Miracle-dz/UniFAR-FTUs huggingface dataset:
Extending optical lithography with immersion

As the semiconductor industry looks to the future to extend manufacturing beyond 100nm, ASML have developed a new implementation of an old optical method for lithography. Immersion lithography can support the aggressive industry roadmap and offers the ability to manufacture semiconductor devices at a low k1. In order to make immersion lithography a production worthy technology a number of challenges have to be overcome. This paper provides the results of our feasibility study on immersion lithography. We show through experimental and theoretical evaluation that we can overcome the critical concerns related to immersion lithography. We show results from liquid containment tests focussing on its effects on the scan speed of the system and the formation of micro-bubbles in the fluid. We present fluid-to-resist compatibility tests on resolution, using a custom-built interference setup. Ultimate resolution is tested using a home build 2 beam interference setup. ASML built a prototype full field scanning exposure system based on the dual stage TWINSCAN platform. It features a full field 0.75 NA refractive projection lens. We present experimental data on imaging and overlay.
Automated Finite-Element-Based Validation of Structures Designed by the Strut-and-Tie Method

Several codes of practice now support the use of the strut-and-tie method (STM) for the design of complex regions in structural concrete. In this method, a load-resisting truss is idealized and designed to carry the applied forces through these regions to their supports. The method assumes that the load can be carried in the manner envisioned by the designer and that the nominal design strength is at least equal to the calculated capacity of the idealized plastic truss. These assumptions are not always valid, particularly for nonductile and complex structures, as revealed by experiments in which some of STM designed structures have exhibited poor performance at service load levels and/or not been able to support their calculated nominal design strength. Thus, there is clearly a need for a convenient and reliable means of assessing the likely performance of complex regions designed using the STM. This paper presents an integrated STM design and computational framework that was developed to overcome the barriers to efficient design by the STM and effective design validation by nonlinear finite-element analysis.
Tracking the movement of discrete gating charges in a voltage-gated potassium 1 channel 2 3

12 Positively-charged amino acids respond to membrane potential changes to drive 13 voltage sensor movement in voltage-gated ion channels, but determining the 14 displacements of voltage sensor gating charges has proven difficult. We optically 15 tracked the movement of the two most extracellular charged residues (R1, R2) in the 16 Shaker potassium channel voltage sensor using a fluorescent positively-charged 17 bimane derivative (qBBr) that is strongly quenched by tryptophan. By individually 18 mutating residues to tryptophan within the putative pathway of gating charges, we 19 observed that the charge motion during activation is a rotation and a tilted translation 20 that differs between R1 and R2. Tryptophan-induced quenching of qBBr also indicates 21 that a crucial residue of the hydrophobic plug is linked to the Cole-Moore shift through 22 its interaction with R1. Finally, we show that this approach extends to additional voltage23
Halftoning by rotating non-Bayer dispersed dither arrays

We propose a new operator for creating rotated dither threshold arrays. This new discrete one- to-one rotation operator is briefly explained. We analyze its application to different dispersed- dot dither arrays such as hexagonal dispersed dither arrays and 3X3 matrix-based Bayer- expanded dither arrays and compare the results with the ones obtained by rotating standard Bayer dither arrays. We show that the rotation operator introduced new lower-frequency components that, for example in the case of rotated dispersed-dot Bayer dither, produces a slight clustering effect, improving the tone reproduction behavior of the halftone patterns. In other cases, such as hexagonal dispersed dither, these new lower frequency components are responsible for strong interferences in the rotated halftone array. When applied to 3x3 matrix- based Bayer-expanded dither arrays, the rotation operator induces sequences of short horizontal and vertical patterns that have very good tone reproduction behavior in the dark tones. Besides their used in black and white printing, rotated dispersed-dot dither halftoning techniques have also been successfully applied to in-phase color reproduction on inkjet printers.
Supplementary for SwinIR: Image Restoration Using Swin Transformer

