bluuebunny/crossref_metadata_2025 huggingface dataset:
Generation and Physiology of Hydrogen Sulfide and Reactive Sulfur Species in Bacteria
Authors: Han Sirui , Li Yingxi , Gao Haichun
Published: December 2022

Sulfur is not only one of the most abundant elements on the Earth, but it is also essential to all living organisms. As life likely began and evolved in a hydrogen sulfide (H2S)-rich environment, sulfur metabolism represents an early form of energy generation via various reactions in prokaryotes and has driven the sulfur biogeochemical cycle since. It has long been known that H2S is toxic to cells at high concentrations, but now this gaseous molecule, at the physiological level, is recognized as a signaling molecule and a regulator of critical biological processes. Recently, many metabolites of H2S, collectively called reactive sulfur species (RSS), have been gradually appreciated as having similar or divergent regulatory roles compared with H2S in living organisms, especially mammals. In prokaryotes, even in bacteria, investigations into generation and physiology of RSS remain preliminary and an understanding of the relevant biological processes is still in its infancy. Despite this, recent and exciting advances in the fields are many. Here, we discuss abiotic and biotic generation of H2S/RSS, sulfur-transforming enzymes and their functioning mechanisms, and their physiological roles as well as the sensing and regulation of H2S/RSS.
Applications of Antioxidants in Dental Procedures
Authors: Qi Fan , Huang Haofei , Wang Ming , Rong Weifeng , Wang Jing
Published: December 2022

As people are paying more and more attention to dental health, various dental treatment procedures have emerged, such as tooth bleaching, dental implants, and dental restorations. However, a large number of free radicals are typically produced during the dental procedures. When the imbalance in distribution of reactive oxygen species (ROS) is induced, oxidative stress coupled with oxidative damage occurs. Oral inflammations such as those in periodontitis and pulpitis are also unavoidable. Therefore, the applications of exogenous antioxidants in oral environment have been proposed. In this article, the origin of ROS during dental procedures, the types of antioxidants, and their working mechanisms are reviewed. Additionally, antioxidants delivery in the complicated dental procedures and their feasibility for clinical applications are also covered. Finally, the importance of safety assessment of these materials and future work to take the challenge in antioxidants development are proposed for perspective.
Assessment of Gnaphalium viscosum (Kunth) Valorization Prospects: Sustainable Recovery of Antioxidants by Different Techniques
Authors: Boyadzhieva Stanislava , Coelho Jose A. P. , Errico Massimiliano , Reynel-Avilla H. Elizabeth , Yankov Dragomir S. , Bonilla-Petriciolet Adrian , Stateva Roumiana P.
Published: December 2022

This work investigates the prospects for exploitation of Gnaphalium viscosum (Kunth) abundant but with limited applications till present biomass. The feasibility of traditional techniques (two-phase solvent, and the benchmark Soxhlet extraction) and supercritical extraction without/with a cosolvent at T = 40–60 °C and p = 30–50 MPa was examined to explore the possibility of recovering phytochemicals from G. viscosum leaves, flowers and stems. The efficiency of the techniques was assessed and compared based on yield, influence of solvents used, total phenolic content and antioxidant activity of the extracts. Phenolics of different complexities were identified and quantified by applying LC (LC–MS/MS, and LC–HRAM), while the fatty acid profile was determined by GC–FID. The results of this extensive study demonstrated the huge valorization potential and prospects of G. viscosum, since highly potent antioxidants such as kaempferol, kaempferol-3-O-β-d-glucoside (astragalin), and chlorogenic acid were ascertained in considerable amounts. Furthermore, for the first time, the presence of leontopodic acid, a greatly substituted derivative of glucaric acid, was detected in the species.
Stevia and Stevioside Attenuate Liver Steatosis through PPARα-Mediated Lipophagy in db/db Mice Hepatocytes
Authors: Park Miey , Sharma Anshul , Baek Hana , Han Jin-Young , Yu Junho , Lee Hae-Jeung
Published: December 2022

Lipophagy, a type of autophagy that breaks down lipid droplets, is essential in the regulation of intracellular lipid accumulation and intracellular free fatty acid levels in numerous organisms and metabolic conditions. We investigated the effects of Stevia rebaudiana Bertoni (S), a low-calorie sweetener, and stevioside (SS) on hepatic steatosis and autophagy in hepatocytes, as well as in db/db mice. S and SS reduced the body and liver weight and levels of serum triglyceride, total cholesterol, and hepatic lipogenic proteins. In addition, S and SS increased the levels of fatty acid oxidase, peroxisome proliferator-activated receptor alpha (PPARα), and microtubule-associated protein light chain 3 B but decreased that of sequestosome 1 (p62) in the liver of db/db mice. Additionally, Beclin 1, lysosomal associated membrane protein 1, and phosphorylated adenosine monophosphate-activated protein kinase protein expression was augmented following S and SS treatment of db/db mice. Furthermore, the knockdown of PPARα blocked lipophagy in response to SS treatment in HepG2 cells. These outcomes indicate that PPARα-dependent lipophagy is involved in hepatic steatosis in the db/db mouse model and that SS, a PPARα agonist, represents a new therapeutic option for managing associated diseases.
A Cybersecurity Knowledge Graph Completion Method Based on Ensemble Learning and Adversarial Training
Authors: Wang Peng , Liu Jingju , Hou Dongdong , Zhou Shicheng
Published: December 2022

