Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic low-count PET image reconstruction using spatio-temporal primal dual network

Objective. Dynamic positron emission tomography (PET) imaging, which can provide information on dynamic changes in physiological metabolism, is now widely used in clinical diagnosis and cancer treatment. However, the reconstruction from dynamic data is extremely challenging due to the limited counts received in individual frame, especially in ultra short frames. Recently, the unrolled model-based deep learning methods have shown inspiring results for low-count PET image reconstruction with good interpretability. Nevertheless, the existing model-based deep learning methods mainly focus on the spatial correlations while ignore the temporal domain. Approach. In this paper, inspired by the learned primal dual (LPD) algorithm, we propose the spatio-temporal primal dual network (STPDnet) for dynamic low-count PET image reconstruction. Both spatial and temporal correlations are encoded by 3D convolution operators. The physical projection of PET is embedded in the iterative learning process of the network, which provides the physical constraints and enhances interpretability. Main results. The experiments of both simulation data and real rat scan data have shown that the proposed method can achieve substantial noise reduction in both temporal and spatial domains and outperform the maximum likelihood expectation maximization, spatio-temporal kernel method, LPD and FBPnet. Significance. Experimental results show STPDnet better reconstruction performance in the low count situation, which makes the proposed method particularly suitable in whole-body dynamic imaging and parametric PET imaging that require extreme short frames and usually suffer from high level of noise.
The future of anatomy teaching post‐pandemic: An academic viewpoint

The COVID‐19 pandemic caused major disruption to anatomical teaching worldwide with both lectures and practicals being moved online. Throughout this period anatomists were able to find new and innovative ways to teach and to aid student learning via a variety of delivery modes. This study aimed to interview anatomists who were involved in teaching undergraduate medical students at UK universities to document the changes that occurred and to understand academic perceptions of pandemic delivery to comprehend how anatomy education may change in the long term. Results suggest that academics are likely to continue to deliver anatomical lectures online post‐pandemic akin to a flipped classroom approach, although caution was noted regarding ‘at‐risk’ student groups. No academics wished to see continued delivery of practical classes online, however, resources designed or invested in during the pandemic will be integrated into practical classes or pre‐class preparation allowing for a more complete student experience. No clear picture emerged as to the preferred way staff and students will communicate in the current post‐pandemic hybrid working environment and beyond. This will likely only be resolved when a new pattern of home working evolves in UK institutions. This report is the first to detail the academic vision of anatomy teaching in a post‐pandemic world and will be useful to those adapting to these changes and for those pedagogical researchers targeting where anatomical education research should focus moving forward.
Genes associated with spontaneous brain activity changes in clinically different patients with major depressive disorder: A transcription‐neuroimaging association study

The amplitude of low‐frequency fluctuations (ALFF) of resting‐state functional MRI signals is a reliable neuroimaging measure of spontaneous brain activity. Inconsistent ALFF alterations have been reported in major depressive disorder (MDD) possibly due to clinical heterogeneity. This study was designed to investigate clinically sensitive and insensitive genes associated with ALFF alterations in MDD and the potential mechanisms.
Adaptive particle swarm optimization via disturbing acceleration coefficents

The Particle Swarm Optimization(PSO) is an evolutionary method which is used to search for the global optimal solution by iteration.However,PSO has the problem that the particle swarm algorithm falls easily into premature convergence and has a low search efficiency.In this paper,after analyzing several existing improved particle swarm algorithms,a new improved particle swarm algorithm is proposed based on the fact that symmetrical particles distribution can enhance the optimation search results.The proposed algorithm can adjust the inertia weight factor adaptively in different phases of the process according to the variation of the cosine function.In addition,the acceleration coefficents based on linear variation are disturbed under a certain condition.Moreover,an appropriate value of the parameter in this condition is determined via experiments.Several classic functions have been used to test this new algorithm and then the results of this new algorithm are analyzed by comparing it with several relevant algorithms in the literature.The results show that this new algorithm can not only improve the convergence speed significantly,but also improve the premature convergence phenomenon.
SLIT2/ROBO1 signaling suppresses mTORC1 for organelle control and bacterial killing

