Miracle-dz/UniFAR-FTUs huggingface dataset:
Refining the Resolution of DUACS Along-Track Level-3 Sea Level Altimetry Products

This paper describes the demonstration of a regional high-resolution level-3 (L3) altimeter data unification and altimeter combination system (DUACS) developed with support from the French space agency (CNES). Deduced from full-rate (20 Hz to 40 Hz) level-2 (L2) altimeter measurements, this product provides sea level anomalies (SLA) and other essential physical variables at a spatial resolution of one sample every ~1 km over the North Atlantic Ocean. This allows us to resolve wavelengths from ~35 km to ~55 km depending on the altimeter considered. This was made possible by recent advances in radar altimeter processing for both synthetic aperture radar (SAR) and low-resolution-mode (LRM) measurements, as well as improvements made to different stages of the DUACS processing chain. Firstly, the new adaptive and low-resolution with range migration correction (LR-RMC) processing techniques were considered for Jason and Sentinel-3 (S3A), respectively. They significantly reduce errors at short wavelengths, and the adaptive processing also reduces possible land contamination near the coast. Next, up-to-date geophysical and environmental corrections were selected for this production. This includes specific corrections intended to reduce the measurement noise on LRM measurements and thus enhance the observability at short wavelengths. Compared with the 1 Hz product, the observable wavelengths reached with the demonstration high-resolution product are reduced by up to one third, or up to half in the northeast Atlantic region. The residual noises were optimally filtered from full-rate measurements, taking into consideration the different observing capabilities of the altimeters processed. A specific data recovery strategy was applied, significantly optimizing the data availability, both in the coastal and open ocean areas. This demonstration L3 product is thus better resolved than the conventional 1 Hz product, especially near the coast, where it is defined up to ~5 km against ~10 km for the 1 Hz version. Multi-mission cross-calibration processing was also optimized with an improved long-wavelength error (LWE) correction, leading to a better consistency between tracks, with a 9–15% reduction in SLA variance at cross-overs. The new L3 product improves the overall consistency with tide gauge measurements, with a reduction in SLA differences variance by 5 and 17% compared with the 1 Hz product from the S3A and Jason-3 (J3) measurements, respectively. Primarily intended for regional applications, this product can significantly contribute to improving high-resolution numerical model output via data assimilation. It also opens new perspectives for a better understanding of regional sea-surface dynamics, with an improved representation of the coastal currents and a refined spectral content revealing the unbalanced signal.
Paediatric rheumatology Subclinical synovitis detected by ultrasound in children affected by coeliac disease: a frequent manifestation improved by a gluten-free diet

Objective Coeliac disease (CD) is a chronic autoimmune disease of the small intestine caused by the ingestion of gluten, in which musculoskeletal manifestations may occur. Aim of this study was to evaluate the prevalence and severity of joint involvement in paediatric patients with CD using musculoskeletal ultrasound (US). Methods Consecutive paediatric CD patients were enrolled and underwent US evaluations at level of knees, hips and ankles. The presence of joint effusion (JE), synovial hypertrophy, power Doppler signal and structural damage lesions (bone irregularities and erosions) was registered. Inflammatory abnormalities were scored on a semi-quantitative scale (0–3), and structural damage lesions on a dichotomous scale (0–1). Seventy-four CD children (mean age: 7.6 years; range: 1–14.2; M/F 24/50) were enrolled. Thirty-eight were on a gluten-containing diet (GCD) and 36 on a gluten-free diet (GFD). US showed the presence of abnormalities in 23 patients overall (31.1%); JE was the most frequently observed change (23/23). US abnormalities were observed in 19 patients (50.0%) of GCD group and in 4 of GFD group (11.1%, p=0.007). Interestingly, 12/23 (52.2%) patients with US-detected changes were asymptomatic. This is the first US study demonstrating joint involvement in children with CD. JE, the most frequent manifestation, was present also in asymptomatic patients and was reduced in those on GFD. These findings may indicate that, also at joint level, an inflammatory response represented by the appearance of JE may be induced by exposure to gluten.
Journal Pre-proof of the SARS-CoV-2 ribonucleosome provides insights into genomic RNA packaging and regulation by phosphorylation

