Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychological Well-being of Employees, its Precedents and Outcomes: A Literature Review and Proposed Framework

Is the psychological well-being (PWB) of employees essential to be considered by organizations? Does it have an impact on an organization in the long-run? This study attempts to provide a holistic view of literature on PWB and how it has become indispensable for employees and the organization. The study also proposes a framework consisting of precedents and outcomes of PWB of employees in organizations. A review of the literature of 142 studies was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework along with the main construct PWB and ten related organizational variables. PWB has been analysed from a eudaimonic perspective. Literature review reveals the scarcity of management literature on the eudaimonic sense of well-being of employees, and how well-being is not distinguished on the basis of its philosophical roots. Our research discusses the variables which have been studied comprehensively in juxtaposition with well-being, and also those variables which are yet to be explored with eudaimonia as the focus. The study is a novel attempt to systematize literature on the under-examined eudaimonic perspective of PWB of employees and its relationship with prominent organizational variables. The study intends to give practitioners and the managers value adding insights into the factors that affect the PWB of employees and also how these factors can be honed for better employee mental health leading to higher organizational returns.
The SILCC (SImulating the LifeCycle of molecular Clouds) project – I. Chemical evolution of the supernova-driven ISM

The SILCC (SImulating the Life-Cycle of molecular Clouds) project aims to self-consistently understand the small-scale structure of the interstellar medium (ISM) and its link to galaxy evolution. We simulate the evolution of the multiphase ISM in a (500 pc)2 × ±5 kpc region of a galactic disc, with a gas surface density of ΣGAS=10M⊙pc−2. The flash 4 simulations include an external potential, self-gravity, magnetic fields, heating and radiative cooling, time-dependent chemistry of H2 and CO considering (self-) shielding, and supernova (SN) feedback but omit shear due to galactic rotation. We explore SN explosions at different rates in high-density regions (peak), in random locations with a Gaussian distribution in the vertical direction (random), in a combination of both (mixed), or clustered in space and time (clus/clus2). Only models with self-gravity and a significant fraction of SNe that explode in low-density gas are in agreement with observations. Without self-gravity and in models with peak driving the formation of H2 is strongly suppressed. For decreasing SN rates, the H2 mass fraction increases significantly from <10 per cent for high SN rates, i.e. 0.5 dex above Kennicutt–Schmidt, to 70–85 per cent for low SN rates, i.e. 0.5 dex below KS. For an intermediate SN rate, clustered driving results in slightly more H2 than random driving due to the more coherent compression of the gas in larger bubbles. Magnetic fields have little impact on the final disc structure but affect the dense gas (n ≳ 10 cm−3) and delay H2 formation. Most of the volume is filled with hot gas (∼80 per cent within ±150 pc). For all but peak driving a vertically expanding warm component of atomic hydrogen indicates a fountain flow. We highlight that individual chemical species populate different ISM phases and cannot be accurately modelled with temperature-/density-based phase cut-offs.
Network Immunization Strategy by Eliminating Fringe Nodes: A Percolation Perspective

To date, many strategies involving graph theory have been proposed to solve the targeted immunization problem. Among them, the well-known relationship-related (RR) method makes use of the sum rule and the product rule from the perspective of the network explosive percolation. However, the RR method needs to carefully consider all nodes within a network, leading to high computational time. To close this gap, we propose the fringe node set: it is applied to an immunization strategy such as RR to remove noncritical nodes before optimizing the node sequence. Besides adapting this algorithm for strategies, such as RR and degree centrality strategy, we further propose a novel reconstruction method (RM) under the percolation perspective, which ranks critical nodes by measuring their contribution to the giant component in the network reconstruction or node reoccupying process. Experimental results based on our proposed identification method have demonstrated the feasibility of using the fringe node set. The competitive advantage of our proposed RM is also demonstrated in comparison with other existing methods.
An Edge Device for Monitor and Control of Electrical Appliances using Smart Power Line Communication

Smart control and monitoring have been critical in recent times due to the increase in cost and demand for electrical energy. In residential, commercial, and industrial sectors like building energy management, IoT farming, Smart Street Lighting, and Hospitals, Internet of Things (IoT) play a vital role in analyzing the consumption of individual loads. Available smart switches are restricted to changing the switch state (control) using a wireless channel. However, they fail to analyze the consumption of each electrical appliance. Signal propagation is more efficient in the case of low voltage networks by using Power line Communication (PLC). PLC is more convenient in analyzing the electrical consumption of individual loads as it does not require any additional wiring infrastructure. The paper proposes a smarter way of controlling and monitoring the consumption of individual appliances using PLC, IoT Sensors, and the Webserver. The design can be effectively implemented and yields appropriate results, as shown by the field experiments that were conducted and presented.
An indicator of sea ice variability for the Antarctic marginal ice zone

