bluuebunny/crossref_metadata_2025 huggingface dataset:
Unveiling the Dual Nature of Heavy Metals: Stressors and Promoters of Phenolic Compound Biosynthesis in Basilicum polystachyon (L.) Moench In Vitro
Authors: Das Sumanta , Sultana Kaniz Wahida , Mondal Moupriya , Chandra Indrani , Ndhlala Ashwell R.
Published: December 2023

The global industrial revolution has led to a substantial rise in heavy metal levels in the environment, posing a serious threat to nature. Plants synthesize phenolic compounds under stressful conditions, which serve as protective agents against oxidative stress. Basilicum polystachyon (L.) Moench is an herbaceous plant of the Lamiaceae family. Some species within this family are recognized for their capacity to remediate sites contaminated with heavy metals. In this study, the effects of mercury (II) chloride and lead (II) nitrate on the in vitro propagation of B. polystachyon were investigated. Shoot tips from in vitro plantlets were cultured in Murashige and Skoog’s (MS) media with heavy metals ranging from 1 to 200 µM to induce abiotic stress and enhance the accumulation of phenolic compounds. After three weeks, MS medium with 1 µM of lead (II) supported the highest shoot multiplication, and the maximum number of roots per explant was found in 100 µM of lead (II), whereas a higher concentration of heavy metals inhibited shoot multiplication and root development. The plantlets were hardened in a greenhouse with a 96% field survival rate. Flame atomic absorption spectroscopy (FAAS) was used to detect heavy metal contents in plant biomass. At both 200 µM and 50 µM concentrations, the greatest accumulation of mercury (II) was observed in the roots (16.94 ± 0.44 µg/g) and shoots (17.71 ± 0.66 µg/g), respectively. Similarly, lead (II) showed the highest accumulation in roots (17.10 ± 0.54 µg/g) and shoots (7.78 ± 0.26 µg/g) at 200 µM and 50 µM exposures, respectively. Reverse-phase high-performance liquid chromatography (RP-HPLC) identified and quantified various phenolic compounds in B. polystachyon leaves, including gallic acid, caffeic acid, vanillic acid, p-coumaric acid, ellagic acid, rosmarinic acid, and trans-cinnamic acid. These compounds were found in different forms, such as free, esterified, and glycosylated. Mercury (II)-exposed plants exhibited elevated levels of vanillic acid (1959.1 ± 3.66 µg/g DW), ellagic acid (213.55 ± 2.11 µg/g DW), and rosmarinic acid (187.72 ± 1.22 µg/g DW). Conversely, lead (II)-exposed plants accumulated higher levels of caffeic acid (42.53±0.61 µg/g DW) and p-coumaric acid (8.04 ± 0.31 µg/g DW). Trans-cinnamic acid was the predominant phenolic compound in control plants, with a concentration of 207.74 ± 1.45 µg/g DW. These results suggest that sublethal doses of heavy metals can act as abiotic elicitors, enhancing the production of phenolic compounds in B. polystachyon. The present work has the potential to open up new commercial opportunities in the pharmaceutical industry.
The Lotus angustissumus Group (Fabaceae): Can Phylogenetic Patterns Be Accommodated by a Taxonomic Concept?
Authors: Kramina Tatiana E. , Hadziev Tamerlan R. , Samigullin Tahir H.
Published: December 2023

The Lotus angustissimus group represents an example of obvious contradictions between the molecular and morphological data. This group includes from six to eight mostly annual species of Lotus section Lotus, with the center of species diversity in the Mediterranean. We performed a phylogenetic analysis of the genus Lotus with an expanded representation of all known species of the L. angustissimus group using both nuclear (nrITS) and a set of plastid DNA markers and compared the results with traditional taxonomy of this group. Our results demonstrated a non-monophyletic nature of the study group. In addition, the nrITS and plastid dataset tree topologies were incongruent with each other in both Bayesian and ML analyses. We revealed very complex phylogenetic relationships among the species of the group. Important results obtained in this study are: (1) genetic and geographical differentiation in the latitudinal direction (between L. angustissimus and L. praetermissus) and in the longitudinal direction among closely related accessions identified as L. castellanus, L. lourdes-santiagoi and L. palustris; (2) close genetic links between the Anatolian endemic L. macrotrichus and L. praetermissus from Eastern Europe and Central Asia; and (3) the hybrid nature of L. subbiflorus with L. parviflorus as its presumed male parent species. These results are discussed in the context of morphology, biogeography and taxonomy.
MtWOX2 and MtWOX9-1 Effects on the Embryogenic Callus Transcriptome in Medicago truncatula
Authors: Krasnoperova Elizaveta Y. , Tvorogova Varvara E. , Smirnov Kirill V. , Efremova Elena P. , Potsenkovskaia Elina A. , Artemiuk Anastasia M. , Konstantinov Zakhar S. , Simonova Veronika Y. , Brynchikova Anna V. , Yakovleva Daria V. , Pavlova Daria B. , Lutova Ludmila A.
Published: December 2023

