Pharmacognostic and phytochemical studies as an invaluable approach for correct identification of medicinal plants:The case of Artemisia vulgaris L.substituted for Artemisia annua L.in Western Uganda

Background:Different parts of Artemisia vulgaris L.(A.vulgaris)are ethno-medicinally used as an emmenagogue and for the treatment of ailments such as malaria fever,ulcers,and cancer.However,anecdotal evidence shows that the plant is often substituted for Artemisia annua L.(A.annua)by herbalists in Western Uganda due to similarities in their morphology.Misidentification of medicinal plants and mislabelling of herbal products have been incriminated in toxicity and adverse health outcomes in traditional medicine practise.Because safety continues to be a major issue with the use of herbal remedies,it becomes imperative therefore that medicinal plants should be correctly identified.Methods:This study focused on investigating the macroscopic,microscopic,physicochemical characteristics and phytochemical composition of A.vulgaris leaves compared to A.annua to ease its correct identification.Results:The results showed that there are some colour differences between the leaves of the two species,with a close arrangement of microscopic features but different leaf constants.The leaves of the two Artemisia species had similar tastes,but their shapes and colours(greenish-yellow for A.annua and dark green for A.vulgaris)can be used by the local community to distinguish between them.The artemisinin content was higher in A.vulgaris leaves(1.72%)than in A.annua(1.43%),but the reverse was observed for the total flavonoid content.Conclusion:This observation could justify the change in the use of A.vulgaris by the indigenous community in western Uganda.Further studies should consider the pharmacognostic comparison of A.annua with other species in the genus Artemisia and the use of molecular techniques such as DNA barcoding.

Hydrocephalic cerebrospinal fluid flowing rotationally with pulsatile boundaries:A mathematical simulation of the thermodynamical approach

To study the kinematics of flow rate and ventricular dilatation,an analytical perturbation approach of hydrocephalus has been devised.This research provides a comprehensive investigation of the characteristics of cerebrospinal fluid(CSF)flow and pressure in a hydrocephalic patient.The influence of hydrocephalic CSF,flowing rotationally with realistic dynamical characteristics on pulsatile boundaries of subarachnoid space,was demonstrated using a nonlinear controlling system of CSF.An analytical perturbation method of hydrocephalus has been developed to investigate the biomechanics of fluid flow rate and the ventricular enlargement.In this paper presents a detailed analysis of CSF flow and pressure dynamics in a hydrocephalic patient.It was elaborated with a nonlinear governing model of CSF to show the influence of hydrocephalic CSF,flowing rotationally with realistic dynamical behaviors on pulsatile boundaries of subarachnoid space.In accordance with the suggested model,the elasticity factor changes depending on how much a porous layer,in this case the brain parenchyma,is stretched.It was improved to include the relaxation of internal mechanical stresses for various perturbation orders,modelling the potential plasticity of brain tissue.The initial geometry that was utilised to create the framework of CSF with pathological disease hydrocephalus and indeed the output of simulations using this model were compared to the actual progression of ventricular dimensions and shapes in patients.According to this observation,the non-linear and elastic mechanical phenomena incorporated into the current model are probably true.Further modelling of ventricular dilation at a normal pressure may benefit from the existence of a valid model whose parameters approximate genuine mechanical characteristics of the cerebral cortex.

Multimodality Medical Image Fusion Based on Pixel Significance with Edge-Preserving Processing for Clinical Applications

Multimodal medical image fusion has attained immense popularity in recent years due to its robust technology for clinical diagnosis.It fuses multiple images into a single image to improve the quality of images by retaining significant information and aiding diagnostic practitioners in diagnosing and treating many diseases.However,recent image fusion techniques have encountered several challenges,including fusion artifacts,algorithm complexity,and high computing costs.To solve these problems,this study presents a novel medical image fusion strategy by combining the benefits of pixel significance with edge-preserving processing to achieve the best fusion performance.First,the method employs a cross-bilateral filter(CBF)that utilizes one image to determine the kernel and the other for filtering,and vice versa,by considering both geometric closeness and the gray-level similarities of neighboring pixels of the images without smoothing edges.The outputs of CBF are then subtracted from the original images to obtain detailed images.It further proposes to use edge-preserving processing that combines linear lowpass filtering with a non-linear technique that enables the selection of relevant regions in detailed images while maintaining structural properties.These regions are selected using morphologically processed linear filter residuals to identify the significant regions with high-amplitude edges and adequate size.The outputs of low-pass filtering are fused with meaningfully restored regions to reconstruct the original shape of the edges.In addition,weight computations are performed using these reconstructed images,and these weights are then fused with the original input images to produce a final fusion result by estimating the strength of horizontal and vertical details.Numerous standard quality evaluation metrics with complementary properties are used for comparison with existing,well-known algorithms objectively to validate the fusion results.Experimental results from the proposed research article exhibit superior performance compared to other competing techniques in the case of both qualitative and quantitative evaluation.In addition,the proposed method advocates less computational complexity and execution time while improving diagnostic computing accuracy.Nevertheless,due to the lower complexity of the fusion algorithm,the efficiency of fusion methods is high in practical applications.The results reveal that the proposed method exceeds the latest state-of-the-art methods in terms of providing detailed information,edge contour,and overall contrast.

