Components Of Different Sizes Research Articles

Epidemic spreading on spatial higher-order network

Higher-order interactions exist widely in mobile populations and are extremely important in spreading epidemics, such as influenza. However, research on high-order interaction modeling of mobile crowds and the propagation dynamics above is still insufficient. Therefore, this study attempts to model and simulate higher-order interactions among mobile populations and explore their impact on epidemic transmission. This study simulated the spread of the epidemic in a spatial high-order network based on agent-based model modeling. It explored its propagation dynamics and the impact of spatial characteristics on it. Meanwhile, we construct state-specific rate equations based on the uniform mixing assumption for further analysis. We found that hysteresis loops are an inherent feature of high-order networks in this space under specific scenarios. The evolution curve roughly presents three different states with the initial value change, showing different levels of the endemic balance of low, medium, and high, respectively. Similarly, network snapshots and parameter diagrams also indicate these three types of equilibrium states. Populations in space naturally form components of different sizes and isolations, and higher initial seeds generate higher-order interactions in this spatial network, leading to higher infection densities. This phenomenon emphasizes the impact of high-order interactions and high-order infection rates in propagation. In addition, crowd density and movement speed act as protective and inhibitory factors for epidemic transmission, respectively, and depending on the degree of movement weaken or enhance the effect of hysteresis loops.

Optimization of Runner Balance for a Family Product of Injection Molding Process

A family mold is used in the injection molding process to produce components of different sizes that would normally be assembled into a single product assembly. The uniform quality of each injection molded part is strongly influenced by the filling balance of the mold cavity. The filling balance can be controlled by optimizing the dimensions of runners that are directed towards each cavity. In this paper, an optimization method is proposed that aims at balancing the filling time that maximizes the quality of a family mold cavity. There are two steps proposed in this research, namely theoretical calculations and simulation of runner balanced design using the software. The results of this study can be used as a practical reference in designing a mold for family products to avoid design errors as early as possible. The result obtained from an industrial case study highlighted the effectiveness of the proposed approach in finding the optimal runner dimension by a restricted number of simulations.

Modification of Protein Micelles by Limited Hydrolysis of Peptide Bonds: A Model of the Sequential Degradation of β-Casein Micelles

A model for the degradation of β-casein micelles with the limited hydrolysis of trypsin-specific peptide bonds was proposed. A sequential mechanism of the degradation of micelles and assembly of peptide nanoparticles from the fragments of a β-casein polypeptide chain was considered. The degradation kinetics was studied by numerical modeling, taking into account the formation of intermediate components of different sizes and peptide nanoparticles, which are more difficult to hydrolyze with trypsin. The simulation results are consistent with the experimental data previously obtained by atomic force microscopy, FTIR spectroscopy, and light scattering.

An Efficient Real-Time Algorithm for Placing Electronic Components on Panel

In this paper, we present an industrial challenge faced by electronic component manufacturers. From each order, the components need to be placed on panels for shipping. Panels incur significant costs. To control expenses, companies are compelled to optimize the placement of components on panels. Every day, thousands of orders have to be shipped. For each order, they have to pack between a hundred and a thousand rectangular electronic components of different sizes on panels with specifications such as free component orientation and tight time constraints. This packaging must be optimized to minimize the number of panels used and associated costs. The industrial challenge lies not only in space optimization but also in the speed of the process, with solutions needing to be found in less than a minute to meet the dynamic and continuous demands of production and shipping.

Biomimetic mineralization of positively charged silica nanoparticles templated by thermoresponsive protein micelles: applications to electrostatic assembly of hierarchical and composite superstructures.

High information content building blocks offer a path toward the construction of precision materials by supporting the organization and reconfiguration of organic and inorganic components through engineered functions. Here, we combine thermoresponsiveness with biomimetic mineralization by fusing the Car9 silica-binding dodecapeptide to the C-terminus of the (VPGVG)54 elastin-like polypeptide (ELP). Using small angle X-ray scattering, we show that the short Car9 cationic block is sufficient to promote the conversion of disordered unimers into 30 nm micelles comprising about 150 proteins, 5 °C above the transition temperature of the ELP. While both species catalyze self-limiting silica precipitation, micelles template the mineralization of highly monodisperse (62 nm) nanoparticles, while unimers yield larger polydisperse species. Strikingly, and unlike traditional synthetic silica, these particles exhibit a positive surface charge, likely due to cationic Car9 sidechains projecting from their surface. Capitalizing on the high monodispersity and positive charge of the micelle-templated products, we use smaller silica and gold particles bearing a native negative charge to create a variety of superstructures via electrostatic co-assembly. This simple biomimetic route to positively charged silica eliminates the need for multiple precursors or surface modifications and enables the rapid creation of single-material and composite architectures in which components of different sizes or compositions are well dispersed and integrated.

