Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictions of optimal heating by magnetic reversal behavior of magnetic nanowires (MNWs) with different materials

Abstract Objective Magnetic nanowires (MNWs) are potential candidates for heating in biomedical applications that require rapid and uniform heating rates, such as warming cryopreserved organs and hyperthermia treatment of cancer cells. Therefore, it is essential to determine which materials and geometries will provide the optimal heating using available alternating magnetic fields (AMF). Method Micromagnetic simulations are used to investigate the heating ability of MNWs by predicting their hysteretic behavior. MNWs composed of iron (Fe), nickel (Ni), cobalt (Co) or permalloy (FeNi alloy, Py) with different diameters (10-200 nm) are simulated using object oriented micromagnetic framework (OOMMF). Results Hysteresis loops are obtained for each simulated MNW, and the 2D/3D magnetic moment map is simulated to show the reversal mechanism. The heating ability, in terms of specific loss power (SLP), is calculated from the area of the hysteresis loop times frequency for each MNW for comparison with others. Conclusion It is estimated that a theoretical optimal heating ability of 2730 W/g can be provided by isolated Co MNWs with 50 nm diameters using a typical AMF system that can supply 72 kA/m field amplitude and 50 kHz in frequency. Generalized correlation between coercivity and size/material of MNWs is provided as a guidance for researchers to choose the most appropriate MNW as a heater for their AMF system and vice versa.
Role of large‐scale moisture advection for simulation of the MJO with increased entrainment

The intraseasonal moisture budget is analyzed in simulations with the UK Met Office climate model, which produces a reasonable representation of the Madden–Julian Oscillation (MJO) when the entrainment rate in the convective parametrization is increased by 50%. Analysis of the moisture budget shows that parametrized convection tends to dry the troposphere and that large‐scale vertical advection moistens the troposphere. These two tendencies mostly balance each other. However, the total moisture tendency is asymmetric relative to the maximum precipitation, corresponding to the recharge and discharge process of organized convection in the Tropics. This moistening before and drying after the maximum precipitation is largely due to large‐scale horizontal advection of moisture. By comparing to the control run that does not simulate a realistic MJO, we find that increasing the entrainment acts to reduce deep convection in the relatively dry environment by increasing the mixing of the dry air. As a result, large‐scale convection and large‐scale advective processes play a stronger role during the development stage, which implies that convection is necessarily better organized.
Proximal 1q21 duplication: A syndrome or a susceptibility locus?

Proximal 1q21 microduplication is an incomplete penetrance and variable expressivity syndrome. This study reports 28 new cases and summarizes data on phenotype, gender, and parental origin. Data on isolated proximal 1q21.1 microduplications (g. chr1:145,394,956–145,762,959 GRCh37/hg19) was retrieved in postnatal and prenatal “clinical cases” group, and prenatal “control group. ” The “clinical cases” cases included cases where chromosomal microarray (CMA) was performed due to congenital anomalies, autism spectrum disorder, seizures, and developmental delay/intellectual disability. The “control group” cases consisted of fetal CMA performed upon parental request despite normal nuchal translucency and anatomical second trimester fetal scans. We analyzed a local database of 27,990 cases and another cohort of 80,000 cases (including both indicated and non‐indicated cases) for population frequency analysis. A total of 62 heterozygous cases were found, including 28 index cases and 34 family members. Among the index cases, 13 (9 males, 4 females) were identified in the “clinical cases” group, of which 10 had developmental abnormalities. Parental origin was tested in 9/13 cases, and all were found to be maternally inherited. In the “control group,” which comprised non‐affected cases, of 15 cases (10 males, 5 females), only 5/11 were maternally inherited. Four cases with clinical follow‐up showed no reported neurodevelopmental abnormalities. No de‐novo cases were detected, and the population frequency in both cohorts was 1:1000. Proximal 1q21.1 microduplication is a recurrent copy number variant, associated with neurodevelopmental abnormalities. It has a greater impact on males inheriting it from their mothers than females from their fathers.
Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15

