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Large Language Models (LLMs) such as ChatGPT possess advanced capabilities in understanding and generating text. These capabilities enable ChatGPT to create text based on specific instructions, which can serve as augmented data for text classification tasks. Previous studies have approached data augmentation (DA) by either rewriting the existing dataset with ChatGPT or generating entirely new data from scratch. However, it is unclear which method is better without comparing their effectiveness. This study investigates the application of both methods to two datasets: a general-topic dataset (Reuters news data) and a domain-specific dataset (Mitigation dataset). Our findings indicate that: 1. ChatGPT generated new data consistently enhanced model's classification results for both datasets. 2. Generating new data generally outperforms rewriting existing data, though crafting the prompts carefully is crucial to extract the most valuable information from ChatGPT, particularly for domain-specific data. 3. The augmentation data size affects the effectiveness of DA; however, we observed a plateau after incorporating 10 samples. 4. Combining the rewritten sample with new generated sample can potentially further improve the model's performance. [ABSTRACT FROM AUTHOR]

Safflower (Carthamus tinctorius L.) is a multipurpose minor crop consumed by developed and developing nations around the world with limited research funding and genetic resources. Genomic selection (GS) is an effective modern breeding tool that can help to fast-track the genetic diversity preserved in genebank collections to facilitate rapid and efficient germplasm improvement and variety development. In the present study, we simulated four GS strategies to compare genetic gains and inbreeding during breeding cycles in a safflower recurrent selection breeding program targeting grain yield (GY) and seed oil content (OL). We observed positive genetic gains over cycles in all four GS strategies, where the first cycle delivered the largest genetic gain. Single-trait GS strategies had the greatest gain for the target trait but had very limited genetic improvement for the other trait. Simultaneous selection for GY and OL via indices indicated higher gains for both traits than crossing between the two single-trait independent culling strategies. The multi-trait GS strategy with mating relationship control (GS_GY + OL + Rel) resulted in a lower inbreeding coefficeint but a similar gain compared to that of the GS_GY + OL (without inbreeding control) strategy after a few cycles. Our findings lay the foundation for future safflower GS breeding. [ABSTRACT FROM AUTHOR]

Larix principis-rupprechtii Mayr, a coniferous species indigenous to Northern China, possesses significant ecological and economic value. Somatic embryogenesis offers a pathway with significant potential for large-scale propagation, long-term germplasm conservation, and genetic transformation in L. principis-rupprechtii Mayr. However, it remains unclear whether significant variations occur in embryogenic tissues during long-term successive subculturing, which could impact the productivity of somatic embryos. This is a pivotal concern that lacks comprehensive understanding. In this study, three embryogenic cell lines were used to explore the dynamics and relationships among proliferation rate, pre-treatment proliferation rate, and embryogenic capabilities across a series of 32 subculturing cycles. Proliferation rate, pre-treatment proliferation rate, and somatic embryo maturation rate showed no significant correlation with subculturing cycles. However, there was a positive correlation between subculturing cycles and pre-treatment proliferation rate and a negative correlation with somatic embryo maturation rate in the BFU1 cell line. In addition, we utilized ten SSR molecular markers to investigate the genetic stability in embryogenic tissues during long-term subculturing. No genomic variations were detected in any of the three embryogenic cell lines, which suggests that the observed phenotypic dynamics during subculturing may not be primarily driven by genomic alterations. This study provides novel insights into the dynamics of the long-term culture of embryogenic tissues, laying a foundation for the optimization and application of somatic embryogenesis techniques in L. principis-rupprechtii Mayr and potentially other coniferous species. [ABSTRACT FROM AUTHOR]

