新型冠状病毒肺炎疫情期间血管外科急症救治的“SEAS”原则及策略

血管外科急症临床常见、病情凶险、死亡率高,在新型冠状病毒肺炎(COVID-19)防控期间的救治难度和风险增加。目前鲜见血管外科急诊手术相关原则和策略报道。本文结合血管外科疾病本身急诊和病变特点,以及疫情期间本中心诊疗体会,提出“SEAS”原则及策略,即遵循安全(safe)、有效(effective)的原则,采取避免或减少(avoidance)、简捷(simple)的策略,可在有效防控COVID-19疫情的同时,及时、安全、有效地开展血管外科急症救治。

Climate prediction of the seasonal sea-ice early melt onset in the Bering Sea

基于大尺度环流异常对海冰消融的影响过程,本文采用年际增量预测方法研制了白令海季节性海冰早期消融开始日期(EMO)的统计预测模型.预测模型选取了3个具有明确物理意义的预测因子:1月波弗特高压,前期11月东西伯利亚地区海平面气压,以及11月东欧平原积雪覆盖率。1月波弗特高压可以通过海气相互作用影响白令海地区海温异常,该海温异常能够从1月持续到3月,进而影响白令海EMO.11月东西伯利亚地区海平面气压与11月至次年2月北太平洋中纬度东部海温密切相关。伴随着北太平洋中纬度东部冷海温异常的出现,白令海地区会出现暖海温异常,进而导致白令海海冰范围减少,EMO较晚.1月北极偶极子异常是11月东欧平原积雪覆盖率影响次年白令海EMO的桥梁之一.1981-2022年的交叉检验结果表明:统计模型对白令海EMO具有较好的预测能力,预测与观测的EMO之间时间相关系数达到了0.45,超过了99%的置信水平.统计模型对白令海EMO正常年份和异常年份的预测准确率分别为60%和41%.

基于FE-SEA模型的整车气动噪声分析

以某款SUV车型为研究对象,将采用计算流体力学(Computational Fluid Dynamics,CFD)和声扰动方程(Acoustic Perturbation Equations,APE)获取的侧窗表面脉动压力作为激励,基于混合有限元-统计能量分析法(Finite Element-Statistical Energy Analysis,FE-SEA)提出一种全新的整车中频段气动噪声预测模型,通过阻抗管吸声系数试验逆推得到声学包材料参数,结合传递损失试验和基于声功率的降噪水平试验(Power Based Noise Reduction,PBNR)对整车混合模型进行调校对标,保证噪声传递路径的准确性。基于该模型,加载外流场对流和声学激励进行中频段气动噪声仿真,并将分析结果与气动噪声试验进行对比,验证该方法的可靠性。研究表明,在车型开发概念设计阶段采用基于声扰动方程与混合有限元-统计能量分析相结合的方法能有效精确预测气动噪声,为后续整车气动噪声性能的优化提升做铺垫。

Sea Cucumber Fishery in Aurora, Philippines

This study was conducted to provide a preliminary assessment of the sea cucumber fishery in Aurora, Philippines. This was conducted from February to June 2013. All sea cucumber gatherers and traders, obtained through snowball sampling, in each identified sea cucumber fishery area in six coastal municipalities (Baler, Dipaculao, Dinalungan, Casiguran, Dilasag and Dingalan) were interviewed using a structured interview schedule and focused group discussions (FGD). Results revealed that gathering sea cucumbers were accomplished by handpicking, skin diving or compressor diving. A total of 15 commercial species were regularly gathered. Out of this, three species are of very high economic value (≥Php 4000/kg) (Holothuria nobilis, Holothuria scabra, and Actinopyga lecanora). The average number of kilograms harvested per hour per trip ranges from 0.21 (Holothuria fuscopunctata) to 2.71 (Holothuria scabra), while the average size of commonly gathered sea cucumber varies among species with Holothuria lecanora showed an average length (29.26 cm) greater than recorded 24 cm. Processing mainly involves washing, slicing, boiling, drying and packing. Processed sea cucumbers or trepan were sold to middlemen or direct buyers who usually offered higher prices (36.36% up to 69.20%) than the former. Problems encountered by sea cucumber gatherers and traders include a decline in total catch, a shift in area of collection from intertidal zones to deeper waters, an increase in the number of hours spent in finding and gathering sea cucumbers, the use of compressors in gathering, the decline of larger species and gathering of smaller sizes in huge amount, the absence of conservation program for sea cucumber, and the lenient implementation of government policies with regards to coastal resources management.

