裂解气相色谱-质谱法鉴别双组分丙烯酸汽车清漆

为了提高微量物证鉴定中对双组分丙烯酸汽车清漆的鉴别能力，采用裂解气相色谱-质谱法(Py-GC/MS)检测该类清漆，并考察该方法在鉴定实践中的适用性。该方法的重现性好，丙烯酸聚氨酯清漆3个裂解单体的相对峰面积的日内RSD不大于5.3%，日间RSD不大于10.6%。应用该方法对6种丙烯酸氨基树脂汽车清漆样品及一例微量物证案件送检样品进行检测，结果表明，裂解气相色谱-质谱法对双组分丙烯酸汽车清漆的鉴别能力优于红外光谱法。在微量物证鉴定实践中，需要根据检材量酌情使用此方法，并注意“先无损后有损”的检验顺序。     

Deubiquitinases as Anticancer Targets of Gold Complexes

Metal-based anticancer agents with non-DNA targets are anticipated for overcoming cisplatin resistance problems. Gold complexes are generally known to undergo ligand exchange or redox reactions with thiols, and hence, are potentially useful agents that could target thiol-containing enzymes, but not DNA. Recent studies have shown that deubiquitinases (DUBs), key enzymes regulating proteasome-related protein homeostasis, are potential anticancer targets of both gold(I) and gold(III) complexes. In this review, the current status of gold complexes as DUB inhibitors is discussed. In particular, auranofin and cyclometalated gold(III) complexes containing dithiocarbamate ligands (e.g., [(Au^III(C N)(DEDT)]⁺, HC N=2-phenylpyridine, DEDT=diethyldithiocarbamate) are highlighted as examples of DUB inhibitors. The mechanisms of their anticancer action, together with in vitro and/or in vivo antitumor potencies, are also explored.     

Improved GDP spatialization approach by combining land-use data and night-time light data: a case study in China’s continental coastal area

Gross domestic product (GDP) reflects a nation or region’s economic growth as a whole, and is the sum of product in the primary, secondary, and tertiary sectors of the economy in the area. However, statistical GDP data is problematic in integrated application with geographical data. The GDP spatialization data, which shows the GDP in grid cells and often is obtained by operating a spatialization model, is more useful than its officially published statistical data recorded by administrative units in both spatial representation and application. Thus, there is a need to improve the GDP spatialization models, and to present these models in a way as clear and transparent as possible. In this article, by taking China’s continental coastal area as a case study area, we combined economic census data, land-use data, and night-time light data together, and developed a technique that we call the ‘dynamic regionalization’ method to improve the GDP spatialization products. We then created GDP spatialization models for three sectors of the economy (i.e. the primary, the secondary, and the tertiary sector) in 2000, 2005, and 2010, respectively. We find the following. (1) Because the ‘overglow’ effect of night-time light data has a bad influence on spatialization models, we used land-use data to distinguish the distribution plots of the tertiary sector on night-time light images. Compared with setting a threshold merely, land-use data can more effectively remove the ‘overglow’ effect. (2) Owing to the prominent spatial heterogeneity of GDP distribution in China’s continental coastal area, building one spatialization model for the whole area would probably produce the estimated products with poor accuracy, so the ‘dynamic regionalization’ method was adopted to dynamically divide the whole study area into several subregions, and build separate spatialization models for each subregion. The accuracy assessment showed that the new method improved the accuracy of GDP spatialization data, especially in the area with high spatial heterogeneity.     

Ethnically bounded homeownership: qualitative insights on Los Angeles immigrant homeowners’ experiences during the U.S. Great Recession

Immigrant homeowners’ function within ethnic boundaries in the housing market may have helped or hindered them during the recent U.S. Great Recession. This research explores this theme through interviews with immigrant and non-immigrant homeowners from four ethnic communities in Los Angeles County and the non-profit organizations that tried to assist them. Immigrant homeowners turned to co-ethnics for advice and support and formed multigenerational households as a strategy to achieve and sustain homeownership. Language and cultural barriers primed them for risky loans and thwarted their pursuit of refinance and modification when they struggled to make mortgage payments. These findings conform to existing evidence of ethnic segmentation in the housing market and imply that analyses of home buying and homeownership in areas with significant immigrant populations should factor in the role of ethnicity.     

