Miracle-dz/UniFAR-FTUs huggingface dataset:
On solving the view selection problem in distributed data warehouse architectures

The use of materialized views in a data warehouse installation is a common tool to speed up mostly aggregation queries. The problems coming along with materialized aggregate views have triggered a huge variety of proposals, such as picking the optimal set of aggregation combinations, transparently rewriting user queries to take advantage of the summary data, or synchronizing pre-computed summary data as soon as the base data changes. The paper focuses on the problem of view selection in the context of distributed data warehouse architectures. While much research was done with regard to the view selection problem in the central case, we are not aware to any other work discussing the problem of view selection in distributed data warehouse systems. The paper proposes an extension of the concept of an aggregation lattice to capture the distributed semantics. Moreover, we extend a greedy-based selection algorithm based on an adequate cost model for the distributed case. Within a performance study, we finally compare our findings with the approach of applying a selection algorithm locally to each node in a distributed warehouse environment.
An extensible simulation tool for overlay networks and services

Research community on distributed systems, and in particular on peer-to-peer systems, needs tools for evaluating their own protocols and services, as well as against other protocols with the same preconditions. Since a (TCP/IP) experimental evaluation is not always feasible, simulation tools appeared. In this paper we introduce PlanetSim, a discrete event-based simulation framework tool for overlay networks and services, as well as extensions from third parties that prove its true extensibility and adaptability to the researchers' needs. In addition, we introduce within PlanetSim a novel methodology for implementing peer-to-peer overlay protocols based on behaviors.
Integration of mRNA Expression Profile, Copy Number Alterations, and microRNA Expression Levels in Breast Cancer to Improve Grade Definition

Defining the aggressiveness and growth rate of a malignant cell population is a key step in the clinical approach to treating tumor disease. The correct grading of breast cancer (BC) is a fundamental part in determining the appropriate treatment. Biological variables can make it difficult to elucidate the mechanisms underlying BC development. To identify potential markers that can be used for BC classification, we analyzed mRNAs expression profiles, gene copy numbers, microRNAs expression and their association with tumor grade in BC microarray-derived datasets. From mRNA expression results, we found that grade 2 BC is most likely a mixture of grade 1 and grade 3 that have been misclassified, being described by the gene signature of either grade 1 or grade 3. We assessed the potential of the new approach of integrating mRNA expression profile, copy number alterations, and microRNA expression levels to select a limited number of genomic BC biomarkers. The combination of mRNA profile analysis and copy number data with microRNA expression levels led to the identification of two gene signatures of 42 and 4 altered genes (FOXM1, KPNA4, H2AFV and DDX19A) respectively, the latter obtained through a meta-analytical procedure. The 42-based gene signature identifies 4 classes of up- or down-regulated microRNAs (17 microRNAs) and of their 17 target mRNA, and the 4-based genes signature identified 4 microRNAs (Hsa-miR-320d, Hsa-miR-139-5p, Hsa-miR-567 and Hsa-let-7c). These results are discussed from a biological point of view with respect to pathological features of BC. Our identified mRNAs and microRNAs were validated as prognostic factors of BC disease progression, and could potentially facilitate the implementation of assays for laboratory validation, due to their reduced number.
Systematic Testing of Model-Based Code Generators

Unlike for conventional compilers for imperative programming languages such as C or ADA, no establishedmethods for safeguarding artifacts generated by model-based code generators exist despite progress in the field of formalverification. Several test approaches dominate the engineering practice. This paper describes a general and toolindependenttest architecture for code generators used in model-based development. We evaluate the effectiveness of ourtest approach by means of testing optimizations performed by the TargetLink code generator, a widely accepted andcomplex development tool used in automotive model-based development.
Song Intersection by Approximate Nearest Neighbor Search

We present new methods for computing inter-song similarities using intersections between multiple audio pieces. The intersection contains portions that are similar, when one song is a derivative work of the other for example, in two different musical recordings. To scale our search to large song databases we have developed an algorithm based on localitysensitive hashing (LSH) of sequences of audio features called audio shingles. LSH provides an efficient means to identify approximate nearest neighbors in a high-dimensional feature space. We combine these nearest neighbor estimates, each a match from a very large database of audio to a small portion of the query song, to form a measure of the approximate similarity. We demonstrate the utility of our methods on a derivative works retrieval experiment using both exact and approximate (LSH) methods. The results show that LSH is at least an order of magnitude faster than the exact nearest neighbor method and that accuracy is not impacted by the approximate method.
Atypical chemokine receptor ACKR2 controls branching morphogenesis in the developing mammary gland

