bluuebunny/crossref_metadata_2025 huggingface dataset:
Radiophysiomics: Brain Tumors Classification by Machine Learning and Physiological MRI Data
Authors: Stadlbauer Andreas , Marhold Franz , Oberndorfer Stefan , Heinz Gertraud , Buchfelder Michael , Kinfe Thomas M. , Meyer-Bäse Anke
Published: May 2022

The precise initial characterization of contrast-enhancing brain tumors has significant consequences for clinical outcomes. Various novel neuroimaging methods have been developed to increase the specificity of conventional magnetic resonance imaging (cMRI) but also the increased complexity of data analysis. Artificial intelligence offers new options to manage this challenge in clinical settings. Here, we investigated whether multiclass machine learning (ML) algorithms applied to a high-dimensional panel of radiomic features from advanced MRI (advMRI) and physiological MRI (phyMRI; thus, radiophysiomics) could reliably classify contrast-enhancing brain tumors. The recently developed phyMRI technique enables the quantitative assessment of microvascular architecture, neovascularization, oxygen metabolism, and tissue hypoxia. A training cohort of 167 patients suffering from one of the five most common brain tumor entities (glioblastoma, anaplastic glioma, meningioma, primary CNS lymphoma, or brain metastasis), combined with nine common ML algorithms, was used to develop overall 135 classifiers. Multiclass classification performance was investigated using tenfold cross-validation and an independent test cohort. Adaptive boosting and random forest in combination with advMRI and phyMRI data were superior to human reading in accuracy (0.875 vs. 0.850), precision (0.862 vs. 0.798), F-score (0.774 vs. 0.740), AUROC (0.886 vs. 0.813), and classification error (5 vs. 6). The radiologists, however, showed a higher sensitivity (0.767 vs. 0.750) and specificity (0.925 vs. 0.902). We demonstrated that ML-based radiophysiomics could be helpful in the clinical routine diagnosis of contrast-enhancing brain tumors; however, a high expenditure of time and work for data preprocessing requires the inclusion of deep neural networks.
Fully Automatic Whole-Volume Tumor Segmentation in Cervical Cancer
Authors: Hodneland Erlend , Kaliyugarasan Satheshkumar , Wagner-Larsen Kari Strøno , Lura Njål , Andersen Erling , Bartsch Hauke , Smit Noeska , Halle Mari Kyllesø , Krakstad Camilla , Lundervold Alexander Selvikvåg , Haldorsen Ingfrid Salvesen
Published: May 2022

Uterine cervical cancer (CC) is the most common gynecologic malignancy worldwide. Whole-volume radiomic profiling from pelvic MRI may yield prognostic markers for tailoring treatment in CC. However, radiomic profiling relies on manual tumor segmentation which is unfeasible in the clinic. We present a fully automatic method for the 3D segmentation of primary CC lesions using state-of-the-art deep learning (DL) techniques. In 131 CC patients, the primary tumor was manually segmented on T2-weighted MRI by two radiologists (R1, R2). Patients were separated into a train/validation (n = 105) and a test- (n = 26) cohort. The segmentation performance of the DL algorithm compared with R1/R2 was assessed with Dice coefficients (DSCs) and Hausdorff distances (HDs) in the test cohort. The trained DL network retrieved whole-volume tumor segmentations yielding median DSCs of 0.60 and 0.58 for DL compared with R1 (DL-R1) and R2 (DL-R2), respectively, whereas DSC for R1-R2 was 0.78. Agreement for primary tumor volumes was excellent between raters (R1-R2: intraclass correlation coefficient (ICC) = 0.93), but lower for the DL algorithm and the raters (DL-R1: ICC = 0.43; DL-R2: ICC = 0.44). The developed DL algorithm enables the automated estimation of tumor size and primary CC tumor segmentation. However, segmentation agreement between raters is better than that between DL algorithm and raters.
Stability of Pt-Adsorbed CO on Catalysts for Room Temperature-Oxidation of CO
Authors: Meunier Frédéric C. , Elgayyar Taha , Dembélé Kassiogé , Kaper Helena
Published: May 2022

A large signal of gas-phase CO overlapping with those of adsorbates is often present when investigating catalysts by operando diffuse reflectance FT-IR spectroscopy. Physically removing CO(g) from the IR cell may lead to a fast decay of adsorbate signals. Our work shows that carbonyls adsorbed on metallic Pt sites fully vanished in less than 10 min at 30 °C upon removing CO(g) when redox supports were used. In contrast, a broad band assigned to CO adsorbed on oxidized Pt sites was stable. It was concluded that physically removing CO(g) at room temperature during IR analyses will most likely lead to changes in the distribution of CO(ads) and a misrepresentation of the Pt site speciation, misguiding the development of efficient low-temperature CO oxidation catalysts. A tentative representation of the nature of the Pt phases present depending on the feed composition is also proposed.
Photo-Induced Preparation of Ag@MOF-801 Composite Based Heterogeneous Nanocatalyst for the Production of Biodiesel
Authors: Alduhaish Osamah M. , Shaik Mohammed Rafi , Adil Syed Farooq
Published: May 2022

