Data compilation of ciliates growth rate, grazing rate and gross gowth efficiency from field and labratory experiments

The present data compilation includes ciliates growth rate, grazing rate and gross growth efficiency determined either in the field or in laboratory experiments. From the existing literature, we synthesized all data that we could find on cilliate. Some sources might be missing but none were purposefully ignored. Field data on microzooplankton grazing are mostly comprised of grazing rate using the dilution technique with a 24h incubation period. Laboratory grazing and growth data are focused on pelagic ciliates and heterotrophic dinoflagellates. The experiment measured grazing or growth as a function of prey concentration or at saturating prey concentration (maximal grazing rate). When considering every single data point available (each measured rate for a defined predator-prey pair and a certain prey concentration) there is a total of 1485 data points for the ciliates, counting experiments that measured growth and grazing simultaneously as 1 data point.

Near-field coupling and resonant cavity modes in plasmonic nanorod metamaterials

Plasmonic resonant cavities are capable of confining light at the nanoscale, resulting in both enhanced local electromagnetic fields and lower mode volumes. However, conventional plasmonic resonant cavities possess large Ohmic losses at metal-dielectric interfaces. Plasmonic near-field coupling plays a key role in a design of photonic components based on the resonant cavities because of the possibility to reduce losses. Here, we study the plasmonic near-field coupling in the silver nanorod metamaterials treated as resonant nanostructured optical cavities. Reflectance measurements reveal the existence of multiple resonance modes of the nanorod metamaterials, which is consistent with our theoretical analysis. Furthermore, our numerical simulations show that the electric field at the longitudinal resonances forms standing waves in the nanocavities due to the near-field coupling between the adjacent nanorods, and a new hybrid mode emerges due to a coupling between nanorods and a gold-film substrate. We demonstrate that this coupling can be controlled by changing the gap between the silver nanorod array and gold substrate.

Resist-substrate interface tailoring for generating high density arrays of Ge and Bi2Se3 nanowires by electron beam lithography

The authors report a chemical process to remove the native oxide on Ge and Bi2Se3 crystals, thus facilitating high-resolution electron beam lithography (EBL) on their surfaces using a hydrogen silsesquioxane (HSQ) resist. HSQ offers the highest resolution of all the commercially available EBL resists. However, aqueous HSQ developers such as NaOH and tetramethylammonium hydroxide have thus far prevented the fabrication of high-resolution structures via the direct application of HSQ to Ge and Bi2Se3, due to the solubility of components of their respective native oxides in these strong aqueous bases. Here we provide a route to the generation of ordered, high-resolution, high-density Ge and Bi2Se3 nanostructures with potential applications in microelectronics, thermoelectric, and photonics devices.                         

From Polarity to Morphogenesis PAK Behaviors and Mechanism for Bud Sensing in Morphogenesis Checkpoint

Bud formation by Saccharomyces cerevisiae is a fundamental process for yeast proliferation. Bud emergence is initiated by the polarization of the cytoskeleton, leading to local secretory vesicle delivery and gulcan synthase activity. The master regulator of polarity establishment is a small Rho-family GTPase – Cdc42. Cdc42 forms a clustered patch at the incipient budding site in late G1 and mediates downstream events which lead to bud emergence. Cdc42 promotes morphogenesis via its various effectors. PAKs (p21-activated kinases) are important Cdc42 effectors which mediate actin cytoskeleton polarization and septin filament assembly. The PAKs Cla4 and Ste20 share common binding domains for GTP-Cdc42 and they are partially redundant in function. However, we found that Cla4 and Ste20 behaved differently during the polarization and this depended on their different membrane interaction domains. Also, Cla4 and Ste20 compete for a limited number of binding sites at the polarity patch during bud emergence. These results suggest that PAKs may be differentially regulated during polarity establishment.

Morphogenesis of yeast must be coordinated with the nuclear cycle to enable successful proliferation. Many environmental stresses temporarily disrupt bud formation, and in such circumstances, the morphogenesis checkpoint halts nuclear division until bud formation can resume. Bud emergence is essential for degradation of the mitotic inhibitor, Swe1. Swe1 is localized to the septin cytoskeleton at the bud neck by the Swe1-binding protein Hsl7. Neck localization of Swe1 is required for Swe1 degradation. Although septins form a ring at the presumptive bud site prior to bud emergence, Hsl7 is not recruited to the septins until after bud emergence, suggesting that septins and/or Hsl7 respond to a “bud sensor”. Here we show that recruitment of Hsl7 to the septin ring depends on a combination of two septin-binding kinases: Hsl1 and Elm1. We elucidate which domains of these kinases are needed, and show that artificial targeting of those domains suffices to recruit Hsl7 to septin rings even in unbudded cells. Moreover, recruitment of Elm1 is responsive to bud emergence. Our findings suggest that Elm1 plays a key role in sensing bud emergence.

Seawater carbonate chemistry, particulate organic particles, nutrients and species data during experiments with diatoms, 2006

We examine the effects of seawater pCO2 concentration of 25, 41, and 76 kPa (250, 400, and 750 matm) on the growth rate of a natural assemblage of mixed phytoplankton obtained from a carefully controlled, 14-d mesocosm experiment. Throughout the experiment period, in all enclosures, two phytoplankton taxa (microflagellates and cryptomonads) and two diatom species (Skeletonema costatum and Nitzschia spp.) account for approximately 90% of the phytoplankton community. During the nutrient-replete period from day 9 to day 14 populations of Skeletonema costatum and Nitzschia spp. increased substantially; however, only Skeletonema costatum showed an increase in growth rate with increasing seawater pCO2. Not all diatom species in Korean coastal waters are sensitive to seawater pCO2 under nutrient-replete conditions.

Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus

BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk

Juniperus navicularis - a study of Portuguese population structure and fitness

Juniperus navicularis Gand. is a dioecious endemic conifer that constitutes the understory of seaside pine forests in Portugal, areas currently threatened by increasing urban expansion. The aim of this study is to assess the conservation status of previously known populations of this species located on its core area of distribution. The study was performed in south-west coast of Portugal. Three populations varying in size and pine density were analyzed. Number of individuals, population density, spatial distribution and individual characteristics of junipers were estimated. Female cone, seed characteristics and seed viability were also evaluated. Results suggest that J. navicularis populations are vulnerable because seminal recruitment is scarce, what may lead to a reduction of genetic variability due solely to vegetative propagation. This vulnerability seems to be strongly determined by climatic constraints toward increasing aridity. Ratio between male and female shrubs did not differ from 1:1 in any population. Deviations from 1:1 between mature and non-mature plants were found in all populations, denoting population ageing. Very low seed viability was observed. A major part of described Juniperus navicularis populations have disappeared through direct habitat loss to urban development, loss of fitness in drier and warmer locations and low seed viability. This study is the first to address J. navicularis conservation, and represents a valuable first step toward this species preservation. 

Contribution to the ethnobotanical study of antidiabetic medicinal plants of the Central Middle Atlas region (Morocco)

An ethnobotanical survey of medicinal plants was carried out in the Central Middle Atlas in the years 2013 and 2014 to establish the catalog of medicinal plants used in traditional medicine in the treatment of diabetes. Thus, 1560 people were interviewed, using questionnaires. The latter enabled us to gather information on traditional healing practices of the local population including scientific name, French name, vernacular name, plant parts used , therapeutic indications , revenues and mode of administration. The results show that 76 medicinal species were inventoried in the study area. These plant species are included into 67 genus and 40 families. The most represented families are: Lamiaceae (12 species), Asteraceae and Brassicaceae species with 14 each. Of 76 medicinal species found in the region, four species are reported for the first time in the traditional treatment of diabetes in Morocco. They are Pistacia atlantica, Ptychotis verticillata, Anacyclus pyrethrum, Alyssum spinosum, Cistus albidus, Juniperus thurifera, Ephedra nebrodensis, Thymus algeriensis, Th. munbyanus, Th. zygis, Abelmoschus esculentus, Fraxinus augustifolia, Sorghum vulgare and, Eriobotrya japonica. The leaves are the most used organs (38%). The decoction is the dominant mode of preparation (50%) and administration is mostly for oral use (97%).

Nanotechnology in food industry II: risk assessment and legislation

Currently, there is increasing use of nanomaterials in the food industry thanks to the many advantages offered and make the products that contain them more competitive in the market. Their physicochemical properties often differ from those of bulk materials, which require specialized risk assessment. This should cover the risks to the health of workers and consumers as well as possible environmental risks. The risk assessment methods must go updating due to more widespread use of nanomaterials, especially now that are making their way down to consumer products. Today there is no specific legislation for nanomaterials, but there are several european dispositions and regulations that include them. This review gives an overview of the risk assessment and the existing current legislation regarding the use of nanotechnology in the food industry.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

Optimal generation scheduling of interconnected wind-coal intensive power systems

Large scale wind power generation complicated with restrictions on the tie line plans may lead to significant wind power curtailment and deep cycling of coal units during the valley load periods. This study proposes a dispatch strategy for interconnected wind-coal intensive power systems (WCISs). Wind power curtailment and cycling of coal units are included in the economic dispatch analysis of regional systems. Based on the day-ahead dispatch results, a tie line power plan adjustment strategy is implemented in the event of wind power curtailment or deep cycling occurring in the economic dispatch model, with the objective of reducing such effects. The dispatch strategy is designed based on the distinctive operation characteristics of interconnected WCISs, and dispatch results for regional systems in China show that the proposed strategy is feasible and can improve the overall system operation performance.

A multi vector energy analysis for interconnected power and gas systems

This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

A novel methodology for analysis of large scale interconnected power and gas systems

The European Union continues to exert a large influence on the direction of member states energy policy. The 2020 targets for renewable energy integration have had significant impact on the operation of current power systems, forcing a rapid change from fossil fuel dominated systems to those with high levels of renewable power. Additionally, the overarching aim of an internal energy market throughout Europe has and will continue to place importance on multi-jurisdictional co-operation regarding energy supply. Combining these renewable energy and multi-jurisdictional supply goals results in a complicated multi-vector energy system, where the understanding of interactions between fossil fuels, renewable energy, interconnection and economic power system operation is increasingly important. This paper provides a novel and systematic methodology to fully understand the changing dynamics of interconnected energy systems from a gas and power perspective. A fully realistic unit commitment and economic dispatch model of the 2030 power systems in Great Britain and Ireland, combined with a representative gas transmission energy flow model is developed. The importance of multi-jurisdictional integrated energy system operation in one of the most strategically important renewable energy regions is demonstrated.

N-opcode analysis for android malware classification and categorization

Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly sophisticated detection avoidance techniques employed by emerging malware families. This calls for more effective techniques for detection and classification of Android malware. Hence, in this paper we present an n-opcode analysis based approach that utilizes machine learning to classify and categorize Android malware. This approach enables automated feature discovery that eliminates the need for applying expert or domain knowledge to define the needed features. Our experiments on 2520 samples that were performed using up to 10-gram opcode features showed that an f-measure of 98% is achievable using this approach.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.