bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Liver-on-Chip Integrating a Hydroscaffold Mimicking the Liver’s Extracellular Matrix
Authors: Messelmani Taha , Le Goff Anne , Souguir Zied , Maes Victoria , Roudaut Méryl , Vandenhaute Elodie , Maubon Nathalie , Legallais Cécile , Leclerc Eric , Jellali Rachid
Published: September 2022

The 3Rs guidelines recommend replacing animal testing with alternative models. One of the solutions proposed is organ-on-chip technology in which liver-on-chip is one of the most promising alternatives for drug screening and toxicological assays. The main challenge is to achieve the relevant in vivo-like functionalities of the liver tissue in an optimized cellular microenvironment. Here, we investigated the development of hepatic cells under dynamic conditions inside a 3D hydroscaffold embedded in a microfluidic device. The hydroscaffold is made of hyaluronic acid and composed of liver extracellular matrix components (galactosamine, collagen I/IV) with RGDS (Arg-Gly-Asp-Ser) sites for cell adhesion. The HepG2/C3A cell line was cultured under a flow rate of 10 µL/min for 21 days. After seeding, the cells formed aggregates and proliferated, forming 3D spheroids. The cell viability, functionality, and spheroid integrity were investigated and compared to static cultures. The results showed a 3D aggregate organization of the cells up to large spheroid formations, high viability and albumin production, and an enhancement of HepG2 cell functionalities. Overall, these results highlighted the role of the liver-on-chip model coupled with a hydroscaffold in the enhancement of cell functions and its potential for engineering a relevant liver model for drug screening and disease study.
Rational Generation of Monoclonal Antibodies Selective for Pathogenic Forms of Alpha-Synuclein
Authors: Gibbs Ebrima , Zhao Beibei , Roman Andrei , Plotkin Steven S. , Peng Xubiao , Hsueh Shawn C. C. , Aina Adekunle , Wang Jing , Shyu Clay , Yip Calvin K. , Nam Sung-Eun , Kaplan Johanne M. , Cashman Neil R.
Published: September 2022

Misfolded toxic forms of alpha-synuclein (α-Syn) have been implicated in the pathogenesis of synucleinopathies, including Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). The α-Syn oligomers and soluble fibrils have been shown to mediate neurotoxicity and cell-to-cell propagation of pathology. To generate antibodies capable of selectively targeting pathogenic forms of α-Syn, computational modeling was used to predict conformational epitopes likely to become exposed on oligomers and small soluble fibrils, but not on monomers or fully formed insoluble fibrils. Cyclic peptide scaffolds reproducing these conformational epitopes exhibited neurotoxicity and seeding activity, indicating their biological relevance. Immunization with the conformational epitopes gave rise to monoclonal antibodies (mAbs) with the desired binding profile showing selectivity for toxic α-Syn oligomers and soluble fibrils, with little or no reactivity with monomers, physiologic tetramers, or Lewy bodies. Recognition of naturally occurring soluble α-Syn aggregates in brain extracts from DLB and MSA patients was confirmed by surface plasmon resonance (SPR). In addition, the mAbs inhibited the seeding activity of sonicated pre-formed fibrils (PFFs) in a thioflavin-T fluorescence-based aggregation assay. In neuronal cultures, the mAbs protected primary rat neurons from toxic α-Syn oligomers, reduced the uptake of PFFs, and inhibited the induction of pathogenic phosphorylated aggregates of endogenous α-Syn. Protective antibodies selective for pathogenic species of α-Syn, as opposed to pan α-Syn reactivity, are expected to provide enhanced safety and therapeutic potency by preserving normal α-Syn function and minimizing the diversion of active antibody from the target by the more abundant non-toxic forms of α-Syn in the circulation and central nervous system.
Contribution of the HIV-1 Envelope Glycoprotein to AIDS Pathogenesis and Clinical Progression
Authors: Valenzuela-Fernández Agustín , Cabrera-Rodríguez Romina , Casado Concha , Pérez-Yanes Silvia , Pernas María , García-Luis Jonay , Marfil Silvia , Olivares Isabel , Estévez-Herrera Judith , Trujillo-González Rodrigo , Blanco Julià , Lopez-Galindez Cecilio
Published: September 2022

In the absence of antiviral therapy, HIV-1 infection progresses to a wide spectrum of clinical manifestations that are the result of an entangled contribution of host, immune and viral factors. The contribution of these factors is not completely established. Several investigations have described the involvement of the immune system in the viral control. In addition, distinct HLA-B alleles, HLA-B27, -B57-58, were associated with infection control. The combination of these elements and antiviral host restriction factors results in different clinical outcomes. The role of the viral proteins in HIV-1 infection has been, however, less investigated. We will review contributions dedicated to the pathogenesis of HIV-1 infection focusing on studies identifying the function of the viral envelope glycoprotein (Env) in the clinical progression because of its essential role in the initial events of the virus life-cycle. Some analysis showed that inefficient viral Envs were dominant in non-progressor individuals. These poorly-functional viral proteins resulted in lower cellular activation, viral replication and minor viral loads. This limited viral antigenic production allows a better immune response and a lower immune exhaustion. Thus, the properties of HIV-1 Env are significant in the clinical outcome of the HIV-1 infection and AIDS pathogenesis.
Novel Therapies for the Treatment of Cardiac Fibrosis Following Myocardial Infarction
Authors: Raziyeva Kamila , Kim Yevgeniy , Zharkinbekov Zharylkasyn , Temirkhanova Kamila , Saparov Arman
Published: September 2022

