High Level Of Integration Research Articles

Improving the End‐to‐End Protection in E‐Voting Using BVM—Blockchain‐Based E‐Voting Mechanism

ABSTRACTVoting has always been a crucial topic of public attention for democratic reasons. The ease of use and low cost are the result of e‐voting being frequently used for such important decision outcomes. However, the tremendous authority and intervening data in current e‐voting systems make it risky and difficult to achieve correct equity and clarity in e‐voting. So, by combining e‐voting with blockchain technology, these issues can be resolved while providing reorganization and intervention‐resistant characteristics. A voter's improper manipulation, frequent voting, or non‐party voting, may also undermine fairness. A verifier is therefore required to check the e‐voting mechanism in order to ensure its effectiveness and control the process equality and fairness. In this paper, a Blockchain‐based e‐Voting Mechanism (BVM) is developed for providing the end to end security and fairness for transparent voting. This mechanism also provides a zero‐knowledge proof (ZP) based verifier to inspect the voting procedure against voter's mis‐operations and uses a novel Improved Master‐key Administration (IMA) based public key cryptography to attack prevention. The utilization of blockchain technology ensures transparency, anonymity, confidentiality, authentication, tamper resistance, and a high level of data integrity, making it a promising choice for modernizing and enhancing the electoral process. Also, the performance of BVM has been compared with similar voting mechanisms and analyzed based on time complexity, security analysis, performance factors like delay and throughput, and anti‐attack examination.

Teacher's Perception Towards Introducing English Language from First Grade

The importance of English language education as a foreign language (FL) is growing significantly in today's globalized technological world, preparing young children to achieve a high level of social integration and language proficiency. Since English has spread widely internationally, many countries teach English at the elementary level to remain competitive in a global economy and to advance individual and national development. This study examines teachers' perceptions of teaching English to first-grade students. It will be evaluating the opportunities, strengths, and weaknesses of the English as a Foreign Language (EFL) program for first-grade students in Saudi Arabian schools. It will also identify differences between teachers' perceptions of teaching needs. The study relies on the questionnaire as the primary quantitative instrument to gather the data. Results confirm that teachers were outstandingly supportive and agreed with teaching a foreign language in first grade. Regarding the second theme of opportunities, strengths, and weaknesses of the EFL program for first graders in Saudi Arabia, many teachers expected opportunities and improvement for the EFL students in the future. The participants showed an urgent need for either educational courses or the appointment of specialized teachers to teach first-grade

Internally Harmonic Matched Compact GaN Power Amplifier with 78.5% PAE for 2.45 GHz Wireless Power Transfer Systems

In this paper, a high-efficiency compact power amplifier is designed and fabricated with a 0.25 μm GaN high electron mobility transistor (HEMT) to meet the demands of a high integration level and high efficiency for microwave wireless power transfer (WPT) systems. The proposed power amplifier (PA) is implemented using an internally matched method to achieve a compact circuit size. The output second and third harmonic impedances can be optimized through output matching circuits, eliminating the need for additional harmonic matching networks. This approach simplifies the design of matching circuits and reduces the circuit size. Furthermore, the input third harmonic has been controled for improving the efficiency of DC-to-RF conversion. The total size of the proposed PA is 13.4 × 13.5 mm2. The test results obtained from the continuous wave (CW) testing indicate that the output power of the power amplifier at 2.45 GHz reaches 43.75 dBm. Additionally, the large-signal gain is measured at 15.75 dB, and the power-added efficiency (PAE) achieves a value of 78.5%.

