Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing the Challenge of Luxury Democratization: A Multicountry Analysis

Once the preserve of the elite, many luxury brands are now targeting the rapidly rising global middle classes. This “democratization of luxury,” understood as the perceived reduction in distinctiveness, exclusivity, and self-differentiation of luxury goods due to wider availability and access, has changed the luxury industry landscape substantially, and yet it remains an underexplored phenomenon in academic research. Building on the theory of network effects, this study focuses on how democratization influences the relationship between conspicuous signaling and luxury purchase intentions. Analysis of primary data (n = 1,156) from luxury consumers in developed (United States and Spain) and developing (China and India) markets with distinctly differing economic trajectories reveals the varying negative moderating influence of democratization. These negative effects of luxury democratization are more pronounced in developing markets (Study 1). Further, the findings highlight that consumer indulgence can help mitigate negative externalities associated with luxury democratization (Study 1) and identify its underlying mechanism through positive affect (Study 2). The multimethod approach demonstrated in this study sheds new light on consumer perceptions of luxury democratization and offers actionable implications for international luxury firms on managing this challenge in developed and developing markets.
Estimation of On‐Road PM2.5 Distributions by Combining Satellite Top‐of‐Atmosphere With Microscale Geographic Predictors for Healthy Route Planning

How to reduce the health risks for commuters, caused by air pollution such as PM2.5 has always been an urgent issue needing to be solved. Proposed in this study, is a novel framework which enables greater avoidance of pollution and hence assists the provision of healthy travel. This framework is based on the estimation of on‐road PM2.5 throughout the whole city. First, the micro‐scale PM2.5 is predicted by land use regression (LUR) modeling enhanced by the use of the Landsat‐8 top‐of‐atmosphere (TOA) data and microscale geographic predictors. In particular, the green view index (GVI) factor derived, the sky view factor, and the index‐based built‐up index, are incorporated within the TOA‐LUR modeling. On‐road PM2.5 distributions are then mapped in high‐spatial‐resolution. The maps obtained can be used to find healthy travel routes with less PM2.5. The proposed framework was applied in high‐density Hong Kong by Landsat 8 images. External testing was based on mobile measurements. The results showed that the estimation performance of the proposed seasonal TOA‐LUR Geographical and Temporal Weighted Regression models is at a high‐level with an R2 of 0.70–0.90. The newly introduced GVI index played an important role in these estimations. The PM2.5 distribution maps at high‐spatial‐resolution were then used to develop an application providing Hong Kong residents with healthy route planning services. The proposed framework can, likewise, be applied in other cities to better ensure people's health when traveling, especially those in high‐density cities.
THE ROLE OF LOSS ADJUSTMENT PRACTICES ON THE PERFORMANCE OF INSURANCE SECTOR

Purpose: The purpose of this study was to determine the role of loss adjustment practices on the performance of insurance sector Methodology: A desktop literature review was used for this purpose. , a systematic search was carried out using Google Scholar, Semantic Scholar, and Research Gate. The study included relevant sources that were published between 2015 and 2022. Findings: It was found that sound loss adjustment practices are a prerequisite for optimal financial and non-financial performance of insurance firms. It was concluded that having a clear policy approved by senior management, with regards to ex-gratia claim payments reduced the financial risks. It was also concluded that insurance firms can enhance their financial performance by regularly reviewing their claims handling guidelines to factor in new developments and trends. The study further concluded that non-financial and financial performance of insurance firms in influenced by quality reviews of claims to assess whether they are handled professionally and resolved appropriately. One of the performance measures could be the number and nature of complaints against the insurer with respect to their claims settlement decisions. The performance is also influenced by monitoring the level of claims which should not have been paid or are overpaid and the severity of delays in claims registration and case reserves revision. Unique Contribution to Theory, Practice and Policy: Based on the study findings, it was recommended that insurance firms should endeavor to set case reserves accurately for each claim in a timely manner, especially in respect of general insurance business. The components of case reserves should also be captured in sufficient details to provide useful statistics for in-depth analysis. For example, a single claim file could have separate components for own property damage, third party liabilities and fees payable to external parties. Another recommendation is that the insurer should have a clear policy, approved by senior management, with regards to ex-gratia claim payments. The authority to approve such payments should also be clearly specified and the rationale for the approval should be properly documented.
Liquid Moisture Transport in Knitted Fabrics in Relaxed and Stretched State

The aim of this work was to analyze the influence of stretch on liquid moisture transport through the knitted fabrics for T-shirts. Five variants of cotton and cotton blended fabrics were measured by means of the Moisture Management Tester. Measurements have been performed for samples in the unstretched state and samples stretched by 15%. To precisely stretch the fabrics, the MMT Stretch Fabric Fixture has been applied. The results have been analyzed statistically in order to assess the influence of stretch on the parameters characterizing the moisture transport through the fabrics.
Social integration mechanisms to strengthen absorptive capacity in agricultural advisory service organisations

