bluuebunny/crossref_metadata_2025 huggingface dataset:
Risk-based hydrologic design under climate change using stochastic weather and watershed modeling
Authors: Shabestanipour Ghazal , Brodeur Zachary , Manoli Benjamin , Birnbaum Abigail , Steinschneider Scott , Lamontagne Jonathan R.
Published: March 2024

Water resources planning and management requires the estimation of extreme design events. Anticipated climate change is playing an increasingly prominent role in the planning and design of long-lived infrastructure, as changes to climate forcings are expected to alter the distribution of extremes in ways and to extents that are difficult to predict. One approach is to use climate projections to force hydrologic models, but this raises two challenges. First, global climate models generally focus on much larger scales than are relevant to hydrologic design, and regional climate models that better capture small scale dynamics are too computationally expensive for large ensemble analyses. Second, hydrologic models systematically misrepresent the variance and higher moments of streamflow response to climate, resulting in a mischaracterization of the extreme flows of most interest. To address both issues, we propose a new framework for non-stationary risk-based hydrologic design that combines a stochastic weather generator (SWG) that accurately replicates basin-scale weather and a stochastic watershed model (SWM) that accurately represents the distribution of extreme flows. The joint SWG-SWM framework can generate large ensembles of future hydrologic simulations under varying climate conditions, from which design statistics and their uncertainties can be estimated. The SWG-SWM framework is demonstrated for the Squannacook River in the Northeast United States. Standard approaches to design flows, like the T-year flood, are difficult to interpret under non-stationarity, but the SWG-SWM simulations can readily be adapted to risk and reliability metrics which bare the same interpretation under stationary and non-stationary conditions. As an example, we provide an analysis comparing the use of risk and more traditional T-year design events, and conclude that risk-based metrics have the potential to reduce regret of over- and under-design compared to traditional return-period based analyses.
Managed aquifer recharge as a strategy to redistribute excess surface flow to baseflow in snowmelt hydrologic regimes
Authors: Ferencz Stephen B. , Mangel Adam , Day-Lewis Frederick
Published: March 2024

Water management in snowmelt hydrologic regimes, characterized by large annual fluctuations in stream flow driven by seasonal snow melt, faces the challenge of highly variable supply that often does not align with timing of demand. Climate change may exacerbate management challenges by significantly reducing snowpack or shifting snow melt earlier. Here, managed aquifer recharge (MAR) is evaluated as a potential strategy to reallocate excess early-season stream flow to time periods when less surface water is available. This strategy differs from traditional MAR, where the goal is to minimize loss to surface water. We assess how to site MAR operations such that groundwater recharge flows back to the surface water system in a lagged manor to benefit water management objectives, which we term “enhanced baseflow.” We use a regional groundwater model for the Treasure Valley aquifer located in southwestern Idaho, United States to demonstrate a generalizable approach using regional groundwater models as tools to identify favorable baseflow enhancement locations. Hypothetical MAR is simulated at 197 candidate locations, which are then evaluated for how effectively they meet potential management objectives. In addition to demonstrating the modeling and evaluation approach, we discuss lessons learned from applying a pre-existing regional groundwater model to MAR for enhanced baseflow and also describe important considerations, such as the physical and institutional availability of surface flows and specific management objectives, when assessing regional and site-specific suitability of MAR for enhanced baseflow as a potential management strategy.
Intradermal methylene blue analgesic application in posthemorrhoidectomy pain management: a randomized controlled trial
Authors: Azhough Ramin , Jalali Pooya , Dashti Mohammad Reza , Taher Sahar , Aghajani Ali
Published: March 2024

Introduction

Unbearable post-hemorrhoidectomy pain is a well-documented challenge, significantly impacting patient well-being and satisfaction after surgery, often influencing patients to decline in undergoing this procedure. It is widely recognized that methylene blue has an effect of reducing inflammation and pain by reduces the production of nitric oxide and inhibiting the action potentials production in nerves. This study aims to explore the potential benefits of postoperative regional administration of methylene blue in providing extended relief from post-hemorrhoidectomy pain.

Methods

This study included 97 patients aged 18–75 undergoing hemorrhoidectomy for stage III or IV hemorrhoids. A double-blind, randomized controlled trial compared postoperative intradermal injections of 1% methylene blue to 0.5% Marcaine as the control group. Two-week follow-up assessed pain. Statistical analysis, adherence to ethical standards, and registration were conducted.

Result

No significant differences were found in baseline demographics, surgical parameters, or complications between the Methylene Blue and control groups. Intervention group remained lower in mean pain score until the 12th day. Methylene blue group reported significantly lower postoperative pain scores from days 1 to 7, with no significant differences afterward.

Conclusion

This ongoing randomized controlled trial reveals the potential analgesic benefits of intradermal injection 1% methylene blue. It demonstrates comparable efficacy in reducing post-hemorrhoidectomy pain, with negligible side effects and complications.
Comparison of the efficacy of Aeromonas veronii ΔhisJ vaccine in Carassius auratus via different immunization routes
Authors: Wu Tonglei , Ma Ruitao , Pan Xiaoyi , Wang Fengjie , Zhang Zhiqiang , Shi Qiumei , Shan Xiaofeng , Gao Guisheng
Published: March 2024

Introdction

Aeromonas veronii is a significant pathogen to various aquatic life. Infections in fish can lead to high mortality rates, causing substantial economic losses in aquaculture. Vaccination is proposed as a substitute for antibiotics in aquaculture to decrease disease-related mortality and morbidity. Our study previously constructed a hisJ-deleted strain of A. veronii, which provided protective effect to Loach.

