Miracle-dz/UniFAR-FTUs huggingface dataset:
Demonstrating Shrodenger equation involving harmonic oscillator potential with a position dependent mass in an external electric field

An external electric field is provided to the familiar one-dimensional quantum harmonic oscillator model with a various position mass m(x)=(a m_0)/(a+x). The Nikiforov-Uvarov approach is involved to investigate a particular solution to the exact Schrödinger equation. The exactly solvable confined model of the quantum harmonic oscillator in an external electric field was proposed. Starting with the BenDanial-Duke kinetic energy operator approximations, the construction of the position-dependent mass Schrödinger equation is studied. The analytic representation of the wave functions of the stationary states is expressed analytically and graphically using modified Laguerre polynomials as well as the energy spectrum. In contrast with the absence of an external electric field, when the energy spectrum totally overlaps with that of the harmonic oscillator potential in an external electric field: the energy spectrum becomes non-equidistant and varies depending on some factors. The Nikiforov-Uvarov approach succeeds broadly in demonstrating the wave function and energy spectrum and showing good sense.
A rapid estimation of near‐field tsunami runup

Many efforts have been made to quickly estimate the maximum runup height of tsunamis associated with large earthquakes. This is a difficult task because of the time it takes to construct an accurate tsunami model using real‐time data from the source. It is possible to construct a database of potential seismic sources and their corresponding tsunami a priori. However, such models are generally based on uniform slip distributions and thus oversimplify the knowledge of the earthquake source. Here we show how to predict tsunami runup from any seismic source model using an analytic solution that is specifically designed for subduction zones with a well‐defined geometry, i.e., Chile, Japan, Nicaragua, and Alaska. The main idea of this work is to provide a tool for emergency response, trading off accuracy for speed. The solutions we present for large earthquakes appear promising. Here runup models are computed for the following: the 1992 Mw 7.7 Nicaragua earthquake, the 2001 Mw 8.4 Perú earthquake, the 2003 Mw 8.3 Hokkaido earthquake, the 2007 Mw 8.1 Perú earthquake, the 2010 Mw 8.8 Maule earthquake, the 2011 Mw 9.0 Tohoku earthquake, and the recent 2014 Mw 8.2 Iquique earthquake. The maximum runup estimations are consistent with measurements made inland after each event, with a peak of 9 m for Nicaragua, 8 m for Perú (2001), 32 m for Maule, 41 m for Tohoku, and 4.1 m for Iquique. Considering recent advances made in the analysis of real‐time GPS data and the ability to rapidly resolve the finiteness of a large earthquake close to existing GPS networks, it will be possible in the near future to perform these calculations within the first minutes after the occurrence of similar events. Thus, such calculations will provide faster runup information than is available from existing uniform‐slip seismic source databases or past events of premodeled seismic sources.
A Hybrid Chirp Scaling Algorithm for Squint Sliding Spotlight SAR Data Imaging

Squint spaceborne synthetic aperture radar (SAR) can significantly improve the ground observation performance of platform sensor through flexible beam pointing; however, it is still challenging for squint spaceborne sliding spotlight SAR data focusing since the significant range cell migration (RCM) and range azimuth coupling (RAC) caused by the squint angles. Whereas the linear range walk correction (LRWC) can deal with these problems, the traditional chirp scaling (CS) algorithm cannot adapt to the signal model after the LRWC operation, especially in the case of sliding spotlight mode. In this letter, a hybrid CS algorithm (HCSA), integrating the modified CS (MCS) in range time domain with the frequency CS (FCS) and frequency nonlinear CS (FNLCS) in azimuth frequency domain, is proposed for squint sliding spotlight SAR system. After LRWC and deramp operations, the hybrid CS (HCS) based on the updated signal model is employed to fulfill whole scene focusing, which can equalize the Doppler frequency modulation rate (DFMR) and handle the back-folding issue in azimuth time domain simultaneously. The geometric correction is then be applied to obtain the focused SAR image without LRWC geometry distortion. Simulation demonstrates that for the spaceborne SAR with 1.0 m resolution in both range and azimuth directions, and a squint angle of 30°, the proposed HCSA can realize effective focusing within the full scene.
Cloud Detection in Hyperspectral Images with Atmospheric Column Water Vapor: Application to PRISMA and AVIRIS-NG Images