Cardiac fibrosis is a common pathological consequence of most myocardial diseases. It is associated with the excessive accumulation of extracellular matrix proteins as well as fibroblast differentiation into myofibroblasts in the cardiac interstitium. This structural remodeling often results in myocardial dysfunctions such as arrhythmias and impaired systolic function in patients with heart conditions, ultimately leading to heart failure and death. An understanding of the precise mechanisms of cardiac fibrosis is still limited due to the numerous signaling pathways, cells, and mediators involved in the process. This review article will focus on the pathophysiological processes associated with the development of cardiac fibrosis. In addition, it will summarize the novel strategies for anti-fibrotic therapies such as epigenetic modifications, miRNAs, and CRISPR technologies as well as various medications in cellular and animal models.
Treatment of Diabetes and Osteoporosis—A Reciprocal Risk?
Authors: Zawada Agnieszka , Ratajczak Alicja Ewa , Rychter Anna Maria , Szymczak-Tomczak Aleksandra , Dobrowolska Agnieszka , Krela-Kaźmierczak Iwona
Published: September 2022

Diabetes mellitus is a metabolic and systematic disorder that requires individualized therapy. The disease leads to various consequences, resulting in the destruction of tissues and organs. The aforementioned outcomes also include bone mineral disorders, caused by medications as well as diet therapy and physical activity. Some drugs may have a beneficial effect on both bone mineral density and the risk of fractures. Nevertheless, the impact of other medications remains unknown. Focusing on pharmacotherapy in diabetes may prevent bone mineral disorders and influence both the treatment and quality of life in patients suffering from diabetes mellitus. On the other hand, anti-osteoporosis drugs, such as antiresorptive or anabolic drugs, as well as drugs with a mixed mechanism of action, may affect carbohydrate metabolism, particularly in patients with diabetes. Therefore, the treatment of diabetes as well as osteoporosis prevention are vital for this group of patients.
Modulation of Inflammatory Responses by a Non-Invasive Physical Plasma Jet during Gingival Wound Healing
Authors: Eggers Benedikt , Stope Matthias Bernhard , Marciniak Jana , Mustea Alexander , Deschner James , Nokhbehsaim Marjan , Kramer Franz-Josef
Published: September 2022

Gingival wound healing plays an important role in the treatment of a variety of inflammatory diseases. In some cases, however, wound healing is delayed by various endogenous or exogenous factors. In recent years, non-invasive physical plasma (NIPP), a highly reactive gas, has become the focus of research, because of its anti-inflammatory and wound healing-promoting efficacy. So far, since NIPP application has been poorly elucidated in dentistry, the aim of this study was to further investigate the effect of NIPP on various molecules associated with inflammation and wound healing in gingival cells. Human gingival fibroblasts (HGF) and human gingival keratinocytes (HGK) were treated with NIPP at different application times. Cell viability and cell morphology were assessed using DAPI/phalloidin staining. Cyclooxygenase (COX)2; tumour necrosis factor (TNF); CC Motif Chemokine Ligand (CCL)2; and interleukin (IL)1B, IL6 and IL8 were analysed at the mRNA and protein level by a real-time PCR and ELISA. NIPP did not cause any damage to the cells. Furthermore, NIPP led to a downregulation of proinflammatory molecules. Our study shows that NIPP application does not damage the gingival tissue and that the promotion of wound healing is also due to an anti-inflammatory component.
Polyethylenimine-Based Electrochemical Sensor for the Determination of Caffeic Acid in Aromatic Herbs
Authors: Zamarchi Felipe , Silva Tânia Regina , Winiarski João Paulo , Santana Edson Roberto , Vieira Iolanda Cruz
Published: September 2022

An electrochemical sensor based on carbon paste modified with polyethyleneimine was developed and employed for the determination of caffeic acid in aromatic herbs. The sensor was prepared by mixing polyethylenimine (1.5% v/v), graphite powder, and mineral oil. The polyethylenimine-based electrode showed an enhancement of charge transfer at the electrode–solution interface and a higher current intensity for the electrochemical reaction of caffeic acid, in comparison to the unmodified electrode. The calibration plot of caffeic acid constructed in 0.1 mol L−1 acetate buffer (pH 5.0) by square wave voltammetry was linear in the range of 1.25 to 19.9 μmol L−1 with a limit of detection of 0.13 μmol L−1, respectively. Finally, the proposed sensor was employed to monitor the caffeic acid with accuracy in dried Thymus vulgaris and Salvia officinalis samples, with recovery results from 93 to 105%.
Association between Physical Fitness and Low Back Pain: The Pepe Cross-Sectional Study
Authors: Galmés-Panadés Aina M. , Vidal-Conti Josep
Published: September 2022

