Miracle-dz/UniFAR-FTUs huggingface dataset:
A Coronagraph with a Variable‐Diameter Occulting Disk

In order to optimize the occulting process of a classical Lyot coronagraph for imaging faint satellites next to Jovian planets, we designed a coronagraph with a variable‐diameter occulting disk (Hg mask). We present the description of the Hg‐mask coronagraph developed at the Observatório Nacional, Rio de Janeiro, and the imaging test on Neptune’s satellite Proteus.
Computation of jacobi sums and cyclotomic numbers with reduced complexity

Jacobi sums and cyclotomic numbers are the important objects in number theory. The determination of all the Jacobi sums and cyclotomic numbers of order $e$ are merely intricate to compute. This paper presents the lesser numbers of Jacobi sums and cyclotomic numbers which are enough for the determination of all Jacobi sums and the cyclotomic numbers of a particular order.
Frame dependence of transition form factors in light-front dynamics

We study the radiative transitions between vector and pseudoscalar quarkonia in the light-front Hamiltonian approach, and investigate the effects of using different current component and different reference frames. In practical calculations with truncated Fock spaces, transition form factors may acquire current component dependence and frame dependence, and such dependences could serve as a measure for the Lorentz symmetry violation. We suggest using the transverse current with $m_j=0$ state of the vector meson, since this procedure employs the dominant spin components of the light-front wavefunctions and is more robust in practical calculations. We calculate the transition form factor between vector and pseudoscalar quarkonia and investigate the frame dependence with light-front wavefunctions calculated from the valence Fock sector. We suggest using frames with minimal longitudinal momentum transfer for calculations in the valence Fock sector, namely the Drell-Yan frame for the space-like region and a specific longitudinal frame for the timelike region; at $q^2=0$ these two frames give the same result.
SAVIOR: Towards Bug-Driven Hybrid Testing

Hybrid testing combines fuzz testing and concolic execution. It leverages fuzz testing to test easy-to-reach code regions and uses concolic execution to explore code blocks guarded by complex branch conditions. As a result, hybrid testing is able to reach deeper into program state space than fuzz testing or concolic execution alone. Recently, hybrid testing has seen significant advancement. However, its code coverage-centric design is inefficient in vulnerability detection. First, it blindly selects seeds for concolic execution and aims to explore new code continuously. However, as statistics show, a large portion of the explored code is often bug-free. Therefore, giving equal attention to every part of the code during hybrid testing is a non-optimal strategy. It slows down the detection of real vulnerabilities by over 43%. Second, classic hybrid testing quickly moves on after reaching a chunk of code, rather than examining the hidden defects inside. It may frequently miss subtle vulnerabilities despite that it has already explored the vulnerable code paths.We propose SAVIOR, a new hybrid testing framework pioneering a bug-driven principle. Unlike the existing hybrid testing tools, SAVIOR prioritizes the concolic execution of the seeds that are likely to uncover more vulnerabilities. Moreover, SAVIOR verifies all vulnerable program locations along the executing program path. By modeling faulty situations using SMT constraints, SAVIOR reasons the feasibility of vulnerabilities and generates concrete test cases as proofs. Our evaluation shows that the bug-driven approach outperforms mainstream automated testing techniques, including state-of-the-art hybrid testing systems driven by code coverage. On average, SAVIOR detects vulnerabilities 43.4% faster than DRILLER and 44.3% faster than QSYM, leading to the discovery of 88 and 76 more unique bugs, respectively. According to the evaluation on 11 well fuzzed benchmark programs, within the first 24 hours, SAVIOR triggers 481 UBSAN violations, among which 243 are real bugs.
The Role of Dynamic Capabilities in Export Performance of Firms from Emerging Economies

