Self-consistent field theory (SCFT) is a powerful tool for the design and interpretation of experiments on block polymer materials. In this Perspective, we lower the barrier to entry to the use of ...SCFT by experimental groups by two means. First, we present a pedagogical introduction to an improved version of the open-source Polymer Self-Consistent Field (PSCF) software package and of the underlying theory. Second, we discuss methods for generating robust initial guesses for the fields that are computed in SCFT. To demonstrate our approach, we present two case studies in which a typical desktop computer has been used to simulate the structure of (i) body-centered cubic, face-centered cubic, A15, and Frank–Kasper σ sphere-forming phases of a diblock copolymer melt and (ii) two core–shell morphologies of ABAC tetrablock terpolymers. A companion Web site provides all of the relevant software and detailed instructions for reproducing all results contained herein.
The increasing availability of high-quality experimental data and first-principles calculations creates opportunities for developing more accurate empirical force fields for simulation of proteins. ...We developed the AMBER-FB15 protein force field by building a high-quality quantum chemical data set consisting of comprehensive potential energy scans and employing the ForceBalance software package for parameter optimization. The optimized potential surface allows for more significant thermodynamic fluctuations away from local minima. In validation studies where simulation results are compared to experimental measurements, AMBER-FB15 in combination with the updated TIP3P-FB water model predicts equilibrium properties with equivalent accuracy, and temperature dependent properties with significantly improved accuracy, in comparison with published models. We also discuss the effect of changing the protein force field and water model on the simulation results.
•Review blockchain technology.•Outline potential applications for immutable distributed ledgers.•Design a reference implementation of an Ethereum based application.•Provide insights into the ...development of blockchain based supply chains.
Blockchain is a promising information technology which can provide several potential applications related to operations and supply chains. By using distributed software architecture and advanced computing, blockchain can solve the problem of immutable ledgers distributed to several actors in the chain. This paper reviews blockchain technology and outlines possible uses for immutable distributed ledgers in operations and supply chains. A classification of the applications of blockchain technology in the scope of operations and supply chain management is presented. In order to demonstrate the technical architecture of the blockchain-based logistics monitoring system (BLMS), a reference implementation was programmed and tested based on Ethereum. The purpose of the BLMS is to provide a solution for parcel tracking in a supply chain to support an open and immutable history record for each transaction. The functionality of the system consists of transaction entry for logistics operators. The presented reference architecture demonstrates how blockchain can be implemented in the operations and supply chain context by using software components.
•A green vehicle routing model to exploit the sustainability of UAVs for deliveries.•A genetic algorithm to efficiently solve the complex model.•Optimal solutions to validate the model and the ...genetic algorithm.•Our model and algorithm minimize carbon emissions as well as delivery costs.
An unmanned aerial vehicle (UAV), commonly known as a drone, offers the advantage of speed, flexibility, and ease in delivering goods to customers. They are particularly useful for tasks that are dull, hazardous, or dirty. Whether the use of drone delivery is beneficial to the environment and cost saving is still a topic under debate. Ideally, drones yield lower energy consumption and reduce greenhouse gas emissions, thus reducing the carbon footprint and enhancing environmental sustainability. In this research, we analytically study the impact of UAVs on CO2 emission and cost. We propose a mixed-integer (0–1 linear) green routing model for UAV to exploit the sustainability aspects of the use of UAVs for last-mile parcel deliveries. A genetic algorithm is developed to efficiently solve the complex model, and an extensive experiment is conducted to illustrate and validate the analytical model and the solution algorithm. We find that optimally routing and delivering packages with UAVs would save energy and reduce carbon emissions. The computational results strongly support the notion that using UAVs for last-mile logistics is not only cost effective, but also environmentally friendly.