Training. For classical and lightweight image SR, following [29, 18, 17], we train SwinIR on 800 training images of DIV2K [1]. Some compared methods (e.g., [7], [23]) further use 2560 images from Flickr2K [20] for training, so we also train SwinIR on larger datasets to investigate whether SwinIR can further improve performance. For fair comparison, we use 48 × 48 and 64 × 64 LQ image patches respectively in above two cases following the common settings. The HQ-LQ image pairs are obtained by the MATLAB bicubic kernel. The total training iterations and mini-batch size are set to 500K and 32, respectively. The learning rate is initialized as 2e-4 and reduced by half at [250K,400K,450K,475K]. Unlike other Transformer-based models that often uses AdamW [13] optimizer with cosine learning rate decay strategy, we find that using Adam [10] optimizer with β1 = 0.9 and β2 = 0.99 leads to better performance. For real-world image SR, we use the same image degradation model as BSRGAN [28] and train it on a combination of DIV2K, Flickr2K and OST [22]. The model is trained for 1,000K iterations for the PSNR training stage. The learning rate is halved at [500K,800K,900K,950K]. For the GAN training stage, we train it for 600K iterations and the learning rate is halved at [400K,500K,550K,575K]. Weighting parameters between L1 pixel loss, perceptual loss and GAN loss are 1, 1 and 0.1, respectively. Note that we use the same USM strategy, perceptual loss and GAN loss as [21]. For denoising and compression artifact reduction, following [30, 27], we use 128 × 128 random crops from the combination of 800 DIV2K images, 2650 Flickr2K images, 400 BSD500 images [2] and 4744 WED images [14]. We obtain noisy images by adding additive white Gaussian noises (AWGN) with noise level σ, and compressed images by the MATLAB JPEG encoder with JPEG level q. The total training iterations and mini-batch size are set to 1600K and 8, respectively. The learning rate is halved at [800K,1200K,1400K,1500K]. Other details are the same as image SR. Evaluation. Following the tradition of image SR, we report PSNR and SSIM [24] on the Y channel of the YCbCr space. For image denoising, we report the PSNR on the RGB channel and Y channel for color and grayscale denoising, respectively. For compression artifact reduction, in addtion to the Y channel PSNR and SSIM, we also report PNSR-B [25] that is specially designed for deblocking quality assessment. Particularly, we pad the image in testing so that the image size is a multiple of window size. We also find that using a sliding window strategy [4] to crop the image into patches can further improve the PSNR by 0.02 ∼ 0.03dB at the cost of longer testing time, so we do not use it for comparison.
DiffImpact: Differentiable Rendering and Identification of Impact Sounds

: Rigid objects make distinctive sounds during manipulation. These sounds are a function of object features, such as shape and material, and of contact forces during manipulation. Being able to infer from sound an object’s acoustic properties, how it is being manipulated, and what events it is participating in could augment and complement what robots can perceive from vision, especially in case of occlusion, low visual resolution, poor lighting, or blurred focus. Annotations on sound data are rare. Therefore, existing inference systems mostly include a sound renderer in the loop, and use analysis-by-synthesis to optimize for object acoustic properties. Optimizing parameters with respect to a non-differentiable renderer is slow and hard to scale to complex scenes. We present DiffImpact, a fully differentiable model for sounds rigid objects make during impacts, based on physical principles of impact forces, rigid object vibration, and other acoustic effects. Its differentiability enables gradient-based, efﬁcient joint inference of acoustic properties of the objects and characteristics and timings of each individual impact. DiffImpact can also be plugged in as the decoder of an autoencoder, and trained end-to-end on real audio data, so that the encoder can learn to solve the inverse problem in a self-supervised way. Experiments demonstrate that our model’s physics-based inductive biases make it more resource efﬁcient and expressive than state-of-the-art pure learning-based alternatives, on both forward rendering of impact sounds and inverse tasks such as acoustic property inference and blind source separation of impact sounds. Code and videos are at https://sites.google. com/view/diffimpact .
Lecture 1 Generative Capacity and Natural Language

