Stop Duration Research Articles

Acoustic features of labial and dental plosives in children with hypernasality

Cleft lip and palate (CLP) is a birth defect that can have negative effects on feeding, physical appearance, speech, hearing, and psychological development.VFI-induced hypernasality are high-pressure sounds such as plosives, fricatives, and affricates. In this study, the influence of hypernasality on plosive sounds was investigated. Six children with CLP with hypernasality and six children with typical development participated in this descriptive comparative study. All of the participants were between 10 and 12 years old and were native Turkish speakers. These two groups were matched by age and gender. For the acoustic analysis, the stop component, burst duration, and total duration of each target sound were calculated. Additionally, voice onset time (VOT) was assessed and contrasted between groups. A linear mixed-effects model was used for the statistical analysis. This study demonstrates that children with hypernasality have longer target sound durations. In addition, the burst duration of target sounds is determined to be prolonged in this group. Moreover, hypernasality is linked to a prolonged stop duration. Children without hypernasality experience a shortened duration of VOT than those with hypernasality. According to this study's findings, velofarengeal insufficiency has an effect on the duration of obstruent sounds. This explains the differences between the hypernasality group and the non-hypernasality group. This research suggests that CLP therapy for children may enhance their condition. Using acoustic measurements, this investigation generates theoretical results. Therapies' administration and evaluation could be combined.

The sublethal impacts of five insecticidal formulations on Oryzaephilus surinamensis behavioral traits.

Mortality caused by various pyrethroids, and neonicotinoids has been studied for stored-product insects in the past, yet limited information exists on the sublethal effects they can induce to Oryzaephilus surinamensis. In the current study, the sublethal effects of deltamethrin, λ-cyhalothrin, α-cypermethrin, etofenprox, and the mixture of acetamiprid with d-tetramethrin and piperonyl butoxide on the mobility of O. surinamensis in the presence or the absence of a food source was investigated. Lethal concentrations (LCs) were lower for deltamethrin, α-cypermethrin, and λ-cyhalothrin (LC10 = 0.000233, 0.000211, and 0.000271 mg active ingredient (a.i.) cm-2, LC30 = 0.000413, 0.000398, and 0.000447 mg a.i. cm-2, respectively), followed by etofenprox, and the mixture of acetamiprid with d-tetramethrin and piperonyl butoxide (LC10 = 0.00228 and 0.003267 mg a.i. cm-2, LC30 = 0.00437 and 0.01188 mg a.i. cm-2, respectively). Deltamethrin and λ-cyhalothrin negatively impacted adult walking behavior, increasing stop durations compared to controls. Adults exposed to LC10 and LC30 of λ-cyhalothrin, and LC30 of deltamethrin exhibited prolonged periods on their backs compared to the remaining treatments and the controls. The α-cypermethrin LC30-exposed adults exhibited significantly shorter walking and stopping durations than controls but demonstrated prolonged climbing on the arena walls compared to adults exposed to the remaining a.i. and the control. A similar trend was observed for etofenprox. Under sublethal concentrations, λ-cyhalothrin and deltamethrin increased stop intervals and reduced the duration of climbing attempts of O. surinamensis versus α-cypermethrin. These findings advance comprehension of the underexplored sublethal impacts of the tested a.i. on O. surinamensis adults, holding potential for leveraging insecticide-induced behavioral effects to enhance warehouse pest management. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Organization of spontaneous spatial behaviors under dark conditions is unaffected in adult male and female long-Evans rats after moderate prenatal alcohol exposure.

