Explore the vast range of titles available.

Emulsifiers are added to enhance product stability to obtain a satisfactory shelf-life. For this reason, stable emulsions that do not form peroxides nor change the fatty acid composition of food, as well as safe treatments to obtain them, are aspects of utmost importance. High-pressure homogenization is a conventional approach to prepare emulsions because of its high efficiency. In addition, the beneficial effects of ultrasound on the processing efficiency are known. Therefore, the impact of high-pressure homogenization (30 MPa, 50M Pa) or ultrasound power (270 W) on the emulsion stability and emulsifying properties of 5% coconut oil-in-water emulsion were discussed in this study. The complexes (3:7and 4:6, by weight) of propylene glycol alginate and xanthan gum were selected as emulsifier. The apparent viscosity, particle size and distribution, emulsifying properties and ζ-potential of 5% coconut oil-in-water emulsion before and after ultrasound treatment or high-pressure homogenization were investigated and compared. The micro structure of the emulsion was observed under the fluorescence microscope. The experimental results showed that both high-pressure homogenization and ultrasonic treatment effectively reduced the apparent viscosity, average droplet size and narrowed the distribution range of the emulsion, compared with the pre-emulsion. However, aggregation in the emulsion appeared only after being subjected to high-pressure homogenization, while the emulsion made by the ultrasound treatment remained stable during 30 days storage. In conclusion, this study provides valuable information regarding emulsion preparation methods that can be feasible in food and beverage industries, demonstrating a better performance of ultrasound in optimizing and extending food shelf-life in food and beverage industries.

Summary Maize is a globally important food, feed crop and raw material for the food and energy industry. Plant architecture optimization plays important roles in maize yield improvement. PIN‐FORMED (PIN) proteins are important for regulating auxin spatiotemporal asymmetric distribution in multiple plant developmental processes. In this study, ZmPIN1a overexpression in maize increased the number of lateral roots and inhibited their elongation, forming a developed root system with longer seminal roots and denser lateral roots. ZmPIN1a overexpression reduced plant height, internode length and ear height. This modification of the maize phenotype increased the yield under high‐density cultivation conditions, and the developed root system improved plant resistance to drought, lodging and a low‐phosphate environment. IAA concentration, transport capacity determination and application of external IAA indicated that ZmPIN1a overexpression led to increased IAA transport from shoot to root. The increase in auxin in the root enabled the plant to allocate more carbohydrates to the roots, enhanced the growth of the root and improved plant resistance to environmental stress. These findings demonstrate that maize plant architecture can be improved by root breeding to create an ideal phenotype for further yield increases.

With the new challenges and crises facing agriculture, digitalization and green transformation have become important ways to solve the problems. This paper uses an international economics perspective to chart a new path for sustainable agricultural development. Specifically, it analyzes whether two-way international direct investment (FDI) can facilitate agricultural digital-green fusion(DGF)? Using a sample of 31 provinces (autonomous regions) from 2012 to 2021, this study finds: (1) Two-way FDI can significantly contribute to agriculture’s DGF. (2) In the mechanism test, it is proved that two-way FDI can promote agriculture’s DGF level by promoting green technology innovation capacity and overall regional technology innovation capacity. (3) The positive effects of two-way FDI are prominent in the eastern and central regions, coastal regions, and economically developed areas. (4) In the spatial Durbin model, the local two-way FDI growth improves agriculture’s DGF level in the surrounding areas to a certain extent. The government is advised to prioritize openness, foster an environment for technological innovation, leverage spatial radiation for agricultural DGF, and advance digitally empowered agricultural modernization.

As an environmentally friendly and controllable technology, Microbially induced carbonate precipitation (MICP) has broad applications in geotechnical and environmental fields. However, the longitudinal dispersivity in MICP multi-process varies with the scale size. Ignoring the effect of the scale size of the research object on the dispersivity leads to the inaccuracy between the numerical model and the experiment data. Thus, this paper has established the relationship between the scale size and the dispersivity initially, and optimized the theoretical system of MICP multi-process reaction. When scale size increases logarithmically from 10 −2 m to 10 5 m, longitudinal dispersivity shows a trend of increasing from 10 −3 m to 10 4 m. The distribution of calcium carbonate is closer to the experimentally measured value when the size effect is considered. After considering the scale size, the suspended bacteria and attached bacteria are higher than the cased without considering the size effect, which leads to a higher calcium carbonate content. Scale has little effect on the penetration law of the suspended bacteria. The maximum carbonate content increases with the increase of the initial porosity, and the average carbonate shows a significant increasing trend with the increase of the bacterial injecting rate. In the simulation of the microbial mineralization kinetic model, it is recommended to consider the influence of the scale size on the MICP multi-process.

