Sustainable Development Goal 9: Industry, Innovation and Infrastructure (17993)

Alginate is a polysaccharide with the property of forming hydrogels, which is economic production, zero toxicity, and biocompatibility. In the agro-industry, alginate is used as a super absorbent polymer, coating seeds, fruits, and vegetables and as a carrier of bacteria and fungi as plant-growth promoters and biocontrol. The latter has a high impact on agriculture since the implementation of microorganisms in a polymer matrix improves soil quality; plant nutrition, and is functional as a preventive measure for the appearance of phytopathogenic. Additionally, it minimizes losses of foods due to wrong post-harvest handling. In this review, we provide an overview of physicochemical properties of alginate, some methods for preparation and modification of capsules and coatings, to finally describe its application in agro-industry as a matrix of plant-growth-promoting microorganisms, its effectiveness in cultivation and post-harvest, and its effect on the environment, as well as the prospects for future agro-industrial applications. Full article

Industry 4.0 features intelligent manufacturing. Among them, the vision-based defect inspection algorithm is remarkable for quality control in parts manufacturing. With the help of AI and machine learning, auto-adaptive instead of manual operation is achievable in this field, and much progress has been made in recent years. In this study, considering the demand of inspection features in industrialization, we made further improvement in smart defect inspection. An efficient algorithm using Field Programmable Gate Array (FPGA)-accelerated You Only Look Once (YOLO) v3 based on an attention mechanism is proposed. First, because of the relatively fixed camera angle and defect features, an attention mechanism based on the concept of directing the focus of defect inspection is proposed. The attention mechanism consists of three improvements: (a) image preprocessing, which is to tailor images for selectively concentrating on the defect relevant things. Image preprocessing mainly includes cutting, zooming and splicing, named CZS operations. (b) Tailoring the YOLOv3 backbone network, which is to ignore invalid inspection regions in deep neural networks and optimize the network structure. (c) Data augmentation. First, two improvements can be made to efficiently reduce deep learning operations and accelerate the inspection speed, but the preprocessed images are similar and the lack of diversity will reduce network accuracy. So, (c) is added to mitigate the lack of considerable amounts of training data. Second, the algorithm is deployed on a PYNQ-Z2 FPGA board to meet the industrialization production requirements for accuracy, efficiency and extensibility. FPGA can provide a low-latency, low-cost, high-power-efficiency and flexible architecture that enables deep learning acceleration for industrial scenarios. A Xilinx Deep Neural Network Development Kit (DNNDK) converted the improved YOLOv3 to Programmable Logic (PL), which can be deployed on FPGA. The conversion process mainly consists of pruning, quantization and compilation. Experimental results showed that the algorithm had high efficiency, inspection accuracy reached 99.2%, processing speed reached 1.54 Frames per Second (FPS), and power consumption was only 10 W. Full article

Oil palm (Elaeis guineensis Jacq.) is the number one source of consumed vegetable oil nowadays. It is cultivated in areas of tropical rainforest, where it meets its natural condition of high rainfall throughout the year. The palm oil industry faces criticism due to a series of practices that was considered not environmentally sustainable, and it finds itself under pressure to adopt new and innovative procedures to reverse this negative public perception. Cultivating this oilseed crop outside the rainforest zone is only possible using artificial irrigation. Close to 30% of the world’s irrigated agricultural lands also face problems due to salinity stress. Consequently, the research community must consider drought and salinity together when studying to empower breeding programs in order to develop superior genotypes adapted to those potential new areas for oil palm cultivation. Multi-Omics Integration (MOI) offers a new window of opportunity for the non-trivial challenge of unraveling the mechanisms behind multigenic traits, such as drought and salinity tolerance. The current study carried out a comprehensive, large-scale, single-omics analysis (SOA), and MOI study on the leaves of young oil palm plants submitted to very high salinity stress. Taken together, a total of 1239 proteins were positively regulated, and 1660 were negatively regulated in transcriptomics and proteomics analyses. Meanwhile, the metabolomics analysis revealed 37 metabolites that were upregulated and 92 that were downregulated. After performing SOA, 436 differentially expressed (DE) full-length transcripts, 74 DE proteins, and 19 DE metabolites underwent MOI analysis, revealing several pathways affected by this stress, with at least one DE molecule in all three omics platforms used. The Cysteine and methionine metabolism (map00270) and Glycolysis/Gluconeogenesis (map00010) pathways were the most affected ones, each one with 20 DE molecules. Full article

The last decade has been a time of great progress in the World Wide Web and this progress has manifested in multiple ways, including both the diffusion and expansion of Semantic Web technologies and the advancement of the aesthetics and usability of Web user interfaces. Online media outlets have often been popular Web destinations and so they are expected to be at the forefront of innovation, both in terms of the integration of new technologies and in terms of the evolution of their interfaces. In this study, various Web data extraction techniques were employed to collect current and archival data from news websites that are popular in Greece, in order to monitor and record their progress through time. This collected information, which took the form of a website’s source code and an impression of their homepage in different time instances of the last decade, has been used to identify trends concerning Semantic Web integration, DOM structure complexity, number of graphics, color usage, and more. The identified trends were analyzed and discussed with the purpose of gaining a better understanding of the ever-changing presence of the media industry on the Web. The study concluded that the introduction of Semantic Web technologies in online media outlets was rapid and extensive and that website structural and visual complexity presented a steady and significant positive trend, accompanied by increased adherence to color harmony. Full article

Commercialization in the meat-processing industry has emerged as one of the major agrobusiness challenges due to the large volume of wastewater produced during slaughtering and cleaning of slaughtering facilities. Slaughterhouse wastewater (SWW) contains proteins, fats, high organic contents, microbes, and other emerging pollutants (pharmaceutical and veterinary residues). It is important to first characterize the wastewater so that adequate treatment techniques can be employed so that discharge of this wastewater does not negatively impact the environment. Conventional characterization bulk parameters of slaughterhouse wastewater include pH, color, turbidity, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total organic carbon (TOC), total suspended solids (TSS), total nitrogen (TN), total phosphorus (TP), and coliform counts. Characterization studies conducted have revealed the effects of the pollutants on microbial activity of SWW through identification of toxicity of antibiotic-resistant strains of bacteria. Due to the high-strength characteristics and complex recalcitrant pollutants, treatment techniques through combined processes such as anaerobic digestion coupled with advanced oxidation process were found to be more effective than stand-alone methods. Hence, there is need to explore and evaluate innovative treatments and techniques to provide a comprehensive summary of processes that can reduce the toxicity of slaughterhouse wastewater to the environment. This work presents a review of recent studies on the characterization of SWW, innovative treatments and technologies, and critical assessment for future research. Full article

To ensure safety and efficacy, cosmetic products are regulated and controlled worldwide. However, the regulatory approaches of each country may be significantly different and impact the competitiveness and economic viability of the industry. This work presents an updated review and comparison of regulatory requirements from the European Union, United States of America, Canada, Japan, People’s Republic of China and Brazil. It outlines contents such as the definition, classification and categorization of cosmetics, pre-market requirements, ingredients management, general labelling requirements, regulation of claims concerning advertisement and commercial practices, increase of animal testing and marketing bans on cosmetic products. Furthermore, it weighs the impact of regulatory differences on the safety and accessibility of these products in the mentioned regions. Full article

