Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Management for Release-based Software Evolution Using EMMA

This paper describes EMMA (Evolution-Memory Management Assistant), a tool to provide collaborative support for the release-based Evolutionary Delivery Model [4] of system development. Evolution information in EMMA is organized around four interrelated concepts: (1) properties, (2) assumptions, (3) solutions, and (4) change events. This information provides context to relate development decisions to higher-level purposes and to the assumptions under which decisions are made. By managing information about design decisions and directions for change, EMMA helps project managers to understand the issues involved and to be proactive in planning for system evolution. 1 The EMMA Metamodel for System Evolution EMMA, an Evolution-Memory Management Assistant, is a collaborative information management tool being developed by CoGenTex, Inc. under the sponsorship of the Evolutionary Development of Complex Software (EDCS) program to address the needs of managers and developers when developing and maintaining complex, evolvable systems. (As described in [8], the costs of maintenance can be much, much more than the cost of initial system development. However, relatively little tool support exists for this crucial activity.) EMMA supports the process of exploring, choosing among, and implementing alternative solutions by aiding in the acquisition and management of the information that needs to be shared among the project participants. 1.1 Goals and Solutions The organizing principle behind EMMA’s metamodel for system development is that to reason about system evolution, it is necessary to understand in detail the goal for a system and the solution constructed to address those goals. A goal for us is the list of desired properties that the system should have, together with the context (assumptions, definitions, resources and constraints) under which the system is to be developed. 1 Rome Laboratory Contract F30602-96-C-0220 A solution in the EMMA metamodel is an approach to satisfying some goal by either explicitly providing a reference to an actual implementation, or by partitioning system responsibilities among system elements, each of which is a solution for a simpler goal. For example, a solution for building a complex system might involve partitioning the system into user interface, data structures, and algorithms, each of which will be a solution with its own requirements to fulfill. In this way, complex high-level solutions are decomposed into simpler, more specific low-level solutions. Then higher-level solutions are constructed by composing low-level solutions. The collection of goals, solutions, subsolutions and their associated system elements will be referred to as a
All the Presidents' Bankers: The Hidden Alliances that Drive American Power

Who rules America? All the Presidents' Bankers is a groundbreaking narrative of how an elite group of men transformed the American economy and government, dictated foreign and domestic policy, and shaped world history. Culled from original presidential archival documents, All the Presidents' Bankers delivers an explosive account of the hundred-year interdependence between the White House and Wall Street that transcends a simple analysis of money driving politics--or greed driving bankers. Prins ushers us into the intimate world of exclusive clubs, vacation spots, and Ivy League universities that binds presidents and financiers. She unravels the multi-generational blood, intermarriage, and protege relationships that have confined national influence to a privileged cluster of people. These families and individuals recycle their power through elected office and private channels in Washington, DC. All the Presidents' Bankers sheds new light on pivotal historic events--such as why, after the Panic of 1907, America's dominant bankers convened to fashion the Federal Reserve System; how J. P. Morgan's ambitions motivated President Wilson during World War I; how Chase and National City Bank chairmen worked secretly with President Roosevelt to rescue capitalism during the Great Depression while J.P. Morgan Jr. invited Roosevelt's son yachting; and how American financiers collaborated with President Truman to construct the World Bank and IMF after World War II. Prins divulges how, through the Cold War and Vietnam era, presidents and bankers pushed America's superpower status and expansion abroad, while promoting broadly democratic values and social welfare at home. But from the 1970s, Wall Street's rush to secure Middle East oil profits altered the nature of political-financial alliances. Bankers' profit motive trumped heritage and allegiance to public service, while presidents lost control over the economy--as was dramatically evident in the financial crisis of 2008. This unprecedented history of American power illuminates how the same financiers retained their authoritative position through history, swaying presidents regardless of party affiliation. All the Presidents' Bankers explores the alarming global repercussions of a system lacking barriers between public office and private power. Prins leaves us with an ominous choice: either we break the alliances of the power elite, or they will break us.
Oral Administration of Recombinant Lactococcus lactis Expressing HSP65 and Tandemly Repeated P277 Reduces the Incidence of Type I Diabetes in Non-Obese Diabetic Mice

