Exploring diverse interests of collaborators in smart cities: A topic analysis using LDA and BERT.

Smart cities have emerged as a promising solution to the problems associated with urbanization. However, research that holistically considers diverse stakeholders in smart cities is scarce. This study utilizes data from four types of collaborators (academia, public sector, industry, and civil society actors) to identify key topics and suggest research areas for developing smart cities. We used latent Dirichlet allocation and Bidirectional Encoder Representations from Transformers for topic extraction and analysis. The analysis reveals that sustainability and digital platform have received similar levels of interest from academia, industry, and government, whereas governance, resource, and green space are less frequently mentioned than technology-related topics. Hype cycle analysis, which considers public and media expectations, reveals that smart cities experienced rapid growth from 2015 to 2021, but the growth rate has slowed since 2022. This means that a breakthrough improvement in the current situation is required. Accordingly, we propose resolving the unbalanced distribution of topic interests among collaborators, especially in the areas of governance, environment, economy, and healthcare. We expect that our findings will help researchers, policymakers, and industry stakeholders in understanding which topics are underdeveloped in their fields and taking active measures for the future development of smart cities.

AI technology specialization and national competitiveness.

This study investigates the factors influencing specialization in artificial intelligence (AI) technology, a critical element of national competitiveness. We utilized a revealed comparative advantage matrix to evaluate technological specialization across countries and employed a three-way fixed-effect panel logit model to examine the relationship between AI specialization and its determinants. The results indicate that the development of AI technology is strongly contingent on a nation's pre-existing technological capabilities, which significantly affect AI specialization in emerging domains. Additionally, this study reveals that scientific knowledge has a positive impact on technological specialization, highlighting the necessity of integrating scientific advancements with technological sectors. Although complex technologies positively influence AI specialization, their effect is less pronounced than that of scientific knowledge. This suggests that in rapidly advancing fields, such as AI, incorporating new scientific knowledge into related industries may be more advantageous than simply advancing existing technologies to outpace competitors. This insight points nations toward enhancing AI competitiveness in new areas, emphasizing the vital importance of both scientific and technological capabilities, and the integration of novel AI knowledge with established sectors. This research offers critical guidance for policymakers in less technologically and economically developed countries, as these nations may not have the technological infrastructure required to foster AI specialization through increased technical complexity.

The role of design engineers: Evidence from intra-firm knowledge and collaboration networks.

Successful new product development requires the integration of design and engineering, bridging the gap between technological feasibility and user-centric considerations. However, direct collaboration between designers and engineers with heterogeneous knowledge presents challenges. In this context, the role of design engineers-professionals skilled in both design and engineering-becomes pivotal. This study categorizes inventors into three primary groups: engineers, designers, and design engineers based on the type of patent applications they hold and investigates their differences in knowledge portfolios and collaboration patterns. The study relies on patent data for 4,665 US publicly-traded firms from 1980 to 2015 from the PATSTAT database, and constructs two networks for each firm period: a social network of inventors and a knowledge network of knowledge elements. Findings show that design engineers are highly connected within the social network but have disconnected knowledge in the knowledge network in comparison to engineers. While design engineers may not be the primary drivers of firms' technological innovations, they facilitate interdisciplinary communication and decision-making, fostering a design-technology integrated new product development environment. This research has practical implications for firms seeking to optimize their innovation processes by creating interdisciplinary teams that harness the complementary strengths of engineers and design engineers.

Electricity demand analysis and forecasting: The case of GADA special economic zone.

Ethiopia is a country in East Africa experiencing significant economic growth in recent years, with an increasing electricity demand. Ensuring sustainable and efficient energy for newly developed industries and economic zones is crucial. In this study, a 15-year electric power demand forecast for the new economic zone under construction is conducted. The electrical power demand forecast is done for the year 2025-2040 by using bottom-up forecasting approach for three different scenarios. Long-range Energy Alternatives Planning (LEAP) system software is used to analyze residential, industrial, and general business sector electric power demand. The analysis of the assessed scenario shows that the economic zone's electric power demand increases by 52.2 % from the base year 2025-2040 for the baseline scenario, due to anticipated rapid urbanization, growth in population, economic expansion, and anticipated political stability. Compared to the baseline scenario, the total power demand shows a growth of 68 % from the forecast year (2025) to 2040 for the aggressive scenario, which ensures sustainable and efficient energy options that can draw businesses from both domestic and international baselines. In contrast, the total power demand in the conservative scenario shows a growth of 30.3 % from the base year (2025) to 2040. This reduction in demand compared to the two scenarios indicates a reflection of how much electricity power demand could be if certain development conditions failed to be realized in the economy. In general, both results show a rapid increase in power demand compared to the base year. To address this increasing demand, a supply-side demand analysis can be done for reference and aggressive scenarios. The analysis result indicated that by 2040, supply-side demand from the national grid will increase by 93.5 % and 175.9 % for reference and aggressive scenarios, respectively, compared to the base year 2025 demand. Due to the huge gap between the supply and demand in the country, onsite off-grid generation can be considered to cover 25 % of the demand in the economic zone. Hence, with the support of off-grid generation, the demand from the national grid was reduced to 45 % and 107 % for reference and aggressive scenarios with the support of onsite generation. Hence, this research clearly shows that there is a serious need for large scale electricity generation and distribution planning and preparation to meet the continually increasing electric power demand in a sustainable manner to accommodate the growth and change required to develop the modern economic zones in the country.

