Distance Threshold Research Articles

HIV-1 drug resistance and genetic transmission network among newly diagnosed people living with HIV/AIDS in Ningbo, China between 2018 and 2021

BackgroundAs the HIV epidemic continues to grow, transmitted drug resistance(TDR) and determining relationship of HIV transmission are major barriers to reduce the risk of HIV transmissions.This study aimed to examine the molecular epidemiology and TDR and evaluated the transmission pattern among newly diagnosed people living with HIV/AIDS(PLWHA) in Ningbo city, which could contribute to the development of targeted precision interventions.MethodsConsecutive cross-sectional surveys were conducted in Ningbo City between January 2018 and December 2021. The HIV-1 pol gene region was amplified and sequenced for drug resistance and genetic transmission network analysis. TDR was determined using the Stanford University HIV Drug Resistance Database. Genetic transmission network was visualized using Cytoscape with the genetic distance threshold of 0.013.ResultsA total of 1006 sequences were sequenced successfully, of which 61 (6.1%) showed evidence of TDR. The most common mutations were K103N (2.3%), E138A/G/Q (1.7%) and V179D/E (1.2%). 12 HIV-1 genotypes were identified, with CRF07_BC being the major genotype (43.3%, 332/767), followed by CRF01_AE (33.7%, 339/1006). 444 (44.1%) pol sequences formed 856 links within 120 transmission clusters in the network. An increasing trend in clustering rate between 2018 and 2021(χ2 = 9.546, P = 0.023) was observed. The odds of older age (≥ 60 years:OR = 2.038, 95%CI = 1.072 ~ 3.872, compared to < 25 years), HIV-1 genotypes (CRF07_BC: OR = 2.147, 95%CI = 1.582 ~ 2.914; CRF55_01B:OR = 2.217, 95%CI = 1.201 ~ 4.091, compared to CRF01_AE) were significantly related to clustering. Compared with CRF01_AE, CRF07_BC were prone to form larger clusters. The largest cluster with CRF07_BC was increased from 15 cases in 2018 to 83 cases in 2021.ConclusionsThis study revealed distribution of HIV-1 genotypes, and genetic transmission network were diverse and complex in Ningbo city. The prevalence of TDR was moderate, and NVP and EFV were high-level NNRTI resistance. Individuals aged ≥ 60 years old were more easily detected in the networks and CRF07_BC were prone to form rapid growth and larger clusters. These date suggested that surveillance and comprehensive intervention should be designed for key rapid growth clusters to reduce the potential risk factors of HIV-1 transmission.

Using the Molecular Transmission Networks to Analyze the Epidemic Characteristics of HIV-1 CRF08_BC in Kunming, Yunnan.

HIV-1CRF08_BC is the most prevalent epidemic subtype among heterosexual (HET) and intravenous drug users (IDUs) in Kunming, Yunnan. Using the pol region of gene sequences derived from molecular epidemiological surveys, we developed a molecular transmission network for the purpose of analyzing its epidemiological characteristics, assessing its epidemiological trends, identifying its potential transmission relationships, and developing targeted interventions. HyPhy 2.2.4 was used to calculate pairwise genetic distances between sequences; GraphPad-Prism 8.0 was employed to determine the standard genetic distance; and Cytoscope 3.7.2 was applied to visualize the network. We used the network analysis tools to investigate network characteristics and the Molecular Complex Detection (MCODE) tool to observe the growth of the network. We utilized a logistic regression model to examine the factors influencing clustering and a zero-inflated Poisson model to investigate the factors influencing potential transmission links. At the standard genetic distance threshold of 0.008, 406 out of 858 study participants were clustered in 132 dissemination networks with a total network linkage of 868, and the number of links per sequence ranged from 1 to 19. The MCODE analysis identified three significant modular clusters in the networks, with network scores ranging from 4.9 to 7. In models of logistic regression, HET, middle-aged and elderly individuals, and residents of northern and southeastern Kunming were more likely to enter the transmission network. According to the zero-inflated Poisson model, age, transmission category, sampling year, marital status, and CD4+ T level had a significant effect on the size of links. The molecular clusters in Kunming's molecular transmission network are specific and aggregate to a certain extent. HIV-1 molecular network analysis provided information on local transmission characteristics, and these findings helped to determine the priority of transmission-reduction interventions.

