Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Analysis of Boolean Equation Systems

We analyze the problem of solving Boolean equation systems through the use of structure graphs. The latter are obtained through an elegant set of Plotkin-style deduction rules. Our main contribution is that we show that equation systems with bisimilar structure graphs have the same solution. We show that our work conservatively extends earlier work, conducted by Keiren and Willemse, in which dependency graphs were used to analyze a subclass of Boolean equation systems, viz., equation systems in standard recursive form. We illustrate our approach by a small example, demonstrating the effect of simplifying an equation system through minimization of its structure graph.
The role of privacy concerns in the sharing economy

ABSTRACT Internet-mediated sharing is growing quickly. Millions of users around the world share personal services and possessions with others ‒ often complete strangers. Shared goods can amount to substantial financial and immaterial value. Despite this, little research has investigated privacy in the sharing economy. To fill this gap, we examine the sharing–privacy nexus by exploring the privacy threats associated with Internet-mediated sharing. Given the popularity of sharing services, users seem quite willing to share goods and services despite the compounded informational and physical privacy threats associated with such sharing. We develop and test a framework for analyzing the effect of privacy concerns on sharing that considers institutional and social privacy threats, trust and social-hedonic as well as monetary motives.
Measuring the quality of design pattern detection results

Detecting design patterns in large software systems is a common reverse engineering task that can help the comprehension process of the system's design. While several design pattern detection tools presented in the literature are capable of detecting design patterns automatically, evaluating these detection results is usually done in a manual and subjective fashion. Differences in design pattern definitions, as well as pattern instance counting and presenting, exacerbate the difficulty of evaluating design pattern detection results. In this paper, we present a novel approach to evaluating and comparing design pattern detection results. Our approach, called MoRe, introduces a novel way to present design pattern instances in a uniform fashion. Based on this characterization of design pattern instances, we propose four measures for design pattern detection evaluation that convey a concise assessment of the quality of the results produced by a given detection method. We have implemented these measures, and present case studies that showcase their usefulness.
Proteasomal Degradation of Rpn4 in Saccharomyces cerevisiae Is Critical for Cell Viability Under Stressed Conditions

The proteasome homeostasis in Saccharomyces cerevisiae is regulated by a negative feedback loop in which the transcription factor Rpn4 induces the proteasome genes and is rapidly degraded by the assembled proteasome. In addition to the proteasome genes, Rpn4 regulates numerous other genes involved in a wide range of cellular pathways. Therefore, the Rpn4–proteasome negative feedback circuit not only controls proteasome abundance, but also gauges the expression of other Rpn4 target genes. Our previous work has shown that Rpn4-induced gene expression is critical for cell viability under stressed conditions. Here we investigate whether proteasomal degradation of Rpn4 is also important for cell survival in response to stress. To this end, we generate a stabilized Rpn4 mutant (Rpn4*) that retains its transcription activity. We find that expression of Rpn4* severely reduces cell viability in response to various genotoxic and proteotoxic agents. This detrimental effect can be eliminated by a point mutation that abolishes the transcription activity of Rpn4*, suggesting that overexpression of some Rpn4 target genes weakens the cell's ability to cope with stress. Moreover, we demonstrate that inhibition of Rpn4 degradation causes synthetic growth defects when combined with proteasome impairment resulting from mutation of a proteasome gene or accumulation of misfolded endoplasmic reticulum membrane proteins. Rpn4 thus represents an important stress-responsive mediator whose degradation as well as availability are critical for cell survival under stressed conditions.
Measurement of Cerebrospinal Fluid Output through External Ventricular Drainage in One Hundred Infants and Children: Correlation with Cerebrospinal Fluid Production

