Hasil untuk "Labor systems"

V. V. Chari, Patrick J. Kehoe, Ellen R Mcgrattan

J. Conesa, S. Kitao, Dirk Krueger

V. Raghupathi, W. Raghupathi

This research explores the association of public health expenditure with economic performance across the United States. Healthcare expenditure can result in better provision of health opportunities, which can strengthen human capital and improve the productivity, thereby contributing to economic performance. It is therefore important to assess the phenomenon of healthcare spending in a country. Using visual analytics, we collected economic and health data from the Bureau of Economic Analysis and the Bureau of Labor Statistics for the years 2003–2014. The overall results strongly suggest a positive correlation between healthcare expenditure and the economic indicators of income, GDP, and labor productivity. While healthcare expenditure is negatively associated with multi-factor productivity, it is positively associated with the indicators of labor productivity, personal spending, and GDP. The study shows that an increase in healthcare expenditure has a positive relationship with economic performance. There are also variations across states that justify further research. Building on this and prior research, policy implications include that the good health of citizens indeed results in overall better economy. Therefore, investing carefully in various healthcare aspects would boost income, GDP, and productivity, and alleviate poverty. In light of these potential benefits, universal access to healthcare is something that warrants further research. Also, research can be done in countries with single-payer systems to see if a link to productivity exists there. The results support arguments against our current healthcare system's structure in a limited way.

B. Aczél, Barnabas Szaszi, Alexander O Holcombe

The amount and value of researchers’ peer review work is critical for academia and journal publishing. However, this labor is under-recognized, its magnitude is unknown, and alternative ways of organizing peer review labor are rarely considered. Using publicly available data, we provide an estimate of researchers’ time and the salary-based contribution to the journal peer review system. We found that the total time reviewers globally worked on peer reviews was over 100 million hours in 2020, equivalent to over 15 thousand years. The estimated monetary value of the time US-based reviewers spent on reviews was over 1.5 billion USD in 2020. For China-based reviewers, the estimate is over 600 million USD, and for UK-based, close to 400 million USD. By design, our results are very likely to be under-estimates as they reflect only a portion of the total number of journals worldwide. The numbers highlight the enormous amount of work and time that researchers provide to the publication system, and the importance of considering alternative ways of structuring, and paying for, peer review. We foster this process by discussing some alternative models that aim to boost the benefits of peer review, thus improving its cost-benefit ratio.

Qi Li, Chongxuan Ma

As an important form of agricultural socialized services, land trusteeship has increasingly become a key institutional arrangement influencing farm household welfare in developing countries. However, existing studies often treat farm households as homogeneous decision-making units and pay limited attention to how intra-household structural differences shape the effects of land institutional arrangements. By incorporating the perspectives of gender roles and intergenerational relations, this study examines how land trusteeship influences farm household consumption structure through intra-household resource allocation mechanisms. Based on first-hand cross-sectional survey data from 856 farm households in Shandong Province, China, this study employs the Endogenous Switching Model to identify the causal effects of land trusteeship and further explores the pathways through which intra-household labor allocation and resource transformation efficiency shape these effects. The results show that: (1) land trusteeship significantly improves household consumption structure, and this finding remains robust after controlling for endogeneity and conducting a series of robustness checks; (2) from the perspective of resource allocation pathways, male engagement in non-agricultural employment and the “dual role” of women in both non-agricultural work and family care serve as effective channels through which land trusteeship enhances household consumption structure; and (3) in terms of resource transformation efficiency, the effect of land trusteeship on improving consumption structure is particularly evident in households with intergenerational childcare responsibilities, but insignificant in households with intergenerational financial support obligations. Further analysis shows that higher levels of intergenerational geographic and educational mobility weaken the positive impact of land trusteeship, while an increase in the number of children amplifies it. Accordingly, differentiated trusteeship services should be provided based on household structure, and gender-sensitive rural labor policies and social security support systems should be strengthened.

