Miracle-dz/UniFAR-FTUs huggingface dataset:
Motion-compensated reconstruction for limited-angle multiphase cardiac CT

ECG-gated multiphase cardiac CT (MP-CCT) is free of motion artifacts and can provide the extra information of cardiac functions for the diagnosis of coronary artery disease. Used majority as a screening tool, the excessive radiation dose becomes a concern of MP-CCT. In this work, we propose a motion-compensated reconstruction method for MP-CCT with the limited angle acquisition for each phase in order to substantially reduce the radiation dose. MP-CCT of the XCAT phantom with eight cardiac phases was simulated with 90° coverage for each phase. The motion was estimated from images reconstructed by combining projections from two phases (for a full 180° coverage). To reconstruct the image at phase k, the motion fields were used to warp images at phase k to phase j (j = 1~8 and j ≠ k) so that all projection data could be used for a total variation (TV) constrained reconstruction. The results show that TV reconstruction for each cardiac phase independently (TV-Single Phase) suffered severe limited-angle artifacts. TV reconstruction with two-phase projections (TV-Two Phases) improved the image quality and was suitable for good motion estimation. Motion-compensated TV reconstruction (TV-MC) achieved almost artifact-free images, although some motion errors could be seen. The root mean square error values are 254 HU, 64 HU and 47 HU for TV-Single Phase, TV-Two Phases, and TV-MC, respectively.
Adaptation of spherical harmonic transform for color shape reconstruction and retrieval using quaternion algebra

Abstract. A set of invariant quaternion moments based on an adaptation of the three-dimensional (3-D) spherical harmonic transform (SHT) for describing two-dimensional color shapes is proposed. The use of quaternions to deal with the color part is beneficial in the way the three color components are integrated in a single feature. An adequate mapping from the 3-D SHT to the unit disc allows a fast and accurate computation of the proposed moments. Experiments are conducted to evaluate the performance of the obtained moments in terms of color image reconstruction, robustness to geometric and photometric transformations, content-based color shape retrieval, and computation time. For this purpose, two image databases (COIL-100 and ALOI) are used. Results illustrate the effectiveness of the proposed moments in dealing with the color information.
Changes in the spatial–temporal patterns of droughts in the Brazilian Northeast

In Northeast Brazil (NEB), severe droughts have high socioeconomic impacts. In this study, the spatial–temporal characteristics of drought were evaluated based on a new drought index at 4‐km spatial resolution, derived from regional empirical relationships between a remote sensing‐based index and rain‐gauge‐based standardized precipitation index (SPI), a well‐known drought meteorological index. This index was used to compare the spatial pattern of severe drought events (1982–1983, 1992–1993, 1997–1998, and 2012–2013) of the last 30 years. Strong El Niño related droughts were found to be generally spatially limited, affecting around 30% of NEB and concentrated in the northern part of the region, while 2012 drought, which was not El Niño related, was widespread, reaching 46% of NEB. These results stressed the importance of analyzing droughts at the subregion scale using data with higher spatial resolution. Statistically significant trends (p < 0.05) toward drier conditions detected in the SPI time‐series were linked to the tropical Atlantic Ocean warming trend, which result in an increased drought risk and social vulnerability in the region.
Backscattered Stokes Vectors of Turbid Media: Anisotropy Factor and Reduced Scattering Coefficient Estimation

Optical characterization of biological tissues is of real interest to improve medical diagnosis and in particular in the detection of precancerous tissues. The reduced scattering coefficient mu's and the absorption coefficient mua are the most commonly retrieved coefficients. Some methods also allow to obtain the anisotropy factor g, but only few of them are noninvasive. We propose a new non-invasive method allowing the estimation of the anisotropy factor and the reduced scattering coefficient. This method is based on the image analysis of the Q- element of Stokes vector backscattered from the turbid medium. These Q-element images show specific patterns depending on g, and mu's is determined by the size of the patterns. Therefore the use of Fourier Descriptors (FD) on simulated and experimental data, to discriminate the specific geometrical features of the Q- element, enabled us to determine the anisotropy factor and the scattering coefficient.
Path Following and Collision Avoidance for an Underwater Swimming Manipulator

