Digital Commons Network^™

Current Status And Future Trends Of Seismic Prediction And Assessment Technology For Coalbed Methane Reservoirs, Wu Haibo, Zhang Pingsong, Xu Shi’Ang, Huang Yaping, Dong Shouhua, Cheng Yan, Li Donghui, Zhang Sheng, Zhang Min

Coal Geology & Exploration

Background The seismic prediction and assessment technology for coalbed methane (CBM) reservoirs has undergone rapid development for over three decades, playing an indispensable role in CBM exploration. Methods This study reviews the development history and current status of core technologies within the seismic prediction and assessment technical system for CBM reservoirs, including seismic-petrophysical tests, modeling and inversion, seismic wavefield simulation, seismic amplitude versus offset (AVO) inversion and seismic attribute inversion, and integrated seismic prediction of the sweet spot areas of CBM reservoir resources and engineering. Furthermore, this study delves into the impacts and limitations of the characteristics of CBM reservoirs, …

A Method Integrating A Non-Stationary Random Field For Constrained Inversion Of Csamt Data, Dai Qianwei, Guo Luyao, Wu Yun, Xiong Zhexian, Duan Dan, Bao Zhonglin, Wu Hongfei, Hao Fengyun

Coal Geology & Exploration

Objective The inversion of controlled-source audio-frequency magnetotelluric (CSAMT) data remains challenging due to two key issues: computational efficiency and resolution. To tackle these two issues, especially the over-smoothing effect caused by traditional regularization methods in estimating complex geological structures, this study proposed an improved regularization inversion method to reflect the spatial distribution characteristics of subsurface physical property parameters more accurately. Methods The proposed method was developed using the method for establishing the stochastic partial differential equation (SPDE) based on the Matérn covariance function. By introducing vector fields and the shape parameters of a range ellipse, this method fully considered both …

Ai-Driven Emi Mitigation For Smart Healthcare: Generative Adversarial Networks And Edge Computing For Reliable Medical Systems, Mona Esmaeili

Electrical and Computer Engineering ETDs

Electromagnetic interference (EMI) from radio frequency (RF) sources poses a major challenge to digital systems, especially in high-electromagnetic environments. Tradi- tional electromagnetic compatibility (EMC) analysis often focuses on continuous wave (CW) interference and overlooks the effects of waveform modulation on EMI coupling. This thesis explores how modulated waveforms influence EMI coupling and introduces a Generative Adversarial Network (GAN)-based classification framework to distinguish between harmful and non-harmful EMI signals. The study extends conventional EMC analysis using machine learning (ML), showing that modulated EMI waveforms can in- crease coupling by up to 27% compared to CW signals. This highlights the need for …

Geochemical Nature Of The Geothermal Water From Lanzhou Basin: Implications For The Genesis Of Shallow Helium-Bearing Fluids, Tang Jianzhou, Wang Shuangming, Zhang Zhicheng, Li Ke, Li Changpeng

Coal Geology & Exploration

Objective and Methods Investigations on the geochemical nature of geothermal water are vital to the comprehension of the origin of helium-rich fluids in shallow basins. To address this issue, this paper reports the results of the chemical analysis, H-O isotopes and ¹⁴C ages from geothermal water and soluble gas components from the well BY-1 in Lanzhou Basin, northeastern margin of Qinghai Tibet Plateau. Chemical analysis of geothermal water samples reveals that the chemical type of geothermal water is NaCl. The show δD value of –78‰, high δ¹⁸O value (–8.7‰), low ³H value (<0.4TU), and old ¹⁴C …

Prediction Of Geological And Engineering Integrated Sweet Spots Of Deep Coalbed Methane, Chen Zhengrong, Liu Wei, Zhu Xueshen, Tian Yongjing, Xie Xin

Coal Geology & Exploration

Objective Deep coalbed methane (CBM) has emerged as a hot topic in CBM resource development. However, deep CBM has characteristics such as great burial depths, complex stress environments, and strong reservoir heterogeneity, which seriously restrict sweet spot prediction and accurate well location deployment in its large-scale exploitation. Methods This study investigated a deep CBM field along the eastern margin of the Ordos Basin. Using sonic, density, and caliper logging, this study developed a coal structure index model for deep coals. By introducing the coal structure index based on the coal structure differences in deep coal seams and combining factors including …

Impacts Of Metakaolin And Fly Ash On The Performance Of Cement-Based Grouting Materials In Anchoring Engineering, Cheng Zhiyuan, Yang Junpeng, Xue Wei, Wei Daidong, Wang Yimin

