Collection Of Environmental Information Research Articles

Medical Intelligence And Public Health In The Complexities Of Contemporary Societies The Role Of FBI In The United States

The term Medical Intelligence (Medint) defines the activities of collection, evaluation, analysis and interpretation of medical, bio-scientific and environmental information, regarding a specific country or geographical area, carried out mainly by military or intelligence agencies and carried out abroad, and useful for military or humanitarian strategic planning. It is of interest to Medint to know the potential of local health facilities, both civil and military, in the diagnostic evaluation, in case of infectious pathologies and in the evaluation of environmental risks as well as the "state of the art" of the development of computerized diagnostic technology and of biotechnology. The SMI (Strategic Medical Intelligence) is instead institutionally delegated to the intelligence agencies that deal with territorial control (counter-terrorism). In the United States, the SMI bioterrorism experts depend on the FBI. According to the definition offered by the FBI, Strategic Medical Intelligence (SMI) deals with all the management activities of a medical or health crisis situation following a terrorist act.

RIGHT TO ENVIRONMENTAL INFORMATION IN THE CONTEXT OF DIGITALIZATION

The article examines the legal signi cance of environmental information in a digital society and examines its characteristics such as reliability. It is this quality of information about the state of the environment that is enshrined in the Constitution of the Russian Federation. It is noted that reliable information about the state of the environment is information that is at the same time genuine (objective, undistorted, accurate), and su cient (not excessive, but not fragmentary and not selective), and relevant (timely), unbiasedly collected and analyzed by a competent subject. The de nition of the term “information on the state of the environment (environmental information)” included in the Federal Law “On Environmental Protection” in 2021 is also analyzed. It is concluded that the legal de nition of the term in question does not allow distinguishing environmental information from all other information. The right to environmental information is analyzed in relation to the modern system of information support for state environmental management. The necessity of establishing a regime of transparency of information on the state of the environment is substantiated. It is proposed to develop and implement an information mechanism in the eld of environmental protection - a system of information measures of in uence (interrelated legal means that mediate the processes of collection, accumulation, analysis, storage, provision and use of reliable environmental information) on people’s behavior in order to ensure environmental protection, rational use of natural resources, environmental safety of humans and other objects.

Typhoon eye-shaped global convective flow field-induced colloidal motor swarm

In nature, living individuals such as fish, gather as much as possible in the wild to carry out life activities to improve their survival rate and environmental adaptability. Colloidal motors are often used as models to form various swarms and reveal their intrinsic mechanisms. Here, we rely on a global convective flow field to prompt the formation of a colloidal motor swarm that can absorb all motors in the range of light radiation without assembly limits. The peanut-shaped colloidal motor photocatalytically decomposes hydrogen peroxide and generates the chemical concentration gradient, which triggers convective flows at its waist in the x-z plane and attracts nearby motors. When motors converge towards the center of the light gradient field due to their positive phototaxis, the chemical gradient fluid resulting from motors’ non-uniform distribution in the entire domain induces a typhoon eye-shaped global convective flow field that flows from the edge of the light to the center. Compared with individuals, the global convective flow has a wider attraction range and gathers motors into a swarm. Moreover, with the number of collected motors increasing, the convective flow integrated in the x-z plane is stronger and ceaselessly accumulates more motors toward the z-axis. The formed swarm can also move to other areas under light control to collect more motors. Such collective phenomena provide a chance for understanding the emergence mechanism of biological swarms and applying artificial swarms to environmental governance, information collection, and drug release.

Collection and processing of environmental information in oil and gas production areas and solving other applied problems using active search methods (Review article)

Collection and processing of environmental information in oil and gas production areas and solving other applied problems using active search methods (Review article)

Research on Enterprise Environmental Risk Management of Industrial Bank under Analytic Hierarchy Process

With the frequent occurrence of corporate environmental incidents and the intensification of bank credit risks, the banking industry urgently needs to strengthen the prevention, control and management of corporate environmental risks. Based on the analytic hierarchy process, this paper takes the three enterprises that have been granted credit by IB as samples, selects the enterprise environmental risk model of four sub-indicators: carbon emissions, basic environmental management, environmental risk management measures, and environmental risk emergency management, and selects the appropriate green credit objects according to the calculation results. It also puts forward suggestions on environmental risk management to improve the collection and transmission of enterprise environmental information, strengthen the supervision of enterprise risk management measures, and formulate a unified enterprise environmental risk rating standard, so as to provide reference for the banking industry to carry out enterprise environmental risk management.