Cloud computing coupled with Internet of Things technology provides a wide range of cloud services such as memory, storage, computational processing, network bandwidth, and database application to the end users on demand over the Internet. More specifically, cloud computing provides efficient services such as “pay as per usage”. However, Utility providers in Smart Grid are facing challenges in the design and implementation of such architecture in order to minimize the cost of underlying hardware, software, and network services. In Smart Grid, smart meters generate a large volume of different traffics, due to which efficient utilization of available resources such as buffer, storage, limited processing, and bandwidth is required in a cost-effective manner in the underlying network infrastructure. In such context, this article introduces a QoS-aware Hybrid Queue Scheduling (HQS) model that can be seen over the IoT-based network integrated with cloud environment for different advanced metering infrastructure (AMI) application traffic, which have different QoS levels in the Smart Grid network. The proposed optimization model supports, classifies, and prioritizes the AMI application traffic. The main objective is to reduce the cost of buffer, processing power, and network bandwidth utilized by AMI applications in the cloud environment. For this, we developed a simulation model in the CloudSim simulator that uses a simple mathematical model in order to achieve the objective function. During the simulations, the effects of various numbers of cloudlets on the cost of virtual machine resources such as RAM, CPU processing, and available bandwidth have been investigated in cloud computing. The obtained simulation results exhibited that our proposed model successfully competes with the previous schemes in terms of minimizing the processing, memory, and bandwidth cost by a significant margin. Moreover, the simulation results confirmed that the proposed optimization model behaves as expected and is realistic for AMI application traffic in the Smart Grid network using cloud computing. Full article

Uranium is an indispensable part of the nuclear industry that benefits us, but its consequent pollution of water bodies also makes a far-reaching impact on human society. The rapid, efficient and convenient extraction of uranium from water is to be a top priority. Thanks to the super hydrophilic and fast adsorption rate of microgel, it has been the ideal adsorbent in water; however, it was too difficult to recover the microgel after adsorption, which limited its practical applications. Here, we developed a uranyl-ion affine and recyclable microgel container that has not only the rapid swelling rate of microgel particles but also allows the detection of the adsorption saturation process by the naked eye. Full article

This study intends to explore the extent of the use of information and communication technology (ICT) in flash-flood-prone haor (wetland ecosystem) areas of north-eastern Bangladesh. Addressing the situation of severe flash floods in 2017 at the community level, this study aims to examine the constraints and challenges in using ICT for flash flood risk management. An empirical study was conducted in two upazilas (administrative sub-districts) within the Sunamganj, the most affected district. A total of 120 household heads were interviewed using a semi-structured questionnaire. Focused group discussions (FGD) and key informant interviews (KII) were also used. Results reveal that people in these areas do not use computers or Internet. However, the use of mobile phones is common for communication during disasters. Illiteracy, poor quality of life, poor social capital, poor infrastructure, and poor communication with institutions are highlighted as the main constraints and challenges in the effective application of ICT in flash flood management. The results showed that the local community people of the study area receive early warning and hazards preparedness-related information through mobile phones, television, radio, and Facebook. However, the results also highlighted the constraints and challenges in applying ICT in DRR at the community level. By addressing a remote region and a relatively less focused disaster (flash flood), this study contributes to boosting the application of ICT in DRR, especially in remote, disadvantaged communities. Full article

Monitoring the fine spatiotemporal distribution of urban GDP is a critical research topic for assessing the impact of the COVID-19 outbreak on economic and social growth. Based on nighttime light (NTL) images and urban land use data, this study constructs a GDP machine learning and linear estimation model. Based on the linear model with better effect, the monthly GDP of 34 cities in China is estimated and the GDP spatialization is realized, and finally the GDP spatiotemporal correction is processed. This study analyzes the fine spatiotemporal distribution of GDP, reveals the spatiotemporal change trend of GDP in China’s major cities during the current COVID-19 pandemic, and explores the differences in the economic impact of the COVID-19 pandemic on China’s major cities. The result shows: (1) There is a significant linear association between the total value of NTL and the GDP of subindustries, with R² models generated by the total value of NTL and the GDP of secondary and tertiary industries being 0.83 and 0.93. (2) The impact of the COVID-19 pandemic on the GDP of cities with varied degrees of development and industrial structures obviously varies across time and space. The GDP of economically developed cities such as Beijing and Shanghai are more affected by COVID-19, while the GDP of less developed cities such as Xining and Lanzhou are less affected by COVID-19. The GDP of China’s major cities fell significantly in February. As the COVID-19 outbreak was gradually brought under control in March, different cities achieved different levels of GDP recovery. This study establishes a fine spatial and temporal distribution estimation model of urban GDP by industry; it accurately monitors and assesses the spatial and temporal distribution characteristics of urban GDP during the COVID-19 pandemic, reveals the impact mechanism of the COVID-19 pandemic on the economic development of major Chinese cities. Moreover, economically developed cities should pay more attention to the spread of the COVID-19 pandemic. It should do well in pandemic prevention and control in airports and stations with large traffic flow. At the same time, after the COVID-19 pandemic is brought under control, they should speed up the resumption of work and production to achieve economic recovery. This study provides scientific references for COVID-19 pandemic prevention and control measures, as well as for the formulation of urban economic development policies. Full article

We consider that a supply chain consists of an original equipment manufacturer (OEM) and a retailer. We analyze how the retailer’s remanufacturing decision affects the decision of the new products’ qualities for the OEM. We use a game theory approach to investigate the interactions between the OEM and the retailer with or without remanufacturing operation. We find the retailer’s motivation to develop the remanufacturing industry depends on the profitability of remanufactured products and the OEM’s deterring strategy. When the remanufacturing operation profit margin is low, the retailer voluntarily gives up remanufacturing; when this profit margin is moderate, the OEM induces the retailer to give up remanufacturing by improving the quality of the new product; when this profit margin is sufficiently high, the OEM cannot prevent the retailer from developing remanufacturing. The retailer developing remanufacturing as well as their threat of developing decrease the OEM’s profit because the OEM improves the quality of the new products to induce the retailer to give up remanufacturing, at the expense of its own profit. We explicitly characterize the process of the OEM from preventing to accepting the retailer developing the remanufacturing industry, as well as the changes in supply-chain members’ operating decisions and profits in the process. Finally, using MATLAB numerical analysis, we also found that the retailer’s development of the remanufacturing industry always benefits the whole supply chain, consumer surplus, and social welfare. Furthermore, the retailer’s development of the remanufacturing industry is not always good for the environment. This development is only good for the environment when the new products’ environmental impacts in the EOL stage are larger than the total environmental impacts of the remanufactured products in every stage of their life cycle. Full article