Focal volume optics for composite structuring in transparent solids

Abstract Achieving high-level integration of composite micro-nano structures with different structural characteristics through a minimalist and universal process has long been the goal pursued by advanced manufacturing research but is rarely explored due to the absence of instructive mechanisms. Here, we revealed a controllable ultrafast laser-induced focal volume light field and experimentally succeeded in highly efficient one-step composite structuring in multiple transparent solids. A pair of spatially coupled twin periodic structures reflecting light distribution in the focal volume are simultaneously created and independently tuned by engineering ultrafast laser-matter interaction. We demonstrated that the generated composite micro-nano structures are applicable to multi-dimensional information integration, nonlinear diffractive elements, and multi-functional optical modulation. This work presents the experimental verification of highly universal all-optical fabrication of composite micro-nano structures with independent controllability in multiple degrees of freedom, expands the current cognition of ultrafast laser-based material modification in transparent solids, and establishes a new scientific aspect of strong-field optics, namely, focal volume optics for composite structuring transparent solids.

The role of government integrity in the impact of environmental taxes on comparative advantage in environmental goods and climate change in emerging markets

The goal of this study is to examine how environmental taxes influence the comparative advantage in environmental products and carbon emissions within emerging economies. To gain a better understanding, we examine whether this impact changes depending on the level of government integrity. This study utilizes panel autoregressive distributed lag (ARDL) techniques and a two-step generalized method of moments (GMM) dynamic panel model to ensure accuracy. The results indicate that increased environmental taxes mitigate the comparative advantage in environmental goods for emerging markets. However, for countries with high levels of government integrity, higher environmental taxes enhance their competitive edge in environmental goods. Additionally, our findings show that although a rise in environmental taxes is associated with higher carbon emissions, raising such taxes results in a reduction in carbon emissions for emerging economies with solid government integrity. These findings suggest that robust political institutions are crucial in promoting the comparative advantage of emerging markets in environmental goods and mitigating climate change. In the absence of substantial confidence in political or governmental institutions, the efficient implementation of climate taxes poses considerable challenges. Furthermore, we observe that an increase in the comparative advantage of environmental goods results in a decrease in carbon emissions.

Design and experiment of a deviation information detection mechanism for sugar beet harvesters based on agricultural machinery and agronomy integration

To address large geometric shape differences, poor ridge distribution straightness and the uncertain spatial distribution of beet roots during the harvesting period, as well as damage caused by the inaccurate row correction detection mechanisms of combine harvesters, this study conducts a design analysis and performance tests of deviation information detection mechanisms based on the integration of agricultural machinery and agronomy. The agronomic process of mechanized sugar beet production was analyzed, the geometric dimensions of root tubers under typical planting patterns of typical varieties in main sugar beet production areas were measured, and a three-dimensional geometric model of beet root tubers was established. A device for measuring ridge shape and root tuber distribution was designed, and agronomic parameters during the harvesting period, such as plant spacing, ridge height, unearthed height, and deviation distance of beet root tubers, were measured and analyzed. A spatial model of ridge shape and beet root tuber growth distribution on the ridge during harvesting was established. The overall structure of the deviation information detection mechanism was analyzed and designed, and the structural forms and key parameters of key mechanisms, such as left‒right swing detection and up‒down floating profiling, were designed on the basis of agronomic parameter analysis. Using the missed detection rate as the evaluation index, field performance tests of the deviation information detection mechanism were conducted. The results revealed that when the average forward speed of the harvester was 0.84 m/s, the average missed detection rate of the deviation information detection mechanism was 0.56%. This method has high adaptability and detection accuracy and achieves a high level of integration for agricultural machinery (detection spatial region of the detection mechanism) and agronomy (beet root distribution spatial region). This study provides a technical basis and methodological reference for improving the quality and efficiency of automatic row correction combined with harvesting operations for crops such as sugar beets.

A fully integrated breathable haptic textile.

Wearable haptics serve as an enhanced media to connect humans and VR/robots. The inevitable sweating issue in all wearables creates a bottleneck for wearable haptics, as the sweat/moisture accumulated in the skin/device interface can substantially affect feedback accuracy, comfortability, and create hygienic problems. Nowadays, wearable haptics typically gain performance at the cost of sacrificing the breathability, comfort, and biocompatibility. Here, we developed a fully integrated breathable haptic textile (FIBHT) to solve these trade-off issues, where the FIBHT exhibits high-level integration of 128 pixels over the palm, great stretchability of 400%, and superior permeability of over 657 g/m2/day (moisture) and 40 mm/s (air). It is a stand-alone haptic system totally composed of stretchable, breathable, and bioadhesive materials, which empowers it with precise, sweating/movement-insensitive and dynamic feedback, and makes FIBHT powerful for virtual touching in broad scenarios.

