Miracle-dz/UniFAR-FTUs huggingface dataset:
Domain Adaptation via Alignment of Operation Profile for Remaining Useful Lifetime Prediction

Effective Prognostics and Health Management (PHM) relies on accurate prediction of the Remaining Useful Life (RUL). Data-driven RUL prediction techniques rely heavily on the representativeness of the available time-to-failure trajectories. Therefore, these methods may not perform well when applied to data from new units of a fleet that follow different operating conditions than those they were trained on. This is also known as domain shifts. Domain adaptation (DA) methods aim to address the domain shift problem by extracting domain invariant features. However, DA methods do not distinguish between the different phases of operation, such as steady states or transient phases. This can result in misalignment due to under- or over-representation of different operation phases. This paper proposes two novel DA approaches for RUL prediction based on an adversarial domain adaptation framework that considers the different phases of the operation profiles separately. The proposed methodologies align the marginal distributions of each phase of the operation profile in the source domain with its counterpart in the target domain. The effectiveness of the proposed methods is evaluated using the New Commercial Modular Aero-Propulsion System (N-CMAPSS) dataset, where sub-fleets of turbofan engines operating in one of the three different flight classes (short, medium, and long) are treated as separate domains. The experimental results show that the proposed methods improve the accuracy of RUL predictions compared to current state-of-the-art DA methods.
Fast and accurate single frequency estimator

A new fast and accurate method for estimating the frequency of a complex sinusoid in complex white Gaussian noise is proposed. The proposed estimator has the lowest computational complexity among the estimators. Its performance and estimation range are similar to the Fitz and L&R estimators, and its threshold is 20 log(m) less than the Kay estimator.
Self-Supervised In-Domain Representation Learning for Remote Sensing Image Scene Classification

Transferring the ImageNet pre-trained weights to the various remote sensing tasks has produced acceptable results and reduced the need for labeled samples. However, the domain differences between ground imageries and remote sensing images cause the performance of such transfer learning to be limited. Recent research has demonstrated that self-supervised learning methods capture visual features that are more discriminative and transferable than the supervised ImageNet weights. We are motivated by these facts to pre-train the in-domain representations of remote sensing imagery using contrastive self-supervised learning and transfer the learned features to other related remote sensing datasets. Specifically, we used the SimSiam algorithm to pre-train the in-domain knowledge of remote sensing datasets and then transferred the obtained weights to the other scene classification datasets. Thus, we have obtained state-of-the-art results on five land cover classification datasets with varying numbers of classes and spatial resolutions. In addition, By conducting appropriate experiments, including feature pre-training using datasets with different attributes, we have identified the most influential factors that make a dataset a good choice for obtaining in-domain features. We have transferred the features obtained by pre-training SimSiam on remote sensing datasets to various downstream tasks and used them as initial weights for fine-tuning. Moreover, we have linearly evaluated the obtained representations in cases where the number of samples per class is limited. Our experiments have demonstrated that using a higher-resolution dataset during the self-supervised pre-training stage results in learning more discriminative and general representations.
Impact of a Cold Control Plate on Fluid Flow and Heat Transfer across an Isothermally Heated Rotary Oscillating Circular Cylinder

