Miracle-dz/UniFAR-FTUs huggingface dataset:
The software engineering of internet software

0 7 4 0 7 4 5 9 / 0 2 / $ 1 7 . 0 0 © 2 0 0 2 I E E E M a r c h / A p r i l 2 0 0 2 I E E E S O F T W A R E 2 3 The real departure for Web-based enterprise applications is the possibility of wideranging accessibility. A system that might be deployed in-house at a manufacturing company can now be deployed to all the dealers of that manufacturer’s products. Indeed, it can be deployed to all the customers. In the past, such a wide deployment was a major hurdle. With Web-based technologies, providing external access to internal systems is as easy as publicizing a URL. Without doubt, the Web has significantly affected the users of computer systems, but what effect has it had on enterprise application designers? That’s the question we wanted to explore with this special issue. What things are the same, what things are new, and what things have changed in some subtle but interesting ways? The activities that people need to do to build Web software do not differ from those we do with any software. We still analyze requirements, design, write code, test, and deploy. Yet the pressures of building Web applications add some new variations of familiar activities. None of these changes are necessarily massive, but they suffice to suggest some new directions.
Mycoplasmas and Ureaplasmas as Neonatal Pathogens

SUMMARY The genital mycoplasmas represent a complex and unique group of microorganisms that have been associated with a wide array of infectious diseases in adults and infants. The lack of conclusive knowledge regarding the pathogenic potential of Mycoplasma and Ureaplasma spp. in many conditions is due to a general unfamiliarity of physicians and microbiology laboratories with their fastidious growth requirements, leading to difficulty in their detection; their high prevalence in healthy persons; the poor design of research studies attempting to base association with disease on the mere presence of the organisms in the lower urogenital tract; the failure to consider multifactorial aspects of diseases; and considering these genital mycoplasmas only as a last resort. The situation is now changing because of a greater appreciation of the genital mycoplasmas as perinatal pathogens and improvements in laboratory detection, particularly with regard to the development of powerful molecular nucleic acid amplification tests. This review summarizes the epidemiology of genital mycoplasmas as causes of neonatal infections and premature birth; evidence linking ureaplasmas with bronchopulmonary dysplasia; recent changes in the taxonomy of the genus Ureaplasma; the neonatal host response to mycoplasma and ureaplasma infections; advances in laboratory detection, including molecular methods; and therapeutic considerations for treatment of systemic diseases.
Parameters Optimization of Back Propagation Neural Network Based on Memetic Algorithm Coupled with Genetic Algorithm

Memetic algorithm is both global and local search algorithm based on evolutionary algorithm, indeed, it has high optimization efficiency and fast searching speed. The paper proposes an efficient method of choosing the proper parameters to set up the moderate-scaled and efficient back propagation neural network via memetic algorithm. In addition, weights and thresholds of BPNN are also optimized by means of the Genetic algorithm in order to build up BPNN with high performances, such as simplified structure, low store memory occupation, high prediction accuracy and generalization etc. Experiments perform on the Wisconsin breast cancer diagnosis datasets from UCI Machine Learning Repository, which show through a serial of simulation results that the proposed algorithm has better accuracy than the state-of-the-art algorithm.
Grounding Symbols through Sensorimotor Integration

A prominent robotics professor surprised me at last year's RSJ conference: "There isn't really a symbol grounding problem for robotics, is there? I often ask people, 'Is symbol grounding a problem for your re search? ' and no one says, 'Yes. ' " Sensing irony in his voice, I replied, "That's because no one is building sys tems with a human or even vertebrate level of competence. When they try to, they may respond to your question differently. " Harnad (1990) identified the symbol grounding prob lem as a problem of embodying symbol systems
Conjoint Analysis of the Mid-Atlantic Food-Fish Market for Farm-Raised Hybrid Striped Bass

