Stress background and rock fractures revealed by ultrasonic borehole television in the Fankou Lead-Zinc Mine

The stress background and rock fractures are essential factors affecting the stability of mines. In order to better understand the in situ stress background and rock fractures in the Guangdong Fankou Mine, we use ultrasonic borehole television scanning to measure rock fractures. The results indicate that rock fractures are intensively distributed at depths of −360 m to −450 m below the surface, suggesting the effect of intensive mining activities. The present maximum horizontal principal stress direction is NWW, which is consistent with the regional tectonic stress field direction. Systematic measurement of rock fractures is fundamental for further three-dimensional geological modeling and is significant for mining engineering

Methylprednisolone as Adjunct to Endovascular Thrombectomy for Large-Vessel Occlusion Stroke

Importance It is uncertain whether intravenous methylprednisolone improves outcomes for patients with acute ischemic stroke due to large-vessel occlusion (LVO) undergoing endovascular thrombectomy. Objective To assess the efficacy and adverse events of adjunctive intravenous low-dose methylprednisolone to endovascular thrombectomy for acute ischemic stroke secondary to LVO. Design, Setting, and Participants This investigator-initiated, randomized, double-blind, placebo-controlled trial was implemented at 82 hospitals in China, enrolling 1680 patients with stroke and proximal intracranial LVO presenting within 24 hours of time last known to be well. Recruitment took place between February 9, 2022, and June 30, 2023, with a final follow-up on September 30, 2023.InterventionsEligible patients were randomly assigned to intravenous methylprednisolone (n = 839) at 2 mg/kg/d or placebo (n = 841) for 3 days adjunctive to endovascular thrombectomy. Main Outcomes and Measures The primary efficacy outcome was disability level at 90 days as measured by the overall distribution of the modified Rankin Scale scores (range, 0 [no symptoms] to 6 [death]). The primary safety outcomes included mortality at 90 days and the incidence of symptomatic intracranial hemorrhage within 48 hours. Results Among 1680 patients randomized (median age, 69 years; 727 female [43.3%]), 1673 (99.6%) completed the trial. The median 90-day modified Rankin Scale score was 3 (IQR, 1-5) in the methylprednisolone group vs 3 (IQR, 1-6) in the placebo group (adjusted generalized odds ratio for a lower level of disability, 1.10 [95% CI, 0.96-1.25]; P = .17). In the methylprednisolone group, there was a lower mortality rate (23.2% vs 28.5%; adjusted risk ratio, 0.84 [95% CI, 0.71-0.98]; P = .03) and a lower rate of symptomatic intracranial hemorrhage (8.6% vs 11.7%; adjusted risk ratio, 0.74 [95% CI, 0.55-0.99]; P = .04) compared with placebo. Conclusions and Relevance Among patients with acute ischemic stroke due to LVO undergoing endovascular thrombectomy, adjunctive methylprednisolone added to endovascular thrombectomy did not significantly improve the degree of overall disability.Trial RegistrationChiCTR.org.cn Identifier: ChiCTR210005172

Dietary Protein Intake Dynamics in Elderly Chinese from 1991 to 2018

Unique rapid urbanization-related changes in China may affect the dietary protein intake of the aging population. We aimed to evaluate trends in dietary protein intake and major food sources of protein and estimate conformity to the dietary reference intakes (DRIs) in the elderly Chinese population. A sample of 10,854 elderly adults aged 60 years or older, drawn from 10 waves of the China Health and Nutrition Survey (CHNS) between 1991 and 2018, was included. Protein intake data were obtained on the basis of 3-day, 24 h dietary recalls. The dietary protein intake among elderly Chinese individuals declined from 63.3 g/day to 57.8 g/day over the 28-year period, with a −0.032 ± 0.0001 g/day change per year (p < 0.05). There was a significant increase in the proportion of subjects with a protein intake level below the estimated averaged requirement (EAR) and a reduction in the proportion of subjects consuming protein above the recommended nutrient intake (RNI) across all population subgroups. Cereals ranked as the major sources of dietary protein, although their contribution to dietary protein gradually decreased as time went on. The contribution from meat steadily rose from 18.2% in 1991 to 28.7% in 2018. The proportion of energy gained from fat increased notably, reaching 34.2% in 2018. The elderly Chinese population experienced a significant reduction in dietary protein intake. Although the transformation of dietary patterns had positive effects on improving protein quality due to increases in animal source food, some elderly Chinese individuals currently face the risk of inadequate dietary protein intake

LaFe11Co0.8Si1.2/Al magnetocaloric composites prepared by hot pressing

The microstructure, mechanical properties, thermal transfer performance, and magnetocaloric effect were investigated in LaFe11Co0.8Si1.2/10 wt% Al composites prepared by hot pressing. The Al particles can deform and form a homogenous matrix during compacting in these composites. Pure Al metal reacts slowly with the LaFe11Co0.8Si1.2 compound at temperatures near 873 K. The introduction of Al particles significantly enhances the mechanical and thermal transfer properties, while slightly degrades the magnetocaloric effect. At room temperature, aforementioned composites show maximum entropy change values of 5.1-5.9 J/kg K under a magnetic change of 2 T, high thermal conductivity of 9.9-17.0 W/m K, and high compressive strength of 106-186 MPa. (C) 2020 Published by Elsevier B.V

Automated Landslides Detection for Mountain Cities Using Multi-Temporal Remote Sensing Imagery

