Deep Policy Dynamic Programming for Vehicle Routing Problems

Routing problems are a class of combinatorial problems with many practical applications. Recently, end-to-end deep learning methods have been proposed to learn approximate solution heuristics for such problems. In contrast, classical dynamic programming (DP) algorithms guarantee optimal solutions, but scale badly with the problem size. We propose Deep Policy Dynamic Programming (DPDP), which aims to combine the strengths of learned neural heuristics with those of DP algorithms. DPDP prioritizes and restricts the DP state space using a policy derived from a deep neural network, which is trained to predict edges from example solutions. We evaluate our framework on the travelling salesman problem (TSP), the vehicle routing problem (VRP) and TSP with time windows (TSPTW) and show that the neural policy improves the performance of (restricted) DP algorithms, making them competitive to strong alternatives such as LKH, while also outperforming most other 'neural approaches' for solving TSPs, VRPs and TSPTWs with 100 nodes.Comment: 21 page

Targeted Next-Generation Sequencing Study in Familial ALS-FTD Portuguese Patients Negative for C9orf72 HRE

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with clinical and etiological heterogeneity and a complex genetic contribution. Clinical, neuropathological, and genetic evidence revealed that ALS and frontotemporal dementia (FTD) are in part of a single disease continuum. Genetic causes have been identified in sporadic (SALS) and familial patients (FALS) and the recurrent genetic factor underlying ALS and FTD is the C9orf72 hexanucleotide repeat expansion (HRE). However, in our population, the concomitance of ALS and FTD cannot be explained by C9orf72 HRE in many FALS and SALS cases. Our aim is to further understand the genetic basis of ALS in Portuguese patients. 34 patients with FALS or SALS-FTD, negative for C9orf72 HRE, were screened for rare variants in a panel of 29 relevant genes by next-generation sequencing. We detected 15 variants in 11 genes, one classified as pathogenic in TARDBP, two as likely pathogenic in TARDBP and PRPH, and the others as variants of unknown significance (VUS). Gene variants, including VUS, were found in 41.2% FALS patients and 40% SALS-FTD. In most patients, no potential pathogenic variants were found. Our results emphasize the need to enhance the efforts to unravel the genetic architecture of ALS-FTD.info:eu-repo/semantics/publishedVersio

Investigating LGALS3BP/90 K glycoprotein in the cerebrospinal fluid of patients with neurological diseases

© The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Galectin-3 binding protein (LGALS3BP or 90 K) is a secreted glycoprotein found in human body fluids. Deregulated levels were observed in cancer and infection and its study in neurological diseases is more recent. Here, we have investigated 90 K from human cerebrospinal fluid (CSF) of patients with amyotrophic lateral sclerosis (ALS, n = 35) and other neurological diseases (n = 23). CSF was fractionated by ultrafiltration/size-exclusion chromatography (SEC) and eluted fractions were analysed by complementary techniques including immunoblotting, electron microscopy and nano-liquid chromatography-tandem mass spectrometry. A fraction of 90 K appeared as nanoparticles of irregular shape with heterogeneous dimensions of 15-60 nm that co-eluted with extracellular vesicles in SEC. Median levels of 90 K quantified by ELISA were not different between ALS patients (215.8 ng/ml) and controls (213.3 ng/ml) in contrast with the benchmark biomarker for ALS phosphoneurofilament heavy chain (1750 and 345 pg/ml, respectively). A multiregression model supported age is the only independent predictor of 90 K level in both groups (p < 0.05). Significant correlation was found between 90 K levels and age for the ALS group (r = 0.366, p = 0.031) and for all subjects (r = 0.392, p = 0.003). In conclusion, this study unveils the presence of 90 K-containing nanoparticles in human CSF and opens novel perspectives to further investigate 90 K as potential aging marker.This work was supported by Euronanomed 2 ERA-NET project GlioEx (ENMed/0001/2013), Fundação para a Ciência e a Tecnologia (FCT), Portugal; iNOVA4Health Research Unit (LISBOA-01–0145-FEDER-007344), which is cofunded by FCT/Ministério da Ciência e do Ensino Superior, through national funds; and by FEDER under the PT2020 Partnership Agreement.info:eu-repo/semantics/publishedVersio

Distance Approximation for Dynamic Waste Collection Planning

Approximating the solution value of transportation problems has become more relevant in recent years, as these approximations can help to decrease the computational eort required for solving those routing problems. In this paper, we apply several regression methods to predict the total distance of the traveling salesman problem (TSP) and vehicle routing problem (VRP). We show that distance can be estimated fairly accurately using simple regression models and only a limited number of features. We use features found in scientific literature and introduce a new class of geographical features. The model is validated on a dynamic waste collection case in the city of Amsterdam, The Netherlands. We introduce a cost function that combines the travel distance and service level, and show that our model can reduce distances up to 17%, while maintaining the same service level, compared to a well-known heuristic approximation. Furthermore, we show the benefits of using approximations for combining oine learning with online or frequent optimization

A deep cut ellipsoid algorithm for convex programming

This paper proposes a deep cut version of the ellipsoid algorithm for solving a general class of continuous convex programming problems. In each step the algorithm does not require more computational effort to construct these deep cuts than its corresponding central cut version. Rules that prevent some of the numerical instabilities and theoretical drawbacks usually associated with the algorithm are also provided. Moreover, for a large class of convex programs a simple proof of its rate of convergence is given and the relation with previously known results is discussed. Finally some computational results of the deep and central cut version of the algorithm applied to a min—max stochastic queue location problem are reported

General models in min-max continous location

In this paper, a class of min-max continuous location problems is discussed. After giving a complete characterization of th stationary points, we propose a simple central and deep-cut ellipsoid algorithm to solve these problems for the quasiconvex case. Moreover, an elementary convergence proof of this algorithm and some computational results are presented

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons