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为了对比不同油体富集物理化性质及功能性质的差异，采用水萃离心法从大豆、花生、葵花籽3种大宗油料种子中提取油体富集物，对比研究了油体富集物的得率、基本成分、粒径、Zeta电位、蛋白质组成、黏度、起泡性、乳化性、分层稳定性以及冻融稳定性。结果表明：大豆油体富集物的得率和固形物含量都显著低于葵花籽和花生油体富集物的（p＜0.05），且具有不易掩盖的豆腥味；3种油体富集物的基本成分之间都存在显著性差异（p＜0.05），蛋白质的分子质量分布也不尽相同；3种油体富集物的粒径和Zeta电位绝对值由小到大顺序均为大豆油体富集物

[Objective] Exploring the changes and ecological effects of the ecological land in the desert oasis area can provide a decision-making reference for the ecological protection and high-quality development of the Yellow River Basin. [Methods] Taking Yinchuan City, a desert oasis in the upper reaches of the Yellow River, as an example, this study put forward the coefficient revision method of ecological service value (ESV) equivalent factors, established the relationship of ESV equivalent factor coefficients between Yinchuan City and China nationwide, and analyzed the response characteristics of ESV to the spatial and temporal changes of production-living-ecological land. [Results] The results show that: (1) The proportion of ecological land was the highest among the production-living-ecological land in Yinchuan City, but this proportion decreased during the study period, from 69.49% in 1990 to 57.68% in 2020. During the same period, the production land increased steadily, from 28.54% to 32.52%, and the living land expanded rapidly, from 2.37% to 9.81%. The dynamic degree of living land changed dramatically, but the dynamic degree trends of production land and ecological land gradually became smooth. (2) During the study period, the total amount of ESV increased by 384.2365 million yuan, and the positive effect of ecological land quality improvement on ESV was greater than the negative effect of the expansion of production land and living land on ESV. The contribution of regulating services to ESV was the largest and continued to increase, with the proportion increasing from 82.29% in 1990 to 83.76% in 2020, but the proportion of other services had decreased. The negative supply services are mainly related to the increase of water-consuming crop planting. (3) Urban expansion, energy base construction, and migration into the city are important reasons for the decline in ESV, resulting in lower ESV in the urban area, the Ningdong energy base, and key immigration areas; ecological construction is the main reason for the increase in ESV, with significant increases in areas such as the Bailitan Nature Reserve, the core area of the Yellow River Ecological Belt, and the grape production corridor at the eastern foot of the Helan Mountains. [Conclusion] In future development, it is necessary to improve the efficiency of living land and production land use to reduce the pressure of their expansion on ecological land, and to continuously improve the quality of ecological land to promote the healthy and sustainable development of the desert oasis ecosystem.