Methods

To further assess the vaccine’s applicability, this study evaluated its genetic stability and safety, and the immune protective effects in Carassius auratus through four distinct administration routes: intraperitoneal injection, intramuscular injection, oral administration, and immersion, to determine the efficacy of these administration routes.

Results

The results showed that the vaccine remained genetically stable after 45 generations. Immunization via these administration routes was safe for Carassius auratus, with intraperitoneal and intramuscular injections causing stronger adverse reactions. Immersion immunization resulted in mild adverse reactions, and no significant adverse reactions were observed following oral immunization. Immunizing Carassius auratus at safe concentrations via these routes enhanced the phagocytic activity in serum, increased the levels of non-specific immune-related enzymes (ACP, AKP, C3, C4, LZM, SOD, and IgM), and improved specific serum antibody levels. It also elevated levels of cytokines related to inflammatory responses (IL-1β, IL-10, TNF-α, TGF-β) in organ tissues (liver, spleen, kidney, mid-post intestine, and gills). The survival rates of Carassius auratus were measured after challenging with the virulent strain A. veronii TH0426, resulting in the relative survival rates of 64% for Intraperitoneal vaccine group, 56% for Intramuscular vaccine group, 52% for oral vaccine group, and 48% for immersion vaccine group. Analysis of bacterial load in the liver, spleen, and kidney post-challenge showed a decreasing trend in the control group, indicating that the vaccine strain ΔhisJ could gradually restrict the rapid proliferation of bacteria in these tissues, thereby providing a certain level of immune protection against A. veronii.

Discussion

In brief, the vaccine strain ΔhisJ can serve as a safe live attenuated vaccine for Carassius auratus, and this study lays the foundation for the development of live attenuated vaccines against Aeromonas veronii.
Modeling, Simulation and Control of a Spacecraft: Automated Rendezvous under Positional Constraints
Authors: Fiori Simone , Rachiglia Francesco , Sabatini Luca , Sampaolesi Edoardo
Published: March 2024

The aim of this research paper is to propose a framework to model, simulate and control the motion of a small spacecraft in the proximity of a space station. In particular, rendezvous in the presence of physical obstacles is tackled by a virtual potential theory within a modern manifold calculus setting and simulated numerically. The roto-translational motion of a spacecraft as well as the control fields are entirely formulated through a coordinate-free Lie group-type formalism. Likewise, the proposed control strategies are expressed in a coordinate-free setting through structured control fields. Several numerical simulations guide the reader through an evaluation of the most convenient control strategy among those devised in the present work.
TeaViTNet: Tea Disease and Pest Detection Model Based on Fused Multiscale Attention
Authors: Chen Zhichao , Zhou Hongping , Lin Haifeng , Bai Di
Published: March 2024

The tea industry, as one of the most globally important agricultural products, is characterized by pests and diseases that pose a serious threat to yield and quality. These diseases and pests often present different scales and morphologies, and some pest and disease target sizes can be tiny and difficult to detect. To solve these problems, we propose TeaViTNet, a multi-scale attention-based tea pest and disease detection model that combines CNNs and Transformers. First, MobileViT is used as the feature extraction backbone network. MobileViT captures and analyzes the tiny pest and disease features in the image via a self-attention mechanism and global feature extraction. Second, the EMA-PANet network is introduced to optimize the model’s learning and attention to the Apolygus lucorum and leaf blight regions via an efficient multi-scale attention module with cross-space learning, which improves the model’s ability to understand multi-scale information. In addition, RFBNet is embedded in the module to further expand the perceptual range and effectively capture the information of tiny features in tea leaf images. Finally, the ODCSPLayer convolutional block is introduced, aiming to focus on acquiring richer gradient flow information. The experimental results show that the TeaViTNet model proposed in this paper has an average accuracy of 89.1%, which is a significant improvement over the baseline network MobileViT and is capable of accurately detecting Apolygus lucorum and leaf blight of different scales and complexities.
Field-Deployed Spectroscopy from 350 to 2500 nm: A Promising Technique for Early Identification of Powdery Mildew Disease (Erysiphe necator) in Vineyards
Authors: Vélez Sergio , Barajas Enrique , Rubio José Antonio , Pereira-Obaya Dimas , Rodríguez-Pérez José Ramón
Published: March 2024

