Efficiency Improvement Research Articles

Out-of-focus holography at the Effelsberg telescope. Systematic measurements of the surface of a 100m telescope using OOF holography

Out-of-focus (OOF) holography can be used to determine the aperture deformations of radio telescopes that lead to errors in the phase of the complex aperture distribution. In contrast to traditional methods, OOF holography can be performed without a reference antenna, which has a number of practical advantages. The aim of this work is to develop a standard procedure for OOF holography at the Effelsberg telescope. This includes performing OOF holography observations and the development of dedicated software, the pyoof package, to compute aberrations of the telescope's optical system. Based on the OOF holography method developed at the Green Bank telescope, we adapted the approach to the Effelsberg 100m telescope in order to determine the aberrations of the aperture phase distribution (phase-error maps). The developed OOF holography software is presented as well as the results from observations at Effelsberg. Early results reveal gravitation-related residual deformation not contained in the previously existing aperture and pointing model, and hence we propose changes to the model to counteract aberrations in the telescope's surface. The OOF holography method (observations and pyoof package) works as expected at the Effelsberg 100m telescope and is able to validate the good performance of the existing finite element model. Test measurements show that slight improvements of the aperture efficiency and gain elevation dependence are possible but limited in the current configuration.

Improvement of Efficiency of Inverters in Hydro Photovoltaic Power Station with Particle Swarm Optimization

In the sparsely populated areas without electricity, the hydro photovoltaic power station is a feasible solution for electricity supply. The strategy of distributing the power among the inverters is critical to the efficiency of them. The conventional distributing strategies result in low efficiency of the inverters. In order to improve the efficiency, this paper analysed the loss and efficiency characteristics of the inverter and expressed the power distributing problem as an optimal control problem minimizing the total loss for the inverters. The optimal control problem was solved with particle swarm optimization and the efficiency optimum power distribution strategies in three operation scenarios were obtained. The quantitative analysis method was adopted to evaluate the effect of the efficiency optimum power distribution strategies. The total efficiency of the inverters with the optimal strategies and the conventional strategies were calculated respectively.  The optimal distribution strategies were compared quantitatively with conventional power distribution strategies on the basis of the efficiency. The results demonstrated the validity of the strategies obtained in this paper in improving the total efficiency of the inverters.

Power Efficiency Improvement in Elastic Optical Networks Using Ring Structure with Optimized Power Routing

Power Efficiency Improvement in Elastic Optical Networks Using Ring Structure with Optimized Power Routing

Approach to Design of Piezoelectric Energy Harvester for Sensors on Electric Machine Rotors

The reliability and efficiency of components are key aspects in the automotive industry. Electric machines become the focus of development. Thus, improvements in efficiency and reliability have gained significance. While it is established to attach sensors to the fixed parts of machines, such as stators, moving parts like rotors pose a major challenge due to the power supply. Piezoelectric generators can operate as energy harvesters on rotors and thus enable the rotor-based integration of sensors. The research in this article proposes the first approach to the design of a piezoelectric energy harvester (PEH) for an electric machine rotor dedicated to powering a wireless sensor system. After introducing the field of PEHs, the integration of the proposed device on a rotor shaft is presented. Further, a gap between the provided and needed data for the design of a PEH is identified. To overcome this gap, a method is presented, starting with the definition of the rotor shaft dimensions and the applied mechanical loads, including a method for the calculation of the imbalance of the rotor. With the first set of dimensions of the shaft and PEH, a co-simulation is performed to calculate the power output of this rotor and PEH set. The results of the simulation indicate the feasible implementation of the PEH on the rotor, providing enough energy to power a temperature sensor.