There is an increasing need to accelerate the diffusion of biogas technology, to contribute to handling grand societal challenges. It is thus concerning that around 30% of all biogas projects are abandoned. Previous studies have found that challenges for deployment of bioenergy technology are mainly economic and financial challenges, market and infrastructure challenges, regulatory and administrative challenges, local opposition, site selection challenges and ecological aspects. Very few studies have however tried to understand how these different types of challenges specifically affect individual biogas projects. Also, no previous studies have identified where these challenges occur in the different phases of a project’s lifecycle (conceptualization, planning, and execution). A lack of understanding that limits the ability of both public institutions and project owners to ensure the success of biogas projects. The aim of this study is to fill this knowledge gap and provide a unique insight into the often very complex and long project lifecycle for the realization of centralized biogas projects. Results based on five comprehensive longitudinal case studies of attempts to realize centralized biogas projects, all taking place between 2008–2020 in Denmark, provide insight into how projects are specially affected by these different types of challenges, and shows that both successful and abandoned projects typically faced an array of challenges that project owners need to overcome. The study also from a bottom-up perspective provides insight into the implementation of national policies and initiatives assigned to the accelerated deployment of biogas technology in Denmark between 2008–2020 as well as critical factors at the local level driving the development. Full article

Based on the traditional framework of resource mismatch theory analysis and existing literature studies, this paper constructs a model of resource mismatch efficiency loss including the digitalization factor of the service industry, measures the resource mismatch of China’s service industry and its sub-sectors, and empirically analyzes the impact of digital economy development on resource mismatch of service industry using panel data of each sub-sector of China’s service industry from 2001 to 2020. The findings reveal that: (1) Resource mismatch exists in China’s service industry, and the degree of mismatch of capital is more serious than that of labor. (2) Traditional service industries with low digitalization have serious efficiency losses, while emerging service industries with high digitalization have almost no efficiency losses. (3) The increase in the development of the digital economy can significantly improve the resource mismatch in the service industry; appropriate government intervention can improve the capital mismatch but not the labor mismatch; the increase in the proportion of state-owned enterprises is conducive to improving the labor mismatch but not the capital mismatch. Meanwhile, the results of the industry heterogeneity test show that the increase in the digital economy can improve the resource mismatch of both emerging and traditional service industries, but the improvement is more obvious for emerging service industries. Therefore, in the context of the development of the digital economy, we make the following suggestions. The government intervenes appropriately in the capital market, develops emerging service industries, and formulates different digital transformation policies for different industries. Relevant enterprises increase their efforts in technology research and development, and actively explore the direction of digital transformation of service industries. The government and enterprises work together to promote the improvement of China’s economic development level. Full article

Mandatory corporate extraterritorial responsibilities to promote environmental, social and human rights awareness and recordkeeping have been criticised as green-washing, despite the progressive intent of such attempts. This article conducts an in-depth investigation of extraterritorial responsibility through the lens of the social licence to operate (SLO), using a hybrid methodology involving doctrinal, conceptual, black letter, interdisciplinary and socio-legal sources. We aim to give an overview of decided cases referred to the Supreme Court by the Court of Appeal, in the hope of offering academic groundwork for legalising corporate extraterritorial responsibility in the context of global value chains with the participation of multinational enterprises and various stakeholders, including those in very vulnerable positions in developing or the least developed countries. Previous research on the notion of the SLO has tended to focus on one particular industry, based on the assumption that an SLO is more relevant in corporate social responsibility (CSR)-sensitive sectors. This article will change the focus and aim to answer the question of whether building and maintaining SLOs can help companies to acquire the social legitimacy to fulfil extraterritorial social responsibility. We link the goals, ideals and breadth of SLOs to those of extraterritorial responsibility in order to provide supplementary support for legislators to achieve better compliance and risk management. We conclude that the benefits of seeking an SLO are that they can help to inform progressive extraterritorial legislative attempts, promote board accountability, and mitigate environmental and social risks. Full article

The oil and gas industry is involved with severe corrosive/sour environmental conditions due to H₂S, CO₂, and moisture content. The National Association of Corrosion Engineers (NACE) has developed standards to enable users to select suitable materials for given sour conditions which utilize laboratory testing. A failed piping sample (API-5L-X65) was removed from a pipeline after 15 years of service. Optical microscopy was used to compare the microstructure of the corroded sample near the exposed surface to both the service environment, and further away from it. Moreover, pitted samples were analyzed using a scanning electron microscope coupled with energy dispersive X-ray (SEM/EDS) to understand the deposits’ morphology. Furthermore, XPS analysis proves the presence of a significant content of sulfur compound. Additionally, the mechanical properties of both corroded and non-corroded samples were evaluated and compared. Micro-hardness was carried out on the cross-section of the removed sample to understand any evident hardness variation from the inner diameter (ID) to the outer diameter (OD) of the piping. All the results suggest that prolonged service exposure has resulted in the development of micro defects, resulting in the reduction of strength and impact toughness, and the reduction in the hardness at the exposed surface of the corroded piping. Understanding the corrosion mechanism of pipelines exposed to sour media in the long-term helps in repair/replacement planning and extending the usable design life of the material, and paving the way for the oil and gas industry to develop additional ways to monitor the changes in the critical materials’ properties when exposed to sour service. Full article

The accurate estimation and monitoring of phenology is necessary for modern agricultural industries. For crops with short phenology occurrence times, such as rice, Sentinel-1 can be used to effectively monitor the growth status in different phenology periods within a short time interval. Therefore, this study proposes a method to monitor rice phenology based on growth curve simulation by constructing a polarized growth index (PGI) and obtaining a polarized growth curve. A recursive neural network is used to realize the classification of phenology and use it as prior knowledge of rice phenology to divide and extract the phenological interval and date of rice in 2021. The experimental results show that the average accuracy of neural network phenological interval division reaches 93.5%, and the average error between the extracted and measured phenological date is 3.08 days, which proves the application potential of the method. This study will contribute to the technical development of planning, management and maintenance of renewable energy infrastructure related to phenology. Full article

Hydraulic systems are widely used in industry due to their small size-to-power ratios and their ability to produce very large linear force and torque. In traditional hydraulic systems, a variable pump driven by an electric motor is often used as power source. In these systems, the electro-hydraulic power source always operates at its rated speed, causing lots of noise and low energy consumption, especially in no-load and light-load conditions. These problems can be solved by changing the speed of the electric motor according to the load state of the electro-hydraulic power source. In order to improve the energy efficiency of the electro-hydraulic power source and realize pressure and flow control on the basis of low cost, this paper presents the power-source structure of a variable-displacement pressure-compensated pump driven by a variable-speed electric motor; this controls the flow by adjusting the electric motor speed and controls the pressure with the variable-displacement pressure-compensated pump. However, for the variable-speed system, the starting of the electric motor with a load is relatively slow; this makes it difficult to meet the demand of flow control, and will also have a great impact on the power grid. To address these problems, a hydraulic accumulator is introduced to the inlet port of the hydraulic pump to assist in starting the pump. This method can realize the combined control of pressure, flow and power, and has high energy efficiency. This research uses experiments to verify the feasibility of the scheme, and the results show that the starting periods of the power source can be shortened from 2.8 s to 0.7 s when the load pressure is about 18 MPa. Furthermore, regarding maintaining pressure without flow outputs, the energy consumption of the designed power source can be reduced by almost 30% compared with a pure variable-displacement power source. Full article

