bluuebunny/crossref_metadata_2025 huggingface dataset:
Owens–Wendt Characterization of Femtosecond-Laser-Textured Hydrophobic Aluminum Surfaces
Authors: Myronyuk Oleksiy , Baklan Denys , Rodin Aleksej M. , Vanagas Egidijus , Yong Zuo
Published: June 2023

The eligibility of applying the Owens–Wendt approach to determining the free surface energy of liquid-repellent aluminum surfaces, with micro- and nanotextures formed by a femtosecond laser, was considered. This approach has been shown to be applicable using two essential parameters that can be derived from the graphs. The first is related to the fraction of the contact area between the liquid and the solid surface in the Cassie state. The second is related to the degree of intrinsic polarity of the surface material or the applied organic modifier. The presented interpretation was used to compare the liquid repellency of the obtained textures. A microtexture with a period of 60 μm and a groove width of 45 μm has been shown to be the most liquid repellent. Among the modifiers, 1H,1H,2H,2H-perfluoroctyltriethoxysilane was the most effective, and stearic acid was only slightly inferior, but promising in terms of cost and environmental friendliness. It was shown that spontaneous hydrophobization provided a contact angle with water up to 159°, but the stability of such textures was inferior to the considered modifiers.
Cell Response on Laser-Patterned Ti/Zr/Ti and Ti/Cu/Ti Multilayer Systems
Authors: Petrović Suzana , Božinović Nevena , Rajić Vladimir , Stanisavljević Ninković Danijela , Kisić Danilo , Stevanović Milena J. , Stratakis Emmanuel
Published: June 2023

Arranged patterns obtained via ultrafast laser processing on the surface of Ti/Cu/Ti/Si and Ti/Zr/Ti/Si thin-film systems are reported. Two differently designed multilayer thin films Ti/Cu/Ti/Si and Ti/Zr/Ti/Si were deposited on silicon using the ion sputtering method. The bioactive surfaces of these systems involve the formation of laser-induced periodic surface structures (LIPSS) in each of the laser-written lines of mesh patterns on 5 × 5 mm areas. The formation of nano- and micro-patterns with an ultra-thin oxide film on the surfaces was used to observe the effects of morphology and proliferation of the MRC-5 cell culture line. To determine whether Ti-based thin films have a toxic effect on living cells, an MTT assay was performed. The relative cytotoxic effect, as a percentage of surviving cells, showed that there was no difference in cell number between the Ti-based thin films and the control cells. There was also no difference in the viability of the MRC-5 cells, except for the Ti/Cu/Ti/Si system, where there was a slight 10% decrease in cell viability.
Preparation and Performance Characterization of an Active Luminous Coating for Asphalt Pavement Marking
Authors: Wang Kaifeng , Lu Ziyu , Zou Yingxue , Zhu Yunsheng , Yu Junhui
Published: June 2023

For improving the night recognition of road markings and enhancing the driving safety of asphalt pavements, single-factor optimization is used to investigate the effects of the component materials, including luminescent power, pigment, filler, and anti-sedimentation agent, on the luminous performance of a coating. Additionally, their composition ratios are optimized using response surface methodology. A phosphorescent marking coating is prepared to investigate the micromorphology, excitation, and emission properties using scanning electron microscopy (SEM) and molecular fluorescence spectroscopy (MFS). The optimum thickness of the coating on an asphalt pavement is investigated, and the durability of the coating on asphalt pavement using a wheel rutting test is evaluated. The results show that the 300 mesh yellow-green luminous powder has the optimal overall performance, with an initial luminescence that exceeds that of orange and sky blue by three times. Initial brightness is mainly influenced by aluminate luminescent powder (ALP), which increases with the dosage. ALP and fumed silica powder (FSP) have a positive effect on brightness after centrifugation, and the effect of FSP dosage is more significant. ALP, rutile titanium dioxide powder (RTDP), and FSP influence the wear value of the coating, and the magnitude of the effect is RTDP > FSP > ALP. The optimal dosages of the main component are 27% ALP, 5% RTDP, and 0.8% FSP. The results of SEM show that the components in the coating are evenly dispersed, and the surface of the coating is rough. The peak excitation wavelength of 420 nm means that the coating has the best excitation effect in UV light, and its emission spectrum in the 440–760 nm wavelength range is well within the sensitive recognition zone of the human eye. The initial brightness gradually reached 4.38 cd/m2 when the coating thickness was increased from 482 μm to 546 μm, and the optimal application thickness of the luminous coating was determined to be 500 μm. At high and normal temperatures, the rutting stripping rates of the luminous marking coating are 16.8% and 8.2%, indicating its satisfactory durability. This study provides an experimental basis for the ratio optimization design of a luminous coating for asphalt pavements.
Seeking the Oxidation Mechanism of Debris in the Fretting Wear of Titanium Functionalized by Surface Laser Treatments
Authors: Marco de Lucas María del Carmen , Torrent Franck , Pillon Gianni-Paolo , Berger Pascal , Lavisse Luc
Published: June 2023

Surface laser treatment (SLT) using nanosecond IR lasers has been shown to improve the tribological behaviour of titanium. Here, we studied the fretting wear of SLT-functionalized pure titanium in a mixture of reactive gases O2 (20 vol.%) + N2 (80 vol.%). The contact geometry was a ball on a plane and the ball was made of bearing steel. The very small amplitude of relative displacement between reciprocating parts in fretting wear makes the evacuation of wear particles difficult. Moreover, the oxidation mechanism of the debris depends on the accessibility of the surrounding atmosphere to the tribological contact. This work focused in the analysis of debris generation and oxidation mechanisms, and sought to differentiate the role of oxygen forming part of the ambient O2 + N2 gas mixture from oxygen present in the surface layer of the SL-treated titanium. Before the fretting test, the surface of the commercially pure titanium plates was treated with a laser under a mixture of O2 + N2 gases with oxygen enriched in the 18O isotope. Then, the fretting tests were performed in regular air containing natural oxygen. Micro-Raman spectroscopy and ion beam analysis (IBA) techniques were used to analyse the TiO2 surface layers and fretting scars. Iron oxide particles were identified by Raman spectroscopy and IBA as the third body in the tribological contact. The spatial distribution of 18O, Ti, 16O and Fe in the fretting scars was studied by IBA. The analysis showed that the areas containing high concentrations of Fe displayed also high concentrations of 16O, but smaller concentrations of 18O and Ti. Therefore, it was concluded that tribological contact allows the oxidation of iron debris by its reaction with ambient air.
Mechanical Properties and Creep Behavior of Undoped and Mg-Doped GaN Thin Films Grown by Metal–Organic Chemical Vapor Deposition
Authors: Khalfallah Ali , Benzarti Zohra
Published: June 2023

This paper investigates the mechanical properties and creep behavior of undoped and Mg-doped GaN thin films grown on sapphire substrates using metal–organic chemical vapor deposition (MOCVD) with trimethylgallium (TMG) and bis(cyclopentadienyl)magnesium (Cp2Mg) as the precursors for Ga and Mg, respectively. The Mg-doped GaN layer, with a [Mg]/[TMG] ratio of 0.33, was systematically analyzed to compare its mechanical properties and creep behavior to those of the undoped GaN thin film, marking the first investigation into the creep behavior of both GaN and Mg-doped GaN thin films. The results show that the incorporated [Mg]/[TMG] ratio was sufficient for the transition from n-type to p-type conductivity with higher hole concentration around 4.6×1017 cm−3. Additionally, it was observed that Mg doping impacted the hardness and Young’s modulus, leading to an approximately 20% increase in these mechanical properties. The creep exponent is also affected due to the introduction of Mg atoms. This, in turn, contributes to an increase in pre-existing dislocation density from 2 × 108 cm−2 for undoped GaN to 5 × 109 cm−2 for the Mg-doped GaN layer. The assessment of the creep behavior of GaN and Mg-doped GaN thin films reveals an inherent creep mechanism governed by dislocation glides and climbs, highlighting the significance of Mg doping concentration in GaN thin films and its potential impact on various technological applications.
Metal-Free Counter Electrodes for DSSCs Based on Nitrogen-Doped Reduced Graphene Oxide Materials
Authors: Duerto Isolda , Carrera Clara , Barrios Daniel , Benito Ana M. , Maser Wolfgang K. , Villacampa Belén , García-Bordejé Enrique , Blesa María-Jesús
Published: June 2023

The importance of counter electrodes in Dye Sensitized Solar Cells (DSSCs) cannot be neglected as they enable the transfer of electrons across the outer circuit, thereby facilitating the reduction reaction of the I3−/I− redox electrolyte. However, the dissolution and deposition of the usual platinum layer on the counter electrode has resulted in contamination concerns. To address this issue, metal-free counter electrodes made of reduced graphene oxide (rGO) aerogels were developed and their catalytic performance towards I3− reduction was evaluated. The reduced graphene materials were characterized, and the fitting analysis of XPS revealed the presence of various nitrogen species, with the primary peaks attributed to pyridinic and pyrrolic nitrogen. The hydrothermal treatment of graphene oxide (GO) resulted in a higher graphitic character and the intensification of the contacts between graphene nanosheets, which should entail higher electrical conductivity, both in-plane and between rGO sheets. Additionally, the presence of nitrogen-provided active sites promoted the catalytic reduction of the electrolyte. Encouragingly, good charge transfer rates were observed between the counter electrode and the electrolyte in the assembled DSSCs, resulting in good photocurrents and exceptional stability over the course of nearly 1200 h after cell assembly. The results obtained suggest that these GO-based systems are promising candidates for developing metal-free counter electrodes for DSSC, supporting the interest of further study.
Spherical Subspace Potential Functional Theory
Authors: Nagy Ágnes
Published: June 2023

The recently introduced version of the density functional theory that employs a set of spherically symmetric densities instead of the density has a ‘set-representability problem’. It is not known if a density exists for a given set of the spherically symmetric densities. This problem can be eliminated if potentials are applied instead of densities as basic variables. Now, the spherical subspace potential functional theory is established.
A Learning Framework for Supporting Digital Innovation Hubs
Authors: Sarraipa Joao , Zamiri Majid , Marcelino-Jesus Elsa , Artifice Andreia , Jardim-Goncalves Ricardo , Moalla Néjib
Published: June 2023

