Miracle-dz/UniFAR-FTUs huggingface dataset:
A Three-Dimensional Scale-Adaptive Turbulent Kinetic Energy Scheme in the WRF-ARW Model

A new three-dimensional (3D) turbulent kinetic energy (TKE) subgrid mixing scheme is developed using the Advanced Research version of the Weather Research and Forecasting (WRF) Model (WRF-ARW) to address the gray-zone problem in the parameterization of subgrid turbulent mixing. The new scheme combines the horizontal and vertical subgrid turbulent mixing into a single energetically consistent framework, in contrast to the conventionally separate treatment of the vertical and horizontal mixing. The new scheme is self-adaptive to the grid-size change between the large-eddy simulation (LES) and mesoscale limits. A series of dry convective boundary layer (CBL) idealized simulations are carried out to compare the performance of the new scheme and the conventional treatment of subgrid mixing to the WRF-ARW LES dataset. The importance of including the nonlocal component in the vertical buoyancy speciﬁcation in the newly developed general TKE-based scheme is illustrated in the comparison. The improvements of the new scheme with the conventional treatment of subgrid mixing across the gray-zone model resolutions are demonstrated through the partitioning of the total vertical ﬂux proﬁles. Results from real-case simulations show the feasibility of using the new scheme in the WRF Model in lieu of the conventional treatment of subgrid mixing.
Within-Host Rhinovirus Evolution in Upper and Lower Respiratory Tract Highlights Capsid Variability and Mutation-Independent Compartmentalization

Abstract Background Rhinovirus (RV) infections can progress from the upper (URT) to lower (LRT) respiratory tract in immunocompromised individuals, causing high rates of fatal pneumonia. Little is known about how RV evolves within hosts during infection. Methods We sequenced RV complete genomes from 12 hematopoietic cell transplant patients with infection for up to 190 days from both URT (nasal wash, NW) and LRT (bronchoalveolar lavage, BAL). Metagenomic and amplicon next-generation sequencing were used to track the emergence and evolution of intrahost single nucleotide variants (iSNVs). Results Identical RV intrahost populations in matched NW and BAL specimens indicated no genetic adaptation is required for RV to progress from URT to LRT. Coding iSNVs were 2.3-fold more prevalent in capsid over nonstructural genes. iSNVs modeled were significantly more likely to be found in capsid surface residues, but were not preferentially located in known RV-neutralizing antibody epitopes. Newly emergent, genotype-matched iSNV haplotypes from immunocompromised individuals in 2008–2010 could be detected in Seattle-area community RV sequences in 2020–2021. Conclusions RV infections in immunocompromised hosts can progress from URT to LRT with no specific evolutionary requirement. Capsid proteins carry the highest variability and emergent mutations can be detected in other, including future, RV sequences.
Shortages of Medicines to Treat COVID-19 Symptoms during the First Wave and Fourth Wave: Analysis of Notifications Reported to Registers in Austria, Italy, and Spain

The study aimed to investigate medicine shortages of critical relevance in the pandemic. A total of 487 active substances for the treatment of COVID-19-related symptoms and therapeutically similar medicines were reviewed as to whether or not a shortage had been notified in Austria, Italy, and Spain for February 2020, March 2020, April 2020 (first wave of the pandemic), and, in comparison, in November 2021 (fourth wave). Publicly accessible shortage registers managed by the national regulatory authorities were consulted. For 48 active substances, a shortage was notified for at least one of the study months, mostly March and April 2020. Out of these 48 active substances, 30 had been explicitly recommended as COVID-19 therapy options. A total of 71% of the active substances with notified shortage concerned medicines labeled as essential by the World Health Organization. During the first wave, Spain and Italy had higher numbers of shortage notifications for the product sample, in terms of active substances as well as medicine presentations, than Austria. In November 2021, the number of shortage notifications for the studied substances reached lower levels in Austria and Spain. The study showed an increase in shortage notifications for COVID-19-relevant medicines in the first months of the pandemic.
Association of Blood Pressure Variability With Death and Discharge Destination Among Critically Ill Patients With and Without Stroke

