Standby State Research Articles

BW312 Hordeum vulgare semi-dwarf mutant exhibits a shifted metabolic profile towards pathogen resistance.

Plant hormonal mutants, which do not produce or are insensitive to hormones, are often affected in their growth and development, but other metabolic rearrangements might be involved. A trade-off between growth and stress response is necessary for the plant survival. Here, we explore the metabolic profile and the pathogen resistance of a brassinosteroid-insensitive Hordeum vulgare L. semi-dwarf mutant, BW312. We investigate BW312 metabolism through a chemical enrichment analysis, confirming a shifted metabolic profile towards pathogen resistance. The effective pathogen resistance of the mutant was tested in presence of Pyrenophora teres and Fusarium graminearum. Four compound families were increased in the mutant (pyrrolidines, basic amino acids, alkaloids, monounsaturated fatty acids), while two compound families were decreased (pyrrolidinones, anthocyanins). Dipeptides were also altered (increased and decreased). BW312 displayed a better resistance to Pyrenophora teres in the earliest stage of infection with a 21.5% decrease of the lesion length 10days after infection. BW312 also exhibited a reduced lesion length (43.3%) and a reduced browning of the lesions (55.5%) when exposed to Fusarium graminearum at the seedling stage. The observed metabolomic shift strongly suggests that the BW312 semi-dwarf mutant is in a primed state, resulting in a standby state of alertness to pathogens.

Smart System for Reducing Standby Energy Consumption in Residential Appliances

Residential consumption represents one of the most important percentages of total electricity consumption. A considerable number of household appliances consume energy even when they are not in operation, i.e., they are in the so-called standby state, thus producing additional costs, which become significant over time. In this context, one method to solve this problem is to develop a smart system capable of severing the power connection to devices in standby mode, thereby conserving energy and reducing the energy costs. The first step in the design of this system consists of the identification and accurate measurement of the standby state, which was carried out for three of the most common household appliances. Then, by using an ESP32 microcontroller, a system was designed to manage the operation of a relay module based on the current consumption of the connected equipment. Control over the system was achieved through a web application that works across all devices equipped with a web browser, offering functionalities to adjust current value time delays and to manually switch the system on or off. Finally, the deployment of this system across the three appliances studied led to a reduction in the energy consumption in standby mode of 26.68 kWh per month.

Static Characteristics and Energy Consumption of the Pressure-Compensated Pump

The motivation of this research was to assess the possibility of speed control for the selected pressure-compensated pump. Measured static characteristics of an axial piston pump with pressure compensation are presented in the paper. Based on these characteristics, the pump efficiencies are determined. The characteristics and efficiencies are determined for the different pump outlet pressures, pump speeds, relative displacements and for the different pressures set at the pressure compensator. In addition, the different methods of pump control were compared. These are displacement control, speed control and both controls. The efficiency of each control method was compared based on the determined mechanical input power at the pump drive shaft. By comparing these control methods, it was found that the combination of both control methods can achieve up to 93% savings of mechanical power in the controlled state (stand-by state). Also, the adverse effects resulting from each control method that reduces pump efficiency were defined.

Optimal maintenance policy considering imperfect switching for a multi‐state warm standby system

AbstractA novel maintenance policy for a two‐component warm standby system with multiple standby states is presented in this paper. Two standby states, that is, cold and warm standby, for components in the system are considered. Components can realize the transition from the cold standby to the warm standby state by periodic switching, intended to shorten recovery time and save system operating costs. Preventive maintenance (PM) and preventive switching (PS) of components are considered. In the PS strategy, the standby component can switch before the operating component fails. In addition, additional standby failure modes based on idle time are studied. Derive the long‐term average cost of the system through the semi‐regenerative process. A numerical example eventually verifies the feasibility of this paper's proposed maintenance and switching strategy.

