A Unified Model Fusing Region of Interest Detection and Super Resolution for Video Compression

High-resolution video transmission requires a substantial amount of bandwidth.In this paper,we present a novel video processing methodology that innovatively integrates region of interest(ROI)identification and super-resolution enhancement.Our method commences with the accurate detection of ROIs within video sequences,followed by the application of advanced super-resolution techniques to these areas,thereby preserving visual quality while economizing on data transmission.To validate and benchmark our approach,we have curated a new gaming dataset tailored to evaluate the effectiveness of ROI-based super-resolution in practical applications.The proposed model architecture leverages the transformer network framework,guided by a carefully designed multi-task loss function,which facilitates concurrent learning and execution of both ROI identification and resolution enhancement tasks.This unified deep learning model exhibits remarkable performance in achieving super-resolution on our custom dataset.The implications of this research extend to optimizing low-bitrate video streaming scenarios.By selectively enhancing the resolution of critical regions in videos,our solution enables high-quality video delivery under constrained bandwidth conditions.Empirical results demonstrate a 15%reduction in transmission bandwidth compared to traditional super-resolution based compression methods,without any perceivable decline in visual quality.This work thus contributes to the advancement of video compression and enhancement technologies,offering an effective strategy for improving digital media delivery efficiency and user experience,especially in bandwidth-limited environments.The innovative integration of ROI identification and super-resolution presents promising avenues for future research and development in adaptive and intelligent video communication systems.

A New Method to Locate the Region of Interest( ROI) of Palmprint

Biometric identification was a kind of identity recognition technology by making use of the human's unique physiological or behavioral characteristics,it provided a high reliability and stability way for the identification. Global threshold binarization palmprint image is used in this paper,and the bio-morphological methods are used to get the sensitive area of palmprint image's positioning point,so as to extract the region of interest. The palmprint collection is realized on the FPGA chip,and this kind of collection method uses the DSP Builder toolbox to realize visual programming in Matlab / Simulink and achieve fast modeling and development. The practice proves that this method is simple,flexible and its equipment is portable and fast.

A mathematical morphological approach for region of interest coding of microscopy image compression

A novel mathematical morphological approach for region of interest(ROI) automatic determination and JPEG2000-based coding of microscopy image compression is presented.The algorithm is very fast and requires lower computing power,which is particularly suitable for some irregular region-based cell microscopy images with poor qualities.Firstly,an active threshold-based method is discussed to create a rough mask of regions of interest(cells).And then some morphological operations are designed and applied to achieve the segmentation of cells.In addition,an extra morphological operation,dilation,is applied to create the final mask with some redundancies to avoid the"edge effect"after removing false cells.Finally,ROI and region of background(ROB) are obtained and encoded individually in different compression ratio flexibly based on the JPEG2000,which can adjust the quality between ROI and ROB without coding for ROI shape.The experimental results certify the effectiveness of the proposed algorithm,and compared with JPEG2000,the proposed algorithm has better performance in both subjective quality and objective quality at the same compression ratios.

Autonomous Lane Keeping Solution Based on Adaptive Gray Threshold and Region of Interest

Autonomous lane keeping is an important technology in intelligent transportation,which is used to avoid unnecessary traffic accidents caused by lane departure.To adapt different lighting environment,and make up ordinary Hough transform’s shortcomings of tardiness and poor immunity,we propose an improved algorithm by using adaptive gray threshold and setting Region of interest(ROI),to do the quick Hough transform for tracking lane line,implementing autonomous lane keeping. The dynamic adaptive threshold method can be suitable with different lighting conditions and quickly,accurately remove most of the information not relative to lane line.Meanwhile setting ROI can let the program only care about the specific region which can provide useful information and further reduce the processing data.And then on the basic of identification,we put forward some efficient innovation strategy about the control logic of straight state,curve state and the transition state.The experiment proves that this solution greatly raises efficiency.

