Miracle-dz/UniFAR-FTUs huggingface dataset:
The structure of a turbulent boundary layer studied by numerical simulation

Time-dependent visualisations of large-scale direct and large-eddy simulations (DNS and LES) of a turbulent boundary layer reaching up to $Re_\theta=4300$ are presented. The focus of the present fluid dynamics video is on analysing the coherent vortical structures in the boundary layer: It is clearly shown that hairpin vortices are indeed present in the simulation data, however they are characteristic remainders of the laminar-turbulent transition at lower Reynolds numbers. At higher $Re$ (say $Re_\theta>2000$), these structures are no longer seen as being dominant; the coherence is clearly lost, both in the near-wall region as well as in the outer layer of the boundary layer. Note, however, that large-scale streaks in the streamwise velocity, which have their peak energy at about half the boundary-layer thickness, are unambiguously observed.
Analysis and Classification of Schizophrenia Using Event Related Potential Signals

— Schizophrenia (SZ) is a neuropsychiatric disease that affects many people around the world and causes death if not diagnosed and treated early. One of the commonly used methods for early diagnosis is electroencephalography (EEG). The application of signal processing and machine learning methods to EEG signals can support experts and researchers who want to determine SZ disease. In this study, event-related potential (ERP) signals were obtained from the recorded EEG signals as a result of sending auditory stimuli to the SZ patient and healthy control (HC) group. P300 amplitude-latency, hjorth parameters and entropy values were calculated as features from these signals. The features obtained were evaluated with Support Vector Machines (SVM), K-Nearest Neighbor (KNN) and Artificial Neural Networks (ANN) classifiers to distinguish SZ patients from the HC group. In this study, the most successful result was obtained in the ANN classifier with an accuracy rate of 93.9%.
Genetic Diversity of the Spotted Seal (Phoca largha) in Liaodong Gulf Following Long Term Conservation Activities

The spotted seal ( Phcoa largha ) is the only pinniped species reproducing in the wild in China. Wild populations of this species have declined sharply in China due to anthropogenic impacts. Forty-six individuals died accidentally in Liaodong Gulf between 2018 to 2020 and were collected. The genetic diversity and population structure of this population were investigated using mitochondrial ND4L and D-loop sequences, and the results were compared with the same population in 2005. The haplotype diversity of Liaodong Gulf spotted seals was low compared to other spotted seal populations in other habitats. Fortunately, the genetic diversity of the current Liaodong Gulf spotted seal population was higher than 15 years ago, and the population expanded between 2005 and 2020. Our findings indicated that conservation activities for Liaodong Gulf spotted seals in recent decades have been valuable, and should persist in the future.
Linear density response function in the projector augmented wave method: Applications to solids, surfaces, and interfaces

Center for Atomic-scale Materials Design, Department of PhysicsTechnical University of Denmark, DK - 2800 Kgs. Lyngby, Denmark(Dated: April 8, 2011)We present an implementation of the linear density response function within the projector-augmented wave (PAW) method with applications to the linear optical and dielectric propertiesof both solids, surfaces, and interfaces. The response function is represented in plane waves whilethe single-particle eigenstates can be expanded on a real space grid or in atomic orbital basis forincreased eﬃciency. The exchange-correlation kernel is treated at the level of the adiabatic localdensity approximation (ALDA) and crystal local ﬁeld eﬀects are included. The calculated staticand dynamical dielectric functions of Si, C, SiC, AlP and GaAs compare well with previous cal-culations. While optical properties of semiconductors, in particular excitonic eﬀects, are generallynot well described by ALDA, we obtain excellent agreement with experiments for the surface lossfunction of the Mg(0001) surface with plasmon energies deviating by less than 0.2 eV. Finally, weapply the method to study the inﬂuence of substrates on the plasmon excitations in graphene. OnSiC(0001), the long wavelength π plasmons are signiﬁcantly damped although their energies remainalmost unaltered. On Al(111) the π plasmon is completely quenched due to the coupling to themetal surface plasmon.
MHA-Net: A Multibranch Hybrid Attention Network for Medical Image Segmentation

