Cost Of Sorting Research Articles

Eyeing DNA barcoding for species identification of fish larvae.

Identification of fish larvae based on morphology is typically limited to higher taxonomic ranks (e.g., family or order), as larvae possess few morphological diagnostic characters for precise discrimination to species. When many samples are presented at any one time, the use of morphology to identify such specimens can be laborious and time-consuming. Using a reverse workflow for specimen sorting and identification leveraging high-throughput DNA sequencing, thousands of fish larvae can be DNA barcoded and sorted into molecular operational taxonomic units (mOTUs) in a single sequencing run with the nanopore sequencing technology (e.g., MinION). This process reduces the time and financial costs of morphology-based sorting and instead deploys experienced taxonomists for species taxonomic work where they are needed most. In this study, a total of 3022 fish larval specimens from plankton tows across four sites in Singapore were collected and sorted based on this workflow. Eye tissue from individual samples was used for DNA extraction and sequencing of cytochrome c oxidase subunit I. We generated a total of 2746 barcodes after quality filtering (90.9% barcoding success), identified 2067 DNA barcodes (75.3% identification success), and delimited 256 mOTUs (146 genera, 52 families). Our analyses identified specific challenges to species assignment, such as the potential misidentification of publicly available sequences used as reference barcodes. We highlighted how the conservative application and comparison of a local sequence database can help resolve identification conflicts. Overall, this proposed approach enables and expedites taxonomic identification of fish larvae, contributing to the enhancement of reference barcode databases and potentially better understanding of fish connectivity.

Research on Quality Grading Evaluation and Performance Prediction of Construction Waste Recycled Materials

The application of construction waste in road engineering is an effective means to improve the level of resource recycling. Due to the lack of specialized sorting equipment for different types of construction waste and the high cost of manual sorting, resource utilization enterprises mainly rely on mixed crushing and regeneration in production, while there is a lack of systematic research on the application technical indicators of recycled aggregates for brick concrete mixed construction waste. This article proposes a quality evaluation model for construction waste coarse aggregates based on the theory of matter element extension, providing new ideas for quantitative evaluation of the quality status of coarse aggregates, and also providing reference for the rational selection of recycled coarse aggregates and the determination of mechanical parameters of coarse aggregates in the construction process, which is conducive to the evaluation and analysis of the quality status of recycled coarse aggregates.

Integrated Multi-Vendor Single-Buyer Inventory System Model in Textile Waste Processing Industry

PT. Superbtex Nonwoven Division is one of the industries implementing a green manufacturing system in Bandung by using textile solid waste as raw material and processing it into value-added finished products. However, the solid waste generated by consumers and garment factories is very large and cannot be accommodated in its entirety by PT. Superbtex Nonwoven Division. Another problem arises in terms of inventory both for vendors and buyers; delivering waste from vendors to buyers in small quantities and frequently can lower inventory costs for buyers, but concurrently raise transportation expenses for vendors, and vice versa. Therefore this research was conducted to solve the problem of an integrated multi vendor-single buyer inventory system that considers independent transportation, sorting, and disposal to find the minimum total system cost by finding the optimal value of order lot size, delivery frequency, and proportion of order lot size. that each vendor needs to send to the buyer. Problem-solving is done using the Mixed Integer Non Linear Programming (MINLP) method with the LINGO 18.0 solver. The results obtained from this study stated that the sorting costs at vendor 1 (S1), the sorting costs at the buyer (Sb), the transportation variable costs (Fy), the delivery truck capacity (X), and the demand rate (D) have a significant effect to changes in total system cost (TC). So that the five parameters need to be estimated carefully to determine the optimal system cost.

Limits of mitochondrial genes in delimiting species within a Carbula species complex (Hemiptera: Pentatomidae).

Molecular data has become a powerful tool for species delimitation, particularly among those that present limited morphological differences; while the mitochondrial genome, with its moderate length, low cost of sequencing and fast lineage sorting, has emerged as a practical data set. Due to the limited morphological differences among the closely related species of Carbula Stål 1865, the species boundaries between Carbula abbreviata (Motschulsky, 1866), Carbula humerigera (Uhler, 1860), and Carbula putoni (Jakovlev, 1876) have remained particularly unclear. In this study, we applied two phylogenetic reconstruction methods to two data sets (mitogenome and COI) to assess the phylogeny of Carbula distributed in Asia, and five species delimitation methods to determine the boundaries between East Asian Carbula species. Our phylogenetic analyses showed Carbula to be paraphyletic; the seven known species distributed within East Asia to form a single monophyletic group, and within this, C. abbreviata, C. humerigera, C. putoni and middle-type to comprise a C. humerigera species complex. Our results show that mitogenome data alone, while effective in the differentiation of more distantly related Carbula species, is not sufficient to accurately delimit the species within this newly described complex.

