bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced antifungal activity of posaconazole against Candida auris by HIV protease inhibitors, atazanavir and saquinavir
Authors: Elgammal Yehia , Salama Ehab A. , Seleem Mohamed N.
Published: January 2024

The increasing incidence and dissemination of multidrug-resistant Candida auris represents a serious global threat. The emergence of pan-resistant C. auris exhibiting resistance to all three classes of antifungals magnifies the need for novel therapeutic interventions. We identified that two HIV protease inhibitors, atazanavir and saquinavir, in combination with posaconazole exhibited potent activity against C. auris in vitro and in vivo. Both atazanavir and saquinavir exhibited a remarkable synergistic activity with posaconazole against all tested C. auris isolates and other medically important Candida species. In a time-kill assay, both drugs restored the fungistatic activity of posaconazole, resulting in reduction of 5 and 5.6 log10, respectively. Furthermore, in contrast to the individual drugs, the two combinations effectively inhibited the biofilm formation of C. auris by 66.2 and 81.2%, respectively. Finally, the efficacy of the two combinations were tested in a mouse model of C. auris infection. The atazanavir/posaconazole and saquinavir/posaconazole combinations significantly reduced the C. auris burden in mice kidneys by 2.04- (99.1%) and 1.44-log10 (96.4%) colony forming unit, respectively. Altogether, these results suggest that the combination of posaconazole with the HIV protease inhibitors warrants further investigation as a new therapeutic regimen for the treatment of C. auris infections.
CPT1A as a potential therapeutic target for lipopolysaccharide-induced acute lung injury in mice
Authors: Wang Gui-Yun , Xu Xia , Xiong Da-Yan , Deng Lang , Liu Wei , Huang Xiao-Ting
Published: January 2024

Acute lung injury (ALI) remains a high mortality rate with dramatic lung inflammation and alveolar epithelial cell death. Although fatty acid β-oxidation (FAO) impairment has been implicated in the pathogenesis of ALI, whether Carnitine palmitoyltransferase 1A (CPT1A), the rate-limiting enzyme for FAO, plays roles in lipopolysaccharide (LPS)-induced ALI remains unclear. Accordingly, we focused on exploring the effect of CPT1A in the context of ALI and the underlying mechanisms. We found that overexpression of CPT1A (AAV-CPT1A) effectively alleviated lung injury by reduction of lung wet-to-dry ratio, inflammatory cell infiltration, and protein levels in the BALF of ALI mice. Meanwhile, AAV-CPT1A significantly lessened histopathological changes and several cytokines’ secretions. In contrast, blocking CPT1A with etomoxir augmented inflammatory responses and lung injury in ALI mice. Furthermore, we found that overexpression of CPT1A with lentivirus reduced the apoptosis rates of alveolar epithelial cells and the expression of apoptosis-related proteins induced by LPS in MLE12 cells, while etomoxir increased the apoptosis of MLE12 cells. Overexpression of CPT1A prevented the drop in bioenergetics, palmitate oxidation, and ATP levels. In conclusion, the results rendered CPT1A worthy of further development into a pharmaceutical drug for the treatment of ALI.
Intense pulsed light annealing of solution-based indium–gallium–zinc–oxide semiconductors with printed Ag source and drain electrodes for bottom gate thin film transistors
Authors: Moon Chang-Jin , Park Jong-Whi , Jang Yong-Rae , Kim Hak-Sung
Published: January 2024

In this study, an intense pulsed light (IPL) annealing process for a printed multi-layered indium–gallium–zinc–oxide (IGZO) and silver (Ag) electrode structure was developed for a high performance all-printed inorganic thin film transistor (TFT). Through a solution process using IGZO precursor and Ag ink, the bottom gate structure TFT was fabricated. The spin coating method was used to form the IGZO semiconductor layer on a heavily-doped silicon wafer covered with thermally grown silicon dioxide. The annealing process of the IGZO layer utilized an optimized IPL irradiation process. The Ag inks were printed on the IGZO layer by screen printing to form the source and drain (S/D) pattern. This S/D pattern was dried by near infrared radiation (NIR) and the dried S/D pattern was sintered with intense pulsed light by varying the irradiation energy. The performances of the all-printed TFT such as the field effect mobility and on–off ratio electrical transfer properties were measured by a parameter analyzer. The interfacial analysis including the contact resistance and cross-sectional microstructure analysis is essential because diffusion phenomenon can occur during the annealing and sintering process. Consequently, this TFT device showed noteworthy performance (field effect mobility: 7.96 cm2/V s, on/off ratio: 107). This is similar performance compared to a conventional TFT, which is expected to open a new path in the printed metal oxide-based TFT field.
Multi-omic analyses of m5C readers reveal their characteristics and immunotherapeutic proficiency
Authors: Xu Rui , Wang Yue , Kuang Ye
Published: January 2024