The lockdown instituted during the COVID-19 pandemic has drawn the world’s attention to the importance of homes as integrated structures for practicing all aspects of life. The home has been transformed from a mere place to live into a complete piece of infrastructure accommodating all activities of life, including study, work, shopping, exercise, entertainment, and even telehealth. Although quarantines were necessary to protect against viral infection, we have faced social and psychological challenges due to the failure of the current home design to accommodate the new lockdown lifestyle during the pandemic. Thus, this study aims to set a foundation for the development and design of resilient homes in a post-quarantine world by establishing a comprehensive framework for quarantine-resilient homes. The framework was established on the basis of the relevant literature and proposals from architects and experts. It brings a perspective to the future requirements of homes so as to provide architects, stakeholders, and policymakers with the appropriate knowledge to mitigate the impact of lockdowns on mental health and well-being in residential buildings by focusing on the physical and architectural environment. Full article

One of the Indonesian government’s policies to achieve national beef self-sufficiency is the 1000 beef village program. The program was piloted in many cattle-farming centers involving the operation of a feed bank to supply animal feed to tackle the challenge of feed limitation during the dry season. This study evaluates the sustainability status of an ongoing feed bank program and its development strategy based on the current progress of a feed bank used to serve five groups of farmers. Ninety sustainability attributes were derived based on six dimensions. The attributes were compiled from the primary data collected using a questionnaire. Expert opinions from practitioners were also considered in evaluating the attributes. The feed bank’s sustainability status and development strategy were determined using the multi-dimensional scaling method with the rapid appraisal approach. It was found that the overall sustainability status of the feed bank was less sustainable, with an overall score of 49.55. The individual dimensions of (A) policy and government support, (B) raw material, (C) facilities and infrastructure, (D) feed bank management, (D) human resource management, (E) price, production, and (F) distribution systems posed sustainability scores of 48.48, 60.33, 48.57, 47.89, 48.76, and 44.64, respectively. Among the 90 predefined attributes, 21 were identified as highly sensitive through both the root mean square and expert opinion. Those attributes led to five main recommended development strategies: (1) strengthening the institution, (2) intensifying training, (3) increasing human resources (4) partnership developments, and (5) increasing the role of multi-stakeholders. Full article

Carbon emission trading market construction is an important policy tool to promote the realization of China’s “double carbon” goal. However, problems still exist, such as the lack of market trading vitality, the large difference in carbon trading prices between the eight pilot markets and the instability of the prices. In order to explore the key influencing factors on carbon trading prices, 15 factors were selected to study in detail according to the policy, green industry, economy and environment. Taking China’s eight pilot carbon trading markets as research subjects, we explored the correlation degree of each factor by using the improved gray relational analysis model (GRAM) from the two dimensions of space and time. The research results show that from the space dimension, the industrial development level, development degree of low-carbon industries, air pollution degree and green technology maturity are the main factors that affect the carbon trading price in the eight pilot areas. Meanwhile, from the time dimension, the correlation degree between various factors and carbon trading price both showed a downward trend as a whole, and the fluctuation of the correlation degree of individual factors was different from the overall trend. In conclusion, we can put forward recommendations on the pricing mechanism of the carbon trading market after this comprehensive study. Full article

Green innovation, which combines “innovation-driven” and “green development,” is one of the most powerful ways to overcome resource and environmental constraints and enhance manufacturing industry sustainability. Based on the innovation value chain perspective, the green innovation process of manufacturing industry is decomposed into two stages: green scientific and technological R&D and achievement transformation. Then, using the three-stage DEA and Malmquist index model to measure the green innovation performance of China’s manufacturing industry, and compare its regional heterogeneity from the dual perspectives of static efficiency and dynamic productivity. In addition, this paper further discusses the improvement path of green innovation performance of China’s manufacturing industry. The findings are as follows: (1) The green innovation efficiency of manufacturing industry in China is at a comparatively low degree and has great potential for improvement. Moreover, it shows apparent regional heterogeneity: The green innovation efficiency in the eastern region is higher than that in the western region, and both are higher than that in the center region, confirming the phenomenon of “central collapse”. (2) The green innovation productivity of China’s manufacturing industry shows a “W-type” dynamic evolution tendency, with green technological progress as the key driving factor, while the green technical efficiency does not clearly exhibit a “catch-up effect”. Additionally, it shows significant regional heterogeneity: green innovation productivity in the western region is higher than that in the central and eastern regions, indicating a potential “backwardness advantage”. (3) The eastern region of China is located in combination IV, which indicates that it has a high rate of green innovation efficiency but a low rate of green innovation productivity; the central region is located in combination III, which indicates that it has a low rate of both green innovation efficiency and productivity; and the western region is located in combination II, which indicates that it has a low rate of green innovation efficiency but a high rate of green innovation productivity. Last but not least, this paper puts forward three kinds of paths for the improvement of the green innovation performance of China’s manufacturing industry: unilateral breakthrough, step-by-step and stimulating jumping type. Full article

Increasing the promotion and application of biofuel ethanol has been a national strategy in China, which in turn has affected changes in the raw material planting structure. This study analyzed the effects of agricultural land-use changes on water quality in a typical maize fuel ethanol raw material planting area. The results revealed that an increase in cultivated land and construction land would also increase the load of TN (total nitrogen) and TP (total phosphorus), while an expansion in forest land would reduce the load. As for crop structures, maize might have a remarkable positive effect on TN and TP, while rice and soybean performed in no significant manner. Furthermore, scenarios under the carbon neutralization policy and water pollution control were carried out to forecast the nonpoint source pollutants based on the quantitative relations coefficients. It was proven that maize planting was not suitable for vigorous fuel ethanol development. Reducing maize area in the Hulan River Basin was beneficial to reducing nonpoint source pollution. However, the area of maize should not be less than 187 km², otherwise, the food security of the population in the basin would be threatened. Under the change in fuel ethanol policy, this study could provide scientific support for local agriculture land-use management in realizing the carbon neutralization vision and set a good example for the development of the fuel ethanol industry in other maize planting countries. Full article

In this work, ionic liquid (IL)-cured epoxy resins were modified by adding poly(ε-caprolactone) (PCL). Three different ILs were used in order to study how (a) the chemical structure of the ILs and (b) the PCL content affect the phase behaviour, microstructure, mechanical and adhesive properties. Regardless of the IL used or the PCL content, the obtained materials showed a single phase. The addition of PCL to the epoxy resin resulted in plasticizing of the network blends, lower glass transition temperatures (T_g), and crosslinking densities (ν_e). Low PCL contents did not have a significant impact on the mechanical properties. However, the adhesive properties improved significantly at low PCL contents. Higher PCL contents led to a significant increase in toughness, especially in the case of the imidazolium-based IL. The balance achieved between the mechanical and adhesive properties of these IL-cured epoxy/PCL blends constitutes an important step towards sustainability. This is because a biodegradable polymer (PCL) was used to substitute part of the epoxy resin, and the ILs—which are non-volatile and cure effectively at much lower contents—were used instead of conventional curing agents. Given the wide use of this kind of materials in the adhesive industry, the practical significance of these results must be emphasised. Full article

