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Aim: The aim of the study was to identify common orthopedic sports injury profiles in adolescent elite athletes with respect to age, sex, and anthropometrics.
Methods: A retrospective data analysis of 718 orthopedic presentations among 381 adolescent elite athletes from 16 different sports to a sports medical department was performed. Recorded data of history and clinical examination included area, cause and structure of acute and overuse injuries. Injury-events were analyzed in the whole cohort and stratified by age (11–14/15–17 years) and sex. Group differences were tested by chi-squared-tests. Logistic regression analysis was applied examining the influence of factors age, sex, and body mass index (BMI) on the outcome variables area and structure (α = 0.05).
Results: Higher proportions of injury-events were reported for females (60%) and athletes of the older age group (66%) than males and younger athletes. The most frequently injured area was the lower extremity (47%) followed by the spine (30.5%) and the upper extremity (12.5%). Acute injuries were mainly located at the lower extremity (74.5%), while overuse injuries were predominantly observed at the lower extremity (41%) as well as the spine (36.5%). Joints (34%), muscles (22%), and tendons (21.5%) were found to be the most often affected structures. The injured structures were different between the age groups (p = 0.022), with the older age group presenting three times more frequent with ligament pathology events (5.5%/2%) and less frequent with bony problems (11%/20.5%) than athletes of the younger age group. The injured area differed between the sexes (p = 0.005), with males having fewer spine injury-events (25.5%/34%) but more upper extremity injuries (18%/9%) than females. Regression analysis showed statistically significant influence for BMI (p = 0.002) and age (p = 0.015) on structure, whereas the area was significantly influenced by sex (p = 0.005).
Conclusion: Events of soft-tissue overuse injuries are the most common reasons resulting in orthopedic presentations of adolescent elite athletes. Mostly, the lower extremity and the spine are affected, while sex and age characteristics on affected area and structure must be considered. Therefore, prevention strategies addressing the injury-event profiles should already be implemented in early adolescence taking age, sex as well as injury entity into account.
Driven by falling photovoltaic (PV) installation costs and potential support policies, rooftop PV is expected to expand rapidly in Thailand. As a result, the relevant stakeholders, especially utilities, have concerns about the net economic impacts of high PV adoption. Using a cost–benefit analysis, this study quantifies the net economic impacts of rooftop PV systems on three utilities and on ratepayers in Thailand by applying nine different PV adoption scenarios with various buyback rates and annual percentages of PV cost reduction. Under Thailand’s current electricity tariff structure, Thai utilities are well-protected and able to pass all costs due to PV onto the ratepayers in terms of changes in retail rates. We find that when PV adoption is low, the net economic impacts on both the utilities and retail rates are small and the impacts on each utility depend on its specific characteristics. On the other hand, when PV adoption ranges from 9–14% in energy basis, five-year retail rate impacts become noticeable and are between 6% and 11% as compared to the projected retail rates in 2036 depending on the PV adoption level. Thus, it is necessary for Thailand to make tradeoffs among the stakeholders and maximize the benefits of rooftop PV adoption.
Background: Telerehabilitation can contribute to the maintenance of successful rehabilitation regardless of location and time. The aim of this study was to investigate a specific three-month interactive telerehabilitation routine regarding its effectiveness in assisting patients with physical functionality and with returning to work compared to typical aftercare.
Objective: The aim of the study was to investigate a specific three-month interactive telerehabilitation with regard to effectiveness in functioning and return to work compared to usual aftercare.
Methods: From August 2016 to December 2017, 111 patients (mean 54.9 years old; SD 6.8; 54.3% female) with hip or knee replacement were enrolled in the randomized controlled trial. At discharge from inpatient rehabilitation and after three months, their distance in the 6-minute walk test was assessed as the primary endpoint. Other functional parameters, including health related quality of life, pain, and time to return to work, were secondary endpoints.
