Rigorous Correlation Research Articles

Study on the Adaptability of 15 Oat Varieties in Different Ecological Regions

The planting of oat varieties is influenced by factors such as their inherent traits, ecological regional climate, altitude conditions, and resistance differences, resulting in a decrease in both forage yield and quality. It is crucial to carefully select appropriate oat varieties for different ecological regions in order to enhance forage yield and quality, thereby facilitating the advancement of the grass industry. The correlation between the indices and the relationship between the indices and varieties were investigated through rigorous correlation analysis and principal component analysis. By employing gray correlation analysis, the 21 indices were transformed into 15 independent comprehensive indices. Subsequently, based on a comprehensive analysis, oat varieties suitable for cultivation in different ecological regions were identified. In this study, fifteen domestic and foreign oat varieties were cultivated in the semi-arid region of Weiqi Town and the alpine region of Damaying Town in Shandan County throughout 2023. Among the yield traits, Everleaf 126 exhibited a significantly lower plant height while possessing the largest leaf area, the highest number of effective tillers, and achieving the highest hay and seed yields (p < 0.05), which were 13,199 kg/ha and 5136 kg/ha, respectively. The plant height of Longyan No.3 in Damaying Town was significantly higher than that of other varieties. This variety also demonstrated the highest number of effective tillers, along with the greatest hay yield (7783 kg/ha) and seed yield (5033 kg/ha). Among the evaluated quality traits, Everleaf 126 in Weiqi Town exhibited the highest leaf–stem ratio, crude protein content, and crude fat content (p < 0.05). In contrast, Mengshi in Damaying Town had the highest leaf–stem ratio, while Longyan No.3 demonstrated the highest levels of crude protein and crude fat content. Furthermore, Molasses displayed the highest soluble sugar content in both locations (p < 0.05). The resistance of 15 oat varieties to pests and diseases was found to be lower in Weiqi Town compared to Damaying Town. Notably, Everleaf 126 exhibited the highest resistance to powdery mildew, red leaf disease, leaf spot disease, and aphids among the varieties tested in Weiqi Town. In contrast, Longyan No.3 demonstrated superior resistance in Damaying Town. In conclusion, based on a comprehensive analysis of the gray correlation degree, in the semi-arid region, Everleaf 126 exhibited the most superior performance, followed by Molasses and Longyan No.3. In the alpine region, Longyan No. 3 demonstrated the highest overall performance, followed closely by Molasses and Mengshi. These varieties exhibit significant potential for promotion as high-yield, high-quality forage oats in semi-arid and alpine environments.

Applying the Sabatier Principle to Decipher the Surface-Structure-Dependent Catalysis of Different Starch Granules by Pullulanase.

Interfacial enzyme catalysis is widespread in both nature and industry. Granular starch is a sustainable and abundant raw material for which a rigorous correlation of the surface structure with enzymatic degradation is lacking. Here pullulanase-catalyzed debranching of 12 granular starches varying in amylopectin contents and branch chain contents and lengths is shown to present a biphasic relationship characteristic of the Sabatier principle. Introducing normalization of the specific rate (v 0/E 0) by a substrate-dependent constant C, related to the Arrhenius prefactor of k cat, reveals that optimal activity according to the Sabatier principle occurs at moderate substrate binding strength. The density of pullulanase attack sites (kinΓmax), determined using combined conventional and inverse Michaelis-Menten kinetics, was increased by branching enzyme treatment. Medium kinΓmax and branch chain length conferred the highest activity depending on substrate load. Correlation analysis demonstrated that starch granular crystallinity, surface order, and average branch chain length influence the enzymatic degradation by affecting the C constant. Therefore, C should be considered together with the enzyme binding strength to understand the degradation of starch granules. The Sabatier principle could serve as a diagnostic tool to characterize enzyme performance on substrates having different surface structures and guide rational modification of granular starches for specific purposes.

