15,335 research outputs found

    HR Analytics: Concept, Application, and Impact on Talent Management, Branding, and Challenges

    Get PDF
    Purpose: Making wiser decisions about employees to improve performance at the individual and/or organizational levels is the process of HR analytics. HR analytics is a method for determining the correlation between HR practices and organizational performance outcomes such as sales volume or customer satisfaction. Human Resource Analytics was established in 1978 by Jac Fitz-Enz, the pioneer of human capital strategic analysis and performance benchmarking. In this paper, the researcher wants to discuss the concept of HR analytics, its application, impact on talent management, branding, and challenges in its application.Design/methodology/approach: The researcher examines secondary data and conducts a thorough literature review to understand the concept and its application across industries and nations, as well as to identify any challenges encountered during deployment and any benefits perceived by various industry professionals. Findings: The study's findings indicate that using HR analytics can help businesses build their brand and gain a competitive edge in today's fiercely competitive business environment while also enhancing workforce and employee productivity.Originality/value: This study has significant implications for both literature and HR analytics. Researchers will know more about the factors that contribute to and the mechanisms by which HR analytics improve organisational performance. The author's second claim is that having access to HR technology both facilitates and precedes HR analytics. Finally, concrete data from the literature demonstrates its influence on branding and organisational success. Keywords: Human resource (HR) analytics, People analytics, Branding, Talent Management, Organizational performance. Paper type: Research paper JEL Code: M12, M15 & M51 DOI: 10.7176/EJBM/15-8-06 Publication date: April 30th 202

    Chiral active fluids: Odd viscosity, active turbulence, and directed flows of hydrodynamic microrotors