Estimating the accuracy of quaternary structural models of protein complexes and assemblies (EMA) is important for predicting quaternary structures and applying them to studying protein function and interaction. The pairwise similarity between structural models is proven useful for estimating the quality of protein tertiary structural models, but it has been rarely applied to predicting the quality of quaternary structural models. Moreover, the pairwise similarity approach often fails when many structural models are of low quality and similar to each other. To address the gap, we developed a hybrid method (MULTICOM_qa) combining a pairwise similarity score (PSS) and an interface contact probability score (ICPS) based on the deep learning inter-chain contact prediction for estimating protein complex model accuracy. It blindly participated in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 and ranked first out of 24 predictors in estimating the global accuracy of assembly models. The average per-target correlation coefficient between the model quality scores predicted by MULTICOM_qa and the true quality scores of the models of CASP15 assembly targets is 0.66. The average per-target ranking loss in using the predicted quality scores to rank the models is 0.14. It was able to select good models for most targets. Moreover, several key factors (i.e., target difficulty, model sampling difficulty, skewness of model quality, and similarity between good/bad models) for EMA are identified and analayzed. The results demonstrate that combining the multi-model method (PSS) with the complementary single-model method (ICPS) is a promising approach to EMA. The source code of MULTICOM_qa is available at https://github.com/BioinfoMachineLearning/MULTICOM_qa.
Statistical Shape Spaces for 3D Data: a Review

Methods and systems for capturing 3D geometry are becoming increasingly commonplace–and with them a plethora of 3D data. Much of this data is unfortunately corrupted by noise, missing data, occlusions or other outliers. However, when we are interested in the shape of a particular class of objects, such as human faces or bodies, we can use machine learning techniques, applied to clean, registered databases of these shapes, to make sense of raw 3D point clouds or other data. This has applications ranging from virtual change rooms to motion and gait analysis to surgical planning depending on the type of shape. In this chapter, we give an overview of these techniques, a brief review of the literature, and comparative evaluation of two such shape spaces for human faces.
How do we…consistently provide high‐dose granulocyte products for transfusions in neutropenic patients?

The therapeutic use of granulocyte transfusions for the treatment of infections in immunocompromised patients has been a controversial practice. Randomized controlled trials suggest that benefit may be provided when a high‐dose product, defined as providing a dose of at least 0.6 × 109/kg, is offered. Here we describe the collection process and granulocyte product yield over a four‐year period at a donation center supplying a large, tertiary academic medical center.
CONTEXT AND FOCUS PROJECTION. A COMPOSITIONAL, INTONATION-BASED ACCOUNT OF FOCUS INTERPRETATION

Theories of focus semantics can be divided into compositional, interpretationoriented approaches (Rooth 1985, Rooth 1992, Krifka 1992) and production-oriented approaches (Schwarzschild 1999). The current paper attempts to bring these different perspectives together and profit from their respective strengths. A compositional algorithm will be developed which starts out from intonation instead of abstract focus; in other words, the algorithm integrates a compositional, givenness-based version of focus projection. Some explications to the notion GIVEN will be presented. Givenness and contrast are shown as two independent modules determining discourse congruence. Finally, the algorithm will be spelled out in Bottom-Up DRT (Kamp, van Genabith and Reyle 2004).
Managing Fear During Pandemics: Risks and Opportunities

Fear is an emotion triggered by the perception of danger and motivates safety behaviors. Within the context of the COVID-19 pandemic, there were ample danger cues (e.g., images of patients on ventilators) and a high need for people to use appropriate safety behaviors (e.g., social distancing). Given this central role of fear within the context of a pandemic, it is important to review some of the emerging findings and lessons learned during the COVID-19 pandemic and their implications for managing fear. We highlight factors that determine fear (i.e., proximity, predictability, and controllability) and review several adaptive and maladaptive consequences of fear of COVID-19 (e.g., following governmental health policies and panic buying). Finally, we provide directions for future research and make policy recommendations that can promote adequate health behaviors and limit the negative consequences of fear during pandemics.
Risk Factors for Recurrence and the Role of Radiotherapy in Low-grade Myofibroblastic Sarcoma

