bluuebunny/crossref_metadata_2025 huggingface dataset:
A Randomized Controlled Trial of the Safety and Efficacy of Systemic Enzyme Supplementation on Symptoms and Quality of Life in Patients with Idiopathic Pulmonary Fibrosis
Authors: Shah Neha
Published: July 2024

Idiopathic pulmonary fibrosis (IPF) imposes a substantial symptom burden that adversely impacts patients’ quality of life. Current anti-fibrotic treatments for IPF provide limited symptomatic relief, necessitating the implementation of complementary disease management strategies to enhance health-related quality of life (HRQOL). Serracor-NK® and Serra Rx260, systemic enzyme supplements, improved symptoms and HRQOL with favorable safety profiles in a proof-of-concept study in PF patients. This prospective, double-blind randomized placebo-controlled trial enrolled 100 IPF patients from six institutions. The supplement group (n = 50) received the oral systemic enzyme supplements Serracor-NK® and Serra Rx260 in addition to standard care for 6 months, while the placebo group (n = 50) received standard care alone. The primary objective was to evaluate the regimen’s impact on symptoms, QOL, and well-being using the UCSD shortness of breath (UCSD-SOB) questionnaire, St. George’s respiratory questionnaire (SGRQ), and WHO well-being index (WHO-5). Safety evaluation was a secondary objective. A significantly higher proportion of patients in the supplement group demonstrated meaningful improvement in symptoms as compared to the placebo group, as assessed by the UCSD-SOB (p < 0.05) and SGRQ questionnaires (p < 0.05). Additionally, a significantly greater proportion of patients in the supplement group showed improved QOL and well-being (p < 0.05) and reduced health impairment (p < 0.05), as assessed by SGRQ. Mental well-being (WHO-5) and physical activity (SGRQ activity domain) did not differ significantly between the groups. Safety assessments, including liver function tests and vital signs, indicated that the supplement regimen was well tolerated. To conclude, Serracor-NK® and Serra Rx260 alleviate symptoms and enhance HRQOL in IPF patients with a favorable safety profile (Clinical Trials Registry India registration number: CTRI/2020/05/025374).
Assessment of Food Masticatory Capability with Clear Aligners
Authors: Levrini Luca , Giannotta Nicola , Mastrapasqua Rodolfo Francesco , Farronato Davide , Maurino Vittorio , Deppieri Alessandro , Tasquier Federico , Saran Stefano
Published: July 2024

Nowadays, aligners represent a possible therapeutical approach that combines both esthetic and function in order to address dental malocclusion. However, they require a significant level of compliance from the patient. According to the manufacturer, at least 22 h of wearing a day is demanded to reach the optimal therapeutical level; hence, aligners can only be removed during meals. Patients’ compliance might increase and the duration of the treatment might decrease if they were allowed to eat with aligners on. The idea of patients keeping the aligners on during meals has been contemplated, not only to favor patients’ compliance but also treatment effectiveness. This study aims to assess the degree of chewing difficulty that aligners cause when eating certain kinds of food and the quantity of residue left. Material and Methods: A questionnaire titled “Questionnaire for the Assessment of Masticatory Function with Aligners” was administered using Google Forms to 240 patients in treatment with clear aligners. The survey was validated through the reliability test using the test–retest method. This method had a higher correlation coefficient of 0.9 across all items (with a cutoff of 0.8) with statistical significance, and an excellent internal correlation coefficient (α > 0.9). The statistical analysis performed consisted of descriptive analysis, frequencies, percentages, Pearson’s correlation test and Friedman’s test. Results: Pearson’s test showed a statistically significant correlation between all items except between meat or clams and yogurt or ice cream and with mozzarella or soft cheese regarding food chewing difficulties. Pearson’s test showed a statistically significant correlation between all items regarding food residues. A total of 69.2% of the cohort reported some movements of aligners during mastication. In total, 88.3% of them affirmed not to have perceived deformations or breakage of aligners during chewing. Furthermore, 79.2% of them declared that they would continue to eat if eating with aligners was proven to speed up treatment. Conclusions: Wearing clear aligners while chewing foods such as yogurt, ice cream, soft cheese, bread, rice, etc., can be possible and can help shorten the duration of orthodontic treatment, benefiting both the patient and the orthodontist. However, further research using qualitative methods is needed to understand the barriers and facilitators to chewing food with aligners.
Multi-UAVs Tracking Non-Cooperative Target Using Constrained Iterative Linear Quadratic Gaussian
Authors: Zhang Can , Wang Yidi , Zheng Wei
Published: July 2024