The capability of embryogenic callus induction is a prerequisite for in vitro plant regeneration. However, embryogenic callus induction is strongly genotype-dependent, thus hindering the development of in vitro plant genetic engineering technology. In this study, to examine the genetic variation in embryogenic callus induction rate (CIR) in peanut (Arachis hypogaea L.) at the seventh, eighth, and ninth subcultures (T7, T8, and T9, respectively), we performed genome-wide association studies (GWAS) for CIR in a population of 353 peanut accessions. The coefficient of variation of CIR among the genotypes was high in the T7, T8, and T9 subcultures (33.06%, 34.18%, and 35.54%, respectively), and the average CIR ranged from 1.58 to 1.66. A total of 53 significant single-nucleotide polymorphisms (SNPs) were detected (based on the threshold value −log10(p) = 4.5). Among these SNPs, SNPB03-83801701 showed high phenotypic variance and neared a gene that encodes a peroxisomal ABC transporter 1. SNPA05-94095749, representing a nonsynonymous mutation, was located in the Arahy.MIX90M locus (encoding an auxin response factor 19 protein) at T8, which was associated with callus formation. These results provide guidance for future elucidation of the regulatory mechanism of embryogenic callus induction in peanut. [ABSTRACT FROM AUTHOR]

Wax is an acellular structural substance attached to the surface of plant tissues. It forms a protective barrier on the epidermis of plants and plays an important role in resisting abiotic and biotic stresses. In this paper, nonheading Chinese cabbage varieties with and without wax powder were observed using scanning electron microscopy, and the surface of waxy plants was covered with a layer of densely arranged waxy crystals, thus differentiating them from the surface of waxless plants. A genetic analysis showed that wax powder formation in nonheading Chinese cabbage was controlled by a pair of dominant genes. A preliminary bulked segregant analysis sequencing (BSA-seq) assay showed that one gene was located at the end of chromosome A09. Within this interval, we identified BraA09000626, encoding an AP2 transcription factor homologous to Arabidopsis AtSHINE3, and we named it BrSHINE3. By comparing the CDS of the gene in the two parental plants, a 35 bp deletion in the BrSHINE3 gene of waxless plants resulted in a frameshift mutation. Tissue analysis showed that BrSHINE3 was expressed at significantly higher levels in waxy plant rosette stage petioles and bolting stage stems than in the tissues of waxless plants. We speculate that this deletion in BrSHINE3 bases in the waxless material may inhibit wax synthesis. The overexpression of BrSHINE3 in Arabidopsis induced the accumulation of wax on the stem surface, indicating that BrSHINE3 is a key gene that regulates the formation of wax powder in nonheading Chinese cabbage. The analysis of the subcellular localization showed that BrSHINE3 is mainly located in the nucleus and chloroplast of tobacco leaves, suggesting that the gene may function as a transcription factor. Subsequent transcriptome analysis of the homology of BrSHINE3 downstream genes in nonheading Chinese cabbage showed that these genes were downregulated in waxless materials. These findings provide a basis for a better understanding of the nonheading Chinese cabbage epidermal wax synthesis pathway and provide important information for the molecular-assisted breeding of nonheading Chinese cabbage. [ABSTRACT FROM AUTHOR]

Nickel (Ni) is an essential trace element for plant growth and a component of the plant body that has many different functions in plants. Although it has been confirmed that nickel ions (Ni2+) havea certain regulatory effect on nitrogen (N) metabolism, there are not enough data to prove whether exogenous Ni2+ can increase the carbon (C) and N metabolism in the roots of tomato seedlingsunder low-nitrogen (LN) conditions. Therefore, through the present experiment, we revealed the key mechanism of Ni2+-mediated tomato root tolerance to LN levels. Tomato plants were cultured at two different N levels (7.66 and 0.383 mmol L−1) and two different Ni2+ levels (0 and 0.1 mg L−1 NiSO4 6H2O) under hydroponic conditions. After nine days, we collected roots for physiological, biochemical, and transcriptome sequencing analyses and found that the activities of N assimilation-related enzymes decreased at LN levels. In contrast, Ni2+ significantly increased the activities of N assimilation-related enzymes and increased the contents of nitrate (NO3−), ammonium (NH4+), and total amino acids. Through root transcriptomic analysis, 3738 differentially expressed genes (DEGs) were identified. DEGs related to C and N metabolism were downregulated after LN application. However, after Ni2+ treatment, PK, PDHB, GAPDH, NR, NiR, GS, GOGAT, and other DEGs related to C and N metabolism were significantly upregulated. In conclusion, our results suggest that Ni2+ can regulate the C and N metabolism pathways in tomato roots to alleviate the impact of LN levels. [ABSTRACT FROM AUTHOR]