S. Sang, S. Sang, Y. Li et al.

<p>Modeling the coupled human–natural systems (CHANS) is vital for understanding human–natural interactions and achieving regional sustainability, offering a powerful tool to alleviate human–water conflicts, ensuring food security, thereby supporting the region's pathway toward sustainable development. However, the scarcity of regional-scale CHANS models constrains progress in practical applications for regional sustainability. The Yellow River basin (YRB) is an ideal region for modeling regional CHANS due to its closely coupled human and natural systems, which are stressed by water and ecosystem fragility. Here, we developed the CHANS-SD-YRB model using the System Dynamics approach, integrating 10 sectors essential for modeling human-water interactions of the basin, including five human sectors (Population, Economy, Energy, Food, and Water Demand) and five natural sectors (Water Supply, Sediment, Land, Carbon, and Climate). The model can simulate evolution and feedbacks of the YRB CHANS annually at provincial and sub-basin scales, while conserving hydrological connectivity between sub-basins. The model can accurately reproduce historical CHANS dynamics, achieving strong quantitative agreement with historical data (<span class="inline-formula"><i>R</i></span> <span class="inline-formula">&gt;</span> 0.95 for human sectors and <span class="inline-formula"><i>R</i></span> <span class="inline-formula">&gt;</span> 0.7 for natural sectors), which supports its applicability for scenario analyses and future projections. We applied the model to explore human–natural system dynamics under a future baseline scenario, assuming the continuation of existing policies and climate projection under middle of the road scenario (SSP–RCP 2-4.5). The future projections (2021–2100) indicate that achieving sustainable development in the YRB will remain challenging, though economic growth and food security are expected to improve. Emerging issues, such as ecological–human water trade-offs, labor shortages, reduced sediment loads, and limited carbon absorption capacity, may hinder regional long-term sustainability, underscoring the need for integrated policies to address these challenges.</p>

Mingxuan Li, Wei Wei, Yin Xu et al.

Extreme events such as earthquakes pose significant threats to integrated electricity-gas distribution systems (IEGDS) by causing widespread damage. Existing restoration approaches typically assume full awareness of damage, which may not be true if monitoring and communication infrastructures are impaired. In such circumstances, field inspection is necessary. This paper presents a novel adaptive restoration framework for IEGDS, considering dynamic damage assessment and repair. The restoration problem is formulated as a partially observable Markov decision process (POMDP), capturing the gradually revealed contingency and the evolving impact of field crew actions. To address the computational challenges of POMDPs in real-time applications, an advanced belief tree search (BTS) algorithm is introduced. This algorithm enables crew members to continuously update their actions based on evolving belief states, leveraging comprehensive simulations to evaluate potential future trajectories and identify optimal inspection and repair strategies. Based on the BTS algorithm, a unified real-time decision-making framework is developed for IEGDS restoration. Case studies on two distinct IEGDS systems demonstrate the effectiveness and scalability of the proposed method. The results indicate that the proposed approach achieves an outage cost comparable to the ideal solution, and reduces the total outage cost by more than 15% compared to strategies based on stochastic programming and heuristic methods.

Ibrahim Denis Fofanah

Automated resume screening systems are now a central part of hiring at scale, yet there is growing evidence that rigid screening logic can exclude qualified candidates before human review. In prior work, we introduced the concept of Artificial Frictional Unemployment to describe labor market inefficiencies arising from automated recruitment systems. This paper extends that framework by focusing on measurement. We present a method for quantifying algorithmic friction in resume screening pipelines by modeling screening as a classification task and defining friction as excess false negative rejection caused by semantic misinterpretation. Using controlled simulations, we compare deterministic keyword-based screening with vector-space semantic matching under identical qualification conditions. The results show that keyword-based screening exhibits high levels of algorithmic friction, while semantic representations substantially reduce false negative rejection without compromising precision. By treating algorithmic friction as a system-level property, this study provides an empirical basis for evaluating how recruitment system design affects matching efficiency in modern labor markets.

