Miracle-dz/UniFAR-FTUs huggingface dataset:
On Some One-Parameter Families Where Maximal Invariants Do Not Distinguish Hypothesized Models

Abstract In one-parameter (θ) families, we were not aware of explicit hypothesis testing scenarios where maximal invariant statistics failed to distinguish the models. We start with a concrete example (Sec. 2.2) to highlight such a hypothesis testing problem involving markedly different models. In this problem, because of the absence of a nontrivial uniformly most powerful invariant (UMPI) test, we briefly suggest two approaches to test the hypothesis. The first resolution (Sec. 3.1) is frequentist in nature. It utilizes a weight function on the parameter space and compares “average” distributions obtained under the null and alternative models in the sense of Wald (1947 1950). In contrast, a fully Bayesian resolution (Sec. 3.2) is also included. The note ends with a series of other interesting examples involving one-parameter families where maximal invariant statistics fail to distinguish the hypothesized models. The examples include easy-to-construct families of probability models involving only a single location or scale parameter θ.
Radiomics-Based Machine Learning Model for Predicting Overall and Progression-Free Survival in Rare Cancer: A Case Study for Primary CNS Lymphoma Patients

Primary Central Nervous System Lymphoma (PCNSL) is an aggressive neoplasm with a poor prognosis. Although therapeutic progresses have significantly improved Overall Survival (OS), a number of patients do not respond to HD–MTX-based chemotherapy (15–25%) or experience relapse (25–50%) after an initial response. The reasons underlying this poor response to therapy are unknown. Thus, there is an urgent need to develop improved predictive models for PCNSL. In this study, we investigated whether radiomics features can improve outcome prediction in patients with PCNSL. A total of 80 patients diagnosed with PCNSL were enrolled. A patient sub-group, with complete Magnetic Resonance Imaging (MRI) series, were selected for the stratification analysis. Following radiomics feature extraction and selection, different Machine Learning (ML) models were tested for OS and Progression-free Survival (PFS) prediction. To assess the stability of the selected features, images from 23 patients scanned at three different time points were used to compute the Interclass Correlation Coefficient (ICC) and to evaluate the reproducibility of each feature for both original and normalized images. Features extracted from Z-score normalized images were significantly more stable than those extracted from non-normalized images with an improvement of about 38% on average (p-value < 10−12). The area under the ROC curve (AUC) showed that radiomics-based prediction overcame prediction based on current clinical prognostic factors with an improvement of 23% for OS and 50% for PFS, respectively. These results indicate that radiomics features extracted from normalized MR images can improve prognosis stratification of PCNSL patients and pave the way for further study on its potential role to drive treatment choice.
Data-Driven Robotic Manipulation of Cloth-like Deformable Objects: The Present, Challenges and Future Prospects

Manipulating cloth-like deformable objects (CDOs) is a long-standing problem in the robotics community. CDOs are flexible (non-rigid) objects that do not show a detectable level of compression strength while two points on the article are pushed towards each other and include objects such as ropes (1D), fabrics (2D) and bags (3D). In general, CDOs’ many degrees of freedom (DoF) introduce severe self-occlusion and complex state–action dynamics as significant obstacles to perception and manipulation systems. These challenges exacerbate existing issues of modern robotic control methods such as imitation learning (IL) and reinforcement learning (RL). This review focuses on the application details of data-driven control methods on four major task families in this domain: cloth shaping, knot tying/untying, dressing and bag manipulation. Furthermore, we identify specific inductive biases in these four domains that present challenges for more general IL and RL algorithms.
Numerical analysis of transient photoconductivity in insulators

The nonlinear partial differential equations which describe transient photoconductivity in insulators are solved numerically. Trapping and recombination are included which allows photoconduction to be studied in the presence of large space charge. Use of methods for ‘‘stiff’’ differential equations insures stable time dependent solutions even for problems which have widely different time constants. The program is applied to a thin film (1000 A) of silicon dioxide to illustrate the salient features of the numerical solutions and the capabilities of the program.
Spatiotemporal Patterns and Regional Differences in Soil Thermal Conductivity on the Qinghai-Tibet Plateau

