Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of psychopathology, purpose in life, and moral courage in healthcare workers during the COVID-19 pandemic: a longitudinal study

Introduction Almost 2 years and five infection waves after the COVID-19 pandemic started, healthcare workers continued dealing with the pandemic situation and facing the health consequences and the mental health disorders it caused. This study aimed to evaluate the onset and progression of psychopathology as well as the role of predictor variables such as purpose in life and moral courage among healthcare workers during this time. Materials and methods This was a longitudinal prospective study carried out with 45 Spanish healthcare workers who answered two questionnaires, the first questionnaire in April–May 2020 (T1) and the second questionnaire in September–October 2021 (T2). Results Although 29.5% of the sample considered that their mental health had improved over this time, almost half of them (47.7%) said it had not changed, while 22.7% reported a decline in their mental health from the first time they were asked. Specifically, 46.8% presented anxiety, 23.4% depression, and 42.6% acute stress at T1, and 38.3% had anxiety, 17% depression, and 27.7% post-traumatic stress disorder at T2. Despite this, there were no differences between T1 and T2 anxiety scores (p = 0.53), although there was a decrease in depression (p = 0.03) and acute stress (p = 0.02) scores. Predictor variable outcomes such as purpose in life (p = 0.88) and moral courage (p = 0.86; p = 0.38) did not change over time, but when modelling the data, purpose in life predicted psychopathology at T1, which in turn affected the psychopathology results at T2. Conclusion This study showed that, although psychopathology decreased over the months, its prevalence remained high. Even though the purpose in life predicted psychopathology at T1, it seems that once the psychopathology is established (T2), the factors that would improve it would be different from the protective factors that prevented its establishment, which become secondary.
Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications

The ability to create automated algorithms to process gridded spatial data is increasingly important as remotely sensed datasets increase in volume and frequency. Whether in business, social science, ecology, meteorology or urban planning, the ability to create automated applications to analyze and detect patterns in geospatial data is increasingly important. This book provides students with a foundation in topics of digital image processing and data mining as applied to geospatial datasets. The aim is for readers to be able to devise and implement automated techniques to extract information from spatial grids such as radar, satellite or high-resolution survey imagery.
Remobilised silicic tuffs in middle Pleistocene fluvial sediments, southern North Island, New Zealand

Abstract Fluvial and lacustrine sediments of middle Pleistocene age (lower Matuyama Reversed Chron and Jaramillo Subchron) contain numerous thick silicic tuffs that have been deposited in the central southern North Island of New Zealand, 100–200 km from their source in the Taupo Volcanic Zone (TVZ). Sedimentary facies indicate most of the tuffs have been transported and deposited subaqueously in a distal braid‐plain environment. Individual emplacement events represent catastrophic floods involving vertical accretion up to 30 m. Sedimentation patterns reflect rapid volcaniclastic aggradation in response to volcanism, and intervening hiatuses. Over half of the tuffs examined are composed of reworked and mixed rhyolitic (SiO2 72–79 wt%) eruptive products. In addition, most contain brown glasses (SiO2 53–79 wt%) and minerals derived from a range of intermediate to silicic eruptives. Ages and characteristics of the tuffs indicate a major phase of volcanism before and during the Jaramillo Subchron, similar in c.
Cardiovascular Disease in Diabetes and Chronic Kidney Disease

Chronic kidney disease (CKD) is a common occurrence in patients with diabetes mellitus (DM), occurring in approximately 40% of cases. DM is also an important risk factor for cardiovascular disease (CVD), but CKD is an important mediator of this risk. Multiple CVD outcomes trials have revealed a greater risk for CVD events in patients with diabetes with CKD versus those without. Thus, reducing the risk of CKD in diabetes should result in improved CVD outcomes. To date, of blood pressure (BP) control, glycemic control, and inhibition of the renin-angiotensin system (RASI), glycemic control appears to have the best evidence for preventing CKD development. In established CKD, especially with albuminuria, RASI slows the progression of CKD. More recently, sodium glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide receptor agonists (GLP1RA) have revolutionized the care of patients with diabetes with and without CKD. SGLT2i and GLP1RA have proven to reduce mortality, heart failure (HF) hospitalizations, and worsening CKD in patients with diabetes with and without existing CKD. The future of limiting CVD in diabetes and CKD is promising, and more evidence is forthcoming regarding combinations of evidence-based therapies to further minimize CVD events.
Performance Analysis of Multi-RIS-Aided mmWave MIMO Systems Using Poisson Point Processes