Diabetes mellitus type 1 (DM1) is an autoimmune disease that gradually destroys insulin-producing beta-cells. We have previously reported that mucosal administration of fusion protein of HSP65 with tandem repeats of P277 (HSP65-6P277) can reduce the onset of DM1 in non-obese diabetic (NOD) mice. To deliver large amounts of the fusion protein and to enhance long-term immune tolerance effects, in the present study, we investigated the efficacy of using orally administrated L. lactis expressing HSP65-6P277 to reduce the incidence of DM1 in NOD mice. L. lactis strain NZ9000 was engineered to express HSP65-6P277 either constitutively or by nisin induction. After immunization via gavage with the recombinant L. lactis strains to groups of 4-week old female NOD mice for 36 weeks, we observed that oral administration of recombinant L. Lactis resulted in the prevention of hyperglycemia, improved glucose tolerance and reduced insulitis. Immunologic analysis showed that treatment with recombinant L. lactis induced HSP65- and P277- specific T cell immuno-tolerance, as well as antigen-specific proliferation of splenocytes. The results revealed that the DM1-preventing function was in part caused by a reduction in the pro-inflammatory cytokine IFN-γ and an increase in the anti-inflammatory cytokine IL-10. Orally administered recombinant L. lactis delivering HSP65-6P277 may be an effective therapeutic approach in preventing DM1.
An Adaptive GA - PSO Approach with Gene Clustering to Infer S-system Models of Gene Regulatory Networks

Theconstructionofgeneregulatorynetworksfromexpressiondataisoneofthemostimportantissues in systems biology research. However, building such networks is a tedious task, especially when both the number of genes and the complexity of gene regulation increase. In this work, we adopt the S-system model to represent the gene network and establish a methodology to infer the model. Our work mainly includes an adaptive genetic algorithm-particle swarm optimization hybrid method to infer appropriate network parameters, and a gene clustering method to decompose a large network into several smaller networks for dimension reduction. To validate the proposed methods, different series of experiments have been conducted and the results show that the proposed methods can be used to infer S-system models of gene networks efficiently and successfully.
On the connection between two quasilinear elliptic problems with source terms of order 0 or 1

We establish a precise connection between two elliptic quasilinear problems with Dirichlet data in a bounded domain of $\mathbb{R}^{N}. $ The first one, of the form \[ -\Delta_{p}u=\beta(u)| \nabla u| ^{p}+\lambda f(x)+\alpha, \] involves a source gradient term with natural growth, where $\beta$ is nonnegative, $\lambda>0,f(x)\geqq0$, and $\alpha$ is a nonnegative measure. The second one, of the form \[ -\Delta_{p}v=\lambda f(x)(1+g(v))^{p-1}+\mu, \] presents a source term of order $0, $where $g$ is nondecreasing, and $\mu$ is a nonnegative measure. Here $\beta$ and $g$ can present an asymptote. The correlation gives new results of existence, nonexistence, regularity and multiplicity of the solutions for the two problems, without or with measures. New informations on the extremal solutions are given when $g$ is superlinear.
Spectrum of K ras mutations in Pakistani colorectal cancer patients

The incidence of colorectal cancer (CRC) is increasing daily worldwide. Although different aspects of CRC have been studied in other parts of the world, relatively little or almost no information is available in Pakistan about different aspects of this disease at the molecular level. The present study was aimed at determining the frequency and prevalence of K ras gene mutations in Pakistani CRC patients. Tissue and blood samples of 150 CRC patients (64% male and 36% female) were used for PCR amplification of K ras and detection of mutations by denaturing gradient gel electrophoresis, restriction fragment length polymorphism analysis, and nucleotide sequencing. The K ras mutation frequency was found to be 13%, and the most prevalent mutations were found at codons 12 and 13. A novel mutation was also found at codon 31. The dominant mutation observed was a G to A transition. Female patients were more susceptible to K ras mutations, and these mutations were predominant in patients with a nonmetastatic stage of CRC. No significant differences in the prevalence of K ras mutations were observed for patient age, gender, or tumor type. It can be inferred from this study that Pakistani CRC patients have a lower frequency of K ras mutations compared to those observed in other parts of the world, and that K ras mutations seemed to be significantly associated with female patients.
Systematic review of the application of the plan–do–study–act method to improve quality in healthcare

Background Plan–do–study–act (PDSA) cycles provide a structure for iterative testing of changes to improve quality of systems. The method is widely accepted in healthcare improvement; however there is little overarching evaluation of how the method is applied. This paper proposes a theoretical framework for assessing the quality of application of PDSA cycles and explores the consistency with which the method has been applied in peer-reviewed literature against this framework. Methods NHS Evidence and Cochrane databases were searched by three independent reviewers. Empirical studies were included that reported application of the PDSA method in healthcare. Application of PDSA cycles was assessed against key features of the method, including documentation characteristics, use of iterative cycles, prediction-based testing of change, initial small-scale testing and use of data over time. Results 73 of 409 individual articles identified met the inclusion criteria. Of the 73 articles, 47 documented PDSA cycles in sufficient detail for full analysis against the whole framework. Many of these studies reported application of the PDSA method that failed to accord with primary features of the method. Less than 20% (14/73) fully documented the application of a sequence of iterative cycles. Furthermore, a lack of adherence to the notion of small-scale change is apparent and only 15% (7/47) reported the use of quantitative data at monthly or more frequent data intervals to inform progression of cycles. Discussion To progress the development of the science of improvement, a greater understanding of the use of improvement methods, including PDSA, is essential to draw reliable conclusions about their effectiveness. This would be supported by the development of systematic and rigorous standards for the application and reporting of PDSAs.
NEMATOCIDAL EFFECTS OF PIPERAZINE AND THE EXTRACT OF ACACIA OXYPHYLLA STEM BARK ON THE POULTRY NEMATODE, ASCARIDIA GALLI

