enables significant computational speed-up as well as the solution of larger problems compared to traditional implementations relying on sparse matrices.As an alternative to grid-based methods, radial basis functions in a Galerkin setting are proposed and analyzed. It is found that considerably higher accuracy can be obtained with the same number of basis functions compared to the Fourier method. Another direction of research presented in this thesis is a new algorithm for quantum optimal control: The field is optimized in the frequency domain where the dimensionality of the optimization problem can drastically be reduced. In this way, it becomes feasible to use a quasi-Newton method to solve the problem.
Konrad-zuse-zentrum F ¨ Ur Informationstechnik Berlin Enhanced Paxos Commit for Transactions on Dhts Enhanced Paxos Commit for Transactions on Dhts

—Key/value stores which are built on structured overlay networks often lack support for atomic transactions and strong data consistency among replicas. This is unfortunate, because consistency guarantees and transactions would allow a wide range of additional application domains to benefit from the inherent scalability and fault-tolerance of DHTs. The Scalaris key/value store supports strong data consistency and atomic transactions. It uses an enhanced Paxos Commit protocol with only four communication steps rather than six. This improvement was possible by exploiting information from the replica distribution in the DHT. Scalaris enables implementation of more reliable and scalable infrastructure for collaborative Web services that require strong consistency and atomic changes across multiple items.
Diagnosis of Board-Level Functional Failures Under Uncertainty Using Dempster–Shafer Theory

Despite recent advances in structural test methods, the diagnosis of the root cause of board-level failures for functional tests remains a major challenge. A promising approach to address this problem is to carry out fault diagnosis in two phases-suspect faulty components on the board or modules within components (together referred to as blocks in this paper) are first identified and ranked, and then fine-grained diagnosis is used to target the suspect blocks in a ranked order. We propose a new method based on dataflow analysis and Dempster-Shafer (DS) theory for ranking faulty blocks in the first phase of diagnosis. The proposed approach transforms the information derived from one functional test failure into multiple-stage failures by partitioning the given functional test into multiple stages. A measure of “belief” is then assigned to each block based on the knowledge of each failing stage, and the DS theory is subsequently used to aggregate the beliefs from multiple failing stages. Blocks with higher beliefs are ranked on the top of the candidate list. Simulations on an industry design for a network interface application as well as on an open source system-on-a-chip show that the proposed method can provide accurate ranking for most board-level functional failures.
Visual task complexity modulates the brain's response to unattended auditory novelty

New, unusual, and changing events are important environmental cues, and the ability to detect these types of stimuli in the environment constitutes a biologically significant survival skill. We used event-related potentials to examine whether sensory and cognitive neural responses to unattended novel events are modulated by the complexity of a primary visuomotor task. Event-related potentials were elicited by unattended task-irrelevant pitch-deviant tones and novel environmental sounds while study participants performed a continuous visuomotor tracking task at two levels of difficulty, achieved by manipulating the control dynamics of a joystick. The results revealed that increased task complexity modulated evoked sensory and cognitive event-related potential components, indicating that detection of change and novelty in the unattended auditory channel is resource-limited.
The Use of Zebrafish (Danio rerio) Behavioral Responses in Identifying Sublethal Exposures to Deltamethrin

Alterations of fish behavioral responses are sensitive indicators to identify accidental chemical pollution. In this research, a series of exposure tests were conducted to investigate behavioral changes of adult zebrafish (Danio rerio) exposed to deltamethrin (DM) in six concentrations of 0, 0.15, 1.5, 3.75, 7.5 and 15 μg/L. Swimming changes in zebrafish were detected at a concentration as low as 1% of the LC50-24h within five hours. Hyperactivity was the first response, followed by a second response of fish surfacing. The change patterns of swimming speed in zebrafish were similar in all exposure groups, but the degree increased with increasing concentrations. Swimming speed and depth were altered within the first two hours after exposure, which was regarded as the most vital phase for water quality monitoring. The duration of hyperactivity and the time of zebrafish surfacing were both logarithmically correlated with exposure concentrations, which was helpful to distinguish the level of pollution.
Economic impact of diabetic ketoacidosis in a multiethnic indigent population: analysis of costs based on the precipitating cause.