Prenatal alcohol exposure can produce disruptions in a wide range of cognitive functions, but it is especially detrimental to spatial navigation. In open environments, rodents organize their spatial behaviors around centralized locations, termed home bases, from which they make circuitous and slow locomotor trips (progressions) into the rest of the environment. Open-field behaviors are organized even under darkened test conditions, suggesting a role for self-motion cues (vestibular, motor, etc.). The impact of moderate prenatal alcohol exposure (mPAE) on the organization of spontaneous open-field behaviors under darkened conditions has not been investigated. Here we tested adult female and male rats with mPAE or saccharin control exposure in a circular open field for 30 min in a testing room that was made completely dark. While general locomotion, as measured by reductions in travel distance and increased stop duration, decreased across the test session, the organization of these behaviors, as measured by stop duration, home base establishment, home base stability, progression accuracy, and scaling of peak speeds with progression length, did not differ between mPAE and saccharin control rats. Together, the findings strongly suggest that spontaneous movement organization in relation to self-motion cues remains intact in adult mPAE rats. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Experimental Campaign on PEMFC Catalyst Degradation: Enlightening the Impact of Automotive Operational Cycles Combined with Short-Stops

Meeting long-term durability targets is still a significant challenge to achieve a wide-scale commercialization of PEM fuel cells in the transportation sector, for which the cathode catalyst layer is one of the most critical components1. Specifically, high potentials and potential cycling have been identified at the origin of its degradation. Indeed, they are responsible for platinum dissolution under the combined electrochemically oxidizing and acidic environment of catalyst layers. To limit ageing, vehicle systems adopt operating strategies that limit the operating voltage range, as well as they accurately control the start/stop procedures, avoiding both the open circuit voltage (OCV) and frequent air leaks into the anode compartment. In this perspective, passengers vehicles, that introduce frequent switching offs called short-stops2, exploit a procedure based on removing the air at the cathode side whilst supplying hydrogen at the anode.At a laboratory scale, accelerated ageing protocols (AST) are usually utilized for rapidly evaluating the degradation of materials, alternated with periodic performance testing and diagnostics. The conditions that promote Pt nanoparticle degradation have been studied over the past years3,4 mainly starting, and suitably modifying, the protocol proposed by the U.S. Department of Energy (DoE) in hydrogen/nitrogen. In this work, it was instead developed a complimentary approach in order to contribute to the study of the effect of the voltage cycles in a range relevant for the application. Different protocols in hydrogen/air or hydrogen/diluted air atmosphere were applied on a zero gradient cell, emulating the conditions of real operations5. The potential profiles under investigation were restricted to the voltage window accessible in real systems (i.e. ≤ 0.90 V), using commercial Catalyst Coated Membranes (CCM). The role both of the voltage range and of voltage transitions was clarified for a total of 40 tested Membrane Electrode Assembly (MEA) samples. Starting from the reference cycle included in Figure 1A, it was analyzed the influence of: (i) the upper potential limit (UPL); (ii) the lower potential limit (LPL), (iii) the impact of holding times, (iv) the role of short stops, (v) the short stop voltage, (vi) the short stop duration, (vii) scan rates during voltage transitions, (viii) the cathode gas feeding composition, (ix) the relative humidity during the short stop transient. Operando performance information indicates a clear recovery and boosting whenever the voltage was progressively reduced in the range 0.7 V–0 V. The irreversible performance decay recorded through polarization curves and impedance spectra (EIS) appeared dominated by the loss of the electrochemically active surface area (ECSA). The decay of this parameter was strictly connected to the Ostwald ripening mechanism, as corroborated by post mortem images obtained by transmission electron microscopy (TEM), while no Pt precipitation into the ionomer was observed. The average Pt nanoparticle diameter increased from 4.4 nm to 6.5 nm, at which value it almost stabilized. All the voltage profiles studied induced an ageing that was interpreted through the development of a newly formulated semi-empirical ECSA degradation model, which accounts for the role of the different stressors. The available data suggest that the Pt catalyst degradation is a strong function not only of UPL but also of LPL. Quite a large degradation was indeed observed in presence of short stops even in the typical system operational range (i.e. keeping UPL between 0.70 V and 0.90 V, Figures 1 B-D). It is suspected that the Pt nanoparticles are fully reduced at potentials significantly lower than 0.6 V and that their de-passivation enhances their growth. The work proves that attention must be paid on the transitions to low cell voltage (0÷0.4 V) in order to decelerate the catalyst ageing. The results are useful to orientate the selection of the PEMFC operational constraints for reaching the durability targets of the automotive sector (8’000 hours), but they can be also extended for matching the struggling requirements of heavy-duty transportation, namely 25’000 operating hours. This work received support from the Italian government (Progetto PERMANENT - BANDO MITE PNRR Missione 2 Investimento 3.5 A - RSH2A_0O0012). Borup, R. L. et al. Curr. Opin. Electrochem. 21, 192–200 (2020).Takahashi, T. et al. J. Electrochem. Soc. 169, 044523 (2022).Ahluwalia, R. K. et al. J. Electrochem. Soc. 168, 044518 (2021).Kneer, A. et al. J. Electrochem. Soc. 165, 805–812 (2018).Colombo, E. et al. J. Power Sources 553, 232246 (2023). Figure 1

