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A challenge for management of wildlife species is the assessment of the effect of roads on migration. We developed models to estimate the spatial (zone of influence (ZOI)) and temporal (delays in migration) effects of roads, and test whether road closures reduced delays in migration. We analyzed collar (2011–2019) and road survey data from two barren-ground caribou (Rangifer tarandus groenlandicus (Borowski, 1780)) herds to assess the impact of a 171 km mine road that bisects their migration corridor. We estimated ZOIs of 16–17 km prior to crossing the road during 2018 and 2019, and 3.0 km after crossing. Estimates of mean delay were 4.3 and 2.5 days for 2018 and 2019, which were reduced by 28%–68% (1.2–1.7 days) if roads were closed when caribou were within the ZOI. In 2017–2018, when the road was extended 64 km north, caribou were 12% less likely to deflect north around the road, therefore increasing delays. Road surveys indicated aggregation of caribou prior to crossing the road, with few caribou observed after crossing, a finding supported by collar data. Our methods can estimate the spatial and temporal effects of roads for any wildlife species and assess mitigation strategies in reducing delays in migration. [ABSTRACT FROM AUTHOR]

Quantifying the atmospheric water balance is critical for the study of hydrological processes in significant regions. This study quantified atmospheric water balance closure at 205 stations in mainland China on a monthly timescale from 2009 to 2018 using datasets from ground- and satellite-based observations and reanalysis data. The closure performances were firstly quantified using the mean and root mean square (RMS) of the residuals, and the possible influencing factors were explored, as well as the influence of different water balance components (WBCs) using different datasets. In the closure experiment using ERA5, the mean and residuals were 6.26 and 12.39 mm/month, respectively, on average, which indicated a closure uncertainty of 12.8%. Using ERA5 analysis as a reference, the closure experiment using different combinations revealed average mean residuals of 8.73, 11.50, and 15.89 mm/month, indicating a precipitation closure uncertainty of 22.0, 23.7, and 24.4% for the ground- and satellite-based observations and reanalysis data, respectively. Two possible influencing factors, station latitude and the climatic zone in which the station is located, were shown to be related to closure performance. Finally, the analysis of the impact from different WBCs showed that precipitation tended to have the most significant impact, which may have been due to larger observation uncertainties. Generally, the atmospheric water balance in mainland China can be closed using datasets from different observational techniques. [ABSTRACT FROM AUTHOR]

A railway level crossing is a risk area despite installations of the warning signal and arm gate that indicate a train approach. Accidents may nevertheless occur if vehicle drivers violate or fail to conform to the rules. Such action is considered a risk behavior that may cause severe collision, injury, and death. Thus, the driver behaviors are the key factors causing accidents. The objective of this study was thus to investigate the risk behaviors and the factors influencing above behaviors. These behaviors were recorded by a high-resolution video camera and the initial data analysis was based on descriptive statistics. An in-depth analysis of the factors influencing the risk behaviors was performed by using Pearson Chi-square technique and Binary Logistic Regression Analysis. The results showed that the railway crossing behaviors of more than half of the drivers under the study were the risk-taking, followed by opportunistic violation. Most violations occurred during the beginning of the warning signal. Overall, the motorcycle riders were found to be the group with greater chance of violating across the railway during the warning signal than the 4-wheeled vehicle drivers. Especially, during the period between the beginning of the warning signal and the complete arm gate closure, as well as the greater width of the crossing road. This could be due to the higher agility and evasive capability of motorcycle riders than 4-wheeled drivers. Additionally, this study recommends approaches to initially prevent or reduce this risky behavior and can serve as a guideline for enhancing areas with physical characteristics similar to the study area. [ABSTRACT FROM AUTHOR]

Integrating both proactive and reactive risk-mitigation mechanisms, this research constructs a bi-level network design problem for hazardous materials (hazmats) to regulate the carriers' use of roads, such that the environmental impact is minimized. In more detail, by embedding the emergency response time into the risk assessment, the locations of hazmat response teams are determined along with toll schemes, road closures, and new road constructions. The uncertainties of demand, including differences in the number of shipments, origin/destination changes, and amount variations, are also taken into account by applying a scenario-based approach. The proposed bi-level model is first solved optimally by a single-level reformulation, and then by a three-stage heuristic method for larger instances. Through numerical experiments on a real-world road network in Nanchang, a city in China, a set of management insights are derived to facilitate policy-making in regulating hazmat transportation. [ABSTRACT FROM AUTHOR]

Evacuation planning and emergency routing systems are crucial in saving lives during disasters. Traditional emergency routing systems, despite their best efforts, often struggle to accurately capture the dynamic nature of flood conditions, road closures, and other real-time changes inherent in urban disaster logistics. This paper introduces the ReinforceRouting model, a novel approach to optimizing evacuation routes using reinforcement learning (RL). The model incorporates a unique RL environment that considers multiple criteria, such as traffic conditions, hazardous situations, and the availability of safe routes. The RL agent in this model learns optimal actions through interaction with the environment, receiving feedback in the form of rewards or penalties. The ReinforceRouting model excels in executing prompt and accurate route planning on large road networks, outperforming traditional RL algorithms and shortest-path-based algorithms. A higher safety score and episode reward of the model are demonstrated when compared to these classical methods. This innovative approach to disaster evacuation planning offers a promising avenue for enhancing the efficiency, safety, and reliability of emergency responses in dynamic urban environments. [ABSTRACT FROM AUTHOR]

Human activities and infrastructures can disturb wildlife and alter their behaviour by triggering antipredator responses such as changes in time allocation to different behaviours. For instance, disturbance sources like traffic can cause significant variation in allocation of time to vigilance and foraging behaviours, which can be used as sensitive measures of the effects of human disturbance on animals. Such changes may ultimately result in physiological and ecological costs for the species. We used a unique opportunity to obtain direct behavioural observations of European wildcats, Felis silvestris , in the Cantabrian Mountains (northwest Spain) to investigate how different sources of anthropogenic disturbance influence time allocation of wildcats to specific behaviours. We also analysed how traffic affects hunting and vigilance time budgets as well as hunting success. We found that wildcats allocated more time to being alert and less time to hunting, feeding and moving in the presence of humans than in undisturbed situations. Wildcats also allocated more time to hunting when traffic levels were high, near roads and further from villages. Similarly, they dedicated more time to vigilance behaviours while feeding in the presence of moving vehicles. Finally, hunting success in the presence of vehicles seemed to decrease more for female wildcats than for males although this effect was not significant. In conclusion, humans and traffic influence the behaviour of wildcats inhabiting pastoral anthropogenic landscapes, although it is difficult to know to what extent such changes may translate into demographic effects. • Human presence increased time spent alert and reduced foraging behaviour. • Wildcats spent more time hunting in scenarios with high traffic and closer to roads. • Wildcats increased vigilance time while foraging in the presence of vehicles. • Hunting success was not significantly influenced by the presence of vehicles. • Humans and traffic affect wildcat behaviour in pastoral landscapes. [ABSTRACT FROM AUTHOR]