The Cloud detection in Hyperspectral Images With Atmospheric column WAter vapor (CHIWAWA) cloud detection method is presented. It aims to detect thick and thin clouds in a single hyperspectral image covering the reflective spectral range (400–2500 nm) in an unsupervised way. Its main originality is to combine the complementary information available in the ground reflectance image and the atmospheric column water vapor (WV) map. The method uses criteria based on reflectance to compute a mask of potential cloud pixels and refine it by exploiting the WV map. The use of the WV map is central to the method, as it has the greatest discriminating power. It, therefore, plays a role similar to that of thermal bands that are very useful for cloud detection but are absent in the reflective spectral range. Two specific processings are also proposed to detect snow and ice pixels and reduce the altitude dependence of the WV map in mountain images. CHIWAWA performance is assessed on several hyperspectral images acquired with PRecursore IperSpettrale della Missione Applicativa (PRISMA) and Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) sensors. Overall accuracy ranges from 97% to 100% for both sensors. When cloud cover is above 10%, $F_{1}$ score ranges in 94%–100% for both sensors. For lower cloud covers, $F_{1}$ score ranges in 83%–94% for PRISMA images and in 84%–91% for AVIRIS-NG images. CHIWAWA may encounter difficulties in detecting thin clouds located over urban areas or when the contrast between the cloud and its surroundings is low in the WV map.
Modulation of the pre-metastatic bone niche: molecular changes mediated by bone-homing prostate cancer extracellular vesicles

Prostate cancer (PCa) is a leading male malignancy worldwide, often progressing to bone metastasis, with limited curative options. Extracellular vesicles (EVs) have emerged as key players in cancer communication and metastasis, promoting the formation of supportive microenvironments in distant sites. Our previous studies have highlighted the role of PCa EVs in modulating osteoblasts and facilitating tumor progression. However, the early pre-metastatic changes induced by PCa EVs within the bone microenvironment remain poorly understood. To investigate the early effects of repeated exposure to PCa EVs in vivo, mimicking EVs being shed from the primary tumor, PCa EVs isolated from cell line PC3MLuc2a were fluorescently labelled and repeatedly administered via tail vein injection to adult CD1 NuNu male mice for a period of 4 weeks. In vivo imagining, histological analysis and gene expression profiling were performed to assess the impact of PCa EVs on the bone microenvironment. We demonstrate for the first time that PCa EVs home to both bone and lymph nodes following repeated exposures. Furthermore, the accumulation of EVs within the bone leads to distinct molecular changes indicative of disrupted bone homeostasis (e.g., changes to signaling pathways such as Paxillin p = 0.0163, Estrogen Receptor p = 0.0271, RHOA p = 0.0287, Ribonucleotide reductase p = 0.0307 and ERK/MAPK p = 0.0299). Changes in key regulators of these pathways were confirmed in vitro on human osteoblasts. In addition, our data compares the known gene signature of osteocytes and demonstrates a high proportion of overlap (52.2%), suggesting a potential role for this cell type in response to PCa EV exposure. No changes in bone histology or immunohistochemistry were detected, indicating that PCa EV mediated changes were induced at the molecular level. This study provides novel insights into the alterations induced by PCa EVs on the bone microenvironment. The observed molecular changes indicate changes in key pathways and suggest a role for osteocytes in these EV mediated early changes to bone. Further research to understand these early events may aid in the development of targeted interventions to disrupt the metastatic cascade in PCa.
Prediction of Compaction Parameters Using Regression and ANN Tools

