Postmortem noninvasive virtual autopsy: extrapleural hemorrhage after blunt thoracic trauma

A 19-year-old man speeding recklessly along a highway caused a left-frontal crash with another car. After his vehicle came to a standstill, he climbed out of the wreck and crawled across the tarmac to the other side of the road, where he died several minutes after the accident and before the arrival of an ambulance. Postmortem multislice computed tomography (MSCT) demonstrated fractures of the first, second, and third ribs and scapula on the left, an extrapleural hemorrhage in the apical region of the left thorax, as well as a large amount of blood in the left thoracic cavity. These radiologic findings were indicative of a delayed rupture of a traumatic extrapleural hematoma into the pleural space. A traditional autopsy confirmed the very rare diagnosis of a traumatic extrapleural hemorrhage with a delayed rupture.

Learning real-world stimuli in a neural network with spike-driven synaptic dynamics

We present a model of spike-driven synaptic plasticity inspired by experimental observations and motivated by the desire to build an electronic hardware device that can learn to classify complex stimuli in a semisupervised fashion. During training, patterns of activity are sequentially imposed on the input neurons, and an additional instructor signal drives the output neurons toward the desired activity. The network is made of integrate-and-fire neurons with constant leak and a floor. The synapses are bistable, and they are modified by the arrival of presynaptic spikes. The sign of the change is determined by both the depolarization and the state of a variable that integrates the postsynaptic action potentials. Following the training phase, the instructor signal is removed, and the output neurons are driven purely by the activity of the input neurons weighted by the plastic synapses. In the absence of stimulation, the synapses preserve their internal state indefinitely. Memories are also very robust to the disruptive action of spontaneous activity. A network of 2000 input neurons is shown to be able to classify correctly a large number (thousands) of highly overlapping patterns (300 classes of preprocessed Latex characters, 30 patterns per class, and a subset of the NIST characters data set) and to generalize with performances that are better than or comparable to those of artificial neural networks. Finally we show that the synaptic dynamics is compatible with many of the experimental observations on the induction of long-term modifications (spike-timing-dependent plasticity and its dependence on both the postsynaptic depolarization and the frequency of pre- and postsynaptic neurons).

Antimicrobial resistance in bacteria from Swiss veal calves at slaughter

Bacteria with antimicrobial resistance can be transferred from animals to humans and may compromise antimicrobial treatment in case of infection. To determine the antimicrobial resistance situation in bacteria from Swiss veal calves, faecal samples from 500 randomly selected calves originating from 129 farms were collected at four big slaughterhouses. Samples were cultured for Escherichia coli, Enterococcus sp. and Campylobacter sp. and isolated strains were tested for antimicrobial susceptibility to selected antimicrobial agents by the minimal inhibitory concentration technique using the broth microdilution method. From 100 farms, data on farm management, animal husbandry and antimicrobial treatments of the calves were collected by questionnaire. Risk factors associated with antimicrobial resistance were identified by logistic regression. In total, 467 E. coli, 413 Enterococcus sp. and 202 Campylobacter sp. were isolated. Of those, 68.7%, 98.7% and 67.8%, respectively, were resistant to at least one of the tested antimicrobial agents. Resistance was mainly observed to antimicrobials frequently used in farm animals. Prevalence of resistance to antimicrobials important for human treatment was generally low. However, a rather high number of quinupristin/dalfopristin-resistant Enterococcus faecium and ciprofloxacin-resistant Campylobacter sp. were detected. External calf purchase, large finishing groups, feeding of milk by-products and administration of antimicrobials through feed upon arrival of the animals on the farm significantly increased the risk of antimicrobial resistance at farm level. Participation in a quality assurance programme and injection of a macrolide upon arrival of the animals on the farm had a protective effect. The present study showed that veal calves may serve as a reservoir for resistant bacteria. To ensure food safety, veal calves should be included in the national monitoring programme for antimicrobial resistance in farm animals. By improving farm management and calf husbandry the prevalence of resistance may be reduced.

