Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Implementation of Generalized Quantification in Relational Query Languages

We present research aimed at improving our understanding of the use and implementation of quantification in relational query languages in general and SQL in particular. In order to make our results as general as possible, we use the framework of Generalized Quantification. Generalized Quantifiers (GQs) are high-level, declarative logical operators that in the past have been studied from a theoretical perspective. In this paper we focus on their practical use, showing how to incorporate a dynamic set of GQs in relational query languages, how to implement them efficiently and use them in the context of SQL. We present experimental evidence of the performance of the approach, showing that it improves over traditional (relational) approaches.
Isothermal Non-Linear Device Characterization

Semiconductor device characterization is traditionally focused on the measurement of the DC and AC characteristics. In view of this, there is a lack of characterization methods supporting the overall qualification of the device (non-) linearity for various bias conditions. One way to study the device linearity is to create constant OIP3 contours in the I(V) output plane. Using this data representation, insight is gained about the device linearity under various bias conditions. This is useful in circuit design, as well as for model verification. In order to avoid thermal effects, this type of data is preferably measured under isothermal (pulsed) conditions. Based on these considerations we have developed a nonlinear RF characterization system for the isothermal measurement of spectral components. In this work we give an overview of the measurement system setup together with some initial results.
Microenvironment and Immunology Tumor MMP-1 Activates Endothelial PAR 1 to Facilitate Vascular Intravasation and Metastatic Dissemination

Intravasation, the active entry of primary tumor cells into the vasculature, remains the least studied step in the metastatic cascade. Protease-mediated escape and stromal invasion of tumor cells represent widely accepted processes leading up to the intravasation step. However, molecular factors that contribute directly to tumor cell vascular penetration have not been identified. In this study, the in vivo role of the collagenolytic protease, MMP-1, in cancer cell intravasation and metastasis was analyzed by using a highly disseminating variant of human HEp3 epidermoid carcinoma, HEp3-hi/diss. Although naturally acquired or experimentally induced MMP-1 deficiency substantially suppressed HEp3-hi/diss intravasation, supplementation of recombinant MMP-1 to MMP-1– silenced primary tumors restored their impaired vascular dissemination. Surprisingly, abrogation of MMP-1 production and activity did not significantly affect HEp3-hi/diss migration or matrix invasion, suggesting noncollagenolytic mechanisms underlying MMP-1–dependent cell intravasation. In support of such noncollagenolytic mechanisms, MMP-1 silencing in HEp3-hi/diss cells modulated the microarchitecture and integrity of the angiogenic vasculature in a novel microtumor model. Concomitantly, MMP-1 deficiency led to decreased levels of intratumoral vascular permeability, tumor cell intravasation, and metastatic dissemination. Taking advantage of PAR1 deficiency of HEp3-hi/diss cells, we further show that endothelial PAR1 is a putative nontumor-cell/nonmatrix target, activation of which by carcinoma-produced MMP-1 regulates endothelial permeability and transendothelial migration. The inhibitory effects of specific PAR1 antagonists in live animals have also indicated that the mechanisms of MMP-1–dependent vascular permeability in tumors involve endothelial PAR1 activation. Together, our findings mechanistically underscore the contribution of a tumor MMP-1/endothelial PAR1 axis to actual intravasation events manifested by aggressive carcinoma cells. Cancer Res; 73(14); 1–16. 2013 AACR.
Fuzzy Logic Control System for Autonomous Sailboats

Sailing experts can explain basic sailing skills by rules about how to steer sails and rudder according to direction of target and wind. This paper describes how to transform the sailor's knowledge into Mamdani type fuzzy inference systems. The proposed system controls two actuators - rudder and sails - even during tack and jibe. In combination with an automatic weather routeing system the sailboat is able to reach any target completely autonomously. Experiments on a demonstration sailboat have shown excellent results. Detailed log data analysis shows manoeuvres carried out as expected by sailing experts.
Glyoxal measurement with a proton transfer reaction time of flight mass spectrometer (PTR‐TOF‐MS): characterization and calibration

We examine the potential for PTR‐TOF‐MS systems to quantitatively measure glyoxal in ambient air by characterizing the response of the instrument to a dilute glyoxal sample, calibrating the system as a function of humidity. The concentration of glyoxal in a sample air‐stream was measured with an UV absorption spectrometer in parallel to a PTR‐TOF‐MS. This calibration demonstrated that the PTR‐TOF‐MS has a relatively low sensitivity to glyoxal particularly at high humidity. Extensive fragmentation of glyoxal to formaldehyde was observed. This behaviour not only desensitizes PTR‐MS system to glyoxal; it may also pose a problem to the quantification of formaldehyde. © 2016 The Authors. Journal of Mass Spectrometry Published by John Wiley & Sons Ltd.
UC Office of the President Recent Work Title Direct and indirect effects of shifting rainfall on soil microbial respiration and enzyme activity in a semi-arid system