Low-grade myofibroblastic sarcoma (LGMS) is a rare malignancy that commonly occurs in the head and neck region. The role of radiotherapy has been unclear in treating LGMS and the risk factors for recurrence have remained undefined. The objective of this study is to determine risk factors for the recurrence of LGMS in the head and neck as well as the role of radiotherapy in the treatment of LGMS. A comprehensive review of the literature was performed through Pubmed leading to the inclusion of 36 articles after our inclusion and exclusion criteria were applied. Continuous variables were analyzed with a 2-tail unpaired t test. Categorical variables were assessed with the χ2 test or Fisher exact test. Logistic regression and multivariable logistic regression analysis with 95% CIs were used to obtain odds ratios. LGMS most commonly occurred in the oral cavity (49.2%). Half of all recurrences occurred in the paranasal sinuses/skull base. LGMS occurring at the paranasal sinuses/skull base had a significantly increased risk of recurrence compared with other subsites within the head and neck (odds ratio: −40; 95% CI: 2.190, 762.005; P = 0.013). The average time to recurrence of LGMS was 19.2 months. Adjuvant treatment with radiation did not improve recurrence rates. Sex, tumor size, or bony involvement were not found as risk factors for recurrence. Patients with LGMS of the paranasal sinuses and skull base are at high risk for recurrence and should be monitored closely. The role of adjuvant radiation treatment in these patients remains unclear.
Impact of the pandemic and its containment measures in Europe upon aspects of affective impairments: a Google Trends informetrics study

Abstract Background In late 2019, a new virus began spreading in Wuhan, China. By the end of 2021, more than 260 million people worldwide had been infected and 5.2 million people had died because of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Various countermeasures have been implemented to contain the infections, depending on the country, infection prevalence, and political and infrastructural resources. The pandemic and the containment measures have induced diverse psychological burdens. Using internet queries as a proxy, this study examines the psychological consequences on a European level of SARS-CoV-2 containment measures. Methods Using informetric analyses, this study reviews within 32 European countries a total of 28 search parameters derived from the International Statistical Classification of Diseases and Related Health Problems (ICD-10) as aspects of affective disorder. Results Our results show that there are several psychological aspects which are significantly emphasized during the pandemic and its containment measures: ‘anxiety’, ‘dejection’, ‘weariness’, ‘listlessness’, ‘loss of appetite’, ‘loss of libido’, ‘panic attack’, and ‘worthlessness’. These terms are significantly more frequently part of a search query during the pandemic than before the outbreak. Furthermore, our results revealed that search parameters such as ‘psychologist’, ‘psychotherapist’, ‘psychotherapy’ have increased highly significantly (p < 0.01) since the pandemic. Conclusions The psychological distress caused by the pandemic correlates significantly with the frequency of people searching for psychological and psychotherapeutic support on the Internet.
Gp05, a Prophage-Encoded Virulence Factor, Contributes to Persistent Methicillin-Resistant Staphylococcus aureus Endovascular Infection

