bluuebunny/crossref_metadata_2025 huggingface dataset:
Mitochondrial VDAC1: A Potential Therapeutic Target of Inflammation-Related Diseases and Clinical Opportunities
Authors: Hu Hang , Guo Linlin , Overholser Jay , Wang Xing
Published: October 2022

The multifunctional protein, voltage-dependent anion channel 1 (VDAC1), is located on the mitochondrial outer membrane. It is a pivotal protein that maintains mitochondrial function to power cellular bioactivities via energy generation. VDAC1 is involved in regulating energy production, mitochondrial oxidase stress, Ca2+ transportation, substance metabolism, apoptosis, mitochondrial autophagy (mitophagy), and many other functions. VDAC1 malfunction is associated with mitochondrial disorders that affect inflammatory responses, resulting in an up-regulation of the body’s defensive response to stress stimulation. Overresponses to inflammation may cause chronic diseases. Mitochondrial DNA (mtDNA) acts as a danger signal that can further trigger native immune system activities after its secretion. VDAC1 mediates the release of mtDNA into the cytoplasm to enhance cytokine levels by activating immune responses. VDAC1 regulates mitochondrial Ca2+ transportation, lipid metabolism and mitophagy, which are involved in inflammation-related disease pathogenesis. Many scientists have suggested approaches to deal with inflammation overresponse issues via specific targeting therapies. Due to the broad functionality of VDAC1, it may become a useful target for therapy in inflammation-related diseases. The mechanisms of VDAC1 and its role in inflammation require further exploration. We comprehensively and systematically summarized the role of VDAC1 in the inflammatory response, and hope that our research will lead to novel therapeutic strategies that target VDAC1 in order to treat inflammation-related disorders.
Mitochondrial Distress in Methylmalonic Acidemia: Novel Pathogenic Insights and Therapeutic Perspectives
Authors: Keller Svenja Aline , Luciani Alessandro
Published: October 2022

Mitochondria are highly dynamic, double-membrane-enclosed organelles that sustain cellular metabolism and, hence, cellular, and organismal homeostasis. Dysregulation of the mitochondrial network might, therefore, confer a potentially devastating vulnerability to high-energy-requiring cell types, contributing to a broad variety of hereditary and acquired diseases, which include inborn errors of metabolism, cancer, neurodegeneration, and aging-associated adversities. In this Review, we highlight the biological functions of mitochondria-localized enzymes, from the perspective of understanding the pathophysiology of the inherited disorders destroying mitochondrial homeostasis and cellular metabolism. Using methylmalonic acidemia (MMA) as a paradigm of mitochondrial dysfunction, we discuss how mitochondrial-directed signaling pathways sustain the physiological homeostasis of specialized cell types and how these may be disturbed in disease conditions. This Review also provides a critical analysis of molecular underpinnings, through which defects in the autophagy-mediated quality control and surveillance systems contribute to cellular dysfunction, and indicates potential therapeutic strategies for affected tissues. These insights might, ultimately, advance the discovery and development of new therapeutics, not only for methylmalonic acidemia but also for other currently intractable mitochondrial diseases, thus transforming our ability to modulate health and homeostasis.
Broadband Dielectric Spectroscopic Detection of Aliphatic Alcohol Vapors with Surface-Mounted HKUST-1 MOFs as Sensing Media
Authors: Amoah Papa K. , Hassan Zeinab Mohammed , Franklin Rhonda R. , Baumgart Helmut , Redel Engelbert , Obeng Yaw S.
Published: October 2022

We leveraged chemical-induced changes to microwave signal propagation characteristics (i.e., S-parameters) to characterize the detection of aliphatic alcohol (methanol, ethanol, and 2-propanol) vapors using TCNQ-doped HKUST-1 metal-organic-framework films as the sensing material, at temperatures under 100 °C. We show that the sensitivity of aliphatic alcohol detection depends on the oxidation potential of the analyte, and the impedance of the detection setup depends on the analyte-loading of the sensing medium. The microwaves-based detection technique can also afford new mechanistic insights into VOC detection, with surface-anchored metal-organic frameworks (SURMOFs), which is inaccessible with the traditional coulometric (i.e., resistance-based) measurements.
A Mini Review: The Application of Eupatorium Plants as Potential Cosmetic Ingredients
Authors: Putri Agmi Sinta , Haqiqi Muhammad Taufiq , Supomo Supomo , Kusuma Irawan Wijaya , Kuspradini Harlinda , Rosamah Enih , Amirta Rudianto , Paramita Swandari , Ramadhan Rico , Lubis Muhammad Adly Rahandi , Ariyanta Harits Atika , Aswandi Aswandi , Kholibrina Cut Rizlani , Ismayati Maya , Fatriasari Widya , Tarmadi Didi , Yuliansyah Yuliansyah , Suwinarti Wiwin , Kim Yong-ung , Arung Enos Tangke
Published: October 2022