The application of cybersecurity knowledge graphs is attracting increasing attention. However, many cybersecurity knowledge graphs are incomplete due to the sparsity of cybersecurity knowledge. Existing knowledge graph completion methods do not perform well in domain knowledge, and they are not robust enough relative to noise data. To address these challenges, in this paper we develop a new knowledge graph completion method called CSEA based on ensemble learning and adversarial training. Specifically, we integrate a variety of projection and rotation operations to model the relationships between entities, and use angular information to distinguish entities. A cooperative adversarial training method is designed to enhance the generalization and robustness of the model. We combine the method of generating perturbations for the embedding layers with the self-adversarial training method. The UCB (upper confidence bound) multi-armed bandit method is used to select the perturbations of the embedding layer. This achieves a balance between perturbation diversity and maximum loss. To this end, we build a cybersecurity knowledge graph based on the CVE, CWE, and CAPEC cybersecurity databases. Our experimental results demonstrate the superiority of our proposed model for completing cybersecurity knowledge graphs.
Fabrication and Characterization of Gel-Forming Cr2O3 Abrasive Tools for Sapphire Substrate Polishing
Authors: Zhao Liang , Feng Kaiping , Lyu Binghai , Zhao Tianchen , Zhou Zhaozhong
Published: December 2022

This paper proposes a gel-formed abrasive tool to address the problem of abrasive agglomeration in a traditional hot-pressing abrasive tool. The effect of Polyimide resin content on the mechanical properties of the gel abrasive tools were tested, and a comparison of the mechanical properties of the gel abrasive tool and the hot-pressing tool was conducted. An orthogonal experiment was conducted to explore the best combination of machining parameters. A polishing experiment of sapphire was conducted to compare the processing effect of the gel abrasive tool and hot-pressing tool. The results from testing the mechanical properties showed that the tensile, flexural, and impact strength of the gel abrasive tool was better than that of the hot-pressing abrasive tool. The results of the orthogonal experiment showed that the best process parameters of the gel abrasive tool were a spindle speed of 900 rpm, a feed rate of 8 μm/min, and a grinding depth of 16 μm. The polishing experiment showed that the gel abrasive tool had a better processing effect on sapphire. The sapphire surface processed by the gel abrasive tool had no deep scratches, and an ultrasmooth surface could be obtained after chemical mechanical polishing (CMP).
Different Path Planning Techniques for an Indoor Omni-Wheeled Mobile Robot: Experimental Implementation, Comparison and Optimization
Authors: Massoud Mostafa Mo. , Abdellatif A. , Atia Mostafa R. A.
Published: December 2022

Omni-wheeled mobile robots (Omni WMRs) are commonly used in indoor navigation applications like surveillance, search and rescue, and autonomous transportation. They are always characterized by their versatility, mobility and high payload. This paper presents the mechatronic design, low-level control and high-level control of an indoor 4 Omni-Wheeled Mobile Robot (4OWMR). Since autonomy and path planning are research necessities for WMRs, four heuristic and probabilistic path-planning techniques are chosen for experimental implementation. The selected techniques are PRM (Probabilistic Roadmaps), RRT (Rapidly exploring Random Tree), RRTSTAR (RRT*), and ASTAR (A*) algorithms. The proposed environments are static, expressed by maps with unknown nodes and obstacles. Local path planning is implemented with simultaneous localization and mapping (SLAM). Path planning techniques are programmed, and the obtained paths are optimized by a multi-objective genetic algorithm technique to ensure the shortest path and its smoothness. The optimized paths are deployed to the 4OWMR. The obtained results are compared in terms of travel time, travel distance, average velocity and convergence error. A ranking technique is utilized to rank the obtained results and show the most preferred technique in terms of energy consumption and convergence accuracy in addition to the overall ranking. Experimental results showed that the Hybrid A* algorithm produced the best-generated paths with respect to other techniques.
Leveraging Machine Learning and Semi-Structured Information to Identify Political Views from Social Media Posts
Authors: Olteanu Adriana , Cernian Alexandra , Gâgă Sebastian-Augustin
Published: December 2022

Social media platforms make a significant contribution to modeling and influencing people’s opinions and decisions, including political views and orientation. Analyzing social media content can reveal trends and key triggers that will influence society. This paper presents an exhaustive analysis of the performance generated by various implementations of the Naïve Bayes classifier, combined with a semi-structured information approach, to identify the political orientation of Twitter users, based on their posts. As research methodology, we aggregate in a semi-structured format a database of over 86,000 political posts from Democrat (right) and Republican (left) ideologies. Such an approach allows us to associate a Democrat or Republican label to each tweet, in order to create and train the model. The semi-structured input data are processed using several NLP techniques and then the model is trained to classify the political orientation based on semantic criteria and semi-structured information. This paper examines several variations of the Naïve Bayes classifier suite: Gaussian Naïve Bayes, Multinomial Naïve Bayes, Calibrated Naïve Bayes algorithms, and tracks a variety of performance indices and their graphical representations: Prediction Accuracy, Precision, Recall, Confusion Matrix, Brier Score Loss, etc. We obtained an accuracy of around 80–85% in identifying the political orientation of the users. This leads us to the conclusion that this type of application can be integrated into a more complex system and can help in determining political trends or election results.
Face Beneath the Ink: Synthetic Data and Tattoo Removal with Application to Face Recognition
Authors: Ibsen Mathias , Rathgeb Christian , Drozdowski Pawel , Busch Christoph
Published: December 2022

Systems that analyse faces have seen significant improvements in recent years and are today used in numerous application scenarios. However, these systems have been found to be negatively affected by facial alterations such as tattoos. To better understand and mitigate the effect of facial tattoos in facial analysis systems, large datasets of images of individuals with and without tattoos are needed. To this end, we propose a generator for automatically adding realistic tattoos to facial images. Moreover, we demonstrate the feasibility of the generation by using a deep learning-based model for removing tattoos from face images. The experimental results show that it is possible to remove facial tattoos from real images without degrading the quality of the image. Additionally, we show that it is possible to improve face recognition accuracy by using the proposed deep learning-based tattoo removal before extracting and comparing facial features.
Attenuation and Frequency Characteristics of Acoustic Waves in Steel and Synthetic Fiber-Reinforced Concrete: 3D-PCT and Unsupervised Pattern Recognition
Authors: Tayfur Sena , Alver Ninel
Published: December 2022

In heterogeneous materials such as concrete, deterioration of the elastic wave—which acoustic emission technique (AET) is based on—is one of the research objects in the field. While many studies reveal that the wave is deteriorated due to the concrete content and deterioration of AE signals causes erroneous data interpretation, a limited number of them have suggested eliminating the effects of this problem. For this reason, contributing to the existing literature, this paper proposes to correct AE signals for fiber-reinforced concrete, which is a highly heterogeneous material, by 3D-PCT (Parameter Correction Technique) developed with new approaches in the authors’ previous study for concrete. First, the attenuation properties of concrete samples, including different types and amounts of fibers, were revealed within this scope. Contour maps showed that the type and amount of fiber are effective on elastic wave attenuation. Then, the samples were tested under flexure, and AE results were compared with mechanical findings after parameter correction. The effectiveness of the proposed correction method was verified by separating fiber activities from concrete cracking activities for the first time in the literature with weighted peak frequency and partial power. In this way, by successfully matching the fiber activities, which were revealed after the correction, with the crack development times obtained from frequency-based unsupervised pattern recognition, it was seen that a more accurate AE interpretation could be made with parameter correction. Moreover, corrected AE parameters also provided to propose a new inference for identifying a relationship between the amplitude and energy loss of the AE signals and the type of damage.
Performance Analysis and Sensor-Target Geometry Optimization for TOA and TDOA-Based Hybrid Source Localization Method
Authors: Ma Guoning , Huang Zhijiang , Wang Ming , Ji Zhengyu , Li Xianglu , Shen Bo , Tian Jie
Published: December 2022

Currently, the performance analysis of positioning algorithms and optimization of ground station deployment schemes are predominantly based on pure TOA or TDOA measurement information, and the relevant theoretical analysis is primarily the geometric analysis of optimal station deployment for fixed point targets, with few placement ranges and amount of station constraints. In practice, however, there are typically several measurements from TOA and TDOA stations, with a focus on positioning precision within a certain region or line trajectory, as well as the necessity for constraints on the ground station placement range. This paper proposes an efficient method for hybrid source localization using TOA and TDOA measurement information, establishes a mathematical model for hybrid source localization based on TOA and TDOA measurement information, derives and simulates the Gauss–Newton iterative localization algorithm with the least squares criterion, and performs a theoretical analysis of the least squares error and CRLB boundary to improve the accuracy of target localization in the aforementioned scenarios. Taking the average CRLB value of target line trajectory positioning error as the objective function, the ground station placement scheme of TOA- and TDOA-receiving sensors is optimized by utilizing a Genetic Algorithm with strong global optimization capability under the constraints of station placement range and station quantities, and a station placement geometry with better performance than typical station placement is obtained. Meanwhile, we summarize the general placement principles for TOA and TDOA hybrid source localization of target line trajectories.
Displacement and Extinction of Jet Diffusion Flame Exposed to Speaker-Generated Traveling Sound Waves
Authors: Zhang Ya-Jie , Jamil Huzaifa , Wei Yan-Ju , Yang Ya-Jing
Published: December 2022

Acoustic flame suppression is a potential technology which does away with the need to carry fire-extinguishing media and does not cause secondary pollution. We herein reported an experimental study on the displacement and extinction of jet diffusion flames exposed to speaker-generated traveling sound waves with a frequency of 110–150 Hz and local sound pressure of 2–16 Pa. The simultaneous movement of the flame and fuel was captured using a high-speed camera and schlieren techniques. Results showed that the flame oscillation was dominated by induced wind produced by membrane vibrations instead of sound pressure, and this induced wind’s frequency was the same as that of sound waves. Moreover, the movement of unburned fuel and flame was not synchronous, which resulted in an interrupted fuel–flame cycle. Consequently, the flame was gradually suppressed and completely extinguished after several oscillation cycles. Finally, we determined the extinction criterion that when the dimensionless gap between the flame and the unburned fuel was greater than or equal to 7, the flame would be extinguished. Results clearly revealed the mechanism of acoustic fire extinguishing, which provided reference for the feasibility of acoustic fire-extinguishing applications.
Application of Digital Image Analysis for Assessment of Starch Content and Distribution in Potatoes
Authors: Boruczkowski Tomasz , Boruczkowska Hanna , Drożdż Wioletta , Raszewski Bartosz
Published: December 2022

