Abstract: This study investigates the transition to sustainable shipping industry within the framework of the IMO's 2050 carbon neutrality objective, focusing on socio-technical systems analysis. The research delves into the sustainable paradigm shift towards alternative marine fuels such as LNG, methanol, ammonia, and hydrogen from a socio-technical transition perspective, analyzing the multi-level per-spective challenges and opportunities. Specifically, it scrutinizes the implications of adopting these al-ternative fuels for global shipping, identifying technical uncertainties, financial constraints, and infra-structure needs. Through a comprehensive review of existing literature on ship emissions and alterna-tive fuels, coupled with socio-technical transition theory, the study addresses the multifaceted chal-lenges and opportunities in meeting the IMO's environmental objectives. It emphasizes the necessity of collaborative governance, innovative niche strategies, and a holistic approach to leverage the current window of opportunity in facilitating the maritime industry's transition to sustainable fuel options. Fi-nally, this research enhances our understanding of the intricate interplay between technological, social, industrial, and cultural dynamics in the greening of shipping and offers insights into the strategic adop-tion of environmentally friendly marine fuels for a sustainable future.

The collaboration of multimodal transport documents is the foundation for conducting multimodal transport operations. Blockchain technology can effectively address trust issues and information sharing difficulties in current multimodal transport document collaboration. However, in current blockchain-based electronic document research, the bottleneck problem lies in the collaboration of multiparty in multimodal transport under the "one-bill coverage system". We design a blockchain platform architecture for multimodal transport, reshaping collaboration processes for different modes of transport based on the blockchain platform. It proposes a collaboration model for multimodal transport under the "one-bill coverage system" and performs model solving and case analysis. The obtained collaboration strategies are embedded into the platform's application layer. Finally, using Solidity language, it writes smart contracts related to multimodal transport under the "one-bill coverage system " and deploys and executes them on the Remix platform.

Air pollution is a leading cause of death worldwide, and has a profound impact on the planet's climate and ecosystems. A substantial portion of air pollution is attributable to Ocean Going Vessels (OGVs). In light of this, international regulations have been put in place to mitigate air pollutant emissions from OGVs. While studies have indicated that these regulations can create significant health, environmental, and economic benefits, there remains a research gap regarding their specific impact on enhancing air quality. The aim of this study is to investigate how the implemented regulations have affected air quality in the Southern North Sea. The study found that the international regulations on ship emissions have successfully led to a decline in SO2 emissions from OGVs in the Southern North Sea, which resulted in a reduction of ambient SO2 concentrations inland, leading to positive effects on public health and the environment. However, it was projected that their proportion is tend to increase in the following years. Moreover, the study revealed that Exhaust Gas Cleaning Systems (EGCS) present significant concerns. They were significantly more frequently found to be non-compliant, and more alarmingly, they emit notably higher average levels of SO2. It also turned out that international regulations in the southern North Sea have less effect on the reduction of NOx emissions from OGVs than expected. The NOx emissions from OGVs will even account for an alarming 40% of the total domestic NOx emissions for the Belgian Region by 2030.

Emerging data processing techniques brought back into attention the HF range communication as an interesting alternative to third-party solutions for IoT applications, such as data transmission in distributed energy production facilities. The physical size of HF antennas, often comparable to the surrounding objects, require in-situ radiation measurements. Drone-borne measuring systems are already known as a flexible solution, but mostly restricted to higher frequency ranges. In this work, we propose to use an electrically small, folded dipole as a probe for drone-borne measurements on HF antennas. We also propose a calibration approach for the effects related to the near-field zone, and to the drone body proximity. The impact of ground reflection is also investigated. We show that despite its low, realized gain figure such a probe can provide stable results for near-field measurements, even at low input power levels.

The effect of wave forces on the structural safety of fixed oscillating water-column (OWC) devices is critical. In this study, a three-dimensional numerical model of an oscillating water column (OWC) device is constructed using the computational fluid dynamics software OpenFOAM. Subsequently, the hydrodynamic performance of the numerical model is comprehensively validated. Finally, the hydrodynamic performance data are analyzed in detail to obtain meaningful conclusions. The results indicate that the horizontal wave force on the OWC device is approximately 6.6 to 7.9 times greater than the vertical wave force, whereas the lateral wave force is relatively small. Both the horizontal and vertical wave forces decrease as the relative water depth increases under a constant wave period and height. The horizontal wave force increases linearly with the wave height, whereas the vertical wave force increases with the square of the wave height. In addition, the highest dynamic water pressure is observed at the interface between the water surface and device, both within and outside the front wall of the gas chamber. The dynamic water pressure at different locations on the front chamber increases and subsequently decreases as the wave frequency increases.

We study a two-echelon supply chain made up of a supplier and a manufacturer, both of which can reduce their component/product carbon emissions. With the vertical technology spillovers, we explore the optimal decisions of centralized and decentralized supply chains with price dependent demand and propose coordination strategy for the decentralized supply chain. Considering the cost contraction effectiveness of the technology spillovers, the centralized and decentralized game theoretic models of a two-echelon supply chain are developed to investigate optimal decisions of pricing and carbon emissions reduction. Through a systematic comparison and numerical analysis, we show that the profits of both players and the entire supply chain improve with the effect of technology spillovers increasing. Carbon emissions reduction will be taken by various protective measures so that the supplier and the manufacturer who do not innovate can hardly share the results of innovating via the “free-riding” methods when the technology spillover is relatively small. We also propose a revenue-cost sharing contract through bargaining to enhance the performance of the decentralized supply chain.

The intense motion of a ship can greatly impacts the comfort of crew members and the safety of the vessel. Therefore, accurately estimating and predicting ship attitudes has become an important issue. This paper introduces the latest development in functional deep learning model called DeepOnet. It takes wave height as input and ship motion as output, using a cause-to-result prediction approach. The modeling data used in this study is sourced from publicly available experimental data from the Iowa Institute of Hydraulic Research. Firstly, parameters system tuning was conducted for the neural network's hyperparameters to determine the appropriate combination of parameters. Secondly, the DeepOnet model for wave height and multi-degree-of-freedom motion was established, and the influence of increasing time steps on prediction accuracy was examined. Finally, a comparison was made between the DeepOnet model and the classical time series model LSTM. It was found that the DeepOnet model had a 10-fold improvement in accuracy for roll and heave attitudes. Moreover, as the forecast duration increased, the advantage of DeepOnet showed a trend of strengthening. As a functional prediction model, DeepOnet provides a new promising tool for very short-term prediction of ship motion.

This study aimed to learn disturbance information to effectively control multiple small unmanned surface vehicles (USVs) for marine research purposes at sea. The learned disturbance information was used to investigate the control of multiple USV swarms based on the leading–following formation technique. Numerous studies have already been conducted on swarm control using drones in the air; however, there has been a paucity of studies on swarm control in the sea. Contrary to swarm control in aviation, the fluid density of the sea is high, and the environment is constantly changing; thus, a robot system would be significantly affected by disturbances. This ultimately influences the maintenance of swarm formations and the accomplishment of missions [1,2]. Therefore, it is difficult to control numerous moving objects while maintaining a formation at sea by using the existing aerial drone swarm control technology. To solve this problem, we learned a long short-term memory (LSTM) model with time-series marine environmental data to predict maritime disturbances. Thereafter, the model was applied to a mission-based position control algorithm of each USV constituting the swarm to design a marine unmanned floating vessel swarm control system that can be applied to various marine environments. Specifically, to effectively control numerous small USVs for marine research purposes, ocean currents are learned using the LSTM algorithm, and the predicted ocean currents are used to generate a swarm USV control system for USV formations. In this study, a control system model of several small USVs equipped with two rear thrusters and a front lateral thruster was designed. The LSTM algorithm was learned using the previous ocean current data, and the velocity of the following ocean currents was predicted. The predictions were then used as a system disturbance to determine the thrust of the controller. To measure ocean currents in the sea when each USV moves, the velocity, azimuth, and position (latitude, longitude) data from the GPS mounted on the USV were used to measure the velocity and direction of the hull's movement. Further, the flow rate was measured using a flow rate sensor on a small USV. The USV movement and position were controlled using an artificial neural network-PID (ANN-PID) controller. This study entailed a comparative analysis of the designed USV model results and those generated by the simulator, including the behavior control rule of the USV swarm and the path of the actual USV swarm at sea. It was verified that the effectiveness of the USV mathematical model and behavior control rules. By comparing the movement path of the swarm USV with and without the disturbance learning algorithm and ANN-PID control algorithm applied to the designed simulator, the position error and maintenance performance of the swarm formation were analyzed, and the application results were compared.

The maneuverability of ships is influenced by several factors, including ship design, size, propulsion system, hull shape, and external conditions such as wind, waves, and currents. The size, shape, and arrangement of the hull, rudder, and propeller are decisive for maneuverability. Hydrodynamic forces such as bank effect and squat significantly impact the maneuverability of large ships in narrow channels. With the increasing trend of building ever-larger ships, the demand to evaluate the maneuvering performance of the ship at the design stage has become more critical than ever. Both experimental and computational methods are used to obtain accurate maneuvering characteristics of vessels. In this study, the methods for predicting ship maneuvering characteristics are analyzed using a systematic review based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA). This article contributes to a deeper understanding of the hydrodynamic capabilities of ships and identifies possible future challenges in the field of ship hydrodynamics. The findings inform educators and the shipping industry about the importance of predicting the maneuvering performance of ships, with an emphasis on the education and training of seafarers needed to make timely decisions in critical situations.

This study proposes and validates a novel combustion control system for Oil-Fired Boilers aimed at reducing air pollutant emissions through flame image prediction. The proposed system is easily applicable to existing ships. Traditional proportional combustion control systems supply fuel and air at fixed ratios according to the set steam load, without considering the emission of air pollutants. To address this, a stable and immediate control system is proposed, which adjusts the air supply to modify the combustion state. The combustion control system utilizes oxygen concentration predictions from flame images via SEF+SVM as control inputs, and applies Internal Model Control (IMC)-based Proportional-Integral (PI) control for real-time combustion control. Due to the complexity of modeling the image-based system, IMC parameter tuning through experimentation is essential for achieving effective control performance. Experiments conducted on a 3000 kg/h marine oil-fired boiler in actual operation optimized the controller parameters for stability and responsiveness, and validated their effectiveness. The results demonstrate the potential of the proposed system to improve combustion efficiency and reduce emissions of air pollutants. This study provides a feasible and effective solution for enhancing the environmental performance of marine oil-fired boilers. Given its ease of application to existing ships, it is expected to contribute to sustainable air pollution reduction across the maritime environment.

The article presents the issues related to the operation and modelling of the ship main propulsion steam boiler. Such objects are used widely in seagoing ships especially the very large crude oil carriers as a main propulsion turbine feed. The advantages of such along with simple construction thus great reliability make oil feed boilers an excellent source of power for chosen type of the large ships. It must be pointed out that a lot of research work was done in the previous years regarding automatic control of boiler automation but since then this technology was not in the focus of the researchers. In the future the fossil fuels will become less important than they are now, but the control techniques of boilers would eventually change due to different fuel parameters therefore, development of such is necessary. The article presents the results of research collected in real ship boilers during their operation and then, based on the results, a digital model of such an object was created. This model was implemented into Hardware-In-Loop which is the initial step for preparing the full model (including sensors etc.) of a steam heated boiler. Theoretical background along with chosen simulation and experimental results of control implemented into HIL were presented to validate assumptions...

The maritime industry contributes to over 80% of global trade and ranks as the sixth-largest emitter of greenhouse gases. The International Maritime Organization has taken strides to reduce these emissions, while the European Union spearheads efforts to establish sustainable maritime transport. However, meeting decarbonisation targets poses significant challenges, with the potential implications of adopting an EU Emission Trading System (ETS) on shipping allowances, particularly at specific borders. If not managed effectively, this could result in diversifying regular container shipping routes away from EU ports, potentially leading to increased shipping emissions and disrupting the logistics trade and security chain. These challenges are exacerbated by the International Maritime Organization's lack of a carbon fee on bunkering, which creates an imbalance. The ETS Directive has fostered unfair competition between EU and non-EU ports due to discrepancies in applying emission unit allowances. It is imperative to implement preventive measures to contain and prevent the shift of operations from EU ports to nearby ports, ensure equitable treatment of EU transhipment ports and their competitors, and thwart carbon leakage. Additionally, the recent Houthis attacks on the Red Sea have significantly impacted shipping costs on the Cape of Good Hope route to Europe, necessitating increased allowances to and from Europe.

A finite element model of 100m X-BOW polar exploration cruise is established. The entire ship frequency response analysis was carried out, comparing the simulated values with the test values, the maximum error is 22%, but only 0.24mm/s difference, the error can be ignored from the perspective of comfort, therefore, the simulation results meet the requirements of engineering accuracy and verify the effectiveness of the model. According to the solution method for global modal equivalent mass, combing the spatial distribution principle of local modal mass, the method for solving the equivalent mass of a single local mode in mixed mode is proposed, the equivalent mass of the local vibration region of 100m X-BOW polar exploration cruise ship is solved by this method, tuned mass dampers mass ratio parameters are calculated using the equivalent mass. According to the analysis, tuned mass dampers has 31dB vibration absorption effect at 13.4Hz when the mass ratio is 0.05, it also has certain control effect at 10Hz and 18.8Hz, the control effect is 3dB and 2dB respectively, the overall control frequency band is flat and robust.

