bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Digital Twins and Metaverse on Cities: History, Current Situation, and Application Perspectives
Authors: Lv Zhihan , Shang Wen-Long , Guizani Mohsen
Published: December 2022

To promote the expansion and adoption of Digital Twins (DTs) in Smart Cities (SCs), a detailed review of the impact of DTs and digitalization on cities is made to assess the progression of cities and standardization of their management mode. Combined with the technical elements of DTs, the coupling effect of DTs technology and urban construction and the internal logic of DTs technology embedded in urban construction are discussed. Relevant literature covering the full range of DTs technologies and their applications is collected, evaluated, and collated, relevant studies are concatenated, and relevant accepted conclusions are summarized by modules. First, the historical process and construction content of a Digital City (DC) under modern demand are analyzed, and the main ideas of a DC design and construction are discussed in combination with the key technology of DTs. Then, the metaverse is the product of the combination of various technologies in different scenes. It is a key component to promote the integration of the real world and the digital world and can provide more advanced technical support in the construction of the DC. DTs urban technology architecture is composed of an infrastructure terminal information center terminal and application server end. Urban intelligent management is realized through physical urban data collection, transmission, processing, and digital urban visualization. The construction of DTs urban platform can improve the city’s perception and decision-making ability and bring a broader vision for future planning and progression. The interactive experience of the virtual world covered by the metaverse can effectively support and promote the integration of the virtual and real, and will also greatly promote the construction of SCs. In summary, this work is of important reference value for the overall development and practical adoption of DTs cities, which improves the overall operation efficiency and the governance level of cities.
Analogue Ensemble Averaging Method for Bias Correction of 2-m Temperature of the Medium-Range Forecasts in China
Authors: Hu Yingying , Wang Qiguang , Shen Xueshun
Published: December 2022

The 2-m temperature is one of the important meteorological elements, and improving the accuracy of medium- and long-term forecasts of the 2-m temperature is important. The similarity forecasting method is widely used as a calibration technique in the statistical postprocessing of numerical weather prediction (NWP). In this study, the analogue ensemble averaging method is used to correct the deterministic forecast of the 2-m temperature with a forecast lead time from 180 h to 348 h using the CMA-GEPS model. The bias, mean absolute error (MAE), and root mean square error (RMSE) are used as the evaluation metrics. In comparison with NWP, the systematic error of the model for 2-m temperature is effectively reduced during each forecast period when using the analogue ensemble averaging method. In addition, the differences in forecast errors between regions are reduced, and the accuracy of 2-m temperature forecasts over complex terrain, especially in Southwest China, Northwest China, and North China, is improved using this method. In the future, there is certainly potential to apply the analogue ensemble averaging method to the bias correction of medium- and long-term forecasts of more meteorological elements.
An Improved Whale Optimization Algorithm for Web Service Composition
Authors: Dahan Fadl
Published: December 2022

In the current circumstance, the Web Service Composition (WSC) was introduced to address complex user needs concerning the Quality of Services (QoS). In the WSC problem, the user needs are divided into a set of tasks. The corresponding web services are retrieved from the web services discovery according to the functionality of each task, and have different non-functional constraints, such as QoS. The WSC problem is a multi-objective optimization problem and is classified as an NP-hard problem. The whale optimization algorithm (WOA) is proven to solve complex multi-objective optimization problems, and it has the advantage of easy implementation with few control parameters. In this work, we contribute to improving the WOA algorithm, where different strategies are introduced to enhance its performance and address its shortcomings, namely its slow convergence speed, which produces low solution accuracy for the WSC problem. The proposed algorithm is named Improved Whale Optimization Algorithm (IWOA) and has three different strategies to enhance the performance of the WOA. Firstly, the Sine chaos theory is proposed to initiate the WOA’s population and enhance the initialization diversity. Secondly, a Lévy flight mechanism is proposed to enhance the exploitation and exploration of WOA by maintaining the whales’ diversity. Further, a neighborhood search mechanism is introduced to address the trade-off between exploration and exploitation searching mechanisms. Different experiments are conducted with datasets on 12 different scales (small, medium, and large), and the proposed algorithm is compared with standard WOA and five state-of-the-art swarm-based algorithms on 30 different independent runs. Furthermore, four evaluation criteria are used to validate the comparison: the average fitness value, best fitness values, standard deviation, and average execution time. The results show that the IWOA enhanced the WOA algorithm’s performance, where it got the better average and best fitness values with a low variation on all datasets. However, it ranked second regarding average execution time after the WOA, and sometimes third after the WOA and OABC, which is reasonable because of the proposed strategies.
Effects of Adding Blueberry Residue Powder and Extrusion Processing on Nutritional Components, Antioxidant Activity and Volatile Organic Compounds of Indica Rice Flour
Authors: Zhang Xinzhen , Gao Yang , Wang Ran , Sun Yue , Li Xueling , Liang Jin
Published: December 2022

