Mandarin's Impact on Poverty Alleviation: An Empirical Study Based on Economic and Social Interaction Dimensions

This paper studies the effect of Mandarin proficiency on poverty reduction and its mechanism. The China General Social Survey (CGSS) is taken as the data source. From the perspective of social integration, the poverty reduction effect of Putonghua and its mechanism are empirically studied from the perspective of social interaction, social fairness, and social trust. The findings showed that improving the ability to listen and speak Mandarin positively affects social interaction, social trust, and social fairness. It showed that Putonghua proficiency positively correlates with the suppression of economic poverty. After the occurrence of poverty, whether a sample of absolute poverty or relative poverty, the ability to listen and speak in Mandarin has a specific inhibitory effect on social interaction, social trust, and social fairness. After the occurrence of poverty, the frequency of social interaction, social trust, and social public since have been reduced to a certain extent. Specifically, the ability to express Mandarin has shown remarkable results in improving social interaction, and the ability to listen among ordinary people has shown remarkable results in enhancing social fairness. The results of this paper provide empirical evidence of poverty alleviation in China via Improving Mandarin Proficiency. This research is also of great significance for optimizing poverty alleviation paths through language in the post-poverty alleviation era

The Effect of Physical Activity on the Non-cognitive Ability of Adolescents: An Empirical Study on Big Five Personality Traits and Large Sample Data of CFPS 2020

Based on the Big Five personality trait dimensions of non-cognitive ability measures, the CFPS 2020 database was used as the basis, The self-answered questionnaires and messages were collected from the people under the age of 18. And information on physical activity were selected as the study sample from the total 28590 samples in this database, among which 1562 valid samples were used as the study subjects. And the corresponding options and answers were selected as the dependent variables related to the Big Five personality like responsibility, agreeableness, extraversion, and neuroticism. After constructing a model with logit regression and calculating the marginal effects, it empirically demonstrated that increasing the frequency of physical exercises (frequency) had positive effects on promoting or improving adolescents' sense of responsibility, agreeableness, extraversion, and neuroticism, the frequency of physical exercise (frequency) in the past 12 months was used as the dependent variable, the effects were different between urban and rural areas, age, and gender. There were differences between urban and rural areas, age and gender

Occlusion Robust Wheat Ear Counting Algorithm Based on Deep Learning

Counting the number of wheat ears in images under natural light is an important way to evaluate the crop yield, thus, it is of great significance to modern intelligent agriculture. However, the distribution of wheat ears is dense, so the occlusion and overlap problem appears in almost every wheat image. It is difficult for traditional image processing methods to solve occlusion problem due to the deficiency of high-level semantic features, while existing deep learning based counting methods did not solve the occlusion efficiently. This article proposes an improved EfficientDet-D0 object detection model for wheat ear counting, and focuses on solving occlusion. First, the transfer learning method is employed in the pre-training of the model backbone network to extract the high-level semantic features of wheat ears. Secondly, an image augmentation method Random-Cutout is proposed, in which some rectangles are selected and erased according to the number and size of the wheat ears in the images to simulate occlusion in real wheat images. Finally, convolutional block attention module (CBAM) is adopted into the EfficientDet-D0 model after the backbone, which makes the model refine the features, pay more attention to the wheat ears and suppress other useless background information. Extensive experiments are done by feeding the features to detection layer, showing that the counting accuracy of the improved EfficientDet-D0 model reaches 94%, which is about 2% higher than the original model, and false detection rate is 5.8%, which is the lowest among comparative methods

Characteristics of cadmium accumulation and tolerance in apple plants grown in different soils

Cadmium (Cd) is a nonessential element and highly toxic to apple tree. However, Cd accumulation, translocation and tolerance in apple trees planted in different soils remain unknown. To investigate soil Cd bioavailability, plant Cd accumulation, physiological changes as well as gene expression patterns in apple trees grown in five different soils, ‘Hanfu’ apple seedlings were planted in orchard soils collected from Maliangou village (ML), Desheng village (DS), Xishan village (XS), Kaoshantun village (KS) and Qianertaizi village (QT), and subjected to 500 μM CdCl2 for 70 d. Results showed that soils of ML and XS had higher content of organic matter (OM), clay and silt, and cation exchange capacity (CEC) but lower sand content than the other soils, thereby reduced Cd bioavailability, which could be reflected by lower concentrations and proportions of acid-soluble Cd but higher concentrations and proportions of reducible and oxidizable Cd. The plants grown in soils of ML and XS had relatively lower Cd accumulation levels and bio-concentration factors than those grown in the other soils. Excess Cd reduced plant biomass, root architecture, and chlorophyll content in all plants but to relatively lesser degree in those grown in soils of ML and XS. The plants grown in soils of ML, XS and QT had comparatively lower reactive oxygen species (ROS) content, less membrane lipid peroxidation, and higher antioxidant content and enzyme activity than those grown in soils of DS and KS. Transcript levels of genes regulating Cd uptake, transport and detoxification such as HA11, VHA4, ZIP6, IRT1, NAS1, MT2, MHX, MTP1, ABCC1, HMA4 and PCR2 displayed significant differences in roots of plants grown in different soils. These results indicate that soil types affect Cd accumulation and tolerance in apple plants, and plants grown in soils with higher OM content, CEC, clay and silt content and lower sand content suffer less Cd toxicity