Abstract. Remote-sensing records over the last 40 years have revealed large year-to-year global and regional variability in Antarctic sea ice extent. Sea ice area and extent are useful climatic indicators of large-scale variability, but they do not allow the quantification of regions of distinct variability in sea ice concentration (SIC). This is particularly relevant in the marginal ice zone (MIZ), which is a transitional region between the open ocean and pack ice, where the exchanges between ocean, sea ice and atmosphere are more intense. The MIZ is circumpolar and broader in the Antarctic than in the Arctic. Its extent is inferred from satellite-derived SIC using the 15 %–80 % range, assumed to be indicative of open drift or partly closed sea ice conditions typical of the ice edge. This proxy has been proven effective in the Arctic, but it is deemed less reliable in the Southern Ocean, where sea ice type is unrelated to the concentration value, since wave penetration and free-drift conditions have been reported with 100 % cover. The aim of this paper is to propose an alternative indicator for detecting MIZ conditions in Antarctic sea ice, which can be used to quantify variability at the climatological scale on the ice-covered Southern Ocean over the seasons, as well as to derive maps of probability of encountering a certain degree of variability in the expected monthly SIC value. The proposed indicator is based on statistical properties of the SIC; it has been tested on the available climate data records to derive maps of the MIZ distribution over the year and compared with the threshold-based MIZ definition. The results present a revised view of the circumpolar MIZ variability and seasonal cycle, with a rapid increase in the extent and saturation in winter, as opposed to the steady increase from summer to spring reported in the literature. It also reconciles the discordant MIZ extent estimates using the SIC threshold from different algorithms. This indicator complements the use of the MIZ extent and fraction, allowing the derivation of the climatological probability of exceeding a certain threshold of SIC variability, which can be used for planning observational networks and navigation routes, as well as for detecting changes in the variability when using climatological baselines for different periods.
POTENTIAL–DENSITY PAIRS FOR A FAMILY OF FINITE DISKS

Exact analytical solutions are given for the three finite disks with surface density Σn = σ0(1 − R2/α2)n−1/2withn = 0, 1, 2. Closed-form solutions in cylindrical coordinates are given using only elementary functions for the potential and for the gravitational field of each of the disks. The n = 0 disk is the flattened homeoid for which . Improved results are presented for this disk. The n = 1 disk is the Maclaurin disk for which . The Maclaurin disk is a limiting case of the Maclaurin spheroid. The potential of the Maclaurin disk is found here by integrating the potential of the n = 0 disk over α, exploiting the linearity of Poisson's equation. The n = 2 disk has the surface density ΣD2 = σ0(1 − R2/α2)3/2. The potential is found by integrating the potential of the n = 1 disk.
Fingerprints of the hierarchical building-up of the structure on the gas kinematics of galaxies

Fil: de Rossi, Maria Emilia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Ciudad Universitaria. Instituto de Astronomia y Fisica del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomia y Fisica del Espacio; Argentina
The Role of Kynurenine and Its Metabolites in Comorbid Chronic Pain and Depression

Chronic pain and depression affect millions of people worldwide, and their comorbidity tends to exacerbate the severity of each individual condition. Intersecting brain regions and molecular pathways could probably explain the unique yet complex bidirectional relationship between these two disorders. Recent studies have found that inflammatory reactions, frequently identified in both chronic pain and depression, stimulate certain enzymes in the kynurenine pathway, while concurrently suppressing others. Kynurenine, a major tryptophan derivative, and its metabolites have been implicated in several inflammation-associated pain syndromes and depressive mood disorders. Due to inflammation, 95% of tryptophan is metabolized via the kynurenine pathway, which drives the reaction towards the production of metabolites that have distinct roles in the pathophysiology of these disorders. Diminished levels of the neuroprotective metabolite, kynurenic acid (KYNA), and elevated levels of the neurotoxic metabolite, quinolinic acid (QUIN), have been frequently identified in human patients formally diagnosed with these disorders, as well as animal models commonly used in medical research. This review not only explores the epidemiology of comorbid chronic pain and depression, but also highlights the involvement of kynurenine and its metabolites, specifically KYNA and QUIN, in these pervasive conditions.
Strategic Rhythms: Insights and Research Directions

Strategic rhythms concern how managers intentionally organize strategic activities by mapping them to the time continuum in hopes of improving a firm's long-term prospects. We develop a clear conceptual scope for strategic rhythms research. We take stock of the research on: rhythms of repeated strategic activity (e.g., serial acquisitions); rhythms of multiple strategic activities (e.g., sequencing activities for innovation); and comparison of strategic rhythms (e.g., for the firm, its rivals, the environment). We synthesize this literature in an integrative framework explaining the antecedents, content, and outcomes of strategic rhythms. We identify firm-level and environmental constraints that limit managers’ discretion in enacting strategic rhythms, and we demonstrate two pathways through which managers may loosen those constraints. Finally, we identify promising opportunities for future research and suggest empirical techniques that will likely be useful for studying strategic rhythms.
Quasiprobabilities for multipartite quantum correlations of light