The Qinghai–Tibet Plateau is an area known to be sensitive to global climate change, and the problems caused by permafrost degradation in the context of climate warming potentially have far-reaching effects on regional hydrogeological processes, ecosystem functions, and engineering safety. Soil thermal conductivity (STC) is a key input parameter for temperature and surface energy simulations of the permafrost active layer. Therefore, understanding the spatial distribution patterns and variation characteristics of STC is important for accurate simulation and future predictions of permafrost on the Qinghai–Tibet Plateau. However, no systematic research has been conducted on this topic. In this study, based on a dataset of 2972 STC measurements, we simulated the spatial distribution patterns and spatiotemporal variation of STC in the shallow layer (5 cm) of the Qinghai–Tibet Plateau and the permafrost area using a machine learning model. The monthly analysis results showed that the STC was high from May to August and low from January to April and from September to December. In addition, the mean STC in the permafrost region of the Qinghai–Tibet Plateau was higher during the thawing period than during the freezing period, while the STC in the eastern and southeastern regions is generally higher than that in the western and northwestern regions. From 2005 to 2018, the difference between the STC in the permafrost region during the thawing and freezing periods gradually decreased, with a slight difference in the western hinterland region and a large difference in the eastern region. In areas with specific landforms such as basins and mountainous areas, the changes in the STC during the thawing and freezing periods were different or even opposite. The STC of alpine meadow was found to be most sensitive to the changes during the thawing and freezing periods within the permafrost zone, while the STC for bare land, alpine desert, and alpine swamp meadow decreased overall between 2005 and 2018. The results of this study provide important baseline data for the subsequent analysis and simulation of the permafrost on the Qinghai–Tibet Plateau.
Supervised texture segmentation using support vector machines

An approach to the problem of supervised texture segmentation using nonlinear support vector machines (SVMs) is presented. For each texture class a nonlinear SVM is constructed which separates that class from the other classes. The segmentation then works by applying all the SVMs to an input image and arbitrating between the SVM outputs. Experimental results show the effectiveness of the proposed method.
Are the Virial Masses of Clusters Smaller than We Think

The constraints that the available X-ray spectral and imaging data place on the mass distribution and mass to light ratio of rich clusters are considered. It was found for the best determined cases that the mass to light ratio is less than 125 h sub 50 at radii exceeding 1 h sub 50 Mpc. The mass to light ratio is approximately constant at radii exceeding 1 h sub 50 Mpc but may rise to values of roughly 200 h sub 50 in the central regions. The fraction of the total mass that is in baryons, primarily the hot X-ray emitting gas, is roughly 30 percent thus setting the mass to light ratio of the dark material to roughly 70. The model that fits the X-ray data for Coma is in good agreement with the observed optical velocity dispersion vs. radius data. 26 references.
Therapeutic Adherence of People with Mental Disorders: An Evolutionary Concept Analysis

Patient therapeutic adherence lies at the core of mental health care. Health Care professionals and organizations play a major role in promoting adherence among people with mental disorders. However, defining therapeutic adherence remains complex. We used Rodgers’ evolutionary concept analysis to explore the concept of therapeutic adherence in the context of mental health. We conducted a systematic literature search on Medline/PubMed and CINAHL for works published between January 2012 and December 2022. The concept analysis showed that major attributes of therapeutic adherence include patient, microsystem and meso/exosystem-level factors. Antecedents are those related to patients, such as their background, beliefs and attitudes, and acceptance of mental illness–and those related to patient-HCP therapeutic engagement. Lastly, three different consequences of the concept emerged: an improvement in clinical and social outcomes, commitment to treatment, and the quality of healthcare delivery. We discuss an operational definition that emerged from the concept analysis approach. However, considering the concept has undergone evolutionary changes, further research related to patient adherence experiences in an ecological stance is needed.
Integrated clutter estimation and target tracking using JIPDA/MHT tracker

