bluuebunny/crossref_metadata_2025 huggingface dataset:
Conversion of Coal-Biomass into Diesel by Using Aspen Plus
Authors: Bashir Bilal , Amin Muhammad , Fareed Anaiz Gul , Farooqi Zia Ur Rahman
Published: November 2022

Taking the importance of Pakistan’s dire need for energy breakthrough, in this paper, we explore how the country’s vast estimated reserves of 175 billion tons of Thar coal is a useful source for the clean and efficient production of good quality liquid fuel. Coal to liquid (CTL) technology has gathered increasing attention among many countries with a sufficient volume of coal reserves, and this technology can also be implemented in Pakistan, which in result can also reduce harmful greenhouse gas (GHG) emissions in the environment. In this study, the Fischer Tropsch Synthesis (FT) liquefaction method was used, and the reactor design, chemical reactions, syngas ratio fraction, and Anderson-Schulz-Flory and Langmuir model were all obtained from the Aspen Plus simulation. The results showed that, at the optimum syngas flow rate of 9 Kg/s, the FT model produced diesel fuel at 0.00134 Kg/s. Per this calculation, the massive amount of Thar coal reserves can be transformed into 123.22 million barrels of diesel. The design of the reactor is very critical, and, in this study, it was prioritized to design a reactor that produces liquid fuel only of composition C12+; during the production of liquid fuel, the quantity of methane is not high; and it can still be further reduced on optimized conditions. On the other hand, CO2 gas, which is a sole contributor of GHG emissions, was also reduced by up to 98%.
Initial Experience of Intra-Arterial Chemotherapy Using a Novel External Carotid Arterial Sheath System Combined with Radiotherapy and Systemic Chemotherapy for Locally Advanced Tongue Cancer
Authors: Nomura Miwako , Fuwa Nobukazu , Ito Shintaro , Toyomasu Yutaka , Takada Akinori , Kobayashi Daisuke , Fuke Tomohito , Taniguchi Masanori , Ii Noriko , Uraki Junji , Yamada Hiroyuki
Published: November 2022

We retrospectively evaluated the safety and effectiveness of an external carotid arterial sheath (ECAS) for intra-arterial chemotherapy (IACT) for locally advanced tongue cancer. Thirty-one patients with the Union for International Cancer Control’s 8th TNM stage III–IV tongue cancer underwent IACT using the ECAS combined with RT and systemic chemotherapy with either cisplatin and fluorouracil (FP) or docetaxel, cisplatin, and fluorouracil (TPF) between October 2015 and February 2021. The ECAS was inserted retrogradely via the superficial temporal artery, and the tip was placed in the external carotid artery between the maxillary and facial arteries. A microcatheter was inserted into each tumor-feeding artery through the ECAS under fluoroscopy, wherein cisplatin 50 mg/m2 was administered. IACT was performed weekly with neutralization using sodium thiosulfate. Complete response of the primary lesion was achieved in 28/31 (90%) patients. The median follow-up for all patients was 39 months. The 3-year overall survival, progression-free survival, and local control rates were 81.6%, 74.2%, and 83.4%, respectively. Grade 3 and greater toxicities included oral mucositis (45%), neutropenia (39%), nausea (13%), anemia (10%), thrombocytopenia (10%), dry mouth (10%), and fever (3%). There were no severe complications associated with IACT. In conclusion, the ECAS is feasible and effective for locally advanced tongue cancer.
Ab Initio Investigation of the Adsorption and Dissociation of O2 on Cu-Skin Cu3Au(111) Surface
Authors: Yu Yanlin , Liu Zhiming , Huang Wenxian , Zhou Shan , Hu Zuofu , Wang Ligen
Published: November 2022

Surface adsorption and dissociation processes can have a decisive impact on the catalytic properties of metal alloys. We have used density functional theory to investigate the adsorption and dissociation of O2 on Cu-skin Cu3Au(111) surface. The calculated results show that the b-f(h)-b adsorption configuration is the most energetically favorable on the Cu-skin Cu3Au(111) surface. For O2 dissociation, there are two thermodynamically favorable dissociation paths. One path is from b-f-b to two O atoms in hcp sites, and the other path is from b-h-b to two O atoms in fcc sites. Moreover, the stability of O2 adsorption is higher and the dissociation energy barrier of the adsorbed O2 is lower as compared to those on the Cu(111) surface. This theoretical work provides valuable guidance for the practical application of Cu-Au alloys as highly efficient CO oxidation catalysts.
Exploring Dynamic Metabolome of the HepG2 Cell Line: Rise and Fall
Authors: Kiseleva Olga I. , Kurbatov Ilya Yu. , Arzumanian Viktoriia A. , Ilgisonis Ekaterina V. , Vakhrushev Igor V. , Lupatov Alexey Yu. , Ponomarenko Elena A. , Poverennaya Ekaterina V.
Published: November 2022