Increased globalisation has led to a great number of firms looking for opportunities abroad, and exporting is themost common form of entry mechanism. The purpose of this study is thus to investigate the impact of dynamiccapabilities on the performance of Thai exporting firms. The study follows quantitative research design usingsurvey method with statistical treatment. Given the extant definitions of dynamic capabilities, contextualambidexterity, an ability of the organization to pursue alignment and adaptation simultaneously, was proposed asdynamic capability in this study. Structured questionnaires were collected from key informants of Thai firmsengaging in exporting (n = 102). Bivariate regression analysis was employed to test the hypothesis, whilst clusteranalysis and one-way analysis of variance were used to explore the results. The findings indicate that dynamiccapability of contextual ambidexterity significantly affected the level of export performance of the participatingfirms. By clustering all participating firms according to their level of alignment and adaptation, ‘highlyambidextrous’ firms (i.e., high scores on both alignment and adaptation) outperformed the firms in the othercombinations. The study offers practical suggestions on how exporting firms can improve profitability andperformance by pursuing the proper combinations of alignment and adaptability corresponding to the dynamismof their export markets. The main contribution of this paper is the examination of performance impact ofdynamic capability in exporting context which should contribute to the future development of this line ofresearch,particularly in emerging economies.
Bifunctional eff ect of fucoidan from Padina tetrastromatica against human pathogenic microbes and free radicals

The antibacterial and antioxidant effect of fucoidan fractions isolated from brown algae Padina tetrastromatica was evaluated. Even though the polysaccharide was found to be a fucan, the composition of this polysaccharide is different from those reported, and the antibacterial and antioxidant effect has not been reported so far. Three fractions (F1, F2, and F3) were isolated by anion-exchange column chromatography. Chemical analysis suggested that the polysaccharide fractions contained a significant amount of sulfate and fucose, galactose xylose, and mannose as the major neutral sugars. Antibacterial activity was checked by disk diffusion method. Antioxidant activity was investigated by various in vitro systems, including 1,1-diphenyl-2-picrylhydrazyl radical scavenging, lipid peroxide inhibition, superoxide and hydroxyl radical scavenging activity, chelating ability and reducing power. Antibacterial and antioxidant assays suggested that the polysaccharide fraction F3 possessed good antibacterial activity and had stronger antioxidant properties than F1 and F2. Available data obtained by in vitro models suggested that the correlation between the sulfate content and pharmacological effect was positive. Fucoidan from P. tetrastromatica have the potential to be developed as anantibacterial and antioxidant agent, but further in vivo research for their mode of action are still needed to shed light on the effects. Overall, the present experiments showed fucoidan from marine brown algae as a potential therapeutic agent.
Error Correcting Algorithms for Sparsely Correlated Regressors

Autonomy and adaptation of machines requires that they be able to measure their own errors. We consider the advantages and limitations of such an approach when a machine has to measure the error in a regression task. How can a machine measure the error of regression sub-components when it does not have the ground truth for the correct predictions? A compressed sensing approach applied to the error signal of the regressors can recover their precision error without any ground truth. It allows for some regressors to be \emph{strongly correlated} as long as not too many are so related. Its solutions, however, are not unique - a property of ground truth inference solutions. Adding $\ell_1$--minimization as a condition can recover the correct solution in settings where error correction is possible. We briefly discuss the similarity of the mathematics of ground truth inference for regressors to that for classifiers.
USING MULTI-SCALE FEATURES FOR THE 3D SEMANTIC LABELING OFAIRBORNE LASER SCANNING DATA

Abstract. In this paper, we present a novel framework for the semantic labeling of airborne laser scanning data on a per-point basis. Our framework uses collections of spherical and cylindrical neighborhoods for deriving a multi-scale representation for each point of the point cloud. Additionally, spatial bins are used to approximate the topography of the considered scene and thus obtain normalized heights. As the derived features are related with different units and a different range of values, they are first normalized and then provided as input to a standard Random Forest classifier. To demonstrate the performance of our framework, we present the results achieved on two commonly used benchmark datasets, namely the Vaihingen Dataset and the GML Dataset A, and we compare the results to the ones presented in related investigations. The derived results clearly reveal that our framework excells in classifying the different classes in terms of pointwise classification and thus also represents a significant achievement for a subsequent spatial regularization.
Corporate Inversions and the Unbundling of Regulatory Competition

