A full list of events and gigs which have been rescheduled, cancelled or postponed across Belfast for the coming months

Welcome to the EU Policy Blog, Microsoft Brussels’ platform for providing insights on the issues that impact Europe’s future in the digital age. This is a forum to discuss the latest trends, research and regulatory developments which are shaping how European citizens, businesses,...

Microsoft news. Your view from the inside.

Sala de prensa de la AHA sobre el COVID-19 WASHINGTON, D. C., 9 de abril del 2020— Las organizaciones sin fines de lucro de la nación están en la primera línea en nuestras comunidades durante la pandemia del COVID-19. Trabajan sin cesar para servir a...

The 2012 french president's election from the side of political activists.

Investigate the simmering tensions between groups of Australians that led to racially motivated violence at Sydney’s Cronulla Beach in December 2005.

There are many apps are available on Microsoft store for free which can be installed very easily but who knows? That is why we are sharing 8 Wallpaper Photos Apps On Microsoft Store You (Might) Never Knew For Windows. So, without any further ado let’s take a...

The post 8 Free Wallpaper Photos Apps On Microsoft Store You (Might) Never Knew For Windows appeared first on SmashingApps.com.

JOEL CRONBAUGH
Norway

Joel Cronbaugh, whose brother David referred to him as the purest, most innocent soul he ever knew, transitioned to his Heavenley home peacefully on May 5, 2020. A person of few words but many, many stories, Joel was a man of action who distinguished himself in many ways during his long, fore-filled life. Mostly we will all remember him for his selfless kindness, goofy sense of humor and many years of taking his fellow truck driver friends, his family of nieces and nephews and all his devoted friends to The Brick Haus in Amana for weekly and often twice a week "Cowboy" lunches.
A graduate of McKinley High in Cedar Rapids, Iowa, as his younger brothers David and Steve shoved each other down the laundry chute, Joel was making his name as a car engine genius. As a member of the famous Cedar Rapids motor club, The Rod Benders, Joel was the go-to guy for making a car engine "scream." This passion for anything with a motor and wheels resulted in him becoming an avid, lifelong collector of bicycles, motocross bikes and cars. Joel drove in motocross well into his 70s, putting much younger competitors to shame.
When his niece and nephew Tara and Todd were young, Joel and his brother David helped them construct national class caliber Soap Box Derby Cars. Tara's car actually finished second in the All-American Championship. During this period, Joel became a friend and mentor to Todd's buddy James Burns, also a Derby Car driver. Both Todd and James took Joel's endless hours of meticulous lessons and teaching and went on to pursue master's degrees in engineering and law at Ivy League schools. Their love and friendship lasted throughout Joel's life. Joel, the man who never told a dirty joke or even used a naughty word, went on to make the long drive to New York City to stand up in James's wedding and proceeded to drive back to Iowa with a $500 parking ticket for parking in Times Square that he "refused" to pay. (The conservative Iowa guy had no idea how to park in NYC.)
Joel cut his mechanical teeth helping his father Melvin W (W for work, he always joked), at Tubb's Transport Service on old Highway 30. Initially helping with car and transport servicing, Joel prided himself on being the electrical wizard at the once-largest truck stop in Iowa. Drivers would scratch their heads as the tall, scrawny kid would solve elusive electrical problems in minutes. Joel's natural ability to troubleshoot or fabricate anything electronic inspired him to follow in his father, Melvin's, footsteps as a longtime businessman in Cedar Rapids. After operating Cronbaugh Transport during the early 1980s, Joel made his mark in the trucking and tank wash industry. Cronbaugh Tank Wash offered interior tank washes for liquid product transport tankers. Joel once again used his diligent, meticulous skill to design one of his own mechanical spinner washers, a washing technique still used today. His scrupulous cleaning process set the gold standard in the liquid tank washing industry. Joel retired from his love of the trucking industry in 1997, when he sold the business to Kevin Smith, an employee at the time but later grew into a devoted, trusted friend. The family would like to extend appreciation to Kevin for all his support during Joel's illness.
Joel spent his retirement years mentoring his niece Tara, as she continued the family trait of business ownership. Until 2017, alongside his brother David, Joel pursued his love to fabricate, troubleshoot and fix anything at The Java House, Tara's company in Iowa City. When Joel was not fixing odds and ends around his farmstead in Norway, he was tinkering on his pride and joy, Ducati motocross bikes, collecting bicycles to rebuild and later donate, or attending Sunday church service, a life-time member at Calvary Baptist Church in Cedar Rapids. He got a kick out of retelling jokes, reciting Bible verses to those he loved (Romans 8:28 was his favorite) and doing favors for people he cared about most. He wore a denim jean shirt every day, carried a tire pressure gauge in his shirt pocket and handed out hundreds of mini-LED flashlights to each of his friends. A man of simple pleasures, he loved hamburgers at The Hamburg Inn and his weekly visits for Beef & Noodles at Maid-Rite in Cedar Rapids, where he would take his Maid-Rite lunch to his longtime high school friend, Evelynn Strait, each week for many years. The family would like to extend deep appreciation to Evelynn for her loving, unconditional and daily support, and friendship to Joel.
Joel Richard was born Feb. 28, 1935, to Katherine Maxine Hepler and Melvin W Cronbaugh. Joel entered the U.S. Army in 1964 and did basic at Fort Leonard Wood. At the age of 41, Joel graduated at LeTourneau College, Longview, Texas.
Joel was preceded in death by his parents and his brothers, David and Stephen.
Surviving are nieces and nephews, Tara Cronbaugh, Todd Miller, Anya Schmitz, Barbara Wolfe and Stephen Cronbaugh; and many great-nieces and -nephews.
The family would like to thank Brown Deer Place and ManorCare, Cedar Rapids, for Joel's last months of care during a long-progressive disease. Thank you to Mercy Hospice Cedar Rapids and specifically, Amy Harris, Mercy Hospice nurse and friend, who offered special attention and love during Joel's last hours. Tara Cronbaugh, Joel's niece, was devoted to Joel's wellbeing during the last, fragile years of his life and we all want to thank her for it. Indeed, it takes a village.
The family will be holding a graveside service at noon Saturday, May 9, in the Honey Creek Township, in Koszta, Iowa, at the Koszta Cemetery. Located outside of Marengo, Highwwy 212 to F Avenue in Koszta. In lieu of flowers, memorials may be directed to Mercy Hospice, Cedar Rapids.
Online condolences may be made at www.lensingfuneral.com.