WOX family transcription factors are well-known regulators of plant development, controlling cell proliferation and differentiation in diverse organs and tissues. Several WOX genes have been shown to participate in regeneration processes which take place in plant cell cultures in vitro, but the effects of most of them on tissue culture development have not been discovered yet. In this study, we evaluated the effects of MtWOX2 gene overexpression on the embryogenic callus development and transcriptomic state in Medicago truncatula. According to our results, overexpression of MtWOX2 leads to an increase in callus weight. Furthermore, transcriptomic changes in MtWOX2 overexpressing calli are, to a large extent, opposite to the changes caused by overexpression of MtWOX9-1, a somatic embryogenesis stimulator. These results add new information about the mechanisms of interaction between different WOX genes and can be useful for the search of new regeneration regulators.
A Water-Processed Mesoscale Structure Enables 18.5% Efficient Binary Layer-by-Layer Organic Solar Cells
Authors: Xie Chen , Huang Hui , Li Zijian , Zeng Xianghui , Deng Baoshen , Li Chengsheng , Zhang Guangye , Li Shunpu
Published: December 2023

The two-step layer-by-layer (LBL) deposition of donor and acceptor films enables desired vertical phase separation and high performance in organic solar cells (OSCs), which becomes a promising technology for large-scale printing devices. However, limitations including the use of toxic solvents and unpredictable infiltration between donor and acceptor still hinder the commercial production of LBL OSCs. Herein, we developed a water-based nanoparticle (NP) ink containing donor polymer to construct a mesoscale structure that could be infiltrated with an acceptor solution. Using non-halogen o-xylene for acceptor deposition, the LBL strategy with a mesoscale structure delivered outstanding efficiencies of 18.5% for binary PM6:L8-BObased LBL OSCs. Enhanced charge carrier mobility and restricted trap states were observed in the meso-LBL devices with optimized vertical morphology. It is believed that the findings in this work will bring about more research interest and effort on eco-friendly processing in preparation for the industrial production of OSCs.
Strong and Durable Wood Designed by Cell Wall Bulking Combined with Cell Lumen Filling
Authors: Dong Yaoyao , Qi Yanran , Dong Xiaoying , Li Yongfeng
Published: December 2023

Traditional wood–polymer composite (WPC) based on the in situ polymerization of ethylene unsaturated monomers in the cellular cavity of wood is significant for the high-value-added utilization of low-quality wood. However, this type of WPC has the problems of volatile monomers, low conversion rates, odor residue, and poor compatibility between the polymer and wood interface, which hinder its promotion and application. In this study, a two-step process of cell wall bulking in combination with cell lumen filling was prepared to modify wood using Maleic anhydride (MAN) as the bulking agent and GMA-EGDMA (molar ratio 2:1) as the active monomer system. The results indicate that the modulus of rupture (MOR) (125.19 ± 8.41 MPa), compressive strength (116.38 ± 7.69 MPa), impact toughness (55.4 ± 2.95 KJ m−2), and hardness (6187 ± 273 N) of the bulking–filling wood composite materials were improved by 54%, 56%, 36%, and 66%, respectively, compared with those of poplar wood. These properties were superior to those of the traditional styrene (PSt)-WPC and even exceeded the performance of Xylosma congesta (Lour.) Merr, a high-quality wood from northeast China. Meanwhile, the mass loss of wood composite materials with bulking–filling treatment was only 2.35 ± 0.05%, and the internal structure remained intact, presenting excellent decay resistance. Additionally, the treatment also significantly improved the thermal and dimensional stability of the wood composites. This study provides a theoretical basis and guidance for realizing the high-value-added application of low-quality wood and the preparation of highly durable wood-based composites.
Regeneration Membranes Loaded with Non-Antibiotic Anti-2 Microbials: A Review
Authors: Adamuz-Jiménez Ana , Manzano-Moreno Francisco-Javier , Vallecillo Cristina
Published: December 2023

Both guided bone and guided tissue regeneration are techniques that require the use of barrier membranes. Contamination and infection of the surgical area is one of the most feared complications. Some current lines of research focus on functionalizing these membranes with different antimicrobial agents. The objective of this study was to carry out a review of the use and antibacterial properties of regeneration membranes doped with antimicrobials such as zinc, silver, chlorhexidine, and lauric acid. The protocol was based on PRISMA recommendations, addressing the PICO question: “Do membranes doped with non-antibiotic antimicrobials have antibacterial activity that can reduce or improve infection compared to membranes not impregnated with said antimicrobial?” Methodological quality was evaluated using the RoBDEMAT tool. A total of 329 articles were found, of which 25 met the eligibility criteria and were included in this review. Most studies agree that zinc inhibits bacterial growth as it decreases colony-forming units, depending on the concentration used and the bacterial species studied. Silver compounds also decreased the secretion of proinflammatory cytokines and presented less bacterial adhesion to the membrane. Some concentrations of chlorhexidine that possess antimicrobial activity have shown high toxicity. Finally, lauric acid shows inhibition of bacterial growth measured by the disk diffusion test, the inhibition zone being larger with higher concentrations. Antimicrobial agents such as zinc, silver, chlorhexidine, and lauric acid have effective antibacterial activity and can be used to dope regenerative membranes in order to reduce the risk of bacterial colonization.
Niches and Sculptures of the Imaginary Realm—Revisiting the Fowan Rock Carvings, Beishan, Dazu
Authors: Sun Bo
Published: December 2023