CO/CO2 hydrogenation has attracted much attention as a pathway to achieve carbon neutrality and production of synthetic natural gas (SNG). In this work, two-dimensional NiAl layered double oxide (2D NiAl-LDO) has been successfully decorated by SiO2 nanoparticles derived from SiCl4 and used as CO/CO2 methanation catalysts. The as-obtained H-SiO2-NiAl-LDO exhibited a large specific surface area of 201 m2/g as well as high ratio of metallic Ni0 species and surface adsorption oxygen that were beneficial for low-temperature methanation of CO/CO2. The conversion of CO methanation was 99% at 400 °C, and that of CO2 was 90% at 350 °C. At 250 °C, the CO methanation reached 85% whereas that of CO2 reached 23% at 200 °C. We believe that this provides a simple method to improve the methanation performance of CO and CO2 and a strategy for the modification of other similar catalysts. [ABSTRACT FROM AUTHOR]

As resource waste and environmental degradation become increasingly serious, closed-loop supply chains have attracted more and more attention from the public. How to effectively undertake corporate social responsibility (CSR) and alleviate the conflict of closed-loop supply chains has become an urgent task for managers and researchers to resolve. With respect to the coordination problems of closed-loop supply chains led by retailers, based on Stackelberg game theory, we establish some models considering manufacturer's CSR, exploit them to compare the optimal decisions under centralized and decentralized decisions, explore the impact of CSR on supply-chain decisions, then design a coordination mechanism through two-step pricing. [ABSTRACT FROM AUTHOR]

At present, the research focus has been aimed at the pursuit of the design and synthesis of catalysts for effective photocatalytic degradation of organic pollutants in wastewater, and further exploration of novel materials of the photodegradation catalyst. In this paper, the Sol-gel route after thermal treatment was used to produce NiFe2O4 carbon aerogel (NiFe2O4-CA) nanocomposites with cotton linter cellulose as the precursor of aerogel, by co-precipitating iron and nickel salts onto its substrate. The structure and composition of these materials were characterized by X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), Raman spectra, high-resolution scanning electron microscopy (HR-SEM), high-resolution scanning electron microscope mapping (SEM-mapping), X-ray photoelectron spectroscopy (XPS) and Brunauer–Emmett–Teller (BET)'s surface area. The magnetic properties of the material were analyzed by a vibrating-sample magnetometer (VSM). Moreover, diffuse reflectance spectra (DRS), electrochemical impedance spectroscopy (EIS) and photo-luminescence spectroscopy (PL) characterized the photoelectric properties of this cellulose-aerogels-based NiFe2O4-CA. Methylene blue (MB) acted as the simulated pollutant, and the photocatalytic activity of NiFe2O4-CA nanocomposites under visible light was evaluated by adjusting H2O2 content and the pH value. The results showed that the optical absorption range of nickel ferrite was broadened by doping cellulose-aerogels-based carbon, which exerted more positive effects on photocatalytic reactions. This is because the doping of this aerogel carbon promoted a more uniform distribution of NiFe2O4 particles. Given the Methylene blue (MB) degradation reaction conformed to the first-order kinetic equation, the NiFe2O4-CA nanocomposites conducted excellent catalytic activity by maintaining almost 99% of the removal of MB (60 mg/L) within 180 min and upheld excellent stability over four consecutive cycles. This study indicated that NiFe2O4-CA nanocomposites reserved the potential as a future effective treatment of dye wastewater. [ABSTRACT FROM AUTHOR]