Objective: Cerebrospinal fluid (CSF) production rates influence shunt design and the care of children with hydrocephalus. Measurement of hourly CSF output through external ventricular drainage (EVD) reflects the CSF production. In the present study, hourly CSF outputs in children with hydrocephalus were measured while they were treated with EVD and correlated with the age, sex and body weight of the patients as well as other clinical parameters. Methods: One hundred children with hydrocephalus due to various causes had EVD treatment. Twenty-six had EVD on two or three separate occasions; thus, the CSF output measurements were observed and analyzed on the basis of 130 EVDs. The most common reason for EVD treatment was shunt infection (n = 75). The duration of EVDs ranged from 25 to 774 h (mean 269 h). The height of the drip chamber from the mid-head position ranged from 0 to 23 cm (mean 9.8 cm). The hourly CSF output was analyzed according to the patient’s age, sex and body weight as well as the presence of CSF infection. Results: The hourly CSF output rapidly increases during the first year of life. By the second year, it reaches 64% of the hourly CSF output of 15-year-old children. The mean hourly output ranged from 0.1 to 26.5 ml/h (mean 8.1 ml/h), with the standard deviation ranging from 0.4 to 10.8 ml/h (mean 5.2 ml/h). A regression analysis indicated that the age and body weight appeared to correlate with the hourly CSF output. Using the natural logarithm of age, body weight and sex, these predictors accounted for 50.9% of the variability in hourly CSF output. The regression equation is as follows: hourly CSF output = 2.78 – 2.23(male = 0, female = 1) + 0.97 log(age in years) + 2.26 log(body weight in kg). R sd = 3.36, R2 = 0.509. The type of infecting organism and the height of EVD did not influence the overall CSF output. Conclusion: The hourly CSF output fluctuates, but the CSF output increases logarithmically with age and body weight. The gender also influences the CSF output, with males having a greater output than females. The data produced by the present study will help us to understand CSF production rates in developing children. They will also help us in the care of children receiving EVD treatment, as well as in selecting and designing shunt systems.
Improving GARCH Volatility Forecasts

Many researchers use GARCH models to generate volatility forecasts. We show, however, that such forecasts are too variable. To correct for this, we extend the GARCH model by distinguishing two regimes with different volatility levels. GARCH effects are allowed within each regime, so that our model generalizes existing regime-switching models that allow for ARCH terms only. The empirical application on U.S. dollar exchange rates shows that our model indeed yields better volatility forecasts than single-regime GARCH and that the allowance for GARCH terms besides ARCH terms can be crucial for the forecast quality.
The Design of IF Delay Line in Spread Spectrum Communication Based on FPGA

In view of the high temperature’s stability of the SAW tap delay line requested and the lower precision questions and so on, a new method is put forward to apply a new multi-element logic circuit based on FPGA in IF delay line in spreading spectrum communication. The scheme is given to design the numerical control one-way analog scanning switch, the key component in the delay line. The simulation result indicates that the system can realize the function of the analog/digit IF signal numerical control delay, and reduce the circuit's complexity greatly. It is prossessed of the advantages of precise delay time, wider bandwidth and lower price. Especially, the shorter delay time and the wider bandwidth enable this design method to apply in higher communication speed easily.
UDBFC: An effective focused crawling approach based on URL Distance calculation

Vertical search engines use focused crawlers as their key component and develops some specific algorithms to select web pages relevant to some pre-defined set of topics. Therefore, to effectively build up a semantic pattern for specific topics is extremely important to such search engines. Crawlers are software which can traverse the internet and retrieve web pages by hyperlinks. Here we propose an UDBFC (URL Distance Based Focused Crawler) algorithm based on a double crawler framework (an experimental crawler and a focused crawler). The main motive of our UDBFC is to measure the relevancy between seed page and child page by vector space model. Seed pages are the common search result generated by three most popular search engine Google, Yahoo and MSN search. Child page links are out links of seed page which are extracted by link extractor tool from seed page. Seed page and child page are fetched by experimental crawler. It calculates the relevancy between seed page and its all child pages. After relevancy calculation it defines groups based on relevancy score. It uses the focused crawler to fetch topic specific pages from internet based on distance score which is calculated between grouped URLs and each URL which is to be fetched.
Dark matter haloes: an additional criterion for the choice of fitting density profiles

Simulated dark matter haloes are fitted by self-similar, universal density profiles, where the scaled parameters depend only on a scaled (truncation) radius which, in turn, is supposed to be independent on the mass and the formation redshift. A criterion for the choice of the best fitting density profile is proposed, with regard to a set of high-resolution simulations, where some averaging procedure on scaled density profiles has been performed, in connection with a number of fitting density profiles. An application is made to a pair of sets each made of a dozen of high-resolution simulations, which are available in literature, in connection with two currently used fitting density profiles, where the dependence of the scaled radius on the mass and the formation redshift, may be neglected to a first extent. Some features of the early evolution of dark matter haloes represented by fitting density profiles, are discussed in the limit of the spherical top-hat model.
Increased serum level of homocysteine correlates with retinal nerve fiber layer thinning in diabetic retinopathy

