bluuebunny/crossref_metadata_2025 huggingface dataset:
Special Issue on Recent Advances in Nonlinear Vibration and Control
Authors: Saeed Nasser A. , Amer T. S.
Published: September 2023

The topics of nonlinear vibration and control have garnered much interest from scientists over the last few decades due to their widespread applications in various fields, such as physics and engineering [...]
A Novel Robust Geolocation-Based Multi-Factor Authentication Method for Securing ATM Payment Transactions
Authors: Alabdulatif Abdullah , Samarasinghe Rohan , Thilakarathne Navod Neranjan
Published: September 2023

Credit/debit cards are a ubiquitous form of payment at present. They offer a number of advantages over cash, including convenience, security, and fraud protection. In contrast, the inherent vulnerabilities of credit/debit cards and transaction methods have led many payment institutions to focus on strengthening the security of these electronic payment methods. Also, the increasing number of electronic payment transactions around the world have led to a corresponding increase in the amount of money lost due to fraud and cybercrime. This loss of money has a significant impact on businesses and consumers, and it necessitates the development of rigid and robust security designs for securing underlying electronic transaction methods. In this regard, this research introduces a novel geolocation-based multi-factor authentication method for improving the security of electronic payment transactions, especially ATM transactions. The proposed method leverages geolocation to verify the user’s identity and prevent fraudulent transactions. In addition, this research also proposes a novel design approach for further controlling the ownership of transactions in a convenient way (e.g., allowing users to deactivate/reactivate authentication at any time, block the card in case it is stolen or lost, and set up a withdrawal limit). Overall, this approach does not require any major modifications to the existing banking infrastructure, which would be an ideal solution for securing ATM transactions around the world.
Generative Adversarial Network-Based Anomaly Detection and Forecasting with Unlabeled Data for 5G Vertical Applications
Authors: Zhang Qing , Chen Bin , Zhang Taoye , Cao Kang , Ding Yuming , Gao Tianhang , Zhao Zhongyuan
Published: September 2023

With the development of 5G vertical applications, a huge amount of unlabeled network data can be collected, which can be employed for evaluating the user experience and network operation status, such as the identifications and predictions of network anomalies. However, it is challenging to achieve highly accurate evaluation results using the conventional statistical methods due to the limitations of data quality. In this paper, generative adversarial network (GAN)-based anomaly detection and forecasting are studied for 5G vertical applications, which can provide considerable detection and prediction results with unlabeled network data samples. First, the paradigm and deployment of the deep-learning-based anomaly detection and forecasting scheme are designed. Second, the network structure and the training strategy are introduced to fully explore the potential of the GAN model. Finally, the experimental results of our proposed GAN model are provided based on the practical unlabeled network operation data in various 5G vertical scenarios, which show that our proposed scheme can achieve significant performance gains for network anomaly detection and forecasting.
Research on a Clustering Forecasting Method for Short-Term Precipitation in Guangdong Based on the CMA-TRAMS Ensemble Model
Authors: Zheng Jiawen , Ren Pengfei , Chen Binghong , Zhang Xubin , Cai Hongke , Li Haowen
Published: September 2023

In light of the 2020–2021 flood season in Guangdong, we conducted a comprehensive assessment of short-term precipitation forecasts generated by the ensemble prediction system (EPS) based on the China Meteorological Administration Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS). Furthermore, we applied four distinct strategies to cluster the ensemble forecast data produced by the model for precipitation, aiming to enhance our understanding of their applicability in short-term precipitation forecasting for Guangdong. Our key findings were as follows.: Precipitation during the 2020–2021 flood season in Guangdong exhibited distinct characteristics. The impacting areas of frontal and subtropical high-edge rainfall were relatively scattered, predominantly occurring in the evening and nighttime. In contrast, monsoon precipitation and return-flow precipitation were concentrated, with their impacts lasting from early morning to evening. Notably, the errors using the ensemble maximum and minimum values were large, while the errors for the ensemble mean values and medians were small. This indicated that the model’s short-term precipitation forecasts possessed a high degree of stability. The vertical shear of different types of precipitation exerted a noticeable influence on the model’s performance. The model consistently displayed a tendency to underestimate short-term precipitation in Guangdong; however, this bias decreased with longer lead times. Simultaneously, the model’s dispersion increased with longer lead times. In terms of mean absolute error (MAE) test results, there was little difference in the performance of ensemble primary forecasts under various strategies, while the “ward” strategy performed well in sub-primary cluster forecasts. This was particularly true for areas and types of precipitation where the model’s performance was poor. While the clustering approach lagged behind ensemble mean forecasts in predicting rainy conditions, it exhibited improvement in forecasting short-term heavy rainfall events. The “complete” and “single” strategies consistently delivered the most accurate forecasts for such events. Our study sheds light on the effectiveness of clustering methods in improving short-term precipitation forecasts for Guangdong, particularly in regions and conditions where the model initially struggled. These findings contribute to our understanding of precipitation forecasting during flood seasons and can inform strategies for enhancing forecast accuracy in similar contexts.
Spatial Downscaling of GPM Satellite Precipitation Data Using Extreme Random Trees
Authors: Zhu Shaonan , Wang Xiangyuan , Jiao Donglai , Zhang Yiding , Liu Jiaxin
Published: September 2023

