bluuebunny/crossref_metadata_2025 huggingface dataset:
Security Authentication Mechanism of Spatio-Temporal Big Data Based on Blockchain
Authors: Zhou Bao , Zhao Junsan , Chen Guoping , Yin Ying
Published: May 2023

Spatiotemporal big data are a kind of data that marks time information and geographic location and has been widely applied in various fields. However, there are always security issues with spatiotemporal big data, especially in data collection and authentication. Traditional authentication protocols are less efficient in the face of ultra-large-scale IoT (Internet of Things, IoT) device verification, and the threat of single-point failure is relatively large. Given these complications, a group authentication scheme is proposed in this paper with blockchain spatiotemporal big data. The decentralization of the blockchain is utilized to solve the single point of failure, and the single-point authentication is combined with the group authentication, the authentication efficiency is improved through the group authentication, and the illegal nodes are accurately identified using the single-point authentication. The simulation results demonstrate that using the MHT (Merkel Hash Tree, MHT) algorithm for group authentication can effectively improve the authentication efficiency of the entire system when the number of users exceeds 200. The time overhead is only 4 ms when the number of users is 16,000. It can have a large throughput (400–500 tps) and a low latency (1–2 s) at the same time when the block size is 1500 KB. This study not only verifies the legitimacy of each device and protects the security of spatiotemporal big data, but also significantly reinforces the authentication efficiency compared with similar schemes.
Driver Attention Detection Based on Improved YOLOv5
Authors: Wang Zhongzhou , Yao Keming , Guo Fuao
Published: May 2023

In response to negative impacts such as personal and property safety hazards caused by drivers being distracted while driving on the road, this article proposes a driver’s attention state-detection method based on the improved You Only Look Once version five (YOLOv5). Both fatigue and distracted behavior can cause a driver’s attention to be diverted during the driving process. Firstly, key facial points of the driver are located, and the aspect ratio of the eyes and mouth is calculated. Through the examination of relevant information and repeated experimental verification, threshold values for the aspect ratio of the eyes and mouth under fatigue conditions, corresponding to closed eyes and yawning, are established. By calculating the aspect ratio of the driver’s eyes and mouth, it is possible to accurately detect whether the driver is in a state of fatigue. Secondly, distracted abnormal behavior is detected using an improved YOLOv5 model. The backbone network feature extraction element is modified by adding specific modules to obtain different receptive fields through multiple convolution operations on the input feature map, thereby enhancing the feature extraction ability of the network. The introduction of Swin Transformer modules in the feature fusion network replaces the Bottleneck modules in the C3 module, reducing the computational complexity of the model while increasing its receptive field. Additionally, the network connection in the feature fusion element has been modified to enhance its ability to fuse information from feature maps of different sizes. Three datasets were created of distracting behaviors commonly observed during driving: smoking, drinking water, and using a mobile phone. These datasets were used to train and test the model. After testing, the mAP (mean average precision) has improved by 2.4% compared to the model before improvement. Finally, through comparison and ablation experiments, the feasibility of this method has been verified, which can effectively detect fatigue and distracted abnormal behavior.
Predicting Hospitalization, Organ Dysfunction, and Mortality in Post-Endoscopic Retrograde Cholangiopancreatography Acute Pancreatitis: Are SIRS and qSOFA Reliable Tools?
Authors: Balan Gheorghe Gh. , Timofte Oana , Gilca-Blanariu Georgiana-Emmanuela , Sfarti Catalin , Diaconescu Smaranda , Gimiga Nicoleta , Antighin Simona Petronela , Sandu Ion , Sandru Vasile , Trifan Anca , Moscalu Mihaela , Stefanescu Gabriela
Published: May 2023

Background: Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) has shown constant incidence throughout time, despite advances in endoscopic technology, devices, or personal skills of the operating endoscopists, with prevention and prediction of severity in PEP being constant concerns. Several prospective studies have investigated the role of systemic inflammatory response syndrome (SIRS) criteria or the quick Sequential Organ Failure Assessment (qSOFA) score in the PEP severity assessment. However, there are no clearly defined tools for the prediction of PEP severity. Methods: A total of 403 patients were prospectively monitored 60 days after ERCP for the detection of PEP development. Consequently, we evaluated the lengths of stay, incidence of organic dysfunction, and mortality rates of these patients. The predictive power of the univariate model was evaluated by using the receiver operating characteristic curve and analyzing the area under the curve (AUC). Results: Incidence of PEP was similar to that reported in the majority of trials. The 60-day survival rate of PEP patients reached 82.8%. A qSOFA score ≥ 1 is a very good predictor for organ dysfunction (AUC 0.993, p < 0.0001). SIRS can also be considered a significant predictor for organic dysfunctions in PEP patients (AUC 0.926, p < 0.0001). However, only qSOFA was found to significantly predict mortality in PEP patients (AUC 0.885, p = 0.003), with SIRS criteria showing a much lower predictive power. Neither SIRS nor qSOFA showed any predictive value for the length of stay of PEP patients. Conclusion: Our study offers novel information about severity prediction in PEP patients. Both SIRS criteria and qSOFA showed good predictive value for organic dysfunction, mortality, and hospitalization.
Plant Extracellular Vesicles: Investigating Their Utilization as Beneficial Nutrients in Diet
Authors: Di Giulio Simona , Carata Elisabetta , Mariano Stefania , Panzarini Elisa
Published: May 2023

