bluuebunny/crossref_metadata_2025 huggingface dataset:
RDE Treatment Prevents Non-Specific Detection of SARS-CoV-2- and Influenza-Specific IgG Antibodies in Heat-Inactivated Serum Samples
Authors: Goshina Arina , Matyushenko Victoria , Mezhenskaya Daria , Rak Alexandra , Katelnikova Anastasia , Gusev Denis , Rudenko Larisa , Isakova-Sivak Irina
Published: June 2023

Assessing the levels of serum IgG antibodies is widely used to measure immunity to influenza and the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after natural infection or vaccination with specific vaccines, as well as to study immune responses to these viruses in animal models. For safety reasons, sometimes serum specimens collected from infected individuals are subjected to heat inactivation at 56 °C to reduce the risk of infecting personnel during serological studies. However, this procedure may affect the level of virus-specific antibodies, making the results of antibody immunoassays uninterpretable. Here, we evaluated the effect of the heat inactivation of human, ferret and hamster serum samples on the binding of IgG antibodies to the influenza and SARS-CoV-2 antigens. For this, serum samples of naive and immune hosts were analyzed in three variants: (i) untreated sera, (ii) heated at 56 °C for 1 h, and (iii) treated with receptor-destroying enzyme (RDE). The samples were studied through an in-house enzyme-linked immunosorbent assay (ELISA) using whole influenza virus or recombinant proteins corresponding to nucleocapsid (N) protein and the receptor-binding domain of SARS-CoV-2 Spike (RBD) as antigens. We demonstrated that the heat inactivation of the naive serum samples of various hosts can lead to false-positive results, while RDE treatment abolished the effect of the non-specific binding of IgG antibodies to the viral antigens. Furthermore, RDE also significantly decreased the level of virus-specific IgG antibodies in SARS-CoV-2 and influenza-immune sera of humans and animals, although it is unknown whether it actually removes true virus-specific IgG antibodies or only non-specifically binding artifacts. Nevertheless, we suggest that the RDE treatment of human and animal sera may be useful in preventing false-positive results in various immunoassays, while also neutralizing infectious virus, since the standard protocol for the use of RDE also includes heating the sample at 56 °C.
The Impact of the COVID-19 Pandemic in Postoperative Neurosurgical Infections at a Reference Center in México
Authors: Soto Hernández José Luis , González Luis Esteban Ramírez , Ramírez Guadalupe Reyes , Hernández Carolina Hernández , Torreblanca Natalia Rangel , Morales Verónica Ángeles , Moreno Karen Flores , Peek Miguel Ramos , Jiménez Sergio Moreno
Published: June 2023

The COVID-19 pandemic has had a major global impact on the treatment of hospitalized surgical patients. Our study retrospectively evaluates the impact of the COVID-19 pandemic at a neurosurgical reference center in Mexico City. We compared the number of neurosurgeries, the rate and type of postoperative infections, the causative microorganisms and in-hospital mortality rates in a 4-year period, from the pre-pandemic year 2019 until 2022. A total of 4150 neurosurgical procedures were registered. In 2020 the total number of surgeries was reduced by 36% compared to 2019 OR = 0.689 (95% CI 0.566–0.834) p ≤ 0.001, transnasal/trans sphenoidal pituitary resections decreased by 53%, and spinal surgeries by 52%. The rate of neurosurgical infections increased from 3.5% in 2019 to 5.6% in 2020 (p = 0.002). Regarding the microorganisms that caused infections, gram positive cocci accounted for 43.5% of isolates, Klebsiella spp. and Pseudomonas spp. caused one third of the infections. No significant differences were found for in-hospital mortality nor patterns of resistance to antibiotics. The number of surgeries increased in the last two years, although the infection rate has returned to pre-pandemic levels. We observed a lower impact from subsequent waves of COVID-19 and despite an increase in the number of surgeries, the surgeries have not amounted to the full pre-pandemic levels.
Evidence of Antibiotic Resistance and Virulence Factors in Environmental Isolates of Vibrio Species
Authors: Pandey Rajkishor , Sharma Simran , Sinha Kislay Kumar
Published: June 2023

The outbreak of waterborne diseases such as cholera and non-cholera (vibriosis) is continuously increasing in the environment due to fecal and sewage discharge in water sources. Cholera and vibriosis are caused by different species of Vibrio genus which are responsible for acute diarrheal disease and soft tissue damage. Although incidences of cholera and vibriosis have been reported from the Vaishali district of Bihar, India, clinical or environmental strains have not been characterized in this region. Out of fifty environmental water samples, twelve different biochemical test results confirmed the presence of twenty Vibrio isolates. The isolates were found to belong to five different Vibrio species, namely V. proteolyticus, V. campbellii, V. nereis, V. cincinnatiensis, and V. harveyi. From the identified isolates, 65% and 45% isolates were found to be resistant to ampicillin and cephalexin, respectively. Additionally, two isolates were found to be resistant against six and four separately selected antibiotics. Furthermore, virulent hlyA and ompW genes were detected by PCR in two different isolates. Additionally, phage induction was also noticed in two different isolates which carry lysogenic phage in their genome. Overall, the results reported the identification of five different Vibrio species in environmental water samples. The isolates showed multiple antibacterial resistance, phage induction, and virulence gene profile in their genome.
The Impact of COVID-19 Pandemic on ESBL-Producing Enterobacterales Infections: A Scoping Review
Authors: Mai Ha Thi Thao , Espinoza J. Luis
Published: June 2023

