Miracle-dz/UniFAR-FTUs huggingface dataset:
Leadership Styles , Subordinates ’ Satisfaction with the Leader and Perceived Effectiveness

The current leadership literature is based on studies mostly carried out in the West. This study attempts to examine the relationship between leadership styles and employee and organizational outcomes in a Nepali telecommunication company. It proposes and tests a model suggesting direct relationship between leadership styles and employees' satisfaction with the leader, leader effectiveness, and work-unit effectiveness as well as the mediating effect of satisfaction with the leader on the relationships between leadership styles and leader effectiveness and work-unit effectiveness. Bass and Avolio’s multifactor leadership questionnaire (MLQ) 5X (short) was used to measure leadership styles and employee’s satisfaction with the leader. The sample consisted of 115 employees working in a Nepali telecommunication company. Structural Equation Modeling was employed to test the hypothesized relationships. Path analysis results indicated that (1) transformational leadership is positively related with outcomes; (2) transformational leadership is the stronger predictor of employee’s satisfaction with the leader, leader effectiveness and work-unit effectiveness than transactional leadership; (3) the relationship between transformational leadership and leader effectiveness and work unit effectiveness were partially mediated by employee’s satisfaction with the leader. Consistent with the findings of previous studies, the findings of this study clearly indicate that transformational leadership style significantly contribute to leader effectiveness and work-unit effectiveness and gives more satisfaction to the subordinates. These findings highlight the importance of transformational leadership style in achieving desired individual and organizational level outcomes. Relatively small sample size, sample drawn from a single organization, and subordinate's ratings for assessing leadership styles and outcomes limit the generalizability of the findings. For increased generalizability, further research with samples from different organizations and objective measures of outcomes will be needed.
Evaluation of changes in left ventricular structure and function in hypertensive patients with coronary artery disease after PCI using real-time three-dimensional echocardiography

We aimed to evaluate the changes in left ventricular structure and function in hypertensive patients with coronary artery disease before and after percutaneous coronary intervention (PCI) using real-time three-dimensional echocardiography. Two hundred and eighty hypertensive patients with coronary artery disease undergoing PCI and 120 cases who did not receive PCI in our hospital were selected as the subjects of our study. All patients were administered with routine antiplatelet, anticoagulant, lipid-lowering, antihypertensive, dilating coronary artery and other medications. The left ventricular systolic function and systolic synchrony index changes before and after subjects were treated by PCI were analyzed using three-dimensional echocardiography. At 2 days before surgery, there were no significant differences in the left ventricular end-diastolic volume, left ventricular end-systolic volume (LVESV) and ejection fraction (EF) between the two patient groups (P>0.05). At 3 months and 9 months, the two key time points after PCI, the LVESV level in the PCI group was distinctly decreased, while EF was significantly increased (P<0.05). In addition, before treatment, there were no significant differences in the parameters of time from the corresponding segment of the myocardium to the minimal systolic volume in two patient groups, such as Tmsv-16SD, Tmsv-16Dif, Tmsv-12SD, Tmsv-12Dif, Tmsv-6SD and Tmsv-6Dif (P>0.05); however, the parameters of time from the corresponding segment of the myocardium to the minimal systolic volume in patients in the PCI group were significantly reduced at 3 and 9 months after surgery (P<0.05). Three-dimensional echocardiography can evaluate the critical parameters in the prognosis of hypertensive patients with coronary artery disease after PCI accurately and in real-time, which may play a significant role.
HE0359-3959: An Extremely Radiating Quasar

We present a multiwavelength spectral study of the quasar HE0359-3959, which has been identified as an extreme radiating source at intermediate redshift (z=1.5209). Along the spectral range, the different ionic species give information about the substructures in the broad line region. The presence of a powerful outflow with an extreme blueshifted velocity of $\sim$-6000$\pm$500 km s$^{-1}$ is shown in the CIV{\lambda}1549 emission line. A prominent blueshifted component is also associated with the 1900{\AA} blend, resembling the one observed in CIV{\lambda}1549. We detect a strong contribution of very the low-ionization lines, FeII and Near-Infrared CaII triplet. We find that the physical conditions for the low, intermediate and high-ionization emission lines are different, which indicate that the emission lines are emitted in different zones of the broad line region. The asymmetries shown by the profiles reveal different forces over emitter zones. The high-ionization region is strongly dominated by radiation forces, which also affect the low and intermediate-ionization emitter region, commonly governed by virial motions. These results support the idea that highly radiating sources host a slim disk.
H∞ performance and robust topology design of relative sensing networks

