This work deals with the efficient numerical solution of the time-fractional heat equation discretized on non-uniform temporal meshes. Non-uniform grids are essential to capture the singularities of "typical" solutions of time-fractional problems. We propose an efficient space-time multigrid method based on the waveform relaxation technique, which accounts for the nonlocal character of the fractional differential operator. To maintain an optimal complexity, which can be obtained for the case of uniform grids, we approximate the coefficient matrix corresponding to the temporal discretization by its hierarchical matrix (${cal H}$-matrix) representation. In particular, the proposed method has a computational cost of ${cal O}(k N M log(M))$, where $M$ is the number of time steps, $N$ is the number of spatial grid points, and $k$ is a parameter which controls the accuracy of the ${cal H}$-matrix approximation. The efficiency and the good convergence of the algorithm, which can be theoretically justified by a semi-algebraic mode analysis, are demonstrated through numerical experiments in both one- and two-dimensional spaces.

In ASPIC-style structured argumentation an argument can rebut another argument by attacking its conclusion. Two ways of formalizing rebuttal have been proposed: In restricted rebuttal, the attacked conclusion must have been arrived at with a defeasible rule, whereas in unrestricted rebuttal, it may have been arrived at with a strict rule, as long as at least one of the antecedents of this strict rule was already defeasible. One systematic way of choosing between various possible definitions of a framework for structured argumentation is to study what rationality postulates are satisfied by which definition, for example whether the closure postulate holds, i.e. whether the accepted conclusions are closed under strict rules. While having some benefits, the proposal to use unrestricted rebuttal faces the problem that the closure postulate only holds for the grounded semantics but fails when other argumentation semantics are applied, whereas with restricted rebuttal the closure postulate always holds. In this paper we propose that ASPIC-style argumentation can benefit from keeping track not only of the attack relation between arguments, but also the relation of deductive joint support that holds between a set of arguments and an argument that was constructed from that set using a strict rule. By taking this deductive joint support relation into account while determining the extensions, the closure postulate holds with unrestricted rebuttal under all admissibility-based semantics. We define the semantics of deductive joint support through the flattening method.

In recent years there has been a burgeoning interest in the use of computational methods to distinguish between elicited speech samples produced by patients with dementia, and those from healthy controls. The difference between perplexity estimates from two neural language models (LMs) - one trained on transcripts of speech produced by healthy participants and the other trained on transcripts from patients with dementia - as a single feature for diagnostic classification of unseen transcripts has been shown to produce state-of-the-art performance. However, little is known about why this approach is effective, and on account of the lack of case/control matching in the most widely-used evaluation set of transcripts (DementiaBank), it is unclear if these approaches are truly diagnostic, or are sensitive to other variables. In this paper, we interrogate neural LMs trained on participants with and without dementia using synthetic narratives previously developed to simulate progressive semantic dementia by manipulating lexical frequency. We find that perplexity of neural LMs is strongly and differentially associated with lexical frequency, and that a mixture model resulting from interpolating control and dementia LMs improves upon the current state-of-the-art for models trained on transcript text exclusively.

Domain of mathematical logic in computers is dominated by automated theorem provers (ATP) and interactive theorem provers (ITP). Both of these are hard to access by AI from the human-imitation approach: ATPs often use human-unfriendly logical foundations while ITPs are meant for formalizing existing proofs rather than problem solving. We aim to create a simple human-friendly logical system for mathematical problem solving. We picked the case study of Euclidean geometry as it can be easily visualized, has simple logic, and yet potentially offers many high-school problems of various difficulty levels. To make the environment user friendly, we abandoned strict logic required by ITPs, allowing to infer topological facts from pictures. We present our system for Euclidean geometry, together with a graphical application GeoLogic, similar to GeoGebra, which allows users to interactively study and prove properties about the geometrical setup.

Participatory Design's vision of democratic participation assumes participants' feelings of agency in envisioning a collective future. But this assumption may be leaky when dealing with vulnerable populations. We reflect on the results of a series of activities aimed at supporting agentic-future-envisionment with a group of sex-trafficking survivors in Nepal. We observed a growing sense among the survivors that they could play a role in bringing about change in their families. They also became aware of how they could interact with available institutional resources. Reflecting on the observations, we argue that building participant agency on the small and personal interactions is necessary before demanding larger Political participation. In particular, a value of PD, especially for vulnerable populations, can lie in the process itself if it helps participants position themselves as actors in the larger world.

