Digital Commons Network^™

Mechanical Anisotropy And Depth Effects Of Deep Coal Seams, Mei Xiaofan, Wang Cong, Wang Kaifeng, Tang Shuheng, Zhang Songhang, Xi Zhaodong

Coal Geology & Exploration

Objective The mechanical properties of coal seams determine the stability, fracability, and fracturing performance of deep coal reservoirs. Since the in situ stress applied to coal increases with burial depth, deep coal differs from its shallow counterpart in damage behavior, key mechanical parameters, and failure mechanism. Furthermore, deep coal exhibits pronounced mechanical anisotropy.Methods Focusing on the No. 9 coal seam in the Linxian area along the eastern margin of the Ordos Basin, this study carried out triaxial compression tests at 60℃ under different confining pressures to determine the mechanical anisotropy of deep coal. By comparing the full stress-strain curves, …

An Improved Brittleness Characterization Method For Deep Coalbed Methane Reservoirs And Its Application To Well Logs, Huang An’Er, Gong Fei, Peng Suping, Zou Guangui, Zhang Zhaoji, Wu Yiquan, Rong Zhihong, Li Qingrun

Coal Geology & Exploration

Background Deep coalbed methane (CBM) reservoirs are characterized by high pressure, low porosity, and low permeability. Therefore, large-scale volume fracturing is required for their commercial development. As an important engineering sweet spot parameter for selecting optimal fracturing targets, the brittleness index can reflect the difficulty in generating complex fracture networks during fracturing. However, existing brittleness characterization methods are largely applicable to strata with high brittle mineral content, such as shales and sandstones, while methods for characterizing the brittleness of deep CBM reservoirs with high organic matter content and low brittle mineral content are lacking. Methods Rock physics experiments on 20 …

A Fault Identification Method For Deep Coalbed Methane Reservoirs Based On An Improved Transunet, Gao Congshun, Wu Haibo, Liu Lei, Wang Zijian, Huang Xuanyu, Jia Lilan, Xu Aiguo

Coal Geology & Exploration

Objective Small-scale faults in deep coalbed methane (CBM) reservoirs significantly affect CBM enrichment and the deployment of development wells. However, deep seismic data tend to suffer from low signal-to-noise ratios (SNRs) and poor continuity of reflection events, while conventional methods are likely to miss small-scale faults. To address these limitations, this study proposes a fault identification method based on an improved TransUNet. Methods The proposed method is developed based on the R50-ViT-B_16 TransUNet architecture. A coordinate attention (CA) module is introduced before the skip connections enter the decoder to enhance the feature representation of the locations and directional continuity of …

Petrophysical Model-Driven Seismic Inversion For Physical Property Parameters Of Deep Coalbed Methane Reservoirs, Chen Yang, Guo Qiang, Ba Jing

Coal Geology & Exploration

Objective Deep coalbed methane (CBM) reservoirs typically exhibit complex pore-fracture structures, as well as strong nonlinear and non-unique corresponding relationships between elastic and physical property parameters. In this context, this study develops a seismic petrophysical inversion method that accounts for pore structure variations. Methods This study investigated deep CBM reservoirs along the eastern margin of the Ordos Basin. First, a petrophysical model based on variable pore aspect ratios was established, and the corresponding linearized forward operator was derived. Then, the pore aspect ratios were estimated using near-borehole log data. Meanwhile, the multimodal prior distributions of reservoir physical property parameters were …

Intelligent Identification Of Deep Coal Macrolithotypes Based On Weighted Ensemble In Machine Learning: A Case Study Of The Shenmu Area, Ordos Basin, Yao Yuhao, Yang Zhaobiao, Huang Daojun, Wang Jianan, Dong Guodong, Chen Yilin, He Jinxian, Zhang Shang

Coal Geology & Exploration

Objective Coal macrolithotype represents a key geological property in the exploration and recovery of deep coalbed methane (CBM) resources, and its accurate identification is of great significance for selecting the optimal geological and engineering sweet-spot intervals. However, conventional coal macrolithotype identification relies heavily on core observation, suffering from prohibitively high costs since core data are extremely valuable and thus feature a small sample size. Meanwhile, conventional log-based threshold methods face challenges in effectively characterizing the complex boundaries between coal macrolithotypes.Methods This study investigated the No. 8 coal seam of the Benxi Formation, Shenmu area, eastern Ordos Basin. Based on …

