bluuebunny/crossref_metadata_2025 huggingface dataset:
Chemical Composition, Structure, and Physical Properties of AlN Films Produced via Pulsed DC Reactive Magnetron Sputtering
Authors: Shayapov Vladimir R. , Bogoslovtseva Alena L. , Chepkasov Sergey Yu. , Asanov Igor P. , Maksimovskiy Evgeny A. , Kapishnikov Aleksandr V. , Mironova Maria I. , Lapega Alina V. , Geydt Pavel V.
Published: July 2023

The chemical composition, structure, and physical properties of aluminum nitride (AlN) films obtained using pulsed DC reactive magnetron sputtering in asymmetric bipolar mode have been studied. X-ray diffraction and electron diffraction confirmed the composition of c–axis textured hexagonal AlN films required for piezoelectric applications. The surface of the films obtained is quite smooth; the arithmetic average roughness does not exceed 2 nm. Transmission electron microscopy has shown the presence of a transition layer at the film–substrate interface. Transmission electron microscopy and X-ray photoelectron spectroscopy depth profile analysis have shown that the films have an oxidized surface layer which has an influence on the optical model of the films derived from ellipsometric data. However, it does not significantly influence the films’ piezoresponse. Piezoelectric force microscopy indicated a piezoelectric effect in the films that is uniform over their surface.
Enhanced Adsorption of Methylene Blue Using Phosphoric Acid-Activated Hydrothermal Carbon Microspheres Synthesized from a Variety of Palm-Based Biowastes
Authors: Alhawtali Saeed , El-Harbawi Mohanad , Al-Awadi Abdulrhman S. , El Blidi Lahssen , Alrashed Maher M. , Yin Chun-Yang
Published: July 2023

In the present study, the ability for novel carbon microspheres (CMs) derived from date palm (Phoenix dactylifera) biomass using a hydrothermal carbonization (HTC) process and activated using phosphoric acid to remove methylene blue dye was investigated. Three types of palm-based wastes (seeds, leaflet, and inedible crystallized date palm molasses) were used and converted to CMs via the HTC process. The prepared samples were then activated using phosphoric acid via the incipient wetness impregnation method. The CMs samples before and after activation were analyzed using scanning electron microscopy (SEM), elemental analysis and scanning (CHNS), and the Fourier transform infrared (FTIR) and Brunauer–Emmet–Teller (BET) methods. The samples exhibited high BET surface areas after activation (1584 m2/g). The methylene blue adsorption results showed good fitting to the Langmuir, Fruendlich, and Temkin isotherm models for all activated samples. The maximum adsorption capacity achieved was 409.84 mg/g for activated CM obtained from the palm date molasses, indicating its high potential for application as a dye-based adsorption material.
Influence of Laser Power on Microstructure and Properties of Al-Si+Y2O3 Coating
Authors: Gao Yali , Lu Pengyong , Bai Sicheng , Qin Baolong , Zhang Dongdong
Published: July 2023

Al-Si/7.5 wt.%Y2O3 coatings were prepared on Mg alloy with laser cladding to enhance the wear and corrosion resistance of substrate. The influence of laser power on the microstructure and properties of the coating were discussed. The results uncovered that the coatings consisted primarily of Mg2Si, Mg17Al12, Mg2Al3, Al4MgY, and α-Mg phases. Through calculating, it was observed that the crystal size decreased with the decrease in the laser power. Y2O3 gave the coating a better strengthening effect due to the fine-grain strengthening and hard-phase strengthening. The average hardness of the coating with laser power of 1100 W achieved 312 HV, which was approximately 4.2 times that of the substrate. The wear volume of the coating was 22.2% that of the substrate. Compared with Mg alloy, the self-corrosion potential of the coating increased by 1.09 V, and the self-corrosion current density decreased by three orders of magnitude.
Analysis of the Dynamics of Tuberculosis in Algeria Using a Compartmental VSEIT Model with Evaluation of the Vaccination and Treatment Effects
Authors: Chennaf Bouchra , Abdelouahab Mohammed Salah , Lozi René
Published: July 2023

Despite low tuberculosis (TB) mortality rates in China, Europe, and the United States, many countries are still struggling to control the epidemic, including India, South Africa, and Algeria. This study aims to contribute to the body of knowledge on this topic and provide a valuable tool and evidence-based guidance for the Algerian healthcare managers in understanding the spread of TB and implementing control strategies. For this purpose, a compartmental mathematical model is proposed to analyze TB dynamics in Algeria and investigate the vaccination and treatment effects on disease breaks. A qualitative study is conducted to discuss the stability property of both disease-free equilibrium and endemic equilibrium. In order to adopt the proposed model for the Algerian case, we estimate the model parameters using Algerian TB-reported data from 1990 to 2020. The obtained results using the proposed mathematical compartmental model show that the reproduction number (R0) of TB in Algeria is less than one, suggesting that the disease can be eradicated or effectively controlled through a combination of interventions, including vaccination, high-quality treatment, and isolation measures.
Kernel-Based Regularized EEGNet Using Centered Alignment and Gaussian Connectivity for Motor Imagery Discrimination
Authors: Tobón-Henao Mateo , Álvarez-Meza Andrés Marino , Castellanos-Dominguez Cesar German
Published: July 2023