Diversity, Abundance and Distribution Patterns of Epibenthic Echinoderms in Dungonab Bay, Red Sea, Sudan

The abundance, distribution and diversity of epibenthic echinoderm were investigated at Dungonab Bay in the Red Sea coastal water of the Sudan. Four permanent line transects were chosen. Eight (30 × 2) square metre belt transects along each permanent line transect at 20 metre intervals were used to collect data. The data were subjected to univariate and multivariate analyses. Spatial variations of epibenthic echinoderm abundance were assessed with one-way analysis of variance. Hierarchical agglomerative clustering was used to identify and illustrate the similarities in echinoderm abundance between line transects and between belt transects. Indices of richness (d), diversity (H'), evenness (J') and dominance (C) were used to explain the diversity of epibenthic echinoderm species. The distribution pattern of each echinoderm species was determined in each permanent line transect. A total of 986 individuals were recorded within sixteen species of epibenthic echinoderms in the four line transects. Holothuriidae was the dominant family (5 species and 342 individuals). The most abundant echinoderms species was Pearsonothuria graeffei (77 individuals, about 7.81%). Abundances intra-transects and intra-families were insignificant (f = 1.67, p = 0.183, df = 3 and f = 3.24, p = 0.083, df = 9, respectively). The highest values of Shannon-Wiener diversity index (H'), Pielou evenness index (J'), Margalef species richness index (d), and Simpson Dominance index (C) were 2.738, 0.9875, 2.791 and 0.07159, respectively. The distribution patterns of all species in the study transects varied between clumped and uniform, with the exception of Asthenosoma varium of the Echinothuridae family, which had clumped distribution patterns in all transects. The study concluded that Dungonab Bay supports rich and diverse communities of epibenthic echinoderms.

The Impact of Sea Level Rise on Roadway Design and Evacuation Routes in Delaware

As the global temperature continues to increase, the sea level continues to rise at a rapid rate that has never been seen before. This becomes an issue for many facets of life but one of the most impacted is the transportation infrastructure. Many people living in low elevation coastal areas can become trapped by flooding with no way in or out. With Delaware being a coastal state, this would affect a large portion of the population and will have detrimental effects over time if nothing is done to combat sea level rise. The issue with sea level rise in transportation is that once the roads become flooded, they become virtually unusable and detour routes would be needed. If all the roads in a coastal area were to be affected by sea level rise, the options for detours would become limited. This article looks at direct solutions to combat sea level rise and indirect solutions that would specifically help transportation infrastructure and evacuation routes in Delaware. There is not one solution that can fix every problem, so many solutions are laid out to see what is applicable to each affected area. Some solutions include defense structures that would be put close to the coast, raising the elevation of vulnerable roads throughout the state and including pumping stations to drain the water on the surface of the road. With an understanding of all these solutions around the world, the ultimate conclusion came in the form of a six-step plan that Delaware should take in order to best design against sea level rise in these coastal areas.

Effects of Natural Processes on Sea Level Change along the West African Coastline

Coastal hazards induced by meteo-marine forcing are exacerbated by sea level change along the West African coastline. Changes in sea level are induced by ocean processes such as ocean heat content and river discharge. However, although these processes control largely change in sea level, they remain poorly understood. This study analyzes changes in ocean heat content, river discharge, and sea level and establishes an interconnection between these parameters using several statistical methods over the 1993-2021 period. Results showed a significant correlation between sea level and ocean heat content at 2000 m depth. The yearly minimum value appears in July from Cote d’Ivoire to Benin, whilst this value appears in June in Nigeria. The temporal variability of ocean heat content, river discharge and sea level along the West African coastline exhibits three or four periods interrupted by some breakpoints with unequal duration. The results indicate that the 1993-2000 period was dominated by an increasing ocean heat content along the coastline, while the period after the 2000s exhibits mostly a decreasing trend. Positive and negative trends characterized river discharge and sea level along this coastline. The result of multiple linear regression between sea level, river discharge and ocean heat content is a good approximation of sea level trend along the West African coastline. The results of this study could be used to predict future sea level trends along the coast.