This study considers the problem of controlling multi-unmanned aerial vehicles (UAVs) to consistently track a non-cooperative ground target with uncertain motion in a hostile environment with obstacles. An active information acquisition (AIA) problem is formulated to minimize the uncertainty of the target tracking task. The uncertain motion of the target is represented as a Wiener process. First, we optimize the configuration of the UAV swarm considering the collision avoidance, horizontal field of view (HFOV), and communication radius to calculate the reference trajectories of the UAVs. Next, a novel algorithm called Constrained Iterative Linear Quadratic Gaussian (CILQG) is introduced to track the reference trajectory. The target’s state with uncertainty and the UAV state are described as beliefs. The CILQG algorithm utilizes the Unscented Transform to propagate the belief regarding the UAVs’ motions, while also accounting for the impact of navigation errors on the target tracking process. The estimation error of the target position of the proposed method is under 4 m, and the error of tracking the reference trajectories is under 3 m. The estimation error remains unchanged even in the presence of obstacles. Therefore, this approach effectively deals with the uncertainties involved and ensures accurate tracking of the target.
Bootstrap Approximation of Model Selection Probabilities for Multimodel Inference Frameworks
Authors: Dajles Andres , Cavanaugh Joseph
Published: July 2024

Most statistical modeling applications involve the consideration of a candidate collection of models based on various sets of explanatory variables. The candidate models may also differ in terms of the structural formulations for the systematic component and the posited probability distributions for the random component. A common practice is to use an information criterion to select a model from the collection that provides an optimal balance between fidelity to the data and parsimony. The analyst then typically proceeds as if the chosen model was the only model ever considered. However, such a practice fails to account for the variability inherent in the model selection process, which can lead to inappropriate inferential results and conclusions. In recent years, inferential methods have been proposed for multimodel frameworks that attempt to provide an appropriate accounting of modeling uncertainty. In the frequentist paradigm, such methods should ideally involve model selection probabilities, i.e., the relative frequencies of selection for each candidate model based on repeated sampling. Model selection probabilities can be conveniently approximated through bootstrapping. When the Akaike information criterion is employed, Akaike weights are also commonly used as a surrogate for selection probabilities. In this work, we show that the conventional bootstrap approach for approximating model selection probabilities is impacted by bias. We propose a simple correction to adjust for this bias. We also argue that Akaike weights do not provide adequate approximations for selection probabilities, although they do provide a crude gauge of model plausibility.
Enhanced Coexistence of Quantum Key Distribution and Classical Communication over Hollow-Core and Multi-Core Fibers
Authors: Kong Weiwen , Sun Yongmei , Dou Tianqi , Xie Yuheng , Li Zhenhua , Gao Yaoxian , Zhao Qi , Chen Na , Gao Wenpeng , Hao Yuanchen , Han Peizhe , Liu Yang , Tang Jianjun
Published: July 2024

In this paper, we investigate the impact of classical optical communications in quantum key distribution (QKD) over hollow-core fiber (HCF), multi-core fiber (MCF) and single-core fiber (SCF) and propose wavelength allocation schemes to enhance QKD performance. Firstly, we theoretically analyze noise interference in QKD over HCF, MCF and SCF, such as spontaneous Raman scattering (SpRS) and four-wave mixing (FWM). To mitigate these noise types and optimize QKD performance, we propose a joint noise suppression wavelength allocation (JSWA) scheme. FWM noise suppression wavelength allocation and Raman noise suppression wavelength allocation are also proposed for comparison. The JSWA scheme indicates a significant enhancement in extending the simultaneous transmission distance of classical signals and QKD, reaching approximately 100 km in HCF and 165 km in MCF under a classical power per channel of 10 dBm. Therefore, MCF offers a longer secure transmission distance compared with HCF when classical signals and QKD coexist in the C-band. However, when classical signals are in the C-band and QKD operates in the O-band, the performance of QKD in HCF surpasses that in MCF. This research establishes technical foundations for the design and deployment of QKD optical networks.
The Journey to Graduate School: An Exploration of First-Generation Latine Students’ Transmission of Knowledge to Capital
Authors: Carrasco Amanda
Published: July 2024

Graduate education often serves as an opportunity for Latine students to leverage their social, familial, and cultural capital as an avenue for increased economic prosperity. However, the journey to pursue a graduate education can be challenging as students often have to navigate multiple roles and identities that lead to feelings of guilt, separation, and stress. Therefore, this study expands our understanding of the familial role in Latine students’ development of graduate school aspirations through the following research question: how do first-generation Latine students (FGLSs) activate funds of knowledge within familial contexts and transmit them into capital as tools to develop their graduate school aspirations? Utilizing plática methodology and educational journey mapping, I explore how five FGLSs draw upon their funds of knowledge from familial contexts and activate it into linguistic, aspirational, and familial capital on their journey to graduate school. The findings highlight FGLSs’ motivations to attend graduate school with a focus on the activation of funds of knowledge from familial contexts to capital as primary contributors in their development of graduate school aspirations.
Professional Support in Teaching Mathematics through Guided Discovery: The Role of Agency on Multiple Levels
Authors: Juhász Péter , Szász Réka , Szűcs Gábor , Varga Eszter
Published: July 2024

