Annotations are what set visual communication and journalism apart from just visualization. They often consist of text, but some of the most useful annotations are graphical elements, and many of them are very simple. One type I have a particular fondness for is the diagonal reference line, which has been used to provide powerful context […]

We study the bi-commutators $[T_1, [b, T_2]]$ of pointwise multiplication and Calder'on-Zygmund operators, and characterize their $L^{p_1}L^{p_2} o L^{q_1}L^{q_2}$ boundedness for several off-diagonal regimes of the mixed-norm integrability exponents $(p_1,p_2) eq(q_1,q_2)$. The strategy is based on a bi-parameter version of the recent approximate weak factorization method.

Device fingerprints like sensor pattern noise (SPN) are widely used for provenance analysis and image authentication. Over the past few years, the rapid advancement in digital photography has greatly reshaped the pipeline of image capturing process on consumer-level mobile devices. The flexibility of camera parameter settings and the emergence of multi-frame photography algorithms, especially high dynamic range (HDR) imaging, bring new challenges to device fingerprinting. The subsequent study on these topics requires a new purposefully built image dataset. In this paper, we present the Warwick Image Forensics Dataset, an image dataset of more than 58,600 images captured using 14 digital cameras with various exposure settings. Special attention to the exposure settings allows the images to be adopted by different multi-frame computational photography algorithms and for subsequent device fingerprinting. The dataset is released as an open-source, free for use for the digital forensic community.

This poster summarizes our contributions to Wikimedia's processing pipeline for mathematical formulae. We describe how we have supported the transition from rendering formulae as course-grained PNG images in 2001 to providing modern semantically enriched language-independent MathML formulae in 2020. Additionally, we describe our plans to improve the accessibility and discoverability of mathematical knowledge in Wikimedia projects further.

The Hierarchical Equal Area isoLatitude Pixelation (HEALPix) scheme is used extensively in astrophysics for data collection and analysis on the sphere. The scheme was originally designed for studying the Cosmic Microwave Background (CMB) radiation, which represents the first light to travel during the early stages of the universe's development and gives the strongest evidence for the Big Bang theory to date. Refined analysis of the CMB angular power spectrum can lead to revolutionary developments in understanding the nature of dark matter and dark energy. In this paper, we present a new method for performing spherical harmonic analysis for HEALPix data, which is a central component to computing and analyzing the angular power spectrum of the massive CMB data sets. The method uses a novel combination of a non-uniform fast Fourier transform, the double Fourier sphere method, and Slevinsky's fast spherical harmonic transform (Slevinsky, 2019). For a HEALPix grid with $N$ pixels (points), the computational complexity of the method is $mathcal{O}(Nlog^2 N)$, with an initial set-up cost of $mathcal{O}(N^{3/2}log N)$. This compares favorably with $mathcal{O}(N^{3/2})$ runtime complexity of the current methods available in the HEALPix software when multiple maps need to be analyzed at the same time. Using numerical experiments, we demonstrate that the new method also appears to provide better accuracy over the entire angular power spectrum of synthetic data when compared to the current methods, with a convergence rate at least two times higher.

Compromised accounts on social networks are regular user accounts that have been taken over by an entity with malicious intent. Since the adversary exploits the already established trust of a compromised account, it is crucial to detect these accounts to limit the damage they can cause. We propose a novel general framework for discovering compromised accounts by semantic analysis of text messages coming out from an account. Our framework is built on the observation that normal users will use language that is measurably different from the language that an adversary would use when the account is compromised. We use our framework to develop specific algorithms that use the difference of language models of users and adversaries as features in a supervised learning setup. Evaluation results show that the proposed framework is effective for discovering compromised accounts on social networks and a KL-divergence-based language model feature works best.

Quantum dialogue is a process of two way secure and simultaneous communication using a single channel. Recently, a Measurement Device Independent Quantum Dialogue (MDI-QD) protocol has been proposed (Quantum Information Processing 16.12 (2017): 305). To make the protocol secure against information leakage, the authors have discarded almost half of the qubits remaining after the error estimation phase. In this paper, we propose two modified versions of the MDI-QD protocol such that the number of discarded qubits is reduced to almost one-fourth of the remaining qubits after the error estimation phase. We use almost half of their discarded qubits along with their used qubits to make our protocol more efficient in qubits count. We show that both of our protocols are secure under the same adversarial model given in MDI-QD protocol.

