bluuebunny/crossref_metadata_2025 huggingface dataset:
The Investigation of the Effect of a-Tomatine as a Novel Matrix Metalloproteinase Inhibitor on the Bond Strength of Sound and Eroded Dentine through In Vitro and In Silico Methods
Authors: Ucuncu Musa Kazim , Ortaakarsu Ahmet Bugra , Batu Sule , Yildiz Esra
Published: September 2023

This study aims to examine the effect of a-tomatine, a new matrix metalloproteinase inhibitor for dentistry, as a surface pretreatment on the bonding strength of different types of dentine via in vitro and in silico methods. The binding efficacy of both a-tomatine and chlorhexidine to MMP-2, 8, and 9 was evaluated through molecular docking and dynamics analyses. For microtensile testing (µTBS), specimens (n = 84) were categorized into two groups based on the type of dentin: sound (SD) and eroded (ED) (n = 42). Each group was further divided into three subgroups according to the utilization of surface pretreatment agents (1.5 µM of tomatine, 2% chlorhexidine (CHX), and the control). Composite buildups were gradually created via a three-step etch-and-rinse technique. The specimens were sectioned into sticks and subsequently subjected to µTBS after aging for either 24 h (n = 7) or 6 months (n = 7). The data were subjected to analysis using two-way ANOVA with a Bonferroni correction post hoc test. The significance level was evaluated at a minimum of p < 0.05. According to molecular docking and dynamic simulation analyses, a-tomatine exhibits a higher affinity for MMP-2, -8, and -9 enzymes compared to chlorhexidine. Lower µTBS values were observed in all ED groups compared to the SD groups. Following 24-h aging, the CHX application in both the SD and ED groups achieved lower µTBS values compared to the control group (p < 0.01 and p > 0.05, respectively). The most favorable results were consistently achieved across all the subgroups subjected to a-tomatine applications (p < 0.05). a-tomatine is a more effective MMP inhibitor than chlorhexidine in terms of preserving bond strength values over time and its capacity to bind to MMP-2,8, and 9 for inhibition.
Modeling and Analysis of Noise Emission Using Data from Flight Simulators
Authors: Tlałka Filip , Rzucidło Paweł
Published: September 2023

The main goal of this article is to examine the impact of various factors, including the aircraft take-off weight and configuration, on the noise and gaseous emissions. The analysis was based on trajectory data obtained from the X-Plane 11 simulator and a MATLAB noise engine created in accordance with ECAC.CEAC (European Civil Aviation Conference) Doc 29 recommendations. It allowed us to present various noise metrics in the form of noise maps and conduct a general analysis of how certain factors, e.g., flap settings, impact the noise and gaseous emissions. The study indicates that, from the “global” perspective (i.e., the entire airport vicinity), the NADP1 procedure shows better noise reduction, while the NADP2 procedure exhibits lower CO2 emissions. Conversely, from the perspective of individual observers (i.e., the local perspective), it may (but not necessarily) be the case that the NADP2 procedure allows for achieving both minimal noise and CO2 emissions compared to the NADP1 procedure. For example, reducing take-off thrust may reduce the SEL > 85 [dB] area in NADP2 by twice as much as in NADP1, but at the cost of almost four times less CO2 emission reductions. The study may be further developed to find an algorithm for designating individual noise-abatement procedure parameters that will account for various factors in order to minimize the aforementioned emissions.
SANA: Sensitivity-Aware Neural Architecture Adaptation for Uniform Quantization
Authors: Guo Mingfei , Dong Zhen , Keutzer Kurt
Published: September 2023

Uniform quantization is widely taken as an efficient compression method in practical applications. Despite its merit of having a low computational overhead, uniform quantization fails to preserve sensitive components in neural networks when applied with ultra-low bit precision, which could lead to a non-trivial accuracy degradation. Previous works have applied mixed-precision quantization to address this problem. However, finding the correct bit settings for different layers always demands significant time and resource consumption. Moreover, mixed-precision quantization is not well supported on current general-purpose machines such as GPUs and CPUs and, thus, will cause intolerable overheads in deployment. To leverage the efficiency of uniform quantization while maintaining accuracy, in this paper, we propose sensitivity-aware network adaptation (SANA), which automatically modifies the model architecture based on sensitivity analysis to make it more compatible with uniform quantization. Furthermore, we formulated four different channel initialization strategies to accelerate the quantization-aware fine-tuning process of SANA. Our experimental results showed that SANA can outperform standard uniform quantization and other state-of-the-art quantization methods in terms of accuracy, with comparable or even smaller memory consumption. Notably, ResNet-50-SANA (24.4 MB) with W4A8 quantization achieved 77.8% top-one accuracy on ImageNet, which even surpassed the 77.6% of the full-precision ResNet-50 (97.8 MB) baseline.
The Surgical Guides for TADs: The Rational and Laboratory Procedures
Authors: Michiko Aonuma , Shirahama Shingo , Shimizu Atsumoto , Romanec Cristian , Anka George
Published: September 2023

The widespread and popular use of TADs for orthodontic anchoring has become a daily routine in clinical orthodontic treatment. However, as there have been many accidents over the past decade, safety action is needed to help reduce these accidents. We have advocated using the surgical guide and developed a procedure that can benefit patients and orthodontists. The first part of this paper is about the rationale for making the surgical guide for various implant placements that were observed. Due to their anatomical structure, some placements may require particular attention, which is focused on and discussed in length. The second part deals with fabricating the surgical guide in the laboratory procedure. The data from the intraoral SLT acquisition was extracted, and with the DICOM data from CBCT and in a 3-Shapes software, the guidance was designed. The detailed and step-by-step laboratory procedure, CAD/CAM, and 3D printers to make the surgical guide for TADs are explained. The procedure is performed in an easy-to-understand manner to make using the surgical guide possible for the daily practice of orthodontics (Pubmed).
One-Dimensional Consolidation Properties of Soft Clay under Multi-Stage Loading
Authors: Wang Jiangfeng , Yuan Wei , Yin Xuexuan , Li Wenjie , Li Xinya
Published: September 2023

The consolidation characteristics of soft clay under multi-stage loading and single-stage loading exhibit significant differences. In order to investigate the consolidation behavior of soft clay under multi-stage loading, one-dimensional oedometer tests were conducted on marine sedimentary soft clay from northern China. The results indicate that the overall time-deformation pattern of multi-stage loading is a cyclic nonlinear extension of that of single-stage loading. The final deformation between multi-stage loading and single-stage loading is approximately equal; however, the consolidation rate of single-stage loading is four times that of multi-stage loading. Furthermore, the coefficient of consolidation (Cv) decreases with increasing stress. Subsequently, the traditional Terzaghi one-dimensional consolidation equation was modified and a consolidation equation suitable for multi-stage loading is proposed in this study. The analysis of engineering applications demonstrates that the traditional theory provides more accurate predictions of consolidation rate and settlement when the load is small. However, when the load is large, the settlement predicted using the Terzaghi one-dimensional consolidation equation may have an error of 0–25% compared to that using the modified equation. The modified Terzaghi one-dimensional consolidation equation provides a more accurate representation of the actual consolidation of soft soil.
Non-Zero Sum Nash Game for Discrete-Time Infinite Markov Jump Stochastic Systems with Applications
Authors: Liu Yueying , Wang Zhen , Lin Xiangyun
Published: September 2023

This paper is to study finite horizon linear quadratic (LQ) non-zero sum Nash game for discrete-time infinite Markov jump stochastic systems (IMJSSs). Based on the theory of stochastic analysis, a countably infinite set of coupled generalized algebraic Riccati equations are solved and a necessary and sufficient condition for the existence of Nash equilibrium points is obtained. From a new perspective, the finite horizon mixed robust H2/H∞ control is investigated, and summarize the relationship between Nash game and H2/H∞ control problem. Moreover, the feasibility and validity of the proposed method has been proved by applying it to a numerical example.
Attention Deficit-Hyperactivity Disorder (ADHD): From Abnormal Behavior to Impairment in Synaptic Plasticity
Authors: Ugarte Gonzalo , Piña Ricardo , Contreras Darwin , Godoy Felipe , Rubio David , Rozas Carlos , Zeise Marc , Vidal Rodrigo , Escobar Jorge , Morales Bernardo
Published: September 2023

Attention deficit-hyperactivity disorder (ADHD) is a neurodevelopmental disorder with high incidence in children and adolescents characterized by motor hyperactivity, impulsivity, and inattention. Magnetic resonance imaging (MRI) has revealed that neuroanatomical abnormalities such as the volume reduction in the neocortex and hippocampus are shared by several neuropsychiatric diseases such as schizophrenia, autism spectrum disorder and ADHD. Furthermore, the abnormal development and postnatal pruning of dendritic spines of neocortical neurons in schizophrenia, autism spectrum disorder and intellectual disability are well documented. Dendritic spines are dynamic structures exhibiting Hebbian and homeostatic plasticity that triggers intracellular cascades involving glutamate receptors, calcium influx and remodeling of the F-actin network. The long-term potentiation (LTP)-induced insertion of postsynaptic glutamate receptors is associated with the enlargement of spine heads and long-term depression (LTD) with spine shrinkage. Using a murine model of ADHD, a delay in dendritic spines’ maturation in CA1 hippocampal neurons correlated with impaired working memory and hippocampal LTP has recently reported. The aim of this review is to summarize recent evidence that has emerged from studies focused on the neuroanatomical and genetic features found in ADHD patients as well as reports from animal models describing the molecular structure and remodeling of dendritic spines.
Application of a Decisional Capacity Assessment for Older Research Participants with Cognitive Impairment
Authors: Xu Ling , Fields Noelle L. , Westmore Megan R. , Daniel Kathryn M. , Troutman Brooke A.
Published: September 2023

Decisional capacity assessment is important for older adult participants who have cognitive impairment. This paper reports the implementation of the University of California, San Diego Brief Assessment of Capacity to Consent (UBACC) and its potential for practice and research. Nine of the 10 items remained to use except for adapting the last item. Approximately 130 older adults with cognitive impairment completed the UBACC screening. Item-by-item descriptive statistics, exploratory factor analysis (EFA), group comparisons of each item, as well as total sum scores of the UBACC were conducted. Results showed that the items that were most often answered correctly included item #10 (participant will be paid), item #4 (study is voluntary), and item #5 (can withdraw at any time). Conversely, the items that were most often answered incorrectly included item #9 (not any benefit potentially), item #7 (potential risk or discomfort), and item #6 (tasks during participation). Respondents with mild cognitive impairment had higher correct answer rates than those with advanced cognitive impairment. The UBACC screening tool has relative utility for older participants with cognitive impairment.
Predictors of Suicide Risk and Mental Health Outcomes among Hong Kong Veterinarians: A Cross-Sectional Study
Authors: Chan Camille K. Y. , Wong Paul W. C.
Published: September 2023

The professional quality of life (ProQOL) in the veterinary profession has gained increasing attention, yet little is known about its association with the mental health status of Hong Kong veterinarians. This study aimed to examine the impact of elements that make up ProQOL on the risk of suicide, depression, and anxiety among Hong Kong veterinarians. All veterinarians registered and practicing in Hong Kong at the time of recruitment were eligible to take part in the e-survey study between 1 January and 31 March 2022. Binary logistic regression was used to analyze the data from 56 participants. The results showed that 22.0% of the participants were at risk of suicide, 19.6% had current suicidal ideation, 29.4% had depression, and 29.4% had anxiety symptoms. The findings suggested poor mental health status among Hong Kong veterinarians and were comparable to or more prevalent than those reported in Anglophone and European countries. Results from the binary logistic regression suggested that burnout was a predictor of depressive symptoms, and that secondary traumatic stress showed potential in predicting suicide risk. Our study, however, did not find conclusive evidence supporting compassion satisfaction as a predictor of reduced symptoms of common mental issues. Further investigation into contextual factors affecting the mental health of veterinarians in Hong Kong is warranted. Improving the profession’s mental health literacy and self-efficacy should be prioritized as a suicide prevention strategy to enhance mental health awareness.
Impacts of Rooftop Photovoltaics on the Urban Thermal Microclimate: Metrological Investigations
Authors: Fassbender Elisabeth , Pytlik Simon , Rott Josef , Hemmerle Claudia
Published: September 2023

Ambitious climate protection requires decentralized renewable energy production via building-related photovoltaics in cities. However, cities are also subject to the Urban Heat Island effect, which negatively impacts human health. In this context, the installation of PV modules in urban areas raises the question of how the energy-active building component affects its surrounding thermal microclimate. The topic is approached with a novel, twofold methodology: First, a horizontal ambient air temperature profile above a rooftop PV installation and the analysis of surface temperatures provide primal indications of the impacts of PV on the thermal microclimate. Secondly, establishing energy balances allows us to retrace the energy fluxes. The data required for the comparative analyses are gathered through metrological investigations of two rooftops with and without PVs in Munich, Germany. The results of the investigation show a daytime heating effect of photovoltaics on the ambient air temperature of up to +1.35 K and a nighttime cooling effect of up to −1.19 K. Cumulated daily, the daytime heating effect exceeds the impact of the nighttime cooling. The main driver of the heating and cooling is the additional convective heat transfer from the PV modules. However, the impacts of the PV modules are marginal and restricted to their direct surroundings.
Modulation of Notch Signaling by Small-Molecular Compounds and Its Potential in Anticancer Studies
Authors: Czerwonka Arkadiusz , Kałafut Joanna , Nees Matthias
Published: September 2023

Notch signaling is responsible for conveying messages between cells through direct contact, playing a pivotal role in tissue development and homeostasis. The modulation of Notch-related processes, such as cell growth, differentiation, viability, and cell fate, offer opportunities to better understand and prevent disease progression, including cancer. Currently, research efforts are mainly focused on attempts to inhibit Notch signaling in tumors with strong oncogenic, gain-of-function (GoF) or hyperactivation of Notch signaling. The goal is to reduce the growth and proliferation of cancer cells, interfere with neo-angiogenesis, increase chemosensitivity, potentially target cancer stem cells, tumor dormancy, and invasion, and induce apoptosis. Attempts to pharmacologically enhance or restore disturbed Notch signaling for anticancer therapies are less frequent. However, in some cancer types, such as squamous cell carcinomas, preferentially, loss-of-function (LoF) mutations have been confirmed, and restoring but not blocking Notch functions may be beneficial for therapy. The modulation of Notch signaling can be performed at several key levels related to NOTCH receptor expression, translation, posttranslational (proteolytic) processing, glycosylation, transport, and activation. This further includes blocking the interaction with Notch-related nuclear DNA transcription. Examples of small-molecular chemical compounds, that modulate individual elements of Notch signaling at the mentioned levels, have been described in the recent literature.
Prognostic Biomarkers of Cell Proliferation in Colorectal Cancer (CRC): From Immunohistochemistry to Molecular Biology Techniques
Authors: Kasprzak Aldona
Published: September 2023

