Miracle-dz/UniFAR-FTUs huggingface dataset:
Structured and Interoperable Logging for the Cloud Computing Era: The Pitfalls and Benefits

Computer logs represent a valuable source of monitoring information being typically the only mechanism for gaining visibility into the behavior of monitored resources. However, even in modern cloud data centers the majority of logs is produced in an unstructured data format with free-form natural language messages carrying the most important portion of the information. This is source of many issues that prevent logs from being effectively and intelligently processed in an automated way. We argue that it is an essential flaw when considering the volume and heterogeneity of logging data produced by cloud. This paper elaborates on the common problems and shortcomings in the domain of (application) logging, and presents an experimental logging mechanism for Java language that is capable of producing logs in a unified and extensible format allowing for their efficient automated processing.
Decision Tree Based Depression Classification from Audio Video and Language Information

In order to improve the recognition accuracy of the Depression Classification Sub-Challenge (DCC) of the AVEC 2016, in this paper we propose a decision tree for depression classification. The decision tree is constructed according to the distribution of the multimodal prediction of PHQ-8 scores and participants' characteristics (PTSD/Depression Diagnostic, sleep-status, feeling and personality) obtained via the analysis of the transcript files of the participants. The proposed gender specific decision tree provides a way of fusing the upper level language information with the results obtained using low level audio and visual features. Experiments are carried out on the Distress Analysis Interview Corpus - Wizard of Oz (DAIC-WOZ) database, results show that the proposed depression classification schemes obtain very promising results on the development set, with F1 score reaching 0.857 for class depressed and 0.964 for class not depressed. Despite of the over-fitting problem in training the models of predicting the PHQ-8 scores, the classification schemes still obtain satisfying performance on the test set. The F1 score reaches 0.571 for class depressed and 0.877 for class not depressed, with the average 0.724 which is higher than the baseline result 0.700.
The impact of Spitzer infrared data on stellar mass estimates – and a revised galaxy stellar mass function at 0 < z < 5

Aims. We estimate stellar masses of galaxies in the high redshift universe with the intention of determining the influence of newly available Spitzer/IRAC infrared data on the analysis. Based on the results, we probe the mass assembly history of the universe. Methods. We use the GOODS-MUSIC catalog, which provides multiband photometry from the U-filter to the 8 µm Spitzer band for almost 15 000 galaxies with either spectroscopic (for ≈7% of the sample) or photometric redshifts, and apply a standard model fitting technique to estimate stellar masses. We than repeat our calculations with fixed photometric redshifts excluding Spitzer photometry and directly compare the outcomes to look for systematic deviations. Finally we use our results to compute stellar mass functions and mass densities up to redshift z = 5. Results. We find that stellar masses tend to be overestimated on average if further constraining Spitzer data are not included into the analysis. Whilst this trend is small up to intermediate redshifts z < 2.5 and falls within the typical error in mass, the deviation increases strongly for higher redshifts and reaches a maximum of a factor of three at redshift z ≈ 3.5. Thus, up to intermediate redshifts, results for stellar mass density are in good agreement with values taken from literature calculated without additional Spitzer photometry. At higher redshifts, however, we find a systematic trend towards lower mass densities if Spitzer/IRAC data are included.
Structural Breaks in the Cointegrated Vector Autoregressive Model

We generalize the cointegrated vector autoregressive model of Johansen (1988, 1991) to allow for structural breaks. We derive the likelihood ratio test for structural breaks occurring at fixed points in time, and show that it is asymptotically chi-squared. Moreover, we show how inference can be made when the null hypothesis is presence of structural breaks. The estimation technique derived for this purpose can be applied to several other generalizations of the standard model, beyond the structural breaks treated here. For example, the new technique can be applied to estimate models with heteroskedasticity. We apply our generalized model to US term structure data, accounting for structural breaks that coincide with the changes in the Fed's policy in September 1979 and October 1982. Contrary to previous findings we cannot reject the long-run implications of the expectations hypothesis.
A novel autoantibody against moesin in the serum of patients with MPO-ANCA-associated vasculitis.