With the increasing demand for digital transformation and (digital) technology transfer (TT), digital innovation hubs (DIHs) are the new piece of the puzzle of our economy and industries’ landscapes. Evidence shows that DIHs can provide good opportunities to access needed innovations, technologies, and resources at a higher level than other organizations that can normally access them. However, it is critically important to note that DIHs are still evolving, under research, and under development. That is, there are many substantial aspects of DIHs that should be considered. For example, DIHs must cater to a wide spectrum of needs for TT. From this perspective, the contribution of this work is proposing a generic and flexible learning framework, aiming to assist DIHs in providing suitable education, training, and learning services that support the process of (digital) TT to companies. The proposed learning framework was designed, evaluated, and improved with the support of two EU projects, and these processes are discussed in brief. The primary and leading results gained in this way show that the learning framework has immense potential for application to similar cases, and it can facilitate and expedite the process of TT to companies. The study is concluded with some directions for future works.
Research on PoW Protocol Security under Optimized Long Delay Attack
Authors: Feng Tao , Liu Yufeng
Published: June 2023

In the blockchain network, the communication delay between different nodes is a great threat to the distributed ledger consistency of each miner. Blockchain is the core technology of Bitcoin. At present, some research has proven the security of the PoW protocol when the number of delay rounds is small, but in complex asynchronous networks, the research is insufficient on the security of the PoW protocol when the number of delay rounds is large. This paper improves the proposed blockchain main chain record model under the PoW protocol and then proposes the TOD model, which makes the main chain record in the model more close to the actual situation and reduces the errors caused by the establishment of the model in the analysis process. By comparing the differences between the TOD model and the original model, it is verified that the improved model has a higher success rate of attack when the probability of mining the delayable block increases. Then, the long delay attack is improved on the balance attack in this paper, which makes the adversary control part of the computing power and improves the success rate of the adversary attack within a certain limit.
Structural, Morphological and Dielectric Characterization of BiFeO3 Fibers Grown by the LFZ Technique
Authors: Peixoto Marina Vieira , Costa Florinda Mendes , Devesa Susana , Graça Manuel Pedro Fernandes
Published: June 2023

BiFeO3 fibers were prepared by the Laser Floating Zone (LFZ) technique using different growth speeds. The structural characterization of the samples was undertaken using X-ray diffraction (XRD) and Raman spectroscopy, the morphological characterization by scanning electron microscopy (SEM), and the electrical characterization by impedance spectroscopy. The XRD patterns showed that BiFeO3 was the major phase in all the samples. Fibers grown at 10 mm/h showed more promising structural and morphological properties. The dielectric characterization revealed that all samples have at least one dielectric relaxation phenomenon that is thermally activated. It was also verified that the dielectric constant is higher at a growth pull rate speed of 10 mm/h.
Sexual Selection and Proteinaceous Diversity in the Femoral Gland Secretions of Lacertid Lizards
Authors: Mangiacotti Marco , Baeckens Simon , Fumagalli Marco , Martín José , Scali Stefano , Sacchi Roberto
Published: June 2023

Sexual selection contributes to the diversity of chemical signals in various animal groups. Lizards are good model species to study how sexual selection shapes signal diversity, as they are a chemically oriented taxonomic group with different levels of social interactions. Many lizard species bear epidermal glands secreting a waxy mixture of lipids and proteins, which are used in intraspecific communication. Previous among-species comparative analyses failed to find a relationship between the strength of sexual selection with the composition of the lipid blend in lizards. Here, we extend the investigation to the proteinaceous fraction. By using a phylogenetically informed approach, we correlated the average electrophoretic profiles of the protein from the femoral glands of 36 lacertid lizard species with the level of sexual dimorphism in size and shape, which are proxies for the strength of sexual selection. We found that as sexual size dimorphism advances, five distinct molecular weight regions in the protein profile increased their expression. Using tandem mass spectrometry, we successfully identified one of these five proteins: a carbonic anhydrase—an enzyme catalyzing the reversible hydration of carbon dioxide. Our findings suggest that proteins may be the target of sexual selection, as an active semiochemicals or as a dynamic support to other molecules: sexual selection may act indirectly on semiochemicals (namely lipids) by modifying the matrix (namely proteins).
Performance Explorations of a PMS Motor Drive Using an ANN-Based MPPT Controller for Solar-Battery Powered Electric Vehicles
Authors: Viswa Teja Anjuru , Razia Sultana Wahab , Salkuti Surender Reddy
Published: June 2023

Solar energy can function as a supplementary power supply for other renewable energy sources. On average, Vellore region experiences approximately six hours of daily sunshine throughout the year. Solar photovoltaic (PV) modules are necessary to monitor and fulfill the energy requirements of a given day. An artificial neural network (ANN) based maximum power point tracking (MPPT) controller is utilised to regulate the solar photovoltaic (PV) array and enhance its output. The utilisation of this controller can enhance the efficiency of the module even in severe circumstances, where reduced current and torque ripples will be observed on the opposite end. The motorised vehicle has the capability to function at its highest torque level in different load scenarios as a result. The proposed method is expected to provide advantages in various electric vehicle (EV) applications that require consistent velocity and optimal torque to satisfy the load conditions. The study employs a solar battery that is linked to an SVPWM inverter and subsequently a DC-DC boost converter to supply power to the load. An Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) control system is proposed for a solar battery powered Electric Vehicle (EV) and the system’s performance is evaluated by collecting and analysing data under adjustable load conditions to obtain constant parameters such as speed and torque. The MATLAB® Simulink® model was utilised for this purpose.
Identifying Optical Coherence Tomography Markers for Multiple Sclerosis Diagnosis and Management
Authors: Cujba Larisa , Stan Cristina , Samoila Ovidiu , Drugan Tudor , Benedec (Cutas) Ancuta , Nicula Cristina
Published: June 2023

