Technical Scenarios Research Articles

Current Status and Future Directions for Combined Tillage and Sowing Technology and Equipment

As the focus of the development of mechanized tillage and sowing, combined tillage and sowing machines have a variety of functions, such as seedbed preparation, fertilizer sowing, and pressing. Compared with the traditional single-function planter, these machines effectively shorten the operation cycle, reduce production costs, and promote increased production and income. This paper categorizes the machines into these combined rotary tillage and sowing machine, the combined disk harrow and sowing machine, and the combined multi-link tillage and sowing machine according to the form of the tillage and operation. It also systematically elaborates on the technical characteristics, application scenarios, and operational requirements of different types of combined tillage and sowing machines. Additionally, this paper outlines key technologies, such as seedbed preparation and precision sowing. Considering the current state of scientific and technological advancements and the practical needs of agricultural production, it also suggests future research directions and trends, offering valuable insights for subsequent studies in this field.

A value-sensitive approach for integrated seawater desalination and brine treatment

The transition to seawater desalination integrated with resource recovery, particularly in water- and energy-scarce regions, requires innovative approaches that consider societal benefits and costs. This study goes beyond traditional techno-economic evaluations by employing a Value-Sensitive Design (VSD) approach, which guides the selection of performance indicators and informs the design of technical scenarios for integrated seawater desalination and brine treatment systems. VSD ensures that the scenarios are socially relevant by directly incorporating stakeholder values into the design and assessment process. Four technical scenarios (Sc) were used to evaluate the VSD approach: Sc1) maximum water recovery, Sc2) and Sc3) integrated desalination with brine treatment for maximum resource recovery (using different configurations) and Sc4) electricity-based desalination for chemical recovery. Techno-economic models are implemented using Python to analyse the feasibility and performance of these scenarios. The modelling results indicate that all scenarios achieve zero brine production. However, the trade-offs between resource recovery and greenhouse gas emissions are evident. Increased salt recovery leads to higher CO2 emissions (locally) due to electricity consumption. Scenario 1 minimized electrical energy consumption and emissions while maximizing water production. Scenarios 2 and 3 performed best in water and high-quality salt production. Despite its higher CO2 emissions, Scenario 4 proved most profitable due to the production of chemicals. These findings highlight the importance of tailoring plant designs to regional needs. By providing a comprehensive understanding of trade-offs, the VSD approach fosters stakeholder dialogue and serves as a valuable decision-making tool for designing sustainable desalination systems.

Integrating gene expression and imaging data across Visium capture areas with visiumStitched

BackgroundVisium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment.ResultsWe generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD.ConclusionsvisiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStitched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStitched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

On Assessing a Potential Reuse of the Indonesian Post-Operation Offshore Oil/Gas Pipelines as A Cold-Water Pipe for an Ocean Thermal Energy Conversion (OTEC) System: A Thermal and Fluid Dynamic Perspective

One of the main issues arising in offshore oil and gas decommissioning is associated with significant required costs. Research assessing the potential reuse of the post-operation offshore oil and gas pipeline (POGP) in Indonesia for the Ocean Thermal Energy Conversion (OTEC) system offer double the potential cost reductions in POGP decommissioning and OTEC development. In the context of OTEC development, research on increasing system efficiency makes a significant effort by modifying working fluids and usually by employing the assumption that the temperature of the cold seawater at the surface outlet of the Cold-Water Pipe (CWP) is practically the same as that at the inlet of the CWP at a depth of about 900 m. Unfortunately, this was not the case when the POGP was to be reused for the OTEC system because there was difficulty in applying additional insulation to the existing subsea pipelines. The temperature change in the cold seawater is even more critical considering that oil and gas operations at a depth of 900 m could be associated with more than 60 km of pipeline length to reach an onshore system for a typical seabed bathymetry. This paper assesses the potential reuse of the POGP as a CWP for the Ocean OTEC system. The temperature distribution within CWP is analyzed using a thermal and fluid dynamics approach. The results show that the reuse of POGP for the OTEC system could offer an excellent opportunity for capital cost reductions because the POGP has a remaining service life of over 20 years. However, the results of the analysis of heat and mass transfers show that the temperature change in cold seawater at CWP is about 3 to 6 oC, depending on the technical scenarios of the pipelines. The POGP used in the OTEC system could be suitable for a 20 kW OTEC system with practically no cost of pipelines, which usually accounts for a significant investment cost.