The Eupatorium plant has been well used in medication and as a decorative plant. Some studies have reported that this herb has biochemical compounds, such as sesquiterpenes, phenolics, polysaccharides, and pyrrolizidine alkaloids. Thus, it has pharmacological effects, including antifungal, antibacterial, cytotoxic, and antinociceptive properties, that can be utilized for cosmetic purposes. However, only a few published works have summarized the active compounds and the application of Eupatorium plants as cosmetic agents. Therefore, this article aims to review the application of Eupatorium plants as a potential cosmetic agent. The active compounds of Eupatorium are contained in the whole plant, as well as the stems, leaves, roots, and aerial parts (flower, fruit, and seeds). In terms of cosmetic applications, the activities of Eupathorium are antioxidant, anti-tyrosinase, anti-melanin/melanogenesis, anti-acne, and anti-inflammatory. This review aims to contribute to a better understanding for expanding the utilization of this plant for cosmetic purposes by using these active compounds.
Electro-Acoustic Properties of Scandium-Doped Aluminum Nitride (ScxAl1-xN) Material and its Application to Phononic Crystal-Coupled SAW Devices
Authors: Arab Fahima , Kanouni Fares , Serhane Rafik , Pennec Yan , Özer Zafer , Bouamama Khaled
Published: October 2022

Within the framework of the Density Functional Theory, the elastic, dielectric, and piezoelectric coefficients of w-ScxAl1−xN material were investigated for scandium (Sc) concentrations x = 0 to 0.375. The electro-acoustic properties are used to investigate the frequency response of the SAW delay line, based on the tilt θ° of the normal c-axis of the w-ScxAl1−xN piezoelectric thin film. We found that the piezoelectric response is improved as the Sc concentration increases, which is consistent with existing works in the literature. A 2D-phononic crystal pillars was then grafted on top of the surface, and the dependence of the acoustic band gaps is investigated with the help of the finite element method as a function of the Sc concentration and the tilted angle of w-Sc0.375Al0.625N. It was found that the two first band gaps exhibit a shift toward low frequencies with increasing Sc concentration. Moreover, the second acoustic bandgap is more sensitive to the inclination angle than the first. Furthermore, the insertion loss (S21) of w-Sc0.375Al0.625N is improved by 22 dB at θ° = 60°. The c-axis tilted Sc0.375Al0.625N-SAW delay line coupled with 2D-phononic crystals is a promising structure for low-loss and high-frequency SAW devices.
Radiomics Based on Nomogram Predict Pelvic Lymphnode Metastasis in Early-Stage Cervical Cancer
Authors: Xia Xueming , Li Dongdong , Du Wei , Wang Yu , Nie Shihong , Tan Qiaoyue , Gou Qiheng
Published: October 2022

The accurate prediction of the status of PLNM preoperatively plays a key role in treatment strategy decisions in early-stage cervical cancer. The aim of this study was to develop and validate a radiomics-based nomogram for the preoperative prediction of pelvic lymph node metastatic status in early-stage cervical cancer. One hundred fifty patients were enrolled in this study. Radiomics features were extracted from T2-weighted MRI imaging (T2WI). Based on the selected features, a support vector machine (SVM) algorithm was used to build the radiomics signature. The radiomics-based nomogram was developed incorporating radiomics signature and clinical risk factors. In the training cohort (AUC = 0.925, accuracy = 81.6%, sensitivity = 70.3%, and specificity = 92.0%) and the testing cohort (AUC = 0.839, accuracy = 74.2%, sensitivity = 65.7%, and specificity = 82.8%), clinical models that combine stromal invasion depth, FIGO stage, and MTD perform poorly. The combined model had the highest AUC in the training cohort (AUC = 0.988, accuracy = 95.9%, sensitivity = 92.0%, and specificity = 100.0%) and the testing cohort (AUC = 0.922, accuracy = 87.1%, sensitivity = 85.7%, and specificity = 88.6%) when compared to the radiomics and clinical models. The study may provide valuable guidance for clinical physicians regarding the treatment strategies for early-stage cervical cancer patients.
Long-Term Functional Hyperemia after Uncomplicated Phacoemulsification: Benefits beyond Restoring Vision
Authors: Ćurić Ana , Bjeloš Mirjana , Bušić Mladen , Kuzmanović Elabjer Biljana , Rak Benedict , Vukojević Nenad
Published: October 2022

The purpose of the study was to investigate the long-term effects of uncomplicated phacoemulsification on macular perfusion using optical coherence tomography angiography (OCTA) in healthy aging subjects. OCTA was performed before phacoemulsification and 1 week, 1 month, 3 months, and 6 months after. Superficial vascular complex (formed of nerve fiber layer vascular plexus and superficial vascular plexus), deep vascular complex (formed of intermediate capillary plexus and deep capillary plexus), as well as choriocapillaris (CC) and large choroidal blood vessels were recorded. Significant changes of vascular parameters in 95 eyes of 95 patients reached plateau 1 week after surgery and remained stable up to 6 months, occurring in all retinal layers but not in choroid and CC. Statistically significant increases in retinal vessels area, vessels percentage area, total number of junctions, junctions density, and total and average vessels length were found, followed by the total number of end points and mean lacunarity decline, proving an increase in blood supply. The study confirmed that uncomplicated phacoemulsification leads to a long-term increase in macular retinal perfusion. The results might ease the decision regarding timing for cataract surgery as long-term perfusion benefits can be achieved. Furthermore, study results provide a normative database of retinal and choroidal vasculature in healthy aging patients.
Sliding Mode Disturbance Observer-Based Adaptive Dynamic Inversion Fault-Tolerant Control for Fixed-Wing UAV
Authors: Dong Zhe , Liu Kai , Wang Shipeng
Published: October 2022

