Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Childbirth on Women’s Formal Labour Market Trajectories: Evidence from Uruguayan Administrative Data

Abstract The motherhood penalty for developed countries is well-established in the economic literature. Childbirth intensifies the traditional gender roles that affect paid and unpaid work and contributes to the persistence of the gender labour gap. However, little is known about this phenomenon for developing contexts. This paper investigates the motherhood effects on women’s formal employment and wage trajectories in Uruguay. We document significant and robust motherhood penalties in the labour market, applying an event study method to almost 20 years of social security administrative data. One year after childbirth, formal monthly labour earnings decrease by 22 per cent. This drop fails to recover over time, and ten years after the arrival of children, women’s earnings are 40 per cent below their level just before childbirth. This penalty is mainly driven by a drop in formal employment and, to a lesser extent, a wage decline for those remaining employed. Heterogeneous analysis shows that low-wage women face higher motherhood penalties than high-wage women. Interestingly, these negative effects on wages and formal employment have reduced over time, and recent mothers face lower motherhood penalties.
Adaptive Multidimensional Parallel Fault Simulation Framework on Heterogeneous System

Fault simulation is a critical component of the automatic test pattern generation (ATPG) tool, which is widely used in chip development. The CPU–GPU heterogeneous system can accelerate fault simulation. However, existing work faces the following challenges: 1) Path Divergence: The simulation path of different faults is not uniform, which leads to low parallel efficiency of different GPU threads; 2) Unbalanced Workload: The load of different computing units is not balanced, leading to serious differences in the execution time of each part; and 3) Poor Scalability: When the circuit scale increases, the GPU memory is limited and the simulation has strong structural dependence, which makes the simulation difficult. In this work, we propose an adaptive multidimensional parallel fault simulation framework based on the CPU–GPU heterogeneous system. We adaptively select different simulation approaches according to different circuit scales. In detail, we use the fanout-free region (FFR) grouping method to solve the problem of path divergence. We also use a combination of static and dynamic load balancing to tradeoff data handling and the execution time of each computing unit. We limit the queue length used in the GPU to improve the scalability of the simulation. To further accelerate, we propose the 4-D parallel architecture on multiple GPUs. Extensive experimental results show that our fault simulator based on 8 GPU is $105.7\times $ faster than the commercial tool on average. For tens of millions of gate-level circuits, our fault simulator based on one GPU is up to $25.9\times $ faster than the CPU single-threaded simulator.
DETECTING THE RAPIDLY EXPANDING OUTER SHELL OF THE CRAB NEBULA: WHERE TO LOOK

We present a range of steady-state photoionization simulations, corresponding to different assumed shell geometries and compositions, of the unseen postulated rapidly expanding outer shell to the Crab Nebula. The properties of the shell are constrained by the mass that must lie within it, and by limits to the intensities of hydrogen recombination lines. In all cases the photoionization models predict very strong emissions from high ionization lines that will not be emitted by the Crab's filaments, alleviating problems with detecting these lines in the presence of light scattered from brighter parts of the Crab. The near-NIR [Ne vi] λ7. 652 μm line is a particularly good case; it should be dramatically brighter than the optical lines commonly used in searches. The C iv λ1549 doublet is predicted to be the strongest absorption line from the shell, which is in agreement with Hubble Space Telescope observations. We show that the cooling timescale for the outer shell is much longer than the age of the Crab, due to the low density. This means that the temperature of the shell will actually “remember” its initial conditions. However, the recombination time is much shorter than the age of the Crab, so the predicted level of ionization should approximate the real ionization. In any case, it is clear that IR observations present the best opportunity to detect the outer shell and so guide future models that will constrain early events in the original explosion.
Inflation from nilpotent Kähler corrections

