bluuebunny/crossref_metadata_2025 huggingface dataset:
Epigenetic Mechanisms as Emerging Therapeutic Targets and Microfluidic Chips Application in Pulmonary Arterial Hypertension
Authors: Ho Linh , Hossen Nazir , Nguyen Trieu , Vo Au , Ahsan Fakhrul
Published: January 2022

Pulmonary arterial hypertension (PAH) is a disease that progress over time and is defined as an increase in pulmonary arterial pressure and pulmonary vascular resistance that frequently leads to right-ventricular (RV) failure and death. Epigenetic modifications comprising DNA methylation, histone remodeling, and noncoding RNAs (ncRNAs) have been established to govern chromatin structure and transcriptional responses in various cell types during disease development. However, dysregulation of these epigenetic mechanisms has not yet been explored in detail in the pathology of pulmonary arterial hypertension and its progression with vascular remodeling and right-heart failure (RHF). Targeting epigenetic regulators including histone methylation, acetylation, or miRNAs offers many possible candidates for drug discovery and will no doubt be a tempting area to explore for PAH therapies. This review focuses on studies in epigenetic mechanisms including the writers, the readers, and the erasers of epigenetic marks and targeting epigenetic regulators or modifiers for treatment of PAH and its complications described as RHF. Data analyses from experimental cell models and animal induced PAH models have demonstrated that significant changes in the expression levels of multiple epigenetics modifiers such as HDMs, HDACs, sirtuins (Sirt1 and Sirt3), and BRD4 correlate strongly with proliferation, apoptosis, inflammation, and fibrosis linked to the pathological vascular remodeling during PAH development. The reversible characteristics of protein methylation and acetylation can be applied for exploring small-molecule modulators such as valproic acid (HDAC inhibitor) or resveratrol (Sirt1 activator) in different preclinical models for treatment of diseases including PAH and RHF. This review also presents to the readers the application of microfluidic devices to study sex differences in PAH pathophysiology, as well as for epigenetic analysis.
Systemic Injection of Oncolytic Vaccinia Virus Suppresses Primary Tumor Growth and Lung Metastasis in Metastatic Renal Cell Carcinoma by Remodeling Tumor Microenvironment
Authors: Park Jee Soo , Lee Myung Eun , Jang Won Sik , Kim Jongchan , Park Se Mi , Oh Keunhee , Lee Namhee , Ham Won Sik
Published: January 2022

Immune checkpoint inhibitors and tyrosine kinase inhibitors are the first-line treatment for metastatic renal cell carcinoma (mRCC), but their benefits are limited to specific patient subsets. Here, we aimed to evaluate the therapeutic efficacy of JX-594 (pexastimogene devacirepvec, Pexa-vec) monotherapy by systemic injection in comparison with sunitinib monotherapy in metastatic orthotopic RCC murine models. Two highly metastatic orthotopic RCC models were developed to compare the treatment efficacy in the International Metastatic RCC Database Consortium favorable-risk and intermediate- or poor-risk groups. JX-594 was systemically injected through the peritoneum, whereas sunitinib was orally administered. Post-treatment, tumor microenvironment (TME) remodeling was determined using immunofluorescence analysis. Systemic JX-594 monotherapy injection demonstrated therapeutic benefit in both early- and advanced-stage mRCC models. Sunitinib monotherapy significantly reduced the primary tumor burden and number of lung metastases in the early-stage, but not in the advanced-stage mRCC model. Systemic JX-594 delivery remodeled the primary TME and lung metastatic sites by increasing tumor-infiltrating CD4/8+ T cells and dendritic cells. Systemic JX-594 monotherapy demonstrated significantly better therapeutic outcomes compared with sunitinib monotherapy in both early- and advanced-stage mRCCs by converting cold tumors into hot tumors. Sunitinib monotherapy effectively suppressed primary tumor growth and lung metastasis in early-stage mRCC.
A More Diverse Cervical Microbiome Associates with Better Clinical Outcomes in Patients with Endometriosis: A Pilot Study
Authors: Chang Cherry Yin-Yi , Chiang An-Jen , Lai Ming-Tsung , Yan Man-Ju , Tseng Chung-Chen , Lo Lun-Chien , Wan Lei , Li Chia-Jung , Tsui Kuan-Hao , Chen Chih-Mei , Hwang Tritium , Tsai Fuu-Jen , Sheu Jim Jinn-Chyuan
Published: January 2022

Infection-induced chronic inflammation is common in patients with endometriosis. Although microbial communities in the reproductive tracts of patients have been reported, little was known about their dynamic profiles during disease progression and complication development. Microbial communities in cervical mucus were collected by cervical swabs from 10 healthy women and 23 patients, and analyzed by 16S rRNA amplicon sequencing. The abundance, ecological relationships and functional networks of microbiota were characterized according to their prevalence, clinical stages, and clinical features including deeply infiltrating endometriosis (DIE), CA125, pain score and infertility. Cervical microbiome can be altered during endometriosis development and progression with a tendency of increased Firmicutes and decreased Actinobacteria and Bacteroidetes. Distinct from vaginal microbiome, upregulation of Lactobacillus, in combination with increased Streptococcus and decreased Dialister, was frequently associated with advanced endometriosis stages, DIE, higher CA125 levels, severe pain, and infertility. Significantly, reduced richness and diversity of cervical microbiome were detected in patients with more severe clinical symptoms. Clinical treatments against infertility can partially reverse the ecological balance of microbes through remodeling nutrition metabolism and transport and cell-cell/cell-matrix interaction. This study provides a new understanding on endometriosis development and a more diverse cervical microbiome may be beneficial for patients to have better clinical outcomes.
Hypoxia Preconditioned Serum (HPS)-Hydrogel Can Accelerate Dermal Wound Healing in Mice—An In Vivo Pilot Study
Authors: Jiang Jun , Kraneburg Ursula , Dornseifer Ulf , Schilling Arndt F. , Hadjipanayi Ektoras , Machens Hans-Günther , Moog Philipp
Published: January 2022

