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38,005 result(s) for "Integrated control"
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WHEAT STRIPE RUST AND INTEGRATION OF SUSTAINABLE CONTROL STRATEGIES IN CHINA
• Stripe rust caused substantial yield losses in China. • P. striiformis is highly variable and the change from avirulence to virulence. • Different comprehensive control strategies were adopted in different epidemic region. Stripe (yellow) rust caused by Puccinia striiformis f. sp. tritici occurs in almost all wheat-producing regions of the world. Severe countrywide epidemics in China have caused substantial yield losses. Growing resistant cultivars is the best strategy to control this disease but the pathogen can overcome resistance in wheat cultivars. The high variation in the virulence of the pathogen combined with the large areas of susceptible wheat cultivars enables the pathogen population to increase rapidly and disperse over long distances under favorable environmental conditions, resulting in severe pandemics within cropping seasons. Current stripe rust control measures are based on many years of research including the underlying epidemiology regarding year-to-year survival of the pathogen, pathways of pathogen dispersal within seasons and years, the role of P. striiformis sexual hybridization, the use of resistance sources in breeding programs, and year-round surveillance of national wheat crops that are present in different parts of the country throughout the year. All these strategies depend on accurate prediction of epidemics, more precise use of fungicides to meet national requirements and better deployment of resistance genes. New ideas with potential application in sustainable protection of stripe rust include negative regulatory gene editing, resistance gene overexpression and biological control based on microbiomes.
Semiconductor manufacturing handbook
After a difficult period, the semiconductor manufacturing industry is growing again, with significant prospects in the world market. This concise reference brings the full range of semiconductor fabrication technologies and methods to the engineer's fingertips.
Research on prediction algorithm of effluent quality and development of integrated control system for waste-water treatment
Research is implemented to protect the environment from an epidemic of chemical materials that could render living conditions hazardous. In order to efficiently use productivity while maintaining a constant and reliable level of waste quality, severe regulations regarding Waste-Water Treatment and Control Systems (WWTCS) must be adopted to mitigate the serious nature of water pollution and impure performance. Suboptimal treatment efficiency and use of resources are the results of the methods used for WWTCS, which are not highly susceptible to changing impact features and complex biological systems. The present study presented a prediction algorithm and an Integrated Control System (ICS) to address the problems of conventional methods. This research proposes a Deep Learning (DL) for the quality of wastewater prediction that employs a Quantile Regression-Random Forest (QR-RF) meta-learner when combined with Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU). The proposed method has been implemented into practice and tested at Asia’s Jiangsu Province Metropolitan Waste-Water Treatment Plant (WWTP). With a Root Mean Absolute Error (RMSE) of 4.76 mg/L for 24-h horizons and a Mean Absolute Error (MAE) of 0.85 mg/L for 1-h predictions, the proposed model outperforms conventional methods in terms of prediction accuracy. The ICS is superior to standard WWTCS by a vital error boundary, minimizing energy consumption by 17% and boosting chemical-based consumption optimization by 24%. With an average removal rate of 94.23% for Chemical Oxygen Demand (COD) compared to 88.76% for standard systems, the findings from experiments exhibited significant performance improvements.
An Overview of Emerging and Sustainable Technologies for Increased Energy Efficiency and Carbon Emission Mitigation in Buildings
The building sector accounts for a significant proportion of global energy usage and carbon dioxide emissions. It is important to explore technological advances to curtail building energy usage to support the transition to a sustainable energy future. This study provides an overview of emerging and sustainable technologies and strategies that can assist in achieving building decarbonization. The main technologies reviewed include uncertainty-based design, renewable integration in buildings, thermal energy storage, heat pump technologies, thermal energy sharing, building retrofits, demand flexibility, data-driven modeling, improved control, and grid-buildings integrated control. The review results indicated that these emerging and sustainable technologies showed great potential in reducing building operating costs and carbon footprint. The synergy among these technologies is an important area that should be explored. An appropriate combination of these technologies can help achieve grid-responsive net-zero energy buildings, which is anticipated to be one of the best options to simultaneously reduce building emissions, energy consumption, and operating costs, as well as support dynamic supply conditions of the renewable energy-powered grids. However, to unlock the full potential of these technologies, collaborative efforts between different stakeholders are needed to facilitate their integration and deployment on a larger and wider scale.
Integrated Pest Management
Integrated Pest Management: Current Concepts and Ecological Perspective presents an overview of alternative measures to traditional pest management practices using biological control and biotechnology.
