Miracle-dz/UniFAR-FTUs huggingface dataset:
Oxidation behaviour of Super 304H stainless steel in supercritical water

Oxidation of Super 304H steel in supercritical water at 600°C and 25 MPa was investigated, for the oxidation time of up to 1000 h. The oxidation kinetics approximately followed a parabolic law. The composition and microstructure of the oxide were investigated using the SEM equipped with EDS, EBSD and XRD. The phase compositions of the oxide evolve with increasing time. Cr2O3 was present at the initial stage and not detected while Fe2O3 appeared at longer time. EBSD indicated that continuous Cr2O3 formed at the interface of oxide and matrix for HR3C at 600°C for 40 h but only scattered Cr2O3 can be observed for 200 h. After the formation of a thin Fe–Cr–Ni oxide film on the Super 304H steel surface, the Fe-rich outer nodular oxide begins to grow and forms a continuous layer after 1000 h. The growth process of Super304H steel in supercritical water was discussed.
‘Implementing a broad quality of life tool for determining care wishes and needs of older adults living at home

ABSTRACT The aim was to investigate the views of stakeholders on the practical relevance of a broad quality of life (QoL) outcome tool for care in older adults: the Extended Quality of Life Tool (EQLT). We conducted individual interviews and focus groups with a variety of stakeholders involved in the care for older adults which were analyzed using a framework analysis. Stakeholders considered relevant: focus on the client perspective; perspective on QoL broader than health; the possibility to take diversity into account; and the possibility to determine a minimum level of QoL. Three facilitators for implementation of the tool were mentioned as well as four barriers. The EQLT can support conversations with clients about their needs and wishes, thus enabling decisions about care services based on a broad set of domains of QoL. Implementation of the tool should take into account the facilitators and barriers identified in the current study.
Human Pose Estimation based on Attention Multi-resolution Network

Recently, multi-resolution neural networks, which combine features of different resolutions, have achieved good results in human pose estimation tasks. In this paper, we propose an attention-mechanism-based multi-resolution network, which adds an attention mechanism to the High-Resolution Network (HRNet) to enhance the feature representation of the network. It improves the ability of networks with different resolutions to extract key features from images, and causes the output to contain more effective multi-resolution representation information, so that the corresponding point positions of human joints can be estimated more accurately. Experiments on the MPII and COCO datasets, and verification on the MPII datasets, obtained an average accuracy of 90.3% under the PCKh@0.5 evaluation standard, and good results were also achieved on the COCO dataset (with an AP of 76.5). The experimental results show that our network model is effective in improving the accuracy of key point estimation in the human pose estimation task.
The value of C-reactive protein/albumin, fibrinogen/albumin, and neutrophil/lymphocyte ratios in predicting the severity of CoVID-19.

OBJECTIVE This retrospective study aimed to determine the predictive values of the C-reactive protein (CRP)/albumin ratio (CAR), fibrinogen/albumin ratio (FAR), and neutrophil/lymphocyte ratio (NLR) parameters, which reflect the systemic inflammatory status, for the severity of COVID-19. METHODS A total of 188 patients diagnosed with COVID-19 were enrolled in this study. Among them, 118 were in the severe group, and 70 were in the non-severe group. Levels of albumin, CRP, D-dimer, procalcitonin, fibrinogen, and hemoglobin; leukocyte, neutrophil, lymphocyte, and monocyte counts; and the FAR, CAR, and NLR were compared between the two groups. RESULTS The CAR, FAR, and NLR values were significantly higher in the severe group compared to the non-severe group. CAR, FAR, and NLR were positively correlated with leukocyte and neutrophil counts and CRP, procalcitonin, and fibrinogen levels. On the other hand, they were inversely correlated with monocyte (except for NLR) and lymphocyte counts. Receiver operator characteristic analysis showed that the area under the curve (AUC) for CAR, FAR, and NLR was 0.841, 0.737, and 0.802, respectively. CONCLUSIONS Our investigation revealed that the CAR, FAR, and NLR indices can be used to predict the severity of COVID-19, among which CAR was the best predictor of severe COVID-19.
Future Network Traffic Matrix Synthesis and Estimation Based on Deep Generative Models