The paper describes a case study of mentoring support provided to a novice mathematics teacher in using Guided Discovery in her classroom. The study used qualitative methods: thematic analysis of interviews and discussions. A central theme that emerged in the results was agency, and we observed that the high level of student and teacher agency in Guided Discovery results in the importance of teacher agency within and over the mentoring framework. We conclude that when supporting teachers in using Guided Discovery in their mathematics classrooms, teacher educators need to put an increased focus on teacher agency within and over the mentoring process.
A Non-Linear Successive Approximation Finite State Machine for ADCs with Robust Performance
Authors: Fuente-Cortes Gisela De La , Espinosa Flores-Verdad Guillermo , Díaz-Méndez Alejandro , Gonzalez-Diaz Victor R.
Published: July 2024

This work presents the detailed design of a Successive Approximation Analog to Digital Data Converter (SAR ADC) using bulk 180 nm CMOS IC technology. The focus of the study is on replacing the typical Successive Approximation Register array with a Finite State Machine. This converter features a fully differential and bipolar architecture, which leads to the logic SAR nonlinear behavior. A novel digital control logic mitigates the conversion errors through the conditions in the previous logic states. The logic scheme, in combination with a robust continuous comparator, demonstrates tolerance to Process, Voltage, and Temperature variations. The architecture does not include calibration or additional redundancies in post-layout simulations to emphasize the exclusive benefits of the new SAR logic. The proposed SAR ADC achieves a 14.07 effective number of bits with 7.04 fJ/conversion step Walden figure of merit in biomedical applications.
An Adjustable Parameter-Based Robust Distributed Fault Diagnosis for One-Sided Lipschitz Formation of Clustered Multi-Agent Systems
Authors: Barzegar Ailin , Rahimi Afshin
Published: July 2024

This paper addresses the challenge of distributed fault diagnosis in the context of the one-sided Lipschitz formation of agents. Each agent integrates an observer to detect and estimate both linear and non-linear faults in its attitude control subsystem. A robust design configuration is also developed to account for external perturbations. The robust observer utilized in this study is an unknown input observer (UIO), designed to mitigate the impact of disturbances on fault and state estimation errors. The observer’s parameters are determined using linear matrix inequalities (LMIs). Furthermore, a UIO incorporating an adjustable parameter (AP) is introduced to enhance fault diagnosis accuracy. Simulation results for two satellite clusters, consisting of five satellites with varying dynamics due to external disturbances, are presented to validate the approach. Instead of equipping every agent with an observer, specific agents can be equipped with observers to detect faults throughout the constellation, thereby reducing computational demands in configurations with numerous agents. Finally, a comparison is made between the proposed AP-based UIO and a standard UIO. The comparison findings reveal a noteworthy average of a substantial 56.61% reduction in root mean square error (RMSE) employing AP-based UIO compared to the utilization of standard robust UIO.
Trial of Brain–Computer Interface for Continuous Motion Using Electroencephalography and Electromyography
Authors: Saga Norihiko , Okawa Yukina , Saga Takuma , Satoh Toshiyuki , Saito Naoki
Published: July 2024

Most BCI systems used in neurorehabilitation detect EEG features indicating motor intent based on machine learning, focusing on repetitive movements, such as limb flexion and extension. These machine learning methods require large datasets and are time consuming, making them unsuitable for same-day rehabilitation training following EEG measurements. Therefore, we propose a BMI system based on fuzzy inference that bypasses the need for specific EEG features, introducing an algorithm that allows patients to progress from measurement to training within a few hours. Additionally, we explored the integration of electromyography (EMG) with conventional EEG-based motor intention estimation to capture continuous movements, which is essential for advanced motor function training, such as skill improvement. In this study, we developed an algorithm that detects the initial movement via EEG and switches to EMG for subsequent movements. This approach ensures real-time responsiveness and effective handling of continuous movements. Herein, we report the results of this study.
Technique for Kernel Matching Pursuit Based on Intuitionistic Fuzzy c-Means Clustering
Authors: Lei Yang , Zhang Minqing
Published: July 2024

Kernel matching pursuit (KMP) requires every step of the searching process to be global optimal searching in the redundant dictionary of functions in order to select the best matching signal structure. Namely, the dictionary learning time of KMP is too long. To solve the above drawbacks, a rough dataset was divided into some small-sized dictionaries to substitute local searching for global searching by using the property superiority of dynamic clustering performance, which is also superior in the intuitionistic fuzzy c-means (IFCM) algorithm. Then, we proposed a novel technique for KMP based on IFCM (IFCM-KMP). Subsequently, three tests including classification, effectiveness, and time complexity were carried out on four practical sample datasets, the conclusions of which fully demonstrate that the IFCM-KMP algorithm is superior to FCM and KMP.
Super-Resolution Image Reconstruction of Wavefront Coding Imaging System Based on Deep Learning Network
Authors: Li Xueyan , Yu Haowen , Wu Yijian , Zhang Lieshan , Chang Di , Chu Xuhong , Du Haoyuan
Published: July 2024

