Miracle-dz/UniFAR-FTUs huggingface dataset:
The efficient set GA for stock portfolios

The genetic algorithm (GA) for the efficient set portfolio problem based on the Markowitz model, introduced by Shoaf and Foster (1996), offers significant benefits over the quadratic programming approach. These benefits include simultaneous optimization of risk and return. The efficient set GA uses an indirect representation style in order to avoid infeasible solutions and penalty functions. The success of this approach had raised questions about the scalability of this GA. New empirical results confirm that the efficient set GA scales well with time complexity O(n log n) for portfolios containing up to n=100 stocks. Additional experiments also show that a deme implementation extends the period of active solution improvement for this GA.
On Factorization of the Nonlinear Drift Term for SDRE Approach

Abstract This study presents necessary and sufficient conditions for the existence of a constant matrix A that satisfies A x = f , ( A, B ) is stabilizable and ( A, C ) is observable (resp., detectable), where x and f are two constant vectors with x ≠ 0 , while B and C are two constant matrices with approximate dimension. The conditions presented are very easy to check and a set of such feasible matrices A are also provided explicitly when the existence conditions are satisfied. In practical applications, this study may cooperate with the state-dependent Riccati equation (SDRE) implementation at those states where the SDRE scheme fails to operate, yet the presented existence conditions hold there.
Syrian refugees in Turkey: exploring the role of I/NGOs in refugee crisis

Abstract This article analyses the role that nongovernmental organisations (NGOs) and civil society organisations play in managing Syrian refugees’ basic needs and access to public services. This research is based on a qualitative approach. We collected information on the role of the NGOs through interviews (from 42 respondents, with NGOs and civil society organisations, selected on a snowball basis) in Turkey. We found that the NGOs play an important role in substantiating the government’s efforts in providing various kinds of basic services to the refugees. However, these NGOs suffer from insufficient funds and uncertain funding commitments. On top of this, there has been a lack of cooperation between the NGOs. This study touches upon the importance of NGOs in terms of structural and practical difficulties. Cooperation and collaboration among the NGOs have appeared as important issues in dealing with the refugee crisis in Turkey. This research has crucial policy implications for the NGOs and the governments of the destination and origin countries.
Surface of CuO Nanoparticles Modified by p-Benzoquinone for N2-Selective Membrane

In this study, CuO nanoparticles and p-benzoquinone (p-BQ) were added to a polyvinylpyrrolidone (PVP) matrix to increase N2/CO2 selectivity. The added p-BQ allowed CuO to be distributed in a uniform size in the PVP/CuO composite membrane and the matrix to be flexible by forming the interaction with PVP. The surface modification of CuO by p-BQ and the well-dispersed size affected the increase in the separation performance. The PVP/CuO/p-BQ composite membranes showed an N2/CO2 selectivity of about 23.1 with N2 permeance of about 13.3 GPU, while the separation performance of PVP was not observed. The enhanced separation performance is attributable to the surface of CuO nanoparticles modified by p-BQ inducing CO2 molecules to be relatively slowly transported by the adsorption properties in the polymer matrix. The chemical properties and coordinative interaction for PVP/CuO/p-BQ composite membrane were measured by FT-IR spectroscopy, thermogravimetric analysis, UV–vis, scanning electron microscopy, X-ray photoelectron spectroscopy, and transmission electron microscopy.
Data-Driven Iterative Optimal Control for Switched Dynamical Systems

This article presents a data-driven algorithm to compute optimal control inputs for input-constrained nonlinear optimal control problems with switched dynamics. We consider multi-stage optimal control problems where the control inputs and the switching instants are both unknown. Our key contribution is the new iterative online optimal control algorithm which mitigates sub-optimal control caused by model bias in the challenging class of under-actuated and intrinsically unstable switched dynamical systems. This is achieved by estimating the cost and computing the control inputs along measured trajectories of the controlled system instead of doing the same procedure along error-prone trajectories predicted by an inexact model. The algorithm is evaluated using an under-actuated and intrinsically unstable hopping robot in a simulation environment. The algorithm enables real-time data-driven optimal control using inaccurate models.
Spicebush Swallowtail Papilio (Pterourus) troilus Linnaeus 1758 (Insecta: Lepidoptera: Papilionidae: Papilioninae)