Several studies have reported an increased frequency of colonization and/or infection with antibiotic-resistant bacteria (ARB) during the COVID-19 pandemic. Extended-spectrum beta-lactamase-producing Enterobacterales (ESBL-PE) are a group of bacteria with intrinsic resistance to multiple antibiotics, including penicillins, cephalosporins, and monobactams. These pathogens are easy to spread and can cause difficult-to-treat infections. Here, we summarize the available evidence on the impact of the COVID-19 pandemic on infections caused by ESBL-PE. Using specific criteria and keywords, we searched PubMed, MEDLINE, and EMBASE for articles published up to 30 March 2023 on potential changes in the epidemiology of ESBL-E since the beginning of the COVID-19 pandemic. We identified eight studies that documented the impact of COVID-19 on ESBL-E. Five studies were focused on assessing the frequency of ESBL-PE in patient-derived specimens, and three studies investigated the epidemiological aspects of ESBL-PE infections in the context of the COVID-19 pandemic. Some of the studies that were focused on patient specimens reported a decrease in ESBL-PE positivity during the pandemic, whereas the three studies that involved patient data (1829 patients in total) reported a higher incidence of ESBL-PE infections in patients hospitalized for COVID-19 compared with those with other conditions. There are limited data on the real impact of the COVID-19 pandemic on the epidemiology of ESBL-PE infections; however, patient-derived data suggest that the pandemic has exacerbated the spread of these pathogens.
Polygenic Variants Linked to Oxidative Stress and the Antioxidant System Are Associated with Type 2 Diabetes Risk and Interact with Lifestyle Factors
Authors: Choi Youngjin , Kwon Hyuk-Ku , Park Sunmin
Published: June 2023

Oxidative stress is associated with insulin resistance and secretion, and antioxidant systems are essential for preventing and managing type 2 diabetes (T2DM). This study aimed to explore the polygenic variants linked to oxidative stress and the antioxidant system among those associated with T2DM and the interaction of their polygenic risk scores (PRSs) with lifestyle factors in a large hospital-based cohort (n = 58,701). Genotyping, anthropometric, biochemical, and dietary assessments were conducted for all participants with an average body mass index of 23.9 kg/m2. Genetic variants associated with T2DM were searched through genome-wide association studies in participants with T2DM (n = 5383) and without T2DM (n = 53,318). The Gene Ontology database was searched for the antioxidant systems and oxidative stress-related genes among the genetic variants associated with T2DM risk, and the PRS was generated by summing the risk alleles of selected ones. Gene expression according to the genetic variant alleles was determined on the FUMA website. Food components with low binding energy to the GSTA5 protein generated from the wildtype and mutated GSTA5_rs7739421 (missense mutation) genes were selected using in silico analysis. Glutathione metabolism-related genes, including glutathione peroxidase (GPX)1 and GPX3, glutathione disulfide reductase (GSR), peroxiredoxin-6 (PRDX6), glutamate–cysteine ligase catalytic subunit (GCLC), glutathione S-transferase alpha-5 (GSTA5), and gamma-glutamyltransferase-1 (GGT1), were predominantly selected with a relevance score of >7. The PRS related to the antioxidant system was positively associated with T2DM (ORs = 1.423, 95% CI = 1.22–1.66). The active site of the GASTA proteins having valine or leucine at 55 due to the missense mutation (rs7739421) had a low binding energy (<−10 kcal/mol) similarly or differently to some flavonoids and anthocyanins. The PRS interacted with the intake of bioactive components (specifically dietary antioxidants, vitamin C, vitamin D, and coffee) and smoking status (p < 0.05). In conclusion, individuals with a higher PRS related to the antioxidant system may have an increased risk of T2DM, and there is a potential indication that exogenous antioxidant intake may alleviate this risk, providing insights for personalized strategies in T2DM prevention.
Therapeutic Applications of Plant-Derived Extracellular Vesicles as Antioxidants for Oxidative Stress-Related Diseases
Authors: Kim Manho , Jang Hyejun , Kim Wijin , Kim Doyeon , Park Ju Hyun
Published: June 2023

Extracellular vesicles (EVs) composed of a lipid bilayer are released from various cell types, including animals, plants, and microorganisms, and serve as important mediators of cell-to-cell communication. EVs can perform a variety of biological functions through the delivery of bioactive molecules, such as nucleic acids, lipids, and proteins, and can also be utilized as carriers for drug delivery. However, the low productivity and high cost of mammalian-derived EVs (MDEVs) are major barriers to their practical clinical application where large-scale production is essential. Recently, there has been growing interest in plant-derived EVs (PDEVs) that can produce large amounts of electricity at a low cost. In particular, PDEVs contain plant-derived bioactive molecules such as antioxidants, which are used as therapeutic agents to treat various diseases. In this review, we discuss the composition and characteristics of PDEVs and the appropriate methods for their isolation. We also discuss the potential use of PDEVs containing various plant-derived antioxidants as replacements for conventional antioxidants.
An Exploit Traffic Detection Method Based on Reverse Shell
Authors: Liu Yajing , Cai Ruijie , Yin Xiaokang , Liu Shengli
Published: June 2023