为了探究葵花籽油体富集物在冰淇淋中应用的可行性，以葵花籽油体富集物作为脂肪来源制备低脂冰淇淋，在无均质条件下研究葵花籽油体富集物添加量对低脂冰淇淋浆料和产品品质的影响。结果表明：冰淇淋浆料的黏度、储能模量和损耗模量都随葵花籽油体富集物添加量的增加而增大，当葵花籽油体富集物添加量为3.5%～4.0%时黏度与对照组相当；浆料中不易流动水和结合水的比例随着葵花籽油体富集物添加量的增加逐渐增大,在4.0%时达到最大；冰淇淋的膨胀率和抗融率随着葵花籽油体富集物添加量的增加先增大后减小；添加葵花籽油体富集物的冰淇淋色泽较差；冰淇淋的硬度和咀嚼性变化规律一致，都是随着葵花籽油体富集物添加量的增大呈现先减小后增大的趋势，弹性变化则相反;冰淇淋黏附性随着葵花籽油体富集物添加量的增加而升高；葵花籽油体富集物添加量为2.5%时冰淇淋感官评分最高。合适的葵花籽油体富集物添加量可以起到与棕榈油相似的效果，因此葵花籽油体富集物可以应用在冰淇淋中。In order to investigate the feasibility of using sunflower seed oil body enrichment in ice cream,low fat ice cream was prepared with sunflower seed oil body enrichment as the fat under the condition of non-homogenization. The effect of the dosage of the oil body enrichment on the quality of low fat ice cream slurry and product was explored. The results showed that the viscosity, storage modulus and loss modulus of ice cream slurry increased with the increase of the oil body enrichment dosage. When the dosage of oil body enrichment was 3.5%- 4.0%, the viscosity was equivalent to that of the control group. The proportion of non-flowing water and bound water in the slurry increased gradually with the increase of the dosage of oil body enrichment, reaching the maximum at 4.0%. The expansion rate and anti-melting rate of ice cream products first increased and then decreased as the increase of the oil body enrichment dosage. The color of ice cream with sunflower seed oil body enrichment was poor. The hardness and chewability of ice cream showed the same change law, which first decreased and then increased with the increase of the oil body enrichment dosage,while the elasticity changed in the opposite direction. The adhesion of ice cream increased with the increase of the oil body enrichment dosage. The sensory score of ice cream was the highest when the dosage of oil body enrichment was 2.5%. The appropriate dosage of sunflower seed oil body enrichment can produce a similar effect as palm oil, and sunflower seed oil body enrichment can be applied in ice cream.

Industrial heat sources (IHSs) are major contributors to energy consumption and environmental pollution, making their accurate detection crucial for supporting industrial restructuring and emission reduction strategies. However, existing models either focus on single-class detection under complex backgrounds or handle multiclass tasks for simple targets, leaving a gap in effective multiclass detection for complex scenarios. To address this, we propose a novel multiclass IHS detection model based on the YOLOv8-FC framework, underpinned by the multiclass IHS training dataset constructed from optical remote sensing images and point-of-interest (POI) data firstly. This dataset incorporates five categories: cement plants, coke plants, coal mining areas, oil and gas refineries, and steel plants. The proposed YOLOv8-FC model integrates the FasterNet backbone and a Coordinate Attention (CA) module, significantly enhancing feature extraction, detection precision, and operational speed. Experimental results demonstrate the model's robust performance, achieving a precision rate of 92.3% and a recall rate of 95.6% in detecting IHS objects across diverse backgrounds. When applied in the Beijing–Tianjin–Hebei (BTH) region, YOLOv8-FC successfully identified 429 IHS objects, with detailed category-specific results providing valuable insights into industrial distribution. It shows that our proposed multiclass IHS detection model with the novel YOLOv8-FC approach could effectively and simultaneously detect IHS categories under complex backgrounds. The IHS datasets derived from the BTH region can support regional industrial restructuring and optimization schemes. [ABSTRACT FROM AUTHOR]

Effective production, living, and ecological space allocation is essential for improving and optimizing urban space development. In this study, we proposed a production–living–ecological space (PLES) identification method based on Point of Interest (POI) data and China Land Cover Dataset (CLCD) to identify PLESs in Xuzhou City for the years 2012, 2018, and 2022, with an average recognition accuracy of 89.81%. Moreover, the land-use transfer matrix, center of gravity migration, and Geo-detector were used to reveal the spatiotemporal pattern evolution of PLESs. The results showed that: (1) The distribution of PLESs presented significant differentiation between Urban Built-Up Area (UBUA) and Non-Urban Built-Up Area (NUBUA). UBUA was mainly composed of living spaces, while NUBUA was primarily characterized by production–ecological spaces. (2) The intensive utilization of urban land led to an increase in the area of multifunctional spaces, while the complexity of urban space increased. (3) During 2012 to 2022, the center of gravity of PLESs remained relatively stable. The moving distances were all less than 1 km (except for ecological space from 2012 to 2018). (4) The evolution of PLESs was closely linked with socio-economic factors, and the interactions between the factors also had a significant driving effect on PLESs. [ABSTRACT FROM AUTHOR]

