Miracle-dz/UniFAR-FTUs huggingface dataset:
The Roles of Organizational Politics and Fairnesin the Relationship between Relative Performance Evaluation and Managerial Performance

The purpose of this study is to investigate if the perceptions of organizational politics and perceptions of fairness mediates the relationships between relative performance evaluation and managerial performance. A survey of 125 managers of manufacturing companies in Indonesia are used to test the models. Data analysis is undertaken with Partial Least Square. Results indicate that relative performance evaluation has a positive impact on organizational politics. The finding suggests that general political behaviour and the politics of going along to get ahead has a negative impact on managerial performance but pay and promotion policies have no impact on managerial performance. The results also indicate that general political behaviour and politics of going along to get ahead significantly mediate the relative performance evaluation and managerial performance relationship. In contrast, the mediating effects of politics on pay and promotion policies on the relationship between relative performance evaluation and managerial performance is insignificant. We also find that the use of relative performance evaluation has a negative impact on fairness; and fairness is positively related to managerial performance. Specifically, the results find that fairness significantly mediate the use of performance relative evaluation and managerial performance relationship.
Carbon Dots Derived from Tea Polyphenols as Photosensitizers for Photodynamic Therapy

Photodynamic therapy (PDT) has become an emerging cancer treatment method. Choosing the photosensitizer (PS) compounds is one of the essential factors that can influence the PDT effect and action. Carbon dots (CDs) have shown great potential as photosensitizers in PDT of cancers due to their excellent biocompatibility and high generation of reactive oxygen species (ROS). Here, we used tea polyphenol as raw material for synthesized tea polyphenol carbon dots (T−CDs) that show dual emission bands of red and blue fluorescence and can efficiently generate hydroxyl radicals (OH) under mildly visible irradiation with a LED light (400–500 nm, 15 mW cm−2). The extremely low cytotoxicity and excellent biocompatibility of T−CDs without light irradiation were tested using MTT and hemolytic assay. Further, T−CDs have been shown by in vivo experiments, using a mouse breast cancer cell line (4T1) subcutaneously injected in the back of the mouse buttock as a model, to effectively inhibit the tumor cell proliferation in solid tumors and show an excellent PDT effect. In addition, pathological sections of the mice tissues after further treatment showed that the T−CDs had no apparent impact on the major organs of the mice and did not produce any side effect lesions. This work demonstrates that the as−synthesized T−CDs has the potential to be used as a PS in cancer treatment.
An Efficient Broadband Symmetrical Doherty Power Amplifier With Extended Back-Off Range

In this brief, a symmetrical Doherty power amplifier (DPA) which exhibits enhanced efficiency, bandwidth and output power back-off range by phase compensation, is proposed. This proposed architecture compensates the phase deviation between main and auxiliary amplifiers mainly caused by the load modulation circuit and parasitic parameters of transistors. With phase compensation, both saturation efficiency and bandwidth are significantly improved while maintaining an extended output back-off range. For verification, a 2.05–2.8-GHz symmetrical DPA is designed, fabricated and measured. Under continuous wave excitation, measurement results show that the implemented DPA exhibits drain efficiency of 40%–49% at 9 dB output back-off level and 66%–76% at saturation with a maximum output power of 43.9–44.9-dBm over the entire band.
The Impact of Coping Strategies and Individual Resilience on Anxiety and Depression among Construction Supervisors

