Background: Microbiome-Inspired Green Infrastructure (MIGI) was recently proposed as an integrative system to promote healthy urban ecosystems, through multidisciplinary design. Specifically, MIGI is defined as nature-centric infrastructure restored and/or designed and managed to enhance health-promoting interactions between humans and environmental microbiomes, whilst sustaining microbially-mediated ecosystem functionality and resilience. MIGI also aims to stimulate a research agenda that focuses on considerations for the importance of urban environmental microbiomes. Objectives: In this paper we provide details of what MIGI entails from a bioscience and biodesign perspective, highlighting the potential dual benefits for human and ecosystem health. We present ‘what is known’ about the relationship between urban microbiomes, green infrastructure and environmental factors that may affect urban ecosystem health (ecosystem functionality and resilience as well as human health). We discuss how to start operationalising the MIGI concept based on current available knowledge, and present a horizon scan of emerging and future considerations in research and practice. We conclude by highlighting challenges to the implementation of MIGI and propose a series of workshops to discuss multi-stakeholder needs and opportunities. Discussion: This article will enable urban landscape managers to incorporate initial considerations for the microbiome in their development projects to promote human and ecosystem health. However, overcoming the challenges to operationalising MIGI will be essential to furthering its practical development. Although the research is in its infancy, there is considerable potential for MIGI to help deliver sustainable urban development driven by considerations for reciprocal relations between humans and the foundations of our ecosystems –– the microorganisms.

The new digital infrastructure has become an important basis for the green development of agriculture. This paper selects provincial sample data from 2006 to 2022, constructs an indicator system to measure new digital infrastructure and agricultural green total factor productivity, and explores how new digital infrastructure can promote agricultural green development. The results show that: (1) the new digital infrastructure has a significant role in promoting the green development of agriculture, and this conclusion is still valid after processing endogeneity and heteroscedasticity; (2) Technology and land factors play an intermediary role in the promotion of green agricultural development by the new digital infrastructure, that is, the new digital infrastructure helps to improve the quality and technical level of cultivated land and thus promote green agricultural development; (3) Labor force factors optimize the mediating role of technology factors, that is, the higher the quality of labor force, the stronger the role of the new digital infrastructure in promoting the green development of agriculture through the technological path; (4) The effect of new digital infrastructure on the green development of agriculture is obviously heterogeneous, and the effect is more obvious in northwest China and the regions with lower marketization level, higher environmental regulation level. This study is helpful to clarify the relationship between new digital infrastructure and agricultural green development in China, and provide corresponding policy suggestions for promoting regional agricultural green development.

Many cities are increasingly adopting blue-green infrastructure (BGI) to bolster resilience against environmental challenges. Beyond its well-acknowledged environmental benefits, the role of BGI in enhancing social resilience is becoming an equally important area of focus. However, the integration of BGI to foster social resilience presents complexities, stemming from the evolving and occasionally ambiguous definition of social resilience. Considering the broad application of BGI across various disciplines makes the evaluation of social resilience within a BGI framework complex. Consequently, a structured approach to develop a clear framework tailored to understanding and measuring social resilience in a BGI setting is needed. This study consolidates various existing frameworks of social resilience, especially utilizing the detailed 5S framework proposed by Saja et al. [1]. It integrates findings from an extensive review of literature on social resilience to develop a novel conceptual framework, the BGI Social Resilience Framework. This new framework specifically aims to capture the distinct social aspects and advantages associated with BGI. The BGI Social Resilience Framework is organized into a three-tier model focusing on four critical aspects of social resilience—social values, social capital, social structure, and social equity—and explores how these aspects are interconnected. Characteristics and indicators are customized to accomodate the BGI context in a way that integrates the physical and human dimensions within a comprehensive approach to measurement that uses a combination of qualitative and quantitative methods. Specifically, this research formulates a theoretical framework for BGI with the aim of investigating BGI strategies and viewpoints that bolster social resilience. The BGI Social Resilience Framework takes into account the varied demographics and the physical characteristics of urban areas to explore ways to create BGI spaces that are more inclusive and contribute to the enhancement of social resilience.

This paper discusses Green Infrastructure, which can be considered a useful tool in the process of ensuring the sustainable development of urban structures in the Carpathian region. It allows for achieving a better quality of the environment of human life and healthy wildlife linkages. The element that supports defining information about the existing state of Green Infrastructure and its resources is the Green Infrastructure fragmentation coefficient based on edge effect calculations, which is the relation between the edge of the patch (circumference) to its surface area [1, 2]. With the use of model analysis of Green Infrastructure, it is possible to implement the provisions of the Carpathian Convention and coordinate planning documents that facilitate the sustainable development of spatial structures. Our study on the state of Green Infrastructure in rural areas of the Polish Carpathian Mountains is a source of knowledge about the quality of this area, its natural environment and fragmentation. Determining the territory’s Green Infrastructure fragmentation coefficient provides an opportunity for higher-precision studies and the detection of threats and integration of GI fragments and addressing proper solutions in conflict areas.

Due to urban warming, energy demand for cooling buildings is rising. The current study used CitySim to estimate the cooling energy requirements for 40 buildings in Downtown, Dubai using high-resolution climate data from weather research and forecasting (WRF) coupled with single layer urban canopy model (SLUCM). Simulating the four mitigation scenarios allowed for the examination of the reduction in cooling load caused by the addition of greenery at a rate ranging from 25% to 100%. The insulated building's cooling demand reduced by a maximum of 13.89% under 100% GI (M4). Scenario M4 resulted in a reduction of 4.6 kWh/m2 and 3.1 kWh/m2 for the non-insulated and insulated low-rise residential buildings, respectively, while the high-rise buildings saw a reduction of 3.09-4.91 kWh/m2 for the non-insulated and 2.07-3.09 kWh/m2 for insulated buildings. This study offered a potential remedy to deal with the problem of urban heating in subtropical environments.

In the quest for more sustainable urban landscape development, the concept of ‘green infrastructure’ (GI) has become central in policy documents and as a multifunctional general planning tool. GI is not however a simple and unambiguous solution. While there in policy documents are claims for more and connected GI, actual urban development takes another direction. The densifying imperative is hard to combine with an increased and more connected GI. This paper argues for a critical and diversified approach to the concept of GI, to facilitate its implementation in urban planning and management. While GI most often is seen as a common asset and a public good, the actual land use negotiations and management responsibilities cannot be limited to a public service discourse, but should address more clearly a variety of actors. Linguistic as well as spatial definitions of the two relevant dichotomies of ‘green-grey’ and ‘public-private’ are crucial in GI location, design, construction and management, it is argued. Overarching representations of GI will be needed, but also – and linked to it – a spatial storm water plan and an overall plan for public space. The development over time will need an intersectorial implementation and management program. Thus some of the GI intentions may be implemented in planning processes, some through reorganisation and redesign of public space, and some by agreements with landowners.

Research on urban heat mitigation has been growing in recent years with many of the studies focusing on green infrastructure (GI) as a strategy to mitigate the adverse effects of Urban Heat Island (UHI). This paper aims at presenting a review of the range of findings from GI research for urban heat mitigation through a review of scientific articles published during the years 2009-2019. This research includes a review of the different types of GI and its contribution for urban heat mitigation and human thermal comfort. In addition to analyzing different mitigation strategies, numerical simulation tools that are commonly used are also reviewed. It is seen that ENVI-met is one of the modelling tools that is considered as a reliable tool to simulate different mitigation strategies and hence has been widely used in the recent past. Considering its popularity in urban microclimate studies, this article also provides a review of ENVI-met simulation results that were reported in the reviewed papers. It was observed that the majority of the research was conducted on a limited spatial scale and focused on temperature and human thermal comfort.

This paper describes the feasibility and probable benefits associated with greening the Tahliah Channel, a concrete drainage channel that was originally built to relieve urban flooding in Jeddah City, Saudi Arabia. It includes an estimation of irrigation needs for channel greening based on a standardized planting specification. The study also demonstrates alternative strategies for meeting the required irrigation demand, including water harvesting and graywater reuse on a residential scale. The study shows that greening Tahliah Channel is possible relying mainly on graywater reuse from the surrounding buildings. Also, the study shows that rainwater harvesting is not a reliable source for irrigation. Rather, it can cover only part of the irrigation needs (6%) and so can be used as a secondary supporting source. The positive results of this case study will be of interest to those in arid countries who are looking to upgrade and replace traditional, single function drainage infrastructure with more sustainable, green infrastructure systems. More specifically, the objectives of the study are consistent with the goals of the Saudi government’s ongoing initiative that advocates for more resilient and sustainable cities. (Vision 2030 year).

This study maps and quantifies the green infrastructure of the cities of Bujumbura, Kinshasa and Lubumbashi. A remote sensing approach, in conjunction with landscape ecology metrics, characterized this analysis, which was based upon three Landsat images acquired in 2000, 2013 and 2022 for each city. Spatial pattern indices show that green infrastructure was suppressed in the cities of Bujumbura and Kinshasa, in contrast to the city of Lubumbashi, which was characterized by a fragmentation of its green areas. Additionally, the values of the stability, aggregation and fractal dimension metrics suggest that the city of Bujumbura underwent rather intense dynamics and a reduction in the continuity of its green areas, while the city of Kinshasa shows weaker dynamics and tendances of patch aggregation in the study period. The city of Lubumbashi, in its turn, exhibits strong dynamics and an aggregation of its green infrastructure, in a context of a high level of anthropization. The evolution of the Normalized Difference Vegetation Index shows a sawtooth evolution of tall vegetation patches for the city of Bujumbura, against a gradual decrease in Kinshasa and Lubumbashi. It is advocated that the urban growth of these cities should be planned carefully in order to integrate the presence of sufficient green infrastructure.

In European countries many measures are carried out to improve the disadvantaged conditions and socio-economic marginality of rural areas in comparison with central places. These conditions also affect the quality of travel for visitors and tourists. Therefore, in response to a 'new' tourist demand, motivated also by the restrictions following the spread of the Covid-19 virus in recent years, the institutions and the different local actors are working more incisively to improve rural areas. The rural tourism services offer, combined with the Green Infrastructure (GI) project, at different scales - from local to regional - prove to be interesting territorial development strategies to achieve the Agenda 2030 objectives. This contribution considers the Sulcis Iglesiente - Guspinese area, in the Sardinia Region (IT), as a case study. In this area, the landscape context is marked by past mining activity and the project of a path of historical, cultural and religious values has proved to be an activator of regenerative processes, in environmental, social and economic terms. The present study proposes a methodological approach to develop an index (FI - Feasibility Index) to assess the feasibility of the Stop Places (SPs) schemes along a horse trail to integrate the current slow mobility by bicycle and pedestrian in the bioregion.

Key elements of Blue-Green Infrastructure are vegetation and stormwater storage. A combination of a bioretention cell with an underlying trench (BC-T) serving as a tree pit is often used in dense urban environments. An adequate ratio of drained area to bioretention cell area is a crucial design parameter. The ratio is derived from the hydrological balance; however, input data are often difficult to obtain or uncertain. The goal is to study the sensitivity of such data (tree water uptake and water holding capacities of soil filter and trench substrate) in the BC-T design. Sensitivity analysis is performed for the setup of a BC-T used in Prague, Czech Republic. A 10-year rainfall series (1 hour resolution) is used as an input. Data that are subject to the sensitivity analysis are changed for different trench exfiltration rates, and the effect on the size of the drained area is studied. At low trench exfiltration rates (1.8 mm.h-1), both the water holding capacity of the trench substrate and potential tree water uptake have a significant influence (more than a 20% change in the size of the drained area) and cannot be neglected. At good exfiltration rates (more than 18 mm.h-1) or when the trench is equipped with an underdrain, all studied parameters can be neglected. However, it is recommended to reduce the size of the drained area by 10-20%.

