bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential Applications of Lilium Plants in Cosmetics: A Comprehensive Review Based on Research Papers and Patents
Authors: Tang Yuchao , Liu Yijie , Luo Kang , Xu Leifeng , Yang Panpan , Ming Jun
Published: July 2022

The application of cosmetics is indispensable in our current society. In recent years, with an increasing awareness of the long-term health benefits of naturally sourced ingredients, plant-based cosmetic products have gained increasing attention. Lilium belongs to the Liliaceae family, which is one of the main plant families used in cosmetics for skin care treatment. A large number of studies have shown that Lilium plants are rich in components such as phenolic acids, flavonoids, and polysaccharides, with high potential for cosmetic applications. However, the application of lilies in cosmetics has not been systematically reported. This knowledge gap can easily lead to the neglect of its application in cosmetics because lilies are most familiar as ornamental plants. Integrating academic papers and patent publications, we analyzed the potential cosmetic application ingredients in lily, as well as their applications in cosmetics and related efficacy. Patent analysis showed that applications for lily-related cosmetic patents are mainly concentrated in East Asia, including China, Korea, and Japan. The application of lilies involves all aspects of cosmetics, such as sunscreens, facial cleansers, facial masks, conditioners, and so on. Its functions are also rich and diverse, including antiaging, radiation protective, whitening, moisturizing, freckle removal, acne treatment, and hair regeneration promotion. In addition, lilies are compatible with the application of other herbs. Moreover, with a change in people’s consumption concepts and the consideration of long-term health benefits, lily-based food and medicine innovation with health care and beautification effects may be a promising direction.
BACH1 Expression Is Promoted by Tank Binding Kinase 1 (TBK1) in Pancreatic Cancer Cells to Increase Iron and Reduce the Expression of E-Cadherin
Authors: Liu Liang , Matsumoto Mitsuyo , Matsui-Watanabe Miki , Ochiai Kyoko , Callens Bert K. K. , Nguyen Long Chi , Kozuki Yushi , Tanaka Miho , Nishizawa Hironari , Igarashi Kazuhiko
Published: July 2022

BTB and CNC homology 1 (BACH1) represses the expression of genes involved in the metabolism of iron, heme and reactive oxygen species and promotes metastasis of various cancers including pancreatic ductal adenocarcinoma (PDAC). However, it is not clear how BACH1 is regulated in PDAC cells. Knockdown of Tank binding kinase 1 (TBK1) led to reductions of BACH1 mRNA and protein amounts in AsPC−1 human PDAC cells. Gene expression analysis of PDAC cells with knockdown of TBK1 or BACH1 suggested the involvement of TBK1 and BACH1 in the regulation of iron homeostasis. Ferritin mRNA and proteins were both increased upon BACH1 knockdown in AsPC−1 cells. Flow cytometry analysis showed that AsPC−1 cells with BACH1 knockout or knockdown contained lower labile iron than control cells, suggesting that BACH1 increased labile iron by repressing the expression of ferritin genes. We further found that the expression of E-cadherin was upregulated upon the chelation of intracellular iron content. These results suggest that the TBK1-BACH1 pathway promotes cancer cell metastasis by increasing labile iron within cells.
Anandamide Alters Barrier Integrity of Bovine Vascular Endothelial Cells during Endotoxin Challenge
Authors: Walker Carsten C. F. , Sordillo Lorraine M. , Contreras G. Andres
Published: July 2022

Vascular endothelial cells are crucial mediators of inflammation during infectious diseases, due to their ability to produce lipid-based inflammatory mediators and facilitate leukocyte migration and translocation to infected tissues. Mastitis is the costliest infectious disease in North America, with over two billion dollars in annual costs due to loss of milk production, medical treatment, and potential loss of the animal. Infections caused by coliform bacteria are particularly deleterious, causing a negative impact on cow well-being and a high mortality rate. Dysfunction and breakdown of the endothelial barrier is a key part of the pathology of coliform mastitis. The endocannabinoid system (ECS), shown to modulate inflammatory responses of vascular endothelial cells in humans and rodents, may be a novel target for inflammatory modulation in dairy cows. The endocannabinoid (EC) arachidonoylethanolamide (AEA) is a potent anti- or pro-inflammatory mediator in endothelial cells, depending on location, timing, and concentration. We hypothesized that elevated AEA during LPS challenge will impair endothelial barrier integrity via increased production of reactive oxygen species (ROS) and activation of apoptotic pathways. Challenge of bovine aortic endothelial cells (BAEC) with 25 ng/mL lipopolysaccharide (LPS) for 8 h induced AEA synthesis, increased expression of cannabinoid receptor 1 and 2 (CB1/2) and the AEA synthesizing enzyme N-acyl phosphatidylethanolamine phospholipase D (NAPE-PLD), while decreasing gene expression of the AEA degradation enzyme fatty acid amide hydrolase (FAAH). Trans endothelial resistance (TER), measured through electrical resistance across the monolayer, increased 2 h after 0.5 µM AEA treatment and decreased with 5 µM AEA, compared to LPS alone. Addition of AEA to BAEC challenged with LPS induced mitochondrial dysfunction via increased ROS production, cytochrome-C release, and activation of caspase 3/7. Antagonism of CB1 by 1 µM AM251 ameliorated AEA induced ROS production and cytochrome-C release. Addition of AM251 also eliminated 2 h TER increase and improved TER following 5 µM AEA. Doses of 0.5, 1, and 5 µM AEA delayed endothelial barrier recovery, which was eliminated by the addition of AM251. Mitochondrial dysfunction and activation of apoptotic pathways in response to AEA treatment during LPS challenge of BAEC may act to delay inflammatory resolution and contribute to endothelial dysfunction.
Intermittent Hypoxia-Induced Cardiomyocyte Death Is Mediated by HIF-1 Dependent MAM Disruption
Authors: Moulin Sophie , Thomas Amandine , Wagner Stefan , Arzt Michael , Dubouchaud Hervé , Lamarche Frédéric , Bouyon Sophie , Vial Guillaume , Godin-Ribuot Diane , Pépin Jean-Louis , Arnaud Claire , Belaidi Elise
Published: July 2022

