Exploration Of Efficiency Research Articles

Effectiveness and mechanism of microbial dust suppressant on coal dust with different metamorphosis degree.

The extraction of coal from open-pit mines significantly contributes to environmental degradation, posing grave risks to human health and the operational stability of machinery. In this milieu, microbial dust suppressants leveraging microbially induced carbonate precipitation (MICP) demonstrate substantial potential for application. This manuscript undertakes an exploration of the dust mitigation efficiency, consolidation attributes, and the fundamental mechanisms of microbial dust suppressants across coal dust samples with varying metamorphic gradations. Empirical observations indicate that, in resistance tests against wind and rain, lignite coal underwent mass losses of 7.43g·m-2·min-1 and 98.62g·m-2·min-1, respectively. The production of consolidating agents within the lignite dust, attributable to the microbial suppressants, was measured at 0.15g per unit mass, a value of 1.25 and 1.07 times greater than that observed in bituminous coal and anthracite, respectively. Scanning electron microscopy coupled with X-ray energy-dispersive spectroscopy (SEM-EDS) and X-ray diffraction (XRD) analyses illuminated that the consolidating products within the coal dust predominantly constituted calcite and vaterite forms of calcium carbonate. The consolidation mechanism of coal dust via microbial suppressants is articulated as follows: Subsequent to the application on coal dust, the suppressants induce the formation of carbonate precipitates with inherent adhesive properties. These carbonates affix to the surfaces of coal dust particles, progressively encapsulating them. Furthermore, they play a pivotal role in bridging and filling the interstices between adjacent dust particles, thereby culminating in the genesis of a dense, cohesive mass capable of withstanding erosive forces.

IMPACT OF ZNCL2 ON MILD STEEL CORROSION IN MANUFACTURING TECHNOLOGIES UNDER PH VARIATIONS

This study investigates the efficacy of ZnCl2 as a corrosion inhibitor for mild steel across varied pH environments (3.5, 7, and 10). Findings highlight a significant reduction in corrosion rates with increasing ZnCl2 concentrations, pinpointing optimal levels at 350 ppm (pH 3.5), 575 ppm (pH 7), and 325 ppm (pH 10). Through comprehensive experimental analyses, the study robustly validates the protective capacity of the inhibitor, shedding light on its practical application in safeguarding metallic materials amidst varying pH conditions. ZnCl2 will be applied as a solution, forming a protective layer on the surface of mild steel, thereby acting as a barrier against corrosive agents. The study's originality lies in its specific exploration of ZnCl2 efficiency under varied pH conditions, emphasizing its substantial contribution to corrosion protection in different environmental settings.

Exploring market efficiency levels: A powerful approach based on a gamma distribution

We introduce a novel measure to assess market inefficiency levels and examine their evolution over time using robust statistical principles. Our innovative approach not only facilitates a comprehensive exploration of market efficiency and its economic impacts but also allows for effortless comparisons across various assets, timeframes, regions, and data frequencies. Our findings reveal that during significant economic events, such as financial crises, markets tend to exhibit decreased efficiency. This research contributes to the understanding of market dynamics, offering a valuable and structured tool for analysts and policymakers.

An exploration of operational efficiency, market efficiency, and sustainable development in the banking industry

