bluuebunny/crossref_metadata_2025 huggingface dataset:
Radiomics approaches to predict PD-L1 and PFS in advanced non-small cell lung patients treated with immunotherapy: a multi-institutional study
Authors: Yolchuyeva Sevinj , Giacomazzi Elena , Tonneau Marion , Lamaze Fabien , Orain Michele , Coulombe François , Malo Julie , Belkaid Wiam , Routy Bertrand , Joubert Philippe , Manem Venkata S. K.
Published: July 2023

With the increasing use of immune checkpoint inhibitors (ICIs), there is an urgent need to identify biomarkers to stratify responders and non-responders using programmed death-ligand (PD-L1) expression, and to predict patient-specific outcomes such as progression free survival (PFS). The current study is aimed to determine the feasibility of building imaging-based predictive biomarkers for PD-L1 and PFS through systematically evaluating a combination of several machine learning algorithms with different feature selection methods. A retrospective, multicenter study of 385 advanced NSCLC patients amenable to ICIs was undertaken in two academic centers. Radiomic features extracted from pretreatment CT scans were used to build predictive models for PD-L1 and PFS (short-term vs. long-term survivors). We first employed the LASSO methodology followed by five feature selection methods and seven machine learning approaches to build the predictors. From our analyses, we found several combinations of feature selection methods and machine learning algorithms to achieve a similar performance. Logistic regression with ReliefF feature selection (AUC = 0.64, 0.59 in discovery and validation cohorts) and SVM with Anova F-test feature selection (AUC = 0.64, 0.63 in discovery and validation datasets) were the best-performing models to predict PD-L1 and PFS. This study elucidates the application of suitable feature selection approaches and machine learning algorithms to predict clinical endpoints using radiomics features. Through this study, we identified a subset of algorithms that should be considered in future investigations for building robust and clinically relevant predictive models.
Study of the biosynthesis and functionality of polyphosphate in Bifidobacterium longum KABP042
Authors: Alcántara Cristina , Perez Marta , Huedo Pol , Altadill Tatiana , Espadaler-Mazo Jordi , Arqués Juan Luis , Zúñiga Manuel , Monedero Vicente
Published: July 2023

Polyphosphate (poly-P) biosynthesis in bacteria has been linked to many physiological processes and has been characterized as an interesting functional molecule involved in intestinal homeostasis. We determined the capacity for poly-P production of 18 probiotic strains mainly belonging to Bifidobacterium and former Lactobacillus genera, showing that poly-P synthesis varied widely between strains and is dependent on the availability of phosphate and the growth phase. Bifidobacteria were especially capable of poly-P synthesis and poly-P kinase (ppk) genes were identified in their genomes together with a repertoire of genes involved in phosphate transport and metabolism. In Bifidobacterium longum KABP042, the strain we found with highest poly-P production, variations in ppk expression were linked to growth conditions and presence of phosphate in the medium. Moreover, the strain produced poly-P in presence of breast milk and lacto-N-tetraose increased the amount of poly-P synthesized. Compared to KABP042 supernatants low in poly-P, exposure of Caco-2 cells to KABP042 supernatants rich in poly-P resulted in decreased epithelial permeability and increased barrier resistance, induction of epithelial protecting factors such as HSP27 and enhanced expression of tight junction protein genes. These results highlight the role of bifidobacteria-derived poly-P as a strain-dependent functional factor acting on epithelial integrity.
Prolonged exposure to high fluoride levels during adolescence to adulthood elicits molecular, morphological, and functional impairments in the hippocampus
Authors: Bittencourt Leonardo Oliveira , Dionizio Aline , Ferreira Maria Karolina Martins , Aragão Walessa Alana Bragança , de Carvalho Cartágenes Sabrina , Puty Bruna , do Socorro Ferraz Maia Cristiane , Zohoori Fatemeh Vida , Buzalaf Marília Afonso Rabelo , Lima Rafael Rodrigues
Published: July 2023

Fluoride is added to water due to its anticariogenic activity. However, due to its natural presence in soils and reservoirs at high levels, it could be a potential environmental toxicant. This study investigated whether prolonged exposure to fluoride from adolescence to adulthood—at concentrations commonly found in artificially fluoridated water and in fluorosis endemic areas—is associated with memory and learning impairments in mice, and assessed the molecular and morphological aspects involved. For this endeavor, 21-days-old mice received 10 or 50 mg/L of fluoride in drinking water for 60 days and the results indicated that the increased plasma fluoride bioavailability was associated with the triggering of short- and long-term memory impairments after high F concentration levels. These changes were associated with modulation of the hippocampal proteomic profile, especially of proteins related to synaptic communication, and a neurodegenerative pattern in the CA3 and DG. From a translational perspective, our data provide evidence of potential molecular targets of fluoride neurotoxicity in the hippocampus at levels much higher than that in artificially fluoridated water and reinforce the safety of exposure to low concentrations of fluoride. In conclusion, prolonged exposure to the optimum fluoride level of artificially fluoridated water was not associated with cognitive impairments, while a higher concentration associated with fluorosis triggered memory and learning deficits, associated with a neuronal density reduction in the hippocampus.
Prediction of injuries, traumas and musculoskeletal pain in elite Olympic and Paralympic volleyball players
Authors: Zwierzchowska Anna , Gaweł Eliza , Gómez Miguel-Angel , Żebrowska Aleksandra
Published: July 2023