Burden of mental disorders and risk factors in the Western Pacific region from 1990 to 2021

BACKGROUND The burden of mental disorders(MD)in the Western Pacific Region(WPR)re-mains a critical public health concern,with substantial variations across demogra-phics and countries.AIM To analyze the burden of MD in the WPR from 1990 to 2021,along with associated risk factors,to reveal changing trends and emerging challenges.METHODS We used data from the Global Burden of Disease 2021,analyzing prevalence,incidence,and disability-adjusted life years(DALYs)of MD from 1990 to 2021.Statistical methods included age-standardisation and uncertainty analysis to address variations in population structure and data completeness.RESULTS Between 1990 and 2021,the prevalence of MD rose from 174.40 million cases[95%uncertainty interval(UI):160.17-189.84]to 234.90 million cases(95%UI:219.04-252.50),with corresponding DALYs increasing from 22.8 million(95%UI:17.22-28.79)to 32.07 million(95%UI:24.50-40.68).During this period,the burden of MD shifted towards older age groups.Depressive and anxiety disorders were predominant,with females showing higher DALYs for depressive and anxiety disorders,and males more affected by conduct disorders,attention-deficit hyperactivity disorder,and autism spectrum disorders.Australia,New Zealand,and Malaysia reported the highest burdens,whereas Vietnam,China,and Brunei Darussalam reported the lowest.Additionally,childhood sexual abuse and bullying,and intimate partner violence emerged as significant risk factors.CONCLUSION This study highlights the significant burden of MD in the WPR,with variations by age,gender,and nation.The coronavirus disease 2019 pandemic has exacerbated the situation,emphasizing the need for a coordinated response.

Infrared and Visible Image Fusion Based on Region of Interest Detection and Nonsubsampled Contourlet Transform

In order to enhance the contrast of the fused image and reduce the loss of fine details in the process of image fusion,a novel fusion algorithm of infrared and visible images is proposed.First of all,regions of interest(RoIs)are detected in two original images by using saliency map.Then,nonsubsampled contourlet transform(NSCT)on both the infrared image and the visible image is performed to get a low-frequency sub-band and a certain amount of high-frequency sub-bands.Subsequently,the coefcients of all sub-bands are classified into four categories based on the result of RoI detection:the region of interest in the low-frequency sub-band(LSRoI),the region of interest in the high-frequency sub-band(HSRoI),the region of non-interest in the low-frequency sub-band(LSNRoI)and the region of non-interest in the high-frequency sub-band(HSNRoI).Fusion rules are customized for each kind of coefcients and fused image is achieved by performing the inverse NSCT to the fused coefcients.Experimental results show that the fusion scheme proposed in this paper achieves better efect than the other fusion algorithms both in visual efect and quantitative metrics.

Robust identification of weld seam based on region of interest operation

For welding path determination,the use of vision sensors is more effctive compared with complex ofline programming and teaching in small to medium volume production.However,interference factors such as scratches and stains on the surface of the workpiece may affect the extraction of weld information.In the obtained weld image,the weld seams have two distinct features related to the workpiece,which are continuous in a single process and separated from the workpiece's gray value.In this paper,a novel method is proposed to identify the welding path based on the region of interest(ROI)opera-tion,which is concentrated around the weld seam to reduce the interference of external noise.To complete the identi-fication of the entire welding path,a novel algorithm is used to adaptively generate a dynamic ROI(DROI)and perform iterative operations.The identification accuracy of this algorithm is improved by setting the boundary condi-tions within the ROI.Moreover,the experimental results confirm that the coefficient factor used for determining the ROI size is a pivotal influencing factor for the robustness of the algorithm and for obtaining an optimal solution.With this algorithm,the welding path identification accuracy is within 2 pixels for three common butt weld types.

Region of Interest Imaging for a General Trajectory with the Rebinned BPF Algorithm

The back-projection-filtration （BPF） algorithm has been applied to image reconstruction for cone-beam configurations with general source trajectories. The BPF algorithm can reconstruct 3-D region- of-interest （ROI） images from data containing truncations. However, like many other existing algorithms for cone-beam configurations, the BPF algorithm involves a back-projection with a spatially varying weighting factor, which can result in the non-uniform noise levels in reconstructed images and increased computation time. In this work, we propose a BPF algorithm to eliminate the spatially varying weighting factor by using a rebinned geometry for a general scanning trajectory. This proposed BPF algorithm has an improved noise property, while retaining the advantages of the original BPF algorithm such as minimum data requirement.

