bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Deep Learning Approach For Dental Implant Planning On Cone-Beam Computed Tomography Images
Authors: Bayrakdar Sevda Kurt , Orhan Kaan , Bayrakdar Ibrahim Sevki , Bilgir Elif , Ezhov Matvey , Gusarev Maxim , Shumilov Eugene 
Published: March 2021

Abstract
Background: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images.Methods: Seventy-five CBCT images were included in this study. In these images, bone height and thickness in 508 regions where implants were required were measured by a human observer with manual segmentation method using InvivoDental 6.0 (Anatomage Inc. San Jose, CA, USA). Also, canals/sinuses/fossae associated with alveolar bones and missing tooth regions were detected. After all of this evaluations were repeated using the deep convolutional neural network (Diagnocat, Inc.) The jaws were separated as mandible/maxilla and each jaw was grouped as anterior/premolar/molar teeth region. The data obtained from manual segmentation and AI methods were compared using Bland-Altman analysis and Wilcoxon signed rank test.Results: In the bone height measurements, there were no statistically significant differences between AI and manual measurements in the premolar region of mandible and the premolar and molar regions of the maxilla (p>0.05). In the bone thickness measurements, there were statistically significant differences between AI and manual measurements in all regions of maxilla and mandible (p<0.001). Also, the percentage of right detection was 72.2% for canals, 66.4% for sinuses/fossae and 95.3% for missing tooth regions.Conclusions: Development of AI systems and their using in future for implant planning will both facilitate the work of physicians and will be a support mechanism in implantology practice to physicians.
Effect of Atomic Layer Deposited HfO2 thin Film Interfacial Layer on the Electrical Properties of Au/Ti/n-GaAs Schottky Diode
Authors: YILDIZ Dilber Esra , Karabulut A. , Orak I. , Türüt A. 
Published: March 2021

Abstract
The electrical properties of Au/Ti/HfO2/n-GaAs metal/insulating layer/semiconductor (MIS) contact structures were analyzed in detail by the help of capacitance-voltage (C-V) and conductance-voltage (G-V) measurements in the temperature range of 60–320 K. The HfO2 thin film layer was obtained by atomic layer deposition technique (ALD). The main electrical parameters such as ideality factor (n) and barrier height (ΦB0) were determined for Au/Ti/n-GaAs and Au/Ti/HfO2/n-GaAs diodes using current-voltage (I-V) measurement at 300 K. The values of these parameters are 1.07 and 0.77 eV for the reference (Au/Ti/n-GaAs) diode, and 1.30 and 0.94 eV for the Au/Ti/HfO2/n-GaAs MIS diode, respectively. An interfacial charge density value of Qss= 4.14x1012 Ccm− 2 for the MIS diode was calculated from the barrier height difference of ΔΦ=0.94-0.77=0.17 V. Depending on these results, the temperature dependent C-V and G-V plots of the device were also investigated. The series resistance (Rs), phase angle, the interface state density (Dit), the real impedance (Z') and imaginary impedance (Z'') were evaluated using admittance measurements. The C and G values increased, whereas (Z'') and Z decreased with increasing voltage at each temperature. An intersection point being independent of temperature in the G–V curves appeared at forward bias side (≈1.4 V), after this intersection point of the G–V plot, the G values decreased with increasing temperature at a given voltage. The intersection points in total (Z) versus V curves appeared at forward bias side (≈1.7 V). The Nyquist spectra was recorded for the MIS structure showing single semicircular arcs with different diameters depending on temperature.
The prevalence, clinical relevance and origin of autoantibodies in patients with Common variable immunodeficiency on regular immunoglobulin replacement therapy – the results from a prospective observational study
Authors: Milota Tomas , Karel Kotaska , Petr Lastuvka , Jitka Smetanova , Marketa Bloomfield , Radana Zachova , Iveta Klojdova , Rudolf Horvath , Anna Sediva 
Published: March 2021

