Miracle-dz/UniFAR-FTUs huggingface dataset:
Scalable hierarchy extraction of repeating structures to enhance full chip mask synthesis

For the past few decades, PPA (performance, power, and area) demand of computation infrastructure has been driving exponential increase of chip density. In recent years, the challenges of printability and process window for advanced manufacturing node continuously motivated innovations in reticle enhancement techniques, notably the adoption of inverse lithography technology (ILT) and curvilinear mask. We have observed a few challenges: 1) ILT provides unmatched quality of results but does incur additional computation time to manage; 2) for curvilinear mask, though the benefits are evident, the associated data volume is very large; and 3) mask consistency remains a critical component for design manufacturability. To utilize the advanced RET techniques to their full potential, it is crucial to identify the repeating structures in design layout and reuse the correction result, getting three benefits at the same time: reducing mask preparation runtime, reducing mask data volume, and improving mask consistency. Conventional layout repetition analysis is based on native design hierarchy. However, in many cases, the input layout for mask synthesis flows is either completely stripped of hierarchy or contains sub-optimal hierarchy. Some layout hierarchy can be detected and reconstructed using manual methods such as using user generated pattern library of highly repeating structures in conjunction with pattern matching technology. However, the preparation of such libraries is a formidable effort, and a significant number of repetitions in designs will be overlooked by this approach. In this paper, we investigate the automatic detection of repeating geometry structures and formed a hierarchy that is optimized for mask synthesis. The detection supports any process layer and both Manhattan and all-angle designs. The engine detects repeating regions of arbitrary shape. The detected repeating structures can also be applied within the chip or across chips to accelerate correction to further improve mask consistency. By scaling well to hundreds of processors, the distributed hierarchy extraction is very efficient for a full chip layout. For highly repetitive layouts, mask synthesis runtime reduction of more than an order of magnitude has been observed by performing this hierarchy extraction.
Eigenvalues and Eigenfunctions of a Stadium-Shaped Quantum Dot Subjected to a Perpendicular Magnetic Field

The eigenvalues and eigenfunctions of the stadium-shaped quantum dot subjected to a constant magnetic field in the perpendicular direction are computed by a simple and efficient method. With the magnetic field increasing, the nearest-neighour-energy-level-spacing distribution of the stadium-shaped quantum dot is found to transform gradually from the Wigner distribution to the Poisson distribution. The transition of the nearest-neighour-energy-level-spacing distribution indicates that system changes from quantum chaotic to regular. The variation of the spatial charge distribution indicates that the system varies from bulk Landau state to the edge state that mainly affects the transport properties of the stadium-shaped quantum dot. The change of the two dimensional charge distribution near the anticrossing point is also discussed.
Lung Cancer Metastasis to the Breast: Consideration of an unusual Presentation

Background: The EML4-ALK fusion oncogene is found in 2 to 7% of all non-small cell lung cancers, most of which are adenocarcinomas. ALK positive lung malignancies are rare; even more rare are primary ALK positive lung malignancies that metastasize to the breast.
A Wavelet-Galerkin Scheme for Nonlinear Elliptic Partial Differential Equations

We are concerned with the construction and numerical implementation of a wavelet based Galerkin scheme for solving non-linear elliptic partial differential equations. We proceed as follows: we choose a nested sequence of finite dimensional approximation spaces building a bi-orthogonal multi-resolution analysis (MRA). Applying the Galerkin discretization results in a finite dimensional non-linear system. In order to treat the non-linear term somehow reasonable we construct a knot oriented quadrature rule based on interpolating wavelets. Finally, we apply Newton’s method to approximate the solution in the given ansatz space. Choosing iteratively finer resolution levels we obtain approximations of the solution with high efficiency. Starting from a general theory we can show in particular the convergence of the constructed Wavelet-Galerkin-Newton scheme. Moreover, to keep the resulting system stable, we apply a wavelet preconditioner. In order to show the applicability of our method a series of numerical examples for different bi-orthogonal systems is presented.
Bayesian Methods for Data-Dependent Priors

