Evolving test instances of the Hamiltonian completion problem

Predicting and comparing algorithm performance on graph instances is challenging for multiple reasons. First, there is usually no standard set of instances to benchmark performance. Second, using existing graph generators results in a restricted spectrum of difficulty and the resulting graphs are usually not diverse enough to draw sound conclusions. That is why recent work proposes a new methodology to generate a diverse set of instances by using an evolutionary algorithm. We can then analyze the resulting graphs and get key insights into which attributes are most related to algorithm performance. We can also fill observed gaps in the instance space in order to generate graphs with previously unseen combinations of features. This methodology is applied to the instance space of the Hamiltonian completion problem using two different solvers, namely the Concorde TSP Solver and a multi-start local search algorithm.Comment: 12 pages, 12 figures, minor revisions in section

Dark Matter reconstruction from stellar orbits in the Galactic Centre

Context. Current constraints on distributed matter in the innermost Galactic Centre (such as a cluster of faint stars and stellar remnants, Dark Matter or a combination thereof) based on the orbital dynamics of the visible stars closest to the central black hole, typically assume simple functional forms for the distributions. Aims. We take instead a general model agnostic approach in which the form of the distribution is not constrained by prior assumptions on the physical composition of the matter. This approach yields unbiased - entirely observation driven - fits for the matter distribution and places constraints on our ability to discriminate between different density profiles (and consequently between physical compositions) of the distributed matter. Methods. We construct a spherical shell model with the flexibility to fit a wide variety of physically reasonable density profiles by modelling the distribution as a series of concentric mass shells. We test this approach in an analysis of mock observations of the star S2. Results. For a sufficiently large and precise data set, we find that it is possible to discriminate between several physically motivated density profiles. However, for data coming from current and expected next generation observational instruments, the potential for profile distinction will remain limited by the precision of the instruments. Future observations will still be able to constrain the overall enclosed distributed mass within the apocentre of the probing orbit in an unbiased manner. We interpret this in the theoretical context of constraining the secular versus non-secular orbital dynamics.Comment: 8 pages, 4 figures, submitted to Astronomy & Astrophysic

Automated Semiconductor Defect Inspection in Scanning Electron Microscope Images: a Systematic Review

A growing need exists for efficient and accurate methods for detecting defects in semiconductor materials and devices. These defects can have a detrimental impact on the efficiency of the manufacturing process, because they cause critical failures and wafer-yield limitations. As nodes and patterns get smaller, even high-resolution imaging techniques such as Scanning Electron Microscopy (SEM) produce noisy images due to operating close to sensitivity levels and due to varying physical properties of different underlayers or resist materials. This inherent noise is one of the main challenges for defect inspection. One promising approach is the use of machine learning algorithms, which can be trained to accurately classify and locate defects in semiconductor samples. Recently, convolutional neural networks have proved to be particularly useful in this regard. This systematic review provides a comprehensive overview of the state of automated semiconductor defect inspection on SEM images, including the most recent innovations and developments. 38 publications were selected on this topic, indexed in IEEE Xplore and SPIE databases. For each of these, the application, methodology, dataset, results, limitations and future work were summarized. A comprehensive overview and analysis of their methods is provided. Finally, promising avenues for future work in the field of SEM-based defect inspection are suggested.Comment: 16 pages, 12 figures, 3 table

Impact of HPV Infection on the Immune System in Oropharyngeal and Non-Oropharyngeal Squamous Cell Carcinoma: A Systematic Review

OBJECTIVES: To review the current knowledge regarding the involvement of human papilloma virus (HPV) infection and the immune system in the development of head and neck squamous cell carcinoma (HNSCC). METHODS: An electronic literature search was conducted to identify articles published between 1990 and 2019 pertaining to tumor-infiltrating immune cells (TICs) in HNSCC using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Issues of clinical relevance, including tumor location, the number of tumor samples, the inclusion of additional specimens (dysplastic or normal mucosa), tumor size, methods used for HPV detection, relationship between antigen expression and patient characteristics (age, gender, smoking, alcohol consumption, etc.), and prognostic data (overall survival (OS) and recurrence-free survival (RFS)) were assessed by four blinded investigators. RESULTS: The search identified 335 relevant studies, of which 41 met the inclusion criteria. Of these, 7 studies focused on the peripheral blood immune cell concentration in patients with HNSCC according to HPV status, and 36 studies investigated TICs in the intraepithelial and/or stromal compartment(s) according to HPV status. The immune cells studied were CD8+ T cells (N = 19), CD4+ T cells (N = 7), regulatory T cells (Tregs, N = 15), macrophages (N = 13), myeloid-derived suppressor cells (MDSCs, N = 4), and Langerhans cells (LCs, N = 2). CONCLUSIONS: Irrespective of tumor location, CD8+ and CD4+ T cells appear to play a key role in the development of HPV-related HNSCC, and their infiltration is likely associated with a significant impact on OS and RFS. To date, the roles and prognostic value of Tregs, macrophages, DCs and MDSCs remain unclear.SCOPUS: ar.jinfo:eu-repo/semantics/publishe