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.

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.

Investigation of Groundwater Quality with Borehole Depth in the Basin Granitoids of the Ashanti Region of Ghana

The dependence of groundwater quality on borehole depth is usually debatable in groundwater studies, especially in complex geological formations where aquifer characteristics vary spatially with depth. This study therefore seeks to investigate the relationship between borehole depth and groundwater quality across the granitoid aquifers within the Birimian Supergroup in the Ashanti Region. Physicochemical analysis records of groundwater quality data were collected from 23 boreholes of public and private institutions in the Ashanti Region of Ghana, and the parametric values of iron, fluoride, total hardness, pH, nitrate, and nitrite were used to study the groundwater quality-depth relationship. The results showed that the depth-to-groundwater quality indicated a marginal increase in water quality in the range of 30 to 50 m, which is mathematically represented by the low-value correlation coefficient (r2 = 0.026). A relatively significant increase occurs in the depth range of 50 to 80 m, which is given by a correlation coefficient of r2 = 0.298. The mean percent parameter compatibility was 74%, 82%, 89%, and 97% at 50, 60, 70, and 80 m depths, respectively. The variations in groundwater quality per depth ratio ranged from 1.48, 1.37, 1.27, and 1.21 for 50, 60, 70, and 80 m depth, respectively. The recommended minimum borehole depth for excellent groundwater quality is suggested with a compatibility per meter depth ratio of 1.37. This results in a range between 50 and 70 m as the most desirable drilling depth for excellent groundwater quality within the granitoids of the Birimian Supergroup of the Ashanti Region in Ghana.

Enhancing Autonomy Capability in Regional Power Grids:A Strategic Planning Approach withMultiple Autonomous Evaluation Indexes

After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power wastage.As a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of DGs.Therefore,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for autonomy.First,a regional Energy Storage(ES)configuration strategy is proposed.This strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES capacity.Then,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy capabilities.The final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on average.The proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluctuation of power exchange between the regional grid and the higher-level grid.This presents a rational and effective planning solution for the regional grid,facilitating the coordinated development between the region and the distribution network.

Regional economic assessment of a novel place-based model for sustainable food systems

Several actions from both the environmental and human viewpoints have already been made to meet the sustainability goals targeted at food systems.Still,new place-based ideas to improve sustainability are needed.Agroecological symbiosis(AES),a novel food system model,is an example of a suggested system-level change to attain sustainability targets;it is a symbiosis of food production and processing using renewable energy that uses its own feedstock.AES has already been found advantageous from the ecological and biophysical viewpoints,but a regional economic evaluation of the model is still lacking.Thus,the aim of our paper is to assess the regional economic impact of a possible systemic change in the food system using the network of agroecological symbiosis(NAES)as an example.We applied scenarios representing different ways of moving towards envisioned NAES models in Mäntsälä,Finland,and a computable general equilibrium model to evaluate the regional economic impact.According to our results,both regional economy and employment would increase,and the regional production base would diversify with NAES implementation applied to the region,but the extent of the benefits varies between scenarios.The scenario that includes change in both public and private food demand,production of bioenergy and utilization of by-products would cause the largest impacts.However,realizing NAES requires investments that may influence the actual implementation of such models.Nonetheless,a change towards NAES can promote an economically and spatially just transition to sustainability,as NAES seems to be economically most beneficial for rural areas.

Factors of Adherence to Concurrent Tuberculosis Treatment and Antiretroviral Therapy among HIV-TB Co-Infected Individuals in the East Region, Cameroon in the COVID-19 Era: A Retrospective Cohort Study

