Long Narrative Songs from the Mongghul of Northeast Tibet: Texts in Mongghul, Chinese, and English

Containing ballads of martial heroism, tales of tragic lovers and visions of the nature of the world, Long Narrative Songs from the Mongghul of Northeast Tibet: Texts in Mongghul, Chinese, and English is a rich repository of songs collected amongst the Mongghul of the Seven Valleys, on the northeast Tibetan Plateau in western China. These songs represent the apogee of Mongghul oral literature, and they provide valuable insights into the lives of Mongghul people—their hopes, dreams, and worries. They bear testimony to the impressive plurilingual repertoire commanded by some Mongghul singers: the original texts in Tibetan, Mongghul, and Chinese are here presented in Mongghul, Chinese, and English. The kaleidoscope of stories told in these songs include that of Marshall Qi, a chieftain from the Seven Valleys who travels to Luoyang with his Mongghul army to battle rebels; Laarimbu and Qiimunso, a pair of star-crossed lovers who take revenge from beyond the grave on the families that kept them apart; and the Crop-Planting Song and the Sheep Song, which map the physical and spiritual terrain of the Mongghul people, vividly describing the physical and cosmological world in which they exist. This collection of songs is supported by an Introduction by Gerald Roche that provides an understanding of their traditional context, and shows that these works offer insights into the practices of multilingualism in Tibet. Long Narrative Songs from the Mongghul of Northeast Tibet is vital reading for researchers and others working on oral literature, as well as those who study Inner Asia, Tibet, and China’s ethnic minorities. Finally, this book is of interest to linguistic anthropologists and sociolinguists, particularly those working on small-scale multilingualism and pre-colonial multilingualism

The impact mechanism of China’s carbon emission trading policy on industrial energy efficiency under multiple innovation approaches

Under the “dual carbon” background, carbon emission trading policy, as an important means of environmental regulation for energy conservation, emission reduction and green development, has a very important impact on energy efficiency. We take China’s pilot carbon trading policy, which began in 2013, as an example, and the energy efficiency of industrial enterprises from 2008 to 2019 as a study sample. In this paper, the single factor industrial energy efficiency (ISE) and the green total factor industrial energy efficiency (IGTE) in China are both included in the influence category of carbon emission trading. The SUPER-EBM method is used to measure IGTE. The direct effects of carbon emission trading policy on the two types of industrial energy efficiency are investigated by Difference-in-difference model combined with stepwise regression method. The dynamic effects are studied by event study method. In order to verify how the “Porter effect” plays a role in this process, this paper examines the influence paths of five important innovation-related intermediate mechanisms. The study find that after a series of robustness tests, such as parallel trend test, placebo test, changing the time window frame and adding control variables, carbon emission trading policy significantly improved the two energy efficiency. The effect of carbon trading policy gradually increased and reached its maximum in the fifth year, but then began to decline. Under multiple innovation approaches, innovation environment level and innovation protection intensity can significantly improve the two energy efficiency. Green innovation intensity and breakthrough innovation intensity improved ISE. The overall level of enterprise innovation improved IGTE. Heterogeneity analysis shows that carbon trading policy has a greater impact on the eastern region, but a smaller impact on the central and western regions. This paper provides differentiated policy inspiration for the overall promotion of China’s national carbon market in the future

Study on the Problems of Specialty Adjustment in Local Universities Under China’s New Normal

In China, the specialty adjustment of the local universities is short of dynamic mechanism and scientificity, which, at present, is one of the most ubiquitous problems among the universities. Particularly, as China’s economy enters into the new normal, what Chinese universities shall jointly deal with at the moment is how to adjust specialty scientifically and effectively according to the current economic changes and exposed problems. Against the background of China’s new normal, combined with the present economic situations and market demands, the local universities shall start from their own problems and find out ways of adjusting specialties scientifically and then put forward some countermeasures and suggestions to promote a higher and more sustainable development