The Fowan Cliff Carvings are a key part of the Dazu Grottoes. Formed in a southern and northern stretch, the 290 individual niches at Fowan were mostly sculpted from the Late Tang to the Southern Song. Previous research by archaeologists and art historians has used typological and iconographic methods to periodize these niches and debate the themes behind particular niche sculptures. This essay employs niche inscriptions in a discussion of typical Fowan niche contents, matching lay feasting activities onto the period background behind their construction. These individual case studies grant an understanding of the overall atmosphere at Fowan through the shared inclinations or connections between niches, also reflecting specific niche sculptures via holistic analysis. This method, repeatedly examining the relationship between the niches and site from the perspective of “venue”, helps us restore a sense of situatedness when facing different eras of Fowan and to understand the choice in statue content, changes in niche content, and the design underlying niche form.
A Parallel-Cascaded Ensemble of Machine Learning Models for Crop Type Classification in Google Earth Engine Using Multi-Temporal Sentinel-1/2 and Landsat-8/9 Remote Sensing Data
Authors: Abdali Esmaeil , Valadan Zoej Mohammad Javad , Taheri Dehkordi Alireza , Ghaderpour Ebrahim
Published: December 2023

The accurate mapping of crop types is crucial for ensuring food security. Remote Sensing (RS) satellite data have emerged as a promising tool in this field, offering broad spatial coverage and high temporal frequency. However, there is still a growing need for accurate crop type classification methods using RS data due to the high intra- and inter-class variability of crops. In this vein, the current study proposed a novel Parallel-Cascaded ensemble structure (Pa-PCA-Ca) with seven target classes in Google Earth Engine (GEE). The Pa section consisted of five parallel branches, each generating Probability Maps (PMs) for different target classes using multi-temporal Sentinel-1/2 and Landsat-8/9 satellite images, along with Machine Learning (ML) models. The PMs exhibited high correlation within each target class, necessitating the use of the most relevant information to reduce the input dimensionality in the Ca part. Thereby, Principal Component Analysis (PCA) was employed to extract the top uncorrelated components. These components were then utilized in the Ca structure, and the final classification was performed using another ML model referred to as the Meta-model. The Pa-PCA-Ca model was evaluated using in-situ data collected from extensive field surveys in the northwest part of Iran. The results demonstrated the superior performance of the proposed structure, achieving an Overall Accuracy (OA) of 96.25% and a Kappa coefficient of 0.955. The incorporation of PCA led to an OA improvement of over 6%. Furthermore, the proposed model significantly outperformed conventional classification approaches, which simply stack RS data sources and feed them to a single ML model, resulting in a 10% increase in OA.
Characterizing the Water Storage Variation of Kusai Lake by Constructing Time Series from Multisource Remote Sensing Data
Authors: Huang Zhengkai , Wu Xin , Wang Haihong , Zhao Zehui , Du Liting , He Xiaoxing , Zhou Hangyu
Published: December 2023

In September 2011, Zhuonai Lake (ZL) in the northeast of Hoh Xil (HX) on the Qinghai–Tibet Plateau (QTP) broke out. The outburst event seriously changed the environmental hydraulics in this region. Due to the insufficient temporal resolution of observations, it is challenging to assess the impact of this event on short-period variations of water volumes in three lakes downstream of ZL. Combining multisource remote sensing data, we constructed long and high-temporal-resolution time series for the lake level, area, and lake water storage (LWS) of Kusai Lake (KL) to characterize the variabilities before and after the outburst. The water level, area, and LWS time series contain 1051 samples from 1990 to 2022, with uncertainties of 0.16 m, 2.5 km2, and 0.016 km3, respectively. The accuracies verified using the Database for Hydrological Time Series of Inland Waters (DAHITI) are 0.26 m, 2.64 km2, and 0.08 km3 for water level, area, and LWS, respectively. We characterized the LWS variations during the past 30 years based on the high temporal resolution LWS time series. Before the outburst, the 1-year and 3.5-year variations dominated the LWS time series, and there was no obvious semi-annual signal. After the outburst, the 3.5-year variation disappeared, and a strong semi-annual oscillation was observed. From 2012 to 2015, the periodic LWS variations in KL were disturbed by the ZL outburst and the subsequent outflow of KL led by the outburst. Regular cyclic signals have been restored since 2016, with an amplified annual fluctuation. By analysis, precipitation, evaporation, and glacier area change are excluded as driving factors of the pattern change in LWS variations of KL. It can be concluded that the altered recharge pattern of KL triggered by the outburst directly resulted in the observed changes in TWS behavior. For the first time, we identified the periodic patterns of LWS variations of KL during the past 30 years and revealed that the ZL outburst event significantly influenced these patterns. This finding contributes to the comprehensive understanding of the effects of the ZL outburst on downstream lake dynamics. Furthermore, the presented procedure for constructing long and high-resolution time series of LWS allows for monitoring and characterizing the short-period variabilities of Tibetan lakes that lack hydrological data.
Can Water-Detection Indices Be Reliable Proxies for Water Discharges in Mid-Sized Braided Rivers Using Coarse-Resolution Landsat Archives?
Authors: Gao Peng , Belletti Barbara , Piégay Hervé , You Yuchi , Li Zhiwei
Published: December 2023