Psychosocial working conditions such as long work hours, low job control, and work–life imbalance faced by construction professionals in site management positions subject them to elevated work stress and poor mental health. This study explored the protective ability of resilience and coping strategies in mitigating mental ill-health among construction supervisors in Nigeria. By adopting a mixed methodology, validated psychometric instruments were used to collect data from 174 construction supervisors, and semi-structured interviews involving 13 participants were used to understand better how supervisors cope with stress. The quantitative data were analysed using mean and univariate logistic regression, while qualitative data were thematically analysed. Univariate logistic regression revealed that individual resilience and problem-focused coping (PFC) strategies related to planful problem-solving, positive reappraisal, and seeking social support reduced anxiety symptoms. Aside from the coping skill considered in the quantitative survey, two additional skills adopted by the supervisors were deduced following thematic analysis. On average, the respondents’ depression, anxiety, and resilience levels were within the mild, minimal, and normal range, respectively. Resilience moderated the relationship between coping skills and anxiety by showing that a stronger relationship between the coping strategy and anxiety will be observed among people with a high level of resilience. Resilience, planful problem-solving, positive reappraisal, and seeking social support coping behaviours are significant predictors of mental health. This study highlights the need for resilience-building as an integral part of stress-reduction and management interventions aimed at construction supervisors in the construction industry.
On‐line expectation–maximization algorithm for latent data models

Summary. We propose a generic on‐line (also sometimes called adaptive or recursive) version of the expectation–maximization (EM) algorithm applicable to latent variable models of independent observations. Compared with the algorithm of Titterington, this approach is more directly connected to the usual EM algorithm and does not rely on integration with respect to the complete‐data distribution. The resulting algorithm is usually simpler and is shown to achieve convergence to the stationary points of the Kullback–Leibler divergence between the marginal distribution of the observation and the model distribution at the optimal rate, i.e. that of the maximum likelihood estimator. In addition, the approach proposed is also suitable for conditional (or regression) models, as illustrated in the case of the mixture of linear regressions model.
Thermal-Spike Lifetime from Picosecond-Duration Preequilibrium Effects in Hyperfine Magnetic Fields Following Ion Implantation

The effective hyperfine magnetic fields acting on short-lived excited nuclear states $(27l\ensuremath{\tau}l127\mathrm{ps})$ have been measured for $\ensuremath{\sim}7.5\mathrm{MeV}$ Ir and Pt ions immediately after implantation into iron hosts at room temperature. The observed field strengths decrease with the lifetime of the probe state and are consistent with the hyperfine field being absent for about 6 ps after implantation. As the hyperfine field is quenched while the local temperature exceeds the Curie temperature, these results give a direct measurement of the thermal-spike lifetime.
Fast Multi-Contrast MRI Acquisition by Optimal Sampling of Information Complementary to Pre-Acquired MRI Contrast

Recent studies on multi-contrast MRI reconstruction have demonstrated the potential of further accelerating MRI acquisition by exploiting correlation between contrasts. Most of the state-of-the-art approaches have achieved improvement through the development of network architectures for fixed under-sampling patterns, without considering inter-contrast correlation in the under-sampling pattern design. On the other hand, sampling pattern learning methods have shown better reconstruction performance than those with fixed under-sampling patterns. However, most under-sampling pattern learning algorithms are designed for single contrast MRI without exploiting complementary information between contrasts. To this end, we propose a framework to optimize the under-sampling pattern of a target MRI contrast which complements the acquired fully-sampled reference contrast. Specifically, a novel image synthesis network is introduced to extract the redundant information contained in the reference contrast, which is exploited in the subsequent joint pattern optimization and reconstruction network. We have demonstrated superior performance of our learned under-sampling patterns on both public and in-house datasets, compared to the commonly used under-sampling patterns and state-of-the-art methods that jointly optimize the reconstruction network and the under-sampling patterns, up to 8-fold under-sampling factor.
New stochastic sampling method for region extraction: theory and experiments

We propose a region extraction method based on a new energy function and a new stochastic sampling method. The new energy function is based on the mixed density description derived by clustering an input image using the ISO DATA algorithm. Our energy function is suitable for natural images. We developed a new stochastic sampling method by modifying the conventional Gibbs sampler. The conventional Gibbs sampler converges to global optimum of the energy function, but is cannot be applied to region extraction because of its inability to preserve topological property of the initial region during its state transition process. To overcome this drawback, our sampling process is driven by 'dynamic site selection' which enables to preserve the topology of the initial region in the state transition process. We prove the global convergence property of our proposed sampling method by extending the existing stochastic sampling theories. We demonstrate the performances of our method by simulation studies for both synthetic and natural images.
Outlier mining in high-dimensional data using the Jensen–Shannon divergence and graph structure analysis