The Influence of Aerial Exposure on Sea Anemones Aulactinia veratra Mucin Genes Expression Using the RNA Sequencing

Mucin genes are the main component of mucus. The sea anemone species, Aulactinia veratra (Phylum Cnidaria) contains different types of mucin genes. In the intertidal zone, A. veratra is found to be exposed to air during the low tide and produces large quantities of mucus as an external covering. The relation between low tide and mucus secretion is still unclear, and what is the role of mucin during arial exposure is not yet investigated. This study hypothesised that the mucin genes in A. veratra would have significantly high expression in response to aerial exposure. Therefore, the aim of current study was to examine and analyses the response of A. veratra mucins in response to an experiment involving three hours of aerial exposure. To achieve this, aim the RNA-sequencing and bioinformatics analyses were used to examine the expression profile of A. veratra mucin genes in response to aerial exposure. The generated results have shown that, Mucin4-like and mucin5B-like were up-regulated in response to the three hours of aerial exposure in A. veratra. This finding shows a significant role of mucin5B-like and mucin4-like genes in response to air stress at low tide. The data generated from this study could be used in conjunction with future mucin gene studies of sea anemones and other cnidarians to compare A. veratra mucin gene expression results across time, and to extend our understanding of mucin stress response in this phylum.

Formulating Dead Sea Mud in Cosmetic Products, Its Effects on Skin, and the Underlying Biological Mechanism: A Review

Research Background: The marketing of cosmetic products derived from Dead Sea (DS) mud has undergone significant evolution, transforming from simple souvenirs into a large-scale cosmetic industry offering a diverse array of products. DS mud is utilized both as pure mud for home spa treatments and as an active ingredient in cosmetic and cosmeceutical formulations. Its global appeal is largely due to its natural, health-oriented image, which aligns with consumer preferences and provides assurance regarding its use in skincare. Research Objectives: This review examines the published data related to the rationale for formulating DS mud in cosmetics, the biological and cosmetic effects of DS mud on the skin, and the speculated bio-mechanisms underlying these effects. Methods: We screened relevant literature on DS mud collected from the shores of the Dead Sea in Jordan and Israel. Publications on mineral muds excavated in different locations around the globe, as well as studies on the biological mechanisms of other DS minerals, were also reviewed as indications and supportive recommendations. Summarizing the vast collected data into a comprehensive review was undertaken to expose readers to the various aspects of DS mud in cosmetics. Results: The primary reason for formulating DS mud in skincare products is its deep cleansing and skin detoxification properties. Consequently, it is often incorporated into rinse-off masks, soaps, and scrubbing products. Additionally, DS mud is used in leave-on products and sheet masks. Cosmeceutical applications of DS mud, recommended for various skin conditions, offer complementary treatments to improve the quality of life for people with skin diseases. The physicochemical and biological effects of DS mud are driven by its rich mineral ion composition, including magnesium, calcium, sodium, potassium, zinc, and strontium—elements known to improve skin barrier function, enhance hydration, and reduce inflammation. The high salt concentration induces moderate ionic osmotic stress, stimulating cellular growth and hydration pathways. Moreover, DS mud’s anti-microbial properties further contribute to its therapeutic potential. Ongoing innovations in formulation techniques continue to expand the applications of DS mud, including blending it with other active ingredients, developing novel application methods, and refining manufacturing processes to improve product quality and efficacy. Conclusions: DS mud remains a valuable ingredient in modern skincare due to its rich mineral content and therapeutic properties. Ongoing research and technological advancements promise further innovations, reinforcing its status as a natural and effective component in the global cosmetics industry.

Soil Cover in the Eastern Part of the Dried Bed of the Aral Sea

The greatest environmental disaster in Central Asiathe drying up of the Aral Seahas led to the formation of a new terrain, extending over 2.7 million hectares in Uzbekistan. This newly formed terrain is dynamically developing, with emerging soil formations replacing bottom sediments. This paper analyzes the results of a study on soil formation in the eastern part of the dried-up seabed, focusing on the influence of natural processes occurring there.

Optimizing the LSTM Deep Learning Model for Arctic Sea Ice Melting Prediction

The National Oceanic and Atmospheric Administration reports a 95% decline in the oldest Arctic ice over the last 33 years [1], while the National Aeronautics and Space Administration states that summer Arctic Sea Ice Extent (SIE) is shrinking by 12.2% per decade since 1979 due to warmer temperatures [2]. Given the rapidly changing Arctic conditions, accurate prediction models are crucial. Deep learning models developed for Arctic forecasts primarily focus on exploring convolutional neural networks (CNN) and convolutional Long Short-Term Memory (LSTM) networks, while the exploration of the power of LSTM networks is limited. In this research, we focus on enhancing the performance of an LSTM network for predicting monthly Arctic SIE. We leverage five climate and atmospheric variables, validated for their correlation with SIE in prior studies [3]. We utilize the Spearman’s rank correlation and ExtraTrees regressor to enhance our understanding of the importance of the five variables in predicting SIE. We further enhance our predictor variables with seasonal information, lagged time steps, and a linear regression simulated SIE that accounts for the influence of past SIE on current SIE. Statistical methods guide our selection of data scalers and best evaluation metrics for our model. By experimenting with hyperparameter optimization and advanced deep learning training techniques, such as batch sizes, number of neurons, early stopping, and model checkpoint, our model achieved a Mean Absolute Error (MAE) of 0.191 and R2 of 0.996, underscoring its ability to account for nearly all the variance in our data and holds great promise for the prediction of SIE.