Both biological and technical variations can discredit the reliability of obtained data in omics studies. In this technical note, we investigated the effect of prolonged cultivation of the HepG2 hepatoma cell line on its metabolomic profile. Using the GC × GC-MS approach, we determined the degree of metabolic variability across HepG2 cells cultured in uniform conditions for 0, 5, 10, 15, and 20 days. Post-processing of obtained data revealed substantial changes in relative abundances of 110 metabolites among HepG2 samples under investigation. Our findings have implications for interpreting metabolomic results obtained from immortal cells, especially in longitudinal studies. There are still plenty of unanswered questions regarding metabolomics variability and many potential areas for future targeted and panoramic research. However, we suggest that the metabolome of cell lines is unstable and may undergo significant transformation over time, even if the culture conditions remain the same. Considering metabolomics variability on a relatively long-term basis, careful experimentation with particular attention to control samples is required to ensure reproducibility and relevance of the research results when testing both fundamentally and practically significant hypotheses.
MicroRNAs in Cancer and Cardiovascular Disease
Authors: Ilieva Mirolyuba , Panella Riccardo , Uchida Shizuka
Published: November 2022

Although cardiac tumor formation is rare, accumulating evidence suggests that the two leading causes of deaths, cancers, and cardiovascular diseases are similar in terms of pathogenesis, including angiogenesis, immune responses, and fibrosis. These similarities have led to the creation of new exciting field of study called cardio-oncology. Here, we review the similarities between cancer and cardiovascular disease from the perspective of microRNAs (miRNAs). As miRNAs are well-known regulators of translation by binding to the 3′-untranslated regions (UTRs) of messenger RNAs (mRNAs), we carefully dissect how a specific set of miRNAs are both oncomiRs (miRNAs in cancer) and myomiRs (muscle-related miRNAs). Furthermore, from the standpoint of similar pathogenesis, miRNAs categories related to the similar pathogenesis are discussed; namely, angiomiRs, Immune-miRs, and fibromiRs.
The CRK5 and WRKY53 Are Conditional Regulators of Senescence and Stomatal Conductance in Arabidopsis
Authors: Burdiak Paweł , Mielecki Jakub , Gawroński Piotr , Karpiński Stanisław
Published: November 2022

In Arabidopsis thaliana, cysteine-rich receptor-like kinases (CRKs) constitute a large group of membrane-localized proteins which perceive external stimuli and transduce the signal into the cell. Previous reports based on their loss-of-function phenotypes and expression profile support their role in many developmental and stress-responsive pathways. Our study revealed that one member of this family, CRK5, acts as a negative regulator of leaf aging. Enrichment of the CRK5 promoter region in W-box cis-elements demonstrated that WRKY transcription factors control it. We observed significantly enhanced WRKY53 expression in crk5 and reversion of its early-senescence phenotype in the crk5 wrky53 line, suggesting a negative feedback loop between these proteins antagonistically regulating chlorophyll a and b contents. Yeast-two hybrid assay showed further that CRK5 interacts with several proteins involved in response to water deprivation or calcium signaling, while gas exchange analysis revealed a positive effect of CRK5 on water use efficiency. Consistent with that, the crk5 plants showed disturbed foliar temperature, stomatal conductance, transpiration, and increased susceptibility to osmotic stress. These traits were fully or partially reverted to wild-type phenotype in crk5 wrky53 double mutant. Obtained results suggest that WRKY53 and CRK5 are antagonistic regulators of chlorophyll synthesis/degradation, senescence, and stomatal conductance.
The Extension of Surgery Predicts Acute Postoperative Pain, While Persistent Postoperative Pain Is Related to the Spinal Pathology in Adolescents Undergoing Posterior Spinal Fusion
Authors: Yrjälä Tommi , Helenius Ilkka , Rissanen Tiia , Ahonen Matti , Taittonen Markku , Helenius Linda
Published: November 2022

Persistent pain after posterior spinal fusion affects 12 to 42% of patients with adolescent idiopathic scoliosis. The incidence of persistent pain among surgically treated children with Scheuermann kyphosis and spondylolisthesis is not known. The aim of our study was to determine the predictors and incidence of acute and chronic postoperative pain in adolescents undergoing posterior spinal fusion surgery. The study was a retrospective analysis of a prospectively collected pediatric spine register data. The study included 213 consecutive patients (158 AIS, 19 Scheuermann kyphosis, and 36 spondylolisthesis), aged 10–21 years undergoing posterior spinal fusion at a university hospital between March 2010 and March 2020. The mean (SD) daily postoperative opioid consumption per kilogram was significantly lower in the spondylolisthesis patients 0.36 mg/kg/day (0.17) compared to adolescent idiopathic scoliosis 0.51 mg/kg/day (0.25), and Scheuermann kyphosis 0.52 mg/kg/day (0.25) patients after surgery (p = 0.0004). Number of levels fused correlated with the daily opioid consumption (rs = 0.20, p = 0.0082). The SRS-24 pain domain scores showed a statistically significant improvement from preoperative levels to two-year follow-up in all three groups (p ≤ 0.03 for all comparisons). The spondylolisthesis patients had the lowest SRS pain domain scores (mean 4.04, SD 0.94), reporting more pain two years after surgery, in comparison to AIS (mean 4.31, SD 0.60) (p = 0.043) and SK (mean 4.43, SD 0.48) patients (p = 0.049). Persistent postoperative pain in adolescents undergoing posterior spinal fusion is related to disease pathology while higher acute postoperative pain is associated with a more extensive surgery. Spondylolisthesis patients report more chronic pain after surgery compared to AIS and SK patients.
Cold Tolerance of ScCBL6 Is Associated with Tonoplast Transporters and Photosynthesis in Arabidopsis
Authors: Zhou Yanli , Zhang Jingling , Zhao Changhong , Long Guangqiang , Zhou Chengli , Sun Xudong , Yang Yunqiang , Zhang Chengjun , Yang Yongping
Published: November 2022