We present a system for automatic diacritization of Hebrew text. The system combines modern neural models with carefully curated declarative linguistic knowledge and comprehensive manually constructed tables and dictionaries. Besides providing state of the art diacritization accuracy, the system also supports an interface for manual editing and correction of the automatic output, and has several features which make it particularly useful for preparation of scientific editions of Hebrew texts. The system supports Modern Hebrew, Rabbinic Hebrew and Poetic Hebrew. The system is freely accessible for all use at this http URL

Reinforcement learning methods have been used to compute dialog policies from language-based interaction experiences. Efficiency is of particular importance in dialog policy learning, because of the considerable cost of interacting with people, and the very poor user experience from low-quality conversations. Aiming at improving the efficiency of dialog policy learning, we develop algorithm LHUA (Learning with Hindsight, User modeling, and Adaptation) that, for the first time, enables dialog agents to adaptively learn with hindsight from both simulated and real users. Simulation and hindsight provide the dialog agent with more experience and more (positive) reinforcements respectively. Experimental results suggest that, in success rate and policy quality, LHUA outperforms competitive baselines from the literature, including its no-simulation, no-adaptation, and no-hindsight counterparts.

Recently, the outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly across the world. Due to the large number of affected patients and heavy labor for doctors, computer-aided diagnosis with machine learning algorithm is urgently needed, and could largely reduce the efforts of clinicians and accelerate the diagnosis process. Chest computed tomography (CT) has been recognized as an informative tool for diagnosis of the disease. In this study, we propose to conduct the diagnosis of COVID-19 with a series of features extracted from CT images. To fully explore multiple features describing CT images from different views, a unified latent representation is learned which can completely encode information from different aspects of features and is endowed with promising class structure for separability. Specifically, the completeness is guaranteed with a group of backward neural networks (each for one type of features), while by using class labels the representation is enforced to be compact within COVID-19/community-acquired pneumonia (CAP) and also a large margin is guaranteed between different types of pneumonia. In this way, our model can well avoid overfitting compared to the case of directly projecting highdimensional features into classes. Extensive experimental results show that the proposed method outperforms all comparison methods, and rather stable performances are observed when varying the numbers of training data.

Fact-based dialogue generation is a task of generating a human-like response based on both dialogue context and factual texts. Various methods were proposed to focus on generating informative words that contain facts effectively. However, previous works implicitly assume a topic to be kept on a dialogue and usually converse passively, therefore the systems have a difficulty to generate diverse responses that provide meaningful information proactively. This paper proposes an end-to-end Fact-based dialogue system augmented with the ability of convergent and divergent thinking over both context and facts, which can converse about the current topic or introduce a new topic. Specifically, our model incorporates a novel convergent and divergent decoding that can generate informative and diverse responses considering not only given inputs (context and facts) but also inputs-related topics. Both automatic and human evaluation results on DSTC7 dataset show that our model significantly outperforms state-of-the-art baselines, indicating that our model can generate more appropriate, informative, and diverse responses.

Smart meters enable remote and automatic electricity, water and gas consumption reading and are being widely deployed in developed countries. Nonetheless, there is still a huge number of non-smart meters in operation. Image-based Automatic Meter Reading (AMR) focuses on dealing with this type of meter readings. We estimate that the Energy Company of Paran'a (Copel), in Brazil, performs more than 850,000 readings of dial meters per month. Those meters are the focus of this work. Our main contributions are: (i) a public real-world dial meter dataset (shared upon request) called UFPR-ADMR; (ii) a deep learning-based recognition baseline on the proposed dataset; and (iii) a detailed error analysis of the main issues present in AMR for dial meters. To the best of our knowledge, this is the first work to introduce deep learning approaches to multi-dial meter reading, and perform experiments on unconstrained images. We achieved a 100.0% F1-score on the dial detection stage with both Faster R-CNN and YOLO, while the recognition rates reached 93.6% for dials and 75.25% for meters using Faster R-CNN (ResNext-101).

