Practicing and Managing Foreign Toponyms in China: Cultural Politics and Ideologies

This study examines the vogue of adopting foreign-origin place names in Chinese cities and the Chinese governments’ endeavors to regulate the toponymic landscape. The place naming practices, management, and public attitudes concerning foreign toponyms are analyzed to reveal the cultural politics and ideologies of place naming in China’s context. It is found that the foreign toponyms emplaced in urban space mostly have Western origins or roots, and their profusion is largely attributed to their associated symbolic capital, and the clientele’s taste and class identity. In the rectification process, Chinese governments at different levels constructed themselves as protectors of traditional Chinese culture and guards against xenophilia, thus enhancing their symbolic power and governing legitimacy. The general public has resisted top-down toponymic planning via acts of citizenship to reclaim the rights of naming and owning public space. Our findings suggest that nowadays, even in highly regulated societies like China, it would be hard to achieve the expected planning goals when governments simply resort to hegemonic power to implement the place (re)naming policies

Joint Power and Multiple Access Control for Wireless Mesh Network with Rose Projection Method

This paper investigates the utility maximization problem for the downlink of the multi-interface multichannel wireless mesh network with orthogonal frequency division multiple access. A cross-layer joint power and multiple access control algorithm are proposed. Rosen projection matrix is combined with Solodov projection techniques to build a three-memory gradient Rosen projection method, which is applied to solve this optimization problem. The convergence analysis is given and simulations show that the proposed solution achieves significant throughput compared with existing approaches

Characterization of CDOM in saline and freshwater lakes across China using spectroscopic analysis

Colored dissolved organic matter (CDOM) is a major component of DOM in waters, and plays a vital role in carbon cycling in inland waters. In this study, the light absorption and three-dimensional excitation-emission matrix spectra (EEMs) of CDOM of 936 water samples collected in 2014–2017 from 234 lakes in five regions across China were examined to determine relationships between lake water sources (fresh versus saline) and their fluorescence/absorption characteristics. Results indicated significant differences regarding DOC concentration and aCDOM(254) between freshwater (6.68 mg C L−1, 19.55 m-1) and saline lakes (27.4 mg C L−1, 41.17 m-1). While humic-like (F5) and fulvic-like (F3) compounds contributed to CDOM fluorescence in all lake waters significantly, their contribution to total fluorescence intensity (FT) differed between saline and freshwater lakes. Significant negative relationships were also observed between lake altitude with either F5 (R2 = 0.63, N = 306) or FT (R2 = 0.64, N = 306), suggesting that the abundance of humic-like materials in CDOM tends to decrease with increased in lakes altitude. In high-altitude lakes, strong solar irradiance and UV exposure may have induced photo-oxidation reactions resulting in decreased abundance of humic-like substances and the formation of low molecular weight compounds. These findings have important implications regarding our understanding of C dynamics in lacustrine systems and the contribution of these ecosystems to the global C cycle

Dissolved carbon in a large variety of lakes across five limnetic regions in China

Dissolved carbon in lakes play a vital role in the global carbon cycling. The concentration and dynamics of lake dissolved carbon can be influenced by both the surrounding landscape and a combination of physical, chemical and biological processes within the lakes themselves. From 2009 to 2016, we conducted a large-scale assessment of dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) in 249 lakes across a diverse range of climatic, geopedologic, topographical and hydrological conditions in five Chinese limnetic regions: the East Limnetic Region (ELR), the Northeast Limnetic Region (NLR), the Inner Mongolia-Xinjiang Limnetic Region (MXR), the Yungui Limnetic Region (YGR), and the Tibet-Qinghai Limnetic Region (TQR). We found that the density of the organic matter in the soil in the surrounding landscape plays an important role in the DOC and DIC in lake water, as was evidenced by the high DOC and DIC levels in the NLR, where the soil is respectively organically rich. Conditions in the arid and semi-arid environments (i.e. TQR and MXR) have created a number of brackish/saline lakes and here we found that, DOC and DIC levels (median: 21.79 and 93.72 mg/L, respectively) are significantly higher than those in the freshwater lakes (median: 5.80 and 29.38 mg/L). It also appears to be the case that the trophic state of freshwater lakes influences the spatial variation of DOC. This can be seen in the relationships between DOC and trophic state index (TSI) in agriculturally-dominated regions such as the ELR (R2 = 0.59, p < 0.01), NLR (R2 = 0.65, p < 0.001), and YGR (R2 = 0.78, p < 0.001). Additionally, a close relationship between DOC and DIC can be found in lake waters with different trophic states (eutrophic: slp = 0.63, R2= 0.69; mesotrophic: slp = 1.03, R2 = 0.65; oligotrophic: slp = 1.00, R2 = 0.64). This indicates that human activities influence the quantity and quality of dissolved carbon in inland water across China. This study is able to provide insights regarding the potential effects of climate change and changes in land-use upon the amount of dissolved carbon in lake water

