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Melatonin mediated tolerance to benzalkonium chloride phytotoxicity through improved growth, photochemical reactions, and antioxidant system in wild-type and snat2 mutant Arabidopsis lines
No full textMelatonin (Mel) is a phytohormone that plays a crucial role in various plant processes, including stress response. Despite numerous studies on the role of Mel in stress resistance, its significance in plants exposed to benzalkonium chloride (BAC) pollution remains unexplored. BAC, a common antiseptic, poses a threat to terrestrial plants due to its widespread use and inefficient removal, leading to elevated concentrations in the environment. This study investigated the impact of BAC (0.5 mg L-1) pollution on wild-type Col-0 and snat2 knockout mutant Arabidopsis lines, revealing reduced growth, altered water relations, and gas exchange parameters. On the other hand, exogenous Mel (100 mu M) treatments mitigated BAC-induced phytotoxicity and increased the growth rate by 1.8-fold in Col-0 and 2-fold in snat2 plants. snat2 mutant seedlings had a suppressed carbon assimilation rate (A) under normal conditions, but BAC contamination led to further A repression by 71% and 48% in Col-0 and snat2 leaves, respectively. However, Mel treatment on stressed plants was successful in improving Fv/Fm and increased the total photosynthesis efficiency by regulating photochemical reactions. Excessive H2O2 accumulation in the guard cells of plants exposed to BAC pollution was detected by confocal microscopy. Mel treatments triggered almost all antioxidant enzyme activities (except POX) in both Arabidopsis lines under stress. This enhanced antioxidant activity, facilitated by foliar Mel application, contributed to the alleviation of oxidative damage, regulation of photosynthesis reactions, and promotion of plant growth in Arabidopsis. In addition to corroborating results observed in many agricultural plants regarding the development of tolerance to environmental stresses, this study provides novel insights into the action mechanisms of Mel under the emerging pollutant benzalkonium chloride.Plant Science
How are energy transition and energy-related R&D investments effective in enabling decarbonization? Evidence from Nordic Countries by novel WLMC model
No full textPublic interest in climate change-related problems has been developing with the contribution of the recent energy crisis. Accordingly, countries have been increasing their efforts to decarbonize economies. In this context, energy transition and energy-related research and development (R&D) investments can be important strategic tools to be helpful to countries in the decarbonization of economies. Among all, Nordic countries have come to the force because of their well-known position as green economies. Hence, this study examines Nordic countries to investigate the impact of energy transition, renewable energy R&D investments (RRD), energy efficiency R&D investments (EEF) on carbon dioxide (CO2) emissions by performing wavelet local multiple correlation (WLMC) model and using data from 2000/1 to 2021/12. The outcomes reveal that (i) based on bi-variate cases, energy transition and RRD have a mixed impact on CO2 emissions in all countries across all frequencies || EEF has a declining impact on CO2 emissions in Norway (Sweden) at low and medium (very high) frequencies || (ii) according to four-variate cases, all variables have a combined increasing impact on CO2 emissions || (iii) RRD is the most influential dominant factor in all countries excluding Norway, where EEF is the pioneering one. Thus, the reach proves the varying impacts of energy transition, RRD, and EEF investments on CO2 emissions. In line with the outcomes of the novel WLMC model, various policy endeavors, such as focusing on displacement between sub-types of R&D investments, are argued to ensure the decarbonization of the economies.Environmental Science
When climate action is strategic The case of the European Neighbourhood Policy towards Egypt
No full textEnvironmental Studies || International Relations || Political Scienc
SCATTER SEARCH WITH STOCHASTIC BEAM SEARCH ON THE COALITION FORMATION PROBLEM
No full textThe coalition formation problem (CFP) is a crucial component of multi-agent systems (MAS), taking place in various areas in the real world with different variants. This study proposes a parallel metaheuristic algorithm for CFP. Our hybrid method combines two metaheuristic algorithms: the Scatter Search and the Beam Search. While the former ensures that the algorithm thor-oughly explores the search space, the latter exploits the visited regions. We re-design Scatter Search's original implementation to perform the time-consuming independent areas of the task in parallel. We employ a perturbation mechanism inside the Beam Search that performs a big jump in the search space when it cannot find any improvement. Moreover, we design a problem-specific repre-sentation that stores meta-information to save significant computational time. The proposed method is examined in parallel and sequential configurations and compared with an exact solver, recent metaheuristic algorithms, and the standard implementation of the Scatter Search. The experimental results show that our solution achieves considerable improvements in both configurations.Engineering, Multidisciplinary || Operations Research & Management Science || Mathematics, Interdisciplinary Application