Identification of critical ecological areas using the ecosystem multifunctionality-stability-integrity framework: A case study in the Yellow River basin, China

Critical ecological areas (CEAs), as important regions for biodiversity and ecosystem functions, are crucial for ecological conservation and environmental management at regional and global scales. However, the methodology and framework of CEA identification have not been well established. In this study, a comprehensive CEA identification method was developed based on the ecosystem multifunctionality-stability-integrity framework by using K-means clustering, critical slowing down theory and possible connectivity. Taking the Yellow River basin (YRB) as a case study, our results showed that ecosystem multifunctionality gradually decreased from the southeast to northwest. A decrease in ecosystem stability was observed since 2017 and was mainly due to the increased impacts of human activities and urbanization within the 10–20 km distance threshold from the ecosystem. Based on the proposed framework, 15.13% of the YRB was identified as CEAs with reliable estimates, and most areas were distributed in the Three-River Headwaters, Qinling and Taihang Mountains. Moreover, urbanization and precipitation were found to be the dominant environmental factors affecting the CEA distribution in the YRB. Our results indicated that the proposed framework could provide a comprehensive approach for CEA identification and useful implications for ecological conservation and environmental management.

Are conversation and whispered voice hearing tests comparable to pure tone audiometry for assessment of hearing loss? A retrospective analysis

BackgroundPure tone audiometry (PTA) is considered the standard method of hearing assessment. However, technical and logistical challenges preclude its usage for hearing screening at primary healthcare facilities. Free field hearing (FFH) tests such as conversation voice (CV) and whispered voice (WV) tests have been used for hearing assessment. However, their correlation to PTA and accuracy in detection of hearing loss are doubtful. This study aims to determine if FFH tests can be used for estimation of hearing thresholds. MethodsA retrospective analytical study was conducted at the otorhinolaryngology department. Spearman's correlation coefficient (ρ) was determined between FFH recognition distance and average air conduction PTA thresholds. A statistical regression model was developed to estimate hearing thresholds from the FFH recognition distance. The FFH tests were studied for their accuracy in detection of hearing loss. ResultsThe audiometric records of 437 persons (874 ears) were analysed. The CV and WV tests were found to have a high correlation (ρ = −0.757 and −0.758, respectively) with average PTA thresholds in persons with hearing loss. The WV test was found to have a 94.7% sensitivity, 90.8% specificity, 97.6% positive predictive value, 80.9% negative predictive value, and 93.9% accuracy in detection of hearing loss. ConclusionFFH tests such as WV test can be used to estimate the hearing thresholds and screen for hearing loss when audiometric tests are not logistically feasible, such as at primary-level healthcare facilities, remote locations, and in schools. However, such tests should not be regarded as a substitute to PTA.

Combining Remote Sensing and a Geographic Information System to Map and Assess the Accessibility of Invasive Alien Species Forest Stands: Case of Acacia mearnsii on Reunion Island

Acacia mearnsii, an invasive alien species, is the main resource identified for the energy transition initiated on Reunion Island. It is, therefore, critical to identify the existent forest stands within the island’s large tropical forest area and to determine which of these stands are accessible for logging operations. In this study, a very high-spatial-resolution image was used to map forest (Acacia mearnsii, Acacia heterophylla, Cryptomeria japonica) and non-forest land cover. To identify the accessible forest stands, we developed a geographic information system (GIS) processing chain, accounting for barriers, the distribution of slopes, and the location of forest roads. User-defined parameters, such as the slope threshold and maximal distance to forest roads, allow different scenarios to be explored. The classification yields an overall accuracy of 88% and a Kappa index of 0.86 and highlights the areas occupied by the different types of Acacia. By applying the GIS processing chain for a standard scenario, the results show that only 19% of the initial study area of 637 ha of Acacia mearnsii patches is suitable for exploitation. In conclusion, our results demonstrate how remote sensing (RS) and GIS can be combined to provide valuable tools for forest managers to design management plans for invasive alien forest species.