Brain–computer interfaces (BCIs) from electroencephalography (EEG) provide a practical approach to support human–technology interaction. In particular, motor imagery (MI) is a widely used BCI paradigm that guides the mental trial of motor tasks without physical movement. Here, we present a deep learning methodology, named kernel-based regularized EEGNet (KREEGNet), leveled on centered kernel alignment and Gaussian functional connectivity, explicitly designed for EEG-based MI classification. The approach proactively tackles the challenge of intrasubject variability brought on by noisy EEG records and the lack of spatial interpretability within end-to-end frameworks applied for MI classification. KREEGNet is a refinement of the widely accepted EEGNet architecture, featuring an additional kernel-based layer for regularized Gaussian functional connectivity estimation based on CKA. The superiority of KREEGNet is evidenced by our experimental results from binary and multiclass MI classification databases, outperforming the baseline EEGNet and other state-of-the-art methods. Further exploration of our model’s interpretability is conducted at individual and group levels, utilizing classification performance measures and pruned functional connectivities. Our approach is a suitable alternative for interpretable end-to-end EEG-BCI based on deep learning.
Exploring the Landscape of Data Analysis: A Review of Its Application and Impact in Ecuador
Authors: Ayala-Chauvin Manuel , Avilés-Castillo Fátima , Buele Jorge
Published: July 2023

Data analysis is increasingly critical in aiding decision-making within public and private institutions. This paper scrutinizes the status quo of big data and data analysis and its applications within Ecuador, focusing on its societal, educational, and industrial impact. A detailed literature review was conducted from academic databases such as SpringerLink, Scopus, IEEE Xplore, Web of Science, and ACM, incorporating research from inception until May 2023. The search process adhered to the PRISMA statement, employing specific inclusion and exclusion criteria. The analysis revealed that data implementation in Ecuador, while recent, has found noteworthy applications in six principal areas, classified using ISCED: education, science, engineering, health, social, and services. In the scientific and engineering sectors, big data has notably contributed to disaster mitigation and optimizing resource allocation in smart cities. Its application in the social sector has fortified cybersecurity and election data integrity, while in services, it has enhanced residential ICT adoption and urban planning. Health sector applications are emerging, particularly in disease prediction and patient monitoring. Educational applications predominantly involve student performance analysis and curricular evaluation. This review emphasizes that while big data’s potential is being gradually realized in Ecuador, further research, data security measures, and institutional interoperability are required to fully leverage its benefits.
Citrulluside T, Isolated from the Citrullus lanatus Stem, Inhibits Melanogenesis in α-MSH-Induced Mouse B16F10 Cells
Authors: Kim Hyeon-Mi , Moon Mi-Yeon , Hyun Chang-Gu
Published: July 2023

With the increasing number of cosmetic consumers emphasizing value consumption and sustainability, upcycling has gained attention as a solution to agricultural by-products, which are the main culprits of environmental problems. In this study, we isolated citrulluside T with whitening activity from discarded Citrullus lanatus stems and investigated the anti-melanogenic effect of citrulluside T and the underlying mechanisms. We found that citrulluside T did not exhibit cytotoxicity up to a concentration of 90 μM and significantly reduced the melanin content and intracellular tyrosinase activity in B16F10 cells. In addition, citrulluside T inhibited the expression of melanogenic enzymes such as tyrosinase, tyrosinase-related protein (TRP)-1, and TRP-2, as well as melanin synthesis via cAMP-dependent protein kinase (PKA)/cAMP response element-binding protein (CREB)-mediated downregulation of microphthalmia-associated transcription factor (MITF), a key transcription factor in melanogenesis. Furthermore, we found that citrulluside T exerted its anti-melanogenic effect by downregulating the β-catenin protein and upregulating phosphorylated β-catenin. Finally, we confirmed that citrulluside T was safe for skin through skin irritation tests on 33 subjects, suggesting its applicability as a protective agent against hyperpigmentation for topical applications such as cosmetics and ointments.
Excitation Density Effects in the Luminescence Yield and Kinetics of MAPbBr3 Single Crystals
Authors: Belsky Andrey N. , Fedorov Nikita A. , Frolov Ivan A. , Kamenskikh Irina A. , Martin Patrick , Rubtsova Elizaveta D. , Shpinkov Igor N. , Spassky Dmitry A. , Vasil’ev Andrey N. , Zadneprovsky Boris I.
Published: July 2023

The luminescent Z-scan technique with time resolution is applied to the study of the luminescence properties of CH3NH3PbBr3 single crystals representative of the family of hybrid organic–inorganic lead perovskites successfully applied recently in photovoltaics and currently investigated as potential nanosecond scintillators. The third harmonic of Ti-sapphire laser (λ = 266 nm) with a pulse duration of 26 fs and 1 kHz frequency was applied for the luminescence excitation creating the charge carriers with the estimated density from 1017 to 1021 cm−3 in the temperature range from 13 to 300 K. Temperature and excitation density dependence of the luminescence yield and kinetics is interpreted with the consideration of the temperature-dependent binding of electrons and holes into excitons, a saturation of defects responsible for the non-radiative relaxation channel competing with exciton creation; absorption saturation resulting in the increased penetration depth of the excitation radiation and hence the increased contribution of the re-absorption.
Negative Linear Compressibility of Formate Crystals from the Viewpoint of Quantum Electronic Pressure
Authors: Matveychuk Yury V. , Sobalev Sergey A. , Borisova Polina I. , Bartashevich Ekaterina V. , Tsirelson Vladimir G.
Published: July 2023