Similarity has always been a key aspect in computer science and statistics. Any time two element vectors are compared, many different similarity approaches can be used, depending on the final goal of ...the comparison (Euclidean distance, Pearson correlation coefficient, Spearman's rank correlation coefficient, and others). But if the comparison has to be applied to more complex data samples, with features having different dimensionality and types which might need compression before processing, these measures would be unsuitable. In these cases, a siamese neural network may be the best choice: it consists of two identical artificial neural networks each capable of learning the hidden representation of an input vector. The two neural networks are both feedforward perceptrons, and employ error back-propagation during training; they work parallelly in tandem and compare their outputs at the end, usually through a cosine distance. The output generated by a siamese neural network execution can be considered the semantic similarity between the projected representation of the two input vectors. In this overview we first describe the siamese neural network architecture, and then we outline its main applications in a number of computational fields since its appearance in 1994. Additionally, we list the programming languages, software packages, tutorials, and guides that can be practically used by readers to implement this powerful machine learning model.
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•Primitive e-waste dismantling led to the highest OPE levels in the atmosphere.•OPEs in the urban region were largely derived from industrial emissions.•Surface evaporation and air ...advection also contributed OPEs in the urban air.•The compositions at the background site suggest atmospheric reaction loss of OPEs.•Emission sources of TEP and TDCIPP nearby the background site were observed.
Organophosphate esters (OPEs) are a focus of research because they are ubiquitous in the environment; however, there is still a limited understanding of the behaviors and fate of OPEs in the environment. In this study, we measured OPEs in fine particulate matter (PM2.5) collected from three regions in South China that have potentially different sources. The concentrations of ∑OPEs in the rural electronic waste (e-waste) recycling area (3852–57,695 pg/m3 with a median of 10,955 pg/m3) were significantly higher than those in the urban and background areas with concentrations of 314–9721 pg/m3 (median = 2346 pg/m3) and 667 and 109,599 pg/m3 (median = 2170 pg/m3), respectively. The OPE compositions in the urban and e-waste areas were generally similar. Correlations analysis with other components of PM2.5 (organic carbon, elemental carbon, and water soluble ions) indicated primary industrial and e-waste sources of OPEs in the urban and e-waste regions, respectively. Correlation analysis also revealed that relative humility played an important role in their air concentrations in the urban and background regions. The air-parcel backward trajectories of the background site demonstrated regional atmospheric transport of OPEs to this region from both the eastern industrial cities and the northern e-waste recycling region.
•Comprehensive description of the history, status and future of the ARB software and SILVA datasets.•The SILVA taxonomic framework as reference for phylogenetic inference and rDNA ...classification.•Positioning of ARB and SILVA with respect to related tools and databases.
SILVA (lat. forest) is a comprehensive web resource, providing services around up to date, high-quality datasets of aligned ribosomal RNA gene (rDNA) sequences from the Bacteria, Archaea, and Eukaryota domains. SILVA dates back to the year 1991 when Dr. Wolfgang Ludwig from the Technical University Munich started the integrated software workbench ARB (lat. tree) to support high-quality phylogenetic inference and taxonomy based on the SSU and LSU rDNA marker genes. At that time, the ARB project maintained both, the sequence reference datasets and the software package for data analysis. In 2005, with the massive increase of DNA sequence data, the maintenance of the software system ARB and the corresponding rRNA databases SILVA was split between Munich and the Microbial Genomics and Bioinformatics Research Group in Bremen. ARB has been continuously developed to include new features and improve the usability of the workbench. Thousands of users worldwide appreciate the seamless integration of common analysis tools under a central graphical user interface, in combination with its versatility.
The first SILVA release was deployed in February 2007 based on the EMBL-EBI/ENA release 89. Since then, full SILVA releases offering the database content in various flavours are published at least annually, complemented by intermediate web-releases where only the SILVA web dataset is updated. SILVA is the only rDNA database project worldwide where special emphasis is given to the consistent naming of clades of uncultivated (environmental) sequences, where no validly described cultivated representatives are available. Also exclusive for SILVA is the maintenance of both comprehensive aligned 16S/18S rDNA and 23S/28S rDNA sequence datasets. Furthermore, the SILVA alignments and trees were designed to include Eukaryota, another unique feature among rDNA databases. With the termination of the European Ribosomal RNA Database Project in 2007, the SILVA database has become the authoritative rDNA database project for Europe. The application spectrum of ARB and SILVA ranges from biodiversity analysis, medical diagnostics, to biotechnology and quality control for academia and industry.