Experimental insights and modeling innovations: Deciphering Fe(VI) oxidation in imidazole ionic liquids through QSAR and RFR

In this investigation, we conducted a detailed analysis of the oxidation of 16 imidazole ionic liquid variants by Fe(VI) under uniform experimental setups, thereby securing a dataset of second-order reaction rate constants (kobs). This methodology ensures superior data consistency and comparability over traditional methods that amalgamate disparate data from varied studies. Utilizing 16 chemical structural parameters obtained via Density Functional Theory (DFT) as descriptors, we developed a Quantitative Structure Activity Relationship (QSAR) model. Through rigorous correlation analysis, Principal Component Analysis (PCA), Multiple Linear Regression (MLR), and Applicability Domain (AD) evaluation, we identified a pronounced negative correlation between the molecular orbital gap energy (Egap) and kobs. MLR analysis further underscored Egap as a pivotal predictive variable, with its lower values indicating heightened oxidative reactivity towards Fe(VI) in the ionic liquids, leading the QSAR model to achieve a predictive accuracy of 0.95. Furthermore, we integrated an advanced machine learning approach - Random Forest Regression (RFR), which adeptly highlighted the critical factors influencing the oxidation efficiency of imidazole ionic liquids by Fe(VI) through elaborate decision trees, feature importance assessment, Recursive Feature Elimination (RFE), and cross-validation strategies. The RFR model demonstrated a remarkable predictive performance of 0.98. Both QSAR and RFR models pinpointed Egap as a key descriptor significantly affecting oxidation efficiency, with the RFR model presenting lower root mean square errors, establishing it as a more reliable predictive tool. The application of the RFR model in this study significantly improved the model's stability and the intuitive display of key influencing factors, introducing promising advanced analytical tools to the field of environmental chemistry.

MiR-371-5p regulates trophoblast cell proliferation, migration, and invasion by directly targeting ZNF516.

Despite its prevalence, preeclampsia (PE) remains unclear as to its etiology. Here, we aimed to investigate the mechanisms regulating differences in the gene expression of zinc-finger protein 516 (ZNF516) in the placenta. The expression of the placental ZNF516 gene and its association with critical clinical markers were verified, and a rigorous correlation analysis was conducted. With a dual-luciferase reporter gene assay, microRNA targeting the ZNF516 gene was predicted and confirmed. Finally, the molecular processes associated with ZNF516 were explored via microarray and bioinformatic analyses. In hypoxic conditions, miR-371-5p expression was reduced, resulting in ZNF516 expression being induced. Moreover, ZNF516 was shown to hinder trophoblast cell migration and invasion while enhancing trophoblast cell death in various in vitro cellular assays, such as cell counting kit-8, colony formation, wound healing, and Transwell assays. Our findings reveal a new regulatory network facilitated by ZNF516. ZNF516 overexpression inhibits trophoblast growth, movement, and penetration, potentially causing problems with placenta formation with the help of miR-371-5p suppression.

Air Quality Class Prediction Using Machine Learning Methods Based on Monitoring Data and Secondary Modeling

Addressing the constraints inherent in traditional primary Air Quality Index (AQI) forecasting models and the shortcomings in the exploitation of meteorological data, this research introduces a novel air quality prediction methodology leveraging machine learning and the enhanced modeling of secondary data. The dataset employed encompasses forecast data on primary pollutant concentrations and primary meteorological conditions, alongside actual meteorological observations and pollutant concentration measurements, spanning from 23 July 2020 to 13 July 2021, sourced from long-term air quality projections at various monitoring stations within Jinan, China. Initially, through a rigorous correlation analysis, ten meteorological factors were selected, comprising both measured and forecasted data across five categories each. Subsequently, the significance of these ten factors was assessed and ranked based on their impact on different pollutant concentrations, utilizing a combination of univariate and multivariate significance analyses alongside a random forest approach. Seasonal characteristic analysis highlighted the distinct seasonal impacts of temperature, humidity, air pressure, and general atmospheric conditions on the concentrations of six key air pollutants. The performance evaluation of various machine learning-based classification prediction models revealed the Light Gradient Boosting Machine (LightGBM) classifier as the most effective, achieving an accuracy rate of 97.5% and an F1 score of 93.3%. Furthermore, experimental results for AQI prediction indicated the Long Short-Term Memory (LSTM) model as superior, demonstrating a goodness-of-fit of 91.37% for AQI predictions, 90.46% for O3 predictions, and a perfect fit for the primary pollutant test set. Collectively, these findings affirm the reliability and efficacy of the employed machine learning models in air quality forecasting.