Unmanned aerial vehicles (UAVs) have been widely applied over the past decades, especially in the military field. Due to the unpredictability of the flight environment and failures, higher requirements are placed on the design of the control system of the fixed-wing UAV. In this study, a sliding mode disturbance observer-based (SMDO) adaptive dynamic inversion fault-tolerant controller was designed, which includes an outer-loop sliding mode observer-based disturbance suppression dynamic inversion controller and an inner-loop real-time aerodynamic identification-based adaptive fault-tolerant dynamic inversion controller. The sliding mode disturbance observer in the outer-loop controller was designed based on the second-order super-twisting algorithm to alleviate chattering. The aerodynamic identification in the inner-loop controller adopts the recursive least squares algorithm to update the aerodynamic model of the UAV online, thereby realizing the fault-tolerant control for the control surface damage. The effectiveness of the proposed SMDO enhanced adaptive fault-tolerant control method was validated by mathematical simulation.
Collaborative Optimal Formation Control for Heterogeneous Multi-Agent Systems
Authors: Li Yandong , Liu Meichen , Lian Jiya , Guo Yuan
Published: October 2022

In this paper, the distributed optimal control method is used to study the cooperative formation of heterogeneous multi-agents in the air–ground environment. The considered system consists of an unmanned aerial vehicle (UAV) and an unmanned ground vehicle (UGV). The optimal control theory is introduced into the formation control protocol, the distributed optimal formation control protocol is designed, and the stability is verified by graph theory. Furthermore, the cooperative optimal formation control protocol is designed, and the stability is analyzed using a block Kronecker product and matrix transformation theory. Through the comparison of simulation results, the introduction of optimal control theory shortens the formation time of the system and accelerates the convergence speed of the system.
Theoretical and Experimental Study on the Impact of Long-Wave Radiation on the Greenhouse Effect of a Prefabricated Temporary House
Authors: Wen Qian , Long Enshen
Published: October 2022

In this paper, an experimental rig of a prefabricated temporary house (PTH) was first established. Then, predicted models for the thermal environment of the PTH with and without considering long-wave radiation were developed. Next, the exterior-surface, interior-surface and indoor temperatures of the PTH were calculated by using the predicted models. The calculated results were then compared with the experimental results to study the influence of long-wave radiation on the predicted characteristic temperature of the PTH. Finally, the predicted models were used to calculate the cumulative annual hours and the intensity of the greenhouse effect of four different climate cities (Harbin, Beijing, Chengdu, Guangzhou, China). The results showed that: (1) the predicted temperature values of the model considering long-wave radiation were closer to the experimental results; (2) the effect level of the long-wave radiation on the three characteristic temperatures of the PTH from big to small was: exterior-surface temperature, interior-surface temperature, and indoor temperature; (3) the long-wave radiation had the greatest impact on the predicted temperature value of the roof; (4) under different climate conditions, the cumulative annual hours and the intensity of the greenhouse effect considering long-wave radiation were smaller than those without considering long-wave radiation; (5) the duration of the greenhouse effect considering and ignoring long-wave radiation varied significantly with the climate region, and that in Guangzhou was the longest, followed by Beijing and Chengdu, and that in Harbin was the shortest.
Higher Education Institution beyond the COVID-19 Pandemic—Evidence from Romania
Authors: David Sofia , Manea Ludmila Daniela , Virlanuta Florina Oana , Bărbuță-Mișu Nicoleta , Șorcaru Iulian Adrian
Published: October 2022

The COVID-19 pandemic has profoundly affected the education system in Romania. The major objective of this study was to identify the challenges in higher education institutions beyond the COVID-19 pandemic. Our study is based on a questionnaire-type analysis with 388 respondents (students from different universities). Using the SEM-PLS method, we designed a conceptual model, which is based on seven latent variables: a resilient education system in the context of the COVID-19 pandemic (SER); teacher–student, student–teacher, and student–institution communication (PS); logistical assistance from the educational institution (AL); adaptation according to knowledge-economy requirements (EC); online teaching–learning in higher education (API); a hybrid education model (EH); and digital skills and the integration of digital technology in institutions (ITE). We formulated seven hypotheses in order to test the strength of the correlation between the latent variables. Our research highlights a significant correlation between logistical assistance from the educational institution (LA) and teacher–student, student–teacher, and student–institution (PS) communication. Moreover, logistical assistance from the educational institution (LA) has a significant effect on the teaching–learning activity.
Multi-Label Vulnerability Detection of Smart Contracts Based on Bi-LSTM and Attention Mechanism
Authors: Qian Shenyi , Ning Haohan , He Yaqiong , Chen Mengqi
Published: October 2022

