Seamless System Research Articles

Seamless multimodality for passenger transportation in the Russian Federation

The paper considers the formation of a seamless multimodal passenger transportation in order to develop transport infrastructure not only at the regional but also at the federal level. The positive aspects and disadvantages of a multimodal transport system are considered. The paper presents a review of the scientific literature on the above issues. The research methodology is based on proven approaches. Founded on the analysis of the tourist flow, it is proposed to build a system of seamless multimodal transportation in the territory of the Russian Federation (hereinafter referred to as RF). The relevance is due to the need to develop regional transport systems as well as consideration of this topic in the scientific literature, regulatory documents of the industry. Based on the Strategic direction in the field of digital transformation of the transport industry of the RF until 2030, the principles of multimodality are proposed to create a seamless system of multimodal passenger transportation. The development has been conducted for the transport system of the Altai Territory. Based on the data on tourist flows of the Federal State Statistics Service, the calculated route Moscow – Barnaul – Gorno-Altaysk is formed. The introduction of a digital platform for convenient search and booking of transportation is considered, the key points of working with requests are highlighted. The movement of financial and information flows and the algorithm of actions of the system participants are determined.

College Amenities Application (CampusIn)

Abstract—In the digital age, enhancing student experience and academic success through efficient services is essential for modern educational institutions. The College Amenities application serves as a comprehensive, multifunctional platform that integrates various aspects of academics into one seamless system. It offers a range of services, including food ordering, where students can conveniently browse menus, place orders, and track deliveries; event showcasing, which keeps students informed about campus events, workshops, social activities and placement information, providing access to job opportunities, internships, and career resources. Additionally, the application features like secure document storage, enabling students to organize and retrieve academic materials such as notes, assignments, and research papers with ease. By combining these features, the application improves campus connectivity, enhances student engagement, and supports academic and professional growth, making it a valuable tool for fostering a more efficient and interactive campus experience. Keywords: Service Automation, Campus dining, Event Registration, Placement Automation, File Storage.

Landslide Hazard Is Projected to Increase Across High Mountain Asia

AbstractHigh Mountain Asia has long been known as a hotspot for landslide risk, and studies have suggested that landslide hazard is likely to increase in this region over the coming decades. Extreme precipitation may become more frequent, with a nonlinear response relative to increasing global temperatures. However, these changes are geographically varied. This article maps probable changes to landslide hazard, as shown by a landslide hazard indicator (LHI) derived from downscaled precipitation and temperature. In order to capture the nonlinear response of slopes to extreme precipitation, a simple machine‐learning model was trained on a database of landslides across High Mountain Asia to develop a regional LHI. This model was applied to statistically downscaled data from the 30 members of the Seamless System for Prediction and Earth System Research large ensembles to produce a range of possible outcomes under the Shared Socioeconomic Pathways 2‐4.5 and 5‐8.5. The LHI reveals that landslide hazard will increase in most parts of High Mountain Asia. Absolute increases will be highest in already hazardous areas such as the Central Himalaya, but relative change is greatest on the Tibetan Plateau. Even in regions where landslide hazard declines by year 2100, it will increase prior to the mid‐century mark. However, the seasonal cycle of landslide occurrence will not change greatly across High Mountain Asia. Although substantial uncertainty remains in these projections, the overall direction of change seems reliable. These findings highlight the importance of continued analysis to inform disaster risk reduction strategies for stakeholders across High Mountain Asia.