The ability to use the body’s resources to promote wound repair is increasingly becoming an interesting area of regenerative medicine research. Here, we tested the effect of topical application of blood-derived hypoxia preconditioned serum (HPS) on wound healing in a murine wound model. Alginate hydrogels loaded with two different HPS concentrations (10 and 40%) were applied topically on full-thickness wounds created on the back of immunocompromised mice. We achieved a significant dose-dependent wound area reduction after 5 days in HPS-treated groups compared with no treatment (NT). On average, both HPS-10% and HPS-40% -treated wounds healed 1.4 days faster than NT. Healed tissue samples were investigated on post-operative day 15 (POD 15) by immunohistology and showed an increase in lymphatic vessels (LYVE-1) up to 45% with HPS-40% application, while at this stage, vascularization (CD31) was comparable in the HPS-treated and NT groups. Furthermore, the expression of proliferation marker Ki67 was greater on POD 15 in the NT-group compared to HPS-treated groups, in accordance with the earlier completion of wound healing observed in the latter. Collagen deposition was similar in all groups, indicating lack of scar tissue hypertrophy as a result of HPS-hydrogel treatment. These findings show that topical HPS application is safe and can accelerate dermal wound healing in mice.
Advanced Methods for Structural Rehabilitation
Authors: Aprile Alessandra , Monti Giorgio
Published: January 2022

Structural rehabilitation has globally become an urgent need due to both widespread construction obsolescence and more demanding requirements from modern construction codes, especially in earthquake-prone areas, where upgrading the existing constructions has become a primary goal [...]
Coke Deposition and Structural Changes of Pellet V2O5/NaY-SiO2 in Air Regeneration: The Effects of Temperature on Regeneration
Authors: Hsieh Chu-Chin , Tsai Jyong-Sian , Sheu Hwo-Shuenn , Chang Jen-Ray
Published: January 2022

V2O5/NaY-SiO2 adsorbents were prepared by soaking up vanadium oxalate precursors into pellet NaY-SiO2. The NaY-SiO2 supports were prepared from NaY-SiO2 dough followed by extrusion and calcination at 450 °C. Ethanol was used as a model adsorbate to test the performance of the adsorbents. The regeneration efficacy, defined as the ratio of the adsorption capacity of a regenerated adsorbent to that of the fresh adsorbent, was investigated through the dynamics of fixed-bed adsorption (breakthrough curve). TPO, DSC, and FT-IR were used to characterize carbonaceous species on the adsorbents; meanwhile, synchrotron XRPD, XAS, and the N2 isotherm were used to characterize the zeolite, vanadia structure, and surface area, respectively. The results indicated that in low temperature (300 °C) regeneration, adsorption sites covered by alkylated aromatic coke formed during regeneration, causing adsorbent deactivation. In contrast, during regeneration at a high temperature (450 °C), the deactivation was caused by the destruction of the NaY framework concomitant with channel blockage, as suggested by the BET surface area combined with Rietvelt XRPD refinement results. In addition, the appearance of V-O-V contribution in the EXAFS spectra indicated the aggregation of isolated VO4, which led to a decrease in the combustion rate of the carbonaceous species deposited on the adsorbents. For regeneration at 350 and 400 °C, only trace coke formation and minor structural destruction were observed. Long-term life tests indicated that regeneration at 400 °C presents a higher maintenance of stability.
PdAg/C Electrocatalysts Synthesized by Thermal Decomposition of Polymeric Precursors Improve Catalytic Activity for Ethanol Oxidation Reaction
Authors: Fornazier Filho Yonis , da Cruz Ana Caroliny Carvalho , Pedicini Rolando , Salgado José Ricardo Cezar , Rodrigues Rodrigo Vieira , Luz Priscilla Paiva , Garcia-Segura Sergi , Ribeiro Josimar
Published: January 2022

