bluuebunny/crossref_metadata_2025 huggingface dataset:
Periodontal Disease in Obese Patients; Interleukin-6 and C-Reactive Protein Study: A Systematic Review
Authors: Cruz-Ávila Julieta , Hernández-Pérez Elizabeth , González-González Rogelio , Bologna-Molina Ronell , Molina-Frechero Nelly
Published: November 2022

Periodontal disease (PD) and obesity are characterized by a dysregulated inflammatory state. Both conditions trigger inflammatory and immune responses with an increase in proinflammatory cytokines such as Interleukin 6 (IL-6) and the release of inflammatory mediators such as C-reactive protein (CRP). Individuals with a high body mass index (BMI) present a chronic inflammatory state. The aim of the present study was to perform a systematic review of inflammatory markers (IL-6 and CRP) in obese patients with PD and their possible relationship by analyzing the levels of these markers. A digital literature search was performed in three databases—PubMed, SciElo and Medigraphic—through an advanced search for original articles, employing IL-6 and CRP in obese patients with PD, within a publication period from 2010 to 2021. PRISMA guidelines, the JADAD scale and a qualitative analysis of scientific evidence were performed using the Cochrane collaboration method and the RoB 2 assessment tool. Ten articles were included in this analysis with the variables recorded and associated with subjects with obesity and PD. Of the ten articles included, three analyzed IL-6 and CRP, four analyzed IL-6 and three analyzed CRP. In conclusion, and based on the available evidence, the aforementioned markers of inflammation demonstrate that there is a relationship between PD and obesity.
Daytime Sleepiness and Quality of Life in Obstructive Sleep Apnoea Patients before and after Long-Term Mandibular Advancement Device Treatment
Authors: Halfeld Signe , Sonnesen Liselotte
Published: November 2022

This study compared daytime sleepiness and quality of life in OSA patients with healthy controls and compared sleepiness and quality of life in OSA patients before and after long-term treatment with a mandibular advancement device (MAD). A total of 27 OSA patients (18 men, 9 women, mean age 52.3 years) and 32 healthy age- and sex-matched controls (20 men, 12 women, mean age 51.1 years) were included. At baseline and after MAD treatment, daytime sleepiness and quality of life were recorded by the Epworth Sleepiness Scale (ESS) and Short Form-36 questionnaires (SF-36). Daytime sleepiness occurred significantly more often in OSA patients compared to controls at baseline (p = 0.01). The quality of life domains Energy and vitality (p < 0.0001), General perception of health (p = 0.0002), Mental health (p = 0.0031), Social functioning (p = 0.0119), Role limitations due to emotional problems (p = 0.0173) and Physical functioning (p = 0.0226) were significantly poorer in OSA patients compared to controls at baseline. After long-term MAD treatment, daytime sleepiness decreased (p < 0.01) and the quality of life domain Energy and Vitality increased (p < 0.01) in OSA patients compared to baseline. The results of the present study support the relevance of MAD treatment as an effective tool for decreasing daytime sleepiness and increasing the quality of life in OSA patients—also in the long term.
A Framework to Develop Urban Aerial Networks by Using a Digital Twin Approach
Authors: Brunelli Matteo , Ditta Chiara Caterina , Postorino Maria Nadia
Published: November 2022

The new concept of Urban Air Mobility (UAM) and the emergent unmanned aerial vehicles are receiving more and more attention by several stakeholders for implementing new transport solutions. However, there are several issues to solve in order to implement successful UAM systems. Particularly, setting a suitable framework is central for including this new transportation system into the existing ones—both ground and aerial systems. Regulation and definition of aerial networks, but also the characterization of ground facilities (vertiports) to allow passengers and freight to access the services are among the most relevant issues to be discussed. To identify UAM transportation networks, suitably connected with ground transportation services, digital twin models could be adopted to support the modelling and simulation of existing—and expected—scenarios with constantly updated data for identifying solutions addressing the design and management of transport systems. In this perspective, a digital twin model applied to an existing urban context—the city of Bologna, in northern Italy—is presented in combination with a novel air transport network that includes the third dimension. The 3D Urban Air Network tries to satisfy the principle of linking origin/destination points by ensuring safe aerial paths and suitable aerial vehicle separations. It involves innovative dynamic links powered by a heuristic cost function. This work provides the initial framework to explore the integration of UAM services into realistic contexts, by avoiding the costs associated with flight simulations in reality. Moreover, it can be used for holistic analyses of UAM systems.
Models for Quantum Measurement of Particles with Higher Spin
Authors: Nieuwenhuizen Theodorus M.
Published: November 2022

