Hypothetical Region Research Articles

Economic evaluation of willingness to pay for natural gas supply reliability in Korea

This study evaluates the economic value and supports infrastructure development of constructing a circular network to improve natural gas supply stability. This study applies a double-bounded dichotomous choice model and shows that households and commercial users are willing to pay an additional 2.97% and 1.19% of their monthly gas bill, respectively. This study also shows the impact of gas supply understanding and population density on willingness to pay (WTP) for both sectors. Scenario analysis is conducted to analyze the cost-benefit ratio for a hypothetical region, which may be useful in setting up new business plans.

A Survey and Analysis of Intelligent Forecasting and Decision-Making Evaluation of Urban Growth using Artificial Intelligence

A dense concentration of human-made features such as residences, businesses, highways, bridges, and trains characterize urban areas, which are developed regions that encircle cities and are home to most of the population's non-agricultural labourers. Monitoring and modeling urban development have become critical for long-term urban planning and decision-making. Urban growth prediction models are crucial for understanding the causes and implications of urban land use patterns and predicting upcoming growth of city based on the current scenario, ensuring sustainable city development. The Cellular Automata (CA) approach has been used to simulate the urban growth in a hypothetical region, based on principles governing cell spatial interaction and parameters for exploring alternative urban shapes. However, CA faces numerous uncertainties and more research is requited to enhance its adaptability to urban environments. In recent times, Artificial Intelligence models like Machine Learning (ML) and Deep Learning (DL) are being utilized for urban growth prediction, enhancing decision-making and overcoming uncertainty. In order to help with future urban development planning, these models are essential for accurate management and control of urban expansion. This article presents a comprehensive review of ML and DL models for urban prediction. The first step is a quick review of the many urban prediction models developed by various academics using ML and DL models. The next step is to provide a new way for reliably projecting where cities will expand in the future by comparing current frameworks and determining their shortcomings.

Abstract P3-05-57: Lymphatico-venous communications and rhythmic, respiratory pressure changes influence the incidence of metastatic disease at presentation in solid tumours

Abstract Background- Dissemination of cancer cells and their colonization at distant sites (metastases) is the primary cause of death in patients with solid tumors. Despite of popular theories of cancer metastases, there are several lacunae in our understanding of extent of Metastatic Disease at Presentation (MDP). The aim of this study was to evaluate if organ sites could be grouped together based on the available knowledge extent of lympho-vascular communication (LVC) and probable respiratory pressure changes they undergo and whether this correlated with incidence of MDP. Methods- We analyzed a prospectively maintained database of patients with solid tumors presenting between January and December 2017 at our tertiary care cancer center. The tumors were hypothetically divided into four regions (R) depending on extent of LVC and respiratory pressure changes. All patients had clinico-radiological staging after pathological confirmation of cancer. The hypothetical region grouping R1-R4 was independently evaluated by unsupervised k-means clustering. The incidence of MDP was compared in subgroups defined by primary tumor stage, anatomical region, histology, gender, and age using logistic regression. Results- Of 17,467 patients included with median age 54 years, 6714 (38.4%) had MDP. The incidence of M1 disease in R1 vs R2 vs R3 vs R4 regions, older (>50 years) vs younger Conclusion- Primary anatomical regions defined by LVC and respiratory pressure changes; primary tumor histology (type and grade) and male gender are significant determinants of MDP in solid tumors. Region grouping of solid organs based on extent of lymphaticovenous communications and rhythmic respiratory pressure changes and % MDP Citation Format: Rajendra Badwe, Shalaka Joshi, Rohini Hawaldar, Rohan Chaubal, Atanu Bhattacharjee, Vaibhav Vanmali, Nita S. Nair, Sudeep Gupta. Lymphatico-venous communications and rhythmic, respiratory pressure changes influence the incidence of metastatic disease at presentation in solid tumours [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-05-57.

