Unified exact design with early stopping rules for single arm clinical trials with multiple endpoints

Adaptive designs are gaining popularity in early phase clinical trials because they enable investigators to change the course of a study in response to accumulating data. We propose a novel design to simultaneously monitor several endpoints. These include efficacy, futility, toxicity and other outcomes in early phase, single-arm studies. We construct a recursive relationship to compute the exact probabilities of stopping for any combination of endpoints without the need for simulation, given pre-specified decision rules. The proposed design is flexible in the number and timing of interim analyses. A R Shiny app with user-friendly web interface has been created to facilitate the implementation of the proposed design.

Packaging Design: Communication with the Consumer

The article considers important issues related to brand positioning and product packaging design. Visual perception of this design product should solve a specific commercial task. Modern market is developing rapidly and packaging expands its functions and becomes multifunctional (ecological, interactive, exclusive). At the same time, buyers are becoming more demanding. Packaging design is a consistent process aimed at positioning the product, segmenting the target audience, identifying competitive advantages of the product, creating an exact design concept that provides individuality, creativity and attention to detail. The aim of the article is to consider the communication process in modern packaging design. Packaging design is one of the most important directions in visual communication design. Today we can conclude that packaging performs not only its original function (protection, storage and transportation of goods). Communication with a consumer is also an extremely important aspect, because it is the key point when choosing a packaging design strategy for a particular product group. It is extremely important to form an exact message and convey it to the target audience. Communicative function of packaging is also directly related to aesthetic perception and advertising of the product. Designers must be aware of the latest world trends because they are the ones who contribute to the introduction of the latest creative ideas in this area. All these innovations make it possible to fully reveal the key image of packaging design. New trends in the field of consumer packaging design put forward by the society and market have brought changes in functional features of packaging. Now much attention is paid to communication packaging, as packaging often appears the factor that stimulates the purchase of goods. It is able to promote brands and products depicted on it and to convey certain ideas about their properties.

Graphical Design Methodology of Multi-Degrees-of-Freedom Tuned Mass Damper for Suppressing Multiple Modes

The multi-degrees-of-freedom (MDOF) tuned mass damper (TMD) has proven its ability to suppress multiple modes of interest, and it possesses less mounting space than multiple single degree-of-freedom TMDs of equal damping mass. However, it is challenging to implement the exact design of MDOF TMDs having expected vibration modes. The conceptual design of MDOF TMD containing visualized DOFs is first presented by the graphical approach, and the visualization of the quantitative relationship between the freedoms and constraints of TMD is attained. Then, dynamics modeling is analytically formulated by incorporating experimental data, and optimization of MDOF TMD considering background modes is performed. Two scenarios of MDOF TMD (i.e., 2DOFs TMD and 3DOFs TMD) are simulated. Vibration suppression of single dominant mode and multiple modes are achieved, corresponding to the case when the primary structure is subjected to wide and narrow band harmonic excitations, respectively. Afterward, a TMD with one rotational and two translational (1R2 T) DOFs is designed by embodying the geometric constraint patterns by flexible beams, and changeable elastic elements are incorporated. Experiments show that the first, second, and third bending modes of the cantilever beam are suppressed by 80.0%, 67.5%, and 61.2%, respectively, by the 3DOFs TMD for multiple modes suppression.

Exact Design Space Exploration Based on Consistent Approximations

The aim of design space exploration (DSE) is to identify implementations with optimal quality characteristics which simultaneously satisfy all imposed design constraints. Hence, besides searching for new solutions, a quality evaluation has to be performed for each design point. This process is typically very expensive and takes a majority of the exploration time. As nearly all the explored design points are sub-optimal, most of them get discarded after evaluation. However, evaluating a solution takes virtually the same amount of time for both good and bad ones. That way, a huge amount of computing power is literally wasted. In this paper, we propose a solution to the aforementioned problem by integrating efficient approximations in the background of a DSE engine in order to allow an initial evaluation of each solution. Only if the approximated quality indicates a promising candidate, the time-consuming exact evaluation is executed. The novelty of our approach is that (1) although the evaluation process is accelerated by using approximations, we do not forfeit the quality of the acquired solutions and (2) the integration in a background theory allows sophisticated reasoning techniques to prune the search space with the help of the approximation results. We have conducted an experimental evaluation of our approach by investigating the dependency of the accuracy of used approximations on the performance gain. Based on 120 electronic system level problem instances, we show that our approach is able to increase the overall exploration coverage by up to six times compared to a conservative DSE whenever accurate approximation functions are available.

Assessment of Workflow Feature Selection on Forest LAI Prediction with Sentinel-2A MSI, Landsat 7 ETM+ and Landsat 8 OLI

The European Space Agency (ESA)’s Sentinel-2A (S2A) mission is providing time series that allow the characterisation of dynamic vegetation, especially when combined with the National Aeronautics and Space Administration (NASA)/United States Geological Survey (USGS) Landsat 7 (L7) and Landsat 8 (L8) missions. Hybrid retrieval workflows combining non-parametric Machine Learning Regression Algorithms (MLRAs) and vegetation Radiative Transfer Models (RTMs) were proposed as fast and accurate methods to infer biophysical parameters such as Leaf Area Index (LAI) from these data streams. However, the exact design of optimal retrieval workflows is rarely discussed. In this study, the impact of five retrieval workflow features on LAI prediction performance of MultiSpectral Instrument (MSI), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) observations was analysed over a Dutch beech forest site for a one-year period. The retrieval workflow features were the (1) addition of prior knowledge of leaf chemistry (two alternatives), (2) the choice of RTM (two alternatives), (3) the addition of Gaussian noise to RTM produced training data (four and five alternatives), (4) possibility of using Sun Zenith Angle (SZA) as an additional MLRA training feature (two alternatives), and (5) the choice of MLRA (six alternatives). The features were varied in a full grid resulting in 960 inversion models in order to find the overall impact on performance as well as possible interactions among the features. A combination of a Terrestrial Laser Scanning (TLS) time series with litter-trap derived LAI served as independent validation. The addition of absolute noise had the most significant impact on prediction performance. It improved the median prediction Root Mean Square Error (RMSE) by 1.08 m2 m−2 when 5% noise was added compared to inversions with 0% absolute noise. The choice of the MLRA was second most important in terms of median prediction performance, which differed by 0.52 m2 m−2 between the best and worst model. The best inversion model achieved an RMSE of 0.91 m2 m−2 and explained 84.9% of the variance of the reference time series. The results underline the need to explicitly describe the used noise model in future studies. Similar studies should be conducted in other study areas, both forest and crop systems, in order to test the noise model as an integral part of hybrid retrieval workflows.

An Augmented Reality-Based Simulation Guide for Apparel Assembly

Augmented Reality (AR)-based technologies have revolutionized prototyping and manufacturing operations in many industries despite limited applications in the context of apparel. Currently, digital technologies are demanded in the process of apparel ‘design to manufacturing’ to improve efficiency while maintaining the product defects to a minimum level. This study proposes an AR-based tool to educate sample machinists to assemble even a complicated new product to meet the exact design specifications. Such guiding device overcomes product defects which occurs due to misinterpretations of design details. This study was carried out in two phases. During the first phase, qualitative research methods were utilized to analyze the impact of new product failures which occur due to misinterpretations of prototyping instructions. Also, this phase was utilized to analyze their perceptions of AR-based guiding tool, along with the suggestions to develop such system to support product assembly. The second phase proposes relevant guide to develop the new AR tool and presents the acceptance of such tool from the focus group consists of potential users. Future work will include creating relevant contents based on the proposed screen images. Then it will be useful tool to train sample developers to produce the prototypes right first time.