First detection of small hive beetle Aethina tumida Murray (Coleoptera: Nitidulidae) infesting eastern honeybee, Apis cerana Fabricius (Hymenoptera: Apidae), in China

We report the infestation of small hive beetle, Aethina tumida, in a honeybee, Apis cerana, in South China. This is the first record for domestic Chinese honey bee infested with small hive beetle

Arbitrary Few Parameters are Good Enough for Adapting Large-scale Pre-trained Language Models

Parameter-efficient tuning (PET) methods can effectively drive extremely large pre-trained language models (PLMs) by only training minimal parameters. Different PET methods utilize different manually designed modules. In a small PLM, there are usually noticeable performance differences among PET methods. Nevertheless, when a PLM's scale grows up to tens of billions of parameters, all PET methods achieve almost the same performance and even perform on par with the full-parameter fine-tuning method. Hence, we hypothesize that model scaling can mitigate the design differences (the module structures and the number of trainable parameters) among PET methods. To study this hypothesis, we introduce a more flexible PET method - arbitrary PET (APET) method - to be compatible with arbitrary module structures and any number of trainable parameters. Then, we experiment on $11$ NLP tasks of $5$ types and $2$ representative PLMs. From our investigations, we find that the model scaling (1) mitigates the effects of the arbitrary module structure on the performance of tuning methods, and (2) enables the tuning methods to optimize fewer parameters to achieve the full-parameter fine-tuning performance. Intriguingly, we also observe that all tuning methods require almost the same number of trainable parameters to drive PLMs. We discuss this phenomenon and the above two findings collectively from optimization perspectives to fathom the mechanisms behind them. These conclusions not only demonstrate the positive impact of model scaling on tuning methods but disclose its mechanisms, which help us design more effective and efficient tuning methods on larger-scale PLMs

Language-Specific Representation of Emotion-Concept Knowledge Causally Supports Emotion Inference

Understanding how language supports emotion inference remains a topic of debate in emotion science. The present study investigated whether language-derived emotion-concept knowledge would causally support emotion inference by manipulating the language-specific knowledge representations in large language models. Using the prompt technique, 14 attributes of emotion concepts were found to be represented by distinct artificial neuron populations. By manipulating these attribute-related neurons, the majority of the emotion inference tasks showed performance deterioration compared to random manipulations. The attribute-specific performance deterioration was related to the importance of different attributes in human mental space. Our findings provide causal evidence in support of a language-based mechanism for emotion inference and highlight the contributions of emotion-concept knowledge.Comment: 39 pages, 13 figures, 2 tables, fix formatting error

Memory-enhancing effect of Rhodiola rosea L extract on aged mice

Purpose: The memory-enhancing effects of Rhodiola rosea L. extract (RRLE) on normal aged mice were assessed.Methods: In the open-field test, the effect of RRLE (150 and 300 mg/kg) on mouse locomotive activities was evaluated by investigating the extract’s influence on CAT and AchE activities in the brain tissue of mice.Results: Compared with aged group, high dose of RRLE reduced the total distance (3212.4 ± 123.1 cm, p < 0.05) significantly, increased catalase (CAT) activity (101.4 ± 12.2 U/mg pro, p < 0.05), and inhibited acetyl cholinesterase (AChE) activity (0.94 ± 0.12 U/mg pro, p < 0.05) in the brain tissue of aged mice.Conclusion: The results show that RRLE improves the memory functions of aged mice probably by increasing CAT activity while decreasing AChE activity.Keywords: Rhodiola rosea, Memory function, Catalase, Acetyl cholinesterase, Open-field tes

Naja naja atra

Systemic lupus erythematosus (SLE) is an autoimmune disease and effective therapy for this pathology is currently unavailable. We previously reported that oral administration of Naja naja atra venom (NNAV) had anti-inflammatory and immune regulatory actions. We speculated that NNAV may have therapeutic effects in MRL/lpr SLE mice. Twelve-week-old MRL/lpr mice received oral administration of NNAV (20, 40, and 80 μg/kg) or Tripterygium wilfordii polyglycosidium (10 mg/kg) daily for 16 weeks. The effects of NNAV on SLE manifestations, including skin erythema, proteinuria, and anxiety-like behaviors, were assessed with visual inspection and Multistix 8 SG strips and open field test, respectively. The pathology of spleen and kidney was examined with H&E staining. The changes in autoimmune antibodies and cytokines were determined with ELISA kits. The results showed that NNAV protected against the manifestation of SLE, including skin erythema and proteinuria. In addition, although no apparent histological change was found in liver and heart in MRL/lpr SLE mice, NNAV reduced the levels of glutamate pyruvate transaminase and creatine kinase. Furthermore, NNAV increased serum C3 and reduced concentrations of circulating globulin, anti-dsDNA antibody, and inflammatory cytokines IL-6 and TNF-α. NNAV also reduced lymphadenopathy and renal injury. These results suggest that NNAV may have therapeutic values in the treatment of SLE by inhibiting autoimmune responses