Using indica rice flour as the main raw material and adding blueberry residue powder, the indica rice expanded powder (REP) containing blueberry residue was prepared by extrusion and comminution. The effects of extrusion processing on the nutritional components, color difference, antioxidant performance and volatile organic compounds (VOCs) of indica rice expanded powder with or without blueberry residue were compared. The results showed that the contents of fat and total starch decreased significantly after extrusion, while the contents of total dietary fiber increased relatively. Especially, the effect of DPPH and ABTS+ free radical scavenging of the indica rice expanded flour was significantly improved by adding blueberry residue powder. A total of 104 volatile compounds were detected in the indica rice expanded powder with blueberry residue (REPBR) by Electronic Nose and GC—IMS analysis. Meanwhile, 86 volatile organic compounds were successfully identified. In addition, the contents of 16 aldehydes, 17 esters, 10 ketones and 8 alcohols increased significantly. Therefore, adding blueberry residue powder to indica rice flour for extrusion is an efficient and innovative processing method, which can significantly improve its nutritional value, antioxidant performance and flavor substances.
Sexually Dimorphic Gene Expression in X and Y Sperms Instructs Sexual Dimorphism of Embryonic Genome Activation in Yellow Catfish (Pelteobagrus fulvidraco)
Authors: Xiong Yang , Wang Dan-Yang , Guo Wenjie , Gong Gaorui , Chen Zhen-Xia , Tang Qin , Mei Jie
Published: December 2022

Paternal factors play an important role in embryonic morphogenesis and contribute to sexual dimorphism in development. To assess the effect of paternal DNA on sexual dimorphism of embryonic genome activation, we compared X and Y sperm and different sexes of embryos before sex determination. Through transcriptome sequencing (RNA-seq) and whole-genome bisulfite sequencing (WGBS) of X and Y sperm, we found a big proportion of upregulated genes in Y sperm, supported by the observation that genome-wide DNA methylation level is slightly lower than in X sperm. Cytokine–cytokine receptor interaction, TGF-beta, and toll-like receptor pathways play important roles in spermatogenesis. Through whole-genome re-sequencing (WGRS) of parental fish and RNA-seq of five early embryonic stages, we found the low-blastocyst time point is a key to maternal transcriptome degradation and zygotic genome activation. Generally, sexual differences emerged from the bud stage. Moreover, through integrated analysis of paternal SNPs and gene expression, we evaluated the influence of paternal inheritance on sexual dimorphism of genome activation. Besides, we screened out gata6 and ddx5 as potential instructors for early sex determination and gonad development in yellow catfish. This work is meaningful for revealing the molecular mechanisms of sex determination and sexual dimorphism of fish species.
Palmitoylethanolamide Mitigates Paclitaxel Toxicity in Primary Dorsal Root Ganglion Neurons
Authors: Elfarnawany Amira , Dehghani Faramarz
Published: December 2022

Chemotherapy-induced peripheral neuropathy (CIPN) is a common side effect of several chemotherapeutic agents, such as Paclitaxel. The main symptoms of CIPN are pain and numbness in the hands and feet. Paclitaxel is believed to accumulate in the dorsal root ganglia and free nerve endings. Novel therapeutic agents might help to mitigate or prevent Paclitaxel toxicity on dorsal root ganglion (DRG) neurons. Thus, we used primary DRG neurons as a model to investigate the potential neuroprotective effects of the endocannabinoid-like substance, palmitoylethanolamide (PEA). DRG neurons were isolated from cervical to sacral segments of spinal nerves of Wister rats (6–8 weeks old). After isolation and purification of neuronal cell populations, different concentrations of Paclitaxel (0.01–10 µM) or PEA (0.1–10 µM) or their combination were tested on cell viability by MTT assay at 24 h, 48, and 72 h post-treatment. Furthermore, morphometric analyses of neurite length and soma size for DRG neurons were performed. Adverse Paclitaxel effects on cell viability were apparent at 72 h post-treatment whereas Paclitaxel significantly reduced the neurite length in a concentration-dependent manner nearly at all investigated time points. However, Paclitaxel significantly increased the size of neuronal cell bodies at all time windows. These phenotypic effects were significantly reduced in neurons additionally treated with PEA, indicating the neuroprotective effect of PEA. PEA alone led to a significant increase in neuron viability regardless of PEA concentrations, apparent improvements in neurite outgrowth as well as a significant decrease in soma size of neurons at different investigated time points. Taken together, PEA showed promising protective effects against Paclitaxel-related toxicity on DRG neurons.
Effect of the Biopolymer Carrier on Staphylococcus aureus Bacteriophage Lytic Activity
Authors: Stipniece Liga , Rezevska Dace , Kroica Juta , Racenis Karlis
Published: December 2022

The use of implant materials is always associated with the risk of infection. Moreover, the effectiveness of antibiotics is reduced due to antibiotic-resistant pathogens. Thus, selecting the appropriate alternative antimicrobials for local delivery systems is correlated with successful infection management. We evaluated immobilization of the S. aureus specific bacteriophages in clinically recognized biopolymers, i.e., chitosan and alginate, to control the release profile of the antimicrobials. The high-titre S. aureus specific bacteriophages were prepared from commercial bacteriophage cocktails. The polymer mixtures with the propagated bacteriophages were then prepared. The stability of the S. aureus bacteriophages in the biopolymer solutions was assessed. In the case of chitosan, no plaques indicating the presence of the lytic bacteriophages were observed. The titre reduction of the S. aureus bacteriophages in the Na-alginate was below 1 log unit. Furthermore, the bacteriophages retained their lytic activity in the alginate after crosslinking with Ca2+ ions. The release of the lytic S. aureus bacteriophages from the Ca-alginate matrices in the TRIS-HCl buffer solution (pH 7.4 ± 0.2) was determined. After 72 h—0.292 ± 0.021% of bacteriophages from the Ca-alginate matrices were released. Thus, sustained release of the lytic S. aureus bacteriophages can be ensured.
Development of Allogeneic Stem Cell-Based Platform for Delivery and Potentiation of Oncolytic Virotherapy
Authors: Nguyen Duong Hoang , Herrmann Thomas , Härtl Barbara , Draganov Dobrin , Minev Ivelina , Neuharth Forrest , Gomez Alberto , Alamillo Ashley , Schneider Laura Edith , Kleinholz Daniela , Minev Boris , Santidrian Antonio F.
Published: December 2022