Rationale: Intermittent hypoxia (IH) is one of the main features of sleep-disordered breathing (SDB). Recent findings indicate that hypoxia inducible factor-1 (HIF-1) promotes cardiomyocytes apoptosis during chronic IH, but the mechanisms involved remain to be elucidated. Here, we hypothesize that IH-induced ER stress is associated with mitochondria-associated ER membrane (MAM) alteration and mitochondrial dysfunction, through HIF-1 activation. Methods: Right atrial appendage biopsies from patients with and without SDB were used to determine HIF-1α, Grp78 and CHOP expressions. Wild-type and HIF-1α+/− mice were exposed to normoxia (N) or IH (21–5% O2, 60 cycles/h, 8 h/day) for 21 days. Expressions of HIF-1α, Grp78 and CHOP, and apoptosis, were measured by Western blot and immunochemistry. In isolated cardiomyocytes, we examined structural integrity of MAM by proximity ligation assay and their function by measuring ER-to-mitochondria Ca2+ transfer by confocal microscopy. Finally, we measured mitochondrial respiration using oxygraphy and calcium retention capacity (CRC) by spectrofluorometry. MAM structure was also investigated in H9C2 cells incubated with 1 mM CoCl2, a potent HIF-1α inducer. Results: In human atrial biopsies and mice, IH induced HIF-1 activation, ER stress and apoptosis. IH disrupted MAM, altered Ca2+ homeostasis, mitochondrial respiration and CRC. Importantly, IH had no effect in HIF-1α+/− mice. Similar to what observed under IH, HIF-1α overexpression was associated with MAM alteration in H9C2. Conclusion: IH-induced ER stress, MAM alterations and mitochondrial dysfunction were mediated by HIF-1; all these intermediate mechanisms ultimately inducing cardiomyocyte apoptosis. This suggests that HIF-1 modulation might limit the deleterious cardiac effects of SDB.
Icariside II, a Naturally Occurring SIRT3 Agonist, Protects against Myocardial Infarction through the AMPK/PGC-1α/Apoptosis Signaling Pathway
Authors: Li Yeli , Feng Linying , Xie Dianyou , Lin Mu , Li Yiqi , Chen Nana , Yang Danli , Gao Jianmei , Zhu Yizhun , Gong Qihai
Published: July 2022

Myocardial infarction (MI) refers to the death of cardiomyocytes triggered by a lack of energy due to myocardial ischemia and hypoxia, and silent mating type information regulation 2 homolog 3 (SIRT3) plays an essential role in protecting against myocardial oxidative stress and apoptosis, which are deemed to be the principal causes of MI. Icariside II (ICS II), one of the main active ingredients of Herbal Epimedii, possesses extensive pharmacological activities. However, whether ICS II can protect against MI is still unknown. Therefore, this study was designed to investigate the effect and possible underlying mechanism of ICS II on MI both in vivo and in vitro. The results showed that pretreatment with ICS II not only dramatically mitigated MI-induced myocardial damage in mice but also alleviated H9c2 cardiomyocyte injury elicited by oxygen and glucose deprivation (OGD), which were achieved by suppressing mitochondrial oxidative stress and apoptosis. Furthermore, ICS II elevated the phosphorylation level of adenosine monophosphate-activated protein kinase (AMPK) and peroxisome proliferator-activated receptor-gamma coactivator 1 alpha (PGC-1α) expression, thereby activating SIRT3. However, these protective effects of ICS II on MI injury were largely abolished in SIRT3-deficient mice, manifesting that ICS II-mediated cardioprotective effects are, at least partly, due to the presence of SIRT3. Most interestingly, ICS II directly bound with SIRT3, as reflected by molecular docking, which indicated that SIRT3 might be a promising therapeutic target for ICS II-elicited cardioprotection in MI. In conclusion, our findings illustrate that ICS II protects against MI-induced oxidative injury and apoptosis by targeting SIRT3 through regulating the AMPK/PGC-1α pathway.
Role of Oxidative Stress and Antioxidants in Acquired Inner Ear Disorders
Authors: Kishimoto-Urata Megumi , Urata Shinji , Fujimoto Chisato , Yamasoba Tatsuya
Published: July 2022

