Miracle-dz/UniFAR-FTUs huggingface dataset:
CEOR_A_289459 175..190

1Department of Orthopedic Surgery, University of Minnesota, Minneapolis, MN, USA; 2Mayo Clinic, Rochester, MN, USA; 3Temple University, Philadelphia, PA, USA; 4Costello Medical Consulting Ltd, Cambridge, UK; 5Zimmer Biomet, Warsaw, IN, USA Purpose: Anterior vertebral body tethering (VBT) is a non-fusion, minimally invasive, growth-modulating procedure with some early positive clinical outcomes reported in pediatric patients with idiopathic scoliosis (IS). VBT offers potential health-related quality of life (HRQoL) benefits over spinal fusion in allowing patients to retain a greater range of motion after surgery. We conducted an early cost-utility analysis (CUA) to compare VBT with fusion as a first-choice surgical treatment for skeletally immature patients (age >10 years) with moderate to severe IS, who have failed nonoperative management, from a US integrated healthcare delivery system perspective. Patients and Methods: The CUA uses a Markov state transition model, capturing a 15year period following index surgery. Transition probabilities, including revision risk and subsequent fusion, were based on published surgical outcomes and an ongoing VBT observational study (NCT02897453). Patients were assigned utilities derived from published patient-reported outcomes (PROs; SRS-22r mapped to EQ-5D) following fusion and the above VBT study. Index and revision procedure costs were included. Probabilistic (PSA) and deterministic sensitivity analyses (DSA) were performed. Results: VBT was associated with higher costs but also higher quality-adjusted life years (QALYs) than fusion (incremental costs: $45,546; QALYs gained: 0.54). The subsequent incremental cost-effectiveness ratio for VBT vs fusion was $84,391/QALY gained. Mean PSA results were similar to the base case, indicating that results were generally robust to uncertainty. The DSA indicated that results were most sensitive to variations in utility values. Conclusion: This is the first CUA comparing VBT with fusion in pediatric patients with IS and suggests that VBT may be a cost-effective alternative to fusion in the US, given recommended willingness-to-pay thresholds ($100,000–$150,000). The results rely on HRQoL benefits for VBT compared with fusion. For improved model accuracy, further analyses with longer-term PROs for VBT, and comparative effectiveness studies, would be needed.
Graded-Mesh Difference Schemes

This paper is concerned with the numerical approximation by compact finitedifference schemes of differential operators of the form Leu = eu(m) + ^Jv=0 avv^ without turning points. The stability of L£ combined with various auxiliary conditions is discussed, and a representation result for solutions of problems involving it is proven. This representation decomposes the solution into a smooth outer component plus a decaying exponential layer term along the lines of the Method of Multiple Scales. The stability of compact difference analogues of L€ is studied, and a stability result is proven which generalizes earlier work. This result encompasses, for example, discretizations of second-order problems that fail to possess a maximum principle. It allows for standard polynomial-based differences in outer regions (away from boundary layers) with uniform meshes, even though such schemes admit oscillatory solutions. A family of finite-difference schemes based on an exponentially graded mesh and local polynomial basis functions is discussed. These schemes can be constructed to have arbitrarily high uniform order of convergence. To achieve a scheme of order 0(hK), roughly K times as many points are distributed inside the layer as outside. The high order is achieved by using extra local evaluations of the coefficient functions and source term of the problem. A rigorous discretization error analysis of these schemes, using the established stability and representation results, is given. Numerical results exhibiting the performance of these schemes are presented and generalizations of the results in the paper are discussed.
Music Information Retrieval and Classification using Deep Learning

------------------------------------------------------------------------***------------------------------------------------------------------------- Abstract - Music classification is one of the fundamental problems in music information retrieval (MIR). This paper describes the work of building a music genre classifier using deep learning methods. We review several different types of music representation techniques to represent music data in the form that most closely mimics a human auditory system’s response to a particular music excerpt; this helps the classifier produce results closely related to how a human brain would classify a music excerpt. Upon extracting and representing the music data in the best possible way in this setting, we then use the extracted information to train and test several different types of deep learning models and compare them on the counts of accuracy in classifying a music excerpt into one of the several different listed genres.
TSDolly: A program generator for TypeScript