This work provides a general framework for the analysis and synthesis of a class of relative sensing networks (RSN) in the context of its H∞ performance. In an RSN, the underlying connection topology couples each agent at their outputs. A distinction is made between RSN with homogeneous agent dynamics and RSN with heterogeneous dynamics. In both cases, explicit graph theoretic expressions and bounds for the H∞ performance are derived. The H∞ performance is structure dependent and related to the spectral radius of the graph Laplacian. The analysis results are then used to develop synthesis methods for RSNs. Using results from robust semi-definite programming, a synthesis procedure for the design of a robust sensing topology is derived.
On the design of wideband and tunable matching and decoupling networks for N-port antennas

This paper deals with the design of matching and decoupling network for a 4-port MIMO antenna system operating in the TV white spaces from 470 MHz to 790 MHz. After stating the limitations on the classical design based on hybrids, we consider a new approach in order to optimize the MIMO antenna performance, in terms of bandwidth, by taking advantage of some degrees of freedom in the matching and decoupling network. The maximum attainable bandwidth will be reported as a function of the network elements.
Efficient time shared task scheduler for cloud computing

Many virtual clusters, virtual machines run in each data center hosting number of heterogeneous tasks submitted by different cloud customers. In this concept, scheduling of incoming tasks to cloud should be scheduled on to less number of physical servers which improves the resource utilization. Scheduler should also efficiently manage the load between resources and achieve minimum execution time. In this paper, we designed an efficient approach for time shared task scheduler which effectively does load balancing, resource utilization and provides high performance than existing time shared task scheduler. This algorithm has been tested using CloudSim toolkit and results were compared with existing time shared task scheduler.
Predicting Results of a Biological Experiment Using Matrix Completion Algorithms

Biologists from McMaster’s Brown Lab are interested in the mechanism of action of uncharacterized inhibitors of the growth of bacteria. To achieve their goal, they systematically combined 186 small molecules of unknown action with 14 known antibiotics of diverse mechanisms. The result of all these experiments is a 186 × 14 matrix of “synergy values” between 186 small molecules and 14 known antibiotics. The entries of the data matrix represent normalized bacteria growth rates in the presence of an antibiotic and a small molecule. The goal of this project is to create an algorithm that can predict all results of this biological experiment given only a subset of the results in question. This project is motivated by: the time and money it could save for experimental biologists, the opportunities for collaboration with people in other disciplines and the fascinating application of algorithms to a problem they were not designed to solve. We quickly realized that predicting all results of a biological experiment given a subset of the results boils down to completing a matrix given a subset of its entries. The methods that we tried fall into the broad categories of Collaborative Filtering (CF) and Nystrom methods. In total we tried 4 methods: a Memory-Based CF method, a Model-Based CF method, the original Nystrom method and Landmark Multidimensional Scaling. All of these methods present different ways to complete a matrix given only a subset of the entries. Both the Nystrom and Landmark Multidimensional Scaling methods were unable to predict the results of our biological experiment with any accuracy. Possible reasons why these two methods failed are discussed. The Memory-Based CF method performed well enough to seem a viable choice for our application. Finally, of all the methods, the Model-Based CF method based on matrix factorization was the most successful.
Structured low-rank matrix learning: algorithms and applications

We consider the problem of learning a low-rank matrix, constrained to lie in a linear subspace, and introduce a novel factorization for modeling such matrices. A salient feature of the proposed factorization scheme is it decouples the low-rank and the structural constraints onto separate factors. We formulate the optimization problem on the Riemannian spectrahedron manifold, where the Riemannian framework allows to develop computationally efficient conjugate gradient and trust-region algorithms. Experiments on problems such as standard/robust/non-negative matrix completion, Hankel matrix learning and multi-task learning demonstrate the efficacy of our approach. A shorter version of this work has been published in ICML'18.
Positive linear relationship between productivity and diversity: evidence from the Eurasian Steppe

