Evaluation Of Integrals Research Articles

Cardiac diastolic maladaptation is associated with the severity of exercise intolerance in sickle cell anemia patients

This pilot study focusing on Sickle Cell Anemia (SCA) patients offers a comprehensive and integrative evaluation of respiratory, cardiovascular, hemodynamic, and metabolic variables during exercise. Knowing that diastolic dysfunction is frequent in this population, we hypothesize that a lack of cardiac adaptation through exercise might lead to premature increase in blood lactate concentrations in SCA patients, a potential trigger for acute disease complication. SCA patients were prospectively included in PHYSIO-EXDRE study and underwent a comprehensive stress test with a standardized incremental exercise protocol up to 4 mmol L−1 blood lactate concentration (BL4). Gas exchange, capillary lactate concentration and echocardiography were performed at baseline, during stress test (at ∼ 2 mmol L−1) and BL4. The population was divided into two groups and compared according to the median value of percentage of theoretical peak oxygen uptake (%V˙O2peakth\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\dot{\ ext{V}}\ ext{O}}_{2peakth}$$\\end{document}) at BL4. Twenty-nine patients were included (42 ± 12 years old, 48% of women). Most patients reached BL4 at low-intensity exercise [median value of predicted power output (W) was 37%], which corresponds to daily life activities. The median value of %V˙O2peakth\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\dot{\ ext{V}}\ ext{O}}_{2peakth}$$\\end{document} at BL4 was 39%. Interestingly, diastolic maladaptation using echocardiography during stress test along with hemoglobin concentration were independently associated to early occurrence of BL4. As BL4 occurs for low-intensity exercises, SCA patients may be subject to acidosis-related complications even during their daily life activities. Beyond assessing physical capacities, our study underlines that diastolic maladaptation during exercise is associated with an early increase in blood lactate concentration.

Equipment design and parameters recommendation of rubber modified 3D printed asphalt in pavement maintenance

As an advanced technology for pavement crack maintenance with high automation level, high precision and high efficiency, 3D asphalt printing technology can effectively improve worker safety and ensure the stability of maintenance quality. In order to optimize the printing parameters of rubber modified 3D printed asphalt (R-3DPA), a three-axis asphalt 3D printer was developed in this study through the design and selection of each component, and it was used for the 3D printing of R-3DPA strips, layers, and structures. Based on the comparison of continuity, uniformity, and width of R-3DPA strips, the recommended extrusion nozzle diameter, printing temperature, and printing speed parameter combinations were superiorly selected. According to the analysis of filling degree, width error and thickness of R-3DPA layers, the optimal printing strip width was recommended. Through the evaluation of integrity, surface characteristics and accuracy of R-3DPA structures, the suitable printing layer thickness was determined. The test results showed that the three-axis asphalt 3D printer can be used to measure the parameters of R-3DPA, and the printing accuracy and scale meet the requirements. The recommended parameters for R-3DPA are an extrusion nozzle diameter of 2 mm, a printing temperature of 180 °C, a printing speed of 20 mm/s, a printing strip width of 2.25 mm and a printing layer thickness of 0.4 mm, resulting in structures with good integrity and precision.

Systematic Development of a Novel Laser-Sintering Machine with Roving Integration and Sustainability Evaluation

Systematic Development of a Novel Laser-Sintering Machine with Roving Integration and Sustainability Evaluation

Systematic evaluation of integration between China's digital economy and sports industry: Two-stage grey relational analysis and vector autoregressive model.

The development of the digital economy constitutes a key component of China's endeavors to advance towards "Digital China." The sports industry functions as a new catalyst for high-quality economic growth. This study systematically evaluated the integration between these two sectors. First, we conducted two levels of grey relational analysis to assess their integration between 2016 and 2021. Second, we conducted a VAR analysis to determine whether their integration between 2009 and 2021 represents a causal relationship. At the macro level, the grey relational analysis reveals that the sports industry (grade = 0.770) ranked second among China's eight key economic sectors in terms of digital economy integration. At the meso level, a wide variation (ranging from 0.606 to 0.789) existed in the grade of integration between the digital economy and the sub-sectors of the sports industry. According to the VAR model, the digital economy does not Granger cause (p = 0.344) the growth of the sports industry. This study yielded two added values to the existing literature: First, there exists a sectoral imbalance in the digitization process; second, the explosive growth of the sports industry was not primarily caused by the digital economy. Accordingly, the "sports + digital" complex is still in the first wave of technological integration. We propose three policy recommendations, namely, sectoral synergistic development, overtaking via esports IP, and new economy and new regulation. Collectively, these findings provide updated insights for the digital transformation towards "building a leading sports nation" and "Digital China."