Background and Objectives It is unclear whether blood pressure variability's (BPV) association with worse outcomes is unique to patients with stroke or a risk factor among all critically ill patients. We (1) determined whether BPV differed between patients with stroke and nonstroke patients, (2) examined BPV's associations with in-hospital death and favorable discharge destination in patients with stroke and nonstroke patients, and (3) assessed how minimum mean arterial pressure (MAP)—a correlate of illness severity and cerebral perfusion—affects these associations. Methods This is a retrospective analysis of adult intensive care unit patients hospitalized between 2001 and 2012 from the Medical Information Mart for Intensive Care III database. Confounder-adjusted logistic regressions determined associations between BPV, measured as SD and average real variability (ARV), and (1) in-hospital death and (2) favorable discharge, with testing of minimum MAP for effect modification. Results BPV was higher in patients with stroke (N = 2,248) compared with nonstroke patients (N = 9,085) (SD mean difference 2.3, 95% CI 2.1–2.6, p < 0.01). After adjusting for minimum tertile of MAP and other confounders, higher SD remained significantly associated (p < 0.05) with higher odds of in-hospital death for patients with acute ischemic strokes (AISs, odds ratio [OR] 2.7, 95% CI 1.5–4.8), intracerebral hemorrhage (ICH, OR 2.6, 95% CI 1.6–4.3), subarachnoid hemorrhage (SAH, OR 3.4, 95% CI 1.2–9.3), and pneumonia (OR 1.9, 95% CI 1.1–3.3) and lower odds of favorable discharge destination in patients with ischemic stroke (OR 0.3, 95% CI 0.2–0.6) and ICH (OR 0.4, 95% CI 0.3–0.6). No interaction was found between minimum MAP tertile with SD (p > 0.05). Higher ARV was not significantly associated with increased risk of death in any condition when adjusting for illness severity but portended worse discharge destination in those with AIS (OR favorable discharge 0.4, 95% CI 0.3–0.7), ICH (OR favorable discharge 0.5, 95% CI 0.3–0.7), sepsis (OR favorable discharge 0.8, 95% CI 0.6–1.0), and pneumonia (OR favorable discharge 0.5, 95% CI 0.4–0.8). Discussion BPV is higher and generally associated with worse outcomes among patients with stroke compared with nonstroke patients. BPV in patients with AIS and patients with ICH may be a marker of central autonomic network injury, although clinician-driven blood pressure goals likely contribute to the association between BPV and outcomes.
Improving phytase production in Pichia pastoris fermentations through de‐repression and methanol induction optimization

Pichia pastoris (Komagataella phaffii) is a fast‐growing methylotrophic yeast with the ability to assimilate several carbon sources such as methanol, glucose, or glycerol. It has been shown to have outstanding secretion capability with a variety of heterologous proteins. In previous studies, we engineered P. pastoris to co‐express Escherichia coli AppA phytase and the HAC1 transcriptional activator using a bidirectional promoter. Phytase production was characterized in shake flasks and did not reflect industrial conditions. In the present study, phytase expression was explored and optimized using instrumented fermenters in continuous and fed‐batch modes. First, the production of phytase was investigated under glucose de‐repression in continuous culture at three dilution factors, 0.5 d−1, 1 d−1, and 1.5 d−1. The fermenter parameters of these cultures were used to inform a kinetic model in batch and fed‐batch modes for growth and phytase production. The kinetic model developed aided to design the glucose‐feeding profile of a fed‐batch culture. Kinetic model simulations under glucose de‐repression and fed‐batch conditions identified optimal phytase productivity at the specific growth rate of 0.041 h−1. Validation of the model simulation with experimental data confirmed the feasibility of the model to predict phytase production in our newly engineered strain. Methanol was used only to induce the expression of phytase at high cell densities. Our results showed that high phytase production required two stages, the first stage used glucose under de‐repression conditions to generate biomass while expressing phytase, and stage two used methanol to induce phytase expression. The production of phytase was improved 3.5‐fold by methanol induction compared to the expression with glucose alone under de‐repression conditions to a final phytase activity of 12.65 MU/L. This final volumetric phytase production represented an approximate 36‐fold change compared to the flask fermentations. Finally, the phytase protein produced was assayed to confirm its molecular weight, and pH and temperature profiles. This study highlights the importance of optimizing protein production in P. pastoris when using novel promoters and presents a general approach to performing bioprocess optimization in this important production host.
Distress, burden, and wellbeing in siblings of people with mental illness: a mixed studies systematic review and meta-analysis

