Flow simulation with locally-refined LBM

We simulate 3D fluid flow by a locally-refined lattice Boltzmann method (LBM) on graphics hardware. A low resolution LBM simulation running on a coarse grid models global flow behavior of the entire domain with low consumption of computational resources. For regions of interest where small visual details are desired, LBM simulations are performed on fine grids, which are separate grids superposed on the coarse one. The flow properties on boundaries of the fine grids are determined by the global simulation on the coarse grid. Thus, the locally refined fine-grid simulations follow the global fluid behavior, and model the desired small-scale and turbulent flow motion with their denser numerical discretization. A fine grid can be initiated and terminated at any time while the global simulation is running. It can also move inside the domain with a moving object to capture small-scale vortices caused by the object. Besides the performance improvement due to the adaptive simulation, the locally-refined LBM is suitable for acceleration on contemporary graphics hardware (GPU), since it involves only local and linear computations. Therefore, our approach achieves fast and adaptive 3D flow simulation for computer games and other interactive applications

Approximate optimum curbside utilisation for pick-up and drop-off (PUDO) and parking demands using reinforcement learning

With the uptake of automated transport, especially Pick-Up and Drop-Off (PUDO) operations of Shared Autonomous Vehicles (SAVs), the valet parking of passenger vehicles and delivery vans are envisaged to saturate our future streets. These emerging behaviours would join conventional on-street parking activities in an intensive competition for scarce curb resources. Existing curbside management approaches principally focus on those long-term parking demands, neglecting those short-term PUDO or docking events. Feasible solutions that coordinate diverse parking requests given limited curb space are still absent. We propose a Reinforcement Learning (RL) method to dynamically dispatch parking areas to accommodate a hybrid stream of parking behaviours. A partially-learning Deep Deterministic Policy Gradient (DDPG) algorithm is trained to approximate optimum dispatching strategies. Modelling results reveal satisfying convergence guarantees and robust learning patterns. Namely, the proposed model successfully discriminates parking demands of distinctive sorts and prioritises PUDOs and docking requests. Results also identify that when the demand-supply ratio situates at 2:1 to 4:1, the service rate approximates an optimal (83\%), and curbside occupancy surges to 80%. This work provides a novel intelligent dispatching model for diverse and fine-grained parking demands. Furthermore, it sheds light on deploying distinctive administrative strategies to the curbside in different contexts

Pathogen spectrum and immunotherapy in patients with anti-IFN-γ autoantibodies: A multicenter retrospective study and systematic review

BackgroundAnti-interferon-γ autoantibody (AIGA) positivity is an emerging immunodeficiency syndrome closely associated with intracellular infection in individuals without human immunodeficiency virus (HIV). However, the information on epidemiology, pathogen spectrum, and immunotherapy among these patients lack a systematic description of large data.MethodsThis systematic literature review and multicenter retrospective study aimed to describe the pathogen spectrum and review treatment strategies among patients with AIGA positivity.ResultsWe included 810 HIV-negative patients with AIGA positivity infected with one or more intracellular pathogens. Excluding four teenagers, all the patients were adults. The most common pathogen was nontuberculous mycobacteria (NTM) (676/810, 83.5%). A total of 765 NTM isolates were identified in 676 patients with NTM, including 342 (44.7%) rapid-grower mycobacteria, 273 (35.7%) slow-grower mycobacteria, and 150 (19.6%) unidentified NTM subtype. Even with long-term and intensive antimicrobial treatments, 42.6% of patients with AIGA positivity had recurrence and/or persistent infection. Sixty-seven patients underwent immunoregulatory or immunosuppressive therapy, and most (60) achieved remission. The most common treatment strategy was rituximab (27/67, 40.3%) and cyclophosphamide (22/67, 32.8%), followed by cyclophosphamide combined with glucocorticoids (8/67, 11.9%).ConclusionsIntracellular pathogen was the most common infection in patients with AIGA positivity. The predominant infection phenotypes were NTM, varicella-zoster virus, Talaromyces marneffei, and Salmonella spp., with or without other opportunistic infections. AIGA immunotherapy, including rituximab or cyclophosphamide, has yielded good preliminary results in some cases

Synthesis, characterization, and solution structure of all-conjugated polyelectrolyte diblock copoly(3- hexylthiophene)s

