Asymmetric Model Research Articles

Mathematical Formalization and Applications to Data with Excess of Zeros and Ones of the Unit-Proportional Hazard Inflated Models

In this study, we model the rate or proportion of a specific phenomenon using a set of known covariates. To fit the regression model, which explains the phenomenon within the intervals (0,1), [0,1), (0,1], or [0,1], we employ a logit link function. This approach ensures that the model’s predictions remain within the appropriate range of zero to one. In cases of inflation at zero, one, or both, the logit link function is similarly applied to model the dichotomous Bernoulli-type variable with a multinomial response. The findings demonstrate that the model yields a non-singular information matrix, ensuring valid statistical inference. This ensures the invertibility of the information matrix, allowing for hypothesis testing based on likelihood statistics regarding the parameters in the model. This is not possible with other asymmetric models, such as those derived from the skew-normal distribution, which has a singular information matrix at the boundary of the skewness parameter. Finally, empirical results show the model’s effectiveness in analyzing proportion data with inflation at zero and one, proving its robustness and practicality for analyzing bounded data in various fields of research.

Multiple environmental regulations and green technology innovation: a boundary theory perspective

Purpose Based on boundary theory, the authors try to clarify the boundaries of multiple environmental regulations. This paper aims to explore the strategic choices of multiple environmental regulations, analyze their spatial impact on green technology innovation and clarify the implementation priorities of multiple environmental regulations in various regions. Design/methodology/approach The authors construct an asymmetric response model based on the boundary theory perspective to analyze the strategic choices of different environmental regulations. In addition, dynamic spatial econometric methods are used to empirically analyze the differentiated regulatory boundaries of command-control type, market-incentive and voluntary-participation in environmental regulations and their spatial effects on green technology innovation. Findings Strict compulsory boundaries are formed in China when the command-control and market-incentive types are selected in a dynamic spatial and competitive game environment. When voluntary participation is selected, strict compulsory or loose basic boundaries are formed in each region. The command-control type is highly dependent on geographical distance, the market-incentive type is more dependent on an economic connection and the voluntary-participation type has obvious spatial spillover effects under the spatial weight matrix of geographical distance and economic connection. When Eastern China chooses voluntary participation in environmental regulation, the incentive effect on green technology innovation is the strongest. Middle China is the market-incentive type, and Western China is the command-control type. Command-control type and market-incentive type form strong complementary effects in dynamic spatial environments. Originality/value From the boundary theory perspective, this study analyzes the differentiated dynamic spatial boundaries of command-control, market-incentive and voluntary-participation in environmental regulations. Analyze the spatial impact of multiple environmental regulations on green technology innovation and clarify the implementation priorities of multiple environmental regulations in various regions.

Revisiting the nexus between tourism and GDP for Cambodia: insights from symmetric and asymmetric causality models

Revisiting the nexus between tourism and GDP for Cambodia: insights from symmetric and asymmetric causality models

Do clean fuel and trade-openness reduce environmental degradation in China: evidence from asymmetric model

IntroductionThis study investigates the relationship between economic growth, clean fuel utilization, trade, and environmental pollution. By focusing on the potential of clean fuels and trade in reducing pollution, this research aims to understand their role in promoting environmental sustainability in China from 1990 to 2020.MethodsThe study employs the Nonlinear Autoregressive Distributed Lags (NARDL) approach to analyze time series data. This method enables the decomposition of impacts from clean fuels and trade on pollution levels, facilitating an understanding of their distinct contributions to environmental outcomes.ResultsFindings indicate that economic growth is associated with an increase in pollution levels, while clean fuel usage exhibits a modest but significant reduction effect. Nonetheless, the relatively small coefficients highlight the need for a greater share of clean fuels in China’s energy mix. Additionally, trade shows a significant negative relationship with pollution emissions, with data reflecting a gradual decline in pollution over time.DiscussionThese results underscore the benefits of clean fuel adoption and trade promotion as effective measures for mitigating pollution. However, they also highlight the necessity for stronger regulatory policies, public awareness initiatives, and investments in sustainable technologies to ensure China’s long-term environmental sustainability.