Predictability and prediction skill of summertime East/Japan Sea surface temperature events

The East/Japan Sea (EJS), a marginal sea of the Northwestern Pacific, is one of the ocean regions showing the most rapid warming and greatest increases in ocean heatwaves over the last several decades. Predictability and skillful prediction of the summer season EJS variability are crucial, given the increasing severity of ocean temperature events impacting fisheries and reinforcing climate conditions like the East Asian rainy season, which in turn affects adjacent high-population density areas over East Asia. We use observations and the Geophysical Fluid Dynamics Laboratory (GFDL) Seamless System for Prediction and Earth System Research (SPEAR) seasonal forecast system to investigate the summertime EJS Sea Surface Temperature (SST) predictability and prediction skill. The observations and seasonal prediction system show that the summer season EJS SST can be closely linked to the previous winter air-sea coupling and predictable 8–9 months in advance. The SPEAR seasonal prediction system demonstrates skillful forecast of EJS SST events from summer to late fall, with added skill for long-lead forecasts initialized in winter. We find that winter large-scale atmospheric circulations linked to Barents Sea variability can induce persistent surface wind anomalies and corresponding northward Ekman heat transport over the East China Sea. The ocean advection anomalies that enter the EJS in prior seasons appear to play a role in developing anomalous SST during summer, along with instantaneous atmospheric forcing, as the source of long-lead predictability. Our findings provide potential applications of large-scale ocean-atmosphere interactions in understanding and predicting seasonal variability of East Asian marginal seas.

Seasonal predictions of summer compound humid heat extremes in the southeastern United States driven by sea surface temperatures

Humid heat extreme (HHE) is a type of compound extreme weather event that poses severe risks to human health. Skillful forecasts of HHE months in advance are crucial for developing strategies to enhance community resilience to extreme events1,2. This study demonstrates that the frequency of summertime HHE in the southeastern United States (SEUS) can be skillfully predicted 0–1 months in advance using the SPEAR (Seamless system for Prediction and EArth system Research) seasonal forecast system. Sea surface temperatures (SSTs) in the tropical North Atlantic (TNA) basin are identified as the primary driver of this prediction skill. The responses of large-scale atmospheric circulation and winds to anomalous warm SSTs in the TNA favor the transport of heat and moisture from the Gulf of Mexico to the SEUS. This research underscores the role of slowly varying sea surface conditions in modifying large-scale environments, thereby contributing to the skillful prediction of HHE in the SEUS. The results of this study have potential applications in the development of early warning systems for HHE.

A Framework for Effective Virtual Commissioning: Guiding Principles for Seamless System Integration

Virtual commissioning (VC), defined as the simulation and testing of systems in a virtual environment before physical implementation, plays a key role in addressing the challenges of integrating and validating complex systems efficiently and effectively. This paper focuses on the topic of virtual commissioning, summarizing and organizing existing research in the field. The paper provides a comprehensive overview of various design methods and technologies currently in use. A case study of virtual commissioning is also presented within the area of the Cyber-Physical Manufacturing Systems Laboratory of the Széchenyi István University, detailing the solution steps taken. Drawing on both research and practical experience, the paper proposes a novel framework to support virtual commissioning design, referred to as the “Virtual Commissioning House” (VCH). The methodology is evaluated through comparisons with existing virtual commissioning solutions, demonstrating its effectiveness.

Estimation of blocked forces for NVH source characterization of a beam axle using analytical methods

Component-Based Transfer Path Analysis (TPA) has been of growing interest recently because, unlike classical TPA, it enables source characterization independent of the receiver structure. The source energy in component TPA is typically characterized by blocked forces. As part of virtual prototyping, OEMs have interest in building a library of component/subsystem models that may be "plugged" into larger system models. For an OEM supplier, it is imperative to have the capability to provide subsystem models along with source energy characterized in component blocked force prior to availability of physical parts to support virtual validation and optimization efforts for seamless system integration. In this paper, three methods of blocked force calculation are considered: Direct, Free Velocity and In-situ. A Finite Element Analysis (FEA) model is used to Directly calculate the blocked forces exerted by a rear beam axle at the vehicle attachment points, then to simulate how they might be estimated in a dynamometer test stand using the Free Velocity or In-situ methods, with the aim of offering practical guidance for both scenarios. Assumptions regarding input and output boundary conditions, along with three versus six degree-of-freedom (DOF) attachment paths, affecting both the analytical and test-based estimation of blocked forces, are also scrutinized.

