Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Quadratic Programming with Mixed-Integer Uncertainty

We study robust convex quadratic programs where the uncertain problem parameters can contain both continuous and integer components. Under the natural boundedness assumption on the uncertainty set, we show that the generic problems are amenable to exact copositive programming reformulations of polynomial size. These convex optimization problems are NP-hard but admit a conservative semidefinite programming (SDP) approximation that can be solved efficiently. We prove that the popular approximate S-lemma method --- which is valid only in the case of continuous uncertainty --- is weaker than our approximation. We also show that all results can be extended to the two-stage robust quadratic optimization setting if the problem has complete recourse. We assess the effectiveness of our proposed SDP reformulations and demonstrate their superiority over the state-of-the-art solution schemes on instances of least squares, project management, and multi-item newsvendor problems.
Core competence, cmpetitive advantage and market analysis : Forging the links

Business people are receiving conflicting advice about the routes to competitive advantage. One set of theories says the key to advantage lies in market positioning: looking outside the firm. The "resource based" view exhorts business people to focus on their firms' existing core competences and assets and how these might be expanded: looking inside the company. In this paper we focus on linking the two. We begin by tracing Porter's cost and differentiation drivers back to the underlying assets on which they draw. Core competences are then viewed as catalysts which reduce the time and cost required for a business to expand its asset base in ways which allow it to deliver a more competitive product. The role of core competences is inherently dynamic: they help companies build new assets which can enhance their competitive advantage, enable them to meet the needs of changing markets and diversify into new ones. It is then critical to know which types of assets, and hence which core competences, will be most advantageous to a firm in a particular market environment. We show empirically that part of the answer is to be found by analysing differences in the value of customer relationships, channel and process experience assets across different markets. By exarnining these differences, strategists can gain a better understanding of where corporate diversifiers can use their core competences to gain an advantage in competing for new business opportunities against independent start-ups; and where new ventures can succeed despite lack of access to corporate competences. "The essential is invisible to the eye" A. de Saint-Exupery, The Little Prince
Task Specificity and the Gender Wage Gap Theoretical Considerations and Empirical Analysis of the Spanish Survey on Wage Structure

Standard research on the wage gap tends to take, often implicitly, an individual human capital approach. As a result, the specificity of the tasks people are employed to perform is rarely incorporated in the analyses, and this is bound to yield mis-specified wage equations. Incorporating task-specificity factors in the wage models can advance our understanding of the mechanisms behind wage differences by sex. Decomposing the task-specificity model poses, however, some methodological problems. These problems are addressed and solutions are proposed. The model is then tested using individual data drawn from the Spanish Survey on Wage Structure. The empirical analysis is performed using a condensed version of Goldthorpe's class schema on the assumption that such schema captures crucial differences in task specificity. The paper ends with a discussion of the advantages of the task-specificity model over both standard human capital and cultural-feminist explanations of the gender wage gap, and calls for using direct measures of task specificity in future research.
Stability Bound of Ruin Probability in a Reduced Two-Dimensional Risk Model

In this work, we introduce the qualitative and quantitative concept of the strong stability method in the risk process modeling two lines of business of the same insurance company or an insurance and re-insurance companies that divide between them both claims and premiums with a certain proportion. The approach proposed is based on the identification of the ruin probability associate to the model considered, with a stationary distribution of a Markov random process called a reversed process. Our objective, after clarifying the condition and the perturbation domain of parameters, is to obtain the stability inequality of the ruin probability which is applied to estimate the approximation error of a model with disturbance parameters by the considered model. In the stability bound obtained, all constants are explicitly written. Keywords—Markov chain, risk models, ruin probabilities, strong stability analysis.
Association of rs7903146 polymorphism in the TCF7L2 gene with diabetic nephropathy and decreased estimated GFR in an Arab population in southwest Iran

