Multi-learner based recursive supervised training

In this paper, we propose the Multi-Learner Based Recursive Supervised Training (MLRT) algorithm which uses the existing framework of recursive task decomposition, by training the entire dataset, picking out the best learnt patterns, and then repeating the process with the remaining patterns. Instead of having a single learner to classify all datasets during each recursion, an appropriate learner is chosen from a set of three learners, based on the subset of data being trained, thereby avoiding the time overhead associated with the genetic algorithm learner utilized in previous approaches. In this way MLRT seeks to identify the inherent characteristics of the dataset, and utilize it to train the data accurately and efficiently. We observed that empirically, MLRT performs considerably well as compared to RPHP and other systems on benchmark data with 11% improvement in accuracy on the SPAM dataset and comparable performances on the VOWEL and the TWO-SPIRAL problems. In addition, for most datasets, the time taken by MLRT is considerably lower than the other systems with comparable accuracy. Two heuristic versions, MLRT-2 and MLRT-3 are also introduced to improve the efficiency in the system, and to make it more scalable for future updates. The performance in these versions is similar to the original MLRT system

Outsourcing CO2 within China

Recent studies have shown that the high standard of living enjoyed by people in the richest countries often comes at the expense of CO2 emissions produced with technologies of low efficiency in less affluent, developing countries. Less apparent is that this relationship between developed and developing can exist within a single country’s borders, with rich regions consuming and exporting high-value goods and services that depend upon production of low-cost and emission-intensive goods and services from poorer regions in the same country. As the world’s largest emitter of CO2, China is a prominent and important example, struggling to balance rapid economic growth and environmental sustainability across provinces that are in very different stages of development. In this study, we track CO2 emissions embodied in products traded among Chinese provinces and internationally. We find that 57% of China’s emissions are related to goods that are consumed outside of the province where they are produced. For instance, up to 80% of the emissions related to goods consumed in the highly developed coastal provinces are imported from less developed provinces in central and western China where many low–value-added but high–carbon-intensive goods are produced. Without policy attention to this sort of interprovincial carbon leakage, the less developed provinces will struggle to meet their emissions intensity targets, whereas the more developed provinces might achieve their own targets by further outsourcing. Consumption-based accounting of emissions can thus inform effective and equitable climate policy within China

Two problems related to prescribed curvature measures

Existence of convex body with prescribed generalized curvature measures is discussed, this result is obtained by making use of Guan-Li-Li's innovative techniques. In surprise, that methods has also brought us to promote Ivochkina's $C^2$ estimates for prescribed curvature equation in \cite{I1, I}.Comment: 12 pages, Corrected typo

Exploring Causal Influences

Recent data mining techniques exploit patterns of statistical independence in multivariate data to make conjectures about cause/effect relationships. These relationships can be used to construct causal graphs, which are sometimes represented by weighted node-link diagrams, with nodes representing variables and combinations of weighted links and/or nodes showing the strength of causal relationships. We present an interactive visualization for causal graphs (ICGs), inspired in part by the Influence Explorer. The key principles of this visualization are as follows: Variables are represented with vertical bars attached to nodes in a graph. Direct manipulation of variables is achieved by sliding a variable value up and down, which reveals causality by producing instantaneous change in causally and/or probabilistically linked variables. This direct manipulation technique gives users the impression they are causally influencing the variables linked to the one they are manipulating. In this context, we demonstrate the subtle distinction between seeing and setting of variable values, and in an extended example, show how this visualization can help a user understand the relationships in a large variable set, and with some intuitions about the domain and a few basic concepts, quickly detect bugs in causal models constructed from these data mining techniques

A Compact Wideband Two-Arm-Antenna for Mobile Phones

A compact film type antenna capable of generating two wide resonant modes for covering the AMPS/GSM bands and the DCS/PCS/UMTS bands for mobile phones is proposed. The antenna consists of two superimposed radiation arms which can support two resonant modes by themselves. The frequency range of a resonant mode generated by one of the arm is arranged to differ a little with the corresponding mode of the other, at the fundamental and higher-order modes. As a result, the bandwidths at both of the resonant modes are significantly enhanced. The antenna has a compact dimension of 5 x 15 x 40 mm3 and covers five bands of AMPS/GSM/DCS/ PCS/UMTS for a VSWR less than 2.5:1. It shows fairly good omnidirectional radiation patterns and high gains over 0 dBi in the azimuthal plane, at all the operating bands