Smart contracts are decentralized applications running on blockchain platforms and have been widely used in a variety of scenarios in recent years. However, frequent smart contract security incidents have focused more and more attention on their security and reliability, and smart contract vulnerability detection has become an urgent problem in blockchain security. Most of the existing methods rely on fixed rules defined by experts, which have the disadvantages of single detection type, poor scalability, and high false alarm rate. To solve the above problems, this paper proposes a method that combines Bi-LSTM and an attention mechanism for multiple vulnerability detection of smart contract opcodes. First, we preprocessed the data to convert the opcodes into a feature matrix suitable as the input of the neural network and then used the Bi-LSTM model based on the attention mechanism to classify smart contracts with multiple labels. The experimental results show that the model can detect multiple vulnerabilities at the same time, and all evaluation indicators exceeded 85%, which proves the effectiveness of the method proposed in this paper for multiple vulnerability detection tasks in smart contracts.
FedZaCt: Federated Learning with Z Average and Cross-Teaching on Image Segmentation
Authors: Yang Tingyang , Xu Jingshuang , Zhu Mengxiao , An Shan , Gong Ming , Zhu Haogang
Published: October 2022

In Federated Learning (FL), data communication among clients is denied. However, it is difficult to learn from the decentralized client data, which is under-sampled, especially for segmentation tasks that need to extract enough contextual semantic information. Existing FL studies always average client models to one global model in segmentation tasks while neglecting the diverse knowledge extracted by the models. To maintain and utilize the diverse knowledge, we propose a novel training paradigm called Federated Learning with Z-average and Cross-teaching (FedZaCt) to deal with segmentation tasks. From the model parameters’ aspect, the Z-average method constructs individual client models, which maintain diverse knowledge from multiple client data. From the model distillation aspect, the Cross-teaching method transfers the other client models’ knowledge to supervise the local client model. In particular, FedZaCt does not have the global model during the training process. After training, all client models are aggregated into the global model by averaging all client model parameters. The proposed methods are applied to two medical image segmentation datasets including our private aortic dataset and a public HAM10000 dataset. Experimental results demonstrate that our methods can achieve higher Intersection over Union values and Dice scores.
An Adaptive Noise Reduction Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries
Authors: Qu Wenyu , Chen Guici , Zhang Tingting
Published: October 2022

Lithium-ion batteries are widely used in the electric vehicle industry due to their recyclability and long life. However, a failure of lithium-ion batteries can cause some catastrophic accidents, such as electric car battery explosion fires and so on. To prevent such harm from occurring, it is essential to monitor the remaining useful life of lithium-ion batteries and give early warning. In this paper, an adaptive noise reduction approach is proposed to predict the RUL (Remaining Useful Life) of lithium-ion batteries, which uses CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) combined with wavelet decomposition to achieve adaptive noise reduction decomposition, and then inputs the obtained IMF (Intrinsic Mode Function) components into LS–RVM (Least Square Relevance Vector Machine) for training, prediction, and reconstruction, so as to achieve high-precision prediction of RUL. Moreover, in order to verify the validity of the model, the model in this paper is compared with other common models. The results demonstrate that the RMSE, MAPE, and MAE of the proposed model are 0.008678, 0.005002, and 0.006894, and that it has higher accuracy than the other common prediction models.
Multiagent Reinforcement Learning Based on Fusion-Multiactor-Attention-Critic for Multiple-Unmanned-Aerial-Vehicle Navigation Control
Authors: Jeon Sangwoo , Lee Hoeun , Kaliappan Vishnu Kumar , Nguyen Tuan Anh , Jo Hyungeun , Cho Hyeonseo , Min Dugki
Published: October 2022

The proliferation of unmanned aerial vehicles (UAVs) has spawned a variety of intelligent services, where efficient coordination plays a significant role in increasing the effectiveness of cooperative execution. However, due to the limited operational time and range of UAVs, achieving highly efficient coordinated actions is difficult, particularly in unknown dynamic environments. This paper proposes a multiagent deep reinforcement learning (MADRL)-based fusion-multiactor-attention-critic (F-MAAC) model for multiple UAVs’ energy-efficient cooperative navigation control. The proposed model is built on the multiactor-attention-critic (MAAC) model, which offers two significant advances. The first is the sensor fusion layer, which enables the actor network to utilize all required sensor information effectively. Next, a layer that computes the dissimilarity weights of different agents is added to compensate for the information lost through the attention layer of the MAAC model. We utilize the UAV LDS (logistic delivery service) environment created by the Unity engine to train the proposed model and verify its energy efficiency. The feature that measures the total distance traveled by the UAVs is incorporated with the UAV LDS environment to validate the energy efficiency. To demonstrate the performance of the proposed model, the F-MAAC model is compared with several conventional reinforcement learning models with two use cases. First, we compare the F-MAAC model to the DDPG, MADDPG, and MAAC models based on the mean episode rewards for 20k episodes of training. The two top-performing models (F-MAAC and MAAC) are then chosen and retrained for 150k episodes. Our study determines the total amount of deliveries done within the same period and the total amount done within the same distance to represent energy efficiency. According to our simulation results, the F-MAAC model outperforms the MAAC model, making 38% more deliveries in 3000 time steps and 30% more deliveries per 1000 m of distance traveled.
Hydropower in the Energy Market in Poland and the Baltic States in the Light of the Challenges of Sustainable Development-An Overview of the Current State and Development Potential
Authors: Chomać-Pierzecka Ewa , Kokiel Andrzej , Rogozińska-Mitrut Joanna , Sobczak Anna , Soboń Dariusz , Stasiak Jacek
Published: October 2022

