Mobile Phone Call Data as a Regional Socio-Economic Proxy Indicator

The advent of publishing anonymized call detail records opens the door for temporal and spatial human dynamics studies. Such studies, besides being useful for creating universal models for mobility patterns, could be also used for creating new socio-economic proxy indicators that will not rely only on the local or state institutions. In this paper, from the frequency of calls at different times of the day, in different small regional units (sub-prefectures) in Côte d''Ivoire, we infer users'' home and work sub-prefectures. This division of users enables us to analyze different mobility and calling patterns for the different regions. We then compare how those patterns correlate to the data from other sources, such as: news for particular events in the given period, census data, economic activity, poverty index, power plants and energy grid data. Our results show high correlation in many of the cases revealing the diversity of socio-economic insights that can be inferred using only mobile phone call data. The methods and the results may be particularly relevant to policy-makers engaged in poverty reduction initiatives as they can provide an affordable tool in the context of resource-constrained developing economies, such as Côte d''Ivoire''s.     

Morpho-anatomical and physiological responses to waterlogging stress in different barley (<Emphasis Type="Italic">Hordeum vulgare</Emphasis> L.) genotypes

Waterlogging is one of the major stresses limiting crop production worldwide. The understanding of the mechanisms of plant adaptations to waterlogging stress helps improve plant tolerance to stress. In this study, physiological responses and morpho-anatomical adaptations of seven different barley genotypes were investigated under waterlogging stress. The results showed that the waterlogging-tolerant varieties (TX9425, Yerong, TF58) showed less reduction in plant height, SPAD (soil–plant analyses development analyses) value, tillers, shoot and root biomasses than did the waterlogging-sensitive varieties (Franklin, Naso Nijo, TF57). Under waterlogging stress condition, the tolerant genotypes also showed a much larger number of adventitious roots than did the sensitive genotypes. More intercellular spaces and better integrated chloroplast membrane structures were observed in the leaves of the waterlogging-tolerant cultivars, which is likely due to increased ethylene content, decreased ABA content and less accumulation of O₂^.?. The ability to form new adventitious roots and intercellular spaces in shoots can also be used as selection criteria in breeding barley for waterlogging tolerance.     

Use HypE to Hide Association Rules by Adding Items

During business collaboration, partners may benefit through sharing data. People may use data mining tools to discover useful relationships from shared data. However, some relationships are sensitive to the data owners and they hope to conceal them before sharing. In this paper, we address this problem in forms of association rule hiding. A hiding method based on evolutionary multi-objective optimization (EMO) is proposed, which performs the hiding task by selectively inserting items into the database to decrease the confidence of sensitive rules below specified thresholds. The side effects generated during the hiding process are taken as optimization goals to be minimized. HypE, a recently proposed EMO algorithm, is utilized to identify promising transactions for modification to minimize side effects. Results on real datasets demonstrate that the proposed method can effectively perform sanitization with fewer damages to the non-sensitive knowledge in most cases.     

Comparative Analysis of Endogenous Hormones and Metabolite Profiles in Early-Spring Flowering Plants and Unflowered Plants Revealing the Strategy of Blossom

Journal of Plant Growth Regulation - Early-spring plants are a special type of plant that complete their life cycle promptly in cold, early spring. Very little effort has been made into researching...     

Hydroxysafflor yellow A (HYSA) inhibited the proliferation and differentiation of 3T3-L1 preadipocytes

Hydroxysafflor yellow A (HSYA), a main component of safflor yellow, has been demonstrated to prevent steroid-induced avascular necrosis of femoral head by inhibiting primary bone marrow-derived mesenchymal stromal cells adipogenic differentiation induced by steroid. In this study, we investigate the effect of HSYA on the proliferation and adipogenesis of mouse 3T3-L1 preadipocytes. The effects of HSYA on proliferation and differentiation of 3T3-L1 cells and its possible mechanism were studied by 3-(4,5-dimethylthiazol-2-yl) 2,5-diphenyl tetrazolium bromide spectrophotometry, Oil Red O staining, intracellular triglyceride assays, real-time quantitative RT-PCR, transient transfection and dual luciferase reporter gene methods. HSYA inhibited the proliferation of 3T3-L1 preadipocytes and cell viability greatly decreased in a dose and time dependent manner. HSYA (1 mg/l) notably reduced the amount of intracellular lipid and triglyceride content in adipocytes by 21.3 % (2.13 ± 0.36 vs 2.71 ± 0.40, P < 0.01) and 22.6 % (1.33 ± 0.07 vs 1.72 ± 0.07, P < 0.01) on days 8 following the differentiation, respectively. HSYA (1 mg/l) significantly increased hormone-sensitive lipase (HSL) mRNA expression and promoter activities by 2.4- and 1.55-fold, respectively (P < 0.01), in differentiated 3T3-L1 adipocytes. HSYA inhibits the proliferation and adipogenesis of 3T3-L1 preadipocytes. The inhibitory action of HYSA on adipogenesis may be due to the promotion of lipolytic-specific enzyme HSL expression by increasing HSL promoter activity.     

Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China

It has long been concerned how crop water use efficiency (WUE) responds to climate change. Most of existing researches have emphasized the impact of single climate factor but have paid less attention to the effect of developed agronomic measures on crop WUE. Based on the long-term field observations/experiments data, we investigated the changing responses of crop WUE to climate variables (temperature and precipitation) and agronomic practices (fertilization and cropping patterns) in the semi-arid area of northern China (SAC) during two periods, 1983–1999 and 2000–2010 (drier and warmer). Our results suggest that crop WUE was an intrinsical system sensitive to climate change and agronomic measures. Crops tend to reach the maximum WUE (WUEmax) in warm-dry environment while reach the stable minimum WUE (WUEmin) in warm-wet environment, with a difference between WUEmax and WUEmin ranging from 29.0%-55.5%. Changes in temperature and precipitation in the past three decades jointly enhanced crop WUE by 8.1%-30.6%. Elevated fertilizer and rotation cropping would increase crop WUE by 5.6–11.0% and 19.5–92.9%, respectively. These results indicate crop has the resilience by adjusting WUE, which is not only able to respond to subsequent periods of favorable water balance but also to tolerate the drought stress, and reasonable agronomic practices could enhance this resilience. However, this capacity would break down under impact of climate changes and unconscionable agronomic practices (e.g. excessive N/P/K fertilizer or traditional continuous cropping). Based on the findings in this study, a conceptual crop WUE model is constructed to indicate the threshold of crop resilience, which could help the farmer develop appropriate strategies in adapting the adverse impacts of climate warming.     

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis

Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users. However, trust relationship in social network has not been taken into account in existing methods of cloud service selection and recommendation. In this paper, we propose a cloud service selection model based on the trust-enhanced similarity. Firstly, the direct, indirect, and hybrid trust degrees are measured based on the interaction frequencies among users. Secondly, we estimate the overall similarity by combining the experience usability measured based on Jaccard’s Coefficient and the numerical distance computed by Pearson Correlation Coefficient. Then through using the trust degree to modify the basic similarity, we obtain a trust-enhanced similarity. Finally, we utilize the trust-enhanced similarity to find similar trusted neighbors and predict the missing QoS values as the basis of cloud service selection and recommendation. The experimental results show that our approach is able to obtain optimal results via adjusting parameters and exhibits high effectiveness. The cloud services ranking by our model also have better QoS properties than other methods in the comparison experiments.