A sizable number of US public companies have recently executed “tax inversions” – acquisitions that move a corporation’s residency abroad while maintaining its listing in domestic securities markets. When appropriately structured, inversions replace American with foreign tax treatment of extraterritorial earnings, often at far lower effective rates. Regulators and politicians have reacted with alarm to the “inversionitis” pandemic, with many championing radical tax reforms. This paper questions the prudence of such extreme reactions, both on practical and on conceptual grounds. Practically, I argue that inversions are simply not a viable strategy for many firms, and thus the ongoing wave may abate naturally (or with only modest tax reforms). Conceptually, I assess the inversion trend through the lens of regulatory competition theory, in which jurisdictions compete not only in tax policy, but also along other dimensions, such as the quality of their corporate law and governance rules. I argue that just as US companies have a strong aversion to high tax rates, they have an affinity for robust corporate governance rules – a traditional strength of American corporate law. This affinity has historically given the US enough market power to impose tax premiums with dampened fear of chasing off incorporations, because US law specifically bundles tax residency and state corporate law into a conjoined regulatory package. To the extent this market power remains durable, radical tax overhauls would be unhelpful (and even counterproductive). A more blameworthy culprit for inversionitis, I argue, can be found in an unlikely source: Securities Law. Over the last fifteen years, financial regulators have progressively suffused US securities regulations with mandates relating to internal corporate governance matters – traditionally the domain of state law. Those federal mandates, in turn, have displaced and/or preempted state law as a primary source of governance regulation for US-traded issuers. And, because US securities law applies to all listed issuers (regardless of tax residence), this displacement has gradually “unbundled” domestic tax law from corporate governance, eroding the US’s market power in regulatory competition. A potential elixir for this erosion, then, may also lie in securities regulation. I propose two alternative reform paths: (a) domestic exchanges should charge listed foreign issuers for their consumption of federal corporate governance policies; and/or (b) federal law should cede corporate governance back to the states by rolling back many of the governance mandates promulgated over the last fifteen years.
Characterization of Some Typical Soils of the Miombo Woodland Ecosystem of Kitonga Forest Reserve, Iringa, Tanzania: Physico-Chemical Properties and Classification

Despite the fact that miombo woodland soils have significant implications in global climate change processes, few studies have been done to characterize and classify the soils of the miombo woodland ecosystem of Tanzania. The current study was carried out to map and classify soils of Kitonga Forest Reserve, which is a typical miombo woodland ecosystem, in order to generate relevant information for their use and management. A representative study area of 52 km 2 was selected and mapped at a scale of 1:50,000 on the basis of relief. Ten representative soil profiles were excavated and described using standard methods. Soil samples were taken from genetic soil horizons and analyzed in the laboratory for physico-chemical characteristics using standard methods. Using field and laboratory analytical data, the soils were classified according to the FAO-World Reference Base (FAO-WRB) for Soil Resources system as Cambisols, Leptosols and Fluvisols. In the USDA-NRCS Soil Taxonomy system the soils were classified as Inceptisols and Entisols. Topographical features played an important role in soil formation. The different soil types differed in physico-chemical properties, hence exhibit differences in their potentials, constraints and need specific management strategies. Texture varied from sandy to different loams; pH from 5.1 to 5.9; organic carbon from 0.9 g/kg to 20 g/kg; and CEC from 3 cmol/(+)kg to 24 cmol/(+)kg. Sustainable management of miombo woodlands ecosystem soils requires reduced deforestation and reduced land degradation.
Control of chaotic systems by deep reinforcement learning

