Science-based Decisions Research Articles

Crossing Oceans: Preclinical Collaboration to Improve Pediatric Drug Development

Changes in the regulatory environment affecting pediatric cancer drug development in the United States and the European Union provide unprecedented opportunity to advance the concept of precision medicine to children with cancer. Increasing evidence suggests that new drugs and biologic products directed at molecular targets presumed to be etiologically associated with many adult cancers may well provide therapeutic options for selected subsets of children with cancer despite their histologic and biologic differences. Regulatory requirements for early evaluation of appropriate new drugs for children based on their molecular mechanism of action, rather than the specific clinical indications for which they are developed and/or approved, will shorten the unacceptable time lag between first-in-human and first-in-children studies. The relative scarcity of pediatric patients eligible for biomarker-directed studies and the ever-expanding compendium of new targeted agents mandate rational, science-based decision-making in selecting and prioritizing appropriate drugs to study early in development. A critical component of the evidence base in such decision-making includes preclinical testing of relevant drugs in pediatric tumor-specific in vitro and in vivo models. Established preclinical testing programs with academic investigator-industry collaborations are actively engaged in such activities. International collaboration is required to address the resource constraints and increasing number of potential products to be tested in a timely, efficient, nonduplicative, and cost-effective manner.

Network Analysis of Swine Shipments in China: The First Step to Inform Disease Surveillance and Risk Mitigation Strategies.

China's pork industry has been dramatically changing in the last few years. Pork imports are increasing, and small-scale farms are being consolidated into large-scale multi-site facilities. These industry changes increase the need for traceability and science-based decisions around disease monitoring, surveillance, risk mitigation, and outbreak response. This study evaluated the network structure and dynamics of a typical large-scale multi-site swine facility in China, as well as the implications for disease spread using network-based metrics. Forward reachability paths were used to demonstrate the extent of epidemic spread under variable site and temporal disease introductions. Swine movements were found to be seasonal, with more movements at the beginning of the year, and fewer movements of larger pigs later in the year. The network was highly egocentric, with those farms within the evaluated production system demonstrating high connectivity. Those farms which would contribute the highest epidemic potential were identified. Among these, different farms contributed to higher expected epidemic spread at different times of the year. Using these approaches, increased availability of swine movement networks in China could help to identify priority locations for surveillance and risk mitigation for both endemic problems and transboundary diseases such as the recently introduced, and rapidly spreading, African swine fever virus.

Perceived losses of scientific integrity under the Trump administration: A survey of federal scientists.

President Trump and his administration have been regarded by news outlets and scholars as one of the most hostile administrations towards scientists and their work. However, no study to-date has empirically measured how federal scientists perceive the Trump administration with respect to their scientific work. In 2018, we distributed a survey to over 63,000 federal scientists from 16 federal agencies to assess their perception of scientific integrity. Here we discuss the results of this survey for a subset of these agencies: Department of Interior (DOI) agencies (the US Fish and Wildlife Service (FWS), the US Geological Survey, and the National Park Service); the Centers for Disease Control and Prevention (CDC); the US Environmental Protection Agency (EPA); the Food and Drug Administration (FDA); and the National Oceanic and Atmospheric Administration (NOAA). We focus our analysis to 10 key questions fitting within three core categories that relate to perceptions of integrity in science. Additionally, we analyzed responses across agencies and compare responses in the 2018 survey to prior year surveys of federal scientists with similar survey questions. Our results indicate that federal scientists perceive losses of scientific integrity under the Trump Administration. Perceived loss of integrity in science was greater at the DOI and EPA where federal scientists ranked incompetent and untrustworthy leadership as top barriers to science-based decision-making, but this was not the case at the CDC, FDA, and NOAA where scientists positively associated leadership with scientific integrity. We also find that reports of political interference in scientific work and adverse work environments were higher at EPA and FWS in 2018 than in prior years. We did not find similar results at the CDC and FDA. These results suggest that leadership, positive work environments, and clear and comprehensive scientific integrity policies and infrastructure within agencies play important roles in how federal scientists perceive their agency's scientific integrity.

Biotransformation and oxidative stress responses in relation to tissue contaminant burden in Clarias gariepinus exposed to simulated leachate from a solid waste dumpsite in Calabar, Nigeria

In this study, we have investigated biotransformation and oxidative stress responses in relation to tissue contaminant burden in the African sharptooth catfish (Clarias gariepinus) exposed to simulated leachate from a solid waste dumpsite in Calabar, Nigeria. Fish were exposed to simulated leachate, diluted to 0:0 (negative control), 1:10, 1:50, 1:100 and phenanthrene (a PAH: 50 μg/L used as a positive control) for 3, 7 and 14 days. Hepatic transcripts for cat, sod1, gpx1, gr, gst, cyp1a, cyp2d3, and cyp27 were analyzed by real-time PCR, while enzymatic assays for ethoxyresorufin O-deethylase (EROD), buthoxyresorufin O-deethylase (BROD), methoxyresorufin O-deethylase (MROD), pentoxyresorufin O-deethylase (PROD), catalase (CAT), glutathione peroxidase (GPx), glutathione reductase (GR), glutathione S-transferase (GST), uridine diphospho-glucuronosyltransferase (UDPGT) and lipid peroxidase (LPO) were measured using standard methods. In addition, protein expression for CYP1A, CYP3A and metallotheionin (MT) were measured by immunoblotting. Fish muscle samples were analyzed for selected group of contaminants after 14 days exposure showing significantly high uptake of heavy metals (Cd, Hg and Pb), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), chlorophenols, organochlorine (OC) and organophosphate pesticides in exposed fish. We observed significant concentration- and time-specific increases in biotransformation and oxidative stress responses at transcript and functional (enzyme and protein) levels, that paralleled tissue contaminants bioaccumulation patterns, after exposure to the simulated leachates. Our results highlighted the potential environmental, wildlife and public health consequences from improper solid waste disposal. In addition, it also provides a scientific basis for local sensitization and inform legislative decisions and policy formulation towards sustainable environmental management of solid wastes in Nigeria and other developing countries.

Monitoring water discharge and floodplain connectivity for the northern Andes utilizing satellite data: A tool for river planning and science-based decision-making

River discharge data and magnitudes of floods are often not readily available for decision makers of many developing nations, including Colombia. And this while flooding for these regions is often devastating, causing many fatalities and insurmountable damage to the most vulnerable communities. During the wet season, in strong La Niña years, infrastructural damages of over $US 7.2 billion have occurred. Mitigation of such natural disasters lacks data-supported scientific approaches for evaluating river response to extreme climate events. Here, we propose a satellite-based technique to measure river discharge at selected sites for the main northern Andean River, the Magdalena. This method has the advantage of back calculating daily river discharges over a period of two decades, and thus making it possible to calculate return intervals of significant flood events. The study shows that satellite based river discharges well capture a) the inter-annual variability of river discharge; b) the natural seasonality of water discharge along the floodplains; and c) peak discharges that were observed during La Niña conditions between 2008 and 2011. The last is likely more accurate compared to ground-based gauging stations, as ground-based stations tend to overflow during large flood events and as such are hampered to accurately monitor peak discharges. Furthermore, we show that these derived discharges can form the base to study river-floodplain connectivity, providing environmental decision makers with a technique that makes it possible to better monitor river and ecosystem processes.

Analysis of spatial-temporal association and factors influencing environmental pollution incidents in China

Environmental risk refers to the possibility of environmental pollution events caused by natural causes or human activities. Environmental risks are transmitted through environmental media and can have destructive effects on human society and the natural environment. Understanding the current status and characteristics of environmental risks can effectively prevent and control environmental risks, which is essential for establishing the safety of ecological systems. Although many scholars have studied the environmental risk characteristics of different enterprises or regional scales and proposed corresponding control methods. However, the study of environmental risk characteristics in the national scale is still insufficient, which affects the accuracy of large-scale environmental impact assessment (EIA) and is not conducive to the formulation of the large-scale environmental management system. This paper attempts to use spatial statistical methods and geographically weighted regression (GWR) models to study the temporal and spatial evolution trends of environmental events in China and the spatial correlation characteristics of influencing factors and environmental events in different regions. The research results show that the focus of China's environmental risk is continuously shifting. At present, environmental pollution incidents are concentrated in the western region, and their spatial correlation with influencing factors varies from region to region. Spatial statistical analysis can help us understand the spatial characteristics of risk and identify the interrelationships of environmental risks in different areas. Therefore, spatial statistical analysis can provide a scientific basis for macro decision-making of large regional EIA and environmental risk management. In the future, it is recommended that the focus of environmental events in different regions should be different to reduce the risk of environmental events in China.