An integrated anthracnose management approach in Tommy Atkins mango cultivars in Cundinamarca - Colombia
Anthracnose, caused by Colletotrichum gloeosporioides in mango production, can lead to crop losses of 60 %. Synthetic fungicides constitute its leading management strategy. We evaluated combinations of different management practices to control anthracnose in a commercial Tommy Atkins mango grove in 2015 and 2016. We followed a randomized complete block experimental design with a subdivided plot arrangement composed of 12 treatments, three replicates per treatment, and one mango tree per replicate for 36 trees. Pruning was practiced at plot level (with and without pruning), nutrients were applied to subplots (soil fertilizer, foliar nutrient application, and no nutrient supply), and at sub-subplot level, three anthracnose management treatments were given (chemical, biological, and no treatment). In 2015 and 2016, the treatments involving natural or biological applications against anthracnose plus nutrient supply led to the most significant reductions in quiescent leaf infections and disease presence in flowers and fruits. In addition, pruning at specific crop development stages improved results. In light of our results, this integrated anthracnose management approach in mango production can deliver the expected results if implemented consistently.
Feasibility and safety of integrating mass drug administration for helminth control with seasonal malaria chemoprevention among Senegalese children: a randomized controlled, observer-blind trial
Background The overlap in the epidemiology of malaria and helminths has been identified as a potential area to exploit for the development of an integrated control strategy that may help to achieve elimination of malaria and helminths. A randomized, controlled, observer-blind trial was conducted to assess the feasibility and safety of combining mass drug administration (MDA) for schistosomiasis and soil transmitted helminths (STH) with seasonal malaria chemoprevention (SMC) among children living in Senegal. Methods Female and male children aged 1–14 years were randomized 1:1:1, to receive Vitamin A and Zinc on Day 0, followed by SMC drugs (sulfadoxine-pyrimethamine and amodiaquine) on Days 1–3 (control group); or praziquantel and Vitamin A on Day 0, followed by SMC drugs on Days 1–3 (treatment group 1); or albendazole and praziquantel on Day 0, followed by SMC drugs on Days 1–3 (treatment group 2). Safety assessment was performed by collecting adverse events from all children for six subsequent days following administration of the study drugs. Pre- and post-intervention, blood samples were collected for determination of haemoglobin concentration, malaria microscopy, and PCR assays. Stool samples were analyzed using Kato-Katz, Merthiolate-iodine-formalin and PCR methods. Urine filtration, PCR and circulating cathodic antigen tests were also performed. Results From 9 to 22 June 2022, 627 children aged 1–14 years were randomized into the three groups described above. Mild, transient vomiting was observed in 12.6% (26/206) of children in treatment group 2, in 10.6% (22/207) in group 1, and in 4.2% (9/214) in the control group (p = 0.005). Pre-intervention, the geometric mean value of Plasmodium falciparum parasite density was highest among children who received albendazole, praziquantel with SMC drugs. Post-intervention, the parasite density was highest among children who received SMC drugs only. Children who received praziquantel and SMC drugs had a lower risk of developing severe anaemia than their counterparts who received SMC drugs alone (OR = 0.81, 95% CI 0.13–5.00, p = 0.63). Conclusions Integration of MDA for helminths with SMC drugs was safe and feasible among Senegalese children. These findings support further evaluation of the integrated control model. Trial registration : The study is registered at Clinical Trial.gov NCT05354258.
Integrating new technologies for striga control
Witchweeds (Striga species) decimate agriculture in much of Africa and parts of Asia, attacking the major cereal grains and legumes, and halving the already very low yields of subsistence farmers. Several years of research have provided promising technologies, based on the fundamental biology of the parasite–host associations, for dealing with this scourge. However, there is an apparent realization that these technologies will fail because highly successful weeds such as Striga evolve resistance to all types of controls unless proven methods are integrated with each other for a more sustainable solution.
Autonomous Earthwork Machinery for Urban Construction: A Review of Integrated Control, Fleet Coordination, and Safety Assurance
Autonomous earthwork machinery is gaining traction as a means to boost productivity and safety on space-constrained urban sites, yet the fast-growing literature has not been fully integrated. To clarify current knowledge, we systematically searched Scopus and screened 597 records, retaining 157 peer-reviewed papers (2015–March 2025) that address autonomy, integrated control, or risk mitigation for excavators, bulldozers, and loaders. Descriptive statistics, VOSviewer mapping, and qualitative synthesis show the output rising rapidly and peaking at 30 papers in 2024, led by China, Korea, and the USA. Four tightly linked themes dominate: perception-driven machine autonomy, IoT-enabled integrated control systems, multi-sensor safety strategies, and the first demonstrations of fleet-level collaboration (e.g., coordinated excavator clusters and unmanned aerial vehicle and unmanned ground vehicle (UAV–UGV) site preparation). Advances include centimeter-scale path tracking, real-time vision-light detection and ranging (LiDAR) fusion and geofenced safety envelopes, but formal validation protocols and robust inter-machine communication remain open challenges. The review distils five research priorities, including adaptive perception and artificial intelligence (AI), digital-twin integration with building information modeling (BIM), cooperative multi-robot planning, rigorous safety assurance, and human–automation partnership that must be addressed to transform isolated prototypes into connected, self-optimizing fleets capable of delivering safer, faster, and more sustainable urban construction.