Illuminating Snow Droughts: The Future of Western United States Snowpack in the SPEAR Large Ensemble

AbstractSeasonal snowpack in the Western United States (WUS) is vital for meeting summer hydrological demands, reducing the intensity and frequency of wildfires, and supporting snow‐tourism economies. While the frequency and severity of snow droughts (SD), that is, anomalously low snowpacks, are expected to increase under continued global warming, the uncertainty from internal climate variability remains challenging to quantify with observations alone. Using a 30‐member large ensemble from a state‐of‐the‐art global climate model, the Seamless System for Prediction and EArth System Research (SPEAR), and an observations‐based data set, we find WUS SD changes are already significant. By 2100, SPEAR projects SDs to be nearly 9 times more frequent under shared socioeconomic pathway 5‐8.5 (SSP5‐8.5) and 5 times more frequent under SSP2‐4.5, compared to a 1921–2011 average. By investigating the influence of the two primary drivers of SD, temperature and precipitation amount, we find the average WUS SD will become warmer and wetter. To assess how these changes affect future summer water availability, we track late winter and spring snowpack across WUS watersheds, finding differences in the onset time of a “no‐snow” threshold between regions and large internal variability within the ensemble that are both on the order of decades. We attribute the inter‐regional variability to differences in the regions' mean winter temperature and the intra‐regional variability to irreducible internal climate variability which is not well‐explained by temperature variations alone. Despite strong scenario forcing, internal climate variability will continue to drive variations in SD and no‐snow conditions through 2100.

AUTOMATIC OPERATION OF ON-GRID SOLAR SYSTEM WITH PROTECTION SCHEME

The on-grid solar energy system is becoming a pivotal component of modern electrical grids due to its potential for sustainable energy production and reduced environmental impact. The integration of automatic operation and protection schemes is essential to ensure optimal performance, reliability, and safety of these systems. This research paper delves into the development and implementation of an automatic operation strategy for an on-grid solar system, incorporating a robust protection scheme to mitigate common operational risks. We explore various components and design considerations, detailing the control strategies employed to achieve seamless system function and high performance. A thorough analysis of the data collected from the implemented system highlights the efficacy and reliability of the proposed method. Additionally, the research compares the findings with existing studies to position the results within the broader academic dialogue. Our findings show significant improvements in both the operational efficiency and protection capabilities of the solar system, thus providing valuable insights for future advancements in renewable energy integration. The developed methodologies could lead to enhanced system durability and energy yield, thereby promoting the broader adoption of renewable energy solutions. As we mentioned in Title, we are going to make the Operation of Solar System Automatic with Protection Scheme. This is very beneficial as point of view to on-Grid Solar Systems which is a Need of Today’s World.

A journey with ASMETA from requirements to code: application to an automotive system with adaptive features

Modern automotive systems with adaptive control features require rigorous analysis to guarantee correct operation. We report our experience in modeling the automotive case study from the ABZ2020 conference using the ASMETA toolset, based on the State Machine formal method. We adopted a seamless system engineering method: from an incremental formal specification of high-level requirements to increasingly refined ASMETA models, to the C++ code generation from the model. Along this process, different validation and verification activities were performed. We explored modeling styles and idioms to face the modeling complexity and ensure that the ASMETA models can best capture and reflect specific behavioral patterns. Through this realistic automotive case study, we evaluated the applicability and usability of our formal modeling approach.

Monolithically Defined Wireless Fully Implantable Nervous System Interfaces.