The compaction parameters are not only important for quality control of earthworks but are required for designing of various works. The engineering properties of soils such as shear strength, CBR, permeability and consolidation parameters are usually determined by testing the samples prepared at optimum moisture content (OMC) and maximum dry density (MDD). On any project, a large number of soil types are generally used. For each soil, besides the basic soil classification parameters, compaction parameters are also determined. Testing of large numbers of soil samples is a cumbersome and time consuming job and requires trained personnel for the purpose. Further, an independent check on the results obtained in the laboratory is also required to make use of test values on site with confidence. Therefore, a need is felt to obtain the required compaction parameters from the basic soil test which are used for the classification of soil viz. Atterberg’s limits, gradation, specific gravity etc. In this endeavour, basic soil parameters were collected from literature and Artificial Neural Network (ANN) techniques have been employed on the data collected, as ANN can better model the relation between compaction parameters and basic soil properties than statistical modelling. Present work demonstrates application of five different ANN algorithms viz. LM, GDM, SCG, BR and CFB to predict standard compaction characteristics of varieties of soils with a large range variation in their basic soil properties. Multiple variable non-linear regression analysis was also carried out, in which establishment of an empirical relationship for prediction of compaction characteristics of Modified compaction (i.e., OMC2 and MDD2) by using Standard compaction values (i.e., OMC1 and MDD1) was attempted. Then validation by an independent outside dataset from literature of Horpibulsuk et al. (2009) was also carried out on ANN models and regression analysis done.
Diet and Chronic Constipation in Children: The Role of Fiber

This is a case control study of the hypothesis that idiopathic chronic constipation in children is related to dietary fiber intake. The study took place in Greece. A randomized sample (291 children with constipation and 1,602 controls aged 2 to 14 years) were examined. The criteria for chronic constipation were less than or equal to three bowel movements per week, or hard stools with painful defecation, regardless of stool frequency, for the past 2 months. Stratification was performed for socioeconomic status, and location: urban, rural, or suburban. A dietary history and 3-day calorie count were performed. Parents
An empirical study on how emotion affects the probability of replies based BERT

The rapid development of the internet, social media, and online forums have become crucial platforms for people to express their views and emotions. Comments are not only a way for users to express their opinions but also play a vital role in promoting discussions and interactions between users, significantly influencing public opinion. This paper aims to explore the impact of emotions on the likelihood of comments receiving replies, deepening the understanding of the role of emotional factors in interactions on social media and online forums. Through large-scale model training and pipeline parallel computation, this paper employs the Bidirectional Encoder Representations from Transformers (BERT) model for learning and prediction, enhancing accuracy and efficiency. The experimental results show that the response rate of negative emotional comments is about 27%, while the response rate of positive emotional comments is about 18%. It means that the comments with negative emotions are more likely to receive replies than those with positive emotions.
Sex-Based Analysis of Quality Indicators of End-of-Life Care in Gastrointestinal Malignancies

Indices of aggressive or supportive end-of-life (EOL) care are used to evaluate health services quality. Disparities according to sex were previously described, with studies showing that male sex is associated with aggressive EOL care. This is a secondary analysis of 69,983 patients who died of a GI malignancy in Ontario between 2006 and 2018. Quality indices from the last 14–30 days of life and aggregate measures for aggressive and supportive EOL care were derived from administrative data. Hospitalizations, emergency department use, intensive care unit admissions, and receipt of chemotherapy were considered indices of aggressive care, while physician house call and palliative home care were considered indices of supportive care. Overall, a smaller proportion of females experienced aggressive care at EOL (14.3% vs. 19.0%, standardized difference = 0.13, where ≥0.1 is a meaningful difference). Over time, rates of aggressive care were stable, while rates of supportive care increased for both sexes. Logistic regression showed that younger females (ages 18–39) had increased odds of experiencing aggressive EOL care (OR 1.71, 95% CI 1.30–2.25), but there was no such association for males. Quality of EOL care varies according to sex, with a smaller proportion of females experiencing aggressive EOL care.
Optimal Trading Volume of Electricity and Capacity of Energy Storage System for Electric Vehicle Charging Station Integrated with Photovoltaic Generator