https://thenextweb.com/microsoft/2020/05/08/microsoft-bundled-its-beautiful-bing-wallpapers-into-a-free-android-app/

https://mitchum.blog/building-a-crossword-puzzle-generator-with-javascript/

Chris Coyier of CSS-Tricks is an amazing engineer and blogger. He’s not only creative but has always had the drive to put his thoughts to work, no matter how large. He also has a good eye for the little things that can make CSS-Tricks or your site special. One of those little things is his […]

The post How to Create a CSS-Tricks Custom Scrollbar appeared first on David Walsh Blog.

Sony introduced the a6400 model of digital cameras in early 2019. The a6400 rapidly became a best-seller among both professional and amateur photographers. The camera is smaller than standard digital single reflex cameras but still uses Sony’s extensive line of lenses. Sony has achieved all this using an APS-C sensor system in a mirrorless body. What is Sony a6400 crop Continue Reading

The post What is the Sony a6400 Crop Factor? appeared first on Photodoto.

13 Questions You Should Ask Before Backing A Crowdfunding Project on Kickstarter, Indiegogo and Beyond

Designing is often as much as a science as it is an art. Using specific knowledge of human psychology & online behaviour, the science of creating effective websites that are optimized for business...

Sometimes interesting things happen on Twitter. Last week Scott Jehl proposed ASPIRE as an acronym for the practices we should follow as web designers and developers. From the resulting blog post: Great websites should aspire to be: Accessible to folks with varying cognitive and physical abilities and disabilities Secure and reliable for storing, manipulating, and transferring information Performant on average devices […]

The post ASPIRE: An Acronym for Better Web Practice appeared first on MOR10.

Andrew Rickmann posted a photo:

Crowds de France heading home after the cyclists have passed through Huddersfield

Andrew Rickmann posted a photo:

Crowds de France heading home after the cyclists have passed through Huddersfield

We provide an explicit construction for a class of commutative, non-associative algebras for each of the simple Chevalley groups of simply laced type. Moreover, we equip these algebras with an associating bilinear form, which turns them into Frobenius algebras. This class includes a 3876-dimensional algebra on which the Chevalley group of type E8 acts by automorphisms. We also prove that these algebras admit the structure of (axial) decomposition algebras.

We study two notions of topological entropy of correspondences introduced by Friedland and Dinh-Sibony. Upper bounds are known for both. We identify a class of holomorphic correspondences whose entropy in the sense of Dinh-Sibony equals the known upper bound. This provides an exact computation of the entropy for rational semigroups. We also explore a connection between these two notions of entropy.