An in Vitro Comparative Evaluation for Internal and Marginal Integrity and the Degree of Monomer Conversion of Alkasite Restorative Material

An in Vitro Comparative Evaluation for Internal and Marginal Integrity and the Degree of Monomer Conversion of Alkasite Restorative Material

Formation integrity evaluation for geosequestration of CO2 in depleted petroleum reservoirs under cyclic stress conditions

The geological storage of carbon dioxide (CO2), also referred to as CO2 geosequestration, represents one of the most promising options for reducing greenhouse gases in the atmosphere. However, most of the time, CO2 is captured with small amounts of other industrial gases such as sulphur dioxide (SO2) and hydrogen sulphide (H2S), which might be compressed together and stored in depleted petroleum reservoirs or aquifers. Moreover, during CO2 geosequestration in reservoirs, pressure variations during injection could force some amount of CO2 (with or without other acid gas impurities) into the caprock; thereby, altering the petrophysical, geochemical, and geomechanical properties of the caprock. Thus, the brittleness index of the reservoir and caprock might be impacted during CO2 geosequestration due to the chemical reactions between the rock minerals and the formation fluid. Furthermore, to meet the world net-zero carbon target, the promotion of CO2 utilization is paramount. This could be possible by developing an effective technology for cyclic CO2 geosequestration (with or without gas impurities). Therefore, studies on the co-injection of CO2 with other acid gases from industrial emissions, their withdrawal from the porous medium, and their impact on reservoir and caprock integrity are paramount. In this study, a dual-tubing string well completion technology was designed for cyclic injection and withdrawal of CO2 (with or without another acid gas), and numerical simulations were performed using TOUGHREACT codes, to model the cyclic process and investigate the co-injection of SO2 and H2S (separately) with CO2 in sandstone formations overlain by shale caprock. A novel technique of converting the volume fraction of minerals to their weight fraction was developed in this study, to evaluate the brittleness index of the sandstone reservoir and shale caprock during CO2 geosequestration. The findings of the study indicate that the porosity and permeability increase for the CO2 only and CO2–H2S injection cases, in the shale caprock; while for the CO2–SO2 injection case, porosity and permeability only decreased in the layers of the shale caprock contacted by SO2 and due to anhydrite precipitation. In all the injection cases, the porosity and permeability of the sandstone reservoir decreased in a few layers directly below the perforation interval of the production zone. However, in other regions in the sandstone reservoir, the porosity and permeability increased for the CO2 only and CO2–H2S injection cases. In contrast, for the CO2–SO2 co-injection case, porosity and permeability decreased in the layers of the sandstone rock contacted by SO2. In all the CO2 geosequestration cases, the brittleness of the shale and sandstone rocks investigated decreased slightly, except in the CO2–SO2 co-injection case where the brittleness of the sandstone rock decreased significantly. Based on the mineralogical composition of the formations in this study, co-injection of SO2 gas with CO2 gas, only decreased the brittleness index of the shale caprock slightly, but significantly decreased the brittleness of the sandstone reservoir.

The updates in Libcint 6: More integrals, API refinements, and SIMD optimization techniques.

Libcint is a library designed for the evaluation of analytical integrals for Gaussian type orbitals. It prioritizes simplicity, ease of use, and efficiency for the development of quantum chemistry programs. In the release of version 6.0, Libcint supports the computation of integrals for various operators, such as overlap, Coulomb, Gaunt, Breit, attenuated Coulomb, Slater-type geminals, and Yukawa potential, as well as arbitrary orders of derivatives for these operators. To enhance the usability of the library, Libcint provides a uniform function signature for all integral functions. A code generator is included to automate the implementation of new integrals. To achieve better performance on modern central processing unit architectures, the library employs explicit single instruction multiple data parallelization in the code implementation.