Exosomes are produced by all cell types, their biogenesis is of endosomal origin, originating as a result of cell membrane invagination. Furthermore, physiochemical characteristics are important prerequisites for their commercial application. The representative size range of exosomes is 50-200 nm. Whereas, comparative to animal cell, exosomes from plant cell sources have a relatively larger size range, moreover, exhibit broader therapeutic potential. In this review study, we have briefly discussed the research potential of plant-derived exosomes. Including their earlier studies on biogenesis, characterization, isolation methods, and possible therapeutic applications. Additionally, we have quoted targeted drug delivery for targeted therapies and have provided insights of methods for customizing exosomes produced from plants with various drugs. Most-importantly, here we have embodied exosomes from plant sources are natural nano-inducers possessing the ability for inter-kingdom communication, resulting in cross-kingdom regulations.

Many fields of human activity benefit from the ability to create images of obscured objects placed behind walls and to map their displacement in a noninvasive way. Usually, imaging devices like Synthetic Aperture Radars (SAR) and Ground Penetrating Radars (GPR) use expensive dedicated electronics which results in prohibitive prices. This paper presents the experimental implementation and the results obtained from an imaging system capable of performing SAR imaging and interferometric displacement mapping of targets located behind walls, as well as 3D GPR imaging using a low-cost general-purpose radar sensor. The proposed solution uses for the RF section of the system a K-band microwave radar sensor module implementing Frequency Modulated Continuous Wave operation. The low-cost sensor was originally intended for simple presence detection and ranging for domestic applications. The proposed system was tested in several scenarios and proved to operate as intended for a fraction of the cost of a commercial imaging device.

The article considers the issues of ensuring operational performance and environmental sustainability of marine diesel engines by using biodiesel fuel. The research was conducted on 5S60ME-C8 MAN-B&W Diesel Group and 6DL-16 Daihatsu Diesel marine diesel engines, which were operated using RMG380 petroleum fuel and B10 and B30 biodiesel fuels. The efficiency of biofuel usage was assessed based on environmental (reduced nitrogen oxide concentration in exhaust gases) and economic (increased specific effective fuel consumption) criteria. It was found out that the use of B10 and B30 biofuels provides reduction of nitrogen oxides concentration in exhaust gases by 14.71–25.13 %, but at the same time increases specific effective fuel consumption by 1.55–6.01 %. Optimum fuel injection advance angles were determined that ensure the best thermal energy, economic and environmental performance of diesel engines. The optimum angle of biofuel supply advance is determined experimentally and should correspond to the limits recommended by the diesel engine operating instructions. It has been proven experimentally that the use of biofuel increases the environmental sustainability of marine diesel engines by 13.75–29.42 %. It increases the diesel engines environmental safety in case of emergency situations, as well as accidental and short-term emissions of exhaust gases with an increased content of nitrogen oxides into the atmosphere - phenomena that are possible in starting modes of diesel engine operation, as well as in modes of sudden load changes. It is the increase in the environmental friendliness of marine diesel engines in the case of using biofuel that is the most positive criterion and contributes to the intensity of biofuel use in power plants of sea vessels.

Shipping is a vital component of global trade. However, shipping activities have negative environmental impacts, including emissions to air and water. The Baltic Sea is severely affected by eutrophication, mainly due to nutrient inputs, especially nitrogen and phosphorus. The aim of this research is to quantify the nutrient content of black and grey water discharged from cargo ships in the Baltic Sea in order to assess their contribution to the total nutrient load. Specifically, the research examines the nitrogen and phosphorus loadings from ships calling the port of HaminaKotka and addresses key questions regarding nutrient generation, discharge proportions, emission shares by ship type and their importance compared to other sources. Using a methodology based on ship data and nutrient production estimates, the study found that 2545 cargo ships generated a total of 781 kg of nitrogen and 134 kg of phosphorus in their effluents during their voyages to the port in 2021. However, only a small fraction (0.5%) of the cargo ships discharged their wastewater at port reception facilities. The study concludes that, although nutrient discharges from cargo ships are relatively small compared to other nutrient sources, efforts to promote port reception or onboard treatment are important for environmental sustainability. Further research is recommended to assess the effectiveness of onboard treatment systems, the impact of other contaminants in wastewater and the development of port reception facilities to facilitate proper wastewater management in the maritime trade.

Climate change poses a significant threat to European security, implicitly to Romania’s naval forces in the Black Sea. Rising sea levels, extreme weather events, and ocean acidification impact maritime operations, infrastructure, and personnel, with potential ramifications for regional stability. This paper explores the implications of climate change for the Romanian Navy and proposes "Green Defence" strategies to enhance resilience and sustainability. These strategies encompass energy efficiency, renewable energy integration, sustainable procurement, and the application of advanced functional materials in naval operations and infrastructure. By adopting a proactive and multifaceted approach, the Romanian Navy can adapt to the changing climate, ensuring operational effectiveness while minimizing environmental impact. This approach aligns with broader European security concerns and contributes to a more sustainable and resilient defence posture in the face of climate-related challenges.

In Korea, laver (Gim) is the leading traded marine product and an important food source, accounting for 82.0% of the world’s exports. Laver exports reached $100 million in 2010 and steadily increased to $600 million in 2020. An increase in laver exports improves the income of laver farmers and promotes the growth of fisheries. However, marine algae are vulnerable to climate change. In this study, we aimed to predict changes in laver production due to climate change using environmental variables, including water temperature, rainfall, and sunlight duration. The results showed that water temperature considerably affected laver production; when water temperature increased by 1 °C, production decreased by 13.78% (t) in the same month. By contrast, when sunlight duration and rainfall increased by 1 h and 1 mm, respectively, 1 month before harvesting laver, production increased by 0.32% (t-1) and 0.13% (t-1), respectively. Using four scenarios based on climate change published by the Intergovernmental Panel on Climate Change in a modeling exercise, we found that laver production in 2100 in Wando in Korea may decline by 73.3% owing to water temperature changes (based on 2020 production), threatening food security. Accordingly, short-, mid-, and long-term countermeasures are needed for sustainable laver aquaculture. Appropriate water temperature (21–22 °C) during seeding is necessary to control environmental variables, based on scientific data and activation of land-based seeding methods. Moreover, mid- and long-term countermeasures should include development of high-temperature resistant laver seeds, identification of suitable new laver aquaculture grounds, and research on seeds that can adapt to climate change.

To address the challenge of recognizing ship states accurately amidst the complexities of marine environments, this study proposes a novel ship state recognition approach leveraging a graph convolutional neural network (GCNN). Initially, the method extracts canonical and efficient ship motion trajectories from AIS data. Subsequently, a state recognition network tailored for ship motion trajectories is devised and implemented employing graph convolution. Notably, the accuracy of this model is enhanced through the introduction of novel weights and optimization of the Adj parameter. Experimental evaluations conducted on a ship state dataset demonstrate significant performance improvements. Specifically, the proposed recognition network achieves a recognition accuracy of 98.3% for regulated ship trajectories, marking an impressive 8.4% enhancement over traditional convolutional neural networks. This advancement holds promise for enhancing ship state recognition accuracy across diverse maritime applications including maritime supervision, navigation safety, and ship management.

Disruptions in power quality have a negative impact on many energy consumers. These include lighting, where interference manifests itself, among others, in the form of light flickering. The article presents phenomena accompanying the operation of modern light sources against the background of exemplary results of studies on the flicker of conventional light sources, such as incandescent or fluorescent lamps. To assess the effects of these phenomena, it is necessary to use measures other than those traditionally used. The results of measurements carried out in accordance with different recommendations take into account both power supply disturbances and the properties of modern light sources.

In GNSS/IMU integrated navigation systems, factors such as satellite occlusion and non-line-of-sight conditions can lead to degradation of satellite positioning results, Subsequently affecting the overall accuracy of the integrated navigation system. To address this issue and ef-fectively utilize historical pseudorange information from satellites, this paper proposes a graph optimization-based GNSS/IMU model with virtual constraints. These virtual constraints are con-structed using satellite ‘s position from previous time step, the rate of change of pseudoranges, and ephemeris data. This virtual constraint can serve as an alternative solution for individual satellites in case of signal anomalies, ensuring the integrity and continuity of the graph optimi-zation model. Additionally, this paper conducts an analysis of the graph optimization model constructed using these virtual constraints, comparing it with traditional integrated navigation graph optimization model, and analyzes and reconstructs the marginalization process based on these virtual constraints. The experimental results, compared with tightly coupled Kalman fil-tering and the original graph optimization method on a set of real-world data, demonstrate that the introduction of virtual pseudoranges maintains high positioning accuracy. The RMSE error between it and the original graph optimization remains within 5%, affirming the high feasibility of this approach.

The last-mile logistics in cities have become an indispensable part of the urban logistics system. This study aims to explore the effective selection of last-mile logistics nodes to enhance the efficiency of logistics distribution, strengthen the corporate distribution image, and further reduce corporate operating costs and alleviate urban traffic congestion. This paper proposes a clustering-based approach to identify urban logistics nodes from the perspective of geographic information fusion. This method comprehensively considers several key indicators, including the coverage, balance, and urban traffic conditions of logistics distribution. Additionally, we employed a greedy algorithm to identify secondary nodes around primary nodes, thus constructing an effective nodal network. To verify the practicality of this model, we conducted an empirical simulation study using the logistics demand and traffic conditions in the Xianlin District of Nanjing. This research not only identified the locations of primary and secondary logistics nodes but also provided a new perspective for constructing the urban last-mile logistics system, enriching the academic research related to logistics node construction. The results of this study are of significant theoretical and practical importance for optimizing urban logistics networks, enhancing logistics efficiency, and promoting the improvement of urban traffic conditions.

To enhance the performance of visual SLAM in underwater environments, this paper presents an enhanced front-end method based on visual feature enhancement. The method comprises three modules aimed at optimizing and improving the matching capability of visual features from different perspectives. Firstly, to address issues related to insufficient underwater illumination and uneven distribution of artificial light sources, a brightness consistency recovery method is pro-posed. This method employs an adaptive histogram equalization algorithm to balance the brightness of images. Secondly, a method for denoising underwater suspended particulates is introduced to filter out noise from the images. After image-level processing, a combined underwater acousto-optic feature association method is proposed, which associates acoustic features from sonar with visual features, thereby providing distance information for the visual features. Finally, utilizing the AFRL dataset, the improved system incorporating the proposed enhancement methods is evaluated for performance against the OKVIS framework. The system achieves better trajectory estimation accuracy compared to OKVIS and demonstrates robustness in underwater environments.

Due to growing environmental concerns and stringent emissions regulations, optimizing the fuel consumption of marine propulsion systems is crucial. This work deals with the potential in an LNG ship propulsion system to reduce fuel consumption through controlled load distribution between engines in Dual Fuel Diesel Electric (DFDE) plant. Based on cyclical data acquisitioning measured on board and using an optimization model, the study evaluates different load distribution strategies between set up according to the optimization model results and automatic (equal) operation to determine their effectiveness in improving fuel efficiency. The analysis includes scenarios with different fuel types, including LNG, MDO and HFO, at different engine loads. The results indicate that load distribution adjustment based on the optimization model results significantly improves fuel efficiency compared to conventional methods of uniform load distribution controlled by power management systems almost in all load intervals. This research contributes to the maritime industry by demonstrating that strategic load management can achieve significant fuel savings and reduce environmental impact, which is in line with global sustainability goals. This work not only provides a framework for the implementation of more efficient energy management systems on LNG vessels, but also sets a benchmark for future innovations in maritime energy optimization as well as in the view of exhaust emission reduction.

The implementation of Emissions Trading System (ETS) poses significant challenges for the Indian maritime sector. This paper investigates the regulatory implications of ETS, focusing on how these regulations impact compliance and operational practices within the Indian shipping sector. It also analyzes the economic effects, including the financial burden and competitive dynamics faced by the Indian shipping companies in a global context. Additionally, the paper explores various adaptation strategies, emphasizing technological innovations and operational adjustments essential for navigating ETS requirements. By integrating recent industry data and case studies, this study offers a comprehensive overview of how the Indian shipping industry can effectively address the evolving regulatory landscape of ETS.