This EDIS publication is an alternate version of a page published first on the Featured Creatures website. The Featured Creatures collection provides in-depth profiles of insects, nematodes, arachnids and other organisms relevant to Florida. These profiles are intended for the use of interested laypersons with some knowledge of biology as well as academic audiences. This 11-page fact sheet that discusses the spicebush swallowtail butterfly was written by Donald W. Hall and Jerry F. Butler, and published by the UF Entomology and Nematology Department, November 2015. EENY636/IN1107: Spicebush Swallowtail Papilio (Pterourus) troilus Linnaeus 1758 (Insecta: Lepidoptera: Papilionidae: Papilioninae) (ufl.edu)
Are California venture capitalists the best venture capitalists?

Abstract We test if California VCs significantly outperform VCs from other US states. We additionally test in which instances California VCs outperform the other VC concentrated states of Massachusetts and New York. We find that VCs from California, Massachusetts, and New York have significantly greater probabilities of successfully exiting their investments than VCs from other states. Additionally, we show that California VCs are even more adept than VCs from Massachusetts and New York at 1. Early-stage investments, 2. Helping their entrepreneurial firms receive future rounds of financing, and 3. Helping their backed entrepreneurial firms receive higher IPO valuations and achieve superior post-IPO accounting ratios. Additional results suggest that VCs from California, Massachusetts, and New York are not only adept at selecting firms in which they invest in and continue to invest in, but they also enhance the value of the firms they select by means of monitoring their investments.
Freire’s Dialogic Process as a Means of Facilitating the Teaching of Controversial Public Policy Issue

Educators have long advocated for the pedagogical and civic importance of engaging students in discussions regarding controversial issues. Unfortunately, due to today’s polarized political atmosphere, many teachers hesitate to introduce issues that might be potentially contentious for fear of repercussions. The Brazilian pedagogue Paulo Freire’s notion of the dialogic process offers educators a means of pursuing this critical work. In his classic work Pedagogy of the Oppressed, Freire described five dispositions that are critical to effective dialogue: humility, hope, faith, love and critical thinking. This article details the findings from a qualitative study of a group of three pre-service teachers that used the Freirean dialogic process to teach about the thorny issue of police reform during their student teaching experiences in urban public school settings. The results of this study, which employed a narrative analysis approach, point to a number of valuable insights resulting from this innovative instructional practice.
High Field Neutron Diffraction Studies on Metamagnetic Transition of Multiferroic BiFeO3

Institute for Materials Research, Tohoku University, Sendai 980-8577, Japan Neutron Science Division, Korea Atomic Energy Research Institute, Daejeon 305-353, Korea Department of Physics, Ewha Womans University, Seoul 120-750, Korea Rutgers Center for Emergent Materials and Department of Physics and Astronomy, Rutgers University, Piscataway, NJ 08854, U.S.A. Center for Strongly Correlated Materials Research and FPRD Department of Physics and Astronomy, Seoul National University, Seoul 151-747, Korea
A comparative study of the Jigsaw and Chalk-and-Talk Methods on grade 12 learners’ achievements in reaction rates in South Africa

The study compared the Jigsaw Method and the Chalk-and-Talk methods of learners’ achievements in grade 12 reaction rates. A quasi-experimental design was used, with two classes of 44 learners, one class of 21 as the experimental group and another with 23 as the control group. Data were collected using Achievements Test for pre-test and post-tests and analysed using percentages, Means, Standard Deviations, t-tests and Analysis of Covariance. The post-test results from EG using Jigsaw Method and the control group using the Chalk-and-Talk show significant differences. Analysis of Covariance shows significant effects between experimental and control groups post-test using pre-test covariate. The experimental group outperformed the control group, and the former had no significant differences in gender achievements, suggesting Jigsaw Method favours both genders. The experimental group learners had minimal misconceptions compared to the control group. Thus, the Jigsaw Method enabled experimental group learners to overcome difficulties and misconceptions. Keywords: : Cooperative learning, conceptual understanding, learners’ achievements
Financial Literacy of Working Women (Case Study in Malaysia)