Background: Recent studies have shown that the lifetime prevalence of low back pain (LBP) in schoolchildren aged 10–12 years is 73.6%, and that it appears to have an impact on people’s quality of life. A wide range of risk factors associated with LBP have been studied. However, inconsistent results have been reported. In recent decades, the physical fitness level of children and adolescents has worsened, and the current data on the relationship between muscular fitness and musculoskeletal pain are ambiguous. The purpose of the present study was to analyze the relationship between physical fitness and the occurrence and intensity of LBP. Methods: This cross-sectional study assessed 849 students, aged 10–12 years, from 10 primary schools (fifth and sixth grades) from Majorca (Spain). It was based on two different structured and self-administered questionnaires and a fitness test battery validated for child populations. Results: The results showed that higher levels of VO2Max correspond to less LBP intensity. Additionally, LBP was less prevalent among participants who self-reported more physical activity, and higher VO2Max and higher levels of flexibility were associated with the absence of LBP in bed. Conclusion: These results are of particular importance, as cardiorespiratory fitness is the parameter most closely related to health, and it seems to also be related to LBP-prevention.
3D LiDAR Based SLAM System Evaluation with Low-Cost Real-Time Kinematics GPS Solution
Authors: Hensel Stefan , B. Marinov Marin , Obert Markus
Published: September 2022

Positioning mobile systems with high accuracy is a prerequisite for intelligent autonomous behavior, both in industrial environments and in field robotics. This paper describes the setup of a robotic platform and its use for the evaluation of simultaneous localization and mapping (SLAM) algorithms. A configuration using a mobile robot Husky A200, and a LiDAR (light detection and ranging) sensor was used to implement the setup. For verification of the proposed setup, different scan matching methods for odometry determination in indoor and outdoor environments are tested. An assessment of the accuracy of the baseline 3D-SLAM system and the selected evaluation system is presented by comparing different scenarios and test situations. It was shown that the hdl_graph_slam in combination with the LiDAR OS1 and the scan matching algorithms FAST_GICP and FAST_VGICP achieves good mapping results with accuracies up to 2 cm.
Using Transfer Learning to Train a Binary Classifier for Lorrca Ektacytometery Microscopic Images of Sickle Cells and Healthy Red Blood Cells
Authors: Butt Marya , de Keijzer Ander
Published: September 2022

Multiple blood images of stressed and sheared cells, taken by a Lorrca Ektacytometery microscope, needed a classification for biomedical researchers to assess several treatment options for blood-related diseases. The study proposes the design of a model capable of classifying these images, with high accuracy, into healthy Red Blood Cells (RBCs) or Sickle Cells (SCs) images. The performances of five Deep Learning (DL) models with two different optimizers, namely Adam and Stochastic Gradient Descent (SGD), were compared. The first three models consisted of 1, 2 and 3 blocks of CNN, respectively, and the last two models used a transfer learning approach to extract features. The dataset was first augmented, scaled, and then trained to develop models. The performance of the models was evaluated by testing on new images and was illustrated by confusion matrices, performance metrics (accuracy, recall, precision and f1 score), a receiver operating characteristic (ROC) curve and the area under the curve (AUC) value. The first, second and third models with the Adam optimizer could not achieve training, validation or testing accuracy above 50%. However, the second and third models with SGD optimizers showed good loss and accuracy scores during training and validation, but the testing accuracy did not exceed 51%. The fourth and fifth models used VGG16 and Resnet50 pre-trained models for feature extraction, respectively. VGG16 performed better than Resnet50, scoring 98% accuracy and an AUC of 0.98 with both optimizers. The study suggests that transfer learning with the VGG16 model helped to extract features from images for the classification of healthy RBCs and SCs, thus making a significant difference in performance comparing the first, second, third and fifth models.
Inverse Airborne Optical Sectioning
Authors: Amala Arokia Nathan Rakesh John , Kurmi Indrajit , Bimber Oliver
Published: September 2022

We present Inverse Airborne Optical Sectioning (IAOS), an optical analogy to Inverse Synthetic Aperture Radar (ISAR). Moving targets, such as walking people, that are heavily occluded by vegetation can be made visible and tracked with a stationary optical sensor (e.g., a hovering camera drone above forest). We introduce the principles of IAOS (i.e., inverse synthetic aperture imaging), explain how the signal of occluders can be further suppressed by filtering the Radon transform of the image integral, and present how targets’ motion parameters can be estimated manually and automatically. Finally, we show that while tracking occluded targets in conventional aerial images is infeasible, it becomes efficiently possible in integral images that result from IAOS.
Fast Terminal Sliding Mode Fault-Tolerant Control for Markov Jump Nonlinear Systems Based on an Adaptive Observer
Authors: Yang Pu , Shen Ziwei , Ding Yu , Feng Kejia
Published: September 2022

In this paper, a new adaptive observer is proposed to estimate the actuator fault and disturbance of a quadrotor UAV system with actuator failure and disturbance. Based on this, a nonsingular fast terminal sliding mode controller is designed. Firstly, according to the randomness of faults and disturbances, the UAV system under faults and disturbances is regarded as one of the Markov jump nonlinear systems (MJNSs). Secondly, an adaptive observer is designed to simultaneously observe the system state, fault, and disturbance. In order to improve the precision, the fast adaptive fault estimation (FAFE) algorithm is adopted in the adaptive observer. In addition, a quasi-one-sided Lipschitz condition is used to deal with the nonlinear term, which relaxes the condition and contains more nonlinear information. Finally, a nonsingular fast terminal sliding mode controller is designed for fault-tolerant control of the system. The simulation results show that the faults and disturbances can be observed successfully, and that the system is stochastic stable.
Capacity Optimization of Next-Generation UAV Communication Involving Non-Orthogonal Multiple Access
Authors: Sarfraz Mubashar , Sohail Muhammad Farhan , Alam Sheraz , Javvad ur Rehman Muhammad , Ghauri Sajjad Ahmed , Rabie Khaled , Abbas Hasan , Ansari Shuja
Published: September 2022