Reliable anomaly/outlier detection algorithms have practical applications in many fields. For instance, anomaly detection allows to filter and clean the data used to train machine learning algorithms, improving their performance. However, outlier mining is challenging when the data is high-dimensional, and different approaches have been proposed for different types of data (temporal, spatial, network, etc). Here we propose a methodology to mine outliers in generic datasets in which it is possible to define a meaningful distance between elements of the dataset. The methodology is based on defining a fully connected, undirected graph, where the nodes are the elements of the dataset and the links have weights that are the distances between the nodes. Outlier scores are defined by analyzing the structure of the graph, in particular, by using the Jensen–Shannon (JS) divergence to compare the distributions of weights of different nodes. We demonstrate the method using a publicly available database of credit-card transactions, where some of the transactions are labeled as frauds. We compare with the performance obtained when using Euclidean distances and graph percolation, and show that the JS divergence leads to performance improvement, but increases the computational cost.
Analytic expressions for MOM calculation of capacitance matrix of two dimensional system of conductors and dielectrics having arbitrarily oriented boundaries

In this paper, the calculation of the capacitance matrix of a two-dimensional system in a multilayered dielectric medium (when there are dielectric-to-dielectric boundaries orthogonal to the Y axis only) over a ground plane is extended to cases when there are dielectric-to-dielectric boundaries: orthogonal to Y axis and X axis only; of arbitrary orientation. Complete derivation of final analytical formulae for elements of the S_matrix for the calculation of a capacitance matrix of two-dimensional system of conductors and dielectrics is presented. For extension of the calculation to the case without ground plane the approach of S.M. Rao et al. (1984). is used.
A Game-Theoretic Approach for the Robust Daily Aircraft Routing Problem

In the operation of airlines, the most important link is determining the route and scheduling of aircraft. The key to this problem is to input the flight segment and aircraft type and finally determine all flight segments for each aircraft. In this paper, we focus on finding feasible, robust scheduling for various uncertainties in the flight process. This paper presents a new robust integer mathematical model based on game theory that considers daily aircraft routing. Then, in order to find the suboptimal solution to a large-scale integer programming problem in a limited amount of time, a heuristic algorithm integrating a column generation algorithm and variable domain search is introduced. In addition, we use the data of a Chinese airline to verify, and the experimental results show that the model proposed by us is more robust than the model in general.
Photoassociation of metastable helium

A theoretical study is performed for the photoassociation of metastable helium. Combining short-range, high-level, ab initio calculations for 5Σg/u+ and 5Πg/u symmetries and long-range behaviour, better described in Hund's case (c), potential-energy curves for attractive, 5Σu+ and 5Πg, as well as repulsive, 5Πu and 5Σg+, states of quintet metastable helium molecules dissociating to 2 3S + 2 3P are obtained. Taking into account the atomic spin-orbit couplings, vibrational levels are derived for near-dissociation levels at the 3P2 asymptote. Comparison with results from three recent photoassociation experiments obtained under different conditions (μK temperatures with spin alignment and mK temperatures without) allowed for an assignation of about three quarters of the observed levels. The robustness of the vibrational numbering is confirmed by testing a modification of the short-range potentials.
The Efficacy and Safety of Rituximab in ANCA-Associated Vasculitis: A Systematic Review