Abstract
Background: Common variable immunodeficiency (CVID) is an inborn error of immunity characterized by disturbed immunoglobulin production. Despite of the terrain with severe antibody deficiency, autoantibody-mediated autoimmune phenomena belong to the most frequent autoimmune manifestation. However, many unresolved issues such as prevalence, clinical relevance and origin of autoantibodies detected in CVID patients receiving immunoglobulin replacement therapy (IRT) make the diagnostics of autoimmune complications difficult.Methods: A prospective observational study evaluating the spectrum of 23 different autoantibodies in 38 CVID patients receiving IRT, and in the immunoglobulin solutions used for IRT. Results: The study reveals a high prevalence of anti-GAD (55.3%) and anti-TPO (68.4%) autoantibodes in the cohort of 38 CVID patients on regular IRT. However, the titers of anti-GAD (3.22 vs. 22 kU/L, p≤0.0001) and anti-TPO (109.7 vs. 713 kU/L, p≤0.0001) were significantly lower compared to the newly diagnosed T1D and AIT patients. Moreover, none of the CVID patients with detectable antibodies manifested with T1D and only three patients became suspected of having AIT. A high quantity of anti-GAD (3.24-24.48 kU/L) and anti-TPO (123.6-156.55 kU/L) autoantibodies was found in immunoglobulin solutions for IRT. Conclusions: The study finds a very high prevalence of anti-GAD and anti-TPO autoantibodies in CVID patients receiving regular IRT. Nevertheless, the presence of anti-GAD and anti-TPO is not associated with the manifestation of the respective autoimmune disease. As the high titers of both anti-GAD and anti-TPO were also found in the therapeutics used for IRT, we suggest that the therapeutic immunoglobulins are the source of this false positivity.
Electro-physical properties of jute fabrics in a condition of high humidity - Effect of fabric chemical composition and coating with Cu-based nanoparticles
Authors: Ivanovska Aleksandra Mirce , Maletić Slavica , Djokić Veljko , Tadić Nenad , Kostić Mirjana 
Published: March 2021

Abstract
The electro-physical properties of raw and chemically modified jute fabrics were studied as complex phenomena of the interaction between the fabrics’ chemical composition, crystallinity, moisture sorption, COOH group content, structural characteristics, and frequency of the electric field. At 80% relative air humidity, all chemically modified jute fabrics have 38–179% and 1.7–5.4 times higher dielectric loss tangent and effective relative dielectric permeability compared to unmodified, respectively. To further improve these properties, fabrics were treated with CuSO4 and Cu-based nanoparticles were in situ synthesized on their surface by reduction. A few single Cu-based nanoparticles were observed across the alkali modified fabric’s surface, while single and agglomerated nanoparticles were distributed over the oxidatively modified fabric’s surface. No matter whether metallic Cu or copper oxide (Cu2O or CuO) nanostructures (or their mixtures) are synthesized (proven by XRD), excellent fabrics’ effective relative dielectric permeability is guaranteed. In other words, during the exploitation in specific conditions contributing to copper reduction, the jute fabrics will be able to store 21–163 times more energy from an external electric field than before the exploitation, which further extended their lifetime. On the other hand, with increasing the total content of Cu after the reduction and formation of single and agglomerated Cu-based nanoparticles, the movement of jute structural components’ molecules becomes difficult resulting in lower energy dissipation within the chemically modified than within unmodified fabric. Applied chemical modification and coating with Cu-based nanoparticles enables designing fabrics with predictable electro-physical properties, which is very important from the application point of view.
Chlamy-EnPhosSite: A deep learning-based approach for Chlamydomonas reinhardtii-specific phosphorylation site prediction
Authors: Thapa Niraj , Chaudhari Meenal , Iannetta Anthony A. , White Clarence , Roy Kaushik , Newman Robert , Hicks Leslie M. , KC Dukka 
Published: March 2021

