Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning to Bid in Repeated First-Price Auctions with Budgets

Budget management strategies in repeated auctions have received growing attention in online advertising markets. However, previous work on budget management in online bidding mainly focused on second-price auctions. The rapid shift from second-price auctions to first-price auctions for online ads in recent years has motivated the challenging question of how to bid in repeated first-price auctions while controlling budgets. In this work, we study the problem of learning in repeated first-price auctions with budgets. We design a dual-based algorithm that can achieve a near-optimal $\widetilde{O}(\sqrt{T})$ regret with full information feedback where the maximum competing bid is always revealed after each auction. We further consider the setting with one-sided information feedback where only the winning bid is revealed after each auction. We show that our modified algorithm can still achieve an $\widetilde{O}(\sqrt{T})$ regret with mild assumptions on the bidder's value distribution. Finally, we complement the theoretical results with numerical experiments to confirm the effectiveness of our budget management policy.
Integrated Architecture for Neural Networks and Security Primitives using RRAM Crossbar

This paper proposes an architecture that integrates neural networks (NNs) and hardware security modules using a single resistive random access memory (RRAM) crossbar. The proposed architecture enables using a single crossbar to implement NN, true random number generator (TRNG), and physical unclonable function (PUF) applications while exploiting the multi-state storage characteristic of the RRAM crossbar for the vector-matrix multiplication operation required for the implementation of NN. The TRNG is implemented by utilizing the crossbar’s variation in device switching thresholds to generate random bits. The PUF is implemented using the same crossbar initialized as an entropy source for the TRNG. Additionally, the weights locking concept is introduced to enhance the security of NNs by preventing unauthorized access to the NN weights. The proposed architecture provides flexibility to configure the RRAM device in multiple modes to suit different applications. It shows promise in achieving a more efficient and compact design for the hardware implementation of NNs and security primitives.
Jet: Multilevel Graph Partitioning on Graphics Processing Units

The multilevel heuristic is the dominant strategy for high-quality sequential and parallel graph partitioning. Partition refinement is a key step of multilevel graph partitioning. In this work, we present Jet, a new parallel algorithm for partition refinement specifically designed for Graphics Processing Units (GPUs). We combine Jet with GPU-aware coarsening to develop a $k$-way graph partitioner, the Jet partitioner. The new partitioner achieves superior quality compared to state-of-the-art shared memory partitioners on a large collection of test graphs.
An Efficient Doubly-Robust Test for the Kernel Treatment Effect

The average treatment effect, which is the difference in expectation of the counterfactuals, is probably the most popular target effect in causal inference with binary treatments. However, treatments may have effects beyond the mean, for instance decreasing or increasing the variance. We propose a new kernel-based test for distributional effects of the treatment. It is, to the best of our knowledge, the first kernel-based, doubly-robust test with provably valid type-I error. Furthermore, our proposed algorithm is computationally efficient, avoiding the use of permutations.
Towards Reliable Colorectal Cancer Polyps Classification via Vision Based Tactile Sensing and Confidence-Calibrated Neural Networks

In this study, toward addressing the over-confident outputs of existing artificial intelligence-based colorectal cancer (CRC) polyp classification techniques, we propose a confidence-calibrated residual neural network. Utilizing a novel vision-based tactile sensing (VS-TS) system and unique CRC polyp phantoms, we demonstrate that traditional metrics such as accuracy and precision are not sufficient to encapsulate model performance for handling a sensitive CRC polyp diagnosis. To this end, we develop a residual neural network classifier and address its over-confident outputs for CRC polyps classification via the post-processing method of temperature scaling. To evaluate the proposed method, we introduce noise and blur to the obtained textural images of the VSTS and test the model's reliability for non-ideal inputs through reliability diagrams and other statistical metrics.
Self-limiting and regenerative dynamics of perturbation growth on a vortex column