Obtaining precise and detailed precipitation data is crucial for analyzing watershed hydrology, ensuring sustainable water resource management, and monitoring events such as floods and droughts. Due to the complex relationship between precipitation and geographic factors, this study divides the entire country of China into eight vegetation zones based on different vegetation types. Within each vegetation zone, we employ a seasonally adjusted Extreme Random Trees approach to spatially downscale GPM (Global Precipitation Measurement) satellite monthly precipitation data. To validate the effectiveness of this method, we compare it with kriging interpolation and traditional global downscaling methods. By increasing the spatial resolution of the GPM monthly precipitation dataset from 0.1° to 0.01°, we evaluate the downscaled results and validate them against ground-level rain gauge data and GPM satellite precipitation data. The results indicate that the partitioned area prediction method outperforms other approaches, resulting in a precipitation dataset that not only achieves high accuracy but also offers finer spatial resolution compared to the original GPM precipitation dataset. Overall, this approach enhances the model’s capability to capture complex spatial features and demonstrates excellent generalization. The resulting higher-resolution precipitation dataset enables the creation of more accurate precipitation distribution maps, providing data support for regions lacking hydrological information. These data can be used to analyze seasonal precipitation patterns and reveal differences in precipitation across different seasons and geographic regions.
Optimal Treatment Strategy for Cancer Based on Mathematical Modeling and Impulse Control Theory
Authors: Luo Wenhui , Tan Xuewen , Shen Juan
Published: September 2023

Adaptive therapy is a new type of cancer treatment in which time and dose are dynamically changed according to different individuals, which is very different from conventional cancer treatment strategies that use the maximum dose to kill the tumor cells. However, how to determine the time and dose of drug treatment is a challenging problem. In this paper, a competition model between drug-sensitive cells and drug-resistant cells was established, in which pulse intervention was introduced. In addition, based on the theory of pulse optimal control, three pulse optimal control strategies are proposed in the process of cancer treatment by controlling the pulse interval and dose, minimizing the number of tumor cells at the end of the day at minimal cost. Finally, three optimization strategies were compared, using numerical simulation, in terms of tumor burden and the effect on drug-resistant cells. The results show that the hybrid control strategy has the best effect. This work would provide some new ideas for the treatment of cancer.
TGF-β and SHH Regulate Pluripotent Stem Cell Differentiation into Brain Microvascular Endothelial Cells in Generating an In Vitro Blood–Brain Barrier Model
Authors: Lee Na Geum , Lim Mi-Hee , Park Jongjin , Jeung In Cheul , Hwang Byungtae , Lee Jangwook , Park Jong-Gil , Son Mi-Young , Han Baek Soo , Yoon Sung-Jin , Lee Seon-Jin , Park Young-Jun , Kim Jae Ho , Lee Nam-Kyung , Lee Sang Chul , Min Jeong-Ki
Published: September 2023

Blood–brain barrier (BBB) models are important tools for studying CNS drug delivery, brain development, and brain disease. In vitro BBB models have been obtained from animals and immortalized cell lines; however, brain microvascular endothelial cells (BMECs) derived from them have several limitations. Furthermore, obtaining mature brain microvascular endothelial-like cells (BME-like cells) from human pluripotent stem cells (hPSCs) with desirable properties for establishing BBB models has been challenging. Here, we developed an efficient method for differentiating hPSCs into BMECs that are amenable to the development and application of human BBB models. The established conditions provided an environment similar to that occurring during BBB differentiation in the presence of the co-differentiating neural cell population by the modulation of TGF-β and SHH signaling. The developed BME-like cells showed well-organized tight junctions, appropriate expression of nutrient transporters, and polarized efflux transporter activity. In addition, BME-like cells responded to astrocytes, acquiring substantial barrier properties as measured by transendothelial electrical resistance. Moreover, the BME-like cells exhibited an immune quiescent property of BBB endothelial cells by decreasing the expression of adhesion molecules. Therefore, our novel cellular platform could be useful for drug screening and the development of brain-permeable pharmaceuticals.
Hybrid Deep Neural Network Framework Combining Skeleton and Gait Features for Pathological Gait Recognition
Authors: Jun Kooksung , Lee Keunhan , Lee Sanghyub , Lee Hwanho , Kim Mun Sang
Published: September 2023

Human skeleton data obtained using a depth camera have been used for pathological gait recognition to support doctor or physician diagnosis decisions. Most studies for skeleton-based pathological gait recognition have used either raw skeleton sequences directly or gait features, such as gait parameters and joint angles, extracted from raw skeleton sequences. We hypothesize that using skeleton, joint angles, and gait parameters together can improve recognition performance. This study aims to develop a deep neural network model that effectively combines different types of input data. We propose a hybrid deep neural network framework composed of a graph convolutional network, recurrent neural network, and artificial neural network to effectively encode skeleton sequences, joint angle sequences, and gait parameters, respectively. The features extracted from three different input data types are fused and fed into the final classification layer. We evaluate the proposed model on two different skeleton datasets (a simulated pathological gait dataset and a vestibular disorder gait dataset) that were collected using an Azure Kinect. The proposed model, with multiple types of input, improved the pathological gait recognition performance compared to single input models on both datasets. Furthermore, it achieved the best performance among the state-of-the-art models for skeleton-based action recognition.
Post-Mating Responses in Insects Induced by Seminal Fluid Proteins and Octopamine
Authors: Guan Guang-Xiang , Yu Xiao-Ping , Li Dan-Ting
Published: September 2023

