Mapping Articles on China in Wikipedia: An Inter-Language Semantic Network Analysis

This article describes an inter-language semantic network analysis examining the differences between articles about China in the Chinese and English versions of Wikipedia. It explores the differences in the content of Wikipedia through (a) correlation analysis of semantic networks and (b) the salience of semantic concepts through their network centralities. The results suggest there is high dissimilarity between the semantic content of the English and Chinese versions of articles on China. While both pages focused on government, population, language, character, diplomatic relations, development of the economy, and science and technology, the Chinese-speaking and English-speaking contributors framed the article on China differently—according to dissimilarities in cultures, values, interests, situations, and emotions of different language groups. This research contributes to the literature and understanding of how culture of different language groups influences the process of crowdsourcing knowledge on online collaboration platforms

Observations of Field Current and Field Winding Temperature in Electrically Excited Synchronous Machines with Brushless Excitation

Electrically excited synchronous machines have become an alternative in electrification of transportations and renewable power generations. To reduce the extra effort in the maintenance of sliprings and brushes for field excitation, brushless excitation has been developed. However, when brushless excitation is adopted, the field winding becomes physically inaccessible when the machine is rotating. To solve this problem, an algorithm is proposed in this study to observe the field current and field winding temperature of an EESM with brushless excitation. The stator currents are measured and then used to correct the machine state predictor. The correction of the state prediction is interpreted to adjust the field winding resistance and temperature value. The algorithm is evaluated in simulations. The estimations of field current and field winding temperature track the measurements successfully

Investigating the potential causal association between consumption of green tea and risk of lung cancer: a study utilizing Mendelian randomization

BackgroundLung cancer is the most common global cancer in terms of incidence and mortality. Its main driver is tobacco smoking. The identification of modifiable risk factors isa public health priority. Green tea consumption has been examined in epidemiological studies, with inconsistent findings. Thus, we aimed to apply Mendelian randomization to clarify any causal link between green tea consumption and the risk of lung cancer.MethodsWe utilized a two-sample Mendelian randomization (MR) approach. Genetic variants served as instrumental variables. The goal was to explore a causal link between green tea consumption and different lung cancer types. Green tea consumption data was sourced from the UK Biobank dataset, and the genetic association data for various types of lung cancer were sourced from multiple databases. Our analysis included primary inverse-variance weighted (IVW) analyses and various sensitivity test.ResultsNo significant associations were found between green tea intake and any lung cancer subtypes, including non-small cell lung cancer (adenocarcinoma and squamous cell carcinoma) and small cell lung cancer. These findings were consistent when applying multiple Mendelian randomization methods.ConclusionGreen tea does not appear to offer protective benefits against lung cancer at a population level. However, lung cancer's complex etiology and green tea's potential health benefitssuggest more research is needed. Further studies should include diverse populations, improved exposure measurements and randomized controlled trials, are warranted

MGMT genomic rearrangements contribute to chemotherapy resistance in gliomas.

Temozolomide (TMZ) is an oral alkylating agent used for the treatment of glioblastoma and is now becoming a chemotherapeutic option in patients diagnosed with high-risk low-grade gliomas. The O-6-methylguanine-DNA methyltransferase (MGMT) is responsible for the direct repair of the main TMZ-induced toxic DNA adduct, the O6-Methylguanine lesion. MGMT promoter hypermethylation is currently the only known biomarker for TMZ response in glioblastoma patients. Here we show that a subset of recurrent gliomas carries MGMT genomic rearrangements that lead to MGMT overexpression, independently from changes in its promoter methylation. By leveraging the CRISPR/Cas9 technology we generated some of these MGMT rearrangements in glioma cells and demonstrated that the MGMT genomic rearrangements contribute to TMZ resistance both in vitro and in vivo. Lastly, we showed that such fusions can be detected in tumor-derived exosomes and could potentially represent an early detection marker of tumor recurrence in a subset of patients treated with TMZ

Using chromosome introgression lines to map quantitative trait loci for photosynthesis parameters in rice (Oryza sativa L.) leaves under drought and well-watered field conditions