    Get PDF
    While the number of publications on rotating active matter has rapidly increased in recent years, studies on purely hydrodynamically interacting rotors on the microscale are still rare, especially from the perspective of particle based hydrodynamic simulations. The work presented here targets to fill this gap. By means of high-performance computer simulations, performed in a highly parallelised fashion on graphics processing units, the dynamics of ensembles of up to 70,000 rotating colloids immersed in an explicit mesoscopic solvent consisting out of up to 30 million fluid particles, are investigated. Some of the results presented in this thesis have been worked out in collaboration with experimentalists, such that the theoretical considerations developed in this thesis are supported by experiments, and vice versa. The studied system, modelled in order to resemble the essential physics of the experimentally realisable system, consists out of rotating magnetic colloidal particles, i.e., (micro-)rotors, rotating in sync to an externally applied magnetic field, where the rotors solely interact via hydrodynamic and steric interactions. Overall, the agreement between simulations and experiments is very good, proving that hydrodynamic interactions play a key role in this and related systems. While already an isolated rotating colloid is driven out of equilibrium, only collections of two or more rotors have experimentally shown to be able to convert the rotational energy input into translational dynamics in an orbital rotating fashion. The rotating colloids inject circular flows into the fluid, such that detailed balance is broken, and it is not a priori known whether equilibrium properties of colloids can be extended to isolated rotating colloids. A joint theoretical and experimental analysis of isolated, pairs, and small groups of hydrodynamically interacting rotors is given in chapter 2. While the translational dynamics of isolated rotors effectively resemble the dynamics of non-rotating colloids, the orbital rotation of pairs of rotors can be described with leading order hydrodynamics and a two-dimensional analogy of Faxén’s law is derived. In chapter 3, a homogeneously distributed ensemble of rotors (bulk) as a realisation of a chiral active fluid is studied and it is explicitly shown computationally and experimentally that it carries odd viscosity. The mutual orbital translation of rotors and an increase of the effective solvent viscosity with rotor density lead to a non-monotonous behaviour of the average translational velocity. Meanwhile, the rotor suspension bears a finite osmotic compressibility resulting from the long-ranged nature of hydrody- namic interactions such that rotational and odd stresses are transmitted through the solvent also at small and intermediate rotor densities. Consequently, density inhomogeneities predicted for chiral active fluids with odd viscosity can be found and allow for an explicit measurement of odd viscosity in simulations and experiments. At intermediate densities, the collective dynamics shows the emergence of multi-scale vortices and chaotic motion which is identified as active turbulence with a self-similar power-law decay in the energy spectrum, showing that the injected energy on the rotor scale is transported to larger scales, similar to the inverse energy cascade of clas- sical two-dimensional turbulence. While either odd viscosity or active turbulence have been reported in chiral active matter previously, the system studied here shows that the emergence of both simultaneously is possible resulting from the osmotic compressibility and hydrodynamic mediation of odd and active stresses. The collective dynamics of colloids rotating out of phase, i.e., where a constant torque instead of a constant angular velocity is applied, is shown to be qualitatively very similar. However, at smaller densities, local density inhomogeneities imply position dependent angular velocities of the rotors resulting from inter-rotor friction. While the friction of a quasi-2D layer of active colloids with the substrate is often not easily modifiable in experiments, the incorporation of substrate friction into the simulation models typically implies a considerable increase in computational effort. In chapter 4, a very efficient way of incorporating the friction with a substrate into a two-dimensional multiparticle collision dynamics solvent is introduced, allowing for an explicit investigation of the influences of substrate on active dynamics. For the rotor fluid, it is explicitly shown that the influence of the substrate friction results in a cutoff of the hydrodynamic interaction length, such that the maximum size of the formed vortices is controlled by the substrate friction, also resulting in a cutoff in the energy spectrum, because energy is taken out of the system at the respective length. These findings are in agreement with the experiments. Since active particles in confinement are known to organise in states of collective dynamics, ensembles of rotationally actuated colloids are studied in circular confinement and in the presence of periodic obstacle lattices in chapters 5 and 6, respectively. The results show that the chaotic active turbulent transport of rotors in suspension can be enhanced and guided resulting from edge flows generated at the boundaries, as has recently been reported for a related chiral active system. The consequent collective rotor dynamics can be regarded as a superposition of active turbulent and imposed flows, leading to on average stationary flows. In contrast to the bulk dynamics, the imposed flows inject additional energy into the system on the long length scales, and the same scaling behaviour of the energy spectrum as in bulk is only obtained if the energy injection scales, due to the mutual generation of rotor translational dynamics throughout the system and the edge flows, are well separated. The combination of edge flow and entropic layering at the boundaries leads to oscillating hydrodynamic stresses and consequently to an oscillating vorticity profile. In the presence of odd viscosity, this consequently leads to non-trivial steady-state density modulations at the boundary, resulting from a balance of osmotic pressure and odd stresses. Relevant for the efficient dispersion and mixing of inert particles on the mesoscale by means of active turbulent mixing powered by rotors, a study of the dynamics of a binary mixture consisting out of rotors and passive particles is presented in chapter 7. Because the rotors are not self-propelled, but the translational dynamics is induced by the surrounding rotors, the passive particles, which do not inject further energy into the system, are transported according to the same mechanism as the rotors. The collective dynamics thus resembles the pure rotor bulk dynamics at the respective density of only rotors. However, since no odd stresses act between the passive particles, only mutual rotor interactions lead to odd stresses leading to the accumulation of rotors in the regions of positive vorticity. This density increase is associated with a pressure increase, which balances the odd stresses acting on the rotors. However, the passive particles are only subject to the accumulation induced pressure increase such that these particles are transported into the areas of low rotor concentration, i.e., the regions of negative vorticity. Under conditions of sustained vortex flow, this results in segregation of both particle types. Since local symmetry breaking can convert injected rotational into translational energy, microswimmers can be constructed out of rotor materials when a suitable breaking of symmetry is kept in the vicinity of a rotor. One hypothetical realisation, i.e., a coupled rotor pair consisting out of two rotors of opposite angular velocity and of fixed distance, termed a birotor, are studied in chapter 8. The birotor pumps the fluid into one direction and consequently translates into the opposite direction, and creates a flow field reminiscent of a source doublet, or sliplet flow field. Fixed in space the birotor might be an interesting realisation of a microfluidic pump. The trans- lational dynamics of a birotor can be mapped onto the active Brownian particle model for single swimmers. However, due to the hydrodynamic interactions among the rotors, the birotor ensemble dynamics do not show the emergence of stable motility induced clustering. The reason for this is the flow created by birotor in small aggregates which effectively pushes further arriving birotors away from small aggregates, which eventually are all dispersed by thermal fluctuations