Purpose To study the correlation between serum levels of vitamin B12, folic acid, and homocysteine and the severity of diabetic retinopathy and the correlation with retinal nerve fiber layer (RNFL) thinning on spectral domain optical coherence tomography (SD-OCT). Methods In a tertiary care center–based prospective cross-sectional study, 60 consecutive cases and 20 healthy controls in the age group of 40–65 years were included. The eyes of the cases were divided into three groups according to Early Treatment Diabetic Retinopathy Study (ETDRS) classification: diabetes mellitus without retinopathy (n = 20), non-proliferative diabetic retinopathy with macular edema (n = 20), and proliferative diabetic retinopathy with macular edema (n = 20). The serum levels of vitamin B12 and folic acid were measured using a standard protocol. The serum homocysteine assay was performed using an enzyme-linked immunosorbent assay (ELISA) kit. Average RNFL thickness was measured using SD-OCT. Statistical analysis was used to assess the correlations between the study variables. Results Increased severity of diabetic retinopathy was found to correlate with an increase in the serum levels of homocysteine (F = 53.79; p<0.001). The mean serum levels of vitamin B12 and folic acid were found to be within the normal reference range. A positive correlation was found between retinal nerve fiber layer thinning and serum levels of homocysteine (p<0.001). Conclusions This study, for the first time, demonstrated a correlation between increased homocysteine with a decrease in RNFL thickness and increased severity of diabetic retinopathy.
An accelerometer-based approach to evaluate 3D unistroke gestures

This paper, presents an evaluation of Three Dimensional (3D) unistroke human arm gestures. Our scheme employs an accelerometer-based approach by using Nintendo™ Wiimote as a gesture device. The system takes acceleration signals from Wiimote in order to, classify different gestures. It deals with numeric gestures, i.e., digits from 0 to 9 and simple mathematical operator gestures for addition, subtraction, multiplication and division. Two techniques, Dynamic Time Warping (DTW) and 2D trajectories are used to recognize and classify gestures. Successful recognition rates indicate that performing 3D gestures using accelerometer-based devices is intuitive and provides an effective means of interaction with computers.
Merged aggregate nearest neighbor query processing in road networks

Aggregate nearest neighbor query, which returns a common interesting point that minimizes the aggregate distance for a given query point set, is one of the most important operations in spatial databases and their application domains. This paper addresses the problem of finding the aggregate nearest neighbor for a merged set that consists of the given query point set and multiple points needed to be selected from a candidate set, which we name as merged aggregate nearest neighbor(MANN) query. This paper proposes an effective algorithm to process MANN query in road networks based on our pruning strategies. Extensive experiments are conducted to examine the behaviors of the solutions and the overall experiments show that our strategies to minimize the response time are effective and achieve several orders of magnitude speedup compared with the baseline methods.
Development and Factor Analysis of the Protective Factors Index: A Report Card Section Related to the Work of School Counselors.

Gwen Bass is a doctoral researcher at the Ronald H. Fredrickson Center for School Counseling Outcome Research at the University of Massachusetts. Ji Hee Lee is a doctoral student at Korea University in South Korea and Center Fellow of the Ronald H. Frederickson Center for School Counseling Outcome Research at the University of Massachusetts. Craig Wells is an Associate Professor at the University of Massachusetts. John C. Carey is a Professor of School Counseling and the Director of the Ronald H. Frederickson Center for School Counseling Outcome Research at the University of Massachusetts. Sangmin Lee is an Associate Professor at Korea University. Correspondence can be addressed to Gwen Bass, School of Cognitive Science, Adele Simmons Hall, Hampshire College, 893 West Street, Amherst, MA 01002, gjbass@gmail.com. Gwen Bass, Ji Hee Lee, Craig Wells, John C. Carey, Sangmin Lee Development and Factor Analysis of the Protective Factors Index: A Report Card Section Related to the Work of School Counselors
Automatic Query Expansion Using SMART: TREC 3

The Smart information retrieval project emphasizes completely automatic approaches to the understanding and retrieval of large quantities of text. We continue our work in TREC 3, performing runs in the routing, ad-hoc, and foreign language environments. Our major focus is massive query expansion : adding from 300 to 530 terms to each query. These terms come from known relevant documents in the case of routing, and from just the top retrieved documents in the case of ad-hoc and Spanish. This approach improves effectiveness from 7% to 25% in the various experiments. Other ad-hoc work extends our investigations into combining global similarities, giving an overall indication of how a document matches a query, with local similarities identifying a smaller part of the document which matches the query. Using an overlapping text window definition of local, we achieve a 16% improvement.
Predictive Timing Models

We consider the problems of learning and planning in Markov decision processes with temporally extended actions represented in the options framework. We propose to use predictions about the duration of extended actions to represent the state and show how this leads to a compact predictive state representation model independent of the set of primitive actions. Then we develop a consistent and efficient spectral learning algorithm for such models.
Sparse Message Passing Algorithms for Weighted Maximum Satisfiability