Regular quasiprobabilities are introduced for the aim of characterizing quantum correlations of multimode radiation fields. Negativities of these quantum-correlation quasiprobabilities are necessary and sufficient for any quantum correlation encoded in the multimode Glauber-Sudarshan P function. The strength of the method is demonstrated for a two-mode phase randomized squeezed-vacuum state. It has no entanglement, no quantum discord, a positive Wigner function, and a classical reduced single-mode representation. Our method clearly visualizes the quantum correlations of this state.
Switched-Capacitor Multi-Input Seven-Level Inverter for HFAC Applications

In this paper, a switched-capacitor-derived multi-level inverter (SCMLI) is developed for high-frequency-ac (HFAC) applications. The proposed inverter uses unequal dc voltage sources as its input. It is useful where multiple dc sources with a common ground are available, e.g., renewable energy systems, ac microgrids, fuel cells, and electric vehicles. This topology gives higher voltage levels and adequate reactive power support with fewer power-electronic switches than the existing switched-capacitor multi-level configurations. Capacitor voltage balancing is not required as it’s charged twice in each cycle of the inverter output. Parallel operation of inverters is required while connecting several dc sources. The proposed inverter solves this problem by connecting multiple sources at once. Selective-harmonic-elimination pulse width modulation (SHE-PWM) technique is used to minimize the higher-order harmonics in the output current. Different operating modes of the inverter are explained in adequate detail. A hardware prototype is assembled for the proposed multi-level inverter. The experimental and simulation results corroborate the expected performance of the proposed inverter.
The quantum hydrodynamic description of quantum gases with different interactions

We describe recent development of quantum hydrodynamics for ultracold Bose particle studying and consider different kinds of interactions. The method of derivation of equations describing the evolution of the neutral Bose particle system at low temperatures is described. Despite the fact that we consider the neutral particles we account the short-range interaction between particles. We consider the particles in the Bose-Einstein condensate (BEC) state. This method is called the method of quantum hydrodynamics, because natural for of the quantum mechanics rewritten in terms of material fields of observable quantities in three dimensional space is the set of equations, which look like the hydrodynamics equations. It can be shown that from the quantum hydrodynamics equations can be derived macroscopic non-linear Schrodinger equation. Most famous non-linear Schrodinger equation is the Gross-Pitaevskii (GP) equation, which contains nonlinearity of the third degree. There are generalizations of the GP equation. New term appears in the GP equation at account of the three-particle interaction. This term contains nonlinearity of the fifth degree. At more detailed account of the two particle interaction we come to the nonlocal non-linear Schrodinger equation. This equation contains spatial derivatives of the order parameter in the non-linear terms caused by the interaction. In this terminology the GP equation corresponds to the first order by the interaction radius. For the BEC of the neutral particles with anisotropic long-range dipole-dipole interaction the generalization of the GP equation was also suggested. Detailed analyses of the applicability conditions shows that this equation valid for the system of dipoles parallel to each other, which do not change their direction, and where the dipole-dipole interaction interferences translational motion of particles.
Nonlocal stability analysis of the MHD Kelvin-Helmholtz instability in a compressible plasma. [solar wind-magnetosphere interaction]

A general stability analysis is performed for the Kelvin-Helmholtz instability in sheared magnetohydrodynamic flow of finite thickness in a compressible plasma. The analysis allows for arbitrary orientation of the magnetic field B0, velocity flow v0, and wave vector k in the plane perpendicular to the velocity gradient, and no restrictions are imposed on the sound or Alfven Mach numbers. The stability problem is reduced to the solution of a single second-order differential equation, which includes a gravitational term to represent coupling between the Kelvin-Helmholtz mode and the interchange mode. In the incompressible limit it is shown that the Kelvin-Helmholtz mode is completely stabilized for any velocity profile as long as the condition is satisfied, where V0 is the total velocity jump across the shear layer. Numerical results are obtained for a hyperbolic tangent velocity profile for the transverse (B0 ⊥ v0) and parallel (B0∥v0) flow configurations. Only modes with kΔ < 2 are unstable, where Δ is the scale length of the shear layer. The fastest growing modes occur for kΔ ∼ 0.5-1.0. Compressibility and a magnetic field component parallel to the flow are found to be stabilizing effects. For the transverse case, only the fast magnetosonic mode is destabilized, but if k · B0 ≠ 0, the instability contains Alfven-mode and slow-mode components as well. The Alfven component gives rise to a field-aligned current inside the shear layer. In the parallel case, both Alfven and slow magnetosonic components are present, with the Alfven mode confined inside the shear layer. The results of the analysis are used to discuss the stability of sheared plasma flow at the magnetopause boundary and in the solar wind. At the magnetopause boundary, the fastest growing Kelvin-Helmholtz mode has a frequency of 0 (V0/2Δ), which overlaps with the frequency range of geomagnetic pulsations (Pc 3-5). It is suggested that the MHD Kelvin-Helmholtz instability could serve as a dynamo process driving small-scale field-aligned currents in the presence of the sheared plasma flow in the magnetosphere.
Zero-Aware Fine-Grained Power Gating for Standard-Cell Memories in Voltage-Scaled Circuits