Alfarooq Al Oide, Dmitry Manasreh, Mohammad Karasneh et al.

Roadside incidents are a leading cause of driver fatalities in the United States, with a significant number involving collisions with barriers, such as guardrails. Guardrails are essential safety barriers designed to maintain vehicle trajectories and shield against roadside hazards. The functionality of guardrails heavily relies on their structural integrity, and damaged guardrails can pose serious dangers to road users. Traditional inspection methods are labor-intensive, time-consuming, and prone to human error, lacking periodic monitoring crucial for timely maintenance. Although advancements in computer vision have enabled automated infrastructure inspections, research dedicated specifically to the inspection of guardrails remains scarce. Existing automated solutions do not fully address the challenges of accurately identifying and assessing guardrail damage under varying lighting and weather conditions and the computational demands of real-time processing. This study addresses these challenges by introducing a novel framework utilizing advanced computer vision techniques, such as YOLOv8 models and the Deep OC–SORT tracker, integrated with camera and GPS systems mounted on a vehicle. This system automates the detection, localization, and severity assessment of guardrail damage, enhancing inspection accuracy and efficiency, enabling faster maintenance responses, and ultimately contributing to safer road conditions.

Kevin Kamau, Benjamin Thorpe, Katie E. Meier et al.

Automated feeding robots (AFR) are increasingly being used on North American dairy farms to reduce dependency on human labor for feeding. These systems mix, deliver, and push up feed to cows at any frequency or interval desired, allowing for more frequent feed delivery than conventional feeding systems (CFS). This observational study investigated differences in ration consistency, milk components, milk fatty acid profile, and cow behavior between herds using AFR and those using CFS. Sixteen commercial dairies with automated milking systems (AMS) in the upper Midwest United States were paired based on herd size and location into eight blocks each consisting of one CFS and one AFR herd. Feed bunk samples were collected at four equally spaced time points for 3 consecutive d and analyzed for coefficient of variation (CV) of nutrient composition and particle size distribution. Bulk tank milk samples were collected 1 ×/d for 3 d and analyzed for fat, protein, milk urea nitrogen (MUN), lactose, and milk fatty acid (FA) profile. Daily AMS visit intervals, milk yield and composition, and rumination time data were collected from AMS software. A linear mixed model tested fixed effects of feeding system, block, and the random effect of day nested within block. The CV of feed bunk DM, ADF, NDF, and lignin was lower in AFR. Bulk tank milk fat, protein, and MUN were not different between AFR or CFS. AFR had a greater proportion of de novo synthesized FA, but no difference in preformed or mixed FA. Herds with AFR had a shorter AMS visit interval with more AMS refusals per day than CFS. Results imply that AFR may be associated with lower daily variation in fiber concentration at the feed bunk, increased mammary de novo fatty acid synthesis, and increased frequency of cow visits to the AMS compared to conventional PMR feeding.

Razi Ullah, Razi Ullah, Mubassir Khan et al.