Unmanned air vehicle communication (UAV) systems have recently emerged as a quick, low-cost, and adaptable solution to numerous challenges in the next-generation wireless network. In particular, UAV systems have shown to be very useful in wireless communication applications with sudden traffic demands, network recovery, aerial relays, and edge computing. Meanwhile, non-orthogonal multiple access (NOMA) has been able to maximize the number of served users with the highest traffic capacity for future aerial systems in the literature. However, the study of joint optimization of UAV altitude, user pairing, and power allocation for the problem of capacity maximization requires further investigation. Thus, a capacity optimization problem for the NOMA aerial system is evaluated in this paper, considering the combination of convex and heuristic optimization techniques. The proposed algorithm is evaluated by using multiple heuristic techniques and deployment scenarios. The results prove the efficiency of the proposed NOMA scheme in comparison to the benchmark technique of orthogonal multiple access (OMA). Moreover, a comparative analysis of heuristic techniques for capacity optimization is also presented.
Respiration Detection of Ground Injured Human Target Using UWB Radar Mounted on a Hovering UAV
Authors: Jing Yu , Qi Fugui , Yang Fang , Cao Yusen , Zhu Mingming , Li Zhao , Lei Tao , Xia Juanjuan , Wang Jianqi , Lu Guohua
Published: September 2022

As an important and basic platform for remote life sensing, unmanned aerial vehicles (UAVs) may hide the vital signals of an injured human due to their own motion. In this work, a novel method to remove the platform motion and accurately extract human respiration is proposed. We utilized a hovering UAV as the platform of ultra-wideband (UWB) radar to capture human respiration. To remove interference from the moving UAV platform, we used the delay calculated by the correlation between each frame of UWB radar data in order to compensate for the range migration. Then, the echo signals from the human target were extracted as the observed multiple range channel signals. Owing to meeting the independent component analysis (ICA), we adopted ICA to estimate the signal of respiration. The results of respiration detection experiments conducted in two different outdoor scenarios show that our proposed method could accurately separate respiration of a ground human target without any additional sensor and prior knowledge; this physiological information will be essential for search and rescue (SAR) missions.
Optimization on Secondary Flow and Auxiliary Entrainment Inlets of an Ejector by Using Three-Dimensional Numerical Study
Authors: Yan Jia , Jiang Jing , Wang Zheng
Published: September 2022

In this paper, by using three-dimensional numerical simulations, the optimization of the cross-sectional area and angle of the secondary flow inlet is first conducted. Then, to further improve the ejector performance, an auxiliary entrainment is proposed and the optimization of the relative position, cross-sectional area and angle of the auxiliary entrainment inlet is accordingly performed by using three-dimensional methods. The results show that: (1) the performance of the ejector with the secondary flow in a vertical direction to the primary flow is slightly better than that in a parallel direction to the primary flow; (2) the effect of the cross-sectional area of the secondary flow has a relatively evident influence on ER, but its effect becomes ignored when the inlet area increases to a certain value; (3) the relative position and axial width of the auxiliary entrainment inlet are important factors influencing ejector performance, and after the optimization of these two geometries, the ejector ER can be increased by 97.7%; and (4) the optimization of the auxiliary entrainment inlet has a substantial effect on the ejector performance as compared to that of the secondary flow inlet. The novelty of this study is that the effect of an auxiliary entrainment on the ejector’s performance is identified by using a three-dimensional numerical simulation for the first time.
UPANets: Learning from the Universal Pixel Attention Neworks
Authors: Tseng Ching-Hsun , Lee Shin-Jye , Feng Jianan , Mao Shengzhong , Wu Yu-Ping , Shang Jia-Yu , Zeng Xiao-Jun
Published: September 2022

With the successful development in computer vision, building a deep convolutional neural network (CNNs) has been mainstream, considering the character of shared parameters in a convolutional layer. Stacking convolutional layers into a deep structure improves performance, but over-stacking also ramps up the needed resources for GPUs. Seeing another surge of Transformers in computer vision, the issue has aroused severely. A resource-hungry model is hardly implemented for limited hardware or single-customers-based GPU. Therefore, this work focuses on these concerns and proposes an efficient but robust backbone, which equips with channel and spatial direction attentions, so the attentions help to expand receptive fields in shallow convolutional layers and pass the information to every layer. An attention-boosted network based on already efficient CNNs, Universal Pixel Attention Networks (UPANets), is proposed. Through a series of experiments, UPANets fulfil the purposes of learning global information with less needed resources and outshine many existing SOTAs in CIFAR-{10, 100}.
Students’ Strategies When Dealing with Science-Based Information in Social Media—A Group Discussion Study
Authors: Belova Nadja , Krause Moritz , Siemens Christopher
Published: September 2022