Plants that are adapted to harsh environments offer enormous opportunity to understand stress responses in ecological systems. Stipa capillacea is widely distributed in the frigid and arid region of the Tibetan Plateau, but its signal transduction system under cold stress has not been characterized. In this study, we isolated a cDNA encoding the signal transduction protein, ScCBL6, from S. capillacea, and evaluated its role in cold tolerance by ectopically expressing it in Arabidopsis. Full-length ScCBL6 encode 227 amino acids, and are clustered with CBL6 in Stipa purpurea and Oryza sativa in a phylogenetic analysis. Compared with tolerance in wild-type (WT) plants, ScCBL6-overexpressing plants (ScCBL6-OXP) were more tolerant to cold stress but not to drought stress, as confirmed by their high photosynthetic capacity (Fv/Fm) and survival rate under cold stress. We further compared their cold-responsive transcriptome profiles by RNA sequencing. In total, 3931 genes were differentially expressed by the introduction of ScCBL6. These gene products were involved in multiple processes such as the immune system, lipid catabolism, and secondary metabolism. A KEGG pathway analysis revealed that they were mainly enriched in plant hormone signal transduction and biomacromolecule metabolism. Proteins encoded by differentially expressed genes were predicted to be localized in chloroplasts, mitochondria, and vacuoles, suggesting that ScCBL6 exerts a wide range of functions. Based on its tonoplast subcellular location combined with integrated transcriptome and physiological analyses of ScCBL6-OXP, we inferred that ScCBL6 improves plant cold stress tolerance in Arabidopsis via the regulation of photosynthesis, redox status, and tonoplast metabolite transporters.
Simple Explanation of Cuprates Linear Magnetoresistance Enigma
Authors: Lakhno Victor D.
Published: November 2022

A simple explanation is given for the linear dependence of electrical resistance on temperature and the linear dependence of the magnetoresistance on the magnetic field in high-temperature superconducting cuprates, which has been mysterious for many years. It is shown that this dependence stems from the treatment of a gas of translationally invariant polarons as a system with heavy fermions for wave vectors close to nesting. The destruction of such polarons at finite temperature and an external magnetic field leads to a linear dependence of the magnetoresistance on the magnetic field and temperature. It is shown that the relationship between the slopes of the magnetoresistance curves at zero magnetic field and at zero temperature is determined by the universal ratio kB/μB in fermion systems and kB/2μB in boson systems, where kB is the Boltzmann constant and μB is the Bohr magneton. A relation between the existence of translationally invariant polarons and the “Planck” time of their relaxation is discussed.
Self-Compacting Cementitious Composites with Heavy Fuel Fly Ash Replacement
Authors: Georgiou Antroula , Chousidis Nicolaos , Ioannou Ioannis
Published: November 2022

Sustainability in construction is related to the use of industrial by-products, such as fly ash (FA). FA varies in chemical/mineralogical composition, depending on the raw materials burnt during its production. While FA produced from coal-fired power stations is extensively used in cementitious composites, heavy oil FA produced from the firing of heavy fuels (e.g., mazut or diesel) remains largely unused. This paper focuses on the novel use of heavy fuel fly ash (HFFA), as a replacement of Class F FA, in high-volume fly ash self-compacting composites. Two different grain size distributions of HFFA were used in quantities 5–15% w/w of cement and Class F FA for the production of the composites. The assessment of the physico-mechanical properties and microstructure of the end-products at different curing ages suggests that HFFA may be used at quantities ≤10% w/w, without any negative effects. In fact, depending on the quantity and grain size distribution of the HFFA, this may even improve some of the properties of the end-products in the long term, provided that a careful mix design is adopted. The findings show the potential of sustainable reuse of HFFA and are beneficial for its incorporation into design codes.
Involvement of Aquaporin 1 in the Motility and in the Production of Fibrillin 1 and Type I Collagen of Cultured Human Dermal Fibroblasts
Authors: Maeda Kazuhisa , Yoshida Shiori
Published: November 2022

Aminocarbonyl proteins increase with age in the dermal layer. Gene Chip analysis of mRNA expression in human dermal fibroblasts cultured on collagen gels treated with glyceraldehyde as an aminocarbonyl protein and on untreated collagen gels showed a decrease in the amount of aquaporin 1 (AQP1) mRNA. In this study, we clarified the involvement of AQP1 in collagen gel contraction and the production of fibrillin 1 and type I collagen in cultured human dermal fibroblasts. In the experiment, AQP1 siRNA was transfected into cultured human dermal fibroblasts to deplete AQP1, and the cell motility and contractile activity of the collagen gel were assessed. The production of fibrillin 1 and type I collagen was also examined by RT–qPCR and antibody staining. AQP1 depletion decreased the collagen gel contractile activity, and both the amount of mRNA and the antibody staining of fibrillin 1 and type I collagen decreased. Furthermore, the depletion of AQP1 reduced the levels of F-actin and phosphorylated myosin light chain 2, suggesting their involvement in reductions of the motility and collagen gel contractile activity of fibroblasts. These findings suggest that AQP1 is an important biomolecule for cell motility in human dermal fibroblasts and that decreased motility results in decreased expression of extracellular matrix proteins such as fibrillin 1 and type I collagen.
Gut Metabolism of Sugars: Formation of Glycotoxins and Their Intestinal Absorption
Authors: Monteiro-Alfredo Tamaeh , Matafome Paulo
Published: November 2022

