Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Adaptive Probing for Real-Time Problem Diagnosis in Distributed Computer Systems

In this work, we focus on cost-efficient techniques for realtime diagnosis in distributed systems that allow an adaptive, on-line selection and execution of appropriate measurements (tests). Particularly, one of our applications concerns fault diagnosis in distributed computer systems and networks by using test transactions, or probes (e.g., "traceroute" or "ping" commands). The key efficiency issues include both the cost of probing (e.g., the number of probes), and the computational complexity of diagnosis. In our past work (see (Rish, Brodie, & Ma 2002a)), we derived some theoretical conditions on the number of probes required for an asymptotic error-free diagnosis, and developed efficient search techniques for probe set selection that can greatly reduce the probe set size while maintaining its diagnostic capability (Brodie, Rish, & Ma 2001). Next, we considered the problem of real-time diagnosis as a probabilistic inference in Bayesian networks and investigated simple and efficient local approximation techniques, based on variable-elimination (the minibucket scheme (Dechter & Rish 2002)). Our empirical studies show that these approximations "degrade gracefully" with noise and often yield an optimal solution when noise is low enough, and our initial theoretical analysis explains this behavior for the simplest (greedy) approximation (Rish, Brodie, & Ma 2002a; 2002b). Our future work will focus on adapting more sophisticated approximation techniques, such as Generalized Belief Propagation (Yedidia, Freeman, & Weiss 2001), to real-time scenarios, and a real-time, incremental learning of Dynamic Bayesian Networks based on the historic data and
Analyzing Tomographic SAR Data of a Forest With Respect to Frequency, Polarization, and Focusing Technique

Forest canopies are semitransparent to microwaves at both L- and P-bands. Thus, a number of scattering sources and different types of scattering mechanisms may contribute to a single range cell of a synthetic aperture radar (SAR) image. By appropriately combining the SAR data of multiple parallel flight paths, a large 2-D aperture is synthesized, which allows for tomographic imaging of the 3-D structure of such semitransparent media and the underlying ground. A separate paper deals with the actual tomographic imaging part that leads to the 3-D data cube. In particular, three focusing techniques are described and analyzed: multilook beamforming, robust Capon beamforming, and multiple signal classification beamforming. In this paper, the resulting data products obtained by tomographically focusing two airborne multibaseline SAR data sets of a partially forested area, one at L-band and another at P-band, are subject to a detailed analysis with respect to the location and the type of backscattering sources. In particular, the following aspects are investigated: 1) The forest structure, as obtained from the vertical profiles of intensities at sample plot locations within the forest, is compared to the height distribution of the top of the forest canopy, as derived from airborne laser scanning data, and profiles are presented for all polarimetric channels and focusing techniques, as well as at both frequencies; 2) the type and location of scattering mechanisms are analyzed as functions of height for the two frequencies, namely, L- and P-bands, and using the polarimetric channels, as well as the Pauli and CloudePottier decompositions thereof; and 3) the accuracy of the ground elevation estimation obtained from the different focusing techniques and the two frequencies is assessed with the help of a lidar-derived digital elevation model.
Inhibition of PI3K Signaling Spurs New Therapeutic Opportunities in Inflammatory/Autoimmune Diseases and Hematological Malignancies

The phosphoinositide 3-kinase/mammalian target of rapamycin/protein kinase B (PI3K/mTOR/Akt) signaling pathway is central to a plethora of cellular mechanisms in a wide variety of cells including leukocytes. Perturbation of this signaling cascade is implicated in inflammatory and autoimmune disorders as well as hematological malignancies. Proteins within the PI3K/mTOR/Akt pathway therefore represent attractive targets for therapeutic intervention. There has been a remarkable evolution of PI3K inhibitors in the past 20 years from the early chemical tool compounds to drugs that are showing promise as anticancer agents in clinical trials. The use of animal models and pharmacological tools has expanded our knowledge about the contribution of individual class I PI3K isoforms to immune cell function. In addition, class II and III PI3K isoforms are emerging as nonredundant regulators of immune cell signaling revealing potentially novel targets for disease treatment. Further complexity is added to the PI3K/mTOR/Akt pathway by a number of novel signaling inputs and feedback mechanisms. These can present either caveats or opportunities for novel drug targets. Here, we consider recent advances in 1) our understanding of the contribution of individual PI3K isoforms to immune cell function and their relevance to inflammatory/autoimmune diseases as well as lymphoma and 2) development of small molecules with which to inhibit the PI3K pathway. We also consider whether manipulating other proximal elements of the PI3K signaling cascade (such as class II and III PI3Ks or lipid phosphatases) are likely to be successful in fighting off different immune diseases.
Phoneme-Based Continuous-Speech Recognition in the SPICOS-II System

