bluuebunny/crossref_metadata_2025 huggingface dataset:
The Localisation of a Tracheoesophageal Shunt during Laryn(-gopharyn)gectomy Determines the Risk of Shunt Insufficiency
Authors: Johnson Felix , Knopf Andreas
Published: December 2023

Background: Tracheoesophageal shunt insufficiency (TESI) is a common and potentially life-threatening complication after laryn(-gopharyn)gectomy (L(P)E). We investigated whether TESI could be the result of a specific shunt location. Methods: A monocentric, retrospective cohort analysis of 171 consecutively treated L(P)E patients was performed. Patients with a secondary prosthesis instillation and patients with insufficient postoperative imaging were excluded. Disease related data as well as location of primary voice prosthesis were assessed. Results: The cohort was divided into 62 TESI-positive and 109 TESI-negative individuals. The mean time from surgery to TESI was 32 months. No differences were observed in gender, age, tumor localization, T/R/M-status. Surgery without adjuvant therapy was more often performed in TESI-negative individuals when compared with their positive counterparts. However, Cox regression including T/N status, therapy and categorized distance of the tracheoesophageal shunt to the manubrium (≤1.5 cm vs. >1.5 cm) revealed that a distance of ≤1.5 cm was associated with a 2.1-fold increased risk of TESI, while all other parameters did not influence the event-free survival. Conclusions: Primary shunt positioning ≤1.5 cm to the ridge of the manubrium is associated with an increased risk of TESI. In these individuals secondary shunt operation resulting in a position >1.5 cm distant to the manubrium should be recommended.
Gestalt’s Perspective on Insight: A Recap Based on Recent Behavioral and Neuroscientific Evidence
Authors: Vitello Mary , Salvi Carola
Published: December 2023

The Gestalt psychologists’ theory of insight problem-solving was based on a direct parallelism between perceptual experience and higher-order forms of cognition (e.g., problem-solving). Similarly, albeit not exclusively, to the sudden recognition of bistable figures, these psychologists contended that problem-solving involves a restructuring of one’s initial representation of the problem’s elements, leading to a sudden leap of understanding phenomenologically indexed by the “Aha!” feeling. Over the last century, different scholars have discussed the validity of the Gestalt psychologists’ perspective, foremost using the behavioral measures available at the time. However, in the last two decades, scientists have gained a deeper understanding of insight problem-solving due to the advancements in cognitive neuroscience. This review aims to provide a retrospective reading of Gestalt theory based on the knowledge accrued by adopting novel paradigms of research and investigating their neurophysiological correlates. Among several key points that the Gestalt psychologists underscored, we focus specifically on the role of the visual system in marking a discrete switch of knowledge into awareness, as well as the perceptual experience and holistic standpoints. While the main goal of this paper is to read the previous theory in light of new evidence, we also hope to initiate an academic discussion and encourage further research about the points we raise.
Formation Control for UAV-USVs Heterogeneous System with Collision Avoidance Performance
Authors: Huang Yuyang , Li Wei , Ning Jun , Li Zhihui
Published: December 2023

This paper investigates the cooperative formation trajectory tracking problem for heterogeneous unmanned aerial vehicle (UAV) and multiple unmanned surface vessel (USV) systems with collision avoidance performance. Firstly, a formation control protocol based on extended state observer (ESO) is proposed to ensure that the UAV and the USVs track the target trajectory simultaneously in the XY plane. Then, the collision avoidance control strategy of USV formation based on artificial potential field (APF) theory is designed. Specifically, the APF method is improved by reconstructing the repulsive potential field to make the collision avoidance action of USVs more in line with the requirements of International Regulations for Preventing Collisions at Sea (COLREGs). Following that, an altitude controller for the UAV is proposed to maintain the cooperative formation of the heterogeneous systems. Based on the input-to-state stability, the stability of the proposed control structure is proven, and all the signals in the closed-loop system are ultimately bounded. Finally, a simulation study is provided to show the efficacy of the proposed strategy.
Analysis of Nuclear Dynamics in Nematode-Trapping Fungi Based on Fluorescent Protein Labeling
Authors: Zhou Liang , He Zhiwei , Zhang Keqin , Wang Xin
Published: December 2023

Nematophagous fungi constitute a category of fungi that exhibit parasitic behavior by capturing, colonizing, and poisoning nematodes, which are critical factors in controlling nematode populations in nature, and provide important research materials for biological control. Arthrobotrys oligospora serves as a model strain among nematophagous fungi, which begins its life as conidia, and then its hyphae produce traps to capture nematodes, completing its lifestyle switch from saprophytic to parasitic. There have been many descriptions of the morphological characteristics of A. oligospora lifestyle changes, but there have been no reports on the nuclear dynamics in this species. In this work, we constructed A. oligospora strains labeled with histone H2B–EGFP and observed the nuclear dynamics from conidia germination and hyphal extension to trap formation. We conducted real-time imaging observations on live cells of germinating and extending hyphae and found that the nucleus was located near the tip. It is interesting that the migration rate of this type of cell nucleus is very fast, and we speculate that this may be related to the morphological changes involved in the transformation to a predatory lifestyle. We suggest that alterations in nuclear shape and fixation imply the immediate disruption of the interaction with cytoskeletal mechanisms during nuclear migration. In conclusion, these findings suggest that the signal initiating nuclear migration into fungal traps is generated at the onset of nucleus entry into a trap cell. Our work provides a reference for analysis of the dynamics of nucleus distribution and a means to visualize protein localization and interactions in A. oligospora.
Manipulation of Auxin Signaling by Smut Fungi during Plant Colonization
Authors: Nagarajan Nithya , Khan Mamoona , Djamei Armin
Published: December 2023