Wild turkeys Meleagris gallopavo are diurnally active birds that spend the dark hours roosting in trees. We tested the hypothesis that multiple benefits exist for roost tree selection by wild turkeys, including thermoregulation, resource acquisition, and protection from predators. We compared 48 roost trees used by eastern wild turkeys M. g. silvestris in Ontario, Canada to 48 non‐roost trees sampled contemporaneously during 2017–2019 to determine roost site selection between seasons. Mean (± SE) roost tree height (21.4 ± 0.8 m) was taller than non‐roost trees (18.2 ± 0.8 m), and roost trees were also larger in diameter at breast height (58.1 ± 5.5 vs 38.7 ± 3.1 cm). Using ibuttons to collect microclimate temperatures at the tree, we found that mean temperature (± SE) of a deciduous roost (14.5 ± 0.1°C) was higher than temperature at either a coniferous roost (13.9 ± 0.1°C) or ambient temperature (13.2 ± 0.1°C) during the summer months. In winter however, we did not find any relationship between temperature and tree type. Roosts were closer to buildings (150.8 ± 26.0 m) in the winter compared to summer and year‐round roosts, and winter roosts were also farther away from crops (395.2 ± 63.7 m) compared to roost sites used year‐round. Summer roosts were closer to roads (143 ± 36.3 m) than the roosts in the winter and roosts used year‐round. Our data suggest that thermoregulation is not the driving force behind roost selection; instead, predator avoidance appears to play the most important role, with some weaker evidence in support of proximity to resources. [ABSTRACT FROM AUTHOR]

This correction notice provides corrected versions of tables in an article titled "Association of risk perception and transport mode choice during the temporary closure of a major inner-city road bridge: results of a cross-sectional study." The tables include data on the main mode of transport before and during the bridge closure, bridge use frequency and group of mode choice, and frequencies and percentages of different groups in the study. Another table presents statistical measures for variables related to alternative use of cars, including attitude, subjective norm, and perceived behavioral control. The results suggest that these factors are significant predictors of alternative use. The article explores the relationship between these factors and transportation choices. [Extracted from the article]

Since ancient times, the closure of roads due to ice and snow accumulation is one of the most critical problems of highway transportation. There are two different approaches to prevent icing on the road: passive and active methods. In this study, the most efficient aggregate type and the asphalt mixture combination containing electrically conductive components was determined for electrically conductive asphalt pavements which are considered among the active anti-icing methods. For this purpose, a two-stage experimental study was carried out. In the first stage, asphalt concrete (CAC) specimens with 25 different aggregate and conductive component contents were produced and their properties such as volumetric resistivity, the temperature variations under constant (30 Volt) electrical direct current (DC), heating and cooling times and thermal conductivity were determined. Marshall asphalt design was also performed for three series (2.1; 4.1, and 4.3) for the best electrical and thermal conductivity properties in the second stage of the study. Volumetric resistivity tests were performed and temperature variations under constant voltage (30 V) were determined on the Marshall specimens. As a result of the study, environmentally friendly asphalt specimens with wearing layer having high electrical conductivity properties were developed. It was concluded that not only the conductive components but also the aggregate type was reasonably effective in terms of anti-icing performance and CAC specimens could exhibit behaviour close to traditional asphalt properties. [ABSTRACT FROM AUTHOR]

Since ancient times, the closure of roads due to ice and snow accumulation is one of the most critical problems of highway transportation. There are two different approaches to prevent icing on the road: passive and active methods. In this study, the most efficient aggregate type and the asphalt mixture combination containing electrically conductive components was determined for electrically conductive asphalt pavements which are considered among the active anti-icing methods. For this purpose, a two-stage experimental study was carried out. In the first stage, asphalt concrete (CAC) specimens with 25 different aggregate and conductive component contents were produced and their properties such as volumetric resistivity, the temperature variations under constant (30 Volt) electrical direct current (DC), heating and cooling times and thermal conductivity were determined. Marshall asphalt design was also performed for three series (2.1; 4.1, and 4.3) for the best electrical and thermal conductivity properties in the second stage of the study. Volumetric resistivity tests were performed and temperature variations under constant voltage (30 V) were determined on the Marshall specimens. As a result of the study, environmentally friendly asphalt specimens with wearing layer having high electrical conductivity properties were developed. It was concluded that not only the conductive components but also the aggregate type was reasonably effective in terms of anti-icing performance and CAC specimens could exhibit behaviour close to traditional asphalt properties. [ABSTRACT FROM AUTHOR]

Background: Since air pollution and physical inactivity pose major public health risks, switching from cars to alternatives like public transport, cycling, and walking is important. Therefore, it is beneficial to identify key events for changes of mode choice. Methods: We examined the association between risk perception and mode choice during the temporary closure of a road bridge between two major German cities in early 2020 using binary and multinomial regression models. Results: 679 people participated in the survey. We found that 22% of car users switched to alternatives. The higher the perceived health risk from traffic-related air pollution, the more likely car users switched to alternatives (odds ratio [OR] = 1.76, 95% CI [1.14, 2.71]). Discussion: Attitude, subjective norm and perceived behavioral control were associated with maintaining but not with switching transport modes. In conclusion, the closure of a main road bridge may present a key event. To explain mode choice, risk perception is a potential extension to the theory of planned behavior. [ABSTRACT FROM AUTHOR]

Over a period of 2 years, we noted that many large mammals in the Murchison Falls National Park, Uganda, remained fairly close to the road--rather than running away--as we drove past at a relatively slow speed, of about 20-25 kph. We consider that over recent years, many of these animals have become habituated to tourist vehicles passing nearby and we recorded the minimum distances at which nine common species remained at, or close to the road edge as we drove past. Many stayed still actually at the edge, while Oribis and Hartebbest sometimes remained on the road itself. [ABSTRACT FROM AUTHOR]

Road pavement maintenance and upgrades (RPU) need to be scheduled in a way that minimises congestion across the road network and matches the schedule with the availability of equipment and skilled labourers to ensure that they are completed on time. RPU should not introduce unbearable congestion around blocked lanes or roads, and increased traffic due to ongoing road upgrades needs to be transferred to alternative routes. In situations where multiple upgrades are planned together, the scheduled road closures should be coordinated to not block alternative routes. While extensive studies have been conducted separately on scheduling and routing, limited research has linked these processes together, and only in restricted scenarios. In this paper, we investigate how to minimise the disruption of a set of road maintenance tasks based on their interaction with other tasks. We propose a new approach for scheduling a set of road maintenance tasks, some at the same time and others at different times, to minimise overall disruption. The proposed approach has two phases: (1) identify the local area affected by the RPU, and (2) determine which upgrades can be planned together to minimise congestion. The comparison of the results shows how the novel optimized approach identifies a better schedule to minimise congestion. [ABSTRACT FROM AUTHOR]