Simple Summary ANCA-associated vasculitis (AAV) is a rare disease and manifests in different organs. The exact mechanism of AAV is not fully understood, but it is speculated that it is induced by autoantibody production against proteinase-3 and myeloperoxidase. Patients diagnosed with ANCA-associated vasculitis are challenging to manage and experience several relapses during and after treatment. This systematic review represents the efficacy and safety profile of rituximab in AAV patients and provides evidence that rituximab can be considered the treatment of choice for AAV patients, especially for challenging patients with refractory releases. Abstract Background and aim: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a rare multisystem autoimmune disease developed by autoantibody production against human neutrophilic granulocytes, including proteinase-3 (PR3) and myeloperoxidase (MPO). The management of AAV patients is difficult due to the multiorgan involvement, high rate of relapse, and complications of immunosuppressive agents that make it challenging. This study aims to investigate the efficacy and safety of rituximab (RTX) therapy in patients with granulomatosis with polyangiitis (GPA) or microscopic polyangiitis (MPA) subtypes. Method: The PubMed/Medline database was searched for any studies related to RTX therapy in ANCA-associated vasculitis (GPA and MPA subtypes), from inception to 1 August 2022, and proceeded in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Results: Our search resulted in 1082 initial records. After the elimination of review papers, irrelevant studies, and non-English records, 223 articles were included, and the data related to the efficacy and safety of RTX therapy were extracted. Several randomized and non-randomized studies showed that RTX is an effective treatment option for patients with AAV. Most of the studies showed the very effective effect of RTX in controlling disease in AAV patients, including pediatrics, adults, and elderlies, although RTX cannot completely prevent relapse. However, maintenance therapy helps delay the disease’s relapse and causes sustained remission. Not only the licensed dose (375 mg/m2 intravenous per week for 4 weeks) could induce disease remission, but studies also showed that a single infusion of RTX could be effective. Although RTX could resolve many rare manifestations in AAV patients, there are few reports showing treatment failure. Additionally, few sudies have reported the unexpeted worsening of the disease after RTX administration. Generally, RTX is relatively safe compared to conventional therapies, but some serious adverse effects, mainly infections, cytopenia, hypogammaglobinemia, malignancy, and hypersensitivity have been reported. Conclusions: RTX is an effective and relatively safe therapeutic option for AAV. Studies on the evaluation of the safety profiles of RTX and the prevention of severe RTX-related side effects in AAV patients are required.
Delivery of Melittin as a Lytic Agent via Graphene Nanoparticles as Carriers to Breast Cancer Cells

Melittin, as an agent to lyse biological membranes, may be a promising therapeutic agent in the treatment of cancer. However, because of its nonspecific actions, there is a need to use a delivery method. The conducted research determined whether carbon nanoparticles, such as graphene and graphene oxide, could be carriers for melittin to breast cancer cells. The studies included the analysis of intracellular pH, the potential of cell membranes, the type of cellular transport, and the expression of receptor proteins. By measuring the particle size, zeta potential, and FT-IT analysis, we found that the investigated nanoparticles are connected by electrostatic interactions. The level of melittin encapsulation with graphene was 86%, while with graphene oxide it was 78%. A decrease in pHi was observed for all cell lines after administration of melittin and its complex with graphene. The decrease in membrane polarization was demonstrated for all lines treated with melittin and its complex with graphene and after exposure to the complex of melittin with graphene oxide for the MDA-MB-231 and HFFF2 lines. The results showed that the investigated melittin complexes and the melittin itself act differently on different cell lines (MDA-MB-231 and MCF-7). It has been shown that in MDA-MD-231 cells, melittin in a complex with graphene is transported to cells via caveolin-dependent endocytosis. On the other hand, the melittin–graphene oxide complex can reach breast cancer cells through various types of transport. Other differences in protein expression changes were also observed for tumor lines after exposure to melittin and complexes.
Cavity ring-down lossmeter using a pulsed light emitting diode source and photon counting