Application of Benthic Microbial Fuel Cells in Systems of Year-Round Monitoring of Water Environment Parameters

The bioelectrogenic activity of sediments of natural microbial association of the Peter’s Bay of Japanese sea research was performed in a year-round experiment with parallel temperature, illumination and water electrical conductivity monitoring by means of benthic microbial fuel cell (MFC) and automatic online-monitoring. Several variants of underwater devices, including benthic microbial fuel cells, monitoring water environment sensor,information collection and transmission systems, have been developed. This device make electrical voltage up to 216 mV, specific power up to 239 mW/m2. Electrogenic activity of natural microflora depends on water temperature and reach maximum on summer with temperature about 20–25°C. The introduction of toxicants in form as hydrocarbons and cadmium into the sluge led to the suppression of microbial electrogenesis. However the introduction of inductor substances of microbial sulfidogenesis led to the stimulation of microbial electrogenesis. The possibility of functioning of the benthic MFC in the field of the Peter’s Great Bay in various climatic periods is shown. It is shown that such experimental devices serve as a basis for autonomous stations monitoring the state of the aquatic environment for a long time and in a wide range of conditions change. Thus, automatic registration of temperature, illumination and salinity of water with a frequency of 48 times a day was carried out for 13 months (11/28/2019–12/31/2020). The electrogenic activity of this microbiota upon MFC scaling can potentially become a new renewable energy source for low-power marine electronics, including those used in mariculture.

Wirelessly Powered Sensing Fertilizer for Precision and Sustainable Agriculture

AbstractSensor networks comprising small wireless sensor devices facilitate the collection of environmental information and increase the efficiency of outdoor practices, including agriculture. However, the sensor‐device installation density of a network is limited because conventional sensor devices must be removed after use. In this study, a sustainable dense sensing system that combines simplified degradable sensor devices, wireless power supply, and thermal‐camera image‐based information recognition is proposed. The proposed wireless‐power‐driven sensor device comprises a biodegradable nanopaper substrate, natural wax, and an eco‐friendly tin conductive line. The sensor device emits a thermal signal based on the soil moisture content. The thermal camera simultaneously acquires the soil moisture‐content data and sensor‐device location. The majority of the sensor‐device components are biodegradable, and the residual components have a minimal adverse impact on the environment. Additionally, the fertilizer component in the substrate promotes plant growth. The proposed sensing concept introduces a novel direction for realizing hyperdense sensor networks and contributes to the development of social systems that combine sustainability with meticulous environmental management.

Mass emissions of polycyclic aromatic hydrocarbons during fuel combustion in thermal power plant boilers

RELEVANCE of this study lies in the establishment of technological indicators of emissions of benz(a)pyrene into the atmosphere to assess the degree of negative impact of energy enterprises on the environment and the development on this basis of primary (air protection) measures, inventory of emissions ofpollutants, collection and preparation of initial environmental information for the effective implementation of the principles of technological regulation of emissions in the domestic thermal power industry. THE PURPOSE. The technological features of the formation of polycyclic aromatic hydrocarbons, in particular benz(a)pyrene, in the furnaces of power boilers burning organic fuel are considered. The regime factors significantly influencing the intensity of the formation of benz(a)pyrene as the most carcinogenic and mutagenic impurity influe gases have been determined. As part of the implementation of the principles of technological rationing of polluting marker substances, energy enterprises should determine the mass emission of highly toxic combustion products to improve the environmental performance of combustion processes and establish technological emission indicators. METHODS. Determination of mass emissions of polycyclic aromatic hydrocarbons was carried out using methods of mathematical statistics, processing of environmental information, system analysis of data and processing of the results obtained. RESULTS. Analytical expressions have been developed to determine the content of benz(a)pyrene in the combustion products of coal and anthracite. The values of mass emissions of benz(a)pyrene for inventory and justification of technological rationing of carcinogenic and mutagenic substances at energy enterprises have been determined. CONCLUSION. The results obtained are recommended to be used for a preliminary assessment of the content of benz(a)pyrene in the flue gases of boilers at power plants at the stage of collecting and preparing information for the introduction of technological rationing of highly toxic substances and the assessment of technological emission indicators.