We develop a new class of supergravity cosmological models where inflation is induced by terms in the Kähler potential which mix a nilpotent superfield S with a chiral sector Φ. As the new terms are non-(anti)holomorphic, and hence cannot be removed by a Kähler transformation, these models are intrinsically Kähler potential driven. Such terms could arise for example due to a backreaction of an anti-D3 brane on the string theory bulk geometry. We show that this mechanism is very general and allows for a unified description of inflation and dark energy, with controllable SUSY breaking at the vacuum. When the internal geometry of the bulk field is hyperbolic, we prove that small perturbative Kähler corrections naturally lead to α-attractor behaviour, with inflationary predictions in excellent agreement with the latest Planck data.
Vitamin C Supplementation for the Treatment of COVID-19: A Systematic Review and Meta-Analysis

Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, caused by the severe respiratory syndrome coronavirus 2 (SARS-CoV-2), millions of people have died, and the medical system has faced significant difficulties. Our purpose was to perform a meta-analysis to estimate the effect of vitamin C on in-hospital mortality and the ICU or hospital length of stay for patients diagnosed with COVID-19. We conducted a systematic review with meta-analysis in the following databases: PubMed, Web of Science, Scopus and Cochrane Central Register of Controlled Trials. We included studies that evaluated the effect of vitamin C supplementation, compared with standard treatment in COVID-19 patients who are ≥18 y of age. Nineteen trials were included in the meta-analysis. In-hospital mortality with and without vitamin C supplementation was 24.1% vs. 33.9% (OR = 0.59; 95%CI: 0.37 to 0.95; p = 0.03), respectively. Sub-analysis showed that, in randomized clinical trials, in-hospital mortality varied and amounted to 23.9% vs. 35.8% (OR = 0.44; 95%CI: 0.25 to 0.76; p = 0.003), respectively. In the non-randomized trials, in-hospital mortality was 24.2% vs. 33.5% (OR = 0.72; 95%CI: 0.38 to 1.39; p = 0.33), respectively. The ICU length of stay was longer in patients treated with vitamin C vs. standard therapy, 11.1 (7.3) vs. 8.3 (4.7) days (MD = 1.91; 95%CI: 0.89 to 2.93; p < 0.001), respectively. Acute kidney injury in patients treated with and without vitamin C varied and amounted to 27.8% vs. 45.0% (OR = 0.56; 95%CI: 0.40 to 0.78; p < 0.001), respectively. There were no differences in the frequency of other adverse events among patients’ treatment with and without vitamin C (all p > 0.05). The use of vitamin C reduces hospital mortality. The length of stay in the ICU is longer among patients treated with vitamin C. In terms of patient safety, vitamin C has an acceptable profile. Low doses of vitamin C are effective and safe. Despite some evidence of the usefulness of vitamin C in modifying the course of COVID-19, it is too early to modify guidelines and recommendations. Further studies, in particular randomized clinical trials, are necessary.
Detection of the effect of the current water crisis on the reduction of the water surface of the Po River, Italy

Italy has been dealing with a major environmental problem in recent times – the water crisis. It is known that this environmental problem can be caused by droughts, lack of rain, and pollution. In July 2022, the Italian government declared a state of emergency in five regions due to the intense water crisis, which coincided with one of the most severe droughts experienced in the last 70 years by the Italian territory. The 652 km-long Po River is the main and longest Italian river and has suffered greatly from the lack of water in its surroundings. This study aims to detect the changes that occurred in the Po River watershed by means of multispectral images (pre- and post-water crisis) obtained by the Sentinel-2 satellite. A methodology different from conventional ones is implemented, which highlights changes by the analysis of images acquired before and after the water crisis. The method is compared to conventional techniques that use subtraction of indexes for the detection of changes. The results obtained here are promising, as the proposed method is a fast and effective approach to mapping the effects of water crisis, besides potentiating the application of the methodology in other areas.
Trident: A three-pronged galaxy survey - I. Lyman alpha emitting galaxies at z ~ 2 in GOODS North