Background: Transcription factor 7-like 2 (TCF7L2) acts as a downstream effector in the Wnt signaling pathway. It plays important roles in the proliferation and differentiation of islet betacell, insulin secretion and kidney development. Objectives: This study aimed to demonstrate whether rs7903146 variant is associated with diabetic nephropathy (DN) and measures of kidney function in a diabetic and healthy Arab population in southwest of Iran. Patients and Methods: This study is comprised of 132 diabetic subjects (T2DM) and 66 healthy participants. The diabetic subgroups were composed of patients with DN (n=56) and early onset of diabetes (n=71). The rs7903146 polymorphism was genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method in all the participants. Blood glucose, HbA1c, blood urea nitrogen (BUN), creatinine and urinary albumin were evaluated by a biochemistry analyzer and enzyme-linked immunosorbent assay (ELISA) was employed for cystatin C measurement. Results: The frequency of genotypes was significantly different between all the diabetic cases and control subjects (P<0.05). The TT variant odds ratio (OR) versus CT/CC genotypes for diabetes was 2.47 (95% CI 1.11-5.48). An association was observed between TT homozygous and DN (OR for TT 2.78, 1.13-6.84). Early onset diabetic patients showed stronger association (OR: 4.64, 1.64-13.14, P=0.003). The TT genotype was also found to be a risk variant for decreased estimated glomerular filtration rate (eGFR)(Cys-Cr) below 60 mL/min/1.73 m2 (OR: 3.36, 1.4-8.1, P=0.005). Conclusions: The results confirmed that the TCF7L2 gene rs7903146 variants are significantly associated with T2DM in Arab population of Iran. The TT genotype of this SNP is also predisposed to the risk of developing DN especially in subjects with early onset diabetes. Patients with TT genotype were also at risk of decreased GFR.
Almost Everything We Need to Better Serve Children of the Opioid Crisis We Learned in the 80s and 90s

Opioid use disorder impedes dependent parents' abilities to care for their children. In turn, children may languish in unpredictability and persistent chaos. Societal responses to these children are often guided by a belief that unless the drug dependent parent receives treatment, there is little help for the child. While a preponderance of the drug dependence research is adult-centric, a significant body of research demonstrates the importance of not only addressing the immediate well being of the children of drug dependent caregivers but preventing the continuing cycle of drug dependence. The present commentary demonstrates through a brief review of the US history of drug dependence crises and research from the 1980s and 1990s, a range of “tried and true” family, school, and community interventions centered on children. We already know that these children are at high risk of maladjustment and early onset of drug dependence; early intervention is critical; multiple risk factors are likely to occur simultaneously; comprehensive strategies are optimal; and multiple risk-focused strategies are most protective. Where we need now to turn our efforts is on how to effectively implement and disseminate best practices, many of which we learned in the 1980s and 1990s. The greatest opportunity in both changing the nature of the opioid epidemic at scale and influencing rapid translation of existing research findings into policy and practice is not in asking what to do, but in asking how to do the right things well, and quickly.
Performance Based Evaluation of New Software Testing Using Artificial Neural Network

Today, testing is the most challenging and dominating activity used by industry, therefore, improvement in its effectiveness, both with respect to the time and resources, is taken as a major factor by many researchers. Software testing forms an integral part of the software development life cycle. Since the objective of testing is to ensure the conformity of an application to its specification, a test "Automated Secure Agent" is needed to determine whether a given test case exposes a fault or not. Using an automated Agent to support the activities of human testers can reduce the actual cost of the testing process and the related maintenance costs. In this paper, we present a new concept of using an artificial neural network as an automated agent for a tested software system. A neural network is trained by the back propagation algorithm on a set of test cases applied to the original version of the system. The network training is based on the "black-box" approach, since only inputs and outputs of the system are presented to the algorithm. The trained network can be used as an artificial Agent for evaluating the correctness of the output produced by new and possibly faulty versions of the software. We present experimental results of using a two-layer neural network to detect faults within mutated code of a small credit approval application. The results appear to be promising for a wide range of injected faults.
A Methylcellulose Hydrogel as Support for 3D Plotting of Complex Shaped Calcium Phosphate Scaffolds

