Experimental Validation of the Reliability-Aware Multi-UAV Coverage Path Planning Problem

Unmanned aerial vehicles (UAVs) have become crucial for various applications, necessitating reliable and time-constrained performance. Multi-UAV solutions offer advantages but require effective coordination. Traditional coverage path planning methods overlook uncertainties and individual UAV failures. To address this, reliability-aware multi-UAV coverage path planning methods optimise task allocation to maximise mission completion probabilities given a failure model. This paper presents an experimental validation of the reliability-aware approach, specifically an approach using a Greedy Genetic Algorithm (GGA). We evaluate the GGA performance in real-world environments, comparing mission reliability to computed reliability and comparing it against a traditional multi-UAV methods. The experimental validation demonstrates the practical viability and effectiveness of the reliability-aware approach, showing significant improvement in mission reliability despite the inevitable mismatch between real and assumed failure models

The case for launch of an international DNA-based birth cohort study

The global health agenda beyond 2015 will inevitably need to broaden its focus from mortality reduction to the social determinants of deaths, growing inequities among children and mothers, and ensuring the sustainability of the progress made against the infectious diseases. New research tools, including technologies that enable high-throughput genetic and ‘-omics’ research, could be deployed for better understanding of the aetiology of maternal and child health problems. The research needed to address those challenges will require conceptually different studies than those used in the past. It should be guided by stringent ethical frameworks related to the emerging collections of biological specimens and other health related information. We will aim to establish an international birth cohort which should assist low- and middle-income countries to use emerging genomic research technologies to address the main problems in maternal and child health, which are still major contributors to the burden of disease globally

Criteria for the use of omics-based predictors in clinical trials.

The US National Cancer Institute (NCI), in collaboration with scientists representing multiple areas of expertise relevant to 'omics'-based test development, has developed a checklist of criteria that can be used to determine the readiness of omics-based tests for guiding patient care in clinical trials. The checklist criteria cover issues relating to specimens, assays, mathematical modelling, clinical trial design, and ethical, legal and regulatory aspects. Funding bodies and journals are encouraged to consider the checklist, which they may find useful for assessing study quality and evidence strength. The checklist will be used to evaluate proposals for NCI-sponsored clinical trials in which omics tests will be used to guide therapy

Turbulence in the Solar Atmosphere: Manifestations and Diagnostics via Solar Image Processing

Intermittent magnetohydrodynamical turbulence is most likely at work in the magnetized solar atmosphere. As a result, an array of scaling and multi-scaling image-processing techniques can be used to measure the expected self-organization of solar magnetic fields. While these techniques advance our understanding of the physical system at work, it is unclear whether they can be used to predict solar eruptions, thus obtaining a practical significance for space weather. We address part of this problem by focusing on solar active regions and by investigating the usefulness of scaling and multi-scaling image-processing techniques in solar flare prediction. Since solar flares exhibit spatial and temporal intermittency, we suggest that they are the products of instabilities subject to a critical threshold in a turbulent magnetic configuration. The identification of this threshold in scaling and multi-scaling spectra would then contribute meaningfully to the prediction of solar flares. We find that the fractal dimension of solar magnetic fields and their multi-fractal spectrum of generalized correlation dimensions do not have significant predictive ability. The respective multi-fractal structure functions and their inertial-range scaling exponents, however, probably provide some statistical distinguishing features between flaring and non-flaring active regions. More importantly, the temporal evolution of the above scaling exponents in flaring active regions probably shows a distinct behavior starting a few hours prior to a flare and therefore this temporal behavior may be practically useful in flare prediction. The results of this study need to be validated by more comprehensive works over a large number of solar active regions.Comment: 26 pages, 7 figure

Cyclophosphamide and human organ transplantation.