We describe the repurposing and optimization of the TK-positive (thymidine kinase) vaccinia virus strain ACAM1000/ACAM2000™ as an oncolytic virus. This virus strain has been widely used as a smallpox vaccine and was also used safely in our recent clinical trial in patients with advanced solid tumors and Acute Myeloid Leukemia (AML). The vaccinia virus was amplified in CV1 cells and named CAL1. CAL1 induced remarkable oncolysis in various human and mouse cancer cells and preferentially amplified in cancer cells, supporting the use of this strain as an oncolytic virus. However, the therapeutic potential of CAL1, as demonstrated with other oncolytic viruses, is severely restricted by the patients’ immune system. Thus, to develop a clinically relevant oncolytic virotherapy agent, we generated a new off-the-shelf therapeutic called Supernova1 (SNV1) by loading CAL1 virus into allogeneic adipose-derived mesenchymal stem cells (AD-MSC). Culturing the CAL1-infected stem cells allows the expression of virally encoded proteins and viral amplification prior to cryopreservation. We found that the CAL1 virus loaded into AD-MSC was resistant to humoral inactivation. Importantly, the virus-loaded stem cells (SNV1) released larger number of infectious viral particles and virally encoded proteins, leading to augmented therapeutic efficacy in vitro and in animal tumor models.
Cancer and Radiosensitivity Syndromes: Is Impaired Nuclear ATM Kinase Activity the Primum Movens?
Authors: El Nachef Laura , Berthel Elise , Ferlazzo Mélanie L. , Le Reun Eymeric , Al-Choboq Joelle , Restier-Verlet Juliette , Granzotto Adeline , Sonzogni Laurène , Bourguignon Michel , Foray Nicolas
Published: December 2022

There are a number of genetic syndromes associated with both high cancer risk and clinical radiosensitivity. However, the link between these two notions remains unknown. Particularly, some cancer syndromes are caused by mutations in genes involved in DNA damage signaling and repair. How are the DNA sequence errors propagated and amplified to cause cell transformation? Conversely, some cancer syndromes are caused by mutations in genes involved in cell cycle checkpoint control. How is misrepaired DNA damage produced? Lastly, certain genes, considered as tumor suppressors, are not involved in DNA damage signaling and repair or in cell cycle checkpoint control. The mechanistic model based on radiation-induced nucleoshuttling of the ATM kinase (RIANS), a major actor of the response to ionizing radiation, may help in providing a unified explanation of the link between cancer proneness and radiosensitivity. In the frame of this model, a given protein may ensure its own specific function but may also play additional biological role(s) as an ATM phosphorylation substrate in cytoplasm. It appears that the mutated proteins that cause the major cancer and radiosensitivity syndromes are all ATM phosphorylation substrates, and they generally localize in the cytoplasm when mutated. The relevance of the RIANS model is discussed by considering different categories of the cancer syndromes.
The Tumor Microenvironment of Hepatocellular Carcinoma: Untying an Intricate Immunological Network
Authors: Volponi Camilla , Gazzillo Aurora , Bonavita Eduardo
Published: December 2022

HCC, the most prevalent form of primary liver cancer, is prototypically an inflammation-driven cancer developing after years of inflammatory insults. Consequently, the hepatic microenvironment is a site of complex immunological activities. Moreover, the tolerogenic nature of the liver can act as a barrier to anti-tumor immunity, fostering cancer progression and resistance to immunotherapies based on immune checkpoint inhibitors (ICB). In addition to being a site of primary carcinogenesis, many cancer types have high tropism for the liver, and patients diagnosed with liver metastasis have a dismal prognosis. Therefore, understanding the immunological networks characterizing the tumor microenvironment (TME) of HCC will deepen our understanding of liver immunity, and it will underpin the dominant mechanisms controlling both spontaneous and therapy-induced anti-tumor immune responses. Herein, we discuss the contributions of the cellular and molecular components of the liver immune contexture during HCC onset and progression by underscoring how the balance between antagonistic immune responses can recast the properties of the TME and the response to ICB.
Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions
Authors: Gaudiano Caterina , Mottola Margherita , Bianchi Lorenzo , Corcioni Beniamino , Cattabriga Arrigo , Cocozza Maria Adriana , Palmeri Antonino , Coppola Francesca , Giunchi Francesca , Schiavina Riccardo , Fiorentino Michelangelo , Brunocilla Eugenio , Golfieri Rita , Bevilacqua Alessandro
Published: December 2022

