Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Identification of Security Risks in Edicts for Software Procurement

Brazilian Federal Institutions must obtain software tools by procurement, requiring that their software teams develop, verify and audit their specifications to ensure that software security risks concerns are clearly included in edicts. This work presents the Automated Analyst of Edicts tool for aiding the analysis of such document by automatically identifying the absence of relationships between its sentences and software security risks or security weaknesses concepts. This tool was tested on over 100 documents and compared to software security experts' performance for multi-label classification into five of the OWASP Top Ten risks. Specificity of 83% was achieved when analyzing individual sentences for multiple risks, and 90% negative prediction probability when applied to specific risk sentence relationships.
An Effective Approach for Key Exposure Resistance in Cloud using De Duplication and Tile Bitmap Method

Since a lot of data is dynamically updated and stored in today‟s scenario, the previous methods used for checking static data integrity can no longer be applied to analyze the integrity of the stored dynamic data in the cloud. In the existing system, the authors had focused on key management in a built in key exposure resilient system. In this paper, we have introduced the concept of de duplication strategy of data wherein the built-in key exposure resilient system will check the duplicacy of data and eliminate the redundant one using MD5 hashing. This will enforce space management in an efficient manner. Also, tile bitmap technique is used wherein the intrusions can be detected without any tampering of data to maintain its integrity.
A Redundant Covering Algorithm Applied to Text Classification

Covering algorithms for learning rule sets tend toward learning concise rule sets based on the training data. This bias may not be appropriate in the domain of text classification due to the large number of informative features these domains typically contain. We present a basic covering algorithm, DAIRY, that learns unordered rule sets, and present two extensions that encourage the rule learner to milk the training data to varying degrees, by recycling covered training data, and by searching for completely redundant but highly accurate rules. We evaluate these modifications on web page and newsgroup recommendation problems and show recycling can improve classification accuracy by over 10%. Redundant rule learning provides smaller increases in most datasets, but may decrease accuracy in some.
Abundance of hybrid genomes among Vibrio cholerae in the aquatic environment determined by fluorescence labelled gene cassette PCR and pulsed field gel electrophoresis : An Australian perspective

Vibrio cholerae is the causative agent of cholera, a life threatening and watery diarrhoea that causes an estimated 3–5 million cholera cases and100000–120000 deaths per year (Zuckerman et al., 2007). The current pandemic of cholera is caused by El Tor biotype of the O1 serotype distinct from the classical biotype that is responsible for the previous pandemics. Recently, V. cholerae strains isolated from Asia and Africa have been reported to harbour phenotypic and genotypic characteristics (Nair et al.,2002 ; Safa et al., 2005; Safa et al., 2009) from both the classical and El Tor (ET) biotypes suggesting that they are genetic hybrids (Safa et al., 2009). These hybrid strains possess all the necessary virulence genes and genetic traits leading to fears that these strains may initiate a new pandemic. The fact that the V. cholerae hybrid strains possess characteristics related to the classical biotype is noteworthy since the classical biotype was believed to be extinct (Safa et al., 2009). The types of V. cholerae residing in the aquatic environment of Sydney, Australia and its relatedness to known strains remains unknown due to the lack of bacteriological and molecular investigations. Using a new technique profiling integron-associated gene cassettes PCR (Labbate et al., 2007) and Pulse Field Gel electrophoresis (PFGE), we provide evidence for the environmental presence of V. cholerae in Sydney with relatedness to characterized hybrid strains.
The Review of Economics and Statistics VOL . LXXIII FEBRUARY 1991 NUMBER 1 IS CONSUMPTION TOO SMOOTH ? LONG MEMORY AND THE DEATON PARADOX

Under common ARIMA representations of income, the permanent-income hypothesis predicts that the volatility of consumption should be larger than the volatility of unanticipated shocks to income; 'this prediction is not supported by the data. We examine whether this apparent excess smoothness of consumption is the result of the ARIMA representation's implicit restrictions on low-frequency dynamics. By using a generalized long-memory stochastic representation, we construct confidence intervals for the long-run impulse response of income in the absence of such lowfrequency restrictions. These intervals are quite wide and include regions in which excess smoothness vanishes.
Knowledge-based management support: an application of diagnostic reasoning to corporate financing decisions

The corporate finance application domain is studied as part of designing a diagnostic decision support system (DSS) for analyzing the financial ‘health’ of a modern corporation. A conceptual model of the financial management application domain is developed to capture the inherent interactions among financial domain objects. We view the objective of financial management to be to maintain a balance among financial performance measures, such as profitability, liquidity, dividend policy, and capital structure. We represent knowledge regarding these performance measures together with the related financial accounting data. A high-level structure to the diagnostic reasoning process is introduced via a classification scheme that identifies the relevant problem categories. The proposed approach supports the interpretation of domain relationships when formulating corrective measures. More importantly, it provides proactive management support by facilitating the analysis of domain facts for probable contingencies. The approach is illustrated with examples.  1998 John Wiley & Sons, Ltd.
The Erythropoietin Receptor