Acoustic correlates of oral and glottal stops in Tahitian

The Eastern Polynesian language Tahitian spoken in French Polynesia, is described as having a simple phonological inventory with a single stop series: /p, t, ʔ/. Little is known about the acoustic properties of these consonants compared to well-resourced languages. Five female speakers of Tahitian produced multiple repetitions of tokens that varied in terms of stress location and prosodic phrase position. Acoustic analyses of stop duration and VOT, as well as voicing measures including voicing fraction and strength of excitation were conducted. As predicted, oral stops were significantly longer than glottal stops by 63 ms in word medial contexts with no effect of stress. VOT values were on average 21–26 ms (with /t/ marginally longer than /p/) confirming these are short lag stops (Cho and Ladefoged, 1999). Stress was marginally significant with shorter VOT values in stressed syllable onsets with no affect of prosodic position, unlike Hawaiian (Davidson and Parker Jones, 2022). Like Hawaiian, however, (Davidson, 2021), the glottal stop in Tahitian has gradient realizations although the majority are realised with full glottal closure with low voicing fraction and strength of excitation values. There are also clear effects of greater coarticulation in unstressed versus stressed syllables suggesting localised hyperarticulation in the latter context.

Auction market placement and a rest stop during transportation affect the respiratory bacterial microbiota of beef cattle.

Bovine respiratory disease (BRD) is a significant health problem in beef cattle production, resulting in considerable economic losses due to mortalities, cost of treatment, and reduced feed efficiency. The onset of BRD is multifactorial, with numerous stressors being implicated, including transportation from farms to feedlots. In relation to animal welfare, regulations or practices may require mandatory rest times during transportation. Despite this, there is limited information on how transportation and rest stops affect the respiratory microbiota. This study evaluated the effect of cattle source (ranch-direct or auction market-derived) and rest stop duration (0 or 8 h of rest) on the upper respiratory tract microbiota and its relationship to stress response indicators (blood cortisol and haptoglobin) of recently weaned cattle transported for 36 h. The community structure of bacteria was altered by feedlot placement. When cattle were off-loaded for a rest, several key bacterial genera associated with BRD (Mannheimia, Histophilus, Pasteurella) were increased for most sampling times after feedlot placement for the ranch-direct cattle group, compared to animals given no rest stop. Similarly, more sampling time points had elevated levels of BRD-associated genera when auction market cattle were compared to ranch-direct. When evaluated across time and treatments several genera including Mannheimia, Moraxella, Streptococcus and Corynebacterium were positively correlated with blood cortisol concentrations. This is the first study to assess the effect of rest during transportation and cattle source on the respiratory microbiota in weaned beef calves. The results suggest that rest stops and auction market placement may be risk factors for BRD, based solely on increased abundance of BRD-associated genera in the upper respiratory tract. However, it was not possible to link these microbiota to disease outcome, due to low incidence of BRD in the study populations. Larger scale studies are needed to further define how transportation variables impact cattle health.