Predictors of oral healthcare utilization and satisfaction among Indian migrants and the host population in the Netherlands

BackgroundThe aim of this study was to explore predictors associated with reasons for visiting an oral healthcare professional (OHP) and satisfaction with OHPs in the Netherlands among the Indian migrants and the host population.MethodsA random sample was obtained for this cross-sectional questionnaire study. Variables were classified according to the Andersen Behavioural Model of Health Services Utilization. Multivariable binary logistic regression analysis was conducted to identify significant predictors for reasons for visiting an oral healthcare professional (OHP) (routine checkups and preventive care or visiting only for pain and/or treatment) and satisfaction with OHPs (satisfied or dissatisfied).ResultsThe sample consisted of 391 participants (Indian migrants = 147 and host population = 244). Indian migrants with higher internal locus of control (LoC) [OR = 7.73 (95% CI: 2.13;27.99)], more trust in OHPs [OR = 4.12 (95% CI:1.68;10.14)] and higher integration level [OR = 1.09 (95% CI:1.03;1.17)] had higher odds of visiting an OHP for routine checkups and preventive care. In the host population, having dental insurance [OR = 2.64 (95% CI:1.00;6.95)] was significantly associated with increased odds of visiting an OHP for routine checkups and preventive care. For satisfaction, Indians with low paid jobs [OR = 16.26 (95% CI:2.83;93.36)] and those with higher integration levels [OR = 1.29 (95% CI:1.16;1.42)] had higher odds of being satisfied with the Dutch OHPs. Among the host population, those with more trust in OHPs [OR = 2.86 (95% CI:1.19;6.88)] had higher odds of being satisfied.ConclusionOur study emphasize that integration levels and trust emerged as two crucial factors, policy makers can leverage upon to improve access to care for Indian migrants.Clinical trialN.A as this is a survey based cross sectional study.

The SME R&D intensity and product innovation relationship: the mediating role of quality management in the context of a developing country

SMEs engage in product innovation despite their inherent resource constraints, lack of financial slack, and the under‐development of competitively viable strategic configurations around the globe. While progress has been made in identifying the antecedents and capabilities attributed to successful innovation outcomes and the performance of these firms, there remain disparate and often paradoxical observations on the factors that affect SME innovation performance across geographies (i.e. developed vs developing countries) and operational contexts (R&D intensity and quality management practices). This study collected data from 241 resource‐constrained small and medium‐sized enterprises (SMEs) in a developing country (Ghana) to contribute to this debate. The results of structural equation modeling show that quality management mediates the relationship between R&D intensity and product innovation. The results also reveal the effects of knowledge integration and financial slack on the relationship between R&D intensity and product innovation, with a high level of knowledge integration enhancing the effect but a high financial slack hinders it. This study sheds light on a broader range of contextual and financial variables when seeking contingencies of SME product innovation performance within theory and practice.

Optimal solution of multiobjective stable environmental economic power dispatch problem considering probabilistic wind and solar PV generation