3D plotting is an additive manufacturing technology enabling biofabrication, thus the integration of cells or biologically sensitive proteins or growth factors into the manufacturing process. However, most (bio-)inks developed for 3D plotting were not shown to be processed into clinically relevant geometries comprising critical overhangs and cavities, which would collapse without a sufficient support material. Herein, we have developed a support hydrogel ink based on methylcellulose (mc), which is able to act as support as long as the co-plotted main structure is not stable. Therefore, 6 w/v %, 8 w/v % and 10 w/v % mc were allowed to swell in water, resulting in viscous inks, which were characterized for their rheological and extrusion properties. The successful usage of 10 w/v % mc as support ink was proven by multichannel plotting of the support together with a plottable calcium phosphate cement (CPC) acting as main structure. CPC scaffolds displaying critical overhangs or a large central cavity could be plotted accurately with the newly developed mc support ink. The dissolution properties of mc allowed complete removal of the gel without residuals, once CPC setting was finished. Finally, we fabricated a scaphoid bone model by computed tomography data acquisition and co-extrusion of CPC and the mc support hydrogel.
A High Resolution Study of the Effect of Morphology On the Mass Spectra of Single PSL Particles with Na-containing Layers and Nodules

The interpretation and quantification of measurements of particle composition by laser ablation based single particle mass spectrometry is complex. Among the most difficult systems to quantify are internally mixed particles containing alkali metals and organics. The alkali atoms in such particles tend to suppress the formation of other ions sometimes to below the detection limit. Here we present a study of the behavior of single particle mass spectral peak intensities as a function of the amount of the sodium containing compounds deposited on the surface of 240 nm polystyrene latex (PSL) spheres. We generate three morphologically distinct and well defined coating types: uniform layers, cubic nodules and rounded nodules, and measure the individual particle mass spectra as a function of the vacuum aerodynamic diameter with nanometer resolution. The data show that the probability of detecting the PSL spheres depends on the amount of the alkali metal on the PSL sphere surface, its morphological distribution and the ablation laser power. The data suggest that PSL spheres with localized Na-containing nodules are easier to detect than those which are completely encapsulated. We show, for example, that at low laser power, PSL particles that are completely encapsulated with Na-containing compounds, whose weight fraction is close to 50%, cannot be detected, while 35% of PSL spheres with same amount of coating can be detected if coating is localized in nodules on a fraction of the particle surface.
CENTRAL BANK AND FINANCIAL SERVICES AUTHORITY OF IRELAND Research Technical Paper New Evidence on Balanced Growth, Stochastic Trends, and Economic Fluctuations

The one-sector Solow-Ramsey growth model informs how most modern researchers characterize macroeconomic trends and cycles, and evidence supporting the model’s balanced growth predictions is often cited. This paper shows, however, that the inclusion of recent data leads to the balanced growth predictions being rejected. An alternative balanced growth hypothesis|that the ratio of nominal consumption to nominal investment is stationary|is put forward, and new measures of the stochastic trends and cycles in aggregate US data are derived based on this hypothesis. The contrasting behavior of real and nominal ratios is consistent with a two-sector model of economic growth, with separate production technologies for consumption and investment and two stochastic trends underlying the long-run behavior of all macroeconomic series. Empirical estimates of these stochastic trends are presented based on a structural VAR and the role played in the business cycle by shocks to these trends is discussed.
ViLab: A Virtual Laboratory for Collaborative Research on Wind Power Forecasting