TypeScript is an increasingly popular open-source language that builds on JavaScript by adding optional static type definitions. Its ecosystem has many tools that require confidence in their correctness when manipulating TypeScript programs. Tool developers commonly use tests for increasing confidence in a tool’s implementation correctness. To test tool implementations, tool developers can manually write TypeScript programs to be used as test inputs, but they can miss problematic programs as there are many language features to consider. In addition, a range of those tools have properties that apply specifically to programs that compile successfully and satisfy complex constraints. We therefore present a program generation technique that allows generating successfully compiling TypeScript programs, that optionally also satisfy tool-specific constraints not captured by syntactic constraints alone. We evaluated our technique by generating programs in the context of five automated TypeScript refactoring implementation, and by running tests with the generated programs as inputs. The majority (97.45%) of the generated programs compiled without errors, and all of the generated programs could be refactored, meaning that they can indeed satisfy tool-specific constraints to be used as test inputs. We tested the refactorings using the generated programs as test inputs and we found and reported a bug in a TypeScript refactoring, where the refactoring introduced a compilation error to programs that previously had no errors.
Development of Jaundice Detection Approaches in Neonates

Jaundice is one of the most common diseases that have a significant impact in the first few days of newborn life. Detection and regular monitoring of bilirubin, which is responsible for Jaundice, is an essential phase during the hyperbilirubinemia. In the literature, various clinical assessment methods of Jaundice are available. It motivates us to present a review of these clinical assessment methods in practice, along with their advantages and limitations. In this paper, we have discussed three widely used methods, such as visual assessment, total serum bilirubin and transcutaneous bilirubinometer. From the comparative analysis of these methods, it is concluded that the visual assessment is very subjective in nature, whereas, the total serum bilirubin method is still a gold standard method. The detailed analysis of the methods depicts that the correlation between this two total serum bilirubin and transcutaneous Journal of University of Shanghai for Science and Technology ISSN: 1007-6735 Volume 22, Issue 12, December 2020 Page-911 bilirubinometer has enormous potential for improvement resulting in the enhancement in precision and accuracy of bilirubin measurement.
Making blends of agarwood waste with empty palm bunches or rubber wood sawdust for pelletized biofuels

This study created biomasspellet fuel with reduced ash content from agarwood waste mixed with empty palm bunches (ACW+EPB) , and from agarwood waste with rubber wood sawdust (ACW+RWS), utilizing the low ash value of the agarwood waste. The tested blends had a 1:1 ratio of agarwood waste and empty palm bunches, and a 1:3 ratio of agarwood waste and rubber wood sawdust. Comparisons were also conducted relative to Korean ( Grade 4) ( 2014) and ENplus B ( 2014) commercial pellet standards. Before pressure molding, the mixture components were dried and ground in a pelletizing device with a motor power of 7.5 kW (380 V, 50 Hz) , yielding 100 to 150 kg/ h without added adhesive. The test results showed that ACW ash content decreased in the RWS hybrid, yet increased in the EPB mixture. The attributes of ash content, moisture content, and heating value of ACW+RWS satisfied ENplus B (2014) and Korean (Grade 4) (2014) standards at 1.70%, 4.50%, and 4,536 kcal/kg. The ACW+EPB also satisfied the Korean (Grade 4) standard at 4.20% , 6.50% , and 4,220 kcal/kg. Thus, the biomass pellets from the mixture of agarwood waste and rubber wood sawdust and that of agarwood waste and empty palm bunches were of suitable quality for commercial purposes.
ExDocS: Evidence based Explainable Document Search

