Predetermined Structures Research Articles

Bayesian tensor network structure search and its application to tensor completion

Tensor network (TN) has demonstrated remarkable efficacy in the compact representation of high-order data. In contrast to the TN methods with pre-determined structures, the recently introduced tensor network structure search (TNSS) methods automatically learn a compact TN structure from the data, gaining increasing attention. Nonetheless, TNSS requires time-consuming manual adjustments of the penalty parameters that control the model complexity to achieve better performance, especially in the presence of missing or noisy data. To provide an effective solution to this problem, in this paper, we propose a parameters tuning-free TNSS algorithm based on Bayesian modeling, aiming at conducting TNSS in a fully data-driven manner. Specifically, the uncertainty in the data corruption is well-incorporated in the prior setting of the probabilistic model. For TN structure determination, we reframe it as a rank learning problem of the fully-connected tensor network (FCTN), integrating the generalized inverse Gaussian (GIG) distribution for low-rank promotion. To eliminate the need for hyperparameter tuning, we adopt a fully Bayesian approach and propose an efficient Markov chain Monte Carlo (MCMC) algorithm for posterior distribution sampling. Compared with the previous TNSS method, experiment results demonstrate the proposed algorithm can effectively and efficiently find the latent TN structures of the data under various missing and noise conditions and achieves the best recovery results. Furthermore, our method exhibits superior performance in tensor completion with real-world data compared to other state-of-the-art tensor-decomposition-based completion methods.

Complementarity and Preorganisation in the Assembly of Heterometallic–Organic Cages via the Metalloligand Approach—Recent Advances

The design of new metallocage polyhedra towards pre-determined structures can offer both practical as well as intellectual challenges. In this mini-review we discuss a selection of recent examples in which the use of the metalloligand approach has been employed to overcome such challenges. An attractive feature of this approach is its stepwise nature that lends itself to the design and rational synthesis of heterometallic metal–organic cages, with the latter often associated with enhanced functionality.

Lemonade as a rich source of antioxidants: Polymerization of 2-(dimethylamino)ethyl methacrylate in lemon extract

Controlled radical polymerization techniques have become increasingly widespread in the interdisciplinary space of polymer chemistry for receiving predetermined structures designed for specific applications. In this contribution, the freshly squeezed lemon extract was used for the polymerization of 2-(dimethylamino)ethyl methacrylate (DMAEMA) by activators regenerated by electron transfer atom transfer radical polymerization (ARGET ATRP) concept at ambient conditions in an air atmosphere. Lemon extract is a rich source of many bioactive compounds that can play a role of reducing agents in ATRP, e.g. ascorbic acid (vitamin C) or citric acid. Therefore lemon extract-accelerated ARGET ATRP provided well-defined PDMAEMA structures, accelerating the polymerization about 3–4 times compared to syntheses in water. The chain extension experiment confirmed the preserved chain-end functionality of prepared PDMAEMA. The proposed concept can be scaled up for the industry due to (a) a facile reaction setup that does not need degassing or heating – the polymerization at room temperature in open to air conditions, hence the use of a readily available reactor is sufficient, (b) no need to use laboratory-grade chemical reducing agents because of their high content in lemon extract, (c) the synthesis in the environmentally-friendly aqueous reaction medium, (d) very low catalyst concentration in the reaction mixture. • Lemon extract is a reach source of reducing agents for ARGET ATRP concept. • Polymerization of DMAEMA in freshly squeezed lemon extract. • ARGET ATRP in lemon extract accelerates the polymerization of DMAEMA compared to synthesis in water. • A reaction setup for polymerization of DMAEMA that can be easily scalable for industrial application.

Network Structure Impacts the Synchronization of Collective Beliefs

Abstract People’s beliefs are influenced by interactions within their communities. The propagation of this influence through conversational social networks should impact the degree to which community members synchronize their beliefs. To investigate, we recruited a sample of 140 participants and constructed fourteen 10-member communities. Participants first rated the accuracy of a set of statements (pre-test) and were then provided with relevant evidence about them. Then, participants discussed the statements in a series of conversational interactions, following pre-determined network structures (clustered/non-clustered). Finally, they rated the accuracy of the statements again (post-test). The results show that belief synchronization, measuring the increase in belief similarity among individuals within a community from pre-test to post-test, is influenced by the community’s conversational network structure. This synchronization is circumscribed by a degree of separation effect and is equivalent in the clustered and non-clustered networks. We also find that conversational content predicts belief change from pre-test to post-test.

