Empirical Determination Research Articles

Empirical Determination of Scattering Matrices from Magnetic Molecular Interferometry for Gas–Surface Collisions

Empirical Determination of Scattering Matrices from Magnetic Molecular Interferometry for Gas–Surface Collisions

Empirical Determination of the Internal Energy, Enthalpy, Helmholtz Free Energy and Gibbs Free Energy of Polyethylene When One of the Thermodynamic Factors, Pressure, Volume, Temperature and Entropy, is Constant

In a previous report the internal energy, U, enthalpy, H, Helmholtz free energy, A, and Gibbs free energy, G, of polyethylene (PE) were determined when two of the thermodynamic factors X or Y were constant, where X and Y were two of the four factors, pressure, P, volume, V, temperature, T, and entropy, S. In this work these various energies were evaluated when one of the four thermodynamic factors is constant based on the thermodynamic conditions. In the case of the isothermal process with T = const, the internal energy was expressed by U T, enthalpy by H T, Helmholtz free energy by A T and Gibbs free energy by G T. The heat, TS T , and the work, PTV T, in the isothermal process were evaluated based on the thermodynamic relation that H T − G T = TS T and H T − U T = P T V T . In the isothermal process the changes of PTV T were large and dominant compared to those of TS T when V T, S T and P T increased independently under constant T, while the changes of TS T were small and almost constant at constant T. The isobaric process with P = const was characterized by the changes of TPS P being large and dominant compared to those of PV P when V P, S P and T P increased independently under constant P, while the isoentropic process with S = const was characterized by the changes of PSV S being large and dominant compared to those of TSS when T S, P S and V S increased independently under constant S where the subscripts, T, P, S, mean the isothermal, isobaric and isoentropic ensembles, respectively.

Empirical Determinants of Innovation in European Countries: Firm-level Analysis Based on CIS 2018

This study examines the role of perceptions about environmental regulations and their influence on the innovative performance and productivity of firms in Germany, Southern Europe, and Central and Eastern Europe. Utilizing the CDM model for innovative performance and data stemming from the Community Innovation Survey (CIS), we explore the alignment with the Porter hypothesis, which posits that well-designed environmental regulations can stimulate technological innovation and enhance market competitiveness. Our findings present a mixed view: in Germany, positive perceptions about environmental regulations correlate with the initiation of innovation activities, contributing to an increase in labour productivity. This supports the Porter hypothesis, evidencing that regulations can lead to beneficial ‘innovation offsets’ such as reduced resource use and pollution. Conversely, in Southern Europe and Central and Eastern Europe, the perceptions about these regulations on innovation activities are insignificant, with no considerable correlation observed between perceptions about environmental regulations and innovation output. Our findings are crucial for policymakers, environmental regulators, and business leaders aiming to leverage environmental regulations to boost innovation and competitiveness within their regions.

Connecting integrated red giant branch mass loss from asteroseismology and globular clusters

Asteroseismic investigations of solar-like oscillations in giant stars enable the derivation of their masses and radii. For mono-age mono-metallicity populations of stars, this allows the integrated red giant branch (RGB) mass loss to be estimated by comparing the median mass of the low-luminosity RGB stars to that of the helium-core-burning (HeCB) stars. We aim to exploit quasi-mono-age mono-metallicity populations of field stars in the alpha -rich sequence of the Milky Way (MW) to derive the integrated mass loss and its dependence on metallicity. By comparison to metal-rich globular clusters (GCs), we wish to determine whether the RGB mass loss differs in the two environments. We used catalogues of asteroseismic parameters based on time-series photometry from the Kepler and K2 missions cross-matched to spectroscopic information from APOGEE-DR17, photometry from 2MASS, parallaxes from Gaia DR3, and reddening maps. We determined the RGB mass loss by comparing mass distributions of RGB and HeCB stars in three metallicity bins. For two GCs, the mass loss is derived from colour--magnitude diagrams. We find the integrated RGB mass loss to increase with decreasing metallicity and/or mass in the Fe/H range from $-0.9$ to $+0.0$. At Fe/H =$-0.50,$ the RGB mass loss of MW alpha -rich field stars is compatible with that in GCs of the same metallicity. We provide novel empirical determinations of the integrated mass loss connecting field stars and GC stars at comparable metallicities. These show that mass loss cannot be accurately described by a Reimers mass-loss law with a single value of eta . This should encourage further development of the theory underlying processes involved in mass loss.

