bluuebunny/crossref_metadata_2025 huggingface dataset:
Planar Delaunay Mesh Smoothing Method Based on Angle and a Deep Q-Network
Authors: Zhao Fu , Sun Guangjun
Published: August 2023

Mesh quality is critical to the accuracy and efficiency of finite element calculations, and mesh smoothing is an essential means of reducing the number of poor elements and improving mesh quality. The deep Q-network-based optimization algorithm for planar Delaunay mesh (unconstrained DQN) has attracted increasing attention due to its advantages in autonomous optimization. However, the unconstrained DQN model does not constrain the movement area of the central node during the training process, and element quality easily falls into a local optimum, resulting in a low generalization of the DQN model. In this paper, an updateable iterative inner polygon is proposed as a constraint to limit the central node’s movement and control the element’s angle. Next, the performance of different neural networks when training the same dataset is analyzed, and the appropriate neural network is selected. After that, the effectiveness and generalization of the method were analyzed. Finally, the results were compared with those obtained by existing methods. The results show that the proposed algorithm can improve the minimum angle of global elements and the shape of poor elements, and the trained DQN model has a high generalization.
Characterization and Degradation of Ancient Architectural Red Sandstone in a Natural Erosion Environment
Authors: Liu Dunwen , Ao Tao , Cao Kunpeng , Meng Xianqing
Published: August 2023

The properties and appearance of ancient architectural red sandstone will be damaged after being eroded by the natural environment for a long time. In order to investigate the weathering and erosion characteristics of the red sandstone structure of an existing ancient building, ultrasonic testing techniques, combined with scanning electron microscopy (SEM), X-ray diffraction (XRD) and X-ray computed tomography (X-CT), were used to analyze a building in Ganzhou. The variation in chemical substances contained in the red sandstone specimens according to phenology was analyzed by X-ray diffraction (XRD). The characteristic parameters of the CT grayscale images of the red sandstone were extracted and combined with the ultrasonic wave velocity values to comprehensively analyze the degradation characteristics of the red sandstone specimens, and a method to characterize the degradation degree of the red sandstone as a whole plane is proposed. We use the gray model (GM (1, 1)) to predict the surface degradation degree of red sandstone specimens, and gray relation analysis (GRA) to further analyze the correlation between the characteristic parameters of CT grayscale images of red sandstone and its degradation degree. The results show that in the natural erosion environment, dolomite and chlorite are generated on the exposed surface of the red sandstone, which can protect the internal sandstone to a certain extent. The degradation degree of the red sandstone specimens in the horizontal X and Y directions varies, and the proposed method of calculating the overall plane degradation degree of the red sandstone is feasible. The minimum average relative error of the surface degradation degree obtained from the gray prediction GM (1, 1) model is 1.4591%. There is a good correlation between the characteristic parameters of the red sandstone CT grayscale images and the degradation degree.
Lightweight Design and Evaluation of Square Reflector
Authors: Zhu Zhongyao , Tian Ailing , Liu Bingcai , Du Xin , Dong Suotao
Published: August 2023

In order to reduce the weight of optical elements in space remote sensors while increasing their stiffness, this paper takes an off-axis system secondary mirror as an example to design a square mirror with a size of 500 mm × 500 mm. The mirror adopts ultra-low expansion glass as the raw material. The paper proposed a lightweight form of gradual reinforcement and conducted the mirror assembly simulation analysis. The analysis results show that the weight of the lightweight mirror is 13.6 kg, and the surface density can reach 54.4 kg/m2. Under the circumstances of 1 g gravity and the temperature change of 15 °C~25 °C, the surface shape accuracy of the mirror assembly can reach 1/90λ (λ = 632.8 nm). Through the final testing, the first-order intrinsic frequency of the reflex mirror components is 167.8 Hz. The gap between the test results and the theoretical simulation results is less than 3%, which proves that the mirror assembly in the lightweight form of gradual reinforcement fully meets the index requirements and can provide a theoretical reference for the assembly of a mirror of similar size and type.
Bespoke Virtual Machine Orchestrator: An Approach for Constructing and Reconfiguring Bespoke Virtual Machine in Private Cloud Environment
Authors: Park Joonseok , Jeong Sumin , Yeom Keunhyuk
Published: August 2023

A cloud-computing company or user must create a virtual machine to build and operate a cloud environment. With the growth of cloud computing, it is necessary to build virtual machines that reflect the needs of both companies and users. In this study, we propose a bespoke virtual machine orchestrator (BVMO) as a method for constructing a virtual machine. The BVMO builds resource volumes as core assets to meet user requirements and builds virtual machines by reusing and combining these resource volumes. This can increase the reusability and flexibility of virtual-machine construction. A case study was conducted to build a virtual machine by applying the proposed BVMO to an actual OpenStack cloud platform, and it was confirmed that the construction time of the virtual machine was reduced compared with that of the existing method.
IoT-Based Big Data Secure Transmission and Management over Cloud System: A Healthcare Digital Twin Scenario
Authors: Stergiou Christos L. , Koidou Maria P. , Psannis Konstantinos E.
Published: August 2023

