Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevention of Seabed Subsidence of Class-1 Gas Hydrate Deposits via CO2-EGR: A Numerical Study with Coupled Geomechanics-Hydrate Reaction-Multiphase Fluid Flow Model

The geomechanics effects and seabed subsidence are critical issues that should be considered in the development of a hydrate reservoir. The purpose of this study is to couple the geomechanics, hydrate reaction, and multiphase fluid flow modules to investigate the feasibility of CO2 enhanced gas recovery (CO2-EGR) of a Class-1 hydrate deposit by observing the formation deformation, and the seabed subsidence. The production methods of depressurization and CO2-EGR are modeled, respectively. The production behaviors and seabed subsidence of different production methods are compared. The positive influence on the gas recovery for a Class-1 hydrate deposit via CO2-EGR is observed. The calculations of seabed subsidence showed a significant improvement can be achieved when CO2-EGR was used. The subsidence is only 6.8% of that from the pure depressurization in the case of a pressure drop of 30%. The effects of production pressure drop and production gas rate are investigated. The association between the gas production and the pressure drop of the well is different from the cases of pure depressurization and the CO2-EGR. The appropriate initial time for the CO2 injection is tested. Slighter seabed subsidence is observed when the CO2 injection is initiated earlier. The case of different injection pressure control showed that a lower injection pressure leads to a heavier seabed subsidence. A higher CO2 fraction allowed in the produced gas stream results in a higher cumulative gas production, but there is no significant impact on the seabed subsidence.
Precarious Childhoods: Childhood Family Income Volatility and Mental Health in Early Adulthood

Abstract:The rise of income volatility in western countries has been extensively documented in the literature, but empirical research has just started to examine how childhood exposure to family income volatility affects subsequent wellbeing. This study takes advantage of several nation-wide, population registers from Sweden with linkages within and across generations to examine the intergenerational impact of childhood family income volatility on psychiatric disorders in early adulthood. In addition to the population-average effects, we also examine the heterogeneity in the impact of family income volatility for families at the top, bottom, and middle of the family income distribution. Our results suggest that after controlling for a set of family- and child-level characteristics, childhood family income volatility has a negative effect on mental wellbeing, and this finding is consistent across a range of psychiatric outcomes. Furthermore, we show that while children from low-income families exhibit the greatest likelihood of psychiatric disorder, children from families in the middle of the income distribution experience the greatest negative impact of income volatility.
Estimation of regional sheep abundance based on group sizes

We used sightability models with aerial counts to estimate regional abundance of desert bighorn sheep (Ovis canadensis) in southwestern Arizona during 1992–2012. Because of incomplete spatial and temporal coverage of surveys, we integrated sightability estimates using Bayesian state-space models. Although some game management units (GMUs) exhibited negative average growth rates during this period, temporal variability in growth was large. The combination of temporal variability and statistical uncertainty in the sightability estimates led to the selection of a regional model having zero mean growth from initial abundance. Hence, the model indicated a relatively stable population of desert bighorn sheep in southern Arizona, beginning with approximately 2,900 bighorn sheep in 1992 to the current number of approximately 2,300 sheep (2012). Our method provides statistically valid estimates of overall regional abundance not otherwise possible given the incomplete spatial coverage of surveys. Additionally, results have implications for other studies, common in wildlife management, where managers seek to integrate information across surveys with partial time-series. © 2014 The Wildlife Society.
Honeybees and other Insect Pollinators of Cultivated Plants: A Review

Insects are viewed from the harmful perspectives and aimed at killing them through several means including indiscriminate use of deadly chemicals. If good judgment made keeping views on sustainable crop production, natural balance and pollution free environment, they are important component of the ecosystem and their beneficial aspects are immense. One of them is that insects provide pollination service to plants. The study showed that over 50 species of insects visited flowers of 17 different species of selected crops during flowering periods. The visiting preferences of insects to flowers of different crops differed among the crop species and insect species as well. In fact, of the total pollination activities, over 80% is performed by insects and bees contribute nearly 80% of the total insect pollination, and therefore, they are considered the best pollinators. The manmade agro-ecosystem exerted pressure and forced to decline pollinators and their diversity, which resulted in reduced agricultural productivity again threatening biodiversity. Management of wide diversities of honeybees and other beneficial insects and flowering plant species occurring in Nepal help to maintain diversity of flora and bee fauna, pollination and reward hive products in the service of mankind. This paper covers honeybees and other insect species visiting various crop flowers. Key words : Pollination, honeybees, insect, flower visitors J. Inst. Agric. Anim. Sci. 27:1-23 (2006)
Glyphosate Plus Carboxylic Compounds Boost Activity of Free Radical-Scavenging Enzymes in Sugarcane

