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1.
Nutrients ; 13(10)2021 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-34684486

RESUMO

Food-based recommendations (FBR) developed using linear programming generally use dietary intake and energy and nutrient requirement data. It is still unknown to what extent the availability and selection of these data affect the developed FBR and identified problem nutrients. We used 24 h dietary recalls of 62 Kenyan children (4-6 years of age) to analyse the sensitivity of the FBR and problem nutrients to (1) dietary intake data, (2) selection criteria applied to these data and (3) energy and nutrient requirement data, using linear programming (Optifood©), by comparing a reference scenario with eight alternative scenarios. Replacing reported by estimated consumption frequencies increased the recommended frequencies in the FBR for most food groups while folate was no longer identified as a problem nutrient. Using the 10-90th instead of the 5-95th percentile of distribution to define minimum and maximum frequencies/week decreased the recommended frequencies in the FBR and doubled the number of problem nutrients. Other alternative scenarios negligibly affected the FBR and identified problem nutrients. Our study shows the importance of consumption frequencies for developing FBR and identifying problem nutrients by linear programming. We recommend that reported consumption frequencies and the 5-95th percentiles of distribution of reported frequencies be used to define the minimum and maximum frequencies.


Assuntos
Alimentos , Modelos Teóricos , Política Nutricional , Programação Linear , Criança , Pré-Escolar , Ingestão de Alimentos , Feminino , Humanos , Quênia , Masculino , Recomendações Nutricionais
2.
Artigo em Inglês | MEDLINE | ID: mdl-34574471

RESUMO

When planning wetland restoration projects, the planting area allocation and the costs of the restoration measures are two major issues faced by decision makers. In this study, a framework based on the interval fuzzy linear programming (IFLP) method is introduced for the first time to plan wetland restoration projects. The proposed framework can not only effectively deal with interval and fuzzy uncertainties that exist in the planning process of wetland restorations but also handle trade-offs between ecological environment benefits and economic cost. This framework was applied to a real-world wetland restoration planning problem in the northeast of China to verify its validity and examine the credibility of the constraints. The optimized results obtained from the framework that we have developed indicate that higher ecological and social benefits can be obtained with optimal restoration costs after using the wetland restoration decision-making framework. The optimal restoration measure allocation schemes obtained by IFLP under different credibility levels can help decision makers generate a range of alternatives, which can also provide decision suggestions to local managers to generate a satisfactory decision-making plan. Furthermore, a comparison was made between the IFLP model and ILP model in this study. The comparison results indicate that the IFLP model provides more information regarding ecological environment and economic trade-offs between the system objective, certainty, and reliability. This framework provides managers with an effective way to plan wetland restoration projects, while transference of the model may help solve similar problems.


Assuntos
Programação Linear , Áreas Alagadas , Lógica Fuzzy , Modelos Teóricos , Reprodutibilidade dos Testes , Incerteza
3.
Sci Total Environ ; 794: 148726, 2021 Nov 10.
Artigo em Inglês | MEDLINE | ID: mdl-34328124

RESUMO

The current linear "take-make-waste-extractive" model leads to the depletion of natural resources and environmental degradation. Circular Economy (CE) aims to address these impacts by building supply chains that are restorative, regenerative, and environmentally benign. This can be achieved through the re-utilization of products and materials, the extensive usage of renewable energy sources, and ultimately by closing any open material loops. Such a transition towards environmental, economic and social advancements requires analytical tools for quantitative evaluation of the alternative pathways. Here, we present a novel CE system engineering framework and decision-making tool for the modeling and optimization of food supply chains. First, the alternative pathways for the production of the desired product and the valorization of wastes and by-products are identified. Then, a Resource-Task-Network representation that captures all these pathways is utilized, based on which a mixed-integer linear programming model is developed. This approach allows the holistic modeling and optimization of the entire food supply chain, taking into account any of its special characteristics, potential constraints as well as different objectives. Considering that typically CE introduces multiple, often conflicting objectives, we deploy here a multi-objective optimization strategy for trade-off analysis. A representative case study for the supply chain of coffee is discussed, illustrating the steps and the applicability of the framework. Single and multi-objective optimization formulations under five different coffee-product demand scenarios are presented. The production of instant coffee as the only final product is shown to be the least energy and environmental efficient scenario. On the contrary, the production solely of whole beans sets a hypothetical upper bound on the optimal energy and environmental utilization. In both problems presented, the amount of energy generated is significant due to the utilization of waste generated for the production of excess energy.


