Miracle-dz/UniFAR-FTUs huggingface dataset:
Relative and Absolute Fit Evaluation in Cognitive Diagnosis Modeling.

As with any psychometric models, the validity of inferences from cognitive diagnosis models (CDMs) determines the extent to which these models can be useful. For inferences from CDMs to be valid, it is crucial that the fit of the model to the data is ascertained. Based on a simulation study, this study investigated the sensitivity of various fit statistics for absolute or relative fit under different CDM settings. The investigation covered various types of model–data misfit that can occur with the misspecifications of the Q-matrix, the CDM, or both. Six fit statistics were considered: –2 log likelihood (–2LL), Akaike's information criterion (AIC), Bayesian information criterion (BIC), and residuals based on the proportion correct of individual items (p), the correlations (r), and the log-odds ratio of item pairs (l). An empirical example involving real data was used to illustrate how the different fit statistics can be employed in conjunction with each other to identify different types of misspecifications. With these statistics and the saturated model serving as the basis, relative and absolute fit evaluation can be integrated to detect misspecification efficiently.
A synchrotron jet from a post-AGB star

The evolution of lowand intermediate-initial-mass stars beyond the asymptotic giant branch (AGB) remains poorly understood. High-velocity outflows la unched shortly after the AGB phase are thought to be the primary shaping mechanism of bipo lar and multipolar planetary nebulae (PNe). However, little is known about the launching a d driving mechanism for these jets, whose momentum and energy often far exceed the energy t hat can be provided by radiation pressure alone. Here, we report direct evidence of a mag netically collimated jet shaping the bipolar morphology of the circumstellar envelope of a po st-AGB star. We present radio continuum observations of the post-AGB star IRAS 15445 −5449 (OH 326.5−0.4) which has water masers tracing a fast bipolar outflow. Our observation s confirm the earlier observed steep negative spectral index of the spectral energy distri bution (SED) above∼ 3 GHz, and resolve, for the first time, the emission to originate from a r adio jet, proving the existence of such jets around a post-AGB star. The SED is consistent wit h a synchrotron jet embedded in a sheath of thermal electrons. We find a close correspon dence between the extent and direction of the synchrotron jet and the bipolar shape of the obj ct observed at other wavelenghts, suggesting that the jet is responsible for the sour ce morphology. The jet is collimated by a magnetic field of the order of mG at almost 7000 AU from the c entral star. We recover observations from the ATCA archive that indicate that the em ission measure of the thermal component has increased by a factor of three between 1998 and 2005 after which it has remained constant. The short timescale evolution of the radio emission suggests a short lifetime for the jet. The observations of a synchrotron jet from a post -AGB star with characteristics similar to those from protostars and young stellar objects, for instance, suggest that magnetic launching and collimation is a common feature of astrophysi cal jets.
Targeting Epidermal Growth Factor Receptor in Head and Neck Cancer

Abstract Head and neck squamous cell carcinomas are rising in incidence worldwide, and despite the advent of improved surgical and radiation techniques, a substantial proportion of patients have disease recurrence, where systemic therapies are the mainstay of management. Recent advances in systemic therapy include the development of epidermal growth factor receptor– and programmed death 1–targeting drugs, which have produced incremental improvements in disease outcomes. However, for most patients, responses to treatment remain elusive because of primary or acquired resistance. Novel drugs and rational drug combinations need to be tested based on biomarker identification and preclinical science that will ultimately advance outcomes for our patients. This review focuses on efforts untaken for epidermal growth factor receptor targeting in head and neck squamous cell carcinoma to date.
The FB Prophet Model Application to the Growth Prediction of International Tourists in Indonesia during the COVID-19 Pandemic

— COVID-19 declared as pandemic by the World Health Organization (WHO) on March 11, 2020. Based on data by the COVID-19 Task Force website the number of COVID-19 cases reached 126,921,284 cases in the world in March 29, 2021. This has an impact on various sectors are supports the Indonesian economy, such the tourism sector. This research predicted the growth of foreign tourists in Indonesia during COVID-19 by applying the Prophet Model. This model was developed by Facebook using a forecasting approach scheme, namely inputting the dataset, preprocessing, processing, post-processing, and output. The results of this research indicated that the growth rate of foreign tourists in Indonesia tends to decline until February 2022 and will begin to increase in March 2022. On the other side, the number of COVID-19daily cases tends to decline until December 2021. This research can be taken into consideration in decision making by parties who needed.
A Composite Source Model With Fractal Subevent Size Distribution