The use of water detection (WD) indices to infer daily discharge (Qd) has a great potential to enrich needed hydrological data for understanding fluvial processes driving the morphological changes of braided rivers. However, no consensus has been reached on which one stands out for use in mid-sized braided rivers. In this study, we compared the physical characteristics of three most commonly used WD indices, the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Normalized Difference Moisture Index (NDMI), for two mid-sized braided reach segments in the Qinghai-Tibet Plateau, China, that have different morphological structures. Relying on the Google Earth Engine web interface, we calculated the total mean water width (WWt) based on the detected surface-water areas (As) and braiding index (BI), as well as the mean values (m) of these indices over about four decades at the braided corridor scale (cs) (mNDWIcs, mMNDWIcs, and mNDMIcs). We then examined different responses of these indices to water and non-water features and their best threshold values for characterizing channel structures. Our analyses demonstrated that (1) NDWI and MNDWI perform well for detecting braided channel structures with the threshold of zero; (2) WWt is generally better correlated to Qd in a linear style than WD indices do, particularly when calculated from MNDWI; and (3) among WD indices calculated at the braided corridor scale, mMNDWIcs shows a better relationship with Qd than mNDMIcs does. Finally, we provided mechanisms that may explain these differences in terms of photometric discrepancies in calculating WWt and WD indices and the impact of image resolution on their calculations.
A General Deep Learning Point–Surface Fusion Framework for RGB Image Super-Resolution
Authors: Zhang Yan , Zhang Lifu , Song Ruoxi , Tong Qingxi
Published: December 2023

Hyperspectral images are usually acquired in a scanning-based way, which can cause inconvenience in some situations. In these cases, RGB image spectral super-resolution technology emerges as an alternative. However, current mainstream spectral super-resolution methods aim to generate continuous spectral information at a very narrow range, limited to the visible light range. Some researchers introduce hyperspectral images as auxiliary data. But it is usually required that the auxiliary hyperspectral images have the same spatial range as RGB images. To address this issue, a general point–surface data fusion method is designed to achieve the RGB image spectral super-resolution goal in this paper, named GRSS-Net. The proposed method utilizes hyperspectral point data as auxiliary data to provide spectral reference information. Thus, the spectral super-resolution can extend the spectral reconstruction range according to spectral data. The proposed method utilizes compressed sensing theory as a fundamental physical mechanism and then unfolds the traditional hyperspectral image reconstruction optimization problem into a deep network. Finally, a high-spatial-resolution hyperspectral image can be obtained. Thus, the proposed method combines the non-linear feature extraction ability of deep learning and the interpretability of traditional physical models simultaneously. A series of experiments demonstrates that the proposed method can effectively reconstruct spectral information in RGB images. Meanwhile, the proposed method provides a framework of spectral super-resolution for different applications.
Evaluation of Open Geotechnical Knowledge in Urban Environments for 3D Modelling of the City of Seville (Spain)
Authors: Soriano-Cuesta Cristina , Romero-Hernández Rocío , Mascort-Albea Emilio J. , Kada Martin , Fuls Andreas , Jaramillo-Morilla Antonio
Published: December 2023

The need for sustainable urban growth management and preventive conservation of built elements constitute the key factors in today’s increasing demand for the better understanding of subsoil. This information, mainly available from geotechnical surveys, can be integrated into spatial databases to produce operational models. Aiming to generate strategies that enable the visualisation of underground properties in highly anthropised environments, the following four-phase methodology has been proposed: (a) Gathering of geotechnical data; (b) Spatial and statistical analysis; (c) Database design; (d) Generation of 2D and 3D models. Following the aforementioned criteria and using open sources, a spatial dataset of 650 points located within the historical centre of Seville (Spain) has been developed. This urban area is characterised by the heterogeneous distribution of its soil layers and their geotechnical properties. The results show that the application of this method enables a prompt and efficient display of the distribution of geotechnical layers in urban and metropolitan environments, by considering the variations in their mechanical properties. This simplified approach therefore establishes a new starting point for the development of predictive strategies based on approaches of a more complex nature that facilitate the analysis of the interactions between subsoil, buildings, and infrastructures.
Outdoor Navigation Assistive System Based on Robust and Real-Time Visual–Auditory Substitution Approach
Authors: Scalvini Florian , Bordeau Camille , Ambard Maxime , Migniot Cyrille , Dubois Julien
Published: December 2023

Blindness affects millions of people worldwide, leading to difficulties in daily travel and a loss of independence due to a lack of spatial information. This article proposes a new navigation aid to help people with severe blindness reach their destination. Blind people are guided by a short 3D spatialised sound that indicates the target point to follow. This sound is combined with other sonified information on potential obstacles in the vicinity. The proposed system is based on inertial sensors, GPS data, and the cartographic knowledge of pedestrian paths to define the trajectory. In addition, visual clues are used to refine the trajectory with ground floor information and obstacle information using a camera to provide 3D spatial information. The proposed method is based on a deep learning approach. The different neural networks used in this approach are evaluated on datasets that regroup navigations from pedestrians’ point-of-view. This method achieves low latency and real-time processing without relying on remote connections, instead using a low-power embedded GPU target and a multithreaded approach for video processing, sound generation, and acquisition. This system could significantly improve the quality of life and autonomy of blind people, allowing them to reliably and efficiently navigate in their environment.
Application of Through Glass Via (TGV) Technology for Sensors Manufacturing and Packaging
Authors: Yu Chen , Wu Shaocheng , Zhong Yi , Xu Rongbin , Yu Tian , Zhao Jin , Yu Daquan
Published: December 2023