Plant-derived extracellular vesicles (EVs) isolated from seeds, leaves, and fruits have shown a significant therapeutic potential for their anticancer, anti-inflammatory, and antioxidant properties. The ability to transport bioactive molecules and the low toxicity give EVs remarkable versatility in the field of nanomedicine for the development of drug delivery systems. Moreover, the physicochemical stability in gastric and intestinal fluids makes them the ideal candidate as nutritional carriers in oral formulations. It is well known that the consumption of antioxidant molecules from dietary plant sources, such as fruits and vegetables, can prevent pathologies caused by oxidative damage, including inflammatory and cardiovascular disease, neurodegeneration, aging, and cancer. EVs present in plant juices are receiving a lot of interest concerning their biological relevance in terms of their health benefits. EVs from food might be new components participating in body homeostasis, as they are in contact with the intestinal tract. This review aims to report and discuss the main biological properties and nutraceutical use of plant-derived EVs as promising therapeutic tools, with a focus on anti-oxidant effect and as a basis in developing new food-derived technology.
Magneto-Inertial Fusion and Powerful Plasma Installations (A Review)
Authors: Ryzhkov Sergei V.
Published: May 2023

A review of theoretical and experimental studies in the field of compression and heating of a plasma target in an external magnetic field, which has recently been called magneto-inertial fusion (MIF), has been carried out. MIF is a concept of magnetically driven inertial fusion that involves the magnetization of fuel, laser pre-heating, and magnetic implosion to create fusion conditions. An analysis of the current state of work on the implosion of magnetized targets and the effect of an external magnetic field on the main plasma parameters and system characteristics is presented. Questions regarding the numerical simulation of experiments on the magnetic-inertial confinement of plasma are touched upon. Particular attention is paid to two promising areas of MIF—with plasma jets and with a laser driver (laser beams).
A Hybrid Deep Learning Model as the Digital Twin of Ultra-Precision Diamond Cutting for In-Process Prediction of Cutting-Tool Wear
Authors: Wu Lei , Sha Kaijie , Tao Ye , Ju Bingfeng , Chen Yuanliu
Published: May 2023

Diamond cutting-tool wear has a direct impact on the processing accuracy of the machined surface in ultra-precision diamond cutting. It is difficult to monitor the tool’s condition because of the slight wear amount. This paper proposed a hybrid deep learning model for tool wear state prediction in ultra-precision diamond cutting. The cutting force was accurately estimated and the wear state of the diamond tool was predicted by using the hybrid deep learning model with the motion displacement, velocity, and other signals in the machining process. By carrying out machining experiments, this method can classify diamond-tool wear condition with an accuracy of more than 85%. Meanwhile, the effectiveness of the proposed method was verified by comparing it with a variety of machine learning models.
Preparation and Performance of a PU/PAN Lithium-Ion Battery Separator Based on a Centrifugal Spinning Method
Authors: Mei Shunqi , Liu Teng , Chen Long , Wang Yifan
Published: May 2023

The diaphragm is a key component of the lithium-ion battery and largely determines its performance. Currently, commercial diaphragms suffer from poor thermal stability, low porosity, and low liquid absorption rate. In this study, we prepared a polyurethane/polyacrylonitrile (PU/PAN) lithium-ion battery diaphragm using a centrifugal spinning method with PU as the main substrate and PAN as the additive. The results showed that the PU/PAN nanofiber diaphragm prepared by centrifugal spinning had a 3D porous structure, and when using 18% PU:PAN = 7:3, the porosity of the fiber diaphragm was 83.9%, the liquid absorption rate was 493%, and the ionic conductivity was 1.79 mS/cm. The battery system had good electrochemical performance and thermal stability, with an electrochemical stability window of 5.2 V. The diaphragm did not shrink when heated at 160 °C. In a lithium-ion battery system with lithium iron phosphate (LiFePO4) as the cathode material, the capacity remained at 147.1 mAh/g after 50 cycles at a 0.2 C rate, with a capacity retention rate of 95.8%. This indicated excellent cycle stability and a multiplicative performance with good application potential.
Study on Cl− Erosion of Concrete under the Combined Effect of Fatigue Load and Wet–Dry Cycles: A Review
Authors: Zhang Maohua , Li Zhiyi , Cui Jiyin , Xu Ronghua
Published: June 2023

The service environment of concrete in the marine environment is harsh, and demands regarding the durability of marine concrete have increased. Marine concrete in harbor and wharf areas suffers from the combined effect of fatigue load, dry–wet cycles, and Cl− erosion, which can result in spalling of the concrete surface, corrosion of the internal reinforcement, and even concrete damage. This paper reviews recent research results on the durability of concrete and reinforced concrete (RC) under the combined effect of fatigue load, dry–wet cycles, and Cl− erosion. We further assess the variation in Cl− transport properties with fatigue load, the causes behind the reduction in the carrying capacity of RC products under fatigue load, the methods of Cl− erosion on concrete under the pressures imposed by dry–wet cycles, and the damage of the protective layer of concrete due to accelerated Cl− erosion caused by the action of dry–wet cycles. Further studies are needed on the durability of concrete under the action of fatigue load, wet and dry cycles, and Cl− erosion, in addition to the testing of the durability of concrete under the combined effects of the afore-mentioned various factors.
Dynamic Analysis of a Delta Parallel Robot with Flexible Links and Joint Clearances
Authors: Cretescu Nadia , Neagoe Mircea , Saulescu Radu
Published: June 2023