Glycotoxins include the group of advanced glycation end-products (AGEs) and their precursors, most of them highly reactive intermediary compounds of sugar metabolism. Glycotoxins and products of the Maillard reaction are present in high concentrations in foods rich in sugars and processed at high temperatures and are often associated with the flavour of the food. Proteins undergoing this type of molecular modification are targets for gut peptidases and may be absorbed into circulation. AGEs are associated with the toxic effects of glucose in diabetic patients, and some studies have shown that they also contribute to metabolically unhealthy obesity and prediabetes development. Restriction of dietary glycotoxins was shown to improve insulin resistance in humans. However, the real contribution of dietary AGEs to such mechanisms is still not understood. This review summarizes the current knowledge about glycotoxin formation from dietary sugars, their digestion throughout the gastrointestinal system, and the mechanisms of their intestinal absorption.
Mathematical Framework for Wearable Devices in the Internet of Things Using Deep Learning
Authors: Mirza Olfat M. , Mujlid Hana , Manoharan Hariprasath , Selvarajan Shitharth , Srivastava Gautam , Khan Muhammad Attique
Published: November 2022

To avoid dire situations, the medical sector must develop various methods for quickly and accurately identifying infections in remote regions. The primary goal of the proposed work is to create a wearable device that uses the Internet of Things (IoT) to carry out several monitoring tasks. To decrease the amount of communication loss as well as the amount of time required to wait before detection and improve detection quality, the designed wearable device is also operated with a multi-objective framework. Additionally, a design method for wearable IoT devices is established, utilizing distinct mathematical approaches to solve these objectives. As a result, the monitored parametric values are saved in a different IoT application platform. Since the proposed study focuses on a multi-objective framework, state design and deep learning (DL) optimization techniques are combined, reducing the complexity of detection in wearable technology. Wearable devices with IoT processes have even been included in current methods. However, a solution cannot be duplicated using mathematical approaches and optimization strategies. Therefore, developed wearable gadgets can be applied to real-time medical applications for fast remote monitoring of an individual. Additionally, the proposed technique is tested in real-time, and an IoT simulation tool is utilized to track the compared experimental results under five different situations. In all of the case studies that were examined, the planned method performs better than the current state-of-the-art methods.
The Omental Cake Sign in Pediatric Tuberculosis
Authors: Fichera Giulia , Causin Francesco , Cecchin Diego , Giraudo Chiara
Published: November 2022

Ultrasound and computed tomography (CT) images showing ascites and omental infiltration (omental cake sign) in a 12-year-old girl with abdominal pain and fever for two weeks. The presence of abdominal and mediastinal lymphadenopathy as well as of a pulmonary consolidation at CT suggested a diagnosis of tuberculosis which was then clinically confirmed. After treatment with ethambutol, rifampicin and isoniazid, pyrazinamide, and vitamin B6 (i.e., intensive treatment for two months followed by a continuation phase with two drugs regimen for four months) the patient fully recovered. Abdominal involvement is rare in children with tuberculosis but the presence of omental involvement together with ascites and enlarged lymph nodes at imaging may suggest this diagnosis and guide the clinicians to proper testing.
Research on the Vibration and Wave Propagation in Ship-Borne Tethered UAV Using Stress Wave Method
Authors: Tao Ye , Zhang Suxia
Published: November 2022

To investigate the vibration behavior of ship-borne tethered UAVs under taut–slack conditions, the Hamilton principle is used to establish the three-dimensional dynamic equations of the ship-borne tethered UAVs while taking into account geometric nonlinearity and simplifying them into the corresponding stress wave equations. By employing the characteristic line technique to solve the stress wave equation of ship-borne tethered UAVs, it is possible to numerically determine the effects of various factors on the vibration behavior of these drones. Dimensional analysis is then used to build the experimental model, ensuring that the numerical outcomes are accurate. The findings show that the impact of equilibrium curvature connects longitudinal and transverse waves and that the geometric dispersion of stress wave propagation in the tethered cable is caused by equilibrium curvature. The standing wave takes the lead and causes subharmonic and frequency doubling components in the top tension response when the end excitation frequency is near the tethered UAVs’ natural frequency. Additionally, the cable’s center as well as its end will display the highest dynamic tension value.
Views of Moroccan University Teachers on Plant Taxonomy and Its Teaching and Learning Challenges
Authors: Maskour Lhoussaine , El Batri Bouchta , Ksiksou Jamal , Jeronen Eila , Agorram Boujemaa , Alami Anouar , Bouali Rahma
Published: November 2022