Landslides that take place in mountain cities tend to cause huge casualties and economic losses, and a precise survey of landslide areas is a critical task for disaster emergency. However, because of the complicated appearance of the nature, it is difficult to find a spatial regularity that only relates to landslides, thus landslides detection based on only spatial information or artificial features usually performs poorly. In this paper, an automated landslides detection approach that is aiming at mountain cities has been proposed based on pre- and post-event remote sensing images, it mainly utilizes the knowledge of landslide-related surface covering changes, and makes full use of the temporal and spatial information. A change detection method using Deep Convolution Neural Network (DCNN) was introduced to extract the areas where drastic alterations have taken place; then, focusing on the changed areas, the Spatial Temporal Context Learning (STCL) was conducted to identify the landslides areas; finally, we use slope degree which is derived from digital elevation model (DEM) to make the result more reliable, and the change of DEM is used for making the detected areas more complete. The approach was applied to detecting the landslides in Shenzhen, Zhouqu County and Beichuan County in China, and a quantitative accuracy assessment has been taken. The assessment indicates that this approach can guarantee less commission error of landslide areal extent which is below 17.6% and achieves a quality percentage above 61.1%, and for landslide areas, the detection percentage is also competitive, the experimental results proves the feasibility and accuracy of the proposed approach for the detection landslides in mountain cities

Ru-Catalyzed Asymmetric Addition of Arylboronic Acids to Aliphatic Aldehydes via P-Chiral Monophosphorous Ligands

Chiral alcohols are among the most widely applied in fine chemicals, pharmaceuticals and agrochemicals. Herein, the Ru-monophosphine catalyst formed in situ was found to promote an enantioselective addition of aliphatic aldehydes with arylboronic acids, delivering the chiral alcohols in excellent yields and enantioselectivities and exhibiting a broad scope of aliphatic aldehydes and arylboronic acids. The enantioselectivities are highly dependent on the monophosphorous ligands. The utility of this asymmetric synthetic method was showcased by a large-scale transformation

Do Chinese Children Get Enough Micronutrients?

The aim of this study was to examine usual daily micronutrient intake of Chinese children based on data from the 2011 China Health and Nutrition Survey. We analyzed data from 4 to 17-year-old participants, who provided dietary data on three consecutive days combined with the household weighing method in 2011. Usual daily intake of each nutrient was estimated using a mixed effects model based on the China Food Composition published in 2009. The means, medians and percentages below Estimated Average Requirements (EAR) were reported for selected micronutrients, including calcium, sodium, potassium, iron, zinc, selenium, vitamin A, thiamine, riboflavin and vitamin C. For sodium and potassium, the means and the distribution of intakes were compared to the Adequate Intake (AI) level. The average usual daily intakes of all micronutrients increase with age, and the intakes of boys were found to be higher than girls in the same age group. The average calcium intake increased from 272 mg/day in 4–6 years to 391 mg/day in 14–17 years, but the percentage of inadequate calcium intake remained very high (>96%). The prevalence of inadequacy of calcium was the highest among the mineral nutrients reported in this study. As the requirements of micronutrients increased with age, the percentage of subjects with inadequate intake increased in the 11–17 years age groups. Among 14–17 years group, the percentages of study participants with dietary intakes of calcium, iron, zinc, selenium, vitamin A, thiamine, riboflavin and vitamin C below the EAR were 96.8%, 18.8%, 37.6%, 72.8%, 36.8%, 91.8%. 85.9% and 75.5%, respectively. Among 11–13 years group, the percentages of study participants with dietary intakes of iron, zinc and vitamin A below the EAR were 23.5%, 41.5%, and 41.6%, respectively. Thus, micronutrient deficiency is a problem in Chinese children. Nutrition education and intervention programs are needed to address these nutritional gaps

High-throughput characterization of the adiabatic temperature change for magnetocaloric materials

The potential applicability of a magnetocaloric material for solid-state refrigeration purposes mainly relies on its magnetocaloric effect (MCE). Since conventional measurements to assess MCE are generally time-consuming, it is uneasy to fast screen prominent magnetocaloric materials. Here, we have developed a high-throughput infrared characterization technique to feasibly evaluate the adiabatic temperature change of magnetocaloric materials. This method is applicable to both the second-order phase transition Gd and the first-order phase transition (FOPT) La-Fe-Si-based materials, allowing simultaneous measurement of the temperature changes induced by MCE of multiple samples. Moreover, it greatly facilitates the examination of the functional stability of FOPT magnetocaloric materials by accomplishing the cycling test in a short time. By repeatedly changing the magnetic field of 0-1.3-0 T in 0.25 Hz for La1.2Ce0.8Fe11Si2Hy, we observed the adiabatic temperature changes of 2.12 K for the first cycle and 1.85 K upon 100000 cycles. Correspondingly, the change in magnetocaloric response of the sample is visualized by the high-resolution infrared image, giving explanations for the evolution of MCE during cycling

Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance

The exponentially large discrete search space in mixed-precision quantization (MPQ) makes it hard to determine the optimal bit-width for each layer. Previous works usually resort to iterative search methods on the training set, which consume hundreds or even thousands of GPU-hours. In this study, we reveal that some unique learnable parameters in quantization, namely the scale factors in the quantizer, can serve as importance indicators of a layer, reflecting the contribution of that layer to the final accuracy at certain bit-widths. These importance indicators naturally perceive the numerical transformation during quantization-aware training, which can precisely and correctly provide quantization sensitivity metrics of layers. However, a deep network always contains hundreds of such indicators, and training them one by one would lead to an excessive time cost. To overcome this issue, we propose a joint training scheme that can obtain all indicators at once. It considerably speeds up the indicators training process by parallelizing the original sequential training processes. With these learned importance indicators, we formulate the MPQ search problem as a one-time integer linear programming (ILP) problem. That avoids the iterative search and significantly reduces search time without limiting the bit-width search space. For example, MPQ search on ResNet18 with our indicators takes only 0.06 seconds. Also, extensive experiments show our approach can achieve SOTA accuracy on ImageNet for far-ranging models with various constraints (e.g., BitOps, compress rate)