This paper gives an overview of a research system for phoneme-based large-vocabulary continuous-speech recognition. The system provides the speaker-dependent recognition component in the speech-understanding system SPICOS that is designed to recognize and understand database queries spoken in natural German language. The recognition technique used in the SPICOS recognition system is based on an integrated approach that combines the various knowledge sources, such as an inventory of subword units, pronunciation lexicon and language model, during the process of decision making in order to improve the reliability of the acoustic recognition. The recognition problem then amounts to an efficient search for the globally optimal decision through a huge state space. The size of this state space depends primarily on the type of language model being used. Stochastic bigram and trigram models are studied and compared with the case of no language model restrictions. Recognition experiments have been carried out on a 917-word task for 4 speakers. For each speaker, 200 sentences totalling 1391 words had to be recognized.
Agreement of CMIP5 Simulated and Observed Ocean Anthropogenic CO2 Uptake

Previous studies found large biases between individual observational and model estimates of historical ocean anthropogenic carbon uptake. We show that the largest bias between the Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble mean and between two observational estimates of ocean anthropogenic carbon is due to a difference in start date. After adjusting the CMIP5 and observational estimates to the 1791–1995 period, all three carbon uptake estimates agree to within 3 Pg of C, about 4% of the total. The CMIP5 ensemble mean spatial bias compared to the observations is generally smaller than the observational error, apart from a negative bias in the Southern Ocean and a positive bias in the Southern Indian and Pacific Oceans compensating each other in the global mean. This dipole pattern is likely due to an equatorward and weak bias in the position of Southern Hemisphere westerlies and lack of mode and intermediate water ventilation.
Phase synchronization of chaotic oscillators.

We present the new effect of phase synchronization of weakly coupled self-sustained chaotic oscillators. To characterize this phenomenon, we use the analytic signal approach based on the Hilbert transform and partial Poincar\'e maps. For coupled R\"ossler attractors, in the synchronous regime the phases are locked, while the amplitudes vary chaotically and are practically uncorrelated. Coupling a chaotic oscillator with a hyperchaotic one, we observe another new type of synchronization, where the frequencies are entrained, while the phase difference is unbounded. A relation between the phase synchronization and the properties of the Lyapunov spectrum is studied.
Physiological and biochemical analyses of FlgH, a lipoprotein forming the outer membrane L ring of the flagellar basal body of Salmonella typhimurium