ObjectiveThe objective of the study was to investigate whether the sequence of oocyte retrieval and salpingectomy for hydrosalpinx affects pregnancy outcomes of in vitro fertilization and embryo transfer (IVF-ET) patients.Study DesignThere were 1,610 bilateral hydrosalpinx patients who underwent laparoscopy salpingectomy and IVF-ET/intracytoplasmic sperm injection (ICSI) from January 2009 to December 2018. They were divided into two groups: oocyte retrieval first group: 235 accepted oocyte retrieval before salpingectomy; operation first group: 1,375 accepted oocyte retrieval after salpingectomy. The basic information and pregnancy outcomes of the two groups were compared. The pregnancy outcomes and influencing factors were analyzed among patients at different starting times of frozen-thawed embryo transfer (FET) or oocyte retrieval after the salpingectomy.ResultsPatients in the oocyte retrieval first group had higher levels of basal follicle stimulating hormone and lower anti-Mullerian hormone levels (P 0.05). The live birth rates of patients ≥35 years old in the operation first group and the oocyte retrieval first group were not significantly different (29.3% vs. 23.3%, P = 0.240). After adjusting for age and antral follicle count (AFC), oocyte retrieval 4–6 and 7–12 months after the operation had higher accumulated pregnancy rates [OR 1.439 (1.045–1.982), P = 0.026; OR 1.509 (1.055–2.158), P = 0.024] and higher accumulated live birth rates [OR 1.419 (1.018–1.977), P = 0.039; OR 1.544 (1.068–2.230), P = 0.021]. No significant difference was observed in the pregnancy outcomes of frozen embryo transfer at different times after salpingectomy (P > 0.05).ConclusionNo contamination of the embryo or infection was observed in patients who underwent oocyte retrieval before the operation. The interval between the operation and frozen embryo transfer did not affect the pregnancy outcomes. After adjusting for age and AFC, patients who underwent oocyte retrieval 4–6 and 7–12 months after the operation had higher accumulated pregnancy rates and live birth rates.

The construction and optimization of urban green infrastructure (UGI) are regarded as effective strategies for harmonizing the natural landscape with human activities, particularly in ecologically vulnerable areas in the Upper Yellow River Basin, China. However, there is little attention paid to the scale effects and object effects as well as an absence of comprehensive assessments regarding landscape stability. Taking the Four-Lake Hydrographic Network (FLHN) in Shizuishan, a prefecture-level city, as an example, this study focuses on identifying the important sources of UGI by integrating both regional and interregional perspectives utilizing morphological spatial pattern analysis (MSPA). UGI networks were constructed and optimized based on trade-offs and synergizing relationships between individual objects using the minimum cumulative resistance (MCR) model, and the UGI network's stability combined centrality and connectivity aspects, which were subsequently assessed. The results showed that a total of 19 important sources covering an area of 105.07 km2 were identified in the FLHN, integrating both regional and interregional levels. It was deemed unnecessary to maintain lengths of 7.79 km key corridors, 9.42 km general corridors, and 29.89 km fragile corridors; furthermore, there was no longer a requirement to upgrade an additional 5.51 km of general corridors and 25.78 km of any corridor, as UGI corridors were extracted based on a trade-off and synthesized objective methodology. The overall connectivity index value (OG) of UGI stability with respect to the multi-objective model demonstrated superior performance compared to the same index in scenarios involving the use of a single-objective approach and the straightforward overlay of each object. This study reveals the multifaceted requirements of urban landscape security and sustainability, indicating that multi-scale and multi-objective approaches in territorial space planning not only ensure the integrity of the landscape patterns but also reduce the costs associated with landscape construction. This model can be utilized to implement urban landscape entity protection and restoration for landscapes with various geographical characteristics, and it can provide valuable guidance for similar areas. [ABSTRACT FROM AUTHOR]