A common feature of many plant-colonizing organisms is the exploitation of plant signaling and developmental pathways to successfully establish and proliferate in their hosts. Auxins are central plant growth hormones, and their signaling is heavily interlinked with plant development and immunity responses. Smuts, as one of the largest groups in basidiomycetes, are biotrophic specialists that successfully manipulate their host plants and cause fascinating phenotypes in so far largely enigmatic ways. This review gives an overview of the growing understanding of how and why smut fungi target the central and conserved auxin growth signaling pathways in plants.
Evaluation of the Acid–Base Status in Patients Admitted to the ICU Due to Severe COVID-19: Physicochemical versus Traditional Approaches
Authors: Sotiropoulou Zoi , Antonogiannaki Elvira Markela , Koukaki Evangelia , Zaneli Stavroula , Bakakos Agamemnon , Vontetsianos Angelos , Anagnostopoulos Nektarios , Rovina Nikoleta , Loverdos Konstantinos , Tripolitsioti Paraskevi , Kyriakopoulou Magdalini , Pontikis Konstantinos , Bakakos Petros , Georgopoulos Dimitrios , Papaioannou Andriana I.
Published: December 2023

Background: Stewart’s approach is known to have better diagnostic accuracy for the identification of metabolic acid–base disturbances compared to traditional methods based either on plasma bicarbonate concentration ([HCO3−]) and anion gap (AG) or on base excess/deficit (BE). This study aimed to identify metabolic acid–base disorders using either Stewart’s or traditional approaches in critically ill COVID-19 patients admitted to the ICU, to recognize potential hidden acid–base metabolic abnormalities and to assess the prognostic value of these abnormalities for patient outcome. Methods: This was a single-center retrospective study, in which we collected data from patients with severe COVID-19 admitted to the ICU. Electronical files were used to retrieve data for arterial blood gases, serum electrolytes, and proteins and to derive [HCO3−], BE, anion gap (AG), AG adjusted for albumin (AGadj), strong ion difference, strong ion gap (SIG), and SIG corrected for water excess/deficit (SIGcorr). The acid–base status was evaluated in each patient using the BE, [HCO3−], and physicochemical approaches. Results: We included 185 patients. The physicochemical approach detected more individuals with metabolic acid–base abnormalities than the BE and [HCO3−] approaches (p < 0.001), and at least one acid–base disorder was recognized in most patients. According to the physicochemical method, 170/185 patients (91.4%) had at least one disorder, as opposed to the number of patients identified using the BE 90/186 (48%) and HCO3 62/186 (33%) methods. Regarding the derived acid–base status variables, non-survivors had greater AGadj, (p = 0.013) and SIGcorr (p = 0.035) compared to survivors. Conclusions: The identification of hidden acid–base disturbances may provide a detailed understanding of the underlying conditions in patients and of the possible pathophysiological mechanisms implicated. The association of these acid–base abnormalities with mortality provides the opportunity to recognize patients at increased risk of death and support them accordingly.
Optimization of Microclimate Conditions Considering Urban Morphology and Trees Using ENVI-Met: A Case Study of Cairo City
Authors: Abdelmejeed Ahmed Yasser , Gruehn Dietwald
Published: December 2023

This research aims to optimize the use of trees to enhance microclimate conditions, which has become necessary because of climate change and its impacts, especially for cities suffering from extreme heat stress, such as Cairo. It considers elements of urban morphology, such as the aspect ratio and orientation of canyons, which play an important role in changing microclimate conditions. It also considers both sides of each canyon because the urban shading is based on the orientation and the aspect ratio, which can provide good shade on one side of the canyon but leave the other side exposed to direct and indirect radiation, to ensure a complete assessment of how the use of trees can be optimized. As Cairo city is very large and has a variety of urban morphologies, a total of 144 theoretical cases have been tested for Cairo city using ENVI-met to cover the majority of the urban cases within the city (Stage 1). Then, the same tree scenarios used in the theoretical study are applied to an existing urban area in downtown Cairo with many urban morphology varieties to validate the results of the theoretical study (Stage 2). After testing all cases in both stages, it became very clear that the addition of trees cannot be the same for the different aspect ratios, orientations, and sides of the different canyons. For example, eastern roads should have more trees than other orientations for all aspect ratios, but the required number of trees is greater for the northern side than the southern side, as the southern side is partially shaded for a few hours of the day by buildings in moderate and deep canyons. Northern streets require a very limited number of trees, even in shallow canyons, on both sides. The correlation between the number of trees on each side for the different orientations and aspect ratios shows a strong negative relationship, but the correlation values change between the different sides and orientations. The results of applying trees to an existing urban area show almost the same results as the theoretical study’s results, with very slight differences occurring because of the irregularity of the existing study area. This proves that when adding trees, not only the aspect ratio and orientation but also the side of each canyon should be considered to ensure that pedestrians, in all cases, have better microclimate conditions and that the use of trees is optimized.
Spatial–Temporal Coupling Analysis of Land Use Function and Urban–Rural Integration in Heilongjiang, China
Authors: Zhang Na , Yao Yishan , Wang Lu , Li Quanfeng
Published: December 2023

