Membrane computing, which is also known as a P system, is a computational model inspired by the activity of living cells. Several P systems, which work in a polynomial number of steps, have been ...proposed for solving computationally hard problems. However, most of the proposed algorithms use an exponential number of membranes, and reduction of the number of membranes must be considered in order to make a P system a more realistic model.In the present paper, we propose asynchronous P systems based on the Bron-Kerbosch algorithm for solving the maximum clique problem with fewer membranes. The proposed P systems solve the maximum clique with n vertices in O(n^2) parallel steps or O(n^2 2^n) sequential steps.We evaluate the number of membranes used in the proposed P systems by comparing with the numbers of membranes used in known P systems. Our experimental results demonstrate the validity and efficiency of the proposed P systems.
Many statistical analyses of genetic data rely on the assumption of independence among samples. Consequently, relatedness is either modeled in the analysis or samples are removed to “clean” the data ...of any pairwise relatedness above a tolerated threshold. Current methods do not maximize the number of unrelated individuals retained for further analysis, and this is a needless loss of resources. We report a novel application of graph theory that identifies the maximum set of unrelated samples in any dataset given a user‐defined threshold of relatedness as well as all networks of related samples. We have implemented this method into an open source program called Pedigree Reconstruction and Identification of a Maximum Unrelated Set, PRIMUS. We show that PRIMUS outperforms the three existing methods, allowing researchers to retain up to 50% more unrelated samples. A unique strength of PRIMUS is its ability to weight the maximum clique selection using additional criteria (e.g. affected status and data missingness). PRIMUS is a permanent solution to identifying the maximum number of unrelated samples for a genetic analysis.
In recent years, institutions such as Cambridge University, and Cambridge societies such as Footlights, have been under scrutiny for their perceived elitism. This article nevertheless makes the case ...that such views overlook the place of gender within these contexts, and above all, the history of gender discrimination and the struggle for representation on the part of women within such institutions. Looking primarily at Footlights, and two of its most prominent early female members (Eleanor Bron and Emma Thompson), and focusing on some of their early work on screen, this article argues that we consider the exceptional nature of female performers emerging from the society. The article argues, in turn, that we take into account the distinctive, critical type of work on the part of these performers, in terms of its comedic and reflextive approach to female representation; arguing also that we link such work to the authorial opportunities, but also competitive contexts, of Cambridge University comedy during these times.
Maximal Clique Enumeration (MCE) is a fundamental and challenging problem in graph theory and various network applications. Numerous algorithms have been proposed in the past decades, however, only a ...few of them focus on improving the practical efficiency in large graphs. To this end, we propose an efficient algorithm called FACEN based on the Bron–Kerbosch framework. To optimize the memory and time consumption, we apply a hybrid data structure with adjacency list and partial adjacency matrix, and introduce a dynamic pivot selection rule based on the degeneracy order. FACEN is evaluated on a total of 64 benchmark instances from various sources. Computational results indicate that the proposed algorithm is highly competitive with the current leading MCE methods. In particular, our algorithm is able to enumerate all maximal cliques on the tested real-world social networks with millions of vertices and edges. For very large graphs, we provide an additional experiment for solving the MCE variant with lower bound, and investigate the benefits of FACEN.
•Enumerating maximal cliques in large graphs is computationally challenging.•An exact method on fast maximal clique enumeration is presented.•We introduce a new dynamic branching heuristic based on the degeneracy order.•The method is highly competitive with the current leading methods.•The method is efficient for solving the real-world social network benchmarks.
Epstein-Barr virus (EBV)-associated neoplasms derived from natural killer (NK) or T cells comprise a group of clinically and biologically heterogenous disorders affecting children and adults, which ...are overall rare but more prevalent in Asia and South America. This review focuses on neoplasms presenting in the adulthood, addressing recent genomic discoveries as well as therapeutic developments in these highly aggressive disorders.
Distinct molecular subtypes of extranodal NK/T-cell lymphomas (ENKTCLs) have been described, with differences in cell of origin, EBV pattern, genomic alterations, clinical characteristics, response to asparaginase-based therapies and to more recent approaches targeting molecular aberrations of the lymphoma. For the last two decades, progress in the clinical management of ENKTCL was based on L-asapraginase containing combinations and the incoroperation of radiotherapy. A subset of cases with PDL1-2 structural alterations may be more responsive to treatment with immune checkpoint inhibitors. Primary nodal EBV+ lymphomas derived from T or NK cells have distinctive features separating them from both peripheral T-cell lymphoma not otherwise specified and ENKTCL. Treatment algorithms correspond to those for advanced ENKTCL.
With better understanding of lymphomagenesis, genomic landscape and immunologic aspects of the diseases, future treatment options will include targeted therapies including immune checkpoint inhibitors and novel antibodies.