Thermal seawater desalination for irrigation purposes in a water-stressed region: Emerging value tensions in full-scale implementation

Water scarcity in arid regions has driven the spread of desalination. These systems contribute to water access but come at an intensive energy cost, and lead to brine discharge and associated environmental impacts. This work aims to investigate emerging societal issues and tensions when developing and implementing a thermal desalination system to produce irrigation water in the South of Spain. This has been done in a demonstration system for solar desalination able to recover water and salts from desalination brine. For this purpose, a context-sensitive design exercise has been implemented. First, tensions between social values expressed by diverse stakeholders have been identified. Then, a set of technical scenarios for the full-scale implementation of the system were designed and evaluated, comparing them to conventional membrane desalination. The analysis indicates high economic and energy costs to avoid the environmental impacts of increasing water production.

Gamification In English Language Teaching: A Pathway to Fostering Teacher-Student Rapport, Teacher Immediacy and Students’ Willingness to Communicate

This research examines the role of gamification in enhancing English language teaching and investigates how it helps in improving teacher-student rapport (TSR), teacher immediacy (TI), and students’ willingness to communicate (WTC). Research focusing on the impact of gamification on these variables is limited. This study bridges the existing gap and sheds light on the necessity of incorporating gamification in foreign language teaching. Data for the study were collected from 50 EFL teachers and 165 EFL students in prominent higher education institutions in two south Indian states, Tamil Nadu and Kerala. Purposive sampling was used to collect the data, and two structured questionnaires were distributed. The reliability of the questionnaire was checked using Cronbach’s Alpha. Different statistical methods and descriptive analysis were used to interpret, represent, and analyze the results of the study. It is observed that gamified modules significantly improve the students’ vocabulary acquisition and motivate them to improve their language skills. They also help to enhance TSR and TI, paving the way to improved WTC. Although gamified simulations prepare students for real-world technical communication scenarios in English, it is observed that EFL teachers face several implementation challenges in the classroom.

Mix proportion design and life cycle assessment of ultra-high-performance lightweight concrete with hollow microspheres

Achieving high strength and low weight in cement-based composites remains a critical objective in material and structure engineering. This study presents the development of an ultra-high-performance lightweight concrete (UHPLC) composite with a density not exceeding 1950 kg/m³ and a compressive strength of at least 100 MPa. The UHPLC mix design was optimized using the central composite design (CCD) response surface methodology, and a life cycle assessment (LCA) was conducted for the first time on UHPLC from cradle to gate. The interactions between cement content, hollow microspheres, and their effects on workability, mechanical properties, and durability were analyzed. The results show that using the CCD response surface method for designing UHPLC mix proportions is feasible, allowing effective optimization for various objectives, such as balancing both strength and density, highlighting low density, or emphasizing ultra-high strength. the designed UHPLC exhibits mechanical and durability properties comparable to or better than UHPC. LCA results show higher energy consumption and environmental impact for UHPLC in the cradle-to-gate stage, mainly due to the microsphere production phase. Monte Carlo uncertainty analysis reveals that ADP, HTP, POCP, and EP are most sensitive to microsphere content, while GWP and AP are more affected by cement content. The optimized UHPLCs in this study can be selected depending on specific technical or environmental scenarios. Introducing HMs into the UHPC system for UHPLC production shows excellent performance, making it a promising material for advanced structural applications.

Real-time data warehousing in the big data environment: A comprehensive review of implementation in the internet industry

A real-time data warehouse is a crucial tool for information management and analysis, enabling the capture, processing, and analysis of vast amounts of data from diverse sources in real-time. It offers enterprises enhanced decision support through its efficient processing capabilities and timely data feedback. This paper reviews the technical characteristics and application scenarios of real-time data warehouses, with a particular focus on the Internet sector. It explores the evolution from traditional data warehouses to modern data lake and lakehouse architectures, emphasizing the advancements in data processing capabilities, including the separation of storage and compute functions. Real-time data warehouses, which enable immediate data processing and feedback, are essential for enterprises requiring up-to-the-minute insights. The study compares the Lambda and Kappa architectures, detailing their strengths and weaknesses in terms of data throughput, latency, and scalability. Innovations such as Apache Hudi and lakehouse architectures offer new opportunities for performance optimization and functional expansion. The emergence of hybrid architectures like HTAP (Hybrid Transactional/Analytical Processing) and HSAP (Hybrid Serving/Analytical Processing) represents a significant advancement in integrating transactional and analytical processing. Future research should focus on the impact of artificial intelligence and machine learning on real-time data warehouses to enhance their analytical and predictive capabilities, reduce complexity, and lower operational costs.