Evolution of implantable neural interfaces is critical in addressing the challenges in understanding the fundamental working principles and therapeutic applications for central and peripheral nervous systems. Traditional approaches utilizing hermetically sealed, rigid electronics and detached electrodes face challenges in power supply, encapsulation, channel count, dispersed application location, and modality. Employing thin-film, wirelessly powered devices is promising to expand capabilities. Devices that forego bulky power supplies, favoring a configuration where electronics are integrated directly onto thin films, reduce displacement volumes for seamless, fully implantable interfaces with high energy availability and soft mechanics to conform to the neuronal target. We discuss 3 device architectures: (1) Highly miniaturized devices that merge electronics and neural interfaces into a single, injectable format; (2) Interfaces that consolidate power, computation, and neural connectivity on a thin sheet applied directly to the target area; (3) A spatially dislocated approach where power and computation are situated subdermally, connected via a thin interconnect to the neural interface.Each has advantages and constraints in terms of implantation invasiveness, power capturing efficiency, and directional sensitivity of power delivery. In powering these devices, near-field power delivery emerges as the most implemented technique. Key parameters are size and volume of primary and secondary antennas, which determine coupling efficiency and power delivery. Based on application requirements, ranging from small to large animal models, subjects require system level designs. Material strategies play a crucial role; monolithic designs, with materials like polyimide substrates, enable scalability with high performance. This contrasts with established hermetic encapsulation approaches that use a stainless steel or titanium box with passthroughs that result in large tissue displacements and prohibit intimate integration with target organ systems. Encapsulation, particularly with parylene, enables longevity and effectiveness; more research is needed to enable human lifetime operation. Implant-to-ambient device communication, focusing on strategies compatible with well-established standards and off-the-shelf electronics, is discussed with the goal of enabling seamless system integration, reliability, and scalability. The interface with the central nervous system is explored through various wireless, battery-free devices capable of both stimulation (electrical and optogenetic) and recording (photometric and electrochemical). These devices show advanced capabilities for chronic studies and insights into neural dynamics. In the peripheral nervous system, stimulation devices for applications, such as spinal and muscle stimulation, are discussed. The challenges lie in the mechanical and electrochemical durability. Examples that successfully navigate these challenges offer solutions for chronic studies in this domain. The potential of wireless, fully implantable nervous system interfaces using near field resonant power transfer is characterized by monolithically defined device architecture, providing a significant leap toward seamless access to the central and peripheral nervous systems. New avenues for research and therapeutic applications supporting a multimodal and multisite approach to neuromodulation with a high degree of connectivity and a holistic approach toward deciphering and supplementing the nervous system may enable recovery and treatment of injury and chronic disease.

Contributions of Tropical Cyclones and Atmospheric Rivers to Extreme Precipitation Trends Over the Northeast US

AbstractThe Northeast United States (NEUS) has faced the most rapidly increasing occurrences of extreme precipitation within the US in the past few decades. Understanding the physics leading to long‐term trends in regional extreme precipitation is essential but the progress is limited partially by the horizontal resolution of climate models. The latest fully coupled 25‐km GFDL (Geophysical Fluid Dynamics Laboratory) SPEAR (Seamless system for Prediction and EArth system Research) simulations provide a good opportunity to study changes in regional extreme precipitation and the relevant physical processes. Here, we focus on the contributions of changes in synoptic‐scale events, including atmospheric rivers (AR) and tropical cyclone (TC)‐related events, to the trend of extreme precipitation in the fall season over the Northeast US in both the recent past and future projections using the 25‐km GFDL‐SPEAR. In observations, increasing extreme precipitation over the NEUS since the 1990s is mainly linked to TC‐related events, especially those undergoing extratropical transitions. In the future, both AR‐related and TC‐related extreme precipitation over the NEUS are projected to increase, even though the numbers of TCs in the North Atlantic are projected to decrease in the SPEAR simulations using the SSP5‐8.5 projection of future radiative forcing. Factors such as enhancing TC intensity, strengthening TC‐related precipitation, and/or westward shift in Atlantic TC tracks may offset the influence of declining Atlantic TC numbers in the model projections, leading to more frequent TC‐related extreme precipitation over the NEUS.