Cardiovascular disease (CVD) represents a significant global health challenge, making the detection of cardiac biomarkers crucial for early diagnosis and tailored treatment strategies. This research aims to transpire a point-of-care (POC) test using a biosensor for CVDs that will be fast and pragmatic for immediate use in acute and resource-constrained environments. Traditional techniques such as enzyme-linked immunosorbent assay and polymerase chain reaction, although very precise, are time-consuming, labor intensive, and not suitable for use in urgent care; however, optical nano biosensors provide rapid, highly selective, and sensitive detection capabilities. The optical nano biosensors produce biological signals that convey light signals as analytes interact with bioreceptors. Optical nano biosensors offer various benefits, including effortless monitoring, inexpensiveness, a broad detection spectrum, and excellent sensitivity with no interference. An optical nano biosensor platform represents an effective method for point-of-care detection of cardiac biomarkers, characterized by a low detection limit. To propose a realistic reference, this study assesses a prompt POC test, which identifies important cardiac biomarkers, such as cardiac troponins (cTnI), B-type natriuretic peptide (BNP), and C-reactive protein (CRP), which together provide an all-encompassing confinement of myocardial injury, cardiac stress, and inflammation. Subsequently, the test was performed using a random patient population; the accuracy of the test was established to be high in terms of both sensitivity (95.2% for cTnI, 91.8% for BNP, and 89% for CRP) and specificity and had a close correlation with laboratory tests. It provided results in 15 min, which makes it effectively useful when used in emergency and primary care, where quick decisions are required to be taken. The low cost and rapidity of the test increase its applicability notably; this multiplexing allows clinicians to identify individuals at high risk for different CVD events. This work highlights the possibility of incorporating biosensor technology into diagnostic systems at the POC level to enhance patient prognosis by facilitating early interventions and establishes a basis for improving biomarker detection.

Sejal Bhattad, Ahmed Abdelmoamen Ahmed, Ahmed A. A. Abdel-Wareth et al.

It is critical to provide proper environmental conditions in poultry houses to maintain birds’ health, boost productivity, and improve the overall economic viability of the poultry industry. Among the myriad of environmental elements, indoor air quality has been a determining factor that directly affects poultry well-being. Elevated concentrations of harmful gases—in particular Carbon Dioxide (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi><msub><mi>O</mi><mn>2</mn></msub></mrow></semantics></math></inline-formula>), Methane (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi><msub><mi>H</mi><mn>4</mn></msub></mrow></semantics></math></inline-formula>), and Ammonia (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>N</mi><msub><mi>H</mi><mn>3</mn></msub></mrow></semantics></math></inline-formula>)—decomposition products of poultry litter, feed wastage, and biological processes have draconian effects on bird health, feed efficiency, the growth rate, reproduction efficiency, and mortality rate. Despite their importance, traditional air quality monitoring systems are often operated manually, labor intensive, and cannot detect sudden environmental changes due to the lack of real-time sensing. To overcome these limitations, this paper presents an interdisciplinary approach combining cloud computing, Artificial Intelligence (AI), and Internet of Things (IoT) technologies to measure real-time poultry gas concentrations. Real-time sensor feeds are transmitted to a cloud-based platform, which stores, displays, and processes the data. Furthermore, a machine learning (ML) model was trained using historical sensory data to predict the next-day gas emission levels. A web-based platform has been developed to enable convenient user interaction and display the gas sensory readings on an interactive dashboard. Also, the developed system triggers automatic alerts when gas levels cross safe environmental thresholds. Experimental results of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi><msub><mi>O</mi><mn>2</mn></msub></mrow></semantics></math></inline-formula> concentrations showed a significant diurnal trend, peaking in the afternoon, followed by the evening, and reaching their lowest levels in the morning. In particular, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi><msub><mi>O</mi><mn>2</mn></msub></mrow></semantics></math></inline-formula> concentrations peaked at approximately 570 ppm during the afternoon, a value that was significantly elevated (<i>p</i> < 0.001) compared to those recorded in the evening (~560 ppm) and morning (~555 ppm). This finding indicates a distinct diurnal pattern in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi><msub><mi>O</mi><mn>2</mn></msub></mrow></semantics></math></inline-formula> accumulation, with peak concentrations occurring during the warmer afternoon hours.