Summary Acacia oxyphylla Graham ex Bentham (Mimosaceae) is a leguminous plant widely used in the traditional medicines of north-east Indian tribes. Among the Mizo tribes, the stem bark is commonly used as fish stupefying and deworming agents. This present experiment was aimed at evaluating the nematocidal effect, if any, upon Ascaridia galli Schrank (Nematoda), the intestinal roundworm of domestic fowl, in comparison to that of piperazine. Different concentrations of the plant extract and piperazine (0.5, 1, 2, 5, 10 and 20 mg/mL) were prepared in 0.9% phosphate buffered saline with 1% dimethylsulfoxide. In vitro treatment of the nematodes indicated concentration-dependent efficacy of both piperazine and the plant extract in terms of mortality effect. Piperazine was significantly effective (P < 0.05) at all concentrations tested. However, the plant extract showed significant efficacy only at the concentrations of 5, 10, and 20 mg/mL. Photomicrographs of the female nematodes treated with 20 mg/mL of the plant indicated extensive structural alterations involving detachment of the cuticle, disintegration of the muscular layers, rupture of the ovaries and deformity on the egg membranes. The results show that A. oxyphylla is an effective nematocide, supporting the feasibility of its usage as traditional anthelmintic.
Child poverty in the UK since 1998-99: lessons from the past decade

As a result of the Child Poverty Act (2010), current and future governments are committed to reducing the rate of relative income child poverty in the UK to 10% by 2020-21. This paper looks in detail at the progress made towards this goal under the previous Labour administrations. Direct tax and benefit reforms are very important in explaining at least three things: the large overall reduction in child poverty since 1998-99; the striking slowdown in progress towards the child poverty targets between 2004-05 and 2007-08; and some of the variation in child poverty trends between different groups of children. However, some of the child poverty-reducing impact of those reforms acted simply to stop child poverty rising as real earnings grew over the period, which increases median income and thus the relative poverty line. The performance of parents in the labour market is important too: between regions, parental employment and child poverty trends are closely related; the overall reduction in child poverty since 1998-99 has been helped by higher lone parent employment rates; and the overall rise in child poverty since 2004-05 has been most concentrated on children of one-earner couples, whose real earnings have fallen.
Local Privacy, Data Processing Inequalities, and Statistical Minimax Rates

Working under a model of privacy in which data remains private even from the statistician, we study the tradeoff between privacy guarantees and the utility of the resulting statistical estimators. We prove bounds on information-theoretic quantities, including mutual information and Kullback-Leibler divergence, that depend on the privacy guarantees. When combined with standard minimax techniques, including the Le Cam, Fano, and Assouad methods, these inequalities allow for a precise characterization of statistical rates under local privacy constraints. We provide a treatment of several canonical families of problems: mean estimation, parameter estimation in fixed-design regression, multinomial probability estimation, and nonparametric density estimation. For all of these families, we provide lower and upper bounds that match up to constant factors, and exhibit new (optimal) privacy-preserving mechanisms and computationally efficient estimators that achieve the bounds.
Source Separation, ICA via Unsupervised Learning: Information-theoretic Approach and Conditions on Cross-cumulants