As the world becomes increasingly complex, students must learn how to critically evaluate media messages and facts. Young people often obtain information from social media. Due to the ease with which information can be spread through such media, science misinformation is more prevalent. Learning how to critically evaluate information is expected to develop students’ abilities to critically evaluate science and media content. Group discussions were conducted with 33 secondary school students in northern Germany to examine (1) their experiences with social media in the (science) classroom, (2) their strategies for dealing with science-based information in the media, and (3) their perception of the role of social media in the science classroom. Qualitative coding revealed that students frequently use social media for information purposes, both in school and privately, and perceive social media as relevant to science education. In social media, they are successful at applying general media literacy and IT strategies, but struggle with science-related strategies. This study suggests that more opportunities should be provided for students to critique science information, and a greater focus should be placed on educating students about evaluation skills and scientific reasoning.
Impact of Digital Literacy and Problematic Smartphone Use on Life Satisfaction: Comparing Pre- and Post-COVID-19 Pandemic
Authors: Taskin Busra , Ok Chiho
Published: September 2022

Although the impact of digital literacy (DL) and problematic smartphone use (PSU) on life satisfaction was verified in previous literature, little is known about how the impact of two given variables can be differentiated during the COVID-19 pandemic situation. Thus, the purpose of this study was to empirically analyze whether the influence of DL and PSU on life satisfaction has changed as a consequence of the COVID-19 pandemic. We applied a cross-sectional study design to analyze data obtained from a nationwide survey on smartphone overdependence conducted in 2019 and 2020 by the South Korean Ministry of Science and ICT and the National Information Society Agency. Large-scale data obtained from 41,883 individuals were analyzed using hierarchical regression analysis. The results show that the positive relationship between digital literacy and life satisfaction was further strengthened post-COVID-19 rather than pre-COVID-19. In addition, the results suggest that the negative relationship between PSU and life satisfaction is further strengthened during post-COVID-19 rather than pre-COVID-19. The findings indicate that the roles of digital literacy and PSU are more important after the COVID-19 pandemic.
A Fault Detection Method Based on CNN and Symmetrized Dot Pattern for PV Modules
Authors: Wang Meng-Hui , Lin Zong-Han , Lu Shiue-Der
Published: September 2022

The photovoltaic (PV) module is a key technological advancement in renewable energy. When the PV modules fail, the overall generating efficiency will decrease, and the power system’s operation will be influenced. Hence, detecting the fault type when the PV modules are failing becomes important. This study proposed a hybrid algorithm by combining the symmetrized dot pattern (SDP) with a convolutional neural network (CNN) for PV module fault recognition. Three common faults are discussed, including poor welding, breakage, and bypass diode failure. Moreover, a fault-free module was added to the experiment for comparison. First, a high-frequency square signal was imported into the PV module, and the original signal was captured by the NI PXI-5105 high-speed data acquisition (DAQ) card for the hardware architecture. Afterward, the signal was imported into the SDP for calculation to create a snowflake image as the image feature for fault diagnosis. Finally, the PV module fault recognition was performed using CNN. There were 3200 test data records in this study, and 800 data records (200 data records of each fault) were used as test samples. The test results show that the recognition accuracy was as high as 99.88%. It is better than the traditional ENN algorithm, having an accuracy of 91.75%. Therefore, while capturing the fault signals effectively and displaying them in images, the proposed method accurately recognizes the PV modules’ fault types.
A Comparison between Solution-Based Synthesis Methods of ZrO2 Nanomaterials for Energy Storage Applications
Authors: Matias Maria Leonor , Carlos Emanuel , Branquinho Rita , do Valle Hadassa , Marcelino João , Morais Maria , Pimentel Ana , Rodrigues Joana , Monteiro Teresa , Fortunato Elvira , Martins Rodrigo , Nunes Daniela
Published: September 2022

The present study is focused on the synthesis of zirconium dioxide (ZrO2) nanomaterials using the hydrothermal method assisted by microwave irradiation and solution combustion synthesis. Both synthesis techniques resulted in ZrO2 powders with a mixture of tetragonal and monoclinic phases. For microwave synthesis, a further calcination treatment at 800 °C for 15 min was carried out to produce nanopowders with a dominant monoclinic ZrO2 phase, as attested by X-ray diffraction (XRD) and Raman spectroscopy. The thermal behavior of the ZrO2 nanopowder was investigated by in situ XRD measurements. From the scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images, the presence of near spherical nanoparticles was clear, and TEM confirmed the ZrO2 phases that comprised the calcinated nanopowders, which include a residual tetragonal phase. The optical properties of these ZrO2 nanopowders were assessed through photoluminescence (PL) and PL excitation (PLE) at room temperature (RT), revealing the presence of a broad emission band peaked in the visible spectral region, which suffers a redshift in its peak position, as well as intensity enhancement, after the calcination treatment. The powder resultant from the solution combustion synthesis was composed of plate-like structures with a micrometer size; however, ZrO2 nanoparticles with different shapes were also observed. Thin films were also produced by solution combustion synthesis and deposited on silicon substrates to produce energy storage devices, i.e., ZrO2 capacitors. The capacitors that were prepared from a 0.2 M zirconium nitrate-based precursor solution in 2-methoxyethanol and annealed at 350 °C exhibited an average dielectric constant (κ) of 11 ± 0.5 and low leakage current density of 3.9 ± 1.1 × 10−7 A/cm2 at 1 MV/cm. This study demonstrates the simple and cost-effective aspects of both synthesis routes to produce ZrO2 nanomaterials that can be applied to energy storage devices, such as capacitors.
Achieving Carbon Neutrality Pledge through Clean Energy Transition: Linking the Role of Green Innovation and Environmental Policy in E7 Countries
Authors: Yu Yang , Radulescu Magdalena , Ifelunini Abanum Innocent , Ogwu Stephen Obinozie , Onwe Joshua Chukwuma , Jahanger Atif
Published: September 2022