Beautiful Days in the Neighborhood: Land–Atmosphere Interactions as Drivers of Forest Expansion

Abstract We explore the possible role of plant–atmosphere feedbacks in accelerating forest expansion using a simple example of forest establishment. We use an unconventional experimental design to simulate an initial forest establishment and the subsequent response of climate and nearby vegetation. We find that the forest’s existence produces favorable nearby growing-season conditions that would promote forest expansion. Specifically, we consider a hypothetical region of forest expansion in modern Alaska. We find that the forest acts as a source of heat and moisture for plants to the west, leading them to experience earlier springtime temperatures, snowmelt, and growth. Summertime cooling and cloud formation over the forest also drive a circulation change that reduces summertime cloud cover south of the forest, increasing solar radiation reaching plants there and driving warming. By isolating these vegetation–atmosphere interactions as the mechanisms of increased growth, we demonstrate the potential for forest expansion to be accelerated in a way that has not been highlighted before. These simulations illuminate two separate mechanisms that lead to increased plant growth nearby: 1) springtime heat advection and 2) summertime cloud feedbacks and circulation changes; both have implications for our understanding of past changes in forest cover and the predictability of biophysical impacts from afforestation projects and climate change–driven forest-cover changes. By examining these feedbacks, we seek to gain a more comprehensive understanding of past and potential future land–atmosphere interactions. Significance Statement This study investigates whether the emergence of a high-latitude forest could influence the way water and energy are exchanged between the land and atmosphere in a way that impacts nearby growing conditions and subsequent forest expansion. We use a computer model to simulate a climate with and without forest establishment in the high latitudes and test the response of plants surrounding the forest to the two different climates. We find that a forest is indeed able to spur neighboring plant growth by modifying regional climate and producing more favorable growing conditions for surrounding vegetation. Specifically, forest establishment can bring better growing conditions to plants adjacent to it by warming the air and altering nearby circulation and cloud cover.

Surgical Parapharyngeal Space Tumor Analysis with Case Series Study.

Background The parapharyngeal space is a hypothetical region in the neck that stretches from the base of the skull to the bigger corner of the hyoid bone. The fascia that connects the styloid process to the tensor veli palatini separates the compartment into prestyloid and poststyloid compartments, with the prestyloid compartment being larger. In the general population, tumors of the parapharyngeal area are very uncommon, accounting for less than 1% of all head and neck neoplasms in the population. In this location, CT scanning and magnetic resonance imaging (MRI) exams are complimentary, and both tests should be performed to examine any lesions found. The most critical component of treatment is the total surgical removal of all the cancerous tissue. Identifying and treating primary parapharyngeal space (PPS) tumors are among the most challenging tasks in the treatment of head and neck cancer. They are also among the most aggressive ones. The primary goal of this study is to review our current knowledge at King Abdulaziz University Hospital, Jeddah, Saudi Arabia, which serves as an academic tertiary referral center and a major teaching center. We will focus on clinical findings, tumor structure, tumor histological distribution, and surgical approaches. Materials and Methods The processing starts with two modules. The first module starts with the input images obtained from various patients and collected as a database. The second module starts with the collection of case series of nine patients undergoing excision via multiple different approaches: transoral, transcervical, transparotid, transmandibular, or infratemporal approach. All cases were conducted at King Abdulaziz University Hospital in Jeddah, Saudi Arabia, between 2014 and 2018. All operative interventions were performed by an otolaryngology-head and neck surgeon. Results Our study comprised nine patients, of which two underwent transparotid and seven transcervical and combined transcervical/transparotid approach. Complications faced included a hematoma in one of our cases. Conclusion The transcervical approach appeared to be the superior surgical approach when facing a pleomorphic adenoma within the parapharyngeal space, arising from the deep lobe of the parotid gland or parapharyngeal space-occupying paraganglioma.

Organelle Genome Variation in the Red Algal Genus Ahnfeltia (Florideophyceae).

The agarophyte Ahnfeltia (Ahnfeltiales, Rhodophyta) is a globally widespread genus with 11 accepted species names. Two of the most widespread species in this genus, A. plicata and A. fastigiata, may have diverged genetically due to past geographic changes and subsequent geographic isolation. To investigate this genomic and genetic diversity, we generated new plastid (ptDNAs) and mitochondrial genomes (mtDNAs) of these Ahnfeltia species from four different regions (A. plicata - Chile and UK and A. fastigiata - Korea and Oregon). Two architecture variations were found in the Ahnfeltia genomes: in ptDNA of A. fastigiata Oregon, the hypothetical pseudogene region was translocated, likely due to recombination with palindromic repeats or a gene transfer from a red algal plasmid. In mtDNA of A. fastigiata Korea, the composition of the group II intronic ORFs was distinct from others suggesting different scenarios of gain and loss of group II intronic ORFs. These features resulted in genome size differences between the two species. Overall gene contents of organelle genomes of Ahnfeltia were conserved. Phylogenetic analysis using concatenated genes from ptDNAs and mtDNAs supported the monophyly of the Ahnfeltiophycidae. The most probable individual gene trees showed that the Ahnfeltia populations were genetically diversified. These trees, the cox1 haplotype network, and a dN/dS analysis all supported the theory that these Ahnfeltia populations have diversified genetically in accordance with geographic distribution.