Vision-and-Language Navigation (VLN) requires an agent to follow natural-language instructions, explore the given environments, and reach the desired target locations. These step-by-step navigational instructions are crucial when the agent is navigating new environments about which it has no prior knowledge. Most recent works that study VLN observe a significant performance drop when tested on unseen environments (i.e., environments not used in training), indicating that the neural agent models are highly biased towards training environments. Although this issue is considered as one of the major challenges in VLN research, it is still under-studied and needs a clearer explanation. In this work, we design novel diagnosis experiments via environment re-splitting and feature replacement, looking into possible reasons for this environment bias. We observe that neither the language nor the underlying navigational graph, but the low-level visual appearance conveyed by ResNet features directly affects the agent model and contributes to this environment bias in results. According to this observation, we explore several kinds of semantic representations that contain less low-level visual information, hence the agent learned with these features could be better generalized to unseen testing environments. Without modifying the baseline agent model and its training method, our explored semantic features significantly decrease the performance gaps between seen and unseen on multiple datasets (i.e. R2R, R4R, and CVDN) and achieve competitive unseen results to previous state-of-the-art models. Our code and features are available at: https://github.com/zhangybzbo/EnvBiasVLN

Dialogue engines that incorporate different types of agents to converse with humans are popular.

However, conversations are dynamic in the sense that a selected response will change the conversation on-the-fly, influencing the subsequent utterances in the conversation, which makes the response selection a challenging problem.

We model the problem of selecting the best response from a set of responses generated by a heterogeneous set of dialogue agents by taking into account the conversational history, and propose a emph{Neural Response Selection} method.

The proposed method is trained to predict a coherent set of responses within a single conversation, considering its own predictions via a curriculum training mechanism.

Our experimental results show that the proposed method can accurately select the most appropriate responses, thereby significantly improving the user experience in dialogue systems.

By Lauren McCauley Common Dreams In landmark agreement, California’s last remaining nuclear plant will be replaced by greenhouse-gas-free energy sources A plan to shutter the last remaining nuclear power plant in California and replace it with renewable energy is being … Continue reading →

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[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?…

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[IMAGE-1] It isn't often that you see a local band selling out most of their gigs, but Indian Goat does. The duo of Garrett Zanol and Travis Tveit formed a few years ago and almost immediately struck a chord with Spokane audiences: Their live shows are usually raucous, sweaty, beer-soaked affairs, with rooms crammed full of people rocking out in unison.…

The present invention relates to a compound of formula A, wherein R is alkyl. Compound A may be used as an intermediate in the preparation of O-desmethyl venlafaxine or a salt thereof, and the present invention provides such a preparation, as well as a process for preparing the compound of formula A.

A process has been developed for preparing 2-methoxymethyl-1,4-benzenediamine (IV-a), other compounds of formula (IV), and the salts thereof, all of which may be used as primary intermediates in compositions for dyeing keratin fibers.

Provided is a method for stably and economically producing xylylenediamine with a high yield and long catalyst service life by hydrogenating dicyanobenzene that is obtained by ammoxidating xylene. By bringing an aqueous basic solution into contact with a dicyanobenzene-absorbed liquid, which is obtained by bringing an ammoxidation reaction gas into contact with an organic solvent, under specified temperature conditions, and subjecting a base and a carboxylic acid in the dicyanobenzene-absorbed liquid to a neutralization reaction so as to form an aqueous phase that contains a water-soluble salt, and then subjecting an organic phase and the aqueous phase to liquid-liquid separation so as to remove the aqueous phase, it is possible to remove the carboxylic acid contained in the dicyanobenzene-absorbed liquid with high selectivity while inhibiting loss of the dicyanobenzene. By subjecting the raw material dicyanobenzene, which is obtained by separating low boiling point compounds from the post liquid-liquid separation organic phase by distillation under reduced pressure, to hydrogenation, xylylenediamine is produced with a high yield and the service life of the hydrogenation catalyst is extended.

A process for reductive amination of aliphatic cyanoaldehydes to aliphatic diamines comprising (1) providing a mixture of 1,3-cyanocyclohexane carboxaldehyde and/or 1,4-cyanocyclohexane carboxaldehyde; (2) contacting said mixture with a metal carbonate based solid bed or a weak base anion exchange resin bed at a temperature from 15 to 40 ° C. for a period of at least 1 minute; (3) thereby treating said mixture, wherein said treated mixture has a pH in the range of 6 to 9; (4) feeding said treated mixture, hydrogen, and ammonia into a continuous reductive amination reactor system; (6) contacting said treated mixture, hydrogen, and ammonia with each other in the presence of one or more heterogeneous metal based catalyst systems at a temperature from 80 ° C. to 160 ° C. and a pressure from 700 to 3500 psig; (7) thereby producing one or more cycloaliphatic diamines is provided.