Glass has emerged as a highly versatile substrate for various sensor and MEMS packaging applications, including electromechanical, thermal, optical, biomedical, and RF devices, due to its exceptional properties such as high geometrical tolerances, outstanding heat and chemical resistance, excellent high-frequency electrical properties, and the ability to be hermetically sealed. In these applications, Through Glass Via (TGV) technology plays a vital role in manufacturing and packaging by creating electrical interconnections through glass substrates. This paper provides a comprehensive summary of the research progress in TGV fabrication along with its integrations, including through via formation and metallization. This paper also reviews the significant qualification and reliability achievements obtained by the scientific community for TGV technology. Additionally, this paper summarizes the application of TGV technology in various sensors such as MEMS sensors and discusses the potential applications and future development directions of TGV technology.
Fluorescence Super-Resolution Imaging Chip for Gene Silencing Exosomes
Authors: Yin Gaoqiang , Qi Tongsheng , Wei Jinxiu , Wang Tingyu , Wang Zhuyuan , Cui Yiping , Zong Shenfei
Published: December 2023

Tumor cell-derived extracellular vesicles and their cargo of bioactive substances have gradually been recognized as novel biomarkers for cancer diagnosis. Meanwhile, the PD-L1 (Programmed Death-Ligand 1) protein, as an immune checkpoint molecule, is highly expressed on certain tumor cells and holds significant potential in immune therapy. In comparison to PD-L1 monoclonal antibodies, the inhibitory effect of PD-L1 siRNA (small interfering RNA) is more advantageous. In this article, we introduced a microfluidic chip integrating cell cultivation and exosome detection modules, which were intended for the investigation of the gene silencing effect of PD-L1 siRNA. Basically, cells were first cultured with PD-L1 siRNA in the chip. Then, the secreted exosomes were detected via super-resolution imaging, to validate the inhibitory effect of siRNA on PD-L1 expression. To be specific, a “sandwich” immunological structure was employed to detect exosomes secreted from HeLa cells. Immunofluorescence staining and DNA-PAINT (DNA Point Accumulation for Imaging in Nanoscale Topography) techniques were utilized to quantitatively analyze the PD-L1 proteins on HeLa exosomes, which enabled precise structural and content analysis of the exosomes. Compared with other existing PD-L1 detection methods, the advantages of our work include, first, the integration of microfluidic chips greatly simplifying the cell culture, gene silencing, and PD-L1 detection procedures. Second, the utilization of DNA-PAINT can provide an ultra-high spatial resolution, which is beneficial for exosomes due to their small sizes. Third, qPAINT could allow quantitative detection of PD-L1 with better precision. Hence, the combination of the microfluidic chip with DNA-PAINT could provide a more powerful integrated platform for the study of PD-L1-related tumor immunotherapy.
Vertical Ground Reaction Forces in Parkinson’s Disease: A Speed-Matched Comparative Analysis with Healthy Subjects
Authors: Giardini Marica , Turcato Anna Maria , Arcolin Ilaria , Corna Stefano , Godi Marco
Published: December 2023

This study aimed to investigate and compare the vertical Ground Reaction Forces (vGRFs) of patients with Parkinson’s Disease (PwPD) and healthy subjects (HS) when the confounding effect of walking speed was absent. Therefore, eighteen PwPD and eighteen age- and linear walking speed-matched HS were recruited. Using plantar pressure insoles, participants walked along linear and curvilinear paths at self-selected speeds. Interestingly, PwPD exhibited similar walking speed to HS during curvilinear trajectories (p = 0.48) and similar vGRF during both linear and curvilinear paths. In both groups, vGRF at initial contact and terminal stance was higher during linear walking, while vGRF at mid-stance was higher in curvilinear trajectories. Similarly, the time to peak vGRF at each phase showed no significant group differences. The vGRF timing variability was different between the two groups, particularly at terminal stance (p < 0.001). In conclusion, PwPD and HS showed similar modifications in vGRF and a similar reduction in gait speed during curvilinear paths when matched for linear walking speed. This emphasized the importance of considering walking speed when assessing gait dynamics in PwPD. This study also suggests the possibility of the variability of specific temporal measures in differentiating the gait patterns of PwPD versus those of HS, even in the early stages of the disease.
Hardware Efficient Direct Policy Imitation Learning for Robotic Navigation in Resource-Constrained Settings
Authors: Sumanasena Vidura , Fernando Heshan , De Silva Daswin , Thileepan Beniel , Pasan Amila , Samarawickrama Jayathu , Osipov Evgeny , Alahakoon Damminda
Published: December 2023