Plant taxonomy includes the identification, description, and classification of plants at the level of species or other taxa. This study aims to analyze the views of university teachers on plant taxonomy and its teaching, the causes of the shortage of plant taxonomists, and the challenges encountered by students in learning plant taxonomy. University teachers in Morocco (n = 24) responded to a survey consisting of fixed and open-ended questions. The data was analyzed by inductive and deductive content analysis. The results showed that all university teachers considered a taxonomist as a scientist and plant taxonomy as a dynamic and highly scientific, and descriptive discipline. They stated that the taxonomist community is in crisis because of the shortage of plant taxonomists and the decrease in the quality of training provided at the university. The biggest challenges in learning plant taxonomy were the prevalence of traditional teacher-centered methods, the inadequacy of time and didactic resources spent on teaching, and the Latin nomenclature. The difficulties associated with the concept of evolution and the diversity of classifications were also mentioned. The angiosperm group was the most difficult for students to understand. Furthermore, this research shows that the financial, human, institutional, pedagogical, and didactic resources for the teaching of plant taxonomy are insufficient and do not allow for the use of teaching methods supporting learning. How to plant taxonomy is taught is important, and when it is considered difficult, it can lead to a reluctance to study plant species and be one of the reasons for the decline in plant taxonomists in Morocco. Consequently, this issue can negatively affect the preservation and conservation of local flora.
An Image Edge Detection Method Based on Fractional-Order Grey System Model
Authors: Jia Li-Na , Pang Ming-Yong
Published: November 2022

The detection of edges in images is a pressing issue in the field of image processing. This technique has found widespread application in image pattern recognition, machine vision, and a variety of other areas. The feasibility and effectiveness of grey theory in image engineering applications have prompted researchers to continuously explore it. The grey model (GM (1,1)) with the first-order differentiation of one variable is the grey prediction model that is most frequently used. It is a typical trend analysis model and can be used for image edge detection. The traditional integer-order differential image edge detection operator has problems such as blurred and discontinuous edges, incomplete image details, and high influence by noise. We present a novel grey model for detecting image edges based on a fractional-order discrete operator in this paper. To improve the features of the original image, our model first preprocesses it before calculating the prediction of the original image using our fractional-order cumulative greyscale model. We obtain the edge information of the image by first subtracting a preprocessed image from the predicted image and then eliminating isolated noise points using the median filtering method. Based on the discrete wavelet transform, image edges are finally extracted. The comparison experiments with a traditional edge detection operator show that our algorithm can accurately locate the image edges, the image edges are clear and complete, and this model has better anti-noise performance.
Adaptive Non-Singular Fast Terminal Sliding Mode Trajectory Tracking Control for Robot Manipulators
Authors: Yang Qiyao , Ma Xiangfeng , Wang Wei , Peng Dongliang
Published: November 2022

In order to improve the efficiency of human–robot interaction (HRI), it is necessary to carry out research on precise control of the manipulator. In this paper, an adaptive non-singular fast terminal sliding mode control scheme is proposed for robot manipulators to solve the trajectory tracking problem with model uncertainty and external disturbances. At first, a novel non-singular fast terminal sliding mode surface is proposed, and by introducing an auxiliary function, the singularity problem caused by the inverse of the error-related matrix could be avoided in the controller design process. Then, the controller is developed by using Lyapunov synthesis. A robust adaptive strategy is used to deal with lumped uncertainty, with an adaptive update law designed to compensate for the upper bound of lumped uncertainty whose upper bound is prior unknown. Finally, a two-link robot manipulators as a simulation example is given to illustrate the effectiveness of the proposed scheme. Compared with other similar algorithms, the proposed adaptive non-singular fast terminal sliding mode control scheme has higher efficiency and smaller computational complexity for the reason that no piecewise continuous function is needed to be constructed during the controller design.
Synthesis of Low Sidelobe Pattern with Enhanced Axial Radiation for Sparse Conformal Arrays Based on MCDE Algorithm
Authors: Zhang Ning , Xue Zhenghui , Zheng Pei , Gao Lu , Liu Jiaqi
Published: November 2022

A hybrid optimization method for the synthesis of a sparse conformal array with the verification of a truncated cone antenna array is proposed in this manuscript. This array synthesis is studied aiming at enhancing axial radiation and reducing the peak sidelobe level (PSLL) by figuring out the optimal antenna element arrangement and corresponding feeding scheme. A multi-agent composite differential evolution (MCDE) algorithm is established by integrating a multi-agent system (MAS) with a differential evolution (DE) algorithm. In addition, a hybrid strategy method and a time-varying weighting factor are added to the mutation operator to accelerate convergence. Two examples of 64-element and 900-element truncated cone antenna arrays were synthesized. After forming a sparse antenna array out of the original full array, the number of antennas was decreased to 80% and 56.8%, respectively. The results show that the main beam of the sparse conformal antenna array is accurately fixed to the axial direction with the PSLL less than −20 dB at both the φ = 0° and φ = 90° planes, which proves the effectiveness of this method in conformal sparse array synthesis.
LSTM-Based Deep Learning Models for Long-Term Tourism Demand Forecasting
Authors: Salamanis Athanasios , Xanthopoulou Georgia , Kehagias Dionysios , Tzovaras Dimitrios
Published: November 2022