Wavefront Coding (WFC) is an innovative technique aimed at extending the depth of focus (DOF) of optics imaging systems. In digital imaging systems, super-resolution digital reconstruction close to the diffraction limit of optical systems has always been a hot research topic. With the design of a point spread function (PSF) generated by a suitably phase mask, WFC could also be used in super-resolution image reconstruction. In this paper, we use a deep learning network combined with WFC as a general framework for images reconstruction, and verify its possibility and effectiveness. Considering the blur and additive noise simultaneously, we proposed three super-resolution image reconstruction procedures utilizing convolutional neural networks (CNN) based on mean square error (MSE) loss, conditional Generative Adversarial Networks (CGAN), and Swin Transformer Networks (SwinIR) based on mean absolute error (MAE) loss. We verified their effectiveness by simulation experiments. A comparison of experimental results shows that the SwinIR deep residual network structure based on MAE loss optimization criteria can generate more realistic super-resolution images with more details. In addition, we used a WFC camera to obtain a resolution test target and real scene images for experiments. Using the resolution test target, we demonstrated that the spatial resolution could be improved from 55.6 lp/mm to 124 lp/mm by the proposed super-resolution reconstruction procedure. The reconstruction results show that the proposed deep learning network model is superior to the traditional method in reconstructing high-frequency details and effectively suppressing noise, with the resolution approaching the diffraction limit.
Effects of a Spike-Annealed HfO2 Gate Dielectric Layer on the On-Resistance and Interface Quality of AlGaN/GaN High-Electron-Mobility Transistors
Authors: Lee Gyuhyung , Yang Jeongyong , Yeom Min Jae , Yoon Sisung , Yoo Geonwook
Published: July 2024

Various high-k dielectrics have been proposed for AlGaN/GaN MOSHEMTs for gate leakage and drain-current collapse suppression. Hafnium oxide (HfO2) is particularly interesting because of its large bandgap, high dielectric constant, and ferroelectricity under specific phase and doping conditions. However, defects and surface scattering caused by HfO2 dissimilarity and degraded HfO2/GaN interface quality still leave the challenge of reducing the SS and Ron. In this study, we investigated the effects of the first spike-annealed HfO2 (6 nm) layer, compared with the conventional ALD-HfO2 (6 nm) layer in the HfO2 bilayer gate dielectric structure on AlGaN/GaN HEMTs. Both devices exhibit negligible hysteresis and near-ideal (~60 mV/dec) subthreshold slopes of more than three orders of magnitude. The device with the first annealed HfO2 layer exhibited a reduced Ron with notably less gate bias dependency and enhanced output current. On the other hand, the capacitance–voltage and conductance methods revealed that the border and interface trap densities of the device were inferior to those of the conventional HfO2 layer. The trade-off between enhanced electrical performance and oxide traps is discussed based on these results.
Audio Pre-Processing and Beamforming Implementation on Embedded Systems
Authors: Wang Jian-Hong , Le Phuong Thi , Kuo Shih-Jung , Tai Tzu-Chiang , Li Kuo-Chen , Chen Shih-Lun , Wang Ze-Yu , Pham Tuan , Li Yung-Hui , Wang Jia-Ching
Published: July 2024

Since the invention of the microphone by Barina in 1876, there have been numerous applications of audio processing, such as phonographs, broadcasting stations, and public address systems, which merely capture and amplify sound and play it back. Nowadays, audio processing involves analysis and noise-filtering techniques. There are various methods for noise filtering, each employing unique algorithms, but they all require two or more microphones for signal processing and analysis. For instance, on mobile phones, two microphones located in different positions are utilized for active noise cancellation (one for primary audio capture and the other for capturing ambient noise). However, a drawback is that when the sound source is distant, it may lead to poor audio capture. To capture sound from distant sources, alternative methods, like blind signal separation and beamforming, are necessary. This paper proposes employing a beamforming algorithm with two microphones to enhance speech and implementing this algorithm on an embedded system. However, prior to beamforming, it is imperative to accurately detect the direction of the sound source to process and analyze the audio from that direction.
Novel Fault Protection Method for Flexible DC Power Systems
Authors: Chen Genqi , Duan Qing , Zhao Caihong , Wang Haoqing , Sha Guanglin , Gao Jian , Li Yong , Zhou Shuiliang
Published: July 2024

A fault protection method is proposed for flexible direct-current (DC) power systems based on the cosine similarity of currents in current-limiting reactors. The typical characteristics of external and internal faults in a flexible DC power system were analyzed. The principles of cosine similarity and the fault current characteristics of current-limiting reactors were used to distinguish between internal and external faults. The ratio of the average positive and negative voltages of the current-limiting reactor was then used to distinguish the fault types and fault line. Finally, a simulation model of a circular flexible DC power system was constructed using MATLAB/Simulink software (2018b). The simulation results show that the proposed protection scheme can quickly and accurately identify the location and type of faults, and has a strong ability to withstand fault resistance and is less affected by distributed capacitance, noise, and communication delay.
Wind Farms’ Location and Geographical Proximity as a Key Factor in Sustainable City Development: Evidence from Poland
Authors: Zarębski Patrycjusz , Katarzyński Dominik , Godlewska-Majkowska Hanna , Komor Agnieszka , Gawryluk Adam
Published: July 2024

