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The aetiology of vestibular migraine (VM) has not yet been defined; endolymphatic hydrops (EH) has been suggested as a candidate.This study aimed to clarify the relationship between VM and EH using neuro-otological tests, including the EH presumption test.Fourteen patients with VM underwent caloric testing, video head impulse test (vHIT), cervical and ocular vestibular evoked myogenic potential (cVEMP and oVEMP), and EH presumption tests such as the Futaki's test and furosemide loading VEMP.Caloric testing was abnormal in two of the 14 cases (14.3%), and vHIT was abnormal in one of 12 cases (8.3%). Abnormal asymmetry ratios (ARs) of cVEMP and oVEMP were observed in two of 14 cases (14.3%) and six of 13 cases (46.2%), respectively. Futaki's test results were positive in five of 14 cases (35.7%). Furosemide loading VEMP was positive in seven of 14 cases (50.0%). Nine patients (64.3%) were positive for at least one EH presumption test.EH is not a rare finding in VM; however, the ratio is less than that in Meniere's disease.

Objective We provided diagnostic and therapeutic strategies for Meniere's disease in accordance with Japanese Clinical Practice Guideline of Meniere's disease and delayed endolymphatic hydrops 2nd ed. Tokyo: Kanehara Shuppan; 2020 edited by the Japan Society for Equilibrium Research. Methods The Committee for Clinical Practice Guidelines was entrusted with a review of the scientific literature on the above topic. Clinical Questions (CQs) concerning the treatment for Meniere's disease were produced, and the literature according to each of them including CQ was searched. The recommendations are based on the literature review and the expert opinion of a subcommittee. Results Diagnosis criteria of Meniere's disease are classified into Meniere's disease with typical cochlear and vestibular symptoms, and atypical Meniere's disease with either cochlear symptoms or vestibular symptoms. Treatment of Meniere's disease was composed of lifestyle changes, medications such as anti-vertigo drugs and diuretics, middle ear positive pressure treatment, and selective destruction of the vestibule. Conclusion Meniere's disease is diagnosed based on clinical histories and examination findings after processes of differential diagnosis. Treatment option of the disease should be selected in order of invasiveness, according to the severity of the disease and the response to each treatment.

A reinforcement learning-based dynamic congestion pricing method for morning commute problems is proposed. In this method, tolls are iteratively updated day by day based on observable information such as traffic volume. The advantage of the method is two fold. First, the method does not require travelers personal preferences such as value of time. Second, the method does not require manually designed toll update scheme; instead, the method automatically find the most efficient toll by a data-driven manner. Results of numerical experiments show that the proposed method properly decreased traffic congestion in various types of networks. Especially, in the experiment with a single bottleneck model, total waiting time decreases to nearly zero in about 200 days. One of future issues is more stable coordination among the time zones.

Liposarcoma is a soft tissue neoplasm that commonly develops in the lower extremities and rarely in the head and neck region. Herein, we report the case of a patient with primary liposarcoma that was detected in the mastoid antrum during staged tympanoplasty for cholesteatoma. The tumor adjacent to the attic cholesteatoma was resected completely, and the pathological diagnosis was that of myxoid-type liposarcoma. Because positron emission tomography after the surgery showed no signs of tumor remnants or systemic metastasis, a second-stage surgery was performed 8 months after the first surgery. After confirming that there was no recurrence, tympanoplasty type III with interposition between the stapes and malleus and canal reconstruction was performed. No recurrence was observed for 5 years, and to date, good hearing has been maintained. This is the first report on long-term follow-up of a patient with liposarcoma in the mastoid antrum.

Urban rail transit often operates with high service frequencies to serve heavy passenger demand during rush hours. Such operations can be delayed by two types of congestion: train congestion and passenger congestion, both of which interact with each other. This delay is problematic for many transit systems, since it can be amplified due to the interaction. However, there are no tractable models describing them; and it makes difficult to analyze management strategies of congested transit systems in general and tractable ways. To fill this gap, this article proposes simple yet physical and dynamic model of urban rail transit. First, a fundamental diagram of transit system (i.e., theoretical relation among train-flow, train-density, and passenger-flow) is analytically derived considering the aforementioned physical interaction. Then, a macroscopic model of transit system for dynamic transit assignment is developed based on the fundamental diagram. Finally, accuracy of the macroscopic model is investigated by comparing to microscopic simulation. The proposed models would be useful for mathematical analysis on management strategies of urban rail transit systems, such as optimal dynamic pricing for travel demand management.