中亚地区大国博弈新趋势

Central Asia was stable and active in the diplomatic sphere in 2023. Maintaining a diversified and balanced diplomacy is the basic policy of Central Asian countries. The major power games will not result in regional turbulence, and the prospects for Central Asian development are promising.

中东欧深陷“前沿困境”

Following the outbreak between Russia and Ukraine, the three Baltic countries, Poland, and other Central and Eastern European countries came to the fore in the confrontation between the West and Russia, and aiding Ukraine and resisting Russia became their main policy choice. Since 2023.

Hybrid Architecture:A Studio-Based Pedagogical Framework for Digital Architectural Design

This article intends to bring a new perspective to the discussion of how studio-based education in architectural studies can improve its quality by embedding meta-tools as paradigmatic frameworks as a learning/teaching strategy.The newly emerging creative and collaborative digital design tools and systems led to the re-shaping and re-definition of the traditional studio-based teaching/learning processes.The shift does not only comprise of a newly gained ability of using“design toolkits”,but also has substantial cognitive and pedagogical implications.The paper presents,describes and discusses the application of a new pedagogical approach through the application of a novel knowledge framework,that has been used in the teaching of DAD(Digital Architectural Design)in the context of a master’s level course.

Spatial variance and assessment of nitrogen dioxide pollution in major cities of Pakistan along N5-Highway

This paper discusses the findings of the first car MAX-DOAS（multi-axis differential optical absorption spectroscopy） field campaign（300 km long） along the National Highway-05（N5-Highway） of Pakistan conducted on 13 and 14 November, 2012. The main objective of the field campaign was to assess the spatial distribution of tropospheric nitrogen dioxide（NO_2）columns and corresponding concentrations along the N5-Highway from Islamabad to Lahore.Source identification of NO_2 revealed that the concentrations were higher within major cities along the highway. The highest NO_2 vertical column densities（NO_2VCDs） were found around two major cities of Rawalpindi and Lahore. This study also presents a comparison of NO_2 VCDs measured by the ozone monitoring instrument（OMI） and car MAX-DOAS observations. The comparison revealed similar spatial distribution of the NO_2 columns with both car MAX-DOAS and satellite observations, but the car MAX-DOAS observations show much more spatial details. Maximum NO_2 VCD retrieved from car MAX-DOAS observations was up to an order of magnitude larger than the OMI observations in urban areas.

Influence of tool rotational speed on mechanical and corrosion behaviour of friction stir processed AZ31/Al_(2)O_(3)nanocomposite

Nano-sized reinforcements improved the mechanical characteristics efficiently by promoting more implicit particle hardening mechanisms compared to micron-sized reinforcements.Nano-sized particles lessen the critical particle solidification velocity for swamp and thus offers better dispersal.In the present investigation,the friction stir processing(FSP)is utilized to produce AZ31/Al_(2)O_(3)nanocomposites at various tool rotation speeds(i.e.,900,1200,and 1500 rpm)with an optimized 1.5%volume alumina(Al_(2)O_(3))reinforcement ratio.The mechanical and corrosion behavior of AZ31/Al_(2)O_(3)-developed nanocomposites was investigated and compared with that of the AZ31 base alloy.The AZ31 alloy experienced a comprehensive dynamic recrystallization during FSP,causing substantial grain refinement.Grain-size strengthening is the primary factor contributed to the enhancement in the strength of the fabricated nanocomposite.Tensile strength and yield strength values were lower than those for the base metal matrix,although an upward trend in both values has been observed with an increase in tool rotation speed.An 19.72%increase in hardness along with superior corrosion resistance was achieved compared to the base alloy at a tool rotational speed of 1500 rpm.The corrosion currents(Jcorr)of all samples dropped with increase in the rotational speed,in contrast to the corrosion potentials(Ecorr),which increased.The values of Jcorr of AZ31/Al_(2)O_(3)were 42.3%,56.8%,and 65.5%lower than those of AZ31 alloy at the chosen rotating speeds of 900,1200,and 1500 rpm,respectively.The corrosion behavior of friction stir processed nanocomposites have been addressed in this manuscript which has not been given sufficient attention in the existing literature.Further,this work offers an effective choice for the quality assurance of the FSP process of AZ31/Al_(2)O_(3)nanocomposites.The obtained results are relevant to the development of lightweight automobile and aerospace structures and components.