The study aimed to identify the prevalence and location of injuries, traumas, and musculoskeletal complaints in Paralympic and Olympic volleyball players with different impairments and initial playing positions (sitting/standing); and to identify the predictors of the abovementioned variables using a multivariate CRT model. Seventy-five elite volleyball players from seven countries took part in the study. They were divided into three study groups: (SG1)—lateral amputee Paralympic volleyball players, (SG2)—able-bodied Paralympic volleyball players, (SG3)—able-bodied Olympic volleyball players. The prevalence and location of the analyzed variables were assessed with surveys quessionaires, while game-related statistics was interpreted based on the CRT analysis. Regardless of the impairment or initial playing position, both the humeral and knee joints were found to be the most frequent locations of musculoskeletal pain and/or injuries in all studied groups, followed by LBP. Players from SG1 and SG3 were characterized by an almost identical prevalence of reported musculoskeletal pain and injuries, what was not noted in SG2. Extrinsic compensatory mechanism (playing position) may be a crucial variable for prediction of musculoskeletal pain and injuries in volleyball players. Lower limb amputation seems to impact the prevalence of musculoskeletal complaints. Training volume may predict the prevalence of LBP.
The effect of chelators on additives in the surface characterization and electrochemical properties of an eco-friendly electroless copper nano deposition
Authors: Jayalakshmi Suseela , Venkatesan Raja , Deepa Simon , A. Vetcher Alexandre , Ansar Sabah , Kim Seong-Cheol
Published: July 2023

We represent the results of a study on as the chelators used in the environmentally friendly electroless deposition bath changed depending on the amounts of hydroxides were present. The baths were prepared using polyhydroxides, glycerol and sorbitol, as chelators with copper methanesulfonate as the metal ion. Dimethylamine borane (DMAB) was used as the reducing agent with N-methylthiourea and cytosine, as additives in both the glycerol and sorbitol contained baths. Potassium hydroxide was used as the pH adjuster, with glycerol and sorbitol baths maintained at a pH of 11.50 and 10.75 respectively at a room temperature of 28 ± 2 °C. XRD, SEM, AFM, cyclic voltammetry studies, Tafel and Impedance studies, as well as additional methods, were employed to monitor and record the surface, structural, and electrochemical characteristics of the deposits and bath. The reports of the study gave interesting results, which clearly the effect of chelators on additives in the nano deposition of copper in an electroless deposition bath.
A fuzzy logic-based secure hierarchical routing scheme using firefly algorithm in Internet of Things for healthcare
Authors: Hosseinzadeh Mehdi , Yoo Joon , Ali Saqib , Lansky Jan , Mildeova Stanislava , Yousefpoor Mohammad Sadegh , Ahmed Omed Hassan , Rahmani Amir Masoud , Tightiz Lilia
Published: July 2023

The Internet of Things (IoT) is a universal network to supervise the physical world through sensors installed on different devices. The network can improve many areas, including healthcare because IoT technology has the potential to reduce pressure caused by aging and chronic diseases on healthcare systems. For this reason, researchers attempt to solve the challenges of this technology in healthcare. In this paper, a fuzzy logic-based secure hierarchical routing scheme using the firefly algorithm (FSRF) is presented for IoT-based healthcare systems. FSRF comprises three main frameworks: fuzzy trust framework, firefly algorithm-based clustering framework, and inter-cluster routing framework. A fuzzy logic-based trust framework is responsible for evaluating the trust of IoT devices on the network. This framework identifies and prevents routing attacks like black hole, flooding, wormhole, sinkhole, and selective forwarding. Moreover, FSRF supports a clustering framework based on the firefly algorithm. It presents a fitness function that evaluates the chance of IoT devices to be cluster head nodes. The design of this function is based on trust level, residual energy, hop count, communication radius, and centrality. Also, FSRF involves an on-demand routing framework to decide on reliable and energy-efficient paths that can send the data to the destination faster. Finally, FSRF is compared to the energy-efficient multi-level secure routing protocol (EEMSR) and the enhanced balanced energy-efficient network-integrated super heterogeneous (E-BEENISH) routing method based on network lifetime, energy stored in IoT devices, and packet delivery rate (PDR). These results prove that FSRF improves network longevity by 10.34% and 56.35% and the energy stored in the nodes by 10.79% and 28.51% compared to EEMSR and E-BEENISH, respectively. However, FSRF is weaker than EEMSR in terms of security. Furthermore, PDR in this method has dropped slightly (almost 1.4%) compared to that in EEMSR.
Impact of gas humidification and nebulizer position under invasive ventilation: preclinical comparative study of regional aerosol deposition
Authors: Montigaud Yoann , Georges Quentin , Leclerc Lara , Clotagatide Anthony , Louf-Durier Aurore , Pourchez Jérémie , Prévôt Nathalie , Périnel-Ragey Sophie
Published: July 2023