Mixed Plastics Wastes Upcycling with High-Stability Single-Atom Ru Catalyst.

Mixed plastic waste treatment has long been a significant challenge due to complex composition and sorting costs. In this study, we have achieved a breakthrough in converting mixed plastic wastes into a single chemical product using our innovative single-atom catalysts for the first time. The single-atom Ru catalyst can convert ∼90% of real mixed plastic wastes into methane products (selectivity >99%). The unique electronic structure of Ru sites regulates the adsorption energy of mixed plastic intermediates, leading to rapid decomposition of mixed plastics and superior cycle stability compared to traditional nanocatalysts. The global warming potential of the entire process was evaluated. Our proposed carbon-reducing process utilizing single-atom catalysts launches a new era of mixed plastic waste valorization.

When core sorting and quality grading is beneficial to remanufacturers: Insights from analytical models

In this paper, we study the core acquisition and remanufacturing problem in which the remanufactured products are produced from acquired cores with uncertain quality condition, and are used to satisfy customer demand. Decision-making models are developed to examine the potential value of core sorting and quality grading in the remanufacturing system: a single-period model with deterministic demand, and a single-period model with stochastic demand (i.e., a newsvendor-type model). In each model, both the sorting strategy and the non-sorting strategy are discussed and compared. Our theoretical and numerical results show that: (1) In the deterministic demand case, core sorting is cost-effective only when the unit sorting cost is below a threshold value and the unit acquisition cost falls into a specific interval. Furthermore, in the case with two quality grades the adoption of sorting strategy with respect to the expected fraction of high-quality cores may be non-monotone: an initial increase in the expected fraction of high-quality cores may motivate a switch to core sorting, however, further increase in the expected fraction may motivate a reverse switch; (2) Similarly, in the stochastic demand case, the sorting strategy also becomes unattractive when the unit sorting cost is sufficiently high. In addition, the value of core sorting will be better off under more fluctuating demand for remanufactured products if the sorting strategy is the dominant strategy. Otherwise, it will be worse off.

Constructing an Evolutionary Tree and Path–Cycle Graph Evolution along It

The paper solves the problem of constructing an evolutionary tree and the evolution of structures along it. This problem has long been posed and extensively researched; it is formulated and discussed below. As a result, we construct an exact cubic-time algorithm which outputs a tree with the minimum cost of embedding into it and of embedding it into a given network (Theorem 1). We construct an algorithm that outputs a minimum embedding of a tree into a network, taking into account incomplete linear sorting; the algorithm depends linearly on the number of nodes in the network and is exact if the sorting cost is not less than the sum of the duplication cost and the loss cost (Theorem 3). We construct an exact approximately quadratic-time algorithm which, for arbitrary costs of SCJ operations, solves the problem of reconstruction of given structures on any two-star tree (Theorem 4). We construct an exact algorithm which reduced the problem of DCJ reconstruction of given structures on any star to a logarithmic-length sequence of SAT problems, each of them being of approximately quadratic size (Theorem 5). The theorems have rigorous and complete proofs of correctness and complexity of the algorithms, and are accompanied by numerical examples and numerous explanatory illustrations, including flowcharts.

Enrichment and Recovery of Lead-Zinc Tailings by Spiral Wall Cyclones

In order to solve the problem of increasing the difficulty of sorting lead-zinc tailings in China, the re-separation of lead-zinc tailings is realized, the recovery efficiency is improved, and the sorting cost is reduced. Through the structural improvement of the traditional column conical cyclone, a spiral wall cyclone suitable for secondary sorting of lead-zinc tailings is proposed, and the lead-zinc tailings with different density are quickly separated by using the diversion of the spiral wall and the enrichment of mineral particles. The results showed that the recovery rate of heavy concentrate PbO increased from 55.55% to 85.25% by the spiral wall cyclone after structural optimization, an increase of nearly 30%, and the enrichment ratio of down-export PbO concentrate also increased from 1.321 to 1.762. It can be seen that the optimized spiral wall cyclone can effectively increase the secondary sorting efficiency of lead-zinc tailings, and provide a reference for the structural design of hydraulic cyclones in the same type of mine to a certain extent.

Detector Processor for a 5G Base Station.