An essential property of human language that distinguishes it from other information-carrying systems (e.g., the system of traffic signs) is its creative aspect: it makes “infinite use of finite means” in the sense that it allows infinitely many ways of combining finitely many basic linguistic units to form arbitrarily complex expressions. (This property is shared by some artificial “languages” like programming languages and languages of symbolic logic.) By a grammar we mean a system of rules whereby words—which we assume to be basic linguistic units for the sake of simplicity—may be put together to form sentences. A speaker of a language has a certain grammar internalized in his/her head and uses it to produce and understand sentences of his/her language. What kind of rule systems human grammars are is an empirical issue and a subject matter of linguistics. One way of approaching this question is to study mathematical models of grammar (formal grammars). Different types of formal grammars (or grammar formalisms) have different formal properties, which may render them more or less plausible as models of human grammars. Especially, a certain limitation in the expressive power or generative capacity of a grammar formalism may be seen to conflict with facts about certain constructions in some existing natural language. Such a discovery would then be considered a reason to reject the grammar formalism in question as a model of human grammar. At the same time, the grammar formalism would serve the useful purpose of characterizing a certain property of natural language in mathematically precise terms: “Natural language goes beyond the expressive power of grammar formalism X. ” There is another way in which the study of grammar formalisms may provide
REDUCTION OF THE DATA PROCESSING TIME FOR LOCK-IN SHEAROGRAPHY

This paper presents possible means of reducing the computing time necessary for processing shearographic phase images obtained using a lock-in technique. The main steps to obtaining meaningful information from lock-in shearography data are filtering, unwrapping and Fourier-transformation, which can all be very time-consuming for large amounts of data. Using Matlab’s Parallel Computing Toolbox, we evaluated and compared the speed-up of processing times when using an optimized programming syntax, parallel CPU-computing or parallel GPU-computing. Coding in a time optimized syntax improved the processing time by a factor of about 10 compared with a simple syntax, employing 12 parallel computing threads leads to a time improvement factor of 29 and utilizing a GPU for computing resulted in a 116-fold speed-up. Optimized GPU-computing it thus recommended for processing large amounts of shearography data and can reduce the computation time for the data acquired by one lock-in measurement in a 5 MP resolution from about 10 hours to competitive 5 minutes.
A probabilistic attack simulation language for the IT domain (cid:63)

Cyber-attacks on IT infrastructures can have disastrous consequences for individuals, regions, as well as whole nations. In order to respond to these threats, the cyber security assessment of IT infrastructures can foster a higher degree of safety and resilience against cyber-attacks. Therefore, the use of attack simulations based on system architecture models is proposed. To reduce the eﬀort of creating new attack graphs for each system under assessment, domain-speciﬁc languages (DSLs) can be employed. DSLs codify the common attack logics of the considered domain.
I Never Promised you a Rose Garden: An Analysis of the Rent Dissipation Effect in Technology Licensing Contracts

Drawing on markets for technology literature we propose and empirically test a model to explain the effect of technology licensing on licensor? s market-share. While several empirical studies have discussed the so called dissipation effect related to technology licensing, few empirical applications can be observed in the licensing literature. We argue that licensing core technologies is likely to generate increasing competition in the product market, resulting in rent dissipation for the licensor. In addition, we prove that this relationship is moderated by licensee size and the technological overlap between licensor and licensee. We test our hypotheses using a sample of 163 licensors involved in licensing contracts
DAM: Discrepancy Alignment Metric for Face Recognition