The Curie–Weiss model for quantum measurement describes the dynamical measurement of a spin-12 by an apparatus consisting of an Ising magnet of many spins 12 coupled to a thermal phonon bath. To measure the z-component s=−l,−l+1,⋯,l of a spin l, a class of models is designed along the same lines, which involve 2l order parameters. As required for unbiased measurement, the Hamiltonian of the magnet, its entropy and the interaction Hamiltonian possess an invariance under the permutation s→s+1 mod 2l+1. The theory is worked out for the spin-1 case, where the thermodynamics is analyzed in detail, and, for spins 32,2,52, the thermodynamics and the invariance are presented.
Technical Efficiency and Productivity Growth of Crude Palm Oil: Variation across Years, Locations, and Firm Sizes in Indonesia
Authors: Azzahra Tarbiyah Islamiya Haura , Wulan Sari Dyah , Zeqi Yasin Mohammad , Restikasari Wenny , Shaari Mohd Shahidan , Devis Susandika Mochamad
Published: November 2022

Crude palm oil (CPO) is a valuable commodity for Indonesia’s economy as the country has become the world’s biggest producer and exporter. Therefore, maintaining productivity in the CPO industry is crucial to ensure that the global demand is met. This study aims to examine Indonesian CPO productivity and its components using total factor productivity growth (TFPg) with stochastic frontier analysis. This study analyzes the variation in the TFPg across years, locations, and firm sizes. The first two analyses imply that, on average, the CPO industry’s productivity declines annually, with firms in 20 provinces experiencing negative TFPg. Regarding size, the analysis demonstrates that the technical efficiency change (TEC) and technical change (TC) have regressed the TFPg in all scale firms. However, medium firms saw a smaller decline in comparison to large firms. Conversely, large firms possess slightly better scale efficiency change (SEC) than medium firms, although both types attain a negative SEC. The findings also show that the main factor contributing to the gain or decline in productivity is TC, which suggests the urgency of innovative technology in the CPO industry.
From College-to-Work: Latent Class Models Analysis of Mutual Adjustment in Internships after the Diploma
Authors: Ramos Rosária , Fonseca Jaime R. S. , Cardim José Casqueiro , Amorim Rita
Published: November 2022

This article aims to identify which factors enable the mutual adjustment of top managers of small enterprises (SEs), frequently their owners, and interns (young college graduates) in their first work experiences. Using latent segment models and data obtained from an archive database of an internship program with complete information on both interns and SEs top managers (n = 102), the categories of mutual adjustment between interns and SEs top managers were obtained: (1) mutual adjustment corresponding to very satisfied SE top managers and interns, hired at the end of the internship (75%); and (2) mutual maladjustment characterized by the dissatisfied SE top managers and interns, resulting in no job creation (25%). Finally, we conducted a binary logistic regression (mutual adjustment as the dependent variable), using forward LR, and we identified organizational socialization practices and learning system as factors that contribute to explain mutual adjustment.
Addiction to New Technologies and Cyberbullying in the Costa Rican Context
Authors: Lozano-Blasco Raquel , Quilez-Robres Alberto , Rodriguez-Araya Roxana , Casanovas-López Raquel
Published: November 2022

Addiction to new technologies (Internet, smartphone and video games) as well as cyber-aggression presents a growing incidence at a global level. Correlational research is proposed with a sample of n = 127 Costa Rican adolescents, with a mean age of 16.32 years, comprising 67 men and 60 women. The objective was to determine the prevalence of Internet, smartphone and video game addiction and its close relationship with cyberbullying (cyber-victim role, cyberbully role and mixed role) in the Costa Rican context. The results show a high rate of abusive use (connection time) of the Internet and “smartphones”, and the correlation study, multiple regressions, backward elimination method and network analysis show how the behavior of cyberbullies is moderately mediated by “Lack of control of Smartphone” and to a large extent by “Avoidance and social problem video games”, while that of victims is moderately mediated by “Avoidance and social problem video games”, and is slightly mediated for “Lack of control of Smartphone” and for “Lack of control of Internet”. In addition, there is a strong relationship between holding both the role of cyber-victim and cyberbully, developing feelings of revenge and lack of empathy. The practical implications, and the relevance of the socio-demographic and social explanatory variables of both phenomena are discussed. It is concluded that there is evidence of an explanatory and close relationship between the phenomena of cybervictimization, cyber-aggression and addiction to the Internet, smartphone and video games.
Pocket Restorative Practice Approaches to Foster Peer-Based Relationships and Positive Development in Schools
Authors: Mas-Expósito Laia , Krieger Virginia , Amador-Campos Juan Antonio , Casañas Rocío , Lalucat-Jo Lluís
Published: November 2022