Hybrid materials based on metal-organic frameworks (MOFs) and nanoparticles (NPs) have gained considerable popularity in a variety of applications. Particularly, these types of materials have demonstrated excellent efficiency in heterogeneous catalysis due to the synergistic effect between the components. Herein, we report a simple, eco-friendly, photocatalytic method for the fabrication of Zr containing MOF-801 and a silver (Ag) NPs-based hybrid (Ag@MOF-801). In this method, the photocatalytic property of the central metal ion (Zr) of MOF was exploited to promote the formation and deposition of Ag NPs on the surface of the MOF-801 under the irradiation of visible light. The successful incorporation of Ag NPs was ascertained by powder X-ray diffraction (XRD) and UV-Vis analysis, while the morphology and surface area of the sample was determined by N2 adsorption–desorption and scanning electron microscopy (SEM), respectively. The resulting Ag@MOF-801 hybrid served as a highly efficient catalyst for the transesterification of used vegetable oil (UVO) for the production of biodiesel. The Ag@MOF-801 catalyst exhibited superior catalytic activity compared to its pristine MOF-801 counterpart due to the enhanced surface area of the material.
Scribble Controls Social Motivation Behavior through the Regulation of the ERK/Mnk1 Pathway
Authors: Moreau Maïté M. , Pietropaolo Susanna , Ezan Jérôme , Robert Benjamin J. A. , Miraux Sylvain , Maître Marlène , Cho Yoon , Crusio Wim E. , Montcouquiol Mireille , Sans Nathalie
Published: May 2022

Social behavior is a basic domain affected by several neurodevelopmental disorders, including ASD and a heterogeneous set of neuropsychiatric disorders. The SCRIB gene that codes for the polarity protein SCRIBBLE has been identified as a risk gene for spina bifida, the most common type of neural tube defect, found at high frequencies in autistic patients, as well as other congenital anomalies. The deletions and mutations of the 8q24.3 region encompassing SCRIB are also associated with multisyndromic and rare disorders. Nonetheless, the potential link between SCRIB and relevant social phenotypes has not been fully investigated. Hence, we show that Scribcrc/+ mice, carrying a mutated version of Scrib, displayed reduced social motivation behavior and social habituation, while other behavioral domains were unaltered. Social deficits were associated with the upregulation of ERK phosphorylation, together with increased c-Fos activity. Importantly, the social alterations were rescued by both direct and indirect pERK inhibition. These results support a link between polarity genes, social behaviors and hippocampal functionality and suggest a role for SCRIB in the etiopathology of neurodevelopmental disorders. Furthermore, our data demonstrate the crucial role of the MAPK/ERK signaling pathway in underlying social motivation behavior, thus supporting its relevance as a therapeutic target.
Pleiotropic Effects of IGF1 on the Oocyte
Authors: Kordowitzki Paweł , Krajnik Kornelia , Skowronska Agnieszka , Skowronski Mariusz T.
Published: May 2022

A woman’s endocrine system plays a crucial role in orchestrating cellular interactions throughout her life. The growth hormone (GH) and insulin-like growth factor (IGF) system appears to impact crucial reproductive events and cell types of the ovary, such as granulosa cells, theca cells, and oocytes. Further, IGF1 is a cornerstone during embryonic development and influences predominantly developing and pre-antral follicles. In this commentary, we will emphasize the pleiotropic effects of IGF1 on physiological processes inside the egg. Herein, we will provide a brief overview on IGF1 related cell signal transduction pathways during the maturation and aging of oocytes. We aim to elucidate from a molecular and biochemical point of view if IGF1 in women with metabolic imbalances such as obesity or diabetes could be used in clinics as a novel, reliable estimator for the developmental competence of an oocyte.
Metastatic Urothelial Carcinoma: Have We Take the Road to the Personalized Medicine?
Authors: Audisio Marco , Buttigliero Consuelo , Turco Fabio , Delcuratolo Marco Donatello , Pisano Chiara , Parlagreco Elena , Di Stefano Rosario Francesco , Di Prima Lavinia , Crespi Veronica , Farinea Giovanni , Cani Massimiliano , Tucci Marcello
Published: May 2022

Urothelial cancer is a lethal malignancy characterized by a wide diffusion in Western countries due to a larger exposure to known risk factors, such as aromatic amines, tobacco smoke and benzene [...]
Fabrication of Functional Super-Hydrophilic TiO2 Thin Film for pH Detection
Authors: Chen Cheng , Zhang Yalei , Gao Han , Xu Kun , Zhang Xiliang
Published: May 2022

A super-hydrophilic pH-sensitive electrode with a porous TiO2 thin film is proposed in this work and fabricated using the chemical etching method. In total, 30 groups of porous TiO2 thin film were obtained by immersing a Ti sheet in NaOH, with the solution concentration ranging from 0.5–4 M and the reaction time ranging from 15–240 min. SEM, XRD, XPS, and a contact angle meter were used to investigate the influence of the chemical etching parameters on the morphology, composition, and wettability of the fabricated electrodes. The chemical etching parameters were found to have a significant influence on the specific surface area and the component of the films, which strongly affected the wettability and pH sensing characteristics of the electrodes. The electrode obtained with a solution concentration of 1 M and reaction time of 120 min is the ideal product because of its excellent wettability, with a contact angle of 5.46°, and good pH sensing characteristics in pH buffer solutions. The electrode also showed good stability regarding its wettability and pH sensing properties during storage and utilization.
Development and Validation of the Young Parenting Inventory (YPI-R3) for Measuring Past Deviant and Normal Variations in Parenting
Authors: Louis John P. , Louis Karen M. , Lockwood George
Published: May 2022