State departments of transportation (DOTs) typically use one of three approaches to operate highway rest areas (RAs): in-house workforce, method-based contracting (MBC), and performance-based contracting (PBC). State DOTs spend over $600 million annually to maintain their facilities and often outsource their work to save costs. Although some studies have calculated the annual cost of facilities operated by the three approaches, their findings are not directly comparable. The primary objective of this study is to compute and compare the average annual operating cost of individual RA facilities and the cost of RA data samples (average annual operating cost of a group of facilities in a specific year under a specific approach in a state) produced from these three approaches to achieve a cost-effective alternative. To achieve the objectives, research hypotheses were developed which state there are significant differences in the average annual costs produced by these three approaches. For data analysis, 6,248 cost data were collected from 29 states. From those individual cost data, 198 data samples were generated. Data sets were not normally distributed; thus, nonparametric tests were conducted to determine the group differences. The results show that outsourcing costs under the MBC are significantly less, followed by in-house and the PBC in both cases. The difference between in-house and PBC is also statistically significant. As the primary contribution, this paper investigated the MBC approach as the cost-effective option, and DOT engineers can utilize this approach in operating regular RA facilities to save costs. Caution should be taken when using the study findings in other types of facilities. This study suggests that state DOTs can use a cost-effective approach to operate their highway RA facilities for future planning. This study identified MBC as the cost-effective approach when operating regular RA facilities. Transportation professionals can directly implement the study findings to regular RA facilities; however, they should take caution when utilizing the findings in the other two types of RA facilities––welcome center and seasonal facilities––which were not considered in this study because their key features (square footage, annual visitors, and full-time employees) are not comparable to regular facilities. If the agencies have key feature data and they can normalize these features when calculating the average annual cost of facilities, then they can implement the findings for welcome center and seasonal RA facilities as well. In addition, the agencies should be aware of adjusting for inflation and location. Using the cost-effective approach may also reduce RA facility closures in the future, which assists in reducing the shortage of national truck parking issues and decreasing fatigue-related highway accidents. [ABSTRACT FROM AUTHOR]

Assessing the importance of managed hunting estates is a focal step in knowing whether they affect game and non-game species. Microhabitat and human presence were measured in managed and unmanaged hunting estates in the Mamora forest to identify the best predictors of the vulnerable European turtle dove (TD) occurrence (presence/absence) by means of generalized linear mixed models (GLMM). The results reveal that TD occurrence increases significantly close to paved roads and to houses of shepherds with enclosures and far away from rural agglomerations in managed hunting estates, whereas, in unmanaged hunting estates, it increases far from paved roads and close to rural agglomerations and houses of shepherds with enclosures. Furthermore, whatever the type of hunting forest estate, the TD occurrence increases with an increasing cover of trees and remoteness from cereal crops. In the Mamora forest, the effect of hunting estate type on TD occurrence is not that strong to be noticeable in the managed hunting estates (apparent positive effect on TD occurrence). However, human presence turns out to be beneficial for TD in unmanaged hunting estates. It is recommended to test the geographical generality of our results using the same analytical approach in other managed and unmanaged hunting estates for both game and non-game species. [ABSTRACT FROM AUTHOR]

Purpose: Polysorbate oxidation can potentially lead to protein degradation and loss of potency, which has been a challenge for the pharmaceutical industry for decades. Many factors have been reported to impact polysorbate oxidation rate, including types of elemental impurities, peroxide content, pH, light exposure, grades of polysorbate, etc. Even though there are many publications in this field, the impact of primary container closure system on PS80 oxidation has not been systematically studied or reported. The purpose of the current study is to close this gap. Methods: Placebo PS80 formulations were prepared and filled into different container-closure systems (CCS), including different types of glass vials and polymer vials. Oleic acid content was monitored on stability as a surrogate value for PS80 content, which will decline upon oxidation. ICP-MS analysis and metal spiking studies were carried out to correlate the PS80 oxidation rate with metals leached from primary containers. Results: PS80 degrades via oxidation at the fastest rate in glass vials with high coefficient of expansion (COE), followed by glass vials with low coefficient of expansion, while polymer vials minimized the oxidation of PS80 in most formulation conditions explored in this paper. ICP-MS analysis demonstrated that 1) 51 COE glass has more metal leachables than 33 COE glass in this study; and 2) More metal leachables correlates with faster PS80 oxidation. Metal spiking studies confirmed the hypothesis that aluminum and iron have a synergistic catalysis effect on PS80 oxidation. Conclusions: Primary containers of drug products play a significant role in the rate of PS80 oxidation. This study revealed a new major contributor to PS80 oxidation and potential mitigation strategy for biological drug products. [ABSTRACT FROM AUTHOR]

The critical points on the rail and road network are their intersections, i.e., level crossings. During a train crossing, car traffic is stopped. This reduces the fluidity of traffic on the road and, consequently, can cause congestion. The problem increases with the number of cars and trains. Frequently, due to national regulations, level crossing closure times are long. It is mainly dictated by safety issues. Building two-level intersections is not always a good solution, mainly because of the high cost of implementation. In the article, the authors proposed the use of sensors to reduce level crossing closure times and improve the Level of Service on the road network. The analyzed railroad lines are local agglomeration lines, mainly due to safety (low speed of commuter trains) and high impact on the road network. The sensors proposed in the article are based on radar/LIDAR. Formulas similar to HCM methods are proposed, which can be implemented in a railroad crossing controller. Simulations using the PTV Vissim program are carried out and the results are worked out based on the obtained data. The considered method can reduce the level crossing closure time by 68.6%, thereby increasing the Level of Service on roads near railroads. [ABSTRACT FROM AUTHOR]

This paper presents a data-driven approach to estimate incident-induced delays (IIDs) using probe vehicle data while accounting for missing data. The proposed approach is applied to evaluate the effectiveness of a safety service patrol (SSP) program. Existing data-driven methods for IID estimation usually rely on complete data sets. The proposed approach employs a random forest-based classification model and an interpolation method to estimate IIDs when real-time data are completely or partially missing during the incident-impacted time period. It also identifies reference profiles from the closest spatial-temporal road segments to improve data availability. The case study shows that the SSP program in the Quad Cities area of Iowa reduces IIDs associated with various incidents by 15%–91%. This data-driven evaluation framework can be applied to other traffic incident management programs, allowing more accurate and objective evaluations of their effectiveness. [ABSTRACT FROM AUTHOR]