Persistent endovascular infections are often caused by MRSA strains that are susceptible to anti-MRSA antibiotics in vitro by CLSI breakpoints. Thus, the persistent outcome represents a unique variant of traditional antibiotic resistance mechanisms and a significant therapeutic challenge. Prophage, a critical mobile genetic element carried by most MRSA isolates, provides their bacterial host with metabolic advantages and resistance mechanisms. ABSTRACT Persistent methicillin-resistant Staphylococcus aureus (MRSA) endovascular infections represent a serious public health threat. We recently demonstrated that the presence of a novel prophage ϕSA169 was associated with vancomycin (VAN) treatment failure in experimental MRSA endocarditis. In this study, we assessed the role of a ϕSA169 gene, ϕ80α_gp05 (gp05), in VAN-persistent outcome using gp05 isogenic MRSA strain sets. Of note, Gp05 significantly influences the intersection of MRSA virulence factors, host immune responses, and antibiotic treatment efficacy, including the following: (i) activity of the significant energy-yielding metabolic pathway (e.g., tricarboxylic acid cycle); (ii) carotenoid pigment production; (iii) (p)ppGpp (guanosine tetra- and pentaphosphate) production, which activates the stringent response and subsequent downstream functional factors (e.g., phenol-soluble modulins and polymorphonuclear neutrophil bactericidal activity); and (iv) persistence to VAN treatment in an experimental infective endocarditis model. These data suggest that Gp05 is a significant virulence factor which contributes to the persistent outcomes in MRSA endovascular infection by multiple pathways. IMPORTANCE Persistent endovascular infections are often caused by MRSA strains that are susceptible to anti-MRSA antibiotics in vitro by CLSI breakpoints. Thus, the persistent outcome represents a unique variant of traditional antibiotic resistance mechanisms and a significant therapeutic challenge. Prophage, a critical mobile genetic element carried by most MRSA isolates, provides their bacterial host with metabolic advantages and resistance mechanisms. However, how prophage-encoded virulence factors interact with the host defense system and antibiotics, driving the persistent outcome, is not well known. In the current study, we demonstrated that a novel prophage gene, gp05, significantly impacts tricarboxylic acid cycle activity, stringent response, and pigmentation, as well as vancomycin treatment outcome in an experimental endocarditis model using isogenic gp05 overexpression and chromosomal deletion mutant MRSA strain sets. The findings significantly advance our understanding of the role of Gp05 in persistent MRSA endovascular infection and provide a potential target for development of novel drugs against these life-threatening infections.
Genotoxic effect of iron oxide (Fe2O3) nanoparticles on Triticum aestivum (wheat)

Industrial activities and unconscious consumption of natural resources cause environmental pollution with the rapid increase in the world population. As a result of the widespread use of iron oxide nanoparticles (Fe2O3 NP) with nano‐industrial activities, it is predicted that this NP will accumulate in the air, water, and soil. In the present study, the purpose was to find out the genotoxic effects on root meristem cells of the Triticum aestivum L. plant, which is an indicator organism exposed to 20–40 nm Fe2O3 NPs at different concentrations (100, 200, and 400 ppm). The amount of Fe2O3 NP accumulated in T. aestivum used in the study was determined with x‐ray diffraction (XRD) spectroscopy, scanning electron microscopy (SEM), SEM element map, and EDS characteristic spectrum. All concentrations of Fe2O3 NP caused significant decreases in the mitotic index. Fe2O3 NPs significantly increased the frequency of mitotic abnormalities in T. aestivum root tip cells at all treatment times and all concentrations when compared to the control. Fe2O3 NPs were formed by various mitotic abnormalities such as loss of genetic material, deconstructed prophase, adhesion, chromosome groupings in metaphase, deconstructed metaphase, C‐Metaphase, chromosomal loss, chromosomal fracture, polyploidy, deconstructed anaphase, lagging chromosome, fragment, polar deviation, bridging, propagation, asynchronous division, star anaphase, multipolarity, and deconstructed telophase. All these results show that Fe2O3 NPs are genotoxic and clastogenic and may also cause DNA damage. Briefly, these data show that Fe2O3 NPs taken by organisms may pose a danger to the organism and the upper consumer. These findings also show that the production and use of Fe2O3 NPs, which affect organisms, must be controlled, and ultimately, be safely disposed of to reduce their bioaccumulation.
Four Axiomatic Characterizations of the Integrated Gradients Attribution Method