A branched hetero polyfunctional polyoxyalkylene compound represented by the following formula (1): wherein Z represents a hydroxyl group-removed residue of pentaerythritol or dipentaerythritol, OA1 and OA2 represent an oxyalkylene group having 2 to 4 carbon atoms, L1, L2 and L3 represent an alkylene group or an alkylene group that contains an ester bond, a urethane bond, an amide bond, an ether bond, a carbonate bond, a secondary amino group or a urea bond, X and Y are different from each other and represent a functional group capable of a chemical reaction; m and n are an average number of moles of the oxyalkylene group added, m represents 5 to 1,000, n represents 0 to 1,000, and p, q and r represent 0 or 1; and s1 is an integer of 2 or more and s1+s2=4 or 6.

A process for preparing alkylated p-phenylenediamine having the steps of reacting aniline and nitrobenzene in presence of a complex base catalyst to obtain 4-aminodiphenylamine intermediates, hydrogenating the 4-aminodiphenylamine intermediates to 4-aminodiphenylamine in presence of a hydrogenation catalyst, and reductively alkylating the 4-aminodiphenylamine to alkylated p-phenylenediamine.

A process for conversion of aliphatic bicyclic amines to aliphatic diamines including contacting one or more bicyclic amines selected from the group consisting of 3-azabicyclo[3.3.1]nonane and azabicyclo[3.3.1]non-2-ene with ammonia and hydrogen, and alcohols in the presence of heterogeneous metal based catalyst systems, a metal selected from the group consisting of Co, Ni, Ru, Fe, Cu, Re, Pd, and their oxides at a temperature from 140° C. to 200° C. and a pressure from 1540 to 1735 psig for at least one hour reactor systems; forming a product mixture comprising aliphatic diamine(s), bicyclic amine(s), ammonia, hydrogen, and alcohol(s); removing said product mixture from the reactor system; removing at least some of the ammonia, hydrogen, water, alcohols, bicyclic amines from said product mixture; thereby separating the aliphatic diamines from said product mixture.

The invention relates to a method for preparing ring-halogenated N,N-dialkylbenzylamines and intermediates obtainable therefrom for preparing agrochemicals and pharmaceutically active ingredients.

A modeling framework for evaluating the impact of weather conditions on farming and harvest operations applies real-time, field-level weather data and forecasts of meteorological and climatological conditions together with user-provided and/or observed feedback of a present state of a harvest-related condition to agronomic models and to generate a plurality of harvest advisory outputs for precision agriculture. A harvest advisory model simulates and predicts the impacts of this weather information and user-provided and/or observed feedback in one or more physical, empirical, or artificial intelligence models of precision agriculture to analyze crops, plants, soils, and resulting agricultural commodities, and provides harvest advisory outputs to a diagnostic support tool for users to enhance farming and harvest decision-making, whether by providing pre-, post-, or in situ-harvest operations and crop analyzes.

Systems and methods for recommending media content items are provided. In some implementations, a method includes, identifying a first set of media items selected by a first plurality of users; causing a second set of media items to be displayed to a second user not included in the first plurality of users in accordance with the first set of media items. The first set of media items and the second set of media items are associated with a same media item category. In some implementations, the method optionally includes, identifying the second set of media items without regard to media content item selection history associated with the second user. In some implementations, the first and second sets of media items are news items.

Disclosed embodiments provide pyrimidinediamine compounds useful for inhibiting kinase activity, including the activity of polo-like kinase 1 (PLK1). Also disclosed are pharmaceutical compositions comprising these compounds and methods of treating diseases associated with kinase activity, in particular enhanced PLK1 catalytic activity, such as diseases associated with abnormal cell proliferation, including neoplastic disorders.

The present invention provides 2,4-pyrimidinediamine compounds that inhibit the IgE and/or IgG receptor signaling cascades that lead to the release of chemical mediators, intermediates and methods of synthesizing the compounds and methods of using the compounds in a variety of contexts, including in the treatment and prevention of diseases characterized by, caused by or associated with the release of chemical mediators via degranulation and other processes effected by activation of the IgE and/or IgG receptor signaling cascades.