5-methylcytosine (m5C) is a post-transcriptional RNA modification identified, m5C readers can specifically identify and bind to m5C. ALYREF and YBX1 as members of m5C readers that have garnered increasing attention in cancer research. However, comprehensive analysis of their molecular functions across pancancer are lacking. Using the TCGA and GTEx databases, we investigated the expression levels and prognostic values of ALYREF and YBX1. Additionally, we assessed the tumor microenvironment, immune checkpoint-related genes, immunomodulators, Tumor Immune Dysfunction and Exclusion (TIDE) score and drug resistance of ALYREF and YBX1. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analyses were performed to investigate the potential functions associated with m5C readers and coexpressed genes. Aberrant expression of ALYREF and YBX1 was observed and positively associated with prognosis in KIRP, LGG and LIHC. Furthermore, the expression levels of ALYREF and YBX1 were significantly correlated with immune infiltration of the tumor microenvironment and immune-related modulators. Last, our analysis revealed significant correlations between ALYREF, YBX1 and eIFs. Our study provides a substantial understanding of m5C readers and the intricate relationship between ALYREF, YBX1, eIFs, and mRNA dynamics. Through multidimensional analysis of immune infiltration and drug sensitivity/resistance in ALYREF and YBX1, we propose a possibility for combined modality therapy utilizing m5C readers.
Anoikis related genes may be novel markers associated with prognosis for ovarian cancer
Authors: Yang Chen , Zhu LuChao , Lin Qin
Published: January 2024

The aim of this study was to determine the prognostic significance of anoikis related genes (ARGs) in ovarian cancer (OC) and to develop a prognostic signature based on ARG expression. We analyzed cohorts of OC patients and used nonnegative matrix factorization (NMF) for clustering. Single-sample gene-set enrichment analysis (ssGSEA) was employed to quantify immune infiltration. Survival analyses were performed using the Kaplan–Meier method, and differences in survival were determined using the log-rank test. The extent of anoikis modification was quantified using a risk score generated from ARG expression. The analysis of single-cell sequencing data was performed by the Tumor Immune Single Cell Hub (TISCH). Our analyses revealed two distinct patterns of anoikis modification. The risk score was used to evaluate the anoikis modification patterns in individual tumors. Three hub-genes were screened using the LASSO (Least Absolute Shrinkage and Selection Operator) method and patients were classified into different risk groups based on their individual score and the median score. The low-risk subtype was characterized by decreased expression of hub-genes and better overall survival. The risk score, along with patient age and gender, were considered to identify the prognostic signature, which was visualized using a nomogram. Our findings suggest that ARGs may play a novel role in the prognosis of OC. Based on ARG expression, we have developed a prognostic signature for OC that can aid in patient stratification and treatment decision-making. Further studies are needed to validate these results and to explore the underlying mechanisms.
Research on the influence of different sampling resolution and spatial resolution in sampling strategy on landslide susceptibility mapping results
Authors: Yu Xianyu , Chen Huihui
Published: January 2024

Landslides, recognized as a significant global natural disaster, necessitate an exploration of the impact of various resolution types in sampling strategies on Landslide Susceptibility Mapping (LSM) results. This study focuses on the segment from Zigui to Badong within the Three Gorges Reservoir Area, utilizing two resolution types: sampling resolution and spatial resolution, The Support Vector Machine (SVM) is employed to obtain LSM results, which are then analyzed using Receiver Operating Characteristic (ROC) curve, specific category accuracy and statistical methods. Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) were used to verify the reliability of the results. Additionally, five common machine learning models, including Logistic Regression (LR), are used to conduct experiments on four sampling resolutions (10 m,30 m,50 m and 70 m) to further investigate the effect of sampling resolution on LSM results. These are evaluated using a comprehensive quantitative method. The results reveal that increasing spatial resolution improves the prediction accuracy, while increasing sampling resolution produces a contrary effect. Furthermore, the impact of spatial resolution on LSM results is more pronounced than that of sampling resolution. Finally, Fanjiaping landslide and Huangtupo landslide are selected as references for comparative analysis, with the results aligning with engineering reality.
2-Dimensional Ti3C2Tx/NaF nano-composites as electrode materials for hybrid battery-supercapacitor applications
Authors: Riaz M. Bilal , Hussain Danish , Awan Saif Ullah , Rizwan Syed , Zainab Sana , Shah Saqlain A.
Published: January 2024

The increasing global demand for energy storage solutions has spurred interest in advanced materials for electrochemical energy storage devices. Transition-metal carbides and nitrides, known as MXenes, are characterized by remarkable conductivity and tunable properties, They have gained significant attention for their potential in energy storage applications. The properties of two-dimensional (2-D) MXenes can be tuned by doping or composite formation. We report a novel Ti3C2Tx/NaF composite prepared via a straightforward hydrothermal process for supercapacitor electrode applications. Three composites with varying NaF concentrations (1%, 3%, and 5%) were synthesized under similar conditions. Structural characterization using X-ray diffraction (XRD) and scanning electron microscopy confirmed the successful formation of the composites, whereas distinct shifts in XRD peaks and new peaks revealed the presence of NaF. Electrochemical performance was evaluated by cyclic voltammetry, galvanostatic charging-discharging, and electrochemical impedance spectroscopy. The composites exhibited pseudo-capacitive behavior with reversible redox reactions during charge and discharge cycles. Specific capacitance of 191 F/g at scan rates of 2 mV/s was measured in 1 M KOH. Electrochemical impedance spectroscopy revealed an escalating impedance factor as NaF content increases within Ti3C2Tx. This study underscores the versatile energy storage potential of Ti3C2Tx/NaF composites, offering insights into their tailored properties and behavior.
Histopathology images-based deep learning prediction of prognosis and therapeutic response in small cell lung cancer
Authors: Zhang Yibo , Yang Zijian , Chen Ruanqi , Zhu Yanli , Liu Li , Dong Jiyan , Zhang Zicheng , Sun Xujie , Ying Jianming , Lin Dongmei , Yang Lin , Zhou Meng
Published: January 2024

Small cell lung cancer (SCLC) is a highly aggressive subtype of lung cancer characterized by rapid tumor growth and early metastasis. Accurate prediction of prognosis and therapeutic response is crucial for optimizing treatment strategies and improving patient outcomes. In this study, we conducted a deep-learning analysis of Hematoxylin and Eosin (H&E) stained histopathological images using contrastive clustering and identified 50 intricate histomorphological phenotype clusters (HPCs) as pathomic features. We identified two of 50 HPCs with significant prognostic value and then integrated them into a pathomics signature (PathoSig) using the Cox regression model. PathoSig showed significant risk stratification for overall survival and disease-free survival and successfully identified patients who may benefit from postoperative or preoperative chemoradiotherapy. The predictive power of PathoSig was validated in independent multicenter cohorts. Furthermore, PathoSig can provide comprehensive prognostic information beyond the current TNM staging system and molecular subtyping. Overall, our study highlights the significant potential of utilizing histopathology images-based deep learning in improving prognostic predictions and evaluating therapeutic response in SCLC. PathoSig represents an effective tool that aids clinicians in making informed decisions and selecting personalized treatment strategies for SCLC patients.
Peptidyl nitroalkene inhibitors of main protease rationalized by computational and crystallographic investigations as antivirals against SARS-CoV-2
Authors: Medrano Francisco J. , de la Hoz-Rodríguez Sergio , Martí Sergio , Arafet Kemel , Schirmeister Tanja , Hammerschmidt Stefan J. , Müller Christin , González-Martínez Águeda , Santillana Elena , Ziebuhr John , Romero Antonio , Zimmer Collin , Weldert Annabelle , Zimmermann Robert , Lodola Alessio , Świderek Katarzyna , Moliner Vicent , González Florenci V.
Published: January 2024

The coronavirus disease 2019 (COVID-19) pandemic continues to represent a global public health issue. The viral main protease (Mpro) represents one of the most attractive targets for the development of antiviral drugs. Herein we report peptidyl nitroalkenes exhibiting enzyme inhibitory activity against Mpro (Ki: 1–10 μM) good anti-SARS-CoV-2 infection activity in the low micromolar range (EC50: 1–12 μM) without significant toxicity. Additional kinetic studies of compounds FGA145, FGA146 and FGA147 show that all three compounds inhibit cathepsin L, denoting a possible multitarget effect of these compounds in the antiviral activity. Structural analysis shows the binding mode of FGA146 and FGA147 to the active site of the protein. Furthermore, our results illustrate that peptidyl nitroalkenes are effective covalent reversible inhibitors of the Mpro and cathepsin L, and that inhibitors FGA145, FGA146 and FGA147 prevent infection against SARS-CoV-2.
Global disparities in urban green space use during the COVID-19 pandemic from a systematic review
Authors: Kleinschroth Fritz , Savilaakso Sini , Kowarik Ingo , Martinez Paloma Julia , Chang Yuyang , Jakstis Kristen , Schneider Jessica , Fischer Leonie K.
Published: January 2024

The COVID-19 pandemic disrupted urban resilience and challenged the use of urban green space (UGS). Previous studies lack consensus on whether UGS use increased or decreased during and after lockdowns and how this related to policy, economic conditions and UGS types. In a systematic review, we screened >3,000 articles in 5 languages, identifying 177 articles on UGS use changes in 60 countries. The cities studied show diverging changes in UGS use. Generally, decreases occurred where COVID-19 policies were stricter and the gross domestic product per capita was lower, including in most of the few studied areas of the Global South. All studies on private gardens and 60% on forests and other natural areas showed increases, while 77% of studies conducted on public parks indicated decreased use. The global disparity in UGS use was exacerbated during the COVID-19 pandemic, demonstrating the need to enhance green infrastructure for healthy cities and to extend it beyond public parks.
Machine learning inference of continuous single-cell state transitions during myoblast differentiation and fusion
Authors: Shakarchy Amit , Zarfati Giulia , Hazak Adi , Mealem Reut , Huk Karina , Ziv Tamar , Avinoam Ori , Zaritsky Assaf
Published: January 2024