This study examines the environmental challenges faced by Malaysian industries in adhering to industrial effluent regulations with the research question, what are the challenges in complying with environmental legislations from industries? It investigates the primary factors contributing to non-compliance and the perspectives, knowledge, and needs of Malaysian industries regarding environmental compliance. This study recommends the best strategy for promoting self-compliance. Thirteen stakeholders from various industries with environmental management experience were interviewed. Over the past seven years, these industries have shown low com-pliance with the Industrial Effluent Regulation 2009, prompting an exploration of their adaptability to regulations. Challenges identified include cost, employee attitudes, technology, management support, public complaints, and jurisdictional issues. Responses varied from divergent to unified viewpoints, highlighting the complexity of compliance issues. Respondents suggested enhancing compliance through behavioral changes, including incentives, enforcement, awareness, guidance, industry ratings, management commitment, and public disclosure of emissions. Suggestions for improvement and innovative solutions emerged based on participants' experiences, emphasizing the importance of continuous improvement. The study emphasizes the government's crucial role in ensuring regulation adherence but underscores the need for analyzing barriers and exploring alternative approaches. Understanding industry perspectives and strategies is essential for progress. Compliance, however, requires an analysis of the current challenges and adopting adaptive measures. It is important to understand industries' perspectives and strategies to move forward.

A sustainable low cost activated carbon substitute was produced based on pretreated lignocellulosic biomass, especially spruce sawdust. A harmful liquid waste, desalination brine was used for the treatment of a solid wood industry waste, spruce sawdust. This approach is in the circular economy theory and aims to the decarbonization of the economy. The pretreated sawdust was tested as an adsorbent appropriate for the removal of a commonly used pollutant, methylene blue, from industrial wastewater. The adsorption capacity of the pretreated material was found to increased four times comparing to the untreated one in the case that the Freundlich equation was fitted to the isotherms’ data. The treatment experimental conditions with desalination brine that gave maximum adsorption capacity correspond to 1.97 combined severity factor in logarithmic form value. The same adsorption capacity was found to increase five to six times comparing to the untreated spruce sawdust in the case that the Langmuir isotherm model was applied at the same data. Moreover, kinetic experiment was cried out as regards the methylene blue adsorption process. The desalination brine pretreated sawdust adsorption capacity increased 1.4 times comparing to the untreated one, in the case of the Lagergren kinetic equation fitting. Furthermore, the adsorption capacity of the same material was increased 1.6 times when the second order kinetic model was applied to the same data. Industrial scale applications can be based on the kinetic data findings as they have to do with a very shorter adsorption period comparing to the isotherm data.

The introduction of Maritime Autonomous Surface Ship (MASS) through the development of autonomous navigation technologies is expected to bring about new technologies, new vessel types, and new job roles such as remote operation center (ROC) and remote operator (RO). The MASS Code are currently being discussed through Maritime Safety Committee (MSC) of International Maritime Organization (IMO). This code is expected to be adopted in the form of non-mandatory guidelines until 2025, with the goal of establishing mandatory requirements by 2028. Additionally, revisions to the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW) related to crew training and qualifications are planned for adoption by 2027, which will include requirements for MASS operators. This paper aims to examine the fundamental competencies required for safe MASS operation by remote operators using the Analytic Hierarchy Process (AHP) method, considering the emergence of the new profession of RO. Building upon the 66 Knowledge, Understanding & Proficiencies (KUPs) outlined for marine officer in the STCW Convention, the study seeks to identify the additional competencies necessary for RO and contribute to the development of a training model for the future.

Planning regulations determine a substantial part of buildings but their constraints are usually not included in the setup of a BIM model or used explicitly for design guidance. This is symptomatic of wider tendencies and ingrained biases that emphasize tacit knowledge and assume that information in a project starts from scratch – an assumption that runs contrary to predesign information ordering practices, as well as to the findings of creativity studies. In terms of process control, it negates important possibilities for feedforward. The paper describes an exercise in which students collected planning regulations for a particular plot of land and modelled their constraints in BIM. The results suggest that converting such information into a foundation for design is constructive and feasible, even for novices, and produce a bandwidth view of project information that acknowledges pre-existing information and includes it in the BIM workflow. They also verify that, for a large part of Dutch housing, this foundation amounts to a considerable and binding part of the design that guides subsequent decisions.

Maritime data not only identify financial resources that can significantly enhance the efficiency of shipping companies but also play a pivotal role in promoting eco-friendly and sustainable shipping practices. However, active corporate strategies are required to include maritime data essential for the commercial operation of autonomous ships in the form of corporate assets by transparent evaluating the data. The aim of this study is to review previous studies on da-ta-valuation models, identify a valuation model suitable for maritime business, consider the characteristics of maritime data. The analytic hierarchy process (AHP) method is used to derive priorities for valuing maritime data assets, with emphasis placed on the characteristics of mari-time data, followed by the character of the future-oriented maritime-data market and the da-ta-valuation model. The results obtained that the most important factors in selecting a maritime data-valuation model by analyzing the AHP method were identified as the characteristics of the maritime data(M1). The next most important factors analyzed were the features of the mari-time-data market(M2) and the features of the maritime data-valuation model(M3) in order. In addition, the characteristics of maritime data were preferentially considered among the main criteria, and the market approach (A2) was selected as the most optimal valuation model. The potential impact of this implementation could contribute to the establishment of an intelligent technology market by estimating the value of data and developing a platform for maritime data trading, allowing for more efficient data sharing and utilization by maritime autonomous sur-face ship(MASS).

Maritime transport has adapted to recent political and economic shifts by addressing stringent pollution reduction requirements, redrawing transport routes for safety, reducing onboard technical incidents, managing data security risks and transitioning to autonomous vessels. The integration of AI-based technologies for fault diagnosis and decision-making, coupled with proper personnel training, has become essential for optimal ship operation, with AI-assisted predictive maintenance emerging as the key strategy to ensure onboard systems function within desired parameters and enhance equipment availability. This study proposes a machine-learning algorithm for evaluating onboard systems performance by analyzing sensor data and mapping it to fault patterns to estimate functional states, validated through tests on a seawater cooling system from an oil tanker, demonstrating operational efficiency and reliability. The immediate advantage is reduced time for fault diagnosis by rapidly assessing the system using operational data, the algorithm enabling real-time monitoring and fault data management to minimize efforts as part of predictive maintenance assisted by machine learning tools.

As a new plant slope protection technology, living stumps can effectively improve slope stability. The current study attemptes to investigate the mechanical characteristics of the root system of living stumps and their reinforcement mechanism on slopes by carrying out a three-dimensional living stump slope modeling test. Using ABS materials, a 3D model of a living elm stump was created by 3D printing and a slope model test was carried out. The reinforcement mechanism of the living stump was studied through a combination of model testing and numerical simulation. The results indicate that, due to the presence of living stumps in the lower and middle parts of the slope, the maximum shear stress area of the soil moved to a deeper direction. The stress state of the soil around the living stump was effectively improved due to the existence of the lateral root system.Living stumps in the lower part of the slope cross the potential sliding surface and transferred the soil shear stress gradually to the root system through root-soil interaction. Moreover, the tap roots and lateral roots of living stumps form a robust spatial structure that bears the shear stress of soil together, thus increasing the stability of the slope.

Tropical regions face significant energy challenges due to climatic conditions. This study investigates the interplay between sustainable architecture and building energy regulations in mitigating these challenges. The study aims to assess the effectiveness of existing building energy regulations in promoting sustainable architecture in tropical climates and identify key architectural strategies and regulatory frameworks for optimizing energy efficiency in tropical buildings. A comparative analysis of building regulations and case studies of sustainable buildings in selected tropical regions is conducted. The findings reveal that current regulations often must be revised to address tropical climates' unique energy demands. Incorporating passive design principles, renewable energy systems, and material selection is crucial for energy efficiency. It is recommended that building energy regulations be strengthened to mandate sustainable design strategies and provide incentives to promote the adoption of energy-efficient technologies.

Tropical regions face unique challenges in building sustainability due to high temperatures, humidity, and heavy rainfall. While building energy regulations are essential for promoting energy efficiency, their effectiveness in addressing tropical climate conditions needs to be studied more. This research aims to systematically investigate tropical building sustainability issues and evaluate the impacts of building energy regulations on these challenges. The study will identify gaps in current regulations by analyzing existing research and recommend strategies for developing more comprehensive frameworks that promote sustainable building practices in tropical regions. This research contributes to developing effective policies and strategies for achieving sustainable and energy-efficient built environments in tropical climates.

Following technological advances, autonomous and remote-controlled ships are performing trials in some sea areas; a mandatory goal-based MASS code, expected to enter into force on 1 January 2032, is under discussion in the International Maritime Organization (IMO). However, there are no unified standards regarding verification methods to define operating limitations for cutting-edge technologies, which are expected to be elements of MASS, so it is difficult to assess the risk factors for the management and operation of MASS. This paper outlines the regulatory framework for MASS, followed by a discussion of its application, considering the differences between MASS and automated driving, and how to develop safety management and operation using standards for automated driving. A requirements management framework developed as a system and software engineering standards to build safety management and operation of MASS is proposed. It is also suggested that the requirements management framework could be used not only for MASS development but also for regulatory review from a requirements management view.

The implementation of cybersecurity standards and directives in the maritime sector plays a crucial role in protecting critical maritime infrastructures from cyber threats. The level of protection depends heavily on humans. However, the effectiveness of cybersecurity training and compliance programs, an essential component of these standards, is often hindered by challenges related to the sector’s environment, including the established technologies, practices, and norms. This paper aims to identify these challenges through a literature review and set the basis for more effective human risk minimisation, responses, and training. We identify 18 challenges and validate them with an online survey (N=205) capturing real-world perspectives from maritime-related stakeholders. Our findings contribute to enhancing the effectiveness of maritime cybersecurity training and compliance programs, ultimately strengthening the maritime cybersecurity posture.

The transportation sector significantly contributes to greenhouse gas emissions, thus imposing sig-nificant environmental hazards. In response, many nations have begun promoting Electric Vehicles (EVs) as an ecologically sustainable substitute for traditional combustion vehicles. Lithium-Ion Batteries (LIBs), characterized by their high energy density, extended lifespan, and relatively low self-discharge rate, have become the suitable energy storage system for EVs, advancing the field of sustainable transportation. The decreasing cost of LIB production has primarily driven this progression, realized through a combination of economies of scale, advancements in electrode materials and cell design, and re-finements in manufacturing processes. All these elements collectively contribute to the cost reduc-tion of LIBs. A foreseeable implication of this trend is an expected surge in LIBs that will exhaust their operational lifespan and, consequently, be cast away into the environment. One mitigating strategy for this impending environmental issue involves collecting these spent EV batteries, re-configuring them, and repurposing them for applications with less rigorous weight, performance, and size prerequisites. This approach would not only prolong the utility life of the batteries but also ameliorate their environmental impacts. Nevertheless, second-life batteries are anticipated to exhibit a higher rate of gas evolution, necessitating comprehensive testing and readjustments to ensure safe operation in secondary ap-plications. The regulatory framework encompassing the second-life battery sector still needs to be defined regarding norms, technical standards, and legislation. This paper aims to elucidate the primary regulations and technical standards proposed thus far in the second-life battery marketplace. The results underscore the exigency for neutral evaluative entities, such as universities, research centers, and governmental institutions, to perform an unbi-ased assessment of the second-life battery market. This would pave the way for novel technical standards and legislative measures specifically tailored to this emerging sector.

When it comes to air pollution complaints, odours are often the most significant contributor. Sources of odour emissions range from natural to anthropogenic. Mitigation of odour can be challenging, multifaceted, site-specific, and is often confounded by its complexity—defined by existing (or non-existing) environmental laws, public ordinances, and socio-economic considerations. The objective of this paper is to review and summarize odour legislation in selected European countries (France, Germany, Austria, Hungary, United Kingdom, Spain, The Netherlands, Italy, Belgium), North America (USA and Canada), South America (Chile and Colombia), as well as Oceania (Australia and New Zealand) and Asia (Japan, China). Many countries have incorporated odour controls into their legislation. However, odour-related assessment criteria tend to be highly variable between countries, individual states, provinces and even counties and towns. Legislation ranges from (1) no specific mention in environmental legislation that regulates pollutants which are known to have an odour impact to (2) extensive details about odour source testing, odour dispersion modeling, ambient odour monitoring, (3) setback distances, (4) process operations, and (5) odour control technologies and procedures. Agricultural operations are one specific source of odour emissions in rural and suburban areas and a model example of such complexities. Management of agricultural odour emissions is important because of the dense consolidation of animal feeding operations and the advance of housing development into rural areas. Overall, there is a need for continued survey, review, development, and adjustment of odour legislation that considers sustainable development, environmental stewardship, and socio-economic realities, all of which are amenable to a just, site-specific, and sector-specific application.