Context. Lyman alpha emitting galaxies (LAEs) are used to probe the distant universe and are therefore important for galaxy evolution studies and for providing clues to the nature of the epoch of reionization, but the exact circumstances under which Lyman alpha escapes a galaxy are still not fully understood. Aims. The Trident project is designed to simultaneously examine Lyman alpha, H-alpha and Lyman Continuum emission from galaxies at redshift z∼2, thus linking together these three aspects of ionising rad iation in galaxies. In this paper, we outline the strategy of this project and examine the properties of LAEs in the GOODS North field. Methods. We performed a narrowband LAE survey in GOODS North using existing and two custom made filters at the Nordic Optical Telescope with MOSCA. We use complementary broad band archival data in the field to make a careful candidate selec tion and perform optical to near-IR SED fitting. We also estimate f ar-infrared luminosities by matching our candidates to detections in Spitzer/MIPS 24µm and Herschel/PACS catalogs. Results. We find a total of 25 LAE candidates, probing mainly the bright end of the LAE luminosity function with LLyα∼ 1−15×10 42 erg s −1 . They display a range of masses of∼ 0.5−50×10 9 M⊙, and average ages from a few tens of Myr to 1 Gyr when assuming a constant star formation history. The majority of our candidates also show signs of recent elevated star formation. Three candidates have counterparts in the GOODS-Herschel far-IR catalogue, with luminosities consistent with ultra-luminous infrared gal axies (ULIRGs). Conclusions. The wide range of parameters derived from our SED fitting, as w ell as part of our sample being detected as ULIRGs, seems to indicate that at these Lyα luminosities, LAEs do not necessarily have to be young dwarfs, and that a lack of dust is not required for Lyα to escape.
The effect of H± on B± → τ±ντ and B± → μ±νμ

The hitherto unobserved purely leptonic decays B± → τ±ντ and B± → μ±νμ are of much interest in current and future runs of the e+e−B factories. Such decays are sensitive to charged Higgs bosons (H±) at the tree-level and provide important constraints on tan β/mH±. We include the large corrections to the H±ub coupling induced by virtual SUSY effects and show that the bounds on tan β/mH± can be significantly weakened or strengthened.
FIRE: A Finely Integrated Risk Evaluation Methodology for Life-Critical Embedded Systems

Life-critical embedded systems, including medical devices, are becoming increasingly interconnected and interoperable, providing great efficiency to the healthcare ecosystem. These systems incorporate complex software that plays a significantly integrative and critical role. However, this complexity substantially increases the potential for cybersecurity threats, which directly impact patients’ safety and privacy. With software continuing to play a fundamental role in life-critical embedded systems, maintaining its trustworthiness by incorporating fail-safe modes via a multimodal design is essential. Comprehensive and proactive evaluation and management of cybersecurity risks are essential from the very design to deployment and long-term management. In this paper, we present FIRE, a finely integrated risk evaluation methodology for life-critical embedded systems. Security risks are carefully evaluated in a bottom-up approach from operations-to-system modes by adopting and expanding well-established vulnerability scoring schemes for life-critical systems, considering the impact to patient health and data sensitivity. FIRE combines a static risk evaluation with runtime dynamic risk evaluation to establish comprehensive risk management throughout the lifecycle of the life-critical embedded system. We demonstrate the details and effectiveness of our methodology in systematically evaluating risks and conditions for risk mitigation with a smart connected insulin pump case study. Under normal conditions and eight different malware threats, the experimental results demonstrate effective threat mitigation by mode switching with a 0% false-positive mode switching rate.
Plasma Catalytic Synthesis of Silver Nanoparticles

We present the experimental results of plasma catalytic synthesis of colloidal silver nanoparticles, using AgNO3 as the precursor, ethanol as the solvent and reducing agent, and poly vinyl pyrrolidone (PVP) as the macromolecular surfactant. The plasma is generated by an atmospheric argon dielectric barrier discharge jet. Silver nanoparticles are produced instantly once the plasma is ignited. The system is not heated so it is necessary to use traditional chemical methods. The samples are characterized by UV-visible absorbance and transmission electron microscopy. For glow discharge mode no obvious silver nanoparticles are observed. For low voltage filamentary streamer discharge mode a lot of silver nanoparticles with the mean diameter of ~3.5 nm are generated and a further increase of the voltage causes the occurrence of agglomeration.
Chronicle of Processes Leading to the 2018 Eruption at Mt. Etna As Inferred by Seismic Ambient Noise Along With Geophysical and Geochemical Observables

