Miracle-dz/UniFAR-FTUs huggingface dataset:
A Phase-resolved View of the Low-frequency Quasiperiodic Oscillations from the Black Hole Binary MAXI J1820+070

Although low-frequency quasiperiodic oscillations (LFQPOs) are commonly detected in the X-ray light curves of accreting black hole X-ray binaries, their origin still remains elusive. In this study, we conduct phase-resolved spectroscopy in a broad energy band for LFQPOs in MAXI J1820+070 during its 2018 outburst, utilizing Insight-HXMT observations. By employing the Hilbert–Huang transform method, we extract the intrinsic quasiperiodic oscillation (QPO) variability, and obtain the corresponding instantaneous amplitude, phase, and frequency functions for each data point. With well-defined phases, we construct QPO waveforms and phase-resolved spectra. By comparing the phase-folded waveform with that obtained from the Fourier method, we find that phase folding on the phase of the QPO fundamental frequency leads to a slight reduction in the contribution of the harmonic component. This suggests that the phase difference between QPO harmonics exhibits time variability. Phase-resolved spectral analysis reveals strong concurrent modulations of the spectral index and flux across the bright hard state. The modulation of the spectral index could potentially be explained by both the corona and jet precession models, with the latter requiring efficient acceleration within the jet. Furthermore, significant modulations in the reflection fraction are detected exclusively during the later stages of the bright hard state. These findings provide support for the geometric origin of LFQPOs and offer valuable insights into the evolution of the accretion geometry during the outburst in MAXI J1820+070.
Using a Soil Hydrology Model to Obtain Regionally Averaged Soil Moisture Values

Abstract The Soil Hydrology Model (SHM) was modified, and daily simulations of soil volumetric water content were made at 38 Oklahoma Mesonet sites for July 1997. These model results were compared with soil moisture observations made at the mesonet sites at depths of 5, 25, 60, and 75 cm. This work is believed to be the first time that a hydrological model has been evaluated with in situ soil moisture measurements over such an extensive area spanning several climate zones. Comparisons of time series between the observed and modeled domain-averaged volumetric water content at 5 cm revealed similar phase and amplitude changes, a coefficient of determination (R2) of 0.64, and small mean bias and root-mean-square errors (MBE and rmse) of 0.03 and 0.09, respectively. At 25, 60, and 75 cm, the model performance was slightly worse, with R2 values between 0.27 and 0.40, MBE between −0.01 and 0.02, and rmse between 0.11 and 0.13. The model response to changes in soil water at these levels was sluggish, possibly be.
Numerical Investigations of Indoor Air Quality in Infection Isolation Rooms

This paper uses computational fluid dynamics to assess the ability of the ventilation system to reduce the risk of infection in isolation rooms. It also deals with the influence of different designs of isolation rooms and operating parameters on the velocity, the characteristics of temperature and concentrations of pollutants distributions. The aim of this work is to investigate various isolation rooms with different ventilation system designs . These predicted behaviour and characteristics were compared numerically to assess compliance with the requirements of air flow patterns and the prevailing International standards. One may conclude that, the unidirectional airflow is the most versatile, low cost, energy efficient and environmentally cleaner of possible air pollutants .
Robust Modeling and Predictions of Greenhouse Gas Fluxes from Forest and Wetland Ecosystems