The Relationship between Extreme Precipitation Events in East Africa during the Short Rainy Season and Indian Ocean Sea Surface Temperature

The East African short rainy season (October-November-December) is one of the major flood seasons in the East African region. The amount of rainfall during the short rainy season is closely related to the lives of the people and the socio-economic development of the area. By using precipitation data and sea surface temperature data, this study reveals the spatial and temporal variation patterns of extreme precipitation during the East African short rainy season. Key findings include significant rainfall variability, with Tanzania experiencing the highest amounts in December due to the southward shift of the Intertropical Convergence Zone (ITCZ), while other regions receive less than 100 mm. Extreme rainfall events (90th percentiles) are evenly distributed, averaging 2 to 10 days annually. Historical data shows maximum seasonal rainfall often peaks at 15 mm, with frequent occurrences of daily rainfall exceeding 10 mm during OND. Additionally, a positive correlation (0.48) between OND precipitation extremes and Indian Ocean Dipole (IOD) anomalies is statistically significant. These findings highlight the climatic variability and potential trends in extreme rainfall events in East Africa, providing valuable insights for regional climate adaptation strategies.

基于混合FE-SEA方法的汽车驾驶室声学包优化设计

以某车型为研究对象,基于混合有限元——统计能量方法建立了驾驶室的中频噪声预测模型,通过实车试验,获取待测工况下的激励信号,并验证构建的驾驶室混合FE-SEA模型的准确性;然后分析车内噪声贡献度,确定声学包优化的主要方向,采用拉丁超立方设计方法,以此构建克里金近似模型。基于遗传算法对声学包布置参数进行优化设计,并验证了优化方案效果。结果表明,合理优化关键板件的声学包布置参数能够有效降低驾驶室噪声水平。

基于SEA图论法的船舶舱室噪声降噪优化设计

针对详细设计阶段易出现的船舶舱室噪声超标问题,依据噪声控制原理,以振动噪声传递路径为切入点,引入SEA图论法,结合振动噪声能量的主导传递路径对2层平板声腔结构降噪设计参数展开声学灵敏度分析,给出降噪设计指导性建议,为船舶舱室降噪设计提供理论支撑;以某VLCC船声学设计实例,采用SEA图论法结合其噪声超标舱室的能量输入谱,确定其噪声主导传递路径的灵敏度,结合评价指标选取最优降噪方案,成功应用于实船(预报值与实测值吻合良好)。可见,基于SEA图论法的船舶舱室噪声的降噪优化设计具有可行性,为降噪声学指标的定量优化设计提供参考。

基于混合FE-SEA法的箱梁结构噪声特性研究

为探讨箱梁结构噪声规律及其影响因素,以南昌某高架铁路箱梁为研究对象,建立混合FE-SEA模型进行数值仿真分析,并进行现场试验验证。在此基础上,探讨了板厚对结构噪声的影响规律,分析了箱梁各子系统对远场声压的声贡献量。研究结果表明:混合FE-SEA法适用于箱梁结构噪声研究;箱梁结构振动的峰值频率为125 Hz,结构噪声频率范围为50~160 Hz;箱梁顶板和翼板对远场声压级的贡献量较大:增加各板厚度能降低结构噪声,其中增加顶板厚度效果较为明显。因此在减振降噪的过程中,应着重关注顶板和翼板。

基于SEA的常规导弹封锁机场跑道作战效能分析的系统建模和解析

为快速分析解决常规导弹封锁机场跑道的作战效能,提出了一种基于系统效能分析(SEA)方法的作战效能分析方法。构建了基于SEA方法的常规导弹封锁机场跑道作战效能分析的框架结构和解析模型;结合导弹武器作战攻防体系对抗的特点,给出了封锁把握程度分布密度的计算方法并验证了模型的计算精度,该精度可满足实际作战需求。分析了抛撒子母弹分段切割机场跑道的封锁作战特点,运用成爆弹威力环“切割”跑道的思想,通过判断母弹落点与被“切割”跑道之间的几何关系,确定有利弹着区,在此基础上建立了刻画封锁把握程度的跑道失效概率的解析模型;为了构建反映机场跑道封锁与反封锁对抗过程的封锁时间计算模型,将跑道封锁时间划分为跑道损毁情况判定时间、确定跑道抢修方案时间、排爆作业时间和弹坑修复时间4个部分。构建了排爆作业和弹坑修复阶段作业时间的计算模型,以及封锁时间性能度量的解析模型。对封锁时间性能度量的概率密度函数进行了统计推断。研究结果为后续运用SEA方法进行常规导弹封锁机场跑道作战效能分析奠定了基础。