OBJECTIVE Diabetic ketoacidosis (DKA) is a common complication of diabetes. We analyzed the inpatient costs of treating DKA in a multiethnic, indigent population in Houston, Texas. RESEARCH DESIGN AND METHODS We measured the cost of resources utilized for all patients admitted to our hospital with DKA from 1 January to 31 December 1998. We also analyzed their medical records to determine the factors that precipitated the episode of DKA and then grouped them into three categories: acute illnesses, noncompliance with diabetes treatment, and new-onset diabetes. The data were analyzed by one-way ANOVA. The Tukey-Kramer procedure was used for post hoc multiple comparisons. RESULTS There were 167 admissions for DKA. The mean age was 40 +/- 13 years. The ethnic distribution was 49% African American, 32% Hispanic American, and 18% white. The total inhospital cost of treating DKA was $1,816,255. The mean cost per hospitalization was $10, 876 +/- 11,024. The frequency distribution by category of DKA-precipitating factor was 18% acute illness, 59% noncompliance, and 23% new onset. There were differences in mean cost of DKA associated with the three categories: $20,864 +/- 17,910 for acute illness, $11,863 +/- 8,701 for new onset, and $7,470 +/- 6,300 for noncompliance (P < 0.0001). The total cost for each category was $671,375 for acute illness, $694,082 for noncompliance, and $450,798 for new onset. CONCLUSIONS DKA is an expensive complication among indigent, multiethnic diabetic patients. Although the mean cost per admission was lowest for DKA precipitated by noncompliance, this causal category was responsible in sum for the greatest portion of the economic burden.
Robust LPV controller synthesis with uncertainty modeling

The paper presents an iterative uncertainty modeling and robust controller synthesis method for linear parameter-varying (LPV) systems in linear fractional transformation (LFT) form. The goal of the method is to improve robust performance by exploiting modeling freedom in the structured uncertainty descriptions while ensuring model consistency with respect to measurement data. The proposed iterative algorithm consists of three steps: robust LPV controller synthesis, tuning of the uncertainty model and performing closed-loop experiments for new validation data.
Linked Data Integration with Conflicts

Linked Data have emerged as a successful publication format and one of its main strengths is its fitness for integration of data from multiple sources. This gives them a great potential both for semantic applications and the enterprise environment where data integration is crucial. Linked Data integration poses new challenges, however, and new algorithms and tools covering all steps of the integration process need to be developed. This paper explores Linked Data integration and its specifics. We focus on data fusion and conflict resolution: two novel algorithms for Linked Data fusion with provenance tracking and quality assessment of fused data are proposed. The algorithms are implemented as part of the ODCleanStore framework and evaluated on real Linked Open Data.
Identifying Distributional Effects of Teachers and Peers in Nonseparable Models ∗

This paper looks at the effects of teacher and peer characteristics on student achievement in the STAR Project conducted in Tennessee in the late 1980s. As in standard linear models, the proposed approach considers two types of unobservables: school-specific effects and idiosyncratic disturbances. It generalizes previous empirical research by allowing both effects to enter the structural function nonseparably. No functional form assumptions are needed for identification. Instead, it uses an exchangeability condition in the way that covariates affect the distribution of the school-specific effects. The model permits nonparametric distributional and counterfactual analysis of heterogeneous effects: it extends policy analysis beyond marginal or discrete changes to consider distributional effects originating from a counterfactual change in the distribution of characteristics of classrooms, peers and teachers. Also, these impacts can be analyzed on any feature of the distribution of student achievement, such as quantiles and inequality measures. The empirical analysis looks at the effects of class size, teacher experience and gender composition of the classroom on test scores. Findings suggest that nonseparable heterogeneity is an important source of individual-level variation in academic performance. The impact of class size is considerably larger using my approach: students in smaller classes benefit about 0.3 standard deviations, compared to a 0.16 effect obtained using a standard linear model. Also, teacher experience has a stronger, nonlinear impact. Still, the distributional analysis suggests that these gains are hard to achieve when facing resource constraints.
Feasible alphabets for communicating the sum of sources over a network