Financial literacy is the convergence of financial, credit and debt management and the knowledge that is necessary to make financially responsible decisions. This paper is conducted to assess the correlation between financial literacy and its component (financial education, financial attitude, financial behavior and financial knowledge). Data processing of this study using a pearson correlation with the number of samples 35 respondents. The data are quantitatively analyzed through Statistical Packages for Social Science (SPSS). According to the findings, financial literacy does not have a significant relationship with financial knowledge, however financial education, financial attitude and financial behavior together have a significant relationship with financial literacy. For appropriate utilization of funds, working women need to be financially literate.
Design of soft and hard active-passive composite beams

Abstract The combination of different materials is prevalent in nature and technology. Particularly, smart (active) materials must be combined with other materials to harness their full potential. Three combination cases are explored: Case I (constrained), Case II (combined) and Case III (free) behavior. Based on analytical theories and Finite Element simulations with the Stimulus-Expansion-Model, design approaches for active-passive composites are proposed. These include, choice of Case for an application, bottom-up design of layers with matching stiffness and replacement of materials. The current work substantiates that the stiffnesses are crucial for combining materials, e.g., in smart structures, additive manufacturing and bioelectronic interfaces.
Electromagnetic study of magneto-optic surface plasmon resonance effects for biosensing applications

Biosensors are gaining interest in scientific research because of their wide variety of applications. Surface plasmon resonance (SPR) based biosensors are the most common platform for label-free biomolecular interaction analysis. In this paper, we present simulations of a magneto-optic SPR (MOSPR) biosensor by using a three-dimensional finite integration technique (FIT). In the past SPR based biosensors have been modeled with the FIT, here, we extend this technique by incorporating the anisotropic material Co for a MOSPR sensor. The MOSPR biosensor uses the properties of surface plasmon polaritons (SPPs) and transverse magneto-optic Kerr effect (TMOKE) simultaneously in the presence of an external magnetic field. We study the magneto-optical activity on the Au/Co/Au trilayer structures with opposite magnetization. The magneto-optic activity strongly depends on the metallic layer thicknesses and the refractive index of the dielectric. The simulation exhibits the electric and magnetic field distributions along the trilayer system. Based on the FIT simulations, we investigate the sensitivity of a MOSPR biosensor by changing the refractive index of the adjacent dielectric material from 1.33 to 1.40. Furthermore, we compare the performance of a MOSPR sensor to a SPR one. Finally experimental and simulation results of a MOSPR sensor in Kretschmann configuration are compared, verifying the used approach.
Semiparametric Bayesian Inference in Autoregressive Panel Data Models

This paper develops semiparametric Bayesian methods for inference in dynamic linear panel data models, and applies them to longitudinal data on labor earnings from the Panel Study of Income Dynamics. We focus on characterizing not only parameters related to conditional means and variances, but the entire joint distribution of earnings. Full distributional inference in semiparametric panel data models must solve a nonparametric deconvolution problem arising from the existence of unobserved additive individual-specific terms. A computational Bayesian approach based on variable augmentation can deal with such latent-variable models effectively, and can allow considerable flexibility in distributional assumptions. We use relatively simple, low-order linear models with individual heterogeneity, but estimate the distribution of the disturbances without requiring that it belong to a restrictive parametric class, such as the class of normal distributions. A prior distribution on the space of probability distributions is used to impose smoothness on an otherwise general specification for the disturbance terms. This nonparametric prior is constructed using a countable mixture of normals representation, where the mixing distribution is given a Dirichlet process prior.
Evaluation of a Southern Mediterranean forage farming system.