Role of energy transition in easing energy security risk and decreasing CO2 emissions: Disaggregated level evidence from the USA by quantile-based models
No full textConsistent with the increasing environmental interest, the clean energy transition is highly critical to achieving decarbonization targets. Also, energy security has become an important topic under the shadow of the energy crisis,. Accordingly, countries have been trying to stimulate clean energy use to preserve the environment and ensure energy security. So, considering the leading role of economic size and volume of energy use, the study examines the USA to define whether energy transition helps decrease energy security risk (ESR) and curb CO 2 emissions. So, the study applies a disaggregated level analysis by performing quantile-based models for the period from 2001/Q1 through 2022/Q4. The results demonstrate that (i) the energy transition index decreases environmental ESR at higher quantiles and reliability ESR at lower and middle quantiles, whereas it is not beneficial in declining economic and geopolitical ESR || (ii) energy transition curbs CO 2 emissions in building and transport sectors at lower quantiles, whereas it does not help decrease CO 2 emissions in industrial and power sectors || (iii) energy transition is mostly ineffective on ESR, whereas it is highly effective in curbing CO 2 emissions in all sectors except for transport across various quantiles as time passes || (iv) the results differ according to the aggregated and disaggregated levels || (v) the results are consistent across main and alternative models. Hence, the study highlights the dominant effect of energy transition in curbing sectoral CO 2 emissions rather than easing ESR. Accordingly, the study discusses various policy implications for the USA.Environmental Science
The analysis of critical success factors for successful kaizen implementation during the COVID-19 pandemic: a textile industry case study
No full textPurposeThe primary objective of this research is to determine critical success factors (CSFs) that enable textile enterprises to effectively implement Kaizen, a Japanese concept of continuous development, particularly during disruptive situations. The study aims to provide insights into how Kaizen is specifically employed within the textile sector and to offer guidance for addressing future crises.Design/methodology/approachThis study employs a structured approach to determine CSFs for successful Kaizen implementation in the textile industry. The Triple Helix Actors structure, comprising business, academia and government representatives, is utilized to uncover essential insights. Additionally, the Matriced Impacts Croises-Multiplication Applique and Classement (MICMAC) analysis and interpretative structural modeling (ISM) techniques are applied to evaluate the influence of CSFs.FindingsThe research identifies 17 CSFs for successful Kaizen implementation in the textile industry through a comprehensive literature review and expert input. These factors are organized into a hierarchical structure with 5 distinct levels. Additionally, the application of the MICMAC analysis reveals three clusters of CSFs: linkage, dependent and independent, highlighting their interdependencies and impact.Originality/valueMajor contribution of this study is understanding how Kaizen can be effectively utilized in the textile industry, especially during disruptive events. The combination of the Triple Helix Actors structure, MICMAC analysis and ISM provides a unique perspective on the essential factors driving successful Kaizen implementation. The identification of CSFs and their categorization into clusters offer valuable insights for practitioners, policymakers and academia seeking to enhance the resilience and sustainability of the textile industry.Managemen
Hotel overbooking, capacity rationing and cooperation with third-parties: a two-period optimisation model
No full textWe propose a two-period optimisation model for a hotel revenue management (RM) problem where overbooking, capacity rationing and cooperation with third-party websites are simultaneously considered. In a Stackelberg game structure, the hotel first sets the price, and overbooking and rationing levels, and as the followers, third-parties decide their effort levels by a Nash game. The proposed model is solved using a genetic algorithm. An extensive numerical study is performed to investigate the effects of multiple night stays, hotel effort level, and hotel capacity on the decisions and the hotel profit. It is shown that the value of capacity rationing increases with multiple night stays and the expected profit of the third-parties is decreasing with the hotel effort level but the relation between the hotel effort level and profit is not monotone. As the hotel capacity is expanded, the effort level of the third-parties and the hotel profit increase. [Received: 1 December 2021 || Accepted: 26 May 2023]Engineering, Industrial || Operations Research & Management Scienc