The Environmental Economic Power Dispatch (EEPD) problem, a widely studied bi-objective nonlinear optimization challenge in power systems, traditionally focuses on the economic dispatch of thermal generators without considering network security constraints. However, environmental sustainability necessitates reducing emissions and increasing the penetration of renewable energy sources (RES) into the electrical grid. The integration of high levels of RES, such as wind and solar PV, introduces stability issues due to their uncertain and intermittent nature. This paper addresses these concerns by formulating and solving the Stable Environmental Economic Power Dispatch (SEEPD) problem, which includes fixed zonal reserve capacity from conventional thermal generators and uncertain reserves from RES. Uncertainties in RES and load demand are modeled using random variable generation techniques, applying Gaussian, Weibull, and log-normal probability density functions (PDFs) for load demand, wind velocity, and solar irradiance, respectively. The stochastic SEEPD problem extends to multiple periods by replicating the single-period problem for each interval in the planning horizon, linking periods through intertemporal ramping costs, physical ramp rate, and fixed zonal reserve constraints on dispatch variables. Multi-Objective Evolutionary Algorithms (MOEAs) have gained importance for solving complex nonlinear problems involving multi-objective functions. This paper applies the latest MOEAs to tackle the proposed SEEPD problem, incorporating stochastic wind and solar PV power sources. Network security constraints, such as transmission line capacities and bus voltage limits, are considered along with constraints on generator capabilities and intertemporal spinning reserves, ramp-up and ramp-down constraints for thermal generators. A bidirectional coevolutionary-based multi-objective evolutionary algorithm is employed, integrating an advanced constraint-handling technique to ensure compliance with system constraints. The simulation results show that the proposed formulation achieves a better trade-off between various conflicting objective functions compared to other state-of-the-art MOEAs.

Calibrating Ukraine’s Growth Model: How Can Ukraine Emulate Poland’s Growth?

This study provides a comparative analysis of the economic growth paths of Ukraine and Poland from a growth‑model perspective and determines how to calibrate Ukraine’s growth model to converge with Poland’s booming economy. The methodology comprises an approach to operationalizing growth models for GDP growth decomposition into “import‑adjusted” demand components, drawing on national input‑output data from 2000 to 2019. I found that from 2000 to 2003, both European economies relied on a combination of exports and domestic consumption. Expanded trade integration and an FDI boost after Poland joined the EU in 2004 spurred the Polish growth model’s shift to a distinctively export‑led, FDI‑driven strategy with accelerated GDP growth rates. In Ukraine, in the wake of the great financial crisis, I identified a transition to a consumption‑led growth model that, along with a declining investment component of aggregate demand, led to fading growth rates. An analysis of sectoral contributions to GDP growth revealed that avoiding deindustrialization in Poland underpinned the country’s export‑led strategy, unlike Ukraine, which underwent a key sectoral shift from manufacturing to a commodities‑based orientation after 2008. Both these economies demonstrated a high level of integration into global value chains, focusing on labor‑intensive manufacturing and services, but Poland has outperformed Ukraine in terms of share of high value‑added exports, which increased after EU accession. Following the Polish pattern, I propose that Ukraine’s growth model should activate the FDI driver of economic growth, upgrading the export structure and moving up value chains to unlock the country’s growth opportunities. The study represents the first comparison of Ukraine’s and Poland’s economic growth paths that traces the changes in dominant final demand components and macro‑sectors in the two countries’ economic growth profiles. This paper contributes to the comparative political economy literature on the growth models of peripheral economies, providing insights that can inform policies for growth model transformation.

Public City as Network of Networks: A Toolkit for Healthy Neighbourhoods

The distinction between the current urban crisis and that which emerged in the latter half of the last century lies in the rise of environmental concerns linked to the climate crisis, which compound the existing socioeconomic issues. The “new urban question”, in its intersectional sense, necessitates high levels of integration, interdisciplinarity, interscalarity, and iterativity to recompose the physical and socioeconomic components of change. In this regard, the proposed contribution aims to develop a transferable methodology to guide urban regeneration actions that are sustainable from a socio-economic and environmental perspective, capable of leading to the creation of “Healthy Neighbourhoods”. This objective is pursued by the authors through the definition of a toolkit of design parameters to assess the improvement of an urban area before and after the regeneration intervention. Indeed, each proposed parameter affects one or more of the ten indicators used to evaluate the health of a neighbourhood. The proposed methodology will later be tested, in subsequent phases of the research, on the case study of Pietralata (Rome, Italy).