As penetration of EVs in the transportation sector is increasing, the demand for the mandatory installation of charging infrastructure also is increasing. In addition, renewable energy and energy storage systems (ESSs) are being reviewed for use in electric vehicle charging stations (EVCSs). In this paper, we present an optimal electricity trading volume and an optimal installation capacity of ESSs to maximize the daily profit of the EVCSs equipped with solar power generation when the EVCSs are licensed to sell energy to the power supplier during a specific time period. By formulating and solving the optimization problem of the EVCSs, this paper analyzes validation results for the different useful lives of ESSs, the peak power of a PV generator, and weather conditions at the Yangjae Solar Station and the Suseo Station public parking lot, Seoul, Republic of Korea. Furthermore, this paper validates that the daily expected profit of EVCSs with the proposed method outperforms the profit of conventional EVCSs which do not utilize ESSs.
Impact of Gender Specific Human Capital on Economic Growth: The Role of Financial Development

This study examines the impact of gender-specific human capital on economic growth and explores how this impact depends on the level of financial development. There is considerable debate about the contribution of gender-specific human capital to substantial economic growth. This study utilized panel data from 57 countries spanning the period of 1980 to 2020 and employed pooled OLS and fixed effect techniques for empirical analysis. The results indicate that both male and female human capital exert a significant and positive impact on economic growth. Furthermore, the findings reveal that financial development undermines the positive impact of male and female human capital on economic growth, suggesting substitutability between human capital and financial development. Based on these findings, this study proposes that policymakers focus on controlling excess money supply to enhance the effectiveness of financial development.
Samuel Beckett’s Dramatic Dialectical Solution to the Contradictory Relationship between Hamm and Clov in Endgame

This article aims to discuss Beckett's dramatic solution to the problematic dramatization of Albert Camus's concept of "the absurd man," which he coined in his book The Myth of Sisyphus translated by Justin O'Brien, in the relationship between Hamm and Clov in Endgame . The departure point is defining the concept of "the absurd" and then the concept of "the absurd man" since they are intertwined and interdependent. In light of this, the article presents some manifestations of the absurd in the dramatic world of the play, and then analyses how the two characters Hamm and Clov respond to them. This intends to answer the pivotal research question: How does Beckett dramatize the concept of the absurd man in the relationship between Hamm and Clov? The investigation of the question unravels the problematic relationship between the two characters who are contradictorily united. This contradiction which bends them together necessitates the adoption of Hegel's dialectical method to investigate their problematic relationship and show how Beckett solves it dialectically.
Comparing ATPase activity of ATP-binding cassette subfamily C member 4, lamprey CFTR, and human CFTR using an antimony-phosphomolybdate assay