A Probabilistic Lithofacies Classification Method For Deep Coal Measures, Xu Aiguo, Zhang Pingsong, Wu Haibo, Li Shenglin

Coal Geology & Exploration

Background Deep coal measures contain multiple unconventional reservoir types, including coal, shale, and tight sandstone. Accurate lithofacies classification helps identify the resource and engineering targets of unconventional gas within these deep sequences, thus guiding category-based extraction and efficient development. However, conventional lithofacies classification methods largely rely on elastic parameters derived based on the isotropic-medium assumption or linear amplitude variation with offset (AVO) inversion while neglecting the pronounced vertical transverse isotropy (VTI) anisotropy of deep coal measures, severely limiting the lithofacies classification accuracy. Methods This study develops a probabilistic lithofacies classification method for deep coal measures. First, high-accuracy elastic parameters, including …

Multi-Round Diverting Fracturing Technology For Deep-Seated Thin Coal Seams And Its Application: A Case Study Of The G3-1 Well Group In The Yichuan Block, Ordos Basin, Li Shuguang, Nie Zhihong, Ji Liang, Zhou Changhui, Bai Kunsen, Huang Li, Zhen Huaibin, Xing Xuejie, Zhao Haifeng

Coal Geology & Exploration

Objective Deep coal seams in the Yichuan block of the Ordos Basin are characterized by small thicknesses, vertical multi-layer superimposition, and strong vertical and horizontal heterogeneities. When used to develop these coal seams, multi-stage horizontal well fracturing faces challenges such as uneven fracture propagation across various stages in the horizontal direction and a low production degree of multiple coal seams in the vertical direction, complicating commercial exploitation. To address these issues, this study proposes a multi-round diverting fracturing technology based on a vertical cluster well group. In this technology, vertical layered fracturing using vertical cluster wells is employed to achieve …

Scaling And Blockage In Deep Coalbed Methane Wells: Mechanisms And Countermeasures, Zhang Lei, Chen Ming, Zhen Huaibin, Zeng Wenting, Hao Pengcheng, Hou Wei, Yin Decai, Zhang Kang, Liu Chuanqing, Tian Zhida, Liu Qihu, Wang Qian, Xiong Wei, Sun Weiwei, Xia Fei, Wang Chunyan

Coal Geology & Exploration

Background The exploitation of deep coalbed methane (CBM) is accompanied by continuous pressure drawdown. In this case, scaling and blockage are prone to occur in systems where formation water with high total dissolved solids (TDS) and high-concentration CO₂ coexist. In the middle to late production stage, the blockage of both wellbore and flow pathways in reservoirs frequently leads to abrupt declines in gas production and bottomhole pressure or even induces the shutdown of natural flowing production, severely restricting the stable production of deep CBM wells. Methods This study investigated the Daning-Jixian block in the eastern Ordos Basin. Using multiple …

Technology Roadmap And Countermeasures For Lean Development Of Low-Grade Deep Coalbed Methane: A Case Study Of The Linxing-Shenfu Block, Ordos Basin, Wu Guang’Ai, Xing Xuesong, Wu Jianshu, Zhu Ying, Zi Jingyu, Wang Zhi, Hou Yanan, Cheng Yuxiong, Liu Xin

Coal Geology & Exploration

Background Accelerating deep coalbed methane (CBM) exploitation is a strategic initiative for the energy security and energy mix optimization of China. The Linxing-Shenfu block in the Ordos Basin holds considerable resource potential of deep CBM. However, this block exhibits typical geological characteristics of low-grade deep CBM, including the complete absence of free gas, gas content < 14 m³/t, reservoir permeability < 0.1 × 10⁻³ μm², and strong heterogeneity. These characteristics lead to low efficiency of conventional development models. Therefore, there is an urgent need to develop an efficient technical system tailored to these characteristics. Method To address the core contradiction between reservoir …

Numerical Simulation Of Stress Shadow Effect And Cluster Spacing Optimization For Multi-Cluster Fracturing In Deep Coalbed Methane Horizontal Wells, Guo Guangshan, Deng Zhiyu, Sun Le, Pu Yifan, Wu Jian, Tao Shu, Chen Shaojuan, Chen Shida