Multiobjective UAV Path Planning for Emergency Information Collection and Transmission

Considering the problem of rapid collection and reliable transmission of emergency information, as well as the emergency response missions and natural environment characteristics of emergency sites, this article proposes a novel unmanned aerial vehicle (UAV) path planning framework that considers waypoint and motion. First, the waypoint planning improves the reliability of the uplink and the downlink data transmission to the greatest extent by jointly optimizing UAVs 3-D position and transmit power of UAV and users’ equipment (UE). Second, the motion planning allows the UAVs to traverse all waypoints in the shortest amount of time, which allows more time for data collection by maximizing the acceleration of each UAV. Our results show that the proposed path planning algorithm can significantly improve the normalized Quality-of-Experience (QoE) index and effectively shorten the flight time of each UAV for different assignments. Therefore, the method proposed in this article can effectively solve the key problems in the technical system of emergency response and provide a scientific decision-making basis for the post-disaster emergency response.

Coastal monitoring and data management for restoration in Louisiana

The Coastal Protection and Restoration Authority (CPRA) of Louisiana was created after the devastating hurricanes of 2005 (Katrina and Rita) and is responsible for planning and implementing projects that will either reduce storm-induced losses (protection) or restore coastal ecosystems that have been lost or are in danger of being lost (restoration). The first task of the CPRA board was to develop Louisiana’s first Coastal Master Plan (CPRA 2007), which formally integrates and guides the protection and restoration of Louisiana’s coast. The System-Wide Assessment and Monitoring Program (SWAMP) was subsequently developed as a long-term monitoring program to ensure that a comprehensive network of coastal data collection activities is in place to support the planning, development, implementation, and adaptive management of the protection and restoration program and projects within coastal Louisiana. SWAMP includes both natural-system and human-system components and also incorporates the previously-developed Coastwide Reference Monitoring System (CRMS), the Barrier Island Comprehensive Monitoring (BICM) program, and fisheries data collected by the Louisiana Department of Wildlife and Fisheries (LDWF) in addition to other aspects of system dynamics, including offshore and inland water-body boundary conditions, water quality, risk status, and protection performance, which have historically not been the subject of CPRA-coordinated monitoring. This program further facilitates the integration of project-specific data needs into a larger, system-level design framework. Monitoring and operation of restoration and protection projects will be nested within a larger hydrologic basin-wide and coast-wide SWAMP framework and will allow informed decisions to be made with an understanding of system conditions and dynamics at multiple scales. This paper also provides an update on the implementation of various components of SWAMP in Coastal Louisiana, which began as a Barataria Basin pilot implementation program in 2015. During 2017, the second phase of SWAMP was initiated in the areas east of the Mississippi River. In 2019, development of SWAMP design was completed for the remaining basins in coastal Louisiana west of Bayou Lafourche (Figure 1). Data collection is important to inform decisions, however if the data are not properly managed or are not discoverable, they are of limited use. CPRA is committed to ensuring that information is organized and publicly available to help all coastal stakeholders make informed, science-based decisions. As a part of this effort, CPRA has re-engineered its data management system to include spatial viewers, tabular download web pages, and a library/document retrieval system along with a suite of public-facing web services providing programmatic access. This system is collectively called the Coastal Information Management System (CIMS). CPRA and U.S. Geological Survey (USGS) are also developing a proposal to create an interface for CIMS data to be exported to a neutral template that could then be ingested into NOAA’s Data Integration Visualization, Exploration and Reporting (DIVER) repository, and vice versa. DIVER is the repository that the Natural Resource Damage Assessment (NRDA) program is using to manage NRDA-funded project data throughout the Gulf of Mexico. Linking CIMS and DIVER will make it easier to aggregate data across Gulf states and look at larger, ecosystem-level changes.