Indoor environmental quality assessment in passively ventilated classrooms in Germany and estimation of ventilation energy losses

In this field study we present an approach for the comprehensive and room-specific assessment of parameters with the overall aim to realize energy-efficient provision of hygienically harmless and thermally comfortable indoor environmental quality in naturally ventilated non-residential buildings. The approach is based on (i) conformity assessment of room design parameters, (ii) empirical determination of theoretically expected occupant-specific supply air flow rates and corresponding air exchange rates, (iii) experimental determination of real occupant-specific supply air flow rates and corresponding air exchange rates, (iv) measurement of indoor environmental exposure conditions of T, RH, cCO2, cPM2.5 and cTVOC, and (v) determination of real energy demands for the prevailing ventilation scheme. Underlying assessment criteria comprise the indoor environmental parameters of category II of EN 16798-1: Temperature T = 20 °C–24 °C, and relative humidity RH = 25 %–60 % as well as the guide values of the German Federal Environment Agency for cCO2cPM2.5 and cTVOC of 1000 ppm, 15 μg m−3, and 1 mg m−3, respectively.Investigation objects are six naturally ventilated classrooms of a German secondary school. Major factors influencing indoor environmental quality in these classrooms are the specific room volume per occupant and the window opening area. It is concluded that the rigorous implementation of ventilation recommendations laid down by the German Federal Environment Agency is ineffective with respect to anticipated indoor environmental parameters and inefficient with respect to ventilation energy losses on the order of about 10 kWh m−2 a−1 to 30 kWh m−2 a−1.

Constraining the Initial Mass Function via Stellar Transients

The stellar initial mass function (IMF) represents a fundamental quantity in astrophysics and cosmology describing the mass distribution of stars from low mass all the way up to massive and very massive stars. It is intimately linked to a wide variety of topics, including stellar and binary evolution, galaxy evolution, chemical enrichment, and cosmological reionization. Nonetheless, the IMF still remains highly uncertain. In this work, we aim to determine the IMF with a novel approach based on the observed rates of transients of stellar origin. We parametrize the IMF with a simple but flexible Larson shape, and insert it into a parametric model for the cosmic UV luminosity density, local stellar mass density, type Ia supernova (SN Ia), core-collapse supernova (CCSN), and long gamma-ray burst (LGRB) rates as a function of redshift. We constrain our free parameters by matching the model predictions to a set of empirical determinations for the corresponding quantities via a Bayesian Markov Chain Monte Carlo method. Remarkably, we are able to provide an independent IMF determination with a characteristic mass mc=0.10−0.08+0.24M⊙ and high-mass slope ξ=−2.53−0.27+0.24 that are in accordance with the widely used IMF parameterizations (e.g., Salpeter, Kroupa, Chabrier). Moreover, the adoption of an up-to-date recipe for the cosmic metallicity evolution allows us to constrain the maximum metallicity of LGRB progenitors to Zmax=0.12−0.05+0.29Z⊙. We also find which progenitor fraction actually leads to SN Ia or LGRB emission (e.g., due to binary interaction or jet-launching conditions), put constraints on the CCSN and LGRB progenitor mass ranges, and test the IMF universality. These results show the potential of this kind of approach for studying the IMF, its putative evolution with the galactic environment and cosmic history, and the properties of SN Ia, CCSN, and LGRB progenitors, especially considering the wealth of data incoming in the future.