In order to understand the phenomenon of negative linear compressibility (NLC) in organic crystals, it is necessary to investigate not only the structural features but also the electronic changes taking place under external hydrostatic pressure. It is also necessary to clarify which electronic properties allow the quantification and comparison of the compressibility of crystals. In our study, the crystal structures of sodium and cadmium formates under hydrostatic compression were modeled, as well as the α and β-phases of calcium formate. The changes in cell parameters and spatial dependences of the linear compressibility were analyzed, and the ranges of external pressure, which must be applied for NLC onset, were predicted for the sodium and α-calcium formates. Although the behavior of chemical bonds is not predicted by the sign or absolute value of the quantum electronic pressure, its relative change under external pressure clearly distinguishes the soft and rigid regions in a crystal. The relationship between the NLC values and the changes in quantum electronic pressure in the cavities of formate crystals was established.
Preparation and Characterization of Nano-Sized Co(II), Cu(II), Mn(II) and Ni(II) Coordination PAA/Alginate Biopolymers and Study of Their Biological and Anticancer Performance
Authors: Al-Fakeh Maged S. , Alazmi Munirah S. , EL-Ghoul Yassine
Published: July 2023

Four of the crosslinked sodium alginate and polyacrylic acid biopolymers based nanoscale metal natural polysaccharides, [M(AG-PAA)Cl(H2O)3], where M = Co(II), Cu(II), Mn(II) and Ni(II), AG = sodium alginate and PAA = polyacrylic acid, have been synthesized and structurally characterized. Because of their numerous biological and pharmacological activities of polysaccharides, including antimicrobial, immunomodulatory, antitumor, antidiabetic, antiviral, antioxidant, hypoglycemic and anticoagulant activities, polysaccharides are one of the near-promising candidates in the biomedical and pharmaceutical fields. The complexity of the polymeric compounds has been verified by carbon and nitrogen analysis, magnetic and conductance measurements, FT-IR spectra, electronic spectral analysis and thermal analysis (DTA, TG). All the synthesized complexes were non-electrolytes with magnetic moments ranging from 1.74 to 5.94 BM. The polymeric complexes were found to be of octahedral geometry. The developed coordination polymeric was found to be crystalline using X-ray powder diffraction examinations, which is confirmed by the SEM analysis. As a result, the crystallite size of all polymeric nanocrystals was in the range of 14 - 69 nm. The test of four compounds exhibits a broad spectrum of antimicrobial activity against both Gram-positive and Gram-negative bacteria and fungal Candida albicans. Using DPPH as a substrate, studies on radical scavenging tests are carried out. The findings demonstrated the antioxidant activities of each complex. In addition, results showed that the two chosen polymeric complexes had a good ability to kill cancer cells in a dose-dependent way. The copper(II) polymeric complex showed to its superior functionality as evidenced by microbial activity. After 72 h of interaction with the normal human breast epithelial cells (MCF10A), the synthesized polymeric compounds of Cu(II) and Co(II) showed exceptional cytocompatibility with the different applied doses. Compared to poly-AG/PAA/Co(II), poly-AG/PAA/Cu(II) exhibits a greater anticancer potential at various polymeric dosages.
The Effectiveness and Safety of Stereotactic Body Radiation Therapy (SBRT) in the Treatment of Oligoprogressive Breast Cancer: A Systematic Review
Authors: Yan Bernie , Ramadan Sherif , Jerzak Katarzyna J. , Louie Alexander V. , Donovan Elysia
Published: July 2023

Stereotactic body radiotherapy (SBRT) has emerged as a technique to treat oligoprogressive sites among patients with breast cancer who are otherwise doing well on systemic therapy. This study systematically reviewed the efficacy and safety of SBRT in the setting of oligoprogressive breast cancer. A literature search was conducted in the MEDLINE database. Studies regarding SBRT and oligoprogressive breast cancer were included. Key outcomes of interest were toxicity, local control, progression, and overall survival. From 863 references, five retrospective single-center cohort studies were identified. All studies included patients with both oligometastatic and oligoprogressive disease; 112 patients with oligoprogressive breast cancer were identified across these studies. Patient age ranged from 22 to 84, with a median of 55 years of age. Most patients had hormone-receptor-positive and HER2-negative disease. SBRT doses varied from 24 to 60 Gy in 1–10 fractions based on the location/size of the lesion. Forty toxicity events were reported, of which the majority (n = 25, 62.5%) were grade 1–2 events. Among 15 patients who received SBRT concurrently with a CDK4/6 inhibitor, 37.5% of patients experienced grade 3–5 toxicities. Progression-free and overall survival ranged from 17 to 57% and 62 to 91%, respectively. There are limited data on the role of SBRT in oligoprogressive breast cancer, and prospective evaluation of this strategy is awaited to inform its safety and efficacy.
30-Min Exposure to Tobacco Smoke Influences Airway Ion Transport—An In Vitro Study
Authors: Henke Katarzyna , Balcerzak Irena , Czepil Ewa , Bem Alicja , Piskorska Elżbieta , Olszewska-Słonina Dorota , Woźniak Alina , Szewczyk-Golec Karolina , Hołyńska-Iwan Iga
Published: July 2023

