Testing The Limits: A Robustness Analysis Of Logistic Growth Models For Life Cycle Estimation During The COVID-19 Pandemic

The semiconductor industry operates in a dynamic environment characterized by rapid technological advancements, extensive research and development investments, long planning horizons, and cyclical market behavior. Consequently, staying vigilant to technological disruptions and shifting trends is crucial. This is especially challenging when external shocks seriously affect supply chain processes and demand patterns. Particularly, recent events, such as the COVID-19 pandemic, the ongoing Russian invasion of Ukraine, and high consumer price inflation impacting the semiconductor cycle emphasize the need to account for these influences. In this context, we analyze growth patterns and life cycles of various technologies within the semiconductor industry by estimating logistic growth models. The logistic growth model was originally formulated to describe population dynamics. However, many processes outside the discipline of ecology share the fundamental characteristics of natural growth: self-proportionality and a self-regulating mechanism. Out of the different applications, two are of particular interest in the context of strategic business decisions: (1) modeling innovation diffusion and technological change to predict the mid- to long-term growth of a market, and (2) modeling of product life cycles. To obtain market growth and life cycle predictions, we apply the logistic growth model to forecast cumulative revenues by technology over time. This model treats the analyzed technology as a closed system. However, in practice, external shocks are the norm. To analyze the robustness to such external shocks, we compare technology life cycle estimates derived from logistic growth models before and after the effects of COVID-19 became evident for a wide array of semiconductor technologies. We find that the impact of COVID-19 on these life cycle estimates is mixed, but the median change is low. Our findings have implications for the application of logistic growth models in strategic decision-making, helping stakeholders navigate the complexities of technological innovation, diffusion, and market growth

Miniband-related 1.4–1.8 μm luminescence of Ge/Si quantum dot superlattices

The luminescence properties of highly strained, Sb-doped Ge/Si multi-layer heterostructures with incorporated Ge quantum dots (QDs) are studied. Calculations of the electronic band structure and luminescence measurements prove the existence of an electron miniband within the columns of the QDs. Miniband formation results in a conversion of the indirect to a quasi-direct excitons takes place. The optical transitions between electron states within the miniband and hole states within QDs are responsible for an intense luminescence in the 1.4–1.8 µm range, which is maintained up to room temperature. At 300 K, a light emitting diode based on such Ge/Si QD superlattices demonstrates an external quantum efficiency of 0.04% at a wavelength of 1.55 µm

Genotype-phenotype spectrum of PYCR1-related autosomal recessive cutis laxa

Autosomal recessive cutis laxa type 2B (ARCL2B; OMIM # 612940) is a segmental progeroid disorder caused by mutations in PYCR1 encoding pyrroline-5-carboxylate reductase 1, which is part of the conserved proline de novo synthesis pathway. Here we describe 33 patients with PYCR1-related ARCL from 27 families with initial diagnoses varying between wrinkly skin syndrome, gerodermia osteodysplastica, De Barsy syndrome or more severe progeria syndromes. Given the difficult differential diagnosis of ARCL syndromes we performed a systematic comparison of clinical features of PYCR1-related ARCL. Intrauterine growth retardation, a characteristic triangular facial gestalt, psychomotor retardation, and hypotonia were the most relevant distinctive hallmarks of ARCL due to proline de novo synthesis defects. Corneal clouding or cataracts, athetoid movements, and finger contractures were rather rare features, but had a high predictive value. In our cohort we identified 20 different PYCR1 mutations of which seven were novel. Most of the mutations accumulated in exons 4 to 6. Missense alterations of highly conserved residues were most frequent followed by splice site changes and a single nonsense mutation. Analysis of genotype-phenotype correlation revealed that patients with mutations in the first two exons had lower average clinical scores and absent or only mild intellectual disability. Structural analyses predicted interference with PYCR1 multimerization for a subset of missense mutations. These findings have implications for the clinics as well as the pathomechanism of PYCR1-related ARCL