As the most crucial link in the network kill chain, exploiting a vulnerability is viewed as one of the most popular attack vectors to get the control authority of the system, which is dangerous for legal users. Therefore, an effective exploit traffic detection method is urgent. However, current methods are almost based on pattern matching, invalid for encrypted traffic. To address this problem, we propose a reverse shell-based exploit traffic detection method, ETDetector. Our key insight is that the reverse shell attack often coexists with vulnerability exploitation as one of the most popular exploit behaviors. So, we first extract the fusion information feature from original features, such as the packet delay sequence, as input of a decision tree model to identify reverse shell traffic in the shellcode execution stage. Then, we trace suspicious traffic in the shellcode delivery stage by reconstructing the session relationship of the two stages above. Compared with Blatta, using a cyclic neural network to detect early exploit traffic, the detection rate of ETDetector is increased by 50% and valid for encrypted exploit traffic. In addition, we propose a traffic stratification method based on a bisecting K-means algorithm, which can intuitively show the traffic communication behavior and improve the interpretability of ETDetector.
Complete Full Arch Supported by Short Implant (<8 mm) in Edentulous Jaw: A Systematic Review
Authors: Rosa Alessio , Pujia Alberto Maria , Arcuri Claudio
Published: June 2023

Background: This study aimed to evaluate survival rate, marginal bone levels, and full arch prosthetic success on short implants when placed in areas of severely resorbed and edentulous mandibles. Methods: This is a systematic review of all randomized controlled trials of at least 10 patients with a control group in which bone augmentations were performed that were published between January 2010 and February 2023. Only three relevant studies met the inclusion criteria. Results: This review showed that short-term dental implant survival rates ranged from 94.2% to 97.4% with a five-year follow-up, and prosthetic success rates ranged around 62% during the same follow-up. The mean marginal bone level values of the affected short implants ranged from 0.2 mm to 0.6 mm. Conclusions: The data obtained demonstrated that short dental implants positioned with criterion and precision as a full-arch fixed support are a valid therapeutic choice for the medium–long-term rehabilitation of severe edentulous mandibular atrophy.
Regional Infrastructure Planning Support Methodology for Public and Private Electrified Transport: A Mountain Case Study
Authors: D’Alonzo Valentina , Zambelli Pietro , Zilio Samuele , Zubaryeva Alyona , Grotto Andrea , Sparber Wolfram
Published: June 2023

The European Union has seen a strong growth of electric passenger vehicles over the last decade. The steady increase in the number of electric vehicles requires a thorough examination of the current infrastructure and their future development, which are critical to the continuous market growth of this technology. The underdeveloped charging infrastructure is identified as one of the main barriers, next to the purchase price of electric vehicles. Thus, the infrastructure (supply side) and the vehicles (demand side) must coevolve and consider not only the quantitative balance between EVs and charging stations but the interlinkages with social, technical, and economic criteria for the overall system development. In this context, the methods presented in this paper address regional specificities when developing an integrated network of charging infrastructure for private and public passengers transport in an alpine region. The results of the application of the methodology to a mountainous area present the potential for replicability and highlight the importance of considering regional characteristics and of stakeholder involvement.
Breast Cancer Detection in the Equivocal Mammograms by AMAN Method
Authors: Ibrahim Nehad M. , Ali Batoola , Jawad Fatimah Al , Qanbar Majd Al , Aleisa Raghad I. , Alhmmad Sukainah A. , Alhindi Khadeejah R. , Altassan Mona , Al-Muhanna Afnan F. , Algofari Hanoof M. , Jan Farmanullah
Published: June 2023

Breast cancer is a primary cause of human deaths among gynecological cancers around the globe. Though it can occur in both genders, it is far more common in women. It is a disease in which the patient’s body cells in the breast start growing abnormally. It has various kinds (e.g., invasive ductal carcinoma, invasive lobular carcinoma, medullary, and mucinous), which depend on which cells in the breast turn into cancer. Traditional manual methods used to detect breast cancer are not only time consuming but may also be expensive due to the shortage of experts, especially in developing countries. To contribute to this concern, this study proposed a cost-effective and efficient scheme called AMAN. It is based on deep learning techniques to diagnose breast cancer in its initial stages using X-ray mammograms. This system classifies breast cancer into two stages. In the first stage, it uses a well-trained deep learning model (Xception) while extracting the most crucial features from the patient’s X-ray mammographs. The Xception is a pertained model that is well retrained by this study on the new breast cancer data using the transfer learning approach. In the second stage, it involves the gradient boost scheme to classify the clinical data using a specified set of characteristics. Notably, the experimental results of the proposed scheme are satisfactory. It attained an accuracy, an area under the curve (AUC), and recall of 87%, 95%, and 86%, respectively, for the mammography classification. For the clinical data classification, it achieved an AUC of 97% and a balanced accuracy of 92%. Following these results, the proposed model can be utilized to detect and classify this disease in the relevant patients with high confidence.
An Unsupervised Image Denoising Method Using a Nonconvex Low-Rank Model with TV Regularization
Authors: Chen Tianfei , Xiang Qinghua , Zhao Dongliang , Sun Lijun
Published: June 2023