Successful aerosol therapy in mechanically ventilated patients depends on multiple factors. Among these, position of nebulizer in ventilator circuit and humidification of inhaled gases can strongly influence the amount of drug deposited in airways. Indeed, the main objective was to preclinically evaluate impact of gas humidification and nebulizer position during invasive mechanical ventilation on whole lung and regional aerosol deposition and losses. Ex vivo porcine respiratory tracts were ventilated in controlled volumetric mode. Two conditions of relative humidity and temperature of inhaled gases were investigated. For each condition, four different positions of vibrating mesh nebulizer were studied: (i) next to the ventilator, (ii) right before humidifier, (iii) 15 cm to the Y-piece adapter and (iv) right after the Y-piece. Aerosol size distribution were calculated using cascade impactor. Nebulized dose, lung regional deposition and losses were assessed by scintigraphy using 99mtechnetium-labeled diethylene-triamine-penta-acetic acid. Mean nebulized dose was 95% ± 6%. For dry conditions, the mean respiratory tract deposited fractions reached 18% (± 4%) next to ventilator and 53% (± 4%) for proximal position. For humidified conditions, it reached 25% (± 3%) prior humidifier, 57% (± 8%) before Y-piece and 43% (± 11%) after this latter. Optimal nebulizer position is proximal before the Y-piece adapter showing a more than two-fold higher lung dose than positions next to the ventilator. Dry conditions are more likely to cause peripheral deposition of aerosols in the lungs. But gas humidification appears hard to interrupt efficiently and safely in clinical use. Considering the impact of optimized positioning, this study argues to maintain humidification.
Exploring park visitation trends during the Covid-19 pandemic in Hungary by using mobile device location data
Authors: Csomós György , Borza Endre Márk , Farkas Jenő Zsolt
Published: July 2023

Sweeping changes in park visitation have accompanied the Covid-19 pandemic. In countries where governments imposed strict lockdowns during the first wave, park visitation declined in cities. The benefits of visiting urban green spaces on people’s mental and physical health and well-being are generally acknowledged; many people in confinement during lockdowns reported increasing mental health issues. Therefore, based on lessons learned from the Covid-19 pandemic’s first wave, urban parks and other urban green spaces remained open in most countries in subsequent pandemic phases. Furthermore, many studies have reported an overall increase in park visitation after strict lockdowns imposed in the pandemic’s first wave have been removed. This study aims to investigate park visitation trends in Hungary based on a dataset of 28 million location data points from approximately 666,000 distinct mobile devices collected in 1884 urban parks and other urban green spaces in 191 settlements between June 1, 2019, and May 31, 2021. Findings demonstrate that park visitation increased in the inter-wave period of 2020, compared to the pre-pandemic period of 2019, and decreased in Waves 2–3 of 2021, compared to Wave 1 of 2020.
Extreme precipitation patterns in the Asia–Pacific region and its correlation with El Niño-Southern Oscillation (ENSO)
Authors: An Dong , Eggeling Jakob , Zhang Linus , He Hao , Sapkota Amir , Wang Yu-Chun , Gao Chuansi
Published: July 2023

In the Asia–Pacific region (APR), extreme precipitation is one of the most critical climate stressors, affecting 60% of the population and adding pressure to governance, economic, environmental, and public health challenges. In this study, we analyzed extreme precipitation spatiotemporal trends in APR using 11 different indices and revealed the dominant factors governing precipitation amount by attributing its variability to precipitation frequency and intensity. We further investigated how these extreme precipitation indices are influenced by El Niño-Southern Oscillation (ENSO) at a seasonal scale. The analysis covered 465 ERA5 (the fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts) study locations over eight countries and regions during 1990–2019. Results revealed a general decrease indicated by the extreme precipitation indices (e.g., the annual total amount of wet-day precipitation, average intensity of wet-day precipitation), particularly in central-eastern China, Bangladesh, eastern India, Peninsular Malaysia and Indonesia. We observed that the seasonal variability of the amount of wet-day precipitation in most locations in China and India are dominated by precipitation intensity in June–August (JJA), and by precipitation frequency in December–February (DJF). Locations in Malaysia and Indonesia are mostly dominated by precipitation intensity in March–May (MAM) and DJF. During ENSO positive phase, significant negative anomalies in seasonal precipitation indices (amount of wet-day precipitation, number of wet days and intensity of wet-day precipitation) were observed in Indonesia, while opposite results were observed for ENSO negative phase. These findings revealing patterns and drivers for extreme precipitation in APR may inform climate change adaptation and disaster risk reduction strategies in the study region.
Research on the data validity of a coal mine solid backfill working face sensing system based on an improved transformer
Authors: Bo Lei , Yang Shangqing , Liu Yang , Wang Yanwen , Zhang Zihang
Published: July 2023

Solid backfilling in coal mining refers to filling the goaf with solid materials to form a support structure, ensuring safety in the ground and upper mining areas. This mining method maximizes coal production and addresses environmental requirements. However, in traditional backfill mining, challenges exist, such as limited perception variables, independent sensing devices, insufficient sensing data, and data isolation. These issues hinder the real-time monitoring of backfilling operations and limit intelligent process development. This paper proposes a perception network framework specifically designed for key data in solid backfilling operations to address these challenges. Specifically, it analyses critical perception objects in the backfilling process and proposes a perception network and functional framework for the coal mine backfilling Internet of Things (IoT). These frameworks facilitate rapidly concentrating key perception data into a unified data centre. Subsequently, the paper investigates the assurance of data validity in the perception system of the solid backfilling operation within this framework. Specifically, it considers potential data anomalies that may arise from the rapid data concentration in the perception network. To mitigate this issue, a transformer-based anomaly detection model is proposed, which filters out data that does not reflect the true state of perception objects in solid backfilling operations. Finally, experimental design and validation are conducted. The experimental results demonstrate that the proposed anomaly detection model achieves an accuracy of 90%, indicating its effective detection capability. Moreover, the model exhibits good generalization ability, making it suitable for monitoring data validity in scenarios involving increased perception objects in solid backfilling perception systems.
Kinetics of chemical deteriorations over the frying protected by gallic acid and methyl gallate
Authors: Hosseinkhani Maedeh , Farhoosh Reza
Published: July 2023