Abstract We study the mechanisms of centrifugal instability and its eventual self-limitation, as well as regenerative instability on a vortex column with a circulation overshoot (potentially unstable) via direct numerical simulations of the incompressible Navier–Stokes equations. The perturbation vorticity ( ${\boldsymbol{\omega} }^{\prime } $ ) dynamics are analysed in cylindrical ( $r, \theta , z$ ) coordinates in the computationally accessible vortex Reynolds number, $\mathit{Re}({\equiv }\mathrm{circulation/viscosity} )$ , range of 500–12 500, mostly for the axisymmetric mode (azimuthal wavenumber $m= 0$ ). Mean strain generates azimuthally oriented vorticity filaments (i.e. filaments with azimuthal vorticity, ${ \omega }_{\theta }^{\prime } $ ), producing positive Reynolds stress necessary for energy growth. This ${ \omega }_{\theta }^{\prime } $ in turn tilts negative mean axial vorticity, $- {\Omega }_{z} $ (associated with the overshoot), to amplify the filament, thus causing instability. (The initial energy growth rate ( ${\sigma }_{r} $ ), peak energy ( ${G}_{\mathit{max}} $ ) and time of peak energy ( ${T}_{p} $ ) are found to vary algebraically with $\mathit{Re}$ . ) Limitation of vorticity growth, also energy production, occurs as the filament moves the overshoot outward, hence lessening and shifting $\vert {- }{\Omega }_{z} \vert $ , while also transporting the core $+ {\Omega }_{z} $ , to the location of the filament. We discover that a basic change in overshoot decay behaviour from viscous to inviscid occurs at $Re\sim 5000$ . We also find that the overshoot decay time has an asymptotic limit of 45 turnover times with increasing $\mathit{Re}$ . After the limitation, the filament generates negative Reynolds stress, concomitant energy decay and hence self-limitation of growth; these inviscid effects are enhanced further by viscosity. In addition, the filament transports angular momentum radially inward, which can produce a new circulation overshoot and renewed instability. Energy decays at the $\mathit{Re}$ studied, but, at higher $\mathit{Re}$ , regenerative growth of energy is likely due to the renewed mean shearing. New generation of overshoot and Reynolds stress is examined using a helical ( $m= 1$ ) perturbation. Regenerative energy growth, possibly resulting in even vortex breakup, can be triggered by this new overshoot at practical $\mathit{Re}$ ( ${\sim }1{0}^{6} $ for trailing vortices), which are currently beyond the computational capability.
Sepsis modulates aortic AT1 and P2Y6 receptors to produce vascular hyporeactivity in mice

Abstract Purpose Hyporeactivity to vasopressors leading to multiple organ failure is a serious clinical implication in sepsis. Though the regulatory role of purinoceptors in inflammation is reported, their involvement in sepsis-induced vasoplegia is still unknown. Thus we investigated the effect of sepsis on vascular AT1 and P2Y6 receptors. Materials and methods Polymicrobial sepsis was induced by cecal ligation and puncture in mice. Vascular reactivity was assessed by organ bath study and aortic mRNA expression of AT1 and P2Y6 was quantified by qRT-PCR. Results Both angiotensin-II and UDP produced higher contractions in the absence of endothelium as well as following inhibition of nitric oxide synthase. Angiotensin-II mediated aortic contraction was antagonized by losartan (AT1 antagonist), but not by PD123319 (AT2 antagonist) whereas UDP-induced aortic contraction was significantly inhibited by MRS2578 (P2Y6 antagonist). In addition, MRS2578 significantly inhibited the contractile response of Ang-II. Compared to SO mice, angiotensin-II and UDP-induced maximum contraction were found to be significantly attenuated in sepsis. Accordingly, aortic mRNA expression of AT1a receptors was significantly down-regulated while that of P2Y6 receptors was significantly increased in sepsis. 1400 W (a selective iNOS inhibitor) significantly reversed angiotensin-II-induced vascular hyporeactivity in sepsis without affecting UDP-induced hypo-reactivity. Conclusion Sepsis-induced vascular hyporeactivity to angiotensin-II is mediated by enhanced expression of iNOS. Moreover, AT1R-P2Y6 cross talk/heterodimerization could be a novel target for regulating vascular dysfunction in sepsis.
Water level prediction using soft computing techniques: A case study in the Malwathu Oya, Sri Lanka