One approach to solving the problem of pricing in the residential real estate market

A stage when an average value began to be considered as a central term of a continuous propor-tion is considered to be the beginning of the development of the «average value» concept. How-ever, this concept, as the central value of the progression, does not make it possible to derive it in relation to a sequence of n terms, regardless of the order in which they follow each other. For this purpose, it is necessary to resort to a formal generalization of average values which prede-termined the transition from continuous proportions to progressions – arithmetic, geometric and harmonic. Currently, a statistical value is given to the average value through its connection to economic categories. In the mathematical theory of average values, there are distinguished two types of them – average values themselves and arithmetic average values. At the same time, each type of average values can act either in the form of a simple or weighted average where the correct choice of the form of the average follows from the material nature of the object of study. Simple average formulas are used in cases where the individual values of the averaged feature do not repeat. If the frequency of repetition of individual values of a feature is present in the calculation formulas of averages, then in this case the formulas of simple averages are called as formulas of weighted averages. With the respect to it, the paper proposes an approach to the description of average socio-economic indicators, using the example of the indicator «Average market value of a square meter of housing» in the real estate market in a hypothetical region by averaging prices based on their weighted average assessment in a particular area. Within the framework of this approach, the distribution function of the weights of housing costs is identified as a self-similar solution (automodel) of a partial differential equation with initial and boundary conditions.

Active regional surveillance for early detection of exotic/emerging pathogens of swine: A comparison of statistical methods for farm selection

In this study, five spatially balanced sampling methods, i.e., generalized random-tessellation stratified (GRTS), local pivotal method (LPM), spatially correlated Poisson sampling (SCPS), local cube method (LCUBE), and balanced acceptance sampling (BAS) were compared to simple random sampling (SRS) based on a livestock disease transmission model on a hypothetical region (195 km × 300 km) populated with 6000 farms in terms of the probability of detection by sample size. Given a fixed sample size, four of the five spatially balanced sampling methods provided better performance than SRS, i.e., higher probabilities of detecting at least one infected farms over a range of regional prevalence evaluated (1%–5%). That is, for any given probability of detection, spatially balanced methods required testing fewer farms than SRS. In an era of pandemics, active regional surveillance for early detection of emerging pathogens becomes urgent, yet shrinking budgets impose intractable constraints. The better performance and higher efficiency of spatially balanced sampling methods suggests a potential improvement in regional livestock disease surveillances and a partial solution to the challenge of affordable surveillance.

Optimization of drug supply for patients with malignant neoplasms in a region of the Russian Federation

The aim was to assess the possibility of optimizing the costs of drugs for cancer patients in a subject of the Russian Federation considering the expiration of patent protection period.Materials and methods. The possibility of optimizing the costs of antitumor drugs was studied using a model of a hypothetical region with a population of 2 million. A gradual replacement of the reference drugs with expiring patent protection by generics or biosimilars over 5 years was simulated. Two replacement scenarios were analyzed: 1) maintaining the drug consumption at a stable level; 2) increasing the drug consumption to the level identified in a previous retrospective analysis of the pharmaceutical market. The baseline scenario implied that the drug purchases remained unchanged (in physical and monetary terms) at the level of 2018. We calculated the difference between the drug costs in the baseline scenario and the costs of the same drugs replaced with generics or biosimilars for a 5 year period.Results. By gradually replacing the reference drugs with generics or biosimilars in a region with a population of 2 million and keeping the costs of drugs for solid tumors at the 352.2 million rubles for 5 years (baseline scenario), 69.4 million rubles can be saved. That amount represents 19.7% of the base level if the drug consumption remains at the 2018 level. With an increase in the INN consumption after the release of generics/ biosimilars, no saving is expected; on the contrary, expenses will increase by 14.1% to 400 million rubles, although, an 8.45-fold increase in consumption is projected.Conclusion. With the appearance of generics / biosimilars for the treatment of solid malignant tumors, the possibility of fund saving depends on the increase in drug consumption.

