Environment Kuznets curve for CO2 emissions: A cointegration analysis for China

Cataloged from PDF version of article.This study examines the long-run relationship between carbon emissions and energy consumption, income and foreign trade in the case of China by employing time series data of 1975–2005. In particular the study aims at testing whether environmental Kuznets curve (EKC) relationship between CO2 emissions and per capita real GDP holds in the long run or not. Auto regressive distributed lag (ARDL) methodology is employed for empirical analysis. A quadratic relationship between income and CO2 emission has been found for the sample period, supporting EKC relationship. The results of Granger causality tests indicate one way causality runs through economic growth to CO2 emissions. The results of this study also indicate that the carbon emissions are mainly determined by income and energy consumption in the long run. Trade has a positive but statistically insignificant impact on CO2 emissions. & 2009 Elsevier Ltd. All rights reserved

Coherently controlled entanglement generation in a binary Bose-Einstein condensate

Considering a two-component Bose-Einstein condensate in a double-well potential, a method to generate a Bell state consisting of two spatially separated condensates is suggested. For repulsive interactions, the required tunnelling control is achieved numerically by varying the amplitude of a sinusoidal potential difference between the wells. Both numerical and analytical calculations reveal the emergence of a highly entangled mesoscopic state.Comment: 6 pages, 6 figures, epl2.cl

School Closures and Returning to School: Views of Parents of Children With Disabilities in England During the Covid-19 Pandemic

Children and young people with special educational needs and disabilities and their families are likely to be significantly affected by the Covid-19 pandemic at various levels, particularly given the implementation of school closures during national lockdowns. This study employed a survey design to assess parental perspectives on the impact of school closures and of returning to school in England, as a result of the Covid-19 pandemic. Eighty-three parents of children and young people with various types of need responded to the survey between September and December 2020. The survey included multiple choice questions and open-ended questions for further in-depth examination of parental perspectives. Results show that: the majority of parents reported that school closures had a detrimental effect on their children’s mental health (particularly those from the most deprived neighbourhoods) and on their own mental and physical health (particularly for ethnically diverse parents and for those whose children attend specialized settings); returning to school was considered to have a positive impact on children’s mental and physical health for the vast majority of parents, despite fearing exposure to the virus; many parents have reported that their children were calmer and happier at home during school closures and became more anxious and stressed upon returning to school. The role of cumulative risk in these children and families, as well as the role of schools as key support agents for the most vulnerable are discussed with implications for future research and policy

Quantum Chaos in the Bose-Hubbard model

We present a numerical study of the spectral properties of the 1D Bose-Hubbard model. Unlike the 1D Hubbard model for fermions, this system is found to be non-integrable, and exhibits Wigner-Dyson spectral statistics under suitable conditions.Comment: 4 pages, 4 figure

Inferring the Origin Locations of Tweets with Quantitative Confidence

Social Internet content plays an increasingly critical role in many domains, including public health, disaster management, and politics. However, its utility is limited by missing geographic information; for example, fewer than 1.6% of Twitter messages (tweets) contain a geotag. We propose a scalable, content-based approach to estimate the location of tweets using a novel yet simple variant of gaussian mixture models. Further, because real-world applications depend on quantified uncertainty for such estimates, we propose novel metrics of accuracy, precision, and calibration, and we evaluate our approach accordingly. Experiments on 13 million global, comprehensively multi-lingual tweets show that our approach yields reliable, well-calibrated results competitive with previous computationally intensive methods. We also show that a relatively small number of training data are required for good estimates (roughly 30,000 tweets) and models are quite time-invariant (effective on tweets many weeks newer than the training set). Finally, we show that toponyms and languages with small geographic footprint provide the most useful location signals.Comment: 14 pages, 6 figures. Version 2: Move mathematics to appendix, 2 new references, various other presentation improvements. Version 3: Various presentation improvements, accepted at ACM CSCW 201

SigMate: a MATLAB-based automated tool for extracellular neuronal signal processing and analysis