Assuntos
Abastecimento de Alimentos , Programação Linear , Engenharia
4.
Methods Mol Biol ; 2328: 99-113, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34251621

RESUMO

The cell expresses various genes in specific contexts with respect to internal and external perturbations to invoke appropriate responses. Transcription factors (TFs) orchestrate and define the expression level of genes by binding to their regulatory regions. Dysregulated expression of TFs often leads to aberrant expression changes of their target genes and is responsible for several diseases including cancers. In the last two decades, several studies experimentally identified target genes of several TFs. However, these studies are limited to a small fraction of the total TFs encoded by an organism, and only for those amenable to experimental settings. Experimental limitations lead to many computational techniques having been proposed to predict target genes of TFs. Linear modeling of gene expression is one of the most promising computational approaches, readily applicable to the thousands of expression datasets available in the public domain across diverse phenotypes. Linear models assume that the expression of a gene is the sum of expression of TFs regulating it. In this chapter, I introduce mathematical programming for the linear modeling of gene expression, which has certain advantages over the conventional statistical modeling approaches. It is fast, scalable to genome level and most importantly, allows mixed integer programming to tune the model outcome with prior knowledge on gene regulation.


Assuntos
Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica/genética , Redes Reguladoras de Genes/genética , Programação Linear , Fatores de Transcrição/metabolismo , Bases de Dados Genéticas , Modelos Teóricos , Software , Fatores de Transcrição/genética
5.
Methods Mol Biol ; 2328: 287-301, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34251634

RESUMO

Genes are transcribed into various RNA molecules, and a portion of them called messenger RNA (mRNA) is then translated into proteins in the process known as gene expression. Gene expression is a high-energy demanding process, and aberrant expression changes often manifest into pathophysiology. Therefore, gene expression is tightly regulated by several factors at different levels. MicroRNAs (miRNAs) are one of the powerful post-transcriptional regulators involved in key biological processes and diseases. They inhibit the translation of their mRNA targets or degrade them in a sequence-specific manner, and hence control the rate of protein synthesis. In recent years, in response to experimental limitations, several computational methods have been proposed to predict miRNA target genes based on sequence complementarity and structural features. However, these predictions yield a large number of false positives. Integration of gene and miRNA expression data drastically alleviates this problem. Here, I describe a mathematical linear modeling approach to identify miRNA targets at the genome scale using gene and miRNA expression data. Mathematical modeling is faster and more scalable to genome-level compared to conventional statistical modeling approaches.


Assuntos
Biologia Computacional/métodos , Regulação da Expressão Gênica/genética , Genoma/genética , MicroRNAs/metabolismo , Programação Linear , Interferência de RNA , Algoritmos , MicroRNAs/genética , Modelos Teóricos , Software
6.
Bioinformatics ; 37(Suppl_1): i133-i141, 2021 07 12.
Artigo em Inglês | MEDLINE | ID: mdl-34252920

RESUMO

MOTIVATION: Protein domain duplications are a major contributor to the functional diversification of protein families. These duplications can occur one at a time through single domain duplications, or as tandem duplications where several consecutive domains are duplicated together as part of a single evolutionary event. Existing methods for inferring domain-level evolutionary events are based on reconciling domain trees with gene trees. While some formulations consider multiple domain duplications, they do not explicitly model tandem duplications; this leads to inaccurate inference of which domains duplicated together over the course of evolution. RESULTS: Here, we introduce a reconciliation-based framework that considers the relative positions of domains within extant sequences. We use this information to uncover tandem domain duplications within the evolutionary history of these genes. We devise an integer linear programming approach that solves our problem exactly, and a heuristic approach that works well in practice. We perform extensive simulation studies to demonstrate that our approaches can accurately uncover single and tandem domain duplications, and additionally test our approach on a well-studied orthogroup where lineage-specific domain expansions exhibit varying and complex domain duplication patterns. AVAILABILITY AND IMPLEMENTATION: Code is available on github at https://github.com/Singh-Lab/TandemDuplications. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Algoritmos , Programação Linear , Evolução Molecular , Duplicação Gênica , Humanos , Filogenia , Domínios Proteicos
7.
PLoS Comput Biol ; 17(6): e1009078, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-34153026