Following insect mating, females often exhibit a series of physiological, behavioral, and gene expression changes. These post-mating responses (PMRs) are induced by seminal fluid components other than sperm, which not only form network proteins to assist sperm localization, supplement female-specific protein requirements, and facilitate the formation of specialized functional structures, but also activate neuronal signaling pathways in insects. This review primarily discusses the roles of seminal fluid proteins (SFPs) and octopamine (OA) in various PMRs in insects. It explores the regulatory mechanisms and mediation conditions by which they trigger PMRs, along with the series of gene expression differences they induce. Insect PMRs involve a transition from protein signaling to neuronal signaling, ultimately manifested through neural regulation and gene expression. The intricate signaling network formed as a result significantly influences female behavior and organ function, contributing to both successful reproduction and the outcomes of sexual conflict.
A Desmethylphosphinothricin Dipeptide Derivative Effectively Inhibits Escherichia coli and Bacillus subtilis Growth
Authors: Khomutov Maxim A. , Giovannercole Fabio , Onillon Laura , Demiankova Marija V. , Vasilieva Byazilya F. , Salikhov Arthur I. , Kochetkov Sergey N. , Efremenkova Olga V. , Khomutov Alex R. , De Biase Daniela
Published: September 2023

New antibiotics are unquestionably needed to fight the emergence and spread of multidrug-resistant bacteria. To date, antibiotics targeting bacterial central metabolism have been poorly investigated. By determining the minimal inhibitory concentration (MIC) of desmethylphosphinothricin (Glu-γ-PH), an analogue of glutamate with a phosphinic moiety replacing the γ-carboxyl group, we previously showed its promising antibacterial activity on Escherichia coli. Herein, we synthetized and determined the growth inhibition exerted on E. coli by an L-Leu dipeptide derivative of Glu-γ-PH (L-Leu-D,L-Glu-γ-PH). Furthermore, we compared the growth inhibition obtained with this dipeptide with that exerted by the free amino acid, i.e., Glu-γ-PH, and by their phosphonic and non-desmethylated analogues. All the tested compounds were more effective when assayed in a chemically-defined minimal medium. The dipeptide L-Leu-D,L-Glu-γ-PH had a significantly improved antibacterial activity (2 μg/mL), at a concentration between the non-desmethytaled (0.1 μg/mL) and the phosphonic (80 μg/mL) analogues. Also, in Bacillus subtilis, the dipeptide L-Leu-D,L-Glu-γ-PH displayed an activity comparable to that of the antibiotic amoxicillin. This work highlights the antibacterial relevance of the phosphinic pharmacophore and proposes new avenues for the development of novel antimicrobial drugs containing the phosphinic moiety.
Functional Analyses of Three Targeted DNA Antimicrobial Peptides Derived from Goats
Authors: Wang Aili , Zhou Mengying , Chen Qian , Jin Hui , Xu Gaochi , Guo Ruiyin , Wang Jianmin , Lai Ren
Published: September 2023

With the increase in drug-resistant bacteria, new antibacterial drugs have emerged as a prominent area of research and development. Antimicrobial peptides (AMPs), as innate immune agents, have garnered significant attention due to their potent, rapid, and broad-spectrum antibacterial activity. This study focused on investigating the functionality of three AMPs (CATH 1, CATH 2, and MAP34-B) derived from goat submandibular glands. Among these AMPs, CATH 2 and MAP34-B exhibited direct antibacterial activity against both Gram-negative and Gram-positive bacteria, primarily targeting the bacterial membrane. Additionally, these two AMPs were found to have the potential to induce reactive oxygen species (ROS) production in bacterial cells and interact with bacterial genome DNA, which may play a crucial role in their mechanisms of action. Furthermore, both CATH 1 and CATH 2 demonstrated significant antioxidant activity, and all three AMPs exhibited potential anti-inflammatory activity. Importantly, the cytotoxic activity of these AMPs against mammalian cells was found to be weak, and their hemolytic activity was extremely low. Overall, the characteristics of these three AMPs found in goat submandibular glands offer new insights for the study of host protection from an immunological perspective. They hold promise as potential candidates for the development of novel antibacterial agents, particularly in the context of combating drug-resistant bacteria.
Circulating Endocannabinoids and N-Acylethanolamines in Individuals with Cannabis Use Disorder—Preliminary Findings
Authors: Boachie Nadia , Gaudette Erin , Bazinet Richard P. , Lin Lin , Tyndale Rachel F. , Mansouri Esmaeil , Huestis Marilyn A. , Tong Junchao , Le Foll Bernard , Kish Stephen J. , George Tony P. , Boileau Isabelle
Published: September 2023