Introduction: Smoking is one of the most important causes of cancer in humans. However, it has not been proven how long exposure to cigarette smoke is sufficient to induce cancerogenesis. Cigarette smoke can cause changes in ion and water transport and the maintenance of mucociliary transport. The conducted research concerned the assessment of changes in ion transport in rabbit tracheal specimens after 30 min of exposure to cigarette smoke. Materials and Methods: A modified Ussing chamber was used to measure the transepithelial electrical potential under stationary conditions (PD) and during mechanical stimulation (PDmin), and the transepithelial electrical resistance (R) in control and cigarette smoke-exposed tracheal fragments. Results: Significant changes in PD (−2.53 vs. −3.92 mV) and PDmin (−2.74 vs. −0.39 mV) were noted for the samples exposed to smoke, which can be associated with a rise in reactivity after applying a mechanical stimulus. In addition, the measured R (108 vs. 136 Ω/cm2) indicated no changes in the vitality of the samples, but an increase in their permeability to ions in the experimental conditions. Conclusions: A single 30-min exposure to cigarette smoke has been shown to be associated with increased permeability of the tracheal epithelium to ions and thus to substances emitted during smoking, which might be sufficient to create the possibility of initiating procarcinogenic processes.
The Role of Sublobar Resection for the Surgical Treatment of Non-Small Cell Lung Cancer
Authors: Behinaein Parnia , Treffalls John , Hutchings Hollis , Okereke Ikenna C.
Published: July 2023

Lung cancer is the most common cancer killer in the world. The standard of care for surgical treatment of non-small cell lung cancer has been lobectomy. Recent studies have identified that sublobar resection has non-inferior survival rates compared to lobectomy, however. Sublobar resection may increase the number of patients who can tolerate surgery and reduce postoperative pulmonary decline. Sublobar resection appears to have equivalent results to surgery in patients with small, peripheral tumors and no lymph node disease. As the utilization of segmentectomy increases, there may be some centers that perform this operation more than other centers. Care must be taken to ensure that all patients have access to this modality. Future investigations should focus on examining the outcomes from segmentectomy as it is applied more widely. When employed on a broad scale, morbidity and survival rates should be monitored. As segmentectomy is performed more frequently, patients may experience improved postoperative quality of life while maintaining the same oncologic benefit.
The Prognostic Value of Serum Biomarkers for Survival of Children with Osteosarcoma of the Extremities
Authors: Basoli Stefano , Cosentino Monica , Traversari Matteo , Manfrini Marco , Tsukamoto Shinji , Mavrogenis Andreas F. , Bordini Barbara , Donati Davide Maria , Errani Costantino
Published: July 2023

Background: Osteosarcoma is a highly aggressive malignant bone tumor that affects mainly adolescents and young adults. We analyzed serum biomarkers for their prognostic significance in children with osteosarcoma. Methods: In this retrospective study, we investigated the prognostic factors in 210 children who were treated for appendicular osteosarcoma, including patient age and sex, tumor site and size (≥8 cm or <8 cm), presence of metastasis, chemotherapy-induced tumor necrosis, serum levels of alkaline phosphatase (AP), C-reactive protein, serum hemoglobin, lactate dehydrogenase, erythrocyte sedimentation rate (ESR), leukocyte counts, platelet count, and neutrophil–lymphocyte ratio. Results: A multivariate Cox regression model showed that high level of AP [HR of 1.73; 95% CI, 1.02 to 2.94], poor chemotherapy-induced tumor necrosis [HR of 2.40; 95% CI, 1.41 to 4.08] and presence of metastases at presentation [HR of 3.71; 95% CI, 2.19 to 6.29] were associated with poor prognosis at 5 years (p < 0.05). Inadequate surgical margins [HR 11.28; 95% CI, 1.37 to 92.79] and high levels of ESR [HR 3.58; 95% CI, 1.29 to 9.98] showed a greater risk of local recurrence at 5 years follow-up (p < 0.05). Conclusions: AP and ESR can identify osteosarcoma-diagnosed children with a greater risk of death and local recurrence, respectively.
Power Drill Craniostomy for Bedside Intracranial Access in Traumatic Brain Injury Patients
Authors: Deng Hansen , Puccio David , Anand Sharath , Yue John , Hudson Joseph , Legarreta Andrew , Wei Zhishuo , Okonkwo David , Puccio Ava , Nwachuku Enyinna
Published: July 2023