Traffic matrices (TMs) contain information that is essential for network management, traffic engineering, and anomaly detection. However, constructing a TM through direct traffic measurements has a high administrative and computational cost. A more feasible approach is to estimate the TM from the easily obtainable link load measurements. In this paper, we address the issue of traffic matrix estimation (TME) from link loads using a deep generative model – namely, a variational autoencoder (VAE) – to solve the respective ill-posed inverse problem. In particular, we train the VAE with historical data (previously observed TMs) and we leverage the trained decoder to transform TME into a minimization problem in the latent space, which in turn can be solved by employing a gradient-based optimizer. Furthermore, the trained decoder can be used for traffic matrix synthesis, i.e., for generating synthetic TM examples that have “similar” properties to the samples of the training set. Finally, we explore the incremental optimization of the sequence of objectives constructed from the sequence of decoders that we obtain at different stages of the VAE training. The performance of the proposed methods is evaluated using a publicly available dataset of actual traffic matrices recorded in a real backbone network.
Workload-adaptive Vertical Hopping of A Single-legged Robot using Model-based Optimization

Frequent workload variation is inevitable when legged robots are deployed for human service tasks like package delivery. The varying workloads can be detrimental to the robustness of robots' locomotion and may even cause task failures if no adjustment of the leg controller is applied. To maintain consistent locomotion performance, this paper explores fast gait generation given system workloads using Spring-Loaded Inverted Pendulum based models and advanced Nonlinear Programming tools. Through solving the properly posed optimization problem, the optimal control trajectory can be generated within seconds to help a vertical hopper maintain the desired apex heights, with an error within ±4% under the tested workloads from 48% up to 190% of the robot's weight. The differences among the optimal control trajectories under different workloads for achieving the same or different apex heights necessitates controller adjustment to ensure workload-adaptive locomotion. Additionally, the leg's proprioceptive-only sensing of the ground reaction force during the stance phase reveals a promising way to quantify workload variation, which can then facilitate to close the control loop of workload-adaptive locomotion in the near future.
The Interleukin-33–Group 2 Innate Lymphoid Cell Axis Represents a Potential Adjuvant Target To Increase the Cross-Protective Efficacy of Influenza Vaccine

Current influenza vaccines, although capable of protecting against predicted viruses/strains included in the vaccine, are inept at providing cross-protection against emerging/novel strains. Thus, we are in critical need of a universal vaccine that can protect against a wide range of influenza viruses. ABSTRACT Interleukin-33 (IL-33) is a multifunctional cytokine that mediates type 2-dominated immune responses. In contrast, the role of IL-33 during viral vaccination, which often aims to induce type 1 immunity, has not been fully investigated. Here, we examined the effects of IL-33 on influenza vaccine responses. We found that intranasal coadministration of IL-33 with an inactivated influenza virus vaccine increases vaccine efficacy against influenza virus infection, not only with the homologous strain but also with heterologous strains, including the 2009 H1N1 influenza virus pandemic strain. Cross-protection was dependent on group 2 innate lymphoid cells (ILC2s), as the beneficial effect of IL-33 on vaccine efficacy was abrogated in ILC2-deficient C57BL/6 Il7rCre/+ Rorafl/fl mice. Furthermore, mechanistic studies revealed that IL-33-activated ILC2s potentiate vaccine efficacy by enhancing mucosal humoral immunity, particularly IgA responses, potentially in a Th2 cytokine-dependent manner. Our results demonstrate that IL-33-mediated activation of ILC2s is a critical early event that is important for the induction of mucosal humoral immunity, which in turn is responsible for cross-strain protection against influenza. Thus, we reveal a previously unrecognized role for the IL-33–ILC2 axis in establishing broadly protective and long-lasting humoral mucosal immunity against influenza, knowledge that may help in the development of a universal influenza vaccine. IMPORTANCE Current influenza vaccines, although capable of protecting against predicted viruses/strains included in the vaccine, are inept at providing cross-protection against emerging/novel strains. Thus, we are in critical need of a universal vaccine that can protect against a wide range of influenza viruses. Our novel findings show that a mucosal vaccination strategy involving the activation of lung ILC2s is highly effective in eliciting cross-protective humoral immunity in the lungs. This suggests that the biology of lung ILC2s can be exploited to increase the cross-reactivity of commercially available influenza subunit vaccines.
Monte Carlo-derived ionization chamber correction factors in therapeutic carbon ion beams

