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A quantitative physical model for potential induced degradation of the shunting type (PID-s) in solar modules is introduced. Based on a drift and diffusion approach for sodium ions and atoms, it gives insight into the kinetics of degradation and the corresponding regeneration. A simple drift/source term is used to describe the time-dependent flux of Na-ions towards stacking faults at the surface of the solar cell. The assumed transport mechanism for Na+ ions through the SiN-layer uses the modified Stern-Eyring rate theory but our approach can also be adapted to other mechanisms. Several PID-s and regeneration curves of one-cell solar modules at T = 49°C and T = 90°C with 1000V potential difference between modul frame and cell were measured and least-square fits of the in-situ measured parallel resistance Rsh to the model were performed giving very good accordance.
Based on a few measurements, the model can predict PID-s and regeneration characteristics of solar modules under different conditions.
A novel approach to optically distinguish plastics based on fluorescence lifetime measurements
(2020)
In medical and biological research, fluorescence lifetime measurements and fluorescence lifetime imaging is already a part of the standardized analysis procedures. As first investigations have shown, polymers can be identified using fluorescence lifetime imaging and an evaluation algorithm. Thus, this contribution pursues a novel approach for the direct differentiation of four polymers with fluorescence lifetime imaging. Therefore, the evaluation algorithm is extended to compare several fluorescence lifetime images to prove that a distinction is possible.
A novel approach to optically distinguish plastics based on fluorescence lifetime measurements
(2020)
Providing a subset of previously studied information as a retrieval cue can impair memory for the remaining information. Previous work with adults has shown that such part-list cuing impairment (PLCI) can be transient or lasting, depending on study condition. Here, we investigated the persistence of PLCI in children. Three age groups (7- and 8-year-olds, 9- and 10-year-olds, and 12- to 14-year-olds) learned a list of items, either through a single study trial (1-study condition) or through two study-test cycles (2-study-test condition). Subsequently, two recall tests were administered, with part-list cues being provided in the first (critical) test but not in the second (final) test. Of primary interest was whether the detrimental effect of part-list cuing induced in the critical test would persist to the uncued final test. In 12- to 14-year-olds, we found an adult-like pattern of results, with lasting impairment in the 1-study condition but transient impairment in the 2-study-test condition. In contrast, in the two younger age groups, we found PLCI to be lasting in both study conditions, suggesting age differences in the persistence of PLCI. The results are discussed in light of a recently proposed two-mechanism account of PLCI that attributes lasting impairment to retrieval inhibition and transient impairment to strategy disruption. Following this account, the results suggest that whereas 12- to 14-year-olds’ PLCI was caused by (lasting) retrieval inhibition in the 1-study condition and by (transient) strategy disruption in the 2-study-test condition, 7- and 8-year-olds’ and 9- and 10-year-olds’ PLCI was caused by (lasting) retrieval inhibition in both study conditions.
Modern production facilities are becoming increasingly complex, as companies battle to meet the increasingly customer-specific demands with shorter lead times and higher efficiency. For the employees in the factory, who often bear the brunt of making short-term process decisions, this complexity is becoming unmanageable. The PhD project presented in the following aims to decrease the complexity of modern manufactory facilities by means of artificial intelligence. The focus is on product data analysis and manufactory process planning. Different approaches of artificial intelligence for use in a Self-Adapting Smart System (SASS) are to be investigated.
Many doubts accompany both the resource potential of hardwoods and their softwood substituting potential within its material utilisation. However, as the feedstock demand will rise with more and more wood-based biorefineries entering the market, wood supply security is an increasingly pressing topic. Currently, hardwood flow models are lacking, but are an essential basis for estimating future hardwood supply security. This study investigates the actual hardwood flows in Germany by applying a Material Flow Analysis (MFA). Visualising the results of the MFA for the reference year 2016. The MFA displays 4.44 +/- 0.12 million m³ (fob) recorded fellings in privately-owned forests, 8.60 +/- 0.15 million m³ (fob) recorded fellings in state forests, 9.31 +/- 0.52 million m³ (fob) as unrecorded harvest from forests (i.e. 37% of the total harvest) and 2.65 +/- 0.35 million m³ (fob) unrecorded fellings from non-forest area (11% of total harvest). Of that, almost 30% were used for materials and 70% were used for energy. Consequently, the potential for material use of hardwood in Germany lies beyond its current usage, especially given that good qualities are being used for energy due to actual low material consumer demand. Thus, the MFA assessed the quality and quantity of the German hardwood potential and showed that it offers significant possibilities for value added usage options such as, for example, producing innovative products in biorefineries using degraded high-quality assortments. Due to the low data consistency, heterogeneous datasets for the forest and wood industry sector were calibrated through data reconciliation and error propagation. Additionally, the lack of statistical data for specific wood industry sectors raised a problem, for instance, actual data on private combustion of wood, established hardwood uses, or new innovative products. Severe data issues regarding the German hardwood flow were confirmed.
Background:
Care pathways (CPWs) are complex interventions that have the potential to reduce treatment errors and optimize patient outcomes by translating evidence into local practice. To design an optimal implementation strategy, potential barriers to and facilitators of implementation must be considered.
The objective of this systematic review is to identify barriers to and facilitators of the implementation of CPWs in primary care (PC).
Methods:
A systematic search via Cochrane Library, CINAHL, and MEDLINE via PubMed supplemented by hand searches and citation tracing was carried out. We considered articles reporting on CPWs targeting patients at least 65 years of age in outpatient settings that were written in the English or German language and were published between 2007 and 2019. We considered (non-)randomized controlled trials, controlled before-after studies, interrupted time series studies (main project reports) as well as associated process evaluation reports of either methodology. Two independent researchers performed the study selection; the data extraction and critical appraisal were duplicated until the point of perfect agreement between the two reviewers. Due to the heterogeneity of the included studies, a narrative synthesis was performed.
Results:
Fourteen studies (seven main project reports and seven process evaluation reports) of the identified 8154 records in the search update were included in the synthesis. The structure and content of the interventions as well as the quality of evidence of the studies varied.
The identified barriers and facilitators were classified using the Context and Implementation of Complex Interventions framework. The identified barriers were inadequate staffing, insufficient education, lack of financial compensation, low motivation and lack of time. Adequate skills and knowledge through training activities for health professionals, good multi-disciplinary communication and individual tailored interventions were identified as facilitators.
Conclusions:
In the implementation of CPWs in PC, a multitude of barriers and facilitators must be considered, and most of them can be modified through the careful design of intervention and implementation strategies. Furthermore, process evaluations must become a standard component of implementing CPWs to enable other projects to build upon previous experience.
Artificial Intelligence (AI) is continuously moving into our surroundings. In its various forms, it has the potential to disrupt most aspects of human life. Yet, the discourse around AI has long been by experts and for experts. In this paper, we argue for a participatory approach towards designing human-AI interactions. We outline how we used design methodology to organise an interdisciplinary workshop with a diverse group of students – a workbook sprint with 45 participants from four different programs and 13 countries – to develop speculative design futures in five focus areas. We then provide insights into our findings and share our lessons learned regarding our workshop topic – AI and Space – our process, and our research. We learned that involving non-experts in complex technical discourses – such as AI – through the structural rigour of design methodology is a viable approach. We then conclude by laying out how others might use our findings and initiate their own workbook sprint to explore complex technologies in a human-centred way.