We introduce a notion of c-group, which is a group up to congruence relation and consider the corresponding category. Extensions, actions and crossed modules (c-crossed modules) are defined in this category and the semi-direct product is constructed. We prove that each categorical group gives rise to c-groups and to a c-crossed module, which is a connected, special and strict c-crossed module in the sense defined by us. The results obtained here will be applied in the proof of an equivalence of the categories of categorical groups and connected, special and strict c-crossed modules.

High-performance implementations of graph algorithms are challenging to implement on new parallel hardware such as GPUs, because of three challenges: (1) difficulty of coming up with graph building blocks, (2) load imbalance on parallel hardware, and (3) graph problems having low arithmetic intensity. To address these challenges, GraphBLAS is an innovative, on-going effort by the graph analytics community to propose building blocks based in sparse linear algebra, which will allow graph algorithms to be expressed in a performant, succinct, composable and portable manner. In this paper, we examine the performance challenges of a linear algebra-based approach to building graph frameworks and describe new design principles for overcoming these bottlenecks. Among the new design principles is exploiting input sparsity, which allows users to write graph algorithms without specifying push and pull direction. Exploiting output sparsity allows users to tell the backend which values of the output in a single vectorized computation they do not want computed. Load-balancing is an important feature for balancing work amongst parallel workers. We describe the important load-balancing features for handling graphs with different characteristics. The design principles described in this paper have been implemented in "GraphBLAST", the first open-source linear algebra-based graph framework on GPU targeting high-performance computing. The results show that on a single GPU, GraphBLAST has on average at least an order of magnitude speedup over previous GraphBLAS implementations SuiteSparse and GBTL, comparable performance to the fastest GPU hardwired primitives and shared-memory graph frameworks Ligra and Gunrock, and better performance than any other GPU graph framework, while offering a simpler and more concise programming model.

Position encoding (PE), an essential part of self-attention networks (SANs), is used to preserve the word order information for natural language processing tasks, generating fixed position indices for input sequences. However, in cross-lingual scenarios, e.g. machine translation, the PEs of source and target sentences are modeled independently. Due to word order divergences in different languages, modeling the cross-lingual positional relationships might help SANs tackle this problem. In this paper, we augment SANs with emph{cross-lingual position representations} to model the bilingually aware latent structure for the input sentence. Specifically, we utilize bracketing transduction grammar (BTG)-based reordering information to encourage SANs to learn bilingual diagonal alignments. Experimental results on WMT'14 English$Rightarrow$German, WAT'17 Japanese$Rightarrow$English, and WMT'17 Chinese$Leftrightarrow$English translation tasks demonstrate that our approach significantly and consistently improves translation quality over strong baselines. Extensive analyses confirm that the performance gains come from the cross-lingual information.

Many efforts of research are devoted to semantic role labeling (SRL) which is crucial for natural language understanding. Supervised approaches have achieved impressing performances when large-scale corpora are available for resource-rich languages such as English. While for the low-resource languages with no annotated SRL dataset, it is still challenging to obtain competitive performances. Cross-lingual SRL is one promising way to address the problem, which has achieved great advances with the help of model transferring and annotation projection. In this paper, we propose a novel alternative based on corpus translation, constructing high-quality training datasets for the target languages from the source gold-standard SRL annotations. Experimental results on Universal Proposition Bank show that the translation-based method is highly effective, and the automatic pseudo datasets can improve the target-language SRL performances significantly.

Human visual attention is a complex phenomenon. A computational modeling of this phenomenon must take into account where people look in order to evaluate which are the salient locations (spatial distribution of the fixations), when they look in those locations to understand the temporal development of the exploration (temporal order of the fixations), and how they move from one location to another with respect to the dynamics of the scene and the mechanics of the eyes (dynamics). State-of-the-art models focus on learning saliency maps from human data, a process that only takes into account the spatial component of the phenomenon and ignore its temporal and dynamical counterparts. In this work we focus on the evaluation methodology of models of human visual attention. We underline the limits of the current metrics for saliency prediction and scanpath similarity, and we introduce a statistical measure for the evaluation of the dynamics of the simulated eye movements. While deep learning models achieve astonishing performance in saliency prediction, our analysis shows their limitations in capturing the dynamics of the process. We find that unsupervised gravitational models, despite of their simplicity, outperform all competitors. Finally, exploiting a crowd-sourcing platform, we present a study aimed at evaluating how strongly the scanpaths generated with the unsupervised gravitational models appear plausible to naive and expert human observers.