Invasive neuromonitoring is a bedrock procedure in neurosurgery and neurocritical care. Intracranial hypertension is a recognized emergency that can potentially lead to herniation, ischemia, and neurological decline. Over 50,000 external ventricular drains (EVDs) are performed in the United States annually for traumatic brain injuries (TBI), tumors, cerebrovascular hemorrhaging, and other causes. The technical challenge of a bedside ventriculostomy and/or parenchymal monitor placement may be increased by complex craniofacial trauma or brain swelling, which will decrease the tolerance of brain parenchyma to applied procedural force during a craniostomy. Herein, we report on the implementation and safety of a disposable power drill for bedside neurosurgical practices compared with the manual twist drill that is the current gold standard. Mechanical testing of the drill’s stop extension (n = 8) was conducted through a calibrated tensile tester, simulating an axial plunging of 22.68 kilogram (kg) or 50 pounds of force (lbf) and measuring the strength-responsive displacement. The mean displacement following compression was 0.18 ± 0.11 mm (range of 0.03 mm to 0.34 mm). An overall cost analysis was calculated based on the annual institutional pricing, with an estimated $64.90 per unit increase in the cost of the disposable electric drill. Power drill craniostomies were utilized in a total of 34 adult patients, with a median Glasgow Coma Scale (GCS) score of six. Twenty-seven patients were male, with a mean age of 50.7 years old. The two most common injury mechanisms were falls and motor vehicle/motorcycle accidents. EVDs were placed in all subjects, and additional quad-lumen neuromonitoring was applied to 23 patients, with no incidents of plunging events or malfunctions. One patient developed an intracranial infection and another had intraparenchymal tract hemorrhaging. Two illustrative TBI cases with concomitant craniofacial trauma were provided. The disposable power drill was successfully implemented as an option for bedside ventriculostomies and had an acceptable safety profile.
The Evolving Concept of the Multidisciplinary Approach in the Diagnosis and Management of Interstitial Lung Diseases
Authors: Sanduzzi Zamparelli Stefano , Sanduzzi Zamparelli Alessandro , Bocchino Marialuisa
Published: July 2023

Background: Interstitial lung diseases (ILDs) are a group of heterogeneous diseases characterized by inflammation and/or fibrosis of the lung interstitium, leading to a wide range of clinical manifestations and outcomes. Over the years, the literature has demonstrated the increased diagnostic accuracy and confidence associated with a multidisciplinary approach (MDA) in assessing diseases involving lung parenchyma. This approach was recently emphasized by the latest guidelines from the American Thoracic Society, European Respiratory Society, Japanese Respiratory Society, and Latin American Thoracic Association for the diagnosis of ILDs. Methods: In this review, we will discuss the role, composition, and timing of multidisciplinary diagnosis (MDD) concerning idiopathic pulmonary fibrosis, connective tissue disease associated with ILDs, hypersensitive pneumonia, and idiopathic pneumonia with autoimmune features, based on the latest recommendations for their diagnosis. Results: The integration of clinical, radiological, histopathological, and, often, serological data is crucial in the early identification and management of ILDs, improving patient outcomes. Based on the recent endorsement of transbronchial cryo-biopsy in idiopathic pulmonary fibrosis guidelines, an MDA helps guide the choice of the sampling technique, obtaining the maximum diagnostic performance, and avoiding the execution of more invasive procedures such as a surgical lung biopsy. A multidisciplinary team should include pulmonologists, radiologists, pathologists, and, often, rheumatologists, being assembled regularly to achieve a consensus diagnosis and to review cases in light of new features. Conclusions: The literature highlighted that an MDA is essential to improve the accuracy and reliability of ILD diagnosis, allowing for the early optimization of therapy and reducing the need for invasive procedures. The multidisciplinary diagnosis of ILDs is an ongoing and dynamic process, often referred to as a “working diagnosis”, involving the progressive integration and re-evaluation of clinical, radiological, and histological features.
A Deep Learning Approach for Atrial Fibrillation Classification Using Multi-Feature Time Series Data from ECG and PPG
Authors: Aldughayfiq Bader , Ashfaq Farzeen , Jhanjhi N. Z. , Humayun Mamoona
Published: July 2023

Atrial fibrillation is a prevalent cardiac arrhythmia that poses significant health risks to patients. The use of non-invasive methods for AF detection, such as Electrocardiogram and Photoplethysmogram, has gained attention due to their accessibility and ease of use. However, there are challenges associated with ECG-based AF detection, and the significance of PPG signals in this context has been increasingly recognized. The limitations of ECG and the untapped potential of PPG are taken into account as this work attempts to classify AF and non-AF using PPG time series data and deep learning. In this work, we emploted a hybrid deep neural network comprising of 1D CNN and BiLSTM for the task of AF classification. We addressed the under-researched area of applying deep learning methods to transmissive PPG signals by proposing a novel approach. Our approach involved integrating ECG and PPG signals as multi-featured time series data and training deep learning models for AF classification. Our hybrid 1D CNN and BiLSTM model achieved an accuracy of 95% on test data in identifying atrial fibrillation, showcasing its strong performance and reliable predictive capabilities. Furthermore, we evaluated the performance of our model using additional metrics. The precision of our classification model was measured at 0.88, indicating its ability to accurately identify true positive cases of AF. The recall, or sensitivity, was measured at 0.85, illustrating the model’s capacity to detect a high proportion of actual AF cases. Additionally, the F1 score, which combines both precision and recall, was calculated at 0.84, highlighting the overall effectiveness of our model in classifying AF and non-AF cases.
The Impact of the COVID-19 Pandemic on Outcomes in Acute Pancreatitis: A Propensity Score Matched Study Comparing before and during the Pandemic
Authors: Rădulescu Patricia Mihaela , Căluianu Elena Irina , Traşcă Emil Tiberius , Mercuţ Dorin , Georgescu Ion , Georgescu Eugen Florin , Ciupeanu-Călugăru Eleonora Daniela , Mercuţ Maria Filoftea , Mercuţ Răzvan , Padureanu Vlad , Streba Costin Teodor , Călăraşu Cristina , Rădulescu Dumitru
Published: July 2023