Deep reinforcement learning (DRL) is applied to control a nonlinear, chaotic system governed by the one-dimensional Kuramoto–Sivashinsky (KS) equation. DRL uses reinforcement learning principles for the determination of optimal control solutions and deep neural networks for approximating the value function and the control policy. Recent applications have shown that DRL may achieve superhuman performance in complex cognitive tasks. In this work, we show that using restricted localized actuation, partial knowledge of the state based on limited sensor measurements and model-free DRL controllers, it is possible to stabilize the dynamics of the KS system around its unstable fixed solutions, here considered as target states. The robustness of the controllers is tested by considering several trajectories in the phase space emanating from different initial conditions; we show that DRL is always capable of driving and stabilizing the dynamics around target states. The possibility of controlling the KS system in the chaotic regime by using a DRL strategy solely relying on local measurements suggests the extension of the application of RL methods to the control of more complex systems such as drag reduction in bluff-body wakes or the enhancement/diminution of turbulent mixing.
Psychometric Properties of Turkish Version of Childhood Trauma Questionnaire among Adolescents with Gender Differences

The aim of this study was to investigate the psychometric properties of the Turkish version of Childhood Trauma Questionnaire (CTQ) and its subscales among adolescents. The participants consisted of 1275 high school students (14 - 19 years) with a mean age of 16.33 (SD = 1.01). The confirmatory factor analysis has revealed that CTQ has three subscale (physical abuse, emotional abuse, sexual abuse). Cronbach’s alpha for the total scale was . 91, for physical abuse . 84, for emotional abuse . 89, for sexaul abuse . 70. The test-retest correlation coefficient for the total score (n = 65) was . 81, for physical abuse . 82, for emotional abuse . 80, and sexual abuse . 75 at 3 weeks indicating adequate reliability. Discriminant validity was satisfactory. The results of the study have shown that the Turkish version of CTQ psychometrically sound among high school students.
Eagle i-Bot: an eye-controlled system

This article was published in IOSR Journal of Computer Engineering (IOSRJCE) [© International Organization Of Scientific Research (IOSR)] and the definite version is available at: http://iosrjournals.org/iosr-jce/papers/Vol7-Issue2/D0722328.pdf? id=404 The article website is at: www.iosrjournals.org
A Kind of Reducing PAPR Algorithm Based on OFDM System Model in Wireless Sensor Network

In Orthogonal Frequency Division Multiplexing (OFDM) used in Wireless Sensor Network (WSN), in order to restrain the intermodulation interference between subcarrier and outof-band radiation brought by system nonlinearity of Peak-to-Average Ratio (PAPR), a kind of joint algorithm is put forward, which is based on Selective Mapping (SLM) and Repeated Clipping and Filtering (RCF). By theoretical analysis, the joint scheme applied in OFDM system can reduce the PAPR dramatically. Further, simulation result afterwards verifies the effectiveness of the method, which can avoid Bit Error Rate (BER) performance degradation. So the method proposed in the paper proves to be very effective. Index Terms Orthogonal Frequency Division Multiplexing (OFDM), Peak-to-Average Ratio (PAPR), Selective Mapping (SLM), Repeated Clipping and Filtering (RCF), Bit Error Rate (BER)
Human mobility analysis by collaborative radio landscape observation

A new method to analyze the spatio-temporal activities of humans based on the symbolic information that can be extracted from a set of observations of mobile networks taken through smart phones is presented. Specifically, GSM and WiFi network observations collected by several users are gathered to collaboratively build a symbolic base map of the logical structure of the geography. At the same time a map of the mobility of each individual is also created from the same set of observations. The Proximity Map is then used to provide some spatial context to the Individual Mobility Maps. This information is intended to be used for the analysis of transportation efficiency.
Relevance of Emotional Intelligence for Effective Job Performance: An Empirical Study