Results: Patients in the intervention group performed telerehabilitation for an average of 55.0 minutes (SD 9.2) per week. Adherence was high, at over 75%, until the 7th week of the three-month intervention phase. Almost all the patients and therapists used the communication options. Both the intervention group (average difference 88.3 m; SD 57.7; P=.95) and the control group (average difference 79.6 m; SD 48.7; P=.95) increased their distance in the 6-minute-walk-test. Improvements in other functional parameters, as well as in quality of life and pain, were achieved in both groups. The higher proportion of working patients in the intervention group (64.6%; P=.01) versus the control group (46.2%) is of note.
Conclusions: The effect of the investigated telerehabilitation therapy in patients following knee or hip replacement was equivalent to the usual aftercare in terms of functional testing, quality of life, and pain. Since a significantly higher return-to-work rate could be achieved, this therapy might be a promising supplement to established aftercare.
Following a quantitative analysis of adequate feedstock, comprising 11 woody biomass species, four biochars were generated using a Kon-Tiki flame curtain kiln in the state of Aguascalientes, Mexico. Despite the high quality (certified by European Biochar Certificate), the biochars contain substantial quantities of hazardous substances, such as polycyclic aromatic hydrocarbons, polychlorinated dibenzo-p-dioxins and dibenzofurans, polychlorinated biphenyls, and heavy metals, which can induce adverse effects if wrongly applied to the environment. To assess the toxicity of biochars to non-target organisms, toxicity tests with four benthic and zooplanktonic invertebrate species, the ciliate Paramecium caudatum, the rotifer Lecane quadridentata, and the cladocerans Daphnia magna and Moina macrocopa were performed using biochar elutriates. In acute and chronic toxicity tests, no acute toxic effect to ciliates, but significant lethality to rotifers and cladocerans was detected. This lethal toxicity might be due to ingestion/digestion by enzymatic/mechanic processes of biochar by cladocerans and rotifers of toxic substances present in the biochar. No chronic toxicity was found where biochar elutriates were mixed with soil. These data indicate that it is instrumental to use toxicity tests to assess biochars’ toxicity to the environment, especially when applied close to sensitive habitats, and to stick closely to the quantitative set-point values.
This article investigates the representation of the issue of refugees travelling to the Italian coast that was reported by two major Italian newspapers between August 8th and August 19th, 2017. Using analysis tools belonging to communication theory and cognitive sciences, i.e. the concepts of frame and attitude, this article highlights two major points: firstly, the analysis reveals how the two newspapers aimed at establishing a specific relationship with their readers on this topic in the relevant period on the basis of specific interpretative models; secondly, each of these interpretative models relies on the representation of specific emotions which play a central role in the interpretation of reality according to a characteristic facet of the definition of post-truth.
Internet of Things (IoT) and Artificial Intelligence (AI) are one of the most promising and disruptive areas of current research and development. However, these areas require deep knowledge in multiple disciplines such as sensors, protocols, embedded programming, distributed systems, statistics and algorithms. This broad knowledge is not easy to acquire and the software used to design these systems is becoming increasingly complex. Small and medium-sized enterprises therefore have problems in developing new business ideas. However, node- and block-based software tools have also been released and are freely available as open source toolboxes. In this paper, we present an overview of multiple node- and block-based software tools to develop IoT- and AI-based business ideas. We arrange these tools according their capabilities and further propose extension and combinations of tools to design a useful open-source library for small and medium-sized enterprises, that is easy to use and helps with rapid prototyping, enabling new business ideas to be developed using distributed computing.
A new comprehensive evaluation system presented here allows to compare and to quantify education for a sustainable development (ESD) in degree programs. The evaluation is based on a criteria system working with three hierarchic levels. The highest level considers a list of 35 indicator terms. Primarily, the two most popular undergraduate (bachelor’s) degree programs in Germany (mechanical engineering, ME, and business administration, BA) have been reviewed for ESD contents based on the new evaluation scheme. Additionally we reviewed and quantified ESD subjects and their temporal changes in the entire bandwidth of degree programs of a university (Umwelt-Campus Birkenfeld, University of Applied Sciences Trier), back to 1999. Moreover, a spot check on international ME and BA bachelor’s degree programs was performed. Through our reviews, we found a high number of elective classes dedicated to ESD particularly in BA bachelor programs. However, the percentage of compulsory classes related to ESD is relatively low with 5-6 % in both ME and BA programs, respectively. The spot check on degree programs outside Germany revealed similar results. Analysing the time trend at Umwelt-Campus Birkenfeld, a considerable share of ESD that was part of the original diploma degrees was moved to what are now master’s degrees.
