Static Techniques Research Articles

Reservoir Static Modelling towards Safe CO2 Storage in Depleted Oil Reservoirs of ‘CRK’ Field, Niger Delta, Nigeria

Geological carbon storage (GCS) is gradually gaining acceptance as the technology of highest repute for the mitigation against greenhouse gas effect. This involves the injection and long-term or permanent storage of carbon dioxide (CO2) in subsurface geological formations. The development of a robust 3D reservoir model then becomes necessary to understand the facies changes and the petrophysical properties distribution of candidate CO2 storage reservoirs. This study attempts the use of static modelling technique to investigate the depleted oil and gas reservoirs of ‘CRK’ field in the Niger Delta sedimentary Basin as a potential CO2 storage site. Using an integrated approach of 3D seismic and a suit of well logs from the study area, two reservoir sands (D10C0 and D6200) were mapped. 3D static modelling of discrete and continuous property distribution of the reservoirs revealed the reservoirs are composed majorly of clean sands with water saturation ranging from 8 to 75%. The average porosity and permeability values are between 20 to 29% and 250 to 890mD respectively. A theoretical storage capacity of 24.85Mt is estimated for the two reservoirs combined, while the median effective storage capacity is 6.22Mt. Comparison of the results obtained in the study with recommended standard values show the reservoirs are suitable for CO2 storage. The property models constructed can serve as primary input for dynamic simulation of the oilfield in future studies.

Estimation of transverse thermoelastic properties of polyimide fibers based on micromechanical models

The determination of the thermoelastic properties of polyimide (PI) fibers is important for their applications, however, these properties are difficult to measure directly, especially the transverse thermoelastic properties. Here, the transverse thermoelastic properties of PI fibers, including transverse Young's modulus (2.12 GPa), shear modulus (0.94 GPa), Poisson's ratio (0.05), and coefficient of thermal expansion (45.68 μm/m°C), were estimated by combining dynamic and static thermo-mechanical techniques, as well as various relevant micromechanical models. The transverse Young's modulus of PI fibers was only 1/46th of the longitudinal one, and the transverse coefficient of thermal expansion of PI fibers was positive, unlike the longitudinal one, which was negative, showing the typical anisotropy of PI fibers. Finally, the thermoelastic properties of the PI fibers were in turn used to predict the thermoelastic behavior of the PI fiber-reinforced composites, thus validating their effectiveness.

PERFORMANCE OF SCREW HORIZONTAL AND BRIDGE LINKAGE PHOTOVOLTAIC ARRAY CONFIGURATIONS

Due to partial shading effects on the productivity of solar panels which in turn negatively impacts the performance characteristics of photovoltaic systems, researchers work on different studies to overcome this phenomenon and improve solar system productivity. Therefore, this study aims to investigate different techniques to enhance the output power, fill factor, and efficiency of the PV system by reducing the number of local maximum power peaks, power losses, and mismatch losses. The configurations include a novel static reconfiguration technique, called a Screw Horizontal photovoltaic array, and a recently developed technique known as a Bridge Linkage array. Both of these are modeled using MATLAB/Simulink software and examined during six shading patterns. The novelty of this study is that we combined the above static reconfiguration technique with another modern technique called blocking and bypass diode technology to prevent the effect of reverse current and hotspot phenomena respectively. According to the results, the Bridge Linkage configuration performs the most efficiently under partial shading conditions compared to the Screw horizontal PV array configuration.

Tree Crown Detection using UAV-captured High-Resolution Aerial Images for Baghdad University Campus

The research paper's objective is to develop an automated system that uses high-resolution aerial images captured by Unmanned Aerial Vehicles (UAVs) to accurately detect and analyze tree crowns on the Baghdad University campus. This analysis of tree crowns is crucial for assessing vegetation health and distribution in urban areas, with applications in urban planning, ecology, and environmental studies. The proposed system utilizes computer vision and machine learning techniques to detect and delineate tree crowns, facilitating objective analysis of tree canopy coverage. The study employed a Phantom Four drone flying at a height of 55 meters with an 80% overlap in image coverage. Ground control points were established using the Topcon_HIPER2 device and Static GPS Surveying Techniques. The flight plan was designed with PIX4Dcapture software, and the resulting ortho-map had a 2 cm resolution. The research used the YOLOv3 artificial intelligence technique for tree detection after training a customized dataset. The model achieved impressive performance metrics, including a low loss function value of 0.023, a high SDC value of 0.984, and a robust Jaccard Index value of 0.943.

