Dynamical tunneling in mushroom billiards

We study the fundamental question of dynamical tunneling in generic two-dimensional Hamiltonian systems by considering regular-to-chaotic tunneling rates. Experimentally, we use microwave spectra to investigate a mushroom billiard with adjustable foot height. Numerically, we obtain tunneling rates from high precision eigenvalues using the improved method of particular solutions. Analytically, a prediction is given by extending an approach using a fictitious integrable system to billiards. In contrast to previous approaches for billiards, we find agreement with experimental and numerical data without any free parameter.Comment: 4 pages, 4 figure

The Case for Learned Index Structures

Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this exploratory research paper, we start from this premise and posit that all existing index structures can be replaced with other types of models, including deep-learning models, which we term learned indexes. The key idea is that a model can learn the sort order or structure of lookup keys and use this signal to effectively predict the position or existence of records. We theoretically analyze under which conditions learned indexes outperform traditional index structures and describe the main challenges in designing learned index structures. Our initial results show, that by using neural nets we are able to outperform cache-optimized B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over several real-world data sets. More importantly though, we believe that the idea of replacing core components of a data management system through learned models has far reaching implications for future systems designs and that this work just provides a glimpse of what might be possible

Human phosphodiesterase 4D7 (PDE4D7) expression is increased in TMPRSS2-ERG positive primary prostate cancer and independently adds to a reduced risk of post-surgical disease progression

background: There is an acute need to uncover biomarkers that reflect the molecular pathologies, underpinning prostate cancer progression and poor patient outcome. We have previously demonstrated that in prostate cancer cell lines PDE4D7 is downregulated in advanced cases of the disease. To investigate further the prognostic power of PDE4D7 expression during prostate cancer progression and assess how downregulation of this PDE isoform may affect disease outcome, we have examined PDE4D7 expression in physiologically relevant primary human samples. methods: About 1405 patient samples across 8 publically available qPCR, Affymetrix Exon 1.0 ST arrays and RNA sequencing data sets were screened for PDE4D7 expression. The TMPRSS2-ERG gene rearrangement status of patient samples was determined by transformation of the exon array and RNA seq expression data to robust z-scores followed by the application of a threshold >3 to define a positive TMPRSS2-ERG gene fusion event in a tumour sample. results: We demonstrate that PDE4D7 expression positively correlates with primary tumour development. We also show a positive association with the highly prostate cancer-specific gene rearrangement between TMPRSS2 and the ETS transcription factor family member ERG. In addition, we find that in primary TMPRSS2-ERG-positive tumours PDE4D7 expression is significantly positively correlated with low-grade disease and a reduced likelihood of progression after primary treatment. Conversely, PDE4D7 transcript levels become significantly decreased in castration resistant prostate cancer (CRPC). conclusions: We further characterise and add physiological relevance to PDE4D7 as a novel marker that is associated with the development and progression of prostate tumours. We propose that the assessment of PDE4D7 levels may provide a novel, independent predictor of post-surgical disease progression

Development of improved semi-organic structural adhesives for elevated temperature applications Technical summary report, 1 ~JUL. 1964 - 29 ~FEB. 1968

Titanium chelate polymer adhesive formulation for aluminum joint curing in high temperature application

Autonomous Light Management in Flexible Photoelectrochromic Films Integrating High Performance Silicon Solar Microcells