The main objective of this paper is to study the effect of a cold, vertical, arc-shaped control plate on the flow characteristics and forced convective heat transfer mechanism across a rotary oscillating, isothermally heated circular cylinder. Two-dimensional, unsteady, incompressible, laminar, and viscous flow of a Newtonian, constant property fluid is considered across the cylinder. The simulations are performed with an in-house code for various gap ratios between the control plate and the cylinder ($0\leq d/R_0 \leq 3$), maximum angular velocity ($0.5\leq \alpha_m \leq 4$) and frequency ratio of oscillation ($f/f_0=0.5,\ 3$) at Prandtl number $0.7$ and Reynolds number $150$. Here, $d$ denotes the gap between the surface of the cylinder and the leading surface of the control plate, $R_0$ denotes the radius of the cylinder, $f$ is the frequency of oscillation and $f_0$ is the frequency of natural vortex shedding. $d/R_0=0$ corresponds to the no plate case. Heat transfer and vortex shedding phenomena are discussed in relation to one another. A significant increase in heat transmission is observed for all $\alpha_m$ with the gap ratio of $d/R_0=0.5$ and $f/f_0=0.5$. The heat absorption on the surface of the control plate decreases to zero with increasing gap ratio when $\alpha_m=0.5$ and $f/f_0=0.5$ but never becomes zero when $\alpha_m=4$ and $f/f_0=3$. Additionally, when compared to the no plate case with $(\alpha_m,\ f/f_0)=(0.5,\ 0.5)$, the maximum peak of the drag coefficient is decreased by $9.877\%$ for the gap ratio of $d/R_0=3$. For $\alpha_m=4$ and $f/f_0=3$, the smallest gap ratio of $d/R_0=0.5$ is found to significantly increase the lift coefficient relative to other cases.
Blockwise Self-Supervised Learning at Scale

Current state-of-the-art deep networks are all powered by backpropagation. In this paper, we explore alternatives to full backpropagation in the form of blockwise learning rules, leveraging the latest developments in self-supervised learning. We show that a blockwise pretraining procedure consisting of training independently the 4 main blocks of layers of a ResNet-50 with Barlow Twins' loss function at each block performs almost as well as end-to-end backpropagation on ImageNet: a linear probe trained on top of our blockwise pretrained model obtains a top-1 classification accuracy of 70.48%, only 1.1% below the accuracy of an end-to-end pretrained network (71.57% accuracy). We perform extensive experiments to understand the impact of different components within our method and explore a variety of adaptations of self-supervised learning to the blockwise paradigm, building an exhaustive understanding of the critical avenues for scaling local learning rules to large networks, with implications ranging from hardware design to neuroscience.
Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval

Recently multi-lingual pre-trained language models (PLM) such as mBERT and XLM-R have achieved impressive strides in cross-lingual dense retrieval. Despite its successes, they are general-purpose PLM while the multilingual PLM tailored for cross-lingual retrieval is still unexplored. Motivated by an observation that the sentences in parallel documents are approximately in the same order, which is universal across languages, we propose to model this sequential sentence relation to facilitate cross-lingual representation learning. Specifically, we propose a multilingual PLM called masked sentence model (MSM), which consists of a sentence encoder to generate the sentence representations, and a document encoder applied to a sequence of sentence vectors from a document. The document encoder is shared for all languages to model the universal sequential sentence relation across languages. To train the model, we propose a masked sentence prediction task, which masks and predicts the sentence vector via a hierarchical contrastive loss with sampled negatives. Comprehensive experiments on four cross-lingual retrieval tasks show MSM significantly outperforms existing advanced pre-training models, demonstrating the effectiveness and stronger cross-lingual retrieval capabilities of our approach. Code and model will be available.
Crescent-shaped Molecular Outflow from the Intermediate-mass Protostar DK Cha Revealed by ALMA

We report on an Atacama Large Millimeter/submillimeter Array study of the Class I or II intermediate-mass protostar DK Cha in the Chamaeleon II region. The 12CO(J = 2–1) images have an angular resolution of ∼1″ (∼250 au) and show high-velocity blueshifted (≳70 km s−1) and redshifted (≳50 km s−1) emissions, which have 3000 au scale crescent-shaped structures around the protostellar disk traced in the 1.3 mm continuum. Because the high-velocity components of the CO emission are associated with the protostar, we concluded that the emission traces the pole-on outflow. The blueshifted outflow lobe has a clear layered velocity gradient with a higher-velocity component located on the inner side of the crescent shape, which can be explained by a model of an outflow with a higher velocity in the inner radii. Based on the directly driven outflow scenario, we estimated the driving radii from the observed outflow velocities and found that the driving region extends over 2 orders of magnitude. The 13CO emission traces a complex envelope structure with arc-like substructures with lengths of ∼1000 au. We identified the arc-like structures as streamers because they appear to be connected to a rotating infalling envelope. DK Cha is useful for understanding characteristics that are visible by looking at nearly face-on configurations of young protostellar systems, providing an alternative perspective for studying the star formation process.
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback

We study stochastic delayed feedback in general multi-agent sequential decision making, which includes bandits, single-agent Markov decision processes (MDPs), and Markov games (MGs). We propose a novel reduction-based framework, which turns any multi-batched algorithm for sequential decision making with instantaneous feedback into a sample-efficient algorithm that can handle stochastic delays in sequential decision making. By plugging different multi-batched algorithms into our framework, we provide several examples demonstrating that our framework not only matches or improves existing results for bandits, tabular MDPs, and tabular MGs, but also provides the first line of studies on delays in sequential decision making with function approximation. In summary, we provide a complete set of sharp results for multi-agent sequential decision making with delayed feedback.
Results of Treatment with Modern Fractionated Radiotherapy, Contemporary Stereotactic Radiosurgery, and Transsphenoidal Surgery in Nonfunctioning Pituitary Macroadenoma

Background: To compare the effects of contemporary stereotactic radiosurgery (SRS), modern fractionated radiotherapy (FRT), and transsphenoidal surgery on nonfunctioning pituitary macroadenoma. Methods: We enrolled patients with nonfunctioning pituitary macroadenoma. To compare treatment outcomes, the patients were categorized into three groups according to the treatment modality: group 1, patients receiving modern FRT; group 2, patients receiving contemporary SRS; and group 3, patients receiving transsphenoidal surgery. Results: In total, 548 patients with nonfunctioning pituitary macroadenoma were selected for our study. Univariate and multivariate Cox regression analysis results indicated that the treatment modalities were significant independent prognostic factors. In multivariable Cox proportional hazard regression analysis, the adjusted hazard ratios (aHR; 95% confidence interval (CI)) of local recurrence were 0.27 (0.10–0.91) and 1.95 (1.25–2.37) for the SRS and transsphenoidal surgery cohorts, respectively, in comparison with the FRT cohort. The aHR (95% CI) of all-cause mortality was 1.03 (0.68–1.56) for the transsphenoidal surgery cohort in comparison with the FRT cohort, without statistical significance. However, the aHR (95% CI) of all-cause mortality was 0.36 (0.15–0.85) for the SRS cohort in comparison with the FRT cohort. Conclusion: Contemporary SRS has optimal effects on local recurrence and survival compared with modern FRT and transsphenoidal surgery. Modern FRT is associated with more favorable local control and equal survival compared with transsphenoidal surgery.
XMD: An Expansive Hardware-Telemetry-Based Mobile Malware Detector for Endpoint Detection

Hardware-based Malware Detectors (HMDs) have shown promise in detecting malicious workloads. However, the current HMDs focus solely on the CPU core of a System-on-Chip (SoC) and, therefore, do not exploit the full potential of the hardware telemetry. In this paper, we propose XMD, an HMD that uses an expansive set of telemetry channels extracted from the different subsystems of SoC. XMD exploits the thread-level profiling power of the CPU-core telemetry, and the global profiling power of non-core telemetry channels, to achieve significantly better detection performance than currently used Hardware Performance Counter (HPC) based detectors. We leverage the concept of manifold hypothesis to analytically prove that adding non-core telemetry channels improves the separability of the benign and malware classes, resulting in performance gains. We train and evaluate XMD using hardware telemetries collected from 723 benign applications and 1033 malware samples on a commodity Android Operating System (OS)-based mobile device. XMD improves over currently used HPC-based detectors by 32.91% for the in-distribution test data. XMD achieves the best detection performance of 86.54% with a false positive rate of 2.9%, compared to the detection rate of 80%, offered by the best performing signature-based Anti-Virus(AV) on VirusTotal, on the same set of malware samples.
Decay of isotropic turbulence in the initial period