Hydrologic models to simulate river flows are computationally costly. In addition to the precipitation and other meteorological time series, catchment characteristics, including soil data, land use, land cover, and roughness, are essential in most hydrologic models. The unavailability of these data series challenged the accuracy of simulations. However, recent advances in soft computing techniques offer better approaches and solutions at less computational complexity. These require a minimum amount of data, while they reach higher accuracies depending on the quality of data sets. The Gradient Boosting Algorithms and Adaptive Network-based Fuzzy Inference System (ANFIS) are two such systems that can be used in simulating river flows based on the catchment rainfall. In this paper, the computational capabilities of these two systems were tested in simulated river flows by developing the prediction models for Malwathu Oya in Sri Lanka. The simulated flows were then compared with the ground-measured river flows for accuracy. Correlation of coefficient (R), Per cent-Bias (bias), Nash Sutcliffe Model efficiency (NSE), Mean Absolute Relative Error (MARE), Kling-Gupta Efficiency (KGE), and Root mean square error (RMSE) were used as the comparative indices between Gradient Boosting Algorithms and Adaptive Network-based Fuzzy Inference Systems. Results of the study showcased that both systems can simulate river flows as a function of catchment rainfalls; however, the Cat gradient Boosting algorithm (CatBoost) has a computational edge over the Adaptive Network Based Fuzzy Inference System (ANFIS). The CatBoost algorithm outperformed other algorithms used in this study, with the best correlation score for the testing dataset having 0.9934. The extreme gradient boosting (XGBoost), Light gradient boosting (LightGBM), and Ensemble models scored 0.9283, 0.9253, and 0.9109, respectively. However, more applications should be investigated for sound conclusions.
Coordinated and Distinct Roles of Peptidoglycan Carboxypeptidases DacC and DacA in Cell Growth and Shape Maintenance under Stress Conditions

Most bacteria have a peptidoglycan architecture for cell shape maintenance and protection against osmotic challenges. Peptidoglycan dd-carboxypeptidases control the amount of pentapeptide substrates, which are used in the formation of 4-3 cross-links by the peptidoglycan synthetic dd-transpeptidases, penicillin-binding proteins (PBPs). ABSTRACT Peptidoglycan (PG) is an essential bacterial architecture pivotal for shape maintenance and adaptation to osmotic stress. Although PG synthesis and modification are tightly regulated under harsh environmental stresses, few related mechanisms have been investigated. In this study, we aimed to investigate the coordinated and distinct roles of the PG dd-carboxypeptidases (DD-CPases) DacC and DacA in cell growth under alkaline and salt stresses and shape maintenance in Escherichia coli. We found that DacC is an alkaline DD-CPase, the enzyme activity and protein stability of which are significantly enhanced under alkaline stress. Both DacC and DacA were required for bacterial growth under alkaline stress, whereas only DacA was required for growth under salt stress. Under normal growth conditions, only DacA was necessary for cell shape maintenance, while under alkaline stress conditions, both DacA and DacC were necessary for cell shape maintenance, but their roles were distinct. Notably, all of these roles of DacC and DacA were independent of ld-transpeptidases, which are necessary for the formation of PG 3-3 cross-links and covalent bonds between PG and the outer membrane lipoprotein Lpp. Instead, DacC and DacA interacted with penicillin-binding proteins (PBPs)—dd-transpeptidases—mostly in a C-terminal domain-dependent manner, and these interactions were necessary for most of their roles. Collectively, our results demonstrate the coordinated and distinct novel roles of DD-CPases in bacterial growth and shape maintenance under stress conditions and provide novel insights into the cellular functions of DD-CPases associated with PBPs. IMPORTANCE Most bacteria have a peptidoglycan architecture for cell shape maintenance and protection against osmotic challenges. Peptidoglycan dd-carboxypeptidases control the amount of pentapeptide substrates, which are used in the formation of 4-3 cross-links by the peptidoglycan synthetic dd-transpeptidases, penicillin-binding proteins (PBPs). Seven dd-carboxypeptidases exist in Escherichia coli, but the physiological significance of their redundancy and their roles in peptidoglycan synthesis are poorly understood. Here, we showed that DacC is an alkaline dd-carboxypeptidase for which both protein stability and enzyme activity are significantly enhanced at high pH. Strikingly, dd-carboxypeptidases DacC and DacA physically interacted with PBPs, and these interactions were necessary for cell shape maintenance as well as growth under alkaline and salt stresses. Thus, cooperation between dd-carboxypeptidases and PBPs may allow E. coli to overcome various stresses and to maintain cell shape.
Assessing Cognitive-Motor Interference in Military Contexts: Validity and Reliability of Two Dual-tasking Tests