Sentence level quality estimation (QE) for machine translation (MT) attempts to predict the translation edit rate (TER) cost of post-editing work required to correct MT output. We describe our view on sentence-level QE as dictated by several practical setups encountered in the industry. We find consumers of MT output---whether human or algorithmic ones---to be primarily interested in a binary quality metric: is the translated sentence adequate as-is or does it need post-editing? Motivated by this we propose a quality classification (QC) view on sentence-level QE whereby we focus on maximizing recall at precision above a given threshold. We demonstrate that, while classical QE regression models fare poorly on this task, they can be re-purposed by replacing the output regression layer with a binary classification one, achieving 50-60\% recall at 90\% precision. For a high-quality MT system producing 75-80\% correct translations, this promises a significant reduction in post-editing work indeed.

Image-based tracking of medical instruments is an integral part of many surgical data science applications. Previous research has addressed the tasks of detecting, segmenting and tracking medical instruments based on laparoscopic video data. However, the methods proposed still tend to fail when applied to challenging images and do not generalize well to data they have not been trained on. This paper introduces the Heidelberg Colorectal (HeiCo) data set - the first publicly available data set enabling comprehensive benchmarking of medical instrument detection and segmentation algorithms with a specific emphasis on robustness and generalization capabilities of the methods. Our data set comprises 30 laparoscopic videos and corresponding sensor data from medical devices in the operating room for three different types of laparoscopic surgery. Annotations include surgical phase labels for all frames in the videos as well as instance-wise segmentation masks for surgical instruments in more than 10,000 individual frames. The data has successfully been used to organize international competitions in the scope of the Endoscopic Vision Challenges (EndoVis) 2017 and 2019.

Despite recent progress on computer vision and natural language processing, developing video understanding intelligence is still hard to achieve due to the intrinsic difficulty of story in video. Moreover, there is not a theoretical metric for evaluating the degree of video understanding. In this paper, we propose a novel video question answering (Video QA) task, DramaQA, for a comprehensive understanding of the video story. The DramaQA focused on two perspectives: 1) hierarchical QAs as an evaluation metric based on the cognitive developmental stages of human intelligence. 2) character-centered video annotations to model local coherence of the story. Our dataset is built upon the TV drama "Another Miss Oh" and it contains 16,191 QA pairs from 23,928 various length video clips, with each QA pair belonging to one of four difficulty levels. We provide 217,308 annotated images with rich character-centered annotations, including visual bounding boxes, behaviors, and emotions of main characters, and coreference resolved scripts. Additionally, we provide analyses of the dataset as well as Dual Matching Multistream model which effectively learns character-centered representations of video to answer questions about the video. We are planning to release our dataset and model publicly for research purposes and expect that our work will provide a new perspective on video story understanding research.

Bayesian predictive coding is a putative neuromorphic method for acquiring higher-level neural representations to account for sensory input. Although originating in the neuroscience community, there are also efforts in the machine learning community to study these models. This paper reviews some of the more well known models. Our review analyzes module connectivity and patterns of information transfer, seeking to find general principles used across the models. We also survey some recent attempts to cast these models within a deep learning framework. A defining feature of Bayesian predictive coding is that it uses top-down, reconstructive mechanisms to predict incoming sensory inputs or their lower-level representations. Discrepancies between the predicted and the actual inputs, known as prediction errors, then give rise to future learning that refines and improves the predictive accuracy of learned higher-level representations. Predictive coding models intended to describe computations in the neocortex emerged prior to the development of deep learning and used a communication structure between modules that we name the Rao-Ballard protocol. This protocol was derived from a Bayesian generative model with some rather strong statistical assumptions. The RB protocol provides a rubric to assess the fidelity of deep learning models that claim to implement predictive coding.