Previous studies have shown that road networks have a wide range of effects on land use and ecological processes, which result in both direct and indirect impacts on ecosystems. However, some of these studies employed predictive inference approaches to identify the causal relationships; we argue that these methods may generate biased conclusions. In this study, taking as the study area the biggest central Chinese megacities where land-use change was massive over the past decades, we investigate the causal relationships between the city's road network and its landscape ecological risk using different quasi-experimental designs. Two different geographic scopes of road effects as well as the intensity of the effects are examined. For the years 2005, 2012, and 2019, we measure the distance to the nearest road, road density, and kernel density as well as landscape ecological risk at a 5-km2 block scale. When applying correlation analyses and ordinary least squares regressions without experimental settings, these data indicate that blocks closer to the road and having higher road density, or kernel density, are associated with higher landscape ecological risk values. Yet, difference-in-difference estimated results suggest new roads built during the 2005–2012 period did not have an economically significant effect on subsequent landscape ecological risk. [ABSTRACT FROM AUTHOR]

With the increasing deployment of autonomous taxis in different cities around the world, recent studies have stressed the importance of developing new methods, models and tools for intuitive human–autonomous taxis interactions (HATIs). Street hailing is one example, where passengers would hail an autonomous taxi by simply waving a hand, exactly like they do for manned taxis. However, automated taxi street-hailing recognition has been explored to a very limited extent. In order to address this gap, in this paper, we propose a new method for the detection of taxi street hailing based on computer vision techniques. Our method is inspired by a quantitative study that we conducted with 50 experienced taxi drivers in the city of Tunis (Tunisia) in order to understand how they recognize street-hailing cases. Based on the interviews with taxi drivers, we distinguish between explicit and implicit street-hailing cases. Given a traffic scene, explicit street hailing is detected using three elements of visual information: the hailing gesture, the person's relative position to the road and the person's head orientation. Any person who is standing close to the road, looking towards the taxi and making a hailing gesture is automatically recognized as a taxi-hailing passenger. If some elements of the visual information are not detected, we use contextual information (such as space, time and weather) in order to evaluate the existence of implicit street-hailing cases. For example, a person who is standing on the roadside in the heat, looking towards the taxi but not waving his hand is still considered a potential passenger. Hence, the new method that we propose integrates both visual and contextual information in a computer-vision pipeline that we designed to detect taxi street-hailing cases from video streams collected by capturing devices mounted on moving taxis. We tested our pipeline using a dataset that we collected with a taxi on the roads of Tunis. Considering both explicit and implicit hailing scenarios, our method yields satisfactory results in relatively realistic settings, with an accuracy of 80%, a precision of 84% and a recall of 84%. [ABSTRACT FROM AUTHOR]

Freeway maintenance and rehabilitation work usually require closing one or multiple lanes, interrupting traffic flows, and creating queues upstream of the work zone. Public agencies can use queue length as a criterion to determine the maximum duration of lane closures and necessary traffic diversions. Previous studies of estimating queue length due to work zone lane closures are data- and time-intensive. This study presents an efficient approach for estimating queue length estimation due to work zone lane closures by developing various statistical and machine-learning models. The inputs for these queue length estimation models were vehicle demand, lane closure duration, active work zone length, and heavy vehicle percentage. The extent of the queues caused by short-term work zones on freeways for 2-to-1 (one-lane closure on a two-lane freeway), 3-to-1 (one-lane closure on a three-lane freeway), and 3-to-2 (two-lane closure on a three-lane freeway) lane-closure configurations can be estimated with these models. The primary scientific contribution of this study is the applicability of the queue length estimation models in any freeway network with work zone configurations and geometric features such as those used for model development. This research evaluated the efficacy of both statistical and machine-learning models for estimating the queue length considering different work zone scenarios. The accuracy of the queue length estimation models was evaluated for a different network that the original models had not seen previously. Among the statistical models, the quantile regression model had the best accuracy based on mean absolute percentage error (MAPE) for the 2-to-1 lane-closure configuration (88%), and the multiple linear regression had the best accuracy for the 3-to-1 (76%) and 3-to-2 (72%) lane-closure configurations. Among the machine-learning models, the stacking regressor model had the best accuracy for 2-to-1 (95%), 3-to-1 (90%), and 3-to-2 (89%) lane-closure configurations. Based on the analysis, it was observed that machine-learning models performed better than the traditional statistical models in estimating queue lengths. [ABSTRACT FROM AUTHOR]

Important infrastructure such as highways or railways traverse unstable terrain in many mountainous and scenic parts of the world. Rockfalls and landslides result in frequent maintenance needs, system unreliability due to frequent closures and restrictions, and safety hazards. Seismic activity significantly amplifies these negative economic and community impacts by generating large rockfalls and landslides as well as weakening the terrain. This paper interrogates a rich database of repeat terrestrial lidar scans collected during the Canterbury New Zealand Earthquake Sequence to document geomorphic processes as well as quantify rockfall activity rates through time. Changes in the activity rate (spatial distribution) and failure depths (size) were observed based on the Rockfall Activity Index (RAI) morphological classification. Forecasting models can be developed from these relationships that can be utilized by transportation agencies to estimate increased maintenance needs for debris removal to minimize road closures from rockfalls after seismic events. [ABSTRACT FROM AUTHOR]

The loss of species with unique traits and evolutionary histories resulting from anthropogenic land-use changes poses a risk to the maintenance of ecosystems. We investigated the influence of Pinus monocultures and roads on functional, phylogenetic, and taxonomic composition, as well as on functional dispersion of an anuran metacommunity in Brazil. We expected the influence of anthropogenic stressors to (1) vary according to the diversity component, with greater influence on the functional and phylogenetic components than on the taxonomic component; and (2) traits related to habitat exploration to be more influenced by monocultures, while the traits related to dispersal and physiological control to be influenced by roads and monocultures, especially for species with smaller body size and low dispersal potential. We found that, while the distance from ponds to monocultures influences the phylogenetic composition, distance to roads influences functional composition and dispersion. The anthropogenic stressors affect the structure of these communities, even those formed by generalist species in terms of habitat use. The phylogenetic composition shows that the distribution of evolutionary clades in human-modified areas is linked to the preferred habitat of species, while functional composition is related to body size. Furthermore, functional dispersion was higher in areas closer to roads, contrary to our expectations. Our results represent new evidence for the conservation of anurans in modified landscapes reinforcing the importance of including functional and phylogenetic information in conservation-driven studies. [ABSTRACT FROM AUTHOR]