Background and aims Higher interannual precipitation variability is predicted for Southern California’s shrubdominated systems, promoting soil moisture variation and changing community composition. We asked if soil microbial responses to rainfall regime will depend on litter inputs; showing direct effects of altered precipitation through soil moisture and indirect effects resulting from shifting litter inputs. Methods Soils were collected from a 2-year field rainfall manipulation experiment. Under lab conditions soils were subjected to high or low moisture pulses with litter amendments from native and exotic species in all combinations. Results Soil respiration was higher with larger water pulses, but rose over time in low pulse treatments (direct response). Litter additions from exotic species promoted greater respiration, and results were stronger under higher soil moisture (indirect response). Extracellular enzyme activities generally were higher with exotic litter and under high moisture pulses. Those involved in N-cycling had much larger increases activity for the exotic litter addition high moisture pulse scenarios compared to other treatments. Conclusions Our results indicate the potential for microbial acclimation to drought conditions over short timescales and that below-ground processes are sensitive to direct and indirect effects of shifting rainfall regimes, especially where invasion is promoted by future climate change.
Gender and Race in School Psychology

Abstract. In the past 2 decades the number of women in the field of school psychology has increased markedly, with some estimates suggesting that approximately 8 out of 10 school psychologists are women, but the percentage of school psychologists who are White has remained constant at approximately 90%. This study was conducted on behalf of the National Association of School Psychologists Research Committee to investigate how other characteristics of the field such as age, years of experience, or type of employment differ by race or gender. Results suggested that significant gender differences existed in terms of age, years of experience, primary employment as a university faculty member, and time worked in university settings. Significant differences related to race existed for the number of hours worked in state departments of education as well as the percentage of minority students served. Potential explanations for the findings are provided and implications for the field are discussed.
Extracting Hierarchical Rules from a Weighted Alignment Matrix

Word alignment is a fundamental step in machine translation. Current statistical machine translation systems suffer from a major drawback: they only extract rules from 1-best alignments, which adversely affects the rule sets quality due to alignment mistakes. To alleviate this problem, we extract hierarchical rules from weighted alignment matrix (Liu et al., 2009). Since the sub-phrase pairs would change the inside and outside areas in the weighted alignment matrix of the hierarchical rules, we propose a new algorithm to calculate the relative frequencies and lexical weights of hierarchical rules. To achieve a balance between rule table size and performance, we construct a scoring measure that incorporates both frequency and lexical weight to select the best target phrase for each source phrase. Experiments show that our approach improves BLEU score by ranging from 1.4 to 1.9 points over baseline for hierarchical phrase-based, and 1.4 to 1.5 points for tree-to-string model.
Using an ambulatory stress monitoring device to identify relaxation due to untrained deep breathing

The objective of this paper is to assess the efficacy of deep breathing as a relaxation activity using a wearable stress monitor. For this purpose, we developed a protocol with different mentally stressful activities interleaved with regular sessions of deep breathing. We used three physiological sensors: a heart rate monitor, a respiration sensor, and an electrodermal activity sensor, to extract parameters that are consistent with the dominance of the sympathetic nervous system. Our results indicate that a large number of subjects were not able to perform the paced deep breathing exercise properly, which caused their stress levels to increase rather than to decrease. The study also showed that our wearable stress monitor can be used to monitor breathing technique and assess its effectiveness in relaxing individuals.
The orientation and dynamics of cell division within the plane of the developing vertebrate retina

The orientation of a dividing cell within the plane of the tissue plays an essential role in regulating cell fate in a range of developing structures. To assess its potential role in the developing vertebrate retina we used standard confocal microscopy of fixed tissue and time‐lapse confocal imaging of living tissue to examine the orientation of cell division and mitotic spindle rotation within the plane of the retinal neuroepithelium. Based on the study of three rat strains and chick, we report in contrast to recent findings that during the main phase of cell production (E18–P4 in the rat and E6–E11 in the chick) dividing cells are randomly orientated with respect to key anatomical landmarks as well as the orientation of their dividing neighbours. Results from live imaging of neonatal rat retinae support these findings and suggest that unlike the developing cortex, in which metaphase plates often rotate extensively before coming to rest in anaphase, retinal mitotic spindle rotations prior to cell division are minimal. Furthermore, the orientation of metaphase entry largely defines that which is finally adopted during anaphase. Hence, the dynamics of metaphase progression through to anaphase in the retina appear to differ markedly from the brain, and cell divisions within the plane of the tissue are randomly orientated. These results contribute to a growing body of evidence that suggests that the current paradigm with respect to asymmetric division derived from the study of invertebrates cannot be generalized to the developing vertebrate nervous system.
State-Taint Analysis for Detecting Resource Bugs