In schools, the implementation of restorative practices is linked to an improvement in school climate, discipline and management of conflict. There are a few systematic reviews about the implementation of pocket restorative practice approaches (PRPA) in schools but they are restricted in terms of practices included, outcomes and study design. Moreover, none of them seem to include evidence-based recommendations for their implementation. We have dealt with such issues by carrying out a systematic review of the effectiveness of PRPA and developing evidence-based practice guidelines. Nineteen studies met the inclusion criteria and we developed eighteen evidence-based practice guidelines. The implementation of PRPA seems to be more common in secondary education and may be used to improve social and emotional skills and relationships, and to deal with and prevent conflicts while changing school culture in disciplinary terms. The greatest evidence available is for a specific model of mediation that is recommended to decrease aggression levels in primary education. Our guidelines may offer support to improve the quality of prevention and intervention actions used in schools. The implementation of these kinds of approaches may help to promote mental health and youth development, and deal with adverse behavioral outcomes such as bullying, which are all major public issues in the school community.
State of Mind Assessment in Relation to Adult Attachment and Text Analysis of Adult Attachment Interviews in a Sample of Patients with Anorexia Nervosa
Authors: Civilotti Cristina , Franceschinis Martina , Gandino Gabriella , Veglia Fabio , Anselmetti Simona , Bertelli Sara , D’Agostino Armando , Redaelli Carolina Alberta , del Giudice Renata , Giampaolo Rebecca , Fernandez Isabel , Finzi Sarah , Celeghin Alessia , Donarelli Edoardo , Di Fini Giulia
Published: November 2022

Background: Attachment theory represents one of the most important references for the study of the development of an individual throughout their life cycle and provides the clinician with a profound key for the purposes of understanding the suffering that underlies severe psychopathologies such as eating disorders. As such, we conducted a cross-sectional study with a mixed-methods analysis on a sample of 32 young women with anorexia nervosa (AN); this study was embedded in the utilized theoretical framework with the following aims: 1. to evaluate the state of mind (SoM) in relation to adult attachment, assuming a prevalence of the dismissing (DS) SoM and 2. to analyze the linguistic attachment profile emerging from the transcripts of the AAIs. Methods: Interviews were transcribed verbatim, coded, and analyzed using the linguistic inquiry and word count (LIWC) method. Results: The results were observed to be consistent with the referenced literature. The prevalence of a DS SoM (68.75%) is observed in the study sample, whereas the results of the lexical analysis of the stories deviate from expectations. Notably, the lexical results indicate the coexistence of the dismissing and entangled aspects at the representational level. Conclusions: The study results suggest a high level of specificity in the emotional functioning of patients with AN, with a focusing on a pervasive control of emotions that is well illustrated by the avoidant/ambivalent (A/C) strategy described in Crittenden’s dynamic–maturational model. These findings and considerations have important implications for clinical work and treatment, which we believe must be structured on the basis of starting from a reappraisal of emotional content.
A Universal Electronically Controllable Memelement Emulator Based on VDCC with Variable Configuration
Authors: Petrović Predrag B.
Published: November 2022

In this paper, a universal fractional order memelement (FOME) emulator is proposed based on the use of a voltage differentiating current conveyor (VDCC) as active block. The emulation circuit was implemented without an analog voltage multiplier and with only one type of grounded passive element—capacitors. Specially designed switching networks allow controlling the type of memelement and the emulator mode—floating or/and grounded, electronically controlled (by changing the bias voltage of the VDCC) FOMEs. The proposed emulator was theoretically analyzed, and the influence of possible non-idealities and parasitic effects was also been analyzed to reduce the undesirable effects by selecting the passive circuit elements. The proposed designs are very simple compared to most of the designs available in the literature and can operate in a wide frequency range (up to 50 MHz) and also satisfy the non-volatility test. All realized memelements can be used in incremental and decremental modes as well as in inverse configuration. The performance of the circuit was verified by HSPICE simulations using 0.18 μm TSMC process parameters and ±0.9 V power supply. The proposal is also supported by experimental results with off-the-shelf components (LM13700 and one AD844) in order to confirm the proposed solution’s workability.
Vertically Federated Learning with Correlated Differential Privacy
Authors: Zhao Jianzhe , Wang Jiayi , Li Zhaocheng , Yuan Weiting , Matwin Stan
Published: November 2022

Federated learning (FL) aims to address the challenges of data silos and privacy protection in artificial intelligence. Vertically federated learning (VFL) with independent feature spaces and overlapping ID spaces can capture more knowledge and facilitate model learning. However, VFL has both privacy and utility problems in framework construction. On the one hand, sharing gradients may cause privacy leakage. On the other hand, the increase in participants brings a surge in the feature dimension of the global model, which results in higher computation costs and lower model accuracy. To address these issues, we propose a vertically federated learning algorithm with correlated differential privacy (CRDP-FL) to meet FL systems’ privacy and utility requirements. A privacy-preserved VFL framework is designed based on differential privacy (DP) between organizations with many network edge devices. Meanwhile, feature selection is performed to improve the algorithm’s efficiency and model performance to solve the problem of dimensionality explosion. We also propose a quantitative correlation analysis technique for VFL to reduce the correlated sensitivity and noise injection, balancing the utility decline due to DP protection. We theoretically analyze the privacy level and utility of CRDP-FL. A real vertically federated learning scenario is simulated with personalized settings based on the ISOLET and Breast Cancer datasets to verify the method’s effectiveness in model accuracy, privacy budget, and data correlation.
Newly Added Construction Land Information Extraction Method for High-Resolution Remote Sensing Images Based on Weakening of the Negative Sample Weight
Authors: Zhao Guiling , Liang Weidong , Liang Zhe , Guo Quanrong
Published: November 2022