ABSTRACT Introduction Cognitive-motor interference is the decrease in cognitive performance and/or physical performance occurring when a cognitive task and a physical task are performed concurrently (dual task) compared to when they are performed in isolation (single task). The aim of this study was to investigate the construct validity and test–retest reliability of two cognitive-motor interference tests in military contexts. Materials and Methods Twenty-two soldiers, officers, and cadets performed a 10-min loaded marching, a 10-min Psychomotor Vigilance Task, and the two tasks combined (visit 1). During visit 2, a 5-min running time trial, a 5-min Word Recall Task, and the two tasks combined. These tests were repeated by 20 participants after 2 weeks (visits 3 and 4). Results Significant impairments were shown on both running distance (P < .001) and number of words recalled (P = .004) in the dual-task condition compared to the single-task condition. Significantly shorter step length (P < .001) and higher step frequency (P < .001) were found during the loaded marching in the dual-task condition compared to the single-task condition. No significant differences were observed in mean reaction time (P = .402) and number of lapses (P = .479) during the Psychomotor Vigilance Task. Good-to-excellent reliability was found for all the cognitive and physical variables in both single- and dual-task conditions, except for the number of lapses. Conclusion These findings suggest that the Running + Word Recall Task test is a valid and reliable dual-tasking test that could be used to assess cognitive-motor interference in military contexts.
Novel pseudonucleosides and sulfamoyl-oxazolidinone β-D-glucosamine derivative as anti-COVID-19: design, synthesis, and in silico study

Abstract New pseudonucleosides containing cyclic sulfamide moiety and sulfamoyl β-D-glucosamine derivative are described. These pseudonucleosides are synthesized in good yields starting from chlorosulfonyl isocyanate and β-D-glucosamine hydrochloride in five steps; (protection, acetylation, removal of the Boc group, sulfamoylation, and cyclization). Further, novel glycosylated sulfamoyloxazolidin-2-one is prepared in three steps; carbamoylation, sulfamoylation, and intramolecular cyclization. The structures of the synthesized compounds were confirmed by usual spectroscopic and spectrometric methods NMR, IR, MS, and EA. Interesting molecular docking of the prepared pseudonucleosides and (Beclabuvir, Remdesivir) drugs with SARS-CoV-2/Mpro (PDB:5R80) was conducted using the same parameters for a fair comparison. A low binding affinity of the synthesized compounds compared to the Beclabuvir and other analysis showed that pseudonucleosides have the ability to inhibit SARS-CoV-2. After the motivating results of molecular docking study, the complex between the SARS-CoV-2 Mpro and compound 7 was subjected to 100 ns molecular dynamics (MD) simulation using Desmond module of Schrodinger suite, during which the receptor-ligand complex showed substantial stability after 10 ns of MD simulation. Also, we studied the prediction of absorption, distribution, properties of metabolism, excretion, and toxicity (ADMET) of the synthesized compounds. Communicated by Ramaswamy H. Sarma
Maternal serotonin: implications for the use of selective serotonin reuptake inhibitors during gestation