In a previous paper the authors described direct measurements of all the terms in the equation for the rate of change of mean square vorticity in isotropic turbulence. The present paper is concerned with developments arising from the earlier work and with the experimental verification of some recent theoretical investigations. The results of measurements of the turbulent intensity u' and of λ are presented; these establish that u'-2 and λ2 are each proportional to the time of decay provided that the time is not too large. Within this initial period of the decay, the double and triple velocity correlation functions are found to maintain their form, i.e. to be self-preserving, for small values of the distance r between the two points at which the correlations are taken. For larger separations the double velocity correlation function changes its form slightly during decay and direct measurements of λ and of the integral scale L show that λ/L increases during the decay. Theoretical predictions about the shape of the correlation function, for limited ranges of r, at high and at low Reynolds numbers are compared with measurements. Theory has shown that the above decay law cannot persist indefinitely, and the present experiments confirm that the decay law changes in the expected direction when the time is large. A division of the life-history of the turbulence into initial, transition and final periods is suggested; within the initial period, a classification based on the Reynblds number is also possible. Some speculations on the interpretation of the initial period are presented.
Assessing the role of family level variation and heat shock gene expression in the thermal stress response of the mosquito Aedes aegypti

The geographical range of the mosquito vector for many human disease-causing viruses, Aedes aegypti, is expanding, in part owing to changing climate. The capacity of this species to adapt to thermal stress will affect its future distributions. It is unclear how much heritable genetic variation may affect the upper thermal limits of mosquito populations over the long term. Nor are the genetic pathways that confer thermal tolerance fully understood. In the short term, cells induce a plastic, protective response known as 'heat shock'. Using a physiological ‘knockdown’ assay, we investigated mosquito thermal tolerance to characterize the genetic architecture of the trait. While families representing the extreme ends of the distribution for knockdown time differed from one another, the trait exhibited low but non-zero broad-sense heritability. We then explored whether families representing thermal performance extremes differed in their heat shock response by measuring gene expression of heat shock protein-encoding genes Hsp26, Hsp83 and Hsp70. Contrary to prediction, the families with higher thermal tolerance demonstrated less Hsp expression. This pattern may indicate that other mechanisms of heat tolerance, rather than heat shock, may underpin the stress response, and the costly production of HSPs may instead signal poor adaptation. This article is part of the theme issue ‘Infectious disease ecology and evolution in a changing world’.
Infection burdens and virulence under heat stress: ecological and evolutionary considerations

As a result of global change, hosts and parasites (including pathogens) are experiencing shifts in their thermal environment. Despite the importance of heat stress tolerance for host population persistence, infection by parasites can impair a host's ability to cope with heat. Host–parasite eco-evolutionary dynamics will be affected if infection reduces host performance during heating. Theory predicts that within-host parasite burden (replication rate or number of infecting parasites per host), a key component of parasite fitness, should correlate positively with virulence—the harm caused to hosts during infection. Surprisingly, however, the relationship between within-host parasite burden and virulence during heating is often weak. Here, we describe the current evidence for the link between within-host parasite burden and host heat stress tolerance. We consider the biology of host–parasite systems that may explain the weak or absent link between these two important host and parasite traits during hot conditions. The processes that mediate the relationship between parasite burden and host fitness will be fundamental in ecological and evolutionary responses of host and parasites in a warming world. This article is part of the theme issue ‘Infectious disease ecology and evolution in a changing world’.
Intraspecific trait variation and changing life-history strategies explain host community disease risk along a temperature gradient

Predicting how climate change will affect disease risk is complicated by the fact that changing environmental conditions can affect disease through direct and indirect effects. Species with fast-paced life-history strategies often amplify disease, and changing climate can modify life-history composition of communities thereby altering disease risk. However, individuals within a species can also respond to changing conditions with intraspecific trait variation. To test the effect of temperature, as well as inter- and intraspecifc trait variation on community disease risk, we measured foliar disease and specific leaf area (SLA; a proxy for life-history strategy) on more than 2500 host (plant) individuals in 199 communities across a 1101 m elevational gradient in southeastern Switzerland. There was no direct effect of increasing temperature on disease. Instead, increasing temperature favoured species with higher SLA, fast-paced life-history strategies. This effect was balanced by intraspecific variation in SLA: on average, host individuals expressed lower SLA with increasing temperature, and this effect was stronger among species adapted to warmer temperatures and lower latitudes. These results demonstrate how impacts of changing temperature on disease may depend on how temperature combines and interacts with host community structure while indicating that evolutionary constraints can determine how these effects are manifested under global change. This article is part of the theme issue ‘Infectious disease ecology and evolution in a changing world’.
The Cooling White Dwarf in VW Hydri after Normal Outburst and Superoutburst: HST Evidence of A Sustained Accretion Belt