Abstract Conjoint analysis was used to examine buyer preferences toward farm-raised hybrid striped bass at the wholesale, retail, and restaurant levels. Low price and round form were found to be important attributes in the product preference rating for the wholesale and retail markets. The filleted form contributed the most to restaurants' preference rating. Following these, larger fish size was preferred by all markets.
The Power of Choice in Scheduling Parallel Tasks

A malleable parallel task is one that can be executed on any number of processors, with its execution time being a function of the number of processors allotted to it. A nonmalleable parallel task is one that requires a speciic number of processors. Given n independent parallel tasks and m identical processors, we consider the problem of scheduling these tasks to minimize average completion time. Even though this is a classical scheduling problem, the rst results in this direction were obtained only recently They presented an algorithm for scheduling nonmalleable parallel tasks with an approximation factor of 32. We give an algorithm for scheduling malleable tasks that has an approximation factor of 2, under the assumption that for each task, work is a nondecreasing function of the number of processors allotted to the task. Our algorithm and analysis incorporate an improved lower bound on average completion time for the nonmalleable problem. We also show that Turek et al.'s algorithm for the nonmalleable problem can be extended to the malleable problem, while preserving the approximation factor. The resulting algorithm does not require any assumptions on the task execution times. The running time of our malleable schedulers is dominated by the cost of determining a minimumweight perfect matching in a bipartite graph.
A Connected Component-Based Distributed method for overlapping community detection

In order to find the overlapping community structure more quickly and accurately in complex network, this paper proposes a Connected Component-Based Distributed method (CCBD) for overlapping community detection. CCBD first divides edges set in the network into smaller one. Next, it seeks out connected component using distributed platforms and gives a serials number to them according to certain rules. Then, it classifies these connected components according to the serials number. Task nodes determine whether any two connected components and non-propagating edges can be connected to become a larger community. Finally, CCBD negotiates a new serials name for the new community. Through repeated iterations, we get the community structure in the network. Nodes belong to multiple communities are overlapping nodes. Experiment results show that CCBD has higher time efficiency benefiting from distributed computing. Moreover, the quality of communities detected by CCBD surpasses those found by other algorithms.
GLACIAL RETREAT IN THE QUILCAYHUANCA VALLEY WATERSHED, PERU Utilizing literature on the Cordillera Blanca as an analogue

This investigation considers existing literature on the Cordillera Blanca mountain range in Peru as an analogue for glacial retreat in the Quilcayhuanca Valley watershed. This watershed provides much of the water resources for the city of Huaraz, particularly during the dry season. Therefore, it is important to predict future glacial retreat in this valley, in order for this community to adapt to the associated decrease in its water resources. Data regarding the Cordillera Blanca can be used to make general predictions for the Quilcayhuanca Valley watershed, given that it is located in the range. A finer temporal and spatial scale study than currently exists, is needed for community specific planning, however, given that glacial retreat varies between watersheds.
Domains of tau protein, differential phosphorylation, and dynamic instability of microtubules.

The dynamic instability of microtubules is thought to be regulated by MAPs and phosphorylation. Here we describe the effect of the neuronal microtubule-associated protein tau by observing the dynamics of single microtubules by video microscopy. We used recombinant tau isoforms and tau mutants, and we phosphorylated tau by the neuronal kinases MARK (affecting the KXGS motifs within tau's repeat domain) and cdk5 (phosphorylating Ser-Pro motifs in the regions flanking the repeats). The variants of tau can be broadly classified into three categories, depending on their potency to affect microtubule dynamics. "Strong" tau variants have four repeats and both flanking regions. "Medium" variants have one to three repeats and both flanking regions. "Weak" variants lack one or both of the flanking regions, or have no repeats; with such constructs, microtubule dynamics is not significantly different from that of pure tubulin. N- or C-terminal tails of tau have no influence on dynamic instability. The two ends of microtubules (plus and minus) showed different activities but analogous behavior. These results are consistent with the "jaws" model of tau where the flanking regions are considered as targeting domains whereas the addition of repeats makes them catalytically active in terms of microtubule stabilization. The dominant changes in the parameters of dynamic instability induced by tau are those in the dissociation rate and in the catastrophe rate (up to 30-fold). Other rates change only moderately or not at all (association rate increased up to twofold, rates of rescue or rapid shrinkage decreased up to approximately twofold). The order of repeats has little influence on microtubule dynamics (i.e., repeats can be re-arranged or interchanged), arguing in favor of the "distributed weak binding" model proposed by Butner and Kirschner (1991); however, we confirmed the presence of a "hotspot" of binding potential involving Lys274 and Lys281 observed by Goode and Feinstein, 1994. Phosphorylation of Ser-Pro motifs by cdk5 (mainly Ser 202, 235, and 404) in the flanking regions had a moderate effect on microtubule dynamics while phosphorylation at the "Alzheimer"-site Ser262 MARK eliminated tau's interactions with microtubules. In both cases the predominant effects of phosphorylation are on the rates of tubulin dissociation and catastrophe whereas the effects on the rates of association or rescue are comparatively small.
A New-Generation Method for Quick and Owren PT