Delta robot is a lightweight parallel manipulator capable of accurately moving heavy loads at high speed and acceleration along a spatial trajectory. This intensive dynamic process may have a significant impact on the end-effector trajectory precision and motor behavior. The paper highlights the influence on the dynamic behavior of a Delta robot by considering individual and combined effects of clearances and friction in the spherical joints, as well as the flexibility of the rod elements. The CAD modeling of the Delta robot and its motion simulation on a representative spatial trajectory where the maximum allowed values of speed and acceleration are reached were performed using the Catia and Adams software packages. The obtained results show that the methods used were successfully applied and the effects are mutually interconnected, but not cumulative.
Beneficiary Contracts on a Lightweight Blockchain Architecture Using Smart Contracts: A Smart Healthcare System for Medical Records
Authors: Mendoza Arvizo Arturo I. , Avelar Sosa Liliana , García Alcaraz Jorge Luis , Cruz-Mejía Oliverio
Published: June 2023

The effective management of medical records is essential in the ordinary and emergency operations of healthcare providers. This work uses blockchain to develop a smart contract algorithm for users of a medical record platform. This algorithm provides immutable execution and addresses authentication and reliability issues to control access to healthcare platforms. An executable distributed code is used to build the smart contract algorithm. In the proposed algorithm, management operations of the clinical history are carried out and integrated in an automated way in a distributed environment. Solidity is the programming language used to create the algorithm for a private and permissioned architecture with a proposed consensus algorithm requiring significantly less computational power using a 22% faster hash function.
Development of Chest X-ray Image Evaluation Software Using the Deep Learning Techniques
Authors: Usui Kousuke , Yoshimura Takaaki , Ichikawa Shota , Sugimori Hiroyuki
Published: June 2023

Although the widespread use of digital imaging has enabled real-time image display, images in chest X-ray examinations can be confirmed by the radiologist’s eyes. Considering the development of deep learning (DL) technology, its application will make it possible to immediately determine the need for a retake, which is expected to further improve examination throughput. In this study, we developed software for evaluating chest X-ray images to determine whether a repeat radiographic examination is necessary, based on the combined application of DL technologies, and evaluated its accuracy. The target population was 4809 chest images from a public database. Three classification models (CLMs) for lung field defects, obstacle shadows, and the location of obstacle shadows and a semantic segmentation model (SSM) for the lung field regions were developed using a fivefold cross validation. The CLM was evaluated using the overall accuracy in the confusion matrix, the SSM was evaluated using the mean intersection over union (mIoU), and the DL technology-combined software was evaluated using the total response time on this software (RT) per image for each model. The results of each CLM with respect to lung field defects, obstacle shadows, and obstacle shadow location were 89.8%, 91.7%, and 91.2%, respectively. The mIoU of the SSM was 0.920, and the software RT was 3.64 × 10−2 s. These results indicate that the software can immediately and accurately determine whether a chest image needs to be re-scanned.
PFAS: A Review of the State of the Art, from Legislation to Analytical Approaches and Toxicological Aspects for Assessing Contamination in Food and Environment and Related Risks
Authors: Schiavone Consolato , Portesi Chiara
Published: June 2023

More than 7000 synthetic compounds known as per- and poly-fluoroalkyl substances (PFAS) are applied to food packaging and other materials to provide fat, fire, and/or water resistance properties. These compounds have exceptional environmental stability and persistence due to the strong C-F chemical bond, earning them the moniker “forever chemicals”. Emission of PFAS from industrial waste leads to water, air, and soil contamination. Due to this ubiquitous nature, combined with the fact that PFAS in humans are known to have carcinogenic and reprotoxic effects and to cause vaccine resistance and depression of the immunity system, PFAS may constitute a major threat to human health. For this reason, the attention of the scientific community and of control bodies is increasing and as a consequence legislation and the scientific literature on PFAS are constantly evolving. This review aims to provide a comprehensive overview of the state of the art about current legislation addressing PFAS; targeted and screening method for identification, detection and quantification of PFAS; toxicity of PFAS; and contamination of environmental and food matrices and from food contact matrices. A comprehensive review of the latest scientific research and recent developments in the legislation of PFAS will provide insights into the current understanding of PFAS and its health implications. Moreover, it will serve as a valuable reference for further studies related to PFAS and could help in informing future policy decisions.
A Formation Mechanism of Spatial Distribution Pattern of Industrial Clusters under Flow Space
Authors: Shi Yan , Wu Yan , Chen Bingrong , Wang Da , Deng Min
Published: June 2023