The energy crisis is affecting a number of countries, but particularly those that are heavily dependent on the traditional energy generation formula (e.g., Poland), as well as those neighbouring the territory of the ongoing war in Ukraine, i.e., Poland, Lithuania, Latvia and Estonia. With this in mind, the authors of this study decided to explore the issue of water energy as a source of green (cheap and environmentally safe) energy in these countries. The main objective of the paper is to review the available literature, which is needed to identify the role hydropower plays in energy security and energy transition in these energy markets. This paper is based on a review and critical appraisal of the available literature and studies together with an inference. The structure of the paper consists of an introduction, the main part of the review and conclusions. The geopolitical location and socio-economic conditions of the adopted set of countries, form the basis of the review of the existing literature on the theme explored and the substantive inference. The main findings of this review indicate that the literature is most strongly focused on the overall assessment of the energy transition of the adopted countries for review, where the hydropower thread is most often taken up as one source of renewable energy supply. Hydropower, due to its relatively low share in the energy systems of the adopted set of countries, is, according to the authors, insufficiently explored. The most significant gap relates to the aspect of the potential for hydropower development in these areas, considering both the construction of new hydropower plants and opportunities signalled in the literature for the modernisation or restoration of existing ones. In this respect, the need for analyses (studies and simulations) of hydropower development, considering the economic benefits associated with their development juxtaposed with the safety dimension of this course of action for the environment (analysis and assessment of environmental costs) is indicated, which is the main recommendation of the review.
Review of Renewable Energy Subsidy System in China
Authors: Song Dongdong , Jia Boya , Jiao Hongtao
Published: October 2022

In the context of the ‘carbon peaking and carbon neutrality goals’, renewable energy, with its clean and low-carbon characteristics, has become one of the key driving forces for sustainable development in China. However, the inherent disadvantages of the renewable energy industry, such as high initial investment costs, technical difficulties, and slow returns on investment, make it difficult to compete with traditional fossil energy sources in the market economy at the initial stage of its establishment. Therefore, after considering the environmental and ecological value, economic value, and industrial growth dilemma brought by the development of renewable energy industry, subsidies as a governmental incentive measure were created to support the development and growth of the renewable energy industry. At present, there are many problems with China’s renewable energy subsidy policy in practice, such as fragmented institutional policies, lack of procedural regulations, and lagging subsidy funds. The excellent legislative practice experience of foreign countries can be borrowed by China to make up for the corresponding loopholes and, on the basis of fully examining the specific conditions of China, to promote the progressive reform of China’s renewable energy subsidy system; form a trinity system of law, general strategy, and specific policies; strengthen collaboration; and enhance its scientific level. At the same time, China can actively broaden the sources of subsidy funds, explore diversified financing methods, further standardize the subsidy procedures, strengthen the supervision in implementation, and enhance the efficiency of the utilization of funds, so as to enhance the legalization of the subsidy system.
Biometric Authentication-Based Intrusion Detection Using Artificial Intelligence Internet of Things in Smart City
Authors: Annadurai C. , Nelson I. , Devi K. , Manikandan R. , Jhanjhi N. , Masud Mehedi , Sheikh Abdullah
Published: October 2022

Nowadays, there is a growing demand for information security and security rules all across the world. Intrusion detection (ID) is a critical technique for detecting dangers in a network during data transmission. Artificial Intelligence (AI) methods support the Internet of Things (IoT) and smart cities by creating gadgets replicating intelligent behavior and enabling decision making with little or no human intervention. This research proposes novel technique for secure data transmission and detecting an intruder in a biometric authentication system by feature extraction with classification. Here, an intruder is detected by collecting the biometric database of the smart building based on the IoT. These biometric data are processed for noise removal, smoothening, and normalization. The processed data features are extracted using the kernel-based principal component analysis (KPCA). Then, the processed features are classified using the convolutional VGG−16 Net architecture. Then, the entire network is secured using a deterministic trust transfer protocol (DTTP). The suggested technique’s performance was calculated utilizing several measures, such as the accuracy, f-score, precision, recall, and RMSE. The simulation results revealed that the proposed method provides better intrusion detection outcomes.
Multi-Step Ahead Natural Gas Consumption Forecasting Based on a Hybrid Model: Case Studies in The Netherlands and the United Kingdom
Authors: Zhang Longfeng , Ma Xin , Zhang Hui , Zhang Gaoxun , Zhang Peng
Published: October 2022