Coal Geology & Exploration

Objective The filling of grouting materials plays a significant role in ensuring the performance of anchoring structures. This study aims to further enhance the fluidity of grouting materials, reduce their dry shrinkage in the curing process, and ensure complete filling. This will help improve the bonding property between the anchoring body and the rock and soil mass to be reinforced. Methods Using cement as the primary material, as well as fly ash and metakaolin as admixtures, this study designed and prepared 20 groups of binary and ternary mixtures and one control group. Through tests of the fluidity, bleeding ratios, and …

Deep Reinforcement Learning-Driven Decision Support System Design For Precision Agriculture: Optimizing Farming And Resource Use, Qingshan Bai

Turkish Journal of Agriculture and Forestry

This study focuses on enhancing the efficiency of agricultural decision support systems by integrating deep reinforcement learning techniques to optimize the path planning of agricultural vehicles. By decomposing the system into dynamics, action, strategy, reward, and discount factor components, a robust framework is established. A value-based reinforcement learning algorithm is introduced, enriched with policy gradient (PG) methodology to enable continuous and adaptive state-to-action decision-making process. A deep neural network (DNN) was used to approximate the state-action value function, resulting in the innovative DNN-PG-Q-learning algorithm. This algorithm leverages an empirical playback pool to enable efficient and intelligent path planning for agricultural …

Diffusion Mechanisms Of Coal-Measure Helium And Their Implications For Helium Accumulation: A Case Study Of The Taiyuan Formation, Northern Qinshui Basin, China, Ma Yong, Xin Zhiyuan, Chen Jianfa, Li Yuhong, Zhang Xiutao, Jiang Haojie, Chen Zeya

Coal Geology & Exploration

Objective The global helium-rich gas reservoirs are dominated by conventional natural gas reservoirs. In recent years, helium-bearing natural gas has been discovered in the Carboniferous-Permian coal measures in the Ordos Basin and surrounding regions, revealing the resource potential of coal-measure helium. However, there is almost a total lack of studies on mechanisms underlying the diffusion and migration of coal-measure helium. This severely restricts further research on the accumulation patterns of coal-measure helium.Methods This study investigated a coal seam in the Taiyuan Formation in the northern Qinshui Basin and mudstones in the coal seam roof. Using physical diffusion experiments on …

Physical Simulation Experiments On Competitive Dissolution Of Helium In Helium-Containing To Helium-Rich Gas Reservoirs, Zou Yi, Luo Qingyong, Chen Jianfa, Zou Huayao, Du Tao, Liu Xiaoqiang, Cai Xinyong, Yu Chengming, Fang Zilong

Coal Geology & Exploration

Background and Purpose Helium is widely applied in high-tech and scientific research fields due to its unique physicochemical properties. Formation water plays a key role in helium migration and enrichment. Typically, in the form of dissolved gas, helium is transported in pores or fractures by formation water. When helium-rich fluids migrate to shallow natural gas reservoirs, helium will experience dissolution and desorption exchange with other gases. This process is affected by formation temperature, pressure, and water salinity, as well as the competitive dissolution between helium and other gases. However, there is a lack of studies on the mechanisms underlying the …

Backfill-Strip Mining And Co2 Mineralization Sequestration In Coal Mine Goaves: A Synergetic Method And Its Key Technologies, Zhu Mengbo, Liu Lang, Wang Shuangming, Wei Baoning, Rong Ruoyu, Zhang Wenzhong, Zhuang Dengdeng, Jia Qifeng

Coal Geology & Exploration

Objective Coals serve as both the cornerstone of China’s energy security and important industrial raw materials. However, their mining and utilization tend to cause ecological and environmental problems such as CO₂ emissions, the generation of solid wastes, and land subsidence. This necessitates reforming coal mining methods to promote the green, low-carbon, and sustainable development of China’s coal industry.Methods Through the comparative analysis of the conditions of CO₂ sequestration in goaves corresponding to the caving, room-and-pillar (also known as knife-pillar), and backfill mining methods, this study developed a synergetic method for backfill-strip mining and CO₂ mineralization sequestration …

A Visual Positioning Method For Tunnel Boring Machines In Underground Coal Mines Based On Anchor Net Features, Zhang Xuhui, Chi Yunkai, Du Yuyang, Jiang Junying, Yang Wenjuan, Zhao Youjun, Wan Jicheng, Wang Yanqun, Tian Chenhui