Cyclophosphamide, a drug that has not previously had an important role in whole-organ transplantation, was given as a primary immunosuppressant to one liver and eleven kidney recipients, in combination with prednisone and horse antilymphocyte globulin. One of the patients died despite good renal-graft function. Two kidneys from a common cadaveric donor failed. The other nine patients have excellent function of their homografts after 2-3 months. Cyclophosphamide was substituted for azathioprine in one hepatic and five renal recipients who were suspected of having liver toxicity from azathioprine 3 months to almost 8 years post-transplantation. Graft function was maintained after this change, and the evidence of liver injury subsided. © 1971

Pim1 promotes human prostate cancer cell tumorigenicity and c-MYC transcriptional activity

<p>Abstract</p> <p>Background</p> <p>The serine/threonine kinase PIM1 has been implicated as an oncogene in various human cancers including lymphomas, gastric, colorectal and prostate carcinomas. In mouse models, Pim1 is known to cooperate with c-Myc to promote tumorigenicity. However, there has been limited analysis of the tumorigenic potential of Pim1 overexpression in benign and malignant human prostate cancer cells <it>in vivo</it>.</p> <p>Methods</p> <p>We overexpressed Pim1 in three human prostate cell lines representing different disease stages including benign (RWPE1), androgen-dependent cancer (LNCaP) and androgen-independent cancer (DU145). We then analyzed <it>in vitro </it>and <it>in vivo </it>tumorigenicity as well as the effect of Pim1 overexpression on c-MYC transcriptional activity by reporter assays and gene expression profiling using an inducible MYC-ER system. To validate that Pim1 induces tumorigenicity and target gene expression by modulating c-MYC transcriptional activity, we inhibited c-MYC using a small molecule inhibitor (10058-F4) or RNA interference.</p> <p>Results</p> <p>Overexpression of Pim1 alone was not sufficient to convert the benign RWPE1 cell to malignancy although it enhanced their proliferation rates when grown as xenografts <it>in vivo</it>. However, Pim1 expression enhanced the <it>in vitro </it>and <it>in vivo </it>tumorigenic potentials of the human prostate cancer cell lines LNCaP and DU145. Reporter assays revealed increased c-MYC transcriptional activity in Pim1-expressing cells and mRNA expression profiling demonstrated that a large fraction of c-MYC target genes were also regulated by Pim1 expression. The c-MYC inhibitor 10058-F4 suppressed the tumorigenicity of Pim1-expressing prostate cancer cells. Interestingly, 10058-F4 treatment also led to a reduction of Pim1 protein but not mRNA. Knocking-down c-MYC using short hairpin RNA reversed the effects of Pim1 on Pim1/MYC target genes.</p> <p>Conclusion</p> <p>Our results suggest an <it>in vivo </it>role of Pim1 in promoting prostate tumorigenesis although it displayed distinct oncogenic activities depending on the disease stage of the cell line. Pim1 promotes tumorigenicity at least in part by enhancing c-MYC transcriptional activity. We also made the novel discovery that treatment of cells with the c-MYC inhibitor 10058-F4 leads to a reduction in Pim1 protein levels.</p

Immune Signatures Predict Prognosis in Localized Cancer

The host immune response can impact cancer growth, prognosis, and response to therapy. In colorectal cancer, the presence of cells involved with T-cell-mediated adaptive immunity predicts survival better than the current staging method. We used the expression of genes recently associated with host immune responses (TH1-mediated adaptive immunity, inflammation, and immune suppression) to perform hierarchical clustering of multiple large cohorts of cancer specimens to determine if immune-related gene expression resulted in clinical significant groupings of tumors. Microarray data from prostate cancer (n = 79), breast cancer (n = 132), lung cancer (n = 84), glioblastoma multiforme (n = 120), and lymphoma (n = 127) were analyzed. Among adenocarcinomas, the TH1-mediated adaptive immunity genes were consistently associated with better prognosis, while genes associated with inflammation and immune suppression were variably associated with outcome. Specifically, increased expression of the TH1-mediated adaptive immunity genes was associated with good prognosis in breast cancer patients under 45 years of age (p = .04, hazard ratio [HR] = 0.42) and in prostate cancer patients (p = .03, HR = 0.36) but not in lung cancer patients (p = 0.45, HR = 1.37). In lymphoma, patients with increased expression of inflammation and immune suppression genes had better prognosis than those expressing the TH1-mediated adaptive immunity genes (p = .01, HR = 0.43) and in glioblastoma multiforme, the expression of inflammation genes conferred improved prognosis than those expressing immune suppression genes (p = 0.05, HR = 0.62). In aggregate, the gene expression signatures implicating specific components of the immune response hold prognostic import across solid tumors