The impact of mindfulness training on the attention to facial expressions among undergraduates

AbstractThe improvements in attention by mindfulness training have been proved. However, the effects of mindfulness training on attention to emotional stimuli were mixed. We employed a randomized, controlled design to investigate the effects of mindfulness training on attention to emotional expressions, and investigated whether baseline levels of dispositional mindfulness and emotional intelligence would moderate the intervention effects. Forty participants received 8‐week mindfulness training, and another forty participants attended two lectures about mindfulness. All participants completed the visual search task, the Five Facet Mindfulness Questionnaire, and the Emotional Intelligence Scale at both pre‐training and post‐training. The results showed that the improvements in search efficiencies were larger in the mindfulness group than those in the control group for sad and angry faces, but not for happy faces. In addition, baseline emotional intelligence but not dispositional mindfulness played a significant moderating role in the relationship between mindfulness training and emotional attention to sadness and anger. The search efficiencies of negative emotions (i.e., anger and sadness) but not positive emotions (i.e., happiness) were significantly improved by mindfulness training. Individuals with a high level of baseline emotional intelligence showed significant improvement in search efficiencies relative to those with a low level of emotional intelligence.

Factors Governing the Presodiation Degree of Hard Carbon Anode for Sodium Ion Batteries

Abstract This study explores the improvement of sodium-ion batteries by presodiating hard carbon anodes, with the goal of reducing initial capacity loss and enhancing the overall electrochemical performance of full cells. Using Na-biphenyl for presodiation and exploring its effects under various conditions—such as electrolyte composition and electrode loading—alongside two different cathode configurations (Na-stoichiometry Na3V2(PO4)3 and Na-deficient Na0.44MnO2), we seek to elevate the overall electrochemical performance of sodium-ion batteries. Our findings reveal the significance of finely tuning presodiation conditions leading to significant improvements in both initial Coulombic Efficiency and the cycling stability of full cells. Furthermore, a comparative analysis of the solid electrolyte interface formed through both chemical and electrochemical presodiation methods reveals significant similarities in impedance characteristics. This research provides valuable insights into the impact of presodiation on hard carbon anodes, offering a pathway to enhance the practical application of presodiation technology for sodium-ion batteries.

Enhancing methane formation in carbon dioxide hydrogenation on nickel clusters with zirconium additives: Exploring active sites, reaction pathways, and catalytic mechanisms

This study focuses on the catalytic reaction of carbon dioxide (CO2) hydrogenation using 0.5 wt% nickel (Ni) deposited on silica oxide support (SiO2). Initially, these Ni clusters exhibit limited catalytic activity and selectivity toward carbon monoxide (CO) formation. However, the introduction of zirconium ions (Zr4+) onto the Ni clusters leads to a remarkable improvement in the catalytic efficiency of CO2 hydrogenation and methane (CH4) production. The interaction between Ni and ZrO2 generates interfacial sites that play a multifaceted role. These sites facilitate the binding of acidic CO2 and promote the atomic hydrogen migration from ZrO2 to Ni. Consequently, the creation of interfacial sites on the Ni catalysts directly enhances the rate of CO2 hydrogenation while also increasing CH4 selectivity. The primary intermediate in this process appears to be monodentate formate species, which can undergo direct decomposition to CO or conversion into formic acid intermediates. The formic acid intermediates subsequently undergo hydrogenation, ultimately leading to the production of CH4.

Reference monopile designs for US East Coast sites supporting the IEA 15 MW reference turbine using a novel conceptual design methodology

A novel conceptual design methodology was developed and implemented to design twelve reference monopile foundations, compatible with the IEA 15 MW reference turbine. The designs are position-specific, corresponding to planned, US East Coast, wind energy development areas. The monopiles were designed considering the fatigue limit state (FLS), ultimate limit state (ULS), serviceability limit state (SLS), and natural frequency analysis (NFA), following an intentionally reduced subset of design load cases (DLCs) in IEC 61400-3-1. In 11 of 12 cases, the diameter and wall thicknesses of the monopile foundations were found to be determined by FLS criteria. The exception was one position subjected to a combination of breaking waves and a large significant wave height. For the 11 positions governed entirely by FLS, the maximum ULS utilization ratios varied between 0.63 and 0.81, indicating significant reserve capacity for the ultimate limit state. Fatigue damage during turbine idling was found to be an important contributor to lifetime fatigue damage, despite having a relatively small probability of occurrence. The novel design methodology described herein includes a preliminary FLS assessment step, which was found to be an efficient way to select an initial foundation geometry, while providing a 92% improvement in computational efficiency.

