Miracle-dz/UniFAR-FTUs huggingface dataset:
Characteristics and influencing factors of movable fluid in ultra-low permeability sandstone reservoir

The sandstone samples of the ultra-low permeability reservoir in Yanchang Formation of Ordos Basin were tested with the nuclear magnetic resonance technique.The porosity parameter was defined to analyze the characteristics and the influencing factors of movable fluid.The existing characteristics of movable fluid include the following aspects: The amplitude of T2 spectrum is relatively low,and the content of movable fluid is also low.The parameters of movable fluid is expanse and the heterogeneity is intense.The relation between the movable fluid parameter and the permeability gets better with the increase of permeability.The movable fluid parameter gets higher attenuation velocity with decrease of permeability and has more sensitivity to the changes of permeability.The micro-pore structure determines the existing state of fluid.The main influencing factors of the movable fluid include micro-fracture,filling degree of clay mineral in pores,secondary porosity and recrystallization.
Discontinuous Galerkin Method in Frequency-space Domain for Wave Propagation in 2D Heterogeneous Porous Media

Wave propagation in heterogenous two dimensions porous media plays an important role for subsurface investigation. We consider solving dynamic wave propagation using discontinuous Galerkin method in frequency domain. This frequential approach allows us to take into account efficiently diffusive phenomena at the source and at any discontinuities including the free surface, related to Biot theory on porous medium. The propagation code is validated on simple cases with a reflectivity code which is working in wavenumber-frequency domain for stratified media. The frequency formulation better controls the energy balance at interfaces due to fluid/solid interactions. The main perspectives is focused on time differential imaging by full waveform techniques in porous media.
Abundance and distribution of the Panama brief squid, Lolliguncula panamensis (Teuthida: Loliginidae), in the Gulf of California Abundancia y distribución del calamar dedal, Lolliguncula panamensis (Teuthida: Loliginidae), en el golfo de California

This study examines the abundance and distribution of Panama brief squid (Lolliguncula panamensis) caught during 15 fishery surveys in the Gulf of California in 2003-2006 and 2008. A total of 2460 individuals were captured in 66 positive squid trawls. Based on the seasonal sea surface temperature pattern, captured individuals were grouped into two periods: cold (<22 oC: December, January, February, March, and April 2003-2006 and 2008) and warm (≥22 oC: May, June, July, August, September, October, and November 2003-2006 and 2008). During the cold period, 1579 organisms were sampled, and during the warm period, 881. Abundance by sex showed that females were more abundant during both periods (62% cold, 57% warm) than males (17% cold, 12% warm). During both periods, females (99.6% cold, 91.0% warm) as well as males (99.3% cold, 95.3% warm) presented reproductive activity (maturing and mature stages), and they were captured at depths between 7 and 40 m. The highest abundances occurred in diurnal trawls at an average depth of 40 m during the cold period and 24 m during the warm period.
Kinodynamic Motion Planning via Branch-and-Cut Over Probabilistic Roadmaps

This letter describes an extension of the classic Lazy Probabilistic Roadmaps algorithm (Lazy PRM), which results from pairing PRM and a novel Branch-and-Cut (BC) algorithm. Cuts are dynamically generated constraints that are imposed on minimum cost paths over the geometric graphs selected by PRM. Cuts eliminate paths that cannot be mapped into smooth plans that satisfy suitably defined geometric and differential constraints. We generate candidate smooth plans by fitting splines to vertices in a minimum-cost path. Plans are validated with a recently proposed algorithm that maps them into finite traces, without the need to choose a fixed discretization step. A trace records the exact sequence of constraint boundaries crossed by the plan, modulo arithmetic precision. We evaluate several planners using our methods over the recently proposed BARN benchmark, reporting evidence of the scalability of our approach.
Reducing Autocorrelation Effect in the Control Chart for PM10 Curves

