Miracle-dz/UniFAR-FTUs huggingface dataset:
Students’ categorizations of organic compounds

Categorization is a fundamental psychological ability necessary for problem solving and many other higher-level cognitive tasks. In organic chemistry, students must establish groupings of different chemical compounds in order not only to solve problems, but also to understand course content. Classic models of categorization emphasize similarity as the primary means of classification: if two items are similar, they belong in the same category and if they are dissimilar, they belong in different categories. These models also underscore a one-dimensional approach where a single salient feature is often used as the basis of categorization, even though multiple salient features may be present. This study examined the critical attribute organic chemistry students used to categorize eight organic compounds possessing similar salient features related to structure, functional groups, and stereochemistry and how this primary feature changed over time. Results from this study support the notion that the critical attribute is not stable, but changes as student learning progresses. The results also suggest that categorization is a systematic process involving conscious selection of the critical attribute and that higher-ability students (e.g., honor students) are more prone to be influenced by the current instructional topic when selecting the critical attribute.
The Influence of the Flight Aerodynamic for Interactions of Wings and Body of the Honeybee

The flight mechanism of flapping-wing was studied by using the translation-rotation model. We established the flapping-coordinate of the wing, gave the equation of the motion, and simplified the flapping-wing model. The aerodynamic and vortices were simulated by the CFD software of Fluent. The leading-edge vortex generated in the translation phase, and delayed stall mechanism had an important effect on the high lift. In the rotation phase, lift peaks appear due to the wing rapidly rotating and rotational circulation mechanism. The aerodynamics were obtained in different amplitudes, frequencies, angles of attack, the locations of rotating axis and timings of rotation. The influence of these parameters on average lift coefficient is obvious, while it can be ignored to average drag coefficient. Keywords: wing, aerodynamics, vortices, numerical simulation.
Neyman-type smooth tests for location-scale families

SUMMARY The smooth tests of Neyman (1937) are modified to permit composite alternatives and a choice of orthonormal functions in their construction. These orthonormal functions may be chosen to improve detection of particular alternatives. The tests are easy to apply and have useful orthogonal components. A test for exponentiality is examined, and shown to perform well against its competitors.
Global real analytic angle parameters for Teichmüller spaces

A Fuchsian group $G$ acting on the unit disk $D$ is of type $(g, 0, m)$ , if the quotient space $D/G$ is a Riemann surface of genus $g$ with $m$ holes. This Riemann surface is also called of tyPe $(g, 0, m)$ . From now on, let $(g, 0, m)$ satisfy $2g+m\geqq 3$ . This condition means that $G$ is non-elementary. Teichm\"uller space $T(g, 0, m)$ is the set of equivalence classes of marked Fuchsian groups of type $(g, 0, m)$ and a global real analytic manifold of dimension $6g+3m-6$ . There are various methods parametrizing $T(g, 0, m)$ . For example, $T(g, 0, m)$ is parametrized global real analytically by some lengths of closed geodesics and intersection angles between geodesics on a Riemann surface represented by a marked Fuchsian group (see Keen [5]). Such lengths and angles are called length parameters and angle parameters, respectively. It is known that length parameters parametrize $T(g, 0, m)$ global real analytically (see for example, [3], [6], [8], [9] and [18]). We denote by
Stereoselective reactions of chiral α-amino aldehydes

Optically active α-amino acids can be converted into the corresponding doubly protected N,N-dibenzyl α-amino aldehydes. These react diastereoselectively with Grignard reagents, lithium enolates and Me3SiCN/ZnX2 to provide the nonchelation-controlled adducts. Molecular modelling explains some of the results. The sense of stereoselectivity can be reversed if Lewis acidic chelating reagents are used. Undesired racemization does not occur.
Physics-driven digital twin for laser powder bed fusion on GPUs

Metal Additive Manufacturing (AM) processes such as Laser Powder Bed Fusion (LPBF) suﬀer from part distortion due to the localized melting and resolidiﬁcation of the metal powder, which introduces stresses and strains. Despite becoming more and more important as a manufacturing process, options for simulating the printing process to predict the distortions are limited, especially because existing solutions often require very long computation times. In this work, we present the results of an implementation of the inherent strain method on graphics processing units (GPUs) that exploits the massive parallelism of the many GPU cores to speed up the simulations considerably compared to CPU-based implementations.
The modified component method for calculation of orientation distribution function from pole figures