The present work shows the possibility of use of gallic acid (GA) and methyl gallate (MG) as natural antioxidants replacing the powerful synthetic antioxidant TBHQ in frying process. Oxidative stability index (OSI) and the kinetics of change in lipid-peroxidation conjugated dienes (LCD), carbonyls (LCO), and acid value were adopted for the evaluation purposes. GA alone (1.2 mM) and in combination with MG (75:25) provided OSI values comparable to that of TBHQ (18.5–19.0 h). The GA/MG 75:25 exerted a frying performance quite better than TBHQ (rn = 0.1351 vs. 0.1784 h−1) in preventing the LCD formation. From the LCO formation standpoint, the GA/MG 75:25 (rn = 0.0758 h−1) and then MG (rn = 0.1004 h−1) provided better performances than TBHQ (rn = 0.1216 h−1). Lipid hydrolysis was also inhibited well by GA (AVm = 8.6) and GA/MG 75:25 (AVm = 7.9), respectively (AVm = 9.2 for TBHQ).
An assessment of the ENSO-monsoon teleconnection in a warming climate
Authors: Goswami Bidyut Bikash , An Soon-Il
Published: July 2023

The El Niño-Southern Oscillation (ENSO) and the Indian summer monsoon (ISM, or monsoon) are two giants of tropical climate. Here we assess the future evolution of the ENSO-monsoon teleconnection in climate simulations with idealized forcing of CO2 increment at a rate of 1% year-1 starting from a present-day condition (367 p.p.m.) until quadrupling. We find a monotonous weakening of the ENSO-monsoon teleconnection with the increase in CO2. Increased co-occurrences of El Niño and positive Indian Ocean Dipoles (pIODs) in a warmer climate weaken the teleconnection. Co-occurrences of El Niño and pIOD are attributable to mean sea surface temperature (SST) warming that resembles a pIOD-type warming pattern in the Indian Ocean and an El Niño-type warming in the Pacific. Since ENSO is a critical precursor of the strength of the Indian monsoon, a weakening of this relation may mean a less predictable Indian monsoon in a warmer climate.
The performance of serious games for enhancing attention in cognitively impaired older adults
Authors: Abd-alrazaq Alaa , Abuelezz Israa , Al-Jafar Eiman , Denecke Kerstin , Househ Mowafa , Aziz Sarah , Ahmed Arfan , Aljaafreh Ali , AlSaad Rawan , Sheikh Javaid
Published: July 2023

Attention, which is the process of noticing the surrounding environment and processing information, is one of the cognitive functions that deteriorate gradually as people grow older. Games that are used for other than entertainment, such as improving attention, are often referred to as serious games. This study examined the effectiveness of serious games on attention among elderly individuals suffering from cognitive impairment. A systematic review and meta-analyses of randomized controlled trials were carried out. A total of 10 trials ultimately met all eligibility criteria of the 559 records retrieved. The synthesis of very low-quality evidence from three trials, as analyzed in a meta-study, indicated that serious games outperform no/passive interventions in enhancing attention in cognitively impaired older adults (P < 0.001). Additionally, findings from two other studies demonstrated that serious games are more effective than traditional cognitive training in boosting attention among cognitively impaired older adults. One study also concluded that serious games are better than traditional exercises in enhancing attention. Serious games can enhance attention in cognitively impaired older adults. However, given the low quality of the evidence, the limited number of participants in most studies, the absence of some comparative studies, and the dearth of studies included in the meta-analyses, the results remain inconclusive. Thus, until the aforementioned limitations are rectified in future research, serious games should serve as a supplement, rather than a replacement, to current interventions.
Physiologically relevant acid-sensing ion channel (ASIC) 2a/3 heteromers have a 1:2 stoichiometry
Authors: Fischer Leon , Schmidt Axel , Dopychai Anke , Joussen Sylvia , Joeres Niko , Oslender-Bujotzek Adrienne , Schmalzing Günther , Gründer Stefan
Published: July 2023

