Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-term exposure to low-concentration PM2.5 and heart disease in older men in Perth, Australia: The Health in Men Study

Background: Exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5) is associated with increased risk of heart disease, but less is known about the relationship at low concentrations. This study aimed to determine the dose-response relationship between long-term PM2.5 exposure and risk of incident ischemic heart disease (IHD), incident heart failure (HF), and incident atrial fibrillation (AF) in older men living in a region with relatively low ambient air pollution. Methods: PM2.5 exposure was estimated for 11,249 older adult males who resided in Perth, Western Australia and were recruited from 1996 to 1999. Participants were followed until 2018 for the HF and AF outcomes, and until 2017 for IHD. Cox-proportional hazards models, using age as the analysis time, and adjusting for demographic and lifestyle factors were used. PM2.5 was entered as a restricted cubic spline to model nonlinearity. Results: We observed a mean PM2.5 concentration of 4.95 μg/m3 (SD 1.68 μg/m3) in the first year of recruitment. After excluding participants with preexisting disease and adjusting for demographic and lifestyle factors, PM2.5 exposure was associated with a trend toward increased incidence of IHD, HF, and AF, but none were statistically significant. At a PM2.5 concentration of 7 μg/m3 the hazard ratio for incident IHD was 1.04 (95% confidence interval [CI] = 0.86, 1.25) compared with the reference category of 1 μg/m3. Conclusions: We did not observe a significant association between long-term exposure to low-concentration PM2.5 air pollution and IHD, HF, or AF.
On Similarities Between Workflow Verification and Grammar Checking

The paper investigates the similarities in the application of attribute grammars to two seemingly different research areas, namely the area of formal description of workﬂows and the area of checking the syntactic correctness of natural languages. It uses existing models and formalisms and tries to ﬁnd a common ground which would enable to exploit mutually the experience gained in both individual ﬁelds. It shows how a slight adaptation of a grammar formalism used for grammar checking of languages with a high degree of word-order freedom may lead to a tool useful for a workﬂow veriﬁ-cation.
A Wide Axial Ratio Bandwidth Circularly Polarized Antenna for Spectrum Occupancy Measurement Campaign

The spectrum measurement campaigns conducted worldwide have confirmed by showing that the considerable amount of radio spectrum is underutilized. In the literature, it is observed that most of the spectrum measurement campaign utilizes commercially available antennas. In this communication, a novel circularly polarized wide axial ratio bandwidth circularly polarized microstrip antenna is designed for Spectrum Occupancy Measurement. The antenna exhibits, wide -10 dB impedance bandwidth from 700 MHz to 2.9 GHz and wide -3dB axial ratio bandwidth from 1.5 GHz to 2.7 GHz. The prototype of the antenna is fabricated, and the simulated results show very good agreement with measured results. Thereafter, the spectrum sensing ability of the antenna is verified through the spectrum sensing measurement setup show excellent spectrum sensing ability, -24 to -31.5 dBm in GSM 900 MHz, LTE 2.1 GHz, and ISM 2.4 GHz bands in the outdoor surrounding. The proposed antenna is compact and easily portable and easy to integrate with the spectrum sensing measurement setup.
Dual Student Networks for Data-Free Model Stealing

Existing data-free model stealing methods use a generator to produce samples in order to train a student model to match the target model outputs. To this end, the two main challenges are estimating gradients of the target model without access to its parameters, and generating a diverse set of training samples that thoroughly explores the input space. We propose a Dual Student method where two students are symmetrically trained in order to provide the generator a criterion to generate samples that the two students disagree on. On one hand, disagreement on a sample implies at least one student has classified the sample incorrectly when compared to the target model. This incentive towards disagreement implicitly encourages the generator to explore more diverse regions of the input space. On the other hand, our method utilizes gradients of student models to indirectly estimate gradients of the target model. We show that this novel training objective for the generator network is equivalent to optimizing a lower bound on the generator's loss if we had access to the target model gradients. We show that our new optimization framework provides more accurate gradient estimation of the target model and better accuracies on benchmark classification datasets. Additionally, our approach balances improved query efficiency with training computation cost. Finally, we demonstrate that our method serves as a better proxy model for transfer-based adversarial attacks than existing data-free model stealing methods.
A Backward/Forward Recovery Approach for the Preconditioned Conjugate Gradient Algorithm