SoK: Analysis Techniques for WebAssembly

WebAssembly is a low-level bytecode language that enables high-level languages like C, C++, and Rust to be executed in the browser at near-native performance. In recent years, WebAssembly has gained widespread adoption and is now natively supported by all modern browsers. Despite its benefits, WebAssembly has introduced significant security challenges, primarily due to vulnerabilities inherited from memory-unsafe source languages. Moreover, the use of WebAssembly extends beyond traditional web applications to smart contracts on blockchain platforms, where vulnerabilities have led to significant financial losses. WebAssembly has also been used for malicious purposes, like cryptojacking, where website visitors’ hardware resources are used for crypto mining without their consent. To address these issues, several analysis techniques for WebAssembly binaries have been proposed. This paper presents a systematic review of these analysis techniques, focusing on vulnerability analysis, cryptojacking detection, and smart contract security. The analysis techniques are categorized into static, dynamic, and hybrid methods, evaluating their strengths and weaknesses based on quantitative data. Our findings reveal that static techniques are efficient but may struggle with complex binaries, while dynamic techniques offer better detection at the cost of increased overhead. Hybrid approaches, which merge the strengths of static and dynamic methods, are not extensively used in the literature and emerge as a promising direction for future research. Lastly, this paper identifies potential future research directions based on the state of the current literature.

Does corruption sand the wheels of sustainable development? Evidence through green innovation

AbstractThis study investigates the impact of corruption on green innovation, as corruption may impede or foster green innovation in developing economies due to their weak governance systems. We develop a dataset of Chinese non‐financial firms listed between 2007 and 2020 and apply static and dynamic regression techniques. The results indicate a highly significant negative association between corruption and green innovation. This supports the notion that corruption culture reduces corporate legitimacy concerns (institutional theory), increases managerial rent‐seeking (agency theory), and hinders green innovation, thus impeding sustainable development and supporting the “sand the wheels” hypothesis. Our analysis also reveals that corruption's negative impact on green innovation is particularly significant for firms with lower media and analyst coverage, non‐state‐owned firms, and firms in heavy‐polluting industries. These results are robust to alternate proxies of green innovation and corruption as well as econometric specifications that account for endogeneity issues and industry, region, and time‐fixed effects.

Demographic review of aesthetic surgery for patients with facial palsy.

This study analyzed the demographic characteristics of patients with facial palsy who were treated using either dynamic or static procedures. This study aimed to compare the frequency of procedure implementation and age distribution between the two groups. This study retrospectively analyzed the medical records of patients treated for facial palsy at a single institution from 2014 to 2022. Among cases included in our study, dynamic procedures involved cross-facial nerve graft and latissimus dorsi or gracilis muscle flap transfer. Static procedures included gold weight insertion, canthopexy, browlift, and thread lift/static slings. Among the 31 patients included in our study, eight (25.8%) incorporated dynamic techniques, and the average age of patients was 44.75 years (range, 24-68 years) with a male to female ratio of 1:4. The remaining 23 patients (74.2%) underwent a static procedure, of which the average age was 59.17 years (range, 23-81 years) which was statistically significantly higher than the average age of 44.75 of dynamic patients (p= 0.013). Regarding the timing of treatment after diagnosis, no patient underwent dynamic procedures more than 20 years after initial diagnosis. A greater diversity in the timing of treatment was observed in the static group. All patients who underwent dynamic procedures were treated using static procedures during the study period. Because aesthetics-based static techniques are typically quick outpatient procedures that can be performed under local anesthesia, our study shows that these are often preferred treatments for all age groups, especially for debilitated or older patients. Further research is required to investigate the long-term functional outcomes of these surgical techniques in a wider population of patients.

Automated Grading and Feedback Tools for Programming Education: A Systematic Review

We conducted a systematic literature review on automated grading and feedback tools for programming education. We analysed 121 research papers from 2017 to 2021 inclusive and categorised them based on skills assessed, approach, language paradigm, degree of automation, and evaluation techniques. Most papers assess the correctness of assignments in object-oriented languages. Typically, these tools use a dynamic technique, primarily unit testing, to provide grades and feedback to the students or static analysis techniques to compare a submission with a reference solution or with a set of correct student submissions. However, these techniques’ feedback is often limited to whether the unit tests have passed or failed, the expected and actual output, or how they differ from the reference solution. Furthermore, few tools assess the maintainability, readability, or documentation of the source code, with most using static analysis techniques, such as code quality metrics, in conjunction with grading correctness. Additionally, we found that most tools offered fully automated assessment to allow for near-instantaneous feedback and multiple resubmissions, which can increase student satisfaction and provide them with more opportunities to succeed. In terms of techniques used to evaluate the tools’ performance, most papers primarily use student surveys or compare the automatic assessment tools to grades or feedback provided by human graders. However, because the evaluation dataset is frequently unavailable, it is more difficult to reproduce results and compare tools to a collection of common assignments.