Cells modify their internal organization during continuous state transitions, supporting functions from cell division to differentiation. However, tools to measure dynamic physiological states of individual transitioning cells are lacking. We combined live-cell imaging and machine learning to monitor ERK1/2-inhibited primary murine skeletal muscle precursor cells, that transition rapidly and robustly from proliferating myoblasts to post-mitotic myocytes and then fuse, forming multinucleated myotubes. Our models, trained using motility or actin intensity features from single-cell tracking data, effectively tracked real-time continuous differentiation, revealing that differentiation occurs 7.5–14.5 h post induction, followed by fusion ~3 h later. Co-inhibition of ERK1/2 and p38 led to differentiation without fusion. Our model inferred co-inhibition leads to terminal differentiation, indicating that p38 is specifically required for transitioning from terminal differentiation to fusion. Our model also predicted that co-inhibition leads to changes in actin dynamics. Mass spectrometry supported these in silico predictions and suggested novel fusion and maturation regulators downstream of differentiation. Collectively, this approach can be adapted to various biological processes to uncover novel links between dynamic single-cell states and their functional outcomes.
Covalently hybridized carbon dots@mesoporous silica nanobeads as a robust and versatile phosphorescent probe for time-resolved biosensing and bioimaging
Authors: Liao Zixuan , Wang Yuhui , Lu Yu , Zeng Ruoxi , Li Lin , Chen Hao , Song Qingwei , Wang Kaizhe , Zheng Jianping
Published: January 2024

Monodisperse, uniform and strong RTP nanobeads of covalently hybridized CDs@DMSNs were first constructed and developed for versatile time-gated biomedical assays.
Assessing the influence of small structural modifications in simple DNA-based nanostructures on their role as drug nanocarriers
Authors: Postigo Alejandro , Martínez-Vicente Pablo , Baumann Kevin N. , del Barrio Jesús , Hernández-Ainsa Silvia
Published: January 2024

Minor structural features in simple DNA-based nanostructures are here shown to exert some influence in different key properties related to their capabilities as nanocarriers for drugs, in particular doxorubicin.
NIR phosphorescence from decatungstate anions allows the conclusive characterization of its elusive excited triplet behaviour and kinetics
Authors: Didarataee Saba , Suprun Anastasiia , Joshi Neeraj , Scaiano Juan C.
Published: January 2024

The characterization of the triplet state of decatungstate (3DT*) and its NIR phosphorescence with lifetimes ∼100 ns in acetonitrile allow the easy determination of rate constants that are key to understanding its role in catalysis.
Infrared spectra prediction using attention-based graph neural networks
Authors: Saquer Naseem , Iqbal Razib , Ellis Joshua D. , Yoshimatsu Keiichi
Published: January 2024

In this work, we present attention-based graph neural networks to predict infrared (IR) spectra from chemical structures.
Green ethylene production in the UK by 2035: a techno-economic assessment
Authors: Nyhus Andreas H. , Yliruka Maria , Shah Nilay , Chachuat Benoît
Published: January 2024

A techno-economic analysis comparing thermocatalytic and electrocatalytic routes to green ethylene from air-captured CO2 and off-shore wind electricity.
A minireview on electrochemical CO2 conversion based on carbonate/bicarbonate media
Authors: Li Tiehuai , Shao Minhua
Published: January 2024

(Bi)Carbonate electrochemical conversion has emerged as a promising technology. Studies on mechanisms, along with latest progress in catalyst design and working electrode optimization. are summarized. Challenges and opportunities are also discussed.
Insights into synaptic functionality and resistive switching in lead iodide flexible memristor devices
Authors: Jain Muskan , Patel Mayur Jagdishbhai , Liu Lingli , Gosai Jeny , Khemnani Manish , Gogoi Himangshu Jyoti , Chee Mun Yin , Guerrero Antonio , Lew Wen Siang , Solanki Ankur
Published: January 2024

Neuromorphic platforms are gaining popularity due to their superior efficiency, low power consumption, and adaptable parallel signal processing capabilities, overcoming the limitations of traditional von Neumann architecture.
Multifunctional nanocomposites based on graphite-phase carbon nitride quantum dot-silver nanospheres for combined photothermal–photodynamic anti-tumor therapy
Authors: He Wenjing , Jin Ying , Wang Baoping , Tan Jie , Yan Wenjia , Xiao Hong , Choi Martin M.F. , Bian Wei
Published: January 2024

In this study, a g-CNQDs@AgNSs nanocomposite was successfully prepared based on graphite-phase carbon nitride quantum dots and silver nanospheres. Both in vitro and cellular experiments proved that the nanocomposite had good PTT/PDT effects, promising efficient combination therapy of tumors.
Persulfate-enhanced degradation of propranolol over BiOCl0.5I0.5 under visible light irradiation
Authors: Deng Yuehua , Luo Jiating , Cao Hongyu , Chen Danni , Li Yani , Che Qianqian , He Yan , Gao Xiang , Hu Xiaobin , Zhao Wei , Wang Fei
Published: January 2024

The photodegradation of propranolol (PRO) by BiOCl0.5I0.5/persulfate under visible light was comprehensively investigated.
A study of complexation and biological fate of polyethyleneimine-siRNA polyplexes in vitro and in vivo by fluorescence correlation spectroscopy and positron emission tomography imaging
Authors: Ludtke Tanja , Simó Cristina , Gimenez Reyes Santiago , Martinez Moro Marta , Salvador Cristian , Ritacco Hernan , Andreozzi Patrizia , Llop Jordi , Moya Sergio E.
Published: January 2024