The FlgH protein of Salmonella typhimurium, from which the outer membrane L ring of the flagellar basal body is constructed, has a consensus motif (LTG C) for lipoylation and signal peptide cleavage. We have confirmed the previous finding (M. Homma, K. Ohnishi, T. Iino, and R. M. Macnab, J. Bacteriol. 169:3617-3624, 1987) that it is synthesized in precursor form and processed to a mature form with an apparent molecular mass of ca. 25 kDa. flgH alleles with an in-frame deletion or a 3' truncation still permitted processing. The deletion permitted partial restoration of motility in complementation tests, whereas the truncation did not. Globomycin, an antibiotic which inhibits signal peptide cleavage of prolipoproteins, caused accumulation of precursor forms of FlgH. When cells transformed with a plasmid containing the flgH gene were grown in the presence of [3H]palmitate, a 25-kDa protein doublet was found to be radiolabeled; its identity as FlgH was confirmed by shifts in mobility when the internally deleted and truncated alleles of the gene were used. Hook-basal body complexes from cells grown in the presence of [3H]palmitate demonstrated that FlgH incorporated into flagellar structure was also labeled. An in-frame fusion between the leader sequence of the periplasmic protein PeIB and the mature FlgH sequence, with the putative N-terminal cysteine replaced by glycine, resulted in production of a fusion protein that was processed to its mature form. With a low-copy-number plasmid, the ability of this pelB-flgH fusion to complement a flgH mutant was poor, but with a high-copy-number plasmid, it was comparable to that of the wild type. Although lacking the N-terminal cysteine and therefore being incapable of lipoylation via a thioether linkage, the mutant protein still incorporated [3H]palmitate at low levels, perhaps through acylation of the N-terminal alpha-amino group. We conclude that FlgH is a lipoprotein and that under normal physiological conditions the lipoyl modification is necessary for FlgH to function properly as the L-ring protein of the flagellar basal body. We suggest that the N terminus of FlgH is responsible for anchoring the basal body in the outer membrane and that the C terminus may be responsible for binding to the P ring to form the L,P-ring complex.
Unwarping heated bones : a quantitative analysis of heat-induced skeletal deformations using 3D geometric morphometrics

COELHO, Joao Pedro Valente de Oliveira - Unwarping heated bones : a quantitative analysis of heat-induced skeletal deformations using 3D geometric morphometrics. Coimbra : [s.n. ], 2015. Dissertacao de Mestrado em Evolucao e Biologia Humanas.
Voiding Pattern of Healthy Taiwanese Women

Aim: Few studies have examined the voiding pattern of healthy females, despite the importance of such research for diagnosing abnormal voiding behavior. This study investigates the voiding behavior of healthy women in Taiwan. Methods: 68 healthy women, aged 19–66 years and claiming to void normally were enrolled. Twenty-two of the subjects (32.4%) were postmenopausal. Each woman completed a 3-day voiding diary. The diary recorded urine volume, voiding frequency, urine volume per voiding for the whole day (24 h), and urine volume during both daytime and nighttime. Age and various other voiding parameters were correlated, and the voiding patterns were compared between premenopausal and postmenopausal women. Results: All women voided 7.34 ± 1.63 times daily. Higher age was associated with higher whole day and daytime voiding frequency. Nocturia was not common for the group as a whole, with a mean nocturnal voiding of 0.25 times per night. However, higher age was significantly associated with a higher nighttime voiding frequency. A significantly positive correlation was also observed between age and whole day urine volume. Compared with regularly menstruating women, postmenopausal women had a significantly higher whole day and nighttime voiding frequency. Menopause and age both independently affect voiding parameters after multivariate analysis. Conclusions: The results of this study provide invaluable baseline data on female voiding behavior. Additionally, this study found that for healthy women, age and menstruation status significantly affect voiding patterns. Analysis of female voiding behavior thus should consider these two factors.
Receptivity and the Welcoming Cities Movement: Advancing a Regional Immigrant Integration Policy Framework in Metropolitan Atlanta, Georgia

ABSTRACT Welcoming America is a nonprofit organization based in Decatur, Georgia. Their focus is on making communities more inclusive for everyone, including racially and ethnically diverse foreign-born residents. In recent years, Welcoming America has developed an affiliate network throughout the United States comprised of institutions including nonprofits and municipal governments. Our research documents their evolution and how these efforts serve as a resource and cultural broker for native- and foreign-born residents. Our examination of four “welcoming cities” in the Atlanta Metropolitan Statistical Area (Atlanta, Clarkston, Decatur, Norcross) describes how these initiatives were established and what substantive policy changes have taken place. We examine whether such criteria are useful for advancing a regional welcoming platform for the Atlanta region. We use geographic information systems to determine whether, and to what extent, other municipalities within the Atlanta metropolitan area beyond the current four welcoming cities could potentially be part of such a welcoming region. Recommendations are made within the broader context of state- and federal-level immigration policy.
Adaptive Random Test Case Prioritization