Highway agencies strive to carry out maintenance of traffic during road project implementation in a bid to reduce the safety and mobility adversities that typically accompany work zones. In certain cases, the agency resorts to a full road closure strategy, where the project location is blocked from traffic use and traffic is detoured to an alternate route, thus bypassing the project location. Often, there exist a number of alternative paths that could be used for the detour. Few specific guidelines exist for defining a detour path, resulting in technical, financial, and operational constraints dominating the detour planning process. The challenge, therefore, is how to identify the best candidate detour path based on several factors including, but not limited to technical, financial, and operational considerations. This paper proposes a methodology to address this question. The methodology is based on a multicriteria decision-making technique and is demonstrated using two case studies. The case study results are discussed in the context of the relative weight specifications of the key performance indicators (KPIs). The results highlight the impact of the KPIs and their weights on detour route choices. The methodology can be used as a basis for developing a decision-support tool to assist practitioners in selecting the best detours based on a comprehensive range of KPIs. This research contributes managerial aspects that can reduce the subjectivity in maintenance of traffic (MOT) strategy selection and lower the inconsistencies of prescribed detours for similar project conditions. [ABSTRACT FROM AUTHOR]

Recommendations analysis of road safety requires decision-making tools that accommodate weather uncertainties. Operation and maintenance of transport infrastructure have been one of the sub-areas that require attention due to its importance in the quality of the road. Several investigations have proposed artificial neural networks and Bayesian networks to assess the risk of the road. These methods make use of historic accident records to generate useful road safety metrics; however, there is less information on how climatic factors and road surface conditions affect the models that generate recommendations for safe traffic. In this research, Bayesian Network, as a Hidden Markov Models, and Apriori method are proposed to evaluate the open and closed state of the road. The weather and road surface conditions are explicitly written as a sequence of latent variables from observed data. Different weather variables were studied in order to evaluate both road states (open or close) and the results showed that the Hidden Markov Model provides explicit insight into the sequential nature of the road safety conditions but does not provide a directly interpretable result for human decision making. In this way, we complement the study with the Apriori algorithm using categorical variables. The experimental results show that combining the Hidden Markov Model and the Apriori algorithm provides an interpretable rule for decision making in recommendations of road safety to decide an opening or closing of the road in extreme weather conditions with a confidence higher than 90%. [ABSTRACT FROM AUTHOR]

We define a new cutting plane closure for pure integer programs called the two-halfspace closure. It is a natural generalization of the well-known Chvátal-Gomory closure. We prove that the two-halfspace closure is polyhedral. We also study the corresponding two-halfspace rank of any valid inequality and show that it is at most the split rank of the inequality. Moreover, while the split rank can be strictly larger than the two-halfspace rank, the split rank is at most twice the two-halfspace rank. A key step of our analysis shows that the split closure of a rational polyhedron can be obtained by considering the split closures of all k-dimensional (rational) projections of the polyhedron, for any fixed k ≥ 2 . This result may be of independent interest. [ABSTRACT FROM AUTHOR]

Background: Since air pollution and physical inactivity pose major public health risks, switching from cars to alternatives like public transport, cycling, and walking is important. Therefore, it is beneficial to identify key events for changes of mode choice. Methods: We examined the association between risk perception and mode choice during the temporary closure of a road bridge between two major German cities in early 2020 using binary and multinomial regression models. Results: 679 people participated in the survey. We found that 22% of car users switched to alternatives. The higher the perceived health risk from traffic-related air pollution, the more likely car users switched to alternatives (odds ratio [OR] = 1.76, 95% CI [1.14, 2.71]). Discussion: Attitude, subjective norm and perceived behavioral control were associated with maintaining but not with switching transport modes. In conclusion, the closure of a main road bridge may present a key event. To explain mode choice, risk perception is a potential extension to the theory of planned behavior. [ABSTRACT FROM AUTHOR]

Roads are human infrastructure that heavily affect wildlife, often with marked impacts on carnivores, including brown bears Ursus arctos. Here, we assessed the potential impact of road networks on the distribution of brown bears in the small, isolated and endangered Cantabrian population of north‐western Spain. To ascertain whether local road networks affect brown bear spatial distribution, we first assessed potential influences on the distance of bear locations to roads using candidate models which included topographic variables, landcover types, bear age and reproductive status, traffic volume and road visibility. Then, we built two sets of habitat suitability models, both with and without roads, to discern the possible loss of habitat suitability caused by roads. The mean distance of bear locations to the nearest road was 968 ± 804 m and the closest road was a low traffic road in 72.5% of cases. Candidate models showed little influence of our variables on bear distance to the nearest road, with the exception of elevation. Habitat suitability models revealed that road networks in our study area seem to have almost no effect on brown bear habitat suitability, except for females with yearlings during the denning season. However, this result may also be a consequence of the fact that only a small proportion (16.5%) of the cells classified as suitable bear habitats were crossed by roads, that is, most of the roads are primarily located in unsuitable bear habitats in the Cantabrian Mountains. Compared to previous studies conducted in other populations, mainly North American ones, our findings might suggest a different response of Eurasian brown bears to roads due to a longer bear‐human coexistence in Europe versus North America. However, the indirect approach used in our study does not exclude other detrimental effects, for example, road mortality, increased stress and movement pattern disruption, only detectable by more direct approaches such as telemetry. [ABSTRACT FROM AUTHOR]

Aim: Limited funds for conservation and research require the development of prioritization schemes. Traditionally, biodiversity metrics were used to delineate priority areas; however, a growing realization emphasizes that logistic factors should be also considered. Here, we combine species richness, past collection efforts, degree of habitat loss and accessibility to define priority areas and spatially orient fieldwork in a cost‐effective manner for xenarthrans. Location: Neotropics. Methods: We assessed spatial patterns of species richness in Xenarthra and identified diversity hotspots based on species distribution models. Spatial patterns and biases in the Xenarthra past collection efforts were analysed using a comprehensive database including 33,464 individual records for 34 species of Xenarthra. Finally, we produced priority area indices relating species richness and collection efforts with levels of habitat loss and accessibility (roads and rivers network) to highlight important but neglected areas. Results: Collection efforts were concentrated to a small portion of the Neotropics (central‐western Brazil, eastern Bolivia and north‐western Argentina) and were biased towards access routes. Only 4% of the Neotropics can be considered well sampled. Major xenarthran diversity hotspots include the Amazonian lowlands of Bolivia and the dry Chaco of Paraguay and Argentina. Priority areas for research varied depending on the metric analysed. Amazon holds a high diversity that remains poorly explored. Central Argentina and eastern Brazil are priority areas for research and conservation given the low sampling efforts, high diversity and endemic species, high levels of habitat loss and a dense road network. Main conclusions: Most areas of the Neotropics lack a proper assessment of the xenarthran assemblage, reflecting extensive knowledge shortfalls. Sites close to roads tend to be better sampled, but many areas with a dense road network are undersampled, being good candidates for low‐cost studies. Xenarthra diversity hotspots facing the highest levels of habitat alteration are the least protected and are priority for both research and conservation. Simultaneous efforts of data collection and conservation actions across most of the xenarthran range should be stimulated. [ABSTRACT FROM AUTHOR]