This study explores spectroscopy in the 350 to 2500 nm range for detecting powdery mildew (Erysiphe necator) in grapevine leaves, crucial for precision agriculture and sustainable vineyard management. In a controlled experimental vineyard setting, the spectral reflectance on leaves with varying infestation levels was measured using a FieldSpec 4 spectroradiometer during July and September. A detailed assessment was conducted following the guidelines recommended by the European and Mediterranean Plant Protection Organization (EPPO) to quantify the level of infestation; categorising leaves into five distinct grades based on the percentage of leaf surface area affected. Subsequently, spectral data were collected using a contact probe with a tungsten halogen bulb connected to the spectroradiometer, taking three measurements across different areas of each leaf. Partial Least Squares Regression (PLSR) analysis yielded coefficients of determination R2 = 0.74 and 0.71, and Root Mean Square Errors (RMSEs) of 12.1% and 12.9% for calibration and validation datasets, indicating high accuracy for early disease detection. Significant spectral differences were noted between healthy and infected leaves, especially around 450 nm and 700 nm for visible light, and 1050 nm, 1425 nm, 1650 nm, and 2250 nm for the near-infrared spectrum, likely due to tissue damage, chlorophyll degradation and water loss. Finally, the Powdery Mildew Vegetation Index (PMVI) was introduced, calculated as PMVI = (R755 − R675)/(R755 + R675), where R755 and R675 are the reflectances at 755 nm (NIR) and 675 nm (red), effectively estimating disease severity (R2 = 0.7). The study demonstrates that spectroscopy, combined with PMVI, provides a reliable, non-invasive method for managing powdery mildew and promoting healthier vineyards through precision agriculture practices.
Effects of Intercropping and Nitrogen Application on Soil Fertility and Microbial Communities in Peanut Rhizosphere Soil
Authors: Wu Haining , Chen Shufang , Huang Zhipeng , Huang Tangwei , Tang Xiumei , He Liangqiong , Li Zhong , Xiong Jun , Zhong Ruichun , Jiang Jing , Han Zhuqiang , Tang Ronghua
Published: March 2024

The intercropping of peanuts and sugarcane is a sustainable planting model that deserves in-depth research. For this study, two variables, i.e., intercropping status (peanut monocropping or sugarcane/peanut intercropping) and the level of nitrogen fertilization (low, medium, or high), were evaluated to analyze the effects of intercropping and nitrogen application on soil fertility and microbial communities in peanut rhizosphere soil. These analyses revealed that higher nitrogen application led to increased total nitrogen (TN), available nitrogen (AN), and soil organic matter (OM) levels in rhizosphere soil for both monocropped and intercropped peanuts, with a decrease in pH. Monocropped peanuts had higher TN, total phosphorus (TP), and total potassium (TK) levels compared to intercropped peanuts at the same nitrogen level but lower AN content and pH levels. The diversity of microbial communities in the rhizosphere soil of intercropped peanuts was significantly higher than that of monocropped peanuts under high levels of nitrogen fertilizer application. Higher levels of Gemmatimonadetes abundance were observed in intercropping rhizosphere soil, compared to that associated with peanut monocropping under low, middle, and high levels of nitrogen fertilizer application, whereas the opposite trend was observed for Chloroflexi abundance. Nitrospira abundance levels rose gradually in the monocropping treatment group, whereas the opposite trend was evident under intercropping conditions. Further analyses of nitrogen cycle-related genes demonstrated higher levels of nitrogen conversion cycle activity in intercropping peanut rhizosphere soil under low nitrogen levels, whereas nitrogen transformation cycle activity levels were higher in monocropping peanut rhizosphere soil under high levels of nitrogen amendment. It can be concluded that intercropping and nitrogen fertilizer application change the physical and chemical properties of soil, thus affecting the diversity and function of soil microbial communities in the peanut rhizosphere. These results offer a theoretical foundation for more efficient sugarcane/peanut intercropping systems.
Remote Sensing Extraction of Crown Planar Area and Plant Number of Papayas Using UAV Images with Very High Spatial Resolution
Authors: Lai Shuangshuang , Ming Hailin , Huang Qiuyan , Qin Zhihao , Duan Lian , Cheng Fei , Han Guangping
Published: March 2024

The efficient management of commercial orchards strongly requires accurate information on plant growing status for the implementation of necessary farming activities such as irrigation, fertilization, and pest control. Crown planar area and plant number are two very important parameters directly relating to fruit growth conditions and the final productivity of an orchard. In this study, in order to propose a novel and effective method to extract the crown planar area and number of mature and young papayas based on visible light images obtained from a DJ Phantom 4 RTK, we compared different vegetation indices (NGRDI, RGBVI, and VDVI), filter types (high- and low-pass filters), and filter convolution kernel sizes (3–51 pixels). Then, Otsu’s method was used to segment the crown planar area of the papayas, and the mean–standard deviation threshold (MSDT) method was used to identify the number of plants. Finally, the extraction accuracy of the crown planar area and number of mature and young papayas was validated. The results show that VDVI had the highest capability to separate the papayas from other ground objects. The best filter convolution kernel size was 23 pixels for the low-pass filter extraction of crown planar areas in mature and young plants. As to the plant number identification, segmentation could be set to the threshold with the highest F-score, i.e., the deviation coefficient n = 0 for single young papaya plants, n = 1 for single mature ones, and n = 1.4 for crown-connecting mature ones. Verification indicated that the average accuracy of crown planar area extraction was 93.71% for both young and mature papaya orchards and 95.54% for extracting the number of papaya plants. This set of methods can provide a reference for information extraction regarding papaya and other fruit trees with a similar crown morphology.
Antifungal and Coagulation Properties of a Copper (I) Oxide Nanopowder Produced by Out-of-Phase Pulsed Sonoelectrochemistry
Authors: Mancier Valérie , Fattoum Sirine , Haguet Hélène , Laloy Julie , Maillet Christina , Gangloff Sophie C. , Chopart Jean-Paul
Published: March 2024

