Miracle-dz/UniFAR-FTUs huggingface dataset:
Benchmarking, analysis, and optimization of serverless function snapshots

Serverless computing has seen rapid adoption due to its high scalability and flexible, pay-as-you-go billing model. In serverless, developers structure their services as a collection of functions, sporadically invoked by various events like clicks. High inter-arrival time variability of function invocations motivates the providers to start new function instances upon each invocation, leading to significant cold-start delays that degrade user experience. To reduce cold-start latency, the industry has turned to snapshotting, whereby an image of a fully-booted function is stored on disk, enabling a faster invocation compared to booting a function from scratch. This work introduces vHive, an open-source framework for serverless experimentation with the goal of enabling researchers to study and innovate across the entire serverless stack. Using vHive, we characterize a state-of-the-art snapshot-based serverless infrastructure, based on industry-leading Containerd orchestration framework and Firecracker hypervisor technologies. We find that the execution time of a function started from a snapshot is 95% higher, on average, than when the same function is memory-resident. We show that the high latency is attributable to frequent page faults as the function's state is brought from disk into guest memory one page at a time. Our analysis further reveals that functions access the same stable working set of pages across different invocations of the same function. By leveraging this insight, we build REAP, a light-weight software mechanism for serverless hosts that records functions' stable working set of guest memory pages and proactively prefetches it from disk into memory. Compared to baseline snapshotting, REAP slashes the cold-start delays by 3.7x, on average.
Equational reasoning for non-determinism monad: the case of Spark aggregation

As part of the author's studies on equational reasoning for monadic programs, this report focus on non-determinism monad. We discuss what properties this monad should satisfy, what additional operators and notations can be introduced to facilitate equational reasoning about non-determinism, and put them to the test by proving a number of properties in our example problem inspired by the author's previous work on proving properties of Spark aggregation.
Deep Graph Convolutional Networks for Wind Speed Prediction

Wind speed prediction and forecasting is important for various business and management sectors. In this paper, we introduce new models for wind speed prediction based on graph convolutional networks (GCNs). Given hourly data of several weather variables acquired from multiple weather stations, wind speed values are predicted for multiple time steps ahead. In particular, the weather stations are treated as nodes of a graph whose associated adjacency matrix is learnable. In this way, the network learns the graph spatial structure and determines the strength of relations between the weather stations based on the historical weather data. We add a self-loop connection to the learnt adjacency matrix and normalize the adjacency matrix. We examine two scenarios with the self-loop connection setting (two separate models). In the first scenario, the self-loop connection is imposed as a constant additive. In the second scenario a learnable parameter is included to enable the network to decide about the self-loop connection strength. Furthermore, we incorporate data from multiple time steps with temporal convolution, which together with spatial graph convolution constitutes spatio-temporal graph convolution. We perform experiments on real datasets collected from weather stations located in cities in Denmark and the Netherlands. The numerical experiments show that our proposed models outperform previously developed baseline models on the referenced datasets. We provide additional insights by visualizing learnt adjacency matrices from each layer of our models.
Context-Specific Likelihood Weighting

Sampling is a popular method for approximate inference when exact inference is impractical. Generally, sampling algorithms do not exploit context-specific independence (CSI) properties of probability distributions. We introduce context-specific likelihood weighting (CS-LW), a new sampling methodology, which besides exploiting the classical conditional independence properties, also exploits CSI properties. Unlike the standard likelihood weighting, CS-LW is based on partial assignments of random variables and requires fewer samples for convergence due to the sampling variance reduction. Furthermore, the speed of generating samples increases. Our novel notion of contextual assignments theoretically justifies CS-LW. We empirically show that CS-LW is competitive with state-of-the-art algorithms for approximate inference in the presence of a significant amount of CSIs.
Transient dispersion process of active particles

Abstract Active particles often swim in confined environments. The transport mechanisms, especially the global one as reflected by the Taylor dispersion model, are of great practical interest to various applications. For the active dispersion process in confined flows, previous analytical studies focused on the long-time asymptotic values of dispersion characteristics. Only several numerical studies preliminarily investigated the temporal evolution. Extending recent studies of Jiang & Chen (J. Fluid Mech., vol. 877, 2019, pp. 1–34; vol. 899, 2020, A18), this work makes a semi-analytical attempt to investigate the transient process. The temporal evolution of the local distribution in the confined-section–orientation space, drift, dispersivity and skewness, is explored based on moments of distributions. We introduce the biorthogonal expansion method for solutions because the classic integral transform method for passive transport problems is not applicable due to the self-propulsion effect. Two types of boundary condition, the reflective condition and the Robin condition for wall accumulation, are imposed respectively. A detailed study on spherical and ellipsoidal swimmers dispersing in a plane Poiseuille flow demonstrates the influences of the swimming, shear flow, initial condition, wall accumulation and particle shape on the transient dispersion process. The swimming-induced diffusion makes the local distribution reach its equilibrium state faster than that of passive particles. Although the wall accumulation significantly affects the evolution of the local distribution and the drift, the time scale to reach the Taylor regime is not obviously changed. The shear-induced alignment of ellipsoidal particles can enlarge the dispersivity but impacts slightly on the drift and the skewness.
Binding of Bicarbonate to Human Carbonic Anhydrase II: A Continuum of Binding States