A real 3D scene rendering optimization method based on region of interest and viewing frustum prediction in virtual reality

As an important technology of digital construction,real 3D models can improve the immersion and realism of virtual reality(VR)scenes.The large amount of data for real 3D scenes requires more effective rendering methods,but the current rendering optimization methods have some defects and cannot render real 3D scenes in virtual reality.In this study,the location of the viewing frustum is predicted by a Kalman filter,and eye-tracking equipment is used to recognize the region of interest(ROI)in the scene.Finally,the real 3D model of interest in the predicted frustum is rendered first.The experimental results show that the method of this study can predict the frustrum location approximately 200 ms in advance,the prediction accuracy is approximately 87%,the scene rendering efficiency is improved by 8.3%,and the motion sickness is reduced by approximately 54.5%.These studies help promote the use of real 3D models in virtual reality and ROI recognition methods.In future work,we will further improve the prediction accuracy of viewing frustums in virtual reality and the application of eye tracking in virtual geographic scenes.

Region of Interest Based Selective Encryption Scheme for Privacy Protection in H.264 Video

A selective encryption scheme for region of interest(ROI) of H.264 video is proposed to protect the personal privacy in a video. The most important part of video can be protected with less cost and operation by only encrypting the content of ROIs. Human face regions are selected as ROI and detected by using Gaussian skin color model. Independent ROI encoding is realized with the mechanism of flexible macro-block ordering(FMO). Frames are divided into grid-like slice-groups which can be combined flexibly to form a required ROI.Both luminance component and chrominance component of the macro-blocks in ROI are modified to achieve good encryption quality and location accuracy. In the process of decryption, the encrypted area is located automatically.There is no need to transmit additional position information of ROIs to the end of decryption. The encrypted video is decrypted correctly with the secret key. JM18.4 software is employed to perform the simulation experiment.Experimental results show the accuracy and effectiveness of our scheme to encrypt and decrypt the ROIs in H.264 video.

Construction and Application of a Regional Kilometer-Scale Carbon Source and Sink Assimilation Inversion System(CCMVS-R)

CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate warming since the 1950s and leading to an increased frequency of extreme weather and climate events.In 2020,China committed to striving for carbon neutrality by 2060.This commitment and China’s consequent actions will result in significant changes in global and regional anthropogenic carbon emissions and therefore require timely,comprehensive,and objective monitoring and verification support(MVS)systems.The MVS approach relies on the top-down assimilation and inversion of atmospheric CO_(2)concentrations,as recommended by the Intergovernmental Panel on Climate Change(IPCC)Inventory Guidelines in 2019.However,the regional high-resolution assimilation and inversion method is still in its initial stage of development.Here,we have constructed an inverse system for carbon sources and sinks at the kilometer level by coupling proper orthogonal decomposition(POD)with four-dimensional variational(4DVar)data assimilation based on the weather research and forecasting-greenhouse gas(WRF-GHG)model.Our China Carbon Monito ring and Verification Support at the Regional level(CCMVS-R)system can continuously assimilate information on atmospheric CO_(2)and other related information and realize the inversion of regional and local anthropogenic carbon emissions and natural terrestrial ecosystem carbon exchange.Atmospheric CO_(2)data were collected from six ground-based monito ring sites in Shanxi Province,China to verify the inversion effect of regio nal anthropogenic carbon emissions by setting ideal and real experiments using a two-layer nesting method(at 27 and 9 km).The uncertainty of the simulated atmospheric CO_(2)decreased significantly,with a root-mean-square error of CO_(2)concentration values between the ideal value and the simulated after assimilation was close to 0.The total anthropogenic carbon emissions in Shanxi Province in 2019 from the assimilated inversions were approximately 28.6%(17%-38%)higher than the mean of five emission inventories using the bottomup method,showing that the top-down CCMVS-R system can obtain more comprehensive information on anthropogenic carbon emissions.