The risk of misclassifying clinically significant prostate cancer (csPCa) by multiparametric magnetic resonance imaging is consistent, also using the updated PIRADS score and although different definitions of csPCa, patients with Gleason Grade group (GG) ≥ 3 have a significantly worse prognosis. This study aims to develop a machine learning model predicting csPCa (i.e., any GG ≥ 3 lesion at target biopsy) by mpMRI radiomic features and analyzing similarities between GG groups. One hundred and two patients with 117 PIRADS ≥ 3 lesions at mpMRI underwent target+systematic biopsy, providing histologic diagnosis of PCa, 61 GG < 3 and 56 GG ≥ 3. Features were generated locally from an apparent diffusion coefficient and selected, using the LASSO method and Wilcoxon rank-sum test (p < 0.001), to achieve only four features. After data augmentation, the features were exploited to train a support vector machine classifier, subsequently validated on a test set. To assess the results, Kruskal–Wallis and Wilcoxon rank-sum tests (p < 0.001) and receiver operating characteristic (ROC)-related metrics were used. GG1 and GG2 were equivalent (p = 0.26), whilst clear separations between either GG[1,2] and GG ≥ 3 exist (p < 10−6). On the test set, the area under the curve = 0.88 (95% CI, 0.68–0.94), with positive and negative predictive values being 84%. The features retain a histological interpretation. Our model hints at GG2 being much more similar to GG1 than GG ≥ 3.
Minimally Invasive Anatomical Segmentectomy versus Lobectomy in Stage IA Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis
Authors: Bertolaccini Luca , Prisciandaro Elena , Bardoni Claudia , Cara Andrea , Diotti Cristina , Girelli Lara , Spaggiari Lorenzo
Published: December 2022

Objective. A systematic review and meta-analysis was performed to assess potential differences in perioperative outcomes and disease-free survival (DFS) and overall survival (OS) of patients with pathological stage IA non-small cell lung cancer (NSCLC) who underwent minimally invasive anatomical segmentectomy or lobectomy. Methods. This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A systematic search of EMBASE (through Ovid), MEDLINE (via PubMed), and Cochrane CENTRAL was conducted. Two researchers independently reviewed each eligible study that included patients with stage IA NSCLC who underwent minimally invasive anatomical segmentectomy and lobectomy and compared perioperative and/or survival outcomes of patients. Results. A total of 887 publications were identified. Of these, 10 articles met our eligibility criteria. A significantly higher number of lymph nodes were harvested in lobectomies. The two groups did not significantly differ in postoperative complication rates, DFS, and OS. Patients who underwent segmentectomy had shorter postoperative hospital stays. Conclusions. Minimally invasive lobectomy and segmentectomy showed comparable short-term and long-term outcomes in stage IA NSCLC patients. Postoperative complication rates were similar. Minimally invasive lobectomies are associated with a higher number of harvested lymph nodes, although this did not affect the final staging or the survival outcomes.
Evaluation of Structural and Functional Properties of La0.6Sr0.4MnO3 Perovskite Prepared by the Fast Solution Combustion Approach
Authors: Rendón Ramón Cobo , Salvo Christopher , Sepúlveda Erwin , Arulraj Arunachalam , Sanhueza Felipe , Rodríguez José Jiménez , Mangalaraja Ramalinga Viswanathan
Published: December 2022

A series of La0.6Sr0.4MnO3 (LSM) perovskite was made using the rapid solution combustion method, which was calcined by varying the temperatures. In order to determine how the calcination temperature affected the nanopowders produced and calcined at various temperatures, their microstructural, morphological, compositional, optical, and electrical properties were analyzed using corresponding characterization tools. The XRD results showed the coexistence of the rhombohedral polymorphs R-3c and Pm-3m for the perovskite phase under a calcination temperature of 1400 °C, which were eliminated with increased calcination temperature. The average grain size was found to increase with increasing calcination temperature. The EDS analysis showed better agreement of the stoichiometry with the theoretical composition. The apparent porosity decreased with increasing temperature due to the coalescence of sintering pores. The sample obtained after calcination at 1500 °C showed 10.3% porosity. The hardness also improved with increasing calcination temperature and reached a maximum value of 0.4 GPa, which matched the bulk density. A similar trend was observed in the resistivity studies as a function of temperature, and all the samples exhibited a low resistivity of ~1.4 Ω·cm in the temperature range of 500–600 °C. The optical characterization showed broad absorption at 560–660 nm and bandwidth values between 3.70 and 3.95 eV, according to the applied heat treatment.
FUT2 Facilitates Autophagy and Suppresses Apoptosis via p53 and JNK Signaling in Lung Adenocarcinoma Cells
Authors: Zhang Yuqi , Yao Enze , Liu Yijing , Zhang Yining , Ding Mengyang , Liu Jingyu , Chen Xiaoming , Fan Sairong
Published: December 2022