The main problem of the quantitative texture analysis is discussed. The sharp texture of nanocrystalline magnesium is under investigation. The well-known harmonic (Roe–Bunge) method of texture determination does not give good results for the materials with low sample symmetry. The robust component fit method for the determination of the orientation distribution function from the set of incomplete X-ray pole figures is used in this work. A unique and reliable solution is achieved.
The impact of underlying diseases-related drugs on the chronic kidney disease-associated pruritus in hemodialysis patients

Background: Uremic pruritus or chronic kidney disease-associated pruritus (CKD-aP) is a frequent compromising symptom in end-stage renal disease. Despite the little attention paid to drugs used among hemodialysis (HD) patients, investigating medications used in this population of patients and examining the status of CKD-aP may lead to the identification of medications that improve or worsen the pruritus condition. We aimed to assess the role of underlying diseases-related drugs on CKD-aP in HD patients. Materials and Methods: We performed a case − control study on HD patients aged over 18 years old. The demographic data and clinical parameters including HD parameters, drug history, dermatologic assessments, and laboratory examination were assessed. Results: We compared 128 patients with CKD-aP as cases and 109 patients without CKD-aP as controls. Cases were on the longer course of dialysis (44.69 ± 43.24 months for cases vs. 38.87 ± 50.73 months for controls; P = 0.02). In multiple analyses of variables related to CKD-aP, backward LR logistic regression revealed that only atorvastatin (P = 0.036) was considered to be a predictive factor associated with CKD-aP. Thus, the use of atorvastatin reduced the index of CKD-aP (95% confidence interval: 0.256–0.954, odd's Ratio = 0.494). Conclusion: Atorvastatin was associated with decreased frequencies of CKD-aP among HD patients in our study. This knowledge may guide further clinical trials to evaluate atorvastatin's immunomodulatory and anti-inflammatory effects on the CKD-aP in HD populations.
The impact of collisional rate coefficients on molecular hyperfine selective excitation

Nuclei with non-zero spin induce hyperfine splittings in the rotational spectrum of many commonly observed interstellar molecules. Radiative transfer modelling of such species requires in general a good knowledge of hyperfine selective collisional rate coefficients. We investigate in this work the impact of collisional rate coefficients on the molecular hyperfine excitation. The approximate sudden and statistical (proportional) methods are first compared to the almost exact recoupling approach. Rate coefficients are presented for a large number of CN and HCN transitions, with para-H2(j = 0) as a collider. The sudden approximation and the recoupling approach, which both predict the propensity rule Δj = ΔF, are found to agree within a factor of 3 or better. Radiative transfer calculations are then performed using the large velocity gradient approximation. At low and moderate total optical depths (τ ≲ 10), where the relative hyperfine populations are close to the statistical weights, both the sudden and the statistical approximations are shown to provide accurate alternatives to the recoupling approach. At higher total opacities, however, the hyperfine propensity rule appears to matter and the sudden method is found to be significantly superior to the statistical approach.
Impact of Real Estate Environment on Knowledge Worker Performance in IT Companies: Evidence from Sri Lanka

Knowledge worker performance is becoming an increasingly important requirement in information technology (IT) firms for its competitiveness. Although employee performance is an extensively researched area, the impact of the real estate environment of office on the performance of employees is still unexploited. The impact of the physical and social workplace on cognition and knowledge sharing by the knowledge worker and its impact on the knowledge worker's performance are hardly discussed in the literature. In this context, this study aims to investigate the relationship between the physical and social workspace setting on the knowledge worker performances in the Information Technology (IT) industry in Sri Lanka. The outcome of the study provides insight to top management of IT companies to confirm how attributes of office real estate environment contributes to knowledge worker performance. The study applied a quantitative approach to explore the impact of the physical and social workspace on the performance of knowledge workers. The study employed a convenience sampling method for collecting data from 185 respondents who worked in IT industry using a self-administered questionnaire. Partial Least Squares Structural Equation Model (PLS –SEM) was used to analyze the data. The findings of the study confirmed that physical workspace support cognitive work and knowledge sharing of a knowledge worker. Physical workspace characteristics have the strongest impact on knowledge sharing than the cognitive work of the knowledge employee. In addition, the analysis confirmed that cognitive work also supports knowledge worker performance. Thus, findings suggest that a review of the physical workspace of the IT organization is an important strategic decision to ensure higher order performance of the IT employees. In summary, the study argued that the physical workspace of the organization seems to play a pivotal role in ensuring the higher performance of the employee via cognition. Thus, this paper contributes to IT company management to think out of the box to ensure an improved physical workspace for better employee performance.
The sealing of soils and its effect on soil-gas migration