Herein, we report molecular dynamics simulations of the enzyme human carbonic anhydrase II (HCAII) complexed with the substrate molecule bicarbonate using a quantum mechanical/molecular mechanical (QM/MM) coupled potential. This study provides novel insights into bicarbonate binding and loss. In particular, we find that a structure related to the so-called Lipscomb binding motif is the global minimum, while the first formed Lindskog binding mode is unstable relative to alternative binding modes. From our simulated results we are able to postulate why Thr-199 destabilizes bicarbonate binding to HCAII (relative to the Ala-199 mutant) and how bicarbonate ion is displace by water to form the zinc−water form of HCAII. This study also demonstrates the capability of QM/MM methods to elucidate structural and mechanistic aspects of enzyme mechanisms.
A Century of Chemical Dynamics Traced through the

This is the fifth in a series of thirteen monthly essays reviewing the Nobel Prizes in chemical dynamics during the 20th century. Cyril Hinshelwood and Nikolay Semenov received the Nobel Prize in 1956 "for their researches into the mechanism of chemical reactions," in particular, chain reactions.
Knockdown of FAM225B inhibits the progression of the hypertrophic scar following glaucoma surgery by inhibiting autophagy

The formation of a hypertrophic scar (HS) may lead to failure of glaucoma surgery. Long non-coding RNAs (lncRNAs) are involved in the formation of HSs. Moreover, family with sequence similarity 225 member B (FAM225B) is upregulated in HS. However, the role of the lncRNA FAM225B in HS remains unknown. Thus, the present study aimed to investigate the function of FAM225B in HS. Scar fibroblasts were isolated from patients who had undergone glaucoma surgery. Western blotting was used to detect the expressions of Bax, Bcl-2, cleaved caspase 3, p62, ATG7 and Beclin 1, and reverse transcription-quantitative PCR (RT-qPCR) were conducted to determine the level of FAM225B in scar fibroblasts. Microtubule associated protein 1 light chain 3 α staining was performed to examine autophagosomes in scar fibroblasts. Furthermore, cell proliferation was evaluated via 5-ethynyl-2′-deoxyuridine staining. Flow cytometry was conducted to determine cell apoptosis and the levels of reactive oxygen species (ROS) in scar fibroblasts. The cell migratory ability was assessed using a Transwell assay. The results demonstrated that FAM225B knockdown significantly attenuated scar fibroblast proliferation and induced apoptosis. Additionally, transfection of scar fibroblasts with FAM225B small interfering RNA (siRNA) significantly increased the ROS levels and significantly decreased the migration of scar fibroblasts. The FAM225B overexpression-induced increase of scar fibroblast proliferation and migration was significantly reversed by 3-methyladenine administration. The results suggested that knockdown of FAM225B significantly inhibited the proliferation of scar fibroblasts by inhibiting autophagy. Therefore, knockdown of FAM225B could inhibit scar fibroblast proliferation after glaucoma surgery by inhibiting autophagy. These findings may provide a novel perspective of developing treatment strategy for the patients with HSs after glaucoma surgery.
Low Expression of Keratin17 is Related to Poor Prognosis in Bladder Cancer

Objective To investigate the association between KRT17 and the prognosis in bladder cancer patients. Methods The clinical data of 101 patients with bladder cancer from May 2013 to May 2015 were retrospectively analyzed. At the same time, the expression of KRT17 and its correlation with clinicopathological factors were examined by immunohistochemistry. We search the prognostic value of KRT17 in bladder cancer from the cancer genome map (TCGA) online database. To explore the possible cellular mechanism, gene set enrichment analysis (GSEA) was used. The patients were divided into two groups: high expression of KRT17 and low expression of KRT17. The patients were followed up for 5 years to observe the survival. Kaplan–Meier method and Log rank test were used for univariate survival analysis, and Cox regression analysis was used for multivariate analysis. Finally, a nomogram was constructed on this basis for internal verification. Results Among the 101 patients, 46 (45.5%) were in the KRT17 low expression group and 55 (54.5%) in the high KRT17 expression group. After 5 years of follow-up, 79 patients survived with a survival rate of 78.2% and 22 patients died with a mortality rate of 21.8%. Kaplan–Meier survival analysis showed that OS and PFS of patients with high expression of KRT17 were significantly higher than those of patients with low expression of KRT17 (p<0.001, p=0.005). Cox multivariate analysis showed that KRT17 expression was an independent risk factor for tumor progression (p=0.019). And tumor size, vascular tumor thrombus, and T stage also affected tumor progression (p<0.05). In the internal validation, the c-index of nomogram was 0.898 (95% CI: 0.854–0.941). Conclusion The decreased expression of KRT17 is associated with poor prognosis in patients with bladder cancer. KRT17 can be used as a novel predictive biomarker to provide a new therapeutic target for bladder cancer patients.
Inherent Importance of Early Visual Features in Attraction of Human Attention