Background: Endocannabinoids and related N-acylethanolamines (NAEs) are bioactive lipids with important physiological functions and putative roles in mental health and addictions. Although chronic cannabis use is associated with endocannabinoid system changes, the status of circulating endocannabinoids and related NAEs in people with cannabis use disorder (CUD) is uncertain. Methods: Eleven individuals with CUD and 54 healthy non-cannabis using control participants (HC) provided plasma for measurement by high-performance liquid chromatography–mass spectrometry of endocannabinoids (2-arachidonoylglycerol (2-AG) and N-arachidonoylethanolamine (AEA)) and related NAE fatty acids (N-docosahexaenoylethanolamine (DHEA) and N-oleoylethanolamine (OEA)). Participants were genotyped for the functional gene variant of FAAH (rs324420, C385A) which may affect concentrations of AEA as well as other NAEs (OEA, DHEA). Results: In overnight abstinent CUD, AEA, OEA and DHEA concentrations were significantly higher (31–40%; p < 0.05) and concentrations of the endocannabinoid 2-AG were marginally elevated (55%, p = 0.13) relative to HC. There were no significant correlations between endocannabinoids/NAE concentrations and cannabis analytes, self-reported cannabis use frequency or withdrawal symptoms. DHEA concentration was inversely related with marijuana craving (r = −0.86; p = 0.001). Genotype had no significant effect on plasma endocannabinoids/NAE concentrations. Conclusions: Our preliminary findings, requiring replication, might suggest that activity of the endocannabinoid system is elevated in chronic cannabis users. It is unclear whether this elevation is a compensatory response or a predating state. Studies examining endocannabinoids and NAEs during prolonged abstinence as well as the potential role of DHEA in craving are warranted.
Role of Non-Coding RNAs in TGF-β Signalling in Glioma
Authors: Shree Bakhya , Sharma Vivek
Published: September 2023

Brain tumours and Gliomas, in particular, are among the primary causes of cancer mortality worldwide. Glioma diagnosis and therapy have not significantly improved despite decades of efforts. Autocrine TGF-β signalling promotes glioma proliferation, invasion, epithelial-to-mesenchymal transition (EMT), and drug resistance. Non-coding RNAs such as miRNA, lncRNA, and circRNAs have emerged as critical transcriptional and post-transcriptional regulators of TGF-β pathway components in glioma. Here, we summarize the complex regulatory network among regulatory ncRNAs and TGF-β pathway during Glioma pathogenesis and discuss their role as potential therapeutic targets for Gliomas.
Predictors of Non-Sentinel Lymph Node Metastasis in Patients with Positive Sentinel Lymph Node in Early-Stage Cervical Cancer: A SENTICOL GROUP Study
Authors: Pache Basile , Tantari Matteo , Guani Benedetta , Mathevet Patrice , Magaud Laurent , Lecuru Fabrice , Balaya Vincent
Published: September 2023

Background: The goal of this study was to identify the risk factors for metastasis in the remaining non-sentinel lymph nodes (SLN) in the case of positive SLN in early-stage cervical cancer. Methods: An ancillary analysis of two prospective multicentric databases on SLN biopsy for cervical cancer (SENTICOL I and II) was performed. Patients with early-stage cervical cancer (FIGO 2018 IA to IIA1), with bilateral SLN detection and at least one positive SLN after ultrastaging, were included. Results: 405 patients were included in SENTICOL I and Il. Fifty-two patients had bilateral SLN detection and were found to have SLN metastasis. After pelvic lymphadenectomy, metastatic involvement of non-SLN was diagnosed in 7 patients (13.5%). Patients with metastatic non-SLN were older (51.9 vs. 40.8 years, p = 0.01), had more often lympho-vascular space invasion (LVSI) (85.7% vs. 35.6%, p = 0.03), and had more often parametrial involvement (42.9% vs. 6.7%, p = 0.003). Multivariate analysis retained age (OR = 1.16, 95% IC = [1.01–1.32], p = 0.03) and LVSI (OR = 25.97, 95% IC = [1.16–582.1], p = 0.04) as independently associated with non-SLN involvement. Conclusions: Age and LVSI seemed to be predictive of non-SLN metastasis in patients with SLN metastasis in early-stage cervical cancer. Larger cohorts are needed to confirm the results and clinical usefulness of such findings.
Neuro-Oncology and Positron Emission Tomography: “Just Can’t Get Enough”
Authors: Muoio Barbara , Espeli Vittoria , Treglia Giorgio
Published: September 2023

Imaging has a pivotal role in neuro-oncology for the management of primary and secondary brain tumors [...]
Critical Role of Novel O-GlcNAcylation of S550 and S551 on the p65 Subunit of NF-κB in Pancreatic Cancer
Authors: Motolani Aishat , Martin Matthew , Wang Benlian , Jiang Guanglong , Alipourgivi Faranak , Huang Xiumei , Safa Ahmad , Liu Yunlong , Lu Tao
Published: September 2023

