A Personalized Trip Planner For Vulnerable Road Users

This research presents an adaptive and personalized routing model that enables individuals with disabilities to save their route preferences to a mobility assistant platform. The proactive approach based on anticipated user need accommodates vulnerable road users’ personalized optimum dynamic routing rather than a reactive approach passively awaiting input. Most of the currently available trip planners target the general public’s use of simpler route options prioritized based on static road characteristics. These static normative approaches are only satisfactory when conditions of intermediate intersections in the network are consistent, a constant rate of change occurs per each change of the segment condition, and the same fixed routes are valid every day regardless of the user preference. In this study, we model the vulnerable road user mobility problem by accommodating personalized preferences changing by time, sidewalk segment traversability, and the interaction between sidewalk factors and weather conditions for each segment contributing to a path choice. The developed reinforcement learning solution presents a lower average cost of personalized, accessible, and optimal path choices in various trip scenarios and superior to traditional shortest path algorithms (e.g., Dijkstra) with static and dynamic extensions

DISPATCHING AND RELOCATION OF EMERGENCY VEHICLES ON FREEWAYS: THEORIES AND APPLICATIONS

Resource allocation decisions are made to serve the current emergency without knowing which future emergency will be occurring. Different ordered combinations of emergencies result in different performance outcomes. Even though future decisions can be anticipated with scenarios, previous models follow an assumption that events over a time interval are independent. This dissertation follows an assumption that events are interdependent, because speed reduction and rubbernecking due to an initial incident provoke secondary incidents. The misconception that secondary incidents are not common has resulted in overlooking a look-ahead concept. This dissertation is a pioneer in relaxing the structural assumptions of independency during the assignment of emergency vehicles. When an emergency is detected and a request arrives, an appropriate emergency vehicle is immediately dispatched. We provide tools for quantifying impacts based on fundamentals of incident occurrences through identification, prediction, and interpretation of secondary incidents. A proposed online dispatching model minimizes the cost of moving the next emergency unit, while making the response as close to optimal as possible. Using the look-ahead concept, the online model flexibly re-computes the solution, basing future decisions on present requests. We introduce various online dispatching strategies with visualization of the algorithms, and provide insights on their differences in behavior and solution quality. The experimental evidence indicates that the algorithm works well in practice. After having served a designated request, the available and/or remaining vehicles are relocated to a new base for the next emergency. System costs will be excessive if delay regarding dispatching decisions is ignored when relocating response units. This dissertation presents an integrated method with a principle of beginning with a location phase to manage initial incidents and progressing through a dispatching phase to manage the stochastic occurrence of next incidents. Previous studies used the frequency of independent incidents and ignored scenarios in which two incidents occurred within proximal regions and intervals. The proposed analytical model relaxes the structural assumptions of Poisson process (independent increments) and incorporates evolution of primary and secondary incident probabilities over time. The mathematical model overcomes several limiting assumptions of the previous models, such as no waiting-time, returning rule to original depot, and fixed depot. The temporal locations flexible with look-ahead are compared with current practice that locates units in depots based on Poisson theory. A linearization of the formulation is presented and an efficient heuristic algorithm is implemented to deal with a large-scale problem in real-time

Travelers\u27 Rationality in Online Anticipatory Emergency Response Model

Traditional allocations decisions of freeway emergency resources only focused on serving the current emergency and have ignored which future emergency will be occurring. These studies have myopic decisions with an assumption of independency between emergencies and neglected travelers’ experience on unexpected events during their commuting. This research will contribute in relaxing the structural assumptions of independency between events, in optimizing online look‐ahead decisions, and in designing behaviors of individual travel agents during the assignment of emergency vehicles. An agent based online optimization model is proposed to represent boundely rational decisions under strictly imposed capacity constraints, due to clearing activities at emergency site. Under tight transportation capacity due to a lane‐ blockage for clearing an emergency, user equilibrium will be considered on the network. This research will find rationality of each traveler to minimize disutility within rational bands, choosing user optimal path from a limited number of capacity feasible routing options. TransModeler, simulation software, will be used to test the optimization model with simulation with a direct and indirect impact of dispatching policy on transportation network and to test the effect of dispatching model on travelers’ rational behavior. The output of the simulation will provide information about wide area multimodal networks in great detail and with high fidelity

Quantifying non-recurring congestion impact on secondary incidents using probe vehicle data

