bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fe3O4/TiO2/Graphene Hybrid Nanocomposite to Improve the Lifespan of Distribution Transformers
Authors: Saravanakumar K , Samson Issac J. , Dhanaselvam J. , Rajesh R. , Singh Ajith.B. , Geetha K. 
Published: September 2022

Abstract
The actual lifetime of a transformer is between 30-50 years, while a foundation can be in service for 100 years. The aim of this research is to get the exact remaining lifetime of the transformers and to suggest a method to improve it. Hybrid nanoparticles are used to improve the thermal properties and dielectric strength of transformer oil. Titanium oxide (TiO2), Iron oxide (Fe3O4), and Graphene is used in specific concentration to prepare the hybrid nanoparticles. Energy Dispersive X-Ray Analysis (EDX), X-Ray Diffraction Analysis (XRD), Fourier Transform Infrared Spectroscopy (FTIR) are carried out to know whether the nanoparticles are properly synthesized. Initially Infrared thermography analysis using Fluke TiX-580 is being carried out to measure the surface temperature of the transformers and transformers under analysis are grouped. Nanofluid Transformer oil is prepared and Break Down Voltage (BDV) Test is taken to analyse the strength. Transformers are filled with nanofluid transformer oil and Infrared Thermography analysis is performed again to analyse the surface temperature. It is showing that lifetime of transformers is increased from 6 to 8% after using nanofluid transformer oil.
Non-Invasive Glucose Monitoring Using NIR Spectroscopy
Authors: Reddy Pulagam Sai Kumar , Mahesh Darapu , Uday Teja C , Janaki Muthuluri , Mannem Kiran 
Published: September 2022

Abstract
Diabetes Mellitus (DM), a metabolic condition, can lead to major health problems if it is not adequately treated. Traditional blood glucose monitors are intrusive and give people pain and irritation. As a result, the study’s goal was to find a non-invasive way to measure blood glucose. To determine blood glucose parameters, this system uses an NIR Spectroscopy-based system with a light source of wavelength 950nm. The light source illuminates the skin of the wrist, and a photodiode receiver captures the reflected beam. An Arduino UNO microcontroller receives the conditioned signal and digitalizes it. The spectrum is calculated by the Arduino board based on the subject’s blood glucose levels. Pre-processing and segmenting the raw waveforms are required to obtain the peaks of the NIR spectrum and to compute the regression model.
Soft Computing Techniques for Driver Alertness
Authors: Reddy Penuballi Phani Srikar , Khadyoth Gunturu Sasi Pavan , Raman Vennalakanti Sri Ganesh , Reddy Gadikota Sai Dheeraj , Valiveti Hima Bindu 
Published: September 2022

Abstract
There has been an alarming increase in the number of accidents that occur due to drowsiness while driving. In order to reduce roadside accidents, the detection of driver fatigue or drowsiness is crucial. Detecting fatigue during driving is crucial for reducing accidents, as well as improving the safety of both the driver and the passengers. Various methods can be used to detect drowsiness among drivers, but fuzzy logic-based detection stands out for its ability to avoid false alarms. As part of the proposed system, we are using eye-tracking in combination with methods such as Haar cascade to identify the level of drowsiness of the driver. This system has been tested in real-time.
Machine Learning approach for Software Effort Estimation using Combination of Principal Component Regression and Neural Network
Authors: Priya Varshini A G , Anitha Kumari K , Bhalavaishnavi V S , Kalpana Devi C , Pranesh S 
Published: September 2022