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with a mere 5-year survival of ~10%. This highlights the urgent need for innovative treatment options for PDAC patients. The nuclear factor κB (NF-κB) is a crucial transcription factor that is constitutively activated in PDAC. It mediates the transcription of oncogenic and inflammatory genes that facilitate multiple PDAC phenotypes. Thus, a better understanding of the mechanistic underpinnings of NF-κB activation holds great promise for PDAC diagnosis and effective therapeutics. Here, we report a novel finding that the p65 subunit of NF-κB is O-GlcNAcylated at serine 550 and 551 upon NF-κB activation. Importantly, the overexpression of either serine-to-alanine (S-A) single mutant (S550A or S551A) or double mutant (S550A/S551A) of p65 in PDAC cells impaired NF-κB nuclear translocation, p65 phosphorylation, and transcriptional activity, independent of IκBα degradation. Moreover, the p65 mutants downregulate a category of NF-κB-target genes, which play a role in perpetuating major cancer hallmarks. We further show that overexpression of the p65 mutants inhibited cellular proliferation, migration, and anchorage-independent growth of PDAC cells compared to WT-p65. Collectively, we discovered novel serine sites of p65 O-GlcNAcylation that drive NF-κB activation and PDAC phenotypes, thus opening new avenues by inhibiting the NF-κB O-GlcNAcylation enzyme, O-GlcNAc transferase (OGT), for PDAC treatment in the future.
Association of Chromosome 17 Aneuploidy, TP53 Deletion, Expression and Its rs1042522 Variant with Multiple Myeloma Risk and Response to Thalidomide/Bortezomib Treatment
Authors: Popek-Marciniec Sylwia , Styk Wojciech , Wojcierowska-Litwin Magdalena , Chocholska Sylwia , Szudy-Szczyrek Aneta , Samardakiewicz Marzena , Swiderska-Kolacz Grazyna , Czerwik-Marcinkowska Joanna , Zmorzynski Szymon
Published: September 2023

Multiple myeloma (MM) is a multifactorial genetic disorder caused by interactive effects of environmental and genetic factors. The proper locus of the TP53 gene (17p13.1) and its protein is essential in genomic stability. The most common variant of the TP53 gene—p.P72R (rs1042522)—shows functional variation. The aim of our study was a complex analysis of the TP53 p.P72R variant and TP53 gene expression in relation to chromosomal changes of the TP53 gene locus, as well as MM risk and outcome. Genomic DNA from 129 newly diagnosed MM patients was analyzed by methods of automated DNA sequencing (for TP53 variant analysis) and cIg-FISH (for chromosomal aberrations analysis). RNA was used in real-time PCR to determine the TP53 expression. In MM patients, the TP53 variant was not in Hardy–Weinberg equilibrium. The RR genotype was associated with lower MM risk (OR = 0.44, p = 0.004). A higher number of plasma cells was found in patients with RR genotype in comparison to those with PP + PR genotypes (36.74% vs. 28.30%, p = 0.02). A higher expression of the TP53 gene was observed in PP + PR genotypes vs. RR homozygote (p < 0.001), in smokers vs. non-smokers (p = 0.02). A positive Pearson’s correlation was found between the TP53 expression level and the number of plasma cells (r = 0.26, p = 0.04). The presence of chromosome 17 aberrations with or without TP53 locus did not affect the MM risk and outcome. Similar results were observed in the case of TP53 gene expression and the p.P72R variant.
The Tetraspanin Tspan8 Associates with Endothelin Converting Enzyme ECE1 and Regulates Its Activity
Authors: Zhu Yingying , Saint-Pol Julien , Nguyen Viet , Rubinstein Eric , Boucheix Claude , Greco Céline
Published: September 2023

Tspan8 is a member of the tetraspanins family of cell surface molecules. The ability of tetraspanins to organize membrane microdomains with other membrane molecules and interfere with their function suggests that they could act as surface integrators of external or internal signals. Among the first identified tetraspanins, Tspan8 promotes tumor progression and metastasis, presumably by stimulating angiogenesis and cell motility. In patients, its expression on digestive tract tumors seems to be associated with a bad prognosis. We showed previously that Tspan8 associates with E-cadherin and EGFR and modulates their effects on cell motility. Using Mass spectrometry and western blot, we found a new partner, the endothelin converting enzyme ECE1, and showed that Tspan8 amplifies its activity of conversion of the endothelin-1 precursor bigET1 to endothelin. This was observed by transduction of the colon carcinoma cell line Isreco1, which does not express Tspan8, and on ileum tissue fragments of tspan8ko mice versus wild type mice. Given these results, Tspan8 appears to be a modulator of the endothelin axis, which could possibly be targeted in case of over-activity of endothelins in biological processes of tissues expressing Tspan8.
Improvements in Maturity and Stability of 3D iPSC-Derived Hepatocyte-like Cell Cultures
Authors: Suominen Siiri , Hyypijev Tinja , Venäläinen Mari , Yrjänäinen Alma , Vuorenpää Hanna , Lehti-Polojärvi Mari , Räsänen Mikko , Seppänen Aku , Hyttinen Jari , Miettinen Susanna , Aalto-Setälä Katriina , Viiri Leena E.
Published: September 2023