Urban–rural integration relies on the rational flow of factors between urban–rural areas. Land represents a closely related factor between urban–rural areas, so the effective utilization of land resources can promote the flow of urban–rural factors. Therefore, there is a certain correlation between land use function and urban–rural integration. The purpose of this study is to explore the coupling and coordination relationship between the two systems and to find out the spatial–temporal differentiation characteristics in the process of land use function and urban–rural integration. The main conclusions are as follows: (1) The comprehensive level of land use function and urban–rural integration in Heilongjiang Province shows an overall upward trend, but there is a large differentiation on a municipal scale. (2) The coupling coordination degree of the two systems in Heilongjiang Province shows a spatial distribution pattern of “high in the north and low in the south, high in the middle and low in the east and west”. From 2013 to 2022, except for Harbin and Yichun, the overall trend in other regions is gradually upward. (3) The obstacle degree analysis of land use function and urban–rural integration in Heilongjiang Province shows that there is a close correlation of obstacle factors between the two systems.
A Corneal Biomechanical Study Measured with a Scheimpflug Dynamic Analyser in Soft Contact Lens Wearers
Authors: López-Muñoz Alfredo , López-Castaño Isabel , Torres-Parejo Úrsula , García-Romera Marta-C.
Published: December 2023

The aim of this study was to evaluate the biomechanical changes in the cornea after wearing soft contact lenses (CLs) in healthy myopic patients measured with a Corvis ST® (CST, Oculus Optikgeräte GmbH, Wetzlar, Germany) analyser. This prospective, cross-sectional, single-centre study was performed on twenty-two Caucasian patients aged between 19 and 24 years (20.64 ± 1.21 years) range. Five device-specific biomechanical parameters, the central corneal thickness (CCT), and biomechanically corrected intraocular pressure (bIOP) were measured prior to fitting and one month after CL wear. Differences between the means of the deflection amplitude ratio (DA Ratio) and the standard deviation of the DA Ratio (SD DA Ratio) pre- and post-CL wear were found to be significant (p value = 0.002 in both cases). Significant differences were found between pre- and post-CL wear values in CCT (p value = 0.013). For all other biomechanical measures, no significant differences were observed before and after treatment. A significant association was found between changes in bIOP and classification according to changes in Int. Radius (p value = 0.047) and SSI (p value = 0.026) standard deviations. The corneal biomechanical indices provided by CST demonstrate that the fitting of soft CLs is a safe optical compensation method for the stability of corneal stiffness. No significant differences were found pre- and post-CL wear in the assessment of bIOP.
Resistin Induces Migration and Invasion in PC3 Prostate Cancer Cells: Role of Extracellular Vesicles
Authors: Oregel-Cortez Mario Israel , Frayde-Gómez Héctor , Quintana-González Georgina , García-González Victor , Vazquez-Jimenez Jose Gustavo , Galindo-Hernández Octavio
Published: December 2023

Resistin is an adipokine with metabolic and inflammatory functions. Epidemiological and translational studies report that an increase in plasma levels and tissue expression of resistin increases the aggressiveness of prostate tumor cells. Extracellular vesicles (EVs) are secreted constitutively and induced by cytokines, growth factors, and calcium and are found in multiple biological fluids such as saliva, serum, semen, and urine. In particular, EVs have been shown to promote tumor progression through the induction of proliferation, growth, angiogenesis, resistance to chemotherapy, and metastasis. However, the role of resistin in the migration, invasion, and secretion of EVs in invasive prostate tumor cells remains to be studied. In the present study, we demonstrate that resistin induces increased migration and invasion in PC3 cells. In addition, these phenomena are accompanied by increased p-FAK levels and increased secretion of MMP-2 and MMP-9 in resistin-treated PC3 cells. Interestingly, EVs isolated from supernatants of PC3 cells treated with resistin induce an increase in migration and invasion accompanied by high MMP-2 and MMP-9 secretion in an autocrine stimulation model. In summary, our data for the first time demonstrate that resistin induces migration and invasion, partly through the secretion of EVs with pro-invasive characteristics in PC3 cells.
Diversity of Culture Microorganisms from Portuguese Sweet Cherries
Authors: Gonçalves Ana C. , Falcão Amílcar , Alves Gilberto , Silva Luís R. , Flores-Félix José D.
Published: December 2023

Consumers today seek safe functional foods with proven health-promoting properties. Current evidence shows that a healthy diet can effectively alleviate oxidative stress levels and reduce inflammatory markers, thereby preventing the occurrence of many types of cancer, hypertension, and cardiovascular and neurological pathologies. Nevertheless, as fruits and vegetables are mainly consumed fresh, they can serve as vectors for the transmission of pathogenic microorganisms associated with various disease outbreaks. As a result, there has been a surge in interest in the microbiome of fruits and vegetables. Therefore, given the growing interest in sweet cherries, and since their microbial communities have been largely ignored, the primary purpose of this study is to investigate their culturome at various maturity stages for the first time. A total of 55 microorganisms were isolated from sweet cherry fruit, comprising 23 bacteria and 32 fungi species. Subsequently, the selected isolates were molecularly identified by amplifying the 16S rRNA gene and ITS region. Furthermore, it was observed that the communities became more diverse as the fruit matured. The most abundant taxa included Pseudomonas and Ralstonia among the bacteria, and Metschnikowia, Aureobasidium, and Hanseniaspora among the fungi.
Patients with Hepatitis C Undergoing Direct-Acting Antiviral Treatment Have a Lower SARS-CoV-2 Infection Rate
Authors: Hsu Chin-Wen , Yang Wan-Wen , Hou Chia-Yi , Feng I-Jung , Huang Ting-Yi , Lee Pei-Lun , Guo How-Ran , Huang Chien-Yuan , Su Shih-Bin
Published: December 2023

