Miracle-dz/UniFAR-FTUs huggingface dataset:
Data report: marine tephra compositions in the deep drilling cores of the South China Sea, IODP Expeditions 349 and 367/368 1

We present geochemical major and trace element glass data for tephra samples from International Ocean Discovery Program (IODP) Expeditions 349 and 367/368 from four drilling sites in the South China Sea. Overall, we obtained data for 55 samples and identified 46 as tephra layers, with dominant volcanic glass shards in the component inventory (in the 63–125 μ fraction). In total, we performed 720 single glass shard analyses using an electron microprobe for major element compositions, as well as 130 single glass shard analyses using laser ablation–inductively coupled plasma– mass spectrometry (LA-ICP-MS) for trace element compositions. The compositions of the samples range from basaltic, (trachy-) andesitic to trachytic, and rhyolitic and fall mainly into the calc-alkaline and K-rich calc-alkaline magmatic series. One sample falls into the shoshonitic series. Tephras from Expedition 349 Site U1431 span the whole compositional range, whereas tephras from the other sites are limited to rhyolitic composition. Tephra ages, calculated applying sedimentation rates, range to ~2 Ma at Site U1431, ~0.8 Ma at Expedition 367 Site U1499, ~0.6 Ma at Expedition 368 Site U1501, and ~0.9 Ma at Expedition 368 Site U1505.
Extension of Ekman (1905) wind-driven transport theory to the β plane

Abstract. The seminal Ekman (1905) f-plane theory of wind-driven transport at the ocean surface is extended to the β plane by substituting the pseudo-angular momentum for the zonal velocity in the Lagrangian equation. When the β term is added, the equations become nonlinear, which greatly complicates the analysis. Though rotation relates the momentum equations in the zonal and the meridional directions, the transformation to pseudo-angular momentum greatly simplifies the longitudinal dynamics, which yields a clear description of the meridional dynamics in terms of a slow drift compounded by fast oscillations; this can then be applied to describe the motion in the zonal direction. Both analytical expressions and numerical calculations highlight the critical role of the Equator in determining the trajectories of water columns forced by eastward-directed (in the Northern Hemisphere) wind stress even when the water columns are initiated far from the Equator. Our results demonstrate that the averaged motion in the zonal direction depends on the amplitude of the meridional oscillations and is independent of the direction of the wind stress. The zonal drift is determined by a balance between the initial conditions and the magnitude of the wind stress, so it can be as large as the mean meridional motion; i.e., the averaged flow direction is not necessarily perpendicular to the wind direction.
Biochemical characterization of the ﬁ rst step in sulfonolipid biosynthesis in Alistipes ﬁ negoldii

Sulfonolipids are unusual lipids found in the outer mem-branes of Gram-negative bacteria in the phylum Bacteroidetes. Sulfonolipid and its deacylated derivative, capnine, are sulfur analogs of ceramide-1-phosphate and sphingosine-1-phosphate, respectively; thus, sulfonolipid biosynthesis is postulated to be similar to the sphingolipid biosynthetic pathway. Here, we identify the ﬁ rst enzyme in sulfonolipid synthesis in Alistipes ﬁ negoldii as the product of the al ﬁ _1224 gene, cysteate acyl-acyl carrier protein (ACP) transferase (SulA). We show SulA catalyzes the condensation of acyl-ACP and cysteate (3-sulfo-alanine) to form 3-ketocapnine. Acyl-CoA is a poor substrate. We show SulA has a bound pyridoxal phosphate (PLP) cofactor that undergoes a spectral redshift in the presence of cysteate, consistent with the transition of the lysine – aldimine complex to a substrate – aldimine complex. Furthermore, the SulA crystal structure shows the same pro-totypical fold found in bacterial serine palmitoyltransferases (Spts), enveloping the PLP cofactor bound to Lys251. We observed the SulA and Spt active sites are identical except for Lys281 in SulA, structural role in assembling the SulA active site rather than promoting cysteate binding by charge neutralization.
IN Affirmative Action, Percent and Holistic