Freight Operational Characteristics Mined from Anonymous Mobile Sensor Data

Effective transportation performance measurement (TPM) benefits from ubiquitous transportation system monitoring both spatially and temporally. In the context of freight-oriented TPM, traditional devices such as inductive loops, cameras, manual counts, and so forth, may fail to provide comprehensive and high-resolution coverage, providing, for example, only volume counts for a small subset of links across a large network with no indication of trip linkages. New sources of big data from mobile sensors including on-board global positioning system (GPS) devices allow more comprehensive network coverage and insights into trip chaining behaviors. However, to gain actionable insights into system performance from large and noisy streams of mobile sensor data, it is necessary to mine it for relevant operational characteristics of the trucks it represents. Such characteristics include stop locations, stop duration, stop time of day, trip length, and trip duration. To address this methodological need, this paper presents three heuristic algorithms: “stop identification,”“path identification,” and “trip identification.” To address the issue of determining relevant operational characteristics, a multinomial logit (MNL) model approach is applied to determine the commodity carried based on the outputs of the heuristic algorithms. The MNL model is novel in that it relates operational characteristics to commodity carried thus filling a critical data gap that currently limits the development of advanced freight forecasting models. The set of models developed in this paper allow large-scale GPS data to be used for freight planning while maintaining levels of data anonymity that allow such data to be shared with public agencies.

Does daily physical activity reflect claudication distance measured on a treadmill and in a community outdoor setting?

Low physical activity in patients with claudication is associated with lower walking abilities as assessed by the treadmill test. The impact of physical activity on the ability to walk in a natural environment is unknown. The study aimed to assess the level of daily physical activity among patients with claudication, as well as the relationship between the level of daily physical activity and claudication distance measured during the outdoor walking and treadmill tests. The study included 37 patients (24 males), aged 70.03±5.9, with intermittent claudication. Daily step count was assessed using the Garmin Vivofit activity monitor, worn on the non-dominant wrist for 7 consecutive days. Pain-free walking distance (PFWDTT) and maximal walking distance (MWDTT) were measured via the treadmill test. During 60-minute outdoor walking, the maximal walking distance (MWDGPS), total walking distance (TWDGPS), walking speed (WSGPS), number of stops (NSGPS) and stop durations (SDGPS) were assessed. Mean daily step count - 7,102±3,433. A significant correlation was observed between daily step count and MWDTT, TWDGPS (R=0.33, R=0.37, respectively (p<0.05). Furthermore, 51% of patients reached less than 7,500 steps/day and presented significantly shorter MWDTT, MWDGPS and TWDGPS, compared to the participants covering ≥7,500 steps (p<0.05). The daily step count reflects claudication distance measured on a treadmill and only partially in a community outdoor setting. The minimal daily step count that should be recommended for patients with claudication, allowing achievement of significantly better results with regard to walking abilities, both on the treadmill and in outdoor settings, is at least 7,500 steps per day.

A Data-Driven Spatio-Temporal Speed Prediction Framework for Energy Management of Connected Vehicles

We present an integrated spatio-temporal framework for multi-range traction power and speed prediction for connected vehicles (CVs). It combines data-driven and model-based strategies to enable CVs energy efficiency optimization. The proposed framework focuses on urban arterial corridors with signalized intersections, and leverages the historical and real-time data collected from CVs and infrastructure to predict location-specific traction loads (e.g. acceleration at intersections), and augment them with time-specific speed profiles (e.g., stop duration at intersections). A Bayesian network is developed to provide a long-term load prediction informed by probabilistic analysis of historical traffic data at intersections and between intersections. Moreover, a shockwave profile model is adopted for modeling the queuing process at intersections by leveraging vehicle-to-infrastructure (V2I) communications, providing a short-range prediction of the vehicle speed with an enhanced accuracy. The benefits of the proposed load prediction framework are demonstrated for energy management of connected hybrid electric vehicles (C-HEVs). By incorporating the predicted loads into a multi-horizon model predictive controller (MPC), integrated power and thermal management of light-duty C-HEVs is enabled over real-world driving cycles, demonstrating a near globally-optimal fuel consumption over the entire trip with a < 1% deviation from dynamic programming (DP) results.