Direct policy learning (DPL) is a widely used approach in imitation learning for time-efficient and effective convergence when training mobile robots. However, using DPL in real-world applications is not sufficiently explored due to the inherent challenges of mobilizing direct human expertise and the difficulty of measuring comparative performance. Furthermore, autonomous systems are often resource-constrained, thereby limiting the potential application and implementation of highly effective deep learning models. In this work, we present a lightweight DPL-based approach to train mobile robots in navigational tasks. We integrated a safety policy alongside the navigational policy to safeguard the robot and the environment. The approach was evaluated in simulations and real-world settings and compared with recent work in this space. The results of these experiments and the efficient transfer from simulations to real-world settings demonstrate that our approach has improved performance compared to its hardware-intensive counterparts. We show that using the proposed methodology, the training agent achieves closer performance to the expert within the first 15 training iterations in simulation and real-world settings.
Android Ransomware Detection Using Supervised Machine Learning Techniques Based on Traffic Analysis
Authors: Albin Ahmed Amnah , Shaahid Afrah , Alnasser Fatima , Alfaddagh Shahad , Binagag Shadha , Alqahtani Deemah
Published: December 2023

In today’s digitalized era, the usage of Android devices is being extensively witnessed in various sectors. Cybercriminals inevitably adapt to new security technologies and utilize these platforms to exploit vulnerabilities for nefarious purposes, such as stealing users’ sensitive and personal data. This may result in financial losses, discredit, ransomware, or the spreading of infectious malware and other catastrophic cyber-attacks. Due to the fact that ransomware encrypts user data and requests a ransom payment in exchange for the decryption key, it is one of the most devastating types of malicious software. The implications of ransomware attacks can range from a loss of essential data to a disruption of business operations and significant monetary damage. Artificial intelligence (AI)-based techniques, namely machine learning (ML), have proven to be notable in the detection of Android ransomware attacks. However, ensemble models and deep learning (DL) models have not been sufficiently explored. Therefore, in this study, we utilized ML- and DL-based techniques to build efficient, precise, and robust models for binary classification. A publicly available dataset from Kaggle consisting of 392,035 records with benign traffic and 10 different types of Android ransomware attacks was used to train and test the models. Two experiments were carried out. In experiment 1, all the features of the dataset were used. In experiment 2, only the best 19 features were used. The deployed models included a decision tree (DT), support vector machine (SVM), k-nearest neighbor (KNN), ensemble of (DT, SVM, and KNN), feedforward neural network (FNN), and tabular attention network (TabNet). Overall, the experiments yielded excellent results. DT outperformed the others, with an accuracy of 97.24%, precision of 98.50%, and F1-score of 98.45%. Whereas, in terms of the highest recall, SVM achieved 100%. The acquired results were thoroughly discussed, in addition to addressing limitations and exploring potential directions for future work.
The Use of Artificial Intelligence and Satellite Remote Sensing in Land Cover Change Detection: Review and Perspectives
Authors: Gu Zhujun , Zeng Maimai
Published: December 2023

The integration of Artificial Intelligence (AI) and Satellite Remote Sensing in Land Cover Change Detection (LCCD) has gained increasing significance in scientific discovery and research. This collaboration accelerates research efforts, aiding in hypothesis generation, experiment design, and large dataset interpretation, providing insights beyond traditional scientific methods. Mapping land cover patterns at global, regional, and local scales is crucial for monitoring the dynamic world, given the significant impact of land cover distribution on climate and environment. Satellite remote sensing is an efficient tool for monitoring land cover across vast spatial extents. Detection of land cover change through satellite remote sensing images is critical in influencing ecological balance, climate change mitigation, and urban development guidance. This paper conducts a comprehensive review of LCCD using remote sensing images, encompassing exhaustive examination of satellite remote sensing data types and contemporary methods, with a specific focus on advanced AI technology applications. Furthermore, the study delves into the challenges and potential solutions in the field of LCCD, providing a comprehensive overview of the state of the art, offering insights for future research and practical applications in this domain.
National Differences in Age and Future-Oriented Indicators Relate to Environmental Performance
Authors: Syropoulos Stylianos , Law Kyle Fiore , Young Liane
Published: December 2023

Environmental concerns inherently involve an intergenerational aspect, where today’s decisions can have far-reaching effects on future generations. Numerous national characteristics can forecast a nation’s commitment to investing in environmental sustainability. This study expands on previous research and offers evidence in support of Gott’s principle, which states that citizens may use their country’s age to forecast its remaining lifespan. Specifically, we show that a nation’s age positively relates to intergenerational solidarity—a country’s willingness to sacrifice for future generations. Furthermore, country age and other future-oriented variables, such as a country’s Long-Term Orientation and ability to overcome temporal discounting, are linked to sustainability-related indicators, indicating that countries concerned about the future also exhibit greater concern for the environment. These findings reinforce the value of framing a country as a long-standing entity and implementing intergenerational framing interventions to motivate pro-environmental engagement.
Harmonizing Sustainability Goals: Empirical Insights into Climate Change Mitigation and Circular Economy Strategies in Selected European Countries with SDG13 Framework
Authors: Sardianou Eleni , Nikou Vasilis , Kostakis Ioannis
Published: December 2023

Global efforts to harmonize the sustainable development goals (SDGs) focus on understanding the nexus between carbon dioxide emissions (CO2) and the circular economy (CE). This study aims to capture variations in carbon emission performance behavior across different European countries, considering their economic performance, population density, material footprint, and circularity rate. The analysis utilizes panel data for 14 EU countries during the period between 2000 and 2020, specifically in relation to their performance within the SDG13 Framework. Empirical analysis employs Ordinary Least Squares, Fixed Effects and Fully Modified Least Squares techniques. The findings suggest that countries with a higher efficiency in utilizing materials within a circular economy framework and higher population density tend to exhibit lower levels of climate change mitigation. Conversely, an increased material footprint corresponds to higher CO2 emissions. This aligns with the circular economy’s emphasis on minimizing resource extraction through promoting reuse, recycling, and remanufacturing. A comprehensive understanding of the CO2-CE nexus is essential for formulating effective policies aligning circularity performance with the SDG13 framework.
Recent Progress in Robot Control Systems: Theory and Applications
Authors: Zhang Chengxi , Wu Jin , Li Chong
Published: December 2023