Reliability Analysis for Unknown Age Class of Lifetime Distribution with Real Applications in Medical Science

Analyzing the reliability of the aging class of life distribution provides important information about how long a product lasts and sustainability measures that are essential for determining the environmental impact and formulating resource-saving plans. The study emphasizes the goodness-of-fit technique of the nonparametric test for the NBRUmgf class because age data are crucial for applications. Evaluations were conducted using the test’s asymptotic properties and Pitman efficiency methodology for some selected asymmetric probability models, and the outcomes were compared with those of alternative methods. We assessed the test’s power against widely used reliability distributions for some well-known alternative asymmetric distributions, including the Weibull, Gamma, and linear failure rate (LFR) distributions, and provided percentiles for both censored and uncensored data. This study shows the efficacy of the test in various sectors using real-world datasets and comprehensive tables of test statistics.

Non-Condensation Turbulence Models with Different Near-Wall Treatments and Solvers Comparative Research for Three-Dimensional Steam Ejectors

Steam ejectors are important energy-saving equipment for solar thermal energy storage; however, a numerical simulation research method has not been agreed upon. This study contributes to a comprehensive selection of turbulence models, near-wall treatments, geometrical modeling (2-D and 3-D), solvers, and models (condensation and ideal-gas) in the RANS equations approach for steam ejectors through validation with experiments globally and locally. The turbulence models studied are k-ε Standard, k-ε RNG, k-ε Realizable, k-ω Standard, k-ω SST, Transition SST, and linear Reynolds Stress. The near-wall treatments assessed are Standard Wall Functions, Non-equilibrium Wall Functions, and Enhanced Wall Treatment. The solvers compared are pressure-based and density-based solvers. The root causes of their distinctions in terms of simulation results, applicable conditions, convergence, and computational cost are explained and compared. The complex phenomena involving shock waves, choking, and vapor condensation captured by different models are discussed. The internal connections of their performance and flow phenomena are analyzed from the mechanism perspective. The originality of this study is that both condensation and 3-D asymmetric effects on the simulation results are considered. The results indicate that the k-ω SST non-equilibrium condensation model coupling the low-Re boundary conditions has the most accurate prediction results, best convergence, and fit for the widest range of working conditions. A 3-D asymmetric condensation model with a density-based solver is recommended for simulating steam ejectors accurately.

Active micro-vibration isolation system for adaptive vibration suppression tests using piezoelectric stack actuator

An active micro-vibration isolation system for adaptive vibration suppression using piezoelectric stack actuators is presented, along with the discrete time modelling method, real-time adaptive controller design, and hardware implementation. The system comprises piezoelectric stack actuators, capacitive displacement sensors, power amplifiers, signal conditioners, and a real-time computer. A discrete asymmetric Bouc-Wen model is developed to characterize the nonlinear behavior of the piezoelectric stack actuators. System identification is conducted using an improved particle swarm optimization method, specifically the Hybrid PSO-Jaya algorithm, which sequentially integrates the PSO algorithm with the Jaya algorithm. Additionally, an improved adaptive filtering algorithm employing affine projection, referred to as the FXAPA algorithm, is introduced to facilitate real-time control. The efficacy of the proposed active micro-vibration isolation technology is validated through micro-vibration suppression tests.

Elucidating Antibiotic Permeation through the Escherichia coli Outer Membrane: Insights from Molecular Dynamics.