The Underwater Swimming Manipulator (USM) is a new type of autonomous unmanned underwater vehicle that combines the highly maneuverable design of the biologically inspired underwater snake robot (USR) with thruster actuators as typically used in more traditional underwater vehicle designs. The USM resembles a submerged multiarticulate manipulator arm with thrusters, and can use joint actuation, thruster actuation, or a combination of the two for motion. The thrusters increase the USM’s controllable degrees of freedom (DOF), and by placing them strategically they can facilitate 6-DOF rigid-body movement almost independently of the robot’s body shape. Together with the long and slender body, this maneuverability enables the USM to gain access to almost any area, that being the inside of shipwrecks or between the steel beams of subsea structure protection cages, and can be utilized to solve complex tasks. One of the most essential abilities of an autonomous mobile robot system is the ability to safely navigate the environment. This thesis proposes controllers for path following and collision avoidance that grants the USM this capability. Both controllers take advantage of the USM’s unique design, with the path following controller using the flexible body to improve path following accuracy and reduce energy consumption, while the collision avoidance controller exploits the maneuverability of the robot to enable movement in highly cluttered areas.
network analysis reveals potential markers for pediatric adrenocortical carcinoma

: Pediatric adrenocortical carcinoma (ACC) is a rare malignancy with a poor outcome. Molecular mechanisms of pediatric ACC oncogenesis and advancement are not well understood. Accurate and timely diagnosis of the disease requires identification of new markers for pediatric ACC. Differentially expressed genes (DEGs) were identified from the gene expression profile of pediatric ACC and obtained from Gene Expression Omnibus. Gene Ontology functional and pathway enrichment analysis was implemented to recognize the functions of DEGs. A protein– protein interaction (PPI) and gene–gene functional interaction (GGI) network of DEGs was constructed. Hub gene detection and enrichment analysis of functional modules were performed. Furthermore, a gene regulatory network incorporating DEGs–microRNAs–transcription factors was constructed and analyzed. A total of 431 DEGs including 228 upregulated and 203 downregulated DEGs were screened. These genes were largely involved in cell cycle, steroid biosynthesis, and p53 signaling pathways. Upregulated genes, CDK1 , CCNB1 , CDC20 , and BUB1B , were identified as the common hubs of PPI and GGI networks. All the four common hub genes were also part of modules of the PPI network. Moreover, all the four genes were also present in the largest module of GGI network. A gene regulatory network consisting of 82 microRNAs and 100 transcription factors was also constructed. CDK1 , CCNB1 , CDC20 , and BUB1B may serve as potential biomarker of pediatric ACC and as potential targets for therapeutic approach, although experimental studies are required to authenticate our findings.
Effects of moult and breeding on the body condition of some forest birds in southwest Nigeria

By using body mass and tarsus length as a proxy for body condition, the effects of moult (actively moulting, new feathers or old feathers) and breeding (breeding or non-breeding) on the Grey-headed Bristlebill Bleda canicapillus , White-throated Greenbul Phyllastrephus albigularis , Little Greenbul Eurillas virens and Yellow-whiskered Greenbul Eurillas latirostris , were investigated in two rainforest patches in southwest Nigeria, 2017–2019. The relative frequency of the studied species across the study sites and the numbers of moulting and breeding individuals are presented. Despite breeding and moulting birds being recorded over much of the year in all four species, only six birds (2 %) of three species were moulting while breeding, suggesting a trade-off. Moult did not significantly influence the body condition of any bird species, but the body condition of breeding Grey-headed Bristlebill, Little Greenbul and White-throated Greenbul was significantly lower than that of non-breeding birds. This was not the case for the Yellow-whiskered Greenbul, which may be able to synchronise moult and breeding with peak food availability. Résumé
Multiscale hidden Markov model applied to ECG segmentation