Global primary energy consumption has increased tenfold over the course of the 20th Century, the availability of non-renewable energy is becoming scarce, and the burning of fossil fuels is leading to global warming. Climate change has now become tangible. The will to act against fossil fuels has become apparent in the western world, and in Germany in particular. This poses a particular challenge for the chemical and pharmaceutical industry, since, in the future, not only will the energy input, but also the feedstock, have to come from non-fossil sources. They must be replaced by carbon capture and utilization, and the exploitation of a circular economy. Concepts for a climate-neutral chemical–pharmaceutical industry have been developed and evaluated. Due to a high predicted consumption of renewable energies and an insufficient expansion of these, Germany will remain an energy importer in the future. The largest consumer in a climate-neutral chemical–pharmaceutical industry will be electrolysis for hydrogen (up to 81%, 553 TWh/a). This can be circumvented by importing green ammonia and cracking. This will require investments of EUR 155 bn. An additional benefit will be increased independence from fossil resource imports, as green ammonia can be produced in a multitude of nations with strong potential for renewable energies and a diversified set of exporting nations. Full article

In February 2020, the president of Microsoft, the executive vice president of IBM, the director general of the Food and Agriculture Organization (FAO) of the United Nations, and the former Italian Minister of Innovation joined the president of the Vatican’s Pontifical Academy for Life in Rome to sign The Rome Call for AI Ethics. In doing so, they promoted a shared sense of responsibility and commitment—by industry, government, and Church—to uphold certain ethical standards in the areas of digital innovation, artificial intelligence, and technological progress. In this article, I discuss The Rome Call for AI Ethics in conjunction with Pope Francis’ rendering of integral ecology and the technocratic paradigm in Laudato Si’. My aim here is to link Catholic teaching on technology (using AI as a starting point) to the environment and the ecological crisis. Full article

Production chemistry is an important field in the petroleum industry to study the physicochemical changes in the production system and associated impact on production fluid flow from reservoir to topsides facilities. Mineral scale deposition and metal corrosion are among the top three water-related production chemistry threats in the petroleum industry, particularly for offshore deepwater and shale operations. Mineral scale deposition is mainly driven by local supersaturation due to operational condition change and/or mixing of incompatible waters. Corrosion, in contrast, is an electrochemical oxidation–reduction process with local cathodic and anodic reactions taking place on metal surfaces. Both mineral scaling and metal corrosion can lead to severe operational risk and financial loss. The most common engineering solution for oilfield scale and corrosion control is to deploy chemical inhibitors, including scale inhibitors and corrosion inhibitors. In the past few decades, various chemical inhibitors have been prepared and applied for scaling and corrosion control. Phosphorus-based polymers are an important class of chemical inhibitors commonly adopted in oilfield operations. Due to the versatile molecular structures of these chemicals, phosphorus-based polymeric inhibitors have the advantage of a higher calcium tolerance, a higher thermal stability, and a wider pH tolerance range compared with other types of inhibitors. However, there are limited review articles to cover these polymeric chemicals for oilfield scale and corrosion control. To address this gap, this review article systematically reviews the synthesis, laboratory testing, and field applications of various phosphorus-based polymeric inhibitors in the oil and gas industry. Future research directions in terms of optimizing inhibitor design are also discussed. The objective is to keep the readers abreast of the latest development in the synthesis and application of these materials and to bridge chemistry knowledge with oilfield scale and corrosion control practice. Full article

In the spirit of innovation, the development of an intelligent robot system incorporating the basic principles of Industry 4.0 was one of the objectives of this study. With this aim, an experimental application of an industrial robot unit in its own isolated environment was carried out using neural networks. In this paper, we describe one possible application of deep learning in an Industry 4.0 environment for robotic units. The image datasets required for learning were generated using data synthesis. There are significant benefits to the incorporation of this technology, as old machines can be smartened and made more efficient without additional costs. As an area of application, we present the preparation of a robot unit which at the time it was originally produced and commissioned was not capable of using machine learning technology for object-detection purposes. The results for different scenarios are presented and an overview of similar research topics on neural networks is provided. A method for synthetizing datasets of any size is described in detail. Specifically, the working domain of a given robot unit, a possible solution to compatibility issues and the learning of neural networks from 3D CAD models with rendered images will be discussed. Full article

One of the most promising research areas in the healthcare industry and the scientific community is focusing on the AI-based applications for real medical challenges such as the building of computer-aided diagnosis (CAD) systems for breast cancer. Transfer learning is one of the recent emerging AI-based techniques that allow rapid learning progress and improve medical imaging diagnosis performance. Although deep learning classification for breast cancer has been widely covered, certain obstacles still remain to investigate the independency among the extracted high-level deep features. This work tackles two challenges that still exist when designing effective CAD systems for breast lesion classification from mammograms. The first challenge is to enrich the input information of the deep learning models by generating pseudo-colored images instead of only using the input original grayscale images. To achieve this goal two different image preprocessing techniques are parallel used: contrast-limited adaptive histogram equalization (CLAHE) and Pixel-wise intensity adjustment. The original image is preserved in the first channel, while the other two channels receive the processed images, respectively. The generated three-channel pseudo-colored images are fed directly into the input layer of the backbone CNNs to generate more powerful high-level deep features. The second challenge is to overcome the multicollinearity problem that occurs among the high correlated deep features generated from deep learning models. A new hybrid processing technique based on Logistic Regression (LR) as well as Principal Components Analysis (PCA) is presented and called LR-PCA. Such a process helps to select the significant principal components (PCs) to further use them for the classification purpose. The proposed CAD system has been examined using two different public benchmark datasets which are INbreast and mini-MAIS. The proposed CAD system could achieve the highest performance accuracies of 98.60% and 98.80% using INbreast and mini-MAIS datasets, respectively. Such a CAD system seems to be useful and reliable for breast cancer diagnosis. Full article

Network Function Virtualization (NFV) is a virtual network model, the goal of which is a cost-efficient transition of the hardware infrastructure into a flexible and reliable software platform. However, this transition comes at the cost of more security threats. A key part of this virtualization environment is the hypervisor, which emulates the hardware resources to provide a runtime environment for virtual machines (VMs). The hypervisor is considered a major attack vector and must be secured to ensure network service continuity. The virtualization environment contains critical non-control data where compromise could lead to several misuses, including information leakage and privilege and resource modification. In this paper, we present a misuse pattern for an attack that exploits the security vulnerabilities of the hypervisor to compromise the integrity of non-control data in the NFV environment. Misuse patterns are used to describe how attacks are carried out from the attackers’ perspective. The threat of modification of non-control data can lead to several misuses, and in this paper, we discuss three of them. The defenses to this attack can be incorporated into the Security Reference Architecture (SRA) of the NFV system to prevent these misuses. Full article

With the rapid development of infrastructure construction, it is an inevitable trend to replace natural sand in short supply with manufactured sand to meet sustainable development. In this paper, the relationship between the particle shape characteristics of manufactured sand and concrete performance is discussed using a morphological analysis and concrete experiments. The particle shape parameters of five types of manufactured sand were obtained by using the aggregate image measurement system (AIMS) and digital image processing (DIP) techniques, and the correlations between different parameters were analyzed. Moreover, the properties of concrete with the five kinds of manufactured sand were tested. The results show that particle size and type have a significant impact on particle shape parameters. Particle shape parameters, especially angularity, correlate well with the workability and compressive strength of concrete while having little effect on the durability of concrete. An accurate understanding of the morphological characteristics of manufactured sand is conducive to the optimization of concrete mix designs. Therefore, it is suggested that a manufactured-sand shape test be included in aggregate specification. Full article

