We present a timing-based framework for interpreting braking-index measurements in young pulsars within a four-channel spin-down model that includes particle-wind, magnetic-dipole, mass-quadrupole, and current-quadrupole torques. In this formulation, the observed braking index is a torque-weighted average of the channel exponents, allowing equation-of-state-independent constraints on the torque fraction of a possible r-mode-like current-quadrupole component from timing data alone. For a positive, slowly varying secular model, the physically allowed range is 1 <= n(obs) <= 7. Within this domain, the lower and capped physical upper bounds on the k = 7 torque fraction are f(7,min) = max[0, (n(obs)-5)/2] and f (phys) (7,max) = min{1, max[0, (n(obs)-1)/6]}, respectively. These bounds are conditional on the non-negativity and slow secular evolution of the effective torque coefficients; if these assumptions are relaxed, a large braking index need not uniquely imply a current-quadrupole torque. Applying this bracket analysis to young pulsars with measured braking indices, we find that most sources do not require a gravitational-wave torque and can be explained by wind-plus-dipole electromagnetic spin-down. Sources with 3 < n(obs) < 5 require some higher-order contribution beyond the wind and dipole terms, but timing alone cannot uniquely identify this contribution as an r-mode torque. PSR J0537 -6910 remains the most suggestive case: its large inter-glitch braking index approaches then similar or equal to 7 limit, where the timing bounds are consistent, within the restricted positive secular model, with a strong current-quadrupole-like contribution. This interpretation is not unique, however, because vortex-creep and superfluid-recovery effects can generate similar effective inter-glitch braking behaviour without invoking gravitational-wave emission. We also translate the timing constraints into stellar-model-dependent r-mode amplitude bounds, braking-index-corrected characteristic ages, and gravitational-wave ranking metrics for continuous-wave searches with current and future detectors, including the reduction in sensitivity expected for glitch-limited semi-coherent searches.
Data-driven innovation (DDI) in Human Resource Analytics (HR Analytics) presents a significant potential for strategic organizational change. A persistent gap exists between the theoretical promises of HR Analytics and its practical, value-generating implementation within organizations. This study aims to develop a conceptual model for the effective implementation of HR Analytics within private-sector organizations in a developing economy (Iran), framed through the lens of DDI. Employing a Grounded Theory (GT) approach, specifically the systematic coding methodology of Strauss and Corbin, this research gathered rich qualitative data through in-depth, semi-structured interviews with HR Analytics and Business Analytics experts operating within the Iranian organizational context. Data analysis, facilitated by MAXQDA, involved rigorous open, axial, and selective coding until theoretical saturation was achieved, with study rigor confirmed via Lincoln and Guba's criteria. The resulting conceptual model elucidates the complex interplay of causal conditions (e.g., transformation in human resource management, data-driven approach), context (e.g., technology adoption, cultural contexts), strategies (pre-adoption, decision-making, adoption phases), intervening obstacles, and possible outcomes. By highlighting the contextual features of the Iranian economic environment, this model offers a coherent framework to assist private enterprises in comparable settings to more effectively navigate their transition toward data-driven HR management, offering insights for organizations aiming to leverage HR Analytics as a driver for strategic innovation and business value enhancement.
This study investigated the combined effects of cold plasma (CP) treatment and various concentrations of basil seed gum (BSG) on the functional, structural, and rheological properties of chickpea protein concentrate (CPC) gels. The results demonstrated that optimal CP treatment (40 W for 15 min) induced notable conformational changes in CPC, as revealed by FTIR spectroscopy, with observable shifts in amide and hydroxyl bands, indicating possible enhanced protein-polysaccharide interactions and stronger hydrogen bonding, particularly at higher BSG concentrations. SEM revealed that optimal CP treatment produced compact and homogeneous CPC particles with rougher surfaces, which may facilitate intermolecular interactions. XRD and DSC analyses further revealed that CP treatment reduced protein crystallinity and improved thermal stability, increasing the peak temperature (Tp) from 65.8 to 72.3 degrees C. Concurrently, a reduction in enthalpy from 114.0 to 89.7 J/g indicated partial protein unfolding, which facilitated the formation of a more compact and structurally stable CPC-BSG gel network. Rheological, functional, and textural evaluations showed significant improvements. Comparing plasma-untreated and CP-treated samples at the same basil seed gum concentration (0.6%), the storage modulus (G') increased from 169.37 to 208.99 Pa, water-holding capacity improved from 92.29% to 96.05%, gel hardness increased from 75.50 to 127.00 g, consistency from 3.90 to 7.50 mJ, and adhesiveness from 1.50 to 2.40 mJ. Overall, these findings highlight that moderate cold plasma treatment, when combined with BSG, is an effective strategy to enhance the functional and structural quality of plant-based protein gels, highlighting its potential for developing high-performance, clean-label plant-based gel systems.
A complex coherent system composed of independent subsystems, each containing two dependent components, is considered. A condition-based maintenance policy is extended to this system based on periodic measurements of component degradation levels. Depending on the measured degradation levels, each subsystem is subjected to either replacement, imperfect repair, or no action. The degradation of components is modeled using separate Inverse Gaussian processes, with their dependency captured using copula functions. The main objective is to determine the optimal inspection interval length as well as the degradation threshold that triggers imperfect repair for each component. To achieve this, the long-run cost rate criterion is applied. A sensitivity analysis is conducted, and the optimal policy is derived by solving a constrained optimization problem. The proposed policy is compared to scenarios where either the components are assumed independent or minimal repair is performed in place of imperfect repair
LaNi1-xCoxO3 (x = 0, 0.3, 0.5) perovskite-type oxides were synthesized and evaluated as three-way catalysts (TWCs) for the simultaneous removal of CO, C3H6, and NO from automotive exhaust. TPR results revealed a progressive decrease in reduction temperatures upon cobalt incorporation, attributed to enhanced hydrogen spillover and improved oxygen mobility. FESEM and BET analyses showed pseudo-spherical morphologies with increased macroporosity but reduced surface areas and particle aggregation upon cobalt doping. XPS demonstrated enrichment of chemisorbed oxygen (O-ad) and higher Ni3+/Ni2+ ratios with increasing cobalt content, correlating with enhanced redox properties. Optical characterization revealed band-gap narrowing from 2.40 eV (LaNiO3) to 2.31 eV (LaNi0.5Co0.5O3), favoring electron transfer. Catalytic activity tests demonstrated significant improvements in CO and C3H6 oxidation after cobalt substitution, with T-50 for CO oxidation decreasing from 185 degrees C (LaNiO3) to 164.6 degrees C (LaNi0.5Co0.5O3), and T-90 from 228.1 degrees C (LaNiO3) to 207.5 degrees C (LaNi0.5Co0.5O3). Similarly, T-50 for C3H6 conversion reached 266.8 degrees C and T-90 at 312.1 degrees C for LaNi0.5Co0.5O3, compared to 307.1 degrees C and 335.0 degrees C for pristine LaNiO3. Although NO conversion peaked at similar to 90% around 275 degrees C for LaNiO3, it decreased upon Co substitution due to equilibrium constraints. These findings demonstrate that cobalt incorporation enhances reducibility, lattice oxygen mobility, and surface oxygen reactivity, thereby promoting CO and hydrocarbon oxidation under TWC conditions.
