Asymmetric warming significantly affects net primary production, but not ecosystem carbon balances of forest and grassland ecosystems in northern China

We combine the process-based ecosystem model (Biome-BGC) with climate change-scenarios based on both RegCM3 model outputs and historic observed trends to quantify differential effects of symmetric and asymmetric warming on ecosystem net primary productivity (NPP), heterotrophic respiration (Rh) and net ecosystem productivity (NEP) of six ecosystem types representing different climatic zones of northern China. Analysis of covariance shows that NPP is significant greater at most ecosystems under the various environmental change scenarios once temperature asymmetries are taken into consideration. However, these differences do not lead to significant differences in NEP, which indicates that asymmetry in climate change does not result in significant alterations of the overall carbon balance in the dominating forest or grassland ecosystems. Overall, NPP, Rh and NEP are regulated by highly interrelated effects of increases in temperature and atmospheric CO2 concentrations and precipitation changes, while the magnitude of these effects strongly varies across the six sites. Further studies underpinned by suitable experiments are nonetheless required to further improve the performance of ecosystem models and confirm the validity of these model predictions. This is crucial for a sound understanding of the mechanisms controlling the variability in asymmetric warming effects on ecosystem structure and functioning

Building Savings and Investments Culture among Nigerians

Many Nigerians today live below the poverty line not necessarily because they have low incomes or poor salaries, but perhaps they lack savings and investments culture. The Harmonized Nigeria Living Standard Survey reports that Nigeria spends about N25 billion daily on food items. There is high propensity to consume but low propensity to save. This is quite alarming for a developing nation. High consumption would mean low savings, low investment, and low capital formation. If this persists, the Nigeria populace will be engulfed in poverty trap. It is therefore necessary to build among Nigerians savings and investments culture. A review of extant literature revealed that people save and invest for several reasons among which are to enhance the standard of living, take advantage of rare business opportunities, and meet unforeseen circumstances. Savings can be done through piggy, stokvel, thrift collection, credits unions, and banking system while investment is in the form of real asset, financial asset, and foreign exchange investment. Whatever form of investment one contemplates, it is very important to assess the risk-return trade off of such investment. Savings and investments guarantee your future. No matter how small is your income, you must learn to save to mobilize funds for investment. If the standard of living of Nigeria populace must be enhanced, there is therefore serious need for household savings and investment. Savings and investments must be our life style. We however in this study recommended the credit unions method of savings for Nigerians who belong to a field of membership

A Twin Study of Early-Childhood Asthma in Puerto Ricans

Background:The relative contributions of genetics and environment to asthma in Hispanics or to asthma in children younger than 3 years are not well understood.Objective:To examine the relative contributions of genetics and environment to early-childhood asthma by performing a longitudinal twin study of asthma in Puerto Rican children ≤3 years old.Methods:678 twin infants from the Puerto Rico Neo-Natal Twin Registry were assessed for asthma at age 1 year, with follow-up data obtained for 624 twins at age 3 years. Zygosity was determined by DNA microsatellite profiling. Structural equation modeling was performed for three phenotypes at ages 1 and 3 years: physician-diagnosed asthma, asthma medication use in the past year, and ≥1 hospitalization for asthma in the past year. Models were additionally adjusted for early-life environmental tobacco smoke exposure, sex, and age.Results:The prevalences of physician-diagnosed asthma, asthma medication use, and hospitalization for asthma were 11.6%, 10.8%, 4.9% at age 1 year, and 34.1%, 40.1%, and 8.5% at 3 years, respectively. Shared environmental effects contributed to the majority of variance in susceptibility to physician-diagnosed asthma and asthma medication use in the first year of life (84%-86%), while genetic effects drove variance in all phenotypes (45%-65%) at age 3 years. Early-life environmental tobacco smoke, sex, and age contributed to variance in susceptibility.Conclusion:Our longitudinal study in Puerto Rican twins demonstrates a changing contribution of shared environmental effects to liability for physician-diagnosed asthma and asthma medication use between ages 1 and 3 years. Early-life environmental tobacco smoke reduction could markedly reduce asthma morbidity in young Puerto Rican children. © 2013 Bunyavanich et al