Induced pluripotent stem cell (iPSC) technology enables differentiation of human hepatocytes or hepatocyte-like cells (iPSC-HLCs). Advances in 3D culturing platforms enable the development of more in vivo-like liver models that recapitulate the complex liver architecture and functionality better than traditional 2D monocultures. Moreover, within the liver, non-parenchymal cells (NPCs) are critically involved in the regulation and maintenance of hepatocyte metabolic function. Thus, models combining 3D culture and co-culturing of various cell types potentially create more functional in vitro liver models than 2D monocultures. Here, we report the establishment of 3D cultures of iPSC-HLCs alone and in co-culture with human umbilical vein endothelial cells (HUVECs) and adipose tissue-derived mesenchymal stem/stromal cells (hASCs). The 3D cultures were performed as spheroids or on microfluidic chips utilizing various biomaterials. Our results show that both 3D spheroid and on-chip culture enhance the expression of mature liver marker genes and proteins compared to 2D. Among the spheroid models, we saw the best functionality in iPSC-HLC monoculture spheroids. On the contrary, in the chip system, the multilineage model outperformed the monoculture chip model. Additionally, the optical projection tomography (OPT) and electrical impedance tomography (EIT) system revealed changes in spheroid size and electrical conductivity during spheroid culture, suggesting changes in cell–cell connections. Altogether, the present study demonstrates that iPSC-HLCs can successfully be cultured in 3D as spheroids and on microfluidic chips, and co-culturing iPSC-HLCs with NPCs enhances their functionality. These 3D in vitro liver systems are promising human-derived platforms usable in various liver-related studies, specifically when using patient-specific iPSCs.
Collecting Paediatric Health-Related Quality of Life Data: Assessing the Feasibility and Acceptability of the Australian Paediatric Multi-Instrument Comparison (P-MIC) Study
Authors: Jones Renee , O’Loughlin Rachel , Xiong Xiuqin , Bahrampour Mina , McGregor Kristy , Yip Shilana , Devlin Nancy , Hiscock Harriet , Mulhern Brendan , Dalziel Kim ,   on behalf of the Quality of Life in Kids: Key Evidence to Strengthen Decisions in Australia (QUOKKA) Project Team
Published: September 2023

Background: Collecting data using paediatric health-related quality of life (HRQoL) instruments is complex, and there is a paucity of evidence regarding the comparative performance of paediatric HRQoL instruments. The Australian Paediatric Multi-Instrument Comparison (P-MIC) study was conducted to address this paucity of evidence. This study aims to understand the (1) feasibility of collecting data using paediatric HRQoL instruments in a research setting and (2) acceptability and feasibility for children and their caregivers to complete common paediatric HRQoL instruments using data from the Australian P-MIC study. Methods: Data were from children aged 5–18 years from the Australian P-MIC study. Demographics, cost and time for data collection, dropout rates, and inconsistent responses were used to assess Aim 1. Participant-reported difficulty and completion time were used to assess Aim 2. Subgroup analyses included child age, report type (self/proxy), sample recruitment pathway (hospital/online), and online panel sample type (general population/condition groups). Results: Overall, 5945 P-MIC participants aged 5–18 years completed an initial survey, of these, 2346 also completed the follow-up survey (39.5% response rate). Compared with online panel recruitment, hospital recruitment was more costly and time-consuming and had higher follow-up completion (33.5% versus 80.4%) (Aim 1). Data were of similar good quality (based on inconsistent responses) for both recruitment pathways (Aim 1). Participants completed each instrument in <3 min, on average, and >70% reported each instrument as easy to complete (Aim 2). Conclusions: The Australian P-MIC study was able to collect good-quality data using both online panel and hospital recruitment pathways. All instruments were acceptable and feasible to children and their caregivers.
Distinctive Features and Fabrication Routes of Metallic-Glass Systems Designed for Different Engineering Applications: A Review
Authors: Jabed Akib , Bhuiyan M. Nabil , Haider Waseem , Shabib Ishraq
Published: September 2023

Materials with a disordered atomic structure, often termed glassy materials, are the focus of extensive research due to the possibility of achieving remarkable mechanical, electrochemical, and magnetic properties compared to crystalline materials. The glassy materials are observed to have an improved elastic modulus combined with a higher strength and hardness. Moreover, better corrosion resistance in different mediums is also observed for glassy solids, which is difficult to attain using conventional crystalline materials. As a result, the potential applications of metallic-glass systems are continually increasing. Amorphous materials are usually divided into two categories based upon their size. Materials with a thickness and diameter larger than the millimeter (mm) scale are termed as bulk metallic glass (BMG). However, the brittle nature of the bulk-sized samples restricts the size of metallic-glass systems to the micron (µm) or nanometer (nm) range. Metallic glasses with a specimen size in the scale of either µm or nm are defined as thin-film metallic glass (TFMG). In this review, BMGs and TFMGs are termed as metallic glass or MG. A large number of multi-component MGs and their compositional libraries reported by different research groups are summarized in this review. The formation of a multicomponent metallic glass depends on the constituent elements and the fabrication methods. To date, different unique fabrication routes have been adopted to fabricate BMG and TFMGs systems. An overview of the formation principles and fabrication methods as well as advantages and limitations of conventional MG fabrication techniques is also presented. Furthermore, an in-depth analysis of MG inherent properties, such as glass forming ability, and structural, mechanical, thermal, magnetic, and electrochemical properties, and a survey of their potential applications are also described.
The Influence of Alumina Airborne-Particle Abrasion on the Properties of Zirconia-Based Dental Ceramics (3Y-TZP)
Authors: Łagodzińska Paulina , Dejak Beata , Konieczny Bartłomiej
Published: September 2023