Many engineering systems, such as electronic rotors, aircraft wings, and spacecraft flywheel structures, rely on the symmetry of their actuators [...]
Tetrodotoxin/Saxitoxin Accumulation Profile in the Euryhaline Marine Pufferfish Chelonodontops patoca
Authors: Zhu Hongchen , Sakai Takashi , Doi Hiroyuki , Yamaguchi Kenichi , Yamada Akinori , Takatani Tomohiro , Arakawa Osamu
Published: December 2023

Marine Takifugu pufferfish, which naturally possess tetrodotoxins (TTXs), selectively take up and accumulate TTXs, whereas freshwater Pao pufferfish, which naturally possess saxitoxins (STXs), selectively take up and accumulate STXs. To further clarify the TTXs/STXs selectivity in pufferfish, we conducted a TTX/STX administration experiment using Chelonodontops patoca, a euryhaline marine pufferfish possessing both TTXs and STXs. Forty nontoxic cultured individuals of C. patoca were divided into a seawater group (SW, acclimated/reared at 33‰ salinity; n = 20) and a brackish water group (BW, acclimated/reared at 8‰ salinity; n = 20). An aqueous TTX/STX mixture was intrarectally administered (both at 7.5 nmol/fish), and five individuals/group were analyzed after 1–48 h. Instrumental toxin analyses revealed that both TTX and STX were taken up, transferred, and retained, but more STX than TTX was retained in both groups. TTX gradually decreased and eventually became almost undetectable in the intestinal tissue, while STX was retained at ~5–10% of the dose level, and only STX showed transient transfer in the liver. The BW group showed a faster decrease/disappearance of TTX, greater STX retention in the intestine, and greater STX transient transfer to the liver. Thus, C. patoca appears to more easily accumulate STXs than TTXs, especially under hypoosmotic conditions.
Subconfluent ARPE-19 Cells Display Mesenchymal Cell-State Characteristics and Behave like Fibroblasts, Rather Than Epithelial Cells, in Experimental HCMV Infection Studies
Authors: Golconda Preethi , Andrade-Medina Mariana , Oberstein Adam
Published: December 2023

Human cytomegalovirus (HCMV) has a broad cellular tropism and epithelial cells are important physiological targets during infection. The retinal pigment epithelial cell line ARPE-19 has been used to model HCMV infection in epithelial cells for decades and remains a commonly used cell type for studying viral entry, replication, and the cellular response to infection. We previously found that ARPE-19 cells, despite being derived from an epithelial cell explant, express extremely low levels of canonical epithelial proteins, such as E-cadherin and EpCAM. Here, we perform comparative studies of ARPE-19 and additional epithelial cell lines with strong epithelial characteristics. We find that ARPE-19 cells cultured under subconfluent conditions resemble mesenchymal fibroblasts, rather than epithelial cells; this is consistent with previous studies showing that ARPE-19 cultures require extended periods of high confluency culture to maintain epithelial characteristics. By reanalyzing public gene expression data and using machine learning, we find evidence that ARPE-19 cultures maintained across many labs exhibit mesenchymal characteristics and that the majority of studies employing ARPE-19 use them in a mesenchymal state. Lastly, by performing experimental HCMV infections across mesenchymal and epithelial cell lines, we find that ARPE-19 cells behave like mesenchymal fibroblasts, producing logarithmic yields of cell-free infectious progeny, while cell lines with strong epithelial character exhibit an atypical infectious cycle and naturally restrict the production of cell-free progeny. Our work highlights important characteristics of the ARPE-19 cell line and suggests that subconfluent ARPE-19 cells may not be optimal for modeling epithelial infection with HCMV or other human viruses. It also suggests that HCMV biosynthesis and/or spread may occur quite differently in epithelial cells compared to mesenchymal cells. These differences could contribute to viral persistence or pathogenesis in epithelial tissues.
Japanese Encephalitis: Risk of Emergence in the United States and the Resulting Impact
Authors: Monath Thomas P.
Published: December 2023