Background: Multiple sclerosis (MS) is a common neurological disease affecting the optic nerve, directly or indirectly, through transsynaptic axonal degeneration along the visual pathway. New ophthalmological tools, arguably the most important being optical coherence tomography (OCT), could prove paramount in redefining MS diagnoses and shaping their follow-up protocols, even when the optic nerve is not involved. Methods: A prospective clinical study was conducted. In total, 158 eyes from patients previously diagnosed with relapsing remitting MS (RRMS)—with or without optic neuritis (ON), clinically isolated syndrome (CIS) with or without ON, and healthy controls were included. Each patient underwent an ophthalmologic exam and OCT evaluation for both eyes (a posterior pole analysis (PPA) and the optic nerve head radial circle protocol (ONH-RC)). Results: The macular retinal thickness (the 4 × 4, respectively, 2 × 2 grid) and thickness of the peripapillary retinal nerve fiber layer (pRNFL) were investigated. Various layers of the retina were also compared. Our study observed significant pRNFL thinning in the RRMS eyes compared to the control group, the pRNFL atrophy being more severe in the RRMS-ON eyes than the RRMS-NON eyes. In the ON group, the macular analysis showed statistically significant changes in the RRMS-ON eyes when compared only to the CIS-ON eyes, regarding decreases in the inner plexiform layer (IPL) thickness and inner nuclear layer (INL) on the central 2 × 2 macular grid. The neurodegenerative process affected both the inner retina and pRNFL, with clinical damage appearing for the latter in the following order: CIS-NON, CIS-ON, RRMS-NON, and RRMS-ON. In the presence of optic neuritis, SMRR patients presented an increase in their outer retina thickness compared to CIS patients. Conclusions: To differentiate the MS patients from the CIS patients, in the absence of optic neuritis, OCT Posterior Pole Analysis could be a useful tool when using a central 2 × 2 sectors macular grid. Retinal changes in MS seem to start from the fovea and spread to the posterior pole. Finally, MS could lead to alterations in both the inner and outer retina, along with pRNFL.
Advantages and Limitations of Ultrasound as a Screening Test for Ovarian Cancer
Authors: Koutras Antonios , Perros Paraskevas , Prokopakis Ioannis , Ntounis Thomas , Fasoulakis Zacharias , Pittokopitou Savia , Samara Athina A. , Valsamaki Asimina , Douligeris Athanasios , Mortaki Anastasia , Sapantzoglou Ioakeim , Katrachouras Alexandros , Pagkalos Athanasios , Symeonidis Panagiotis , Palios Vasileios-Chrysovalantis , Psarris Alexandros , Theodora Marianna , Antsaklis Panos , Makrydimas George , Chionis Athanasios , Daskalakis Georgios , Kontomanolis Emmanuel N.
Published: June 2023

Ovarian cancer (OC) is the seventh most common malignancy diagnosed among women, the eighth leading cause of cancer mortality globally, and the most common cause of death among all gynecological cancers. Even though recent advances in technology have allowed for more accurate radiological and laboratory diagnostic tests, approximately 60% of OC cases are diagnosed at an advanced stage. Given the high mortality rate of advanced stages of OC, early diagnosis remains the main prognostic factor. Our aim is to focus on the sonographic challenges in ovarian cancer screening and to highlight the importance of sonographic evaluation, the crucial role of the operator΄s experience, possible limitations in visibility, emphasizing the importance and the necessity of quality assurance protocols that health workers have to follow and finally increasing the positive predictive value. We also analyzed how ultrasound can be combined with biomarkers (ex. CA-125) so as to increase the sensitivity of early-stage OC detection or, in addition to the gold standard examination, the CT (Computed tomography) scan in OC follow–up. Improvements in the performance and consistency of ultrasound screening could reduce the need for repeated examinations and, mainly, ensure diagnostic accuracy. Finally, we refer to new very promising techniques such as liquid biopsies. Future attempts in order to improve screening should focus on the identification of features that are unique to OC and that are present in early-stage tumors.
A Novel Diagnostic Imaging Method for the Early Detection of Pancreatic Cancer
Authors: Kikuyama Masataka
Published: June 2023

Pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis, with a survival rate of less than 10% [...]
Editorial on Special Issue “Medical Data Processing and Analysis”
Authors: Mustafa Wan Azani , Alquran Hiam
Published: June 2023

Medical data plays an essential role in several applications in the medical field [...]
The Role of Non-Invasive Multimodality Imaging in Chronic Coronary Syndrome: Anatomical and Functional Pathways
Authors: Bergamaschi Luca , Pavon Anna Giulia , Angeli Francesco , Tuttolomondo Domenico , Belmonte Marta , Armillotta Matteo , Sansonetti Angelo , Foà Alberto , Paolisso Pasquale , Baggiano Andrea , Mushtaq Saima , De Zan Giulia , Carriero Serena , Cramer Maarten-Jan , Teske Arco J. , Broekhuizen Lysette , van der Bilt Ivo , Muscogiuri Giuseppe , Sironi Sandro , Leo Laura Anna , Gaibazzi Nicola , Lovato Luigi , Pontone Gianluca , Pizzi Carmine , Guglielmo Marco
Published: June 2023