Abstract A composite source model, incorporating different sized subevents, provides a possible description of complex rupture processes during earthquakes. The number of subevents with characteristic dimension greater than R is proportional to R. The subevents do not overlap with each other, and the sum of their areas equals to the area of the target event. The subevents are distributed randomly over the fault. Each subevent is modeled either as a finite source using kinematic approach, or as a point source. The synthetic Green's functions are calculated by the discretewavenumber method in a 1D horizontally layered crustal model in a relatively coarse grid of points covering the fault plane. The Green's functions in a fine grid are obtained by cubic spline interpolation. The composite source model described above allows interpretation in terms of a kinematic model with non-uniform final slip and rupture velocity spatial distributions.
Predicting and Investigating the Permeability Coefficient of Soil with Aided Single Machine Learning Algorithm

The permeability coefficient of soils is an essential measure for designing geotechnical construction. The aim of this paper was to select a highest performance and reliable machine learning (ML) model to predict the permeability coefficient of soil and quantify the feature importance on the predicted value of the soil permeability coefficient with aided machine learning-based SHapley Additive exPlanations (SHAP) and Partial Dependence Plot 1D (PDP 1D). To acquire this purpose, five single ML algorithms including K-nearest neighbors (KNN), support vector machine (SVM), light gradient boosting machine (LightGBM), random forest (RF), and gradient boosting (GB) are used to build ML models for predicting the permeability coefficient of soils. Performance criteria for ML models include the coefficient of correlation R2, root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE). The best performance and reliable single ML model for predicting the permeability coefficient of soil for the testing dataset is the gradient boosting (GB) model, which has R2 = 0.971, RMSE = 0.199 × 10−11 m/s, MAE = 0.161 × 10−11 m/s, and MAPE = 0.185%. To identify and quantify the feature importance on the permeability coefficient of soil, sensitivity studies using permutation importance, SHapley Additive exPlanations (SHAP), and Partial Dependence Plot 1D (PDP 1D) are performed with the aided best performance and reliable ML model GB. Plasticity index, density > water content, liquid limit, and plastic limit > clay content > void ratio are the order effects on the predicted value of the permeability coefficient. The plasticity index and density of soil are the first priority soil properties to measure when assessing the permeability coefficient of soil.
Metaverse dünyasında marka aşkını etkileyen faktörler ve marka aşkının, ağızdan ağıza pazarlamaya etkisi

Metaverse Dünyası son yıllarda en fazla tartışılan ve dikkatleri üzerine çeken bir kavram olarak karşımıza çıkmaktadır. Metaverse’te yer almak isteyen işletmeler, rekabete hazır olabilmek adına markalaşma süreçlerine özen göstermekte; marka güveni ve marka imajı yaratarak, tüketicilerin marka aşkı duymalarını sağlamaya çalışmaktadır. Bu bağlamda, marka aşkının ağızdan ağıza pazarlamayı olumlu yönde etkilemesiyle işletmeler karlılığa giden yolda şanslarını arttırmaktadır. Bu çalışmada Metaverse dünyasında yer alan uluslararası bir spor giyim markasının müşterilerine çevrimiçi anket çalışması uygulanmıştır. Bu çalışmada Metaverse dünyasında yer alan uluslararası bir spor giyim markasının müşterilerine yönelik çevrimiçi anket çalışması uygulanmış ve 380 kişiden veri toplanmıştır. Araştırma bulgularına göre, Metaverse dünyasındaki müşterilerin, marka güveni ve markanın imajının yüksek olduğu ve bu öncüllerin müşterilerin marka aşkı duymalarını sağladığı tespit edilmiştir. Ayrıca marka aşkı duyan müşterilerin, memnuniyetlerini çevreleri ile paylaşarak ağızdan ağıza pazarlamayı arttırdıkları sonucuna ulaşılmıştır.
A Multigranularity Text Driven Named Entity Recognition CGAN Model for Traditional Chinese Medicine Literatures

Recognition of Traditional Chinese Medicine (TCM) entities from different types of literature is challenging research, which is the foundation for extracting a large amount of TCM knowledge existing in unstructured texts into structured formats. The lack of large-scale annotated data makes unsatisfactory application of conventional deep learning models in TCM text knowledge extraction. Some other unsupervised methods rely on other auxiliary data, such as domain dictionaries. We propose a multigranularity text-driven NER model based on Conditional Generation Adversarial Network (MT-CGAN) to implement TCM NER with small-scale annotated corpus. In the model, a multigranularity text features encoder (MTFE) is designed to extract rich semantic and grammatical information from multiple dimensions of TCM texts. By differentiating the conditional constraints of the generator and discriminator of MT-CGAN, the synchronization between the generated tag labs and the named entities is guaranteed. Furthermore, seeds of different TCM text types are introduced into our model to improve the precision of NER. We compare our method with other baseline methods to illustrate the effectiveness of our method on 4 kinds of gold-standard datasets. The experiment results show that the standard precision, recall, and F1 score of our method are higher than the state-of-the-art methods by 0.24∼8.97%, 0.89∼12.74%, and 0.01∼10.84%. MT-CGAN is able to extract entities from different types of TCM literature effectively. Our experimental results indicate that the proposed approach has a clear advantage in processing TCM texts with more entity types, higher sparsity, less regular features, and a small-scale corpus.
Introductory Lectures on Multiple Membranes