RESUMO

It is computationally challenging to detect variation by aligning single-molecule sequencing (SMS) reads, or contigs from SMS assemblies. One approach to efficiently align SMS reads is sparse dynamic programming (SDP), where optimal chains of exact matches are found between the sequence and the genome. While straightforward implementations of SDP penalize gaps with a cost that is a linear function of gap length, biological variation is more accurately represented when gap cost is a concave function of gap length. We have developed a method, lra, that uses SDP with a concave-cost gap penalty, and used lra to align long-read sequences from PacBio and Oxford Nanopore (ONT) instruments as well as de novo assembly contigs. This alignment approach increases sensitivity and specificity for SV discovery, particularly for variants above 1kb and when discovering variation from ONT reads, while having runtime that are comparable (1.05-3.76×) to current methods. When applied to calling variation from de novo assembly contigs, there is a 3.2% increase in Truvari F1 score compared to minimap2+htsbox. lra is available in bioconda (https://anaconda.org/bioconda/lra) and github (https://github.com/ChaissonLab/LRA).


Assuntos
Mapeamento de Sequências Contíguas/estatística & dados numéricos , Alinhamento de Sequência/estatística & dados numéricos , Software , Análise por Conglomerados , Biologia Computacional , Simulação por Computador , Bases de Dados de Ácidos Nucleicos/estatística & dados numéricos , Variação Genética , Genoma Humano , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Programação Linear , Análise de Sequência de DNA
8.
Food Nutr Bull ; 42(2): 274-288, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-34002635

RESUMO

BACKGROUND: Lack of dietary diversity in complementary feeding contributes to nutrient gaps leading to undernutrition. Food-based strategies have been successfully used to enrich the complementary diets of infants and young children. However, context-specific recommendations based on an objective diet optimization are needed to formulate sound and practical nutritional guidelines. OBJECTIVES: The present study aimed to identify problem nutrients in complementary diets and formulate complementary feeding recommendations (CFRs) using linear programming analysis for children aged 6 to 23 months in the rural Philippines. METHODS: A cross-sectional survey was conducted in the municipality of Mercedes, Philippines. Dietary intakes of breastfed children 6 to 8, 9 to 11, and 12 to 23 months of age (n = 297) were assessed using a multipass 24-hour recall method with 7-day food consumption frequency. A linear programming tool was used to identify the recommended nutrient intakes that could not be met within the existing local food patterns and develop CFRs that would best fulfill nutrient adequacy for 11 modeled micronutrients. RESULTS: Problem nutrients in the current diets were iron and calcium in any age-group, zinc for 6 to 8 and 9 to 11 months old, and thiamine and folate for 12 to 23 months old children. Adoption of CFRs with 4 to 5 food groups in the diet would ensure the adequacy of 7 to 8 nutrients, depending on the age-group. CONCLUSION: Within the boundaries of local dietary patterns, adequacy for most nutrients could be achieved by promoting realistic servings of nutrient-dense foods and food groups. The linear programming results provide an evidence-based strategy in designing interventions to improve the quality of Filipino complementary diets.