: Several recent papers have introduced a periodic veriﬁcation mechanism to detect silent errors in iterative solvers. Chen [PPoPP’13, pp. 167–176] has shown how to combine such a veriﬁcation mechanism (a stability test checking the orthogonality of two vectors and recomputing the residual) with checkpointing: the idea is to verify every d iterations, and to checkpoint every c × d iterations. When a silent error is detected by the veriﬁcation mechanism, one can rollback to and re-execute from the last checkpoint. In this paper, we also propose to combine checkpointing and veriﬁcation, but we use algorithm-based fault tolerance (ABFT) rather than stability tests. ABFT can be used for error detection, but also for error detection and correction, allowing a forward recovery (and no rollback nor re-execution) when a single error is detected. We introduce an abstract performance model to compute the performance of all schemes, and we instantiate it using the preconditioned conjugate gradient algorithm. Finally, we validate our new approach through a set of simulations.
A Theory of Experimenters

This paper proposes a decision-theoretic framework for experiment design. We model experimenters as ambiguity-averse decision-makers, who make trade-offs between subjective expected performance and robustness. This framework accounts for experimenters' preference for randomization, and clarifies the circumstances in which randomization is optimal: when the available sample size is large enough or robustness is an important concern. We illustrate the practical value of such a framework by studying the issue of rerandomization. Rerandomization creates a trade-off between subjective performance and robustness. However, robustness loss grows very slowly with the number of times one randomizes. This argues for rerandomizing in most environments.
PROGRAPHER: An Anomaly Detection System based on Provenance Graph Embedding

In recent years, the Advanced Persistent Threat (APT), which involves complex and malicious actions over a long period, has become one of the biggest threats against the security of the modern computing environment. As a countermeasure, data provenance is leveraged to capture the complex relations between entities in a computing system/network, and uses such information to detect sophisticated APT attacks. Though showing promise in countering APT attacks, the existing systems still cannot achieve a good balance between efficiency, accuracy, and granularity. In this work, we design a new anomaly detection system on provenance graphs, termed P RO G RAPHER . To address the problem of “dependency explosion” of provenance graphs and achieve high efficiency, P RO G RAPHER extracts temporal-ordered snapshots from the ingested logs and performs detection on the snapshots. To capture the rich structural properties of a graph, whole graph embedding and sequence-based learning are applied. Finally, key indicators are extracted from the abnormal snapshots and reported to the analysts, so their workload will be greatly reduced. We evaluate P RO G RAPHER on five real-world datasets. The results show that P RO G RAPHER can detect standard attacks and APT attacks with high accuracy and outperform the state-of-the-art detection systems.
Prescribed consensus and formation error constrained finite-time sliding mode control for multi-agent mobile robot systems

This study addresses a predefined performance constraint control scheme by applying the concept of graph theory to a distributed wheeled mobile robot (WMR) system. The kinematic and dynamic models of the WMR systems are considered simultaneously to design a finite-time sliding mode controller with a novel constraint control term that assures the prescribed performances such as overshoot, rising time, and steady-state error size, for the consensus and formation errors among the distributed WMR systems. Compared with a conventional prescribed controller, the structure of the proposed constraint controller is more compact and can be conveniently implemented in actual systems. The stability conditions and finite convergence time are discussed using the Lyapunov function with the adaptive law to describe the uncertainty. Numerical simulation results of formation control for the WMR systems support the validity of the proposed control method and demonstrate its potential performance.
Radiation reaction formula in electrodynamics from the momentum carried out by the electromagnetic field due to an accelerating charge