These lecture notes introduce the multiple membrane theories known as BLG and ABJM. We assume the reader is familiar with string theory, but not with M-theory, 11-dimensional supergravity or membranes. We therefore start with a background on M-theory and its extended objects before discussing BLG and ABJM. The link to string theory via dimensional reduction will be maintained throughout.
Nanothermodynamics:a generic approach to material properties at nanoscale

Granular and nanoscale materials containing a relatively small number of constituents have been studied to discover how their properties differ from their macroscopic counterparts. These studies are designed to test how far the known macroscopic approaches such as thermodynamics may be applicable in these cases. A brief review of the recent literature on these topics is given as a motivation to introduce a generic approach called nanothermodynamics. An important feature that must be incorporated into the theory is the non-additive property because of the importance of surface contributions to the physics of these systems. This is achieved by incorporating fluctuations into the theory right from the start. There are currently two approaches to incorporate this property. Hill (and further elaborated more recently with Chamberlin) initiated an approach by modifying the thermodynamic relations by taking into account the surface effects. We generalize Boltzmann-Gibbs statistical mechanics by relaxing the additivity properties of thermodynamic quantities to include nonextensive features of such systems. An outline of this generalization of the macroscopic thermodynamics to nano-systems will be given here.
Intraoperative pressure injury and risk factors in long-term surgical interventions 1

Background: If the operation time is 60 minutes or longer, the patient's risk of intraoperatively acquired pressure injury (IAPI) increases. Aim: This study aims to determine the prevalence and risk factors for IAPI in patients who underwent surgery for 60 > minutes in a private university hospital in Turkey. Methods: The research is a cross-sectional, descriptive, prospective design. Data were collected in the perioperative period (N=200). Sociodemographic and Clinical Characteristics Form and 3S intraoperative risk assessment scale (3S-IRAS) for PI and Braden Scale were used for data collection. Findings: IAPI occurred in 18.0% of participants. Although the risk of pressure injury was higher in women, those with chronic disease, those with major surgery, and those with chronic disease, this risk was weaker. However, the intraoperative position of the patient was 2.6 times (95% CI [Confidence Interval]: 0.552-12,674), the operative time was 2.0 times (95% CI: 1.113-3.780), the magnitude of the surgery was 11.5 times (95% CI: 2.029). -65.954), intraoperative skin stress constituted a 4.3-fold (95% CI: 1.815-10.369) risk of pressure injury. Conclusion: IAPI is an important risk factor for the patient in the operating room. Although sociodemographic characteristics are weakly associated with pressure injury, nurses should closely monitor patients with these risk factors. Especially in major surgical interventions and long-term surgeries, the position of the patient gains importance. It can be said that the management of IAPI requires the cooperation of the perioperative nurse. intraoperative mL, mL, and mL); 38.3°C 38.3°C 36.1°C); operative position point supine position, 2 lateral position, lithotomy position, and 4 for prone position). total score the scale a 9 and a of 36; patients above 23 as and those 23 as (Gao et al.
PITCH MOVEMENT AND ANALYSIS OF AIRCRAFT USING OPENVSP

There are many different design options available thanks to the growing number of customised solutions in the aircraft design process, which mostly rely on new technology at the component level. In addition, there is a rising need for a uniform, intelligible data model due to the process' increased complexity as well as the increasing number of possible fixed-wing aircraft configurations. Design is made simpler by the use of parametric geometry tools like Vehicle Sketch Pad (OpenVSP), which express geometry in language that are most familiar to designers. The development of new OpenVSP features and capabilities has been extensively covered in publications and presentations over the years, but use case studies and best practises are frequently not documented. To illustrate the use of OpenVSP in the design process, this paper provides examples of advanced OpenVSP templates best practises.
Analyse numérique de problèmes de contrôle stochastique