The Internet of Things (IoT) was introduced as a recently developed technology in the telecommunications field. It is a network made up of real-world objects, things, and gadgets that are enabled by sensors and software that can communicate data with one another. Systems for monitoring gather, exchange, and process video and image data captured by sensors and cameras across a network. Furthermore, the novel concept of Digital Twin offers new opportunities so that new proposed systems can work virtually, but without differing in operation from a “real” system. This paper is a meticulous survey of the IoT and monitoring systems to illustrate how their combination will improve certain types of the Monitoring systems of Healthcare–IoT in the Cloud. To achieve this goal, we discuss the characteristics of the IoT that improve the use of the types of monitoring systems over a Multimedia Transmission System in the Cloud. The paper also discusses some technical challenges of Multimedia in IoT, based on Healthcare data. Finally, it shows how the Mobile Cloud Computing (MCC) technology, settled as base technology, enhances the functionality of the IoT and has an impact on various types of monitoring technology, and also it proposes an algorithm approach to transmitting and processing video/image data through a Cloud-based Monitoring system. To gather pertinent data about the validity of our proposal in a more safe and useful way, we have implemented our proposal in a Digital Twin scenario of a Smart Healthcare system. The operation of the suggested scenario as a Digital Twin scenario offers a more sustainable and energy-efficient system and experimental findings ultimately demonstrate that the proposed system is more reliable and secure. Experimental results show the impact of our proposed model depicts the efficiency of the usage of a Cloud Management System operated over a Digital Twin scenario, using real-time large-scale data produced from the connected IoT system. Through these scenarios, we can observe that our proposal remains the best choice regardless of the time difference or energy load.
GCARe: Mitigating Subgroup Unfairness in Graph Condensation through Adversarial Regularization
Authors: Mao Runze , Fan Wenqi , Li Qing
Published: August 2023

Training Graph Neural Networks (GNNs) on large-scale graphs in the deep learning era can be expensive. While graph condensation has recently emerged as a promising approach through which to reduce training cost by compressing large graphs into smaller ones and for preserving most knowledge, its capability in treating different node subgroups fairly during compression remains unexplored. In this paper, we investigate current graph condensation techniques from a perspective of fairness, and show that they bear severe disparate impact toward node subgroups. Specifically, GNNs trained on condensed graphs become more biased than those trained on original graphs. Since the condensed graphs comprise synthetic nodes, which are absent of explicit group IDs, the current algorithms used to train fair GNNs fail in this case. To address this issue, we propose Graph Condensation with Adversarial Regularization (GCARe), which is a method that directly regularizes the condensation process to distill the knowledge of different subgroups fairly into resulting graphs. A comprehensive series of experiments substantiated that our method enhances the fairness in condensed graphs without compromising accuracy, thus yielding more equitable GNN models. Additionally, our discoveries underscore the significance of incorporating fairness considerations in data condensation, and offer invaluable guidance for future inquiries in this domain.
Fragility Analysis of Transmission Towers Subjected to Downburst Winds
Authors: Zhu Chao , Yang Qingshan , Wang Dahai , Huang Guoqing , Liang Shuguo
Published: August 2023

A downburst is a typical local highly intensive wind all over the world, which is attributed to be the main cause of wind damage to transmission lines in inland areas worldwide. The collapse accidents of transmission towers under the downburst still occur every year. Therefore, it is of great significance to assess the safety of the transmission towers under downbursts. The motivation of the present study is to propose a fragility assessment method for transmission towers under the action of a downburst considering the uncertainty of wind-resistance capacity and the stochastic wind load effect. First, the downburst wind field of the transmission tower with different wind attack angles and different radial distances is simulated according to the mixed stochastic model. Then, random material characteristic samples are generated by the Latin hypercube sampling technique and applied to establish uncertain finite element models for transmission towers. Next, the static nonlinear buckling analysis is carried out by numerical methods to determine the ultimate capacity under the downburst wind load. The parameter analysis of different wind attack angles and radial distances between the downburst and the tower is conducted to determine the most unfavorable location of the maximum response. The failure mode of the transmission tower and the probabilities of the initial failure main members are summarized. Finally, the fragility curves of the transmission tower under the downburst and the atmospheric boundary layer (ABL) wind are compared. The results show that the maximum response is located at R = 1.6D. Most of the initial buckling members are located close to the first section of the tower. The fragility curves of the tower under the downburst are more dangerous than the ABL wind with the attack angle increasing from 0° to 90°. Furthermore, considering the probability model of intensity and direction of the downburst and based on the previous fragility analysis, the collapse probability of the transmission tower caused by the downburst is obtained. By probability analysis of the parameters, including layout conditions, different directions, and different wind speeds, it is found that the most favorable arrangement is 157.5°, and the most unfavorable arrangement is 112.5°.
Grape By-Products in Sustainable Cosmetics: Nanoencapsulation and Market Trends
Authors: Castro Maria Leonor , Ferreira João Paulo , Pintado Manuela , Ramos Oscar L. , Borges Sandra , Baptista-Silva Sara
Published: August 2023