Designing of a new transdermal antibiotic delivery polymeric membrane modified by functionalized SBA-15 mesoporous filler

A new drug delivery system using an asymmetric polyethersulfone (PES) membrane modified by SBA-15 and glutamine-modified SBA-15 (SBA-Q) was prepared in this study by the aim of azithromycin delivery enhancement in both in vitro and ex vivo experiments. The research focused on optimizing membrane performance by adjusting critical parameters including drug concentration, membrane thickness, modifier percentage, polymer percentage, and pore maker percentage. To characterize the fabricated membranes, various techniques were employed, including scanning electron microscopy, water contact angle, and tensile strength assessments. Following optimization, membrane composition of 17% PES, 2% polyvinylpyrrolidone, 1% SBA-15, and 0.5% SBA-Q emerged as the most effective. The optimized membranes demonstrated a substantial increase in drug release (906 mg/L) compared to the unmodified membrane (440 mg/L). The unique membrane structure, with a dense top layer facilitating sustained drug release and a porous sub-layer acting as a drug reservoir, contributed to this improvement. Biocompatibility assessments, antibacterial activity analysis, blood compatibility tests, and post-diffusion tissue integrity evaluations confirmed the promising biocompatibility of the optimized membranes. Moreover, long-term performance evaluations involving ten repeated usages underscored the reusability of the optimized membrane, highlighting its potential for sustained and reliable drug delivery applications.

Topological twists of massive SQCD, Part I

We consider topological twists of four-dimensional N=2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal {N}=2$$\\end{document} supersymmetric QCD with gauge group SU(2) and Nf≤3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N_f\\le 3$$\\end{document} fundamental hypermultiplets. The twists are labelled by a choice of background fluxes for the flavour group, which provides an infinite family of topological partition functions. In this Part I, we demonstrate that in the presence of such fluxes the theories can be formulated for arbitrary gauge bundles on a compact four-manifold. Moreover, we consider arbitrary masses for the hypermultiplets, which introduce new intricacies for the evaluation of the low-energy path integral on the Coulomb branch. We develop techniques for the evaluation of these path integrals. In the forthcoming Part II, we will deal with the explicit evaluation.

High-Temperature and High-Pressure Tribological Properties of Siliconized Graphite for Water-Lubricated Thrust Bearing Application in Main Coolant Pump

The effect of the microstructure of siliconized graphite on tribological properties is investigated by using a high-temperature and high-pressure water-lubricated tribometer on a self-mated ring-on-ring configuration under an applied load of 500–1500 N with a spindle speed of 100–5000 rpm in both 90 °C (5 MPa) and 25 °C (1 MPa) water environments, respectively. The Stribeck curves measurement and continuous wear tests are performed and analyzed in both water environments. The wear behaviors of the graphite, SiC, and free-silicon phases in siliconized graphite are demonstrated to explore the wear mechanism. The larger wear depths of a low-worn surface roughness on the three phases contribute to the boundary lubrication. The shallower wear depths are observed on the SiC and Si phases under the mixed lubrication, corresponding to partial contact wear of surface asperities. The wavy surface of the SiC phase and uniform flow-oriented striae of the Si phase are attributed to hydrodynamic lubrication, caused by full water film scouring the worn surface. Finally, an integrated evaluation method of G duty parameters is successfully used to identify the lubrication regimes of siliconized graphite from the boundary, mixed, to hydrodynamic lubrications for a water-lubricated thrust bearing application in the main coolant pump of a nuclear power plant.

HOG-CNN based evaluation of cement integrity using 2D dispersion curves from an experimental through tubing logging setup