A new electrocardiogram (ECG) segmentation method is proposed, which uses a Wavelet Tree Hidden Markov Model. The principle of this approach is, on one hand, to use wavelet coefficients to characterize the different ECG waves, and on the other hand, to link these coefficients by a tree structure permitting to detect wave changes. By associating this method to a fusion method between scales based on the context concept, good results are obtained on a special database created for risk analysis of atrial fibrillation, particularly in P wave segmentation.
Breaking The Link: An Analysis Of Procedures To Decrease Inappropriate Behavior When It Is A Link In A Response Chain

The current study examined the effectiveness of a strategy to disrupt behavior chains, consisting of an inappropriate behavior followed by an appropriate behavior of 3 children with moderate to severe disabilities. A baseline measure was collected of each response in the chain: response one (R1) and response two (R2). Conditional probabilities were calculated to provide evidence that the two responses occurred in a predictable sequence and may therefore constitute a chain. The subsequent intervention consisted of providing the appropriate discriminative stimulus that occasioned R2 on a fixed schedule and reinforcing the appropriate response (R2) regardless of when it occurred (i.e., within the chain or alone). The results of a multiple baseline across participants analysis demonstrated that the intervention was effective in disrupting the response chains and in decreasing the inappropriate response for all 3 participants. In addition, the intervention was effective in increasing the appropriate response in 2 of the 3 participants. These results have implications for use of the disruption procedure in applied settings in which challenging behavior is a member of a response chain.
A polynomial-time interior-point method for circular cone programming based on kernel functions

We present an interior-point method based on kernel functions for circular cone optimization problems, which has been found useful for describing optimal design problems of optimal grasping manipulation for multi-fingered robots. Since the well-known second order cone is a particular circular cone, we first establish an invertible linear mapping between a circular cone and its corresponding second order cone. Then we develop a kernel function based interior-point method to solve circular cone optimization in terms of the corresponding second order cone optimization problem. We derive the complexity bound of the interior-point method and conclude that circular cone optimization is polynomial-time solvable. Finally we illustrate the performance of interior-point method by a real-world quadruped robot example of optimal contact forces taken from the literature [10].
Perioperative hyperglycemia is associated with postoperative neurocognitive disorders after cardiac surgery

Objective: Neurocognitive disorders commonly occur following cardiac surgery. However, the underlying etiology of these disorders is not well understood. The current study examined the association between perioperative glucose levels and other risk factors and the onset of neurocognitive disorders in adult patients following coronary artery bypass and/or valvular surgery. Methods: Adult patients who underwent their first cardiac surgery at a large tertiary care medical center were identified and those with neurocognitive disorders prior to surgery were excluded. Demographic, perioperative, and postoperative neurocognitive outcome data were extracted from the Society for Thoracic Surgery database, and from electronic medical records, between January 2004 and June 2009. Multiple clinical risk factors and measures associated with insulin resistance, such as hyperglycemia, were assessed. Multivariable Cox competing risk survival models were used to assess hyperglycemia and postoperative neurocognitive disorders at follow up, adjusting for other risk factors and confounding variables. Results: Of the 855 patients included in the study, 271 (31.7%) had new onset neurocognitive disorders at follow-up. Age, sex, New York Heart Failure (NYHF) Class, length of postoperative intensive care unit stay, perioperative blood product transfusion, and other key factors were identified and assessed as potential risk factors (or confounders) for neurocognitive disorders at follow-up. Bivariate analyses suggested that new onset neurocognitive disorders were associated with NYHF Class, cardiopulmonary bypass, history of diabetes, intraoperative blood product use, and number of diseased coronary vessels, which are commonly-accepted risk factors in cardiac surgery. In addition, higher first glucose level (median = 116 mg/dL) and higher peak glucose . 169 mg/dL were identified as risk factors. Male sex and nonuse of intra-operative blood products appeared to be protective. Controlling for potential risk factors and confounders, multivariable Cox survival models suggested that increased perioperative first glucose measured in 20 unit increments, was significantly associated with the onset of postoperative neurocognitive disorders at follow-up (hazard ratio [HR] = 1.16, P , 0.001) and that women had an elevated risk for this outcome (HR = 4.18, P = 0.01). Conclusion: Our study suggests that perioperative hyperglycemia was associated with new onset of postoperative neurocognitive disorders in adult patients after cardiac surgery, and that men tended to be protected from these outcomes. These findings may suggest a need for the revision of clinical protocols for perioperative insulin therapy to prevent long-term neurocognitive complications.
Semi-device-independent randomness expansion with partially free random sources using 3 →1 quantum random access code

