Sentiment analysis of video danmakus based on MIBE-RoBERTa-FF-BiLSTM.

Danmakus are user-generated comments that overlay on videos, enabling real-time interactions between viewers and video content. The emotional orientation of danmakus can reflect the attitudes and opinions of viewers on video segments, which can help video platforms optimize video content recommendation and evaluate users' abnormal emotion levels. Aiming at the problems of low transferability of traditional sentiment analysis methods in the danmaku domain, low accuracy of danmaku text segmentation, poor consistency of sentiment annotation, and insufficient semantic feature extraction, this paper proposes a video danmaku sentiment analysis method based on MIBE-RoBERTa-FF-BiLSTM. This paper constructs a "Bilibili Must-Watch List and Top Video Danmaku Sentiment Dataset" by ourselves, covering 10,000 positive and negative sentiment danmaku texts of 18 themes. A new word recognition algorithm based on mutual information (MI) and branch entropy (BE) is used to discover 2610 irregular network popular new words from trigrams to heptagrams in the dataset, forming a domain lexicon. The Maslow's hierarchy of needs theory is applied to guide the consistent sentiment annotation. The domain lexicon is integrated into the feature fusion layer of the RoBERTa-FF-BiLSTM model to fully learn the semantic features of word information, character information, and context information of danmaku texts and perform sentiment classification. Comparative experiments on the dataset show that the model proposed in this paper has the best comprehensive performance among the mainstream models for video danmaku text sentiment classification, with an F1 value of 94.06%, and its accuracy and robustness are also better than other models. The limitations of this paper are that the construction of the domain lexicon still requires manual participation and review, the semantic information of danmaku video content and the positive case preference are ignored.

Trends and driving forces of agricultural carbon emissions: A case study of Anhui, China.

To facilitate accurate prediction and empirical research on regional agricultural carbon emissions, this paper uses the LLE-PSO-XGBoost carbon emission model, which combines the Local Linear Embedding (LLE), Particle Swarm Algorithm (PSO) and Extreme Gradient Boosting Algorithm (XGBoost), to forecast regional agricultural carbon emissions in Anhui Province under different scenarios. The results show that the regional agricultural carbon emissions in Anhui Province generally show an upward and then downward trend during 2000-2021, and the regional agricultural carbon emissions in Anhui Province in 2030 are expected to fluctuate between 11,342,100 tones and 14,445,700 tones under five different set scenarios. The projections of regional agricultural carbon emissions can play an important role in supporting the development of local regional agriculture, helping to guide the input and policy guidance of local rural low-carbon agriculture and promoting the development of rural areas towards a resource-saving and environment-friendly society.

Relationship between Photosynthetic CO2 Assimilation and Chlorophyll Fluorescence for Winter Wheat under Water Stress.

Solar-induced chlorophyll fluorescence (SIF) has a high correlation with Gross Primary Production (GPP). However, studies focusing on the impact of drought on the SIF-GPP relationship have had mixed results at various scales, and the mechanisms controlling the dynamics between photosynthesis and fluorescence emission under water stress are not well understood. We developed a leaf-scale measurement system to perform concurrent measurements of active and passive fluorescence, and gas-exchange rates for winter wheat experiencing a one-month progressive drought. Our results confirmed that: (1) shifts in light energy allocation towards decreasing photochemistry (the quantum yields of photochemical quenching in PSII decreased from 0.42 to 0.21 under intermediate light conditions) and increasing fluorescence emissions (the quantum yields of fluorescence increased to 0.062 from 0.024) as drought progressed enhance the degree of nonlinearity of the SIF-GPP relationship, and (2) SIF alone has a limited capacity to track changes in the photosynthetic status of plants under drought conditions. However, by incorporating the water stress factor into a SIF-based mechanistic photosynthesis model, we show that drought-induced variations in a variety of key photosynthetic parameters, including stomatal conductance and photosynthetic CO2 assimilation, can be accurately estimated using measurements of SIF, photosynthetically active radiation, air temperature, and soil moisture as inputs. Our findings provide the experimental and theoretical foundations necessary for employing SIF mechanistically to estimate plant photosynthetic activity during periods of drought stress.

Photosynthetic base of reduced grain yield by shading stress during the early reproductive stage of two wheat cultivars.

The young microspore (YM) stage is the most sensitive period for wheat grain formation to abiotic stress. Shading stress during YM stage reduces grain yield mainly due to grain number decrease. However, the photosynthetic base for grain number decrease is still unclear. In this study, 100% (control), 40% (S1), and 10% (S2) of natural light were applied for 1, 3, 5, and 7 days (D1, D3, D5 and D7) during YM stage of two wheat cultivars (Henong825, Kenong9204). The results showed that grain number in Henong825 and Kenong9204 was reduced by - 3.6 to 33.3% and 14.2-72.7%, respectively. The leaf photosynthetic rate (Pn) in Henong825 and Kenong9204 was deducted by 4.5-93.9% and 26.4-99.0%. Under S1-D1, the leaf Pn of Henong825 reducing was mainly due to the reduction of light intensity. With shading intensity and duration increasing, the reasons for leaf Pn decrease were the low light intensity, the low Gs (stomatal conductance) and chlorophyll content, the damage of ultrastructure of chloroplast and photosynthetic system. Under S2-D7, the chlorophyll content, Fv/Fm (maximal photochemical efficiency of photosystem II) and Jmax (maximum electron transport) were reduced by 19.6%, 5.2% and 28.8% in Henong825, and by 29.9%, 7.8% and 33.1% in Kenong9204. After shading removal, the leaf Pn of Kenong9204 under D5 and D7 could not reach to the level of CK. This study indicated that the reduction of leaf Pn was mainly due to the low light intensity under short shading duration (shorter than 3 days), and due to low light intensity and damage of the leaf photosynthetic system under longer shading duration (longer than 5 days), especially for Kenong9204 (shade-sensitive cultivar).

Effects of Drought Stress on Pollen Sterility, Grain Yield, Abscisic Acid and Protective Enzymes in Two Winter Wheat Cultivars.

Drought stress induced pollen sterility is a detrimental factor reducing grain number in wheat. Exploring the mechanisms underlying pollen fertility under drought conditions could assist breeding high-yielding wheat cultivars with stress tolerance. Here, by using two Chinese wheat cultivars subjected to different levels of polyethylene glycol (PEG)-induced drought stress, possible links between pollen fertility and stress tolerance were analyzed under different levels of drought stress at the young microspore stage. In both cultivars, higher grain number reduction was observed under condition of lower water availability. Overall, the drought tolerant cultivar (Jinmai47) exhibited less grain number reduction than the drought sensitive cultivar (Shiluan02-1) under all stress conditions. Compared with Shiluan02-1, Jinmai47 exhibited superior physiological performance in terms of leaf photosynthetic rate, ear carbohydrate accumulation, pollen sink strength, pollen development and fertility under stress. Moreover, Jinmai47 showed a lower increase in endogenous abscisic acid in ears than Shiluan02-1. Furthermore, higher levels of superoxide dismutase (SOD) and peroxidase (POD) activities were also found in the drought tolerant cultivar Jinmai47 under PEG stress, compared with the drought sensitive cultivar Shiluan02-1. Changes in these physiological traits could contribute to better pollen development and male fertility, ultimately leading to the maintenance of grain number under drought stress.