Novel planning methodology for energy stations and networks in regional integrated energy systems

The effective planning of energy stations and networks is critical for improving the economic and energy performance of regional integrated energy systems. Based on the principle of minimizing investment cost and network losses, this study proposes a novel methodology involving both kernel density estimation and shortest path methods to optimize the transmission network. The optimal locations of energy supply and storage stations are determined according to the kernel density of the annual energy consumption of building groups and the annual energy output of energy stations in the kernel density estimation method, respectively. The shortest path method using the Astar search algorithm with a screening algorithm is used to optimize the distribution of energy networks. The proposed methodology is verified by a hypothetical region from literature. The modified energy station and network planning methodology based on kernel density hotspots can reduce the total network length by 21.3%. Moreover, the proposed methodology can be applied easily and effectively to select the locations of the energy stations and determine the distribution of the energy networks in a regional integrated energy system.

Effect of potassium thiocyanate on the phase diagram of Methyl Ethyl Ketone + secondary Butyl Alcohol + Water: Search for the Quadruple Critical Point

The effect of addition of small amounts of the ionic impurity Potassium Thiocyanate (KSCN) on the tunnel-like region in the phase diagram of Methyl Ethyl Ketone (MEK) + secondary Butyl Alcohol (sBA) + Water (W) is investigated in detail. The KSCN weight fraction range, 0 ≤ XKSCN ≤ 0.0318, results in a systematic decrease in the diameter of the critical-tunnel from ΔT = 71.416 K at XKSCN = 0, to ΔT = 5.275 K at XKSCN = 0.0315. For 0.03190 ≤ XKSCN ≤ 0.03195 the line of critical points end abruptly at specific values of water weight fractions (XW) resulting in the formation of several critical end points. For XKSCN ≥ 0.0320 the critical-tunnel splits into several pairs of parabolic critical lines, each carrying double critical points (DCPs) at their vertices, with one-phase region in-between. The distance between the DCPs corresponding to the low- and high-MEK regions can be made to approach or recede from each other depending on the KSCN weight fraction. The QCP in this system is pushed into a hypothetical region due to curvature effects of the coexistence surface in MEK + W + sBA + KSCN.

Informing decision-making for universal access to quality tuberculosis diagnosis in India: an economic-epidemiological model

BackgroundIndia and many other high-burden countries have committed to providing universal access to high-quality diagnosis and drug susceptibility testing (DST) for tuberculosis (TB), but the most cost-effective approach to achieve this goal remains uncertain. Centralized testing at district-level hub facilities with a supporting sample transport network can generate economies of scale, but decentralization to the peripheral level may provide faster diagnosis and reduce losses to follow-up (LTFU).MethodsWe generated functions to evaluate the costs of centralized and decentralized molecular testing for tuberculosis with Xpert MTB/RIF (Xpert), a WHO-endorsed test which can be performed at centralized and decentralized levels. We merged the cost estimates with an agent-based simulation of TB transmission in a hypothetical representative region in India to assess the impact and cost-effectiveness of each strategy.ResultsCompared against centralized Xpert testing, decentralization was most favorable when testing volume at decentralized facilities and pre-treatment LTFU were high, and specimen transport network was exclusively established for TB. Assuming equal quality of centralized and decentralized testing, decentralization was cost-saving, saving a median $338,000 (interquartile simulation range [IQR] − $222,000; $889,000) per 20 million people over 10 years, in the most cost-favorable scenario. In the most cost-unfavorable scenario, decentralized testing would cost a median $3161 [IQR $2412; $4731] per disability-adjusted life year averted relative to centralized testing.ConclusionsDecentralization of Xpert testing is likely to be cost-saving or cost-effective in most settings to which these simulation results might generalize. More decentralized testing is more cost-effective in settings with moderate-to-high peripheral testing volumes, high existing clinical LTFU, inability to share specimen transport costs with other disease entities, and ability to ensure high-quality peripheral Xpert testing. Decision-makers should assess these factors when deciding whether to decentralize molecular testing for tuberculosis.