Macrophages are important regulators of branching morphogenesis during development and postnatally in the mammary gland. Regulation of macrophage dynamics during these processes can therefore have a profound impact on development. We demonstrate here that the developing mammary gland expresses high levels of inflammatory CC-chemokines, which are essential in vivo regulators of macrophage migration. We further demonstrate that the atypical chemokine receptor ACKR2, which scavenges inflammatory CC-chemokines, is differentially expressed during mammary gland development. We have previously shown that ACKR2 regulates macrophage dynamics during lymphatic vessel development. Here, we extend these observations to reveal a novel role for ACKR2 in regulating the postnatal development of the mammary gland. Specifically, we show that Ackr2−/− mice display precocious mammary gland development. This is associated with increased macrophage recruitment to the developing gland and increased density of the ductal epithelial network. These data demonstrate that ACKR2 is an important regulator of branching morphogenesis in diverse biological contexts and provide the first evidence of a role for chemokines and their receptors in postnatal development processes. Summary: Ackr2−/− mice display precocious mammary gland development as a result of impaired chemokine scavenging and increased macrophage recruitment to the mammary gland.
Metadata Quality and the Use of Hierarchical Schemes to Determine Meta Keywords: An Exploration

This study explores the impact of vocabulary scheme arrangement on the quality of author-generated metadata, specifically specificity and frequency of vocabulary terms chosen from schemes to describe websites. By evaluating vocabulary assigned using hierarchical and flat schemes, and by comparing these evaluations, this study seeks to isolate the arrangement of the scheme used from other variables, such as skill level and intentions of metadata generators, which have been the focus of previous research into the viability of author-generated metadata. This study suggests a relationship between term specificity and scheme arrangement, and possible relationships between term frequency and scheme arrangement, and submits that it is therefore possible that non-professional status, lack of skills, or intentions to misrepresent web page content via metadata are not the sole contributing factors to quality of author-generated metadata. New methods for researching metadata quality are tested and their validity discussed.
Play it again: a study of the factors underlying speech browsing behavior

Several recent UIs support access to recorded speech archives, but these have not yet been systematically evaluated. We describe a laboratory study of speech archive browsing using a GUI. We evaluate the effects of four factors: task type, familiarity, structure, and play operation duration. We found that while users learnt the overall layout of topics in the archive, they experienced major problems in learning the internal structure of archival topics. Contrary to our expectations, we also discovered that structural information and fixed duration play operations were less useful for browsing than anticipated. We discuss the impact of our results for speech archive UI design, and describe a new UI which supports navigation within topic.
Discontinuation and switching patterns of tumour necrosis factor inhibitors (TNFis) in TNFi-naive and TNFi-experienced patients with psoriatic arthritis: an observational study from the US-based Corrona registry

Objective To examine patterns of tumour necrosis factor inhibitor (TNFi) use in TNFi-naive and TNFi-experienced patients with psoriatic arthritis (PsA) in the USA. Methods All patients aged ≥18 years with PsA enrolled in the Corrona Psoriatic Arthritis/Spondyloarthritis Registry who initiated a TNFi (index therapy) between March 2013 and January 2017 and had ≥1 follow-up visit were included. Times to and rates of discontinuation/switch of the index TNFi were compared between TNFi-naive and TNFi-experienced cohorts. Patient demographics and disease characteristics at the time of TNFi initiation (baseline) were compared between cohorts and between patients who continued versus discontinued their index TNFi by the first follow-up visit within each cohort. Results This study included 171 TNFi-naive and 147 TNFi-experienced patients (total follow-up, 579.2 person-years). Overall, 75 of 171 TNFi-naive (43.9%) and 80 of 147 TNFi-experienced (54.4%) patients discontinued their index TNFi; 33 of 171 (19.3%) and 48 of 147 (32.7%), respectively, switched to a new biologic. TNFi-experienced patients had a shorter time to discontinuation (median, 20 vs 27 months) and were more likely to discontinue (p=0.03) or switch (p<0.01) compared with TNFi-naive patients. Among those who discontinued, 49 of 75 TNFi-naive (65.3%) and 59 of 80 TNFi-experienced (73.8%) patients discontinued by the first follow-up visit; such patients showed a trend towards higher baseline disease activity compared with those who continued. Conclusions The results of this real-world study can help inform treatment decisions when selecting later lines of therapy for patients with PsA.
Energy-aware routing in data center network