We define the group measure matrix of the alternative scheme and the ideal scheme based on the relevant factor sequence and the system characteristic behavior sequence. Furthermore, the information distances of decision makers and decision criteria are defined, respectively. According to the information distance, we obtain each scheme's grey matrix incidence degree for the scheme ranking. Finally, we use an example to verify the rationality of the model and compare it with other classic methods, such as TOPSIS, VIKOR, MULTI-MOORA. Compared with previous grey incidence analysis model, the proposed model can make full use of information of the decision-maker dimension and the criteria dimension. The proposed model can avoid high-dimensional information loss. The results show that the proposed method has superiority in measuring decision-maker information and decision-making standard information. [ABSTRACT FROM AUTHOR]

Featured Application: With the development of artificial intelligence, Internet technology, smart exercise equipment, and smart wearable devices, more and more people are becoming willing to use these technologies for exercise, whether out of curiosity or because they want to use them for scientific fitness. At the same time, many non-invasive static human data acquisition devices have become commonplace, and many hospitals and communities are already using them. The smart health system that we designed can easily process the in-exercise and non-exercise data collected by the above two ways. The system, which includes a mobile application, website, cloud server, smart wearable device, and other platforms, generates personalized prescriptions for users by learning the data. The system also includes many functions for public health, and exercise prescription is just one module of it. Using absolute intensity methods (metabolic equivalent of energy (METs), etc.) to determine exercise intensity in exercise prescriptions is straightforward and convenient. Using relative intensity methods (heart rate reserve (%HRR), maximal heart rate (%HRmax), etc.) is more recommended because it is more personalized. Taking target heart rate (THR) given by the relative method as an example, compared with just presenting the THR value, intuitively providing the setting parameters for achieving the THR with specific sport equipment is more user-friendly. The objective of this study was to find a method which combines the advantages (convenient and personalized) of the absolute and relative methods and relatively avoids their disadvantages, helping individuals to meet the target intensity by simply setting equipment parameters. For this purpose, we recruited 32 males and 29 females to undergo incremental cardiopulmonary exercise testing with cycling equipment. The linear regression model of heart rate and exercise wattage (the setting parameter of the equipment) was constructed for each one (R2 = 0.933, p < 0.001), and the slopes of the graph of these models were obtained. Next, we used an iterative algorithm to obtain a multiple regression model (adjusted R2 = 0.8336, p < 0.001) of selected static body data and the slopes of participants. The regression model can accurately predict the slope of the general population through their static body data. Moreover, other populations can guarantee comparable accuracy by using questionnaire data for calibration. Then, the predicted slope can be utilized to calculate the equipment's settings for achieving a personalized THR through our equation. All of these steps can be assigned to the intelligent system. [ABSTRACT FROM AUTHOR]

Pseudotsuga gaussenii is a forest species under protection in China. Propagation via somatic embryogenesis is efficient and needed for recovering this species. In this research, effects of medium supplements, i.e., methylglyoxal-bis (guanylhydrazone) (MGBG), polyethylene glycol (PEG), and maltose, on somatic embryo (SE) development were studied. More mature SEs developed with the pre-maturation treatment medium supplemented with 50 μM or 100 μM MGBG. During SE maturation, when the medium was supplemented with both PEG and maltose, the over-proliferation of embryogenic tissue was suppressed. When maltose was eliminated from the maturation medium, SEs were slightly smaller but developed better than other treatments due to the supply of lower carbon source, whereas when PEG was taken out from the maturation medium, no mature SE was obtained, only the heavily-proliferated plant tissue. Meanwhile, DNA methylation levels differed in these SE maturation cultures at the late culture stage of SE maturation. The level increased sharply with no maltose treatment (20.28%) while decreasing without PEG supplement (10.35%). DNA methyltransferase genes MET1-1, MET1-2, MET1-3, CMT3, DRM1, and DRM2 were partially cloned in this study to detect their expression level via qPCR. Expression of these genes, except MET1-3, in the culture of no PEG was higher significantly than the cultures of other treatments at weeks 1, 3, and 10. Our results suggested that MGBG and/or PEG play an important role in stimulating SE development and maturation. Furthermore, sugar supplements at a lower level benefited SE maturation in Pseudotsuga gaussenii. [ABSTRACT FROM AUTHOR]