Gap-filling of net ecosystem exchange (NEE) in eddy covariance time series is necessary for the accurate estimation of the terrestrial ecosystems’ carbon balance. Available gap-filling techniques are mostly site-specific and require meteorological data (non-linear regression, artificial neural network, semi-parametric models) and historical NEE information (mean diurnal variation method) as inputs. These limitations require the development of a model that is robust in space and time and needs minimum parameter set. Application of scaling can lead to such generalized modeling approach for the gap-filling of different diurnal hours of NEE. In this connection, a scaling based empirical model was developed for spatiotemporally robust predictions of the diurnal cycle of terrestrial growing season NEE from a corresponding single reference observation by using an extended stochastic harmonic algorithm (ESHA). A reference-time observation from each diurnal cycle was utilized as the scaling parameter to normalize the corresponding hourly observations of NEE for different days into a single, dimensionless diurnal curve. The scaled harmonic model was evaluated by predicting the hourly observed growing season NEE time-series of June to September during 2005-2013 for five AmeriFlux sites, representing distinct deciduous forest ecosystems as the case studies. The developed model incorporated a parsimonious set of five parameters, which exhibited spatiotemporal robustness by collapsing into narrow ranges with no apparent trends or groupings among the different days and sites. Model calibrations demonstrated good modeling efficiency (coefficient of determination, R2 = 0.68 to 0.88) and accuracy (ratio of root-mean-square error to the standard deviation of observations, RSR = 0.35 to 0.57) for different sites. Model validations with the years of growing season observations outside the calibration period also showed good performance (R2 = 0.66 to
Epidemic spreading on coupling network with higher-order information layer

Epidemic tends to break out with information spreading which occurs between pairwise individuals or in groups. In active social online platform, three or more individuals can share information or exchange opinion, which could be modeled as a clique beyond pairwise interaction. This work studies the influence of information with higher-order cliques whose closure probability is described by higher-order clustering coefficient on epidemic spreading. The coupled spreading process of disease and awareness follows an unaware-aware-unaware-susceptible-infected-susceptible model on multiplex networks. We deduce the epidemic threshold of multiplex network with higher-order cliques, and explore the effects of cliques on epidemic spreading process at slow, middle and fast pairwise information spreading rates. The results show that the epidemic threshold and higher-order clustering coefficient are positively correlated. Moreover, we find that the effect of higher-order cliques could be ignored when pairwise information spreading rate is large enough. Finally, we show that the steady infection ratio decreases with the increase of the higher-order clustering coefficient.
Waterfronts : spatial composition and cultural use

During the 1950s and 1960s, the change in economic conditions and new transportation technologies resulted in the abandonment of large tracks of urban industrial waterfronts. In the last two decades, these derelict and underutilised urban waterfronts have come to be seen as an important cultural public domain reflecting a 'cultural turn' in post-modern and post-industrial society. There is, however, a lack of research into the spatial and functional composition of these waterfronts for cultural uses and activities. In addition, there is a lack of studies on the design of cultural waterfronts that highlight the different spatiality of these waterfronts compared to inland areas. This study looks at the various design approaches that generate opportunities for cultural uses and activities at the post-industrial waterfront. A combination of an in-depth literature review on past and present waterfront redevelopments around the world, and an in-depth study of the Baltimore Inner Harbour cultural waterfront were undertaken. The case study applied a multi dimensional approach consisting of five individual methods - historical, morphological, observation, a questionnaire and an interview analysis. These methods collected different layers of data through which a picture of the use and value of Baltimore Inner Harbour as a cultural space was gradually built up. The study uncovered seven theoretical themes to be considered in the design of a successful cultural waterfront, each of which is examined through empirical evidence from the research findings: 1) the notion of a cultural waterfront 2) the image of the cultural waterfront 3) design process for cultural waterfronts 4) five realms of waterfronts 5) designing the 'waterscape environment' 6) characteristics of the five components that make cultural waterfronts and 7) the concept of 'waterfront attraction' in designing waterfront space.
Contribution of Next Sequencing Generation in Lung Cancer and Its Prognostic Implication