The use of data-dependent priors is strangely ubiquitous in Bayesian statistical modeling given the alarm it raises within some cadres. Indeed, the researcher who employs a data-dependent prior faces the inescapable truth that he or she has used the data twice: the first time in establishing prior belief, and the second in updating the prior with the likelihood to obtain the posterior distribution. In this dissertation, we introduce the Adjusted Data-Dependent Bayesian Paradigm as a principled approach to using data-dependent priors in weak accordance with Bayes’ theorem. Suppose that a researcher peeks at the data through some summary statistic prior to applying the Bayesian update. This novel method systematically chooses the posterior distribution that captures the information regarding model parameters that is contained in the data above and beyond the information contained in the observed statistic. In special situations the adjusted approach is formally equivalent to other Bayesian methods, but these cases are necessarily rare. The adjusted procedure imposes a null update when the observed statistic is sufficient, choosing the posterior distribution that is equal to the prior. Conversely, observing a non-sufficient statistic will invite a non-trivial update. Of particular interest is how analyses under the adjusted and naive (unadjusted) procedures compare. Implementation strategies are described for imposing the adjustment in low and high dimensional settings. Posterior simulation is emphasized ii using Markov Chain Monte Carlo (MCMC) techniques modified to accommodate the adjusted paradigm. Black box strategies (e.g. preprocessing data) used to fit Dirichlet Process (DP) mixture models are cast as data-dependent and we demonstrate how to apply the adjustment in these settings. Additionally, we compare the predictive power of the naive and adjusted techniques in analyzing the classic galaxies data set popularized in Roeder (1990).
Half-linear regularization for nonconvex image restoration models

Image restoration is the problem of recovering an original image from an observation of it in order to extract the most meaningful information. In this paper, we study this problem from a variational point of view through the minimization of energies composed of a quadratic data-fidelity term and a nonsmooth nonconvex regularization term. In the discrete setting, existence of minimizer is proved for arbitrary linear operators. For this kind of problems, fully segmented solutions can be found by minimizing objective nonconvex functionals. We propose a dual formulation of the model by introducing an auxiliary variable with a double function. On one hand, it marks the edges and it ensures their preservation from smoothing. On the other hand, it makes the criterion half-linear in the sense that the dual energy depends linearly on the gradient of the image to be recovered. This leads to design an efficient optimization algorithm with wide applicability to several image restoration tasks such as denoising and deconvolution. Finally, we present experimental results and we compare them with TV-based image restoration algorithms.
Integrative Analysis of Metabolomic and Transcriptomic Data Reveals the Mechanism of Color Formation in Corms of Pinellia ternata

Pinellia ternata (Thunb.) Breit. (P. ternata) is a very important plant that is commonly used in traditional Chinese medicine. Its corms can be used as medicine and function to alleviate cough, headache, and phlegm. The epidermis of P. ternata corms is often light yellow to yellow in color; however, within the range of P. ternata found in JingZhou City in Hubei Province, China, there is a form of P. ternata in which the epidermis of the corm is red. We found that the total flavonoid content of red P. ternata corms is significantly higher than that of yellow P. ternata corms. The objective of this study was to understand the molecular mechanisms behind the difference in epidermal color between the two forms of P. ternata. The results showed that a high content of anthocyanidin was responsible for the red epidermal color in P. ternata, and 15 metabolites, including cyanidin-3-O-rutinoside-5-O-glucoside, cyanidin-3-O-glucoside, and cyanidin-3-O-rutinoside, were screened as potential color markers in P. ternata through metabolomic analysis. Based on an analysis of the transcriptome, seven genes, including PtCHS1, PtCHS2, PtCHI1, PtDFR5, PtANS, PtUPD-GT2, and PtUPD-GT3, were found to have important effects on the biosynthesis of anthocyanins in the P. ternata corm epidermis. Furthermore, two transcription factors (TFs), bHLH1 and bHLH2, may have regulatory functions in the biosynthesis of anthocyanins in red P. ternata corms. Using an integrative analysis of the metabolomic and transcriptomic data, we identified five genes, PtCHI, PtDFR2, PtUPD-GT1, PtUPD-GT2, and PtUPD-GT3, that may play important roles in the presence of the red epidermis color in P. ternata corms.
Evaluation of the Analgesic Efficacy of Undiluted Intraperitoneal and Incisional Ropivacaine for Postoperative Analgesia in Dogs after Major Abdominal Surgery