SLIT2, a canonical neurorepellent, promotes lysosome biogenesis and augments autophagic flux to modulate immune responses in macrophages. In cancer cells, SLIT2 negatively regulates mTORC1 signaling to control cell growth. SLIT/ROBO signaling impacts many aspects of tissue development and homeostasis, in part, through the regulation of cell growth and proliferation. Recent studies have also linked SLIT/ROBO signaling to the regulation of diverse phagocyte functions. However, the mechanisms by which SLIT/ROBO signaling acts at the nexus of cellular growth control and innate immunity remain enigmatic. Here, we show that SLIT2-mediated activation of ROBO1 leads to inhibition of mTORC1 kinase activity in macrophages, leading to dephosphorylation of its downstream targets, including transcription factor EB and ULK1. Consequently, SLIT2 augments lysosome biogenesis, potently induces autophagy, and robustly promotes the killing of bacteria within phagosomes. Concordant with these results, we demonstrate decreased lysosomal content and accumulated peroxisomes in the spinal cords of embryos from Robo1−/−, Robo2−/− double knockout mice. We also show that impediment of auto/paracrine SLIT-ROBO signaling axis in cancer cells leads to hyperactivation of mTORC1 and inhibition of autophagy. Together, these findings elucidate a central role of chemorepellent SLIT2 in the regulation of mTORC1 activity with important implications for innate immunity and cancer cell survival.
Psychometric validation of the Perceived Perioperative Competence Scale-Revised Short Form.

AIM To develop a parsimonious, shortened version of the Perceived Perioperative Competence Scale-Revised for perioperative nurses to complete as part of their specialty training while retaining good psychometric properties. DESIGN A longitudinal online survey was adopted. METHODS A national sample of perioperative nurses from Australia completed an online survey at two different time points 6 months apart between February and October 2021. Confirmatory factor analysis was conducted for item reduction and construct validity, while criterion, convergent validity and internal consistency were examined. RESULTS Usable data for psychometric assessment were obtained from 485 operating room nurses at time 1 and 164 nurses at time 2. The original 40-item revised scale was reduced to an 18-item measure, maintaining its six domains. Cronbach's alpha for the 18-item scale was . 92 at time 1 and . 90 at time 2. Scale validation demonstrated moderate to weak positive relationships in perceived competence scores relative to general self-efficacy, years of operating room experience, postgraduate education and recency of training. CONCLUSIONS Results suggest the 18-item Perceived Perioperative Competence Scale-Revised Short Form has initial robust psychometric properties and may be implemented in clinical settings as part of perioperative transition-to-practice, orientation programs and yearly professional development reviews. IMPLICATIONS FOR THE PROFESSION This short-form scale can help prepare perioperative nurses to demonstrate clinical competence in a climate of increasing professional demands using a valid measure of competence required in clinical practice. IMPACT Short and validated scales of perioperative competence are needed in clinical practice. Assessment of practising operating room nurses' perceived competence is essential in quality care provision, workforce planning and human resource management. This study provides an 18-item measure of the previously validated 40-item Perceived Perioperative Competence Scale-Revised. This scale can help provide an option for future testing of perioperative nurses' competence in clinical or research settings. PATIENT OR PUBLIC CONTRIBUTION Perioperative nurses were involved in the design of the study, particularly in the assessment of validation of the tools used in the study.
Surface morphology and magnetic property of wrinkled FeGa thin films fabricated on elastic polydimethylsiloxane