Most measures of past parenting patterns have a restricted range of about two to three negative parenting constructs. The Young Parenting Inventory (YPI-R2) provides a more nuanced framework that measures a fuller spectrum of these negative parenting patterns and, therefore, holds the potential of being a more useful guide to parents and caretakers. The YPI-R2 is made up of six validated subscales. An additional four were identified but were not sufficiently robust to be included. The purpose of this study is to determine if these four scales can be strengthened through the development of additional items and be empirically validated. Using non-clinical, English-speaking community samples from Singapore (n = 592, 628) and Malaysia (n = 222, 229), these revised scales were tested using multiple exploratory factor analyses with fathers and mothers rated separately. After further scale refinement, the final model, which consisted of 10 subscales and 41 items, was then subjected to confirmatory factor analysis using 4 other non-clinical international samples with separate ratings for fathers and mothers—USA (n = 259, 281), South Africa (n = 318, 372), Nigeria (n = 328, 344) and India (n = 277, 289). The results show that the YPI-R3 with 10 subscales is a robust and cross-culturally acceptable model. Correlations and hierarchical multiple regression analyses showed that the YPI-R3 has good convergent validity and predictive capabilities with measures of psychopathology, personality traits, emotional distress, negative schemas and other distal measures of functioning in everyday life—gratitude, humor and satisfaction with life.
Environmental Comparison of Different Mechanical–Biological Treatment Plants by Combining Life Cycle Assessment and Material Flow Analysis
Authors: Gadaleta Giovanni , De Gisi Sabino , Todaro Francesco , Notarnicola Michele
Published: May 2022

The role of Mechanical–Biological Treatment (MBT) is still of the utmost importance in the management of residual Municipal Solid Waste (MSW). These plants can cover a wide range of objectives, combining several types of processes and elements. The aim of this work is to assess and compare, from an environmental point of view, the performance of seven selected MBT plants currently operating in different countries, which represent the main MBT layout and processes. For the scope, a combined Life Cycle Assessment (LCA) and Material Flow Analysis (MFA) approach has been adopted to assess plant-specific efficiencies in materials and energy recovery. Metals recovery was a common and high-efficiency practice in MBT; further recovery of other types of waste was often performed. Each assessed MBT plant achieved environmental benefits: among them, the highest environmental benefit was achieved when the highest amount of waste was recovered (not only with material recycling). Environmental results were strongly affected by the recycling processes and the energy production, with a little contribution from the energy requirement. The impacts achieved by the MBT process were, on average, 14% of the total one. The main condition for a suitable MBT process is a combination of materials recovery for the production of new raw materials, avoiding disposal in landfill, and refuse-derived fuel production for energy recovery. This work can be of help to operators and planners when they are asked to define MBT schemes.
Experimental Analysis of Bearing Capacity of Basalt Fiber Reinforced Concrete Short Columns under Axial Compression
Authors: Wang Xinzhong , Yang Yiming , Yang Rihua , Liu Peng
Published: May 2022

Adding basalt fiber to concrete can improve the mechanical properties of concrete, and it is also one of the best ways to enhance the ultimate bearing capacity of concrete structure. In this paper, the construction performance and the compressive strength of basalt-fiber-reinforced concrete (BFRC) with five kinds of fiber lengths and eight kinds of fiber volume content subjected to an axial load are systematically investigated. The optimum fiber length and fiber volume content are obtained by comprehensively considering the construction performance and compressive strength. Moreover, the prediction model and finite element analysis method of the ultimate bearing capacity of basalt-fiber-reinforced concrete are developed. The results show that the optimum fiber length is about 12–24 mm and the fiber volume content is 0.15%. Adding an appropriate amount of basalt fiber can effectively improve the ultimate bearing capacity of concrete short columns, with maximum and average increases of 28% and 24%, respectively. In addition, the comparison with the experimental results shows that both the proposed prediction method and the finite element modeling method have good applicability, and they can be used to predict the ultimate bearing capacity of the BRFC short columns in practical engineering.
Pulsed Electrodeposition and Properties of Nickel-Based Composite Coatings Modified with Graphene Oxide
Authors: Tseluikin Vitaly , Dzhumieva Asel , Tikhonov Denis , Yakovlev Andrey , Strilets Anastasia , Tribis Alena , Lopukhova Marina
Published: May 2022

Composite electrochemical coatings (CECs) on the basis of nickel modified with multilayer graphene oxide (GO) were deposited from a sulfate–chloride electrolyte in pulsed electrolysis mode. The microstructure of these CECs was studied by X-ray phase analysis and scanning electron microscopy. It was found that the microhardness of nickel–GO CECs increases by approximately 1.40 times compared to pure nickel. The corrosion–electrochemical behavior of nickel–GO composite coatings in 0.5 M H2SO4 was studied. Based on tests in 3.5% NaCl, it was found that the addition of graphene oxide particles into the matrix of nickel electrodeposits, increases their corrosion resistance by 1.40–1.50 times. This can be explained by the uniformity of the distribution of GO in the nickel matrix, which contributes to the reduction in grain size, as well as the impermeability and stability of graphene oxide.
Geomorphological Data from Detonation Craters in the Fehmarn Belt, German Baltic Sea
Authors: Papenmeier Svenja , Darr Alexander , Feldens Peter
Published: May 2022