The process of erythropoiesis in the fetal liver and adult bone marrow is regulated by the hormone erythropoietin (Epo), which is produced in the kidney at low levels under homeostatic conditions. Defects in Epo production result in severe anemia; use of recombinant hormone has improved the lives of patients with renal failure or anemia because of bone marrow suppression. Deletion of the Epo gene in mice leads to embryonic lethality at days 13 to 15, coincident with the establishment of definitive (adult-type) erythropoiesis and underscoring the absolute necessity of Epo function in vivo. Epo has proven to be a successful pharmaceutical agent, one of the early triumphs of recombinant protein technology. Because of its clinical importance, a great deal of attention has focused on the molecular mechanisms of Epo-regulated erythropoiesis. This review highlights the basic concepts of Epo signal transduction within the hematopoietic system, the major site of Epo action in vivo.
Recursive Partitioning via Discriminant Functions for Rating

Aim of this paper is to propose a nonparametric method for the rating of financial stocks, such as Mutual Funds, Corporates, Equities etc. To this purpose, we refer to a procedure based on the joint use of linear discriminant analysis and tree based recursive partitioning. This method is applied when dealing with large sets of within-groups correlated covariates in order to overcome the dimensionality problem. For that, multiple splits defined upon a suitable linear combination of covariates are required. We describe a methodology that builds up a treebased model which nodes splitting is due to multiple splitting, following a recursive partitioning algorithm considering a splitting criterion based on linear discriminant functions. As a result, an automated and fast procedure allows to look for multiple splits able to capture suitable directions in the variability among the sets of covariates. We identify some variables to be meant as key factor in the rating attribution process. To rate financial assets, we perform T ti es the recursive partitioning procedure based on discriminant functions in order to obtain a partial rating with respect to each key factor. For each stock, the final rating is obtained averaging the partial ratings associated to each key factor. Main results of the performance of the proposed method to a set of equities listed in the Eurostox 600 Index are presented. K EYWORDS: Rating, Linear Discriminant Analysis, Recursive Partitioning, Multiple Splitting
Process Tracing in Public Administration: The Implications of Practitioner Insights for Methods of Inquiry

ABSTRACT The field of public administration is often seen as a late adopter of cutting-edge research methods. Related disciplines like political science use more advanced research methods for single or small-n case studies including techniques like process tracing. Many elements of process tracing are analogous to investigations. To inform process tracing practices, political scientists looked at Sherlock Holmes novels. We draw on the experiences of a police inspector and a former soldier who worked with intelligence to offer insights on the implementation of process tracing, bridge the academic–practitioner gap, and increase the methodological rigor in public administration research.
Why blame Bob ? Probabilistic generative models , counterfactual reasoning , and blame attribution

We consider an approach to blame attribution based on counterfactual reasoning in probabilistic generative models. In this view, people intervene on each variable within their model and assign blame in proportion to how much a change to a variable would have improved the outcome. This approach raises two questions: First, what structure do people use to represent a given situation? Second, how do they choose what alternatives to consider when intervening on an event? We use a series of coin-tossing scenarios to compare empirical data to different models within the proposed framework. The results suggest that people sample their intervention values from a prior rather than deterministically switching the value of a variable. The results further suggest that people represent scenarios differently when asked to reason about their own blame attributions, compared with the blame attributions they believe others will assign.
Towards Dynamic Bandwidth Management Optimization in VSDN Networks

Software Defined Network (SDN) mixed with Virtual Network (VN) is considered as a future network architecture-Virtual Software Defined Network (VSDN) for enhancing the network planning and the resource usage of networks. However, how to assign VSDN resources to virtual links and virtual network topologies efficiently and on- demand is one of the most challenging problems of any VSDN solution. This paper first proposes a dynamic bandwidth management architecture based on VSDN, and then presents an overall virtual network request scheduling model and finally proposes an optimization algorithm for dynamic bandwidth allocation, namely, K- Shortest Path based on Historical Path Data (HP-KSP). By taking advantage of historical path data and the real-time bandwidth of the physical network links, our HP-KSP algorithm adds a path allocation mechanism to the bandwidth management. Independent of the number of physical nodes, simulation results show that our proposed approach outperforms existing K-Shortest Path (KSP) and K-Shortest Path based on Disjoint Paths (DPKSP) algorithms since our HP-KSP satisfies more virtual requests which are mapped onto the same substrate and has higher QoA (Quality of Algorithms).
Differential Sympathetic Vasomotor Activation Induced by Liver Cirrhosis in Rats