Gina Paola Escobar Cuero

The intersection of gender, irregular legal status, and economic precarity places undocumented women in Leipzig at heightened risk of exclusion from both healthcare and the labor market. German migration policy, increasingly centered on border enforcement and deterrence, continues to neglect the realities of women working in informal care and domestic sectors. This policy orientation reinforces institutional barriers, especially in reproductive and mental healthcare, and marginalizes undocumented women within systems of care and employment. Between March and June 2025, a structured mini-review of academic and grey literature was conducted using the Vienna University Library and key NGO reports. The review analyzed gendered exclusions across Germany’s legal, healthcare, and labor frameworks, with a particular focus on Leipzig. Findings indicate a striking absence of gender-disaggregated municipal data, perpetuating the invisibility of undocumented women. This invisibility is unintentionally reinforced by Section 87 of the Residence Act (AufenthG), which obliges public authorities to report undocumented individuals, thereby deterring women from accessing healthcare or labor rights protections. The review confirms national trends of labor exploitation and healthcare avoidance among undocumented migrants while highlighting the significant data gaps in Leipzig, which undermine effective local governance. Addressing this invisibility requires gender-sensitive data collection, robust legal firewalls decoupling essential services from immigration enforcement, and targeted municipal investment in safe-reporting mechanisms. Taken together, the Leipzig case demonstrates how migration law, though not explicitly intended for this purpose, produces exclusionary effects and underscores the urgent need for rights-based reforms that recognize undocumented women as social and political actors rather than individuals rendered invisible through policy design and implementation.

Claudia Tomateo, Zbigniew Grabowski

In the face of systematic expropriation, massive biodiversity loss, and the ongoing climate crisis, Indigenous peoples, knowledge, and labor have protected over 80% of the global biodiversity. This is remarkable given that Indigenous management or tenure remains over 20–25% of the planet’s terrestrial surface. Indigenous people’s capacity to protect biodiversity within their territories cannot be separated from the ethical frameworks that shape their relationships with land. These frameworks have been articulated by a diverse array of Indigenous scholars across the globe, and while they cannot be generalized, many share principles that go beyond dominant Western Scientific approaches that normalize utilitarian or idealized (e.g. ideals of wilderness) ethical systems. We argue that dominant policy and research discourses around land-based practices such as nature-based solutions and green infrastructure, will not be effective ‘solutions’ to ongoing crises of climate change and biodiversity loss. Instead, we must go beyond paradigms of improvement and anthropocentric utility and ground land-based practices in the paradigm of relational ethics. Through this perspective paper, we argue that rather than seeking solutions through redesigning ecosystems for utilitarian reasons, all interventions on Indigenous ancestral lands (recognized by settler states or not) should first center relational ethical approaches for land-based design practices and ground efforts in Indigenous justice. Our proposed ‘Indigenous Justice Frameworks for Relational Ethics in Land-based Design’ is based on the inseparability of bodies, lands, and knowledges, and is guided by the following elements: (1) generative refusal, (2) centering healing, reparation, and right relations, and (3) restoring and evolving Indigenous governance.

Yinyin Liang, Kai Zhou, Lin Cao

The phenotyping of plant roots is essential for improving plant productivity and adaptation. However, traditional techniques for assembling root phenotyping information are limited and often labor-intensive, especially for woody plants. In this study, an advanced approach called accurate and detailed quantitative structure model-based (AdQSM-based) root phenotypic measurement (ARPM) was developed to automatically extract phenotypes from Ginkgo tree root systems. The approach involves three-dimensional (3D) reconstruction of the point cloud obtained from terrestrial laser scanning (TLS) to extract key phenotypic parameters, including root diameter (RD), length, surface area, and volume. To evaluate the proposed method, two approaches [minimum spanning tree (MST)-based and triangulated irregular network (TIN)-based] were used to reconstruct the Ginkgo root systems from point clouds, and the number of lateral roots along with RD were extracted and compared with traditional methods. The results indicated that the RD extracted directly from point clouds [coefficient of determination (R2) = 0.99, root-mean-square error (RMSE) = 0.41 cm] outperformed the results of 3D models (MST-based: R2 = 0.71, RMSE = 2.20 cm; TIN-based: R2 = 0.54, RMSE = 2.80 cm). Additionally, the MST-based model (F1 = 0.81) outperformed the TIN-based model (F1 = 0.80) in detecting the number of first-order and second-order lateral roots. Each phenotyping trait fluctuated with a different cloud parameter (CP), and the CP value of 0.002 (r = 0.94, p &lt; 0.01) was found to be advantageous for better extraction of structural phenotypes. This study has helped with the extraction and quantitative analysis of root phenotypes and enhanced our understanding of the relationship between architectural parameters and corresponding physiological functions of tree roots.