Numerical studies of sCO2 Brayton cycle

This work describes the one-dimensional, thermo-hydraulic model of the sCO2 cycle Sofia developed to investigate optimal control methods and the behaviour of the cycle during operation. This dynamic model includes all devices such as turbomachinery, heat exchangers, valves, and piping including heat loss, in line with concept of the 1 MWe sCO2 cycle, to be realised in the site of a fossil power plant in the Czech Republic.The model assembly and calculations were conducted using the commercial Modelica-based library ClaRa + using the simulation environment Dymola and in combination with another Modelica-based library, UserInteraction; the real-time simulations, with some parameter changes during the calculation, are made and described in this paper.Nominal parameters were achieved during the steady-state simulation, except for the lower mass flow of sCO2. Transient simulation of power turbine start-up from standby state and results are also presented in this paper. The nominal state is achieved with the semi-automatic procedure in approx. 3 h. The simulation results allow more detailed analyses of control methods and a better understanding of real device control and behaviour during start-up, shutdown, or other transients.Careful manipulation of turbine valves in coordination with the pressuriser operation was identified as crucial for optimal control of the system. Also, the initial amount of CO2 in the pressuriser affects its behaviour during transients.

TEKSTİL ENDÜSTRİSİNDE DERİN ÖĞRENME KULLANARAK AŞIRI ELEKTRİK TÜKETİMİNİN ÖNLENMESİNE YÖNELİK BİR VAKA ÇALIŞMASI

Resources are the most critical input in the manufacturing industry therefore, resource consumption is an essential issue to be minimized. On the other hand, consumption depends on several parameters thus, it is difficult to estimate. Recently, Machine Learning (ML) and Deep Learning (DL) are powerful Artificial Intelligence (AI) subdomains for future prediction in any area. In this paper, a DL-supported electricity prediction method is designed for the textile industry as a case study in order to prevent resource over-consumption while the machines are in the standby state. This method provides dynamic consumption thresholds of electricity consumption by sliding window technique based Long-Short Term Memory (LSTM) model that helps the machines to interrupt manufacturing in their decision. These calculated thresholds are also compared with the results of Recurrent Neural Networks (RNN) and Gated Recurrent Units (GRU) as the other DL methods and Automated Regressive Integrated Moving Average (ARIMA) as a traditional method and then the results have been analyzed how close they are to real-time electricity consumption data at standby. According to the results, the LSTM model successfully predicts electricity consumption levels, sends an interrupt signal to Programmable Logic Controller (PLC) unit when the consumption levels reach the threshold and therefore prevents resource over-consumption.

Project 1M: A Do-It-Yourself (Diy) Physical Distancing Accurate Rechargeable Face Shield With A 20-Second Handwashing Timer

Amid the persistent challenges of the COVID-19 pandemic, there is an escalating need for innovative and accessible solutions that prioritize individual safety. Project 1M emerges as a Do-It-Yourself (DIY) Physical Distancing Accurate Rechargeable Face Shield, integrating advanced features tailored to the contemporary health landscape. A Real-Time Buzzer and LED Notification system serves as a cornerstone, instantly alerting wearers to breaches in the 1-meter physical distancing guideline. Complementary to this, an Embedded 20-second Handwashing Timer actively promotes thorough hand hygiene practices, aligning with global health recommendations. Prioritizing sustainability, the project incorporates a Recharging Capability, eliminating the need for frequent battery replacements. The culmination of these features results in an impressive 12 hours of active duration when all components are turned on, extending to an exceptional 32 hours in a normal standby and less-used state. This extended battery life not only ensures longevity but also accommodates diverse usage patterns, making Project 1M a dependable companion for daily activities. Beyond the technical features, Project 1M stands out as a comprehensive COVID-19 protection solution. The amalgamation of real-time alerts, hygiene promotion, and sustainable power management positions this DIY face shield as a tangible and accessible contribution to individual safety. Extensive trials and evaluations have validated the project's design and functionality, providing insights that underscore its potential impact in the ongoing efforts to combat infectious diseases. Project 1M represents a pivotal step towards empowering individuals to actively engage in safeguarding their health amidst the evolving landscape of global health challenges. As the project moves forward, these findings will inform potential refinements and optimizations, ensuring its continued relevance and effectiveness in the ongoing fight against the spread of infectious diseases.