CCL3 and CCL20-recruited dendritic cells modified by melanoma antigen gene-1 induce anti-tumor immunity against gastric cancer ex vivo and in vivo

<p>Abstract</p> <p>Background</p> <p>To investigate whether dendritic cell (DC) precursors, recruited by injection of <b>chemokine ligand 3 (CCL3) and CCL20</b>, induce anti-tumor immunity against gastric cancer induced by a DC vaccine expressing melanoma antigen gene-1 (MAGE-1) ex vivo and in vivo.</p> <p>Methods</p> <p>B6 mice were injected with CCL3 and CCL20 via the tail vein. Freshly isolated F4/80^-B220^-CD11c⁺cells cultured with cytokines were analyzed by phenotype analysis and mixed lymphocyte reaction (MLR). For adenoviral (Ad)-mediated gene transduction, cultured F4/80^-B220^-CD11c⁺cells were incubated with Ad-MAGE-1. Vaccination of stimulated DC induced T lymphocytes. The killing effect of these T cells against gastric carcinoma cells was assayed by MTT. INF-γ production was determined with an INF-γ ELISA kit. In the solid tumor and metastases model, DC-based vaccines were used for immunization after challenge with MFC cells. <b>Tumor size, survival of mice, and number of pulmonary metastatic foci were used to assess the therapeutic effect of DC vaccines</b>.</p> <p>Results</p> <p>F4/80^-B220^-CD11c⁺cell numbers increased after <b>CCL3 and CCL20 </b>injection. Freshly isolated F4/80^-B220^-CD11c⁺cells cultured with cytokines were phenotyically identical to typical DC and gained the capacity to stimulate allogeneic T cells. These DCs were transduced with Ad-MAGE-1, which were prepared for DC vaccines expressing tumor antigen. T lymphocytes stimulated by DCs transduced with Ad-MAGE-1 exhibited specific killing effects on gastric carcinoma cells and produced high levels of INF-γ ex vivo. In vivo, tumor sizes of the experimental group were much smaller than both the positive control group and the negative control groups (<it>P </it>< 0.05). Kaplan-Meier survival curves showed that survival of the experimental group mice was significantly longer than the control groups (<it>P </it>< 0.05). In addition, MAGE-1-transduced DCs were also a therapeutic benefit on an established metastatic tumor, resulting in a tremendous decrease in the number of pulmonary metastatic foci.</p> <p>Conclusions</p> <p><b>CCL3 and CCL20</b>-recruited DCs modified by adenovirus-trasnsduced, tumor-associated antigen, MAGE-1, can stimulate anti-tumor immunity specific to gastric cancer ex vivo and in vivo. This system may prove to be an efficient strategy for anti-tumor immunotherapy.</p

The Fulaan Bulog 'Red Springs' and the Mongol presence in the Huzhu Tu (Mongghul) area, Qinghai Province, PR China

Peer reviewe

Joint Association of Dietary Pattern and Physical Activity Level with Cardiovascular Disease Risk Factors among Chinese Men: A Cross-Sectional Study

The purpose of this cross-sectional study was to investigate the joint associations of physical activity level (PAL) and dietary patterns in relation to cardiovascular disease (CVD) risk factors among Chinese men. The study population consisted of 13 511 Chinese males aged 18–59 years from the 2002 China National Nutrition and Health Survey. Based on dietary data collected by a food frequency questionnaire, four dietary patterns were identified and labeled as “Green Water” (high consumption of rice, vegetables, seafood, pork, and poultry), “Yellow Earth” (high consumption of wheat flour products and starchy tubers), “New Affluent” (high consumption of animal sourced foods and soybean products), and “Western Adopter” (high consumption of animal sourced foods, cakes, and soft drinks). From the information collected by a 1-year physical activity questionnaire, PAL was calculated and classified into 4 categories: sedentary, low active, active, and very active. As compared with their counterparts from the New Affluent pattern, participants who followed the Green Water pattern had a lower likelihood of abdominal obesity (AO; 50.2%), hypertension (HT; 37.9%), hyperglycemia (HG; 41.5%), elevated triglyceride (ETG; 14.5%), low HDL (LHDL; 39.8%), and metabolic syndrome (MS; 51.9%). When compared to sedentary participants, the odds ratio of participants with very active PAL was 0.62 for AO, 0.85 for HT, 0.71 for HG, 0.76 for ETG, 0.74 for LHDL, and 0.58 for MS. Individuals who followed both very active PAL and the Green Water pattern had a lower likelihood of CVD risk factors (AO: 65.8%, HT: 39.1%, HG: 57.4%, ETG: 35.4%, LHDL: 56.1%, and MS: 75.0%), compared to their counterparts who followed both sedentary PAL and the New Affluent pattern. In addition, adherence to both healthy dietary pattern and very active PAL presented a remarkable potential for CVD risk factor prevention