To investigate the effect of pyrolysis temperature on the adsorption behavior of the emerging organic pollutant tris-(1-chloro-2-propyl) phosphate (TCIPP) on biochar, corn stover was used as raw materials to prepare biochars at different pyrolysis temperatures (250, 350, 500, 700 °C) through limited oxygen carbonization. Elemental analysis, Boehm titration, FTIR, XPS, and other analytical methods were used to reveal the effect of pyrolysis temperature on the physicochemical properties of biochar and its mechanism of TCIPP adsorption. The results showed that the pyrolysis temperature had a significant impact on the physicochemical properties of biochar. As the pyrolysis temperature increases, the specific surface area of biochar rises from 3.083 m 2 /g to 435.573 m 2 /g, the pH value increases from 6.60 to 10.66, the mass percentage of C increases from 63.10 to 80.58%, and the mass percentage of O decreases from 26.42 to 9.20%. Additionally, the hydrophobicity and aromaticity of biochar also increase with rising pyrolysis temperature, while its polarity decreases. Boehm titration, FTIR, and XPS analysis showed that the total amount of functional groups on the surface of biochar decreased relatively with increasing temperature. Functional groups such as -OH, C = C/C = O, and C-O-C participated in the adsorption of TCIPP on biochar, and ester groups were produced after adsorption. The adsorption process of TCIPP on biochar fits best with the pseudo-second-order equation, indicating that the adsorption process is mainly chemical adsorption, and the main rate-controlling stage is intraparticle diffusion. The isothermal adsorption results were more in line with the Temkin model, indicating that the adsorption process of TCIPP on biochar was mainly surface adsorption. As the pyrolysis temperature increases, the maximum adsorption capacity of biochar increases from 0.8837 mg/g to 2.2574 mg/g. The adsorption process of TCIPP on biochar mainly included pore filling, hydrogen bonding, P-π interaction, hydrophobic interaction, and electrostatic attraction. Among them, pore filling, P-π interaction, and hydrophobic interaction were significantly enhanced with increasing temperature, while hydrogen bonding was relatively weakened. This study will provide a theoretical basis and technical support for the removal of TCIPP from water using biochar adsorption.

Background: It is well known that carbapenem-resistant Klebsiella pneumoniae (CRKP) has become a more problematic public health issue due to its widespread spread worldwide. In China, ST11-type CRKP is the most prevalent CRKP, but ST15-type CRKP, a recently prevalent high-risk clone, has emerged widely throughout China, posing a serious public health risk. Therefore, we conducted an epidemiological of an outbreak of ST15 CRKP of producing CTX-M-15, KPC-2 and SHV-106 in a tertiary hospital in Anhui, China, to Understanding the potential risks of the current STT15 CRKP outbreak. Results: From July 2021 to December 2021, 13 ST15 CRKP isolates were identified by collecting non-repeated clinical multidrug-resistant isolates, with all capsular typing of serotype KL19. All ST15 CRKP isolates were resistant to cephalosporins, carbapenems and quinolones, but were sensitive to amikacin, tigecycline and polymyxin B. In addition, isolates carried bla SHV−106 (100%), bla KPC−2 (69%), bla CTX−M−15 (69%), bla TEM−1B (69%), bla OXA−1 (62%) and bla LAP−2 (8%), as well as iron chelators ( iutA , ybt , fyuA , ent , fepA , irp1 , irp2 , 100%) were detected. In phenotyping experiments, all ST15 CRKP exhibited lower growth rates than NTUH-K2044, and all ST15 CRKP did not exhibit mucoviscositty characteristics. However, in the Galleria mellonella infection model, isolates 21081212, 21081241 and 21091216 were more lethal than the hypervirulent isolates NTUH-K2044. Sequencing results showed that the genetic environment surrounding the genes bla SHV−106 , bla KPC−2 , bla CTX−M−15 , bla OXA−1 and bla TEM−1B were all identical in the ST15 CRKP isolates. Phylogenetic analysis showed that 13 ST15 CRKP isolates were divided into three subgroups, and when placed in global analysis, 10 of them were highly homologous to isolates from Jiangsu, two were highly homologous to isolates from Zhejiang, and one was homologous to an isolate from an unlabelled region. Conclusion: Our research shows that ST15 CRKP, which carries multiple β-lactamases genes and siderophores-encoding genes, may be evolving to hypervirulence and may have spread widely in localised areas. Therefore, environmental surveillance and clinical infection control in hospitals should be strengthened to prevent further spread of ST15 CRKP.