Deep neural networks have produced significant progress among machine learning models in terms of accuracy and functionality, but their inner workings are still largely unknown. Attribution methods seek to shine a light on these"black box"models by indicating how much each input contributed to a model's outputs. The Integrated Gradients (IG) method is a state of the art baseline attribution method in the axiomatic vein, meaning it is designed to conform to particular principles of attributions. We present four axiomatic characterizations of IG, establishing IG as the unique method to satisfy different sets of axioms among a class of attribution methods.
Decision-Dependent Distributionally Robust Markov Decision Process Method in Dynamic Epidemic Control

In this paper, we present a Distributionally Robust Markov Decision Process (DRMDP) approach for addressing the dynamic epidemic control problem. The Susceptible-Exposed-Infectious-Recovered (SEIR) model is widely used to represent the stochastic spread of infectious diseases, such as COVID-19. While Markov Decision Processes (MDP) offers a mathematical framework for identifying optimal actions, such as vaccination and transmission-reducing intervention, to combat disease spreading according to the SEIR model. However, uncertainties in these scenarios demand a more robust approach that is less reliant on error-prone assumptions. The primary objective of our study is to introduce a new DRMDP framework that allows for an ambiguous distribution of transition dynamics. Specifically, we consider the worst-case distribution of these transition probabilities within a decision-dependent ambiguity set. To overcome the computational complexities associated with policy determination, we propose an efficient Real-Time Dynamic Programming (RTDP) algorithm that is capable of computing optimal policies based on the reformulated DRMDP model in an accurate, timely, and scalable manner. Comparative analysis against the classic MDP model demonstrates that the DRMDP achieves a lower proportion of infections and susceptibilities at a reduced cost. [ FROM AUTHOR] Copyright of IISE Transactions is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
LiResolver: License Incompatibility Resolution for Open Source Software

Open source software (OSS) licenses regulate the conditions under which OSS can be legally reused, distributed, and modified. However, a common issue arises when incorporating third-party OSS accompanied with licenses, i.e., license incompatibility, which occurs when multiple licenses exist in one project and there are conflicts between them. Despite being problematic, fixing license incompatibility issues requires substantial efforts due to the lack of license understanding and complex package dependency. In this paper, we propose LiResolver, a fine-grained, scalable, and flexible tool to resolve license incompatibility issues for open source software. Specifically, it first understands the semantics of licenses through fine-grained entity extraction and relation extraction. Then, it detects and resolves license incompatibility issues by recommending official licenses in priority. When no official licenses can satisfy the constraints, it generates a custom license as an alternative solution. Comprehensive experiments demonstrate the effectiveness of LiResolver, with 4.09% false positive (FP) rate and 0.02% false negative (FN) rate for incompatibility issue localization, and 62.61% of 230 real-world incompatible projects resolved by LiResolver. We discuss the feedback from OSS developers and the lessons learned from this work. All the datasets and the replication package of LiResolver have been made publicly available to facilitate follow-up research.
Self-enhanced coherent harmonic amplification in seeded free-electron lasers

High-intensity, ultrashort, fully coherent X-ray pulses hold great potential for advancing spectroscopic techniques to unprecedented levels. Here, we propose a novel scheme for generating high-brightness and femtosecond-scale soft X-ray radiation within a seeded free-electron laser (FEL) operating at an MHz repetition rate. This scheme relies on the principles of self-modulation and superradiance. A relatively weak energy modulation of the pre-bunched electron beam is significantly amplified by the coherent radiation emitted in the self-modulator. Consequently, a coherent signal at ultra-high harmonics of the seed is achieved, and this signal is further amplified in the subsequent radiator through the fresh bunch and superradiant processes. Based on the parameters of the Shanghai soft X-ray FEL facility, three-dimensional simulations have been performed. The simulation results demonstrate that an electron beam with a laser-induced energy modulation as small as 2.3 times the slice energy spread can generate ultrashort coherent radiation pulses of around 2 GW within the water window spectral range. Moreover, the experimental results demonstrate that self-enhanced coherent energy modulation enables the production of coherent signals up to the 15th harmonic of a 266-nm seed laser. These findings indicate that the proposed scheme can facilitate the generation of high-repetition-rate seeded FEL.