The distribution of industrial heat sources (IHSs) is a crucial indicator for evaluating energy consumption and air pollution levels. However, there is a notable lack of IHS datasets in China that are frequently updated, span long periods, contain detailed characteristic information, have been individually validated and are publicly available. In this study, IHS datasets from China between 2012 and 2021 were constructed using the Visible Infrared Imaging Radiometer Suite (VIIRS) I Band 375 m NRT Active Fire/Hotspots (ACF) Product (VNP14IMGTDL_NRT) to monitor and analyse large‐scale IHSs. First, a density segmentation method based on an improved K‐means algorithm using ACF data and spatial topological correlation analysis was conducted to construct the IHS. Then, 4410 records covering China between 2012 and 2021, with 21 attributes, were obtained and verified, with an individual identification precision of 95.08% via manual verification based on high‐resolution remote‐sensing images and point of interest (POI) data. Finally, the trend of the spatiotemporal variation in IHSs was analysed using a long time series. The results showed that the spatial distribution of IHSs in China from 2012 to 2021 exhibited local aggregation and a gradual shift from east to west. In addition, the number of IHSs in China showed an initial increasing trend from 2012 to 2014, followed by a decrease since 2014, consistent with national energy reform‐related policies. The results of this study indicate the temporal variation in IHSs, enhance the precision of identifying fire location categories and demonstrate the potential for improving energy efficiency, reducing emissions and ensuring sustainable development in China. [ABSTRACT FROM AUTHOR]

Arid oasis ecosystems are susceptible and fragile ecosystems on Earth. Studying the interaction between deserts, oases, and impervious surfaces is an essential breakthrough for the harmonious and sustainable development of people and land in drylands. Based on gridded data such as land use and NDVI, this article analyzes the interaction characteristics between oases, deserts, and impervious surfaces in northern Egypt and examines their dynamics using modeling and geographic information mapping methods. The results show the following: In terms of the interaction between deserts and oases, the primary manifestation was the expansion of oases and the reduction of deserts. During the study period, the oases in the Nile Delta and Fayoum District increased significantly, with the area of oases in 2020 being 1.19 times the area in 2000, which shows a clear trend of advance of people and retreat of sand. The interaction between oases and impervious surfaces was mainly observed in the form of the spread of impervious surfaces on arable land into oases. During the study period, the area of impervious surfaces increased 2.32 times. The impervious surface expanded over 1903.70 km2 of arable land, accounting for 66.67% of the expanded area. The central phenomenon between the impervious surface and the desert was the encroachment of the covered area of the impervious surface into the desert, especially around the city of Cairo. Population growth and urbanization are the two central drivers between northern Egypt's oases, deserts, and impervious surfaces. The need for increased food production due to population growth has forced oases to move deeper into the desert, and occupation of arable land due to urbanization has led to increasing pressure on arable land, creating a pressure-conducting dynamic mechanism. Finally, countermeasures for sustainable regional development are suggested. [ABSTRACT FROM AUTHOR]

Land use change has a significant impact on the sustainability of ecosystems, and ecological security patterns (ESPs) can improve environmental quality through spatial planning. This study explored a multi-scenario ESP framework by integrating future land use simulation (FLUS) and minimum cumulative resistance (MCR) for urban agglomeration along the Yellow River Basin (YRB) in Ningxia. The research involved simulating land use change in 2035 under four development scenarios, identifying ecological security networks, and evaluating network stability for each scenario. The study revealed that the ecological sources under different development scenarios, including a natural development scenario (NDS), an economic development scenario (EDS), a food security scenario (FSS), and an ecological protection scenario (EPS), were 834.82 km2, 715.46 km2, 785.56 km2, and 1091.43 km2, respectively. The overall connectivity values (OG) for these scenarios were 0.351, 0.466, 0.334, and 0.520, respectively. It was found that under an EPS, the ESPs had the largest area of ecological sources and the most stable ecological network structure, which can effectively protect natural habitats. This study provides a valuable method for identifying ESPs that can respond to diversity and the uncertainty of future development. It can assist decision-makers in enhancing the ecological quality of the study area while considering various development scenarios. [ABSTRACT FROM AUTHOR]