Selective disrupted gray matter volume covariance of amygdala subregions in schizophrenia.

Although extensive structural and functional abnormalities have been reported in schizophrenia, the gray matter volume (GMV) covariance of the amygdala remain unknown. The amygdala contains several subregions with different connection patterns and functions, but it is unclear whether the GMV covariance of these subregions are selectively affected in schizophrenia. To address this issue, we compared the GMV covariance of each amygdala subregion between 807 schizophrenia patients and 845 healthy controls from 11 centers. The amygdala was segmented into nine subregions using FreeSurfer (v7.1.1), including the lateral (La), basal (Ba), accessory-basal (AB), anterior-amygdaloid-area (AAA), central (Ce), medial (Me), cortical (Co), corticoamygdaloid-transition (CAT), and paralaminar (PL) nucleus. We developed an operational combat harmonization model for 11 centers, subsequently employing a voxel-wise general linear model to investigate the differences in GMV covariance between schizophrenia patients and healthy controls across these subregions and the entire brain, while adjusting for age, sex and TIV. Our findings revealed that five amygdala subregions of schizophrenia patients, including bilateral AAA, CAT, and right Ba, demonstrated significantly increased GMV covariance with the hippocampus, striatum, orbitofrontal cortex, and so on (permutation test, P< 0.05, corrected). These findings could be replicated in most centers. Rigorous correlation analysis failed to identify relationships between the altered GMV covariance with positive and negative symptom scale, duration of illness, and antipsychotic medication measure. Our research is the first to discover selectively impaired GMV covariance patterns of amygdala subregion in a large multicenter sample size of patients with schizophrenia.

Leveraging Innovation for Success: A Study of Innovation Practices and Performance in Private Kenyan Universities

This study delves into the nuanced interplay between innovation practices and the performance of private universities. Employing a descriptive research design, the investigation sought to comprehensively examine the effect of innovation practices on performance outcomes. Data collection was facilitated through the administration of meticulously crafted questionnaires, with a judiciously selected sample of 121 respondents drawn from private universities purposively. The empirical findings unearthed a compelling and affirmative correlation between innovation practices and performance. Through rigorous correlation analysis, the study further illuminated the intricate dynamics between innovation practices and performance (r = 0.731, p &lt; 0.05), underscoring a statistically significant relationship. The research establishes a substantive and affirmative effect of Innovation Practices, particularly in the domain of innovation, on the performance landscape of private universities. The implications of these findings reverberate beyond the institution's walls, offering valuable insights for private universities navigating the multifaceted challenges of contemporary higher education. This study recommends an extension of the investigation to encompass the realm of public universities in Kenya.

Correlation or Causation: Unraveling the Relationship between PM2.5 Air Pollution and COVID-19 Spread Across the United States

Numerous studies have examined the potential connection between air pollution, particularly PM2.5, and the incidence of COVID-19 cases during the pandemic. While several studies have demonstrated a strong correlation, caution is advised as correlation does not imply causation. To address this concern, our two-year observational study employs a comprehensive approach that utilizes a large sample size and draws on temporal and spatial data across the United States, surpassing the limitations of previous studies restricted to specific locations. Through rigorous correlation and regression analyses, we control for potential confounding factors. Air pollution data, a crucial component of our study, has been sourced from the United States Environmental Protection Agency (EPA). Additionally, COVID-19 case data is extracted from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, providing a robust and widely recognized dataset for our analyses. Notably, a significant spatial correlation exists between COVID-19 cases and population size (r=0.98, p-value &lt;0.01), as confirmed by multivariate regression analysis, suggesting a confounding influence of population. It is crucial to emphasize that correlation does not automatically imply a direct cause-and-effect relationship. Moreover, to minimize the impact of population, we employ rates (COVID-19 cases/population of States), demonstrating that the rate of COVID-19 cases is independent of PM2.5 and population. Additionally, the rate of COVID-19 infection is not correlated with population density, implying the population's influence on infection is more likely due to probability rather than being a direct cause. In summary, while many studies report a correlation between air pollution and COVID-19 cases, the influence of confounding factors like population density necessitates further investigation to establish a definitive causal relationship. In conclusion, while many studies report a correlation between air pollution and COVID-19 cases, the influence of confounding factors like population density necessitates further investigation to establish a definitive causal relationship.

