Abstract Background Intratumour heterogeneity is recognised across different tumour types and has implications for therapeutic resistance. At present, clinical practice often relies upon molecular information derived from a single biopsy of a primary or metastatic tumour. This information guides treatment choice but may not be representative of the diversity of the tumour. It is currently difficult to evaluate how effectively a single region guides treatment decisions because the formalin-fixed residual surgical sample that is not paraffin embedded for diagnostic purposes is typically thrown away. Retention and homogenisation – ‘blending’- of this residual formalin-fixed leftover tumour tissue creates a more representative sample for analysis. DNA may be extracted from this sample for sequencing. Pilot data in kidney cancer has demonstrated the potential of this methodology for robust mutational calling, accurate determination of cancer cell fraction and the ability to discern clonal from subclonal variants. Such information may be clinically relevant; for example, discerning resistant subclones prior to treatment, or identifying clonal neoantigens worth targeting with immunotherapy. Trial design In order to establish the feasibility of homogenization as a potential companion diagnostic tool, our study aims to 1) identify the proportion of primary tumour cases that have left over tissue amenable to homogenization across multiple tumour types and 2) pilot homogenization across multiple tumour types. The molecular profile of the homogenate will be compared to that obtained from the diagnostic specimen using next generation sequencing techniques. This is a prospective non-interventional study (NCT03832062). Patients undergoing surgical intervention at The Royal Marsden Hospital (NHS Foundation Trust) with leftover tumour tissue from primary breast, colorectal, gastric, pancreatic, ovarian, renal cancer and sarcoma surgeries, as well as melanoma lymph node dissections will be included in the feasibility assessment. We plan to homogenise 500 cases across different tumour types. The study opened in September 2018 and is expected to run for 2 years. Clinical trial identification NCT03832062; Release date: February 2019. Legal entity responsible for the study Royal Marsden NHS Foundation Trust. Funding Ventana Medical Systems (a subsidiary of Roche). Disclosure L. Gallegos: Full / Part-time employment: Roche. S. Hill: Full / Part-time employment: Roche. A. Barhoumi: Full / Part-time employment: Roche. S. Stanislaw: Full / Part-time employment: Roche. M. Mendoza: Full / Part-time employment: Roche. J.M.G. Larkin: Research grant / Funding (institution): Roche; Advisory / Consultancy: Roche. N. Alexander: Full / Part-time employment: Roche; Shareholder / Stockholder / Stock options: Roche. S. Turajlic: Research grant / Funding (institution): Ventana Medical Systems (subsidiary of Roche). All other authors have declared no conflicts of interest.

Abstract Background In 2017 a new PN led clinic was established for immunotherapy patients. At the 1-year mark to ensure patients were satisfied with the service provision, a patient experience survey was conducted. The survey explored if patients felt comfortable in discussing side effects with the PN and if they felt part of their treatment related decisions. Importantly patients were asked if they had confidence and trust in the PN. Methods The survey was provided to all patients whom attended the PN led clinic from May 2017 to May 2018. The survey consisted of 10 closed questions using the Likert scale, with spaces provided for personal comments. Data collection period was 1.06.18 to 29.06.18. Estimated number of patients was 10. Results Questionnaires were provided to a total of 10 patients. Three questionnaires could not be provided to 3 patients whom attended the PN led clinic as they had died. Two patients did not respond back. 6/8 patients strongly agreed (SAg) to feeling comfortable in discussing treatment related side effects and 2/8 patients agreed (Ag). This same result was found when patients were asked if they felt involved in the decisions related to their care e.g. stopping immunotherapy treatment at 2 yrs. With respect to having confidence and trust with the advice and care provided by the PN, 7 patients SAg and 1 Ag. All patients felt that they were being listened to and had the opportunity to ask questions during their consultations (7 patients SAg and 1 Ag). Reassuringly all 8 patients said that they would recommend this service to their friends and family (7 patients SAg and 1 Ag). Conclusions This survey was to ensure patients were satisfied with being reviewed by a PN and as the service was new to the melanoma unit in 2017; it was vital that the patients had the opportunity to evaluate the service provision. With this positive feedback the clinic was expanded from September 2018 and to date 36 patients have now been seen within the PN led immunotherapy clinic and another patient experience survey is due. Legal entity responsible for the study The authors. Funding Has not received any funding. Disclosure All authors have declared no conflicts of interest.

