Miracle-dz/UniFAR-FTUs huggingface dataset:
Distance supervision as experienced by occupational therapists in mental health: An interpretative phenomenological study

Introduction: Distance methods of supervision rapidly increased in use during the coronavirus disease 2019 (COVID-19) pandemic, and it is important to consider if these methods meet the needs of supervisees when deciding whether to retain these practices moving forward. Methods: An interpretative phenomenological approach was used to gain insight into the lived experience of distance supervision. Semi-structured interviews were completed with six occupational therapists who had experience receiving distance supervision as a supervisee, all of whom work in inpatient mental health units within a private healthcare company. Results: Interpretative phenomenological analysis revealed four superordinate themes of an altered interaction; the importance of a protected space; factors within the supervisory relationship and maximising the best of both worlds. Conclusion: Distance supervision methods afford increased access for supervisees and a reduction in the practical demands when supervised by an off-site supervisor. There are, however, clear differences in the nature of the experience which need to be considered to ensure that supervisee needs are met. This study provides insight into how distance supervision methods impact on the experience for supervisees and suggests areas for further consideration in moving forward with such approaches.
Naïve Bayes untuk Prediksi Tingkat Pemahaman Kuliah Online Terhadap Mata Kuliah Algoritma Struktur Data

Banyak masalah yang terjadi dalam proses pembelajaran daring, salah satunya adalah kesulitan mahasiswa dalam memahami materi dengan baik. Berbagai upaya telah diklakukan dosen untuk mendukung pembelajaran secara daring, mulai dari penjelasan materi langsung melalui media conference maupun pembuatan video pembelajaran. Untuk mengetahui apakah siswa benar-benar memahami materi yang disampaikan dosen, maka diperlukan penelusuran dengan tujuan jika terdapat banyak mahasiswa yang belum menguasai materi maka perlu ada perubahan pada proses penyampaian materinya. Penelitian ini melakukan prediksi tingkat pemahaman dalam perkuliahan daring. Data yang digunakan pada penelitian ini adalah data nilai mata kuliah Algoritma Struktur Data. Data dengan variable tugas, praktikum, UTS, UAS dan jumlah kehadiran perkuliahan diperoleh dari nilai mahasiswa program studi D3 Manajemen Informatika angkatan 2020 dan 2019. Metode yang digunakan pada penelitian ini adalah Naïve Bayes dengan hasil prediksi pada angkatan 2019 sebesar 46.15% dengan akurasi confusion matrix 69.23% dan hasil prediksi angkatan 2020 sebesar 54.54% dengan akurasi confusion matrix 72.73%, sehingga dapat disimpulkan bahwa perkuliahan online tingkat pemahamanya meningkat dari perkuliahan offline.
A Taxonomic Survey of Physics-Informed Machine Learning

Physics-informed machine learning (PIML) refers to the emerging area of extracting physically relevant solutions to complex multiscale modeling problems lacking sufficient quantity and veracity of data with learning models informed by physically relevant prior information. This work discusses the recent critical advancements in the PIML domain. Novel methods and applications of domain decomposition in physics-informed neural networks (PINNs) in particular are highlighted. Additionally, we explore recent works toward utilizing neural operator learning to intuit relationships in physics systems traditionally modeled by sets of complex governing equations and solved with expensive differentiation techniques. Finally, expansive applications of traditional physics-informed machine learning and potential limitations are discussed. In addition to summarizing recent work, we propose a novel taxonomic structure to catalog physics-informed machine learning based on how the physics-information is derived and injected into the machine learning process. The taxonomy assumes the explicit objectives of facilitating interdisciplinary collaboration in methodology, thereby promoting a wider characterization of what types of physics problems are served by the physics-informed learning machines and assisting in identifying suitable targets for future work. To summarize, the major twofold goal of this work is to summarize recent advancements and introduce a taxonomic catalog for applications of physics-informed machine learning.
The hadron calorimeter design and construction

The design of the LHCb Hadron Calorimeter is being described in this note. An internal structure consisting of thin iron plates interspaced with scintillating tiles have been chosen. The HCAL consists of two symmetric movable parts getting in touch in operation position without non-instrumented zones. The lat-eral dimensions of the HCAL active area is of X =8.4 m in width, Y =6.8 m in height, and is distanced from the interaction point at Z =13.33 m. Both halfs are assembled from stacked up modules. Each half of about 245 tonn is located on the separate platform. Attention is paid to the strength analysis of the module as a basic assembling unit. Di(cid:11)erent phases are being discussed: the iron plates glueing, the submodule and module construction, the scintillating tiles and (cid:12)bers preparation for insertion, the pre-installation test and calibration. The documentation incorporates a set of tools needed for detector assembly. In the summary the construction rate is estimated.
Spline collocation on adaptive grids and non-rectangular domains