This research is a reflection on new challenges in the economy called Industry 4.0, which has brought about revolutionary changes in many areas of life, including education. To fully use the potential of smart products, services and business opportunities that are expected to be widely used in all sectors in the near future, education systems need to be revised to produce the skilled labour force required by this dynamic process. The ability of companies and institutions with a strong IT and technology infrastructure to reflect advanced digital technologies in innovation and production processes requires specific skills, described as 21st-century skills. Education 4.0 should be a response to these challenges with changed learning and teaching paradigms. In this context, we have organised an extensive survey on the relationship between the economy and higher education in Bosnia and Herzegovina. We have created a web questionnaire that contains desirable characteristics of new employees and a set of questions, the analysis of which was used to determine an actual connection between the economy and higher education. After the factor analysis of the questionnaire, we obtained four desirable characteristics of new employees and the assessment of employers on their representation in each individual. We also concluded that the current impact of the economy on the processes of adopting new curricula is very low. We got the impression that higher education and economic development run in parallel, often without any points of contact. Full article

To resolve the environmental problems of China’s aquaculture industry, we must examine the current situation and comprehensively consider aquaculture growth, resource conservation and environmental protection. Using the unit investigation and evaluation method to evaluate the nonpoint source pollution of each province, this paper calculates eco-efficiency to evaluate the coordination of environment and aquaculture growth based on the slacks-based measure directional distance function dealing with undesirable outputs. The results reveal that the eco-efficiency of aquaculture in China from 2003 to 2018 is 0.70 and obviously lower than the industry’s economic efficiency, indicating aquaculture development has not been coordinated with resources and the environment. Environmental pollution brings great loss to the economic efficiency of aquaculture. Specifically, eastern China, with the highest aquaculture output, shows the best degree of coordination, followed by western China. Six provinces or province-level municipalities, including Fujian, Shanghai, Beijing, Hainan and Tianjin, are growing soundly and rapidly, while central China exhibits the most obvious imbalance among the environment, resources and aquaculture development. Full article

The thriving circular economy is expected to contribute to all three dimensions of sustainable development: environmental, economic, and social. This paper aims to propose a framework to assess social indicators to support circular business models. To validate the framework, we conducted a case study in a medium-size Italian footwear luxury industry, using the Value Focused Thinking–VFT. This approach was used to define proper social indicators to measure the perception of the company’s managers related to the level of incorporation of social dilemmas in the company. We collect data through interviews, documental analysis and direct observation from October/2019 until August/2020 and apply a questionnaire in 2020/2021. The novelty of this paper lies in the proposition of a framework to assess the social indicators in broad categories, capable of covering all supply chains: Corporation, Community; Consumers; Suppliers; Human Rights and Human Resources. Another novelty is related to the analysis of indicators in terms of strategic, tactical, and operational levels, similarly to the idea of a Balanced Scorecard, which was allowed by applying the VFT approach. Full article

Fifth-generation (5G) and beyond networks are envisioned to serve multiple emerging applications having diverse and strict quality of service (QoS) requirements. To meet ultra-reliable and low latency communication, real-time data processing and massive device connectivity demands of the new services, network slicing and edge computing, are envisioned as key enabling technologies. Network slicing will prioritize virtualized and dedicated logical networks over common physical infrastructure and encourage flexible and scalable networks. On the other hand, edge computing offers storage and computational resources at the edge of networks, hence providing real-time, high-bandwidth, low-latency access to radio network resources. As the integration of two technologies delivers network capabilities more efficiently and effectively, this paper provides a comprehensive study on edge-enabled network slicing frameworks and potential solutions with example use cases. In addition, this article further elaborated on the application of machine learning in edge-sliced networks and discussed some recent works as well as example deployment scenarios. Furthermore, to reveal the benefits of these systems further, a novel framework based on reinforcement learning for controller synchronization in distributed edge sliced networks is proposed. Full article

In our analysis, we assessed how Romania dealt with the numerous challenges presented by the COVID-19 pandemic during 2021. In that year, the government had to deal with two waves of COVID-19 pandemics caused by the new variants, the low vaccination rate of the population, the overload of the healthcare system and political instability at the same time. Based on publicly available databases and international literature, we evaluated government measures aimed at reducing the spread of the pandemic and ensure the operation of the healthcare workforce and infrastructure. In addition, we evaluated measures to provide health services effectively and the government’s pandemic responses regarding excess mortality in 2021. In the absence of a complex monitoring system, limited information was available on the spread of the pandemic or the various risk factors at play. Due to incomplete and inadequate management systems, the government was unable to implement timely and adequate measures. Our analysis concludes that the management of a pandemic can only be successful if data are collected and evaluated using complex systems in a timely manner, and if members of society adhere to clearly communicated government measures due to high levels of trust in the government. Full article

Quality evaluation of koi (Cyprinus rubrofuscus) is essential to the koi industry. However, the community has a lack of knowledge about the quality evaluation of koi and about features of koi which are valuable. During the “All Japan Nishikigoi Show” competition, a quality evaluation of koi was conducted by authoritative experts. In the present study, photos of participants of this competition were used for analysis to discover features affecting the quality of the Kohaku variety of koi. The HSVA color model was used to define and extract from image red and pale red coverage rates in Kohaku body coloration. Body aspect ratio, body proportions, red coverage rate, and pale red coverage rate were extracted using tools written in Python programming language. Analyses of the extracted data revealed the significant impact body aspect ratio (p < 0.001) and pale red coverage rate (p < 0.001) on Kohaku quality. A low body aspect ratio has a positive impact on Kohaku quality, while a high pale red coverage rate has a very strong negative impact on Kohaku quality. This study and its results can be an important foundation for further research about koi quality. Full article

Climate-induced pressures spur on the need for urban green infrastructure (UGI) planning. This approach offers a possible way to improve ecosystem functionality and human well-being in adversely affected urban regions, wherein UGI is perceived as a green and nature-based climate change mitigation/adaptation strategy. In Pakistan, the Khyber Pakhtunkhwa (KP) province lacks such urban landscape and greening policies (ULGP) or legislative frameworks for transitioning to green action plans (GAP), to alleviate the risk of multi-climatic hazards. Thus, this study aims to investigate a sustainable UGI-indicator-based framework model, based on the due inclusion of the concerned stakeholders. The relative importance index (RII) and inter-quartile range (IQR) techniques are employed for field data analysis. The findings proclaim excellent reliability (α > 0.7) and internal consistency, wherein sustainable UGI indicators are grouped based on their importance. The results portray the ecological and economic sustainability dimensions as being important (RII = 0.835 and RII = 0.807, respectively), socio-cultural dimensions as being moderately important (RII = 0.795), and a set of UGS elements (RII ≥ 0.77) as vital for bolstering individual UGI indicators. The main UGS elements emerging in each category can be grouped as follows: ecological category—“reducing rainwater runoff” (RII = 0.94); socio-cultural category—“enhancement of mental and physical health” (RII = 0.90); and eco category—“minimizing the risk of flood disasters” (RII = 0.96). The simulation results demonstrate the need for an inclusive perspective when building the urban green space (UGS) infrastructure (and standards) that will be most suitable for ensuring climate-resilient urban regions. This study contributes to putting the scientific research knowledge of the natural green-landscape-based (NBLB) approach into practice. The study calls for the establishment of an effective, pragmatic relationship between the urban landscape and greening policies, alongside a constructive relationship with the native inhabitants to ensure eco-friendly and resilient settlements. Full article