There is considerable interest in the impact of policy alternatives to race-based affirmative action (AA) on under-represented minority (URM) university enrollment. Widely-implemented alternatives include percent plans, which guarantee admission to top high school students, and holistic review, in which applications are evaluated on a comprehensive set of merits. This study estimates each policy's URM enrollment effect at the University of California (UC). Difference-in-difference estimates show that AA increased annual UC URM enrollment by more than 8 00 students ( 20 %), and by more than 60% at the Berkeley and UCLA campuses. Three years after UC's AA program ended in 1998, UC guaranteed admission to the top 4 percent of students from each California high school under its Eligibility in the Local Context program. Extrapolation from a regression discontinuity design shows that ELC increased total URM enrollment among applicants annually by about 250, or 3.5%, primarily at three UC campuses. ELC largely ceased impacting UC enrollment after a 2012 reform, but triple-difference estimates show that several campuses' simultaneous switches to holistic review prevented URM enrollment decline. Six UC campuses have implemented holistic review, with an event study suggesting that each implementation increased URM enrollment at that campus by about 10%, though some enrollees were pulled from other UC campuses. While AA had a larger effect on URM enrollment than percent plans or holistic review, the latter policies have substantively mitigated URM enrollment declines at some UC campuses following AA's prohibition.
Hydrodynamics of higher-rank gauge theories

We extend recent work on hydrodynamics with global multipolar symmetries — known as “fracton hydrodynamics” — to systems in which the multipolar symmetries are gauged. We refer to the latter as “fracton magnetohydrodynamics”, in analogy to conventional magnetohydrodynamics (MHD), which governs systems with gauged charge conservation. We show that fracton MHD arises naturally from higher-rank Maxwell’s equations and in systems with one-form symmetries obeying certain constraints; while we focus on “minimal” higher-rank generalizations of MHD that realize diffusion, our methods may also be used to identify other, more exotic hydrodynamic theories (e.g., with magnetic subdiffusion). In contrast to semi-microscopic derivations of MHD, our approach elucidates the origin of the hydrodynamic modes by identifying the corresponding higher-form symmetries. Being rooted in symmetries, the hydrodynamic modes may persist even when the semi-microscopic equations no longer provide an accurate description of the system.
Anomaly Detection in a Data Center with a Reconstruction Method Using a Multi-Autoencoders Model

 Abstract — Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.
Poseidon: Efficient, Robust, and Practical Datacenter CC via Deployable INT

The difﬁculty in gaining visibility into the ﬁne-timescale hop-level congestion state of networks has been a key chal-lenge faced by congestion control (CC) protocols for decades. However, the emergence of commodity switches supporting in-network telemetry (INT) enables more advanced CC. In this paper, we present Poseidon , a novel CC protocol that ex-ploits INT to address blind spots of CC algorithms and realize several fundamentally advantageous properties. First, Poseidon is efﬁcient : it achieves low queuing delay, high throughput, and fast convergence. Furthermore, Poseidon decouples bandwidth fairness from the traditional AIMD control law, using a novel adaptive update scheme that converges quickly and smooths out oscillations. Second, Poseidon is robust : it realizes CC for the actual bottleneck hop , and achieves max-min fairness across trafﬁc patterns, including multi-hop and reverse-path congestion. Third, Poseidon is practical : it is amenable to incremental brownﬁeld deployment in networks that mix INT and non-INT switches. We show, via testbed and simulation experiments, that Poseidon provides signiﬁcant improvements over the state-of-the-art Swift CC algorithm across key metrics – RTT, throughput, fairness, and convergence – resulting in end-to-end application performance gains. Evaluated across several scenarios, Poseidon lowers fabric RTT by up to 50%, reduces time to converge up to 12 × , and decreases throughput variation across ﬂows by up to 70%. Collectively, these improvements reduce message transfer time by more than 61% on average and 14.5 × at 99.9p.
Augmented Reality for Safety Zones in Human-Robot Collaboration

Worker productivity in manufacturing could be increased by reducing the distance between robots and humans in human-robot collaboration (HRC). However, physical cages generally limit this interaction. We use Augmented Reality (AR) to visualise virtual safety zones on a real robot arm, thereby replacing the physical cages and bringing humans and robots closer together. We demonstrate this with a collaborative pick and place application that makes use of a Universal Robots 10 (UR10) robot arm and a Microsoft HoloLens 2 for control and visualisation. This mimics a real task in an industrial robot cell. The virtual safety zone sizes are based on ISO standards for HRC. However, we are the first to also consider hardware and network latencies in the calculations of the virtual safety zone sizes.
The Wetland Intrinsic Potential tool: mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators

Abstract. Accurate, unbiased wetland inventories are critical to monitor and protect wetlands from future harm or land conversion. However, most wetland inventories are constructed through manual image interpretation or automated classification of multi-band imagery and are biased towards wetlands that are easy to directly detect in aerial and satellite imagery. Wetlands that are obscured by forest canopy, that occur ephemerally, and that have no visible standing water are, therefore, often missing from wetland maps. To aid in the detection of these cryptic wetlands, we developed the Wetland Intrinsic Potential (WIP) tool, based on a wetland-indicator framework commonly used on the ground to detect wetlands through the presence of hydrophytic vegetation, hydrology, and hydric soils. Our tool uses a random forest model with spatially explicit input variables that represent all three wetland indicators, including novel multi-scale topographic indicators that represent the processes that drive wetland formation, to derive a map of wetland probability. With the ability to include multi-scale topographic indicators that help identify cryptic wetlands, the WIP tool can identify areas conducive to wetland formation while providing a flexible approach that can be adapted to diverse landscapes. For a study area in the Hoh River watershed in western Washington, USA, classification of the output probability with a threshold of 0.5 provided an overall accuracy of 91.97 %. Compared to the National Wetlands Inventory, the classified WIP tool output identified over 2 times the wetland area and reduced errors of omission from 47.5 % to 14.1 % but increased errors of commission from 1.9 % to 10.5 %. The WIP tool is implemented as an ArcGIS toolbox using a combination of R and Python scripts.
Defending Smart Electrical Power Grids against Cyberattacks with Deep 
Q
-Learning

A key to ensuring the security of smart electrical power grids is to devise and deploy eﬀective defense strategies against cyberattacks. To achieve this goal, an essential task is to simulate and understand the dynamical interplay between the attacker and defender, for which stochastic game theory and reinforcement learning stand out as a powerful mathematical/computational framework. Existing works were based on conventional Q-learning to ﬁnd the critical sections of a power grid to choose an eﬀective defense strategy, but the methodology was applicable to small systems only. Additional issues with Q-learning are the diﬃculty to consider the timings of cascading failures in the reward function and deterministic modeling of the game while the attack success depends on various parameters and typically has a stochastic nature. Our solution to overcoming these diﬃculties is to develop a deep Q-learning based stochastic zero-sum Nash strategy solution. We demonstrate the workings of our deep-Q learning solution using the benchmark W&W 6-bus and the IEEE 30-bus systems, the latter being a relatively large-scale power-grid system that deﬁes the conventional Q-learning approach. Comparison with alternative reinforcement learning methods provides further support for the general applicability of our deep-Q learning framework in ensuring secure operation of modern power grid systems.
Open Research Online Expected Performances of the NOMAD/ExoMars instrument

, , , CH , , HCN, , , , should have the ability to measure methane concentrations o 25 parts per trillion (ppt) in solar occultation mode, and 11 parts per billion in nadir mode. Occultation detections as low as 10 ppt could be made if spectra are averaged (Drummond et al., 2011). Results have been obtained for all three channels in nadir and in solar occultation. & 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
A daily and 500 m coupled evapotranspiration and gross primary production product across China during 2000–2020

Abstract. Accurate high-resolution actual evapotranspiration (ET) and gross primary production (GPP) information is essential for understanding the large-scale water and carbon dynamics. However, substantial uncertainties exist in the current ET and GPP datasets in China because of insufficient local ground measurements used for model constraint. This study utilizes a water–carbon coupled model, Penman–Monteith–Leuning Version 2 (PML-V2), to estimate 500 m ET and GPP at a daily scale. The parameters of PML-V2(China) were well calibrated against observations of 26 eddy covariance flux towers across nine plant functional types in China, indicated by a Nash–Sutcliffe efficiency (NSE) of 0.75 and a root mean square error (RMSE) of 0.69 mm d−1 for daily ET, respectively, and a NSE of 0.82 and a RMSE of 1.71 g C m−2 d−1 for daily GPP. The model estimates get a small Bias of 6.28 % and a high NSE of 0.82 against water-balance annual ET estimates across 10 major river basins in China. Further evaluations suggest that the newly developed product is better than other typical products (MOD16A2, SEBAL, GLEAM, MOD17A2H, VPM, and EC-LUE) in estimating both ET and GPP. Moreover, PML-V2(China) accurately monitors the intra-annual variations in ET and GPP in the croplands with a dual-cropping system. The new data showed that, during 2001–2018, the annual GPP and water use efficiency experienced a significant (p<0.001) increase (8.99 g C m−2 yr−2 and 0.02 g C mm−1 H2O yr−1, respectively), but annual ET showed a non-significant (p>0.05) increase (0.43 mm yr−2). This indicates that vegetation in China exhibits a huge potential for carbon sequestration with little cost in water resources. The PML-V2(China) product provides a great opportunity for academic communities and various agencies for scientific studies and applications, freely available at https://doi.org/10.11888/Terre.tpdc. 272389 (Zhang and He, 2022).
Predictors of Higher-Order Affective Skills in Health Promotion Among Indonesian Nursing Students: Assessment and Evaluation