Information regarding newly added construction land can be extracted from high-resolution remote sensing images. The retrieval accuracy of land cover changes across the country has improved, and the illegal use of land is actively monitored. To address the imbalance between positive and negative training samples in extracting information regarding newly added construction land, a method for identifying newly added construction land by weakening the weight of negative samples was proposed. A focal loss function was used to weaken the negative samples’ weights and improve the overfitting U-net. Since the two parameters of the focal loss function are not independent of each other, they need to be selected at the same time. Therefore, this paper developed a formula for selecting the balance factor α based on a large number of experimental results. First, the GF-2 image was combined with the historical land change survey data and monitoring vector results to construct a dataset, and then the training dataset was input into a fully convolutional neural network (CNN) integrated with feature fusion and a focal loss function. Finally, the accuracy of the trained network model was verified. To demonstrate the applicability of the method of determining the parameters of the focal loss function, the validation set was divided into four subsets for accuracy verification. The experimental results showed that the F1-score of newly added construction land information extracted by this method reached 0.913, which is 0.078 and 0.033 higher than those of the U-net and the improved U-net. The parameters obtained by the method proposed in this study achieved the best results on the four verification sets, which shows that the method for extracting newly added construction land information and that for selecting parameters have strong applicability.
Driving Assistance System for Ambulances to Minimise the Vibrations in Patient Cabin
Authors: Aldegheishem Abdulaziz , Alrajeh Nabil , Parra Lorena , Romero Oscar , Lloret Jaime
Published: November 2022

The ambulance service is the main transport for diseased or injured people which suffers the same acceleration forces as regular vehicles. These accelerations, caused by the movement of the vehicle, impact the performance of tasks executed by sanitary personnel, which can affect patient survival or recovery time. In this paper, we have trained, validated, and tested a system to assess driving in ambulance services. The proposed system is composed of a sensor node which measures the vehicle vibrations using an accelerometer. It also includes a GPS sensor, a battery, a display, and a speaker. When two possible routes reach the same destination point, the system compares the two routes based on previously classified data and calculates an index and a score. Thus, the index balances the possible routes in terms of time to reach the destination and the vibrations suffered in the patient cabin to recommend the route that minimises those vibrations. Three datasets are used to train, validate, and test the system. Based on an Artificial Neural network (ANN), the classification model is trained with tagged data classified as low, medium, and high vibrations, and 97% accuracy is achieved. Then, the obtained model is validated using data from three routes of another region. Finally, the system is tested in two new scenarios with two possible routes to reach the destination. The results indicate that the route with less vibration is preferred when there are low time differences (less than 6%) between the two possible routes. Nonetheless, with the current weighting factors, the shortest route is preferred when time differences between routes are higher than 20%, regardless of the higher vibrations in the shortest route.
Review of the Chosen Methods of Producing Front Contacts to Transparent Conductive Oxides Layers in Photovoltaic Structures
Authors: Musztyfaga-Staszuk Małgorzata , Czupryński Artur , Radev Rossen
Published: November 2022

It is well known that PV thin films can be deposited by an extensive range of more or less expensive and complicated techniques (such as sputtering, chemical vapor deposition (CVD), physical vapor deposition (PVD), pulsed laser deposition, atomic layer deposition (ALD)). The present paper focuses on TCO layers applied by chosen techniques, including mainly the ALD and CVD methods. Thin layers of transparent conductive oxides constitute a well-known group of materials with unique properties. Oxides such as ZnO, SnO2, and In2O3 are the most significant materials of this type; some of them are discussed in the paper. From the application point of view in the photovoltaic industry, the goal is to apply a method that will provide the highest value of electric charge conductivity while maintaining the minimum value of absorption in the layer and a reduced value of the reflection coefficient. The implementation of significant achievements in the coming decade is for developing guidelines for metallization processes and TCO layers deposited by the ALD method. The work contains chosen engineering processes, including the fabrication of transparent conductive oxides (TCO) thin films applied to silicon substrates by ALD and CVD for application as emitter conductive coatings in photovoltaic structures and the fabrication front metallization of solar cell using different techniques, including among others laser techniques. Moreover, the work also contains predictions about solar cells, which will be among the most prevalent solar cells in mass production using thin- and thick-film technology.
Dissolved Gas Analysis and Application of Artificial Intelligence Technique for Fault Diagnosis in Power Transformers: A South African Case Study
Authors: Thango Bonginkosi A.
Published: November 2022