Lung cancer is the most common cancer with high morbidity and mortality worldwide. Our previous studies showed that fucosyltransferase 2 (FUT2) is highly expressed in lung adenocarcinoma (LUAD) and plays a vital role in the tumorigenesis of LUAD. However, the underlying mechanism is not fully understood. Autophagy has recently attracted increasing attention due to its pro-survival role in cancer progression and metastasis. Here, we found that FUT2 was up-regulated and had an AUC (Area Under Curve) value of 0.964 in lung adenocarcinoma based on the TCGA dataset. Knockdown of FUT2 weakened the autophagy response, as evidenced by a degradation of LC3-II and Beclin1. The phosphorylation levels of AMPK, ULK1, and PI3K III were significantly reduced by FUT2 knockdown. FUT2 promoted the translocation of p53 from the cytoplasm into the nucleus, which triggered the DRAM1 pathway and enhanced autophagy. Meanwhile, the knockdown of FUT2 increased the phosphorylation of JNK and promoted mitochondrial-mediated apoptosis. Furthermore, the knockdown of FUT2 inhibited the autophagy induced by Z-VAD-FMK and promoted the apoptosis suppressed by rapamycin. The autophagy and apoptosis regulated by FUT2 antagonized each other. Taken together, these findings provide a mechanistic understanding of how FUT2 mediated the crosstalk between autophagy and apoptosis, which determine lung cancer cell death and survival, leading to the progression of lung adenocarcinoma.
WiFi Related Radiofrequency Electromagnetic Fields Promote Transposable Element Dysregulation and Genomic Instability in Drosophila melanogaster
Authors: Cappucci Ugo , Casale Assunta Maria , Proietti Mirena , Marinelli Fiorenzo , Giuliani Livio , Piacentini Lucia
Published: December 2022

Exposure to artificial radio frequency electromagnetic fields (RF-EMFs) has greatly increased in recent years, thus promoting a growing scientific and social interest in deepening the biological impact of EMFs on living organisms. The current legislation governing the exposure to RF-EMFs is based exclusively on their thermal effects, without considering the possible non-thermal adverse health effects from long term exposure to EMFs. In this study we investigated the biological non-thermal effects of low-level indoor exposure to RF-EMFs produced by WiFi wireless technologies, using Drosophila melanogaster as the model system. Flies were exposed to 2.4 GHz radiofrequency in a Transverse Electromagnetic (TEM) cell device to ensure homogenous controlled fields. Signals were continuously monitored during the experiments and regulated at non thermal levels. The results of this study demonstrate that WiFi electromagnetic radiation causes extensive heterochromatin decondensation and thus a general loss of transposable elements epigenetic silencing in both germinal and neural tissues. Moreover, our findings provide evidence that WiFi related radiofrequency electromagnetic fields can induce reactive oxygen species (ROS) accumulation, genomic instability, and behavioural abnormalities. Finally, we demonstrate that WiFi radiation can synergize with RasV12 to drive tumor progression and invasion. All together, these data indicate that radiofrequency radiation emitted from WiFi devices could exert genotoxic effects in Drosophila and set the stage to further explore the biological effects of WiFi electromagnetic radiation on living organisms.
RAC1, a Potential Diagnostic and Prognostic Marker for Diffuse Large B Cell Lymphoma
Authors: Wu Xue , Li Yuan , Zhang Wandong , Zhang Jing , Chen Baoan , Ge Zheng
Published: December 2022

The gene changes for diagnosis and prognosis of diffuse large B cell lymphoma (DLBCL) still remain unclear. RAC1 was reported to be asso;ciated with the B cell receptor signal pathway, but its relations with DLBCL have not yet been systematically explored. In this study, we have conducted molecular, bioinformatics and clinical analyses by using publicly available data from The Cancer Genome Atlas (TCGA). Wilcoxon signed-rank test and logistic regression were performed to evaluate the association between RAC1 and clinical features in patients. Kaplan–Meier and Cox regression methods were used to examine the impacts of RAC1 expression level on overall survival, and a nomogram was performed to illustrate the correlation between RAC1 and the risk of DLBCL. Our results revealed that the expression level of RAC1 in DLBCL was higher than that in normal tissues or lymphadenitis. High-level expression of RAC1 was significantly associated with clinical stage, as well as being an independent factor affecting overall survival. RAC1 was negatively correlated with Bruton’s tyrosine kinase (BTK). The association between RAC1 gene expression and the risk of DLBCL was presented in a nomogram. In conclusion, RAC1 expression patterns may be used to predict the development and prognosis of DLBCL.
High-Throughput DNA Metabarcoding as an Approach for Ichthyoplankton Survey in Oujiang River Estuary, China
Authors: Jiang Rijin , Lusana James Leonard , Chen Yongjiu
Published: December 2022

High-throughput DNA metabarcoding of mitochondrial 12S rRNA and Cyt b gene sequences was coupled with a morphology-based identification tool to assess ichthyoplankton community structure in Oujiang River Estuary, China. The performances of 12S and Cyt b barcoding markers were compared in terms of taxonomic resolution, detection and coverage, and their suitability was established for use as a quick and powerful ichthyoplankton assessment tool. A total of 30,138 ichthyoplankton (2462 eggs and 27,676 larvae) samples were collected from April to August 2015 and identified to 145 taxa belonging to 57 families and 105 genera. June and July were the main spawning months. Ichthyoplankton were more abundant around Lingkun and Qidu Islands and the upper parts of Oujiang River Estuary. The 12S gene marker presented higher species coverage and detection rate than Cyt b. DNA metabarcoding exhibited more representative species identification power than morphology. The findings reported in this study provided a key attempt towards the development of time-efficient and cost-effective ichthyoplankton identification and assessment tool.
Recommendation Model Based on Probabilistic Matrix Factorization and Rated Item Relevance
Authors: Han Lifeng , Chen Li , Shi Xiaolong
Published: December 2022