AbstractSustainable development is the primary goal of the current global economic transformation. The banking industry, as an intermediary institution within the financial system, not only serves as a crucial foundation for national economic development but also plays a key role in the global transition to sustainability and a low‐carbon economy. Banks can leverage the influence of financing to direct funds towards sustainable ventures and simultaneously develop green financial products, guiding ordinary consumers to make more environmentally friendly choices. How the banking industry can effectively improve operational efficiency while considering sustainable development is one of the key focuses of ongoing development in the banking sector. The main aim of this study is to incorporate the aspect of sustainable development into the evaluation of operational efficiency, aligning with the goals of corporate sustainable development. It allows for an analysis of how decision‐makers in the banking industry can adjust resources to maintain stable and sustainable profitability while promoting sustainable development. This study selected 13 financial holding banks and 19 non‐financial holding banks in Taiwan as research subjects, covering the period from 2016 to 2021. Utilizing a meta assurance regions (AR) parallel dynamic two‐stage slacks‐based measure model with “operational stage” and “market and sustainability parallel stage,” the research explores the efficiency performance of banks considering sustainable development. It examines the differences in efficiency performance at various stages among different types of banks. The research findings are as follows: (1) among the banking industry in Taiwan, operational stage efficiency ranks the highest, followed by sustainable stage efficiency, while market stage performance lags behind. (2) Financial holding banks outperform non‐financial holding banks on average in operational stage, market stage, and sustainable stage efficiency. (3) Fubon Financial, TFH, CATHAY HOLDINGS, and SKFH are benchmark performers among financial holding banks. (4) Non‐financial holding banks exhibit a higher average technical gap ratio compared to financial holding banks, indicating that non‐financial holding banks have fewer inefficient areas to improve. However, the technical efficiency of both groups of banks approaches each other over the years. (5) In the sustainable stage, financial holding banks demonstrate superior environmental indicators and corporate treatment efficiency compared to non‐financial holding banks.

Investigating Space Utilization in Skyscrapers Designed with Prismatic Form

The enduring appeal of prismatic shapes, historically prevalent in office building designs, persists in contemporary skyscraper architecture, which is attributed particularly to their advantageous aspects concerning cost-efficiency and optimal space utilization. Space efficiency is a crucial factor in prismatic skyscraper design, carrying substantial implications for sustainability. However, the current academic literature lacks a complete exploration of space efficiency in supertall towers with prismatic forms, despite their widespread use. This paper seeks to address this significant gap by conducting a comprehensive analysis of data gathered from a carefully selected set of 35 case studies. The primary discoveries presented in this paper are outlined as follows: (i) average space efficiency stood at approximately 72%, covering a range that extended from 56% to 84%; (ii) average core to gross floor area ratio averaged around 24%, spanning a spectrum that ranged from 12% to 36%; (iii) the majority of prismatic skyscrapers utilized a central core approach, mainly customized for residential use; (iv) the dominant structural system observed in the analyzed cases was the outriggered frame system, with concrete being the commonly utilized material for the structural components; and (v) the impact of diverse structural systems on space efficiency showed no significant deviation, although differences in function led to variations in average space efficiency. The authors expect that these findings will provide valuable guidance, especially for architects, as they strive to enhance the sustainable planning of prismatic towers.

Exploration of hyperparameter efficiency for image style transfer

Image style transfer is a popular computer vision technique that aims to merge the content of one image with the style of another to generate a unique, original image with a different aesthetic feel. Numerous models have been developed for various applications in this field, including portrait painting, art creation, and medical image processing, where additional information or annotations could be added to medical images, making them easier to read and understand. This study focuses on optimizing parameters within the pre-trained Visual Geometry Group (VGG19) network architecture, building on Google Brains 2017 work on Arbitrary style transfer in one model. The goal is to improve the quality and realism of the generated images by exploring different parameter combinations and fine-tuning weights and learning rates. This work carefully selects a range of styles and content to compare their effects during the optimization process. Finally, this fine-tuning process strikes a balance between content loss and style loss, which results in high-quality and more realistic images.

Optimizing GANs for Cryptography: The Role and Impact of Activation Functions in Neural Layers Assessing the Cryptographic Strength