Tourism demand forecasting comprises an important task within the overall tourism demand management process since it enables informed decision making that may increase revenue for hotels. In recent years, the extensive availability of big data in tourism allowed for the development of novel approaches based on the use of deep learning techniques. However, most of the proposed approaches focus on short-term tourism demand forecasting, which is just one part of the tourism demand forecasting problem. Another important part is that most of the proposed models do not integrate exogenous data that could potentially achieve better results in terms of forecasting accuracy. Driven from the aforementioned problems, this paper introduces a deep learning-based approach for long-term tourism demand forecasting. In particular, the proposed forecasting models are based on the long short-term memory network (LSTM), which is capable of incorporating data from exogenous variables. Two different models were implemented, one using only historical hotel booking data and another one, which combines the previous data in conjunction with weather data. The aim of the proposed models is to facilitate the management of a hotel unit, by leveraging their ability to both integrate exogenous data and generate long-term predictions. The proposed models were evaluated on real data from three hotels in Greece. The evaluation results demonstrate the superior forecasting performance of the proposed models after comparison with well-known state-of-the-art approaches for all three hotels. By performing additional benchmarks of forecasting models with and without weather-related parameters, we conclude that the exogenous variables have a noticeable influence on the forecasting accuracy of deep learning models.
Developing PCM-Based Microwave and Millimetre-Wave Switching Networks by Optimised Building Blocks
Authors: Ramer Rodica , Chan King Yuk
Published: November 2022

The implementation of microwave and millimetre-wave switching networks using phase change material (PCM) is presented in this paper. We propose integrating a combination of ultra-wide bandwidth-optimised building cells into a unique semi-T type switch. The construction of arrays with different dimensions is enabled. The present paper selected GeTe for the PCM-based switches, which are 150 nm GeTe thin-film offering on- and off-state σon = 37,203,703 S/m and σoff = 94.97 S/m conductivities by a customised eight-step fabrication process. The integrated semi-T switch cell with two, thru, and turn operational states allows easy expansion into the form of a staircase switch matrix. The simulated results for the semi-T type switch show excellent insertion loss of better than 0.8 dB, return loss of better than 20 dB, and isolation of 40 dB for both the thru and turn paths from DC to 120 GHz. The proposed 4 × 4 staircase switch matrix with a dimension of only 510 × 510 μm2 is also the smallest in its class. The switch matrix exhibits better than 17 dB return loss and 40 dB isolations across all possible combinations and paths.
Proposed Model for Secured Data Storage in Decentralized Cloud by Blockchain Ethereum
Authors: Khan Nabeel , Aljoaey Hanan , Tabassum Mujahid , Farzamnia Ali , Sharma Tripti , Tung Yew Hoe
Published: November 2022

Since cloud computing is an essential component of any modern company (usually accounting for a considerable share of information technology (IT) infrastructure investment), consumers rely on cloud services. Data privacy and security are worries when data remains in third-party storage. Existing document version control systems are centralized and at risk from data loss, as seen by higher time utilization and incorrect document update procedures that allow modifications to a document without the awareness of other network operators. Underutilized peer resources might be leveraged to construct storage. According to this argument, an elevated level of data security may be obtained by encrypting the data and dispersing it among numerous nodes. In this study, we attempted to review the security of cloud systems when using the blockchain Ethereum, and cloud computing was briefly discussed with its advantages and disadvantages. The idea of a decentralized cloud was briefly demonstrated with blockchain technology. Furthermore, previous papers were reviewed and presented in tabular form. This dictated that there are still research gaps in the field of blockchain-based cloud computing systems. This study proposed a model for secured data storage over a decentralized cloud by blockchain Ethereum.
Poisonous Plants Species Prediction Using a Convolutional Neural Network and Support Vector Machine Hybrid Model
Authors: Noor Talal H. , Noor Ayman , Elmezain Mahmoud
Published: November 2022

The total number of discovered plant species is increasing yearly worldwide. Plant species differ from one region to another. Some of these discovered plant species are beneficial while others might be poisonous. Computer vision techniques can be an effective way to classify plant species and predict their poisonous status. However, the lack of comprehensive datasets that include not only plant images but also plant species’ scientific names, description, poisonous status, and local name make the issue of poisonous plants species prediction a very challenging issue. In this paper, we propose a hybrid model relying on transformers models in conjunction with support vector machine for plant species classification and poisonous status prediction. First, six different Convolutional Neural Network (CNN) architectures are used to determine which produces the best results. Second, the features are extracted using six different CNNs and then optimized and employed to Support Vector Machine (SVM) for testing. To prove the feasibility and benefits of our proposed approach, we used a real case study namely, plant species discovered in the Arabian Peninsula. We have gathered a dataset that contains 2500 images of 50 different Arabic plant species and includes plants images, plant species scientific name, description, local name, and poisonous status. This study on the types of Arabic plants species will help in the reduction of the number of poisonous plants victims and their negative impact on the individual and society. The results of our experiments for the CNN approach in conjunction SVM are favorable where the classifier scored 0.92, 0.94, and 0.95 in accuracy, precision, and F1-Score respectively.
Optical Evaluation of Effects of Energy Substrates on PHB Accumulation for Bioplastic Production
Authors: Staśczak Alicja , Langer-Macioł Hanna , Widzisz Karolina , Śliwińska Wiktoria , Lucińska Kinga , Wencel Przemysław , Strózik Barbara , Frąckiewicz Mariusz , Skupin Piotr , Choiński Dariusz , Student Sebastian
Published: November 2022