A trial-and-error congestion pricing scheme finds the optimal toll based only on observable information (e.g., travel time) without information on travelers’ personal preferences that are often unobservable in practice (e.g., value of time, scheduling preference). This paper proposes a trial-and-error pricing scheme for the morning commute problem, also known as the departure time choice problem and Vickrey’s bottleneck model, with day-to-day dynamics. The proposed scheme is guaranteed to find the social optimal congestion toll under somewhat restrictive assumptions. We numerically confirm that the proposed scheme converges to the social optimal toll regardless of the parameter setting, and it decreased the social cost fairly quickly.

In an era of highly developed information and communication technologies, social networks play an important role in all aspects of businesses, including transportation. The use of dynamic ridesharing systems, which are systems in which travelers can find partner(s) to share their upcoming rides in real time, is also expected to be affected by the information propagated by friends on social networks. In this study, we investigate how such information in both online and offline social networks affects travelers’ decisions pertaining to ridesharing over days. Because travelers can choose which information to obtain, we also investigate whether the information collected only from nearby friends (in physical space) affects their decisions. To do this, we formulate a day-to-day behavior-based model of a dynamic ridesharing system. Results obtained from the numerical experiments, which are based on the formulated model, show that with the information propagation on social networks, the more friends that a traveler has, the greater is the number of travelers who use dynamic ridesharing systems.

A dynamic ridesharing system (DRS) is a system where users can find ridesharing partner(s) at any time, even shortly before making a trip. A DRS that does not consider individual preferences may ca...

Small imaging satellites (SISs), which has attracted attention in remote sensing field recently, would provide a novel type of data for traffic state estimation (TSE): that is, spatial distribution of every cars in anywhere on our planet with relatively short time interval. This nature is particularly useful to complement connected vehicle (CV) data, which is sampled but time-continuous data. This paper proposes an ensemble Kalman filter-based TSE method using SIS and CV data. The proposed method endogenously estimates the fundamental diagram of traffic flow and penetration rate of CVs based only on SIS and CV data, making the method completely free from roadside detectors. The accuracy of the proposed method is verified by numerical simulation.

The presence of endolymphatic hydrops can be suggested by improving the amplitude of vestibular-evoked myogenic potential (VEMP) after furosemide administration (furosemide loading VEMP [FVEMP]). The authors aimed to determine a stimulation frequency and judgment criteria to ascertain whether a revised FVEMP protocol can be applied to clinical settings.The study included 25 individuals with unilateral Meniere's disease (MD) and 11 normal healthy volunteers. Normalized amplitude of VEMP, using a tone burst sound at 250, 500, 700, 1000, 1500 and 2000 Hz, was measured before and after furosemide administration in the two groups. Improvement ratio (IR) of amplitude was calculated at each frequency.There were no significant differences in IR between the control group and the MD group at each frequency, except at 500 Hz. Receiver operating characteristic curve analysis revealed an IR cut-off value of 14.2% at 500 Hz, with a sensitivity of 0.706 and a specificity of 0.810.The revised FVEMP protocol using a 500 Hz tone burst stimulus and normalized amplitudes was defined as positive when IR exceeded 14.2% or when a biphasic wave could be detected after furosemide administration in cases without a detectable biphasic wave before administration.

We used ocular vestibular evoked myogenic potentials to investigate the relationship between residual dizziness and utricular function following the canalith repositioning procedure for benign paroxysmal positional vertigo.Ocular vestibular evoked myogenic potentials were measured in 44 patients (40 included in analyses, four excluded) with successful results from the canalith repositioning procedure. The patients were examined before treatment and again one week after treatment. We analyzed how various general factors and ocular vestibular evoked myogenic potentials related to residual dizziness.Residual dizziness was not related to gender, affected side, age, duration of symptoms, recurrence, or the results of the initial ocular vestibular evoked myogenic potential test (p .05). However, residual dizziness was significantly associated with the results of the second ocular vestibular evoked myogenic potential test (p = .007).Residual dizziness after a successful canalith repositioning procedure may be caused by persistent utricular dysfunction.