Acid-sensing ion channels (ASICs) sense extracellular protons and are involved in synaptic transmission and pain sensation. ASIC1a and ASIC3 are the ASIC subunits with the highest proton sensitivity. ASIC2a in contrast has low proton sensitivity but increases the variability of ASICs by forming heteromers with ASIC1a or ASIC3. ASICs are trimers and for the ASIC1a/2a heteromer it has been shown that subunits randomly assemble with a flexible 1:2/2:1 stoichiometry. Both heteromers have almost identical proton sensitivity intermediate between ASIC1a and ASIC2a. Here, we investigated the stoichiometry of the ASIC2a/3 heteromer. Using electrophysiology, we extensively characterized, first, cells expressing ASIC2a and ASIC3 at different ratios, second, concatemeric channels with a fixed subunit stoichiometry, and, third, channels containing loss-of-functions mutations in specific subunits. Our results conclusively show that only ASIC2a/3 heteromers with a 1:2 stoichiometry had a proton-sensitivity intermediate between ASIC2a and ASIC3. In contrast, the proton sensitivity of ASIC2a/3 heteromers with a 2:1 stoichiometry was strongly acid-shifted by more than one pH unit, which suggests that they are not physiologically relevant. Together, our results reveal that the proton sensitivity of the two ASIC2a/3 heteromers is clearly different and that ASIC3 and ASIC1a make remarkably different contributions to heteromers with ASIC2a.
Plasmarons in high-temperature cuprate superconductors
Authors: Yamase Hiroyuki , Bejas Matías , Greco Andrés
Published: July 2023

Metallic systems exhibit plasmons as elementary charge excitations. This fundamental concept was reinforced also in high-temperature cuprate superconductors recently, although cuprates are not only layered systems but also strongly correlated electron systems. Here, we study how such ubiquitous plasmons leave their marks on the electron dispersion in cuprates. In contrast to phonons and magnetic fluctuations, plasmons do not yield a kink in the electron dispersion. Instead, we find that the optical plasmon accounts for an emergent band—plasmarons—in the one-particle excitation spectrum; acoustic-like plasmons typical to a layered system are far less effective. Because of strong electron correlations, the plasmarons are generated by bosonic fluctuations associated with the local constraint, not by the usual charge-density fluctuations. Apart from this physical mechanism, the plasmarons are similar to those discussed in alkali metals, Bi, graphene, monolayer transition-metal dichalcogenides, semiconductors, diamond, two-dimensional electron systems, and SrIrO3 films, establishing a concept of plasmarons in metallic systems in general. Plasmarons are realized below (above) the quasiparticle band in electron-doped (hole-doped) cuprates, including a region around (π, 0) and (0, π) where the superconducting gap and the pseudogap are most enhanced.
A novel biosensor based on a bio-barcode for the detection of Mycobacterium tuberculosis
Authors: Wei Shanhong , Dou Yanzhi , Yu Yuanyuan , Yang Jinghui , Yu Fangyou , Sha Wei , Li Tie
Published: July 2023

A novel biosensor combining magnetic separation, urease catalysis and SiNW FET detection is reported for simple, rapid and sensitive detection of Mycobacterium tuberculosis DNA.
Construction of a hierarchical membrane with angstrom-scale ion channels for enhanced Li+/Mg2+ separation
Authors: Fu Lin , Wang Qingchen , Hu Yuhao , Qian Yongchao , Xin Weiwen , Zhou Shengyang , Kong Xiang-Yu , Wen Liping
Published: July 2023

This work reports a ZIF-8/MXene membrane with a hierarchical channel structure fabricated via facile phytic acid-assisted electrochemical deposition. The resulting membrane achieved Li+/Mg2+ sieving performance with the perm-selectivity up to 47.4.
Permanent irreversible structural color based on core–shell chemically bonded SiO2@P(St-BA) particles
Authors: Song Liujun , Qi Yong , Zhang Shufen
Published: July 2023

Permanent irreversible structural color patterns based on the thermal collapse of core–shell chemically bonded SiO2@P(St-BA) particles.
LC567: a new 2D semimetallic carbon allotrope as a promising anode material for lithium-ion batteries
Authors: Cai Yusheng , Wei Yi , Lv Cuihong , Zhang Lichuan , Chen Yuanping
Published: July 2023

LC567, a new 2D semimetallic carbon allotrope with Dirac points, is proposed for high-performance lithium-ion battery anodes.
Scope and significance of transition metal oxide nanomaterials for next-generation Li-ion batteries
Authors: Saravanan Raaju Sundhar Arul , Bejigo Keyru Serbara , Kim Sang-Jae
Published: July 2023

This article presents a comprehensive overview of the current state-of-the-art research on the use of nanomaterials in batteries and provides valuable insights into their potential applications.
Advances in multicolor electrochromic devices based on inorganic materials
Authors: Huang Lin , Cao Sheng , Liang Yi , Chen Junyao , Yang Tao , Zhao Jialong , Zou Bingsuo
Published: July 2023

This review article focuses on the latest research progress in the construction of multicolor EC devices based on the intrinsic chemical and structural colors of inorganic materials.
Domain‐adapted driving scene understanding with uncertainty‐aware and diversified generative adversarial networks
Authors: Hua Yining , Sui Jie , Fang Hui , Hu Chuan , Yi Dewei
Published: July 2023

Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel. It requires massive pixel‐level labelled data to optimise the network. However, it is challenging to collect sufficient data and labels in the real world. An alternative solution is to obtain synthetic dense pixel‐level labelled data from a driving simulator. Although the use of synthetic data is a promising way to alleviate the labelling problem, models trained with virtual data cannot generalise well to realistic data due to the domain shift. To fill this gap, the authors propose a novel uncertainty‐aware generative ensemble method. In particular, ensembles are obtained from different optimisation objectives, training iterations, and network initialisation so that they are complementary to each other to produce reliable predictions. Moreover, an uncertainty‐aware ensemble scheme is developed to derive fused prediction by considering the uncertainty from ensembles. Such a design can make better use of the strengths of ensembles to enhance adapted segmentation performance. Experimental results demonstrate the effectiveness of our method on three large‐scale datasets.
A case study of environmental considerations and opportunities in cyber physical systems
Authors: Cortes‐Cornax Mario , Lago Paula , Roncancio Claudia
Published: July 2023