The Calculation Method of the Floating Conductor Potential in the Ion Flow Field

For bipolar DC transmission projects, when one pole conductor is charged and running normally, and the other pole conductor is in a standby state (including cold standby and hot standby), if the standby pole conductor is not grounded, a high charging potential will appear on the surface. On the one hand, it will affect the insulation coordination and protection setting of the DC system. On the other hand, it will also affect the ion current and synthetic electric field on the ground. This article studies the calculation method of the potential of suspended conductors in the presence of floating conductors in the ion flow field, establishes a calculation model based on the minimum absolute value of the space charge density on the surface of the conductor, and calculates and analyzes the distribution of ionizing current and synthetic electric field below the ground of high-voltage DC lines in the presence of suspended conductors. The distribution laws of ground field strength and ion current in single-circuit bipolar DC transmission lines are studied when one pole is suspended, the other is operated, and when one circuit is operated. One circuit is shut down in double-circuit DC transmission lines on the same tower. For practical engineering, on the one hand, it is possible to predict the potential of suspended conductors in the ion flow field and propose adjustment plans for protection settings, insulation coordination, etc., in advance. On the other hand, when considering abnormal operating conditions, the impact of ion flow fields on the ground electromagnetic environment can be reduced by changing the geometric architecture and line selection.

Super-resolution imaging reveals the relationship between CaMKIIβ and drebrin within dendritic spines

Dendritic spines are unique postsynaptic structures that emerge from the dendrites of neurons. They undergo activity-dependent morphological changes known as structural plasticity. The changes involve actin cytoskeletal remodeling, which is regulated by actin-binding proteins. CaMKII is a crucial molecule in synaptic plasticity. Notably, CaMKIIβ subtype is known to bind to filamentous-actin and is closely involved in structural plasticity. We have shown that CaMKIIβ binds to drebrin, and is localized in spines as both drebrin-dependent and drebrin-independent pools. However, the nanoscale relationship between drebrin and CaMKIIβ within dendritic spines has not been clarified. In this study, we used stochastic optical reconstruction microscopy (STORM) to examine the detailed localization of these proteins. STORM imaging showed that CaMKIIβ co-localized with drebrin in the core region of spines, and localized in the submembrane region of spines without drebrin. Interestingly, the dissociation of CaMKIIβ and drebrin in the core region was induced by NMDA receptor activation. In drebrin knockdown neurons, CaMKIIβ was decreased in the core region but not in the submembrane region. Together it indicates that the clustering of CaMKIIβ in the spine core region is dependent on drebrin. These findings suggest that drebrin-dependent CaMKIIβ is in a standby state before its activation.

Energy efficiency improvement of industrial parts washers using state control

In recent years, the energy efficiency topic drastically increased its relevance in manufacturing industry management. One of the most supported strategies to reduce the energy consumed by manufacturing equipment is the machine state control during idle periods, triggering the machine in a standby state with low power request. This approach is aimed at reducing system energy consumption while not jeopardizing the overall production rate and it is referred to as energy efficient control (EEC). Policies implementing EEC techniques are proven to be effective in a manufacturing system but have been tested only for assembly and machining operations. This work is focused on industrial parts washers: widely used machines in manufacturing with significant energy consumption associated. The objective is to demonstrate the applicability and the potential of EEC strategies when applied to washing processes. Proper EEC policies are identified for an industrial parts washer operating in a real production line in the automotive sector. Different scenarios are analyzed and the focus is placed on the effect that these energy efficient actions have on the overall production system in terms of throughput and energy consumption. In this way, the industrial impact of the EEC application on the industrial parts washer is computed by running simulation experiments.