The robust segmentation of organs from the medical image is the key technique in medical image analysis for disease diagnosis. U-Net is a robust structure for medical image segmentation. However, U-Net adopts consecutive downsampling encoders to capture multiscale features, resulting in the loss of contextual information and insufficient recovery of high-level semantic features. In this paper, we present a new multibranch hybrid attention network (MHA-Net) to capture more contextual information and high-level semantic features. The main idea of our proposed MHA-Net is to use the multibranch hybrid attention feature decoder to recover more high-level semantic features. The lightweight pyramid split attention (PSA) module is used to connect the encoder and decoder subnetwork to obtain a richer multiscale feature map. We compare the proposed MHA-Net to state-of-art approaches on the DRIVE dataset, the fluoroscopic roentgenographic stereophotogrammetric analysis X-ray dataset, and the polyp dataset. The experimental results on different modal images reveal that our proposed MHA-Net provides better segmentation results than other segmentation approaches.
Russian History: From the Early East Slavs to the Grand Duchy of Moscow

But before the creation of Gardaríki, many nomad tribes settled the land, and their influence over the early Russian state will be further discussed. Then, Rurik’s successor, Oleg of Novgorod founded Kievan Rus’, the first united East Slavic state. [2] Christianity became the official religion of the state in 988, after extended commercial ties with the Bizantine Empire. [3] This crucial event is considered as the beginning of the synthesis between Byzantine and Slavic cultures, which would define Russian culture until the advent of the Empire. [4]
The MagE spectrograph

The Magellan Echellette (MagE) spectrograph is a single-object optical echellette spectrograph for the Magellan Clay telescope. MagE has been designed to have high throughput in the blue; the peak throughput is 22% at 5600 Å including the telescope. The wavelength coverage includes the entire optical window (3100 Å - 1 μm). The spectral resolution for a 1" slit is R~4100. MagE is a very simple spectrograph with only four moving parts, prism cross-dispersion, and a vacuum Schmidt camera. The instrument saw first light in November 2007 and is now routinely taking science observations.
Sequential Organ Failure Assessment Score and the Need for Organ Support Predict Mortality in Allogeneic Stem Cell Transplant Patients Admitted to the Intensive Care Unit Transplantation and Cellular Therapy

A B S T R A C T Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is an effective therapy resulting in increased de ﬁ nitive cure rates or extended disease-free survival in various malignant and nonmalignant hematologic diseases. However, because of the high risk of severe complications of this therapy, up to 50% of patients may require being admitted to the intensive care unit (ICU) to manage life-threatening conditions. We aimed to evaluate the in-hos- pital mortality of allo-HSCT recipients admitted to the ICU and to identify those variables associated with in-hos-pital mortality. A 10-year (January 2010 to December 2019), single-center, retrospective study was conducted in Vall d (cid:1) Hebron University Hospital, Barcelona. We included all consecutive allo-HSCT patients who required admission to the ICU. Baseline and disease-related characteristics were registered. Severity scores and the need for organ support were also assessed on days 1, 3, and 5 of ICU admission. In-hospital mortality (cid:1) associated independent variables were identi ﬁ ed using the Cox proportional hazards regression model. Three hundred twenty-three patients underwent allo-HSCT during the study period, of whom 82 (25%) were admitted to the ICU; 53 (65%) male, with a median age of 51 (38-59) years. Most patients received allo-HSCT for the treatment of lymphoma (20 patients [24%]) or acute leukemia (44 patients [54%]). The median Acute Physiology And Chronic Health Evaluation II score was 23 (17-28), and the median Sequential Organ Failure Assessment (SOFA) score on admission was 9 (7-11). Forty-nine (60%) patients died in the ICU, and 11 (13%) died in the hospital after being discharged from the ICU. Disease-related characteristics were not associated with mortality. Yet, SOFA score on day 1 (hazard ratio [HR]: 1.11 [95% con ﬁ dence interval {CI}: 1.04-1.02]; P = .002), the need for vasopressors on day 3 (HR: 2.35 [95% CI: 1.27-4.36]; P = .007), and a nondecreasing SOFA score on day 5 (HR: 2.13 [95% CI: 1.03-4.39]; P = .04), were independently associated with in-hospital mortality. Mortality in allo-HSCT patients who require ICU admission remains high. In the present study, SOFA score, the need for vasopressors on day 3, and a nondecreasing SOFA score on day 5 predicted in-hospital mortality.
COMPARISON STUDIES OF ITERATIVE ALGORITHMS FOR CENTER-OF-SETS TYPE-REDUCTION OF INTERVAL TYPE-2 FUZZY LOGIC SYSTEMS