Thermaikos Gulf (TG) is a semi-enclosed, river-influenced, marine system situated in the eastern Mediterranean Sea, sustaining both urban coastal regions and ecologically preserved natural areas. Facing a plethora of environmental and anthropogenic pressures, the TG serves as a critical nexus where human activities intersect with marine ecosystems. The second largest city of Greece, Thessaloniki, is located in the northern part of the gulf, while a large environmentally protected zone with multiple river deltas is lying along its western coasts. The quality and health of the TG’s marine environment are tightly linked to the socioeconomic activities of the coastal communities comprising approximately 1.5 million inhabitants. The main features of TG’s environmental dynamics and ecological status have been scrutinized by dedicated research endeavours during the last 50 years. This review synthesizes the seminal findings of these investigations, offering an evaluation of their contribution to research, their present collective impact, and their trajectory toward the future. A severe deterioration of the TG’s environmental quality was detected in the 1970s and 1980s when treatment of urban wastewater was completely absent. A steady trend of recovery was observed after the 1990s, however without achieving, so far, the goal of a “good environmental state”, mandated by national legislation and European directives. The most important research gaps and uncertainties are also discussed and specific recommendations for the improvement of monitoring and understanding about the physical, biochemical, and ecological state of the gulf are provided. The most significant discrepancy is related to the fragmentary monitoring of the TG in both space (partial coverage) and time (temporal gaps), which has been intensified after 2010 due to the reduced funding for environmental research and protection under the severe Greek economic recession. This review aspires to highlight the importance of bolstering monitoring initiatives that can provide continuous observations and further understanding on the TG's ecological and physicochemical conditions. Targeted recommendations, aimed at ameliorating the fragmented monitoring processes, are also provided, advocating for a holistic approach that can safeguard the ecological integrity of the Thermaikos Gulf and uphold its role as a crucial link to marine biodiversity and sustainability in the Mediterranean basin.

AI is extraordinarily useful technology but it is becoming increasingly powerful with rapidly growing capabilities to disrupt and harm human society. We call on international and national organizations and individuals to join forces in banning the development of superintelligent AI and introducing regulations to prevent and mitigate AI-caused harm.

The years 2021 and 2022 showed that maritime logistics are prone to interruptions. Especially the ports turned out to be bottlenecks with long queues of waiting vessels. This leads to the question of whether this can be (at least partly) mitigated by means of better and more flexible terminal operations. Digital Twins have been in use in production and logistics to increase flexibility in operations and are considered a reasonable fit. They are suitable for real-time data integration to support decision-making. However, the true potential of Digital Twins to enhance terminal operations still needs to be further investigated. A Delphi study is conducted to explore operational pain points, best practices to counter them, and how these best practices can be supported by Digital Twins. A questionnaire with 16 propositions is developed, and a panel of 17 experts is asked for their degrees of confirmation for each. The results indicate that today’s terminal operations are far from ideal and leave space for optimisation. The experts see great potential in analysing past working shifts data to identify reasons for poor terminal performance. Moreover, they agree on the proposed best practices and support the use of aiding IT solutions.

ABSTRACT After locavore was chosen as “the best word of the year” in 2007, its popularity increased gradually. Today great number of locavores consciously prefer locally produced food for the benefit of themselves and their community. Undoubtedly this conscious movement has its consequences in marketing discipline. Accordingly, this paper is purposed to examine the how locavore perceptions affect loyalty towards retailers that sell locally produced food. In this context, a survey was applied to people residing in Istanbul and Kocaeli districts to measure the robustness of these effects. Furthermore, attitude towards locavore is used as a control variable to reveal to what extend locavorism affects these proposed connections. According to results, for participants with low attitude, Social Responsibility and Health Consciousness variables have significant effect on local retailer shopping loyalty. However, for participants with high attitude, all independent variables proved to have substantial effect on local retailer shopping loyalty. As the first empirical study in Turkey on the subject, this paper will provide important insight to academia and practicioners due to today’s ever-increasing consciousness in green marketing.

In this paper, a new method is proposed to detect traffic regulations at intersections using GPS traces. The knowledge of traffic rules of regulated locations can help various location-based applications in the context of Smart Cities, such as the accurate estimation of travel time and fuel consumption from a starting point to a destination. Traffic regulations as map features, however, are surprisingly still largely absent from maps, although they do affect traffic flow which in turn affects vehicle idling time at intersections, fuel consumption, CO_2 emissions and arrival time. In addition, mapping them using surveying equipment is costly and any update process has severe time constraints. This fact is precisely the motivation for this study. Therefore, its objective is to propose an automatic, fast, scalable and inexpensive way to identify the type of intersection control (e.g. traffic lights, stop signs). A new method based on summarizing the collective behavior of vehicles crossing intersections is proposed. A modification of a well-known clustering algorithm for detecting stopping and decelerating events is presented. These detected events are then used to categorize vehicle crossing of intersections into four possible traffic categories (p1: free flow, p2: deceleration without stopping events, p3: only one stopping event, p4: more than one stopping event). The percentages of crossings of each class per junction arm, together with other speed/stop/deceleration features, extracted from trajectories, are then used as features to classify the junction arms according to their traffic control type dynamic model). The classification results of the dynamic model are compared with those of the static model, where the classification features are extracted from OpenStreetMap. Finally, a hybrid model is also tested, where a combination of dynamic and static features is used, which outperforms the other two models. For each of the three models, two variants of the feature vector are tested: one where only features associated with a single junction arm are used (one-arm model) and another where features also from neighbouring junction arms of the same junction are used to classify an arm (all-arm model). The methodology was tested on three datasets and the results show that all-arm models perform better than single-arm models with an accuracy of 94\% to 97\%.

The inappropriate use of pesticides in the world and particularly in Africa, explains their presence in various environmental compartments. This presence in the environment has harmful consequences on living beings, especially humans. This review, based on scientific publications, aims to analyze the problem of pesticides in Africa. From a corpus of 81 articles published in Africa on this topic between 1996 and 2019, we have outlined the issues relating to phytosanitary practices, environmental pollution, food contamination, intoxication of farmers and consumers, qualitative and quantitative analysis methods used, as well as the regulations on the subject and their application in Africa. Based on an analysis of the factors that are at the root of the problems of environmental pollution, contamination and health that they cause in Africa, possible solutions were proposed to produce healthy products and preserve our common environmental heritage.

This study investigates the impact of AI regulations and adoption on labor markets and employment in the USA. In order to achieve the study's objective, a robust econometric approach was employed using Principal Components Analysis (PCA) to address multicollinearity among the variables. The regression analysis incorporated principal components representing overall AI adoption and education (PC1), AI innovation and academic output (PC2), economic growth (PC3), and unemployment and AI strategies (PC4). The analysis utilized heteroskedasticity-robust standard errors to ensure reliable coefficient estimates and tested for stationarity to confirm the stability of the time series data. Data were collected from 2010 to 2022, encompassing key AI-related and economic indicators. The results reveal that higher AI adoption and education levels initially lead to job displacement, negatively impacting labor market metrics. Similarly, AI innovation and economic growth driven by AI do not immediately translate into job creation, reflecting transitional challenges. However, the strategic implementation of AI significantly mitigates these adverse effects and enhances employment conditions. The study finds that comprehensive AI strategies, robust regulatory frameworks, and effective workforce retraining and upskilling programs are essential for supporting labor market stability and promoting employment growth. Based on the findings, the study recommended that there is the need to develop and implement comprehensive AI strategies that include robust regulatory frameworks to support workforce transitions. Policies should focus on retraining and upskilling programs to help displaced workers adapt to new AI-driven roles.

This research examines the overtopping volumes associated with focused wave groups on smooth dikes with an emerged toe. Focused wave groups are employed to represent the highest waves of random sea states in a compact form, obviating the need to model the entire irregular wave train. The study investigates how overtopping volumes are affected by focus location and phase. Results from 418 experimental tests have been gathered and analyzed. The experiments employed first-order wave generation theory to analyse structural response. Subsequent studies will address the errors induced by this approximation and compare it with second-order wave generation. The experiments simulated extreme wave impacts on an idealised coastal layout, comprising a 1:6.3 foreshore slope and three different dike slopes, including vertical structures, with the initial still water level set below the dike toe. The study employed NewWave theory for generating focused wave groups, aiming to extend recent research on wave overtopping under varied conditions. The results, analysed in both dimensional and non-dimensional forms, indicate that overtopping volumes are significantly influenced by the focus phase. Critical focus locations were identified at a distance of one-third of the deep-water wavelength from the toe.

This paper examines hybrid threats to maritime transportation systems, and their governance re-sponses; focusing on the congested Straits of Malacca and Singapore (SOMS) as an illustrative case study. The methodology combines secondary sources with primary data from 42 expert in-terviews, a 30-respondent survey, and two maritime security roundtables. Key findings were that ships’ critical systems are increasingly interconnected, yet aging IT infrastructure and minimal cybersecurity awareness among crews heighten risks. Meanwhile, regional terrorist groups have previously targeted shipping and shown considerable skill in exploiting online tools, aligning with broader calls for jihadist violence. Further, opportunistic piracy persists in the SOMS with the po-tential to disrupt shipping. Experts confirmed maritime cybersecurity lags other critical infra-structure sectors and needs updated governance. Initial International Maritime Organization (IMO) guidelines lack specificity but revisions and updated IMO guidance are in process, while Port state implementation of maritime cybersecurity standards varies. Crucially, information sharing remains inadequate, even as recorded attacks increase. Findings underscore that although major hybrid incidents have not occurred, simulations and threat actors’ capabilities demonstrate potential for catastrophic collisions or cascading disruption in congested waterways. Mitigating factors like redundancy and crew training are deficient currently. Some alignment between SOMS states on maritime security cooperation exists, but not cyber threats specifically. Key recommen-dations include an anonymous cyber-attack reporting system, reinforced training and shipboard systems, and consolidated regional frameworks. Until these priorities are addressed, the analysis concludes that hybrid vulnerabilities in this vital global chokepoint remain a serious concern.

The rise of the Internet of Things (IoT) has opened up exciting possibilities for new applications. One such novel application is the modernization of maritime communications. Effective maritime communication is vital for ensuring the safety of crew members, vessels, and cargo. The maritime industry is responsible for the transportation of a significant portion of global trade, and as such, the efficient and secure transfer of information is essential to maintain the flow of goods and services. With the increasing complexity of maritime operations, technological advancements such as unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs), and the Internet of Ships (IoS) have been introduced to enhance communication and operational efficiency. However, these technologies also bring new challenges in terms of security and network management. Compromised IT systems, with escalated privileges, can potentially enable easy and ready access to operational technology (OT) systems and networks with the same privileges, with an increased risk of zero-day attacks. In this paper, we first provide a review of the current state and modalities of maritime communications. We then review the current adoption of Software-Defined Radios (SDRs) and Software-Defined Networks (SDNs) in the maritime industry and evaluate their impact, as IoT enablers, on the future of maritime industry operations, safety, and security.

C-terminal Src kinase (CSK) is the major inhibitory kinase for Src family kinases (SFKs) through phosphorylation of their C-tail tyrosine site, and regulates various cellular activities in association with SFKs functions. As a cytoplasmic protein, CSK need be recruited to the plasma membrane to regulate SFKs activities. The regulatory mechanism for CSK activity and its subcellular localization remains largely unclear. In this work, we developed a genetically encoded biosensor based on fluorescence resonance energy transfer (FRET) to visualize CSK activity in live cells. The biosensor with optimized substrate peptide confirmed crucial Arg107 site in CSK SH2 domain, and displayed sensitivity and specificity to CSK activity while little responses to co-transfected Src and Fyn. FRET measurements showed CSK having relatively mild level of kinase activity in comparison to Src and Fyn ones in rat airway smooth muscle cells. The biosensor tagged with different submembrane-targeting signals detected CSK activity at both non-lipid raft and lipid raft microregions, while showed higher FRET level at non-lipid ones. Co-transfected receptor-type protein tyrosine phosphatase alpha (PTPα) had inhibitory effect on the CSK FRET response. The biosensor didn’t detect obvious changes of CSK activity between metastatic cancer cells and normal ones. In conclusion, a novel FRET biosensor was generated to monitor CSK activity, and demonstrated CSK activity existing in both non-lipid and lipid raft membrane microregions while more present at non-lipid ones.

Mature B cells notably diversify immunoglobulin (Ig) production through class switch recombination (CSR), allowing the junction of distant “switch” (S) regions. CSR is initiated by activation-induced deaminase (AID) which targets cytosines adequately exposed within single-stranded DNA of transcribed targeted S regions, with a specific affinity for WRCY motifs. In mammals, G-rich sequences are additionally present in S regions, forming canonical G-quadruplexes (G4s) DNA structures which favor CSR. Small molecules interacting with G4-DNA (G4 ligands), proved able to regulate CSR in B lymphocytes, either positively (such as for nucleoside diphosphate kinase isoforms) or negatively (such as for RHPS4). G4-DNA is also implicated in the control of transcription, and due to their impact on both CSR and transcriptional regulation, G4-rich sequences likely play a role in the natural history of B cell malignancies. Since G4-DNA stands at multiple locations in the genome, and notably within oncogene promoters, it remains to be clarified how it can more specifically promote legitimate CSR in physiology, rather than pathogenic translocation. The specific regulatory role of G4 structures in transcribed DNA and/or in corresponding transcripts and recombination hereby appears as a major issue for understanding immune responses and lymphomagenesis.