This study retrospectively analyzed the medical records of 602 patients with first-time positive results for the HCV nucleic acid test between 1 May 2021 and 31 March 2023, exploring the association between DAA treatment and SARS-CoV-2 infection. The results showed that 9.8% of HCV patients were co-infected with SARS-CoV-2. Gender, age, vaccination status, and HCV genotype did not significantly affect SARS-CoV-2 infection. However, patients undergoing DAA treatment showed significantly lower rates of SARS-CoV-2 infection and mortality compared to those not undergoing DAA treatment. The analysis also compared patients undergoing different DAA treatments, with Epclusa and Maviret showing superior protection against SARS-CoV-2. Furthermore, this study explored the severity and mortality of SARS-CoV-2 infection in patients undergoing and having completed DAA treatment. It revealed that patients diagnosed with COVID-19 during DAA treatment experienced only mild symptoms, and none died, suggesting a potential protective effect of DAA treatment against severe outcomes of SARS-CoV-2 infection. The findings contribute to the understanding of the interplay between HCV, DAA treatment, and SARS-CoV-2 infection, highlighting the need for continued monitoring and healthcare measures for individuals with chronic conditions during the ongoing COVID-19 pandemic.
Sources and Destinations of Oil Leakage through TPOCR Based on 2D-LIF Observation and Modeling Analysis
Authors: Li Mo , Tian Tian
Published: December 2023

The Three-Piece Oil Control Ring (TPOCR) is becoming a viable option for heavy duty gas and hydrogen engines due to the low particle concentration in these engines. Although direct oil leakage from the gap is not likely to happen with the misalignment of the upper and lower rail gaps, there exist other less-apparent oil leaking mechanisms through the TPOCR. This work is targeted at understanding the oil leakage’s source and destination through the rail and liner interfaces across the whole cycle. The 2D Laser Induced Fluorescence technique was applied on an optical engine to study the oil transport behavior. Combined with a TPOCR model for dynamics and lubrication, the mechanisms that cause rail twist and oil scraping by the upper rail were analyzed. It was found that the symmetrical rail can scrape the oil up in the up-strokes. The scraped oil first accumulates in the clearance between the upper rail and groove, as well as at the upper corner of the rail Outer Diameter before being transferred to both the third land and liner when the piston changes direction at Top Dead Center. Rails with an asymmetrical profile can reduce or enhance these effects depending the orientation of the rails. This study provides findings that could help design the engine to better control Lubricate Oil Consumption and properly lubricate the Top Dead Center’s dry region at the same time.
Research on the Relationship between Dynamic Characteristics and Friction Torque Fluctuation of CMGB under the Condition of Time-Varying Moment
Authors: Zhang Wenhu , Li Shili , Zhou Gang , Zhou Ningning , Zhao Yan , Li Wanjia
Published: December 2023

In this paper, a dynamic simulation analysis model was established for CMGB (control moment gyroscope bearing) under the conditions of time-varying moment. The influences of the moment’s response time, axial preload, and working temperature on the dynamic characteristics and friction torque of CMGB were analyzed, and the relevant verification tests were conducted. The results show that the friction torque fluctuation of CMGB directly corresponds to the dynamic characteristics. The faster the response time of the time-varying moment, the larger the friction torque fluctuation of CMGB. The larger preload minimizes the difference in the ball’s loading state, which is the actual reason for reducing the friction torque fluctuation. Moreover, as the working temperature increases, the friction torque fluctuation of CMGB decreases.
Online Condition Monitoring of Industrial Loads Using AutoGMM and Decision Trees
Authors: Brescia Elia , Vergallo Patrizia , Serafino Pietro , Tipaldi Massimo , Cascella Davide , Cascella Giuseppe Leonardo , Romano Francesca , Polichetti Andrea
Published: December 2023

Condition monitoring and fault management approaches can help with timely maintenance planning, assure industry-wide continuous production, and enhance both performance and safety in complex industrial operations. At the moment, data-driven approaches for condition monitoring and fault detection are the most attractive being conceived, developed, and applied with less of a need for sophisticated expertise and detailed knowledge of the addressed plant. Among them, Gaussian mixture model (GMM) methods can offer some advantages. However, conventional GMM solutions need the number of Gaussian components to be defined in advance and suffer from the inability to detect new types of faults and identify new operating modes. To address these issues, this paper presents a novel data-driven method, based on automated GMM (AutoGMM) and decision trees (DTree), for the online condition monitoring of electrical industrial loads. By leveraging the benefits of the AutoGMM and the DTree, after the training phase, the proposed approach allows the clustering and time allocation of nominal operating conditions, the identification of both already-classified and new anomalous conditions, and the acknowledgment of new operating modes of the monitored industrial asset. The proposed method, implemented on a commercial cloud-computing platform, is validated on a real industrial plant with electrical loads, characterized by a daily periodic working cycle, by using active power consumption data.
Progressively Multi-Scale Feature Fusion for Image Inpainting
Authors: Wen Wu , Li Tianhao , Tolba Amr , Liu Ziyi , Shao Kai
Published: December 2023

