Micro pore characteristics of Luohe aquifer sandstone in Binchang Mining Area typical roof water hazard mines

The mining of Huanglong Coalfield faces a serious threat from roof sandstone water disaster of the extremely thick Luohe Formation. A laboratory study on the microscopic pore characteristics of the sandstone of the Luohe Formation in the Gaojiapu Coal Mine, Binchang Mining Area were carried out using various methods. XRD diffraction, casting thin sections, and scanning electron microscopy were combined to study the pore types of the sandstone particles. Overburden porosimeter was used to illustrate the variation characteristics of porosity and permeability under different confining pressures. High-pressure mercury injection and nuclear magnetic resonance techniques were used to characterize the pore-throat radius of the sandstone core, and X-ray three-dimensional CT scanning was used to quantitatively characterize sandstone pores larger than 9 μm. The results show that, ①the sandstone particles of medium-grained sandstone are larger, and the pore types are mainly residual intergranular pores with a small amount of intergranular dissolved pores, while the particles of fine-grained sandstone are smaller, and the intergranular pores are mostly filled with clay minerals, secondary dissolution intergranular pores, and a smaller degree of pore development.; ②The pore throat radius of large pores in medium-grained sandstone ranges from 0.61 to 4.94 μm, with a cumulative distribution frequency of 48%, while in fine-grained sandstone, the pore-throat radius ranges from 0.188 to 0.683 um, with a cumulative distribution frequency of 47%, indicating that medium-grained sandstone has larger pore-throat radius, which are more conducive to groundwater storage and migration.; ③CT scanning shows that the average surface porosity of medium-grained sandstone is 7.081%, and that of fine grained sandstone is 2.032%. The highly developed macropores (equivalent pore diameter > 180 μm) and micropores contribute to a higher surface porosity. Combined with a larger pore throat radius, the medium-grained sandstone presents a higher permeability. The microscopic pore characteristics of the two types of sandstone are consistent with the on-site evaluation result of the water yield propertyof the corresponding aquifer. The research findings can provide a basic reference for the prevention and control of water disasters from the sandstone roof of the Luohe Formation

A new post-frac evaluation method for shale gas wells based on fracturing curves

AbstractPost-fracturing evaluation by using limited data is of great significance to continuous improvement of the fracturing programs. In this paper, a fracturing curve was divided into two stages (i.e., prepad fluid injection and main fracturing) so as to further understand the parameters of reservoirs and artificial fractures. The brittleness and plasticity of formations were qualitatively identified by use of the statistics of formation fracture frequency, and average pressure dropping range and rate during the prepad fluid injection. The composite brittleness index was quantitatively calculated by using the energy zones in the process of fracturing. It is shown from the large-scale true triaxial physical simulation results that the complexity of fractures is reflected by the pressure fluctuation frequency and amplitude in the main fracturing curve, and combined with the brittleness and plasticity of formations, the fracture morphology far away from the well can be diagnosed. Well P, a shale gas well in SE Chongqing, was taken as an example for post-fracturing evaluation. It is shown that the shale beds are of stronger heterogeneity along the extension directions of horizontal wells, and with GR 260 API as the dividing line between brittleness and plasticity in this area, complex fracture systems tend to form in brittleness-prone formations. In Well P, half of the fractures are single fractures, so it is necessary to carry out fine subsection and turnaround fracturing so as to improve development effects. This paper provides a theoretical basis for improving the fracturing well design and increasing the effective stimulated volume in this area

SAM: a unified self-adaptive multicompartmental spiking neuron model for learning with working memory

Working memory is a fundamental feature of biological brains for perception, cognition, and learning. In addition, learning with working memory, which has been show in conventional artificial intelligence systems through recurrent neural networks, is instrumental to advanced cognitive intelligence. However, it is hard to endow a simple neuron model with working memory, and to understand the biological mechanisms that have resulted in such a powerful ability at the neuronal level. This article presents a novel self-adaptive multicompartment spiking neuron model, referred to as SAM, for spike-based learning with working memory. SAM integrates four major biological principles including sparse coding, dendritic non-linearity, intrinsic self-adaptive dynamics, and spike-driven learning. We first describe SAM’s design and explore the impacts of critical parameters on its biological dynamics. We then use SAM to build spiking networks to accomplish several different tasks including supervised learning of the MNIST dataset using sequential spatiotemporal encoding, noisy spike pattern classification, sparse coding during pattern classification, spatiotemporal feature detection, meta-learning with working memory applied to a navigation task and the MNIST classification task, and working memory for spatiotemporal learning. Our experimental results highlight the energy efficiency and robustness of SAM in these wide range of challenging tasks. The effects of SAM model variations on its working memory are also explored, hoping to offer insight into the biological mechanisms underlying working memory in the brain. The SAM model is the first attempt to integrate the capabilities of spike-driven learning and working memory in a unified single neuron with multiple timescale dynamics. The competitive performance of SAM could potentially contribute to the development of efficient adaptive neuromorphic computing systems for various applications from robotics to edge computing

Predicting treatment failure in stage III colon cancer patients after radical surgery