Traffic flow monitoring is essential to take effective measures on traffic jams. Wide-ranging monitoring is still a challenging task, because the conventional observation methods by roadside detectors only observe the location where the costly sensors are installed. In this study, we propose a wide-ranging traffic flow monitoring method utilizing remote sensing by small satellites, which is a new approach of remote sensing. Compared with the conventional remote sensing satellites, small satellites have a significant advantage: they can conduct frequent observation (e.g., few hours) by using dozens of satellites simultaneously. On the other hand, a severe disadvantage is that their sensor is inferior due to the size limitation, and thus existing vehicle detection methods are not applicable to small satellite imagery. In order to solve this issue, we develop a convolutional neural network-based image recognition algorithm that estimate traffic density. The proposed method is applied to satellite imagery with 93 cm resolution, which corresponding to small satellite imagery. The accuracy of the proposed method was RMSE 11 veh/km, sufficient to recognize traffic situations.

"Sharing economy", including car-sharing and ride-sharing, will change our society and transport in the near future. To effectively introduce ride-sharing service into our society, we need to determine route and schedule of vehicles based on users’ activity. We also need to understand how users’ activity patterns affect the performance of this sharing service, and we have to evaluate social benefit of introducing ride-sharing service. The objective of this study is to investigate how the ride-sharing service would be successfully operated in the above context. The optimal vehicle routing and scheduling problem which satisfies all the users’ activities is formulated as an integer linear programming problem. By using the proposed model, numerical experiments are conducted with different types of activity patterns. Then, efficiency of the optimized ride-sharing service is examined by comparing its performance with those of car-sharing service and fully private-owned car transport. The results show spatial and temporal distribution of users’ activity patterns will have great effects on the performance of ride-sharing services.

A fundamental diagram (FD), also known as flow–density relation, is one of the most important principles in traffic flow theory. It would be valuable if an FD could be calibrated by using GPS-equipped probe vehicles; since they can continuously collect data from wide spatiotemporal area, compared to traditional fixed sensors. This paper proposes methods for calibrating an FD from trajectories of sampled vehicles. We formulate a method that identifies values of a free-flow speed and a critical density of a tri-angular FD, while it relies on exogenous assumptions on FD's functional form and a value of its jam density. Then, a heuristic algorithm for FD calibration in actual traffic environment is developed based on the proposed method. It was validated using traffic data generated by microscopic traffic simulator. The results suggested that the proposed methods can calibrate an FD precisely and robustly. It implies that FDs in road sections on which congestion happens frequently can be calibrated using probe vehicles, if probe vehicle data were collected for a long period. Therefore, the proposed methods would contribute to significant improvement of applicability of probe vehicle-based traffic management methods.

Automated and connected vehicles (ACVs) have received a great deal of attention. Indeed, their full market penetration will be desirable in terms of traffic efficiency, as ACVs can efficiently drive by precisely and instantaneously communicating, recognizing, and reacting to other ACVs. However, it is not yet certain whether traffic efficiency is improved in mixed traffic where ratio of manual vehicles is substantially high. This is because, for example, ACVs in mixed traffic may require excessive safety clearance, as they have to rely on relatively imperfect vision/radar-based vehicle recognition. Meanwhile, relative benefit of ACVs compared to manual vehicles would be proportional to travel time (because the most significant merit of ACVs for their driver is comfortable in-vehicle experience) and therefore severity of congestion. Consequently, equilibrium states of a myopic car market may suffer severer congestion and higher social cost than the current state—this is congestion paradox. This kind of phenomena can be considered as a consequence of market penetration of a good with network externality or social interaction, where market penetration of ACVs is endogenously determined based on their cost/benefit which depend on current number of ACVs users. This study analyzes this problem under idealized conditions. Specifically, a theoretical model of endogenous market penetration of ACVs considering changes in value of time, travel time, and transportation fare, which are the most direct impacts of ACVs to the society, is formulated. Then, its market dynamics is analyzed. Finally, strategic policies to avoid congestion paradox and achieve social optimum are proposed.