Gelidium corneum (Giant Gelidium or Atlantic agar) is a well-known red seaweed harvested for its high-quality agar content. Agar is a mixture of the polysaccharides used in the food industry as a gelling, thickener, clarifying, and stabilizer agent. The best agar quality is also used in the laboratory as bacteriological agar. Yet, in recent years, the species has been studied for many other applications. Examples of uses are pharmaceuticals, cosmetics, food supplements, bioremediation, biofuels, biofertilizers and biostimulants, biomaterials, and nanocrystals, among others. The use of this biomass, though, raises concerns about the sustainability of the resource, since this is not a cultivated species, being harvested in the wild. Thus, other uses of G. corneum biomass increase pressure on wild stocks already stressed due to climate change. However, in a biorefinery approach, a new trend is emerging, using waste biomass rather than harvested biomass to produce new bio-based materials. These are smart solutions that transform waste into innovative products, useful for various sectors of society while reducing the impact of biomass exploitation. The aim of this review paper, thus, is to address the current state of G. corneum biology, ecology, threats, its current uses and market, and the ongoing research on innovative proposals in a circular economy framework. Full article

As one of the most destructive oligophagous pests, the chrysanthemum aphid (Macrosiphoniella sanborni) has seriously restricted the sustainable development of the chrysanthemum industry. Olfaction plays a critical role in the environmental perception of aphids, but very little is currently known about the chemosensory mechanism of M. sanborni. In this study, four MsanOBPs, four MsanCSPs, eight MsanORs, two MsanIRs and one MsanSNMP were identified among the 28,323 unigenes derived from the antennal transcriptome bioinformatic analysis of M. sanborni adults. Then, comprehensive phylogenetic analyses of these olfactory-related proteins in different aphid species were performed using multiple sequence alignment. Subsequently, the odor-specific and wing-specific expression profiles of these candidate chemosensory genes were investigated using quantitative real-time PCR. The data showed that most of these chemosensory genes exhibited higher expression levels in alate aphids. Among them, MsanOBP9, MsanOR2, MsanOR4, MsanOR43b-1, MsanCSP1, MsanCSP2, MsanCSP4, MsanIR25a and MsanIR40a in alate aphids showed remarkably higher expression levels than in apterous aphids under the effect of the host plant volatiles, indicating that these genes may take part in the specific behaviors of alate adults, such as host recognition, oviposition site selection and so on. This study lays the groundwork for future research into the molecular mechanism of olfactory recognition in M. sanborni. Full article

To control the negative effects resulting from the disorderly development of aquaculture ponds and promote the development of the aquaculture industry, rapid and accurate identification and extraction techniques are essential. An aquaculture pond is a special net-like water body divided by complex roads and dikes. Simple spectral features or spatial texture features are not sufficient to accurately extract it, and the mixed feature rule set is more demanding on computer performance. Supported by the GEE platform, and using the Landsat satellite data set and corresponding DEM combined with field survey data, we constructed a decision-making model for the extraction of aquaculture ponds in the coastal waters, and applied this method to the coastal waters of Southeast China. This method combined the image spectral information, spatial features, and morphological operations. The results showed that the total accuracy of this method was 93%, and the Kappa coefficient was 0.86. The overlapping proportions of results between the automated extraction and visual interpretation for test areas were all more than 90%, and the average was 92.5%, which reflected the high precision and reliability of this extraction method. Furthermore, in 2020, the total area of coastal aquaculture ponds in the study area was 6348.51 km², which was distributed primarily in the cities of Guangdong and Jiangsu. Kernel density analysis suggested that aquaculture ponds in Guangdong and Jiangsu had the highest degree of concentration, which means that they face higher regulatory pressure in the management of aquaculture ponds than other provinces. Therefore, this method can be used to extract aquaculture ponds in coastal waters of the world, and holds great significance to promote the orderly management and scientific development of fishery aquaculture. Full article

The road transport industry faces the need to develop its fleet for lower energy consumption, pollutants and CO₂ emissions. Waste heat recovery systems with Thermoelectric Generators (TEGs) can directly convert the exhaust heat into electric energy, aiding the electrical needs of the vehicle, thus reducing its dependency on fuel energy. The present work assesses the optimisation and evaluation of a temperature-controlled thermoelectric generator (TCTG) concept to be used in a commercial heavy-duty vehicle (HDV). The system consists of a heat exchanger with wavy fins (WFs) embedded in an aluminium matrix along with vapour chambers (VCs), machined directly into the matrix, that grant the thermal control based on the spreading of local excess heat by phase change, as proposed by the authors in previous publications and patents. The TCTG concept behaviour was analysed under realistic driving conditions. An HDV with a 16 L Diesel engine was simulated in AVL Cruise to obtain the exhaust gas temperature and mass flow rate for each point of two cycle runs. A model proposed in previous publications was adapted to the new fin geometry and vapour chamber configuration and used the AVL Cruise data as input. It was possible to predict the thermal and thermoelectric performance of the TCTG along the corresponding driving cycles. The developed system proved to have a good capacity for applications with highly variable thermal loads since it was able to uncouple the maximisation of heat absorption from the regulation of the thermal level at the hot face of the TEG modules, avoiding both thermal dilution and overheating. This was achieved by the controlled phase change temperature of the heat spreader, that would ensure the spreading of the excess heat from overheated to underheated areas of the generator instead of wasting excess heat. A maximum average electrical production of 2.4 kW was predicted, which resulted in fuel savings of about 2% and CO₂ emissions reduction of around 37 g/km. Full article

The digitization of electrical substations brings great challenges for the commissioning of electrical protections, and interoperability tests must be performed with different equipment. Therefore, this work evaluates the response time of an electrical protection relay operating with sampled values in a digital substation with a process bus. A test scheme is proposed to emulate the process bus based on analyzing the main components in a digital substation with multi-vendor device interoperability. In addition, the delay times of the protection relay with the process bus are measured, considering interoperable infrastructure as a fundamental factor in the system performance. The results are compared with the response times of a conventional relay that operates with analog signals to identify the impact of the digitalization of signals in electrical substations with a process bus. Each relay has an instantaneous overcurrent function adjusted to operate with the same pickup currents at different fault current levels. The results show that tripping times are admissible for the operation of the protection relays, considering three-time measuring points in the test scheme. The time delays found are related to high data traffic in the communication network and the traffic saturation according to the time measuring point. Other delays related to processing SVs in an MU do not represent a risk for the protection scheme. For the industry, the methods presented in the research are useful for configuring and testing electrical substations with different equipment and topologies. In addition, the results presented here seek to generate confidence in companies and engineering teams when migrating to systems with digital substations. Full article