Coal Geology & Exploration

Purpose Multi-stage, multi-cluster fracturing in horizontal wells represents a key technique for deep coalbed methane (CBM) recovery and the sustainable development of the industry. However, during multi-cluster fracturing in deep CBM horizontal wells, the stress shadow effect tends to induce non-uniform fracture propagation and a limited stimulated reservoir volume (SRV). Methods To address these challenges. this study established a two-dimensional (2D) numerical model for multi-cluster hydraulic fracturing in horizontal wells using the finite element method. Then, it systematically analyzed the impacts of in situ stress and cluster spacing on both the stress shadow effect and the competitive propagation of hydraulic …

Fracturing With Three-Dimensional Full-Scale Fracture Network Propping For Deep Coalbed Methane Reservoirs: A Novel Ceramic Micro-Proppant And Its Verification Through Numerical Simulations, Li Xiang, Xu Jun, Li Ting, Zhang Xiaoyu, Yang Bo

Coal Geology & Exploration

Objective and Methods Conventional fracturing struggles to achieve the long-term effective propping of complex fracture networks during the development of deep coalbed methane (CBM) reservoirs. To address this challenge, this study developed a novel ceramic micro-proppant suitable for the volumetric microfracture propping and, through numerical simulations, verified its performance when it was applied to reservoir stimulation in conjunction with the technology of fracturing with three-dimensional full-scale fracture network propping. First, a novel ceramic micro-proppant with a core-shell structure was designed according to the requirements of microfracture propping. Its key properties, including compressive strength, settling behavior, hydraulic conductivity, and stability, were …

A Spatiotemporal Surrogate Model And Multi-Objective Optimization For Multi-Well Coalbed Methane Production, Qin Yuancheng, Wang Mengyi, Wang Yanfeng, Li Yuan, He Bo, Fang Junling, Duan Qingshan, Liu Chen

Coal Geology & Exploration

Objective and Methods In the full-lifecycle optimization of multi-well and long-term coalbed methane (CBM) production, conventional numerical simulation methods face challenges including extremely high computational costs and difficult multi-objective trade-offs. To address these issues, this study proposed a spatiotemporal surrogate model for multi-objective optimization of CBM production. First, a heterogeneous reservoir model involving 17 production wells was constructed based on high-fidelity numerical simulation, and a sample dataset was created by applying random perturbations to the baseline production scheme. Second, a hybrid surrogate model integrating a convolutional neural network (CNN) and a Transformer decoder was established. The CNN was utilized for …

Numerical Simulation And Process Optimization Of Multi-Round Fracturing In Deep Coalbed Methane Wells In The Linxing-Shenfu Block, Li Yu, Zhang Liang, Li Yunyun, An Qi, Feng Xuesong, Lan Tian, Yu Ji, Liu Xin

Coal Geology & Exploration

Objective Deep coalbed methane (CBM) holds considerable resource potential. However, deep CBM reservoirs exhibit high in-situ stresses, while deep coals feature strong plasticity and heterogeneity. These characteristics render it challenging to generate complex fracture networks through conventional fracturing, thus restricting the large-scale commercial development of deep CBM resources. Multi-round fracturing enables fracture initiation, propagation, and propping through sequential cycles of fracturing fluid injection, pump shut-in, and injection. By constantly changing near-wellbore stress fields, this technique facilitates the formation of complex fracture networks and ensures uniform reservoir stimulation. Method Using the finite-discrete element method (FDEM), this study established a numerical model …

Multi-Solution Ternary Grover’S Algorithm For Logic-Based Quantum Machine Learning With Pseudo-Kronecker Reed–Muller Form Minimization, Sophia Lee, Ali Al-Bayaty, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Optimization problems in machine-learning (ML) applications can be computationally challenging for classical methods, particularly when they involve large, unstructured search spaces. Quantum computing offers a promising approach to combinatorial optimization by utilizing quantum superposition and amplitude amplification. This paper presents a new methodology using logic-based quantum machine learning (QML) as a complete framework for employing a multi-solution ternary Grover’s algorithm to minimize incomplete binary functions represented by Pseudo-Kronecker Reed–Muller (PKRO) expansions, consistent with Occam’s razor principle. Unlike previous quantum approaches based on Kronecker Reed–Muller (KRO) or fixed-polarity Reed–Muller (FPRM) representations, our work introduces the first Grover-based optimization framework for PKRO …