Assuntos
Aleitamento Materno , Programação Linear , Criança , Pré-Escolar , Estudos Transversais , Dieta , Ingestão de Alimentos , Feminino , Humanos , Lactente , Fenômenos Fisiológicos da Nutrição do Lactente , Micronutrientes , Filipinas
9.
BMC Public Health ; 21(1): 891, 2021 05 10.
Artigo em Inglês | MEDLINE | ID: mdl-33971851

RESUMO

BACKGROUND: Food cost and affordability is one of the main barriers to improve the nutritional quality of diets of the population. However, in Argentina, where over 60% of adults and 40% of children and adolescents are overweight or obese, little is known about the difference in cost and affordability of healthier diets compared to ordinary, less healthy ones. METHODS: We implemented the "optimal approach" proposed by the International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support (INFORMAS). We modelled the current diet and two types of healthy diets, one equal in energy with the current diet and one 6.3% lower in energy by linear programming. Cost estimations were performed by collecting food product prices and running a Monte Carlo simulation (10,000 iterations) to obtain a range of costs for each model diet. Affordability was measured as the percentage contribution of diet cost vs. average household income in average, poor and extremely poor households and by income deciles. RESULTS: On average, households must spend 32% more money on food to ensure equal energy intake from a healthy diet than from a current model diet. When the energy intake target was reduced by 6.3%, the difference in cost was 22%. There are no reasonably likely situations in which any of these healthy diets could cost less or the same than the current unhealthier one. Over 50% of households would be unable to afford the modelled healthy diets, while 40% could not afford the current diet. CONCLUSIONS: Differential cost and affordability of healthy vs. unhealthy diets are germane to the design of effective public policies to reduce obesity and NCDs in Argentina. It is necessary to implement urgent measures to transform the obesogenic environment, making healthier products more affordable, available and desirable, and discouraging consumption of nutrient-poor, energy-rich foods.


Assuntos
Dieta Saudável , Programação Linear , Adolescente , Adulto , Argentina , Criança , Custos e Análise de Custo , Dieta , Alimentos , Humanos
10.
Artigo em Inglês | MEDLINE | ID: mdl-33946999

RESUMO

The rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel reverse supply chain (DRSC). The adoption of DRSC will make the system lose stability and fall into the trap of complexity. Further the consumer-related factors, such as consumer preference, service level, have also severely affected the system efficiency of DRSC. Therefore, it is necessary to help DRSCs to design their networks for maintaining competitiveness and profitability. This paper focuses on the issues of quantitative modelling for the network design of a general multi-echelon, dual-objective DRSC system. By incorporating consumer preference for the online recycling channel into the system, we investigate a mixed integer linear programming (MILP) model to design the DRSC network with uncertainty and the model is solved using the ε-constraint method to derive optimal Pareto solutions. Numerical results show that there exist positive correlations between consumer preference and total collective quantity, online recycling price and the system profits. The proposed model and solution method could assist recyclers in pricing and service decisions to achieve a balance solution for economic and environmental sustainability.


Assuntos
Comportamento do Consumidor , Reciclagem , Comércio , Custos e Análise de Custo , Programação Linear
11.
Neuron ; 109(9): 1433-1448, 2021 05 05.
Artigo em Inglês | MEDLINE | ID: mdl-33689687

RESUMO

Over the past few decades, neuroscience experiments have become increasingly complex and naturalistic. Experimental design has in turn become more challenging, as experiments must conform to an ever-increasing diversity of design constraints. In this article, we demonstrate how this design process can be greatly assisted using an optimization tool known as mixed-integer linear programming (MILP). MILP provides a rich framework for incorporating many types of real-world design constraints into a neuroscience experiment. We introduce the mathematical foundations of MILP, compare MILP to other experimental design techniques, and provide four case studies of how MILP can be used to solve complex experimental design challenges.


Assuntos
Modelos Neurológicos , Modelos Teóricos , Neurociências/métodos , Programação Linear , Projetos de Pesquisa , Animais , Humanos
12.
Ground Water ; 59(4): 503-516, 2021 07.
Artigo em Inglês | MEDLINE | ID: mdl-33533499