An efficient ethanol oxidation reaction (EOR) is required to enhance energy production in alcohol-based fuel cells. The use of bimetallic catalysts promises decreasing reliance on platinum group metal (PGM) electrocatalysts by minimizing the use of these expensive materials in the overall electrocatalyst composition. In this article, an alternative method of bimetallic electrocatalyst synthesis based on the use of polymeric precursors is explored. PdAg/C electrocatalysts were synthesized by thermal decomposition of polymeric precursors and used as the anode electrocatalyst for EOR. Different compositions, including pristine Pd/C and Ag/C, as well as bimetallic Pd80Ag20/C, and Pd60Ag40/C electrocatalysts, were evaluated. Synthesized catalysts were characterized, and electrochemical activity evaluated. X-ray diffraction showed a notable change at diffraction peak values for Pd80Ag20/C and Pd60Ag40/C electrocatalysts, suggesting alloying (solid solution) and smaller crystallite sizes for Pd60Ag40/C. In a thermogravimetric analysis, the electrocatalyst Pd60Ag40/C presented changes in the profile of the curves compared to the other electrocatalysts. In the cyclic voltammetry results for EOR in alkaline medium, Pd60Ag40/C presented a more negative onset potential, a higher current density at the oxidation peak, and a larger electrically active area. Chronoamperometry tests indicated a lower poisoning rate for Pd60Ag40/C, a fact also observed in the CO-stripping voltammetry analysis due to its low onset potential. As the best performing electrocatalyst, Pd60Ag40/C has a lower mass of Pd (a noble and expensive metal) in its composition. It can be inferred that this bimetallic composition can contribute to decreasing the amount of Pd required while increasing the fuel cell performance and expected life. PdAg-type electrocatalysts can provide an economically feasible alternative to pure PGM-electrocatalysts for use as the anode in EOR in fuel cells.
Tumoral Neuroligin 1 Promotes Cancer–Nerve Interactions and Synergizes with the Glial Cell Line-Derived Neurotrophic Factor
Authors: Bizzozero Laura , Pergolizzi Margherita , Pascal Davide , Maldi Elena , Villari Giulia , Erriquez Jessica , Volante Marco , Serini Guido , Marchiò Caterina , Bussolino Federico , Arese Marco
Published: January 2022

Many nervous proteins are expressed in cancer cells. In this report, we asked whether the synaptic protein neuroligin 1 (NLGN1) was expressed by prostatic and pancreatic carcinomas; in addition, given the tendency of these tumors to interact with nerves, we asked whether NLGN1 played a role in this process. Through immunohistochemistry on human tissue microarrays, we showed that NLGN1 is expressed by prostatic and pancreatic cancer tissues in discrete stages and tumor districts. Next, we performed in vitro and in vivo assays, demonstrating that NLGN1 promotes cancer cell invasion and migration along nerves. Because of the established role of the neurotrophic factor glial cell line-derived neurotrophic factor (GDNF) in tumor–nerve interactions, we assessed a potential NLGN1–GDNF cooperation. We found that blocking GDNF activity with a specific antibody completely inhibited NLGN1-induced in vitro cancer cell invasion of nerves. Finally, we demonstrated that, in the presence of NLGN1, GDNF markedly activates cofilin, a cytoskeletal regulatory protein, altering filopodia dynamics. In conclusion, our data further prove the existence of a molecular and functional cross-talk between the nervous system and cancer cells. NLGN1 was shown here to function along one of the most represented neurotrophic factors in the nerve microenvironment, possibly opening new therapeutic avenues.
Fluorescent Analogues of FRH Peptide: Cu(II) Binding and Interactions with ds-DNA/RNA
Authors: Košćak Marta , Krošl Ivona , Žinić Biserka , Piantanida Ivo
Published: January 2022

Four novel peptidoids, derived from the Phe-Arg-His (FRH) peptide motif, were prepared by replacing the histidine heterocycle with triazole and consequent triazole-fluorophore (coumarin) extension and also replacing arginine with less voluminous lysine. So the constructed Phe-Lys-Ala(triazole) (FKA(triazole)) peptidoids bind Cu2+ cations in water with a strong, nanomolar affinity comparable to the parent FRH and its known analogs, demonstrating that triazole can coordinate copper similarly as histidine. Moreover, even short KA(triazole)coumarin showed submicromolar affinity to Cu2+. Only FKA(triazole)coumarin with free amino groups and its shorter analog KA(triazole)coumarin showed strong induced CD spectra upon Cu2+ cation binding. Thus, KA(triazole)coumarin can be considered as the shortest peptidoid sequence with highly sensitive fluorescent and chiral CD response for Cu2+ cation, encouraging further studies with other metal cations. The FKA(triazole) coumarin peptidoids show biorelevant, 10 µM affinity to ds-DNA and ds-RNA, binding within DNA/RNA grooves. Intriguingly, only peptidoid complexes with Cu2+ strongly stabilize ds-DNA and ds-RNA against thermal denaturation, suggesting significant interactions of Cu2+ cation within the DNA/RNA binding site.
Burden of Traumatic Brain Injuries in Children and Adolescents in Europe: Hospital Discharges, Deaths and Years of Life Lost
Authors: Majdan Marek , Melichova Juliana , Plancikova Dominika , Sivco Patrik , Maas Andrew I. R. , Feigin Valery L. , Polinder Suzanne , Haagsma Juanita A.
Published: January 2022

