Miracle-dz/UniFAR-FTUs huggingface dataset:
A hypothesis for mitigation of risk of liquefaction

INTRODUCTION Liquefaction of sandy soils during earthquakes is a cause for concern as it may lead to disastrous consequences, such as significant structural damage and loss of life. Considerable advances have been made in recent years in the area of numerical analysis of soil liquefaction. The mathematical formulation governing the behaviour of saturated porous media was first established by Biot (1941, 1956). Subsequent contributions focused on the development of various integration schemes for the set of governing differential equations (Zienkiewicz et al., 1980, 1990). The numerical simulations conducted by many researchers have undoubtedly provided a deeper insight into the mechanics of the phenomenon of liquefaction. However, even now, few effective guidelines are available to the engineer for the development of suitable measures to mitigate the risk of liquefaction. In this paper, a hypothesis for mitigating the risk of liquefaction is put forward. According to this hypothesis, the liquefaction potential of sandy deposits may be significantly lowered by reducing the degree of saturation, even by a small amount. The underlying reason is an increase in compressibility of the system in the presence of a small quantity of air. This effect can, in principle, be achieved by a variety of techniques including electrical and/or chemical treatment. Once the proposed hypothesis is verified, practical measures and techniques can be developed. In the first part of the paper, results of an experimental programme consisting of a series of saturated and unsaturated undrained triaxial compression tests performed on Ottawa sand are presented. The tests have been conducted to demonstrate the influence of the degree of saturation on the evolution of excess pore pressure. These tests are then simulated using a constitutive model developed by Pietruszczak & Pande (1996), in which partially saturated soil is considered as a three-phase medium comprising soil skeleton, pore water and air. It is shown that the numerical predictions are consistent with experimental results, thereby demonstrating the ability of the constitutive relation to model the behaviour at various degrees of saturation. In the second part, the same constitutive relation is applied to assess the liquefaction potential of a sand layer at different degrees of saturation subjected to a scaled-down version of El Centro (1940) earthquake. It is shown that a fully saturated layer liquefies during this seismic event, whereas at 90% degree of saturation no liquefaction takes place. The experimental and numerical investigations presented in this paper strongly support the hypothesis put forward. However, further experimental verification is required. This should include tests of model structures on saturated and partially saturated sand layers subjected to simulated seismic excitation on a shaking table.
Potassium-Argon Dates of Some Cenozoic Volcanic Rocks of the Sierra Nevada, California

A date of 19.9 m. y. (early Hemingfordian) from a welded rhyolite tuff at the top of the type section of the Valley Springs Formation, and one of 25.7 m. y. (early Arikareean) from the basal welded rhyolite tuff in the Sonora Pass area, indicate that the Valley Springs Formation was deposited before late Miocene, and that rhyolitic volcanism in the Sierra Nevada began by earliest Miocene time. Three dates of 8.8–9.0 m. y. (early Hemphillian) on biotite-augite latite, which stratigraphically overlies the Table Mountain latite in the Stanislaus drainage, show that the Table Mountain latite is a member of the Mehrten Formation, which contains the late Hemphillian Oakdale fauna and the early Clarendonian Two Mile Bar fauna. A 3.5-million year date on basalt filling a canyon cut in the Chagoopa surface at Little Kern River, a 9.5-million year date on basalt from Jose Basin in Fresno County, and dates of 3.5–3.6 m. y. from basalts in the Upper San Joaquin drainage indicate that the Chagoopa surface and the Mountain Valley stage are at least as old as early Pliocene, and that the Sierra Nevada had a minimum relief of 4000 feet at that time. Basalt beneath McGee Till on McGee Mountain gives a date of 2.6 m. y. , and basalt on Coyote Flat gives a date of 9.6 m. y. Basalt beneath Sherwin Till in Owens Gorge has an age of 3.2 m. y. A rhyolite tuff and an overlying basalt in Deep Springs Valley, White Mountains, give ages of 10.9 and 10.8 m. y. , respectively.
A Comparative Analysis of Deep Learning Convolutional Neural Network Architectures for Fault Diagnosis of Broken Rotor Bars in Induction Motors