In real-world scenarios, images may be affected by additional noise during compression and transmission, which interferes with postprocessing such as image segmentation and feature extraction. Image noise can also be induced by environmental variables and imperfections in the imaging equipment. Robust principal component analysis (RPCA), one of the traditional approaches for denoising images, suffers from a failure to efficiently use the background’s low-rank prior information, which lowers its effectiveness under complex noise backgrounds. In this paper, we propose a robust PCA method based on a nonconvex low-rank approximation and total variational regularization (TV) to model the image denoising problem in order to improve the denoising performance. Firstly, we use a nonconvex γ-norm to address the issue that the traditional nuclear norm penalizes large singular values excessively. The rank approximation is more accurate than the nuclear norm thanks to the elimination of matrix elements with substantial approximation errors to reduce the sparsity error. The method’s robustness is improved by utilizing the low sensitivity of the γ-norm to outliers. Secondly, we use the l1-norm to increase the sparsity of the foreground noise. The TV norm is used to improve the smoothness of the graph structure in accordance with the sparsity of the image in the gradient domain. The denoising effectiveness of the model is increased by employing the alternating direction multiplier strategy to locate the global optimal solution. It is important to note that our method does not require any labeled images, and its unsupervised denoising principle enables the generalization of the method to different scenarios for application. Our method can perform denoising experiments on images with different types of noise. Extensive experiments show that our method can fully preserve the edge structure information of the image, preserve important features of the image, and maintain excellent visual effects in terms of brightness smoothing.
Dielectric Spectroscopy Studies and Modelling of Piezoelectric Properties of Multiferroic Ceramics
Authors: Lisińska-Czekaj Agata , Czekaj Dionizy , Garbarz-Glos Barbara , Bąk Wojciech , Zate Temesgen Tadeyos , Jeon Jae-Ho
Published: June 2023

Compounds and solid solutions of bismuth ferrite (BiFeO3)—barium titanate (BaTiO3) system are of great scientific and engineering interest as multiferroic and potential high-temperature lead-free piezoelectric materials. In the present paper, the results of research on the synthesis and characterisation of 0.67Bi1.02FeO3–0.33BaTiO3 (67BFBT) ceramics in terms of crystal structure and dielectric and piezoelectric properties are reported. It was found that the produced 67BFBT ceramics were characterised by a tetragonal crystal structure described by the P4mm space group, an average crystallite size  ≈ 80 nm, and an average strain <ε> = 0.01%. Broad-band dielectric spectroscopy (BBDS) was employed to characterise the dielectric response of polycrystalline ceramics. The frequency range from ν = 10−1 Hz to ν = 105 Hz was used to characterise the influence of the electric field strength on dielectric response of the ceramic sample at room temperature. The dielectric spectra were checked for consistency with the Kramers–Kronig test, and the high quality of the measurements were confirmed. The electric equivalent circuit method was used to fit the dielectric spectra within the frequency range that corresponded to the occurrence of the resonant spectra of the radial mode for thin disk sample, i.e., from ν = 105 Hz to ν = 107 Hz and the temperature range from T = −20 °C to T = 50 °C. The electric equivalent circuit [RsCPE1([L1R1C1]C0)] was used, and good fitting quality was reached. The relevant calculations were performed, and it was found that the piezoelectric charge coefficient exhibited a value of d31 = 35 pC/N and the planar coupling factor was kp = 31% at room temperature. Analysis of impedance spectra performed in terms of circumferential magnetic field made it possible to establish an influence of magnetic field on piezoelectric parameters of 67BFBT multiferroic ceramics. Additionally, the “magnetic” tunability of the modulus of the complex dielectric permittivity makes 67BFBT a sensing material with vast potential.
Application of Conditional Generative Adversarial Networks to Efficiently Generate Photon Phase Space in Medical Linear Accelerators of Different Primary Beam Parameters
Authors: Baran Mateusz , Tabor Zbisław , Rzecki Krzysztof , Ziaja Przemysław , Szumlak Tomasz , Kalecińska Kamila , Michczyński Jakub , Rachwał Bartłomiej , Waligórski Michael P. R. , Sarrut David
Published: June 2023

