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High-resolution wind measurements are crucial for the understanding of dynamic processes in the atmosphere. In the troposphere and lower stratosphere, radiosondes provide a good vertical resolution of a few metres, but the wind data are usually low-pass filtered by the manufacturer in order to suppress disturbances in the data caused by the spurious motions of the sonde. As an example, the filter within the standard processing of Vaisala radiosondes becomes effective at vertical scales below 300 m for an ascent rate of 5 m s−1. We describe a method for increasing the usable resolution of radiosonde wind measurements. The main ideas are to avoid self-induced motions of the balloon by keeping it in the subcritical Reynolds number range, to avoid typical pendulum motions of a 15 s period by using a shorter string, and to use data from a descending balloon in order to avoid disturbances from the wake of the balloon affecting temperature and humidity measurements due to the decreased string length. We demonstrate that our changes in hardware and software allow for artefact-free wind data down to scales of 50 m, while the remaining disturbances on even smaller scales are removed. Accordingly, the usable resolution of the wind data has been increased by a factor of 6, compared to the standard data output, at relatively low cost.

Abstract Ataxias are a group of movement disorders that are characterized by progressive loss of balance, impaired coordination and speech disturbance, which together lead to markedly reduced quality of life. Speech disturbance is clinically diagnosed, but methods for objective assessment of severity are lacking. Using 71 sets of speech recordings from ataxia patients, we developed an automated classification system. With a tolerance of ±1 point, this classification system correctly predicted experts’ ratings of speech disturbance according to item 4 of the Scale for Assessment and rating of ataxia (SARA) in 80% of cases. We thereby demonstrate feasibility of computer-assisted voice analysis for automated assessment of severity of speech disturbance.

Abstract Background Improved, multimodal treatment strategies have been shown to increase cure rates in cancer patients. Those who survive cancer as a child, adolescent or young adult (CAYA), are at a higher risk for therapy-, or disease-related, late or long-term effects. The CARE for CAYA-Program has been developed to comprehensively assess any potential future problems, to offer need-based preventative interventions and thus to improve long-term outcomes in this particularly vulnerable population. Methods The trial is designed as an adaptive trial with an annual comprehensive assessment followed by needs stratified, modular interventions, currently including physical activity, nutrition and psycho-oncology, all aimed at improving the lifestyle and/or the psychosocial situation of the patients. Patients, aged 15–39 years old, with a prior cancer diagnosis, who have completed tumour therapy and are in follow-up care, and who are tumour free, will be included. At baseline (and subsequently on an annual basis) the current medical and psychosocial situation and lifestyle of the participants will be assessed using a survey compiled of various validated questionnaires (e.g. EORTC QLQ C30, NCCN distress thermometer, PHQ-4, BSA, nutrition protocol) and objective parameters (e.g. BMI, WHR, co-morbidities like hyperlipidaemia, hypertension, diabetes), followed by basic care (psychological and lifestyle consultation). Depending on their needs, CAYAs will be allocated to preventative interventions in the above-mentioned modules over a 12-month period. After 1 year, the assessment will be repeated, and further interventions may be applied as needed. During the initial trial phase, the efficacy of this approach will be compared to standard care (waiting list with intervention in the following year) in a randomized study. During this phase, 530 CAYAs will be included and 320 eligible CAYAs who are willing to participate in the interventions will be randomly allocated to an intervention. Overall, 1500 CAYAs will be included and assessed. The programme is financed by the innovation fund of the German Federal Joint Committee and will be conducted at 14 German sites. Recruitment began in January 2018. Discussion CAYAs are at high risk for long-term sequelae. Providing structured interventions to improve lifestyle and psychological situation may counteract against these risk factors. The programme serves to establish uniform regular comprehensive assessments and need-based interventions to improve long-term outcome in CAYA survivors. Trial registration Registered at the German Clinical Trial Register (ID: DRKS00012504, registration date: 19th January 2018).

Despite a growing number of autistic children completing high school and venturing into college and vocational settings, their rates of postsecondary attendance, graduation, and vocational success still lag behind those of their nonautistic counterparts. This study surveyed 162 autistic and nonautistic high school students about internal and external factors that may increase or decrease their motivation to succeed academically. Results of this study suggest that autistic students rated neither internal nor external factors as significantly contributing to their academic success when compared to their nonautistic peers. Moreover, when compared to their nonautistic peers, autistic high school students were less likely to endorse motivators to their academic success that were future-oriented toward college and career success and more likely to favor factors related to seeking approval from others and validating their own capability for success.

Main problems related to reliability of interaction between human subject and artificial system (namely of the transportation character) are discussed. The paper consists of three mayor parts:The first one is devoted to the theoretical backgrounds of the problem from the both theory of system reliability and neurology/psychology views.Second part presents the discussion of relevant methodologies of the classification and prediction of the reliability decline. The methodology based on EEG pattern analysis is chosen as the appropriate one for the presented task. The key phenomenon of "micro-sleep" is discussed in detail.The last part presents some latest experimental results in context of presented knowledge. Proposals for the future studies are presented at the end of the presented article. The special interest should be devoted to the analysis and in-time prediction of fatal attention decreases and to the design and construction of the respective on-board applicable warning system.