Another Year of Record Heat for the Oceans

Changes in ocean heat content(OHC), salinity, and stratification provide critical indicators for changes in Earth’s energy and water cycles. These cycles have been profoundly altered due to the emission of greenhouse gasses and other anthropogenic substances by human activities, driving pervasive changes in Earth’s climate system. In 2022, the world’s oceans, as given by OHC, were again the hottest in the historical record and exceeded the previous 2021 record maximum.According to IAP/CAS data, the 0–2000 m OHC in 2022 exceeded that of 2021 by 10.9 ± 8.3 ZJ(1 Zetta Joules = 1021Joules);and according to NCEI/NOAA data, by 9.1 ± 8.7 ZJ. Among seven regions, four basins(the North Pacific, North Atlantic, the Mediterranean Sea, and southern oceans) recorded their highest OHC since the 1950s. The salinity-contrast index, a quantification of the “salty gets saltier–fresh gets fresher” pattern, also reached its highest level on record in 2022,implying continued amplification of the global hydrological cycle. Regional OHC and salinity changes in 2022 were dominated by a strong La Ni?a event. Global upper-ocean stratification continued its increasing trend and was among the top seven in 2022.

Proton pump inhibitors and gastroprotection in patients treated with antithrombotic drugs: A cardiologic point of view

Aspirin,other antiplatelet agents,and anticoagulant drugs are used across a wide spectrum of cardiovascular and cerebrovascular diseases.A concomitant proton pump inhibitor(PPI)treatment is often prescribed in these patients,as gastrointestinal complications are relatively frequent.On the other hand,a potential increased risk of cardiovascular events has been suggested in patients treated with PPIs;in particular,it has been discussed whether these drugs may reduce the cardiovascular protection of clopidogrel,due to pharmacodynamic and pharmacokinetic interactions through hepatic metabolism.Previously,the concomitant use of clopidogrel and omeprazole or esomeprazole has been discouraged.In contrast,it remains less known whether PPI use may affect the clinical efficacy of ticagrelor and prasugrel,new P2Y12 receptor antagonists.Current guidelines recommend PPI use in combination with antiplatelet treatment in patients with risk factors for gastrointestinal bleeding,including advanced age,concurrent use of anticoagulants,steroids,or non-steroidal anti-inflammatory drugs,and Helicobacter pylori(H.pylori)infection.In patients taking oral anticoagulant with risk factors for gastrointestinal bleeding,PPIs could be recommended,even if their usefulness deserves further data.H.pylori infection should always be investigated and treated in patients with a history of peptic ulcer disease(with or without complication)treated with antithrombotic drugs.The present review summarizes the current knowledge regarding the widespread combined use of platelet inhibitors,anticoagulants,and PPIs,discussing consequent clinical implications.

Mapping essential urban land use categories in China(EULUC-China):preliminary results for 2018

Land use reflects human activities on land.Urban land use is the highest level human alteration on Earth,and it is rapidly changing due to population increase and urbanization.Urban areas have widespread effects on local hydrology,climate,biodiversity,and food production[1,2].However,maps,that contain knowledge on the distribution,pattern and composition of various land use types in urban areas,are limited to city level.The mapping standard on data sources,methods,land use classification schemes varies from city to city,due to differences in financial input and skills of mapping personnel.To address various national and global environmental challenges caused by urbanization,it is important to have urban land uses at the national and global scales that are derived from the same or consistent data sources with the same or compatible classification systems and mapping methods.This is because,only with urban land use maps produced with similar criteria,consistent environmental policies can be made,and action efforts can be compared and assessed for large scale environmental administration.However,despite of the fact that a number of urban-extent maps exist at global scales[3,4],more detailed urban land use maps do not exist at the same scale.Even at big country or regional levels such as for the United States,China and European Union,consistent land use mapping efforts are rare[5,6](e.g.,https://sdi4apps.eu/open_land_use/).

