ARE LOWER-INCOME SHOPPERS AS PRICE SENSITIVE AS HIGHER-INCOME ONES?: A LOOK AT BREAKFAST CEREALS

Scanner data for breakfast cereals are used to estimate demand elasticities for six supermarket stores in two distinct socio-economic areas. Three stores are in low-income locations and three are in high-income locations. A time series cross-section model is estimated for five product categories across six cross sections over forty-two weeks. Results show lower-income shoppers to have more elastic demands for four of the five product categories: private label cold cereals, the top ten brands of cold cereals, all other brands of cold cereals, and hot cereals. Price is not statistically significant for a fifth product category, snack cereals.Consumer/Household Economics,

IMPACT OF HEALTH INFORMATION ON DEMAND FOR FATS AND OILS IN JAPAN: COINTEGRATION AND A COMPLETE DEMAND SYSTEM APPROACH

This paper deals with the structural change for fats and oils in Japan focusing on the possible influence of health information. The newly developed fat and cholesterol information index appears to reflect the changing health information on fat and cholesterol much better than the ad-hoc cumulative index.Food Consumption/Nutrition/Food Safety,

Characterising functions of long non-coding RNAs in Drosophila embryogenesis

An appreciation of the complexity of the mammalian transcriptome has expanded our understanding of eukaryotic genome regulation with the discoveries of functional non-coding ribonucleic acids (RNAs). In recent years, the number of studies in the field of long non-coding RNA (lncRNA) biology has increased dramatically. Transcriptomic analyses of the eukaryotic genome revealed that the genome is pervasively transcribed and contains a vast number of lncRNA transcripts, most with unknown functions. Although relatively little is known about lncRNAs in general, a few have been shown to function in the regulation of gene expression during development and have been associated with a number of diseases. The aim of my dissertation is to investigate the impact of lncRNAs loss of function during embryogenesis of Drosophila melanogaster. I chose this model organism for its well documented developmental stages and the plethora of established tools available to facilitate genetic studies. Twenty-two lncRNA candidates were chosen based on their conservation at the sequence level and similar expression profiles across 5 Drosophila species, suggesting their potential for biological importance. The CRISPR/Cas9 system was used to generate lncRNA mutants and their requirement for development and the phenotypic consequences of losing each lncRNA was investigated. 13 lncRNA mutants were generated and two of them, lncRNA-9 and lncRNA-3 respectively, were required for viability, with homozygous mutants showing full lethality. Majority of the lncRNA-9 null mutant embryos were found to be unable to complete embryonic development and whereas lncRNA-3 null mutants had a pupal lethal phenotype. None of the lncRNA mutants were found to be required for fertility. I characterised the sub-cellular localization of lncRNA-9 during embryogenesis using a combination of RNA Fluorescence In Situ Hybridization (RNA-FISH) and Immunofluorescence (IF) approaches. An analysis of the transcriptome of lncRNA-9 mutants, in comparison to controls, was carried out to discover the genes that were mis-regulated and responsible for the observed lethality. Our investigation of lncRNA-9 revealed a nuclear lncRNA that is expressed in neurons and preliminary results from GO analysis revealed a loss of lncRNA-9 resulted in a reduction in the expression of neuronal genes involved in chemical synaptic transmission activities. Further characterization of lncRNA-9 will allow us to understand how lncRNAs contributes to various neural circuits and the overall signalling in the Drosophila connectome.Cancer Research U