RESUMO

Due to increasing water demands globally, freshwater ecosystems are under constant pressure. Groundwater resources, as the main source of accessible freshwater, are crucially important for irrigation worldwide. Over-abstraction of groundwater leads to declines in groundwater levels; consequently, the groundwater inflow to streams decreases. The reduction in baseflow and alteration of the streamflow regime can potentially have an adverse effect on groundwater-dependent ecosystems. A spatially distributed, coupled groundwater-surface water model can simulate the impacts of groundwater abstraction on aquatic ecosystems. A constrained optimization algorithm and a simulation model in combination can provide an objective tool for the water practitioner to evaluate the interplay between economic benefits of groundwater abstractions and requirements to environmental flow. In this study, a holistic catchment-scale groundwater abstraction optimization framework has been developed that allows for a spatially explicit optimization of groundwater abstraction, while fulfilling a predefined maximum allowed reduction of streamflow (baseflow [Q95] or median flow [Q50]) as constraint criteria for 1484 stream locations across the catchment. A balanced K-Means clustering method was implemented to reduce the computational burden of the optimization. The model parameters and observation uncertainties calculated based on Bayesian linear theory allow for a risk assessment on the optimized groundwater abstraction values. The results from different optimization scenarios indicated that using the linear programming optimization algorithm in conjunction with integrated models provides valuable information for guiding the water practitioners in designing an effective groundwater abstraction plan with the consideration of environmental flow criteria important for the ecological status of the entire system.


Assuntos
Água Subterrânea , Teorema de Bayes , Ecossistema , Programação Linear , Rios , Abastecimento de Água
13.
Health Care Manag Sci ; 24(1): 140-159, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33483910

RESUMO

A new scheduling problem arising in the home care context is addressed, whose novelty with respect to the literature lies in the way overtime is paid. In this problem, some clients are willing to pay a higher fee to cover the additional overtime cost, if such overtime is incurred because a caregiver works extra time with the client to preserve continuity of care. These overtime hours charged to clients unburden the company, which no longer has to balance between cost and continuity of care in a traditional way. The problem is also studied in a context that includes preferences expressed by both clients and caregivers. Strict preferences must be respected with a high priority, while soft preferences increase the satisfaction and should be preferably respected. We formalize the problem as a Mixed Integer Linear Problem and also propose a cluster-based decomposition to solve real-life instances. The problem is inspired by the real case study of a provider operating in the USA. Numerical results validate the model and confirm the capability of the decomposition approach to deal with real-life instances.


Assuntos
Agendamento de Consultas , Serviços de Assistência Domiciliar/economia , Serviços de Assistência Domiciliar/organização & administração , Continuidade da Assistência ao Paciente , Humanos , Programação Linear , Fatores de Tempo , Transportes
14.
Physiol Behav ; 233: 113337, 2021 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-33493544

RESUMO

This study aimed to compare the effect of linear (LP) and daily-undulating (DUP) programming models on neuromuscular and functional performance using the velocity-based resistance training (VBRT) approach. Thirty-two resistance trained men were randomly assigned into 2 groups: LP (n = 16) or DUP (n = 16). Both training groups completed an 8-week VBRT intervention using the full squat exercise, only differing in the relative intensity (% 1RM) distribution during the training program. Changes produced by each periodization model were evaluated using the following variables: estimated 1RM; average mean propulsive velocity (MPV) attained for all absolute loads common to Pre-test and Post-test; average MPV attained against absolute loads lifted faster than 1 m•s-1; average MPV attained against absolute loads lifted slower than 1 m•s - 1; countermovement jump (CMJ) and fatigue test. Moreover, CMJ and 1RM parameters were evaluated weekly to analyze their evolution along the training program. LP and DUP strategies significantly improved all performance variables analyzed (p<0.001), except the fatigue test in the DUP group. Significant "time x group" interactions were observed in all strength variables and fatigue test in favour of the LP group. In addition, pre-post effect size (ES), percentages of change and weekly comparisons showed higher improvements in the LP group (ES=0.54-2.49, ∆=9.5-60.4%) compared to DUP (ES=0.40-1.65, ∆=5.5-27.2%). Based on these findings, the LP appears to stand as a more effective strategy than DUP to achieve greater, earlier and uninterrupted neuromuscular and functional adaptations in VBRT interventions.


