Continuous Performance Benchmarking Framework for ROOT

Foundational software libraries such as ROOT are under intense pressure to avoid software regression, including performance regressions. Continuous performance benchmarking, as a part of continuous integration and other code quality testing, is an industry best-practice to understand how the performance of a software product evolves over time. We present a framework, built from industry best practices and tools, to help to understand ROOT code performance and monitor the efficiency of the code for a several processor architectures. It additionally allows historical performance measurements for ROOT I/O, vectorization and parallelization sub-systems.Comment: 8 pages, 5 figures, CHEP 2018 - 23rd International Conference on Computing in High Energy and Nuclear Physic

Extending ROOT through Modules

The ROOT software framework is foundational for the HEP ecosystem, providing capabilities such as IO, a C++ interpreter, GUI, and math libraries. It uses object-oriented concepts and build-time components to layer between them. We believe additional layering formalisms will benefit ROOT and its users. We present the modularization strategy for ROOT which aims to formalize the description of existing source components, making available the dependencies and other metadata externally from the build system, and allow post-install additions of functionality in the runtime environment. components can then be grouped into packages, installable from external repositories to deliver post-install step of missing packages. This provides a mechanism for the wider software ecosystem to interact with a minimalistic install. Reducing intra-component dependencies improves maintainability and code hygiene. We believe helping maintain the smallest "base install" possible will help embedding use cases. The modularization effort draws inspiration from the Java, Python, and Swift ecosystems. Keeping aligned with the modern C++, this strategy relies on forthcoming features such as C++ modules. We hope formalizing the component layer will provide simpler ROOT installs, improve extensibility, and decrease the complexity of embedding in other ecosystemsComment: 8 pages, 2 figures, 1 listing, CHEP 2018 - 23rd International Conference on Computing in High Energy and Nuclear Physic

A Multi-Objective Optimization Model For Operations Planning Of Multi-Reservoir Systems

This paper presents the development and evaluation of a multi-objective linear programming (LP) optimization tool for an operations planning platform (OPP). The LP optimization model is coded using a high level programming language called AMPL (A Mathematical Programming Language) and solved using a solver called CPLEX. This model was developed by closely working with operations planning engineers at BC Hydro, in Canada, with the support of a research team from the University of British Columbia. The optimization model incorporates two objectives to optimize the operation of a multi reservoir system: maximize revenue from power generation, and to minimize penalties resulting from deviations of reservoir elevations and spill releases from a preferred operating regime. Several multi-objective optimization techniques are being investigated including traditional methods such as the Weighting Method and the Constraint Method, as well as Goal Programming (GP) techniques. These methods would be tested for optimality and computational efficiency and would be generalized and used to study a number of multi-reservoir systems in British Columbia. Stochastic inflows would be considered in the model making use of chance-constraints and probability distribution functions based on historical inflow records. The model also incorporates features which simulate maintenance outages on hydropower plants. The goal is to determine the optimal maintenance schedules that minimize the cost of these outages. We present results of a case study to illustrate the capabilities of the model to provide decision makers with timely information on trade-off between different objectives. Maintenance schedules of generating units with and without optimization are also considered

Reliability Analysis Approach For Operations Planning Of Hydropower Systems

Many existing hydropower storage facilities were built decades ago and components of these aging infrastructure facilities have higher risk of failure. Insufficient capacity or forced outages of the spillway and other waterway passage facilities during flooding incident could potentially increase the probability of dam safety incidents leading to public safety concerns. Currently approaches used to assess the risk and uncertainty in operational decision making are mainly based on qualitative assessment and expert judgment and can be significantly improved by the development of a framework that formally incorporates both qualitative and quantitative reliability analysis methods. Event tree analysis and fault tree analysis have traditionally been used in dam safety risk analysis, with results subject to data adequacy and availability. Our research shows that other methods, such as nonparametric analysis and Monte Carlo simulation techniques can yield good results as well. This study investigated the application of reliability analysis methods to existing hydropower storage facilities, with the objective of developing a new systems engineering based approach for risk and uncertainty analysis to assess and manage the risks of hydropower system operations. Our approach integrates reliability-based methods with hydro system optimization modeling to develop an operational reliability-based modeling framework and to formally treat risk and uncertainty in operations planning. This approach incorporates different sources of uncertainty that are typically encountered in operations planning of these systems, including failure probability of hydro system components such as non-power release structures and turbine facilities. This paper presents the framework we have developed and illustrates the application of our investigation for a hydropower system facility in British Columbia, Canada