Path Planning of Mecanum Wheel Chassis Based on Improved A* Algorithm

This study is concerned with path planning in a structured greenhouse, in contrast to much of the previous research addressing applications in outdoor fields. The prototype mainly comprises an independently driven Mecanum wheel, a lidar measuring module, a single-chip microcomputer control board, and a laptop computer. Environmental information collection and mapping were completed on the basis of lidar and laptop computer connection. The path planning algorithm used in this paper expanded the 8-search-neighborhood of the traditional A* algorithm to a 48-search-neighborhood, increasing the search direction and improving the efficiency of path planning. The Floyd algorithm was integrated to smooth the planned path and reduced the turning points in the path. In this way, the problems of the traditional A* algorithm could be solved (i.e., slow the path planning speed and high numbers of redundant points). Tests showed that the turning points, planning path time, and distance of the improved algorithm were the lowest. Compared with the traditional 8-search-neighborhood A* algorithm, the turning point was reduced by 50%, the planning time was reduced by 13.53%, and the planning distance was reduced by 13.96%. Therefore, the improved method of the A* algorithm proposed in this paper improves the precision of the planning path and reduces the planning time, providing a theoretical basis for the navigation, inspection, and standardization construction of greenhouses in the future.

Obstacles to the Use of Citizen Data in Environmental Litigation before East African Courts

Increasingly, citizen data are used as evidence before courts in the context of environmental litigation. This trend is especially strong in Europe and in the United States, but is still poorly researched in Africa. This paper may serve as a starting point to identify some general features in East African legal frameworks and judicial practice that could complicate the use of citizen data as evidence in environmental litigation before courts in this region. From the onset, it is important to emphasize the colonial origins of environmental legislation in East Africa, which was not only designed to make the exploitation of natural resources easier for the occupiers (instead of conserving the natural resource base), but was also specifically geared towards excluding the local population from decision-making. As a first obstacle, environmental statutes still lack clear technical standards concerning air, soil, and water quality. This forces litigants to rely on vague constitutional rights, and leads to a focus on procedural rather than substantive questions in court proceedings. Secondly, there is a lack of standards concerning the collection of environmental information. Thirdly, NGOs often operate in hostile environments. If citizen data are to be used for litigation, it is important to ensure a cooperative relationship with the authorities and to protect the organizers of citizen science projects from retaliation. Fourthly, many environmental procedures in Africa are of a criminal nature, which may influence the requirements concerning the use of citizen data.

Integrating “One Health” Concepts in the Design of Sustainable Systems for Environmental Use

Ensuring for the national defense requires the use of substances such as energetics, propellants, pyrotechnics, and other materials in environmental applications. Systems that use these materials do so in testing and training environments and must be used in an environmentally sustained manner to ensure success during actual kinetic defensive operations. Environmental and occupational health assessments require a weighted evaluation of toxicity, bioaccumulation, persistence, and environmental fate and transport considerations for each substance in the formulation to include potential combustion products. Data that support these criteria need to be collected in a phased and matrixed approach and considered iteratively as technology advances. Further, these criteria are often considered as disparate and separate; hence, comparing favorable aspects of one may or may not offset detrimental data from another. Here, we describe an approach to the phased collection of environmental, safety, and occupational health (ESOH) information for new systems and substances and provide recommendations for evaluating such data streams in making decisions for use and for evaluating alternatives.