Green Infrastructure (GI) is increasingly prioritised in landscape policy and planning, due to its potential to benefit ecosystems and enhance wildlife conservation. However, due to the uneven distribution of protected areas (PAs) and the fragmentation of habitats more generally, multi-level policy strategies are needed to create an integrated GI network bridging national, regional and local scales. To help address this challenge, we present proposals to integrate GI elements for the province of Almeria, southeast Spain. We delimit and define key GI elements, and apply GIS-based connectivity tools to generate ecological corridors connecting the province’s 35 PAs. Currently, the PAs are threatened by the advance of intensive greenhouse agriculture and tourism-related urban growth of the municipalities to which they belong. Common patterns in the location of the most suitable areas for the development of GI can be identified. New GI networks would be located along the coast, specifically in the western part of the study area. They would also occupy the valleys of the main rivers of the province. Around 50% of the area occupied by the proposed corridors would be located in places of medium and high suitability for the movement of species between core areas.

Green Stormwater Infrastructure (GSI), a sustainable engineering design approach for managing urban stormwater runoff, has long been recommended as an alternative to conventional conveyance-based stormwater management strategies to mitigate the adverse impact of sprawling urbanization. Hydrological and hydraulic simulations of small-scale GSI measures in densely urbanized micro watersheds require high-resolution spatial databases of urban land use, stormwater structures, and topography. This study presents a highly resolved Storm Water Management Model developed under considerable spatial data constraints. It evaluates the cumulative effect of the implementation of dispersed, retrofitted, small-scale GSI measures in a heavily urbanized micro watershed of Costa Rica. Our methodology includes a high-resolution digital elevation model based on Google Earth information, whose accuracy was sufficient to determine flow patterns and slopes, as well as to approximate the subsurface stormwater structures. The model produced satisfactory results in event-based calibration and validation, which ensured the reliability of the data collection procedure. Simulating the implementation of GSI shows that dispersed, retrofitted, small-scale measures could significantly reduce impermeable surface runoff (peak runoff reduction up to 40%) during frequent, less intense storm events and delay peak surface runoff 5-10 minutes. The presented approach can benefit stormwater practitioners and modelers conducting small scale hydrological simulation under spatial data constraint.

The management of urban water has evolved from single-function systems to more sustainable designs promoting society and nature as inputs to engineer novel infrastructure. In transdisciplinary research, co-design refers to a design thinking strategy in which people jointly frame a problem-solution. This article presents a conceptual framework to assess a case study focusing on the process of co-design and implementation of green infrastructure as a prototype for stormwater management. The evaluation is carried out from a self-reflective post-implementation perspective. Research activities are translated into the framework to evaluate conditions shaping the trajectory of the prototype. As a result, key aspects driving the research regarding levels of stakeholder participation and dimensions of power are identified. Planning resilient co-design strategies to retrofit urban spaces is necessary to avoid unintended consequences, especially at the initial experimental stages. This study aims to contribute to the continuous improvement of pilot strategies in urban spaces by providing a framework for a structured evaluation of research experiences.

Green Infrastructures (GI) are considered key to reconcile ecological and social benefits by providing multiple functions. The concept is increasingly promoted and guidelines for its implementation have been developed in many countries and regions of the Western Hemisphere. However, for other parts of the world, especially for countries with less developed infrastructures, promotion, guidance for decision-making and manuals for GI are often lacking. But the state of infrastructure development and often unplanned character of settlements in the Global South differ and result in specific constraints as well as demands to GI that need to be addressed explicitly. This study presents a methodological approach to explicitly address the specific conditions and physical limitations to GI development in urban areas of the Global South. A four step methodology was developed to assess the implementation potential for retrofitted and multifunctional urban green infrastructure in public areas. An initial site analysis (1) and the definition of design criteria as well as general strategies (2) to achieve the different dimensions of multi-functionality are the basis to derive spatial typologies (3) for GI elements and finally the spatial suitability assessment for potential placements (4). An application of the methodology to a study area in the metropolitan region of San José, Costa Rica, shows exemplarily that the potential to improve the hydrological conditions (up to 34% of surface runoff reduction), ecological conditions (increase of green space by 2,2 %, creation of 1500 m length of roadside greenery and two new habitat types), and social conditions (2.200 m of road type upgrading) of multi-functionality of the site through Green Infrastructures. These assessment results of different multi-functionality dimension can serve as a guidance for GI promotion and implementation in urban areas of the Global South.

Achieving Urban Flood Resilience (UFR) is essential for modern societies, requiring the implementation of effective practices in different countries to mitigate hydrological events. Green Water Systems (GWS) emerge as a promising alternative to achieve UFR, but they are still poorly explored and present varied definitions. This article aims to define GWS within the framework of sustainable practices and propose a regulation that promotes UFR. Through a systematic review of existing definitions and an analy-sis of international regulations on Sustainable Urban Drainage Systems (SuDS), the study reveals diverse perceptions and applications of GWS and their role in Blue-Green Infrastructure (BGI). The research proposes a standardized definition of GWS and their role in Blue – Green Infrastructure (BGI). The research proposes a standardized definition of GWS and the implementation of SuDS in Peru, addressing the current knowledge gap and contributing to the development of sustainable urban infrastructure.

Cities are small on earth’s surface but they are the most attractive places for people to live and work; cities are developing quickly, thus it’s important to keep it a better quality place to live as it has the major of the economic activities and more job opportunities and other social and economic advantages to be a more green and sustainable place. Seeking to achieve sustainable use of ecosystems and conserve natural resources in the city of Prague; integrating ecological sustainability goals, the political borders as a reflection of urban development in the city, and ecosystems edges in blue and green functions impact the city development, and present opportunities to create strategies for green and blue infrastructure and clarifying threats could slow down the process to achieve the sustainability and greenery application. Also checking possible urban areas for development like brownfields and clarifying their relationship with political borders and ecosystems to find possible areas to add for sustainable green use, which will create better places for people to live and raise the value of life as well.

Urban green spaces provide a range of environmental and health benefits, which may become even more critical during times of crisis such as the current COVID-19 pandemic. However, with a radical shift in mobility, additional concerns over safety, and access temporarily restricted during the implementation of social distancing policies, the experience and use of urban green spaces may be reduced. This is particularly concerning for densely populated cities like New York, considered the first U.S. epicenter or vanguard of the outbreak. To better understand the impact of COVID-19 on the perception and use of urban green spaces, we conducted a social survey during the early months of the Covid-19 pandemic in New York City (May 13 - June 15, 2020). The results of the survey show respondents continued to use urban green spaces during the pandemic and consider them to be more important for mental and physical health than before the pandemic began. However, the study revealed a pattern of concerns residents have about green space accessibility and safety, and found key differences between the concerns and needs of different populations, suggesting a crucial role for inclusive decision-making, support for additional management strategies, and urban ecosystem governance that reflect the differential values, needs and concerns of communities across the City. As urban centers face looming budget cuts and reduced capacity, this study provides some empirical evidence to illustrate the value of urban green spaces as critical urban infrastructure, and may have implications for funding, policy, and management, of urban green spaces in NYC, with potential applications to other cities, particularly during times of crisis.

Green infrastructure systems are often overdesigned. This may be a byproduct of static sizing (e.g., accounting for a design storm’s runoff volume but not exfiltration rates) or may be deliberate (e.g., buffering against performance loss through time). Regardless, overdesign may compromise plants’ access to water in systems where soil pits are embedded in infiltration beds. It could raise the storm size required for water to reach soil pits, reducing water availability between storms, which could ultimately induce plant physiological stress. This study investigated the hydrological dynamics and water relations of a tree trench system suspected to have been overbuilt and identified factors contributing to, compounding, and mitigating the risk of plant stress. Results provided strong evidence that the abovementioned processes played out. Water in the infiltration bed reached soil pits only once in three years, with that event occurring during a hydrant release. Moreover, minimal water was retained in the soil pit during the event due to the hydraulic properties of the soil media. Through a growing season, one of the two tree types frequently experienced water stress, while the other did so only rarely. These contrasting responses can likely be attributed to roots either being largely confined to the soil pits or reaching a deeper water source. Implications of these results for green infrastructure design are considered.

The Urban heat island (UHI) effect has evolved into one of the key environmental problems affecting urban ecological environment and sustainable development. Based on 52 Urban Thermal Heat spots (UTHSs) with significant differences between land use structure and UGI spatial layout within the influence range of UHI in Shanghai, Landsat-8/9 satellite images were used to construct a high-dimensional data set reflecting the impact of built environment components on urban thermal environment. Descriptive statistical analysis was used to analyze the spatial difference qualitatively. Using stepwise regression model and partial least square regression (PLSR) model, the complex response relationship between UGI pattern differentiation and urban thermal environment in three spatial stratification ranges of UTHSs was quantitatively analyzed. Overall, the statistical explanatory power of the partial least square regression PLSR model is due to the stepwise regression model. The PLSR model points out that moderately increasing the average building height, CA, PLAND, LSI and LPI play a positive role in inhibiting/slowing down the growth of LST (land surface temperature), and the cooling effect of index weights decreases in order. However, the interaction effects of CA×Cohesion×AI×LPI and PLAND×CA×Cohesion×AI×LPI exert relatively small weight on the cooling effect, and according to the results, suggestions such as UGI structure and urban construction layout optimization can effectively alleviate the urban heat island effect are proposed.

We give three new authentication schemes without secrecy. The first two on finite fields and Galois rings, using Gray map for this link. The third construction is given on Galois rings. The main achievement in this work is to obtain optimal impersonation and substitution probabilities in the schemes. Additionally, in the first and second scheme, we simplify the source space and bring a better relationship between the size of the message space and the key space than the given in [8]. Finally, we provide a third scheme on Galois rings, which generalizes the scheme over finite fields constructed in [9].

Two new systematic authentication codes based on the Gray map over a Galois ring are introduced. The first introduced code attains optimal impersonation and substitution probabilities. The second code improves space sizes but it does not attain optimal probabilities. Besides it is conditioned to the existence of a special class of bent maps on Galois rings.

In recent years, drones have become increasingly prevalent in a wide range of applications, performing complex and critical tasks. To accomplish these tasks, drones cooperate by forming a Fly Ad-hoc Network (FANET) using specific routing protocols for communication. However, most of the routing protocols used in this type of network lack appropriate built-in security mechanisms, which creates numerous security challenges and concerns. To reduce the resulting security vulnerabilities and mitigate the impact of potential attacks, it is crucial to address these challenges before any deployment of FANETs. In this paper, we address two of the most harmful routing attacks - Sybil and Gray Hole and propose mitigating techniques to alleviate these attacks on FANET routing protocols. The proposed solution is secGPSR a secure version of the Greedy Perimeter Stateless Routing Protocol (GPSR). We validate the robustness of secGPSR through simulation using Omnet++ and present the results which show its effectiveness against Sybil and Gray Hole attacks.

Size-based fungal growth studies have limitations. For example, the growth in size stops in closed systems once it reaches the borders and poorly describes the metabolic status, especially in the stationary phase. This might lead mycotoxin studies to unrealistic results. Color change could be a viable alternative as pigments are results of the mold’s metabolic activity. This study aimed to verify the possibility of using gray values and the RGB system to analyze the growth of Fusarium graminearum. It consisted color and area measurement using the ImageJ software for specimens grown in yeast extract agar (YEA). The results suggest the usability of color and gray values as reliable tools to analyze the growth of F. graminearum.

Objective: We aimed to clarify the differences in the association between re-admission for heart failure (HF) and left atrial (LA) overload indices by sex in heart failure and a preserved ejection fraction (HFpEF). Methods: We analysed 898 HFpEF patients hospitalized for acute decompensated HF. Blood tests and transthoracic echocardiography were performed before discharge. The primary endpoint was re-admission for HF during the first year. Results: The ratio of diastolic elastance to arterial elastance (p=0.014), a relative index of LA pressure overload, in men and LA volume index (LAVI, p=0.020) in women were significant for re-admission for HF during the first year in the multivariable Fine-Gray analysis. Stroke volume (SV)/LA volume (LAV), another index for LAV overload, was not a significant prognostic factor of re-admission for HF during this time. Conclusion: LA overload was an important prognostic factor for HF re-readmission during the first year after enrolment in patients with HFpEF, but the indices relating to LA overload differed by sex.