In oil wells, adequate cementation is essential to guarantee that the well has support for the casing and is able to isolate the well from groundwater. Operations known as Plugging & Abandonment (P&A) must carry out inspections in the cement layer of the well to ensure that the bond quality of the cement with the formation and the hydraulic isolation is adequate before well sealing. The interpretation of data logs during the decommissioning processes is made exclusively for a petrophysicists team, which makes the process susceptible to human errors. Furthermore, it requires a lot of analysis time, increasing the search for alternative solutions that help reduce errors in the interpretation of data logs. So far, the use of machine learning has proven to be a strong candidate in this search. This paper deals with frequency domain images (dispersion curves and Cepstrum) that are acquired from acoustic pressure signals obtained in the time domain and along the vertical axis of an experimental setup. These images are used to train machine learning models to test and compare the accuracies obtained. An adjustment of the hyperparameters was carried out to find those that best describe the simulated experimental characteristics. Furthermore, the convolution neural network (CNN) model was combined with the oriented gradient histogram technique (HOG) to verify its efficiency by analyzing experimental data. Two different databases were used in this work, one with 130 samples relating to the average results of the four hydrophones used in the experiment and one with 520 samples relating to all results. The results found demonstrated that when using the dispersion curves as input with the CNN the accuracy hits 100%. Other combinations of models were also tested hitting similar results. This article contributes to the current research scenario as it presents an innovative combination of machine learning techniques applied to the oil and gas field (HOG-CNN) with the proposal to compare different types of databases, such as using Cepstrum instead of dispersion curves and image processing.

Deep margin elevation in class II cavities: A comparative evaluation of microleakage and interface integrity using confocal laser microscopy and scanning electron microscopy

Aim: This study aims to evaluate the microleakage between the gingival seat and base material and to assess the interface integrity between the base material and overlying composite in class II cavities restored using deep margin elevation. Materials and Methods: Thirty maxillary molars (n = 30) were taken, and class II cavities were prepared with a gingival seat extending below the cementoenamel junction. These teeth were divided into three groups for subgingival margin elevation using different materials: Group A (n = 10) – flowable composite, Group B (n = 10) – glass ionomer cement (GIC), and Group C (n = 10) – GIC with nanohydroxyapatite (GIC n-HAp). The remaining cavities were restored with bulk-fill composite. After undergoing 1000 thermocycling cycles, half of the samples were examined for microleakage using confocal laser microscopy, and the other half were assessed for interface integrity using scanning electron microscopy. Microleakage was statistically analyzed by one-way ANOVA, and interface integrity was analyzed by Kruskal–Wallis tests. Results: The study found that GIC n-HAp exhibited significantly lower microleakage between the base material and gingival seat than flowable composite and GIC. However, regarding interface integrity between the base material and bulk-fill composite, flowable composite, and GIC outperformed GIC n-HAp. Conclusions: Incorporating n-HAp into GIC effectively reduced microleakage at the dentin-base material interface. However, the interface integrity between GIC n-HAp and the composite poses a challenge.

Evaluation of RPV closure head penetration integrity considering fitting and residual stresses

To ensure the structure integrity of the Reactor Pressure Vessel (RPV), the main challenge is the embrittlement of beltline material. However, the stress is more complex for the regions of Closure Head Penetration (CHP). Feedback of leakage at the CHP has been found during in-service inspection. Although the detailed mechanical evaluation of the RPV head and the CHP has been carried out by many international institutions, there are limited studies to concern structure integrity of CHP tube. The systematic analysis of the influence of material strength matching, assemble stress, the Welding Residual (WR) stress and work pressure load on the fracture is also limited. In this paper, the systematic influence of these factors is analyzed, and the distribution characteristics of Stress Intensity Factor (SIF) and the crack propagation characteristics are studied. The 2D model and accurate 3D model are carried out using the finite element method. The results show that the WR stress on the outer surface of the CHP and the area adjacent to the weld is larger than the yield strength of the material. There is a gap between the RPV and the upper part of the CHP. The attenuation rate of the WR stress in the outlet direction of RPV is lower than that in the inlet direction, so cracks are more likely to occur in the out of direction. The influence of WR stress on the circumferential stress distribution and fracture parameters in the wall thickness direction of CHP is bigger than the influence of assemble load and design condition load. However, the overall stress of CHP is low. The SIF values along the crack front have an asymmetric distribution, and the SIF value is very small. As the fatigue crack propagation life is much longer than the assumed limit in the design lifetime, the risk of fracture and crack fatigue propagation caused by mechanical stress is low.