We have proved that new randomness can be certified by partially free sources using $2\ensuremath{\rightarrow}1$ quantum random access code (QRAC) in the framework of semi-device-independent (SDI) protocols [Y. -Q. Zhou, H. -W. Li, Y. -K. Wang, D. -D. Li, F. Gao, and Q. -Y. Wen, Phys. Rev. A 92, 022331 (2015)]. To improve the effectiveness of the randomness generation, here we propose the SDI randomness expansion using $3\ensuremath{\rightarrow}1$ QRAC and obtain the corresponding classical and quantum bounds of the two-dimensional quantum witness. Moreover, we get the condition which should be satisfied by the partially free sources to successfully certify new randomness, and the analytic relationship between the certified randomness and the two-dimensional quantum witness violation.
Burnout, Depression, Anxiety, and Stress Among Family Physicians in Kansas: 18 Months into the COVID-19 Pandemic

Introduction: Given the signiﬁcant turmoil during the COVID-19 pandemic, the authors evaluated burnout and other types of emotional distress experienced by family physicians in Kansas during the second year of the pandemic. The authors compared ﬁndings of this study to a similar study conducted 3 months into the pandemic. Methods: A cross-sectional online survey of 272 actively practicing family physicians in Kansas was conducted from September 15 to October 18, 2021. A 34-item questionnaire was used to measure the physicians’ levels of burnout, personal depression, anxiety, and stress. A mixed method approach was used to collect, analyze, and interpret the data. Descriptive statistics, Mann-Whitney U test/independent samples t -test, v 2 , adjusted odds ratio, and immersion-crystallization methods were used to analyze the data. Results: The response rate was 48.9% (n = 133). In aggregate, 69.2% of respondents reported at least 1 manifestation of professional burnout in 2021 compared with 50.4% in 2020; P ≤ . 01). The 2021 respondents were at higher odds of experiencing burnout compared with 2020 respondents (aOR = 1.86; 95% CI, 1.00 to 3.57; P = .046). The respondents who reported at least 1 manifestation of professional burnout were more likely to screen positive for depression (aOR = 1.87; 95% CI, 1.31-2.66; P ≤ .01), report higher levels of anxiety (aOR = 1.53; 95% CI, 1.04-2.24; P = .013), and higher levels of stress (aOR = 1.39; 95% CI, 1.17-1.66; P ≤ .001). Conclusion: As the COVID-19 pandemic continued, there are signiﬁcant and worsening rates of professional burnout and other forms of emotional distress among family physicians. These ﬁndings suggest timely need for appropriate psychological supports.
Bioequivalence & Bioavailability