Winter precipitation predictability in Central Southwest Asia and its representation in seasonal forecast systems

In Central Southwest Asia (CSWA; 22°N to 40°N and 30°E to 70°E), winter (November to February) precipitation contributes up to 70% of the annual mean, but substantial interannual variations exist. Dynamical models exhibit subpar predictability in this region, but the limits of their skills are not well established. Here, we identify the tropical and extratropical forcings that explain ~75% of area-averaged seasonal variability in CSWA winter precipitation. Tropical forcing comes from the indirect El Niño-Southern Oscillation (ENSO) pathway, the leading mode of tropical Indian Ocean precipitation variability. This mode is coupled with ENSO-related Pacific Ocean sea surface temperature variability. A direct ENSO influence on CSWA does not extend beyond its Indian Ocean connection. Extratropical forcing comes from a large-scale mode of internal atmospheric variability. The spatial structure, variability of tropical forcing, and teleconnection with CSWA winter precipitation are skillfully depicted in two seasonal forecasting systems: the fifth-generation seasonal forecasting system (SEAS5) and Seamless System for Prediction and Earth System Research (SPEAR). Extratropical forcing’s spatial structure is also produced skillfully in the two modelling systems; however, the representation of its interannual variability and teleconnection requires improvement. While SEAS5 displays skill in representing extratropical forcing influence on CSWA winter precipitation and marginal skill in reproducing interannual variability, SPEAR has negligible ability in both areas. Consequently, these models have limited predictive skills over CSWA in winter. While improvements in representing extratropical forcing may be inherently limited as it arises from internal atmospheric variability, further research is needed to establish its predictability limits fully.

A Lightweight Seamless Unimodal Biometric Authentication System

Nowadays, authentication remains a crucial and primordial process in securing Information Technology (IT) systems and infrastructures, while keeping users’ data more secure and privacy-preserving. Indeed, finding a distinctive characteristic(s) for each individual is done through personal identification and verification. Therefore, techniques such as Two-Factor Authentication (2FA) have been widely used to increase the security level in the authentication processes; where passwords are combined with secret codes or Unimodal Biometrics (UB). In this research study, we consider the case of 2FA based on UB, where the users are mainly asked each time to choose the suited biometric trait for their current authentication process. The thing that can obviously lead to a degradation of the User Experience (UX) and increases the Authentication Time (AT). To overcome these shortcomings, we propose in this article an “Autonomous Unimodal Biometric Authentication System”, abbreviated to “AUBAS”, which is modeled and developed on the basis of discrete-time Markov chains. It is a lightweight and seamless system that allows authenticating users according to two strategies, namely “likelihood” and “weighting”. Eventually, we take a case study and evaluate the system performance with the necessary simulations. Consequently, the implementation of AUBAS allows for improving the UX of an IT system and can be further applied in any environment or process relying on unimodal biometric authentication, such as cloud or mobile computing.

Diagnosing Overlapping and Differing Information for SPEAR and CFSv2 Global Precipitation Forecasts

Global climate models (GCMs) provide valuable forecasts of precipitation around the world. This paper has presented an in-depth investigation of the overlapping versus differing information for 2 sets of GCM forecasts based on the classic set operations. Specifically, by using the coefficient of determination to measure the amount of information of precipitation observations contained in GCM forecast, the common part of the 2 sets of forecasts is quantified by the intersection operation and the unique part of 1 set of forecasts is quantified by the difference operation. A case study is devised for the global precipitation forecasts in December-January-February generated by the Seamless System for Prediction and EArth System Research (SPEAR) and the Climate Forecast System version 2 (CFSv2). Their overlapping and differing information are diagnosed. It is found that significant information common to the 2 sets of forecasts exists over 54.61% of global land grid cells, significant information unique to SPEAR forecasts over 23.59% of global land grid cells, and significant information unique to CFSv2 forecasts over 18.15% of global land grid cells. While the information unique to the SPEAR forecasts suggests that the SPEAR forecasts provide new information compared to the CFSv2 forecasts and the information unique to the CFSv2 forecasts suggests that the CFSv2 forecasts also provide new information compared to the SPEAR forecasts, the common information of the 2 sets of forecasts indicates that they present substantial amount of similar information. Overall, the diagnosis of the overlapping and differing information for different sets of GCM forecasts yields insights into GCM predictive performances.