Trends of surface ozone based on hourly concentrations in the Beijing–Tianjin–Hebei region during 2017–2021

As a typical secondary air pollutant,surface ozone has been monitored routinely since 2013 in China.Most studies on the spatiotemporal variation of ozone have been centered around the daily maximum 8-h average,with little attention paid to the trends of hourly ozone,especially hourly ozone exceedances.Focusing on hourly ozone exceedances and peak values,the spatiotemporal trends of hourly ozone at 77 sites in 13 cities of the Beijing-Tianjin-Hebei(BTH)region during 2017-2021 were analyzed in this study.The number of hours with exceedances(N_(H200))in 2019 was nearly three times that of 2021.On a five-year average,the percentage of cumulative NH200 in June accounted for up to 40.5%of all hourly exceedances.Cities in central Hebei Province had the highest cumulative annual N_(H200).June had the highest average hourly ozone exceeded multiples of 0.158.The top two cities with the highest average exceeded multiple were Tangshan(0.166)and Beijing(0.158).Tangshan and Xingtai ranked as the top two in terms of the mean of the 10 highest daily maximum ozone concentrations(MTDM),with 286.74 and 285.37μg m^(−3),respectively.The gap between the MTDM and the daily maximum of hourly ozone averaged over all sites had narrowed to 97.88μg m^(−3) in 2021,much lower than that in other years,which indicated that the stability and convergence of ozone pollution in BTH region had been enhanced in 2021 to some extent.

A core-satellite self-assembled SERS aptasensor containing a“biological-silent region”Raman tag for the accurate and ultrasensitive detection of histamine

Herein,a novel interference-free surface-enhanced Raman spectroscopy(SERS)strategy based on magnetic nanoparticles(MNPs)and aptamer-driven assemblies was proposed for the ultrasensitive detection of histamine.A core-satellite SERS aptasensor was constructed by combining aptamer-decorated Fe_(3)O_(4)@Au MNPs(as the recognize probe for histamine)and complementary DNA-modified silver nanoparticles carrying 4-mercaptobenzonitrile(4-MBN)(Ag@4-MBN@Ag-c-DNA)as the SERS signal probe for the indirect detection of histamine.Under an applied magnetic field in the absence of histamine,the assembly gave an intense Raman signal at“Raman biological-silent”region due to 4-MBN.In the presence of histamine,the Ag@4-MBN@Ag-c-DNA SERS-tag was released from the Fe_(3)O_(4)@Au MNPs,thus decreasing the SERS signal.Under optimal conditions,an ultra-low limit of detection of 0.65×10^(-3)ng/mL and a linear range 10^(-2)-10^5 ng/mL on the SERS aptasensor were obtained.The histamine content in four food samples were analyzed using the SERS aptasensor,with the results consistent with those determined by high performance liquid chromatography.The present work highlights the merits of indirect strategies for the ultrasensitive and highly selective SERS detection of small biological molecules in complex matrices.

Diagnostic Study of an Extreme Explosive Cyclone over the Kuroshio/Kuroshio Extension Region

Explosive cyclones(ECs)occur frequently over the Kuroshio/Kuroshio Extension region.The most rapidly intensified EC over the Kuroshio/Kuroshio Extension region during the 42 years(1979-2020)of cold seasons(October-April)was studied to reveal the variations of the key factors at different explosive-developing stages.This EC had weak low-level baroclinicity,mid-level cyclonic-vorticity advection,and strong low-level water vapor convergence at the initial explosive-developing stage.The low-level baroclinicity and mid-level cyclonic-vorticity advection increased substantially during the maximum-deepening-rate stage.The diagnostic analyses using the Zwack-Okossi equation showed that diabatic heating was the main contributor to the initial rapid intensification of this EC.The cyclonic-vorticity advection and warm-air advection enhanced rapidly in the middle and upper troposphere and contributed to the maximum rapid intensification,whereas the diabatic heating weakened slightly in the mid-low troposphere.The relative contribution of the diabatic heating decreased from the initial explosive-developing stage to the maximum-deepening-rate stage due to the enhancement of other factors(the cyclonic-vorticity advection and warm-air advection).Furthermore,the physical factors contributing to this EC varied with the explosive-developing stage.The non-key factors at the initial explosive-developing stage need attention to forecast the rapid intensification.