BACKGROUND Antineutrophil cytoplasmic autoantibody (ANCA) directed against myeloperoxidase (MPO), a diagnostic criterion in MPO-ANCA-associated vasculitis (MPO-AAV), does not always correlate with disease activity. Here, we detected autoantibodies against moesin, which was located on the surface of stimulated endothelial cells, in the serum of patients. METHODS The anti-moesin autoantibody titer was evaluated by ELISA. Seventeen kinds of cytokines/chemokines were measured by a Bio-Plex system. RESULTS Serum creatinine in the anti-moesin autoantibody-positive group was higher than that in the negative group. Additionally, interferon (IFN)-γ, macrophage chemotactic peptide-1 (MCP-1), interleukin (IL)-2, IL-7, IL-12p70, IL-13, granulocyte/macrophage colony-stimulating factor (GM-CSF) and granulocyte colony-stimulating factor were significantly higher in the positive group. Furthermore, IL-7 and IL-12p70 levels correlated with the anti-moesin autoantibody titer. Based on these findings and the binding of anti-moesin IgG to neutrophils and monocytes, we detected the secretion of cytokines/chemokines such as IFN-γ, MCP-1 and GM-CSF from these cells. CONCLUSIONS The anti-moesin autoantibody existed in the serum of patients with MPO-AAV and was associated with the production of inflammatory cytokines/chemokines targeting neutrophils with a cytoplasmic profile, which suggests that the anti-moesin autoantibody has the possibility to be a novel autoantibody developing vasculitis via neutrophil and endothelial cell activation.
Enabling ‘ambitious activism’: Davutoğlu’s vision of a new foreign policy identity for Turkey

ABSTRACT Building on the argument that a state’s history and location in the world are inherent parts of its foreign policy narrative which constitutes its identity, this article analyzes the spatial and temporal representations of Turkey in Ahmet Davutoğlu’s articulation of foreign policy. It employs a critical constructivist perspective and explores how these representations have shaped the identity of the country. It contends that Davutoğlu’s foreign policy vision for Turkey is an attempt to reconstruct the international role and responsibilities of Turkey through a transformed identity based on a reinterpretation of its historical heritage and geographic location. Further, it argues that Davutoglu’s foreign policy discourse depicts Turkey as the global representative, speaker and leader of a specific community of peoples, which in turn has enabled an ‘ambitious activism’ in Turkish foreign policy, which is distinct from the previous period’s proactive foreign policy.
On the Industry Concentration of Actively Managed Equity Mutual Funds

Mutual fund managers may decide to deviate from a well-diversified portfolio and concentrate their holdings in industries where they have informational advantages. In this paper, we study the relation between the industry concentration and the performance of actively managed U.S. mutual funds from 1984 to 1999. Our results indicate that, on average, more concentrated funds perform better after controlling for risk and style differences using various performance measures. This finding suggests that investment ability is more evident among managers who hold portfolios concentrated in a few industries.
Validating silicon polytrodes with paired juxtacellular recordings: method and dataset

Cross-validating new methods for recording neural activity is necessary to accurately interpret and compare the signals they measure. Here we describe a procedure for precisely aligning two probes for in vivo “paired-recordings” such that the spiking activity of a single neuron is monitored with both a dense extracellular silicon polytrode and a juxtacellular micro-pipette. Our new method allows for efficient, reliable, and automated guidance of both probes to the same neural structure with micron resolution. We also describe a new dataset of paired-recordings, which is available online. We propose that our novel targeting system, and ever expanding cross-validation dataset, will be vital to the development of new algorithms for automatically detecting/sorting single-units, characterizing new electrode materials/designs, and resolving nagging questions regarding the origin and nature of extracellular neural signals.
Larger Right Posterior Parietal Volume in Action Video Game Experts: A Behavioral and Voxel-Based Morphometry (VBM) Study

Recent studies suggest that action video game players exhibit superior performance in visuospatial cognitive tasks compared with non-game players. However, the neural basis underlying this visuospatial cognitive performance advantage remains largely unknown. The present human behavioral and imaging study compared gray matter volume in action video game experts and non-experts using structural magnetic resonance imaging and voxel-based morphometry analysis. The results revealed significantly larger gray matter volume in the right posterior parietal cortex in experts compared with non-experts. Furthermore, the larger gray matter volume in the right posterior parietal cortex significantly correlated with individual performance in a visual working memory task in experts. These results suggest that differences in brain structure may be linked to extensive video game play, leading to superior visuospatial cognitive performance in action video game experts.
The Market Crash and Mass Layoffs: How the Current Economic Crisis May Affect Retirement

Abstract Recent dramatic declines in U.S. stock and housing markets have led to widespread speculation that shrinking retirement accounts and falling home equity will lead workers to delay retirement. Yet the weakness in the labor market and its impact on retirement are often overlooked. If older job seekers have difficulty finding work, they may retire earlier than expected. The net effect of the current economic crisis on retirement is thus far from clear. In this paper, we use 30 years of data from the March Current Population Survey to estimate models relating retirement decisions to fluctuations in equity, housing, and labor markets. We find that workers age 62 to 69 are responsive to the unemployment rate and to long-run fluctuations in stock market returns. Less-educated workers are more sensitive to labor market conditions and more-educated workers are more sensitive to stock market conditions. We find no evidence that workers age 55 to 61 respond to these fluctuations or that workers at any age respond to fluctuating housing markets. On net, we predict that the increase in retirement attributable to the rising unemployment rate will be almost 50 percent larger than the decrease in retirement brought about by the stock market crash.
Cost Versus Distance In the Traveling Salesman Problem