In this study, the potential impact of wind farm locations on the sustainable development of cities in Poland was evaluated, considering the availability of wind-generated electricity. We analyzed 37 cities in Poland with populations over 100,000. Research indicates that wind farms located 30–80 km from large cities perform best in terms of generating capacity, while greater distances increase transmission costs and energy losses. In Poland, wind farms are primarily situated in the northwestern regions, posing challenges for energy transmission to the southern cities, which are the main centers of energy consumption. The findings show that wind farms with the highest generating capacity are generally about 50 km from major cities. Key factors influencing wind farm locations include technical criteria, economic feasibility, environmental impact, public opinion, and the availability of transmission networks. Sustainable development of wind farms requires strategic cooperation between urban and rural municipalities, joint spatial planning, coordinated land acquisition, and the exchange of know-how.
The Impact of Various Factors on Long-Term Storage of Biodiesel and Its Prevention: A Review
Authors: Ai Wenbo , Cho Haeng Muk , Mahmud Md. Iqbal
Published: July 2024

With the continuous growth of global energy demand and increasingly prominent environmental issues, the research and utilization of renewable energy as a substitute for traditional fossil fuels have gained significant importance. Biofuels, recognized as a key renewable energy source, are widely considered a viable alternative to fossil fuels. The primary component of biodiesel is fatty acid methyl esters (FAMEs), which are prone to oxidative degradation due to their unsaturated nature during storage and transportation. Various studies have identified several factors influencing the stability of biodiesel, including oxygen, temperature, light, water content, microbial growth, and the corrosion of metal storage tanks. This article provides a comprehensive summary of the effects of different environmental factors on the storage stability of biodiesel and explores the interrelationships between these factors. To enhance the storage stability of biodiesel, several strategies have been proposed, such as optimizing production processes, adding antioxidants, controlling storage environments, and conducting regular inspections. This review aims to provide a theoretical basis for the long-term storage of biodiesel and promote its widespread application in practical scenarios.
Conditions of Decision-Making Related to Implementation of Hydrogen-Powered Vehicles in Urban Transport: Case Study of Poland
Authors: Filina-Dawidowicz Ludmiła , Sęk Joanna , Trojanowski Piotr , Wiktorowska-Jasik Anna
Published: July 2024

The changes in geopolitical and ecological conditions brought about the need to use environmentally friendly sources of vehicle power. This impacted the accelerated activities related to the use of hydrogen fuel in transport means. Based on the observations carried out in the countries of Central and Eastern Europe, it was found that the process of implementing hydrogen-powered vehicles in public transport is connected with difficulties faced by transport companies with regard to the purchase of these transport means. This study aims to analyse the conditions for making decisions regarding the implementation of hydrogen-powered buses in urban transport. A case study was considered, and the factors influencing the decisions related to the application of hydrogen-powered buses in Poland were analysed. The survey method was used to carry out the research. A questionnaire was developed, and the survey was conducted among representatives of transport companies that provide public transport services in Polish cities. As a result of the research, it was found that city authorities play a key role in deciding on the implementation of hydrogen-powered buses. The highest ranks among the proposed criteria influencing the decision on the purchase of hydrogen-powered buses were the economic ones. The concerns and benefits resulting from the potential purchase of hydrogen-powered buses were also examined. It was revealed that the decision to buy buses is most influenced by factors such as ensuring access to hydrogen and its price. The recommendations for transport companies and city authorities were formulated.
Joint Component Estimation for Electricity Price Forecasting Using Functional Models
Authors: Lisi Francesco , Shah Ismail
Published: July 2024

This work considers the issue of modeling and forecasting electricity prices within the functional time series approach. As this is often performed by estimating and predicting the different components of the price dynamics, we study whether jointly modeling the components, able to account for their inter-relations, could improve prediction with respect to a separate instance of modeling. To investigate this issue, we consider and compare the predictive performance of four different predictors. The first two, namely Smoothing Splines-Seasonal Autoregressive (SS-SAR) and Smoothing Splines-Functional Autoregressive (SS-FAR) are based on separate modeling while the third one is derived from a single-step procedure that jointly estimates all the components by suitably including exogenous variables. It is called Functional Autoregressive with eXogenous variables (FARX) model. The fourth one is a combination of the SS-FAR and FARX predictors. The predictive performances of the models are tested using electricity price data from the northern zone of the Italian electricity market (IPEX), both in terms of forecasting error indicators (MAE, MAPE and RMSE) and by means of the Diebold and Mariano test. The results point out that jointly estimating the components leads to significantly more accurate predictions than using a separate instance of modeling. In particular, the MAE, MAPE, and RMSE values for the best predictor, based on the FARX(3,0,4) model, are 4.25, 9.28, and 5.38, respectively. The percentage error reduction is about 20% with respect to SS-SAR(3,1) and about 10% with respect to SS-FAR(5). Finally, this study suggests that the forecasting errors are generally higher on Sunday and Monday, from hours 3 to 6 in the morning and 14 to 15 in the afternoon, and in June and December. On the other hand, prices are relatively lower on Wednesday, Thursday, and Friday, from hour 20 to 1 a.m., and in January and February.
Price Risk Exposure of Small Participants in Liberalized Multi-National Power Markets: A Case Study on the Belize–Mexico Interconnection
Authors: Usher Khadija Sherece , McLellan Benjamin Craig
Published: July 2024

