Miracle-dz/UniFAR-FTUs huggingface dataset:
Interferograms analysis for measuring the thickness of aluminum thin films

In this work, a specific procedure to measure the thickness of aluminum thin films by interferogram analysis is described. Six interferograms correspond to the image of the aluminum thin film superimposed with interference fringes are obtained from a Michelson-type interferential microscope. A six-frame phase shift algorithm is used to demodulate the optical phase. The measured phase is proportional to the height variation between the thin film wafer and the substrate. Finally, the obtained 3D height map permits us measure the thickness of the sample over an area of 1024 μm × 1280 μm.
Operational Loss Scaling by Exposure Indicators: Evidence from the ORX Database

We investigate whether the size of operational risk losses can be correlated with geographical region and flrm size. We extend past studies of losses on flrm size by applying quantile regression techniques to obtain a more complete view of scaling relationships across the loss distribution. Furthermore, we test whether these distributional scaling relations can be described using simple location-shift or location-scale shift models. In addition, we develop a novel \quantile matching" algorithm to address statistical issues that arise when estimating loss scaling models when the data are subjected to a loss reporting threshold.
A decadal climate service for insurance: Skilful multi-year predictions of North Atlantic hurricane activity and US hurricane damage

North Atlantic hurricane activity exhibits significant variation on multi-annual timescales. Advance knowledge of periods of high activity would be beneficial to the insurance industry, as well as society in general. Previous studies have shown that climate models initialized with current oceanic and atmospheric conditions, known as decadal prediction systems, are skilful at predicting North Atlantic hurricane activity averaged over periods of 2-10 years. We show that this skill also translates into skilful predictions of real-world US hurricane damages. Using such systems, we have developed a prototype climate service for the insurance industry giving probabilistic forecasts of 5-year-mean North Atlantic hurricane activity, measured by the total accumulated cyclone energy (ACE index), and 5-year-total US hurricane damages (given in US dollars). Rather than tracking hurricanes in the decadal systems directly, the forecasts use a relative temperature index known to be strongly linked to hurricane activity. Statistical relationships based on past forecasts of the index and observed hurricane activity and US damages are then used to produce probabilistic forecasts. The predictions of hurricane activity and US damages for the coming period 2020-2024 are high, with ~95% probabilities of being above average. We note that skill in predicting the temperature index on which the forecasts are based has declined in recent years. More research is therefore needed to understand under which conditions the forecasts are most skilful.
Fisher-Cochrans Theorem (with application to Analysis of a One Factor Experiment)

Tests in ANOVA tables are often constructed using F-tests. The theory for the tests is usually justified by Cochran's theorem. We give the usual version of this theorem with sums of squares terminology (from Kirk (1995), p226). We follow this description with Fisher-Cochran's Theorem as given by (Rao (1971), p185) that makes use of quadratic forms. Finally, we relate these results to a One Factor experiment with equal numbers of units, 1,. , i n = randomly assigned to each level (or treatment), 1,. , j p = of the factor.
COVID-19 prevention intentions of pre-science science teachers from South African and Indonesian universities

Science teachers could play a vital role in promoting health literacy and safe behaviors to limit the spread of communicable diseases. However, there is limited research concerning their attitudes and behavioral intentions toward diseases, such as COVID-19. Using the theory of planned behavior as a framework, we employed a non-experimental survey to compare the behavioral intentions towards adopting COVID-19 preventative measures among pre-service science teachers from South African (n=87) and Indonesian (n=93) universities. Data were collect data using a closed-ended questionnaire. Results show that the behavioral intentions toward COVID-19 between South African and Indonesian pre-service science teachers are similar. Safe attitudes, subjective norms, perceived behavioral control, behavioral, and normative beliefs that support safe behavioral intentions toward COVID-19 were reported, even though vaccine hesitancy may occur. We extrapolate that interventions should be implemented to enhance pre-service teachers’ behavioral intentions and enhance their role in health education.
Hidden order in hexagonalRMnO3multiferroics (R=Dy–Lu, In, Y, and Sc)

Hexagonal RMnO3 manganites are improper ferroelectrics in which the electric polarization is a by-product of the tripling of the unit cell. In YMnO3, there is a second transition at ~ 920K whose nature remains unexplained. We argue that this transition can be seen as a sort of hidden order in which a residual symmetry displayed by the trimerization order parameter is spontaneously broken. This additional order gives rise to twelve structural domains instead of six, and structural domain boundaries that can be either ferroelectric or non-ferroelectric domain walls.
Tonality and transformation

