Significant Deviations Research Articles

Development of a Brand Value Measurement Model with a Corporate Social Responsibility Perspective. A Comparative Analysis of Consumer Perception of Energy Providers in Spain and Colombia

Sustainable development of companies and their products involves the integration of multiple dimensions, including economic, ethical, social, and environmental considerations, all of which are increasingly important to consumers. The present study identified key variables that define brand value in the context of Corporate Social-Environmental Responsibility (CSR), comparing two companies in the energy sector in Spain and Colombia (Naturgy and Ecopetrol S.A.). Among the factors that contribute to brand success, this study evaluated three variables: Visibility, Loyalty and Experience as perceived by consumers. Data measuring brand value were collected through an online survey of 640 respondents in Spain and Colombia, assessing their response to company logos and corporate messaging regarding environmental sustainability of their operations. Structural equation models (SEM) were then used to measure brand value based on latent variables and compared to survey data. Our results show that company visibility had a positive impact on brand loyalty and consumer experience, which ultimately increases brand value. Conversely, an improved consumer experience can also enhance brand loyalty and visibility. Our findings represent a framework to quantify brand value within the energy sector that is based on integrating multiple indicators of brand equity (BE) using the analysis of company logos, while simultaneously considering CSR, greenwashing and other forms of company messaging. This integration is a significant departure from traditional approaches and offers a new and novel perspective when developing a comprehensive corporate model. Our study suggests that implicit and explicit allusion to corporate environmental-social responsibility has a profound influence on brand recognition and brand acceptance by customers, due to the positive responses it elicits. The current study's findings support incorporating references to CSR in sustainable branding in its broadest spectrum and definition and offer a procedure to quantify and measure brand value, which can help company managers make effective branding decisions.

The Gaza Crisis and the Indian Exceptionalism

India’s attitude on the ongoing Israel-Hamas conflict marks a significant departure vis-à-vis India’s own position toward the Israeli-Palestinian conflict as well as the general view of the Global South. Its prime focus has been on the terrorist nature of the October 7 violence and the resolution of the conflict through the two-state solution. Both these positions exhibit the sympathy of the Indian government toward Israel, and despite reservations and criticisms, the domestic reaction to the official position has been more muted than in the past.

Germylene Mediated Reductive C−C and C−N Coupling of an Isocyanide and its Device Application

AbstractWe have demonstrated a unique reductive coupling of 4‐iodophenyl isocyanide, facilitated by a perimidine‐based N‐heterocyclic germylene (NHGe), which yields a bis‐spirogerma compound featuring simultaneous C−C and C−N bond formation. This reaction, which leads to the oxidation of germanium from +2 to +4, represents a significant departure from previously documented isocyanide‐germylene interactions. The product exhibits extensive conjugation across its bicyclic C4Ge2N2 framework, conferring distinct photophysical properties, including prominent orange luminescence in both solution and solid states. The photophysical properties are supported by the TD‐DFT calculations confirming an n→π* transition. The potential application of this compound in optoelectronic devices, particularly as a hole transport layer in PbS quantum dot solar cells, is also explored, with promising preliminary results.

Germylene Mediated Reductive C-C and C-N Coupling of an Isocyanide and its Device Application.

We have demonstrated a unique reductive coupling of 4-iodophenyl isocyanide, facilitated by a perimidine-based N-heterocyclic germylene (NHGe), which yields a bis-spirogerma compound featuring simultaneous C-C and C-N bond formation. This reaction, which leads to the oxidation of germanium from +2 to +4, represents a significant departure from previously documented isocyanide-germylene interactions. The product exhibits extensive conjugation across its bicyclic C4Ge2N2 framework, conferring distinct photophysical properties, including prominent orange luminescence in both solution and solid states. The photophysical properties are supported by the TD-DFT calculations confirming an n→π* transition. The potential application of this compound in optoelectronic devices, particularly as a hole transport layer in PbS quantum dot solar cells, is also explored, with promising preliminary results.

Institutionalizing co‐production diplomacy in contexts of long‐term epistemological conflict: A case study of cod fisheries governance

AbstractKnowledge co‐production is a collaborative approach to research that seeks to enable transformative societal change and improve outcomes in natural resource management and sustainable development. Instituting knowledge co‐production requires that researchers, decision‐makers, and stakeholders be willing to work together towards shared goals. In the context of fisheries management, co‐production represents a significant departure from the technocratic discourses and governance practices that have characterized decision‐making for decades. Moreover, some fisheries contexts have been plagued by persistent and seemingly intractable epistemological conflicts between stakeholders and decision‐makers. Such situations complicate the implementation of co‐production and raise questions about the extent to which researchers can achieve the aims of co‐production in situations of distrust, amenity, and entrenched positions. We use the case study of Northern Cod, a stock of Atlantic Cod (Gadus morhua) governance in Newfoundland and Labrador, Canada, a case of long‐standing conflict between the regulator, fishers, Indigenous peoples, and industry parties, to explore whether and how co‐production can enable collaborative research leading to “transformative societal change.” We find five factors complicating uptake of co‐production in the governance of Northern Cod: (i) competing perspectives exist regarding the relative worth of different types of knowledge; (ii) links between epistemic preferences and interests; (iii) barriers related to access and inclusion in governance spaces; (iv) barriers related to institutional design; and, (v) conflict‐ridden stakeholder relations. In a context of persistent epistemological conflict and distrust, we propose that knowledge co‐production focus on diplomacy through science with an aim to repair relationships rather than produce new knowledge that can serve as evidence in decision‐making as the primary goal of the co‐production process.

Upper Palaeolithic fishing techniques: Insights from the engraved plaquettes of the Magdalenian site of Gönnersdorf, Germany.

The ~15,800 year-old Magdalenian site of Gönnersdorf, in Germany, has produced 406 engraved schist plaquettes which have been extensively studied in the past. The introduction of advanced imaging technologies, notably Reflectance Transformation Imaging (RTI), has now precipitated a re-evaluation of these artifacts, uncovering nuanced depictions of fishing practices previously unrecorded for the Upper Palaeolithic. Our investigation harnesses RTI to elucidate fine engraving details on the plaquettes, revealing depictions of fish and accompanying grid motifs. The analytical process enabled by RTI has exposed an intricate link between the grid patterns and fish figures, showing that they were a deliberate combination portraying the use of fishing nets. This discovery posits a significant departure from earlier interpretations of the site's iconography, which predominantly emphasized more naturalistic representations of fauna. Furthermore, these findings illuminate aspects of Magdalenian cultural praxis, suggesting that representations of aquatic life and fishing technologies were not merely utilitarian in nature but were embedded within a broader symbolic framework. This study enhances our comprehension of Magdalenian peoples' interaction with the aqueous milieu, revealing a sophisticated symbiosis between ecological adaptation and artistic expression.

Distinguishing and Further Reinforcement for Nanocrystal XRD Peaks Caused by Instrument Broadening in Nanomixed Materials

X-ray diffraction (XRD) is one of the most essential techniques for characterizing various crystals. However, when nanocrystals are present, the diffraction peaks become significantly broadened and reduced in intensity, making phase and microstructure analysis challenging. To obtain more refined microstructural information from nanocrystals, various methods have been developed to enhance diffraction peaks, with step scanning being a commonly used approach. Additionally, increasing instrument broadening (IB) by adjusting slit sizes to enlarge the irradiation area is a convenient yet often overlooked method. In this study, the effects of IB on the diffraction peak intensities of nanocrystals and micron crystals in mixed materials were thoroughly investigated. The results show that the intensities of both nanocrystals and micron crystals increase as IB increases, a behavior similar to that observed when extending the testing time during step scanning. However, the rate of increase in peak heights for nanocrystals is higher than for micron crystals, while the rate of increase in peak width for nanocrystals is lower, which is a significant departure from the effects seen in step scanning. In other words, nanocrystal peaks become sharper and more distinct as IB increases. This phenomenon is explained by the different components of peak width for nanocrystals and micron crystals, based on Lorentz mathematical model analysis. Based on these findings, it is recommended to utilize larger IBs in combination with step scanning to further reinforce nanocrystal peaks in mixed materials.