Hubble Faint Object Spectrograph (FOS) observations of VW Hyi one day after the end of a normal dwarf nova outburst reveal a heated white dwarf with deep, broad Lyα, narrow metallic absorption features, and evidence of a hotter Keplerian-broadened component manifested in quiescence as a broad continuum hump. Our best reduced χ2 fit to the data reveals (1) a DAZQ white dwarf with Teff = 22,500 ± 500 K, log g = 8, and photospheric abundances C = 0.5 solar, N = 5.0 solar, O = 2.0 solar, Si = 0.2 solar, Fe = 0.5 solar, with all other metals being 0.3 solar, and (2) a rapidly spinning accretion belt with Vrot = 3350 km s-1, Tbelt = 26,000 ± 1000 K, log g = 6.0, and a fractional belt area of approximately 11%. Our earlier FOS spectrum obtained 10 days after superoutburst reveals a cooler DAZQ white dwarf (20,500 ± 1000 K), relatively lower metal abundances, and a smaller fractional area (3%) for the accretion belt. Thus, 1 day after a normal outburst, the white dwarf is ≈ 2000 K hotter, the accretion belt fractional area is a factor of 3 greater, the accretion belt temperature appears to be cooler than at 10 days post-superoutburst, and the accreted atmosphere has relatively higher metal abundances. Finally, the accretion belt maintained during quiescence may provide a natural explanation for the 14 s soft X-ray oscillations, requires a deeper source of heating (compression and shear mixing), and implies a lower limit to the viscous spin-down timescale of 10 days.
Long-term Effects of Androgen Deprivation in a Patient with Spinal and Bulbar Muscular Atrophy - A Case Report with 14 Years of Follow-up

Spinal and bulbar muscular atrophy (SBMA) is a progressive hereditary neuromuscular disease caused by the testosterone-dependent accumulation of pathogenic polyglutamine-expanded androgen receptor protein. A 41-year-old man with SBMA received the androgen deprivation agent leuprorelin acetate for 7 years in clinical trials and underwent castration following the trial. Suppression of testosterone levels for 14 years resulted in a slower disease progression, as measured prospectively with quantitative measurements, than the historical control data reported in previous studies. This suggests that long-term androgen deprivation delays disease progression in SBMA.
Central Limit Theorem And Law Of Iterated Logarithm For Least Squares Algorithms In Adaptive Tracking

In autoregressive adaptive tracking, we prove that the least squares and the weighted least squares algorithms possess the same asymptotic properties, sharing the same central limit theorem and the same law of iterated logarithm. We also obtain the same asymptotic behavior and show the limitations of these results in the autoregressive with moving average framework.
VLBI observations of southern EGRET identifications .1. PKS 0208-512, PKS 0521-365, and PKS 0537-441

We present high-resolution very long baseline interferometry images of three southern radio sources that the Energetic Gamma-Ray Experiment Telescope (EGRET), on board the Compton Gamma Ray Observatory, has identified as greater than 100 MeV gamma-ray sources. These are the first results in a continuing program of VLBI observations of southern EGRET identifications. For two of these sources, PKS 0208-512 (at 4.851 GHz) and PKS 0537-441 (at 4.851 and 8.418 GHz), the images represent first-epoch observations. For the remaining lower redshift object, PKS 0521-365, we present images from three epochs at 4.851 GHz and an image from one further epoch at 8.418 GHz, spanning approximately 1 yr. We discuss the need for further extensive VLBI observations of EGRET-identified radio sources.