Children and adolescents are at high risk of traumatic brain injuries (TBI). To identify those most at risk across Europe, a comprehensive epidemiological study on the burden of TBI is needed. Our aim was to estimate the burden of TBI in the pediatric and adolescent population of Europe by calculating rates of hospital-based incidence, death and years of life lost (YLL) due to TBI in 33 countries of Europe in 2014 (most recent available data). We conducted a cross-sectional observational, population-based study. All cases with TBI in the age range 0 to 19, registered in the causes of death databases or hospital discharge databases of 33 European countries were included. Crude and age-standardized rates of hospital discharges, deaths and YLLs due to TBI; and pooled estimates for all countries combined were calculated. TBI caused 2303 deaths (71% in boys), 154,282 YLLs (68% in boys) and 441,368 hospital discharges (61% in boys) in the population of 0–19 year-olds. We estimated pooled age-standardized rates of death (2.8, 95% CI: 2.4–3.3), YLLs (184.4, 95% CI: 151.6–217.2) and hospital discharges (344.6, 95% CI: 250.3–438.9) for the analyzed countries in 2014. The population of 15–19 year-olds had the highest rates of deaths and YLLs, and the population of 0–4 year-olds had the highest rate of hospital discharges. Detailed estimates of hospital discharge, death and YLL rates based on high-quality, standardized data may be used to develop health policies, aid decision-making and plan prevention.
Multiscale Modelling and Characterization of Mechanical Properties in Heat-Resistant Alloys
Authors: Watanabe Ikumu , Ueshima Nobufumi , Ruzic Jovana , Cui Hongzhi
Published: January 2022

Various heat-resistant alloys have been used in industry; however, the bridge between the bulk mechanical properties and the underlying micro- and nanoscopic local properties remains an issue [...]
The Impact of Global Structural Information in Graph Neural Networks Applications
Authors: Buffelli Davide , Vandin Fabio
Published: January 2022

Graph Neural Networks (GNNs) rely on the graph structure to define an aggregation strategy where each node updates its representation by combining information from its neighbours. A known limitation of GNNs is that, as the number of layers increases, information gets smoothed and squashed and node embeddings become indistinguishable, negatively affecting performance. Therefore, practical GNN models employ few layers and only leverage the graph structure in terms of limited, small neighbourhoods around each node. Inevitably, practical GNNs do not capture information depending on the global structure of the graph. While there have been several works studying the limitations and expressivity of GNNs, the question of whether practical applications on graph structured data require global structural knowledge or not remains unanswered. In this work, we empirically address this question by giving access to global information to several GNN models, and observing the impact it has on downstream performance. Our results show that global information can in fact provide significant benefits for common graph-related tasks. We further identify a novel regularization strategy that leads to an average accuracy improvement of more than 5% on all considered tasks.
An Efficient Spark-Based Hybrid Frequent Itemset Mining Algorithm for Big Data
Authors: Al-Bana Mohamed Reda , Farhan Marwa Salah , Othman Nermin Abdelhakim
Published: January 2022

Frequent itemset mining (FIM) is a common approach for discovering hidden frequent patterns from transactional databases used in prediction, association rules, classification, etc. Apriori is an FIM elementary algorithm with iterative nature used to find the frequent itemsets. Apriori is used to scan the dataset multiple times to generate big frequent itemsets with different cardinalities. Apriori performance descends when data gets bigger due to the multiple dataset scan to extract the frequent itemsets. Eclat is a scalable version of the Apriori algorithm that utilizes a vertical layout. The vertical layout has many advantages; it helps to solve the problem of multiple datasets scanning and has information that helps to find each itemset support. In a vertical layout, itemset support can be achieved by intersecting transaction ids (tidset/tids) and pruning irrelevant itemsets. However, when tids become too big for memory, it affects algorithms efficiency. In this paper, we introduce SHFIM (spark-based hybrid frequent itemset mining), which is a three-phase algorithm that utilizes both horizontal and vertical layout diffset instead of tidset to keep track of the differences between transaction ids rather than the intersections. Moreover, some improvements are developed to decrease the number of candidate itemsets. SHFIM is implemented and tested over the Spark framework, which utilizes the RDD (resilient distributed datasets) concept and in-memory processing that tackles MapReduce framework problem. We compared the SHFIM performance with Spark-based Eclat and dEclat algorithms for the four benchmark datasets. Experimental results proved that SHFIM outperforms Eclat and dEclat Spark-based algorithms in both dense and sparse datasets in terms of execution time.
The Diagnostic Role of Uric Acid to Creatinine Ratio for the Identification of Patients with Adverse Pulmonary Embolism Outcomes
Authors: Bartziokas Konstantinos , Kyriakopoulos Christos , Potonos Dimitrios , Exarchos Konstantinos , Gogali Athena , Kostikas Konstantinos
Published: January 2022