The nucleocapsid (N) protein of SARS-CoV-2 is responsible for compaction of the ~30-kb RNA genome in the ~90-nm virion. Previous studies suggest that each virion contains 35-40 viral ribonucleoprotein (vRNP) complexes, or ribonucleosomes, arrayed along the genome. There is, however, little mechanistic understanding of the vRNP complex. Here, we show that N protein, when combined in vitro with short fragments of the viral genome, forms 15-nm particles similar to the vRNP structures observed within virions. These vRNPs depend on regions of N protein that promote protein-RNA and protein-protein interactions. Phosphorylation of N protein in its disordered serine/arginine (SR) region weakens these interactions to generate less compact vRNPs. We propose that unmodified N protein binds structurally diverse regions in genomic RNA to form compact vRNPs within the nucleocapsid, while phosphorylation alters vRNP structure to support other N protein functions in viral transcription.
Resource A Rapid, Extensive, and Transient Transcriptional Response to Estrogen Signaling in Breast Cancer Cells

SUMMARY We report the immediate effects of estrogen signaling on the transcriptome of breast cancer cells using global run-on and sequencing (GRO-seq). The data were analyzed using a new bioinformatic approach that allowed us to identify transcripts directly from the GRO-seq data. We found that estrogen signaling directly regulates a strikingly large fraction of the transcriptome in a rapid, robust, and unexpectedly transient manner. In addition to protein-coding genes, estrogen regulates the distribution and activity of all three RNA polymerases and virtually every class of noncoding RNA that has been described to date. We also identiﬁed a large number of previously unde-tected estrogen-regulated intergenic transcripts, many of which are found proximal to estrogen receptor binding sites. Collectively, our results provide the most comprehensive measurement of the primary and immediate estrogen effects to date and a resource for understanding rapid signal-depen-dent transcription in other systems.
FairPoS: Input Fairness in Proof-of-Stake with Adaptive Security

We present “FairPoS”, the first blockchain protocol that achieves input fairness with adaptive security. Here, we introduce a novel notion of “input fairness”: the adversary cannot learn the plain-text of any finalized client input before it is include in a block in the chain’s common-prefix. Should input fairness hold, input ordering attacks which depend on the knowledge of plain-text of client inputs are thwarted. In FairPoS, input fairness with adaptive security is achieved by means of the delay encryption scheme of DeFeo et al. [9], a recent cryptographic primitive related to time-lock puzzles, allowing all client inputs in a given round to be encrypted under the same key, which can only be extracted after enough time has elapsed. In contrast, alternative proposals that prevent input order attacks by encrypting user inputs are not adaptively secure as they rely on small static committees to perform distributed key generation and threshold decryption for efficiency’s sake. Such small committees are easily corrupted by an adaptive adversary with a corruption budget applicable over a large set of participants in a permissionless blockchain system. The key extraction task in delay encryption can, in principle, be performed by any party and is secure upon adaptive corruption, as no secret key material is learned. However, the key extraction requires highly specialized hardware in practice. Thus, FairPoS requires resource-rich, staking parties to insert extracted keys to blocks which enables light-clients to decrypt past inputs. Note that naive application of key extraction can result in chain stalls lasting the entire key extraction period. In FairPoS, this is addressed by a novel longest-extendable-chain rule. We formally prove that FairPoS achieves input fairness and the original security of Ouroborous Praos against an adaptive adversary
A NEW PROBE OF THE DISTRIBUTION OF DARK MATTER IN GALAXIES