Abstract Background Family members of people with mental illness (MI) may experience a host of psychological adversities such as increased stress, burden, and reduced wellbeing. However, relatively little is known about siblings. This study aimed to characterise the experience of distress (viz. depressive and anxiety symptoms), burden, and wellbeing in siblings of people with MI. Methods Studies reporting on quantitative measures of depression, anxiety, burden, or wellbeing in siblings; and/or qualitative findings on siblings’ experience were eligible. The literature search was conducted up until 20th October 2022. Results Sixty-two studies comprising data from 3744 siblings were included. The pooled mean percentage of depressive symptoms fell in the mild range at 15.71 (k = 28, N = 2187, 95% CI 12.99–18.43) and anxiety symptoms fell in the minimal range at 22.45 (k = 16, N = 1122, 95% CI 17.09–27.80). Moderator analyses indicate that siblings of people with a schizophrenia spectrum disorder experience greater depressive symptoms than siblings of people with other types of MI (β = −16.38, p < 0.001). Qualitative findings suggest that individuals may be particularly vulnerable during their siblings’ illness onset and times of relapse. Limited communication, confusion about MI, and the need to compensate may contribute to siblings’ distress and/or burden. Siblings’ experience of wellbeing and caregiving were closely related. Conclusion This review highlights the complex psychological experience of siblings and the need for greater research and clinical support for this important yet often overlooked cohort.
Percutaneous left atrial appendage closure in patients with gastrointestinal bleeding associated with oral anticoagulants

Abstract Introduction Percutaneous left atrial appendage closure (LAAC) has shown non-inferiority compared to oral anticoagulation (OAC) in preventing atrial fibrillation (AF)-related stroke. The objective of this study was to assess whether LAAC reduces the incidence of gastrointestinal bleeding (GIB) and/or chronic anaemia associated with OAC, as well as the consumption of healthcare resources. Materials and Methods Prospective, single-center study from 2016 to 2022, LAAC was performed. Clinical, analytical and healthcare resource consumption data were collected (endoscopies, blood transfusions, hospital admissions) prior and 6 months after LAAC. Results 43 patients were included, with an average age of 77.6 years. LAAC indication was upper, low and obscure GIB in 7 (16%), 8 (19%) and 28 patients (65%) respectively. GIB source was intestinal angiodysplasias in 27 patients (63%), occult origin in 12 (28%), and others (antral vascular ectasia, portal hypertension gastropathy, etc.) in 4 patients (9%). The mean number of packed red blood cells per patient before LAAC was (mean ± SD) 7.29 ± 5 vs 0.42 ± 1.3 (p < 0.001); endoscopic procedures were 4.34 ± 2.85 vs 0.27 ± 0.76 (p < 0.001); and hospitalizations 2.67 ± 2.14 vs 0.03 ± 0.17 (p < 0.001), with a hospital stay of 21.5 ± 17.3 vs 0.09 ± 0.5 days (p < 0.001) at 6 months post-intervention. Haemoglobin value increased from 8.1 ± 1.2g/dl to 12.4 ± 2.2g/dl (p < 0.001) at 6 months. No thromboembolic events were registered during a median follow-up of 16.6 months (range 6–65). Conclusions LAAC could be a safe and effective alternative to OAC in patients with non-valvular AF presenting significant, recurrent or potentially unresolvable GIB. This intervention also leads to important savings in the consumption of healthcare resources.
Quantitative analysis of charge transport in intrinsic and doped organic semiconductors combining steady-state and frequency-domain data

