Miracle-dz/UniFAR-FTUs huggingface dataset:
A Filter Approach to Multiple Feature Construction for Symbolic Learning Classifiers Using Genetic Programming

Feature construction is an effort to transform the input space of classification problems in order to improve the classification performance. Feature construction is particularly important for classifier inducers that cannot transform their input space intrinsically. This paper proposes GPMFC, a multiple-feature construction system for classification problems using genetic programming (GP). This paper takes a nonwrapper approach by introducing a filter-based measure of goodness for constructed features. The constructed, high-level features are functions of original input features. These functions are evolved by GP using an entropy-based fitness function that maximizes the purity of class intervals. A decomposable objective function is proposed so that the system is able to construct multiple high-level features for each problem. The constructed features are used to transform the original input space to a new space with better separability. Extensive experiments are conducted on a number of benchmark problems and symbolic learning classifiers. The results show that, in most cases, the new approach is highly effective in increasing the classification performance in rule-based and decision tree classifiers. The constructed features help improve the learning performance of symbolic learners. The constructed features, however, may lack intelligibility.
Analytics of Quinine and its Derivatives

ABSTRACT The objective of this study was to perform a synthesis and analysis of the most important information on quinine and its derivatives, which are still very important in the treatment of malaria. The analysis of stereoisomers of quinine and its derivatives was conducted using two techniques, high-performance liquid chromatography and capillary electrophoresis. Particularly noteworthy is the technique used for the determination of isotachophoresis, referred to as one of the so-called green chemistry techniques. Particular attention was paid to properties and the use of quinine and its derivatives in the treatment of malaria. The analytical part will supplement knowledge about quinidine, quinine, and cinchonidine, and will contribute to the growth of research on the so-much-needed drugs against malaria.
Analysis of Allele and Haplotype Diversity Across 25 Genomic Regions in Three Eastern European Populations

Objective: Individual population history is the main reason for the variability of linkage disequilibrium (LD) patterns and haplotype frequencies among populations. Such diversity may influence the transferability of tag SNPs from one population to another. Our goal was to compare patterns of pairwise LD and allele and haplotype frequencies in Estonian and Russian populations, to estimate the genetic variation between populations and assess the potential transferability of tag SNPs. Methods: 452 SNPs from 25 unlinked genomic regions on 12 chromosomes were genotyped in 140 Estonians and 207 Russians from Northern and Western regions of the European area of Russia. Results: The allele frequency distributions were highly consistent between populations (R > 0.90 for all pairwise comparisons). The overall frequency variation among populations was low (FST = 0.0054). The number of SNPs with high-range FST values (0.02–0.09) was most prominent for the MC5R genomic region. Haplotype heterogeneity among populations was low (FST values ranged within 0.00–0.01, with the exception of haploblocks in the ADIPOR2 and MC5R regions). The interpopulation proximity was also evaluated using haplotype diversity. Conclusion: Our data showed a high concordance between the populations studied, which may be considered as the result of their historical formation on a cognate genetic basis.
Leakage dissipation reduction of single-phase power-gating adiabatic sequential circuits using MTCMOS

Reducing leakage dissipation is becoming more and more important in low-power design. The dynamic energy dissipation reduction of adiabatic circuits using power-gating schemes has been introduced. In order to reduce leakage losses of the adiabatic circuits using power-gating schemes under deep submicron process, this paper proposes a MTCMOS (Multi-Threshold CMOS) power-gating scheme for adiabatic sequential circuits based on two-phase CPAL (complementary pass-transistor adiabatic logic) circuits, which can operate in a single-phase power clock by introducing a two-phase power-clock generator. A practical sequential system with a mode-10 counter is demonstrated using the MTCMOS power-gating scheme. All circuits are verified using HSPICE, and BSIM4 model is adopted to reflect the characteristics of the leakage currents. Simulations show that the leakage losses are greatly reduced.
Active Distribution System Reinforcement Planning With EV Charging Stations—Part I: Uncertainty Modeling and Problem Formulation

Due to the associated uncertainties, the large-scale deployment of electric vehicles (EVs) and renewable distributed generation is a major challenge faced by the modern distribution systems. The first part of this two-paper series proposes a scenario-based stochastic model for the multistage joint reinforcement planning of the distribution systems and the electric vehicle charging stations (EVCSs). The historical EV charging demand is first determined using the Markovian analysis of EV driving patterns and charging demand. A scenario matrix, based on the heuristic moment matching method, is then generated to characterize the stochastic features and correlation among historical wind and photovoltaic generation, and conventional loads and EV demands. The scenario matrix is then utilized to formulate the expansion planning framework, aiming at the minimization of the investment and operational costs. The proposed expansion plan determines the optimal construction/reinforcement of substations, EVCSs, and feeders, in addition to the placement of wind and photovoltaic generators, and capacitor banks over the multi-stage planning horizon. In the second companion paper, the effectiveness and scalability of the proposed model is assessed through case studies in the 18-bus and the IEEE 123-bus distribution systems, respectively.
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges

While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently, there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services, such as traffic engineering, anomaly detection, Internet traffic classification, and quality of service optimization. The growing interest in applying unsupervised learning techniques in networking stems from their great success in other fields, such as computer vision, natural language processing, speech recognition, and optimal control (e.g., for developing autonomous self-driving cars). In addition, unsupervised learning can unconstrain us from the need for labeled data and manual handcrafted feature engineering, thereby facilitating flexible, general, and automated methods of machine learning. The focus of this survey paper is to provide an overview of applications of unsupervised learning in the domain of networking. We provide a comprehensive survey highlighting recent advancements in unsupervised learning techniques, and describe their applications in various learning tasks, in the context of networking. We also provide a discussion on future directions and open research issues, while identifying potential pitfalls. While a few survey papers focusing on applications of machine learning in networking have previously been published, a survey of similar scope and breadth is missing in the literature. Through this timely review, we aim to advance the current state of knowledge, by carefully synthesizing insights from previous survey papers, while providing contemporary coverage of the recent advances and innovations.
Quality Control of PCB using Image Processing

An automated testing system for Printed Circuit Board (PCB) is preferred to get the technological advances in PCBs design and manufacturing, eliminates particular aspects and then provides fast, quantitative, and dimensional impositions. It reduces the testing time and manufacturing cost as human inspectors decisions are ineffective, slow and costly. Thus in this area, digital image processing can be used mainly for the detection of faulty parts or missing components. This system mainly deals with analysis to detect faulty PCB. Digital camera is used in automated visual inspection system that captures image of each sample PCB product. The captured image is then provided to computer for further processing which includes conversion in various forms such as Gray scale image and binarized image. XOR operation is performed on these converted images to obtain the required results. Contour Analysis is performed on these results for classification. Missing components, polarities, circuit breaks, missing tracks these types of faults are detected and classified accordingly. This concept increases the speed and accuracy, eliminates human errors which are frequent in quality testing and also overcomes the weakness in the existing system. Hence the productivity can be increased by replacing manual testing with the proposed concept. General Terms Image Processing, Quality Control, Printed Circuit Board.
Ab initio calculations of the giant magnetoresistance.

We present ab initio calculations of the giant magnetoresistance in magnetic multilayers. The electronic structure of the multilayers is calculated by spin density functional theory using a screened Korringa–Kohn–Rostoker method. The scattering of nanostructural defects in the multilayers is described by means of a Green’s function method. The scattering potentials are calculated self-consistently. The transport properties are treated quasiclassically solving the Boltzmann equation including the electronic structure of the layered system and the anisotropic scattering. The solution of the Boltzmann equation is performed iteratively taking into account both scattering out and scattering in terms (vertex corrections). Since we consider ferromagnetic systems a two current model is applied. Trends of residual resistivities and giant magnetoresistance ratios are discussed for Co/Cu multilayers with 3d transition metal defects.
Three-Dimensional Wafer Stacking Using Cu–Cu Bonding for Simultaneous Formation of Electrical, Mechanical, and Hermetic Bonds

Wafer-on-wafer stacking is demonstrated successfully using bumpless Cu-Cu bonding for the simultaneous formation of electrical connection, mechanical support, and hermetic frame for 3-D IC application. The ohmic behavior of the Cu-Cu bond is verified. A daisy chain of at least 44 000 contacts at a 15-μm pitch is connected successfully and sustains thermal cycling. Postbonding delamination is found to be strongly affected by the wafer curvature and bond strength. The Cu-Cu hermetic seal ring shows a helium leak rate more than ten times lower than the reject limit (5 × 10-8 atm · cm/s based on MIL-STD-883E standard) without underfill. This provides a robust IC-to-IC connection density of 4.4 × 105 cm-2, suitable for future wafer-level 3-D integration.
Design and characterization of high-sensitivity cantilevers