PurposeThe aim to assess treatment failure in patients with stage III colon cancer who underwent radical surgery and was analyzed using the nomogram.MethodsClinical factors and survival outcomes for stage III colon cancer patients registered in the SEER database from 2018 to 2019 were analyzed, with patients split into training and testing cohorts (7:3 ratio). A total of 360 patients from the First Affiliated Hospital of Longyan served as an external validation cohort. Independent predictors of treatment failure were identified using logistic regression analyses. The nomograms was evaluated by concordance index (C-index), calibration curves, and the area under the curve (AUC), decision curve analysis (DCA) and clinical impact curves (CIC) assessed the clinical utility of nomograms versus TNM staging.ResultsThe study included 4,115 patients with stage III colon cancer. Multivariate logistic analysis age, tumor site, pT stage, pN stage, chemotherapy, pretreatment CEA levels, number of harvested lymph nodes, perineural invasion and marital status were identified as independent risk factors for treatment failure. The C-indices for the training and testing sets were 0.853 and 0.841. Validation by ROC and calibration curves confirmed the stability and reliability of the model. DCA showed that the net clinical effect of the histogram was superior to that of the TNM staging system, while CIC highlighted the potentially large clinical impact of the model.ConclusionsThe developed Nomogram provides a powerful and accurate tool for clinicians to assess the risk of treatment failure after radical surgery in patients with stage III colon cancer

New way for green and low-carbon development of coal industry under the target of “daul-carbon”

Under the background of “dual-carbon” goal and current technological conditions, coal, waste and carbon constitute an impossible triangle in the coal industry which severely constrains its green, low-carbon, and sustainable development. Adhering to the principles of treating waste with waste and returning the waste to where it comes from, with a focus on the three-dimensional perspectives of damage reduction in coal mining, the functional utilization of mining waste, and low-carbon disposal of carbon in mining industry, this paper explores a synergistic development path for coal, waste and carbon. It provides a comprehensive solution to unravel the impossible triangle and promote the overall green, low-carbon development of coal industry. The specific contributions of this work include: ① Clarifying the scientific connotation of damage reduction in coal mining, the spatial combination characteristics of aquifers in the ecologically fragile areas, the movement patterns of overlying strata under the application of coal mining damage reduction techniques, and the surface deformation patterns resulting from overlying strata damage; proposing the original technologies of drilling-backfilling-retention for section pillar extraction, narrow strip mining with backfill, and backfilling behind fully-mechanized longwall face aiming to address the challenges posed by damage reduction mining; ② Interpreting the scientific connotation of functional utilization for mining waste; clarifying the scientific issues related to the modification methods and mechanisms of magnesium-coal-based solid waste material, the mechanisms of synergistic interactions among diverse solid wastes, and the properties control of total solid waste backfilling materials. These efforts have led to the establishment of a key technological system for the functional utilization of solid waste, with a core focus on the modification of solid waste raw materials, the development of solid waste-based cementitious materials, and the preparation of solid waste based backfilling materials; ③ Elucidating the scientific connotation of low-carbon disposal of carbon with a scientific practical framework and implementation pathway; clarifying some scientific issues related to mineralization material preparation, storage space construction, CO2 storage and control mechanisms, the long-term environmental effects of CO2 storage, and reservoir stability in the low-carbon disposal process of carbon. The scientific issues related to mineralization material preparation, seal space key technologies such as fractured space CO2 storage and CO2 sequestration through coal mine carbon solidification are explicitly defined which results in a new model for achieving a low-carbon CO2 storage in coal mine goaf. Based on the green, low-carbon and sustainable development of coal industry, it is of great significance to collaboratively promote the damage reduction in coal mining, the functional utilization of mining waste, and the low-carbon disposal of carbon. This coordinated effort plays a crucial role in advancing the realization of the dual-carbon goal in the coal industry

A4. En tekst om å ville â og ikke ville være vanlig

People living outside conventional families have to grapple with the concept of ordinariness. If their lives are not seen as ordinary intimate lives, what life choices and narrative choices do they have in claiming and responding to this extraordinariness? The article explores ordinariness as a theoretical and cultural concept, and shows how both theoretical approaches and self-narratives can have very different as well as ambivalent attitudes towards ordinariness

Cloud Point Extraction for the Determination of Trace Amounts of Cobalt in Water and Food Samples by Flame Atomic Absorption Spectrometry

A cloud point extraction (CPE) procedure which was developed for the separation and preconcentration of trace amounts of cobalt is combined with �ame atomic absorption spectrometry (FAAS) to determine trace amounts of cobalt in water and food samples. e procedure is based on the formation of the hydrophobic complex between Co(II) and 4-methoxy-2-sulfobenzenediazoaminoazo-benzene (MOSDAA) followed by its extraction into a Triton X-114 surfactant-rich phase. e parameters such as pH of sample, concentrations of MOSDAA and Triton X-114, equilibrium temperature, and equilibrium time, which affect both complexation and extraction, are optimized. Under the selected optimum conditions, the preconcentration of 10.0 mL, 0.1 g mL −1 Co(II) solution results in a limit of detection of 0.47 ng mL −1 (3 ) and an enrichment factor of 19. A relative standard deviation of 2.78% ( , 1 g mL −1 ) for the determination of Co(II) is obtained. e proposed method was applied for the determination of trace amounts of cobalt in river water and millet samples with satisfactory results

Evolutionary Optimization of Neuromorphic Architecture for Low-power Cerebellum Prosthetic Instrumentation and Device in Biomedical Systems

Neuromorphic computing is a new generation of technique, which has been used in the neuroprosthetic implementation in biomedical applications. The spike-based computing mechanism enables it with low power consumption and real-time speed. However, there is a lack of optimization strategy for neuromorphic architecture of neuroprosthetic. In this paper, a novel optimization strategy for neuromorphic architecture of neuroprosthetic, named the Evolutionary Neuromorphic Optimization Framework (ENOF), is presented. A HEMA algorithm is proposed for the implementation of ENOF. It can continuously find the optimal mapping scheme and achieve better accuracy by jumping out of local optimization. Experimental results show that the proposed method can cut down the energy consumption and have better stability. Better optimization can be achieved along with the NoC scale increasing. The proposed work is meaningful for the low-power prosthetic instrumentation and device of biomedical systems, and can be applied in healthcare or clinical situations