—The traditional control chart for industry often requires identical and independent (i.i.d) assumptions. Thus, some modification on the control chart used in the industry need to be done before it can be used in the environmental application due to the difference in the nature of the data. The recorded environmental data are usually multivariate, correlated, and non-stationary and can be expressed as a function of time. In this present study, a control chart for monitoring curves data is to be applied where the hourly recorded data within a one day period is treated as multivariate point data and the occurrence is treated as a function of time. The control chart is constructed using the Functional Principal Component Analysis (FPCA) model. In the monitoring of quality indices overtime, autocorrelated data often negatively affects the performance of a control chart resulting into increase in the number of false alarm. Data pre-whitening approach is proposed during the monitoring phase of analysis to tackle the problem of data autocorrelation. Based on the seven years (2004-2010) recorded data from the Shah Alam air quality monitoring station which is located in the Selangor state of Peninsular Malaysia, after data pre-whitening has been conducted, the analysis results have shown that the false alarm rate in the control chart for the PM10 indices has reduced and the existence of lag 1 autocorrelation AR(1) effect is found insignificant. Thus, it is indicated that the employment of data pre-whitening approach able to improve the control chart performance.
Impact of COVID-19 restrictions on health and well-being in the United Arab Emirates

Background Restrictions during the COVID-19 pandemic are thought to have impacted both the physical health and well-being of individuals where lockdown was applied. The United Arab Emirates (UAE) was one of the leading countries in implementing the international guidelines to limit the intensely contagious nature of the outbreak. Aim To identify the impact of COVID-19 on changes to exercise and general physical activity habits, changes to the consumption of various foods and potential weight gain, as well as any differences in smoking habits among individuals residing in the UAE during the COVID-19 quarantine. Methods This is a cross-sectional analytical study that used a quantitative electronic questionnaire sent by the Ministry of Health and Prevention to individuals on its platform in order to collect data on the physical health and well-being of a UAE sample population. A total of 2,362 responses were received to specific questions on physical activity, eating habits, and tobacco use for the period before, during, and after the COVID-19 lockdown. Descriptive statistical analysis was used to display the sample’s demographic data and the changes in physical health and well-being. Paired t-test was used to show the changes in dietary habits. Results This study reveals concerning changes in health risk behaviors during the COVID-19 lockdown in the UAE. Physical activity levels declined across mild, moderate and vigorous ranges in most participants. Alarmingly, sedentary behavior dramatically increased with 71% of participants spending an average of 4–8 h per day sitting and over 54% of participants spending more than 4 h watching TV on an average day during lockdown. Fast-food consumption and snacking rose, hence weight gain was observed in over 53% of participants. Smoking habits, especially among cigarette smokers, may have worsened, with 45.2% reporting an increase in cigarette smoking, 16.8% declaring an increase in shisha smoking and 35.3% reporting an increase in smoking other tobacco products. These unfavorable behaviors during confinement could have serious long-term health consequences. Conclusion This study demonstrates that long periods of home quarantine may have led to unhealthy consequences that increase the risk of developing disease. This study therefore aims to highlight these health impacts, and recommend strategies and policies that can encourage healthy habits.
A 480 mVpp Linear Input Range, Low Noise Transconductance Cell for Multi-Input Sensor Interface

This brief proposes a high-linear transconductance cell based on parallel source degeneration and differential flipped voltage followers (FVFs) with balance resistors. The prototype is implemented in a 180 nm BCD process, occupying a core area of 0.0298 mm2. Experimental result shows that the 1% total harmonic distortion (THD) linear input range is up to 480 mVpp with a 1.8 V voltage supply. The noise floor is 80.53 nV/<inline-formula> <tex-math notation="LaTeX">$\sqrt {\mathbf {Hz}}$ </tex-math></inline-formula>, and the integrated noise is 8.69 <inline-formula> <tex-math notation="LaTeX">$\mu \text{V}_{\mathrm {rms}}$ </tex-math></inline-formula> within the bandwidth of 0.3-10 kHz. The proposed transconductance cell is applied to a multi-input sensor interface based on frequency division multiplexing (FDM), demonstrating its effectiveness and versatility in practical applications.
“Black Women Saved my Life”: A Case Study on Healing Intersectional Racial Trauma