We present an explainable document search system (ExDocS), based on a re-ranking approach, that uses textual and visual explanations to explain document rankings to non-expert users. ExDocS attempts to answer questions such as “Why is documentXrankedatYforagivenquery? ”,“Howdowecomparemultipledocumentstounderstandtheirrelativerankings? ”. Thecontributionofthisworkisonre-rankingmethodsbasedonvariousinterpretablefacetsofevidencesuchasterm statistics,contextualwords,andcitation-basedpopularity.Contributionfromtheuserinterfaceperspectiveconsistsofprovidingintuitiveaccessibleexplanationssuchas:“documentXisatrankYbecauseofmatchesfoundlikeZ”alongwith visualelementsdesignedtocomparetheevidenceandtherebyexplaintherankings.Thequalityofourre-rankingapproachisevaluatedonbenchmarkdatasetsinanad-hocretrievalsetting.Duetotheabsenceofgroundtruthofexplanations,we evaluatetheaspectsofinterpretabilityandcompletenessofexplanationsinauserstudy.ExDocSiscomparedwitharecentbaseline-explainablesearchsystem(EXS),thatusesapopularposthocexplanationmethodcalledLIME.Inlinewiththe “nofreelunch”theorem,wefindstatisticallysignificantresultsshowingthatExDocSprovidesanexplanationforrankingsthatareunderstandableandcompletebuttheexplanationcomesatthecostofadropinrankingquality.
Water masses distribution offshore the Sabrina Coast (East Antarctica)

Abstract. Current glacier melt rates in West Antarctica substantially exceed those around the East Antarctic margin. The exception is Wilkes Land where, e.g., Totten Glacier, underwent significant retreat between 2000 and 2012, underlining its sensitivity to climate change. This process is strongly influenced by ocean dynamics, which in turn changes in accordance with the evolution of the ice caps. Here, we present oceanographic data (temperature, salinity, density, dissolved oxygen) collected for the first time offshore the Sabrina Coast (East Antarctica), from the continental shelf break to ca 3000 m depth during austral summer 2017. The main water masses are identified by analysing thermohaline properties: the Antarctic Surface Water with θ > −1. 5 °C and S < 34.2 (σθ < 27.55 kg m−3), the Winter Water with −1.92 < θ < −1.75 °C and 34.0 < S < 34.5 (27.55 < σθ < 27.7 kg m−3), the modified Circumpolar Deep Water with θ > 0 °C and S > 34.5 (σθ > 27.7 kg m−3), and Antarctic Bottom Water with −0.50 < θ < 0 °C and 34.63 < S < 34.67 (27.83 < σθ < 27.85). The latter in this region is a mixture of dense waters originating from the Ross Sea and Adélie Land continental shelves, and is affected by the mixing process they undergo as they move westward along the Antarctic margin and interact with the locally formed dense waters, and with the warmer and saltier Circumpolar Deep Water. The spatial distribution of water masses offshore the Sabrina Coast also appears to be strongly linked with the complex morpho-bathymetry of the slope and rise area, supporting the hypothesis that downslope processes contribute to shaping the architecture of the distal portion of the continental margin.
Quantifing Model Uncertainity to Improve Stream Flow Prediction for Geba Cathment, Upper Tekeze Sub basin, Ethiopia

This study was conducted to predict stream flow at the outlet of the gauged Geba watershed and analyze the associated uncertainty that can affects its accurate prediction. Semi distributed HBV light model was a0pplied to estimate stream flow of the Geba catchment and associated uncertainty through Monte Carlo Simulation procedure. The calibration and validation of the model was found satisfactory as performance rating criteria value of coefficient of correlation (R) and Nash-Sutcliffe simulation efficiency (ENS) is found to be 0.74 and 0.72 for calibration and 0.73 and 0.70 for validation ,respectively. In the same order from the model uncertainties analysis the percentage of the simulated data within the uncertainty bound is only 35% for calibration and 29% for validation, which shows that there is uncertainty in the process. Then using Monte Carlo Simulation procedure in HBV light model parameter uncertainty was tested and found with ENS value of 0.76 for calibration and 0.79 for validation. And this shows that the overall associated uncertainty come from either from conceptual or inputuncertainity or combination of them but not from parameter identification.Even though the predicted amount of flow of 955.33MCM is almost equivalent to the latest study, the uncertainty might come due to either neglected abstractions or poor quality of input data. Therefore, this simulated amount should not be used for any water resource development works unless the correction of these cause of uncertainties are reduced as uncertainty in estimation of simulated flow will lead to wrong water resource management decision.
Boron and Phosphorus Removal from Si-Cu Alloy Using CaO-SiO2-Na2O-Al2O3 Slag