Ong RHS, Nurjono M, Oh HC et al.

Rebecca Hui Shan Ong,1 Milawaty Nurjono,1 Hong Choon Oh,1– 3 Christopher Tsung Chien Lien,4 Junisha Jumala,5 Raymond Choon Chye Teo,6 Peiying Gan,7 Karen Lai Ming Kan,8 Lina Farhana Rosle,8 Moi Kim Wee,8 Shou Lin Low4 1Health Services Research, Changi General Hospital, Singapore; 2Centre for Population Health Research and Implementation, Singapore Health Services, Singapore; 3Health Services & Systems Research, Duke-NUS Medical School, Singapore; 4Geriatric Medicine, Changi General Hospital, Singapore; 5Rehabilitative Services, Changi General Hospital, Singapore; 6Singapore Sport & Exercise Medicine Centre, Changi General Hospital, Singapore; 7Community Nursing, Changi General Hospital, Singapore; 8Community and Mental Health, Changi General Hospital, SingaporeCorrespondence: Rebecca Hui Shan Ong, Health Services Research, Changi General Hospital, 2 Simei Street 3, 529889, Singapore, Tel +65 6788 8833, Fax +65 67826049, Email Rebecca.ong.h.s@singhealth.com.sgPurpose: Multiple falls preventions exercise programs have been rolled out globally, however, few studies have explored the factors necessary for their implementation. This study aimed to investigate the factors influencing the implementation of “Steady Feet” (SF), a 12-week community fall prevention exercise intervention, for older adults living in Singapore.Material and Methods: This study utilized purposive sampling to recruit two participant groups: (i) older adults who declined or withdrew from the program and (ii) providers of the program (eg, instructors). We conducted 22 semi-structured interviews, recordings were transcribed and translated, followed by thematic analysis. Data collection and analysis were informed by the PRECEDE-PROCEED framework, focusing on predisposing, enabling, and reinforcing factors.Results: Findings revealed two predisposing, four enabling, and two reinforcing themes. Predisposing themes encompassed (i) knowledge, attitudes, and practices of older adults towards exercises and falls prevention, and (ii) perceptions and attitudes of providers towards SF. Both older adults and providers identified several enabling elements in implementing SF, emphasizing the significance of (i) accessibility, availability, and affordability. Providers highlighted (ii) tools and structural support for continual engagement, (iii) minimizing variations in capabilities through a competency development program, and (iv) fostering synergistic partnerships. Positive reinforcement included (i) the role of providers in engaging and promoting participation, (ii) family support, social networks, and (iii) incentives for older adults. Conversely, both groups highlighted negative reinforcements, including (iv) communication issues and (v) repetitive exercises, while providers specifically identified (vi) labor constraints as a deterrent for implementation.Conclusion: Findings indicate that effective implementation necessitates a multifaceted approach. Promoting participation involves engaging instructors, emphasizing social bonds and family involvement, offering incentives, and providing subsidized or free classes. A competency development program proved effective in reducing variations in providers’ capabilities. Strengthening community partnerships, with management support, was crucial for ensuring the availability and accessibility of falls prevention programs.Keywords: falls prevention, community-dwelling, older adults, exercise, qualitative, precede-proceed

Aulia Rahman

This study examines the application of railway technology in West Sumatra, focusing on the challenges and innovations during the colonial period. The research aims to explore the historical context, technical developments, and socio-economic impacts of the railway construction in this region. Using a historical method with a qualitative approach, the study analyzes primary sources such as colonial archives and technical reports, along with secondary sources like historical books and scholarly articles. The findings highlight the introduction of rack railway systems to navigate steep terrains, demonstrating Dutch colonial technical prowess. Additionally, the construction of the Ombilin coal mines and the associated railway network significantly boosted the local economy but also revealed the exploitation of labor. Overall, the study provides insights into the interplay between technology, colonialism, and local society, emphasizing the importance of geographical adaptation in infrastructure development.