Empirical Determination of the Internal Energy, Enthalpy, Helmholtz Free Energy and Gibbs Free Energy of Polyethylene When Two of the Thermodynamic Factors, Pressure, Volume, Temperature and Entropy, are Constant

The internal energy, U, enthalpy, H, Helmholtz free energy, A, and Gibbs free energy, G, of polyethylene (PE) have been determined when two of the thermodynamic factors X and Y are constant where X and Y are pressure, P, volume, V, temperature, T, and entropy, S. We call an ensemble with the thermodynamic factor X being constant an iso-X ensemble, such as that with X = T is an iso-thermal ensemble, iso-T ensemble, while an ensemble with the thermodynamic factors X or Y being constant is an iso-X or iso-Y ensemble, such as that with X = T or Y = P being constant is an iso-thermal or iso-baric ensemble, iso-T or iso-P ensemble. In the case of the iso-T or iso-P ensemble, an increment of the internal energy expressed by dU T,P, was evaluated based on thermodynamic conditions, T = const and P = const, and was given by dU T,P = dU T + dU P where dU T and dU P are the increments of the internal energy for the iso-T and iso-P ensembles, respectively, and the increments occur with the increment of dU T,P simultaneously.

A Systemic Approach to the Determinants of Employability

This paper identifies the economic, sociological, psychological, and managerial approaches to analyzing the determinants of employability, and their limitations, and then proposes an interdisciplinary approach and systemic framework. Through a theoretical analysis, we find that these determinants interact with the internal and external environment of the individual who is integrated within society; has upgradable human and social capital; has a psychological make-up; and lives in a constantly changing socioeconomic context. The complexity of societies, companies, and a globalized economic system induces the use of interdisciplinarity by considering instability, openness, creativity, ambiguity, and paradox. The operationalization of the systems approach is to analyze the internal factors of each subsystem, the interactions between subsystems, and the relationships between subsystems and their environments. Future investigations should seek to identify the empirical determinants of employability through a systemic approach.

Empirical determination of the energy loss of heavy quarks in nuclear collisions at RHIC and LHC energies

Empirical determination of the energy loss of heavy quarks in nuclear collisions at RHIC and LHC energies

Analysing the Potency of a Seasonal Influenza Vaccine Using Reference Antisera from Heterologous Strains.

The potency of inactivated seasonal influenza vaccine is harmonised by establishing the haemagglutinin (HA) content using the compendial single radial diffusion (SRD) method. SRD reagents (antigens and antisera) are prepared, calibrated and distributed by regulatory agencies as standards for potency testing, following the biannual World Health Organization (WHO) announcements of the virus strains suitable for inclusion in the vaccine. The generation of a homologous hyperimmune sheep antiserum constrains the time to vaccine release. This study tests the application of heterologous antisera to determine the potency of influenza vaccine compared to that of a standard homologous antiserum. The results indicate that the selected heterologous sheep antisera directed to seasonal H1N1, H3N2 or B Victoria virus strains can be used to determine the accurate potency of inactivated seasonal influenza vaccines. Individually selected antisera could be useful for two to fourteen seasons. A limitation to the heterologous antiserum approach is the diversity of each individual serum, indicating that the empirical determination of a specific serum is required. This application has the potential to enable the earlier availability of a seasonal vaccine and reduce animal usage.

β Cephei Pulsators in Eclipsing Binaries Observed with TESS

The combined strength of asteroseismology and empirical stellar basic parameter determinations for in-depth asteroseismic analysis of massive pulsators in eclipsing binaries shows great potential for treating the challenging and mysterious discrepancies between observations and models of stellar structure and the evolution of massive stars. This paper compiles a comprehensive list of massive pulsators in eclipsing binary systems observed with TESS. The TESS light curves and discrete Fourier transforms of a sample of 8055 stars of spectral type B0–B3 were examined for eclipses and stellar pulsations, and the ephemerides of the resulting subsample of massive pulsators in eclipsing binaries were computed. This subsample was also crossmatched with existing catalogs of massive pulsators. Until now, fewer than 30 β Cephei pulsators in eclipsing binaries have been reported in the literature. Here we announce a total of 78 pulsators of the β Cephei type in eclipsing binaries, 59 of which are new discoveries. Forty-three are recognized as definite, and 35 are candidate pulsators. Our sample of pulsating massive stars in eclipsing binaries allows for future asteroseismic modeling to better understand the internal mixing profile and to resolve the mass discrepancy in massive stars. We have already started follow-up work on some of the most interesting candidates.