Progress on Research and Application of New Non-destructive Testing Techniques in Tomato Quality Inspection

Tomatoes are one of the most widely cultivated vegetables in China and are popular among consumers. In recent years, as the demand for healthy food has grown, the quality of tomatoes has aroused increasing attention. While tomatoes are generally uniform in shape, there are significant differences in size, fruit type and color among tomato varieties, and tomatoes contain a variety of nutrients with complex chemical structures, so its quality is difficult to assess. The traditional tomato quality testing methods are subjective, destructive, time-consuming and laborious, and thus cannot meet the demand of large-scale quality testing. Recently, with the development of non-destructive testing technologies, new detection methods such as machine learning, multispectral techniques, and electronic nose/electronic tongue have been developed and applied for the rapid and non-destructive testing of tomato quality. This paper provides a summary of the development and application of artificial intelligence based on image recognition, electronic nose technology and spectroscopic technologies for the non-destructive testing of tomatoes in order to provide a reference for future research and development of tomato quality inspection

Evaluation of the immune feature of ACPA-negative rheumatoid arthritis and the clinical value of matrix metalloproteinase-3

Anti-citrullinated protein antibodies (ACPAs) are highly specific for the diagnosis of rheumatoid arthritis (RA). However, about one-third of RA patients are negative for ACPAs, which presents a challenge to the early diagnosis of RA. The purpose of this study was to analyze differences in lymphocyte subsets and CD4+ T cell subsets between ACPA+ and ACPA- RA patients, and to evaluate the value of matrix metalloproteinase-3 (MMP-3) as a diagnostic and monitoring marker in ACA- RA patients. A total of 145 ACPA+ RA patients, 145 ACPA- RA patients, and 38 healthy controls (HCs) were included in this study. Peripheral lymphocyte subsets were detected using flow cytometry, and serum MMP-3 was detected using chemiluminescence. Information about joint symptoms, other organ involvement, and related inflammatory markers was also collected. The results showed that, compared to ACPA- RA patients, ACPA+ cases had greater imbalances between peripheral CD4+ T cell subsets, mainly manifested as an increase in T-helper 1 (Th1) cells (p &lt; 0.001) and decrease in regulatory T (Treg) cells (p = 0.029). This makes these patients more prone to inflammatory reactions and joint erosion. MMP-3 levels in ACPA+ and ACPA- RA patients were significantly higher than in HCs (p &lt; 0.001), and MMP-3 could effectively distinguish between ACPA- RA patients and HCs (area under the curve [AUC] = 0.930, sensitivity 84.14%, specificity 92.11%). MMP-3 was also a serum marker for distinguishing between RA patients with low and high disease activities. Further analysis showed that MMP-3 was positively correlated with the levels of inflammatory markers and disease activity, and negatively correlated with the levels of lymphocyte subsets. In addition, with improvements in the disease, MMP-3 levels decreased, and further increased as the patients started to deteriorate. In summary, our research showed that there was a mild imbalance between peripheral CD4+ T cell subsets in ACPA- RA patients. MMP-3 may be used as a potential marker for early diagnosis of ACPA- RA. MMP-3 was an important index for RA disease evaluation, disease activity stratification, and prognosis