Fluorescence correlation spectroscopy and positron emission tomography are used to study the formation of PEI siRNA polyplex nanoparticles and to trace their biological fate at cell level and in vivo.
Oxygen self-supplying small size magnetic nanoenzymes for synergistic photodynamic and catalytic therapy of breast cancer
Authors: Cai Xinyi , Xu Tiantian , Ding Rui , Zhang Dou , Chen Guiquan , Zhao Wenchang , Hou Jiajie , Pan Hong , Zhang Qian , Yin Ting
Published: January 2024

In this study, we developed oxygen-supplying magnetic bead nanozymes that integrate hemoglobin and encapsulate the photosensitizer curcumin, demonstrating reactive oxygen species (ROS)-induced synergistic breast cancer therapy.
Thermally assisted layer–layer crosslinking towards programmable evolution of pore structures for tunable electromagnetic response capability
Authors: Quan Bin , Chen Yu , Lin Litao , Zhou Xunyi , Lu Xiaochi , Zhang Mingji , Huang Xiaogu
Published: January 2024

The research and development of aerogel-based microwave absorbing materials with strong electromagnetic (EM) wave response is an emerging research topic in the EM wave absorption field.
Amphiphilic–zwitterionic block polymers
Authors: Ghosh Ria , Wong Wen-Wei , Reimers Tom , Radzanowski Anne , Correa Ruiz Juan , Coughlin E. Bryan
Published: January 2024

Amphiphilic zwitterionic (AZ) block copolymers are readily prepared using post-polymerization modification, which offers exciting prospects for structure property relationship studies.
F-doped NiOOH derived from progressive reconstruction for efficient and durable water oxidation
Authors: Guo Kailu , Jia Jinzhi , Lu Xiaoyan , Wang Shuang , Wang Huijiao , Wu Haixia , Xu Cailing
Published: January 2024

Ammonium nickel fluoride (NH4NiF3) undergoes progressive reconstruction via anodic oxidation in alkaline media and ultimately transforms into a F-doped NiOOH with excellent OER activity and durability.
Influence of organic matters on the adsorption–desorption of 1,2-dichloroethane on soil in water and model saturated aquifer
Authors: Huang Xinhong , Liang Yan , Yun Jinhu , Cao Feishu , Xie Tian , Song Hainong , Wang Shuangfei
Published: January 2024

1,2-Dichloroethane (1,2-DCA) is a typical organic chlorinated compound largely utilized in chemical manufacturing and industrial production and also a common pollutant in organically contaminated sites.
Design strategies and biological applications of β-galactosidase fluorescent sensor in ovarian cancer research and beyond
Authors: Li Liangliang , Jia Feifei , Li Yunxiu , Peng Yan
Published: January 2024

Beta-galactosidase (β-galactosidase), a lysosomal hydrolytic enzyme, plays a critical role in the catalytic hydrolysis of glycosidic bonds, leading to the conversion of lactose into galactose.
Reversible interfacial Li-oxide formation on germanium and silicon anodes revealed by time-resolved microgravimetry
Authors: Wang Ke , Joshi Yug , Kohler Tobias , Mead Monica , Schmitz Guido
Published: January 2024

A reversible Li2O on the surface of the electrode is formed upon Li intercalation, mainly due to the kinetic overpotential arising from limited Li mobility. Ge, in comparison with Si, shows much less Li2O formation due to the faster diffusion of Li.
A robust silicone aerogel via copolymerization of a difunctional organoalkoxysilane and polymethylmethoxysiloxane for high-temperature thermal insulation
Authors: Luo Yi , Yan Aoqing , Tian Hao , Niu Bo , Zhang Yayun , Wang Hualin , Long Donghui
Published: January 2024

A robust silicone aerogel for high-temperature thermal insulation prepared by a sol–gel process using polymethylmethoxysiloxane as the framework and a difunctional organoalkoxysilane as the crosslinker.
Diminishing the migration resistance of zinc ions by cation vacancy engineering in a spinel-framework
Authors: Yuan Jingjing , Qiao Yifan , Li Yifan , Xu Hui , Zhang Wenyao , Zhang Zhihao , He Guangyu , Chen Haiqun
Published: January 2024

ZnMn2O4 with Zn vacancies has been constructed via alkaline etching, which shows lower diffusion energy barriers for Zn2+ than ZnMn2O4.
An injectable photocuring silk fibroin-based hydrogel for constructing an antioxidant microenvironment for skin repair
Authors: Liu Tangjinhai , Wang Yuxiang , Liu Jingyi , Han Xiaowen , Zou Yaping , Wang Peilei , Xu Ruiling , Tong Lei , Liu Junli , Liang Jie , Sun Yong , Fan Yujiang , Zhang Xingdong
Published: January 2024

An injectable photocurable hydrogel based on methacrylated dopamine and silk fibroin constructs an antioxidant protein microenvironment, which prevents oxidative stress in vitro, and promotes collagen disposition and angiogenesis in vivo.
Intermittent short-duration reoxygenation relieves high-altitude pulmonary hypertension via NOX4/H2O2/PPAR-γ axis
Authors: Li Shaohua , Lyu Qiang , Shi Qixin , Bai Yungang , Ren Xinling , Ma Jin
Published: January 2024