Coronary artery disease (CAD) is one of the major causes of mortality and morbidity worldwide, with a high socioeconomic impact. Currently, various guidelines and recommendations have been published about chronic coronary syndromes (CCS). According to the recent European Society of Cardiology guidelines on chronic coronary syndrome, a multimodal imaging approach is strongly recommended in the evaluation of patients with suspected CAD. Today, in the current practice, non-invasive imaging methods can assess coronary anatomy through coronary computed tomography angiography (CCTA) and/or inducible myocardial ischemia through functional stress testing (stress echocardiography, cardiac magnetic resonance imaging, single photon emission computed tomography—SPECT, or positron emission tomography—PET). However, recent trials (ISCHEMIA and REVIVED) have cast doubt on the previous conception of the management of patients with CCS, and nowadays it is essential to understand the limitations and strengths of each imaging method and, specifically, when to choose a functional approach focused on the ischemia versus a coronary anatomy-based one. Finally, the concept of a pathophysiology-driven treatment of these patients emerged as an important goal of multimodal imaging, integrating ‘anatomical’ and ‘functional’ information. The present review aims to provide an overview of non-invasive imaging modalities for the comprehensive management of CCS patients.
Machine Learning-Based Diagnosis and Ranking of Risk Factors for Diabetic Retinopathy in Population-Based Studies from South India
Authors: Vyas Abhishek , Raman Sundaresan , Sen Sagnik , Ramasamy Kim , Rajalakshmi Ramachandran , Mohan Viswanathan , Raman Rajiv
Published: June 2023

This paper discusses the importance of investigating DR using machine learning and a computational method to rank DR risk factors by importance using different machine learning models. The dataset was collected from four large population-based studies conducted in India between 2001 and 2010 on the prevalence of DR and its risk factors. We deployed different machine learning models on the dataset to rank the importance of the variables (risk factors). The study uses a t-test and Shapely additive explanations (SHAP) to rank the risk factors. Then, it uses five machine learning models (K-Nearest Neighbor, Decision Tree, Support Vector Machines, Logistic Regression, and Naive Bayes) to identify the unimportant risk factors based on the area under the curve criterion to predict DR. To determine the overall significance of risk variables, a weighted average of each classifier’s importance is used. The ranking of risk variables is provided to machine learning models. To construct a model for DR prediction, the combination of risk factors with the highest AUC is chosen. The results show that the risk factors glycosylated hemoglobin and systolic blood pressure were present in the top three risk factors for DR in all five machine learning models when the t-test was used for ranking. Furthermore, the risk factors, namely, systolic blood pressure and history of hypertension, were present in the top five risk factors for DR in all the machine learning models when SHAP was used for ranking. Finally, when an ensemble of the five machine learning models was employed, independently with both the t-test and SHAP, systolic blood pressure and diabetes mellitus duration were present in the top four risk factors for diabetic retinopathy. Decision Tree and K-Nearest Neighbor resulted in the highest AUCs of 0.79 (t-test) and 0.77 (SHAP). Moreover, K-Nearest Neighbor predicted DR with 82.6% (t-test) and 78.3% (SHAP) accuracy.
The Utilization of Machine Learning Algorithms for Assisting Physicians in the Diagnosis of Diabetes
Authors: Nguyen Linh Phuong , Tung Do Dinh , Nguyen Duong Thanh , Le Hong Nhung , Tran Toan Quoc , Binh Ta Van , Pham Dung Thuy Nguyen
Published: June 2023

This paper investigates the use of machine learning algorithms to aid medical professionals in the detection and risk assessment of diabetes. The research employed a dataset gathered from individuals with type 2 diabetes in Ninh Binh, Vietnam. A variety of classification algorithms, including Decision Tree Classifier, Logistic Regression, SVC, Ada Boost Classifier, Gradient Boosting Classifier, Random Forest Classifier, and K Neighbors Classifier, were utilized to identify the most suitable algorithm for the dataset. The results of the present study indicate that the Random Forest Classifier algorithm yielded the most promising results, exhibiting a cross-validation score of 0.998 and an accuracy rate of 100%. To further evaluate the effectiveness of the selected model, it was subjected to a testing phase involving a new dataset comprising 67 patients that had not been previously seen. The performance of the algorithm on this dataset resulted in an accuracy rate of 94%, especially the study’s notable finding is the algorithm’s accurate prediction of the probability of patients developing diabetes, as indicated by the class 1 (diabetes) probabilities. This innovative approach offers a meticulous and quantifiable method for diabetes detection and risk evaluation, showcasing the potential of machine learning algorithms in assisting clinicians with diagnosis and management. By communicating the diabetes score and probability estimates to patients, the comprehension of their disease status can be enhanced. This information empowers patients to make informed decisions and motivates them to adopt healthier lifestyle habits, ultimately playing a crucial role in impeding disease progression. The study underscores the significance of leveraging machine learning in healthcare to optimize patient care and improve long-term health outcomes.
Community-Acquired Methicillin-Resistant Staphylococcus aureus in Hospitals: Age-Specificity and Potential Zoonotic–Zooanthroponotic Transmission Dynamics
Authors: Alsolami Ahmed , ALGhasab Naif Saad , Alharbi Mohammed S. M. , Bashir Abdelhafiz I. , Saleem Mohd , Syed Khaja Azharuddin Sajid , Aldakheel Dakheel F. , Rakha Ehab , Alshammari Jabar Aziz , Taha Taha E. , Melibari Ziyad , Alharbi Yaseer H. , Almutlag Ali A. , Said Kamaleldin B.
Published: June 2023