Clarifying the relationship between PM2.5 and ozone complex pollution and synoptic patterns in a typical petrochemical city in the Bohai Rim region of China:Implications for air pollution forecasting and control

Meteorological conditions are vital to PM_(2.5)and ozone(O_(3))complex pollution.Herein,the T-mode principal com-ponent analysis method was employed to objectively classify the 925-hPa geopotential height field of Dongying from 2017 to 2022.Synoptic patterns associated with four pollution types-namely,PM_(2.5)-only pollution,O_(3)-only pollution,Co-occurring of PM_(2.5)and O_(3)pollution,Non-occurring of PM_(2.5)and O_(3)pollution-were characterized at different time scales.The results indicated that synoptic classes conducive to PM_(2.5)-only pollution were“high-pressure top front”,“offshore high-pressure rear”,and“high-pressure inside”,while those conducive to O_(3)-only pollution were“offshore high-pressure rear”,“subtropical high”,and“high and low systems”.The Co-occurring of PM_(2.5)and O_(3)pollution were influenced by high pressure,and the Non-occurring of PM_(2.5)and O_(3)pollution were linked to precipitation and strong northerly winds.The variation in dominant synoptic patterns is crucial in the frequency changes of the four pollution types,which was further validated through the analysis of typical cases.Under the favorable meteorological conditions of high-pressure control with strong northerly winds or a subtropical high and inverted trough both with strong precipitation,there is potential to achieve coordinated control of PM_(2.5)and O_(3)in Dongying.Additionally,measures like artificially manipulating local humidity could be adopted to alleviate pollution levels.This study reveals the importance of comprehending the meteorological factors contributing to the formation of PM_(2.5)and O_(3)complex pollution for the improvement of urban air quality in the Bohai Rim region of China when emissions are high and the concentration of air pollutants exhibits high meteorological sensitivity.

Interdecadal variability of summer precipitation in the Three River Source Region: Influences of SST and zonal shifts of the East Asian subtropical westerly jet

Summer precipitation in the Three Rivers Source Region(TRSR)of China is vital for the headwaters of the Yellow,Yangtze,and Lancang rivers and exhibits significant interdecadal variability.This study investigates the influence of the East Asian westerly jet(EAWJ)on TRSR rainfall.A strong correlation is found between TRSR summer precipitation and the Jet Zonal Position Index(JZPI)of the EAWJ from 1961 to 2019(R=0.619,p<0.01).During periods when a positive JZPI indicates a westward shift in the EAWJ,enhanced water vapor anomalies,warmer air,and low-level convergence anomalies contribute to increased TRSR summer precipitation.Using empirical orthogonal function and regression analyses,this research identifies the influence of large-scale circulation anomalies associated with the Atlantic–Eurasian teleconnection(AEA)from the North Atlantic(NA).The interdecadal variability between the NA and central tropical Pacific(CTP)significantly affects TRSR precipitation.This influence is mediated through the AEA via a Rossby wave train extending eastward along the EAWJ,and another south of 45°N.Moreover,the NA–CTP Opposite Phase Index(OPI),which quantifies the difference between the summer mean sea surface temperatures of the NA and the CTP,is identified as a critical factor in modulating the strength of this teleconnection and influencing the zonal position of the EAWJ.

Hydrochemical characteristics of surface water in Hengduan mountain region of Eastern Tibet and its response to human activities:A case study of Duoqu Basin,Jinsha River