    Vegetation responses to variations in climate: A combined ordinary differential equation and sequential Monte Carlo estimation approach

    Get PDF
    Vegetation responses to variation in climate are a current research priority in the context of accelerated shifts generated by climate change. However, the interactions between environmental and biological factors still represent one of the largest uncertainties in projections of future scenarios, since the relationship between drivers and ecosystem responses has a complex and nonlinear nature. We aimed to develop a model to study the vegetation’s primary productivity dynamic response to temporal variations in climatic conditions as measured by rainfall, temperature and radiation. Thus, we propose a new way to estimate the vegetation response to climate via a non-autonomous version of a classical growth curve, with a time-varying growth rate and carrying capacity parameters according to climate variables. With a Sequential Monte Carlo Estimation to account for complexities in the climate-vegetation relationship to minimize the number of parameters. The model was applied to six key sites identified in a previous study, consisting of different arid and semiarid rangelands from North Patagonia, Argentina. For each site, we selected the time series of MODIS NDVI, and climate data from ERA5 Copernicus hourly reanalysis from 2000 to 2021. After calculating the time series of the a posteriori distribution of parameters, we analyzed the explained capacity of the model in terms of the linear coefficient of determination and the parameters distribution variation. Results showed that most rangelands recorded changes in their sensitivity over time to climatic factors, but vegetation responses were heterogeneous and influenced by different drivers. Differences in this climate-vegetation relationship were recorded among different cases: (1) a marginal and decreasing sensitivity to temperature and radiation, respectively, but a high sensitivity to water availability; (2) high and increasing sensitivity to temperature and water availability, respectively; and (3) a case with an abrupt shift in vegetation dynamics driven by a progressively decreasing sensitivity to water availability, without any changes in the sensitivity either to temperature or radiation. Finally, we also found that the time scale, in which the ecosystem integrated the rainfall phenomenon in terms of the width of the window function used to convolve the rainfall series into a water availability variable, was also variable in time. This approach allows us to estimate the connection degree between ecosystem productivity and climatic variables. The capacity of the model to identify changes over time in the vegetation-climate relationship might inform decision-makers about ecological transitions and the differential impact of climatic drivers on ecosystems.Estación Experimental Agropecuaria BarilocheFil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Bruzzone, Octavio Augusto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Perri, Daiana Vanesa. Instituto Nacional de Tecnologia Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Naturales; ArgentinaFil: Perri, Daiana Vanesa. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Easdale, Marcos Horacio. Instituto Nacional de Tecnologia Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Naturales; ArgentinaFil: Easdale, Marcos Horacio. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentin

    Inferring networks from time series: a neural approach

    Full text link
    Network structures underlie the dynamics of many complex phenomena, from gene regulation and foodwebs to power grids and social media. Yet, as they often cannot be observed directly, their connectivities must be inferred from observations of their emergent dynamics. In this work we present a powerful and fast computational method to infer large network adjacency matrices from time series data using a neural network. Using a neural network provides uncertainty quantification on the prediction in a manner that reflects both the non-convexity of the inference problem as well as the noise on the data. This is useful since network inference problems are typically underdetermined, and a feature that has hitherto been lacking from network inference methods. We demonstrate our method's capabilities by inferring line failure locations in the British power grid from observations of its response to a power cut. Since the problem is underdetermined, many classical statistical tools (e.g. regression) will not be straightforwardly applicable. Our method, in contrast, provides probability densities on each edge, allowing the use of hypothesis testing to make meaningful probabilistic statements about the location of the power cut. We also demonstrate our method's ability to learn an entire cost matrix for a non-linear model from a dataset of economic activity in Greater London. Our method outperforms OLS regression on noisy data in terms of both speed and prediction accuracy, and scales as N2N^2 where OLS is cubic. Since our technique is not specifically engineered for network inference, it represents a general parameter estimation scheme that is applicable to any parameter dimension

    Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Review

    Full text link
    In this paper, a critical bibliometric analysis study is conducted, coupled with an extensive literature survey on recent developments and associated applications in machine learning research with a perspective on Africa. The presented bibliometric analysis study consists of 2761 machine learning-related documents, of which 98% were articles with at least 482 citations published in 903 journals during the past 30 years. Furthermore, the collated documents were retrieved from the Science Citation Index EXPANDED, comprising research publications from 54 African countries between 1993 and 2021. The bibliometric study shows the visualization of the current landscape and future trends in machine learning research and its application to facilitate future collaborative research and knowledge exchange among authors from different research institutions scattered across the African continent

    Interview with Wolfgang Knauss

    Get PDF
    An oral history in four sessions (September 2019–January 2020) with Wolfgang Knauss, von Kármán Professor of Aeronautics and Applied Mechanics, Emeritus. Born in Germany in 1933, he speaks about his early life and experiences under the Nazi regime, his teenage years in Siegen and Heidelberg during the Allied occupation, and his move to Pasadena, California, in 1954 under the sponsorship of a local minister and his family. He enrolled in Caltech as an undergraduate in 1957, commencing a more than half-century affiliation with the Institute and GALCIT (today the Graduate Aerospace Laboratories of Caltech). He recalls the roots of his interest in aeronautics, his PhD solid mechanics studies with his advisor, M. Williams, and the GALCIT environment in the late 1950s and 1960s at the dawn of the Space Age, including the impact of Sputnik and classes with NASA astronauts. He discusses his experimental and theoretical work on materials deformation, dynamic fracture, and crack propagation, including his solid-propellant fuels research for NASA and the US Army, wide-ranging programs with the US Navy, and his pioneering micromechanics investigations and work on the time-dependent fracture of polymers in the 1990s. He offers his perspective on GALCIT’s academic culture, its solid mechanics and fluid mechanics programs, and its evolving administrative directions over the course of five decades, as well as its impact and reputation both within and beyond Caltech. He describes his work with Caltech’s undergraduate admissions committee and his scientific collaborations with numerous graduate students and postdocs and shares his recollections of GALCIT and other Caltech colleagues, including C. Babcock, D. Coles, R.P. Feynman, Y.C. Fung, G. Neugebauer, G. Housner, D. Hudson, H. Liepmann, A. Klein, G. Ravichandran, A. Rosakis, A. Roshko, and E. Sechler. Six appendices contributed by Dr. Knauss, offering further insight into his life and career, also form part of this oral history and are cross-referenced in the main text

    Statistical-dynamical analyses and modelling of multi-scale ocean variability

    Get PDF
    This thesis aims to provide a comprehensive analysis of multi-scale oceanic variabilities using various statistical and dynamical tools and explore the data-driven methods for correct statistical emulation of the oceans. We considered the classical, wind-driven, double-gyre ocean circulation model in quasi-geostrophic approximation and obtained its eddy-resolving solutions in terms of potential vorticity anomaly and geostrophic streamfunctions. The reference solutions possess two asymmetric gyres of opposite circulations and a strong meandering eastward jet separating them with rich eddy activities around it, such as the Gulf Stream in the North Atlantic and Kuroshio in the North Pacific. This thesis is divided into two parts. The first part discusses a novel scale-separation method based on the local spatial correlations, called correlation-based decomposition (CBD), and provides a comprehensive analysis of mesoscale eddy forcing. In particular, we analyse the instantaneous and time-lagged interactions between the diagnosed eddy forcing and the evolving large-scale PVA using the novel `product integral' characteristics. The product integral time series uncover robust causality between two drastically different yet interacting flow quantities, termed `eddy backscatter'. We also show data-driven augmentation of non-eddy-resolving ocean models by feeding them the eddy fields to restore the missing eddy-driven features, such as the merging western boundary currents, their eastward extension and low-frequency variabilities of gyres. In the second part, we present a systematic inter-comparison of Linear Regression (LR), stochastic and deep-learning methods to build low-cost reduced-order statistical emulators of the oceans. We obtain the forecasts on seasonal and centennial timescales and assess them for their skill, cost and complexity. We found that the multi-level linear stochastic model performs the best, followed by the ``hybrid stochastically-augmented deep learning models''. The superiority of these methods underscores the importance of incorporating core dynamics, memory effects and model errors for robust emulation of multi-scale dynamical systems, such as the oceans.Open Acces