A comprehensive overview is provided evaluating direct real-world CO2 emissions of both diesel and petrol cars newly registered in Europe between 1995 and 2015. Before 2011, European diesel cars emitted less CO2 per kilometre than petrol cars, but since then there is no appreciable difference in per-km CO2 emissions between diesel and petrol cars. Real-world CO2 emissions of diesel cars have not declined appreciably since 2001, while the CO2 emissions of petrol cars have been stagnant since 2012. When adding black carbon related CO2-equivalents, such as from diesel cars without particulate filters, diesel cars were discovered to have had much higher climate relevant emissions until the year 2001 when compared to petrol cars. From 2001 to 2015 CO2-equivalent emissions from new diesel cars and petrol cars were hardly distinguishable. Lifetime use phase CO2-equivalent emissions of all European passenger vehicles were modelled for 1995–2015 based on three scenarios: the historic case, another scenario freezing percentages of diesel cars at the low levels from the early 1990s (thus avoiding the observed “boom” in new diesel registrations), and an advanced mitigation scenario based on high proportions of petrol hybrid cars and cars burning gaseous fuels. The difference in CO2-equivalent emissions between the historical case and the scenario avoiding the diesel car boom is only 0.4%. The advanced mitigation scenario would have been able to achieve a 3.4% reduction in total CO2-equivalent emissions over the same time frame. The European diesel car boom appears to have been ineffective at reducing climate-warming emissions from the European transport sector.
Background: To facilitate access to evidence-based care for back pain, a German private medical insurance offered a health program proactively to their members. Feasibility and long-term efficacy of this approach were evaluated.
Methods: Using Zelen’s design, adult members of the health insurance with chronic back pain according to billing data were randomized to the intervention (IG) or the control group (CG). Participants allocated to the IG were invited to participate in the comprehensive health program comprising medical exercise therapy and life style coaching, and those allocated to the CG to a longitudinal back pain survey. Primary outcomes were back pain severity (Korff’s Chronic Pain Grade Questionnaire) as well as health-related quality of life (SF-12) assessed by identical online questionnaires at baseline and 2-year follow-up in both study arms. In addition to analyses of covariance, a subgroup analysis explored the heterogeneity of treatment effects among different risks of back pain chronification (STarT Back Tool).
Results: Out of 3462 persons selected, randomized and thereafter contacted, 552 agreed to participate. At the 24-month follow-up, data on 189 of 258 (73.3%) of the IG were available, in the CG on 255 of 294 (86.7%). Significant, small beneficial effects were seen in primary outcomes: Compared to the CG, the IG reported less disability (1.6 vs 2.0; p = 0.025; d = 0.24) and scored better at the SF-12 physical health scale (43.3 vs 41.0; p < 0.007; d = 0.26). No effect was seen in back pain intensity and in the SF-12 mental health scale. Persons with medium or high risk of back pain chronification at baseline responded better to the health program in all primary outcomes than the subgroup with low risk at baseline.
Conclusions: After 2 years, the proactive health program resulted in small positive long-term improvements. Using risk screening prior to inclusion in the health program might increase the percentage of participants deriving benefits from it.
Fuzzy system based on two-step cascade genetic optimization strategy for tobacco tar prediction
(2019)
There are many challenges in accurately measuring cigarette tar constituents. These include the need for standardized smoke generation methods related to unstable mixtures. In this research were developed algorithms using fusion of artificial intelligence methods to predict tar concentration. Outputs of development are three fuzzy structures optimized with genetic algorithms resulting in genetic algorithm (GA)-FUZZY, GA-adaptive neuro fuzzy inference system (ANFIS), GA-GA-FUZZY algorithms. Proposed algorithms are used for the tar prediction in the cigarette production process. The results of prediction are compared with gas chromatograph (high-performance liquid chromatography (HPLC)) readings.