The temporal segmentation of events is an essential task and a precursor for the automatic recognition of human actions in the video. Several attempts have been made to capture frame-level salient aspects through attention but they lack the capacity to effectively map the temporal relationships in between the frames as they only capture a limited span of temporal dependencies. To this end we propose a complete end-to-end supervised learning approach that can better learn relationships between actions over time, thus improving the overall segmentation performance. The proposed hierarchical recurrent attention framework analyses the input video at multiple temporal scales, to form embeddings at frame level and segment level, and perform fine-grained action segmentation. This generates a simple, lightweight, yet extremely effective architecture for segmenting continuous video streams and has multiple application domains. We evaluate our system on multiple challenging public benchmark datasets, including MERL Shopping, 50 salads, and Georgia Tech Egocentric datasets, and achieves state-of-the-art performance. The evaluated datasets encompass numerous video capture settings which are inclusive of static overhead camera views and dynamic, ego-centric head-mounted camera views, demonstrating the direct applicability of the proposed framework in a variety of settings.

We provide a dynamical perspective on the classical problem of 3D point cloud registration with correspondences. A point cloud is considered as a rigid body consisting of particles. The problem of registering two point clouds is formulated as a dynamical system, where the dynamic model point cloud translates and rotates in a viscous environment towards the static scene point cloud, under forces and torques induced by virtual springs placed between each pair of corresponding points. We first show that the potential energy of the system recovers the objective function of the maximum likelihood estimation. We then adopt Lyapunov analysis, particularly the invariant set theorem, to analyze the rigid body dynamics and show that the system globally asymptotically tends towards the set of equilibrium points, where the globally optimal registration solution lies in. We conjecture that, besides the globally optimal equilibrium point, the system has either three or infinite "spurious" equilibrium points, and these spurious equilibria are all locally unstable. The case of three spurious equilibria corresponds to generic shape of the point cloud, while the case of infinite spurious equilibria happens when the point cloud exhibits symmetry. Therefore, simulating the dynamics with random perturbations guarantees to obtain the globally optimal registration solution. Numerical experiments support our analysis and conjecture.

Randomized Numerical Linear Algebra (RandNLA) uses randomness to develop improved algorithms for matrix problems that arise in scientific computing, data science, machine learning, etc. Determinantal Point Processes (DPPs), a seemingly unrelated topic in pure and applied mathematics, is a class of stochastic point processes with probability distribution characterized by sub-determinants of a kernel matrix. Recent work has uncovered deep and fruitful connections between DPPs and RandNLA which lead to new guarantees and improved algorithms that are of interest to both areas. We provide an overview of this exciting new line of research, including brief introductions to RandNLA and DPPs, as well as applications of DPPs to classical linear algebra tasks such as least squares regression, low-rank approximation and the Nystr"om method. For example, random sampling with a DPP leads to new kinds of unbiased estimators for least squares, enabling more refined statistical and inferential understanding of these algorithms; a DPP is, in some sense, an optimal randomized algorithm for the Nystr"om method; and a RandNLA technique called leverage score sampling can be derived as the marginal distribution of a DPP. We also discuss recent algorithmic developments, illustrating that, while not quite as efficient as standard RandNLA techniques, DPP-based algorithms are only moderately more expensive.

Neural networks have opened up many new opportunities to utilize remotely sensed images in meteorology. Common applications include image classification, e.g., to determine whether an image contains a tropical cyclone, and image translation, e.g., to emulate radar imagery for satellites that only have passive channels. However, there are yet many open questions regarding the use of neural networks in meteorology, such as best practices for evaluation, tuning and interpretation. This article highlights several strategies and practical considerations for neural network development that have not yet received much attention in the meteorological community, such as the concept of effective receptive fields, underutilized meteorological performance measures, and methods for NN interpretation, such as synthetic experiments and layer-wise relevance propagation. We also consider the process of neural network interpretation as a whole, recognizing it as an iterative scientist-driven discovery process, and breaking it down into individual steps that researchers can take. Finally, while most work on neural network interpretation in meteorology has so far focused on networks for image classification tasks, we expand the focus to also include networks for image translation.

We study how to infer new choices from previous choices in a conservative manner. To make such inferences, we use the theory of choice functions: a unifying mathematical framework for conservative decision making that allows one to impose axioms directly on the represented decisions. We here adopt the coherence axioms of De Bock and De Cooman (2019). We show how to naturally extend any given choice assessment to such a coherent choice function, whenever possible, and use this natural extension to make new choices. We present a practical algorithm to compute this natural extension and provide several methods that can be used to improve its scalability.