With worldwide activities of carbon neutrality, clean energy is playing an important role these days. Natural gas (NG) is one of the most efficient clean energies with less harmful emissions and abundant reservoirs. This work aims at developing a swarm intelligence-based tool for NG forecasting to make more convincing projections of future energy consumption, combining Extreme Gradient Boosting (XGBoost) and the Salp Swarm Algorithm (SSA). The XGBoost is used as the core model in a nonlinear auto-regression procedure to make multi-step ahead forecasting. A cross-validation scheme is adopted to build a nonlinear programming problem for optimizing the most sensitive hyperparameters of the XGBoost, and then the nonlinear optimization is solved by the SSA. Case studies of forecasting the Natural gas consumption (NGC) in the United Kingdom (UK) and Netherlands are presented to illustrate the performance of the proposed hybrid model in comparison with five other intelligence optimization algorithms and two other decision tree-based models (15 hybrid schemes in total) in 6 subcases with different forecasting steps and time lags. The results show that the SSA outperforms the other 5 algorithms in searching the optimal parameters of XGBoost and the hybrid model outperforms all the other 15 hybrid models in all the subcases with average MAPE 4.9828% in NGC forecasting of UK and 9.0547% in NGC forecasting of Netherlands, respectively. Detailed analysis of the performance and properties of the proposed model is also summarized in this work, which indicates it has high potential in NGC forecasting and can be expected to be used in a wider range of applications in the future.
Possibilities of Using Zeolites Synthesized from Fly Ash in Adsorption Chillers
Authors: Mlonka-Mędrala Agata , Hasan Tarikul , Kalawa Wojciech , Sowa Marcin , Sztekler Karol , Pinto Moises Luzia , Mika Łukasz
Published: October 2022

Adsorption chillers produce cold energy, using heat instead of electricity, thus reducing electrical energy consumption. A major industrial waste, fly ash, can be converted to zeolite and used in adsorption chillers as an adsorbent. In this research, three different types of zeolites were synthesised from fly ash via a hydrothermal reaction in an alkaline solution (NaOH). The obtained samples (Na-A zeolites) were modified with K2CO3 to increase the water adsorption capacity of these samples. Phase and morphology analyses shows that desired zeolites formed properly but other crystalline phases also exist along with nonporous amorphous phases. The determined specific surface areas for Na-A zeolite (12 h) and Na-A zeolite (24 h) are 45 m2/g and 185 m2/g respectively, while the specific surface area for synthesized 13X zeolite is almost negligible. Water-isotherm for each of these samples was measured. Considering the application of adsorption chillers, average adsorption capacity was very low, 1.73% and 1.27%, respectively, for the two most probable operating conditions for synthesized 13X zeolite, whereas no water was available for the evaporation from Na-A zeolite (12 h) and Na-A zeolite (24 h). This analysis implies that among the synthesized materials only 13X zeolite has a potential as an adsorber in sorption chillers.
Design of Battery Thermal Management System with Considering the Longitudinal and Transverse Temperature Difference
Authors: Dong Junhao , Lu Xipo , Sun Yang , Mitin Vladislav , Xu Huaping , Kong Wei
Published: October 2022

For a bottom-liquid-cooled battery thermal management system (BTMS), the small contact area between the battery bottom and the cold plate leads to a large temperature difference in the battery height direction. In addition, the increase in coolant temperature from the inlet to the outlet results in an excessive temperature difference in the battery module in the coolant flow direction. In order to solve the above issues, a wavy channel was first designed to strengthen the heat exchange between the battery bottom and the cold plate. The maximum battery module temperature for the wavy-channel design is 29.61 °C, which is a reduction of 1.75 °C compared to the straight-channel design. Then, the transverse temperature difference in the battery module was reduced by introducing a composite-channel design. Finally, on the basis of the composite channel, phase change material (PCM) was added to the battery’s top surface to reduce the temperature difference in the battery height direction. The results show that the maximum temperature and maximum temperature difference in the battery module of the composite-channel/PCM design proposed in this study are reduced by 6.8% and 41%, respectively, compared with the conventional straight-channel design.
Geometry, Mesh and Numerical Scheme Influencing the Simulation of a Pelton Jet with the OpenFOAM Toolbox
Authors: Decaix Jean , Münch-Alligné Cécile
Published: October 2022

Hydropower is a key source of electricity production for allowing the integration of intermittent renewable energy resources. Among the various hydraulic power plants around the world, the ones equipped with Pelton turbines already provide large flexibility that is still enhanced with the development, for instance, of the hydraulic short circuit operating mode. However, the knowledge of the flow inside Pelton turbines is still a challenging task, both numerically and experimentally, despite progress in the last two decades. One key feature of the Pelton efficiency is the jet quality, i.e., the jet velocity needs to be uniform, not perturbed by secondary flows and compact. The compactness of the jet is mainly dependent o nthe location of the jet detachment at the nozzle outlet, which is challenging for computational fluid dynamics simulations mainly due to numerical diffusion. Even if this point has already been mentioned in previous papers, the present paper focuses on all the parameters that can influence the jet detachment: the nozzle geometry, the mesh and the numerical scheme used to discretize the convective fluxes. The simulations of an existing Pelton injector are performed using the OpenFOAM toolbox. It is noticed that, in addition to the nozzle geometry and the mesh resolution at the nozzle outlet, the choice of the numerical schemes influences the jet detachment and, consequently, the jet diameter and discharge. The use of an anti-diffusive scheme such as the “SUPERBEE” limiter improves the prediction of the jet in accordance with the on-site measurements.
Conservation Genetics of the Rare and Endangered Tree Species, Camellia nitidissima (Theaceae), Inferred from Microsatellite DNA Data
Authors: Chen Zongyou , Wang Junfang , Tang Jianmin , Wang Zhengfeng , Chai Shengfeng , He Xingjin , Wei Xiao
Published: October 2022