SoybeanNet: Transformer-Based Convolutional Neural Network for Soybean Pod Counting from Unmanned Aerial Vehicle (UAV) Images

Soybeans are a critical source of food, protein and oil, and thus have received extensive research aimed at enhancing their yield, refining cultivation practices, and advancing soybean breeding techniques. Within this context, soybean pod counting plays an essential role in understanding and optimizing production. Despite recent advancements, the development of a robust pod-counting algorithm capable of performing effectively in real-field conditions remains a significant challenge This paper presents a pioneering work of accurate soybean pod counting utilizing unmanned aerial vehicle (UAV) images captured from actual soybean fields in Michigan, USA. Specifically, this paper presents SoybeanNet, a novel point-based counting network that harnesses powerful transformer backbones for simultaneous soybean pod counting and localization with high accuracy. In addition, a new dataset of UAV-acquired images for soybean pod counting was created and open-sourced, consisting of 113 drone images with more than 260k manually annotated soybean pods captured under natural lighting conditions. Through comprehensive evaluations, SoybeanNet demonstrated superior performance over five state-of-the-art approaches when tested on the collected images. Remarkably, SoybeanNet achieved a counting accuracy of $84.51\%$ when tested on the testing dataset, attesting to its efficacy in real-world scenarios. The publication also provides both the source code (\url{https://github.com/JiajiaLi04/Soybean-Pod-Counting-from-UAV-Images}) and the labeled soybean dataset (\url{https://www.kaggle.com/datasets/jiajiali/uav-based-soybean-pod-images}), offering a valuable resource for future research endeavors in soybean pod counting and related fields.Comment: 12 pages, 5 figure

Causal connectivity abnormalities of regional homogeneity in children with attention deficit hyperactivity disorder: a rest-state fMRI study

The present study aimed to investigate individual differences of causal connectivity between brain regions in attention deficit hyperactivity disorder (ADHD) which was a psychiatric disorder. Resting-state functional magnetic resonance imaging (R-fMRI) data of typically-developing controls (TDC) children group and combined ADHD (ADHD-C) children group were distinguished by the support vector machine (SVM) with linear kernel function, based on regional homogeneity (ReHo), amplitude of low frequency fluctuation (ALFF) and fractional ALFF (FALFF). The highest classification accuracy yielded by ReHo was 90.91 %. Furthermore, the granger causality analysis (GCA) method based on the classified weight map of regions of interesting (ROIs) showed that five causal flows existed significant difference between TDC and ADHD-C. That is, the averaged GCA values of three causal connections (i.e. left VLPFC left CC1, right PoCG left CC1, and right PoCG right CC2) for ADHD-C were separately stronger than those for TDC. And the other two connections (i.e. right FEF right SOG and right CC1 right SOG) were weaker for ADHD-C than those for TDC. In addition, only two causality flows (i.e. left VLPFC left CC1 and right PoCG right CC2) presented that their GCA values were positively correlation with ADHD index scores, respectively. Our findings revealed that ADHD children represented widespread abnormalities in the causality connectivity, especially involved in the attention and memory related regions. And further provided evidence that the potential neural causality flows could play a key role in characterizing individual’s ADHD