DNA self-organization controls valence in programmable colloid design

Just like atoms combine into molecules, colloids can self-organize into predetermined structures according to a set of design principles. Controlling valence-the number of interparticle bonds-is a prerequisite for the assembly of complex architectures. The assembly can be directed via solid "patchy" particles with prescribed geometries to make, for example, a colloidal diamond. We demonstrate here that the nanoscale ordering of individual molecular linkers can combine to program the structure of microscale assemblies. Specifically, we experimentally show that covering initially isotropic microdroplets with N mobile DNA linkers results in spontaneous and reversible self-organization of the DNA into Z(N) binding patches, selecting a predictable valence. We understand this valence thermodynamically, deriving a free energy functional for droplet-droplet adhesion that accurately predicts the equilibrium size of and molecular organization within patches, as well as the observed valence transitions with N Thus, microscopic self-organization can be programmed by choosing the molecular properties and concentration of binders. These results are widely applicable to the assembly of any particle with mobile linkers, such as functionalized liposomes or protein interactions in cell-cell adhesion.

Dynamic Exciton Funneling by Local Strain Control in a Monolayer Semiconductor.

The ability to control excitons in semiconductors underlies numerous proposed applications, from excitonic circuits to energy transport. Two dimensional (2D) semiconductors are particularly promising for room-temperature applications due to their large exciton binding energy and enormous stretchability. Although the strain-induced static exciton flux has been observed in predetermined structures, dynamic control of exciton flux represents an outstanding challenge. Here, we introduce a method to tune the bandgap of suspended 2D semiconductors by applying a local strain gradient with a nanoscale tip. This strain allows us to locally and reversibly shift the exciton energy and to steer the exciton flux over micrometer-scale distances. We anticipate that our result not only marks an important experimental tool but will also open a broad range of new applications from information processing to energy conversion.

Solid-Phase Radical Polymerization of Halogen-Bond-Based Crystals and Applications to Pre-Shaped Polymer Materials.

Liquid vinyl monomers were converted into solid crystals via halogen bonding. They underwent solid-phase radical polymerizations through heating at 40 °C or ultraviolet photo-irradiation (365 nm). The X-ray crystallography analysis showed the high degree of monomer alignment in the crystals. The polymerizations of the solid monomer crystals yielded polymers with high molecular weights and relatively low dispersities because of the high degree of the monomer alignment in the crystal. As a unique application of this system, the crystalized monomers were assembled to pre-determined structures, followed by solid-phase polymerization, to obtain a two-layer polymer sheet and a three-dimensional house-shaped polymer material. The two-layer sheet contained a unique asymmetric pore structure and exhibited a solvent-responsive shape memory property and may find applications to asymmetric membranes and polymer actuators.

Low-Latency Data Aggregation Scheduling for Cognitive Radio Networks With Non-Predetermined Structure

Data aggregation is a fundamental yet popular operation in wireless networks where the sink needs to obtain the combined information of the whole network. However, the problem of minimum latency aggregation scheduling (MLAS) is not well studied in cognitive radio networks. Few studies have addressed this issue and most previous aggregation methods all assume that a fixed-structure based aggregation tree is constructed in advance, which may result in the selection of a node with limited spectrum opportunities as the parent by many nodes and by extension results in a large latency. Thus, the MLAS problem in cognitive radio networks (MLAS-CR) without the above limitation is investigated in this paper. First, the MLAS-CR problem with primary social behaviors where the activity of primary users can be predicted is studied. To make full use of the limited spectrum opportunities, we integrate the construction of the aggregation tree, and the computation of a conflict-free schedule simultaneously, without any predetermined structures. Second, the MLAS-CR problem without the above assumption is also investigated. To reduce the latency, a two-way aggregation scheduling method is proposed to adaptively choose the parent with only current channel information. To further reduce the latency, we also introduce a new data aggregation mode for CRN, i.e., Data Aggregation Scheduling in The Dark, to utilize the spectrum opportunities of scheduled nodes. Finally, the theoretical analysis and simulation results verify that the proposed algorithms have high performance in terms of latency.

Organoselenium chemistry-based polymer synthesis

Novel synthesis of selenium containing polymers with pre-determined structures and applications thereof.