Modeling Truck Parking Demand at Commercial and Industrial Establishments

In urban areas, there exists a mismatch between where trucks need to park and the availability of spaces, forcing many truck drivers to park in undesignated locations that are unsafe, disrupt traffic, and cause a nuisance to the community. This mismatch also decreases the productivity of the sector, as drivers spend more time searching for spaces, take longer detours, and end their workday early. Most commercial and industrial establishments currently do not allow trucks to park at their facilities beyond the loading or unloading of cargo, which generates parking demand in the surrounding areas. This paper quantifies the truck parking requirements of different commercial and industrial establishments in Phoenix, AZ, to inform land use and development decision-making. GPS data were combined with land use and employment data to identify where, when, and for how long trucks are parking. Parking rates were calculated at 2-digit and 3-digit NAICS level, for three parking metrics: stops per weekday, cumulative stop duration per weekday, and peak occupancy. Linear and negative binomial models were estimated, along with other types of models, to improve the prediction of parking demand. Results show that parking demand is the highest for establishments that store trucks overnight, such as truck terminals, and establishments with large in-house fleets. Parking demand is also high for establishments moving bulky commodities or having significant transportation needs, like in warehousing and the wholesale trade. Manufacturing establishments have a wide range of parking demand rates, based on the bulkiness of products and use of in-house fleets.

Basic Research for the Development of a Vegetation Biofilter Operation Algorithm in a Subway Station

Background and objective We measured the particulate matter (PM) reduction rate when the vegetation biofilter operated for 1 hour every 6 hours. As a result of data analysis, PM concentrations in the subway station showed a high correlation with the train stop duration depending on the service frequency of train operations, and the reduction rate was high in the section where PM concentrations as well as the change rates were high. Therefore, in order to maximize PM reduction using the biofilter, it is necessary to optimize the performance of the biofilter in various environments by designing an intelligent algorithm that takes the frequency of train operations into account. Methods We collected PM10 and PM2.5 data for 2 weeks in position 5 (POS5) and POS6. The multi-module vegetation biofilter was installed in POS6, whereas it was not in POS5. The average hourly data for PM concentrations were obtained, and the change in concentrations was analyzed every 24 hours. Results PM in subway stations is known to spread from the tracks to waiting areas as the train moves. Therefore, the change in PM concentrations by time zone has a high correlation of about 0.8 with the sum of the stop duration depending on the frequency of train operations. The vegetation biofilter is operated 4 times a day for 1 hour every 6 hours. The reduction rate reached up to 30% in 6–8 hours, where the PM concentrations increased sharply. Conclusion We came up with an algorithm to maximize the PM reduction effect by identifying the effect using the vegetation biofilter as a means for air purification in public use facilities such as subway stations. To this end, there is a need for a method that can dynamically select the section where the PM concentrations increase rapidly and set the biofilter operation time.

Quantification of Thermal Uniformity for Asphalt Paving Using the Thermal Segregation Index

Thermal and mechanical segregation are significant asphalt paving issues that affect the quality of asphalt pavements. Both types of segregation can be caused by inadequate mix material production, material delivery, and paving operation. Severe segregation results in lower in-place asphalt densities, which affect pavement performance. Measuring thermal segregation with technology such as paver mounted thermal profiling (PMTP) is critical to ensuring pavement quality. PMTP can continuously measure surface temperature profiles behind the trailing edge of a paver screed with an infrared sensor or photogrammetry. PMTP can also track paver speeds, stop locations, and stop durations. The differential range statistic (DRS) was created in the 2000s to evaluate thermal segregation. However, the DRS does not always adequately capture narrow bands of longitudinal thermal segregation caused by poor auger extension setup, mix building up beneath the reverse auger box and/or slat conveyors, worn deflector plates, and so forth. This paper introduces the thermal segregation index (TSI), which combines overall 2D sublot thermal uniformity and lateral thermal uniformity to overcome DRS’ shortcomings. The TSI combines the transverse semivariogram index (TSVI) and standard deviation (StDev) for sublots of 45.7 m (150 ft) in length. TSVI represents the lateral thermal uniformity in the transverse direction, while StDev represents the overall sublot temperature variation and is comparable with the DRS method. The TSI method was validated with an extensive thermal profile database and implemented in the Veta software allowing agencies and contractors to identify thermal segregation reliably and timely to conduct adequate corrective actions to resolve mix and paving issues.