Abstract The painful consequences of intersectional racial trauma on the mental health of Black women have been examined in the existing literature. However, limited research explicates how to assess, conceptualize, and treat intersectional racial trauma in clinical practice. Practicing psychologists seeking to integrate science and practice for mental health and social justice breakthroughs desire innovative clinical models to facilitate this work. This paper presents a case study of a week-long, intensive teletherapy retreat to treat the intersectional racial trauma of a queer, middle-aged, Black cisgender woman. We detail theories and research regarding racial trauma and intersectionality and present the integrated How to Love a Human model. Then, we describe the client’s presenting concerns and how to assess and conceptualize intersectional racial trauma to inform a multifaceted, collectivistic treatment approach. Last, we chronologically overview each day of the retreat and address how our healing approach can serve as a research framework and clinical example to treat intersectional racial trauma among Black women. PUBLIC SIGNIFICANCE STATEMENT Racial trauma is a painful reality for many Black women, with other intersecting forms of oppression exacerbating the impact. This paper describes how four Black women provided therapy through an innovative, collectivist model for a queer Black woman experiencing intersectional racial trauma.
L'approche DARE pour une mesure de risque diversifiée

The objective of this paper is to provide a complete framework to aggregate different quantile and expectile models for obtaining more diversified Value-at-Risk and Expected Shortfall measures, by applying the diversification principle to model risk. Following Taylor (2008) and Gourieroux and Jasiak (2008), we introduce a new class of models called Dynamic AutoRegressive Expectiles (DARE). We first briefly present the main literature about VaR and ES estimations, and we secondly explain the DARE approach and how expectiles can be used to estimate quantile risk measures. We finally use the main validation tests to compare the DARE approach to other traditional methods for computing extreme risk measures on the French stock market
Video Based Depression Detection And Analysis

Depression is one of the most serious and frequent diagnosed mental disorders. It affects not only the sufferers but also their families, friends and even the society in general. With rapid advancements in Artificial Intelligence and Machine Learning, there have been some new developments that aim to predict the strength of depression in an individual by analyzing certain parameters extracted from their video sample. This paper discusses some of the new and most worthy of note researches in the domain of depression analysis and balance their different frameworks like CNNs, RNN, etc. and algorithms used. The strength of depression is identified by using the Beck Depression Inventory-II (BDI-II) that range from 0 to 63. The performance of all these models is compared based on the structure (architecture and algorithms) assume and based on the MAE & RMSE scores obtained after testing them on AVEC 2013 & AVEC 2014 datasets. Apart from the comparative analysis, this paper also discusses a couple of approaches that study some unconventional parameters that scientific analysis in the task of depression detection and prediction from video data.
Seal Failure Related to Basin-scale Processes

The leakage of trapped petroleum is a major concern in hydrocarbon exploration and has led to a large number of exploration failures. Changes in stress state, fluid pressure, and cap rock permeability may all result in a loss of trapped hydrocarbons. Such changes may result from several different subsurface processes. This chapter describes an examination of important processes that control compaction, fluid flow in reservoirs, fault reactivation, and their influence on leakage from hydrocarbon reservoirs. It was concluded that seal-failure analysis is seldom based on more than a few of the operating processes and therefore does not reach its full potential. Especially, the effects of overpressures on sediment compaction and hydrocarbon leakage seem to have been oversimplified and commonly overstated. The conditions for hydrofracturing and the corresponding loss of hydrocarbons from structural crests are also commonly considered too superficially in sealing analyses. It was concluded that inadequate leakage assessments can result from neglect of some subsurface processes that influence stress, pore pressure, and hydrocarbon permeability in the seal. Seal integrity predictions can be improved if thorough analyses of the relevant subsurface processes routinely precede the sealing analyses.
Study of correlation between the shear wave velocity and the liquefaction resistance of saturated sands