Logging Practices with Mobile Analytics: An Empirical Study on Firebase

Software logs are of great value in both industrial and open-source projects. Mobile analytics logging enables developers to collect logs remotely from their apps running on end user devices at the cost of recording and transmitting logs across the Internet to a centralised infrastructure.This paper makes a first step in characterising logging practices with a widely adopted mobile analytics logging library, namely Firebase Analytics. We provide an empirical evaluation of the use of Firebase Analytics in 57 open-source Android applications by studying the evolution of code-bases to understand: a) the needs-in-common that push practitioners to adopt logging practices on mobile devices, and b) the differences in the ways developers use local and remote logging.Our results indicate mobile analytics logs are less pervasive and less maintained than traditional logging code. Based on our analysis, we believe logging using mobile analytics is more user centered compared to traditional logging, where the latter is mainly used to record information for debugging purposes

Physical Characterization and Volatile Organic Compound Monitoring of Recycled Polyethylene Terephthalate under Mechanical Recycling

In this study, physical characterization and monitoring of volatile organic compounds (VOCs) were investigated on recycled polyethylene terephthalate (rPET) from a mechanical recycling process and rPET bottles made with different rPET contents, with the aim of tracing the source of rPET and assessing its safety when use as a food contact material. It was found that rPET had a similar thermal stability to that of virgin PET (vPET). rPET bottles did not show any significant changes in groups or structure and exhibit similar crystallization and melting behaviors to vPET. However, there were minor mechanical scratches in the surface micromorphology of rPET bottles, and the color of rPET bottles became darker, greener and yellower as the content of recycled material increased. The solid-state polycondensation process was found to play an important role in the removal of VOCs, as detected by headspace gas chromatography-mass spectrometry (HS-GC-MS), resulting in a very small amount of residual VOCs in rPET. Four VOCs (acetaldehyde, glycol and nonanal at levels less than 1.00 mg/kg; 2-methyl-1,3 dioxolane at levels of 1.72-5.76 mg/kg) were detected in the rPET bottles. This study shows that rPET bottles are qualified for reuse in food contact in terms of thermal properties, structure, morphology and VOC residues, although there is variability in color

Variations in the light absorption coefficients of phytoplankton, non-algal particles and dissolved organic matter in reservoirs across China

Reservoirs were critical sources of drinking water for many large cities around the world, but progress in the development of large-scale monitoring protocols to obtain timely information about water quality had been hampered by the complex nature of inland waters and the various optical conditions exhibited by these aquatic ecosystems. In this study, we systematically investigated the absorption coefficient of different optically-active constituents (OACs) in 120 reservoirs of different trophic states across five eco-regions in China. The relationships were found between phytoplankton absorption coefficient at 675 nm (aph (675)) and Chlorophyll a (Chla) concentration in different regions (R2:0.60-0.82). The non-algal particle (NAP) absorption coefficient (aNAP) showed an increasing trend for reservoirs with trophic states. Significant correlation (p < 0.05) was observed between chromophoric dissolved organic matter (CDOM) absorption and water chemical parameters. The influencing factors for contributing the relative proportion of OACs absorption including the hydrological factors and water quality factors were analyzed. The non-water absorption budget from our data showed the variations of the dominant absorption types which underscored the need to develop and parameterize region-specific bio-optical models for large-scale assessment in water reservoirs

Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning

We present CM3Leon (pronounced "Chameleon"), a retrieval-augmented, token-based, decoder-only multi-modal language model capable of generating and infilling both text and images. CM3Leon uses the CM3 multi-modal architecture but additionally shows the extreme benefits of scaling up and tuning on more diverse instruction-style data. It is the first multi-modal model trained with a recipe adapted from text-only language models, including a large-scale retrieval-augmented pre-training stage and a second multi-task supervised fine-tuning (SFT) stage. It is also a general-purpose model that can do both text-to-image and image-to-text generation, allowing us to introduce self-contained contrastive decoding methods that produce high-quality outputs. Extensive experiments demonstrate that this recipe is highly effective for multi-modal models. CM3Leon achieves state-of-the-art performance in text-to-image generation with 5x less training compute than comparable methods (zero-shot MS-COCO FID of 4.88). After SFT, CM3Leon can also demonstrate unprecedented levels of controllability in tasks ranging from language-guided image editing to image-controlled generation and segmentation