Successful application of external photon beam therapy in oncology requires that the dose delivered by a medical linear accelerator and distributed within the patient’s body is accurately calculated. Monte Carlo simulation is currently the most accurate method for this purpose but is computationally too extensive for routine clinical application. A very elaborate and time-consuming part of such Monte Carlo simulation is generation of the full set (phase space) of ionizing radiation components (mainly photons) to be subsequently used in simulating dose delivery to the patient. We propose a method of generating phase spaces in medical linear accelerators through learning, by artificial intelligence models, the joint multidimensional probability density distribution of the photon properties (their location in space, energy, and momentum). The models are conditioned with respect to the parameters of the primary electron beam (unique to each medical accelerator), which, through Bremsstrahlung, generates the therapeutical beam of ionizing radiation. Two variants of conditional generative adversarial networks are chosen, trained, and compared. We also present the second-best type of deep learning architecture that we studied: a variational autoencoder. Differences between dose distributions obtained in a water phantom, in a test phantom, and in real patients using generative-adversarial-network-based and Monte-Carlo-based phase spaces are very close to each other, as indicated by the values of standard quality assurance tools of radiotherapy. Particle generation with generative adversarial networks is three orders of magnitude faster than with Monte Carlo. The proposed GAN model, together with our earlier machine-learning-based method of tuning the primary electron beam of an MC simulator, delivers a complete solution to the problem of tuning a Monte Carlo simulator against a physical medical accelerator.
Evaluation of Excavation Ergonomics of Drill and Blast Method Based on Game Theory G2-EW-TOPSIS Model
Authors: Yang Chengtao , Zhang Ruiping , Liu Dunwen , Tang Yu , Huang Rendong , Qiu Weichao
Published: June 2023

The demand for tunnel construction continues to grow by leaps and bounds. Therefore, tunnel mechanization construction is receiving more and more attention for improving excavation ergonomics. To enhance the scientific and comprehensive evaluation results of tunnel drilling and blasting method excavation ergonomics, a set of evaluation methods of tunnel drilling and blasting method excavation ergonomics based on the game theory G2-EW-TOPSIS model is proposed. From the three dimensions of drilling efficiency, construction process duration, and synergistic influence factors, a tunnel drilling and blasting construction ergonomics evaluation index system consisting of 11 indicators such as perimeter hole drilling efficiency, drilling duration, construction quality, and comprehensive cost is constructed. The subjective and objective weights of evaluation indicators are calculated by using the improved sequential relationship analysis method (G2 method) and entropy weight method, respectively, and the combination weights are carried out by using game theory method (GTM) with the Nash equilibrium as the goal. The indices are classified into five grades: excellent (I), good (II), average (III), rather poor (IV), and poor (V), according to the daily tunnel construction. The excavation ergonomics index to be evaluated is calculated using the combined weights, and the comprehensive evaluation index of excavation ergonomics to be evaluated is calculated using the technique for order preference by similarity to an ideal solution (TOPSIS). The proposed rating model was used to analyze the excavation ergonomics of the Shangtianling Tunnel in the Chizhou–Huangshan High-Speed Railway using jumbo drills (JD) and drilling machines (DM) in large- and small-mileage construction, respectively, and to obtain the excavation ergonomics rating and comprehensive evaluation rating of each evaluation object. The research results show that the established excavation ergonomics evaluation model can effectively identify the main factors affecting the excavation ergonomics of the drill and blast method, and has a certain reference value.
SAFEPA: An Expandable Multi-Pose Facial Expressions Pain Assessment Method
Authors: Alghamdi Thoria , Alaghband Gita
Published: June 2023

Accurately assessing the intensity of pain from facial expressions captured in videos is crucial for effective pain management and critical for a wide range of healthcare applications. However, in uncontrolled environments, detecting facial expressions from full left and right profiles remains a significant challenge, and even the most advanced models for recognizing pain levels based on facial expressions can suffer from declining performance. In this study, we present a novel model designed to overcome the challenges posed by full left and right profiles—Sparse Autoencoders for Facial Expressions-based Pain Assessment (SAFEPA). Our model utilizes Sparse Autoencoders (SAE) to reconstruct the upper part of the face from the input image, and feeds both the original image and the reconstructed upper face into two pre-trained concurrent and coupled Convolutional Neural Networks (CNNs). This approach gives more weight to the upper part of the face, resulting in superior recognition performance. Moreover, SAFEPA’s design leverages CNNs’ strengths while also accommodating variations in head poses, thus eliminating the need for face detection and upper-face extraction preprocessing steps needed in other models. SAFEPA achieves high accuracy in recognizing four levels of pain on the widely used UNBC-McMaster shoulder pain expression archive dataset. SAFEPA is extended for facial expression recognition, where we show it to outperform state-of-the-art models in recognizing seven facial expressions viewed from five different angles, including the challenging full left and right profiles, on the Karolinska Directed Emotional Faces (KDEF) dataset. Furthermore, the SAFEPA system is capable of processing BioVid Heat Pain datasets with an average processing time of 17.82 s per video (5 s in length), while maintaining a competitive accuracy compared to other state-of-the-art pain detection systems. This experiment demonstrates its applicability in real-life scenarios for monitoring systems. With SAFEPA, we have opened new possibilities for accurate pain assessment, even in challenging situations with varying head poses.
Petrographic and Chemical Characterization of the Frescoes by Saturnino Gatti (Central Italy, 15th Century)
Authors: Germinario Luigi , Giannossa Lorena C. , Lezzerini Marco , Mangone Annarosa , Mazzoli Claudio , Pagnotta Stefano , Spampinato Marcello , Zoleo Alfonso , Eramo Giacomo
Published: June 2023