In order to increase the sensitivity of a cantilever-based biosensor, piezoresistive cantilevers with stress concentration holes were designed and fabricated. Firstly the stress distributions and the vertical displacements of the designed cantilevers were simulated through ANSYS analyzing system. Then the relative resistance changes of the piezoresistors as a function of the cantilever vertical displacements were measured. As expected, the stresses are highly concentrated for the designed cantilevers, and this design can obviously result in an improvement on the sensitivity of the surface-stress mode cantilevers
Pharmacological Potential of Asthma Weed ( E uphorbia hirta ) Extract toward Eradication of Plasmodium berghei in Infected Albino

Malaria, a mosquito borne infectious disease of human and other animals affects a large number of the world’s population, and it’s caused by parasitic protozoan of the genus plasmodium. The search for new antimalarial chemotherapies has however become urgently increasing due to the parasite resistance to available drugs. Asthma weed (Euphorbia hirta) which is a natural therapeutic herb used for the management of gastrointestinal disorders, respiratory diseases and other ailments was therefore investigated in order to establish the whole plant aqueous-methanolic extract in vivo antiplasmodial effects on chloroquine-sensitive Plasmodium berghei in infected mice, using the suppressive and prophylactic test models. The in vivo antimalarial activity of the Euphorbia hirta extract doses (200, 400 and 800 mg/kg body weight) against P. berghei showed that it has significant (p<0.05) suppressive activity of 51 – 59 % and prophylactic activity of 25 – 50 % when compared with Chloroquine that gave 95 and 81 % suppressive and prophylactic antiplasmodial activities respectively. Result further showed that antiplasmodial action may not be through the oxidation of red blood cell membrane lipids as increasing extract concentration results in the reduction of the enzymatic activities of SOD and GPx, and concentrations of GSH and TBARS. We assumed that the antiplasmodial effect of the extract may have been contributed by its phytochemical components. This thus suggests that E. hirta plant extract has a very good potential pharmacological activity, and this could be beneficial in the development of new drugs for treatment or prophylaxis against malaria.
LIMITS Special Issue on Durban Platform scenarios On the regional distribution of climate mitigation costs: the impact of delayed cooperative action

This paper analyzes the results of the climate-energy-economy model, Regionalized Model of Investment and Technological Development (REMIND), to assess the regional costs of climate-change mitigation for reaching the 2°C target with a medium to high likelihood. We assume that the global climate regime remains fragmented until 2020 after which a global mitigation target is adopted. We decompose the regional mitigation costs into (a) domestic and energy trade effects and (b) permit trade effects. Delaying cooperative action affects domestic costs by increasing the energy system's costs as a consequence of lock-in of carbon-intensive infrastructures. This is particularly true in developing countries with low near-term emissions reduction commitments. In a global cap-and-trade system, the effect of delayed action highly depends on whether or not the regions are over- or under-allocated with emissions allowances in the long term. Those with allowances exceeding their long-term emissions will likely benefit from the delay, while others suffer the consequences of higher long-term carbon prices.
Design of an Aberration Correction System for a Deployable Space Telescope

Launch costs for high-resolution space telescopes for Earth observation can be reduced when the telescope mirrors are made deployable. However, such a system is subject to optical aberrations that decreases image quality. To counter these aberrations, an Aberration Correction System (ACS) is proposed that uses a deformable mirror (DM) which is calibrated by applying image sharpness optimisation. A stochastic gradient descent algorithm is applied to the output of two image detectors, such that the DM deformation can even be optimised during in-orbit scanning operations, without the need for a dedicated wavefront sensor. The effects of different sharpness metrics and algorithm settings have been analysed. With this novel control method, an average Strehl ratio of above 0.9 and 0.8 can be achieved on the central field and extreme field of the primary detector respectively. Also, in-orbit drift effects can be actively compensated without interrupting nominal operations.
Validity of a Linear Velocity Transducer for Testing Maximum Vertical Jumps.

This study aimed to examine the validity of mechanical variables obtained by a linear velocity transducer from the unconstrained and constrained squat jump (SJ). Twenty-three men were tested on the unconstrained SJ and the SJ constrained by a Smith machine. Maximum values of force, velocity, and power were simultaneously recorded both by a linear velocity transducer attached to a bar of mass of 17, 30, 45, 60, and 75 kg and by a force plate. Linear velocity transducer generally overestimated the outcomes measured as compared to the force plate, particularly in unconstrained SJ. Bland-Altman plots revealed that heteroscedasticity of errors was mainly observed for velocity variables (r 2 = .26-.58) where the differences were negatively associated with the load magnitude. However, exceptionally high correlations were observed between the same outcomes recorded with the 2 methods in both unconstrained (median r = .89 [.71-.95]) and constrained SJ (r = .90 [.65-.95]). Although the systematic and proportional bias needs to be acknowledged, the high correlations between the variables obtained by 2 methods suggest that the linear velocity transducer could provide valid values of the force, velocity, and power outputs from both unconstrained and constrained SJ.
AIS Electronic