An automated mineralogy derived criterion for clustering ore samples for mineral liberation studies

Correctly determining the optimal grinding size is crucial for mineral processors, yet it poses several challenges. Still popular among practitioners, the empirical determination of the grinding target involves time-consuming and resource-intensive laboratory routines employed for generating quality, recovery and energy curves from which the target size is set. This approach becomes even more challenging for mines with diverse ore textures, requiring extensive testing on numerous samples to accurately capture the behaviour of the entire ore body. Consequently, a more efficient experimental method is highly desirable. A solution for reducing the laboratory effort is clustering samples according to the mineral liberation characteristics. This paper introduces a novel multivariate criterion for statistical clustering of ore samples for mineral liberation studies, derived from SEM-based automated mineralogy data. The criterion considers three variables: two coefficients (named A and k) derived from the exponential correlation equation between degree of liberation and the top size of the size fraction, and the overall degree of liberation, both easily obtained from the liberation spectrum for a top size of 1 mm. The effectiveness of the proposed criterion has been experimentally demonstrated. It was concluded that the clustering process correctly grouped samples with similar mineral liberation characteristics. The clustering approach can be used to significantly reduce the laboratory effort on liberation studies involving a great number of samples of different types of ore. Although developed using iron ore samples, the criterion's theoretical basis suggests its potential for adaptation to other types of ore.

On fuzzy order in fuzzy sets based on t-norm fuzzy arithmetic

In this paper we study some fuzzy order in fuzzy sets based on t-norm fuzzy arithmetic. The definition of the order comes from the extension principle for interval order: a>b iff a−b>0 and from measurement sciences. In measurement sciences the order is given by a comparator whose operation is based on empirical determination of the difference of two input signals. Fuzzy comparison based on fuzzy sets subtraction is considered as an extension of substraction operation, namely a fuzzy set B is greater than a fuzzy set A if B−A is greater than zero in fuzzy arithmetic. In the paper we show that this fuzzy order is irreflexive, transitive, asymmetric and compact, subhomothetic, Archimedean and semi-Ferrers. Our idea refers to the work of M. K. Urbański (Modeling the measurement in algebraic fuzzy structures, Warsaw 2003, in polish) and to the fundamental problems in the measurement theory.

A little mica goes a long way: Impact of phyllosilicates on quartz deformation fabrics in naturally deformed rocks

Quartz deformation fabrics reflect stress and strain conditions in mylonites, and their interpretation has become a mainstay of kinematic and structural analysis. Quantification of grain size and shape and interpretation of textures reflecting deformation mechanisms can provide estimates of flow stress, strain rate, kinematic vorticity, and deformation temperatures. Empirical calibration and determination of quartz flow laws is based on laboratory experiments of pure samples; however, pure quartzite mylonites are relatively uncommon. In particular, phyllosilicates may localize and partition strain that can inhibit or enhance different deformation mechanisms. Experimental results demonstrate that even minor phyllosilicate content (<15 vol%) can dramatically alter the strain behavior of quartz; however, few field studies have demonstrated these effects in a natural setting. To investigate the role of phyllosilicates on quartz strain fabrics, we quantify phyllosilicate content and distribution in quartzite mylonites from the Miocene Raft River detachment shear zone (NW Utah, USA). We use microstructural analysis and electron backscatter diffraction to quantify quartz deformation fabrics and muscovite spatial distribution, and X-ray computed tomography to quantify muscovite content in samples with varying amounts of muscovite collected across the detachment shear zone. Phyllosilicate content has a direct control on quartz deformation mechanisms, and application of piezometers and flow laws based on quartz deformation fabrics yield strain rates and flow stresses that vary by up to two orders of magnitude across our samples. These findings have important implications for the application of flow laws in quartzite mylonites and strain localization mechanisms in mid-crustal shear zones.