Incidence of low central venous oxygen saturation during unplanned admissions in a multidisciplinary intensive care unit: an observational study

INTRODUCTION: It has been shown that early central venous oxygen saturation (ScvO2)-guided optimization of hemodynamics can improve outcome in septic patients. The early ScvO2 profile of other patient groups is unknown. The aim of this study was to characterize unplanned admissions in a multidisciplinary intensive care unit (ICU) with respect to ScvO2 and outcome. METHODS: Ninety-eight consecutive unplanned admissions to a multidisciplinary ICU (median age 63 [range 19 to 83] years, median Simplified Acute Physiology Score [SAPS II] 43 [range 11 to 92]) with a clinical indication for a central venous catheter were included in the study. ScvO2 was assessed at ICU arrival and six hours later but was not used to guide treatment. Length of stay in ICU (LOSICU) and in hospital (LOShospital) and 28-day mortality were recorded. RESULTS: ScvO2 was 70% +/- 12% (mean +/- standard deviation) at admission and 71% +/- 10% six hours later (p = 0.484). Overall 28-day mortality was 18%, LOSICU was 3 (1 to 28) days, and LOShospital was 19 (1 to 28) days. Patients with an ScvO2 of less than 60% at admission had higher mortality than patients with an ScvO2 of more than 60% (29% versus 17%, p < 0.05). Changes in ScvO2 during the first six hours were not predictive of LOSICU, LOShospital, or mortality. CONCLUSION: Low ScvO2 in unplanned admissions and high SAPS II are associated with increased mortality. Standard ICU treatment increased ScvO2 in patients with a low admission ScvO2, but the increase was not associated with LOSICU or LOShospital.

Low awareness of transient ischemic attacks and risk factors of stroke in a Swiss urban community

BACKGROUND AND PURPOSE: Time delays from stroke onset to arrival at the hospital are the main obstacles for widespread use of thrombolysis. In order to decrease the delays, educational campaigns try to inform the general public how to act optimally in case of stroke. To determine the content of such a campaign, we assessed the stroke knowledge in our population. METHODS: The stroke knowledge was studied by means of a closed-ended questionnaire. 422 randomly chosen inhabitants of Bern, Switzerland, were interviewed. RESULTS: The knowledge of stroke warning signs (WS) was classified as good in 64.7%. A good knowledge of stroke risk factors (RF) was noted in 6.4%. 4.2% knew both the WS and the RF of stroke indicating a very good global knowledge of stroke. Only 8.3% recognized TIA as symptoms of stroke resolving within 24 hours, and only 2.8% identified TIA as a disease requiring immediate medical help. In multivariate analysis being a woman, advancing age, and having an afflicted relative were associated with a good knowledge of WS (p = 0.048, p < 0.001 and p = 0.043). Good knowledge of RF was related to university education (p < 0.001). The good knowledge of TIA did not depend on age, sex, level of education or having an afflicted relative. CONCLUSIONS: The study brings to light relevant deficits of stroke knowledge in our population. A small number of participants could recognize TIA as stroke related symptoms resolving completely within 24 hours. Only a third of the surveyed persons would seek immediate medical help in case of TIA. The information obtained will be used in the development of future educational campaigns.

Under the Crimson Flag: Fahle Burman's Two Trips to the Michigan Supreme Court

Erick Fahle Burman. a Swedish-born, Finnish-speaking labor and political activist, twice had cases argued on his behalf before the Michigan Supreme Court. In People vs. Burman, Burman, along with nine other defendants, had his conviction affirmed by the court and all ten were forced to pay a fine of $25 each for disturbing the peace. In People vs. Immonen, Burman and his co-defendant, Unto Immonen, had their convictions overturned because of improper evidence being admitted in their lower court trial. Though the conviction was overturned, the two men had already spent several months as prisoners at hard labor in Marquette State Prison located in Michigan's Upper Peninsula. Over twenty-five years separate Burman's two trips to Michigan's high court. On the first occasion, his arrest came less than five years after his arrival as an immigrant to the U. S. On the second occasion, his arrest came less than two years after his return to the state after being away for nearly two decades. On both occasions, Burman was arrested for his involvement with red flags. Though separated by decades, these cases, taken together, are important indicators of the state of Finnish-American radicalism in the years surrounding the red flag incidents and provide interesting insights into the delicacies of political suppression. Examination of these cases within the larger career of Fahle Burman points up his overlooked importance in the history of Finnish-American socialism and communism.