High-altitude pulmonary hypertension (HAPH) is a severe and progressive disease that can lead to right heart failure. Intermittent short-duration reoxygenation at high altitude is effective in alleviating HAPH; however, the underlying mechanisms are unclear. In the present study, a simulated 5,000-m hypoxia rat model and hypoxic cultured pulmonary artery smooth muscle cells (PASMCs) were used to evaluate the effect and mechanisms of intermittent short-duration reoxygenation. The results showed that intermittent 3-h/per day reoxygenation (I3) effectively attenuated chronic hypoxia-induced pulmonary hypertension and reduced the content of H2O2 and the expression of NADPH oxidase 4 (NOX4) in lung tissues. In combination with I3, while the NOX inhibitor apocynin did not further alleviate HAPH, the mitochondrial antioxidant MitoQ did. Furthermore, in PASMCs, I3 attenuated hypoxia-induced PASMCs proliferation and reversed the activated HIF-1α/NOX4/PPAR-γ axis under hypoxia. Targeting this axis offset the protective effect of I3 on hypoxia-induced PASMCs proliferation. The present study is novel in revealing a new mechanism for preventing HAPH and provides insights into the optimization of intermittent short-duration reoxygenation.
AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things
Authors: Zeeshan Aslam Muhammad , Raza Basit , Faheem Muhammad , Raza Aadil
Published: January 2024

Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some work tried to make a lightweight model and do channel pruning that made a small receptive field which compromised the accuracy. The authors propose an attention‐based multi‐scale lightweight model called AML‐Net in Internet of Medical Things to overcome the above issues. This model consists of three small encoder‐decoder architectures that are trained with different scale input images along with previously learned features to diminish the loss. Moreover, the authors designed an attention module which replaced the traditional skip connection. For the attention module, six different experiments were conducted, from which dilated convolution with spatial attention performed well. This attention module has three dilated convolutions which make a relatively large receptive field followed by spatial attention to extract global context from encoder low‐level features. Then these fine features are combined with the decoder's same layer of high‐level features. The authors perform the experiment on a low‐grade‐glioma dataset provided by the Cancer Genome Atlas which has at least Fluid‐Attenuated Inversion Recovery modality. The proposed model has 1/43.4, 1/30.3, 1/28.5, 1/20.2 and 1/16.7 fewer parameters than Z‐Net, U‐Net, Double U‐Net, BCDU‐Net and CU‐Net respectively. Moreover, the authors’ model gives results with IoU = 0.834, F1‐score = 0.909 and sensitivity = 0.939, which are greater than U‐Net, CU‐Net, RCA‐IUnet and PMED‐Net.
Heterogeneous decentralised machine unlearning with seed model distillation
Authors: Ye Guanhua , Chen Tong , Hung Nguyen Quoc Viet , Yin Hongzhi
Published: January 2024

As some recent information security legislation endowed users with unconditional rights to be forgotten by any trained machine learning model, personalised IoT service providers have to put unlearning functionality into their consideration. The most straightforward method to unlearn users' contribution is to retrain the model from the initial state, which is not realistic in high throughput applications with frequent unlearning requests. Though some machine unlearning frameworks have been proposed to speed up the retraining process, they fail to match decentralised learning scenarios. A decentralised unlearning framework called heterogeneous decentralised unlearning framework with seed (HDUS) is designed, which uses distilled seed models to construct erasable ensembles for all clients. Moreover, the framework is compatible with heterogeneous on‐device models, representing stronger scalability in real‐world applications. Extensive experiments on three real‐world datasets show that our HDUS achieves state‐of‐the‐art performance.
Block sparse vector recovery for compressive sensing via ℓ1−αℓq$\ell _1-\alpha \ell _q$‐minimization Model
Authors: Shi Hongyan , Xie Shaohua , Wang Jiangtao
Published: January 2024

This paper solves the problem of block sparse vector recovery using the block ‐minimization model. Based on the block restricted isometry property (B‐RIP) condition, exact block sparse vector recovery result is obtained. The theoretical bound for the block ‐minimization model are also obtained when measurements are depraved by the noises.
S‐parameter extraction for electromagnetic modelling of memristor‐based crossbar array circuits
Authors: Yu Junwei , Ma Hanzhi , Tao Tuomin , Zhang Ling , Li Da , Li Er‐Ping
Published: January 2024

This article presents an efficient S‐parameter extraction method for memristor‐based crossbar array circuits. The proposed approach involves converting the array into an equivalent circuit and analytically solving the circuit to obtain the S‐parameters. Memristor‐based crossbar array circuit simulations and corresponding experimental measurements are conducted to verify the high accuracy and low computation complexity of the established method. These numerical results indicate that the authors’ S‐parameter extraction method has the potential for evaluating signal integrity performance in neuromorphic chips, thus aiding their design and optimization for diverse applications.
Unmanned aerial vehicle localization using angle of departure from a single base station and dead‐reckoning
Authors: Rajasekaran Akash , Meles Mehari , Virrankoski Reino , Jäntti Riku
Published: January 2024