Nonlinear soft bit detection is essential for the uplink receivers of 5G base stations, especially for users around the cell edge. However, its throughput and computing complexity are always challenges for both research and industry. A low-cost and low-power parallel implementation of a soft-output detector based on sorted QR decomposition (SQRD) and the K-best breadth-first search algorithm is thus proposed to reduce computational complexity and latency. In addition, to save area and reduce latency, two improvement methods are used: (1) reduce the computing cost by saturating and truncating large values during PED computing and (2) reduce the sorting cost by using the binary bit sorting method for a reduced sample set with finite accuracy. Furthermore, a pipelined VLSI architecture is designed using 28-nm digital CMOS technology offered by Semiconductor Manufacturing International Corporation (SMIC). It can achieve a peak throughput of 6400 Mbps while consuming 153 K gates (including all flip-flops) for SMIC’s 28-nm technology and running at 800 MHz, a 32% cost reduction compared with the published reference design.

Evaluating automated benthic fish detection under variable conditions

Abstract Advances in imaging systems have facilitated the collection of high-volume imagery datasets in fisheries science. To alleviate the costs of sorting these datasets, automated image processing techniques are used. In this study, we investigate a machine learning-enabled imaging technique for automating individual fish detection from stereo image pairs of orange roughy (Hoplostethus atlanticus). We performed a set of object detection experiments to investigate how well a Single Shot Multi-Box Detector (SSD) model worked under dynamic real-world conditions when trained over a small number of epochs. We tested model generalization between the port and starboard side cameras; at variable fish densities; different benthic substrates; and at different altitudes above the seafloor. We show that (1) changes in perspective between starboard and port images are not enough to break the object detector, (2) the object detector begins to have trouble differentiating individuals at high fish densities (>20 fish per image), (3) substrate type does not affect model performance, and (4) altitude is not a major factor contributing to model error. Ideally, this type of real-world dataset exploration should be performed prior to committing the resources to train the final object detector over several hundred epochs.

Optimal strategy to sort plastic waste considering economic feasibility to increase recycling efficiency

In this study, we suggested an optimal strategy to sort plastic waste to improve recycling efficiency considering economic feasibility. To derive the optimal sorting strategy, we developed a novel optimization model that considers the overall cost, which is sorting cost minus the revenue obtained by selling the recycling plastic from the sorting cost. Then we used the developed model to identify the optimal strategy to sort plastic waste in mixed-integer programming that minimizes the overall cost of plastic waste sorting systems. We also conducted a sensitivity analysis to analyze the extent to which the results obtained can change under different conditions. The optimization results, identify that the plastics in the optimal sorting strategy are of four types: LDPE, HDPE, PP, and PVC. This optimal sorting strategy increase the overall sorting efficiency slightly by 4 wt%, but considering the revenue obtained by selling the recycled plastic the strategy significantly decreased the overall sorting cost by 69.28 % compared to the conventional case. The developed model can determine the optimal strategy to sort plastic waste considering economic improvement. Therefore, the results allow increase in plastic recycling by minimizing the overall cost of the sorting system.

I/O-Efficient Algorithms for Topological Sort and Related Problems

This article presents I/O-efficient algorithms for topologically sorting a directed acyclic graph and for the more general problem identifying and topologically sorting the strongly connected components of a directed graph G = ( V, E ). Both algorithms are randomized and have I/O-costs O ( sort ( E ) · poly(log V)), with high probability, where sort ( E ) = O( E / B log M / B ( E/B )) is the I/O cost of sorting an | E |-element array on a machine with size- B blocks and size- M cache/internal memory. These are the first algorithms for these problems that do not incur at least one I/O per vertex, and as such these are the first I/O-efficient algorithms for sparse graphs. By applying the technique of time-forward processing, these algorithms also imply I/O-efficient algorithms for most problems on directed acyclic graphs, such as shortest paths, as well as the single-source reachability problem on arbitrary directed graphs.