What installed mobile applications tell about their owners and how they affect users’ download behavior

The rapid growth in the mobile application market presents a significant challenge to find interesting and relevant applications for users. An experimental study was conducted through the use of a specifically designed mobile application, on users’ mobile phones. The goals were; first, to learn about the users’ personality and the applications they downloaded to their mobile phones, second to recommend applications to users via notifications through the use of experimental mobile application and learn about user behavior in mobile environment. The question of how the personality features of users affect their compliance to recommendations is explored in this study. It is found that conscientiousness is positively related with accepting recommended applications and being agreeable is related with the preference for the applications of editor’s choice. Furthermore, in this study, applications owned by the user and the composition of applications under categories and their relation with personality features are explored. It is shown that the number of user owned applications and their category differ according to gender and personality. Having similar applications and the number of applications owned under specific categories increase the probability of accepting recommended applications.     

Observation of the semiconductor–metal transition behavior in monolayer graphene

We have observed that during temperature-dependent four-terminal resistance measurement of monolayer graphene, the resistance exhibits anomalous rising and falling behavior at different temperature regions. At lower temperature region (2–200 K) the resistance decreases gradually, but when the temperature rise further it turn to a sudden increase, and after 280 K it resumes gradual decrease. The rising and falling resistance behavior is characteristic of semiconductor or metal property. Consequently, the resistance transition follows a phase of semiconductor–metal–semiconductor. However, when a perpendicular magnetic field is applied, the resistance shows reverse transition behavior which follows a sequence of metal–semiconductor–metal. The novel transition property is attributed to the competition between the disorder of lattice defects as a short-range scattering in monolayer graphene and the Landau levels interaction. Magneto-transport measurement reveals that the excitonic gap induced by magnetic field in the monolayer graphene show an anomalous thermally activated property.     

Monte Carlo Data Envelopment Analysis with Genetic Algorithm for Knowledge Management performance measurement

The paper targets to devise a genuine Knowledge Management (KM) performance measurement model in a stochastic setting based on Data Envelopment Analysis (DEA), Monte Carlo simulation and Genetic Algorithm (GA). The proposed model evaluates KM using a set of proxy measures correlated with the major KM processes. Data Collection Budget Allocation (DCBA) that maximizes the model accuracy is determined using GA. Additional data are generated and analyzed using a Monte-Carlo-enhanced DEA model to obtain the overall KM efficiency and KM processes’ efficiency scores. An application of the model has been carried out to evaluate KM performance in higher educational institutions. It is found that with GA, the accuracy of the model has been greatly improved. Lastly, comparing with a conventional deterministic DEA model, the results from the proposed model would be more useful for managers to determine future strategies to improve their KM.     

Unseen science? Representation of BRICs in global science

A survey of scientific periodical publications (or venues-as distinct from articles) from BRIC country practitioners counted more than 15,000 national publications. Data collected from and about Brazil, Russia, India, and China (BRIC countries) show that 495 venues, or about 3%, are listed in the Science Citation Index Expanded^© (SCIE^©) in 2010. Contrary to our expectation of under-representation overall and coverage limitation of SCIE, the average percentage of SCIE-listed venues for the BRICs is about the same as that for advanced countries. China has the lowest representation of national venues in SCIE at 2% of all publications; Russia has the highest at about 8%. India has about 6% of venues in SCIE; Brazil has about 4%. In other words, SCIE includes about the same percentage of high quality science from these four countries as for North America and Europe, meaning that these countries are not under-represented in SCIE. Moreover, the number of national venues available as outlets suggests that national scientists in these countries have good access to publications and venues. Some of the BRIC national publications are difficult to “see” at the global level because of language barriers, diverse publication formats, and lack of digitization. Other national differences represent historical traditions surrounding publication.