bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of Contrast-Enhanced Ultrasonography in Hepatocellular Carcinoma by Using LI-RADS and Ancillary Features: A Single Tertiary Centre Experience
Authors: Ciocalteu Adriana , Iordache Sevastita , Cazacu Sergiu Marian , Urhut Cristiana Marinela , Sandulescu Sarmis Marian , Ciurea Ana-Maria , Saftoiu Adrian , Sandulescu Larisa Daniela
Published: November 2021

Clinical utility of ancillary features (AFs) in contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS®) is yet to be established. In this study, we assessed the diagnostic yield of CEUS LI-RADS and AFs in hepatocellular carcinoma (HCC). We retrospectively included patients with risk factors for HCC and newly diagnosed focal liver lesions (FLL). All lesions have been categorized according to the CEUS LI-RADS v2017 by an experienced sonographer blinded to clinical data and to the final diagnosis. From a total of 143 patients with 191 FLL, AFs favoring HCC were observed in 19.8% cases as hypoechoic rim and in 16.7% cases as nodule-in nodule architecture. From the total of 141 HCC cases, 83.6% were correctly classified: 57.4%- LR-5 and 26.2%- LR-4. In 9.21% cases, CEUS indicated LR-M; 2.12% cases- LR-3. The LR-5 category was 96.2% predictive (PPV) of HCC. LR-5 had 60.4% sensitivity and 93.6% specificity. PPV for primitive malignancy (LR-4 + LR-5) was 95.7%, with 88% sensitivity, 89.3% specificity and 88.4% accuracy for HCC. LR-4 category had 94.8% PPV and 26.2% sensitivity. CEUS LR4 + LR5 had 81,8% sensitivity for HCCs over 2 cm and 78.57% sensitivity for smaller HCCs. CEUS LR-5 remains an excellent diagnostic tool for HCC, despite the size of the lesion. The use of AFs might improve the overarching goal of LR-5 + LR-4 diagnosis of high specificity for HCC and exclusion of non-HCC malignancy.
Assessing Liver Fibrosis Using the FIB4 Index in the Community Setting
Authors: Blanco-Grau Albert , Gabriel-Medina Pablo , Rodriguez-Algarra Francisco , Villena Yolanda , Lopez-Martínez Rosa , Augustín Salvador , Pons Mònica , Cruz Luz-Maria , Rando-Segura Ariadna , Enfedaque Belen , Riveiro Mar , Casis Ernesto , Ferrer-Costa Roser , Buti Maria , Rodriguez-Frias Francisco
Published: November 2021

Liver disease is frequently asymptomatic, challenging early identification in the primary care setting. The fibrosis 4 (FIB4) index is a liver fibrosis biomarker that is a potential alternative to liver biopsy for diagnosing and managing liver disease. This study aimed to calculate the FIB4 index for screening individuals at high risk of liver disease at the community level. This was a retrospective real-world study analyzing blood and serum test results from a central laboratory. The primary outcome was the number of individuals within each risk category for hepatic fibrosis: high risk (FIB4 ≥ 3.25) and low risk (FIB4 < 1.3). The analysis included samples from 31,753 patients, of which 18,102 were aged 40 to 75 years. In these patients, the FIB4 index had been explicitly requested in 1852 (10.2%) cases and estimated ad hoc in the rest. Of the 263 (1.5%) cases with FIB4 ≥ 3.25, the FIB4 index was requested in 46 (17.5%), and 52 (19.8%) showed evidence of liver fibrosis in their medical records, while the rest did not report any data regarding liver fibrosis. FIB4 is a simple score that can play a role as a “red flag” for early identification of patients at high risk of advanced liver fibrosis and their referral to specialized care.
Adjunctive Effect of Green Tea Mouthwash Prepared at Different Steeping Temperatures on Gingivitis: A Triple-Blind Randomized Controlled Clinical Trial
Authors: Fadel Hani T. , AlRehaili Alhanouf M. , AlShanqiti Mona M. , Alraddadi Afnan A. , Albolowi Alhanouf M.
Published: December 2021

Purpose: To compare the effect of green tea mouthwashes prepared at different steeping temperatures as adjuncts to mechanical plaque control on gingivitis. Methods: Forty-five women with gingivitis participated in this 4-week randomized controlled clinical trial. They received professional mechanical plaque control and rinsed daily with either warm green tea, hot–cold green tea or placebo. Dental plaque control record (PCR) and gingival bleeding indices (GBI) were recorded at baseline and 7, 14 and 28 days after. Results: Participants’ mean age was 20.7 ± 2 years. The mean scores for the PCR and GBI at baseline were 82.4 ± 19 and 85.8 ± 7, respectively. All groups showed significant reduction in PCR and GBI between Days 0 and 28 (p < 0.01). No significant differences in PCR were observed between the groups at any of the examinations (p > 0.01). The warm green tea group demonstrated significantly lower GBI at all examinations compared to the hot–cold group (p < 0.01). Conclusions: Within study limits, green tea-made mouthwashes significantly reduced plaque and gingivitis when used as adjuncts to mechanical plaque control. The green tea mouthwash prepared in warm water demonstrated significantly higher efficacy in lowering gingivitis compared to that prepared in hot water followed by ice.
Antibacterial Activities of Methanol and Aqueous Extracts of Salvadora persica against Streptococcus mutans Biofilms: An In Vitro Study
Authors: Balhaddad Abdulrahman A. , Mokeem Lamia , Melo Mary Anne S. , Gregory Richard L.
Published: December 2021