Statistical Data Mining with Slime Mould Optimization for Intelligent Rainfall Classification

Statistics are most crucial than ever due to the accessibility of huge counts of data from several domains such as finance,medicine,science,engineering,and so on.Statistical data mining(SDM)is an interdisciplinary domain that examines huge existing databases to discover patterns and connections from the data.It varies in classical statistics on the size of datasets and on the detail that the data could not primarily be gathered based on some experimental strategy but conversely for other resolves.Thus,this paper introduces an effective statistical Data Mining for Intelligent Rainfall Prediction using Slime Mould Optimization with Deep Learning(SDMIRPSMODL)model.In the presented SDMIRP-SMODL model,the feature subset selection process is performed by the SMO algorithm,which in turn minimizes the computation complexity.For rainfall prediction.Convolution neural network with long short-term memory(CNN-LSTM)technique is exploited.At last,this study involves the pelican optimization algorithm(POA)as a hyperparameter optimizer.The experimental evaluation of the SDMIRP-SMODL approach is tested utilizing a rainfall dataset comprising 23682 samples in the negative class and 1865 samples in the positive class.The comparative outcomes reported the supremacy of the SDMIRP-SMODL model compared to existing techniques.

4-CP在零价铁／H2O2体系中的降解研究

文章对4-氯酚在非均相零价铁/H2O2体系中的降解进行了实验研究。结果表明,4-氯酚能在低pH零价铁/H2O2体系中迅速降解。pH对降解具有重要影响,当pH大于5,4-CP降解效果<10%。同时在低pH(pH3)环境下考察了铁粉和H2O2投加量的影响,在最佳条件下对溶液中亚铁离子的形成和过氧化氢的分解进行了进一步的实验研究。最后在对中间产物分析的基础上提出了4-CP降解路径假设。

探索证候与影像相关性,构建中医证候影像新学科

四诊合参,辨证论治是临床中医诊断与治疗疗疾病的基本方法和特色。现代影像学是人体运用视觉诊断疾病即望诊的延伸和发展。发生于疾病不同阶段的证候,以该病病理生理或/及病理解剖的变化为基础,是中医证候与医学影像可能具备相关性的立论依据。探索并逐步阐明西医常见病中医证候与该病医学影像诊断指标的相关性、诊断与疗效评价价值及其生理病理基础,构建中医证候影像学体系,对于促进中医与现代科学技术理论与实践的融合,临床诊疗水平提高具有重要意义。

基于ESMS过滤器的信息融合理论研究及SLAM应用

本文解决了多源信息融合时信息源选择的难题,提出了一种广义的证据支持贴近度过滤器来选择最一致的证据源,并耦合基于DSmT和PCR5的融合机,应用于PioneerII移动机器人的SLAM;通过对运行在虚拟环境中的一个虚拟机器人(自身携带16个Sonar传感器),感知周围环境信息,对有或没有ESMS过滤器两种情况下的环境地图重构效果进行比较,充分验证了ESMS过滤器作为信息融合源选择先决条件的优点。

^13CH4分子ν3振动带空气和氮气加宽系数温度依赖性研究

采用中红外波段连续可调谐二极管激光器和自行研制的低温吸收池,测量了温度为296 K,252 K,213K,173 K时,3.38μm附近13CH4分子的四条跃迁谱线的氮气和空气加宽光谱;首次通过实验获得空气和氮气对13CH4分子的碰撞加宽系数,以及谱线加宽系数的温度依赖系数.实验过程中,利用Voigt线型对所测量的光谱进行拟合.实验结果表明,氮气和空气对13CH4分子的碰撞诱导加宽系数随温度的降低而增大;相同温度下,氮气对13CH4分子的碰撞加宽系数普遍大于空气加宽系数.实验数据为地球和外星体大气遥感探测提供了依据.