Copper (I) oxide (cuprite) is a material widely used nowadays, and its versatility is further amplified when it is brought to the nanometric size. Among the possible applications of this nanomaterial, one of the most interesting is that in the medical field. This paper presents a cuprite nanopowder study with the aim of employing it in medical applications. With regards to the environmental context, the synthesis used is related to green chemistry since the technique (out-of-phase pulsed electrochemistry) uses few chemical products via electricity consumption and soft conditions of temperature and pressure. After different physico-chemical characterizations, the nanopowder was tested on the Candida albicans to determine its fungicide activity and on human blood to estimate its hemocompatibility. The results show that 2 mg of this nanopowder diluted in 30 µL Sabouraud broth was able to react with Candida albicans. The hemocompatibility tests indicate that for 25 to 100 µg/mL of nanopowder in an aqueous medium, the powder was not toxic for human blood (no hemolysis nor platelet aggregation) but promoted blood coagulation. It appears, therefore, as a potential candidate for the functionalization of matrices for medical applications (wound dressing or operating field, for example).
Stigmasterol Exerts an Anti-Melanoma Property through Down-Regulation of Reactive Oxygen Species and Programmed Cell Death Ligand 1 in Melanoma Cells
Authors: Han Na-Ra , Park Hi-Joon , Ko Seong-Gyu , Moon Phil-Dong
Published: March 2024

Cancer immunotherapy as a promising anti-cancer strategy has been widely studied in recent years. Stigmasterol (STIG), a phytosterol, is known to have various pharmacological effects, including anti-inflammatory effects. However, the pharmacological role of STIG on melanoma immunotherapy has not been investigated. The present study demonstrates the anti-melanoma potency of STIG through the regulation of PD-L1 levels. The results reveal that STIG reduces reactive oxygen species (ROS) levels induced by hydrogen peroxide and increases glutathione levels decreased by α-MSH in B16F10 cells. Moreover, STIG significantly decreases melanin content and tyrosinase activities elevated by α-MSH. It also suppresses nitric oxide production induced by α-MSH. Additionally, STIG induces apoptosis with the up-regulation of PARP activation. STIG inhibits IFN-γ-induced PD-L1 expression and STAT1 phosphorylation levels. STIG also reverses the up-regulation of PD-L1 and phosphorylated STAT1 levels augmented by cisplatin, and STIG enhances CD8(+) T-cell-mediated cell death against B16F10 cells. These findings represent the first evidence of pro-apoptotic activity of STIG on melanoma cells through the down-regulation of ROS and PD-L1 pathways. Therefore, STIG may be an effective candidate for melanoma immunotherapy.
Protective Mechanism of Rosa roxburghii Tratt Fermentation Broth against Ultraviolet-A-Induced Photoaging of Human Embryonic Skin Fibroblasts
Authors: Yuan Minglu , Fu Hao , Mo Qiuting , Wang Shiwei , Wang Changtao , Wang Dongdong , Zhang Jiachan , Li Meng
Published: March 2024

This study takes the fruit of Rosa roxburghii Tratt (RRT) as a fermentation substrate and carries out a quantitative visual analysis of the domestic and foreign literature on screenings of five different lactic acid bacteria to obtain a fermentation broth. Systemic anti-photoaging effects are analyzed at the biochemical, cellular, and molecular biological levels. DPPH and ABTS free radical scavenging activities are used to verify the antioxidant capacity of the RRT fruit fermentation broth in vitro. Human embryonic skin fibroblasts (HESs) are used to establish a UVA damage model, and the antioxidant capacity of the RRT fruit fermentation broth is verified in terms of intracellular reactive oxygen species (ROS) and antioxidant enzyme activity. RT-qPCR and ELISA are used to detect the expression of TGF-β/Smad, MMPs, and the MAPK/AP-1 and Nrf2/Keap-1 signaling pathways in order to explore the anti-oxidation and anti-photoaging effects of the RRT fruit fermentation broth by regulating different signaling pathways. The results show that an RRT fruit fermentation broth can effectively protect cells from oxidative stress caused by UVA and has significant anti-photoaging effects, with the co-cultured Lactobacillus Yogurt Starter LYS-20297 having the highest overall effect.
Motion Characteristics of Self-Sensing Piezoelectric Actuator for Yarn Micro-Gripper
Authors: Peng Laihu , Sun Yuan , Qi Yubao , Ru Xin
Published: March 2024

In order to solve the problem of low response frequency and poor consistency of conventional yarn grippers in weft accumulators, in this study, a piezoelectric yarn gripper is used instead of conventional yarn grippers and the motion characteristics of its actuator are studied. This gripper uses a bimorph piezoelectric bending actuator with a low-cost, well integrated self-sensing method based on charge measurement. The modeling of the piezoelectric micromanipulator is based on the piezoelectric and Euler–Bernoulli beam equations. The static and dynamic characteristics of the piezoelectric actuator as well as the self-sensing capability were experimentally tested. The experimental results show that the maximum output displacement at the end of the piezoelectric actuator is 834 μm, and the maximum output force is 388 μN at 150 V driving voltage. The stability and consistency of its response are also very good, with a response speed of 24 ms. The self-sensing test of the output force also proved the feasibility of the self-sensing method used, with an error of 0.74%. The piezoelectric yarn gripper studied in this paper is promising for practical clamping applications.
Current Applications and Future Perspectives of Photobiomodulation in Ocular Diseases: A Narrative Review
Authors: Cannas Claudia , Pintus Benedetta , Corgiolu Lina , Borrelli Enrico , Boscia Giacomo , Toro Mario Damiano , Giannaccare Giuseppe
Published: March 2024