As a significant cost and externality to economic efficiency, congestion is partly caused by traffic incidents. For more systematic, planned and coordinated incident management, quantifying a primary incident’s impact on secondary incidents is crucial and challenging. Many thresholds have been suggested in defining the secondary incidents, but there is no universal acceptance of a definition and corresponding set of measurement parameters. Static threshold methods cannot consider the actual representation of prevailing traffic conditions when the incidents took place. On the other hand, dynamic methods have disadvantages because necessary traffic detector data may not be available, and replication of the incidents using a simulation package can be time consuming. The novelty of this study rests in the attempt of a probe vehicle technique for capturing the dynamics of traffic evolution during the primary-crash incidents. Compared to the previous thresholds which have many errors, proposed speed contour map from Traffic Message Channel codes provides accurate feasible area for identification of secondary incidents

A Markov Decision Process Approach to Vacant Taxi Routing with E-Hailing

The optimal routing of a vacant taxi is formulated as a Markov Decision Process (MDP) problem to account for long-term profit over the full working period. The state is defined by the node at which a vacant taxi is located, and action is the link to take out of the node. State transition probabilities depend on passenger matching probabilities and passenger destination probabilities. The probability that a vacant taxi is matched with a passenger during the traversal of a link is calculated based on temporal Poisson arrivals of passengers and spatial Poisson distributions of competing vacant taxis. Passenger destination probabilities are calculated directly using observed fractions of passengers going to destinations from a given origin. The MDP problem is solved by value iteration resulting in an optimal routing policy, and the computational efficiency is improved by utilizing parallelized matrix operations. The proposed model and an efficient implementation of the value iteration algorithm are tested in a case study with parameters derived from GPS trajectories of over 12,000 taxis in Shanghai, China for a study period of 5:30 - 11:30 am on a typical weekday. The optimal routing policy is compared with three heuristics based on simulated trajectories. Results show that the optimal routing policy improves average unit profit by 23.0% and 8.4% over the random walk and local hotspot heuristic respectively; and improves occupancy rate by 23.8% and 8.3% respectively. The improvement is larger during higher demand periods

Usefulness of the Modified Videofluoroscopic Dysphagia Scale in Choosing the Feeding Method for Stroke Patients with Dysphagia

Introduction: The Videofluoroscopic Dysphagia Scale (VDS) is used to predict the long-term prognosis of dysphagia in patients with strokes. However, the inter-rater reliability of the VDS was low in a previous study. To overcome the mentioned limitations of the VDS, the modified version of the VDS (mVDS) was created and clinically applied to evaluate its usefulness in choosing the feeding method for stroke patients with dysphagia. Methods: The videofluoroscopic swallowing study (VFSS) data of 56 stroke patients with dysphagia were collected retrospectively. We investigated the presence of aspiration pneumonia and the selected feeding method. We also evaluated the correlations between the mVDS and the selected feeding method, and between the mVDS and the presence of aspiration pneumonia after stroke. Univariate logistic regression and receiver operating characteristic analyses were used in the data analysis. Results: The inter-rater reliability (Cronbach α value) of the total score of the mVDS was 0.886, which was consistent with very good inter-rater reliability. In all patients with dysphagia, the supratentorial stroke subgroup, and the infratentorial stroke subgroup, the mVDS scores were statistically correlated with the feeding method selected (p < 0.05) and the presence of aspiration pneumonia (p < 0.05). Conclusions: The mVDS can be a useful scale for quantifying the severity of dysphagia, and it can be a useful tool in the clinical setting and in studies for interpreting the VFSS findings in stroke patients with dysphagia. Further studies with a greater number of patients and various stroke etiologies are required for more generalized applications of the mVDS

Association of Plasma Oligomerized Amyloid-beta and Cerebral White Matter Lesions in a Health Screening Population