The analysis of hydrochemical characteristics and influencing factors of surface river on plateau is helpful to study water hydrological cycle and environmental evolution,which can scientifically guide rational development and utilization of water resources and planning of ecological environment protection.With the expansion and diversification of human activities,the quality of surface rivers will be more directly affected.Therefore,it is of great significance to pay attention to the hydrochemical characteristics of plateau surface rivers and the influence of human activities on their circulation and evolution.In this study,surface water in the Duoqu basin of Jinsha River located in Hengduan mountain region of Eastern Tibet was selected as the representative case.Twenty-three groups of surface water samples were collected to analyze the hydrochemical characteristics and ion sources based on correlation analysis,piper trigram,gibbs model,hydrogen and oxygen isotopic techniques.The results suggest the following:(1)The pH showed slight alkalinity with the value ranged from 7.25 to 8.62.Ca^(2+),Mg^(2+)and HCO_(3)^(–)were the main cations and anions.HCO_(3)^(-)Ca and HCO_(3)^(-)Ca·Mg were the primary hydrochemical types for the surface water of Duoqu River.The correlation analysis showed that TDS had the most significant correlation with Ca^(2+),Mg^(2+)and HCO_(3)^(–).Analysis on hydrogen and oxygen isotopes indicated that the surface rivers were mainly recharged by atmospheric precipitation and glacial melt water in this study area.(2)The surface water had a certain reverse cation alternating adsorption,and surface water ions were mainly derived from rock weathering,mainly controlled by weathering and dissolution of carbonates,and secondly by silicates and sodium rocks.(3)The influence of human activities was weak,while the development of cinnabar minerals had a certain impact on the hydrochemistry characteristics,which was the main factor for causing the increase of SO_(4)^(2–).The densely populated county towns and temples with frequent incense burning activities may cause some anomalies of surface water quality.At present,the Duoqu River watershed had gone through a certain influence of mineral exploitation,so the hydrological cycle and river eco-environment at watershed scale will still bound to be change.The results could provide basic support for better understanding water balance evolution as well as the ecological protection of Duoqu River watershed.

Spatiotemporal variability of rain-on-snow events in the arid region of Northwest China

Rain-on-snow(ROS)events involve rainfall on snow surfaces,and the occurrence of ROS events can exacerbate water scarcity and ecosystem vulnerability in the arid region of Northwest China(ARNC).In this study,using daily snow depth data and daily meteorological data from 68 meteorological stations provided by the China Meteorological Administration National Meteorological Information Centre,we investigated the spatiotemporal variability of ROS events in the ARNC from 1978 to 2015 and examined the factors affecting these events and possible changes of future ROS events in the ARNC.The results showed that ROS events in the ARNC mainly occurred from October to May of the following year and were largely distributed in the Qilian Mountains,Tianshan Mountains,Ili River Valley,Tacheng Prefecture,and Altay Prefecture,with the Ili River Valley,Tacheng City,and Altay Mountains exhibiting the most occurrences.Based on the intensity of ROS events,the areas with the highest risk of flooding resulting from ROS events in the ARNC were the Tianshan Mountains,Ili River Valley,Tacheng City,and Altay Mountains.The number and intensity of ROS events in the ARNC largely increased from 1978 to 2015,mainly influenced by air temperature and the number of rainfall days.However,due to the snowpack abundance in areas experiencing frequent ROS events in the ARNC,snowpack changes exerted slight impact on ROS events,which is a temporary phenomenon.Furthermore,elevation imposed lesser impact on ROS events in the ARNC than other factors.In the ARNC,the start time of rainfall and the end time of snowpack gradually advanced from the spring of the current year to the winter of the previous year,while the end time of rainfall and the start time of snowpack gradually delayed from autumn to winter.This may lead to more ROS events in winter in the future.These results could provide a sound basis for managing water resources and mitigating related disasters caused by ROS events in the ARNC.

Assessment of plant diversity of endemic species of the Saharo-Arabian region in Egypt