Oxygen metabolism in the mitochondria is essential for biological activity, and reactive oxygen species (ROS) are produced simultaneously in the cell. Once an imbalance between ROS production and degradation (oxidative stress) occurs, cells are damaged. Sensory organs, especially those for hearing, are constantly exposed during daily life. Therefore, almost all mammalian species are liable to hearing loss depending on their environment. In the auditory pathway, hair cells, spiral ganglion cells, and the stria vascularis, where mitochondria are abundant, are the main targets of ROS. Excessive generation of ROS in auditory sensory organs is widely known to cause sensorineural hearing loss, and mitochondria-targeted antioxidants are candidates for treatment. This review focuses on the relationship between acquired hearing loss and antioxidant use to provide an overview of novel antioxidants, namely medicines, supplemental nutrients, and natural foods, based on clinical, animal, and cultured-cell studies.
Protective Role of Mitochondrial Uncoupling Proteins against Age-Related Oxidative Stress in Type 2 Diabetes Mellitus
Authors: Čater Maša , Križančić Bombek Lidija Križančić
Published: July 2022

The accumulation of oxidative damage to DNA and other biomolecules plays an important role in the etiology of aging and age-related diseases such as type 2 diabetes mellitus (T2D), atherosclerosis, and neurodegenerative disorders. Mitochondrial DNA (mtDNA) is especially sensitive to oxidative stress. Mitochondrial dysfunction resulting from the accumulation of mtDNA damage impairs normal cellular function and leads to a bioenergetic crisis that accelerates aging and associated diseases. Age-related mitochondrial dysfunction decreases ATP production, which directly affects insulin secretion by pancreatic beta cells and triggers the gradual development of the chronic metabolic dysfunction that characterizes T2D. At the same time, decreased glucose oxidation in skeletal muscle due to mitochondrial damage leads to prolonged postprandial blood glucose rise, which further worsens glucose homeostasis. ROS are not only highly reactive by-products of mitochondrial respiration capable of oxidizing DNA, proteins, and lipids but can also function as signaling and effector molecules in cell membranes mediating signal transduction and inflammation. Mitochondrial uncoupling proteins (UCPs) located in the inner mitochondrial membrane of various tissues can be activated by ROS to protect cells from mitochondrial damage. Mitochondrial UCPs facilitate the reflux of protons from the mitochondrial intermembrane space into the matrix, thereby dissipating the proton gradient required for oxidative phosphorylation. There are five known isoforms (UCP1-UCP5) of mitochondrial UCPs. UCP1 can indirectly reduce ROS formation by increasing glutathione levels, thermogenesis, and energy expenditure. In contrast, UCP2 and UCP3 regulate fatty acid metabolism and insulin secretion by beta cells and modulate insulin sensitivity. Understanding the functions of UCPs may play a critical role in developing pharmacological strategies to combat T2D. This review summarizes the current knowledge on the protective role of various UCP homologs against age-related oxidative stress in T2D.
Simulations of Extrusion 3D Printing of Chitosan Hydrogels
Authors: Ramezani Hamed , Mohammad Mirjamali Seyyed , He Yong
Published: July 2022

Extrusion-based three-dimensional (3D) printing has recently become a major field that provides significant benefits, as it is principally employed to fabricate 3D scaffolds, exploiting soft biomaterials. The 3D printing hydrogel-based ink requires crucial properties, such as printability and printing fidelity to fabricate the appropriate structure. However, it typically uses trial and error techniques to achieve a three-dimensional structure, which wastes material and time. This study employed multiphysics simulation to predicate the potential printability of chitosan hydrogel as a desirable biomaterial used in tissue engineering. The flow was presumed to be laminar and two-phased in the simulations. Furthermore, the impact of different velocities and viscosities in extrusion-based chitosan 3D printing was investigated. Moreover, the model validation of the printed chitosan hydrogel was investigated to confirm the simulation outcomes for high-quality printing. The effect of different printing settings was studied during the experimental test. The results obtained from the simulation and experiments provide information for deciding the optimum parameters for printing chitosan-based ink with high quality.
Digitalization of Calibration Data Management in Pharmaceutical Industry Using a Multitenant Platform
Authors: Mustapää Tuukka , Nummiluikki Juho , Viitala Raine
Published: July 2022

The global quality infrastructure (QI) has been established and is maintained to ensure the safety of products and services for their users. One of the cornerstones of the QI is metrology, i.e., the science of measurement, as the quality management systems commonly rely on measurements for evaluating quality. For this reason, the calibration procedures and the management of the data related to them are of the utmost importance for the quality management in the process industry and given a high priority by the regulatory authorities. To overcome the relatively low level of digitalization in metrology, machine-interpretable data formats such as digital calibration certificates (DCC) are being developed. In this paper, we analyze the current calibration processes in the pharmaceutical industry, and the requirements defined for them in the relevant standards and regulations. For digitalizing the calibration-related data exchange, a multitenant cloud platform-based method is presented. To test and validate the approach, a proof of concept (POC) implementation of the platform is developed with a focus on ease and cost-efficiency of deployment and use while ensuring the preservation of traceability and data integrity. The POC is based on two industrial use cases involving organizations with different roles in the metrology infrastructure. In the testing, the presented approach proves to be an efficient method for organizing the calibration data exchange in industrial use.
Non-Invasive Evaluation of Polymeric Protective Coatings for Metal Surfaces of Cultural Heritage Objects: Comparison of Optical and Electromagnetic Methods
Authors: Quintero Balbas Diego , Dal Fovo Alice , Porcu Daniela , Chaban Antonina , Porcinai Simone , Fontana Raffaella , Striova Jana
Published: July 2022