The objective of this study was to assess the effect of airborne-particle abrasion with alumina particles of various sizes (50 μm, 110 μm, 250 μm) on the surface properties of 3Y-TZP (3 mol% yttria-stabilized tetragonal zirconia polycrystals). The analysis comprised the Vickers hardness test (HV1kp), a surface roughness evaluation (Ra, Rq, Rz, Rsk, Rsm, Rt, Vo, profile displays), and SEM–EDS microanalysis (scanning electron microscopy–energy-dispersive X-ray spectroscopy). Any statistical relationships were assessed using the Kruskal–Wallis one-way analysis-of-variance-by-rank test (p = 0.05). While airborne-particle abrasion with 50 µm alumina significantly increases the Vickers hardness of 3Y-TZP (1678.8 HV1kp), 110 μm and 250 μm alumina particles do not appear to have any such effect. The surface roughness of 3Y-TZP increases with the size of the alumina particles (Ra, Rq, Rz, Rt, Vo: vertical plane and retention volume assessment); a higher Rsm (horizontal plane assessment) was noted for specimens air-abraded with 250 µm alumina particles; air abrasion with 50 μm alumina particles yielded a symmetrical surface roughness profile (Rsk). The major topographic pattern of the surface of 3Y-TZP is altered by alumina airborne-particle abrasion, with larger alumina particles causing more severe changes. Aluminum traces on the 3Y-TZP surface are observed. The shape of the alumina particles is irregular, with rough edges; the size of the alumina particles plays a significant role in the air abrasion of zirconia-based dental ceramics, affecting their morphology and properties.
Special Issue “Natural Fiber Based Composites II”
Authors: Evon Philippe
Published: September 2023

In the last twenty years, the use of cellulosic and lignocellulosic agricultural by-products for composite applications has been of great interest, especially for reinforcing matrices [...]
Study on Hot Corrosion of Low-Nickel Cladding Metals Containing Nitrogen in K2SO4-MgSO4 Binary Molten Salt
Authors: Zhang Wen , Su Yunhai , Zhang Guiqing , Yang Taisen
Published: September 2023

Molten salt is usually used as the energy storage medium for solar energy heat storage pipes, and 40wt% K2SO4 + 60wt% MgSO4 is very suitable for use as a heat storage material for solar thermal power generation in tower and butterfly parabolic systems. The demand for high-temperature thermal energy storage systems has prompted research on low-cost alloys for use in high-temperature and corrosion-resistant environments. The 44% Ni-24% Cr-0.18N nitrogen-containing low-nickel flux-cored welding wire designed in this article has a corrosion resistance of up to 900 °C after welding repair, which is better than the repair ability of Inconel 625 flux-cored welding wire. Using the high-temperature static immersion corrosion method, the corrosion behavior of two deposited metals immersed in molten salt for 60 h at 900 °C was assessed. The corrosion product phase composition, corrosion morphology, and elemental distribution of the two deposited metals were systematically studied using X-ray diffraction (XRD) and a Gemini SEM 300 (Zeiss thermal field scanning electron microscope). The results showed that the corrosion weight loss of the deposited metals showed the same trend at 900 °C, with corrosion occurring slowly from 0 h to 10 h and increasing after 10 h to 60 h. It was found that 10 h was the boundary point for corrosion behavior, and the corrosion resistance of the low-nickel nitrogen-containing deposited metal is better than that of the Inconel 625 deposited metal. This was because the addition of N energy elements allowed the formation of a stable composite nitride layer to suppress corrosion.
Potential Spread of Desert Locust Schistocerca gregagia (Orthoptera: Acrididae) under Climate Change Scenarios
Authors: Tang Qianhong , Feng Jianmeng , Zong Donglin , Zhou Jing , Hu Xiaokang , Wang Bingru , Wang Tao
Published: September 2023

The desert locust Schistocerca gregagia (Forskål, 1775) is one of the most harmful migratory pests in the world, posing a major threat to agricultural production, livelihoods, and food security. Climate, land use, and topography influence the distribution of desert locusts, but few studies have integrated all the factors on a global scale to explore the suitable areas for desert locusts and the paths through which this species could potentially spread. In this study, we established ensemble distribution models to investigate the distribution patterns and driving factors of desert locusts under baseline and future scenarios; we used ensembled niche dynamic models to evaluate their niche conservation during outbreaks. The results showed that the most important factor influencing desert locust distribution is climate, especially the minimum temperature of the coldest month, the annual precipitation, and the mean temperature of the driest quarter. Some areas with little or no desert locust distribution at present will be suitable for desert locusts in the future, and highly suitable contiguous areas may become the dispersal paths. The results also showed that the climatic niche of the desert locust is still conservative, which might explain why desert locusts tend to retreat after intermittent outbreaks rather than settle at the site of invasion. Therefore, more attention should be paid to the areas that are highly suitable for desert locusts, the key factors driving their outbreaks, and the shifting of their climatic niche in order to prevent desert locusts from settling in invasion areas and affecting local ecosystems and food security.
A Comparison of Different Data Fusion Strategies’ Effects on Maize Leaf Area Index Prediction Using Multisource Data from Unmanned Aerial Vehicles (UAVs)
Authors: Ma Junwei , Chen Pengfei , Wang Lijuan
Published: September 2023

The leaf area index (LAI) is an important indicator for crop growth monitoring. This study aims to analyze the effects of different data fusion strategies on the performance of LAI prediction models, using multisource images from unmanned aerial vehicles (UAVs). For this purpose, maize field experiments were conducted to obtain plants with different growth status. LAI and corresponding multispectral (MS) and RGB images were collected at different maize growth stages. Based on these data, different model design scenarios, including single-source image scenarios, pixel-level multisource data fusion scenarios, and feature-level multisource data fusion scenarios, were created. Then, stepwise multiple linear regression (SMLR) was used to design LAI prediction models. The performance of models were compared and the results showed that (i) combining spectral and texture features to predict LAI performs better than using only spectral or texture information; (ii) compared with using single-source images, using a multisource data fusion strategy can improve the performance of the model to predict LAI; and (iii) among the different multisource data fusion strategies, the feature-level data fusion strategy performed better than the pixel-level fusion strategy in the LAI prediction models. Thus, a feature-level data fusion strategy is recommended for the creation of maize LAI prediction models using multisource UAV images.
Co-Evolutionary Algorithm-Based Multi-Unmanned Aerial Vehicle Cooperative Path Planning
Authors: Wu Yan , Nie Mingtao , Ma Xiaolei , Guo Yicong , Liu Xiaoxiong
Published: September 2023