The scale radius of dark matter halos is a critical parameter for specifying the density distribution of dark matter, and is therefore a fundamental parameter for modeling galaxies. We develop here a novel, observationally motivated probe to quantitatively infer its value within the context of the Navarro, Frenk, & White profile. We demonstrate that disturbances in the extended atomic hydrogen gas disks of galaxies can be analyzed to infer the scale radius of the dark matter halo. Our primary metric is the phase (i.e., the shape of the spiral) of the m = 1 mode of the disturbance in the outskirts of the gas disk, which we take to be produced by a tidal interaction. We apply the method to the Whirlpool galaxy, which has an optically visible satellite. We infer a scale radius of ∼17 kpc for M51, which is consistent with expectations from dissipationless cosmological simulations. We explore potential degeneracies due to orbital inclination, initial conditions, satellite mass, and pericenter approach distance, and find our results to be relatively insensitive to these considerations. Our method of tracing the dark potential well through observed disturbances in outer gas disks is complementary to gravitational lensing.
Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis

Abstract. We examine 20 years of monthly global ocean color data and modeling outputs of nutrients using self-organizing map (SOM) analysis to identify characteristic spatial and temporal patterns of high-nutrient low-chlorophyll (HNLC) regions and their association with different climate modes. The global nitrate-to-chlorophyll ratio threshold of NO3 : Chl > 17 (mmol NO3 mg Chl−1) is estimated to be a good indicator of the distribution limit of this unproductive biome that, on average, covers 92 × 106 km2 (∼ 25 % of the ocean). The trends in satellite-derived surface chlorophyll (0.6 ± 0.4 % yr−1 to 2 ± 0.4 % yr−1) suggest that HNLC regions in polar and subpolar areas have experienced an increase in phytoplankton biomass over the last decades, but much of this variation, particularly in the Southern Ocean, is produced by a climate-driven transition in 2009–2010. Indeed, since 2010, the extent of the HNLC zones has decreased at the poles (up to 8 %) and slightly increased at the Equator (< 0.5 %). Our study finds that chlorophyll variations in HNLC regions respond to major climate variability signals such as the El Niño–Southern Oscillation (ENSO) and Meridional Overturning Circulation (MOC) at both short (2–4 years) and long (decadal) timescales. These results suggest global coupling in the functioning of distant biogeochemical regions.
RELATIONSHIP BETWEEN WORK FAMILY CONFLICT AND MARITAL SATISFACTION: MARITAL POWER AS A MEDIATOR

Work family conflict (WFC), which is defined as a specific kind of tension that stems from contradictory demands of work and family roles, is one of the important factors associated with marital satisfaction. The purpose of this study was to examine the relation between work family conflict and marital satisfaction via the mediating role of marital power on this relationship. With this purpose, data was collected from 289 individuals who were in dual-earning marriages. A survey package including a demographic information form, Work Family Conflict Scale, Personal Sense of Power Scale, and Marital Life Scale, were administered to participants. Both types of work-family conflict were negatively correlated with marital power and with marital satisfaction. Series of ANOVAs yielded significant gender differences on both forms of work-family conflict. More specifically, women experienced both forms of work-family conflict more. On the other hand, no significant gender difference was found on marital power and marital satisfaction. Results of regression analysis via Process Macro indicated that only F-to-WC significantly and negatively predicted marital satisfaction via marital power. That is, family to work conflict tended to decrease marital power; decreased marital power in turn tended to decrease marital satisfaction. These results indicate that marital power has an important role on the relation between family to work conflict and marital satisfaction. Additionally, the results indicated the criticality of F-to-WC over W-to FC in examining the relations among marriage related variable. That is, as family to work conflict increases marital power decreases; as marital power decreases marital satisfaction also decreases. These results indicate that marital power has an important role on the relation between family to work conflict and marital satisfaction. Additionally, the results indicated that family-to-work conflict is more important than work-to-family conflict in examining the relations among marriage related variables. Family related problems seem to be more important than work related problems in determining marital satisfaction.
Historical rainfall data in northern Italy predict larger meteorological drought hazard than climate projections