Antibiotic resistance represents a critical public health threat, with an increasing number of Gram-negative pathogens demonstrating resistance to a broad range of clinical drugs. A primary challenge in enhancing antibiotic efficacy is overcoming the robust barrier presented by the bacterial outer membrane. Our research addresses a longstanding question: What is the rate of antibiotic permeation across the outer membrane (OM) of Gram-negative bacteria? Utilizing molecular dynamics (MD) simulations, we assess the passive permeability profiles of four commercially available antibiotics─gentamicin, novobiocin, rifampicin, and tetracycline across an asymmetric atomistic model of the Escherichia coli (E. coli) OM, employing the inhomogeneous solubility-diffusion model. Our examination of the interactions between these drugs and their environmental context during OM permeation reveals that extended hydrogen bond formation and drug-cation interactions significantly hinder the energetics of passive permeation, notably affecting novobiocin. Our MD simulations corroborate well with experimental data and reveal new implications of solvation on drug permeability, overall advancing the possible use of computational prediction of membrane permeability in future antibiotic discovery.

A comparative study of the effect of facet tropism on the index-level kinematics and biomechanics after artificial cervical disc replacement (ACDR) with Prestige LP, Prodisc-C vivo, and Mobi-C: a finite element study

IntroductionArtificial cervical disc replacement (ACDR) is a widely accepted surgical procedure in the treatment of cervical radiculopathy and myelopathy. However, some research suggests that ACDR may redistribute more load onto the facet joints, potentially leading to postoperative axial pain in certain patients. Earlier studies have indicated that facet tropism is prevalent in the lower cervical spine and can significantly increase facet joint pressure. The present study aims to investigate the changes in the biomechanical environment of the cervical spine after ACDR using different prosthese when facet tropism is present.MethodsA C2-C7 cervical spine finite element model was created. Symmetrical, moderate asymmetrical (7 degrees tropism), and severe asymmetrical (14 degrees tropism) models were created at the C5/C6 level by adjusting the left-side facet. C5/C6 ACDR with Prestige LP, Prodisc-C vivo, and Mobi-C were simulated in all models. A 75 N follower load and 1 N⋅m moment was applied to initiate flexion, extension, lateral bending, and axial rotation, and the range of motions (ROMs), facet contact forces(FCFs), and facet capsule stress were recorded.ResultsIn the presence of facet tropism, all ACDR models exhibited significantly higher FCFs and facet capsule stress compared to the intact model. In the asymmetric model, FCFs on the right side were significantly increased in neutral position, extension, left bending and right rotation, and on both sides in right bending and left rotation compared to the symmetric model. All ACDR model in the presence of facet tropism, exhibited significantly higher facet capsule stresses at all positions compared to the symmetric model. The stress distribution on the facet surface and the capsule ligament in the asymmetrical models was different from that in the symmetrical model.ConclusionsThe existence of facet tropism could considerably increase FCFs and facet capsule stress after ACDR with Prestige-LP, Prodisc-C Vivo, and Mobi-C. None of the three different designs of implants were able to effectively protect the facet joints in the presence of facet tropism. Research into designing new implants may be needed to improve this situation. Clinical trials are needed to validate the impact of facet tropism.

Implementation of WRF‐Urban Asymmetric Convective Model (UACM) for Simulating Urban Fog Over Delhi, India

AbstractAccurate fog prediction in densely urbanized cities poses a challenge due to the complex influence of urban morphology on meteorological conditions in the urban roughness sublayer. This study implemented a coupled WRF‐Urban Asymmetric Convective Model (WRF‐UACM) for Delhi, India, integrating explicit urban physics with Sentinel‐updated USGS land‐use and urban morphological parameters derived from the UT‐GLOBUS dataset. When evaluated against the baseline Asymmetric Convective Model (WRF‐BACM) using Winter Fog Experiment (WiFEX) data, WRF‐UACM significantly improved urban meteorological variables such as diurnal variations in 10‐m wind speed, 2‐m air temperature (T2), and 2‐m relative humidity (RH2) during a fog event. UACM also demonstrates improved accuracy in simulating temperature and significantly reducing biases for wind speed and daytime RH2 under clear sky conditions. UACM reproduced the nighttime urban heat island effect within the city, showing realistic diurnal heating and cooling patterns that are important for accurate fog onset and duration. UACM effectively predicts the onset, evolution, and dissipation of fog, aligning well with observed data and satellite imagery. Compared to WRF‐BACM, WRF‐UACM reduces the cold bias soon after sunset, thus improving the fog onset error by ∼3 hr. This study highlights the UACM's potential to improve fog prediction and its application in operational settings. With further investigation into different fog types, the UACM can provide crucial insights for preventive measures and reducing disruptions in urban areas.