Simultaneous localization and mapping (SLAM) algorithm is a prerequisite for unmanned ground vehicle (UGV) localization, path planning, and navigation, which includes two essential components: frontend odometry and backend optimization. Frontend odometry tends to amplify the cumulative error continuously, leading to ghosting and drifting on the mapping results. However, loop closure detection (LCD) can be used to address this technical issue by significantly eliminating the cumulative error. The existing LCD methods decide whether a loop exists by constructing local or global descriptors and calculating the similarity between descriptors, which attaches great importance to the design of discriminative descriptors and effective similarity measurement mechanisms. In this paper, we first propose novel multi-channel descriptors (CMCD) to alleviate the lack of point cloud single information in the discriminative power of scene description. The distance, height, and intensity information of the point cloud is encoded into three independent channels of the shadow-casting region (bin) and then compressed it into a two-dimensional global descriptor. Next, an ORB-based dynamic threshold feature extraction algorithm (DTORB) is designed using objective 2D descriptors to describe the distributions of global and local point clouds. Then, a DTORB-based similarity measurement method is designed using the rotation-invariance and visualization characteristic of descriptor features to overcome the subjective tendency of the constant threshold ORB algorithm in descriptor feature extraction. Finally, verification is performed over KITTI odometry sequences and the campus datasets of Jilin University collected by us. The experimental results demonstrate the superior performance of our method to the state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

In recent years, intelligent driving technology based on vehicle–road cooperation has gradually become a research hotspot in the field of intelligent transportation. There are many studies regarding vehicle perception, but fewer studies regarding roadside perception. As sensors are installed at different heights, the roadside object scale varies violently, which burdens the optimization of networks. Moreover, there is a large amount of overlapping and occlusion in complex road environments, which leads to a great challenge of object distinction. To solve the two problems raised above, we propose RD-YOLO. Based on YOLOv5s, we reconstructed the feature fusion layer to increase effective feature extraction and improve the detection capability of small targets. Then, we replaced the original pyramid network with a generalized feature pyramid network (GFPN) to improve the adaptability of the network to different scale features. We also integrated a coordinate attention (CA) mechanism to find attention regions in scenarios with dense objects. Finally, we replaced the original Loss with Focal-EIOU Loss to improve the speed of the bounding box regression and the positioning accuracy of the anchor box. Compared to the YOLOv5s, the RD-YOLO improves the mean average precision (mAP) by 5.5% on the Rope3D dataset and 2.9% on the UA-DETRAC dataset. Meanwhile, by modifying the feature fusion layer, the weight of RD-YOLO is decreased by 55.9% while the detection speed is almost unchanged. Nevertheless, the proposed algorithm is capable of real-time detection at faster than 71.9 frames/s (FPS) and achieves higher accuracy than the previous approaches with a similar FPS. [ABSTRACT FROM AUTHOR]

Road extraction from remote sensing images is significant for urban planning, intelligent transportation, and vehicle navigation. However, it is challenging to automatically extract roads from remote sensing images because the scale difference of roads in remote sensing images varies greatly, and slender roads are difficult to identify. Moreover, the road in the image is often blocked by the shadows of trees and buildings, which results in discontinuous and incomplete extraction results. To solve the above problems, this paper proposes a multiscale feature encoding and long-range context-aware network (MECA-Net) for road extraction. MECA-Net adopts an encoder–decoder structure and contains two core modules. One is the multiscale feature encoding module, which aggregates multiscale road features to improve the recognition ability of slender roads. The other is the long-range context-aware module, which consists of the channel attention module and the strip pooling module, and is used to obtain sufficient long-range context information from the channel dimension and spatial dimension to alleviate road occlusion. Experimental results on the open DeepGlobe road dataset and Massachusetts road dataset indicate that the proposed MECA-Net outperforms the other eight mainstream networks, which verifies the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Fully supervised road segmentation neural networks from remote sensing images rely on a large number of densely labeled road samples, limiting their potential in large-scale applications. In this paper, a weakly-supervised road segmentation network based on structural and orientational consistency (SOC-RoadNet) is proposed to learn road surface from open-source road maps, thus supporting high-quality large-scale road extraction. The open-source road maps can be made with scribble-labels to train the weakly-supervised SOC-RoadNet. However, these scribble-labels that represent the approximate location of road centerlines with only one-pixel width cannot provide supervision for road boundaries, leading to low road surface segmentation accuracy using scribble-supervised methods. Existing weakly-supervised road extraction networks deploy complex scribble-label propagation procedures to generate pseudo labels to train models and exploit image edge maps to refine road boundaries. Nevertheless, road edges in images are blurry due to occlusions and spectral-confusing backgrounds, limiting reliability when processing complex scenes. The proposed SOC-RoadNet is designed as a one-stage end-to-end architecture that directly learns road surface features from scribble-labels without extra label propagation procedures. Instead of using unreliable edge maps to regularize road boundaries, a structural consistency loss function is introduced to evaluate the structural similarity between road surface segmentation results and the input images for improved road boundary accuracy. Considering that roads are elongated targets with local directional consistency, orientation learning is integrated to SOC-RoadNet to improve road integrity. A road refining module was designed to aggregate the road surface features and road orientation features to further refine the road extraction results. The reference road orientation maps are generated from the scribble labels; thus, the results of orientation learning are supervised without extra input. Extensive experimental results on the public Deep Globe Road Dataset and four city-scale images confirm the effectiveness of our SOC-RoadNet in large-scale road extraction tasks. [ABSTRACT FROM AUTHOR]

Mine closure practices have continued to improve over the last few decades; however, across the industry rehabilitation outcomes continue to fall short of community expectations. While examples of successful rehabilitation exist, there are still limited examples of mines closing, relinquishing, and transitioning to another land use. Barriers to relinquishment such as residual risk, land transfer liability, and limited next land use options are compounded by the lack of legislated mine relinquishment policy. Broader mine closure policy has evolved significantly over the last few decades in Australia, with recent changes in some states enhancing mandates requiring progressive rehabilitation and financial assurance mechanisms in an effort to continue to improve mine closure outcomes. Government authorities with legislative powers to report and influence rehabilitation activities in Queensland and Victoria are also considered a positive mine closure policy direction. Despite these recent legislative developments there is still no multi‐agency regulatory policy framework integrating mine closure and relinquishment in any Australian jurisdiction. This article explores how recent mine closure policy changes in Australia could be used by policy makers to enable relinquishment in the future and provides recommendations for an integrated multi‐agency relinquishment policy framework. [ABSTRACT FROM AUTHOR]