Understanding the drivers of the renewable energy transition

Empirical evidence on renewable energy (RE) deployment remains controversial, and little consensus exists on how empirical determinants can shape a country's transition to a low-carbon economy. Using a sample of 38 countries from 2002 to 2020, we apply nonlinear panel data modeling, where the energy transition process can be properly treated. Our empirical results indicate the prominent role of geopolitical risk in influencing the use of RE, depending on the level of gross domestic product (GDP) per capita. Richer countries have a greater capacity to develop clean technologies in times of uncertainty; however, with fewer resources to bear the transition costs, the RE sector in low-income countries is more vulnerable to adverse geopolitical events.

Optimal modeling of nonlinear systems Method of variable injections

Our work addresses a development and justification of the new approach to the modeling of nonlinear systems. Let $\f$ be an unknown input-output map of the system with a random input and output $\y$ and $\x$, respectively. It is assumed that $\y$ and $\x$ are available and covariance matrices formed from $\y$ and $\x$ are known. We determine a model of $\f$ so that an associated error is minimized. To this end, the model $\ttt_p$ is constructed as a sum of $p+1$ particular parts, in the form $\ttt_p (\y) = \sum_{j=0}^{p}G_j H_j Q_j(\vv_j)$ where $G_j$ and $ H_j$, for $j=0,\ldots, p$, are matrices to be determined, and $\vv_j$, for $j=1,\ldots,p$, is a special random vector called the injection. We denote $\vv_0=\y$. Injections $\vv_1,\ldots, \vv_p$ are aimed to diminish the error associated with the proposed model $\ttt_p$. Further, $Q_j$ is a special transform aimed to facilitate the numerical realization of model $\ttt_p$. It is determined in the way allowing us to optimally determine $G_j$ and $ H_j$ as a solution of $p+1$ separate error minimization problems which are simpler than the original minimization problem. The empirical determination of injections $\vv_1,\ldots, \vv_p$ is considered. The proposed method has several degrees of freedom to diminish the associated error. They are `degree' $p$ of $\ttt_p$, choice of matrices $G_0, H_0, \ldots,$ $G_p, H_p$, dimensions of matrices $G_0, H_0, \ldots,$ $G_p, H_p$ and injections $\vv_1,\ldots, \vv_p$, respectively. Four numerical examples are provided. At the end, the open problem is formulated.

Investigating the characteristics of biomass wastes via particle feeder in downdraft gasifier

Particle feeding plays a crucial role in the gasifier due to its effects on the efficiency and performance metrics of the thermochemical process. Investigating particle size distribution's impact on downdraft gasification reactor performance, this study delves into the significance of feedstock characteristics (moisture, volatile matter, fixed carbon, and ash contents) during the particle feeding stage. Various biomass wastes (date palm waste, olive pomace and sewage sludge) at diverse compositions and sizes are subjected to empirical determination of mass flow rates (MFR), power ratings, and storage times for each feedstock. The preheating process in the gasifier is considered, employing both an approximation and analytical solution. In addition, the influence of the equivalence ratio (ER) on the syngas yield is analyzed. The collected data reveals that for average particle size of 200 μm, the highest MFR (in g/min) are 0.518 ± 0.033, 7.691 ± 0.415, and 16.111 ± 1.050, for palm wood biomass, olive pomace and sewage sludge, respectively. Smaller particles (80 μm) led to extended storage times. Moreover, the lumped capacitance approximation method consistently underestimates preheating time, with a percentage error of 6.26%–17.08%. Response surface methodology (RSM) optimization analysis provides optimal gasification conditions for palm wood biomass, olive pomace, and sewage sludge with maximum cold gas efficiencies (CGEs) of 58.01%, 63.29%, and 52.27%. The peak conversion was attained at gasification temperatures of 1089.83 °C, 1151.93 °C, and 1102.91 °C for palm wood biomass, olive pomace, and sewage sludge, respectively. In addition, gasification equilibrium model determined optimal gasification temperatures as 1150 °C for palm biomass, 1200 °C for olive pomace, and 1150 °C for sewage sludge with respective syngas efficiencies of 59.62%, 64.13%, and 53.66%. Consequently, the examination of the dosing procedure, preheating dynamics, particle dimensions, ER, storage time, and their combined impacts offer practical insights to effectively control downdraft gasifiers in handling a variety of feedstocks.