This study examined the price risk of the Belize–Mexico interconnection using ARMA-ARCH models to assess electricity pricing volatility and autoregression to determine the influence of conditional volatilities and import consumption. The findings revealed that the volatility of both markets, especially spot price, showed rare high-impact shocks and prolonged periods of volatile clusters. Volatile pricing tendencies, and forward pricing to a lesser extent, had positive effects on premiums. Premiums were largely dependent on pricing properties and system conditions of the supplier’s (Mexico) side, with negligible influence from the buyer’s (Belize) side. However, significant effects were found during certain hours with the buyer’s loading and transmission loss patterns. Practical implications revealed the possibility of occasional losses caused mostly by information delays and misalignment of risk factors and premiums, which could affect Belize’s power cost affordability and scheduling of local generation. Further research can broaden this current scope to enhance planning on local power supply by integrating current findings on the importation market behavior with the buyer’s local power expansion plan.
The Trend in Environmental Load in the European Union during the Period of 2012–2022
Authors: Török László
Published: July 2024

The environmental burden is a global problem affecting the European Union. A comprehensive analysis of the environmental burden is essential for creating strategies supporting sustainable economic development. This study attempts to answer the question of why, despite the continuously decreasing energy consumption of the EU, the environmental burden of this region is not substantially decreasing. This study provides novel insights into this research area by integrating EU economic dynamics and environmental efficiency indicators. In this study, we used the IPAT method. Before the main analysis, the researcher conducted cross-sectional dependence, slope heterogeneity, and Westerlund cointegration tests using the primary data. Based on the results, the EU member states were classified into clusters, and a linear trend model analysis was carried out. The results show that the total environmental load of the EU did not decrease significantly between 2012 and 2022. The fact that the environmental burden remained at the same level is explained by the fact that there were 16 member countries whose total environmental load increased but whose economic output was lower during this time period. This was offset by 11 member countries with high economic outputs, whose total environmental load decreased. This study proved that GDP growth was the main driving force maintaining the total environmental load at the same level. The EU should encourage member states to continue to implement environmental protection rules to limit and eliminate costly environmental burdens on their societies and economies. This study can be helpful to researchers, political decision-makers, and experts working on environmental public policies for the EU.
Novel Frequency Regulation Scenarios Generation Method Serving for Battery Energy Storage System Participating in PJM Market
Authors: Zhang Yichao , Anvari-Moghaddam Amjad , Peyghami Saeed , Blaabjerg Frede
Published: July 2024

As one of the largest frequency regulation markets, the Pennsylvania-New Jersey-Maryland Interconnection (PJM) market allows extensive access of Battery Energy Storage Systems (BESSs). The designed signal regulation D (RegD) is friendly for use with BESSs with a fast ramp rate but limited energy. Designing operating strategies and optimizing the sizing of BESSs in this market are significantly influenced by the regulation signal. To represent the inherent randomness of the RegD signal and reduce the computational burden, typical frequency regulation scenarios with lower resolution are often generated. However, due to the rapid changes and energy neutrality of the RegD signal, generating accurate and representative scenarios presents challenges for the methods based on shape similarity. This paper proposes a novel probability-based method for generating typical regulation scenarios. The method relies on the joint probability distribution of two features with a 15-min resolution, extracted from the RegD signal with a 2 s resolution. The two features can effectively portray the characteristic of RegD signal and its influence on BESS operation. Multiple regulation scenarios are generated based on the joint probability distributions of these features at first, with the final typical scenarios chosen based on their probability distribution similarity to the actual distribution. Utilizing regulation data from the PJM market in 2020, this paper validates and analyzes the performance of the generated typical scenarios in comparison to existing methods, specifically K-means clustering and the forward scenarios reduction method.
Advancing Renewable Energy Forecasting: A Comprehensive Review of Renewable Energy Forecasting Methods
Authors: Teixeira Rita , Cerveira Adelaide , Pires Eduardo J. Solteiro , Baptista José
Published: July 2024

Socioeconomic growth and population increase are driving a constant global demand for energy. Renewable energy is emerging as a leading solution to minimise the use of fossil fuels. However, renewable resources are characterised by significant intermittency and unpredictability, which impact their energy production and integration into the power grid. Forecasting models are increasingly being developed to address these challenges and have become crucial as renewable energy sources are integrated in energy systems. In this paper, a comparative analysis of forecasting methods for renewable energy production is developed, focusing on photovoltaic and wind power. A review of state-of-the-art techniques is conducted to synthesise and categorise different forecasting models, taking into account climatic variables, optimisation algorithms, pre-processing techniques, and various forecasting horizons. By integrating diverse techniques such as optimisation algorithms and pre-processing methods and carefully selecting the forecast horizon, it is possible to highlight the accuracy and stability of forecasts. Overall, the ongoing development and refinement of forecasting methods are crucial to achieve a sustainable and reliable energy future.
Regional Interferences to Photovoltaic Development: A Polish Perspective
Authors: Kocur-Bera Katarzyna
Published: July 2024