The largest human organ, the skin, serves a variety of essential functions including protection, preservation of water and electrolytes, regulation of body temperature, and fat storage. Its maintenance and preservation are supported by cosmetic products, whose functions include cleaning, protection, and modulation. The market for these products is predicted to increase from 100.13 billion USD in 2021 to 145.82 billion USD in 2028. Recently, it has been suggested that grape by-products (totalling 14.5 million tons per year just in Europe) has a great potential to be used in the creation of new cosmetic products. In this regard, this article aims to provide a comprehensive overview of the current state of knowledge regarding the bioactive compounds in grape pomace, the advantages of applying them to the skin, and the main cosmetic products already on the market incorporating these bioactives. Most of these compounds are derived from the Vitis vinifera L. species, and exhibit several biological properties, such as antioxidant, antimicrobial, anti-inflammatory, inhibition of skin degrading enzymes, protection from UVA damage, increased cell viability, and skin whitening effect. On the other hand, nanoencapsulation techniques can provide a significant improvement in the stability of grape-derived bioactive compounds, in particular of resveratrol, and this issue is also addressed in a critical manner in this review.
Macro–Meso Mechanical Behavior of Loose Sand under Multi-Directional Cyclic Simple Shear Tests
Authors: Dong Xing , Li Jiaping , Li Yao , Wang Zhe , Han Ruida
Published: August 2023

Loose sand samples under different complex shear paths and directions of consolidation shear stress were simulated using bi-directional simple shear DEM models. Liquefaction characteristics and corresponding meso-mechanisms were analyzed, and the following conclusions were drawn. Bi-directional cyclic shear stress accelerated the drop in vertical stress, especially in the first and last cycles. Compared to uni-directional cyclic simple shear tests, the contact force between particles decreased faster in bi-directional cyclic simple shear tests. With an increased θ, the skeleton of the sample became unstable, and more particles were in a floating state, making the sample easier to liquefy. The mechanical coordination number decreased rapidly at the beginning and the end of shearing, and was relatively stable in the middle; it was around 4.2 when samples were liquefied. The magnitude of the anisotropy tensor gradually increased during shearing. Under bi-directional shear paths, the sample’s skeleton structure was subjected to a greater disturbance during the initial shear stage, caused damage to the particle skeleton and faster liquefaction. With an increased θ, the amplitude and peak value of the anisotropy tensor increased.
Empirical Comparison of Higher-Order Mutation Testing and Data-Flow Testing of C# with the Aid of Genetic Algorithm
Authors: Abd-Elkawy Eman H. , Ahmed Rabie
Published: August 2023

Data-Flow and Higher-Order Mutation are white-box testing techniques. To our knowledge, no work has been proposed to compare data flow and Higher-Order Mutation. This paper compares all def-uses Data-Flow and second-order mutation criteria. The comparison will support the testing decision-making, especially when choosing a suitable criterion. This compassion investigates the subsumption relation between these two criteria and evaluates the effectiveness of test data developed for each. To compare the two criteria, a set of test data satisfying each criterion is generated using genetic algorithms; the set is then used to explore whether one criterion subsumes the other criterion and assess the effectiveness of the test set that was developed for one methodology in terms of the other. The results showed that the mean mutation coverage ratio of the all du-pairs adequate test cover is 80.9%, and the mean data flow coverage ratio of the second-order mutant adequate test cover is 98.7%. Consequently, second-order mutation “ProbSubsumes” the all du-pairs data flow. The failure detection efficiency of the mutation (98%) is significantly better than the failure detection efficiency of data flow (86%). Consequently, second-order mutation testing is “ProbBetter” than all du-pairs data flow testing. In contrast, the size of the test suite of second-order mutation is more significant than the size of the test suite of all du-pairs.
Marine-Originated Materials and Their Potential Use in Biomedicine
Authors: Lagopati Nefeli , Pippa Natassa , Gatou Maria-Anna , Papadopoulou-Fermeli Nefeli , Gorgoulis Vassilis G. , Gazouli Maria , Pavlatou Evangelia A.
Published: August 2023

Aquatic habitats cover almost 70% of the Earth, containing several species contributing to marine biodiversity. Marine and aquatic organisms are rich in chemical compounds that can be widely used in biomedicine (dentistry, pharmacy, cosmetology, etc.) as alternative raw biomaterials or in food supplements. Their structural characteristics make them promising candidates for tissue engineering approaches in regenerative medicine. Thus, seaweeds, marine sponges, arthropods, cnidaria, mollusks, and the biomaterials provided by them, such as alginate, vitamins, laminarin, collagen, chitin, chitosan, gelatin, hydroxyapatite, biosilica, etc., are going to be discussed focusing on the biomedical applications of these marine-originated biomaterials. The ultimate goal is to highlight the sustainability of the use of these biomaterials instead of conventional ones, mainly due to the antimicrobial, anti-inflammatory, anti-aging and anticancer effect.
YOLOv7 Optimization Model Based on Attention Mechanism Applied in Dense Scenes
Authors: Wang Jiabao , Wu Jun , Wu Junwei , Wang Jiangpeng , Wang Ji
Published: August 2023