Photosynthesis is fundamental to biomass production, but sensitive to drought. To understand the genetics of leaf photosynthesis, especially under drought, upland rice cv. Haogelao, lowland rice cv. Shennong265, and 94 of their introgression lines (ILs) were studied at flowering and grain filling under drought and well-watered field conditions. Gas exchange and chlorophyll fluorescence measurements were conducted to evaluate eight photosynthetic traits. Since these traits are very sensitive to fluctuations in microclimate during measurements under field conditions, observations were adjusted for microclimatic differences through both a statistical covariant model and a physiological approach. Both approaches identified leaf-to-air vapour pressure difference as the variable influencing the traits most. Using the simple sequence repeat (SSR) linkage map for the IL population, 1–3 quantitative trait loci (QTLs) were detected per trait–stage–treatment combination, which explained between 7.0% and 30.4% of the phenotypic variance of each trait. The clustered QTLs near marker RM410 (the interval from 57.3 cM to 68.4 cM on chromosome 9) were consistent over both development stages and both drought and well-watered conditions. This QTL consistency was verified by a greenhouse experiment under a controlled environment. The alleles from the upland rice at this interval had positive effects on net photosynthetic rate, stomatal conductance, transpiration rate, quantum yield of photosystem II (PSII), and the maximum efficiency of light-adapted open PSII. However, the allele of another main QTL from upland rice was associated with increased drought sensitivity of photosynthesis. These results could potentially be used in breeding programmes through marker-assisted selection to improve drought tolerance and photosynthesis simultaneously

Modeling the impact of invasive species litter on conditions affecting its spread and potential regime shift

•Spatially explicit agent-based modeling aids in understanding invader success.•Invader litter suppression of native seedlings facilitates spread.•Earlier implementation of biocontrol dramatically improves its success.•Very strong invader litter suppression of native seedlings can cause regime shift.Many introduced plants pose invasion risks globally and threaten the biodiversity of native ecosystems. Such non-native plants can become invasive when they have advantages over native plants, such as having fewer natural enemies. Invasive plants often have the ability to alter ecosystem properties after they have become established, which can make it difficult to eliminate the invasive. In principle, this can cause a regime shift that may not be reversed through intense control efforts that increase mortality and reduce growth of the invasive species. Here we use spatially explicit agent-based modeling to simulate the invasion of an introduced tree species into a habitat occupied by a native species. The model describes an invasive tree with fast growth and high seed production and, in addition, produces litter that has a suppressive effect on native seedlings. These are properties, for example, shared by the invasive Melaleuca quinquenervia in southern Florida habitats. We use simulation modeling to test the following logical hypotheses: Partial suppression of native tree seedlings by the invasive tree's litter (1) will accelerate the spread of the invasive tree into native vegetation, (2) will impede efforts to control invasive spread through biocontrol, and (3) can cause a regime shift that is not reversed even if the biocontrol lowers invasive growth and reproduction to levels substantially lower than those of the native species. Additionally, (4) the earlier in the invasion biocontrol is introduced, the more effective it will be in reversing the invasion. The simulations support all four hypotheses. While these results highlight the potential for biocontrol of invasive tree species, our findings also suggest that successful elimination of positive litter feedbacks and invasive spread may critically depend on the timing of control efforts within the invasion process

Active Balancing of Reconfigurable Batteries Using Reinforcement Learning Algorithms

In reconfigurable batteries, series or parallel connections among cells/modules are able to be actively changed during operations. One big advantage of reconfiguration is to achieve active balancing among cells/modules. Rule-based and greedy algorithms of reconfigurable battery control have problems of being sensitive to battery characteristic variation and requiring a lot of computing resources. Therefore, deep reinforcement learning (DRL) algorithms are used to overcome these difficulties. Very few studies related to this idea have been done previously, and the studied battery reconfiguration topologies are either too simple or too complex. Thus, in this paper, a module-level reconfigurable battery with moderate flexibilities is controlled by DRL algorithms. Two neighboring modules are connected in either parallel or series by following a well-trained optimal policy. Two battery discharging cases, constant power and variable power, are simulated. The final results prove the feasibility and great potential of utilizing DRL algorithms in reconfigurable battery control

Width design for gobs and isolated coal pillars based on overall burst-instability prevention in coal mines

An investigation was conducted on the overall burst-instability of isolated coal pillars by means of the possibility index diagnosis method (PIDM). First, the abutment pressure calculation model of the gob in side direction was established to derive the abutment pressure distribution curve of the isolated coal pillar. Second, the overall burst-instability ratio of the isolated coal pillars was defined. Finally, the PIDM was utilized to judge the possibility of overall burst-instability and recoverability of isolated coal pillars. The results show that an overall burst-instability may occur due to a large gob width or a small pillar width. If the width of the isolated coal pillar is not large enough, the shallow coal seam will be damaged at first, and then the high abutment pressure will be transferred to the deep coal seam, which may cause an overall burst-instability accident. This approach can be adopted to design widths of gobs and isolated coal pillars and to evaluate whether an existing isolated coal pillar is recoverable in skip-mining mines