Data Aggregation for Increase Performance of Wireless Sensor Networks Using Learning Automata Approach

Wireless sensor networks, a new generation of networks, are composed of a large numbers of nodes and the communication between nodes takes place wirelessly. The main purpose of these networks is collecting information about the environment surrounding the network sensors. The sensors collect and send the required information. There are many challenges and research areas concerned in the literature, one of which is power consumption in network nodes. Nodes in these networks have limited energy sources and generally consume more energy in long communication distances and therefore run out of battery very fast. This results in inefficacy in the whole system. One of the proposed solutions is data aggregation in wireless networks which leads to improved performance. Therefore, in this study an approach based on learning automata is proposed to achieve data aggregation which leads to dynamic network at any hypothetical region. This approach specifies a cluster head in the network and nodes send their data to the cluster head and the cluster head sends the information to the main receiver. Also each node can change its sensing rate using learning automata. Simulation results show that the proposed method increases the lifetime of the network and more nodes will be alive.

Realization of Internet of vehicles technology integrated into an augmented reality system

The goal of this study is to develop an internet of vehicles system with augmented reality technology. The system deals mainly with three subjects, namely, lane departure warning, forward collision detection and warning, and internet of vehicles. First, to deal with the subject of lane departure warning, the Hough transform is used in this study to extract the possible positions of lane lines from the region of interest of an image. The Kalman filter is further employed to remove noises and estimate the actual positions of car lane lines. The lane departure decision is then used to determine whether a lane departure situation occurs. Second, the Sobel edge detector and taillight detection method are used to locate the hypothetical region of the vehicle. The characteristic parameters within the hypothetical region can also be obtained through the Harris corner detection method. To verify the hypothetical region and identify the vehicle, the support vector machine algorithm is used. The collision decision is then applied to determine whether the distance between two vehicles is short, thus fulfilling the goal of forward collision detection and warning. In addition, a secure and easy-to-use internet of vehicles is achieved with the use of the Rivest–Shamir–Adleman encryption algorithm, which uses public and secret keys to encrypt and decrypt messages to achieve the task of user identification. Upon obtaining control of the vehicle, the driver has full access to the most up-to-date information provided by the driver assistance system. Finally, internet of vehicles applications incorporating the previously mentioned methods, smart glasses, and augmented reality are implemented in this study. Smart glasses provide the drivers easy access to information about the vehicle and warnings, which helps enhance driver convenience and safety considerably.

Modeling the damage and recovery of interdependent civil infrastructure network using Dynamic Integrated Network model

In a modern society, civil infrastructure facilities in different systems depend upon each other for product input and/or information sharing. Thus, understanding such dependencies and properly modeling them is essential to assess the performance of the civil infrastructure systems during and following a disruptive event, which lays the foundation of assessing the community resilience. This paper introduces the Dynamic Integrated Network model which is developed to assess the damage and recovery of the network of all considered systems following a disaster by considering the facility-level dependencies. A hypothetical study region consisting of electric power, potable water and cellular systems under a scenario hurricane is used to demonstrate the proposed model. A comparative study is performed with the case when inter-system dependency is ignored. This study confirms the importance of incorporating the inter-system dependencies to improve the estimation on the recovery process.

Exploring ligand dissociation pathways from aminopeptidase N using random acceleration molecular dynamics simulation.

Aminopeptidase N (APN) is a zinc-dependent ectopeptidase involved in cell proliferation, secretion, invasion, and angiogenesis, and is widely recognized as an important cancer target. However, the mechanisms whereby ligands leave the active site of APN remain unknown. Investigating ligand dissociation processes is quite difficult, both in classical simulation methods and in experimental approaches. In this study, random acceleration molecular dynamics (RAMD) simulation was used to investigate the potential dissociation pathways of ligand from APN. The results revealed three pathways (channels A, B and C) for ligand release. Channel A, which matches the hypothetical channel region, was the most preferred region for bestatin to dissociate from the enzyme, and is probably the major channel for the inner bound ligand. In addition, two alternative channels (channels B and C) were shown to be possible pathways for ligand egression. Meanwhile, we identified key residues controlling the dynamic features of APN channels. Identification of the dissociation routes will provide further mechanistic insights into APN, which will benefit the development of more promising APN inhibitors. Graphical Abstract The release pathways of bestatin inside active site of aminopeptidase N were simulated using RAMD simulation.