Introduction: ATP-binding cassette (ABC) transporters use the hydrolysis of ATP to power the active transport of molecules, but paradoxically the cystic fibrosis transmembrane regulator (CFTR, ABCC7) forms an ion channel. We previously showed that ATP-binding cassette subfamily C member 4 (ABCC4) is the closest mammalian paralog to CFTR, compared to other ABC transporters. In addition, Lamprey CFTR (Lp-CFTR) is the oldest known CFTR ortholog and has unique structural and functional features compared to human CFTR (hCFTR). The availability of these evolutionarily distant orthologs gives us the opportunity to study the changes in ATPase activity that may be related to their disparate functions. Methods: We utilized the baculovirus expression system with Sf9 insect cells and made use of the highly sensitive antimony-phosphomolybdate assay for testing the ATPase activity of human ABCC4 (hABCC4), Lp-CFTR, and hCFTR under similar experimental conditions. This assay measures the production of inorganic phosphate (Pi) in the nanomolar range. Results: Crude plasma membranes were purified, and protein concentration, determined semi-quantitatively, of hABCC4, Lp-CFTR, and hCFTR ranged from 0.01 to 0.36 μg/μL. No significant difference in expression level was found although hABCC4 trended toward the highest level. hABCC4 was activated by ATP with the equilibrium constant (Kd) 0.55 ± 0.28 mM (n = 8). Estimated maximum ATPase rate (Vmax) for hABCC4 was about 0.2 nmol/μg/min when the protein was activated with 1 mM ATP at 37°C (n = 7). Estimated maximum ATPase rate for PKA-phosphorylated Lp-CFTR reached about half of hCFTR levels in the same conditions. Vmax for both Lp-CFTR and hCFTR were significantly increased in high PKA conditions compared to low PKA conditions. Maximum intrinsic ATPase rate of hABCC4 in the absence of substrate was twice that of hCFTR when activated in 1 mM ATP. Conclusion: The findings here suggest that while both ABCC4 and hCFTR bear one consensus and one degenerate ATPase site, the hCFTR exhibited a reduced intrinsic ATPase activity. In addition, ATPase activity in the CFTR lineage increased from Lp-CFTR to hCFTR. Finally, the studies pave the way to purify hABCC4, Lp-CFTR, and hCFTR from Sf9 cells for their structural investigation, including by cryo-EM, and for studies of evolution in the ABC transporter superfamily.
Research gaps and future needs for allergen prediction in food safety

The allergenicity and protein risk assessments in food safety are facing new challenges. Demands for healthier and more sustainable food systems have led to significant advances in biotechnology, the development of more complex foods, and the search for alternative protein sources. All this has increased the pressure on the safety assessment prediction approaches anchored into requirements defined in the late 90's. In 2022, the EFSA's Panel on Genetically Modified Organisms published a scientific opinion focusing on the developments needed for allergenicity and protein safety assessments of new products derived from biotechnology. Here, we further elaborate on the main elements described in this scientific opinion and prioritize those development needs requiring critical attention. The starting point of any new recommendation would require a focus on clinical relevance and the development of a fit-for-purpose database targeted for specific risk assessment goals. Furthermore, it is imperative to review and clarify the main purpose of the allergenicity risk assessment. An internationally agreed consensus on the overall purpose of allergenicity risk assessment will accelerate the development of fit-for-purpose methodologies, where the role of exposure should be better clarified. Considering the experience gained over the last 25 years and recent scientific developments in the fields of biotechnology, allergy, and risk assessment, it is time to revise and improve the allergenicity safety assessment to ensure the reliability of allergenicity assessments for food of the future.
Overcoming Beam Squint in mmWave MIMO Channel Estimation: A Bayesian Multi-Band Sparsity Approach

The beam squint effect, which manifests in different steering matrices in different sub-bands, has been widely considered a challenge in millimeter wave (mmWave) multi-input multi-output (MIMO) channel estimation. Existing methods either require specific forms of the precoding/combining matrix, which restrict their general practicality, or simply ignore the beam squint effect by only making use of a single sub-band for channel estimation. Recognizing that different steering matrices are coupled by the same set of unknown channel parameters, this paper proposes to exploit the common sparsity structure of the virtual channel model so that signals from different sub-bands can be jointly utilized to enhance the performance of channel estimation. A probabilistic model is built to induce the common sparsity in the spatial domain, and the first-order Taylor expansion is adopted to get rid of the grid mismatch in the dictionaries. To learn the model parameters, a variational expectation-maximization (EM) algorithm is derived, which automatically obtains the balance between the likelihood function and the common sparsity prior information, and is applicable to arbitrary forms of precoding/combining matrices. Simulation results show the superior estimation accuracy of the proposed algorithm over existing methods under different noise powers and system configurations.