To date, hundreds of millions tons of plastics has been produced worldwide. Their production and disposal are associated with high pollution and carbon release into the atmosphere. A more environmentally friendly alternative is bioplastics, and the most popular is polyhydroxybutyrate (PHB) polymer. Large amounts of PHB can be obtained from activated sludge where used cooking oil or other industrial waste can be used as potential substrates. In this work, efficient bioplastic production strategies are studied, and the considered substrate is a mixture of oil and peptone. Pseudomonas fluorescens bacteria are used to accumulate PHB, and the cultivation of microorganisms is carried out in batch and continuous-flow bioreactors. Microscopic observations and laboratory essays are performed to confirm presence of PHB and other key parameters. The obtained results allow us to determine the optimal feeding strategy.
Design Optimization of Auxetic Structure for Crashworthy Pouch Battery Protection Using Machine Learning Method
Authors: Carakapurwa Farras , Santosa Sigit
Published: November 2022

In 2021, the electric vehicles (EVs) market reached a record-breaking 6.5 million vehicles, and it will continuously grow to USD 31 million in 2030. However, the risk of battery damage should be reduced using a lightweight crashworthy protection system, which can be performed through design optimization to achieve maximum Specific Energy Absorption (SEA). Maximum SEA can be gained by selecting a material with a light weight and high energy absorption properties. An auxetic-shaped cell structure was used since its negative Poisson ratio yields better energy absorption. The research was performed by varying the auxetic cell shape (Re-entrant, Double Arrow, Star-shaped, Double-U), material selection (GFRP, CFRP, aluminum, carbon steel), and geometry variables until the maximum possible SEA was reached. The Finite Element Method (FEM) was used to simulate the impact and obtain the value of the SEA of the varied auxetic cellular structure design samples. The design variation amounted to 100 samples generated using Latin Hypercube Sampling (LHS) to distribute the variables. Finally, the Machine Learning method predicted the design that yielded maximum SEA. The optimization process through Machine Learning consisted of two processes: model approximation using an Artificial Neural Network (ANN) and variable optimization using a Nondominated Sorting Genetic Algorithm-II (NSGA-II). The optimization demonstrated that the maximum SEA resulted from Star-shaped auxetic cells and aluminum material with a thickness of 2.95 mm. This design yielded 1220% higher SEA compared to the baseline model. A numerical simulation was also carried out to validate the result. The prediction error amounted to 6.7%, meaning that the approximation model can successfully predict the most optimum design. After the complete battery system configuration simulation, the design could also prevent excessive battery deformation. Therefore, the optimized structure can protect the battery from failure.
A Comprehensive Review on a Virtual-Synchronous Generator: Topologies, Control Orders and Techniques, Energy Storages, and Applications
Authors: Shadoul Myada , Ahshan Razzaqul , AlAbri Rashid S. , Al-Badi Abdullah , Albadi Mohammed , Jamil Mohsin
Published: November 2022

In recent years, the penetration of renewable power generations into the electrical grid has substantially increased. Continuous deployment of power electronic-based distributed generations and the reduction of traditional synchronous machines with their essential dynamics in modern power networks are very critical in this change. The use of power electronic inverters leads to the dissociation of sources and loads and lowering the power system inertia. Under power imbalance, this drop causes an elevated rate of change in frequency and frequency divergences, which has a notable impact on the system’s frequency stability. As a result, enhanced control techniques for grid-tied electronic converters are required to secure the power system’s stability and support. The virtual-synchronous generator (VSG) control is used to mimic the dynamics of a rotating synchronous generator and improve the power system’s stability. In this article, the problems of such low-inertia power systems, as well as the VSG technologies, are explored. This research also looks at different control orders and strategies for virtual-synchronous generators (VSG). In addition, the utilization of energy storage and critical matters in VSG and further research recommendations are explained.
Comprehensive Benefit Evaluation of Hybrid Pumped-Storage Power Stations Based on Improved Rank Correlation-Entropy Weight Method
Authors: Tan Yudong , Xie Guosheng , Xiao Yunhao , Luo Yi , Xie Xintao , Wen Ming
Published: November 2022

Over the past decade, the growth of new power plants has become a trend, with new energy stations growing particularly fast. In order to solve the problem of electricity consumption, the development of hybrid pumped storage based on hydropower stations has become a focus, so it is necessary to evaluate and analyze its technical and economic characteristics. Based on the characteristics of pumped-storage power stations, this paper proposes a comprehensive benefit evaluation model for the functional, financial, and environmental benefits. The model uses the fuzzy Delphi method to improve the rank correlation analysis method and introduces the entropy weighting method, calculating the comprehensive weight of indicators by the subjective and objective combination weighting method. The fuzzy comprehensive evaluation method is used to establish a comprehensive evaluation model and calculate the comprehensive benefit evaluation grade of hybrid pumped-storage power plants. Finally, the practicality and validity of the evaluation model are verified through case studies, and the technical and economic characteristics and superiority of the hybrid pumped-storage power plants are analyzed based on the evaluation results.
Mean Flow, Turbulent Structures, and SPOD Analysis of Thermal Mixing in a T-Junction with Variation of the Inlet Flow Profile
Authors: Lampunio Lisa , Duan Yu , Eaton Matthew D. , Bluck Michael J.
Published: November 2022