Drought, heat, and salinity, as well as pests, are stressing agents, which have impressively declined the productivity and quality of sugarcane crop in harsh environments. Our study aimed to examine the effect of various chemical ripeners as alternatives to enhancing the reactiveness of the enzymatic antioxidant system of sugarcane crop. The field experiment consisted of spraying the ingredients, ethephon, ethyl-trinexapac, glyphosate, carboxylic compounds (MTD) and methyl-sulfumeturon on the Brazilian commercial varieties, SP80-1842 and SP80-3280, before flowering stage. The enzymatic assay comprised the monitoring of the rate of degradation of free radical by ascorbate peroxidase (APX), catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD) in the extract from leaves of 11-month-old plants. Spraying glyphosate at 0.15 L ha−1 with MTD at 1.00 L ha−1 provided the highest activity of CAT, 0.65 µmol H2O2 min−1 mg−1 protein, in variety SP80-1842 Spraying glyphosate at 0.15 L ha−1 with ethephon at 0.33 L ha−1 caused the highest activity of APX, 1.70 nmol ascorbate min−1 mg−1 protein, in variety SP80-3280. The conclusion is, therefore, that mixtures of glyphosate with the insecticide/acaricide, MTD, and with the synthetic ethylene-releasing product, ethephon could help sugarcane crop grow adequately under uncontrollable or unpredictable agroecosystems like marginal lands.
Field-Programmable System-on-Chip-Based Control System for Real-Time Distortion Correction in Optical Imaging

The digital transition requires real-time control of complex systems with short loop time and low latency in various applications. Field-programmable gate arrays (FPGAs) are, in principle, capable of complying with this task but demand, on the other hand, a high programming effort. In this article, we propose a field-programmable system on chip (FPSoC) as a hybrid solution of an FPGA and a central processing unit (CPU) on a single monolithic die to combine the strengths of both architectures. An FPSoC-based adaptive optical wavefront correction system is presented as a case study to correct camera images in real time that are distorted by time-varying aberrations. While a short total loop time is achieved by interfacing the camera and a deformable mirror on a low level directly with the FPGA, all computationally nonintensive tasks are implemented on the CPU to keep the flexibility, reusability, and development expense low. The system corrects the optical distortion of water surface waves with up to 3600 control cycles per second and spatially attenuates the distortion up to Zernike polynomial 14 with up to 150 Hz. The FPSoC system enables fast spatiotemporal aberration correction in technical processes and offers a perspective for measuring complex flows through fluctuating interfaces.
A 33-ppm/°C 240-nW 40-nm CMOS Wakeup Timer Based on a Bang-Bang Digital-Intensive Frequency-Locked-Loop for IoT Applications

This paper presents a wakeup timer in 40-nm CMOS for Internet-of-Things (IoT) applications based on a bang-bang Digital-intensive Frequency-Locked Loop (DFLL). A self-biased <inline-formula> <tex-math notation="LaTeX">$\Sigma \Delta $ </tex-math></inline-formula> Digitally Controlled Oscillator (DCO) is locked to an RC time constant via a feedback loop consisting of a single-bit chopped comparator and a digital loop filter, thus maximizing the use of digital circuits while keeping only the RC network and the comparator as the sole analog blocks. Analysis and behavior level simulations of the DFLL have been carried out to guide the optimization of the long-term stability and frequency accuracy of the timer. High frequency accuracy and a <inline-formula> <tex-math notation="LaTeX">$10\times $ </tex-math></inline-formula> enhancement of long-term stability is achieved by the adoption of chopping to reduce the effect of comparator offset and 1/f noise and by the use of <inline-formula> <tex-math notation="LaTeX">$\Sigma \Delta $ </tex-math></inline-formula> modulation to improve the DCO resolution. Such highly digitized architecture fully exploits the advantages of advanced CMOS processes, thus enabling operation down to 0.7 V and a small area (0.07 mm<sup>2</sup>). The proposed timer achieves the excellent energy efficiency (0.57 pJ/cycle at 417 kHz at 0.8-V supply) over prior art while keeping excellent on-par long-term stability (Allan deviation floor < 20 ppm) and temperature stability (33 ppm°Cat 0.8-V supply).
An Unsupervised Retinal Vessel Extraction and Segmentation Method Based On a Tube Marked Point Process Model

