Tuning the Computational Effort: An Adaptive Accuracy-aware Approach Across System Layers

This thesis introduces a novel methodology to realize accuracy-aware systems, which will help designers integrate accuracy awareness into their systems. It proposes an adaptive accuracy-aware approach across system layers that addresses current challenges in that domain, combining and tuning accuracy-aware methods on different system layers. To widen the scope of accuracy-aware computing including approximate computing for other domains, this thesis presents innovative accuracy-aware methods and techniques for different system layers. The required tuning of the accuracy-aware methods is integrated into a configuration layer that tunes the available knobs of the accuracy-aware methods integrated into a system

Model Factory for Additive Manufacturing of Mechatronic Products: Interconnecting World-class Technology Partnerships with Leading AM Players

AbstractThe additive manufacturing (AM) model factory's aim is to establish a leading-edge learning academy for the digital and generative production of innovative mechatronic products, where the complete value chain is integrated on a single site. Short courses and deep dives enable easier access to the state of the art technologies and increase the awareness for their potentials. Anchored in key industries such as automotive, aerospace, and medical by major OEMs and regional SMEs, the AM model factory cooperates with world-class partners and leading market players. This paper displays the model factory's setup, selected technologies, exemplary courses, and benefits

It is not just menopause: symptom clustering in the Study of Women’s Health Across the Nation

Abstract Background Patterns of symptom clustering in midlife women may suggest common underlying mechanisms or may identify women at risk of adverse health outcomes or, conversely, likely to experience healthy aging. This paper assesses symptom clustering in the Study of Women’s Health Across the Nation (SWAN) longitudinally by stage of reproductive aging and estimates the probability of women experiencing specific symptom clusters. We also evaluate factors that influence the likelihood of specific symptom clusters and assess whether symptom clustering is associated with women’s self-reported health status. Methods This analysis includes 3289 participants in the multiethnic SWAN cohort who provided information on 58 symptoms reflecting a broad range of physical, psychological and menopausal symptoms at baseline and 7 follow-up visits over 16 years. We conducted latent transition analyses to assess symptom clustering and to model symptomatology across the menopausal transition (pre, early peri-, late peri- and post-menopausal). Joint multinomial logistic regression models were used to identify demographic characteristics associated with premenopausal latent class membership. A partial proportional odds regression model was used to assess the association between latent class membership and self-reported health status. Results We identified six latent classes that ranged from highly symptomatic (LC1) across most measured symptoms, to moderately symptomatic across most measured symptoms (LC2), to moderately symptomatic for a subset of symptoms (vasomotor symptoms, pain, fatigue, sleep disturbances and physical health symptoms) (LC3 and LC5) with one class (LC3) including interference in life activities because of physical health symptoms, to numerous milder symptoms, dominated by fatigue and psychological symptoms (LC4), to relatively asymptomatic (LC6). In pre-menopause, 10% of women were classified in LC1, 16% in LC2, 14% in LC3 and LC4, 26% in LC5, and 20% in LC6. Intensity of vasomotor and urogenital symptoms as well as sexual desire) differed minimally by latent class. Classification into the two most symptomatic classes was strongly associated with financial strain, White race/ethnicity, obesity and smoking status. Over time, women were most likely to remain within the same latent class as they transitioned through menopause stages (range 39–76%), although some women worsened or improved. The probability of moving between classes did not differ substantially by menopausal stage. Women in the highly symptomatic classes more frequently rated their health as fair to poor compared to women in the least symptomatic class. Conclusion Clear patterns of symptom clustering were present early in midlife, tended to be stable over time, and were strongly associated with self-perceived health. Notably, vasomotor symptoms tended to cluster with sleep disturbances and fatigue, were present in each of the moderate to highly symptomatic classes, but were not a defining characteristic of the symptom clusters. Clustering of midlife women by symptoms may suggest common underlying mechanisms amenable to interventions. Given that one-quarter of midlife women were highly or moderately symptomatic across all domains in the pre-menopause, addressing symptom burden in early midlife is likely critical to ameliorating risk in the most vulnerable populations.https://deepblue.lib.umich.edu/bitstream/2027.42/137710/1/40695_2017_Article_21.pd

Generation of narrowband, high-intensity, carrier-envelope phase-stable pulses tunable between 4 and 18 THz

We demonstrate the generation of narrowband (<1 THz) high-energy (~2 uJ) carrier-envelope phase-stable pulses, tunable between 4 and 18 THz as achieved by difference-frequency mixing between chirped near-infrared pulses in organic DSTMS

Generation of narrowband, high-intensity, carrier-envelope phase-stable pulses tunable between 4 and 18 THz

We demonstrate the generation of narrowband (<1 THz) high-energy (~2 uJ) carrier-envelope phase-stable pulses, tunable between 4 and 18 THz as achieved by difference-frequency mixing between chirped near-infrared pulses in organic DSTMS

Optisches Sortiersystem sowie entsprechendes Sortierverfahren

Optisches Sortiersystem zum Sortieren von Objekten (O) eines Materialstroms (M) umfassend eine Bildaufnahmeeinheit (1) zum optischen Erfassen des Materialstroms (M) und zum Erzeugen von Bilddaten (4) desselben (M), eine Auswerteeinheit (2) zum Identifizieren und Klassifizieren von Objekten (O) im Materialstrom (M), und eine Sortiereinheit (3) zum Sortieren klassifizierter Objekte (O) des Materialstroms (M), dadurch gekennzeichnet, dass mit der Auswerteeinheit (2) aus den erzeugten Bilddaten (4) ein oder mehrere Belegungsparameter (5), der/die den Materialstrom (M) hinsichtlich seiner Belegung mit den Objekten (O) kennzeichnet/n, bestimmbar ist/sind und dass auf Basis des/der bestimmten Belegungsparameter(s) (5) ein oder mehrere das Identifizieren und Klassifizieren der Objekte (O) durch die Auswerteeinheit (2) steuernde(r) Auswertungsparameter (6, 8) einstellbar ist/sind

EVI1 Promotes the Proliferation and Invasive Properties of Human Head and Neck Squamous Cell Carcinoma Cells

Head and neck squamous cell carcinoma (HNSCC) is a frequent malignancy with a poor prognosis. So far, the EGFR inhibitor cetuximab is the only approved targeted therapy. A deeper understanding of the molecular and genetic basis of HNSCC is needed to identify additional targets for rationally designed, personalized therapeutics. The transcription factor EVI1, the major product of the MECOM locus, is an oncoprotein with roles in both hematological and solid tumors. In HNSCC, high EVI1 expression was associated with an increased propensity to form lymph node metastases, but its effects in this tumor entity have not yet been determined experimentally. We therefore overexpressed or knocked down EVI1 in several HNSCC cell lines and determined the impact of these manipulations on parameters relevant to tumor growth and invasiveness, and on gene expression patterns. Our results revealed that EVI1 promoted the proliferation and migration of HNSCC cells. Furthermore, it augmented tumor spheroid formation and the ability of tumor spheroids to displace an endothelial cell layer. Finally, EVI1 altered the expression of numerous genes in HNSCC cells, which were enriched for Gene Ontology terms related to its cellular functions. In summary, EVI1 represents a novel oncogene in HNSCC that contributes to cellular proliferation and invasiveness