This paper investigates the effects of different inlet flow profiles on thermal mixing within a T-junction using CFD simulations with the IDDES-SST turbulence model. The different combinations of inlet flow profiles are related to different stage in the flow entry region. The effects of the inlet flow profile on the mean and transient flow behaviour are assessed, while a spectral proper orthogonal decomposition and power spectral density analysis are performed to assess the underlying flow structures and the predominant frequency modes. It is found that the vortical structures associated with the horseshoe and hovering vortex systems consist of a single roll-up vortex for cases with uniformly distributed boundary conditions (BCs) at the branch inlet whereas a double roll-up vortex is observed for the other cases. The double roll-up vortex enhances the mixing locally due to the entrainment of fluid from the branch pipe in these vortical structures, which then results in a lower mean temperature distribution. The appearance of the secondary vortex pair and the nested vortices is delayed for cases with uniformly distributed BCs at the branch inlet, which again results in lower thermal mixing and consequently higher values of mean temperature when compared with the other cases. It is also found that the vorticity related to the counter-rotating vortex pair as well as to the second pair of vortices rotating in the opposite direction is higher for cases with uniformly distributed BCs at the branch inlet. Lastly, the combinations of inlet flow profiles lead to different coherent structures, and the dominant frequencies are of a Strouhal number of around 0.7 for uniformly distributed profiles at the branch inlet and in the range 0.4–0.5 for the other cases.
Thermal Performance Analysis of Various Heat Sinks Based on Alumina NePCM for Passive Cooling of Electronic Components: An Experimental Study
Authors: Zahid Imran , Farooq Muhammad , Farhan Muhammad , Usman Muhammad , Qamar Adnan , Imran Muhammad , Alqahtani Mejdal A. , Anwar Saqib , Sultan Muhammad , Javaid Muhammad Yasar
Published: November 2022

In the modern digital world, electronic devices are being widely employed for various applications where thermal performance represents a significant technical challenge due to continued miniaturization, high heat generated in the system, and non-uniform high-temperature causing failure. Phase change materials (PCMs) owing to the immense heat of fusion are primarily considered for thermal management, but their insulating properties hedge their applications in electronics cooling. Nano-enhanced phase change materials (NePCMs) have the ability to improve the thermal conductivity of PCM, decrease system temperature and escalate the operating time of devices. Accordingly, the current study focused on the experimental investigations for the thermal performance of three heat sinks (HS) with different configurations such as a simple heat sink (SHS), a square pin-fins heat sink (SpfHS), and Cu foam integrated heat sink (CufmHS) with various alumina nanoparticles mass concentrations (0.15, 0.20 and 0.25 wt%) incorporated in PCM (RT-54HC) and at heat flux (0.98–2.94 kW/m2). All HSs reduced the base temperature with the insertion of NePCM compared to the empty SHS. The experimental results identified that the thermal performance of CufmHS was found to be superior in reducing base temperature and enhancing working time at two different setpoint temperatures (SPTs). The maximum drop in base temperature was 36.95%, and a 288% maximum working time enhancement was observed for CufmHS. Therefore, NePCMs are highly recommended for the thermal management of the electronic cooling system.
Stochastic Operation Optimization of the Smart Savona Campus as an Integrated Local Energy Community Considering Energy Costs and Carbon Emissions
Authors: Di Somma Marialaura , Buonanno Amedeo , Caliano Martina , Graditi Giorgio , Piazza Giorgio , Bracco Stefano , Delfino Federico
Published: November 2022

Aiming at integrating different energy sectors and exploiting the synergies coming from the interaction of different energy carriers, sector coupling allows for a greater flexibility of the energy system, by increasing renewables’ penetration and reducing carbon emissions. At the local level, sector coupling fits well in the concept of an integrated local energy community (ILEC), where active consumers make common choices for satisfying their energy needs through the optimal management of a set of multi-carrier energy technologies, by achieving better economic and environmental benefits compared to the business-as-usual scenario. This paper discusses the stochastic operation optimization of the smart Savona Campus of the University of Genoa, according to economic and environmental criteria. The campus is treated as an ILEC with two electrically interconnected multi-energy hubs involving technologies such as PV, solar thermal, combined heat and power systems, electric and geothermal heat pumps, absorption chillers, electric and thermal storage. Under this prism, the ILEC can participate in the day-ahead market (DAM) with proper bidding strategies. To assess the renewables’ uncertainties, the roulette wheel method is used to generate an initial set of scenarios for solar irradiance, and the fast forward selection algorithm is then applied to preserve the most representative scenarios, while reducing the computational load of the next optimization phase. A stochastic optimization model is thus formulated through mixed-integer linear programming (MILP), with the aim to optimize the operation strategies of the various technologies in the ILEC, as well as the bidding strategies of the ILECs in the DAM, considering both energy costs and carbon emissions through a multi-objective approach. Case study results show how the optimal bidding strategies of the ILEC on the DAM allow minimizing of the users’ net daily cost, and, as in the case of environmental optimization, the ILEC operates in self-consumption mode. Moreover, in comparison to the current operation strategies, the optimized case allows reduction of the daily net energy cost in a range from 5 to 14%, and the net daily carbon emissions in a range from 6 to 18%.