Elastic and inelastic scattering of flat-top solitons

We investigate the interaction between two flat-top solitons within the cubic-quintic nonlinear Schrödinger equation framework. Our study results point towards a significant departure of flat-top solitons' collisional characteristics from the conventional behaviors exhibited in the scattering dynamics of two bright solitons. Our investigation outlines specific regimes corresponding to the dual flat-top solitons' elastic and inelastic collisions. We determine regimes in the parameter space where exchange in the widths of the interacting flat-top solitons is possible, even within the elastic collision domain. We find a periodic occurrence of completely elastic scattering of flat-top solitons in terms of the solitons' parameters. Investigating the internal energy transfers between the solitons and the emitted radiation reveals the origin of inelasticity in flat-top soliton collisions. We perform a variational calculation that accounts for the amount of radiation produced by the collision and hence provides further insight into the physics underlying the loss of elasticity of collisions. Published by the American Physical Society 2024

LES and RANS Modeling of an 84-Pin Hexagonal Rod Bundle with Spacer Grid and Experimental Validation

As part of an ongoing integrated research project (IRP), detailed investigations of the flow characteristics of an 84-pin hexagonal rod bundle representing a potential modular gas-cooled fast reactor design have been performed. The rod bundle features a pitch-to-diameter ratio of 1.5 and a large central guide tube, along with simple spacer grids and an outer enclosure. The primary focus of the current work is modeling and simulation of this geometry using multiple computational techniques. These include high-fidelity large eddy simulation (LES) and advanced Reynolds-averaged Navier-Stokes (RANS) approaches. The flow predictions are validated at a Reynolds number of 12 000 using matched index of refraction particle image velocimetry experimental data that were also generated by Texas A&M University as part of the IRP. The comparison data include velocity magnitude and turbulent kinetic energy (TKE) at different lateral locations and at multiple distances downstream of the spacer grid. Many characteristics of the experimental flow are replicated in the LES and RANS runs, and a general agreement between simulation and experiment is shown. Except for the immediate vicinity of the grid, LES is able to capture the velocity magnitude within a 10% error and the TKE to within the experimental uncertainty. The LES shows notably better agreement with the experimental data than RANS, particularly regarding the TKE decay behavior downstream of the grid. Both methods show significant departures from the experiment in their predictions close to the central guide tube. The experimental and high-fidelity data will be used to inform closures for novel multiscale methodologies. The long-term goal of the work is to use the high-fidelity data to yield improved multiscale thermal analysis techniques for solving fuel performance problems of direct relevance to industry.

Bitcoin: an alternative to fiat money? A post-Keynesian perspective

Motivation: This paper addresses the ongoing debate surrounding Bitcoin’s potential to function as an alternative to state-issued fiat currencies. With the advent of Bitcoin and its increasing global prominence, it is essential to explore its viability, particularly in light of its formal adoption in El Salvador as legal tender. The limited supply and decentralized nature of Bitcoin present a significant departure from traditional monetary systems, which raises questions regarding its capacity to fulfill the roles of money under Modern Monetary Theory (MMT).Aim: The primary goal of this paper is to critically examine whether Bitcoin can serve as a functional replacement for fiat money. Using a post-Keynesian analytical framework, this study investigates Bitcoin’s ability to meet the requirements of sovereign money, particularly within the theoretical framework of MMT. The analysis focuses on Bitcoin’s decentralized issuance, limited supply, and its role in fiscal policy and credit creation.Materials and methods: This research employs a critical literature review and a case study analysis, using the framework of MMT and post-Keynesian endogenous money theory to assess Bitcoin’s economic implications and its real-world application in El Salvador’s Bitcoin Law. The study analyzes Bitcoin’s economic implications based on the endogenous money supply model and evaluates its impact on government fiscal policy, credit markets, and economic stability in both theoretical and practical contexts, with a special focus on El Salvador’s Bitcoin Law.Results: The analysis reveals significant limitations in Bitcoin’s ability to function as a fiat currency. Its rigid supply and speculative nature hinder its capacity to serve as a medium of exchange, store of value, and unit of account, as envisaged by MMT. The study concludes that Bitcoin’s decentralized nature and deflationary design pose challenges for its broader adoption as state money, particularly in managing aggregate demand and economic crises.