To verify whether a program uses resources in a valid manner is vital for program correctness. A number of solutions have been proposed to ensure such a property for resource usage. But most of them are sophisticated to use for resource bugs detection in practice and do not concern about the issue that an opened resource should be used. This open-but-not-used problem can cause resource starvation in some case as well. In particular, resources of smartphones are not only scarce but also energy-hungry. The misuse of resources could not only cause the system to run out of resources but also lead to a shorter battery life. That is the so-call energy leak problem. Aiming to provide a lightweight method and to detect as many resource bugs as possible, we propose a statetaint analysis in this paper. First, take the open-but-not-used problem into account, we specify the appropriate usage of resources as resource protocols. Then we propose a taint-like analysis which takes resource protocols as a guide to detect resource bugs. As an application, we enrich the resource usage protocols by taking into account energy leaks and use the refined protocols to guide the analysis for energy leak detection. We implement the analysis as a prototype tool called statedroid. Using this tool, we conduct experiments on several real Android applications and find several energy leaks.
Applying the meta-heuristic algorithms for mutation-based test data generation for Simulink models

Test data generation is one of the most important steps in testing process in order to reveal the faults in software. This activity is time-consuming and labor intensive. With the development of modeling tools such as Simulink, testing is able to early realize at design level. Therefore, it is desirable to seek the effective techniques for automating the testing process for Simulink models in order to make sure that the accurateness of systems which are built from these models. Mutation testing could be used as criterion to generate test data for Simulink models. In this paper, we evaluate the application of different meta-heuristic algorithms, like genetic algorithm, simulated annealing and artificial immune system, to optimize mutation-based test data generation in terms of killing the number of generated mutants for Simulink models. We discuss the effectiveness of these approaches and propose also an improvement of the genetic algorithm. These approaches have been applied to some different case studies and the obtained results are very promising.
Women In Their Place: Paul and the Corinthian Discourse of Gender and Sanctuary space

Women in Their Place: Paul and the Corinthian Discourse of Gender and Sanctuary Space, by Jorunn Okland. JSNTSup 269. London: TT thus, the examination can ascertain how both cosmic and urban spaces had particularly gendered associations. The divide between the private and public sphere becomes especially relevant in this analysis, as Okland maintains that sanctuary space should not be treated as a subcategory of public space, but as its own separate category (p. 58). In treating the ancient gender system of space, Okland borrows historian Yvonne Hirdman's description of two dynamics of gender distinction, a dichotomy that separates and a hierarchy that integrates. Okland will have frequent reason to return to the logics of this system throughout her analysis, since, even when the Romans or Paul begin to include women and men in similar spaces, the gendered power relations can still be maintained by hierarchical measures. Moving from the general ancient Mediterranean context to the particular spaces of early Roman Corinth, ch. 4 ("Places for Women in Early Roman Corinth's Ritual and Sanctuary Spaces") carefully sketches how women are constructed in ritual space. …
Determinants of Species Richness in the Park Grass Experiment

The Park Grass Experiment at Rothamsted in southeast England was started in 1856, making it the longest‐running experiment in plant ecology anywhere in the world. Experimental inputs include a range of fertilizers (nitrogen, phosphorus, potassium, and organic manures) applied annually, with lime applied occasionally, and these have led to an increase in biomass and, where nitrogen was applied in the form of ammonium sulfate, to substantial decreases in soil pH. The number of species per plot varies from three to 44 per 200 m2, affording a unique opportunity to study the determinants of plant species richness and to estimate the effect sizes attributable to different factors. The response of species richness to biomass depends on the amount and type of nitrogen applied; richness declined monotonically with increasing biomass on plots receiving no nitrogen or receiving nitrogen in the form of sodium nitrate, but there was no relationship between species richness and biomass on plots acidified by ammonium sulfate application. The response to lime also depended on the type of nitrogen applied; there was no relationship between lime treatment and species richness, except in plots receiving nitrogen in the form of ammonium sulfate, where species richness increased sharply with increasing soil pH. The addition of phosphorus reduced species richness, and application of potassium along with phosphorus reduced species richness further, but the biggest negative effects were when nitrogen and phosphorus were applied together. The analysis demonstrates how multiple factors contribute to the observed diversity patterns and how environmental regulation of species pools can operate at the same spatial and temporal scale as biomass effects.
A Java signal analysis tool for signal processing experiments

A program to simulate discrete time linear systems is presented. The software is written as a Java applet and can be accessed on the Internet. Object oriented programming allows the user to construct and simulate a variety of systems. The program uses a graphical user interface which is easy to learn and it provides a visualization of the system and signal flow. The software is currently being used at Arizona State University to support an online software laboratory for a senior level digital signal processing (DSP) course. This paper presents our experiences gained by using the program in a class setting and gives examples of possible laboratory problems.
A Novel Endmember Bundle Extraction and Clustering Approach for Capturing Spectral Variability Within Endmember Classes