Andreas Katsanikakis, Nikolaos Bekiaris-Liberis, Delphine Bresch-Pietri

We develop an input delay-compensating feedback law for linear switched systems with time-dependent switching. Because the future values of the switching signal, which are needed for constructing an exact predictor-feedback law, may be unavailable at current time, the key design challenge is how to construct a proper predictor state. We resolve this challenge constructing an average predictor-based feedback law, which may be viewed as an exact predictor-feedback law for a particular average system without switching. We establish that, under the predictor-based control law introduced, the closed-loop system is exponentially stable, provided that the plant's parameters are sufficiently close to the corresponding parameters of the average system. In particular, the allowable difference is inversely proportional to the size of delay and proportional to the dwell time of the switching signal. Since no restriction is imposed on the size of delay or dwell time themselves, such a limitation on the parameters of each mode is inherent to the problem considered (in which no a priori information on the switching signal is available), and thus, it cannot be removed. The stability proof relies on two main ingredients-a Lyapunov functional constructed via backstepping and derivation of solutions' estimates for the difference between the average and the exact predictor states. We present consistent, numerical simulation results, which illustrate the necessity of employing the average predictor-based law for achieving stabilization and desired performance of the closed-loop system.

Gabriel C. M. da Silva, Victor F. Monteiro, Diego A. Sousa et al.

As the number of user equipments increases in fifth generation (5G) and beyond, it is desired to densify the cellular network with auxiliary nodes assisting the base stations. Examples of these nodes are integrated access and backhaul (IAB) nodes, network-controlled repeaters (NCRs) and reconfigurable intelligent surfaces (RISs). In this context, this work presents a system level overview of these three nodes. Moreover, this work evaluates through simulations the impact of network planning aiming at enhancing the performance of a network used to cover an outdoor sport event. We show that, in the considered scenario, in general, IAB nodes provide an improved signal to interference-plus-noise ratio and throughput, compared to NCRs and RISs. However, there are situations where NCR outperforms IAB due to higher level of interference caused by the latter. Finally, we show that the deployment of these nodes in unmanned aerial vehicles (UAVs) also achieves performance gains due to their aerial mobility. However, UAV constraints related to aerial deployment may prevent these nodes from reaching results as good as the ones achieved by their stationary deployment.

Z. Li, H. Zou, J. Liu et al.

Meteors carry important and indispensable information about the interplanetary environment, which can be used to understand the origin and evolution of our solar system. We have developed a Multi-station Meteor Monitoring ($\rm M^3$) system that can observe almost the entire sky and detect meteors automatically, and it determines their trajectories. They are highly extensible to construct a large-scale network. Each station consists of a waterproof casing, a wide field-of-view lens with a CMOS camera, and a supporting computer. The camera has a built-in GPS module for accurately timing the meteoroid entry into the atmosphere (accurate to 1 $μ$s), which is the most prominent characteristic compared with other existing meteor monitoring devices. We have also developed a software package that can efficiently identify and measure meteors appearing in the real-time video stream and compute the orbits of meteoroids in the solar system via multi-station observations. During the Geminid meteor shower in 2021, the M$^3$ system was tested at two stations ($\sim$55 km apart) in the suburbs of Beijing. The test results show that the astrometric accuracy is about 0.3-0.4 arcmin. About 800 meteors were detected by these two stations. A total of 473 meteors have their orbits calculated by our software, and 377 of them belong to the Geminid meteoroid stream. Our M$^3$ system will be further tested and upgraded, and it will be used to construct a large monitoring network in China in the future.