An appraisal of statistical and probabilistic models in highway pavements

Accurate performance prediction is crucial for safe and efficient travel on highway pavements. Within pavement engineering, statistical models play a pivotal role in understanding pavement behavior and durability. This comprehensive study critically evaluates a spectrum of statistical models utilized in pavement engineering, encompassing mechanistic-empirical, Weibull distribution, Markov chain, regression, Bayesian networks, Monte Carlo simulation, artificial neural networks, support vector machines, random forest, decision tree, fuzzy logic, time series analysis, stochastic differential equations, copula, hidden semi-Markov, generalized linear, survival analysis, response surface methodology and extreme value theory models. The assessment meticulously examines equations, parameters, data prerequisites, advantages, limitations, and applicability of each model. Detailed discussions delve into the significance of equations and parameters, evaluating model performance in predicting pavement distress, performance assessment, design optimization, and life-cycle cost analysis. Key findings emphasize the critical aspects of accurate input parameters, calibration, validation, data availability, and model complexity. Strengths, limitations, and applicability across various pavement types, materials, and climate conditions are meticulously highlighted for each model. Recommendations are outlined to enhance the effectiveness of statistical models in pavement engineering. These suggestions encompass further research and development, standardized data collection, calibration and validation protocols, model integration, decision-making frameworks, collaborative efforts, and ongoing model evaluation. Implementing these recommendations is anticipated to enhance prediction accuracy and enable informed decision-making throughout highway pavement design, construction, maintenance, and management. This study is anticipated to serve as a valuable resource, providing guidance and insights for researchers, practitioners, and stakeholders engaged in asphalt engineering, facilitating the effective utilization of statistical models in real-world pavement projects.

A systematic review of evaluation and program planning strategies for technology integration in education: Insights for evidence-based practice

A systematic review of evaluation and program planning strategies for technology integration in education: Insights for evidence-based practice

Early Blood-Brain Barrier Impairment as a Pathological Hallmark in a Novel Model of Closed-Head Concussive Brain Injury (CBI) in Mice.

Concussion, caused by a rotational acceleration/deceleration injury mild enough to avoid structural brain damage, is insufficiently captured in recent preclinical models, hampering the relation of pathophysiological findings on the cellular level to functional and behavioral deficits. We here describe a novel model of unrestrained, single vs. repetitive concussive brain injury (CBI) in male C56Bl/6j mice. Longitudinal behavioral assessments were conducted for up to seven days afterward, alongside the evaluation of structural cerebral integrity by in vivo magnetic resonance imaging (MRI, 9.4 T), and validated ex vivo by histology. Blood-brain barrier (BBB) integrity was analyzed by means of fluorescent dextran- as well as immunoglobulin G (IgG) extravasation, and neuroinflammatory processes were characterized both in vivo by positron emission tomography (PET) using [18F]DPA-714 and ex vivo using immunohistochemistry. While a single CBI resulted in a defined, subacute neuropsychiatric phenotype, longitudinal cognitive testing revealed a marked decrease in spatial cognition, most pronounced in mice subjected to CBI at high frequency (every 48 h). Functional deficits were correlated to a parallel disruption of the BBB, (R2 = 0.29, p < 0.01), even detectable by a significant increase in hippocampal uptake of [18F]DPA-714, which was not due to activation of microglia, as confirmed immunohistochemically. Featuring a mild but widespread disruption of the BBB without evidence of macroscopic damage, this model induces a characteristic neuro-psychiatric phenotype that correlates to the degree of BBB disruption. Based on these findings, the BBB may function as both a biomarker of CBI severity and as a potential treatment target to improve recovery from concussion.

Big data resolving using Apache Spark for load forecasting and demand response in smart grid: a case study of Low Carbon London Project

Using recent information and communication technologies for monitoring and management initiates a revolution in the smart grid. These technologies generate massive data that can only be processed using big data tools. This paper emphasizes the role of big data in resolving load forecasting, renewable energy sources integration, and demand response as significant aspects of smart grids. Meters data from the Low Carbon London Project is investigated as a case study. Because of the immense stream of meters' readings and exogenous data added to load forecasting models, addressing the problem is in the context of big data. Descriptive analytics are developed using Spark SQL to get insights regarding household energy consumption. Spark MLlib is utilized for predictive analytics by building scalable machine learning models accommodating meters' data streams. Multivariate polynomial regression and decision tree models are preferred here based on the big data point of view and the literature that ensures they are accurate and interpretable. The results confirmed the descriptive analytics and data visualization capabilities to provide valuable insights, guide the feature selection process, and enhance load forecasting models' accuracy. Accordingly, proper evaluation of demand response programs and integration of renewable energy resources is accomplished using achieved load forecasting results.