As memories are becoming a ubiquitous and indispensable part of electronic devices across all industrial domains, the importance of their reliability and fault-tolerance increases. This especially holds for safety-critical applications, which exhibit different levels of data criticality. As a consequence, recent research aims to proactively engage environmentally induced soft errors, by developing new methods for error detection, mitigation, and data recovery in the mixed-critical memories. This article presents a flexible soft error correction strategy called Redundant Parity (RP), designed to enhance existing 1oo2 architectures. RP extends a 1oo2 system's ability of fault detection by enabling the recovery of faulty data utilizing the parity bit concept. An initial evaluation of the strategy in terms of its runtime performance and memory overhead is performed and compared with other software-based mitigation strategies. The preliminary results suggest that RP is indeed a suitable soft error mitigation strategy in existing 1oo2 fail-safe systems.

Distribution network power flow (DNPF) is a core application of distribution management system (DMS). Two methods to implement fast DNPF are using Newton-Raphson (NR) approach and current iteration (CI) approach. In distribution systems with high penetration of renewable energy sources both methods must be able to model PV nodes correctly and efficiently. This paper explores implementations of NR DNPF and CI DNPF, their execution time and performance in networks with numerous distributed generators.

The vision of the smart-city environment is based on a large number of sensors, actuators, devices connected to the Internet. As interest in the practical implementation of the smart city environment increases, so does the interest in examining network connectivity which can be useful for investigating security vulnerabilities, identifying or blocking traffic accessibility (when needed), and other. In this paper, we analyze the network connectivity of smart-home Xiaomi solutions based on measurements made over 30 days. We analyze the installation phase, the usage phase, and identify key Xiaomi network nodes using geolocation techniques.

The success of fundamental network tasks of traffic delivery from a source to a destination node is mainly dependent on the efficiency of the routing protocol. In mobile ad hoc networks, the effectiveness of routing protocols is additionally demanding due to the dynamic nature of network nodes. In this paper, we dealt with the exploitation of the routes generated using DSDV bellman-ford routing protocol. Through a total of 3960 network simulations with different topologies, network loads and mobility nodes, various parameters of the DSDV were considered. Our results show that there are a large number of unused routes, and techniques for improving the efficiency of routing and reducing routing overhead can be implemented.

For unstructured environments, multi-leg platforms such as hexapods, introduce better stability and adaptation during the moving in a more complex environment. The common hexapod robots, which are controlled by discrete conventional microcontrollers would require new chip replacement due to I/O constraint. With an FPGA, the user can scale design and include new functionality later in the design process without buying new additional hardware. In this paper, we introduce the hybrid architecture as a combination of FPGA and microcontroller design. The goal of this work is to extend context arbitration of a fuzzy behavior-based approach for hexapod robot navigation at the FPGA device. Verilog has been used to develop FLC on FPGA. The controller algorithm is developed and implemented on FPGA Altera Cyclone IV board. An experimental evaluation of hexapod autonomous navigation at a rough terrain presents advantages of this hierarchy approach for real-time robot embedded systems.

In order to validate and demonstrate newly developed ranging techniques, a flexible test platform for signal acquisition enabling offline signal processing is generally needed. Developing such a platform becomes challenging when working with wideband (> 100MHz) signals due to the critical timing, the very high sampling rates and the huge data throughput involved. In this paper, we introduce an Ettus X310 SDR platform using custom designed logic allowing for dual-channel 400 Msps data transmission and acquisition for centimeter level ranging applications. Furthermore, we present initial measurement results as a benchmark of the platform, which show that the time delay of a 10 m cable can be estimated with high accuracy, in the order of 50 ps.

This paper presents a new meta-heuristic algorithm called Playground algorithm. The Playground algorithm is designed to model social interaction amongst children, and the mechanisms and operators of the algorithm are inspired by the model of child interaction and engagement in games during a child's stay at the playground. In order to evaluate the performance of the algorithm, a series of tests were performed over a class of functions selected so that they possess properties such as: multimodality / unimodality, (non) separability, (non) differentiability, (non) convexity, existence of ridges and valleys and multidimensionality. During testing, the values of the algorithm parameters are varied, in order to determine their recommended values. The analysis was carried out with an overview of the effects of the algorithm parameters on the performance of the algorithm in the problem area, performance in the criterion domain, and the execution time.