Although the performance of unmanned aerial vehicle (UAV) tracking has benefited from the successful application of discriminative correlation filters (DCF) and convolutional neural networks (CNNs), UAV tracking under occlusion and deformation remains a challenge. The main dilemma is that challenging scenes, such as occlusion or deformation, are very complex and changeable, making it difficult to obtain training data covering all situations, resulting in trained networks that may be confused by new contexts that differ from historical information. Data-driven strategies are the main direction of current solutions, but gathering large-scale datasets with object instances under various occlusion and deformation conditions is difficult and lacks diversity. This paper proposes an attention-based mask generation network (AMGN) for UAV-specific tracking, which combines the attention mechanism and adversarial learning to improve the tracker's ability to handle occlusion and deformation. After the base CNN extracts the deep features of the candidate region, a series of masks are determined by the spatial attention module and sent to the generator, and the generator discards some features according to these masks to simulate the occlusion and deformation of the object, producing more hard positive samples. The discriminator seeks to distinguish these hard positive samples while guiding mask generation. Such adversarial learning can effectively complement occluded and deformable positive samples in the feature space, allowing to capture more robust features to distinguish objects from backgrounds. Comparative experiments show that our AMGN-based tracker achieves the highest area under curve (AUC) of 0.490 and 0.349, and the highest precision scores of 0.742 and 0.662, on the UAV123 tracking benchmark with partial and full occlusion attributes, respectively. It also achieves the highest AUC of 0.555 and the highest precision score of 0.797 on the DTB70 tracking benchmark with the deformation attribute. On the UAVDT tracking benchmark with the large occlusion attribute, it achieves the highest AUC of 0.407 and the highest precision score of 0.582. [ABSTRACT FROM AUTHOR]

The United States has over three trillion vehicle miles of travel annually on over four million miles of public roadways, which require regular maintenance. To maintain and improve these facilities, agencies often temporarily close lanes, reconfigure lane geometry, or completely close the road depending on the scope of the construction project. Lane widths of less than 11 feet in construction zones can impact highway capacity and crash rates. Crash data can be used to identify locations where the road geometry could be improved. However, this is a manual process that does not scale well. This paper describes findings for using data from onboard sensors in production vehicles for measuring lane widths. Over 200 miles of roadway on US-52, US-41, and I-65 in Indiana were measured using vehicle sensor data and compared with mobile LiDAR point clouds as ground truth and had a root mean square error of approximately 0.24 feet. The novelty of these results is that vehicle sensors can identify when work zones use lane widths substantially narrower than the 11 foot standard at a network level and can be used to aid in the inspection and verification of construction specification conformity. This information would contribute to the construction inspection performed by agencies in a safer, more efficient way. [ABSTRACT FROM AUTHOR]

National forest roads allow access to public lands providing connections to natural and cultural heritage. Planning processes that address potential road closures or conversions can be highly contentious. Public participatory GIS (PPGIS) has been used as a tool to gather information for environmental planning and decision-making. Our PPGIS approach in a national forest in Washington (USA) incorporated workshops and online engagement with 1,810 participants to gather public input for sustainable roads planning. We identified the most important forest destinations and developed an analytical framework for assessing forest roads based on the density and diversity of use. In this paper, we summarize our PPGIS process and identify challenges faced in the application of socio-spatial data. A comparative analysis of road planning in other forests further highlights challenges in incorporating public use data. While the PPGIS process was valued for relationship-building, it is less evident how directly the socio-spatial data informed outcomes. [ABSTRACT FROM AUTHOR]

Scent marks deposited as semiochemical signals are a primary mode of communication for a broad range of mammal species. Such scent signals are often deposited at specific, frequently visited marking sites called latrines. Despite descriptions of widespread latrine use by numerous mammal species, detailed understanding of site visit rates and latrine function is lacking. Here we report for the first time a quantitative assessment of scent-marking behaviours that represent interpack olfactory communication by African wild dogs, Lycaon pictus , at latrines visited by multiple resident neighbouring packs, hereafter called a 'shared marking site' (SMS). We show that multiple packs visited specific SMSs frequently and regularly throughout the year, with a notable decrease in visits during the 3-month denning season coinciding with a contraction in range size. In addition to resident neighbouring packs, dispersing individuals visited and scent-marked at SMSs, suggesting that latrines function at least in part as sites communicating information about residence and possibly reproductive status. Further detailed investigation of the relevance of latrine use to territorial behaviour, ranging, habitat use and dispersal in this species is required, particularly as it may have direct applied conservation implications for this wide-ranging but territorial endangered species. • African wild dogs repeatedly visit and scent-mark at shared marking sites (SMSs). • Visits decrease during the denning season, coinciding with a range contraction. • SMSs are implicated in territorial advertisement. • SMSs are closer to roads than are controls and avoid grassland and permanent water. [ABSTRACT FROM AUTHOR]

Traffic signs are indispensable fixtures in modern transportation activities, which are installed along the roadside or over the pathway to provide important prompt messages. The timely emergences, complete visibilities, and definite signals of traffic signs matter significantly to direct the driving behaviors and ensure the convenience and security of the transportation activities. Moreover, the efficient and accurate recognition of traffic signs can also provide decisive evidences to a variety of intelligent transportation systems. Nevertheless, the unignorable presence issues of traffic signs caused by vision factors, such as small sizes, dimness, deformations, and occlusions, impact essentially on the high-quality recognition of traffic signs. This paper develops a novel attentive semi-anchoring guided high-resolution network, named SignHRNet, for street-level traffic signs recognition purpose. First, stacked with a high-resolution network boosted by a dual-attention module as the feature extractor, the SignHRNet can exploit informative channel features and task-oriented spatial features to generate multiscale strong feature semantics for instance-level predictions. Second, designed with a semi-anchoring guided detection strategy assisted by instance-aware feature alignment, the SignHRNet can achieve highly-efficient sign type categorization and highly-accurate sign location determination. The proposed SignHRNet is intensively evaluated on three large-size datasets towards traffic signs recognition. Quantitative verifications demonstrate a competitive accuracy with an average mAP, mAP50, and mAP75 of 72.85%, 96.48%, and 85.31%, respectively, in processing traffic signs of varying self-conditions under diverse scenarios. Ablative and comparative analyses also confirmed the practical reliability and performance superiority of the SignHRNet in traffic signs recognition applications. [ABSTRACT FROM AUTHOR]