Nutritional recommendations agree on the importance of a predominantly plant-based diet (http://www.choosemyplate.gov); however, sole reliance on plants for nutrition can limit the intake of the essential nutrients calcium (Ca), vitamins B12 and D [1]. Bioavailable Ca is critical to human health, which is needed specifically for bone growth and muscle control. Inadequate Ca uptake can cause imbalanced Ca levels in serum, resulting in hormone-regulated adaptation which promotes the mobilization of Ca from bone Ca phosphate and increases the risk of osteoporosis [2,3]. In recent years, concerns over the development of osteoporosis in an aging population has led to an increase in food fortification of Ca in the United States [4,5]. Several studies show that Ca-fortified vegetables can increase Ca uptake in mice and humans [6,7], but the long term efficacy of these fortification activities remains questionable [8]. Calcium in plants exist as complexes with oxalate, phytate, and fiber [9,10], all of which suppress Ca bioavailability. It is believed that the Ca oxalate (CaOx) content is the best predictor of Ca availability [11]. For example, spinach contains a high concentration of Ca but a significant amount of this Ca is complexed with oxalate which reduces its Ca bioavailability to about 5.0% [12]. However, in soybeans oxalate levels are similar to spinach but its Ca bioavailability is around 20%
A Study on Moving Mesh Finite Element Solution of Phase-Field Models for Hydraulic Fracturing

A moving mesh finite element method is studied for the numerical solution of a phase-field model for brittle fracture and hydraulic fracture. In the phase-field modeling, a continuous phase field variable is introduced to describe the unbroken or broken status of the material, which can model fractures without explicitly tracking discontinuous displacement fields. It has the advantages of being able to handle complex cracks, crack propagation, and creation of new cracks more easily. It is noted that the parameter , which describes the width of smeared cracks, should be chosen small for the model to be sufficiently accurate. On the other hand, the mesh size ( ) should be chosen small typically satisfying or at least . This deems it necessary to use mesh adaptation for an efficient numerical simulation. Moreover, cracks propagate under continuous load, which means the mesh must adapt to the evolving cracks dynamically. In this talk we will employ the moving mesh partial differential equation approach for dynamic mesh adaption. Numerical examples will be presented to show that the moving mesh finite element method is able to adaptively capture the crack propagation and handle multiple crack systems.
THE ET INTERVIEW: PROFESSOR MAX KING

In 1951, Maxwell Leslie King was born in Christchurch New Zealand. He grew up within walking distance of the Ilam Campus of the University of Canterbury where he completed a B.Sc. with First Class Honours in mathematics in 1972. A bursary with the Reserve Bank of New Zealand allowed him to complete an M.Com. in economics with First Class honours in 1974. He returned to the University in 1976 to undertake a Ph.D. in econometrics which was completed in 1979. Max took up an appointment as Lecturer at Monash University in March 1979. He was promoted to Senior Lecturer in 1983 and Reader in 1986. In mid-1986, he was appointed Professor of Econometrics and in 1988 he became Head of the newly created Department of Econometrics, a position he held for 13 years. In 1993 he was invited to chair Monash University’s Ph.D. and Scholarships Committee, a position that led him to become the inaugural Director of the Monash Research Graduate School and in 2003, Pro Vice-Chancellor (Research and Research Training). Other Monash University appointments include Deputy
Class Augmented Semi-Supervised Learning for Practical Clinical Analytics on Physiological Signals.

Computational analysis on physiological signals would provide immense impact for enabling automated clinical analytics. However, the class imbalance issue where negative or minority class instances are rare in number impairs the robustness of the practical solution. The key idea of our approach is intelligent augmentation of minority class examples to construct smooth, unbiased decision boundary for robust semi-supervised learning. This solves the practical class imbalance problem in anomaly detection task for computational clinical analytics using physiological signals. We choose two critical cardiac marker physiological signals: Heart sound or Phonocardiogram (PCG) and Electrocardiogram (ECG) to validate our claim of robust anomaly detection of clinical events under augmented class learning, where intelligent synthesis of minority class instances attempt to balance the class distribution. We perform extensive experiments on publicly available expert-labelled MIT-Physionet PCG and ECG datasets that establish high performance merit of the proposed scheme, and our scheme fittingly performs better than the state-of-the-art algorithms.