Most countries, notably those that signed the Paris Climate Agreement, prioritize achieving the zero carbon or carbon neutrality aim. Unlike earlier studies, this one assesses the contribution of environmental policy, clean energy, green innovation, and renewable energy to the E7 economies’ achievement of carbon neutrality goals from 1990 to 2019. Findings emanating from the study show that the EKC hypothesis is valid in E7 countries. Implying that emissions in the E7 countries increased with the kick-off of development but declined later due to possible potent environmental regulatory policies put in place. Similarly, across all models, renewable energy (REN), green innovations (GINNO), environmental tax (ETAX), and technological innovations (TECH) were found to exert a negative and significant impact on carbon emissions in the E7 countries both in the short and long run. On the other hand, economic expansion (GDP) positively impacts environmental deterioration. Furthermore, the country-specific result shows that, on average, Brazil, India, China, Russia, Mexico, and Indonesia have significant environmental policies aiding carbon abatement. Except for Brazil, Mexico, and Indonesia, the income growth in the rest of the countries does not follow the EKC proposition. Furthermore, the causality result revealed a unidirectional causal relationship between GDP, REN, and GINNO to CO2 emission. No causality was found between ETAX with CO2, while a bi-directional causality exists between technology and CO2 emissions. Based on the finding, policymakers in the E7 countries should move away from fossil fuels because future electricity output will not be sufficient to reduce emissions considerably. Environmental regulations, encouraging technological innovation, adopting green and sustainable technology, and clean energy sources, among other things, demand radical and broad changes.
Development of a Control-Oriented Ignition Delay Model for GCI Combustion
Authors: Silvagni Giacomo , Ravaglioli Vittorio , Falfari Stefania , Ponti Fabrizio , Mariani Valerio
Published: September 2022

Increasingly stringent pollutant emission limits and CO2 reduction policies are forcing the automotive industry toward cleaner and decarbonized mobility. The goal is to achieve carbon neutrality within 2050 and limit global warming to 2 °C (possibly 1.5 °C) with respect to pre-industrial levels as stated in both the European Green Deal and the Paris Agreement and further reiterated at the COP26. With the aim of simultaneously reducing both pollutants and CO2 emissions, a large amount of research is currently carried out on low-temperature highly efficient combustions (LTC). Among these advanced combustions, one of the most promising is Gasoline Compression Ignition (GCI), based on the spontaneous ignition of a gasoline-like fuel. Nevertheless, despite GCI proving to be effective in reducing both pollutants and CO2 emissions, GCI combustion controllability represents the main challenge that hinders the diffusion of this methodology for transportation. Several works in the literature demonstrated that to properly control GCI combustion, a multiple injections strategy is needed. The rise of pressure and temperature generated by the spontaneous ignition of small amounts of early-injected fuel reduces the ignition delay of the following main injection, responsible for the torque production of the engine. Since the combustion of the pre-injections is chemically driven, the ignition delay might be strongly affected by a slight variation in the engine control parameters and, consequently, lead to misfire or knocking. The goal of this work was to develop a control-oriented ignition delay model suitable to improve the GCI combustion stability through the proper management of the pilot injections. After a thorough analysis of the quantities affecting the ignition delay, this quantity was modeled as a function of both a thermodynamic and a chemical–physical index. The comparison between the measured and modeled ignition delay shows an accuracy compatible with the requirements for control purposes (the average root mean squared error between the measured and estimated start of combustion is close to 1.3 deg), over a wide range of operating conditions. As a result, the presented approach proved to be appropriate for the development of a model-based feed-forward contribution for a closed-loop combustion control strategy.
Experimental Study on the Compressive and Shear Mechanical Properties of Cement–Formation Interface Considering Surface Roughness and Drilling Mud Contamination
Authors: Wang Lei , Liu Bohang , Yang Hanzhi , Guo Yintong , Li Jing , Liu Hejuan
Published: September 2022

In a casing-cement sheath-formation system, the cement–formation interface is usually weakly cemented for the residual of drilling mud, in which a leakage path would easily form, threatening the safe operation of underground energy exploitation and storage. To evaluate the compressive and shear mechanical behavior of the cement–formation interface, cement–rock composite cylindrical specimens were prepared. Uniaxial and triaxial compression and direct shear tests were implemented. The flushing efficiency of the rock surface, compressive strength, interface incompatible deformation, parameters of shear strength, and morphology of shear failure surface were acquired and analyzed. Results show that the flushing efficiency of shale surface decreases from 76.7% to 64.2% with the surface roughness increasing from 0 to 2 mm. The flushing efficiency of sandstone is only 44.7%, remarkably lower than that of shale. With the stress condition transforming from uniaxial to triaxial compression, the feature of the stress–strain curves changes from elastic-brittle to elastoplastic, and the compressive strength increases from 20.6~60.1 MPa to 110~120 MPa. The cement part presents noteworthy plastic deformation and several micro shear fractures develop. There is incompatible deformation between cement and rock, which induces interface debonding for almost all the composite specimens. The internal friction angle and cohesive strength both decrease with the increase in pollution degree of drilling mud, and increase with the rise in surface roughness. The shear facture surface is not exactly the rock–cement interface, but usually manifests as a shear zone, in which the rock, cement, and interface all contribute to the final shear failure. The above findings would be valuable for the revealing of cement–formation interface failure mechanism.
Forecast of Coal Demand in Shanxi Province Based on GA—LSSVM under Multiple Scenarios
Authors: Liu Yujing , Du Ruoyun , Niu Dongxiao
Published: September 2022