In an effort to re-focus on their core competences, an increasing number of companies outsource parts of their IT services. In this context, based on Hamel and Prahalad’s definition of core competences, numerous theoretical models for identifying and analyzing core competences were developed. However, at present, due to the high complexity of outsourcing decisions, it is not clear which theoretical models can support decision-makers and to what extent these models can make a contribution. To address these questions, theoretical models for identifying and analyzing core competences, suitable for supporting IT outsourcing decisions in general, are identified, and systematically classified within a framework. Based on the developed classification, one model of each model category is evaluated on the basis of a list of six criteria.
The role of Rho GTPase proteins in CNS neuronal migration

The architectonics of the mammalian brain arise from a remarkable range of directed cell migrations, which orchestrate the emergence of cortical neuronal layers and pattern brain circuitry. At different stages of cortical histogenesis, specific modes of cell motility are essential to the stepwise formation of cortical architecture. These movements range from interkinetic nuclear movements in the ventricular zone, to migrations of early‐born, postmitotic polymorphic cells into the preplate, to the radial migration of precursors of cortical output neurons across the thickening cortical wall, and the vast, tangential migrations of interneurons from the basal forebrain into the emerging cortical layers. In all cases, actomyosin motors act in concert with cell adhesion receptor systems to provide the force and traction needed for forward movement. As key regulators of actin and microtubule cytoskeletons, cell polarity, and adhesion, the Rho GTPases play critical roles in CNS neuronal migration. This review will focus on the different types of migration in the developing neocortex and cerebellar cortex, and the role of the Rho GTPases, their regulators and effectors in these CNS migrations, with particular emphasis on their involvement in radial migration. © 2010 Wiley Periodicals, Inc. Develop Neurobiol 71: 528–553, 2011
A First Order Method for Solving Convex Bilevel Optimization Problems

In this paper we study convex bilevel optimization problems for which the inner level consists of minimization of the sum of smooth and nonsmooth functions. The outer level aims at minimizing a smooth and strongly convex function over the optimal solutions set of the inner problem. We analyze a first order method which is based on an existing fixed-point algorithm. Global sublinear rate of convergence of the method is established in terms of the inner objective function values.
Changes in postural stability in women aged 20 to 80 years.

BACKGROUND A study of postural stability was undertaken to identify the relationship between vision and support surface across age decades. Understanding when reliance on vision for postural stability emerges and the support conditions contributing to this instability may provide the evidence required to introduce falls-prevention strategies in younger age decades. METHODS We measured postural stability in 453 women aged 20 to 80 years using the Balance Master force-plate system while the women performed the modified Clinical Test for the Sensory Interaction and Balance (firm and foam surfaces, eyes open and closed) and the Single-Limb Stance Test (eyes open and closed). RESULTS Women in their 60s and 70s were more unstable than younger women in bilateral stance on a firm surface with the eyes closed. This instability was evident from the 50s when a foam surface was introduced and from the 40s when single-limb stance was tested with eyes closed. A further decline in stability was demonstrated for each subsequent decade when the eyes were closed in single-limb stance. CONCLUSIONS Age, visual condition, and support surface were significant variables influencing postural stability in women. Reliance on vision for postural stability was evident for women from the 40s when single-limb stance was tested, from the 50s when bilateral stance on foam was tested, and from the 60s when a firm surface was used. The cause(s) of this decline in stability requires further investigation, and screening for postural instability between the ages of 40 and 60 is advocated.
Computation of stability regions for the cylindrical ion trap with no octupole electric field as compared to the corresponding results of the Paul trap

The cylindrical ion trap is analyzed so that the octupole component of the electric field inside the trap is set to zero. As a consequence, the diameter to height ratio is computed to be 1.20 for which the quadrupole component of the cylindrical ion trap is dominant. Afterwards, it is concluded that the electric potential inside the trap as well as the corresponding stability regions are very similar to those obtained for an ideal Paul trap with pure quadrupole electric field. Furthermore, we drew a conclusion that the stability diagrams of the cylindrical ion trap without octupole term and the stability diagrams of the Paul trap have 5.6%, 3.7%, and 2.9% discrepancy for the first, second, and third stability diagrams, respectively. It should be noted that, expansion of the electric potential inside the cylindrical ion trap in terms of the multipole electric field components and making the advantages of the octupole term elimination has not been reported in the literature previously.