The object of the present invention is to provide an intermediate film for laminated glass which prevents reductions of transparency and appearance property caused by permeation of moisture and water. The above object is attained by the present invention, i.e., a composition for forming an intermediate film for a laminated glass which comprises ethylene-vinyl acetate copolymer and a compound having alkyleneoxy group. The composition of the present invention enables the formation of an intermediate film for a laminated glass that restrains white spots from occurring by the permeation of moisture and water.

A glass for a magnetic recording medium substrate permitting the realization of a magnetic recording medium substrate affording good chemical durability and having an extremely flat surface, a magnetic recording medium substrate comprised of this glass, a magnetic recording medium equipped with this substrate, and methods of manufacturing the same. The glass is an oxide glass not including As or F.

Aspects of the present invention provide a tool for analyzing and remediating an update-related failure. In an embodiment, a failure state of a computer system that has been arrived at as a result of an update is captured. A semantic diff that includes the difference between the failure state and at least one of an original state or a completion state is then computed. This semantic diff is transformed into a feature vector format. Then the transformed semantic diff is analyzed to determine a remediation for the update. Failure and/or resolution signatures can be constructed using the semantic diff and contextual data, and these signatures can be used in comparison and analysis of failures and resolutions.

Embodiments of the present invention relate to an apparatus, method, and/or sequence for a distributed ECC that may be used in a storage system. In another embodiment of the invention, an apparatus for handling distributed error correction code (ECC) operations, includes: a plurality of ECC engines configured to perform ECC operations in parallel on multiple data parts; the plurality of ECC engines distributed in parallel to receive some of the multiple data parts that are read from storage media devices and to receive some of the other multiple data parts that are to be written to the storage media devices; and the plurality of ECC engines configured to use respective ECC bytes corresponding to respective ones of the multiple data parts.

There is disclosed a silicone rubber composition curable by a radial ray comprising, at least, (A) an organopolysiloxane shown by the following general formula (1), (B) a phenyl ester derivative having an acryl group, (C) a sensitizer sensitized by a radial ray, and (D) a photosensitive dye, wherein each R1, R2, and R3 independently represents a monovalent hydrocarbon group having 1 to 10 carbon atoms; X represents the same or different monovalent organic group having an acryl group or a methacryl group. As a result, there is provided a silicone rubber composition capable of being cured by irradiation of a radial ray whereby showing excellent adhesion with various substrates, capable of forming a cured film, and capable of easily distinguishing whether it is cured or not by observing appearance when not irradiated with a radial ray.

Described is a radiation-crosslinkable hotmelt adhesive comprising at least one radiation-crosslinkable poly(meth)acrylate formed to an extent of at least 60% by weight of C1 to C10 alkyl(meth)acrylates and at least one oligo(meth)acrylate which comprises nonacrylic C C double bonds and has a K value of less than or equal to 20. The hotmelt adhesive comprises a photoinitiator which may be present in the form of an additive not attached to the poly(meth)acrylate and/or not attached to the oligo(meth)acrylate, may be incorporated by copolymerization into the poly(meth)acrylate, and/or may be attached to the oligo(meth)acrylate. The hotmelt adhesive can be used for producing adhesive tapes.

The invention relates to a radiation curable composition for taking a dental impression comprising (A) a cationically hardenable compound comprising at least one aziridine moiety, and (B) a radiation sensitive starter, the radiation sensitive starter comprising an onium salt, a ferrocenium salt, a combination or mixture thereof.

A radiation curable temporary laminating adhesive composition for use in temperature applications at 150° C. or greater, and typically at 200° C. or greater, comprises (A) a hydrogenated polybutadiene diacrylate; (B) a radical photoinitiator; and (C) a diluent.

The description generally relates to a system designed to synchronize the rendering of a media file between a master device and a sister device. The system is designed so that a media file is simultaneously rendered on a master device and a sister device beginning from identical temporal starting points.

A usage allocation of a hardware resource to each of a number of workloads over time is determined using a demand model. The usage allocation of the resource includes a current and past actual usage allocation of the resource, a future projected usage allocation of the resource, and current and past actual usage of the resource. A capacity allocation of the resource is determined using a capacity model. The capacity allocation of the resource includes a current and past capacity and a future projected capacity of the resource. Whether a gap exists between the usage allocation and the capacity allocation is determined using a mapping model. Where the gap exists between the usage allocation of the resource and the capacity allocation of the resource, a user is presented with options determined using the mapping model and selectable by the user to implement a remediation strategy to close the gap.