Protrusive defects on the color filter of thin-film transistor (TFT) liquid crystal displays (LCDs) frequently damage the valuable photomask. An fast method using side-view illuminations associated with digital charge-couple devices (CCDs) to detect the protrusive defect in the four substrates, which are the black matrix (BM), red, green, and blue. Between the photomask and substrate, the depth of field (DOF) is normally 300 μm for the proximity-type aligner; we select the four substrates to evaluate the detectability in the task. The experiment is capable of detecting measurements of 300 μm and even lower than 100 μm can be assessed successfully. The maximum error of the measurement is within 6% among the four samples. Furthermore, the uncertainty analysis of three standard deviations is conducted. Thus, the method is cost-effective to prevent damage for valuable photomasks in the flat panel display industry.

Guayule (Parthenium argentatum Gray) is a shrub native of the arid regions of Mexico. In the last decades, significant attention for its cultivation has risen because it is the raw material for the production of hypoallergenic natural rubber. Guayule biomass contains also high amounts of resin, which is not normally exploited in any way. Among other sesquiterpenic esters, guayulins (i.e. the parteniol esters of cinnamic acid, guayulin A, or of anisic acid, guayulin B) are contained in resin. In addition, minor amounts of guayulin C and guayulin D are formed by degradation/oxidation of guayulins A and B, respectively. Guayulins likely act as cinnamate and p-anisate reservoirs for Guayule shrub, in addition, it has been postulated that they might have a key role in the chemical defense system of Guayule. Furthermore, it seems reasonable that guayulins may possess significant biological properties (e.g. antibacterial and anticancer activities), in close analogy with those shown by sesquiterpene lactones contained in many other species of Parthenum genus. As a matter of fact, guayulins A and B play an important role in the synthesis of antineoplastics used in breast cancer treatment. In this contribution we propose an original and validated RP-HPLC approach to the simultaneous quantification of guayulins A, B, C and D. The procedure of resin extraction from Guayule biomass has been optimized in terms of both extraction method and solvent. RP-HPLC separation has been accomplished by an Ascentis^® C18 column under isocratic elution with a 80:20 (v:v) acetonitrile:water mixture. Validation was carried out in terms of limits of detection and quantification, linearity, precision, and trueness. Finally, the method was tested with a number of fresh and seasoned samples of spontaneous Guayule shrub from Mexico.

Environmental concern has attained a higher level than in the past, with numerous organisations, including the pioneering "Green Banking" institution, expressing their concern. This study examines the relationship between green brand innovativeness and perceived value, as well as its effect on green brand loyalty. It expands on previous research that investigated the differences between innovation and innovativeness and their effects on brand loyalty. In addition, the role of perceived green value as a mediator and consumer green knowledge as a moderator in the formation of green brand loyalty is investigated. To test the conceptual model, a convenience-sampling survey of 600 Ethiopian customers was administered to capture a sample of respondents for the conceptual model. For data analysis, structural equation modelling (SEM) was employed. The results indicate that consumers' perceptions of green value have indirect effects on brand loyalty and direct effects on the innovativeness of green brands. In addition, green knowledge mediates the relationship between green brand innovation and green value perception in a significant way. Therefore, organisations should concentrate on enhancing consumers' environmental literacy and nurturing positive attitudes towards green brands in order to increase green brand loyalty.

Background/Objectives: Interest in diversity is growing worldwide. Today, understanding and social acceptance of diverse people is becoming increasingly important. Therefore, in this study, we aimed to clarify the relationship between gray matter volume (GMV), which is thought to reflect brain health, and understanding of diversity (gender, LGBTQ, and race). Methods: GMV was the value of the Gray Matter Brain Healthcare Quotient (GM-BHQ) based on MRI image analysis. Meanwhile, diversity was calculated from the answers to the psychological questions included in the World Values Survey Wave 7 (WVS7). Results: As a result of the analysis, in the group of participants with the highest understanding of diversity (PHUD. n = 11), not only the GMV at the whole brain level but also the GMV of the central executive network (CEN) and saliency network (SN) were shown to be significantly higher than the theoretical value estimated from sex, age, and BMI at the 5% level. In addition, the GMV of the default mode network (DMN) was also shown to be higher than the theoretical value at the 10% level. Meanwhile, in the group of others (n = 10), there was no significant difference from the theoretical value. These differences between PHUD and others were also observed when comparing the two. Conclusions: These results suggest that understanding diversity requires a healthy brain, centered on three networks that govern rational judgment, emotion regulation, other-awareness, self-awareness, and the valuing of actions. This is the first study to show that brain structure is related to understanding and acceptance of diverse people.

This article presents a new method of segmenting images with gray levels. The method is based on determining several thresholds for separation of gray levels. The determination of these thresholds is done using the certainty of the neutrosophic information. The concept of this method can be stated simply: to choose the local maximums for the neutrosophic certainty.

Gray cast iron is one of the most important engineering materials that has many applications in various industries including automotive and machinery manufacturing due to its mechanical properties, wear resistance, machining potentials and low price. In this research effect of adding aluminum and silicon to composition of gray cast iron on microstructure and wear resistance was studied. Moreover, it was investigated the role of formation of Fe-Al-Si intermetallic compound in final properties of the alloy. For studying wear resistance of samples pin-on-disc method was carried out. The results showed that addition of aluminum to gray cast iron causes formation of ferrite matrix, which leads to a decrease in hardness value. Increasing silicon content up to 2 wt. % in cast iron with 4 wt. % aluminum intensifies the formation of ferrite matrix, while further increase to 3 wt. % causes emerging a Fe-Al-Si intermetallic phase. Improvement in hardness value was achieved by increasing silicon content from 3 wt. % to 4 wt. % due to the increased percentage of intermetallic phase. Effect of intermetallic phase on decreasing wear rate was showed by studying microstructure and hardness values, however the lowest wear resistance was observed in aluminum bearing cast iron containing 2 wt. % silicon.

Gray cast iron is one of the most important engineering materials that has many applications in various industries including automotive and machinery manufacturing due to its mechanical properties, wear resistance, machining potentials and low price. In this research effect of adding aluminum and silicon to composition of gray cast iron on microstructure and wear resistance was studied. Moreover, it was investigated the role of formation of Fe-Al-Si intermetallic compound in final properties of the alloy. For studying wear resistance of samples pin-on-disc method was carried out. The results showed that addition of aluminum to gray cast iron causes formation of ferrite matrix, which leads to a decrease in hardness value. Increasing silicon content up to 2 wt. % in cast iron with 4 wt. % aluminum intensifies the formation of ferrite matrix, while further increase to 3 wt. % causes emerging a Fe-Al-Si intermetallic phase. Improvement in hardness value was achieved by increasing silicon content from 3 wt. % to 4 wt. % due to the increased percentage of intermetallic phase. Effect of intermetallic phase on decreasing wear rate was showed by studying microstructure and hardness values, however the lowest wear resistance was observed in aluminum bearing cast iron containing 2 wt. % silicon.

Major emergencies can have a devastating impact on society, becoming a catalyst for social disorder and unrest and a trigger for social or political change. In today's world of frequent emergencies, the emergency management capacity of local governments is key to promoting safe operations and maintaining stability in cities and towns. Aiming to explore the direction and focus of local government emergency management capacity building, this paper establishes a local government emergency capacity evaluation system based on the emergency management process and combines Gray-Dematel, a gray decision laboratory analysis method, and AISM, an adversarial explanatory agency model, to derive the importance and intrinsic relationship among emergency capacity indicators. The algorithm describes the importance degree of each indicator in the system and also helps better understand the intrinsic relationship among the indicators. The outcomes of this research can be used to outline directional suggestions for the development of local government emergency response capacity and provide a new theoretical basis for more effective construction of local government emergency response capacity.

This article presents a new method of segmenting grayscale images by minimizing Shannon's neutrosophic entropy. For the proposed segmentation method, the neutrosophic information components, i.e., the degree of truth, the degree of neutrality and the degree of falsity are defined taking into account the belonging to the segmented regions and at the same time to the separation threshold area. The principle of the method is simple and easy to understand and can lead to multiple thresholds. The efficacy of the method is illustrated using some test gray level images. The experimental results show that the proposed method has good performance for segmentation with optimal gray level thresholds.

The main purpose of study is to identify the impact of COVID-19 pandemic on the green financing of banks and non-bank financial institutions (NBFIs) in an emerging economy such as Bangladesh. Also, this study shows the green banking activities of the banks and NBFIs during the pandemic. To analyze the impact of the pandemic on green financing, secondary data were obtained from the quarterly and annual reports of Bangladesh Bank (BB) on green financing as well as the annual reports and websites of 61 banks and 34 NBFIs in Bangladesh for the period 2021–2019. Subsequently, the study deployed dependent t-test statistics, growth rate (year-on-year), descriptive statistics, relative percentage changes, and varying tables and graphs to analyze the obtained secondary data. The empirical findings revealed that during the COVID-19 pandemic, there was an increase in green finance for all banks and NBFIs compared to before the epidemic, indicating that the pandemic had no negative impact on the total green finance growth of all banks and NBFIs. On the other hand, compared to the pre-pandemic period, bank-wise growth in green financing was higher for state-owned commercial banks (SOCBs), specialized banks (SDBs), and private commercial banks (PCBs) but lower for foreign-owned commercial banks (FCBs) during the COVID-19 epidemic. This suggests that the pandemic does not affect the expansion of green finance by SOCBs, SDBs and PCBs but significantly impacted the growth of green financing by FCBs. Furthermore, the research findings showed that the total outstanding and classified loans within the green finance investment decrease for both banks and NBFIs during the COVID-19 pandemic. The results indicated that the Bangladeshi banks’ level of automation towards green banking were satisfactory during the pandemic. Therefore, major policy implications for the green economic recovery by the government, BB, and managers of the banks and financial institutions in emerging economies like Bangladesh were discussed.

CD4 count recovery is the main goal for an HIV patient who initiated ART. Some patients respond positively to ART and attain CD4 count recovery, some patients might fail to recover their CD4 count due to non-adherence, treatment resistance, and virological failure, leading to HIV-related complications and death. The purpose of this study is to find the determinants of death in patients who failed to recover their CD4 count after initiating antiretroviral therapy. The data used in this study was obtained from KwaZulu-Natal, South Africa, where 2528 HIV-infected patients with a baseline CD4 count of 200 cells/ were initiated on ART. We used a Fine-Gray sub-distribution hazard and cumulative incidence function to estimate potential confounding factors of death, where CD4 count recovery was a competing event for failure due to death. Patients who were not suffering from tuberculosis were 1.33 times at risk of dying before attaining CD4 count recovery [aSHR 1.33; 95% CI (0.96-1.85] compared to those who had no tuberculosis. Rural patients had a higher risk of not recovering and leading to death [aSHR 1.97; 95%CI (1.57-2.47)] than those from urban areas. The patient’s tuberculosis status, viral load, regimen, baseline CD4 count, and location were significant contributors to death before CD4 count recovery. Intervention programs targeting HIV testing in rural areas for early ART initiation and promoting treatment adherence are recommended.

This article presents a method of segmenting images with gray levels that uses Onicescu's information energy calculated in the context of the neutrosophic theory. Starting from the information energy calculation for complete neutrosophic information, it is shown how to extend its calculation for incomplete and inconsistent neutrosophic information. The segmentation method is based on calculation of thresholds for separating the gray levels using the local maximum points of the Onicescu information energy.

The identification of linear dynamic systems with static nonlinearities in the delta domain has been presented in this paper applying a firefly based hybrid meta-heuristic algorithm integrating Firefly algorithm (FA) and Gray wolf optimizer (GWO). FA diversifies the search space globally while GWO intensifies the solutions through its local search abilities. A test system with continuous polynomial nonlinearities has been considered for hammerstein and wiener system identification in continuous, discrete and delta domain. Delta operator modelling unifies system identification of continuous-time systems with discrete domain at higher sampling frequency. Pseudo random binary sequence, contaminated with white noise, has been taken up as the input signal to estimate the unknown model parameters as well as static nonlinear coefficients. The hybrid algorithm not only outperforms the parent heuristics of which they are constituted but also proves better as compared to some standard and latest heuristic approaches reported in the literature.