The rapid advancement of Wise Information Technology of med (WITMED) has made the integration of traditional Chinese medicine tongue diagnosis and computer technology an increasingly significant area of research. The doctor obtains patient’s tongue images to make a further diagnosis. However, the tongue image may be broken during the process of collecting the tongue image. Due to the extremely complex texture of the tongue and significant individual differences, existing methods fail to fully obtain sufficient feature information, which result in inaccurate inpainted tongue images. To address this problem, we propose a recurrent tongue image inpainting algorithm based on multi-scale feature fusion called Multi-Scale Fusion Module and Recurrent Attention Mechanism Network (MSFM-RAM-Net). We first propose Multi-Scale Fusion Module (MSFM), which preserves the feature information of tongue images at different scales and enhances the consistency between structures. To simultaneously accelerate the inpainting process and enhance the quality of the inpainted results, Recurrent Attention Mechanism (RAM) is proposed. RAM focuses the network’s attention on important areas and uses known information to gradually inpaint image, which can avoid redundant feature information and the problem of texture confusion caused by large missing areas. Finally, we establish a tongue image dataset and use this dataset to qualitatively and quantitatively evaluate the MSFM-RAM-Net. The results shows that the MSFM-RAM-Net has a better effect on tongue image inpainting, with PSNR and SSIM increasing by 2.1% and 3.3%, respectively.
A Microscopic Traffic Model Incorporating Vehicle Vibrations Due to Pavement Condition
Authors: Ali Faryal , Khan Zawar Hussain , Khattak Khurram Shehzad , Gulliver Thomas Aaron , Altamimi Ahmed B.
Published: December 2023

A microscopic traffic flow model is developed that incorporates vehicle vibrations due to pavement condition. The Intelligent Driver (ID) model employs a fixed exponent so traffic behavior is the same regardless of the road condition. Thus, it ignores the underlying physics. To address this limitation, the proposed model employs the Pavement Condition Index (PCI) in describing traffic behavior. The performance of both models is evaluated on a 3000 m circular road using the Euler numerical discretization technique. The results show that the performance of the proposed model varies with the pavement condition (PCI), as expected. Furthermore, the traffic flow increases with vehicle speed. The oscillations in speed and density with the proposed model decrease as the PCI increases, and are larger when the speed is higher. Consequently, the results with the proposed model align more closely with reality as they are based on the PCI, and so are a more accurate representation of traffic behavior.
Get Spatial from Non-Spatial Information: Inferring Spatial Information from Textual Descriptions by Conceptual Spaces
Authors: Abbasi Omid Reza , Alesheikh Ali Asghar , Razavi-Termeh Seyed Vahid
Published: December 2023

With the rapid growth of social media, textual content is increasingly growing. Unstructured texts are a rich source of latent spatial information. Extracting such information is useful in query processing, geographical information retrieval (GIR), and recommender systems. In this paper, we propose a novel approach to infer spatial information from salient features of non-spatial nature in text corpora. We propose two methods, namely DCS and RCS, to represent place-based concepts. In addition, two measures, namely the Shannon entropy and the Moran’s I, are proposed to calculate the degree of geo-indicativeness of terms in texts. The methodology is compared with a Latent Dirichlet Allocation (LDA) approach to estimate the accuracy improvement. We evaluated the methods on a dataset of rental property advertisements in Iran and a dataset of Persian Wikipedia articles. The results show that our proposed approach enhances the relative accuracy of predictions by about 10% in case of the renting advertisements and by 13% in case of the Wikipedia articles. The average distance error is about 13.3 km for the advertisements and 10.3 km for the Wikipedia articles, making the method suitable to infer the general region of the city in which a property is located. The proposed methodology is promising for inferring spatial knowledge from textual content that lacks spatial terms.
Mathematical Modeling of Periodic Outbreaks with Waning Immunity: A Possible Long-Term Description of COVID-19
Authors: Viguerie Alex , Carletti Margherita , Silvestri Guido , Veneziani Alessandro
Published: December 2023

The COVID-19 pandemic is still ongoing, even if the emergency is over, and we now have enough data to analyze the outbreak over a long timeline. There is evidence that the outbreak alternates periods of high and low infections. Retrospectively, this can help in understanding the nature of an appropriate mathematical model for this dramatic infection. The periodic behavior may be the consequence of time-dependent coefficients related to seasonal effects and specific political actions, or an intrinsic feature of the model. The present paper relies on the assumption that the periodic spikes are an intrinsic feature of the disease, and, as such, it should be properly reflected in the mathematical model. Based on the concept of waning immunity proposed for other pathologies, we introduce a new model with (i) a compartment for weakly immune people subject to immunity booster, represented by a non-linear term; (ii) discrimination between individuals infected/vaccinated for the first time, and individuals already infected/vaccinated, undergoing to new infections/doses. We analyze some preliminary properties of our model, called SIRW2, and provide a proof-of-concept that it is capable of reproducing qualitatively the long-term oscillatory behavior of COVID-19 infection.
A Projection Pursuit Dynamic Cluster Model for Tourism Safety Early Warning and Its Implications for Sustainable Tourism
Authors: Zhong Chenghao , Lou Wengao , Lai Yongzeng
Published: December 2023