Colorectal cancer (CRC) is one of the most common and severe malignancies worldwide. Recent advances in diagnostic methods allow for more accurate identification and detection of several molecular biomarkers associated with this cancer. Nonetheless, non-invasive and effective prognostic and predictive testing in CRC patients remains challenging. Classical prognostic genetic markers comprise mutations in several genes (e.g., APC, KRAS/BRAF, TGF-β, and TP53). Furthermore, CIN and MSI serve as chromosomal markers, while epigenetic markers include CIMP and many other candidates such as SERP, p14, p16, LINE-1, and RASSF1A. The number of proliferation-related long non-coding RNAs (e.g., SNHG1, SNHG6, MALAT-1, CRNDE) and microRNAs (e.g., miR-20a, miR-21, miR-143, miR-145, miR-181a/b) that could serve as potential CRC markers has also steadily increased in recent years. Among the immunohistochemical (IHC) proliferative markers, the prognostic value regarding the patients’ overall survival (OS) or disease-free survival (DFS) has been confirmed for thymidylate synthase (TS), cyclin B1, cyclin D1, proliferating cell nuclear antigen (PCNA), and Ki-67. In most cases, the overexpression of these markers in tissues was related to worse OS and DFS. However, slowly proliferating cells should also be considered in CRC therapy (especially radiotherapy) as they could represent a reservoir from which cells are recruited to replenish the rapidly proliferating population in response to cell-damaging factors. Considering the above, the aim of this article is to review the most common proliferative markers assessed using various methods including IHC and selected molecular biology techniques (e.g., qRT-PCR, in situ hybridization, RNA/DNA sequencing, next-generation sequencing) as prognostic and predictive markers in CRC.
Correction for Self-Selection in Breast Cancer Screening. Comment on Dibden et al. Worldwide Review and Meta-Analysis of Cohort Studies Measuring the Effect of Mammography Screening Programmes on Incidence-Based Breast Cancer Mortality. Cancers 2020, 12, 976
Authors: Yaffe Martin J.
Published: September 2023

Observational studies of cancer screening are subject to bias associated with the self-selection of screening participants for whom the underlying probability of cancer death may be different from those who do not participate. Dibden et al. reviewed data on mortality reduction from 27 observational studies of mammography screening expressed in terms of relative risk for women who were screened versus not screened. Results were given, both unadjusted and after application of a correction for self-selection. The correction was based on a constant (1.17)—the ratio of risks of death in screening non-attenders versus those not invited, derived from a Swedish study. For some of the studies this correction had a large effect in diminishing the measured mortality benefit associated with screening. In particular, application to The Pan-Canadian Study of Mammography Screening, a study whose authors had previously tested for and found no evidence of self-selection bias, caused the estimated benefit to decrease from 40% to 10%. The appropriateness of applying a correction based on a constant to a population whose healthcare environment and screening participation rates are very different from those from which it was derived is questionable.
Reply to Yaffe, M.J. Correction for Self-Selection in Breast Cancer Screening. Comment on “Dibden et al. Worldwide Review and Meta-Analysis of Cohort Studies Measuring the Effect of Mammography Screening Programmes on Incidence-Based Breast Cancer Mortality. Cancers 2020, 12, 976”
Authors: Dibden Amanda , Offman Judith , Duffy Stephen W. , Gabe Rhian
Published: September 2023

In his Comment [...]
Advances in Versatile Chiral Ligands for Asymmetric Gold Catalysis
Authors: Wu Yufeng , Yang Hui , Gao Haojie , Huang Xiaoyi , Geng Liyuan , Zhang Rui
Published: September 2023

The formation of valuable chiral skeletons through asymmetric gold catalysis has made considerable progress due to the unrivaled affinity of gold complexes with multiple carbon–carbon bonds. The renaissance of chiral ligands in recent decades has enabled the elaborate design of chiral gold complexes, which are of great significance to control chiral formation in these catalytic reactions. Therefore, this review intends to highlight the design and central role of versatile chiral ligands in asymmetric gold catalysis. Specifically, the seminal applications of various chiral ligands with representative examples in various gold-catalyzed asymmetric reactions are comprehensively explored. In addition, the reaction mechanisms are mentioned when the crucial interactions between ligands and activated substrates are introduced. Furthermore, the applications of enantioselective gold catalysis in the construction of chiral functional organic materials and drug molecules are also presented.
Modulation of Pro-Inflammatory IL-6 Trans-Signaling Axis by Splice Switching Oligonucleotides as a Therapeutic Modality in Inflammation
Authors: Gupta Dhanu , Orehek Sara , Turunen Janne , O’Donovan Liz , Gait Michael J. , El-Andaloussi Samir , Wood Matthew J. A.
Published: September 2023