Exploring the job (dis)satisfaction indicators of online food delivery employees: insights from employees' online reviews

PurposeThe present study sought to determine the main themes employees discussed in online reviews associated with satisfaction (pros) and dissatisfaction (cons).Design/methodology/approachThis study used qualitative content analysis to examine employee reviews working in India's largest food delivery company.FindingsThe analyses revealed the existence of seven themes: company environment, employees, salary, work–life balance, company culture and values, flexibility and favoritism. Negative themes were associated with the “work-life balance” and “favoritism” themes. The results provided valuable insights into online food delivery platform employees' overall experiences based on social media information and aided in identifying key themes associated with various satisfaction levels.Originality/valueThis study contributes to the literature by uniquely utilizing user-generated content from an employment search engine as a novel data source to investigate the factors influencing satisfaction and dissatisfaction among online food delivery employees. This approach represents a significant departure from traditional survey-based methods, filling a gap in the literature by offering insights directly from employees' unfiltered perspectives. By leveraging this innovative methodology, our research provides a fresh and nuanced understanding of the experiences and concerns of online food delivery workers, thereby adding substantial value to the fields of organizational behavior and human resource management.

Prolonged exposure to air pollution and risk of acute kidney injury and related mortality: a prospective cohort study based on hospitalized AKI cases and general population controls from the UK Biobank

BackgroundPrevious investigations identified a connection between air pollution and kidney diseases. Nevertheless, there is a lack of comprehensive evidence on the long-term risks posed by air pollution with respect to acute kidney injury (AKI) and AKI-related death.MethodsThis prospective cohort analysis included 414,885 UK Biobank (UKB) participants who did not exhibit AKI at the study’s outset. AKI was defined based on ICD-10 codes recorded for hospitalized patients. Cox proportional hazards models were used to assess the association between prolonged exposure to air pollutants (particulate matter with diameters of 2.5 micrometers or less (PM2.5), between 2.5 and 10 micrometers (PM2.5−10), and 10 micrometers or less (PM10), along with nitrogen dioxide (NO2) and nitrogen oxides (NOx)) and the risk of AKI and AKI-related death, adjusting for potential confounders including sex, age, ethnicity, education, income, lifestyle factors, and relevant clinical covariates. Restricted cubic splines were applied to evaluate non-linear dose-response relationships, and stratified analyses were performed to explore potential effect modification across subgroups.ResultsOver an average follow-up duration of 11.7 years, 14,983 cases of AKI and 326 cases of AKI-related death were diagnosed. Quartile analysis showed individuals exposed to higher levels of these air pollutants had a significantly higher risk of developing AKI and AKI-related death compared to those in the lowest quartile (all P < 0.05). The RCS curves depicting the relationship between PM2.5, PM2.5−10, PM10, NO2, NOx, and the risk of AKI showed a significant departure from linearity (P for non−linearity < 0.05), while the relationships between PM2.5, NO2, NOx, and the risk of AKI-related death did not exhibit a significant departure from linearity (P for non−linearity > 0.05). Sensitivity analyses confirmed the robustness of our findings.ConclusionOur study reveals a direct association between prolonged air pollution exposure and elevated risks of both AKI and AKI-related death. These findings offer scientific validation for the adoption of environmental and public health measures directed towards the reduction of air pollution. Such initiatives could potentially ease the impact associated with AKI and AKI-related death.

Instability analysis of Li-ion battery electrode particles induced by chemomechanical growth using incremental deformation theory

Volumetric swelling due to lithiation into active battery materials is a well-known phenomenon. A chemo-mechanical framework can suitably explain the deformations of the electrode and the generation of diffusion-induced stresses (DIS). Various experimental works have shown that the effects of DIS further cause the active material to lose its structural stability. However, relatively few frameworks exist that can investigate such phenomena in a comprehensive manner. These are mainly based on the Euler–Bernoulli beam theory and the von-Karman plate theory. In the present work we present a generalized three-dimensional instability framework incorporating the theory of incremental deformation. We use this theory on a widely used chemo-mechanical framework. Notably, similar existing instability investigations on negative electrode materials are based only on incompressible material behaviour. As opposed to it, in this work we have considered a compressible material. Also, we account for the spatial and temporal nature of growth, which is a significant departure from the existing instability frameworks. Therefore, this current work brings the investigation of structural instability of electrode material closer to physical reality. In our study, we use the compound matrix method to find the critical lithiation parameter. Then we consider three sets of problems, each with a particular combination of boundary conditions applied on the inner and outer cylindrical surfaces of hollow cylindrical anode particles. These are free-free, fixed-free, and free-fixed, where each combination represents a particular type of interaction between an electrode particle and its surroundings. Most importantly, we find that the free-free and fixed-free conditions show only a pure axial and mixed mode of instability, and do not show the pure circumferential mode. The free-fixed conditions, however, shows all three modes of instability. Additionally, the presence of mode crossover makes the instability pattern of such electrode particles significant.