Methicillin-resistant Staphylococcus aureus (MRSA) lineages are a devastating clinical and public health issue. Data on local lineage profiles are limited. We report on the frequency of community-acquired and hospital-acquired cases (CA-MRSA, HA-MRSA). We studied 147 isolates from King Khalid tertiary care hospitals (KKH), each from a case in a patient and including 33 patients at the Maternity and Children’s Hospital (MCH). Of the 147 isolates, 87 males (59%) and 60 females (41%) were in KKH. The overwhelming majority (80%; n = 119/147) were CA-MRSA in KKH. Intriguingly, despite significant differences between males (70%) and females (53%), lineage-acquisition remained age-specific around 58–60 years in both genders. However, while CA-MRSA dominated early in life (0–20, 70% MCH), it increased with age in KKH adults; 21–50 (28%), >50 (59%) until the overall 80% (n = 144/180). Major specimens included skin-wounds, surgeries (70.3%), blood (13.5%), sputum (8.8%), very rarely urine (4.1%), and nasal (3.4%), albeit most patients showed severe enteritis and necrotizing pneumonia. Antibiograms showed high beta lactam resistances, including amoxicillin–clavulanate (83%), oxacillin (84%), cefoxitin FOX (100%), penicillin and ampicillin (~100%), as well as high resistance (82%) to carbapenem. Fortunately, high susceptibility was seen to non-beta lactams and, to a lesser extent, gentamicin, erythromycin, and fusidic acid; 33%, 34%, and 38%, respectively, in KKH. A similar pattern was seen in MCH except for a low resistance pattern to gentamicin CN, clindamycin CD, erythromycin E, and tobramycin TOB; 34%, 31%, 39%, and 41%, respectively, except for fusidic acid. These findings have significant clinical implications for MRSA patient management strategies. Clinical- and lineage-profiles imply host-selection and zoonotic–zooanthroponotic transmission dynamics. Future molecular typing, sequencing, and characterization of dominant clone(s) is imperative.
Exploring the Power of Deep Learning: Fine-Tuned Vision Transformer for Accurate and Efficient Brain Tumor Detection in MRI Scans
Authors: Asiri Abdullah A. , Shaf Ahmad , Ali Tariq , Shakeel Unza , Irfan Muhammad , Mehdar Khlood M. , Halawani Hanan Talal , Alghamdi Ali H. , Alshamrani Abdullah Fahad A. , Alqhtani Samar M.
Published: June 2023

A brain tumor is a significant health concern that directly or indirectly affects thousands of people worldwide. The early and accurate detection of brain tumors is vital to the successful treatment of brain tumors and the improved quality of life of the patient. There are several imaging techniques used for brain tumor detection. Among these techniques, the most common are MRI and CT scans. To overcome the limitations associated with these traditional techniques, computer-aided analysis of brain images has gained attention in recent years as a promising approach for accurate and reliable brain tumor detection. In this study, we proposed a fine-tuned vision transformer model that uses advanced image processing and deep learning techniques to accurately identify the presence of brain tumors in the input data images. The proposed model FT-ViT involves several stages, including the processing of data, patch processing, concatenation, feature selection and learning, and fine tuning. Upon training the model on the CE-MRI dataset containing 5712 brain tumor images, the model could accurately identify the tumors. The FT-Vit model achieved an accuracy of 98.13%. The proposed method offers high accuracy and can significantly reduce the workload of radiologists, making it a practical approach in medical science. However, further research can be conducted to diagnose more complex and rare types of tumors with more accuracy and reliability.
Prediction of the Prevalence of Hypertension and Associated Risk Factors in Rwanda Using Gibbs Sampling Method
Authors: Dukunde Angélique , Ntaganda Jean Marie , Kasozi Juma , Nzabanita Joseph
Published: June 2023

In Rwanda, the prevalence of hypertension was 15.3% in 2015. At present, there are no accurate predictions of the prevalence of hypertension and its trend over time in Rwanda to assist decision makers in making plans for prevention and more effective interventions. This study used the Gibbs sampling method in combination with the Markov Chain Monte Carlo approach to predict the prevalence of hypertension and its associated risk factors in Rwanda over a period of ten years. The data were from World Health Organization (WHO) reports. The findings showed that the prevalence of hypertension is estimated to reach 17.82% in 2025, with tobacco use, being overweight or obese, and other risk factors having a respective prevalence of 26.26%, 17.13%, 4.80%, and 33.99%, which shows the increase and, therefore, measures for prevention to be taken. Therefore, to prevent and reduce the prevalence of this disease, the government of Rwanda should take appropriate measures to promote a balanced diet and physical exercise.
Software-Defined Networking Orchestration for Interoperable Key Management of Quantum Key Distribution Networks
Authors: Sim Dong-Hi , Shin Jongyoon , Kim Min Hyung
Published: June 2023