The influence of a sealed soil on soil-gas migration is described by using 222Rn as a natural tracer. It is shown that 222Rn is focused to the rims of anthropogenic sealing, like asphalt or concrete. At a test site, the sealing effect was investigated in detail by using a radon-tight foil. A model to understand the soil-gas migration in dependence on the degree of sealing is developed. This study enhance the knowledge about the migration of hazardous gases in the soil, like methane or the carcinogenic 222Rn itself. Additionally, the sealing effect can be used to increase the efficiency of soil venting systems.
Blue Moon Approach to Rare Events

The "Blue Moon" ensemble is a computationally efficient molecular dynamics method to estimate the rate constants of rare activated events when the process can be described by a reaction coordinate ξ(r), a well-defined function in configuration space. By means of holonomic constraints a number of values of ξ(r) can be prescribed along the relevant path to identify the "bottleneck" region first and to sample an ensemble of starting conditions to generate activated trajectories. These MD trajectories sample phase space according to a biased configurational distribution. With a suitable re-weighting of averages from such ensemble of trajectories one can characterize completely rare events.
Data-driven geometric modelling methods for digital twinning: manufacturing, geospatial and medical applications

In recent years there has been an explosion of interest in digital twinning in many disciplines, including the manufacturing, geospatial, and medical domains. A core topic of importance in modelling digital twins, is reconstruction of geometric models from raw data. Despite the diversity of requirements in the vast space of digital twin applications, methods for geometric reconstruction can often be transferred between disciplines with only minor modiﬁcations. In this paper we present some recent results related to how advances in machine learning over the last decade can be used for data-driven geometric reconstruction in the medical, geospatial and manufacturing domains.
Integrating Design-Based Learning and Mentoring Strategies into a Professional Development Program for Distance Education Instructors

This study evaluates the effectiveness of the professional development program designed for distance education instructors, in which design-based learning and mentoring strategies are implemented consecutively. Eight university instructors from the same university in Turkey with one year of experience in online teaching participated in the study. The study first conducted a needs analysis, that revealed that the instructors were not accustomed to student-centered instructional methods, and they maintained direct instruction in their online courses. Moreover, the instructors’ technology integration understanding was inadequate, and they were generally concerned about the students’ low participation in online classes. Considering these findings, the professional development program was designed for the instructors who first joined a one-week design-based learning training and then attended mentorship for two weeks. The findings indicated that this approach was effective for the instructors’ professional development. The implications of this approach and suggestions for professional development programs were discussed based on the findings.
Data representation by field calculus and leading to the orthonormal linear transforms

Abstract. This paper proposes a method of data set representation by potential ﬁeld equations. The principal idea of therepresentation is to regard a numerical data set as a kind of potential/source ﬁelds, leading to the governing equations. Themodal analysis of the equations derives the orthonormal linear transform matrix. It is described that the matrix corresponds tothat of discrete wavelets performing an efﬁcient wavelet multi-resolution analysis. 1. IntroductionThe spread of high performance and reasonably priced computers has yielded a large scale Internetcommunity as well as information resources. Data handling technologies based on the digital computersare of main importance to realize more efﬁcient networking and computing. Discrete wavelet transform(WT) becomes a deterministic methodology to handle the digital signals and images, e.g., compressingdata quantity, extracting their characteristics, etc. [1]. Moreover, their applications to electromagneticﬁeld calculation, solving for forward and inverse problems, have been investigated and spurred to fastercalculationalgorithm[2,3]. TheconventionalWT,however,sometimessuffersfromlimitationonsubjectdata length which must be to the power of 2. Thereby, the applications depend on employed waveletbasis,andneedanenormousmemoryinstallation for implementation. The aim of this studyis to proposea new concept of representation to handle a numerical data set in most efﬁcient mannar. As a result, thewavelet-like linear transform matrices are derived from the modal analysis of potential ﬁeld equations.This paper proposes the modal-wavelet transform (MWT) as one of the WTs. The bases of MWT arederived from a modal analysis of the ﬁeld of equations. Regarding a numerical data set as a potentialﬁeld leads to a partial-differential-equation-based data modeling, i.e., the data set can be representedby Poisson’s equations. Then, the modal analysis of the discretized Poisson’s equation gives a modalmatrix constituting characteristic vectors. The modal matrix enables us orthogonal transformation in thesame way as WT. MWT uses this matrix as a wavelet basis. Because of the differential equation basedmodeling, MWT yields an optimal basis to the subject data length. We demonstrate two types of MWTbased on differential equation and Green-function. One dimentional Fourier analysis to each of columnvectors in the transformation matrix shows that MWT has the similar nature to Fourier transform nothaving complex numbers.
Interannual variability and decadal trend of global fractional vegetation cover from 1982 to 2000