Different from previous literature assuming either single reconfigurable intelligent surface (RIS) or multiple RISs at given locations, this letter first studies a multi-user millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system aided by multiple RISs following Poisson point processes. Then we derive an accurate closed-form expression for the spectral efficiency of an arbitrary user and an approximation for the ergodic spectral efficiency of the cell. Moreover, we consider the hardware impairment and model a practical phase-dependent amplitude for each reflecting element. Finally, the simulation results verify the derivations and demonstrate that RISs can provide greater performance gain than the active nodes and require different deployment strategy, which is related to the number of RISs.
Bridging the extant and fossil record of planktonic foraminifera: implications for the Globigerina lineage

We conducted a morphometric study and wall texture analysis on extant and fossil specimens of the planktonic foraminifera Globigerina falconensis plexus. Our global data reveal morphological inconsistencies between fossil and extant populations. Our results are significant as G. falconensis is widely used in palaeoceanographic studies in conjunction with its sister taxon G. bulloides. Morphologically these two species are similar, with the main difference being the distinctive apertural lip present in G. falconensis. We selected cores covering the entire stratigraphic range of G. falconensis, from the early Miocene to current day, spanning sites from high latitudes in the North Atlantic Ocean and the southern Indian Ocean to sites in equatorial regions. The morphology found in the modern ocean is not consistent with the Miocene holotype of Globigerina falconensis Blow described from lower Miocene sediments in Venezuela. A more lobate morphology evolved in the late Miocene, thus, a new name is required for this morphotype, coexisting in the modern oceans with G. falconensis s.s. We thus describe the new morphospecies, G. neofalconensis for the more lobate forms which evolved in the late Miocene and inhabit the modern oceans. Additionally, we report a pseudocancellate wall texture present in the G. falconensis plexus. We use the molecular sequences from the PR2 database to explore the generic attribution of the G. falconensis lineage, confirming its close relationship with G. bulloides and its retention in the genus Globigerina.
Equilibrium and Disequilibrium Trace Element Partitioning in Hydrous Eclogites (Trescolmen, Central Alps)

elements, Pb, Th and U, whereas phengite hosts Ba and is, along Despite the widespread presence of hydrous phases in subductionwith clinopyroxene and paragonite, an important phase for B. related systems, experimental D trace element values for many However, because of their low modal abundance in eclogite-facies hydrous phases are lacking. To fill this gap, we present a set of rocks, phengite and paragonite do not control the B whole-rock budget. D values (where Min indicates amphibole, zoisite, We infer that estimated D values from equilibrium phengite, paragonite or apatite) derived from equilibrium parageneses assemblages can be used as a good approximation for partition of eclogites from Trescolmen (Central Alps, Switzerland). These coefficients under the given PT conditions (>650°C and 2·0 data can be combined with experimental data for D, GPa). Deformation-induced dynamic recrystallization seems to be to estimate D values for the hydrous phases, thus circumventing the driving process necessary for a close approach towards trace experimental problems with the direct determination of such values. element equilibrium. This process should work efficiently during We analysed Li, Be, B, Sr, Y, Zr, Nb, Ba, Ce, Nd, Sm, Pb, Th subduction close to the slab–mantle interface, affecting sediments and U in coexisting phases by laser ablation microprobe inductively and low-T altered mid-ocean ridge basalt, but is of less importance coupled plasma mass spectrometry. Many of the values are extremely inside the slab. Knowledge of D values from equilibrium assemblages low; for example, Nb, Ba, Ce, Th and U are in the lower ppb determined in this study is useful not only for large-scale subductionrange in clinopyroxene. Attainment of equilibrium was evaluated zone modelling, but also as an aid in the selection of equilibrium by textural, and major and trace element characteristics. Nonsubassemblages in imperfectly equilibrated samples, so that a equilibrated assemblages are common in most eclogite localities, crystallization sequence can be derived. including Trescolmen, and using such samples would lead to the derivation of erroneous values for equilibrium partitioning. However, four of the 10 studied eclogites from Trescolmen having homogeneous
Bio-inspired branch structure seismic metamaterial: attenuating low-frequency Rayleigh waves

This study investigates the transmission characteristics of natural forests with branches and introduces a bio-inspired branch structure seismic metamaterial (SM) designed to create bandgaps for low-frequency Rayleigh waves. Employing the finite element method, we reveal the mechanism behind the generation of these Rayleigh wave bandgaps and their transmission properties. A distinct ‘collectivization mode’ within the bio-inspired branch structure SM is identified, effectively attenuating Rayleigh waves. A collectivization coefficient is introduced for quantitative characterization, and we extend the analysis to multi-layered soil mediums, demonstrating an interface with the metamaterial’s bandgaps. The frequency-domain analysis highlights the difference between using the collectivization mode and traditional methods for attenuating surface waves, offering a novel approach to low-frequency Rayleigh wave reduction with implications in seismology and related engineering fields.
'The Place of Cool Waters': Women and Water in the Slums of Nairobi, Kenya