Recent efforts to achieve social, economic, and environmental goals related to sustainability emphasize the importance of nature-based solutions (NBS), as grey infrastructure alone is insufficient to address current challenges. The majority of frameworks proposed in the literature fail to address the full potential of NBS, neglecting long-term results, unintended consequences, co-benefits, and their contribution to achieving global environmental agreements, such as the Agenda 2030, especially for water management in a peri-urban context. Here we present an innovative framework that can be applied to both NBS project planning and evaluation for several water-based challenges, giving practitioners and researchers a tool not only to evaluate ongoing projects but also to guide new ones. The framework considers three main stages of a NBS project: (1) context assessment, (2) NBS implementation and adaptation process, and (3) NBS results. This tool has the potential to be used to evaluate whether NBS projects are aligned with sustainability dimensions through a set of adaptable sustainability indicators. The framework can also highlight how the NBS targets are related to the sustainable development goals (SGD) and contribute to catalyzing the 2030 Agenda. The framework is an important tool for water management and other NBS types. Full article

Metallic nanoparticles potentially have wide practical applications in various fields of science and industry. In biosensorics, they usually act as catalysts or nanozymes (NZs) and as mediators of electron transfer. We describe here the development of amperometric biosensors (ABSs) based on purified oxidases, synthesized nanoparticles of CuCe (nCuCe), and micro/nanoporous gold (pAu), which were electro-deposited on a graphite electrode (GE). As an effective peroxidase (PO)-like NZ, nCuCe was used here as a hydrogen-peroxide-sensing platform in ABSs that were based on glucose oxidase, alcohol oxidase, methylamine oxidase, and L-arginine oxidase. At the same time, nCuCe is an electroactive mediator and has been used in laccase-based ABSs. As a result, the ABSs we constructed and characterized were based on glucose, methanol, methyl amine, L-arginine, and catechol, respectively. The developed nCuCe-based ABSs exhibited improved analytical characteristics in comparison with the corresponding PO-based ABSs. Additionally, the presence of pAu, with its extremely advanced chemo-sensing surface layer, was shown to significantly increase the sensitivities of all constructed ABSs. As an example, the bioelectrodes containing laccase/GE, laccase/nCuCe/GE, and laccase/nCuCe/pAu/GE exhibited sensitivities to catechol at 2300, 5055, and 9280 A·M⁻¹·m⁻², respectively. We demonstrate here that pAu is an effective carrier of electroactive nanomaterials coupled with oxidases, which may be promising in biosensors. Full article

Ensuring the reliability of data gathering from every connected device is an essential issue for promoting the advancement of the next paradigm shift, i.e., Industry 4.0. Blockchain technology is becoming recognized as an advanced tool. However, data collaboration using blockchain has not progressed sufficiently among companies in the industrial supply chain (SC) that handle sensitive data, such as those related to product quality, etc. There are two reasons why data utilization is not sufficiently advanced in the industrial SC. The first is that manufacturing information is top secret. Blockchain mechanisms, such as Bitcoin, which uses PKI, require plaintext to be shared between companies to verify the identity of the company that sent the data. Another is that the merits of data collaboration between companies have not been materialized. To solve these problems, this paper proposes a business-to-business collaboration system using homomorphic encryption and blockchain techniques. Using the proposed system, each company can exchange encrypted confidential information and utilize the data for its own business. In a trial, an equipment manufacturer was able to identify the quality change caused by a decrease in equipment performance as a cryptographic value from blockchain and to identify the change one month earlier without knowing the quality value. Full article

Over recent decades, Circular Economy (CE) has become a major topic when organizations try to develop their business amid the constrains of resource limitation and the desire to reduce their environmental impact. This study’s main purpose is to assess the integration of CE practices in public and private organizations in the northwest of the Iberian Peninsula. Through an online survey distributed to 294 companies from the cited region, we assessed their perceptions on CE, including such aspects as the area(s) it was integrated in, why, with what difficulties or what was necessary to accomplish it, and how the impact of the implemented CE practices was measured. Results showed that companies associate CE mostly with “resource optimization”. “Entity’s vision and mission” was the main strategic area where CE was implemented. The main motivation why entities/organizations embraced CE was “environmental reasons”, while “lack of information and guidance” and “lack of financial resources” represented the main obstacles to CE implementation. Non-parametrical statistical tests were used to compare the answers of three groups of people with different positions within the company/entity (manager, executive, and technician), as well as to compare the answers of two activity sectors (industry and services). Full article

The increase in predatory practices in the substance use disorder treatment industry calls for the development of measures to assess individuals’ knowledge about these practices. Methods: This study describes the development of the Knowledge of Predatory Practices Scale (KPPS), a newly developed measure designed to assess the knowledge of predatory practices within the substance use disorder treatment industry. An exploratory factor analysis was conducted to determine the factor structure of this measure. Results: The final 11-item KPPS consisted of two factors—knowledge about general predatory practices (9 items) and knowledge about unethical practices (2 items). Overall, these factors explained 61.75% of the total variance. The Cronbach’s alpha for the KPPS was 0.81. Conclusions: The KPPS is a reliable measure of knowledge of predatory practices within the substance use disorder treatment industry and can be used as a measurement tool to educate individuals seeking help for their loved ones who are misusing substances. Full article

This study explores the relationship between environmental regulations (ERs) and competitiveness, and the moderating role of the research level, economic development, industry characteristics, and types of measurement in this relationship. To this end, we conducted a meta-analysis of 30 empirical studies. We found that overall, ERs are positively correlated with competitiveness; the industry characteristics have a significant moderating effect on the ER–competitiveness relationship, and ERs more significantly improve the competitiveness of pollution-intensive industries; and the relationship between ERs and competitiveness is universal across research levels, economic development, and types of measurement. This study extends the previous research by supporting the Porter hypothesis and provides a theoretical basis for governments to strengthen the intensity of ERs for pollution-intensive industries and theoretical guidance for enterprises to respond to ERs. Full article

Blockchain-based platforms utilise cryptographic protocols to enforce the correct behaviour of users, as well as to guarantee a sufficient level of protection against malicious adversaries. Cryptography is, however, an ever-evolving discipline, and any breakthrough would have immediate consequences on the security of blockchain-based applications. A possible threat currently under investigation is given by the development of quantum computers, since several wide-adopted cryptographic protocols have been proved to be unsafe against quantum-capable adversaries. In this work, we propose a novel approach for the management of cryptographic primitives in smart-contract-based ledgers, discussing how it fits in both a (partially) permissioned and a fully permissionless setting. The cryptographic protocols are managed in a flexible manner via a set of smart-contracts defined on the ledger itself, in this way the choice of algorithms and parameters can change quickly. Among the advantages of this approach, we remark how it allows designing an adaptive post-quantum-based blockchain that keeps up with ongoing technological advances. In general, the introduction of new features and the application of fixes to a blockchain cause forks in the chain, which may cause major disruptions. The use of smart contracts in blockchain management allows to avoid this problem, dynamically introducing new protocols or deprecating old ones without compromising previous data. The Cryptographic Kernel approach has been adopted by Quadrans, an open-source, public, decentralised smart-contract-based blockchain with a specific focus on the needs of industry, complex supply chains, and IOT devices. Full article