The application of protective coatings is an effective preventive strategy to avoid metal corrosion. Constant monitoring of the coating’s quality is fundamental for the successful preservation of the metallic objects by reducing their interaction with corroding agents. Their evaluation over time helps to identify failure at early stages and promote their removal and substitution. Several methods have been employed for coating evaluation (i.e., chemical analysis, thickness and homogeneity investigation). In this paper, we compare three methods—Optical Coherence Tomography (OCT), Confocal Raman Microspectroscopy (CRM), and Eddy Currents (ECs)—to evaluate thickness values and coating integrity. The results from the two optical techniques (CRM and OCT) agree, being able to detect the inhomogeneity of the layer on a micron scale but requiring correction to account for the refraction phenomenon. The Eddy Current is a fast and efficient method for thickness estimation, providing data with millimetric lateral resolution.
An Improved Robust Fractal Image Compression Based on M-Estimator
Authors: Huang Penghe , Li Dongyan , Zhao Huimin
Published: July 2022

In this paper, a robust fractal image compression method based on M-estimator is presented. The proposed method applies the M-estimator to the parameter estimation in the fractal encoding procedure using Huber and Tukey’s robust statistics. The M-estimation reduces the influence of the outliers and makes the fractal encoding algorithm robust to the noisy image. Meanwhile, the quadtree partitioning approach has been used in the proposed methods to improve the efficiency of the encoding algorithm, and some unnecessary computations are eliminated in the parameter estimation procedures. The experimental results demonstrate that the proposed method is insensitive to the outliers in the noisy corrupted image. The comparative data shows that the proposed method is superior in both the encoding time and the quality of retrieved images over other robust fractal compression algorithms. The proposed algorithm is useful for multimedia and image archiving, low-cost consumption applications and progressive image transmission of live images, and in reducing computing time for fractal image compression.
Design and Implementation of OPC UA-Based VR/AR Collaboration Model Using CPS Server for VR Engineering Process
Authors: Kim Jeehyeong , Jeong Jongpil
Published: July 2022

In order to cope with the changing era of the innovative management paradigm of the manufacturing industry, it is necessary to advance the construction of smart factories in the domestic manufacturing industry, and in particular, the 3D design and manufacturing content sector is highly growthable. In particular, the core technologies that enable digital transformation VR (Virtual Reality)/AR (Augmented Reality) technologies have developed rapidly in recent years, but have not yet achieved any particular results in industrial engineering. In the manufacturing industry, digital threads and collaboration systems are needed to reduce design costs that change over and over again due to the inability to respond to various problems and demands that should be considered when designing products. To this end, we propose a VR/AR collaboration model that increases efficiency of manufacturing environments such as inspection and maintenance as well as design simultaneously with participants through 3D rendering virtualization of facilities or robot 3D designs in VR/AR. We implemented converting programs and middleware CPS (Cyber Physical System) servers that convert to BOM (Bill of Material)-based 3D graphics models and CPS models to test the accuracy of data and optimization of 3D modeling and study their performance through robotic arms in real factories.
Effect of Sex-Specific Running Shoes on Female Recreational Runners
Authors: Rasmussen Spencer , Wilkes Baker , Poulton Lily , Roser Megan , Draper Shane , Creer Andrew , Standifird Tyler
Published: July 2022

Alterations in running shoe design have been studied and used in the prevention of injury and enhancement of performance allowing running shoe companies to market to a variety of runners based on skill level, foot-strike pattern, and even sex. These alterations have been shown to affect biomechanical and physiological variables associated with running. Some shoe companies have designed shoes specifically for biological female runners due to the morphological differences found between male and female feet. The purpose of this study is to determine if sex-specific running shoes can alter female runner biomechanics or physiology. Female runners were asked to run in the male and female models of the Altra Torin 4 Plush shoe to determine if there were differences in ground reaction forces (GRFs), sagittal plane joint angles and moments, oxygen consumption (VO2), respiratory exchange ratio (RER), and perceived level of comfort while running; There were no significant differences in GRFs, sagittal joint angles and moments, VO2, RER, or perceived comfort; There were no differences in measured biomechanical or physiological variables between the female and male version of the shoes suggesting that the alterations made to the female-specific shoe do not provide any additional benefit to female recreational runners.
FVR-Net: Finger Vein Recognition with Convolutional Neural Network Using Hybrid Pooling
Authors: Tamang Lakpa Dorje , Kim Byung Wook
Published: July 2022