Abstract
Protein phosphorylation is one of the most important post-translational modifications (PTMs) and involved in myriad cellular processes. Although many non-organism-specific computational phosphorylation site prediction tools and a few tools for organism-specific phosphorylation site prediction exist, none are currently available for Chlamydomonas reinhardtii. Herein, we present a novel deep learning (DL) based approach for organism-specific protein phosphorylation site prediction in Chlamydomonas reinhardtii, a model algal phototroph. Our novel approach called Chlamy-EnPhosSite (based on ensemble approach combining convolutional neural networks (CNN) and long short-term memory LSTM) produces AUC and MCC of 0.90 and 0.64 respectively for a combined dataset of serine (S) and threonine (T) in independent testing. When applied to the entire C. reinhardtii proteome (totaling 1,809,304 S and T sites), Chlamy-EnPhosSite yielded 499,411 phosphorylated sites with a cut-off value of 0.5 and 237,949 phosphorylated sites with a cut-off value of 0.7. These predictions were compared to an experimental dataset of phosphosites identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a blinded study and approximately 90% of 2,663 C. reinhardtii S and T phosphorylation sites were successfully predicted by Chlamy-EnPhosSite at a probability cut-off of 0.5 and 77% of sites were successfully identified at a more stringent 0.7 cut-off. Interestingly, Chlamy-EnPhosSite also successfully predicted experimentally confirmed phosphorylation sites in a protein sequence (e.g., RPS6 S245) which did not appear in the training dataset, highlighting prediction accuracy and the power of leveraging predictions to identify biologically relevant PTM sites. These results demonstrate that our method represents a robust and complementary technique for high-throughput phosphorylation site prediction in C. reinhardtii. It has potential to serve as a useful tool to the community. Chlamy-EnPhosSite will contribute to the understanding of how protein phosphorylation influences various biological processes in this important model microalga.
Simulation Study and Comparative Evaluation of Viral Contiguous Sequence Identification Tools
Authors: Glickman Cody , Hendrix Jo , Strong Michael 
Published: March 2021

Abstract
Background:Viruses, including bacteriophage, are important components of environmental and human associated microbial communities. Viruses can act as extracellular reservoirs of bacterial genes, can mediate microbiome dynamics, and can influence the virulence of clinical pathogens. It is essential, therefore, to have robust sequence analysis methods in place to detect and annotate viral elements within microbial communities. Various targeted metagenomic analysis techniques detect viral sequences, but these methods often exclude large and genome integrated viruses. In this study, we evaluate and compare the ability of nine state-of-the-art bioinformatic tools, including Vibrant, VirSorter, VirSorter2, VirFinder, DeepVirFinder, MetaPhinder, JGI Earth Virome Pipeline, Kraken 2, and VirBrant, to identify viral contiguous sequences (contigs) across simulated metagenomes with different read distributions, taxonomic compositions, and complexities.Results:Of the tools tested in this study, VirSorter achieved the best F1 score while Vibrant had the highest average F1 score at predicting integrated prophages. Though less balanced in its precision and recall, Kraken2 had the highest average precision by a substantial margin. We introduced the machine learning tool, VirBrant, which demonstrated an improvement in average F1 score over tools such as MetaPhinder. The tool utilizes machine learning with both protein compositional and nucleotide features. The addition of nucleotide features improves the precision and recall compared to the protein compositional features alone. Viral identification by all tools was not impacted by underlying read distribution but did improve with contig length. Tool performance was inversely related to taxonomic complexity and varied by the phage host. Rhizobium and Enterococcus phage were identified consistently by the tools; whereas, Neisseria phage were commonly missed in this study.Conclusion:This study benchmarked the performance of nine state-of-the-art bioinformatic tools to identify viral contigs across different simulation conditions. This study explored the ability of the tools to identify integrated prophage elements traditionally excluded from targeted sequencing approaches. Our comprehensive analysis of viral identification tools to assess their performance in a variety of situations provides valuable insights to viral researchers looking to mine viral elements from publicly available metagenomic data.
SARS-CoV-2 And Other Human Coronavirus Show Genome Patterns Previously Associated to Reduced Viral Recognition and Altered Immune Response
Authors: Franzo Giovanni 
Published: March 2021