HARDWARE-SOFTWARE PLATFORM OF INDUSTRIAL MONITORING

The paper describes basic requirements for a modern supervisory control and data acquisition system (SCADA), in particular for monitoring systems of complex industrial facilities. It is known that many robotic processes require non‑destructive testing with pattern recognition elements within a common monitoring system. On the widely used GENESIS64 SCADA example, it is considered a solution based on the hardware and software platform RT -XDC of RASTER TECHNOLOGY digital cameras, allowing to integrate into the system of this class any set of complex sensors such as digital cameras that support standard interfaces, built -in processing and data analysis. In addition, it is proposed the hierarchical model of complex objects monitoring and the universal way of its representation on the Moscow metro station network example, which includes four levels: the model map level, the model level, the model objects level and the level of their attributes. The considered data structure, which have to operate in solving the common monitoring task, make a choice in favor of object -oriented databases application like IPR, used in Delta Design CAD. The results were obtained during the development of experimental software that allows visualizing 3D models and displaying information about the selected object in the form of any predetermined structures.

4D Printing: The Shape-Morphing in Additive Manufacturing.

3D printing of polymers can now be considered as a common processing technology for the development of biomaterials. These can be constituted out of polymeric abiotic material alone or can be co-printed with living cells. However, the adaptive and shape-morphing characteristics cannot be developed with the rigid, pre-determined structures obtained by 3D printing. In order to produce functional engineered biomaterials, the dynamic properties/characteristics of the living cells must be attained. 4D printing can be envisaged as a route to achieve these goals. This paper intends to give a brief review of the pioneer 4D printing research that has been developed and to present an insight into future research in this field.

Computer-aided design of amino acid-based therapeutics: a review.

During the last two decades, the pharmaceutical industry has progressed from detecting small molecules to designing biologic-based therapeutics. Amino acid-based drugs are a group of biologic-based therapeutics that can effectively combat the diseases caused by drug resistance or molecular deficiency. Computational techniques play a key role to design and develop the amino acid-based therapeutics such as proteins, peptides and peptidomimetics. In this study, it was attempted to discuss the various elements for computational design of amino acid-based therapeutics. Protein design seeks to identify the properties of amino acid sequences that fold to predetermined structures with desirable structural and functional characteristics. Peptide drugs occupy a middle space between proteins and small molecules and it is hoped that they can target “undruggable” intracellular protein–protein interactions. Peptidomimetics, the compounds that mimic the biologic characteristics of peptides, present refined pharmacokinetic properties compared to the original peptides. Here, the elaborated techniques that are developed to characterize the amino acid sequences consistent with a specific structure and allow protein design are discussed. Moreover, the key principles and recent advances in currently introduced computational techniques for rational peptide design are spotlighted. The most advanced computational techniques developed to design novel peptidomimetics are also summarized.

DNA Directed Self-Assembly of Single Walled Carbon Nanotubes into Three-Way Junction Nanostructures.

Utilization of a self-assembled two-dimensional DNA nanostructure to arrange single-walled carbon nanotubes (SWNTs) into predetermined structures at controllable angles is presented. A specially designed DNA three-way junction (3WJ) composed of three double-stranded DNA arms containing single-stranded overhang sequences was prepared by annealing of partially complementary ssDNA sequences and ultrasonicated with SWNTs, resulting in DNA-3WJ/SWNT hybrid nanostructures. Utilization of DNA-3WJ not only allowed the precise dispersion of SWNTs but also acted as a rigid template for the self-assembly of SWNTs into three-armed junctions at an angle of approximately 120° to each other as visualized by scanning electron microscopy and atomic force microscopy. Prepared DNA-3WJ/SWNT nanostructures were also demonstrated to have the appropriate binding sites for fluorophores, providing a simple method for the fluorescent labeling of SWNTs. When ssDNA sequences forming the DNA-3WJ are ultrasonicated with SWNTs, followed by annealing of resulting ssDNA wrapped SWNTs, instead of hybrid junctions composed of three SWNT molecules, a web-like structure composed of interconnected SWNT junctions was obtained. The design approaches demonstrated here provide simple methods for the arrangement of SWNTs into desired nanostructures utilizing pre-assembled DNA nanostructures as linkers in aqueous solution through noncovalent interactions which can greatly contribute to efforts along the controlled assembly of SWNTs.

