bluuebunny/crossref_metadata_2025 huggingface dataset:
Organoid Technology and Its Role for Theratyping Applications in Cystic Fibrosis
Authors: Conti Jessica , Sorio Claudio , Melotti Paola
Published: December 2022

Cystic fibrosis (CF) is a autosomal recessive, multisystemic disease caused by different mutations in the CFTR gene encoding CF transmembrane conductance regulator. Although symptom management is important to avoid complications, the approval of CFTR modulator drugs in the clinic has demonstrated significant improvements by targeting the primary molecular defect of CF and thereby preventing problems related to CFTR deficiency or dysfunction. CFTR modulator therapies have positively changed the patients’ quality of life, especially for those who start their use at the onset of the disease. Due to early diagnosis with the implementation of newborn screening programs and considerable progress in the treatment options, nowadays pediatric mortality was dramatically reduced. In any case, the main obstacle to treat CF is to predict the drug response of patients due to genetic complexity and heterogeneity. Advances in 3D culture systems have led to the extrapolation of disease modeling and individual drug response in vitro by producing mini organs called “organoids” easily obtained from nasal and rectal mucosa biopsies. In this review, we focus primarily on patient-derived intestinal organoids used as in vitro model for CF disease. Organoids combine high-validity of outcomes with a high throughput, thus enabling CF disease classification, drug development and treatment optimization in a personalized manner.
Access to Healthcare for Children and Adolescents with a Chronic Health Condition during the COVID-19 Pandemic: First Results from the KICK-COVID Study in Germany
Authors: Göldel Julia M. , Kamrath Clemens , Minden Kirsten , Wiegand Susanna , Lanzinger Stefanie , Sengler Claudia , Weihrauch-Blüher Susann , Holl Reinhard W. , Tittel Sascha R. , Warschburger Petra
Published: December 2022

This study examines the access to healthcare for children and adolescents with three common chronic diseases (type-1 diabetes (T1D), obesity, or juvenile idiopathic arthritis (JIA)) within the 4th (Delta), 5th (Omicron), and beginning of the 6th (Omicron) wave (June 2021 until July 2022) of the COVID-19 pandemic in Germany in a cross-sectional study using three national patient registries. A paper-and-pencil questionnaire was given to parents of pediatric patients (<21 years) during the routine check-ups. The questionnaire contains self-constructed items assessing the frequency of healthcare appointments and cancellations, remote healthcare, and satisfaction with healthcare. In total, 905 parents participated in the T1D-sample, 175 in the obesity-sample, and 786 in the JIA-sample. In general, satisfaction with healthcare (scale: 0–10; 10 reflecting the highest satisfaction) was quite high (median values: T1D 10, JIA 10, obesity 8.5). The proportion of children and adolescents with canceled appointments was relatively small (T1D 14.1%, JIA 11.1%, obesity 20%), with a median of 1 missed appointment, respectively. Only a few parents (T1D 8.6%; obesity 13.1%; JIA 5%) reported obstacles regarding health services during the pandemic. To conclude, it seems that access to healthcare was largely preserved for children and adolescents with chronic health conditions during the COVID-19 pandemic in Germany.
Wetland Water Level Prediction Using Artificial Neural Networks—A Case Study in the Colombo Flood Detention Area, Sri Lanka
Authors: Jayathilake Tharaka , Sarukkalige Ranjan , Hoshino Yukinobu , Rathnayake Upaka
Published: December 2022

Historically, wetlands have not been given much attention in terms of their value due to the general public being unaware. Nevertheless, wetlands are still threatened by many anthropogenic activities, in addition to ongoing climate change. With these recent developments, water level prediction of wetlands has become an important task in order to identify potential environmental damage and for the sustainable management of wetlands. Therefore, this study identified a reliable neural network model by which to predict wetland water levels over the Colombo flood detention area, Sri Lanka. This is the first study conducted using machine learning techniques in wetland water level predictions in Sri Lanka. The model was developed with independent meteorological variables, including rainfall, evaporation, temperature, relative humidity, and wind speed. The water levels measurements of previous years were used as dependent variables, and the analysis was based on a seasonal timescale. Two neural network training algorithms, the Levenberg Marquardt algorithm (LM) and the Scaled Conjugate algorithm (SG), were used to model the nonlinear relationship, while the Mean Squared Error (MSE) and Coefficient of Correlation (CC) were used as the performance indices by which to understand the robustness of the model. In addition, uncertainty analysis was carried out using d-factor simulations. The performance indicators showed that the LM algorithm produced better results by which to model the wetland water level ahead of the SC algorithm, with a mean squared error of 0.0002 and a coefficient of correlation of 0.99. In addition, the computational efficiencies were excellent in the LM algorithm compared to the SC algorithm in terms of the prediction of water levels. LM showcased 3–5 epochs, whereas SC showcased 34–50 epochs of computational efficiencies for all four seasonal predictions. However, the d-factor showcased that the results were not within the cluster of uncertainty. Therefore, the overall results suggest that the Artificial Neural Network can be successfully used to predict the wetland water levels, which is immensely important in the management and conservation of the wetlands.
Experimental vs. Numerical Computation of Acoustic Analyses on the Thickness Influence of the Multilayer Panel
Authors: Vasile Ovidiu , Bugaru Mihai
Published: December 2022

Sound-absorbing panels made with a perforated front and a sound-absorbing material on the back have been used in many forms of construction for a long time. It is a reasonably efficient system, obtaining high values of sound absorption at a specific resonant frequency, depending on the design of the structure of the sound-absorbing multilayer panel. The present work considers an acoustic panel in two constructive types, consisting of four layers: a front panel made of perforated sheet, polyethylene foam foil, basalt wool board with two different thicknesses, and a back panel of the non-perforated sheet. Due to the different thicknesses of the basalt wool board, for the multilayer structure of the acoustic panel, differences in acoustic impedance and acoustic absorption can be highlighted, experimentally determined with an impedance tube, using the transfer function method (TFM) based on EN ISO 10534-2 in the frequency range 100–3200 Hz. In the meantime, a method was developed to predict the sound absorption coefficient, namely the prediction of sound absorption coefficient using the transfer matrix method (PSAC-TMM). This computational model of the multilayer acoustic panel is introduced considering the internal geometry of the multilayer panel, as well as the computation of the acoustic impedance of each layer, all gathered through the transfer matrix method (TMM). Comparative analyses between experimental data and predictive results using PSAC-TMM were performed, validating the PSAC-TMM as a predictive method to estimate the sound absorption coefficient for acoustic multilayer panels.
After Wildfires and Rewetting: Results of 15+ Years’ Monitoring of Vegetation and Environmental Factors in Cutover Peatland
Authors: Vozbrannaya Anna , Antipin Vladimir , Sirin Andrey
Published: December 2022

On examples of n × 100 m2 permanent plots laid in 2005 on peatlands disturbed by quarrying and milling peat extraction in Meshchera National Park (central European Russia), changes in vegetation cover and environmental factors during self-revegetation, the impact of wildfire, and rewetting are considered. Peat extraction pits are overgrown with floating mats, on which mire, predominantly mesotrophic, vegetation is formed. Cofferdams with retained original mire vegetation contribute to the formation of a spatially diverse mire landscape, but they can also be prone to natural fires. The environmental conditions at the abandoned milled peat extraction sites do not favour natural overgrowth. The driest areas can remain with bare peat perennially. Such peatlands are the most frequent targets of wildfires, which have a severely negative impact and interrupt revegetation processes. Alien plant species emerge and disappear over time. To prevent wildfires and create conditions favourable for the restoration of mire vegetation, rewetting is required. With an average ground water level (GWL) during the growing season of −5 to +15 cm, mire vegetation can actively re-establish. Communities with near-aquatic and aquatic plants can form on flooded areas with GWL of +30. This generally contributes to both fire prevention and wetland diversity.
Suboptimal Performance of Hepatocellular Carcinoma Prediction Models in Patients with Hepatitis B Virus-Related Cirrhosis
Authors: Lee Jae , Lim Tae , Lee Hye , Kim Seung , Park Jun , Kim Do , Ahn Sang , Lee Hyun , Lee Jung , Kim Ja , Min In , Kim Beom
Published: December 2022

This study aimed to evaluate the predictive performance of pre-existing well-validated hepatocellular carcinoma (HCC) prediction models, established in patients with HBV-related cirrhosis who started potent antiviral therapy (AVT). We retrospectively reviewed the cases of 1339 treatment-naïve patients with HBV-related cirrhosis who started AVT (median period, 56.8 months). The scores of the pre-existing HCC risk prediction models were calculated at the time of AVT initiation. HCC developed in 211 patients (15.1%), and the cumulative probability of HCC development at 5 years was 14.6%. Multivariate Cox regression analysis revealed that older age (adjusted hazard ratio [aHR], 1.023), lower platelet count (aHR, 0.997), lower serum albumin level (aHR, 0.578), and greater LS value (aHR, 1.012) were associated with HCC development. Harrell’s c-indices of the PAGE-B, modified PAGE-B, modified REACH-B, CAMD, aMAP, HCC-RESCUE, AASL-HCC, Toronto HCC Risk Index, PLAN-B, APA-B, CAGE-B, and SAGE-B models were suboptimal in patients with HBV-related cirrhosis, ranging from 0.565 to 0.667. Nevertheless, almost all patients were well stratified into low-, intermediate-, or high-risk groups according to each model (all log-rank p < 0.05), except for HCC-RESCUE (p = 0.080). Since all low-risk patients had cirrhosis at baseline, they had unneglectable cumulative incidence of HCC development (5-year incidence, 4.9–7.5%). Pre-existing risk prediction models for patients with chronic hepatitis B showed suboptimal predictive performances for the assessment of HCC development in patients with HBV-related cirrhosis.
Immune Complex Glomerulonephritis in a Patient with Myelodysplastic Syndrome with Ring Sideroblasts Treated with Luspatercept
Authors: Delanghe Sigurd , Nguyen Tri Q. , Mazure Dominiek , Dendooven Amélie , Speeckaert Marijn M.
Published: December 2022

Myelodysplastic syndromes (MDS) are a group of clonal myeloid disorders distinguished by dysplastic bone marrow and peripheral blood cells, ineffective hematopoiesis, and an increased risk of developing acute myeloid leukemia (AML). MDS with ring sideroblasts (MDS-RS) is a favorable outcome subtype with a lower frequency of AML transformation. The FDA recently approved luspatercept for the treatment of patients with very-low-, low-, and intermediate-risk MDS-RS who have failed to correct anemia with an erythropoiesis-stimulating agent (ESA) and require two units of red blood cells over an eight-week period. This drug’s pharmacology is based on the critical role of the transforming growth factor-beta (TGF-β) pathway in regulating erythropoiesis. In this case report, we describe for the first time an acute kidney injury caused by membranoproliferative glomerulonephritis (MPGN) in a patient with MDS-RS who was treated with luspatercept. We propose that a multi-hit hypothesis could explain the immunopathogenesis. A first unknown hit may stimulate IgA immune complex production, whereas luspatercept administration acts as a second hit, causing Smad1-5-8 phosphorylation. This intriguing case report on immune-complex-mediated proliferative glomerulonephritis following luspatercept treatment generates hypotheses and stimulates further research in this area.
An Assessment of the Impact of Distance Learning on Pupils’ Performance
Authors: Gaidelys Vaidas , Čiutienė Rūta , Cibulskas Gintautas
Published: December 2022

Distance education has influenced the organization of education at the level of systems and schools, the change in the specificity of teachers’ activities, the change in pupils’ learning, and, undoubtedly, the attainment of learning outcomes. The aim of this study is to determine what factors have affected pupils’ learning outcomes in the course of distance learning during the COVID-19 pandemic, from the perspective of pupils, pupils’ parents, and teachers. A quantitative study was conducted in order to reveal the impact of distance learning. The positive and negative aspects of distance education became clear. As regards the negative consequences of distance teaching/learning, the results of the study showed that in the teachers’ opinion, the pupils’ learning outcomes generally deteriorated. The positive factors of distance learning influencing the learning process and thus learning outcomes were a comfortable environment, the possibility to use a variety of learning aids available at home, and the possibility to view the lesson records at a time convenient for pupils.
The Legends of Elendor: Educational Gamification as an Influential Factor in Academic Flow and Academic Performance in Socially Depressed Communities
Authors: Manzano-León Ana , Rodríguez-Ferrer José M. , Aguilar-Parra José M. , Salavera Carlos
Published: December 2022

Secondary education needs to find learning strategies that favor student engagement, particularly in socially deprived communities. The objective of this study is to analyze the influence of gamification on educational flow and academic performance. A quasi-experimental pre-test/post-test study has been carried out with 207 secondary school students that compares the gamified cooperative learning method with the directive teaching methodology. The results show statistically significant differences in perceived class flow and academic performance in favor of the gamified group. In addition, it has been analyzed whether these improvements vary according to sex, proving that the gamified methodology is just as effective for girls as for boys. It is concluded that the game systems achieved with gamification favor student engagement because they perceive the tasks as enjoyable and immersive.
Calculation and Analysis of Characteristic Parameters for Lossy Resonator
Authors: Cui Jian , Yu Yu , Lu Yuanyao
Published: December 2022

Resonator is widely employed in microwave and millimeter-wave fields. However, it is challenging and crucial to calculate the electromagnetic field distribution in the resonant cavity with various loss dielectrics. In this paper, according to the axisymmetric distribution characteristics of the lossy resonator, the electromagnetic function of each part in the cavity is established with the Borgnis function, the characteristic equation is obtained based on the mode-matching method, and the resonance frequency and Q factor of the eigenmode TM010 are numerically calculated. With the proposed method, the impact of various dielectric structures and characteristics parameters on the resonant properties of the TM010 mode may be thoroughly examined by taking into account the influence of the thickness as well as the materials of the lossy layer in the z direction. The relative error between the theoretical and the simulated results is below 0.7% at different structures and lossy dielectrics, which indicates that the general calculation approach, as well as crucial data and structure references, is suitable for a related device design in TM010 mode.
Adaptive Dendritic Cell-Negative Selection Method for Earthquake Prediction
Authors: Zhou Wen , Lan Wuyang , Ye Zhiwei , Ming Zhe , Chen Jingliang , He Qiyi
Published: December 2022

Earthquake prediction (EQP) is an extremely difficult task, which has been overcome by adopting various technologies, with no further transformation so far. The negative selection algorithm (NSA) is an artificial intelligence method based on the biological immune system. It is widely used in anomaly detection due to its advantages of requiring little normal data to detect anomalies, including historical seismic-events-based EQP. However, NSA can suffer from the undesirable effect of data drift, resulting in outdated normal patterns learned from data. To tackle this problem, the data changes must be detected and processed, stimulating fast algorithmic adaptation strategies. This study proposes a dendritic cell algorithm (DCA)-based adaptive learning method for drift detection and negative selection algorithm (DC-NSA) that dynamically adapts to new input data. First, this study adopts the Gutenberg–Richter (GR) law and other earthquake distribution laws to preprocess input data. Then, the NSA is employed for EQP, and then, the dendritic cell algorithm (DCA) is employed to detect changes to trigger gradient descent strategies and update the self-set in NSA. Finally, the proposed approach is implemented to predict the earthquakes of MW > 5 in Sichuan and the surroundings during the next month. The experimental results demonstrate that our proposed DC-NSA is superior to the existing state-of-the-art EQP approaches.
Deep Learning-Based BoVW–CRNN Model for Lung Tumor Detection in Nano-Segmented CT Images
Authors: S. U. Aswathy , P. P. Fathimathul Rajeena , Abraham Ajith , Stephen Divya
Published: December 2022

One of the most common oncologies analyzed among people worldwide is lung malignancy. Early detection of lung malignancy helps find a suitable treatment for saving human lives. Due to its high resolution, greater transparency, and low noise and distortions, Computed Tomography (CT) images are most commonly used for processing. In this context, this research work mainly focused on the multifaceted nature of lung cancer diagnosis, a quintessential, fascinating, and risky subject of oncology. The input used here has been nano-image, enhanced with a Gabor filter and modified color-based histogram equalization. Then, the image of lung cancer was segmented by using the Guaranteed Convergence Particle Swarm Optimization (GCPSO) algorithm. A graphical user interface nano-measuring tool was designed to classify the tumor region. The Bag of Visual Words (BoVW) and a Convolutional Recurrent Neural Network (CRNN) were employed for image classification and feature extraction processes. In terms of findings, we achieved the average precision of 96.5%, accuracy of 99.35%, sensitivity of 97%, specificity of 99% and F1 score of 95.5%. With the proposed solution, the overall time required for the segmentation of images was much smaller than the existing solutions. It is also remarkable that biocompatible-based nanotechnology was developed to distinguish the malignancy region on a nanometer scale and has to be evaluated automatically. That novel method succeeds in producing a proficient, robust, and precise segmentation of lesions in nano-CT images.
Explainable AI to Predict Male Fertility Using Extreme Gradient Boosting Algorithm with SMOTE
Authors: GhoshRoy Debasmita , Alvi Parvez Ahmad , Santosh KC
Published: December 2022

Infertility is a common problem across the world. Infertility distribution due to male factors ranges from 40% to 50%. Existing artificial intelligence (AI) systems are not often human interpretable. Further, clinicians are unaware of how data analytical tools make decisions, and as a result, they have limited exposure to healthcare. Using explainable AI tools makes AI systems transparent and traceable, enhancing users’ trust and confidence in decision-making. The main contribution of this study is to introduce an explainable model for investigating male fertility prediction. Nine features related to lifestyle and environmental factors are utilized to develop a male fertility prediction model. Five AI tools, namely support vector machine, adaptive boosting, conventional extreme gradient boost (XGB), random forest, and extra tree algorithms are deployed with a balanced and imbalanced dataset. To produce our model in a trustworthy way, an explainable AI is applied. The techniques are (1) local interpretable model-agnostic explanations (LIME) and (2) Shapley additive explanations (SHAP). Additionally, ELI5 is utilized to inspect the feature’s importance. Finally, XGB outperformed and obtained an AUC of 0.98, which is optimal compared to existing AI systems.
Numerical Simulation of the Proppant Settlement in SC-CO2 Sand-Carrying Fluid in Fracturing Fractures
Authors: Chen Dayong , Sun Zheng
Published: December 2022

Supercritical CO2 fracturing has unique advantages for improving unconventional reservoir recovery. Supercritical CO2 can penetrate deep into the reservoir and increase reservoir reform volume, and it is less damaging to reservoir and easy to flow back. However, when the supercritical CO2 flows as the sand-carrying fluid in the fracture, the settlement of the proppant is still worth studying. Based on the study of supercritical CO2 density and viscosity properties, assuming that the reservoir has been pressed out of the vertical crack by injecting prepad fluid, the proppant characteristics in sand-carrying fluid under different conditions were studied by numerical simulation. After the analysis, the proppant accumulation and backflow will occur at the end of the crack. Large sand diameters, high fluid flow rates, high sand concentrations, high reservoir temperatures, and low reservoir pressures can help to shorten deposition time, and the small particle size, high fluid flow rate, low sand concentration, low reservoir temperature, and high reservoir pressure can help increase the uniformity of sand deposition. Shortening the sand deposition time can help to complete the fracturing efficiently, and increasing the deposition uniformity can improve the fracture conductivity. This article has studied the proppant settling and crack formation characteristics. It is hoped that this study can provide theoretical support for field fracturing and provide theoretical assistance to relevant researchers.
Comparative Analysis of Numerical Methods for Simulating N-Heptane Combustion with Steam Additive
Authors: Minakov Andrey V. , Kuznetsov Viktor A. , Dekterev Artem A. , Anufriev Igor S. , Kopyev Evgeny P. , Alekseenko Sergey V.
Published: December 2022

Currently, thermal power plants operating on hydrocarbon fuels (gas, fuel oil, peat, shale, etc.) are one of the main sources of electricity. An effective and promising method for suppressing harmful emissions (NOx, carbon oxides, soot) from the combustion of fossil fuels is the injection of steam into the combustion chamber. The influence of various mathematical submodels was studied on the accuracy of the numerical simulation of the process of n-heptane combustion in a laboratory burner with steam additive to the reaction zone as a promising chemical engineering method for the disposal of substandard liquid fuels and combustible waste with the production of thermal energy. The problem was solved in a three-dimensional stationary formulation. Systematic verification of these submodels, and a comparison of the results of the calculation with the experimental data obtained were carried out. The comparison with the experimental data was carried out for gas components and temperature distribution at the burner outlet; high agreement of the results was achieved. Optimal submodels of the methodology for calculating the process of fuel combustion in a jet of steam were determined. The best agreement with the experiment data was obtained using the EDC model in combination with a mechanism consisting of 60 components and 305 elementary reactions. More correct simulation results were obtained using the RSM turbulence model and the DO radiation model.
Quantification Methodology of Ammonia Produced from Electrocatalytic and Photocatalytic Nitrogen/Nitrate Reduction
Authors: Utomo Wahyu Prasetyo , Wu Hao , Ng Yun Hau
Published: December 2022

Nitrogen reduction reaction (NRR) and nitrate reduction reaction (NO3−RR) provide a potential sustainable route by which to produce ammonia, a next-generation energy carrier. Many studies have been conducted over the years, mainly emphasizing material design and strategies to improve catalytic performance. Despite significant achievements in material design and corresponding fundamental knowledge, the produced ammonia is still very limited, which makes it prone to bias. The presence of interferants (e.g., cations and sacrificial reagents), the pH of the solution, and improper analytical procedure can lead to the over or underestimation of ammonia quantification. Therefore, the selection of the appropriate ammonia quantification method, which meets the sample solution condition, along with the proper analytical procedures, is of great importance. In this review, the state-of-the-art ammonia quantification method is summarized, emphasizing the advantages, limitations, and practicality for NRR and NO3−RR studies. Fundamental knowledge of the quantification method is introduced. Perspective on the considerations for selecting the suitable quantification method and for performing the quantification process is also provided. Although non exhaustive, this focused review can be useful as a guide to design the experimental setup and procedure for more reliable ammonia quantification results.
Late Paleozoic Accumulation of Coal-Bearing Successions in the Wuhai Coalfield, Western North China: Back-Arc Basin Response to Southward Subduction of the Paleo-Asian Ocean
Authors: Liu Jia , Sun Jiaopeng , Chen Qiang , Kou Feng , Ma Yao , Wang Teng , Zhang Qian , He Weidong , He Lei , Qi Yukun
Published: December 2022

The Late Paleozoic is an important epoch of coal-bed accumulation in the North China, particularly in its western segment, where a world-class coal field has been found and exploited for three decades. Coal-bearing layers recorded rapid Late Carboniferous to Early Permian sea-level rise that led to the evolution of the shallow marine tidal flat basin, followed by regression that resulted in the formation of deltaic facies. However, little attention has been paid to the tectonic factors that assisted in the coal accumulation processes, which have been demonstrated worldwide to be pivotal. In this study, we evaluate the significant influence of southward subduction of the middle segment of the Paleo-Asian Ocean (PAO) during Carboniferous to Early Permian deposition of coal-bearing neritic to deltaic successions in the western North China Block (NCB). We pinpoint a direct link between basin-filling evolution of the northwestern Ordos Basin and the progressive uplift of the Inner Mongolia continental arc triggered by the south-dipping subduction of the Solonker ocean plate. Sedimentary facies variation and paleocurrent reconstruction indicate sedimentary routing from the north to northeast. The petrology and detrital zircon geochronology of sampled sandstones indicate evolving provenances from a dominated cratonic basement to a mixed orogen and continental arc. The Carboniferous samples are generally quartz arenites and contain a large number of Archean to Paleoproterozoic zircons with small amounts of Paleozoic arc pluton components, indicating sediment supply dominated by the western NCB Precambrian basement. In contrast, the youngest sample of the Shanxi Formation is sub-litharenite, the age spectrum of which is characterized by the dominance of ca. 450 and 270 Ma ages, indicative of a high influx of Paleozoic arc detritus. This shift in sandstone petrology, detrital zircon distribution, and depositional setting allows us to link the shoaling of the Ordos Basin with mountain building and the unroofing of the continental arc, which enhances our understanding of both the subduction of the PAO and coal accumulation in the NCB.
Fault Diagnosis of Wind Turbine Bearings Based on CEEMDAN-GWO-KELM
Authors: Liu Liping , Wei Ying , Song Xiuyun , Zhang Lei
Published: December 2022

To solve the problem of fault signals of wind turbine bearings being weak, not easy to extract, and difficult to identify, this paper proposes a fault diagnosis method for fan bearings based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Grey Wolf Algorithm Optimization Kernel Extreme Learning Machine (GWO-KELM). First, eliminating the interference of noise on the collected vibration signal should be conducted, in which the wavelet threshold denoising approach is used in order to reduce the noise interference with the vibration signal. Next, CEEMDAN is used to decompose the signal after a denoising operation to obtain the multi-group intrinsic mode function (IMF), and the feature vector is selected by combining the correlation coefficients to eliminate the spurious feature components. Finally, the fuzzy entropy for the chosen IMF component is input into the GWO-KELM model as a feature vector for defect detection. After diagnosing the Case Western Reserve University (CWRU) dataset by the method presented in this research, it is found that the method can identify 99.42% of the various bearing states. When compared to existing combination approaches, the proposed method is shown to be more efficient for diagnosing wind turbine bearing faults.
Energy Policy for Agrivoltaics in Alberta Canada
Authors: Jamil Uzair , Pearce Joshua M.
Published: December 2022

As Alberta increases conventional solar power generation, land-use conflicts with agriculture increase. A solution that enables low-carbon electricity generation and continued (in some cases, increased) agricultural output is the co-locating of solar photovoltaics (PV) and agriculture: agrivoltaics. This review analyzes policies that impact the growth of agrivoltaics in Alberta. Solar PV-based electricity generation is governed by three regulations based on system capacity. In addition, agrivoltaics falls under various legislations, frameworks, and guidelines for land utilization. These include the Land Use Framework, Alberta Land Stewardship Act, Municipal Government Act, Special Areas Disposition, Bill 22, and other policies, which are reviewed in the agrivoltaics context. Several policies are recommended to support the rapid deployment of agrivoltaics. Openly accessible agrivoltaics research will help optimize agrivoltaic systems for the region, and can be coupled with public education to galvanize social acceptability of large-scale PV deployment. Clearly defining and categorizing agrivoltaics technology, developing agrivoltaics standards, making agrivoltaics technology-friendly regulations and frameworks, and developing programs and policies to incentivize agrivoltaics deployment over conventional PV will all accelerate the technology’s deployment. Through these measures, Alberta can achieve conservation and sustainability in the food and energy sectors while simultaneously addressing their renewable energy and climate-related goals.
A Review of the Continuum Theory-Based Stress and Drag Models in Gas-Solid Flows
Authors: Zhao Junnan , Guo Xinyao , Liu Guodong , Wang Rui , Lu Huilin
Published: December 2022

The continuum theory-based models, which include solid stress models and gas-solid drag models, are required for the modeling of gas-solid flows in the framework of the Eulerian–Eulerian method. The interactions among particles are characterized by their diverse behaviors at different flow regimes, including kinetic motion, particle–particle collision and enduring friction. It is difficult to describe the particle behaviors at various regimes by mathematical methods accurately. Therefore, it is very important to develop proper solid stress models that can capture the inherent characteristics of the flow behaviors. In addition, the gas-solid fluidization system is a typical heterogeneous system, which exhibits locally inhomogeneous structures such as bubbles or particle clusters with different shapes and sizes. Due to these inhomogeneous characteristics, the gas-solid drag model has become one of the key challenges in the simulation of gas-solid flows. Various forms of constitutive relations for solid stress models and gas-solid drag models have been reported in the literature. In this paper, we reviewed the solid stress models crossing various flow regimes and drag models in both micro- and mesoscales, which provide a useful reference for model selection in simulating gas-solid flows.
Fire Dynamics in an Emerging Deforestation Frontier in Southwestern Amazonia, Brazil
Authors: Dutra Débora Joana , Anderson Liana Oighenstein , Fearnside Philip Martin , Graça Paulo Maurício Lima de Alencastro , Yanai Aurora Miho , Dalagnol Ricardo , Burton Chantelle , Jones Christopher , Betts Richard , Aragão Luiz Eduardo Oliveira e Cruz de
Published: December 2022

Land management and deforestation in tropical regions cause wildfires and forest degradation, leading to a loss of ecosystem services and global climate regulation. The objective of the study was to provide a comprehensive assessment of the spatial extent and patterns of burned areas in a new deforestation frontier in the Amazonas state. The methodology applied cross-referenced burned area data from 2003 to 2019 with climate, land cover, private properties and Protected Areas information and performed a series of statistical tests. The influence of the Multivariate ENSO Index (MEI) contributed to a decreasing rainfall anomalies trend and increasing temperature anomalies trend. This process intensified the dry season and increased the extent of annual natural vegetation affected by fires, reaching a peak of 681 km2 in 2019. The results showed that the increased deforestation trend occurred mostly in public lands, mainly after the new forest code, leading to an increase in fires from 66 to 84% in 2019. The methods developed here could identify fire extent, trends, and relationship with land cover change and climate, thus pointing to priority areas for preservation. The conclusion presented that policy decisions affecting the Amazon Forest must include estimates of fire risk and impact under current and projected future climates.
Formation and Behaviour of Active Droplets and Bubbles in a Magnetic Fluid in an Inhomogeneous Magnetic Field
Authors: Sokolov Evgeniy , Kaluzhnaya Dariya , Shel’deshova Elena , Ryapolov Petr
Published: December 2022

This work proposes a new technique for creating active bubbles and droplets with a non-magnetic core and a coating formed by a magnetic fluid. The procedure consists of the injection of a non-magnetic phase into a magnetic one that is supported by the presence of an inhomogeneous magnetic field from the source, which combines an annular magnet and an electromagnet. We explored various modes leading to different active bubbles and drops as well as the influence of the magnetic field on the size, velocity, and acceleration of the formed active droplets. It is shown that active bubbles change their trajectory under the action of a constant magnetic field and also disintegrate under the action of a pulsed one. This provides a new mechanism for controlling the absorption of droplets and bubbles using a magnetic field. Therefore, these results can be applied to create droplet-based microfluidics systems, in which an inhomogeneous magnetic field can be used for focusing droplet and bubble flows in a magnetic fluid.
Metabolomics Characterize the Differential Metabolic Markers between Bama Xiang Pig and Debao Pig to Identify Pork
Authors: Chen Changyi , Zheng Junwen , Xiong Chenyong , Zhou Hongjin , Wei Chuntao , Hu Xin , Qian Xinxiu , He Mengyi , Shi Yandi , Liu Yuwen , Li Zongqiang
Published: December 2022

The Bama Xiang pig (BM) is a unique pig species in Guangxi Province, China. Compared to other breeds of domestic pig, such as the Debao pig (DB), it is smaller in size, better in meat quality, resistant to rough feeding and strong in stress resistance. These unique advantages of Bama Xiang pigs make them of great edible value and scientific research value. However, the differences in muscle metabolites between Bama Xiang pigs (BM) and Debao pigs (DB) are largely unexplored. Here, we identified 214 differential metabolites between these two pig breeds by LC-MS. Forty-one such metabolites are enriched into metabolic pathways, and these metabolites correspond to 11 metabolic pathways with significant differences. In Bama pigs, the abundance of various metabolites such as creatine, citric acid, L-valine and hypoxanthine is significantly higher than in Debao pigs, while the abundance of other metabolites, such as carnosine, is significantly lower. Among these, we propose six differential metabolites: L-proline, citric acid, ribose 1-phosphate, L-valine, creatine, and L-arginine, as well as four potential differential metabolites (without the KEGG pathway), alanyl-histidine, inosine 2′-phosphate, oleoylcarnitine, and histidinyl hydroxyproline, as features for evaluating the meat quality of Bama pigs and for differentiating pork from Bama pigs and Debao pigs. This study provides a proof-of-concept example of distinguishing pork from different pig breeds at the metabolite level and sheds light on elucidating the biological processes underlying meat quality differences. Our pork metabolites data are also of great value to the genomics breeding community in meat quality improvement.
Parboiled Germinated Brown Rice Improves Cardiac Structure and Gene Expression in Hypertensive Rats
Authors: On-Nom Nattira , Khaengamkham Kanoknad , Kettawan Aikkarach , Rungruang Thanaporn , Suttisansanee Uthaiwan , Temviriyanukul Piya , Prangthip Pattaneeya , Chupeerach Chaowanee
Published: December 2022

Hypertension leads to oxidative stress, inflammation, and fibrosis. The suppression of these indicators may be one treatment approach. Parboiled germinated brown rice (PGBR), obtained by steaming germinated Jasmine rice, reduces oxidative stress and inflammation in vivo. PGBR contains more bioactive compounds than brown rice (BR) and white rice (WR). Anti-hypertensive benefits of PGBR have been predicted, but research is lacking. The anti-hypertensive effects of PGBR were investigated in the downstream gene network of hypertension pathogenesis, including the renin–angiotensin system, fibrosis, oxidative stress production, and antioxidant enzymes in N-nitro-L-arginine methyl ester (L-NAME)-induced hypertensive rats. To strengthen our findings, the cardiac structure was also studied. PGBR-exposed rats showed significant reductions in systolic blood pressure (SBP) compared to the hypertensive group. WR did not reduce SBP because of the loss of bioactive compounds during intensive milling. PGBR also reduced the expression of the angiotensin type 1 receptor (AT1R), transforming growth factor-β (TGF-β), and nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (NOX4), which contribute to the renin–angiotensin system, fibrosis, and oxidative stress production, respectively. Losartan (Los, an anti-hypertensive drug)-treated rats also exhibited similar gene expression, implying that PGBR may reduce hypertension using the same downstream target as Los. Our data also indicated that PGBR reduced cardiac lesions, such as the cardiomyopathy induced by L-NAME. This is the first report on the anti-hypertensive effects of PGBR in vivo by the suppression of the renin response, fibrosis, and improved cardiac structure.
Isolation of Cherry Seed Oil Using Conventional Techniques and Supercritical Fluid Extraction
Authors: Dimić Ivana , Pavlić Branimir , Rakita Slađana , Cvetanović Kljakić Aleksandra , Zeković Zoran , Teslić Nemanja
Published: December 2022

This study aims to compare the suitability of three extraction techniques (cold pressing, Soxhlet and supercritical fluid extraction (SFE)) to isolate oil from cherry seeds. Oils were examined in terms of extraction yield, fatty acids profile, tocopherols yield and antioxidant activity. Additionally, influence of SFE parameters was evaluated using one-factor-at-a-time design with pressure (200–350 bar), temperature (40–70 °C), flow rate (0.2–0.4 kg/h) and particle size (<800 µm and >800 µm). Oil yields ranged from 2.50% to 13.02%, whereas the highest yield was achieved with SFE. Samples were rich in polyunsaturated fatty acids, regardless of the applied extraction technique. The main fatty acids were linoleic (46.32–47.29%), oleic (40.89–41.65%), palmitic (6.56–8.00%) and stearic (2.21–2.30%) acid. Total tocopherols yield was between 16.63 mg/100 g oil and 60.61 mg/100 g oil, and highest yield was achieved with SFE. Among the tocopherols, γ-tocopherol was the most abundant, followed by α-, δ- and β-tocopherol. Antioxidant activity was determined using 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2’-azinobis-(3-ethylbenzothiazoline-6-sulfonic) cation (ABTS) assays, and the results indicated that SFE extracts exhibited better or comparable antioxidant potential compared to traditional techniques. The comparison between modern and conventional extractions for oil recovery demonstrates pros and cons for the possibility of industrial application.
A Transition towards a Food and Agricultural System That Includes Both Food Security and Planetary Health
Authors: Hofman-Bergholm Maria
Published: December 2022

This theoretical paper builds on a multidisciplinary framework which is structured to acknowledge the need to combine different research disciplines to understand the problems within our current unsustainable food system and be able to develop possible solutions through new innovations. Current food production methods come at an environmental cost as they generate large amounts of greenhouse gas emissions which affect biodiversity and climate change. The article shows that the problems surrounding food systems and our culture around food, are multifaceted and intricate. The fact is that a growing number of citizens suffer from obesity with various consequential diseases as a result, while a part of the population is still malnourished and dying of hunger. This paper summarizes results from some fairly new studies and different international policy reports to try to clarify how broad the problem is, which is crucial to find new pathways forward to address the problems. Through theoretical discussion, the paper identifies some of the deep underlying root causes and fundamental reasons as to why the urgent needed change is so slow.
The Heat Is On: Modeling the Persistence of ESBL-Producing E. coli in Blue Mussels under Meal Preparation
Authors: Kausrud Kyrre , Skjerdal Taran , Johannessen Gro S. , Ilag Hanna K. , Norström Madelaine
Published: December 2022

Pathways for exposure and dissemination of antimicrobial-resistant (AMR) bacteria are major public health issues. Filter-feeding shellfish concentrate bacteria from the environment and thus can also harbor extended-spectrum β-lactamase—producing Escherichia coli (ESBL E. coli) as an example of a resistant pathogen of concern. Is the short steaming procedure that blue mussels (Mytilus edulis) undergo before consumption enough for food safety in regard to such resistant pathogens? In this study, we performed experiments to assess the survival of ESBL E. coli in blue mussel. Consequently, a predictive model for the dose of ESBL E. coli that consumers would be exposed to, after preparing blue mussels or similar through the common practice of brief steaming until opening of the shells, was performed. The output of the model is the expected number of colony forming units per gram (cfu/g) of ESBL E. coli in a meal as a function of the duration and the temperature of steaming and the initial contamination. In these experiments, the heat tolerance of the ESBL-producing E. coli strain was indistinguishable from that of non-ESBL E. coli, and the heat treatments often practiced are likely to be insufficient to avoid exposure to viable ESBL E. coli. Steaming time (>3.5–4.0 min) is a better indicator than shell openness to avoid exposure to these ESBL or indicator E. coli strains.
Evaluation of Chemical and Sensory Characteristics of Sauerkraut Juice Powder and its Application in Food
Authors: Jansone Liene , Kruma Zanda , Straumite Evita
Published: December 2022

Sauerkraut juice is rich in bioactive compounds; however, it is considered a byproduct of the production process. An innovative solution was found through the process of spray-drying to obtain sauerkraut juice powder. The aim of this study was to evaluate chemical and sensory characteristics of sauerkraut juice powder (SJP) and its application in foodstuffs. For SJP, total phenol content, antiradical activity, and nutritional value were determined, and the results showed that SJP is rich in minerals, especially calcium and potassium, as well as organic acids and vitamin C. SJP contains 12% NaCl and a total phenol content of 359.54 mg GAE 100 g−1 dw. SJP has umami attributes, such as sweet, sour, and salty. Sensory tests—descriptive, rate-all-that-apply, overall liking, and volatile profile determination—were carried out separately in SJP experimental samples with olive oil and sour cream. Among the sweet, sour, and salty flavours, garlic, yogurt, and mayonnaise were also mentioned. In the detection of volatile compounds, leafy and grassy green aromas with light almond were identified in the samples with olive oil and butter and rancid cheese and fishy/amine odours were identified in samples with sour cream. There were significant differences in the overall likability of samples, but the experimental samples with SJP were more popular than control samples; therefore, SJP may be used as a salt alternative in food applications.
Thermal Conductivity Model of Porous Media Embedded with a Damaged Tree-like Branching Network Considering the Influence of Roughness
Authors: Shao Yihao , Yang Huai , Guo Xiuya , Wang Huili , Zhu Limei , Ma Xuan , Chen Ruijuan , Ruan Shufen , Ren Lulu , Zheng Qian
Published: December 2022

In the study of heat transfer in tree-like branching network, neither the heat convection caused by fluid flow in the tree-like branching network nor the asymmetric structure of the tree-like branching network can be ignored. In this work, we assume the porous media is embedded with a tree-like branching network that are characterized by damaged pipes. We investigated the effects of surface roughness on heat conduction and heat convection in the porous media embedded with the damaged tree-like branching network based on the fractal features of tree-like branching networks and the basic theory of thermodynamics. The proposed model for thermal conductivity can be expressed as a function of micro-structural parameters of the composite, such as the relative roughness, the ratio of thermal conductivity of the wall to that of the fluid in the micro-channel, the diameter ratio, the length ratio, the branching level, the number of damaged channels, the total number of branching levels, and the main tube porosity of the porous media. The effects of the micro-structural parameters of the model on its effective thermal conductivity have been analyzed in detail. It is believed that the joint expression of heat conduction and heat convection could enrich and develop the physical study of heat transport in porous media.