In this paper, we present FVR-Net, which is a novel finger vein recognition network using a convolutional neural network (CNN) with a hybrid pooling mechanism. The scheme is based on the use of a block-wise feature extraction network to extract discrete features from interclass vein image samples, regardless of their visual quality. Input images to FVR-Net are subjected to preprocessing prior to being fed into the network in order to segment the vein patterns from the background. We designed a feature extraction network in which each block consists of a convolutional layer followed by hybrid pooling, whose output activation maps are concatenated before passing features to another block within the network. In the hybrid pooling layer, two subsampling layers of maxpooling and average pooling are placed in parallel where the former activates the most discrete features of the input, and the latter considers the complete extent of the input volume so better localization of features can be accessed. After the features are extracted, they are passed to three fully connected layers (FCLs) for classification. We conduct several experiments on two publicly available finger vein datasets based on visual quality of the images. When compared to conventional studies, the proposed model achieves outstanding recognition performance with accuracies of up to 97.84% and 97.22% for good and poor-quality images, respectively. By varying multiple network hyperparameters, we obtain optimal settings such that the model can guarantee the best recognition accuracy for a finger vein biometric system.
State Evaluation and Fault Prediction of Protection System Equipment Based on Digital Twin Technology
Authors: Dong Yuzhan , Chen Qing , Ding Wei , Shao Ning , Chen Guanting , Li Guanbin
Published: July 2022

Digital twin technology aims to build a map of physical entities in virtual space, and simulate the real-time state and dynamic characteristics of physical devices through bi-directional interactive data flow. In order to guarantee the safe and stable operation of protection system equipment in intelligent substations and improve the efficiency of protection system operation and condition maintenance, this paper proposes a protection system state evaluation and fault prediction method based on digital twin technology. The architecture, application and operation control mode of digital twin technology in a real-time state analysis of a protection system are studied. The state evaluation model based on matter-element extension and the fault prediction model based on clustering algorithm are constructed. By analyzing the historical data of an intelligent station protection system in actual operation, a database that can be updated and corrected in real time is constructed. The effectiveness and accuracy of the state evaluation and fault prediction method are verified with actual cases, which can provide technical support for the operation and maintenance of the protection system.
Carbonic: A Framework for Creating and Visualizing Complex Compound Graphs
Authors: Rodriguez Cristian , Toharia Pablo , Pastor Luis , Mata Susana
Published: July 2022

Advances in data generation and acquisition have resulted in a volume of available data of such magnitude that our ability to interpret and extract valuable knowledge from them has been surpassed. Our capacity to analyze data is hampered not only by their amount or their dimensionality, but also by their relationships and by the complexity of the systems they model. Compound graphs allow us to represent the existing relationships between nodes that are themselves hierarchically structured, so they are a natural substrate to support multiscale analysis of complex graphs. This paper presents Carbonic, a framework for interactive multiscale visual exploration and editing of compound graphs that incorporates several strategies for complexity management. It combines the representation of graphs at multiple levels of abstraction, with techniques for reducing the number of visible elements and for reducing visual cluttering. This results in a tool that allows both the exploration of existing graphs and the visual creation of compound graphs following a top-down approach that allows simultaneously observing the entities and their relationships at different scales. The results show the applicability of the developed framework to two use cases, demonstrating the usefulness of Carbonic for moving from information to knowledge.
Calibration Method of Projectional Geometry for X-ray C-arm Fluoroscopy Using Sinogram Data
Authors: Lee Donggi , Kim Sungmin
Published: July 2022

X-ray imaging represents the most commonly used imaging modality in X-ray-guided vascular intervention procedures. Computed tomography (CT) data ensure that the procedure is performed accurately and safely by providing medical staff with positional information of the body part before starting the procedure. In particular, accurate geometric information of the imaging equipment is essential to accurately calculate the three-dimensional (3D) position of catheters used in delicate operations. However, it is difficult to gather this information before surgery. Therefore, this study proposes a novel calibration method that can be used immediately before a procedure and can guarantee the stability of the procedure. The calibration was performed without additional radiography using sinogram data obtained during the 3D CT imaging process, and both the accuracy and calculation time available in the vascular intervention theater were allowable. The experimental results show that the best angular conditions in terms of calculations and accuracy are between −40 and 40 degrees in angular range and 1.6 degrees in angular interval. Consequently, we achieved a calculation time of 2.92 s and an average accuracy of 0.36 mm, thus meeting our goal of accuracy below 1 mm within a minute of computational time.
Implementing a GIS-Based Digital Atlas of Agricultural Plastics to Reduce Their Environmental Footprint: Part II, an Inductive Approach
Authors: Cillis Giuseppe , Statuto Dina , Schettini Evelia , Vox Giuliano , Picuno Pietro
Published: July 2022

Plastic pollution, largely perceived by the public as a major risk factor that strongly impacts sea life and preservation, has an even higher negative impact on terrestrial ecosystems. Indeed, quantitative data about plastic contamination on agricultural soils are progressively emerging in alarming ways. One of the main contributors to this pollution involves the mismanagement of agricultural plastic waste (APW), i.e., the residues from plastic material used to improve the productivity of agricultural crops, such as greenhouse covers, mulching films, irrigation pipes, etc. Wrong management of agricultural plastics during and after their working lives may pollute the agricultural soil and aquifers by releasing macro-, micro-, and nanoplastics, which could also enter into the human food chain. In this study, we aimed to develop a methodology for the spatial quantification of agricultural plastics to achieve sustainable post-consumer management. Through an inductive approach, based on statistical data from the agricultural census of the administrative areas of the Italian provinces, an agricultural plastic coefficient (APC) was proposed, implemented, and spatialized in a GIS environment, to produce a database of APW for each type of crop. The proposed methodology can be exported to other countries. It represents valuable support that could realize, in integration with other tools, an atlas of agricultural plastics, which may be a starting point to plan strategies and actions targeted to the reduction of the plastic footprint of agriculture.
Research on the Construction of Malware Variant Datasets and Their Detection Method
Authors: Lu Faming , Cai Zhaoyang , Lin Zedong , Bao Yunxia , Tang Mengfan
Published: July 2022