The stability of energy generation is crucial for the functioning of every country. Currently, the EU policy is moving towards becoming independent of fossil energy sources, which can be replaced with sources that are not exhaustible, for example, energy from the sun. Public awareness of renewable energy is increasing. People are willing to invest in natural solutions. However, planning large photovoltaic farm projects is difficult due to complex location requirements. The study aimed to analyse the interferences/barriers to be considered when searching for a suitable location to install a photovoltaic farm. The analysis was conducted for the territory of Poland. The study used a literature and local legislation query and the Delphi method. The Delphi method identified the most important interferences from the investor’s perspective. Eleven interferences have been identified, classified into legal, spatial, technical, social, and financial groups. Several are locally determined and only exist in selected locations (e.g., technical determinants of the power grid condition, etc.). In contrast, others are unitary (e.g., concerns about the impact of PV on human health, etc.). The decision-makers are aware of the existing interferences/barriers, and the proposed administrative, legal, and technical solutions marginally mitigate barriers. System solutions are recommended, allowing an easier way to find a suitable location for a PV system.
Influence of Hydrothermal Carbonization (HTC) Temperature on Hydrochar and Process Liquid for Poultry, Swine, and Dairy Manure
Authors: Devnath Bilash , Khanal Sami , Shah Ajay , Reza Toufiq
Published: July 2024

Hydrothermal carbonization (HTC) is a promising technology for wet manure treatment by converting animal manure into valuable fuels, materials, and chemicals. Among other HTC process parameters, the temperature influences HTC products the most. As various animal manures have different compositions, it is not certain how the HTC temperature influences the hydrochar and HTC process liquid. To evaluate the temperature’s effect on HTC, three different manures (poultry, swine, and dairy) were hydrothermally carbonized at three different temperatures (180, 220, and 260 °C), and solid and liquid products were characterized for their morphology, elemental compositions, and ions. The carbon contents of the hydrochar reached as high as 38.98 ± 0.36% and 40.05 ± 0.57% for poultry and swine manure, respectively, when these manures were treated at 260 °C. Ammonium showed an around 30% increase in poultry manure hydrochar with the increase in the HTC temperature. In contrast, in swine manure, it decreased by around 80%, and in dairy manure, the HTC temperature did not have any remarkable effect on the ammonium content. The process liquids from HTC of dairy manure at 220 °C showed the most balanced distribution of different ions, with 4970 ± 673 ppm of sodium, 4354 ± 437 ppm of ammonium, 2766 ± 417 ppm of potassium, 978 ± 82 ppm of magnesium, 953 ± 143 ppm of calcium, 3607 ± 16 ppm of chloride, and 39 ± 7 ppm of phosphate. These results emphasize the manure-specific effects of the HTC temperature on both solid and liquid products, indicating the need for optimized strategies to enhance HTC processes for various types of animal manures.
DNA Methylation as Drug Sensitivity Marker in RCC: A Systematic Review
Authors: Koudonas Antonios , Dimitriadis Georgios , Anastasiadis Anastasios , Papaioannou Maria
Published: July 2024

Patient response after treatment of renal cell cancer (RCC) with systemic agents, which include various drug categories, is generally poor and unpredictable. In this context, the ideal drug administration includes tools to predict the sensitivity of the disease to therapy. The aim of this study was to systematically summarize the reports on the predictive value of the methylation status in the systemic therapy of RCC. Only original articles reporting on the association of promoter methylation with the response of patients or cell lines to systemic agents were included in this review. We applied PRISMA recommendations to the structure and methodology of this systematic review. Our literature search concluded with 31 articles conducted on RCC cell lines and patient tissues. The majority of the studies demonstrated a methylation-dependent response to systemic agents. This correlation suggests that the methylation pattern can be used as a predictive tool in the management of RCC with various classes of systemic agents. However, although methylation biomarkers show promise for predicting response, the evidence of such correlation is still weak. More studies on the gene methylation pattern in patients under systemic therapy and its correlation with different degrees of response are needed.
Functional Diversity of Soil Microorganisms in Taiga Forests in the Middle and Late Stages of Restoration after Forest Fires
Authors: Cheng Zhichao , Gao Mingliang , Pan Hong , Fu Xiaoyu , Wei Dan , Lu Xinming , Wu Song , Yang Libin
Published: July 2024