We report on a new class of all-conjugated polyelectrolyte diblock copoly(3-hexylthiophene)s, poly(3-hexylthiophene)-b-poly [3-[6-(N-methylimidazolium)hexyl]thiophene] (P3HT-b-P3MHT). The polyelectrolyte diblock copolymers were prepared by a catalyst-transfer Kumada polycondensation followed by quaternization of the bromohexyl side groups of the poly[3-(6-bromohexyl)thiophene] block with Nmethylimidazole. The obtained diblock copolymers have well-defined block ratios, narrow polydispersity indices, and high regioregularity. Their characterization as well as the thermal, crystalline, and optical properties, and self-assembly behavior have been investigated in detail. Transmission electron microscopy (TEM) provided evidence for solvent-induced self-assembly. A series of morphologies including short or long nanowires and nanorings could be obtained depending on the selectivity of solvents toward different blocks and the block ratios

A giant hemolymphangioma of the pancreas in a 20-year-old girl: a report of one case and review of the literature

<p>Abstract</p> <p>Background</p> <p>Hemolymphangioma of the pancreas is a very rare benign tumor. There were only six reports of this disease until December 2008. Herein, we report a case of giant hemolymphangioma of the pancreas in a 20-year-old girl.</p> <p>Case presentation</p> <p>We describe a 20-year-old girl who presented with a mass in abdominal cavity and epigastric discomfort about a week. Physical examination showed a great abdominal mass. Abdominal computed tomography showed extrinsic duodenal compression due to a large retroperitoneal tumor possibly arising from pancreas. The tumor enucleation was performed and a diagnosis of hemolymphangioma of the pancreas was made. The patient had a complication of chylous leakage, which was successfully managed. The patient is alive and well, after 26 months of follow-up, with no complaints or recurrence.</p> <p>Conclusion</p> <p>From this case and literature, we can conclude that hemolymphangioma of the pancreas in adult is a rare benign tumor, and accurate diagnosis can not be preoperatively established. Tumor resection should be performed whenever possible. The risk of recurrence seems very low.</p

Separate density and viscosity measurements of unknown liquid using quartz crystal microbalance

Aqueous liquids have a wide range of applications in many fields. Basic physical properties like the density and the viscosity have great impacts on the functionalities of a given ionic liquid. For the millions kinds of existing liquids, only a few have been systematically measured with the density and the viscosity using traditional methods. However, these methods are limited to measure the density and the viscosity of an ionic liquid simultaneously especially in processing micro sample volumes. To meet this challenge, we present a new theoretical model and a novel method to separate density and viscosity measurements with single quartz crystal microbalance (QCM) in this work. The agreement of experimental results and theocratical calculations shows that the QCM is capable to measure the density and the viscosity of ionic liquid

Robust nodal superconductivity induced by isovalent doping in Ba(Fe1−x_{1-x}Rux_x)2_2As2_2 and BaFe2_2(As1−x_{1-x}Px_x)2_2

We present the ultra-low-temperature heat transport study of iron-based superconductors Ba(Fe$_{1-x}$Ru$_x$)$_2$As$_2$ and BaFe$_2$(As$_{1-x}$P$_x$)$_2$. For optimally doped Ba(Fe$_{0.64}$Ru$_{0.36}$)$_2$As$_2$, a large residual linear term $\kappa_0/T$ at zero field and a $\sqrt{H}$ dependence of $\kappa_0(H)/T$ are observed, which provide strong evidences for nodes in the superconducting gap. This result demonstrates that the isovalent Ru doping can also induce nodal superconductivity, as P does in BaFe$_2$(As$_{0.67}$P$_{0.33}$)$_2$. Furthermore, in underdoped Ba(Fe$_{0.77}$Ru$_{0.23}$)$_2$As$_2$ and heavily underdoped BaFe$_2$(As$_{0.82}$P$_{0.18}$)$_2$, $\kappa_0/T$ manifests similar nodal behavior, which shows the robustness of nodal superconductivity in the underdoped regime and puts constraint on theoretical models.Comment: 5 pages, 4 figures - with two underdoped samples added, this paper supersedes arXiv:1106.541

Nanocone‐Modified Surface Facilitates Gas Bubble Detachment for High‐Rate Alkaline Water Splitting