This paper demonstrates the use of software-defined networking (SDN) orchestration to integrate regionally separated networks in which different network parts use incompatible key management systems (KMSs) managed by different SDN controllers to ensure end-to-end QKD service provisioning to deliver the QKD keys between geographically different QKD networks. The study focuses on scenarios in which different parts of the network are managed separately by different SDN controllers, requiring an SDN orchestrator to coordinate and manage these controllers. In practical network deployments, operators often utilize multiple vendors for their network equipment. This practice also enables the expansion of the QKD network’s coverage by interconnecting various QKD networks equipped with devices from different vendors. However, as coordinating different parts of the QKD network is a complex task, this paper proposes the implementation of an SDN orchestrator which acts as a central entity to manage multiple SDN controllers, ensuring end-to-end QKD service provisioning to address this challenge. For instance, when there are multiple border nodes to interconnect different networks, the SDN orchestrator calculates the path in advance for the end-to-end delivery of keys between initiating and target applications belonging to different networks. This path selection requires the SDN orchestrator to gather information from each SDN controller managing the respective parts of the QKD network. This work shows the practical implementation of SDN orchestration for interoperable KMS in commercial QKD networks in South Korea. By employing an SDN orchestrator, it becomes possible to coordinate multiple SDN controllers and ensure the efficient and secure delivery of QKD keys between different QKD networks with varying vendor equipment.
Hierarchical Wilson–Cowan Models and Connection Matrices
Authors: Zúñiga-Galindo W. A. , Zambrano-Luna B. A.
Published: June 2023

This work aims to study the interplay between the Wilson–Cowan model and connection matrices. These matrices describe cortical neural wiring, while Wilson–Cowan equations provide a dynamical description of neural interaction. We formulate Wilson–Cowan equations on locally compact Abelian groups. We show that the Cauchy problem is well posed. We then select a type of group that allows us to incorporate the experimental information provided by the connection matrices. We argue that the classical Wilson–Cowan model is incompatible with the small-world property. A necessary condition to have this property is that the Wilson–Cowan equations be formulated on a compact group. We propose a p-adic version of the Wilson–Cowan model, a hierarchical version in which the neurons are organized into an infinite rooted tree. We present several numerical simulations showing that the p-adic version matches the predictions of the classical version in relevant experiments. The p-adic version allows the incorporation of the connection matrices into the Wilson–Cowan model. We present several numerical simulations using a neural network model that incorporates a p-adic approximation of the connection matrix of the cat cortex.
Determinants of Peruvian Export Efficiency: Poisson PML Estimation Approach
Authors: Navarro-Soto Fabiola Cruz , Morote Elsa-Sofia , Macha-Huamán Roberto , Saavedra-Soplín Enzo Arnold
Published: June 2023

Given their increasing engagement with the global economy, emerging countries such as Peru depend on their export sector. This research evaluates the level of efficiency of Peruvian exports (EF) and the impact of four regional trade agreements (RTAs) (MERCOSUR, the EU, the European Free Trade Association (EFTA), and the Andean Community of Nations (CAN)), twelve bilateral agreements (BAs), the World Trade Organization (WTO), institutional distance (ID), cultural distance (CD), foreign direct investment (FDI), trade freedom (TF), and traditional (TX) and nontraditional exports (NTX) by sector on the export efficiency of Peru. This non-experimental study used a dataset of 38 countries from 1995 to 2019. An extended stochastic frontier gravity (SFGM) ten-variable model with the one-step estimation method was applied to estimate export efficiency. Poisson’s PML estimator was used to investigate the factors that impact export efficiency (EF). The results showed that the export efficiency of Peru was moderate, ranging between 0.462 and 0.458, with a stationary trend, indicating considerable export potential between Peru and its trading partners. The major contributors to this efficiency are ID (voice and accountability, corruption control, nonadherence to the rule of law), NTX (chemicals and metal mechanics), and BA with American countries. On the other hand, CD (indulgence, long-term orientation, individualism, uncertainty, and lack of a culture of achievement), TF, agreements with MERCOSUR and the EU, FDI, and TX weakened the efficiency of exports. Finally, CAN, EFTA, BA with Asian countries, FDI, TX, and WTO did not have a significant effect on the EF. Recommendations to policy makers are presented.
Feminist Academic Activism in English Language Teaching: The Need to Study Discourses on Femininities Critically
Authors: López-Medina Esteban Francisco
Published: June 2023

Social research into English Language Teaching (ELT) has a long history. Within it, gender studies have gained ground in recent decades, with special focus on materials and resources. However, a proper integration of the category of femininity has not yet been achieved. The article offers an ample, argumentative, narrative literature review of the main realizations of femininity, as theorized in recent years, such as emphasized femininity or entitled femininity, as well as some other concepts like ambivalent sexism and postfeminism. It is written as the second item within a series of papers that aims to theoretically support the assumption of Feminist Critical Discourse Analysis as a suitable method to discover how all these social phenomena interact in ELT contexts, helping to shape its (gender’s) hidden curriculum. The paper concludes the necessity of integrating the issue of femininities in teacher training programs and in social research in ELT, for the sake of making this field more a liberating practice and less a means of (re)production of (gender) inequalities. To do so, it offers areas of interest for critical researchers and ELT practitioners to carry out such empirical investigation, which is the upcoming stage in this sequence of publications.
ID-Based Deniable Authentication Protocol with Key Agreement and Time-Bound Properties for 6G-Based WBAN Healthcare Environments
Authors: Hsu Chien-Lung , Nguyen Anh-Tuan , Cheng Guan-Lin
Published: June 2023