According to the United Nations World Tourism Organization, tourism promotes sustainable economic development. Ensuring tourism safety is an essential prerequisite for its sustainable development. In this paper, based on the three evaluation index systems for tourism safety early warning and the collected sample data, we establish three projection pursuit dynamic cluster (PPDC) models by applying group search optimization, a type of swarm intelligence algorithm. Based on case studies, it is confirmed that the results derived from the PPDC models are consistent with the expert judgments. The importance of the evaluation indicators can be sorted and classified according to the obtained optimal projection pursuit vector coefficients, and the tourism risks of the destinations can be ranked according to the sample projection values. Among the three aspects influencing tourism safety in case one, the stability of the tourism destination has the most significant impact, followed by the frequency of disasters. Of the ten evaluation indicators, the frequency of epidemic disease affects tourism safety the most, and the unemployment ratio affects it the second most. Overall, the PPDC model can be adopted for tourism safety early warning with high-dimensional non-linear and non-normal distribution data modeling, as it overcomes the “curse of dimensionality” and the limitations associated with small sample sizes.
Quantized Graph Neural Networks for Image Classification
Authors: Xu Xinbiao , Ma Liyan , Zeng Tieyong , Huang Qinghua
Published: December 2023

Researchers have resorted to model quantization to compress and accelerate graph neural networks (GNNs). Nevertheless, several challenges remain: (1) quantization functions overlook outliers in the distribution, leading to increased quantization errors; (2) the reliance on full-precision teacher models results in higher computational and memory overhead. To address these issues, this study introduces a novel framework called quantized graph neural networks for image classification (QGNN-IC), which incorporates a novel quantization function, Pauta quantization (PQ), and two innovative self-distillation methods, attention quantization distillation (AQD) and stochastic quantization distillation (SQD). Specifically, PQ utilizes the statistical characteristics of distribution to effectively eliminate outliers, thereby promoting fine-grained quantization and reducing quantization errors. AQD enhances the semantic information extraction capability by learning from beneficial channels via attention. SQD enhances the quantization robustness through stochastic quantization. AQD and SQD significantly improve the performance of the quantized model with minimal overhead. Extensive experiments show that QGNN-IC not only surpasses existing state-of-the-art quantization methods but also demonstrates robust generalizability.
Attitude Stabilization of a Satellite with Large Flexible Elements Using On-Board Actuators Only
Authors: Tkachev Stepan , Shestoperov Alexey , Okhitina Anna , Nuralieva Anna
Published: December 2023

Attitude control of a satellite with three flexible elements is considered. Control torque is developed by a set of reaction wheels, which are installed on the central hub of the satellite. The flexible elements are large, so the control torque constraints must be taken into account. In the paper, a control algorithm based on a linear-quadratic regulator is studied. The asymptotic stability of this control is shown. The choice of the control parameters is based on the closed form solution of the corresponding algebraic Riccati equation, which is supplemented by the linear matrix inequality. To increase the convergence rate, particle swarm optimization is used to tune the control parameters.
Biotechnological Potential of Macroalgae during Seasonal Blooms for Sustainable Production of UV-Absorbing Compounds
Authors: Rosic Nedeljka , Thornber Carol
Published: December 2023

Marine macroalgae (seaweeds) are important primary global producers, with a wide distribution in oceans around the world from polar to tropical regions. Most of these species are exposed to variable environmental conditions, such as abiotic (e.g., light irradiance, temperature variations, nutrient availability, salinity levels) and biotic factors (e.g., grazing and pathogen exposure). As a result, macroalgae developed numerous important strategies to increase their adaptability, including synthesizing secondary metabolites, which have promising biotechnological applications, such as UV-absorbing Mycosporine-Like Amino Acid (MAAs). MAAs are small, water-soluble, UV-absorbing compounds that are commonly found in many marine organisms and are characterized by promising antioxidative, anti-inflammatory and photoprotective properties. However, the widespread use of MAAs by humans is often restricted by their limited bioavailability, limited success in heterologous expression systems, and low quantities recovered from the natural environment. In contrast, bloom-forming macroalgal species from all three major macroalgal clades (Chlorophyta, Phaeophyceae, and Rhodophyta) occasionally form algal blooms, resulting in a rapid increase in algal abundance and high biomass production. This review focuses on the bloom-forming species capable of producing pharmacologically important compounds, including MAAs, and the application of proteomics in facilitating macroalgal use in overcoming current environmental and biotechnological challenges.
Natural Product Cordycepin (CD) Inhibition for NRP1/CD304 Expression and Possibly SARS-CoV-2 Susceptibility Prevention on Cancers
Authors: Li Ting , Luo Na , Fu Jiewen , Du Jiaman , Liu Zhiying , Tan Qi , Zheng Meiling , He Jiayue , Cheng Jingliang , Li Dabing , Fu Junjiang
Published: December 2023