In this paper, we explore how women and young girls in two informal settlements in Nairobi, Kenya, are affected by water in its various forms. We analyze sixteen focus group discussions with women, girls in school, and girls out of school, focusing on their unique water experiences and concerns. Drawing on the strengths of qualitative data, we thickly describe how women navigate the water challenges prevalent in the urban slum context.
Time Frequency Spectral Decomposition for Determination of Bottom Simulating Reflector of Gas Hydrate Seismic Data

Summary Gas hydrate, a complex compound, formed in the special condition of low temperature and high pressure, has been considered as very high potential new energy resources. In the gas hydrate exploration, bottom simulating reflector (BSR), defined as the boundary between gashydrate and free gas zone, is considered as the most important indicator for the gas hydrate exploration by seismic reflectivity method. Additionally, the location of BSR can help to estimate the thermo-dynamic parameters for gas hydrate stability zone. Spectral decomposition methods such as STFT (Short Time Fourier Transform), CWT (Continuous Wavelet Transform) and MPD (Marching Pursuit Decomposition) for seismic data has been proposed and applied in the various rock reservoirs to characterize hydrocarbon indicators as positive anomalies in the spectrum. Because the BSR has several specific characteristics that create strong reflectivity pattern in the seismic section, the time-frequency decomposition could be used to distinguish this boundary in the gas hydrate seismic data by taking the high energy position at the frequency gather slice. The output of seismic data processing for gas hydrate exploration in the Ulleung basin, Korea, will be used for time-frequency analysis and integrated to the well logging data in order to locate the BSR in seismic data. These results showed the high energy position at the time of 0.25-0.30 second below the sea floor reflector at the frequency gather slice of 60 Hz that would indicate to the position of BSR.
Robust Data-Driven Structural Impact Localization With Multisensor Real-Time Monitoring

Transient impact loads can easily cause structural damage and destruction, especially for composite structures that are susceptible to collisions. An accurate impact source localization method is crucial for evaluating the potential structure damage location. The impact response signals, on the other hand, contain varying degrees of high- and low-frequency noise, and the structure is not limited to a single dimension. In this article, the robust localization method with empirical mode decomposition combined wavelet denoising (EMD-WD) and multi-output support vector regression (MSVR) is proposed. Following the achievement of intrinsic mode function (IMF) of distinct frequency bands, the last order IMF is abandoned to filter the low-frequency disturbance. Following that, the discrete wavelet transform is used to treat high-frequency noise. Then, multidimensional features of impact responses, including time domain (TT), frequency domain (FF), time–frequency domain (TF), and distance domain (DD), are extracted. Finally, MSVR trained with multidimensional feature vectors is used to predict various impact location coordinate values. The results on plate structure and cylinder composite monitoring data prove that the proposed method can realize acceptable localization performance on both the 2-D and 3-D structures compared with other methods, with certain abilities to resist noise interference.
Holocene vegetation history from the

The pollen stratigraphy of an ombrotrophic patterned ridge-hollow raised bog in the Salym-Yugan Mire Area in boreal West Siberia (60°10N, 72°50E) covers the entire Holocene period. Pollen data from three parallel peat cores suggest that, contrary to previous assumptions, Betula forests did not spread into tundra until the Boreal period (9000-10 000 cal. BP). After 9000 cal. BP, Pinus sylvestris and Picea abies forests displaced Betula forests in the area and dominated until 4100-4300 cal. BP, when Picea decreased considerably due to a climatic change and Pinus sylvestris became the most abundant tree species. Average pollen influx estimates during the wooded period, from about 9000 cal. BP onwards, were 5600-6350 grains cm-2 yr-1, similar to pollen-trap estimates from boreal coniferous forests.
Classification of Time Series Using FCM-Based Forecasting Models

In this study, a method of time series classification is considered. Classification is performed using forecasting models. It is assumed that processed time series are of different natures, i.e., they belong to different classes. Each class has its forecasting model. Thus, an unknown time series is presented to the models to evaluate forecasting errors. The classified time series is assigned to the class with the winning forecasting model. In the study, Fuzzy Cognitive Maps are used to build forecasting models. Prior to forecasting, the processed raw time series are preprocessed. Six different error functions having the most significant influence on classification are used. The error functions come from root mean square error and mean percentage error.
Optimization of the Black-Box Arc Models for DC Current Limiting Circuit Breakers Using Levenberg-Marquardt Algorithm