We investigated the surface morphology and the magnetic property of wrinkled Fe81Ga19 (FeGa) thin films fabricated in two different processes onto elastic polydimethylsiloxane (PDMS) substrates. The films obtained by directly depositing Ta and FeGa layers on a pre-strained PDMS substrate display a sinusoidally wrinkled surface and a weak magnetic anisotropy. The wavelength and amplitude of the sinusoidal morphology linearly increase with the metallic layer thickness, while the magnetic anisotropy decreases with increasing FeGa thickness. The other films grown by depositing FeGa layer on a wrinkled Ta/PDMS surface show a remarkable uniaxial magnetic anisotropy. The strength of magnetic anisotropy increases with increasing FeGa thickness. The magnetic anisotropy can be ascribed to the surface anisotropy, the magnetostrictive anisotropy, and the shape anisotropy caused, respectively, by the magnetic charges on wavy morphology, the residual mechanical stress, and the inhomogeneous thickness of FeGa films.
Ηeparan sulphate in infectious and non‐infectious exacerbations of COPD

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are associated with worsening health outcomes and effective treatment of each episode is essential. In this study, we aimed to investigate if plasma levels of heparan sulphate (HS) are associated with the aetiology of AECOPD.
Expansion of the Materials Cloud 2D Database

Two-dimensional (2D) materials are among the most promising candidates for beyond-silicon electronic, optoelectronic, and quantum computing applications. Recently, their recognized importance sparked a push to discover and characterize novel 2D materials. Within a few years, the number of experimentally exfoliated or synthesized 2D materials went from a few to more than a hundred, with the number of theoretically predicted compounds reaching a few thousand. In 2018 we first contributed to this effort with the identification of 1825 compounds that are either easily (1036) or potentially (789) exfoliable from experimentally known 3D compounds. Here, we report on a major expansion of this 2D portfolio thanks to the extension of the screening protocol to an additional experimental database (MPDS) as well as the updated versions of the two databases (ICSD and COD) used in our previous work. This expansion leads to the discovery of an additional 1252 monolayers, bringing the total to 3077 compounds and, notably, almost doubling the number of easily exfoliable materials to 2004. We optimize the structural properties of all these monolayers and explore their electronic structure with a particular emphasis on those rare large-bandgap 2D materials that could be precious in isolating 2D field-effect-transistor channels. Finally, for each material containing up to 6 atoms per unit cell, we identify the best candidates to form commensurate heterostructures, balancing requirements on supercell size and minimal strain.
Irreducible Infeasible Subsystem Decomposition for Probabilistically Constrained Stochastic Integer Programs

This dissertation explores methods for finding irreducible infeasible subsystems (IISs) of systems of inequalities with binary decision variables and for solving probabilistically constrained stochastic integer programs (SIP-C). Finding IISs for binary systems is useful in decomposition methods for SIP-C. SIP-C has many important applications including modeling of strategic decision-making problems in wildfire initial response planning. New theoretical results and two new algorithms to find IISs for systems of inequalities with binary variables are developed. The first algorithm uses the new theory and the method of the alternative polyhedron within a branch-and-bound (BAB) approach. The second algorithm applies the new theory and the method of the alternative polyhedron to a system in which zero/one box constraints are appended. Decomposition schemes using IISs for binary systems can be used to solve SIP-C. SIP-C is challenging to solve due to the generally non-convex feasible region. In addition, very weak lower (upper) bounds on the objective function are obtained from the linear programming (LP) relaxation of the deterministic equivalent problem (DEP) to SIP-C. This work develops a branch-and-cut (BAC) method based on IIS inequalities to solve SIP-C with random technology matrix and random righthandside vector. Computational results show that the LP relaxation of the DEP to SIP-C can be strengthened by the IIS inequalities. SIP-C modeling can be applied to wildfire initial response planning. A new methodology for wildfire initial response that includes a fire behavior simulation model, a wildfire risk model, and SIP-C is developed and tested. The new methodology assumes a known standard response needed to contain a fire of given size. Likewise, this methodology is used to evaluate deployment decisions in terms of the
Playing the game: The educational role of gamified peer‐led assessment