Abstract
A new pandemic caused by the betacoronavirus SARS-CoV-2 originated in China in late 2019. Although often asymptomatic, a relevant percentage of affected people can develop severe pneumonia. Initial evidence suggests that dysregulation of the immune response could contribute to the pathogenesis, as previously demonstrated for SARS-CoV. The presence of genome composition features involved in delaying viral recognition is herein investigated for human coronaviruses (HCoVs), with a special emphasis on SARS-CoV-2. A broad collection of HCoVs polyprotein, envelope, matrix, nucleocapsid and spike coding sequences was downloaded and several statistics representative of genome composition and codon bias were investigated. A model able to evaluate and test the presence of a significant under- or over-representation of dinucleotide pairs while accounting for the underlying codon bias and protein sequence was also implemented. The study revealed the significant under-representation of CpG dinucleotide pair in all HcoV, but especially in SARS-CoV and even more in SARS-CoV-2. The presence of forces acting to minimize CpG content was confirmed by relative synonymous codon usage pattern. Codons containing the CpG pair were severely under-represented, primarily in the polyprotein and spike coding sequences of SARS-CoV-2. Additionally, a significant under-representation of the TpA pair was observed in the N and S region of SARS-CoV and SARS-CoV-2. Increasing experimental evidence has proven that CpG and TpA are targeted by innate antiviral host defences, contributing both to RNA degradation and RIG-1 mediated interferon production. The low content of these dinucleotides could contribute to a delayed interferon production, dysregulated immune response, higher viral replication and poor outcome. Significantly, the RIG-1 signalling pathway was proven to be defective in elderlies, suggesting a likely interaction between limited viral recognition and lower responsiveness in interferon production that could justify the higher disease severity and mortality in older patients.
Design of CPW-fed Star-Shaped Monopole Antenna for UWB Applications using Transmission Line Model
Authors: MAITY BUDHADEB , NAYAK SISIR KUMAR 
Published: March 2021

Abstract
This article presents a structure of coplanar waveguide (CPW)-fed star-shaped monopole antenna (SSMA) with a pair of quarter-circular-slit (QCS) and partly-hexagonal-ring-slit (PHRS) defected ground structure. By inserting a pair of QCS and PHRS on the rectangular ground plane, an excellent impedance bandwidth is achieved i.e., 139 % (from 2.2--12.21 GHz). The dimension of the SSMA is about 0.286λ l ×0.216λ l mm 2 , where λ l is the wavelength in free space at the lowest operating frequency i.e, 2.2 GHz. The transmission line model (TLM) of the SSMA is presented and it shows the antenna behavior based on the effect of each element. It is observed that the characteristics of the TLM model are close to the simulation result using the CST simulator. From the results, it is observed that the proposed ultra-wideband (UWB) antenna close to omnidirectional radiation patterns and suitable for UWB Applications.
Compliance-Based Estimation of Seismic Collapse Risk of an Existing Reinforced Concrete Frame Building
Authors: Tsiavos Anastasios , Amrein Pascal , Bender Nathan , Stojadinovic Bozidar 
Published: March 2021

Abstract
The seismic evaluation of existing structures is based on the determination of the damage likely to occur during the lifetime of these structures due to earthquake ground motion excitation. However, there is not a consensus about the acceptable level of seismic damage, the expected lifetime of these structures, and the seismic hazard level(s) to evaluate the structures at. This paper presents a methodology for the parametric determination of the seismic collapse risk of an existing Reinforced Concrete (RC) frame building based on its seismic code compliance, quantified by a dimensionless metric. This metric, defined as compliance factor, compares the seismic capacity of an existing structure with the seismic demand for a new structure at a predetermined hazard level. The inelastic seismic behavior of four models of the RC frame building of varying compliance was analytically investigated in this study to demonstrate the implementation of the novel methodology. The four models of the RC building were chosen to represent existing RC frame structures, designed and constructed before the introduction of the modern seismic code provisions. These four building models were excited by a group of earthquake ground motion excitations using Incremental Dynamic Analysis (IDA). The collapse probability of the four models of the RC building representing varying values of seismic code compliance was determined for two different locations corresponding to regions of moderate and high seismic hazard, thus laying the basis for the compliance-based estimation of the seismic collapse risk of existing structures.
Performance Evaluation, Comparison and Identification of Efficient Hypercube Interconnection Networks
Authors: K Karthik , Jena Sudarson , T Venu Gopal 
Published: March 2021