Combined effect of artificial cervical disc replacement and facet tropism on the index-level facet joints: a finite element study

BackgroundArtificial Cervical Disc Replacement (ACDR) is an effective treatment for cervical degenerative disc diseases. However, clinical information regarding the facet joint alterations after ACDR was limited. Facet tropism is common in the sub-axial cervical spine. Our previous research indicated that facet tropism could lead to increased pressure on the cervical facet joints. This study aimed to assess the impact of facet tropism on the facet contact force and facet capsule stress after ACDR.MethodsA C2–T1 cervical finite element model was constructed from computed tomography (CT) scans of a 28-year-old male volunteer. Symmetrical, moderate asymmetrical (7 degrees tropism), and severe asymmetrical (14 degrees tropism) models were created at the C5/C6 level by altering the facet orientation at the C5-C6 level. The C5/C6 ACDR was simulated in the intact, moderate asymmetrical and severe asymmetrical models. A 75-N follower load with 1.0-Nm moments was applied to the top of C2 vertebra in the models to simulate flexion, extension, lateral bending, and axial rotation with the T1 vertebra fixed. The range of motions (ROMs) under all moments, facet contact forces (FCFs) and facet capsule strains were tested.ResultsIn the asymmetrical model, the right FCFs considerably increased under flexion, extension, right bending, left rotation, especially under right bending the right sided FCF of the severe asymmetrical model was about 5.44 times of the neutral position, and 3.14 times of the symmetrical model. and concentrated on the cephalad part of the facets. The facet capsule stresses on both sides remarkably increased under extension, lateral bending and right rotation. In the moderate and severe asymmetrical models, the capsule strain was greater on both sides of each position than in the symmetric model.ConclusionsThe face tropism increased facet contact force and facet capsule strain after ACDR, especially under extension, lateral bending, and rotation, and also could result in abnormal stress distribution on the facet joint surface and facet joint capsule. The results suggest that face tropism might be a risk factor for post-operative facet joint degeneration progression after ACDR. Facet tropism may be noteworthy when ACDR is considered as a surgical option.

CellSAM: Advancing Pathologic Image Cell Segmentation via Asymmetric Large-Scale Vision Model Feature Distillation Aggregation Network.

Segment anything model (SAM) has attracted extensive interest as a potent large-scale image segmentation model, with prior efforts adapting it for use in medical imaging. However, the precise segmentation of cell nucleus instances remains a formidable challenge in computational pathology, given substantial morphological variations and the dense clustering of nuclei with unclear boundaries. This study presents an innovative cell segmentation algorithm named CellSAM. CellSAM has the potential to improve the effectiveness and precision of disease identification and therapy planning. As a variant of SAM, CellSAM integrates dual-image encoders and employs techniques such as knowledge distillation and mask fusion. This innovative model exhibits promising capabilities in capturing intricate cell structures and ensuring adaptability in resource-constrained scenarios. The experimental results indicate that this structure effectively enhances the quality and precision of cell segmentation. Remarkably, CellSAM demonstrates outstanding results even with minimal training data. In the evaluation of particular cell segmentation tasks, extensive comparative analyzes show that CellSAM outperforms both general fundamental models and state-of-the-art (SOTA) task-specific models. Comprehensive evaluation metrics yield scores of 0.884, 0.876, and 0.768 for mean accuracy, recall, and precision respectively. Extensive experiments show that CellSAM excels in capturing subtle details and complex structures and is capable of segmenting cells in images accurately. Additionally, CellSAM demonstrates excellent performance on clinical data, indicating its potential for robust applications in treatment planning and disease diagnosis, thereby further improving the efficiency of computer-aided medicine.