We aimed to evaluate the outcomes and survival of patients with acute pancreatitis who shared the same clinical form, age, and sex before the pandemic, during the pandemic, and among those with confirmed COVID-19 infection upon hospital admission. This consideration used the sparse data in the existing literature on the influence of the pandemic and COVID-19 infection on patients with acute pancreatitis. To accomplish this, we conducted a multicentric, retrospective case–control study using propensity score matching with a 2:1 match of 28 patients with SARS-CoV-2 infection and acute pancreatitis, with 56 patients with acute pancreatitis pre-pandemic, and 56 patients with acute pancreatitis during the pandemic. The study outcome demonstrated a six-fold relative risk of death in patients with acute pancreatitis and SARS-CoV-2 infection compared to those with acute pancreatitis before the pandemic. Furthermore, restrictive measures implemented during the pandemic period led to a partial delay in the care of patients with acute pancreatitis, which likely resulted in an impairment of their immune state. This, in certain circumstances, resulted in a restriction of surgical treatment indications, leading to a three-fold relative risk of death in patients with acute pancreatitis during the pandemic compared to those with acute pancreatitis before the pandemic.
The Clinical and Microbiological Effects of LANAP Compared to Scaling and Root Planing Alone in the Management of Periodontal Conditions
Authors: Bechir Edwin Sever
Published: July 2023

The purpose of this study was to evaluate the efficiency of two therapeutic procedures clinically and microbiologically in the management of periodontally affected teeth: scaling and root planing alone and the laser-assisted new attachment procedure (LANAP). Molecular biological determinations of bacterial markers through the polymerase chain reaction (real-time PCR) method with standard PET tests (species-specific DNA probes at a time) were used for the quantification of three of the most important periodontal pathogens (Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, and Treponema denticola). Both nonsurgical periodontal therapies were proven effective in patients with chronic periodontal disease; however, LANAP was associated with a greater reduction in pocket depth and improved clinical outcomes, associated with a significant decrease in the amount of Porphyromonas gingivalis. The clinical results included a decrease in periodontal pocket depth, bleeding on probing, and dental plaque, with LANAP having better overall outcomes than SRP alone. The use of Nd:YAG lasers in LANAP therapy is a safe and effective procedure that is well accepted by patients.
Artificial Intelligence-Assisted Processing of Anterior Segment OCT Images in the Diagnosis of Vitreoretinal Lymphoma
Authors: Gozzi Fabrizio , Bertolini Marco , Gentile Pietro , Verzellesi Laura , Trojani Valeria , De Simone Luca , Bolletta Elena , Mastrofilippo Valentina , Farnetti Enrico , Nicoli Davide , Croci Stefania , Belloni Lucia , Zerbini Alessandro , Adani Chantal , De Maria Michele , Kosmarikou Areti , Vecchi Marco , Invernizzi Alessandro , Ilariucci Fiorella , Zanelli Magda , Iori Mauro , Cimino Luca
Published: July 2023

Anterior segment optical coherence tomography (AS-OCT) allows the explore not only the anterior chamber but also the front part of the vitreous cavity. Our cross-sectional single-centre study investigated whether AS-OCT can distinguish between vitreous involvement due to vitreoretinal lymphoma (VRL) and vitritis in uveitis. We studied AS-OCT images from 28 patients (11 with biopsy-proven VRL and 17 with differential diagnosis uveitis) using publicly available radiomics software written in MATLAB. Patients were divided into two balanced groups: training and testing. Overall, 3260/3705 (88%) AS-OCT images met our defined quality criteria, making them eligible for analysis. We studied five different sets of grey-level samplings (16, 32, 64, 128, and 256 levels), finding that 128 grey levels performed the best. We selected the five most effective radiomic features ranked by the ability to predict the class (VRL or uveitis). We built a classification model using the xgboost python function; through our model, 87% of eyes were correctly diagnosed as VRL or uveitis, regardless of exam technique or lens status. Areas under the receiver operating characteristic curves (AUC) in the 128 grey-level model were 0.95 [CI 0.94, 0.96] and 0.84 for training and testing datasets, respectively. This preliminary retrospective study highlights how AS-OCT can support ophthalmologists when there is clinical suspicion of VRL.
Joint Task Offloading and Resource Allocation for Space–Air–Ground Collaborative Network
Authors: Mei Chengli , Gao Cheng , Wang Heng , Xing Yanxia , Ju Ningyao , Hu Bo
Published: July 2023