This work analyzes temporal variations of seismic velocities at Mt. Etna from August 2018 to February 2019. During this time period, a strong flank eruption accompanied by intense seismicity and ground deformation took place along a fracture that opened on 24 December 2018 at the base of the New South‐East summit crater. Furthermore, two moderate earthquakes—the 6 October 2018 ML 4.7 and 26 December 2018 ML 4.8—associated with the volcanic activity were recorded. In this study, we computed cross‐correlation functions (CCFs) between windows of seismic ambient noise to identify seismic velocity variations within the volcano edifice. We calculated daily CCFs at 16 stations for 120 interstation pairs using the vertical component in the 1.0–1.5 Hz frequency band. We observe that dv/v starts to decrease rapidly from the beginning of October 2018 and reaches approximately −0.45% in the pre‐eruption period. The spatio‐temporal distribution of seismic velocities shows that the reduction of dv/v mostly occurs in the vicinity of the summit and close to the flank area and is interpreted to be affected by magmatic intrusion at 0–3 km depth. To infer the source mechanism of this eruption, we compared these observations with volcano‐tectonic earthquakes, volcanic tremor, volcanic degassing, gravity, and ground deformation data. Our study suggests that a relationship between magma intrusion and associated crack opening is responsible for the decrease of dv/v.
Pre-Print: Please do not copy without permiussion from the CobBauge Project Working Title: The Optimisation of Cob to Meet Current Standards of Thermal Transmittance

Earth building materials offer architects, engineers and architects a very low carbon walling solution for low rise properties (under 3 storeys). Unfortunately the mixture of sub-soil and fibre known as Cob does not currently comply with the thermal aspects of many building regulations across the world, including France and the UK. This paper reports the results of some joint research that, through a mixture of laboratory and practical measurements optimises two cob mixes, one low density (minimised thermal conductivity) and one high density (maximised compressive strength ). Results are reported from a range of unmodified subsoils, dug from the ground near to the site of some propective buildings. These subsoils are combined with a range of commonly grown fibres at high and low densities and the results are compared. The optimal low and high density mixes are combined into a single composite 2-layer cob wall offering a ready made solution to complient low-carbon energy-efficient low rise properties or the extension of existing historic buildings.
Familial Linkage and Association of the NR3C1 Gene with Type 2 Diabetes and Depression Comorbidity

Impairment in the hypothalamic-pituitary-adrenal (HPA) axis and cortisol pathway may be major contributing factors to the common pathogenesis of major depressive disorders (MDD) and type 2 diabetes (T2D). A significant player in the neuroendocrine HPA axis and cortisol response is the glucocorticoid receptor (GR), which is encoded by the nuclear receptor subfamily 3 group C member (NR3C1) gene. Variants in the NR3C1 gene have been reported in patients with MDD and obesity and found to confer reduced risk for quantitative metabolic traits and T2D in Cushing syndrome; variants have not been reported in T2D and MDD-T2D comorbid patients. We studied 212 original Italian families with a rich family history for T2D and tested 24 single nucleotide polymorphisms (SNPs) in the NR3C1 gene for linkage to and linkage disequilibrium (LD) with T2D and MDD across different inheritance models. We identified a total of 6 novel SNPs significantly linked/in LD to/with T2D (rs6196, rs10482633, rs13186836, rs13184611, rs10482681 and rs258751) and 1 SNP (rs10482668) significantly linked to/in LD with both T2D and MDD. These findings expand understanding of the role that NR3C1 variants play in modulating the risk of T2D-MDD comorbidity. Replication and functional studies are needed to confirm these findings.
Intelligent Piano Teaching Based on Internet of Things Technology and Multimedia Technology