A combination of solvent refining and slag treatment was employed to investigate the possibility of removing boron and phosphorus from crude silicon to acceptable levels for solar applications. Metallurgical grade silicon (MG-Si) was alloyed with pure copper and the alloy was subjected to refining by liquid CaO-SiO2-Na2O-Al2O3 slags at 1773K (1500°C). The distribution of B and P between the slags and the alloy was measured under a range of slag compositions, varying in CaO:SiO2 and SiO2:Al2O3 ratios and the amount of Na2O. The results showed that both basicity and oxygen potential have a strong influence on the distribution of B and P. With silica affecting both parameters in these slags, a critical could be identified that yields the highest impurity pick–up. The addition of Na2O to the slag was found to increase the distributions of boron and phosphorus into the slag. A thermodynamic evaluation of the system showed that alloying copper with MG-Si leads to substantial increase of boron distribution coefficient. The highest boron and phosphorus distributions were 47 and 1.1, respectively. Using these optimum slags to
Neural End-to-end Coreference Resolution for German in Different Domains

We apply neural coreference resolution to German, surpassing the previous state-of-the-art performance by a wide margin of 10– 30 points F1 across three established datasets for German. This is achieved by a neural end-to-end approach, training contextual word-embeddings jointly with mention and entity similarity scores. We explore the impact of various parameters such as language models, pre-training and computational limits with respect to German data. In an effort to support datasets representing the domains of both news and literature, we make use of two distinct model architectures: a mention linking-based and an incremental entity-based approach that should scale to very long documents such as literary works. Our code and ready-to-use models are publicly available.
COVI SCAN (Face mask detection and social distancing violation detection)

— COVID-19 pandemic is a great humanitarian challenge faced by the world today. The pandemic has spread widely causing the world to halt and the number of cases continues to rise. Governments all round the world are working to slow down if not completely stop the spread of this pandemic. Many protocols have been implemented, crucial ones are face masks and social distancing. Since social distancing and wearing a mask are the only monitored ways to avoid the infection till vaccinations become accessible to all. Real times mask detection and social distance violation using computer vision and deep learning techniques. For face mask detection we collected a dataset consisting of with-mask and without-mask labels.
Indexed Dataset from YouTube for a Content-Based Video Search Engine

: Numerous researches on content-based video indexing and retrieval besides video search engines are tied to a large-scaled video dataset. Unfortunately, reduction in open-sourced datasets resulted in complications for novel approaches exploration. Although, video datasets that index video files located on public video streaming services have other purposes, such as annotation, learning, classification, and other computer vision areas, with little interest in indexing public video links for purpose of searching and retrieval. This paper introduces a novel large-scaled dataset based on YouTube video links to evaluate the proposed content-based video search engine, gathered 1088 videos, that represent more than 65 hours of video, 11,000 video shots, and 66,000 unmarked and marked keyframes, 80 different object names used for marking. Moreover, a state-of-the-art features vector, and combinational-based matching, beneficial to the accuracy, speed, and precision
Object-based Scene Recognition Algorithm using Mask R-CNN

In this paper, an object-based scene recognition algorithm was proposed by applying the mask region-based convolutional neural network (Mask R-CNN) framework, and the accuracy of the proposed algorithm was analyzed. The proposed algorithm is designed based on a deep learning model consisting of a convolutional neural network (CNN), region proposal network (RPN), and region of interest (RoI) align, and detects objects scattered in the surrounding environment. The average object-based scene recognition accuracy was measured to be about 95% and 93% in 1 st and 2 nd experiments, respectively
Insilico Drug Designing and Pharmacokinetics Studies on the Gene, Macc1 (Metastasis Associated Gene in Colon Cancer 1), Responsible for Colon Cancer