Military munitions from World War I and II dumped at the seafloor are a threat to the marine environment and its users. Decades of saltwater exposure make the explosives fragile and difficult to dispose of. If required, the munition is blast-in-place. In August 2019, 42 ground mines were detonated in a controlled manner underwater during a NATO maneuver in the German Natura2000 Special Area of Conservation Fehmarn Belt, the Baltic Sea. In June 2020, four detonation craters were investigated with a multibeam echosounder for the first time. This dataset is represented here as maps of bathymetry, slope angle, and height difference to the surrounding. The circular craters were still clearly visible a year after the detonation. The diameter and depth of the structures were between 7.5–12.6 m and 0.7–2.2 m, respectively. In total, about 321 m2 of the seafloor was destroyed along the track line.
Synovial Fluid Interleukin Levels Cannot Distinguish between Prosthetic Joint Infection and Active Rheumatoid Arthritis after Hip or Knee Arthroplasty
Authors: Qin Leilei , Du Chengcheng , Yang Jianye , Wang Hai , Su Xudong , Wei Li , Zhao Chen , Chen Cheng , Chen Hong , Hu Ning , Huang Wei
Published: May 2022

Inflammatory arthritis affects the level of synovial inflammatory factors, which makes it more difficult to diagnose prosthetic joint infection (PJI) patients with inflammatory arthritis. The aim of this study was to analyze synovial interleukin levels to distinguish between PJI and active rheumatoid arthritis (RA) after a hip or knee arthroplasty. From September 2019 to September 2021, we prospectively enrolled patients with joint pain after arthroplasty due to aseptic prosthesis loosening (n = 39), acute RA (n = 26), and PJI (n = 37). Synovial fluid from the affected joint is obtained and tested with a standard enzyme-linked immunosorbent assay. Receiver operating characteristic curve (ROC) was analyzed for each biomarker. Interleukin (IL)-1β, IL-6, and IL-8 showed promising value in differentiating of aseptic loosening from PJI, with areas under the curves (AUCs) of 0.9590, 0.9506, and 0.9616, respectively. Synovial IL-1β, IL-6, and IL-8 showed limited value in distinguishing between PJI and acute episodes of RA after arthroplasty, with AUCs of 0.7507, 0.7069, and 0.7034, respectively. Interleukins showed satisfactory efficacy in differentiating aseptic loosening from PJI. However, when pain after arthroplasty results from an acute episode of RA, current synovial interleukin levels do not accurately rule out the presence of PJI.
Characteristics of Urine Organic Acid Metabolites in Nonalcoholic Fatty Liver Disease Assessed Using Magnetic Resonance Imaging with Elastography in Korean Adults
Authors: Haam Ji-Hee , Lee Yun Kyong , Suh Eunkyung , Kim Young-Sang
Published: May 2022

The liver is an essential organ that manufactures energy through various metabolic pathways; thus, exploring the intermediate metabolites in nonalcoholic fatty liver disease (NAFLD) may help discover novel parameters in hepatic steatosis or fibrosis. The present study aimed to investigate the traits of urine organic acid metabolites in participants with hepatic steatosis and fibrosis in nonalcoholic Korean adults. Hepatic steatosis and fibrosis, in 68 men and 65 women, were evaluated using quantification by proton density fat fraction with magnetic resonance (MR) imaging and MR elastography, respectively. Urine metabolites were obtained using a high-performance liquid chromatography–mass spectrometry analysis. The candidate metabolites were included in the logistic regression models for hepatic steatosis and fibrosis. The association between high p-hydroxyphenyllactate levels and hepatic steatosis was not independent of body mass index and Homeostatic Model Assessment-insulin resistance. High ethylmalonate, β-hydroxybutyrate, and sulfate levels were significantly related to a low probability of hepatic fibrosis, independent of covariates. In conclusion, urine metabolites were not related to hepatic steatosis independent of obesity and insulin resistance, while several metabolites were specifically associated with hepatic fibrosis. Further study is required to verify the diagnostic value of the metabolites in a population with wide-spectrum NAFLD.
Gastrointestinal Involvement in Dermatomyositis
Authors: Matas-Garcia Ana , Milisenda José C. , Espinosa Gerard , Cuatrecasas Míriam , Selva-O’Callaghan Albert , Grau Josep María , Prieto-González Sergio
Published: May 2022

Dermatomyositis is a systemic vasculopathy mainly affecting skin, muscle and lung, but may affect the gastrointestinal tract. We aim to describe clinical characteristics of patients with severe gastrointestinal involvement related to dermatomyositis in our center and medical literature. We retrospectively analysed these patients in our center, including cases of erosions/ulcers, perforation or digestive bleeding. Reported cases from April 1990 to April 2021 were reviewed through PubMed and Cochrane. From our cohort (n = 188), only 3 presented gastrointestinal compromise. All were women (10, 46 and 68 years). The initial symptom was abdominal pain and all had ≥2 episodes of digestive bleeding. All died due to complications of gastrointestinal involvement. Available pathological samples showed vascular ectasia. From the literature review (n = 50), 77% were women with a mean age of 49 years and the main symptom was abdominal pain (65%). All presented active muscular and cutaneous involvement at complication diagnosis. Mortality was 41.7%. The underlying lesion was perforation or ulcer (n = 22), intestinal wall thickening (n = 2), macroscopic inflammation (n = 2) or intestinal pneumatosis (n = 15). In 13 cases, vasculitis was described. Gastrointestinal involvement in dermatomyositis denotes severity, so an early intensive treatment is recommended. Pathological findings suggest that the underlying pathophysiological mechanism is a vasculopathy and not a true vasculitis.
Clinical and Imaging Features of COVID-19-Associated Pulmonary Aspergillosis
Authors: Fischer Tim , El Baz Yassir , Graf Nicole , Wildermuth Simon , Leschka Sebastian , Kleger Gian-Reto , Pietsch Urs , Frischknecht Manuel , Scanferla Giulia , Strahm Carol , Wälti Stephan , Dietrich Tobias Johannes , Albrich Werner C.
Published: May 2022