Energy-efficient control in multi-stage production lines with parallel machine workstations and production constraints

Nowadays, the growing interest in industry for enhancing manufacturing processes sustainability is a major trend. One of the most supported strategies to increase the energy-efficiency of manufacturing activities is the control of machine state towards the optimum trade-off between production rate and energy demand. This method is referred to as energy-efficient control and it triggers machines in a standby state with low power request. In this article, multi-stage production lines composed of identical parallel machine workstations are the systems of interest, and the energy-efficient control policies make use of buffer level information. Each machine can be switched off instantaneously and switched on with a stochastic startup time. Problem objective is to minimize the energy demand while ensuring production constraints. This article proposes a novel approach to solve the problem at hand. An exact model for two-stage system is formulated using a Markov Decision Process to be solved with a linear programming methodology. A novel technique, namely the Backward-Recursive approach, is used to address systems with more than two stages. Numerical experiments confirm the effectiveness of the proposed approach.

Galyean appreciation club review: a holistic perspective of the societal relevance of beef production and its impacts on climate change.

This article provides a science-based, data-driven perspective on the relevance of the beef herd in the U.S. to our society and greenhouse gas (GHG) contribution to climate change. Cattle operations are subject to criticism for their environmental burden, often based on incomplete information disseminated about their social, economic, nutritional, and ecological benefits and detriments. The 2019 data published by the U.S. Environmental Protection Agency reported that U.S. beef cattle emitted 22.6% of the total agricultural emissions, representing about 2.2% of the total anthropogenic emissions of CO2 equivalent (CO2e). Simulations from a computer model developed to address global energy and climate challenges, set to use extreme improvements in livestock and crop production systems, indicated a potential reduction in global CO2e emissions of 4.6% but without significant enhancement in the temperature change by 2030. There are many natural and anthropogenic sources of CH4 emissions. Contrary to the increased contribution of peatlands and water reservoirs to atmospheric CO2e, the steady decrease in the U.S. cattle population is estimated to have reduced its methane (CH4) emissions by about 30% from 1975 to 2021. This CH4 emission deacceleration of 2.46 Mt CO2e/yr2 might be even more significant than reported. Many opportunities exist to mitigate CH4 emissions of beef production, leading to a realistic prospect of a 5% to 15% reduction in the short term after considering the overlapping impacts of combined strategies. Reduction strategies include feeding synthetic chemicals that inactivate the methyl-coenzyme M reductase (the enzyme that catalyzes the last step of methanogenesis in the rumen), red seaweed or algae extracts, ionophore antibiotics, phytochemicals (e.g., condensed tannins and essential oils), and other nutritional manipulations. The proposed net-zero concept might not solve the global warming problem because it will only balance future anthropogenic GHG emissions with anthropogenic removals, leaving global warming on a standby state. Recommendations for consuming red meat products should consider human nutrition, health, and disease and remain independent of controversial evidence of causational relationships with perceived negative environmental impacts of beef production that are not based on scientific data.

Pandemizacija i nova normalnost

The paper investigates the phenomenon of a declared pandemic and the processes that take place within such a situation. It's about processes in education, culture, economy, and social life in general. Those processes could not have happened if the pandemic had not been declared. It can be said that we are living in a turning point that should establish a new state of affairs in public and private life. That new state of affairs implies a new paradigm representing a kind of refeudalization of various parameters related to the significant denial of various rights and freedoms. The new paradigm includes a significant degree of control, ie. various forms of supervision and forced medical treatments. The new state of affairs has its slogans such as "social distancing", "new normal", "digitalization", etc. Those slogans are contrasted with the slogans of freedom, equality, and fraternity that marked the creation of civil society during the French Revolution. The declaration of a pandemic enabled the introduction of restrictive measures that go beyond medicine and primarily relate to basic human rights and freedoms. In this way, from the sphere of medicine, it entered the sphere of philosophy, sociology, politics, and other areas of human social practice. Propaganda has produced a situation in which it has made fear a desirable state of affairs. Those who were not afraid, as a rule, were declared non-solidarity and irresponsible persons who endanger other people, the health system, the functioning of the state, etc. People agreed to the measures either out of primal existential fear or out of fear of punishment if they did not respect them. Deconstruction of the so-called old normal would also represent the deconstruction of the existing civil society and the establishment of new totalitarianism. The articles of recognized scientists, such as Kary Mullis, Luc Montagnier, John Ioannidis, etc., if they did not fit into the given matrix, were either ignored or declared unscientific. It could be argued that the declared pandemic was primarily a political project. Its factual ending also testifies to this. Pandemization entered a standby state when the Russian special military operation on the territory of Ukraine began in February 2022.