Abstract AIM We examined health-promoting lifestyle in undergraduate nursing students and its potential as a predictor of health-promoting behaviors and basis for curriculum improvement. BACKGROUND A health-promoting lifestyle is essential among students for their future nursing roles. Development requires the internalization of healthy behaviors beyond the cognitive learning domain. METHOD Guided by Pender’s health promotion model, this multisite, cross-sectional, and descriptive-correlational study surveyed 1,634 undergraduate nursing students in Bali, Indonesia. RESULTS The regression analysis revealed that student profiles explained the 5 percent variation in their overall health-promoting lifestyle. Perceived health status was observed to be a significant predictor (p < .05) of health-promoting behaviors among a diverse sample of undergraduate nursing students. CONCLUSION The study findings emphasize the role of nursing education in instilling healthy behaviors among undergraduate students and the importance of integrating student-centered and context-responsive health promotion strategies into the nursing curriculum.
Burned area and carbon emissions across northwestern boreal North America from 2001–2019

Abstract. Fire is the dominant disturbance agent in Alaskan and Canadian boreal ecosystems and releases large amounts of carbon into the atmosphere. Burned area and carbon emissions have been increasing with climate change, which have the potential to alter the carbon balance and shift the region from a historic sink to a source. It is therefore critically important to track the spatiotemporal changes in burned area and fire carbon emissions over time. Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and Canada at 500 m (meters) resolution that utilizes finer-scale 30 m Landsat imagery to account for land cover unsuitable for burning. This method strictly balances omission and commission errors at 500 m to derive accurate landscape- and regional-scale burned-area estimates. Using this new burned-area product, we developed statistical models to predict burn depth and carbon combustion for the same period within the NASA Arctic–Boreal Vulnerability Experiment (ABoVE) core and extended domain. Statistical models were constrained using a database of field observations across the domain and were related to a variety of response variables including remotely sensed indicators of fire severity, fire weather indices, local climate, soils, and topographic indicators. The burn depth and aboveground combustion models performed best, with poorer performance for belowground combustion. We estimate 2.37×106 ha (2.37 Mha) burned annually between 2001–2019 over the ABoVE domain (2.87 Mha across all of Alaska and Canada), emitting 79.3 ± 27.96 Tg (±1 standard deviation) of carbon (C) per year, with a mean combustion rate of 3.13 ± 1.17 kg C m−2. Mean combustion and burn depth displayed a general gradient of higher severity in the northwestern portion of the domain to lower severity in the south and east. We also found larger-fire years and later-season burning were generally associated with greater mean combustion. Our estimates are generally consistent with previous efforts to quantify burned area, fire carbon emissions, and their drivers in regions within boreal North America; however, we generally estimate higher burned area and carbon emissions due to our use of Landsat imagery, greater availability of field observations, and improvements in modeling. The burned area and combustion datasets described here (the ABoVE Fire Emissions Database, or ABoVE-FED) can be used for local- to continental-scale applications of boreal fire science.
Response to Anonymous Referee # 2 on " In-situ measurements of NH 3 : instrument performance and applicability

The manuscript presented by Twigg et al. represents an important study towards improving the quality of in-situ ammonia (NH3) measurements. Significant challenges still exist in obtaining accurate and precise NH3 measurements, specifically in field observations where a large range of ambient conditions impact the performance of instrumentation. So far, there have been only a limited number of studies comparing different NH3 measurement methodologies under field conditions. The authors present a comparison of 13 online instruments, spanning over the most important measurement techniques, and 1 type of passive samplers, making it to my knowledge the broadest NH3 intercomparison study conducted up to date. The authors use different statistical methods to compare the instruments determining their precision and accuracy. The comparison of closed-path systems with the open-path miniDOAS as well as employing some instruments of the same type with different inlet systems, allows the authors to investigate dampening effects caused by inlet tubing surfaces. Finally, the authors also give advice on what future measurement setup should consider such as regular calibrations (which were missing in this study). The setup of the study, analysis of data and presentation of results was performed with great care, considering the major challenges of each instrument. Given the importance and uniqueness of the study, I suggest it to be published in AMT after addressing the comments below. The major parts where the manuscript in my view needs improvement is (1) the determination of the residence time and (2) the description of inlet tubing effects and the derivation of time constants.