Japanese encephalitis virus is a mosquito-borne member of the Flaviviridae family. JEV is the leading cause of viral encephalitis in Asia and is characterized by encephalitis, high lethality, and neurological sequelae in survivors. The virus also causes severe disease in swine, which are an amplifying host in the transmission cycle, and in horses. US agricultural authorities have recently recognized the threat to the swine industry and initiated preparedness activities. Other mosquito-borne viruses exotic to the Western Hemisphere have been introduced and established in recent years, including West Nile, Zika, and chikungunya viruses, and JEV has recently invaded continental Australia for the first time. These events amply illustrate the potential threat of JEV to US health security. Susceptible indigenous mosquito vectors, birds, feral and domestic pigs, and possibly bats, constitute the receptive ecological ingredients for the spread of JEV in the US. Fortunately, unlike the other virus invaders mentioned above, an inactivated whole virus JE vaccine (IXIARO®) has been approved by the US Food and Drug Administration for human use in advance of a public health emergency, but there is no veterinary vaccine. This paper describes the risks and potential consequences of the introduction of JEV into the US, the need to integrate planning for such an event in public health policy, and the requirement for additional countermeasures, including antiviral drugs and an improved single dose vaccine that elicits durable immunity in both humans and livestock.
Extraordinary Titer and Broad Anti-SARS-CoV-2 Neutralization Induced by Stabilized RBD Nanoparticles from Strain BA.5
Authors: Wang Zhantong , Zhang Baoshan , Ou Li , Qiu Qi , Wang Lingshu , Bylund Tatsiana , Kong Wing-Pui , Shi Wei , Tsybovsky Yaroslav , Wu Lingyuan , Zhou Qiong , Chaudhary Ridhi , Choe Misook , Dickey Thayne H. , El Anbari Mohammed , Olia Adam S. , Rawi Reda , Teng I-Ting , Wang Danyi , Wang Shuishu , Tolia Niraj H. , Zhou Tongqing , Kwong Peter D.
Published: December 2023

The receptor-binding domain (RBD) of the SARS-CoV-2 spike is a primary target of neutralizing antibodies and a key component of licensed vaccines. Substantial mutations in RBD, however, enable current variants to escape immunogenicity generated by vaccination with the ancestral (WA1) strain. Here, we produce and assess self-assembling nanoparticles displaying RBDs from WA1 and BA.5 strains by using the SpyTag:SpyCatcher system for coupling. We observed both WA1- and BA.5-RBD nanoparticles to degrade substantially after a few days at 37 °C. Incorporation of nine RBD-stabilizing mutations, however, increased yield ~five-fold and stability such that more than 50% of either the WA1- or BA.5-RBD nanoparticle was retained after one week at 37 °C. Murine immunizations revealed that the stabilized RBD-nanoparticles induced ~100-fold higher autologous neutralization titers than the prefusion-stabilized (S2P) spike at a 2 μg dose. Even at a 25-fold lower dose where S2P-induced neutralization titers were below the detection limit, the stabilized BA.5-RBD nanoparticle induced homologous titers of 12,795 ID50 and heterologous titers against WA1 of 1767 ID50. Assessment against a panel of β-coronavirus variants revealed both the stabilized BA.5-RBD nanoparticle and the stabilized WA1-BA.5-(mosaic)-RBD nanoparticle to elicit much higher neutralization breadth than the stabilized WA1-RBD nanoparticle. The extraordinary titer and high neutralization breadth elicited by stabilized RBD nanoparticles from strain BA.5 make them strong candidates for next-generation COVID-19 vaccines.
Zooplankton in brackish water bodies of the plain territory of the Altai territory in the vegetation season of 2022
Authors:   Altai branch of the VNIRO (", Pyatkova Ya.S. ,   AltaiNIRO",   ), Russia, Barnaul,   Institute for Water and Environmental Problems Siberian Branch of the Russian Academy of Sciences, Russia, Barnaul, Bezmaternykh D.M. ,   Institute for Water and Environmental Problems Siberian Branch of the Russian Academy of Sciences, Russia, Barnaul
Published: December 2023

The zooplankton of three small brackish lakes (Bulatovo, Korostelevskoye and Markovskoye) located in the plain territory of Altai Krai was studied in 2022. Data on the main characteristics of the zooplankton habitat are presented. An assessment of the ecological state of lakes is given based on qualitative and quantitative indicators of zooplankton. The taxonomic composition and main quantitative characteristics of zooplankton in the spring, summer and autumn periods are characterized. Seasonal dynamics of quantitative indicators and changes in the taxonomic composition of zooplankton were noted. The lowest quantitative indicators of zooplankton development were noted in the spring season (April). All identified representatives of zooplankton were cosmopolitans. Common to all lakes are 5 taxa of crustaceans and rotifers (Keratella quadrata, Filinia longiseta, Daphnia magna, Cyclopidae ind., Diaptomidae ind.). In the spring and autumn seasons, copepods dominated in abundance and biomass, reaching 99.9% of the zooplankton population. Differences in the composition of the dominant taxa in the summer season were noted between the lakes. In the lake Bulatovo was dominated in numbers by rotifers due to Brachionus quadridentatus, and in biomass by cladocerans due to Daphnia magna. In the lake Korostelevskoe, the dominant taxonomic group in terms of numbers was copepods, the basis of which were Diaptomidae ind., in terms of biomass — cladocerans due to Diaphanosoma brachiurum. Only in the lake In Markovskoe, copepods — Diaptomidae ind. — dominated in numbers and biomass. The zooplankton of the studied lakes was characterized by a poor species composition, but high summer numbers and biomass (from 342 thou. eq./m3 and 7.13 g/m3 in Lake Markovskoe to 1895 th. eq./m3 and 33.7 g/m3 in Lake Bulatovo). In the summer season, the zooplankton biomass of the lake. Markovskoye belonged to reservoirs of the α-eutrophic type, lakes Bulatovo and Korostelevskoye were of the polytrophic type. The majority of noted species (60%) were indicators of β-mesosaprobic conditions.