Interleukin-6 (IL-6) is a pleiotropic cytokine that plays a crucial role in maintaining normal homeostatic processes under the pathogenesis of various inflammatory and autoimmune diseases. This context-dependent effect from a cytokine is due to two distinctive forms of signaling: cis-signaling and trans-signaling. IL-6 cis-signaling involves binding IL-6 to the membrane-bound IL-6 receptor and Glycoprotein 130 (GP130) signal-transducing subunit. By contrast, in IL-6 trans-signaling, complexes of IL-6 and the soluble form of the IL-6 receptor (sIL-6R) signal via membrane-bound GP130. Various strategies have been employed in the past decade to target the pro-inflammatory effect of IL-6 in numerous inflammatory disorders. However, their development has been hindered since these approaches generally target global IL-6 signaling, also affecting the anti-inflammatory effects of IL-6 signaling too. Therefore, novel strategies explicitly targeting the pro-inflammatory IL-6 trans-signaling without affecting the IL-6 cis-signaling are required and carry immense therapeutic potential. Here, we have developed a novel approach to specifically decoy IL-6-mediated trans-signaling by modulating alternative splicing in GP130, an IL-6 signal transducer, by employing splice switching oligonucleotides (SSO), to induce the expression of truncated soluble isoforms of the protein GP130. This isoform is devoid of signaling domains but allows for specifically sequestering the IL-6/sIL-6R receptor complex with high affinity in serum and thereby suppressing inflammation. Using the state-of-the-art Pip6a cell-penetrating peptide conjugated to PMO-based SSO targeting GP130 for efficient in vivo delivery, reduced disease phenotypes in two different inflammatory mouse models of systemic and intestinal inflammation were observed. Overall, this novel gene therapy platform holds great potential as a refined therapeutic intervention for chronic inflammatory diseases.
Association among Orthodontic Malocclusions, Paranasal Sinuses Anatomic Variations and Adenoid Vegetation in Children Using CBCT
Authors: Kose Serdal , Aksoy Secil , Onder Merve , Oz Ulas , Orhan Kaan
Published: September 2023

The aim of this study is to evaluate the relationship between orthodontic malocclusion, paranasal sinus (PS) variations, and adenoid vegetation in a group of pediatric patients with chronic rhinosinusitis. Clinical and radiographical data were retrospectively evaluated and 58 patients were diagnosed as having chronic sinus disease. Cone-beam computed tomography (CBCT) images were acquired with Newtom-3G. Anatomical variations of the PS were assessed on every section. Additionally, for cephalometric analysis, the images were imported into the InVivoDental software program. A total of 252 anatomical variations, which encompassed 19 different types, were detected in the current study. Concha bullosa was the most common anatomical variation, at 72.4%. Septum deviation was the second most common one, at 67.2%. The Class III group exhibited a significantly higher prevalence of concha bullosa and secondary middle turbinate than the other groups. While adenoid vegetation was most common in the Class III group, sinusitis and antral disease were most common in the Class II group. Overall, Class III subjects exhibited fewer PS variations. In conclusion, concha bullosa emerged as the most prevalent anatomical variation, with distinctive patterns observed across different malocclusion groups. Therefore, CBCT is useful, especially in pediatric patients, due to its low dose advantage.
Chitosan-Based Sustainable Coatings for Corrosion Inhibition of Aluminum in Seawater
Authors: Aguilar-Ruiz Ana , Dévora-Isiordia Germán , Sánchez-Duarte Reyna , Villegas-Peralta Yedidia , Orozco-Carmona Víctor , Álvarez-Sánchez Jesús
Published: September 2023

Metals are widely used in various industrial applications due to their advantageous properties, but they often exhibit signs of degradation over time because of prolonged exposure to environmental conditions. To prevent corrosion, coatings have gained popularity owing to their practicality in maintaining the original shape and dimensions of the object being protected. Nevertheless, traditional coatings may pose significant toxicological and environmental concerns, leading researchers to explore eco-friendly alternatives such as chitosan-based coatings. Chitosan, a biopolymer derived from chitin, is abundant in nature and has been extensively studied for its physicochemical properties, including its potential in the development of new materials. Chitosan-based coatings have shown promise as effective corrosion inhibitors, and this study aims to develop a crosslinked chitosan-based coating from shrimp waste as an alternative to expensive, commercial coatings. Chitosan, and chemically modified polyethylene glycol, polyvinylpyrrolidone, and ammonium paratungstate chitosan coatings of high- and medium molecular weight prepared by the sol-gel technique, were used for the study of corrosion protection of aluminum in 3.5% synthetic seawater. The molecular interactions and structural alterations following cross-linking of chitosan-based coatings was supported by FTIR-ATR. Surface morphology analysis by AFM indicated good coating adsorption on aluminum surfaces. Contact angle measurements showed hydrophilic properties with contact angles >62° and <90°. Physicochemical characterization (molecular weight (kDa), deacetylation (%), humidity (%), and ash (%)) was also carried out. The corrosion inhibition effectiveness was assessed by gravimetric tests after immersion studies, and the results highlighted the MMW-Chi-based coating’s performance.
Specification Mining over Temporal Data
Authors: Bergami Giacomo , Appleby Samuel , Morgan Graham
Published: September 2023

