Open Access

The research project "Herbar Digital" was started in 2007 with the aim to digitize 3.5 million dried plants on paper sheets belonging to the Botanic Museum Berlin in Germany. Frequently the collector of the plant is unknown, so a procedure had to be developed in order to determine the writer of the handwriting on the sheet. In the present work the static character was transformed into a dynamic form. This was done with the model of an inert ball which was rolled along the written character. During this off-line writer recognition, different mathematical procedures were used such as the reproduction of the write line of individual characters by Legendre polynomials. When only one character was used, a recognition rate of about 40% was obtained. By combining multiple characters, the recognition rate rose considerably and reached 98.7% with 13 characters and 93 writers (chosen randomly from the international IAM-database [3]). A global statistical approach using the whole handwritten text resulted in a similar recognition rate. By combining local and global methods, a recognition rate of 99.5% was achieved.

Objectives: The aim was to identify theoretically expected as well as actually reported benefits from drug development and the importance of individual patient benefits compared to the collective benefits to society in general. Background: Ethical guidelines require that clinical research involving humans offer the potential for benefit. A number of characteristics can be applied to define research benefit. Often benefit is categorized as being either direct or indirect. Indirect benefits can involve collective benefits for society rather than any benefits to the trial patient or subject. The purpose of this review was to examine which potential individual and societal benefits were mentioned as being expected in publications from government experts and which were mentioned in publications describing completed drug development trial results. Methods: Literature on research benefit was first identified by searching the PubMed database using several combinations of the key words benefit and clinical research. The search was limited to articles published in English. A Google search with the same combinations of key words but without any language limitation was then performed. Additionally, the reference lists of promising articles were screened for further thematically related articles. Finally, a narrative review was performed of relevant English- and German-language articles published between 1996 and 2016 to identify which of several potential benefits were either theoretically expected or which were mentioned in publications on clinical drug development trial results. Results: The principal benefits from drug development discussed included 2 main types of benefit, namely individual benefits for the patients and collective benefits for society. Twenty-one of an overall total of 26 articles discussing theoretically expected benefits focused on individual patient benefits, whereas 17 out of 26 articles mentioned collective benefits to society. In these publications, the most commonly mentioned theoretically expected individual patient benefit was the chance to receive up-to-date care (38.1%). A general increase in knowledge about health care, treatments, or drugs (70.6%) was the most commonly mentioned theoretically expected benefit for society. In contrast, all 13 publications reporting actual benefits of clinical drug development trials focused on personal benefits and only 1 of these publications also mentioned a societal benefit. The most commonly mentioned individual benefit was an increased quality of life (53.9%), whereas the only mentioned collective benefit to society was a general gain of knowledge (100.0%). Conclusions: Both theoretically expected and actually reported benefits in the majority of the included publications emphasized the importance of individual patient benefits from drug development rather than the collective benefits to society in general. The authors of these publications emphasized the right of each individual patient or subject to look for and expect some personal benefit from participating in a clinical trial rather than considering societal benefit as a top priority. From an ethical point of view, the benefits each individual patient receives from his or her participation in a clinical trial might also be seen as a societal benefit, especially when the drug or device tested, if approved for marketing, would eventually be made available for other similar patients from the country in which the clinical trial was conducted.

Background: Depletion of ovarian hormone in postmenopausal women has been associated with changes in the locomotor apparatus that may compromise walking function including muscle atrophy/weakness, weight gain, and bone demineralization. Therefore, handgrip strength (HGS), bone mineral density (BMD) and body composition [percentage body fat mass (%BFM), fat mass (FM), Fat-free mass (FFM) and body mass index (BMI)], may significantly vary and predict WB in postmenopausal women. Consequently, the study sought to 1. Explore body composition, BMD and muscle strength differences between premenopausal and postmenopausal women and 2. Explore how these variables [I.e., body composition, BMD and muscle strength] relate to WB in postmenopausal women. Method: Fifty-one pre-menopausal (35.74 + 1.52) and 50 postmenopausal (53.32 + 2.28) women were selected by convenience sampling and studied. Six explanatory variables (HGS, BMD, %BFM, FFM, BMI and FM) were explored to predict WB in postmenopausal women: Data collected were analyzed using multiple linear regression, ANCOVA, independent t-test and Pearson correlation coefficient at p < 0.05. Result: Postmenopausal women had higher BMI(t = + 1.72; p = 0.04), %BFM(t = + 2.77; p = .003), FM(t = + 1.77; p = 0.04) and lower HGS(t = − 3.05; p = 0.001),compared to the premenopausal women. The predicted main effect of age on HGS was not significant, F(1, 197) = 0.03, p = 0.06, likewise the interaction between age and %BFM, F(1, 197) = 0.02, p = 0.89; unlike the predicted main effect of %BFM, F(1, 197) = 10.34, p = .002, on HGS. HGS was the highest predictor of WB (t = 2.203; β=0.3046) in postmenopausal women and combined with T-score right big toe (Tscorert) to produce R2 = 0.11;F (2, 47)=4.11;p = 0.02 as the best fit for the predictive model. The variance (R2) change was significant from HGS model (R2 = 0.09;p = 0.03) to HGS + Tscorert model (R2 = 0.11;p = 0.02). The regression model equation was therefore given as: WB =5.4805 + 0.1578(HGS) + (− 1.3532) Tscorert. Conclusion: There are differences in body composition suggesting re-compartmentalization of the body, which may adversely impact the (HGS) muscle strength in postmenopausal women. Muscle strength and BMD areassociated with WB, although, only contribute to a marginal amount of the variance for WB. Therefore, other factors in addition to musculoskeletal health are necessary to mitigate fall risk in postmenopausal women.

Up to 80% of medical information is documented by unstructured data such as clinical reports written in natural language. Such data is called unstructured because the information it contains cannot be retrieved automatically as straightforward as from structured data. However, we assume that the use of this flexible kind of documentation will remain a substantial part of a patient’s medical record, so that clinical information systems have to deal appropriately with this type of information description. On the other hand, there are efforts to achieve semantic interoperability between clinical application systems through information modelling concepts like HL7 FHIR or openEHR. Considering this, we propose an approach to transform unstructured documented information into openEHR archetypes. Furthermore, we aim to support the field of clinical text mining by recognizing and publishing the connections between openEHR archetypes and heterogeneous phrasings. We have evaluated our method by extracting the values to three openEHR archetypes from unstructured documents in English and German language.

The network security framework VisITMeta allows the visual evaluation and management of security event detection policies. By means of a "what-if" simulation the sensitivity of policies to specific events can be tested and adjusted. This paper presents the results of a user study for testing the usability of the approach by measuring the correct completion of given tasks as well as the user satisfaction by means of the system usability scale.