The accuracy of electromagnetic transport in the GEANT4 Monte Carlo (MC) code was investigated for carbon ion beams and ionization chamber (IC)-specific beam quality correction factors were calculated. This work implemented a Fano cavity test for carbon ion beams in the 100–450 MeV/u energy range to assess the accuracy of the default electromagnetic physics parameters. The Urban and the Wentzel-VI multiple Coulomb scattering models were evaluated and the impact of maxStep, dRover, and final range parameters on the accuracy of the transport algorithm was investigated. The optimal production thresholds for an accurate calculation of fQ values, which is the product of the water-to-air stopping power ratio and the IC-specific perturbation correction factor, were also studied. The fQ correction factors were calculated for a cylindrical and a parallel-plate IC using carbon ions in the 150–450 MeV/u energy range. Modifying the default electromagnetic physics parameters resulted in a maximum deviation from theory of 0.3%. Therefore, the default EM parameters were used for the remainder of this work. The fQ factors were found to converge for both ICs with decreasing production threshold distance below 5 μm. The fQ values obtained in this work agreed with the TRS-398 stopping power ratios and other previously reported results within uncertainty. This study highlights an accurate MC-based technique to calculate the combined stopping power ratio and the perturbation correction factor for any IC in carbon ion beams.
Nanobodies as allosteric modulators of Parkinson’s disease–associated LRRK2

Mutations in the gene coding for Leucine-Rich Repeat Kinase 2 (LRRK2) are a leading cause of the inherited form of Parkinson’s disease (PD), while LRRK2 overactivation is also associated with the more common idiopathic form of PD. LRRK2 is a large multi-domain protein, including a GTPase as well as a Ser/Thr protein kinase domain. Common disease-causing mutations increase LRRK2 kinase activity, presenting LRRK2 as an attractive target for inhibitory drug design. Currently, drug development has mainly focused on ATP-competitive kinase inhibitors. Here, we report the identification and characterization of a variety of Nanobodies that bind to different LRRK2 domains and inhibit or activate LRRK2 activity in cells and in vitro. Importantly, diverse groups of Nanobodies were identified that inhibit LRRK2 kinase activity through a mechanism that does not involve binding to the ATP pocket or even to the kinase domain. Moreover, while certain Nanobodies completely inhibit the LRRK2 kinase activity, we also identified Nanobodies that specifically inhibit the phosphorylation of Rab protein substrates. Finally, in contrast to current type-I kinase inhibitors, the studied kinase-inhibitory Nanobodies did not induce LRRK2 microtubule association. These comprehensively characterized Nanobodies represent versatile tools to study the LRRK2 function and mechanism, and can pave the way toward novel diagnostic and therapeutic strategies for PD.
Early Decoding for Gaussian Broadcast Channels with Heterogeneous Blocklength Constraints

In this work, we investigate a two-user Gaussian broadcast channel (GBC) with heterogeneous blocklength constraints, specified according to users' channel output signal to noise ratios (SNRs). Unlike traditional GBC where two users have the same blocklength constraints, here the user with higher output SNR may have a shorter blocklength constraint. Then it is unclear whether this user can decode the interference to perform successive interference cancellation (SIC) or not. We argue that with sufficient large output SNR, this user can invoke the technique named as the early decoding to decode the interference. Then SIC can proceed. We derive an explicit lower bound on the necessary blocklength for successful early decoding, using an independent and identically distributed Gaussian input, given a maximal input power constraint and an average error probability constraint. A huge SNR gain can be achieved over treating interference as noise when SIC is applied with the aid of early decoding.
Recent insights into the pathogenesis of autoimmune hypophysitis