This study focuses on analyzing the spatial distribution pattern and formation mechanisms of urban industrial clusters and aims to address the mismatch between industrial clusters and resource distribution. Firstly, the spatial distribution pattern of industrial clusters is analyzed using the kernel density estimation approach. Subsequently, a multi-layered model of interactive driving factors is constructed to analyze the functional types within the multi-layered network space. Lastly, a spatial weighted regression analysis model, considering the intensity of flow space, is developed to explore the intrinsic formation mechanisms of industrial agglomeration. The experimental results indicate the following: (1) There is a trend of industrial agglomeration in the Yangtze River Delta region, primarily concentrated in cities such as Shanghai, Nanjing, Hefei, Jinhua, and Taizhou. (2) The impact of spatial interaction factors on industrial agglomeration development is significant, and the analysis of interaction networks reflects the strength of interactive influencing factors to a certain extent. (3) The regression analysis model, which incorporates interactive information considering flow space intensity, better aligns with the study of the actual mechanisms behind industrial agglomeration in physical space.
Blockchained Trustable Federated Learning Utilizing Voting Accountability for Malicious Actor Mitigation
Authors: Stanley Brian , Lee Sang-Gon , Witanto Elizabeth Nathania
Published: June 2023

The federated learning (FL) approach in machine learning preserves user privacy during data collection. However, traditional FL schemes still rely on a centralized server, making them vulnerable to security risks, such as data breaches and tampering of models caused by malicious actors attempting to gain access by masquerading as trainers. To address these issues that hamper the trustability of federated learning, requirements were analyzed for several of these problems. The findings revealed that issues, such as the lack of accountability management, malicious actor mitigation, and model leakage, remained unaddressed in prior works. To fill this gap, a blockchain-based trustable FL scheme, MAM-FL, is proposed with the focus on providing accountability to trainers. MAM-FL established a group of voters responsible for evaluating and verifying the validity of the model updates submitted. The effectiveness of MAM-FL was tested based on the reduction of malicious actors present on both trainers’ and voters’ sides and the ability to handle colluding participants. Experiments show that MAM-FL succeeded at reducing the number of malicious actors, despite the test case involving initial collusion in the system.
Parameter Extraction of Solar Photovoltaic Model Based on Nutcracker Optimization Algorithm
Authors: Duan Zhenjiang , Yu Hui , Zhang Qi , Tian Li
Published: June 2023

In order to improve the accuracy and reliability of the photovoltaic (PV) model, this paper explores a novel nature-inspired metaheuristic algorithm, i.e., the nutcracker optimizer algorithm (NOA), for the parameter extraction of a PV model, such as a single diode model (SDM), double diode model (DDM), and triple diode model (TDM) of PV components. The Aleo Solar S79Y300 monocrystalline silicon solar panel was tested at 1000 W/m2 solar irradiance and 25 °C temperature, and the results of the proposed NOA algorithm were compared with three popular algorithms, i.e., particle swarm optimization (PSO), firework algorithm (FWA), and whale optimization algorithm (WOA), in terms of algorithm accuracy and running time, and non-parametric tests were performed. The results show that the NOA can improve the efficiency of PV parameter extraction, and its performance is the best among the tested algorithms. It has the best root mean square error (RMSE) values in the SDM, being 7.92587 × 10−5 and 6.02460 × 10−5 in the DDM and 6.23617 × 10−5 in the TDM, and the shortest average execution time according to the overall ranking, making it well suited for extracting PV model parameters.
Quick Overview of Face Swap Deep Fakes
Authors: Walczyna Tomasz , Piotrowski Zbigniew
Published: June 2023

Deep Fake technology has developed rapidly in its generation and detection in recent years. Researchers in both fields are outpacing each other in their axes achievements. The works use, among other methods, autoencoders, generative adversarial networks, or other algorithms to create fake content that is resistant to detection by algorithms or the human eye. Among the ever-increasing number of emerging works, a few can be singled out that, in their solutions and robustness of detection, contribute significantly to the field. Despite the advancement of emerging generative algorithms, the fields are still left for further research. This paper will briefly introduce the fundamentals of some the latest Face Swap Deep Fake algorithms.
Spatial Azimuthal Misalignment Characteristics of High-Temperature Superconducting Wireless Power Transmission Systems
Authors: Yan Zhichao , Zou Tanyuan , Chen Mingyue , Zhou Difan , Zhao Suchuan , Guo Yanqun , Cai Chuanbing
Published: June 2023

Magnetically coupled resonant wireless power transmission technology (WPT) based on high-temperature superconducting (HTS) coils has gained wide popularity due to its low impedance and high-quality factor Q value characteristics. This technology has greatly improved the energy transfer performance of wireless power transmission (WPT) systems. However, practical applications of conventional WPT, such as wireless charging of autonomous underwater vehicles at mooring points, often encounter spatial misalignment issues due to the complex ocean environment and ocean currents. Nonetheless, few studies have investigated the spatial misalignment of HTS WPT systems, particularly the angular misalignment. This paper presents a solution to address this problem by constructing magnetically coupled resonant wireless energy transmission systems based on HTS coils and copper coils. The study analyzes the relationship between the transmission efficiency of the WPT system and the received power of the load with respect to the spatial orientation of the coil. The performance of the superconducting coil and copper coil WPT systems is compared. The experimental results demonstrate that, under the same spatially misaligned conditions, the WPT system using HTS coils can significantly improve the transmission efficiency and load power compared to the conventional copper WPT system. Moreover, simultaneous adjustment of the lateral misalignment distance and different orientation deflection angles can improve the transmission efficiency and smooth load output power of the high-temperature superconducting WPT system.
Incidence of Chronic Pain following Oral Soft Tissue Biopsies: A Retrospective Study
Authors: Cohen Adir , Daod Rame , Czerninski Rakefet , Keshet Naama , Yanko Robert , Rettman Andra , Sharav Yair , Aframian Doron J. , Haviv Yaron
Published: June 2023