Forecast of electric transport property via two models

Temperature and synthesis condition-dependent resistivity are critical parameters for determining the electrical properties of materials. Modeling serves as a powerful tool for predicting the electrical transport characteristics of materials. The first objective of this work was to conduct a quantitative analysis of the reported metallic and insulating resistivity behaviors in double-phase materials. Using non-linear regression, both a phenomenological model and an Asym2sig asymmetric peak model were employed to quantitatively analyze the temperature-dependent resistivity. The fitting results align closely with the observed resistivity-temperature curves. The second objective of this work was to establish a method linking chemical composition (synthesis conditions) to the parameters derived from the two models, calculation on the principle of non-linear curve fitting, two numerical equations are highlighted for quantitatively analyzing chemical composition-dependent parameters. The observed effects of chemical composition on the shift in the temperature-resistive curve, which are fundamental to understanding resistivity behavior, are discussed quantitatively for the first time to our knowledge for resistive-temperature behavior. Hence, the resistivity of both crystalline and non-crystalline materials can be forecasted across various compositions and temperatures using the methods presented, even without experimental data.

J-Curve For Indonesia’s Trade Balance with Non-Linier ARDL

The performance of Indonesia’s Balance of Payments (BOP), especially for the trade balance/current account, which recorded a surplus and adequate foreign exchange reserves, controlled political conditions, and attractive yields, can impact the exchange rate. This improvement in the exchange rate further encouraged the entry of foreign investors, which caused the Indonesian economy to continue to grow when the world experienced a financial crisis. This study analyzes asymmetric models to prove the Marshall Lerner Condition of Indonesia with trading partners. Using NARDL methods, this study uses monthly data from 2005 to 2021 from the International Federal Reserve (IFS), a data source for foreign trade activities. The result of this study is a J curve in Indonesia’s trade pattern with its trading partners, formed in the United States, Singapore, Vietnam, and Japan. For the nonlinear ARDL method, the J curve is formed in trading partners Netherlands, Germany, Korea, Singapore, United Kingdom, Vietnam, and Japan. The implementation of Indonesia’s exchange rate policy should be followed by a policy that can suppress the exchange rate against inflation because if this policy is not followed, it will not significantly impact Indonesia’s trade performance in the long run.

PERBANDINGAN METODE EXPONENTIAL GARCH (EGARCH) DAN GLOSTEN-JAGANNATHAN-RUNKLE GARCH (GJR-GARCH) PADA MODEL VOLATILITAS SAHAM TUNGGAL

Financial data, such as stock prices, usually have a tendency to fluctuate rapidly and create a heteroscedastic effect on the variance of residuals. The Covid-19 pandemic that occurred from 2020 to 2022 is one factor that can affect economic movements, especially in Indonesia, and has an impact on the volatility of financial data. The problem of heteroscedasticity can be addressed using the ARCH/GARCH model. However, this model has a weakness in capturing the asymmetry of volatility resulting from good news and bad news. Several models that can overcome the problem of volatility asymmetry are EGARCH and GJR-GARCH. The purpose of this thesis research is to determine the best volatility model using the daily stock price data of PT Bank Rakyat Indonesia (Persero) Tbk. covering the period from February 2020 to February 2023. The result of the asymmetric GARCH model suggests that the ARIMA(2,0,2) EGARCH(1,1) model has an AIC value of -4.8850, and the ARIMA(2,0,2) GJR-GARCH(1,1) model has an AIC value of -4.8907. Therefore, the model with the minimum AIC value, which is the ARIMA(2,0,2) GJR-GARCH(1,1) model, is considered the best model. Furthermore, this model exhibits very good forecast accuracy, as evaluated by the sMAPE value of 5,17%.