Single-carrier devices are an excellent model system to study charge injection and charge transport properties of (doped) transport layers and to draw conclusions about organic electronics devices in which they are used. By combining steady-state and impedance measurements at varying temperatures of hole-only devices with different intrinsic layer thicknesses, we are able to determine all relevant material parameters, such as the charge mobility and the injection barrier. Furthermore, the correlation and sensitivity analyses reveal that the proposed approach to study these devices is especially well suited to extract the effective doping density, a parameter which cannot be easily determined otherwise. The effective doping density is crucial in organic light-emitting diodes (OLEDs) for realizing efficient injection, charge balance, and lateral conductivity in display or lighting applications. With the fitted drift-diffusion device model, we are further able to explain the extraordinary two-plateau capacitance–frequency curve of these hole-only devices, which originates from charges that flow into the intrinsic layer at zero applied offset voltage. We demonstrate that the observation of this behaviour is a direct indication for ideal charge injection properties and the observed capacitance–frequency feature is linked to the charge carrier mobility in the intrinsic layer. The extracted material parameters may directly be used to simulate and optimize full OLED devices employing the investigated hole-injection and -transport materials.Single-carrier devices are an excellent model system to study charge injection and charge transport properties of (doped) transport layers and to draw conclusions about organic electronics devices in which they are used. By combining steady-state and impedance measurements at varying temperatures of hole-only devices with different intrinsic layer thicknesses, we are able to determine all relevant material parameters, such as the charge mobility and the injection barrier. Furthermore, the correlation and sensitivity analyses reveal that the proposed approach to study these devices is especially well suited to extract the effective doping density, a parameter which cannot be easily determined otherwise. The effective doping density is crucial in organic light-emitting diodes (OLEDs) for realizing efficient injection, charge balance, and lateral conductivity in display or lighting applications. With the fitted drift-diffusion device model, we are further able to explain the extraordinary two-plateau capacit.
Fog System Configuration Management with CRDTs

Current fog systems rely on centralized and strongly consistent services for configuration management originally designed for cloud systems. In the geo-distributed fog, such systems can exhibit high communication latency or become unavailable in case of network partition. In this paper, we examine the drawbacks of strong consistency for fog configuration management and propose an alternative based on CRDTs. We prototypically implement our approach for the FReD fog data management platform. Early results show reductions of server response times of up to 50\%.
Learning to Solve Integer Linear Programs with Davis-Yin Splitting

In many applications, a combinatorial problem must be repeatedly solved with similar, but distinct parameters. Yet, the parameters $w$ are not directly observed; only contextual data $d$ that correlates with $w$ is available. It is tempting to use a neural network to predict $w$ given $d$. However, training such a model requires reconciling the discrete nature of combinatorial optimization with the gradient-based frameworks used to train neural networks. When the problem in question is an Integer Linear Program (ILP), one approach to overcome this training issue is to consider a continuous relaxation of the combinatorial problem. While existing methods utilizing this approach have shown to be highly effective on small problems, they do not always scale well to large problems. In this work, we draw on ideas from modern convex optimization to design a network and training scheme which scales effortlessly to problems with thousands of variables. Our experiments verify the computational advantage our proposed method enjoys on two representative problems, namely the shortest path problem and the knapsack problem.
Concept Algebra for (Score-Based) Text-Controlled Generative Models

This paper concerns the structure of learned representations in text-guided generative models, focusing on score-based models. A key property of such models is that they can compose disparate concepts in a `disentangled' manner. This suggests these models have internal representations that encode concepts in a `disentangled' manner. Here, we focus on the idea that concepts are encoded as subspaces of some representation space. We formalize what this means, show there's a natural choice for the representation, and develop a simple method for identifying the part of the representation corresponding to a given concept. In particular, this allows us to manipulate the concepts expressed by the model through algebraic manipulation of the representation. We demonstrate the idea with examples using Stable Diffusion. Code in https://github.com/zihao12/concept-algebra-code
Segmenting Known Objects and Unseen Unknowns without Prior Knowledge