The field of face recognition (FR) has witnessed remarkable progress with the surge of deep learning. The effective loss functions play an important role for FR. In this paper, we observe that a majority of loss functions, including the widespread triplet loss and softmax-based cross-entropy loss, embed inter-class (negative) similarity sn and intra-class (positive) similarity sp into similarity pairs and optimize to reduce (sn − sp) in the training process. However, in the verification process, existing metrics directly take the absolute similarity between two features as the confidence of belonging to the same identity, which inevitably causes a gap between the training and verification process. To bridge the gap, we propose a new metric called Discrepancy Alignment Metric (DAM) for verification, which introduces the Local Inter-class Discrepancy (LID) for each face image to normalize the absolute similarity score. To estimate the LID of each face image in the verification process, we propose two types of LID Estimation (LIDE) methods, which are reference-based and learning-based estimation methods, respectively. The proposed DAM is plug-and-play and can be easily applied to the most existing methods. Extensive experiments on multiple popular face recognition benchmark datasets demonstrate the effectiveness of our proposed method.
Computational Modelling of Flatfoot Deformity

Flatfoot is a deformity that leads to the misalignment of the foot and ankle joints, affecting 25% of the general population. Despite being a common foot deformity, the biomechanics of flatfoot are not fully understood. Choosing the best suited surgical treatment to correct this deformity is a troubling subject among the medical community. This work is presented as a first approach, using finite element method for the evaluation of the biomechanical behaviour of the foot when its anatomy sets up in a valgus foot situation. A foot and ankle finite element model of both a healthy and a flatfoot were developed consisting of bones, cartilages, ligaments, and tendons. A comparison between the von Mises stresses distribution of the healthy and the flatfoot was performed. Overall, the results showed that the flatfoot was subjected to higher stresses than the healthy foot. The cartilages and ligaments of the flatfoot also yield higher stresses than the healthy foot. The clinical use of this type of FE models can be of great importance since they can lead the way for novel diagnostic techniques and novel methods for treatment planning/optimization. In the future, a study of which should be the most suitable osteotomy for flatfoot correction will be performed, using the model developed on this work.
Part 2: Pavement Monitoring, Evaluation, and Data Storage: Statistical Analysis of Automated Versus Manual Pavement Condition Surveys

The Alabama Department of Transportation (ALDOT) has used a vendor to perform automated pavement condition surveys for the Alabama payement network since 1997. In 2002, ALDOT established a quality assurance (QA) program to check the accuracy of the automated pavement condition data. The QA program revealed significant discrepancies between manual and automatically collected data. ALDOT uses a composite pavement condition index called pavement condition rating (PCR) in its pavemen management system. The equation for PCR was developed in 1985 for use with manual pavement condition surveys; however, ALDOT continues to use it with data from automated condition surveys. Since the PCR equation was developed for manual surveys, the discrepancies between the manual and automated data led ALDOT to question the continuity between its manual and automated pavement condition survey programs. A regression analysis was completed to look for any systematic error or general trends in the error between automated and manua.
Optimal design of wide band low loss SAW filters, using slanted interdigital transducers

Slanted finger SAW transducers allow one to design wide band filters with excellent characteristics. One of the most interesting modifications of such a filter is the slanted SPUDT. We present an approach to the analysis of such filters based on consistent use of the Y-matrix instead of the conventional P-matrix. Conditions of optimal matching of such SPUDT are obtained and examples of the use of the method developed for the design of wide band SPUDT are shown.
Calculation of Rail Impedance of Track Circuit Considering Earth Stratification

Rail impedance directly affects the transmission performance of track circuit . Considering the condition of earth stratification, for the difficult to calculate the rail impedance due to the semi-infinite integration interval and the oscillation of the integrand by using the Carson formula, The truncation method is proposed to divide the impedance formula is divided into definite integral and tail integral. The integral is approximated by the spline function, and the tail integral is calculated by using the exponential integral and Euler formula. Based on it, the rail impedance calculation formula of track circuit is obtained. The electromagnetic field model of track circuit with earth stratification is simulated by finite element method, and the correctness of the method is verified. Based on the formula, the influence of current frequency, soil depth and conductivity on rail impedance is studied. The relative error between the calculated results of rail impedance and the simulation results of finite element is within 5%. It can be seen that the formula has high accuracy and correctly reflects the law of rail impedance variation with current frequency, soil depth and resistivity. It provides a reliable reference for the theoretical calculation of rail impedance of track circuit.
Influence of Surface Treatment on Steel Adhesive Joints Strength—Varnish Coats