Oral anticoagulant therapy (OAT) calls for continuous control by prothrombin time (PT) test, as the therapeutic range in INR units is very narrow. Warfarin (or coumarin) inhibits coagulation factor synthesis in the liver, but at the same time inactive coagulation factors are formed. The aim here was to measure "active coagulation factors" and inhibition in calibrator kits and patient plasmas by a new method for Quick and Owren PT. Four calibration kits and 200 plasma samples obtained from OAT patients were assessed using Quick and Owren PT for INRTot (active coagulation factors + inhibition) and INRAcf (only active coagulation factors). Conspicuous variation in in- hibition was noted between the four calibration kits. The new- generation PT method develops anticoagulation therapy based on active coagulation factors in vivo and improves INR result harmonization for Quick and Owren PT reagents. This new approach improves Quick PT reliability.
Improved Rates and Asymptotic Normality for Nonparametric Neural Network Estimators

We obtain an improved approximation rate (in Sobolev norm) of r/sup -1/2-/spl alpha//(d+1)/ for a large class of single hidden layer feedforward artificial neural networks (ANN) with r hidden units and possibly nonsigmoid activation functions when the target function satisfies certain smoothness conditions. Here, d is the dimension of the domain of the target function, and /spl alpha//spl isin/(0, 1) is related to the smoothness of the activation function. When applying this class of ANNs to nonparametrically estimate (train) a general target function using the method of sieves, we obtain new root-mean-square convergence rates of Op([n/log(n)]/sup -/(1+2/spl alpha//(d+1))/[4(1+/spl alpha//(d+1))])=op(n/sup -1/4/) by letting the number of hidden units /spl tau//sub n/, increase appropriately with the sample size (number of training examples) n. These rates are valid for i.i. d. data as well as for uniform mixing and absolutely regular (/spl beta/-mixing) stationary time series data. In addition, the rates are fast enough to deliver root-n asymptotic normality for plug-in estimates of smooth functionals using general ANN sieve estimators. As interesting applications to nonlinear time series, we establish rates for ANN sieve estimators of four different multivariate target functions: a conditional mean, a conditional quantile, a joint density, and a conditional density. We also obtain root-n asymptotic normality results for semiparametric model coefficient and average derivative estimators.
Short hairpin RNA targeting Twist1 suppresses cell proliferation and improves chemosensitivity to cisplatin in HeLa human cervical cancer cells