Current specification mining algorithms for temporal data rely on exhaustive search approaches, which become detrimental in real data settings where a plethora of distinct temporal behaviours are recorded over prolonged observations. This paper proposes a novel algorithm, Bolt2, based on a refined heuristic search of our previous algorithm, Bolt. Our experiments show that the proposed approach not only surpasses exhaustive search methods in terms of running time but also guarantees a minimal description that captures the overall temporal behaviour. This is achieved through a hypothesis lattice search that exploits support metrics. Our novel specification mining algorithm also outperforms the results achieved in our previous contribution.
Atomic-Level Description of Chemical, Topological, and Surface Morphology Aspects of Oxide Film Grown on Polycrystalline Aluminum during Thermal Oxidation—Reactive Molecular Dynamics Simulations
Authors: Trybula Marcela E. , Żydek Arkadiusz , Korzhvayi Pavel A. , Wojewoda-Budka Joanna
Published: September 2023

Oxidation results in the formation of an oxide film whose properties and structure can be tailored by controlling the oxidation conditions. Reactive molecular dynamics simulations were performed to study thermal oxidation of polycrystalline Al substrates as a function of O2 density and temperature. The structural, chemical, and topological aspects of polycrystalline Al (poly-Al) substrates and oxide films formed upon oxidation were studied. The studies were supported by surface topography and morphology analyses before and after oxidation. An analysis of Al–O atomic pair distribution showed the development of long-range order in the oxide films grown upon exposure to low-density (0.005 g/cm3) and high-density (0.05 g/cm3) O2 gas. The long-range order was more apparent for the high-density environment, as the oxide films formed in low-density O2 gas did not fully cover the poly-Al surface. The dominance of over-coordinated polyhedral units in a tightly packed structure was indicative of medium- and long-range atomic order in the oxide films. The two-phase structure of the oxide was found in the films, with a crystalline phase at the metal/oxide interface and an amorphous phase at the oxide/O2 interface. The combination with topological analyses supported the conclusions of the chemical analysis and enabled us to capture an amorphous-to-crystalline phase transformation in the oxide films with increasing oxygen density and temperature. An important effect of Al surface roughness before oxidation on the behavior of the metal/oxide interface and on the oxide film structure was observed.
Particle Swarm Method for Optimization of ATIG Welding Process to Joint Mild Steel to 316L Stainless Steel
Authors: Touileb Kamel , Djoudjou Rachid , Ouis Abousoufiane , Hedhibi Abdeljlil Chihaoui , Boubaker Sahbi , Ahmed Mohamed M. Z.
Published: September 2023

316L stainless steel joined to mild steel is widespread in several applications to reach a requested good association of mechanical properties at a lower cost. The activating tungsten inert gas (ATIG) weld was carried out using a modified flux composed of 76.63% SiO2 + 13.37% Cr2O3 + 10% NaF to meet standard recommendations in terms of limiting the root penetration. Modified optimal flux gave a depth of penetration 1.84 times greater than that of conventional tungsten inert gas (TIG) welds and a root penetration of up to 0.8 mm. The microstructure of the dissimilar joints was investigated using a scanning electron microscope and EDS analysis. The mechanical properties of the weld were not affected by the modified flux. The results show that the energy absorbed in the fusion zone in the case of ATIG weld (239 J/cm2) is greater than that of TIG weld (216 J/cm2). It was found that the weld bead obtained with the optimal flux combination in ATIG welding can better withstand sudden loads. The obtained UTS value (377 MPa) for ATIG welding was close to that of TIG welding (376 MPa). The average Vickers hardness readings for ATIG welds in the fusion zone are up to 277 HV, compared to 252 HV for conventional TIG welding.
Hybrid Techniques of Facial Feature Image Analysis for Early Detection of Autism Spectrum Disorder Based on Combined CNN Features
Authors: Awaji Bakri , Senan Ebrahim Mohammed , Olayah Fekry , Alshari Eman A. , Alsulami Mohammad , Abosaq Hamad Ali , Alqahtani Jarallah , Janrao Prachi
Published: September 2023

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by difficulties in social communication and repetitive behaviors. The exact causes of ASD remain elusive and likely involve a combination of genetic, environmental, and neurobiological factors. Doctors often face challenges in accurately identifying ASD early due to its complex and diverse presentation. Early detection and intervention are crucial for improving outcomes for individuals with ASD. Early diagnosis allows for timely access to appropriate interventions, leading to better social and communication skills development. Artificial intelligence techniques, particularly facial feature extraction using machine learning algorithms, display promise in aiding the early detection of ASD. By analyzing facial expressions and subtle cues, AI models identify patterns associated with ASD features. This study developed various hybrid systems to diagnose facial feature images for an ASD dataset by combining convolutional neural network (CNN) features. The first approach utilized pre-trained VGG16, ResNet101, and MobileNet models. The second approach employed a hybrid technique that combined CNN models (VGG16, ResNet101, and MobileNet) with XGBoost and RF algorithms. The third strategy involved diagnosing ASD using XGBoost and an RF based on features of VGG-16-ResNet101, ResNet101-MobileNet, and VGG16-MobileNet models. Notably, the hybrid RF algorithm that utilized features from the VGG16-MobileNet models demonstrated superior performance, reached an AUC of 99.25%, an accuracy of 98.8%, a precision of 98.9%, a sensitivity of 99%, and a specificity of 99.1%.
Acute Effects of Running on Shear Wave Elastography Measures of the Achilles Tendon and Calf Muscles in Professional Female Handball and Volleyball Players
Authors: Römer Claudia , Legerlotz Kirsten , Czupajllo Julia , Fischer Thomas , Wolfarth Bernd , Lerchbaumer Markus
Published: September 2023