There has been an increase in interest in ‘emotional intelligence’ within the Indian organization system in recent years. This increase has been attributed to the popularization of the construct of emotional intelligence in the research area. The promotion of emotional development in corporate organizations assumes that the ability to regulate emotions is a positive trait, which is associated with positive workplace performance. There is however, currently, little evidence to support the existence of such a relationship. The aim of the current study was to explore the relationship between emotional intelligence and workplace performance among corporate executives. The research was carried out in various organizations in Delhi NCR. A questionnaire design was used to explore whether there was a relationship between emotional intelligence scores and scores from performance assessment checklist for a sample of 90 males and females from different streams of population were taken. The relationship was explored using an analysis of correlation. The effect of demographic variables, e.g., gender, academic qualification, and work experience on EI score were also explored. The analysis found statistically significant positive correlations between scores on the emotional intelligence scale and scores on the performance scales. This means that increased emotional intelligence scores were associated with increased performance among executives working in various sectors. These results provide evidence of the concurrent validity of the emotional intelligence scale and also support the notion that emotional intelligence is associated with more or less workplace performances. The causal nature of this relationship cannot be inferred from the current study and further research is recommended to explore alternative explanations for this relationship. Out of the different demographic variables, only work experience was found to correlate positively with EI score. Experienced executives scored significantly higher on EI scale compared to less experienced executives. The results of the study are discussed within the context of the limitations of the current study and findings from previous research. The implications of the findings for organizations, policy makers, HR professionals, trainers, and future research are reflected upon.
Mineral supplementation of lambing ewes grazing dual-purpose wheat

Lambing ewes were grazed on dual-purpose wheat in two experiments in 2010 and 2011 with or without access to a mineral supplement. The calcium, magnesium and sodium content of wheat forage was below the requirements of ewes during late pregnancy and lactation; however, no clinical cases of hypocalcaemia or hypomagnesaemia were observed in either experiment. Blood serum assays identified eight hypocalcaemic ewes and one hypomagnesaemic ewe in Experiment 1, and one hypocalcaemic ewe in Experiment 2, and the provision of a mineral supplement comprising of magnesium oxide, calcium carbonate and coarse salt had no effect on blood magnesium, total calcium, phosphorus or sodium. Lamb birthweight and survival were not affected by provision of the mineral supplement in either experiment; however, the growth rate to marking (mean 38 ± 10 days of age) of twin-born lambs was higher in Experiment 1 when the supplement was provided to ewes grazing wheat (259 vs 243 g/head.day; P = 0.002).
Global Multivariable Control of Permanent Magnet Synchronous Motor for Mechanical Elastic Energy Storage System under Multiclass Nonharmonic External Disturbances

For the technology of mechanical elastic energy storage utilizing spiral torsion springs as the energy storage media presented previously, a global multivariable control algorithm based on nonlinear internal model principle under multiclass external disturbances is proposed. The nonlinear external disturbances with nonharmonic periodic characteristics are generated by multiclass nonlinear external systems. New equations of nonlinear internal model are designed to estimate the multiclass external disturbances. On the basis of constructing the control law of nominal system, a state feedback controller is designed to guarantee the closed-loop system globally uniformly bounded, and a Lyapunov function is constructed to theoretically prove the global uniform boundedness of the multivariable closed-loop system signals. The simulation results verify the correctness and effectiveness of the presented algorithm.
DISSECTING THE PARTIAL GENOMIC REGION OF CXCR TO CORRELATE WITH CMT IN VRINDAVANI CATTLE

Genetic markers associated with inflammatory responses during mastitis could aid in selection of cattle for mastitis resistance. The genomic region of 256 bp of CXCR2, a chemokine receptor required for neutrophil migration to infection sites was investigated in the current study to identify genetic polymorphism if any and to associate it with subclinical and clinical mastitis. Ninety five Vrindavani crossbred cows (42-mastitis tolerant and 53- with clinical mastitis) who completed at least two full lactations were taken for study. The cows which had never been affected by clinical mastitis during their productive life and tested negative for California mastitis test (CMT) were kept in the mastitis tolerant group. PCR-SSCP technique was used to reveal the polymorphism in 256bp fragments of CXCR2 gene. The fragment was found to be monomorphic in the population studied and hence it can not be used as a candidate for selecting mastistis resistant cattle.