Soft tissue oral biopsies (STOB) are commonly performed in the medical field to obtain tissue samples for diagnostic purposes. However, like all invasive procedures, these biopsies may carry risks, such as the development of chronic long-lasting neuropathic pain. This study aims to examine the occurrence of chronic pain following STOBs. A retrospective study was conducted on the medical records of 695 patients who underwent STOBs at the Maxillofacial Surgery Department of Hadassah Medical Center between the years 2013 and 2022. Demographic information, details of the procedure, histopathological diagnosis, and data related to post-procedure pain in the biopsy area were collected and analyzed. Out of the 695 patients, only 4 reports of chronic pain with mild intensity lasting more than three months following oral biopsy were documented, with incidence rate of 0.57%; all were females with a median age of 59 ± 2.0 years. The biopsies were taken from various sites and the common diagnoses were lichen planus, venous malformation, and fibromas. In conclusion, chronic pain after oral soft-tissue biopsies is rare, generally mild, and typically does not require extra therapy. These insights can aid clinicians and patients in making informed decisions about these procedures.
A Multitask Cross-Lingual Summary Method Based on ABO Mechanism
Authors: Li Qing , Wan Weibing , Zhao Yuming
Published: June 2023

Recent cross-lingual summarization research has pursued the use of a unified end-to-end model which has demonstrated a certain level of improvement in performance and effectiveness, but this approach stitches together multiple tasks and makes the computation more complex. Less work has focused on alignment relationships across languages, which has led to persistent problems of summary misordering and loss of key information. For this reason, we first simplify the multitasking by converting the translation task into an equal proportion of cross-lingual summary tasks so that the model can perform only cross-lingual summary tasks when generating cross-lingual summaries. In addition, we splice monolingual and cross-lingual summary sequences as an input so that the model can fully learn the core content of the corpus. Then, we propose a reinforced regularization method based on the model to improve its robustness, and build a targeted ABO mechanism to enhance the semantic relationship alignment and key information retention of the cross-lingual summaries. Ablation experiments are conducted on three datasets of different orders of magnitude to demonstrate the effective enhancement of the model by the optimization approach; they outperform the mainstream approaches on the cross-lingual summarization task and the monolingual summarization task for the full dataset. Finally, we validate the model’s capabilities on a cross-lingual summary dataset of professional domains, and the results demonstrate its superior performance and ability to improve cross-lingual sequencing.
Injection Harmonic Current Differential Protection Based on Control-Protection Synergy for Distribution Networks with IBDGs
Authors: Yu Chengao , Gao Zhanjun , Liu Zhao , Tao Zhengchen
Published: June 2023

The high penetration of inverter-based distributed generations (IBDGs) leads to traditional distribution networks’ complex and variable fault characteristics. Traditional passive detection protection methods can hardly meet the stability and reliability requirements. To solve this problem, an injection harmonic current differential protection (IHCDP) scheme based on the idea of control-protection synergy is proposed in this paper. By analyzing the circuit structure, control strategy, low-voltage-ride-through characteristics of IBDGs, and short-circuit currents provided by IBDGs, an injection-control strategy of characteristic harmonic currents (CHCs) based on the d-axis and q-axis is proposed. According to the change of short-circuit currents provided by the IBDG, the amplitude of CHCs is adaptively corrected to strengthen the fault characteristics and ensure that the distribution network harmonic injection protocols are always satisfied. An IHCDP criterion based on the distortion rate of the negative-sequence component of CHCs is proposed by analyzing the fault characteristics of the CHCs after injection. To effectively eliminate the dead-zone problem during symmetrical short-circuit faults, the proposed IHCDP utilizes the distortion rate of A-phase CHCs. The feasibility of the proposed protection scheme is demonstrated by the theoretical analysis and simulation results in this paper.
Review of Photogrammetric and Lidar Applications of UAV
Authors: Kovanič Ľudovít , Topitzer Branislav , Peťovský Patrik , Blišťan Peter , Gergeľová Marcela Bindzárová , Blišťanová Monika
Published: June 2023