Shear Wave Elastography (SWE) is currently used to detect tissue pathologies, i.e., tendinopathy. For preventive medicine, it is important to examine the sensitivity of SWE and to investigate how stiffness measures are affected by methodological variables. The aim of this study is to examine shear wave elastography (SWE) measures in order to compare the pre- and post-running values and to determine the correlation between the shear wave speed values (m/s). SWE examinations of the Achilles tendon (AT), soleus muscle (MS) and gastrocnemius muscle (MG)) were performed in 24 healthy professional female athletes. Measurements of the shear wave speed (m/s) were taken before and after incremental treadmill running until exhaustion. Correlations were investigated using the Pearson correlation coefficient and were examined for significance using the Student’s t-test. The pre- and post-exercise shear wave speed did not differ. The pre-exercise and post-exercise stiffness for MS (r = 0.613), MG (r = 0.609) and AT (r = 0.583) correlated strongly. The pre-exercise values and changes in stiffness showed a significant correlation (p < 0.001). In professional athletes, acute exercise induces different tissue stiffness changes in AT, MS and MG for each individual. Thus, exercise activity immediately prior to the SWE measurement needs to be factored in when evaluating tissue stiffness.
The Preparedness of Student Teachers in Open and Distance Learning Environments for the Classroom
Authors: Du Plessis E. C.
Published: September 2023

Teaching practice is crucial to preparing teachers for teacher education globally. Studies on open and distance learning (ODL) environments, in which collaboration and discussion play a crucial role, ought to inform the design of distance learning. They should also force a more in-depth examination of and interest in teaching practice in higher education. Learning is seen as a positive experience, whether entirely lecturer-room-based or distance-based. It is essential to combine theory and practice with efficient distance training as part of work-integrated learning. Consequently, this study aimed to determine the perceived classroom skills of ODL student teachers during the teaching practice sections associated with their Postgraduate Certificate in Education (PGCE) course. The objective of ascertaining the preparedness of ODL student teachers after their PGCE program carries substantial importance in guaranteeing the quality, efficiency, and influence of the education system by cultivating competent and well-equipped teachers. A qualitative research approach was used to gather, analyse, and interpret data. Fifteen (15) student teachers registered at a College of Education of an ODL organisation were invited to participate in the research voluntarily. In the light of the research findings, it is suggested that extra care be given to the collaboration between academic lecturers, mentor teachers and student teachers, as well as to the expectations and duties of these role-players.
Assessing the Enactus Global Sustainability Initiative’s Alignment with United Nations Sustainable Development Goals: Lessons for Higher Education Institutions
Authors: Omotosho Ademola Olumuyiwa , Akintolu Morakinyo , Kimweli Kimanzi Mathew , Modise Motalenyane Alfred
Published: September 2023

Various institutions across the world encourage young people to get involved in community development initiatives and set up small businesses that contribute to the sustainability of society. There is a growing body of literature suggesting that Enactus International is a key stakeholder in this endeavor, as university students’ transformational innovations are developed and exported through Enactus-established collaborations. However, further investigation is required to identify how this phenomenon works. Previous studies have not explored Enactus student teams’ sustainability practices in relation to global goals, and most were limited to the context of a particular institution. As a result, this article examines the relationship between the Enactus sustainability initiative and the United Nations Sustainable Development Goals, thus identifying critical lessons for South African higher education institutions as well as HEIs in other nations facing comparable circumstances. A focused review methodology is used in this analysis to assess the Enactus global sustainability initiative’s alignment with the SDGs, which involves a comprehensive search of the Web of Science and Scopus databases to identify relevant articles. As the year 2030 approaches, the authors warn that university stakeholders’ resistance to change and knowledge gaps about sustainability practices, as well as other limiting factors identified in this study, may impede the attainment of Sustainable Development Goals in the country. This study intends to encourage higher education institutions as change agents, stimulating them to take the lead in overcoming obstacles to the attainment of the SDGs by 2030. The study illuminates cogent approaches necessary for HEIs to create a more sustainable world. It specifically highlights the multidisciplinary perspective and collaborative opportunities offered by SDG-driven organizations.
A DRL-Based Task Offloading Scheme for Server Decision-Making in Multi-Access Edge Computing
Authors: Lim Ducsun , Joe Inwhee
Published: September 2023

Multi-access edge computing (MEC), based on hierarchical cloud computing, offers abundant resources to support the next-generation Internet of Things network. However, several critical challenges, including offloading methods, network dynamics, resource diversity, and server decision-making, remain open. Regarding offloading, most conventional approaches have neglected or oversimplified multi-MEC server scenarios, fixating on single-MEC instances. This myopic focus fails to adapt to computational offloading during MEC server overload, rendering such methods sub-optimal for real-world MEC deployments. To address this deficiency, we propose a solution that employs a deep reinforcement learning-based soft actor-critic (SAC) approach to compute offloading and facilitate MEC server decision-making in multi-user, multi-MEC server environments. Numerical experiments were conducted to evaluate the performance of our proposed solution. The results demonstrate that our approach significantly reduces latency, enhances energy efficiency, and achieves rapid and stable convergence, thereby highlighting the algorithm’s superior performance over existing methods.
Digital Infrastructure Quality Assessment System Methodology for Connected and Automated Vehicles
Authors: Cucor Boris , Petrov Tibor , Kamencay Patrik , Simeonov Marcel , Dado Milan
Published: September 2023