Regression testing assures changed programs against unintended amendments. Rearranging the execution order of test cases is a key idea to improve their effectiveness. Paradoxically, many test case prioritization techniques resolve tie cases using the random selection approach, and yet random ordering of test cases has been considered as ineffective. Existing unit testing research unveils that adaptive random testing (ART) is a promising candidate that may replace random testing (RT). In this paper, we not only propose a new family of coverage-based ART techniques, but also show empirically that they are statistically superior to the RT-based technique in detecting faults. Furthermore, one of the ART prioritization techniques is consistently comparable to some of the best coverage-based prioritization techniques (namely, the "additional" techniques) and yet involves much less time cost.
On Random Weights for Texture Generation in One Layer Neural Networks

Recent work in the literature has shown experimentally that one can use the lower layers of a trained convolutional neural network (CNN) to model natural textures. More interestingly, it has also been experimentally shown that only one layer with random filters can also model textures although with less variability. In this paper we ask the question as to why one layer CNNs with random filters are so effective in generating textures? We theoretically show that one layer convolutional architectures (without a non-linearity) paired with the an energy function used in previous literature, can in fact preserve and modulate frequency coefficients in a manner so that random weights and pretrained weights will generate the same type of images. Based on the results of this analysis we question whether similar properties hold in the case where one uses one convolution layer with a non-linearity. We show that in the case of ReLu non-linearity there are situations where only one input will give the minimum possible energy whereas in the case of no nonlinearity, there are always infinite solutions that will give the minimum possible energy. Thus we can show that in certain situations adding a ReLu non-linearity generates less variable images.
Time based Activity Inference using Latent Dirichlet Allocation

In this paper we address the problem of time based activity inference in unsupervised manner for an area under surveillance. We use a Latent Dirichlet Allocation based model that captures the activities and how they change over time. We use agglomerative clustering on optical flow vectors to code direction and spatial information. In this model each activity is associated with not only a mixture distribution over these cluster occurrences but also on the distribution over timestamps of their occurrences. Our method thus helps in determining the prominence and the correlation of activities over a period of time.
Flavonoid intake and all-cause mortality.

BACKGROUND Flavonoids are bioactive compounds found in foods such as tea, chocolate, red wine, fruit, and vegetables. Higher intakes of specific flavonoids and flavonoid-rich foods have been linked to reduced mortality from specific vascular diseases and cancers. However, the importance of flavonoids in preventing all-cause mortality remains uncertain. OBJECTIVE The objective was to explore the association between flavonoid intake and risk of 5-y mortality from all causes by using 2 comprehensive food composition databases to assess flavonoid intake. DESIGN The study population included 1063 randomly selected women aged >75 y. All-cause, cancer, and cardiovascular mortalities were assessed over 5 y of follow-up through the Western Australia Data Linkage System. Two estimates of flavonoid intake (total flavonoidUSDA and total flavonoidPE) were determined by using food composition data from the USDA and the Phenol-Explorer (PE) databases, respectively. RESULTS During the 5-y follow-up period, 129 (12%) deaths were documented. Participants with high total flavonoid intake were at lower risk [multivariate-adjusted HR (95% CI)] of 5-y all-cause mortality than those with low total flavonoid consumption [total flavonoidUSDA: 0.37 (0.22, 0.58); total flavonoidPE: 0.36 (0.22, 0.60)]. Similar beneficial relations were observed for both cardiovascular disease mortality [total flavonoidUSDA: 0.34 (0.17, 0.69); flavonoidPE: 0.32 (0.16, 0.61)] and cancer mortality [total flavonoidUSDA: 0.25 (0.10, 0.62); flavonoidPE: 0.26 (0.11, 0.62)]. CONCLUSIONS Using the most comprehensive flavonoid databases, we provide evidence that high consumption of flavonoids is associated with reduced risk of mortality in older women. The benefits of flavonoids may extend to the etiology of cancer and cardiovascular disease.
Neuroprotection of soyabean isoflavone co-administration with folic acid against β-amyloid 1-40-induced neurotoxicity in rats