Performance evaluation of a deep learning-based cascaded HRNet model for automatic measurement of X-ray imaging parameters of lumbar sagittal curvature.

To develop a deep learning-based cascaded HRNet model, in order to automatically measure X-ray imaging parameters of lumbar sagittal curvature and to evaluate its prediction performance. A total of 3730 lumbar lateral digital radiography (DR) images were collected from picture archiving and communication system (PACS). Among them, 3150 images were randomly selected as the training dataset and validation dataset, and 580 images as the test dataset. The landmarks of the lumbar curve index (LCI), lumbar lordosis angle (LLA), sacral slope (SS), lumbar lordosis index (LLI), and the posterior edge tangent angle of the vertebral body (PTA) were identified and marked. The measured results of landmarks on the test dataset were compared with the mean values of manual measurement as the reference standard. Percentage of correct key-points (PCK), intra-class correlation coefficient (ICC), Pearson correlation coefficient (r), mean absolute error (MAE), mean square error (MSE),root-mean-square error (RMSE), and Bland-Altman plot were used to evaluate the performance of the cascade HRNet model. The PCK of the cascaded HRNet model was 97.9-100% in the 3mm distance threshold. The mean differences between the reference standard and the predicted values for LCI, LLA, SS, LLI, and PTA were 0.43mm, 0.99°, 1.11°, 0.01mm, and 0.23°, respectively. There were strong correlation and consistency of the five parameters between the cascaded HRNet model and manual measurements (ICC = 0.989-0.999, R = 0.991-0.999, MAE = 0.63-1.65, MSE = 0.61-4.06, RMSE = 0.78-2.01). The cascaded HRNet model based on deep learning algorithm could accurately identify the sagittal curvature-related landmarks on lateral lumbar DR images and automatically measure the relevant parameters, which is of great significance in clinical application.

Automated Fragmentation Quantum Mechanical Calculation of 15N and 13C Chemical Shifts in a Membrane Protein.

In this work, we developed an accurate and cost-effective automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) method to calculate the chemical shifts of 15N and 13C of membrane proteins. The convergence of the AF-QM/MM method was tested using Krokinobacter eikastus rhodopsin 2 as a test case. When the distance threshold of the QM region is equal to or larger than 4.0 Å, the results of the AF-QM/MM calculations are close to convergence. In addition, the effects of selected density functionals, basis sets, and local chemical environment of target atoms on the chemical shift calculations were systematically investigated. Our results demonstrate that the predicted chemical shifts are more accurate when important environmental factors including cross-protomer interactions, lipid molecules, and solvent molecules are taken into consideration, especially for the 15N chemical shift prediction. Furthermore, with the presence of sodium ions in the environment, the chemical shift of residues, retinal, and retinal Schiff base are affected, which is consistent with the results of the solid-state nuclear magnetic resonance (NMR) experiment. Upon comparing the performance of various density functionals (namely, B3LYP, B3PW91, M06-2X, M06-L, mPW1PW91, OB95, and OPBE), the results show that mPW1PW91 is a suitable functional for the 15N and 13C chemical shift prediction of the membrane proteins. Meanwhile, we find that the improved accuracy of the 13Cβ chemical shift calculations can be achieved by the employment of the triple-ζ basis set. However, the employment of the triple-ζ basis set does not improve the accuracy of the 15N and 13Cα chemical shift calculations nor does the addition of a diffuse function improve the overall prediction accuracy of the chemical shifts. Our study also underscores that the AF-QM/MM method has significant advantages in predicting the chemical shifts of key ligands and nonstandard residues in membrane proteins than most widely used empirical models; therefore, it could be an accurate computational tool for chemical shift calculations on various types of biological systems.