We develop a categorical compositional distributional semantics for Lambek Calculus with a Relevant Modality !L*, which has a limited edition of the contraction and permutation rules. The categorical part of the semantics is a monoidal biclosed category with a coalgebra modality, very similar to the structure of a Differential Category. We instantiate this category to finite dimensional vector spaces and linear maps via "quantisation" functors and work with three concrete interpretations of the coalgebra modality. We apply the model to construct categorical and concrete semantic interpretations for the motivating example of !L*: the derivation of a phrase with a parasitic gap. The effectiveness of the concrete interpretations are evaluated via a disambiguation task, on an extension of a sentence disambiguation dataset to parasitic gap phrase one, using BERT, Word2Vec, and FastText vectors and Relational tensors.

Motivated by the current demand of clinical governance, surgical simulation is now a well-established modality for basic skills training and assessment. The practical deployment of the technique is a multi-disciplinary venture encompassing areas in engineering, medicine and psychology. This paper provides an overview of the key topics involved in surgical simulation and associated technical challenges. The paper discusses the clinical motivation for surgical simulation, the use of virtual environments for surgical training, model acquisition and simplification, deformable models, collision detection, tissue property measurement, haptic rendering and image synthesis. Additional topics include surgical skill training and assessment metrics as well as challenges facing the incorporation of surgical simulation into medical education curricula.

Are you looking to start 2020 with a fresh web design for your business? If so, you must know what you need to do in 2020 to have a website that drives success for your business. With website statistics for 2020, you can see what to do and what to avoid, which will help you […]

The post Website Statistics for 2020: 10 Critical Stats to Know for Web Design appeared first on WebFX Blog.

Node.js 14 is available now. We wanted to get more context and details about the state of Node, and why developers should care about Node.js 14. We talked with Bethany Griggs, Node.js Technical Steering Committee member and Open-source Engineer at IBM, to find out more. 

Bethany has been a Node Core Collaborator for over two years. She contributes to the open-source Node.js runtime and is a member of the Node.js Release Working Group where she is involved with auditing commits for the long-term support (LTS) release lines and the creation of releases. 

The Cannabis Issue People have been enjoying cannabis for recreational purposes for centuries, including in the United States since the early 1900s. That means weed was in America a good 50 years or so before the invention of rock 'n' roll.…

[IMAGE-1] First of all: No. Why would a suddenly single dad to traumatized young children leave said shocked and distressed kids with his new fiancée, who is also the sole survivor of her own massive childhood trauma?…

Pardon the interruption for a little fanboy boosterism, but one of my favorite all-time bands surprise-dropped a brand new album on Bandcamp today, and damned if I'm not going to tell you to go listen to it. The band is X, pioneering Los Angeles legends who helped establish the West Coast punk scene in the late '70s and early '80s with a sound that was rooted in American rock's roots.…

You might not know it from the fancy attire they wear on stage at the Fox Theater, but for the musicians in the Spokane Symphony, it's a part-time gig. It's a prestigious gig, to be sure, but like most artists, for the musicians, it's just one piece of a puzzle full of hustle they have to solve to make a living.…

ON INLANDER.COM NATION: As meatpacking plants nationwide shutdown due to COVID-19 outbreaks, certain meat products are becoming harder to find at grocery stores and fast-food drive-thrus.…

This is what it feels like to live during an historic event.…

Growing up, Luke Parker played sports.…

A nonmetallic compound having an ionic bond with a halide ion is used as a catalyst for living radical polymerization. Even if a radical initiator is not used, a monomer can be subjected to a radical polymerization to obtain a polymer having narrow molecular weight distribution. The cost of the living radical polymerization can be remarkably reduced, and it is made possible to prevent adverse effects of using a radical initiator (such as side reactions). The present invention is significantly more environmentally friendly and economically excellent than conventional living radical polymerization methods, due to advantages such as low toxicity of the catalyst, low amount of the catalyst necessary, high solubility of the catalyst, mild reaction conditions, and no coloration/no odor, etc. The catalyst can be applied to various monomers and enables synthesis of high molecular weight polymers.

A computer-implemented method is provided for statistical data learning under privacy constraints. The method includes: receiving, by a processor, a plurality of pieces of statistical information relating to a statistical object and aggregating, by the processor, the plurality of pieces of statistical information so as to provide an estimation of the statistical object. Each piece of statistical information includes an uncertainty variable, the uncertainty variable being a value determined from a function having a predetermined mean. The number of pieces of statistical information aggregated is proportional to the reliability of the estimation of the statistical object.