A Highly Efficient Catalytic Co-Combustion of Aromatic and Oxygenated Volatile Organic Compounds (VOCs) via H2-Driven Onsite Heating

Catalytic combustion, a highly efficient technique for reducing volatile organic compounds (VOCs), is the focus of this study. We investigate the improved catalytic efficiency of the physical mixing of nanosized Pt and atomically dispersed Co, supported on Al2O3 catalysts (Pt-Co)/Al2O3 (PM) for the catalytic combustion of VOCs. The catalyst efficiency is evaluated for the hydrogen-assisted catalytic oxidation of various VOCs, including aromatic and oxygenated VOCs such as benzene, toluene, methanol, and formic acid. Our study aims to understand the impact of hydrogen incorporation on the combustion process of various VOCs. The findings of this work underscore the potential of hydrogen-assisted catalytic ignition, which can achieve ignition at ambient temperature, a significant departure from conventional electric heating that typically requires additional energy to raise the temperature. Various characterization techniques, such as BET, STEM, and XRD, are employed to assess the structure–activity relationship of the catalyst. The optimal hydrogen concentration for complete VOC conversion is 3%. Notably, even at a lower hydrogen concentration of 2%, benzene and methanol reach an ideal ignition temperature of over 500 °C when introduced into the physically mixed catalyst. This study highlights the significant potential of hydrogen-assisted catalytic combustion, inspiring further research and offering a promising method to reduce VOCs effectively.

Transcriptome-Optimized Hydrogel Design of a Stem Cell Niche for Enhanced Tendon Regeneration.

Bioactive hydrogels have emerged as promising artificial niches for enhancing stem cell-mediated tendon repair. However, a substantial knowledge gap remains regarding the optimal combination of niche features for targeted cellular responses, which often leads to lengthy development cycles and uncontrolled healing outcomes. To address this critical gap, an innovative, data-driven materiomics strategy is developed. This approach is based on in-house RNA-seq data that integrates bioinformatics and mathematical modeling, which is a significant departure from traditional trial-and-error methods. It aims to provide both mechanistic insights and quantitative assessments and predictions of the tenogenic effects of adipose-derived stem cells induced by systematically modulated features of a tendon-mimetic hydrogel (TenoGel). The knowledge generated has enabled a rational approach for TenoGel design, addressing key considerations, such as tendon extracellular matrix concentration, uniaxial tensile loading, and in vitro pre-conditioning duration. Remarkably, our optimized TenoGel demonstrated robust tenogenesis in vitro and facilitated tendon regeneration while preventing undesired ectopic ossification in a rat tendon injury model. These findings shed light on the importance of tailoring hydrogel features for efficient tendon repair. They also highlight the tremendous potential of the innovative materiomics strategy as a powerful predictive and assessment tool in biomaterial development for regenerative medicine.

A reflective study on the intricate history of Chinese immigration in Peninsular Malaysia

This article presents a reflective microcosm to faithfully echo the intricate history of Chinese immigration in Peninsular Malaysia, focusing on two migration waves that occurred during the Malacca Sultanate and colonial eras. It meticulously examines the underlying causes, defining the characteristics, patterns and quantities of each immigration wave by drawing upon historical documents, tombstone inscriptions and demographic data. In a significant departure from conventional wisdom, this study challenges the prevailing notion that Chinese immigrants were overwhelmingly male, shedding light on the fact that the initial wave featured a higher proportion of females. Moreover, the analysis illuminates the intricate interplay between local colonial policies and the external factors emanating from China, demonstrating their profound influence on migration patterns and quantities. The present quantitative study offers fresh insights into the multifaceted experiences of Chinese immigrants in Peninsular Malaysia. It underscores the key findings while bringing attention to the associated complexities and nuances.