Background: COVID-19 superinfection by Aspergillus (COVID-19-associated aspergillosis, CAPA) is increasingly observed due to increased awareness and use of corticosteroids. The aim of this study is to compare clinical and imaging features between COVID-19 patients with and without associated pulmonary aspergillosis. Material and Methods: In this case–control study, hospitalized patients between March 2020 and March 2021 were evaluated. Two observers independently compared 105 chest CTs of 52 COVID-19 patients without pulmonary aspergillosis to 40 chest CTs of 13 CAPA patients. The following features were evaluated: lung involvement, predominant main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings. Chronological changes in the abnormal extent upon CT and chronological changes in the main patterns were compared with mixed models. Patient-wise comparisons of additional features and demographic and clinical data were performed using Student’s t-test, Chi-squared test, Fisher’s exact tests and Wilcoxon rank-sum tests. Results: Compared to COVID-19 patients without pulmonary aspergillosis, CAPA patients were older (mean age (±SD): 70.3 (±7.8) versus 63.5 (±9.5) years (p = 0.01). The time-dependent evolution rates for consolidation (p = 0.02) and ground glass (p = 0.006) differed. In early COVID-19 disease, consolidation was associated with CAPA, whereas ground glass was less common. Chronological changes in the abnormal extent upon CT did not differ (p = 0.29). Regardless of the time point, bronchial wall thickening was observed more frequently in CAPA patients (p = 0.03). Conclusions: CAPA patients showed a tendency for consolidation in early COVID-19 disease. Bronchial wall thickening and higher patient age were associated with CAPA. The overall lung involvement was similar between both groups.
The Use of 18F-FET-PET-MRI in Neuro-Oncology: The Best of Both Worlds—A Narrative Review
Authors: van de Weijer Tineke , Broen Martijn P. G. , Moonen Rik P. M. , Hoeben Ann , Anten Monique , Hovinga Koos , Compter Inge , van der Pol Jochem A. J. , Mitea Cristina , Lodewick Toine M. , Jacquerie Arnaud , Mottaghy Felix M. , Wildberger Joachim E. , Postma Alida A.
Published: May 2022

Gliomas are the most frequent primary tumors of the brain. They can be divided into grade II-IV astrocytomas and grade II-III oligodendrogliomas, based on their histomolecular profile. The prognosis and treatment is highly dependent on grade and well-identified prognostic and/or predictive molecular markers. Multi-parametric MRI, including diffusion weighted imaging, perfusion, and MR spectroscopy, showed increasing value in the non-invasive characterization of specific molecular subsets of gliomas. Radiolabeled amino-acid analogues, such as 18F-FET, have also been proven valuable in glioma imaging. These tracers not only contribute in the diagnostic process by detecting areas of dedifferentiation in diffuse gliomas, but this technique is also valuable in the follow-up of gliomas, as it can differentiate pseudo-progression from real tumor progression. Since multi-parametric MRI and 18F-FET PET are complementary imaging techniques, there may be a synergistic role for PET-MRI imaging in the neuro-oncological imaging of primary brain tumors. This could be of value for both primary staging, as well as during treatment and follow-up.
Plasma microRNAs as a Potential Biomarker for Identification of Progressive Supranuclear Palsy
Authors: Ramaswamy Palaniswamy , Christopher Rita , Kumar Pal Pramod , Debnath Monojit , Yadav Ravi
Published: May 2022

Progressive supranuclear palsy (PSP) is the second most common Parkinsonian disorder with complex etiology. The underlying molecular mechanism of PSP pathogenesis remains unclear. The present study aims to find the feasibility of using plasma miRNAs as novel biomarkers. Plasma-focused qPCR panels were used for microRNA profiling and identified differentially expressed microRNAs in PSP compared to controls. The DIANA-miRPath v3.0 was used to perform KEGG pathway analysis. We then confirmed the expression of selected candidates by RT-qPCR and their clinical utility was assessed by ROC analysis. Profiling data revealed 28 differentially expressed microRNAs in PSP. Five overexpressed miRNAs were selected for further analysis. The KEGG pathway analysis revealed 48 high-risk pathways. The study revealed that as a single marker—miR-19b-3p, miR-33a-5p, miR-130b-3p, miR-136-3p, and miR-210-3p had a specificity of 64.71%, 82.35%, 68.75%, 82.35%, and 70.59% at sensitivity 77.78%, 77.78%, 66.67%, 73.33%, and 66.67%, respectively. The result suggests that circulating plasma miRNAs were altered in PSP compared to control. The findings of this study may provide potential biomarkers and pathways associated with PSP. Further large-scale validation studies are required to confirm the same.
Improving Nasal Airflow with a Novel Nasal Breathing Stent
Authors: Suzuki Hiroshi , Sawa Arisa , Yagi Tatsuo , Iwata Yoshihiro , Nakayama Toshiyuki , Chow Chin-Moi , Komiyama Osamu
Published: May 2022

Nasal obstruction requires close attention, as it is a risk factor for obstructive sleep apnea (OSA). This study evaluated airflow rates of our newly designed nasal breathing stent (NBS) compared with those of existing nasal dilators in 10 adult men. We hypothesized that the NBS would expand the nasal passage more than the other nasal dilators by means of airflow measurements. We compared airflow measurements between the NBS and three existing appliances and no appliance. Velocity measurements were recorded by analyzing 499 videographic images when each appliance was placed next to a steam generator at 0, 5, and 10 mm from the outlet port for airflow visualization. The peak nasal inspiratory flow (PNIF) rate was measured using an inspiratory flow meter. The NBS resulted in significantly higher airflow velocity measurements at all distances from the outlet port and a higher PNIF rate than the other appliances. Thus, the NBS offers a significantly decreased resistance to air movement compared with other appliances. Future in-depth investigations are required to demonstrate the use of NBS as a nasal dilator in conjunction with continuous positive airway pressure/oral appliance treatments in patients with OSA.
Distally Tilted Implants According to the All-on-Four® Treatment Concept for the Rehabilitation of Complete Edentulism: A 3.5-Year Retrospective Radiographic Study of Clinical Outcomes and Marginal Bone Level Changes
Authors: Szabó Árpád László , Nagy Ádám László , Lászlófy Csaba , Gajdács Márió , Bencsik Péter , Kárpáti Krisztina , Baráth Zoltán
Published: May 2022

Bone grafting procedures during the use of dental implants may be avoided by the use of tilted implants in the maxilla and the mandible; advantages of angled implants are associated with the extension of the distal cantilever, leading to better implant survival rates. However, the bending effect on the single tilting implants may increase the marginal bone stress. The purpose of the present study was to retrospectively assess the clinical success and proximal bone loss rate following the implantation of distally tilted implants according to the All-on-Four™ prosthetic concept—based on radiographic findings—in a single-center experience, in addition to the assessment of the outcomes in the context of various clinico-epidemiological correlates. During the study period, n = 36 patients (24 males and 12 females) with complete records of periapical radiographs, received a full-arch fixed bridge supported by two axial and two distal tilted implants; overall n = 144 and n = 144 implants (Nobel B) were place in the maxilla and mandibles of patients, respectively. Mean age of patients at the time of fixture installation was 58.75 ± 13.71 years; n =11 patients presented with relevant underlying conditions/habits. To assess peri-implant bone-level changes, matched and calibrated orthopantomogram (OPT) images were taken at follow-ups after 1.5 years, 2.5 years, and 3.5 years post-restoration, and marginal bone levels were assessed on the mesio- (MA) and disto-approximal (DA) aspects. All implants were successful, resulting in a 100% overall survival rate. The radiographic mean bone loss levels at baseline (mean ± SEM) were 0.181 ± 0.011 mm and 0.178 ± 0.017 mm in the maxilla and mandible, respectively, while by the 3.5-year mark, bone loss was 0.770 ± 0.029 mm and 0.713 ± 0.026 mm in the maxilla and mandible (p > 0.05), respectively; bone-level changes were significant over time (p = 0.035 and p = 0.033). Peri-implant bone loss was more aggressive around titled distal implants versus mesial actual position implants. The effect of smoking and other underlying conditions showed significantly higher (p < 0.05) bone resorption levels when assessed on an individual implant-level, while during patient-level analysis, only a tendency was shown for higher bone loss rates for both MA and DA implants (p > 0.05). Within its limitations, our study has concluded that the use of All-on-Four™ prosthetic concept for total arch rehabilitation yields higher bone loss in association with tilted implants and, in some cases, on the MA surfaces at vertically positioned implants after >40 months in function.
Blind Speech Watermarking Method with Frame Self-Synchronization Based on Spread-Spectrum Using Linear Prediction Residue
Authors: Isoyama Takuto , Kidani Shunsuke , Unoki Masashi
Published: May 2022

State-of-the-art speech watermarking techniques enable speech signals to be authenticated and protected against any malicious attack to ensure secure speech communication. In general, reliable speech watermarking methods must satisfy four requirements: inaudibility, robustness, blind-detectability, and confidentiality. We previously proposed a method of non-blind speech watermarking based on direct spread spectrum (DSS) using a linear prediction (LP) scheme to solve the first two issues (inaudibility and robustness) due to distortion by spread spectrum. This method not only effectively embeds watermarks with small distortion but also has the same robustness as the DSS method. There are, however, two remaining issues with blind-detectability and confidentiality. In this work, we attempt to resolve these issues by developing an approach called the LP-DSS scheme, which takes two forms of data embedding for blind detection and frame synchronization. We incorporate blind detection with frame synchronization into the scheme to satisfy blind-detectability and incorporate two forms of data embedding process, front-side and back-side embedding for blind detection and frame synchronization, to satisfy confidentiality. We evaluated these improved processes by carrying out four objective tests (PESQ, LSD, Bit-error-rate, and accuracy of frame synchronization) to determine whether inaudibility and blind-detectability could be satisfied. We also evaluated all combinations with the two forms of data embedding for blind detection with frame synchronization by carrying out BER tests to determine whether confidentiality could be satisfied. Finally, we comparatively evaluated the proposed method by carrying out ten robustness tests against various processing and attacks. Our findings showed that an inaudible, robust, blindly detectable, and confidential speech watermarking method based on the proposed LP-DSS scheme could be achieved.
Gull’s Theorem Revisited
Authors: Gill Richard D.
Published: May 2022