Rapid advances in neuronal probe technology for multisite recording of brain activity have posed a significant challenge to neuroscientists for processing and analyzing the recorded signals. To be able to infer meaningful conclusions quickly and accurately from large datasets, automated and sophisticated signal processing and analysis tools are required. This paper presents a Matlab-based novel tool, “SigMate”, incorporating standard methods to analyze spikes and EEG signals, and in-house solutions for local field potentials (LFPs) analysis. Available modules at present are – 1. In-house developed algorithms for: data display (2D and 3D), file operations (file splitting, file concatenation, and file column rearranging), baseline correction, slow stimulus artifact removal, noise characterization and signal quality assessment, current source density (CSD) analysis, latency estimation from LFPs and CSDs, determination of cortical layer activation order using LFPs and CSDs, and single LFP clustering; 2. Existing modules: spike detection, sorting and spike train analysis, and EEG signal analysis. SigMate has the flexibility of analyzing multichannel signals as well as signals from multiple recording sources. The in-house developed tools for LFP analysis have been extensively tested with signals recorded using standard extracellular recording electrode, and planar and implantable multi transistor array (MTA) based neural probes. SigMate will be disseminated shortly to the neuroscience community under the open-source GNU-General Public License

Karakteristik Dan Akar Masalah Kemiskinan Kasus Pada 4 Tipologi Desa Di Kabupaten Sumbawa

This research meant to dig and comprehends indicators distinguishing characteristic and poorness problem root in Sumbawa regency. Because of research region broadness, hence research subject is determined in purposive by four countrysides assessed representation able to in geographical typology complete and characteristic countryside public and also level of poorness of resident Sumbawa regency in general. As for fourth of countryside typology is rural area, mountain area, coastal area, and sub urban area. Analyzer applied to comprehend characteristic and poorness problem root of the countryside public, that is using analysis Method Participative Poorness, which developed with method Root Cause Analysis (RCA). This method applied to comprehend characteristic and poorness problem root in each countryside typology. The result of data analysis in general inferential that the poorness characteristic in each countryside typology actually not solely determined by region typology, because at most all countryside typologies there is poor resident amounts which relative still big. This condition altogether determined by economic indicators as factor that is very influences level of prosperity/ poorness of countryside public

Configuration Detection of Grounding Grid: Static Electric Field Based Nondestructive Technique

Grounding grid configuration which, is key to its fault diagnosis, changes continuously with the extension in a substation. Furthermore, older substations grounding grid configurations are unknown. Existing literature regarding configuration detection mainly accounts for the magnetic field that required a gradient to locate the grounding conductor. The gradient of raw measurement in the substation vicinity enhances electromagnetic noise and distorts the results. Therefore, in this paper, we have developed a new algorithm, Configuration Detection of Grounding Grid (CDGG) based on the static electric field and the concept of ordered pairs to draw the configuration of the unknown grounding grid. Unlike, the practiced magnetic field, the electric field does not require a gradient. The maximum electric field value indicates the location of a grounding conductor. The connection between nodes is verified by measuring the electric field on the circle. Furthermore, the proposed algorithm also locates any diagonal conductor in the configuration. Mathematical reasoning and simulation results illustrate that our proposed algorithm is feasible to draw the configuration of the unknown grounding grid

Demographic dynamics in rural Northern Nigeria : a case study of Gimba, Kaduna State

The purpose of this case study, conducted in February and March, 1979 was to obtain data on the general population characteristics, as well as the fertility and mortality of a typical rural Hausa community. The selected village of Gimba is situated in the Soba district of Zaria emirate, Kaduna State, in the North of Nigeria. Gimba is typical of the area being predominantly agricultural as well as being a traditional moslem community. A total of 471 households were enumerated in the village. Previous information on the demographic condition of the rural Hausa has come from data collected in the course of anthropological and economic studies. Such information is necessarily scanty. This study thus represents an attempt to fill some of the gaps in the existing knowledge of the demography of the Hausa people, who are the largest single ethnic group in Nigeria. The survey data shows that the population is characterised by universal and early age at marriage. Most girls marry before the age of 15. Marriage is fairly stable: over three fourths of the wives under 50 years of age were in their first unions at the time of the survey. By applying relatively new analytical techniques this study has succeeded in deriving estimates of mortality that are internally consistent and plausible. The average expectations of life at birth of 44.4 and 43.9 years have been estimated for females and males respectively. Various fertility measures, such as the crude birth rate, age-specific fertility rates as well as net reproduction rate have also been estimated. The total fertility rate for the population was 6.0 and the mean age of childbearing is estimated at 27 years. The data shows that the level of fertility in the survey population is, by Nigerian experience, moderate, occupying the middle position between the high and low levels observed in other rural communities. It is demonstrated that level of fertility and the length of breast feeding are inversely related. The data indicates that monogamously married women in Gimba have a slightly higher fertility than their polygamous counterparts, but that the actual family size of the women was substantially below the ideal family size. Besides providing hitherto unavailable data, it is hoped that this study will provide a suitable framework for future demographic research in other similar communities