Effect of CO2 Elevation on Tomato Gas Exchange, Root Morphology and Water Use Efficiency under Two N-Fertigation Levels.

Atmospheric elevated CO2 concentration (e[CO2]) decreases plant nitrogen (N) concentration while increasing water use efficiency (WUE), fertigation increases crop nutrition and WUE in crop; yet the interactive effects of e[CO2] coupled with two N-fertigation levels during deficit irrigation on plant gas exchange, root morphology and WUE remain largely elusive. The objective of this study was to explore the physiological and growth responses of ambient [CO2] (a[CO2], 400 ppm) and e[CO2] (800 ppm) tomato plant exposed to two N-fertigation regimes: (1) full irrigation during N-fertigation (FIN); (2) deficit irrigation during N-fertigation (DIN) under two N fertilizer levels (reduced N (N1, 0.5 g pot-1) and adequate N (N2, 1.0 g pot-1). The results indicated that e[CO2] associated with DIN regime induced the lower N2 plant water use (7.28 L plant-1), maintained leaf water potential (-5.07 MPa) and hydraulic conductivity (0.49 mol m-2 s-1 MPa-1), greater tomato growth in terms of leaf area (7152.75 cm2), specific leaf area (223.61 cm2 g-1), stem and total dry matter (19.54 g and 55.48 g). Specific root length and specific root surface area were increased under N1 fertilization, and root tissue density was promoted in both e[CO2] and DIN environments. Moreover, a smaller and denser leaf stomata (4.96 µm2 and 5.37 mm-2) of N1 plant was obtained at e[CO2] integrated with DIN strategy. Meanwhile, this combination would simultaneously reduce stomatal conductance (0.13 mol m-2 s-1) and transpiration rate (1.91 mmol m-2 s-1), enhance leaf ABA concentration (133.05 ng g-1 FW), contributing to an improvement in WUE from stomatal to whole-plant scale under each N level, especially for applying N1 fertilization (125.95 µmol mol-1, 8.41 µmol mmol-1 and 7.15 g L-1). These findings provide valuable information to optimize water and nitrogen fertilizer management and improve plant water use efficiency, responding to the potential resource-limited and CO2-enriched scenario.

Synthesis and Electrocatalytic Performance Study of Sulfur Quantum Dots Modified MoS2.

The electrolysis of water for hydrogen production is currently receiving significant attention due to its advantageous features such as non-toxicity, safety, and environmental friendliness. This is especially crucial considering the urgent need for clean energy. However, the current method of electrolyzing water to produce hydrogen largely relies on expensive metal catalysts, significantly increasing the costs associated with its development. Molybdenum disulfide (MoS2) is considered the most promising alternative to platinum for electrocatalyzing the hydrogen evolution reaction (HER) due to its outstanding catalytic efficiency and robust stability. However, the practical application of this material is hindered by its low conductivity and limited exposure of active sites. MoS2/SQDs composite materials were synthesized using a hydrothermal technique to deposit SQDs onto MoS2. These composite materials were subsequently employed as catalysts for the HER. Research findings indicate that incorporating SQDs can enhance electron transfer rates and increase the active surface area of MoS2, which is crucial for achieving outstanding catalytic performance in the HER. The MoS2/SQDs electrocatalyst exhibits outstanding performance in the HER when tested in a 0.5 M H2SO4 solution. It achieves a remarkably low overpotential of 204 mV and a Tafel slope of 65.82 mV dec-1 at a current density of 10 mA cm-2. Moreover, during continuous operation for 24 h, the initial current density experiences only a 17% reduction, indicating high stability. This study aims to develop an efficient and cost-effective electrocatalyst for water electrolysis. Additionally, it proposes a novel design strategy that uses SQDs as co-catalysts to enhance charge transfer in nanocomposites.

Effective Removal of Dyes from Wastewater by Osmanthus Fragrans Biomass Charcoal.