Lung cancer is one of the most commonly diagnosed cancers worldwide. It is the leading cause of cancer-related deaths in both men and women. In 2020, there were an estimated 2.2 million new cases of lung cancer and 1.8 million deaths due to the disease. Historically, lung cancer has been more common in men, but the gap has been closing. Smoking tobacco is the leading cause of lung cancer. Survival rates for lung cancer vary greatly depending on the stage at diagnosis and other factors. Overall, the prognosis for lung cancer is often poor, with a relatively low five-year survival rate compared to some other cancers. In this work we aim to show new paths in the diagnosis of lung cancer, through the study of several mutations and proteins, mostly detected by Next-generation sequencing (NGS) which has significantly transformed our understanding of cancer, by providing high-throughput and cost-effective methods for analyzing genomic information. In the context of lung cancer, NGS has played a crucial role in advancing our knowledge of the disease, improving diagnosis and treatment, and guiding personalized medicine approaches. key points highlighting the importance of next-generation sequencing in lung cancer: Comprehensive Genomic Profiling Identification of Driver Mutations Stratification of Patients Predicting Treatment Response Monitoring Disease Progression Clinical Trials and Drug Development Early Detection and Prognosis A large meta-analysis has been done, as well as a detailed study of 86 patients diagnosed with lung cancer in the ANALIZA laboratory. In this sense the most frequently implicated mutations in this tumor have been analyzed, ALK, ROS1 and EGFR, the positions they occupy in the genes, in addition to the programmed death ligand 1 (PD-L1), an immune control protein, which is expressed in activated immune cells and in tumor cells, and how its identification allows us to direct treatment in a more optimal way. In summary, next-generation sequencing has revolutionized the field of lung cancer research and clinical practice. By providing detailed insights into the genomic landscape of tumors, NGS facilitates personalized treatment approaches, early detection, and ongoing monitoring, ultimately leading to improved patient outcomes.
Global Warming and the Pattern of Overall Climate Changes in Sub-Himalayan Assam Region of North-East India

This study examines the changing pattern of climatic factors in the Sub-Himalayan region in the Northeast during last four decades. Sub-regional variation in climatic indicators and their relation with the anthropogenic human activities like deforestation, mining and industrial developments are analysed. In addition, inter-relation among the variations in major climatic components (precipitation, temperature and humidity) are analysed through various time series methods. The analysis reveals a growing uncertainty and erratic nature of yearly and seasonal rainfall, accompanied by significant interregional variations. The monsoon rainfall has been declining significantly over the years, while the proportion of pre and post monsoon months' rainfall has been rising. Both maximum and minimum temperature has been increasing and trend rate of minimum temperature has been higher than that of maximum temperature and the rate is more during winter. There is uncertain variation in maximum-minimum difference of temperature over the years. Finally, significant cointegrated relation exists among all the climate variables.
Graph machine learning framework for depicting wavefunction on interface

The wavefunction, as the basic hypothesis of quantum mechanics, describes the motion of particles and plays a pivotal role in determining physical properties at the atomic scale. However, its conventional acquisition method, such as density functional theory, requires a considerable amount of calculation, which brings numerous problems to wide application. Here, we propose an algorithmic framework based on graph neural network to machine-learn the wavefunction of electrons. This framework primarily generates atomic features containing information about chemical environment and geometric structure and subsequently constructs a scalable distribution map. For the first time, the visualization of wavefunction of interface is realized by machine learning methods, bypassing complex calculation and obscure comprehension. In this way, we vividly illustrate quantum mechanics, which can inspire theoretical exploration. As an intriguing case to verify the ability of our method, a novel quantum confinement phenomenon on interfaces based on graphene nanoribbon is uncovered. We believe that the versatility of this framework paves the way for swiftly linking quantum physics and atom-level structures.
Morphometric Measurements of Red Foxes (Vulpes vulpes) in Somogy County, Hungary