Separate Waste Collection as part of Reforming the Municipal Solid Waste Management Industry

As the experience of developed countries has shown, the creation of an effective zero-waste economic model based on the principles of a circular economy is impossible without the competent management of production and consumption waste. The most important aspect in this case is the separate collection of waste by fractions, which reduces the cost of sorting and, as a result, increases the attractiveness of recyclables. The purpose of the study is to identify the main obstacles that the Russian Federation faces in carrying out the waste reform and creating a system for the separate collection of municipal solid waste. An analysis of the accumulated scientific and practical experience on this issue allows us to assert that the viability of separate waste collection as an economic model for handling them can hardly be contested. The feasibility and potential cost-effectiveness of separate collection is confirmed by studies conducted both in the context of the country as a whole and at the level of individual regions. Based on this, the author assumes that the problem of introducing separate waste collection is of an organizational and legal nature, in connection with which he analyzed the main theoretical and legal approaches to solving the issue. Having studied the empirical material accumulated by science, the author concludes that three main factors prevent separate waste collection, namely a low level of waste management culture among the population, an insufficient number of incentive mechanisms for the industry, and the existence of legal gaps and administrative barriers that prevent creation of infrastructure for separate collection and disposal of waste. The author considers the main aspects of these factors and suggests options for solving the identified problems.

Color Classification and Texture Recognition System of Solid Wood Panels

Solid wood panels are widely used in the wood flooring and furniture industries, and paneling is an excellent material for indoor decoration. The classification of colors helps to improve the appearance of wood products assembled from multiple panels due to the differences in surface colors of solid wood panels. Traditional wood surface color classification mainly depends on workers’ visual observations, and manual color classification is prone to visual fatigue and quality instability. In order to reduce labor costs of sorting and to improve production efficiency, in this study, we introduced machine vision technology and an unsupervised learning technique. First-order color moments, second-order color moments, and color histogram peaks were selected to extract feature vectors and to realize data dimension reduction. The feature vector set was divided into different clusters by the K-means algorithm to achieve color classification and, thus, the solid wood panels with similar surface color were classified into one category. Furthermore, during twice clustering based on second-order color moment, texture recognition was realized on the basis of color classification. A sample of beech wood was selected as the research object, not only was color classification completed, but texture recognition was also realized. The experimental results verified the effectiveness of the technical proposal.

A high-precision detection method of hydroponic lettuce seedlings status based on improved Faster RCNN

In order to improve the efficiency and reduce high cost for seedlings sorting in the raising process of hydroponic lettuce seedlings, we propose an automatic detection method for hydroponic lettuce seedlings based on improved Faster RCNN framework, taking the dead and double-planting status of seedlings growing in a single hole as our research objects. Since the characteristics of hydroponic lettuce seedlings are dense and small in the images, our model uses High Resolution Network (HRNet) as the backbone network for image feature extraction so as to obtain reliable and high- resolution feature expressions. Besides, we adopt focal loss as the classification loss in the Region Proposal Network (RPN) stage to address the imbalance between difficult and easy samples in seedlings classification. We also employ the Region of Interest (RoI) Align instead of the RoI Pooling layer to improve the detection accuracy of seedlings in the different status. The results show that the mean average precision of our method for the hydroponic lettuce seedlings is 86.2%, which is higher than RetinaNet, SSD, Cascade RCNN, FCOS and other detectors. Compared with different feature extraction networks, the detection accuracy of adopting HRNet performs nicely. Therefore, our method presented for the detection of hydroponic lettuce seedlings status can achieve high accuracy and identify seedlings in a problematic status well, which will provide technical support for automatic seedlings detection of hydroponic lettuce.

The Sorting Process as a Tool for Promoting the Demand of Heterogeneous Customers

The present study concerns product diversification. The products differ in size, shape, flavor, fat content, etc., so that the producer can more specifically modify the particular product to the unique requirements of nonhomogeneous customers. The mathematical model assumes diversified demands of nonhomogeneous consumers for an initial unsorted item. The sorting process generates a better match between customer requirements and the actual supply of sorted products. Thus, the implementation of sorting costs allows for an increase in customer demands by adopting product characteristics that are closer to customer needs and tastes. The study also considers the pricing policy for diversified products in order to determine if price discrimination is preferable for attaining the manufacturer’s goal of profit maximization.

Improving the sorting efficiency of maize haploid kernels using an NMR-based method with oil content double thresholds