Hertz-level Measurement of the 40Ca+ 4s 2S1/2-3d 2D5/2 Clock Transition Frequency With Respect to the SI Second through GPS

We report a frequency measurement of the clock transition of a single ^40Ca^+ ion trapped and laser cooled in a miniature ring Paul trap with 10^-15 level uncertainty. In the measurement, we used an optical frequency comb referenced to a Hydrogen maser, which was calibrated to the SI second through the Global Positioning System (GPS). Two rounds of measurements were taken in May and June 2011, respectively. The frequency was measured to be 411 042 129 776 393.0(1.6) Hz with a fractional uncertainty of 3.9{\times}10^-15 in a total averaging time of > 2{\times}10^6 s within 32 days

Embracing Geographic Analysis Beyond Geography - Harvard's Center for Geographic Analysis Enters its 5th Year

Without a department of geography, Harvard University established the Center for Geographic Analysis (CGA) in 2006 to support research and teaching of all disciplines across the University with emerging geospatial technologies. In the past four and a half years, CGA built an institutional service infrastructure and unleashed an increasing demand on geographic analysis in many fields. CGA services range from helpdesk, project consultation, training, hardware/software administration, community building, to system development and methodology research. Services often start as an application of existing GIS technology, eventually contributing to the study of geographic information science in many ways. As a new generation of students and researchers growing up with Google Earth and the like, their demand for geospatial services will continue to push CGA into new territories.East Asian Languages and Civilization

KDM2B/FBXL10 targets c-Fos for ubiquitylation and degradation in response to mitogenic stimulation.

KDM2B (also known as FBXL10) controls stem cell self-renewal, somatic cell reprogramming and senescence, and tumorigenesis. KDM2B contains multiple functional domains, including a JmjC domain that catalyzes H3K36 demethylation and a CxxC zinc-finger that recognizes CpG islands and recruits the polycomb repressive complex 1. Here, we report that KDM2B, via its F-box domain, functions as a subunit of the CUL1-RING ubiquitin ligase (CRL1/SCF(KDM2B)) complex. KDM2B targets c-Fos for polyubiquitylation and regulates c-Fos protein levels. Unlike the phosphorylation of other SCF (SKP1-CUL1-F-box)/CRL1 substrates that promotes substrates binding to F-box, epidermal growth factor (EGF)-induced c-Fos S374 phosphorylation dissociates c-Fos from KDM2B and stabilizes c-Fos protein. Non-phosphorylatable and phosphomimetic mutations at S374 result in c-Fos protein which cannot be induced by EGF or accumulates constitutively and lead to decreased or increased cell proliferation, respectively. Multiple tumor-derived KDM2B mutations impaired the function of KDM2B to target c-Fos degradation and to suppress cell proliferation. These results reveal a novel function of KDM2B in the negative regulation of cell proliferation by assembling an E3 ligase to targeting c-Fos protein degradation that is antagonized by mitogenic stimulations

Dealing with Web service QoS factors using constraint hierarchy

Functionality and non-functional properties are two critical factors in web service technology, but non-functional properties (quality factors) are often ignored. Usually, these are articulated as statements of objectives, as opposed to prepositional assertions. A key challenge in dealing with objectives is that there is no obvious means to decide when they are satisfied. In effect, these objectives are never fu lly satisfied, but satisficed to varying degrees. Alternative design decisions need to trade-off varying degrees of satisfaction of potentially mutually contradictory non-functional requirements. In some circumstances, non-Junctional properties are crucial; they do affect the design decision. Upon a request, there are a range o f web services that might provide the required functionality, so the web service selection can only be done based on their Quality of Service (QoS). Therefore, a quality-based web service model is in high demand. The key contribution of this paper is the use of the hierarchical constraint logic programming framework [9, 10] in dealing with quality factors. We show how quality factors can be formulated as soft constraints and how the machinery associated with constraint hierarchies can be used to evaluate the web services