The Tikhonov-L-curve regularization method for determining the best geoid gradients from SWOT altimetry

The Surface Water and Ocean Topography (SWOT) mission generates dense altimetry data that, when used in geoid gradient component estimations through least-squares collocation (LSC), lead to an ill-conditioned problem. Such problems also arise in geodetic network designs. This study introduces the Tikhonov-L-curve regularization to effectively address this challenge. By pinpointing the maximum curvatures of the L-curve, we discern optimal regularization parameters, countering issues stemming from the dense data of SWOT and the resulting ill-conditioned covariance matrices. Our approach not only stabilizes LSC solutions but also achieves gradient accuracies at 1-microrad levels compared to theoretical values. Additionally, we experimented with a strategic removal process that selectively eliminates adjacent geoid gradients. This technique considerably improves geoid gradient component determinations, especially evident at a threshold distance of 0.755 km within an 8′× 8′ data selection window. While our findings are rooted in simulated SWOT data, they are pivotal for future research intending to employ real SWOT data, anticipated by late 2023. This work serves as a precursor for marine gravity field determinations, emphasizing the importance of stabilized LSC solutions to avoid misleading seafloor signatures due to data compactness.

Optimizing crop residues collection patterns in rural areas to reduce transportation costs and carbon emissions

Cost optimization of biomass collection is indispensable for its increased utilization, especially in rural areas where crop residues (CRs)-based biomass is in abundance and energy is usually in short supply. However, due to the discrete distribution of rural settlements, the increasing economic and environmental costs associated with CRs collection have become key factors limiting its application. Therefore, this study proposes a method for optimizing the spatial pattern of CRs collection in rural areas while also considering transportation costs and carbon emissions reduction. Based on a multi-scenario location–allocation model, a CRs collection pattern was constructed for biomass resource points and energy facilities. An empirical study in Fujin County found that as CRs collection distance threshold (CDT) increased, transportation costs and carbon emissions reduction potential tended to increase and gradually converge. When the CDT was taken for 15 km, the spatial pattern of CRs collection maximized the overall benefits of transportation costs and carbon emissions reduction, with a transportation cost of 898,104 yuan and a carbon emissions reduction potential of 501,627.5 t. The optimal spatial pattern for collection achieved the collection-utilization spatial matching of 647 biomass feedstock resource points and 196 villages in the study area, resulting in the exploitation of 84% of CRs in total. 25% of villages in the study area can independently meet their heating needs through CRs, and 75% need to consider mixed energy sources for heating. This method can support planning and decision-making for the distributed development and sustainable utilization of biomass resources in rural areas.

A risk source identification model for network security of power CPS system (CPS) based on fuzzy artificial neural network

In order to improve the effect and accuracy of risk source identification, this paper studied the network security risk source identification model of power CPS system based on fuzzy artificial neural network. The network security risk source index system of power CPS system was constructed, and the dimension of index data was reduced by principal component analysis. Fuzzy theory is used to process the index data after dimension reduction, and the comprehensive membership vector of each index is obtained. The dynamic clustering algorithm is used to determine the number of hidden layer units of radial basis function neural network, and the network security risk source identification model is established. Finally, the quantitative value of risk source identification is output. The experimental results show that the model can effectively reduce the dimension of the network security risk source index data of the power CPS system. The optimal distance threshold of the hidden layer is 4.2, and the optimal number of units is 6. In the final identification results, four severe risk sources and five moderate risk sources were obtained, and the quantitative values of risk source identification of each index were 63, 70, 71, 77, 65, 89 and 96, respectively, indicating that the model can effectively identify network security risk sources of power CPS systems. With the increase of the proportion of communication nodes removed, when there are various types of security vulnerability information, the mean square error value of the model is always lower than the set threshold, indicating that the model has high recognition accuracy.

High Genetic Diversity of HIV-1 and Active Transmission Clusters among Male-to-Male Sexual Contacts (MMSCs) in Zhuhai, China.