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.

Finding a good regularization parameter for Tikhonov regularization problems is a though yet often asked question. One approach is to use leave-one-out cross-validation scores to indicate the goodness of fit. This utilizes only the noisy function values but, on the downside, comes with a high computational cost. In this paper we present a general approach to shift the main computations from the function in question to the node distribution and, making use of FFT and FFT-like algorithms, even reduce this cost tremendously to the cost of the Tikhonov regularization problem itself. We apply this technique in different settings on the torus, the unit interval, and the two-dimensional sphere. Given that the sampling points satisfy a quadrature rule our algorithm computes the cross-validations scores in floating-point precision. In the cases of arbitrarily scattered nodes we propose an approximating algorithm with the same complexity. Numerical experiments indicate the applicability of our algorithms.

Asymptotic expansions are derived for eigenvalues produced by both the Crouzeix-Raviart element and the enriched Crouzeix--Raviart element. The expansions are optimal in the sense that extrapolation eigenvalues based on them admit a fourth order convergence provided that exact eigenfunctions are smooth enough. The major challenge in establishing the expansions comes from the fact that the canonical interpolation of both nonconforming elements lacks a crucial superclose property, and the nonconformity of both elements. The main idea is to employ the relation between the lowest-order mixed Raviart--Thomas element and the two nonconforming elements, and consequently make use of the superclose property of the canonical interpolation of the lowest-order mixed Raviart--Thomas element. To overcome the difficulty caused by the nonconformity, the commuting property of the canonical interpolation operators of both nonconforming elements is further used, which turns the consistency error problem into an interpolation error problem. Then, a series of new results are obtained to show the final expansions.

We design and implement the first private and anonymous decentralized crowdsourcing system ZebraLancer, and overcome two fundamental challenges of decentralizing crowdsourcing, i.e., data leakage and identity breach.

First, our outsource-then-prove methodology resolves the tension between the blockchain transparency and the data confidentiality to guarantee the basic utilities/fairness requirements of data crowdsourcing, thus ensuring: (i) a requester will not pay more than what data deserve, according to a policy announced when her task is published via the blockchain; (ii) each worker indeed gets a payment based on the policy, if he submits data to the blockchain; (iii) the above properties are realized not only without a central arbiter, but also without leaking the data to the open blockchain. Second, the transparency of blockchain allows one to infer private information about workers and requesters through their participation history. Simply enabling anonymity is seemingly attempting but will allow malicious workers to submit multiple times to reap rewards. ZebraLancer also overcomes this problem by allowing anonymous requests/submissions without sacrificing accountability. The idea behind is a subtle linkability: if a worker submits twice to a task, anyone can link the submissions, or else he stays anonymous and unlinkable across tasks. To realize this delicate linkability, we put forward a novel cryptographic concept, i.e., the common-prefix-linkable anonymous authentication. We remark the new anonymous authentication scheme might be of independent interest. Finally, we implement our protocol for a common image annotation task and deploy it in a test net of Ethereum. The experiment results show the applicability of our protocol atop the existing real-world blockchain.

The patterns in which the syntax of different languages converges and diverges are often used to inform work on cross-lingual transfer. Nevertheless, little empirical work has been done on quantifying the prevalence of different syntactic divergences across language pairs. We propose a framework for extracting divergence patterns for any language pair from a parallel corpus, building on Universal Dependencies. We show that our framework provides a detailed picture of cross-language divergences, generalizes previous approaches, and lends itself to full automation. We further present a novel dataset, a manually word-aligned subset of the Parallel UD corpus in five languages, and use it to perform a detailed corpus study. We demonstrate the usefulness of the resulting analysis by showing that it can help account for performance patterns of a cross-lingual parser.

Cassava a major food crop in many parts of Africa, has majorly been affected by Cassava Brown Streak Disease (CBSD). The disease affects tuberous roots and presents symptoms that include a yellow/brown, dry, corky necrosis within the starch-bearing tissues. Cassava breeders currently depend on visual inspection to score necrosis in roots based on a qualitative score which is quite subjective. In this paper we present an approach to automate root necrosis scoring using deep convolutional neural networks with semantic segmentation. Our experiments show that the UNet model performs this task with high accuracy achieving a mean Intersection over Union (IoU) of 0.90 on the test set. This method provides a means to use a quantitative measure for necrosis scoring on root cross-sections. This is done by segmentation and classifying the necrotized and non-necrotized pixels of cassava root cross-sections without any additional feature engineering.