Type-reduction is the kernel block of type-2 fuzzy logic systems. Studying the center-of-sets type-reduction is helpful for real applications of systems. This paper introduces the fuzzy reasoning, center-of-sets type-reduction and defuzzi(cid:12)cation of interval type-2 fuzzy logic systems. Based on the Karnik-Mendel algorithms, enhanced Karnik-Mendel algorithms and enhanced iterative algorithms with stopping condition for computing the centroids of interval type-2 fuzzy sets, this paper extends them for investigating the center-of-sets type-reduction of Mamdani type interval type-2 fuzzy logic systems. Several simulation experiments analyze the computational costs of three types of iterative algorithms for obtaining the output of interval type-2 fuzzy logic systems, which provides the potential reference values for designing and applying interval type-2 fuzzy logic systems.
Target Attention Network for Targeted Sentiment Analysis

We propose a novel target attention network (TAN) to identify the sentiment of opinion targets in a review or a twitter. Unlike previous works which represent the target in an averaging manner, we apply target attention to focus on more relevant parts of the target, which shows beneﬁts for later sentiment classiﬁcation. We also introduce a novel target-aware position embedding, which directly models the location relation between the target and its context to provide distinct information from semantic meanings for sequence encoder. Extensive experiments demonstrate the robustness of our ﬁndings. The experimental re-sults show that our model consistently out-performs the state-of-the-art methods on four public benchmarks.
Graph-Embedding Based Clustering for Log Anomaly Detection

Console logs rarely help operators detect problems in large-scale data-center services, for they often consist of the voluminous intermixing of messages from many software components written by independent developers. However, log messages are the most straightforward indicator of anomaly events. Thus, automatic anomaly detection on logs with computers is very important for automatic operation and maintenance systems. In this proposal, we leverage both the semantic knowledge and relationship among individual log messages to create meaningful and robust embedding for each event. The embedding is then aggregated to form sequence feature vectors for log anomaly detection through clustering and distance weighing. With the employment of efficient clustering assignment model, we reduce the offline computation time and complexity while preserving the distinct identification of anomalies. Our best model achieves 0.6 f1-score for the anomaly class and 0.97 weighted average f1-score for both classes, which surpasses previous state-of-art.
Learning Experiences that Facilitate Innovation and Workforce Preparation: Exploring the Impact of In-Class and Extracurricular Activities*

The ability to think innovatively is necessary for important workforce outcomes and is linked to the production of successful entrepreneurial endeavors. Gaining a better understanding of in class activities and extracurricular experiences that facilitate development of innovative thinking plays a critical role in developing engineering graduates who can contribute innovative ideas and solutions in the workforce. A mixed-method study (N = 595 survey, N = 52 focus group) was undertaken to understand what classes, groups, activities, or other resources inﬂuenced students’ innovative thinking. Our ﬁndings indicate that as engineering students progress through their undergraduate career they feel more prepared to contribute innovative solutions in future workplace settings. However, our study indicates that students do not engage in activities that facilitate development of innovative thinking skills until their fourth year of study. Educators would beneﬁt from weaving opportunities throughout students’ undergraduate experience including those that incorporate increased opportunities for students to share ideas, gain diﬀerent perspectives, and solve problems in environments inside and outside of an engineering classroom. helping me to broaden my view and actually explore a broader perspective. ’’
DEEP LEARNING APPROACHES FOR CLASSIFYING DATA: A REVIEW