In South Africa, the growing power demand, challenges of having idle infrastructure, and power delivery issues have become crucial problems. Reliability enhancement necessitates a life-cycle performance analysis of the electrical power transformers. To attain reliable operation and continuous electric power supply, methodical condition monitoring of the electrical power transformer is compulsory. Abrupt breakdown of the power transformer instigates grievous economic detriment in the context of the cost of the transformer and disturbance in the electrical energy supply. On the condition that the state of the transformer is appraised in advance, it can be superseded to reduced loading conditions as an alternative to unexpected failure. Dissolved gas analysis (DGA) nowadays has become a customary method for diagnosing transformer faults. DGA provides the concentration level of various gases dissolved, and consequently, the nature of faults can be predicted subject to the concentration level of the gases. The prediction of fault class from DGA output has so far proven to be not holistically reliable when using conventional methods on account of the volatility of the DGA data in line with the rating and working conditions of the transformer. Several faults are unpredictable using the IEC gas ratio (IECGR) method, and an artificial neural network (ANN) has the hindrance of overfitting. Nonetheless, considering that transformer fault prediction is a classification problem, in this work, a unique classification algorithm is proposed. This applies a binary classification support vector machine (BCSVM). The classification precision is not reliant on the number of features of the input gases dataset. The results indicate that the proposed BCSVM furnishes improved results concerning IECGR and ANN methods traceable to its enhanced generalization capability and constructional risk-abatement principle.
Deep Reinforcement Learning-Based Operation of Transmission Battery Storage with Dynamic Thermal Line Rating
Authors: Avkhimenia Vadim , Gemignani Matheus , Weis Tim , Musilek Petr
Published: November 2022

It is well known that dynamic thermal line rating has the potential to use power transmission infrastructure more effectively by allowing higher currents when lines are cooler; however, it is not commonly implemented. Some of the barriers to implementation can be mitigated using modern battery energy storage systems. This paper proposes a combination of dynamic thermal line rating and battery use through the application of deep reinforcement learning. In particular, several algorithms based on deep deterministic policy gradient and soft actor critic are examined, in both single- and multi-agent settings. The selected algorithms are used to control battery energy storage systems in a 6-bus test grid. The effects of load and transmissible power forecasting on the convergence of those algorithms are also examined. The soft actor critic algorithm performs best, followed by deep deterministic policy gradient, and their multi-agent versions in the same order. One-step forecasting of the load and ampacity does not provide any significant benefit for predicting battery action.
Energy Sector Derived Combustion Products Utilization—Current Advances in Carbon Dioxide Mineralization
Authors: Zdeb Janusz , Howaniec Natalia
Published: November 2022

Carbon dioxide and combustion products are among the main waste streams deriving from the energy sector. Efficient and cost-effective methods of solid waste valorization and carbon capture, storage and utilization are needed in the transition period towards carbon neutrality in light of the recent scenarios forecasting energy demand and energy supply mix under dynamic social, economic and political circumstances. Within this paper, the current advances in carbon dioxide mineralization, combining carbon dioxide utilization and combustion products valorization, are presented in terms of the recognized methodological options of carbonation methods, process efficiency and effects on the process product properties. Special attention is given to the studies on the valorization of fluidized bed boilers fly ash, differing in a range of parameters from the conventional boilers fly ash, as well as the effects of the carbonation process on the stabilization and improvement of its properties and the resulting extended range of applicability. The relevant research fields needing further investigations, as well as the desired decision makers’ supporting actions, are also specified.
What China’s Environmental Policy Means for PV Solar, Electric Vehicles, and Carbon Capture and Storage Technologies
Authors: Pouran Hamid M. , Karimi Seyed M. , Padilha Campos Lopes Mariana , Sheng Yong
Published: November 2022

This perspective paper elaborates on how the burden of environmental issues on public health and the economy led China’s government to declare its revised environmental policies or “war on pollution”. It explains the importance of photovoltaic solar (PV), electric vehicles (EV), and carbon capture and storage (CCS) in helping China to mitigate its environmental concerns while maintaining economic growth. China already leads PV solar and EV manufacturing; however, it has not made a tangible contribution to CCS technology yet. On the other hand, CCS is far behind its envisaged role in contributing to the reduction of greenhouse gas emissions and supporting countries to meet their net carbon zero targets. China’s existing coal power plants are good candidates to be retrofitted with CCS. Similar to PV and EV technologies, China could influence this technology globally, by reducing the uncertainties, demonstrating the viability, and driving the costs lower. China’s revised policies have been effective and shown global impacts, but their implementations remain as strong as the political will behind them.
Analysis of Surrounding Rock Control Technology and Its Application on a Dynamic Pressure Roadway in a Thick Coal Seam
Authors: Hao Jian , Chen Anfa , Li Xuelong , Bian Hua , Zhou Guanghua , Wu Zhenguo , Peng Linjun , Tang Jianquan
Published: November 2022