Most studies on speaker verification systems focus on long-duration utterances, which are composed of sufficient phonetic information. However, the performances of these systems are known to degrade when short-duration utterances are inputted due to the lack of phonetic information as compared to the long utterances. In this paper, we propose a method that compensates for the performance degradation of speaker verification for short utterances, referred to as "crop aggregating". The proposed method adopts an ensemble-based design to improve the stability and accuracy of speaker verification systems. The proposed method segments an input utterance into several short utterances and then aggregates the segment embeddings extracted from the segmented inputs to compose a speaker embedding. Then, this method simultaneously trains the segment embeddings and the aggregated speaker embedding. In addition, we also modified the teacher-student learning method for the proposed method. Experimental results on different input duration using the VoxCeleb1 test set demonstrate that the proposed technique improves speaker verification performance by about 45.37% relatively compared to the baseline system with 1-second test utterance condition.

Person re-identification (re-ID) remains challenging in a real-world scenario, as it requires a trained network to generalise to totally unseen target data in the presence of variations across domains. Recently, generative adversarial models have been widely adopted to enhance the diversity of training data. These approaches, however, often fail to generalise to other domains, as existing generative person re-identification models have a disconnect between the generative component and the discriminative feature learning stage. To address the on-going challenges regarding model generalisation, we propose an end-to-end domain adaptive attention network to jointly translate images between domains and learn discriminative re-id features in a single framework. To address the domain gap challenge, we introduce an attention module for image translation from source to target domains without affecting the identity of a person. More specifically, attention is directed to the background instead of the entire image of the person, ensuring identifying characteristics of the subject are preserved. The proposed joint learning network results in a significant performance improvement over state-of-the-art methods on several benchmark datasets.

Inspired by Bitcoin, many different kinds of cryptocurrencies based on blockchain technology have turned up on the market. Due to the special structure of the blockchain, it has been deemed impossible to directly trade between traditional currencies and cryptocurrencies or between different types of cryptocurrencies. Generally, trading between different currencies is conducted through a centralized third-party platform. However, it has the problem of a single point of failure, which is vulnerable to attacks and thus affects the security of the transactions. In this paper, we propose a distributed cryptocurrency trading scheme to solve the problem of centralized exchanges, which can achieve trading between different types of cryptocurrencies. Our scheme is implemented with smart contracts on the Ethereum blockchain and deployed on the Ethereum test network. We not only implement transactions between individual users, but also allow transactions between multiple users. The experimental result proves that the cost of our scheme is acceptable.

March is obviously going to be the busiest month for any purveyor of traditional Irish music, and with St. Patrick's Day right around the corner, Spokane's Floating Crowbar has multiple gigs crowding the week's calendar.…

A library of macrocyclic compounds of the formula (I) where part (A) is a bivalent radical, a —(CH2)y— bivalent radical or a covalent bond;where part (B) is a bivalent radical, a —(CH2)z— bivalent radical, or a covalent bond;where part (C) is a bivalent radical, a —(CH2)t— bivalent radical, or a covalent bond; andwhere part (T) is a —Y-L-Z— radical wherein Y is CH2 or CO, Z is NH or O and L is a bivalent radical. These compounds are useful for carrying out screening assays or as intermediates for the synthesis of other compounds of pharmaceutical interest. A process for the preparation of these compounds in a combinatorial manner, is also disclosed.

Provided are an anti-static and anti-microbial surface treatment agent including a quaternary ammonium salt compound as an active ingredient and a method of preventing a polymer fiber from developing static electricity by using the surface treatment agent. The quaternary ammonium salt compound has excellent anti-static and anti-microbial effects for the prevention or improvement of static electricity in a polymer fiber. Accordingly, the quaternary ammonium salt compound is suitable for use as a fabric softener, or an anti-static agent, and also, provides anti-microbial effects to a polymer fiber.

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.

Various embodiments provide lossless compression of an enumeration space for genetic founder lines. In one embodiment, an input comprising a set of genetic founder lines and a maximum number of generations G is obtained. A set of genetic crossing templates of a height h is generated. A determination is made if at least a first genetic crossing template in the set of genetic crossing templates is redundant with respect to a second genetic crossing template in the set of genetic crossing templates. Based on the at least first genetic crossing template being redundant is redundant with respect to the second genetic crossing template, the at least first genetic crossing template is removed from the set of genetic crossing templates. This process of removing the at least first genetic crossing template from the set of genetic crossing templates the redundant creates an updated set of genetic crossing templates.