Primary central nervous system lymphoma (PCNSL) is a rare central nervous system (CNS) malignancy, which represents a heterogenous group of tumors. Among PCNSL, diffuse large B-cell lymphoma of the ...CNS (CNS-DLBCL) represents the most common tumor type. Multiomics studies have recently revealed the complex genomic landscape of these rare diseases. These findings lead to a potential new molecular and epigenetic classification.
Our review is focused on CNS-DLBCL in immunocompetent patients. CNS-DLBCL are derived from self-reactive/polyreactive precursor cells. An early molecular event such as MYD88 mutation leads to escape elimination of precursor cells, which, by a dysregulated GC reaction, acquire auto-/polyreactivity of the B-cell tumoral cells for antigens physiologically expressed in the CNS. Most of CNS-DLBCL tumor cells harbor a non-GCB, ABC-like immunophenotype associated with a late GC (exit) B-cells genotype by gene expression profiling. Various mechanisms of genetic alterations are involved in the pathogenesis of PCNSL, including point mutations nonsomatic hypermutation (SHM), aberrant SHM (aSHM), SHM/aSHM, chromosome copy gains or losses, and DNA hypermethylation. Constitutive NFκB activation plays a key role in lymphoma cell proliferation and survival by dysregulation of toll-like receptor (mutations of CARD11 and MYD88 ), BCR ( CD79B ), JAK-STAT, and NFκB signaling pathways.
Multiomics approaches have succeeded to substantially improve the understanding of the pathogenesis, as well as the molecular and epigenetic events in PCNSL. Challenges remain due to the obvious heterogeneity of CNS-DLBCL, and improvement is needed for their classification.
High-flow nasal cannula (HFNC) therapy is a respiratory modality that has been adopted to support pediatric patients with bronchiolitis. There is no standardized protocol for initiation, escalation, ...or weaning of HFNC in the pediatric ICU. The aim of this respiratory therapist (RT)-driven quality improvement management protocol was to decrease duration of HFNC.
An RT-driven HFNC management protocol based on an objective respiratory score was implemented in 2017 at a quaternary care children's hospital. Subjects included children less than 2 y old admitted to the pediatric ICU with bronchiolitis. All subjects needing HFNC were scored and placed within the protocol as appropriate for age, then weaned or escalated per the scoring tool. Comparison to a pre-intervention control group was performed. Average HFNC duration per subject was used as the primary outcome measure. Protocol compliance was used as a process measure. Noninvasive ventilation use, intubation rate, and 30-d pediatric ICU readmission rate were used as balancing measures. RT satisfaction with HFNC management before and after protocol implementation were measured.
Protocol compliance was sustainable and above the goal of 80% after 4 months of protocol implementation. HFNC duration decreased from 2.5 d to 2 days for each subject during planning and then to 1.8 d after protocol implementation. Length of stay (LOS) in the pediatric ICU and hospital LOS decreased from 2.6 d to 2.1 d and from 5.7 d to 4.7 d after protocol implementation, respectively. The use of noninvasive ventilation and the rate of intubation did not change significantly. RTs reported increased involvement in HFNC management decisions and appropriateness on how quickly the team weaned HFNC.
An RT-driven HFNC management protocol was safely implemented in a pediatric ICU and decreased HFNC duration, pediatric ICU LOS, and hospital LOS. It allows the RT to work independently to the highest extent of their scope of practice, leading to improvement in RT job satisfaction.
This paper proposes a parallel implementation of the Bron-Kerbosch algorithm, which finds all maximal cliques in large, complex graphs using CPU and thread-level parallelism and distributed memory ...with multiple cores. With the growing size and complexity of modern graphs, sequential algorithms can become impractical, making parallel computation a promising solution for reducing duration and enhancing scalability. Decomposing the graph into smaller components and distributing the workload across multiple threads using task parallelism is the proposed method. To optimise the algorithm's efficacy across processes, load-balancing techniques are also investigated. The modified Bron-Kerbosch algorithm is implemented and evaluated on a variety of large graphs, exhibiting significant runtime and scalability enhancements over the sequential version. The conclusion of the paper discusses the prospective applications of the parallel Bron-Kerbosch algorithm in a variety of domains, including social network analysis, bio informatics, and network security. Overall, this research contributes to the expanding body of work on parallel computing and graph analysis by emphasising the advantages of CPU and thread-level parallelism for efficiently solving complex computational problems.
We represent a new method for finding all connected maximal common subgraphs in two graphs which is based on the transformation of the problem into the clique problem. We have developed new ...algorithms for enumerating all cliques that represent connected maximal common subgraphs. These algorithms are based on variants of the Bron–Kerbosch algorithm. In this paper we explain the transformation of the maximal common subgraph problem into the clique problem. We give a short summary of the variants of the Bron–Kerbosch algorithm in order to explain the modification of that algorithm such that the detected cliques represent connected maximal common subgraphs. After introducing and proving several variants of the modified algorithm we discuss the runtimes for all variants by means of random graphs. The results show the drastical reduction of the runtimes for the new algorithms.
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