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[Objective] This study aimed to establish a preparation process for starch-lipid complex with high resistant starch （RS） content and to explore the effects of process parameters on the anti-digestibility of the complex. [Methods] Using RS content as the indicator, one-way experimental and orthogonal designs were employed to study the effects of temperature and time parameters during the pretreatment of high amylose corn starch （HA） and its complexation with stearic acid （SA）. The physicochemical properties, anti-digestibility, and hydration characteristics of the HA-SA complex prepared by the optimal process were analyzed. [Results] Increasing pretreatment temperature in the gelatinization temperature range, prolonging the pre-treatment time, and complexing temperature above 75 ℃ all led to a significant decrease in RS content of HA-SA （P＜0.05）. The optimal process was as following: HA being pretreated at an annealing temperature of 85 ℃ for 12 h, and then complexed with SA at 75 ℃ for 90 min. The prepared HA-SA showed the V-type crystalline pattern and entire starch granules shape, and was characterized as the type I complex. It also presented the significantly enhanced thermal stability, bettered anti-digestibility, and lowered swelling power than HA （P＜0.05）. [Conclusion] Annealing temperature pretreatment and optimal complexation temperature favored to prepare the starch-lipid complex with higher anti-digestibility and entire granule structure. Excessive thermal strength during pretreatment causing excessive gelatinization could impede the formation of RS in the complexes. And a complexation temperature over 75 ℃ led to the disassociation of the complexation, decreasing the RS content. Annealing pretreatment preserved the entire starch granule of HA, which was one of the reasons for the higher digestibility of HA-SA.

Context. Low precipitation and soil erosion are critical threats to sustainable agricultural development in the north-western coastal zone of Egypt. Conservation tillage may offer a good opportunity to mitigate these threats; however, switching from traditional tillage to conservation tillage causes initial challenges such as soil compaction and erosion. Aims. This study was designed in order to assess the effects of various tillage practices on soil bulk density, volumetric water content, runoff rate, runoff initiation time, soil loss, sediment yield rate and wheat (Triticum aestivum L.) yield in a cultivated basin area. Furthermore, to investigate the efficacy of various rainfall intensities in generating runoff in a micro-catchment area. Methods. Under rainfall simulation, five rainfall intensities (14, 21, 30, 36, and 45 mm [h.sup.-1]) and three tillage practices (contour tillage, CT; traditional tillage, TT; and no tillage, NT) were investigated. Key results. Under various rainfall intensities, the CT treatment significantly reduced surface runoff compared with the TT and NT treatments. For the 30 mm [h.sup.-1] rainfall intensity, the CT treatment decreased sediment yield rate by 58.7% and 49.4% compared with NT and TT treatments, respectively. Furthermore, the CT treatment significantly increased precipitation use efficiency by 11.8% and 19.9% compared with TT and NT treatments, respectively. Additionally, the CT increased grain yield by 12.3% more than TT and 21% more than NT. Conclusions and implications. Consequently, it is preferable to encourage farmers to use CT practices when transitioning from traditional tillage to conservation tillage. Moreover, soil compaction and smoothing may contribute to enhance the generated runoff on the micro-catchment area. Keywords: precipitation use efficiency, rainfall intensity, runoff, soil erosion, soil moisture, soil properties, tillage practices, wheat yield., Introduction Low precipitation, severe water loss and soil erosion are major environmental threats to crop production, and are the most common cause of land degradation in arid and semiarid areas [...]

A rational landslide susceptibility mapping (LSM) can minimize the losses caused by landslides and enhance the efficiency of disaster prevention and reduction. At present, frequency ratio (FR), information value (IV), and certainty factor (CF) are widely used to quantify the relationships between landslides and their causative factors; however, it remains unclear which method is the most effective. Moreover, existing landslide susceptibility zoning methods lack full automation; thus, the results are full of uncertainties. To address this, the FR, IV, and CF were used to analyze the relationship between landslides and causative factors. Subsequently, three distinct sets of models were developed, namely random forest models (RF_FR, RF_IV, and RF_CF), support vector machine models (SVM_FR, SVM_IV, and SVM_CF), and logistic regression models (LR_FR, LR_IV, and LR_CF) using the analysis results as inputs. A Gaussian mixture model (GMM) was introduced as a new method for landslide susceptibility zoning, classifying the LSM into five distinct levels. An accuracy evaluation of the models and a rationality analysis of the LSM indicated that the FR is superior to the IV and CF in quantifying the relationship between landslides and causative factors. Additionally, the quantile method was employed as a comparative approach to the GMM, further validating the effectiveness of the GMM. This research contributes to more effective and efficient LSM, ultimately enhancing landslide prevention measures. [ABSTRACT FROM AUTHOR]