The goal of data center network is to interconnect the massive number of data center servers, and provide efficient and fault-tolerant routing service to upper-layer applications. To overcome the problem of tree architecture in current practice, many new network architectures are proposed, represented by Fat-Tree, BCube, and etc. A consistent theme in these new architectures is that a large number of network devices are used to achieve 1:1 oversubscription ratio. However, at most time, data center traffic is far below the peak value. The idle network devices will waste significant amount of energy, which is now a headache for many data center owners. In this paper, we discuss how to save energy consumption in high-density data center networks in a routing perspective. We call this kind of routing energy-aware routing. The key idea is to use as few network devices to provide the routing service as possible, with no/little sacrifice on the network performance. Meanwhile, the idle network devices can be shutdown or put into sleep mode for energy saving. We establish the model of energy-aware routing in data center network, and design a heuristic algorithm to achieve the idea. Our simulation in typical data center networks shows that energy-aware routing can effectively save power consumed by network devices.
On the Noncommutative Residue for Projective Pseudodifferential Operators

A well known result on pseudodifferential operators states that the noncommutative residue (Wodzicki residue) of a pseudodifferential projection vanishes. This statement is non-local and implies the regularity of the eta invariant at zero of Dirac type operators. We prove that in a filtered algebra the value of a projection under any residual trace depends only on the principal part of the projection. This general, purely algebraic statement applied to the algebra of projective pseudodifferential operators implies that the noncommutative residue factors to a map from the twisted K-theory of the co-sphere bundle. We use arguments from twisted K-theory to show that this map vanishes, thus showing that the noncommutative residue of a projective pseudodifferential projection vanishes. This also gives a very short proof in the classical setting.
Rapid Determination of 30 Polyphenols in Tongmai Formula, a Combination of Puerariae Lobatae Radix, Salviae Miltiorrhizae Radix et Rhizoma, and Chuanxiong Rhizoma, via Liquid Chromatography-Tandem Mass Spectrometry

Tongmai formula (TMF) is a herbal preparation composed of three traditional Chinese medicinal materials: Puerariae Lobatae Radix (Gegen), Salviae Miltiorrhizae Radix et Rhizoma (Danshen) and Chuanxiong Rhizoma (Chuanxiong). It has been used to treat cardiovascular diseases for decades. To develop a reliable and convenient analytical method for a comprehensive determination of polyphenols in TMF and the ascertainment of their chemical correlations with its herbal components, a method combining high-performance liquid chromatography with electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) was developed and validated for rapid determination of 30 polyphenols in TMF and its three herbal components. The chromatographic separation was carried out on a Chromolith Fastgradient RP-18 endcapped 50-2 column using an optimized gradient elution. Statistical analysis of obtained data demonstrated that the method had a desirable linearity, precision, and accuracy, as well as excellent sensitivity. The obtained results indicated that, among the 30 polyphenols in TMF, 22 originated from Gegen, 6 originated from Danshen, and 2 originated from Chuanxiong. The major polyphenols in TMF have been identified as puerarin, mirificin, salvianolic acid B, salvianic acid A, 3’-hydroxypuerarin, 3’-methoxypuerarin, and salvianolic acid A, with a combined contribution of 19.2% of the preparation. The development and validation of this method will greatly facilitate future pharmacological studies of TMF and its herbal components, as well as polyphenols in cardiovascular therapies.
Capturing Uncertainty in Magnetospheric Ultralow Frequency Wave Models

We develop and test an empirical model predicting ground‐based observations of ultralow frequency (ULF, 1–20 mHz) wave power across a range of frequencies, latitudes, and MLT sectors. This is parameterized by instantaneous solar wind speed vsw, variance in proton number density var(Np), and interplanetary southward magnetic field Bz. A probabilistic model of ULF wave power will allow us to address uncertainty in radial diffusion coefficients and therefore improve diffusion modeling of radial transport in Earth's outer radiation belt. Our model can be used in two ways to reproduce wave power: by sampling from conditional probability distribution functions and by using the mean (expectation) values. We derive a method for testing the quality of the parameterization and test the ability of the model to reproduce ULF wave power time series. Sampling is a better method for reproducing power over an extended time period as it retains the same overall distribution, while mean values are better for predicting the power in a time series. The model predicts each hour in a time series better than the assumption that power persists from the preceding hour. Finally, we review other sources of diffusion coefficient uncertainty. Although this wave model is designed principally for the goal of improved radial diffusion coefficients to include in outer radiation belt diffusion‐based modeling, we anticipate that our model can also be used to investigate the occurrence of ULF waves throughout the magnetosphere and hence the physics of ULF wave generation and propagation.
Theoretical evaluation of electroactive-polymer based on micropump diaphragm for air flow control