Multi-Objective Counterfactual Explanations

Counterfactual explanations are one of the most popular methods to make predictions of black box machine learning models interpretable by providing explanations in the form of `what-if scenarios'. Most current approaches optimize a collapsed, weighted sum of multiple objectives, which are naturally difficult to balance a-priori. We propose the Multi-Objective Counterfactuals (MOC) method, which translates the counterfactual search into a multi-objective optimization problem. Our approach not only returns a diverse set of counterfactuals with different trade-offs between the proposed objectives, but also maintains diversity in feature space. This enables a more detailed post-hoc analysis to facilitate better understanding and also more options for actionable user responses to change the predicted outcome. Our approach is also model-agnostic and works for numerical and categorical input features. We show the usefulness of MOC in concrete cases and compare our approach with state-of-the-art methods for counterfactual explanations

Investigation of Critical Body Residues and Modes of Toxic Action Based on Injection and Aquatic Exposure in Fish

The internal concentration represented by the critical body residue (CBR) is an ideal indicator to reflect the intrinsic toxicity of a chemical. Whilst some studies have been performed on CBR, the effect of exposure route on internal toxicity has not been investigated for fish. In this paper, acute toxicity data to fish comprising LC50 and LD50 values were used to investigate CBR. The results showed that exposure route can significantly affect the internal concentration. LD50 and CBR calculated from LC50 and BCF both vary independently of hydrophobicity as expressed by log Kow; conversely, LC50 is related to log Kow. A poor relationship was observed between LC50 and LD50, but the relationship can be improved significantly by introduction of log Kow because log CBR is positively related to log LD50. The parallel relationship of log CBR-log Kow and log LD50-log Kow indicates that LD50 does not reflect the actual internal concentration. The average LD50 is close to the average CBR for less inert and reactive compounds, but greater than the average CBR for baseline compounds. This difference is due to the lipid fraction being the major storage site for most of the baseline compounds. Investigation on the calculated and observed CBRs shows that calculated CBRs are close to observed CBRs for most of compounds. However, systemic deviations of calculated CBRs have been observed for some compounds. The reasons for these systemic deviations may be attributed to BCF, equilibrium time and experimental error of LC50. These factors are important and should be considered in the calculation of CBRs

Cutting tool tracking and recognition based on infrared and visual imaging systems using principal component analysis (PCA) and discrete wavelet transform (DWT) combined with neural networks

The implementation of computerised condition monitoring systems for the detection cutting tools’ correct installation and fault diagnosis is of a high importance in modern manufacturing industries. The primary function of a condition monitoring system is to check the existence of the tool before starting any machining process and ensure its health during operation. The aim of this study is to assess the detection of the existence of the tool in the spindle and its health (i.e. normal or broken) using infrared and vision systems as a non-contact methodology. The application of Principal Component Analysis (PCA) and Discrete Wavelet Transform (DWT) combined with neural networks are investigated using both types of data in order to establish an effective and reliable novel software program for tool tracking and health recognition. Infrared and visual cameras are used to locate and track the cutting tool during the machining process using a suitable analysis and image processing algorithms. The capabilities of PCA and Discrete Wavelet Transform (DWT) combined with neural networks are investigated in recognising the tool’s condition by comparing the characteristics of the tool to those of known conditions in the training set. The experimental results have shown high performance when using the infrared data in comparison to visual images for the selected image and signal processing algorithms