Research on Establishment and Application of Evaluation System of Urban Energy Strategy Development Indicators under the Perspective of Carbon Neutrality

A scientific, comprehensive and integrated assessment of urban energy development is of great significance for the establishment of a clean, low-carbon and efficient urban modern energy system. From the perspective of carbon neutrality, this paper sets 25 evaluation indicators in seven dimensions: energy supply, energy consumption, energy efficiency improvement, clean and low-carbon, safety and reliability, low-carbon transport, and scientific and technological innovation, and constructs a secondary indicator system for evaluating the strategic development of urban energy. The system adopts the hierarchical analysis method to determine the weights of the indicators, the double-baseline progression method to standardize the indicator scores, and finally the weighted composite index method to calculate the level of urban energy strategy development. This paper applies the index system to evaluate the current energy development status of Wenzhou city in 2020 and 2022, and to predict the energy strategy development in 2025 and 2030. The scores of Wenzhou city's urban energy strategy development level in the corresponding four periods are 63.56, 70.59, 77.87 and 85.06, indicating that by 2023, Wenzhou city's urban energy development level will go from medium development to high development. Wenzhou City should accelerate the proportion of renewable energy in the future. It is necessary to complement multiple energy sources and improve the integration of heat, electricity, gas and cold. In terms of end consumption, it is necessary to improve the efficiency of energy use, reduce energy intensity, implement electric energy substitution and form an energy consumption pattern centered on electricity.

Air Purification Performance Analysis of Magnetic Fluid Filter with AC Non-Thermal Plasma Discharge

Air pollution caused by particulate matter (PM) is a worldwide concern. PM is particularly problematic from fossil-fuel-based energy conversion devices. For PM collection, a low-pressure loss method is ideal. Although PM collection via electrostatic force is an effective method with low pressure loss for PM with a wide range of diameters, it is difficult to apply to low-resistive PM, such as diesel particulates, owing to re-entrainment on the collection electrode. A magnetic fluid filter with an AC non-thermal plasma discharge solves the problem of re-entrainment. Based on our previous study, we hypothesized that an increase in the number of magnetic fluid spikes leads to an improvement in collection efficiencies with energy conservation. In this study, experiments are performed to verify this hypothesis. By improving our previous experimental methodology, the experiments include not only collection efficiency but also pressure loss, power consumption, and ozone generation efficiency. PM collection efficiencies using diesel fine particles and the ozone generation efficiencies required for air purification are investigated under different discharge conditions. The results revealed that the PM collection and ozone generation efficiencies increase proportionally with the number of spikes of the magnetic fluid with discharge, as hypothesized. The resulting PM collection and ozone generation efficiencies are sufficiently high for air purification.

Growth of Life and Non-life Insurance Market in India

In the midst of high cost of health care both at the macro and micro levels, health insurance becomes a viable alternative for financing health care in India. Health insurance is fast emerging as an important mechanism to finance health care needs of the people. The insurance industry in India has witnessed an impressive growth rate over the last two decades driven by the greater private sector participation and an improvement in distribution capabilities, along with substantial improvements in operational efficiencies. The paper presents the growth of life and non-life health insurance in India

Hybrid Energy-Efficient Task Offloading Algorithm (HEETA): A Framework for Optimizing Edge Computing Offloading Decisions

In the evolving realm of Mobile Edge Computing (MEC), efficient task offloading remains pivotal. This paper introduces the Hybrid Energy-Efficient Task Offloading Algorithm (HEETA) to address the deficiencies of the current Joint Optimization Task Offloading Strategy based on Particle Swarm Optimization (JOBPSO). Drawing from a broad dataset encompassing diverse MEC operational variables, HEETA exhibits exemplary performance metrics, with a notable mean fitness of approximately 0.99984 and a minimal standard deviation of 0.000116. Such metrics not only reflect HEETA's robustness but also its adaptability across multifaceted MEC parameters. Furthermore, its dynamic nature facilitates adaptability to variables including task numbers, computational capacity, and latency constraints, resulting in marked improvements in energy efficiency. Quantitative evaluations, as evidenced by a performance matrix, position HEETA's global best fitness values between approximately 0.9998 and 0.9999. While HEETA signifies a monumental step in enhancing energy efficiency, prolonging device longevity, and optimizing overall MEC system performance, the research acknowledges potential limitations, emphasizing the imperatives of accurate modeling and subsequent validations within distinct MEC environments.