Building High-Performing Teams: Analyzing the Influence of Employee Development Practices on Private University Performance in Kenya

This research delves into the intricate relationship between employee development practices and the performance of private universities. Employing a descriptive research design, the study aims to comprehensively analyze the effect of employee development practices on overall performance outcomes within the higher education sector. Data collection was meticulously executed through well-crafted questionnaires, administered to a judiciously purposively selected sample of 121 respondents from private universities in Kenya. The empirical findings of this research unveil a robust and affirmative correlation between employee development practices and performance. Rigorous correlation analysis further elucidates the nuanced dynamics, indicating a statistically significant relationship (r = 0.325, p &lt; 0.05). This study establishes a substantive and affirmative effect of employee development practices. Beyond the institution’s confines, these findings provide valuable insights for private universities grappling with the complex challenges of contemporary higher education. The implications of this research extend to inform strategic decision-making and policy formulation aimed at optimizing employee development practices for enhanced performance outcomes. In light of these outcomes, this study recommends an extension of the investigation to encompass the realm of public universities in Kenya.

ECONOMIC DEVELOPMENT OF ITALY IN THE XXI CENTURY

This article presents a comprehensive study of macroeconomic indicators that shape the trajectory of the Italian economy in the XXI century. In an effort to understand the complex interrelationships between key factors, the purpose of the study is to assess the aggregate impact of key indicators, including the poverty index, economic openness, foreign direct investment and persistent unemployment, on the Italian economic landscape. In particular, the research sheds light on the government's proactive measures to tackle the complex issue of unemployment, underlining the urgency of addressing this critical problem. The paper also examines the dynamics of Italy's balance of payments since its integration into the euro area, highlighting the country's key role in global markets. Italy's status as a major producer in sectors ranging from clothing and automobiles to renowned products such as wine and cheese underlines its importance as an attractive destination for international investment. This analysis aims to provide a detailed understanding of Italy's integration into the global economy and the consequences for its economic performance. The methodology applied in this study uses rigorous correlation and regression analysis. To address potential multicollinearity issues, three distinct models are proposed. These models offer a robust framework for economic interpretation by highlighting the complex interrelationships between different indicators. The study emphasises the key role of such indicators as public spending, economic openness, poverty index, labour force dynamics and gross fixed capital formation in shaping Italy's economic trajectory. The results of the analysis underline the importance of taking these indicators into account when developing future economic development plans for Italy. The key factors identified, including public expenditure, economic openness, the poverty index, labour force dynamics and gross fixed capital formation, have a significant impact on a country's gross domestic product (GDP) and GDP per capita. In terms of practical implementation, the study suggests that policymakers and stakeholders should prioritise these indicators when designing robust and sustainable economic strategies. Such practical implications of the research findings are necessary to guide Italy's economic development and ensure its continued leadership in a dynamic global market. The originality of this study lies in its holistic approach, which offers a comprehensive study of various macroeconomic factors. The proposed models significantly deepen the understanding of Italy's economic dynamics, making a valuable contribution to the academic discourse on this topic.

Digitalization as a driver of transformation towards sustainable performance in wine tourism – the Italian case

PurposeThe main aim of this research was to investigate whether and how digitalization affects sustainability and performance in wine tourism.Design/methodology/approachBased on the data emerging from the 2019 National Report on Wine Tourism from the National Association of “Wine Cities” in Italy (the most extreme case in the world of wine), three macro-agglomerates were investigated: digitalization, sustainability and performance, adopting descriptive and inferential statistics.FindingsAlthough rigorous correlation between adopted digitalization and performed sustainability on one side and performed sustainability and market performance on the other cannot be verified for the 92 wineries under investigation, there is visible evidence that the more digitalized wineries are, the more sustainable they become and the better their performance. Evidence was not found to support the idea that the more sustainable wineries are, the more they are digitalized and the better their performance. Research implications and limitations to theoretical and practical application have been discussed.Originality/valueWine tourism, which is naturally associated with rural tourism, is a form of tourism in which sustainability has strong relevance, particularly considering the future needs/desires of post-pandemic tourists. At the same time, digitalization, especially in pandemic and post-pandemic tourism, is credited with developing a huge impact in this business, although wine tourism is most probably conceivable as a meta-market, with a strong cultural essence. In this respect, a digitalization > sustainability > performance approach seems practicable and globally profitable.