Development of multidrug resistance (MDR) remains a major hurdle to successful cancer chemotherapy and MDR1/P-gp overexpression is believed to be mainly responsible for MDR of tumor cells. Twist1, which is a highly conserved transcription factor that belongs to the family of basic helix-loop-helix proteins, has been shown to be a major regulator of the epithelial-mesenchymal transition (EMT), and therefore promotes carcinoma metastasis. Recently, a novel function of Twist1 was reported to confer radioresistance or chemoresistance in cervical cancer. However, mechanisms of such efficacy are not completely elucidated. In the present study, we firstly analyzed the relationship between Twist1 and MDR1/P-gp expression in human cervical cancer specimens and demonstrated a positive correlation between Twist1 and MDR1/P-gp expression in the same patient. Additionally, we provide the first evidence that silencing of Twist1 by RNAi downregulated MDR1/P-gp expression in HeLa cervical cancer cells, suppressed the cell proliferation, inhibited Rhodamine123 efflux activity of cells and sensitized cells to cisplatin treatment. Collectively, these findings suggest that Twist1-mediated modulation of MDR1/P-gp expression plays an important role in sensitization of cervical cancer cells to cisplatin, and also indicate a novel therapeutic strategy to overcome drug resistance through inactivation of Twist1 expression in cervical cancer.
Reducing the Health and Digital Divides: A Model for Using Community-Based Participatory Research Approach to E-Health Interventions in Low-Income Hispanic Communities

Low-incomeHispanicsarethemostdigitallyunderservedpopulationintheU.S. Thisarticle examines the potential of community-based participatory research approach to e-health to decrease the disparities in access to technology and health information in low-income Hispaniccommunities.Todemonstrate thisframework,wedescribe theprocessofdesigning a community-based e-health intervention to increase knowledge and parental self-efficacy in coping with young children’s mental health problems including mental health service utilization. Our model incorporates utilizing promotoras de salud (lay community health educators) and community media principles to create the content of e-health interventions and train community members in using the technology. This case study illustrates the processes involved in using this approach, barriers for participatory e-health interventions in bridging the Digital Divide, and lessons learned.
Isoprene in poplar emissions: effects on new particle formation and OH concentrations

Abstract. Stress-induced volatile organic compound (VOC) emissions from transgenic Grey poplar modified in isoprene emission potential were used for the investigation of photochemical secondary organic aerosol (SOA) formation. In poplar, acute ozone stress induces the emission of a wide array of VOCs dominated by sesquiterpenes and aromatic VOCs. Constitutive light-dependent emission of isoprene ranged between 66 nmol m −2 s −1 in non-transgenic controls (wild type WT) and nearly zero ( −2 s −1 ) in isoprene emission-repressed plants (line RA22), respectively. Nucleation rates of up to 3600 cm −3 s −1 were observed in our experiments. In the presence of isoprene new particle formation was suppressed compared to non-isoprene containing VOC mixtures. Compared to isoprene/monoterpene systems emitted from other plants the suppression of nucleation by isoprene was less effective for the VOC mixture emitted from stressed poplar. This is explained by the observed high efficiency of new particle formation for emissions from stressed poplar. Direct measurements of OH in the reaction chamber revealed that the steady state concentration of OH is lower in the presence of isoprene than in the absence of isoprene, supporting the hypothesis that isoprenes' suppressing effect on nucleation is related to radical chemistry. In order to test whether isoprene contributes to SOA mass formation, fully deuterated isoprene (C 5 D 8 ) was added to the stress-induced emission profile of an isoprene free poplar mutant. Mass spectral analysis showed that, despite the isoprene-induced suppression of particle formation, fractions of deuterated isoprene were incorporated into the SOA. A fractional mass yield of 2.3% of isoprene was observed. Future emission changes due to land use and climate change may therefore affect both gas phase oxidation capacity and new particle number formation.
Frame Activated Inferences in a Story Understanding Program

An effective story undcrstander must be able to reason about characters in the story, their affects, actions, plans, and goals, as well as the settings and important points of the story. In many systems this has been done with separate inference mechanisms for each class of knowledge structure. This paper proposes a story understander with a unified frame-based inference component used on each class of knowledge structure.
Chronic Illness and Mental Health Underutilization in African-Americans: A Labeling Theory Perspective