The deformation control of roadways surrounded by rock in the fully mechanized amplification sections of extra-thick coal seams is problematic. To analyze the failure and failure characteristics of a support frame, as well as the deformation and failure processes of the surrounding rock, through theoretical analysis and industrial tests, the deformation and support conditions of a return airway of a fully mechanized caving face in an extra-thick coal seam in the Yangchangwan Coal Mine, in the Ningdong mining, area were examined. Combined with limit equilibrium theory and roadway section size, the width of the coal pillar of the return air roadway at the 130,205 working face was calculated to be 6 m. The layout scheme and implementation parameters of roof blasting pressure relief, coal pillar grouting modification, and bolt (cable) support were designed. Based on the analysis, a “Coal pillar optimization–roof cutting destressing–routing modification–rock bolting” system for surrounding rock control in synergy with the fully enlarged section mining roadway in the extra-thick coal seam was proposed, and the deformation of the surrounding rock was monitored, along with the stress of the support body and the grouting effect on the site. Field experiments show that after the implementation of the surrounding rock control in synergy with the roadway, the maximum subsidence of the top plate was 55 mm, the maximum bottom heave of the bottom plate was 55 mm, the maximum values of the upper and lower side drums were 30 mm and 70 mm, respectively, and the breaking rate of the bolt (cable) and the deformation of the surrounding rock of the roadway was reduced by more than 90% and 70%, respectively. The effective performance of the coal pillar grouting was observed as well. Field practice of the roadway surrounding rock control in the synergy method indicated that rock deformation was effectively controlled, and the successful application of this technology was able to provide reliable technical and theoretical support for the Ningdong mining area and mines with similar conditions.
Temporal Verification of Relay-Based Railway Traffic Control Systems Using the Integrated Model of Distributed Systems
Authors: Karolak Juliusz , Daszczuk Wiktor B. , Grabski Waldemar , Kochan Andrzej
Published: November 2022

Relay-based traffic control systems are still used in railway control systems. Their correctness is most often verified by manual analysis, which does not guarantee correctness in all conditions. Passenger safety, control reliability, and failure-free operation of all components require formal proof of the control system’s correctness. Formal evidence allows certification of control systems, ensuring that safety will be maintained in correct conditions and the in event of failure. The operational safety of systems in the event of component failure cannot be manually checked practically in the event of various types of damage to one component, pairs of components, etc. In the article, we describe the methodology of automated system verification using the IMDS (integrated model of distributed systems) temporal formalism and the Dedan tool. The novelty of the presented verification methodology lays in graphical design of the circuit elements, automated verification liberating the designer from using temporal logic, checking partial properties related to fragments of the circuit, and fair verification preventing the discovering of false deadlocks. The article presents the verification of an exemplary relay traffic control system in the correct case, in the case of damage to elements, and the case of an incorrect sequence of signals from the environment. The verification results are shown in the form of sequence diagrams leading to the correct/incorrect final state.
Review on Research Progress of Hydraulic Powered Soft Actuators
Authors: Shi Hu , Tan Kun , Zhang Boyang , Liu Wenqiao
Published: November 2022

Soft actuators have received extensive attention in robotics and smart device applications due to their distinctive dexterity and compliance. Among them, hydraulic soft actuators play an important role in the area because they have much higher specific power and power density than other types such as pneumatic soft actuators. Nevertheless, the deformation of flexible materials in soft actuators brings about inherent hysteresis and nonlinearity, which severely hinders them from producing the desired movement in the presence of advanced control strategies. In this paper, previous research efforts made to enhance the driving capability and actuation efficiency of hydraulic soft actuators are illustrated and analyzed from the three aspects of architecture, materials, and control strategy. Meanwhile, the issues and challenges that have emerged when developing hydraulic soft actuators are discussed. Finally, the potential future development of hydraulic powered soft actuators is discussed.
Grid-Forming Virtual Power Plants: Concepts, Technologies and Advantages
Authors: Gholami Khalil , Behi Behnaz , Arefi Ali , Jennings Philip
Published: November 2022

Virtual Power Plants (VPPs) are efficient structures for attracting private investment, increasing the penetration of renewable energy and reducing the cost of electricity for consumers. It is expected that the number of VPPs will increase rapidly as their financial return is attractive to investors. VPPs will provide added value to consumers, to power systems and to electricity markets by contributing to different services such as the energy and load-following services. One of the capabilities that will become critical in the near future, when large power plants are retired, is grid-forming capability. This review paper introduces the concept of grid-forming VPPs along with their corresponding technologies and their advantages for the new generation of power systems with many connected VPPs.
Elaboration of Energy Balance: A Model for the Brazilian States
Authors: Ferreira Denilson , Pinto João O. P. , da Silva Luiz E. B. , Kimpara Marcio L. M. , Galotto Luigi
Published: November 2022