Using Unmanned Aerial Vehicles (UAVs) combined with various sensors brings the benefits associated with fast, automatic, and contactless spatial data collection with high resolution and accuracy. The most frequent application is the possibility of effectively creating spatial models based on photogrammetric and lidar data. This review analyzes the current possibilities of UAVs. It provides an overview of the current state of the art and research on selected parameters regarding their history and development, classification, regulation, and application in surveying with creating spatial models. Classification and regulation are based on national sources. The importance and usability of this review are also carried out by analyzing the UAV application with selected photogrammetric and lidar sensors. The study explores and discusses results achieved by many authors in recent years, synthesizing essential facts. By analyzing the network of co-occurring High-Frequency Words, in addition, we visualized the importance of the primary keyword UAV in the context of other keywords in the literary sources processed.
Numerical Investigation on the Interaction between a U-Shaped Pile Supporting Structure and an Adjacent Gravity Retaining Wall in River Dredging
Authors: Yan Jiaqi , Qin Zipeng , Jiang Ning , Zhou Linzhen , Chen Zengran , Niu Yaqiang , Zhang Yu
Published: June 2023

There is significant interaction between the new supporting structure and the existing adjacent retaining wall in the dredging and excavation project of urban rivers. In addition, the three factors, the spatial location, the stiffness of the structures, and the soil conditions of the two sides of the interaction will exert effects on the bearing properties of the two structures. Combined with an actual dredging project, FLAC3D software was applied to analyze the influencing rule of U-shaped concrete sheet pile (USCSP) section size, pile length, retaining wall height, and pile–wall spacing on the supporting structure and the bearing properties of the existing gravity retaining wall during dredging excavation. The results are that when the length of the sheet pile increases, the horizontal displacement of the pile gradually decreases, the horizontal displacement of the existing retaining wall declines, and the earth pressure at the wall’s back rises. With the increase in the section size of the sheet pile, its bending resistance enhances gradually, and the horizontal displacement of the existing retaining wall reduces, while the earth pressure slightly increases. When the pile–wall spacing grows, the interaction between the supporting structure and the retaining wall is gradually weakened under the process of excavation, the horizontal displacements of the sheet pile and the retaining wall decrease continuously, and the earth pressure at the retaining wall’s bottom continues to strengthen. Moreover, with the retaining wall growing, the passive resistance from the soil in front of the wall is greater for keeping the stability of the retaining wall, and the horizontal displacement and the stress of the sheet pile increase significantly after excavation. The above results indicate that the characteristics of the pile–wall interaction should be deeply considered in designing and constructing such projects in order to determine the overall stability of the retaining pile and the existing retaining wall. In this study, FLAC3D software was used to analyze the influence of various factors on the structure in order to provide reference for ensuring the safety of the whole structure.
Summary Study on Temperature Calculation Method for Water Accumulation in Permafrost Regions
Authors: Hu Xiaoying , Peng Erxing , Sheng Yu , Chen Ji , Zhao Xiangbin , Yang Qifan
Published: June 2023

With permafrost degeneration caused by climate change, water accumulation has increased in permafrost regions during recent decades. Water accumulation will deteriorate the existing status of engineering in cold regions. Water accumulation can have a thermal effect on permafrost during its formation, even resulting in failure of the subgrade. Moreover, the thermal effect is related to water temperature. However, temperature variation of water accumulation is complex, and its influencing factors include air temperature, environment, scope of water accumulation and so on. In order to conduct analysis of the damage mechanism of water accumulation on permafrost, it is necessary to explore the internal temperature change of water accumulation. This paper proposes a review of temperature calculation method for water accumulation in cold environment. The thermal calculation method for the space between the air and the water boundary of water accumulation is summarized. Water temperature change of water accumulation of various types is analyzed. The thermal calculation considering phase transformation in water accumulation is discussed, and heat transfer from the bottom of the water accumulation to the underlying soil is further studied. Finally, the key factors that are advantageous for conducting research about the thermal effect of water accumulation in permafrost are proposed to optimize the calculation method.
Minimality Conditions Equivalent to the Finitude of Fermat and Mersenne Primes
Authors: Shlossberg Menachem
Published: May 2023

The question is still open as to whether there exist infinitely many Fermat primes or infinitely many composite Fermat numbers. The same question concerning Mersenne numbers is also unanswered. Extending some recent results of Megrelishvili and the author, we characterize the Fermat primes and the Mersenne primes in terms of the topological minimality of some matrix groups. This is achieved by showing, among other things, that if F is a subfield of a local field of characteristic ≠2, then the special upper triangular group ST+(n,F) is minimal precisely when the special linear group SL(n,F) is. We provide criteria for the minimality (and total minimality) of SL(n,F) and ST+(n,F), where F is a subfield of C. Let Fπ and Fc be the set of Fermat primes and the set of composite Fermat numbers, respectively. As our main result, we prove that the following conditions are equivalent for A∈{Fπ,Fc}: A is finite; ∏Fn∈ASL(Fn−1,Q(i)) is minimal, where Q(i) is the Gaussian rational field; and ∏Fn∈AST+(Fn−1,Q(i)) is minimal. Similarly, denote by Mπ and Mc the set of Mersenne primes and the set of composite Mersenne numbers, respectively, and let B∈{Mπ,Mc}. Then the following conditions are equivalent: B is finite; ∏Mp∈BSL(Mp+1,Q(i)) is minimal; and ∏Mp∈BST+(Mp+1,Q(i)) is minimal.
Intelligent Task Planning System Based on Methods of Fuzzy Natural Logic
Authors: Walek Bogdan , Novák Vilém
Published: June 2023