Vascular smooth muscle cell-derived hydrogen sulfide promotes atherosclerotic plaque stability via TFEB (transcription factor EB)-mediated autophagy

ABSTRACT Vascular smooth muscle cells (VSMCs) contribute to plaque stability. VSMCs are also a major source of CTH (cystathionine gamma-lyase)-hydrogen sulfide (H2S), a protective gasotransmitter in atherosclerosis. However, the role of VSMC endogenous CTH-H2S in pathogenesis of plaque stability and the mechanism are unknown. In human carotid plaques, CTH expression in ACTA2+ cells was dramatically downregulated in lesion areas in comparison to non-lesion areas. Intraplaque CTH expression was positively correlated with collagen content, whereas there was a negative correlation with CD68+ and necrotic core area, resulting in a rigorous correlation with vulnerability index (r = −0.9033). Deletion of Cth in VSMCs exacerbated plaque vulnerability, and were associated with VSMC autophagy decline, all of which were rescued by H2S donor. In ox-LDL treated VSMCs, cth deletion reduced collagen and heightened apoptosis association with autophagy reduction, and vice versa. For the mechanism, CTH-H2S mediated VSMC autophagosome formation, autolysosome formation and lysosome function, in part by activation of TFEB, a master regulator for autophagy. Interference with TFEB blocked CTH-H2S effects on VSMCs collagen and apoptosis. Next, we demonstrated that CTH-H2S sulfhydrated TFEB at Cys212 site, facilitating its nuclear translocation, and then promoting transcription of its target genes such as ATG9A, LAPTM5 or LDLRAP1. Conclusively, CTH-H2S increases VSMC autophagy by sulfhydration and activation of TFEB, promotes collagen secretion and inhibits apoptosis, thereby attenuating atherogenesis and plaque vulnerability. CTH-H2S may act as a warning biomarker for vulnerable plaque.

An Alternative Parameterization of Relative Permeability and Capillary Pressure Curves

SummaryThis paper presents a theoretically rigorous correlation of the performance of capillary pressure and relative permeability of naturally fractured sandstone and carbonate reservoirs involving saturation shocks and loading/unloading hysteresis under various stress and thermal conditions. The proposed modeling approach accounts for the combined effects of the porous-rock alteration by various processes, including deformation, transformation, deterioration, and collapse of pore structure, under prevailing temperature and stress conditions during loading and unloading processes, and their effect on the capillary pressure and relative permeability of naturally fractured reservoirs. A saturation shock causing a slope discontinuity in the capillary pressure and relative permeability is shown to occur during saturation change in some sandstone- and carbonate-reservoir formations at a critical saturation condition. This phenomenon can be triggered by alteration of fluid-percolation pathways as a result of the transition from open to closed natural or induced fractures and the deformation of pore structure. The effect of the saturation shock and loading/unloading hysteresis on the capillary pressure and relative permeability of reservoir-rock formations is formulated by means of a phenomenological kinetics model and its applicability is demonstrated by analyzing and correlating the available experimental data.In this paper, the proven comprehensive model developed from a kinetics equation is shown to lead to a theoretically meaningful, universal, and practical constitutive equation in the form of a modified power law. This kinetics equation expresses the probability of dependence of a petrophysical property of porous rocks on a variable, such as saturation for capillary pressure and relative permeability, based on the value of the property relative to its low- and high-end limit values. The applicability of the modified power-law equation is validated by means of the experimental data of the capillary pressure and relative permeability gathered by testing of representative samples from various sandstone and carbonate reservoirs. The phenomenological parameters of the core samples obtained from sandstone and carbonate reservoirs are determined for best match of the experimental data with the modified power-law equation. The value of the critical fluid saturation is determined by the observance of a slope discontinuity occurring in the measured experimental data of the variation of the capillary pressure and relative permeability with saturation. The scenarios presented in this study indicate that loading/unloading hysteresis and saturation shock have significant effects on the stress- and temperature-dependent capillary pressure and relative permeability of the porous reservoir-rock formations. The data-inferred physics-based model presented in this paper is proved to describe the stress- and temperature-dependent capillary pressure and relative permeability of sandstone and carbonate rocks with high accuracy while meeting the endpoint-limit conditions satisfactorily.