Under the “carbon peaking and carbon neutrality” goal, Shanxi Province adjusts the power supply structure and promotes the development of a high proportion of new energy, which has a certain impact on the demand for thermal coal. Therefore, constructing a reasonable forecasting model for thermal coal demand can play a role in stabilizing coal supply and demand. This paper analyzes various factors related to coal demand, and uses Pearson coefficient to screen out six variables with strong correlation. Then, based on the scenario analysis method, combined with the “14th Five-Year Plan” of Shanxi Province, different scenarios of economic development and carbon emission reduction development are set. Finally, a multi-scenario GA–LSSVM forecasting model of thermal coal demand in Shanxi Province is constructed, and the future development trend of thermal coal demand in Shanxi Province is predicted. The results show that the demand for thermal coal is the largest in the mode of high-speed economic development and low emission reduction, and the demand for thermal coal is the lowest in the mode of low-speed economic development and strong emission reduction, which provides a scientific basis for the implementation of Shanxi Province’s thermal coal supply policy.
A Review of the Energy Potential of Residual Biomass for Coincineration in Kazakhstan
Authors: Askarova Aliya , Zamorano Montserrat , Martín-Pascual Jaime , Nugymanova Aizhan , Bolegenova Saltanat
Published: September 2022

Although it has access to hydrocarbon reserves, Kazakhstan has developed a strategy for the transition to a low-carbon economy, which should include the use of renewable energy sources. In this framework, the use of biomass from waste could have the potential to reduce emissions from traditionally fueled energy generation, as well as adding value to the generated waste, which also improves waste management according to the principles of a circular economy. The analysis of the resources and energy potential from residual biomass in Kazakhstan presents an annual production of 37.26 × 106 tons of residual biomass, which could be capable of producing an energy potential of 466.74 PJ/year, little more than half to the total production from all the installed power plants in the country. Agricultural, animal and municipal solid waste are available to produce energy in Kazakhstan based on combustion technologies; however, animal waste and agricultural are the main potential sources with 61.02% and 38.34% of the theoretical total biomass potential energy analyses, respectively. Considering that 80% of Kazakhstan’s electricity generation comes from coal-fired plants, energy from agriculture could be co-fired for the gradual replacement of coal with biomass in operational power plants, without substantially increasing costs or infrastructure investments, thereby making the transition to a low-carbon economy and renewable energy sources in the country easier.
Passionfruit (Passiflora edulis) Peel Powder Stimulates the Immune and Antioxidant Defense System in Nile Tilapia, Oreochromis niloticus, Cultivated in a Biofloc System
Authors: Outama Piyatida , Linh Nguyen Vu , Xuan Chinh Le , Wannavijit Supreya , Tongsiri Sudaporn , Chitmanat Chanagun , Montha Napatsorn , Van Doan Hien
Published: September 2022

This study aimed to assess the impacts of dietary supplementation with passionfruit (Passiflora edulis) peel powder (PSPP) on the growth, immune response, and expression of immune and antioxidant-related genes in Nile tilapia (Oreochromis niloticus) maintained in a biofloc system. Fish were fed basal diets supplemented with different doses of PSPP at 10 g kg−1 (PSPP10), 20 g kg−1 (PSPP20), 40 g kg−1 (PSPP40), and 80 g kg−1 (PSPP80). The basal diet, without PSPP-supplementation, was used as a control at 0 g kg−1 (PSPP0). We observed that the dietary supplementation groups fed different levels of PSPP exhibited no substantial difference or only slight increases in growth performance and immunological response in Nile tilapia (p > 0.05), whereas fish fed diets supplemented with PSPP at concentrations of 10 g kg−1, 20 g kg−1, and 40 g kg−1 had significantly higher mRNA transcripts (approximately 1.5–4.5 fold) of immune (il-1, il-8, and lbp) and antioxidant (gst-α, gpx, and gsr) gene expressions than fish in the control treatment group (0 g kg−1). These findings suggest that dietary supplementation with PSPP may effectively stimulate the immune and antioxidant defense system and may function as feed additives in Nile tilapia cultured in a biofloc system.
Development and Validation of a Quantitative Polymerase Chain Reaction Assay for the Detection of Red Sea Bream Iridovirus
Authors: Kim Kyung-Ho , Choi Kwang-Min , Kang Gyoungsik , Woo Won-Sik , Sohn Min-Young , Son Ha-Jeong , Yun Dongbin , Kim Do-Hyung , Park Chan-Il
Published: September 2022