Safety And Resilience In Disaster Debris Removal And Clean-Up Operations: A Field And Training Guide For Resilience Workers In Disaster Debris Removal And Cleanup, Mohsen Shahandashti, Ph.D, P.E., Abhijit Roy, Ph.D, Zhe Yin, Ph.D, P.E., Pmp, Leed Ap, Antonio Balderrama, Ph.D, P.E., Sandesh Adhikari, Santosh Acharya

Mavs Open Press Open Educational Resources

A practical safety guide for the people who clear debris after disasters, and for the trainers who prepare them. Built for crews of every experience level--from seasoned operators to first-time volunteers--it teaches how to read a damaged site, recognize hidden and shifting hazards, work safely around heavy equipment and hazardous materials, and make sound decisions under pressure. Every chapter pairs clear guidance with a one-page field job aid, facilitator notes for trainers, and a real-world scenario, all grounded in OSHA, FEMA, EPA, and NIOSH guidance.

Safety and Resilience in Disaster Debris Removal and Clean-Up Operations Copyright © 2026 by Mohsen …

Integrated Fire Protection Design In Pharmaceutical Manufacturing Facilities: An Applied Case Study, Eman Osman Mahmoud Osman, Fouad Abdel-Mawgoud Abdel-Halim Qasim, Alaa El-Din El-Sayed Farid Hassan

HBRC Journal

The architectural design of pharmaceutical manufacturing facilities presents a complex engineering challenge, requiring simultaneous compliance with Good Manufacturing Practice (GMP) containment standards and life safety egress codes. This research presents an applied methodology for integrated fire protection design in sterile pharmaceutical environments, demonstrated through a case study of a manufacturing complex comprising cleanroom production zones and high-bay storage warehouses with heights reaching 14.8 m. The study reconciles facility classification under the Egyptian Fire Code and NFPA standards by defining Occupancy Hazard Groups W-1 and W-2 (high- and moderate-hazard storage), while utilizing regulatory Code Tables C-1 and C-2 to calculate occupant …

Cognitive Resilience At The Edge: Hyperdimensional Computing Versus Deep Learning For Hardware-Degraded Rf Classification, Adrian B. Cisneros, Jeong Yang

Military Cyber Affairs

Autonomous Collaborative Combat Aircraft (CCA) operating in contested electromagnetic environments must classify Radio Frequency (RF) signals on edge silicon that degrades over the mission lifetime due to thermal stress, radiation, and manufacturing variation. Deep neural networks dominate RF classification on pristine hardware, but their weights are precise and interdependent, causing catastrophic accuracy collapse as the underlying chip ages. We investigate whether Hyperdimensional Computing (HDC), a brain-inspired paradigm that distributes information across thousands of dimensions, can provide a reliability floor where Deep Learning fails. Using the RadioML 2016.10A dataset filtered to five digital modulations relevant to drone command-and-control links, we trained …

Hands-On Ransomware: An Experiential Wannacry Case Study For Undergraduate Cybersecurity Education, Eli Creek Richmond, Thomas R. Devine

Military Cyber Affairs

Ransomware represents one of the most disruptive threats in the cyber landscape, yet hands-on malware analysis remains rare in undergraduate cybersecurity curricula. This paper presents the design, implementation, and evaluation of an experiential learning module centered on the WannaCry ransomware case study, deployed in a senior-level course at West Virginia University. Students performed static and dynamic analysis using industry-standard tools. Pre- and post-module assessments demonstrated measurable gains in self-reported competency across seven technical dimensions. The module's competencies align directly with DoD Cyber Workforce Framework Work Role 212, Cyber Defense Forensics Analyst, supporting education-to-workforce pipeline development.