Organotypic lung tissue culture as a preclinical model to study host-influenza A viral infection: A case for repurposing of nafamostat mesylate
No full textReliable and effective models for recapitulation of host-pathogen interactions are imperative for the discovery of potential therapeutics. Ex vivo models can fulfill these requirements as the multicellular native environment in the tissue is preserved and be utilized for toxicology, vaccine, infection and drug efficacy studies due to the presence of immune cells. Drug repurposing involves the identification of new applications for already approved drugs that are not related to the prime medical indication and emerged as a strategy to cope with slow pace of drug discovery due to high costs and necessary phases to reach the patients. Within the scope of the study, broadspectrum serine protease inhibitor nafamostat mesylate was repurposed to inhibit influenza A infection and evaluated by a translational ex vivo organotypic model, in which human organ-level responses can be achieved in preclinical safety studies of potential antiviral agents, along with in in vitro lung airway culture. The safe doses were determined as 10 mu M for in vitro, whereas 22 mu M for ex vivo to be applied for evaluation of host-pathogen interactions, which reduced virus infectivity, increased cell/tissue viability, and protected total protein content by reducing cell death with the inflammatory response. When the gene expression levels of specific proinflammatory, anti-inflammatory and cell surface markers involved in antiviral responses were examined, the significant inflammatory response represented by highly elevated mRNA gene expression levels of cytokines and chemokines combined with CDH5 downregulated by 5.1-fold supported the antiviral efficacy of NM and usability of ex vivo model as a preclinical infection model.Anatomy & Morphology || Cell Biolog
Enhancing lighting efficiency in deep-plan classroom: Artificial lighting and daylighting
No full textInsufficient light distribution throughout the classroom has a negative impact on students. Therefore, it is crucial to implement effective daylighting and artificial lighting strategies in educational buildings. To address this issue, a combination of a horizontal daylight tubes and an overhang was proposed for a classroom at the selected university. The aim was to enhance the availability of daylight, reduce glare and improvement of the artificial lighting system performance. The goal is to achieve a Spatial Daylight Autonomy (sDA) of at least 55% and an Annual Sunlight Exposure (ASE) of no more than 10% in the designated analysis area, as stipulated by the daylight assessment criteria outlined in LEEDv4 standards. In addition to the improvements in the daylight performance of the classroom, an artificial lighting system was proposed to replace the existing system, which creates homogeneous and sufficient lighting. Reducing the energy consumption of the proposed system is also among the desired targets while evaluating the proposed systems, Rhinoceros and ClimateStudio were used for daylight simulations and DIALux was used for artificial lighting simulations. The results show that proposed solutions were successful as intended. The sDA value for the zone with the lowest initial value was improved from 1.6% to 59.1%, while the ASE value for the zone with the highest initial value was improved from 16.1% to 9.7%. Additionally, energy consumption was reduced by 72.34%.Engineering, Multidisciplinar
Performance analysis of data-driven sustainable supply chain management
No full textTo be sustainable is essential for the long-term welfare of organisations, and to be sustainable, companies need to focus primarily on complicated supply chain structures. With digitalisation, the most critical issue of supply chains in the new industrial age is to be data-driven. Therefore, bridging the sustainable supply chain (SSC) to data-driven performance is necessary. The research question of this study is whether data-driven performance criteria can contribute to a SSC. Therefore, it is aimed to identify the various enablers and determine the relative importance of these enablers that are critical to the success of data-driven SSC management. To achieve this aim, this study proposes a holistic structure consisting of a detailed literature review and best worst method (BWM) implementation. This study's main contribution is integrating sustainability and data-driven dimensions by presenting criteria for the supply chain management.Managemen