The advent of 6G technology is expected to bring a paradigm shift in the field of wireless communication. With its faster data transfer rates and lower latency, 6G could be an ideal solution for the challenges faced by Wireless Body Area Networks (WBANs) in terms of efficient data bandwidth and edge computing. Smart healthcare systems with 6G-based WBANs might provide more efficient and higher-quality healthcare services. However, 6G-based WBAN healthcare systems might face potential security and safety challenges from cybersecurity threats. This paper will propose an ID-based deniable authentication protocol with key agreement and time-bound properties for 6G-based WBAN healthcare environments by considering user privacy, secure communications, authentication, authorization, and scalability of 6G-based WBANs. As compared with previously proposed protocols, the proposed protocol will achieve the following security requirements: mutual authentication, key agreement for secure communication, deniability, time-bound access privilege control, and identity-based public key management for scalable wearable devices and 6G-based WBAN Service Providers. We proved the claimed security requirements of the proposed protocol by using AVISPA simulation and discussed its computational complexities. As compared with previous works, the proposed protocol can gain better contributions in terms of security requirements and performance evaluations for 6G-based WBAN healthcare environments.
MKGCN: Multi-Modal Knowledge Graph Convolutional Network for Music Recommender Systems
Authors: Cui Xiaohui , Qu Xiaolong , Li Dongmei , Yang Yu , Li Yuxun , Zhang Xiaoping
Published: June 2023

With the emergence of online music platforms, music recommender systems are becoming increasingly crucial in music information retrieval. Knowledge graphs (KGs) are a rich source of semantic information for entities and relations, allowing for improved modeling and analysis of entity relations to enhance recommendations. Existing research has primarily focused on the modeling and analysis of structural triples, while largely ignoring the representation and information processing capabilities of multi-modal data such as music videos and lyrics, which has hindered the improvement and user experience of music recommender systems. To address these issues, we propose a Multi-modal Knowledge Graph Convolutional Network (MKGCN) to enhance music recommendation by leveraging the multi-modal knowledge of music items and their high-order structural and semantic information. Specifically, there are three aggregators in MKGCN: the multi-modal aggregator aggregates the text, image, audio, and sentiment features of each music item in a multi-modal knowledge graph (MMKG); the user aggregator and item aggregator use graph convolutional networks to aggregate multi-hop neighboring nodes on MMKGs to model high-order representations of user preferences and music items, respectively. Finally, we utilize the aggregated embedding representations for recommendation. In training MKGCN, we adopt the ratio negative sampling strategy to generate high-quality negative samples. We construct four different-sized music MMKGs using the public dataset Last-FM and conduct extensive experiments on them. The experimental results demonstrate that MKGCN achieves significant improvements and outperforms several state-of-the-art baselines.
Near-Infrared CMOS Image Sensors Enabled by Colloidal Quantum Dot-Silicon Heterojunction
Authors: Xu Qiwei , Tong Xinghao , Zhang Jiangwen , Wang Xihua
Published: June 2023

The solution processibility of colloidal quantum dots (CQDs) promises a straightforward integration with Si readout integrated circuits (Si-ROCIs), which enables a near-infrared (NIR) CMOS image sensor (CIS; CMOS stands for complementary metal-oxide semiconductor). Previously demonstrated CQD NIR CISs were achieved through integrating CQD photodiode or PhotoFET with Si-ROCIs. Here, we conduct a simulation study to investigate the feasibility of a NIR CIS enabled by another integration strategy, that is, by forming a CQD-Si heterojunction. Simulation results clearly show that each active pixel made of CQD-Si heterojunction photodiode on the CIS sensitively responds to NIR light, and generated photocarriers induce changes in electrostatic potentials in the active pixel. The potential changes are read out through the integrated circuits as validated by the readout timing sequence simulation.
A Design of a Dual Delay Line DLL with Wide Input Duty Cycle Range
Authors: Qin Binyu , Zhao Leilei , Fang Chenyu , Poechmueller Peter
Published: June 2023

This article describes a dual-controller dual-delay line delay lock loop (DC-DL DLL). The proposed DLL adopted a dual delay line structure, each delay line was composed of a coarse adjustment and a fine adjustment unit, and the dual delay lines had corresponding control units to reduce the mismatch between the delay lines, and it avoided the complicated design of duty cycle correction (DCC) circuit. A frequency divider was added to divide the input clock to achieve a wider input clock duty cycle adjustment. Additionally, a simple clock synthesis circuit was proposed to synthesize the required clock. The DLL design used the 25 nm process with a voltage of 1.2 V. The simulation results showed that at a working frequency of 1.6 GHz, the peak-to-peak jitter of the DC-DL DLL after locking was approximately 17.61 ps, the maximum output duty cycle error was about 1.3%, and the input duty cycle ranged from 20% to 80%, with a power consumption of 10.06 mW.