The exploration of low-cost, high-performance adsorbents is a popular research issue. In this work, a straightforward method that combined hydrothermal with tube firing was used to produce Osmanthus fragrans biomass charcoal (OBC) from low-cost osmanthus for dye adsorption in water. The study examined the parameters of starting concentration, pH, and duration, which impacted the process of adsorption of different dyes by OBC. The analysis showed that the adsorption capacities of OBC for six dyes: malachite green (MG, C0 = 800 mg/L, pH = 7), Congo red (CR, C0 = 1000 mg/L, pH = 8), rhodamine B (RhB, C0 = 500 mg/L, pH = 6), methyl orange (MO, C0 = 1000 mg/L, pH = 7), methylene blue (MB, C0 = 700 mg/L, pH = 8), and crystalline violet (CV, C0 = 500 mg/L, pH = 7) were 6501.09, 2870.30, 554.93, 6277.72, 626.50, and 3539.34 mg/g, respectively. The pseudo-second-order model and the Langmuir isotherm model were compatible with the experimental findings, which suggested the dominance of ion exchange and chemisorption. The materials were characterized by using XRD, SEM, FTIR, BET, and XPS, and the results showed that OBC had an outstanding specific surface area (2063 m2·g-1), with potential adsorption mechanisms that included electrostatic mechanisms, hydrogen bonding, and π-π adsorption. The fact that the adsorption capacity did not drastically decrease after five cycles of adsorption and desorption suggests that OBC has the potential to be a dye adsorbent.

A Novel Non-Metallic Photocatalyst: Phosphorus-Doped Sulfur Quantum Dots.

In this paper, a novel phosphorus-doped sulfur quantum dots (P-SQDs) material was prepared using a simple hydrothermal method. P-SQDs have a narrow particle size distribution as well as an excellent electron transfer rate and optical properties. Compositing P-SQDs with graphitic carbon nitride (g-C3N4) can be used for photocatalytic degradation of organic dyes under visible light. More active sites, a narrower band gap, and stronger photocurrent are obtained after introducing P-SQDs into g-C3N4, thus promoting its photocatalytic efficiency by as much as 3.9 times. The excellent photocatalytic activity and reusability of P-SQDs/g-C3N4 are prospective signs of its photocatalytic application under visible light.

Public sentiment analysis on urban regeneration: A massive data study based on sentiment knowledge enhanced pre-training and latent Dirichlet allocation.

BACKGROUND: Public satisfaction is the ultimate goal and an important determinant of China's urban regeneration plan. This study is the first to use massive data to perform sentiment analysis of public comments on China's urban regeneration. METHODS: Public comments from social media, online forums, and government affairs platforms are analyzed by a combination of Natural Language Processing, Knowledge Enhanced Pre-Training, Word Cloud, and Latent Dirichlet Allocation. RESULTS: (1) Public sentiment tendency toward China's urban regeneration was generally positive but spatiotemporal divergences were observed; (2) Temporally, public sentiment was most negative in 2020, but most positive in 2021. It has remained consistently negative in 2022, particularly after February 2022; (3) Spatially, at the provincial level, Guangdong posted the most comments and Tibet, Shanghai, Guizhou, Chongqing, and Hong Kong are provinces with highly positive sentiment. At the national level, the east and south coastal, southwestern, and western China regions are more positive, as opposed to the northeast, central, and northwest regions; (4) Topics related to Shenzhen's renovations, development of China's urban regeneration and complaints from residents are validly categorized and become the public's key focus. Accordingly, governments should address spatiotemporal disparities and concerns of local residents for future development of urban regeneration.

Comparison of machine learning and deep learning models for evaluating suitable areas for premium teas in Yunnan, China.

BACKGROUND: Tea is an important economic crop in Yunnan, and the market price of premium teas such as Lao Banzhang is significantly higher than ordinary teas. For planting lands to promote, the tea industry to develop and minority lands' economies to prosper, it is vital to evaluate and analyze suitable areas for premium tea cultivation. METHODS: Climate, terrain, soil, and green cropping system in the premium tea planting areas were used as evaluation variables. The suitability of six machine learning models for predicting suitable areas of premium teas were evaluated. RESULT: FA+ResNet demonstrated the best performance with an accuracy score of 0.94 and a macro-F1 score of 0.93. The suitable areas of premium teas were mainly located in the southern catchment of LancangJiang River, south-central part of Dehong, a few areas in the mid-west of Lincang, central scattered areas of Pu'er, most of the southern western part of Xishuangbanna and the southern edge of Honghe. Annual mean temperature, annual mean precipitation, mist belt, annual mean relative humidity, soil type and elevation were the key components in evaluating the suitable areas of premium teas in Yunnan.