AN ENHANCED TECHNO-ECONOMIC ANALYSIS OF LCOE: PUBLIC INCENTIVES VS PRIVATE INVESTMENT

This paper offers a new approach for the estimation of levelized cost of energy (LCOE) by considering the shareholder internal rate of return (IRR) as an unexplored measure in this kind of analysis. The study relies on a comprehensive techno-economic evaluation based on interactions among a set of factors. This mathematical model is then empirically tested for a CSP power plant in Extremadura (Spain) due to their dominant market position and also for being the most developed renewable system at the present. A sensitivity analysis is also performed to establish the influence that market conditions have on the determination of LCOE for different scenarios under the maintenance of a given shareholder IRR for investors. This last assumption makes investment decisions indifferent among several projects in order to focus solely on the minimization of the LCOE. Results reveal that while the annual net electricity production contributes to the reduction of LCOE, total investments, equity percentage and operation and maintenance (O&M) costs help to increase their value by a high percentage. This study gives important scientific basis for investment decision making and also becomes a standpoint to design suitable public incentives that may enhance future technological developments in the CSP generation industry.

Software of Rational Choice of Adaptive Technologies for the Cultivation of Grain Crops as an Element of Agriculture Digitalization

Purpose of research. The goal of research is to develop a science-based decision support system for agricultural producers to choose adaptive technologies for growing crops in the European part of Russia.Methods. System approach, database design theory, mathematical modeling, software and information systems development theory, software qualimetry methods.Results. The paper consistently addresses the issues of the need to digitalize agriculture, describes the results of current research on this topic, identifies areas for further research of such developments, and describes the process of creating and testing application software in stages on the example of our own research. As a result of the conducted research, a finished product has been created and tested. It is a computer program that solves not only the problem of increasing the profitability of grain production, but also ensures the environmental orientation of the technologies used, which is extremely important and relevant at the present time. The proposed software package consists of a client-server application for personal computers, a web application, a mobile application for smartphones based on the Android operating system, and two databases (for personal computers and for the online version of the application).Conclusion. There has been created software that allows us to select the technology for cultivating the given grain crop, taking into account the prevailing soil and climatic conditions of a particular territory, and, thus,it can help to increase the profitability of grain production, ensure the environmental orientation of the applied technologies by effectively using mineral fertilizers, fuel and chemical plant protection productsand select the optimal variety or hybrid of grain crops. It can also help to choose agricultural machinery, taking into account the requirements of import substitution and preliminary calculation of the economic efficiency of the proposed agricultural technology.

Interregional ecosystem services benefits transfer from wind erosion control measures in Inner Mongolia

In an increasingly meta-coupled world, the balance of interregional environmental development is becoming increasingly important, and an ecological cooperation community is emerging. Mapping the flow of an ecosystem service (ES) can aid in understanding the spatiotemporal transport paths from generation to use, thereby facilitating a visualization of the interregional relationship on environmental management. In this study, we evaluated the material quantity and value of the wind-break and sand-fixing service (WSS) of Inner Mongolia, simulated the material and value flow and identified the service benefitting regions (SBRs). The benefitting land, population and economy in China were used to reflect the WSS flow effect. The results showed that: the total material quantity of WSS in Inner Mongolia was 7.83 × 1012 kg in 2010 and 7.37 × 1012 kg in 2015, with a total value of 7.83 × 1010 CNY and 7.37 × 1010 CNY, respectively, of which 79.18% in 2010 and 79.92% in 2015 flowed to the downwind SBRs out of Inner Mongolia. The spatial transport paths and SBRs were mainly located in northern China, the Korean Peninsula, Japan, Mongolia and the Russian Far East in 2010 and 2015. The material and value flow rate of the WSS had spatial proximity features, resulting in differences in the benefits received by benefitting countries and provinces. The SBRs in China covered 67.50% and 65.67% of the total area of China in 2010 and 2015, respectively. The people benefitting amounted to 88.01% of the total population in China in 2010 and 86.58% in 2015, corresponding to a beneficial gross domestic product (GDP) of 92.00% and 90.50%, respectively, of China's total GDP in each year. Based on the spatiotemporal movements of the material and value flows of the WSS, this study revealed the spatial and temporal correspondences between the area's supply and benefits from the WSS of Inner Mongolia. It provides a scientific basis for decision-makers to coordinate interregional benefit transfers through wind erosion control in Inner Mongolia and ensure continuing flow of benefits to SBRs.