The present article provides an overview of photobiomodulation (PBM), also known as low-level laser light therapy (LLLT), which has garnered attention in ophthalmology for its potential therapeutic benefits in various ocular diseases. Photobiomodulation involves the use of low-intensity lasers or light-emitting diodes to stimulate biological processes in target tissues without causing thermal damage. This article discusses how PBM has been explored across various ocular conditions, including ocular surface diseases, age-related macular degeneration, diabetic retinopathy, myopia, amblyopia, and glaucoma. It summarizes findings from human studies and clinical trials demonstrating positive outcomes of PBM treatment in these areas. Moreover, the article emphasizes the importance of establishing standardized treatment protocols in terms of session duration and frequency, light type, and patients’ inclusion criteria to further validate the role of PBM in managing ocular diseases.
Investigating the Impact of Wildfires on Lake Water Quality Using Earth Observation Satellites
Authors: Caroni Rossana , Pinardi Monica , Free Gary , Stroppiana Daniela , Parigi Lorenzo , Tellina Giulio , Bresciani Mariano , Albergel Clément , Giardino Claudia
Published: March 2024

A study was carried out to investigate the effects of wildfires on lake water quality using a source dataset of 2024 lakes worldwide, covering different lake types and ecological settings. Satellite-derived datasets (Lakes_cci and Fire_cci) were used and a Source Pathway Receptor approach applied which was conceptually represented by fires (burned area) as a source, precipitation/drought representing transport dynamics, and lakes as the ultimate receptor. This identified 106 lakes worldwide that are likely prone to be impacted by wildfires via a terrestrial pathway. Satellite-derived chlorophyll-a (Chl-a) and turbidity variables were used as indicators to detect changes in lake water quality potentially induced by wildfires over a four-year period. The lakes with the largest catchment areas burned and characterized by regular annual fires were located in Africa. Evidence for a strong influence of wildfires was not found across the dataset examined, although clearer responses were seen for some individual lakes. However, among the hydro-morphological characteristics examined, lake depth was found to be significant in determining Chl-a concentration peaks which were higher in shallow and lower in deep lakes. Lake turbidity responses indicated a dependence on lake catchment and weather conditions. While wildfires are likely to contribute to the nutrient load of lakes as found in previous studies, it is possible that in many cases it is not a dominant pressure and that its manifestation as a signal in lake Chl-a or turbidity values depends to a large part on lake typology and catchment characteristics. Assessment of lake water quality changes six months after a fire showed that Chl-a concentrations either increased, decreased, or showed no changes in a similar number of lakes, indicating that a lake specific ecological and hydro-morphological context is important for understanding lake responses to wildfires.
Multi-Scale Cross-Attention Fusion Network Based on Image Super-Resolution
Authors: Ma Yimin , Xu Yi , Liu Yunqing , Yan Fei , Zhang Qiong , Li Qi , Liu Quanyang
Published: March 2024

In recent years, deep convolutional neural networks with multi-scale features have been widely used in image super-resolution reconstruction (ISR), and the quality of the generated images has been significantly improved compared with traditional methods. However, in current image super-resolution network algorithms, these methods need to be further explored in terms of the effective fusion of multi-scale features and cross-domain application of attention mechanisms. To address these issues, we propose a novel multi-scale cross-attention fusion network (MCFN), which optimizes the feature extraction and fusion process in structural design and modular innovation. In order to make better use of the attention mechanism, we propose a Pyramid Multi-scale Module (PMM) to extract multi-scale information by cascading. This PMM is introduced in MCFN and is mainly constructed by multiple multi-scale cross-attention modules (MTMs). To fuse the feature information of PMMs efficiently in both channel and spatial dimensions, we propose the cross-attention fusion module (CFM). In addition, an improved integrated attention enhancement module (IAEM) is inserted at the network’s end to enhance the correlation of high-frequency feature information between layers. Experimental results show that the algorithm significantly improves the reconstructed images’ edge information and texture details, and the benchmark dataset’s performance evaluation shows comparable performance to current state-of-the-art techniques.
Exploring EEG Emotion Recognition through Complex Networks: Insights from the Visibility Graph of Ordinal Patterns
Authors: Yao Longxin , Lu Yun , Wang Mingjiang , Qian Yukun , Li Heng
Published: March 2024

