The use of bioproducts, economically viable, are of extreme importance in the protection and stimulation of germination in vegetable crops. This work evaluated the effect of the microorganisms Azospirillum brasiliense, Bacillus sub-tilis, Trichoderma harzianum and the commercial seed treatment product (Fipronil + Pilaclostrobin and Methyl Thiophanate) on seeds and seedlings of lettuce (Lactuca sativa), carrot (Daucus carota) and tomato (Solanum lycopersicum). The seeds were inoculated before being submitted to the germination test. The chemical treatment proved ineffective in protecting the seed of all crops and stimulating germination. T. harzianum increased the germination index of lettuce seeds, had better values in root system size in tomato crop and stimulated radicle emission in carrot. B. subtilis stood out in dry matter accumulation in tomato crop. The microorganisms B. subtilis and T. harzianum present potential for vegetable seed treatment.

Eucalyptus is an important source of cellulose and a widely cultivated plant. Biotechnology tools can save time spent in breeding and transcriptomic approaches generate a gene profile that allows the identification of candidates involved in processes of interest. RNA-seq is a commonly used technology for transcript analysis and it provides an overview of regulatory pathways. Here, we selected two contrasting Eucalyptus species for cold acclimatization and focused in responsive genes under cold condition aiming woody properties – lignin and cellulose. The number of differentially expressed genes identified in stem sections were 3.300 in Eucalyptus globulus and 1370 in Eucalyptus urograndis. We listed genes with expression higher than 10 times including NAC, MYB and DUF family members. The GO analysis indicates increased oxidative process for E. urograndis. This data can provide information for more detailed analyses for breeding, especially in perennial plants.

Improving the competitiveness of tourism destinations is crucial for driving local economies and achieving income growth. In light of this evidence, numerous government departments strive to assess specific factors that impact the competitiveness of tourism destinations, enabling them to issue appropriate new tourism policies that promote more effective forms of tourism business. Therefore, the primary objective of this paper is to investigate how various elements such as tourism resources, tourism support, tourism management, location conditions, and tourism demand influence regional competitiveness in the Northern Bay region of Guangxi Province in China. To accomplish this goal, an online survey was conducted to collect data from 420 visitors who had experienced North Gulf Tourism; yielding an impressive response rate of 95 percent. The findings reveal that all aforementioned factors—namely: Tourism resources, tourism support, tourism management, location conditions and tourist demand—significantly impact destination competitiveness. Notably though, it was found that among these factors influencing destination competitiveness; it is primarily determined by effective local-level management (β = 0.345). Following closely behind are tourist demand (β = 0.133) as the second most influential factor affecting destination competitiveness; followed by location conditions (β = 0.116) ranking third; then comes tourist support (β = 0.03) as fourth in line impacting destination competitiveness; finally with least impact being exerted by available tourist resources (β = 0.016). Consequently, highlighting that regional competitiveness within Guangxi’s Northern Bay area predominantly hinges on efficient local-level management practices thus strongly recommending relevant authorities formulate novel work policies aimed at enhancing levels of local-level competitive advantage within the realm of regional touristic offerings.

Bangladesh’s coastal regions are rich in saline water resources. The majority of these resources are still not being used to their full potential. In the southern Bangladeshi region of Patuakhali, research was conducted to investigate the effects of mulching and drip irrigation on tomato yield, quality, and blossom-end rot (BER) at different soil salinity thresholds. There were four distinct treatments applied: T₁= drip irrigation with polythene mulch, T₂ = drip irrigation with straw mulch, T₃ = drip irrigation without mulch, and T₄ = standard procedure. While soil salinity was much greater in treatment T₃ (1.19–8.42 dS/m) fallowed by T₄ (1.23–8.63 dS/m), T1 treatments had the lowest level of salinity and the highest moisture retention during every development stage of the crops, ranging from 1.28–4.29 dS/m. Treatment T₃ exhibited the highest soil salinity levels (ranging from 1.19 to 8.42 dS/m), followed by T₄ with a range of 1.23 to 8.63 dS/m. In contrast, T₁ treatments consistently maintained the lowest salinity levels (ranging from 1.28 to 4.29 dS/m) and the highest moisture retention throughout all stages of crop development. In terms of yield, drip irrigation with no mulch treatment (T₃) provided the lowest output (13.37 t/ha), whereas polyethylene mulching treatment (T₁) produced the maximum yield (46.04 t/ha). According to the study, conserving moisture in tomato fields and reducing soil salinity may both be achieved with drip irrigation combined with polythene mulch. The research suggests that employing drip irrigation in conjunction with polythene mulch could effectively preserve moisture in tomato fields and concurrently decrease soil salinity.

Recognizing the discipline category of the abstract text is of great significance for automatic text recommendation and knowledge mining. Therefore, this study obtained the abstract text of social science and natural science in the Web of Science 2010-2020, and used the machine learning model SVM and deep learning model TextCNN and SCI-BERT models constructed a discipline classification model. It was found that the SCI-BERT model had the best performance. The precision, recall, and F1 were 86.54%, 86.89%, and 86.71%, respectively, and the F1 is 6.61% and 4.05% higher than SVM and TextCNN. The construction of this model can effectively identify the discipline categories of abstracts, and provide effective support for automatic indexing of subjects.

As the saying goes, "There are a thousand Hamlets for a thousand readers." Every child is a different individual, due to the differences in family environment, social relations, education and so on, personality, special skills, needs will also be different. Our garden adheres to the educational concept of "harmony but different harmonious coexistence", to create a warm, comfortable and appropriate educational environment, follow the children as the main body, inspire children to know themselves, adapt to the environment, gradually release their personality, promote the healthy and happy growth of children, get diversified experience, better integrate into the collective life.