The role of technology in modern industrial processes: a comparative analysis of automated, automatic and mechanical systems

In the modern technological sphere, systems are categorized into various types based on their level of complexity and functional capabilities. The primary types are mechanical, automatic, and automated systems. Each of these types has its unique characteristics and areas of application. Mechanical systems are the simplest of all. They consist primarily of physical components such as gears, levers, and springs, which interact to perform specific tasks. These systems typically lack built-in control or regulation mechanisms, and their operation is based on basic mechanical principles. Examples of mechanical systems include simple clock mechanisms or traditional measuring devices. Automatic systems represent an evolutionary step beyond mechanical systems, as they include elements for automatic control. These may be electrical or electronic components that enable the system to perform certain operations without direct human intervention. For example, automatic doors or thermostats that regulate room temperature are examples of such systems. They can respond to changing conditions and perform tasks based on predefined parameters. Automated systems, in turn, are the most complex and integrated. They combine automatic control with software and advanced management systems, allowing them to adapt to changing environmental conditions and make decisions independently. Automated systems may include elements of artificial intelligence and machine learning, enabling them to perform complex tasks such as data processing or optimizing production processes. Examples include industrial robotic lines or management systems in distribution networks. Thus, the main differences between these systems lie in their level of complexity and functional capabilities: mechanical systems are based on simple physical principles, automatic systems contain elements of automatic control, and automated systems provide a high level of integration and autonomy.

Assessing the Impact of Artificial Intelligence Tools on Employee Productivity: Insights from a Comprehensive Survey Analysis

This study provides a nuanced understanding of AI’s impact on productivity and employment using machine learning models and Bayesian Network Analysis. Data from 233 employees across various industries were analyzed using logistic regression, Random Forest, and XGBoost, with 5-fold cross-validation. The findings reveal that high levels of AI tool usage and integration within organizational workflows significantly enhance productivity, particularly among younger employees. A significant interaction between AI tools usage and integration (β = 0.4319, p < 0.001) further emphasizes the importance of comprehensive AI adoption. Bayesian Network Analysis highlights complex interdependencies between AI usage, innovation, and employee characteristics. This study confirms that strategic AI integration, along with targeted training programs and ethical frameworks, is essential for maximizing AI’s economic potential.

COMPARATIVE ANALYSIS OF SMART ECONOMY DEVELOPMENT IN SELECTED COUNTRIES OF SOUTHEAST ASIA

Research subject. The development of the global economy indicates the formation of a new trend in the formation of the smart economy, which currently covers both developed and developing countries. According to the analysis, developed countries are leaders in economic development precisely because of the development of technologies that are the basis for the formation of the smart economy and the smart intellectualisation of economic activity. The smart economy in Asia is actively developing due to the intensive introduction of the latest technologies, innovative management approaches, and increased resource efficiency. Asian countries such as China, Japan, South Korea, Singapore, and India are leaders in the development of the smart economy. At the same time, Asian countries have been demonstrating one of the highest rates of economic development since the beginning of the XXI century, which is primarily due to the active technologisation of production and the spread of communication technologies in all areas of economic activity. Several technology centres are emerging in Asia, concentrating technology companies and creating a favourable environment for the development of the smart economy. Methodology. The article conducts a comparative analysis of the factors contributing to the development of the smart economy in individual Asian countries, identifies the most influential factors and the degree of their impact on each country. The purpose of this study is to identify the factors influencing the development of the smart economy and compare their impact in the economies of China, India and Singapore. To achieve this goal, the following research objectives are envisaged: to identify factors that have a significant impact on the development of the smart economy in different countries; to assess the impact of individual factors on the development of the smart economy in China, India and Singapore; to compare the impact of individual factors of the smart economy on the economies of these countries; and to assess the models of smart economy development in China, India and Singapore. Conclusion. The smart economy in Asia is characterised by unique features that reflect the cultural, technological and economic conditions of the region. The key features of the Asian smart economy include a high level of digitisation and technological integration, active development of smart cities, financial technologies (FinTech), a focus on automation and robotics, innovation hubs and support for start-ups, environmental sustainability and green energy, and the digitalisation of governance and public services. Asian countries are also distinguished by the integration of smart technologies into the everyday life of citizens and the support of innovation ecosystems at the state level.