Machine learning detects altered spatial navigation features in outdoor behaviour of Alzheimer\u2019s disease patients

Impairment of navigation is one of the earliest symptoms of Alzheimer’s disease (AD), but to date studies have involved proxy tests of navigation rather than studies of real life behaviour. Here we use GPS tracking to measure ecological outdoor behaviour in AD. The aim was to use data-driven machine learning approaches to explore spatial metrics within real life navigational traces that discriminate AD patients from controls. 15 AD patients and 18 controls underwent tracking of their outdoor navigation over two weeks. Three kinds of spatiotemporal features of segments were extracted, characterising the mobility domain (entropy, segment similarity, distance from home), spatial shape (total turning angle, segment complexity), and temporal characteristics (stop duration). Patients significantly differed from controls on entropy (p-value 0.008), segment similarity (p-value {10}^{-7}), and distance from home (p-value {10}^{-14}). Graph-based analyses yielded preliminary data indicating that topological features assessing the connectivity of visited locations may also differentiate patients from controls. In conclusion, our results show that specific outdoor navigation features discriminate AD patients from controls, which has significant implication for future AD diagnostics, outcome measures and interventions. Furthermore, this work illustrates how wearables-based sensing of everyday behaviour may be used to deliver ecologically-valid digital biomarkers of AD pathophysiology.

Phonetic indices of syllabic organization in German stop-lateral clusters

Using articulatory data from five German speakers, we study how segmental sequences under different syllabic organizations respond to perturbations of phonetic parameters in the segments that compose them. Target words contained stop-lateral sequences /bl, gl, kl, pl/ in word-initial and cross-word contexts and were embedded in carrier phrases with different prosodic boundaries, i.e., no phrase boundary versus an utterance phrase boundary preceded the target word in the case of word-initial clusters, or separated the consonants in the case of cross-word sequences. For word-initial cluster (CCV) onsets, we find that increasing C1 stop duration or the lag between two consonants leads to earlier vowel initiation and reduced local timing stability across CV, CCV. Furthermore, as the inter-consonantal lag increases, C2 duration decreases. In contrast, for cross-word C#CV sequences, increasing inter-consonantal lag does not lead to earlier vowel initiation and robust local timing stability is maintained across CV, C#CV. In other words, in CCV sequences within words, local perturbations to segments have effects that ripple through the rest of the sequence. Instead, in cross-word C#CV sequences, local perturbations stay local. Overall, the findings indicate that the effects of phonetic perturbations on coordination patterns depend on the syllabic organization superimposed on these clusters.

Inland waterway network mapping of AIS data for freight transportation planning

AbstractTravel demand models (TDMs) with freight forecasts estimate performance metrics for competing infrastructure investments and potential policy changes. Unfortunately, freight TDMs fail to represent non-truck modes with levels of detail adequate for multi-modal infrastructure and policy evaluation. Recent expansions in the availability of maritime movement data, i.e. Automatic Identification System (AIS), make it possible to expand and improve representation of maritime modes within freight TDMs. AIS may be used to track vessel locations as timestamped latitude–longitude points. For estimation, calibration and validation of freight TDMs, this work identifies vessel trips by applying network mapping (map-matching) heuristics to AIS data. The automated methods are evaluated on a 747-mile inland waterway network, with AIS data representing 88% of vessel activity. Inspection of 3820 AIS trajectories was used to train the heuristic parameters including stop time, duration and location. Validation shows 84⋅0% accuracy in detecting stops at ports and 83⋅5% accuracy in identifying trips crossing locks. The resulting map-matched vessel trips may be applied to generate origin–destination matrices, calculate time impedances, etc. The proposed methods are transferable to waterways or maritime port systems, as AIS continues to grow.