Evaluation of Sustainable Urban Development under Environmental Constraints: A Case Study of Jiangsu Province, China

Sustainable development is a long-term solution for urban development and a guideline for urban development. Only by better coordination around the population, resources, and environment can the city achieve sustained and steady development. In order to evaluate the efficiency of sustainable urban development under environmental constraints, this paper takes 13 prefecture-level cities in Jiangsu Province as an example. To address the infeasibility problem in the Malmquist-Luenberger (M-L) index, a modified M-L index analysis method based on the new directional distance function (DDF) is adopted. Combined with the consideration of desirable and undesirable outputs, a linear programming model for sustainable urban development evaluation is constructed to provide a scientific decision-making basis for sustainable development of the city. The results show that the growth of sustainable urban development efficiency is not only related to desirable outputs but also affected by undesirable outputs. Technical change is the main driver of most sustainable urban development efficiency growth. However, efficiency changes also affect the sustainable development potential of cities to a certain extent. Through the modified M-L index analysis, we analyze the characteristics of different regions of Jiangsu Province, the changes in efficiency and the impact of technological innovation on sustainable urban development, and give policy recommendations to promote sustainable urban development.

Preliminary Study on the Evaluation System of Technological Innovation Index for the Central Enterprises of International First-class Enterprises

The State-Owned Assets Supervision and Administration attached great importance to the construction of technological innovation capabilities of central enterprises, and clearly proposed to study the evaluation index system of technological innovation capabilities of central enterprises, carry out evaluation of technological innovation indexes, and guide and encourage enterprises to upgrade the level of technological innovation. Technological innovation has become a powerful driving force for continuously promoting the scientific development of central enterprises. It is of great significance for accelerating the improvement of the level of technological innovation of central enterprises to carry out the evaluation of central enterprises’ technological innovation index, establish an effective mechanism to guide technological innovation of all departments, and provide scientific decision-making basis for technological innovation of central enterprises. The core of this research revolves around the technology innovation index of central enterprise for building a world-class enterprise. First, systematically sort out the characteristics of technological innovation in world-class enterprises. Second, analyze the characteristics of technological innovation of central enterprises and the shortcomings of current state-owned enterprises’ technological characteristics compared with first-class enterprises. Third, build a technology innovation index evaluation system of world-class enterprises.

Science-based decision support for formulating crop fertilizer recommendations in sub-Saharan Africa

In sub-Saharan Africa, there is considerable spatial and temporal variability in relations between nutrient application and crop yield, due to varying inherent soil nutrients supply, soil moisture, crop management and germplasm. This variability affects fertilizer use efficiency and crop productivity. Therefore, development of decision systems that support formulation and delivery of site-specific fertilizer recommendations is important for increased crop yield and environmental protection. Nutrient Expert (NE) is a computer-based decision support system, which enables extension advisers to generate field- or area-specific fertilizer recommendations based on yield response to fertilizer and nutrient use efficiency. We calibrated NE for major maize agroecological zones in Nigeria, Ethiopia and Tanzania, with data generated from 735 on-farm nutrient omission trials conducted between 2015 and 2017. Between 2016 and 2018, 368 NE performance trials were conducted across the three countries in which recommendations generated with NE were evaluated relative to soil-test based recommendations, the current blanket fertilizer recommendations and a control with no fertilizer applied. Although maize yield response to fertilizer differed with geographic location; on average, maize yield response to nitrogen (N), phosphorus (P) and potassium (K) were respectively 2.4, 1.6 and 0.2 t ha−1 in Nigeria, 2.3, 0.9 and 0.2 t ha−1 in Ethiopia, and 1.5, 0.8 and 0.2 t ha−1 in Tanzania. Secondary and micronutrients increased maize yield only in specific areas in each country. Agronomic use efficiencies of N were 18, 22 and 13 kg grain kg−1 N, on average, in Nigeria, Ethiopia and Tanzania, respectively. In Nigeria, NE recommended lower amounts of P by 9 and 11 kg ha−1 and K by 24 and 38 kg ha−1 than soil-test based and regional fertilizer recommendations, respectively. Yet maize yield (4 t ha−1) was similar among the three methods. Agronomic use efficiencies of P and K (300 and 250 kg kg−1, respectively) were higher with NE than with the blanket recommendation (150 and 70 kg kg−1). In Ethiopia, NE and soil-test based respectively recommended lower amounts of P by 8 and 19 kg ha−1 than the blanket recommendations, but maize yield (6 t ha−1) was similar among the three methods. Overall, fertilizer recommendations generated with NE maintained high maize yield, but at a lower fertilizer input cost than conventional methods. NE was effective as a simple and cost-effective decision support tool for fine-tuning fertilizer recommendations to farm-specific conditions and offers an alternative to soil testing, which is hardly available to most smallholder farmers.