Integrating gene expression and imaging data across Visium capture areas with visiumStitched.

Visium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment. We generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD. visiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStiched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStiched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

Carbon capture and co-pollutants in a networked power system

Abstract We evaluate how the availability of Carbon Capture (CC) in a networked electricity system affects the emissions of both carbon and of co-pollutants, under a range of plausible technical, economic, and policy scenarios about CC technology, the pace of renewable deployment, the structure of the power grid, and climate policy. We employ a Power Flow model of a three-node, mixed-source network in which fossil fuel power plants may invest in CC via retrofit. Our stylized model retains some of the complexities of a real power system while allowing for a detailed analysis of the impact of power plant operations and transmission constraints. We find that, in a networked system, the availability of CC may lead some generation to move from Natural Gas to Coal, thus leading to a significant increase in co-pollutants. This is of particular concern during the mid-transition, a period when both carbon and non-carbon electrical generation is active. The introduction of CC can lead to an increase in co-pollution even as the energy system transitions toward renewable energy and, surprisingly, co-pollution outcomes can be worse under a stronger decarbonization policy. This insight is important and timely in light of recent rules incentivizing the use of CC. Systems in the early stages of the energy transition may experience an increase in co-pollution if the co-pollutant dynamics are not considered in the first steps of CC policy design.

Collective intelligence-driven 3D printing factory for social manufacturing: implementing a testbed for industrial application

ABSTRACT The emergence of 3D printing technology has imbued the mass customization production model with novel implications. Concurrently, investigations into social manufacturing (SocialM) and collective intelligence present a fresh challenge for the 3D printing industry in their pursuit of realizing customized mass production. However, there is still a lack of investigation on the technical implementation and application scenarios of SocialM, and it hinders the development of SocialM from theory to industrial application. To mitigate this gap, firstly a five-layer framework based on collective intelligence for the configuration of design-production-service integrated 3D printing factory is established, together with the key enabling techniques that support the configuration and operation of the factory from social interaction software perspective and cyber-physical-social interconnection perspective. Secondly, the running logic of the 3D printing factory is demonstrated, and it starts from order generation to order completion. Thirdly, a testbed of the 3D printing factory is built, which contains both social interaction software and physical production hardware environments, and a production order of a 3D printed robotic arm is used to verify the feasibility of the testbed and the configuration and operation theories of SocialM. The work in this paper provides technical solutions for the industrial application of SocialM.

Survey of Research on Face Recognition Methods Based on Depth Learning

The field of face recognition has recently become a quite popular area of research, which is of great significance to the development of technology. It introduced the definition of face recognition technology and its development process, as well as the technical advantages and application scenarios of the technology. with the development of deep learning, face recognition technology based on deep learning is gradually realized. firstly, the limitations of traditional face recognition technology are pointed out. Then, several popular face recognition methods based on depth learning are analyzed. Finally, this paper introduces the application of deep learning technology in face recognition, summarizes a new deep learning model based on big data, and summarizes and prospects the development of face recognition technology in the future.

Audio signal processing technology in Arduino controlling

In recent years, the application of audio signal processing technology is frequent, which is beneficial for developing both technologies. A significant advantage of the application of audio signal processing is allowing users to input their commands by voice, which is why it is widely used in Arduino controlling. Besides, Arduino can also be applied in audio signal processing. Because Arduino is an open-source multi-functions platform with the features of low cost, its utilization will be wider and more flexible in audio-digital signal processing and many other fields in the following time. So, the combination of these two technologies can produce more and more meaningful outcomes. This paper first introduces the technical features and application scenarios of these two technologies respectively, and then analyzes some samples of the combination of the two technologies specifically and summarizes them in different aspects to know about the current situation of these fields. By deeply understanding the inadequacies of these projects, this paper also analyzes the future developing trends of the fields that can solve the current problems and improve the quality of the projects.