‘Assessment drives learning’ is an often-repeated phrase highlighting the educational benefits that can be achieved through assessment activities. Although typically mentioned in relation to formative and summative examinations, recent research has highlighted the importance of implementing broader curricular assessment interventions to enhance learner engagement and promote mastery-level competency. One such approach draws upon the well-recognised educational benefits of peer-assisted learning that can be further enhanced using gamification to motivate learners to both design and review assessment activities for their peers and answer those created by others. This toolbox article describes the educational principles that underpin gamified peer-led assessment (PLA) and offers practical recommendations for clinical teachers considering implementing such schemes in their own institutions. We draw upon our collective expertise in both designing and evaluating a formal dedicated online PLA platform (BH and JW) and providing informal PLA opportunities within an undergraduate curriculum (HT and BH).
Polyphenol removal with ultrasound-assisted ethanol extraction from defatted walnut powder: Optimization of conditions and effect on functional properties of protein isolates.

BACKGROUND Walnut kernels are high in polyphenols (PP), which causes low protein solubility, limiting the use of walnut protein in the food industry. To obtain the best technical parameters of the dephenolization treatment, the defatted walnut powder were dephenolized using ultrasound-assisted ethanol extraction (UAE), and the response surface optimization was performed on the basis of single factor. On this basis, the effects of dephenolization on the solubility, emulsifying properties and foaming properties of walnut protein isolates (WPI) were compared to those of defatted walnut powder without dephenolization. RESULTS The results showed that PP extraction in the UAE could significantly increase PP yield. The optimal process parameters were as follows: 51% (v/v) ethanol concentration, 140 W ultrasound power, 10 min extraction time, 30 °C ultrasound temperature, and a material-liquid ratio of 1:30 (w/v). The results revealed that the UAE dephenolization treatment significantly improved the functionality of WPI and that the functionality of the dephenolized WPI by UAE was superior to that of the protein without dephenolization, and that the functionality of both walnut proteins was the worst at pH 5, with solubility of 5.31% and 4.86%, EAI of 24.95 and 19.91 m2 /g, and FC of 3.66% and 2.94%, respectively; and the best at pH 11, with solubility of 82.35%, 73.55%, EAI of 46.35, 37.28 m2 /g, and FC of 35.85%, 18.87%, respectively. CONCLUSION The study found that dephenolization by UAE can significantly improve the functionality of WPI, and this method should be promoted and used in walnut and walnut protein processing industries. This article is protected by copyright. All rights reserved.
Development of a Rasch-Built Amyotrophic Lateral Sclerosis Impairment Multidomain Scale to Measure Disease Progression in ALS

Background and Objectives Current scales used in amyotrophic lateral sclerosis (ALS) attempt to summarize different functional domains or “dimensions” into 1 overall score, which may not accurately characterize the individual patient's disease severity or prognosis. The use of composite score risks declaring treatments ineffective if not all dimensions of ALS disease progression are affected equally. We aimed to develop the ALS Impairment Multidomain Scale (AIMS) to comprehensively characterize disease progression and increase the likelihood of identifying effective treatments. Methods The Revised ALS Functional Rating Scale (ALSFRS-R) and a preliminary questionnaire, based on literature review and patient input, were completed online by patients from the Netherlands ALS registry at bimonthly intervals over a period of 12 months. A 2-week test-retest, factor analysis, Rasch analysis, and a signal-to-noise optimization strategy were performed to create a multidomain scale. Reliability, longitudinal decline, and associations with survival were evaluated. The sample size required to detect a 35% reduction in progression rate over 6 or 12 months was assessed for a clinical trial that defines the ALSFRS-R or AIMS subscales as a primary endpoint family. Results The preliminary questionnaire, consisting of 110 questions, was completed by 367 patients. Three unidimensional subscales were identified, and a multidomain scale was constructed with 7 bulbar, 11 motor, and 5 respiratory questions. Subscales fulfilled Rasch model requirements, with excellent test-retest reliability of 0.91–0.94 and a strong relationship with survival (p < 0.001). Compared with the ALSFRS-R, signal-to-noise ratios were higher as patients declined more uniformly per subscale. Consequently, the estimated sample size reductions achieved with the AIMS compared with those achieved with the ALSFRS-R were 16.3% and 25.9% for 6-month and 12-month clinical trials, respectively. Discussion We developed the AIMS, consisting of unidimensional bulbar, motor, and respiratory subscales, which may characterize disease severity better than a total score. AIMS subscales have high test-retest reliability, are optimized to measure disease progression, and are strongly related to survival time. The AIMS can be easily administered and may increase the likelihood of identifying effective treatments in ALS clinical trials.
The Diversity-Multiplexing Tradeoff of Secret-Key Agreement Over Multiple Antenna Channels