ABSTRACT Introduction Hypophysitis is an inflammation of the pituitary gland and a rare case of hypopituitarism. Despite the expanding spectrum of histological variants and causative agents, its pathogenesis is far to be fully understood. The present review is focused on recent evidence concerning the pathogenesis of autoimmune hypophysitis by searching through online databases like MEDLINE and Scopus up to May 2021. Areas covered Hypophysitis frequently develops in the context of a strong autoimmune background, including a wide spectrum of subtypes ranging from the commonest form of lymphocytic hypophysitis to the newly described and less common IgG4-, anti-PIT-1, and ICI-induced forms. A peculiar combination of genetic predisposition, pituitary damage and immunological setting represents the pathogenetic basis of autoimmune hypophysitis, which is characterized by diffuse infiltration of the gland by lymphocytes and variable degrees of fibrosis followed by pituitary cell destruction. Anti-pituitary antibodies (APA) have been described in sera from patients suffering from autoimmune hypophysitis, though their pathophysiological significance remains largely unknown and their diagnostic value limited. Expert opinion In recent years hypophysitis has gained interest due to the increased number of new diagnoses and the recognition of novel subtypes. Further studies could lead to improvements in biochemical/immunological diagnosis and targeted treatments.
Songbird subthalamic neurons signal song timing and error and project to dopaminergic midbrain

Skill learning requires motor output to be evaluated against internal performance benchmarks. In songbirds, ventral tegmental area (VTA) dopamine neurons (DA) signal performance errors important for learning, but it remains unclear which brain regions project VTA and how these inputs may implement the sensorimotor comparisons necessary for error computation. Here we find that the songbird subthalamic nucleus (STN) projects to VTA and that STN microstimulation can excite VTA neurons. We also discover that STN receives inputs from auditory cortical and ventral pallidal brain regions previously implicated in song evaluation. In the first neural recordings from songbird STN, we discover that the activity of most STN neurons is associated with body movements and not singing, but a small fraction of neurons exhibits precise song timing and performance error signals consistent with performance evaluation. Together our results implicate the STN-VTA projection as an evolutionarily conserved pathway important for motor learning and expand the territories of songbird brain associated with song learning. New & Noteworthy Songbird subthalamic (STN) neurons exhibit song-timing and performance error signals and are interconnected with auditory pallium, ventral pallidum and ventral tegmental area, three areas important for song learning.
Association Between LIN28A Gene Polymorphisms and Glioma Susceptibility in Chinese Children

Gliomas are the most prevalent brain tumors among children and adolescents. The occurrence and development of various malignant tumors is closely related with LIN28A gene, but its relationship with glioma susceptibility has not been widely discovered. In this case-control study, we conducted four single nucleotide polymorphisms (SNPs) (rs3811464 G>A, rs3811463 T>C, rs34787247 G>A, and rs11247957 G>A) of LIN28A gene to investigate whether they increase the risk of glioma. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate their relationship. There was no significant correlation between four SNPs and glioma risk in single polymorphism and conjoint analysis. However, in stratification analysis, we found that rs3811463 TC/CC may add to the risk of glioma with clinical stage III (adjusted OR = 3.16, 95% CI = 1.15-8.70, P = .026) or stage III+IV patients (adjusted OR = 2.05, 95% CI = 1.02-4.13, P = .044). Our research suggested that four SNPs of LIN28A gene have a weak relationship with the risk of glioma in Chinese children. LIN28A rs3811463 TC/CC may increase the possibility of glioma in clinical stage III or stage III+IV patients which need larger samples and further confirmation.
Compact diffractive optics for THz imaging