Experimental evaluation of the plunger technique: A method of cyclic manual aspiration thrombectomy for treatment of acute ischemic stroke.

Mechanical thrombectomy via direct aspiration is a rapid treatment for acute ischemic stroke. This method often results in the partial ingestion of the clot or "corking" of the catheter tip. Cyclic aspiration may take advantage of the mechanical properties of the clot, resulting in greater clot ingestion and overall procedure success. An in vitro analysis was performed comparing static and cyclic (plunger technique) aspiration. Embolus analogs were used to create occlusions in a mock circulatory flow loop, and one aspiration attempt (first pass effect) using either a static or plunger technique was performed. The percent ingestion of each embolus analog was recorded for each trial. Static aspiration for 0% and 50% hematocrit embolus analogs resulted in ingestions of 12.8 ± 4.6% and 15.1 ± 10.0%, respectively, while plunger technique (cyclic) aspiration resulted in 15.8 ± 7.3% and 34.4 ± 19.5% ingestion. Complete ingestion was observed only with 50% hematocrit analogs, occurring in 30% of plunger and 10% of static cases. Statistical differences were determined between the two aspiration techniques for the 50% hematocrit samples, with the plunger technique yielding significantly more ingestion. In addition, the plunger technique was shown to maintain a negative vacuum pressure throughout the duration of cyclic plunging. The plunger technique for manual cyclic aspiration resulted in higher rates of complete ingestion and greater average % ingestions when compared to static aspiration. Increased clot ingestion can result in a higher rate of complete reperfusion during the first aspiration attempt, maximizing the number of patients with good clinical outcomes.

Porównanie rozkładów dawek dla napromieniania mózgu dla technik dynamicznych IMRT i VMAT oraz techniki 3DCRT

Whole-brain radiotherapy is a standard treatment for many brain metastases. Whole brain irradiation is a palliative treatment aimed at improving the patient's quality of life. Historically, this procedure was most often performed using two opposing side beams. However, as patients increasingly undergo repeated radiotherapy, dynamic techniques are used to minimize doses to critical organs. The study aimed to compare techniques used in whole brain irradiation in terms of dose analysis in critical organs (OAR, Organs at Risk). A group of 5 patients with brain metastases were qualified for the study. For each patient, a treatment plan was prepared using a static three-dimensional conformal radiotherapy technique (3DCRT) and two plans using a dynamic technique (IMRT, Intensity Modulated Radiation Therapy), and (VMAT, volumetric modulated arc therapy). All plans were compared with each other in terms of isodose coverage of 98% and 95% of the planned irradiation volume (PTV, Planning Target Volume) and the dose in 2% of the PTV volume, maximum doses in the OAR: lenses, eyes and in the left and right optic nerve. Mean maximum lens dose values ​​were below tolerance dose values but with better lens protection in favor of dynamic techniques; the average value of the maximum dose for the eyes and optic nerve was very similar consistent with the tolerance doses. Dynamic techniques enable better coverage of the PTV volume with the administered dose and minimize doses administered to critical organs.

Novel Technique of Interproximal Enamel Reduction Based on Computer-Aided Navigation Technique-An In Vitro Study.