ABSTRACT Purpose To explore the structures and processes within agricultural advisory organisations that may enhance absorptive capacity (AC) and determine how organisations develop their AC. Design/methodology/approach A qualitative explorative case study of advisory services in Norway, which are structured as farmer cooperatives. Interviews, document analysis, and internet information are applied. Findings Strong social mechanisms are needed to realise the potential AC in an organisation. Advisory organisations with incorporated research and development (R&D) can translate findings from both their own research projects and external sources, which increases their absorptive capacity and boosts service innovation. Further, systematic emphasis on continuous learning strengthens AC, as do networking and internal communications. Practical implications By improving the incorporation of R&D, continuous learning and networking, advisory service organisations can benefit from the Agricultural Knowledge and Innovation System (AKIS). Ultimately farmers can receive more updated and relevant services for their farms. Theoretical implications Incorporation of R&D, continuous learning and networking are significant social integration mechanisms that can improve a firm’s AC. Originality/value Previous studies on AC have shown that it is important for innovation. This paper sheds additional light on how AC can be improved.
The effects of public goods framing for a union default policy

Union provision of collective bargaining and political lobbying generates positive outcomes across society. A union default holds significant promise to revive the flagging fortunes of unions by enabling them to recruit many more members, extend their bargaining coverage, and place them in a stronger position to deliver these positive outcomes. Non-unionism is the default setting in employment arrangements. A union default would reverse this, so employees are defaulted into membership in the first instance, but with a right to opt-out. In this article the authors test whether framing unions as providers of public goods increases worker support for a union default and intention to stay in a union, if defaulted. The authors find that workers are significantly more likely to support a union default and stay in union membership in scenarios involving positive framing for unions.
Interplanetary shock waves and the structure of solar wind disturbances

Observations and theoretical models of interplanetary shock waves are reviewed, with emphasis on the large-scale characteristics of the associated solar wind disturbances and on the relationship of these disturbances to solar activity. The sum of observational knowledge indicates that shock waves propagate through the solar wind along a broad, roughly spherical front, ahead of plasma and magnetic field ejected from solar flares. Typically, the shock front reaches 1 AU about two days after its flare origin, and is of intermediate strength. Not all large flares produce observable interplanetary shock waves; the best indicator of shock production appears to be the generation of both type 2 and type 4 radio bursts by a flare. Theoretical models of shock propagation in the solar wind can account for the typically observed shock strength, transit time, and shape.
Evaluation of the Fitch wind-farm wake parameterization with large-eddy simulations of wakes using the Weather Research and Forecasting model

Wind-farm parameterizations in weather models can be used to predict both the power output and farm effects on the flow; however, their correctness has not been thoroughly assessed. We evaluate the wind-farm parameterization of the Weather Research and Forecasting model with large-eddy simulations (LES) of the wake performed with the same model. We study the impact on the velocity and turbulence kinetic energy (TKE) of inflow velocity, roughness, resolution, number of turbines (one or two), and inversion height and strength. We compare the mesoscale with the LES by spatially averaging the LES within areas correspondent to the mesoscale horizontal spacing; one covering the turbine area and two downwind. We find an excellent agreement of the velocity within the turbine area between the two types of simulations. However, within the same area, we find the largest TKE discrepancies because in mesoscale simulations, the turbine-added TKE has to be highest at the turbine position to be advected downwind. Within the downwind areas, differences between velocities increase as the wake recovers faster in the LES, whereas for the TKE both types of simulations show similar levels. From the various configurations, the impact of inversion height and strength is small for these heights and inversion levels. The highest impact for the one-turbine simulations appears under the low-speed case due to the higher thrust, whereas the impact of resolution is low for the large-eddy simulations but high for the mesoscale simulations. Our findings demonstrate that higher-fidelity simulations are needed to validate wind-farm parameterizations.
Self-Awareness and Stereotypes: Accurate Prediction of Implicit Gender Stereotyping

Research showing that people can predict the patterns of their implicit evaluations toward social groups has raised questions concerning how widely these findings extend to other domains, such as semantic implicit stereotyping. In a preregistered laboratory study, participants were asked to predict their scores on five implicit gender stereotyping Implicit Associations Tests (IATs). Within-subjects correlations between IAT score predictions and IAT scores showed high levels of accuracy. Although part of the IAT score patterns could be predicted from shared knowledge, own predictions significantly outperformed predictions of random others and normative patterns, suggesting self-awareness beyond reliance on shared knowledge. In line with dual-process models emphasizing that different information is captured by implicit as opposed to explicit measures, predictions explained correlations between implicit and traditional explicit stereotyping measures, and led to acknowledgment of bias. Discussion focuses on understanding conscious awareness of semantic automatic processes and conceptualizations of the cognitions underlying implicit measures.
Design of additive quantum codes via the code-word-stabilized framework