The black-box arc model is a tool that facilitates efficient research based on empirical studies in breaker design and analysis. However, its application has primarily focused on the design of ACCBs, with only a few instances of its implementation in the design of low-voltage (LV) DC circuit breakers (DCCBs) using mechanical methods. In DCCBs with non-zero crossing characteristics, several factors need to be considered in the design process. Therefore, it is crucial to have a reliable and accurate DC arc model to effectively apply black-box arc model studies to actual DCCB designs. Especially, DC Current limiting circuit breaker (CLCB), which has fast operation characteristics through its own over current relays (OCR), requires reliable and accurate modeling because minor factors in the topology can contribute significantly to the interrupting performance. This paper presents a study on the characterization and modeling approach for the DC CLCB, which exhibits somewhat different arc voltage characteristics compared to the general Air Circuit Breaker (ACB). The black-box arc model incorporates existing schwarz and kema arc models, and the Levenberg-Marquardt Algorithm (LMA) is employed to optimize the parameters of each model. An efficient parameter optimization method for the CLCB model is proposed, and the characteristics of factors that should be considered in the design are identified. Consequently, the applicability and reliability of the model are verified through a comparative study with the short-circuit test results of the actual DC CLCB.
The Exploratory Factor Analysis on Firms Performance of Micro and Small Enterprises in Indonesia

Research on Firms Performance of Micro and small-sized enterprises (MSEs) continues to grow, especially in developing countries such as Indonesia. This study is designed to build and validate the SME Performance (SP) instrument through the Exploratory Factor Analysis (EFA) which is limited to MSEs in Pekanbaru, Indonesia. This study analysed variable of Entrepreneur Expertise (EC), Government Support (GS) and Entrepreneur Environment (EE). This study followed a cross-sectional study style, with quantitative data obtained from 100 small and mediumsized enterprises based in Indonesia. This study Focused on the reliability measure, this analysis completed the instrument in eighteen (31) pieces. In this case the researcher measures the internal reliability value (i.e. the Cronbach Alpha Value) for the current SP Variable. This research outlines in depth the process for carrying out an EFA examination of SP constructs. This research outlines in depth the process for carrying out an EFA examination of SP constructs. The findings of this analysis may be useful for applied researchers involved in Entrepreneur Performance research.
Impacts of airborne volcanic ash on the surface ocean biogeochemistry and marine ecosystems

The availability of nutrients in the surface ocean affects the marine primary productivity (MPP), and the atmosphere represents an important source of nutrients to the euphotic zone of the in the global ocean. Volcanic eruptions, can through atmospheric transport, deposit volcanic ash into the ocean and partial dissolution of ash particles in seawater can provide biologically relevant elements for the ocean. Despite the high input of volcanic ash into the ocean, the role of volcanic eruptions in the surface ocean biogeochemistry was largely overlooked. The primary goal of this study is to evaluate the possible impact of explosive volcanic eruptions on the surface ocean nutrient and its influence on MPP in different oceanic regions (in high- and low-nutrient, low production areas), and influence on the oceanic food-web. By using new clean-laboratory-based geochemical nutrient release data from volcanic ash, and estimates of the marine flux of volcanic ash over long-term periods and/or during single major eruptions, the study provides a new constraints on the importance of volcanic ash deposition for marine nutrient-cycles compared to other major sources such as desert dust. It is also indicated that increased phytoplankton abundance in the surface ocean in large-scale ash fall-out regions can impact the marine food-web (e.g., the increased abundance of zooplankton and salmon fish). Shifts in the phytoplankton community upon addition of volcanic ash can influence the export of biogenic material into the deep ocean, and may eventually affect the carbon cycle.
Inversion of 1-D Resistivity Data using RR-PSO algorithm to identify Shallow Gas in Balikpapan

In recent years shallow gas blowouts have occurred several times in Balikpapan residential areas due to drilling activities for groundwater exploration and geological structures that play as a gas trap. It is necessary to identify structures containing shallow gas by implementing geophysical methods namely Vertical Electrical Sounding (VES). VES is an electrical resistivity method which involves the rapid measurement of variations of the ground resistivity with increasing electrode spaces. The output of this method is a 1-D resistivity model used to identify shallow gas. The 1-D resistivity model can be obtained by the inversion technique. In general, the inversion of VES data is conducted using local optimization method. However, this method has several limitations hence we need to implement a global optimization method in VES data inversion. In this work, the RRPSO algorithm was implemented, which is a global optimization method, in VES data inversion to obtain 1-D resistivity model. First, the RR-PSO algorithm is built and tested to invert synthetic data to evaluate the algorithm's performance. In this stage, the similarity index and several statistical parameters of the inversion results were calculated. After the synthetic test, the algorithm is implemented on field data inversion. The result shows that the RR-PSO algorithm has successfully inverted both the synthetic and field data. In the synthetic test, the similarity index obtained is more than 95%. The 1-D resistivity model from field data inversion indicates at the depth of 20 – 55 m a high resistivity anomaly that is identified as shallow gas. For further study, the RR-PSO algorithm could be implemented for other VES data to construct 2-D resistivity model in the study area (Palm Hills Resident area, south Balikpapan) for imaging the shallow gas presence as a mitigation measure.