Optimal spline collocation is a computationally cost effective finite element method that has been relatively recently developed. Although there are many important results for optimal spline collocation, we believe the method can further be extended to solve a series of more relevant and difficult problems. We first consider using optimal spline collocation on non-uniform partitions to solve one-dimensional linear second-order Boundary Value Problems (BVPs) that have solutions with regions of high variations, such as boundary layers. Optimal quadratic spline collocation (QSC) is extended to non-uniform partitions by using a mapping function from uniform to non-uniform partitions. Optimal cubic spline collocation (CSC) on non-uniform partitions is also examined. The formulation and analysis of the CSC methods are based, as in the QSC case, on a mapping function from uniform to non-uniform partitions. However, this method is converted into a mapping-free method and is integrated with adaptive techniques that include error and grid size estimators. Spline collocation is then considered for solving two-dimensional linear second-order BVPs. We extend optimal spline collocation to solving BVPs on L- and T-shaped domains, which occur often in practice. The CSC method can handle general boundary conditions, which had previously never been done, but our approach requires a third step to achieve optimal convergence. We also consider two adaptive approaches for solving problems on rectangular domains whose solutions have rapid variations. As in the one-dimensional case, such problems present a significant challenge to obtain accurate approximations at minimal computational cost. We first implement a static method, which involves adding collocation points to regions where the solution has sharp variations, with CSC that uses skipped grids, which are grids that have several levels of refinement, in certain regions of the domain. An optimal skipped grid method is developed by converting the second-order BVP into a system of three first-order BVPs. We then implement a dynamic method, which involves moving the collocation points to regions where the solution has sharp variations, with CSC that incorporates the Moving Mesh Partial Differential Equation (MMPDE). The MMPDE method is further integrated into an adaptive method that can solve BVPs within a specific error tolerance.
Turbulence Modeling for Heat Transfer to Supercritical Pipe Flows

In the present work, a comprehensive review on different mechanisms affecting heat transfer characteristics of supercritical flows is carried out. The physical mechanism of heat transfer is then further investigated using inhouse DNS data. In addition, RANS simulations of a heated vertical pipe with supercritical CO2 are carried out using conventional low-Reynolds number eddy viscosity turbulence models. The turbulence models are implemented in an inhouse FORTRAN code and validated using canonical cases available in the literature. The performance of the turbulence models is assessed by comparison with the inhouse DNS data. Furthermore, a theoretical framework has been established to take into account the large thermophysical property variations close to pseudo-critical point in the RANS averaged governing equations.
Profiling of miRNAs and their interfering targets in peripheral blood mononuclear cells from patients with chronic myeloid leukaemia

Introduction MicroRNAs may be implicated in the acquisition of drug resistance in chronic myeloid leukemia as they regulate the expression of not only BCR-ABL1 but also genes associated with the activation of drug transfer proteins or essential signaling pathways. Methods To understand the impact of specifically expressed miRNAs in chronic myeloid leukemia and their target genes, we collected peripheral blood mononuclear cells (PBMC) from patients diagnosed with chronic myeloid leukemia (CML) and healthy donors to determine whole miRNA expression by small RNA sequencing and screened out 31 differentially expressed microRNAs (DE-miRNAs) with high expression. With the utilization of miRNA set enrichment analysis tools, we present here a comprehensive analysis of the relevance of DE-miRNAs to disease and biological function. Furthermore, the literature-based miRNA-target gene database was used to analyze the overall target genes of the DE-miRNAs and to define their associated biological responses. We further integrated DE-miRNA target genes to identify CML miRNA targeted gene signature singscore (CMTGSS) and used gene-set enrichment analysis (GSEA) to analyze the correlation between CMTGSS and Hallmark gene-sets in PBMC samples from clinical CML patients. Finally, the association of CMTGSS stratification with multiple CML cell lineage gene sets was validated in PBMC samples from CML patients using GSEA. Results Although individual miRNAs have been reported to have varying degrees of impact on CML, overall, our results show that abnormally upregulated miRNAs are associated with apoptosis and aberrantly downregulated miRNAs are associated with cell cycle. The clinical database shows that our defined DE-miRNAs are associated with the prognosis of CML patients. CMTGSS-based stratification analysis presented a tendency for miRNAs to affect cell differentiation in the blood microenvironment. Conclusion Collectively, this study defined differentially expressed miRNAs by miRNA sequencing from clinical samples and comprehensively analyzed the biological functions of the differential miRNAs in association with the target genes. The analysis of the enrichment of specific myeloid differentiated cells and immune cells also suggests the magnitude and potential targets of differentially expressed miRNAs in the clinical setting. It helps us to make links between the different results obtained from the multi-faceted studies to provide more potential research directions.
Scalable Game-Theoretic Decision-Making for Self-Driving Cars at Unsignalized Intersections