Steven Rings has made an important contribution to the ongoing studies in transformation theory. A number of volumes have appeared within the recent past, including [1–4]. Rings is a penetrating musical analyst with an impressive command of the fields of cognition, philosophy, and formal systems. Tonality and Transformation grew out of an interest in neo-Riemannian theory but has transcended its initial inspiration. Rings wants to address what he believes to be a common misperception, namely that transformation theory is inapplicable to works of common practice tonality. Although the number of tonal works that have already been investigated through a transformational lens is prodigious, Rings focuses his analytical lights on others in this volume to good effect. Meanwhile, by analysing two complete movements and two tonally complete excerpts at the end of the volume, he dispels the common misconception that the focus of transformation theory is necessarily narrow. At least one notion about transformational theory is reinforced: the presumption that transformational theory is most effective in treating tonally ambiguous works. Rings’s analyses of such works are particularly insightful. This even applies to his analysis of the E Major Fugue from WTC I, which deliberately recalls an older style of analysis, one sensitive to moment-to-moment shifts of tonal allegiance. The phrase ‘tonality and transformation’may be understood simply to indicate transformational readings of works of tonal music, or, more ambitiously, as a transformational model of tonal hearing. Although there are serious attempts to provide transformational models for tonality, it seems that theory building is not the primary aim here. What Tonality and Transformation does offer is an abundance of analytical tools. The real value of this study, ultimately, is in the clarity and insight of Rings’s analyses. For example, Rings provides a compelling and original reading of the Grail motive of Parsifal, comparing the ‘Dresden Amen’ form in Act I with a greatly transfigured version in Act III. The latter instance has been the subject of much discussion.1 As shown here as Figure 1, Rings’s Figure 2.34 presents a tonal analysis of the original version and a neo-Riemannian analysis of the later version (ending with a parenthesized tonal reading of the cadence in D ). By design, neoRiemannian readings suppress tonal implications. Rings argues that the effects of tonal gravitation in this passage, although attenuated, are still noticeable and deserve attention. He tracks the active tonal forces in the Act III version in his Figure 2.35 (p. 85). The analysis is based on a 12 × 7 structure whose rows represent pitch classes, and whose columns represent diatonic scale degrees. However, the central analytical insight may be expressed with far more primitive technology (Figure 2). Rings is telling us that Wagner transposes the music that appears over the harmonic
Query expansion using novel use case scenario relationship for finding feature location

Feature location is a technique for determining source code that implements specific features in software. It developed to help minimize effort on program comprehension. The main challenge of feature location research is how to bridge the gap between abstract keywords in use cases and detail in source code. The use case scenarios are software requirements artifacts that state the input, logic, rules, actor, and output of a function in the software. The sentence on use case scenario is sometimes described another sentence in other use case scenario. This study contributes to creating expansion queries in feature locations by finding the relationship between use case scenarios. The relationships include inner association, outer association and intratoken association. The research employs latent Dirichlet allocation (LDA) to create model topics on source code. Query expansion using inner, outer and intratoken was tested for finding feature locations on a Java-based open-source project. The best precision rate was 50%. The best recall was 100%, which was found in several use case scenarios implemented in a few files. The best average precision rate was 16.7%, which was found in inner association experiments. The best average recall rate was 68.3%, which was found in all compound association experiments.
Roof Reconstruction of Aerial Point Cloud Based on BPPM Plane Segmentation and Energy Optimization

In this article, a novel reconstruction method for aerial LiDAR point cloud building models is proposed to obtain valid roof building models. There are two problems in the reconstruction. First, in the process of primitive segmentation, due to the uneven density of the point cloud, there is the problem of over- or undersegmentation of the plane, resulting in the inability to extract concise and suitable building planes, which, in turn, affects the reconstruction topology. Second, in the model construction process, due to the variety and complexity of building structures, obtaining regular, compact, and topologically correct surface models from sparse and noisy point clouds is still a challenge. To address the first problem, first, the initial primitives are obtained using an improved multiresolution supervoxel-based region growing segmentation algorithm. Then, a new progressive primitive fusion algorithm Belief Propagation Primitive Merge is proposed to optimize the fragmented primitives. For the second problem, first, the Corner KLine regularization algorithm is proposed to obtain the building footprints. Then, the height map is constructed from the point cloud to extract the polyline of the building boundaries and deduce the vertical planes. Finally, a new energy function is proposed to encourage the selection of the recommended combination of model planes to obtain a compact and valid roof reconstruction model. Experiments are performed on different roof point clouds to quantitatively evaluate the proposed method, and qualitative experiments are conducted with comparative experiments to confirm the effectiveness of the algorithm.
Analysis and Control of Cascaded Energy Storage System for Energy Efficiency and Power Quality Improvement in Electrified Railways