Multi-UAV cooperative path planning is a key technology to carry out multi-UAV tasks, and its research has important practical significance. A multi-UAV cooperative path is a combination of single-UAV paths, so the idea of problem decomposition is effective to deal with multi-UAV cooperative path planning. With this analysis, a multi-UAV cooperative path planning algorithm based on co-evolution optimization was proposed in this paper. Firstly, by analyzing the meaning of multi-UAV cooperative flight, the optimization model of multi-UAV cooperative path planning was given. Secondly, we designed the cost function of multiple UAVs with the penalty function method to deal with multiple constraints and designed two information-sharing strategies to deal with the combination path search between multiple UAVs. The two information-sharing strategies were called the optimal individual selection strategy and the mixed selection strategy. The new cooperative path planning algorithm was presented by combining the above designation and co-evolution algorithm. Finally, the proposed algorithm is applied to a rendezvous task in complex environments and compared with two evolutionary algorithms. The experimental results show that the proposed algorithm can effectively cope with the multi-UAV cooperative path planning problem in complex environments.
WLP-VBL: A Robust Lightweight Model for Water Level Prediction
Authors: Yi Congqin , Huang Wenshu , Pan Haiyan , Dong Jinghan
Published: September 2023

Accurate and reliable water level prediction plays a crucial role in the optimal management of water resources and reservoir scheduling. Water level data have the characteristics of volatility and temporality; a single water level prediction model can only be applied to specific hydrological conditions and reservoirs. Therefore, in this paper, we present a robust lightweight model for water level prediction, namely WLP-VBL, by using a combination of VMD, BA, and LSTM. The proposed WLP-VBL model consists of three steps: first, the water level dataset is decomposed by EMD to obtain a number of decomposition layers K, and then VMD is used to decompose the original water level dataset into K intrinsic modal functions (IMFs) to produce a clearer signal. Next, the IMF data are sent to an LSTM neural network optimized by BA for prediction, and finally each component is superimposed to obtain the predicted value. In order to evaluate the effectiveness of the model, experiments were carried out on water level data for the Gan River. The results indicate that: (1) Compared with state-of-the art methods, e.g., LSTM, VMD-LSTM, and EMD-LSTM, WLP-VBL exhibited the best performance. The MSE and MAE of WLP-VBL decreased by 69.6~74.7% and 45~98.5%, respectively. (2) The proposed model showed stronger robustness for water level prediction, and was able to handle highly volatile and noisy data.
Active Thermal Control in Neutral-Point-Clamped Multilevel Converters Based on Switching-Cell Arrays
Authors: Alepuz Salvador , Nicolás-Apruzzese Joan , Rafiezadeh Roya , Busquets-Monge Sergio , Raya Mariana , Filbà-Martínez Àlber
Published: September 2023

Neutral-point-clamped multilevel converters are a suitable solution to the implementation of low–medium voltage and power applications at present, thanks to their intrinsic superior voltage and current quality. The conventional configurations of these converters present uneven power loss distribution, causing thermal stress in some power semiconductors, which weakens the power converter reliability. To overcome this, an implementation of the neutral-point-clamped multilevel converter based on a switching-cell array is introduced, adding redundant conduction paths on one side and more options to distribute the switching losses on the other side. An active thermal control is proposed to balance the temperature distribution in the converter. A four-level converter has been implemented to evaluate the proposed solution. The experimental results show that the proposed implementation and active thermal control presents an enhanced temperature distribution in the converter and, therefore, reduced thermal stress and better reliability.
Calibration of a Near-Wall Differential Reynolds Stress Model Using the Updated Direct Numerical Simulation Data and Its Assessment
Authors: Usov Lev , Troshin Alexei , Anisimov Kirill , Sabelnikov Vladimir
Published: September 2023

In the article, a differential Reynolds stress model is recalibrated using turbulent channel flow direct numerical simulation data in the range of friction Reynolds numbers 550–5200. The calibration aims to produce a RANS sublayer model for use within the hybrid RANS/LES framework. The model is designed to capture the average field of a thin near-wall part of a boundary layer as accurately as possible. An a posteriori procedure is employed in which one-dimensional channel flow calculations are performed for all variations of the model coefficients at each stage of the optimization procedure. The coefficients are initialized with their original values and then optimized by minimizing the appropriately chosen norm. An improved representation of the mean velocity profile and peak Reynolds stress values is demonstrated. Both models—baseline and recalibrated—are implemented in an in-house CFD code, and several simulations, including a channel flow, a flat plate boundary layer and a boundary layer separation from a rounded step, are performed. The latter benchmark flow is also simulated in hybrid RANS/LES mode. The updated model is compared to the original one, demonstrating improvements over the baseline model in the cases it was designed for.