Camellia nitidissima Chi, is a rare and endangered plant that is narrowly distributed in South China and North Vietnam. In this study, seven polymorphic microsatellite markers were used to investigate the genetic diversity, recent population bottlenecks as well as population structure of twelve remnant populations of the plant. Our results indicated that, despite their severely fragmented natural range, C. nitidissima remnants maintained a moderate level of genetic variability, and only a bottlenecked population was detected by the clear evidences. No significant correlation was found between genetic diversity and population size. Significantly high genetic differences among populations were found, and the twelve populations could be classified into two distinct genetic groups. AMOVA indicated that 16.14% (16.73%, after one suspected artificial population was excluded) of the molecular variation was attributable to regional divergences (between Nanning and Fangcheng), and the majority of genetic variation existed within populations which were 69.24% (70.63%, after one suspected artificial population was excluded). For conservation management plans, the genetic resources of the two distinct groups are of equal importance for conservation, separate management unit for each of them should be considered. Given that all remnant populations are small and isolated, and many plants are illegally dug out for commercial purposes, management efforts in terms of habitat protection and legal protection, as well as transplantations and reintroductions, would be necessary for this species.
Transcriptome-Based Analysis of the Response Mechanism of Leopard Coralgrouper Liver at Different Flow Velocities
Authors: Yang Min , Gao Jin , Ke Hongji , Wang Yongbo , Liu Jinye , Wen Xin , Fu Shuyuan , Wang Jiang
Published: October 2022

The velocity of water can cause differences in the growth of inhabitant fish, thereby functioning as an important aquatic environmental factor. In order to explore the response mechanism of Leopard Coralgrouper (Plectropomus leopardus) under different flow velocities, P. leopardus fish of the same sizes were fed in water characterized by three different flow rates (5 cm/s, 10 cm/s, and 20 cm/s) for 150 d, after which the differences in growth and the levels of liver oxidative stress kinase were analyzed. Additionally, potential underlying regulatory pathways were explored using comparative transcriptomic approaches. The results showed that in the feeding environment involving a flow rate of 10 cm/s, the weight increase of P. leopardus and its liver contents of glutathione peroxidase (GPX), alanine aminotransferase (ALT), and superoxide dismutase (T-SOD) were significantly higher than for the other two groups. After matching the comparative transcriptomic results between group pairs (5 cm/s and 10 cm/s, 5 cm/s and 20 cm/s, and 10 cm/s and 20 cm/s), a total of 225 common differential gene expressions were screened. The KEGG pathway enrichment analysis showed that these genes were mainly involved in protein processing in the endoplasmic reticulum, the TGF-β signaling pathway, fatty acid metabolism, fatty acid synthesis, and other pathways. These results not only provide a theoretical basis for the selection of flow velocity in the culture environment of P. leopardus, but also reveal its potential means of adaption to different flow velocities.
Nitric Oxide Made a Major Contribution to the Improvement of Quality in Button Mushrooms (Agaricus bisporus) by the Combined Treatment of Nitric Oxide with 1-MCP
Authors: Wang Xiaoyu , Yang Zhifeng , Cui Jinxia , Zhu Shuhua
Published: October 2022

Browning is one of the major effects of shelf-life responsible for the reduction in the commercial value of the button mushrooms (Agaricus bisporus). In this study, the individual and the combined effects of exogenous sodium nitroprusside (SNP, a nitric oxide donor) and 1-methylcyclopropene (1-MCP) on the quality of button mushrooms were evaluated. The results demonstrated that mushrooms treated with SNP+1-MCP promoted reactive oxygen species (ROS) metabolism thereby protecting cell membrane integrity, hindering polyphenol oxidase (PPO) binding to phenolic compounds, and downregulating the PPO activity. In addition, the SNP+1-MCP treatment effectively maintained quality (firmness, color, total phenol, and flavonoid) and mitigated oxidative damage by reducing ROS accumulation and malondialdehyde production through the stimulation of the antioxidant enzymes activities and the enhancement of ascorbic acid (AsA) and glutathione (GSH) contents. Moreover, the correlation analysis validated the above results. The SNP+1-MCP treatment was observed to be more prominent on maintaining quality than the individual effects of SNP followed by 1-MCP, suggesting that the combination of NO and 1-MCP had synergistic effects in retarding button mushrooms senescence, and NO signaling molecules might be predominant in the synergy.
Vegan Ice Cream Made from Soy Extract, Soy Kefir and Jaboticaba Peel: Antioxidant Capacity and Sensory Profile
Authors: Mendonça Giovana M. N. , Oliveira Estela M. D. , Rios Alessandro O. , Pagno Carlos H. , Cavallini Daniela C. U.
Published: October 2022