Background: Uric acid (UA) is the final product of purine metabolism and a marker of oxidative stress that may be involved in the pathophysiology of cardiovascular and thromboembolic disease. The aim of the current study is to investigate the potential value of UA to creatinine ratio (UA/Cr) as a diagnostic tool for the outcome of patients admitted with acute pulmonary embolism (PE) and the correlations with other parameters. Methods: We evaluated 116 patients who were admitted for PE in a respiratory medicine department. PE was confirmed with computed tomography pulmonary angiography. Outcomes evaluated were hospitalization duration, mortality or thrombolysis and a composite endpoint (defined as mortality or thrombolysis). Patients were assessed for PE severity with the PE Severity Index (PESI) and the European Society of Cardiology (ESC) 2019 risk stratification. Results: The median (interquartile range) UA/Cr level was 7.59 (6.3–9.3). UA/Cr was significantly associated with PESI (p < 0.001), simplified PESI (p = 0.019), and ESC 2019 risk stratification (p < 0.001). The area under the curve (AUC) for prediction of 30-day mortality by UA/Cr was 0.793 (95% CI: 0.667–0.918). UA/Cr levels ≥7.64 showed 87% specificity and 94% negative predictive value for mortality. In multivariable analysis UA/Cr was an independent predictor of mortality (HR (95% CI): 1.620 (1.245–2.108), p < 0.001) and composite outcome (HR (95% CI): 1.521 (1.211–1.908), p < 0.001). Patients with elevated UA/Cr levels (≥7.64) had longer hospitalization (median (IQR) 7 (5–11) vs. 6 (5–8) days, p = 0.006)), higher mortality (27.3% vs. 3.2%, p = 0.001) and worse composite endpoint (32.7% vs. 3.4%, p < 0.001). Conclusion: Serum UA/Cr ratio levels at the time of PE diagnosis are associated with disease severity and risk stratification, and may be a useful biomarker for the identification of patients at risk of adverse outcomes.
Epigenome-Wide DNA Methylation Profiling in Colorectal Cancer and Normal Adjacent Colon Using Infinium Human Methylation 450K
Authors: Baharudin Rashidah , Ishak Muhiddin , Muhamad Yusof Azliana , Saidin Sazuita , Syafruddin Saiful Effendi , Wan Mohamad Nazarie Wan Fahmi , Lee Learn-Han , Ab Mutalib Nurul-Syakima
Published: January 2022

The aims were to profile the DNA methylation in colorectal cancer (CRC) and to explore cancer-specific methylation biomarkers. Fifty-four pairs of CRCs and the adjacent normal tissues were subjected to Infinium Human Methylation 450K assay and analysed using ChAMP R package. A total of 26,093 differentially methylated probes were identified, which represent 6156 genes; 650 probes were hypermethylated, and 25,443 were hypomethylated. Hypermethylated sites were common in CpG islands, while hypomethylated sites were in open sea. Most of the hypermethylated genes were associated with pathways in cancer, while the hypomethylated genes were involved in the PI3K-AKT signalling pathway. Among the identified differentially methylated probes, we found evidence of four potential probes in CRCs versus adjacent normal; HOXA2 cg06786372, OPLAH cg17301223, cg15638338, and TRIM31 cg02583465 that could serve as a new biomarker in CRC since these probes were aberrantly methylated in CRC as well as involved in the progression of CRC. Furthermore, we revealed the potential of promoter methylation ADHFE1 cg18065361 in differentiating the CRC from normal colonic tissue from the integrated analysis. In conclusion, aberrant DNA methylation is significantly involved in CRC pathogenesis and is associated with gene silencing. This study reports several potential important methylated genes in CRC and, therefore, merit further validation as novel candidate biomarker genes in CRC.
Gait Alterations in Adults after Ankle Fracture: A Systematic Review
Authors: Mirando Marta , Conti Corrado , Zeni Federica , Pedicini Fabio , Nardone Antonio , Pavese Chiara
Published: January 2022

(1) Background: Ankle fracture results in pain, swelling, stiffness and strength reduction, leading to an altered biomechanical behavior of the joint during the gait cycle. Nevertheless, a common pattern of kinematic alterations has still not been defined. To this end, we analyzed the literature on instrumental gait assessment after ankle fracture, and its correlation with evaluator-based and patient-reported outcome measures. (2) Methods: We conducted a systematic search, according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, of articles published from January 2000 to June 2021 in PubMed, Embase and PEDro on instrumental gait assessment after ankle fracture. (3) Results: Several changes in gait occur after ankle fracture, including a reduction in step length, swing time, single support time, stride length, cadence, speed and an earlier foot-off time in the affected side. Additionally, trunk movement symmetry (especially vertical) is significantly reduced after ankle fracture. The instrumental assessments correlate with different clinical outcome measures. (4) Conclusions: Instrumental gait assessment can provide an objective characterization of the gait alterations after ankle fracture. Such assessment is important not only in clinical practice to assess patients’ performance but also in clinical research as a reference point to evaluate existing or new rehabilitative interventions.
Influence of Framework Material and Posterior Implant Angulation in Full-Arch All-on-4 Implant-Supported Prosthesis Stress Concentration
Authors: Tribst João Paulo Mendes , Campanelli de Morais Dayana , Melo de Matos Jefferson David , Lopes Guilherme da Rocha Scalzer , Dal Piva Amanda Maria de Oliveira , Souto Borges Alexandre Luiz , Bottino Marco Antonio , Lanzotti Antonio , Martorelli Massimo , Ausiello Pietro
Published: January 2022