This paper studies the distribution of good solutions for the traveling salesman problem (TSP) on a well-known 532-city instance that has been solved optimally by Padberg and Rinaldi 16]. For each of ve local search heuristics, solutions are obtained from 2,500 diierent random starting points. Comparisons of these solutions show that lower-cost solutions have a strong tendency to be both closer to the optimal tour and closer to other good solutions. (Distance between two solutions is deened in terms of the number of edges they have in common.) These results support the conjecture of Boese, Kahng and Muddu 3] that the solution spaces of TSP instances have a \globally convex" or \big valley" character. This observation was used by 3] to motivate a new multi-start strategy for global optimization called Adaptive Multi-Start (AMS).
Daily variation of particulate air pollution and poor cardiac autonomic control in the elderly.

examined the cardiac autonomic response to daily variations in PM in 26 elderly (mean age 81) individuals for 3 consecutive weeks. Several standardized methods were used to measure 24-hr average PM concentrations prior to the clinical test inside (indoor PM2.5) and immediately outside (outdoor PM2.5 and PM2.5-10) of participants' residences. Resting, supine, 6-min R wave to R wave (R-R) interval data were collected to estimate high frequency (0.15-0.40 Hz) and low frequency (0.04-0.15 Hz) powers and standard deviation of normal R-R intervals (SDNN) as cardiac autonomic control indices. Participant-specific lower heart rate variability days were defined as days for which the high-frequency indices fell below the first tertile of the individual's high-frequency distribution over the study period. Indoor PM2.5 > 15 microg/m3 was used to define high pollution days. Results show that the odds ratio (95% confidence interval) of low heart rate variability high frequency for high (vs. not high) pollution days was 3.08 (1.43, 6.59). The ss-coefficients (standard error) from mixed models to assess the quantitative relationship between variations in indoor PM2.5 and the log-transformed high frequency, low frequency, and SDNN were: -0.029 (0.010), -0.027 (0.009), and -0.004 (0.003), respectively. This first study of cardiac autonomic control response to daily variations of PM2.5 indicates that increased levels of PM2.5 are associated with lower cardiac autonomic control, suggesting a possible mechanistic link between PM and cardiovascular disease mortality. ImagesFigure 1
Adaptive ontology-based navigation

This paper presents a proposal of navigation for the user, based on an existing ontology of the domain of the learning course. The navigation scheme of the course stands on interconnection of an ontology with existing learning material by the use of the keywords of the domain. On one side there is the user’s needs and goals and on the other side are possibilities and limitation of existing systems.
Process Innovation and Corporate Agility Balancing Efficiency and Adaptability in a Knowledge-Centric World

Customer service, corporate agility, speed, and efficiency are central to business performance in the modern world. Underpinning each of these concepts is a subtly different emphasis in the notion of business process – i.e., how the firm is organized. This paper explores issues associated with finding the right balance between standardization and evolution – allowing the firm to achieve organizational longevity (one result of corporate agility), with a special emphasis on service orientation and business process outsourcing. It first discusses business process terminology and then examines the increasing importance of knowledge workers in generating value for the firm. Focusing on the innovation imperative, it addresses service orientation as one component of corporate agility before exploring why knowledge workers need to be able to exercise their judgment. We then delve into the potential implications for process architecture, organizational maturity, and related management practices. We investigate the situations where process evolution is acceptable (if not desirable), challenging some of the existing design philosophies while highlighting alternatives that support both flexibility and efficiency. Finally, we look into the capabilities of modern Business Process Management (BPM) suites to support these competing agendas.
Clinical Significance of Early Detection of Esophageal Cancer in Patients with Head and Neck Cancer

Background/Aims The efficacy of surveillance for esophageal squamous cell neoplasia (ESCN) in patients with head and neck squamous cell carcinoma (HNSCC) remains controversial. Our study aimed to provide clinical data concerning the necessity of surveillance for detecting early ESCN in patients with HNSCC. Methods We retrospectively reviewed the data from 714 patients who were pathologically confirmed as having HNSCC (n=236 oral cavity cancers, 137 oropharyngeal cancers, 87 hypopharyngeal cancers, and 254 laryngeal cancers). Results Of 714 patients, during a median follow-up of 31 months, 48 ESCNs (37 synchronous and 11 metachronous) were detected in 36 patients (5%). Fifteen synchronous lesions (40.3%) were early ESCN, whereas nine metachronous lesions (81.8%) were early ESCN. The 3-year survival rates of HNSCC only and HNSCC combined with ESCN were 71.2% and 48.2%, respectively (p<0.001). Among 36 patients with ESCN, the 3-year survival rates for early and advanced ESCN were 77.7% and 21.7%, respectively (p=0.01). In the multivariate analysis, alcohol consumption and hypopharyngeal cancer were significant factors associated with the development of ESCN. Conclusions HN-SCC patients with early ESCN were similar in prognosis with patients without ESCN, in contrast to patients with advanced ESCN. Therefore, surveillance for the early detection of ESCN in patients with HNSCC, especially in alcohol drinkers and those with hypopharyngeal cancer, is warranted.
ACTUATED TRAFFIC SIGNAL OPTIMIZATION USING EVOLUTIONARY ALGORITHMS

The optimization of traffic signal systems is an important step towards successful traffic control, since delays in urban road networks depend largely on the signal system's performance. Due to their adaptivity, traffic-actuated signal controllers are widely used in traffic systems around the globe. However, their performance largely depends on the choice of appropriate control parameters. Here, we describe the application of NSGA-II, a multiobjective evolutionary algorithm, to the optimization of a traffic-actuated controller. Results show that parameters found by NSGA-II can be superior to those defined by a traffic engineer with respect to several objectives, including the resulting travel times and the necessary number of stops.
Short-term Debt and Financial Crises: What we can learn from U.S. Treasury Supply

We present a theory in which the key driver of short-term debt issued by the financial sector is the portfoliodemandforsafeandliquidassetsbythenon-financial sector. Households â€™ demand for safe andliquidassetsdrivesapremiumonsuchassetsthatthefinancial sector exploits by owning risky and illiquid assets and writing safe and liquid claims against these assets. The central prediction of the theory is that government debt should be a substitute for the net supply of privately issued short-term debt. We verify this prediction with data from 1914 to 2011 by showing the net supply of government debt, predominantly Treasuries, is strongly negatively correlated with the net supply of private short-term debt, defined to be the private supply of short-term safe and liquid debt, net of the financial sectorâ€™s holdings of Treasuries (and reserves and currency). A second set of predictions of the model concern the quantity of money (i.e. liquid bank liabilities such as checking accounts). The theory predicts that when government supply is large, banks should hold more of the supply and use it to back issuance of more liquid bank liabilities. We confirm this prediction as well. Moreover, we show that accounting for the impact of Treasury supply on bank money results in a stable estimate for money demand and can help resolve the â€œmissing money â€ puzzle of the post-1980 period. Finally, the theory predicts that the quantity of short-term debt issued by the financial sector should predict financial crises better than standard measures such as private credit/GDP. We also confirm this prediction.
Self-Organized Formation of Various Invariant-Feature Filters in the Adaptive-Subspace SOM

The adaptive-subspace self-organizing map (ASSOM) is a modular neural network architecture, the modules of which learn to identify input patterns subject to some simple transformations. The learning process is unsupervised, competitive, and related to that of the traditional SOM (self-organizing map). Each neural module becomes adaptively specific to some restricted class of transformations, and modules close to each other in the network become tuned to similar features in an orderly fashion. If different transformations exist in the input signals, different subsets of ASSOM units become tuned to these transformation classes.
Proactive personality, organizational context, employee creativity and innovative capability: Evidence from MNCs and domestic corporations

Purpose The purpose of this study is to develop and empirically examine antecedents of innovative capability in different organization categories of multinational corporations (MNCs) and domestic firms by applying the integrative theory, linking both personal and contextual factors in explaining employee creativity. Design/methodology/approach A conceptual framework has been developed based on previous research investigating the relationship between proactive personality, organizational context (hierarchy, communication, atmosphere and risk-taking orientation), employee creativity and, ultimately, corporate innovative capability. More remarkably, by applying multiple group analysis, this research emphasizes on the identification of distinct organizational and contextual characteristics in MNCs and native corporations that respectively affect organizations’ capacity to innovate via employee creativity. Findings The analysis revealed that four dimensions, communication, atmosphere, risk-taking orientation and employees’ proactive personality, have significant impacts on employee creativity and ultimately organizational innovative capability, whereas the proposed negative effect of hierarchy on employee creativity did not exist. This research also highlights the identification of respective organizational characteristics in MNCs and native corporations that affect their capacity to innovate via employee creativity. Given that proactive personality is a critical antecedent of innovative capability regardless of organization types, communication and atmosphere are statistically confirmed to be more influential antecessors in the MNC context, whereas for domestic corporations, risk-taking orientation is dominant. Originality/value This research is original and of great value for several reasons. First, it provides suggestion on a single personality trait, proactive personality, that correlates remarkably with creativity. Second, it examines the association between various organizational aspects and employee creativity to appraise and advance the results of previous classic studies done in the field. Last, it incorporates both personal and organizational factors in the evaluation of creativity and innovative capability not only in the context of multinational but also in domestic corporations.