A single-cell genomic strategy for alternative transcript start sites identification.

Alternative transcription start sites (TSSs) usage plays a critical role in gene transcription regulation in mammals. However, precisely identifying alternative TSSs remains challenging at the genome-wide level. We report a single-cell genomic technology for alternative TSSs annotation and cell heterogeneity detection. In the method, we utilize Fluidigm C1 system to capture individual cells of interest, SMARTer cDNA synthesis kit to recover full-length cDNAs, then dual priming oligonucleotide system to specifically enrich TSSs for genomic analysis. We apply this method to a genome-wide study of alternative TSSs identification in two different IFN-β stimulated mouse embryonic fibroblasts (MEFs). The data clearly discriminate two IFN-β stimulated MEFs. Moreover, our results indicate 81% expressed genes in these two cell types containing multiple TSSs, which is much higher than previous predictions based on Cap-Analysis Gene Expression (CAGE) (58%) or empirical determination (54%) in various cell types. This indicates that alternative TSSs are more pervasive than expected and implies our strategy could position them at an unprecedented sensitivity. It would be helpful for elucidating their biological insights in future.

Empirical Determinants of Research and Development (R&D) Investment in Chinese Manufacturing Companies

Background and Aim: As manufacturing enters the fourth industrial revolution, R&D investments help in converting new ideas into innovative products and services. Manufacturing firms rely on R&D projects to improve product quality, increase productivity, reduce waste, and enhance operational efficiency. This study examined the empirical determinants of Research and Development (R&D) investment in Chinese manufacturing companies. Materials and Methods: Data was obtained from the Oriana database, which keeps updated records regarding R&D investments across Southeast Asia. The database provides information about key R&D drivers and resources that companies are willing to invest as percentages of their revenues. A systematic analysis of data was used to identify the key determinants and their impact on R&D decisions and intensity. The FE model equations were used for calculating correlational relationships among variables. Results: The study found that key determinants associated with R&D decisions and intensity include firm size, market power, demand-pull, technology opportunity, and appropriability. Technology opportunity and demand-pull had the strongest influence on R&D decisions and intensity. Firm size also showed a significant influence on research intensity and development decisions. However, market power showed limited impact on both R&D decisions and intensity. Conclusion: Technology opportunity and demand-pull are the key determinants of Research and Development (R&D) investment in Chinese manufacturing companies.

Empirical Determination of the Pressure-Volume-Temperature-Entropy Equation of State of Polyethylene in Isothermal, Isobaric and Isochoric Ensembles: V. The Internal Energy, Enthalpy, Helmholtz Free Energy and Gibbs Free Energy for the Various Ensembles

The internal energy, U, enthalpy, H, Helmholtz free energy, A, and Gibbs free energy, G, for the isothermal, isobaric, isochoric and isoentropic ensembles for polyethylene (PE) have been determined over a range of temperature, including the zero Kelvin, using the intrinsic equation of states based on the pressure-volume-temperature-entropy equations of state, P-V-T-S Eos determined in our previous reports. Each energy function was separated into its two parts; the energy = (the energy- the energy (0 K)) and the energy (0 K) where the energy (0 K) is the energy at the zero Kelvin. The energy (0 K) was much larger than the former, (the energy- the energy (0 K)), for the internal energy in the isobaric ensemble, the enthalpy in the isothermal, isochoric and isoentropic ensembles and the Gibbs free energy in the isothermal, isochoric and isoentropic ensembles, while the energy (0 K) was negligibly small for the internal energy in the isothermal ensemble and the Helmholtz free energy in the isothermal and isoentropic ensembles. The energy derivatives intrinsic to each ensemble, such as ( ∂ U ∂ T ) P , ( ∂ H ∂ T ) V , ( ∂ A ∂ V ) S , ( ∂ G ∂ P ) S , were evaluated where the subscripts, P, V, S, mean the isobaric, the isochoric and the isoentropic ensembles, respectively.