The red fox (Vulpes vulpes) has the widest natural distribution of any terrestrial carnivore. Sexual dimorphism in this species is well known and is frequently observed in body and skull measurements. Morphological analysis is essential because the skull and body morphologies reflect many population/individual characteristics, genetic distances, environmental effects, and growth-affecting factors. Our study presents the first comprehensive analysis of red fox body and skull morphometry in Hungary. We performed morphometric measurements on 200 red foxes at two developmental stages, juvenile and adult, of different sexes, male and female, from Somogy County, Hungary, between January 2021 and January 2022. Statistical tests showed significant differences in all seven body measurements (body weight, total body length, tail length, head length, wither height, hind leg (left) length, and neck circumference of adult red foxes between the sexes, being significantly lower in the case of females than males. Significant differences were also found between the sexes in adult red fox skull measurements (total skull length, zygomatic width, and mandible length). In the case of juvenile red foxes, not all body dimensions differed significantly between the sexes (body weight, head length, and neck circumference did not differ significantly). We also found significant differences between the sexes in skull dimensions, except for zygomatic width. Regarding significant differences, the values for females were lower than those for males. Concerning the red foxes in Hungary, we found evidence of sexual dimorphism in all body and skull measurements in adult red foxes, which were larger in males, but not in all of the dimensions in juveniles.
Millimeter-Wave ME-Dipole Array Antenna Decoupling Using a Novel Metasurface Structure

A novel customized <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-shaped split-ring resonator metasurface arranged in two configurations is presented to decouple <inline-formula> <tex-math notation="LaTeX">$1\times 2$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$1\times 4$ </tex-math></inline-formula> Millimeter-Wave (MMW) Magneto-Electric (ME) Dipole in the H-Plane with 1.6 mm (<inline-formula> <tex-math notation="LaTeX">$0.32\lambda $ </tex-math></inline-formula> at 60 GHz) inter-element spacing. The metamaterial unit cell is first designed to inhibit the propagation of coupled surface waves within the bandwidth of interest. A <inline-formula> <tex-math notation="LaTeX">$5\times 2$ </tex-math></inline-formula> arrangement of this unit cell is carefully positioned on the top and bottom of the superstrate with 1 mm spacing (<inline-formula> <tex-math notation="LaTeX">$0.2\lambda $ </tex-math></inline-formula> at 60 GHz) between the antenna and the superstrate. In the <inline-formula> <tex-math notation="LaTeX">$1\times 2$ </tex-math></inline-formula> array, a maximum measured mutual coupling reduction of 53 dB is observed within the 52–66 GHz bandwidth (23.7%). To further demonstrate the uniqueness of the metasurface, an <inline-formula> <tex-math notation="LaTeX">$11\times 2$ </tex-math></inline-formula> configuration of this unit cell is arranged as a superstrate for the <inline-formula> <tex-math notation="LaTeX">$1\times 4$ </tex-math></inline-formula> ME-dipoles. A maximum measured mutual coupling reduction of 40 dB is achieved without a considerable effect on the radiation characteristics. Parametric analysis is performed to confirm the uniqueness of this new decoupling structure. The proposed antenna exhibits measured high total efficiency (>89%), high gain (>8 dB), low envelope correlation coefficient (<inline-formula> <tex-math notation="LaTeX">$ < 0.0003$ </tex-math></inline-formula>), and very good radiation characteristics throughout the entire bandwidth. The fabricated prototype antenna is measured to validate the simulation results. The proposed antenna is a good recommendation for V-band millimeter-wave MIMO applications like radar research.
Cracked Tongue Extraction Model Based on Improved U-Net Method

Tongue diagnosis holds significant importance in Traditional Chinese Medicine (TCM), with cracked tongues serving as a key diagnostic feature. However, the considerable variability in the morphology, depth, and distribution of tongue cracks poses a challenge for accurate extraction. In this paper, a novel deep learning approach is proposed to enhance the decoder of the U-Net model for cracked tongue extraction by incorporating the Hybrid Parallel Attention Mechanism (HPAM). The inclusion of HPAM enables the model to better concentrate on the small-scale feature information of tongue cracks, thereby improving the accuracy of crack segmentation. Experimental results demonstrate the effectiveness of the proposed method across all three tongue crack datasets. The method achieves a MIoU of 69.31% on the open environment dataset, 76.05% MIoU on the non-open environment dataset, and an overall MIoU of 76.92% on the combined dataset. These results signify a significant improvement over existing methods. This study not only offers an effective approach for automating the extraction of cracked tongues but also contributes to the automation and accuracy of tongue diagnosis, thereby benefiting the field of TCM.
Seeking Womanist-Liberation: Using Testimonios to Drive Anti-Racism in Psychology