Personalized recommendation has become indispensable in today’s information society. Personalized recommendations play a significant role for both information producers and consumers. Studies have shown that probability matrix factorization can improve personalized recommendation performance. However, most probability matrix factorization models ignore the effect of item-implicit association and user-implicit similarity on recommendation performance. To overcome this lack, we propose a recommendation model based on probability matrix factorization that considers the correlation of user rating items. Our model uses the resource allocation of the bipartite graphs and the random walk of meta-paths in heterogeneous networks to determine the implicit association of items and the implicit similarity of users, respectively. Thus, the final item association and user similarity are obtained. The final item and user similarity relationships are integrated into the probability matrix factorization model to obtain the user’s prediction score for a specific project. Finally, we validated the model on the Delicious-2k, Movielens-2k and last.fm-2k datasets. The results show that our proposed algorithm model has higher recommendation accuracy than other recommendation algorithms.
Model Free Predictive Current Control Based on a Grey Wolf Optimizer for Synchronous Reluctance Motors
Authors: Mahmoudi Abdelkader , Jlassi Imed , Cardoso Antonio J. Marques , Yahia Khaled
Published: December 2022

A Model-based predictive current control (MBPCC) has recently become a powerful advanced control technology in industrial drives. However, MBPCC relies on the knowledge of the system model and parameters, being, therefore, very sensitive to parameters errors. In the case of the synchronous reluctance motor (SynRM), where the parameters vary due to its ferromagnetic structure and nonlinear magnetic properties, MBPCC performance would suffer significantly. Accordingly, in this paper, a Grey Wolf Optimizer based model-free predictive current control (GW-MFPCC) of SynRM is proposed, to skip all the effects of the model dependency and parameters uncertainty. The proposed method predicts the stator current through tracking the minimum cost function using the grey wolf optimizer. The proposed GW-MFPCC scheme is compared to MBPCC, and its effectiveness is evaluated and confirmed by experimental results.
FPSNET: An Architecture for Neural-Network-Based Feature Point Extraction for SLAM
Authors: Farrukh Fasih Ud Din , Zhang Weiyi , Zhang Chun , Wang Zhihua , Jiang Hanjun
Published: December 2022

The hardware architecture of a deep-neural-network-based feature point extraction method is proposed for the simultaneous localization and mapping (SLAM) in robotic applications, which is named the Feature Point based SLAM Network (FPSNET). Some key techniques are deployed to improve the hardware and power efficiency. The data path is devised to reduce overall off-chip memory accesses. The intermediate data and partial sums resulting in the convolution process are stored in available on-chip memories, and optimized hardware is employed to compute the one-point activation function. Meanwhile, address generation units are used to avoid data overlapping in memories. The proposed FPSNET has been designed in 65 nm CMOS technology with a core area of 8.3 mm2. This work reduces the memory overhead by 50% compared to traditional data storage for activation and overall by 35% for on-chip memories. The synthesis and simulation results show that it achieved a 2.0× higher performance compared with the previous design while achieving a power efficiency of 1.0 TOPS/W, which is 2.4× better than previous work. Compared to other ASIC designs with close peak throughput and power efficiency performance, the presented FPSNET has the smallest chip area (at least 42.4% reduction).
A Point Cloud Registration Method Based on Histogram and Vector Operations
Authors: Zhang Yanan , Qiao Dayong , Xia Changfeng , He Qing
Published: December 2022

Point-pair registration in a real scene remains a challenging task, due to the complexity of solving three transformations (scale, rotation, and displacement) simultaneously, and the influence of noise and outliers. Aimed at this problem, a registration algorithm based on histogram and vector operations is proposed in this paper. This approach converts point-based operations into vector-based operations, thereby decomposing the registration process into three independent steps solving for scale transformation factors, rotation matrices, and displacement vectors, which reduces the complexity of the solution and avoids the effects of scaling in the other two processes. The influence of outliers on the global transformation matrix is simultaneously eliminated using a histogram-based approach. Algorithm performance was evaluated through a comparison with the most commonly used SVD method in a series of validation experiments, with results showing that our methodology was superior to SVD in the cases with scaling transformation or outliers.
Handcrafted Deep-Feature-Based Brain Tumor Detection and Classification Using MRI Images
Authors: Mohan Prakash , Veerappampalayam Easwaramoorthy Sathishkumar , Subramani Neelakandan , Subramanian Malliga , Meckanzi Sangeetha
Published: December 2022