This paper studies the flexural behavior of the bridge deck link slabs made with the Polyvinyl Alcohol-Strain Hardening Cementitious Composites (PVA-SHCC). Tensile and flexural properties of the PVA-SHCC with four volume fractions, i.e., 0%, 1%, 1.5%, and 2%, were evaluated first. Next, using the similarity theory, composite models with a geometric similarity ratio of 1: 5 were designed to represent the bridge deck with the link slabs. The models considered three materials for link slabs, including concrete, cement mortar and self-compacting PVA-SHCC; and two different curing ages at 7 and 56 days. Bending tests were performed to investigate the flexural behavior of the models. Based on the fractal theory, cracking characteristics of the models with different types of link slabs were compared, and the relationship between Df and the flexural behavior of the models were studied. Numerical models were built to correlate with the results from the bending tests. It is illustrated that the flexural behavior of the self-compacting PVA-SHCC link slab is better than that of concrete and cement mortar link slabs, where the crack initiation and propagation can be postponed.

this paper focuses on a scientific study of the restoration, rehabilitation and reuse of the great throne hall, the most important hall in al-jawhara palace. it also aims to study the most important factors and forces of damage that affected the great throne hall, natural, biological, and human, and the resulting damage. field tests were performed, laboratory tests to determine fracture stress, liquidity and spandex limits tests, chemical analysis on soil samples and geoelectrical testing of the soil, and the results did not show caves or voids in the ground until a depth of 10.00 m, construc-tion materials were studied and tested using x-ray, (xrd), mechanical tests (tensile, shear, com-pression), and a study of the effect of seismic loads on the walls; the results showed horizontal and vertical cracks; based on the study and analysis of these cracks, it was possible to present modern techniques in restoration and reinforcement methods, and in conclusion, the researcher's recommendations.

This study investigates the influence of adding hydrogen as an additive to gasoline in a four-stroke engine, utilizing a comprehensive thermodynamic comparative analysis conducted with self-developed engine model. The research aims to assess the performance, emissions, and efficiency of the engine when using gasoline-hydrogen blends, and to provide insights into the potential benefits of this approach. First the engine performance and emissions under different hydrogen blending levels were examined. A range of different air-to-fuel ratios (rich to lean) and varying percentages of hydrogen were considered. This systematic variation allowed for a detailed evaluation of the influence of hydrogen content on combustion efficiency, power out-put, and emissions characteristics. The analysis results included key parameters such as indicated specific fuel consumption and mean effective pressure. Additionally, the study focused on range prediction of nitrogen oxides (NOx) emissions, which are a critical environmental concern asso-ciated with internal combustion engines. The analysis of pressure and temperature profiles throughout the engine cycle shed light on the combustion characteristics and efficiency im-provements associated with hydrogen addition. In terms of emissions, the study projected that all emissions were reduced except NOx, which is highly dependent on hydrogen percentage, and it might be reduced in some cases, but with higher temperatures and pressures associated with hydrogen addition in most cases there is actually NOx increase, especially at higher engine loads.

The task of automatically and intelligently diagnosing faults in marine equipment is of great significance due to the numerous duties that shipboard professionals must handle. Incorporating automated and intelligent systems on ships allows for more efficient equipment monitoring and better decision-making. This approach has attracted considerable interest in both academia and industry because of its potential for economic savings and improved safety. Several fault diagnosis methods are documented in the literature, often involving mathematical and control theory models. However, due to the inherent complexity of some processes, not all characteristics are precisely known, making mathematical modeling highly challenging. As a result, fault diagnosis often depends on data or heuristic information. Fuzzy logic theory is particularly well-suited for processing this type of information. Therefore, this paper employs fuzzy models to diagnose faults in a marine pneumatic servo-actuated valve. The proposed fault diagnosis framework analyzes the discrepancy signals between the outputs of the fuzzy models and the actual process outputs. These discrepancies, known as residuals, help in detecting and isolating equipment faults. The fault isolation process uses an intelligent decision-making approach to determine the specific fault in the system. This method is applied to diagnose abrupt faults in a marine pneumatic servo-actuated valve.

Maritime surveillance technology faces challenges of astronomical size in this vast ocean world—challenges vital to global security and environmental protection alike. Such as these may be reversible or not. Remotely sensed monitoring also uses photos taken from satellites, synthetic aperture radar (SAR) equipment, and unmanned aerial vehicles (UAVs) to fully monitor maritime activities but also ferret out suspicious behaviour like piracy, bootleg shipments, and illegal fishing. This mixed-method approach--quantitatively and qualitatively——measures the efficiency of difficulties associated with, and legal implications behind aerospace-monitored maritime surveillance. The results show that remote sensing provides a great deal of sea-level situational awareness; however, there are also many complex technical, operational, and legal issues, including information overcrowding, complications in integration, privacy issues, as well as the need for worldwide legal harmonisation. It ends with recommendations on ways to ultimately increase capacity, how to write standard procedures for secondary development and proposals for revising laws to absorb these new technologies. Its goal, therefore, is to benefit the global anti-maritime crime effort. Ultimately, though, it dreams that we might construct an entirely marine environment where all marine activities are conducted both safely and freely, without fear.

Using the culture-work-health model, this study investigates the factors influencing the quality of life of maritime workers. This study conducted a survey of 320 maritime workers who have experience living and working on a ship for more than six months. This self-administered questionnaire included questions on organizational culture and support, self-efficacy, perceived fatigue, as well as the quality of work life. Organizational culture and self-efficacy were identified as factors affecting the quality of work life, while organizational support was found to have an indirect effect after passing through self-efficacy and perceived fatigue. The final model accounts for 63.1% of the variance in maritime workers’ quality of life. As such, this study shows that self-efficacy is important for the quality of life of maritime workers, having both direct and indirect effects. Moreover, organizational support may prove the primary intervention point for relieving perceived fatigue and enhancing self-efficacy, thus improving the quality of work life.

In the evolving landscape of digital marketing, cross-channel attribution modeling plays a crucial role in understanding and optimizing the customer journey across various touchpoints. As consumers interact with brands through multiple channels—such as social media, email, search engines, and display ads—accurately attributing conversions to the right channels is vital for optimizing marketing strategies and budgets. However, the advent of stringent privacy regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), has significantly impacted the data collection and analysis processes in digital marketing. This paper explores the challenges and opportunities presented by cross-channel attribution modeling in the age of heightened privacy awareness. It examines how traditional data-driven attribution models, which often rely on tracking individual user behavior, are being adapted or replaced in response to privacy concerns and regulatory requirements. The paper discusses the emergence of privacy-preserving techniques, such as aggregated data analysis, differential privacy, and the use of anonymized data, which aim to balance the need for accurate attribution with the protection of consumer privacy. Furthermore, the paper highlights the role of first-party data and the growing importance of consent management in the collection and utilization of consumer information. It also investigates how marketers are leveraging advancements in artificial intelligence and machine learning to enhance attribution models in a privacy-conscious world. The study concludes by offering best practices for businesses seeking to navigate the complexities of cross-channel attribution in the context of evolving privacy regulations, emphasizing the need for transparency, compliance, and ethical data handling. This research provides valuable insights for marketers, data scientists, and policymakers on how to effectively manage the interplay between accurate attribution and privacy, ensuring that marketing efforts remain effective while respecting consumer rights.

Drinking water, in addition to the best-known chemical and biological agents, contains radionuclides of both natural and artificial origin, which can contribute significantly to the overall effective dose received by the population. The Italian Decree Law 28/2016, implementing 2013/51/EURATOM Directive, establishes the activities for risk management and the parameter values for different radionuclides activity concentrations. In addition to the institutions involved, annually the National Inspectorate for Nuclear Safety and Radiation Protection (ISIN), publishes the monitoring reports of environmental radioactivity in Italy, including radioactivity in drinking water. The purpose of the study was to integrate ISIN reports with 2018 to 2020 data by collecting measurements performed by institutional laboratories to obtain a more complete information and adding, for the Campania region, some data not yet published. This new updated report was not significantly different from ISIN’s one, meaning that those publications are nevertheless extremely representative of the radioactivity in Italian drinking water. However, the study allowed to obtain a more detailed data also including measurements not considered in ISIN reports, for instance, radon-222 activity concentrations. This may be of great usefulness for all radiation protection stakeholders in order to ensure environmental protection, pollution prevention and the population safety.

Oil floating on the sea surface can be detected by both passive and active methods using the ultraviolet-to-microwave spectrum, whereas oil immersed below the sea surface can signal its presence only in visible light. This paper presents an optical model of a sea area deeply polluted by an oil suspension (10 ppm) located in a layer (thickness 5 m) separated from the sea surface by a clear layer (thickness 1 m). The impact of wavelength and state of the sea surface on reflectance changes is shown based on the results of Monte Carlo ray tracing. A two-wavelength index of reflectance is proposed to detect oil suspended in the water column (645-469 nm).

Unmanned Underwater Vehicles (UUVs) are pivotal in ocean exploration, research, and various industrial activities such as marine mining and offshore engineering. However, traditional methods of navigating these vehicles face significant challenges, mainly due to the inefficacy of electromagnetic waves in water, leading to signal loss. To address these limitations, researchers are increasingly turned learning, an artificial intelligence technique capable of learning from data-enhancing underwater navigation, mainly through visual Simultaneous Localization and Mapping (SLAM). This paper explores integrating deep learning methodologies and sensor technologies to revolutionize underwater navigation for UUVs. Proprioceptive sensors, along with exteroceptive sensors, are crucial in accurately measuring and comprehending the underwater environment. Additionally, the paper provides detailed insights into the processes of underwater SLAM, camera-based underwater positioning systems, sonar systems for underwater navigation, and the utilization of Lidar in underwater navigation. Furthermore, it delves into applying deep learning techniques in underwater SLAM, offering a comprehensive understanding of the innovative processes driving advancements in underwater vehicle navigation. By leveraging these advancements, this research aims to improve underwater navigation systems' precision, reliability, and adaptability, thereby unlocking new frontiers in ocean exploration and industrial applications for UUVs.

This paper presents a scenario evolution model for maritime accidents using Bayesian networks (BN) to predict the most likely causes of specific types of maritime incidents. The BN nodes encompass accident type, life loss contingency, accident severity, the quarter and time period of the accident, and the type and gross tonnage of the ships involved. We analyzed 5,660 global maritime accidents from 2005 to 2020. Using Netica software, we constructed a Tree Augmented Network (TAN) model, accounting for interdependencies among risk influencing factors. We validated the results through sensitivity analysis and historical accident records. Forward causal inference and reverse diagnostic inference were then performed on each node variable to investigate the accident development trend and evolution process under predetermined conditions. The findings indicate that the model can effectively predict the likelihood of various accident scenarios under specific conditions, as well as the extrapolation of accident consequences. Forward causal reasoning reveals that general cargo ships with a gross tonnage of 1-18,500 t are most likely to experience collision, grounding, and stranding accidents in the first quarter. Reverse diagnostic reasoning indicates that during early morning hours, container ships, general cargo ships, and chemical ships with a tonnage of 1-18,500 t are less likely to involve life loss in the event of collision accidents.

Port state control inspections implemented under the Paris Memorandum of Understanding (MoU) have become known as one of the best instruments for maritime administrations in European Union (EU) Member States to ensure that the ships docked in their ports comply with all maritime safety requirements. This paper focuses on the analysis of all inspections made between 2013 and 2018 in the top ten EU ports incorporated in the Paris MoU (17,880 inspections). The methodology consists of a multivariate statistical information system (STATIS) analysis using the inspected ship’s characteristics as explanatory variables. The variables used describe both the inspected ships (classification society, flag, age and gross tonnage) and the inspection (type of inspection and number of deficiencies), yielding a dataset with more than 600,000 elements in the data matrix. The most important results are that the classifications obtained match the performance lists published annually by the Paris MoU and the classification societies. Therefore, the approach is a potentially valid classification method and would then be useful to maritime authorities as an additional indicator of a ship’s risk profile to decide inspection priorities and as a tool to measure the evolution in the risk profile of flag over time.

The use of fuel material and different sources of ignition causes unwanted fires, producing and spreading in different spaces. Fire fighting. systems are measures taken to minimize the effects of fire. This struggle is not only on land, but also in the maritime world, through maritime security that has become a very important element for the International Maritime Organization (IMO). Therefore, maritime accidents caused by fire are one of the challenges to be taken into account, because they require immediate control and response. This article presents a historical interpretation of the concept of maritime safety through first responders on ships. It will be demonstrate how the technological advances of such equipment have been very important for their arrival on ships. In addition, the article reveals the legislative changes of International Convention for the Safety of Life at Sea (SOLAS), which reflects the IMO requirements to prevent fire risks on board, requiring a reading of the primary documents. Finally, the importance of the evolution of first intervention equipment for safety on board has been shown.

This article analyzes local level normative regulations aimed at directly or indirectly conserving the urban landscape in rural areas. Using a discursive analysis methodology on regulatory documents being enforced in a series of localities assigned to a tourism promotion program, evidence suggests that promotional activity retroactively influences the phraseology of these municipal regulations. The results obtained point to the existence of perpetuating historicist approaches within the current regulations, which appear to largely derive from the search for success in the tourism market and the resulting benefits to the local economy.