Malware detection is of great significance for maintaining the security of information systems. Malware obfuscation techniques and malware variants are increasingly emerging, but their samples and API (application programming interface) sequences are difficult to obtain. This poses difficulties for the development of malware variant detection models. To address this issue in this paper, we first generated a malware variant dataset using the obfuscation technique based on the disassembly and decompilation of malware. Then, an API call dataset of these malware variants was constructed through sandboxing. Compared to similar work, the malware variants and their obfuscated API call sequences generated in this paper were all runnable. After that, taking a public API call sequence dataset of obfuscation-free malware as input, a BERT (bidirectional encoder representation from transformers) pretrained model for malware detection was constructed. To enhance the ability of this pretrained model to handle obfuscation and variants, in this paper, we used adversarial training to improve the robustness and generalization of the detection model under obfuscation. As the experimental results show, the proposed scheme can improve the classification performance of malware variants under obfuscation. The accuracy of the malware variant classification was close to that of the unobfuscated case.
Fv-AD: F-AnoGAN Based Anomaly Detection in Chromate Process for Smart Manufacturing
Authors: Park Chanho , Lim Sumin , Cha Daniel , Jeong Jongpil
Published: July 2022

Anomaly detection for quality prediction has recently become important, as data collection has increased in various fields, such as smart factories and healthcare systems. Various attempts have been made in the existing manufacturing process to improve discrimination accuracy due to data imbalance in the anomaly detection model. Predicting the quality of a chromate process has a significant influence on the completeness of the process, and anomaly detection is important. Furthermore, obtaining image data, such as monitoring during the manufacturing process, is difficult, and prediction is challenging owing to data imbalance. Accordingly, the model employs an unsupervised learning-based Generative Adversarial Networks (GAN) model, performs learning with only normal data images, and augments the Fast Unsupervised Anomaly Detection with GAN (F-AnoGAN) base with a visualization component to provide a more intuitive judgment of defects with chromate process data. In addition, anomaly scores are calculated based on mapping in the latent space, and new data are applied to confirm anomaly detection and the corresponding location values. As a result, this paper presents a GAN architecture to detect anomalies through chromate facility data in a smart manufacturing environment. It proved meaningful performance and added visualization parts to provide explainable interpretation. Data experiments on the chromate process show that the loss value, anomaly score, and anomaly position are accurately distinguished from abnormal images.
A Novel Decoupled Synchronous Control Method for Multiple Autonomous Unmanned Linear Systems: Bounded L2-Gain for Coupling Attenuation
Authors: Li Yinsheng , Wang Bing , Chen Yuquan
Published: July 2022

This paper addresses the distributed optimal decoupling synchronous control of multiple autonomous unmanned linear systems (MAUS) subject to complex network dynamic coupling. The leader–follower mechanism based on neighborhood error dynamics is established and the network coupling term is regarded as the external disturbance to realize the decoupling cooperative control of each agent. The Bounded L2-Gain problem for the network coupling term is formulated into a multi-player zero-sum differential game. It is shown that the solution to the multi-player zero-sum differential game requires the solution to coupled Hamilton–Jacobi (HJ) equations. The coupled HJ equations are transformed into an algebraic Riccati equation (ARE), which can be solved to obtain the Nash equilibrium of a multi-player zero-sum game. It is shown that the bounded L2-Gain for coupling attenuation can be realized by applying the zero-sum game solution as the control protocol and the ultimately uniform boundedness (UUB) of a local neighborhood error vector under conservative conditions is proved. A simulation example is provided to show the effectiveness of the proposed method.
A Soft-Voting Ensemble Classifier for Detecting Patients Affected by COVID-19
Authors: Manconi Andrea , Armano Giuliano , Gnocchi Matteo , Milanesi Luciano
Published: July 2022

COVID-19 is an ongoing global pandemic of coronavirus disease 2019, which may cause severe acute respiratory syndrome. This disease highlighted the limitations of health systems worldwide regarding managing the pandemic. In particular, the lack of diagnostic tests that can quickly and reliably detect infected patients has contributed to the spread of the virus. Reverse Transcriptase—Polymerase Chain Reaction (RT-PCR) and antigen tests, which are the main diagnostic tests for COVID-19, showed their limitations during the pandemic. In fact, RT-PCR requires several hours to provide a diagnosis and is not properly accurate, thus generating a high number of false negatives. Unlike RT-PCR, antigen tests provide rapid diagnosis but are less accurate in detecting COVID-19 positive patients. Medical imaging is an alternative diagnostic test for COVID-19. In particular, chest computed tomography allows detecting lung infections related to the disease with high accuracy. However, visual analysis of a chest scan generated by computed tomography is a demanding activity for radiologists, making widespread use of this test unfeasible. Therefore, it is essential to lighten their work with automated tools able to provide accurate diagnosis in a short time. To deal with this challenge, in this work, an approach based on 3D Inception CNNs is proposed. Specifically, 3D Inception-V1 and Inception-V3 models have been built and compared. Then, soft-voting ensemble classifier models have been separately built on these models to boost the performance. As for the individual models, results showed that Inception-V1 outperformed Inception-V3 according to different measures. As for the ensemble classifier models, the outcome of experiments pointed out that the adopted voting strategy boosted the performance of individual models. The best results have been achieved enforcing soft voting on Inception-V1 models.
BPG-Based Automatic Lossy Compression of Noisy Images with the Prediction of an Optimal Operation Existence and Its Parameters
Authors: Kovalenko Bogdan , Lukin Vladimir , Kryvenko Sergii , Naumenko Victoriya , Vozel Benoit
Published: July 2022