Early Stopping in Experimentation With Real-Time Functional Magnetic Resonance Imaging Using a Modified Sequential Probability Ratio Test.

Introduction: Functional magnetic resonance imaging (fMRI) often involves long scanning durations to ensure the associated brain activity can be detected. However, excessive experimentation can lead to many undesirable effects, such as from learning and/or fatigue effects, discomfort for the subject, excessive motion artifacts and loss of sustained attention on task. Overly long experimentation can thus have a detrimental effect on signal quality and accurate voxel activation detection. Here, we propose dynamic experimentation with real-time fMRI using a novel statistically driven approach that invokes early stopping when sufficient statistical evidence for assessing the task-related activation is observed.Methods: Voxel-level sequential probability ratio test (SPRT) statistics based on general linear models (GLMs) were implemented on fMRI scans of a mathematical 1-back task from 12 healthy teenage subjects and 11 teenage subjects born extremely preterm (EPT). This approach is based on likelihood ratios and allows for systematic early stopping based on target statistical error thresholds. We adopt a two-stage estimation approach that allows for accurate estimates of GLM parameters before stopping is considered. Early stopping performance is reported for different first stage lengths, and activation results are compared with full durations. Finally, group comparisons are conducted with both early stopped and full duration scan data. Numerical parallelization was employed to facilitate completion of computations involving a new scan within every repetition time (TR).Results: Use of SPRT demonstrates the feasibility and efficiency gains of automated early stopping, with comparable activation detection as with full protocols. Dynamic stopping of stimulus administration was achieved in around half of subjects, with typical time savings of up to 33% (4 min on a 12 min scan). A group analysis produced similar patterns of activity for control subjects between early stopping and full duration scans. The EPT group, individually, demonstrated more variability in location and extent of the activations compared to the normal term control group. This was apparent in the EPT group results, reflected by fewer and smaller clusters.Conclusion: A systematic statistical approach for early stopping with real-time fMRI experimentation has been implemented. This dynamic approach has promise for reducing subject burden and fatigue effects.

Revealing migratory path, important stopovers and non-breeding areas of a boreal songbird in steep decline

Abstract The Olive-sided Flycatcher (Contopus cooperi) is a steeply declining aerial insectivore with one of the longest migrations of any North American passerine. We deployed light-level geolocators and archival GPS tags on breeders in boreal Alaska to determine migratory routes, important stopovers and non-breeding locations. Data from 16 individuals revealed a median 23,555 km annual journey (range: 19,387, 27,292 km) over 95 days (range: 83, 139 days) with wintering occurring in three regions of South America (NW Colombia/Ecuador, central Peru and W Brazil/S Peru). We developed a new method to identify “Important Stopovers” by quantifying intensity of use (a function of bird numbers and stop durations) along migratory routes. We identified 13 Important Stopovers that accounted for ~66% of the annual migratory period, suggestive of refueling activities. Some sites coincided with key areas previously identified for other Neotropical-Nearctic migrants. Percent land “protected” at Important Stopovers, as defined by IUCN, ranged from 3.8% to 49.3% (mean [95% CI]: 17.3% [9.6, 25.0]). Total migration speed did not differ by season (median: 255 km day-1, range: 182, 295km day-1), despite greater spring travel distances. Birds with longer non-breeding periods, however, migrated north faster. Climate-driven mismatches in migratory timing may be less of a concern for western than for eastern flycatcher populations, given recent con-generic analyses (C. sordidulus, C. virens). However, accelerated high-latitude changes, may nonetheless impact boreal breeders.

Fewer-Angle SPECT/CT Blood Pool Imaging for Infection and Inflammation.