We consider design of the quantum stabilizer codes via a two-step, low-complexity approach based on the framework of codeword-stabilized (CWS) codes. In this framework, each quantum CWS code can be specified by a graph and a binary code. For codes that can be obtained from a given graph, we give several upper bounds on the distance of a generic (additive or nonadditive) CWS code, and the lower Gilbert-Varshamov bound for the existence of additive CWS codes. We also consider additive cyclic CWS codes and show that these codes correspond to a previously unexplored class of single-generator cyclic stabilizer codes. We present several families of simple stabilizer codes with relatively good parameters.
A large-scale streaming motion in the local universe.

Resultats de l'etude des distances et des vitesses des galaxies elliptiques jusqu'a ∼6000 kms −1 . On en deduit l'existence d'un mouvement moyen des galaxies elliptiques par rapport au fond microonde de 599±104 kms −1 dans la direction l=312°±11°, P=6°±10°
Knowledge, attitude and precautionary measures regarding Covid-19 among mothers in a tertiary care hospital: Cross-sectional study

Introduction Knowledge, attitude and precautionary measures regarding COVID-19 among mothers play an important role in reducing the spread of the infection and helping control the pandemic. It also provides insight into the role of the media in controlling the pandemic. Objective To assess knowledge, attitude and precaution measures (KAP) regarding COVID-19 among mothers in a tertiary care hospital. Methodology This was a questionnaire-based cross-sectional study regarding COVID-19 which was conducted at a tertiary care obstetric facility in India among 100 consenting mothers. The consenting mothers were assessed for demographic data and KAP scores (Knowledge - 8 questions, Attitude - 7 questions, Precautionary measures - 5 questions). Results A total of 100 mothers participated in the study. 21% of the mothers were less than 25 years of age, 67% of them were between the ages of 25 and 29 and the remaining 12% were between the ages of 30 and 35. The participants were asked to fill out a questionnaire on COVID-19 from which their knowledge was assessed. Common questions were about the type of disease, the mode of transmission and the symptoms. Concerning the current stage of distribution of COVID-19, the majority of the mothers stated that it was a pandemic (81%). Regarding the type of disease, the majority of the mothers stated that it was a communicable disease (79%). When enquired about the symptoms of the disease, the majority of the mothers stated fever (97%), cough (98%), and breathlessness (97%). All of the mothers (100%) agreed that the delivery of the baby should be performed at a hospital if they contracted COVID-19. Conclusion This study demonstrates that the majority of the mothers had satisfactory knowledge, a positive attitude and were applying appropriate precautionary measures to protect themselves from COVID-19.
Hysteresis in streamflow‐water table relation provides a new classification system of rainfall‐runoff events

Rainfall‐runoff event types can be used to better understand the hydrological functioning of catchments. In this study, we propose a framework to characterize and classify runoff events relying on the hysteresis analysis of the relation between streamflow (independent variable) and depth to water table (dependent variable). We evaluated hysteresis for 112 rainfall‐runoff events occurred in the period 2012–2016 in a small forested catchment in the Italian Pre‐Alps. Three main groups of rainfall‐runoff events were identified, each associated with specific hydro‐meteorological characteristics of the events. A first group, identified by a faster response of streamflow compared to the groundwater level (which led to a clockwise hysteretic loop), was characterized by dry antecedent conditions, short rainfall events, low streamflow peaks and small runoff coefficients. A second group had characteristics similar to the first group, that is, faster response of streamflow compared to the groundwater level (clockwise hysteretic loop), but on average displayed a narrower hysteretic loop. A third group, identified by a faster response of the groundwater level compared to streamflow (which led to an anti‐clockwise loop), was characterized by wet antecedent conditions, long rainfall events, high streamflow peaks and large runoff coefficients. Results showed statistically significant differences among the groups, corroborated by an analysis based on environmental tracers (2H and electrical conductivity). This study shows how the analysis of the hysteretic relation between streamflow and depth to water table can be used for grouping rainfall‐runoff events and to better identify the catchment's hydrological response to rainfall inputs.
Feeling Good or Feeling Right: Sustaining Negative Emotion After Exposure to Human Suffering