Generative Adversarial Networks (GANs) have surfaced as a transformative approach in the domain of cryptography, introducing a novel paradigm where two neural networks, the generator (akin to Alice) and the discriminator (akin to Bob), are pitted against each other in a cryptographic setting. A third network, representing Eve, attempts to decipher the encrypted information. The efficacy of this encryption–decryption process is deeply intertwined with the choice of activation functions employed within these networks. This study conducted a comparative analysis of four widely used activation functions within a standardized GAN framework. Our recent explorations underscore the superior performance achieved when utilizing the Rectified Linear Unit (ReLU) in the hidden layers combined with the Sigmoid activation function in the output layer. The non-linear nature introduced by the ReLU provides a sophisticated encryption pattern, rendering the deciphering process for Eve intricate. Simultaneously, the Sigmoid function in the output layer guarantees that the encrypted and decrypted messages are confined within a consistent range, facilitating a straightforward comparison with original messages. The amalgamation of these activation functions not only bolsters the encryption strength but also ensures the fidelity of the decrypted messages. These findings not only shed light on the optimal design considerations for GAN-based cryptographic systems but also underscore the potential of investigating hybrid activation functions for enhanced system optimization. In our exploration of cryptographic strength and training efficiency using various activation functions, we discovered that the “ReLU and Sigmoid” combination significantly outperforms the others, demonstrating superior security and a markedly efficient mean training time of 16.51 s per 2000 steps. This highlights the enduring effectiveness of established methodologies in cryptographic applications. This paper elucidates the implications of these choices, advocating for their adoption in GAN-based cryptographic models, given the superior results they yield in ensuring security and accuracy.

Reducing the Power Consumption of Edge Devices Supporting Ambient Intelligence Applications

Having as a main objective the exploration of power efficiency of microcontrollers running machine learning models, this manuscript contrasts the performance of two types of state-of-the-art microcontrollers, namely ESP32 with an LX6 core and ESP32-S3 with an LX7 core, focusing on the impact of process acceleration technologies like cache memory and vectoring. The research employs experimental methods, where identical machine learning models are run on both microcontrollers under varying conditions, with particular attention to cache optimization and vector instruction utilization. Results indicate a notable difference in power efficiency between the two microcontrollers, directly linked to their respective process acceleration capabilities. The study concludes that while both microcontrollers show efficacy in running machine learning models, ESP32-S3 with an LX7 core demonstrates superior power efficiency, attributable to its advanced vector instruction set and optimized cache memory usage. These findings provide valuable insights for the design of power-efficient embedded systems supporting machine learning for a variety of applications, including IoT and wearable devices, ambient intelligence, and edge computing and pave the way for future research in optimizing machine learning models for low-power, embedded environments.

Enhancing interpretability in the exploration of high-energy conversion efficiency in CsSnBr3−xIx configurations using crystal graph convolutional neural networks and adversarial example methods

Enhancing interpretability in the exploration of high-energy conversion efficiency in CsSnBr3−xIx configurations using crystal graph convolutional neural networks and adversarial example methods

Multiple Sclerosis, Fatigue, Expanded Disability Status Scale: A Cross-Sectional Exploration of Sleep Efficiency and Quantitative Sleep Parameters.

Poor sleep quality and sleep disorders are more prevalent in individuals with multiple sclerosis (MS) than in the general population. Poor sleep has been correlated with worse MS outcomes. Sleep efficiency (SE) is one of the most sensitive markers of sleep quality. There is very little written about SE and other polysomnography (PSG) parameters and MS measures. This is a retrospective review of 280 consecutive individuals with MS evaluated by PSGs and other standardized MS measures over 13 years at a comprehensive MS center. In addition, the cohort was assessed with 2 fatigue scales, the Epworth Sleepiness Scale, and the Expanded Disability Status Scale. A comparison of means test (independent t test) and a correlation coefficient (r) were used. The PSG measures of SE and Total Sleep Time were significantly different between a group of individuals with MS with a disease duration of more than 5 years vs a group of individuals with MS with a disease duration less than or equal to 5 years. Prevalence of obstructive sleep apnea was 63%, higher than reported in the literature while the prevalence of moderate to severe obstructive sleep apnea was 33.4%, which was lower than reported. Longer disease duration and worse disability correlate with sleep quality as measured by SE.

The Spatiotemporal exploration of intercity transport energy efficiency in the mainland of China on the basis of improved stochastic frontier modelling

In order to determine the upper bound of Transport Energy Efficiency (TEE) and investigate the temporal and regional heterogeneities of TEE, an improved stochastic frontier analysis model taking into account the meta-frontier is established in this work. Focusing on thirty provinces in the mainland of China from 2000 to 2018, this research employs the transport energy efficiency index, technical efficiency variation, frontier transport technical index, and total factor energy efficiency to assess the energy technical disparities among the studied provinces. The results indicate that TEE remains relatively low from 2000 to 2010 due to regional energy technical disparities. However, a noteworthy increase in TEE is observed from 2011 to 2018 owing to technological advancements. Furthermore, among four main intercity transport modes including highway, railway, aviation and water transports, the TEE of railway is the highest, followed by aviation and water transports. In view of the present situation and in order to develop the transport system in a sustainable way, narrowing the energy technical disparities among provinces and constructing a sustainable transport network are vital for policymakers to adopt a more rational transport development plan.