Cyber Physical Systems (CPS) are becoming more ubiquitous, complex and powerful as well as more and more present in our daily life. The inherent benefit and comfort come with an environmental impact at every step of their life‐cycle. This impact is significant and unfortunately often ignored today. As cyber‐physical systems tend to be ‘invisible’, there is a need for awareness of the underlying infrastructure and required resources, early in the design phases. In this article, the environmental impact considerations in the early stages of the implementation and opportunities to improve design choices with a people‐planet‐system perspective are discussed. The authors discuss the aspects related to system configuration, data management and the overall goal and functionalities supported by the CPS. Through a specific smart home case, the potential of considering life‐cycle assessment of both the devices and data management is illustrated. By explicitly considering different configurations, it will be possible to analyse the environmental impacts of the design decisions. Our research in progress targets a design approach to converge into an equilibrium between utility, performance, and minor environmental impact of smart systems.
Robust Malware identification via deep temporal convolutional network with symmetric cross entropy learning
Authors: Sun Jiankun , Luo Xiong , Wang Weiping , Gao Yang , Zhao Wenbing
Published: July 2023

Recent developments in the field of Internet of things (IoT) have aroused growing attention to the security of smart devices. Specifically, there is an increasing number of malicious software (Malware) on IoT systems. Nowadays, researchers have made many efforts concerning supervised machine learning methods to identify malicious attacks. High‐quality labels are of great importance for supervised machine learning, but noises widely exist due to the non‐deterministic production environment. Therefore, learning from noisy labels is significant for machine learning‐enabled Malware identification. In this study, motivated by the symmetric cross entropy with satisfactory noise robustness, the authors propose a robust Malware identification method using temporal convolutional network (TCN). Moreover, word embedding techniques are generally utilised to understand the contextual relationship between the input operation code (opcode) and application programming interface function names. Here, considering the numerous unlabelled samples in real‐world intelligent environments, the authors pre‐train the TCN model on an unlabelled set using a word embedding method, that is, Word2Vec. In the experiments, the proposed method is compared with several traditional statistical methods and more recent neural networks on a synthetic Malware dataset and a real‐world dataset. The performance comparisons demonstrate the better performance and noise robustness of their proposed method, especially that the proposed method can yield the best identification accuracy of 98.75% in real‐world scenarios.
Adoption of blended learning: Chinese university students’ perspectives
Authors: Yu Teng , Dai Jian , Wang Chengliang
Published: July 2023

Against the backdrop of the deep integration of the Internet with learning, blended learning offers the advantages of combining online and face-to-face learning to enrich the learning experience and improve knowledge management. Therefore, the objective of this present study is twofold: a. to fill a gap in the literature regarding the adoption of blended learning in the post-pandemic era and the roles of both the technology acceptance model (TAM) and the theory of planned behavior (TPB) in this context and b. to investigate the factors influencing behavioral intention to adopt blended learning. For that purpose, the research formulates six hypotheses, incorporates them into the proposed conceptual model, and validates them using model-fit indices. Based on data collected from Chinese university students, the predicted model’s reliability and validity are evaluated using structural equation modeling (SEM). The results of SEM show that (a) the integrated model based on the TAM and the TPB can explain 67.6% of the variance in Chinese university students’ adoption of blended learning; (b) perceived usefulness (PU), perceived ease of use (PEU), and subjective norms (SN) all have positive impacts on learning attitudes (LA); (c) PEU has a positive influence on PU, and SN has a positive influence on perceived behavioral control (PBC); and (d) both PU and LA have a positive influence on the intention to adopt blended learning (IABL). However, PEU, SN, and PBC have little effect on IABL; e. LA mediates the effect of PU on IABL, and PU mediates the effect of PEU on IABL. This study demonstrated that an integrated conceptual framework based on the TAM and the TPB as well as the characteristics of blended learning offers an effective way to understand Chinese university students’ adoption of blended learning.
Mode transformation for a Schrödinger type equation: Avoided and unavoidable level crossings
Authors: Fialkovsky Ignat , Perel Maria
Published: July 2023

Methods elaborated in quantum mechanics for the Landau–Zener problem are generalized to study the non-adiabatic transitions in a wide class of problems of wave propagation, in particular in the waveguide problems. If the properties of the waveguide slowly vary along its axis and the phase velocities of two modes have a degeneracy point or are almost degenerate near some point, the transformation of modes may occur. The conditions are formulated under which we can find formal asymptotic expansions of modes outside the vicinity of the degeneracy point and write out explicitly the transition matrix. The starting point is rewriting the governing equations in the form of the Schrödinger type equation. The Hamiltonian is assumed to be the result of a small perturbation of an operator with a degeneracy point of the crossing types of two eigenvalues. The perturbation of the Hamiltonian produces a close pair of simple degeneracy points. Two regimes of mode transformation for the Schrödinger type equation are identified: avoided crossing of eigenvalues (corresponding to complex degeneracy points) and an explicit unavoidable crossing (with real degeneracy points).
System dynamics monitoring using PIC micro-controller-based PLSE
Authors: Djeufa Dagoumguei Guy Morgand , Tagne Samuel , Eyebe Fouda J. S. Armand , Koepf Wolfram
Published: July 2023