We tested the hypothesis that there is a topographical sympathetic activation in rats submitted to experimental cirrhosis. Baseline renal (rSNA) and splanchnic (sSNA) sympathetic nerve activities were evaluated in anesthetized rats. In addition, we evaluated main arterial pressure (MAP), heart rate (HR), and baroreceptor reflex sensitivity (BRS). Cirrhotic Wistar rats were obtained by bile duct ligation (BDL). MAP and HR were measured in conscious rats, and cardiac BRS was assessed by changes in blood pressure induced by increasing doses of phenylephrine or sodium nitroprusside. The BRS and baseline for the control of sSNA and rSNA were also evaluated in urethane-anesthetized rats. Cirrhotic rats had increased baseline sSNA (BDL, 102 vs control, 58 spikes/s; p<0.05), but no baseline changes in the rSNA compared to controls. These data were accompanied by increased splanchnic BRS (p<0.05) and decreased cardiac (p<0.05) and renal BRS (p<0.05). Furthermore, BDL rats had reduced basal MAP (BDL, 93 vs control, 101 mmHg; p<0.05) accompanied by increased HR (BDL, 378 vs control, 356; p<0.05). Our data have shown topographical sympathetic activation in rats submitted to experimental cirrhosis. The BDL group had increased baseline sSNA, independent of dysfunction in the BRS and no changes in baseline rSNA. However, an impairment of rSNA and HR control by arterial baroreceptor was noted. We suggest that arterial baroreceptor impairment of rSNA and HR is an early marker of cardiovascular dysfunction related to liver cirrhosis and probably a major mechanism leading to sympathoexcitation in decompensated phase.
The Research Focus of Nations: Economic vs. Altruistic Motivations

What motivates the research strategies of nations and institutions? We suggest that research primarily serves two masters–altruism and economic growth. Some nations focus more research in altruistic (or non-economic) fields while others focus more research in fields associated with economic growth. What causes this difference? Are there characteristics that would suggest why a nation is more aligned with altruism or economic growth? To answer this question, we have identified nine major fields of research by analyzing the publication activity of 4429 institutions using Scopus data. Two fields of research are clearly altruistic (there is relatively little involvement by industry) and two fields are clearly aligned with economic growth. The altruistic vs. economic nature of nations based on their publication profiles across these fields is correlated with national indicators on wealth, education, capitalism, individualism, power, religion, and language. While previous research has suggested that national research strategy is aligned with national wealth, our analysis shows that national wealth is not highly correlated with the tradeoff between altruistic and economic motives. Instead, the tradeoff is largely captured by a culture of individualism. Accordingly, implications for national research strategies are discussed.
The Popularity of Articles in PubMed

The PubMed search engine displays query results in reverse chronological order, which is appropriate for users interested in the latest publications. The purpose of this paper is to use machine learning to order documents by popular- ity, or the predicted frequency that an article is viewed by the average PubMed user. Other research on general search en- gine usability has applied machine learning to order documents by their relevance to a given query. The approach here takes a global view of popularity across all users in a given time period, independent of their information need. An effec- tive method for learning popularity from clickthrough data is identified, and a novel measure of success in this task is pro- posed. The resulting model shows that the topic of an article has the largest single influence on its popularity, and its pub- lication date has a strong secondary influence. Possible applications and extensions are discussed.
Localization of Seizure Foci: Pitfalls and Caveats

The pitfalls and difficulties in accurately localizing seizure foci are reviewed. Basic issues regarding modeling, volume conduction, inhomogeneities, and corticocortical propagation are discussed, and the limitations of scalp and intracranial recordings are outlined. The ambiguities in interpreting patterns and their significance are highlighted with a concluding commentary on pitfalls in defining the epileptogenic region.
A no-reference synthesized view quality assessment using statistical features in morphological multiscale domain

In this paper a no-reference quality assessment metric for DIBR-synthesized images is proposed. Proposed metric uses the statistical features of morphologically decomposed image subbands in order to estimate distortion level in synthesized images. Hoyer index as a measure of sparsity is used as a statistical feature. A Support vector regression is used to calculate quality score. The performance is evaluated using publicly available IRCCyN/IVC DIBR image database. Performance of the proposed measure is compared with commonly used full-reference and no-reference metrics. Experimental results show that proposed metric achieves good results in terms of correlation with human subjective quality perception.
Optimal Unbiased Estimators for Evaluating Agent Performance