Coal Geology & Exploration

Background Precise positioning of tunnel boring machines (TBMs) in underground coal mines plays a fundamental role in the automated and intelligent guidance and control of fully mechanized heading face. However, traditional visual positioning methods show limited application effects in underground roadways due to their narrow and enclosed spaces, insufficient illumination, and sparse textures. This study proposed a visual positioning method for TBMs in underground coal mines based on anchor net features.Methods A three-stream depthwise separable convolutional neural network (TSCR-NET) for image enhancement was employed to estimate the reflection, illumination, and noise in images individually. Through illumination adjustment while suppressing …

Colloidal Hot-Injection Synthesis Of Cubse2 Nanocrystals: Tetragonal Chalcogenide Templates For Superionic Lithiation Pathways, Yunhao Xu, Niket Powar, Kelly Zervos, Isabella Campbell, Simran Choudhary, Layan Al-Khaled, Progna Banerjee

Chemistry: Faculty Publications and Other Works

Copper boron selenides represent a previously unexplored class of materials with tetragonal structural symmetries and bonding chemistries potentially relevant to lithium-ion conduction. In this work, the first colloidal synthesis of nanocrystalline copper boron selenides is reported, enabling access to nanocrystals with reaction times shown as the synthetic knob to control composition and morphology. Copper boron selenide nanocrystals are synthetically designed as precursors for lithiation reactions aimed at probing structural evolution and ionic mobility pathways toward superionic conductors applicable as solid electrolytes in lithium-ion batteries. Postsynthetic lithiation studies under ambient conditions reveal a series of phase transformations and morphological changes, which …

Human Settlement Environment And Architectural Ecological Design Based On Artificial Intelligence Technology, Mingxing Xu, Xiongjun Tao

Turkish Journal of Agriculture and Forestry

The main purpose of this paper was to use artificial intelligence (AI) technology to improve the coordination between architectural design and the natural environment, so as to optimize resource utilization and reduce negative environmental impacts and improve the quality of human settlements. To do this, multiple types of data covering the environment, buildings, and user feedback were first collected and preprocessed. Based on these data, the long short-term memory model was used to predict future environmental changes, and the particle swarm optimization algorithm was used for multiobjective optimization of architectural design. The experimental results showed that the AI-driven design scheme …

Cover And Content

Turkish Journal of Physics

No abstract provided.

Circular Motion And Thermodynamic Characteristics Of Particles Around A Quintessential Nonrotating Black Hole, Indrajit Halder, Kamal Lochan Mahanta, Rakesh Ranjan Sahoo

Turkish Journal of Physics

This paper investigates the geodesics of the Schwarzschild black hole modified with the quintessence field and modeled as a barotropic fluid with a constant equation of state derived in Boyer Lindquist coordinates with natural units G = c = 1. Hamilton–Jacobi formalization is applied to investigate the geodesics in both static and nonstatic black hole spacetime. It specifically examines the formation of bound orbits of test particles around the black hole, highlighting that these orbits result from the interplay between the gravitational pull of the black hole and a repulsive force associated with quintessence. The thermodynamic properties of a black …

Variational Monte Carlo Optimization Of Proton-Proton Scattering Potential Using The Phase Function Method, Shikha Awasthi, Anil Khachi, O.S.K.S. Sastri

Turkish Journal of Physics

The Riccati-type nonlinear differential equation, also known as the Phase Function equation, is used to construct local inverse potentials for the 1S0 - pp state by bypassing the well-known Schrödinger equation. The pp interaction is described using the Malfliet-Tjon potential model for the nuclear component combined with a screened Coulomb potential, with the phase equation solved via the fourth-order Runge-Kutta (RK-4) method. Based on our analysis, we confirm that the optimized interaction potential closely matches the well-known realistic Argonne V18 and Reid potentials for the 1S0 state, and the computed phase shifts and cross-sections show excellent agreement with experimental data. …

Selecting An Internal Carbon Price For Academic Institutions, Alexander R. Barron, Dimitra Prassa

Environmental Science and Policy: Faculty Publications

Many businesses have adopted internal carbon prices (ICPs) to help drive smarter business decisions, innovation, and emissions reductions. The objective of this white paper is to provide a framework that institutions, particularly those in higher education, can use as they think about selecting a price in the context of their own goals for an ICP.