Prototype of Monitoring Transportation Pollution Spikes through the Internet of Things Edge Networks.

Air pollution is a critical problem in densely populated urban areas, with traffic significantly contributing. To mitigate the adverse effects of air pollution on public health and the environment, there is a growing need for the real-time monitoring and detection of pollution spikes in transportation. This paper presents a novel approach to using Internet of Things (IoT) edge networks for the real-time detection of air pollution peaks in transportation, specifically designed for innovative city applications. The proposed system uses IoT sensors in buses, cabs, and private cars. These sensors are equipped with air quality monitoring capabilities, including the measurement of pollutants such as particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), and carbon dioxide (CO2). The sensors continuously collect air quality data and transmit them to edge devices within the transportation infrastructure. The data collected by these sensors are analyzed, and alerts are generated when pollution levels exceed predefined thresholds. By deploying this system within IoT edge networks, transportation authorities can promptly respond to pollution spikes, improving air quality, public health, and environmental sustainability. This paper details the sensor technology, data analysis methods, and the practical implementation of this innovative system, shedding light on its potential for addressing the pressing issue of transportation-related pollution. The proposed IoT edge network for real-time air pollution spike detection in transportation offers significant advantages, including low-latency data processing, scalability, and cost-effectiveness. By leveraging the power of edge computing and IoT technologies, smart cities can proactively monitor and manage air pollution, leading to healthier and more sustainable urban environments.

Clinical Implication of Maumgyeol Basic Service-the 2 Channel Electroencephalography and a Photoplethysmogram-based Mental Health Evaluation Software.

Objective: Maumgyeol Basic service is a mental health evaluation and grade scoring software using the 2 channels EEG and photoplethysmogram (PPG). This service is supposed to assess potential at-risk groups with mental illness more easily, rapidly, and reliably. This study aimed to evaluate the clinical implication of the Maumgyeol Basic service. Methods: One hundred one healthy controls and 103 patients with a psychiatric disorder were recruited. Psychological evaluation (Mental Health Screening for Depressive Disorders [MHS-D], Mental Health Screening for Anxiety Disorders [MHS-A], cognitive stress response scale [CSRS], 12-item General Health Questionnaire [GHQ-12], Clinical Global Impression [CGI]) and digit symbol substitution test (DSST) were applied to all participants. Maumgyeol brain health score and Maumgyeol mind health score were calculated from 2 channel frontal EEG and PPG, respectively. Results: Participants were divided into three groups: Maumgyeol Risky, Maumgyeol Good, and Maumgyeol Usual. The Maumgyeol mind health scores, but not brain health scores, were significantly lower in the patients group compared to healthy controls. Maumgyeol Risky group showed significantly lower psychological and cognitive ability evaluation scores than Maumgyeol Usual and Good groups. Maumgyel brain health score showed significant correlations with CSRS and DSST. Maumgyeol mind health score showed significant correlations with CGI and DSST. About 20.6% of individuals were classified as the No Insight group, who had mental health problems but were unaware of their illnesses. Conclusion: This study suggests that the Maumgyeol Basic service can provide important clinical information about mental health and be used as a meaningful digital mental healthcare monitoring solution to prevent symptom aggravation.

Immunologic Aspects of Dyslipidemia: a Critical Regulator of Adaptive Immunity and Immune Disorders.

Dyslipidemia is a major cause of cardiovascular diseases which represent a leading cause of death in humans. Diverse immune cells are known to be involved in the pathogenesis of cardiovascular diseases such as atherosclerosis. Conversely, dyslipidemia is known to be tightly associated with immune disorders in humans, as evidenced by a higher incidence of atherosclerosis in patients with autoimmune diseases including psoriasis, rheumatoid arthritis, and systemic lupus erythematosus. Given that the dyslipidemia-related autoimmune diseases are caused by autoreactive T cells and B cells, dyslipidemia seems to directly or indirectly regulate the adaptive immunity. Indeed, accumulating evidence has unveiled that proatherogenic factors can impact the differentiation and function of CD4+ T cells, CD8+ T cells, and B cells. This review discusses an updated overview on the regulation of adaptive immunity by dyslipidemia and proposes a potential therapeutic strategy for immune disorders by targeting lipid metabolism.

Carrier depletion and exciton diffusion in a single ZnO nanowire.

Carrier depletion and transport in a single ZnO nanowire Schottky device have been investigated at 5 K, using cathodoluminescence measurements. An exciton diffusion length of 200 nm has been determined along the nanowire axis. The depletion width is found to increase linearly with the reverse bias. The origin of this unusual dependence in semiconductor material is discussed in terms of charge location and dimensional effects on the screening of the junction electric field.

M-plane core-shell InGaN/GaN multiple-quantum-wells on GaN wires for electroluminescent devices.

Nonpolar InGaN/GaN multiple quantum wells (MQWs) grown on the {11-00} sidewalls of c-axis GaN wires have been grown by organometallic vapor phase epitaxy on c-sapphire substrates. The structural properties of single wires are studied in detail by scanning transmission electron microscopy and in a more original way by secondary ion mass spectroscopy to quantify defects, thickness (1-8 nm) and In-composition in the wells (∼16%). The core-shell MQW light emission characteristics (390-420 nm at 5 K) were investigated by cathodo- and photoluminescence demonstrating the absence of the quantum Stark effect as expected due to the nonpolar orientation. Finally, these radial nonpolar quantum wells were used in room-temperature single-wire electroluminescent devices emitting at 392 nm by exploiting sidewall emission.