This study evaluated the influence of distal implants angulation and framework material in the stress concentration of an All-on-4 full-arch prosthesis. A full-arch implant-supported prosthesis 3D model was created with different distal implant angulations and cantilever arms (30° with 10-mm cantilever; 45° with 10-mm cantilever and 45° with 6-mm cantilever) and framework materials (Cobalt–chrome [CoCr alloy], Yttria-stabilized tetragonal zirconia polycrystal [Y-TZP] and polyetheretherketone [PEEK]). Each solid was imported to computer-aided engineering software, and tetrahedral elements formed the mesh. Material properties were assigned to each solid with isotropic and homogeneous behavior. The contacts were considered bonded. A vertical load of 200 N was applied in the distal region of the cantilever arm, and stress was evaluated in Von Misses (σVM) for prosthesis components and the Maximum (σMAX) and Minimum (σMIN) Principal Stresses for the bone. Distal implants angled in 45° with a 10-mm cantilever arm showed the highest stress concentration for all structures with higher stress magnitudes when the PEEK framework was considered. However, distal implants angled in 45° with a 6-mm cantilever arm showed promising mechanical responses with the lowest stress peaks. For the All-on-4 concept, a 45° distal implants angulation is only beneficial if it is possible to reduce the cantilever’s length; otherwise, the use of 30° should be considered. Comparing with PEEK, the YTZP and CoCr concentrated stress in the framework structure, reducing the stress in the prosthetic screw.
Demystifying the Differences between Structure-from-MotionSoftware Packages for Pre-Processing Drone Data
Authors: Pell Taleatha , Li Joan Y. Q. , Joyce Karen E.
Published: January 2022

With the increased availability of low-cost, off-the-shelf drone platforms, drone data become easy to capture and are now a key component of environmental assessments and monitoring. Once the data are collected, there are many structure-from-motion (SfM) photogrammetry software options available to pre-process the data into digital elevation models (DEMs) and orthomosaics for further environmental analysis. However, not all software packages are created equal, nor are their outputs. Here, we evaluated the workflows and output products of four desktop SfM packages (AgiSoft Metashape, Correlator3D, Pix4Dmapper, WebODM), across five input datasets representing various ecosystems. We considered the processing times, output file characteristics, colour representation of orthomosaics, geographic shift, visual artefacts, and digital surface model (DSM) elevation values. No single software package was determined the “winner” across all metrics, but we hope our results help others demystify the differences between the options, allowing users to make an informed decision about which software and parameters to select for their specific application. Our comparisons highlight some of the challenges that may arise when comparing datasets that have been processed using different parameters and different software packages, thus demonstrating a need to provide metadata associated with processing workflows.
Attitude to Distance Learning of Schoolchildren and Students: Subjective Assessments of Advantages and Disadvantages
Authors: Belousova Alla , Mochalova Yuliya , Tushnova Yulya
Published: January 2022

Currently, during the pandemic, the forced transition to distance learning carries a number of problems. These problems affect various aspects of education, including the study of students’ attitudes to distance learning. The purpose of this research is to study the features of the subjective attitude of schoolchildren and students to distance learning. This research involved 140 secondary school students (average age M = 10.7, SD = 7.2 (66.3% men)) and 30 university students (average age M = 22.5, SD = 2.4 (20% men)). The methods used were a questionnaire, Chi-square test and Criterion φ*. Fisher angular transformation. The study showed that schoolchildren do not intend to continue studying in the distance form if they choose, with a generally positive attitude towards distance learning. The self-assessment of motivation to study in a distance format has not changed, both among schoolchildren and students. Students are more likely to have a positive attitude to distance learning than schoolchildren. The variety of choices of advantages and disadvantages of distance learning is greater among students than among schoolchildren. The perspective of this study is thus to study the factors that determine the positive and negative attitudes to distance learning.
Exploring How Secondary STEM Teachers and Undergraduate Mentors Adapt Digital Technologies to Promote Culturally Relevant Education during COVID-19
Authors: Kier Meredith Weaver , Johnson Lindy L.
Published: January 2022

The COVID-19 global pandemic presented unprecedented challenges to K-16 educators, including the closing of educational agencies and the abrupt transition to online teaching and learning. Educators sought to adapt in-person learning activities to teach in remote and hybrid online settings. This study explores how a partnership between middle and high school teachers in an urban school district and undergraduate STEM mentors of color leveraged digital tools and collaborative pedagogies to teach science, technology, and engineering during a global pandemic. We used a qualitative multi-case study to describe three cases of teachers and undergraduate mentors. We then offer a cross-case analysis to interpret the diverse ways in which partners used technologies, pedagogy, and content to promote equitable outcomes for students, both in remote and hybrid settings. We found that the partnership and technologies led to rigorous and connected learning for students. Teachers and undergraduates carefully scaffolded technology use and content applications while providing ongoing opportunities for students to receive feedback and reflect on their learning. Findings provide implications for community partnerships and digital tools to promote collaborative and culturally relevant STEM learning opportunities in the post-pandemic era.
Prospective Primary Teachers’ Professional Noticing in Non-Formal Learning Environments: The Case of a Mathematics Fair
Authors: Xenofontos Constantinos , Hizli Alkan Sinem
Published: January 2022

Research around mathematics teachers’ professional noticing has been largely contextualised by the formal setting of the classroom. In addressing the lack of relevant studies in non-formal learning environments, this paper draws on student teachers’ observations within a Mathematics Fair, which was part of a mathematics methods module of a primary education undergraduate programme. Working in pairs, 64 student teachers designed interactive mathematical games which upper primary school pupils had the opportunity to play in an event having taken place at our university. In this study, we analyse student teachers’ individual reflective essays written after the Fair, where they discussed important, in their view, incidents and observations. Employing a thematic analysis approach, we identified four themes discussed by students: the task; learning; teaching; non-formal environment. We conclude with the implications for teacher education and suggestions for future research.
A Study to Evaluate Students’ Performance, Engagement, and Progression in Higher Education Based on Feedforward Teaching Approach
Authors: Saeed Nagham , Mohamedali Fehmida
Published: January 2022