The use of herbal products in oral hygiene care has a long history, and their use is popular today. A tree stick, named Salvadora persica (S. persica), is commonly used to remove dental plaque and clean teeth in many countries. In addition, extracts of S. persica can be used as a mouthwash, as they demonstrate antimicrobial properties. This study aimed to investigate the antibacterial effect of S. persica methanol and aqueous extracts against Streptococcus mutans (S. mutans) biofilm. A S. mutans biofilm formation assay was conducted using different concentrations of S. persica methanol or water extracts in tryptic soy broth (TSB) supplemented with 1% sucrose. The biofilm was stained with crystal violet dye, and the absorbance was assessed to examine biofilm formation. One-way analysis of variance (ANOVA) and Tukey tests were used to analyze the results. The S. persica methanol extract displayed a significant inhibition (p ≤ 0.001) against the S. mutans biofilm. The 10 mg/mL concentration of the S. persica methanol extract was determined as the minimum biofilm inhibitory concentration (MBIC). The used methanol concentration, mixed with TSB supplemented with 1% sucrose and without the S. persica extract, did not inhibit the S. mutans biofilm. The S. persica aqueous extract did not demonstrate any biofilm inhibition at any concentration (p ≥ 0.05). The findings of this study suggest the potential of using S. persica methanol extract as a mouthwash or adjunctive to oral hygiene tools.
A Hybrid Preaching Optimization Algorithm Based on Kapur Entropy for Multilevel Thresholding Color Image Segmentation
Authors: Wu Bowen , Zhu Liangkuan , Cao Jun , Wang Jingyu
Published: November 2021

Multilevel thresholding segmentation of color images plays an important role in many fields. The pivotal procedure of this technique is determining the specific threshold of the images. In this paper, a hybrid preaching optimization algorithm (HPOA) for color image segmentation is proposed. Firstly, the evolutionary state strategy is adopted to evaluate the evolutionary factors in each iteration. With the introduction of the evolutionary state, the proposed algorithm has more balanced exploration-exploitation compared with the original POA. Secondly, in order to prevent premature convergence, a randomly occurring time-delay is introduced into HPOA in a distributed manner. The expression of the time-delay is inspired by particle swarm optimization and reflects the history of previous personal optimum and global optimum. To better verify the effectiveness of the proposed method, eight well-known benchmark functions are employed to evaluate HPOA. In the interim, seven state-of-the-art algorithms are utilized to compare with HPOA in the terms of accuracy, convergence, and statistical analysis. On this basis, an excellent multilevel thresholding image segmentation method is proposed in this paper. Finally, to further illustrate the potential, experiments are respectively conducted on three different groups of Berkeley images. The quality of a segmented image is evaluated by an array of metrics including feature similarity index (FSIM), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and Kapur entropy values. The experimental results reveal that the proposed method significantly outperforms other algorithms and has remarkable and promising performance for multilevel thresholding color image segmentation.
New Pythagorean Entropy Measure with Application in Multi-Criteria Decision Analysis
Authors: Gandotra Neeraj , Kizielewicz Bartłomiej , Anand Abhimanyu , Bączkiewicz Aleksandra , Shekhovtsov Andrii , Wątróbski Jarosław , Rezaei Akbar , Sałabun Wojciech
Published: November 2021

The purpose of this paper is to propose a new Pythagorean fuzzy entropy for Pythagorean fuzzy sets, which is a continuation of the Pythagorean fuzzy entropy of intuitionistic sets. The Pythagorean fuzzy set continues the intuitionistic fuzzy set with the additional advantage that it is well equipped to overcome its imperfections. Its entropy determines the quantity of information in the Pythagorean fuzzy set. Thus, the proposed entropy provides a new flexible tool that is particularly useful in complex multi-criteria problems where uncertain data and inaccurate information are considered. The performance of the introduced method is illustrated in a real-life case study, including a multi-criteria company selection problem. In this example, we provide a numerical illustration to distinguish the entropy measure proposed from some existing entropies used for Pythagorean fuzzy sets and intuitionistic fuzzy sets. Statistical illustrations show that the proposed entropy measures are reliable for demonstrating the degree of fuzziness of both Pythagorean fuzzy set (PFS) and intuitionistic fuzzy sets (IFS). In addition, a multi-criteria decision-making method complex proportional assessment (COPRAS) was also proposed with weights calculated based on the proposed new entropy measure. Finally, to validate the reliability of the results obtained using the proposed entropy, a comparative analysis was performed with a set of carefully selected reference methods containing other generally used entropy measurement methods. The illustrated numerical example proves that the calculation results of the proposed new method are similar to those of several other up-to-date methods.
Minimum Message Length in Hybrid ARMA and LSTM Model Forecasting
Authors: Fang Zheng , Dowe David L. , Peiris Shelton , Rosadi Dedi
Published: November 2021

Modeling and analysis of time series are important in applications including economics, engineering, environmental science and social science. Selecting the best time series model with accurate parameters in forecasting is a challenging objective for scientists and academic researchers. Hybrid models combining neural networks and traditional Autoregressive Moving Average (ARMA) models are being used to improve the accuracy of modeling and forecasting time series. Most of the existing time series models are selected by information-theoretic approaches, such as AIC, BIC, and HQ. This paper revisits a model selection technique based on Minimum Message Length (MML) and investigates its use in hybrid time series analysis. MML is a Bayesian information-theoretic approach and has been used in selecting the best ARMA model. We utilize the long short-term memory (LSTM) approach to construct a hybrid ARMA-LSTM model and show that MML performs better than AIC, BIC, and HQ in selecting the model—both in the traditional ARMA models (without LSTM) and with hybrid ARMA-LSTM models. These results held on simulated data and both real-world datasets that we considered.We also develop a simple MML ARIMA model.
Quantum–Classical Correspondence Principle for Heat Distribution in Quantum Brownian Motion
Authors: Chen Jin-Fu , Qiu Tian , Quan Hai-Tao
Published: November 2021

Quantum Brownian motion, described by the Caldeira–Leggett model, brings insights to the understanding of phenomena and essence of quantum thermodynamics, especially the quantum work and heat associated with their classical counterparts. By employing the phase-space formulation approach, we study the heat distribution of a relaxation process in the quantum Brownian motion model. The analytical result of the characteristic function of heat is obtained at any relaxation time with an arbitrary friction coefficient. By taking the classical limit, such a result approaches the heat distribution of the classical Brownian motion described by the Langevin equation, indicating the quantum–classical correspondence principle for heat distribution. We also demonstrate that the fluctuating heat at any relaxation time satisfies the exchange fluctuation theorem of heat and its long-time limit reflects the complete thermalization of the system. Our research study justifies the definition of the quantum fluctuating heat via two-point measurements.
Kolmogorov Basic Graphs and Their Application in Network Complexity Analysis
Authors: Farzaneh Amirmohammad , Coon Justin P. , Badiu Mihai-Alin
Published: November 2021

Throughout the years, measuring the complexity of networks and graphs has been of great interest to scientists. The Kolmogorov complexity is known as one of the most important tools to measure the complexity of an object. We formalized a method to calculate an upper bound for the Kolmogorov complexity of graphs and networks. Firstly, the most simple graphs possible, those with O(1) Kolmogorov complexity, were identified. These graphs were then used to develop a method to estimate the complexity of a given graph. The proposed method utilizes the simple structures within a graph to capture its non-randomness. This method is able to capture features that make a network closer to the more non-random end of the spectrum. The resulting algorithm takes a graph as an input and outputs an upper bound to its Kolmogorov complexity. This could be applicable in, for example evaluating the performances of graph compression methods.
Increasing Quantum Correlations Based on Measurement-Induced Disturbance via a Swapping Procedure with Two-Qubit Mixed States
Authors: Xie Chuanmei , Wu Feiyang , Zhang Zhanjun , Liang Jiawei , Yin Xiaofeng
Published: November 2021

In this paper, quantum correlation (QC) swapping for certain separable two-qubit mixed states is treated. A QC quantifier, measurement-induced disturbance (MID) (Luo in Phys Rev A 77:022301, 2008), is employed to characterize and quantify QCs in the relevant states. Properties of all QCs in the swapping process are revealed. Particularly, it is found that MID can be increased through QC swapping for certain separable two-qubit mixed states.
Generalizing Boltzmann Configurational Entropy to Surfaces, Point Patterns and Landscape Mosaics
Authors: Cushman Samuel A.
Published: December 2021

Several methods have been recently proposed to calculate configurational entropy, based on Boltzmann entropy. Some of these methods appear to be fully thermodynamically consistent in their application to landscape patch mosaics, but none have been shown to be fully generalizable to all kinds of landscape patterns, such as point patterns, surfaces, and patch mosaics. The goal of this paper is to evaluate if the direct application of the Boltzmann relation is fully generalizable to surfaces, point patterns, and landscape mosaics. I simulated surfaces and point patterns with a fractal neutral model to control their degree of aggregation. I used spatial permutation analysis to produce distributions of microstates and fit functions to predict the distributions of microstates and the shape of the entropy function. The results confirmed that the direct application of the Boltzmann relation is generalizable across surfaces, point patterns, and landscape mosaics, providing a useful general approach to calculating landscape entropy.
“The School for the Travellers and the Blacks”: Student and Teacher Perspectives on “Choosing” a Post-Primary School with a High Concentration of Disadvantage
Authors: Mc Ginley Hannagh , Keane Elaine
Published: December 2021

Since the formation of the Irish State, the participation and attainment in education of members of the Irish Traveller community have been low. In terms of school-related factors, research points to Travellers perceiving the curriculum as irrelevant, experiencing problematic relationships with peers and teachers, a strong sense of not belonging, and low teacher expectations. This paper draws on the findings of a wider study which explored how an intercultural approach to education was conceptualised and enacted, with particular reference to Travellers, in one urban DEIS (disadvantaged) post-primary school in the West of Ireland (St. Greg’s) with a highly diverse student population. Located in the interpretivist/constructivist paradigm, and informed by critical race theory, an in-depth qualitative case study research design was employed. Data collection involved twenty-eight semi-structured interviews with teacher and student participants, including Traveller and “other” minority ethnic students, as well as White settled Irish students. Data analysis involved several coding stages, and the development of categories. In this paper, we examine one of the categories, the participants’ perceptions of the school as being a school “for the Travellers and the Blacks” and its “reputation” in this regard, as well as the factors impacting the “choice” of the school by different groups of students. Both teacher and student participants were aware of the school’s negative reputation and how this was associated with the socio-demographic composition of its student population. Regarded as the school “for the Travellers and the Blacks”, it was seen as a “tough” school and one in which academic expectations were low. Choosing St. Greg’s was perceived as being related to having a family history of attending the school, not being able to access other schools, and the school providing supports and “freebies”. The findings are discussed in the context of previous research, focusing in particular on critical issues of school socio-demographics, reputation, and choice. The paper concludes with observations about the problematic nature of Ireland’s increasingly segregated schooling system and recommendations about how the education system might better work to include and support Traveller and other minority ethnic students in post-primary education.
Teachers’ Abstracted Conceptualizations of Their Way in Experiencing the Leadership in the Classroom: Transferring Knowledge, Expanding Learning Capacity, and Creating Knowledge
Authors: Zydziunaite Vilma , Kaminskiene Lina , Jurgile Vaida
Published: December 2021

Despite the abundance of decades of research into teacher leadership, uncertainty remains due to confusion around the notions of teacher leadership and the unity or at least the authenticity of definitions, and there is a need for a deeper understanding of this leadership process as the teacher works with students in the classroom. The existing definitions and descriptions of teacher leadership do not determine the connection between teacher leadership and student learning, and the subject remains empirically unsubstantiated. The aim of this study was to develop a set of categories of description derived from the teachers’ conceptions of their leadership in the classroom through learning interactions with students. The study was based on the phenomenographic research methodology. Data were collected by conducting semistructured interviews with 37 teachers. A phenomenographic analysis sought a description, analysis, and understanding of experiences with the focus on variation in the conceptions of the phenomenon, as experienced by teachers. Findings revealed that teachers discern their leadership through working with students at school in three stages represented by three categories of description—transferring knowledge, expanding learning capacity, and creating knowledge. All these stages are linked by teacher-student interaction which facilitates successful and meaningful learning for students within the classroom. The connections between the three stages demonstrate the need for teacher–student collaboration, teaching personalization, the professional expertise of the teacher, and learning cocreation. The findings of this study contribute to the expansion of the concept of teacher leadership not only as expert influence through the application of specific teaching methods, but as a coherent process from knowledge transfer to its creation through reciprocal teacher–student learning in the classroom.
DCRN: An Optimized Deep Convolutional Regression Network for Building Orientation Angle Estimation in High-Resolution Satellite Images
Authors: Shahin Ahmed I. , Almotairi Sultan
Published: November 2021

Recently, remote sensing satellite image analysis has received significant attention from geo-information scientists. However, the current geo-information systems lack automatic detection of several building characteristics inside the high-resolution satellite images. The accurate extraction of buildings characteristics helps the decision-makers to optimize urban planning and achieve better decisions. Furthermore, Building orientation angle is a very critical parameter in the accuracy of automated building detection algorithms. However, the traditional computer vision techniques lack accuracy, scalability, and robustness for building orientation angle detection. This paper proposes two different approaches to deep building orientation angle estimation in the high-resolution satellite image. Firstly, we propose a transfer deep learning approach for our estimation task. Secondly, we propose a novel optimized DCRN network consisting of pre-processing, scaled gradient layer, deep convolutional units, dropout layers, and regression end layer. The early proposed gradient layer helps the DCRN network to extract more helpful information and increase its performance. We have collected a building benchmark dataset that consists of building images in Riyadh city. The images used in the experiments are 15,190 buildings images. In our experiments, we have compared our proposed approaches and the other approaches in the literature. The proposed system has achieved the lowest root mean square error (RMSE) value of 1.24, the lowest mean absolute error (MAE) of 0.16, and the highest adjusted R-squared value of 0.99 using the RMS optimizer. The cost of processing time of our proposed DCRN architecture is 0.0113 ± 0.0141 s. Our proposed approach has proven its stability with the input building image contrast variation for all orientation angles. Our experimental results are promising, and it is suggested to be utilized in other building characteristics estimation tasks in high-resolution satellite images.
A Flexible Turning and Sensing System for Pressure Ulcers Prevention
Authors: Zhang Ying , Zou Xiaofeng , Zhang Bin , Han Yi , Wang Shuoyu , Liu Tao , Zhang Xiufeng
Published: November 2021

Pressure ulcers (PU) are one of the most frequent hazards of long-term bedridden patients. With the continuous increase of aging, the number of long-term bedridden disabled and semi-disabled elderly people is increasing. At the same time, there is a serious shortage of professional pressure ulcer nursing staff. There is also a lack of flexible turning equipment for PU prevention. The research in the field of pressure ulcer prevention at home and abroad is carried out steadily, and the equipment for turning over by pneumatic or mechanical drive is developed. However, these devices often have insurmountable defects, such as complex structure, cost constraints, difficult control, weak body feeling, and so on. Under these circumstances, a set of pneumatic turnover mattresses based on clinical nursing methods have been developed. The mattress is divided into a turnover area and two support areas. The turnover airbag is linked with the support airbag to improve the patient’s comfort when passively turning over. The turnover amplitude and interval can be adjusted to provide a personalized turnover experience for bedridden patients. To improve the safety of the turning mattress during automatic turning, we also add a temperature sensor based on the principle of infrared reflection to monitor the status of bedridden patients, which can realize real-time temperature measurement, monitoring of getting out of bed and monitoring of the turning process.
Estimation of Knee Joint Extension Force Using Mechanomyography Based on IGWO-SVR Algorithm
Authors: Li Zebin , Gao Lifu , Lu Wei , Wang Daqing , Xie Chenlei , Cao Huibin
Published: November 2021

Muscle force is an important physiological parameter of the human body. Accurate estimation of the muscle force can improve the stability and flexibility of lower limb joint auxiliary equipment. Nevertheless, the existing force estimation methods can neither satisfy the accuracy requirement nor ensure the validity of estimation results. It is a very challenging task that needs to be solved. Among many optimization algorithms, gray wolf optimization (GWO) is widely used to find the optimal parameters of the regression model because of its superior optimization ability. Due to the traditional GWO being prone to fall into local optimum, a new nonlinear convergence factor and a new position update strategy are employed to balance local and global search capability. In this paper, an improved gray wolf optimization (IGWO) algorithm to optimize the support vector regression (SVR) is developed to estimate knee joint extension force accurately and timely. Firstly, mechanomyography (MMG) of the lower limb is measured by acceleration sensors during leg isometric muscle contractions extension training. Secondly, root mean square (RMS), mean absolute value (MAV), zero crossing (ZC), mean power frequency (MPF), and sample entropy (SE) of the MMG are extracted to construct feature sets as candidate data sets for regression analysis. Lastly, the features are fed into IGWO-SVR for further training. Experiments demonstrate that the IGWO-SVR provides the best performance indexes in the estimation of knee joint extension force in terms of RMSE, MAPE, and R compared with the other state-of-art models. These results are expected to become the most effective as guidance for rehabilitation training, muscle disease diagnosis, and health evaluation.
Attack and Defense Strategy of Distribution Network Cyber-Physical System Considering EV Source-Charge Bidirectionality
Authors: Li Tong , Zhao Hai , Wang Shihao , Yang Chao , Huang Bonan
Published: November 2021

In the last few years, there has been an exponential increase in the penetration of electric vehicles (EVs) due to their eco-friendly nature and ability to support bidirectional energy exchanges with the power cyber-physical system. However, the existing research only proposes energy management in terms of vehicle-to-grid (V2G) support using fleets of EVs, which lacks research on EV attacks. Motivated by these facts, this paper first introduces a new data integrity attack strategy for a consistent energy management algorithm which considers electric vehicles as energy storage. In particular, we consider EV aggregators as energy storage with source-charge bidirectional characteristics. The attacker carefully constructs false information to manipulate aggregators to participate in scheduling and obtaining additional benefits on the premise of meeting the constraints of microgrid and various devices by attacking the consistent algorithm. Then, we propose a disturbance rejection control strategy combining privacy protection protocols and an isolation mechanism. We analyze the effectiveness of the proposed encryption mechanism and verify the feasibility of the isolation control algorithm by simulation and comparison.
Selected Aspects of Corporate Social Responsibility in the Industry Related to the Production and Supply of Energy
Authors: Kurowski Mateusz , Huk Katarzyna
Published: November 2021

The development of the economy is related not only to its benefits, but also its negative aspects. One of the negative impacts is the impact on the environment and society. Many types of industry and, in a narrower sense, of enterprises, adversely affect their surroundings. It is one of the many factors that has contributed to the growing popularity of the concept of corporate social responsibility (CSR). It is important to balance business and industry with the environment and community impacts. This study presents selected aspects of corporate social responsibility, such as society, the environment, and corporate governance in relation to the industry responsible for energy production and distribution. This group includes the energy sector (mining oil, gas, consumer fuels, and energy equipment and services), the materials sector (metallurgy and mining), as well as distribution (gas, electricity supply, independent energy producers, and renewable energy). The aim of the article was to present the level of implementation of the concept of corporate social responsibility in enterprises responsible for the production and supply of energy. The article uses the analysis of the literature and the statistical analysis showing the level of use of the described concept in the analysed entities. It was based on an analysis of 1904 companies from 41 countries around the world. The article presents the level of implementation of the concept of corporate social responsibility in selected sectors, divided into three areas: social, environmental, and corporate governance. In each of them, the analysis was performed with regard to the selected, most important factors. In addition, an analysis of the described industry, in relation to the others, is presented, which shows the level of use of individual CSR aspects. Thus, it shows which criteria are followed by enterprises in their activities and indicates the real areas of CSR impact on companies.
Hybrid Machine Learning for Solar Radiation Prediction in Reduced Feature Spaces
Authors: Hedar Abdel-Rahman , Almaraashi Majid , Abdel-Hakim Alaa E. , Abdulrahim Mahmoud
Published: November 2021

Solar radiation prediction is an important process in ensuring optimal exploitation of solar energy power. Numerous models have been applied to this problem, such as numerical weather prediction models and artificial intelligence models. However, well-designed hybridization approaches that combine numerical models with artificial intelligence models to yield a more powerful model can provide a significant improvement in prediction accuracy. In this paper, novel hybrid machine learning approaches that exploit auxiliary numerical data are proposed. The proposed hybrid methods invoke different machine learning paradigms, including feature selection, classification, and regression. Additionally, numerical weather prediction (NWP) models are used in the proposed hybrid models. Feature selection is used for feature space dimension reduction to reduce the large number of recorded parameters that affect estimation and prediction processes. The rough set theory is applied for attribute reduction and the dependency degree is used as a fitness function. The effect of the attribute reduction process is investigated using thirty different classification and prediction models in addition to the proposed hybrid model. Then, different machine learning models are constructed based on classification and regression techniques to predict solar radiation. Moreover, other hybrid prediction models are formulated to use the output of the numerical model of Weather Research and Forecasting (WRF) as learning elements in order to improve the prediction accuracy. The proposed methodologies are evaluated using a data set that is collected from different regions in Saudi Arabia. The feature-reduction has achieved higher classification rates up to 8.5% for the best classifiers and up to 15% for other classifiers, for the different data collection regions. Additionally, in the regression, it achieved improvements of average root mean square error up to 5.6% and in mean absolute error values up to 8.3%. The hybrid models could reduce the root mean square errors by 70.2% and 4.3% than the numerical and machine learning models, respectively, when these models are applied to some dataset. For some reduced feature data, the hybrid models could reduce the root mean square errors by 47.3% and 14.4% than the numerical and machine learning models, respectively.
Tailor-Made Phosphorylated Polyvinyl Alcohol/Tungsten Polyoxometalate Proton Exchange Membrane for a Bio-Electrochemical Energy Storage System
Authors: Glibin Vassili , Vajihinejad Vahid , Pupkevich Victor , Karamanev Dimitre G.
Published: November 2021

In this work, the synthesis of a phosphorylated polyvinyl alcohol (p-PVA)/polyoxometalate (tungsto-phosphate) membrane for the BioGenerator, a bio-electrochemical energy storage technology, is reported. It was shown that bonding of lacunary tungsto-phosphate ions to the carbon skeleton of a polymer matrix results in an increase in proton conductivity of up to 2.7 times, compared to previously studied phosphorylated PVA membranes. Testing of the membrane in an actual Fe3+/H2 electrochemical cell showed that it performs significantly better (0.28 W·cm−2 at 0.79 A·cm−2) than the previously used commercial Selemion HSF (Japan) membrane (0.18 W·cm−2 at 0.60 A·cm−2).
Shock Wave Propagation and Flame Kernel Morphology in Laser-Induced Plasma Ignition of CH4/O2/N2 Mixture
Authors: Zhang Junjie , Hu Erjiang , Gao Qunfei , Yin Geyuan , Huang Zuohua
Published: November 2021

The application of laser ignition in the aerospace field has promising prospects. Based on the constant volume combustion chamber, the laser ignition of CH4/O2/N2 mixture with different initial pressure, different laser energy, different equivalence ratio and different oxygen content has been carried out. The development characteristics of the flame kernel and shock wave under different conditions are analyzed. In addition, the Taylor model and Jones model are also used to simulate the development process of the shock wave, and a new modified model is proposed based on the Jones model. The experimental results show that under pure oxygen conditions, the chemical reaction rate of the mixture is too fast, which makes it difficult for the flame kernel to form the ring and third-lobe structure. However, the ring structure is easier to form with the pressure and laser energy degraded; the flame kernel morphology is easier to maintain at a rich equivalence ratio, which is caused by the influence of the movement of hot air flow and a clearer boundary between the ring and the third-lobe. The decrease of the initial pressure or the increase of the laser energy leads to the increase in shock wave velocity, while the change of the equivalence ratio and oxygen content has less influence on the shock wave.
Xerogel-like Materials from Sustainable Sources: Properties and Electrochemical Performances
Authors: Amaral-Labat Gisele , Munhoz Manuella Gobbo C. , Fonseca Beatriz Carvalho da Silva , Boss Alan Fernando Ney , de Almeida-Mattos Patricia , Braghiroli Flavia Lega , Bouafif Hassine , Koubaa Ahmed , Lenz e Silva Guilherme F. B. , Baldan Maurício Ribeiro
Published: November 2021

Energy storage is currently one of the most significant technological challenges globally, and supercapacitor is a prominent candidate over batteries due to its ability for fast charging and long lifetime. Supercapacitors typically use porous carbon as electrodes, because of both the high conductivity and surface area of the material. However, the state-of-the-art porous carbon described in the literature uses toxic chemicals and complex procedures that enhance costs and pollute the environment. Thus, a more sustainable procedure to produce porous carbon is highly desirable. In this context, xerogel-like carbons were prepared by a new, cheap, simple route to polymerization reactions of tannin-formaldehyde in a bio-oil by-product. Using bio-oil in its natural pH allowed a cost reduction and avoided using new reactants to change the reactional medium. Textural properties and electrochemical performances were improved by fast activating the material per 20 min. The non-activated carbon xerogel presented a capacitance of 92 F/g, while the activated one had 132 F/g, given that 77% of the components used are eco-friendly. These results demonstrate that renewable materials may find applications as carbon electrodes for supercapacitors. Overhauling the synthesis route with a different pH or replacing formaldehyde may enhance performance or provide a 100% sustainable carbon electrode.
The Essence of Relationships between the Crude Oil Market and Foreign Currencies Market Based on a Study of Key Currencies
Authors: Szturo Marek , Włodarczyk Bogdan , Miciuła Ireneusz , Szturo Karolina
Published: November 2021

Structural changes occurring in the crude oil market have stimulated the emergence of hypotheses suggesting that the relationship between prices of this raw material and the US dollar exchange rate can gradually become similar to that observed between oil prices and exchange rates of the currencies of the countries whose revenues from the export of this resource are a significant part of their current account balance. The purpose of this study was to determine and evaluate the time-varying dependence between oil prices and the exchange rate of the US dollar in the context of the same relationship for the Chinese, European, Japanese, Saudi, and Russian currencies. The results of our analyses implicate that a negative correlation between the variables in question grows stronger in time periods preceding global shocks and during thereof. The dominance of the USD in the crude oil market is reflected in similar characteristics of the correlations of the currencies of other countries, such as China, countries of the Euro area, or Japan. As for countries exporting crude oil, the situation varies. The results of our research suggest the lack of a stable relationships between prices of crude oil and currency exchange rates. It is also impossible to observe a long-term, unequivocal tendency of the currencies of oil exporting countries being positively correlated with oil prices. Russia was the closest to this situation. In Saudi Arabia, a positive correlation emerged during moments of crisis.
An Improved Droop Control Scheme of a Doubly-Fed Induction Generator for Various Disturbances
Authors: Xu Yien , Chen Pei , Zhang Xinsong , Yang Dejian
Published: November 2021

Doubly-fed induction generators (DFIGs) participate in the system frequency regulation using a fixed-coefficient droop control scheme. Nevertheless, the frequency-supporting capability of this control scheme with fixed gain is limited for different disturbances. This paper suggests an improved droop control scheme for a DFIG that can both alleviate the frequency nadir and maximum rate of change of frequency (ROCOF) during the frequency regulation. To achieve this, an adaptive droop control coefficient based on the ROCOF is suggested. The proposed droop control coefficient is a linear function of the ROCOF. Therefore, the proposed scheme can adjust the control coefficient according to the varying ROCOF. Simulation results clearly demonstrate that the proposed droop control scheme shows better effectiveness in improving the maximum ROCOF and frequency nadir under various sizes of disturbance, even in a varying wind speed.
Exploring the Role of Mycorrhizal and Rhizobium Inoculation with Organic and Inorganic Fertilizers on the Nutrient Uptake and Growth of Acacia mangium Saplings in Acidic Soil
Authors: Sethi Debadatta , Subudhi Sachidananda , Rajput Vishnu D. , Kusumavathi Konathala , Sahoo Tapas Ranjan , Dash Subhaprada , Mangaraj Satyabrata , Nayak Dhirendra Kumar , Pattanayak Sushanta Kumar , Minkina Tatiana , Glinushkin Alexey P. , Kalinitchenko Valery P.
Published: November 2021