The aim of this study was to analyze and compare the accuracy of a novel interproximal enamel reduction (IPR) technique based on a computer-aided static navigation technique with respect to a conventional free-hand-based technique for interproximal enamel reduction. Twenty anatomical-based experimental cast models of polyurethane were randomly distributed into the following IPR techniques: IPR technique based on computer-aided static navigation technique (n = 10) (GI) for Group A and conventional free-hand-based technique for the IPR (n = 10) (FHT) for Group B. The anatomical-based experimental cast models of polyurethane randomly assigned to the GI study group were submitted for a preoperative 3D intraoral surface scan; then, datasets were uploaded into 3D implant-planning software to design virtual templates for the interproximal enamel reduction technique. Afterward, the anatomical-based experimental cast models of polyurethane of both GI and FHT study groups were subjected to a postoperative digital impression by a 3D intraoral surface scan to compare the accuracy of the interproximal enamel reduction techniques at the buccal (mm), lingual/palatal (mm), and angular (◦) levels using the Student t-test. Statistically significant differences between the interproximal enamel reduction technique based on the computer-aided static navigation technique and the conventional free-hand-based technique for the interproximal enamel reduction at the buccal (p = 0.0008) and lingual/palatal (p < 0.0001) levels; however, no statistically significant differences were shown at the angular level (p = 0.1042). The interproximal enamel reduction technique based on computer-aided static navigation technique was more accurate than the conventional free-hand-based technique for interproximal enamel reduction.

An IoT-Based Water Leakage Detection and Localization System

In this research, we present a proposed Internet of Things based model, which we have named iWaLDeL, for the detection and localization of water leakages which we simulated for the Ghana Water Company (GWC) pipe network, using YF-S201 Flow Rate Sensors and Static Leak Detection techniques. Through an extensive review of existing methods, the research highlights the limitations of traditional detection approaches and emphasizes the potential of modern technologies. The iWaLDeL system harnesses the power of IoT devices, deploying an array of strategically placed sensors capable of detecting leakages and pressure variations. These sensors form a distributed network which communicates with a central hub, ensuring comprehensive coverage of the monitored area. Crucially, the research delves into the innovative aspect of leak localization. By combining data from multiple sensors and pipes, the system can estimate the precise location of a leakage following a mathematical model we developed. This localization capability significantly reduces the time required for maintenance teams to address leakage issues, minimizing water loss and further damages. To validate its effectiveness, the system was prototyped and tested, which demonstrated a successful leak detection and localization, showcasing its adaptability in both residential and commercial settings. The system’s seamless integration with existing smart infrastructure enhances its feasibility for real-world implementation.

Comparative dynamics analysis of the environmental policy efficacy in a nonlinear Cournot duopoly with differentiated goods and emission charges

The price and the exchanged quantity volatility observed in real-world markets may be explained, according to the existing empirical literature, in terms of the endogenous fluctuations generated by the presence of nonlinearities. We then replace with a sigmoid adaptive best response mechanism the linear partial adjustment best response rule considered in Mamada and Perrings (2020), where the effect produced by quadratic emission charges on the dynamics of a Cournot duopoly model with homogeneous goods was investigated. Moreover, the sigmoid nonlinearity, in addition to being well suited to describe the bounded output variations caused by physical, historical and institutional constraints, makes the model able to generate interesting, non-divergent dynamic outcomes, despite the linearity of the demand function and of marginal costs. Additionally, following the suggestion in Mamada and Perrings (2020), we deal with the more general case of differentiated products. Beyond analytically studying the stability of the unique steady state, coinciding with the Nash equilibrium, and the effect produced by the main parameters on the stability region, we perform two comparative dynamics investigations which allow to evaluate the environmental policy efficacy when the Nash equilibrium is not stable and thus the standard comparative statics technique does not fit for the purpose. In particular, the former analysis, which is based on a comparison of emissions for different levels of charges, shows that, also in case the Nash equilibrium is not stable, the considered environmental policy may be effective both with complements and with substitutes. The latter investigation, consisting in a comparison of emissions along non-stationary trajectories and along the equilibrium path, in the proposed experiments highlights that emissions are larger along non-stationary trajectories. This gives us the opportunity to show how to act on the level of the asymptotes of the sigmoid adjustment mechanism to reduce output variations, reaching at one time a complete stabilization of the system and limiting pollution.

Comprehensive analysis of line losses and valuation of energy savings in optimized photovoltaic array subjected to partial shadings