The research carried out in the pastures of the Nebrodi Mountains (Sicily, Southern Italy) shows high variability of climate and vegetation in relation to altitude. Agricultural improvement practices and grazing management are occasional. There are also areas of high yield as well as highly degraded areas due to soil erosion and over-grazing. Stabilizing seasonal forage yield even in difficult years is one of the most significant problems related to pasturage in this area. So a biennial research project (2006 and 2008) was carried out in a representative farm to evaluate daily growth cycle, seasonal yield, fodder value and forage quality of a natural pasture, an improved pasture, an under tree pasture and a meadow, to estimate forage system efficiency. The results show that yield was related to the amount of spring rainfall and phosphate fertilizers; the meadow did not modify forage quality, quantity or seasonal availability.
Sampling from Gauss Rules

Approximating multidimensional integrals via product quadrature rules becomes increasingly intractable as the dimension increases. Hammersley [Ann. New York Acad. Sci., 86 (1960), pp. 844–874] suggested sampling from product quadrature rules and Tsuda [Numer. Math., 20 (1973), pp. 377–391] considered this method using Fejer rules. In this paper we consider this approach using Gauss rules. Results are obtained concerning the variance of this form of sampling relative to sampling from the continuous distributions represented by the weight functions. It is shown that this approach can lead to variance reduction and its use is discussed in several examples.
The Stochastic Robustness of Nominal and Stochastic Model Predictive Control

In this work, we establish and compare the stochastic and deterministic robustness properties achieved by nominal model predictive control (MPC), stochastic MPC (SMPC), and a proposed constraint-tightened MPC (CMPC) formulation, which represents an idealized version of tube-based MPC. We consider three definitions of robustness for nonlinear systems and bounded disturbances: robustly asymptotically stable (RAS), robustly asymptotically stable in expectation (RASiE), and RASiE with respect to the stage cost <inline-formula><tex-math notation="LaTeX">$\ell (\cdot)$</tex-math></inline-formula> used in these MPC formulations (<inline-formula><tex-math notation="LaTeX">$\ell$</tex-math></inline-formula>-RASiE). Via input-to-state stability (ISS) and stochastic ISS (SISS) Lyapunov functions, we establish that MPC, subject to sufficiently small disturbances, and CMPC ensure all three definitions of robustness without a stochastic objective function. While SMPC is RASiE and <inline-formula><tex-math notation="LaTeX">$\ell$</tex-math></inline-formula>-RASiE, SMPC is not neccesarily RAS for nonlinear systems. Through a few simple examples, we illustrate the implications of these results and demonstrate that, depending on the definition of robustness considered, SMPC is not necessarily more robust than nominal MPC even if the disturbance model is exact.
Iran’s Nuclear Policy: A Cognitive Study on Defiance and Compliance

This paper argues that the divides in Iran’s nuclear behavior between the three periods of 2005-2012, 2012-2016 and 2016-2021 are reflections of the varying modes of Iran’s cognizing the value of the nuclear program versus its costs. The predominant belief in the first period that Iran is in the gain domain made it defiant and risk-averse leading to Iran’s avoidance of entering a pact with the untrusted US. The change of belief that Iran is moved to the domain of losses as a result of sanctions drove Tehran more risk-taker and compliant in the second period and a part of the third period, resulting in conclusion of the nuclear deal and the efforts to maintain it. While suffering in the domain of losses, the belief that another deal with the US is a predetermined failure explains the rest of the third period’s Iranian fluctuation between compliance and defiance.
Scanning secondary-electron microscopy on ferroelectric domains and domain walls in YMnO3

Ferroelectric domain structures in YMnO3 single crystals on the hexagonal polar surface have been investigated by scanning electron microscopy in secondary electron emission mode. The experimental results demonstrate that the domain, as well as domain walls, can be clearly revealed under the operation voltages ranging from 0.6 to 3 kV. Evolution of domain contrasts arising from electron-beam irradiation can be mainly explained by the pyroelectric effect and related charging process. A rich variety of microstructure features of ferroelectric domains can be clearly revealed in YMnO3 by this high-resolution technique.
Narrow Weld Joint Recognition Method Based on Laser Profile Sensor