An abnormal growth of cells in the brain, often known as a brain tumor, has the potential to develop into cancer. Carcinogenesis of glial cells in the brain and spinal cord is the root cause of gliomas, which are the most prevalent type of primary brain tumor. After receiving a diagnosis of glioblastoma, it is anticipated that the average patient will have a survival time of less than 14 months. Magnetic resonance imaging (MRI) is a well-known non-invasive imaging technology that can detect brain tumors and gives a variety of tissue contrasts in each imaging modality. Until recently, only neuroradiologists were capable of performing the tedious and time-consuming task of manually segmenting and analyzing structural MRI scans of brain tumors. This was because neuroradiologists have specialized training in this area. The development of comprehensive and automatic segmentation methods for brain tumors will have a significant impact on both the diagnosis and treatment of brain tumors. It is now possible to recognize tumors in photographs because of developments in computer-aided design (CAD), machine learning (ML), and deep learning (DL) approaches. The purpose of this study is to develop, through the application of MRI data, an automated model for the detection and classification of brain tumors based on deep learning (DLBTDC-MRI). Using the DLBTDC-MRI method, brain tumors can be detected and characterized at various stages of their progression. Preprocessing, segmentation, feature extraction, and classification are all included in the DLBTDC-MRI methodology that is supplied. The use of adaptive fuzzy filtering, often known as AFF, as a preprocessing technique for photos, results in less noise and higher-quality MRI scans. A method referred to as “chicken swarm optimization” (CSO) was used to segment MRI images. This method utilizes Tsallis entropy-based image segmentation to locate parts of the brain that have been injured. In addition to this, a Residual Network (ResNet) that combines handcrafted features with deep features was used to produce a meaningful collection of feature vectors. A classifier developed by combining DLBTDC-MRI and CSO can finally be used to diagnose brain tumors. To assess the enhanced performance of brain tumor categorization, a large number of simulations were run on the BRATS 2015 dataset. It would appear, based on the findings of these trials, that the DLBTDC-MRI method is superior to other contemporary procedures in many respects.
An Efficient Framework for Accurate Liver Segmentation in Abdominal CT Images with Low Knowledge Requirement
Authors: Yu Shao-Qian , Zhou Tao , Wen Yan-Hua , Li Chuang
Published: December 2022

Liver segmentation from abdominal computed tomography (CT) images is a primary step in the diagnosis and treatment of liver cancer, but previous liver segmentation methods have the problems of excessive demand for prior knowledge, under- and oversegmentation, and boundary leakage. To solve these problems, this paper proposes a new method of liver segmentation to assist doctors in medical judgment. Firstly, a liver reconstruction algorithm is proposed to obtain the approximate initial region of the liver, which reduces the requirement of prior knowledge and can reconstruct the liver region closer to the liver boundary. Then, we refine the edge of the liver region based on the reaction diffusion level set (RD level set). This edge refinement method can effectively deal with the weak boundary problem, prevent under- and oversegmentation, and obtain a more accurate liver region. Our method is verified on the clinical and public datasets, respectively. The segmentation results in terms of mean VOE, RVD, ASD, RMSD, and MSD on dataset Sliver07 are 5.1%, −0.1%, 1.0 mm, 2.0 mm, and 18.2 mm, and on dataset 3Dircadb are 8.1%, −0.2%, 1.5 mm, 2.4 mm, and 20.8 mm, respectively. Compared with the previous algorithms, the experiment results show that this method has a great improvement in accuracy with less prior knowledge. The liver reconstruction algorithm proposed in this paper can obtain a more accurate initial liver region, reduce the requirement for prior knowledge, and reduce time costs compared with the level set algorithm.
Optimal Solution for a Renewable-Energy-Generation System at a Private Educational Institute in South Korea
Authors: Kwon Sangjib , Gil Hyungbae , Baek Seoin , Kim Heetae
Published: December 2022

Climate change has been turning into a climate crisis. Thus, we live in an era in which it is important to carry out the promise of 2050 carbon neutrality worldwide. South Korea is a country with a very large private education market. As the online education market has also recently expanded rapidly, interest in the electricity consumed by educational institutions is growing. One way to reduce the power consumption of private educational institutions, which is expected to gradually increase, is to replace the existing power system with a hybrid energy system based on renewable energy. This study aims to investigate an optimized renewable-energy-based hybrid system to supply adequate power to private educational institutions in Korea. We propose an optimal system using the HOMER (Hybrid Optimization Model for Electric Renewables) program. The result is that when private educational institutions adopt a hybrid renewable energy system, the renewable fraction is negligible in the grid-connected type, but it is analyzed that the NPC (Net Present Cost) will greatly increase because it exceeds 70% in the stand-alone type. The difference between on-grid and off-grid is significant, so it must be taken into account when devising renewable energy policies.
Integrated SDN-NFV 5G Network Performance and Management-Complexity Evaluation
Authors: Surantha Nico , Putra Noffal A.
Published: December 2022

Digitalization is one of the factors that affects the acceleration of the application of telecommunications technologies such as 5G. The 5G technology that has been developed today does not yet meet different performance and manageability standards, particularly for data center networks as a supportive technology. Software-defined networking (SDN) and network function virtualization (NFV) are two complementary technologies that are currently used by almost all data centers in the telecommunications industry to rectify performance and manageability issues. In this study, we deliver an integrated SDN-NFV architecture to simplify network management activities in telecommunication companies. To improve network performance at the computing level, we performed a modification of a networking system at the computing level, underlying NFV devices by replacing the default virtual switch with a data plane development kit (DPDK) and single root I/O virtualization (SR-IOV). This study evaluated the proposed architecture design in terms of network performance and manageability. Based on 30 days of observation in prime time, the proposed solution increased throughput up to 200 Mbps for the server leaf and 1.6 Gbps for the border leaf compared to the legacy architecture. Meanwhile, the latency decreased to 12 ms for the server leaf and 17 ms for the border leaf. For manageability, we tested three different scenarios and achieved savings of 13 min for Scenario 1, 22 min for Scenario 2 and 9 min for Scenario 3.
The Multifaceted Function of Water Hyacinth in Maintaining Environmental Sustainability and the Underlying Mechanisms: A Mini Review
Authors: Xu Jing , Li Xiaoxiao , Gao Tianpeng
Published: December 2022