The separation of isopropyl alcohol from diisopropyl ether system using glycols: Phase equilibrium and rigorous correlation

The liquid-liquid equilibria data for the (diisopropyl ether + isopropyl alcohol + ethylene glycol or 1,3-propanediol ternary) system were measured at 303.2 K and 323.2 K under 101.3 kPa. The tie-line data for both systems are displayed in the phase diagram with typical type-I behaviour. The distribution coefficient and separation factor were calculated according to the measured tie-line data. The calculated results suggest that both the two solvents can separate the diisopropyl ether and isopropyl alcohol mixture. Ethylene glycol possesses much better separation efficiency for low concentration extraction. The non-random two liquids (NRTL) and universal quasi-chemical (UNIQUAC) models were applied to obtain the binary interaction parameters of pure components with all the root-mean-square deviation values less than 1.0%, indicating the deviation of regression process can be acceptable. Based on Gibbs stability criteria, the topological analysis with a graphical user interface confirmed the binary interaction parameters from data regression were well consistent with the experimental tie-line data.

Detection and Characterisation of Eemian Marine Tephra Layers within the Sapropel S5 Sediments of the Aegean and Levantine Seas

The Eemian was the last interglacial period (~130 to 115 ka BP) to precede the current interglacial. In Eastern Mediterranean marine sediments, it is marked by a well-developed and organic-rich “sapropel” layer (S5), which is thought to reflect an intensification and northward migration of the African monsoon rain belt over orbital timescales. However, despite the importance of these sediments, very little proxy-independent stratigraphic information is available to enable rigorous correlation of these sediments across the region. This paper presents the first detailed study of visible and non-visible (cryptotephra) layers found within these sediments at three marine coring sites: ODP Site 967B (Levantine Basin), KL51 (South East of Crete) and LC21 (Southern Aegean Sea). Major element analyses of the glass component were used to distinguish four distinct tephra events of Santorini (e.g., Vourvoulos eruption) and possible Anatolian provenance occurring during the formation of S5. Interpolation of core chronologies provides provisional eruption ages for the uppermost tephra (unknown Santorini, 121.8 ± 2.9 ka) and lowermost tephra (Anatolia or Kos/Yali/Nisyros, 126.4 ± 2.9 ka). These newly characterised tephra deposits have also been set into the regional tephrostratigraphy to illustrate the potential to precisely synchronise marine proxy records with their terrestrial counterparts, and also contribute to the establishment of a more detailed volcanic history of the Eastern Mediterranean.

A new multiscale model for flow and transport in unconventional shale oil reservoirs