From Framework To Toolchain: Implementing Zero Trust Architecture In Cloud-Native Environments For Dow Compliance, Shelby C. Snyder

Military Cyber Affairs

Federal agencies face a fiscal year 2027 target for enterprise-wide Zero Trust deployment, but NIST SP 800-207A defines logical components without identifying the Kubernetes technologies that implement them. This paper proposes a three-tier mapping of the Policy Engine, Policy Administrator, and Policy Enforcement Point to service mesh, microsegmentation, and perimeter tooling, stating the criteria by which each component is classified. It then applies a defined rubric to six Zero Trust vendors across component alignment, Kubernetes capability, federal authorization posture, and evidence quality, finding that no single vendor covers all three tiers. The mapping is a testable architectural proposition; a Stage …

Semantic Shields: Automating Critical Infrastructure Defense Via Nlp-Driven Ransomware Profiling, Henry Trowbridge, Ian Zalcberg, Ryan Schley, Carter Yagemann, Natasha Phan, Srikar Maduposu, Vimal Buck

Military Cyber Affairs

Ransomware poses a growing threat to critical infrastructure, where successful attacks can disrupt operational technology (OT) and industrial control systems (ICS) with significant public safety consequences. However, attributing ransomware incidents to specific threat actors remains challenging due to ransomware-as-a-service ecosystems, actor rebranding, and the obfuscation of traditional indicators of compromise. This paper presents Semantic Shields, an NLP-driven attribution framework that leverages BERT-generated semantic embeddings and DBSCAN clustering to profile ransomware actors through the linguistic characteristics of ransom notes. Using a dataset of 295 ransom notes from 189 distinct threat groups, the framework achieved an 87.2% true positive clustering rate and …

Llm-Generated Countermeasures For Iot Cyberattacks, James Alger, Michael Tu

Military Cyber Affairs

The rapid expansion of the Internet of Things (IoT) has introduced significant cybersecurity challenges, particularly for resource-constrained devices that traditional intrusion detection systems often fail to protect effectively. This paper proposes a novel, two-phase autonomous security pipeline designed to bridge the gap between probabilistic threat detection and deterministic network enforcement. The framework first utilizes a custom Time Series Transformer (TST) to classify multivariate network traffic and identify specific attack vectors, such as ransomware, SQL injections, and malicious file uploads. In the second phase, an agentic AI layer, comprising a locally hosted Large Language Model (LLM) orchestrated via LangGraph, processes the …

Letter From The Director: Mastery In Practice, Joseph Schafer

Military Cyber Affairs

No abstract provided.

Main Challenges To China’S Scientific Research Instrument Innovation From Perspective Of The United States Export Controls, Jing Li, Daixie Chen, Qinghua Lin, Guohua Xiao

Bulletin of Chinese Academy of Sciences (Chinese Version)

China has long been heavily dependent on imports of scientific research instruments, making this sector particularly vulnerable to intensified technological containment by the United States and other Western countries and their efforts to maintain technological dominance. Since the Donald Trump’s tenure as the 45th president of the United States began in 2017, the United States has frequently used export controls to suppress China’s scientific and technological progress, posing great security risks to China. Based on a review of the development of scientific research instrument innovation in China, this article analyzes the updates and trends of the United States export controls …

Use Of Generative Ai Tools In An Undergraduate Engineering Design Course, Wei Yin, Esther Ocharo, Lillian Best, Harrison Martin

International Journal of Transformative Teaching and Learning in Higher Education

Generative AI tools are widely used by college students. This study aimed to investigate the best ways to teach students the limits of AI, especially in hands-on engineering classes. A class project in a sophomore biomedical engineering class was used to test the effectiveness of generative AI tools in supporting engineering CAD design and 3D modeling. Students were tasked with designing a finger basketball toy, creating 2D engineering drawings, and creating a physical prototype using 3D modeling and printing. Students used ChatGPT, Copilot, and Gemini to support the completion of the design project. Students’ manual work demonstrated satisfactory skills in …

A Quad-Port Dual-Band Elliptical Patch Mimo Antenna For 5g And Wlan Applications, Livingstone L. Kimaro, Hashimu Uledi Iddi, Mussa M. Kissaka, Neema S. Joseph

Tanzania Journal of Engineering and Technology (TJET)

A dual-band multiple-input multiple-output (MIMO) antenna for wireless local area network (WLAN) and fifth-generation new radio (5G NR) band n104 applications is presented. Two U-shaped slots interconnected back to back are etched on an elliptical shaped patch, four identical patch elements are then arranged orthogonally to form a quad-port antenna that resonates at 5.8 GHz and 6.7 GHz. Without additional extrinsic decoupling structures, the proposed design achieves measured isolation levels above 25.13 dB and 21.31dB, realized gains of 7 dBi and 7.2 dBi and -10 dB impedance bandwidths of 155.4 MHz and 90 MHz in the lower and upper frequency …