This study presents the possibility of using digital image analysis for the assessment of the starch content and distribution in potatoes. Tubers of six cultivars that were stored for 3 months in contrasting conditions (4 °C vs. −15 °C) were used in the experiment. The starch distribution in the potato tubers was assessed on the basis of histograms of the pixel values along four lines in the tuber cross-sections. Next, the basic statistics were calculated and used for the analysis of variance. The applied method allowed more precise distinguishing between the studied potato cultivars than comparing the total starch content alone. The new method also clearly distinguished potatoes stored in a freezer from those kept in a cold store.
State Observer Based on an Accelerometer for an Elastic Joint with Nonlinear Friction
Authors: Lee Kwang-Hee , Kim Hyungjong , Kuc Tae-Yong
Published: December 2022

This paper presents a state observer for an elastic joint with nonlinear friction via the information from an acceleration sensor. In order to avoid discontinuities, the nonlinear friction of the motor, which includes static, coulomb, and viscous terms, is considered a smooth function. In addition, it uses an acceleration sensor to obtain the information about the link with high uncertainty. The proposed state observer guarantees that the estimation error for the position and velocity of the link connected via an elastic joint containing a nonlinear stiffness (elasticity) converges to zero. In addition, it is shown that the observer gain can be designed by LMI (linear matrix inequality) optimization. Finally, to verify the performance of the proposed observer, the method proposed in this paper is tested by experiments on a two-inertia system with an elastic shaft.
Cybersecurity in the AI-Based Metaverse: A Survey
Authors: Pooyandeh Mitra , Han Ki-Jin , Sohn Insoo
Published: December 2022

The Metaverse is a multi-user virtual world that combines physical reality with digital virtual reality. The three basic technologies for building the Metaverse are immersive technologies, artificial intelligence, and blockchain. Companies are subsequently making significant investments into creating an artificially intelligent Metaverse, with the consequence that cybersecurity has become more crucial. As cybercrime increases exponentially, it is evident that a comprehensive study of Metaverse security based on artificial intelligence is lacking. A growing number of distributed denial-of-service attacks and theft of user identification information makes it necessary to conduct comprehensive and inclusive research in this field in order to identify the Metaverse’s vulnerabilities and weaknesses. This article provides a summary of existing research on AI-based Metaverse cybersecurity and discusses relevant security challenges. Based on the results, the issue of user identification plays a very important role in the presented works, for which biometric methods are the most commonly used. While the use of biometric data is considered the safest method, due to their uniqueness, they are also susceptible to misuse. A cyber-situation management system based on artificial intelligence should be able to analyze data of any volume with the help of algorithms. To prepare researchers who will pursue this topic in the future, this article provides a comprehensive summary of research on cybersecurity in the Metaverse based on artificial intelligence.
Oral Immune-Related Adverse Events Associated with PD-1 Inhibitor Treatment: A Case Series
Authors: Pergolini Daniele , Botticelli Andrea , Fascetti Roberta , Rocchetti Federica , Cirillo Alessio , Tenore Gianluca , Palaia Gaspare , Polimeni Antonella , Romeo Umberto
Published: December 2022

Introduction: Immune Checkpoint Inhibitor (ICI) drugs have led to a revolution in the treatment of different forms of cancer, shifting the target of action from cancer cells to the patient’s immune system, enhancing their responses against the tumor itself. On the other hand, this mechanism can lead to responses against oneself, with the appearance of immune-related adverse events. The aim of the present study was to examine the immune-related adverse events (irAEs) affecting the mucous membranes of the oral cavity and the possible correlation between these and skin toxicities, which are reported in the literature as the most common adverse events. Materials and methods: Thirteen patients treated with anti-Programmed Death (PD-1) drugs (pembrolizumab, nivolumab, and cemiplimab) were selected. The data collected include the general history of the patient and the type of anticancer treatment. The sample was then analyzed by recording the alterations found on the mucous membranes of the oral cavity and on the skin. Finally, the average time that elapsed between the start of immunotherapy and the onset of lesions was analyzed. Results: Patients often had multiple lesions at the same time. Hyperkeratosis was found in three patients, candidiasis (pseudomembranous and median rhomboid glossitis) in two patients, epithelial atrophy in four patients, and ulcerative areas in two patients. One patient reported xerostomia with dysphagia. The anatomical areas most involved were the dorsal tongue and palate. Skin irAEs included skin rash erythema (n = 7) with diffuse redness, the presence of small bubbles with a crusty outcome, and dryness of the skin in the affected areas. Discussion: In the literature, there are few studies that analyze how irAEs affect the mucous membranes of the oral cavity in patients treated with ICI drugs. The most frequently described lesions are lichenoid reactions and xerostomia. Moreover, the development of mucositis, generally of low grade, has been reported. The present study has confirmed the data from the literature and, in addition, reports two cases of candidiasis, an adverse event that has never been shown in the literature. Conclusions: irAEs have the potential to affect any organ. The only way to avoid the occurrence of serious events that is currently available is early interception, which is only possible through the knowledge of these manifestations. It is therefore considered necessary to deepen our knowledge of oral irAEs and their correlation with dermatological toxicities, allowing for a multidisciplinary classification of the patient and a timely diagnosis of any adverse event and avoiding progression to more advanced stages, which could lead to the temporary or permanent suspension of anticancer drugs.
Transformer: An OS-Supported Reconfigurable Hybrid Memory Architecture
Authors: Chi Ye , Liu Haikun , Peng Ganwei , Liao Xiaofei , Jin Hai
Published: December 2022