In this manuscript, an attempt is made to reconfigure the conventional total cross-tied (TCT) array through a novel optimized SuDoKu (OPSDK) static reconfiguration technique. This approach helps to reduce the line losses occurring due to increased wire length and simultaneously diminishes the adverse effects of accumulated shadings in close vicinity by diffusing it across the photovoltaic array (PVA). The MATLAB/Simulink platform is used to study the variations in the performance of various existing topologies and the proposed OPSDK PVA model under various shading scenarios such as bottom-right corner, bottom-left corner, top-right corner, top-left corner and drifted-locus centre. The performance is monitored with regard to the specific characteristics viz., % fill-factor, mismatch power losses, % power loss, % efficiency, global maximum power point, maximum voltage, maximum current, local maximum power points (LMPPs), number of LMPPs, misleading power loss, current loss, voltage loss, % execution ratio, % power improvement, % thermal voltage, % power enhancement ratio, line loss and annual energy saving. Theresults show that the proposed OPSDKmethod generates 28.12852 kWh energy units per day, which is maximum when compared to other five topologies viz. SuDoKu (SDK), futoshiki SuDoKu (FSDK), skyscraper SuDoKu (SKYSDK), modified SuDoKu (MSDK), ancient chinese magic square (ACMS). Consequently, the annual income generatedby [9×9] SDK, FSDK, SKYSDK, MSDK, ACMS and OPSDK PVAs is ₹ 150,839.54, ₹ 141,514.52, ₹150,108.08, ₹ 150,751.94, ₹ 150,249.33 and ₹154,003.72, respectively, signifying that OPSDK PVA produces highest income. The extensive analysis signifies that the proposed OPSDK topology succeeds in reducing line losses by 25.62 %, 0.00 %, 37.98 %, 33.43 % and 35.49 % in comparison to SDK, FSDK, SKYSDK, MSDK and ACMS, respectively. The mismatch power losses in power output are also reduced by 643.1 W as compared to the other configurations. The OPSDK technique, thus, proves to be one of the most efficient, effective, optimised and sustainable PVA reconfiguration technique with good power savings and greater economic returns/viability.

Artificial Intelligence and Malicious Code Detection

Malicious software has become a critical cybersecurity issue due to the increasing number of threats it poses to devices and internet environments. Traditional static scanning techniques and behavior-based malware detection methods have limitations in meeting the new requirements in information security due to high false positives and false negatives. In this work, we propose a CNN convolutional neural network-based method for detecting malicious code. Practical operations were conducted using the Cuckoo sandbox system, and Python programs were utilized to preprocess analytical reports. This article presents the construction of a deep learning training model for CNN designed to identify malicious code. The model is compared with machine learning and general antivirus tools for comprehensive evaluation. Experimental verification shows that our proposed method exhibits greater advantages in comparison and achieved excellent detection results with higher feasibility. The research significance of this work is highlighted as malicious software has become a core issue in cybersecurity. The method proposed in this article provides powerful support for addressing new needs in information security. This paper emphasizes the importance of utilizing CNN-based methods in detecting malware, which can better address the limitations of traditional detection techniques. Overall, this work provides an effective solution to detect malicious code and addresses a critical cybersecurity issue.

Automatic Parallelism Management

On any modern computer architecture today, parallelism comes with a modest cost, born from the creation and management of threads or tasks. Today, programmers battle this cost by manually optimizing/tuning their codes to minimize the cost of parallelism without harming its benefit, performance. This is a difficult battle: programmers must reason about architectural constant factors hidden behind layers of software abstractions, including thread schedulers and memory managers, and their impact on performance, also at scale. In languages that support higher-order functions, the battle hardens: higher order functions can make it difficult, if not impossible, to reason about the cost and benefits of parallelism. Motivated by these challenges and the numerous advantages of high-level languages, we believe that it has become essential to manage parallelism automatically so as to minimize its cost and maximize its benefit. This is a challenging problem, even when considered on a case-by-case, application-specific basis. But if a solution were possible, then it could combine the many correctness benefits of high-level languages with performance by managing parallelism without the programmer effort needed to ensure performance. This paper proposes techniques for such automatic management of parallelism by combining static (compilation) and run-time techniques. Specifically, we consider the Parallel ML language with task parallelism, and describe a compiler pipeline that embeds "potential parallelism" directly into the call-stack and avoids the cost of task creation by default. We then pair this compilation pipeline with a run-time system that dynamically converts potential parallelism into actual parallel tasks. Together, the compiler and run-time system guarantee that the cost of parallelism remains low without losing its benefit. We prove that our techniques have no asymptotic impact on the work and span of parallel programs and thus preserve their asymptotic properties. We implement the proposed techniques by extending the MPL compiler for Parallel ML and show that it can eliminate the burden of manual optimization while delivering good practical performance.