Summary 1 Understanding the productivity–diversity relationship (PDR) is a key issue in biodiversity–ecosystem functioning research, and has important implications for ecosystem management. Most studies have supported the predominance of a hump-shaped form of PDR in which species richness peaks at an intermediate level of productivity. However, this view has been challenged recently on several grounds. 2 Based on data from 854 field sites across the Inner Mongolia region of the Eurasian Steppe, we tested the form of PDR at different organizational levels (association type, vegetation type and biome) and multiple spatial scales (local, landscape and regional). 3 Our results showed that a positive linear, rather than hump-shaped, form was ubiquitous across all organizational levels and spatial scales examined. On the regional scale, this monotonic PDR pattern corresponded closely with the gradient in mean annual precipitation (MAP) and soil nitrogen. Increasing species dissimilarity with productivity could also contribute to the positive linear form of PDR. 4 Our results also indicated that grazing decreased both primary productivity and species richness but, intriguingly, not the form of PDR. 5 Synthesis and applications. This study provides the first direct test of the productivity–diversity relationship for the world's largest contiguous terrestrial biome – the Eurasian Steppe. The predominance of a positive linear relationship in this region defies the commonly held view that a unimodal form of PDR dominates terrestrial ecosystems, supported mainly by studies in Africa, Europe and North America. It suggests that precipitation has a greater control on the productivity–diversity relationship in the Eurasian Steppe than grasslands elsewhere. Also, the positive linear relationship is surprisingly robust to grazing. Our results provide new insight into the productivity–diversity relationship and have several implications for restoring degraded lands and understanding ecological consequences of climate change in the Eurasian Steppe.
Using a sensor-assisted model for learning retention in an e-book reading environment

Modern life has a strong tie with ICT technology, so as to the sensing technology which has played an important role than before. Its application is somewhat more than we have learned, such as education. Meanwhile, with the advance of software/hardware and the popularity of the Internet, e-books have drawn much of attention. With the introduction of the sensing technology to e-readers, it instills e-books the functions of reading or learning behavior. In self-learning situation, learners often suffer from detraction problem which cannot be easily detected and amended. In this study, we proposed a sensor-assisted learning system to monitor a learner's retention during the reading or learning process. The system has been incorporated into an e-book platform, or e-reader to become a personalized e-reader system. We proceed to conduct two experiments for sensor-assisted model (SAM) and e-book systems, respectively. The ultimate objective is to establish an adaptive personalized learning system by the feedback of data collected by sensors.
First Results of Digital Topography Applied to Macromolecular Crystals

An inexpensive digital CCD camera was used to record X-ray topographs directly from large imperfect crystals of cubic insulin. The topographs recorded were not as detailed as those which can be measured with film or emulsion plates, but do show great promise. Six reflections were recorded using a set of finely spaced stills encompassing the rocking curve of each reflection. A complete topographic reflection profile could be digitally imaged in minutes. Interesting and complex internal structure was observed by this technique. The CCD chip used in the camera has anti-blooming circuitry and produced good data quality, even when pixels became overloaded.
Order-lot pegging heuristics for minimizing total tardiness in a semiconductor wafer fabrication facility

We consider a problem of order-lot pegging in a semiconductor wafer fabrication facility. In the problem, we determine assignments of wafers in lots to orders and plans for input release of wafers into wafer fabrication facility with the objective of minimizing the total tardiness of orders over finite time horizon. The problem is formulated as a mixed integer linear program. To tackle industrial-sized problems, we develop six heuristic algorithms based on the earliest due date rule. The test results on randomly generated problems show that the suggested algorithms give better solutions than an optimization method of a commercial software package within a reasonable computation time.
O-Vanillin and Some of its Novel Schiff Bases: A Cheminformatic Approach to Identify their Biological Functions

Ortho-Vanillin (2-Hydroxy-3-methoxybenzaldehyde) is an organic solid present in the extracts and essential oils of many plants. Its functional groups include aldehyde, ether and phenol. Recent years, most ortho-vanillin is used in the study of mutagenesis and as a synthetic precursor for pharmaceuticals. The current study is focused on the prediction of biological target through target fishing approach for the novel o- vanillin and some of their Schiff bases which are synthesized by our group. Various tools and databases were employed to identify the biological function of the synthesized O-vanillin derivatives, the obtained results were confirmed through docking and molecular dynamics simulation studies.
A Single-Stage Stand-Alone Photovoltaic Energy System With High Tracking Efficiency