The gross primary productivity (GPP) of Shanxi Province, China, plays an important role in the carbon cycle of the Loess Plateau ecosystem. However, Shanxi Province lacks carbon flux stations, leading to imprecise GPP estimation results. Additionally, few studies have explored the drivers of long-term GPP change in Shanxi Province. Therefore, in this study, we aimed to estimate the GPP in Shanxi Province from 2001 to 2022 and determine the driving factors of long-term GPP trends. To this end, we proposed an improved GPP estimation method based on the CatBoost model. Our CatBoost GPP model reduces model overfitting in few-shot scenarios and effectively captures the time dependence in time-series data. In addition, it integrates the change characteristics of vegetation ecological indicators and topography constraints, improving GPP estimation accuracy. Subsequently, we explored the spatial and temporal variations driving force through methods such as Theil-Sen Median trend analysis and Geodetectors. Our results show that (1) Compared with existing methods, the proposed CatBoost GPP method achieved superior site-level accuracy, with an value of 0.890, root mean square error (RMSE) of 1.155 gC , and mean absolute error (MAE) of 0.772 gC . Furthermore, we compared our results with previous GPP products to further assess the regional-level accuracy; (2) The GPP in Shanxi Province displayed a fluctuating increase, with a growth rate of 20.58 gC from 2001 to 2022. The overall spatial variation was characterized by low GPP in the northwest and high GPP in the southeast. The GPP change was mainly characterized by weak anti-persistence; thus, approximately 58.8% of the area may experience degradation in the future; and (3) Land use type significantly influenced GPP changes in Shanxi, with the restoration and improvement of grassland being the main contributor to the increase in GPP. The interaction between precipitation and temperature had the most complex and significant impact on GPP, affecting approximately 62.05% of the study area. The results of this study provide a theoretical basis for ecological protection and sustainable development in Shanxi Province.

Efficient, rapid, and non-destructive detection of pesticide residues in fruits and vegetables is essential for food safety. The visible/near infrared (VNIR) and short-wave infrared (SWIR) hyperspectral imaging (HSI) systems were used to detect different types of pesticide residues on the surface of Hami melon. Taking four pesticides commonly used in Hami melon as the object, the effectiveness of single-band spectral range and information fusion in the classification of different pesticides was compared. The results showed that the classification effect of pesticide residues was better by using the spectral range after information fusion. Then, a custom multi-branch one-dimensional convolutional neural network (1D-CNN) model with the attention mechanism was proposed and compared with the traditional machine learning classification model K-nearest neighbor (KNN) algorithm and random forest (RF). The traditional machine learning classification model accuracy of both models was over 80.00%. However, the classification results using the proposed 1D-CNN were more satisfactory. After the full spectrum data was fused, it was input into the 1D-CNN model, and its accuracy, precision, recall, and F1-score value were 94.00%, 94.06%, 94.00%, and 0.9396, respectively. This study showed that both VNIR and SWIR hyperspectral imaging combined with a classification model could non-destructively detect different pesticide residues on the surface of Hami melon. The classification result using the SWIR spectrum was better than that using the VNIR spectrum, and the classification result using the information fusion spectrum was better than that using SWIR. This study can provide a valuable reference for the non-destructive detection of pesticide residues on the surface of other large, thick-skinned fruits.

Cobalt-free spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) positive electrodes, promise high energy density when coupled with lithium negative electrodes, due to the high discharge voltage platform. However, the intrinsic dissolution of Mn in positive electrode, electrolyte decomposition at high voltage, and dendrite growth on lithium severely compromise cycling stability, limiting the practical application. Herein, we propose ferrocene hexafluorophosphate as an electrolyte additive to achieve dynamic doping of Fe 3+ in positive electrodes during electrochemical cycling. Furthermore, additive molecule preferentially decomposes at both the positive and negative electrode interfaces, forming thin, dense inorganic positive electrode electrolyte interphase and F, P-rich inorganic solid electrolyte interphase respectively, effectively stabilizing electrode interfaces. Consequently, the Li | |LNMO batteries based on modified electrolytes effectively enhance cycling stability and rate performance at a charge cutoff voltage of 4.9 V and an LNMO pouch cell performs consistently over 160 cycles. Additionally, the efficacy of ferrocene hexafluorophosphate extends beyond LNMO, demonstrating its universal applicability in stabilizing positive electrodes operating at challenging voltages, including LiNi 0.8 Co 0.1 Mn 0.1 O 2 , LiNi 0.6 Co 0.2 Mn 0.2 O 2 , and LiCoO 2 and a 470 Wh kg −1 level Li metal pouch cell was successfully realized. Cobalt-free Mn-based lithium metal batteries suffer from serious Mn dissolution and lithium dendrite problems. Here, authors propose ferrocene hexafluorophosphate as an electrolyte additive to achieve dynamic doping of positive electrode and interphase stabilization of electrodes.

Improving the green electricity efficiency (GEE), is an important issue for China's high-quality economic development. This study presents a spatial correlation network of urban GEE in the Yellow River Basin from 2012 to 2021, constructed using an improved gravity model. Social network analysis and the quadratic assignment procedure method are employed to analyze the spatial correlation characteristics and influencing factors. The findings indicate that urban GEE in the Yellow River Basin exhibits complex and stable network characteristics. The spatial network analysis reveals that Jiayuguan City, Dongying City, Dingxi City, Zibo City, and Shizuishan City occupy central positions within the network. The results indicate that spatial adjacency, GDP per capita, industrial structure, and the level of science and technology expenditure are positively related to urban GEE, while environmental regulation and average temperature are negatively related. The findings of the study have led to policy recommendations aimed at enhancing urban GEE in the Yellow River Basin.