As a follow up of the author’s earlier papers the new theory of radiation reaction is placed on a sound theoretical basis. This includes the nature of the equation of motion both under a relativistic Lorentz transformation as well as under a non-relativistic Galilean transformation. It is claimed that both momentum and energy carried out by the radiated fields need to be considered to reach the desired results. It is also shown that the radiation reaction force is non linearly dependent on the externally applied force.
Skill Mismatch One Year Into the COVID19 Pandemic

In this paper, we examine whether the economic recovery from the COVID19 pandemic has been accompanied by abnormal rates mismatch between an individual’s pre-pandemic occupation and their occupation in the first five months of 2021. We consider an individual to be mismatched if they are employed in a new occupation that is not higher paying than their pre-pandemic occupation, is not contained within the same 2 digit occupation code as their new occupation, and has dissimilar skills requirements from their pre-pandemic occupation as measured by the Euclidean distance between the O*NET skills of the two occupations. We find evidence of an increase in the prevalence of mismatch for women, Hispanics, married individuals,individuals with a high school level education, and workers at the beginning of their careers. With the exception of married individuals, these demographic groups largely correspond to the demographic groups for which non-employment rates increased the most in spring 2020. We find that this rise in mismatch is entirely driven by individuals who were out of work in spring 2020, indicating that this mismatch is a result of individuals who are returning to work being unable to find work in occupations that are well matched. Corresponding author We would like to thank Guido Matias Cortes, Ye Jia, Justin Kakeu, Fabian Lange, Huju Liu, and Wimal Rankaduwa for their helpful comments. We would also like to thank participants at the 55th Annual Canadian Economics Association Meetings, and seminar participants at the University of Prince Edward Island.
Comparison of two nationwide lightning location systems and 1 characteristics of could-to-ground lightning in China 2

8 The lightning location system based on multiple sub-stations is an effective means 9 of lightning observation. This study first compares the two nationwide lightning 10 location systems in China, the Advanced TOA and Detection System (ADTD) and the 11 Three-Dimensional Lightning Location System (3D-LLS), using the observations in 12 2020. As a significantly updated version of ADTD, 3D-LLS has a cloud-to-ground (CG) 13 detection efficiency of nearly twice ADTD. However, its scarce distribution sites in 14 central Tibet, western Xinjiang, eastern Qinghai, and eastern Heilongjiang account for 15 some blind observation areas where ADTD could play a supplementary role. The ratio 16 of +CG and the distribution of currents indicate that 3D-LLS misjudges a certain 17 number of intracloud (IC) pulses as return strokes. Besides, the IC detection developed 18 by 3D-LLS is still inefficient. In the results, the IC flashes only account for half of CG 19 flashes, much smaller than the regular ratio (twice). According to the comparison with 20 the nearly no-miss optical observations in Guangzhou, the CG detection efficiency of 21 ADTD and 3D-LLS herein is 24.5% and 50.5%. Further improvements are expected in 22 terms of the above shortages. Still, the ground-based observation has better detection 23 efficiency and accuracy than the satellite, especially for CG lightning. The dataset from 24 ADTD in 2016-2021 is employed to analyze the lightning characteristics' temporal and 25 spatial distributions and the difference between +CG and -CG over China. It can be 26 concluded that low
InSARViz: an open source interactive visualization tool for InSAR

Satellite SAR interferometry (InSAR [3]) is a wellestablished technique in Earth Observation that is able to monitor ground displacement with a high precision (up to mm/year), combining high spatial resolution (up to a few m) and large coverage capabilities (up to continental scale) with a temporal resolution from a few days to a few weeks. It is used to study a wide range of phenomena (e.g. earthquakes, landslides, permafrost, volcanoes, glaciers dynamics, subsidence, building and infrastructure deformation, etc.) In this project we are mainly interested in the tectonic loading of faults the leads to earthquakes. Actually, the loading of faults is done through slow tectonic plates motion (few cm/year to mm/year). Estimating this load and its variability is critical to understand the mechanics that lead to earthquake, hence evaluate the seismic hazard [1]. To be relevant, the measure has to be done on large spatial areas (e.g. six time the surface of France) with a resolution of around one hundred meters.
Response of “The Important Contribution of Secondary Formation and Biomass Burning to Oxidized Organic Nitrogen (OON) in a Polluted Urban Area: Insights from In Situ FIGAERO-CIMS Measurements” in Atmos