Exploration of grid energy efficiency influencing factors by applying principal component analysis approach

Abstract This paper focuses on the problem of power losses in the transmission, transformation, distribution and marketing segments of the power system, and explores how to effectively improve the energy efficiency of the power grid to optimize the cost management of the power grid. The article uses principal component analysis to accurately diagnose the energy efficiency status of the grid, and analyzes the multiple factors affecting grid losses and their degree of influence. It is found that the total loss in 10km transmission line when wind power access reaches 328kw, and the complete loss of wind power access is higher than photovoltaic access under the condition of different line lengths, which are 315kw, 321kw, and 328kw, respectively. In the use of iron transmission line, the average loss at the current of 400A is 89.600W, which is higher than using aluminum alloy material by 66.200 W. If energy-efficient aluminum alloy fittings are fully utilized in transmission lines, the average annual power saving can be up to 301,368 kWh. The study shows that it is crucial to analyze the factors affecting the energy efficiency of power grids during the planning and construction stage of the power grids.

Examining Space Efficiency in Supertall Towers through an Analysis of 135 Case Studies

This study addresses the critical need for a comprehensive exploration of space efficiency in supertall buildings, a crucial aspect of skyscraper architecture with profound implications for sustainability. Despite the paramount importance of spatial utilization, the existing literature lacks a thorough investigation into this domain. This research aims to fill this significant gap by conducting an exhaustive analysis based on data from 135 case studies. The proposed model for evaluating space efficiency yielded compelling technical insights. The key metrics employed in this examination include: (1) average space efficiency: the findings revealed an average space efficiency of about 72%. This metric provides a quantitative measure of how effectively space is utilized in supertall buildings. (2) core area proportion: on average, the proportion of core area to the gross floor area was around 24%. This metric sheds light on the distribution of core areas within the overall structure, impacting both functionality and spatial optimization. This study also highlighted notable trends and characteristics observed in the examined cases: (3) central core design: the majority of skyscrapers featured a central core design tailored primarily for mixed-use purposes. This architectural choice reflects a strategic approach to maximize functionality and versatility in supertall structures. (4) structural systems: The outriggered frame system emerged as the prevailing structural system, with composite materials commonly used for the structural components. This insight into prevalent structural choices contributes to the understanding of the technical aspects influencing space utilization in skyscraper design.

Analyzing E-Bike Driving Conditions on Indian Roads Using Two Different Drive Cycles

Recent technological strides have caused electric vehicles (EVs) to reshape the transportation landscape, boasting environmental advantages alongside positive impacts on human health. Crafting electric vehicles involves intricate motor and battery considerations due to multifaceted design requisites. This study leverages the MATLAB Simulink platform to model an electric bike equipped with a 2 kW Brushless DC motor and a 48 V, 50 Ah battery. The comprehensive model encapsulates the battery, driver controller, power converter, motor, and vehicle subsystems, with a dynamic drive cycle-based representation. An H-bridge converter is adopted to engineer the power converter. The efficacy of the EV is assessed through the Indian driving cycle and the World Harmonized Test Cycle, gauging motor speed and power output. Additionally, the State of Charge (SoC) and Battery Current consumption parameters are quantified for both test drive cycles. This endeavor unveils a meticulous exploration of EV dynamics, motor efficiency, and battery performance, reinforcing the potential of EVs as sustainable and health-beneficial mobility solutions.