Abstract. Simulations of daily rainfall for the region of Bologna produced by 13 climate models for the period 1850–2100 are compared with the historical series of daily rainfall observed in Bologna for the period 1850–2014 and analysed to assess meteorological drought changes up to 2100. In particular, we focus on monthly and annual rainfall data, seasonality, and drought events to derive information on the future development of critical events for water resource availability. The results show that historical data analysis under the assumption of stationarity provides more precautionary predictions for long-term meteorological droughts with respect to climate model simulations, thereby outlining that information integration is key to obtaining technical indications.
THE IMPACT OF OWNERSHIP STRUCTURE ON DIVIDEND POLICY: EVIDENCE OF MALAYSIAN LISTED FIRMS

: Drawing on the existence evidence indicating that corporate ownership in emerging market is predominantly concentrated and controlled by large-block shareholders, this study attempts to investigate the effect of ownership structure on dividend payout decision of Malaysian listed firms. The study employs a panel data analysis of 141 firms listed on Bursa Malaysia for the financial year from 2009 to 2013. The sample is subdividing into concentrated and dispersed ownership counties. Multiple regression analysis is used to estimate the association proposed in the hypotheses. The results support the hypothesis that ownership is positively and significantly related to dividend payout decision. This finding is consistent with the view that dividend payout policy is a solution to reduce agency conflict between managers and shareholders. The findings also advocate that profitability is positively and significantly related to dividend payout. This finding supports the assertion that highly profitable firms distribute higher dividend to their shareholders. Finally, firm size and leverage are found to be negatively related to dividend payout at very strong and relatively weak level of significance respectively.
How to learn more about hydrological conditions and phytoplankton dynamics and diversity in the eastern English Channel and the southern bight of the North Sea? the SRN data set (1992-2021).

This article describes the historical data series produced by the SRN network managed by Ifremer. Since 1992, the SRN (‘Suivi Régional des Nutriments’ in French; Regional Nutrients Monitoring Programme) network has been analysing phytoplankton species and measuring twelve physicochemical parameters at ten different stations distributed along three 10 different transects located in the Eastern English Channel, and the Southern Bight of the North Sea. The SRN collects a maximum of 184 samples per year and detects up to 281 taxa, including harmful algal bloom species (HABs), with a bi-weekly to monthly sampling frequency (depending on the location and the season). The objectives of this monitoring program are to assess the influence of continental inputs on the marine environment, and their implications on possible eutrophication processes. It also aims to estimate the effectiveness of development and management policies in the marine coastal zone. The 15 regular acquisition of data allows the establishment of a long-term monitoring of the evolution of coastal water quality, as well as the observation of the consequences of large-scale alterations and modifications that are more related to regional anthropogenic activities. This paper provides an overview of the main characteristics of SRN data (descriptive statistics and data series main patterns) as well as an analysis of temporal trends using specific numerical tools available as an R package to help make use of such data. Main results of several research projects are also highlighted providing the readers with examples 20 of what is doable with such a data set.
Trajectory ensembling for ﬁne tuning - performance gains without modifying training

In this work, we present a simple algorithm for ensembling checkpoints from a single training trajectory (trajectory ensembling) resulting in signiﬁcant gains for several ﬁne tuning tasks. We compare against classical ensembles and perform ablation studies showing that the important checkpoints are not necessarily the best performing models in terms of accuracy. Rather, relatively poor models with low loss are vital for the observed performance gains. We also investigate various mixtures of checkpoints from several independent training trajectories, making the surprising observation that this only leads to marginal gains in this setup. We study how calibrating constituent models with a simple temperature scaling impacts results, and ﬁnd that the most important region of training is still that of the lowest loss in spite of potential poor accuracy.
Passivity-based Optimal Control of Discrete-time Nonlinear Systems

In this paper, a passivity-based optimal control method for a broad class of nonlinear discrete-time systems is proposed. The resulting control law is a static output feedback law which is practically preferred with respect to the state feedback law and is simple to implement. The control law has a general structure with adjustable parameters which are tuned, using an optimization method (genetic algorithm), to minimize an arbitrary cost function. By choosing this cost function it is possible to shape the transient response of the closed-loop system, as it is desirable. An illustrative example shows the effectiveness of the proposed approach.
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model