To meet the dual-carbon objective, China's economy needs to move from a carbon-intensive to a green economy. Green technology innovation and renewable energy development are key to promoting green economic growth. The study uses 2010–2022 provincial panel data from 30 Chinese provinces. The super-efficient SBM model measures the province's green economic growth index. A panel fixed-effects model is used to experimentally evaluate how green technology innovation and renewable energy development affect green economic growth. Green financing moderates and a panel threshold model tests the threshold effect of renewable energy development on green economic growth. The results demonstrate that (1) China's green economic growth is rising and has a "U" shape. (2) all selected variables significantly impact green economic growth. However, population density, government intervention, and industrial structure are inversely associated with GEG. Green economic growth is significantly boosted by the moderate role of green finance in the development of renewable energy and green technological innovation. (3) Renewable energy development has a single threshold non-linear effect on green economic growth, depending on its development level and green technological innovation. Considering China's current condition and research findings, this study examines the green energy transition to promote green economic growth and high-quality economic development. Meanwhile, puts forward some important policy recommendations.

There is an overall scientific consensus that public space and, mainly, space with a high ecological index – most notably experienced in green areas – positively affects individual and collective well-being and urban dwellers’ physical and mental health. However, the ‘reality check’ indicates difficulties in translating the assumed benefits of green space into implementable interventions in urban environments. To examine such an ‘implementation gap’ on the case of Zurich seems valid, given that the ‘green urban agenda’ debate has been embedded in numerous Swiss policies (from the federal to the municipal levels). In narrow terms, the research first focuses on Zurich’s district 9 consisting of two neighborhoods (Altstetten and Albisrieden) – the area under ongoing densification yet with a variety of green spaces, to then elucidate four green space clusters and their 400-meter catchment areas in the mentioned district. The mixed-method approach has been applied at three analytical levels: 1) documentary analysis of multi-scale national policy toolkits, to identify the critical tenets associated with the ‘green urban agenda’, 2) assessment of green spaces in Zurich’s district 9 based on online available quantitative data and on-site observation, to determine their provision, types, size and mutual connectivity, and 3) analysis of four green space clusters within the mentioned district through on-site observation, to identify green space attributes and main activities. Through critical mutual examination of the identified ‘green urban agenda’ principles in the national policies, on the one hand, and green space attributes, on the other, the research findings reveal the extent of the convergence and/or divergence between the ‘green urban agenda’ policy trends and their implementation in practice.

The global movement of inputs, raw materials, products, and the marketing of products requires the use of supply chains. Green logistics refers to the set of policies and measures aimed at reducing the environmental impacts generated by logistics activities. The traditional supply chain has a certain inability to adapt to the rules agreed in Coop 15. The Green Supply Chain deals with the distribution flows of goods with a view to generating low environmental impact. The Green Supply Chain (GSC) involves aspects of reducing negative impacts throughout the logistics chain, from raw material suppliers, production to the distribution of the product to the customer. In this way, this article seeks to identify the factors that generate negative impacts in the traditional Supply Chain, thus helping to decarbonize it, and create a path for the development of the GSC and thus avoid interruptions in the distribution flow due to not meeting environmental targets. The main problem in decarbonizing the Supply Chain is its difficulty in complying with the rules agreed by the nations in COOP 15. To this end, a systematic literature review was carried out based on the available literature. Based on various articles and books, the parameters that define a Green Supply Chain and the factors that generate environmental impacts in conventional chains were identified. As a result, it was possible to verify a positive relationship between the carbon emission reduction factors that are linked to the supply chain performance factors found in the literature. Of the factors relating to the decarbonization of supply chains, some were more clearly related, such as reducing carbon emissions, reducing environmental risks and the ability to operate using new technologies. Future research could build on the limitations of this study.

The development of sustainability, the improvement of the quality of life, and the protection of future generations have become of prime importance in light of climate changes and carbon emissions. Universities are at the top of institutions that should participate in creating an environmentally friendly infrastructure. This study thus aimed to explore the extent to which Saudi universities achieve sustainability in the light of the Saudi Green Initiative from the faculty members’ perspective. Surely, this investigation would produce a proposal to promote sustainability in Saudi universities. A questionnaire consisting of five dimensions, namely academic sustainability, community partnership, resource management, planning and administration, and innovation and leadership was developed and administered to 120 faculty members from five Saudi universities. The participants’ ratings of Saudi universities’ achievement of sustainability dimensions ranged from high to moderate. Based on the results, a proposal was offered to take sustainability in Saudi universities to a higher level.

When it comes to financial transactions and counterfeit detection systems, banknote classification is crucial. In this paper, we propose an approach for the classification of Kazakhstan banknote images integrating Learning Vector Quantization (LVQ) with Statistical Texture Feature Extraction using the Gray Level Co-occurrence matrix (GLCM). Our methodology demonstrates effectiveness in accurately classifying banknote images, as evidenced by experimental results. The comprehensive testing scenarios show promising outcomes, with the combination of GLCM and Color Histogram under the LVQ algorithm achieving a high accuracy of 94.87 percent at distance 1 and 90°. These findings indicate the robustness and practical viability of the proposed method for authenticating banknotes.

Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multipath protocols which send data to its destination using routes with separate links. One of such protocols is RPL routing protocol. In this paper, this method is improved using composite metrics which chooses the best paths used for separate routes to send packets. We propose Energy and Load aware RPL (ELaM-IoT) protocol, which is an enhancement of RPL protocol. It uses a composite metric, calculated based on remaining energy, hop count, Link Expiration Time (LET), load and battery depletion index (BDI) for the route selection. In order to evaluate and report the results, the proposed ELaM-IoT method is compared to the ERGID and ADRM-IoT approaches with regard to average remaining energy, and network lifetime. The results demonstrate the superior performance of the proposed ELaM-IoT compared to the ERGID and ADRM-IoT approaches.

Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. IoT has introduced various services and daily human life depends on its reliable and accessible operation. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multi-path protocols which send data to its destination using routs with separate links. One of such protocols is AOMDV routing protocol. AOMDV protocol is a multi-path protocol which uses multiple different paths for sending information in order to maintain the network traffic balance, manage and control node energy, decrease latency, etc. In this paper, this method is improved using gray system theory which chooses the best paths used for separate routes to send packets. To do this, AOMDV packet format is altered and some fields are added to it so that energy criteria, link expiration time, and signal to noise ratio can also be considered while selecting the best route. The proposed method named GSTMPR-IoT is introduced which chooses the routs with highest rank for concurrent transmission of data, using a specific routine based on the gray system theory. In order to evaluate and report the results, the proposed GSTMPR-IoT method is compared to the EECRP and AOMDV approaches with regard to throughput, packet delivery rate, end to end delay, average residual energy, and network lifetime. The results demonstrate the superior performance of the proposed GSTMPR-IoT compared to the EECRP and AOMDV approaches.

Technological development has profoundly marked the evolution of the economy. The constant changes brought about by scientific and technological advances have been decisive in the transition from an analogue to a digital world. In this context, the impact of the fourth industrial revolution (or Industry 4.0.) manifests itself in many ways. Environmental impact is one of these. The energy sector has been evolving and changing just like the economy and society. Therefore, a study of this sector, and of the other related elements, is of interest to better understand the 4.0 concept. The promotion of sustainability at both political and social levels has led to changes in different areas, such as the productive vision, the use of green energies or the implementation of green taxes. Energy as a key factor in Industry 4.0. involves studying it both quantitatively and qualitatively. This is to under-stand the lights and shadows that the concept currently presents. Therefore, this work aims to bring the reality of the energy sector closer to reality, both in its positive and negative aspects, considering the main factors of incidence, in order to show the strengths and weaknesses that can be deduced.

The current rapidly changing and highly competitive market has put companies under a great pressure not only to be successful, but also to sustain their success into the future. In addition, in recent years, companies have become more aware of the fact that it is no longer enough to take care of economic aspects, being crucial to also take care of environmental and social aspects in order to actually succeed and lead in the current and future markets. In this context, companies are urged to move towards more innovative manufacturing practices that maintain a healthy balance among economic, environmental and social performances, which are the three pillars of the sustainability performance. To give some insight into this issue, a Systematic Literature Review (SLR) is conducted in this paper regarding the current trends in the field, doing special focus on the link between lean-green manufacturing and the different sustainability aspects. The SLR concluded that lean and green implementations as stand-alone systems are usually not enough to ensure the required balance between the three pillars of sustainability, suggesting further combining them into a single approach. Researchers expect to achieve further improvements in the sustainability performance moving towards the next level of sustainability.

This study aims to examine Turkish companies from a sustainability and green innovation point of view. Through this purpose, this research’s objective is to find out relationship between sustainability drivers and green innovation and also to search for green organizational culture’s mediation effect in this relationship. Survey was carried in companies operating in Turkey which were listed among İstanbul Chamber of Industry (ICI) Top 500 companies for last 3 years successively and have ISO14001 Environmental Management Certificate. According to the survey results, it was manifested that factors directing companies to sustainability having a positive relationship with green organizational culture and green innovation. It is found that there is a partial mediation effect of green organizational culture between motivating factors for sustainability and green innovation.

The StarDICE experiment strives to establish an instrumental metrology chain with a targeted accuracy of 1 mmag in griz bandpasses to meet the calibration requirements of next-generation cosmological surveys. Atmospheric transmission stands out as a significant source of systematic uncertainty. Specifically, gray extinction induces spurious variations of photometric fluxes. We propose a solution relying on an uncooled long-wave infrared thermal camera to evaluate it. This type of camera can provide real-time insights into atmospheric conditions and detect cirrus clouds. However, achieving accurate measurements with thermal imaging systems necessitates prior calibration due to the influence of temperature-induced effects, which compromise their spatial and temporal precision. Moreover, these systems cannot provide scene radiance values in physical units by default. This study introduces a new calibration process utilizing a tailored forward modeling approach. The method is applied to an uncooled FLIR Tau2 thermal camera. It incorporates sensor, housing, flat-field support, and ambient temperatures, along with raw digital response, as input data. Experimental measurements are conducted inside a climatic chamber, with the camera imaging a thermoregulated blackbody source. Results demonstrate the calibration effectiveness, achieving precise radiance measurements with a temporal pixel root-mean-square error (RMSE) of 0.09 W/m2/srand residual spatial noise of 0.03 W/m2/sr.

Due to the highly nonlinear, multi-stage, and strongly time-varying marine lysozyme fermentation process, it is difficult to assure the stability and prediction accuracy of the traditional single global soft sensor model on a global scale. This study innovatively proposed a soft sensor model based on an improved seagull optimization algorithm (ISOA) combined with Gaussian process regression (GPR) weighted ensemble learning. First, the sample data set is divided into multiple local sample subsets by the improved density peak clustering algorithm (ADPC). Second, the Gaussian process regression model is optimally altered with an improved seagull optimization algorithm for the purpose of establishing the corresponding sub-prediction model. Finally, the prediction model's fusion strategy is ultimately determined depending on the degree of connection between the test samples and a subset of local pieces. Simulation results show that the proposed soft sensor model, which searches GPR based on ISOA and combines various sub-models, can predict the key biochemical parameters of the marine lysozyme fermentation process better with less prediction error under the condition of fewer training data, and it can be expanded to the soft sensor models of general nonlinear systems, according to simulation results.

Physical symptoms are defined as symptoms for which adequate examination does not reveal a sufficient underlying root cause, e.g., pain and fatigue. The extant literature of the neurobiological underpinnings of physical symptoms has been largely inconsistent and primarily consists of (clinical) case-control studies with relatively small samples sizes. Therefore, we studied the association of brain morphology with physical symptoms in pre-adolescents from two independent and population-based cohorts. This study included 2,683 individuals from the Generation R Study (51% girls, 10.1 ± 0.6 years old) and 10,567 pre-adolescents from the ABCD Study (48% girls, 9.9 ± 0.6 years old). High- resolution structural magnetic resonance imaging (MRI) was collected using 3-Tesla MRI systems. Physical symptoms were evaluated using the somatic complaints syndrome scale from the parent-reported school-age version of the Child Behavior Checklist. Linear regression models were fitted for global brain metrics (i.e., cortical and subcortical grey matter volume and total white matter volume) as well as surface-based vertex-wise measures (surface area and cortical thickness). Analyses were initially conducted separately in each cohort and later meta-analysed. No associations were observed in either cohort separately. In the combined vertex-wise meta-analysis of both cohorts; the right hemisphere surface area, most notably the rostral middle frontal gyrus, superior frontal gyrus and anterior cingulate cortex, were related to physical symptoms after correcting for multiple comparisons (cluster area = 1,882 mm2). The present study, which is the most representative and well-powered to date, suggests that surface area, but not other measures of brain morphology, are modestly related to physical symptoms in pre- adolescents. While these effects are subtle, future longitudinal research is warranted to elucidate whether such associations indicate a cause or a consequence of the physical symptoms.

Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multi-path protocols which send data to its destination using routes with separate links. One of such protocols is AOMDV routing protocol. In this paper, this method is improved using gray system theory which chooses the best paths used for separate routes to send packets. To do this, AOMDV packet format is altered and some fields are added to it so that energy criteria, link expiration time, and signal to noise ratio can also be considered while selecting the best route. The proposed method named RMPGST-IoT is introduced which chooses the routes with highest rank for concurrent transmission of data, using a specific routine based on the gray system theory. In order to evaluate and report the results, the proposed RMPGST-IoT method is compared to the ERGID and ADRM-IoT approaches with regard to throughput, packet receiving rate, packet loss rate, average remaining energy, and network lifetime. The results demonstrate the superior performance of the proposed RMPGST-IoT compared to the ERGID and ADRM-IoT approaches.

District heating networks have become widespread due to their ability to distribute thermal energy efficiently, which leads to reduced carbon emissions and improved air quality. The characteristics of these networks vary remarkably depending on the urban layout and system amplitude. Moreover, extensive data about the energy distribution and thermal capacity of different areas are seldom available. Design, optimization and control of these systems are enabled by the availability of fast and scalable models of district heating networks. This work addresses this issue by proposing a novel method to develop a scale-free model of large-scale district heating networks. Starting from coarse data available at the main substations, a physics-based model of the system aggregated regions is developed by identifying the heat capacity and heat loss coefficients. The model validation on the network of Västerås, Sweden, shows compatibility with literature data and can therefore be exploited for system design, optimization and control-oriented applications. In particular, the possibility to estimate the heat storage potential of network regions allows new smart management strategies to be investigated.

Under the new pattern of “double carbon” development, good ESG performance is the best way to promote the sustainable development of enterprises, and the ESG investment strategies are directly affected by the strategic vision of managers. Based on the upper echelons theory and stakeholder theory, this paper takes Chinese A-share listed companies from 2011 to 2022 as samples to empirically analyze the impact of managerial myopia on corporate ESG performance. The results show that managerial myopia significantly inhibits corporate ESG performance, mainly by inhibiting corporate green investment and green innovation sustainability. Furthermore, for state-owned enterprises (SOE), heavy polluting enterprises (HPE) and non-high-tech enterprises, the inhibitory effect of manager myopia on ESG performance is stronger. When the enterprise is in the growth stage, the above inhibition effect is more severe. For external governance, the greater the analyst attention and public environmental attention are, the more conducive they are to alleviating the restraining effect of managerial myopia on enterprise ESG performance. Therefore, effectively improving the time cognition level of managers and strengthening external supervision have become important measures for comprehensively optimizing the ESG performance.

The digital economy promotes economic development, industrial upgrading, and environmental protection. This article calculates the green total factor productivity (GTFP) based on the SBM-DDF model and uses the entropy method and principal component analysis to calculate the digital economy index. We use panel data from 282 Chinese cities to test the driving effect of the digital economy on green total factor productivity. The study results show that the digital economy significantly increases GTFP, and the heterogeneity of this impact is further explored. We also explored the mechanism of the digital economy in promoting green. The digital economy can indirectly increase industrial production efficiency by promoting innovation in green technologies.

The paper in question explores the connection between green areas and urban well-being in an effort to give readers a comprehensive grasp of the topic. The major goals of this study are to evaluate how green spaces affect urban residents' physical and mental health, sense of community, and general quality of life. This research presents numerous major conclusions through a thorough investigation of the current literature and empirical analysis of urban environments across various areas. First of all, it shows that being close to green spaces is associated with better physical health, including a decline in obesity and cardiovascular disease rates. Second, green areas are linked to better mental health, with residents of greener neighbourhoods reporting reduced levels of stress, anxiety, and sadness. However, neighbourhoods having green open grass areas have greater levels of social interaction, and cohesion, which encourages residents to feel a sense of belonging. Lastly, this study highlights the positive impact of green spaces on overall urban quality of life, as they contribute to cleaner air, lower noise pollution, and increased property values. The implications of these findings are significant for urban planning and policy development. They underscore the importance of prioritizing green spaces in urban design, as investments in such areas not only promote physical and mental health but also enhance social bonds and elevate the overall liveability of cities. This research provides a foundation for evidence-based decision-making in urban development to create healthier, more vibrant, and sustainable urban environments.

As customer demand for green products increases in the digital economic era, this study analyses the green innovation of the e-tailer and supplier in drop shipping models. Moreover, drop shipping e-tailers and suppliers with a drop shipping option need to make choices regarding whether to provide green or normal products to the market. When a supplier with a drop shipping option produces green products, more fees may be invested on the production of green products than on normal products. The drop shipping e-tailers and suppliers with a drop shipping option can also choose to sell normal products at a low cost, as before. This study designs four models of drop shipping e-teilers and suppliers with a drop shipping option under different choices, analyzes their operational process in drop shipping models, and investigates five theorems. The optimal pricings decisions and green degree of drop shipping e-tailers and suppliers with a drop shipping option were evaluated in this study. The impacts of the green innovation factor, green elasticity coefficient, manufacturing and distribution costs on the drop shipping e-tailers and suppliers with a drop shipping option, and the effect of other environmental parameters on the green degree of green products are also analyzed through computer simulation. The findings of the simulation analysis provide valuable guidance for e-tailers and suppliers with green innovation in drop shipping models and offer important academic and practical implications for e-commerce and the digital economy.

As an important means of controlling the spread of cities, large-scale urban green belts have been widely used in the planning and construction of green space systems in various mega-size cities around the world. In previous studies, there has been more research on the overall isolation effect of green belts, while there has been less research on changes in their internal structure. There have been more perspectives on the land-use change (LUC) caused by urban expansion, and less systematic research on the dual driving factors of LUC. In this paper, we constructed a multi-dimensional index system to measure the "contraction-expansion" mechanism of land use in the overlapping vegetation areas of large green belts under the dual influence of urban expansion and urban greening, from the perspectives of quantity, space, and connectivity during different construction periods. Taking the boundary of two green belts in Beijing as an example, we hope to provide scientific support for the construction and ecological protection of Beijing's green belts.

Abstract: Green walls and green dams are increasingly being considered as part of many nation-al and international desertification initiatives. This paper studies the spatiotemporal evolution of the green dam in the Moudjbara region (Djelfa Province, Algeria) from 1972 to 2019 by using Landsat imagery, Land Change Modeler and Open Land package. The future evolution of pine plantations for the year 2029 was also forecasted, based on an anthropogenic scenario (i.e., an-thropogenic pressure is the main driver of the green dam destruction). Our findings revealed that the green dam project was successful for a few years, but after that, pine plantations deteri-orated significantly due to forest harvesting, livestock overgrazing, and the proliferation of the pine caterpillar processionary, which destroyed most of the reforestation. Land Change Modeler predicted a huge degradation of pine plantations for the year 2029, and if the deforestation con-tinues at the same rate, the green dam will disappear in the Moudjbara region during the next few decades. Aware of this threat, the Algerian authorities are now planning to reforest more than 1.2 million ha under the latest rural renewal policy by introducing new principles related to sustainable development, fighting desertification, and climate change adaptation

Braskem is the only company in the world that produces green polyethylenes (HDPE – high density polyethylene and LLDPE – linear low density polyethylene) derived from the dehydration of sugarcane ethanol. Although the performance of green and fossil nominally same polyethylenes are equivalent, commercial clients may use blends of up to 51% of green polyethylenes and 49% of fossil polyethylenes and still have the right to use the I’m greenTM label which appeals to environmental conscious consumers and places these companies in a noticeable position. The Annual Income Statement - AISs from 2010, when Braskem started production of green PE, until 2018, show there was growth of revenues. Despite of the production of polyethylenes have continued stable and the number of green polyethylenes patents have decreased since 2014, the profits with the BRKM5 stocks increased. There is no transparency of how carbon credits were gained and in the AIS. Investments in securities in the Brazilian financial market (BRKM5 and carbon credits) are much more attractive than the investment in new patents, because they generate greater gains (268% increase in the average share price of BRKM5 from 2012 to 2018) and do not require large investments in R&D.

This study examines the dynamic relationship between Green Human Resource Management (Green HRM), Environmental Performance (EP), Green Employee Behavior (GEB), and Environmental Knowledge and Awareness (EKAW) within the Egyptian hospitality sector context. Using Pearson correlation coefficients and regression analyses on a sample of 400 staff members from hotels and tourist villages in Egypt, the study examines Green HRM practices’ influence on EP, mediated by GEB and moderated by EKAW. The findings reveal significant positive correlations between Green HRM practices and these mediators, indicating that comprehensive environmental strategies and incentive management are pivotal in promoting eco-friendly practices among employees. The study further confirms GEB and EKAW’s substantial mediating role in enhancing EP. The results also suggest that while EKAW and GEB independently contribute to EP, their interaction and the role of environmental awareness as a potential moderator warrant further examination. This research contributes to the literature on sustainable business practices by underscoring human resource strategies’ integral role in achieving environmental sustainability goals, highlighting the importance of incentivizing green practices, and cultivating an organizational culture that prioritizes EKAW. These insights are particularly valuable for organizations seeking to enhance their ecological footprint through effective Green HRM practices.

In recent years, the contamination of aquatic environments by organic chemicals has become an increasing concern. To effectively remove toxic pollutants and biologically resistant compounds, a combination of advanced technologies must complement conventional methods. Indeed, among environmental pollutants, dyes such as methylene blue (MB), congo red and crystal violet persist in the environment because they are difficult to biodegrade. Advanced oxidation processes (AOPs) are widely employed to treat various types of wastewaters, often in conjunction with bi-ological treatments. Among these technologies, heterogeneous photocatalysis stands out as one of the most extensively studied, with Titanium dioxide being the most researched photocatalyst due to its high photoactivity. In this study, Titanium dioxide nanoparticles (NPs) were synthe-sized using both a green method, leveraging the natural properties of Aloe vera leaf extract, and a conventional approach. The resulting NPs were thoroughly characterized using XRD, TEM, and ζ-potential analysis. Their photocatalytic performance was assessed by measuring the degrada-tion of MB under UV light. The TiO2 NPs synthesized via the green method demonstrated a degradation efficiency of (50 ± 3) % after 180 minutes, significantly higher than the (16 ± 3)% achieved by NPs synthesized through the conventional route. Moreover, the reaction rate con-stant for the green-synthesized TiO2 NPs was found to be approximately five times greater than that of the conventionally synthesized NPs. These results open new scenario in the pollution removing strategy research.

Green investments help to create less harmful alternatives and adequate funds that contribute to economic growth, sustainable development, and social well-being. The applied methods are empirical and analytical based on the study of literature, multi-criteria modelling, determination of weights, and ranking of criteria in deciding green investments mapping of indicators, and monitoring of progress towards green growth through official OECD data. The analysis uses official sources on indicators related to the green economy and the environment. Multi-criteria decision-models (MCDM) were used to select adequate green investments, where instead of indicators from the official OECD-database, investors use the areas in which the indicators are distributed. According to the findings of AHP, half of the investments in the green economy come from public sources (0.51), and the other half are private (0.25), and institutional investors (0.24). While, BWM reveals that the best criterion for the decision to invest in the green economy is the environmental and resource productivity of the economy, and the worst is the base of natural assets. This paper aims to enable decision-makers to use these results as weights for the overall assessment of green investments in ESG and to simplify the decision-making approach in future analyses.