Assuntos
Treinamento de Força , Adaptação Fisiológica , Humanos , Masculino , Força Muscular , Músculo Esquelético , Postura , Programação Linear
15.
Environ Sci Pollut Res Int ; 28(14): 18004-18020, 2021 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-33403639

RESUMO

In order to achieve at better water quality of a given trans-boundary river mainly contributed by high-intensive and spatially dispersed pig farming at upstream area, an effective ecological compensation system is in urgent need. In this study, an evolutionary bottom-up framework of ecological compensation system was proposed to analyze the tradeoffs of behavior among the pig farmers, government of upstream area, and government of downstream area. Shutting down pig farms, upgrading traditional piggeries to elevated bed piggeries, and adopting centralized facilities for disposing wastes from small-scale pig farms are three effective measures to control pollution from pig farming and were considered into this study. The combined use of cost-benefit analysis, linear programming, willingness to accept and willingness to pay method, and its application to a typical case of Jiuzhou River, China, showed good performance to quantify short-term and long-term watershed ecological compensation standard and amount for promoting sustainability of livestock industry. Besides, we also proposed a framework of long-term reward and punishment compensation mechanism binding upon both sides for maintaining good water quality. The proposed systematic and feasible framework of methodology has important theoretical and application significance for other similar related researches and enriched the field in paying for good water quality.


Assuntos
Gado , Programação Linear , Animais , China , Análise Custo-Benefício , Padrões de Referência , Suínos
16.
Public Health Nutr ; 24(7): 1952-1961, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33118911

RESUMO

OBJECTIVE: Sustainable diets are diets with low environmental impacts and high affordability which contribute to food and nutrition security. The present study aimed to develop a healthy, low-cost and environmental-friendly food basket for Iran based on current consumption. DESIGN: The Households Income and Expenditure Survey data were used. Linear Programming was utilised to obtain the optimal diets, separately, for each goal of the sustainable food basket: (1) Diet with maximum Nutrient Rich Food (NRF) index, (2) Diet with minimum cost, (3) Diet with the minimum water footprint and (4) Diet with the minimum carbon footprint. Goal Programming techniques were used to optimise the sustainable food basket by considering all goals simultaneously. SETTING: Iran. PARTICIPANTS: Households (n 100 500) in urban and rural areas of Iran, nationally representative. RESULTS: In the 'optimal model', compared with the usual consumption, the amount of the 'bread, cereal, rice, and pasta', 'meat, poultry, fish, eggs, legumes, and nuts' and 'fats, oils, sugars, and sweets' groups was decreased. Inside those food groups, cereals, poultry and vegetable oil subgroups were increased. Also, dairy, fruits and vegetable groups were increased. In this model, there was a 14 % reduction in the total water footprint, a 14 % decrease in the total carbon footprint, a 23 % decrease in the cost and a 7 % increase in NRF of diet compared with the usual consumption. CONCLUSIONS: Increasing the consumption of dairy, fruits and vegetables and reducing the consumption of bread, rice, pasta, meat, fish, eggs, legumes, nuts, hydrogenated fats and sugars are required to achieve a sustainable food basket.


Assuntos
Dieta , Verduras , Animais , Frutas , Humanos , Nozes , Programação Linear
17.
Environ Sci Pollut Res Int ; 28(8): 10192-10206, 2021 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-33174176

RESUMO

With the increasing number of car trips in cities, energy consumption and environmental pollution have become key issues in urban transportation. In particular, the increasing use of private cars not only leads to more energy consumption and produces more waste gas, but also makes the traffic structure unbalanced. Therefore, it is necessary to establish and optimize the reasonable traffic structure in order to promote the sustainable development of urban traffic. Based on the characteristics of different transportation modes, this paper proposes a multi-objective optimization model that maximizes transportation utility, minimizes ecological impact, and minimizes generalized cost. The ideal point method, linear weighting method, and hierarchical sequence method were used to solve and compare the model. It has been concluded that the ideal point method is more suitable for the research of this paper and can be applied to optimize the traffic structure of Beijing. Through example analysis, the optimized urban passenger traffic turnover and sharing rate are more scientific and reasonable, which verifies the feasibility of the model. This model not only guarantees the interests of passengers and reduces carbon emissions, it also maximizes the utility of urban traffic and the lowest generalized cost. It reflects the concept of sustainable development of urban transportation. Finally, we are able to make reasonable suggestions to relevant departments based on the optimization results.


