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Carbon emissions from the Yangtze River Economic Belt are an important element of China's carbon emission endeavor, and a study of its emission reduction pathway can provide a reference for the country's overall management of carbon emission reduction. From the perspective of energy consumption, this paper uses the carbon emission factor method to estimate the carbon emissions of the transportation industry in the Yangtze River Economic Belt during 2006–2020, based on the extended STIRPAT model, considering the influence of seven factors, i.e., population size, urbanization rate, GDP per capita, transportation added value, energy structure, energy intensity, and transportation intensity, on carbon emissions. Based on these factors, a scenario analysis, combined with a forecasting model, is used to predict the peak carbon performance of the transportation industry under different development scenarios. The results show that the overall carbon emissions of transportation in the YEB from 2006 to 2020 show a fluctuating upward trend, and the downstream carbon emissions are significantly higher than those in other regions. The main factors influencing carbon emissions from transportation in different upstream, midstream, and downstream regions vary, with both population and economic factors contributing to carbon emissions, while technical factors affect them differently. There are significant differences in the peak carbon performance of transportation under different development scenarios, and the government should take effective measures to work towards achieving the goals of the low-carbon or enhanced low-carbon scenarios. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Nigeria is one of the most vulnerable countries to climate change (CC) impact. Thus, there is a need to mitigate emission and implement strategies to adapt to the impacts of CC. This study is a review of publications on CC mitigation and/or adaptation in Nigeria. The aims are as follows: to identify commonly adopted climate change adaptation strategies (CCAS) and their determinants; and to identify the climate change mitigation strategies (CCMS) that are widely deployed to reduce emissions in Nigeria. Relevant keywords were used to search for publications in Scopus and Google Scholar. Our dataset shows that from 1999 to the present, there has been an exponential growth in the number of publications on CCAS and CCMS. In total, 75.2% of the papers were on CCAS, 19.6% were on CCMS and 5.2% combined CCAS and CCMS. Many of the papers on CCMS were on 'Energy' and 'Agriculture'. Other sectors identified from the included studies pertinent to mitigation in Nigeria included 'forestry', 'waste management', 'industry' and others. Most (80.7%) of the CCAS papers were related to 'Agriculture', showing the most important sector where CC-adaptive capacity is required in Nigeria. In all, 45% of the papers on CCAS were on 'Social' adaptation, followed by 'Structural measures' (42%), with the smallest amount being on 'Institutional' measures (13%). The relatively fewer number of papers on institutional CCAS highlights the need for more research. This is because institutional measures which include policies, legal and fiscal support are important to build resilience to climate change impact. The greatest determinant influencing the adoption of CCAS is 'Education'. A higher number of publications on 'Agriculture' for both CCMS and CCAS underscores the importance of the sector and the need to develop its mitigation and adaptive capacity strategies. Our results and findings were also compared and discussed in line with similar works on CCMS and CCAS in Africa. [ABSTRACT FROM AUTHOR]

Finding sustainable solutions to the increasing waste generation in Ghana has received a lot of attention in recent years. Through several waste-to-energy processes, the energy potential of municipal solid waste has recently witnessed significant technological advancements. The Renewable Energy Master Plan has projected the production of about 122 MWp from waste-to-energy installations by 2030 in Ghana. To help policymakers and engineers achieve national goals, this paper reviews the waste generation in Ghana estimated from 2010 to 2030 and the status of various bioenergy technologies in Ghana. This paper further estimates the energy recovery potential of municipal solid waste in Ghana under incineration, anaerobic digestion, and landfill gas recovery technologies. The review establishes that, by 2030, municipal solid waste generation will increase by 123% of the 2023 quantities and may produce 1484.25 MW of installed electricity capacity and 13,002.03 GWh per year, which would amount to nearly 59% of Ghana's 2030 renewable energy target. Additionally, it was determined that anaerobic digestion, incineration, and landfill gas recovery technologies, when properly developed, will add 105.33 MW, 301.4 MW, and 377.31 MW of installed electrical capacity, respectively, to Ghana's energy mix in 2028. [ABSTRACT FROM AUTHOR]

The study assessed quality of briquettes produced from bagasse (B), corn husk (CH), and cassava roots (CR) using banana peels (BP), wastepaper (WP), and clay soil (CS) as binders. Mixing ratios were established from carbonized materials, and briquettes physical and combustion properties were determined. Weak shatter resistance appeared in WP, CS briquettes had best tumbling resistances while WP briquettes had better water penetration. CS briquettes (3:1:1) had low (2.7%) moisture content (MC), and 1:3:1 had low (28%) volatile matter (VM) while the highest was 41% for 2:2:1. Ash content (AC) for 2:2:1 was the highest (41%) with highest heating value (HV). BP briquettes for 0:4:1 (CH:CR:BP) had the lowest MC (4.9%), whereas 2:2:1 (B:CH:BP) had the highest VM (41.5%). AC (15.5%) for 1:3:1 was the highest while 2:2:1 (CH:CR) had the highest HV. WP briquettes 1:3:1 (B:CH) had the lowest MC (2%) and 3:1:1 had highest VM (35%), while the highest AC appeared for 4:0:1. The 2:2:1 (B:CR:WP) briquette yielded the highest HV (25.5 MJ/Kg). All materials were suitable for briquetting, although their qualities are sensitive to weather conditions. Together with BP briquettes, WP briquettes 2:2:1 (B:CR:WP) produce the best results, especially when using CR and CH feedstocks. [ABSTRACT FROM AUTHOR]

