An Examination Of Environmental Orientation Of Consumers In Malaysia

Walaupun banyak usaha telah dilaksanakan dengan matlamat untuk mempertingkatkan keprihatian terhadap alam sekitar, dan mengubah sikap orang awam Despite many efforts have been formulated with the intention to improve environmental concern and change attitude of the public

Achieving Community Happiness through Affordable Eco-Friendly Smart Houses

The significant lack of affordable house is contributed by urbanization, economic power, and population growth. Accessible housing views having different types of houses at variety of costs to suit the needs of different levels of household income. This paper proposes to resolve the unaffordable house issues by constructing eco-friendly smart houses. Eco-friendly smart houses play a vital role in developing affordable houses because it will minimize construction costs, minimize negative environmental impact and reduce energy consumption. Besides, it was suggested that those houses will lead to community happiness. This study identifies the determinants for buyer intends to purchase the houses and make recommendations on the impact of the houses towards community happiness expectation. Questionnaires have been distributed to the potential buyer using the online application. The results conclude that attitude, perceive behavioral control and social media influence potential buyer intention to purchase the affordable eco-friendly smart houses. The findings further reveal that purchase intention leads to expectation on community happiness. This study contributes in two ways. First, it contributes to sustainable development goals agenda and offers a new approach in constructing affordable houses. Second, it contributes to theoretical development on the linkage between purchase intention and expectation on community happiness

HRM and KM as catalysts of environmental performance: A conceptual framework

The purpose of this paper is to develop a theoretical framework to investigate the relationships among human resource management (HRM), knowledge management (KM) and environmental performance (EP).Environmental friendly business activities demand high level of human resource competency in terms of knowledge, skills and capabilities in order to better firm performance. This paper serves to establish the link among HRM, KM, and EP to fill the gap in the current literature.The research model is proposed based on reviews of the literature on HR and KM perspectives on environmental management and performance.Both theoretical and practical implications are discussed in this paper.With new knowledge gained on the associations among HRM, KM and EP, manufacturing firm managers can focus their effort and resources on HRM and KM to deliver better environmental management effectiveness.It is anticipated that this paper will contribute towards sustainability development for a better living environment

A scattering and repulsive swarm intelligence algorithm for solving global optimization problems

The firefly algorithm (FA), as a metaheuristic search method, is useful for solving diverse optimization problems. However, it is challenging to use FA in tackling high dimensional optimization problems, and the random movement of FA has a high likelihood to be trapped in local optima. In this research, we propose three improved algorithms, i.e., Repulsive Firefly Algorithm (RFA), Scattering Repulsive Firefly Algorithm (SRFA), and Enhanced SRFA (ESRFA), to mitigate the premature convergence problem of the original FA model. RFA adopts a repulsive force strategy to accelerate fireflies (i.e. solutions) to move away from unpromising search regions, in order to reach global optimality in fewer iterations. SRFA employs a scattering mechanism along with the repulsive force strategy to divert weak neighbouring solutions to new search regions, in order to increase global exploration. Motivated by the survival tactics of hawk-moths, ESRFA incorporates a hovering-driven attractiveness operation, an exploration-driven evading mechanism, and a learning scheme based on the historical best experience in the neighbourhood to further enhance SRFA. Standard and CEC2014 benchmark optimization functions are used for evaluation of the proposed FA-based models. The empirical results indicate that ESRFA, SRFA and RFA significantly outperform the original FA model, a number of state-of-the-art FA variants, and other swarm-based algorithms, which include Simulated Annealing, Cuckoo Search, Particle Swarm, Bat Swarm, Dragonfly, and Ant-Lion Optimization, in diverse challenging benchmark functions

Nonstandard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Common variants in SOX-2 and congenital cataract genes contribute to age-related nuclear cataract

Nuclear cataract is the most common type of age-related cataract and a leading cause of blindness worldwide. Age-related nuclear cataract is heritable (h2 = 0.48), but little is known about specific genetic factors underlying this condition. Here we report findings from the largest to date multi-ethnic meta-analysis of genome-wide association studies (discovery cohort N = 14,151 and replication N = 5299) of the International Cataract Genetics Consortium. We confirmed the known genetic association of CRYAA (rs7278468, P = 2.8 × 10−16) with nuclear cataract and identified five new loci associated with this disease: SOX2-OT (rs9842371, P = 1.7 × 1

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS