bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of the Operating Parameters of Supersonic Separators on the Supersonic Liquefaction Characteristics of Natural Gas
Authors: Long Xueyuan , Huang Qian , Tian Yuan , Mu Lingyan
Published: March 2022

In this study, a mathematical model for the supersonic condensate flow of natural gas to understand its condensation process in a supersonic separator has been proposed. The effects of export back pressure, inlet temperature, and inlet pressure on the condensation parameters were investigated. The results indicate that the condensation position moves forward with the increase in the inlet pressure and the decrease in the inlet temperature. A method for determining the optimal range of operating parameters (export back pressure, inlet temperature, and inlet pressure) for the supersonic separator is proposed. Within the optimal back pressure range, the region of extreme Mach number in the device should be at the inlet of the straight pipe section after the separation gap, and extreme value distribution areas of low temperature, condensation nucleation, and humidity should be between the nozzle expansion section and the inlet of the straight pipe section. It is important to choose a higher temperature among the optimal values as the inlet temperature and also ensure that the optimal inlet pressure is not higher than the pressure corresponding to the humidity inflection point. At the optimal inlet pressure, the maximum humidity distribution area should be behind the supersonic nozzle expansion section and in front of the inlet of the straight pipe section.
Real-Time State of Health Estimation for Solid Oxide Fuel Cells Based on Unscented Kalman Filter
Authors: Xu Yuanwu , Shu Hao , Qin Hongchuan , Wu Xiaolong , Peng Jingxuan , Jiang Chang , Xia Zhiping , Wang Yongan , Li Xi
Published: March 2022

The evolution of performance degradation has become a major obstacle to the long-life operation of the Solid Oxide Fuel Cell (SOFC) system. The feasibility of employing degradation resistance to assess the State of Health (SOH) is proposed and verified. In addition, a real-time Unscented Kalman Filter (UKF) based SOH estimation method is further proposed to eliminate the disturbance of calculating the SOH directly utilizing measurement and electric balance model. The results of real-time SOH estimation with an UKF under constant and varying load conditions demonstrate the feasibility and effectiveness of the SOFC performance degradation assessment method.
An Analytical Heat Transfer Model in Oil Reservoir during Long-Term Production
Authors: Jang Minsoo , Chun Troy S. , An Jaewoo
Published: April 2022

Contrary to the assumption of previous researchers, the radial temperature in the petroleum reservoir during production is non-isothermal because several heat transfer mechanisms change the radial temperature in reservoirs. As there have been few studies, especially after long-term production, this work derives steady-state analytic solutions considering the long-term production. It also presents sensitivity analysis with the various production conditions to investigate heat transfer between the producing fluids and surrounding formations during fluids flowing (hereafter, system heat transfer) in a steady-state. For oil production, the system heat transfer induces a cooling effect on the radial temperature in the reservoir, reducing the temperature rise due to the Joule–Thomson (J–T) heating. This cooling effect increases with the larger Peclet number, however, the relative contribution of the cooling effect to the radial temperature change diminishes. The equations explain that the cooling effect is proportional to the temperature increase due to J–T heating. With a larger permeability, a more convective-dominant phase causes more heat transfer actively. Although the cooling effect itself is amplified with the larger permeability, its relative contribution to the temperature change decreases. From the analysis, the cooling effect of system heat transfer is significant in the low-permeability reservoirs with large drawdown. The system heat transfer is confirmed to be an essential factor in measuring the accurate productivity index of unconventional reservoirs.
Forecasting the Total South African Unplanned Capability Loss Factor Using an Ensemble of Deep Learning Techniques
Authors: Motepe Sibonelo , Hasan Ali N. , Shongwe Thokozani
Published: April 2022

Unplanned power plant failures have been seen to be a major cause of power shortages, and thus customer power cuts, in the South African power grid. These failures are measured as the unplanned capability loss factor (UCLF). The study of South Africa’s UCLF is almost non-existent. Parameters that affect the future UCLF are, thus, still not well understood, making it challenging to forecast when power shortages may be experienced. This paper presents a novel study of South African UCLF forecasting using state-of-the-art deep learning techniques. The study further introduces a novel deep learning ensemble South African UCLF forecasting system. The performance of three of the best recent forecasting techniques, namely, long short-term memory recurrent neural network (LSTM-RNN), deep belief network (DBN), and optimally pruned extreme learning machines (OP-ELM), as well as their aggregated ensembles, are investigated for South African UCLF forecasting. The impact of three key parameters (installed capacity, demand, and planned capability loss factor) on the future UCLF is investigated. The results showed that the exclusion of installed capacity in the LSTM-RNN, DBN, OP-ELM, and ensemble models doubled the UCLF forecasting error. It was also found that an ensemble model of two LSTM-RNN models achieved the lowest errors with a symmetric mean absolute percentage error (sMAPE) of 6.43%, mean absolute error (MAE) of 7.36%, and root-mean-square error (RMSE) of 9.21%. LSTM-RNN also achieved the lowest errors amongst the individual models.
An Evaluation Method of Renewable Energy Resources’ Penetration Capacity of an AC-DC Hybrid Grid
Authors: Li Chenghao , Zhang Di , Liu Zhiwei , Xiong Yulong , Yu Tianhang , Gao Ze , Miao Shihong
Published: April 2022

With increasingly more renewable energy being integrated into the AC-DC hybrid grid, the grid shows more complex dynamic characteristics due to the mutual coupling of HVDC and renewable energy. To evaluate the renewable energy resources’ penetration capacity of the AC-DC hybrid grid, this paper proposes an evaluation method of the renewable energy resources’ penetration capacity of an AC-DC hybrid grid, which considers both economy and safety. Firstly, indicators are proposed for an evaluation of the economy and safety of the AC-DC hybrid grid integrated with renewable energy, where both static and transient stability indicators are considered. Secondly, to maximize the renewable energy penetration capacity and minimize the network loss, an optimization model of the renewable energy penetration capacity of the AC-DC hybrid grid is established considering the static and transient stability constraints. Then, a heuristic solution method for solving the renewable energy penetration capacity optimization model is proposed. Finally, based on the improved IEEE 39 node system, a case analysis is carried out. The simulation results verify the correctness and effectiveness of the proposed method.
The Determinants of Energy and Electricity Consumption in Developed and Developing Countries: International Evidence
Authors: Dokas Ioannis , Panagiotidis Minas , Papadamou Stephanos , Spyromitros Eleftherios
Published: April 2022

Aim and background—As research on the energy and electricity consumption determinants yields mixed results and a multifactorial model has not yet been developed, our study aims to investigate the growth dynamics of the factors that affect energy consumption in developed and developing countries. Motivation—The current global energy crisis has led us to a thorough investigation of the determinants that are affecting it. Hypothesis—It is hypothesized that a set of macro-financial, macro-environmental, and institutional variables are factors that causally affect energy and electricity consumption in a holistic model. Μethods—This research uses the data from 109 countries within a multivariate panel framework taken during 2010–2018, through the error correction, dynamic cointegration econometric methodologies, and causality tests. Results—The results indicate a coherent model with high interpretive power (80%) and that the main determinants of energy consumption in developing countries are economic growth, investment, and winter temperature, whereas, in developed countries, the determinants are trade openness, corruption, and innovation. Conclusion—Because energy consumption and economic growth share a bilateral relationship, the conservation of energy policy measures must be implemented according to the income category in which the country is classified.
Application of Machine Learning to Predict the Performance of an EMIPG Reactor Using Data from Numerical Simulations
Authors: Sedej Owen , Mbonimpa Eric , Sleight Trevor , Slagley Jeremy
Published: April 2022

Microwave-driven plasma gasification technology has the potential to produce clean energy from municipal and industrial solid wastes. It can generate temperatures above 2000 K (as high as 30,000 K) in a reactor, leading to complete combustion and reduction of toxic byproducts. Characterizing complex processes inside such a system is however challenging. In previous studies, simulations using computational fluid dynamics (CFD) produced reproducible results, but the simulations are tedious and involve assumptions. In this study, we propose machine-learning models that can be used in tandem with CFD, to accelerate high-fidelity fluid simulation, improve turbulence modeling, and enhance reduced-order models. A two-dimensional microwave-driven plasma gasification reactor was developed in ANSYS (Ansys, Canonsburg, PA, USA) Fluent (a CFD tool), to create 644 (geometry and temperature) datasets for training six machine-learning (ML) models. When fed with just geometry datasets, these ML models were able to predict the proportion of the reactor area with temperature above 2000 K. This temperature level is considered a benchmark to prevent formation of undesirable byproducts. The ML model that achieved highest prediction accuracy was the feed forward neural network; the mean absolute error was 0.011. This novel machine-learning model can enable future optimization of experimental microwave plasma gasification systems for application in waste-to-energy.
Phylogenetic Signal, Root Morphology, Mycorrhizal Type, and Macroinvertebrate Exclusion: Exploring Wood Decomposition in Soils Conditioned by 13 Temperate Tree Species
Authors: Malik Rondy J. , Bruns Mary Ann V. , Bell Terrence H. , Eissenstat David M.
Published: March 2022

Woodlands are pivotal to carbon stocks, but the process of cycling C is slow and may be most effective in the biodiverse root zone. How the root zone impacts plants has been widely examined over the past few decades, but the role of the root zone in decomposition is understudied. Here, we examined how mycorrhizal association and macroinvertebrate activity influences wood decomposition across diverse tree species. Within the root zone of six predominantly arbuscular mycorrhizal (AM) (Acer negundo, Acer saccharum, Prunus serotina, Juglans nigra, Sassafras albidum, and Liriodendron tulipfera) and seven predominantly ectomycorrhizal (EM) tree species (Carya glabra, Quercus alba, Quercus rubra, Betula alleghaniensis, Picea rubens, Pinus virginiana, and Pinus strobus), woody litter was buried for 13 months. Macroinvertebrate access to woody substrate was either prevented or not using 0.22 mm mesh in a common garden site in central Pennsylvania. Decomposition was assessed as proportionate mass loss, as explained by root diameter, phylogenetic signal, mycorrhizal type, canopy tree trait, or macroinvertebrate exclusion. Macroinvertebrate exclusion significantly increased wood decomposition by 5.9%, while mycorrhizal type did not affect wood decomposition, nor did canopy traits (i.e., broad leaves versus pine needles). Interestingly, there was a phylogenetic signal for wood decomposition. Local indicators for phylogenetic associations (LIPA) determined high values of sensitivity value in Pinus and Picea genera, while Carya, Juglans, Betula, and Prunus yielded low values of sensitivity. Phylogenetic signals went undetected for tree root morphology. Despite this, roots greater than 0.35 mm significantly increased woody litter decomposition by 8%. In conclusion, the findings of this study suggest trees with larger root diameters can accelerate C cycling, as can trees associated with certain phylogenetic clades. In addition, root zone macroinvertebrates can potentially limit woody C cycling, while mycorrhizal type does not play a significant role.
Technological Improvements on FML in the Chianti Classico Wine Production: Co-Inoculation or Sequential Inoculation?
Authors: Bianchi Alessandro , Taglieri Isabella , Venturi Francesca , Sanmartin Chiara , Ferroni Giuseppe , Macaluso Monica , Palla Fabrizio , Flamini Guido , Zinnai Angela
Published: March 2022

Winemaking variables and techniques are known to affect the composition of wines. To obtain a rapid and safe fermentation course, with a reduced risk of proliferation of unwanted microbial species, frequent recourse is made to the use of selected microorganisms, which can greatly simplify the complex management of the fermentation process. In particular, selected strains of lactic acid bacteria are used, which are much more sensitive than yeasts to the operating conditions of the medium. In this regard, the overall aim of this research was to verify whether the early inoculation of homolactic acid bacteria for hexoses (Lactobacillus plantarum) carried out after 24 h, compared with that of saccharomycetes operating alcoholic fermentation, could be advantageous compared with a traditional innoculation with a different heterolactic bacterial strain for hexoses (Oenococcus oeni) operated at the end of alcoholic fermentation. The grape variety chosen was Sangiovese, the protagonist of Tuscan oenology. The evaluation focused on different aspects such as the management of winery operations, and the quality and longevity of the product; was carried out in all phases of winemaking; and analysed both from a chemical and sensory point of view.
Novel Gluten-Free Cinnamon Rolls by Substituting Wheat Flour with Resistant Starch, Lupine and Flaxseed Flour
Authors: Maghaydah Sofyan , Alkahlout Asma , Abughoush Mahmoud , Al Khalaileh Nazieh I. , Olaimat Amin N. , Al-Holy Murad A. , Ajo Radwan , Choudhury Imranul , Hayajneh Waed
Published: April 2022

Celiac disease (CD) is an immunological mediated disorder that occurs to genetically susceptible individuals who suffer from gluten consumption. Therefore, the most effective treatment of CD is a life-long gluten-free diet. This study aimed to produce a nutritious gluten-free cinnamon roll, where resistant starch and lupine flour were used instead of wheat flour, in addition to 10% flaxseed flour and a fixed amount of hydrocolloid (1% xanthan gum). Eight different gluten-free cinnamon roll treatments (T1–T8) were produced with different ratios of resistant starch and lupine flour according to the following percentages (85:5, 80:10, 75:15, 70:20, 65:25, 60:30, 55:35 and 50:40, respectively). The proximate analysis, physical properties, color measurements and sensory evaluation of all cinnamon roll treatments and flours were determined. It was found that lupine and flaxseed flours in all different treatments had significantly (p ≤ 0.05) higher levels of ash, protein, lipid and crude fiber compared to wheat flour treatment (control treatment). However, carbohydrate levels were significantly (p ≤ 0.05) higher in control treatment compared with treatments 3–8. Gluten-free cinnamon rolls had significantly (p ≤ 0.05) higher levels of unsaturated fatty acids (oleic acid, linoleic acid and linolenic acid) than control. Further, there were significant differences in lightness (L*), redness (a*) and yellowness (b*) color values between the gluten-free and control treatments. The control cinnamon roll significantly (p ≤ 0.05) had the highest level of lightness and the lowest level of redness. The sensory evaluation obtained by consumer evaluation indicated that control cinnamon rolls significantly (p ≤ 0.05) received the highest score in overall impression, overall flavor, hardness and aftertaste. However, treatment 5 significantly (p ≤ 0.05) received the highest score in all the sensory scores in comparison with other gluten-free treatments. It is possible to develop a quality gluten-free cinnamon roll with respect to nutritional value manifested in higher levels of protein, fibers, unsaturated acids and prebiotics with acceptable sensory attributes.
The Effect of Heat Treatment on Cow’s Milk Protein Profiles
Authors: Čurlej Jozef , Zajác Peter , Čapla Jozef , Golian Jozef , Benešová Lucia , Partika Adam , Fehér Alexander , Jakabová Silvia
Published: April 2022

Milk is a food of high nutritional value processed by heat treatment. Heat treatment of milk is a technological process designed to inhibit the growth of microorganisms and extend the shelf life of products. The heating process directly affects the molecular structure of whey proteins by the process of denaturation. It leads to the formation of a whey protein–casein polymer complex. Based on these facts, milk heat-treatment conditions should be controlled during milk processing. This work focuses on describing the whey protein denaturation process and formation of the complex of whey protein with casein. The effect of heat treatment on individual milk protein fractions alpha-casein (α-cas), beta-casein (β-cas), kappa-casein (κ-cas), beta-lactoglobulin (β-lg) and alpha-lactalbumin (α-la) was studied by SDS-PAGE. Formation of the whey protein–casein polymer complex increased significantly (p < 0.05) on increasing the temperature and duration of the heat treatment.
Dynamics, Periodic Orbit Analysis, and Circuit Implementation of a New Chaotic System with Hidden Attractor
Authors: Dong Chengwei
Published: March 2022

Hidden attractors are associated with multistability phenomena, which have considerable application prospects in engineering. By modifying a simple three-dimensional continuous quadratic dynamical system, this paper reports a new autonomous chaotic system with two stable node-foci that can generate double-wing hidden chaotic attractors. We discuss the rich dynamics of the proposed system, which have some interesting characteristics for different parameters and initial conditions, through the use of dynamic analysis tools such as the phase portrait, Lyapunov exponent spectrum, and bifurcation diagram. The topological classification of the periodic orbits of the system is investigated by a recently devised variational method. Symbolic dynamics of four and six letters are successfully established under two sets of system parameters, including hidden and self-excited chaotic attractors. The system is implemented by a corresponding analog electronic circuit to verify its realizability.
Synchronization of Fractional Stochastic Chaotic Systems via Mittag-Leffler Function
Authors: Sathiyaraj T. , Fečkan Michal , Wang JinRong
Published: March 2022

This paper is involved with synchronization of fractional order stochastic systems in finite dimensional space, and we have tested its time response and stochastic chaotic behaviors. Firstly, we give a representation of solution for a stochastic fractional order chaotic system. Secondly, some useful sufficient conditions are investigated by using matrix type Mittag-Leffler function, Jacobian matrix via stochastic process, stability analysis and feedback control technique to assure the synchronization of stochastic error system. Thereafter, numerical illustrations are provided to verify the theoretical parts.
Lactic Acid Metabolism and Transporter Related Three Genes Predict the Prognosis of Patients with Clear Cell Renal Cell Carcinoma
Authors: Guo Tuanjie , Zhang Jian , Wang Tao , Yuan Zhihao , Tang Heting , Zhang Dongliang , Chen Siteng , Wang Xiang
Published: March 2022

Lactic acid was previously considered a waste product of glycolysis, and has now become a key metabolite for cancer development, maintenance and metastasis. So far, numerous studies have confirmed that tumor lactic acid levels are associated with increased metastasis, tumor recurrence and poor prognosis. However, the prognostic value of lactic acid metabolism and transporter related genes in patients with clear cell renal cell carcinoma has not been explored. We selected lactic acid metabolism and transporter related twenty-one genes for LASSO cox regression analysis in the E-MTAB-1980 cohort, and finally screened three genes (PNKD, SLC16A8, SLC5A8) to construct a clinical prognostic model for patients with clear cell renal cell carcinoma. Based on the prognostic model we constructed, the over survival (hazard ratio = 4.117, 95% CI: 1.810–9.362, p < 0.0001) of patients in the high-risk group and the low-risk group in the training set E-MTAB-1980 cohort had significant differences, and similar results (hazard ratio = 1.909, 95% CI: 1.414–2.579 p < 0.0001) were also observed in the validation set TGCA cohort. Using the CIBERSORT algorithm to analyze the differences in immune cell infiltration in different risk groups, we found that dendritic cells, M1 macrophages, and CD4+ memory cells in the high-risk group were significantly lower than those in the low-risk group, while Treg cells were higher than in the low-risk group. Finally, through gene enrichment analysis, we found that the signal pathway that is strongly related to the prognostic model is the cell cycle.
InsuLock: A Weakly Supervised Learning Approach for Accurate Insulator Prediction, and Variant Impact Quantification
Authors: Srinivasan Shushrruth Sai , Gong Yanwen , Xu Siwei , Hwang Ahyeon , Xu Min , Girgenti Matthew J. , Zhang Jing
Published: March 2022

Mapping chromatin insulator loops is crucial to investigating genome evolution, elucidating critical biological functions, and ultimately quantifying variant impact in diseases. However, chromatin conformation profiling assays are usually expensive, time-consuming, and may report fuzzy insulator annotations with low resolution. Therefore, we propose a weakly supervised deep learning method, InsuLock, to address these challenges. Specifically, InsuLock first utilizes a Siamese neural network to predict the existence of insulators within a given region (up to 2000 bp). Then, it uses an object detection module for precise insulator boundary localization via gradient-weighted class activation mapping (~40 bp resolution). Finally, it quantifies variant impacts by comparing the insulator score differences between the wild-type and mutant alleles. We applied InsuLock on various bulk and single-cell datasets for performance testing and benchmarking. We showed that it outperformed existing methods with an AUROC of ~0.96 and condensed insulator annotations to ~2.5% of their original size while still demonstrating higher conservation scores and better motif enrichments. Finally, we utilized InsuLock to make cell-type-specific variant impacts from brain scATAC-seq data and identified a schizophrenia GWAS variant disrupting an insulator loop proximal to a known risk gene, indicating a possible new mechanism of action for the disease.
Association of Androgenic Regulation and MicroRNAs in Acinar Adenocarcinoma of Prostate
Authors: Bernardes Julio Guilherme Balieiro , Fernandes Marianne Rodrigues , Rodrigues Juliana Carla Gomes , Vinagre Lui Wallacy Morikawa Souza , Pastana Lucas Favacho , Dobbin Elizabeth Ayres Fragoso , Medeiros Jéssyca Amanda Gomes , Dias Junior Leonidas Braga , Bernardes Gabriel Monteiro , Bernardes Izabel Maria Monteiro , Santos Ney Pereira Carneiro Dos , Demachki Samia , Burbano Rommel Mario Rodriguez
Published: March 2022

Background: Prostate cancer represents 3.8% of cancer deaths worldwide. For most prostate cancer cells to grow, androgens need to bind to a cellular protein called the androgen receptor (AR). This study aims to demonstrate the expression of five microRNAs (miRs) and its influence on the AR formation in patients from the northern region of Brazil. Material and Methods: Eighty-four tissue samples were investigated, including nodular prostatic hyperplasia (NPH) and acinar prostatic adenocarcinoma (CaP). Five miRs (27a-3p, 124, 130a, 488-3p, and 506) were quantified using the TaqMan® Real Time PCR method and AR was measured using Western blotting. Results: Levels of miRs 124, 130a, 488-3p, and 506 were higher in NPH samples. Conversely, in the CaP cases, higher levels of miR 27a-3p and AR were observed. Conclusion: In the future, these microRNAs may be tested as markers of CaP at the serum level. The relative expression of AR was 20% higher in patients with prostate cancer, which suggests its potential as a biomarker for prostate malignancy.
Correction: Ntakolia et al. An Explainable Machine Learning Approach for COVID-19’s Impact on Mood States of Children and Adolescents during the First Lockdown in Greece. Healthcare 2022, 10, 149
Authors: Ntakolia Charis , Priftis Dimitrios , Charakopoulou-Travlou Mariana , Rannou Ioanna , Magklara Konstantina , Giannopoulou Ioanna , Kotsis Konstantinos , Serdari Aspasia , Tsalamanios Emmanouil , Grigoriadou Aliki , Ladopoulou Konstantina , Koullourou Iouliani , Sadeghi Neda , O’Callaghan Georgia , Lazaratou Eleni
Published: April 2022

Argyris Stringaris was initially included as an author in the original publication [...]
Towards Facial Gesture Recognition in Photographs of Patients with Facial Palsy
Authors: Parra-Dominguez Gemma S. , Sanchez-Yanez Raul E. , Garcia-Capulin Carlos H.
Published: April 2022

Humans express their emotions verbally and through actions, and hence emotions play a fundamental role in facial expressions and body gestures. Facial expression recognition is a popular topic in security, healthcare, entertainment, advertisement, education, and robotics. Detecting facial expressions via gesture recognition is a complex and challenging problem, especially in persons who suffer face impairments, such as patients with facial paralysis. Facial palsy or paralysis refers to the incapacity to move the facial muscles on one or both sides of the face. This work proposes a methodology based on neural networks and handcrafted features to recognize six gestures in patients with facial palsy. The proposed facial palsy gesture recognition system is designed and evaluated on a publicly available database with good results as a first attempt to perform this task in the medical field. We conclude that, to recognize facial gestures in patients with facial paralysis, the severity of the damage has to be considered because paralyzed organs exhibit different behavior than do healthy ones, and any recognition system must be capable of discerning these behaviors.
Trajectories of Anxiety and Depression Symptoms over Five Years since Breast Cancer Diagnosis: Results of the NEON-BC Prospective Study
Authors: Lopes Catarina , Severo Milton , Fontes Filipa , Lopes-Conceição Luisa , Ferreira Augusto , Pereira Susana , Lunet Nuno , Araújo Natália
Published: April 2022

Anxiety and depression symptoms are frequent among patients with breast cancer (BCa) and may last after initial treatments. We aimed to identify five-year trajectories of anxiety and depression symptoms among women with BCa. Neuro-oncological complications of BCa (NEON-BC) cohort included 506 patients admitted at the Portuguese Institute of Oncology of Porto in 2012, who were evaluated with the Hospital Anxiety and Depression Scale before cancer treatment and after one, three, and five years (7.9% attrition rate). Mixed-effect models were used to model anxiety and depression scores over time and model-based clustering to identify the different trajectories. Three trajectories of anxiety symptoms were identified: (1) high scores at baseline and increasing over time (21.7%); (2) consistently low scores over time (63.6%); (3) mid-range scores at baseline, decreasing over time (14.6%). Three trajectories were identified for depression symptoms: (1) high scores at baseline and increasing over time (21.1%); (2) mid-range scores at baseline, which decreased afterward (58.7%); (3) consistently low levels over time (20.2%). Age, education, baseline, and one-year anxiety/depression status predicted the worst five-year trajectories. These results show that assessing anxiety and depression symptoms before treatment and after one year may contribute to identifying the patients who could benefit the most from psychological support.
Optimising Soilless Culture Systems and Alternative Growing Media to Current Used Materials
Authors: Gruda Nazim S. , Fernández Juan A.
Published: March 2022

In the last few decades, soilless culture systems (SCSs) have been gaining worldwide popularity, making them one of the fastest-growing sectors in agriculture [...]
The Effective Role of Nano-Silicon Application in Improving the Productivity and Quality of Grafted Tomato Grown under Salinity Stress
Authors: Sayed Eman G. , Mahmoud Abdel Wahab M. , El-Mogy Mohamed M. , Ali Mahmoud A. A. , Fahmy Mahmoud A. M. , Tawfic Ghada A.
Published: March 2022

This study aims to determine the influence of grafting and nano-silicon fertilizer on the growth and production of tomatoes (Solanumlycopersicum L.) under salinity conditions. A commercial tomato hybrid (cv. Strain B) was used as a scion and two tomato phenotypes were used as rootstocks: S. pimpinellifolium and Edkawy. The rootstock effect was evaluated by growing plants at two NaCl concentrations plus the control (0, 4000, and 8000 ppm NaCl). Nano-silicon foliar application (0.5 ppm) after 20, 28, and 36 days from transplanting was also used to mitigate salinity stress. Antioxidants, hormones, and proline were evaluated for a better understanding of the physiological changes induced by salinity and grafting. The results showed that grafting either on S. pimpinellifolium or Edkawy combined with nano-silicon application enhanced shoot and root growth, fruit yield, and fruit quality. The Edkawy rootstock was more effective than the S. pimpinellifolium rootstock in terms of counteracting the negative effect of salinity. Higher levels of mineral contents, GA3, ABA, and proline were detected in shoots that were subjected to grafting and nano-silicon application compared to the control treatment. This study indicates that grafting and nano-silicon application hold potential as alternative techniques to mitigate salt stress in commercial tomato cultivars.
Correction: Burgel et al. Impact of Different Growing Substrates on Growth, Yield and Cannabinoid Content of Two Cannabis sativa L. Genotypes in a Pot Culture. Horticulturae 2020, 6, 62
Authors: Burgel Lisa , Hartung Jens , Graeff-Hönninger Simone
Published: April 2022

In the original publication [...]
Determination of Skin Friction Factor in Gravel Bed Rivers: Considering the Effect of Large-Scale Topographic Forms in Non-Uniform Flows
Authors: Kazem Masoud , Afzalimehr Hossein , Nazari-Sharabian Mohammad , Karakouzian Moses
Published: April 2022

Determination of skin friction factor has been a controversial topic, particularly in gravel-bed rivers where total flow resistance is influenced by the existence of small-scale skin roughness and large-scale topographic forms. The accuracy of existing models predicting skin friction factors in conditions where small-scale skin roughness and large-scale topographic forms exist is very low. The objective of this study is to develop a modified model that improves the accuracy of the determination of skin friction factors in gravel-bed rivers. To this end, 100 velocity profile data obtained from eight gravel-bed rivers were utilized to develop an analytical method that considers the momentum thickness of the boundary layer and its deviation in large-scale topographic bedforms in a 1D force-balance model. The results show that the accuracy of the skin friction factors is enhanced when (1) the model is in the form of an exponential function of energy slope, and (2) the deviation of momentum thickness is considered in the model. The proposed model results in high accuracy of the predicted skin friction factors for energy slopes between 0.001 and 0.1, which exist in most gravel-bed rivers with different morphologies. Additionally, this study model was used to modify the classic Einstein–Strickler equation. The modified equation resulted in improved accuracy of the predicted skin friction factors in non-uniform flow conditions even when velocity profiles and energy slope were not available.
Analysis of Disaster-Related Deaths in the Great East Japan Earthquake: A Retrospective Observational Study Using Data from Ishinomaki City, Miyagi, Japan
Authors: Tsuboi Motohiro , Hibiya Manabu , Tsuboi Rumiko , Taguchi Shigemasa , Yasaka Koichi , Kiyota Kazuya , Sakisaka Kayako
Published: March 2022

Disaster-related deaths are of two types: direct and indirect. Preventable disaster-related deaths reported in the Great East Japan Earthquake (GEJE) included a large number of indirect deaths. This study aimed to investigate the data on disaster-related deaths in the GEJE in Ishinomaki City, Miyagi Prefecture, and to clarify the scope of disaster-related deaths to help future disaster preparedness. A retrospective observational study was conducted using public data on disaster-related deaths from March 2011 to January 2021, available at Ishinomaki City Hall. Descriptive and Cox regression analyses were conducted. The most common direct cause of disaster-related deaths was respiratory diseases, which were more common among those aged less than three months and over 60 years. Suicide was common among those aged under 60 years, and the proportion increased more than six months after the disaster. The risk of death was significantly higher among those who needed nursing care than among those independent in daily living. The results indicate that measures should be taken for the elderly and those who need care from an early phase after the disaster. The analysis of data on disaster-related deaths in other affected municipalities may provide further evidence to help reduce disaster-related deaths.
The Effect of Cone-Beam Computed Tomography (CBCT) Evaluation on Treatment Planning after Endodontic Instrument Fracture
Authors: Kalogeropoulos Konstantinos , Xiropotamou Alexandra , Koletsi Despina , Tzanetakis Giorgos N.
Published: March 2022

Intracanal instrument fracture is a procedural iatrogenic event during endodontic treatment that may affect treatment planning and eventually treatment outcome. Cone Beam Computed Tomography (CBCT) has offered several advantages, especially in endodontic cases in which information from conventional periapical radiograph may not be adequate to allow a precise treatment planning decision and a subsequent appropriate management of the cases. The present study was firstly conducted to assess the effect of CBCT evaluation on the decision-making process after instrument fracture; secondly, to introduce a new clinical approach in cases with fractured instruments located in the mesial roots of mandibular and maxillary molars. The study design was observational. The sample comprised all cases of mandibular and maxillary molars where an instrument fracture had occurred in the mesial roots. Two qualified (National and Kapodistrian University of Athens, Greece) and experienced (more than fifteen years of daily practicing) endodontists evaluated all the cases. The initial treatment plan made by evaluating periapical radiographs of each case was compared to the final plan set after CBCT evaluation. A marginal homogeneity test for paired data was conducted to test the concordance of treatment planning with periapical radiographs versus CBCT. Multivariable logistic regression was structured to identify predictors of modification in treatment planning following CBCT assessment, and to record estimators for decision to remove, bypass or retain the fragment. The level of statistical significance was pre-specified at p < 0.05. Of a total 52 cases evaluated, change in treatment planning with conventional periapical radiograph as a reference, following evaluation of CBCT, was observed in more than half of the teeth. The difference was statistically significant (p < 0.001). Apical location of the fragment was more likely to induce a perceived change in treatment planning after CBCT evaluation (p < 0.01). Canal merging induced 95% lower odds (p = 0.01) for taking a decision to remove or bypass, revealing that retaining the fragment was by far a more likely decision. A significant impact of CBCT preoperative evaluation on treatment planning for the management of such cases was demonstrated. Apical location of the fragment and canal merging seem to influence the decision-making process.
Succession and Driving Factors of Periphytic Community in the Middle Route Project of South-to-North Water Division (Henan, China)
Authors: Chen Xiaonuo , Wang Xiaojun , Li Yuying , Yao Yinlei , Zhang Yun , Jiang Yeqing , Lei Xiaohui , Liu Han , Wu Naicheng , Fohrer Nicola
Published: March 2022

The Middle Route Project of the South-to-North Water Diversion is an artificially independent system that does not connect to other surface waters. Excessive periphyton proliferation causes a series of environmental problems in the canal. In this study, the periphyton community and environmental factors on the left and right banks of the canal in the algal growing area were investigated and sampled six times (June, September, and November of 2019 and 2020). The succession pattern of the attached organism community in the artificial canal was analyzed, and the key factors affecting the algal community were analyzed using RDA and GAM. The results showed that the seasonal variability of the environmental factors was more significant than the spatial variability. A total of 114 taxa of periphytic algae were found, belonging to seven phyla and 69 genera, and mainly composed of Bacillariophyta. Species richness was ranked as Bacillariophyta (60 taxa), Chlorophyta (31 taxa) and Cyanobacteria (15 taxa), and higher in autumn than in summer. The dominant taxa were Cymbella sp., Fragilaria sp., Navicula sp. and Diatoma sp. The abundance of periphytic algal varied from 0.07 × 105 to 8.99 × 105 ind./cm2, with trends similar to that of species richness. The redundancy analysis and generalized additive model showed that water temperature and nutrient concentration were the key factors influencing the structure of the algal community, followed by discharge rate and velocity, which were the determinants of the spatial and temporal patterns of the algal community. In view of the influence of discharge and velocity on the structure of algal communities, it is suggested that ecological scheduling could be used to regulate the structure of the algal community on the canal wall in the operation of later water division projects to ensure the safety of water division.
Incentive Mechanisms for Carbon Emission Abatement Considering Consumers’ Low-Carbon Awareness under Cap-and-Trade Regulation
Authors: Xue Kelei , Sun Guohua , Yao Tongtong
Published: March 2022

In the era of sustainable development, reducing carbon emissions and achieving carbon neutrality are gradually becoming a consensus for our society. This study explores firms’ incentive mechanisms for carbon emission abatement in a two-echelon supply chain under cap-and-trade regulation, where consumers exhibit low-carbon awareness. To boost the manufacturer’s motivation for abatement, the retailer can provide four incentive strategies, i.e., price-only (PO), cost-sharing (CS), revenue-sharing (RS), and both (cost and revenue) sharing (BS). The equilibrium decisions under the four incentive strategies are obtained by establishing and solving game models. A two-part tariff contract is also proposed to coordinate the low-carbon supply chain. Finally, through comparisons and analyses, we find that: (1) Consumers’ high low-carbon awareness can boost the manufacturer’s incentive for carbon emission abatement (CEA), thus increasing supply chain members’ profits. (2) It is more effective for the retailer to share its revenue to incentivize the manufacturer for abatement than to bear the investment cost of CEA. Thus, Strategy RS is better than Strategy CS and equivalent to Strategy BS. (3) The manufacturer and retailer have consistent incentive strategy preference under cap-and-trade regulation. Both firms prefer the incentive strategy with a higher cooperation level. (4) The incentive strategy with a higher cooperation level can also bring higher eco-social welfare under certain conditions.
Dynamic Phosphorylation of miRNA Biogenesis Factor HYL1 by MPK3 Involving Nuclear–Cytoplasmic Shuttling and Protein Stability in Arabidopsis
Authors: Bhagat Prakash Kumar , Verma Deepanjali , Singh Kirti , Badmi Raghuram , Sharma Deepika , Sinha Alok Krishna
Published: March 2022

MicroRNAs (miRNAs) are one of the prime regulators of gene expression. The recruitment of hyponastic leaves 1 (HYL1), a double-stranded RNA binding protein also termed as DRB1, to the microprocessor complex is crucial for accurate primary-miRNA (pri-miRNA) processing and the accumulation of mature miRNA in Arabidopsis thaliana. In the present study, we investigated the role of the MAP kinase-mediated phosphorylation of AtHYL1 and its sub-cellular activity. AtMPK3 specifically phosphorylates AtHYL1 at the evolutionarily conserved serine-42 present at the N-terminal regions and plays an important role in its nuclear–cytosolic shuttling. Additionally, we identified that AtHYL1 is cleaved by trypsin-like proteases into an N-terminal fragment, which renders its subcellular activities. We, for the first time, report that the dimerization of AtHYL1 not only takes place in the nucleus, but also in the cytosol, and the C-terminal of AtHYL1 has a role in regulating its stability, as well as its subcellular localization. AtHYL1 is hyper-phosphorylated in mpk3 mutants, leading to higher stability and reduced degradation. Our data show that AtMPK3 is a negative regulator of AtHYL1 protein stability and that the AtMPK3-induced phosphorylation of AtHYL1 leads to its protein degradation.
Extracellular Vesicles and Acute Kidney Injury: Potential Therapeutic Avenue for Renal Repair and Regeneration
Authors: Kosanović Maja , Milutinovic Bojana , Glamočlija Sofija , Morlans Ingrid Mena , Ortiz Alberto , Bozic Milica
Published: March 2022

Acute kidney injury (AKI) is a sudden decline of renal function and represents a global clinical problem due to an elevated morbidity and mortality. Despite many efforts, currently there are no treatments to halt this devastating condition. Extracellular vesicles (EVs) are nanoparticles secreted by various cell types in both physiological and pathological conditions. EVs can arise from distinct parts of the kidney and can mediate intercellular communication between various cell types along the nephron. Besides their potential as diagnostic tools, EVs have been proposed as powerful new tools for regenerative medicine and have been broadly studied as therapeutic mediators in different models of experimental AKI. In this review, we present an overview of the basic features and biological relevance of EVs, with an emphasis on their functional role in cell-to-cell communication in the kidney. We explore versatile roles of EVs in crucial pathophysiological mechanisms contributing to AKI and give a detailed description of the renoprotective effects of EVs from different origins in AKI. Finally, we explain known mechanisms of action of EVs in AKI and provide an outlook on the potential clinical translation of EVs in the setting of AKI.
Glutathione Modulation in PVYNTN Susceptible and Resistant Potato Plant Interactions
Authors: Otulak-Kozieł Katarzyna , Kozieł Edmund , Przewodowski Włodzimierz , Ciacka Katarzyna , Przewodowska Agnieszka
Published: March 2022

Glutathione is a metabolite that plays an important role in plant response to biotic stress through its ability to remove reactive oxygen species, thereby limiting the degree of potential oxidative damage. It can couple changes in the intracellular redox state to the development, especially the defense responses, of plants. Several studies have focused on measuring glutathione levels in virus infected plants, but have not provided complete information. Therefore, we analyzed, for the first time, the content of glutathione as well as its ultrastructural distribution related to susceptible and hypersensitive potato–Potato virus Y NTN (PVYNTN) interaction, with an aim of providing new insight into interactive responses to PVYNTN stress. Our findings reported that the inoculation of PVYNTN caused a dynamic increase in the content of glutathione, not only in resistance but also in susceptible reaction, especially at the first steps of plant–virus interaction. Moreover, the increase in hypersensitive response was much more dynamic, and accompanied by a significant reduction in the content of PVYNTN. By contrast, in susceptible potato Irys, the content of glutathione decreased between 7 and 21 days after virus inoculation, which led to a significant increase in PVYNTN concentration. Additionally, our findings clearly indicated the steady induction of two selected potato glutathione S-transferase StGSTF1 and StGSTF2 genes after PVYNTN inoculation, regardless of the interaction type. However, the relative expression level of StGSTF1 did not significantly differ between resistant and susceptible plants, whereas the relative expression levels of StGSTF2 differed between susceptible and resistant reactions. Therefore, we proposed that StGSTF2 can act as a marker of the type of response to PVYNTN. Our observations indicated that glutathione is an important component of signaling as well as the regulatory network in the PVYNTN–potato pathosystem. In resistance responses to PVYNTN, this metabolite activates plant defenses by reducing potential damage to the host plant cell, causing a reduction in virus concentration, while it can also be involved in the development of PVYNTN elicited symptoms, as well as limiting oxidative stress, leading to systemic infection in susceptible potato plants.
Shining Damaged Hearts: Immunotherapy-Related Cardiotoxicity in the Spotlight of Nuclear Cardiology
Authors: Kersting David , Settelmeier Stephan , Mavroeidi Ilektra-Antonia , Herrmann Ken , Seifert Robert , Rischpler Christoph
Published: March 2022

The emerging use of immunotherapies in cancer treatment increases the risk of immunotherapy-related cardiotoxicity. In contrast to conventional chemotherapy, these novel therapies have expanded the forms and presentations of cardiovascular damage to a broad spectrum from asymptomatic changes to fulminant short- and long-term complications in terms of cardiomyopathy, arrythmia, and vascular disease. In cancer patients and, particularly, cancer patients undergoing (immune-)therapy, cardio-oncological monitoring is a complex interplay between pretherapeutic risk assessment, identification of impending cardiotoxicity, and post-therapeutic surveillance. For these purposes, the cardio-oncologist can revert to a broad spectrum of nuclear cardiological diagnostic workup. The most promising commonly used nuclear medicine imaging techniques in relation to immunotherapy will be discussed in this review article with a special focus on the continuous development of highly specific molecular markers and steadily improving methods of image generation. The review closes with an outlook on possible new developments of molecular imaging and advanced image evaluation techniques in this exciting and increasingly growing field of immunotherapy-related cardiotoxicity.