Learners who enter higher education (HE) at the foundational level are susceptible to many challenges that impact their performance, engagement, and progression. Not all students who enter HE at the foundational level will progress and attain their course qualifications. In addition, many university lecturers struggle to give effective support to their students. This study focuses on feedforward teaching approaches that define ways to enhance learning by using advanced organisational strategies to offer relevant supporting concepts and meaningful verbal material. To date, there are insufficient literature reviews on feedforward approaches to facilitate students’ subsequent learning. Providing better academic support for students and a strong foundation for independent learning is the focus of this paper. Therefore, the main contributions of this paper are identifying the key feedforward features and suggesting effective feedforward approaches. This study was undertaken to rigorously implement feedforward approaches that would support groups of students in modules at the foundational entry-level. At the end of module delivery, different students’ data sets were analysed related to the progression rates, standard deviation, and mean. In addition, the student satisfaction questionnaire (module evaluation survey) and feedback survey were also considered for engagement and retention purposes. The outcomes from this exercise suggest that feedforward approaches allow students to increase their overall effort when attempting summative assessments and, thus, improve their performance, engagement, and retention.
Outage Constrained Design in NOMA-Based D2D Offloading Systems
Authors: Chen Yun , Zhang Guoping , Xu Hongbo , Ren Yinshuan , Chen Xue , Li Ruijie
Published: January 2022

Non-orthogonal multiple access (NOMA) is a new multiple access method that has been considered in 5G cellular communications in recent years, and can provide better throughput than traditional orthogonal multiple access (OMA) to save communication bandwidth. Device-to-device (D2D) communication, as a key technology of 5G, can reuse network resources to improve the spectrum utilization of the entire communication network. Combining NOMA technology with D2D is an effective solution to improve mobile edge computing (MEC) communication throughput and user access density. Considering the estimation error of channel, we investigate the power of the transmit nodes optimization problem of NOMA-based D2D networks under the rates outage probability (OP) constraints of all single users. Specifically, under the channel statistical error model, the total system transmit power is minimized with the rate OP constraint of a single device. Unfortunately, the problem presented is thorny and non-convex. After equivalent transformation of the rate OP constraints by the Bernstein inequality, an algorithm based on semi-definite relaxation (SDR) can efficiently solve this challenging non-convex problem. Numerical results show that the channel estimation error increases the power consumption of the system. We also compare NOMA with the OMA mode, and the numerical results show that the D2D offloading systems based on NOMA are superior to OMA.
An Adaptive Modeling Framework for Bearing Failure Prediction
Authors: Zhao Yuntian , Toothman Maxwell , Moyne James , Barton Kira
Published: January 2022

Rolling element bearings are a common component in rotating equipment, a class of machines that is essential in a wide range of industries. Detecting and predicting bearing failures is then vital for reducing maintenance and production costs due to unplanned downtime. In previous literature, significant efforts have been devoted to building data-driven health models from historical bearing data. However, a common limitation is that these methods are typically tailored to specific failure instances and have limited ability to model bearing failures between repairs in the same system. In this paper, we propose a multi-state health model to predict bearing failures before they occur. The model employs a regression-based method to detect health state transition points and applies an exponential random coefficient model with a Bayesian updating process to estimate time-to-failure distributions. A model training framework is also introduced to make our proposed model applicable to more bearing instances in the same system setting. The proposed method has been tested on a publicly available bearing prognostics dataset. Case study results show that the proposed method provides accurate failure predictions across several system failures, and that the training approach can significantly reduce the time necessary to generate an effective, generalized model.
Efficient Iterative Regularization Method for Total Variation-Based Image Restoration
Authors: Ma Ge , Yan Ziwei , Li Zhifu , Zhao Zhijia
Published: January 2022

Total variation (TV) regularization has received much attention in image restoration applications because of its advantages in denoising and preserving details. A common approach to address TV-based image restoration is to design a specific algorithm for solving typical cost function, which consists of conventional ℓ2 fidelity term and TV regularization. In this work, a novel objective function and an efficient algorithm are proposed. Firstly, a pseudoinverse transform-based fidelity term is imposed on TV regularization, and a closely-related optimization problem is established. Then, the split Bregman framework is used to decouple the complex inverse problem into subproblems to reduce computational complexity. Finally, numerical experiments show that the proposed method can obtain satisfactory restoration results with fewer iterations. Combined with the restoration effect and efficiency, this method is superior to the competitive algorithm. Significantly, the proposed method has the advantage of a simple solving structure, which can be easily extended to other image processing applications.
High-Performance InGaAs HEMTs on Si Substrates for RF Applications
Authors: Wang Bo , Wang Yanfu , Feng Ruize , Wei Haomiao , Cao Shurui , Liu Tong , Liu Xiaoyu , Li Haiou , Ding Peng , Jin Zhi
Published: January 2022