A method, system and computer program product for generating answers to questions. In one embodiment, the method comprises receiving an input query, decomposing the input query into a plurality of different subqueries, and conducting a search in one or more data sources to identify at least one candidate answer to each of the subqueries. A ranking function is applied to each of the candidate answers to determine a ranking for each of these candidate answers; and for each of the subqueries, one of the candidate answers to the subquery is selected based on this ranking. A logical synthesis component is applied to synthesize a candidate answer for the input query from the selected the candidate answers to the subqueries. In one embodiment, the procedure applied by the logical synthesis component to synthesize the candidate answer for the input query is determined from the input query.

A computer implemented method for automatic chemical assay classification, the method comprising steps the computer is programmed to perform, the steps comprising: receiving a plurality of sets of parameters, each one of the received sets of parameters characterizing a respective assay of a chemical reaction, calculating a space enhancing proximity among points representative of assays of qualitatively identical chemical reactions, and representing each one of at least two of the received sets of parameters as a respective point in the calculated space, and dividing the points in the calculated space into a number of groups, according to proximity among the points in the calculated space, each group pertaining to a respective chemical reaction, thereby classifying the assays.

A surfactant composition for agricultural chemicals, containing fatty acid polyoxyalkylene alkyl ether expressed by the following general formula (I), R1CO(EO)m(PO)nOR2 (I) wherein the fatty acid polyoxyalkylene alkyl ether has a narrow ratio of 55% by mass or more, where the narrow ratio is expressed by the following formula (A): Narrow ratio=Σi=nMAX−2i=nMAX+2Yi (A).

An object of the present invention is to provide a novel trans-2-decenoic acid derivative or a pharmaceutically acceptable salt thereof and to provide a pharmaceutical agent which contains said compound as an active ingredient and has a highly safe neurotrophic factor-like activity or an alleviating action for side effect induced by administration of anti-cancer agents. The trans-2-decenoic acid derivative or a pharmaceutically acceptable salt thereof which is the compound of the present invention is specifically represented by the formula (1): (In the formula, Y is —O—, —NR— or —S—, R is hydrogen atom, alkyl group, dialkylaminoalkyl group or the like and W is a substituent such as dialkylaminoalkyl group) and has a quite high usefulness as a pharmaceutical agent such as a preventive or therapeutic agent for dementia, Alzheimer's disease, Parkinson's disease, depression, etc., a treating or repairing agent for spinal cord injury.

Bioassays for detecting the ability of one sample of a food substance, nutritional supplement, therapeutic agent and/or disease preventive agent relative to that of a second sample of such a substance, supplement and/or agent to inhibit, upregulate or otherwise modulate translation initiation, and thereby demonstrate a disease curative and/or preventive effect in a human and/or animal that consumes a such substance, supplement and/or agent or to whom a such substance, supplement and/or agent is administered are provided.

The invention relates to ceramide dimers which are constructed from two ceramide molecules which are crosslinked to each other via their lipophilic end. The ceramide molecules thereby have at least one hydrophilic group at their hydrophilic end for increasing the hydration shell of the dimer. The ceramide dimers according to the invention can be used as pharmaceutical preparation or as cosmetic preparation.

The present invention provides: an uracil derivative represented by general formula (I) or a physiologically acceptable salt thereof (in the formula, R1 represents a hydrogen atom, a C1-10 alkyl group, a C2-6 alkene group or a 3- to 6-membered saturated or 4- to 6-membered unsaturated aliphatic ring group which may contain 1 to 2 hetero atoms independently selected from the group consisting of N, O and S; R2 represents a hydrogen atom, a halogen atom, a cyano group, —NRcRd, —N═CHN(CH3)2, or an C1-3 alkyl group; Ar1 and Ar2 independently represent a 5- to 6-membered aromatic ring group which may contain 1 to 3 hetero atoms independently selected from the group consisting of N, O and S; and L represents a 6-membered aromatic ring group which may contain 1 to 4 nitrogen atoms, a pyrazole group, a triazole group, or an imidazole group); and a therapeutic agent or prophylactic agent for various inflammatory diseases associated with elastase, comprises the compound or the like as an active ingredient.

The present invention relates to compounds of Formula (I): to pharmaceutically acceptable salts thereof, to methods of using them to treat bacterial infections, and to methods for their preparation.