This is a paper of Political Economy and Economic Policies into the European Green Deal framework to improve the Recovery Plan post-COVID-19. This paper is focused on the green jobs opportunity for Europe, especially for Spain. It is offered a systematization of concepts and calculations in the issue (attending the international institutions and forums proposals) to harmonize the recovery plans, to apply them beyond the energy sector and to align public and private sector, as well other key stakeholders in achieving this goal. The obtained outcome gives the creation of around 350.000 new green jobs and the necessity of a new workforce reskilled. This result makes necessary to coordinate sectoral plans by the policymakers in which all the involved entities might express their needs and views on the best education approach to renewables sector and green jobs.

The procedures for the extraction and separation of lipids and nutraceutics from microalgae using classic solvents have been used many times. However, these production methods usually require expensive and toxic solvents. Based on our studies involving the use of eco-sustainable methodologies and alternative solvents, we select ethanol (EtOH) and cyclopentyl methyl ether (CPME) for extracting bio-oil and lipids from algae. Different percentage of EtOH in CPME favors the production of an oil rich of SFA useful to production biofuel or rich of compounds bioactive. The proposed method for obtain a rich extract of saturated or unsaturated fatty acids from dry algal biomass is disclosed is eco-friendly and allows a good extraction yield. The method is compared both in extracted oil percentage yield and in extracted fatty acids selectivity to extraction by supercritical carbon dioxide.

The objective of the current investigation is to identify the first or first draining node or sentinel lymph node (SLN) from the primary tumor mass in a regional lymphocenter. Four different indirect lymphography (IL) methods were employed in 96 canine patients with different types of cancer between 2018 and 2021. The IL technique involved intradermal, submucosal, and peritumoral injections of 2ml contrast agent in the four-quadrant principle which were divided into equal aliquots. Lymphatic mapping with lipiodol (iodized oil) was 100% in squamous cell carcinoma of the head and neck, anal sac apocrine gland adenocarcinoma, mast cell tumor, squamous cell carcinoma of the skin, mammary carcinoma, and with methylene blue dye, 100% detection was achieved in testicular tumor and mammary carcinoma. Instead of a very short washout time of 2 minutes, Iohexol showed an excellent detection in indirect CT lymphography for histiocytic sarcoma and in indirect radiographic lymphography for lymphosarcoma. The significance of contrast and blue dyes in detecting the lymphatic spread of canine cancers is clearly emphasized in the current investigation. The nature of cancerous tissue was again analyzed through image and machine learning approach in this work. Supervised machine learning technique is applied in this work for automatic classification of cancerous and non-cancerous regions. Various statistical and texture-based features are extracted from X-Ray images and support vector machine with linear, polynomial, multilayer perceptron (MLP), and RBF kernel functions are applied for classification. Highest 95.53%, 94.64%, 93.05% sensitivity, specificity, accuracy, respectively, is achieved using RBF kernel function.

Surface defect detection is one of the most widely used research areas in the field of image processing and machine vision. Detection of surface defects is used in visual inspection systems and medical image analysis. In this manuscript, an innovative method for detecting surface defects based on energy changes in co-occurrence matrices is presented in several directions. The method presented in this manuscript includes two stages of learning and testing. In the learning phase, to extract texture features, the gray level co-occurrence matrix operator is applied on the healthy image of the desired level. Then the energy value of the output matrix is ​​calculated. In the following, changes in the amount of energy are considered as statistical characteristics that are a good representative of the image of a healthy surface. Finally, with its help, a suitable threshold for the health of the images is obtained. Then, in the test phase, with the help of the calculated quorum, the defective windows that have suffered from non-normality are distinguished from the healthy surface sections. In the results section, the efficiency of the mentioned method has been measured on medical images and stone and ceramic images, and its detection accuracy has been compared with some previous effective methods. The advantages of the presented method include high accuracy, low calculations and compatibility with all types of levels due to the use of the learning stage. The proposed approach can be used in medical applications to diagnose abnormalities such as diseases. All extracted features are statistical, so its detection speed is higher than deep neural networks.

Prediction of crop yield is essential for food security policymaking, planning, and trade. The objective of the current study is to propose novel crop yield prediction models based on hybrid machine learning methods. In this study, the performance of artificial neural networks-imperialist competitive algorithm (ANN-ICA) and artificial neural networks-gray wolf optimizer (ANN-GWO) models for the crop yield prediction is evaluated. According to the results, ANNGWO, with R of 0.48, RMSE of 3.19, and MEA of 26.65, proved a better performance in the crop yield prediction compared to the ANN-ICA model. The results can be used by either practitioners, researchers or policymakers for food security.

The purpose of this research is to understand the relationship between green business ethics, green finance, and sustainable business performance, and to evaluate the role of corporate social responsibility (CSR) in this relationship. The impact of the damage inflicted on nature's functioning order is being felt much more strongly today. In light of these realities, companies are required to place greater emphasis on sustainability principles not just out of financial concerns but as a result of corporate social responsibility. In this context, focusing on the role of corporate social responsibility in sustainable business performance is the main goal of this research. Quantitative research methods, specifically the cross-sectional survey method, were employed for data collection and analysis. For this purpose, a convenience sampling method was used to select 427 white-collar employees working in industries operating in Türkiye as the sample for this study. The data collected through surveys were analyzed using the AMOS 24 statistical program. The findings underscore that green business ethics and green finance have a significant impact on corporate social responsibility and sustainable business performance. Additionally, it was determined that corporate social responsibility plays an intermediary role in shaping sustainable business performance. These findings are expected to provide an important foundation that can guide both employees and managers in developing awareness about green policies and sustainability, emphasizing the importance of green policies in the working life.

This study aims to broaden the current understanding of the antecedents and consequences of green purchase intention within the realm of perceived green value (PGV) A mixed-method approach is deployed, integrating PLS-SEM and Necessary Condition Analysis (NCA) to examine the role of influence and interaction as key precursors to perceived responsibility and perceived self-efficacy, and explores how perceived responsibility and perceived self-efficacy impacts green purchasing intention, mainly through the mediation of perceived responsibility (PER) and perceived self-efficacy (PSE) using survey data gathered from consumers participating. The results indicate that PGV positively influences green purchase intention (GPI). Moreover, PER and PSE exhibit significant chain mediation effects, with the mediation effect of perceived environmental responsibility being particularly strong. It is recommended that the government intensify green disseminate and education, promote the establishment of certification and evaluation systems for electric vehicle products, and that electric vehicle factories emphasize the environmental attributes and economic interest of their products to encourage green purchasing behavior.

This research aims to review the educational and research operations of Mahasarakham University and propose development directions for the university to meet sustainable development criteria for ranking as a green university. This involves gathering data and analyzing the results of operations over the past 3 years, then using this analysis to synthesize lessons learned and develop guidelines for sustainable development in the coming years. The study found that the university's policies and strategies implemented following the annual performance evaluation criteria align with the green university assessment criteria for education and research. This has resulted in minor improvements in curriculum for sustainability. However, community service projects for sustainability have increased by 89.10%, while funding for sustainable research and academic publications related to sustainability has decreased. In summary, the projects under the university's development strategy adequately support and drive suitable development activities. Nevertheless, the university must continuously review its operations to adapt to changing contexts, budget constraints, and evolving competition and develop each year sustainably.

Real assets in the energy market are subject to ecological uncertainty due to the penetration of renewables. We illustrate this point by analysing electrolysers, a class of assets which recently became the subject of a large interest, as they lead to the production of the desirable green hydrogen and green ammonia. The latter has the advantage of being easily stored and has huge potential in decarbonising both the fertilizer and shipping industries. We consider the optimization of green ammonia production with different types of electricity procurement in the context of stochastic power and ammonia markets, a necessary assumption to translate the features of renewable, hence intermittent, electricity. We emphasise the importance of using stochastic prices to effectively model the volatile nature of the price dynamics, illustrating the project risks that can be mitigated by hedging activities. This study shows the pivotal role of flexibility when dealing with fluctuating renewable production and volatile electricity prices to maximise profits and better manage risks.

Green carbon-based materials (GCM), i.e. carbon materials produced using renewable biomass or recycled wastes, ought to be used in order to processes become sustainable and carbon neutral. Carbon nanomaterials, like for example carbon dots and nanobichar families, and carbon materials, like for example activated carbon and biochar substances, are sustainable materials with great potential to be used in different technology applications. In this review, the following four applications were selected, and the works published in the last two years (since 2022) critically reviewed: agriculture; water treatment; energy management; and, carbon dioxide reduction and sequestration. GCM improved the performance of the technological applications under revision and play an important role in the sustainability of the processes, contributing to the mitigation of the climate change, namely by reducing emission and increase sequestration of CO2eq..

The present study identified the influence of green advertising and eco-labels on the attitude and environmental awareness of millennials who purchase ecological products in shopping centers in Ecuador. The research was quantitative, correlational and with a cross-sectional design. A total of 430 millennials participated in the study. A 20-question survey was applied in person outside the shopping centers of Quito and Guayaquil - Ecuador. The convergent and discriminant validity of the research model was verified using Confirmatory Factor Analysis (CFA) and Structural Equation Models (SEM). SPSS 20 and AMOS 24 programs were used for statistical analysis. The results show that green advertising influences environmental attitudes (β: 0,245) and awareness (β: 0,110) and specifically influences purchasing behaviour (β: 0,154) for green products. Although eco-labels do not directly influence purchasing behaviour (β: 0,128), they influence the attitudes (β: 0,406) and ecological awareness (β: 0,277) of millennials who buy organic products. This article is one of the first studies to identify the relationship between green advertising elements and green product purchasing behaviors among millennials in a developing country, concluding that marketing strategies based on green advertising and eco-labels have an impact on the attitude and environmental awareness of millennials, but only advertising directly affects purchasing behaviour while eco-labels do not. This research has social implications since it corroborates that millennials are concerned about environmental problems and are willing to contribute to sustainability.

Abstract: The conundrum of Latin American countries in the green transition unveils new opportunities and old structural problems. There is a clear advantage in the energy grid for Argentina, Brazil, and Mexico, coming mainly from hydropower, solar, and wind energy. In 2022, Brazil had the largest solar photovoltaic energy generation capacity in Latin America and the Caribbean, with over 24 gigawatts. Mexico ranked second, with some 9 gigawatts, and Chile ranked third, with a capacity of around 6 gigawatts. The window of opportunity for the industrialized Latin American countries resides chiefly in greening the natural resources industries and agriculture and husbandry, mainly for Brazil and Argentina. Latin America faces the dual challenge of promoting renewable energy and upgrading its value chains while managing the socioeconomic dynamics inherent in its developmental stages. It poses an enormous challenge for Latin American countries because of the phenomenon of "time compression" (Whittaker et al., 2020). Developing country's innovation and technology-intensive segments coexist with informal labor and low-skilled workers. Far from disappearing with economic growth, such coexistence becomes reinforced through an increasingly wide array of temporary and insecure jobs. Time compression condenses different stages of industrial and economic development within the same space and time, directly affecting the indicators related to the reduction of environmental impacts. Instead of locking in one path for this transition, Latin American countries had better not cling to panaceas but consider the threats, the risks, and the need to experiment with multiple paths and solutions simultaneously. However, this change implies the formation of a genuine developmental and environmental coalition guided by rigorous strategic considerations not captured by immediate interests.

This research aims to understand the Cambodian green economy transition and analyze its strengths, weaknesses, opportunities, and threats (SWOT). The research showed that Cambodia has been significantly transitioning its green economy since 2009 as evidenced by the National Green Growth Roadmap. Cambodia also established the National Council for Green Growth in 2012 and upgraded it to the National Council for Sustainable Development in 2015 in alignment with 2030 Agenda for Sustainable Development of the United Nations. The members of the Council are from all the government’s ministries and relevant inter-ministerial councils/committees, which are significant for policymaking. All governors of the capital and provincial administrations are also its members, which are significant for supporting and implementing the works at the subnational levels. Under the structure of the Council’s Secretariat, Department of Green Economy is playing an important role in promoting green economic development in Cambodia by looking at national policies and strategic plans, undertaking projects, and mobilizing resources. Through coordination between this Department and UNIDO, Cambodia in 2022 became a Member of the United Nations Partnership for Action on Green Economy. The findings showed that Cambodia is transitioning its green economy at the right time, especially the new government’s Pentagonal Strategy strongly supported this green economy transition with a clear and strong political commitment. The national inter-ministerial council for sustainable development is also very significant for cross sectoral policy-making and implementing levels, inclusively for promoting green economic development.