Recommendations for mRNA analysis of micro-dissected glomerular tufts from paraffin-embedded human kidney biopsy samples

BackgroundGlomeruli are excellent pre-determined natural structures for laser micro-dissection. Compartment-specific glomerular gene expression analysis of formalin-fixed paraffin-embedded renal biopsies could improve research applications. The major challenge for such studies is to obtain good-quality RNA from small amounts of starting material, as applicable for the analysis of glomerular compartments. In this work, we provide data and recommendations for an optimized workflow of glomerular mRNA analysis.ResultsWith a proper resolution of the camera and screen provided by the next generation of micro-dissection systems, we are able to separate parietal epithelial cells from glomerular tufts. Selected compartment-specific transcripts (WT1 and GLEPP1 for glomerular tuft as well as PAX2 for parietal epithelial cells) seem to be reliable discriminators for these micro-dissected glomerular substructures. Using the phenol–chloroform extraction and hemalaun-stained sections (2 µm), high amounts of Bowman’s capsule transections (> 300) reveal sufficient RNA concentrations (> 300 ng mRNA) for further analysis. For comparison, in unstained sections from a number of 60 glomerular transections upwards, a minimum amount of 157 ng mRNA with a reasonable mRNA purity [A260/A280 ratio of 1.5 (1.4/1.7) median (25th/75th percentiles)] was reversely transcribed into cDNA. Comparing the effect of input RNA (20, 60, 150 and 300 micro-dissected glomerular transections), transcript expression of POLR2A significantly correlated when 60 and 150 laser micro-dissected glomerular transections were used for analysis. There was a lower inter-assay coefficient of variability for ADAMTS13, when at least 60 glomerular transections were used. According to the algorithms of geNormPlus and NormFinder, PGK1 and PPIA are more stable glomerular reference transcripts compared to GUSB, GAPDH, POLR2A, RPLPO, TBP, B2M, ACTB, 18SrRNA and HMBS.ConclusionsOur approach implements compartment-specific glomerular mRNA expression analysis into research applications, even regarding glomerular substructures like parietal epithelial cells. We recommend using of at least 60 micro-dissected unstained glomerular or 300 hemalaun-stained Bowman’s capsule transections to obtain sufficient input mRNA for reproducible results. Hereby, the range of RNA concentrations in 60 micro-dissected glomeruli is low and appropriate normalization of Cq values using our suggested reference transcripts (PGK1 and PPIA) allows compensation with respect to different amounts of RNA purity and quantity.

Film Writing Adapted for Game Narrative: Myth or Error?

Film Writing Adapted for Game Narrative: Myth or Error?

Prediction of surface topography due to finite pixel spacing in FIB milling of rectangular boxes and trenches

For applying focused ion beam technologies in fabrication of the predetermined structures it is essential to evaluate the ion dose delivered to the specimen by the beam and on this basis to predict the formed topography. In this article the authors obtain exact expressions for the ion dose distribution arising in the irradiated region when trenches and rectangular boxes are milled. Based on them the authors describe the surface shape of the structures under consideration when the constant sputtering yield conditions are realized during the milling process. The rather cumbersome analytical description can be transformed into the simple form for milled regions at the distance slightly exceeding the beam diameter from the structure boundaries. Within this region the milled surface shape can be represented as a sum of sinusoidal functions analogous to one- or two-dimensional Fourier series. For typical structure fabrication when the distance between neighboring beam stops is less than approximately two beam diameters the authors derive simple formulas for evaluating the mean depth and the peak-to-valley surface roughness. The authors also estimate when constant sputtering yield conditions can be utilized for the description of the actual milling process. To testify the theoretical considerations two trenches and four rectangular boxes were prepared. In addition, several deep and shallow dotlike structures were created for evaluating the ion flux density determining the beam shape, which was presented as the sum of two Gaussian functions. Peripheral regions of the deep dots cross-sections allow us to find the standard deviation of the second Gaussian function while the standard deviation of the first Gaussian function and the weight factor are retrieved using the milling profiles of the shallow dots. A set of parameters describing the ion flux density of the beam and milling process enables calculating the surface shapes and cross-sectional profiles of the fabricated structures. The authors show that the simulated shapes of the trench and the box and scanning electron microscope images of these structures are similar in appearance. Comparison of experiment and theoretical milling profiles demonstrates good agreement between them. Theoretically estimated mean depth and peak-to-valley surface roughness are consistent with experimental data.

Oznog the great and powerful

ABSTRACTI am an American gay pornographer. That is the lens through which I see and understand things. For both straight and gay males, the sex in pornography is meaningful to the extent that it works against the predetermined structures associated with ‘functional’ sex. While there are similarities in the behaviours of gay and straight males in porn sex, the meanings of the specific syllabic gestures of the sex are different. For straight men, the allure of unfettered, unlimited sex derives from the fact that each heterosexual man exists in society as a proxy for the children he may generate. For gay men, sex is devoid of this generative remove. In this Forum piece I examine the ways in which queer porn functions by arousing the viewer, and then presenting behaviours, institutions and ideas with which the viewer can identify.