Method for Estimating Non-study Cigarette Use among Switchers to Low Nicotine Content Cigarettes in Ambulatory Clinical Studies

Background: FDA is considering to establish a product standard to reduce nicotine in cigarettes to make them “minimally addictive or non addictive.” FDA has funded many clinical studies where smokers are switched to smoking low nicotine cigarettes to determine a nicotine ceiling that is appropriate for the protection of the public health. Unlike typical clinical trials involving pharmaceuticals or medical devices, ambulatory studies with low nicotine cigarettes face a unique challenge in that conventional nicotine nonstudy cigarettes are readily available to participants when protocols require them to exclusively use study cigarettes. As a consequence, protocol deviation in non-study product use is a major limitation common in such ambulatory studies, with up to 80 percent of participants using non-study cigarettes during the study. There is no published method for estimating the magnitude of such protocol deviation, i.e., the number of non-study cigarettes smoked by participants, in such studies. Methods: We present a method for estimating the magnitude of noncompliance based on the proposition that the level of biomarker of exposure to a smoke constituent is proportional to the amount of the constituent per cigarette and the number of cigarettes smoked by participants. The method estimates the number of non-study cigarettes smoked by participants based on the discrepancies between the yield of smoke constituents (e.g., nicotine) and the level of the corresponding biomarkers measured in a study. Results: Data from a confined study confirmed the validity of this method. Under-reporting on the magnitude of non-study cigarette use is widespread across studies using different low nicotine cigarettes. Participants in one of the largest published studies under-reported the number of non-study cigarette used by 79-90%. Conclusions: Controlling and accurately estimating non-study cigarette use is critical for ambulatory low nicotine cigarette switching studies to ensure the resulting data can be appropriately evaluated to support science-based regulatory decision-making. In planning future studies, researchers should consider incorporating specific biomarkers that would enable objective assessment of both the prevalence and the magnitude of non-study cigarette use.

The usage of artificial intelligence in the commodity house price evaluation model

The current standardization and legalization of commercial housing price assessment is low. In addition, computer technology is less used in this field. Therefore, the evaluation of commercial housing prices can no longer meet the requirements of today’s economy and society. Traditional real estate assessment methods such as market comparison method, cost estimation method, income reduction method, etc., pay attention to market information, but tend to emphasize the total value of real estate in evaluation practice, and they ignore the impact of various constraints on real estate prices, so it is impossible to scientifically understand the influencing factors of real estate prices and their mechanisms of action, resulting in a lack of scientific basis for decision-making by governments, developers or property users. Therefore, this paper introduces the improved algorithm of BP neural network to establish the housing price evaluation model, which reduces the subjectivity and randomness in the evaluation process. This has certain reference for the development of China’s real estate assessment method. The evaluation results show that the real estate evaluation price of the network output is close to the actual price, with maximum error of 3.04%. This shows that the application of improved BP neural network model in real estate price evaluation is not only technically feasible, but also credible.