Big Data Clustering Using Chemical Reaction Optimization Technique: A Computational Symmetry Paradigm for Location-Aware Decision Support in Geospatial Query Processing

The emergence of geospatial big data has opened up new avenues for identifying urban environments. Although both geographic information systems (GIS) and expert systems (ES) have been useful in resolving geographical decision issues, they are not without their own shortcomings. The combination of GIS and ES has gained popularity due to the necessity of boosting the effectiveness of these tools in resolving very difficult spatial decision-making problems. The clustering method generates the functional effects necessary to apply spatial analysis techniques. In a symmetric clustering system, two or more nodes run applications and monitor each other simultaneously. This system is more efficient than an asymmetric system since it utilizes all available hardware and does not maintain a node in a hot standby state. However, it is still a major issue to figure out how to expand and speed up clustering algorithms without sacrificing efficiency. The work presented in this paper introduces an optimized hierarchical distributed k-medoid symmetric clustering algorithm for big data spatial query processing. To increase the k-medoid method’s efficiency and create more precise clusters, a hybrid approach combining the k-medoid and Chemical Reaction Optimization (CRO) techniques is presented. CRO is used in this approach to broaden the scope of the optimal medoid and improve clustering by obtaining more accurate data. The suggested paradigm solves the current technique’s issue of predicting the accurate clusters’ number. The suggested approach includes two phases: in the first phase, the local clusters are built using Apache Spark’s parallelism paradigm based on their portion of the whole dataset. In the second phase, the local clusters are merged to create condensed and reliable final clusters. The suggested approach condenses the data provided during aggregation and creates the ideal clusters’ number automatically based on the dataset’s structures. The suggested approach is robust and delivers high-quality results for spatial query analysis, as shown by experimental results. The proposed model reduces average query latency by 23%.

Optimal standby activation in m‐out‐of‐n systems: A preventive approach

AbstractThis article investigates an optimal preventive standby activation policy for an ‐out‐of‐ redundant system. We assume that for such a system, which starts operating at time , a standby component will be activated at either the failure time of the system or at a predetermined time , whichever occurs first. We first obtain the system reliability function under this switching policy as a function of . Then, we investigate the optimal switching time so that the mean time to failure of the system is maximized. The results indicate that the existence of an optimal value of depends on the lifetime of the standby redundancy and its virtual age in the standby state. Some illustrative examples are presented to examine the theoretical outcomes.

Thermal management of reversible solid oxide cells in the dynamic mode switching

Reversible solid oxide cell (rSOC) can flexibly switch between fuel cell and electrolyzer, making it promising for power generation and storage. However, the dynamic mode switching causes reversed electrochemical reactions and severe temperature fluctuation, leading to performance decline and even cell failure. Herein, we propose a thermal management strategy that combines rSOC with thermochemical energy storage (TES) to store/supply heat during exothermic/endothermic processes. Performance of the integrated new system is evaluated by a 2D non-adiabatic dynamic model. It is found that the maximum temperature difference across the cell surface can be reduced by 75.7 % at 0.75 V, where 18.21 % of the fuel enthalpy is stored in the TES section. Besides, a small air flow rate of 10 SCCM is enough to maintain a hot standby state during the shutdown stage, which reduces the energy consumption by 99.5 % compared with the hot air purging method. The temperature change rate in the switching process between the fuel cell mode and the shutdown stage is also decreased by 69 % on average. This work identifies the key characteristics of rSOC during mode switching and provides a new method towards its safe and economic operation when combining with fluctuating renewable powers.

Interactive Art Design and Color Perception Based on the Sparse Network and the VR System.