Wrong-way driving (WWD) crashes result in more fatalities per crash, involve more vehicles, and cause extended road closures compared to other types of crashes. Previous studies have used descriptive and parametric statistical models to identify factors that affect WWD crash severity on limited access facilities. This study adopted a combination of non-parametric data mining techniques aiming to recognize the pattern of contributing factors that affect the WWD crash severity on non-limited access facilities. These non-parametric methods can handle heterogeneity in crash datasets well. In this study, hierarchical clustering was used to divide the crash dataset into homogeneous clusters. A random forests analysis was used to select important variables, and decision trees and decision rules were generated to show the underlying pattern and interactions between different factors that affect WWD crash severity. The analysis was based on 1,475 WWD crashes that occurred on arterial streets from 2012-2016 in Florida. Results show that head-on collisions, weekend days, high-speed facilities, crashes involving vehicles entering from a driveway, dark-not lighted roadways, older drivers, and driver impairment are important factors that play a crucial role in WWD crash severity on non-limited access facilities. [ABSTRACT FROM AUTHOR]

Although the Seljuk State experienced a period of rising with the Melikshah period, its gradual downturn period after Melikshah's death led to the emergence of independent states such as the Khârizmshahs. The Khârizmshahs, entered into a directly independent formation for the first time compared to the periods of Anustekin, Kutbeddin Muhammed and Atsız, where struggles were made for the state to become independent. Historians accept Il Arslan as the first independent sultan of the Khârizmshahs. Taking advantage of the emergence of atabek and small sultans as a result of the political conflicts before the attack of the Mongols, the Khârizmshahs expanded their borders from the Ural Mountains in the north to the Golden Horn in the south, from the Sind mountains in the east to Iraq in the west. Earlier in XIII, when the Khârizmshahs continued to exist in the Turkestan and Transoxiana region, Genghis Khan brought all the tribes together in 1206 and established the Mongol state. Genghis Khan wanted the commercial relations between the two sides to continue despite the inconsistent attitudes of Alâeddin Muhammed. However, the murder of around 450 merchants he sent to the city of Otrar by Governor Yinâl Khan on the grounds that they were spies, led to the deterioration of relations. After the peace road was closed, Genghis Khan started to attack various places in the Transoxiana region with his sons Ögedey, Cuci and Çağatay. In 1220, the Mongolian troops broke the resistance of the Khârizmshahs State as a result of the struggle that lasted for about five months and captured the city of Otrar. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to show how the national border closures within the EU-27 have an impact on changes in potential accessibility in individual transport at the NUTS3 level. We are referring to the situation that occurred during the COVID-19 pandemic outbreak in Europe in March 2020. The study distinguishes between long and short trips, comparing the situation before the pandemic with that after the complete closure of national borders by all EU countries, thus showing which areas of the EU will suffer from accessibility losses for both long and short trips. We conclude that the spatial pattern of regions at risk of peripheralisation for short trips well defines the zones in which a serious crisis threatens local cross-border commuting. The threat of peripheralisation for long trips mainly concerns those parts of countries which are closer to the demographic and economic core of the European Union. Nevertheless, it is also compounded by other factors: including the national settlement and road networks. • COVID-19 and the closure of borders have an impact on road potential accessibility. • The COVID-19 pandemic is a black swan event for border regions and border sections. • We compare full permeability and closure of national borders within the EU-27 (NUTS3). • Accessibility losses are related to cross-border commuting and migration flows. [ABSTRACT FROM AUTHOR]

Several industrial pick-and-place applications, such as collaborative assembly lines, rely on visual tracking of the parts. Recurrent occlusions are caused by the manipulator motion decrease line productivity and can provoke failures. This work provides a complete solution for maintaining the occlusion-free line of sight between a variable-pose camera and the object to be picked by a 6R manipulator that is not wrist-partitioned. We consider potential occlusions by the manipulator as well as the operator working at the assembly station. An actuated camera detects the object goal (part to pick) and keeps track of the operator. The approach consists of using the complete set of solutions obtained from the derivation of the univariate polynomial equation solution to the inverse kinematics (IK). Compared to numerical iterative solving methods, our strategy grants us a set of joint positions (posture) for each root of the equation from which we extract the best (minimizing the risks of occlusion). Our analytical-based method, integrating collision and occlusion avoidance optimizations, can contribute to greatly enhancing the efficiency and safety of collaborative assembly workstations. We validate our approach with simulations as well as with physical deployments on commercial hardware. [ABSTRACT FROM AUTHOR]

Summary: Host‐associated microbiomes play an essential role in the health of organisms, including immune system activation, metabolism and energy uptake. It is well established that microbial communities differ depending on the life stage and natural history of the organism. However, the effects of life stage and natural history on microbial communities may also be influenced by human activities. We investigated the effects of amphibian life stage (terrestrial eft vs. aquatic adult) and proximity to roadways on newt skin bacterial communities. We found that the eft and adult life stages differed in bacterial community composition; however, the effects of roads on community composition were more evident in the terrestrial eft stage compared to the aquatic adult stage. Terrestrial efts sampled close to roads possessed richer communities than those living further away from the influence of roads. When accounting for amplicon sequence variants with predicted antifungal capabilities, in the adult life stage, we observed a decrease in anti‐fungal bacteria with distance to roads. In contrast, in the eft stage, we found an increase in anti‐fungal bacteria with distance to roads. Our results highlight the need to consider the effects of human activities when evaluating how host‐associated microbiomes differ across life stages of wildlife. [ABSTRACT FROM AUTHOR]

Scour is one of the main causes of bridge failures resulting in significant macro-economic impacts, often beyond the direct costs of infrastructure damage. Given the pressure to increase the resilience of transport networks, ageing bridge infrastructure, constrained budgets, variable knowledge of asset conditions and limited data, mixed ownership and operation of bridges, and concerns about the risks of climate change, there is a need to implement cost-effective monitoring and maintenance strategies. To this end, this study aims to set the scene for a risk-informed approach for tackling bridge scour, while considering the socio-economic impacts of disruptions due to bridge failures or closures. This study reviews the current practices in predicting, monitoring and managing bridge scour. It discusses the development of a risk-informed approach to aid the whole-life appraisal of bridges while considering the direct and indirect costs associated with bridge failure or closures. The approach provides a rational means to enable asset managers to evaluate the factors that affect bridge failure risk, select and prioritise appropriate mitigation measures, thereby improving the allocation of scarce monitoring and maintenance resources. [ABSTRACT FROM AUTHOR]

The work zones greatly change the traffic wave characteristics on the urban road and further significantly influence the signal timing schemes. However, studies on the traffic wave under the influence of work zones are limited. This paper attempts to investigate how a work zone changes the traffic wave propagation characteristics. The traffic wave profiles for different scenarios are analyzed to explore the propagation characteristics of the traffic waves. Then the novel models for the various traffic waves are proposed. Furthermore, a real case study is conducted to evaluate the performance of the proposed models. The study indicates on the road with the work zone, the lane-blockage phenomenon is more likely to occur, which can be improved by releasing the left-turn vehicles before the through-right vehicles in the intersection signal scheme. The case study shows the proposed models have good performance, with the MAPE value of 20%. [ABSTRACT FROM AUTHOR]