In this paper, we present a novel approach to task planning based on an intelligent expert system that makes it possible to obtain a conclusion based on linguistically characterized knowledge. The main goal of the proposed task planning system is to arrange and display tasks for the solver in an effective way. Therefore, the system shows the most important tasks first and then the less important ones (in a determined ordering). The solver has a list of tasks arranged according to their importance at each time the task list is displayed. Another goal of the system is to show the effectiveness of all subordinate workers (solvers) for the manager. The expert knowledge contained in the system is characterized by three linguistic descriptions: determination of the task importance, determination of the final task importance, and determination of the efficiency of the task solvers. The system shows the ordered task list in real time. Evaluation of the relative and final importance of the tasks is performed periodically. The system has been implemented as a WEB application and verified on real data set. We also present experimental results of our system.
Solution Method for Systems of Nonlinear Fractional Differential Equations Using Third Kind Chebyshev Wavelets
Authors: Polat Sadiye Nergis Tural , Dincel Arzu Turan
Published: June 2023

Chebyshev Wavelets of the third kind are proposed in this study to solve nonlinear systems of FDEs. The main goal of the method is to convert the nonlinear FDE into a nonlinear system of algebraic equations that can be easily solved using matrix methods. In order to achieve this, we first generate the operational matrices for the fractional integration using third kind Chebyshev Wavelets and block-pulse functions (BPF) for function approximation. Since the obtained operational matrices are sparse, the obtained numerical method is fast and computationally efficient. The original nonlinear FDE is transformed into a system of algebraic equations in a vector-matrix form using the obtained operational matrices. The collocation points are then used to solve the system of algebraic equations. Numerical results for various examples and comparisons are presented.
Feasibility of Wave Intensity Analysis from 4D Cardiovascular Magnetic Resonance Imaging Data
Authors: Sophocleous Froso , Delchev Kiril , De Garate Estefania , Hamilton Mark C. K. , Caputo Massimo , Bucciarelli-Ducci Chiara , Biglino Giovanni
Published: May 2023

Congenital heart defects (CHD) introduce haemodynamic changes; e.g., bicuspid aortic valve (BAV) presents a turbulent helical flow, which activates aortic pathological processes. Flow quantification is crucial for diagnostics and to plan corrective strategies. Multiple imaging modalities exist, with phase contrast magnetic resonance imaging (PC-MRI) being the current gold standard; however, multiple predetermined site measurements may be required, while 4D MRI allows for measurements of area (A) and velocity (U) in all spatial dimensions, acquiring a single volume and enabling a retrospective analysis at multiple locations. We assessed the feasibility of gathering hemodynamic insight into aortic hemodynamics by means of wave intensity analysis (WIA) derived from 4D MRI. Data were collected in n = 12 BAV patients and n = 7 healthy controls. Following data acquisition, WIA was successfully derived at three planes (ascending, thoracic and descending aorta) in all cases. The values of wave speed were physiological and, while the small sample limited any clinical interpretation of the results, the study shows the possibility of studying wave travel and wave reflection based on 4D MRI. Below, we demonstrate for the first time the feasibility of deriving wave intensity analysis from 4D flow data and open the door to research applications in different cardiovascular scenarios.
Characterization of 3D-Bioprinted In Vitro Lung Cancer Models Using RNA-Sequencing Techniques
Authors: Zou Sheng , Ye Jiayue , Wei Yiping , Xu Jianjun
Published: June 2023

Objective: To construct an in vitro lung cancer model using 3D bioprinting and evaluate the feasibility of the model. Transcriptome sequencing was used to compare the differential genes and functions of 2D and 3D lung cancer cells. Methods: 1. A549 cells were mixed with sodium alginate/gelatine/fibrinogen as 3D-printed biological ink to construct a hydrogel scaffold for the in vitro model of lung cancer; 2. A hydrogel scaffold was printed using a extrusion 3D bioprinter; 3. The printed lung cancer model was evaluated in vitro; and 4. A549 cells cultured in 2D and 3D tumour models in vitro were collected, and RNA-seq conducted bioinformatics analysis. Results: 1. The in vitro lung cancer model printed using 3D-bioprinting technology was a porous microstructure model, suitable for the survival of A549 cells. Compared with the 2D cell-line model, the 3D model is closer to the fundamental human growth environment; 2. There was no significant difference in cell survival rate between the 2D and 3D groups; 3. In the cell proliferation rate measurement, it was found that the cells in the 2D group had a speedy growth rate in the first five days, but after five days, the growth rate slowed down. Cell proliferation showed a declining process after the ninth day of cell culture. However, cells in the 3D group showed a slow growth process at the beginning, and the growth rate reached a peak on the 12th day. Then, the growth rate showed a downward trend; and 4. RNA-seq compared A549 cells from 2D and 3D lung cancer models. A total of 3112 genes were differentially expressed, including 1189 up-regulated and 1923 down-regulated genes, with p-value ≤ 0.05 and |Log2Ratio| ≥ 1 as screening conditions. After functional enrichment analysis of differential genes, these differential genes affect the biological regulation of A549 cells, thus promoting lung cancer progression. Conclusion: This study uses 3D-bioprinting technology to construct a tumour model of lung cancer that can grow sustainably in vitro. Three-dimensional bioprinting may provide a new research platform for studying the lung cancer TME mechanism and anticancer drug screening.
Simultaneous Quantitative SARS-CoV-2 Antigen and Host Antibody Detection and Pre-Screening Strategy at the Point of Care
Authors: Srinivasan Rajsri Kritika , McRae Michael P. , Christodoulides Nicolaos J. , Dapkins Isaac , Simmons Glennon W. , Matz Hanover , Dooley Helen , Fenyö David , McDevitt John T.
Published: June 2023