Intelligent manufacturing technology has recently experienced rapid development, where robot welding systems are an essential component. A laser profile sensor is commonly utilized in intelligent robot welding systems. However, when the laser stripe is projected onto a narrow weld joint, the deformation of the laser stripe is not sufficiently apparent, and the traditional weld joint recognition methods based on the laser profile sensors cannot detect the narrow weld joint position. Meanwhile, the strong arc and spatter noise during welding and the expansion of weld joint width caused by welding thermal expansion are likely to interfere with weld joint recognition. In addition, many common weld seam recognition methods can only recognize certain weld joints and have limited flexibility and robustness for other types of weld joints. This study proposes a wide range of weld joint recognition algorithms based on the laser profile sensor to overcome these challenges. The gray value histogram analysis method, the adaptive threshold method, the internal propulsion center and boundary extraction (IPCBE) method, the coordinate analysis method, and the stripe end center detection method proposed in this study are used primarily in the algorithm. The algorithm solves the problem of identifying narrow weld joints and allows for the identification of larger conventional weld joints. Furthermore, the algorithm has good a anti-spatter and anti-arc interference ability and a fast speed, allowing it to meet the demand for real-time welding identification.
A Systematic Mapping Study of Business Process Reengineering

Business Process Reengineering needs to be carried out in line with technological developments and changes in the environment. The goal is to modify procedures, systems, structures, responsibilities, and skills. the need for technology and the importance of increasing the efficiency and competitiveness of the organization or company in the face of organizational change. This article aims to classify, identify scientific publications and conduct a thematic analysis of the current literature in order to create an extensive and detailed understanding of Business Process Reengineering. The research method used is a systematic mapping study (SMS) to examine scientific publications produced from time to time, focus, locus, the type of research that is most widely investigated, as well as the most widely used research method. The SMS procedure follows established empirical guidelines and mapping data relies on the Scopus electronic database. Based on the results of SMS on research in the field of rural banks, it is known that there are 40 studies that meet the inclusion criteria. We classified 40 articles in topic areas by category of paper type, method, focus, locus, and year of research publication. Then, categorized and quantified current studies are generated on various dimensions, a summary of topics, and current research trends.
CKM angle γ measurements at LHCb

The CKM angle γ remains the least known parameter of the CKM mixing matrix. The precise measurement of this angle, as a Standard Model benchmark, is a key goal of the LHCb experiment. We present four recent CP violation studies related to the measurement of γ, including amplitude analysis of B± → DK± decays, the ADS/GLW analysis of B± → DK*0 decays and the time-dependent analysis of B± → DK±sK± decays.
Effects of Temporary Respiration Exercise with Individual Harmonic Frequency on Blood Pressure and Autonomic Balance

This study investigated the effects of modulated respiration on blood pressure and autonomic balance to develop a healthcare application system for stabilizing autonomic balance. Thirty-two participants were asked to perform self-regulated tasks with 18 different respiration sequences, and their electrocardiograms (ECG) and blood pressure were measured. Changes in cardiovascular system functions and blood pressure were compared between free-breathing and various respiration conditions. Systolic and diastolic blood pressures stabilized after individual harmonic breathing. Autonomic balance, characterized by heart rate variability, was also stabilized with brief respiration training according to harmonic frequency. Five machine-learning algorithms were used to classify the two opposing factors between the free and modulated breathing conditions. The random forest models outperformed the other classifiers in the training data of systolic blood pressure and heart rate variability. The mean areas under the curves (AUCs) were 0.82 for systolic blood pressure and 0.98 for heart rate variability. Our findings lend support that blood pressure and autonomic balance were improved by temporary harmonic frequency respiration. This study provides a self-regulated respiration system that can control and help stabilize blood pressure and autonomic balance, which would help reduce mental stress and enhance human task performance in various fields.