The impact of Web Api technology on the efficiency of freight transportation

In the contemporary world, where logistics plays a critical role in ensuring the continuity and optimization of freight transportation, WEB API technologies become a crucial tool for enhancing the efficiency of this process. This topic explores the influence of utilizing WEB API on various aspects of logistic processes in freight transportation. It analyzes the role of this technology in increasing speed, accuracy, and simplifying interactions among different participants in the logistic chain. The research covers the impact of WEB API integration on monitoring processes, cargo tracking, route planning, inventory management, and other key logistics aspects. The analysis results can serve as a foundation for developing optimization strategies and implementing innovative solutions in the field of freight transportation. Beyond its operational benefits, the study delves into the challenges and opportunities associated with the adoption of WEB API in the freight industry. Issues such as data security, seamless system integration, and the overall transformation of logistics practices are scrutinized. The analysis not only identifies potential hurdles but also provides strategic insights into mitigating risks and maximizing the benefits of WEB API technology. The implementation of WEB API facilitates precise route planning, optimizing transit times and resource utilization. Furthermore, it streamlines inventory management, offering a dynamic and responsive system that adapts to changing demands. In conclusion, the research findings serve as a comprehensive foundation for developing optimization strategies and implementing innovative solutions in the field of freight transportation. In conclusion, the research findings serve as a comprehensive foundation for developing optimization strategies and implementing innovative solutions in the field of freight transportation. The transformative potential of WEB API technology is evident in its ability to reshape traditional logistic practices, contributing to the evolution of a more efficient, agile, and technologically advanced logistics ecosystem.

Atmospheric River Sequences as Indicators of Hydrologic Hazard in Historical Reanalysis and GFDL SPEAR Future Climate Projections

AbstractWhen multiple atmospheric rivers (ARs) occur in rapid succession, the combined effect on the hydrologic system can lead to more flooding and damage than would be expected from the individual events. This temporally compounding risk is a source of growing concern for water managers in California. We present a novel moving average‐based definition of AR “sequences” that identifies the time periods of elevated hydrologic hazard that occur during and after consecutive AR events. This marks the first quantitative evaluation of when temporal compounding is contributing to AR flood risk. We also assess projected changes in sequence frequency, intensity, and duration in California using the Geophysical Fluid Dynamics Laboratory Seamless System for Prediction and EArth system Research (GFDL SPEAR) global coupled model. Sequence frequency increases over time and is fairly uniform across the state under both intermediate (SSP2–4.5) and very high (SSP5–8.5) emissions scenarios, with the largest changes occurring by the end of the century (+0.72 sequences/year in SSP2–4.5, +1.13 sequences/year in SSP5–8.5). Sequence intensity and duration both see increases in the medians and extreme values of their respective distributions relative to the historical baselines. In particular, “super‐sequence” events longer than 60 days are projected to occur 2–3x more frequently and to emerge in places that have never seen them in the historical record. In a world where California precipitation is becoming more variable, our definition of sequences will help identify when and where hydrologic impacts will be most extreme, which can in turn support better management of the state's highly variable water resources and inform future flood mitigation strategies.

Promoting Coordination and Collaboration in Tribal Home Visiting Programs in the United States.