The problem of separation of independent source signals from their instantaneous mixtures, is addressed by using two diierent approaches: (1) information-theoretic approach; (2) higher-order cross-cumulants approach. Natural gradient 4] is known as eecient and fast convergent for on-line learning. First, we present further results on natural gradient-based source separation algorithms. Second, we discuss source separation criteria based on higher-order cross-cumulants. Blind source separation is a fundamental problem encountered in many applications such as array signal processing, sonar, digital communications, some biomedical applications. The goal of blind source separation is to recover the independent source signals from their linear mixtures without the knowledge of mixing matrix. For instance, the narrow-band signals received by antenna sensors in communication systems are often a linear transformation of statistically independent source signals, and it is desirable to restore these source signals without the knowledge of the linear transformation. The problem is formulated as follows. The received signals x(t) 2 IR m consist of instantaneous mixtures of independent source signals s(t) 2 IR n by a mixing matrix A 2 IR mn , i.e., x(t) = As(t): (1) In source separation as shown in Figure 1 , it is required to update a demixing networkW(t), i.e., y(t) = W(t)x(t); (2) such that the global system G(t) = W(t)A converges as t ! 1 to a matrix G = PP; (3) for some permutation matrix P and nonsingular diagonal matrix. Unknown Mixing Demixing PSfrag replacements s(t) x(t) y(t) A W(t) Figure 1. Schematic diagram for source separation via unsupervised learning Source separation is often called as ICA, which can be viewed as a nonlinear extension of principal component analysis (PCA) where only second-order statistics is considered. Neural computational approach to blind source separation was rst introduced by Jutten and Herault 18]. Introducing nonlinear functions in a linear feedback network, the network was trained in unsu-pervised manner to nd a linear transformation which forces higher-order correlations between network outputs to vanish zero. Later this was further developed by Cichocki et al 17] by employing self-connections for normalization. Bell and Sejnowski 6] presented a simple learning algorithm derived from information-theoretic approach, while past algorithms were based on heuristic investigation. Amari et al 1] introduced natural gradient and presented a algorithm with approximating a marginal entropy using Gram-Charlier
Learning and business value of information systems : The case of customs automation system implementation

Although major studies assert that user learning could be one mechanism driving the lagged business value from information system investments, little systematic empirical evidence of learning has been offered. In this study, we seek to address this gap in the literature by providing a systematic analysis to understand how user learning of inter-organizational information systems improves operational performance. We classify users into legacy and new workers based on their experience in the task before the implementation of the system, and argue that as users’ experience with the system increases, their efficiency will improve, and that the rate of increase should be higher for legacy workers. In addition, we hypothesize that major enhancements of the system could dampen users’ learning, and this dampening effect will be stronger for new workers. We test our hypotheses under the setting of a customs automation system implementation in Costa Rica. Using customs declaration data from 2006-2010, we find that customs agents, the major stakeholders of the system, exhibit significant learning as hypothesized. However, contrary to our hypothesis, new agents learn more quickly than legacy agents. In addition, some, but not all enhancements of the system to implement new regimes are associated with a slowdown of agents’ learning. We discuss our results, contributions and future extensions of this research.
Breast Microcalcifications: Diagnostic Outcomes According to Image-Guided Biopsy Method

Objective To evaluate the diagnostic outcomes of ultrasonography-guided core needle biopsy (US-CNB), US-guided vacuum-assisted biopsy (US-VAB), and stereotactic-guided vacuum-assisted biopsy (S-VAB) for diagnosing suspicious breast microcalcification. Materials and Methods We retrospectively reviewed 336 cases of suspicious breast microcalcification in patients who subsequently underwent image-guided biopsy. US-CNB was performed for US-visible microcalcifications associated with a mass (n = 28), US-VAB for US-visible microcalcifications without an associated mass (n = 59), and S-VAB for mammogram-only visible lesions (n = 249). Mammographic findings, biopsy failure rate, false-negative rate, and underestimation rate were analyzed. Histological diagnoses and the Breast Imaging Reporting and Data System (BI-RADS) categories were reported. Results Biopsy failure rates for US-CNB, US-VAB, and S-VAB were 7.1% (2/28), 0% (0/59), and 2.8% (7/249), respectively. Three false-negative cases were detected for US-CNB and two for S-VAB. The rates of biopsy-diagnosed ductal carcinoma in situ that were upgraded to invasive cancer at surgery were 41.7% (5/12), 12.9% (4/31), and 8.6% (3/35) for US-CNB, US-VAB, and S-VAB, respectively. Sonographically visible lesions were more likely to be malignant (66.2% [51/77] vs. 23.2% [46/198]; p < 0.001) or of higher BI-RADS category (61.0% [47/77] vs. 22.2% [44/198]; p < 0.001) than sonographically invisible lesions. Conclusion Ultrasonography-guided vacuum-assisted biopsy is more accurate than US-CNB when suspicious microcalcifications are detected on US. Calcifications with malignant pathology are significantly more visible on US than benign lesions.
Structural Distortions and Decentralized Fiscal Policies in EMU

The combination of discretionary monetary policy, labor-market distortions, and nominal wage rigidity yields excessive inflation as monetary policy tries to exploit nominal wage contracts to address labor-market distortions. An inflation target reduces inflation, but creates a conflict between monetary policy and discretionary fiscal policy if fiscal policy is set at a higher frequency than nominal wages are. Preventing the associated excessive accumulation of public debt calls for debt ceilings. If countries differ substantially in terms of structural distortions, uniform debt ceilings must be complemented by country-specific debt targets in order to prevent decentralized fiscal authorities from employing debt policy strategically.