Unmanned aerial vehicle face recognition technology research progress

In recent years, face recognition technology has become a significant advance in the area of biometrics and machine vision. It paves the way for a wide range of applications, including security systems, access control, surveillance, and user authentication. These applications are undoubtedly a major innovation in the field of UAV, which will greatly expand and extend its application scenarios. This paper shows a compositive review of UAV facial identification technology, including its basic principles, techniques, challenges, and ethical considerations. According to the different stages, this paper focuses on RCNN and YOLO, two more widely used target detection technologies and their respective technical iterations, and through the comparison of the two in terms of technical characteristics and application scenarios, the advantages of the two are obtained, and combined with the current UAV workflow. Get the stage in which they play a specific role. This paper reviews the existing literature and research on face recognition, aiming to help people better understand the current process of this technology and its wider social application and impact.

ЗМІНА МОДЕЛІ РОБОТИ ЧАТ-БОТІВ У СФЕРІ ОБСЛУГОВУВАННЯ КЛІЄНТІВ

In modern business, customer support stands as a pivotal element for successful client servicing. The operation of customer support involves providing assistance and resolving client issues regarding company products or services. In the current simplified model, the efficacy of technical support agent searches generally surpasses that of chatbots or human assistance. Filtering internal staff-only articles from those intended for clients poses a challenge, necessitating complex implementations that not all companies may afford. Previous-generation chatbots have shown limited effectiveness in replacing humans due to varying client articulations, necessitating human intervention. Conventional chatbots offer limited options: information retrieval based on client queries, problem narrowing through additional inquiries, and sending tailored instructions. However, maintaining and updating knowledge for both internal staff and clients poses resource-intensive challenges for large companies. An alternative emerges with LLM-based chatbots, automating communication with users via chat interfaces. LLM chatbots enhance speed and efficiency, reduce personnel costs, and ensure 24/7 client service. Yet, they require con- stant knowledge updating and careful handling to address a spectrum of issues effectively. Notably, LLM chatbots can handle complex articles, gathering step-by-step instructions from various sources. Still, undocumented issues or incorrect solutions may necessitate human assistance. The primary functional difference between LLM chatbots and conventional ones lies in their contextual and linguistic processing capabilities, making communication with LLM chatbots akin to human interaction. Despite advancements, the nuances of context and language remain pivotal for effective client servicing, particularly in technical support scenarios. Future exploration in this direction should focus on optimizing knowledge management and enhancing LLM chatbot capabilities for improved client satisfac- tion and operational efficiency."

Introducing hydrothermal carbonization to sewage sludge treatment systems—a way of improving energy recovery and economic performance?

Hydrothermal carbonization (HTC) can mitigate the disposal costs of sewage sludge in a wastewater treatment plant. This study analyzes the impact of integrating HTC with anaerobic digestion (AD) and combustion from a combined energy and economic performance perspective. Net energy balance and investment opportunity are investigated for a number of technical scenarios considering i) different combinations of the technologies: AD + HTC, AD + thermal dryer + combustion, and AD + HTC + combustion, ii) different options for HTC process water treatment: wet oxidation (WO) + AD, and direct return to AD, and iii) different products: heat-only, heat and electricity, hydrochar, and phosphorus.The results show trade-offs between investment cost, self-supplement of heat, and output electricity when WO is used. In AD + HTC, net heat output decreases compared to the reference plant, but avoided disposal costs and hydrochar revenue result in profitable investment when the process water is directly returned to the AD. Although HTC has a lower heat demand than the thermal dryer, replacing the thermal dryer with HTC is only possible when AD, HTC, and combustion are connected, or when WO covers HTC’s heat demand. HTC may impair the electricity production because of the necessity for a high-temperature heat source, whereas the thermal dryer can utilize a low-temperature heat source. In conclusion, energy advantages of HTC in AD + HTC + combustion are insufficient to provide a promising investment opportunity due to high investment costs of HTC. The investment opportunity improves by co-combustion of hydrochar and external sludge.