This study introduces a novel approach to landslide detection by incorporating the Spatial and Band Refinement Convolution (SBConv) module into the U-Net architecture, to extract features more efficiently. The original U-Net architecture employs convolutional layers for feature extraction, during which it may capture some redundant or less relevant features. Although this approach aids in building rich feature representations, it can also lead to an increased consumption of computational resources. To tackle this challenge, we propose the SBConv module, an efficient convolutional unit designed to reduce redundant computing and enhance representative feature learning. SBConv consists of two key components: the Spatial Refined Unit (SRU) and the Band Refined Unit (BRU). The SRU adopts a separate-and-reconstruct approach to mitigate spatial redundancy, while the BRU employs a split-transform-and-fuse strategy to decrease band redundancy. Empirical evaluation reveals that models equipped with SBConv not only show a reduction in redundant features but also achieve significant improvements in performance metrics. Notably, SBConv-embedded models demonstrate a marked increase in Recall and F1 Score, outperforming the standard U-Net model. For instance, the SBConvU-Net variant achieves a Recall of 75.74% and an F1 Score of 73.89%, while the SBConvResU-Net records a Recall of 70.98% and an F1 Score of 73.78%, compared to the standard U-Net's Recall of 60.59% and F1 Score of 70.91%, and the ResU-Net's Recall of 54.75% and F1 Score of 66.86%. These enhancements in detection accuracy underscore the efficacy of the SBConv module in refining the capabilities of U-Net architectures for landslide detection of multisource remote sensing data. This research contributes to the field of landslide detection based on remote sensing technology, providing a more effective and efficient solution. It highlights the potential of the improved U-Net architecture in environmental monitoring and also provides assistance in disaster prevention and mitigation efforts. [ABSTRACT FROM AUTHOR]

Absolute measurements of cerebral blood flow (CBF) are an important endpoint in studies of cerebral pathophysiology. Currently no accepted method exists for in vivo longitudinal monitoring of CBF with high resolution in rats and mice. Using three-dimensional Doppler Optical Coherence Tomography and cranial window preparations, we present methods and algorithms for regional CBF measurements in the rat cortex. Towards this end, we develop and validate a quantitative statistical model to describe the effect of static tissue on velocity sensitivity. This model is used to design scanning protocols and algorithms for sensitive 3D flow measurements and angiography of the cortex. We also introduce a method of absolute flow calculation that does not require explicit knowledge of vessel angles. We show that OCT estimates of absolute CBF values in rats agree with prior measures by autoradiography, suggesting that Doppler OCT can perform absolute flow measurements in animal models.

Objective $ This work was aimed to analysis the influence of steaming processing on the extraction, physio¬chemical properties, and digestion properties of sweet potato soluble dietary fiber (SDF). Methods: The response surface methodology and desirability function were conducted to optimize the solid-liquid ratio, extract temperature, and extract time of sweet potato SDF extraction for higher yield and total sugar content. SDF from steamed sweet potato (SDF-S) and from fresh sweet potato (SDF-F) were extracted by the optimized parameters. The yield, polysaccharide composition, and dietary fiber content, as well as water holding capability and oil holding capability, were measured to compare the differences of two SDF. Besides, simulated digestion in vitro was performed to assess the digestion properties. Results: The optimized parameters were 1#16 of solid-liquid ration, 40 $ of extraction temperature, and 40 min extraction time. The SDF-S showed significantly higher yield [(6.13±0.25%) vs (2.89±0.18)%], neutral polysaccharide content [(59.31 ± 0.73)% vs (46.83±0.63)%], acidic polysaccharide content [(25.36±0.48)% vs (9.60±0.14)%], dietary fiber content [(54.71±6.70)% vs (35.69±3.25)%], water holding capability [(4.60±0.31) g/g vs (3.27±0.21) g/g] and oil holding capa¬bility [(3.30±0.40) g/g vs (1.82±0.28) g/g] than SDF-F (P<0.05), while the SDF-F showed better resistance to digestion than SDF-S. Conclusion: Steaming processing improved the accessibility of sweet potato SDF but weakened its resistance to digestion.en [ABSTRACT FROM AUTHOR]

Some nutritional factors have been suggested to improve postoperative outcomes in rotator cuff (RC) repair, but dietary effects on the recovery speed after the surgery remain undefined. To investigate the potential roles of dietary habits in this context, we analyzed the 12-month follow-up data of 55 patients with RC repair and found that these patients could be categorized into a rapid recovery group (n = 35) and slow recovery group (n = 20) according to their postoperative recovery patterns. Group-based logistic analysis revealed that habitual intakes of meat (OR = 1.84, 95%CI, 1.22–2.76, p = 0.003), fruits (OR = 2.33, 95%CI, 1.26–5.67, p = 0.01), and wheat-flour foods (OR = 1.62, 95%CI, 1.2–2.25, p = 0.002) were significantly associated with rapid recovery. Moreover, among all intakes of wheat-flour foods, intakes of steamed and boiled flour products were also associated with rapid recovery. Further mediation analysis showed that eosinophilic granulocytes (EOs) significantly mediated the association between rapid RC recovery and the habitual intakes of meat (mediation proportion = 17.5%, P-mediation < 0.0001), fruits (17.9%, p < 0.0001), and wheat-flour foods (11.4%, p < 0.0001). Thus, our study suggests that certain dietary habits play beneficial roles in the context of postoperative recovery for RC repair. [ABSTRACT FROM AUTHOR]