Monitoring genetic diversity and recent HIV infections (RHIs) is critical for understanding HIV epidemiology. Here, we report HIV-1 genetic diversity and RHIs in blood samples from 190 HIV-positive MMSCs in Zhuhai, China. MMSCs with newly reported HIV were enrolled from January 2020 to June 2022. A nested PCR was performed to amplify the HIV polymerase gene fragments at HXB2 positions 2604-3606. We constructed genetic transmission network at both 0.5% and 1.5% distance thresholds using the Tamura-Nei93 model. RHIs were identified using a recent infection testing algorithm (RITA) combining limiting antigen avidity enzyme immunoassay (LAg-EIA) assay with clinical data. The results revealed that 19.5% (37/190) were RHIs and 48.4% (92/190) were CRF07_BC. Two clusters were identified at a 0.5% distance threshold. Among them, one was infected with CRF07_BC for the long term, and the other was infected with CRF55_01B recently. We identified a total of 15 clusters at a 1.5% distance threshold. Among them, nine were infected with CRF07_BC subtype, and RHIs were found in 38.8% (19/49) distributed in eight genetic clusters. We identified a large active transmission cluster (n = 10) infected with a genetic variant, CRF79_0107. The multivariable logistic regression model showed that clusters were more likely to be RHIs (adjusted OR: 3.64, 95% CI: 1.51~9.01). The RHI algorithm can help to identify recent or ongoing transmission clusters where the prevention tools are mostly needed. Prompt public health measures are needed to contain the further spread of active transmission clusters.

Proximity-centred accessibility—A conceptual debate involving experts and planning practitioners

Recognised as an important dimension of quality of life, accessibility has gained increasing attention from research and planning practice in the last decades. Rising concern with global warming and the dehumanization of cities has spotlighted the proximity-centred dimension of accessibility, which for decades has been mostly undervalued. In both research and practice, we witness a rise in references to proximity-centred accessibility, however, using a variety of different terms, with somewhat nuanced meanings or underlying concerns. Proximity-centred accessibility concepts are still in flux, inhibiting the establishment of a comprehensive understanding for the development of a cohesive research field and of effective public policies.This paper provides a first contribution to the development of a conceptual framework for proximity-centred accessibility, through a co-development process involving both research and practice. For this we used a mixed methods approach incorporating bibliographic research, surveys, and a focus group, involving both experts in the research field and a sample of planning practitioners from Portugal and Germany.Our research revealed over a dozen different proximity-centred accessibility terms currently in use in the scientific research field, of which, local accessibility and neighbourhood accessibility are the most commonly used. A difference in favoured terminology was identified between research and practice as well as different national contexts, requiring further explorations. While Proximity thresholds have been defined using a variety of physical distances or travel times, our survey revealed a nearly unanimous consensus around a threshold of 1600 m (roughly 20 min walking). Mixed evidence was found with regard to activities relevant at proximity. Regardless, playgrounds, green spaces, food shopping and elementary education showed particular relevance.Building on the empirical evidence collected, we strike out a first conceptual framework for proximity-centred accessibility. Building on the general definition for accessibility, we include a maximum distance threshold of 1600 m to consider accessibility as proximity-centred. The proposed framework encourages multiple distances (up to 1600 m), transport modes, and activities (although the relevance of activities seems to be clearly dependent of distance and local context). The importance of clearly specifying the exact distances, transport mode(s) and activities for each application of the framework is stressed.

Active travel to schools in Wales

ObjectivesActive travel to school (ATS), such as walking and cycling, not only reduces carbon emissions and air pollution but also contributes to a myriad of health benefits. Understanding the ‘potential’ for ATS across Wales is poorly understood yet vital to inform policy and practice aimed at increasing ATS.&#x0D; MethodsUsing geospatial techniques, network distances have been calculated for all residences to all schools in Wales. Distances for each residence were de-identified and imported into the Secure Anonymised Information Linkage (SAIL) databank using SAIL’s split file approach. Within SAIL, anonymised distances were linked to encrypted school locations and a cohort of approximately 440,000 children attending a state school in Wales as recorded in the Education Wales (EDUW) dataset. Travel distance to school was subsequently filtered for each child within our cohort.&#x0D; ResultsThe incorporation of geospatial network derived origin-destination pairs (n=2,205,000,000) allows us to explore how households can engage in ATS, and how this varies by primary/secondary school, welsh-speaking, urban/rural, and socioeconomic status. Initially we will present findings based on distance alone, with future refinements to encompass other factors influencing ATS including: active travel routes, road safety, and topography. We will link our results to anonymised ATS survey responses in SAIL, to calculate specific ATS distance thresholds by age, deprivation, and urban/rural status, including social indicators such as household composition.&#x0D; ConclusionCurrently there is limited local or national comparable information on the potential for ATS in Wales. This baseline information is urgently needed to inform ATS policy and planning, and to ensure appropriate ATS interventions are prioritised for schools and communities where need is greatest.