Non-volatile memories (NVMs) have aroused vast interest in hybrid memory systems due to their promising features of byte-addressability, high storage density, low cost per byte, and near-zero standby energy consumption. However, since NVMs have limited write endurance, high write latency, and high write energy consumption, it is still challenging to directly replace traditional dynamic random access memory (DRAM) with NVMs. Many studies propose to utilize NVM and DRAM in a hybrid memory system, and explore sophisticated memory management schemes to alleviate the impact of slow NVM on the performance of applications. A few studies architected DRAM and NVM in a cache/memory hierarchy. However, the storage and performance overhead of the cache metadata (i.e., tags) management is rather expensive in this hierarchical architecture. Some other studies architected NVM and DRAM in a single (flat) address space to form a parallel architecture. However, the hot page monitoring and migration are critical for the performance of applications in this architecture. In this paper, we propose Transformer, an OS-supported reconfigurable hybrid memory architecture to efficiently use DRAM and NVM without redesigning the hardware architecture. To identify frequently accessed (hot) memory pages for migration, we propose to count the number of page accesses in OSes by sampling the access bit of pages periodically. We further migrate the identified hot pages from NVM to DRAM to improve the performance of hybrid memory system. More importantly, Transformer can simulate a hierarchical hybrid memory architecture while DRAM and NVM are physically managed in a flat address space, and can dynamically shift the logical memory architecture between parallel and hierarchical architectures according to applications’ memory access patterns. Experimental results show that Transformer can improve the application performance by 62% on average (up to 2.7×) compared with an NVM-only system, and can also improve performance by up to 79% and 42% (21% and 24% on average) compared with hierarchical and parallel architectures, respectively.
Road Pavement Damage Detection Based on Local Minimum of Grayscale and Feature Fusion
Authors: Jin Wei-Wei , Chen Guo-Hong , Chen Zhuo , Sun Yun-Lei , Ni Jie , Huang Hao , Ip Wai-Hung , Yung Kai-Leung
Published: December 2022

In this work, we propose a road pavement damage detection deep learning model based on feature points from a local minimum of grayscale. First, image blocks, consisting of the neighborhood of feature points, are cut from the image window to form an image block dataset. The image blocks are then input into a convolutional neural network (CNN) to train the model, extracting the image block features. In the testing process, the feature points as well as the image blocks are selected from a test image, and the trained CNN model can output the feature vectors for these feature image blocks. All the feature vectors will be combined to a composite feature vector as the feature descriptor of the test image. At last, the classifier of the model, constructed by a support vector machine (SVM), gives the classification as to whether the image window contains damaged areas or not. The experimental results suggest that the proposed pavement damage detection method based on feature-point image blocks and feature fusion is of high accuracy and efficiency. We believe that it has application potential in general road damage detection, and further investigation is desired in the future.
Effects of Piston Bowl Geometry on Combustion and Emissions of a Four-Stroke Heavy-Duty Diesel Marine Engine
Authors: Pham Van Chien , Kim Jeong Kuk , Lee Won-Ju , Choe Su-Jeong , Le Van Vang , Choi Jae-Hyuk
Published: December 2022

Piston bowl geometry plays an important role in the fuel/air mixing quality which has a direct influence on the performance and emission characteristics of the engine. This work studied the effects of piston bowl geometry on the combustion and emissions of a four-stroke direct injection (DI) heavy-duty diesel marine engine. Three types of piston bowls with various parameters were numerically investigated, targeting to improve engine performance, fuel oil consumption, and emission characteristics. The results pointed out that the ω-type and re-entrant piston bowls enhanced cylinder power by 1.26% and 2.67% while reducing the indicated specific fuel oil consumption (ISFOC) of the engine by 1.06% and 1.60%, respectively, compared to the U-type bowl. Especially, the ω-type and re-entrant piston bowls reduced NO (nitric oxide) emission by up to 25.61% and 46.09%, respectively, owing to lower peak temperatures in comparison to the U-type piston bowl. The results also pointed out that changing the piston bowl type has negligible effects on the engine-out soot and CO2 emission characteristics of the engine. Based on this study, it is highly recommended to utilize the re-entrant piston bowl for four-stroke DI diesel engines to improve both engine performance and fuel oil consumption while reducing NO emission simultaneously.
Special Issue on the Advance of the Mechanical Properties of Dental Materials
Authors: De Stefani Alberto , Bruno Giovanni , Gracco Antonio
Published: December 2022

In the oral environment, restorative and prosthetic materials and appliances are exposed to chemical, thermal and mechanical challenges. The mechanical properties of a material define how it responds to the application of physical force. This Special Issue focuses on all the recent technology that can enhance the mechanical properties of materials used in all of the different branches of dentistry. This Special Issue is closed, but the topic is certainly of interest, and therefore new research will be needed to explore further evolution in dental materials.
Nonhomogeneous Dirichlet Problems with Unbounded Coefficient in the Principal Part
Authors: Motreanu Dumitru
Published: December 2022