Multi-node TOA-DOA cooperative LOS-NLOS localization : enabling high accuracy and reliability

This dissertation investigates high performance cooperative localization in wireless environments based on multi-node time-of-arrival (TOA) and direction-of-arrival (DOA) estimations in line-of-sight (LOS) and non-LOS (NLOS) scenarios. Here, two categories of nodes are assumed: base nodes (BNs) and target nodes (TNs). BNs are equipped with antenna arrays and capable of estimating TOA (range) and DOA (angle). TNs are equipped with Omni-directional antennas and communicate with BNs to allow BNs to localize TNs; thus, the proposed localization is maintained by BNs and TNs cooperation. First, a LOS localization method is proposed, which is based on semi-distributed multi-node TOA-DOA fusion. The proposed technique is applicable to mobile ad-hoc networks (MANETs). We assume LOS is available between BNs and TNs. One BN is selected as the reference BN, and other nodes are localized in the coordinates of the reference BN. Each BN can localize TNs located in its coverage area independently. In addition, a TN might be localized by multiple BNs. High performance localization is attainable via multi-node TOA-DOA fusion. The complexity of the semi-distributed multi-node TOA-DOA fusion is low because the total computational load is distributed across all BNs. To evaluate the localization accuracy of the proposed method, we compare the proposed method with global positioning system (GPS) aided TOA (DOA) fusion, which are applicable to MANETs. The comparison criterion is the localization circular error probability (CEP). The results confirm that the proposed method is suitable for moderate scale MANETs, while GPS-aided TOA fusion is suitable for large scale MANETs. Usually, TOA and DOA of TNs are periodically estimated by BNs. Thus, Kalman filter (KF) is integrated with multi-node TOA-DOA fusion to further improve its performance. The integration of KF and multi-node TOA-DOA fusion is compared with extended-KF (EKF) when it is applied to multiple TOA-DOA estimations made by multiple BNs. The comparison depicts that it is stable (no divergence takes place) and its accuracy is slightly lower than that of the EKF, if the EKF converges. However, the EKF may diverge while the integration of KF and multi-node TOA-DOA fusion does not; thus, the reliability of the proposed method is higher. In addition, the computational complexity of the integration of KF and multi-node TOA-DOA fusion is much lower than that of EKF. In wireless environments, LOS might be obstructed. This degrades the localization reliability. Antenna arrays installed at each BN is incorporated to allow each BN to identify NLOS scenarios independently. Here, a single BN measures the phase difference across two antenna elements using a synchronized bi-receiver system, and maps it into wireless channel’s K-factor. The larger K is, the more likely the channel would be a LOS one. Next, the K-factor is incorporated to identify NLOS scenarios. The performance of this system is characterized in terms of probability of LOS and NLOS identification. The latency of the method is small. Finally, a multi-node NLOS identification and localization method is proposed to improve localization reliability. In this case, multiple BNs engage in the process of NLOS identification, shared reflectors determination and localization, and NLOS TN localization. In NLOS scenarios, when there are three or more shared reflectors, those reflectors are localized via DOA fusion, and then a TN is localized via TOA fusion based on the localization of shared reflectors.

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency.

EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.

High precision range estimation techniques for multi-path wireless environments

Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic assumptions in practical systems. The performance and complexity of the proposed technique is investigated as well. This study’s results show that selecting bandwidth, center frequency, and SNR levels for each sub-band can adapt positioning accuracy.

Space trajectories optimization using variable-chromosome-length genetic algorithms

The problem of optimal design of a multi-gravity-assist space trajectories, with free number of deep space maneuvers (MGADSM) poses multi-modal cost functions. In the general form of the problem, the number of design variables is solution dependent. To handle global optimization problems where the number of design variables varies from one solution to another, two novel genetic-based techniques are introduced: hidden genes genetic algorithm (HGGA) and dynamic-size multiple population genetic algorithm (DSMPGA). In HGGA, a fixed length for the design variables is assigned for all solutions. Independent variables of each solution are divided into effective and ineffective (hidden) genes. Hidden genes are excluded in cost function evaluations. Full-length solutions undergo standard genetic operations. In DSMPGA, sub-populations of fixed size design spaces are randomly initialized. Standard genetic operations are carried out for a stage of generations. A new population is then created by reproduction from all members based on their relative fitness. The resulting sub-populations have different sizes from their initial sizes. The process repeats, leading to increasing the size of sub-populations of more fit solutions. Both techniques are applied to several MGADSM problems. They have the capability to determine the number of swing-bys, the planets to swing by, launch and arrival dates, and the number of deep space maneuvers as well as their locations, magnitudes, and directions in an optimal sense. The results show that solutions obtained using the developed tools match known solutions for complex case studies. The HGGA is also used to obtain the asteroids sequence and the mission structure in the global trajectory optimization competition (GTOC) problem. As an application of GA optimization to Earth orbits, the problem of visiting a set of ground sites within a constrained time frame is solved. The J2 perturbation and zonal coverage are considered to design repeated Sun-synchronous orbits. Finally, a new set of orbits, the repeated shadow track orbits (RSTO), is introduced. The orbit parameters are optimized such that the shadow of a spacecraft on the Earth visits the same locations periodically every desired number of days.