Piezoresistivity in self-compacting concrete mixes with hybrid additions of carbon fibers and nanofibers

Self-sensing properties of concrete structures can be achieved through the incorporation of additions in carbon-based materials (CBM) that modify electrical properties and provide piezoresistive (PZR) properties to the cement paste. PZR in pastes and mortar mixes with different types of carbon-based materials such as fibers of different sizes has been extensively tested. However, very limited studies on self-sensing properties in concrete are available due to the lower content of paste volume that leads to a decrease of concrete PZR. However, self-compacting concrete (SCC) can be an ideal candidate to implement PZR, due to two fundamental traits: the larger amount of paste of SCC compared to a conventional concrete and larger volumetric fraction of fiber can be incorporated due to a reduced effect on SCC workability and consistency. The present study aims to assess PZR properties of SCC with carbon-based components of different sizes. Combining carbon nanofibers (NFC) and carbon fibers (CF), in hybrid systems, could lead to obtain SCC with self-sensing properties identifying their effectiveness thresholds. The self-detection performance of PZR-SCC samples under mechanical stress was verified by resistivity and PZR experimental tests.

The component counts of random functions

Consider functions f:A→A∪C, where A and C are disjoint finite sets. The weakly connected components of the digraph of such a function are cycles of rooted trees, as in random mappings, and isolated rooted trees. Let n1=|A| and n3=|C|. When a function is chosen from all (n1+n3)n1 possibilities uniformly at random, then we find the following limiting behaviour as n1→∞. If n3=o(n1), then the size of the maximal mapping component goes to infinity almost surely; if n3∼γn1, γ>0 a constant, then process counting numbers of mapping components of different sizes converges; if n1=o(n3), then the number of mapping components converges to 0 in probability. We get estimates on the size of the largest tree component which are of order log⁡n3 when n3∼γn1 and constant when n3∼n1α, α>1. These results are similar to ones obtained previously for random injections, for which the weakly connected components are cycles and linear trees.

Optical efficiency and performance optimization of a two-stage secondary reflection hyperbolic solar concentrator using machine learning

This paper focuses on the geometric analysis of parabolic trough solar collectors (PTCs) with components of different sizes. The concentration ratio of the receiver tube, intercept factor, and optical efficiency are the three main features for PTCs geometric optimization. This study proposes a python-based algorithm for calculating the optical efficiency of PTCs based on a secondary hyperbolic mirror. This algorithm is suitable for writing programs, inputting AutoCAD data into software for simulation of different incident angles and focal lengths of the secondary hyperbolic mirror concentrator, and processing simulation data. The error between the simulated and theoretical optical efficiency results is less than 3.13%. To provide an accurate optical efficiency computing method for geometric designing, energy analyses, and optimizing solar concentration collectors, this paper presents an available method of predicting optical efficiency for solar concentrating design based on machine learning is presented. The optical efficiency was fitted using machine learning approaches numerically with a coefficient of determination (R2 = 0.97874). The optical efficiency fitting formulas for PTCs are generated by analyzing the secondary reflection hyperbolic data of samples computed through a variable reduction technique, while the R2 values are obtained from linear regression. Then the final optical efficiency fitting formula is applied to adequately characterize optical efficiency under different geometrical configurations, incidence angles, and tracking models for the optical and geometrical optimization of PTCs. Data from tests involving the secondary hyperbolic mirror concentrators are used to validate the ray-tracing model and compute optical efficiency based on a secondary reflection hyperbolic mirror.