The rapid integration of Connected and Automated Vehicles (CAVs) into modern transportation systems necessitates a robust and systematic approach to assess the quality of the underlying digital infrastructure. In the presented work, we propose a methodology and evaluation of framework that can be used to assess digital infrastructure segments based on their readiness for the deployment of CAVs. The methodology encompasses a comprehensive framework that collects, processes, and evaluates diverse data sources, including real-time traffic, communication, and environmental data. The proposed framework is developed based on experimental data and provides a systematic approach to assess infrastructure readiness for CAVs. The proposed methodology is applied in a system for detecting the readiness status of digital infrastructure from a Cooperative, Connected, and Automated Mobility (CCAM) perspective. The system can determine the percentage of non-compliance of technical service requirements in terms of latency, bandwidth, and localization accuracy. Thanks to this, we can determine in advance in which state the current digital infrastructure is and which services can be currently operated, and thus locate the segments of the route in which the telecommunication systems need to be supported.
Self-Tuning Process Noise in Variational Bayesian Adaptive Kalman Filter for Target Tracking
Authors: Cheng Yan , Zhang Shengkang , Wang Xueyun , Wang Haifeng
Published: September 2023

Many practical systems, such as target tracking, navigation systems, autonomous vehicles, and other applications, are usually applied in dynamic conditions. Thus, the actual noise statistics characteristics of these systems are generally time varying and unknown, which will deteriorate the state estimation accuracy of the Kalman filter (KF) and even cause filter diverging. To address this issue, this paper proposes an adaptive process noise covariance (Qk)-based variational Bayesian adaptive Kalman filter (AQ-VBAKF) algorithm. Firstly, the adaptive factor is introduced to self-tune the process noise covariance; the adaptive factor is obtained based on the innovation sequences, which can adapt to the input measurement values. Then, the VB solution is applied to approximate the time variant and unknown measurement noise covariance. Therefore, this proposed algorithm can adjust the process noise covariance and the measurement noise covariance simultaneously based on the variable input signals, which can improve the self-adaptive ability of the state estimation filter in dynamic conditions. According to the dynamic target tracking test results, the proposed AQ-VBAKF outperforms several other existing filtering methods in estimation accuracy, robustness, and computational efficiency.
Fully Automatic Approach for Smoke Tracking Based on Deep Image Quality Enhancement and Adaptive Level Set Model
Authors: Daoudi Rimeh , Mouelhi Aymen , Bouchouicha Moez , Moreau Eric , Sayadi Mounir
Published: September 2023

In recent decades, the need for advanced systems with good precision, low cost, and high-time response for wildfires and smoke detection and monitoring has become an absolute necessity. In this paper, we propose a novel, fast, and autonomous approach for denoising and tracking smoke in video sequences captured from a camera in motion. The proposed method is based mainly on two stages: the first one is a reconstruction and denoising path with a novel lightweight convolutional autoencoder architecture. The second stage is a specific scheme designated for smoke tracking, and it consists of the following: first, the foreground frames are extracted with the HSV color model and textural features of smoke; second, possible false detections of smoke regions are eliminated with image processing technique and last smoke contours detection is performed with an adaptive nonlinear level set. The obtained experimental results exposed in this paper show the potential of the proposed approach and prove its efficiency in smoke video denoising and tracking with a minimized number of false negative regions and good detection rates.
Enhancing the Transferability of Targeted Attacks with Adversarial Perturbation Transform
Authors: Deng Zhengjie , Xiao Wen , Li Xiyan , He Shuqian , Wang Yizhen
Published: September 2023

The transferability of adversarial examples has been proven to be a potent tool for successful attacks on target models, even in challenging black-box environments. However, the majority of current research focuses on non-targeted attacks, making it arduous to enhance the transferability of targeted attacks using traditional methods. This paper identifies a crucial issue in existing gradient iteration algorithms that generate adversarial perturbations in a fixed manner. These perturbations have a detrimental impact on subsequent gradient computations, resulting in instability of the update direction after momentum accumulation. Consequently, the transferability of adversarial examples is negatively affected. To overcome this issue, we propose an approach called Adversarial Perturbation Transform (APT) that introduces a transformation to the perturbations at each iteration. APT randomly samples clean patches from the original image and replaces the corresponding patches in the iterative output image. This transformed image is then used to compute the next momentum. In addition, APT could seamlessly integrate with other iterative gradient-based algorithms, incurring minimal additional computational overhead. Experimental results demonstrate that APT significantly enhances the transferability of targeted attacks when combined with traditional methods. Our approach achieves this improvement while maintaining computational efficiency.