It is crucial to detect and classify industrial heat sources for sustainable industrial development. Sustainable Development Science Satellite 1 (SDGSAT-1) thermal infrared spectrometer (TIS) data were first introduced for detecting industrial heat source production areas to address the difficulty in identifying factories with low combustion temperatures and small scales. In this study, a new industrial heat source identification and classification model using SDGSAT-1 TIS and Landsat 8/9 Operational Land Imager (OLI) data was proposed to improve the accuracy and granularity of industrial heat source recognition. First, multiple features (thermal and optical features) were extracted using SDGSAT-1 TIS and Landsat 8/9 OLI data. Second, an industrial heat source identification model based on a support vector machine (SVM) and multiple features was constructed. Then, industrial heat sources were generated and verified based on the topological correlation between the identification results of the production areas and Google Earth images. Finally, the industrial heat sources were classified into six categories based on point-of-interest (POI) data. The new model was applied to the Beijing–Tianjin–Hebei (BTH) region of China. The results showed the following: (1) Multiple features enhance the differentiation and identification accuracy between industrial heat source production areas and the background. (2) Compared to active-fire-point (ACF) data (375 m) and Landsat 8/9 thermal infrared sensor (TIRS) data (100 m), nighttime SDGSAT-1 TIS data (30 m) facilitate the more accurate detection of industrial heat source production areas. (3) Greater than 2~6 times more industrial heat sources were detected in the BTH region using our model than were reported by Ma and Liu. Some industrial heat sources with low heat emissions and small areas (53 thermal power plants) were detected for the first time using TIS data. (4) The production areas of cement plants exhibited the highest brightness temperatures, reaching 301.78 K, while thermal power plants exhibited the lowest brightness temperatures, averaging 277.31 K. The production areas and operational statuses of factories could be more accurately identified and monitored with the proposed approach than with previous methods. A new way to estimate the thermal and air pollution emissions of industrial enterprises is presented. [ABSTRACT FROM AUTHOR]

The prevalent high-energy, high-pollution and high-emission economic model has led to significant air pollution challenges in recent years. The industrial sector in the Beijing–Tianjin–Hebei (BTH) region is a notable source of atmospheric pollutants, with industrial heat sources (IHSs) being primary contributors to this pollution. Effectively managing emissions from these sources is pivotal for achieving air pollution control goals in the region. A new three-stage model using multi-source long-term data was proposed to estimate atmospheric, delicate particulate matter (PM2.5) concentrations caused by IHS. In the first stage, a region-growing algorithm was used to identify the IHS radiation areas. In the second and third stages, based on a seasonal trend decomposition procedure based on Loess (STL), multiple linear regression, and U-convLSTM models, IHS-related PM2.5 concentrations caused by meteorological and anthropogenic conditions were removed using long-term data from 2012 to 2021. Finally, this study analyzed the spatial and temporal variations in IHS-related PM2.5 concentrations in the BTH region. The findings reveal that PM2.5 concentrations in IHS radiation areas were higher than in background areas, with approximately 33.16% attributable to IHS activities. A decreasing trend in IHS-related PM2.5 concentrations was observed. Seasonal and spatial analyses indicated higher concentrations in the industrially dense southern region, particularly during autumn and winter. Moreover, a case study in Handan's She County demonstrated dynamic fluctuations in IHS-related PM2.5 concentrations, with notable reductions during periods of industrial inactivity. Our results aligned closely with previous studies and actual IHS operations, showing strong positive correlations with related industrial indices. This study's outcomes are theoretically and practically significant for understanding and addressing the regional air quality caused by IHSs, contributing positively to regional environmental quality improvement and sustainable industrial development. [ABSTRACT FROM AUTHOR]