Strong and healthy saplings are a prerequisite to establish a successful forest. Therefore, an attempt has been made to develop the best package for nutrient supplementation to raise healthy Acacia mangium saplings, especially in acidic soil. The seeds were sown in pots, receiving different combinations of Arbuscularmycorrhizal (AM), Rhizobium inoculation with application of lime, and mustard oil cake (MOC). The highest spore count and infection percentage (3220 kg−1 soil and 69) were recorded in the AM + MOC + R treated pot, whereas the lowest (2553 kg−1 soil and 37) were recorded in the AM + L treated pot. Nitrogen concentration and uptake in the sapling were higher in the Rhizobium-inoculated treatments than the uninoculated ones. The sulfur concentration and uptake were higher in the MOC-supplemented treatment. Similarly, the P, K, Ca, and Mg concentrations and uptakes were higher in the limed treatments than the unlimed ones. The micronutrient concentration and uptake were higher in the unlimed treatments compared to the lime practice. The concentration of N in Rhizobium-treated pots, P and K in lime-treated pots, and S in MOC-treated pots were increased, whereas the soil pH decreased in all treatments except in the integrated package (AM + MOC + R + L) after 120 days. The Ca and Mg were reduced in all treatments, whereas micronutrients were reduced in all packages except the control. Under different nutrient management practices, plant height and stem girth continuously increased by 9.5 to 12 cm and 3 to 4 times, respectively. The production of robust saplings required integrated application of lime, MOC, AM, and Rhizobium in an acid soil that facilitated better root growth with availability of adequate nutrients for saplings.
Mitigation Potential of Ecosystem-Based Forest Management under Climate Change: A Case Study in the Boreal-Temperate Forest Ecotone
Authors: Landry Gabriel , Thiffault Evelyne , Cyr Dominic , Moreau Lucas , Boulanger Yan , Dymond Caren
Published: December 2021

The forest sector can help reduce atmospheric CO2 through carbon (C) sequestration and storage and wood substitution of more polluting materials. However, climate change can have an impact on the C fluxes we are trying to leverage through forestry. We calculated the difference in CO2 eq. fluxes between ecosystem-based forest management and total forest conservation in the context of the temperate-boreal forest ecotone of Quebec (Canada), taking into account fluxes from forest ecosystems, wood product life cycle, and the substitution effect of wood products on markets. Over the 2020–2120 period, in the absence of climate change, ecosystem-based forest management and wood production caused average net annual emissions of 66.9 kilotonnes (kt) of CO2 eq. year−1 (relative to forest conservation), and 15.4 kt of CO2 eq. year−1 when assuming a 100% substitution effect of wood products. While management increased the ecosystem C sink, emissions from degradation of largely short-lived wood products caused the system to be a net source. Moreover, climate warming would decrease the capacity of ecosystems to sequester C and cause a shift towards more hardwood species. Our study highlights the need to adapt the industrial network towards an increased capacity of processing hardwoods into long-lived products and/or products with high substitution potential.
Sustaining Biomaterials in Bioeconomy: Roles of Education and Learning in Mekong River Basin
Authors: Onpraphai Thaworn , Jintrawet Attachai , Keoboualapha Bounthanh , Khuenjai Suprapat , Guo Ruijia , Wang Jing , Fan Jun
Published: December 2021

The demands to improve the livelihood of small farmers require a systemic shift from fossil fuel-based and destructive approaches to sustainable renewable raw materials and non-destructive approaches. This should be accompanied by a fundamental reorganization of education and learning policies to create new bio-oriented value chains for biomaterials, food, wood, and energy, as well as in large parts of the health, manufacturing, and service industries. In the long run, the successful implementation of bio-oriented production depends on the systemic linking of both first- and second-hand learning in communities in rural as well as urban settings. The purpose of this paper is to present a concept for the co-design of a new curriculum to better equip new graduates with the ability to support the effort of the sustainable production of biomaterials that are non-destructive to the environment. To sustain biomaterials and enhance non-destructive ways of thinking, learning needs a community of practice in both online and onsite platforms—allowing students to better understand and support cascade use. Therefore, the use of by-products and recycling products after use will increase in importance. A community of practice, and institutions, must create education and learning platforms for improved actions regarding biomaterials across generations and experiences, which will subsequently be integrated into the circular value chains of the bioeconomy. The first- and second-hand learning to sustain these value chains depends on higher education and learning institutions with both legal mandates and systems approaches.
Towards a Global Framework for Analysing the Forest-Based Bioeconomy
Authors: Piplani Meenakshi , Smith-Hall Carsten
Published: December 2021

The bioeconomy approach offers potential solutions to global challenges, including sustainable forest management. The body of literature on the forest-based bioeconomy is rapidly expanding, and the diversity of approaches is bewildering. In this paper, we (1) discuss and clarify terminology related to the forest-based bioeconomy as a basis for (2) developing a general framework for analysing the forest-based bioeconomy, which is then (3) applied to two bioeconomy cases. The point of departure is a structured literature review; through qualitative content analysis, we identified the key questions characterizing current approaches to the forest-based bioeconomy; subsequently, the two cases were investigated through analysis of nominal and functional national bioeconomy policy documents and case-specific literature. Answering the key questions allowed the identification of five distinct schools of thought that make up the global framework: the biotechnology, techno-bioresource, socio-bioresource, eco-efficiency, and eco-society schools. These provide a systematic tool to analyse key paradigms, public policy goals, product or service sold, stakeholders, strength of environmental sustainability, and likely transition pathways. We illustrate the application of the framework through analysis of two cases (medicinal plants in Nepal and timber in Finland). We end by discussing how to operationalize the framework further.