When talk meets actions – return to commission leadership in EU environmental policy-making with the European Green Deal

ABSTRACT With the Green Deal, the von der Leyen Commission has put forward an ambitious agenda to transform the European Union towards climate neutrality. However, this commitment to environmental and climate policy has been tested by the numerous crises that have shaped her tenure. Historically, previous Commissions have often deprioritized environmental policy in times of crisis. In light of this, we examine the Commission’s leadership in the realm of environmental policy. Our analysis demonstrates that both the President and her Executive Vice President provided strong leadership and maintained a clear focus on the Green Deal. We further explore this leadership by examining the Commission’s actions in relation to four key Green Deal policies: the Climate Law, the Battery Regulation, the Methane Regulation, and the Nature Restoration Law. Our findings reveal that the rhetorical commitment to environmental and climate policy has translated into mostly ambitious policy proposals, marking a significant departure from the more restrained environmental ambitions of previous Commissions. This analysis contributes to the body of research on the European Commission’s role in environmental and climate policy, as well as its leadership dynamics.

Stability and bipartite synchronization of fractional-order coupled reaction–diffusion neural networks under unbalanced graph

This paper delves into the analysis of stability and bipartite synchronization (BS) in fractional-order coupled neural networks with reaction–diffusion terms (FORDNNs) under structurally unbalanced signed graphs. Central to our investigation is the novel observation in structurally unbalanced graphs without cycles, where specific nodes under particular structures are capable of achieving BS, while others maintain stability. Subsequently, for unbalanced graphs with negative rooted cycles, we present criteria that guarantee the stability of FORDNNs. Moreover, under structurally balanced graphs, sufficient conditions for achieving BS are established. A novel approach is introduced, wherein synchronization is attained without the presence of a leader node, marking a significant departure from conventional models. Finally, illustrative examples are provided, demonstrating the effectiveness and relevance of our findings.

Scaling properties of particle density fluctuations at LHC energies

The availability of high-multiplicity events at LHC energies provides a unique opportunity to examine the nature of phase-transition (PT) in heavy-ion collisions. Within the framework of HYDJET++ model, a systematic study of particle density fluctuations in narrow phase-space bins in Pb-Pb collisions at and 5.02 TeV energies is performed using the method of scaled factorial moments (SFM). The findings reveal the presence of intermittency in the 2-dimensional (2D) phase space distribution of charged particles at the LHC energies. The anomalous fractal dimensions, d q , are observed to increase with the order of the moments q, suggesting the multifractal nature of the charged particle production. The parameter λ q is found to exhibit a monotonically decreasing trend with the order of the moments but with no clear minima in λ q values. Furthermore, the value of the critical exponent is estimated and compared with those predicted by other models reported at RHIC and LHC energies. The value of the critical exponent, ν, obtained in the present study, shows significant departure from the value ∼1.304, as expected for the Ginzberg-Landau (GL) type second-order PT but exhibits a good level of agreement with the results obtained by other models at LHC energies.

Solutions to the Schrödinger equation using deep neural networks for integrated photonics

Abstract This paper introduces a novel method for solving the Schrödinger equation through the use of deep neural networks (DNNs), presenting a significant departure from traditional techniques. Conventional approaches to solving the Schrödinger equation, such as analytical methods and numerical algorithms, often face challenges when dealing with complex quantum systems due to their inherent limitations. These traditional methods can become cumbersome or even infeasible as the complexity of the systems increases. In contrast, our approach harnesses the capabilities of deep neural networks to approximate both the wavefunction and the energy eigenvalues of quantum systems. By leveraging the flexible and powerful nature of DNNs, we provide a new pathway to solving the Schrödinger equation that can potentially overcome the constraints of classical methods. To validate the effectiveness of our approach, we apply it to the particle in a box problem – a fundamental quantum mechanics model with well-established analytical solutions. This benchmark problem serves as a useful test case, allowing us to demonstrate that DNNs can not only replicate the known results accurately but also offer insights into how these networks can handle more intricate quantum systems. Our results reveal that DNNs are capable of accurately reproducing the analytical solutions for the particle in a box, illustrating their potential as a versatile tool for quantum mechanics.