We present a compact diffractive silicon-based multilevel phase Fresnel lens (MPFL) with up to 50 mm in diameter and a numerical aperture up to 0.86 designed and fabricated for compact terahertz (THz) imaging systems. The laser direct writing technology based on a picosecond laser was used to fabricate diffractive optics on silicon with a different number of phase quantization levels P reaching an almost kinoform spherical surface needed for efficient THz beam focusing. Focusing performance was investigated by measuring Gaussian beam intensity distribution in the focal plane and along the optical axis of the lens. The beam waist and the focal depth for each MPFL were evaluated. The influence of the phase quantization number on the focused beam amplitude was estimated, and the power transmission efficiency reaching more than 90% was revealed. The THz imaging of less than 1 mm using a robust 50 mm diameter multilevel THz lens was achieved and demonstrated at 580 GHz frequency.
An Implementation of Multi-Chip Architecture for Real-Time Ray Tracing Based on Parallel Frame Rendering

In this paper, we propose a multi-chip architecture based on parallel frame rendering suitable for real-time ray tracing in dynamic scenes. In multi-chip architecture with the commonly used screen partitioning method, the acceleration structure data, such as a tree, updated in a dynamic scene must be transmitted to each chip. In the proposed frame division method, a tree build and ray tracing are performed on the same chip, and each frame is allocated to a predesignated multi-chip. Thus, the proposed method can achieve scalable performance improvement not only of ray tracing but also of a tree build. We implemented a multi-chip architecture on three field-programmable gate array (FPGA) boards and built 12 ray-tracing cores in the FPGA chip of each board. This configuration means that the inter-chip operates using the frame division method, while the inner chip operates using the screen partitioning method. The results of experiments showed that the proposed multi-chip architecture improved frames per second (FPS) performance by an average of 2.83 times compared to a single-chip architecture.
COVID-19 disruption to family medicine residency curriculum: results from a 2020 US programme directors survey

Objective This research project examined the effects of the COVID-19 pandemic on the required curriculum in graduate medical education for family medicine residencies. Design Our questions were part of a larger omnibus survey conducted by the Council of Academic Family Medicine Educational Research Alliance. Data were collected from 23 September to 16 October 2020. Setting This study was set in the USA. Participants Emails were sent to 664 family medicine programme directors in the USA. Of the 312 surveys returned, 35 did not answer our questions and were excluded, a total of 277 responses (44%) were analysed. Results The level of disruption varied by discipline and region. Geriatrics had the highest reported disruption (median=4 on a 5-point scale) and intensive care unit had the lowest (median=1 on a 5-point scale). There were no significant differences for disruption by type of programme or community size. Conclusion Programme directors reported moderate disruption in family medicine resident education in geriatrics, gynaecology, surgery, musculoskeletal medicine, paediatrics and family medicine site during the pandemic. We are limited in generalisations about how region, type of programme, community size or number of residents influenced the level of disruption, as less than 50% of programme directors completed the survey.
Rheological Properties of Six Plant-Based Seed Gums

The rheological properties of six mucilage solutions (Guar Gum, Locust Bean Gum, Tamarind Gum, Flaxseed Gum, Artemisia Sphaerocephala Krasch Gum and Cassia Gum) have been examined. It was found that all six gums could be classified into three different types according to the changes of viscosity with increasing shear rate. Steady shear viscous properties in a range of shear rate from 0.1 to 100 s-1 were investigated in the provision of mucilage concentration, pH, temperature and salts. A non-Newtonian shear-thinning behavior was observed. The data of viscosity-shear successfully correlated Power law model. Apparent viscosity was apparently dependent on mucilage concentration increasing significantly as mass fraction went up. A marked dependence of viscosity on temperature was also observed; as temperature increased, the viscosity decreased sharply. The value n of flaxseed gum is minimum, which means it behaves the greatest shear-thinning properties. Both Guar gum and Tamarind gum possessed better acid-proof and alkali-proof advantages. The flow activation energy of ASKG is 4.3 kcal which is higher than other gums so that the influence of temperature on characteristics of viscosity is stronger. The mechanical spectra in the linear viscoelasticity region were studied in the temperature range from 20°C to 90°C, at a frequency range from 0.1 to 10 Hz. It was observed that Both elastic modulus G' and viscous modulus G" behaviors were found to be dependent on temperature and frequency. What have been investigated in this work could provide guidance for practical application in the field of food industry.