Control energy of complex networks towards distinct mixture states

Controlling complex networked systems is a real-world puzzle that remains largely unsolved. Despite recent progress in understanding the structural characteristics of network control energy, target state and system dynamics have not been explored. We examine how varying the final state mixture affects the control energy of canonical and conformity-incorporated dynamical systems. We find that the control energy required to drive a network to an identical final state is lower than that required to arrive a non-identical final state. We also demonstrate that it is easier to achieve full control in a conformity-based dynamical network. Finally we determine the optimal control strategy in terms of the network hierarchical structure. Our work offers a realistic understanding of the control energy within the final state mixture and sheds light on controlling complex systems.This work was funded by The National Natural Science Foundation of China (Grant Nos. 61763013, 61703159, 61403421), The Natural Science Foundation of Jiangxi Province (No. 20171BAB212017), The Measurement and Control of Aircraft at Sea Laboratory (No. FOM2016OF010), and China Scholarship Council (201708360048). The Boston University Center for Polymer Studies is supported by NSF Grants PHY-1505000, CMMI-1125290, and CHE-1213217, and by DTRA Grant HDTRA1-14-1-0017. (61763013 - National Natural Science Foundation of China; 61703159 - National Natural Science Foundation of China; 61403421 - National Natural Science Foundation of China; 20171BAB212017 - Natural Science Foundation of Jiangxi Province; FOM2016OF010 - Measurement and Control of Aircraft at Sea Laboratory; 201708360048 - China Scholarship Council; PHY-1505000 - NSF; CMMI-1125290 - NSF; CHE-1213217 - NSF; HDTRA1-14-1-0017 - DTRA)Published versio

Simple spatial scaling rules behind complex cities

Although most of wealth and innovation have been the result of human interaction and cooperation, we are not yet able to quantitatively predict the spatial distributions of three main elements of cities: population, roads, and socioeconomic interactions. By a simple model mainly based on spatial attraction and matching growth mechanisms, we reveal that the spatial scaling rules of these three elements are in a consistent framework, which allows us to use any single observation to infer the others. All numerical and theoretical results are consistent with empirical data from ten representative cities. In addition, our model can also provide a general explanation of the origins of the universal super- and sub-linear aggregate scaling laws and accurately predict kilometre-level socioeconomic activity. Our work opens a new avenue for uncovering the evolution of cities in terms of the interplay among urban elements, and it has a broad range of applications.This work is supported by the National Natural Science Foundation of China under Grant Nos. 61673070, 61773069, 71731002 and the Fundamental Research Funds for the Central Universities with the Grant No. 2015KJJCB13, and also partially supported by NSF Grants PHY-1505000, CMMI-1125290, CHE-1213217, DTRA Grant HDTRA1-14-1-0017, DOE Grant DE-AC07-05Id14517. J.Z. acknowledges discussions with Prof. Bettencourt of the Santa Fe Institute, Dr. Lingfei Wu of Arizona State University, and Profs. Yougui Wang and Qinghua Chen of Beijing Normal University. R.L. acknowledges helpful discussions with and comments from Dr. Remi Louf in CASA, University College London, Dr. Longfeng Zhao from Huazhong (Central China) Normal University, and selfless help from Prof. Yougui Wang. R.L. is also supported by the Chinese Scholarship Council. (61673070 - National Natural Science Foundation of China; 61773069 - National Natural Science Foundation of China; 71731002 - National Natural Science Foundation of China; 2015KJJCB13 - Fundamental Research Funds for the Central Universities; PHY-1505000 - NSF; CMMI-1125290 - NSF; CHE-1213217 - NSF; HDTRA1-14-1-0017 - DTRA Grant; DE-AC07-05Id14517 - DOE; Chinese Scholarship Council)Published versio

Emergence of communities and diversity in social networks

Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics.This work was supported by the National Nature Science Foundation of China under Grants 61573064, 71631002, 71401037, and 11301032; the Fundamental Research Funds for the Central Universities and Beijing Nova Programme; and the Natural Sciences and Engineering Research Council of Canada (Individual Discovery Grant). The Boston University work was supported by NSF Grants PHY-1505000, CMMI-1125290, and CHE- 1213217, and by Defense Threat Reduction Agency Grant HDTRA1-14-1-0017, and Department of Energy Contract DE-AC07-05Id14517. (61573064 - National Nature Science Foundation of China; 71631002 - National Nature Science Foundation of China; 71401037 - National Nature Science Foundation of China; 11301032 - National Nature Science Foundation of China; Fundamental Research Funds for the Central Universities and Beijing Nova Programme; Natural Sciences and Engineering Research Council of Canada (Individual Discovery Grant); PHY-1505000 - NSF; CMMI-1125290 - NSF; CHE-1213217 - NSF; HDTRA1-14-1-0017 - Defense Threat Reduction Agency; DE-AC07-05Id14517 - Department of Energy)Published versio