The energy balance constitutes a powerful management instrument for government agencies, as it offers an overview of the energy situation of the country (or region) and serves as a guide for energy policies and monitoring of these policies. Although Brazil has published the national energy balance for more than half a century, the national publication does not adequately address energy statistics at the level of the states. This occurs either due to the lack of specific data or the absence of total disaggregation. Accordingly, the elaboration and implementation of public policies for the energy sector in the Brazilian states lack consistent energy statistics. Therefore, this paper aims to present a model for the Brazilian states to elaborate the energy balance. The proposed model consists of applying internationally referenced methodologies to develop a user-friendly software, which includes automatic energy unit conversions, different chart styles, high-level data organization, and Sankey diagrams. As a result, the software can be adopted by local governments as a tool to maintain the state energy balance publication periodically, and hence obtain the detailed information necessary to manage and formulate energy policies. The advantage of the software is that it can be operated by non-experts and the energy flow as well as the entire report can be generated automatically. The proposed software was successfully used to generate the energy balance of the Mato Grosso do Sul state.
Geometrical Optimization of Pelton Turbine Buckets for Enhancing Overall Efficiency by Using a Parametric Model—A Case Study: Hydroelectric Power Plant “Illuchi N2” from Ecuador
Authors: Erazo Jose , Barragan Guillermo , Pérez-Sánchez Modesto , Tapia Clotario , Calahorrano Marco , Hidalgo Victor
Published: November 2022

In Ecuador, the implementation of hydroelectric power plants has had a remarkable growth in the energy sector due to its high efficiency, low environmental impact, and opportunities to generate employment. One of the sectors with the greatest benefits from this type of energy has been the rural sector, where several small-scale hydroelectric plants (0.5 MW–10 MW) have been installed, usually with Pelton turbines. Although these turbines are highly efficient, one of the challenges is to obtain the optimal geometry of the bucket to take advantage of the greatest amount of energy from the water, avoiding the separation of the fluid. In this context, this study focuses on the development of an analytical and iterative methodology that allows for the determining of the appropriate dimensions of the buckets to achieve maximum turbine efficiency. For that, a parametric model has been proposed considering the dimensions and main angles of the bucket, the net hydraulic head and the working flow, as well as the power losses. The results of the model have been validated by means of CFD and by contrasting the experimental data obtained from the “Illuchi N2” Hydroelectric Power Plant in Ecuador, and it is concluded that it is possible to improve the turbine efficiency by up to 4%.
Influence of the Design of a Residual Current Device on Its Break Time
Authors: Czaja Pawel
Published: November 2022

Residual current devices (RCDs) are devices that can provide very good protection measures against electric shock. Yet, under certain circumstances, they can cause unnecessary and unexpected switching off of power in the protected circuits. The main component that determines the properties of an RCD is the summation current transformer. In recently produced RCDs, whose operation is independent from the installation voltage, the summation transformer, apart from detection of the residual current, has yet another task: it must also provide an appropriate energy value to the electromagnetic release in order to carry out mechanical disconnection of the contacts. In this type of RCD, the core of the summation transformer should be made of magnetic material with very high permeability and appropriate geometric dimensions. Manufacturers of RCDs, in order to reduce production costs and to promote miniaturization of the devices, use cores for summation transformers made of amorphous or nanocrystalline materials quite often. In such RCD designs, the impedance-matching circuit is used in the secondary circuit of the summation transformer to ensure proper sensitivity to the residual current. The paper describes the impact of using additional impedance-matching elements in the secondary circuit on the RCD break time. The paper presents the results of tests and measurements of the RCD break times of various internal structures.
Technological Advancements and Challenges of Geothermal Energy Systems: A Comprehensive Review
Authors: Kumar Laveet , Hossain Md. Shouquat , Assad Mamdouh El Haj , Manoo Mansoor Urf
Published: November 2022

Geothermal is a renewable energy source, but this is not as often seen as other renewable energy sources, such as solar, wind, hydro, etc. Several applications could be implemented through geothermal energy, and heating & cooling systems are one of them. Because of the limits of technology, it is hard to improve cooling systems as an application. To address long-term sustainable space heating and cooling, it is imperative to develop geothermal technology. It is known as the oldest, most flexible, most adaptable, and most prevalent approach toward using renewable energy. Therefore, this review has reviewed the global development and challenges of geothermal energy for cooling systems. There are large reserves of geothermal energy available around the world, and numerous scholars have emphasized its importance, but due to a lack of knowledge, no operational work has been done in using these systems for cooling up to this point. This review paper examines globally available geothermal energy sources and technologies for environmentally friendly and sustainable cooling supplies. Finally, the benefits and challenges of geothermal systems for cooling are outlined to promote local, regional, and global investment in utilizing these resources for cooling.
The Concept of Extended Producer Responsibility in the Field of Packaging Industry and the Energy Sector in the Light of the Circular Economy—The Example of Poland
Authors: Siuta-Tokarska Barbara , Thier Agnieszka , Hornicki Krzysztof
Published: November 2022