We consider directed acyclic sum-networks with m sources and n terminals where the sources generate symbols from an arbitrary alphabet field F, and the terminals need to recover the sum of the sources over F. We show that for any co-finite set of primes, there is a sum-network which is linearly solvable only over fields of characteristics belonging to that set. We further construct a sum-network where a scalar linear solution exists over all fields other than the binary field F2. We also show that a sum-network is linearly solvable over a field if and only if its reverse network is linearly solvable over the same field.
Quality Assurance for Fortran 90A Survey of Available Tools

This report provides a survey of some of the software tools currently available to assist in the development of Fortran programs using the new 1990 and 1995 standards. A few tools also address the development of High Performance Fortran (HPF). This report is particularly concerned with tools which will enhance the quality of software developed. We have not looked at tools which focus on the high level design and requirements analysis, since these are often common to many languages. Instead we have concentrated on tools that help in the detection of programming errors and highlight poor practice, such as “spaghetti” style coding. At present, there appear to be few such tools available for the new Fortran standard. However, many Fortran 90 compilers can provide quite extensive compile and run time checks and some examples of these are also discussed.
Neuronal activity differentially regulates NMDA receptor subunit expression in cerebellar granule cells

Reverse-transcription PCR assays were used to measure levels of NMDA receptor (NR) subunit mRNAs encoding splice variants of NR1 (NR1a, -exon 5; NR1b, +exon 5) and the major NR2 subunits (NR2A, NR2B, and NR2C) in dissociated cerebellar granule cell cultures. Cultures chronically exposed to 25 mM KCl or 100 microM NMDA/15 mM KCl, which promote survival by stimulating Ca2+ influx through voltage-sensitive Ca2+ channels or NRs, were compared with 5 mM KCl culture conditions, which results in limited cell survival attributable to a lower level of NR stimulation by ambient glutamate. In situ granule-cell maturation is associated with downregulation of NR2B and increases both of NR2A and NR2C and in the ratio of NR1b/NR1a mRNAs. In culture, 25 mM KCl or NMDA rapidly induced NR2A and downregulated NR2B, followed by gradual induction of NR2C. In 5 mM KCl, a similar, rapid increase in NR2A was observed, but disappearance of NR2B occurred over a longer time course. By 9-12 d in vitro in 5 mM KCl, the relative proportions of all three NR2 mRNAs in surviving cells were not significantly different from cells cultured in 25 mM KCl. NR1a mRNA predominated at every stage of culture in 25 mM KCl or NMDA, however, whereas gradual induction of the mature-form NR1b was observed in 5 mM KCl. Although using high potassium- or NMDA-containing media enhanced granule cell survival, it did not reproduce the pattern of expression of NR mRNAs observed in situ, whereas this pattern was observed in granule cells surviving in 5 mM KCl.
Finite Element Solution of Unsteady Mixed Convection Flow of Micropolar Fluid over a Porous Shrinking Sheet

The objective of this investigation is to analyze the effect of unsteadiness on the mixed convection boundary layer flow of micropolar fluid over a permeable shrinking sheet in the presence of viscous dissipation. At the sheet a variable distribution of suction is assumed. The unsteadiness in the flow and temperature fields is caused by the time dependence of the shrinking velocity and surface temperature. With the aid of similarity transformations, the governing partial differential equations are transformed into a set of nonlinear ordinary differential equations, which are solved numerically, using variational finite element method. The influence of important physical parameters, namely, suction parameter, unsteadiness parameter, buoyancy parameter and Eckert number on the velocity, microrotation, and temperature functions is investigated and analyzed with the help of their graphical representations. Additionally skin friction and the rate of heat transfer have also been computed. Under special conditions, an exact solution for the flow velocity is compared with the numerical results obtained by finite element method. An excellent agreement is observed for the two sets of solutions. Furthermore, to verify the convergence of numerical results, calculations are conducted with increasing number of elements.
On Plug-ins and Extensible Architectures

In a world of increasingly complex computing requirements, we as software developers are continually searching for that ultimate, universal architecture that allows us to productively develop high-quality applications. This quest has led to the adoption of many new abstractions and tools. Some of the most promising recent developments are the new pure plug-in architectures. What began as a callback mechanism to extend an application has become the very foundation of applications themselves. Plug-ins are no longer just add-ons to applications; today’s applications are made entirely of plug-ins. This field has matured quite a bit in the past few years, with significant contributions from a number of successful projects.
Weed Seeds Classification Based on PCA, 2DPCA, Column-directional 2DPCA and (2D)2PCA