Simple Summary Pain in animals is an important problem as a lack of verbal communication might underestimate their perception and thus lead to undertreatment. Abdominal surgery is frequently performed in dogs, be it elective or for curative reasons. Recommendations to administer a local anaesthetic agent (i.e., a drug that inhibits pain at the site where it is administered) into the abdomen are existing without knowing how good they really work to prevent pain after surgery. In this study, pain, sedation level, the heart rate and opioid requirements were assessed in dogs that underwent abdominal surgery for an underlying disease. Half of the dogs received the investigated drug ropivacaine, while the other half received saline. Pain and sedation level were assessed using scientifically established scores. Rescue analgesia was provided if necessary. Sedation, pain on one score, and sensitivity to pressure next to the surgical wound were not different between both groups. Another pain score achieved slightly higher scores in dogs treated with ropivacaine, and the heart rate was lower in this group. These findings lead to the conclusion that the dosage and concentration used in this study should not be investigated further and cannot be promoted for clinical use. Abstract Recommendations for intraperitoneal (IP) and incisional (INC) administration of local anaesthetics after visceral surgery exist, but evidence is scarce. This prospective, randomized, blinded, controlled, clinical trial compared postoperative pain in dogs undergoing major abdominal surgery. Sixteen client-owned dogs were anaesthetized with a standardized balanced protocol including opioids and received either 2 mg/kg ropivacaine IP (0.27 mL/kg) and a 1 mg/kg INC splash (0.13 mL/kg) or equal volumes of saline. Influence of the treatment on heart rate (HR) and postoperative pain was assessed using the Short Form of the Glasgow Composite Pain Scale (GCPS-SF), a dynamic interactive visual analogue scale (DIVAS) and mechanical nociceptive threshold testing (MNT). Data was tested with mixed ordinal regression and log linear mixed models for 0.5, 1, 2, 3, 4, 6, 8, 10 and 12 h after extubation. Rescue analgesia was given to 3/8 dogs after ropivacaine and 0/8 dogs after saline. GCPS-SF and MNT were not different between groups. DIVAS was slightly higher after ropivacaine (odds increased by 5.44 (confidence interval (CI) 1.17–9.96, p = 0.012)), and HR after ropivacaine was 0.76 * that after saline (CI 0.61–0.96, p = 0.02) with no effect of time (p = 0.1). Undiluted ropivacaine IP and INC was not beneficial for postoperative analgesia.
Laboratory measurements of sedimentation velocity of columnar ice crystals

The terminal velocity of cloud particles may be particularly important to climate studies, because they may have a non‐negligible effect on the radiation budget of the planet, and on the lifetime of clouds. In the present study, the terminal velocity of individual columnar ice crystals was measured under controlled laboratory conditions. The size and fall orientation were determined for ice crystals with maximum dimensions less than 160 µm. The results, which are in agreement with the fall velocity presented in previous studies, show a random orientation of the columnar ice crystals during free fall with a fall velocity which is best represented by their capacitance. A linear relationship between fall velocity and ice crystal capacitance is presented that could be used in cloud modelling. Although the mass of ice crystals was not measured, an estimation of this parameter was made and an empirical Best–Reynolds power‐law relationship was found.
A Nonlinear Image Enhancement Algorithm Based on Single Scale Retinex