Context/Objectives: Tuberculosis (TB) and HIV co-infection is a serious health problem in Cameroon. The problems associated with poor adherence to treatment are on the increase worldwide. This problem can be observed in all situations where patients are required to administer their own medication, whatever the type of illness. The general objective of this study was to assess the factors affecting adherence to treatment among HIV-TB co-infected patients in health facilities in the East Region in the COVID context. Method: A retrospective cohort study before and during COVID-19 was conducted in HIV care units in 13 health districts in the East Region of Cameroon. Data were collected using a questionnaire recorded in the Kobo Collect android application, analyzed using SPSS version 25 software and plotted using Excel. Results: The pre-COVID-19 cohort compared to the during-COVID-19 cohort had a 1.90 risk of not adhering to treatment (OR: 1.90, CI {1.90 - 3.37}) and the difference was statistically significant at the 5% level (p-value = 0.029). Frequency of adherence was 65.4% (140/214). Adherence before COVID-19 was 56.9% whereas during COVID-19, it was 74.3%. Conclusion: The implementation of targeted interventions in the COVID-19 context, using evidence-based data and integrating the individual needs of HIV-TB co-infected patients, improved adherence to concurrent anti-tuberculosis treatment and antiretroviral therapy during the COVID-19 Era.

Image Hiding with High Robustness Based on Dynamic Region Attention in the Wavelet Domain

Hidden capacity,concealment,security,and robustness are essential indicators of hiding algorithms.Currently,hiding algorithms tend to focus on algorithmic capacity,concealment,and security but often overlook the robustness of the algorithms.In practical applications,the container can suffer from damage caused by noise,cropping,and other attacks during transmission,resulting in challenging or even impossible complete recovery of the secret image.An image hiding algorithm based on dynamic region attention in the multi-scale wavelet domain is proposed to address this issue and enhance the robustness of hiding algorithms.In this proposed algorithm,a secret image of size 256×256 is first decomposed using an eight-level Haar wavelet transform.The wavelet transform generates one coefficient in the approximation component and twenty-four detail bands,which are then embedded into the carrier image via a hiding network.During the recovery process,the container image is divided into four non-overlapping parts,each employed to reconstruct a low-resolution secret image.These lowresolution secret images are combined using densemodules to obtain a high-quality secret image.The experimental results showed that even under destructive attacks on the container image,the proposed algorithm is successful in recovering a high-quality secret image,indicating that the algorithm exhibits a high degree of robustness against various attacks.The proposed algorithm effectively addresses the robustness issue by incorporating both spatial and channel attention mechanisms in the multi-scale wavelet domain,making it suitable for practical applications.In conclusion,the image hiding algorithm introduced in this study offers significant improvements in robustness compared to existing algorithms.Its ability to recover high-quality secret images even in the presence of destructive attacksmakes it an attractive option for various applications.Further research and experimentation can explore the algorithm’s performance under different scenarios and expand its potential applications.

Individual alcohol consumption by the population of Russia versus regional living conditions

Background:There are substantial regional differences in drinking alcohol in Russia,both at the population and individual levels.However,the causes of these differences have not been studied yet.Objective:The goal of our study was to examine the effect of regional living conditions on individual alcohol consumption by the population of Russia.Methods:For the analysis,we used data from a cross-sectional epidemiological study conducted in 2013-2014.The final analytical sample included 18,130 people aged 25-64 years.We conducted the interviews face to face,based on which any drinking in the last year,as well as alcohol abuse,were considered as a response.Alcohol abuse was recorded when the respondent consumed 5.75 or more grams of pure ethanol per day(75th percentile of average daily alcohol consumption among alcohol drinkers).The assessment of the regional living conditions was accomplished via integral indexing,which was previously performed based on publicly available data for 2010-2014.Associations were assessed using generalized scoring equations with unchanging standard errors.The associations were expressed by odds ratios(OR)and 95%confidence intervals(C).Results:Deterioration of social conditions and increase in demographic depression in the region of residence increased the odds of any drinking(OR 1.51,95%CI:1.33 to 1.72,P<0.001 and OR 1.22,95%CI:1.05 to 1.41,P=0.oo9,respectively).The odds of alcohol abuse increased with the deterioration of social living conditions and the growth of the industrial development in the region:OR 1.35,95%CI:1.14 to 1.59,P<0.001 and OR 1.16,95%CI:1.05 to 1.28,P=0.002,respectively.Conclusion:Our analysis allowed assessing the impact of the regional living conditions on individual drinking alcohol in the population of Russia.