The maritime industry contributes to over 80% of global trade and ranks as the sixth-largest emitter of greenhouse gases. The International Maritime Organization has taken strides to reduce these emissions, while the European Union spearheads efforts to establish sustainable maritime transport. However, meeting decarbonisation targets poses significant challenges, with the potential implications of adopting an EU Emission Trading System (ETS) on shipping allowances, particularly at specific borders. If not managed effectively, this could result in diversifying regular container shipping routes away from EU ports, potentially leading to increased shipping emissions and disrupting the logistics trade and security chain. These challenges are exacerbated by the International Maritime Organization's lack of a carbon fee on bunkering, which creates an imbalance. The ETS Directive has fostered unfair competition between EU and non-EU ports due to discrepancies in applying emission unit allowances. It is imperative to implement preventive measures to contain and prevent the shift of operations from EU ports to nearby ports, ensure equitable treatment of EU transhipment ports and their competitors, and thwart carbon leakage. Additionally, the recent Houthis attacks on the Red Sea have significantly impacted shipping costs on the Cape of Good Hope route to Europe, necessitating increased allowances to and from Europe.

Alzheimer’s is a degenerative brain condition brought on by intricate brain changes after cell injury. The prevalence of Alzheimer’s disease is highest in those over 65. Presently, AD is detected by manual examination of a patient’s Magnetic Resonance Imaging (MRI) scan and neuropsychological assessments. Due to its subpar accuracy and performance, solutions based on artificial intelligence (AI) have not been made more widely available. This paper proposes a deep Convolutional Neural Network (CNN) with the pre-trained MobileNet-V2 architecture as the model’s base for feature extraction and reducing the parameter size and training time. The proposed model accurately classifies various early stages of AD. The proposed approach visualizes the class activation maps in the form of a heat map on brain MRI scans via the Grad-CAM algorithm that lifts the black-box nature of the deep model. To handle the imbalance problem of the AD data set acquired from Kaggle, the oversampling algorithm SMOTE interpolates new images to even the class samples. The proposed multi-class classification deep model is named Bio-AD and evaluated using different quality metrics. The Bio-AD model has the following values for evaluation metrics: 97.92%, 99.87%, 97.87%, 98%, 98%, and 0.0646 for accuracy, Area Under the Curve (AUC), F1-score, Precision, Recall, and loss respectively. The proposed Bio-AD model is compared with DenseNet-169, VGG-19, and InceptionResNet-V2 using different quality metrics and outperformed in comparison with all other models using the AD data set.

In the extensive monitoring of maritime traffic, maritime management frequently encounters incomplete automatic identification system (AIS) data, particularly in critical static fields like vessel types. This shortfall presents substantial challenges in safety management, necessitating robust methods for data completion. Distinct from road traffic, where road width imposes constraints, maritime vessels of identical classifications often choose significantly divergent routes, deviating by several nautical miles. Sole dependence on trajectory clustering is insufficient. Addressing this issue, we segments the maritime area into spatiotemporal grids, transforming vessel paths into sequences of grid encodings. Utilizing natural language processing techniques, we integrate the Word2vec word embedding approach with our novel biLSTM self-attention chunk-max pooling net (biSAMNet) model, enhancing the classification of vessel trajectories. This method is crucial for determining static details like vessel types. Employing the Taiwan Strait as a case study and benchmarking against CNN, RNN, and methods based on the attention mechanism, our findings underscore our model’s superiority. The biSAMNet achieves an impressive vessel classification F1 score of 0.94, using only 5-dimensional word embeddings, highlighting the effectiveness of Word2vec pre-trained embedding layers. This research introduces a novel paradigm for processing vessel trajectory data, greatly enhancing the accuracy of filling in incomplete vessel type details.

Changes in crude oil price affect the shipping freight market in three different channels. This study explores the dependence structure between oil prices and maritime freight rates to identify the strongest channel. Therefore, it investigates the relationship between oil prices and three major maritime freight rates; the Baltic Dry Index (BDI), the Baltic Dirty Tanker Index (BDTI), and the Baltic Clean Tanker Index (BCTI). We employ the decomposition method, not studied in the existing literature. The copula approach identifies the time-varying effects and asymmetry in the tail dependence structure between oil prices and freight rates. The main results of this analysis are as follows. The decomposed components display different conditional dependence patterns, and asymmetry is revealed in the upper and lower tail dependence. In the long run, we find more dependence in extreme periods like the financial crises. In short-run fluctuations, we find the dependence increases in an economic boom. The implications of the results suggest that dependence can vary over time and may change depending on extreme events, implying that the complementary strategies of the long run and short run should be different.

In today's world, wherein more than 80% of world trade is carried out by maritime routes, the safety and security of the seas where this trade takes place is of vast importance for nations and the in-ternational community. For this reason, ensuring the sustainable safety and security of the seas has become an integral part of the mission of all maritime-related entities. The utilization of big data extracted from the seas and maritime activities into meaningful information with artificial intelli-gence applications and developing applications that can be used in maritime surveillance will be of great importance for augmenting maritime safety and security. In this article, data sources which can be used by a maritime surveillance system based on big data and artificial intelligence tech-nologies and which can be established around sensitive sea areas and critical coastal facilities, are identified and a model proposal using this maritime big data is put forward.

The purpose of this study was to report data analysis results from the International Health Regulations (2005) Ship Sanitation Certificates (SSC), recorded in the European Information System (EIS). International sea trade and population movements by ships can contribute to the global spread of diseases. SSC are issued to ensure the implementation of control measures if public health risk exists on board. EIS designed according to the World Health Organization (WHO) “Handbook for Inspection of Ships and Issuance of SSC”. Inspection data were recorded and SSC issued by inspectors working at European ports were analysed. From July 2011-February 2017, 107 inspectors working at 54 ports in 11 countries inspected 5579 ships. Of these, there were 29 types under 85 flags (including 19 EU flags). As per IHR (2005) 10,281 Ship Sanitation Control Exception Certificates (SSCEC) and 296 Ship Sanitation Control Certificates (SSCC) were issued, 74 extensions to existing SSC were given, 7565 inspection findings were recorded, and 47 inspections were recorded without issuing an SSC. The most frequent inspection findings were the lack of potable water quality monitoring reports (23%). Ships aged ≥12 years (Odds Ratio, OR = 1.77, 95%Confidence Intervals, CI = 1.37–2.29) with an absence of cargo at time of inspection (OR = 3.36, 95%CI = 2.51–4.50) had a higher probability of receiving an SSCC, while ships under the EU flag had a lower probability of having inspection findings (OR = 0.72, 95%CI = 0.66–0.79). Risk factors to prioritise the inspections according to IHR were identified by using the EIS. A global information system, or connection of national or regional information systems and data exchange, could help to better implement SSC using common standards and procedures.

The document sets out three differentiated proposals for the transport of medicines through RPAS with their respective regulations, adapted to different operational categories: open category, special category and military scope. In the open category, an economical and efficient solution is prioritized for urban and rural areas, complying with weight and height regulations, in addition to guaranteeing the stability and quality of medications during transportation. The special category allows more complex operations and in more adverse conditions, such as densely populated areas and long routes, incorporating advanced security measures and training for personnel. In the military field, RPAS are used in conflict zones and hard-to-reach areas, ensuring the safe and rapid delivery of medical supplies under extreme conditions. Success stories in different countries are highlighted, demonstrating significant improvements in delivery times and risk reduction for health personnel.

The maritime sector, grapples with environmental challenges, but the adoption of "cold ironing" emerges as a promising solution, signifying a shift toward sustainability by providing energy to ships at port, reducing reliance on fossil fuels, and significantly lowering emissions, contributing to global climate change efforts. This transition towards renewable energy is especially crucial for islands like Lesvos, addressing challenges of high energy costs and environmental degradation resulting from reliance on imported fossil fuels, highlighting the potential for positive economic and environmental impacts. The existing literature highlights a research gap in the development of Renewable Energy Sources (RES) to support cold ironing operations, specifically due to the absence of specific data for the power demand needed in such operations and the lack of monitoring data for accurate calculations. This study's primary objective is to utilize real monitoring data from the port of Lesvos to evaluate the power demand for a potential cold ironing application. Additionally, the study aims to analyze the implementation of a wind power park to meet the energy needs of an electric port and evaluate the potential reduction in CO2 emissions. The database of Marine Traffic S.A. was utilized, while the determination of the energy used in-port per ship depended on factors such as the number of arrivals, the duration of hoteling, and the type of engine used by the ships. In addition, the software RETSCREEN was used for the energy analysis of a simulated 20 MW wind park that can support the in-port operations. The combined monthly energy demand for both main and auxiliary engines of shipping vessels at Mytilini port was assessed to be 6118 MWh and averaging a power demand equaled to 8.2 MW. The simulation analysis indicates that the annual electricity delivered to the port can be72080 MWh, with a significant portion remaining unused and exported to the grid, amounting to 14956 MWh annually. Due to demand fluctuations, in-port activities require an additional 924 MWh from the main electrical grid, which highlights the importance of additional measures like energy storage and demand-response practices for the gradual transition to 100% Renewable Energy Sources (RES) operations.

Understanding aspects of maritime/underwater cultural heritage (MUCH) and the associated cultural values and integrating them into maritime spatial planning (MSP) endeavors, is a new global challenge, alongside the rapid increase of human activities at sea and climate change impacts on the seas and the oceans. The article highlights the significance of cultural values in shaping human interactions with the marine environments, and how MSP can address the cultural dimensions of marine resources management. To this end, a systematic literature review was carried out to address the research question on how maritime/underwater cultural heritage is incorporated into MSP and map relevant academic literature. Following, a methodology that entailed an academic database search and the application of exclusion criteria, 346 articles resulted from Scopus. These articles were classified using science mapping techniques (i.e the VOSviewer Software ) and several categories (clusters) were created. The research showed a diversity of literature addressing the relationship between MUCH and MSP with a strong focus on sustainability, the significance of cultural ecosystem services (CES) and cultural values, the role of indigenous and local communities, but also of local stakeholders, the transfer of traditional knowledge to MSP and the participatory approaches and tools. The article concludes that for MSPlans to be innovative and acceptable by local communities, the “missing layer”of socio-cultural values and data is indispensable. In the MSP process, MUCH should be understood within this broader framework of socio-cultural considerations and values.

Understanding and evaluating urban investment environment is essential for effectively improving the efficiency of resource allocation between cities and promoting overall development of the regional economy. This paper takes 15 node cities on maritime Silk Road covered by the “Belt and Road” as the research object, establishes a dynamic evaluation index system for investment environment, and uses projection pursuit cluster to analyze and evaluate the investment environment of the cities. It is found that the investment environment potential of a city is directly related to the level of social development, economic development, and the degree of opening to the outside world. It is recommended that node cities should seize the important opportunity of the construction of the Maritime Silk Road, introduce world-wide human, financial and material resources to promote regional resources allocation and flow, and continuously improve and upgrade the investment environment quality.

The agricultural ecological environment provides an important resource guarantee for social development. The extensive management mode of agriculture in China has not fundamentally changed; the contradiction between production and governance is still prominent, and the management of agricultural surface pollution has a long way to go. Based on the data of 547 rural households in Jiangxi province, this paper uses the Ordered Logit, 2SLS, and moderation effect model to analyze the mechanism between social norms (SNs) and rural households’ (RHs) disposal of pesticide packaging waste (PPW) and to test the moderation effect of environmental regulation (ER) in the influence path of SN to RHs’ disposal of PPW. The results show that (1) descriptive and directive norms can promote RHs not to litter PPW. However, the role of surrounding crowd supervision (directive norms) is more obvious than the behavior of the surrounding crowd (descriptive norms). The consistent conclusion was still obtained after the robustness test and endogeneity treatment. (2) The results of the moderation effect test showed that reputational incentives strengthened the promotional effect of directive norms on RHs' behavior of not littering PPW; punitive regulation hindered the promotional effect of descriptive norms on RHs' behavior of not littering PPW. Based on the findings of the study, the following policy recommendations are put forward: continue to strengthen the guidance and soft binding force of informal institutions such as SNs; accurately locate the target groups and formulate differentiated measures; pay attention to the complementary nature of formal and informal institutions, and reasonably formulate environmental regulations to fit in with SNs.

Maritime ports represent an important ecosystem for pollutant emissions and, taking into account the ongoing energy transition, need to adopt new solutions to mitigate current emission levels. These emissions are partially avoidable if ships and vessels docked at the port use electric energy to feed their internal power needs instead of using their internal combustion engines. In Europe, there is an ongoing discussion on including such emissions in the European Emissions Trading System which will represent added costs for maritime operators. Onshore Power Supply systems can contribute to the ongoing energy transition by allowing the use of electric power to feed docked ships. As a first step to contribute to the development of Onshore Power Supply solutions, it is necessary to evaluate the added power needs that these systems would represent for the port. This paper presents a methodology that allows port operators to verify, straightforwardly and transparently, their power needs for Onshore Power Supply applications. The methodology is based on the historical data of docked ships at the port or quay level and provides an energy analysis of each type of vessel to determine the power to be installed at the port so that it is possible to supply energy to different types of ships and vessels simultaneously. Additionally, the implemented methodology provides economic and technical decision support factors by comparing the fuel costs with electric power costs, assessing the potential for this transition to Onshore Power Supply. The methodology is validated using a real case study for the port of Lisbon and obtained results demonstrate the potential for the installation of Onshore Power Supply in medium to large-dimension maritime ports.