With object detection technology, real-time detection of dense scenes has become an important application requirement in various industries, which is of great significance for improving production efficiency and ensuring public safety. However, the current mainstream target detection algorithms have problems such as insufficient accuracy or inability to achieve real-time detection when detecting dense scenes, and to address this problem this paper improves the YOLOv7 model using attention mechanisms that can enhance critical information. Based on the original YOLOv7 network model, part of the traditional convolutional layers are replaced with the standard convolution combined with the attention mechanism. After comparing the optimization results of three different attention mechanisms, CBAM, CA, and SimAM, the YOLOv7B-CBAM model is proposed, which effectively improves the accuracy of object detection in dense scenes. The results on VOC datasets show that the YOLOv7B-CBAM model has the highest accuracy, reaching 87.8%, 1.5% higher than that of the original model, and outperforms the original model as well as other models with improved attention mechanisms in the subsequent results of two other different dense scene practical application scenarios. This model can be applied to public safety detection, agricultural detection, and other fields, saving labor costs, improving public health, reducing the spread and loss of plant diseases, and realizing high-precision, real-time target detection.
Performance of Iterative Coded CDMA Receivers with APP Feedback: A Use of a Weighted Delay Filter
Authors: Altalbe Ali , Tahir Muhammad
Published: August 2023

The prohibitive computational complexity of optimal coded multiuser detection necessitates using suboptimal detectors in practical implementations. The filter is very computationally simple and is also demonstrated to provide faster convergence and superior bit error rate (BER) performance. Further investigation of the weighted delay filter concept produces a second filter—derived via the joint likelihood function. It is analytically demonstrated that extrinsic feedback systems will not benefit from weighted delay filtering. A system model is provided that introduces the notion of feedback ‘residue’, which is shown to be the key difference between a-posterior probability (APP) and extrinsic systems when determining the parallel interference cancellation (PIC) output statistics. It is analytically shown that the weighted delay filter derived via a maximum signal-to-noise ratio (SNR) approach is identical to a weighted delay filter derived via the joint likelihood function. It is analytically shown that when extrinsic feedback is used in a coded-code division multiple access (C-CDMA) system, no benefit will be realised by weighted delay filtering, as soft outputs from previous cycles are a merely scaled, noisy version of the most recent data. The notion of a ‘feedback residue’ for systems with APP feedback is introduced, and it is empirically shown that this residue term is a key consideration when determining the PIC output statistics. Using the ‘residual feedback’ model, it is shown that when APP feedback is utilised, data from previous cycles is not simply “a scaled, noisy version” of the current data. For this reason, benefits may be realised by APP feedback use. The simulation results shows that the residue may be trivial at small loads, the residue builds to the substantial value of nearly 0.4 at a reasonably modest load of K/N=15/10, and continues to grow as the load increases.
The Subsea Micro-Drilling Vehicle’s Dynamic Analysis during Landing
Authors: Huang Ruifan , Jin Yongping , Liu Deshun
Published: August 2023

Whether the subsea micro-drilling vehicle (SMDV) can perform its subsequent operations safely depends on the quality of the landing procedure. RecurDyn creates the SMDV dynamic model for this study. A model of the interaction between the SMDV and deep-sea sediment is built, and a simulation of the SMDV falling on the sea’s sediment substrate is developed. The water resistance is applied to the model by equivalent height replacement, and the in-situ soil data is measured with a triaxial undrained unconsolidated (UU) compression test and a load-sinkage experiment. When the landing surface is a flat sediment substrate, the release height is 5 m, the sinkage amount is 347 mm, and the center of mass’s impact acceleration is less than seven gravitational accelerations. Three states can occur when the vehicle lands on a sloped surface: stability, slip, and overturning. The risk of slipping and overturning is the least when the vehicle is landing on the ground in the forward direction, and the risk is equal when it lands on the ground in the backward and sideways directions. The ultimate overturning angle drops, and the final slip angle remains relatively constant as the vehicle’s release height increases. Our findings offer a theoretical foundation for the SMDV’s safe landing and the scientific formulation of rational release intervals.
Feature-Oriented CBCT Self-Calibration Parameter Estimator for Arbitrary Trajectories: FORCAST-EST
Authors: Tönnes Christian , Zöllner Frank G.
Published: August 2023

Background: For the reconstruction of Cone-Beam CT volumes, the exact position of each projection is needed; however, in some situations, this information is missing. Purpose: The development of a self-calibration algorithm for arbitrary CBCT trajectories that does not need initial positions. Methods: Projections are simulated in a spherical grid around the center of rotation. Through using feature detection and matching, an acquired projection is compared to each simulated image in this grid. The position with the most matched features was used as a starting point for a fine calibration with a state-of-the-art algorithm. Evaluation: This approach is compared with the calibration of nearly correct starting positions when using FORCASTER and CMA-ES minimization with a normalized gradient information (NGI) objective function. The comparison metrics were the normalized root mean squared error, structural similarity index, and the dice coefficient, which were evaluated on the segmentation of a metal object. Results: The parameter estimation for a regular Cone-Beam CT with a 496 projection took 1:26 h with the following metric values: NRMSE = 0.0669; SSIM = 0.992; NGI = 0.75; and Dice = 0.96. FORCASTER with parameter estimation took 3:28 h with the following metrics: NRMSE = 0.0190; SSIM = 0.999; NGI = 0.92; and Dice = 0.99. CMA-ES with parameter estimation took 5:39 h with the following metrics: NRMSE = 0.0037; SSIM = 1.0; NGI = 0.98; and Dice = 1.0. Conclusions: The proposed algorithm can determine the parameters of the projection orientations for arbitrary trajectories with enough accuracy to reconstruct a 3D volume with low errors.
Hyperspectral Image Dimensionality Reduction Algorithm Based on Spatial–Spectral Adaptive Multiple Manifolds
Authors: Xu Shufang , Geng Sijie , Yang Qi , Gao Hongmin
Published: August 2023