Water hyacinth (Eichhornia crassipes) (WH) is a widespread aquatic plant. As a top invasive macrophyte, WH causes enormous economic and ecological losses. To control it, various physical, chemical and biological methods have been developed. However, multiple drawbacks of these methods limited their application. While being a noxious macrophyte, WH has great potential in many areas, such as phytoremediation, manufacture of value-added products, and so on. Resource utilization of WH has enormous benefits and therefore, is a sustainable strategy for its control. In accordance with the increasing urgency of maintaining environmental sustainability, this review concisely introduced up to date WH utilization specifically in pollution remediation and curbing the global warming crisis and discussed the underlying mechanisms.
Assessing the Impact of COVID-19 Phased Vaccine Eligibility on COVID-19 Vaccine Intent among African Americans in Southeastern Louisiana: A Community-Based, Cohort Study
Authors: Al-Dahir Sara , Earls Martha , Gillard Christopher , Singleton Brittany , Hall Erica
Published: December 2022

The purpose of this study was to explore the impact of eligibility for the coronavirus 2019 (COVID-19) vaccine at the time of the vaccine rollout as a predictor of vaccine intent within the African American community. Methods: Four hundred eighty-seven African American participants in southeastern Louisiana were surveyed from January–April of 2021, with follow-up surveys occurring in Fall 2021. Survey domains included demographics, vaccine hesitancy, discrimination in the healthcare setting, and knowledge and experiences with COVID-19. Descriptive statistics, Chi-square tests, and binary logistic regression were performed. Results: Participants eligible for the vaccine were 1.61 times as likely to express positive vaccine intent versus ineligible participants. Additional predictors of vaccine intent were age, insurance status and coverage, and female sex at birth. In the multivariable logistic analysis, eligible individuals were 2.07 times as likely to receive the vaccine versus ineligible individuals. Conclusions: Vaccine eligibility for the COVID-19 vaccine was a significant predictor of intent to vaccinate in the African American community. Younger individuals were less likely to have a positive intent, correlating with the eligibility of ages 16+ occurring 5 months post-vaccine approval.
Research on the Anti-Risk Mechanism of Mask Green Supply Chain from the Perspective of Cooperation between Retailers, Suppliers, and Financial Institutions
Authors: Chen Haibo , Wang Zongjun , Yu Xuesong , Zhong Qin
Published: December 2022

Against the background of the pandemic, the mask supply chain faces the risk of pollution caused by discarded masks, the risk of insufficient funds of retailers, and the risk of mask overstock. To better guard against the above risks, this study constructed a two-party game model and a cusp catastrophe model from the perspective of the mask green supply chain, and studied the strategic choices of retailers and suppliers in the supply chain affected by the risk of capital constraints and overstock. The result shows that the risk shocks will lead to the disruption of the mask green supply chain, and the main factors affecting the strategy choice of mask suppliers and retailers are mask recycling rate, deposit ratio, risk occurrence time, etc. In further research, this study involved a mechanism for financial institutions, mask retailers, and the government to jointly deal with the risk of mask overstock, the risk of retailers’ insufficient funds, and the risk of environmental pollution from discarded masks. The research path and conclusion of this study reveal the risks in the circulation area of mask supplies during the pandemic, and provide recommendations for planning for future crises and risk prevention.
Clinical Features and Management of Umbilical Endometriosis: A 30 Years’ Monocentric Retrospective Study
Authors: Dridi Dhouha , Buggio Laura , Donati Agnese , Giola Francesca , Lazzari Caterina , Brambilla Massimiliano , Chiaffarino Francesca , Barbara Giussy
Published: December 2022

Introduction: Umbilical endometriosis (UE) is defined as the presence of endometrial-like tissue within the umbilicus and represents around 0.5–1% of all cases of endometriosis. UE is classified into primary or secondary UE. In this retrospective study, we aimed to assess symptoms, signs, recurrence rate of treated lesions, psychological wellbeing and health-related quality of life in women with UE. Material and methods: We retrospectively reviewed all cases of women diagnosed with UE in the period 1990–2021 in our center. Post-operative recurrence of UE was considered as the reappearance of the umbilical endometriotic lesion, or as the recurrence of local symptoms in the absence of a well-defined anatomical recurrence of the umbilical lesion. Moreover, participants were invited to fill in standardized questionnaires on their health conditions. Results: A total of 55 women with histologically proven UE were assessed in our center during the study period. At time of diagnosis, local catamenial pain and swelling were reported by 51% and 53.2% of women, respectively. A total of 46.8% of women reported catamenial umbilical bleeding. Concomitant non-umbilical endometriosis was identified in 66% of cases. As regards the treatment of UE, 83.6% of women underwent an en-bloc excision with histological confirmation of UE. During the follow-up period, 37 women (67.3%) agreed to undergo a re-evaluation. Recurrence of either umbilical symptoms, or umbilical nodule, was observed in 27% of patients, 11% of which did not receive post-operative hormonal therapy. Specifically, a recurrence of the umbilical endometriotic lesion was observed only in two women. Among the 37 women which we were able to contact for follow-up, 83.8% were satisfied with the treatment they had received. Conclusions: The high rate of patient satisfaction confirmed that surgical excision should be considered the gold standard treatment for umbilical endometriosis. Future studies should investigate the role of post-operative hormonal therapy, particularly in reducing the risk of symptom recurrence.