The use of plants for remediation of metal-contaminated soils,

The use of green plants to remove, contain, inactivate, or degrade harmful environmental contaminants (generally termed phytoremediation) is an emerging technology. In this paper, an overview is given of existing information concerning the use of plants for the remediation of metal-contaminated soils. Both site decontamination (phytoextraction) and stabilization techniques (phytostabilization) are described. In addition to the plant itself, the use of soil amendments for mobilization (in case of phytoextraction) and immobilization (in case of phytostabilization) is discussed. Also, the economical impacts of changed land-use, eventual valorization of biomass, and cost-benefit aspects of phytoremediation are treated. In spite of the growing public and commercial interest and success, more fundamental research is needed still to better exploit the metabolic diversity of the plants themselves, but also to better understand the complex interactions between metals, soil, plant roots, and micro-organisms (bacteria and mycorrhiza) in the rhizosphere. Further, more demonstration experiments are needed to measure the underlying economics, for public acceptance and last but not least, to convince policy makers

Steam reforming of phenol as biomass tar model compound over Ni/Al₂O₃ catalyst

Catalytic steam reforming of phenol over Ni/Al₂O₃ catalyst with 10 wt% of Ni loading was carried out in a fixed bed reactor. The effect of temperature (650–800 °C), reaction time (20–80 min) and catalyst amount (0–2 g corresponding to 0–4.5 gcat h gphenol−1) on carbon conversion, H2 potential and catalyst deactivation was studied. High efficiency of Ni/Al₂O₃ catalyst in steam reforming of phenol is observed at 750 °C for a reaction time of 60 min when 1.5 g of catalyst (3.4 gcat h gphenol−1) is used, with carbon conversion and H2 potential being 81 and 59%, respectively. An increase in temperature enhances phenol reforming reaction as well as coke gasification, minimizing its deposition over the catalyst. However, at high temperatures (800 °C) an increase in Ni crystal size is observed indicating catalyst irreversible deactivation by sintering. As catalyst time on stream is increased the coke amount deposited over the catalyst increases, but no differences in Ni crystal size are observed. An increase in catalyst amount from 0 to 1.5 g increases H2 potential, but no further improvement is observed above 1.5 g. It is not observed significant catalyst deactivation by coke deposition, with the coke amount deposited over the catalyst being lower than 5% in all the runs

MDM2 antagonist Nutlin-3a potentiates antitumour activity of cytotoxic drugs in sarcoma cell lines

<p>Abstract</p> <p>Background</p> <p>Frequent failure and severe side effects of current sarcoma therapy warrants new therapeutic approaches. The small-molecule MDM2 antagonist Nutlin-3a activates the p53 pathway and efficiently induces apoptosis in tumours with amplified <it>MDM2 </it>gene and overexpression of MDM2 protein. However, the majority of human sarcomas have normal level of MDM2 and the therapeutic potential of MDM2 antagonists in this group is still unclear. We have investigated if Nutlin-3a could be employed to augment the response to traditional therapy and/or reduce the genotoxic burden of chemotherapy.</p> <p>Methods</p> <p>A panel of sarcoma cell lines with different <it>TP53 </it>and <it>MDM2 </it>status were treated with Nutlin-3a combined with Doxorubicin, Methotrexate or Cisplatin, and their combination index determined.</p> <p>Results</p> <p>Clear synergism was observed when Doxorubicin and Nutlin-3a were combined in cell lines with wild-type <it>TP53 </it>and amplified <it>MDM2</it>, or with Methotrexate in both <it>MDM2 </it>normal and amplified sarcoma cell lines, allowing for up to tenfold reduction of cytotoxic drug dose. Interestingly, Nutlin-3a seemed to potentiate the effect of classical drugs as Doxorubicin and Cisplatin in cell lines with mutated <it>TP53</it>, but inhibited the effect of Methotrexate.</p> <p>Conclusion</p> <p>The use of Nutlin in combination with classical sarcoma chemotherapy shows promising preclinical potential, but since clear biomarkers are still lacking, clinical trials should be followed up with detailed tumour profiling.</p

Integrated management of ash from industrial and domestic combustion : a new sustainable approach for reducing greenhouse gas emissions from energy conversion

This work supports, for the first time, the integrated management of waste materials arising from industrial processes (fly ash from municipal solid waste incineration and coal fly ash), agriculture (rice husk ash), and domestic activities (ash from wood biomass burning in domestic stoves). The main novelty of the paper is the reuse of wood pellet ash, an underestimated environmental problem, by the application of a new technology (COSMOS-RICE) that already involves the reuse of fly ashes from industrial and agricultural origins. The reaction mechanism involves carbonation: this occurs at room temperature and promotes permanent carbon dioxide sequestration. The obtained samples were characterized using XRD and TGA (coupled with mass spectroscopy). This allowed quantification of the mass loss attributed to different calcium carbonate phases. In particular, samples stabilized using wood pellet ash show a weight loss, attributed to the decomposition of carbonates greater than 20%. In view of these results, it is possible to conclude that there are several environmental benefits from wood pellet ash reuse in this way. In particular, using this technology, it is shown that for wood pellet biomass the carbon dioxide conversion can be considered negative

