Method for Automatic Level Matching in a Local Network, in Particular a Multicomputer Arrangement, Comprising a Bus System Having Lightwaves Guides, for the Purpose of Collision Recognition

A method is disclosed for automatic level matching in a local network, particularly for a multicomputer arrangement, comprising an optical bus system, for the purpose of collision recognition. Given a required level matching, the process is executed such that a fundamental phase is provided in which level matching devices respectively individually assigned to the computers are synchronized with one another. A first matching phase is provided in which all level matching devices simultaneously execute a process for setting a reference voltage to the lowest received level, whereby the sum of all attenuation components of the signal path at the receiving side of the appertaining computer is taken into consideration. A second matching phase is provided in which all level matching devices successively execute a process for setting the transmission level of their own transmitter such that the emitted light power at its own receiver leads to the receiving power registered as lowest, whereby the sum of all attenuation components of the signal path at the transmitting side of the appertaining computer is taken into consideration

Preferences of diabetes patients and physicians: A feasibility study to identify the key indicators for appraisal of health care values

<p>Abstract</p> <p>Background</p> <p>Evidence-based medicine, the Institute of Medicine (IOM) and the German Institute for Quality and Efficiency in Health Care (IQWiG), support the inclusion of patients' preferences in health care decisions. In fact there are not many trials which include an assessment of patient's preferences. The aim of this study is to demonstrate that preferences of physicians and of patients can be assessed and that this information may be helpful for medical decision making.</p> <p>Method</p> <p>One of the established methods for assessment of preferences is the conjoint analysis. Conjoint analysis, in combination with a computer assisted telephone interview (CATI), was used to collect data from 827 diabetes patients and 60 physicians, which describe the preferences expressed as levels of four factors in the management and outcome of the disease. The first factor described the main treatment effect (reduction of elevated Hb_A1c, improved well-being, absence of side effects, and no limitations of daily life). The second factor described the effect on the body weight (gain, no change, reduction). The third factor analyzed the mode of application (linked to meals or flexible application). The fourth factor addressed the type of product (original brand or generic product). Utility values were scaled and normalized in a way that the sum of utility points across all levels is equal to the number of attributes (factors) times 100.</p> <p>Results</p> <p>The preference weights confirm that the reduction of body weight is at least as important for patients - especially obese patients - and physicians as the reduction of an elevated Hb_A1c. Original products were preferred by patients while general practitioners preferred generic products.</p> <p>Conclusion</p> <p>Using the example of diabetes, the difference between patients' and physicians' preferences can be assessed. The use of a conjoint analysis in combination with CATI seems to be an effective approach for generation of data which are needed for policy and medical decision making in health care.</p

LEAN PANEL BENDER – Einige mechanische Aspekte der Modellierung in Echtzeit für Produktion in Losgröße 1

Nachfolgend werden einige wissenschaftliche Aspekte der Echtzeit-Materialerkennungsstrategie MAC diskutiert, die in der neuen Maschinenfamilie LEAN PANEL BENDER der Firma Salvagnini Maschinenbau realisiert ist und die eine hochpräzise und hocheffiziente Herstellung von komplex geformten Blechprodukten sowohl bei Losgröße 1 als auch in der Serie erlaubt.(VLID)342339

Advanced mechanical simulation models for automatic panel benders

With automatic panel benders complete products are manufactured from sheet metal. In order to achieve short cycle times with high flexibility, a deep insight into the non-linear bending process is required. For this reason, efficient mechanical simulation models have been implemented, combining Finite Element Method, multibody dynamics simulation tools, contact mechanics algorithms and substructuring. Scope of this work is the comparison of several simulation models with measurement results performed on a Salvagnini P4XeD automatic panel bender

Industrial application of advanced adaptive concepts for automatic panel benders

Recently, the requirements on sheet metal production processes have increased significantly. Highest precision and flexibility with efficient energy consumption and short cycle times can be achieved by advanced concepts only. This requires a deep insight into the non-linear bending process. For this sake, efficient simulation models have been implemented to model the bending process: two and three dimensional finite element models combined with multibody simulation tools, contact mechanics algorithms and substructure techniques. The simulation tools have been successfully calibrated by measurement results. With the obtained detailed process knowledge, new adaptive concepts have been introduced, e.g. a smart crowning system in order to achieve straight profiles. The industrial application has shown the advantage of utilizing the above mentioned techniques. The straightness of the bends has been significantly increased, while energy consumption and cycle times have been reduced. Secondly, the development time of new machine concepts has been drastically reduced, such that the first prototype can be transferred to series production within short time. Moreover, the applied strategies show a large potential for future developments

Estimating Snow Accumulation and Ablation with L-Band Interferometric Synthetic Aperture Radar (InSAR)

Snow is a critical water resource for the western United States and many regions across the globe. However, our ability to accurately measure and monitor changes in snow mass from satellite remote sensing, specifically its water equivalent, remains a challenge. To confront these challenges, NASA initiated the SnowEx program, a multiyear effort to address knowledge gaps in snow remote sensing. During SnowEx 2020, the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) team acquired an L-band interferometric synthetic aperture radar (InSAR) data time series to evaluate the capabilities and limitations of repeat-pass L-band InSAR for tracking changes in snow water equivalent (SWE). The goal was to develop a more comprehensive understanding of where and when L-band InSAR can provide SWE change estimates, allowing the snow community to leverage the upcoming NASA–ISRO (NASA–Indian Space Research Organization) SAR (NISAR) mission. Our study analyzed three InSAR image pairs from the Jemez Mountains, NM, between 12 and 26 February 2020. We developed a snow-focused multi-sensor method that uses UAVSAR InSAR data synergistically with optical fractional snow-covered area (fSCA) information. Combining these two remote sensing datasets allows for atmospheric correction and delineation of snow-covered pixels within the radar swath. For all InSAR pairs, we converted phase change values to SWE change estimates between the three acquisition dates. We then evaluated InSAR-derived retrievals using a combination of fSCA, snow pits, meteorological station data, in situ snow depth sensors, and ground-penetrating radar (GPR). The results of this study show that repeat-pass L-band InSAR is effective for estimating both snow accumulation and ablation with the proper measurement timing, reference phase, and snowpack conditions