A single-stage flyback PV inverter with maximum power point tracking (MPPT) high-speed capability is presented in this paper. The proposed stand-alone photovoltaic energy system (SAPES) incorporates the use of hybrid MPPT to ensure peak energy harvesting under all weather conditions. The proposed hybrid MPPT method combines the conventional short current pulse (SCP) MPPT method and the perturb and observe (P&O) methods. Measurement of the offline parameter [short-circuit current of PV module (<inline-formula><tex-math notation="LaTeX">${I}_{\rm sc}$</tex-math> </inline-formula>)] for SCP is made on the basis of the difference between the offline parameter and the instantaneous current of PV module (<inline-formula><tex-math notation="LaTeX">${I}_{\rm pv}$</tex-math></inline-formula>). Use of a single power conversion stage is achieved by employing a modified flyback inverter operating in a discontinuous-conduction mode. The control structure of the conventional flyback inverter is also modified to incorporate the hybrid MPPT algorithm. The proposed SAPES method is tested using computer-aided simulations and real-time hardware in the loop experimentation using the dSPACE DS1104 board. The results obtained using the proposed systems are better than those for the conventional algorithms under the environmental conditions tested.
Magnetic Cycles in the Sun: Modeling the Changes in Radius, Luminosity, and p-Mode Frequencies

We report on the results obtained with a stellar evolution code in which cyclic magnetic fields are imposed in the convection zone of a 1.0 M☉ star. Magnetic effects are incorporated in two ways: (1) the field pressure and energy density are included in the equations of hydrostatic equilibrium and conservation of energy; and (2) the field inhibits the onset of convection according to a prescription derived by Gough & Tayler (1966). Inserting magnetic fields into the convection zone with strengths comparable to the observed global fields in the Sun, and assuming a simple depth dependence for the field strength, we find differences in luminosity and radius between nonmagnetic and magnetic models that are consistent in amplitude with the observed activity-related changes in the Sun. Using the same magnetic fields, and computing p-mode frequencies for nonmagnetic and magnetic models, we find that the frequencies in a magnetic model are larger than those for a nonmagnetic model. The frequency differences between nonmagnetic and magnetic models agree in sign, and overlap in magnitude and frequency dependence, with the shifts in frequency which have been observed in the Sun between solar minimum and solar maximum. We find that the luminosity variations are out of phase with the magnetic variations: in order to help reconcile this result with empirical solar data, we note that the global (poloidal) fields in the Sun are observed to pass through minimum values at times that correspond roughly with times of maximum toroidal fields.
Algebraic-numerical method for the slightly perturbed harmonic oscillator

The solution of slightly perturbed harmonic oscillators can easily be obtained in the form of a series given by Poisson's method. However, this perturbation method leads to secular terms unbounded for large time (the time unit being the fundamental period of the harmonic oscillator), which prevent the use of finite series. The analytical elimination of such terms was first solved by Poincare and, more recently, generalized by Krylov and Bogoliubov. Unfortunately, these methods are very difficult to handle and are not easily carried out for high orders. A numerical reinitialization method is combined here with the Poisson perturbation treatment to avoid the growth of secular terms and therefore to get the solution at any time. The advantages of such a method is that the analytical work can be carried to high orders keeping the step of numerical integration to a relatively large value (compared to a purely numerical method). This algorithm has been tested on the Mathieu equation. A method for the computation of the eigenvalues of this equation is given. By properly selecting the order of the perturbation and the time step of reinitialization, we can recover, at any order, all the effects of the slight perturbation (including all the unstable zones). Consequently, such a method is a useful intermediate between purely analytical and purely numerical algorithms.
The radiative efficiency of a radiatively inefficient accretion flow

A recent joint XMM–Newton/Nuclear Spectroscopic Telescope Array (NuSTAR) observation of the accreting neutron star Cen X-4 (LX ∼ 10^(33) erg s^(−1)) revealed a hard power-law component (Γ ∼ 1–1.5) with a relatively low cut-off energy (∼10 keV), suggesting bremsstrahlung emission. The physical requirements for bremsstrahlung combined with other observed properties of Cen X-4 suggest the emission comes from a boundary layer rather than the accretion flow. The accretion flow itself is thus undetected (with an upper limit of L_(flow) ≲ 0.3LX). A deep search for coherent pulsations (which would indicate a strong magnetic field) places a 6 per cent upper limit on the fractional amplitude of pulsations, suggesting the flow is not magnetically regulated. Considering the expected energy balance between the accretion flow and the boundary layer for different values of the neutron star parameters (size, magnetic field, and spin) we use the upper limit on L_(flow) to set an upper limit of e ≲ 0.3 for the intrinsic radiative efficiency of the accretion flow for the most likely model of a fast-spinning, non-magnetic neutron star. The non-detection of the accretion flow provides the first direct evidence that this flow is indeed ‘radiatively inefficient’, i.e. most of the gravitational potential energy lost by the flow before it hits the star is not emitted as radiation.