• New mathematical model for multiphase flow in porous media is proposed. • Macroscopic response is bridging with the adsorbed gas behavior in the nanopore. • Gas adsorption isotherm is described by the Density Functional Theory. • Constitutive laws for the retardation coefficient and conductivity are obtained. A new multiscale computational model for two-phase gas/oil flow in a multiporosity shale formation composed of three levels of porosity associated with nano/micro pores and hydraulic fractures is rigorously constructed within the framework of the homogenization procedure in conjunction with the Discrete Fracture Modeling, where fractures are treated as ( n -1) interfaces ( n =2, 3) immersed in the domain occupied by the matrix. Effective equations are obtained by upscaling the microstructural information of the shale oil formation with matrix composed of three distinct solid phases: the organic matter, constituted by kerogen aggregates containing particles and nanopores with adsorbed gas, and the pyrobitumen network, also containing an organic solid with micropores filled by tight oil and dissolved gas, along with the inorganic solid composed of clay, quartz and calcite, assumed impermeable and free of adsorption. Such distinct solid phases are separated from each other by the network of interparticle pores. Together with the pyrobitumen such a network form the pathways for multiphase flow in the matrix whereas the kerogen aggregates are treated as disconnected inclusions playing the role of storage sites for adsorbed gas. The homogenization of the multiphase flow model of black oil type gives rise to new pressure and saturation equations with effective coefficients strongly correlated with the shale microstructure, volume fractions and total organic content ( TOC ). Constitutive laws for the effective hydraulic conductivity and retardation parameter, which captures adsorption of methane in the nanopores, are numerically reconstructed by solving the local cell problems arising from the homogenization procedure. In particular the partition coefficient is computed from adsorption isotherms rigorously constructed within the framework of the Thermodynamics of confined gases seated on the Density Functional Theory (DFT). The effective equations in the matrix resemble in form of a generalized black oil model coupled with the two-phase flow model posed in the subdomain occupied by the network of hydraulic fractures. A macroscopic model is obtained by averaging the mass conservation equation across the fracture aperture giving rise to reduced balance laws posed in a network of reduced ( n -1)-dimension ( n =2, 3) supplemented by a source term arising from the jump in the oil/gas fluxes in the shale matrix. The resultant coupled Discrete Fracture/Multiscale model consists of a first attempt at constructing a rigorous correlation between the nature of the macroscopic multiphase flow equations and the local shale-microstructure mainly characterized by the simultaneous presence of inorganic and organic matters with the latter containing nanopores. Numerical simulations of gas/oil withdrawal are performed to accurately predict hydrocarbon movement in stimulated shale oil formations.

Complexity of the early Archean Uivak Gneiss: Insights from Tigigakyuk Inlet, Saglek Block, Labrador, Canada and possible correlations with south West Greenland

The Saglek Block of Labrador comprises Eoarchean to Neoarchean lithologies, metamorphosed at high temperature at ca. 2.7 Ga. Here, we investigate the gneisses of Tigigakyuk Inlet, previously identified as the locality exposing the most ancient rocks in the Saglek Block. New geochronological and geochemical results reveal a multistage history. Precise magmatic emplacement ages of 3.75–3.71 Ga refine the age of the Uivak Gneiss. Zircon rims and neoblastic grains with low Th/U record metamorphism at ca. 3.6 and 2.8–2.7 Ga. Magmatism between these tectono-metamorphic events is recorded by the presence of meta-mafic dykes in the gneisses, gabbroic enclaves in ca. 2.7 Ga syn-tectonic granitoids, as well as by a ca. 3.56 Ga age for monzonitic gneiss in which metamorphic zircon is present as xenocrysts. Felsic (TTG) magmatism between ca. 3.75 Ga and 3.71 Ga, as well as metamorphism at both ca. 3.6 Ga and 2.8–2.7 Ga, is also recognised in the Itsaq Gneiss Complex of south West Greenland, and is restricted to the Færingehavn Terrane. Our new data enable a more rigorous correlation between these formerly conjugate parts of the North Atlantic Craton.

Spacetime dynamics of a Higgs vacuum instability during inflation

A remarkable prediction of the Standard Model is that, in the absence of corrections lifting the energy density, the Higgs potential becomes negative at large field values. If the Higgs field samples this part of the potential during inflation, the negative energy density may locally destabilize the spacetime. We use numerical simulations of the Einstein equations to study the evolution of inflation-induced Higgs fluctuations as they grow towards the true (negative-energy) minimum. These simulations show that forming a single patch of true vacuum in our past light cone during inflation is incompatible with the existence of our Universe; the boundary of the true vacuum region grows outward in a causally disconnected manner from the crunching interior, which forms a black hole. We also find that these black hole horizons may be arbitrarily elongated---even forming black strings---in violation of the hoop conjecture. By extending the numerical solution of the Fokker-Planck equation to the exponentially suppressed tails of the field distribution at large field values, we derive a rigorous correlation between a future measurement of the tensor-to-scalar ratio and the scale at which the Higgs potential must receive stabilizing corrections in order for the Universe to have survived inflation until today.