The construction of complex networks from electroencephalography (EEG) proves to be an effective method for representing emotion patterns in affection computing as it offers rich spatiotemporal EEG features associated with brain emotions. In this paper, we propose a novel method for constructing complex networks from EEG signals for emotion recognition, which begins with phase space reconstruction to obtain ordinal patterns and subsequently forms a graph network representation from the sequence of ordinal patterns based on the visibility graph method, named ComNet-PSR-VG. For the proposed ComNet-PSR-VG, the initial step involves mapping EEG signals into a series of ordinal partitions using phase space reconstruction, generating a sequence of ordinal patterns. These ordinal patterns are then quantified to form a symbolized new sequence. Subsequently, the resulting symbolized sequence of ordinal patterns is transformed into a graph network using the visibility graph method. Two types of network node measures, average node degree (AND) and node degree entropy (NDE), are extracted from the graph networks as the inputs of machine learning for EEG emotion recognition. To evaluate the effectiveness of the proposed construction method of complex networks based on the visibility graph of ordinal patterns, comparative experiments are conducted using two types of simulated signals (random and Lorenz signals). Subsequently, EEG emotion recognition is performed on the SEED EEG emotion dataset. The experimental results show that, with AND as the feature, our proposed method is 4.88% higher than the existing visibility graph method and 12.23% higher than the phase space reconstruction method. These findings indicate that our proposed novel method for constructing complex networks from EEG signals not only achieves effective emotional EEG pattern recognition but also exhibits the potential for extension to other EEG pattern learning tasks, suggesting broad adaptability and application potential for our method.
Remote Sensing Image Segmentation for Aircraft Recognition Using U-Net as Deep Learning Architecture
Authors: Shaar Fadi , Yılmaz Arif , Topcu Ahmet Ercan , Alzoubi Yehia Ibrahim
Published: March 2024

Recognizing aircraft automatically by using satellite images has different applications in both the civil and military sectors. However, due to the complexity and variety of the foreground and background of the analyzed images, it remains challenging to obtain a suitable representation of aircraft for identification. Many studies and solutions have been presented in the literature, but only a few studies have suggested handling the issue using semantic image segmentation techniques due to the lack of publicly labeled datasets. With the advancement of CNNs, researchers have presented some CNN architectures, such as U-Net, which has the ability to obtain very good performance using a small training dataset. The U-Net architecture has received much attention for segmenting 2D and 3D biomedical images and has been recognized to be highly successful for pixel-wise satellite image classification. In this paper, we propose a binary image segmentation model to recognize aircraft by exploiting and adopting the U-Net architecture for remote sensing satellite images. The proposed model does not require a significant amount of labeled data and alleviates the need for manual aircraft feature extraction. The public dense labeling remote sensing dataset is used to perform the experiments and measure the robustness and performance of the proposed model. The mean IoU and pixel accuracy are adopted as metrics to assess the obtained results. The results in the testing dataset indicate that the proposed model can achieve a 95.08% mean IoU and a pixel accuracy of 98.24%.
The eDNA-Container App: A Simple-to-Use Cross-Platform Package for the Reproducible Analysis of eDNA Sequencing Data
Authors: Wheeler David , Brancalion Lillian , Kawasaki Akitomo , Rourke Meaghan L.
Published: March 2024

The analysis of environmental DNA (eDNA) is a powerful and non-invasive method for monitoring the presence of species in ecosystems. However, ecologists and laboratory staff can find it challenging to use eDNA analysis software effectively due to the unfamiliar command-line interfaces used by many of these packages. Therefore, we developed the eDNA-container app, a free and open-source software package that provides a simple user-friendly interface for eDNA analysis. The application is based on the popular QIIME2 library and is distributed as a Docker image. The use of Docker makes it compatible with a wide range of operating systems and facilitates the reproducible analysis of data across different laboratories. The application includes a point-and-click user interface for selecting sequencing files, configuring parameters, and accessing the results. Key pipeline outputs, such as sequence quality plots, denoising, and ASV generation statistics, are automatically included in a PDF report. This open-source and freely available analysis package should be a valuable tool for scientists using eDNA in biodiversity and biosecurity applications.
EWS Time Delay in Low Energy e−C60 Elastic Scattering
Authors: R. Aiswarya , Shaik Rasheed , Jose Jobin , Varma Hari R. , Chakraborty Himadri S.
Published: March 2024

Access to time delay in a projectile-target scattering is a fundamental tool in understanding their interactions by probing the temporal domain. The present study focuses on computing and analyzing the Eisenbud-Wigner-Smith (EWS) time delay in low energy elastic e−C60 scattering. The investigation is carried out in the framework of a non-relativistic partial wave analysis (PWA) technique. The projectile-target interaction is described in (i) Density Functional Theory (DFT) and (ii) Annular Square Well (ASW) static model, and their final results are compared in details. The impact of polarization on resonant and non-resonant time delay is also investigated.
Advances in the Development of Biofertilizers and Biostimulants from Microalgae
Authors: Miranda Alejandra M. , Hernandez-Tenorio Fabian , Villalta Fabian , Vargas Gabriel J. , Sáez Alex A.
Published: March 2024

Microalgae have commercial potential in different sectors of the industry. Specifically in modern agriculture, they can be used because they have the ability to supply nutrients to the soil and produce plant growth hormones, polysaccharides, antimicrobial compounds, and other metabolites that improve agricultural productivity. Therefore, products formulated from microalgae as biofertilizers and biostimulants turn out to be beneficial for agriculture and are positioned as a novel and environmentally friendly strategy. However, these bioproducts present challenges in preparation that affect their shelf life due to the rapid degradation of bioformulated products. Therefore, this work aimed to provide a comprehensive review of biofertilizers and biostimulants from microalgae, for which a bibliometric analysis was carried out to establish trends using scientometric indicators, technological advances were identified in terms of formulation methods, and the global market for these bioproducts was analyzed.
Developing Bioactive Hydrogels with Peptides for Dental Application
Authors: Muntean Alexandrina , Sarosi Codruta , Petean Ioan , Cuc Stanca , Carpa Rahela , Chis Ioana Andreea , Ilea Aranka , Delean Ada Gabriela , Moldovan Marioara
Published: March 2024