Production environment of tomorrow (ProMo): Partially automated repair process of small tool moulds, forming tools, injection moulding tools and sand casting tools

Small defects in the grain or major damage to a moulded part or tool can bring production to a standstill. SMEs in particular have neither the personnel nor the equipment to repair such damage on their own, so they send it to specialised contractors. The repair process is carried out manually, depending on the accuracy requirements, and is usually completed by a finishing process. This work requires qualified personnel and, at the same time, requires a lot of time in case of larger damages. In this paper we present a way to map the Maintenance, Repair and Operations (MRO) process chain in a partially automated manner.The symbiosis of individual technologies results in a significantly increased efficiency of the MRO process chain, which continues to focus on people and their process knowledge.While Directed Energy Deposition (DED) for the MRO of moulded parts is used widely, usually a high manual effort in measuring the component geometries and teaching of the machine tool paths is necessary. However, there are clear advantages compared to the manufacture of new parts or manual laser welding repair. At the same time, the resource and energy requirements can often be significantly reduced compared to new part production. Promo focuses on automating the time-consuming machine programming by reducing the number of necessary work steps in CAD/CAM-based program creation.Based on a subsequent robot-guided scan, a digital actual 3D model is generated. Due to intelligent path planning algorithms, no manual programming of the robot is necessary and at the same time it is possible to detect components of different sizes, shapes and covers in this system with a minimum of effort. In addition, the operator passes on elementary information, such as the approach path of the milling head, to the subsequent processes by means of finger gestures and can thus significantly reduce tedious CAM programming steps. Now, the scanned component is transferred to a 3D-CAD model and a target/actual comparison is created for the damaged areas. Those are milled out in a defined manner and then restored using DED.

Влияние дополнительных иерархических уровней на рабочие характеристики распределенных моделей

In designing modern computer equipment and digital electronics, the use of simulation models is of great importance. At first, monolithic models were widely used for this. However, they worked well only when their size was relatively small. Because of it developers began to refuse gradually use of monolithic models and to pass to use of the distributed models allowing to increase their speed and to expand borders of their admissible sizes. At the same time, they begin to pay special attention to hierarchical distributed models, which provide the opportunity to investigate the behavior of the created devices at different levels of detail. Similar models made it possible to noticeably expand the permissible boundaries of their sizes and increase the speed of work. However, such distributed models have the disadvantage that their effectiveness is noticeably dependent not only on the number of components included in their composition, but also on the size of these components. he paper presents the results of a study of the effect of introducing an additional upper hierarchical level on the performance of distributed models based on Petri networks. The use of such a method of modifying distributed models leads to an increase in their speed in a wide range of changes in their sizes. At the same time, the most significant effect achieved in distributed models containing a large number of small components. The maximum speed of the thus modified models can be an order of magnitude higher than that of the non-modified ones. As a result, in addition to the overall increase in the efficiency of the modified hierarchical distributed models, this also led to a significant equalization of the performance of the modified distributed models with subordinate components of different sizes.

Full on-line preparation of polymer composites reinforced with aligned carbon nanotubes

Carbon nanotubes (CNTs) reinforced composite materials have been widely studied, but the long-standing technical issues with poor dispersion, low CNT content, and low CNT alignment remain to be solved. In this study, a CNT/polymer composite material is prepared by continuously winding a highly aligned CNT assembly with the polymer resin introduced and cured on-line. CNTs are mixed with the resin at the molecular level, and their alignment is maintained. Effects of critical experimental parameters such as winding rate, curing temperature, and curing time are studied. Under optimal conditions, the composite material with a high CNT content of 65 wt% exhibits a high tensile strength of 751 MPa and elongation at break of 6%. All the preparation processes are completed in air and on line without any post off-line processing as involved in previous conventional techniques. Therefore, this study provides a new strategy for manufacturing cost-effective composite materials in large scale and structural components of different sizes for wide applications.

Comparisons of Multi-State Systems with Binary Components of Different Sizes

The system signatures of multi-state coherent or mixed systems with i.i.d. (independent and identically distributed) binary-state components are considered in this paper. For any multi-state coherent or mixed system with m i.i.d. components, the signature of its equivalent system of size m + l can be written as a mixture of signatures of several multi-state vector k -out-of- m + l: F systems. This facilitates the comparison of two multi-state systems of different sizes upon transforming the signature of the system of smaller size to the signature of its equivalent system of larger size along the lines of Navarro et al. (2008) for the usual Samaniego signature. Some numerical examples are finally presented to illustrate all the results established here.