The permutation largest slope entropy (PLSE) algorithm has been shown to be effective to distinguish between regular and non-regular dynamics from time series analysis. However, as it is the case for many non-linear time series analysis algorithms, such a characterization is locally made and does not allow one to capture some micro-phenomena, such as intermittency, that may occur in the system behavior. This paper presents a PIC micro-controller based implementation of the PLSE for a real-time monitoring of system dynamics. The PLSE algorithm is optimized to fit the program and data memory of low-end processors using the XC8 compiler and the MPLAB X IDE. The resulting algorithm is implemented on the PIC16F18446 and deployed on the Explorer 8 development board. The effectiveness of the developed tool is validated by considering an electrical circuit of the Duffing oscillator that can generate both periodic and chaotic dynamics. By comparing the PLSE values with the phase portraits and previous results on the Duffing oscillator circuit, the developed tool efficiently allows one to monitor the behavior of dynamical systems.
Strong single-photon to two-photon bundles emission in spin-1 Jaynes–Cummings model
Authors: Tang Jing , Deng Yuangang
Published: July 2023

High-quality special nonclassical states beyond the strong single atom-cavity coupling regime are fundamental elements in quantum information science. Here, we study strong single-photon blockade to two-photon bundles emission in a single spin-1 atom coupled to an optical cavity by constructing a spin-1 Jaynes–Cummings model (JCM). By tuning the quadratic Zeeman shift, the energy-spectrum anharmonicity can be significantly enhanced, leading to a remarkable increase in the dressed-state splitting of the well-resolved n-photon resonance. The mechanism, which benefits from the internal degrees of freedom in high-spin systems, compensates for the strong coupling condition required by the multi-photon blockade, thereby facilitating the experimental feasibility of engineering special nonclassical states beyond the strong-coupling limit. It is shown that the photon emission from the spin-1 JCM demonstrates high-quality single photon and two-photon bundles with large steady-state photon numbers in the cavity-driven and atom-pump cases, respectively. In particular, compared to the two-level two-photon JCM, the antibunching amplitude of the three-order correlation function for two-photon bundles in the spin-1 JCM is enhanced by 3 orders of magnitude. More interestingly, a multimode transducer, enabling a transition from strong single-photon blockade to two-photon bundles and super-Poissonian photon emission, is achieved and highly controllable by the light-cavity detuning in the presence of both atom and cavity driven fields. This study based on the high-spin JCM broadens the scope of engineering special nonclassical quantum states beyond the standard two-level JCM. Our proposal not only opens up a new avenue for generating high-quality n-photon sources but also provides versatile applications in quantum networks and metrology.
Analog of electromagnetically induced transparency based on asymmetric nickel-ferrite metamaterials in THz regime
Authors: Kim Tae-Han , Yoo Young Joon , Park Sang Yoon , Lee Bo Wha
Published: July 2023

The electromagnetically induced transparency-like characteristics of asymmetric nickel-ferrite metamaterials through near-field coupling are investigated in the terahertz regime. The nickel-ferrite metamaterial consists of a cut wire resonator on the front side and a disk resonator at the back of the quartz substrate. The analog of electromagnetically induced transparency is characterized by employing a finite difference frequency domain technique. By designing the nickel-ferrite metamaterial to overcome Snoek’s limitation of ferrite materials in the THz spectral region, electromagnetically induced transparency-like spectral features with a high quality factor and slow-light effect are achieved. These results may provide an important way to understand the coupling mechanism and ferrite material application in slow-light devices, THz sensors, and tunable switching in THz frequency bands.
Early warning of tipping in a chemical model with cross-diffusion via spatiotemporal pattern formation and transition
Authors: Lu Yunxiang , Xiao Min , Huang Chengdai , Cheng Zunshui , Wang Zhengxin , Cao Jinde
Published: July 2023

The spatiotemporal pattern formation and transition driven by cross-diffusion of the Gray–Scott model are investigated for the early warning of tipping in this paper. The mathematical analyses of the corresponding non-spatial model and spatial model are performed first, which enable us to have a comprehensive understanding. Then, the linear stability analysis and the multiple scale analysis method exhibit that cross-diffusion is the key mechanism for the evolution of spatiotemporal patterns. Through selecting a cross-diffusion coefficient as the bifurcation parameter, the amplitude equations that can describe structural transition and determine the stability of different types of Turing patterns are derived. Ultimately, numerical simulations verify the validity of the theoretical results. It is demonstrated that in the absence of cross-diffusion, the spatiotemporal distribution of substances is homogeneous. Nevertheless, when the cross-diffusion coefficient exceeds its threshold value, the spatiotemporal distribution of substances will become inhomogeneous in space. As the cross-diffusion coefficient increases, the Turing instability region will be extended, leading to various types of Turing patterns: spots, stripes, and a mixture of spots and stripes.
Fast equilibrium reconstruction by deep learning on EAST tokamak
Authors: Lu Jingjing , Hu Youjun , Xiang Nong , Sun Youwen
Published: July 2023