Intelligent piano teaching is based on traditional piano teaching, combined with relevant intelligent technology, to improve students’ teaching methods, or to change the traditional piano structure, so that students can change from learning piano to playing piano. This study aimed to select a more suitable specific algorithm by studying the Internet of things (LOT) technology and multimedia technology and conduct in-depth research on the piano intelligent teaching, so that it can better serve the current piano teaching intelligence. Based on the experiment of this study, it can be seen that among the 600 investigators in place O, there are 587 valid questionnaires, of which 265 are willing to accept both traditional teaching and intelligent piano teaching, accounting for 45.1% of the valid questionnaires; 136 people are more willing to accept intelligent piano teaching, accounting for 23.2% of the valid questionnaires; 186 people are more willing to accept traditional piano teaching, accounting for 31.7% of the valid questionnaires. The experimental results of this study show that the research process of intelligent piano teaching based on LOT and multimedia technology is more effective than other methods of analyzing experimental data, and it is of great reference significance for the development of intelligent piano teaching.
Applying Natural Language Processing and TRIZ Evolutionary Trends to Patent Recommendations for Product Design

Traditional TRIZ theory provides methods and processes for systematic analysis on engineering problems, which can improve the efficiency of solving problems. However, the effect of solving problems is not necessarily guaranteed, and depends on the user’s profession and experience. Therefore, this study proposes a methodology to apply evolutionary benefits in the 37 trend lines developed by TRIZ researchers to assist in intelligently screening relevant patents applicable to the content of the product design. In such a way, the efficiency of problem solving and product design quality may be improved more effectively. First, the patent database is used as the training dataset, words and sentences in the patent documents are analyzed through natural language processing to obtain keywords that may be related to evolutionary benefits. Using word vectors trained by Doc2vec, the semantic similarity can be calculated to obtain the similarity relationship between patent text and evolutionary benefit. Secondly, the goals of the product development project may make be related to the evolutionary benefits, and then applicable patent recommendations can be provided. The proposed methodology may achieve the purpose of intelligent design assistance to enhance the product development process and problem-solving.
Analytical considerations about the cosmological constant and dark energy

The accelerated expansion of the universe has now been confirmed by several independent observations including those of high redshift type Ia supernovae, and the cosmic microwave background combined with the large scale structure of the universe. Another way of presenting this kinematic property of the universe is to postulate the existence of a new and exotic entity, with negative pressure, the dark energy (DE). In spite of observationally well established, no single theoretical model provides an entirely compelling framework within which cosmic acceleration or DE can be understood. At present all existing observational data are in agreement with the simplest possibility that the cosmological constant be a candidate for DE. This case is internally self-consistent and noncontradictory. The extreme smallness of the cosmological constant expressed in either Planck, or even atomic units means only that its origin is not related to strong, electromagnetic, and weak interactions. Although in this case DE reduces to only a single fundamental constant we still have no derivation from any underlying quantum field theory for its small value. From the principles of quantum cosmologies, for example, it is possible to obtain the reason for an inverse-square law for the cosmological constant with no conflict with observations. Despite the fact that this general expression is well known, in this work we introduce families of analytical solutions for the scale factor different from the current literature. The knowledge of the scale factor behavior might shed some light on these questions mentioned above since the entire evolution of a homogeneous isotropic universe is contained in the scale factor. We use different parameters for these solutions and with these parameters we establish a connection with the equation of state for different DE scenarios.
The Effects of Seemingly Nonbinding Price Floors: An Experimental Analysis

Price floors are common policies in markets for storable goods such as commodities, bankable emissions permits, and currencies. Hard price floors are implemented as unlimited governmental buybacks and prevent the price from falling below the floor; soft floors, including those implemented as auction reserve prices in emission permit auctions, allow the market price to fall below the floor. We specify and then test in the laboratory a two-period model with the same properties as our infinite-horizon model, Salant et al. (2022). Most of our experimental findings are consistent with theoretical predictions: a seemingly nonbinding floor can cause the price and carryover to jump up, the jump is higher with a hard floor than a soft one, and when the floor is so low that the theory predicts no effect, none is observed.