Charge material distribution behaviour in blast furnace charging system

Smooth operation, permeability control and high energy efficiency are critical operational indices which relate to the overall economic measure of the blast furnace (BF) ironmaking process. The BF charging system is central to the realisation of good operational indices. However, the readiness of granular material to segregate (de-mix) due to particle geometry (size, shape, distribution and density) regardless of the material has been uniformly blended, remains a challenge. This research paper presents discrete element modelling (DEM) study to investigate, characterise and compare the effects of initial positioning of high flowability pellets material in ternary ferrous mixtures with two sinter material components of different sizes. In order to elucidate quantification of the particle-particle scale distributions of particle types relative to others as charge materials mix as well as providing useful inferences on segregation and dispersion, a quantitative approach using near-neighbour separation index (NNSI) was used to give instantaneous quantitative description of the material status in space and time during multiple handling state positions within the charging system. Based on the results obtained from the DEM simulations, the initial positioning of the high flowability pellets material in the upstream of the BF charging system has a bearing on the discharge flow characteristics in the downstream discharging operations as well as mixing and segregation behaviour of the material. The mobility of the high flowability pellets particles, compounded by their relatively small size, influence the overall material movement and interactions as they are acquiescent to percolation and sieving. The observations in this study form a significant contribution for considerations of a discharge model formulation for a mathematical model possible of tracking real-time material movements in a BF charging system.

Lifetime of a structure evolving by cluster aggregation and particle loss, and application to postsynaptic scaffold domains.

The dynamics of several mesoscopic biological structures depend on the interplay of growth through the incorporation of components of different sizes laterally diffusing along the cell membrane, and loss by component turnover. In particular, a model of such an out-of-equilibrium dynamics has recently been proposed for postsynaptic scaffold domains, which are key structures of neuronal synapses. It is of interest to estimate the lifetime of these mesoscopic structures, especially in the context of synapses where this time is related to memory retention. The lifetime of a structure can be very long as compared to the turnover time of its components and it can be difficult to estimate it by direct numerical simulations. Here, in the context of the model proposed for postsynaptic scaffold domains, we approximate the aggregation-turnover dynamics by a shot-noise process. This enables us to analytically compute the quasistationary distribution describing the sizes of the surviving structures as well as their characteristic lifetime. We show that our analytical estimate agrees with numerical simulations of a full spatial model, in a regime of parameters where a direct assessment is computationally feasible. We then use our approach to estimate the lifetime of mesoscopic structures in parameter regimes where computer simulations would be prohibitively long. For gephyrin, the scaffolding protein specific to inhibitory synapses, we estimate a lifetime longer than several months for a scaffold domain when the single gephyrin protein turnover time is about half an hour, as experimentally measured. While our focus is on postsynaptic domains, our formalism and techniques should be applicable to other biological structures that are also formed by a balance of condensation and turnover.

Multiscale modelling of photoinduced processes in composite systems

In the past few decades, quantum mechanical (QM) modelling has moved from isolated molecules made of few atoms to large supramolecular aggregates embedded in complex environments. The integration of QM methods within classical descriptions in multiscale models made such advances possible. One of the first examples of this integration is represented by continuum solvation models that have been largely and successfully applied to predict properties and processes of solvated molecules since the 1980s. Almost in the same years, an alternative classical description based on molecular mechanics (MM) was coupled to QM methods in hybrid QM/MM approaches. Since their first formulations, these QM/classical models have seen great development in terms of accuracy, robustness and generalizability. This progress has enabled their application to systems of increasing complexity and processes never studied before within a QM framework, such as photoinduced processes in biomolecules, nanomaterials and, more generally, composite systems. These systems bring together components of different sizes — molecular, nano and mesoscopic — and multiscale approaches enable their simultaneous investigation. In this Review, we highlight potentials and limitations of multiscale approaches for the modelling of photoinduced processes in composite systems. We discuss the developments that are still needed to elevate the QM-based multiscale strategy to a gold standard for the prediction of light-activated events in composite systems and the analysis of the outputs of novel advanced spectroscopies. Modelling composite systems with components on different length scales is challenging. However, multiscale models based on quantum and classical descriptions can describe these systems and represent the most effective way to explain and predict light-activated events in such complex systems.