NRP1/CD304 is a typical membrane-bound co-receptor for the vascular endothelial cell growth factor (VEGF), semaphorin family members, and viral SARS-CoV-2. Cordycepin (CD) is a natural product or active gradient from traditional Chinese medicine (TCM) from Cordyceps militaris Link and Ophiocordyceps sinensis (Berk.). However, NRP1 expression regulation via CD in cancers and the potential roles and mechanisms of SARS-CoV-2 infection are not clear. In this study, online databases were analyzed, Western blotting and quantitative RT-PCR were used for NRP1 expression change via CD, molecular docking was used for NRP/CD interaction, and a syncytial formation assay was used for CD inhibition using a pseudovirus SARS-CoV-2 entry. As a result, we revealed that CD inhibits NRP1 expressed in cancer cells and prevents viral syncytial formation in 293T-hACE2 cells, implying the therapeutic potential for both anti-cancer and anti-viruses, including anti-SARS-CoV-2. We further found significant associations between NRP1 expressions and the tumor–immune response in immune lymphocytes, chemokines, receptors, immunostimulators, immune inhibitors, and major histocompatibility complexes in most cancer types, implying NRP1’s roles in both anti-cancer and anti-SARS-CoV-2 entry likely via immunotherapy. Importantly, CD also downregulated the expression of NRP1 from lymphocytes in mice and downregulated the expression of A2AR from the lung cancer cell line H1975 when treated with CD, implying the NRP1 mechanism probably through immuno-response pathways. Thus, CD may be a therapeutic component for anti-cancer and anti-viral diseases, including COVID-19, by targeting NRP1 at least.
A PCR-Based Survey of Methane-Cycling Archaea in Methane-Soaked Subsurface Sediments of Guaymas Basin, Gulf of California
Authors: Hinkle John E. , Mara Paraskevi , Beaudoin David J. , Edgcomb Virginia P. , Teske Andreas P.
Published: December 2023

The Guaymas Basin in the Gulf of California is characterized by active seafloor spreading, the rapid deposition of organic-rich sediments, steep geothermal gradients, and abundant methane of mixed thermogenic and microbial origin. Subsurface sediment samples from eight drilling sites with distinct geochemical and thermal profiles were selected for DNA extraction and PCR amplification to explore the diversity of methane-cycling archaea in the Guaymas Basin subsurface. We performed PCR amplifications with general (mcrIRD), and ANME-1 specific primers that target the alpha (α) subunit of methyl coenzyme M reductase (mcrA). Diverse ANME-1 lineages associated with anaerobic methane oxidation were detected in seven out of the eight drilling sites, preferentially around the methane-sulfate interface, and in several cases, showed preferences for specific sampling sites. Phylogenetically, most ANME-1 sequences from the Guaymas Basin subsurface were related to marine mud volcanoes, seep sites, and the shallow marine subsurface. The most frequently recovered methanogenic phylotypes were closely affiliated with the hyperthermophilic Methanocaldococcaceae, and found at the hydrothermally influenced Ringvent site. The coolest drilling site, in the northern axial trough of Guaymas Basin, yielded the greatest diversity in methanogen lineages. Our survey indicates the potential for extensive microbial methane cycling within subsurface sediments of Guaymas Basin.
Oral Microbial Profile Analysis in Patients with Oral and Pharyngeal Cancer Reveals That Tumoral Fusobacterium nucleatum Promotes Oral Cancer Progression by Activating YAP
Authors: Yamamoto Yuki , Kamiya Tomonori , Yano Megumu , Huyen Vu Thuong , Oishi Masahiro , Nishio Miki , Suzuki Akira , Sunami Kishiko , Ohtani Naoko
Published: December 2023

The incidence of oral cancer has recently been increasing worldwide, particularly among young individuals and women. The primary risk factors for head and neck cancers, including oral and pharyngeal cancers, are smoking, alcohol consumption, poor oral hygiene, and repeated exposure to mechanical stimuli. However, approximately one-third of the patients with oral and pharyngeal cancers are neither smokers nor drinkers, which points to the existence of other mechanisms. Recently, human microbes have been linked to various diseases, including cancer. Oral pathogens, especially periodontal pathobionts, are reported to play a role in the development of colon and other types of cancer. In this study, we employed a series of bioinformatics analyses to pinpoint Fusobacterium nucleatum as the predominant oral bacterial species in oral and pharyngeal cancer tissue samples. We successfully isolated Fn. polymorphum from the saliva of patients with oral cancer and demonstrated that Fn. polymorphum indeed promoted oral squamous cell carcinoma development by activating YAP in a mouse tongue cancer model. Our research offers scientific evidence for the role of the oral microbiome in oral cancer progression and provides insights that would help in devising preventative strategies against oral cancer, potentially by altering oral bacterial profiles.
Complete Genome Sequence and Pan-Genome Analysis of Shewanella oncorhynchi Z-P2, a Siderophore Putrebactin-Producing Bacterium
Authors: Zhang Ying , Pan Mengjie , Wang Qiaoyun , Wang Lan , Liao Li
Published: December 2023