ANALYSIS OF INVESTMENT ACTIVITIES IN THE AGRICULTURAL SECTOR OF UKRAINE: DETERMINATION OF FACTORS AND WAYS OF ITS ACTIVATION

The purpose of the article is to study the theoretical aspects of investment activity, analyse the current level of investment activity in the agricultural sector of Ukraine's economy and identify factors and methods of its increase. Methodology. The theoretical and methodological basis of the study is the fundamental principles of national economic management, investment activity and development of agricultural production entities. The research used the following scientific methods: axiomatic (to establish basic definitions that clarify the essence of the study), systematic (to identify components within the agricultural production sector), institutional (to construct the subject-object framework of the institutional environment for investment activity in agricultural production), correlation-regression analysis (to identify key predictors influencing investment activity in the agricultural sector), abstraction (to prioritise the stimulation of investment activity in agricultural production), and reproductive (to substantiate alternative strategies for attracting investment in agricultural enterprises). The results of the study show that diversification of investment sources and modernisation of technological infrastructure of agricultural production are important prerequisites for institutional reforms in the agricultural sector of the country. Increasing investment activity in agricultural enterprises can be achieved by creating a favourable investment climate. This includes government initiatives to create a transparent and stable regulatory framework, simplify bureaucratic processes, and ensure legal and financial stability. Another key aspect is to facilitate access to financial instruments such as low-interest loans, grants and subsidies to support the development of agricultural enterprises. The results of the study are presented in the form of tables, figures, graphs, diagrams and charts. Practical implications. Given the high level of integration of the domestic agricultural sector into the global food market, it is worth exploring the potential of using customs instruments to stimulate investment processes. Such instruments could include a zero VAT rate for investment agricultural goods and measures to prevent double taxation. Value / Оriginality. Investment activity in Ukraine can be intensified under the following conditions: ensuring financing for innovations; developing and implementing a system of measures to increase the investment activity of commercial banks; promoting the development of the stock market and venture capital; developing investment infrastructure; borrowing the best international experience in assessing the efficiency of business centres and business incubators; forming an investment and innovation culture in society, etc.

Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis

Gingivitis—the inflammation of the gums—is a reversible stage of periodontal disease. It is caused by dental plaque formation due to poor oral hygiene. However, gingivitis susceptibility involves a complex set of interactions between the oral microbiome, oral metabolome and the host. In this study, we investigated the dynamics of the oral microbiome and its interactions with the salivary metabolome during experimental gingivitis in a cohort of 41 systemically healthy participants. We use Parallel Factor Analysis (PARAFAC), which is a multi-way generalization of Principal Component Analysis (PCA) that can model the variability in the response due to subjects, variables and time. Using the modelled responses, we identified microbial subcommunities with similar dynamics that connect to the magnitude of the gingivitis response. By performing high level integration of the predicted metabolic functions of the microbiome and salivary metabolome, we identified pathways of interest that describe the changing proportions of Gram-positive and Gram-negative microbiota, variation in anaerobic bacteria, biofilm formation and virulence.

Analysis of genotyping data reveals the unique genetic diversity represented by the breeds of sheep native to the United Kingdom