Copyright of Hacettepe University Journal of Economics & Administrative Sciences / Hacettepe Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of Hacettepe University, Faculty of Economic & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Air-conditioning system applies dehumidification by condensation technique, where the cooling coil handles both latent and sensible load. Energy consumption by the system increases by handling both loads. In order to reduce operating energy and load on cooling coil, latent load needs to be reduced or eliminated. Latent load can be handled separately using desiccant-type dehumidifiers irrespective of cooling coil temperature. This paper investigates the dehumidification performance of a desiccant wheels (DWs) made of fiber paper substrates such as Ceramic Fiber, Glass Fiber, Wood Pulp Fiber, Nomex Fiber, and Brown Wood Pulp Paper (BWPP) coated with synthesized mesoporous nano-titania desiccant for energy-efficient air-conditioning. Moisture adsorption ability test was conducted for different fiber papers at 30 °C and 75% RH, where BWPP has maximum moisture adsorption of 38 g m−2 and 0.42 g g−1 due to its hydrophilic nature, with the highest coating ratio of 3.5 g cm−3. The thermal conductivity, nitrogen adsorption/desorption isotherm, pore structure, and thermal stability of the fiber substrates were also analyzed before and after coating. The thermal conductivity of the fiber papers coated with nano-titania desiccant has enhanced compared to the raw fiber papers, and it reaches 0.116 W m−1 K−1 for BWPP. The dehumidification coefficient of performance of BWPP–DW at a 1:1 airflow area ratio, 60 °C regeneration temperature, and 10 rph is 0.82. The BWPP matrix DWs can be reactivated by low-grade energy sources with 0.82 kg kW−1 h−1 and saves energy up to 2.39 times. [ABSTRACT FROM AUTHOR]

Emerging global environmental pollution issues have caused a reduction in coal utilization, leading to an increased research focus on biomass use as an alternative. However, due to the low heat values of biomass, studies in this field are still in progress. Biomass primarily comprises cellulose, hemicellulose, and lignin. To determine the composition of these three components, the measurement methods recommended by TAPPI (Technical Association of the Pulp and Paper Industry) and NREL (National Renewable Energy Laboratory) are typically employed involving equipment such as HPLC. However, these methods are time consuming. In this study, we proposed a model for predicting cellulose, hemicellulose, and lignin contents based on elemental and industrial analyses. A dataset comprising 174 samples was used to develop this model. This was validated using 25 additional samples. The R2P values for cellulose, hemicellulose, and lignin were 0.6104–0.6362, 0.4803–0.5112, and 0.7247–0.7914, respectively; however, the R2CV values obtained from the validation results were 0.7387–0.7837, 0.3280–0.4004, and 0.7427–0.7757, respectively. The optimal models selected for cellulose, lignin, and hemicellulose were C1, L2, and 100-(C1-L2) or H2, respectively. Our predictions for woody and herbaceous biomass, including torrefied samples, should be applied with caution to other biomass types due to the potential accuracy limitations. To enhance the prediction accuracy, future research should broaden the range of biomass types considered and gather more data specifically related to woody and herbaceous biomass. [ABSTRACT FROM AUTHOR]

Offloading some tasks from the local device to the remote cloud is one of the important methods to overcome the drawbacks of the medical mobile device, such as the limitation in the execution time and energy supply. The challenges of offloading task is how to meet multiple requirement while keeping energy-saving. We classify tasks in the medical mobile device into two kinds: the first is the task that hopes to be executed as soon as possible, those tasks always have a deadline; the second is the task that can be executed anytime and always has no deadlines. Past work always neglects the energy consumption when the medical mobile device is charged. To the best of our knowledge, this paper is the first paper that focuses on the energy efficiency of charging from a power grid to a medical device during work. By considering the energy consumption in different locations, the energy efficiency during working and energy transmission, the available energy of and the battery, we propose a scheduling method based on DQN. Simulations show that our proposed method can reduce the number of un-completed tasks, while having a minimum value in the average execution time and energy consumption. [ABSTRACT FROM AUTHOR]

The excessive growth of carbon emissions (CO2E) from industrial energy use not only exacerbates global warming and severely curbs the sustainable development of the economy and society. As a high energy-consuming sector second only to the fossil energy division, the power and heavy division, China's chemical industry should have received more attention for its CO2E. However, there are limited literatures on energy CO2E in China's chemical sector at present. Based on this fact, this current paper uses the energy utilization approach, the input–output analysis approach, and the extended structural decomposition method to evaluate the energy-related CO2E of China's chemical sector from 2007 to 2017. (1) China's chemical sector energy-related CO2E showed a trend of first growth and then a slow decline, demonstrating that the rapid growth of China's chemical sector energy-related CO2E has been effectively controlled; However, it should be noted that the chemical industry is still dominated by high-CO2E energy-related CO2E at the current stage. (2) Input structure and energy intensity effects have a reduced influence on the growth of energy-related CO2E in China's chemical sector. This is due to upgrading energy use technology and optimizing the generalized technology progress rate in the chemical sector. (3) Energy structure and final demand effects have encouraged the growth of the chemical sector's energy-related CO2E. It shows that the industrial system's demand for chemical products is constantly expanding, and the chemical products still have the characteristics of high carbonization. Also, the chemical sector's supply-side energy utilization structure has not been significantly enhanced. [ABSTRACT FROM AUTHOR]

In this paper, we make the first attempt to figure out the differences on Hölder regularity in time of solutions and conserved physical quantities between the ideal electron magnetohydrodynamic equations concerning Hall term and the incompressible Euler equations involving convection term. It is shown that the regularity in time of magnetic field B is C_{t}^{\frac {\alpha }2} provided it belongs to L_{t}^{\infty } C_{x}^{\alpha } for any \alpha >0, its energy is C_{t}^{\frac {2\alpha }{2-\alpha }} as long as B belongs to L_{t}^{\infty } \dot {B}^{\alpha }_{3,\infty } for any 0<\alpha <1 and its magnetic helicity is C_{t}^{\frac {2\alpha +1}{2-\alpha }} supposing B belongs to L_{t}^{\infty } \dot {B}^{\alpha }_{3,\infty } for any 0<\alpha <\frac 12, which are quite different from the classical incompressible Euler equations. [ABSTRACT FROM AUTHOR]