Retinal vessel extraction and segmentation is essential for supporting diagnosis of eye-related diseases. In recent years, deep learning has been applied to vessel segmentation and achieved excellent performance. However, these supervised methods require accurate hand-labeled training data, which may not be available. In this paper, we propose an unsupervised segmentation method based on our previous connected tube marked point process (MPP) model. The vessel network is extracted by the connected-tube MPP model first. Then a new tube-based segmentation method is applied to the extracted tubes. We test this method on STARE and DRIVE databases and the results show that not only do we extract the retina vessel network accurately, but we also achieve high G-means score for vessel segmentation, without using labeled training data.
Model-Driven Testing in Umple

classes are meant to define properties of a particular entity without allowing the user to directly instantiate the entity [76]. The rationale behind using abstract classes is to introduce reusability of elements and reduce redundancy of attributes and other features. Umple supports ‘abstract’ classes by allowing the use to declare any Umple class as ‘abstract’.
IκB Family Members Function by Different Mechanisms*

The IκB family of proteins regulates NF-κB-dependent transcription by inhibiting DNA binding and localizing these factors to the cell cytoplasm. IκBα does this by shifting the balance between nuclear import of Rel proteins and their export from the nucleus. Here we show that, unlike IκBα, IκBβ and IκBε appear to sequester p65 or c-Rel in the cytoplasm by inhibiting nuclear import. Furthermore, because IκBβ does not undergo nucleocytoplasmic shuttling, it cannot remove nuclear proteins like IκBα does. We conclude that the mechanism of action differs among IκB family members.
Routing Schemes in Software-Defined Vehicular Networks: Design, Open Issues and Challenges

Software-defined vehicular networks (SDVN) is a promising technology to overcome the limitations of current vehicular networking. However, existing vehicular routing schemes are not equipped to handle communication in SDVNs. In addition, routing schemes in SDVNs, in general, has been lightly addressed in the literature to well compute the flow tables. To fill this gap, this article explores the potential of SDVNs from the aspect of routing and studies the design principles of routing schemes in SDVNs and classifies the current routing solutions based on different criteria. SDVN routing schemes are then compared through comprehensive analysis, and key open issues and opportunities for future research directions are discussed.
Influence of β1 Integrin Intracytoplasmic Domains in the Regulation of VLA-4-Mediated Adhesion of Human T Cells to VCAM-1 under Flow Conditions1

The VLA-4 integrin supports static cell-cell, cell-matrix adhesion, and dynamic interactions with VCAM-1. Although functions for well-conserved β1 integrin cytoplasmic domains in regulating static cell adhesion has been established, the molecular basis for β1 integrin-dependent arrest on VCAM-1 under flow conditions remains poorly understood. We have transfected the β1 integrin-deficient A1 Jurkat T cell line with β1 cDNA constructs with deletions of the NPXY motifs and specific mutations of tyrosine residues. Deletion of either NPXY motif impaired static adhesion induced by CD2 or CD47 triggering or direct β1 integrin stimulation. In contrast, PMA-induced adhesion to VCAM-1 was unaffected by deletion of the NPIY motif and only slightly impaired by deletion of NPKY. Moreover, deletion of the NPIY motif resulted in enhanced rolling and reduced arrest on VCAM-1 under shear flow conditions. In contrast, deletion of the NPKY motif did not alter arrest under flow. Although tyrosine to phenylalanine substitutions within two NPXY motifs did not alter static adhesion to VCAM-1, these mutations enhanced arrest on VCAM-1 under flow conditions. Furthermore, although deletion of the C′-terminal 5 AA of the β1 cytoplasmic domain dramatically impaired activation-dependent static adhesion, it did not impair arrest on VCAM-1 under flow conditions. Thus, our results demonstrate distinct structural requirements for VLA-4 function under static and shear flow conditions. This may be relevant for VLA-4 activity regulation in different anatomic compartments, such as when circulating cells arrest on inflamed endothelium under shear flow and when resident cells in bone marrow interact with VCAM-1- positive stromal cells.
Study on Two Component Gas Transport in Nanopores for Enhanced Shale Gas Recovery by Using Carbon Dioxide Injection