The space–air–ground collaborative network can provide computing service for ground users in remote areas by deploying edge servers on satellites and high-altitude platform (HAP) drones. However, with the growing number of ground devices required to be severed, it becomes imperative to address the issue of spectrum demand for the HAP drone to meet the access of a large number of users. In addition, the long propagation distance between devices and the HAP drone, and between the HAP drone and LEO satellites, will lead to high data transmission energy consumption. Motivated by these factors, we introduce a space–air–ground collaborative network that employs the non-orthogonal multiple access (NOMA) technique, enabling all ground devices to access the HAP drone. Therefore, all devices can share the same communication spectrum. Furthermore, the HAP drone can process part of the ground devices’ tasks locally, and offload the rest to satellites within the visible range for processing. Based on this system, we formulate a weighted energy consumption minimization problem considering power control, computing frequency allocation, and task-offloading decision. The problem is solved by the proposed low-complexity iterative algorithm. Specifically, the original problem is decomposed into interconnected coupled subproblems using the block coordinate descent (BCD) method. The first subproblem is to optimize power control and computing frequency allocation, which is solved by a convex algorithm after a series of transformations. The second subproblem is to make an optimal task-offloading strategy, and we solve it using the concave–convex procedure (CCP)-based algorithm after penalty-based transformation on binary variables. Simulation results verify the convergence and performance of the proposed iterative algorithm compared with the two benchmark algorithms.
The Necessary and Sufficient Conditions When Global and Local Fidelities Are Equal
Authors: Kim Seong-Kun , Lee Yonghae
Published: July 2023

In the field of quantum information theory, the concept of quantum fidelity is employed to quantify the similarity between two quantum states. It has been observed that the fidelity between two states describing a bipartite quantum system A⊗B is always less than or equal to the quantum fidelity between the states in subsystem A alone. While this fidelity inequality is well understood, determining the conditions under which the inequality becomes an equality remains an open question. In this paper, we present the necessary and sufficient conditions for the equality of fidelities between a bipartite system A⊗B and subsystem A, considering pure quantum states. Moreover, we provide explicit representations of quantum states that satisfy the fidelity equality, based on our derived results.
The Time Evolution of Mutual Information between Disjoint Regions in the Universe
Authors: Pandey Biswajit
Published: July 2023

We study the time evolution of mutual information between mass distributions in spatially separated but casually connected regions in an expanding universe. The evolution of mutual information is primarily determined by the configuration entropy rate, which depends on the dynamics of the expansion and growth of density perturbations. The joint entropy between distributions from the two regions plays a negligible role in such evolution. Mutual information decreases with time in a matter-dominated universe, whereas it stays constant in a Λ-dominated universe. The ΛCDM model and some other models of dark energy predict a minimum in mutual information beyond which dark energy dominates the dynamics of the universe. Mutual information may have deeper connections to the dark energy and accelerated expansion of the universe.
Double-Layer Detection Model of Malicious PDF Documents Based on Entropy Method with Multiple Features
Authors: Song Enzhou , Hu Tao , Yi Peng , Wang Wenbo
Published: July 2023

Traditional PDF document detection technology usually builds a rule or feature library for specific vulnerabilities and therefore is only fit for single detection targets and lacks anti-detection ability. To address these shortcomings, we build a double-layer detection model for malicious PDF documents based on an entropy method with multiple features. First, we address the single detection target problem with the fusion of 222 multiple features, including 130 basic features (such as objects, structure, content stream, metadata, etc.) and 82 dangerous features (such as suspicious and encoding function, etc.), which can effectively resist obfuscation and encryption. Second, we generate the best set of features (a total of 153) by creatively applying an entropy method based on RReliefF and MIC (EMBORAM) to PDF samples with 37 typical document vulnerabilities, which can effectively resist anti-detection methods, such as filling data and imitation attacks. Finally, we build a double-layer processing framework to detect samples efficiently through the AdaBoost-optimized random forest algorithm and the robustness-optimized support vector machine algorithm. Compared to the traditional static detection method, this model performs better for various evaluation criteria. The average time of document detection is 1.3 ms, while the accuracy rate reaches 95.9%.
A Specialized Database for Autonomous Vehicles Based on the KITTI Vision Benchmark
Authors: Ortega-Gomez Juan I. , Morales-Hernandez Luis A. , Cruz-Albarran Irving A.
Published: July 2023

Autonomous driving systems have emerged with the promise of preventing accidents. The first critical aspect of these systems is perception, where the regular practice is the use of top-view point clouds as the input; however, the existing databases in this area only present scenes with 3D point clouds and their respective labels. This generates an opportunity, and the objective of this work is to present a database with scenes directly in the top-view and their labels in the respective plane, as well as adding a segmentation map for each scene as a label for segmentation work. The method used during the creation of the proposed database is presented; this covers how to transform 3D to 2D top-view image point clouds, how the detection labels in the plane are generated, and how to implement a neural network for the generated segmentation maps of each scene. Using this method, a database was developed with 7481 scenes, each with its corresponding top-view image, label file, and segmentation map, where the road segmentation metrics are as follows: F1, 95.77; AP, 92.54; ACC, 97.53; PRE, 94.34; and REC, 97.25. This article presents the development of a database for segmentation and detection assignments, highlighting its particular use for environmental perception works.
Resilient Localization and Coverage in the Internet of Things
Authors: Al Mtawa Yaser , Hassanein Hossam S. , Nasser Nidal
Published: July 2023