Globally more than 1 million people get colorectal cancer every year resulting in about 715,000 deaths as of 2010 up from 490,000 in 1990. As of 2012, it is the second most common cause of cancer in women (9.2% of diagnoses) and the third most common in men (10%). In this research, we focused on the potential mutated gene, MACC1 Metastasis-Associated Gene in Colon Cancer 1. We examined the potential mutated sites which are responsible for colon cancer. We modeled the 3D structure of both the normal and the mutated protein and validated it. The potential existing drug and the anti-oxidant agent were combined using advanced cheminformatics protocols. The designed drug was validated using pharmacokinteics techniques (ADME and Toxicity). Finally the designed drug and the control drug were docked using automated drug docking server. Based on the drug binding scores, we deduced that the designed drug has good binding affinities with the target modeled protein. Hence, we finally conclude that the regions of MACC1 act as therapeutic agent for Colon cancer.
Drivers and consequences of partial migration in an alpine bird species

Abstract Partial migration, where a portion of the population migrates between winter and summer (breeding) areas and the rest remain year‐round resident, is a common phenomenon across several taxonomic groups. Several hypotheses have been put forward to explain why some individuals migrate while others stay resident, as well as the fitness consequences of the different strategies. Yet, the drivers and consequences of the decision to migrate or not are poorly understood. We used data from radio‐tagged female (n = 73) willow ptarmigan Lagopus lagopus in an alpine study area in Central Norway to test if (i) the decision to migrate was dependent on individual state variables (age and body weight), (ii) individuals repeated migratory decisions between seasons, and (iii) the choice of migratory strategy was related to reproductive success. Partially supporting our prediction that migratory strategy depends on individual state, we found that juvenile birds with small body sizes were more likely to migrate, whereas large juveniles remained resident. For adult females, we found no relationship between the decision to migrate or stay resident and body weight. We found evidence for high individual repeatability of migratory decision between seasons. Migratory strategy did not explain variation in clutch size or nest fate among individuals, suggesting no direct influence of the chosen strategy on reproductive success. Our results indicate that partial migration in willow ptarmigan is related to juvenile body weight, and that migratory behavior becomes a part of the individual life history as a fixed strategy. Nesting success was not affected by migratory strategy in our study population, but future studies should assess other traits to further test potential fitness consequences.
Improvement of Technology of Passenger Intermodal Transportation with Involvement of Railway Transport in the Conditions of Tourism Development

Dep. «Operational Work Management», Ukrainian State University of Railway Transport, Feuerbach Sq. 7, Kharkiv, Ukraine, 61050, tel. +38 (057) 730 10 89, e-mail uermp@ukr.net, ORCID 0000-0003-1082-599X Dep. «Operational Work Management», Ukrainian State University of Railway Transport, Feuerbach Sq. 7, Kharkiv, Ukraine, 61050, tel. +38 (099) 420 45 28, e-mail vicmmx@gmail.com, ORCID 0000-0001-8963-6467 Dep. «Operational Work Management», Ukrainian State University of Railway Transport, Feuerbach Sq. 7, Kharkiv, Ukraine, 61050, tel. +38 (057) 730 10 88, e-mail l.o. parkhomenko@kart.edu. ua, ORCID 0000-0003-1647-7746 Dep. «Cargo and Commercial Work Management», Ukrainian State University of Railway Transport, Feuerbach Sq. 7, Kharkiv, Ukraine, 61050, tel. +38 (057) 730 10 88, e-mail prokopovartem1301@gmail.com, ORCID 0000-0001-7324-4047
Study of electric power system oscillation damping

Operation of an electric power system through a transmission network that has limited capacity can cause system instability when the system is disturbance. This study aims to investigate the influence of dynamic loads on the electric power system oscillation damping. The interaction between the electric power system and dynamic load after and before interference is simulated through Simulink Matlab. Dynamic load models are developed from the Hill model based on load power responses due to voltage changes. While the electric power system model is based on a model developed by Demello, which is a Single Machine Infinite Bus System. Based on the two models, an overall block diagram is made that illustrates the interaction between dynamic loads and the electric power system. The results showed that there was an increase in the stability of the electric power system with dynamic load feedback and a decrease in the rotor angle and increase in voltage. So that it can be concluded that changes in dynamic load parameters affect the stability of the electric power system. This study can be used as a basis for studying the behavior of electrical power systems that experience greater disturbance with load feedback.