Second Nature’s recent 2025 Carbon Markets and Offsets guidance recommends that: “colleges and universities develop a climate action strategy that includes some type of internal carbon pricing, either as a mechanism to inform climate-positive decision-making or as a mechanism for generating revenue estimates for decarbonization …

Homework, Households, And Hurdles: The Unexpected Drivers Of Student Graduation Perceptions, Daniel Alhassan, Zahra Fatah, Priscilla Mansah Codjoe, Caroline Bena Kuno, Dorcas Ofori-Boateng

Mathematics and Statistics Faculty Publications and Presentations

Students’ perceptions of their likelihood to graduate are important determinants of their academic engagement, yet these perceptions remain understudied. This study, which is based on the 2021 Monitoring the Future survey of 8th- and 10th-grade students in the United States, uses machine learning algorithms to identify the most important factors that influence these perceptions. Among the tested models, random forest provided the best classification performance. Using permutation-based feature importance, we identified frequent participation in schoolwork, maternal education, paternal education, and homework completion as the most important predictors of students’ graduation perceptions. These results highlight the importance of targeted and well-coordinated …

Quantum Management: A Revolution In The Future Of Management Science And Business Practice, Bartosz Niedzielski

Studia i Materiały Wydział Zarządzania Uniwersytet Warszawski

Purpose: The article aims to propose a nominal definition of quantum management and analyze the differences between the classical and quantum paradigms of management, with particular emphasis on their impact on organizational structure and decision-making processes.

Methodology: The article is based on a synthetic literature review concerning the application of quantum theory in management sciences, including publications from bibliometric databases such as Scopus, Web of Science, and Elsevier. The review focuses on the theoretical and practical differences between the classical and quantum approaches to management. Additionally, a comparative method is used to identify key differences between these two …

Evolution Of Wormholes Under F(R, T) Theory, The Karmarkar Condition And The Casimir Energy, Murat Metehan Türkoğlu

Turkish Journal of Physics

In this study, both the evolution of wormholes (by examining both the energy conditions and using the TOV equations) and the effects of the Karmarkar condition on the solutions obtained under certain specific cases were examined in the light of the f(R, T) gravity theory, using two f(R, T) functions predicted to describe the accelerated expansion of the universe. In this context, for the first time in the literature, a generalized shape function was obtained using the Karmarkar condition. It was observed that solutions of the type R -a12/R+a2g(T) satisfy the energy conditions (with the dominant energy condition being partially …

Precision Crop Yield Prediction Model Based On Deep Learning And Multimodal Data Fusion, Zijin Mo, Yanxiong Wu

Turkish Journal of Agriculture and Forestry

More precise crop yield prediction methods are essential in advancing precision agriculture, ensuring food security, and promoting sustainable agricultural practices. Deep learning technologies have significantly improved prediction accuracy by allowing the analysis of large-scale agricultural datasets. However, existing approaches still face challenges in effectively integrating multisource data, such as meteorological, soil, and remote sensing information, and optimizing model parameters. To address these issues, this study introduces TCGNet, a novel deep learning architecture that combines a time convolutional network (TCN), convolutional long short-term memory (ConvLSTM), and the grey wolf optimization (GWO) algorithm. The TCN is employed for time series analysis, ConvLSTM …

A Comprehensive Review Of Fermentation Technologies In Food Processing: From Traditional To Cutting Edge, Pragati Singh, Niharika Arya, Shalini Sharma, Ankita Sharma, Prasad Rasane, Supriya Singh Gaur, Sawinder Kaur, Mahendra Gunjal, Hasan Kiliçgün, Jyoti Singh

Turkish Journal of Agriculture and Forestry

Fermentation technologies play crucial roles in food processing, offering various advantages, including enhanced flavor profiles, extended shelf life, and improved nutritional qualities. This paper provides a comprehensive overview on the major types of fermentation as well as effects of various factors such as substrate composition, temperature, pH, oxygen availability, and microbial strain selection on the process. Despite its widespread application, traditional fermentation processes face limitations related to yield optimization, contamination risks, and process consistency. Recent advancements have significantly enhanced fermentation efficiency, product quality, and scalability, ultimately expanding the applications beyond food and beverage production into pharmaceuticals, nutraceuticals, biofuels, and waste …

Risk-Sensitive Markov-Perfect Equilibrium, Matthew J. Sobel

Faculty Scholarship

We investigate the existence and structure of Markov-perfect equilibria of discrete-time dynamic games in which players are risk averse and have time preferences consistent with discounting. We establish the existence of a Markov-perfect equilibrium when each player strives to maximize the expected exponential utility of the present value of the time stream of rewards. Also, we give sufficient conditions for a Markov-perfect equilibrium to be myopic, namely to be a sequence of Nash equilibria of static games. The myopia results are applied to a dynamic oligopoly model in which firms choose prices and production quantities, encounter stochastic demand and hold …

Table Of Contents, The Editors

Coal Geology & Exploration

No abstract provided.