Abstract. Ammonia (NH3) is an important atmospheric constituent. It plays a role in air quality and climate through the formation of ammonium sulfate and ammonium nitrate particles. It has also an impact on ecosystems through deposition processes. About 85 % of NH3 global anthropogenic emissions are related to food and feed production and, in particular, to the use of mineral fertilizers and manure management. Most global chemistry transport models (CTMs) rely on bottom-up emission inventories, which are subject to significant uncertainties. In this study, we estimate emissions from livestock by developing a new module to calculate ammonia emissions from the whole agricultural sector (from housing and storage to grazing and fertilizer application) within the ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) global land surface model. We detail the approach used for quantifying livestock feed management, manure application, and indoor and soil emissions and subsequently evaluate the model performance. Our results reflect China, India, Africa, Latin America, the USA, and Europe as the main contributors to global NH3 emissions, accounting for 80 % of the total budget. The global calculated emissions reach 44 Tg N yr−1 over the 2005–2015 period, which is within the range estimated by previous work. Key parameters (e.g., the pH of the manure, timing of N application, and atmospheric NH3 surface concentration) that drive the soil emissions have also been tested in order to assess the sensitivity of our model. Manure pH is the parameter to which modeled emissions are the most sensitive, with a 10 % change in emissions per percent change in pH. Even though we found an underestimation in our emissions over Europe (−26 %) and an overestimation in the USA (+56 %) compared with previous work, other hot spot regions are consistent. The calculated emission seasonality is in very good agreement with satellite-based emissions. These encouraging results prove the potential of coupling ORCHIDEE land-based emissions to CTMs, which are currently forced by bottom-up anthropogenic-centered inventories such as the CEDS (Community Emissions Data System).
Programming Is Hard - Or at Least It Used to Be: Educational Opportunities and Challenges of AI Code Generation

The introductory programming sequence has been the focus of much research in computing education. The recent advent of several viable and freely-available AI-driven code generation tools present several immediate opportunities and challenges in this domain. In this position paper we argue that the community needs to act quickly in deciding what possible opportunities can and should be leveraged and how, while also working on overcoming otherwise mitigating the possible challenges. Assuming that the effectiveness and proliferation of these tools will continue to progress rapidly, without quick, deliberate, and concerted efforts, educators will lose advantage in helping shape what opportunities come to be, and what challenges will endure. With this paper we aim to seed this discussion within the computing education community.
di-Processing of whey modulates proliferative and immune functions in intestinal epithelial cells

Whey protein concentrate (WPC) is often subjected to heat treatment during industrial processing, resulting in protein denaturation and loss of protein bioactivity. We hypothesized that WPC samples subjected to different degrees of thermal processing are associated with different levels of bioactive proteins and effects on proliferation and immune response in intestinal epithelial cells (IEC). The results showed that low-heat-treated WPC had elevated levels of lactoferrin and transforming growth factor-β2 compared with that of standard WPC. The level of aggregates depended on the source of whey, with the lowest level being found in WPC derived from acid whey. Following acid activation, WPC from acid whey enhanced IEC proliferation compared with WPC from sweet whey or nonactivated WPC. Low-heat-treated WPC from acid whey induced greater secretion of IL-8 in IEC than either standard WPC from acid whey or low-heat-treated WPC from sweet whey. Following acid activation (to activate growth factors), low-heat-treated WPC from sweet whey induced higher IL-8 levels in IEC compared with standard WPC from sweet whey. In conclusion, higher levels of bioactive proteins in low-heat-treated WPC, especially from acid whey, may enhance proliferation and cytokine responses of IEC. These considerations could be important to maintain optimal bioactivity of infant formulas, including their maturational and im-munological effects on the developing intestine.