The present invention relates to a novel acid addition salt of risperidone, wherein acid counterion is selected from the group consisting of pamoic acid, caproic acid, cypionic acid, decanoic acid, camphor sulfonic acid, enanthic acid, palmitic acid, fusidic acid, gluceptic acid, gluconic acid, lactobionic acid, lauric acid, levulinic acid and valeric acid, a process for the preparation and pharmaceutical composition comprising the same. Further, the invention relates to the use of said pharmaceutical composition comprising the acid addition salt of risperidone in the treatment of patient suffering from psychotic disorders.

Disclosed is a method for preparing optically pure (+)-ambrisentan and (+)-darusentan, comprising: firstly catalyzing the asymmetric epoxidation of a β-unsaturated alkene using a chiral ketone derived from fructose or a hydrate thereof as a catalyst, and then subjecting the product to an epoxy compound ring-opening reaction and substitution reaction successively to obtain optically pure (+)-ambrisentan and (+)-darusentan.

The invention relates to radiation curable coating systems on the basis of aqueous polyurethane dispersions, to a method for the production thereof, to the use of the coating systems as paints and/or adhesives, and to objects and substrates provided with said paints and/or adhesives.

The present invention relates to novel heterocycle-substituted diphosphonic acids, and the pharmaceutically-acceptable salts and esters thereof, in which the diphosphonate-substituted carbon atom moiety is attached to a carbon atom in a nitrogen-containing six membered ring heterocycle, preferably a piperidine ring. The heterocycle-substituted diphosphonic acid compounds have the general structure: ##STR1## wherein Z is a nitrogen-containing six membered ring heterocycle moiety selected from piperidinyl, diazinyl and triazinyl; m, n and m+n are from 0 to 10; Q is a covalent bond or a moiety selected from oxygen, sulfur or nitrogen; and R1, R2, R3 and R4 are substituent groups.The present invention further relates to pharmaceutical compositions containing these novel compounds. Finally this invention relates to methods for treating or preventing diseases characterized by abnormal calcium and phosphate metabolism by utilizing a compound or pharmaceutical composition of the present invention.

Antivirally active compounds of formula (I), wherein R1 is hydrogen, hydroxy, mercapto or amino; R2 is hydrogen, hydroxy, fluoro, chloro or amino; R3 and R4 are independently selected from (II), (III), amino, hydroxy or an ether or ester residue thereof, or R3 together with R4 is (IV), wherein M is hydrogen or a pharmaceutically acceptable counterion; and n is 1 or 2; with the proviso that, when R2 is amino and R3 and R4 are hydroxy, R1 is not hydroxy and in addition, when n=1, R1 is not hydrogen, and pharmaceutically acceptable salts thereof; processes for preparation of said compounds, a pharmaceutical composition comprising said compounds, methods for treatments of virus infections as well as use of compounds of formula (I) without the proviso for the manufacture of a medicament for treatment of AIDS. ##STR1##

A metal complex having a β-diketonate represented by the following formula (1): wherein M represents a metal atom of the VIII group, R1, R2 and R3 represent a group or an atom selected from the group consisting of an alkyl group, an aryl group, a hydroxyl group, an amino group, an alkoxy group, a hydrogen atom and a halogen atom; X−1 represents an ion selected from a halogen, nitric acid, sulfonic acid, fluoroboric acid, fluorophosphoric acid, or perchloric acid ion; L1 or L2 represents a 2,2'-bipyridine or 1,10-phenanthroline group where these groups may be substituted with a group or an atom selected from an alkyl group, a carboxyl group, a sulfonic acid group, a phosphonic acid group, a hydroxyl group, an amino group, a hydrogen atom and a halogen atom. A photoelectric conversion element and a photochemical cell using the above-mentioned metal complex.

The invention aims at an aqueous ink for high-temperature electrochemical cell electrodes and/or electrolyte containing particles of at least one mineral filler, at least one binder, and at least one dispersant. It also concerns the electrode and the electrolyte using such an ink.