Induction machines (IMs) play a critical role in various industrial processes but are susceptible to degenerative failures, such as broken rotor bars. Effective diagnostic techniques are essential in addressing these issues. In this study, we propose the utilization of convolutional neural networks (CNNs) for detection of broken rotor bars. To accomplish this, we generated a dataset comprising current samples versus angular position using finite element method magnetics (FEMM) software for a squirrel-cage rotor with 28 bars, including scenarios with 0 to 6 broken bars at every possible relative position. The dataset consists of a total of 16,050 samples per motor. We evaluated the performance of six different CNN architectures, namely Inception V4, NasNETMobile, ResNET152, SeNET154, VGG16, and VGG19. Our automatic classification system demonstrated an impressive 99% accuracy in detecting broken rotor bars, with VGG19 performing exceptionally well. Specifically, VGG19 exhibited high accuracy, precision, recall, and F1-Score, with values approaching 0.994 and 0.998. Notably, VGG19 exhibited crucial activations in its feature maps, particularly after domain-specific training, highlighting its effectiveness in fault detection. Comparing CNN architectures assists in selecting the most suitable one for this application based on processing time, effectiveness, and training losses. This research suggests that deep learning can detect broken bars in induction machines with accuracy comparable to that of traditional methods by analyzing current signals using CNNs.
Impact of Russia–Ukraine conflict on Russian financial market: Evidence from TVP-VAR and quantile-VAR analysis

This study aims to analyze the repercussions of the Russia–Ukraine conflict on the Russian financial market, focusing on the main stock market and sectorial stock indices. High-frequency hourly data from September 12, 2021, to April 29, 2022, covering the period before and after the outbreak of conflict, is utilized for analysis. The empirical investigation employs the TVP-VAR and Quantile-VAR connectedness approaches. Our findings indicate a significant impact of the conflict on the Russian stock market, leading to increased market risk during the event period. Notably, certain sectors, including oil and gas, utilities, metals & mining, financials, consumer goods, and services exerted more influence on other sectors, while chemicals, transport, and telecoms were influenced by other sectors. These insights are crucial for comprehending the financial implications of the ongoing conflict on the local economy, providing valuable guidance to portfolio managers, investors, and policymakers in devising effective financial strategies.
Three-dimensional numerical modelling of reservoir flushing in a prototype scale

A fully three-dimensional numerical model for reservoir flushing has been tested against field measurements for the Angostura reservoir in Costa Rica. The numerical program solves the Reynolds-averaged Navier–Stokes (RANS) equations in three-dimensions and uses for discretization the finite-volume method together with a second-order upwind scheme. The used grid is unstructured and non-orthogonal, made of a mixture of hexahedral and tetrahedral cells. In addition to the bathymetry data of the prototype, the model uses grain size distributions of the bed, discharge rates and water levels during the flushing. Simulated bed level changes during the flushing are presented in this study as well as the computed amount of eroded sediments. Where the amount of flushed out sediments show reasonable agreement, differences in the developed flushing channel simulated by the model and compared to the prototype were observed. However, the presented study shows that due to the increasing development of three-dimensional RANS models, the simulation of a reservoir flushing in a prototype becomes feasible.
Fluctuations in the monthly discharge of Guyana Shield rivers, related to Pacific and Atlantic climate variability

Abstract The discharge variability of the main rivers that drain the Guyana Shield is analysed over the last 50 years using cross-wavelet, coherence and composite analysis involving oceanic and atmospheric variables. We highlight the overall hydro-climatological homogeneity of this region that allowed us to focus on the longest discharge time series available. Therefore, a wavelet cross-analysis was carried out between monthly and seasonal Maroni River discharge at the Langa Tabiki station and selected climate indices. This confirms a strong relationship between the hydrology of the Guyana Shield and the Pacific sea-surface temperature (SST) fluctuations. There is evidence of intermittent influence, of between inter-annual and near decadal scales, of the Atlantic SST fluctuations, in particular around 1970 and 1990. Finally, we show that the links between oceanic regions and high discharge in the rivers of Guyana are realized through the reinforcement of the Walker and Hadley cells between the Amazon and the adjacent oceans and through decreased trade winds and monsoon flux that favour the persistence of humidity over the Guyana Shield. Editor Z.W. Kundzewicz; Associate editor D. Hughes Citation Labat, D. , Espinoza, J.-C. , Ronchail, J., Cochonneau, G. , de Oliveira, E. , Doudou, J.C. and Guyot, J.-L. , 2012. Fluctuations in the monthly discharge of Guyana Shield rivers, related to Pacific and Atlantic climate variability. Hydrological Sciences Journal, 57 (6), 1081–1091.
Complex slab subduction beneath northern Sumatra

New data provided by the 2004–2005 Sumatra‐Andaman great earthquake sequences allow us to image with improved detail the P‐wave velocity structure beneath Sumatra and adjacent regions. Below northern Sumatra, we find that the slab is folded at depth, exhibiting geometry similar to that of the volcanic arc and the trench at the surface. We speculate that this fold plays a major role in the segmentation of the Sumatra megathrust, and may impede rupture propagation in the region. North of Sumatra, significant slab material in the mantle transition zone is imaged for the first time, and we infer the presence of a major tear between the upper mantle and transition zone there.
Image harmonization and deep learning automated classification of plus disease in retinopathy of prematurity