As in every workplace, human sustainability in dental enterprises is connected to air and water quality, eco-friendly and naturally designed working spaces and 4R’s culture. Purpose of this study is to access the preferences and knowledge on circular economy and green building construction in a sample of students and dentists in Greece. Students (N1=93) and dentists (N2= 126) filled in e-questionnaires from April to December 2022. The response rate was 17,88% for N1 and 1.94% for N2. Data revealed that both students and dentists lack knowledge on circular economy (N1=67.7%, N2=68,25%), EU regulations on amalgam disposal (N1=64.5%, N2=58.73%) and plastic recycling (N1=76.34%, N2=76,98) while they do recycle at home (N1= 80.6%, N2=82.54%) and have participated in voluntary environmental actions (N1=58.1%, N2=66.67%). Gender influences the importance of factors related to green dental practices, with women students being more prone to answer positively as important for increase costs for network changes (p=0.02), lack of environmental awareness of manufacturers (p=0.057), and poor wastewater management (p=0.01). Students from urban areas are more prone to answer positively for lack of state financial support (p=0.02), low level of green design in the building (p=0.03), low direct financial benefit of a green dental office (p=0.04), low benefit to the reputation of the green dental office (p=0.02), lack of continuing education training seminars on green dentistry (p=0.05). For dentists, no significant relationships were observed except of a weak positive relationship in increase in costs for changes related to utility networks (p=0.08) while increased wasteful energy (p=0.12) and waste of dental materials (p=0.19) seemed important only for dentists in urban areas. Women dentists were more prone to answer positively on wasting energy (p=0.024) and use of unapproved disinfection products (p=0.036). The findings contribute ideas and solutions on green dental office buildings and sustainable behaviors through educational activities and social perspective of factors such as age, experience in dentistry, gender, and urbanism. It also inspires future multi-disciplinary research on dental quality assurance, psychology of environmentalism, economics, and behavioral science in dentistry.

Irrigation and fertilization are indispensable links in the jujube planting industry in southern Xinjiang, China. However, the water and fertilizer integration effects on jujube growth and fruit quality remain unclear. A two-year water and fertilizer optimization coupling test was conducted to determine the optimal water- and nutrient-supply scheme. The three-factor randomized block experiment included water (W), nitrogen (N), and phosphorus (P). According to the principal component analysis of each index, each treatment’s comprehensive score was obtained. Using yield and economic regression models, the theoretical value and yield value of the optimal economic benefit are inferred. When W, N, and P were applied together, the fruit quality and yield of each treatment significantly differed, and the vitamin C, soluble sugar, and sugar–acid ratio increased significantly with an increase in nitrogen fertilizer. However, the titratable acid decreased. An increase in irrigation and nitrogen application significantly increased fruit yield. The comprehensive score was the highest in the N3P3W2 treatment, which improved fruit quality, and the lowest in the N4P3W2 treatment. When the amounts of N, P, and W were 275.56 kg·hm-2, 413.66 kg·hm-2, and 7278.19 m3·hm-2, respectively, the theoretical economic benefit was the best. The N4P3W2 treatment is the optimal treatment.

A microwave assisted method for synthesis of 2-substituted benzimidazoles has been developed. The combination of molar ratio N-phenyl-o-phenylenediamine:benzaldehyde (1:1) using microwave irradiation and only 1% mol of Er(OTf)3 provide an efficient, environmental and mild access to a diversity of benzimidazoles under solvent-free conditions.

Green development ensures the socioeconomic development that incorporates environmental issues while remaining economically viable for owners and tenants. Government as the authority of the state should provide favorable incentives, policy and regulatory pressure for green development. The present study aims to investigate the government policies and regulations for green development in Bangladesh and make a critical discussion of the initiatives. The study is descriptive in nature and collects secondary information. Evidence suggests that environmental degradation and climate change related risks and vulnerabilities have intensified in Bangladesh. The government of Bangladesh (GOB) is concerned about green development and formulates various Acts, regulations and policy initiatives since 2010. Major green development initiatives observed in the financial institutions due to the mandatory requirements by Bangladesh Bank but green bond and green insurance in capital market are yet to be developed. The GOB required taking proper policy initiatives for the garments and leather industries to ensure pollution free production system which ensures green trade initiatives. The environmental taxes and ecological compensation mechanisms should be revised. Urban green space and Government green procurement are still less concerning matter. The GOB should make effective collaboration with all related stakeholders to ensure the green development.

Digital transformation and green innovation are critical to firms’ competitive advantage and, thus, firms desire to make digital transformation enhance green innovation. However, the relationship between the digital transformation on green innovation is unclear. Drawing on digital empowerment, we delineate types of digital transformation and their impacts on green innovation in manufacturing firms. Our empirical results indicate that production digitalization and service digitalization have a significant promoting effect on both of green technological innovation and green management innovation. However, the effect of production digitalization on green management innovation is stronger than that of service digitalization. Moreover, environmental regulation enhances the positive effect of service digitalization on green technological innovation and green management innovation. While it enhances the effect of production digitalization on green management innovation. Peer firms’ green innovation strengthens the effect of service digitalization on both of green technological innovation and green management innovation.

Concept sustainable of banking is based on principle realization growth and profit for the bank and shareholders, but only with achievement social goals, as and care for conservation life environment. Providing new ones banking service and creation new ( green ) banking jobs, except for _ profitable, they achieve and spreads social and ecological goals, chances are with creation competitive advantages, both in countries Western Balkans observed in the work, so and in all countries of the world In this one work we will focus on analysis macroeconomic parameters in countries Western Balkans works tests influence selected indicators on performance banking system, with special in retrospect on social and component protection life environment. The results indicate that rate unemployment the most significant indicator potentially risky events for bankers, as and banks they are not recognized in national conservation strategies _ life environment which are in WB countries currently on strength. Accordingly, the former is necessary to carry out education foreign affairs, and in parallel to promote green loans like they live and in the long term more favorable of traditional loans, with update the existing one regulatory frame in the domain protection life environment.

Purpose, This research aimed to examine the effect of green logistics (GL) and green human resource management (GHRM) on the performance of environmentally friendly manufacturing industries oriented towards sustainable development of organizations (SDO) through the role of sustainable production (SP) as a mediating variable. Methodology, A quantitative approach was employed through a standardized questionnaire to obtain data from 110 manufacturing industries in Indonesia that implemented environmentally friendly practices. Advanced statistical techniques, such as Structural Equation Modeling (SEM) and data analysis using Smart PLS (Partial Least Square) version 4 were utilized to analyze the collected data. Findings, The results showed that the model supported the statistical significance of all seven hypotheses and confirmed the direct and mediating effects of GL, GHRM, and SP on SDO. Practical implications, This research added critical insights into the theory and practice of GL and GHRM to realize SDO through the role of SP as a mediator in environmentally friendly manufacturing industries. Originality, This research contributd to the existing literature by adding to the effect of SP mediation on the relationship of GL and GHRM on SDO. There was no previous research that discussed the important role of SP mediation in influencing the relationship between GL and GHRM on SDO.

This study was conducted to propose the Green Economic Development Plan for Manufacturing S.M.E.s based on financial performance and operations thru Green Initiatives. The descriptive survey method used to gather data to determine the green initiative's implementation of small and medium (S.M.E.s) manufacturing enterprises. Green initiatives use as a basis for crafting a green economic development plan. Document analysis was also employed to obtain data from any available printed materials and records provided by the respondents. Such methods of gathering information used to validate data gathered from local and foreign-related literature. The observation also employed to survey the assets owned and validate any green initiatives practiced, including their implementation. The study's findings show that among the green initiatives implemented by SMMEs, which resulted in the reduction of total costs and expenses, were the proper disposal and segregation of waste materials, water management by recycling wastewater and using water-efficient equipment, natural resources, and raw materials management. SMMEs should encourage active participation and support of suppliers and customers in achieving G.E.D.'s objectives by developing incentive schemes.Furthermore, SMMEs should continue to benchmark with G.E.D. Practitioners are operating locally and abroad to adopt best greening strategies and regularly network with concerned government agencies for continuous updating on G.E.D. Initiatives that may benefit the firm. Further research may be conducted on green initiatives implemented by small and medium enterprises in other industry sectors.

Public access to high quality green environments has become a key issue for city managers and a matter of environmental justice. Remnants of natural ecosystems allow citizens a direct contact with nature, but conversely the presence of people contributes further to the existing disturbances. Urban pressures on ecosystem remnants may act to favour the expansion of some invasive species in cities. Whilst the negative impacts of invasive species on ecosystem function is well documented little is known how invasive species influence the use of green spaces by people. Here, we examined one of the few remnants of urban riparian forests in Europe, the Vistula river valley in Warsaw which has recently become an attractive recreation site. Despite their high ecological value, the poplar and willow forests have been increasingly taken over by the invasive tree species Acer negundo. We examined the status of the invasion process and the relationship between recreational ecosystem services and the characteristics of the tree stands – tree species, tree density and age and NDVI values. We found the willow forest to be more susceptible to invasion by A. negundo than the poplar forest, which was revealed in significantly higher share of the maple individuals and their greater volume per unit area. Presence of A. negundo affected biodiversity resulting in decreased undergrowth density and number of species. The use intensity by the public, assessed on the basis of trampling intensity and the density of existing informal tracks, were negatively correlated to the presence of A. negundo. This study highlights the need to integrate invasive species management into green infrastructure planning and management.

Green ICT has received significant attention in organizations to reduce global warming since last decade. Several maturity models have been proposed for tracking green ICT practices in organizations. Current literature shows that SMEs around the world try to follow some common strategies such as virtualization, consolidation of devices, energy efficiency and disposal of ICT equipment for greening ICT. The increasing interest for green ICT practices in organizations is not only due to the desire to attain environment-friendly atmosphere but mainly because of sustaining business goals such as cost reduction, competitive advantages and stakeholders’ pressure. Nevertheless, due to the lack of green ICT knowledge, organizations, specially SMEs, tend to ignore those practices. Therefore, this research proposes a framework that provides combination of existing green and sustainable ICT maturity models by mapping them with the strategies the businesses are already following. Out of this framework, a web application has been developed that provides questionnaire for SMEs to identify their present situation of green ICT practices and guidelines for improvement. The results have been analyzed by testing the application in some SMEs of Finland and Bangladesh. Finally, a survey has been conducted to attain SMEs’ perception about the possibility of sustainable development of businesses through this application.

Melanoma is widely recognized as one of the most lethal forms of skin cancer, with its incidence showing an upward trend in recent years. Nonetheless, the timely detection of this malignancy substantially enhances the likelihood of patients’ long-term survival. Several computer-based methods have recently been proposed in the pursuit of diagnosing skin lesions at their early stages. Despite achieving some level of success, there still remains a margin of error that the machine learning community considers to be an unresolved research challenge. This study presents a novel framework for the classification of skin lesions. The framework incorporates deep features to generate a highly discriminant feature vector, while also maintaining the integrity of the original feature space. Recent deep models including Darknet53, DenseNet201, InceptionV3, and InceptionResNetV2 are employed in our study for the purpose of feature extraction. Additionally, transfer learning is leveraged to enhance the performance of our approach. In the subsequent phase, the extracted feature information from the chosen pre-existing models is combined, with the aim of preserving maximum information, prior to undergoing the process of feature selection using a novel entropy-controlled grey wolf optimization (ECGWO) algorithm. The integration of fusion and selection techniques is employed to initially incorporate the feature vector with a high level of information and subsequently eliminate redundant and irrelevant feature information. The efficacy of our design is substantiated through the evaluation on three benchmark dermoscopic datasets, namely PH2, ISIC-MSK, and ISIC-UDA. In order to validate the proposed methodology, a comprehensive evaluation is conducted, including a rigorous comparison with established techniques in the field.

Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and brain volumes and white matter integrity (FA and MD) with magnetic resonance imaging in the BrainSCALE cohort, consisting of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years of the twins. Genes influenced externalizing behavior and changes therein (h2 up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation rph up to +0.20) and lower MD (rph up to –0.20); with sizeable genetic correlations (FA ra up to +0.42; MD ra up to –0.33). Cortical gray matter (CGM; rph up to –0.20) and cerebral white matter (CWM; rph up to +0.20) volume were phenotypically but not genotypically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence from the same genetic factor.