Optimal stochastic control problems have a large number of applications in problems of economy, finance (see e. G. The portfolio selection problem in a market with risky assets and non-risky assets, the investment problem and the super-replication price in a model with uncertain volatility), and management of energy. These are typical situations in where we are faced to a dynamical system which evolves under some conditions of uncertainty, and where we have to take a decision at every time, to optimize an economical criterion. In particular, the control variable acts on the state of the system. Stochastic control problems are historically handled with the Bellman dynamic programming principle, which leads to obtain a characterization of the value function of the optimal control problem as solution of a partial differential equation, said the Hamilton-Jacobi- Bellman equation. In most cases, the value function is not sufficiently smooth to satisfy the HJB-equation in the classical sense. It is for this reason that the notion of viscosity solution, introduced by Crandall and Lions for the deterministic Hamilton-Jacobi-Bellman equation, has been extended to the second order problem by Lions. The theory of viscosity solutions, provided an extremely convenient framework for dealing with the lack of smoothness of the value function of the optimal stochastic control problem. In some situations, the value function could be smooth : this is the case, for example, of the Merton portfolio selection problem, for which a classical solution of the correspondent HJB-equation can be performed. However, in the general case, the HJB-equation can not be solved explicitly, hence it is necessary to analyze it numerically. In particular a discretization of the HJB-equation via Markov chain approximation is considered, and an approximate solution is computed. It is then necessary to guarantee that the numerical solution is a good approximation of the viscosity solution, and for this reason a theory of error estimate has been developed. This theory leads to obtain a theoretical estimate of the differences between the viscosity solution and the discrete solution. The thesis is divided in two parts. In the first part we give error estimates for a problem on stochastic game theory, and stochastic impulse control problem. Both these problems have some particular difficulties, and classical results on error estimate can not be applied directly. The second part concerns a study of some algorithms to implement, in particular for two problems : a stochastic impulse control problem, and a problem with unbounded control.
Quantifying the effects of grass distribution patterns on the relative hydrodynamic parameters of overland flow

Grass distribution pattern (GDP) plays a crucial role in soil erosion, which is driven by overland flow on hillslopes caused by rainfall. To quantify the effects of GDPs on the hydrodynamic characteristics of overland flow, indoor scouring experiments were conducted in a hydraulic flume across eight flow discharges (3–45 L min−1), six slope gradients (2–12°), and five GDPs—a vertical strip pattern parallel to the slope direction (VP), chequerboard pattern (CP), small patches distributed in an ‘X’‐shape (XP), a banded pattern perpendicular to slope direction (BP), and a random pattern (RP). The results showed that GDP had a significant effect on the hydrodynamic parameters of overland flow when compared with bare slope (BS). For the five GDPs, the relative water depth, relative flow velocity, relative Froude number, and relative resistance coefficient were positively affected by flow discharge (p < 0.001), and negatively affected by slope gradient (p < 0.001); whereas the effects on the relative Reynolds number were inverted. Compared with the other patterns, the effects of BP on retarding flow was the best, as it maintained particularly remarkable characteristics affecting all five relative hydrodynamic parameters. Through parameterising GDP as a calculation factor, the prediction models of relative flow velocity (adj.R2 = 0.788**, Nash–Sutcliffe efficiency [NSE] = 0.692), and relative Froude number (adj.R2 = 0.756*, NSE = 0.674) were established via nonlinear regression analysis. The effects of GDP on overland flow revealed here can help inform optimal GDP designs for water and soil conservation on sloped environments.
Twenty Thousand Parallel Special-Purpose Computer for Phase-Type Electroholography Using the Hilbert Transform

Electroholography is gaining popularity as an ideal three-dimensional display technology, but it requires high-performance computers for practical use. In this paper, we used the Hilbert transform to build a special-purpose computer for phase-only electroholography. As a result, we succeeded in speeding up calculation 400 times faster than commercial CPUs.
Medicine Insufficient Evidence for the Efficacy of Massage as Intervention for Autism Spectrum Disorder: A Systematic Review

The efficacy of massage therapy in the treatment of children with autism spectrum disorder (ASD) remains unclear. This study systematically reviewed the impact of massage therapy on children with ASD according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) declaration guidelines. A literature search of the PubMed, Web of Science, Science Direct, Scopus, Google Scholar, and China National Knowledge Infrastructure (CNKI) electronic databases from inception to December 20, 2020, was conducted using the term “autistic/autism” along with one of the following terms, “massages,” and “Tui na. ” The risk of bias was assessed using the Cochrane risk of bias Tool. Eight randomized controlled trials examining the impact of massage on children with ASD were included. Interventions combining Qigong massage or Tui na with the control group treatments from once a day to twice a week, for a duration of 15–30 mins, and lasting for six weeks to five months were the main interventions. All reviewed studies reported significant improvement in children with ASD who received massage, especially in the sensory domain, and that massage in combination with control treatment was superior to control treatment alone. However, the overall quality of the available studies is poor with a high degree of heterogeneity. The majority of studies showed a high risk of bias with poor study design, inconsistency in massage protocols, and subjective outcome measures. Assessment bias was a common weakness of these studies. Therefore, there is insufficient evidence to conclude that massage is effective for ASD. Future studies should include large sample sizes, incorporate double-blind designs, employ appropriate outcome measures, and allow for long observation and follow-up periods. Furthermore, consensus must be reached on standardized treatments and additional therapies in order to provide better quality evidence for the treatment of ASD.