Hyperspectral images contain rich spatial–spectral information and have high dimensions, which can lead to challenges related to feature extraction for classification tasks, resulting in suboptimal performance. We propose a hyperspectral image dimensionality reduction algorithm based on spatial–spectral adaptive multiple manifolds to address the problem of small differences between features of dissimilar samples in the subspace caused by the uniform projection transformation in traditional dimensionality reduction methods. Firstly, to address spatial boundary mismatch problems caused by re-characterizing a pixel using pixels in a fixed area around it as its near neighbors in traditional algorithms, an adaptive weight representation method based on super-pixel segmentation is proposed, which enhances the similarity of similar samples and the dissimilarity of dissimilar samples. Secondly, to address the problem that a single manifold cannot completely characterize the near neighbor between samples of different categories, an adaptive multi-manifold representation method is proposed. The feature representation of the entire hyperspectral data in the low-dimensional subspace is obtained by adaptively fusing the intra- and inter-manifold maps constructed for each category of samples in the spatial and spectral dimensions. Experimental results on two public datasets show that the proposed method achieves better results when performing the hyperspectral image dimensionality reduction task.
The Compressive Strength and Microstructure of Alkali-Activated Mortars Utilizing By-Product-Based Binary-Blended Precursors
Authors: Elbasir Otman M. M. , Johari Megat Azmi Megat , Ahmad Zainal Arifin , Mashaan Nuha S. , Milad Abdalrhman
Published: August 2023

Researchers have investigated the feasibility of using ultrafine palm oil fuel ash (u-POFA) as a cement replacement material because of its potential to reduce the environmental impact of concrete production. u-POFA, a by-product of palm oil fuel combustion, is a suitable replacement for Portland cement in concrete mixes because of its sustainability and cost-effectiveness. This study investigated the microstructural and compressive strengths of alkali-activated mortars (AAMs) based on fly ash (FA) and granulated blast-furnace slag (GBFS) being added with varying percentages of u-POFA. The mixture samples were prepared in eighteen mortars using sodium metasilicate (Na2SiO3) as the source material and sodium hydroxide (NaOH) as the alkaline activator. This study used field-emission scanning electron microscopy coupled with energy-dispersive X-ray spectrometry, X-ray diffraction, X-ray fluorescence, and Fourier-transform infrared spectroscopy to characterize the binary-blended mortars after 28 days of curing and determined the strength of the FA+GBFS (87.80 MPa), u-POFA+GBFS (88.87 MPa), and u-POFA+FA mortars (54.82 MPa). The mortars’ compressive strength was influenced by the CaO/SiO2 and SiO2/Al2O3 ratios in the mixture, which was directly due to the formation rate of geopolymer products of the calcium–alumina–silicate–hydrate (C–(A)–S–H), aluminosilicate (N–A–S–H), and calcium–silicate–hydrate (C–S–H) phases. Based on the contents of FA and GBFS, u-POFA significantly enhanced concrete strength; therefore, u-POFA used in a suitable proportion could enhance binary-blended AAMs’ microstructure.
The Effect of Forest Growth Rate on Climate Change Impacts of Logging Residue Utilization
Authors: Gan Xiaofan , Guo Bingqian , Ma Zemeng , Fang Mingjie , Yan Yan , Liu Weiguo
Published: August 2023

Biofuel is encouraged because of its low impact on climate change. A new framework was developed to accurately assess the climate change impacts (CCI) of biofuel by integrating the atmospheric carbon cycle model and vegetation carbon dynamic models. Forests with different growth rates (fast, medium, slow) and three collection intensities (71%, 52%, 32%) of logging residues were presumed to test the performance of this framework. The CCI of biofuel was analyzed under two functional units: 1 GJ of biofuels and 1 ha of forests to supply biofuels. According to this study, increasing the forest growth rate could decrease the CCI in both functional units. Increasing the collection intensity could decrease the CCI of 1 GJ of biofuel but increase the CCI of 1 ha of forest land (unless the impacts were negative in fast-growth forests with high and medium collection intensities). Producing bioethanol resulted in a lower CCI (−3.1–67.7 kg CO2 eq/GJ) compared to bio-diesel (29.3–94.7 kg CO2 eq/GJ). Hence, collecting all available logging residues (without inhibiting forest regrowth) to produce low CCI biofuels such as bioethanol was found to be the optimal option for achieving high mitigation effects.
The Effects of Planetary Boundary Layer Features on Air Pollution Based on ERA5 Data in East China
Authors: Deng Xueliang , Chen Jian , Dai Rui , Zhai Zhenfang , He Dongyan , Zhao Liang , Jin Xiaolong , Zhang Jiping
Published: August 2023