Large-scale photonic chiplet Taichi empowers 160-TOPS/W artificial general intelligence.

The pursuit of artificial general intelligence (AGI) continuously demands higher computing performance. Despite the superior processing speed and efficiency of integrated photonic circuits, their capacity and scalability are restricted by unavoidable errors, such that only simple tasks and shallow models are realized. To support modern AGIs, we designed Taichi-large-scale photonic chiplets based on an integrated diffractive-interference hybrid design and a general distributed computing architecture that has millions-of-neurons capability with 160-tera-operations per second per watt (TOPS/W) energy efficiency. Taichi experimentally achieved on-chip 1000-category-level classification (testing at 91.89% accuracy in the 1623-category Omniglot dataset) and high-fidelity artificial intelligence-generated content with up to two orders of magnitude of improvement in efficiency. Taichi paves the way for large-scale photonic computing and advanced tasks, further exploiting the flexibility and potential of photonics for modern AGI.

Efficiency Improvements Must be Holistic

Efficiency Improvements Must be Holistic

Complementarities between product and process innovation and their effects on employment: a firm-level analysis of manufacturing firms in Colombia

ABSTRACT The introduction or adoption of innovations at the firm level has consequences for job creation that may differ across low-middle and high-income countries. Also, the type of innovation that firms introduce, such as process or product innovations, can affect employment through different channels. This paper aims to study the effects of innovation on employment growth at the firm level using a framework that considers the nature of innovation and the relative efficiency of the firms. The study uses a rich panel dataset that combines information from two different surveys in Colombia: the Annual Manufacturing Survey and the Survey on Development and Technological Innovation in the Manufacturing Sector. The article provides empirical evidence supporting the idea that the nature of innovation in the country involves complementarities between process and product innovations. The paper discusses how this result is related to the patterns of innovation in middle income countries, which need not only new technologies but also imitation of processes and products. Another novelty of this analysis is the study of displacement effects of process innovation through improvements in the relative efficiency of the firms. Findings show that some firms reduce employment from process innovations, reflecting high heterogeneity in efficiency among firms.

Design of a tunable bacterial gene expression system using engineered σ factors.

The synthesis of organic compounds involves the action of multiple enzymes in a biosynthetic pathway. Incorporating such biosynthetic pathways into microbes often leads to substantial cellular and metabolic stress resulting in low titers of the target compound. This limitation can be offset, in part, by optimizing enzyme efficiency and cellular enzyme concentration. The former involves significant efforts to achieve improvements in catalytic efficiency with the caveat that the metabolic load on a microbial cell imposed by the overexpression of the exogenous enzyme could result in reduced cell fitness. Here, we demonstrate the feasibility of engineered σ factors to modulate gene expression levels without significant genetic engineering. We note that changing the sequence of two flexible polypeptide loops without any changes to the structural scaffold of the transcription initiation factor σE could modulate the expression levels of the target genes. This ability provides a route to improve the efficiency of a biosynthetic pathway without altering the overall genomic makeup. The σE chimera library thus provides an avenue for pre-determined conditional gene expression of specific genes in Escherichia coli.

A new synergistic hydrocolloid with superior rheology: Locust bean /xanthan gum binary solution powdered by different drying methods