As COVID-19 pandemic public health measures are easing globally, the emergence of new SARS-CoV-2 strains continue to present high risk for vulnerable populations. The antibody-mediated protection acquired from vaccination and/or infection is seen to wane over time and the immunocompromised populations can no longer expect benefit from monoclonal antibody prophylaxis. Hence, there is a need to monitor new variants and its effect on vaccine performance. In this context, surveillance of new SARS-CoV-2 infections and serology testing are gaining consensus for use as screening methods, especially for at-risk groups. Here, we described an improved COVID-19 screening strategy, comprising predictive algorithms and concurrent, rapid, accurate, and quantitative SARS-CoV-2 antigen and host antibody testing strategy, at point of care (POC). We conducted a retrospective analysis of 2553 pre- and asymptomatic patients who were tested for SARS-CoV-2 by RT-PCR. The pre-screening model had an AUC (CI) of 0.76 (0.73–0.78). Despite being the default method for screening, body temperature had lower AUC (0.52 [0.49–0.55]) compared to case incidence rate (0.65 [0.62–0.68]). POC assays for SARS-CoV-2 nucleocapsid protein (NP) and spike (S) receptor binding domain (RBD) IgG antibody showed promising preliminary results, demonstrating a convenient, rapid (<20 min), quantitative, and sensitive (ng/mL) antigen/antibody assay. This integrated pre-screening model and simultaneous antigen/antibody approach may significantly improve accuracy of COVID-19 infection and host immunity screening, helping address unmet needs for monitoring vaccine effectiveness and severe disease surveillance.
Genetic Diversity, Morphometric Characterization, and Conservation Reassessment of the Critically Endangered Freshwater Snail, Heleobia atacamensis, in the Atacama Saltpan, Northern Chile
Authors: Collado Gonzalo A. , Torres-Díaz Cristian , Vidal Marcela A. , Valladares Moisés A.
Published: May 2023

Evaporitic ecosystems of the Atacama Desert contain a rich endemic fauna, including mollusk species. A recent study performed in the freshwater snail Heleobia atacamensis, endemic to the Atacama Saltpan, revealed a strong interdependence of genetic patterns with climatic fluctuations and landscape physiography. The species is currently listed as Critically Endangered at regional scale and as Data Deficient on the International Union for Conservation of Nature (IUCN) Red List. Here, we studied genetic diversity and demographic history of several populations of the species occurring on a connectivity gradient, including snails from new peripherical localities (Peine and Tilomonte), which were compared with topotype specimens. In addition, we reassessed the conservation status using the IUCN Red List categories and criteria considering species-specific idiosyncrasy. Phylogenetic and phylogeographical analyses indicated that snails from Peine and Tilomonte belong to H. atacamensis. We discovered significant differentiation in shell morphology, which was generally greater in geographically isolated populations. We also inferred six genetic clusters and a demographic expansion congruent with the wet periods that occurred at the end of the Pleistocene. Considering the highest risk category obtained, H. atacamensis was reassessed as Endangered at regional scale. Future conservation plans should consider the genetic assemblages as conservation units.
Trace Element Imbalances in Acquired Hepatocerebral Degeneration and Changes after Liver Transplant
Authors: Nascimento Henrique , Malaquias Maria João , Pinto Catarina Mendes , Sá Silva José , Rochate Dina , Fraga Cristina , Alves José Eduardo , Ramos Cristina , Gandara Judit , Ferreira Sofia , Lopes Vítor , Cavaco Sara , Pessegueiro Miranda Helena , Almeida Agostinho , Magalhães Marina
Published: June 2023

Brain manganese (Mn) accumulation is a key feature in patients with acquired hepatocerebral degeneration (AHD). The role of trace elements other than Mn in AHD needs to be clarified. In this study, using inductively coupled plasma mass spectrometry, we aimed to evaluate blood levels of trace elements in patients with AHD before and after liver transplantation (LT). Trace element levels in the AHD group were also compared with those of healthy controls (blood donors, n = 51). Fifty-one AHD patients were included in the study (mean age: 59.2 ± 10.6 years; men: 72.5%). AHD patients had higher levels of Mn, Li, B, Ni, As, Sr, Mo, Cd, Sb, Tl and Pb and a higher Cu/Se ratio, and lower levels of Se and Rb. Six patients (two women; mean age 55 ± 8.7 years) underwent LT, and there was an improvement in neurological symptoms, a significant increase in the Zn, Se and Sr levels, and a decrease in the Cu/Zn and Cu/Se ratios. In summary, several trace element imbalances were identified in AHD patients. Liver transplantation resulted in the improvement of neurological manifestations and the oxidant/inflammatory status. It is possible that observed changes in trace element levels may play a role in the pathophysiology and symptomatology of AHD.