Commercial smart window technologies for dynamic light and heat management in building and automotive environments traditionally rely on electrochromic (EC) materials powered by an external source. This design complicates building-scale installation requirements and substantially increases costs for applications in retrofit construction. Self-powered photoelectrochromic (PEC) windows are an intuitive alternative wherein a photovoltaic (PV) material is used to power the electrochromic device, which modulates the transmission of the incident solar flux. The PV component in this application must be sufficiently transparent and produce enough power to efficiently modulate the EC device transmission. Here, we propose Si solar microcells (μ-cells) that are i) small enough to be visually transparent to the eye, and ii) thin enough to enable flexible PEC devices. Visual transparency is achieved when Si μ-cells are arranged in high pitch (i.e. low-integration density) form factors while maintaining the advantages of a single-crystalline PV material (i.e., long lifetime and high performance). Additionally, the thin dimensions of these Si μ-cells enable fabrication on flexible substrates to realize these flexible PEC devices. The current work demonstrates this concept using WO₃ as the EC material and V₂O₅ as the ion storage layer, where each component is fabricated via sol-gel methods that afford improved prospects for scalability and tunability in comparison to thermal evaporation methods. The EC devices display fast switching times, as low as 8 seconds, with a modulation in transmission as high as 33%. Integration with two Si μ-cells in series (affording a 1.12 V output) demonstrates an integrated PEC module design with switching times of less than 3 minutes, and a modulation in transmission of 32% with an unprecedented EC:PV areal ratio

On Hilberg's Law and Its Links with Guiraud's Law

Hilberg (1990) supposed that finite-order excess entropy of a random human text is proportional to the square root of the text length. Assuming that Hilberg's hypothesis is true, we derive Guiraud's law, which states that the number of word types in a text is greater than proportional to the square root of the text length. Our derivation is based on some mathematical conjecture in coding theory and on several experiments suggesting that words can be defined approximately as the nonterminals of the shortest context-free grammar for the text. Such operational definition of words can be applied even to texts deprived of spaces, which do not allow for Mandelbrot's ``intermittent silence'' explanation of Zipf's and Guiraud's laws. In contrast to Mandelbrot's, our model assumes some probabilistic long-memory effects in human narration and might be capable of explaining Menzerath's law.Comment: To appear in Journal of Quantitative Linguistic

Three-body Faddeev Calculation for 11Li with Separable Potentials

The halo nucleus $^{11}$Li is treated as a three-body system consisting of an inert core of $^{9}$Li plus two valence neutrons. The Faddeev equations are solved using separable potentials to describe the two-body interactions, corresponding in the n-$^{9}$Li subsystem to a p$_{1/2}$ resonance plus a virtual s-wave state. The experimental $^{11}$Li energy is taken as input and the $^{9}$Li transverse momentum distribution in $^{11}$Li is studied.Comment: 6 pages, RevTeX, 1 figur

Histologic Heterogeneity of Extirpated Renal Cell Carcinoma Specimens: Implications for Renal Mass Biopsy

Pathologic characteristics of extirpated renal cell carcinoma (RCC) specimens <7 cm were reviewed to get better information on technical nuances of renal mass biopsy (RMB). Specimens were stratified according to tumor stage, nuclear grade, size, histology, presence of lymphovascular invasion (LVI), necrosis, and sarcomatoid features. When considering pT1 (0–7 cm) tumors, pT1b (4–7 cm) RCC masses were more likely to have necrosis (43% vs 16%, P < 0.001), LVI (6% vs 2%, P = 0.024), high-grade nuclear elements (29% vs 17%, P < 0.001), and sarcomatoid features (2% vs 0%, P = 0.006) compared with pT1a (0–4 cm) tumors. Additionally, pT3a tumors were more highly associated with necrosis (P = 0.005), LVI, sarcomatoid features, and high-grade disease (P for all < 0.001) when compared to pT1 masses. For masses ≤ 4 cm, pT3a cancers were more likely to demonstrate necrosis (38% vs 16%, P < 0.001), LVI (22% vs 2%, P < 0.001), high-grade nuclear elements (45% vs 17%, P < 0.001), and sarcomatoid features (12% vs 0%, P < 0.001) compared to pT1a tumors. Similarly, for masses 4–7 cm, pathologic T3a tumors were significantly more likely to have sarcomatoid features (12% vs 2%, P = 0.006) and LVI (22% vs 6%, P = 0.003) compared to pT1b tumors. In summary, pT3a tumors and those RCC masses >4 cm exhibit considerable histologic heterogeneity and may harbor elements that are not easily appreciated with limited renal sampling. Therefore, if RMB is considered for renal masses greater than 4 cm or those that abut sinus fat, a multi-quadrant biopsy approach is necessary to ensure adequate sampling and characterization of the mass