In this paper, the problem of tracking multiple targets in unknown clutter background using the Joint Integrated Probabilistic Data Association (JIPDA) tracker and the Multiple Hypotheses Tracker (MHT) is studied. It is common in real tracking problems to have little or no prior information on clutter background. Furthermore, the clutter backgroundmay be dynamic and evolve with time. Thus, in order to get accurate tracking results, trackers need to estimate parameters of clutter background in each sampling instant and use the estimate to improve tracking. In this paper, incorporated with the JIPDA tracker or the MHT algorithm, a method based on Nonhomogeneous Poisson point processes is proposed to estimate the intensity function of non-homogeneous clutter background. In the proposed method, an approximated Bayesian estimate for the intensity of non-homogeneous clutter is updated iteratively through the Normal-Wishart Mixture Probability Hypothesis Density (PHD) filter technique. Then, the above clutter density estimate is used in the JIPDA algorithm and the MHT algorithm for multitarget tracking. It is demonstrated thorough simulations that the proposed clutter background estimation method improves the performance of the JIPDA tracker in unknown clutter background.
Summer Moisture and Wildfire Risks across Canada

Abstract The Fire Weather Index System has been in use across Canada for the past 30 years in the daily operations of fire management agencies. As part of this system, the Drought Code (DC) was developed to act as a daily index of water stored in the soil. A major obstacle to the completion of climate risk analyses on the DC is that lengthy series of daily temperature and precipitation are not available for large portions of the circumboreal forest. Here the authors present a methodological modification to the daily DC to allow its approximation using monthly data. This new Monthly Drought Code (MDC) still retains its ability to capture moisture trends in deep organic layers. On the basis of high-resolution temperature and precipitation data, an analysis of summer moisture availability across Canada over 1901–2002 is presented. The driest periods on record were from the 1920s to the early 1960s, with the driest years being 1955, 1958, and 1961. The wettest period was from the mid-1960s to the 1980s. For t.
Wavelengths, energy levels and hyperfine structure constants in Ho ii

We recorded spectra of Ho ii emitted by hollow-cathode lamps, using the ultraviolet Fourier transform spectrometer (FTS) at Lund Observatory and the 2-m FTS at the National Institute of Standards and Technology. The combined wavenumber coverage spans the interval from 8000 to 49 600 cm−1 (12 500 to 2016 Å). We measured 303 lines in these spectra and used them to determine energies and hyperfine structure constants of 100 levels. Of these, 41 energy levels have not been reported previously and hyperfine structure constants have not been reported previously for 83 levels. Comparisons between the hyperfine structure constants and energy levels presented in this article and those previously determined from other studies are included and discrepancies are discussed. A theoretical study of the odd-parity levels leads to hyperfine structure parameters and to predictions for unknown excited levels of the ground-state configuration.
The development of a novel natural language processing tool to identify pediatric chest radiograph reports with pneumonia

Objective Chest radiographs are frequently used to diagnose community-acquired pneumonia (CAP) for children in the acute care setting. Natural language processing (NLP)-based tools may be incorporated into the electronic health record and combined with other clinical data to develop meaningful clinical decision support tools for this common pediatric infection. We sought to develop and internally validate NLP algorithms to identify pediatric chest radiograph (CXR) reports with pneumonia. Materials and methods We performed a retrospective study of encounters for patients from six pediatric hospitals over a 3-year period. We utilized six NLP techniques: word embedding, support vector machines, extreme gradient boosting (XGBoost), light gradient boosting machines Naïve Bayes and logistic regression. We evaluated their performance of each model from a validation sample of 1,350 chest radiographs developed as a stratified random sample of 35% admitted and 65% discharged patients when both using expert consensus and diagnosis codes. Results Of 172,662 encounters in the derivation sample, 15.6% had a discharge diagnosis of pneumonia in a primary or secondary position. The median patient age in the derivation sample was 3.7 years (interquartile range, 1.4–9.5 years). In the validation sample, 185/1350 (13.8%) and 205/1350 (15.3%) were classified as pneumonia by content experts and by diagnosis codes, respectively. Compared to content experts, Naïve Bayes had the highest sensitivity (93.5%) and XGBoost had the highest F1 score (72.4). Compared to a diagnosis code of pneumonia, the highest sensitivity was again with the Naïve Bayes (80.1%), and the highest F1 score was with the support vector machine (53.0%). Conclusion NLP algorithms can accurately identify pediatric pneumonia from radiography reports. Following external validation and implementation into the electronic health record, these algorithms can facilitate clinical decision support and inform large database research.
Direct observation and mechanism for enhanced field emission sites in platinum ion implanted/post-annealed ultrananocrystalline diamond films