2.0. The authors performed measurements of gas and particle-phase organic compounds using a FIGAERO-CIMS in a polluted urban location in China, with a particular focus in oxidized organic nitrogen species. Using C6H10O5 (levoglucosan) as a tracer, they estimated the contribution of biomass burning to the measured gas and particle concentrations. Calculations were done to estimate the contribution of different oxidants and precursors to secondary organic nitrogen production. Broadly, the measurements and analysis presented in this manuscript are useful for helping to understand sources of organic nitrogen gases and particles in urban areas. Before this work is published, I believe there are several major issues that should be addressed. If I understand the experimental setup correctly, I am worried about the impact of sampling through a nafion tube. I think the authors should consider how much that could affect their measurements in light of recent literature on the topic. I also want to see an uncertainty analysis of the measurements, especially of the voltage scanning technique that is still a relatively new method of CIMS quantification. Taken together, I think the authors should carefully discuss the strengths or limits of their conclusions in the context of these uncertainties. A2.0. We appreciate the reviewer for his/her insightful comments and suggestions, which help us tremendously in improving the quality of our work. Following the reviewer’s suggestions, we have carefully revised the manuscript. To facilitate the review process, we have copied the reviewer comments in black text. Our responses are in regular blue font. We have responded to all the referee comments and made alterations to our paper (in bold text).
Modeling and Testing of Control Logic Approaches for Series Hybrid-Electric Powertrain for Unmanned Aerial Systems

Hybrid-Electric aircraft powertrain modeling for Unmanned Aerial Systems (UAS) is a useful tool for predicting powertrain performance of the UAS aircraft. UAS aircraft utilize small-displacement engines that have poor thermal eﬃciency and, as a result, could beneﬁt from a hybridized powertrain by reducing fuel consumption. The scope of this work aims to model a hybrid electric powertrain and explore diﬀerent control strategies that can be validated on a physical system. Utilizing MATLAB Simulink, a powertrain model will be developed that can estimate the component power requirements during mission segments, as well as provide a system model for a comparative study of rule-based control strategies
Deep-Learning based Filter for Hardware Prefetchers

Prefetching is one of the techniques that is widely used to hide the memory latency by bringing the data into the caches before the processor asks for it. Thus, for a prefetcher to be e↵ective, it must not only be accurate in its prefetching decisions, but also be timely because transferring data from the main-memory to the caches takes time. Even if a prefetcher is 100% accurate, if it fails to achieve timeliness, then the utility of prefetching reduces and it might reduce the performance of a system instead because of the increased memory tra c. Conversely, even if the prefetcher is 100% timely, but is not accurate, it will drastically reduce the performance of a system, especially under low memory bandwidth due to increased miss penalty and eviction of possibly useful cache-lines. This work proposes a deep-learning based filter that can be augmented with any prefetcher and can improve timeliness as well as accuracy of the prefetchers. Although it is a proof-of-concept, it shows promising results by achieving near-similar performance by significantly reducing the memory tra c.
Exploring aerosol-cloud interactions over eastern China and its adjacent ocean using the WRF-SBM-MOSAIC model