Abstract. Purpose Retinopathy of prematurity (ROP) is a retinal vascular disease affecting premature infants that can culminate in blindness within days if not monitored and treated. A disease stage for scrutiny and administration of treatment within ROP is “plus disease” characterized by increased tortuosity and dilation of posterior retinal blood vessels. The monitoring of ROP occurs via routine imaging, typically using expensive instruments ($50 to $140 K) that are unavailable in low-resource settings at the point of care. Approach As part of the smartphone-ROP program to enable referrals to expert physicians, fundus images are acquired using smartphone cameras and inexpensive lenses. We developed methods for artificial intelligence determination of plus disease, consisting of a preprocessing pipeline to enhance vessels and harmonize images followed by deep learning classification. A deep learning binary classifier (plus disease versus no plus disease) was developed using GoogLeNet. Results Vessel contrast was enhanced by 90% after preprocessing as assessed by the contrast improvement index. In an image quality evaluation, preprocessed and original images were evaluated by pediatric ophthalmologists from the US and South America with years of experience diagnosing ROP and plus disease. All participating ophthalmologists agreed or strongly agreed that vessel visibility was improved with preprocessing. Using images from various smartphones, harmonized via preprocessing (e.g., vessel enhancement and size normalization) and augmented in physically reasonable ways (e.g., image rotation), we achieved an area under the ROC curve of 0.9754 for plus disease on a limited dataset. Conclusions Promising results indicate the potential for developing algorithms and software to facilitate the usage of cell phone images for staging of plus disease.
Assessment of downscaled current and future projections of diurnal rainfall patterns for the Himalaya

In this study we investigate the diurnal precipitation cycle in high‐resolution regional climate simulations for present (2000–2010) and future time periods (2030–2040 and 2040–2050) over subregions of the Himalayas. The future periods are simulated under a high‐emission scenario, Representative Concentration Pathway 8.5 (RCP8.5) in order to maximize any projected externally driven precipitation signal. For present climate, 4‐hourly simulated precipitation is first evaluated against observations to establish model credibility. The diurnal cycle, which is typically characterized by a bimodal structure with primary (secondary) maxima in nighttime (afternoon), is reasonably well represented in the present, giving us confidence when assessing potential future changes. The timing of the precipitation maxima and minima is found to match the observed timings well in the diurnal cycle. In general, the Weather Research and Forecasting model captures the principal shape of the diurnal cycle observed over all the subregions. Under projected future conditions, no significant changes in the diurnal cycle occur. The results suggest modest changes in diurnal precipitation under RCP8.5 emission scenario, as evidenced by an increase in afternoon precipitation around the Himalayas. Although the projected future changes of precipitation presented in this article are within of the expected range of precipitation changes caution must be exercised when interpreting single‐model experiments.
Application of Object Based Image Analysis for Glacial Cirques Detection. Case Study: The Ţarcu Mountains (Southern Carpathians)

Geomorphologic mapping is an important fact in many research studies and the traditional methods are time consuming and expensive. This paper aims to develop a semi-automated rule-based method for the detection of glacial cirques for a test area located in the Ţarcu Mountains (Southern Carpathians) in an objectoriented approach. In this study we have established the morphometric characteristics of the glacial cirques developed in a particularly geomorphologic context at the edge of planation surfaces, using a 10 m horizontal resolution DEM (Digital Elevation Model). The parameters extracted from DEM (i.e. curvature) were further used in segmentation and classification process. Also, other factors were introduced in the rule set, as the context regarding neighboring objects like planation surfaces to the target class. The most important factor in segmentation was the curvature and to choose an appropriate scale factor we have used the available ESP (Estimation of Scale Parameter) tool. The results achieved were very close to the field reality, except for some areas where there are large negative landforms such as gullies and torrents, which were identified as objects belonging to glacial cirques class and also some roches moutonnees with high positive curvature values, objects that could be filtered manually by the user based on previous field knowledge and ancillary data such as orthophotoplans and the geomorphologic map of glacial relief in the Ţarcu Mountains. For further research, we intend to identify the characteristic thresholds for morphometric parameters that can be integrated in a set of rules in order to detect and classify other type of landforms in the alpine domain of the Ţarcu Mountains.
Aerosol variability in the Adriatic Sea from automated optical field measurements and Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS)