Abstract
For software projects that deploy vital tasks, it is difficult to estimate the effort of a project. In order to anticipate a few hours of labour effort (either time or personal) to deploy or maintain the software programme, software measurement points must be used. It is difficult to predict the behavior of an application that is engaged in software development during the initial phases of the effort. The hybrid model technique is used in this paper. It is necessary to apply Supervised Learning techniques in the Machine Learning algorithm. It is further subdivided into different types, such as linear regression, logistic regression, SVM (Support Vector Machine) algorithm, Naive Bayes algorithm, PCR(Principal Component Regression) algorithm, (Neural Network)NNET algorithm, KNN (K-Nearest Neighbour) algorithm, K-means, Random Forest algorithm, Dimensionality reduction algorithms, Gradient boosting algorithm, and Ada Boosting algorithm, to name a few examples. PCR algorithm and the nnet algorithm have been utilised for hybrid method, as shown above. Predictions from JM1/Software have been used to create this data collection. With 10886 unique instances and 18 unique traits, this is a very large amount. Metrics for evaluating this system include Mean Absolute Error (MAE), Mean Relative Error (MRE), Mean Magnitude of Relative Error (MMRE), Percentage of Predictive Accuracy (PRED), and R-squared. Compared to single model approaches based on machine learning algorithms techniques, the proposed hybrid using principal component regression and neural networks produced the best results, as demonstrated by the results.
Observation of well-defined Kohn-anomaly in high-quality graphene devices at room temperature
Authors: Gadelha Andreij C , Nadas Rafael , Barbosa Tiago C , Watanabe Kenji , Taniguchi Takashi , Campos Leonardo C , Raschke Markus B , Jorio Ado 
Published: September 2022

Abstract
Due to its ultra-thin nature, the study of graphene quantum optoelectronics, like gate-dependent graphene Raman properties, is obscured by interactions with substrates and surroundings. For instance, the use of doped silicon with a capping thermal oxide layer limited the observation to low temperatures of a well-defined Kohn-anomaly behavior, related to the breakdown of the adiabatic Born–Oppenheimer approximation. Here, we design an optoelectronic device consisting of single-layer graphene electrically contacted with thin graphite leads, seated on an atomically flat hexagonal boron nitride substrate and gated with an ultra-thin gold layer. We show that this device is optically transparent, has no background optical peaks and photoluminescence from the device components, and no generation of laser-induced electrostatic doping (photodoping). This allows for room-temperature gate-dependent Raman spectroscopy effects that have only been observed at cryogenic temperatures so far, above all the Kohn-anomaly phonon energy normalization. The new device architecture, by decoupling graphene optoelectronic properties from the substrate effects, allows for observing quantum phenomena at room temperature.
On constant-time quantum annealing and guaranteed approximations for graph optimization problems
Authors: Braida Arthur , Martiel Simon , Todinca Ioan 
Published: September 2022

Abstract
Quantum annealing (QA) is a computational framework where a quantum system’s continuous evolution is used to find the global minimum of an objective function over an unstructured search space. It can be seen as a general metaheuristic for optimization problems, including NP-hard ones if we allow an exponentially large running time. While QA is widely studied from a heuristic point of view, little is known about theoretical guarantees on the quality of the solutions obtained in polynomial time. In this paper, we use a technique borrowed from theoretical physics, the Lieb–Robinson (LR) bound, and develop new tools proving that short, constant-time QA guarantees constant factor approximations ratios for some optimization problems when restricted to bounded degree graphs. Informally, on bounded degree graphs the LR bound allows us to retrieve a (relaxed) locality argument, through which the approximation ratio can be deduced by studying subgraphs of bounded radius. We illustrate our tools on problems MaxCut and maximum independent set for cubic graphs, providing explicit approximation ratios and the runtimes needed to obtain them. Our results are of similar flavor to the well-known ones obtained in the different but related QAOA (quantum optimization algorithms) framework.
SPARSEMODr: Rapidly simulate spatially explicit and stochastic models of COVID-19 and other infectious diseases
Authors: Mihaljevic Joseph R , Borkovec Seth , Ratnavale Saikanth , Hocking Toby D , Banister Kelsey E , Eppinger Joseph E , Hepp Crystal , Doerry Eck 
Published: September 2022