In 2016, Steve Gull has outlined has outlined a proof of Bell’s theorem using Fourier theory. Gull’s philosophy is that Bell’s theorem (or perhaps a key lemma in its proof) can be seen as a no-go theorem for a project in distributed computing with classical, not quantum, computers. We present his argument, correcting misprints and filling gaps. In his argument, there were two completely separated computers in the network. We need three in order to fill all the gaps in his proof: a third computer supplies a stream of random numbers to the two computers representing the two measurement stations in Bell’s work. One could also imagine that computer replaced by a cloned, virtual computer, generating the same pseudo-random numbers within each of Alice and Bob’s computers. Either way, we need an assumption of the presence of shared i.i.d. randomness in the form of a synchronised sequence of realisations of i.i.d. hidden variables underlying the otherwise deterministic physics of the sequence of trials. Gull’s proof then just needs a third step: rewriting an expectation as the expectation of a conditional expectation given the hidden variables.
Linking Leadership to Employees Performance: The Mediating Role of Human Resource Management
Authors: Siraj Nuru , Hágen István , Cahyadi Afriyadi , Tangl Anita , Desalegn Goshu
Published: May 2022

Human resource management (HRM) practices along with appropriate leadership have a paramount role in enhancing employees’ performance. Even though there was much literature on the subject of HRM and leadership, there were still some unanswered questions about the set of HR practices that most effectively contribute to improved employees’ performance through proper leadership. The primary goal of this research was to look at how leadership quality affects employee performance, as well as the function of human resource management in mediating the relationship between leadership and employee performance in manufacturing industries in Addis Ababa, Ethiopia. The study used an explanatory and descriptive research design, and a mixed research approach (qualitative and quantitative), to achieve its goal. More specifically, a multi-stage sampling technique (simple random and purposive sampling) was employed. The data was collected from both primary and secondary sources, and analysis was made using a structural and measurement model by AMOS Version 2021. The finding of the study implies that; leadership has a positive and significant relationship with employee performance through human resource management, hence the full mediating role of human resource management was observed between leadership and employee performance. This study is novel in that, it contributes new finding to the existing literature by combining the relationship between leadership and employee performance in a single study and two different directions (direct and indirect). Hence, the recommendations can be applied by industry managers to boost employees’ performance through appropriate HRM practices and leadership by taking this finding as a benchmark. Based on the finding of the study, we recommend industry managers focus on human resource management indicators such as collaboration, involvement, actualization, perceivance, and teamwork to boost their leadership quality that deliberately influences employees’ performance.
How do Facilitating Conditions Influence Student-to-Student Interaction within an Online Learning Platform? A New Typology of the Serial Mediation Model
Authors: Wut Tai Ming , Lee Stephanie Wing , Xu Jing (Bill)
Published: May 2022

This study investigates factors affecting university student-to-student interaction within online learning platforms. A new model was proposed based on the United Theory of Acceptance and Use of Technology (UTAUT). The single-stage cluster-sampling method was employed, and 113 university students in Hong Kong were respondents. It was found that Information Quality, Social Influence, and Facilitating Conditions affect students’ intention to interact with each other. A quasi-full mediation model was established of the mechanism from Facilitating Conditions to students’ interaction behavior. The direct effect of Facilitating Conditions on students’ interaction and the effect of System Quality on the intention of student interaction were not significant. A fast network, computing facilities, and mobile-friendly software are possible candidates of the virtual environment conditions affecting the intention of student-interaction behavior within online learning platforms.
Distributed Deep Learning: From Single-Node to Multi-Node Architecture
Authors: Lerat Jean-Sébastien , Mahmoudi Sidi Ahmed , Mahmoudi Saïd
Published: May 2022

During the last years, deep learning (DL) models have been used in several applications with large datasets and complex models. These applications require methods to train models faster, such as distributed deep learning (DDL). This paper proposes an empirical approach aiming to measure the speedup of DDL achieved by using different parallelism strategies on the nodes. Local parallelism is considered quite important in the design of a time-performing multi-node architecture because DDL depends on the time required by all the nodes. The impact of computational resources (CPU and GPU) is also discussed since the GPU is known to speed up computations. Experimental results show that the local parallelism impacts the global speedup of the DDL depending on the neural model complexity and the size of the dataset. Moreover, our approach achieves a better speedup than Horovod.
Quantum Brain Networks: A Perspective
Authors: Miranda Eduardo R. , Martín-Guerrero José D. , Venkatesh Satvik , Hernani-Morales Carlos , Lamata Lucas , Solano Enrique
Published: May 2022

We propose Quantum Brain Networks (QBraiNs) as a new interdisciplinary field integrating knowledge and methods from neurotechnology, artificial intelligence, and quantum computing. The objective is to develop an enhanced connectivity between the human brain and quantum computers for a variety of disruptive applications. We foresee the emergence of hybrid classical-quantum networks of wetware and hardware nodes, mediated by machine learning techniques and brain–machine interfaces. QBraiNs will harness and transform in unprecedented ways arts, science, technologies, and entrepreneurship, in particular activities related to medicine, Internet of Humans, intelligent devices, sensorial experience, gaming, Internet of Things, crypto trading, and business.
Anomaly Detection in Multi-Host Environment Based on Federated Hypersphere Classifier
Authors: Kwon Junhyung , Jung Byeonggil , Lee Hyungil , Lee Sangkyun
Published: May 2022