Dental caries is an avoidable and complex condition impacting billions of individuals worldwide, posing a specific concern among younger generations, despite the progress of oral hygiene products. This deterioration occurs due to the acid demineralization of tooth enamel, leading to the loss of minerals from the enamel subsurface. The remineralisation of early enamel carious lesions could prevent the cavitation of teeth. The enamel protein amelogenin constitutes 90% of the total enamel matrix protein and plays a key role in the bio mineralisation process. The aim of this study is to investigate the self-assembly microstructure and reticulation behaviour of a newly developed bioactive hydrogel with leucine-rich amelogenin peptide (LRAP) intended for enamel remineralisation. SEM, AFM, UV-VIS, and FTIR analyses emphasize the ability of peptides to promote cell adhesion and the treatment of early carious lesions. In conclusion, short-chain peptides can be used in hydrogels for individual or professional use.
Repurposing of the Cardiovascular Drug Statin for the Treatment of Cancers: Efficacy of Statin–Dipyridamole Combination Treatment in Melanoma Cell Lines
Authors: Irie Nanami , Mizoguchi Kana , Warita Tomoko , Nakano Mirai , Sasaki Kasuga , Tashiro Jiro , Osaki Tomohiro , Ishikawa Takuro , Oltvai Zoltán N. , Warita Katsuhiko
Published: March 2024

Metastatic melanoma has a very poor prognosis. Statins, 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR) inhibitors, are cholesterol-lowering agents with a potential for cancer treatment. The inhibition of HMGCR by statins, however, induces feedback, which paradoxically upregulates HMGCR expression via sterol regulatory element-binding protein-2 (SREBP2). Dipyridamole, an antiplatelet agent, is known to inhibit SREBP2 upregulation. We aimed to demonstrate the efficacy of statin–dipyridamole combination treatment in both human and spontaneously occurring canine melanoma cell lines. The half maximal inhibitory concentration (IC50) of atorvastatin showed a 68–92% reduction when combined with dipyridamole, compared with that of atorvastatin alone. In some melanoma cell lines, cell proliferation was suppressed to almost zero by the combination treatment (≥3 μM atorvastatin). Finally, the BRAF inhibitor, vemurafenib, further potentiated the effects of the combined statin–dipyridamole treatment in BRAF V600E mutation-bearing human melanoma cell lines. In conclusion, the inexpensive and frequently prescribed statin–dipyridamole combination therapy may lead to new developments in the treatment of melanoma and may potentiate the effects of vemurafenib for the targeted therapy of BRAF V600E-mutation bearing melanoma patients. The concordance between the data from canine and human melanoma cell lines reinforces this possibility.
Development of Cell Technologies Based on Dendritic Cells for Immunotherapy of Oncological Diseases
Authors: Kurilin Vasily , Alshevskaya Alina , Sennikov Sergey
Published: March 2024

Immunotherapy using dendritic cell-based vaccination is a natural approach using the capabilities and functions inherent in the patient’s immune system to eliminate tumor cells. The development of dendritic cell-based cell technologies evolved as the disorders of dendritic cell differentiation and function in cancer were studied; some of these functions are antigen presentation, priming of cytotoxic T-lymphocytes and induction of antigen-specific immune responses. At the initial stage of technology development, it was necessary to develop protocols for the in vitro generation of functionally mature dendritic cells that were capable of capturing tumor antigens and processing and presenting them in complex with MHC to T-lymphocytes. To achieve this, various forms of tumor-associated antigen delivery systems were tested, including lysates, tumor cell proteins (peptides), and DNA and RNA constructs, and it was shown that the use of DNA and RNA constructs was the most effective method, as it made it possible not only to deliver the most immunogenic epitopes of tumor-associated antigens to dendritic cells, but also to enhance their ability to induce antigen-specific cytotoxic T-lymphocytes. Currently, cell therapy based on dendritic cells is a modern basis for antigen-specific immunotherapy of cancer due to the simplicity of creating DNA and RNA constructs encoding information about both target tumor antigens and regulatory molecules. The potential development of cell technologies based on dendritic cells aims to obtain antigen-specific cytotoxic T-lymphocytes induced by dendritic cells, study their functional activity and develop cell-based therapy.
Gut Microbiota Signatures with Potential Clinical Usefulness in Colorectal and Non-Small Cell Lung Cancers
Authors: Tesolato Sofía , Vicente-Valor Juan , Paz-Cabezas Mateo , Gómez-Garre Dulcenombre , Sánchez-González Silvia , Ortega-Hernández Adriana , de la Serna Sofía , Domínguez-Serrano Inmaculada , Dziakova Jana , Rivera Daniel , Jarabo Jose-Ramón , Gómez-Martínez Ana-María , Hernando Florentino , Torres Antonio , Iniesta Pilar
Published: March 2024