Energy efficiency of lithium-ion batteries: Influential factors and long-term degradation

As the integration of renewable energy sources into the grid intensifies, the efficiency of Battery Energy Storage Systems (BESSs), particularly the energy efficiency of the ubiquitous lithium-ion batteries they employ, is becoming a pivotal factor for energy storage management. This study delves into the exploration of energy efficiency as a measure of a battery’s adeptness in energy conversion, defined by the ratio of energy output to input during the discharge and charge cycles. Energy efficiency values were systematically calculated over the course of the battery lifespan, revealing a predominantly linear trend in the efficiency trajectories, as substantiated by the Mann–Kendall (MK) trend test. Subsequently, a linear model was proposed to represent the efficiency degradation. Further analysis shows that ambient temperature, discharge current, and cutoff voltage all affect energy efficiency in different ways. Using the energy efficiency and its behavior observed in this study, Battery Management Systems (BMS) can improve the energy efficiency of batteries by adjusting operating conditions or developing better management strategies.

A numerical exploration of structural efficiency of steel plates with 3D sinusoidal wave patterns

The current study proposes the use of innovative additive manufacturing to produce metallic plate elements with predefined wave patterns capable of postponing instability via the lowest buckling mode thus providing increased buckling resistances. Two plate boundary conditions - internal and outstand elements were considered and tested by employing square hollow section (SHS) and equal angle section (EAS) stub columns, respectively. An experimental testing programme comprising tensile coupon tests and stub column tests on flat-faced SHS and EAS has been carried out and used to validate numerical models. This was followed by a numerical parametric study exploring various combinations of pre-defined surface waves with different amplitudes in stainless steel plates of varying slenderness. Their relative stiffness, strength, and material consumption been assessed and the optimum wave patterns have been identified for each boundary conditions based on their structural efficiencies. The optimum geometric wave pattern has also been compared with and shown to outperform another two common stiffening methods based on the same material consumption. This innovative study highlights the significant potential of metallic additive manufacturing technologies in achieving unprecedented material efficiency and economic design in the future steel construction industry.

Evaluation of Carbon Emission Efficiency in the Construction Industry Based on the Super-Efficient Slacks-Based Measure Model: A Case Study at the Provincial Level in China

Rapid urbanization and an increasing carbon footprint have underscored the need for sustainable practices in the construction industry. With the aim of prioritizing global sustainable development, the measurement of carbon emission efficiency in the construction industry (CEECI) has emerged as a critical indicator. Nevertheless, a comprehensive exploration of carbon emission efficiency within the Chinese construction sector remains limited, despite the pressing demand to mitigate carbon emissions. To address this research gap, this study aims to provide valuable policy recommendations for effectively reducing carbon emissions. We conducted a thorough assessment of both the total carbon emissions and the carbon emission intensity in 30 provinces and cities across China from 2010 to 2020. Utilizing the slacks-based measure (SBM) model with non-desired outputs, we evaluated the static CEECI, including the spatial correlation analysis and the evaluation of the carbon reduction potential in the construction industry (CRPCI). Additionally, the dynamic CEECI was quantified using the Malmquist–Luenberger (ML) index model, followed by an index decomposition analysis. The findings reveal several noteworthy insights: (1) There exists a positive correlation between carbon emissions in the construction industry and the economic scale. Generally, less developed areas (e.g., central and western regions of China) exhibit higher levels of carbon emission intensity (CEICI), while more developed areas (e.g., eastern regions of China) demonstrate lower levels of CEICI. (2) The CEECI across various provinces and cities demonstrates a clear spatial positive autocorrelation, while the CRPCI exhibits a negative correlation with the CEECI, with larger CRPCI values observed predominantly in western China. (3) Technological progress (MLTC) emerges as a crucial factor influencing the CEECI in our dynamic analysis. These findings offer valuable insights for policymakers to develop focused strategies to effectively mitigate carbon emissions nationwide.

Large-scale exploration of nitrogen utilization efficiency in Asia region for rice crop: Variation patterns and determinants.

Improving rice nitrogen utilization efficiency (NUtE) is imperative to maximizing future food productivity while minimizing environmental threats, yet knowledge of its variation and the underlying regulatory factors is still lacking. Here, we integrated a dataset with 21,571 data compiled by available data from peer-reviewed literature and a large-scale field survey to address this knowledge gap. The overall results revealed great variations in rice NUtE, which were mainly associated with human activities, climate conditions, and rice variety. Specifically, N supply rate, temperature, and precipitation were the foremost determinants of rice NUtE, and NUtE responses to climatic change differed among rice varieties. Further prediction highlighted the improved rice NUtE with the increasing latitude or longitude. The indica and hybrid rice exhibited higher NUtE in low latitude regions compared to japonica and inbred rice, respectively. Collectively, our results evaluated the primary drivers of rice NUtE variations and predicted the geographic responses of NUtE in different varieties. Linking the global variations in rice NUtE with environmental factors and geographic adaptability provides valuable agronomic and ecological insights into the regulation of rice NUtE.

Emerging pathways to sustainable economic development: An interdisciplinary exploration of resource efficiency, technological innovation, and ecosystem resilience in resource-rich regions

Innovation has always been a key factor in economic growth. But with the increasing pressure on natural resources, it has become even more crucial to understand the relationship between innovation, resources, and economic development. Technology has also played a significant role in helping to achieve sustainability. By utilizing the right strategies and investing in innovative technologies, businesses and governments can promote sustainable economic progress while decreasing their influence on the environment. This work explores the nexus among resource consumption, technological innovations, sustainability, and economic development and how this relationship has evolved from a traditional resource-poor region to a more resource-rich one. A correlation heat map showed the highest association between GDP growth (GDPG) and research and development expenditure (RDE) (−0.47). Support vector Regression with radial basis function (SVR-RBF) was applied to see the impact of contributing parameters that influence GDPG. For GDPG, the model generated R = 0.88 and R2 = 0.78 (RMSE = 1.16). The results of the SVR showed that the strongest coefficient in the SVR model is self-employed, total (SE), followed by electricity production from the nuclear resource (EPNR). This study could have several contributions. Firstly, the study’s focus on sustainable economic development provides insights into how resource-rich regions can balance economic growth with environmental conservation. This information could be valuable to policymakers, businesses, and other stakeholders interested in creating sustainable economic growth strategies. Secondly, the study’s interdisciplinary approach could help bridge the gap between different fields of study, leading to more holistic and effective solutions to environmental and economic challenges. This interdisciplinary approach could also help build stronger partnerships between academia, industry, and government. Finally, the study’s exploration of resource efficiency, technological innovation, and ecosystem resilience could provide useful information for China, a resource-rich country undergoing rapid economic growth. China faces numerous environmental and economic challenges, and the study’s findings could help inform policies and strategies to address these challenges.

An exploration of efficiency of proposed drug delivery system including BNNT, C48N12, and TMZ in treating of glioblastoma through classical molecular dynamics

In the present study, density functional theory (DFT) and classical molecular dynamics (MD) simulation were applied to introduce a viable drug delivery system including, Temozolomide (TMZ) as drug, boron nitride nanotube (BNNT) as nanocarrier, and C48N12 as drug releasing agent to better glioblastoma treatment. In order to clarify the capability of introduced drug delivery system encountering various challenges, a prototype of bilayer cell membrane was considered in calculations. To achieve reliable results, simulations were carried out using CHARMM and Tersoff potential through the hybrid pair style under designed in vitro environment. Results showed that the drug binds both inside and outside of BNNT, however inside state more stable in term of energy. Moreover, obtained data reveals that TMZ encapsulation inside BNNT as well as appropriate capacity of nanotube for drug act like barrier against TMZ hydrolysis inside BNNT. Although, the related BNNT have capacity of 30 molecules of TMZ, but zeta potential estimation demonstrated that the stability of drug delivery system decreases with increasing of number of encapsulated drugs. Also, the obtained data reveals that the C48N12 is a proper drug releasing agent for TMZ in lower numbers of encapsulated TMZ. However, the releasing process encounters serious challenge with increasing the number of drugs into BNNT because of interaction between encapsulated drugs such as hydrogen bonding. Finally competitive assessment in term of TMZ adsorption showed that the prototype bilayer cell membranes will complete releasing process due to more interaction between TMZ and membrane in comparison with BNNT-12C48N12 complex.