A joint statement from two federal agencies in the United States calls for coordination and collaboration between programs serving families of infants and toddlers who are at risk or developmentally delayed or disabled U.S. Department of Education and U.S. Department of Health and Human Services. Policy guidance: Joint statement on collaboration and coordination of the MIECHV and IDEA Part C programs. (2017). Individuals with Disabilities Education Act. ED/HHS Joint Guidance Document: Collaboration and Coordination of the Maternal, Infant, and Early Childhood Home Visiting Program and the Individuals with Disabilities Education Act Part C Programs. Young Native American children living on tribal lands in this country are currently eligible for two federal programs associated with these agencies which overlap in mission and implementation. This paper outlines potential strategies for creating a more seamless system of services for tribal families involving more centralized intake processes and procedures, cross training of staff to work across programs, and adopting more unifying approaches to program implementation. A streamlined system of services will result in interventions that better support family and child outcomes while reducing duplication of services, consolidating the limited number of qualified professionals available to provide services, and increasing convenience and cultural attunement of services to Native American families currently participating in both programs.

Shaping the future of chronic disease management: Insights into patient needs for AI-based homecare systems

BackgroundThe rising demand for healthcare resources, especially in chronic disease management, has elevated the importance of Artificial Intelligence (AI) in healthcare. While AI-based homecare systems are being developed, the perspectives of chronic patients, who are one of the primary beneficiaries and risk bearers of these technologies, remain largely under-researched. While recent research has highlighted the importance of AI-based homecare systems, the current understanding of patients’ desired designs and features is still limited. ObjectiveThis paper explores chronic patients’ perspectives regarding AI-based homecare systems, an area currently underrepresented in research. We aim to identify the factors influencing their decision to use such systems, elucidate the potential roles of government and other concerned authorities, and provide feedback to AI developers to enhance adoption, system design, and usability and improve the overall healthcare experiences of chronic patients. MethodA web-based open-ended questionnaire was designed to gather the perspectives of chronic patients about AI-based homecare systems. In total, responses from 181 participants were collected. Using Krippendorff's clustering technique, an inductive thematic analysis was performed to identify the main themes and their respective subthemes. ResultThrough rigorous coding and thematic analysis of the collected responses, we identified four major themes further segmented into thirteen subthemes. These four primary themes were: 1) “Personalized Design”, emphasizing the need for patients to manage their health condition better through personalized and educational resources and user-friendly interfaces; 2) “Emotional & Social Support”, underscoring the desire for AI systems to facilitate social connectivity and provide emotional support to improve the well-being of chronic patients at home; 3) “System Integration & Proactive Care”, addressing the importance of seamless communication, proactive patient monitoring and integration with existing healthcare platforms; and 4) “Ethics & Regulation”, prioritizing ethical guidelines, regulatory compliance, and affordability in the design. ConclusionThis study has offered significant insights into the needs and expectations of chronic patients regarding AI-based home care systems. ‘The findings highlight the importance of personalized and accessible care, emotional and social support, seamless system integration, proactive care, and ethical considerations in designing and implementing such systems. By aligning the design and operation of these systems with the lived experiences and expectations of patients, we can better ensure their acceptance and effectiveness.

Advances in advanced solution‐synthesis‐based structural materials for tactile sensors and their intelligent applications

AbstractIntelligent applications, with tactile sensors at their core, represent significant advancement in the field of artificial intelligence. However, achieving perception abilities in tactile sensors that match or exceed human skin remains a formidable challenge. Consequently, the design and implementation of hierarchical structural materials are considered the optimal solution to this challenge. In contrast to conventional methods, such as complicated lithography and three‐dimensional printing, the cost‐effective and scalable nature of advanced solution‐synthesis methods makes them ideal for preparing diverse tactile sensors with hierarchical structural materials. However, the process and applicability of advanced solution synthesis methods have yet to form a seamless system. Accordingly, the development and intellectualization of tactile sensors based on advanced solution synthesis methods are still in their early stages, and require a comprehensive and systematic review to usher in progress. This study delves into the advantages and disadvantages of various advanced solution synthesis methods, providing detailed insights. Furthermore, the positive effects of hierarchical structural materials constructed using these methods in tactile sensors and their intelligent applications are also discussed in depth. Finally, the challenges and future opportunities faced by this emerging field are summarized.image