Invent (Germany)

Mevcut çalışmanın amacı, kişilerarası duygu düzenleme stratejilerinden yatıştırılma alt boyutunun ve algılanan romantik ilişki kalitesinin psikolojik sıkıntı üzerindeki etkilerini incelemektir. Araştırmaya, uygun örnekleme yöntemiyle seçilen 18-65 yaş arası, romantik ilişki içinde olan 230 yetişkin katılmıştır. Araştırmada “Kişilerarası Duygu Düzenleme Ölçeği”, “Algılanan Romantik İlişki Kalitesi Ölçeği” ve “Depresyon, Anksiyete ve Stres Ölçeği” kullanılmıştır. Çalışmanın sonuçlarına göre yatıştırılma stratejisinin kullanım düzeyi psikolojik sıkıntı düzeyini anlamlı ve pozitif yönde [F(1, 229) = 5.49, ß= .15, p

Os nematoides de solo são organismos que podem ser utilizados como indicadores de perturbações no solo por estarem presente em toda cadeia trófica. Esses organismos são diretamente influenciado pelas propriedades quimicas e fisicas do solo, umidade e presença de espécies vegetais. Com o objetivo de estudar a comunidade de nematoides do solo no Brasil, foi realizada uma revisão bibliográfica sobre este tema no banco de dados da Web of Sience utilizando as palvras community, nematodes, soil e Brazil e após realizar um filtro para separar os artigos que avaliaram apenas os fitonematoides sobraram 19 artigos. Os nematoides do solo são divididos por hábito alimentar em bacteriófagos, micófagos, herbívoros, onívoros e predadores, cada grupo com a sua função, destacando-se os fitonematoides que são prejudiciais ao desenvolvimento de culturas agrícolas. Com esta revisão foi possível identificar que pucos artigos foram publicados relacionados a comunidade de nematoides de solo no Brasil e apenas oito unidades federativas realizaram pesquisa na área, com enfase em poucas culturas agrícolas. Demosntrando a necessidade de mais pesquisas relacionadas a comunidade de nematoides nos solos brasileiros.

Abstract Importance: Decision-making in trauma patients remains challenging and often result in deviation from guidelines. Machine-Learning (ML) enhanced decision-support could improve hemorrhage resuscitation. Aim To develop a ML enhanced decision support tool to predict Need for Hemorrhage Resuscitation (NHR) (part I) and test the collection of the predictor variables in real time in a smartphone app (part II). Design, Setting, and Participants: Development of a ML model from a registry to predict NHR relying exclusively on prehospital predictors. Several models and imputation techniques were tested. Assess the feasibility to collect the predictors of the model in a customized smartphone app during prealert and generate a prediction in four level-1 trauma centers to compare the predictions to the gestalt of the trauma leader. Main Outcomes and Measures: Part 1: Model output was NHR defined by 1) at least one RBC transfusion in resuscitation, 2) transfusion ≥ 4 RBC within 6 hours, 3) any hemorrhage control procedure within 6 hours or 4) death from hemorrhage within 24 hours. The performance metric was the F4-score and compared to reference scores (RED FLAG, ABC). In part 2, the model and clinician prediction were compared with Likelihood Ratios (LR). Results From 36325 eligible patients in the registry (Nov 2010 - May 2022), 28614 were included in the model development (Part 1). Median age was 36 [25–52], median ISS 13 [5–22], 3249/28614 (11%) corresponded to the definition of NHR. A XGBoost model with nine prehospital variables generated the best predictive performance for NHR according to the F4-score with a score of 0.76 [0.73–0.78]. Over a 3-month period (Aug - Oct 2022), 139 of 391 eligible patients were included in part II (38.5%), 22/139 with NHR. Clinician satisfaction was high, no workflow disruption observed and LRs comparable between the model and the clinicians. Conclusions and Relevance: The ShockMatrix pilot study developed a simple ML-enhanced NHR prediction tool demonstrating a comparable performance to clinical reference scores and clinicians. Collecting the predictor variables in real-time on prealert was feasible and caused no workflow disruption.

Two-dimensional(2d) data access is crucial in connecting people with blindness and visual impairment (BVI) with the rest of the world. Such 2d information includes, for example, floor plans of train stations provided by transportation networks to help travellers navigate and understand a train station and its surroundings, but these documents are not yet accessible. Existing assistive technologies, such as 2d pin-matrix displays, offer new possibilities here to present 2d information via a refreshable tactile pin-matrix display and audio feedback. However, user interfaces that enable people with BVI to perceive the shape and content of information are still not yet fully functional and explored. This paper presents a workflow for converting PDF files of station floor plans provided by transportation networks into an accessible Scalable Vector Graphics format (SVG). Those files are not only usable for 2d pin-matrix displays but can also be printed on swell paper or can be embossed and used in 2d tactile graphic readers. Moreover, we propose a new user interface for 2d refreshable pin-matrix devices that enables people with BVI to interact with train station floor plans. This user interface was implemented for Inventivio GmbH’s Tactonom pin-matrix device (V1) and supports moving, navigating to elements and zooming in SVG train station map documents. Further work includes implementing new features to reduce the complexity and information overload on a tactile surface.