Abstract
Building realistically complex models of infectious disease transmission that are relevant for informing public health is conceptually challenging and requires knowledge of coding architecture that can implement key modeling conventions. For example, many of the models built to understand COVID-19 dynamics have included stochasticity, transmission dynamics that change throughout the epidemic due to changes in host behavior or public health interventions, and spatial structures that account for important spatio-temporal heterogeneities. Here we introduce an R package, SPARSEMODr, that allows users to simulate disease models that are stochastic and spatially explicit, including a model for COVID-19 that was useful in the early phases of the epidemic. SPARSEMOD stands for SPAtial Resolution-SEnsitive Models of Outbreak Dynamics, and our goal is to demonstrate particular conventions for rapidly simulating the dynamics of more complex, spatial models of infectious disease. In this report, we outline the features and workflows of our software package that allow for user-customized simulations. We believe the example models provided in our package will be useful in educational settings, as the coding conventions are adaptable, and will help new modelers to better understand important assumptions that were built into sophisticated COVID-19 models.
The neural correlates of domain-general visual ability
Authors: McGugin Rankin W , Sunday Mackenzie A , Gauthier Isabel 
Published: September 2022

Abstract
People vary in their general ability to compare, identify, and remember objects. Research using latent variable modeling identifies a domain-general visual recognition ability (called o) that reflects correlations among different visual tasks and categories. We measure associations between a psychometrically-sensitive measure of o and a neurometrically-sensitive measure of visual sensitivity to shape. We report evidence for distributed neural correlates of o using functional and anatomical regions-of-interest (ROIs) as well as whole brain analyses. Neural selectivity to shape is associated with o in several regions of the ventral pathway, as well as additional foci in parietal and premotor cortex. Multivariate analyses suggest the distributed effects in ventral cortex reflect a common mechanism. The network of brain areas where neural selectivity predicts o is similar to that evoked by the most informative features for object recognition in prior work, showing convergence of 2 different approaches on identifying areas that support the best object recognition performance. Because o predicts performance across many visual tasks for both novel and familiar objects, we propose that o could predict the magnitude of neural changes in task-relevant areas following experience with specific task and object category.
Diffused calcification in a patient with long-term warfarin therapy: a case report
Authors: Sasmita Bryan Richard , Luo Suxin , Huang Bi 
Published: September 2022

Abstract

Background
Lifelong warfarin is mandatory in patients with mechanic valvular replacement. The main adverse effect of warfarin is haemorrhage; however, there are several rare adverse events associated with long-term warfarin treatment, such as calcification, cholesterol microembolization, and nephropathy. Here we report a case of chronic warfarin use that gradually manifested with diffused calcification.

Case summary
A 78-year-old woman received a prosthetic mechanical mitral valve replacement when she was 46 years old due to rheumatic mitral stenosis. She has been taking warfarin ever since. Ten years prior to admission, the chest radiography revealed a mild diffused calcification tracheobronchial and subsequent chest imaging indicated a progressive calcification of the tracheobronchial tree. In addition, a series of echocardiography examinations indicated progressive calcific aortic stenosis and diffused calcification in abdominal aorta. Furthermore, the patient gradually presented with advanced heart failure. Finally, she received transcatheter aortic valve replacement and the symptoms of the heart failure significantly improved.

Discussion
Currently, patients with valvular atrial fibrillation or mechanical valve replacement have no other choice for anticoagulation medication except warfarin. However, long-term use of warfarin was associated with some rare complications such as diffused calcification. Therefore, close monitoring of such side effects in patients with long-term use of warfarin is warranted.
Effect of calcium fluoride nanoparticles in prevention of demineralization during orthodontic fixed appliance treatment: a randomized clinical trial
Authors: Al Tuma Rawof R , Yassir Yassir A 
Published: September 2022