An optically active bisbenzyl compound or a racemic bisbenzyl compound represented by formula (2) that has axial chirality: where: R1 represents a halogen, or an optionally substituted: linear, branched, or cyclic C1-8 alkyl, C2-8 alkenyl, C2-8 alkynyl, C6-14 aryl, C3-8 heteroaryl, linear, branched, or cyclic C1-8 alkoxy, or C7-16 aralkyl;R21 each independently represents hydrogen, halogen, nitro, or an optionally substituted: linear, branched, or cyclic C1-8 alkyl, C2-8 alkenyl, C2-8 alkynyl, C6-14 aryl, linear, branched, or cyclic C1-8 alkoxy, or a C7-16 aralkyl;R3 represents hydrogen, or an optionally substituted: C6-14 aryl, a C3-8 heteroaryl, or a C7-16 aralkyl; andY2 represents a halogen, or an optionally substituted: C1-8 alkylsulfonyloxy, C6-14 arylsulfonyloxy, or C7-16 aralkylsulfonyloxy.

Disclosed are: a diaryliodonium salt mixture which is a precursor of a BF4 salt or the like of a diaryliodonium compound, can be produced in the form of crystals at ambient temperature, can be purified in a simple manner, can be produced with high efficiency, and can be induced into a BF4 salt or the like salt that has excellent solubility in a monomer or the like; and a process for producing the diaryliodonium salt mixture. Also disclosed is a production process which can achieve good yield and can produce reduced amounts of byproducts, and is therefore applicable to the industrial mass production of a diaryliodonium compound. The diaryliodonium salt mixture is characterized by containing at least two specific diaryliodonium salts.

A processing apparatus includes an execution unit which performs computation on two operand inputs each being selectable between read data from a register and an immediate value. The processing apparatus also includes another execution unit which performs computation on two operand inputs, one of which is selectable between read data from a register and an immediate value, and the other of which is an immediate value. A control unit determines, based on a received instruction specifying a computation on two operands, whether each of the two operands specifies read data from a register or an immediate value. Depending on the determination result, the control unit causes one of the execution units to execute the computation specified by the received instruction.

A para-methoxy protected benzaldehyde useful in preparation of treprostinil, and of formula: (Formula (1)) is prepared by subjecting to Claisen re-arrangement a substituted benzaldehyde of formula (1a): (Formula (Ia)) to form the m-hydroxy-substituted benzaldehyde of formula (1b): (Formula (Ib)) and then reacting compound (1b) with a p-methoxybenzyl (PMB) compound to form a PMB-substituted benzaldehyde of formula (1).

Processes are disclosed for the conversion of a carbohydrate source to hexamethylenediamine (HMDA) and to intermediates useful for the production of hexamethylenediamine and other industrial chemicals. HMDA is produced by direct reduction of a furfural substrate to 1,6-hexanediol in the presence of hydrogen and a heterogeneous reduction catalyst comprising Pt or by indirect reduction of a furfural substrate to 1,6-hexanediol wherein 1,2,6-hexanetriol is produced by reduction of the furfural substrate in the presence of hydrogen and a catalyst comprising Pt and 1,2,6-hexanediol is then converted by hydrogenation in the presence of a catalyst comprising Pt to 1,6 hexanediol, each process then proceeding to the production of HMDA by known routes, such as amination of the 1,6 hexanediol. Catalysts useful for the direct and indirect production of 1,6-hexanediol are also disclosed.

A chemical composition for cleaning a medium is provided. For some embodiments, the chemical composition comprises a nonionic surfactant, an inorganic salt, a glycol compound, a chelating agent, and deionized water. For example, the chemical composition may comprise between about 1% and 5% of nonionic surfactant, between about 2% and 6% by weight of an inorganic salt, between about 5% and 10% by weight of a glycol compound, between about 5% and 10% by weight of a chelating agent, and deionized water.

Acidic viscoelastic cleaning compositions are disclosed which use non polymer thickening agents. According to the invention, cleaning compositions have been developed using viscoelastic surfactants in acidic cleaning formulations. These provide the dual benefit of thickening as well as an additional cleaning, thereby improving performance. Applicants have also identified several pseudo linking agents which when, used with viscoelastic surfactants provide enhanced viscoelasticity and cleaning.

A mixture of surfactants from alkylene oxide adducts with different degrees of alkoxylation is used in a urea solution to be added to an exhaust stream for reduction of nitrous gases.