南亚夏季风爆发前后青藏高原地表热通量的长期变化特征分析

青藏高原作为世界第三极,其热力强迫作用不仅对亚洲季风系统的发展和维持十分重要,也会对大气环流场产生深远影响。利用欧洲中期天气预报中心(ECMWF)的ERA-Interim中1979—2016年3—10月青藏高原及其周边地区的地表热通量月平均再分析资料,通过分析得出以下结论:3—5月青藏高原主体由感热占据,感热强度快速上升且呈西高东低的分布态势,潜热强度较小但随时间而增强。季风爆发后的6—8月,青藏高原感热强度减弱,潜热强度迅速增强且呈东高西低的分布特征。季风消退后的9—10月,感热与潜热强度相当,但感热呈现出西高东低的分布特征。过去38年,青藏高原地表感热总体呈现微弱下降趋势,潜热呈较弱上升趋势。青藏高原西部地区感热呈微弱下降趋势,潜热呈上升趋势。东部感热呈较为明显的下降趋势且近年来变化趋势增强,东部潜热通量则呈现较为明显的上升趋势,分析结论与近期全球变暖条件下青藏高原气候变暖变湿这一变化状况一致,通过对青藏高原地表热通量的变化分析为下一步运用第三次青藏高原大气科学试验所获资料分析青藏高原上空大气热源的变化以及地表加热场如何影响大气环流奠定基础。

人工智能技术在新型电力系统中的分析、诊断和控制研究

在碳达峰、碳中和目标的大背景下,以高渗透率的可再生能源、高比例的电力电子设备、高速增长的直流负荷“三高”为主要特征的新型电力系统正在逐步形成。新型电力系统的开放性、不确定性和复杂性使其对电力系统的规划、调控、运行、分析提出了新的挑战。通过人工智能技术与电力核心生产应用的深度耦合,针对新型电力系统的运行特点,运用数据挖掘、深度学习、智能算法等通用人工智能技术,可有效提高新型电力系统的分析决策速度,提升可再生能源消纳比例。

Enhanced Fenton,photo-Fenton and peroxidase-like activity and stability over Fe_3O_4/g-C_3N_4 nanocomposites

We prepared the Fe3O4/g‐C3N4nanoparticles(NPs)through a simple electrostatic self‐assembly method with a3:97weight ratio to investigate their Fenton,photo‐Fenton and oxidative functionalities besides photocatalytic functionality.We observed an improvement of the Fenton and photo‐Fenton activities of the Fe3O4/g‐C3N4nanocomposites.This improvement was attributed to efficient charge transfer between Fe3O4and g‐C3N4at the heterojunctions,inhibition of electron‐hole recombination,a high surface area,and stabilization of Fe3O4against leaching by the hydrophobic g‐C3N4.The obtained NPs showed a higher degradation potential for rhodamine B(RhB)dye than those of Fe3O4and g‐C3N4.As compared to photocatalysis,the efficiency of RhB degradation in the Fenton and photo‐Fenton reactions was increased by20%and90%,respectively.Additionally,the horseradish peroxidase(HRP)activity of the prepared nanomaterials was studied with3,3,5,5‐tetramethylbenzidinedihydrochloride(TMB)as a substrate.Dopamine oxidation was also examined.Results indicate that Fe3O4/g‐C3N4nanocomposites offers more efficient degradation of RhB dye in a photo‐Fenton system compared with regular photocatalytic degradation,which requires a long time.Our study also confirmed that Fe3O4/g‐C3N4nanocomposites can be used as a potential material for mimicking HRP owing to its high affinity for TMB.These findings suggest good potential for applications in biosensing and as a catalyst in oxidation reactions.

Hybrid Machine Learning Model for Face Recognition Using SVM

Face recognition systems have enhanced human-computer interactions in the last ten years.However,the literature reveals that current techniques used for identifying or verifying faces are not immune to limitations.Principal Component Analysis-Support Vector Machine(PCA-SVM)and Principal Component Analysis-Artificial Neural Network(PCA-ANN)are among the relatively recent and powerful face analysis techniques.Compared to PCA-ANN,PCA-SVM has demonstrated generalization capabilities in many tasks,including the ability to recognize objects with small or large data samples.Apart from requiring a minimal number of parameters in face detection,PCA-SVM minimizes generalization errors and avoids overfitting problems better than PCA-ANN.PCA-SVM,however,is ineffective and inefficient in detecting human faces in cases in which there is poor lighting,long hair,or items covering the subject’s face.This study proposes a novel PCASVM-based model to overcome the recognition problem of PCA-ANN and enhance face detection.The experimental results indicate that the proposed model provides a better face recognition outcome than PCA-SVM.