An electroactive polymer (EAP), high energy electron irradiated poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)] copolymer, based actuation micropump diaphragm (PAMPD) has been developed for air flow control. The displacement strokes and profiles as a function of amplifier and frequency of electric field have been characterized. The volume stroke rates (volume rate) as function of electric field, driving frequency have been theoretically evaluated, too. The PAMPD exhibits high volume rate. It is easily tuned with varying of either amplitude or frequency of the applied electric field. In addition, the performance of the diaphragms were modeled and the agreement between the modeling results and experimental data confirms that the response of the diaphragms follow the design parameters. The results demonstrated that the diaphragm can fit some future aerospace applications to replace the traditional complex mechanical systems, increase the control capability and reduce the weight of the future air dynamic control systems.
Cognitive Rehab Solutions: A computer-assisted cognitive training program

Attention disturbances represent the largest portion of neuropsychological deficits following a brain injury. An estimated 73% of neuro-rehab centers across the nation utilize Computer Assisted Cognitive Retraining (CACR) to treat attention and other cognitive impairments. Effectiveness of CACR has led to the development of various types of cognitive software. However, limitations of these applications have surfaced and point to their lack of test parameter control and their inability to generate reports with graphical output. Cognitive Rehab Solutions (CRS) is a direct answer to these problems. CRS is a functionally comprehensive software package designed for neuropsychologists to deliver restorative cognitive therapy. Its key features include an attention test that can be tailored to an individual patient's need, ability to store and maintain patient records and the capability to generate graphical & tabular reports. CRS precisely addresses the concerns of its users and can prove to be an effective adjunct to a comprehensive cognitive rehabilitation program.
L-Graph: A General Graph Analytic System on Continuous Computation

Massive graph analytics have become an important aspect of multiple diverse applications. With the growing scale of real world graphs, efficient execution of entire graph analytics has become a challenging problem. Recently a number of distributed graph processing systems (Pregel, PowerGraph, Trinity) and centralized systems (GraphChi and XStream) have been designed. Compared with high expense of distributed systems deployed on a cluster of commodity machines, the centralized systems on cheap PCs are very attractive propositions with low expense and comparable performance. By careful analysis, we find that (i) the graph computation abstraction in the centralized systems inherently adopted a batch model similar to the distributed systems. The batch model could lead to suboptimal performance. (ii) The execution model in the centralized systems advocates sequential operations on Solid State Disk (SSD) which are still slower than memory-based operations. In order to tackle the above efficiency issues in centralized systems, we first propose a novel continuous graph computation abstraction. This model continuously processes edges and updates computation results. It allows much faster convergence than the batch model. Second, we propose to maintain vertex states in memory and advocates memory-based operations for much faster I/O operations than sequential operations on SSD. Finally, we design an adaptive memory layout to minimize overall I/O cost. We develop a proof of concept prototype L-Graph and implement four example graph analytic applications atop L-Graph. Preliminary evaluation on real and synthetic graphs have verified that the proposed continuous model greatly performs the widely used batch model and L-Graph can achiever much higher efficiency than the state of arts GraphChi.
An application of Rasch analysis to questionnaire design : using vignettes to study the meaning of work in the Current Population Survey

As part of the research to develop a new questionnaire for the Current Population Survey (CPS), a special respondent debriefing study was designed to learn more about how respondents understand and formulate their answers to the labor force questions. Between July and December of 1988, a sample of approximately 2300 respondents answered standardized debriefing questions after they had completed the main CPS interview. As part of the respondent debriefing interview, respondents were asked to classify descriptions of various activities in terms of their own understanding of labor force concepts, such as 'work'. The findings clearly show that many respondents interpret 'work' differently from that intended by the survey definition of work. Results further suggest that respondents' definitions depend on their characteristics and experience.
Entropy Message Passing

The paper proposes a new message passing algorithm for cycle-free factor graphs. The proposed "entropy message passing" (EMP) algorithm may be viewed as sum-product message passing over the entropy semiring, which has previously appeared in automata theory. The primary use of EMP is to compute the entropy of a model. However, EMP can also be used to compute expressions that appear in expectation maximization and in gradient-descent algorithms.
University of Pennsylvania Working Papers in Linguistics Unsupervised Learning of Prosodic Boundaries in Asl Unsupervised Learning of Prosodic Boundaries in Asl Unsupervised Learning of Prosodic Boundaries in Asl

In both spoken and sign languages, prosodic cues signal the ends of intonational phrases. Children must somehow learn to associate these cues with phrase boundaries without explicitly being told where those boundaries are. We present two unsupervised statistical models that learn to identify the ends of intonational phrases (I-phrases) in American Sign Language (ASL) based on prosodic cues: a mixture model, and a hidden Markov model. Although neither model is presented with labeled phrase boundaries, both models recover reasonable parameters and achieve performance comparable to models that are trained with labeled boundaries. However, the between-state dependence of the hidden Markov model does not improve the performance. The success of these models sheds light on how infants might learn the prosodic system without explicit instruction.