Construction And Application Of A Tcn-Lstm-Svm-Based Time Series Prediction Model For Water Inflow In Coal Seam Roofs, Liu Xuan, Ji Yadong, Zhu Kaipeng, Zhao Chunhu, Li Kai, Li Chaofeng, Yuan Chenhan, Li Panpan, Yan Pengzhen

Coal Geology & Exploration

Background The accurate prediction of mine water inflow plays a significant role in the prevention and control of water hazards and the safe and efficient production in coal mines. Methods To construct a prediction model of water inflow in mines under threat of water hazards from extremely thick sandstones aquifer in West China, this study investigated a typical mine (also referred to as the studied mine) severely affected by such water hazards in the Binchang mining area of Shaanxi Province. The correlation between the mining footage and water inflow of the mining face was selected as the characteristic variable for …

Influencing Patterns Of Low-Temperature Nitrogen On The Pore Structure And Oxidation Characteristics Of Lignite, Xie Shuliang, Wang Gang, Qu Qingdong, Liu Hao, Sun Lulu

Coal Geology & Exploration

Objective During fire prevention and extinguishment for mines, injecting normal-temperature nitrogen into goaves can only play an inerting role. Meanwhile, the preparation of liquid nitrogen is complicated and costly. Therefore, in the Wudong Coal Mine in Xinjiang, low-temperature gaseous nitrogen of –40 ℃ was prepared using nitrogen cooling devices and then injected into goaves to prevent the spontaneous combustion of residual coals. However, the influencing patterns of low-temperature nitrogen on the pore structures and oxidation characteristics of residual coals in goaves remain poorly understood. This tends to affect the prediction and forecast of the secondary oxidation of residual coals in …

Mechanisms Underlying Differential Helium Enrichment In Shale Gas Of Varying Structural Styles In The Southeastern Sichuan Basin, Xin Zhiyuan, Chen Jianfa, Wang Jie, Ma Yong

Coal Geology & Exploration

Objective Shale gas reservoirs hold considerable helium reserves despite relatively low helium abundance, establishing them as a critical replacement for helium production growth. The southeastern Sichuan Basin exhibits diverse structural styles with varying preservation conditions, leading to an unclear understanding of the distribution characteristics and enrichment patterns of helium in shale gas. Determining the mechanisms behind the differential helium enrichment in shale gas is significant for the effective utilization of helium in shale gas.Methods Focusing on the typical shale gas reservoirs of different structural styles in the southeastern Sichuan Basin, this study explored the mechanisms underlying differential helium accumulation …

Strategies To Improve Nurse Staffing And Workforce Management In Home Health Agencies, Kelechi Lillian Wabeke

Walden Dissertations and Doctoral Studies

Home health agencies continue to grapple with challenges in nurse staffing and workforce management. This integrative review explored effective strategies to address these challenges and improve operational efficiency. The review focused on identifying best practices for enhancing nurse recruitment, retention, and scheduling processes within home health settings. Guided by the transformational leadership framework, the study examined 30 empirical and theoretical articles published over the past 5 years. The selected articles were further assessed for relevance and quality using the Johns Hopkins evidence-based practice model. Through an in-depth thematic analysis, five primary themes and 10 supporting subthemes emerged. The key themes …

Intraspecific Competition Can Promote Population-Level Specialization, Abdel H. Halloway

Faculty Scholarship

The hypothesis of competitive diversification asserts that increased intraspecific competition will cause a population to generalize in resource use. The reasoning is that as preferred resources are depleted, individuals which use alternative resources become more fit, leading to an overall broadening of resource use. However, recent studies have shown instances of the opposite effect: increased intraspecific competition leading to increased population resource specialization. We explored how intraspecific competition could affect population resource specialization by creating an evolutionary game theoretic consumer-resource model in which individuals have both resource use preference and resource use breadth which are flexible and adaptable. Using this …

Phytoremediation Of Lead Heavy Metals In The Mangrove Ecosystem Of The Lembar Harbor Area, West Lombok Regency, Indonesia, Firman Ali Rahman/Firman, Muhammad Shohibul Ihsan, Dwi Agustini, Ervina Titi Jayanti

Makara Journal of Science

Mangroves play a vital role as bioindicator plants in port areas with the potential for non-essential heavy metal contamination. This study aimed to determine the potential for phytoremediation of lead heavy metal in mangrove vegetation resulting from port operations. The research was conducted in the mangrove ecosystem of Lembar Harbor, West Lombok Regency, West Nusa Tenggara, Indonesia. Substrate, leaf, and root samples were collected using a purposive random sampling technique and analysis for testing the lead heavy metal content using atomic absorption spectrophotometry. The results showed that the average heavy metal content of lead accumulated in the substrate in each …