LiDAR Odometry and Mapping Based on Neighborhood Information Constraints for Rugged Terrain

The simultaneous localization and mapping (SLAM) method estimates vehicles’ pose and builds maps established on the collection of environmental information primarily through sensors such as LiDAR and cameras. Compared to the camera-based SLAM, the LiDAR-based SLAM is more geared to complicated environments and is not susceptible to weather and illumination, which has increasingly become a hot topic in autonomous driving. However, there has been relatively little research on the LiDAR-based SLAM algorithm in rugged scenes. The following two issues remain unsolved: on the one hand, the small overlap area of two adjacent point clouds results in insufficient valuable features that can be extracted; on the other hand, the conventional feature matching method does not take point cloud pitching into account, which frequently results in matching failure. Hence, a LiDAR SLAM algorithm based on neighborhood information constraints (LoNiC) for rugged terrain is proposed in this study. Firstly, we obtain the feature points with surface information using the distribution of the normal vector angles in the neighborhood and extract features with discrimination through the local surface information of the point cloud, to improve the describing ability of feature points in rugged scenes. Secondly, we provide a multi-scale constraint description based on point cloud curvature, normal vector angle, and Euclidean distance to enhance the algorithm’s discrimination of the differences between feature points and prevent mis-registration. Subsequently, in order to lessen the impact of the initial pose value on the precision of point cloud registration, we introduce the dynamic iteration factor to the registration process and modify the corresponding relationship of the matching point pairs by adjusting the distance and angle thresholds. Finally, the verification based on the KITTI and JLU campus datasets verifies that the proposed algorithm significantly improves the accuracy of mapping. Specifically in rugged scenes, the mean relative translation error is 0.0173%, and the mean relative rotation error is 2.8744°/m, reaching the current level of the state of the art (SOTA) method.

Network Architecture for Intelligent Identification of Faults in Rabbit Farm Environment Monitoring Based on a Biological Neural Network Model.

Currently, livestock and poultry farming is gradually developing towards modernization and scale, and closed livestock and poultry farms are widely used for poultry feeding management, but at the same time, the farming risks of large-scale farms are increasing. In this paper, based on the study of wireless sensor networks and biological neural network models, the environmental factors that mainly affect the growth of domestic rabbits are analyzed as an example, and the technology is used to design and implement an environmental monitoring system for modern farms. The design of the system is divided into three main parts: hardware design of each node, software design, and upper computer monitoring software design. The hardware part of the system uses coordinator nodes, router nodes, sensor nodes, and control nodes to form a wireless sensor network in the farm, carries out the hardware circuit design of each node, and based on the protocol stack, designs the software program of each node to realize the collection, transmission, and regulation of environmental information in the farm. In the upper computer part, the design and development of the upper computer monitoring software interface are used to complete the real-time display of environmental data, historical query, database storage, and curve drawing, and to design a remote client data query system based on the architecture to realize the query of environmental data of the farm by remote users and to carry out monitoring fault intelligent identification alarm. At the same time, the paper investigates the optimal deployment of wireless sensor network nodes and searches for the optimal location of sensor nodes through an improved biological neural network algorithm to maximize the network coverage and reduce the coverage of blind areas, and conducts simulation experiments with the coverage rate of a rabbit farm as the optimization target.