Energy-efficient and grid-friendly railway power system (RPS) is critical for the sustainable development of electrified railways. In this article, a cascaded energy storage system (CESS) is investigated for energy efficiency and power quality improvement of the RPS. First, the detailed operation principles of the CESS for multiple control objectives, including regenerative braking energy (RBE) utilization, reactive power compensation, and negative sequence current (NSC) suppression, are analyzed. On this basis, a hierarchical power flow control strategy is developed for achieving the power flow management and control of multiple objectives for CESS. Specifically, a multiobjective power flow management strategy is designed in the system layer to allocate the power references for the CESS under sufficient and insufficient capacity scenarios (ICS). In the sufficient capacity scenario (SCS), the power references are directly obtained by the operation principles. In the ICS, the power references are allocated through a three-stage optimization method considering the power shaving rate, grid power factor, and grid imbalance degree. Subsequently, the power references from the system layer are tracked in the converter layer to achieve power flow control. Finally, the effectiveness of the proposed hierarchical power flow control strategy is verified through experimental results. The results show that the proposed CESS can achieve superior performance on RBE utilization and power quality improvement under complex operating conditions in electrified railways.
An Agent-Based Model for Public Security Strategies by Predicting Crime Patterns

In recent years, statistical methods have been applied to the study of crime patterns. However, these schemes have several drawbacks that prevent accurate modeling of complex behaviors. Agent-based models (ABM) allow the modeling of human behavior by employing simple rules that consider each agent’s neighborhood. In this paper, a new agent-based model is proposed to emulate crime patterns produced by the interaction of different urban actors, such as offenders (criminals), citizens, and defenders (police officers). Using this approach, the simulation results provide escape trajectories and robbery frequencies that can be used to create or improve public security strategies. Although our scheme can be generically applied, we validated the model by considering different scenarios for the case of Guadalajara, Mexico. Experimental results show that the proposed scheme creates realistic offender behaviors that efficiently predict criminal patterns and provides essential data that allow the creation and improvement of public security strategies to reduce the number of crimes.
Trajectories of Spirometric Patterns, Obstructive and PRISm, in a Population-Based Cohort in Latin America

Background Preserved ratio impaired spirometry (PRISm) has been associated with adverse outcomes and increased transition to other spirometric categories over time. We aimed to examine its prevalence, trajectories over time, and outcomes in a population-based sample from Latin America. Methods Data were obtained from two population-based surveys of adults from three cities in Latin America (PLATINO study), conducted on the same individuals 5–9 years after their baseline examination. We estimated the frequency of PRISm defined by FEV1/FVC≥0.70 with FEV1 <80%, describing their clinical characteristics, longitudinal transition trajectories over time, factors associated with the transition. Results At baseline, 2942 participants completed post-bronchodilator spirometry, and 2026 at both evaluations. The prevalence of normal spirometry was 78%, GOLD-stage 1 10.6%, GOLD 2–4 6.5%, and PRISm was: 5.0% (95% CI 4.2–5.8). PRISm was associated with less schooling, more reports of physician-diagnosis of COPD, wheezing, dyspnea, missing days at work, having ≥2 exacerbations in the previous year but without accelerated lung function decline. Mortality risk was significantly higher in PRISm (HR 1.97, 95% CI 1.2–3.3) and COPD GOLD 1–4 categories (HR 1.79, 95% CI 1.3–2.4) compared with normal spirometry. PRISm at baseline most frequently transitioned to another category at follow-up (46.5%); 26.7% to normal spirometry and 19.8% to COPD. The best predictors of transition to COPD were closeness of FEV1/FVC to 0.70, older age, current smoking, and a longer FET in the second assessment. Conclusion PRISm, is a heterogeneous and unstable condition prone to adverse outcomes that require adequate follow-up.
Gate‐Defined Josephson Weak‐Links in Monolayer WTe2

Systems combining superconductors with topological insulators offer a platform for the study of Majorana bound states and a possible route to realize fault tolerant topological quantum computation. Among the systems being considered in this field, monolayers of tungsten ditelluride (WTe2) have a rare combination of properties. Notably, it has been demonstrated to be a quantum spin Hall insulator (QSHI) and can easily be gated into a superconducting state. Measurements on gate‐defined Josephson weak‐link devices fabricated using monolayer WTe2 are reported. It is found that consideration of the 2D superconducting leads are critical in the interpretation of magnetic interference in the resulting junctions. The reported fabrication procedures suggest a facile way to produce further devices from this technically challenging material and the results mark the first step toward realizing versatile all‐in‐one topological Josephson weak‐links using monolayer WTe2.
Widespread intra‐axonal signal fraction abnormalities in bipolar disorder from multicompartment diffusion MRI: Sensitivity to diagnosis, association with clinical features and pharmacologic treatment