Building on work which has shown the role of digital technologies in reframing environmental relations, this paper explores ethnographically how environmental data is reconfiguring the concept of place. The paper takes as its focus an action-research project within a UK based, citizen-oriented initiative called Newtown Energy Futures, in which we sought to enfold climate and energy data into a social-justice informed attempt at climate action. By exploring how the project used data as an invitation for citizens to engage with and participate in local infrastructural and environmental dynamics, the paper sheds light on how environmental data came to participate in the making of place and in doing so raised questions about how to rebuild the socio-material relations through which 'a sense of place' might be reproduced. As climate and energy data increasingly demand that places become enrolled into environmental projects our findings suggest that data enables place to emerge as a 'socio-technical potentiality' an observation that has implications both for both engagement with, and the study of data and place. In practical terms, we suggest that this refiguration of place has the effect of creating hopeful trajectories for change, whilst also posing difficult questions about the limits of participation in a data-infused form of place-based politics. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) architectures generally focus on providing consistent performance and reliable communications. The convergence of IoT, edge, fog, and cloud aims to improve the quality of service of applications, which does not typically emphasize energy efficiency. Considering energy in IoT architectures would reduce the energy impact from billions of IoT devices. The research presented in this paper proposes an optimization framework that considers energy consumption of nodes when selecting a node for processing an IoT request in edge-fog-cloud layered architecture. The IoT use cases considered in this paper include smart grid, autonomous vehicles, and eHealth. The proposed framework is evaluated using CPLEX simulations. The results provide insights into mechanisms that can be used to select nodes energy-efficiently whilst meeting the application requirements and other network constraints in multi-layered IoT architectures. [ABSTRACT FROM AUTHOR]

Refuse derived fuel (RDF) is an environmentally friendly renewable fuel developed to reduce waste generation. RDF can consist of various kinds of waste such as paper and gardens. One of the critical parameters is the chemical element and calorific value. The purpose of this study was to determine the potential for waste reduction and the relationship of ultimate longevity in RDF to the calorific value. This study's paper and garden waste mixture were P0 (100% paper), P25 (75% paper and 25% garden), P50 (50% paper and 50% garden), P75 (25% paper and 75% garden), and P100 (100% garden). The calorific value of the mixture can reach 3.6-5.2 kWh/kg. Simultaneously the relationship of ultimate elements nitrogen (N), hydrogen (H), oxygen (O), and ash affects the heating value of RDF. Sampling the application in Depok City can reduce waste by 6.67%, with the potential for electrical energy from paper and garden wastes of 358,903.8 kWh and 48,681 kWh, respectively. This shows that this energy waste can supply 0.1% of the total daily electricity demand in Depok City. [ABSTRACT FROM AUTHOR]

Vehicle-to-grid (V2G) systems play a key role in the integration of electric vehicles (EVs) into smart grids by enabling bidirectional energy flows between EVs and the grid. Optimizing V2G operations poses significant challenges due to the dynamic nature of energy demand, grid constraints, and user preferences. This paper addresses the optimization challenges in V2G systems and explores the use of artificial intelligence (AI) methods to tackle these challenges. The paper provides a comprehensive analysis of existing work on optimization in V2G systems and identifies gaps where AI-driven algorithms, machine learning, metaheuristic extensions, and agile optimization concepts can be applied. Case studies and examples demonstrate the efficacy of AI-driven algorithms in optimizing V2G operations, leading to improved grid stability, cost optimization, and user satisfaction. Furthermore, agile optimization concepts are introduced to enhance flexibility and responsiveness in V2G optimization. The paper concludes with a discussion on the challenges and future directions for integrating AI-driven methods into V2G systems, highlighting the potential for these intelligent algorithms and methods. [ABSTRACT FROM AUTHOR]

One of the key challenges in Multi-Spectral Automatic Diagnostic (MAD) robot design is the precise targeting of narrow-angle cameras on a specific part of the equipment. The paper shows that a low-cost MAD robot, whose navigation system is based on open-source ArduRover firmware and a pair of low-cost Ublox F9P GNSS receivers, can inspect the 8 × 4 degree ultraviolet camera bounding the targeting error within 0.5 degrees. To achieve this result, we propose a new targeting procedure that can be implemented without any modifications in ArduRover firmware and outperforms more expensive solutions based on LiDAR SLAM and UWB. This paper will be interesting to the developers of robotic systems for power equipment inspection because it proposes a simple and effective solution for MAD robots' camera targeting and provides the first quantitative analysis of the GNSS reception conditions during power equipment inspection. This analysis is based on the experimental results collected during the inspection of the overhead power transmission lines and equipment inspections on the open switchgear of different power plants. Moreover, it includes not only satellite, dilution of precision, and positioning/heading estimation accuracy but also the direct measurements of angular errors that could be achieved on operating power plants using GNSS-only camera targeting. [ABSTRACT FROM AUTHOR]

This paper provides a detailed literature review of the environmental implications of vehicle platooning, a topic gaining significant attention in transportation. While previous reviews have focused on the safety, planning, fuel economy, and microsimulation aspects of platooning, this paper delves into environmental aspects. It identifies a lack of research adopting a holistic approach to transport and environmental benefits and emphasizes the need for further research to enhance vehicle efficiency and improve air quality and health conditions. This study traces the historical evolution of platooning, highlighting the shift in research focus over the decades. It advocates for more research on platooning's environmental aspects, particularly pollutant emissions and air quality. The primary contributions of this work are threefold and include the following: firstly, it delineates simulation methodologies for platooning and the associated pollutant emissions; secondly, it offers a critical assessment of the existing literature on vehicle emissions, fuel consumption, and energy savings; and thirdly, it illuminates the prospective research challenges within the specialized domain of vehicle platooning. [ABSTRACT FROM AUTHOR]

In order to improve the operation efficiency of low-head tubular pump, this paper studies the influence of shaft type in the shaft tubular pump on the flow characteristics and energy characteristics of the pump. To optimize the shaft structure of shaft tubular pumping systems and realize the efficient use of energy, numerical simulation and model test was employed to study the optimization of the entire pumping system. In this paper, the CFD method was used to numerically simulate the whole pumping system, and the effect of changing the shaft length, shaft head profile, and shaft tail profile on the internal flow and entropy production characteristics of the inlet passage and impeller position were analyzed. It is found that the tapered tail profile can make the inlet passage overflow area change more smoothly and thus make the flow pattern more favorable. The wall entropy production dissipation at the inlet passage position dominates the total entropy production, and the high-value area of mainstream entropy production at this position is distributed periodically. The mainstream entropy production dissipation at the impeller section accounts for a relatively large proportion. After the entropy production dissipation analysis, it is believed that the tapered can reduce the entropy production dissipation of the pumping systems. The change of the shaft tail profile will make the entropy production dissipation change more noticeable compared with other optimization factors. Therefore, the tapered tail profile with better transition in the actual project is recommended. [ABSTRACT FROM AUTHOR]