SummaryBackgroundWhite spot lesions (WSLs) are the most common complications of fixed appliance orthodontic treatment.ObjectivesTo evaluate the effectiveness of calcium fluoride nanoparticles-containing orthodontic primer (nCaF2-primer) in preventing the incidence of WSLs during orthodontic treatment.Trial designSingle-centre, double-blinded, split-mouth, randomized clinical trial.MethodsThe sample involved 31 orthodontic patients (≥12 years). Participants were recruited using a simple nonstratified randomization. Data collection, measurements, and analysis were performed blindly. Outcome measures included comparing the effect of nCaF2-primer with control primer (Transbond) regarding the degree of demineralization (DIAGNOdent pen), Streptococcus mutans (S. mutans) bacterial counting [real-time polymerase chain reaction device (PCR)], and WSLs incidence (pre- and post-operative photographs). The measurements were performed before bonding, 1, 3, and 6 months after bonding and after appliance removal. A two-way repeated measure analysis of variance test (for DIAGNOdent pen scores), and Wilcoxon signed-rank test (for the difference between bacterial counting and WSLs incidence) were used (P &lt; 0.05).ResultsThirty-one patients were recruited and randomized (mean age 17.9 ± 2.45 years). For the primary outcome (DIAGNOdent pen scores) and secondary outcome of S. mutans counting: 31 patients (310 teeth for each group) were included in scoring at T1 and T3, and 30 patients (300 teeth) were included at T6. While for the photographic scores, 26 patients were included after bracket bonding. The demineralization scores showed significant differences at all-time intervals within the 6 months after bracket bonding which was more noticeable after the first month. There was a significant difference in bacterial count between the two primer groups at the T1 only. Regarding photographic scores, there were no significant differences in the WSLs incidence between the two primers groups after brackets removal. No harm was detected during treatment, except the usual pain/gingival irritation.ConclusionsnCaF2-primer effectively decreased demineralization scores within the 6 months after bracket bonding. Moreover, it significantly reduced S. mutans colonization after the first month. However, the tested primer did not have an extra advantage in preventing WSLs development at the clinical level after appliance removal.Trial registrationThe trial was registered with ClinicalTrials.gov on 8 May 2021 (registration number: NCT04994314).
Reduction in blood pressure for elevated blood pressure/stage 1 hypertension according to the American College of Cardiology/American Heart Association guideline and cardiovascular outcomes
Authors: Kaneko Hidehiro , Yano Yuichiro , Suzuki Yuta , Okada Akira , Itoh Hidetaka , Matsuoka Satoshi , Fujiu Katsuhito , Michihata Nobuaki , Jo Taisuke , Takeda Norifumi , Morita Hiroyuki , Node Koichi , Viera Anthony J , Lima Joao A C , Oparil Suzanne , Lam Carolyn S P , Carey Robert M , Yasunaga Hideo , Komuro Issei 
Published: September 2022

Abstract

Aims
Few studies have examined the relationship of blood pressure (BP) change in adults with elevated BP or stage 1 hypertension according to the American College of Cardiology (ACC)/American Heart Association (AHA) guideline with cardiovascular outcomes. We sought to identify the effect of BP change among individuals with elevated BP or stage 1 hypertension on incident heart failure (HF) and other cardiovascular diseases (CVDs).

Methods and results
We conducted a retrospective cohort study including 616 483 individuals (median age 46 years, 73.7% men) with elevated BP or stage 1 hypertension based on the ACC/AHA BP guideline. Participants were categorized using BP classification at one-year as normal BP (n = 173 558), elevated BP/stage 1 hypertension (n = 367 454), or stage 2 hypertension (n = 75 471). The primary outcome was HF, and the secondary outcomes included (separately) myocardial infarction (MI), angina pectoris (AP), and stroke. Over a mean follow-up of 1097 ± 908 days, 10 544 HFs, 1317 MIs, 11 070 APs, and 5198 strokes were recorded. Compared with elevated BP/stage 1 hypertension at one-year, normal BP at one-year was associated with a lower risk of developing HF [hazard ratio (HR): 0.89, 95% CI:0.85–0.94], whereas stage 2 hypertension at one-year was associated with an elevated risk of developing HF (HR:1.43, 95% CI:1.36–1.51). This association was also present in other cardiovascular outcomes including MI, AP, and stroke. The relationship was consistent in all subgroups stratified by age, sex, baseline BP category, and overweight/obesity.