This study presents the petrographic and chemical characterization of the frescoes in the Church of San Panfilo in Tornimparte (AQ, Italy) by Saturnino Gatti, a prominent painter of the late 15th–early 16th century, known for his exquisite technique, composition, and use of color. The characterization of the frescoes is essential for understanding the materials and techniques used by Gatti, as well as for identifying the stratigraphy and painting phases. Eighteen samples were collected from the original paint layers, later additions (17th century), and restored surfaces, and analyzed by optical microscopy, cathodoluminescence microscopy, scanning electron microscopy (SEM-EDS), μ-Raman, and electron paramagnetic resonance (EPR). The analyses revealed a microstratigraphy often made of three main layers: (1) preparation, consisting of lime plaster and sand; (2) pigmented lime, applied by the fresco technique; and (3) additional pigmented layer on the surface. The most often recurring pigments are black, red, yellow (all generally linked with the fresco technique), and blue (applied “a secco”). The presence of two painting phases was also noted in one sample, probably resulting from a rethinking or restoration. These findings contribute to the understanding of the history and past restoration works of this cultural heritage site, providing important insights not only for conservators and restorers, but also for a broader understanding of Italian fresco painting and art history of the late 15th and early 16th centuries.
Absence of Progressive Bone Loss Following Peri-Implantitis Surgical Therapy with Implantoplasty: A Case Series
Authors: Brincat Arthur , Antezack Angéline , Sadowski Camille , Faure-Brac Mathias , Ohanessian Romain , Monnet-Corti Virginie
Published: June 2023

Background: Peri-implantitis, a bacteria-associated inflammatory disease, is characterized by inflammation of the peri-implant mucosa and progressive loss of the supporting bone, thereby reducing the chances of dental implant survival. The absence of progressive marginal bone loss is crucial for implant success. The aim of this study is to assess the peri-implantitis resolution by measuring the absence of progressive bone loss rate around the implant over a period of one year to more than three years after surgical reconstructive (REC) treatment, apically repositioned flap (ARP) surgery, or combined (COM) treatment of peri-implantitis with implantoplasty. Methods: Peri-implantitis patients, that underwent surgical therapy with implantoplasty and that enrolled in a regular peri-implant supportive care program with a follow up of ≥12 months, were recruited in this study. ARP, REC, or COM surgical therapy was performed depending on the anatomy of the bone defect. For REC and COM groups, intraosseous defects were filled with a bone substitute. The ARP group consisted of an apically positioned flap without osseous surgery. Absence of progressive marginal bone loss was evaluated on radiographs of the treated implants. Results: A total of 57 patients (91 implants) were included. The study occurred over a follow-up period of 12 to 42 months (mean = 24 months). The surgical treatment with implantoplasty yielded an absence of progressive bone loss rate of 96.7% at implant level (100% REC, 98% COM, 92.9% ARP) and 96.5% at patient level. Three implants had to be removed in two patients due to relapse or progression of peri-implantitis. Conclusions: This case series demonstrated that implantoplasty during surgical treatment of peri-implantitis lesions resulted in favorable biological conditions to maintain functional implants with 96.7% of implants that did not show bone loss over time from one year to more than three years.
A Robust Tool Condition Monitoring System Based on Cluster Density under Variable Machining Processes
Authors: Li Zhimeng , Zhong Wen , Liao Weiwen , Cai Yiqun , Zhao Jian , Wang Guofeng
Published: June 2023

Real-time tool condition monitoring (TCM) is becoming more and more important to meet the increased requirement of reducing downtime and ensuring the machining quality of manufacturing systems. However, it is difficult to satisfy both robustness and effectiveness of pattern recognition for a TCM system without using an unsupervised strategy. In this paper, a clustering-based TCM system is proposed that can be used for different machining conditions such as variable cutting parameters, variable cutters, and even variable cutting methods. The solution is based on a significant statistical correlation between tool wear and the distribution of cutting force features, which is revealed through the clustering results obtained from a novel clustering method based on adjacent grids searching (CAGS). This statistical correlation is converted into tool wear status by using an empirical factor that is robust for variable cutting processes. The proposed TCM system is completely unsupervised as a training-free procedure is used in the monitoring process. To verify the effectiveness of the system, a series of experiments are conducted, such as whole life-cycle wear experiment under same milling condition, tool wear experiment under variable milling conditions and tool wear experiment under same turning condition. The prediction accuracy of our system for tool wear experiment under variable milling conditions is 100%, 75% and 75%, respectively. In contrast, BP neural network, Bayesian network and SVM are used for tool wear prediction under the same conditions. Experimental results show the superiority and effectiveness of our TCM system based on cluster density of CAGS over several state-of-the-art supervised methods.
Comparison of Culture Media for In Vitro Expansion of Oral Epithelial Keratinocytes
Authors: Cuadra Giancarlo A. , Shamim Abrar , Shah Raivat , Morgan Joey , Palazzolo Dominic L.
Published: June 2023