In this study, we reported the complete genome sequence of Shewanella oncorhynchi for the first time. S. oncorhynchi Z-P2 is a bacterium that produces the siderophore putrebactin. Its genome consists of a circular chromosome of 5,034,612 bp with a G + C content of 45.4%. A total of 4544 protein-coding genes, 109 tRNAs and 31 rRNAs were annotated by the RAST. Five non-ribosomal peptide synthetase (NRPS) and polyketide synthetase (PKS) gene clusters were identified by the antiSMASH analysis. The pan-genome analysis of Z-P2 and 10 Shewanella putrefaciens revealed 9228 pan-gene clusters and 2681 core gene clusters, with Z-P2 having 618 unique gene clusters. Additionally, the gene cluster involved in putrebactin biosynthesis in Z-P2 was annotated, and the mechanism of putrebactin biosynthesis was analyzed. The putrebactin produced by Z-P2 was detected using UPLC-MS analysis, with an [M + H]+ molecular ion at m/z 373.21. These findings provide valuable support for further research on the genetic engineering of putrebactin biosynthetic genes of Z-P2 and their potential applications.
Structural Characterization and Properties of Modified Soybean Meal Protein via Solid-State Fermentation by Bacillus subtilis
Authors: Miao Xinyu , Niu Honghong , Sun Mubai , Li Da , Hua Mei , Wang Jinghui , Su Ying
Published: December 2023

Soybean meal (SBM) is a high-quality vegetable protein, whose application is greatly limited due to its high molecular weight and anti-nutritional properties. The aim of this study was to modify the protein of soybean meal via solid-state fermentation of Bacillus subtilis. The fermentation conditions were optimized as, finally, the best process parameters were obtained, namely fermentation temperature of 37 °C, inoculum amount of 12%, time of 47 h, and material-liquid ratio of 1:0.58, which improved the content of acid-soluble protein. To explore the utilization of modified SBM as a food ingredient, the protein structure and properties were investigated. Compared to SBM, the protein secondary structure of fermented soybean meal (FSBM) from the optimal process decreased by 8.3% for α-helix content, increased by 3.08% for β-sheet, increased by 2.71% for β-turn, and increased by 2.51% for random coil. SDS-PAGE patterns showed that its 25–250 KDa bands appeared to be significantly attenuated, with multiple newborn peptide bands smaller than 25 KDa. The analysis of particle size and zeta potential showed that fermentation reduced the average particle size and increased the absolute value of zeta potential. It was visualized by SEM and CLSM maps that the macromolecular proteins in FSBM were broken down into fragmented pieces with a folded and porous surface structure. Fermentation increased the solubility, decreased the hydrophobicity, increased the free sulfhydryl content, decreased the antigenicity, improved the protein properties of SBM, and promoted further processing and production of FSBM as a food ingredient.
Carbon Nanostructured Immunosensing of Anti-SARS-CoV-2 S-Protein Antibodies
Authors: du Plooy Jarid , Kock Branham , Jahed Nazeem , Iwuoha Emmanuel , Pokpas Keagan
Published: December 2023

The rampant spread and death rate of the recent coronavirus pandemic related to the SARS-CoV-2 respiratory virus have underscored the critical need for affordable, portable virus diagnostics, particularly in resource-limited settings. Moreover, efficient and timely monitoring of vaccine efficacy is needed to prevent future widespread infections. Electrochemical immunosensing poses an effective alternative to conventional molecular spectroscopic approaches, offering rapid, cost-effective, sensitive, and portable electroanalysis of disease biomarkers and antibodies; however, efforts to improve binding efficiency and sensitivity are still being investigated. Graphene quantum dots (GQDs) in particular have shown promise in improving device sensitivity. This study reports the development of a GQD-functionalized point-of-contamination device leveraging the selective interactions between SARS-CoV-2-specific Spike (S) Protein receptor binding domain (RBD) antigens and IgG anti-SARS-CoV-2-specific S-protein antibodies at screen-printed carbon electrode (SPCE) surfaces. The immunocomplexes formed at the GQD surfaces result in the interruption of the redox reactions that take place in the presence of a redox probe, decreasing the current response. Increased active surface area, conductivity, and binding via EDC/NHS chemistry were achieved due to the nanomaterial inclusion, with 5 nm, blue luminescent GQDs offering the best results. GQD concentration, EDC/NHS ratio, and RBD S-protein incubation time and concentration were optimized for the biosensor, and inter- and intra-screen-printed carbon electrode detection was investigated by calibration studies on multiple and single electrodes. The single electrode used for the entire calibration provided the best results. The label-free immunosensor was able to selectively detect anti-SARS-CoV-2 IgG antibodies between 0.5 and 100 ng/mL in the presence of IgM and other coronavirus antibodies with an excellent regression of 0.9599. A LOD of 2.028 ng/mL was found, offering comparable findings to the literature-reported values. The detection sensitivity of the sensor is further compared to non-specific IgM antibodies. The developed GQD immunosensor was compared to other low-oxygen content carbon nanomaterials, namely (i) carbon quantum dot (CQD), (ii) electrochemically reduced graphene oxide, and (iii) carbon black-functionalized devices. The findings suggest that improved electron transfer kinetics and increased active surface area of the CNs, along with surface oxygen content, aid in the detection of anti-SARS-CoV-2 IgG antibodies. The novel immunosensor suggests a possible application toward monitoring of IgG antibody production in SARS-CoV-2-vaccinated patients to study immune responses, vaccine efficacy, and lifetime to meet the demands for POC analysis in resource-limited settings.