Data mining can be considered as the first approach for classification of sentiments. Data mining can be considered as the first approach for classification of sentiments. Later, Machine learning and its techniques were used to analyse sentiments but, machine language-based learning systems find it complex to understand the language of humans. Therefore, we move towards deep learning models to analyse sentiments. The subgroup of machine learning is Deep-Learning; it involves networks, namely RNN (Recurrent Neural Networks), Recursive Neural Networks, Convolutional Neural Network (CNN) and Deep Belief Networks. Neural networks are very useful in the generation of text, the depiction of vector, word assessment, classifying sentences and representation. Sentiment analysis can be determined as a process for identifying the emotions with the help of a series of words which are used in online sites. It can be utilized to analyse the point of view and attitudes, depending on the words. Sentiment analysis is mostly used in monitoring social media to gain information about public opinion on certain trending topics. Sentiment analysis is performed by taking some sentiment examples, the features are extracted from sentiments and then the parameters are trained in our model and in the final stage, the model is tested. In this paper, an empirical survey of the three models of deep learning, namely RecurrentNN, RecursiveNN and ConvolutionalNN are discussed.
Cepheid Calibration of the Peak Brightness of Type Ia Supernovae: Calibration of SN 1990N in NGC 4639 Averaged with Six Earlier Type Ia Supernova Calibrations to Give H0 Directly

Periods and light curves have been measured with the Hubble Space Telescope for 20 Cepheids in NGC 4639, parent galaxy to the Type Ia, prototypical supernova SN 1990N. The periods range from 17 to 69 days. The mean apparent magnitudes, averaged over the light curves, range from ⟨V⟩ = 25.6 to ⟨V⟩ = 27.3. Well-determined period-luminosity relations exist in V and I. Corrected for differential extinction, these give a true modulus for NGC 4639 of (m - M)0 = 32.00 ± 0.23. Combining the light curves for SN 1990N with this modulus gives MB(max) = -19.30 ± 0.23 and MV(max) = -19.39 ± 0.23. This, together with six previous calibrations of Type Ia supernovae, gives the mean calibrations of “Branch normal” supernovae to date as ⟨MB(max)⟩ = -19.47 ± 0.07 and ⟨MV(max)⟩ = -19.48 ± 0.07. The resulting Hubble constants, reading the Type Ia supernova Hubble diagrams at very large redshifts beyond any possible local velocity anomalies, give global values of the Hubble constant of H0(B) = 56 ± 4 (internal) km s-1 Mpc-1 and H0(V) = 58 ± 4 (internal) km s-1 Mpc-1.
Angiographic and clinical outcome of SARS-CoV-2 positive patients with ST-segment elevation myocardial infarction undergoing primary angioplasty: A collaborative, individual patient data meta-analysis of six registry-based studies European Journal of Internal Medicine

Background: The characteristics and outcome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)- positive patients with ST-Elevation Myocardial Infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI) are still poorly known. Methods: The PANDEMIC study was an investigator-initiated, collaborative, individual patient data (IPD) meta-analysis of registry-based studies. MEDLINE, ScienceDirect, Web of Sciences, and SCOPUS were searched to identify all registry-based studies describing the characteristics and outcome of SARS-CoV-2-positive STEMI patients undergoing PPCI. The control group consisted of SARS-CoV-2-negative STEMI patients undergoing PPCI in the same time period from the ISACS-STEMI COVID 19 registry. The primary outcome was in-hospital mortality; the secondary outcome was postprocedural reperfusion assessed by TIMI flow. Results: Of 8 registry-based studies identified, IPD were obtained from 6 studies including 941 SARS-CoV-2-positive patients; the control group included 2005 SARS-CoV-2-negative patients. SARS-CoV-2-positive pa- tients showed a significantly higher in-hospital mortality ( p < 0.001) and worse postprocedural TIMI flow ( < 3, p < 0.001) compared with SARS-CoV-2-negative subjects. The increased risk for SARS-CoV-2-positive patients was significantly higher in males compared to females for both the primary (p interaction = 0.001) and secondary outcome (p interaction = 0.023). In SARS-CoV-2-positive patients, age ≥ 75 years (OR = 5.72; 95%CI: 1.77 – 18.5), impaired postprocedural TIMI flow (OR = 11.72; 95%CI: 2.64 – 52.10), and cardiogenic shock at presentation (OR = 11.02; 95%CI: 2.84 – 42.80) were independent predictors of mortality. Conclusions: In STEMI patients undergoing PPCI, SARS-CoV-2 positivity is independently associated with impaired reperfusion and with a higher risk of in-hospital mortality, especially among male patients. Age ≥ 75 years, cardiogenic shock, and impaired postprocedural TIMI flow independently predict mortality in this high- risk population.
Fully-resolved simulations of single char