Local contrasts attract human attention to different areas of an image. Studies have shown that orientation, color, and intensity are some basic visual features which their contrasts attract our attention. Since these features are in different modalities, their contribution in the attraction of human attention is not easily comparable. In this study, we investigated the importance of these three features in the attraction of human attention in synthetic and natural images. Choosing 100% percent detectable contrast in each modality, we studied the competition between different features. Psychophysics results showed that, although single features can be detected easily in all trials, when features were presented simultaneously in a stimulus, orientation always attracts subject's attention. In addition, computational results showed that orientation feature map is more informative about the pattern of human saccades in natural images. Finally, using optimization algorithms we quantified the impact of each feature map in construction of the final saliency map.
Clinical Significance of Continuable Treatment with Nintedanib Over 12 Months for Idiopathic Pulmonary Fibrosis in a Real-World Setting

Purpose The INPULSIS-ON study suggested the safety and tolerability of long-term nintedanib treatment for idiopathic pulmonary fibrosis (IPF). However, there are no real-world studies on long-term nintedanib treatment. The main aim of the study was to investigate the efficacy and the tolerability of long-term treatment with nintedanib for IPF in clinical practice. Patients and Methods This retrospective study enrolled 104 IPF patients who underwent treatment with nintedanib. Among these patients, 51 were able to receive nintedanib for more than 12 months (ie, treatment with nintedanib over 12 months was possible [P group]) and 53 were not able to receive nintedanib for more than 12 months (ie, treatment with nintedanib over 12 months was impossible [I group]). The tolerability and efficacy of nintedanib were compared between the two groups. Results In the I group, 29 patients were unable to continue nintedanib therapy because of adverse effects, including diarrhea and nausea/anorexia. In addition, 19 and four patients could not continue nintedanib treatment because of IPF progression and worsening of performance status (PS), respectively. One patient suddenly died during nintedanib treatment. The incidence of nausea/anorexia in the I group was significantly higher than in the P group (49.06 vs 25.49%). The survival time was significantly longer in the P group than in the I group (35 vs 12 months). The decline in forced vital capacity was significantly larger in the I group than in the P group (165 vs 10 mL/year). Poor PS at nintedanib initiation was the only significant risk factor for nintedanib treatment discontinuation over 12 months. Finally, the survival time was significantly longer in patients with good PS than in those with poor PS (27 vs 13 months). Conclusion Poor PS can result in discontinuation of nintedanib after 12 months. Long-term nintedanib treatment may be effective for survival.
Application of a prediction model with laboratory indexes in the risk stratification of patients with COVID-19

In the present study, a prediction model with combined laboratory indexes in risk stratification of patients with COVID-19 was established and tested. The data of 170 patients with COVID-19 who were divided into an asymptomatic-moderate group (141 cases) and severe or above group (29 cases) were retrospectively analyzed. The clinical characteristics and laboratory indexes of the two groups were compared. Multivariate logistic regression analysis was performed to construct the prediction model based on laboratory indexes. A receiver operating characteristic (ROC) curve analysis was used to compare the diagnostic efficacy of different indexes. Decision curve analysis (DCA) was performed to quantify and compare the clinical validity of the prediction models. There were significant differences in blood cell count, high-sensitivity C-reactive protein (hsCRP) and procalcitonin (PCT) levels between the severe or above group and the asymptomatic-moderate group (all P<0.05). Among all individual indexes, hsCRP had the highest diagnostic efficacy (area under the curve=0.870), with a sensitivity and specificity of 0.828 and 0.802, respectively. The red blood cell count, hsCRP and PCT were used to construct the prediction model. The AUC of the prediction model was higher than that of hsCRP (0.912 vs. 0.870) but the difference was not significant (P=0.307). DCA suggested that the net benefit of the prediction model was higher than that of hsCRP in most cases and significantly higher than that of PCT, lymphocytes and monocytes. The prediction model with combined laboratory indexes was able to more effectively predict the clinical classification of patients with COVID-19 and may be used as a tool for risk stratification of patients.
Characterization of the complete mitochondrial genome of Saron marmoratus (Hippolytidae, Decapoda) and its phylogenetic analysis