Considering the need for functional foods and the use of by-products of the food industry, a potentially functional ice cream was developed, using soy extract, soy kefir and dehydrated jaboticaba peel. Five ice creams were produced using soy kefir (K) and soy extract (S): (1) GS—100% S; (2) GK1-75% S/25% K; (3) GK2-50% S/50% K; (4) GK3-25% S/75% K and (5) GK-100% K; The products were evaluated by physicochemical, microbiological and sensory (check all that apply) analyses. The addition of kefir was found to increase the acidity of the products. The concentrations of total phenolic compounds in the formulations with kefir were approximately ten times higher than the GS formulation. All products presented concentrations of thermotolerant coliforms <3 NMP/g and absence of Salmonella ssp. The viability of Lactobacillus ssp., Streptococcus spp. and Bifidobacterium ssp. was higher than 10 log CFU/g during the whole storage period. The GS and GK1 formulations had the lowest scores, while GK ice cream was preferred. The formulations showed distinct sensory profiles in the CATA, and the ice cream with 100% kefir was associated with desirable attributes. The ice creams exhibited microbiological and sensory characteristics that meet the expectations of the product’s target audience.
Lignocellulosic Biomasses from Agricultural Wastes Improved the Quality and Physicochemical Properties of Frying Oils
Authors: Ahmed Eman , Zeitoun Ashraf , Hamad Gamal , Zeitoun Mohamed A. M. , Taha Ahmed , Korma Sameh A. , Esatbeyoglu Tuba
Published: October 2022

In this work, the effects of using natural lignocellulosic-based adsorbents from sugarcane bagasse (SC), cornstalk piths (CP), and corn cob (CC) on the physicochemical properties and quality of fried oils were studied. The properties of lignocellulosic biomasses were examined using X-ray diffraction (XRD), scanning electron microscope (SEM), and Fourier transform infrared spectroscopy (FTIR). Moreover, the changes in the physicochemical properties of fresh, fried oils (for 4, 8, 12, 16 and 20 h) and adsorbents-treated oils were examined. The XRD results revealed that SC and CP biomasses have more amorphous regions than CC biomass, which had the highest crystallinity percentage. The results also showed that lignocellulosic biomasses enhanced the quality of the used oils. SC was the most effective biomass to enhance the properties of the used sunflower oil. For instance, the acid value of oil samples fried for 20 h reduced from 0.63 ± 0.02 to 0.51 ± 0.02 mg KOH/g oil after SC biomass treatment. For the peroxide value, the SC biomass treatment reduced it from 9.45 ± 0.56 (fried oil for 20 h) to 6.91 ± 0.12 meq O2/kg. Similarly, SC biomass adsorbent reduced the p-Anisidine Value (p-AV) of the used oil (20 h) from 98.45 ± 6.31 to 77.92 ± 3.65. Moreover, SC adsorbents slightly improved the lightness of the used oils (20 h). In conclusion, natural lignocellulosic biomasses, particularly SC, could be utilized as natural adsorbents to improve the oil quality. The results obtained from this study could help in developing sustainable methods to regenerate used oils using natural and cheap adsorbents.
Nuts as a Dietary Enrichment with Selected Minerals—Content Assessment Supported by Chemometric Analysis
Authors: Markiewicz-Żukowska Renata , Puścion-Jakubik Anna , Grabia Monika , Perkowski Jakub , Nowakowski Patryk , Bielecka Joanna , Soroczyńska Jolanta , Kańgowski Grzegorz , Bołtryk Jakub M. , Socha Katarzyna
Published: October 2022

Nuts used as a snack and meal accompaniment supply plant protein and fatty acids that are beneficial for human health; however, they can also provide minerals. The aim of this study was to determine the content of selected elements that are often deficient in the diet (calcium, potassium, magnesium, selenium, and zinc) in nuts and determine whether they can be used to supplement deficiencies in the diet. In this study, we analyzed 10 types of nuts (n = 120 samples) that are consumed and available for sale in Poland. The content of calcium, magnesium, selenium, and zinc was determined by the atomic absorption spectrometry method, and flame atomic emission spectrometry was used for determination of potassium contents. The highest median calcium content was found in almonds (2825.8 mg/kg), the highest potassium content in pistachio nuts (15,730.5 mg/kg), the highest magnesium and selenium contents in Brazil nuts (10,509.2 mg/kg and 4348.7 μg/kg, respectively), and the highest zinc content in pine nuts (72.4 mg/kg). All the tested nuts are a source of magnesium, eight types of tested nuts are a source of potassium, six nut types are a source of zinc, and four nut types are a source of selenium; however, among the tested nuts, only almonds can be considered a source of calcium. Moreover, we found that selected chemometric methods can be useful in the classification of nuts. The studied nuts are valuable products that can be used to supplement the diet with selected minerals and can therefore be labelled as functional products crucial for disease prevention.
Fermented Minor Grain Foods: Classification, Functional Components, and Probiotic Potential
Authors: Qin Huibin , Wu Houbin , Shen Ke , Liu Yilin , Li Meng , Wang Haigang , Qiao Zhijun , Mu Zhixin
Published: October 2022

Fermented minor grain (MG) foods often have unique nutritional value and functional characteristics, which are important for developing dietary culture worldwide. As a kind of special raw material in fermented food, minor grains have special functional components, such as trace elements, dietary fiber, and polyphenols. Fermented MG foods have excellent nutrients, phytochemicals, and bioactive compounds and are consumed as a rich source of probiotic microbes. Thus, the purpose of this review is to introduce the latest progress in research related to the fermentation products of MGs. Specific discussion is focused on the classification of fermented MG foods and their nutritional and health implications, including studies of microbial diversity, functional components, and probiotic potential. Furthermore, this review discusses how mixed fermentation of grain mixtures is a better method for developing new functional foods to increase the nutritional value of meals based on cereals and legumes in terms of dietary protein and micronutrients.