The prediction of CNC machine tool wear is limited due to the scarcity of data in industry. A sufficient amount of experimental and real-live factory data is missing to train accurate supervised machine learning prediction models. Considering that collecting a large amount of data in real industrial environments can be a great challenge, this paper investigates the applicability of data augmentation techniques for generating synthetic data. Our paper focuses on a multi-sensor approach for the classification of tool wear states in the milling process. Multi-sensor data fusion is performed in the frequency domain. Extracted features are then used for tool wear classification. In order to increase the amount of training data, a generative adversarial network (GAN) is designed for data augmentation purposes. An early stopping strategy is designed to improve the effectiveness of the proposed GAN. The experimental results show that the proposed GAN helps to significantly improve the performance of tool wear classification models. With the inclusion of GAN, the number of required real-environment industrial data can be reduced. The research shows promising results to supplement experimental data by GAN-based synthetic data for predicting tool wear.

Abstract Die bei der Wiederaufbereitung von recyceltem Altpapier rückgewonnenen Fasern führen bei der Produktion von braunem Karton und Pappe zu einem hohen Eintrag von Kalk, Füllstoffen und Bindemitteln. Aus der Produktion werden auch große Mengen an organischen

Abstract Commercial aircraft today require efficient high-lift and control systems on the wings to reduce the drag in flight or decrease the take-off and landing speeds. Morphing mechanisms are one approach for improved high-lift systems. In most cases the objective function is an increased lift to drag ratio or the noise reduction. On closer examination control systems as well as morphing mechanisms are located in a certain wing segment. The transition between a moving wing part and the fixed wing is a step, which creates additional vortices. This segments the wing in span-wise direction and reduces the efficiency. A flexible skin between a moving and a fixed wing parts smooths the contour and minimize the efficiency reduction of the wing. A full scale demonstrator of a wing segment was manufactured with two flexible skin designs. The first subcomponent connects a morphing leading edge with a rib of the wing over a span of one meter. The skin is a material mix of ethylene-propylene-diene monomer (EPDM) rubber and fiberglass-reinforced plastic. The rubber is the basis of the skin and the glass-fiber is added as local skin stiffeners in the form of strips in chord-wise direction. The second subcomponent blends the aileron with a rib of the wing in a triangular design. The connection of three different hinges realizes a morphing triangle, which is loaded in an in-plane shear only state of stress in each aileron position. The core of the triangle is a 3D printed structure, which is free in shear. The covering skin is a combination of EPDM with carbon fibers oriented in +/−30° direction to obtain shear compliance and to resist the loads on the triangle. The deformation of each concept is identified at the demonstrator. Therefore, an optical measurement system scans the surface in the initial and deflected state. The required deformation precision of the concepts differs due to their design. The contour at the leading edge requires a certain shape over the span. The analysis of the skin buckling is one requirement at the transition triangle during the aileron motion. The experimental results show a smooth transition contour at the leading edge and no buckling effects at the triangle. The results can be used for the validation of simulation models. Furthermore, both skin concepts cover the gap between a moving wing segment and a fixed wing part. The elimination of steps in span-wise direction can improve the aero-acoustic behavior along the wing for future aircraft.

This study focused on the potential of topology optimization (TO) for metallic tertiary structures of spacecrafts produced by the additive manufacturing (AM) technique laser powder bed fusion. First, a screening of existing conventionally manufactured products was carried out to evaluate the benefits of a redesign concerning product performance and the associated economic impact. As a result of the study, the most suitable demonstrator was selected. This reference structure was redesigned by TO taking into consideration the AM process constraints. Another major aim of this work was to evaluate the possibilities and challenges of AM (accuracies, surface quality, process parameters, postmachining, and mechanical properties) in addition to the redesign process. A comprehensive approach was implemented including detailed analysis of the powder, mechanical properties, in-process parameters, and nondestructive inspection (NDI). All measured values were used for a back loop to the design process, thereby providing a final robust redesign. Finally, the fine-tuned demonstrator was built up in an iterative process. The parts were tested under representative conditions for the application to verify the performance. The demonstrator qualification test campaign contained thermal cycling, vibration testing, static load testing, and NDI. Thus, an improvement in technology readiness level up to “near flight qualified” was reached.