Direction finding in the presence of a more realistic environment model

Direction-of-arrival (DOA) estimation is susceptible to errors introduced by the presence of real-ground and resonant size scatterers in the vicinity of the antenna array. To compensate for these errors pre-calibration and auto-calibration techniques are presented. The effects of real-ground constituent parameters on the mutual coupling (MC) of wire type antenna arrays for DOA estimation are investigated. This is accomplished by pre-calibration of the antenna array over the real-ground using the finite element method (FEM). The mutual impedance matrix is pre-estimated and used to remove the perturbations in the received terminal voltage. The unperturbed terminal voltage is incorporated in MUSIC algorithm to estimate DOAs. First, MC of quarter wave monopole antenna arrays is investigated. This work augments an existing MC compensation technique for ground-based antennas and proposes reduction in MC for antennas over finite ground as compared to the perfect ground. A factor of 4 decrease in both the real and imaginary parts of the MC is observed when considering a poor ground versus a perfectly conducting one for quarter wave monopoles in the receiving mode. A simulated result to show the compensation of errors direction of arrival (DOA) estimation with actual realization of the environment is also presented. Secondly, investigations for the effects on received MC of λ/2 dipole arrays placed near real-earth are carried out. As a rule of thumb, estimation of mutual coupling can be divided in two regions of antenna height that is very near ground 0

MODELING AND PROTOCOL DESIGN FOR EMERGING WIRELESS SYSTEMS

Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.

SEARCH FOR LONG-LIVED WEAKLY INTERACTING PARTICLES USING THE PIERRE AUGER OBSERVATORY

Data collected with the surface detector array of the Pierre Auger Observatory during the period from January 1, 2004 to March 17, 2015 was examined for evidence of production of long-lived weakly interacting particles in interactions of ultra high energy cosmic rays in the atmosphere. The search was performed using extensive air showers with primary energies more than 10 EeV and arrival directions in the range of 57.5◦ to 77.5◦. There was no evidence of significant production of such particles. An upper limit on the fraction of extensive air showers in which such particles are produced was set.

Prevalence and time course of acute mountain sickness in older children and adolescents after rapid ascent to 3450 meters

OBJECTIVE: Acute mountain sickness is a frequent and debilitating complication of high-altitude exposure, but there is little information on the prevalence and time course of acute mountain sickness in children and adolescents after rapid ascent by mechanical transportation to 3500 m, an altitude at which major tourist destinations are located throughout the world. METHODS: We performed serial assessments of acute mountain sickness (Lake Louise scores) in 48 healthy nonacclimatized children and adolescents (mean +/- SD age: 13.7 +/- 0.3 years; 20 girls and 28 boys), with no previous high-altitude experience, 6, 18, and 42 hours after arrival at the Jungfraujoch high-altitude research station (3450 m), which was reached through a 2.5-hour train ascent. RESULTS: We found that the overall prevalence of acute mountain sickness during the first 3 days at high altitude was 37.5%. Rates were similar for the 2 genders and decreased progressively during the stay (25% at 6 hours, 21% at 18 hours, and 8% at 42 hours). None of the subjects needed to be evacuated to lower altitude. Five subjects needed symptomatic treatment and responded well. CONCLUSION: After rapid ascent to high altitude, the prevalence of acute mountain sickness in children and adolescents was relatively low; the clinical manifestations were benign and resolved rapidly. These findings suggest that, for the majority of healthy nonacclimatized children and adolescents, travel to 3500 m is safe and pharmacologic prophylaxis for acute mountain sickness is not needed.