Causes of the record-low Antarctic sea-ice in austral summer 2022

2022年夏季(2021年12月至2022年2月)南极海冰面积达到历史新低,西南极减少最显著.2021年8~10月南半球环状模接近历史最强和7~9月海洋性大陆附近海温显著增暖是两个关键因素.由于平流层臭氧破纪录减少使得前者维持历史最强或接近最强,导致阿蒙森低压(ASL)加深并向西南移动,有利于海冰减少.后者持续到夏季,有利于拉尼娜的发展,通过激发罗斯贝波列加深ASL.在热力上,臭氧减少导致向下净短波辐射增加,引起西南极增暖.此外,净短波辐射-海温-云形成正反馈,与埃克曼输送一起,放大表面增暖,从而促进海冰融化.

Subseasonal transition of Barents-Kara sea-ice anomalies in winter related to the reversed warm Arctic-cold Eurasia pattern

“暖北极-冷欧亚”模态(WACE)的次季节反转会触发中国东部冬季的极端冷/暖转换以及春季沙尘暴.在这一显著的高纬度大气模态反转的驱动下,巴伦支海-喀拉海(BKS)的海冰异常也表现出次季节转换.当北极变暖以及乌拉尔山高压增强时,BKS异常向下的湍流热通量和增强的向下红外辐射有利于海冰融化;近地面的异常偏南风使海冰从薄冰区向多年冰区漂移,进一步扩大了开阔洋面.相反的机制出现在WACE反位相,导致BKS海冰异常偏多.当WACE次季节反转时,上述机制分别发生在前冬和后冬,使得BKS海冰异常出现显著的次季节转换.近10年随着WACE反转频率增多,BKS海冰前后冬的次季节变化增强.本文构建了WACE次季节反转的综合示意图,有助于更好地理解和预测中国东部极端气候.

2023年夏季我国气候异常特征及成因分析

2023年夏季,我国气候特征整体表现为“温高雨少”,区域性、阶段性高温、旱涝等气象灾害明显。降水的空间分布差异显著,主要多雨区位于我国北方,松花江、海河流域出现严重汛情。生成和登陆台风频数均较常年同期偏少,但北上台风却对京津冀等地造成极其严重的雨涝灾害。2023年夏季我国气温为1961年以来历史次高,北方地区暖异常明显,华北、西北等地区阶段性高温热浪尤为突出。华北、东北地区降水偏多是由不同环流系统造成的。其中,华北南部降水异常偏多主要由7月底至8月初一次极为罕见的天气尺度持续性极端降水过程所致,台风杜苏芮和卡努外围环流与异常偏西、偏北的西太平洋副热带高压相配合,再加上太行山东麓的地形效应是其主要原因。盛夏东北东部异常偏南风引导的水汽输送在整个对流层都异常偏强,造成东北北部和东部降水明显偏多,这一异常环流与初夏巴伦支海海冰密集度减小及盛夏西北太平洋海温异常偏暖均有一定关联。

中国极端天气气候研究——“地球系统与全球变化”重点专项项目简介及最新进展

全球变暖背景下,极端天气气候事件频发,并表现出群发性、持续性、复合性等特点,不可预测性增加;持续性强降水、极端低温、复合型极端高温干旱、群发性热浪和台风等极端天气气候事件对我国经济社会和可持续发展影响巨大。然而,上述极端天气气候事件的新特征、关键过程和机理尚不完全清楚,重大极端事件的预报预测水平亟待提升。文章首先简要介绍“地球系统与全球变化”重点专项项目“中国极端天气气候事件的形成机理及其预测和归因”的基本情况。项目拟在分析全球变化背景下对我国造成重大影响的极端天气气候事件新特征的基础上,深入研究多尺度海-陆-气耦合过程影响极端天气气候事件的机理,挖掘极端天气气候事件次季节-季节预测的前兆信号;发展动力与物理统计相结合的极端事件预测新方法,研制针对中国极端事件的新一代高分辨率数值预报与检测归因系统。文章重点总结了自2022年12月项目立项至今取得的最新研究成果和进展。