DESIGN OF INDOOR AGARIC CULTIVATION MONITORING DEVICE BASED ON INTERNET OF THINGS AND EMOTIONAL BEHAVIOR CHANGE

BackgroundAuricularia auricula grows in high environmental conditions and takes a long time to produce. The environmental quality control of Auricularia auricula has gradually become the biggest bottleneck and obstacle restricting its quality production. At present, the environmental control of most edible fungi still depends on artificial experience. The control and regulation efficiency of environment and nutrient solution is low, prone to deviation, unable to provide a comprehensive and high-quality growth environment for edible fungi, which seriously affects its production efficiency and hinders its large-scale development. Therefore, in order to create the best environmental conditions for the growth and development of Auricularia auricula and improve the quality, yield and economic value of Auricularia auricula products, it is particularly important to introduce the Internet of things technology into indoor Auricularia auricula cultivation monitoring from the perspective of cognitive psychology to control the environmental parameters of Auricularia auricula cultivation. Based on cognitive psychology and emotional behavior changes, the cultivation system of Auricularia auricula was improved accordingly.Subjects and MethodsFrom the perspective of cognitive psychology, an indoor agaric cultivation monitoring device based on Internet of things is designed, which is mainly composed of monitoring terminal (stm32f103zet6 microcomputer as the main controller), cloud platform and user control center. The monitoring terminal is mainly responsible for sensor data acquisition, threshold setting and control of some external equipment, including fan cooling, lighting, grass curtain ventilation, water pump watering and infrared anti-theft alarm control; The cloud platform mainly receives various data information uploaded by the main controller through wireless data communication technology and sends it to users; The user control center is mainly responsible for real-time remote monitoring of the growth environment of Auricularia auricula through mobile phones or computers. The information collected by each sensor is automatically identified and tracked in real time after being processed by single chip microcomputer. The data is displayed in real time through LCD, and the data is uploaded to onenet cloud platform through NB IOT wireless communication technology, so as to realize accurate and fast data interactive transmission, remote monitoring and report the real-time status to users. On the other hand, the alarm effect is achieved by setting the corresponding threshold, and the corresponding decision-making and control are carried out automatically. SPSS 22.0 software is also used for data statistical analysis. The measurement data is expressed as mean ± standard deviation (x ± s). The statistical method is: descriptive statistics is used for general data characteristics, t-test is used for the comparison of the mean of two independent samples, nonparametric Kruskal Wallis test is used for ordered classified data, and regression analysis is used to verify the mediation effect of RS between as and terminal according to the mediation effect test model. P < 0.05 was statistically significant.ResultsCompile and download the software and assemble the module, process the environmental parameters collected by the sensor through the microcomputer, and send the sensor data to the onenet cloud platform through the Nb Internet of things module. Users can remotely monitor data through computer or mobile phone to realize the functions of data detection, threshold setting, data display, audible and visual alarm, parameter adjustment, cloud platform monitoring and so on., The total score of Internet of things terminal as is different in whether to monitor the environment (P < 0.05), and the total score of RS is different in users' use of cloud platform data (P < 0.05), that is, the terminal running with emotional behavior changes performs better; The total score of SCL-90 was only different in use.ConclusionThe indoor agaric cultivation monitoring device based on Internet of things and cognitive psychology adopts NB IOT wireless data communication module for wireless transmission, which can complete the collection of indoor environmental information and display the information on mobile phones and computers. It has the functions of remote monitoring and anti-theft alarm, and can realize the intelligent management of agaric cultivation. At the same time, it can also promote the application of cognitive psychology of the Internet of things in various fields and achieve good social builders, managers and collaborators.AcknowledgementsSupported by a project grant from Ministry of education industry university cooperation collaborative education project, (Grant No. 202102371060).

PointLAE: A Point Cloud Semantic Segmentation Neural Network via Multifeature Aggregation for Large-Scale Application

The fast semantic segmentation algorithm of 3D laser point clouds for large scenes is of great significance for mobile information measurement systems, but the point cloud data is complex and generates problems such as disorder, rotational invariance, sparsity, severe occlusion, and unstructured data. We address the above problems by proposing the random sampling feature aggregation module ATSE module, which solves the problem of effective aggregation of features at different scales, and a new semantic segmentation framework PointLAE, which effectively presegments point clouds and obtains good semantic segmentation results by neural network training based on the features aggregated by the above module. We validate the accuracy of the algorithm by training on Semantic3D, a public dataset of large outdoor scenes, with an accuracy of 90.3, while verifying the robustness of the algorithm on Mvf CNN datasets with different sparsity levels, with an accuracy of 86.2, and on Bjfumap data aggregated by our own mobile environmental information collection platform, with an accuracy of 77.4, demonstrating that the algorithm is good for mobile information complex scale data in mobile information collection with great recognition effect.