MAVEN observation of magnetosonic waves in the Martian magnetotail region

Magnetosonic waves are an important medium for energy transfer in collisionless space plasma.Magnetosonic waves have been widely investigated in the upstream of the bow shock at Mars.These waves are believed to originate from pickup ions or reflected particles.By utilizing MAVEN spacecraft data,we have observed the occurrence of quasi-perpendicularly propagating magnetosonic emissions near the proton gyrofrequency in the Martian magnetotail region.These plasma waves are associated with a significant enhancement of proton and oxygen flux.The excited magnetosonic waves could possibly heat the protons through resonance and facilitate the ionospheric plasma escape.Our results could be helpful to better understand the Mars’magnetospheric dynamics and offer insights into possible energy redistribution between waves and plasma in the Martian nightside magnetosphere.

Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics

This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

Even Search in a Promising Region for Constrained Multi-Objective Optimization

In recent years, a large number of approaches to constrained multi-objective optimization problems(CMOPs) have been proposed, focusing on developing tweaked strategies and techniques for handling constraints. However, an overly finetuned strategy or technique might overfit some problem types,resulting in a lack of versatility. In this article, we propose a generic search strategy that performs an even search in a promising region. The promising region, determined by obtained feasible non-dominated solutions, possesses two general properties.First, the constrained Pareto front(CPF) is included in the promising region. Second, as the number of feasible solutions increases or the convergence performance(i.e., approximation to the CPF) of these solutions improves, the promising region shrinks. Then we develop a new strategy named even search,which utilizes the non-dominated solutions to accelerate convergence and escape from local optima, and the feasible solutions under a constraint relaxation condition to exploit and detect feasible regions. Finally, a diversity measure is adopted to make sure that the individuals in the population evenly cover the valuable areas in the promising region. Experimental results on 45 instances from four benchmark test suites and 14 real-world CMOPs have demonstrated that searching evenly in the promising region can achieve competitive performance and excellent versatility compared to 11 most state-of-the-art methods tailored for CMOPs.

Hydrogeophysical and Structural Investigations Using VES: A Case Study of Dosso Region in the Southwestern Part of the Meso-Cenozoic Iullemmeden Basin (Southwestern Niger)

A regional study connecting geolelectrical surveys with geology and hydrogeology was carried out in the western part of the Iullemmeden basin, precisely in the Dosso region in Niger. One hundred and four (104) vertical electrical sounds have been realized, among them nineteen representative were thus be used as parametric surveys. The local resistivity values of the geological formations of Quaternary range from 100 Ω⋅m to 1000 Ω⋅m (sands and lateritic sandstones). The Oligo-Miocene formation of the Continental terminal (Ct) shows resistivity values ranging from 1 to 5 Ω⋅m (brackish groundwaters) to 1500 Ω⋅m (clay sandstones) while the Upper Cretaceous formation of the Continental “hamadien” (Ch) indicates values ranging from 20 Ω⋅m (sandy clay) to 5000 Ω⋅m (clayey sandstones). The geological formations of Paleocene have values from 2 Ω⋅m (marls) to 60 Ω⋅m (calcareous marl), while the Precambrian basement exhibits values of granite around 300 Ω⋅m to 60,000 Ω⋅m. The update of the structural settings reveals many faults in the study area which explain both the shape of the basin and the geometry of the aquifers. Tectonics is also consistent with the hydraulic characteristics of aquifers. In addition, brackish groundwaters were identified as perched aquifer groundwaters in different depths in Dosso region. They probably come from the marine brines during the regression of the Paleocene Sea.