Weed seeds classification is significant to seed selection and weed prevention and control in both agriculture and grass industry. There have already been some classification methods based on image-processing which mainly deal with the seedling of weeds[1][2]. We propose to classify weeds with their digital images by using PCA, 2DPCA, column-directional 2DPCA and (2D)2PCA. With 20 repeated experiments, we prove that applying these dimensionality-reduction algorithms to seed images processing is feasible and can achieve an ideal result. We evaluate these methods by both the average results and the optimal results from which we know (2D)2PCA is more efficient and accurate than others. 2DPCA and c2DPCA do not outperform PCA in our experiment but they need fewer dimensions to reach their respective highest recognition accuracy
A CHARACTERIZATION OF FACES OF THE BASE POLYHEDRON ASSOCIATED WITH A SUBMODULAR SYSTEM

For a distributive lattice J) ~ 2E and a submodular function f on J) with </1 E J) and f(</1) = 0, the pair (J), f) is called a submodular system and, when E EJ), the polyhedron given by B(f) = {x I x E RE, \IX EJ): x(X) ~ f(X),x(E) = f(E) ) is called the base polyhedron associated with (J), f). We examine the structure of the base polyhedron B(f) and give a characterization of all the faces of B(f). Faces of B(f) are made correspond one-to-one to certain sublattices of J), so that the collection D of all such sublattices of.7) is anti-isomorphic with the collection F of all the non­ empty faces of B(f). Here, D and F are considered as posets relative to set inclusion. The incidence relation among faces, dimensions of faces, and extreme points and extreme rays of faces are given based on the structure of the sublattices in D. These include as special cases recent results on (1) a poset structure of a polymatroid extreme point and connected components by Bixby, Cunningham and Topkis, (2) extreme rays of a cone determined by a distributive lattice by Tomizawa, and (3) adjacency for polymatroid extreme points by Topkis. Moreover, given a sublattice.7)1 of J) on which f is modular, F(J)I) = (x I x E B(f), \IX EJ)I: x(X) = f(X) ) is a nonempty face of B(f) and there uniquely exists a sublattice J)2 in D which corresponds to the face F(J)J). We show a theorem which characterizes the relationship between J)J and J)2' J)2 is considered as a closure of . DJ and this closure operation is closely related to the concept of maximal skeleton recently considered by Nakamura and lri. Algorithmic aspects of these characterizations are also discussed.
Understanding Homeland Security : Theory and UK-Evidence

We investigate the relationship between defense spending and terrorism by testing the predictions of a game-theoretic model on the interaction between a benevolent government and a terrorist organization with UK data. In doing so we apply both linear and non-linear methods. Consistent with our theoretical results we provide evidence in favor of the non-linear approach. Both, our theoretical model as well as the empirical evidence suggest that a strategy of high defense spending reduces the probability of being in a state of high terror in the consecutive period.
Interdigitated 3-D Silicon Ring Microelectrodes for DEP-Based Particle Manipulation

This paper describes the design, the fabrication, and the characterization of an interdigitated 3-D silicon (Si) ring microelectrodes for dielectrophoretic (DEP) manipulation of particles. The 3-D microelectrodes are derived from a high-aspect-ratio comb structure etched in a doped single crystal Si on an insulating dielectric (silicon-on-insulator). Fingers of the comb are evolved into ring microelectrodes once perforated with a linear array of well-defined round lateral constrictions. This is achieved by the segmented finger layout and the Si dry release strategy borrowed from inertial microelectromechanical systems. The fingers and their interspaces are sealed with a cover layer forming a microfluidic flow chamber surrounded by 3-D microelectrodes and accessible via single inlet/outlet. The functionality of the device has been verified on 2- and 10-μm polystyrene microspheres in pressure-driven flow through the ring microelectrodes at 3.3 μL/min effectively focusing them into streams or trapping them around the fingers at moderate voltage levels (20-40 Vpp).