The main result of the paper establishes the existence of a bounded weak solution for a nonlinear Dirichlet problem exhibiting full dependence on the solution u and its gradient ∇u in the reaction term, which is driven by a p-Laplacian-type operator with a coefficient G(u) that can be unbounded. Through a special Moser iteration procedure, it is shown that the solution set is uniformly bounded. A truncated problem is formulated that drops that G(u) be unbounded. The existence of a bounded weak solution to the truncated problem is proven via the theory of pseudomonotone operators. It is noted that the bound of the solution for the truncated problem coincides with the uniform bound of the original problem. This estimate allows us to deduce that for an appropriate choice of truncation, one actually resolves the original problem.
Analytical and Numerical Simulations of a Delay Model: The Pantograph Delay Equation
Authors: El-Zahar Essam Roshdy , Ebaid Abdelhalim
Published: December 2022

In this paper, the pantograph delay differential equation y′(t)=ay(t)+byct subject to the condition y(0)=λ is reanalyzed for the real constants a, b, and c. In the literature, it has been shown that the pantograph delay differential equation, for λ=1, is well-posed if c<1, but not if c>1. In addition, the solution is available in the form of a standard power series when λ=1. In the present research, we are able to determine the solution of the pantograph delay differential equation in a closed series form in terms of exponential functions. The convergence of such a series is analysed. It is found that the solution converges for c∈(−1,1) such that ba<1 and it also converges for c>1 when a<0. For c=−1, the exact solution is obtained in terms of trigonometric functions, i.e., a periodic solution with periodicity 2πb2−a2 when b>a. The current results are introduced for the first time and have not been reported in the relevant literature.
Deep Learning Model for Computer-Aided Diagnosis of Urolithiasis Detection from Kidney–Ureter–Bladder Images
Authors: Liu Yi-Yang , Huang Zih-Hao , Huang Ko-Wei
Published: December 2022

Kidney–ureter–bladder (KUB) imaging is a radiological examination with a low cost, low radiation, and convenience. Although emergency room clinicians can arrange KUB images easily as a first-line examination for patients with suspicious urolithiasis, interpreting the KUB images correctly is difficult for inexperienced clinicians. Obtaining a formal radiology report immediately after a KUB imaging examination can also be challenging. Recently, artificial-intelligence-based computer-aided diagnosis (CAD) systems have been developed to help clinicians who are not experts make correct diagnoses for further treatment more effectively. Therefore, in this study, we proposed a CAD system for KUB imaging based on a deep learning model designed to help first-line emergency room clinicians diagnose urolithiasis accurately. A total of 355 KUB images were retrospectively collected from 104 patients who were diagnosed with urolithiasis at Kaohsiung Chang Gung Memorial Hospital. Then, we trained a deep learning model with a ResNet architecture to classify KUB images in terms of the presence or absence of kidney stones with this dataset of pre-processed images. Finally, we tuned the parameters and tested the model experimentally. The results show that the accuracy, sensitivity, specificity, and F1-measure of the model were 0.977, 0.953, 1, and 0.976 on the validation set and 0.982, 0.964, 1, and 0.982 on the testing set, respectively. Moreover, the results demonstrate that the proposed model performed well compared to the existing CNN-based methods and was able to detect urolithiasis in KUB images successfully. We expect the proposed approach to help emergency room clinicians make accurate diagnoses and reduce unnecessary radiation exposure from computed tomography (CT) scans, along with the associated medical costs.
Advances in Multivariate and Multiscale Physiological Signal Analysis
Authors: Lanata Antonio , Nardelli Mimma
Published: December 2022

Physiological systems are characterized by complex dynamics and nonlinear behaviors due to their intricate structural organization and regulatory mechanisms [...]
The Nature of Functional Features of Different Classes of G-Protein-Coupled Receptors
Authors: An Ke , Zhu Xiaohong , Bai Chen
Published: December 2022

G-protein-coupled receptors (GPCRs) are a critical family in the human proteome and are involved in various physiological processes. They are also the most important drug target, with approximately 30% of approved drugs acting on such receptors. The members of the family are divided into six classes based on their structural and functional characteristics. Understanding their structural–functional relationships will benefit us in future drug development. In this article, we investigate the features of protein function, structure, and energy that describe the dynamics of the GPCR activation process between different families. GPCRs straddle the cell membrane and transduce signals from outside the membrane into the cell. During the process, the conformational change in GPCRs that is activated by the binding of signal molecules is essential. During the binding process, different types of signal molecules result in different signal transfer efficiencies. Therefore, the GPCR classes show a variety of structures and activation processes. Based on the experimental crystal structures, we modeled the activation process of the β2 adrenergic receptor (β2AR), glucagon receptor (GCGR), and metabotropic glutamate receptor 2 (mGluR2), which represent class A, B, and C GPCRs, respectively. We calculated their activation free-energy landscapes and analyzed the structure–energy–function relationship. The results show a consistent picture of the activation mechanisms between different types of GPCRs. This could also provide us a way to understand other signal transduction proteins.
Differential Expression of Dickkopf 1 and Periostin in Mouse Strains with High and Low Bone Mass
Authors: Kerschan-Schindl Katharina , Schramek Victoria , Butylina Maria , Föger-Samwald Ursula , Pietschmann Peter
Published: December 2022