Seasonal Characteristics of Forecasting Uncertainties in Surface PM_(2.5)Concentration Associated with Forecast Lead Time over the Beijing-Tianjin-Hebei Region

Forecasting uncertainties among meteorological fields have long been recognized as the main limitation on the accuracy and predictability of air quality forecasts.However,the particular impact of meteorological forecasting uncertainties on air quality forecasts specific to different seasons is still not well known.In this study,a series of forecasts with different forecast lead times for January,April,July,and October of 2018 are conducted over the Beijing-Tianjin-Hebei(BTH)region and the impacts of meteorological forecasting uncertainties on surface PM_(2.5)concentration forecasts with each lead time are investigated.With increased lead time,the forecasted PM_(2.5)concentrations significantly change and demonstrate obvious seasonal variations.In general,the forecasting uncertainties in monthly mean surface PM_(2.5)concentrations in the BTH region due to lead time are the largest(80%)in spring,followed by autumn(~50%),summer(~40%),and winter(20%).In winter,the forecasting uncertainties in total surface PM_(2.5)mass due to lead time are mainly due to the uncertainties in PBL heights and hence the PBL mixing of anthropogenic primary particles.In spring,the forecasting uncertainties are mainly from the impacts of lead time on lower-tropospheric northwesterly winds,thereby further enhancing the condensation production of anthropogenic secondary particles by the long-range transport of natural dust.In summer,the forecasting uncertainties result mainly from the decrease in dry and wet deposition rates,which are associated with the reduction of near-surface wind speed and precipitation rate.In autumn,the forecasting uncertainties arise mainly from the change in the transport of remote natural dust and anthropogenic particles,which is associated with changes in the large-scale circulation.

Evaluation of Medical Prescribers’ Theoretical Knowledge on Medical Imaging in the Northern Region of Burkina Faso

Introduction: Medical imaging is a medical specialty that involves producing images of the human body and interpreting them for diagnostic, therapeutic purposes, and for monitoring the progress of pathologies. We aimed to assess the theoretical knowledge of doctors and interns in medical imaging in the northern region of Burkina Faso. Methodology: This was a descriptive cross-sectional survey based on a self-administered questionnaire. Prescribers knowledge was estimated based on scores derived from questionnaire responses. Results: We collected 106 questionnaires out of 163, i.e. a participation rate of 65.03%. The average knowledge score was 81.71% for the contribution of medical imaging to patient management. It was 60.02% for the indications/counter-indications of radiological examinations and 72.56% for the risks associated with exposure to radiation during these examinations. The score was 59.83% for the methods used to select the appropriate radiological examination. As regards the completeness of the clinical and biological information on the forms requesting imaging examinations, the score was 96.65%. Specialist doctors had the highest overall level of knowledge (74.68%). Conclusion: Improved technical facilities, good initial and in-service training, and interdisciplinary collaboration will help to ensure that imaging tests are properly prescribed, leading to better patient care.

A Dual-Task Learning Approach for Bearing Anomaly Detection and State Evaluation of Safe Region

Predictive maintenance has emerged as an effective tool for curbing maintenance costs,yet prevailing research predominantly concentrates on the abnormal phases.Within the ostensibly stable healthy phase,the reliance on anomaly detection to preempt equipment malfunctions faces the challenge of sudden anomaly discernment.To address this challenge,this paper proposes a dual-task learning approach for bearing anomaly detection and state evaluation of safe regions.The proposed method transforms the execution of the two tasks into an optimization issue of the hypersphere center.By leveraging the monotonicity and distinguishability pertinent to the tasks as the foundation for optimization,it reconstructs the SVDD model to ensure equilibrium in the model’s performance across the two tasks.Subsequent experiments verify the proposed method’s effectiveness,which is interpreted from the perspectives of parameter adjustment and enveloping trade-offs.In the meantime,experimental results also show two deficiencies in anomaly detection accuracy and state evaluation metrics.Their theoretical analysis inspires us to focus on feature extraction and data collection to achieve improvements.The proposed method lays the foundation for realizing predictive maintenance in a healthy stage by improving condition awareness in safe regions.