A new combined test apparatus is developed on torsion vibration principle, which can be used to measure shear-wave velocity and to determine cyclic liquefaction resistance of soil specimen simultaneously. The relation between the shear wave velocity and the cyclic liquefaction resistance is analyzed for a lot of undisturbed and remolded specimens of same kind of sand with same consolidation pressure, which are taken from more than 20 sites within the depth of 20 m under ground surface. The results show that the relation is good if the strain criterion for evaluating liquefaction is not larger than 6%.
Gender Related Educational Development Index (GEDI) of Kolkata Municipal Corporation (KMC) India

Literacy is an indispensable means to acquire skills for improving socio-economic development of well being. The present research paper is Gender Related Education Development Index of Kolkata Municipal Corporation which studies the gender disparity in literacy level in Kolkata Municipal Corporation. For this analysis GEDI or gender development index has been used. On the basis of GEDI value spatial and temporal analysis has done. Here census data of 2001 and 2011 of Kolkata Municipal Corporation have used for this analysis. In Kolkata Municipal Corporation there is a minimum change in GEDI value (2001 to 2011). In 2001 GEDI value was 0.75 and in 2011 it was 0.80 which shows the value is near to 1. It reflects a maximum achievement with perfect gender equality. The percentage of GEDI value changes is 6.67% which is low. The main objective of this study is to measure the gender differences in respect of education with the help of Gender Related Education Development Index at ward level of Kolkata Municipal Corporation.
Downregulation of Exosomal hsa-miR-551b-3p in Obesity and Its Link to Type 2 Diabetes Mellitus

Obesity is a significant risk factor for the development of type 2 diabetes mellitus (T2DM). Adipose tissue dysfunction can affect the pool of circulating exosomal miRNAs, driving concomitant disease in obesity. These exosomal miRNAs can reflect adipose tissue functionality, thus serving as prognostic biomarkers for disease monitoring in case of T2DM. In the present study, we conducted NanoString microRNA profiling of extracellular vesicles (EVs) secreted by adipose tissue of obese patients (body mass index (BMI) > 35) without T2DM and nonobese individuals (BMI < 30) as a control group. Functional and pathway enrichment analysis showed that miRNAs associated with obesity in this study were implicated in insulin signaling and insulin resistance biological pathways. Further, these microRNAs were screened in serum EVs in the following groups: (1) obese patients with T2DM, (2) obese patients without T2DM, and (3) nonobese individuals as a control group. has-miR-551b-3p was shown to be downregulated in adipose tissue EVs, as well as in serum EVs, of patients with obesity without T2DM. At the same time, the serum exosomal hsa-miR-551b-3p content was significantly higher in obese patients with T2DM when compared with obese patients without T2DM and may be a potential biomarker of T2DM development in obesity.
Qualitative classification and determining pollution sources of Iran's Talkherud river using multivariate statistical methods

This researchwas carried out for qualitative evaluation of Talkherud which is located in northwest Iran in East Azerbaijan Province. The sampling has been conducted on 13 physical and chemical parameters at eight stations within one year. The results obtained from the measurements were analyzed using multivariate cluster analysis (CA). With respect to the obtained results of cluster analysis, the studied stations were divided into three groups: (a) High Pollution(HP), (b) Middle Pollution(MP), and (c) Low Pollution (LP). The stations which were alike in amount of pollution fell into one group. This showed the difference in pollution sources and the amount of pollution in different regions of the river. The study of the differences between the mentioned groups shows, that in terms of assessed parameters, there is no significant difference between the stations in each cluster. While based on most assessment parameters, there was a significant difference among the clusters at the 5% and 1% probability levels. The total results of this study show the usefulness of multivariate statistical techniques in the interpretation of multiple datasets, qualitative evaluation of water, and the identification of pollution sources and causes.
DFC-UNet: A U-Net-Based Method for Road Extraction From Remote Sensing Images Using Densely Connected Features