Fire can significantly affect the structure and function of forest soil microorganisms. Therefore, it is important to study the effects of different fire intensities on soil microbial carbon source utilization capacity in cold-temperate larch forests to protect and utilize forest ecosystems. In this study, we investigated the effects of different burning intensities on the carbon utilization capacity of soil microorganisms in fire sites from 2010 and 2000 using Biolog-Eco technology. Our findings revealed that (1) fire significantly increased soil pH, AN (available nitrogen), and AK (available potassium) (p < 0.05); (2) fire significantly increased the average color change rate (AWCD) of soil microorganisms (p < 0.05); (3) the Shannon index of soil microorganisms increased significantly, whereas the Simpson index and the McIntosh index decreased significantly after the fire—however, the McIntosh index in the 10M site was not altered; (4) the metabolic functions of soil microbial communities differed significantly among different fire intensities—MC (moisture content), TN (total nitrogen), and AK were the most influential soil environmental factors in the soil microbial community; and (5) mid-term fire restoration significantly increased microbial responses to carbohydrates, amino acids, esters, alcohols, amines, and acids, while late-fire burn sites significantly increased the microbial utilization intensity of amino acids, esters, and acids. In conclusion, fire significantly altered the functional diversity of soil microorganisms and microbial activities related to carbon source substrate utilization. Additionally, the ability of microorganisms to utilize a single carbon source substrate was also altered.
Studying the Impact of Heat Treatments and Distance from Pith on the Sorption Behavior of Tree of Heaven Wood (Ailanthus altissima (Mill.) Swingle)
Authors: Fodor Fanni , Emmerich Lukas , Horváth Norbert , Németh Róbert , Hofmann Tamás
Published: July 2024

The application of tree of heaven (Ailanthus altissima (Mill.) Swingle) is constrained by its poor durability and dimensional stability. Despite exhibiting promising physical and mechanical properties comparable to ash wood (Fraxinus excelsior L.), it is regarded as an invasive species and receives limited attention in wood property enhancement research. This study subjected tree of heaven to heat treatment at 180 °C and 200 °C to investigate its sorption characteristics using dynamic vapor sorption tests. The results revealed a 13% reduction in equilibrium moisture content at 95% relative humidity and 25 °C after thermal modification at 180 °C and a 25% reduction after thermal modification at 200 °C. Increasing the treatment temperature lowered the moisture content ratio to 0.76 and shortened the conditioning time by up to 10%. The highest hysteresis, ranging from 3.39% to 3.88%, was observed at 70% relative humidity.
Predicting the Future Distribution and Habitat Suitability of Ilex latifolia Thunb. in China under Climate Change Scenarios
Authors: Ma Yunyang , Liu Ying , Xiang Yangzhou , He Ji , Zhao Ling , Guo Xinzhao
Published: July 2024

Ilex latifolia Thunb., a plant of significant economic and medicinal value, is both edible and medicinal. Assessing the climate suitability for I. latifolia has profound implications for advancing medical progress and enhancing the quality of human life. This study comprehensively utilized data on the field distribution of I. Latifolia, as well as corresponding climatic, topographical, and soil data at these distribution points, with the aid of future climate data predicted by global climate models, and employed the MaxEnt model to predict and analyze the climate suitability areas of I. latifolia under three greenhouse gas emission scenarios (SSP126, SSP245, and SSP585). The research covers the spatiotemporal distribution characteristics, suitable growth range, and influencing factors from the present to the end of the 21st century (2041–2100). The predictive results of the MaxEnt model indicate that, under current climatic conditions, the main suitable growth areas for I. latifolia are concentrated in the southeastern part of China, especially in the provinces of Fujian and Zhejiang. However, facing the challenges of future climate change, it is expected that the moderately high suitable growth areas for I. latifolia will show a trend of gradual reduction. The primary climatic factors crucial for I. latifolia’s growth are annual precipitation (1469.05 to 4499.50 mm), the lowest temperature in the coldest month (−18.72 to 3.88 °C), seasonal precipitation changes (11.94 to 64.69 mm), and topographic slope (0.37 to 3.00°), with annual precipitation being the most influential. The findings of this study provide a scientific basis for the introduction of I. latifolia and offer important reference information for the artificial cultivation, resource development, and achievement of sustainable industrial development of this species.
Analysis of the Environments Where Natural Regeneration Is Established in the Absence of a Wildfire in the Open Pinus brutia Forests in the Middle Elevations of the Central Part of Cyprus
Authors: Petrou Petros , Stampoulidis Athanasios , Pipinis Elias , Kitikidou Kyriaki , Milios Elias
Published: July 2024

The objective of this research was to analyze the P. brutia natural regeneration and the environments where it was established in the absence of a wildfire in the open formations of the species in the middle elevations of the central part of Cyprus. Forty-eight rectangular plots of 0.1 ha were established in three site productivity types. Individuals of the species with a height from 0.1 m to 1.5 m were considered regeneration plants. Within each plot, various measurements and estimations were made. Moreover, 480 hemispherical photographs were taken. Additionally, hemispherical photographs were taken above each of the recorded naturally regenerated P. brutia plants. In all the site productivity types, the most regeneration plants were established and grew under the process of facilitation. In each of the site productivity types, there were no differences in the light condition diversity between the environments where the regeneration plants grew and the existing light conditions. Regeneration exhibited a small number of plants and constituted only a very small proportion of all trees in the three site productivity types. To achieve sustainability in P. brutia forests, forest practices must develop strategies for the enhancement of P. brutia regeneration in the studied area and in analogous environments.