Moderating Effect of Managerial Efficiency on the Association between Corporate Social Responsibility and Market Value of Nigerian Banks

This research paper investigates the moderating effect of managerial efficiency (ME) on the association between corporate social responsibility (CSR) and market value of Nigerian banks, incorporating four control variables. The paper utilized a panel data of eight Nigerian listed banks over the study period 2010- 2021. Static panel techniques such as Pooled Ordinary Least Squares (POLS) and the Fixed Effects Model (FEM) in conjunction with the Weighted Least Squares (WLS) were considered in the model estimation However, the Restricted F-test rated the POLS over the FEM, which was later dropped for WLS due to heteroskedasticity problem. The main findings reveal that CSR has a significant positive effect on the market value; ME has a positive and significant effect on the market value and ME significantly and negatively moderates the link that binds CSR and the market value. The research concludes that the role of ME matters when it comes to understanding the CSR and the market value nexus. Expenditure on CSR activities should be multiplied by banks, as doing so will create good image, loyalty and reputations for the banks, and consequently improve their market value.

Empirical assessment of methane emissions, socioeconomic factors, and infant mortality in Europe

AbstractThe 2030 United Nations Sustainable Development Goals (SDG) Target 3.9 aims to “reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contamination.” Methane belongs to the class of greenhouse gases and it is a harmful ambient atmospheric pollutant with adverse effects on human health. Hence, this paper aligns with SDG 3 and 11 to analyze the impact of methane emissions on infant mortality rate in Europe. Using an unbalanced panel data on 53 European countries from 1990 to 2018, we probe if the impact differs by union membership. Consistent findings from static and dynamic panel data techniques reveal that: methane emissions exhibit mortality‐inducing properties on the full sample, European Union (EU) and non‐EU countries by 0.041%, 0.037%, and 0.047%, respectively; EU countries show lower mortality rates relative to non‐EU countries by −0.164%; and mortality rate is persistent. Additional sensitivity checks by including nitrous oxide as a regressor indicates that it picks up the mortality effects of methane emissions due to collinearity (in the static analysis) but the aggravating impact of methane is upheld in the dynamic model. Likewise, the results are sustained when we control for outliers by excluding Russia (the largest emitter in Europe) and robustness checks using under‐5 mortality rate uphold the mortality‐increasing effect of methane emissions. Based on our empirical investigations, adequate policy recommendations are provided to help in stemming the harmful effects of methane emissions on the environment such that it reduces its adverse effect on infant mortality rate in Europe. These outcomes enrich the health economics and child health literature, and policy recommendations are discussed.

A degradation feature extraction technique based on static divided symbol sequence entropy

Due to the doping of considerable noise and impact components in vibration signals of quay crane gearboxes, some traditional methods have difficulty uncovering degradation patterns. To accurately extract degradation features from vibration monitoring signals, a degradation feature extraction technique based on static divided symbol sequence entropy is proposed. Based on the basic scale entropy technique, considering the uniformity of the symbolization standard, the technique takes the root mean square of the health condition signal as the basis and incorporates the scale coefficient to establish a uniform basic scale. Simultaneously, the symbol set is expanded to enhance the information content and the ability of the approach to characterize the complexity levels of signals in large-value regions. Therefore, the proposed static divided symbol sequence entropy technique can accurately and flexibly characterize performance degradations. The logistic chaotic sequence and the lifetime signal of hoisting mechanism gearbox are separately used for analysis. It shows that the proposed technique can characterize the complexity of the nonlinear time series and sensitively describe the performance degradation exhibited by hoisting mechanism gearbox. This technique is computationally fast, and it can be implemented as a foundation for developing new methods for evaluating the health conditions of quay crane gearboxes.

A Novel Strategy for the Characterization of Self-Assembled Structures Using the Static Solid-State Phosphorus Nuclear Magnetic Resonance Technique.

Structural characterization of assemblies in solutions is essential for understanding the relationship between the structure and material properties. In this study, we introduce a novel approach to investigate amphiphilic self-assemblies in solutions using the phospholipid molecule 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphocholine (Lyso PC) as a 31P NMR probe. The high natural abundance and gyromagnetic ratio of 31P make it one of the most sensitive nuclei in the low-frequency region, enabling efficient detection even in dilute solutions. Lyso PC can readily co-assemble with amphiphilic molecules and ions in aqueous solutions, forming various structures, such as hexagonal, lamellar, and micellar assemblies. The characteristic line shapes of these assemblies reflect the chemical environment around the probe and provide insights into the different phase states of the assemblies. This strategy offers a simple, cost-effective, and static method for obtaining structural information about various assemblies. Our work not only introduces a sensitive probe for characterizing assemblies in a solvent environment but also inspires new ideas for the development of similar spectroscopic probes.