Enhanced electron field emission (EFE) properties for ultrananocrystalline diamond (UNCD) films upon platinum (Pt) ion implantation and subsequent post-annealing processes is reported, viz., low turn-on field of 4.17 V/μm with high EFE current density of 5.08 mA/cm2 at an applied field of 7.0 V/μm. Current imaging tunneling spectroscopy (CITS) mode in scanning tunneling spectroscopy directly revealed the increased electron emission sites density for Pt ion implanted/post-annealed UNCD films than the pristine one. The high resolution CITS mapping and local current–voltage characteristic curves demonstrated that the electrons are dominantly emitted from the diamond grain boundaries and Pt nanoparticles.
Primary Ciliary Dyskinesia in a Portuguese Bronchiectasis Outpatient Clinic

Primary ciliary dyskinesia (PCD) is a rare hereditary condition characterized by decreased mucociliary clearance of the airways and a compromised reproductive system, resulting in male and female infertility. Several mutations with varied clinical and pathological features have been documented, making diagnosis a challenging process. The purpose of this study is to describe the clinical and pathological features of Portuguese patients with PCD and to examine their genetic variants. A retrospective observational analysis was conducted with patients who were being monitored at a bronchiectasis outpatient clinic in 2022 and had a confirmed or high-likelihood diagnosis of PCD. In total, 17 patients were included in the study, with 12 (66.7%) having PCD confirmed and 5 (29.4%) having a high-likelihood diagnosis. Furthermore, 12 patients were subjected to transmission electron microscopy (TEM), with 7 (58.3%) exhibiting one hallmark defect. Genetic test data was obtained for all 17 patients, with 7 of them (41.2%) displaying a pathogenic/likely pathogenic mutation in homozygosity. To summarize, PCD is an uncommon but significant hereditary illness with consequences regarding morbidity and mortality. Despite the lack of a specific treatment, it is critical to confirm the diagnosis with genetic testing in order to effectively manage the disease and its accompanying disorders.
Biomass Burning Aerosols Observed in Northern Finland during the 2010 Wildfires in Russia

A smoke plume originating from the massive wildfires near Moscow was clearly detected in northern Finland on 30 July 2010. Measurements made with remote sensing instruments demonstrated how the biomass burning aerosols affected the chemical and optical characteristics of the atmosphere in regions hundreds of kilometers away from the actual fires. In this study, we used MODIS, AIRS, CALIOP, PFR, ceilometers, FTS and Brewer data to quantify the properties of the transported smoke plume. In addition, in situ measurements of aerosol concentration (DMPS), absorption (aethalometer) and scattering (nephelometer) are presented. We found that due to the smoke plume in northern Finland, the daily averaged optical thickness of aerosols increased fourfold, and MODIS retrieved AOD as high as 4.5 for the thickest part of the plume. FTS measurements showed that CO concentration increased by 100% during the plume. CALIOP and ceilometer measurements revealed that the smoke plume was located close to the surface, below 3 km, and that the plume was not homogeneously mixed. In addition, in situ measurements showed that the scattering and absorption coefficients were almost 20 times larger in the smoke plume than on average, and that the number of particles larger than 320 nm increased 14-fold. Moreover, a comparison with in situ measurements recorded in eastern Finland on the previous day showed that the transport from eastern to northern Finland decreased the scattering coefficient, black carbon concentration, and total number concentration 0.5%/h, 1.5%/h and 2.0%/h, respectively.
Power System Restoration With Renewable Participation