Injecting carbon dioxide to enhance shale gas recovery (CO2-EGR) is a useful technique that has raised great research interests. Clear understanding of the two-component gas transport mechanisms in shale nanopores is the foundation for the efficient development of shale gas reservoir (SGR) and also the long-term geological storage of CO2. Although extensive studies on single-component gas transport and corresponding models in shale nanopores have been carried out in recent years, limited studies have been conducted on two-component or even multi-component gas transport models in shale nanopores. In this work, the shale nanopores were classified into inorganic and organic nanopores. The corresponding models for two-component gas transport were constructed. Mechanisms including Knudsen diffusion, slip flow, viscous flow, and molecular diffusion are considered in the inorganic pores. In the organic pores, due to existence of adsorption gas, surface diffusion is further considered besides the aforementioned mechanisms. Effects of pressure, temperature, fraction of organic nanopores, and gas concentration were analyzed. Results show that gas apparent permeability is negatively correlated with pressure, and positively correlated with temperature and organic nanopore fraction. As the concentration of CH4 decreases, the apparent permeability of CH4 increases continuously, while the apparent permeability of CO2 decreases. The permeability ratio of CH4 in the total permeability is negatively correlated with pressure and gas concentration ratio. Additionally, the contribution of transport mechanisms to the total gas apparent permeability has been analyzed. It is found that the surface diffusion contributes up to 5.68% to gas apparent permeability under high pressure. The contribution of molecular diffusion can reach up to 88.83% in mesopores under low pressure. Under high pressure and macropores, it contributes less than 1.41%. For all situations, the contribution of viscous flow is more than 46.36%, and its contribution can reach up to 86.07%. Results of this study not only can improve the understanding of two-component gas transport in nanochannels, but also can lay the foundation for more reliable reservoir simulation of CO2-EGR.
Motivation of students to study a tourism programme in India

ABSTRACT Every year thousands of students enrol in tourism and hospitality management courses to make a career in the tourism industry. The issue, why students study tourism and hospitality programme is still under-researched. The present study investigates the motivations of students to pursue a tourism and hospitality management course at the post-graduation level. The study was conducted during the year 2017–2019 on a cohort of 758 students from 30 universities in India. The present study reports the key factors explaining students’ motivations and discuss their relevance in the tourism education scenario.
Spatial variations of litterfall silicon flux and plant-available silicon in highly weathered soil in a lowland mixed dipterocarp forest of Lambir Hills National Park in Borneo

Tropical forest trees take up silicon (Si) and return it to the forest ﬂoor via leaf litterfall. Our objective was to explore to what extent litter Si ﬂux and Si availability from the soil are spatially coupled. We examined these relationships within a 4-ha area of lowland mixed dipterocarp forest of Lambir Hills National Park in Borneo. Using leaf litter samples collected with litter traps, we found that Si concentration and ﬂux of leaf litter ranged 2 - 23 mg Si g − 1 and 0.8 - 13.1 g Si m − 2 yr − 1 , respectively, whereas water-extractable Si from 0 - 10 cm deep soil ranged from 5.9 to 24.5 mg kg − 1 (0.7 to 3.0 g Si m − 2 ) at 80 litter trap locations. There was no signiﬁcant correlation among these three aspects of Si cycling via trees. Water-extractable soil Si from three 95 cm deep cores showed no signiﬁcant change with depth, whereas in-situ measurements with six tension lysimeters showed higher soil-water Si concentration in the upper soil layer (0 - 5 cm depth). These results suggest that spatial variations of Si concentration and ﬂux in leaf litter do not reﬂect those of soil Si availability, but are modulated by distribution of tree species that differ in Si uptake. Si returned to the soil via leaf litter did not show strong spatial signals probably because solubility of Si from dead leaves differs among species. At the stand level, our results are consistent with the perspective that litter Si input enriches plant-available Si pool in the upper soil horizons in tropical forests.
Vulnerability analyses in forests using AHP in a GIS environment