Background: Expansion of OKF6/TERT-2 oral epithelial cells in vitro is important for studying the molecular biology of disease and pathology affecting the oral cavity. Keratinocyte serum-free medium (KSFM) is the medium of choice for this cell line. This study compares three media for OKF6/TERT-2 cultures: KSFM, Dulbecco’s Modified Eagle Medium/Nutrient Mixture of Hams F-12 (DMEM/F12), and a composite medium comprised of DMEM/F-12 and KSFM (1:1 v/v), referred to as DFK. The toxicological effects of electronic cigarette liquids (e-liquids) on OKF6/TERT-2 cells cultured in these media were also compared. Methods: Cells were cultured in KSFM, DMEM/F12, or DFK, and cellular morphology, growth, wound healing and the gene expression of mucins and tight junctions were evaluated. Additionally, cytotoxicity was determined after e-liquid exposures. Results: Switching from KSFM to DMEM/F12 or DFK 24 h post-seeding leads to typical cellular morphologies, and these cultures reach confluency faster than those in KSFM. Wound-healing recovery occurred fastest in DFK. Except for claudin-1, there is no difference in expression of the other genes tested. Additionally, e-liquid cytotoxicity appears to be amplified in DFK cultures. Conclusions: DMEM/F12 and DFK are alternative media for OKF6/TERT-2 cell culture to study the molecular biology of disease and pathology, provided cells are initially seeded in KSFM.
Practical Application of Mesh Opportunistic Networks
Authors: Martín-Pascual Miguel Ángel , Andreu-Sánchez Celia
Published: June 2023

Opportunistic networks allow for communication between nearby mobile devices through a radio connection, avoiding the need for cellular data coverage or a Wi-Fi connection. The limited spatial range of this type of communication can be overcome by using nodes in a mesh network. The purpose of this research was to examine a commercial application of electronic mesh communication without a mobile data plan, Wi-Fi, or satellite. A mixed study, with qualitative and quantitative strategies, was designed. An experimental session, in which participants tested opportunistic networks developing different tasks for performance, was carried out to examine the system. Different complementary approaches were adopted: a survey, a focus group, and an analysis of participants’ performance. We found that the main advantage of this type of communication is the lack of a need to use data networks for one-to-one and group communications. Opportunistic networks can be integrated into professional communication workflows. They can be used in situations where traditional telephones and the Internet are compromised, such as at mass events, emergency situations, or in the presence of frequency inhibitors.
Evasion of Gaseous Elemental Mercury from Forest and Urban Soils Contaminated by Historical and Modern Ore Roasting Processes (Idrija, Slovenia)
Authors: Floreani Federico , Pavoni Elena , Gosar Mateja , Covelli Stefano
Published: June 2023

Considerable amounts of gaseous elemental mercury (Hg0) can be released into the atmosphere from Hg-enriched substrates, such as those from former mining areas, posing a potential environmental threat. In this work, Hg0 fluxes at the soil–air interface under natural vegetation covers were measured in various locations within the Idrija Hg mining area (Slovenia) and its surroundings. Sites were selected in order to compare Hg0 fluxes from both forest soils heavily impacted by historical ore roasting and urban soils characterised by a different degree of Hg enrichment due to the natural occurrence of Hg in rocks or recent mining and roasting processes. Replicate measurements at each site were conducted using a non-steady state flux chamber coupled with a real-time Hg0 analyser (Lumex RA-915M). Moreover, topsoil samples (0–2 cm) were analysed for Hg total concentration and speciation. Cinnabar was the predominant Hg form in almost all the sites. Despite Hg0 being undetectable in soils using thermo-desorption, substantial emissions were observed (70.7–701.8 ng m−2 h−1). Urban soils in a naturally enriched area showed on average the highest Hg0 fluxes, whereas relatively low emissions were found at the historical roasting site, which is currently forested, despite the significantly high total Hg content in soils (up to 219.0 and 10,400 mg kg−1, respectively). Overall, our findings confirm that shading by trees or litter may effectively limit the amount of Hg0 released into the atmosphere even from extremely enriched soils, thus acting as a natural mitigation.
Dynamics of a Fractional-Order COVID-19 Epidemic Model with Quarantine and Standard Incidence Rate
Authors: Trisilowati  , Darti Isnani , Musafir Raqqasyi Rahmatullah , Rayungsari Maya , Suryanto Agus
Published: June 2023

In this paper, we propose a fractional-order COVID-19 epidemic model with a quarantine and standard incidence rate using the Caputo fractional-order derivative. The model consists of six classes: susceptible (S), exposed (E), infected (I), quarantined (Q), recovered (R), and deceased (M). In our proposed model, we simultaneously consider the recovery rate and quarantine rate of infected individuals, which has not been considered in other fractional-order COVID-19 epidemic models. Furthermore, we consider the standard incidence rate in the model. For our proposed model, we prove the existence, uniqueness, non-negativity, and boundedness of the solution. The model has two equilibrium points: disease-free equilibrium and endemic equilibrium. Implementing the spectral radius of the next-generation matrix, we obtain the basic reproduction number (R0). The disease-free equilibrium always exists and is locally and globally asymptotically stable only if R0<1. On the other hand, endemic equilibrium exists and is globally asymptotically stable if R0>1. Our numerical simulation confirms the stability properties of the equilibrium. The smaller the order of the derivative, the slower the convergence of the solution of the model. Both the recovery rate and quarantine rate of the infected class are important parameters determining the stability of the equilibrium point. Based on parameter estimation from COVID-19 data in Indonesia, the fractional-order model has better performance than the first-order model for both the calibration and 20-day forecasting of confirmed daily active cases of COVID-19.
Estimates for Generalized Parabolic Marcinkiewicz Integrals with Rough Kernels on Product Domains
Authors: Ali Mohammed , Al-Qassem Hussain
Published: June 2023