A semantic RBM-based model for image set classification

Most existing image set classification methods use either appearance variations or temporal information to represent semantic knowledge (relationships) and subject appearance. Such methods usually rely on a predetermined surface structures that the image sets could lie on, and/or are highly influenced by the temporal correlations between images within the image sets. In contrast, this paper introduces a novel RBM-based model which is capable of combining both, appearance variations and temporal information within image sets, to provide an automated and robust representation of semantic knowledge and subject appearance even with small image sets with weak temporal correlations. The structure of the proposed model involves two hidden sets which are used to encode different feature types. The first hidden set is used to represent the dominant appearances (facial features) from appearance variations, while the second set is used to represent the temporal information between different appearances. An extension of the standard Constructive Divergence algorithm is proposed to learn the proposed model encoding two different feature types simultaneously, while isolating them from each other. The proposed model was evaluated for the task of face recognition, using two datasets, namely UCSD/Honda and YouTube Celebrities. The results show superior performance compared to state-of-the-art methods.

Using Varian’s Eclipse Scripting API to Calculate, Add, and Report Biologically Equivalent Doses for Gynecological Brachytherapy and External Beam Radiation Therapy Patients

Standard procedure adopted by our institution involves generating post treatment reports for all gynecological patients receiving brachytherapy. These reports tabulate physical doses, biological effective doses (BED), and biological equivalent doses (EQD2) for two Gray fractionation schemes to the high risk clinical target volume (HRCTV), intermediate risk clinical target volume (IRCTV), bladder, rectum, sigmoid, bowel, and vagina. All doses are reported following ABS guidelines for cervical cancers. These metrics were previously read individually from the dose volume histogram and dose statistics tab and charted one by one in a spreadsheet which was uploaded to the patient’s electronic chart. To streamline data collection and metric calculation for reporting after treatment and to better inform on cumulative doses for treatments in progress, an integrated script within Varian’s Brachytherapy Planning (Varian Medical Systems, Palo Alto, CA) was developed using the Eclipse Scripting Application Programming Interface (ESAPI). ESAPI was used in conjunction with Microsoft Virtual Studio (Microsoft Corporation, Redmond, WA) to write a script that can be called within the Eclipse External Beam Planning or Brachytherapy Planning user interfaces. The script queries all external beam and brachytherapy plans within an opened course to return the physical dose and calculate the biological effective and biological equivalent doses for seven pre-determined structures. The values returned are consistent with the reporting values used in the ABS guidelines for cervical cancers. While all plans within a course are included in the totals, the option to exclude specific plans or add in additional dose from external beam radiation therapy can be added for improved usability depending on the clinic’s desired use and implementation of the script. The development of an integrated script within the treatment planning interface allows for efficient dose recording for brachytherapy patients. In addition, the ease of use also allows for tracking dosimetric progress during the boosted brachytherapy course of treatment. This allows for adapting the brachytherapy plans to meet the desired objectives and dose constraints. Use of the script allows for an overall more streamlined approach to our clinical procedures of reporting doses in gynecological brachytherapy patients while minimizing the potential for errors in using multistep approach of entering metrics by hand. Adaptations and implementations of the script will be extended to external beam radiation therapy gynecological clinical protocols in place at our institution.

Stability of gluten free sweet biscuit elaborated with rice bran, broken rice and okara

A challenge to the food sector has been the development of new products incorporating co-products from the food processing industry with minimal impact on their pre-determined structures and adding nutritional quality. In order to add value and develop alternatives for the use of co-products generated during the agroindustrial processing, this work aimed to study the stability of gluten-free sweet biscuits developed with soybean okara, rice bran and broken rice. The formulations were elaborated with increasing percentages of these ingredients and compared with the standard (commercial sweet biscuit) for ten months. The analyses were: weight, diameters (internal and external), thickness, specific volume, instrumental parameters of color, texture, scanning electron microscopy, water activity, proximal composition and isoflavones. The experimental sweet biscuits had characteristics of color, weight, volume and diameters (internal and external) very similar to the commercial, whereas texture, lipids and energy value decreased, and aw, moisture and protein increased during storage. The sweet biscuits showed the same stability when compared to the standard, and the