In the current study, a novel gum powder containing locust bean and xanthan gums was prepared by three different drying methods of their synergistic aqueous solutions: direct cabinet drying (CD), drying after alcohol precipitation (PD), and direct freeze drying (FD). The purpose of this process is to develop ready-to-use synergistic gum powders with improved rheological properties by modifying intermolecular interactions. Significant improvements in viscosity, consistency efficiency and pseudoplastic character were observed for PD, followed by CD and FD, as well as the higher values of G′ and G″ values of PD, indicating a stronger entanglement network development between the macromolecules for PD. PD exhibited better elasticity and shear resistance compared to FD and CD in the strain sweep test. In Lissajous curves, straight line shapes were found for synergistic solutions at low strain, which continued for increasing strain values for PD and CD. However, the pronounced viscous behavior was found for FD at 500% strain. Compared to CD and FD, PD exhibited a more desirable thixotropic character. A lower zeta potential was observed in the production of synergistic gums using the PD process. Gel strength was found to be higher for PD. Therefore, PD was a more effective method to produce a ready-to-use synergistic powder with better viscoelastic properties and a more stable solution.

Expectations and Outcomes when Quantifying Energy Improvements Achieved by Building Envelope Retrofitting

This paper assesses the energy efficiency of two buildings constructed in the 1960s in Madrid. One of the buildings is refurbished including passive energy efficiency improvements, while the other remains in its original state. The area is one of a series of low-income residential inefficient developments built by the state on the capital’s outskirts in the 1950s. Their buildings require huge amounts of energy to meet occupants’ basic energy needs. This paper quantifies the energy savings and improved comfort achieved by building envelope energy retrofitting. For this purpose, it proposes a comprehensive methodology spanning data monitoring in homes in buildings, occupant surveys and energy simulation models—a standard approach to estimating improvement potential. Our aim is to compare the expected energy savings predicted by energy certificates with monitored data. The paper concludes that the comfort level in the retrofitted building improved tangibly but that the differing behaviours of the building’s occupants make the energy saving difficult to quantify with any precision. The calibrated model targets energy consumption savings after renovation of approximately 25% in heating and 50% in cooling for a typical household of four people with basic comfort needs reasonably met. Regarding heating consumption, the results of the calibrated model are lower than expected savings using the official certificate input data. However, cooling consumption savings were found to be greater than expected.

Unleashing Deep Learning: Transforming E-commerce Profit Prediction with CNNs

This research examines the potential of Convolutional Neural Networks (CNNs), including VGG16, ResNet50, and InceptionV3, in predicting ecommerce profits. Emphasizing the importance of high-quality datasets, the study showcases the superior performance of CNN models over traditional algorithms, particularly noting a notable accuracy rate of 92.55% with CNN (VGG16). These results highlight deep learning's capability to extract actionable insights from complex ecommerce data, offering significant opportunities for revenue optimization and operational efficiency improvement. The conclusion underscores the need for investment in infrastructure and expertise for successful CNN integration, alongside ethical and privacy considerations. This research contributes valuable insights to the discourse on deep learning in ecommerce, offering guidance to businesses navigating the competitive global market landscape.

Design and Techno-economic Analysis of an Improved Multipurpose Cooker Stove

In response to the growing concerns surrounding the adverse health and environmental impacts of inefficient and hazardous traditional cooking fuels and stoves, this research aims to design and assess the performance of an improved multipurpose cooker stove. The study focuses on Zambia, a country deeply affected by air pollution and deforestation due to charcoal and firewood production using inefficient cooking stoves called Mbaula. The primary objective is to create an economically viable and environmentally friendly cooking stove that addresses the sustainability challenges of traditional cooking practices. The research is guided by key objectives. The study outlines the design process of the improved multipurpose cooker stove, emphasizing the incorporation of sustainable design principles. The improved multipurpose cooker stove demonstrated a thermal efficiency of 87.49%, significantly higher than the 11.88% thermal efficiency of traditional stoves. This improvement in efficiency is crucial for reducing fuel consumption and maximizing heat transfer during cooking processes. In addition, the research findings showed that the improved multipurpose cooker stove consumed 0.3643 kg/L less fuel compared to traditional stoves. This fuel savings not only reduces the cost of raw materials but also contributes to environmental sustainability by lowering deforestation rates and air pollution. Despite the initial investment cost of the improved cooker stove, the long-term operation costs are lower due to reduced fuel consumption and maintenance expenses. The study's findings and recommendations hold promise for addressing critical challenges related to clean cooking solutions, environmental preservation, and the well-being of households in Zambia and similar contexts.