Применение принципа обратной связи для решения уравнений трансформаторов и электрических машин

Anapproach is suggested according to which the primary winding resistance istakeninto account using the well-known feed back principle. The search procedure involves two stages. In the first stage, a voltage source is applied behind the resistance. Then, if flux linkages of the loops are taken as independent variables instead of currents, the order of the equation system to be solved is decreased by unity, a circumstance due to which both the search and the form of sought solutions become essentially simpler. Atthesecondstage, a mathematically rigorous correlation between the conditional and actual voltage across the terminals is found using atechnique known as the feed back principle, as a result of which the preliminarily found quantities are presented as functions of the actual voltage across the terminals. Examples demonstrating the validity and effectiveness of the proposed approach are given as applied to a number of problems concerned with studying steady-state and transient modes of electrical machines and transformers.

Technology Focus: Hydraulic Fracturing (March 2016)

Technology Focus With the significant drop in oil price and slowing down of the world economy, one might think many petroleum-related technology items will stall or fade out. Although it may be true for those technologies that are “good to have but not essential,” the oil-economy downturn will not affect the areas where research, development, and application of novel technologies are absolutely necessary for the commercialization of hydrocarbon. When we look at world statistics, we find hydraulic fracturing being used as a key operational technique and enabler in the majority of oil and gas wells to produce them economically with long-term stabilized rates. Any major cut in fracturing or stimulation technology will severely affect world production outlook and, consequently, world energy and therefore is unlikely to happen. Because of the success achieved through hydraulic fracturing, the industry strives relentlessly to maintain the cutting edge in development of novel and innovative technologies and their field applications. Major progress has been made in well completions to accommodate well-stimulation treatments. These include multistage-fracturing (MSF) completions, both openhole and cased; screen tubulars to prevent proppant and sand flowback; and disintegrating dropdown isolation balls and in-tubing plugs, all of which have contributed to fracturing efficiency and cost-effectiveness. A stimulation item worth mentioning is the energized fracturing processes with liquid carbon dioxide (CO2). If the economics works out, the technology is particularly helpful in treating partially depleted reservoirs where natural flowback after fracturing is difficult. For such reservoirs, when fractured with conventional fluids, nitrogen (N2) -assisted lift is needed for the initial startup, resulting in additional time and expense. Liquid CO2 can eliminate or curtail the use of water and simultaneously provide both the hydrostatic head and the energy to clean and lift the well without N2 intervention. One main challenge faced in the development of tight and ultratight reservoirs is the ability to fracture the formation and produce at commercial rates. The challenge occurs particularly in deep reservoirs exhibiting high fracture gradients. In openhole MSF, the placement of isolation packers and fracturing ports is important to pump a successful treatment. In plug-and-perforate MSF, the proper location of perforations and clusters is important. In either completion system, if the induced fractures are not initiated in the right place, very high breakdown pressures may be encountered that can exceed completion limitations. On the other hand, when perforations are placed in nonsweet intervals, the production may suffer even when fractures can be induced. Industry statistics have shown that, many times, more than 50% of the perforation clusters are nonproductive because of poor placement of perforations, thereby reducing production efficiency significantly. Therefore, it is absolutely necessary to perform a complete assessment and evaluation— from drilling to production— to ensure well placement; landing point; azimuth; trajectory; and, most importantly, packer and perforation/port locations. A model that fully integrates drilling dynamics, real-time geomechanics, geosteering, completion placement, production forecast, and rate sustainability is an essential tool for successful fracturing operations. JPT Recommended additional reading at OnePetro: www.onepetro.org. SPE 174026 Impact of Remaining Water in Hydraulic Fractures on Well Productivity—Field Examples From Saudi Arabian Sandstone Reservoirs by Zillur Rahim, Saudi Aramco, et al. SPE 174060 Application of Microproppant To Enhance Well Production in Unconventional Reservoirs: Laboratory and Field Results by Jeff Dahl, Devon Energy, et al. SPE 177953 How To USE Hydraulic- Fracture Interference To Improve Unconventional Development by Basak Kurtoglu, Citibank Global Energy, et al. IPTC 17731 A Rigorous Correlation for Quantification of Skin in Preanalysis of Hydraulic Fracturing by Rizwan Ahmed Khan, King Fahd University of Petroleum and Minerals, et al.