In this paper, we have fabricated InGaAs high-electron-mobility transistors (HEMTs) on Si substrates. The InAlAs/InGaAs heterostructures were initially grown on InP substrates by molecular beam epitaxy (MBE), and the adhesive wafer bonding technique was employed to bond the InP substrates to Si substrates, thereby forming high-quality InGaAs channel on Si. The 120 nm gate length device shows a maximum drain current (ID,max) of 569 mA/mm, and the maximum extrinsic transconductance (gm,max) of 1112 mS/mm. The current gain cutoff frequency (fT) is as high as 273 GHz and the maximum oscillation frequency (fMAX) reaches 290 GHz. To the best of our knowledge, the gm,max and the fT of our device are the highest ever reported in InGaAs channel HEMTs on Si substrates at given gate length above 100 nm.
A Lightweight Learning Method for Stochastic Configuration Networks Using Non-Inverse Solution
Authors: Nan Jing , Jian Zhonghua , Ning Chuanfeng , Dai Wei
Published: January 2022

Stochastic configuration networks (SCNs) face time-consuming issues when dealing with complex modeling tasks that usually require a mass of hidden nodes to build an enormous network. An important reason behind this issue is that SCNs always employ the Moore–Penrose generalized inverse method with high complexity to update the output weights in each increment. To tackle this problem, this paper proposes a lightweight SCNs, called L-SCNs. First, to avoid using the Moore–Penrose generalized inverse method, a positive definite equation is proposed to replace the over-determined equation, and the consistency of their solution is proved. Then, to reduce the complexity of calculating the output weight, a low complexity method based on Cholesky decomposition is proposed. The experimental results based on both the benchmark function approximation and real-world problems including regression and classification applications show that L-SCNs are sufficiently lightweight.
A Coarse-to-Fine Registration Approach for Point Cloud Data with Bipartite Graph Structure
Authors: Yuan Munan , Li Xiru , Cheng Longle , Li Xiaofeng , Tan Haibo
Published: January 2022

Alignment is a critical aspect of point cloud data (PCD) processing, and we propose a coarse-to-fine registration method based on bipartite graph matching in this paper. After data pre-processing, the registration progress can be detailed as follows: Firstly, a top-tail (TT) strategy is designed to normalize and estimate the scale factor of two given PCD sets, which can combine with the coarse alignment process flexibly. Secondly, we utilize the 3D scale-invariant feature transform (3D SIFT) method to extract point features and adopt fast point feature histograms (FPFH) to describe corresponding feature points simultaneously. Thirdly, we construct a similarity weight matrix of the source and target point data sets with bipartite graph structure. Moreover, the similarity weight threshold is used to reject some bipartite graph matching error-point pairs, which determines the dependencies of two data sets and completes the coarse alignment process. Finally, we introduce the trimmed iterative closest point (TrICP) algorithm to perform fine registration. A series of extensive experiments have been conducted to validate that, compared with other algorithms based on ICP and several representative coarse-to-fine alignment methods, the registration accuracy and efficiency of our method are more stable and robust in various scenes and are especially more applicable with scale factors.
On the Performance of Energy Criterion Method in Wi-Fi Transient Signal Detection
Authors: Mohamed Ismail , Dalveren Yaser , Catak Ferhat Ozgur , Kara Ali
Published: January 2022

In the development of radiofrequency fingerprinting (RFF), one of the major challenges is to extract subtle and robust features from transmitted signals of wireless devices to be used in accurate identification of possible threats to the wireless network. To overcome this challenge, the use of the transient region of the transmitted signals could be one of the best options. For an efficient transient-based RFF, it is also necessary to accurately and precisely estimate the transient region of the signal. Here, the most important difficulty can be attributed to the detection of the transient starting point. Thus, several methods have been developed to detect transient start in the literature. Among them, the energy criterion method based on the instantaneous amplitude characteristics (EC-a) was shown to be superior in a recent study. The study reported the performance of the EC-a method for a set of Wi-Fi signals captured from a particular Wi-Fi device brand. However, since the transient pattern varies according to the type of wireless device, the device diversity needs to be increased to achieve more reliable results. Therefore, this study is aimed at assessing the efficiency of the EC-a method across a large set of Wi-Fi signals captured from various Wi-Fi devices for the first time. To this end, Wi-Fi signals are first captured from smartphones of five brands, for a wide range of signal-to-noise ratio (SNR) values defined as low (−3 to 5 dB), medium (5 to 15 dB), and high (15 to 30 dB). Then, the performance of the EC-a method and well-known methods was comparatively assessed, and the efficiency of the EC-a method was verified in terms of detection accuracy.
Easy Fabrication of Performant SWCNT-Si Photodetector
Authors: Capista Daniele , Passacantando Maurizio , Lozzi Luca , Faella Enver , Giubileo Filippo , Di Bartolomeo Antonio
Published: January 2022

We propose a simple method to fabricate a photodetector based on the carbon nanotube/silicon nitride/silicon (CNT/Si3N4/Si) heterojunction. The device is obtained by depositing a freestanding single-wall carbon nanotube (SWCNT) film on a silicon substrate using a dry transfer technique. The SWCNT/Si3N4/Si heterojunction is formed without the thermal stress of chemical vapor deposition used for the growth of CNTs in other approaches. The CNT film works as a transparent charge collecting electrode and guarantees a uniform photocurrent across the sensitive area of the device. The obtained photodetector shows a great photocurrent that increases linearly with the incident light intensity and grows with the increasing wavelength in the visible range. The external quantum efficiency is independent of the light intensity and increases with the wavelength, reaching 65% at 640 nm.