The Current Situation, Problems and Improvement of Ex-ante Performance Management in China

Budget decision-making is the first step in the process of budget management, which can have a huge impact on the effect of budget management. The correct decision can make budget expenditure achieve expected output, and the wrong decision will lead to a serious waste of budget funds. Therefore, improving the level of budget decision is the key to the full implementation of budget performance management in China. Ex-ante performance management is located in the front of budget management. It is to collect, sort out and analyze relevant information purposefully and systematically before budget decision-making. So, ex-ante performance management can provide scientific basis for budget decision-making and effectively improve the level of budget decision-making, which is of great significance to ensure the implementation effect of comprehensive budget performance management in China. Therefore, it is necessary to study the current situation of China's performance management in advance, find out the problems existing in the performance management in advance and put forward the corresponding countermeasures. This paper first clarifies the background of the implementation of Ex-ante performance management, then studies the current situation and existing problems of the implementation of Ex-ante performance management from the central and local perspectives, and finally puts forward corresponding countermeasures and suggestions.

Methods for High Voltage Transmission Line Detection Based on Image Recognition

With the development of national economy, the demand for electric power from all walks of life is expanding. How to prevent and discover the natural disaster and accident that harm the transmission line in time has become an important basic work to guarantee the power supply. Image identification and automatic alarm system of transmission lines adopts image technology to monitor and analyze and process transmission lines, which can automatically identify and alarm the safe operation of transmission lines, provide basis for scientific decision-making of power enterprises, and improve response efficiency of natural disasters and accidents. Based on the research direction of identification and detection of transmission lines, this paper summarizes the commonly used methods of detection of transmission lines.

Long-term agro-economic and environmental assessment of adaptive nutrient management on cropland fields with established structural conservation practices

On-farm adoption of agricultural conservation practices or management alternatives depends on conservation ethic, social pressure, regulatory attention, and perceived impact on yield and economic return. Although agro-economic and environmental impacts are assumed to conflict, little research has been conducted to address potential tradeoffs and provide a scientific basis for decision-making. Thus, this 16-year evaluation of adaptive nutrient management was conducted in the Texas Blackland Prairies ecoregion on six fields with structural conservation practices already in place. Each field was randomly selected to receive either commercial fertilizer or poultry litter at rates of 4.5 to 13.4 Mg ha⁻¹. Two major nutrient management adaptations were made (i.e., soil test nitrogen [N] rate recommendations in 2009, and reduction of fallow period length and cover cropping during prolonged fallow periods in 2013). Important results included (1) soil test recommendations that consider historical crop yields reduced N application 25% to 38% for low rates of poultry litter, but did not reduce profits; (2) interannual variability of economic and weather conditions contributed to the lack of statistically significant differences in profit, although profit reduction for high nutrient rate treatments was clear; and (3) litter application, especially at rates in excess of crop phosphorus (P) needs, also increased runoff P losses by 1 to 1.4 kg ha⁻¹ indicating the need for careful management of organic nutrient sources. Results of this long-term study showed that maintaining or increasing economic return does not have to be sacrificed to improve environmental impacts, which is an important consideration as producers make on-farm management decisions.

Inversion of Soil Water Content in Jiyang District Based on High Resolution Remote Sensing Image

The monitoring of soil water content plays an important role in agricultural production. This paper uses high resolution remote sensing image (GF-2 image) and measured soil water content data combined with dual-band, multi-band and PDI index inversion models to invert the soil water content of Xiyan and Wangxingjia Village of Jiyang District, Jinan City, and the effects of soil water content inversion were compared and verified. The results show that the decision coefficients of the multi-band inversion model reach 0.690, respectively, with the highest accuracy. More than 90% of the area in this study area has a soil water content greater than 0.15, which is dominated by suitable and wet soils, mainly distributed in the central part of the study area and near water bodies such as paddy fields, pit ponds and ditches; heavy drought, moderate drought, Light and dry soils account for a very small number, mainly distributed in the southwest direction of the study area, that is, the west side of Wangxingjia Village, distributed in a strip shape. It can be seen that GF-2 images can carry out the inversion of large-scale soil water content and provide a basis for scientific decision-making of agricultural production.