Maritime transport has become very important due to its ability to internationally unite all continents. In turn, during the last two years, we have observed that the increase of consumer goods has resulted in global shipping deadlocks. In addition, the future goes through the role of ports and efficiency in maritime transport, with the aim of decarbonizing its impact on the environment. In order to improve the economy and people's lives, in this work, we propose to enhance services offered in maritime logistics. To do this, a communications system is designed on the deck of ships to transmit data through a constellation of satellites using interconnected smart devices based on IoT. Among the services, we highlight the monitoring and tracking of refrigerated containers, the transmission of geolocation data from GPS, and security through AIS. This information will be used for a fleet of ships to make better decisions and help guarantee the status of the cargo, as well as maritime safety on the routes. The system design, network dimensioning, and a communications protocol for decision-making will be presented.

In various domains such as energy, manufacturing, and maritime, cyber-physical systems (CPS) have seen increased interest. Both academia and industry have focused on the cybersecurity aspects of such systems. The assessment of cyber risks in CPS is a popular research area with many existing approaches that aim to suggest relevant methods and practices. However, few works have addressed the extensive and objective evaluation of the proposed approaches. In this paper, a standard-aligned evaluation methodology is presented and empirically conducted to evaluate a newly proposed cyber risk assessment approach for CPS. The approach, which is called FMECA-ATT&CK is based on Failure Mode, Effects & Criticality Analysis (FMECA) risk assessment process and enriched with the semantics and encoded knowledge in the Adversarial Tactics, Techniques, and Common Knowledge framework (ATT&CK). Several experts were involved in conducting two risk assessment processes, FMECA-ATT\&CK and Bow-Tie, against two use cases in different application domains, particularly an autonomous passenger ship (APS) as a maritime use case and a digital substation as an energy use case. This allows for the evaluation of the approach based on a group of characteristics, namely, applicability, feasibility, accuracy, comprehensiveness, adaptability, scalability, and usability. The results highlight the positive utility of FMECA-ATT&CK in model-based, design-level, and component-level cyber risk assessment of CPS with several identified directions for improvements. Moreover, the standard-aligned evaluation method and the evaluation characteristics have been demonstrated as enablers for the thorough evaluation of cyber risk assessment methods.

The aim of this paper is to apply a new lane separation methodology for the maritime sector emissions attributed to the different vessel types and marine traffic loads in the Mediterranean and the Black Sea defined via the European Marine and Observation Data network (EMODnet), developed in 2016. This methodology is implemented for the first time on the Copernicus Atmospheric Monitoring Service Global Shipping (CAMS-GLOB-SHIP v2.1) nitrogen dioxide (NOX) emissions inventory, on the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) nitrogen dioxide (NO2) tropospheric vertical column densities and on the LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog) chemical transport model simulations. By applying this new, EMODnet-based lane separation method to the CAMS-GLOB-SHIP v2.1 emission inventory, we find that cargo and tanker vessels account for approximately 80% of the total emissions in the Mediterranean, followed by fishing, passenger, and other vessel emissions with contributions of 8%, 7% and 5%, respectively. Tropospheric NO2 vertical column densities sensed by TROPOMI for 2019 and simulated by the LOTOS-EUROS CTM have been successfully attributed to the major vessel activities in the Mediterranean; the mean annual NO2 load of the observations and the simulations reported for the entire maritime EMODnet-reported fleet of the Mediterranean is in satisfactory agreement, 1.26 ± 0.56x1015 molecules cm-2 and 0.98 ± 0.41x1015 molecules cm-2, respectively. The spatial correlation of the annual maritime NO2 loads of all vessel types between observation and simulation ranges between 0.93 and 0.98. On seasonal basis, both observations and simulations show a common variability. The winter-time comparisons are in excellent agreement for the highest emitting sector, cargo vessels, with the observations reporting a mean load of 0.98 ± 0.54 and the simulations of 0.81 ± 0.45x1015 molecules cm-2 and correlation of 0.88. Similarly, the passenger sector reports 0.45 ± 0.49 and 0.39 ± 0.45x1015 molecules cm-2 respectively, with correlation of 0.95. In summertime, the simulations report a higher decrease in modelled tropospheric columns than the observations, however still resulting in a high correlation between 0.85 and 0.94 for all sectors. These encouraging findings will permit us to proceed with creating a top-down inventory for NOx shipping emissions using S5P/TROPOMI satellite observations and a data assimilation technique based on the LOTOS-EUROS chemical transport model.

The Forest Stewardship Council initiated a pilot Forest Certification for Ecosystem Services (ForCES) project from 2011 to 2017 to improve and promote sustainable forest management addressing a range of ecosystem services. Three sites in Indonesia were studied in the pilot. Whilst the development of the certification standard was largely by a partnership between the certification standard organization, civil society and research organisations, implementation and monitoring of the impact of this voluntary sustainability standard will entail interaction with state regulations. This study sought to understand how certification and state regulations concerning ecosystem services in Indonesia interplay, particularly in the agenda setting and negotiation stage. Using the conceptual lenses of transition theory and state and non-state market-based governance, the interrelationships between ecosystem services certification and regulations were found to be both complementary, supporting and antagonistic. The majority were complementary. Antagonism occurred where regulations do not accommodate land use issues and due to different contradictory state regulations. The voluntary instruments were developed largely in the absence of state involvement and without any substitution with regulatory standards. Given the increasing proliferation of voluntary market-driven initiatives at farm, forest concession and landscape level, stakeholders developing and managing voluntary standards need to collaborate with national and local governments to create synergy to enable their acceptance, adoption and effectiveness to positively enhance the conservation of ecosystem services through incentivizing market-based instruments.

The use of digital twins for the development of Autonomous Maritime Surface Vessels (AMSVs) has enormous potential to resolve the increasing need for water-based navigation and safety at the seas. Aiming at the problem of lack of broad and integrated digital twin implementations with live data along with the absence of a digital twin-driven framework for AMSV design and development, an application framework for the development of a fully autonomous vessel using an integrated digital twin in a 3D simulation environment has been presented. Our framework has four layers to ensure that the simulation and the real-world boat as well as the environment are as close as possible. Åboat, an experimental research platform for maritime automation and autonomous surface ship applications, equipped with two trolling electric motors, cameras, LiDARs, IMU and GPS has been used as the case study to provide a proof of concept. Åboat and its sensors, alongwith the environment have been replicated in a 3D simulation environment. Using the proposed application framework, we develop obstacle detection and path planning systems based on machine learning which leverage live data from a 3D simulation environment to mirror the complex dynamics of the real world.

This work investigates the stability conditions for linear systems with time-varying delays via augmented Lyapunov-Krasovskii functional(LKF). Two types of augmented LKFs with cross terms in integral are suggested to improve the stability conditions for interval time-varying linear systems. Through this work, the compositions of the LKFs are considered to enhance the feasible region of stability criterion for linear systems. Mathematical tools such as Wirtinger-based integral inequality(WBII), zero equalities, reciprocally convex approach, and Finsler’s lemma are utilized to solve the problem of stability criteria. Two sufficient conditions are derived to guarantee the asymptotic stability of the systems using linear matrix inequality(LMI). First, asymptotic stability criteria are induced by constructing the new augmented LKFs in Theorem 1. And then simplified LKFs in Corollary 1 are proposed to show the effectiveness of Theorem 1. Second, asymmetric LKFs are shown to reduce the conservatism and the number of decision variables in Theorem 2. Finally, the advantages of the proposed criteria are verified by comparing maximum delay bounds in two examples. Two numerical examples show that the proposed Theorem 1 and 2 obtained less conservative results than existing outcomes. Also, Example 2 shows that the asymmetric LKF methods of Theorem 2 can provide larger delay bounds and fewer decision variables than Theorem 1’s in some specific systems.

With the continuous breakthrough of natural language processing, the application of intelligent question answering technology in electric power system has attracted wide attention. However, at present, the traditional question answering system has poor performance and is difficult to be applied in engineering practice. This paper proposes an improved BERTserini algorithm for intelligent answering of electric power regulations based on a BERT model. The proposed algorithm is implemented in two stages. The first stage is the text segmentation stage, where a multi-document long text preprocessing technique is utilized that accommodates the rules and regulations text, and then Anserini is used to extract paragraphs with high relevance to the given question. The second stage is answer generation and source retrieval stage, where a two-step fine-tuning based on the Chinese BERT model is applied to generate precise answers based on given questions, while the information regarding documents, chapters, and page numbers of these answers are also output simultaneously. The algorithm proposed in this paper eliminates the necessity for manual organization of professional question-answer pairs, thereby effectively reducing the manual labor cost compared to traditional question answering systems. Additionally, this algorithm exhibits a higher degree of exact match rate and a faster response time for providing answers.

The exponential growth of maritime traffic has brought with it a multitude of business opportunities, while at the same time posing unprecedented challenges in terms of control and surveillance. Traditional methods struggle to cope with the sheer volume and complexity of maritime activities, which calls for innovative solutions. This study presents a comparative analysis of three prominent computing object detection models applied to maritime surveillance. By evaluating their performance metrics in dynamic maritime environments, this study provides information on the most suitable model for effective maritime monitoring applications, attaining an impressive 91\% mean Average Precision (mAP) using the YOLOv5n model.

The invasion of ship domain stands out as a significant factor contributing to the risk of collisions during vessel navigation. However, there is a lack of research on the mechanisms underlying collision risks specifically related to merchant and fishing vessels in coastal waters. This study proposes an assessment method for collision risks between merchant and fishing vessels in coastal waters and validated through a comparative analysis through visualization. First of all, the operational status of fishing vessels is identified. Collaboratively working fishing vessels are treated as a unified entity, expanding their ship domain during operation to assess collision risks. Secondly, to quantify the collision risk between ships, a collision risk index (CRI) is proposed and visualized based on the severity of collision risk. Finally, taking the high risk area of merchant and fishing vessels collision in the Minjiang River Estuary as an example, this paper conduct the analysis involves classifying ship collision scenarios, extracting risk data under different collision scenarios, and visually analyzing areas prone to danger. The results indicate that this method effectively evaluates the severity of collision risk, and the identified high-risk areas resulting from the analysis is verified by accidents occurred in the recent three years.

The architecture, Engineering, and Construction (AEC) industry is dealing with serious challenges on a global scale, i.e., project delays, budget overruns, and insufficient stakeholder collaboration. In this context, Value Engineering (VE) and Building Information Modeling (BIM) have been used recently to address these challenges and cope with large-scale and complex construction projects. An extensive body of literature highlights significant advantages of integrated VE within BIM technology. Despite this, it is full practical potential has not yet been realized. For this reason, this paper aims to investigate the integration of Value Engineering (VE) and Building Information Modeling (BIM) within a Common Data Environment (CDE) for the Architecture, Engineering, and Construction (AEC) industry. In doing this research, a comprehensive framework was developed and systematically implemented into practice through the use of four interconnected modules: (M. 1); Creating CDE, (M. 2); Design BIM Model Development, (M. 3); Value Analysis / Engineering Model, and (M. 4); Value Engineering Study. Introducing a new term the ""VEIDEA"" databank based on the OmniClass classification system provides a structured database utilized to store, manage, and accumulate VE ideas. Moreover, the study incorporates the Analytical Hierarchy Process (AHP) to automate the evaluation phase. Such a framework seeks to assist designers and VE team members make informed decisions when choosing appropriate design alternatives. Lastly, a case study method was adopted to examine the proposed framework for an office building. Quantitative data showed a significant link between cost savings and VR integration with BIM technology. For instance, cost of the RC slabs dropped by 20%, while flooring materials cost dropped by a 39%. Empirically, evidence from the case study supports literature regarding t the potential for significant enhancements in both cost-effectiveness and overall project performance through this innovative integration. In the context of knowledge contribution, this study provides an innovative way to assist designers and VE team members in making well-informed decisions when choosing appropriate design alternatives.

Maritime search and rescue is a crucial component of the national emergency response system, which currently mainly relies on Unmanned Aerial Vehicles (UAVs) to detect the objects. Most traditional object detection methods focus on boosting the detection accuracy while neglecting the detection speed of the heavy model. However, it is also essential to improve the detection speed which can provide timely maritime search and rescue. To address the issues, we propose a lightweight object detector named Shuffle-GhostNet-based detector (SG-Det). First, we construct a lightweight backbone, named Shuffle-GhostNet, which enhances the information flow between channel groups by redesigning the correlation group convolution and introducing the channel shuffle operation. Second, we propose an improved feature pyramid model, namely BiFPN-tiny, which has a lighter structure while being capable of reinforcing small object features. Furthermore, we incorporate the atrous spatial pyramid pooling module (ASPP) to the network, which employs atrous convolution with different sampling rates to obtain multi-scale information. Finally, we generate three sets of bounding boxes at different scales – large, medium, and small – to detect objects of different sizes. Compared with other lightweight detectors, SG-Det achieves better tradeoffs across performance metrics, and enables real-time detection with an accuracy rate of over 90% for maritime objects, which shows that it can be better meet the actual requirements of maritime search and rescue.