A nonlinear image enhancement algorithm based on single scale retinex was proposed.Unlike classical retinex methods estimate the illumination image in a complex way,the proposed algorithm estimates the illumination image approximately,and then compensates the approximate estimation in a nonlinear way.Compared with classical retinex methods,the experimental results show that the proposed method can offer better performance not only in visual enhancement but also in fast processing.
High-energy x-ray grating-based phase-contrast radiography of human anatomy

X-ray grating-based phase-contrast Talbot-Lau interferometry is a promising imaging technology that has the potential to raise soft tissue contrast in comparison to conventional attenuation-based imaging. Additionally, it is sensitive to attenuation, refraction and scattering of the radiation and thus provides complementary and otherwise inaccessible information due to the dark-field image, which shows the sub-pixel size granularity of the measured object. Until recent progress the method has been mainly limited to photon energies below 40 keV. Scaling the method to photon energies that are sufficient to pass large and spacious objects represents a challenging task. This is caused by increasing demands regarding the fabrication process of the gratings and the broad spectra that come along with the use of polychromatic X-ray sources operated at high acceleration voltages. We designed a setup that is capable to reach high visibilities in the range from 50 to 120 kV. Therefore, spacious and dense parts of the human body with high attenuation can be measured, such as a human knee. The authors will show investigations on the resulting attenuation, differential phase-contrast and dark-field images. The images experimentally show that X-ray grating-based phase-contrast radiography is feasible with highly absorbing parts of the human body containing massive bones.
Adiabaticity Engineered Silicon Polarization Independent 3-dB Coupler for the O-Band

We demonstrate a compact and broadband polarization independent 3-dB coupler for the O-band on silicon-on-insulator platform. Using the multi-parameter adiabaticity engineering protocol, unwanted coupling between eigenmodes in mode evolution couplers are redistributed for dual polarization modes and multiple wavelengths, resulting in a large operating bandwidth for both TE and TM polarizations. The fabricated device has a bandwidth of 70 nm with a compact mode evolution region of 27 μm.
A computational method for the singularly perturbed delay pseudo-parabolic differential equations on adaptive mesh

This paper aims to establish the finite difference scheme on Bakhvalov-type mesh for the singularly perturbed pseudo-parabolic problems with time-delay. Using the energy estimates, the bounds of the solution are investigated. An error analysis is derived in the discrete energy norm and the almost second order convergence is obtained. The reliability of the suggested method is displayed by means of a numerical example.
Anti-N-methyl-D-aspartate receptor encephalitis in pregnancy associated with teratoma

Abstract A 36-year-old pregnant woman with a prior history of depression and recent gunshot wounds presented with sudden deterioration in her mental status. Clinical examination revealed psychosis, hallucinations, and lack of orientation, with an otherwise normal neurological and cardiorespiratory examination. Computed tomographic scan of her head was normal, and she was diagnosed with acute psychosis and excited delirium. She did not respond to supraphysiologic dosages of antipsychotic therapy and needed physical restraints for combativeness and agitation. Her cerebrospinal fluid analysis was negative for an infectious etiology, but was positive for anti-N-methyl-D-aspartate receptor encephalitis antibodies. Abdominal imaging revealed a right-sided ovarian cyst. Subsequently she underwent right-sided oophorectomy. Postoperatively the patient continued to have intermittent episodes of agitation requiring antipsychotic medications. Later, she was safely transitioned to home care with family support.
A novel hierarchical aggregation algorithm for optimal repartitioning of statistical regions

Abstract Data regionalisation allows spatial inference over a population. The statistical regions must be updated to account for population changes, but this update process is more restrictive and iterative than ab initio regionalisation. This creates a need for an algorithmic solution that minimises human-in-the-loop involvement in population-driven regionalisation. The new method must address the basic regionalisation criteria – contiguity, compactness, homogeneity, equinumeriosity, and temporal consistency. We present a novel validation metric to assess the quality of partition based on these criteria. We have developed a novel hybrid aggregation algorithm (HeLP), combining elements of hierarchical and graph-theoretic approaches, for the primary purpose of repartitioning. This algorithm operates in average computational time complexity. HeLP was tested on simulated data and the Australian Statistical Geography Standard. The method can emulate the human operator successfully, providing statistically significant results in repartitioning parcel-based systems, such as the Cadastre.
Significant Differences and Experimental Designs Do Not Necessarily Imply Clinical Relevance: Effect Sizes and Causality Claims in Antidepressant Treatments

