The multi-visit drone-assisted pickup and delivery problem with time windows

We consider a new combined truck-drone routing problem with time windows in the context of last-mile logistics. A fleet of trucks, each equipped with an identical drone, is scheduled to provide both pickup and delivery services to a set of customers with minimum cost. Some customers are paired, in that the goods picked up from one must be delivered to the other on the same route. Drones are launched from and retrieved by trucks at a pool of designated stations, which can be used multiple times. Each drone can serve multiple customers in one flight. We formulate this problem as a large-scale mixed-integer bilinear program, with the bilinear terms used to calculate the load-time-dependent energy consumption of drones. To accelerate the solution process, multiple valid inequalities are proposed. For large-size problems, we develop a customised adaptive large neighbourhood search (ALNS) algorithm, which includes several preprocessing procedures to quickly identify infeasible solutions and accelerate the search process. Moreover, two feasibility test methods are developed for trucks and drones, along with an efficient algorithm to determine vehicles’ optimal waiting time at launch stations, which is important to consider due to the time windows. Extensive numerical experiments demonstrate the effectiveness of the valid inequalities and the strong performance of the proposed ALNS algorithm over two benchmarks in the literature, and highlight the cost-savings of the combined mode over the truck-only mode and the benefits of allowing multiple drone visits

Genetic testing and prognosis of sarcomatoid hepatocellular carcinoma patients

BackgroundSarcomatoid hepatocellular carcinoma (SHC) is a rare epithelial malignancy with high invasiveness and poor prognosis. However, the molecular characteristics and main driver genes for SHC have not been determined. The aim of this study is to explore the potentially actionable mutations of driver genes, which may provide more therapeutic options for SHC.MethodsIn this study, DNA extraction and library preparation were performed using tumor tissues from 28 SHC patients. Then we used Miseq platform (Illumina) to sequence the target-enriched library, and we aligned and processed the sequencing data. The gene groups were tested for SNVs/Indels/CNVs. Tumor mutation burden (TMB) was assessed by the 425-cancer-relevant gene panel. Multivariate analysis of COX’s model was used for survival analysis (OS) of patients’ clinical characteristics.ResultThe median overall survival (OS) of the patients was only 4.4 months. TP53, TERT, and KRAS were the top three frequently mutated genes, with frequencies of 89.3%, 64.3%, and 21.4%, respectively. A considerable number of patients carried mutations in genes involved in the TP53 pathway (96%) and DNA Damage Repair (DDR) pathway (21%). Multiple potentially actionable mutations, such as NTRK1 fusions and BRCA1/2 mutations, were identified in SHCs.ConclusionsThis study shows a landscape of gene mutations in SHC. SHC has high mutation rates in TP53 pathway and DDR pathway. The potentially actionable mutations of driver genes may provide more therapeutic options for SHC. Survival analysis found that age, smoking, drinking, and tumor diameter may be independent prognostic predictors of SHC

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Multi-objective optimization design for the multi-bubble pressure cabin in BWB underwater glider

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method. Keywords: Multi-objective optimization, Multi-bubble pressure cabin, Finite element analysis, Kriging, NSGA-II, TOPSI

Self-Organized Patchy Target Searching and Collecting with Heterogeneous Swarm Robots Based on Density Interactions

The issue of searching and collecting targets with patchy distribution in an unknown environment is a challenging task for multiple or swarm robots because the targets are unevenly dispersed in space, which makes the traditional solutions based on the idea of path planning and full spatial coverage very inefficient and time consuming. In this paper, by employing a novel framework of spatial-density-field-based interactions, a collective searching and collecting algorithm for heterogeneous swarm robots is proposed to solve the challenging issue in a self-organized manner. In our robotic system, two types of swarm robots, i.e., the searching robots and the collecting robots, are included. To start with, the searching robots conduct an environment exploration by means of formation movement with Levy flights; when the targets are detected by the searching robots, they spontaneously form a ring-shaped envelope to estimate the spatial distribution of targets. Then, a single robot is selected from the group to enter the patch and locates at the patch’s center to act as a guiding beacon. Subsequently, the collecting robots are recruited by the guiding beacon to gather the patch targets; they first form a ring-shaped envelope around the target patch and then push the scattered targets inward by using a spiral shrinking strategy; in this way, all targets eventually are stacked near the center of the target patch. With the cooperation of the searching robots and the collecting robots, our heterogeneous robotic system can operate autonomously as a coordinated group to complete the task of collecting targets in an unknown environment. Numerical simulations and real swarm robot experiments (up to 20 robots are used) show that the proposed algorithm is feasible and effective, and it can be extended to search and collect different types of targets with patchy distribution

Experimental research on Chinese antique buildings with dual-lintel-column joint of steel and composite structures

In order to study the mechanical behavior of Chinese traditional style architecture dual-lintel-column joint, a typical Chinese traditional style architecture dual-lintel-column joint was selected as the model structure. Two specimens with viscous damper and one specimen without viscous damper were designed and tested under fast harmonic load. On the basis of experimental study, the key indexes of mechanical properties are analyzed, such as the load–displacement hysteretic curve of specimens and viscous damper, skeleton curve, and load-bearing capacity. The results indicate that mechanical properties of antique buildings dual-lintel-column subassemblages with steel and composite structures and viscous damper can significantly increase the mechanical properties. The hysteretic curve of the damping joint is plump. The descending phase of skeleton curves is smoother. The carrying capacity is increased by 13.9%–14.1%, and displacement ductility is increased by 13.0%–18.6%. The viscous damper and the dual-lintel-column subassemblages work together. They significantly improve the deformation performance of structures at the failure stage and enhance the collapse resistance of the structure. The study of traditional architecture can also provide valuable insights into the development of structural engineering and construction technology. Also, people can learn the wisdom and experience of ancestors and apply it to modern engineering practices