Evaluating the performance of an agent or group of agents can be, by itself, a very challenging problem. The stochastic nature of the environment plus the stochastic nature of agents' decisions can result in estimates with intractably large variances This paper examines the problem of finding low variance estimates of agent performance. In particular, we assume that some agent-environment dynamics are known, such as the random outcome of drawing a card or rolling a die. Other dynamics are unknown, such as the reasoning of a human or other black-box agent. Using the known dynamics, we describe the complete set of all unbiased estimators, that is, for any possible unknown dynamics the estimate's expectation is always the agent's expected utility. Then, given a belief abcut the unknown dynamics, we identify the unbiased estimator with minimum variance. If the belief is correct our estimate is optimal, and if the belief is wrong it is at least unbiased. Finally, we apply our unbiased estimator to the game of poker, demonstrating dramatically reduced variance and faster evaluation.
Suction Drain Tip Culture after Spine Surgery: Can It Predict a Surgical Site Infection?

Study Design Retrospective clinical study. Purpose To assess the diagnostic value of suction drain tip culture in patients undergoing primary posterior spine surgery. Overview of Literature To date, the diagnostic value of suction drain tip culture for predicting surgical site infection (SSI) has not been firmly established in orthopedic or spinal surgery. Methods In total, 133 patients who underwent primary posterior spine surgery from January 2013 to April 2015 were included in this retrospective study. Patients diagnosed with infective disease or condition was excluded. The suction drain tip was cut off approximately 5 cm from its far end. The sample was sent to the microbiological laboratory of the hospital for culture analysis. Any signs of infection, such as wound discharge or dehiscence, fever, chills, or chronic pain, were recorded. The culture outcome, identification of bacteria, and postoperative transition of the serum C-reactive protein level were also recorded in all patients. The wounds were followed up for a minimum of 3 months. Results A positive drain tip culture was found in 48 patients (36.1%), of whom, 6 developed SSI. The sensitivity of drain tip culture for SSI after primary posterior spine surgery was 60.0%, and the specificity was 65.9%. The association between the incidence of positive suction tip culture and SSI was not statistically significant. Among the 48 positive drain tip cultures, there was no significant association between the occurrence of SSI and virulence of isolated bacteria. There was no significant association between drain tip culture positivity and the duration of drainage, or between the rate of SSI and duration of drainage. Conclusions Suction drain tip culture analysis is a poor predictor of SSI after primary posterior spine surgery. Routine use of a drain tip culture is not supported by the results of this study.
Social Positions and Political Cross-Pressures: A Re-Examination

A distinction is made between two different theories of political behavior which have been grouped together under the term "cross-pressures. " Attention is focused on one of these two theories which holds that the existence of socially based partisan differences will have a direct effect on nonvoting and other forms of political escape. It is shown that earlier empirical support for this theory is generated by analyses which are subject to much the same methodological difficulties as in the case of status inconsistency and mobility effects. The theory is tested using a properly specified model for the 1956 national voting data and then for the 1948 Elmira data. In both cases no evidence of the existence of cross-pressure effects is found.
General and Fractional Hypertree Decompositions: Hard and Easy Cases

Hypertree decompositions, as well as the more powerful generalized hypertree decompositions (GHDs), and the yet more general fractional hypertree decompositions (FHD) are hypergraph decomposition methods successfully used for answering conjunctive queries and for the solution of constraint satisfaction problems. Every hypergraph H has a width relative to each of these methods: its hypertree width hw(H), its generalized hypertree width ghw(H), and its fractional hypertree width fhw(H), respectively. It is known that hw(H) ≤ k can be checked in polynomial time for fixed k, while checking ghw(H) ≤ k is NP-complete for k >= 3. The complexity of checking fhw(H) ≤ k for a fixed k has been open for over a decade. We settle this open problem by showing that checking fhw(H) ≤ k is NP-complete, even for k=2. The same construction allows us to prove also the NP-completeness of checking ghw(H) ≤ k for k=2. After proving these results, we identify meaningful restrictions, for which checking for bounded ghw or fhw becomes tractable.
Multiple-access channel with correlated states and cooperating encoders

In this study, a two-user discrete memoryless multiple-access channel with two correlated states known non-causally at the corresponding encoder is considered. Each encoder transmits a message independent of the other encoder's and tries to cooperate with it. To consider cooperative encoders, it is assumed that each encoder strictly-causally receives and finds out the other encoder's transmitted signals and tries to cooperate with the other encoder by transmitting its message. A special case is also studied in which the common part of the states is known at the both encoders, resulting in a larger rate region. For these two scenarios, achievable rate regions are derived using a combination of block-Markov and Gel'fand-Pinsker coding techniques, and outer bounds are also established. For the second scenario, the achievable rate region of the Gaussian model is derived, and some implications of the results are discussed.