Legal Significance of Digitalization of Environmental Information in Ensuring Environmental Safety

The article is devoted to the study of legal problems, studies of the importance of digitalization of environmental information in ensuring environmental safety have been conducted. In addition, studies have been conducted on the possibility of digitalization of information in the field of environmental protection and the use of natural resources to address issues of the effectiveness of environmental policy implementation, compliance with environmental standards and requirements, participation in the adoption of environmentally significant decisions of measures to coordinate the activities of state and other bodies in ensuring the environmental safety of the country. The legal experience of foreign countries has been carefully studied in this area. Specific recommendations are given to the basics of state regulation of digitalization of collection, analysis and accumulation of environmental information in ensuring environmental safety, topical issues of both state bodies and in the field of environmental, legal and information digitalization. The study of the problems of digitalization of environmental information was considered as a set of legal, economic, organizational, technical measures aimed at ensuring environmental safety, protecting the rights and interests of the state, individuals, and legal entities in the field of environmental protection and the use of natural resources, ensuring cybersecurity in the field of environmental information.

Global priorities for large-scale biomarker-based prospective cohorts

The focus of this paper is on strategic approaches for establishing population-based prospective cohorts that collect and store biological samples from very large numbers of participants to help identify the determinants of common health outcomes. In particular, it aims to address key issues related to investigation of genetic, as well as social, environmental, and ancestral, diversity; generation of detailed genetic and other types of assay data; collection of detailed lifestyle and environmental exposure information; follow-up and characterization of incident health outcomes; and overcoming obstacles to data sharing and access (including capacity building). It concludes that there is a need for strategic planning at an international level (rather than the current ad hoc approach) toward the development of a carefully selected set of deeply characterized large-scale prospective cohorts that are readily accessible by researchers around the world.

Design and Implementation of Farmland Environment Monitoring System Based on Micro Quadrotor UAV

In view of the lack of effective basic information collection mechanism for outdoor farmland, this paper designs and implements a farmland environment monitoring system based on micro quadrotor UAV. In this system, the micro quadrotor UAV is equipped with sensors such as DHT11, MS5611, SRH-01 for collecting farmland environment information, and the purpose of farmland environment information collection and monitoring is realized under the control of software. The system consists of three parts: the flight control module, the information acquisition module, and the ground station module. This paper introduces the main functions of each part of the system, the design and implementation of software and hardware, and gives the experimental results. The results show that the system can be used to effectively monitor the farmland environment. Compared with the traditional agricultural monitoring system, it has the characteristics of low cost, high efficiency and easy operation.

Clinical Network for Big Data and Personalized Health: Study Protocol and Preliminary Results.

The use of secondary hospital-based clinical data and electronical health records (EHR) represent a cost-efficient alternative to investigate chronic conditions. We present the Clinical Network Big Data and Personalised Health project, which collects EHRs for patients accessing hospitals in Central-Southern Italy, through an integrated digital platform to create a digital hub for the collection, management and analysis of personal, clinical and environmental information for patients, associated with a biobank to perform multi-omic analyses. A total of 12,864 participants (61.7% women, mean age 52.6 ± 17.6 years) signed a written informed consent to allow access to their EHRs. The majority of hospital access was in obstetrics and gynaecology (36.3%), while the main reason for hospitalization was represented by diseases of the circulatory system (21.2%). Participants had a secondary education (63.5%), were mostly retired (25.45%), reported low levels of physical activity (59.6%), had low adherence to the Mediterranean diet and were smokers (30.2%). A large percentage (35.8%) were overweight and the prevalence of hypertension, diabetes and hyperlipidemia was 36.4%, 11.1% and 19.6%, respectively. Blood samples were retrieved for 8686 patients (67.5%). This project is aimed at creating a digital hub for the collection, management and analysis of personal, clinical, diagnostic and environmental information for patients, and is associated with a biobank to perform multi-omic analyses.

Broadcasting capability analysis of WSNs in ship information collection system

In the Internet of things environment, the information collection system designed with wireless sensor networks (WSNs) equipment as the transmission medium can realize the collection of marine environmental information. The WSN nodes can work in a harsh environment without the costly and complicate wiring in the ships. It is necessary to distribute monitoring or alarm information through broadcast operation in ship WSNs. Therefore, in order to improve the efficient application of WSNs in ship information system, the broadcast characteristics of WSNs are analysed and the existing broadcast algorithms are summarized and classified. Finally, some problems faced by broadcast technology are pointed out through simulation results.