This paper explores the under-utilization of mental health services amongst African-Americans, with particular emphasis on labeling theory in defining the structural origins for perceived barriers to treatment. In the United States, with its tragic legacy of racially-based oppression, race is generally understood to have powerful connotations for social norms and individual self-concept, and in the case of discriminated minorities such as African-Americans, to have broad negative effects on quality of life. With health outcomes for African-Americans already poorer than their white counterparts, reducing barriers to all forms of treatment is essential to achieving a greater level of health parity. This is especially relevant for mental health services, as comorbid mental distress can serve to confound the treatment of physical ailments, most notably those that require long term care or lifestyle modification, where personal agency has its most significant impact. Indeed, mental health, more than any other component of overall health, can act as a gateway to a broader range of positive life choices, thereby facilitating improved health lifestyles. We will begin with an overview of the disparities between the races in terms of utilization and outcomes, including rates of inpatient care, We will then examine the perceived barriers to mental health treatment experienced by African-Americans, noting the stigma of seeking treatment, and the role of social integration in recovery and using labeling theory as a framework. Next, we will examine the consequences of these perceived barriers: how lack of mental health treatment creates negative health outcomes in the African-American population and contributes to disparity in survivability and mortality rates. Finally, some suggestions for improving utilization equity are advanced, based in successful programs from other fields and relevant research on attitudes towards accessing care.
Nonlinear pH Control with Input Disturbance

This paper presents a novel nonlinear Internal Model Controller architecture that achieves linear rejection of input disturbances from the control signal. For a large class of SISO nonlinear systems, appropriate open loop stability properties guarantee closed loop tracking and disturbance rejection of asymptotically constant signals. The convenient tuning and improved performance is illustrated for pH neutralization.
Efficient Sparse Matrix Multiplication on GPU for Large Social Network Analysis

As a number of social network services appear online recently, there have been many attempts to analyze social networks for extracting valuable information. Most existing methods first represent a social network as a quite sparse adjacency matrix, and then analyze it through matrix operations such as matrix multiplication. Due to the large scale and high complexity, efficient processing multiplications is an important issue in social network analysis. In this paper, we propose a GPU-based method for efficient sparse matrix multiplication through the parallel computing paradigm. The proposed method aims at balancing the amount of workload both at fine- and coarse-grained levels for maximizing the degree of parallelism in GPU. Through extensive experiments using synthetic and real-world datasets, we show that the proposed method outperforms previous methods by up to three orders-of-magnitude.
Fixing and evaluating texts: Mixed text reconstruction method for data fusion environments

This paper presents a method for the reconstruction of malformed texts into Spanish, these texts can be found regularly in social media environments. Also a method of sentiment analysis based on analysis of pairs will be presented. This sentiment analysis method includes intensifiers and applies the same procedures for analyse words, phrases and paragraphs. The method is centred on Spanish but the solutions proposed can be extended to any language.
Advanced Approximation Algorithms ( CMU 15-854 B , Spring 2008 ) Lecture 20 : Embeddings into Trees and L 1 Embeddings March 27 2008

where c(E(S, S̄)) is the sum of the weights of the edges that cross the cut, and D(S, S̄) is the sum of the demands of the pairs (si, ti) that are separated by the cut. We recall that optimizing over the set of cuts is equivalent to optimizing over `1 metrics, and is NP-hard. Instead, we may optimize over the set of all metrics. In this lecture, we bound the gap introduced by this relaxation by showing how these metrics embed into `1 with low distortion. From last time, we have a theorem of Bourgain: Theorem 1.1 (Bourgain 85 [1]). Any n point metric d admits an α-distortion embedding into `p for any 1 ≤ p ≤ ∞ with α = O(log n). This embedding is into 2 dimensions, however! Fortunately, Linial, London, and Rabinovich [3] proved that it is possible to get such an embedding into online O(log n) dimensions. In this lecture, we will show a somewhat weaker result: We will achieve an α = O(log n) embedding into `1 using poly(n, dmax/dmin) dimensions, where dmax is the maximum distance between any two points according to metric d, and dmin is the minimum distance. We note that dmax/dmin could potentially be exponentially large – but we won’t worry about this detail.