The planetary boundary layer (PBL) structure and its evolution can significantly affect air pollution. Here, the PBL’s characteristics and their association with air pollution were analyzed in Hefei, east China, using ERA5 reanalysis data, weather observations and air pollutant measurements from 2016 to 2021. In the near-surface level, air pollution was directly influenced by ground meteorological conditions, and high PM2.5 was normally related to weak wind speed, northwest wind anomalies, low temperature and high relative humidity. Moreover, in the trajectory analysis, air masses from the north and the northwest with short length played an important role in the high PM2.5 with pollutant transport within the PBL. Furthermore, high PM2.5 showed a tight dependence on PBL stratification. There was high temperature and relative humidity and low wind speed and PBL height within all PBL altitudes in the polluted condition. Notably, vertical wind shear (VWS) and temperature gradient tended to be much weaker below 900 hPa, which created a deeply stable stratification that acted as a cap to upward-moving air. Such a PBL structure facilitated more stable stratification and enhanced the generation of air pollution. Finally, the stable stratification in the PBL was related to the special synoptic configuration for the high PM2.5 conditions, which included the block situation at the high level, the southerly wind anomalies at the middle level and the wild range of the uniform pressure field at the near-ground level. Therefore, air pollutant concentrations were regulated by ground factors, PBL structure and the synoptic situation. Our results provide a precise understanding of the role of PBL features in air pollution, which contributes to improving the assimilation method of the atmospheric chemistry model in east China.
Editorial for the Special Issue “Atmospheric Dispersion and Chemistry Models: Advances and Applications”
Authors: Viúdez-Moreiras Daniel
Published: August 2023

Atmospheric dispersion and chemical transport models (CTMs) are a key tool in both atmospheric chemistry and environmental sciences [...]
Dynamic Response of a Light-Modulated Magnetometer to Time-Dependent Fields
Authors: Bevilacqua Giuseppe , Biancalana Valerio , Dancheva Yordanka
Published: August 2023

The dynamic response of a Bell-and-Bloom magnetometer to a parallel (to the bias field) time-dependent field is studied by means of a model that goes beyond the commonly assumed quasi-static regime. The findings unveil features that are related to the parametric nature of the considered system. It is shown that for low-amplitude time-dependent fields, different operating conditions are possible and that, besides the commonly reported low-pass filter behavior, a band-pass response emerges. Moreover, we show that a larger amplitude of the time-dependent field makes the parametric nature of the system appear more clearly in the output signal. A harmonic analysis of the latter is numerically performed to highlight and characterize these emerging features.
Viability Analysis of Tidal Turbine Installation Using Fuzzy Logic: Case Study and Design Considerations
Authors: Rodríguez-Pérez Ángel M. , Rodríguez César A. , Márquez-Rodríguez Alba , Mancera Julio J. Caparros
Published: August 2023

Tidal energy represents a clean and sustainable source of energy generation that can address renewable energy challenges, especially the global challenge of optimizing alternatives for stable supply. Although tidal stream energy extraction technology is in the early stages of development, it shows great potential compared to other renewable energy sources. The main objective of this research is to provide a digital tool for the optimization of the installation of turbines through fuzzy logic. The methodology in this study includes the design and development of a fuzzy-logic-based tool for this purpose. Design criteria included parameters such as salinity, temperature, currents, depth, and water viscosity, which affect the performance of tidal turbines. These parameters are obtained from the geographic location of the installation. A decision-making system is provided to support the tool. The designed fuzzy logic system evaluates the suitability of different turbine locations and presents the results through graphics and probability of success percentages. The results indicate that currents and temperatures are the most limiting factors in terms of potential turbine locations. The program provides a practical and efficient tool for optimizing the selection of tidal turbines and generating energy from ocean currents. This tool is evaluated and validated through different cases. With this approach, the aim is to encourage the development of tidal energy and its adoption worldwide.
Moderate Deviation Principle for Linear Processes Generated by Dependent Sequences under Sub-Linear Expectation
Authors: Sun Peiyu , Wang Dehui , Ding Xue , Tan Xili , Zhang Yong
Published: August 2023

We are interested in the linear processes generated by dependent sequences under sub-linear expectation. Using the Beveridge–Nelson decomposition of linear processes and the inequalities, the moderate deviation principle for linear processes produced by an m-dependent sequence is established. We also prove the upper bound of the moderate deviation principle for linear processes produced by negatively dependent sequences via different methods from m-dependent sequences. These conclusions promote and improve the corresponding results from the traditional probability space to the sub-linear expectation space.
Bioremediation of Neonicotinoid Pesticide, Imidacloprid, Mediated by Bacillus cereus
Authors: Talpur Farah Naz , Unar Ahsanullah , Bhatti Sana Kanwal , Alsawalha Laila , Fouad Dalia , Bashir Humaira , Afridi Hassan Imran , Ataya Farid Shokry , Jefri Ohoud A. , Bashir Muhammad Sohail
Published: August 2023