Monitoring the crack lengths in composite lap joints under cyclic loading

Abstract Monitoring crack lengths in composites lap joints is crucial for the evaluation of safety and integrity in composite structures. The crack lengths in adhesively bonded single-lap and double-strap joints were characterized by using epoxy adhesive containing aligned graphene. The epoxy adhesive was prepared by adding graphene to epoxy resin and then aligning the graphene through an electrical field. The incorporation of 0.15wt% aligned graphene can have the epoxy adhesive being electrically conductive. The single-lap and double-strap joints containing the graphene epoxy adhesive were tested under cyclic loading. During the cyclic tests, the crack extension and electrical resistance were measured concurrently. In addition, the electrical resistance model expressed in terms of the crack lengths for the lap joints was proposed in the examination. The results illustrated that the crack length and the electrical resistance increased as the cyclic number increased. Moreover, the experimental resistance variation associated with the increased crack length can be described using the electrical resistance model. Thus, the functionalized epoxy adhesive containing aligned graphene can be employed for effectively detecting the length of cracks in composite lap joints under cyclic loading.

Combined diffusion tensor imaging and quantitative susceptibility mapping to characterize normal-appearing white matter in self-limited epilepsy with centrotemporal spikes.

In brain development, Myelination is the characteristic feature of white matter maturation, which plays an important role in efficient information transmitting. The white matter abnormality has been reported to be associated with self-limited epilepsy with centrotemporal spikes (SeLECTS). This study aimed to detect the altered white matter region in the SeLECTS patients by the combination of diffusion tensor imaging (DTI) and quantitative susceptibility mapping (QSM) technique. 27 children with SeLECTS and 23 age- and gender-matched healthy children were enrolled. All participants were scanned with 3.0-T MRI to acquire the structure, diffusion and susceptibility-weighted data. The susceptibility and diffusion weighted data were processed to obtain quantitative susceptibility map and fraction anisotropy (FA) map. Then voxel-wise tract-based spatial statistics (TBSS) were used to analyze quantitative susceptibility and FA data. Both DTI and QSM revealed extensive white matter alterations in the frontal, parietal, and temporal lobes in SeLECTS patients. The overlapped region of DTI and QSM analyses was located in the fiber tracts of the corona radiata. The FA values in this overlapped region were negatively correlated with the magnetic susceptibility values. Our results suggest that TBSS-based QSM can be employed as a novel approach for characterizing alterations in white matter in SeLECTS. And the combination of QSM and DTI can provide a more comprehensive evaluation of white matter integrity by utilizing different biophysical features.

Security evaluation of China's indium industrial chain: Perspective on substance flow throughout the whole life cycle

As the world's largest supplier of primary indium, China's indium industrial chain structure and demand change affect global supply. It is necessary to evaluate the security of China's indium industrial chain and determine the reasons that affect security. The past substance flow analysis (SFA) of indium and mineral industrial chain security evaluation has problems such as a lack of timeliness, a single dimension mainly focusing on the upstream, and simple evaluation methods. In this paper, based on the SFA, an integrated evaluation system for the whole life cycle is constructed from 2000 to 2022 according to mineral industrial chain security characteristics. The results show that since introducing liquid crystal in 2003, China's indium industrial chain security level has been low despite a slight increase. Although China has gradually broken through the production technology of high-purity indium and indium tin oxide (ITO) targets, the large consumption and export of refined indium has reduced China's indium metal stock to 2214 t, while the resource reserves advantage is also diminishing. Mass consumption has also led China to import more ores, while China still imports high-end products from other countries with high import source concentrations. The pollutants emitted by the large production and the declining environmental governance level pose a significant environmental threat. Finally, suggestions for strengthening international cooperation, increasing technological research, establishing a reserve system, risk monitoring mechanisms, and strict emission standards can improve China's indium industrial chain security.