The growing demand for space and financial resources to manage current and new municipal solid waste (MSW) landfills has become a massive challenge for several countries. Additionally, landfills contribute to adverse environmental impacts such as pollution and CO2 (carbon dioxide) and CH4 (methane) emissions. This paper has analyzed the possibility of producing biogas from landfilled MSW. An easily degradable fraction of landfilled MSW with 8 years of landfilling was mined and subjected to chemical characterization and elemental composition analysis. The abbreviation for the study sample was called ED8 – Mined. The low values of lignin (24.5%) and nitrogen content (0.7%) and high values of holocellulose (75.9%) and C/N (46.1%) on dry basis were obtained resulting in materials with the potential to be used for biogas generation. Recalcitrant materials were found in greater amounts than easily biodegradable fresh MSW fractions. The reuse of energy from landfilled MSW can contribute positively to the country's environment and economy, reducing environmental liabilities and generating energy in a controlled way. In Delta A Sanitary Landfill, Southeastern Brazil, the recovery of the ED8 – Mined would reflect a significant recovery of about 100,000 tonnes of landfilled materials for annual MSW cells of about 450,000 tonnes, allowing recovery of materials and space expansion for rejects. fx1 [ABSTRACT FROM AUTHOR]

In our paper, we continue the study of the theory of fuzzy soft sets and their properties. Based on the singular values of the corresponding matrix, we define the energy of a fuzzy soft set, as well as the λ-energy of a fuzzy soft set, allowing us to introduce an effective method for decision-making. Then, we consider the limits of the defined energies, which are essentially non-negative numerical values. The paper demonstrates through examples how the introduced method can be successfully applied to many problems containing uncertainties. Additionally, the paper includes comparisons of the introduced method with other methods addressing similar problems. [ABSTRACT FROM AUTHOR]

This editorial article discusses recent findings in the optimization and engineering for sustainable development. The current Special Issue (SI) of the Optimization and Engineering journal stems from the 2022 Sustainable Development of Energy, Water and Environment Systems Conferences. These events included the 5th South East European, 3rd Latin American, and 17th SDEWES Conferences. Being selected from conference presentations, the papers in SI represent the main topics in optimization approaches that integrate various life-supporting systems discussed during these three events. After careful selection, the current SI accepted ten excellent papers summarized here. These contributions use differentiated modeling approaches and supporting tools, such as P-graph and network-flow modeling, computational fluid dynamics, pinch analysis (PA), and the Geographic Information System. The range of optimization methods includes mixed-integer linear and mixed-integer nonlinear programming (MILP and MINLP), dynamic programming, stochastic optimization, and PA and P-graph extensions. [ABSTRACT FROM AUTHOR]

From a biophysical point of view, incorporating a variety of electric components into branch circuits of a neuron circuit can enhance the biophysical function of an isolated neuron, for example, piezoelectric ceramic can detect external auditory waves, thermistor can enhance temperature dependence and phototube can capture light signals. Thus, the physical neuron circuits of auditory neuron, thermosensitive neuron and light-dependent neuron are designed and the corresponding dimensionless equations are obtained in this paper. Firstly, the three different physical neurons are connected reciprocally by induction coils to excite magnetic field coupling under multiple external stimuli, and then synaptic connections are activated in an adaptive manner. Then, the criterion for exponential growth of coupling strength is proposed to discuss the enhancement of neuronal synaptic connections. It is found that the heterogeneous functional neurons coupled by induction coils can achieve quasi-synchronization accompanied by energy evolution. Moreover, the coupled functional neurons are taken as a network node to construct a functional neural network via voltage coupling based on resistor, so electrical synapse is activated and the influence of functional regions on network collective behavior is discussed. The findings show that the orderliness of neural network can be enhanced or destroyed under different external stimuli. The results in this paper can explain the collaboration and signal interaction in different functional areas, and it is expect to enhance the functionality and intelligence of artificial neural networks. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate through an empirical analysis the impact of social capital on the innovative performance of companies of the energy sector in Spain, as well as the role of firms’ absorptive capacity and membership to a business association as mediating variables in this relationship. The energy supply sector in Spain is analyzed through a sample of 197 companies, using PLS-SEM technique. This study provides empirical evidence on the positive and significant effect of firms’ social capital on their innovative performance, and the mediating effect of firms’ absorptive capacity and membership in a business association. It is concluded that politicians and managers should be aware about the importance of firms’ connectivity in the current digital society. But interaction and knowledge diffusion are of little use if companies do not develop their knowledge absorptive capacity, to effectively exploit external knowledge. Finally, the role of business associations as platforms for the dissemination and absorption of knowledge, as well as business innovation, is highlighted. [ABSTRACT FROM AUTHOR]

Foreign object debris (FOD) includes any unwanted and unintentional material lying on the charging lane or parking lots, posing a risk to the wireless charging system, the vehicle, or the people inside. FOD in an Electric Vehicle (EV) wireless charging system can cause problems, including decreased charging efficiency, safety risks, charging system damage, communication issues, and health risks. To address this problem, this paper proposes the deep learning object detection network approach of using YOLOv4 (You Only Look Once), which is a single-shot detector. Additionally, for real-time implementation, YOLOv4-Tiny is suggested, which is a compressed version of YOLOv4 designed for devices with low computational power. YOLOv4-Tiny enables faster inferences and facilitates the deployment of FOD detectors on edge devices. The algorithm is trained using the FOD dataset, consisting of images of common debris on runways or taxiways. Furthermore, utilizing the concept of transfer learning, the last few layers of the pre-trained YOLOv4 model are modified using the COCO (Common Objects in Context) dataset to transfer features to the new network and retrain the model on the FOD dataset. The results obtained using this YOLOv4 model yielded a precision rate of 99.05%, while the results from YOLOv4-Tiny achieved a precision rate of 97.74%, with an average inference time of 150 ms under the ambient light and weather conditions. [ABSTRACT FROM AUTHOR]