Conclusion
A one-year decline in BP was associated with the lower risk of HF, MI, AP, and stroke, suggesting the importance of lowering BP in individuals with elevated BP or stage 1 hypertension according to the ACC/AHA guideline to prevent the risk of developing CVD.
Tooth Loss, Periodontal Disease, and Mild Cognitive Impairment Among Hispanic/Latino Immigrants: The Moderating Effects of Age at Immigration
Authors: Luo Huabin , Wu Bei , González Hector M , Stickel Ariana , Kaste Linda M , Tarraf Wassim , Daviglus Martha L , Sanders Anne E , Cai Jianwen 
Published: September 2022

Abstract

Background
The objectives were to assess (a) the association between poor oral health and mild cognitive impairment (MCI) in Hispanic/Latino immigrants and (b) potential modification effects on this association by age at immigration.

Methods
Data were from the Hispanic Community Health Study/Study of Latinos and its ancillary study—the Study of Latinos–Investigation of Neurocognitive Aging. MCI, a binary outcome variable, defined by the National Institute on Aging-Alzheimer’s Association criteria. The main exposure was significant tooth loss (STL), defined as a loss of 8 or more teeth, and periodontitis, classified using the Centers for Disease Control and Prevention and American Academy of Periodontology case classification. Multiple logistic regression was used to assess the association between STL/periodontitis and MCI and test moderation effects of age at immigration. The analytical sample comprised 5 709 Hispanic/Latino adult immigrants.

Results
Hispanic/Latino immigrants with STL (adjusted odds ratio [AOR] = 1.36, 95% confidence interval [CI]: 1.01–1.85) were more likely to have MCI than those with greater tooth retention. Overall, migration to the United States after age 18 was associated with greater odds of MCI than migration at a younger age. A significant interaction effect between STL and age at immigration revealed that the effect of STL on MCI is even higher in those who immigrated to the United States at ages 35–49 years.

Conclusions
STL is a significant risk factor for MCI and age at immigration had a modification effect on the association between STL and MCI. Better access to dental care, health education on risk factors of MCI, and promotion of good oral health may mitigate the burden of cognitive impairment in Hispanics/Latinos.
A high-resolution microseismic source location method based on contrast source algorithm
Authors: Wei Shuying , Chen Xiaohong , Li Jingye , Ma Jitao , Huang Guangtan 
Published: September 2022

SUMMARY
Passive source location estimation technology plays an extremely important role in microseismic monitoring. However, the energy of microseismic signals is generally weak and prone to be interrupted as noise, which will affect the detection and location accuracy of microseismic events. Besides, the existing wave-equation-based source location estimation methods are not suitable for strongly heterogeneous strata, such as faults, salt bodies, fractures filled with proppant and other fluids, etc. These complex geological structures often trigger scattered waves. Thus, based on scattering theory, a high-resolution microseismic source location estimation method with a new grouping imaging condition is proposed by implementing a contrast source numerical simulation method in the process of wavefield backpropagation. First, the contrast source algorithm is used to perform wavefield extrapolation by solving the Helmholtz equation in the frequency domain, which can provide more comprehensive, effective information to get high-precision locations. Moreover, an optimized grouping imaging condition is proposed, which can improve the imaging resolution and computational efficiency. The effectiveness of the method we propose is illustrated using numerical examples. Compared with traditional source location estimation methods, including with low signal-to-noise ratio or multisource location estimation, this method results in strong energy focusing achieved in an effecient manner.