Abstract: The significant amount of gas bubbles generated during high‐rate alkaline water splitting (AWS) can be detrimental to the process. The accumulation of bubbles will block the active catalytic sites and hinder the ion and electrolyte diffusion, limiting the maximum current density. Furthermore, the detachment of large bubbles can also damage the electrode's surface layer. Here, a general strategy for facilitating bubble detachment is demonstrated by modifying the nickel electrode surface with nickel nanocone nanostructures, which turns the surface into underwater superaerophobic. Simulation and experimental data show that bubbles take a considerably shorter time to detach from the nanocone‐modified nickel foil than the unmodified foil. As a result, these bubbles also have a smaller detachment size and less chance for bubble coalescence. The nanocone‐modified electrodes, including nickel foil, nickel foam, and 3D‐printed nickel lattice, all show substantially reduced overpotentials at 1000&nbsp;mA&nbsp;cm−2 compared to their pristine counterpart. The electrolyzer assembled with two nanocone‐modified nickel lattice electrodes retains &gt;95% of the performance after testing at ≈900&nbsp;mA&nbsp;cm−2 for 100&nbsp;h. The surface NC structure is also well preserved. The findings offer an exciting and simple strategy for enhancing the bubble detachment and, thus, the electrode activity for high‐rate AWS

SaliencyCut: Augmenting plausible anomalies for anomaly detection

Anomaly detection under the open-set scenario is a challenging task that requires learning discriminative features to detect anomalies that were even unseen during training. As a cheap yet effective approach, data augmentation has been widely used to create pseudo anomalies for better training of such models. Recent wisdom of augmentation methods focuses on generating random pseudo instances that may lead to a mixture of augmented instances with seen anomalies, or out of the typical range of anomalies. To address this issue, we propose a novel saliency-guided data augmentation method, SaliencyCut, to produce pseudo but more common anomalies that tend to stay in the plausible range of anomalies. Furthermore, we deploy a two-head learning strategy consisting of normal and anomaly learning heads to learn the anomaly score of each sample. Theoretical analyses show that this mechanism offers a more tractable and tighter lower bound of the data log-likelihood. We then design a novel patch-wise residual module in the anomaly learning head to extract and assess anomaly features from each sample, facilitating the learning of discriminative representations of anomaly instances. Extensive experiments conducted on six real-world anomaly detection datasets demonstrate the superiority of our method to competing methods under various settings. Codes are available at: https://github.com/yjnanan/SaliencyCut

Risk stratification and survival time of patients with gram-negative bacillary pneumonia in the intensive care unit

IntroductionPneumonia is a common infection in the intensive care unit (ICU), and gram-negative bacilli are the most common bacterial cause. The purpose of the study was to investigate the risk factors for 30-day mortality in patients with gram-negative bacillary pneumonia in the ICU, construct a predictive model, and stratify patients based on risk to assess their short-term survival.MethodsPatients admitted to the ICU with gram-negative bacillary pneumonia at Fujian Medical University Affiliated First Hospital between January 2018 and September 2020 were selected. Patients were divided into deceased and survivor groups based on whether death occurred within 30 days. Multifactorial logistic regression analysis was used to identify independent risk factors for 30-day mortality in these patients, and a predictive nomogram model was constructed based on these factors. Patients were categorized into low-, medium-, and high-risk groups according to the model's predicted probability, and Kaplan-Meier survival curves were plotted to assess short-term survival.ResultsThe study included 305 patients. Lactic acid (odds ratio [OR], 1.524, 95% CI: 1.057-2.197), tracheal intubation (OR: 4.202, 95% CI: 1.092-16.169), and acute kidney injury (OR:4.776, 95% CI: 1.632-13.978) were identified as independent risk factors for 30-day mortality. A nomogram prediction model was established based on these three factors. Internal validation of the model showed a Hosmer-Lemeshow test result of X2=5.770, P=0.834, and an area under the ROC curve of 0.791 (95% CI: 0.688-0.893). Bootstrap resampling of the original data 1000 times yielded a C-index of 0.791, and a decision curve analysis indicated a high net benefit when the threshold probability was between 15%-90%. The survival time for low-, medium-, and high-risk patients was 30 (30, 30), 30 (16.5, 30), and 17 (11, 27) days, respectively, which were significantly different.ConclusionLactic acid, tracheal intubation, and acute kidney injury were independent risk factors for 30-day mortality in patients in the ICU with gram-negative bacillary pneumonia. The predictive model constructed based on these factors showed good predictive performance and helped assess short-term survival, facilitating early intervention and treatment