In this work, we consider a problem from the field of power-aware scheduling in which a fleet of electric vehicles have to be charged in a minimum time. Each vehicle is equipped with a lithium-ion battery of a given capacity. The initial power used for charging each battery is known, whereas it is assumed that the power drops to zero at the moment when the battery gets fully loaded. The power usage function is linear and decreasing. The charging jobs are nonpreemptable and independent, whereas the total available amount of power is limited. The objective is to minimize the schedule length. In this paper, we analyze the case of a problem with identical jobs that already cover a wide variety of practical situations. By employing inverses of natural numbers, similar to harmonic series, we prove two properties of this case, and we also discuss the phenomenon of the stabilization of the difference between the start times of two successive jobs in a schedule. We also take under examination a few special cases of the problem. Some conclusions and directions for future research are given. [ABSTRACT FROM AUTHOR]

Purpose. This paper aims to present a unique perspective that emphasizes the intricate interplay between energy, dietary proteins, and amino acid composition, underscoring their mutual dependence for health-related considerations. Energy and protein synthesis are fundamental to biological processes, crucial for the sustenance of life and the growth of organisms. Methods and Results. We explore the intricate relationship between energy metabolism, protein synthesis, regulatory mechanisms, protein sources, amino acid availability, and autophagy in order to elucidate how these elements collectively maintain cellular homeostasis. We underscore the vital role this dynamic interplay has in preserving cell life. Conclusions. A deeper understanding of the link between energy and protein synthesis is essential to comprehend fundamental cellular processes. This insight could have a wide-ranging impact in several medical fields, such as nutrition, metabolism, and disease management. [ABSTRACT FROM AUTHOR]

The existing battery management systems perform many functions, such as simply monitoring the battery's voltage, current, and temperature for the most basic and compensating energy imbalances between battery cells for the most advanced systems. In this last example, the function balancing helps protect the battery from obtaining a better lifespan. However, these systems with such functions remain complex because they involve techniques specific to power electronics and energy conversion. The number of components, implementation complexity, and cost increased. The work presented in this paper fits directly into this context. The main objective is to provide a solution to the problem of battery management and careful pack cell balancing. The proposed system aims to balance the battery pack cells based on the intermediate state of charge by charging or discharging the imbalanced cell. The implementation of the proposed control strategy was for a battery pack composed of five cells under MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

Background: The multinational, open-label COMPLETE study (NCT03835715) investigated the effectiveness of vortioxetine in alleviating emotional blunting in patients with major depressive disorder (MDD) experiencing inadequate response and emotional blunting while being treated with a selective serotonin reuptake inhibitor (SSRI) or serotonin–noradrenaline reuptake inhibitor (SNRI). This paper presents results for the subgroup of patients enrolled in Spain. Methods: Patients with MDD (n = 67) experiencing partial response and emotional blunting during monotherapy with an SSRI or SNRI were switched to vortioxetine (10– 20 mg/day) for 8 weeks. The primary study outcome was emotional blunting, assessed by the Oxford Depression Questionnaire (ODQ). Results: After 8 weeks of vortioxetine, the mean (SE) change in ODQ total score from baseline was − 26.0 (2.9) (P < 0.001). Respective changes in Montgomery–Åsberg Depression Rating Scale (MADRS), Motivation and Energy Inventory, Digit Symbol Substitution Test, and Sheehan Disability Scale (SDS) total scores were − 14.9 (0.8), +34.2 (4.5), +6.3 (1.6), and ‒9.0 (1.3) (all P < 0.001 vs baseline). At week 8, 70.4% of patients no longer reported emotional blunting and 53.7% had achieved remission from their depressive symptoms (defined as a MADRS total score ≤ 10). Mediation analysis showed 77.1% of the change in SDS total score to be a direct effect of the improvement in ODQ total score after switching to vortioxetine. Adverse events were reported by 35 patients (52.2%), most commonly nausea (14 patients, 20.9%). At week 8, 33/54 patients (61.1%) were receiving vortioxetine 20 mg/day. Conclusion: In this study investigating the effectiveness of vortioxetine in Spanish patients with MDD who experienced inadequate response and emotional blunting on SSRI/SNRI monotherapy, significant improvements in emotional blunting, core depressive symptoms (including anhedonia), sleep duration, motivation and energy, cognitive performance, and overall patient functioning were observed during the 8 weeks of treatment. Two-thirds of patients no longer reported emotional blunting and over half were in remission from their depressive symptoms at week 8. [ABSTRACT FROM AUTHOR]

I have previously situated the UPIC of Iannis Xenakis, a computer music instrument of legendary intransigence, as set apart from the mainstream of electroacoustic technologies, developing its own "voice" as the utterance of "prophetic" traces: ancient, not modern. Here, I will approach the sound of the UPIC from the perspective of Robert Hatten's recent theory of "virtual agency." The sounds of the UPIC confound traditional notions of meaning in music as expressive -- in a human sense and reconfigure what Brian Kane calls the "audile techniques" of a "community of listeners." Yet the works made with this technology remain engaging and meaningful to us as music. In this paper, I will explore the idea of 'virtual agency' as extended to non-human agents, as figured by the events and appearances of the natural world, and consider the ways in which Xenakis allows us, as listeners, to engage with these "virtual agents" through their traces, evident in the graphism of the UPIC's interface. [ABSTRACT FROM AUTHOR]

World Trade Organisation which replaced GATT, has entered new domains in addition to General Agreement on Tariffs and Trade (GATT); e.g. trade aspects of intellectual property and anti-dumping measures. In some of them like TRIPS, it’s pioneer in rule-setting and in some like subsidies, it is the first time that mandatory rules have been envisaged. In Doha negotiations, commenced since 2001, following the organization's ministerial conference, many subjects have been put forward like environment in addition to conventional issues like tariff reduction except for energy, and only renewable energies are visible in WTO practice. The present paper tries to find the place of (renewable) energy in main WTO agreements and practice using a descriptive-analytical approach, and concludes that (renewable) energy lacks enough attention in the organisation's agreements and practice. It tries to give practical solutions for improvement of this kind of energy in WTO, suggest that the issue of energy be included as a comprehensive agreement in WTO's negotiation agenda. [ABSTRACT FROM AUTHOR]