Localization in GNSS‐denied environments for unmanned aerial vehicles (UAVs) has recently gained significant interest from the research community. Most of the research is focused primarily on visual localization. This paper examines an algorithm which employs angle of departure and UAVs payload sensor data for UAV localization. First the algorithm uses multiple angle of departures from a single base station and a travel calculated by applying dead‐reckoning on the UAVs inertial measurement unit (IMU), to compute UAV location in 2D coordinates. The 2D location estimate is then fed into a modified extended Kalman filter, which employs the estimate, IMU and barometer data to compute the 3D coordinates for UAV. For the simulation, simulation‐in‐the‐loop accompanied by Arducopter and MAVLink is used to simulate different trajectories and collect the required data for the algorithm. The algorithm is validated by comparing the extended Kalman filter estimates with IMU dead‐reckoned positions. Three simulations were performed, consisting of linear, zigzag, and curved trajectories. A percentile error of 2.5 and 4 m is achieved for the x‐coordinate and y‐coordinate, respectively, on the zigzag and curved trajectories. Interestingly, the linear trajectory showed a larger localization error in its y‐coordinate.
High frequency resonance characteristics analysis of voltage‐source virtual synchronous generator and suppression strategy
Authors: Li Zhi , Liu Mingbo , Gong Yu , Li Xudong
Published: January 2024

The voltage‐source virtual synchronous generator is a grid‐forming type power electronic control technology and is able to support converters that have the ability of inertial, primary frequency and voltage regulation. Firstly, the authors build the small‐signal model of the voltage‐source virtual synchronous generator and conventional converters, compare and analyse the characteristics of the high‐frequency resonance modes, the results show that the voltage‐source virtual synchronous generator has almost the same high‐frequency resonance characteristics as the conventional converter. Secondly, the different control parameters and power grid strength that affect the high‐frequency resonance characteristic are analysed with eigenvalue, and the mechanism of voltage‐source VSG that caused high‐frequency resonance is derived. The leading factor that causes high‐frequency resonance is power grid strengths, and the authors proposed introducing virtual impedance into the front‐end channel of the current inner loop control strategy to suppress resonance for the voltage‐source virtual synchronous generator based on the theoretical analysis with the small‐signal model and eigenvalue analysis. In addition, the electromagnetic transient simulation model and RT‐LAB controller‐in‐loop platform are built, and the simulation and experiment results indicate the effectiveness of the virtual impedance control strategy.
Electromagnetic optimization of piezoelectric ceramic and its application in mechanical antenna
Authors: Gao Song , Wang Liwei , Lu Jingtong , Zhang Shuai , Sun Hongyu , Huang Kai , Xu Jianchun , Hao Yanan
Published: January 2024

Mechanical antennas have garnered considerable attention due to their ability to address the challenges posed by the significant size and high energy consumption associated with traditional electric antennas when operating at low frequencies. Here, a compact and structurally stable mechanical antenna design is presented. The proposed antenna is constructed using cylindrical piezoelectric ceramics, which have dimensions smaller than 1/1000 of the wavelength. The scrutiny of the influence exerted by the antenna feed area and material thickness on the radiation performance was undertaken, followed by an exhaustive discourse on these effects. Experimental measurements demonstrate the practical functionalities of signal coding, transmission, and reception in the low‐frequency communication system. Notably, at a frequency of 288 kHz, a single proposed antenna achieves an effective information transmission distance of 60 m using binary information coding. This remarkable outcome underscores the potential of this design in facilitating the development of portable and cost‐effective wireless communication equipment for low‐frequency applications.
Deep learning method for predicting electromagnetic emission spectrum of aerospace equipment
Authors: Zhang Yuting
Published: January 2024

This paper proposes a deep learning method to predict the electromagnetic emission spectrum in the electromagnetic compatibility (EMC) test of aerospace products. A threshold‐based data decomposition method is used to propose the spike signal, reconstruct the original test data, and solve the contradiction between the overfitting and prediction accuracy of the deep learning method to deal with the EMC test spectrum. Using a long short‐term memory neural network architecture for predicting electromagnetic emission spectrum, the Bayesian optimization method is used to optimize the network hyperparameter, and the acquisition function is introduced into the loss function to improve the comprehensive training optimization of deep learning network. Apply the method to three numerical examples: signal line current conduction emission, power line voltage conduction emission, and electric field radiation emission. The analysis results indicate that at a 95% confidence level, the predicted electromagnetic emission spectrum is basically consistent with the test results. The prediction results can be used as the basis for EMC evaluation of aerospace electronic equipment.
Application of the support vector machines method for metal analyse by an eddy current system
Authors: Abramovych Anton , Zaitsev Ievgen , Piddubnyi Volodymyr , Bereznychenko Viktoriia
Published: January 2024

The eddy current method of control analyzed and the possibility of its use for the identification of metals and alloys substantiated. It is shown that this can be done by modernizing the eddy current radio engineering system with dynamic scanning of metal samples, which consists in the use of modern microcontrollers with high‐precision ADC operation. The structural of the modernized system is presented, some aspects of processing the received response signal are considered, which made it possible to highlight the information coefficients that would represent the metal or alloy as a generalized image. It is proposed to use machine learning methods to compare an unknown sample of a metal or alloy under study with those available in the collected database, which is shown on the example of the support vector machine method, which allows for real‐time identification of metals and alloys, to carry out express control, without human intervention in the identification process.
An integrated fuse information fusion method for infrared imaging detector and range finder based on improved particle filter
Authors: Wei Daozhi , Li Ning , Li Junwei
Published: January 2024