Methods of separating renewable materials, such as lipids, from microorganisms, such as oleaginous yeasts, may include conditioning cell walls of the microorganisms to form, open or enlarge pores, and removing at least a portion of the renewable material through the pores. These methods may result in delipidated microorganisms with cell walls that are substantially intact and with mesopores. These delipidated microorganisms may be used to produce biofuels.

Disclosed is a process for reducing the amount of sterol in a sterol-containing microbial oil composition, including distilling, under short path distillation conditions, a sterol-containing microbial oil wherein said distillation produces a distillate fraction containing the sterol and a triacylglycerol-containing fraction having a reduced amount of the sterol when compared to the amount of sterol in the sterol-containing microbial oil composition that has not been subjected to short path distillation.

Disclosed are oil-extended olefin block copolymer compositions with microcrystalline wax. The microcrystalline wax reduces oil-bleed while maintaining composition softness.

Water-borne cross-linking polymeric compositions and related embodiments, such as methods of making and using the compositions, as well as products formed with said compositions are described. The water-borne composition may comprise one or more polymers formulated from one or more monomers of which at least one is a monomer that yields acetaldehyde as a hydrolysis product, and incorporating cross-linking functionality such as, but not limited to, carbonyl or epoxy functionality, and a blocked cross-linking agent, for example, a hydrazone. Neither the cross-linking functionality nor the acetaldehyde reacts with the blocked cross-linking agent; however, the blocked cross-linking agent is capable of conversion to an alternative form cross-linking agent such as, but not limited to, a hydrazide, to yield a cross-linked polymer. The alternative form cross-linking agent may be formed in an equilibrium reaction including the blocked cross-linking agent.

An aqueous dispersion includes particles at least partially encapsulated in a microgel where the microgel is prepared from a hyperbranched acrylic polymer. In addition, a method for making an aqueous dispersion includes: (1) mixing in an aqueous medium: (a) particles, (b) at least one ethylenically unsaturated monomer, and (c) a water-dispersible hyperbranched acrylic polymer having ethylenic unsaturation; and (2) polymerizing the at least one ethylenically unsaturated monomer and water-dispersible hyperbranched acrylic polymer having ethylenic unsaturation to at least partially encapsulate the particles in a microgel.

A method for manufacturing a plurality of glass microspheres comprises: melting a batch into a first glass melt in a melter system, processing the first glass melt into a second glass, pulverizing the second glass into a plurality of glass fragments, thermally processing the plurality of glass fragments into a plurality of glass microspheres, providing at least one of a plurality of redox reactions and a plurality of events in at least one of the first glass melt and a melt of the second glass, and the plurality of redox reactions and the plurality of events are induced by a plurality of redox active group (RAG) components.

Temperatures in microelectronic integrated circuit packages and components may be measured in situ using carbon nanotube networks. An array of carbon nanotubes strung between upstanding structures may be used to measure local temperature. Because of the carbon nanotubes, a highly accurate temperature measurement may be achieved. In some cases, the carbon nanotubes and the upstanding structures may be secured to a substrate that is subsequently attached to a microelectronic package.

A random number generation method and apparatus using a low-power microprocessor is provided. In the random number generation method, a low-power microprocessor determines whether external power is supplied to a random number generator. The low-power microprocessor updates an internal state of the random number generator based on a first scheme if it is determined that the external power is supplied to the random number generator. The low-power microprocessor updates the internal state of the random number generator based on a second scheme different from the first scheme if it is determined that the external power is not supplied to the random number generator.

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.

A crosslinkable curing super-branched polyester and the cured product and the preparation method thereof are disclosed. The super-branched polyester has high refractive index and comprises a compound represented by the following structural formula (I). In the formula (I), HBP is the backbone of the super-branched polyester; both a and b are positive integers; the sum of a and b is less than or equal to n; n is more than or equal to 10 and less than 80. In the super-branched polyester, A is represented by formula (II) and N is represented by formula (III), wherein R is methyl or hydrogen atom; the mole ratio of N relative to the total mole of A and N is more than 30 mol %, and the ratio of the total mole of A and N relative to the product of the total mole of HBP backbone and n is more than 0.5 and less than or equal to 1.

The present disclosure provides a method of providing an adhesive composition comprising the steps of combining crosslinkable composition including: a) a (meth)acryloyl monomer mixture with the b) photocrosslinking agent mixture, and irradiating with UVC radiation to polymerize and crosslink the composition.