Energy demand forecasting is crucial for effective resource management within the energy sector and is aligned with the objectives of Sustainable Development Goal 7 (SDG7). This study undertakes a comparative analysis of different forecasting models to predict future energy demand trends in Brazil, improve forecasting methodologies, and achieve sustainable development goals. The evaluation encompasses the following models: Seasonal Autoregressive Integrated Moving Average (SARIMA), Exogenous SARIMA (SARIMAX), Facebook Prophet (FB Prophet), Holt–Winters, Trigonometric Seasonality Box–Cox transformation, ARMA errors, Trend, and Seasonal components (TBATS), and draws attention to their respective strengths and limitations. Its findings reveal unique capabilities among the models, with SARIMA excelling in tracing seasonal patterns, FB Prophet demonstrating its potential applicability across various sectors, Holt–Winters adept at managing seasonal fluctuations, and TBATS offering flexibility albeit requiring significant data inputs. Additionally, the investigation explores the effect of external factors on energy consumption, by establishing connections through the Granger causality test and conducting correlation analyses. The accuracy of these models is assessed with and without exogenous variables, categorized as economical, industrial, and climatic. Ultimately, this investigation seeks to add to the body of knowledge on energy demand prediction, as well as to allow informed decision-making in sustainable energy planning and policymaking and, thus, make rapid progress toward SDG7 and its associated targets. This paper concludes that, although FB Prophet achieves the best accuracy, SARIMA is the most fit model, considering the residual autocorrelation, and it predicts that Brazil will demand approximately 70,000 GWh in 2033. [ABSTRACT FROM AUTHOR]

The focus of this paper is the relationship between sustainable energy sources and financial development. The main research hypothesis assumes a positive link between these areas, with inevitable differences across countries and business sectors. The following research questions were asked: Is the impact of financial development on sustainable energy resources the same in different EU countries advanced in green transition processes? How is transition towards renewable energy sources progressing in different economic sectors? Does financial development influence sectoral transition in particular countries? This study uses the TOPSIS method and 25 variables for EU countries from 2013 to 2021. Key findings reveal that the link between sustainable energy sources and financial development varies across EU countries, country size affects energy autonomy, and the transition also differs by business sector. Surprisingly, higher financial development correlates with less progress in sustainable energy initiatives. The results of our research may be useful for government decision-makers in the process of designing and controlling the country's transition to sustainable energy. The original contribution of the study is expressed in its the diagnosis of the relationship between financial development and sustainable energy sources, while most studies have focused on the relationship between the energy market and financial development. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate environmental efficiency based on energy change by using energy-related or nonenergy-related variables by reckoning with months and years as decision-making units (DMUs) for a hospital under radial and nonradial models. Design/methodology/approach: The non-oriented slack-based measures (SBM)-data envelopment analysis (DEA) model considering desirable and undesirable outputs has been embraced in this study, where its obtained results were compared with the results of other DEA models are output-oriented SBM-DEA and Banker, Charnes, & Cooper-DEA. For this purpose, this research has used a data set covering the 2012–2018 period for a reference hospital, which includes energy-related and nonenergy-related variables. Findings: The results demonstrate that environmental efficiency based on energy reached the highest level in the winter months, whereas the summer months have the lowest efficiency values arising from the increasing electricity consumption due to high cooling needs. According to results of the non-oriented SBM model, the month with the highest efficiency in all periods is January with a 0.936 average efficiency score, the lowest month is August with a 0.406 value. Originality/value: This paper differs from other studies related to energy and environmental efficiencies in the literature with some aspects. First, to the best of the authors' knowledge, this study is the first one that takes into account time periods (months and years) as (DMUs for a single organization. Second, this study investigates environmental nonefficiencies, which are derived from energy uses and factors affecting energy use. [ABSTRACT FROM AUTHOR]

Cultural institutions hold a unique position of influence, serving as hubs of education and knowledge dissemination for the people they serve. Embracing sustainable energy use in buildings in zoos and botanical gardens is a commitment to environmental responsibility that reinforces these institutions as trusted sources of information and community leaders on climate change, one of the most vital issues of our time. Sustainable energy solutions can synergize operations with educational missions, allowing zoos and botanical gardens to lead by example and inspire visitors to adopt eco-friendly practices in their own lives. In this opinion paper, Phipps Conservatory and Botanical Gardens President and CEO Richard Piacentini discusses key elements in developing a sustainable building energy plan, reviews potential barriers to implementation, and makes a case for adopting regenerative thinking and new metrics for measuring success—citing example cases from Phipps' Center for Sustainable Landscapes (CSL) project. Additionally, the paper demonstrates how green building certification systems and peer-based resource networks like The Climate Toolkit can help guide institutions in the process. [ABSTRACT FROM AUTHOR]

Over the last decades, drinking water and energy use have increased exponentially. To preserve ecosystems in the long term, a change in behavior is necessary on all levels of society including on the household level. This paper presents an integrated review of the determinants of long-term drinking water and energy conservation behavior of households. We identified forty-nine relevant studies discussing long-term conservation behavior in the context of drinking water and energy use. Long-term conservation behavior was measured as either persistent behavior, maintaining behavioral change, or intentions to maintain behavior, each with specific determinants. We found four key factors for long-term conservation behavior: consumption feedback, household characteristics, effort, and motives for conservation behavior. For future studies, we suggest follow-up questionnaires or interviews to measure the persistence of behavior and differentiate between curtailment and efficiency behavior. Worthwhile avenues for future research on long-term conservation behavior are household-tailored feedback mechanisms and the interaction between contextual factors and effort-based choices. [ABSTRACT FROM AUTHOR]