Abstract Eighty-six percent of psychologists are white, leading to implicit and explicit discrepancies, exclusion, and discrimination against people of color in the discipline. Additionally, academia tends to center white, Eurocentric, and male narratives and experiences in psychology which perpetuates oppression of marginalized communities, especially women of color, in psychology. Thus, in this article, we propose a womanist-liberation framework to support radical healing of women of color in psychology and, ultimately, growth of the discipline. We share reflexive narratives called testimonios to describe our experiences as women of color in academia, in the hopes of encouraging reflection, developing insight, cultivating compassion, and inciting social justice action amongst our readers. Lastly, we propose recommendations stemming from a womanist-liberation framework to make psychology more inclusive, responsive, attuned, and liberatory toward the experiences of women of color.
An Overconfident Market Environment - A Place for Irrational Noise Trading

: Compared to developed foreign capital markets, the Chinese A-share market is not always efficient. In most cases, noise trading by investors using misinformation does not generate excess returns for them and can even lead to losses. However, in somewhat overconfident market environments such as the one studied in this paper, noise trading can lead to positive returns in a bull market that develops after the end of a bear market with persistent pessimistic market sentiment starting with a major short-term negative event. This paper selects the time period that fits the above description, combines the theoretical basis of behavioral finance, analyses and compares the performance of investment agents with different noise levels in general and specific market environments, and analyses the correlation between overall market noise trading risk and excess returns in different market environments through regressions, finally concluding that the additional noise trading risk borne by investors in an overconfident market environment risk can earn them excess returns.
Seasonal forecast skill of Arctic sea ice area in a dynamical forecast system

We assess the seasonal forecast skill of pan‐Arctic sea ice area in a dynamical forecast system that includes interactive atmosphere, ocean, and sea ice components. Forecast skill is quantified by the correlation skill score computed from 12 month ensemble forecasts initialized in each month between January 1979 to December 2009. We find that forecast skill is substantial for all lead times and predicted seasons except spring but is mainly due to the strong downward trend in observations for lead times of about 4 months and longer. Skill is higher when evaluated against an observation‐based dataset with larger trends. The forecast skill when linear trends are removed from the forecasts and verifying observations is small and generally not statistically significant at lead times greater than 2 to 3 months, except for January/February when forecast skill is moderately high up to an 11 month lead time. For short lead times, high trend‐independent forecast skill is found for October, while low skill is found for November/December. This is consistent with the seasonal variation of observed lag correlations. For most predicted months and lead times, trend‐independent forecast skill exceeds that of an anomaly persistence forecast, highlighting the potential for dynamical forecast systems to provide valuable seasonal predictions of Arctic sea ice.
Crustal structure in southeastern Egypt: Symmetric thinning of the northern Red Sea rifted margins

Crustal structure in southeastern Egypt has been investigated to elucidate the nature of crustal thinning across the northern Red Sea. P-wave receiver function modeling for 7 stations in southeastern Egypt yields typical Proterozoic crustal thicknesses of 35–38 km around Lake Aswan, and thinner crust (25–26 km) within 50 km of the Red Sea coast. The Vp/Vs ratios are on average 1.78 and indicate an intermediate-composition crust. These results, when combined with other estimates of crustal thickness in the region, reveal a symmetric pattern of crustal thickness beneath the conjugate margins of the northern Red Sea. Such a pattern is consistent with a pure shear model of extension, and suggests that the greater amounts of uplift and volcanism on the eastern side of the Red Sea compared to the western side may be the result of deeper flow in the mantle associated with the African superplume and not a direct consequence of the rifting process.