Design Of Permanent Magnet Synchronous Motor For Railways Traction Application, Anna S. Mwang'onda, Jackson J. Justo, Francis Mwasilu

Tanzania Journal of Engineering and Technology (TJET)

This paper presents the design of surface mounted permanent magnet synchronous motor (SMPMSM) intended for traction applications in standard gauge railway (SGR) for passengers. The proposed motor is rated 350 kW with a base speed of 3000 rpm. Moreover, speed control strategy with stability analysis is incorporated in the design to validate the performance of the SPMSM. The simulation results achieved a torque of approximately 1115 Nm at a terminal voltage of 800 V. The flux linkage of 150 mVs which ensures effective electromagnetic pertinence while maintaining safe magnetic loading because the flux density is less than 1.5 T. The …

Thermal Monitoring Of Solidification In Molded Casting Of Drone Landing Leg, Sadettin Cem Altıparmak, Maher Zayed, Samuel Hawk, Mohamed Baddi, Jesus Degollado, Ahmed Bendaouia, Jianzhi Li

Manufacturing & Industrial Engineering Faculty Publications

This paper presents the design, fabrication, and thermal characterization of an acrylonitrile butadiene styrene (ABS) mold produced by fused deposition modeling (FDM) extrusion-based additive manufacturing used for the wax casting of a drone landing leg. A thermal monitoring framework, consisting of four K-type thermocouples logged at 1 s intervals, was deployed across six casting trials to capture the complete solidification cycle, yielding 84,717 time-stamped measurements. The study focuses on thermal data analysis and materials science interpretation through descriptive statistics, normality diagnostics, inter-trial Kruskal–Wallis tests, phase-duration analysis, rolling-variance monitoring, and inter-channel Pearson correlation. Key findings include a persistent spatial temperature hierarchy …

Exploring The Role Of Single Pilot Operations In Night Cargo Aviation: A Phenomenological Study, Kollin Ellis

Doctoral Dissertations and Projects

The purpose of this qualitative descriptive phenomenology was to examine the lived experiences of pilots who have operated alone at night in an aviation cargo environment. The design was guided by an epistemological philosophical assumption. Extreme advancements in the technology of artificial intelligence and their applications in the aviation industry have raised the question of the value of a single operator serving in commercial cockpits. Some experts argue that a two-person crew is unnecessarily redundant. A significant gap in the current literature of experiential data existed to prompt this study. Through the contextual lens of the Dual Process Theory and …

Application Of Machine Learning To Discover Dynamical Structures In 4d Poincaré Maps In The Circular Restricted Three-Body Problem, Kevin M. Trigg, Daniel J. Broyles, Robert A. Bettinger, Tyler J. Kapolka

Faculty Publications

The spatial Circular Restricted Three-Body Problem (CR3BP) produces complex orbital dynamics that are difficult to classify at scale using traditional, manual Poincaré map analysis. A Poincaré map simplifies continuous orbital motion by recording the points where a trajectory intersects a chosen surface in phase space, converting a continuous path into a discrete set of crossings that reveal underlying topological structure. These crossings make it easier to characterize trajectory behavior, but interpreting them visually becomes impractical for large datasets and as Poincaré maps evolve from two into four dimensions. To address this challenge, an unsupervised clustering pipeline for discovering dynamical structures …

Comparison Of Gravity Separation And Flotation For Pyrite Recovery From Tailings, Gülay Bulut, Gönül Göksu Gökçe, Dilruba Karamanlı, Oğuzhan Mert Gürkan, Ergin Sarp Zenzirci, Binnur Kırım, Alim Gül

Journal of Sustainable Mining

Tailings generated during the production of lead, zinc, and copper concentrates contain significant amounts of sulfide minerals, particularly pyrite. Pyrite, which remains in tailings after the recovery of other metals, is one of the main contributors to acid mine drainage (AMD). Therefore, recovering pyrite from tailings is environmentally and economically an important issue. In this study, pyrite recovery from tailings was investigated using flotation and gravity separation methods. Mineralogical characterization and liberation analyses were conducted by Mineral Liberation Analysis (MLA), indicating that pyrite is the major sulfide mineral with over 76% liberation degree even in the coarsest fractions. Flotation tests …