Power system restoration requires initial power sources to restart generators, energizing transmissions, and pick up critical loads. Sufficient initial power capacity is critical for restoration success and reducing outage duration. Due to the reliability requirement and high standby costs, black-start resources are scarce and expensive in areas where hydro power is not available. Variable renewable energy (VRE), whose fast-ramping capability and economical standby costs are suitable for black-start, is traditionally excluded from participation in system restoration because its uncertainty and variability could cause severe disturbance to the system that is already fragile during restoration. Recently, VRE is becoming a potential participant in system restoration as auxiliary black-start resources. This work will explore the potential benefits of renewable energy in restoration and potential ways for VRE to participate in system restoration. We propose two dispatch models for wind participation. The uncertainty of wind generation is handled by probabilistic constraints to guarantee a feasible restoration plan with a high probability. We perform computational experiments to demonstrate the effectiveness of proposed models and benefits of renewable participation in restoration with the two approaches.
Adaptive frequency comb illumination for interferometry in the case of nested two-beam cavities

The homogeneity test of glass plates in a Fizeau interferometer is hampered by the superposition of multiple interference signals coming from the surfaces of the glass plate as well as the empty Fizeau cavity. To evaluate interferograms resulting from such nested cavities, various approaches such as the use of broadband light sources have been applied. In this paper, we propose an adaptive frequency comb interferometer to accomplish the cavity selection. An adjustable Fabry–Perot resonator is used to generate a variable frequency comb that can be matched to the length of the desired cavity. Owing to its flexibility, the number of measurements needed for the homogeneity test can be reduced to four. Furthermore, compared to approaches using a two-beam interferometer as a filter for the broadband light source, the visibility of the fringe system is considerably higher if a Fabry–Perot filter is applied.
Probability and Conditionals

The aim of the paper is to draw a connection between a semantical theory of conditional statements and the theory of conditional probability. First, the probability calculus is interpreted as a semantics for truth functional logic. Absolute probabilities are treated as degrees of rational belief. Conditional probabilities are explicitly defined in terms of absolute probabilities in the familiar way. Second, the probability calculus is extended in order to provide an interpretation for counterfactual probabilities--conditional probabilities where the condition has zero probability. Third, conditional propositions are introduced as propositions whose absolute probability is equal to the conditional probability of the consequent on the antecedent. An axiom system for this conditional connective is recovered from the probabilistic definition. Finally, the primary semantics for this axiom system, presented elsewhere, is related to the probabilistic interpretation.
Evaluation and Modeling of SiC Based Power Converter for Low Temperature Operation

Cryogenic power electronics is regarded as the next step to improve the power converter efficiency and power density. Thus, investigations on component and converter performances under low temperature operations are of great importance. Silicon carbide (SiC) devices have gradually replaced traditional Silicon (Si) devices in high voltage and high power applications. This is due to their fast switching speed and low switching loss. In this article, the performance of SiC device based power converters are investigated under low temperature operation. Firstly, the individual component performances are evaluated under low temperatures. Then, a 600 W resonant converter based DC transformer was built and tested under low temperatures. The efficiency for the tested converter with ferrite cores drops from 97.86% at room temperature (298 K) to 93.44% at 143 K. The converter power loss model under low temperature operation was developed to facilitate the understanding of converter performance at various operating temperatures.
CO-TRENDING: AN EXTENDED VERSION ⁄

The present paper reproduces the outline of reasoning in M. Hatanaka and H. Yamada, Cotrending, 2003, Springer Verlag. The relations among deterministic trends of dierent variables are modeled in a framework analogous to the cointegration. Inference methods are presented to determine the co-trending rank as well as the rank of the space that is common to the co-trending and cointegration. In comparison with the previous publication, additional explanations are provided on several strategic points, and the framework of analyses is extended along advice of C.W. J. Granger, while technical details are deleted.