Abstract The complete mitochondrial genome of shrimp Saron marmoratus was obtained and characterized in this study. This complete mitochondrial genome is 16,330 bp in size and comprises 13 protein-coding genes (PCGs), two ribosomal RNA genes, and 22 transfer RNA genes. Fourteen genes were encoded by light strand and another 23 genes were encoded by heavy strand. The A + T content of the heavy-strand was 67.89%. Most PCGs had ATN as the start codon except ND4 initiated with GAT. Eleven PCGs terminated with a complete stop codon TAN, but two PCGs (ND5 and Cytb) had an incomplete stop codon. The phylogenetic analysis suggested that Hippolytidae shrimp may be considered as the polyphyletic taxon. These results are useful for understanding the phylogenetic relationships and evolution of Hippolytidae shrimp.
Magnetic properties of NiCuZn ferrite nanoparticles synthesized using egg-white

A new process to prepare single-phase nano-sized ferrites, Ni0.8-xCu0.2ZnxFe2O4 with x = 0.1-0.7, was developed using egg-white precursors. TG measurement showed that, the precursors must be calcined at 550 °C. XRD patterns indicated the formation of single-phase cubic ferrites with particle size in the range 28.7-48.4 nm. TEM image gave particle size agrees well with that estimated using XRD. FT-IR spectroscopy showed the characteristic ferrite bands. Hysteresis loops measurements exhibited an increase in the saturation magnetization value (Ms) up to zinc content of 0.2 followed by unexpected decrease, which suggests the preference of Zn2+ ions to occupy octahedral sites. The decrease in the coercivity (Hc) with increasing zinc content is attributed to the lower magneto-crystalline anisotropy of Zn2+ ions compared to Ni2+ ions. Temperature dependence of the molar magnetic susceptibility (χM) suggested a ferrimagnetic behavior of the investigated samples and showed a decrease in the value of the Curie temperature (TC) with increasing zinc.
Trimethylamine N-oxide (TMAO) Is not Associated with Cardiometabolic Phenotypes and Inflammatory Markers in Children and Adults

ABSTRACT Background Trimethylamine N-oxide (TMAO) is a diet- and microbiome-derived metabolite and a proposed biomarker of adverse cardiometabolic outcomes. TMAO studies have mainly been conducted in individuals with cardiometabolic disease, and studies in population-derived samples are limited. Objective We aimed to investigate the associations between plasma TMAO concentrations and its precursors [carnitine, choline, betaine, and dimethylglycine (DMG)] with metabolic syndrome (MetS) scores, preclinical cardiovascular phenotypes, and inflammatory biomarkers (i.e. high-sensitivity C-reactive protein and serum glycoprotein acetyls) in a population-derived cohort of children and their parents. Methods The concentrations of TMAO and its precursors were quantified using UHPLC coupled with tandem MS (UHPLC/MS-MS) in 1166 children (mean age 11 y ± 0.5 y, 51% female) and 1324 adults (44 y ± 5.1 y, 87% female) participating in The Growing Up in Australia's Child Health CheckPoint Study. We developed multivariable fractional polynomial models to analyze associations between TMAO, its precursors, MetS (adjusted for sex and age), and cardiovascular phenotypes (adjusted for sex, age, BMI, household income, and the urinary albumin to creatinine ratio). Pearson's correlations were computed to identify associations between TMAO, its precursors, and inflammatory biomarkers. Results The concentrations of TMAO precursors, but not TMAO itself, were associated with MetS, cardiovascular phenotypes, and inflammatory biomarkers in children and adults. Conclusions TMAO precursors, but not TMAO itself, were associated with adverse cardiometabolic and inflammatory phenotypes in children and adults. TMAO precursor concentrations may better reflect cardiovascular health and inflammatory status within the wider population. Replication in other population settings and mechanistic studies are warranted.
Hydrodynamic Analysis for the Morphing Median Fins of Tuna during Yaw Motions

Tuna can change the area and shape of the median fins, including the first dorsal, second dorsal, and anal fins. The morphing median fins have the ability of adjusting the hydrodynamic forces, thereby affecting the yaw mobility of tuna to a certain extent. In this paper, the hydrodynamic analysis of the median fins under different morphing states is carried out by the numerical method, so as to clarify the influence of the erected median fins on the yaw maneuvers. By comparing the two morphing states of erected and depressed, it can be concluded that the erected median fins can increase their own hydrodynamic forces during the yaw movement. However, the second dorsal and anal fins have limited influence on the yaw maneuverability, and they tend to maintain the stability of tuna. The first dorsal fin has more lift increment in the erection state, which can obviously affect the hydrodynamic performance of tuna. Moreover, as the median fins are erected, the hydrodynamic forces of the tuna's body increase synchronously due to the interaction between the body and the median fins, which is also very beneficial to the yaw motion. This study indicates that tuna can use the morphing median fins to adjust its mobility and stability, which provides a new idea for the design of robotic fish.