With a resolution improvement, the size of modern remote sensing images increases. This makes it desirable to compress them, mostly by using lossy compression techniques. Often the images to be compressed (or some component images of multichannel remote sensing data) are noisy. The lossy compression of such images has several peculiarities dealing with specific noise filtering effects and evaluation of the compression technique’s performance. In particular, an optimal operation point (OOP) may exist where quality of a compressed image is closer to the corresponding noise-free (true) image than the uncompressed (original, noisy) image quality, according to certain criterion (metrics). In such a case, it is reasonable to automatically compress an image under interest in the OOP neighborhood, but without having the true image at disposal in practice, it is impossible to accurately determine if the OOP does exist. Here we show that, by a simple and fast preliminary analysis and pre-training, it is possible to predict the OOPs existence and the metric values in it with appropriate accuracy. The study is carried out for a better portable graphics (BPG) coder for additive white Gaussian noise, focusing mainly on one-component (grayscale) images. The results allow for concluding that prediction is possible for an improvement (reduction) in the quality metrics of PSNR and PSNR-HVS-M. In turn, this allows for decision-making about the existence or absence of an OOP. If an OOP is absent, a more “careful” compression is recommended. Having such rules, it then becomes possible to carry out the compression automatically. Additionally, possible modifications for the cases of signal-dependent noise and the joint compression of three-component images are considered and the possible existence of an OOP for these cases is demonstrated.
High-Temperature Thermodynamics Modeling of Graphite
Authors: Söderlind Per , Landa Alexander , Hood Randolph Q. , Moore Emily E. , Perron Aurélien , McKeown Joseph T.
Published: July 2022

We present high-temperature thermodynamic properties for graphite from first-principles anharmonic theory. The ab initio electronic structure is obtained from density-functional theory coupled to a lattice dynamics method that is used to model anharmonic lattice vibrations. This combined approach produces free energies and specific heats for graphite that compare well with available experiments and results from models that empirically represent experimental data, such as CALPHAD. We show that anharmonic theory for the phonons is essential for accurate thermodynamic quantities above about 1000 K.
A pH Monitoring Algorithm for Orifice Plate Culture Medium
Authors: Li Yuqi , Huang Anyi , Zhang Tao , Wen Luhong , Shi Zhenzhi , Shi Lulu
Published: July 2022

Recently, there has been renewed interest in cell therapy, which plays a key role in the clinical research of genetic diseases, advanced blood disease, and other diseases. It shows considerable clinical application value and is known as “the new pillar of future medicine”. Automatic cell culture and operation technology is the key to ensuring scale, standardization, and stability between batches of therapeutic cells. The pH of the cell culture medium is vital for cell growth. Most cells are suitable for growth at pH 7.2~7.4. A pH of cell culture medium lower than 6.8 or higher than 7.6 is harmful to cells, and cells will degenerate or even die. At present, the monitoring method of cell culture medium pH of automatic cell culture equipment is mainly a visual observation method, which can not accurately or quickly reflect changes in the cell culture medium. To address the issue of monitoring of cell culture fluid pH for automated cell culture equipment and the inability to employ invasive sensors to measure pH during well plate culture, a pH monitoring method for orifice plate culture medium algorithm based on HSV (hue, saturation, value) model is proposed by studying the changes of cell culture medium in the process of cell culture. The research presented here reveals the laws of cell culture fluid pH change and its color moment, and the intelligent monitoring of cell culture fluid pH was successfully achieved. The problem of non-destructive monitoring of the pH of cell culture fluids in well plates is also addressed.
Exploiting Biofilm Characteristics to Enhance Biological Nutrient Removal in Wastewater Treatment Plants
Authors: Mpongwana Ncumisa , Rathilal Sudesh
Published: July 2022