The continuous cropping of sugar beet can result in soil degradation and a decrease in the sugar beet yield and quality. However, the role of continuous sugar beet (Beta vulgaris L. var. saccharifera) cropping in shaping the structure and function of the rhizosphere microbial community remains poorly investigated. In this study, we comparatively investigated the impact of different numbers of years of continuous sugar beet cropping on structural and functional changes in the microbial community of the rhizosphere using high-throughput sequencing and bioinformatics analysis. We collected rhizosphere soils from fields continuously cropped for one-year (T1), five-year (T5), and thirty-year (T30) periods, as well as one bulk soil (T0), in the Xinjiang Uygur Autonomous Region. The results demonstrated that continuous sugar beet cropping resulted in a significant decline in the community diversity of soil bacterial and fungal populations from T1 to T5. With continuous change in the structure of the microbial community, the Shannon diversity and observed species were increased in T30. With an abundance of pathogenic microbes, including Acidobacteria, Alternaria, and Fusarium, that were highly enriched in T30, soil-borne diseases could be accelerated, deduced by functional predictions based on 16S rRNA genes. Continuous sugar beet cropping also led to significant declines in beneficial bacteria, including Actinobacteria, Pseudomonas spp., and Bacillus spp. In addition, we profiled and analyzed predictive metabolic characteristics (metabolism and detoxification). The abundance of phenolic acid decarboxylase involved in the phenolic acid degradation pathway was significantly lower in groups T5 and T30 than that in T0 and T1, which could result in the phenolic compounds becoming excessive in long-term continuous cropping soil. Our results provide a deeper understanding of the rhizosphere soil microbial community's response to continuous sugar beet cropping, which is important in evaluating the sustainability of this agricultural practice. [ABSTRACT FROM AUTHOR]

The continuous cropping of sugar beet can result in soil degradation and a decrease in the sugar beet yield and quality. However, the role of continuous sugar beet ( Beta vulgaris L. var. saccharifera) cropping in shaping the structure and function of the rhizosphere microbial community remains poorly investigated. In this study, we comparatively investigated the impact of different numbers of years of continuous sugar beet cropping on structural and functional changes in the microbial community of the rhizosphere using high-throughput sequencing and bioinformatics analysis. We collected rhizosphere soils from fields continuously cropped for one-year (T1), five-year (T5), and thirty-year (T30) periods, as well as one bulk soil (T0), in the Xinjiang Uygur Autonomous Region. The results demonstrated that continuous sugar beet cropping resulted in a significant decline in the community diversity of soil bacterial and fungal populations from T1 to T5. With continuous change in the structure of the microbial community, the Shannon diversity and observed species were increased in T30. With an abundance of pathogenic microbes, including Acidobacteria , Alternaria , and Fusarium , that were highly enriched in T30, soil-borne diseases could be accelerated, deduced by functional predictions based on 16S rRNA genes. Continuous sugar beet cropping also led to significant declines in beneficial bacteria, including Actinobacteria , Pseudomonas spp., and Bacillus spp. In addition, we profiled and analyzed predictive metabolic characteristics (metabolism and detoxification). The abundance of phenolic acid decarboxylase involved in the phenolic acid degradation pathway was significantly lower in groups T5 and T30 than that in T0 and T1, which could result in the phenolic compounds becoming excessive in long-term continuous cropping soil. Our results provide a deeper understanding of the rhizosphere soil microbial community's response to continuous sugar beet cropping, which is important in evaluating the sustainability of this agricultural practice.