This study aims to explore aerosol-cloud interaction over eastern China (EC) and its adjacent ocean (ECO) in boreal winter by coupling of a spectral-bin cloud microphysics (SBM) and an online aerosol module (MOSAIC) in WRF-Chem, with the support of four-dimensional data assimilation. The evaluation shows that assimilation has an overall positive impact on the 10 simulation, and the coupling system reproduces the satellite-retrieved cloud parameters while exhibiting significantly improved simulation ability compared to the original SBM scheme as well as the bulk microphysical and MOSAIC coupling system. Differences in aerosol composition and physical processes lead to clear discrepancies in the aerosol-cloud interactions of EC and ECO during the simulation period. In EC with the gradual increase of aerosol number concentration (N aero ), cloud droplet number concentration (N d ) first increases then decreases and fluctuates around 800 cm -3 , while N d in ECO increases 15 faster initially, but soon its activation is suppressed by aerosol hygroscopicity and high activation threshold of numerous small particles, and almost no additional cloud droplets are produced. In terms of rapid adjustments, more bursty atmospheric supersaturation and lack of subsequent water cause cloud liquid water content (CLWC) in EC to increase explosively with N d when there are few cloud droplets, but only maintains a low increase rate with further increasing N d . ECO exhibits a fast increase in CLWC with N d at high proportion of naturally emitted large aerosol particles, but its CLWC increase gradually 20 stagnates as N d increases. For non-precipitating clouds with less water content, CLWC in EC increases slowly with N d , but can maintain a stable trend. While ECO, which relies mainly on large scale water and temperature variations to reach supersaturation, the increase in N d leads to a decrease in CLWC
Operational modal analysis of two identical single span road bridges

Identification of modal parameters using response only measurements on the two identical single span road bridges is presented. The main advantage of output – only measurements is that it is not necessary to have information about excitation applied to the investigated structure. This technique is known as Operational modal analysis (OMA) as it uses ambient excitation, in this case heavy trucks passing over the bridge multiple times. Furthermore, 3D finite element numerical model of the bridge superstructure was constructed, and results were compared to the measured ones. Overview of modal parameters (natural frequencies, modal shapes and damping ratios) determined on two identical road bridges using Operational modal analysis and their comparison to the results calculated within numerical model are given. Experimentally determined modal parameters can be used for damage detection and assessment of health condition of the structure as damage, i.e. and structural deterioration causes changes in these parameters. Finally, the aim was to validate a cost effective and time saving procedure of modal parameter determination.
In-vitro antimicrobial activity of Acacia farnesiana & Rosmarinus officinalis crude extract and isolated compounds against foodborne pathogens

: This study aims at evaluating the antimicrobial activity of the extracts derived from Acacia farnesiana and Rosmarinus officinalis . The two medicinal plants are used traditionally in Al-Madinah Al-Munawarah for the treatment of diarrhea. The bioassay-guided fractionation of the ethanol extract and further purification of the most antibacterial active fraction led to the isolation and identification of carnosol from Rosmarinus officinalis , O - galloyl- D -glucopyranose, and 5, 6, 3', 5' tetrahydroxy 7,8, 4' trimethoxy flavones from Acacia farnesiana. The ethanolic extracts and the three isolated compounds were screened against both Gram-positive bacteria, Bacillus cereus and Staphylococcus aureus , and Gram-negative bacteria, Escherichia coli . The crude extracts and compounds showed antimicrobial activities against most of the strains with Gram-negative strains being more resistant. The inhibitory effect of carnosol started at 500 µg/ml with an inhibition zone of 7.3 against S. aureus. Rosmarinus officinalis extract and O -galloyl- D -glucopyranose inhibited B. cereus growth at a concentration of 250 µg/ml and 125 µg/ml with 10.1 and 11.3 mm inhibition zones, respectively. Carnosol suppressed S. aureus and B. cereus at concentrations of 500 and 125 µg/ml with 11.1 and 9.1 mm inhibition zones respectively. Acacia farnesiana extract inhibited the growth of B. cereus , S. aureus , and E. coli at a concentration of 125 µg/ml with an inhibition zone of 10.5, 7.2 and 12.8 mm, respectively. The presented data show that Acacia farnesiana and Rosmarinus officinalis could potentially use as an attractive alternative to control food poisoning bacteria and as a natural source of food preservatives.