Clinical trials are the backbone of medical scientific research. However, this experimental strategy has some drawbacks. We focused on two issues: (a) The internal validity ensured by clinical trial procedures does not necessarily allow for generalization of efficacy results to causal claims about effectiveness in the population. (b) Statistical significance does not imply clinical or practical significance; p-values should be supplemented with effect size (ES) estimators and an interpretation of the magnitude of the effects found. We conducted a systematic review (from 2000 to 2020) on Scopus, PubMed, and four ProQuest databases, including PsycINFO. We searched for experimental studies with significant effects of pharmacological treatments on depressive symptoms, measured with a specific scale for depression. We assessed the claims of effectiveness, and reporting and interpreting of effect sizes in a small, unbiased sample of clinical trials (n = 10). Only 30% of the studies acknowledged that efficacy does not necessarily translate to effectiveness. Only 20% reported ES indices, and only 40% interpreted the magnitude of their findings. We encourage reflection on the applicability of results derived from clinical trials about the efficacy of antidepressant treatments, which often influence daily clinical decision-making. Comparing experimental results of antidepressants with supplementary observational studies can provide clinicians with greater flexibility in prescribing medication based on patient characteristics. Furthermore, the ES of a treatment should be considered, as treatments with a small effect may be worthwhile in certain circumstances, while treatments with a large effect may be justified despite additional costs or complications. Therefore, researchers are encouraged to report and interpret ES and explicitly discuss the suitability of their sample for the clinical population to which the antidepressant treatment will be applied.
Zinc Oxide Nanostructures for Optical and Optoelectronic Applications

Wurtzite ZnO nano-structures with high crystalline quality have been grown by the electro-deposition of zinc on copper substrate followed by its hydrothermal oxidation in NaCl solution. Ni-doped ZnO nano-structures with up to 17 at% Ni have been formed for the first time without nickel-based impurity phase. The wire diameter decreases with Ni content, up to about 20-50 nm. Optical studies illustrate strong ultraviolet emission in the photoluminescence and cathode-luminescence spectra of ZnO nanostructures without, previously ever-existent, emission in the visible region, depending on the choice of NaCl solution (instead of pure water) and / or nickel doping. Annealing at 500 oC in air causes emission in green and orange region, as accompanied by pronounced decrease in the intensity of UV emission. Annealing in argon results in intense green emission. As-synthesized doped and un-doped ZnO nanostructures obtained in this work are ideal choice for UV- based optical and optoelectronic devices. Gold nanoparticles have been attached to ZnO nano-structures by etching in potassium iodide followed by immersion in HAuCl4 solution. The defect emission (in the visible region) intensified by etching almost completely vanishes after gold deposition. Photocatalytic activity of the ZnO nanostructures has also enhanced by attaching the gold nanoparticles. Wurtzite ZnO thin films with high crystalline quality and almost perfect growth along c-axis have been formed by sputtering and PLD. These films, although composed of nano-crystalline columns present features of epitaxial growth on sapphire substrate. The ZnO film formed by PLD in air does not exhibit green and orange emission. Due to non-stoichiometric nature of ZnO film sputter-deposited in argon, green emission is observed. The charge carrier density is almost comparable in these films (about 2 x 1018 cm-3), while the electron mobility in the former is significantly higher (about 35 cmV-1s-1) than the latter, owing to high crystalline quality as assessed by omega and phi scans in XRD analysis). ZnO-Ge multilayer thin film structures have also been deposited by evaporation. Quantum confinement has been indicated by blue shift in the optical band gap of germanium.