This paper will explore policy shifts in Nigeria's oil and gas, solar, nuclear, and mineral energy sectors. This policy shift by way of a transition, indigenization, and Nigerianization, has given way to deregulation, decentralization, and de-indigenization of many industries, most notably in the oil and gas sector, through the Petroleum Industry Act (PIA) of 2021 and the Local Content Act of 2010 (LCA). The paper recommends, amongst others, the establishment of a new legal regime that grants resource-based and property rights to resource-bearing communities and incorporates principles of international law, energy diplomacies, International Environmental Law, and international best practices. [ABSTRACT FROM AUTHOR]

Extensive analysis of intertwinement with other industries caused the energy sector to gain momentum in the recent economic literature. This paper aims to create an indicator that captures the impact of financial stability for energy companies on all other industrial groups. To this end, we use daily data from 2007 until the end of 2021 to compute financial stability metrics for all European companies from the STOXX 600 index. The main contribution of our study is to harness the neural network forecasting power to predict extreme levels of this impact. We motivate this choice with evidence from the literature that documents the improved performance of these methods in predicting crises. Our methodological approach also employs an outlier detection algorithm based on copula (COPOD) to identify situations when the energy sector substantially impacts other industries and develop a framework to predict out-of-sample situations. We found evidence that the Deep Renewal model has superior forecasting accuracy to the standard Croston model. The main conclusion is that the design of this methodological framework allows authorities to monitor the impact of shocks produced by the energy sector on financial stability at the European level and undertake strategic management actions. [ABSTRACT FROM AUTHOR]

Energy is known as the lifeline of national development, and from the last decade or so, the security of human energy supply has been frequently disturbed by natural disasters due to global warming and frequent geological activities. In this paper, by combing the literature, we found that the past literature on the relationship between energy and natural disasters mainly focused on measuring energy consumption under natural disasters, but less on the integrated evaluation of human economic activities, energy security and natural disasters, and less on the evaluation of the energy governance efficiency of each provincial, municipal, and autonomous region government in preventing and managing exposure to natural disasters from the perspective of Chinese provinces. Therefore, in order to fill the gap in the literature in this field, this paper collects panel data of energy consumption efficiency stages and natural disaster treatment stages from 2013 to 2017 for 30 provinces in China (excluding Hong Kong, Macao and Taiwan as well as Tibet Autonomous Region) and uses the two-stage undesirable dynamic DDF model as a framework to study the relationship between economic, environmental pollution and natural disasters for the sample data and to analyze the phase-by-phase evaluation of energy and natural disaster efficiency and make corresponding policy recommendations. The following conclusions are drawn: (1) The overall efficiency of China's eastern coastal provinces is higher than that of the central and western provinces. (2) The first-stage efficiency of Chinese provinces is better than the second stage, and the difference in efficiency of the first stage of each province is smaller than that of the second stage. (3) In terms of the efficiency of disaster prevention and relief inputs, the efficiency values are generally lower in most regions of China. (4) Finally, the annual efficiency of natural disaster losses is not high in all regions, and the efficiency values are higher in the eastern coastal regions than in the central and western regions. Accordingly, this paper proposes that each province should formulate relevant disaster prevention and economic development strategies according to regional characteristics, while the central government should also propose locally appropriate coordinated governance policies to effectively control carbon dioxide emissions and air pollution, as well as increase disaster prevention publicity and incorporate disaster prevention education-related work into the performance assessment mechanism of local governments to promote the interactive development of the two. [ABSTRACT FROM AUTHOR]

The research problem of this paper is related to numerous open questions in the field of energy, its understanding, its use, and the challenges of the energy future. After the introductory part, in which a brief historical overview of energy literacy is provided, the paper focuses on energy literacy, its emergence, and the different approaches to its definition and measurement. The paper analyzes the energy literacy of students at the Faculty of Economics in Rijeka based on their cognitive, affective, and behavioral skills. Their knowledge about energy, energy processes, and the energy efficiency of the objects they encounter on a daily basis is examined. Their personal attitudes and values are examined through various forms of personal initiatives and active participation in energy sustainability projects. Finally, the habits and behavioral patterns that the respondents have in their daily lives and their tendencies to save energy resources and find energy-efficient solutions are examined. Despite some positive findings, the current results are not satisfactory and point to the creation of adequate public policies with a particular focus on education and the role of the corrective mechanisms of the state, but also the need for joint negotiations between policy makers, regulators, scientists, representatives of civil society, and the business community. The particular contribution of this work is reflected in being the first research of its kind conducted among Croatian economics students, as well as among Croatian students in general; in the creation of a research instrument that is conceptually consistent with the findings from the existing literature, but with an original set of questions within each energy literacy skill adapted to the cultural and sociological background of the respondents; and in a kind of progress from previous research by taking into account the quantitative aspect (in addition to the qualitative) assessment of the respondents' energy literacy. [ABSTRACT FROM AUTHOR]

Within global debates, decentralization with respect to renewable electricity is positioned as pivotal in overlapping calls for decarbonization, energy access and just transitions. The promise is that technologies that are smaller and distributed will deliver a range of benefits, including enabling infrastructural innovations and expanding sustainable access, notably by empowering local authorities. While shifting to low-carbon systems is imperative, in this paper we call for attention to the complexity, opportunities and risks of commonly celebrated experiments in distributed electricity technologies when applied to African contexts. We draw on the case of Uganda, unpacking a series of four innovative electricity projects currently under way. For each case, we look at the actors involved and the imagined relationship between the projects and the incumbent grid. From these cases, we argue that, in this African context characterized by contested urban governance and fragmented networks, careful attention to supporting urban scale institutional and infrastructural development is necessary, although in many cases bypassed. [ABSTRACT FROM AUTHOR]