Renewable energy scenarios for water desalination and conveyance: Case of red sea-dead sea project

The objective of the Jordan Red Sea-Dead Sea (RSDS) project is to transport desalinated water from the Gulf of Aqaba to the Dead Sea. It aims to resolve two fundamental issues in Jordan: the lack of potable water in the country's center and the low water level in the Dead Sea. Desalinated seawater should be pumped from the Gulf of Aqaba to the Dead Sea as part of the RSDS project.This study is not only the first study to focus on the feasibility of using renewable energy sources to meet the project's energy needs, but the approach taken in this research is also novel. It employs a variety of software packages in order to accomplish the research goals. Thus, a number of operational scenarios for the RSDS project employing renewable energy technologies, as these resources are essential for sustainable development, are proposed. Based on the availability of renewable energy sources in the project region, only solar and wind technologies are included in the technology selection process. The selection of a suitable technology from renewable energy technologies was based on eight scenarios that were developed using several selection criteria. The social, technical, environmental, risk evaluation, and financial impact scenarios were investigated. Analytic hierarchy process and multi-criteria decision analysis were utilized to evaluate the electricity generation options for the project. The results indicated that the economic scenario is the optimal scenario for covering the entire load. Levelized Cost Of Energy (LCOE) and payback period are sub-criteria for this scenario. The primary goal of this scenario is to cover the load with the lowest LCOE and shortest payback period possible. The results indicated that a 945 MW Photovoltaic plant and a 630 MW wind energy plant are required to cover the total loads for desalination and water pumping. Energy storage is essential in any scenario where renewable energy sources are used to meet demand. Electric vehicles are employed in this research as a kind of energy storage to lessen the demand for more traditional storage methods. The number of 85 kWh electric vehicles needed to replace traditional storage medium is estimated. It is determined that 53,614 and 57,584 electric vehicles in the 24 hour and 12 hour operating times, respectively, are required under the economic scenario.

Evaluation of green hydrogen production using solar, wind, and hybrid technologies under various technical and financial scenarios for multi-sites in Egypt

The importance of energy storage is increased with the intermittent nature of renewable energy resources (RERs). Green hydrogen is increasingly being employed to address its shortcomings. Furthermore, lowering carbon emissions has accelerated the quest for green alternatives instead of fossil-based fuels. This research focuses on Egypt's capacity to generate green hydrogen using natural renewable resources to serve islanded electrical and hydrogen loads. To obtain the lowest net present cost (NPC), cost of hydrogen (COH), and levelized cost of energy (LCOE), the state-of-the-art prices of the system elements are investigated and optimized using the HOMER professional software. Three situations with solar photovoltaic (PV), wind, and hybrid RERs are evaluated in three separate Egyptian cities. A sensitivity analysis is investigated based on the influence of the system's reliability and hydrogen load variance on the cost. The results of the three locations are compared to indicate the best site for green hydrogen production. The results obtained with the wind scenario located on the coast of the Suez Gulf provided the lowest LCOE, ranged from 0.308 $/kWh to 0.353 $/kWh, and the COH ranged from 3.73 $/kg to 4.13 $/kg.

Ethical and Legal Considerations behind the Prevalence of ChatGPT: Risks and Regulations

In response to the prevalence of ChatGPT, this paper summarized its technical model, core capabilities, and application scenarios, analyzed the ethical risks such as autonomy, moral misconduct, human alienation, and value reconstruction, as well as legal risks such as legal entity status, copyright ownership, data security, and algorithmic black box. Then proposed the regulating principles of tool positioning, safety, legality, transparency, credibility, fairness, shared responsibility, and the regulating path of encouraging the development of autonomous, safe and controllable technologies, improving artificial intelligence legislation and justice, and establishing a diverse governance system.

Analysis of The Problem of Low Sales of Insta360 Panoramic Cameras

The Insta 360 panoramic camera simulates a two-dimensional floor plan into real three-dimensional space. Panoramic landscapes diversify the way an image is viewed, and at the same time, add interest. In addition to good interactive performance, the sense of realism is also very strong. Most importantly, objects can be seen in perspective, also known as naked-eye 3D. The purpose of this study was to explore why Insta 360's product is new and unique, and why sales are so low that the company has faced two innovation failures. After further analyzing its technical conditions, market atmosphere, and application scenarios, this paper improved product performance and development direction. This study concluded that only the novelty of the product is considered, ignoring immature technologies and markets and limited application scenarios. These led to low sales of the product in the first two times. Therefore, the panoramic camera is an emerging product, and it is necessary to determine the target user. Then, discuss the development model suitable for the Insta 360 panoramic camera under the above conditions.