Sharing the road with human drivers requires autonomous vehicles to account for interactions between them. To resolve traffic conflicts in unsignalized intersections, a robust adaptive game-theoretic decision-making algorithm with scalability is proposed based on the receding horizon optimization, level-k game theory, and switching directed graph. A mismatch between the inherent (k-1) assumption of level-k theory and actual driver type may lead to unsafe action selection and reduce driving safety. To handle this problem, in this work, an autonomous vehicle would predict the driver types of surrounding vehicles based on historical interactive behaviors between them and utilize its trust in the driver types to achieve an adaptive driving strategy. Besides, switching interaction graph is incorporated into an adaptive level-k framework for the first time, so as to cutoff the connection between ego vehicle and nearby vehicles that do not affect driving behavior of the former, contributing to reducing the computing complexity. The feasibility, effectiveness, and real-time implementation of the proposed method are validated on both hardware and ROS-Gazebo platform.
Wavelet tight frame and prior image-based image reconstruction from limited-angle projection data

The limited-angle projection data of an object, in some practical applications of computed tomography (CT), are obtained due to the restriction of scanning condition. In these situations, since the projection data are incomplete, some limited-angle artifacts will be presented near the edges of reconstructed image using some classical reconstruction algorithms, such as filtered backprojection (FBP). The reconstructed image can be fine approximated by sparse coefficients under a proper wavelet tight frame, and the quality of reconstructed image can be improved by an available prior image. To deal with limited-angle CT reconstruction problem, we propose a minimization model that is based on wavelet tight frame and a prior image, and perform this minimization problem efficiently by iteratively minimizing separately. Moreover, we show that each bounded sequence, which is generated by our method, converges to a critical or a stationary point. The experimental results indicate that our algorithm can efficiently suppress artifacts and noise and preserve the edges of reconstructed image, what's more, the introduced prior image will not miss the important information that is not included in the prior image.
Optimum structures for gamma‐ray radiation resistant SiC‐MOSFETs

In order to develop highly radiation‐tolerant SiC MOSFETs, we investigated the dependence of the gamma‐ray radiation response on the gate oxide thickness and nitridation processes, used for oxide growth and p‐well implantation. SiC MOSFETs with a thick gate oxide (60 nm) showed a rapid decrease in the threshold voltage shift ΔVth of more than 400 kGy, and transitioned to the normally‐on state at lower doses than those with a thin gate oxide (35 nm). The MOSFETs with gate oxides treated with lower concentrations of N2O (10%) demonstrated a higher radiation tolerance (ΔVth, channel mobility, and subthreshold swing) than with a 100% N2O treatment. The MOSFETs with more p‐well implantation steps (three steps) showed a smaller negative shift of the threshold voltage relative to those implanted with two steps.
A three dimensional point cloud registration method based on rotation matrix eigenvalue

We usually need to measure an object at multiple angles in the traditional optical three-dimensional measurement method, due to the reasons for the block, and then use point cloud registration methods to obtain a complete threedimensional shape of the object. The point cloud registration based on a turntable is essential to calculate the coordinate transformation matrix between the camera coordinate system and the turntable coordinate system. We usually calculate the transformation matrix by fitting the rotation center and the rotation axis normal of the turntable in the traditional method, which is limited by measuring the field of view. The range of exact feature points used for fitting the rotation center and the rotation axis normal is approximately distributed within an arc less than 120 degrees, resulting in a low fit accuracy. In this paper, we proposes a better method, based on the invariant eigenvalue principle of rotation matrix in the turntable coordinate system and the coordinate transformation matrix of the corresponding coordinate points. First of all, we control the rotation angle of the calibration plate with the turntable to calibrate the coordinate transformation matrix of the corresponding coordinate points by using the least squares method. And then we use the feature decomposition to calculate the coordinate transformation matrix of the camera coordinate system and the turntable coordinate system. Compared with the traditional previous method, it has a higher accuracy, better robustness and it is not affected by the camera field of view. In this method, the coincidence error of the corresponding points on the calibration plate after registration is less than 0.1mm.
The US State-Level Wood Product-Based Bilateral Trade Balances with Canada Under the Protectionist US Trade Policy, COVID-19, and Economic Policy Uncertainty