Assuntos
Programação Linear , Transportes , Automóveis , Pequim , Cidades , Emissões de Veículos/análise
18.
Ann Sci ; 78(1): 1-21, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-32893729

RESUMO

At the beginning of the 13th century Fibonacci described the rules for making mixtures of all kinds, using the Hindu-Arabic system of arithmetic. His work was repeated in the early printed books of arithmetic, many of which contained chapters on 'alligation', as the subject became known. But the rules were expressed in words, so the subject often appeared difficult, and occasionally mysterious. Some clarity began to appear when Thomas Harriot introduced a modern form of algebraic notation around 1600, and he was almost certainly the first to express the basic rule of alligation in algebraic terms. Thus a link was forged with the work on Diophantine problems that occupied mathematicians like John Pell and John Kersey in the 17th century. Joseph Fourier's work on mechanics led him to suggest a procedure for handling linear inequalities based on a combination of logic and algebra; he also introduced the idea of describing the set of feasible solutions geometrically. In 1898, inspired by Fourier's work, Gyula Farkas proved a fundamental theorem about systems of linear inequalities. This topic eventually found many applications, and it became known as Linear Programming. The theorem of Farkas also plays a significant role in Game Theory.


Assuntos
Matemática/história , Programação Linear/história , História do Século XVI , História do Século XVII , História do Século XVIII , História do Século XIX
19.
IEEE Trans Biomed Eng ; 68(4): 1106-1114, 2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-32746026

RESUMO

OBJECTIVE: The use of a close-fitting roughly head-shaped volume coil for MRI (magnetic resonance imaging) has the merit of improving the filling factor and thus the SNR (signal-to-noise ratio) from the brain. However, the surface of the RF coil follows that of the head which makes it difficult to determine an optimal coil winding pattern. We describe here a new method to optimize a head-shaped RF coil with the objective of maximizing its SNR and RF-magnetic-field homogeneity for operation at ultra-low magnetic field (6.5 mT, 276 kHz). METHODS: The approach consists of FEM (finite-element-method) simulation and linear programing based optimization. RESULTS: We have implemented the optimization and further studied the relationship between the design requirements and the performance of the RF coil. Finally, we constructed an optimal RF coil and scanned both a head-shaped phantom and a human subject. CONCLUSION: The method we outline here provide new insight into the conductor layout needed for magnetic optimization of structurally complex coils, especially when tradeoffs between competing attributes (SNR and homogeneity in this case) must be made.


Assuntos
Programação Linear , Ondas de Rádio , Encéfalo/diagnóstico por imagem , Desenho de Equipamento , Humanos , Imageamento por Ressonância Magnética , Neuroimagem , Imagens de Fantasmas
20.
Bioinformatics ; 37(8): 1083-1092, 2021 05 23.
Artigo em Inglês | MEDLINE | ID: mdl-33135733

RESUMO

MOTIVATION: The study of the evolutionary history of biological networks enables deep functional understanding of various bio-molecular processes. Network growth models, such as the Duplication-Mutation with Complementarity (DMC) model, provide a principled approach to characterizing the evolution of protein-protein interactions (PPIs) based on duplication and divergence. Current methods for model-based ancestral network reconstruction primarily use greedy heuristics and yield sub-optimal solutions. RESULTS: We present a new Integer Linear Programming (ILP) solution for maximum likelihood reconstruction of ancestral PPI networks using the DMC model. We prove the correctness of our solution that is designed to find the optimal solution. It can also use efficient heuristics from general-purpose ILP solvers to obtain multiple optimal and near-optimal solutions that may be useful in many applications. Experiments on synthetic data show that our ILP obtains solutions with higher likelihood than those from previous methods, and is robust to noise and model mismatch. We evaluate our algorithm on two real PPI networks, with proteins from the families of bZIP transcription factors and the Commander complex. On both the networks, solutions from our ILP have higher likelihood and are in better agreement with independent biological evidence from other studies. AVAILABILITY AND IMPLEMENTATION: A Python implementation is available at https://bitbucket.org/cdal/network-reconstruction. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Algoritmos , Programação Linear , Probabilidade , Proteínas
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