Abstract Fractional vegetation cover (FVC) is one of the most important variables in land surface modeling and also provides a continuous field to complement discrete land cover classification. A global 8-km FVC dataset for 1982–2000 is derived using the NOAA–NASA land Pathfinder normalized difference vegetation index data. The confidence in the dataset is provided by the insensitivity of the algorithm to the data resolution (between 1 and 8 km), the good agreement of the results with the field survey data over Germany, the consistency of the results with previous observational studies over the savannas in North Africa and the forests in Bolivia, and the robustness of the algorithm, as demonstrated by the small interannual variability of FVC over areas where anthropogenic land cover change is expected to be small, based on the 30-m Landsat data analysis. Significant interannual variability is found over shrubland, savanna, and grassland; both positive and negative trends exist over different areas of the .
Unified treatment of one-range addition theorems for integer and non-integer n-STO, -GTO and -generalized exponential type orbitals with hyperbolic cosine in position, momentum and four-dimensional spaces

Simpler formulas are derived for one-range addition theorems for the integer and noninteger n generalized exponential type orbitals, momentum space orbitals, and hyperspherical harmonics with hyperbolic cosine (GETO HC, GMSO HC, and GHSH HC) in position, momentum and four-dimensional spaces, respectively. The final results are expressed in terms of one-range addition theorems of complete orthonormal sets of ψα-exponential type orbitals, φα-momentum space orbitals and zα-hyperspherical harmonics. We notice that the one-range addition theorems for integer and noninteger n-Slater type orbitals and Gaussian type orbitals in position, momentum and four dimensional spaces are special cases of GETO HC, GMSO HC, and GHSH HC. The theorems presented can be useful in the accurate study of the electronic structure of atomic and molecular systems.
Numerical study of the risk of thrombosis in the left atrial appendage of chicken wing shape in atrial fibrillation

Atrial fibrillation (AF) is a common and life-threatening disease. For the patients with AF, more than 90% of the thrombi are formed in the left atrial appendage (LAA), thrombus dislodgement can cause vascular embolism, making them is becoming a high-risk group for stroke. Therefore, identifying the patients with high risk of thrombosis is crucial for advanced stroke warning. To better investigate the mechanism behind thrombus formation in the LAA, this study reconstructed the 3-D Left Atrium (LA) models of six AF volunteer patients by corresponding Computed Tomography (CT) images. Combine the advantages of Computational Fluid Dynamics (CFD), the blood flow field in LA both in AF and sinus heart rate states were studied. The risk of thrombus was evaluated based on the blood viscosity, shear rate thrombus prediction model and Time Average Wall Shear Stress (TAWSS), Oscillatory Shear Index (OSI), and Relative Residence Time (RRT) values. The results showed that the left atrium had lower blood flow velocity and TAWSS values at the LAA in both AF and sinus rhythm, thus the LAA is the most thrombogenic region in the LA. Besides, the RRT value of LAA was generally higher in AF than in sinus rhythm. Therefore, AF carries a higher risk of thrombosis.
Influenza Vaccination Reduces the Risk of Liver Cancer in Patients with Chronic Kidney Disease: A Nationwide Population-Based Cohort Study

Previous studies have indicated that influenza vaccination reduces the development of lung cancer. However, the protective effects of influenza vaccination on primary liver cancer in patients with chronic kidney disease (CKD) are unclear. This cohort study identified 12,985 patients aged at least 55 years who had received a diagnosis of CKD between 1 January 2001 and 31 December 2012 from the National Health Insurance Research Database of Taiwan. The patients were classified according to vaccination status. Propensity score matching was used to reduce selection bias. Cox proportional hazards regression analysis was used to evaluate the correlation between influenza vaccination and primary liver cancer in patients with CKD. The prevalence of primary liver cancer was lower in patients with CKD who had received an influenza vaccine (adjusted hazard ratio: 0.45, 95% confidence interval [CI]: 0.35–0.58, p < 0.001). The protective effects were observed regardless of sex, age, and comorbidities. Moreover, dose-dependent protective effects were observed. In the subgroup analysis, where the patients were classified by the number of vaccinations received, the adjusted hazard ratios for 1, 2–3, and ≥4 vaccinations were 0.86 (95% CI: 0.63–1.17), 0.45 (95% CI: 0.31–0.63), and 0.21 (95% CI: 0.14–0.33), respectively. In conclusion, influenza vaccination was associated with a lower incidence of liver cancer in patients with CKD.