Weighted maximum satisfiability is a wellstudied problem that has important applicability to artificial intelligence (for instance, MAP inference in Bayesian networks). General-purpose stochastic search algorithms have proven to be accurate and efficient for large problem instances; however, these algorithms largely ignore structural properties of the input. For example, many problems are highly clustered, in that they contain a collection of loosely coupled subproblems (e.g. pipelines of NLP tasks). In this paper, we propose a message passing algorithm to solve weighted maximum satisfiability problems that exhibit this clustering property. Our algorithm fuses local solutions to each subproblem into a global solution by iteratively passing summary information between clusters and recomputing local solutions. Because the size of these messages can become unwieldy for large problems, we explore several message compression techniques to transmit the most valuable information as compactly as possible. We empirically compare our algorithm against a state-of-the-art stochastic solver and show that for certain classes of problems our message passing algorithm finds significantly better solutions.
Minimal vs. non Minimal Adaptive Routing on k-ary n-cubes

There is a common agreement in the scientiic community that ad-aptive routing algorithms will eventually replace the deterministic ones that are currently in use in multicomputer networks. An open issue in this research area is to determine the optimal degree of ad-aptivity that the routing algorithm should provide. Through simulation on a 16-ary 2-cube, we analyze some minimal wormhole algorithms based on Duato's methodology and a non minimal cut-through algorithm, the Chaos routing. The experimental results show that the Chaos routing outperforms the minimal adaptive algorithms under the uniform traac, but suuers from post saturation problems with the complement, transpose and bit reversal traacs. From these results we argue that non minimal algorithms should pose an upper bound on the degree of adaptivity in order to avoid performance degradations due to excessive misrouting.
An Analysis of Peer to Peer Protocols for Massively Multiplayer Online Games

In this paper three current massively multiplayer online game peer to peer protocols are simulated and analysed. The results of the simulations suggest that improvement is still needed in order to lower the bandwidth usage of the protocols. Areas for improvement for the protocols are suggested and their business viability is discussed. It is also discovered that a complete solution that is suitable for the market is not yet available. Ideas for future research into peer to peer protocols and network middleware are put forward.
A Computational Statistics Approach to Stochastic Inverse Problems and Uncertainty Quantication in Heat Transfer

As most engineering systems and processes operate in an uncertain environment, it becomes increasingly important to address their analysis and inverse design in a stochastic manner using statistical data-driven methods. Recent advances in computational Bayesian and spatial statistics enable complete and efficient solution procedures to such problems. Herein, a novel framework based on Bayesian inference is presented for the solution of stochastic inverse problems in heat transfer. The posterior probability density function (PPDF) of unknowns (modeled as random variables or stochastic processes), such as material thermal properties and boundary heat flux, is computed given finite set of thermocouple temperature measurements. Markov Chain Monte Carlo (MCMC) algorithms are exploited to obtain estimates of statistics of random unknowns. A parameter estimation problem is first solved using simple, hierarchical and augmented Bayesian models. Boundary heat flux reconstruction in heat conduction is then studied. Simulation results demonstrate the great potential of applying a Bayesian approach to stochastic estimation and design problems. Although discussed in the context of thermal systems, the methodology presented is general and applicable to design and estimation problems in diverse areas of engineering.
Antimicrobial Properties and Membrane-Active Mechanism of a Potential α-Helical Antimicrobial Derived from Cathelicidin PMAP-36

Antimicrobial peptides (AMPs), which present in the non-specific immune system of organism, are amongst the most promising candidates for the development of novel antimicrobials. The modification of naturally occurring AMPs based on their residue composition and distribution is a simple and effective strategy for optimization of known AMPs. In this study, a series of truncated and residue-substituted derivatives of antimicrobial peptide PMAP-36 were designed and synthesized. The 24-residue truncated peptide, GI24, displayed antimicrobial activity comparable to the mother peptide PMAP-36 with MICs ranging from 1 to 4 µM, which is lower than the MICs of bee venom melittin. Although GI24 displayed high antimicrobial activity, its hemolytic activity was much lower than melittin, suggesting that GI24 have optimal cell selectivity. In addition, the crucial site of GI24 was identified through single site-mutation. An amino acid with high hydrophobicity at position 23 played an important role in guaranteeing the high antimicrobial activity of GI24. Then, lipid vesicles and whole bacteria were employed to investigate the membrane-active mechanisms. Membrane-simulating experiments showed that GI24 interacted strongly with negatively charged phospholipids and weakly with zwitterionic phospholipids, which corresponded well with the data of its biological activities. Membrane permeabilization and flow cytometry provide the evidence that GI24 killed microbial cells by permeabilizing the cell membrane and damaging membrane integrity. GI24 resulted in greater cell morphological changes and visible pores on cell membrane as determined using scanning electron microscopy (SEM) and transmission electron microscope (TEM). Taken together, the peptide GI24 may provide a promising antimicrobial agent for therapeutic applications against the frequently-encountered bacteria.