Biological treatments are integral processes in wastewater treatment plants (WWTPs). They can be carried out using sludge or biofilm processes. Although the sludge process is effective for biological wastewater systems, it has some drawbacks that make it undesirable. Hence, biofilm processes have gained popularity, since they address the drawbacks of sludge treatments, such as the high rates of sludge production. Although biofilms have been reported to be essential for wastewater, few studies have reviewed the different ways in which the biofilm properties can be explored, especially for the benefit of wastewater treatment. Thus, this review explores the properties of biofilms that can be exploited to enhance biological wastewater systems. In this review, it is revealed that various biofilm properties, such as the extracellular polymeric substances (EPS), quorum sensing (Qs), and acylated homoserine lactones (AHLs), can be enhanced as a sustainable and cost-effective strategy to enhance the biofilm. Moreover, the exploitation of other biofilm properties such as the SOS, which is only reported in the medical field, with no literature reporting it in the context of wastewater treatment, is also recommended to improve the biofilm technology for wastewater treatment processes. Additionally, this review further elaborates on ways that these properties can be exploited to advance biofilm wastewater treatment systems. A special emphasis is placed on exploiting these properties in simultaneous nitrification and denitrification and biological phosphorus removal processes, which have been reported to be the most sensitive processes in biological wastewater treatment.
Constitutive High Expression Level of a Synthetic Deleted Encoding Gene of Talaromyces minioluteus Endodextranase Variant (r–TmDEX49A–ΔSP–ΔN30) in Komagataella phaffii (Pichia pastoris)
Authors: Arísticas Ribalta Roberto Carlos , Valdés Lisandra Martínez , Lafargue Gámez Meinardo , Rodríguez Davydenko Sonia , Dubreucq Eric , Perrier Veronique , Moreau Benoît , Vidal Reinaldo Fraga
Published: July 2022

In the sugar industry, dextran generates difficulties in the manufacturing process. Using crude dextranase (EC 3.2.1.11) to eliminate dextran in sugar is an effective practice. In this study, a synthetic dextranase-encoding gene of the filamentous fungus Talaromyces minioluteus, lacking its putative native signal peptide (1–20 amino acids) and the next 30 amino acids (r–TmDEX49A–ΔSP–ΔN30), was fused to the Saccharomyces cerevisiae prepro α–factor (MFα–2) signal sequence and expressed in Komagataella phaffii under the constitutive GAP promoter. K. phaffii DEX49A–ΔSP–ΔN30, constitutively producing and secreting the truncated dextranase, was obtained. The specific activity of the truncated variant resulted in being nearly the same in relation to the full-length mature enzyme (900–1000 U·mg−1 of protein). At shaker scale (100 mL) in a YPG medium, the enzymatic activity was 273 U·mL−1. The highest production level was achieved in a fed-batch culture (30 h) at 5 L fermenter scale using the FM21–PTM1 culture medium. The enzymatic activity in the culture supernatant reached 1614 U·mL−1, and the productivity was 53,800 U·L−1·h−1 (53.8 mg·L−1·h−1), the highest reported thus far for a DEX49A variant. Dextran decreased r–TmDEX49A–ΔSP–ΔN30 mobility in affinity gel electrophoresis, providing evidence of carbohydrate–protein interactions. K. phaffii DEX49A–ΔSP–ΔN30 shows great potential as a methanol-free, commercial dextranase production system.
Questioning the Anisotropy of Pedestrian Dynamics: An Empirical Analysis with Artificial Neural Networks
Authors: Subaih Rudina , Maree Mohammed , Tordeux Antoine , Chraibi Mohcine
Published: July 2022

Identifying the factors that control the dynamics of pedestrians is a crucial step towards modeling and building various pedestrian-oriented simulation systems. In this article, we empirically explore the influential factors that control the single-file movement of pedestrians and their impact. Our goal in this context is to apply feed-forward neural networks to predict and understand the individual speeds for different densities of pedestrians. With artificial neural networks, we can approximate the fitting function that describes pedestrians’ movement without having modeling bias. Our analysis is focused on the distances and range of interactions across neighboring pedestrians. As indicated by previous research, we find that the speed of pedestrians depends on the distance to the predecessor. Yet, in contrast to classical purely anisotropic approaches—which are based on vision fields and assume that the interaction mainly depends on the distance in front—our results demonstrate that the distance to the follower also significantly influences movement. Using the distance to the follower combined with the subject pedestrian’s headway distance to predict the speed improves the estimation by 18% compared to the prediction using the space in front alone.
Experimental Investigation on Jet Vector Deflection Jumping Phenomenon of Coanda Effect Nozzle
Authors: Chi Shaoqing , Gu Yunsong
Published: July 2022

The Coanda effect nozzle is a fluid thrust vectoring technology that uses the Coanda effect to control jet vector deflection. The jumping phenomenon often occurs in the process of controlling jet vector deflection. This phenomenon leads to the nonlinearity of thrust vector control. It destroys the control performance of the aircraft and brings potential dangers to the safety of the aircraft. The jumping phenomenon occurs in an unsteady flow field different from the traditional flow phenomenon. The flow structure in an unsteady flow field changes with time, so it is not easy to control by the traditional active flow control method. This paper explains the reasons for the jumping phenomenon from two aspects: flow field stability and flow structure. Secondly, the unsteady flow field with the jumping phenomenon is studied and analyzed by a flow visualization experiment and dynamic force measurement. Furthermore, the dynamic modal decomposition (DMD) method is used to extract the characteristic frequencies of the critical vortices causing jets to jump in unsteady flow fields. Finally, a pulsed jet with the same characteristic frequency is used to control the varying vortices in the unsteady flow field. The experimental results show that the active flow control method, which extracts the characteristic frequency of the critical flow field structure by DMD, effectively suppresses the jumping phenomenon in the unsteady flow field. It also linearizes the process of jet nonlinear vector deflection.