Pesticides have a vital contribution to the agricultural industry in Australia. However, pesticide applications may not always selective to its target organism. Exposure to pesticide has been associated with negative impacts to human health. One of the ways to reduce pesticide risk to the population and the environment is through government regulations. To put Australia pesticide regulations into perspective, comparisons were made between Australia and other nation’s pesticides regulations. The EU pesticide regulatory system was chosen for comparison with the Australian’s in the aspect of protecting the population from pesticide exposure. The comparison showed that the assessment to authorize a pesticide in Australia is based on the risk while in the EU, the assessment is based on the hazard of the pesticide. A registered active substance in Australia can be authorized for use indefinitely unless it is nominated for reconsideration while the period of registration of an active substance in the EU lasts for 10 years. In addition, no routine systematic chemical residue surveys are conducted in Australia for food commodities. The results highlight areas for improvement in the Australian pesticide regulatory system from the perspective of controlling undue exposure among the general population.

The growing adoption of electric propulsion systems in Maritime Autonomous Surface Ships (MASS) necessitates advancements in shipboard electronics for safe, efficient, and reliable operation. These advancements are crucial for tasks like real-time sensor data processing, control algorithms for autonomous navigation, and robust decision-making capabilities. This study investigates research trends in MASS using bibliographic analysis to inform policy and future research directions in this evolving field. We analyze 3,363 MASS-related articles from the Web of Science database, employing co-occurrence word analysis and latent Dirichlet allocation (LDA) topic modeling. Findings reveal a rapidly growing field dominated by image recognition research. Keywords like "datum," "image," and "detection" suggest a focus on collecting and analyzing marine data, particularly with deep learning for synthetic aperture radar imagery. LDA confirms this, with "Image analysis and classification research" as the leading topic. The study also identifies national and organizational leaders in MASS research. However, research on Arctic routes lags behind other areas. This work provides valuable insights for policymakers and researchers, promoting a deeper understanding of MASS and informing future policy and research agendas for the integration of electric propulsion systems in the maritime industry.

In the dynamic interplay between people and their physical environments, the Global South stands as a mosaic undergoing a multitude of transformative influences in architecture and urbanism where examining social sustainability becomes imperative. While prevailing attention remains on environmental and economic sustainability, this study addresses a persistent gap in the urban literature by focusing on the dynamic and manifold nature of social sustainability. Positioning itself within the context of sustainable development, the study links the pursuit of social aspects of sustainability with selected unique urban contexts from the Global South. Five cases that include Alexandria (Egypt), Tripoli (Libya), Basra (Iraq), Lilongwe (Malawi), and Accra (Ghana) are discussed through multi-layered investigations that involve attitude surveys, interviews, focus groups, participatory systematic observations, and behavioral mapping, engaging directly with inhabitants and stakeholders. Uncovering people-place narratives in the identified contexts, the cases are developed into five knowledge typologies that serve as practical tools for planning and design decision-making, policy formulation, and academic discourse. Discussions are conceived to demonstrate the transformative role people-place narratives play in fostering a more sustainable and equitable urban future. Conclusions are drawn to offer practical insights for stakeholders involved in various capacities in shaping the urban landscape of the Global South.

Various UAV applications, especially those based on reconnaissance and observation missions, often require an unlimited time of flight. This is possible only when a UAV is being continuously power supplied from the ground power source, and that is why tethered UAV systems were developed. Tethered UAV systems are based on multicopters which can hover above the landing pad, or track its position in the case it is movable. The presented research is about the development of a large C3 class hexacopter having a maximal payload of about 1 kg, and takeoff mass of 16 kg, which was tested in maritime conditions during the ferry’s cruise. The main purpose of the hexacopter is the continuous observation of the area ahead of a vessel to detect and localize obstacles in the water. During experimental tests critical phases of flight were identified, the AC-DC power supply unit as well as the power cord unwinder were tested, and the power taken by six BLDC motors was registered. The obtained results can be useful in future work on tethered UAV systems used in windy maritime conditions.

Software is playing the most important role in recent vehicle innovation, and consequently the amount of software has been rapidly growing last decades. Safety-critical nature of ships, one sort of vehicles, makes Software Quality Assurance (SQA) has gotten to be a fundamental prerequisite. Just-In-Time Software Defect Prediction (JIT-SDP) aims to conduct software defect prediction (SDP) on commit-level code changes to achieve effective SQA resource allocation. The first case study of SDP in maritime domain reported feasible prediction performance. However, we still consider that the prediction model has still rooms for improvement since the parameters of the model are not optimized yet. Harmony Search (HS) is a widely used music-inspired meta-heuristic optimization algorithm. In this article, we demonstrated that JIT-SDP can produce the better performance of prediction by applying HS-based parameter optimization with balanced fitness value. Using two real-world datasets from the maritime software project, we obtained an optimized model that meets the performance criterion beyond baseline of previous case study throughout various defect to non-defect class imbalance ratio of datasets. Experiments with open source software also showed better recall for all datasets despite we considered balance as performance index. HS-based parameter optimized JIT-SDP can be applied to the maritime domain software with high class imbalance ratio. Finally, we expect that our research can be extended to improve performance of JIT-SDP not only in maritime domain software but also in open source software.

: This study examines the prospects of residential water demand management policy regulations in Ethiopia and their implications for sustainable water resource management. This study aims to evaluate the existing policy regulations and analyze their effectiveness in promoting efficient water use and conservation practices in residential areas. By considering the potential challenges and opportunities associated with these regulations, the research provides insights into the future of residential water demand management in Ethiopia and suggests strategies for enhancing sustainable water resource management. Integrated literature and policy document review, alongside observation and interviews, was used to assess the viability of residential water demand management policies. The assessment of current policy regulations for residential water demand management in Ethiopian urban towns has revealed significant shortcomings in promoting water conservation activities. Hence, there is a need for significant improvements in the current water resource policy guidelines, which lack specificity, particularly in residential water demand management conservation strategies. The lack of awareness among residents regarding the importance of conserving their limited water resources is evident. To address these challenges and ensure the sustainability of the water supply, the government and policy developers must engage with various stakeholders, including the community, in the process of revising current policy documents. A more precise and tailored approach is necessary for its effective implementation.

The homeostasis of cellular calcium is fundamental for many physiological activities, while calcium levels maintain inhomogeneous within cells. During the onset of asthma, epithelial and inflammatory cells secrete platelet derived growth factor (PDGF), inducing proliferation and migration of airway smooth muscle (ASM) to the epidermal layer, narrowing the airway. The regulation of ASM cells by PDGF is closely related to the conduction of calcium signals. In this work, we generated subcellular-targeted FRET biosensors to investigate calcium regulations at different compartments of ASM cells. PDGF-induced cytoplasmic calcium [Ca2+]C increase was attributed from both extracellular calcium influx and endoplasmic reticulum (ER) calcium [Ca2+]ER release, which was partially regulated by PLC-IP3R pathway. Interestingly, removal of extracellular calcium influx led to inhibited ER calcium release, likely through inhibitory effect on calcium-dependent activation of ER ryanodine receptor. Inhibition of L-type calcium channel on plasma membrane, or SERCA pump on ER resulted in both reduced [Ca2+]C and [Ca2+]ER from PDGF stimulation, while IP3R channel inhibition led to reduced [Ca2+]C only. Inhibited SERCA pump caused immediate [Ca2+]C increase and [Ca2+]ER decrease, indicating an active calcium exchange between cytosol and ER storage in resting cells. PDGF-induced calcium at outer mitochondrial membrane sub-region showed similar regulatory response to cytosolic calcium, not influenced by inhibition of mitochondrial calcium uniporter channel. Therefore, our work identified calcium flow pathways among extracellular medium, cell cytosol, and ER by regulatory calcium channels. Particularly, extracellular calcium flow has an essential function to fully activate ER calcium release.

In today's digital landscape, the use of smartphones is almost inevitable, and so is the pervasive use of social media (SM), a constantly evolving system that has become an integral part of the daily lives of adolescents. Over the past seven years, the usage of social media platforms such as Instagram, Twitter, and TikTok has seen exponential growth among younger audiences. Excess SM use has raised concerns. This paper examines the possible negative consequences of the escalating trend in social media usage, and the implications of social media addiction (SMA), especially platforms featuring short-form video content, among teenagers. The paper also addresses the debate surrounding the validity of the term "addiction" concerning social media overuse and highlights the neurobiological processes associated with addiction, including the activation of dopamine-related brain structures. Furthermore, it discusses the researched structural and functional changes to the adolescent brain, including drawing parallels with substance addictions based on neuroimaging studies. Finally, this review advocates for exploring avenues of regulation to ensure a safer digital future, emphasizing the importance of policy to mitigate unforeseen long-term consequences of SMA and provides recommendations for reasonable and efficient future policy directions, guided by scientific and health concerns rather than political motives.

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory interactions, which study at the global scale has been challenged by the lack of data integration. Here, we update the manually-curated C. glutamicum transcriptional regulatory network, now including protein-protein interactions having a direct effect on gene transcription. The network model with regulations supported by any experimental evidence increased by 557 interactions regarding the previous (2018) version. 73 interactions supported by directed experiments were also included in a second model. We included 545 sRNA-mediated regulations in a third model with a total of 5164 interactions. We deposited the three network models in Abasy Atlas v2.4. We study the C. glutamicum regulatory structure by comparing it against the networks for more than 40 species, finding it to contrast in several global structural properties. We analyze the system-level components of the networks, finding that the inclusion of the sRNAs regulations changes their proportions, transferring part of the basal machinery to the modular class and increasing the number of modules while decreasing their size. Finally, we use strong networks of three model organisms to provide insights in future directions of the C. glutamicum network characterization.

The term new genomic techniques (NGTs), is an umbrella term to describe a variety of techniques that can alter the genetic material of an organism and that have emerged or have been developed since 2001, when the existing genetically modified organism (GMO) legislation was adopted. The analytical framework to detect GMOs in Europe is a established single harmonized procedure which is mandatory for authorization of GM food and feed, thus generating reliable, transparent and effective labelling scheme for GMO products. However, NGT products challenge the implementation and enforcement of the current regulatory system in the EU, relating in particular to the detection of NGT products that contain no foreign genetic material. Consequently, current detection methods will fail to meet minimum performance requirements. Although existing detection methods may be able to detect and quantify even small alterations in the genome, this does not necessarily confirm the distinction between products resulting from NGTs subject to the GMO legislation and other products. Therefore, this study provides a stepwise approach for the in silico prediction of PCR systems specificity by testing a bioinformatics pipeline for amplicon and primer set searches in current genomic databases. We have tested our methodology in two mutant genotypes produced by CRISPR/Cas9 in Arabidopsis thaliana. Overall, our results demonstrated that the single PCR system developed for the identification of a nucleotide insertion in the grf1-3 genotype has sufficient hits in the databases that would not allow discrimination of this mutanted event. Differently, the second mutated genotype grf8-61 which contains a -3bp deletion, found no matches in the sequence variant database. Our approach is the first step in decision making on PCR system and modification of them for empirical testings.

The authors present a framework for assessing seasonal events which may influence maritime operations. Most maritime-related research tends to focus on single events, such as a storm, but maritime systems operate within complex systems that have some predictable patterns. These predictable patterns due to natural events, such as weather and water levels, can influence operations, while other factors, such as cargo peaks or cultural activities, could also shape maritime systems. By integrating data from emergency management databases and weather information sources with other inputs, the authors created a matrix of regionally specific predictable events that may occur within a region by time of year. The matrix was vetted with various stakeholder groups to verify the information in the matrix. The main findings were that a seasonal event matrix is helpful as a reference for examining operational patterns in a river for various uses, such as training, operational planning, and emergency response coordination.

Taking into account the increase in the emission of greenhouse gases produced by ships, during navigation and maneuvering in the port, a direct consequence of the increase in maritime traffic, the international community has developed a broad set of regulations to limit such emissions. The installation in commercial ports of automatic mooring systems by means of vacuum suction cups (AMS), thus reducing considerably the time required to carry out the mooring and unmooring maneuvers of ships, is a factor that is considerably influencing the decrease in Emissions of polluting gases in commercial ports with high traffic. The objective of the present work is to verify the influence of the use of the AMS on the emissions of polluting gases produced in the facilities destined to the traffic of container ships. It examines the CO2 emissions of container ships that call in the only three container ports equipped with AMS: Salalah (Oman), Beirut (Lebanon) and Ngqura (South Africa). Between them, these three ports supported the transit of 6 million TEUS in 2017. The calculation of emissions is made taking into account the time saved when performing the mooring maneuvers using the new AMS system compared with when it is not used. To do this, two different calculation methods are used: EPA and ENTEC to then compare the results of the two and thus obtain the reduction in emissions per TEU in these terminals during the mooring maneuvers. The paper concludes with a discussion on the values of the reductions in emissions obtained and the advantages of the installation of AMS in commercial ports located near population centres.