A new mode of cavity ring-down measurements in which an incoherent, broadband light emitting diode (LED) is used as the spectroscopic source is described. Light from a pulsed LED (570 nm, 12 nm FWHM) was coupled into a 32 cm linear optical resonator and a ring-down waveform obtained on a gated photon counter. Cavity time constants observed were on the order of 3–4 µs, yielding effective optical path-lengths in excess of 1 km. In an effort to demonstrate the function of the instrument we have measured absorption and Rayleigh scattering by gases introduced into the measurement cell. Measurements of Rayleigh scatter by CO2 and 1,1,1,2 tetrafluoroethane (R-134a) were used to calibrate the instrument. The Rayleigh extinction coefficients determined through the LED–CRD method were found to agree with literature values to within 12% on average. In an additional set of experiments, a laboratory-generated vapour containing either iodine or ozone was introduced into the measurement cell in an effort to demonstrate the technique's ability to monitor absorbing gases. The ring-down time constants (τ) observed were found to decrease by 15–75% when the absorbing gases were added to the measurement cell. The observed decrease in cavity time constant was proportional to the quantity of absorbing gas within the measurement cell. Minimum detectable extinction coefficients (2s) of ≈2.5 × 10−7 cm−1 were achieved. The LED–CRD approach may lead to development of inexpensive gas sensors or monitoring systems for atmospheric extinction/visibility.
Kinetic Exchange between the Conduction Band Electrons and Magnetic Ions in Quantum-Confined Structures

We provide an experimental evidence and a theoretical substantiation for a strong reduction of the $s\ensuremath{-}d$ exchange interaction between electrons and Mn-ion spins with increasing degree of the confinement in nanostructures of diluted magnetic semiconductors. By spin-flip Raman scattering a strong (up to $25%$) reduction of the exchange parameter is observed in $(\mathrm{Cd},\mathrm{Mn})\mathrm{Te}/(\mathrm{Cd},\mathrm{Mn},\mathrm{Mg})\mathrm{Te}$ quantum well structures. As a responsible mechanism we suggest switching-on of the kinetic exchange for the conduction electrons with finite $\mathbf{k}$ vectors. Quantitative agreement between experimental data and calculations is achieved.
Vortex Method for computing high-Reynolds number flows: Increased accuracy with a fully mesh-less formulation.

For the applications of high Reynolds number flows, the vortex method presents the advantage of being free from numerically dissipative truncation error. In practice, however, many vortex methods introduce some numerical dissipation in mesh-based spatial adaption stages, or schemes such as vortex particle splitting. The need for spatial adaption in vortex methods arises from the Lagrangian framework, which results in an increase of discretization error over time. Presently, a vortex method is devised that incorporates radial basis function (RBF) interpolation to provide spatial adaption in a fully mesh-less formulation. Numerical experiments show that there is a potential for higher accuracy in comparison with the standard remeshing techniques. The rate of convergence of the new spatial adaption method is exponential, however convection error limits the vortex method to second order convergence. Avenues for future research involve decreasing convection error, for example by means of deformable basis functions. Nevertheless, the RBF-based spatial adaption scheme has various advantages, in addition to a demonstrated higher accuracy and the obvious benefit of not requiring a regular arrangement of particles or mesh. One presently demonstrated advantage is automatic core size control for the core spreading viscous method, without the need for vortex particle splitting. Three applications have been successfully treated with the presently developed vortex method. The relaxation of monopoles under non-linear perturbations has been computed, resulting in noticeable improvements compared to previously published results. The existence of a quasi-steady state consisting of a rotating tripole has been corroborated, for the case of large amplitude perturbations. The second application consists of the early adaptation of two co-rotating vortices at high Reynolds number, characterized by elliptical deformation of the cores, as well as small scale deformation in the weak areas of vorticity. This is considered to pose a severe test on the present method, or indeed any method. Comparison with results using spectral methods demonstrate in practice the potential for high accuracy computations using a mesh-less method, and in addition show that the naturally adaptive vortex method can result in considerably reduced problem sizes. Finally, for the calculation of non-symmetric Burgers vortices, a correction to the core spreading method for out-of-plane strain was developed. The results establish the capability of the vortex method for the computation of vortices under three-dimensional strain.