Panoptic segmentation methods assign a known class to each pixel given in input. Even for state-of-the-art approaches, this inevitably enforces decisions that systematically lead to wrong predictions for objects outside the training categories. However, robustness against out-of-distribution samples and corner cases is crucial in safety-critical settings to avoid dangerous consequences. Since real-world datasets cannot contain enough data points to adequately sample the long tail of the underlying distribution, models must be able to deal with unseen and unknown scenarios as well. Previous methods targeted this by re-identifying already-seen unlabeled objects. In this work, we propose the necessary step to extend segmentation with a new setting which we term holistic segmentation. Holistic segmentation aims to identify and separate objects of unseen, unknown categories into instances without any prior knowledge about them while performing panoptic segmentation of known classes. We tackle this new problem with U3HS, which finds unknowns as highly uncertain regions and clusters their corresponding instance-aware embeddings into individual objects. By doing so, for the first time in panoptic segmentation with unknown objects, our U3HS is trained without unknown categories, reducing assumptions and leaving the settings as unconstrained as in real-life scenarios. Extensive experiments on public data from MS COCO, Cityscapes, and Lost&Found demonstrate the effectiveness of U3HS for this new, challenging, and assumptions-free setting called holistic segmentation. Project page: https://holisticseg.github. io.
Decreased nitrosylation of CaMKII causes aging-associated impairments in memory and synaptic plasticity in mice

CaMKII has molecular memory functions because transient calcium ion stimuli can induce long-lasting increases in its synaptic localization and calcium ion–independent (autonomous) activity, thereby leaving memory traces of calcium ion stimuli beyond their duration. The synaptic effects of two mechanisms that induce CaMKII autonomy are well studied: autophosphorylation at threonine-286 and binding to GluN2B. Here, we examined the neuronal functions of additional autonomy mechanisms: nitrosylation and oxidation of the CaMKII regulatory domain. We generated a knock-in mouse line with mutations that render the CaMKII regulatory domain nitrosylation/oxidation-incompetent, CaMKIIΔSNO, and found that it had deficits in memory and synaptic plasticity that were similar to those in aged wild-type mice. In addition, similar to aged wild-type mice, in which CaMKII was hyponitrosylated, but unlike mice with impairments of other CaMKII autonomy mechanisms, CaMKIIΔSNO mice showed reduced long-term potentiation (LTP) when induced by theta-burst stimulation but not high-frequency stimulation (HFS). As in aged wild-type mice, the HFS-LTP in the young adult CaMKIIΔSNO mice required L-type voltage-gated calcium ion channels. The effects in aged mice were likely caused by the loss of nitrosylation because no decline in CaMKII oxidation was detected. In hippocampal neurons, nitrosylation of CaMKII induced its accumulation at synapses under basal conditions in a manner mediated by GluN2B binding, like after LTP stimuli. However, LTP-induced synaptic CaMKII accumulation did not require nitrosylation. Thus, an aging-associated decrease in CaMKII nitrosylation may cause impairments by chronic synaptic effects, such as the decrease in basal synaptic CaMKII. Description Nitrosylation sends CaMKII to neuronal synapses to support learning and memory in mice. Editor’s summary Cognitive function declines with age, as does the amount of S-nitrosylated proteins in the brain. One such protein is the kinase CaMKII, which in neurons mediates synaptic signaling that supports learning and memory. Rumian et al. found that S-nitrosylation of CaMKII was critical for the localization of the kinase to synapses and for the response of hippocampal neurons to a stimulus that mimics experience-induced brain activity. Cognitive function in young mice expressing S-nitrosylation–deficient CaMKII was impaired to similar extents as those seen in older, wild-type mice. The findings reveal a mechanism of age-related cognitive decline. —Leslie K. Ferrarelli