Boundary green infrastructure: a green infrastructure connecting natural and artificial spaces

As a naturally-based solution (NBS), green infrastructural network constructing can improve urban ecological resilience and support sustainable urban development. However, as the Frontier of urban expansion, the boundary of built-up areas has little research on the boundary green infrastructure (BGI) connecting natural and artificial spaces. In order to make up for the shortcomings of relevant research, we propose a method for identifying BGI and analyze its landscape pattern characteristics. We selected 15 European cities as cases to extract the boundaries of built-up areas. Moreover, we used morphological pattern analysis (MSPA) to identify the ecological source and select the best distance threshold for the landscape connectivity model to identify the BGI range. Through the gradient area method and MSPA, the BGI landscape pattern characteristics of the case cities were analyzed quantitatively. The BGI scale was affected by the area of the built-up area and the threshold of GI landscape connectivity distance. Additionally, the BGI space contained a small number of large ecological sources and many scattered and small fragmented patches. The best landscape model of BGI was the surrounding pattern, followed by the aggregation pattern, which had good landscape connectivity; however, the fragmentation of the scattered pattern was high. Lastly, the ecological core area in BGI was the main landscape type; it has a high landscape connection function for the GI network inside and outside the built-up area and promotes biological exchange inside and outside the built-up area. This study proves that BGI has an important ecological significance, can guarantee the scientific nature of the NBS method, and ensures the ecological security pattern of cities.

NT-ARS-RRT: A novel non-threshold adaptive region sampling RRT algorithm for path planning

Rapidly-Exploring Random Tree (RRT) algorithm is a widely used path planning method. However, it suffers from low solution efficiency, no search guidance, poor quality of the obtained path and the problem of obvious reduction of search efficiency in the narrow exit environment, which greatly reduces its performance. To overcome these issues, this paper proposes a novel non-threshold adaptive region sampling RRT (NT-ARS-RRT) algorithm for path planning. First, a map preprocessing method is proposed to reduce the explore space of the random tree and improves the path search efficiency especially at narrow exits. Second, a branch-and-leaf backtracking method is proposed to optimize the selection of the nearest node. Third, a distance threshold connection constraints optimization method between the newest node and the target point is proposed to reduce the generation of unnecessary nodes and thus further improves the algorithm’s speed. Fourth, the initial path is optimized by using a rewiring method based on triangular inequality to improve the path quality. Experimental results show the effectiveness of the proposed algorithm.

Simulation and optimization of dynamic-hybrid parking reservation strategies for one-way vehicle-sharing systems

ABSTRACT In this paper, we explore the regulation of one-way station-based vehicle-sharing system (OSVS) through dynamic-hybrid parking reservation policies. We first propose a dynamic-hybrid parking reservation policy. This policy only requires trips with expected travel distances shorter than a specific threshold to make a parking reservation. The distance threshold varies with time. We develop a discrete event simulation model based on the O2DES (object-oriented discrete event simulation) framework to compare the dynamic-hybrid parking reservation (DHPR) strategy with the no-reservation (NR), static-hybrid parking reservation (SHPR) and complete parking reservation (CPR) strategies. Furthermore, we propose a simulation-optimization model and an Elitism-based Genetic algorithm with the optimal computation budget allocation to determine the fleet size, station capacity, and dynamic reservation distance threshold. The analysis of case studies of a real-world system indicates that DHPR is always superior to NR, SHPR and CPR.