Soya isoflavones (SIF) and folic acid (FA) both confer the biological properties of antioxidation; however, the mechanism of their antioxidant effect on nervous system development is unclear. Our purpose is to investigate the neuroprotective effects of SIF, FA or co-administration of SIF with FA against β-amyloid 1-40 (Aβ1-40)-induced learning and memory impairment in rats. In the present study, the learning and memory ability of rats and the amount of amyloid-positive neurons in the cerebral cortex and hippocampal CA1 area were measured. The levels of total antioxidant capacity (T-AOC), glutathione (GSH) and glutathione peroxidase (GSH-Px) in serum and brain tissue were also measured. The results showed that intracerebroventricular administration of Aβ1-40 resulted in a dramatic prolongation of the escape latency; however, in the SIF, FA and SIF+FA treatment groups, the functional deficits of learning and memory were significantly improved. Moreover, after Aβ1-40 injection, the levels of T-AOC and GSH were profoundly decreased, suggesting a decline of antioxidant activity in the rats. However, intragastric pre-treatment with SIF, or FA, or SIF+FA resulted in a significant increase of antioxidative activity. SIF, or FA, or SIF+FA treatments also reversed the Aβ1-40-induced increase in the amount of amyloid-positive neurons. These results suggest that: (1) learning or memory impairment in experimental rats was caused by Aβ1-40, which is probably attributed to Aβ-induced oxidative damage and deposition of β-amyloid peptides in the brain; (2) pre-administration of SIF and/or FA may prevent the pathological alterations caused by Aβ1-40 treatment and the neuroprotective effects of SIF and/or FA are indicated.
An investigation of two multivariate permutation methods for controlling the false discovery proportion

Identifying genes that are differentially expressed between classes of samples is an important objective of many microarray experiments. Because of the thousands of genes typically considered, there is a tension between identifying as many of the truly differentially expressed genes as possible, but not too many genes that are not really differentially expressed (false discoveries). Controlling the proportion of identified genes that are false discoveries, the false discovery proportion (FDP), is a goal of interest. In this paper, two multivariate permutation methods are investigated for controlling the FDP. One is based on a multivariate permutation testing (MPT) method that probabilistically controls the number of false discoveries, and the other is based on the Significance Analysis of Microarrays (SAM) procedure that provides an estimate of the FDP. Both methods account for the correlations among the genes. We find the ability of the methods to control the proportion of false discoveries varies substantially depending on the implementation characteristics. For example, for both methods one can proceed from the most significant gene to the least significant gene until the estimated FDP is just above the targeted level (‘top‐down’ approach), or from the least significant gene to the most significant gene until the estimated FDP is just below the targeted level (‘bottom‐up’ approach). We find that the top‐down MPT‐based method probabilistically controls the FDP, whereas our implementation of the top‐down SAM‐based method does not. Bottom‐up MPT‐based or SAM‐based methods can result in poor control of the FDP. Published in 2007 by John Wiley & Sons, Ltd.
Let's put the person back into entrepreneurship research: A meta-analysis on the relationship between business owners' personality traits, business creation, and success

The role of personality traits in the decision to start a business and to maintain it successfully is discussed controversially in entrepreneurship research. Our meta-analysis builds upon and extends earlier meta-analyses by doing a full analysis of personality traits that includes a comparison of different traits from a theoretical perspective and by analysing a full set of personality predictors for both start-up activities as well as success. Theoretically, our article adds to the literature by matching traits to the tasks of entrepreneurs. The results indicate that traits matched to the task of running a business produced higher effect sizes with business creation than traits that were not matched to the task of running an enterprise, corrected r = . 247, K = 47, N = 13,280, and corrected r = . 124, K = 20, N = 3975, respectively. Moreover, traits matched to the task produced higher correlations with success, corrected r = . 250, K = 42, N = 5607, than traits not matched to the task of running a business, corrected r = . 028, K = 13, N = 2777. The traits matched to entrepreneurship significantly correlated with entrepreneurial behaviour (business creation, business success) were need for achievement, generalized self-efficacy, innovativeness, stress tolerance, need for autonomy, and proactive personality. These relationships were of moderate size in general and, moreover, heterogeneity suggested that future research should analyse moderator variables.