23 A novel ghost-cell immersed boundary method for fully resolved simulation of 24 char particle combustion has been developed. The boundary conditions at the solid 25 particle surface, such as velocity, temperature, density and chemical species 26 concentration, are well enforced through the present method. Two semi-global 27 heterogeneous reactions and one homogeneous reaction are used to describe the 28 chemical reactions in the domain, and the Stefan flow caused by the heterogeneous 29 reactions is considered. A satisfactory agreement can be found between the present 30 simulation results and experimental data in the literature. The method is then used to 31 investigate the combustion property of a char particle and the interaction between CO2 32 gasification and O2 oxidation. Furthermore, combustion effect on the exchange of mass, 33 momentum and energy between gasand solidphase is explored. 34 35
Donor flow formulation for momentum flux differencing

A new donor flow formulation for momentum flux differencing has been developed to eliminate the pressure and velocity anomalies caused by fictitious momentum sources that arise when other numerical formulations are used to characterize the large density gradients associated with sodium boiling. This new formulation has been incorporated into the CAPRICORN subchannel code for sodium boiling in fuel bundles, resulting in considerable improvement in numerical performance.
Size distributions of incomes and expenditures testing the parametric approach

It is common in economics to describe the size distribution of income by a parametric function. We will fit some of the most frequently used functional forms (Gamma, Generalized Gamma, Singh-Maddala, Lognormal and Fisk) to the income data made available by the ESRC Data Archive at the University of Essex. Using the Kolmogorov-Smirnov test, the data reject all functional forms applied to the whole population. Stratifying the data into subgroups using the criteria of household composition or the main source of income reveals differences in the flexibilities of the parametric forms to represent the data.
Comparativeclinical Evaluation of Changes in Marginal Bone Level Following Implants Placed With Flapless Versus Flap Method

---------------------------------------------------------------------------------------------------------------------------------------ABSTRACT : Implant-supported restorations have been used as a successful modality in edentulous region restorations. The conventional technique for implant placement includes elevation of mucoperiosteal flap. Flapless technique is gaining popularity due to numerous advantages like preservation of circulation, soft tissue architecture, and hard tissue volume; improved patient comfort; and accelerated recuperation. Therefore, the study is aimed to comparethe marginal bone loss by both proceduresand evaluate which procedure leads to minimal crestal boneloss.The study concluded that flapless technique showed minimal crestal bone loss than flap technique which was statistically insignificant. replacing
Distribution of the European green lizard, Lacerta viridis (Squamata: Lacertidae), in the Czech Republic: Real data and a predictive model

The European green lizard, Lacerta viridis (Laurenti, 1768), is listed in the Czech Republic as critically endangered. Its distribution in the Bohemia region is restricted to small isolated local populations which are located beyond the northern border of continuous range of this species and are closely related to very specific habitats. Populations in southern Moravia form the northwestern boundary of the continuous distribution of the species. Based on the statewide database of the Czech Nature Conservation Agency, we created a predictive model and determined key factors influencing the species distribution in the Czech Republic. The most relevant factors were: annual precipitation, terrain slope, average temperature of the warmest quarter and precipitation in the coldest quarter. The model is well compatible with published data on Lacerta viridis distribution in the Czech Republic and is applicable in both theory and practice of the species conservation – e.g. focusing faunistic research to certain areas, critical analysis of controversial presence reports and as an input for species management in the form of repatriation and introduction.
A Statistical Modeling Approach for FEC-Encoded High-Speed Wireline Links

This paper presents a statistical modeling approach to accurately estimate post-FEC BER for high-speed wireline links using standard linear block codes, such as the RS(544,514,15) KP4 and RS(528,514,7) KR4 codes. A hierarchical approach is adopted to analyze the propagation of PAM-symbol and FEC-symbol errors through a two-layer Markov model. In this paper, we will turn our proposed BER estimation method into a set of tools to assist in making architectural choices for wireline transceivers, such as co-design of the equalization and FEC in the presence of DFE error propagation and various noise sources including residual ISI, crosstalk, transmitter and receiver jitter.