The proliferation of the Internet of Things (IoT) has revolutionized traditional services, giving rise to emerging smart infrastructures by connecting the physical and digital worlds. Sensory data is essential in IoT-based systems for providing context-aware and location-based services. Hence, the accurate localization of IoT devices is paramount. Anchor misplacement can significantly affect location information and coverage services in IoT. We study the effect of anchor misplacement in typical IoT settings where sensors are randomly deployed, can be mobile, and may belong to multiple providers. We identify sensing coverage holes formed by anchor misplacement and analyze their presence and impact. To mitigate the impact of anchor misplacement on network reliability, we propose a framework to identify the affected sensor nodes and then identify and remove misplaced anchor nodes. The validity of our approach is verified, and its effectiveness is demonstrated by several experiments with different network topologies and parameters. Our results are promising and can be utilized in multiple coverage applications, such as smart agriculture systems and habitat monitoring, regardless of the sensors or deployment types. It also sheds light on best practices and methods for a reliable design of IoT-based systems.
Underwater Image Color Constancy Calculation with Optimized Deep Extreme Learning Machine Based on Improved Arithmetic Optimization Algorithm
Authors: Yang Junyi , Yu Qichao , Chen Sheng , Yang Donghe
Published: July 2023

To overcome the challenges posed by the underwater environment and restore the true colors of marine objects’ surfaces, a novel underwater image illumination estimation model, termed the iterative chaotic improved arithmetic optimization algorithm for deep extreme learning machines (IAOA-DELM), is proposed. In this study, the gray edge framework is utilized to extract color features from underwater images, which are employed as input vectors. To address the issue of unstable prediction results caused by the random selection of parameters in DELM, the arithmetic optimization algorithm (AOA) is integrated, and the search segment mapping method is optimized by using hidden layer biases and input layer weights. Furthermore, an iterative chaotic mapping initialization strategy is incorporated to provide AOA with a better initial search proxy. The IAOA-DELM model computes illumination information based on the input color vectors. Experimental evaluations conducted on actual underwater images demonstrate that the proposed IAOA-DELM illumination correction model achieves an accuracy of 96.07%. When compared to the ORELM, ELM, RVFL, and BP models, the IAOA-DELM model exhibits improvements of 6.96%, 7.54%, 8.00%, and 8.89%, respectively, making it the most effective among the compared illumination correction models.
SP-YOLO-Lite: A Lightweight Violation Detection Algorithm Based on SP Attention Mechanism
Authors: Huang Zhihao , Wu Jiajun , Su Lumei , Xie Yitao , Li Tianyou , Huang Xinyu
Published: July 2023

In the operation site of power grid construction, it is crucial to comprehensively and efficiently detect violations of regulations for the personal safety of the workers with a safety monitoring system based on object detection technology. However, common general-purpose object detection algorithms are difficult to deploy on low-computational-power embedded platforms situated at the edge due to their high model complexity. These algorithms suffer from drawbacks such as low operational efficiency, slow detection speed, and high energy consumption. To address this issue, a lightweight violation detection algorithm based on the SP (Segmentation-and-Product) attention mechanism, named SP-YOLO-Lite, is proposed to improve the YOLOv5s detection algorithm and achieve low-cost deployment and efficient operation of object detection algorithms on low-computational-power monitoring platforms. First, to address the issue of excessive complexity in backbone networks built with conventional convolutional modules, a Lightweight Convolutional Block was employed to construct the backbone network, significantly reducing computational and parameter costs while maintaining high detection model accuracy. Second, in response to the problem of existing attention mechanisms overlooking spatial local information, we introduced an image segmentation operation and proposed a novel attention mechanism called Segmentation-and-Product (SP) attention. It enables the model to effectively capture local informative features of the image, thereby enhancing model accuracy. Furthermore, a Neck network that is both lightweight and feature-rich is proposed by introducing Depthwise Separable Convolution and Segmentation-and-Product attention module to Path Aggregation Network, thus addressing the issue of high computation and parameter volume in the Neck network of YOLOv5s. Experimental results show that compared with the baseline network YOLOv5s, the proposed SP-YOLO-Lite model reduces the computation and parameter volume by approximately 70%, achieving similar detection accuracy on both the VOC dataset and our self-built SMPC dataset.
Hybrid Model Predictive Control with Penalty Factor Based on Image-Based Visual Servoing for Constrained Mobile Robots
Authors: Gu Haojie , Qin Qiuyue , Mao Jingfeng , Sun Xingjian , Huang Yuxu
Published: July 2023

For the constrained mobile robot automatic parking system, the hybrid model predictive control with a penalty factor based on image-based visual servoing (IBVS) is proposed to address the problem of feature point loss and emergency braking in dynamic obstacle scenarios caused by excessive target bias gain when using traditional IBVS control methods. The traditional IBVS control is transformed into an optimization problem with constraints in the finite time domain, by defining the optimization function based on the mobile robot’s positional deviation and image feature point deviation, while using actuator saturation and speed limit as constraints. Based on this, a convex optimization function with penalty factors is defined and combined with incremental model predictive control. This control strategy could ensure the emergency braking performance of the mobile robot when the image feature points are massively obscured by obstacles in dynamic scenes, while improving the accuracy and real-time of its trajectory tracking control. Finally, simulation comparisons are conducted to verify the effectiveness of the proposed control method.