We prove Lp estimates of a class of generalized Marcinkiewicz integral operators with mixed homogeneity on product domains. By using these estimates along with an extrapolation argument, we obtain the boundedness of our operators under very weak conditions on the kernel functions. Our results in this paper improve and extend several known results on both generalized Marcinkiewicz integrals and parabolic Marcinkiewicz integrals on product domains.
The Dynamics of a General Model of the Nonlinear Difference Equation and Its Applications
Authors: Moaaz Osama , Altuwaijri Aseel A.
Published: June 2023

This article investigates the qualitative properties of solutions to a general difference equation. Studying the properties of solutions to general difference equations greatly contributes to the development of theoretical methods and provides many pieces of information that may help to understand the behavior of solutions of some special models. We present the sufficient and necessary conditions for the existence of prime period-two and -three solutions. We also obtain a complete perception of the local stability of the studied equation. Then, we investigate the boundedness and global stability of the solutions. Finally, we support the validity of the results by applying them to some special cases, as well as numerically simulating the solutions.
Constructing a Quasi-Liquid Interphase to Enable Highly Stable Zn-Metal Anode
Authors: Wang Junzhang , Xu Zhou , Qin Tengteng , Wang Jintian , Tian Rui , Guo Xingzhong , Wang Zongrong , Luo Zhongkuan , Yang Hui
Published: June 2023

Rechargeable aqueous Zn-metal batteries have attracted widespread attention owing to their safety and low cost beyond Li-metal batteries. However, due to the lack of the solid electrolyte interphase, problems such as dendrites, side reactions and hydrogen generation severely restrict their commercial applications. Herein, a quasi-liquid interphase (QLI) with a “solid–liquid” property is constructed to stabilize the Zn-metal anode. The synergistic effect of solid and liquid behavior ensures the stable existence of QLI and simultaneously enables the interphase dynamic and self-adaptive to the anode evolution. Electrolyte erosion, Zn2+ diffusion and side reactions are inhibited during long-term cycling after introducing QLI, significantly improving the cycling stability and capacity retention of the symmetric and full cells modified with QLI (Zn@QLI), respectively. Constructing an interphase with a quasi-liquid state represents a promising strategy to stabilize the metal anodes in aqueous electrolytes and even extend to organic electrolytes.
The Effects of Obesity on the Inflammatory, Cardiovascular, and Neurobiological Responses to Exercise in Older Adults
Authors: Fico Brandon G. , Maharaj Arun , Pena Gabriel S. , Huang Chun-Jung
Published: June 2023

Obesity with advancing age leads to increased health complications that are involved in various complex physiological processes. For example, inflammation is a critical cardiovascular disease risk factor that plays a role in the stages of atherosclerosis in both aging and obesity. Obesity can also induce profound changes to the neural circuitry that regulates food intake and energy homeostasis with advancing age. Here we discuss how obesity in older adults impacts inflammatory, cardiovascular, and neurobiological functions with an emphasis on how exercise mediates each topic. Although obesity is a reversible disorder through lifestyle changes, it is important to note that early interventions are crucial to prevent pathological changes seen in the aging obese population. Lifestyle modifications such as physical activity (including aerobic and resistance training) should be considered as a main intervention to minimize the synergistic effect of obesity on age-related conditions, such as cerebrovascular disease.
The Role of Sphingolipids in Regulating Vascular Permeability in Idiopathic Pulmonary Fibrosis
Authors: Jayant Girish , Kuperberg Stephen , Somnay Kaumudi , Wadgaonkar Raj
Published: June 2023

Idiopathic pulmonary fibrosis (IPF) is a disease that causes scarring and fibrotic transformation of the lung parenchyma, resulting in the progressive loss of respiratory function and, often, death. Current treatments that target profibrotic factors can slow the rate of progression but are unable to ultimately stop it. In the past decade, many studies have shown that increased vascular permeability may be both a predictive and perpetuating factor in fibrogenesis. Consequently, there is a search for therapeutic targets to try and modulate vascular permeability in fibrotic lungs. One such class of targets that show great promise is sphingolipids. Sphingolipids are common in cell membranes and are increasingly recognized as critical to many cell signaling pathways, including those that affect the integrity of the vascular endothelial barrier. In this focused review we look at sphingolipids, particularly the sphingosine-1-phosphate (S1P) axis and its effects on vascular permeability, and how those effects may affect the pathogenesis of IPF. We further examine existing S1P modulators and their potential efficacy as therapeutics for IPF.