ABSTRACT The US-Canada wood product trade is a longstanding dispute due to protectionist high-tariff policies, further exacerbated by COVID-19 restrictions on US production and exports. This study investigates the J-curve effect at the US state level, revealing that only 11 US states support the asymmetric J-curve for wood products, whereas 10 US states support the asymmetric inverse J-curve (shown in Appendix 2 online). Furthermore, high tariffs imposed by the US improved trade balances for only three states, implying that the high-tariff policy did not enhance the US wood-based trade balance with Canada.
Challenging students through mathematics: a culturally relevant problem solving

According to the Human Science Research Council of South Africa’s (2002) analysis of the Third International Mathematics and Science Study-Repeat, reveals that low achievement was related to: (1) low socioeconomic status, (2) fairly low parental educational level, and (3) lack of fluency in the language of testing. This last factor implies difficulty in communication. Only about a quarter (26%) of the participants had the language of the test as their first language and these scored better in mathematics and science. The current study investigated the effect and role that culturally relevant problem solving in the language of their choice may have on learning mathematics. It explored students’ thinking and recorded any emerging mathematics concepts during culturally relevant mathematics problem solving while using any language of their choice. The investigation started with six South African grade 10 students. One participant withdrew from the study while two volunteered, thus ending with seven participants. They were selected from two schools whose only common denominator was that they are from previously disadvantaged communities and use English as the medium of instruction. Data were collected from whole class observations, participants’ journals, transcripts of audio taped interviews, and participants’ written work. The majority of the seven participants, preferred to communicate their mathematics thoughts in a mixture of English and their first language. It also emerged from the data that they solved problems ii they could not solve before using own strategies. These strategies differed from person to person. The data also revealed that culture had an influence on the type of strategy to be used and the solution of the problem.
On Tree Pattern Matching by Pushdown Automata

Tree pattern matching is an important operation in Computer Science on which a number of tasks such as mechanical theorem proving, term-rewriting, symbolic computation and non-procedural programming languages are based on. Work has begun on a systematic approach to the construction of tree pattern matchers by deterministic pushdown automata which read subject trees in prefix notation. The method is analogous to the construction of string pattern matchers: for given patterns, a non-deterministic pushdown automaton is created and then it is determinised. In this first paper, we present the proposed non-deterministic pushdown automaton which will serve as a basis for the determinisation process, and prove its correctness.
The Effect of Concept Mapping on Community College Precalculus Students' Conceptual Understanding of Inverse Functions

MERRITT, RONALD L. , JR. The Effect of Concept Mapping on Community College Precalculus Students’ Conceptual Understanding of Inverse Functions. (Under the direction of William M. Waters, Jr.) The purpose of this study was to investigate the efficacy of concept mapping on community college precalculus students’ conceptual understanding of inverse functions. This study employed a quasi-experimental nonequivalent control group design in which a single instructor taught one experimental precalculus algebra class and one control precalculus algebra class. Students in the experimental group (n = 15) participated in one collaborative “System of Equations” concept mapping exercise. These students also individually constructed maps given the seed concepts “Inverse” and “Functional Inverse. ” Other than the concept mapping treatment, all assignments, assessments and instruction were equivalent for the experimental and control groups (n = 21). The duration of the experiment was about 12 weeks. Three veteran mathematics community college instructors and two professors of mathematics education from a local university collaborated to create criterion maps for this study. The Markham, Mintzes and Jones’ rubric for scoring science-oriented concept maps and these criterion maps were used to quantify students’ individual maps. Quantification of the maps relied on seven components: concept, link, hierarchy, initial branching, successive branching, crosslink, and example. Other data collected for analysis in this experiment includes pretest diagnostic scores, unit test scores and selected subscores, a routine writing assignment score, final examination subscore, and a variety of demographic data. ANOVA and a Backward Elimination model ( 05 . = α ) revealed that the inverse function map score is significant and contributes to significant variation in the final course grade. However, distribution-free and independent non-equivalent t-tests disclose very few significant differences between the two groups for the duration of the course. Qualitative analyses of the (1) mathematics instructors and professors surveys on concept mapping usefulness, (2) system of equations and inverse function maps, and (3) the follow-up survey provided further evidence that concept mapping supports the NCTM and AMATYC Standards. THE EFFECT OF CONCEPT MAPPING ON COMMUNITY COLLEGE PRECALCULUS STUDENTS’ CONCEPTUAL UNDERSTANDING OF INVERSE FUNCTIONS