Discussion on hot topics of skeletal sternal reconstruction

Sternum is an important constituent of the thoracic cage, and a pivotal part of the anterior chest wall. When a considerable portion of the sternum needs to be resected, in order to protect the vital organs beneath, restore the anatomical structure and physiological function, reconstruction is unavoidable. Sternal reconstruction consists of two related parts: skeletal and soft tissue reconstruction. Skeletal reconstruction uses materials such as autograft or allograft of bones, metallic plates, sandwich patch, non-rigid patches, bio-synthetic patches and three-dimensional printing prosthesis. Each has its advantages and disadvantages. For example, autogenous bone transplantation is limited by the source of donor bones and surgical trauma; allograft bone transplantation demands cryopreservation and is susceptible to infection; titanium plate cannot be placed overlapped; "sandwich" patch is susceptible to local fluid accumulation and infection; non-rigid patches cannot provide enough mechanical support; the design and manufacture of three-dimensional printing prosthesis is complicated, time consuming and expensive, and cannot be adjusted due to change of extent of resection during operation. The modularized prosthesis system is a promising new technique developed on the basis of titanium plate. It is divided into standard components of different sizes that can be selected according to operational requirement and easily assembled. Until now, no perfect method or material has been found to imitate the autogenous sternum. Soft tissue reconstruction is a prerequisite to the success of large scale skeletal reconstruction of the sternum.

Spatial Distribution of Attentional Modulation at Columnar Resolution in Macaque Area V4.

Attention to a location in a visual scene affects neuronal responses in visual cortical areas in a retinotopically specific manner. Optical imaging studies have revealed that cortical responses consist of two components of different sizes: the stimulus-nonspecific global signal and the stimulus-specific mapping signal (domain activity). It remains unclear whether either or both of these components are modulated by spatial attention. In this study, to determine the spatial distribution of attentional modulation at columnar resolution, we performed cerebral blood volume (CBV)-based optical imaging in area V4 of monkeys performing a color change detection task in which spatial attention was manipulated. We found that spatial attention enhanced global signals of the hemodynamic responses, but did not affect stimulus-selective domain activities. These results indicate the involvement of global signals in neural processing of spatial attention. We propose that global signals reflect the neural substrate of the normalization pool in normalization models of attention.

Nodewise Decay in Two-Way Flow Nash Network: A Study of Network Congestion

This paper studies a non-cooperative model of network formation. Built upon the two-way flow model of Bala and Goyal (2000a), it assumes that information decay as it flows through each agent, and the decay is increasing and concave in the number of his links. This assumption results in the fact that a large set of Nash networks are disconnected and consist of components of different sizes, a feature that resembles that of real-world networks. Discussions on this insight are provided.

Component aggregation for PEPA models: An approach based on approximate strong equivalence

Approximate aggregation for PEPA components involves the construction of a smaller component that approximates the behaviour of the original one. Such an approximation at the component level can be very efficient and it can also result in a considerable reduction of the state-space for the underlying continuous-time Markov chain. We propose an approximate PEPA component aggregation strategy that relies on an approximate form of strong equivalence. The notion of strong equivalence captures behavioural similarity between components of different size. This quality renders approximate strong equivalence appropriate as a criterion to aggregate the state-space of PEPA components. We compare our newly proposed approach with previous work on component aggregation, where only a part of the component behaviour has been used as a criterion for aggregation. Our method requires fewer assumptions regarding the form of the components, and is therefore readily applicable to a larger family of PEPA models.

Profiling analysis of low molecular weight heparins by multiple heart-cutting two dimensional chromatography with quadruple time-of-flight mass spectrometry.

Low molecular weight heparins (LMWHs) are polydisperse and microheterogenous mixtures of polysaccharides used as anticoagulant drugs. Profiling analysis is important for obtaining deeper insights into the structure of LMWHs. Previous oligosaccharide mapping methods are relatively low resolution and are unable to show an entire picture of the structural complexity of LMWHs. In the current study a profiling method was developed relying on multiple heart-cutting, two-dimensional, ultrahigh performance liquid chromatography with quadruple time-of-flight mass spectrometry. This represents an efficient, automated, and robust approach for profiling LMWHs. Using size-exclusion chromatography and ion-pairing reversed-phase chromatography in a two-dimensional separation, LMW components of different sizes and LMW components of the same size but with different charges and polarities can be resolved, providing a more complete picture of a LMWH. Structural information on each component was then obtained with quadrupole time-of-flight mass spectrometry. More than 80 and 120 oligosaccharides were observed and unambiguously assigned from the LMWHs, nadroparin and enoxaparin, respectively. This method might be useful for quality control of LMWHs and as a powerful tool for heparin-related glycomics.