BackgroundMaize haploid breeding technology can be used to rapidly develop homozygous lines, significantly shorten the breeding cycle and improve breeding efficiency. Rapid and accurate sorting haploid kernels is a prerequisite for the large-scale application of this technology. At present, the automatic haploid sorting based on nuclear magnetic resonance (NMR) using a single threshold method has been realized. However, embryo-aborted (EmA) kernels are usually produced during in vivo haploid induction, and both haploids and EmA kernels have lower oil content and are separated together using a single threshold method based on NMR. This leads to a higher haploid false discrimination rate (FDR) and requires secondary manual sorting to select the haploid kernels from the mixtures, which increases the sorting cost and decreases the haploid sorting efficiency. In order to improve the correct discrimination rate (CDR) in sorting haploids, a method to distinguish EmA kernels is required.ResultsSingle kernel weight and oil content were measured for the diploid, haploid, and EmA kernels derived from three maize hybrids and nine inbred lines by in vivo induction. The results showed that the distribution of oil content showed defined boundaries between the three types of kernels, while the single kernel weight didn't. According to the distribution of oil content in the three types of kernels, a double-threshold method was proposed to distinguish the embryo-aborted kernels, haploid and diploid kernels based on NMR and their oil content. The double thresholds were set based on the minimum oil content of diploid kernels and the maximum content of EmA kernels as the upper and lower boundary values, respectively. The CDR of EmA kernels in different maize materials was > 97.8%, and the average FDR was reduced by 27.9 percent.ConclusionsThe oil content is an appropriate indicator to discriminate diploid, haploid and EmA kernels. An oil content double-threshold method based on NMR was first developed in this study to identify the three types of kernels. This methodology could reduce the FDR of haploids and improve the sorting efficiency of automated sorting system. Thus, this technique represents a potentially efficient method for haploid sorting and provides a reference for the process of automated sorting of haploid kernels with high efficiency using NMR.

E-commerce shipping through a third-party supply chain

We consider an e-commerce retailer who must ship orders from a warehouse to a set of customers with delivery deadlines. As is often the case, the retailer uses a third-party service provider to ensure its distribution. The retailer can enter the supply chain of the service provider at various levels. Entering it at a higher level entails lower sorting costs for the retailer, but higher delivery costs, and longer delivery times. The customer orders arrive at various moments over a rolling planning horizon. This means that the retailer must also make consolidation decisions. We model and solve the static and dynamic cases of this problem. The static case is modeled as an integer linear program and solved by CPLEX. We develop and compare four shipping policies for the dynamic case. Extensive computational results based on real location data from California and Texas are reported.

An overview of the municipal solid waste management modes and innovations in Shanghai, China.

Municipal solid waste (MSW) management and recycling has become an emerging issue in developing countries. Shanghai, the largest megacity in China, is well-known nationwide due to leading China's MSW separation and recycling. Therefore, this paper introduces the Shanghai mode for MSW management and its current situation to enrich existing MSW management studies. Results show that the total generation volume of MSW and amount of MSW generation per capita were 9.00 million tons and 372.16 kg in 2017, increased approximately eight-fold and four-fold compared with the data in 1978, respectively. The MSW treatment rate reached 100% since 2014, with incineration rate increased to 48.56% in 2017. The cost of MSW management after implementing MSW sorting regulation is increased to 985 CNY/ton, including 390 CNY/ton of MSW sorting cost. Then three key features and innovative MSW management modes, namely, mandatory MSW sorting legislation, Green Account program, and the Combined Network program are introduced. Meanwhile, two main challenges are urgent to be responded, including inadequate collecting vehicles and limited wet waste treatment capacity. Finally, policy recommendations on strengthening MSW recycling process, constructing complete terminal treatment industry, and making systematic policies were provided to respond existing challenges.

Market Power in the Presence of Adverse Selection

Market power can reduce the symptoms of adverse selection. To see the relationship, consider the incentive for a firm to offer a product that appeals to low-risk consumers and leads high-risk consumers to purchase insurance elsewhere. This incentive problem can be addressed through regulation but is also absent in a monopoly. This paper develops a model of welfare to explicitly characterize the substitutability between adverse selection regulation and market power. Market concentration has welfare benefits by reducing inefficient sorting of consumers among available plan options, a symptom of adverse selection. However, since market concentration also carries the welfare cost of higher markups, the magnitude and net direction of the effects are an empirical question. The model is estimated for the non-group market using novel choice data from a private online broker and a risk prediction model to relate preferences to marginal cost. The analysis focuses on two policies that target different dimensions of adverse selection: risk adjustment and the individual mandate. A simulation of a proposed merger of two insurance firms shows that, in the absence of a risk adjustment policy, the merger improves consumer welfare in markets that are not already highly concentrated. While the risk adjustment policy does not optimally price the sorting externality, it is successful in reducing the welfare cost of inefficient sorting and also eliminating the potential benefit to consumers from additional market power. The individual mandate is successful in increasing the insurance rate and lowering prices in the least concentrated markets, but leads to higher prices in the most concentrated markets. These results suggest that selection regulation is advantageous in competitive insurance markets, and less necessary and potentially harmful in very concentrated markets.