Normalized closeness centrality of urban networks: impact of the location of the catchment area and evaluation based on an idealized network

The decision of where to locate the catchment area of an urban network exerts significant influence on the indicator values and in this research this influence is referred to as the placement effect. Placement effect has significant impact on the studies at the neighborhood scale focusing on the structural properties of the network models, the network analysis results and centrality measures, the inferred movement patterns and the accessibility to destination. Placement effect becomes even more significant when multiple catchment areas are sampled to be compared or classified. This research examines placement effect on one of the most affected indicators, closeness centrality, and proposes using an idealized network as a reference to be compared with the real network in order to find a solution to mitigate the placement effects. By comparing the normalized closeness centrality in the real network with that in the idealized network, we can (1) evaluate the placement effect on the closeness centrality and (2) find the threshold distance in order to mitigate the placement effect. The results show that the closeness centrality of the same node varies remarkably depending on its position and how central it is in the chosen catchment area. Specifically, in the selected areas in this research, if the center point of a catchment area is moved by more than 100 m away from the original center point, the closeness centrality of the same node starts to be significantly influenced by the placement effect. The threshold distance of 100 m offers a recommendation that a direct comparison of the closeness centrality between different nodes in the same catchment area should be drawn only if these nodes are less than 100 m away from each other. In other words, when comparing two nodes located further than the threshold distance from each other, it is advisable to create two separate catchment areas, where these nodes serve as the center points. It should be noted that the threshold distance of 100 m derived specifically from the current research should not be generalized to other cases. The threshold distance of different case studies remains open for further investigation in the future as it may vary among cities or areas.

Three-state opinion model with mobile agents.

We study an agent-based opinion model with two extreme (opposite) opinion states and a neutral intermediate one. We adjust the relative degree of conviction between extremists and neutrals through a dimensionless parameter called the "neutrality parameter" to investigate its impact on the outcome of the system. In our model, agents move randomly on a plane with periodic boundary conditions and interact with each other only when they are within a fixed distance threshold. We examine different movement mechanisms and their interplay with the neutrality parameter. Our results show that in general, mobility promotes the global consensus, especially for extreme opinions. However, it takes significantly less time to reach a consensus on the neutral opinion.

Wearable Wireless Sensor Network for Mitigating COVID-19 Transmission Through Physical Distancing

The global community is currently facing a critical situation with the widespread transmission of the Covid-19 virus. The rapid increase in Covid-19 cases has necessitated immediate action and treatment. As the World Health Organization (WHO) recommended, maintaining a minimum distance of one meter between individuals is an effective preventive measure to avoid transmission through respiratory droplets. To address this issue, this paper introduces a cost-effective design and implementation of a wearable wireless sensor network using the ESP32 microcontroller and Bluetooth Low-Energy (BLE) technology that promotes physical distancing and contact tracing to mitigate the spread of COVID-19. In this research, we have determined that the safe distance between individuals is 1.5 meters. Proximity testing has indicated that an RSSI value of -62 dBm corresponds to a distance below 1.5 meters. Hence, we set -62 dBm as the distance threshold between wearable devices to ensure safe physical distancing. These wearable wireless sensor network devices are intended to assist individuals in maintaining a safe distance from others, thereby reducing the risk of COVID-19 transmission.

Gender gap and parenthood penalties in business travel changes from 2001 to 2017: Occupational variations and associations with technology use

This paper evaluates transitions in gender differences and parenthood penalties in the chance of business travel, focusing on variations by occupation and technology usage. Although literature documents that women and parents of small children are substantially less likely to travel for business, particularly long ones, little research has explored changes in the gap. Moreover, not much attention has been given to whether they vary by business travel distance, occupation, or technology adaptations. This study analyzes domestic intra-regional business travel likelihood by different distance thresholds, using three U.S. National Household Travel Surveys from 2001 to 2017. By employing the Probit model, our analysis finds narrowing gender gaps and parenthood penalties in business mobility, thanks to the shrinking travel needs. Internet-savvy workers, in particular, experienced narrower gender gaps, especially among those without small children. The conditional prediction suggests a disappearing gender gap and parenthood gap for the sales and service workers, even for trips over 50 miles per day. Contrary, the gender gap in business mobility among the professional and managerial workers persistently remained in 2017 for long-distance trips. The declining trend in the gender gap and parenthood penalty for the business travel likelihood is a vital sign for reducing inequalities and work-life balances.