[1] The aerosol optical properties in the Adriatic Sea are presented using a 9-year time series (1996–2005) of automated measurements collected on the Acqua Alta Oceanographic Tower (AAOT) in the northern part of the basin and a coincident satellite record obtained from an atmospheric correction scheme adapted for European seas and applied to the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). At AAOT, the overall averages of aerosol optical thickness τa at 500 nm and Angstrom exponent α are 0.29 ± 0.21 and 1.51 ± 0.34, respectively. The average single scattering albedo varies from 0.957 at 440 nm to 0.910 at 1020 nm. The aerosol size distribution derived by optical data inversion exhibits an increase of the radius of the accumulation mode with τa. From 402 coincident data records, the agreement between satellite and field τa is remarkable, with mean absolute percentage differences of 17–20% in the 412–870 nm spectral range. On the other hand, the satellite record tends to filter out occurrences of high τa. The satellite-derived products are used to analyze the seasonal cycle over the Adriatic basin, showing minima in winter and maxima in summer (τa(500) from 0.06 to 0.23). Then, the results of radiative transfer simulations are combined with the satellite-derived seasonal cycles of τa and cloud fraction to determine the clear-sky aerosol direct radiative effect for the Adriatic Sea. At the surface, the aerosol load results in a monthly average cooling effect ranging from −1 W m−2 in winter up to −9.6 W m−2 in August and a corresponding atmospheric warming from 0.5 to 4.6 W m−2.
Age, Intentions and the Implicit Role of Out-Selection Factors of International Migration

In this paper, I propose to isolate the role of age as a self-selection factor of international migration. The role of age is estimated on intended emigration rather than on observed outcomes of migration, using individual measures of intended emigration drawn from a large-scale survey conducted by Gallup. I find evidence that age has a monotonic negative effect on desired emigration for the working-age population. The estimations point to a very robust effect, suggesting that an additional year of age decreases the probability of intended emigration by about 0.5%. This effect is steady over different periods of time and for most types of countries of origin. The results contrast with previous evidence obtained on observed outcomes of migration, suggesting that out-selection factors interact with age and shape the demographic profile of migrants.
Air-sea CO2 fluxes above the stratified oxygen minimum zone in the coastal region off Mexico

Oxygen minimum zones (OMZs) are important sources of CO2 to the atmosphere when physical forces bring subsurface water with high dissolved inorganic carbon (DIC) to the surface. This study examines, for the first time, the influence of the OMZ of the coastal North Eastern Tropical Pacific off Mexico on surface CO2 fluxes. We use variations in the oxycline depth and subsurface water masses to discern physical oceanographic influences. During two cruises, in November 2009 and August 2010, DIC and total alkalinity (TA) measurements were used to estimate pCO2 and air-sea CO2 fluxes. At the OMZ layer, Subtropical Subsurface Water (StSsW) was found to have high pCO2 values (1290 ± 70 μatm). Due to strong vertical stratification, however, the relationship between ΔpCO2 at the air-sea interface and the oxycline/StSsW upper limit depth was weak. During November, the region was a weak source of CO2 to the atmosphere (up to 2.5 mmol C m−2 d−1), while during August a range of values were observed between −4.4 and 3.3 mmol C m−2 d−1). Strong stratification (>1200 J m−3) prevented subsurface mixing of water from the OMZ to the upper layer; particularly in November 2009 which was during an El Nino event. Results suggest that advection of surface water masses, reinforced by strong vertical stratification, controlled surface pCO2, and air-sea CO2 fluxes.
An AC Voltage Balancer and its Improved Modulation Strategy for CHB Based PV Inverters

Cascaded H-bridge (CHB) inverters have been widely used in distributed photovoltaic (PV) power generation systems due to their attractive features in terms of power quality and easy to expand compared to two-level or three-level inverters. Especially the modular inverters with an interphase structure composed of four-port isolated DC/DC converters and CHB inverters are preferred by academia and industry because it can naturally balance the power difference between phases. However, such modular inverters still suffer from some issues that need to be addressed, such as power mismatch between modules within the same phase. This will lead to overmodulation of some H-bridge inverter units and grid-connected current distortion, and even threaten the safe and stable operation of the entire modular inverter. In view of this problem, an AC voltage balancer (ACVB) is proposed in this article to achieve power balance between adjacent H-bridge inverter units. Furthermore, an improved modulation strategy is also presented to achieve soft switching of ACVB. Finally, the effectiveness of the proposed ACVB and its improved modulation strategy is verified by experimental results.
Markov Flow Models and the Flood Warning Problem

Let {Yj} represent periodically sampled river discharge values. For simplicity, say that a flood occurs at epoch n + 1 if, for some fixed T, Yn+1 > T. Assume that at epoch n, the decision maker must decide whether or not to issue a flood warning, this decision being based on the past flow record {Yj} j≤n. Finally, assume that costs have been assigned to the two types of mistakes: the “false alarm” event, and the event that a flood occurs when no warning was issued. It is argued that outside the Gaussian assumption, standard time series methodology is inappropriate for the flood warning problem. The purpose of this paper is to relate recent progress based on alternate principles. A nonparametric inference procedure is described which converges to the optimal decision function for the flood warning problem as the length of the historical record increases for any stationary G2-ergodic Markov process. Under additional assumptions, rates can be established and shown to be optimal in a certain sense. The new methodology is compared with autoregressive moving average predictors on simulated and river flow data.