Imidacloprid, a toxic pesticide of the chloronicotinyl category, is employed extensively in agricultural fields, and its exposure causes serious health issues. Biodegradation is considered to be a green and economical approach to remediate pesticides. Herein, imidacloprid degradation efficiency of Bacillus sp. is highlighted, among which Bacillus cereus exhibited the greatest degradation; optimization of experimental variables (pH, imidacloprid and agitation time) via Box–Behnken factorial design and analysis of variance (ANOVA) revealed 92% biodegradation at the initial substrate concentration of 0.03 mM, aerobically in 11 days under favorable pH 7. The subsequent metabolites, identified through liquid chromatography–mass spectrometry, were 5-hydroxy imidacloprid, imidacloprid-guanidine and 6-chloronicotinic acid.
NIR-II Nanoprobes: A Review of Components-Based Approaches to Next-Generation Bioimaging Probes
Authors: Dunn Bryce , Hanafi Marzieh , Hummel John , Cressman John , Veneziano Rémi , Chitnis Parag
Published: August 2023

Fluorescence and photoacoustic imaging techniques offer valuable insights into cell- and tissue-level processes. However, these optical imaging modalities are limited by scattering and absorption in tissue, resulting in the low-depth penetration of imaging. Contrast-enhanced imaging in the near-infrared window improves imaging penetration by taking advantage of reduced autofluorescence and scattering effects. Current contrast agents for fluorescence and photoacoustic imaging face several limitations from photostability and targeting specificity, highlighting the need for a novel imaging probe development. This review covers a broad range of near-infrared fluorescent and photoacoustic contrast agents, including organic dyes, polymers, and metallic nanostructures, focusing on their optical properties and applications in cellular and animal imaging. Similarly, we explore encapsulation and functionalization technologies toward building targeted, nanoscale imaging probes. Bioimaging applications such as angiography, tumor imaging, and the tracking of specific cell types are discussed. This review sheds light on recent advancements in fluorescent and photoacoustic nanoprobes in the near-infrared window. It serves as a valuable resource for researchers working in fields of biomedical imaging and nanotechnology, facilitating the development of innovative nanoprobes for improved diagnostic approaches in preclinical healthcare.
Emerging Applications of Chlorella sp. and Spirulina (Arthrospira) sp.
Authors: Abreu Ana P. , Martins Rodrigo , Nunes João
Published: August 2023

Chlorella sp. and Spirulina (Arthrospira) sp. account for over 90% of the global microalgal biomass production and represent one of the most promising aquiculture bioeconomy systems. These microorganisms have been widely recognized for their nutritional and therapeutic properties; therefore, a significant growth of their market is expected, especially in the nutraceutical, food, and beverage segments. However, recent advancements in biotechnology and environmental science have led to the emergence of new applications for these microorganisms. This paper aims to explore these innovative applications, while shedding light on their roles in sustainable development, health, and industry. From this state-of-the art review, it was possible to give an in-depth outlook on the environmental sustainability of Chlorella sp. and Spirulina (Arthrospira) sp. For instance, there have been a variety of studies reported on the use of these two microorganisms for wastewater treatment and biofuel production, contributing to climate change mitigation efforts. Moreover, in the health sector, the richness of these microalgae in photosynthetic pigments and bioactive compounds, along with their oxygen-releasing capacity, are being harnessed in the development of new drugs, wound-healing dressings, photosensitizers for photodynamic therapy, tissue engineering, and anticancer treatments. Furthermore, in the industrial sector, Chlorella sp. and Spirulina (Arthrospira) sp. are being used in the production of biopolymers, fuel cells, and photovoltaic technologies. These innovative applications might bring different outlets for microalgae valorization, enhancing their potential, since the microalgae sector presents issues such as the high production costs. Thus, further research is highly needed to fully explore their benefits and potential applications in various sectors.
Functional Cardiovascular Characterization of the Common Marmoset (Callithrix jacchus)
Authors: Klösener Lina , Samolovac Sabine , Barnekow Ina , König Jessica , Moussavi Amir , Boretius Susann , Fuchs Dieter , Haegens Astrid , Hinkel Rabea , Mietsch Matthias
Published: August 2023

Appropriate cardiovascular animal models are urgently needed to investigate genetic, molecular, and therapeutic approaches, yet the translation of results from the currently used species is difficult due to their genetic distance as well as their anatomical or physiological differences. Animal species that are closer to the human situation might help to bridge this translational gap. The common marmoset (Callithrix jacchus) is an interesting candidate to investigate certain heart diseases and cardiovascular comorbidities, yet a basic functional characterization of its hemodynamic system is still missing. Therefore, cardiac functional analyses were performed by utilizing the invasive intracardiac pressure–volume loops (PV loop) system in seven animals, magnetic resonance imaging (MRI) in six animals, and echocardiography in five young adult male common marmosets. For a direct comparison between the three methods, only data from animals for which all three datasets could be acquired were selected. All three modalities were suitable for characterizing cardiac function, though with some systemic variations. In addition, vena cava occlusions were performed to investigate the load-independent parameters collected with the PV loop system, which allowed for a deeper analysis of the cardiac function and for a more sensitive detection of the alterations in a disease state, such as heart failure or certain cardiovascular comorbidities.
Effects of Tropomodulin 2 on Dendritic Spine Reorganization and Dynamics
Authors: Kuruba Balaganesh , Starks Nickolas , Josten Mary Rose , Naveh Ori , Wayman Gary , Mikhaylova Marina , Kostyukova Alla S.
Published: August 2023