The Static Stability Region of an Integrated Electricity-Gas System Considering Voltage and Gas Pressure

In an integrated electricity-gas system(IEGS),load fluctuations affect not only the voltage in the power system but also the gas pressure in the natural gas system.The static voltage stability region(SVSR)method is a tool for analyzing the overall static voltage stability in a power system.However,in an IEGS,the SVSR boundary may be overly optimistic because the gas pressure may collapse before the voltage collapses.Thus,the SVSR method cannot be directly applied to an IEGS.In this paper,the concept of the SVSR is extended to the IEGS-static stability region(SSR)while considering voltage and gas pressure.First,criteria for static gas pressure stability in a natural gas system are proposed,based on the static voltage stability criteria in a power system.Then,the IEGS-SSR is defined as a set of active power injections that satisfies multi-energy flow(MEF)equations and static voltage and gas pressure stability constraints in the active power injection space of natural gas-fired generator units(NGUs).To determine the IEGSSSR,a continuation MEF(CMEF)method is employed to trace the boundary point in one specific NGU scheduling direction.A multidimensional hyperplane sampling method is also proposed to sample the NGU scheduling directions evenly.The obtained boundary points are further used to form the IEGSSSR in three-dimensional(3D)space via a Delaunay triangulation hypersurface fitting method.Finally,the numerical results of typical case studies are presented to demonstrate that the proposed method can effectively form the IEGS-SSR,providing a tool for IEGS online monitoring and dispatching.

Suitable region of dynamic optimal interpolation for efficiently altimetry sea surface height mapping

The dynamic optimal interpolation(DOI)method is a technique based on quasi-geostrophic dynamics for merging multi-satellite altimeter along-track observations to generate gridded absolute dynamic topography(ADT).Compared with the linear optimal interpolation(LOI)method,the DOI method can improve the accuracy of gridded ADT locally but with low computational efficiency.Consequently,considering both computational efficiency and accuracy,the DOI method is more suitable to be used only for regional applications.In this study,we propose to evaluate the suitable region for applying the DOI method based on the correlation between the absolute value of the Jacobian operator of the geostrophic stream function and the improvement achieved by the DOI method.After verifying the LOI and DOI methods,the suitable region was investigated in three typical areas:the Gulf Stream(25°N-50°N,55°W-80°W),the Japanese Kuroshio(25°N-45°N,135°E-155°E),and the South China Sea(5°N-25°N,100°E-125°E).We propose to use the DOI method only in regions outside the equatorial region and where the absolute value of the Jacobian operator of the geostrophic stream function is higher than1×10^(-11).

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.

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.

A phylogenetic approach identifies patterns of beta diversity and floristic subregions of the Qinghai-Tibet Plateau

Patterns of taxonomic and phylogenetic beta diversity and their relationships with environmental correlates can help reveal the origin and evolutionary history of regional biota.The Qinghai-Tibet Plateau(QTP)harbors an exceptionally diverse flora,however,a phylogenetic perspective has rarely been used to investigate its beta diversity and floristic regions.In this study,we used a phylogenetic approach to identify patterns of beta diversity and quantitatively delimit floristic regions on the Qinghai-Tibet Plateau.We also examined the relationships between multifaceted beta diversity,geographical distance,and climatic difference,and evaluated the relative importance of various factors(i.e.,climate,topography and history)in shaping patterns of beta diversity.Sørensen dissimilarity indices indicated that patterns of species turnover among sites dominated the QTP.We also found that patterns of both taxonomic and phylogenetic beta diversity were significantly related to geographical distance and climatic difference.The environmental factors that contributed most to these patterns of beta diversity include annual precipitation,mean annual temperature,climatic gradients and climatic instability.Hierarchical dendrograms of dissimilarity and non-metric multidimensional scaling ordination based on phylogenetic beta diversity data identified ten floristic subregions in the QTP.Our results suggest that the contemporary environment and historical climate changes have filtered species composition among sites and eventually determined beta diversity patterns of plants in the QTP.