The purpose of the paper is to determine the impact of surface treatment on the strength of adhesive joints, made from various steel sheets. Two variants of the surface treatment steel adherends were used: without the varnish coat and with the varnish coat, using three polymer-based varnishes (a simple, a hybrid, and a gel). Two types of the adhesives were used to prepare the adhesive joints: a single-component cyanoacrylate adhesive and a two-component epoxy adhesive. A strength test of the adhesive joints (EN DIN 1465 standard), a coating adhesion test (ASTM D3359-B standard), and surface topography, as well as surface roughness, parameters (PN-EN ISO 11562, PN-EN ISO 4287, and PN-EN ISO 25178 standards) were used. Based on the strength tests, it was observed that the adhesive joints, with the hybrid varnish onto the adherend’s surface, achieved markedly lower shear strength. The best results, in terms of the adhesive joint strength, made using the cyanoacrylate adhesive were achieved for the joints where the adherends were coated with a simple varnish, while in the joints made using the epoxy adhesive, the highest shear strength was achieved by the joints of sheets whose surfaces were coated with the gel varnish.
An analysis on deep learning approaches: addressing the challenges in remote sensing image retrieval

ABSTRACT A considerable volume of high-resolution remote sensing (HRRS) data is generated with the intense space explorations happening globally. Remote sensing image retrieval (RSIR) is a fundamental task in the remote sensing domain, providing excellent opportunities for a broad spectrum of applications. Difficulty in describing the heterogeneous remote sensing image (RSI) content and the availability in huge volumes is challenging in many analyses and certainly needs many added processing challenges. Also, the popularity of using deep learning (DL) techniques is also increased in the remote sensing domain. The practice of using DL methods to strengthen the efficiency of RSIR frameworks has a very broad prospect. Thus, HRRS data brings new challenges for deep-learning-based RSIR (DL-RSIR) tasks, especially when the data is experienced as ‘big data. ’ This article systematically reviews many existing works, concentrating on the advancements and current trends related to DL-RSIR. Also, it narrates the challenges incorporated with the RSIR tasks and how to utilize DL techniques and frameworks to address them. Almost all potential factors that could influence the DL-RSIR performance are analysed, and many evaluations are performed with a comparative analysis. The observations and recommendations presented can help researchers to bring new insights into designing DL-RSIR frameworks.
Characterization of the complete mitochondrial genome of Pseudorhaetus sinicus Boileau, 1899 (Coleoptera: Lucanidae)

Abstract Pseudorhaetus sinicus is a stag beetle common to China and Vietnam, but whose distribution is limited within China. Little is known about the molecular biological characteristics of this species, so we characterized its complete mitochondrial genome (GenBank accession number MZ504793.1). The mitogenome consists of a circular DNA molecule of 18,126 bp, with 67.693% AT content. It contains 13 protein-coding genes (PCGs), 22 tRNA genes, and two rRNA genes. The PCGs have typical ATN (Met) start codons and TAN stop codons. Phylogenetic analysis suggests that P. sinicus is closely related to Prosopocoilus confucius. This newly described mitochondrial genome provides a valuable resource for the phylogenetic analysis of Lucanidae beetles.
Effective MOSFET modeling for SPICE circuit simulation

The analytical MOSFET models used in SPICE circuit simulation are the key "communication vehicle" between a circuit designer and the fabrication facility; unfortunately, they are often a source of great misery to the designer. This workshop will examine the SPICE MOSFET models from the perspective of the circuit designer. Consideration of the basics of analytical MOS modeling will be followed by a detailed discussion of the various MOSFET models used in SPICE, along with an examination of other issues such as gate capacitance and statistical simulations. Submicron and analog design aspects will be emphasized throughout.