This paper proposes a standard-cell memory structure with fine-grained power gating techniques for low voltage circuits. Focusing on the fact that a number of zeros appear in many applications such as artificial intelligence, power gating techniques are applied to bit cells storing zeroes only. After describing a standard-cell structure which is suitable for fine-grained power gating, this paper proposes a memory cell structure with a built-in power switch. By finely and dynamically powering off only the latch cells storing zeroes only, leakage energy can be reduced while we can fully access the entire memory data. Experimental results using a 55-nm commercial process technology show that up to 33% leakage energy consumption can be reduced.
Nucleosynthesis in thermonuclear supernovae with tracers: convergence and variable mass particles

Nucleosynthetic yield predictions for multidimensional simulations of thermonuclear supernovae generally rely on the tracer particle method to obtain isotopic information of the ejected material for a given supernova simulation. We investigate how many tracer particles are required to determine converged integrated total nucleosynthetic yields. For this purpose, we conduct a resolution study in the number of tracer particles for different hydrodynamical explosion models at fixed spatial resolution. We perform hydrodynamic simulations on a co-expanding Eulerian grid in two dimensions assuming rotational symmetry for both pure deflagration and delayed detonation Type Ia supernova explosions. Within a given explosion model, we vary the number of tracer particles to determine the minimum needed for the method to give a robust prediction of the integrated yields of the most abundant nuclides. For the first time, we relax the usual assumption of constant tracer particle mass and introduce a radially varying distribution of tracer particle masses. We find that the nucleosynthetic yields of the most abundant species (mass fraction > 10 -5 ) are reasonably well predicted for a tracer number as small as 32 per axis and direction - more or less independent of the explosion model. We conclude that the number of tracer particles that were used in extant published works appear to have been sufficient as far as integrated yields are concerned for the most copiously produced nuclides. Additionally we find that a suitably chosen tracer mass distribution can improve convergence for nuclei produced in the outer layer of the supernova, where the constant tracer mass prescription suffers from poor spatial resolution.
Terahertz-driven, all-optical electron gun

Ultrashort electron beams with narrow energy spread, high charge, and low jitter are essential for resolving phase transitions in metals, semiconductors, and molecular crystals. These semirelativistic beams, produced by phototriggered electron guns, are also injected into accelerators for x-ray light sources. The achievable resolution of these time-resolved electron diffraction or x-ray experiments has been hindered by surface field and timing jitter limitations in conventional RF guns, which thus far are 96 fs, respectively. A gun driven by optically-generated single-cycle THz pulses provides a practical solution to enable not only GV/m surface fields but also absolute timing stability, since the pulses are generated by the same laser as the phototrigger. Here, we demonstrate an all-optical THz gun yielding peak electron energies approaching 1 keV, accelerated by 300 MV/m THz fields in a novel micron-scale waveguide structure. We also achieve quasimonoenergetic, sub-keV bunches with 32 fC of charge, which can already be used for time-resolved low-energy electron diffraction. Such ultracompact, easy to implement guns driven by intrinsically synchronized THz pulses that are pumped by an amplified arm of the already present photoinjector laser provide a new tool with potential to transform accelerator based science.
Output‐feedback robust control of systems with uncertain dynamics via data‐driven policy learning

In this article, we develop two online learning techniques to address the output‐feedback robust control problem of systems with uncertain dynamics. For this purpose, an equivalence is first constructed between the robust control problem of the uncertain systems and the optimal control problem of the nominal systems. Then, an output algebraic Riccati equation (OARE) is constructed using its state‐feedback control counterpart, which can be adopted to realize the online learning. To obtain the online solution of the OARE, an online policy learning (PL) algorithm based on the state reconstruction (SR) is first presented, where the unknown system internal states can be reconstructed via using the input–output information. To further relax the requirement on the system internal states, a novel online PL method is designed, where only the system output information is required, thus the observer or SR is removed in this online PL algorithm. Simulations are provided to test the developed online learning methods.