Vulnerability, which is one of the criteria used in the preparation of the World Risk Index, is the measure of the damage and loss that a community or structure can suffer when a hazard occurs. In this research, a region with a high fire hazard was selected, and a model was created to determine the extent to which spatial objects (assets) could be damaged when the expected danger occurs in the selected region, using AHP in a GIS environment. Since GIS-based AHP analysis is based on the comparison of different layers with each other and determining the weight values of the layers, the Terrestrial Measurement, Photogrammetry and Remote Sensing techniques, which are used as data sources in the evaluation of spatial data, are also discussed in the study.
Automatic Segmentation of Microaneurysm in Retinal Fundus Images

Diabetes interferes with the body’s ability to use and store sugar (glucose), which it can cause damage throughout the body. Generally, Microaneurysm (MA) is the first clinically observable lesions in the Diabetic Retinopathy (DR). Since interference of biological objects in eye fundus images are similar to MA, locate Microaneurysm lesions precisely is a challenging task for researches. This research employs U-Net Convolutional Neural Network to model saliency of objects in images, global and local context are both taken into account to provide a better initialization for the process. Feature extraction techniques are applied first to assign a local saliency value to each pixel by considering its local context from fundus images such as ORB, SURF, and MSER. The extracted feature vectors are applied for training the network. The sum of the weighted salient object regions produce the final saliency map, then implements U-Net to segment MA lesions.Our experiment has carried out using the publicly available Indian Diabetic Retinopathy Image Dataset (IDRiD), which has used in "Diabetic Retinopathy: Segmentation and Grading Challenge" workshop and our proposed method has given an outstanding accuracy of 98.78 %.
Estimation of Biomass Enzymatic Hydrolysis State in Stirred Tank Reactor through Moving Horizon Algorithms with Fixed and Dynamic Fuzzy Weights

Second generation ethanol faces challenges before profitable implementation. Biomass hydrolysis is one of the bottlenecks, especially when this process occurs at high solids loading and with enzymatic catalysts. Under this setting, kinetic modeling and reaction monitoring are hindered due to the conditions of the medium, while increasing the mixing power. An algorithm that addresses these challenges might improve the reactor performance. In this work, a soft sensor that is based on agitation power measurements that uses an Artificial Neural Network (ANN) as an internal model is proposed in order to predict free carbohydrates concentrations. The developed soft sensor is used in a Moving Horizon Estimator (MHE) algorithm to improve the prediction of state variables during biomass hydrolysis. The algorithm is developed and used for batch and fed-batch hydrolysis experimental runs. An alteration of the classical MHE is proposed for improving prediction, using a novel fuzzy rule to alter the filter weights online. This alteration improved the prediction when compared to the original MHE in both training data sets (tracking error decreased 13%) and in test data sets, where the error reduction obtained is 44%.
Capacities for the Development of Creative Capital in Lithuanian Counties

The concept of a creative class was introduced by Richard Florida in 2002 in his book The Rise of the Creative Class. The creative class consists of people involved in occupations recognised as inventive. This study is designed to identify capacities for the development of creative capital in the counties of Lithuania. Florida’s methodology for his creative model refers to the three powers of talent, technology and tolerance, which are determinants of development. The present assessment is based on generally available data acquired from the Statistical Yearbook of Lithuania. It takes into account information related to all the counties of the Republic of Lithuania. The accumulated data described are, at a relative level, the areas of talent, tolerance, technology and cultural amenities.