Many users need social media platforms to improve business. The usage of those platforms is usually focused on the marketing and customer targeting. Platforms like Facebook, Instagram or YouTube give their users a large number of reports and analytic tools. Public figures and organizations have a large number of followers who generate a significant number of activities. This paper focuses on the use of Facebook's geography analytic in the process of events planning. The problem is formulated as a combinatorial optimization problem. Data from social media platforms are used as an input to nature-inspired optimization algorithm. A public data set has been created with cities from 20 European countries. An adjusted genetic algorithm (AGA) is proposed. The greedy approach and AGA are compared on real data from several Facebook pages and on the created public dataset. The genetic algorithm shows better results and it gives the same solution as an exhaustive search for smaller instances.

The planning of concert tours can be a challenging process which requires a large amount of data to be analyzed. The greatest profit cannot be obtained only by maximizing the expected number of visitors. However, most of the organizers mainly focus on that part of planning. To achieve the maximum profit possible, organizers must include other data in their analysis. Social media play a powerful role in music industry. Most of the mentioned data can be found online on social media like Facebook, YouTube or Instagram. Such data can be found in analytic sections of fan or event pages. In this paper, algorithms for tour planning have been introduced by using above mentioned data. Proposed algorithms are based on heuristic methods such as simulated annealing and genetic algorithm. A clustering based method is also implemented. Aforementioned algorithms were tested on real-world instances from Facebook fan page analytics and use number of fans and distance between cities.

The scope and scale of biological data are increasing at an exponential rate, as technologies like next-generation sequencing are becoming radically cheaper and more prevalent. Over the last two decades, the cost of sequencing a genome has dropped from $100 million to nearly $100—a factor of over 106—and the amount of data to be analyzed has increased proportionally. Yet, as Moore’s Law continues to slow, computational biologists can no longer rely on computing hardware to compensate for the ever-increasing size of biological datasets. In a field where many researchers are primarily focused on biological analysis over computational optimization, the unfortunate solution to this problem is often to simply buy larger and faster machines. Here, we introduce Seq, the first language tailored specifically to bioinformatics, which marries the ease and productivity of Python with C-like performance. Seq starts with a subset of Python—and is in many cases a drop-in replacement—yet also incorporates novel bioinformatics- and computational genomics-oriented data types, language constructs and optimizations. Seq enables users to write high-level, Pythonic code without having to worry about low-level or domain-specific optimizations, and allows for the seamless expression of the algorithms, idioms and patterns found in many genomics or bioinformatics applications. We evaluated Seq on several standard computational genomics tasks like reverse complementation, k-mer manipulation, sequence pattern matching and large genomic index queries. On equivalent CPython code, Seq attains a performance improvement of up to two orders of magnitude, and a 160× improvement once domain-specific language features and optimizations are used. With parallelism, we demonstrate up to a 650× improvement. Compared to optimized C++ code, which is already difficult for most biologists to produce, Seq frequently attains up to a 2× improvement, and with shorter, cleaner code. Thus, Seq opens the door to an age of democratization of highly-optimized bioinformatics software.