Purpose: The reason for writing the paper is growing complexity of management of the electric grid. Our collective electric system faces accelerating, multi-dimensional needs that must be addressed to deliver to our communities. Design/methodology/approach: The supply, transmission, distribution, and consumption of electricity are closely coupled, and must be actively coordinated. This requires the coordinated sensing, measurement, and control of devices and systems spread across the grid. This paper assesses the suitability of blockchain for this purpose, as a platform for transactive energy. Findings: Blockchain technology can facilitate secure and transparent record-keeping and transactions and thus may have many potential applications in the energy sector. Practical implications: Blockchain technology is still evolving and faces some challenges, such as scalability, interoperability, regulation, and adoption. However, blockchain has the potential to revolutionize the energy sector by transforming the way energy is produced, distributed, consumed, and traded. Social implications: High electricity demand, aging power grids, and climate disasters are straining our current energy system. As a result, more people are looking to optimize energy usage—and transactive energy may offer an answer. A Blockchain-enabled transacted energy framework can help everyone from consumers to corporations benefit from improved energy efficiency and profit in the process. Originality/value: Distributed energy resources, such as energy efficiency, smart demand response, smart electric vehicle charging, building-level energy storage and distributed solar photovoltaics, become more critical every year. Review of recent papers on these issues may be a valuable source of knowledge for interested parties. [ABSTRACT FROM AUTHOR]

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In The Birth of Energy (2019), Cara New Daggett offers an incisive critique of the dominant thermodynamic concept of energy. 'Energy', Daggett shows, is inextricably tied to an exploitative productivist politics that extols the virtues of work and the sins of waste. In this paper, I seek to develop new conversations between Daggett's account in The Birth of Energy and an important empirical development within the energy industry that Daggett herself does not consider: the smart grid. The paper draws upon a mixed-methods research project, investigating a UK smart grid trial called 'OpenDSR' devised and implemented by Manchester-based co-operative Carbon Co-op, with funding from the UK government. I draw on my research within OpenDSR to make two interconnected arguments. Firstly, I argue that the smart grid sees an intensification of the energy-as-work logic that Daggett opposes, taking pre-existing preoccupations with calculation and measurement within the energy system to new extremes in pursuit of the maximisation of efficiency and the minimisation of waste. I then proceed to think through the political implications of this argument, contending that while the smart grid reproduces the dominant energy logic that Daggett critiques, it might still have a part to play within an emancipatory environmental politics. In making this claim, a second argument emerges, constituting a sympathetic critique of Daggett's account more broadly. Daggett offers an incisive and important contribution that does much to develop debates within the energy social sciences and humanities. However, I suggest that her account risks obscuring some important political differences between variegated forms of work and waste: while she makes a persuasive case for an anti-work conceptualisation of energy that portends liberation from waged labour, her analysis of the kinds of 'efficiency' that pertain to the energy system seems less compelling. [ABSTRACT FROM AUTHOR]

To effectively utilize paper sludge and allow for energy recovery, the thermal behaviors of two paper sludge (PS) were studied by thermogravimetric analysis (TGA). The kinetic analysis was conducted according to Coats-Redfern (CR) method. The evolution of pore structure and surface morphology was investigated by N2 adsorption and scanning electron microscopy (SEM), respectively. The mineral transformation was analyzed by Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD). Derivative thermogravimetry (DTG) curves of PS show two different stages. The first stage was due to devolatilization (200–400 °C) and the second stage (650–800 °C) accounted for the mineral decomposition and char degradation. It was found that a large number of pores formed during pyrolysis because of char fragmentation. The specific surface areas increased from 5.161 to 22.894 m2 g−1 for PSA and from 9.007 to 16.126 m2 g−1 for PSB with the increase of temperature. The intense absorption bands of calcite (1426, 875 and 712 cm−1) in raw material indicated that calcite was the main mineral of PS. The decomposition of calcite at 700 °C and the further production of gehlenite (916 cm−1) at 900 °C, and the dehydration of kaolinite at 500 °C and further transformation into mullite (996 cm−1) at 900 °C were observed by both FTIR and XRD. The XRD results were generally consistent with FTIR analyses. [ABSTRACT FROM AUTHOR]

Considering the negative consequences of the excessive use of non-renewable energy and the development of technologies related to photovoltaic energy, the present paper aims to analyze if the photovoltaic systems are economically viable for university hospitals. A photovoltaic system was designed in the parking lot of the University Hospital of the Federal University of São Carlos (UFSCar) and analyzed the financial viability of its installation. As a result, the photovoltaic system is financially viable, with an expected generation of 194.2 MWh in the first year and a payback of 7 years. Thus, this paper contributes to the feasibility of photovoltaic projects in university hospitals, reducing electric energy consumption, reducing its operational costs, reducing the emission of pollution, and diversification of the Brazilian energy matrix. Furthermore, the results can be used as a scientific basis for other fields, such as public and private hospitals and clinics. [ABSTRACT FROM AUTHOR]

The booming growth of the internet of things has brought about widespread deployment of devices and massive amounts of sensing data to be processed. Federated learning (FL)-empowered mobile edge computing, known for pushing artificial intelligence to the network edge while preserving data privacy in learning cooperation, is a promising way to unleash the potential information of the data. However, FL's multi-server collaborative operating architecture inevitably results in communication energy consumption between edge servers, which poses great challenges to servers with constrained energy budgets, especially wireless communication servers that rely on battery power. The device-to-device (D2D) communication mode developed for FL turns high-cost and long-distance server interactions into energy-efficient proximity delivery and multi-level aggregations, effectively alleviating the server energy constraints. A few studies have been devoted to D2D-enabled FL management, but most of them have neglected to investigate server computing power for FL operation, and they have all ignored the impact of dataset characteristics on model training, thus failing to fully exploit the data processing capabilities of energy-constrained edge servers. To fill this gap, in this paper we propose a D2D-assisted FL mechanism for energy-constrained edge computing, which jointly incorporates computing power allocation and dataset correlation into FL scheduling. In view of the variable impacts of computational power on model accuracy at different training stages, we design a partite graph-based FL scheme with adaptive D2D pairing and aperiodic variable local iterations of heterogeneous edge servers. Moreover, we leverage graph learning to exploit the performance gain of the dataset correlation between the edge servers in the model aggregation process, and we propose a graph-and-deep reinforcement learning-based D2D server pairing algorithm, which effectively reduces FL model error. The numerical results demonstrate that our designed FL schemes have great advantages in improving FL training accuracy under edge servers' energy constraints. [ABSTRACT FROM AUTHOR]