Savanna, semi-deserts, and hot deserts characterize the Saharo-Arabian region, which includes Morocco, Mauretania, Algeria, Tunisia, Libya, Egypt, Palestine, Kuwait, Saudi Arabia, Qatar, Bahrain, the United Arab Emirates, Oman, Yemen, southern Jordan, Syria, Iraq, Iran, Afghanistan, Pakistan, and northern India. Its neighboring regions, the Sudano-Zambezian region belonging to the Paleotropical Kingdom and the Mediterranean and Irano-Turanian regions included in the Holarctic Kingdom, share a large portion of their flora with the Saharo-Arabian region. Despite the widespread acknowledgment of the region's global importance for plant diversity, an up to date list of the Saharo-Arabian endemics is still unavailable. The available data are frequently insufficient or out of date at both the whole global and the national scales. Therefore, the present study aims at screening and verifying the Saharo-Arabian endemic plants and determining the phytogeographical distribution of these taxa in the Egyptian flora. Hence, a preliminary list of 429 Saharo-Arabian endemic plants in Egypt was compiled from the available literature. Indeed, by excluding the species that were recorded in any countries or regions outside the Saharo-Arabian region based on different literature, database reviews, and websites, the present study has reduced this number to 126 taxa belonging to 87 genera and 37 families. Regarding the national geographic distribution, South Sinai is the richest region with 83 endemic species compared with other eight phytogeographic regions in Egypt, followed by the Isthmic Desert(the middle of Sinai Peninsula, 53 taxa). Sahara regional subzone(SS1) distributes all the 126 endemic species, Arabian regional subzone(SS2) owns 79 taxa, and Nubo-Sindian subzone(SS3) distributes only 14 endemics. Seven groups were recognized at the fourth level of classification as a result of the application of the two-way indicator species analysis(TWINSPAN) to the Saharo-Arabian endemic species in Egypt, i.e., Ⅰ Asphodelus refractus group, Ⅱ Agathophora alopecuroides var. papillosa group, Ⅲ Anvillea garcinii group, Ⅳ Reseda muricata group, V Agathophora alopecuroides var. alopecuroides group, Ⅵ Scrophularia deserti group, and Ⅶ Astragalus schimperi group. It's crucial to clearly define the Saharo-Arabian endemics and illustrate an updated verified database of these taxa for a given territory for providing future management plans that support the conservation and sustainable use of these valuable species under current thought-provoking devastating impacts of rapid anthropogenic and climate change in this region.

Contour Farming Suitability of the Black Soil Region in Northeast China and Its Spatial Characteristics

Contour farming technology plays a key role in reducing soil erosion,enhancing water use efficiency,and fostering sustain-able agricultural development,Despite being a straightforward yet efficacious farming technique,it has not seen widespread implement-ation in China.Considering the deteriorating quality of arable lands in the Black Soil Region of Northeast China(BSR-NEC),it is ne-cessary to investigate spatial patterns and identify suitable areas for contour farming in this region.To achieve this objective,spatial autocorrelation and grouping analysis methods were employed to classify the land into four categories of suitability for contour farming:highly suitable,moderately suitable,generally suitable,and unsuitable.The results reveal that:1)the contour farming suitable area in BSR-NEC covers 89861.32 km^(2),accounting for 21.59%of arable land as of 2020.Heilongjiang Province owns the largest suitable area of 32853.68 km^(2),and Inner Mongolia has the highest proportion of 28.89%.2)In terms of the spatial distribution,regions with higher suitability for contour farming are concentrated in the Da Hinggan Mountains region,particularly Nenjiang City(Heilongjiang Province),which has the highest area of 2593.07 km^(2).Areas with a high proportion of suitable arable lands for contour farming are mainly found in the Da Hinggan Mountains and Changbai Mountains regions,with Ergun City(Inner Mongolia)having the highest pro-portion at 47.2%.Regions with higher suitability and proportion are concentrated in the Da Hinggan Mountains region,primarily cover-ing the Inner Mongolia and Heilongjiang.3)Regarding spatial clustering,both the area and proportion of suitable contour farming areas exhibit noticeable clustering effects,though not entirely consistent.4)Group analysis results designate 148 counties in BSR-NEC as highly suitable areas,predominantly located in the Changbai Mountains region,Liaodong Peninsula,Hulun Buir Plateau,and the north and south regions of the Da Hinggan Mountains.The zoning of suitable areas for contour farming in BSR-NEC informs the strategic de-velopment of policies and measures,allowing for the implementation of targeted policies in distinct areas suitable for contour farming.This provides a valuable reference for promoting contour farming technology more effectively and efficiently.re effectively and effi-ciently.