Abstract
A Multiprocessor is a system with at least two processing units sharing access to memory. The principle goal of utilizing a multiprocessor is to process the undertakings all the while and support the system’s performance. An Interconnection Network interfaces the various handling units and enormously impacts the exhibition of the whole framework. Interconnection Networks, also known as Multi-stage Interconnection Networks, are node-to-node links in which each node may be a single processor or a group of processors. These links transfer information from one processor to the next or from the processor to the memory, allowing the task to be isolated and measured equally. Hypercube systems are a kind of system geography used to interconnect various processors with memory modules and precisely course the information. Hypercube systems comprise of 2n nodes. Any Hypercube can be thought of as a graph with nodes and edges, where a node represents a processing unit and an edge represents a connection between the processors to transmit. Degree, Speed, Node coverage, Connectivity, Diameter, Reliability, Packet loss, Network cost, and so on are some of the different system scales that can be used to measure the performance of Interconnection Networks. A portion of the variations of Hypercube Interconnection Networks include Hypercube Network, Folded Hypercube Network, Multiple Reduced Hypercube Network, Multiply Twisted Cube, Recursive Circulant, Exchanged Crossed Cube Network, Half Hypercube Network, and so forth. This work assesses the performing capability of different variations of Hypercube Interconnection Networks. A group of properties is recognized and a weight metric is structured utilizing the distinguished properties to assess the performance exhibition. Utilizing this weight metric, the performance of considered variations of Hypercube Interconnection Networks is evaluated and summed up to recognize the effective variant. A compact survey of a portion of the variations of Hypercube systems, geographies, execution measurements, and assessment of the presentation are examined in this paper. Degree and Diameter are considered to ascertain the Network cost. On the off chance that Network Cost is considered as the measurement to assess the exhibition, Multiple Reduced Hypercube stands ideal with its lower cost. Notwithstanding it, on the off chance that we think about some other properties/ scales/metrics to assess the performance, any variant other than MRH may show considerably more ideal execution. The considered properties probably won't be ideally adequate to assess the effective performance of Hypercube variations in all respects. On the off chance that a sensibly decent number of properties are utilized to assess the presentation, a proficient variation of Hypercube Interconnection Network can be distinguished for a wide scope of uses. This is the inspiration to do this research work.
Combination of Topical Use of a Thrombin-based Hemostatic Matrix and Tranexamic Acid Does Not Have a Synergic Effect on Reducing Postoperative Blood Loss in Minimally Invasive Total Knee Arthroplasty. A Prospective Randomized Controlled Study
Authors: Yen Shih-Hsiang , Lin Po-Chun , Wang Jun-Wen 
Published: March 2021

Abstract
BackgroundThere is limited information regarding the blood-conservation effect of combined topical tranexamic acid (TXA) and thrombin-based hemostatic matrix (TBHM) in total knee arthroplasty (TKA). This study is to evaluate whether there is synergic effect of combined use of TXA and TBHM to reduce blood loss during TKA.Material and MethodsSixty-nine patients (69 knees) who underwent primary TKA were randomly assigned into a TXA group (n = 34), who received intra-articular administration of 3g of TXA in 60mL saline, and a TXA + TBHM group (n = 35), who received intra-articular TBHM and TXA (3g) in 60mL saline after TKA. The primary outcomes were total blood loss (TBL) and postoperative hemoglobin (Hb) level. Secondary outcomes included the transfusion rate and the incidence of venous thromboembolism (VTE).ResultsThe mean TBL in the TXA + TBHM group was 678 ± 203mL , which was similar to that in the TXA only group at 733 ± 217mL (p= 0.276). There were no differences in the postoperative Hb level between the two groups. The transfusion rate was similar in the TXA + TBHM group and the TXA only group (2.9% versus 0%, p= 0.242). No patients in either group developed VTE within 3 months.ConclusionsOur prospective randomized controlled study did not show a synergic blood-conservation effect of combined use of topical TBHM and TXA in patients undergoing TKA. Further investigation with a larger sample size may be required.Trial registration: ClinicalTrials.gov, NCT03328832. Registered Oct 30 2017, http://clinicaltrials.gov/ct/show/NCT03328832?order=1