BackgroundSheep breeds native to the United Kingdom exhibit a striking diversity of different traits. Some of these traits are highly sustainable, such as seasonal wool shedding in the Wiltshire Horn, and are likely to become more important as pressures on sheep production increase in coming decades. Despite their clear importance to the future of sheep farming, the genetic diversity of native UK sheep breeds is poorly characterised. This increases the risk of losing the ability to select for breed-specific traits from native breeds that might be important to the UK sheep sector in the future. Here, we use 50 K genotyping to perform preliminary analysis of breed relationships and genetic diversity within native UK sheep breeds, as a first step towards a comprehensive characterisation. This study generates novel data for thirteen native UK breeds, including six on the UK Breeds at Risk (BAR) list, and utilises existing data from the publicly available Sheep HapMap dataset to investigate population structure, heterozygosity and admixture.ResultsIn this study the commercial breeds exhibited high levels of admixture, weaker population structure and had higher heterozygosity compared to the other native breeds, which generally tend to be more distinct, less admixed, and have lower genetic diversity and higher kinship coefficients. Some breeds including the Wiltshire Horn, Lincoln Longwool and Ryeland showed very little admixture at all, indicating a high level of breed integrity but potentially low genetic diversity. Population structure and admixture were strongly influenced by sample size and sample provenance – highlighting the need for equal sample sizes, sufficient numbers of individuals per breed, and sampling across multiple flocks. The genetic profiles both within and between breeds were highly complex for UK sheep, reflecting the complexity in the demographic history of these breeds.ConclusionOur results highlight the utility of genotyping data for investigating breed diversity and genetic structure. They also suggest that routine generation of genotyping data would be very useful in informing conservation strategies for rare and declining breeds with small population sizes. We conclude that generating genetic resources for the sheep breeds that are native to the UK will help preserve the considerable genetic diversity represented by these breeds, and safe-guard this diversity as a valuable resource for the UK sheep sector to utilise in the face of future challenges.

Social relationships and their impact on health-related quality of life in a long-term breast cancer survivor cohort.

Health-related quality of life (HRQOL) has become increasingly important for breast cancer survivors, but clinically relevant declines often persist for many years after treatment. This study aimed to investigate whether social relationships can mitigate or prevent this decline in HRQOL. Data were used from the German population-based Mamma Carcinoma Risk Factor Investigation (MARIE) cohort of 2022 breast cancer cases with follow-up information for more than 15 years after diagnosis. Correlations between social integration, social support, and global health status (GHS) as an overall measure of HRQOL were analyzed, and linear regression analysis was performed with structural equation modeling. The majority of participants reported high levels of social integration and social support and moderate levels of GHS. Social integration 5 years after diagnosis was associated with GHS 5 years after diagnosis (β=1.12; 95% CI,0.25-1.99), but no longitudinal effects were found. Social support 5 years after diagnosis was associated with better GHS 5 years (β=0.42; 95% CI,0.36-0.48) and 10 years after diagnosis (β=0.12; 95% CI,0.02-0.22), whereas social support 10 years after diagnosis was associated with GHS 10 years (β=0.29; 95% CI,0.20-0.39) and 15 years after diagnosis (β=0.10; 95% CI,0.01-0.21). These results confirm that social relationships positively influence HRQOL in long-term breast cancer survivors and that their association should receive more attention clinically and beyond routine care.

Hitless two-dimensional focal plane switch array based on Mach-Zehnder interferometer-embedded micro-ring resonators

Empowered by compact micro-ring (MRR) arrays, wavelength-division-multiplexing (WDM)-based focal plane switch array (FPSA) chip is a promising solution for light detection and ranging (LiDAR) due to its parallelism and high-level integration. However, an MRR channel with a shifting central wavelength may interrupt another channel by dropping an optical signal with an unexpected wavelength, which causes discontinuous beam scanning. To overcome this bottleneck, we propose and fabricate a hitless two-dimensional (2-D) FPSA chip based on a 2 × 8 Mach-Zehnder interferometer-embedded micro-ring resonator (MZER) array. The FPSA chip realizes a beam divergence of 0.18° × 0.05°, a field of view (FoV) of 9.07° × 6.42° with single-ended emission, and a FoV of 10.75° × 6.42° with dual-ended field-of-view splicing technology. Besides, we demonstrate the hitless function of our FPSA chip by performing continuous wavelength sweeping and further applying it to a free-space optical communication link. The experimental results validate the feasibility of our proposed hitless FPSA chip, which efficiently prevents signal interruptions during beam steering.