The potential of optical proteomic technologies to individualize prognosis and guide rational treatment for cancer patients

Genomics and proteomics will improve outcome prediction in cancer and have great potential to help in the discovery of unknown mechanisms of metastasis, ripe for therapeutic exploitation. Current methods of prognosis estimation rely on clinical data, anatomical staging and histopathological features. It is hoped that translational genomic and proteomic research will discriminate more accurately than is possible at present between patients with a good prognosis and those who carry a high risk of recurrence. Rational treatments, targeted to the specific molecular pathways of an individual’s high-risk tumor, are at the core of tailored therapy. The aim of targeted oncology is to select the right patient for the right drug at precisely the right point in their cancer journey. Optical proteomics uses advanced optical imaging technologies to quantify the activity states of and associations between signaling proteins by measuring energy transfer between fluorophores attached to specific proteins. Förster resonance energy transfer (FRET) and fluorescence lifetime imaging microscopy (FLIM) assays are suitable for use in cell line models of cancer, fresh human tissues and formalin-fixed paraffin-embedded tissue (FFPE). In animal models, dynamic deep tissue FLIM/FRET imaging of cancer cells in vivo is now also feasible. Analysis of protein expression and post-translational modifications such as phosphorylation and ubiquitination can be performed in cell lines and are remarkably efficiently in cancer tissue samples using tissue microarrays (TMAs). FRET assays can be performed to quantify protein-protein interactions within FFPE tissue, far beyond the spatial resolution conventionally associated with light or confocal laser microscopy. Multivariate optical parameters can be correlated with disease relapse for individual patients. FRET-FLIM assays allow rapid screening of target modifiers using high content drug screens. Specific protein-protein interactions conferring a poor prognosis identified by high content tissue screening will be perturbed with targeted therapeutics. Future targeted drugs will be identified using high content/throughput drug screens that are based on multivariate proteomic assays. Response to therapy at a molecular level can be monitored using these assays while the patient receives treatment: utilizing re-biopsy tumor tissue samples in the neoadjuvant setting or by examining surrogate tissues. These technologies will prove to be both prognostic of risk for individuals when applied to tumor tissue at first diagnosis and predictive of response to specifically selected targeted anticancer drugs. Advanced optical assays have great potential to be translated into real-life benefit for cancer patients

Post-glacial determinants of regional species pools in alpine grasslands

[Aim] Alpine habitats support unique biodiversity confined to high-elevation areas in the current interglacial. Plant diversity in these habitats may respond to area, environment, connectivity and isolation, yet these factors have been rarely evaluated in concert. Here we investigate major determinants of regional species pools in alpine grasslands, and the responses of their constituent species groups.[Location] European mountains below 50° N.[Time period] Between 1928 and 2019.[Major taxa studied] Vascular plants.[Methods] We compiled species pools from alpine grasslands in 23 regions, including 794 alpine species and 2,094 non-alpines. We used species–area relationships to test the influence of the extent of alpine areas on regional richness, and mixed-effects models to compare the effects of 12 spatial and environmental predictors. Variation in species composition was addressed by generalized dissimilarity models and by a coefficient of dispersal direction to assess historical links among regions.[Results] Pool sizes were partially explained by current alpine areas, but the other predictors largely contributed to regional differences. The number of alpine species was influenced by area, calcareous bedrock, topographic heterogeneity and regional isolation, while non-alpines responded better to connectivity and climate. Regional dissimilarity of alpine species was explained by isolation and precipitation, but non-alpines only responded to isolation. Past dispersal routes were correlated with latitude, with alpine species showing stronger connections among regions.[Main conclusions] Besides area effects, edaphic, topographic and spatio-temporal determinants are important to understand the organization of regional species pools in alpine habitats. The number of alpine species is especially linked to refugia and isolation, but their composition is explained by past dispersal and post-glacial environmental filtering, while non-alpines are generally influenced by regional floras. New research on the dynamics of alpine biodiversity should contextualize the determinants of regional species pools and the responses of species with different ecological profiles.The authors thank Daniela Gaspar for support in GIS analyses. B.J.-A. thanks the Marie Curie Clarín-COFUND program of the Principality of Asturias-EU (ACB17-26), the regional grant IDI/2018/000151, and the Spanish Research Agency grant AEI/ 10.13039/501100011033. J.V.R.-D. was supported by the ACA17-02FP7 Marie Curie COFUND-Clarín grant. G.P.M. was funded by US National Science Foundation award 1853665. C.M. was funded by grant no. 19-28491 of the Czech Science Foundation.Peer reviewe