Detecting anomalous inputs is essential in many mission-critical systems in various domains, particularly cybersecurity. In particular, deep neural network-based anomaly detection methods have been successful for anomaly detection tasks with the recent advancements in deep learning technology. Nevertheless, the existing methods have considered somewhat idealized problems where it is enough to learn a single detector based on a single dataset. In this paper, we consider a more practical problem where multiple hosts in an organization collect their input data, while data sharing among the hosts is prohibitive due to security reasons, and only a few of them have experienced abnormal inputs. Furthermore, the data distribution of the hosts can be skewed; for example, a particular type of input can be observed by a limited subset of hosts. We propose the federated hypersphere classifier (FHC), which is a new anomaly detection method based on an improved hypersphere classifier suited for running in the federated learning framework to perform anomaly detection in such an environment. Our experiments with image and network intrusion detection datasets show that our method outperforms the state-of-the-art anomaly detection methods trained in a host-wise fashion by learning a consensus model as if we have accessed the input data from all hosts but without communicating such data.
Evaluation of GaN HEMTs in H3TRB Reliability Testing
Authors: Rodriguez Jose A. , Tsoi Tsz , Graves David , Bayne Stephen B.
Published: May 2022

Gallium Nitride (GaN) power devices can offer better switching performance and higher efficiency than Silicon Carbide (SiC) and Silicon (Si) devices in power electronics applications. GaN has extensively been incorporated in electric vehicle charging stations and power supplies, subjected to harsh environmental conditions. Many reliability studies evaluate GaN power devices through thermal stresses during current conduction or pulsing, with a few focusing on high blocking voltage and high humidity. This paper compares GaN-on-Si High-Electron-Mobility Transistors (HEMT) device characteristics under a High Humidity, High Temperature, Reverse Bias (H3TRB) Test. Twenty-one devices from three manufacturers were subjected to 85 °C and 85% relative humidity while blocking 80% of their voltage rating. Devices from two manufacturers utilize a cascade configuration with a silicon metal-oxide-semiconductor field-effect transistor (MOSFET), while the devices from the third manufacturer are lateral p-GaN HEMTs. Through characterization, three sample devices have exhibited degraded blocking voltage capability. The results of the H3TRB test and potential causes of the failure mode are discussed.
Transforming Future Cities: Smart City
Authors: Singh Dhananjay , Jara Antonio J.
Published: May 2022

The primitive elements of city transformation include the integration of urban infrastructure and artificial intelligence and cutting edge IoT technologies [...]
A Triple Relation Network for Joint Entity and Relation Extraction
Authors: Wang Zixiang , Yang Liqun , Yang Jian , Li Tongliang , He Longtao , Li Zhoujun
Published: May 2022

Recent methods of extracting relational triples mainly focus on the overlapping problem and achieve considerable performance. Most previous approaches extract triples solely conditioned on context words, but ignore the potential relations among the extracted entities, which will cause incompleteness in succeeding Knowledge Graphs’ (KGs) construction. Since relevant triples give a clue for establishing implicit connections among entities, we propose a Triple Relation Network (Trn) to jointly extract triples, especially handling extracting implicit triples. Specifically, we design an attention-based entity pair encoding module to identify all normal entity pairs directly. To construct implicit connections among these extracted entities in triples, we utilize our triple reasoning module to calculate relevance between two triples. Then, we select the top-K relevant triple pairs and transform them into implicit entity pairs to predict the corresponding implicit relations. We utilize a bipartite matching objective to match normal triples and implicit triples with the corresponding labels. Extensive experiments demonstrate the effectiveness of the proposed method on two public benchmarks, and our proposed model significantly outperforms previous strong baselines.
Real Time Power Control in a High Voltage Power Supply for Dielectric Barrier Discharge Reactors: Implementation Strategy and Load Thermal Analysis
Authors: Neretti Gabriele , Popoli Arturo , Scaltriti Silvia Giuditta , Cristofolini Andrea
Published: May 2022

Atmospheric-pressure plasma treatments for industrial and biomedical applications are often performed using Dielectric Barrier Discharge reactors. Dedicated power supplies are needed to provide the high voltage frequency waveforms to operate these nonlinear and time-dependent loads. Moreover, there is a growing technical need for reliable and reproducible treatments, which require the discharge parameters to be actively controlled. In this work, we illustrate a low-cost power supply topology based on a push–pull converter. We perform experimental measurements on two different reactor topologies (surface and volumetric), showing that open loop operation of the power supply leads to a temperature and average power increase over time. The temperature increases by ΔTvol~120 °C and ΔTsup~70 °C, while the power increases by ΔPvol~78% and ΔPsup~60% for the volumetric (40 s) and superficial reactors (120 s), respectively. We discuss how these changes are often unwanted in practical applications. A simplified circuital model of the power supply–reactor system is used to infer the physical relation between the observed reactor thermal behavior and its electrical characteristics. We then show a control strategy for the power supply voltage to ensure constant average power operation of the device based on real-time power measurements on the high voltage side of the power supply and an empirical expression relating the delivered power to the power supply output voltage. These are performed with an Arduino Due microcontroller unit, also used to control the power supply. In a controlled operation the measured power stays within 5% of the reference value for both configurations, reducing the temperature increments to ΔTvol~80 °C and ΔTsup~44 °C, respectively. The obtained results show that the proposed novel control strategy is capable of following the transient temperature behavior, achieving a constant average power operation and subsequently limiting the reactor thermal stress.