A deep neural network is developed and trained on magnetic measurements (input) and EFIT poloidal magnetic flux (output) on the EAST tokamak. In optimizing the network architecture, we use automatic optimization to search for the best hyperparameters, which helps in better model generalization. We compare the inner magnetic surfaces and last-closed-flux surfaces with those from EFIT. We also calculated the normalized internal inductance, which is completely determined by the poloidal magnetic flux and can further reflect the accuracy of the prediction. The time evolution of the internal inductance in full discharge is compared with that provided by EFIT. All of the comparisons show good agreement, demonstrating the accuracy of the machine learning model, which has high spatial resolution compared with the off-line EFIT while still meeting the time constraint of real-time control.
Three-dimensional imaging by compressed sensing based dual-frequency laser phase ranging
Authors: Jie Yuchen , Li Xiaotian , Zhang Zilong , Wang Jie , Hu Yetong , Li Yabi , He Wei , Zhao Changming
Published: July 2023

Scanless three-dimensional (3D) imaging technology has received extensive attention in recent years due to its rapid detection and system reliability. Compressed sensing imaging technology provides a new solution for the realization of scan-free 3D imaging. In this paper, a 3D imaging method based on dual-frequency laser phase ranging based on compressed sensing technology is introduced and realized. Using the combination of dual-frequency laser phase ranging and compressed sensing theory, two-dimensional range reconstruction from the time-domain light intensity signal collected by a single-point detector is performed. Aiming at the spatial sparsity of the target scene, this technology uses the compressed sensing algorithm to solve the phase information of the two-dimensional spatial distribution contained in the time domain signal so as to invert the 3D image information of the target scene and realize the effect of scanning-free 3D imaging. First, the feasibility of the system is verified by simulations, and the imaging effects of different reconstruction algorithms on different terrains are compared. Second, a non-scanning 3D imaging experimental platform is designed and built. Finally, the 3D images of multiple objects with 32 × 32 resolution are successfully reconstructed through experiments with a compression ratio of 0.25. The ranging accuracy of this system is 0.05 m. This work is promising for applications in multiple objects’ fast detections.
Breakthrough the physical barrier on spatial resolution in Raman distributed fiber sensing using chaotic correlation demodulation
Authors: Li Jian , Wang Chenyi , Cao Kangyi , Fan Bowen , Zhou Xinxin , Xu Yang , Cheng Zijia , Zhang Qian , Qiao Lijun , Xue Xiaohui , Zhang Jianzhong , Zhang Mingjiang
Published: July 2023

Raman distributed optical fiber temperature sensors possess the unique capability of measuring spatial environmental temperatures, which can be of great interest in several fields of application. The key physics barrier to spatial resolution for most optical time-domain reflection (OTDR) systems is the positioning principle of pulse-time-flight. It obtains the spatial resolution of the existing Raman distributed optical fiber temperature sensor, with the kilometer-level sensing distance being limited to the meter-level. Here, we propose a chaotic laser Raman distributed optical fiber temperature sensing scheme that replaces the traditional OTDR positioning principle used for more than 40 years with the chaotic correlation positioning principle. The proposed scheme possesses the characteristics of the chaos Raman scattering light excited by the chaos signal along the sensing fiber. A novel measurement mechanism based on chaotic time-domain differential reconstruction and chaotic correlation demodulation is developed, and a relationship between the temperature variation information and the chaotic correlation peak is experimentally demonstrated. Importantly, the proposed optics mechanism scheme overcomes the physics limitation of the effect of a wide pulse width on sensing spatial resolution; its spatial resolution is optimized from 50 to 0.3 m under the modulation of a 500 ns pulse width. This scheme provides a new concept for chaos optics and fiber sensing research.
A physical understanding and quantification for the regulation of orexin on sleep
Authors: Yao Chenggui , Xu Fei , Tang Xiangdong , Zou Wei , Yang Dongping , Shuai Jianwei
Published: July 2023

The orexinergic neurons located in the lateral hypothalamus play a vital role in maintaining wakefulness and regulating sleep stability. Previous research has demonstrated that the absence of orexin (Orx) can trigger narcolepsy, a condition characterized by frequent shifts between wakefulness and sleep. However, the specific mechanisms and temporal patterns through which Orx regulates wakefulness/sleep are not fully understood. In this study, we developed a new model that combines the classical Phillips–Robinson sleep model with the Orx network. Our model incorporates a recently discovered indirect inhibition of Orx on sleep-promoting neurons in the ventrolateral preoptic nucleus. By integrating appropriate physiological parameters, our model successfully replicated the dynamic behavior of normal sleep under the influence of circadian drive and homeostatic processes. Furthermore, our results from the new sleep model unveiled two distinct effects of Orx: excitation of wake-active neurons and inhibition of sleep-active neurons. The excitation effect helps to sustain wakefulness, while the inhibition effect contributes to arousal, consistent with experimental findings [De Luca et al., Nat. Commun. 13, 4163 (2022)]. Moreover, we utilized the theory of potential landscapes to investigate the physical mechanisms underlying the frequent transitions observed in narcolepsy. The topography of the underlying landscape delineated the brain’s capacity to transition between different states. Additionally, we examined the impact of Orx on barrier height. Our analysis demonstrated that a reduced level of Orx led to a bistable state with an extremely low threshold, contributing to the development of narcoleptic sleep disorder.