Although hedonic principles of emotion regulation suggest that people wish to feel good, the current research demonstrates that sometimes feeling good just seems wrong. Specifically, the authors argue that, immediately after viewing moralized content such as human suffering, consumers believe that it is morally appropriate to sustain negative emotions (Study 1). Thus, after exposure to content related to human suffering (vs. other negative content), consumers view subsequent mood-sustaining consumption as morally appropriate and hedonic consumption as morally inappropriate (Study 2). Consequently, they avoid repairing their emotions through hedonic consumption because of their preference to engage in morally appropriate behavior (Studies 3 through 4b); this is particularly true for individuals who view themselves as more moral (Study 4b). These effects are mitigated when the hedonic consumption is morally relevant (Study 4a), rather than prototypically frivolous. This research offers clear prescriptions to marketers about when and when not to offer hedonic consumption as mood repair. By allowing people to pay respect to suffering victims, marketers can give consumers needed space to feel their compassionate emotions.
String-theoretic breakdown of effective field theory near black hole horizons

We investigate the validity of the equivalence principle near horizons in string theory, analyzing the breakdown of effective field theory caused by longitudinal string spreading effects. An experiment is set up where a detector is thrown into a black hole a long time after an early infalling string. Light cone gauge calculations, taken at face value, indicate a detectable level of root-mean-square longitudinal spreading of the initial string as measured by the late infaller. This results from the large relative boost between the string and detector in the near-horizon region, which develops automatically despite their modest initial energies outside the black hole and the weak curvature in the geometry. We subject this scenario to basic consistency checks, using these to obtain a relatively conservative criterion for its detectability. In a companion paper, we exhibit longitudinal nonlocality in well-defined gauge-invariant S-matrix calculations, obtaining results consistent with the predicted spreading albeit not in a direct analog of the black hole process. We discuss applications of this effect to the firewall paradox, and estimate the time and distance scales it predicts for new physics near black hole and cosmological horizons.
Machine learning using convolutional neural networks for SERS analysis of biomarkers in medical diagnostics

Abstract Surface‐enhanced Raman spectroscopy (SERS) has wide diagnostic applications because of narrow spectral features that allow multiplexed analysis. Machine learning (ML) has been used for non‐dye‐labeled SERS spectra but has not been applied to SERS dye‐labeled materials with known spectral shapes. Here, we compare the performances of spectral decomposition, support vector regression, random forest regression, partial least squares regression, and convolutional neural network (CNN) for SERS “spectral unmixing” from a multiplexed mixture of 7 SERS‐active “nanorattles” loaded with different dyes for mRNA biomarker detection. We showed that CNN most accurately determined relative contributions of each distinct dye‐loaded nanorattle. CNN and comparative models were then used to analyze SERS spectra from a singleplexed, point‐of‐care assay detecting an mRNA biomarker for head and neck cancer in 20 samples. The CNN, trained on simulated multiplexed data, determined the correct dye contributions from the singleplex assay with RMSElabel = 6.42 × 10−2. These results demonstrate the potential of CNN‐based ML to advance SERS‐based diagnostics.
Enhancing Upper Secondary Learners’ Problem-solving Abilities using Problem-based Learning in Mathematics

Developing problem-solving abilities is a major objective of learning mathematics at school. However, learners’ problem-solving abilities are still critical. The main purpose of this study was to investigate how the problem-based learning model could enhance learners’ problem-solving abilities in mathematics. The study used quasi-experimental research with one group pre-test-post-test design. The population in this study consisted of fifty-four grade eleven learners (aged between 16 to 19 years old) from one school in Kayonza District in Rwanda. Data were collected using mathematical problem-solving tests and interviews and were analysed using paired t-tests for dependent sample means and descriptive analysis. The study results indicate that problem-based learning potentially impacts learners’ problem-solving abilities. It is shown from learners’ work in problem-solving that all indicators of problem-solving abilities, namely understanding the problem, planning ways to approach the problem, monitoring the progress while tackling the problem and reviewing the solution process, emerged as being fairly well improved. In addition, based on the interview results from some learners and their teachers, they like the PBL model because embedded tasks helped them to apply the knowledge that can improve their reasoning, creativity and thinking capability. The study recommends that schools encourage teachers to adopt PBL for enhancing learners’ problem-solving abilities. Additionally, researchers are urged to use findings from this study as a reference for further research. Furthermore, researchers could conduct similar research on a large scale using different methodologies.
A twisted generalization of Novikov-Poisson algebras

Hom-Novikov-Poisson algebras, which are twisted generalizations of Novikov-Poisson algebras, are studied. Hom-Novikov-Poisson algebras are shown to be closed under tensor products and several kinds of twistings. Necessary and sufficient conditions are given under which Hom-Novikov-Poisson algebras give rise to Hom-Poisson algebras.