World trade and regional trade orientation in the context of forthcoming transatlantic trade and investment partnership

We analyse potential consequences of the forthcoming Trade and Investment Partnership between the European Union and the United States (TTIP) for trade orientation of both partners. We do it so with along with the short analysis of the characteristics of the third wave of regionalism and the TTIP position in this process as well as the dominant role of the EU and the U.S. in the world economy – especially – in the world trade. Next, we study trade orientation of the hypothetical region created in result of TTIP. We use regional trade introversion index (RTII) to analyze trade between the EU and the U.S. that has taken place until now to get familiar with the potential changes caused by liberalization of trade between both partners. We analyze RTII for mutual trade of the EU and the U.S. Then, we apply disaggregated data to analyze and compare selected partial RTII (e.g. for trade in final and intermediate goods as well as goods produced in the main sectors of economy like agriculture or manufacturing). The analysis of the TTIP region’s orientation of trade based on the historical data from the period 1999-2012 revealed several conclusions. Nowadays, the trade between the EU and the U.S. is constrained by the protection applied by both partners. Trade liberalization constituting one necessary part of TTIP will surely help to intensify this trade. The factor of special concern is trade of agricultural products which is most constrained and will hardly be fully liberalized even within a framework of TTIP. Simultaneously, both parties are even now trading relatively intensively with intermediaries, which are often less protected than the average of the economy for the sake of development of final goods’ production. The manufactured goods are traded relatively often as well, mainly in consequence of their poor protection after many successful liberalization steps in the framework of GATT/WTO. Consequently, we point out that in many respects the TTIP will be important not only for its participants, but for the whole world economy as well. TTIP appears to be an economic and political project with serious consequences for the world economy and politics.

Sustainability assessment of urban water systems: a case study

The concept of sustainability has received much attention from urban water systems planners and decision makers during the last two decades. A variety of system analysis tools have been used to assess the performance of urban water systems in achieving sustainability goals. This paper presents the lessons learned from conducting a hypothetical case study in the context of sustainability assessment of urban water systems. A fuzzy analytic hierarchy process, a well-known multi-criteria decision-making tool, is employed in terms of a group decision-making model as the sustainability assessment method. The case study is performed for a hypothetical region in Iran; however, data and information obtained from Tehran's urban water system are applied to simulate the real-world situation in the case study. The objective of the case study is the sustainability assessment and prioritisation of development scenarios for the region's urban water system. The results show that group decision-making models are efficient tools to provide a framework for incorporating stakeholder participation into the decision-making processes of urban water systems development. Also, fuzzy techniques can aid decision makers in dealing with the uncertainties and ambiguities of sustainability assessment models, particularly when most data and information are non-quantitative.

Western Corn Rootworm (Coleoptera: Chrysomelidae) Dispersal and Adaptation to Single-Toxin Transgenic Corn Deployed With Block or Blended Refuge

A simulation model of the temporal and spatial dynamics and population genetics of western corn rootworm, Diabrotica virgifera virgifera LeConte, was created to evaluate the use of block refuges and seed blends in the management of resistance to transgenic insecticidal corn (Zea mays L.). This Bt corn expresses one transgenic corn event, DAS-59122-7, that produces a binary insecticidal protein toxin (Cry34Ab1/Cry35Ab1) and provides host-plant resistance. The model incorporates the latest information about larval and adult behavior. Results of this modeling effort indicate that the seed-blend scenarios in many cases produced equal or greater durability than block refuges that were relocated each year. Resistance evolved in the most likely scenarios in 10-16 yr. Our standard analysis presumed complete adoption of 59122 corn by all farmers in our hypothetical region, no crop rotation, and 100% compliance with Insect Resistant Management (IRM) regulations. As compliance levels declined, resistance evolved faster when block refuges were deployed. Seed treatments that killed the pest when applied to all seeds in a seed blend or just to seeds in Bt corn blocks delayed evolution of resistance. Greater control of the pest population by the seed treatment facilitated longer durability of the transgenic trait. Therefore, data support the concept that pyramiding a transgenic insecticidal trait with a highly efficacious insecticidal seed treatment can delay evolution of resistance.

A method of urban ecological risk assessment: combining the multimedia fugacity model and GIS

Industrial pollution has caused serious human health risk because the pollutants can be accumulated in human body via multi routes in a long term, especially in areas of rapid industrialization. It is of great importance to obtain the pollutants’ information, including the transport routes and spatial distribution in the various environmental media of different sub-regions, to facilitate more accurate risk assessment and more effective risk management in urban ecosystems. In this article, we proposed a research framework of urban ecological risk assessment method, which combines the multimedia fugacity model, the multi-route exposure model, exposure-risk relationships and geographic information system (GIS). An urban ecological risk assessment of a hypothetical region indicates that it is possible and feasible to introduce GIS into the previous method to satisfy the requirements of risk management. The assessment results can be further utilized for industrial pollution emission control.