By expressing different genes and proteins that regulate osteoclast as well as osteoblast formation, osteocytes orchestrate bone metabolism. The aim of this project was the evaluation of the differences in the osteocytes’ secretory activity in the low bone mass mouse strain C57BL/6J and the high bone mass strain C3H/J. The femura of eight- and sixteen-week-old male C57BL/6J and C3H/J mice—six animals per group—were analyzed. Using immunohistochemistry, osteocytes expressing dickkopf 1, sclerostin, periostin, fibroblast growth factor 23 (FGF23), and osteoprotegerin were detected. By means of the OsteoMeasure-System, 92.173 osteocytes were counted. At the age of eight weeks, approximately twice as many cortical and trabecular osteocytes from the C57BL/6J mice compared to the C3H/J mice expressed dickkopf 1 (p < 0.005). The number of cortical osteocytes expressing sclerostin was also higher in the C57BL/6J mice (p < 0.05). In contrast, the cortical and trabecular osteocytes expressing periostin were twice as high in the C3H/J mice (p < 0.005). The dickkopf 1 expressing osteocytes of the C57BL/6J mice decreased with age and showed a strain-specific difference only in cortical bone by 16 weeks of age (p < 0.05). In the C3H/J mice, the amount of osteocytes expressing periostin tended to increase with age. Thus, strain-related differences were maintained in 16-week-old rodents (p < 0.005). No strain-specific differences in the expression of FGF23 or osteoprotegerin in the cortical compartment could be detected. This experimental study showed that the osteocytes’ protein expression reflects differences in bone characteristics and strain-related differences during skeletal maturation. Besides the osteocytes’ expression of sclerostin, their expression of dickkopf 1 and periostin seems to be important for bone properties as well.
Simulation Palynologists for Pollinosis Prevention: A Progressive Learning of Pollen Localization and Classification for Whole Slide Images
Authors: Zhao Lin-Na , Li Jian-Qiang , Cheng Wen-Xiu , Liu Su-Qin , Gao Zheng-Kai , Xu Xi , Ye Cai-Hua , You Huan-Ling
Published: December 2022

Existing API approaches usually independently leverage detection or classification models to distinguish allergic pollens from Whole Slide Images (WSIs). However, palynologists tend to identify pollen grains in a progressive learning manner instead of the above one-stage straightforward way. They generally focus on two pivotal problems during pollen identification. (1) Localization: where are the pollen grains located? (2) Classification: which categories do these pollen grains belong to? To perfectly mimic the manual observation process of the palynologists, we propose a progressive method integrating pollen localization and classification to achieve allergic pollen identification from WSIs. Specifically, data preprocessing is first used to cut WSIs into specific patches and filter out blank background patches. Subsequently, we present the multi-scale detection model to locate coarse-grained pollen regions (targeting at “pollen localization problem”) and the multi-classifiers combination to determine the fine-grained category of allergic pollens (targeting at “pollen classification problem”). Extensive experimental results have demonstrated the feasibility and effectiveness of our proposed method.
Does Caffeine Supplementation Associated with Paralympic Powerlifting Training Interfere with Hemodynamic Indicators?
Authors: Menezes Jainara Lima , Aidar Felipe J. , Badicu Georgian , Cataldi Stefania , Carvutto Roberto , Silva Ana Filipa , Clemente Filipe Manuel , Cerulli Claudia , de Jesus Joseane Barbosa , Vieira-Souza Lucio Marques , Tranchita Eliana , Brito Ciro José , Fischetti Francesco , Greco Gianpiero
Published: December 2022

Exercise, including resistance exercise with high loads, has positive hemodynamic responses such as reduced systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), Pressure Product Rate (PPR), and estimated myocardial oxygen volume (MVO2). Caffeine (CA), used to improve performance, tends to interfere with BP and HR. This study aimed to analyze the effects of CA supplementation on hemodynamic indicators in Paralympic weightlifting (PP). The exercise was performed on 14 male athletes (32.4 ± 8.5 years; 81.7 ± 21.9 kg) for three weeks. Two conditions were evaluated: supplementation with CA Anhydrous 9 mg/kg and with placebo (PL). The adapted bench press was used, with 5 × 5 at 80% 1RM. We evaluated BP, HR, PPR, and MVO2, before, after, 5, 10, 20, 30, 40, 50, 60 min, and 24 h later. The CA presented higher absolute values in the pressure indicators than the PL, and after 24 h there was an inversion. The HR was higher in the CA and showed a reduction after 10 min. The PPR and MVO2 in the CA presented absolute values greater than the PL, and 24 h later there was an inversion. There was no hypotensive effect, but the use of CA did not present risks related to PPR and MVO2, demonstrating the safe use of this supplement in adapted strength sports.
Characterization of Acinetobacter baumannii Isolated from Raw Milk
Authors: Mohamed Hams M. A. , Abd-Elhafeez Hanan H. , Al-Jabr Omar A. , El-Zamkan Mona A.
Published: December 2022