There is provided a glass for chemical strengthening having a black color tone and excelling in characteristics preferred for the purposes of housing or decoration of an electronic device, that is, bubble quality, strength, and light transmittance characteristics. A glass for chemical strengthening contains, in mole percentage based on following oxides, 55% to 80% of SiO2, 3% to 16% of Al2O3, 0% to 12% of B2O3, 5% to 16% of Na2O, 0% to 4% of K2O, 0% to 15% of MgO, 0% to 3% of CaO, 0% to 18% of ΣRO (where R represents Mg, Ca, Sr, Ba or Zn), 0% to 1% of ZrO2, and 0.1% to 7% of a coloring component having at least one metal oxide selected from the group consisting of oxides of Co, Mn, Fe, Ni, Cu, Cr, V and Bi.

This optical glass contains, as represented by mol %, 18 to 38% P2O5, 0 to 15% B2O3, 23 to 40% P2O5+B2O3, 4 to 28% Nb2O5, 0 to 20% TiO2, 10 to 30% Nb2O5+TiO2, 15 to 35% Li2O+Na2O+K2O, and 21 to 38% ZnO, but does not contain BaO, WO3, Bi2O3 or SiO2, and the ratio of the mol % of ZnO to the total mol % of Li2O+Na2O+K2O (i.e., ZnO/(Li2O+Na2O+K2O)) is 0.8 to 2.0.

A highly refractive and highly transparent optical glass is provided. The use of such a glass, optical elements and processes for producing the glass or the optical elements are also provided.

The present invention relates to a chemically strengthened glass for a display device, having a visible light transmittance Tva of 50% or more and less than 91% at a thickness of 1 mm using A light source, and an excitation purity Pe of less than 0.5% at a thickness of 1 mm.

Provided is an optical glass that has desired optical properties, superior resistance to devitrification, and superior mass productivity. An optical glass is made of a SiO2—Nb2O5—TiO2-based glass having a refractive index (nd) of 1.75 to 1.95 and an Abbe's number (νd) of 15 to 35 and has an operation temperature range (ΔT=(temperature at 100.5 poise)−(liquidus temperature)) of 20° C. or more. The optical glass preferably contains, in percent by mass, 15% to 45% SiO2, 15% to 40% (but excluding 40%) Nb2O5 and 1% to 30% TiO2 as glass components.

An optical glass including B3+, La3+ and Nb5+ as cationic components constituting the glass, wherein the optical glass satisfies the following expressions represented in cation percentages: 10 cat. %≦B3+≦50 cat. %;40 cat. %≦La3+≦65 cat. %;0 cat. %≦Nb5+≦40 cat. %;80 cat. %≦(total amount of B3++La3++Nb5+)≦100 cat. %; and0 cat. %≦Si4+≦10 cat. %;0 cat. %≦Ge4+≦5 cat. %;0 cat. %≦Mg2+≦5 cat. %;0 cat. %≦Ba2+≦10 cat. %;0 cat. %≦Ca2+≦10 cat. %;0 cat. %≦Sr2+≦10 cat. %;0 cat. %≦Zn2+≦20 cat. %;0 cat. %≦W6+≦5 cat. %;0 cat. %≦Zr4+≦5 cat. %;0 cat. %≦Ti4+≦5 cat. %;0 cat. %≦Bi3+≦5 cat. %;0 cat. %≦Ta5+≦10 cat. %;0 cat. %≦(total amount of Y3++Gd3+)≦20 cat. %; and0 cat. %≦(total amount of Yb3++Lu3+)≦10 cat. %.

A nanostructure, an optical device including the nanostructure, and methods of manufacturing the nanostructure and the optical device. A method of manufacturing a nanostructure may include forming a block copolymer template layer and a precursor pattern of metal coupled to the block copolymer template layer on a graphene layer, and forming a metal nanopattern on the graphene layer by removing the block copolymer template layer and reducing the precursor pattern.

In a method for fabricating a graphene structure, there is formed on a fabrication substrate a pattern of a plurality of distinct graphene catalyst materials. In one graphene synthesis step, different numbers of graphene layers are formed on the catalyst materials in the formed pattern. In a method for fabricating a graphene transistor, on a fabrication substrate at least one graphene catalyst material is provided at a substrate region specified for synthesizing a graphene transistor channel and at least one graphene catalyst material is provided at a substrate region specified for synthesizing a graphene transistor source, and at a substrate region specified for synthesizing a graphene transistor drain. Then in one graphene synthesis step, at least one layer of graphene is formed at the substrate region for the graphene transistor channel, and at the regions for the transistor source and drain there are formed a plurality of layers of graphene.