The application of bacterial metagenomic analysis as a biomarker for cancer detection is emerging. Our aim was to discover gut microbiota signatures with potential utility in the diagnosis of colorectal cancer (CRC) and non-small cell lung cancer (NSCLC). A prospective study was performed on a total of 77 fecal samples from CRC and NSCLC patients and controls. DNA from stool was analyzed for bacterial genomic sequencing using the Ion Torrent™ technology. Bioinformatic analysis was performed using the QIIME2 pipeline. We applied logistic regression to adjust for differences attributable to sex, age, and body mass index, and the diagnostic accuracy of our gut signatures was compared with other previously published results. The feces of patients affected by different tumor types, such as CRC and NSCLC, showed a differential intestinal microbiota profile. After adjusting for confounders, Parvimonas (OR = 53.3), Gemella (OR = 6.01), Eisenbergiella (OR = 5.35), Peptostreptococcus (OR = 9.42), Lactobacillus (OR = 6.72), Salmonella (OR = 5.44), and Fusobacterium (OR = 78.9) remained significantly associated with the risk of CRC. Two genera from the Ruminococcaceae family, DTU089 (OR = 20.1) and an uncharacterized genus (OR = 160.1), were associated with the risk of NSCLC. Our two panels had better diagnostic capacity for CRC (AUC = 0.840) and NSLC (AUC = 0.747) compared to the application of two other published panels to our population. Thus, we propose a gut bacteria panel for each cancer type and show its potential application in cancer diagnosis.
Stereo Camera Setup for 360° Digital Image Correlation to Reveal Smart Structures of Hakea Fruits
Authors: Fischer Matthias , Mylo Max D. , Lorenz Leon S. , Böckenholt Lars , Beismann Heike
Published: March 2024

About forty years after its first application, digital image correlation (DIC) has become an established method for measuring surface displacements and deformations of objects under stress. To date, DIC has been used in a variety of in vitro and in vivo studies to biomechanically characterise biological samples in order to reveal biomimetic principles. However, when surfaces of samples strongly deform or twist, they cannot be thoroughly traced. To overcome this challenge, different DIC setups have been developed to provide additional sensor perspectives and, thus, capture larger parts of an object’s surface. Herein, we discuss current solutions for this multi-perspective DIC, and we present our own approach to a 360° DIC system based on a single stereo-camera setup. Using this setup, we are able to characterise the desiccation-driven opening mechanism of two woody Hakea fruits over their entire surfaces. Both the breaking mechanism and the actuation of the two valves in predominantly dead plant material are models for smart materials. Based on these results, an evaluation of the setup for 360° DIC regarding its use in deducing biomimetic principles is given. Furthermore, we propose a way to improve and apply the method for future measurements.
Worry about the Future in the Climate Change Emergency: A Mediation Analysis of the Role of Eco-Anxiety and Emotion Regulation
Authors: Orrù Luisa , Taccini Federica , Mannarini Stefania
Published: March 2024

The climate change emergency is one of the most important challenges of our time, and its impact on mental health has been evident for years. It is very important for clinicians to delve deeper into these manifestations. There are a wide variety of constructs, symptoms, and scales to measure the impact of climate change on mental health. Eco-anxiety is one of the constructs that has specifically emerged, in association with worry, about the future. In mental health studies, it is important to explore the relationship between eco-anxiety and emotion regulation and how much this relationship leads to worry about the future in order to be able to offer clinical intervention recommendations. Indeed, the hypothesis of this study is that it is possible to develop worries about the future when symptoms of eco-anxiety and a poor ability to regulate emotions are present. Particularly, emotion dysregulation could increase eco-anxiety symptoms and generate worries about one’s own future. For this reason, we have chosen to explore the relationships between these three constructs with the use of a mediation analysis. For this research, 351 participants were recruited in Italy. The proposed mediation model highlighted the findings that emotion dysregulation was positively related with eco-anxiety and that eco-anxiety predicts worry about the future. An association between emotion dysregulation and worry about the future was present. Eco-anxiety appeared to be an important mediator between emotional dysregulation and worry about the future. Emotion regulation could play a pivotal role in addressing concerns about the future. These findings could pave the way for exploring new research avenues and potential clinical interventions.
The Relationship between Executive Functions and Body Weight: Sex as a Moderating Variable
Authors: Ilardi Ciro Rosario , Monda Antonietta , Iavarone Alessandro , Chieffi Sergio , Casillo Maria , Messina Antonietta , Villano Ines , Federico Giovanni , Alfano Vincenzo , Salvatore Marco , Sapuppo Walter , Monda Vincenzo , Monda Marcellino , Di Maio Girolamo , La Marra Marco
Published: March 2024

This study explores the interplay between executive functions and body weight, examining both the influence of biological factors, specifically sex, and methodological issues, such as the choice between Body Mass Index (BMI) and waist circumference (WC) as the primary anthropometric measure. A total of 386 participants (222 females, mean age = 45.98 years, SD = 17.70) were enrolled, from whom sociodemographic (sex, age, years of formal education) and anthropometric (BMI and WC) data were collected. Executive functions were evaluated using the Frontal Assessment Battery–15 (FAB15). The results showed the increased effectiveness of WC over BMI in examining the relationships between executive functions, sex differences, and body weight. In particular, this study revealed that there was a significant moderating effect of sex at comparable levels of executive functioning. Specifically, women with higher executive performance had lower WCs than their male counterparts, suggesting that executive function has a greater impact on WC in women than in men. Our findings highlight the importance of conducting more in-depth investigations of the complex relationship between cognitive deficits and weight gain, considering confounding variables of behavioral, psychobiological, and neurophysiological origin.