Acinetobacter baumannii (A. baumannii) is an opportunistic pathogen associated with nosocomial infections. In this study, 100 raw milk samples were collected from Qena, Egypt, and subjected to conventional and molecular assays to determine the presence of A. baumannii and investigate their antimicrobial resistance and biofilm formation. Our findings revealed that, among the 100 samples, Acinetobacter spp. were found in 13 samples based on CHROM agar results. We further characterized them using rpoB and 16S-23SrRNA sequencing and gyrB multiplex PCR analysis and confirmed that 9 out of the 13 Acinetobacter spp. isolates were A. baumannii and 4 were other species. The A. baumannii isolates were resistant to β-lactam drugs, including cefotaxime (44%), ampicillin-sulbactam and levofloxacin (33.3% for each), imipenem, meropenem and aztreonam (22.2% for each). We observed different antimicrobial resistance patterns, with a multi-antibiotic resistant (MAR) index ranging from 0.2 to 0.3. According to the PCR results, blaOXA-51 and blaOXA-23 genes were amplified in 100% and 55.5% of the A. baumannii isolates, respectively, while the blaOXA-58 gene was not amplified. Furthermore, the metallo-β-lactamases (MBL) genes blaIMP and blaNDM were found in 11.1% and 22.2% of isolates, respectively, while blaVIM was not amplified. Additionally, eight A. baumannii isolates (88.8%) produced black-colored colonies on Congo red agar, demonstrating their biofilm production capacity. These results showed that, besides other foodborne pathogens, raw milk should also be examined for A. baumannii, which could be a public health concern.
Human J-Domain Protein DnaJB6 Protects Yeast from [PSI+] Prion Toxicity
Authors: Dolder Richard E. , Kumar Jyotsna , Reidy Michael , Masison Daniel C.
Published: December 2022

Human J-domain protein (JDP) DnaJB6 has a broad and potent activity that prevents formation of amyloid by polypeptides such as polyglutamine, A-beta, and alpha-synuclein, related to Huntington’s, Alzheimer’s, and Parkinson’s diseases, respectively. In yeast, amyloid-based [PSI+] prions, which rely on the related JDP Sis1 for replication, have a latent toxicity that is exposed by reducing Sis1 function. Anti-amyloid activity of DnaJB6 is very effective against weak [PSI+] prions and the Sup35 amyloid that composes them, but ineffective against strong [PSI+] prions composed of structurally different amyloid of the same Sup35. This difference reveals limitations of DnaJB6 that have implications regarding its therapeutic use for amyloid disease. Here, we find that when Sis1 function is reduced, DnaJB6 represses toxicity of strong [PSI+] prions and inhibits their propagation. Both Sis1 and DnaJB6, which are regulators of protein chaperone Hsp70, counteract the toxicity by reducing excessive incorporation of the essential Sup35 into prion aggregates. However, while Sis1 apparently requires interaction with Hsp70 to detoxify [PSI+], DnaJB6 counteracts prion toxicity by a different, Hsp70-independent mechanism.
Cardiac Magnetic Resonance Findings in Patients Recovered from COVID-19 Pneumonia and Presenting with Persistent Cardiac Symptoms: The TRICITY-CMR Trial
Authors: Wojtowicz Dagmara , Dorniak Karolina , Ławrynowicz Marzena , Wąż Piotr , Fijałkowska Jadwiga , Kulawiak-Gałąska Dorota , Rejszel-Baranowska Joanna , Knut Robert , Haberka Maciej , Szurowska Edyta , Koziński Marek
Published: December 2022

The prevalence and clinical consequences of coronavirus disease 2019 (COVID-19)-related non-ischemic cardiac injury are under investigation. The main purpose of this study was to determine the occurrence of non-ischemic cardiac injury using cardiac magnetic resonance (CMR) imaging in patients with persistent cardiac symptoms following recovery from COVID-19 pneumonia. We conducted a single-center, cross-sectional study. Between January 2021 and May 2021, we enrolled 121 patients with a recent COVID-19 infection and persistent cardiac symptoms. Study participants were divided into those who required hospitalization during the acute phase of SARS-CoV-2 infection (n = 58; 47.9%) and those non-hospitalized (n = 63; 52.1%). Non-ischemic cardiac injury (defined as the presence of late gadolinium enhancement (LGE) lesion and/or active myocarditis in CMR) was detected in over half of post-COVID-19 patients (n = 64; 52.9%). LGE lesions were present in 63 (52.1%) and active myocarditis in 10 (8.3%) post-COVID-19 study participants. The majority of LGE lesions were located in the left ventricle at inferior and inferolateral segments at the base. There were no significant differences in the occurrence of LGE lesions (35 (60.3%) vs. 28 (44.4%); p = 0.117) or active myocarditis (6 (10.3%) vs. 4 (6.3%); p = 0.517) between hospitalized and non-hospitalized post-COVID-19 patients. However, CMR imaging revealed lower right ventricular ejection fraction (RVEF; 49.5 (44; 54) vs. 53 (50; 58) %; p = 0.001) and more frequent presence of reduced RVEF (60.3% vs. 33.3%; p = 0.005) in the former subgroup. In conclusion, more than half of our patients presenting with cardiac symptoms after a recent recovery from COVID-19 pneumonia had CMR imaging abnormalities indicating non-ischemic cardiac injury. The most common finding was LGE, while active myocarditis was detected in the minority of patients. CMR imaging abnormalities were observed both in previously hospitalized and non-hospitalized post-COVID-19 patients. Further research is needed to determine the long-term cardiovascular consequences of COVID-19 infection and the optimal management of patients with suspected post-COVID-19 non-ischemic cardiac injury.