Aiming at the traditional integrated fuse information fusion method that cannot simultaneously obtain high‐precision burst control parameters such as burst delay time, azimuth angle, and detection angle, the infrared imaging detector and range finder information fusion method based on particle filtering with BAS algorithm is proposed. Under the centralized information fusion structure that can obtain higher accuracy, first, use a faster linear interpolation method to realize the time alignment of the two asynchronous sensors. Second, for the strong non‐linear observation model in the missile target rendezvous model, use a particle filter framework that is not affected by the nonlinearity of the system function and non‐gaussian noise. Finally, Utilizing the single search BAS algorithm with low computational complexity to solve the problem of particle degradation in particle filtering and improve the accuracy of burst control. The experiment shows that in a typical simulation environment, the optimized information fusion method improves the burst delay time accuracy by 61.82%, azimuth accuracy by 66.28%, detection angle accuracy by 36.15%, and simulation time is shorter compared to traditional methods.
Biochar based tin-oxide nanocomposite for remediation of water
Authors: Kaswan Vipin , Saleem Maha , Harpreet
Published: January 2024

In the present scenario, pure drinking water is a great problem. Scientists are finding out ways to combat this problem. Various approaches are being used for water remediation, but there is always a need to get more economical, eco-friendly and viable method for removal of pollutants from water. In the present study, an attempt have been made to prepare composite (RHAC/SnO2) from biochar from rice husk and SnO2. The comparison of adsorption and photo catalysis for removal of methylene blue (MB)has been done. It was concluded that biochar is efficient in removal of MB by adsorption at all the tested pH, whereas SnO2 has removed 75% MB by adsorption at pH 10. The RHAC/SnO2 composite was found to be a better adsorbent of MB with 90% efficiency, whereas its photocatalytic activity was less with 61% efficiency at pH 10. The present findings need to be further explored so as to get a better insight of the prepared composite.
Pertinence of Literature in Destroying Menstrual Taboos
Authors: Shalini  , Batta Ajoy
Published: January 2024

The impurity of menstrual blood is a universal myth that spans across all societies and cultures. This notion has also established a barrier to gender equality, as females are instructed, throughout cultures, that menstruation is disgraceful. This belief restricts their capacity to conduct regular duties when they are bleeding, hence making them organize their lives around their menstrual period. The need to fill the inadequate understanding of the menstrual cycle in society is a necessity. The third wave of feminism encouraged society to discuss certain challenging topics, which led to considerable breakthroughs in beliefs around menstruation. The day when feminist discussions were limited to people who could pay to express their opinions has long since passed. The concept of feminism in the twenty-first century encompasses a larger spectrum of opinions. Strong arguments on women’s cleanliness and the need for understanding menstruation only serve to emphasize how crucial and significant the issue is. The present paper attempts to explore the myths and taboos, cultural and political perspectives on menstruation, and the role literature is playing in altering society’s attitudes about menstruation. The paper will attempt to comprehend how important literature is in eradicating the stigma associated with menstruation and how it contributes to raising awareness of menstrual hygiene among people.
Three-Dimensional Hydrogel Bioprinting Technology as a Scaffold of Novel Drug Delivery and Biomedical Devices: A Comprehensive Review
Authors: Ramzan Mohhammad , Sabir Mohammed , Singh Sukhbir , Debnath Abhijit
Published: January 2024

Polymer hydrogel used as computer-aided, non-biological arsenal utilize as a drug delivery vehicle overthe past few years.New advances in three-dimensional (3D) bioprinting technology have created new opportunitiesfor the use of hydrogel polymer-based medication delivery systems. 3D printing can deliver the ideal shapes or changecapabilities under specific circumstances which have a better adaptation to physiological function. The accuracy of 3Dprinting technology was significantly higher than that of conventional production techniques.A model bioink acquireproper physicochemical characteristics (mechanical and rheological) and biological properties important for proper functioning.It acts as additive manufacturing with complex spatial structure in biomedical research. In this review, we outlined the currentdevelopments in 3D printed polymer hydrogels as delivery and other platforms.
Writing the Female Body: A Study of Kazuo Ishiguro’s A Pale View of Hills
Authors: Bhola Meenu , Pandya Digvijay
Published: January 2024

Ishiguro projects the struggle of a migrated woman and the search for her identity primarily, at the same time subtly describing the pains and fears of a woman who traverses through the phase of pregnancy and imminent motherhood. Contemporary literary criticism may focus on the problematics of the conscious and subconscious desires of the characters, but body essentially is the locus of all human adventures which are represented through desires, moods, fears, creativity and feelings. The paper discusses Ishiguro’s depiction of pregnancy in A Pale View of Hills and his projection of female body in order to determine that pregnancy and procreation are no longer taboo subjects and to analyze the impact pregnancy has on female. Kristeva talks about the female body, motherhood and pain which is not a construct of the society and culture. She presents a universal and natural interpretation of womanhood. Ishiguro effectively presents this pressure of being a female through Etsuko’s character in A Pale View of Hills. Etsuko’s own painful experience of pregnancy and maternity has made it difficult for her to believe that for other women, pregnancy can be a matter of happiness and joy.