A new protocol for rapid SPECT/CT blood pool imaging consisting of fewer image-angle acquisitions (fewer-angle SPECT/CT, or FASpecT/CT) was evaluated for localization of focal sites of soft-tissue inflammation, infection, and osteomyelitis. Methods: Immediately after dynamic flow and standard planar blood pool imaging with 99mTc-methylene diphosphonate, FASpecT/CT was performed with a dual-head γ-camera consisting of 6 steps over 360°, 12 total images with 30° of separation between angles, and 30 s per image, requiring a total imaging time of approximately 3 min. Images were reconstructed using iterative ordered-subset expectation maximization. Before use in a patient-care setting, various FASpecT/CT acquisition protocols were modeled using a phantom to determine the minimum number of stops and the stop duration required to produce a reliable image. Results: FASpecT/CT images provided excellent 3-dimensional localization of spine osteomyelitis, soft-tissue infection of the foot, and tendonitis of the hand and foot using a 3-min image acquisition time. The FASpecT/CT acquisition protocol required 1.3-3.5 min, including camera movement time. This was a reduction of 72%-90% from the time required for the standard 60-angle, 20-s SPECT/CT acquisition. Conclusion: The ability of FASpecT/CT blood pool images to help localize focal sites of hyperemia and inflammation can increase exam sensitivity and specificity. Additionally, using a FASpecT/CT protocol decreases imaging time by up to 90%.

Experimental study on unidirectional pedestrian flows in a corridor with a fixed obstacle and a temporary obstacle

Pedestrians may encounter obstacles during walking, and necessary actions such as reducing velocity and changing the walking direction will be made to avoid collisions. Previous studies on the effect of obstacles on pedestrian dynamics mainly focused on fixed obstacles, but the influence of temporary obstacles, such as the sudden stop caused by a moving pedestrian, has not been investigated. In this paper, a series of controlled experiments were conducted to explore the influence of fixed obstacles and temporary obstacles on the unidirectional pedestrian flow in a corridor. For the fixed obstacle, it was found that pedestrians would change their walking direction and reducing velocity at varied distances away from the obstacle. Interestingly, right side preference during evading maneuvers can be observed, and some pedestrians are not urgent to return to the initial route after passing by the obstacle. In terms of temporary obstacles, such as the sudden stop during pedestrian movement, influences of stop duration, stop position, crowd density on pedestrian movements and evading behaviors of the affected pedestrians at different positions were studied. Generally, the longer the stop duration, the more pedestrians would be affected, and the affected pedestrians may change their routes at a further distance from the temporary obstacle. By analyzing the stop position, a temporary stop near the boundary would be a better choice when compared to that in the middle part of the corridor, since other pedestrians are less affected. In addition, in an environment with a relatively high crowd density, the affected pedestrians would usually experience significant decrease in velocity and obvious deviation in their trajectory. For pedestrians in the same lane with the temporary obstacle, it is obvious that the person right behind the pedestrian would be the most affected. With the increase in the sequence number after the temporary obstacle, the influence on velocity and target drift angle will gradually be reduced. The results of the present study can contribute to the relative modeling of pedestrian dynamics with fixed and temporary obstacles, and provide useful insights to crowd management.

PVDF Sensor Foils Employed to Measure Shear Stress and Temperature of Friction Welding

Friction welding is a popular process for joining metal and polymer work pieces by rubbing them against each other. This way, friction heat is generated in a zone of the faying surfaces, thinner than 1 mm. After cooling down, the heated surfaces establish a tight and strong bond. To improve this joining process, a method is desirable allowing measuring generated temperature and shear stress in the zone between the joining work pieces. Unfortunately, this is a very difficult task because the welding zone cannot be accessed with a sensor without significantly altering the process and thereby the desired measurement results. This paper describes how shear stress and temperature change generated by rubbing polymer pieces in a friction welding machine have been measured between the faying surfaces by employing sensor foils from the piezoelectric and pyroelectric polymer polyvinylidene fluoride (PVDF). This way, heating and cooling rates, pressure rise of the pneumatic system, frequency rise of the starting machine, the duration of starting and stopping, the damping of the vibrations after the drive was stopped, and the stress generated by the pullback of the machine head have been measured. A careful characterization of the sensor was necessary to enable distinguishing the measured voltage due to straining, shearing and temperature change.