We study the problem of secret-key agreement between two legitimate parties, Alice and Bob, in the presence of an eavesdropper Eve. There is a public channel with unlimited capacity that is available to the legitimate parties and is also observed by Eve. Our focus is on Rayleigh fading quasistatic channels. The legitimate receiver and the eavesdropper are assumed to have perfect channel knowledge of their channels. We study the system in the high-power regime. First, we define the secret-key diversity gain and the secret-key multiplexing gain. Second, we establish the secret-key diversity multiplexing tradeoff (DMT) under no channel state information (CSI) at the transmitter (CSI-T). The eavesdropper is shown to “steal” only transmit antennas. We show that, like the DMT without secrecy constraint, the secret-key DMT is the same either with or without full channel state information at the transmitter. This insensitivity of secret-key DMT toward CSI-T features a fundamental difference between secret-key agreement and the wiretap channel, in which secret DMT depends heavily on CSI-T. Finally, we present several secret-key DMT-achieving schemes in case of full CSI-T. We argue that secret DMT-achieving schemes are also key DMT-achieving. Moreover, we show formally that artificial noise (AN), likewise zero-forcing (ZF), is DMT-achieving. We also show that the public feedback channel improves the outage performance without having any effect on the DMT.
Hippocampal CA3 inhibitory neurons receive extensive noncanonical synaptic inputs from CA1 and subicular complex

Hippocampal CA3 is traditionally conceptualized as a brain region within a unidirectional feedforward trisynaptic pathway that links major hippocampal subregions. Recent genomic and viral tracing studies indicate that the anatomical connectivity of CA3 and the trisynaptic pathway is more complex than initially expected and suggests that there may be cell type–specific input gradients throughout the three‐dimensional hippocampal structure. In several recent studies using multiple viral tracing approaches, we describe subdivisions of the subiculum complex and ventral hippocampal CA1 that show significant back projections to CA1 and CA3 excitatory neurons. These novel connections form “noncanonical” circuits that run in the opposite direction relative to the well‐characterized feedforward pathway. Diverse subtypes of GABAergic inhibitory neurons participate within the trisynaptic pathway. In the present study, we have applied monosynaptic retrograde viral tracing to examine noncanonical synaptic inputs from CA1 and subicular complex to the inhibitory neuron in hippocampal CA3. We quantitatively mapped synaptic inputs to CA3 inhibitory neurons to understand how they are connected within and beyond the hippocampus formation. Major brain regions that provide typical inputs to CA3 inhibitory neurons include the medial septum, the dentate gyrus, the entorhinal cortex, and CA3. Noncanonical inputs from ventral CA1 and subicular complex to CA3 inhibitory neurons follow a proximodistal topographic gradient with regard to CA3 subregions. We find novel noncanonical circuit connections between inhibitory CA3 neurons and ventral CA1, subiculum complex, and other brain regions. These results provide a new anatomical connectivity basis to further study the function of CA3 inhibitory neurons.
Optimal Rate of Convergence for Empirical Quantiles and Distribution Functions for Time Series

Given a stationary sequence Xkk∈Z , we are interested in the rate of convergence in the central limit theorem of the empirical quantiles and the empirical distribution function. Under a general notion of weak dependence, we show a Berry–Esseen result with optimal rate n−1/2. The setup includes many prominent time series models, such as functions of ARMA or (augmented) GARCH processes. In this context, optimal Berry–Esseen rates for empirical quantiles appear to be novel.