The consortium of the European Coordination Action ‘Prediction of Waves, Wakes and Offshore Wind’ (POW'WOW) has established a Virtual Laboratory (ViLab) for the development and operational use of wind power prediction systems. The objectives are to stimulate research in this field, to tighten the collaboration between forecasters and forecast users, and to follow and communicate the state of the art in short term prediction of wind generation. The present note clarifies the benefits for the participants to the ViLab. Also, it describes the methodology employed and some practical issues related to data and confidentiality.
Instrumental mediations and students’ identities

espanolEste articulo teorico considera la relacion entre el uso de herramientas digitales en la ensenanza y aprendizaje de las matematicas y el desarrollo de las identidades de los estudiantes como escritores matematicos en la ensenanza secundaria superior. El marco teorico es el enfoque instrumental en educacion matematica, que estudia como los estudiantes se apropian de los artefactos digitales como herramientas. Argumentamos que el foco en las mediaciones epistemicas y pragmaticas, dominantes durante mucho tiempo en este enfoque, se pueden incrementar con un foco en el trabajo de identidad de los alumnos. El interes por el trabajo de identidad de los alumnos en relacion con el uso de herramientas digitales en matematicas crecio a partir de un estudio de caso etnografico longitudinal con estudiantes de matematicas de la secundaria superior danesa. Utilizando datos de este estudio, presentamos ejemplos empiricos de una perspectiva de identidad sobre el uso de herramientas digitales en educacion matematica y discutimos posibles maneras de incorporar la "identidad" y el "trabajo identitario" en el enfoque instrumental. EnglishThis theoretical article considers the relation between the use of digital tools in the teaching and learning of mathematics and the development of students’ identities as mathematical writers, within their upper secondary school education. The theoretical outset is the instrumental approach in mathematics education, which studies how students appropriate digital artifacts as tools. We argue that the focus on epistemic and pragmatic mediations, which has long been prevalent within this approach, can benefit from being augmented with a focus on the students’ identity work. The interest for students’ identity work in relation to their use of digital tools in mathematics grew out of a longitudinal ethnographic case study of Danish upper secondary students’ work with mathematics. Using data excerpts from this study we provide empirical examples of an identity perspective on the use of digital tools in mathematics education and discuss possible ways to incorporate “identity" and "identity work" in the instrumental approach. francaisCet article s’interesse a la relation entre l’utilisation des outils numeriques dans l’enseignement et l’apprentissage et le developpement de l’identite des eleves en tant qu’auteurs en mathematiques, au lycee. L’approche instrumentale nous permet d’etudier comment les eleves s’approprient les artefacts numeriques en tant qu’outils. Nous soutenons que l’accent porte sur les mediations epistemiques et pragmatiques, qui prevaut dans ce type d’approche theorique, peut etre enrichi par un focus sur le travail identitaire des eleves. Cet aspect est ne d’une etude de cas ethnographique longitudinale du travail d’etudiants danois du lycee en mathematiques. Nous presentons des extraits de cette etude portant sur la perspective identitaire sur l’utilisation des outils numeriques et discutons des possiblites d’integration de « l’identite » et du « travail identitaire » dans l’approche instrumentale.
Norms in Bargaining : Evidence from Government Formation

Theories of multilateral bargaining and coalition formation applied to legislatures predict that parties’ seat shares determine their bargaining power. We present findings that are difficult to reconcile with this prediction, but consistent with a norm prescribing that “the most voted party should form the government. ” We first present case studies from several countries and regression discontinuity design-based evidence from 28 national European parliaments. We then focus on 2,898 Spanish municipal elections in which two parties tie in the number of seats. We find that the party with slightly more general election votes is substantially more likely to appoint the mayor. Since tied parties should (on average) have equal bargaining power, this identifies the effect of the norm. This effect is comparable to that of obtaining an additional seat. This norm binds behavior even when the second and third most voted parties can form a winning coalition that prefers the most voted not to appoint the mayor. A model where elections both aggregate information and discipline incumbents can rationalize our results and yields additional predictions we take to the data, such as voters punishing second most voted parties that appoint mayors and municipalities following the norm having less government corruption. We thank Albert Falcó-Gimeno, Olle Folke, Nicola Gennaioli, M. Daniele Paserman, Rohini Pande, Francesco Trebbi, Leeat Yariv, three anonymous referees, and seminar participants at Bank of Spain, Brown, Caltech, CEMFI, Chicago Harris, Columbia, Cornell, Cowles-Yale Political Economy Conference, EEA-ESEM Conference, HBS, IDB, IEB Political Economy Workshop, Kellogg, Princeton, Spanish Economic Association Symposium, Stanford GSB, Wharton, and UBC for helpful comments. We are grateful to Albert Solé-Ollé and Pilar Sorribas-Navarro for sharing the corruption data. Vishan Nigam and Susannah Scanlan provided excellent research assistance.
G RAVITY : A Mathematical Modeling Language for Optimization and Machine Learning