This paper undertakes a comprehensive review to underscore the central role of sustainability in the evaluation and innovation of jet grouting technologies. It meticulously traces the evolution of evaluation methodologies, emphasizing the imperative of sustainable practices throughout history. Traditional evaluation paradigms are examined alongside contemporary trends, with a particular focus on sustainability metrics and visualization techniques. Through an examination of innovative jet grouting technologies, this paper illustrates how sustainability principles have driven advancements aimed at improving the efficiency and environmental impact of jet grouting methods. Central to this review is an assessment of sustainability across multiple dimensions, including method applicability, installation and operational compatibility, and the performance of the resulting jet grouted piles. By emphasizing sustainability considerations, the paper highlights the intrinsic link between environmental integrity and technological innovation in the field of jet grouting. In addition, it discusses analytical evaluation methods designed to proactively address sustainability concerns prior to construction, thereby promoting a more environmentally responsible approach. Finally, this paper presents a pioneering evaluation framework that integrates real-time monitoring and visualization tools, allowing stakeholders to track sustainability milestones throughout the construction process. By emphasizing sustainability as a guiding principle, this review advocates for a paradigm shift toward more ecologically sound and resilient jet grouting practices.

This study aims to investigate the influence of various economic, environmental, and social factors on sustainable development, with a specific focus on the impact of green technology and climate change adaptation. A panel dataset comprising 38 OECD member countries from 1990 to 2020 is employed, and a series of dynamic panel data models are estimated using the system generalized method of moments (GMM) approach. Numerous covariates, such as globalization, socio-economic conditions, economic and political values, climate and technological progress, and environmental determinants, are examined. The empirical findings highlight the significant role played by macroeconomic, institutional, social, and government policy-related factors in sustainable development. More importantly, our results provide novel and robust evidence that the diffusion of green technology and climate change adaptation positively affect green growth. The study's empirical outcomes are demonstrated to be robust to misspecification errors and statistically significant at traditional significance levels. These findings carry substantial policy implications for the development and implementation of strategies that promote climate change adaptation and green innovation. Consequently, policymakers should prioritize the integration of green technology and adaptive measures in their sustainable development agendas to foster a greener, more resilient future.

Solar green roofs, namely rooftops functionalized with properly selected living vegetation and photovoltaic modules, achieve an ideal symbiotic relationship in which promotion of biodiversity and onsite renewable energy production are both enhanced whereas the roof provides a wide range of environmental, health, aesthetic and economic benefits. This study provides a unified outlook of this eminent sustainable technology at the dawn of its uptake across the world, especially in polluted urban areas.

The persistent challenge of IPF, characterized by disease progression and high mortality, underscores the urgent need for innovative therapeutic strategies. We have developed a novel small molecule – catechin derivative ABI-171 – selectively targeting DYRK1A and PIM1 kinases, crucial in the pathogenesis of fibrotic processes. We employed the Bleomycin-induced (intratracheal) mouse model of pulmonary fibrosis (PF) to evaluate the therapeutic efficacy of ABI-171. Mice with induced PF were treated QD with ABI-171 either prophylactically or therapeutically using oral and intranasal routes. Pirfenidone (100mg/kg, TID) and Epigallocatechin gallate (EGCG, 100 mg/kg, QD), a natural catechin currently in a Phase 1 clinical trial, were used as reference compounds. ABI-171, administered prophylactically, led to a significant reduction in hydroxyproline levels and fibrotic tissue formation compared to the control group. Treatment with ABI-171 improved body weight, indicating mitigation of disease-related weight loss. Additionally, ABI-171 demonstrated anti-inflammatory activity, reducing lymphocyte and neutrophil infiltration. In the therapeutic setting, ABI-171, administered 7 days post-induction, reduced mortality rates (P = 0.04) compared with the bleomycin and EGCG control groups. ABI-171 also ameliorated the severity of lung injuries assessed by improved Masson’s trichrome scores when administered both orally and intranasally. ABI-171 significantly decreases bleomycin-induced PF and improves survival in mice, showcasing promising therapeutic potential beyond current medications like Pirfenidone and EGCG for patients with IPF. Based on these results, further studies with ABI-171 are ongoing in preclinical studies.

Greenflation or inflation for green energy transition in Europe, it becomes a structural problem of new scarcity and poverty, because the Green Deal and its fiscal and monetary policies. In this paper, it is paid attention to the Green financial bubble and the European greenflation paradox: in order to achieve greater future social wellbeing, due to a looming climate risk, present wellbeing and wealth is reduced, causing a real and ongoing risk of social impoverishment. According to the European Union data, it is going to show the relations between green transition (emissions, tax, debt, credit boom, etc.), GDP and inflation. As many emissions are reduced, there is a decrease of GDP (once deflated) and GDP per capita, evidencing social deflation, which in turn means more widespread poverty and a reduction of middle-class. Also, there is a risk of a green-bubble, like in the Great Recession of 2008 (but this time supported by the European Union) and possible stagflation. To analyze this problem, it is used here some econometric tools, but under the theoretical support of heterodox approaches, especially the Austrian Economics and the New-Institutional Schools.

The increasing focus on sustainability and the adoption of green practices across industries underscore the necessity of equipping future professionals with competencies in implementing sustainable solutions. This study explores the perceptions of former students from two departments within the technological sector towards sustainability practices. A cross-sectional online survey was carried out among alumni from two programs at the University of Thessaly, a university recognized for its commitment to sustainability and green initiatives as a member of the INVEST European University alliance. The survey questionnaire included background inquiries and 16 statements designed to gauge alumni perspectives towards sustainability practices. Specifically, it aims to assess their views through self-assessment and compare differences between the two alumni groups. Responses were collected on a 5-point Likert scale ranging from strongly disagree to strongly agree. A total of 300 graduates from the Computer Science and Telecommunications as well as Electrical Engineering undergraduate programs were encouraged to take part in the survey, achieving a response rate of 69%. Of those who responded, 61% (n = 126) represented the Computer Science and Telecommunications group, while 39% (n = 81) were from the Electrical Engineering program. Our findings indicate a generally positive attitude towards sustainability, with statistically significant differences in perspectives on the implementation of sustainable technologies and stakeholder engagement. These results underscore the necessity of integrating sustainability education deeply within the curricula of technological programs to cultivate a workforce capable of addressing future environmental challenges. This study illuminates the critical role of educational frameworks in shaping the sustainability competencies of technology professionals.

Continuity of activities and projects are important for sustainably developing organizations, especially universities. The purpose of this research study is to find university development guidelines regarding waste management according to the green university ranking criteria for sustainable developments by studying and collecting the data covering the last five years (2019 - 2023) of Mahasarakham University. We also analyzed and synthesized lessons learned from the details of the operations and the factors involved in successes while comparing and providing suggestions for the operations in the next year. It was found that waste management that resulted in continuous developments that achieved the goals of Mahasarakham University consisted of the five guidelines. (1) Making green university policies and using them as the (key performance index) KPI of the divisions and also announcing the university's waste management policies by applying the principles of 3R (Reuse-Reduce-Recycle). (2) Allocating the budgets supporting the projects' activities according to the evaluation criteria. (3) Student and personnel participation as well as the mechanisms used by the committees from various administrative divisions such as Student Council, Student Association and clubs to drive the operations. (4) Identifying the main responsible individuals and committees for the green university who communicated and drove the operations while collecting, analyzing and preparing the data. (5) Follow-ups and evaluations of the project's activities with the Plan-Do-Check-Act (PDCA) processes for continuous and sustainable developments and improvements leading to the green university. With the above operations, Mahasarakham University's waste management scores of the six indices during 2019 - 3023 increased annually as follows: 900, 900, 1050, 1275 and 1350.

A preventive effect for tea and its bio active components in cardiovascular health has been suggested by the results of several epidemiological studies, treatments utilizing randomized controlled trials, and mechanistic investigations. Therefore, scientific interest in green tea's ability to prevent cardiovascular diseases (CVDs) is growing. Green tea benefits for the metabolic syndrome, which includes diabetes and hypertension but may also raise cholesterol levels. Additionally, green tea reduces the mortality from any cause, arrhythmia, stroke, coronary heart disease, heart failure, and other conditions.

Magnesium oxide is typically white and can be colorized with transition metal insertion by doping or by adsorption. We present the preparation of green colored hydroxide by the adsorption of nickel ions by porous MgO. MgO was prepared by the colloidal starch suspension method and used to remove nickel ions from the aqueous solution. The oxides and hydroxides, before and after adsorption, were characterized by X-ray diffraction technical, and show that a phase change occurs, a transition from periclase (MgO) to brucite (Mg(OH)2) due to the interaction with nickel salts (acetate, chloride, and nitrate). The FTIR spectrum corroborates with the DRX data on the formation of brucite like crystal lattices. The new samples present a green color, indicative of the incor-po-ration of the Ni2+ ions. Mixed oxides in the form of brucite were used in microbiological tests and showed action against fungi and bacteria, with bactericidal, bacteriostatic, or fungistatic function. Green brucite (NixMg1-x(OH)2) can be used as an inorganic pigment in white or colorless paints with a special biocidal property.

Although the contribution of the Indonesian batik industry is quite significant, its activities also lead to environmental damage. There is thus a need to develop procedures and tools to achieve sustainability and Green Industry Standards. Before doing so, it is important to conduct a systematic literature review regarding this topic. This study investigates the existing research and debates relevant to sustainability in the batik sector. Therefore, this study provides an understanding of responsible batik consumption and production activities. After reviewing 42 papers from 593 generated results, the batik production aspect is the most dominant aspect analysed by the papers, with production waste being the most-discussed topic. There are opportunities to update the research on the batik production aspect, enrich the discussion about the organisation and marketing aspects, and begin to examine the finance-related aspect regarding the sustainable batik theme.

The paper is an investigation on the impact of financial markets on the volatility of green bonds credit risk component, measured by the option-adjusted spread/swap curve (OAS) of the Global Bloomberg Barclays MSCI Green Bond Index, for both the non and pandemic periods. For these purpose, after observing the dynamic joint correlations between all the variables through a DCC-GARCH, we adopt GARCH(1,1) and EGARCH(1,1) models, putting the OAS as dependent variable. Our main results show that the conditional variance parameters are significant and persistent in both times, testifying the overall impact of the other markets on the OAS. In more detail, we highlight that the gamma in the two EGARCH models is positive: so the “green” credit risk volatility is more sensitive to positive shocks than negative ones. With reference to the conditional mean, we note that if during the non pandemic time only the stock market is significant, during the pandemic also conventional bonds and gold are impacting. To the best of our knowledge this is the first study that analyzes the specific credit risk component of green bond yields: we deem our findings useful to observe the change of green bonds creditworthiness in a complex market context.

Siliceous sandstones used in Khmer temples such as the Prasat Basset, Wat Ek Phnom, Phnom Banan temples in Battambang Province, Phnom Chisor and Ta Prohm temples in Ta Keo Province, and Wat Nokor Bachey temple in Kampong Cham Province in Cambodia were investigated in this study. Chemical composition analyses and magnetic susceptibility measurements were conducted for the sandstone blocks used in these temples. Siliceous sandstone is a primary construction material in all investigated temples. Two types of siliceous sandstone, pale brown and red, were found. Pale brown siliceous sandstone was used for the construction of all the investigated temples. In contrast, red siliceous sandstone was found only in the Wat Ek Phnom, Prasat Basset, and Phnom Banan temples. It is suggested that the pale brown siliceous sandstone originated from the Phra Wihan Formation within the Khorat Group. Based on the chemical composition analysis, the pale brown siliceous sandstone in the Ta Prohm temple at Tonle Bati and the Wat Nokor Bachey temple may have been sourced from the lower level of the Phra Wihan Formation. In contrast, the pale brown siliceous sandstone used in the Prasat Basset, Wat Ek Phnom, and Phnom Banan temples was likely sourced from the upper level. The origin of the red siliceous sandstone is proposed to be from the Sao Khua Formation, which is situated above the Phra Wihan Formation.