Background: Cerebral white matter lesions (WML) are related to a higher risk of vascular and Alzheimer's dementia. Moreover, oligomerized amyloid-beta (OA beta) can be measured from blood for dementia screening. Objective: We aimed to investigate the relationship of plasma OA beta levels with clinical and radiological variables in a health screening population. Methods: WML, other volumetric parameters of magnetic resonance images, cognitive assessment, and plasma OA beta level were evaluated. Results: Ninety-two participants were analyzed. The majority of participants' clinical dementia rating was 0 or 0.5 (96.7%). White matter hyperintensities (WMH) increased with age, but OA beta levels did not (r(2) = 0.19, p < 0.001, r(2) = 0.03, p = 0.10, respectively). No volumetric data, including cortical thickness/hippocampal volume, showed any significant correlation with OA beta. Log-WMH volume was positively correlated with OA beta (r = 0.24, p = 0.02), and this association was significant in the periventricular area. White matter signal abnormalities from 3D-T1 images were also correlated with the OA beta in the periventricular area (p = 0.039). Multivariate linear regression showed that log-WMH values were independently associated with OA beta (B = 0.879 (95% confidence interval 0.098 -1.660, p = 0.028)). Higher tertiles of WMH showed higher OA beta levels than lower tertiles showed (p = 0.044). Using a cutoff of 0.78 ng/mL, the high OA beta group had a larger WMH volume, especially in the periventricular area, than the low OA beta group (p = 0.036). Conclusion: Both WML and plasma OA beta levels can be early markers for neurodegeneration in the healthcare population. The lesions, especially in the periventricular area, might be related to amyloid pathogenesis, which strengthens the importance of WML in the predementia stage.N

Seasonal Developing Xylem Transcriptome Analysis of <i>Pinus densiflora</i> Unveils Novel Insights for Compression Wood Formation

Wood is the most important renewable resource not only for numerous practical utilizations but also for mitigating the global climate crisis by sequestering atmospheric carbon dioxide. The compressed wood (CW) of gymnosperms, such as conifers, plays a pivotal role in determining the structure of the tree through the reorientation of stems displaced by environmental forces and is characterized by a high content of lignin. Despite extensive studies on many genes involved in wood formation, the molecular mechanisms underlying seasonal and, particularly, CW formation remain unclear. This study examined the seasonal dynamics of two wood tissue types in Pinus densiflora: CW and opposite wood (OW). RNA sequencing of developing xylem for two consecutive years revealed comprehensive transcriptome changes and unique differences in CW and OW across seasons. During growth periods, such as spring and summer, we identified 2255 transcripts with differential expression in CW, with an upregulation in lignin biosynthesis genes and significant downregulation in stress response genes. Notably, among the laccases critical for monolignol polymerization, PdeLAC17 was found to be specifically expressed in CW, suggesting its vital role in CW formation. PdeERF4, an ERF transcription factor preferentially expressed in CW, seems to regulate PdeLAC17 activity. This research provides an initial insight into the transcriptional regulation of seasonal CW development in P. densiflora, forming a foundation for future studies to enhance our comprehension of wood formation in gymnosperms

Establishment of an Efficient In Vitro Propagation of Cnidium officinale Makino and Selection of Superior Clones through Flow Cytometric Assessment of DNA Content

Cnidium officinale is a valuable medicinal plant cultivated in Asia for its rhizomes. This study reports the in vitro regeneration of Cnidium officinale plants and the induction of rhizomes from microshoots. The rhizomatous buds of Cnidium officinale induced multiple shoots on Murashige and Skoog (MS) medium supplemented with 0.5 mg L&minus;1 BA, which led to the regeneration of plants within four weeks of culture. After four weeks of culture, the plants were assessed for fresh weight, the number of leaves, the number of roots, and the length of roots to compare the performance of the different clones. The clones with good growth characteristics were selected with the aid of a flow cytometric analysis of 2C nuclear DNA content. The plants bearing high DNA values showed better growth characteristics. Various factors, namely, sucrose concentration (30, 50, 70, and 90 g L&minus;1), ABA (0, 0.5, 1.0, and 2.0 mg L&minus;1), the synergistic effects of BA (1.0 mg L&minus;1) + NAA (0.5 mg L&minus;1) and BA (1.0 mg L&minus;1) + NAA (0.5 mg L&minus;1) + ABA (1.0 mg L&minus;1) with or without activated charcoal (1 g L&minus;1), and light and dark incubation were tested on rhizome formation from microshoots. The results of the above experiments suggest that MS medium supplemented with 50 g L&minus;1 sucrose, 1.0 mg L&minus;1 ABA, and 1 g L&minus;1 AC is good for the induction of rhizomes from the shoots of Cnidium officinale. Plantlets with rhizomes were successfully transferred to pots, and they showed 100% survival