Despite diffusion tensor imaging (DTI) evidence for widespread fractional anisotropy (FA) reductions in the brain white matter of patients with bipolar disorder, questions remain regarding the specificity and sensitivity of FA abnormalities as opposed to other diffusion metrics in the disorder. We conducted a whole‐brain voxel‐based multicompartment diffusion MRI study on 316 participants (i.e., 158 patients and 158 matched healthy controls) employing four diffusion metrics: the mean diffusivity (MD) and FA estimated from DTI, and the intra‐axonal signal fraction (IASF) and microscopic axonal parallel diffusivity (Dpar) derived from the spherical mean technique. Our findings provide novel evidence about widespread abnormalities in other diffusion metrics in BD. An extensive overlap between the FA and IASF results suggests that the lower FA in patients may be caused by a reduced intra‐axonal volume fraction or a higher macromolecular content in the intra‐axonal water. We also found a diffuse alteration in MD involving white and grey matter tissue and more localised changes in Dpar. A Machine Learning analysis revealed that FA, followed by IASF, were the most helpful metric for the automatic diagnosis of BD patients, reaching an accuracy of 72%. Number of mood episodes, age of onset/duration of illness, psychotic symptoms, and current treatment with lithium, antipsychotics, antidepressants, and antiepileptics were all significantly associated with microstructure abnormalities. Lithium treatment was associated with less microstructure abnormality.
Incidence and Factors Associated with Uncontrolled Hypertension at 12 months after Kidney Transplantation in Saudi Arabia

Introduction: Uncontrolled blood pressure (uBP) after kidney transplantation (KTx) is very common and is associated with significant morbidity. However, studies that assess its incidence and risk factors are limited and outdated in the Middle East. Methods: This is a single-center retrospective study of KTx recipients (KTRs) in our center between January 2017 and May 2020 with a 12-month follow-up period. The target of hypertension treatment during the time of this study was <140/90 mm Hg, according to the published guidelines. We divided patients according to their blood pressure (BP) control at 1 year into two groups: controlled BP (cBP) (<140/90) and uBP (≥140/90). We studied the association between uBP and patients’ demographics, baseline cardiovascular risk factors, and changes in their metabolic and cardiovascular profile during the first 12 months post-KTx. Results: A total of 254 KTRs were included. 79.2% developed post-KTx hypertension, 74% were ≥30 years, 58% were men, and 80% were living donor KTRs. The renal replacement modality among our patients pre-KTx was hemodialysis in 78.4%, peritoneal dialysis in 11.5%, and 10.1% underwent preemptive transplantation. At 1 year, 76 (29.9%) KTRs did not attain the target BP goal. Systolic BP (SBP) decreased from baseline to 12 months by 13 ± 24 mm Hg in the cBP group and increased by 8.7 ± 21 mm Hg in the uBP group (p < 0.001). Additionally, diastolic BP (DBP) decreased by 8.5 ± 16.9 mm Hg in the cBP group and increased by 2.3 ± 18.8 mm Hg in the uBP group (p < 0.001). Factors associated with uBP included age (47 vs. 41 years, p = 0.008) and diabetes mellitus (p = 0.012). Contrarily, gender, dialysis vintage, preemptive transplantation, type of dialysis (hemodialysis vs. peritoneal dialysis), type of transplant (living donor KTx vs. deceased donor KTx), and smoking were not different among the two groups. There were no significant differences between the two groups in regard to changes in creatinine, weight, A1c, low-density lipoprotein, and parathyroid hormone levels. Additionally, rate of rejection, new onset diabetes post-transplant, and persistent hyperthyroidism were not different between the groups. However, higher body mass index at 12 months was associated with a higher incidence of uBP (27.2 ± 5.9 vs. 29.2 ± 5.4, p = 0.013). Using multivariate analysis, we found that serum creatinine at 12 months was the only predictor of uBP (OR = 1.005 [1–1.011], p = 0.036). Conclusion: At 1-year post-renal transplantation, about one-third of KTRs had uBP despite multiple antihypertensive medications. SBP and DBP significantly trended upward after transplantation in uBP patients, whereas SBP and DBP significantly trended downward after transplantation in cBP patients. Serum creatinine at 12 months was the only factor independently associated with uBP.
Induction of ordinal decision trees

In many disciplines, such as social and behavioral sciences, we often have to do ordinal classification by assigning objects to ordinal classes. The fundamental objective of ordinal classification is to create an ordering in the universe of discourse. As such, a decision tree for ordinal classification should aim at producing an ordering which is most consistent with the implicit ordering in the input data. Ordinal classification problems are often dealt with by treating ordinal classes as nominal classes, or by representing the classes as values on a quantitative scale. Such approaches may not lead to the most desirable results since the methods do not fit the type of data, viz. ordinal data, concerned. In this paper, we propose a new measure for assessing the quality of output from an ordinal classification approach. We also propose an induction method to generate an ordinal decision tree for ordinal classification based on this quality perspective. We demonstrate the advantage of our method using results from a set of experiments.