Dendritic spines are actin-rich protrusions that receive a signal from the axon at the synapse. Remodeling of cytoskeletal actin is tightly connected to dendritic spine morphology-mediated synaptic plasticity of the neuron. Remodeling of cytoskeletal actin is required for the formation, development, maturation, and reorganization of dendritic spines. Actin filaments are highly dynamic structures with slow-growing/pointed and fast-growing/barbed ends. Very few studies have been conducted on the role of pointed-end binding proteins in the regulation of dendritic spine morphology. In this study, we evaluated the role played by tropomodulin 2 (Tmod2)—a brain-specific isoform, on the dendritic spine re-organization. Tmod2 regulates actin nucleation and polymerization by binding to the pointed end via actin and tropomyosin (Tpm) binding sites. We studied the effects of Tmod2 overexpression in primary hippocampal neurons on spine morphology using confocal microscopy and image analysis. Tmod2 overexpression decreased the spine number and increased spine length. Destroying Tpm-binding ability increased the number of shaft synapses and thin spine motility. Eliminating the actin-binding abilities of Tmod2 increased the number of mushroom spines. Tpm-mediated pointed-end binding decreased F-actin depolymerization, which may positively affect spine stabilization; the nucleation ability of Tmod2 appeared to increase shaft synapses.
Graph-Based Analyses of Dynamic Water-Mediated Hydrogen-Bond Networks in Phosphatidylserine: Cholesterol Membranes
Authors: Jain Honey , Karathanou Konstantina , Bondar Ana-Nicoleta
Published: August 2023

Phosphatidylserine lipids are anionic molecules present in eukaryotic plasma membranes, where they have essential physiological roles. The altered distribution of phosphatidylserine in cells such as apoptotic cancer cells, which, unlike healthy cells, expose phosphatidylserine, is of direct interest for the development of biomarkers. We present here applications of a recently implemented Depth-First-Search graph algorithm to dissect the dynamics of transient water-mediated lipid clusters at the interface of a model bilayer composed of 1-palmytoyl-2-oleoyl-sn-glycero-2-phosphatidylserine (POPS) and cholesterol. Relative to a reference POPS bilayer without cholesterol, in the POPS:cholesterol bilayer there is a somewhat less frequent sampling of relatively complex and extended water-mediated hydrogen-bond networks of POPS headgroups. The analysis protocol used here is more generally applicable to other lipid:cholesterol bilayers.
Assessment of Oxidative Stress-Induced Oral Epithelial Toxicity
Authors: Mohammed Ali I. , Sangha Simran , Nguyen Huynh , Shin Dong Ha , Pan Michelle , Park Hayoung , McCullough Michael J. , Celentano Antonio , Cirillo Nicola
Published: August 2023

Reactive oxygen species (ROS) are highly reactive molecules generated in living organisms and an excessive production of ROS culminates in oxidative stress and cellular damage. Notably, oxidative stress plays a critical role in the pathogenesis of a number of oral mucosal diseases, including oral mucositis, which remains one of cancer treatments’ most common side effects. We have shown previously that oral keratinocytes are remarkably sensitive to oxidative stress, and this may hinder the development and reproducibility of epithelial cell-based models of oral disease. Here, we examined the oxidative stress signatures that parallel oral toxicity by reproducing the initial events taking place during cancer treatment-induced oral mucositis. We used three oral epithelial cell lines (an immortalized normal human oral keratinocyte cell line, OKF6, and malignant oral keratinocytes, H357 and H400), as well as a mouse model of mucositis. The cells were subjected to increasing oxidative stress by incubation with hydrogen peroxide (H2O2) at concentrations of 100 μM up to 1200 μM, for up to 24 h, and ROS production and real-time kinetics of oxidative stress were investigated using fluorescent dye-based probes. Cell viability was assessed using a trypan blue exclusion assay, a fluorescence-based live–dead assay, and a fluorometric cytotoxicity assay (FCA), while morphological changes were analyzed by means of a phase-contrast inverted microscope. Static and dynamic real-time detection of the redox changes in keratinocytes showed a time-dependent increase of ROS production during oxidative stress-induced epithelial injury. The survival rates of oral epithelial cells were significantly affected after exposure to oxidative stress in a dose- and cell line-dependent manner. Values of TC50 of 800 μM, 800 μM, and 400 μM were reported for H400 cells (54.21 ± 9.04, p < 0.01), H357 cells (53.48 ± 4.01, p < 0.01), and OKF6 cells (48.64 ± 3.09, p < 0.01), respectively. Oxidative stress markers (MPO and MDA) were also significantly increased in oral tissues in our dual mouse model of chemotherapy-induced mucositis. In summary, we characterized and validated an oxidative stress model in human oral keratinocytes and identified optimal experimental conditions for the study of oxidative stress-induced oral epithelial toxicity.