Abstract Background BRAF genomic alterations (GA) occur in multiple tumor types and BRAF/MEK targeted therapies are approved in melanoma and NSCLC. Diverse mechanisms of AR to these therapies have been proposed but have not been comprehensively assessed. Methods Hybrid-capture based comprehensive genomic profiling (CGP) was performed on FFPE (n = 228,629) or blood-based cell free DNA (cfDNA, n = 15,069) samples for 222,952 patients (pts). Tumor mutational burden (TMB) was determined on 0.8-1.1 Mbp of sequenced DNA. Samples without evidence of tumor DNA or known to have not received RAF/MEK inhibitors were excluded. Paired samples were collected >60 days apart (median 523, range 71-5571). Results Paired samples with BRAF V600E (64%) or other activating BRAF GA (36%) were available for 154 pts with NSCLC (20%), melanoma (19%), CRC (15%) myeloma (8.4%) glioma (7.1%) or other (30%) cancers. Acquired GA previously described preclinically or clinically including in BRAF, KRAS, NRAS, MEK1, PIK3CA, PTEN, MET, and CCND1 occurred in 34 cases (Table). 56 additional cases had reportable acquired GA in other genes (eg. STK11, NF1). Median TMB was 4.0 vs 5.2 mut/Mb in the first vs second sample (p = 0.23). In 12% of cases (9 tissue, 9 cfDNA) a BRAF GA was not detected in the second sample. Most AR mechanisms (MET amp, KRAS mut, secondary BRAF GA) were tumor agnostic, but PIK3CA and PTEN GA were enriched in brain samples and absent in CRC, and NRAS mut were exclusive to melanoma (Table). Treatment status was available for a subset of cases. Notably V600E CRC, NSCLC and melanoma each had acquired MET amp post-dabrafenib + trametinib, and a V600E myeloma had acquired MEK C121S post-trametinib + vemurafenib. Additional clinical data will be presented. Table: 1878PD . Potential AR mechanism No. cases# AR subtypes Disease Histologies Associated Primary BRAF GA Biopsy location * KRAS mut 7 G12D (2), G12R, G12V, G13D, Q61H, K117N CRC (2), NSCLC (2), cholangiocarcinoma, multiple myeloma, CLL V600E (6), G466A omentum (2), liver NRAS mut 4 G12C, G13R, G13R/Q61H, Q61H/K melanoma (4) V600E (2), V600R, G469A brain (1), lymph node (1), soft tissue (1) NRAS amp 1 amp estimated copies: 41 NSCLC V600E pericardial fluid Secondary BRAF GA 10 N-terminal deletion exons 2-8 (6), duplications exons 10-18, L505H, N581I/D594G, amp estimated copies: 6 NSCLC (4), CRC (2), melanoma (2), multiple myeloma, pancreatic V600E (9), G466A liver (3), lymph node (2), lung, abdominal wall, brain MEK1 mut 1 C121S multiple myeloma V600E NA PIK3CA mut 5 H1047R (2), G1049R, R88Q, S405F glioma (3), NSCLC, thyroid V600E (3), N486_T491>K, R506_K507insVLR brain (4), lung PTEN GA 5 E7fs * , R130 * , G129R, splice site 165-1G>A, loss melanoma (2), glioma, NSCLC, UP neuroendocrine V600E, V600K, R506_K507insVLR, KHDRBS2-BRAF fusion brain (2), abdomen, soft tissue CCND1 amp 2 amp estimated copies: 9, 10 NSCLC, thyroid V600E, G464V brain, pleural fluid MET amp 4 amp estimated copies: 12, 14, 15, 56 NSCLC, CRC, melanoma, UP adenocarcinoma V600E (4) lymph node, colon, brain, liver * Indicated for tissue samples only (NA= not applicable); #5 cases had AR alterations in multiple genes included here; NSCLC: non-small cell lung cancer, CRC: colorectal carcinoma; CLL: chronic lymphocytic leukemia; UP: unknown primary; AR: acquired resistance; mut: mutation; amp: amplification. Conclusions Novel and previously observed potential AR alterations in paired BRAF altered clinical samples were detected using CGP. Most AR mechanisms appeared independent of tumor type and biopsy site. Additional clinical studies to explore effective treatments for these AR subsets are needed. Legal entity responsible for the study The authors. Funding Foundation Medicine. Disclosure F. Pietrantonio: Advisory / Consultancy: Roche; Advisory / Consultancy: Amgen; Advisory / Consultancy: Eli-Lily; Advisory / Consultancy: Bayer; Advisory / Consultancy: Sanofi; Advisory / Consultancy: Servier; Advisory / Consultancy: Merck Serono. J. Lee: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. L. Boussemart: Advisory / Consultancy: Novartis; Advisory / Consultancy: Pierre Fabre. G. Srkalovic: Speaker Bureau / Expert testimony: Foundation Medicine. R. Madison: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. J.S. Ross: Leadership role, Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. V.A. Miller: Leadership role, Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche; Advisory / Consultancy: Revolution Medicines. B.M. Alexander: Leadership role, Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. S.M. Ali: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. A.B. Schrock: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine; Shareholder / Stockholder / Stock options: Roche. All other authors have declared no conflicts of interest.