GRAVITY is an open source, scalable, memory efficient modeling language for solving mathematical models in Optimization and Machine Learning. GRAVITY exploits structure to reduce function evaluation time including Jacobian and Hessian computation. GRAVITY is implemented in C++ with a flexible interface allowing the user to specify the numerical accuracy of variables and parameters. It is also designed to offer efficient iterative model solving, convexity detection, multithreading of subproblems, and lazy constraint generation. When compared to state-of-the-art modeling languages such as JUMP, GRAVITY is 5 times faster in terms of function evaluation and up to 60 times more memory efficient. GRAVITY enables researchers and practitioners to access state-of-the-art optimization solvers with a user-friendly interface for writing general mixed-integer nonlinear models.
Development and characterization of electrically conductive polyaniline coated fabrics

Electrically conductive cotton, polyester and nylon fabrics have been prepared from conductive polyaniline (PANI) polymer by in situ chemical oxidative polymerization of aniline using ammonium persulphate as the oxidant by a process of diffusion polymerization in a mixed bath. These fabrics are then characterized by ATR-FTIR, WAXD, SEM and DSC. The tensile strength, stiffness and electrical and electromagnetic measurements of the fabric samples are also studied. The structural studies show that the crystalline region of cotton, polyester and nylon is not affected by the polyaniline and the interaction of polyaniline with the fabrics. The SEM studies reveal a very uniform deposition of polyaniline on the fabrics. The thermal studies show that the PANI-treated fabrics have better thermal stability. The intact textile characteristics of the polyester and nylon fabrics coated with PANI are found to be protected, whereas the characteristics of the cotton fabric coated with PANI become inferior. The conductivity studies show that the treated fabrics have good electrical conductivity. The electromagnetic shielding tests show that the cotton, polyester and nylon fabrics have the electromagnetic interference values of -1.62, -2.78 and -1.5 dB respectively in the frequency range 8-12 GHz.
A Research Paper on the Performance Analysis of a Self-Mode Locking High Power Linearly Polarised Fiber Laser

In this research a design for high power linearly polarized all-fiber linear cavity lasers with self-mode-locking is presented, and a new theoretical model based on a Nonlinear Schrodinger Equation (NLSE) is developed and implemented on the MATLAB platform. For the design of cavity, Polarization Maintaining (PM) fibers for both the gain medium and the Fiber Bragg Gratings (FBGs) is implemented. The FBG pairs are used to select the lasing wavelength and polarization. The fiber lasers incorporate specially designed FBGs to achieve an extinction ratio larger than 23 dB. The proposed configuration is based on Non-Linear Polarization (NPR) using PM Yb-doped active fiber and two matching FBGs to form the laser cavity. The combination of nonlinearity, gain, and birefringence in the cavity made the laser generate mode-locked pulses in the picosecond range and with high average output power. Experimental data and numerical simulations of the self-mode-locking fiber laser are presented. Main parameters affecting mode-locked pulses and its envelope are identified. The model proposed here explains the self-mode-locking mechanism and the source of the pulse envelope. In this model, it is proven that self-phase modulation (SPM) plays an essential role in pulse formation and shaping.