A Categorical Clustering of Publishers for Mobile Performance Marketing

Mobile marketing is an expanding industry due to the growth of mobile devices (e.g., tablets, smartphones). In this paper, we explore a categorical approach to cluster publishers of a mobile performance market, in which payouts are only issued when there is a conversion (e.g., a sale). As a case study, we analyze recent and real-world data from a global mobile marketing company. Several experiments were held, considering a first internal evaluation stage, using training data, clustering quality metrics and computational effort. In the second stage, the best method, COBWEB algorithm, was analyzed using an external evaluation based on business metrics, computed over test data, and that allowed an identification of interesting clusters.This article is a result of the project NORTE-01-0247-FEDER- 017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work was also supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT Funda ̧ca ̃o para a Ciˆencia e Tecnologia within the Project Scope: UID/CEC/00319/2013

Chiral tunneling and the Klein paradox in graphene

The so-called Klein paradox - unimpeded penetration of relativistic particles through high and wide potential barriers - is one of the most exotic and counterintuitive consequences of quantum electrodynamics (QED). The phenomenon is discussed in many contexts in particle, nuclear and astro- physics but direct tests of the Klein paradox using elementary particles have so far proved impossible. Here we show that the effect can be tested in a conceptually simple condensed-matter experiment by using electrostatic barriers in single- and bi-layer graphene. Due to the chiral nature of their quasiparticles, quantum tunneling in these materials becomes highly anisotropic, qualitatively different from the case of normal, nonrelativistic electrons. Massless Dirac fermions in graphene allow a close realization of Klein's gedanken experiment whereas massive chiral fermions in bilayer graphene offer an interesting complementary system that elucidates the basic physics involved.Comment: 15 pages, 4 figure

Small inhibitor of Bcl-2, HA14-1, selectively enhanced the apoptotic effect of cisplatin by modulating Bcl-2 family members in MDA-MB-231 breast cancer cells

Inhibition or downregulation of Bcl-2 represents a new therapeutic approach to by-pass chemoresistance in cancer cells. Therefore, we explored the potential of this approach in breast cancer cells. Cisplatin and paclitaxel induced apoptosis in a dose-dependent manner in MCF-7 (drug-sensitive) and MDA-MB-231 (drug-insensitive) cells. Furthermore, when we transiently silenced Bcl-2, both cisplatin and paclitaxel induced apoptosis more than parental cells. Dose dependent induction of apoptosis by drugs was enhanced by the pre-treatment of these cells with HA14-1, a Bcl-2 inhibitor. Although the effect of cisplatin was significant on both cell lines, the effect of paclitaxel was much less potent only in MDA-MB-231 cells. To further understand the distinct role of drugs in MDA-MB-231 cells pretreated with HA14-1, caspases and Bcl-2 family proteins were studied. The apoptotic effect of cisplatin with or without HA14-1 pre-treatment is shown to be caspase-dependent. Among pro-apoptotic Bcl-2 proteins, Bax and Puma were found to be up-regulated whereas Bcl-2 and Bcl-x(L) were down-regulated when cells were pretreated with HA14-1 followed by paclitaxel or cisplatin. Enforced Bcl-2 expression in MDA-MB-231 cells abrogated the sensitizing effect of HA14-1 in cisplatin induced apoptosis. These results suggest that the potentiating effect of HA14-1 is drug and cell type specific and may not only depend on the inhibition of Bcl-2. Importantly, alteration of other pro-apoptotic or anti-apoptotic Bcl-2 family members may dictate the apoptotic response when HA14-1 is combined with chemotherapeutic drugs

Robust aircraft conceptual design using automatic differentiation in Matlab

The need for robust optimisation in aircraft conceptual design, for which the design parameters are assumed stochastic, is introduced. We highlight two approaches, first-order method of moments and Sigma-Point reduced quadrature, to estimate the mean and variance of the design’s outputs. The method of moments requires the design model’s differentiation and here, since the model is implemented in Matlab, is performed using the AD tool MAD. Gradient-based constrained optimisation of the stochastic model is shown to be more efficient using AD-obtained gradients than finite-differencing. A post-optimality analysis, performed using ADenabled third-order method of moments and Monte-Carlo analysis, confirms the attractiveness of the Sigma-Point technique for uncertainty propagation