•The behavior of different MPPT techniques applied to PV systems.•Using co-simulation between PSIM and Simulink software packages.•Modeling and simulation of four PV MPPT techniques.•Transient and ...steady state response of four PV MPPT techniques.
This paper aimed to study the behavior of different maximum power point tracking (MPPT) techniques applied to PV systems. In this work, techniques such as hill climbing (HC), incremental conductance (INC), perturb-and-observe (P&O), and fuzzy logic controller (FLC) are assessed. A model of PV module and DC/DC boost converter with the different techniques of MPPTs was simulated using PSIM and Simulink software. Co-simulation between PSIM and Simulink software packages is used to establish FLC MPPT technique. The co-simulation is done to take advantage of each program to handle certain part of the system. The response of the different MPPT techniques is evaluated in rapidly changing weather conditions. The results indicate that, FLC performed best among compared MPPT techniques followed by P&O, INC, and, HC MPPT techniques in both dynamic response and steady-state in most of the normal operating range.
•A drone scheduling problem is extended to consider drop and pickup syncronization.•A constraint programming is applied to UAVs transportation scheduling problem.•Integrated scheduling of multiple ...depots is studied.
The idea of deploying unmanned aerial vehicles, also known as drones, for final-mile delivery in logistics operations has vitalized this new research stream. One conceivable scenario of using a drone in conjunction with a traditional delivery truck to distribute parcels is discussed in earlier literature and termed the parallel drone scheduling traveling salesman problem (PDSTSP). This study extends the problem by considering two different types of drone tasks: drop and pickup. After a drone completes a drop, the drone can either fly back to depot to deliver the next parcels or fly directly to another customer for pickup. Integrated scheduling of multiple depots hosting a fleet of trucks and a fleet of drones is further studied to achieve an operational excellence. A vehicle that travels near the boundary of the coverage area might be more effective to serve customers that belong to the neighboring depot. This problem is uniquely modeled as an unrelated parallel machine scheduling with sequence dependent setup, precedence-relationship, and reentrant, which gives us a framework to effectively consider those operational challenges. A constraint programming approach is proposed and tested with problem instances of m-truck, m-drone, m-depot, and hundred-customer distributed across an 8-mile square region.
Fluidized gas–particle systems are inherently unstable and they manifest structures on a wide range of length and time scales. In this article we present for the first time in the literature a ...coarse-grained drag force model for Euler–Lagrange (EL) based simulations of fluidized gas–particle suspensions. Two types of coarse graining enter into consideration: coarse fluid grids as well as particle coarsening in the form of parcel-based simulations where only a subset of particles is simulated. We use data from well-resolved EL simulations to assemble a model for the filtered drag force that examines fluid and particle coarsening separately. We demonstrate that inclusion of correction to gas–particle drag to account for fluid coarsening leads to superior predictions in a test problem. We then present an ad hoc modification to account for particle coarsening, which improves accuracy of simulations involving both fluid and particle coarsening. We also identify an approximate characteristic length scale that can be used to collapse the results for different gas–particle systems.
Snapshots for the particle distribution colored by the vertical particle velocity (left, the gray surface indicates an isocontour at ϕp=0.54) and the vertical fluid velocity (right, a thin cross section through the computational domain is shown; 〈ϕp〉=0.25). Display omitted
•We use data from EL simulations to assemble a model for the filtered drag force.•Corrections to gas–particle drag lead to superior predictions.•We identify an approximate characteristic length scale of particle clusters.
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