Abstract Maternal use of antidepressants has increased throughout the last decades; selective serotonin reuptake inhibitors (SSRI) are the most prescribed antidepressants. Despite the widespread use of SSRI by women during reproductive age and pregnant women, an increasing amount of research warns of possible detrimental effects of maternal use of SSRI during pregnancy including low birthweight/small for gestational age and preterm birth. In this review, we revisited the impact of maternal use of SSRI during pregnancy, its impact on serotonin homeostasis in the maternal and fetal circulation and the placenta, and its impact on pregnancy outcomes—particularly intrauterine growth restriction and preterm birth. Maternal use of SSRI increases maternal and fetal serotonin. The increase in maternal circulating serotonin and serotonin signaling likely promotes vasoconstriction of the uterine and placental vascular beds decreasing blood perfusion to the uterus and consequently to the placenta and fetus with potential impact on placental function and fetal development. Several adverse pregnancy outcomes are similar between women, sheep, and rodents (decreased placental size, decreased birthweight, shorter gestation length/preterm birth, neonatal morbidity, and mortality) highlighting the importance of animal studies to assess the impacts of SSRI. Herein, we address the complex interactions between maternal SSRI use during gestation, circulating serotonin, and the regulation of blood perfusion to the uterus and fetoplacental unit, fetal growth, and pregnancy complications. Summary Sentence Although SSRI are commonly used by pregnant women, they are associated with detrimental effects on fetal development and pregnancy outcomes likely through increasing maternal circulating serotonin leading to reduced placental vascular perfusion. Graphical Abstract
Hybrid Genome Assemblies of 245 Avian and Broiler Barn Environment-Associated Escherichia coli Strains Isolated from Saskatchewan Broiler Farms

Escherichia coli infections in poultry cause significant morbidity and economic losses for producers each year. In a 3-year period, we collected and sequenced the whole genomes of E. coli disease isolates (n = 91), isolates from presumed healthy birds (n = 61), and isolates from 8 barn sites (n = 93) on broiler farms in Saskatchewan. ABSTRACT Escherichia coli infections in poultry cause significant morbidity and economic losses for producers each year. In a 3-year period, we collected and sequenced the whole genomes of E. coli disease isolates (n = 91), isolates from presumed healthy birds (n = 61), and isolates from 8 barn sites (n = 93) on broiler farms in Saskatchewan.
Risk factors for post-contrast acute kidney injury in patients sequentially administered iodine- and gadolinium-based contrast media on the same visit to the emergency department: a retrospective study

Background This study compares the incidence of post-contrast acute kidney injury (PC-AKI) in patients who received a single administration of iodine-based contrast medium (ICM) with that in patients who received a sequential administration of ICM and gadolinium-based contrast agents (GBCA) in a single visit to an emergency department (ED) to determine the risk factors for PC-AKI. Methods Patients who received one or more contrast media in the ED from 2016 to 2021 were included in this retrospective study. They were divided into the ICM alone and ICM + GBCA groups, and the incidence of PC-AKI was compared between the groups. The risk factors were assessed using a multivariable analysis after propensity score matching (PSM). Results Overall, 6,318 patients were analyzed, of whom 139 were in the ICM + GBCA group. The incidence of PC-AKI was significantly higher in the ICM + GBCA group than in the ICM alone group (10.9% vs. 27.3%, p < 0.001). In the multivariable analysis, sequential administration was a risk factor for PC-AKI, and single administration was not (adjusted odds ratio [95% confidence interval] in the 1:1, 2:1, and 3:1 PSM cohorts: 2.38 [1.25–4.55], 2.13 [1.26–3.60], and 2.28 [1.39–3.72], respectively). In subgroup analyses of the ICM + GBCA group, osmolality (1.05 [1.01–1.10]) and estimated glomerular filtration rate (eGFR, 0.93 [0.88–0.98]) were associated with PC-AKI. Conclusion Compared with a single administration of ICM alone, sequential administration of ICM and GBCA during a single ED visit might be a risk factor for PC-AKI. Osmolality and eGFR might be associated with PC-AKI after sequential administration.