Road extraction from high-resolution remote sensing images is a challenging task due to the presence of disturbing features and the diversity of road representations. To overcome these problems, deep neural networks-based methods have been recently used to improve the speed and accuracy of road extraction. In this letter, we propose a simple yet effective method for feature extraction with context fusion and self-learning sampling, which we call dual feature fusion (DFF). Moreover, we point out that the DFF method is functionally similar to the downsampling and upsampling structure. From this, we propose a network with a dense feature skip connect structure (DFC-UNet) to extract the roads from remote sensing images. The complexity of the high-dimensional features of the U-shaped structure is also analyzed, and the redundant features are suppressed through the equivalent replacement of the DFF block. Aiming at the unbalanced characteristics of samples and the topological characteristics of the road network, we then propose a comprehensive loss function based on dynamic weighting to strengthen the learning of the road network. Experimental results on the Massachusetts road dataset, the DeepGlobe dataset, and the CHN6_CUG dataset confirm the effectiveness of the proposed method.
Current understanding of pathogenetic mechanisms in neuroendocrine neoplasms

ABSTRACT Introduction Despite the fact that important advances in research on neuroendocrine neoplasms (NENs) have been made, consistent data about their pathogenetic mechanism are still lacking. Furthermore, different primary sites may recognize different pathogenetic mechanisms. Areas covered This review analyzes the possible biological and molecular mechanisms that may lead to NEN onset and progression in different organs. Through extensive research of the literature, risk factors including hypercholesterolemia, inflammatory bowel disease, chronic atrophic gastritis are evaluated as potential pathogenetic mechanisms. Consistent evidence is available regarding sporadic gastric NENs and MEN1 related duodenopancreatic NENs precursor lesions, and genetic-epigenetic mutations may play a pivotal role in tumor development and bone metastases onset. In lung neuroendocrine tumors (NETs), diffuse proliferation of neuroendocrine cells on the bronchial wall (DIPNECH) has been proposed as a premalignant lesion, while in lung neuroendocrine carcinoma nicotine and smoke could be responsible for carcinogenic processes. Also, rare primary NENs such as thymic (T-NENs) and Merkel cell carcinoma (MCC) have been analyzed, finding different possible pathogenetic mechanisms. Expert opinion New technologies in genomics and epigenomics are bringing new light to the pathogenetic landscape of NENs, but further studies are needed to improve both prevention and treatment in these heterogeneous neoplasms.
IMPACT OF MINERAL N AND P AND MANURE ON ARBUSCULAR MYCORRHIZAL FUNGI, OTHER SOIL MICROORGANISMS AND ON SOIL FUNCTIONALITY IN DIFFERENT AGROECOSYSTEMS

Microorganisms and their interactions in soil play a critical role in nutrient transformations and cycling, and in sustaining soil productivity. Arbuscular mycorrhizal fungi (AMF) are a keystone group of fungi influencing nutrient cycling. In turn, the activity and composition of microorganisms in soil are influenced by management practices such as the choice of crop species and fertilization. Long-term effects of cropping, manuring and mineral fertilization on the soil-plant system were defined in three selected agro-ecosystems of Canada. A greenhouse experiment was also conducted to define the involvement of AMF in organic residue decomposition and nitrogen (N) mineralization. In the greenhouse experiment, pasteurized soil was inoculated or not with a strain of Glomus claroideum, G. clarum or G. intraradices. N-labelled organic residue in a nylon mesh was buried in the soil. The fate of residue-N was determined after 24 weeks. Arbuscular mycorrhizal fungal species enhanced mineralization of organic residue to different degrees. The highest recovery of mineralized N by plants (25%) occurred when inoculated with G. clarum. The AMF enhanced N-mineralization differentially leading to differential plant growth stimulation, differences in the C-to-N ratio of the decomposing organic residue, and in soil microbial community structure. In a field trial conducted on a Brown Chernozemic soil at the Semiarid Prairies Agricultural Research Centre in Swift Current, SK, eight years of phosphorus (P) (0, 20 and 40 kg P2O5 ha) application to alfalfa monoculture and alfalfa-Russian wildrye (RWR) dual culture modified the soil microbial community structure. Low levels of phosphorus (0 and 20 kg P2O5 ha) fertilization in alfalfa-RWR dual culture increased