    Towards a non-equilibrium thermodynamic theory of ecosystem assembly and development

    Get PDF
    Non-equilibrium thermodynamics has had a significant historic influence on the development of theoretical ecology, even informing the very concept of an ecosystem. Much of this influence has manifested as proposed extremal principles. These principles hold that systems will tend to maximise certain thermodynamic quantities, subject to the other constraints they operate under. A particularly notable extremal principle is the maximum entropy production principle (MaxEPP); that systems maximise their rate of entropy production. However, these principles are not robustly based in physical theory, and suffer from treating complex ecosystems in an extremely coarse manner. To address this gap, this thesis derives a limited but physically justified extremal principle, as well as carrying out a detailed investigation of the impact of non-equilibrium thermodynamic constraints on the assembly of microbial communities. The extremal principle we obtain pertains to the switching between states in simple bistable systems, with switching paths that generate more entropy being favoured. Our detailed investigation into microbial communities involved developing a novel thermodynamic microbial community model, using which we found the rate of ecosystem development to be set by the availability of free-energy. Further investigation was carried out using this model, demonstrating the way that trade-offs emerging from fundamental thermodynamic constraints impact the dynamics of assembling microbial communities. Taken together our results demonstrate that theory can be developed from non-equilibrium thermodynamics, that is both ecologically relevant and physically well grounded. We find that broad extremal principles are unlikely to be obtained, absent significant advances in the field of stochastic thermodynamics, limiting their applicability to ecology. However, we find that detailed consideration of the non-equilibrium thermodynamic mechanisms that impact microbial communities can broaden our understanding of their assembly and functioning.Open Acces

    Stratosphere-Troposphere Coupling and Oceanic Feedbacks in an Aquaplanet Model

    Get PDF
    Since the 90’s, there have been many studies looking at the impact of stratospheric temperature perturbations (STP’s) on the troposphere below, and the mechanisms involved. However, it is not well-understood how these interactions might be modified by atmosphere-ocean coupling. This holds particular relevance to the study of e.g. ozone depletion/recovery in the Southern Ocean region. To investigate this, abrupt uniform, polar, and equatorial STP’s – corresponding to different types of forcings - were applied to the atmosphere of MITgcm in an aquaplanet, double-drake configuration. Each was conducted in three different versions of the model: atmosphere-only, atmosphere + slab-ocean, and fully-coupled atmosphere + ocean. In the atmosphere-only model, atmospheric responses similar to those of previous studies were recorded, underscoring their generic nature. In the coupled models, an initial weakening (~decades), and – in the fully coupled model - subsequent strengthening and poleward-shift (~centuries) of the underlying atmospheric response was produced, in polar/equatorial heating experiments. Uniform heating saw the latter process occur initially too. Sea surface temperature (SST) anomalies were found to drive these changes, with extratropical/tropical anomalies controlling the former/latter process. These were in turn attributable to changes in the zonal winds, causing anomalies in the turbulent and ocean heat fluxes, although uniform STP’s saw SST changes that were more controlled by large, near-uniform anomalous downwelling longwave fluxes. Our results highlight the importance of incorporating atmosphere-ocean coupling when studying the effects of STP’s, especially over longer timescales (&100 years). With respect to ozone depletion in the Southern Ocean, they suggest an amplified poleward jet shift which - as greenhouse gases continue to rise – may continue and amplify further into the 21st/22nd century.Open Acces
    corecore