The analytical and diagnostic performances of methods for detecting red sea bream iridovirus (RSIV), which infects marine fish, have not been evaluated. As disease management and transmission control depend on early and reliable pathogen detection, rapid virus detection techniques are crucial. Herein, we evaluated the diagnostic performance of a TaqMan-based real-time polymerase chain reaction (PCR) assay that detects RSIV rapidly and accurately. The assay amplified the RSIV, infectious spleen and kidney necrosis virus, and turbot reddish body iridovirus genotypes of Megalocytivirus and the detection limit was 10.96 copies/reaction. The assay’s performance remained uncompromised even in the presence of nine potential PCR inhibitors, including compounds commonly used in aquaculture. The variation of the cycle threshold values between assays performed by three technicians was evaluated using a plasmid DNA containing the major capsid protein gene sequence. The variation between replicates was low. The diagnostic sensitivity and specificity of the developed assay were evaluated using fish samples (n = 510) and were found to be 100% and 99.60%, respectively. Two technicians evaluated the reproducibility of the assay using fish samples (n = 90), finding a high correlation of 0.998 (p < 0.0001). Therefore, the newly developed real-time PCR assay detects RSIV both accurately and rapidly.
Heat Flux Measurement in Shock Heated Combustible Gases and Clarification of Ignition Delay Time
Authors: Kotov Mikhail A. , Kozlov Pavel V. , Gerasimov Gennady Ya. , Levashov Vladimir Yu. , Shemyakin Andrey N. , Solovyov Nikolay G. , Yakimov Mikhail Yu. , Glebov Vladislav N. , Dubrova Galina A. , Malyutin Andrey M.
Published: September 2022

Correct understanding of the ignition and combustion processes in the combustion chambers are critical for modeling advanced schemes of engines of high-speed aircraft and promising spacecraft. Moreover, experimental data on the ignition delay time are a universal basis for the development and testing of combustion kinetic models. Moreover, the higher the temperature of the fuel mixture, the smaller this time value and the more important its correct determination. The use of a thermoelectric detector allows to measure ignition delay times and record heat fluxes with a high time resolution (to tenths of μs) during ignition in propane–air mixtures. Due to the faster response time, the use of it allows refining the ignition delay time of the combustible mixture, and the detector itself can serve as a useful device that allows a more detailed study of the ignition processes.
Mechanism of Inosine Monophosphate Degradation by Specific Spoilage Organism from Grass Carp in Fish Juice System
Authors: Li Dapeng , Zhuang Shuai , Peng Yankun , Tan Yuqing , Hong Hui , Luo Yongkang
Published: September 2022

Microbial growth strongly affects the quality and flavor of fish and fish products. This study aimed to explore the role and function of grass carp-borne microorganisms in the degradation of inosine monophosphate (IMP) related compounds in a fish juice system during chill storage (4 °C. Prokaryotic transcriptomic analysis was used to explore the microbial contribution to metabolic pathways and related enzymes. The degree of microbial contribution was verified by the activity of enzymes and metabolite content. Collectively, there were multiple IMP relative product degradation pathways. A. rivipollensis degraded IMP by producing 5′-nucleotidase (5′-NT) while S. putrefaciens degraded IMP mainly by alkaline phosphatase (ALP). Hypoxanthine (Hx) was degraded to uric acid (Ua) induced by P. putida and S. putrefaciens mainly with producing xanthine oxidase (XOD), while A. rivipollensis almost could not produce XOD. This work can used as a guide and provide basic knowledge for the quality and flavor control of aquatic products.
PCR Mediated Nucleic Acid Molecular Recognition Technology for Detection of Viable and Dead Foodborne Pathogens
Authors: Chen Mengtao , Lan Xinyue , Zhu Longjiao , Ru Ping , Xu Wentao , Liu Haiyan
Published: September 2022

Living foodborne pathogens pose a serious threat to public and population health. To ensure food safety, it is necessary to complete the detection of viable bacteria in a short time (several hours to 1 day). However, the traditional methods by bacterial culture, as the gold standard, are cumbersome and time-consuming. To break through the resultant research bottleneck, PCR mediated nucleic acid molecular recognition technologies, including RNA-based reverse transcriptase PCR (RT-PCR) and DNA-based viability PCR (vPCR) have been developed in recent years. They not only sensitively amplify detection signals and quickly report detection results, but also distinguish viable and dead bacteria. Therefore, this review introduces these PCR-mediated techniques independent of culture for viable and dead foodborne pathogen detection from the nucleic acid molecular recognition principal level and describes their whole-process applications in food quality supervision, which provides a useful reference for the development of detection of foodborne pathogens in the future.
Modelling and Optimization of the Processing of a Healthy Snack Bar Made of Grape and Tomato Pomaces
Authors: Santiago-Ramos Rocío , Silva Cristina L. M. , Ramos Inês N.
Published: September 2022

A snack made of 36% by byproducts of grape and tomato pomaces was developed, also including other ingredients, such as oats, chia, quinoa, honey and peanut butter. The recipe was defined as tasty and healthy by a focus group. The snack was produced by using forced air at three different drying temperatures (50 °C, 60 °C and 70 °C). The Newton, Page, Henderson and Pabis, and Midilli–Kucuk models fit the drying curves well. The average values for the Newton’s model drying constants were k50 = 2.71 × 10−1 ± 3 × 10−3 min−1, k60 = 2.76 10−1 ± 4 × 10−3 min−1 and k70 = 3.91 × 10−1 ± 8 × 10−3 min−1 at 50 °C, 60 °C and 70 °C, respectively. The product’s quality was assessed in terms of storage with respect to water activity and texture (hardness, springiness, cohesiveness, chewiness and resilience). There were no differences among the three tested processing temperatures in terms of their influence the final product’s quality. As there were no significant differences between initial and final water activity and texture attributes at any temperature and they were mainly unaltered during storage, the snack bar was considered stable during this period. This new snack, which includes byproducts from the food industry, reduces food waste and contributes to a circular economic model, simultaneously presenting environmental and economic advantages.