Spectral variability, unrelated to the purity of endmembers, can change the geometry of the dataspace and affect conventional methods used to identify endmembers. Several methods have been developed to identify and extract endmember bundles representing the spectral variability within each endmember class. These methods, however, operate on the geometry of the dataspace. In addition, they commonly use k-means clustering that requires a priori the number of endmember classes present in a scene and may fail to group endmember spectra representing spectral variability within each class. This paper introduces a novel approach, spectral curve-based endmember extraction (SCEE), which allows for the extraction and clustering of multiple spectra representing spectral variability within endmember classes. The significant differences between SCEE and conventional methods are: i) SCEE is based on the shape of a spectral curve, not the geometry of the data simplex; and ii) SCEE extracts multiple endmember bundle candidates representing a particular class, without a priori knowledge of the number of endmember classes in a scene. Once multiple endmember bundle candidates are identified, they are automatically grouped by sequential pairwise clustering in order to determine the final number of endmember classes. The performance of SCEE is compared with that of other state-of-the-art endmember bundle extraction methods using simulated data and hyperspectral imagery of a mine pit and Cuprite. Results showed that multiple endmember bundles identified by SCEE gave better matches with spectral variability of reference spectra than those by other methods and were better able to encompass the range of variability within each class.
Pro-/Antiinflammatory Dysregulation in Early Psychosis: Results from a 1-Year Follow-Up Study

Background: Previous studies indicated a systemic deregulation of the pro-/antiinflammatory balance in subjects after 6 months of a first psychotic episode. This disruption was reexamined 12 months after diagnosis to identify potential risk/protective factors and associations with symptom severity. Methods: Eighty-five subjects were followed during 12 months and the determination of the same pro-/antiinflammatory mediators was carried out in plasma and peripheral blood mononuclear cells. Multivariate logistic regression analyses were used to identify risk/protective factors. Multiple linear regression models were performed to detect the change of each biological marker during follow-up in relation to clinical characteristics and confounding factors. Results: This study suggests a more severe systemic pro-/antiinflammatory deregulation than in earlier pathological stages in first psychotic episode, because not only were intracellular components of the inflammatory response increased but also the majority of soluble elements. Nitrite plasma levels and cyclooxygenase-2 expression in peripheral blood mononuclear cells are reliable potential risk factors and 15d-prostaglandin-J2 plasma levels a protection biomarker. An interesting relationship exists between antipsychotic dose and the levels of prostaglandin-E2 (inverse) and 15d-prostaglandin-J2 (direct). An inverse relationship between the Global Assessment of Functioning scale and lipid peroxidation is also present. Conclusions: Summing up, pro-/antiinflammatory mediators can be used as risk/protection biomarkers. The inverse association between oxidative/nitrosative damage and the Global Assessment of Functioning scale, and the possibility that one of the targets of antipsychotics could be the restoration of the pro-/antiinflammatory balance support the use of antiinflammatory drugs as coadjuvant to antipsychotics.
Reducing the energy consumption in wireless sensor networks using delay aware dynamic routing protocol

An energy-efficient smart protocol design is a key challenging problem in Wireless Sensor Networks (WSNs). Some of the few existing energy-efficient routing protocols schemes always forward the packets through the minimum energy based optimal route to the sink to minimize energy consumption. It causes an unbalanced distribution of residual energy between sensor nodes, which leads to network partition. The prime goal of this approach is to forward packets to sink through the energy denser area to protect the nodes with less residual energy, which is maximizing the Sensor Networks Lifetime. The existing technique Energy Balanced Routing Protocol (EBRP) fails to achieve Throughput, End-to-End Delay, in order to improve the Network Performance. So the efficient routing protocol is needed with the capabilities of both the Energy Efficiency and Energy Balancing. To address these issues, we have proposed Delay Aware Energy Balanced Dynamic Routing Protocol (DA-EBDRP). The proposed routing technique achieves in terms of End-to-End Delay, Throughput, Portion of Living Node (PLN) and Network Lifetime. By simulation results the proposed algorithm achieves better performance than the existing methods.
Tracking Business Trends - Dilemmas Of Measurement

Corporate performance may be tracked using various measures. Our model simulating the behaviour of a simple firm underlines that the choice on measurement unit determines what distortions we will face so based on different measures we may end up identifying completely different cycles. On the top of that, these cycles would radically modify if firms within the given industry would change their strategy towards the same direction or when structural changes happen in the economy. This may end in researchers analyzing nonexisting cycle changes.