The aim of this article is to analyze the effectiveness of the Extended Producer Responsibility (EPR) concept for packaging in the context of the transition to a Circular Economy (CE) and the corresponding transformation of the energy sector. The functioning of today’s packaging industry is becoming more and more linked to the assumptions of the CE due to the use and recycling of raw materials. The basic research method used in this work is an analysis of the literature on the links between the concept of the EPR and the CE. The authors limited their research to the selected legal, economic and social aspects of packaging production and management in the European Union (EU). The situation in Poland is discussed in particular and the legal, economic and social specificity of the implementation of the EPR in this country is presented. This paper emphasizes the dependance between the implementation of the EPR concept and the effectiveness of the transformation toward a CE, which is achieved by increasing the circularity in the energy sector.
Field Measurements and Analyses of Traction Motor Noise of Medium and Low Speed Maglev Train
Authors: Ou Fengyu , Liao Xiaokang , Yi Cai , Lin Jianhui
Published: November 2022

In order to reduce the impact of noise on the environment and reduce the dissipation of useless energy of traction motors, this study analyzed the noise of a traction motor by detecting the vibration acceleration of the suspension frame. Field tests were conducted to measure the traction noise and suspension frame vibration in a commercially operational medium- and low-speed maglev train. The tests showed that as the train accelerates, the sound pressure grows overall, but the increase becomes smaller at each test speed. The speed of the maglev train is closely correlated with the vibrations of the suspension frame in lateral/vertical directions. The dominant frequency of traction motor noise is basically consistent with that of suspension frame vibration acceleration, showing that the suspension frame vibration is the main reason for high-frequency noise in the operation of low–medium-speed maglev trains.
Lignin Gasification: Current and Future Viability
Authors: Castro Garcia Abraham , Cheng Shuo , Cross Jeffrey S.
Published: November 2022

The consumption of fossil fuels is one of the main drivers of climate change. Lignin derived from biomass is a carbon-neutral raw feedstock, and its conversion into fuels is gaining much attention. The gasification of biomass aims to transform heterogeneous feedstocks into syngas and heat that could be used for various purposes. Lignin is a biomass feedstock of special interest due to its particular properties and its ability to be obtained in abundant quantities as a side product from the paper pulp industry as well as the growing cellulosic ethanol industry. This review explores the existing works regarding lignin gasification from different perspectives and compares the results obtained with other existing thermochemical processes, in addition to providing a perspective on the long-term fate of gasification as a technology compared to other emerging technologies. The analysis indicates that while lignin gasification may grow in importance in the near future due to increased interest in hydrogen production, its potential in emerging applications indicates that lignin may be too valuable to be used purely for energy generation purposes, and applications that take advantage of its inherent chemical compounds are expected to take priority in the long-term.
Analysis of the Hybridization of PV Plants with a BESS for Annual Constant Power Operation
Authors: Bayod-Rújula Ángel A. , Tejero-Gómez Juan A.
Published: November 2022

The electrical generation of photovoltaic systems is variable and non-dispatchable. Energy storage systems can provide the system with energy management capabilities. In particular, with a hybrid system that combines a photovoltaic system and an energy storage system, it is possible to deliver firm power to the grid, if it is correctly dimensioned and operated. The objective of this work is to study the most appropriate relationship between the capacity of the battery energy storage system (BESS) and the peak power of the photovoltaic generator that enables the delivery of constant power throughout the year. Analysis parameters are presented that help to decide the most convenient energy injection constant value (PV-CPG set point) and the size of the storage system. As a case study, the most suitable battery capacity for a 1 MWp photovoltaic system with a battery located in Zaragoza (Spain), and the most convenient annual setpoint values for its operation are analyzed.
Research on Fault Early Warning of Wind Turbine Based on IPSO-DBN
Authors: Zhang Zhaoyan , Wang Shaoke , Wang Peiguang , Jiang Ping , Zhou Hang
Published: November 2022

Aiming at the problem of wind turbine generator fault early warning, a wind turbine fault early warning method based on nonlinear decreasing inertia weight and exponential change learning factor particle swarm optimization is proposed to optimize the deep belief network (DBN). With the data of wind farm supervisory control and data acquisition (SCADA) as input, the weights and biases of the network are pre-trained layer by layer. Then the BP neural network is used to fine-tune the parameters of the whole network. The improved particle swarm optimization algorithm (IPSO) is used to determine the number of neurons in the hidden layer of the model, pre-training learning rate, reverse fine-tuning learning rate, pre-training times and reverse fine-tuning training times and other parameters, and the DBN predictive regression model is established. The experimental results show that the proposed model has better performance in accuracy, training time and nonlinear fitting ability than the DBN model and PSO-DBN model.