At present, with the gradual development of science and technology, people's life has also produced a lot of changes, the traditional communication technology has been gradually changed by the new computer technology, people's life has become more intelligent. However, many current artificial intelligence technologies rely on the promotion of network data. In the mobile terminal, especially in the poor state of some data network environment, many users' intelligence needs cannot be met. From the perspective of user interaction experience, this paper analyzes and investigates the interactive standby link in detail and systematically based on the perspective of context awareness and carries out a battle summary with the scientific, systematic, reasonable, and executable design methods suitable for an interactive standby state and puts forward the recommended items of matrix decomposition. The static information is embedded in the model. The status of information is imported as a dimension different from the previous matrix factorization model, and the accumulation of interaction between user's status conditions and project factors is considered, as well as the sensitivity difference between user and information project status. In order to obtain the global situation of user balance, the project prediction deviation caused by the vector and sensitivity to various conditions is needed. Finally, the training model gets the final prediction score value and puts forward the mobile system user interaction experience art design strategy based on context awareness, which provides a certain idea to meet the needs of mobile system users.

Electronic MOV-Based Voltage Clamping Circuit for DC Solid-State Circuit Breaker Applications

Traditional metal oxide varistor (MOV) based voltage clamping circuits (VCC) used in solid-state circuit breakers reduce the efficiency of the system due to the high voltage requirement imposed on the main solid-state device. The voltage burden arises from the material properties of the MOV which fixes its clamping voltage at a value more than twice its maximum continuous dc voltage rating. This letter proposes a novel and reliable VCC termed as the electronic MOV (eMOV) to altogether decouple the peak clamping voltage of the MOV from the nominal dc voltage of the system aiming to improve the voltage suppression index (VSI = <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V_pk</i> / <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dc</sub> ) of the VCC, thereby reducing the system conduction losses. The eMOV introduces a breakover diode to share the system dc voltage during the standby state and a Silicon controlled rectifier to provide the bypass path for the fault current for quick MOV insertion. Comprehensive design criteria are developed to guide the component selection and overall design. Experimental results at 2 kV dc and 1.1 kA peak current are presented to validate the operation of the proposed eMOV based VCC.

Investigation of Flow Characteristics of Flow Passage Components in Francis Turbine under No-load and 50% Load operating conditions

Due to the varying demand of power grid for the electric supply of hydraulic power stations, the units are often under low-load operating condition and no-load standby state, causing a significant flow instability in hydraulic generator units. To further investigate the inside flow characteristics of hydraulic turbines under such operating conditions. In this study, a CFD (computational fluid dynamics) numerical simulation with applying RNG (Renorm alization Group) k-ε turbulence model is performed to study the inside flow characteristics of each flow passage components of a Francis turbine under no-load and 50% load conditions. The results indicate that under the two operating conditions, the flow distribution inside and outside the draft tube pier is significantly nonuniform. Simultaneously, the large-scale vortex in the runner area caused by the high-speed flow in the vane-free area with small opening and the nonuniform flow velocity distribution in the straight cone section of the draft tube are the main reasons for the increase of hydraulic loss and the decrease of efficiency.

Sistem Monitoring Instrument Air System Berbasis Internet Of Things di PT.Parna Raya

There is an operation process for facility &amp; equipment support in the distribution process of the oil and gas company such as the Pressure Regulating System and Process Shutdown Valve. The supporting equipment uses pneumatic actuators as a driving force whose power source comes from air, as from the fact the compressor as an air producer is still manually used and the air pressure in the air receiver is not monitored from the control room. The purpose of this research is to develop the previous system by creating an integrated system that can be monitored remotely in real time by adding several electronic devices and utilizing Internet of Things technology. Based on the research that have been carried out, the pressure sensor has good accuracy with an average error of 0.06%, so it can be a reference in monitoring the pressure on the air receiver and a notification alarm will appear if the pressure on the air receiver reads 5.5 Bar as evidenced by testing 10 times the average pressure read on the blynk app of 5,460 Bar. Hardware and software function properly according to the design, air pressure at the air receiver and status of the compressor in stand-by or running state can be monitored through the blynk app, so that the gas distribution process does not stop again