Catch the Cyber Thief: A Multi-Dimensional Asymmetric Network Attack–Defense Game

This paper presents a novel multi-dimensional asymmetric game model for network attack–defense decision-making, called “Catch the Cyber Thief”. The model is built upon the concept of partially observable stochastic games (POSG) and is designed to systematically incorporate multi-dimensional asymmetry into network attack–defense problems. The attack agent is called a “thief” who wants to control a key host by exploring the unfamiliar network environment, and the defense agent is called a “police” who needs to catch the opponent before its goal is accomplished. The results indicate that the asymmetry of network attack and defense is not only influenced by attack and defense strategies but also by spatio-temporal factors such as the attacker’s initial position, network topology, and defense lag time. In addition, we have found that there may exist the “attack rhythm,” which makes “how to maintain a good attack rhythm” and “how to generate a robust defense strategy against different attackers” worth exploring. Compared with existing attack–defense game models, our game model can better generate a direct mapping relationship with real elements, enabling us to understand network attack and defense interactions better, recognize security risks, and design defense strategies that can directly serve real-world decision-making.

The Actualities of Public Relations Practice at an Eastern Ontario University: A Quasi-ethnographic Study

Although various studies have used ethnographic techniques to examine different concepts, contexts, and practices in public relations (Sriramesh, 2000; Daymon & Hodges, 2009), none of these studies ethnographically examined the culture within which public relations is practiced, and discourse is produced in a college or university context. This quasi-ethnographic study aims to: (1) produce an account of the core aspects of the culture within which public relations is practiced at a university in Eastern Ontario and (2) identify what PR model best represents the PR practice there. To collect data for this study, I conducted e-mail interviews with five public relations participants at the university under investigation to collect data for this study. The data collected was about the groups’ routines, practices, and behaviors that shape their experience and facilitate producing relevant discourse. I also collected some genres and documents. The findings showed that (1) collaboration characterized the culture within which PR performs its duties and activities and produces relevant discourse, and (2) the two-way asymmetrical model best represents the PR practice in the university examined. Besides filling the gap identified here, the study contributes to theory and practice in the field. It benefits those who teach public relations writing and the institution itself as it evaluates how excellent the PR practice in that institution is.

COVID-19 and time-frequency spillovers between oil and sectoral stocks and portfolio implications: Evidence from China and US economies

This paper examines the volatility spillovers and the time-frequency dependence between crude oil and stock sectors in the U.S. and China using both wavelet coherence and asymmetric BEKK GARCH models. This study also investigates the impact of the COVID-19 pandemic on spillover effects and portfolio management. The results reveal strong positive co-movements between WTI oil and US sector stock returns at medium and low frequencies particularly in 2020Q1. We find significant long-term co-movements between oil and Chinese sector stock returns (64–128 days). Furthermore, the findings reveal a significant and asymmetric volatility transmission between oil and sector stocks in both the US and Chinese economies. The evidence of spillovers is more pronounced during the COVID-19 period. It is recommended that equity investors should hold more stocks than oil assets to minimize risk without reducing the expected return. Finally, hedging with oil is expensive for U.S. sectors during the pandemic but inexpensive for Chinese sectors.

Electric Field Features and Charge Behavior in Oil-Pressboard Composite Insulation under Impulse Voltage

Oil-pressboard/paper insulation materials are essential in transformers for ensuring their safe and stable operation, primarily due to their roles in spatial electric field distribution and charge migration mechanisms. Current spatial distribution analyses rely on computational methods that lack empirical validation, particularly for oil-pressboard/paper composites. This study leverages the principles of the Kerr electro-optic effect to develop a rapid measurement platform for electric fields within oil-pressboard/paper insulation under impulse voltage conditions, which measures the spatial electric field characteristics using Cu-Cu and Al-Al electrodes under various scenarios: with asymmetric and symmetric pressboard coverage and different numbers of insulating paper layers. Findings indicated: (1) In asymmetric pressboard models, Cu-Cu electrodes exhibit a consistent peak electric field of approximately 16 kV/mm, while Al-Al electrodes show peak values of 18.13 kV/mm and −14.98 kV/mm. Charge density patterns are similar, with Cu-Cu at about 68 μC/m2 and Al-Al at 11.2 μC/m2 and −124.8 μC/m2. (2) Symmetric models present consistent peak electric fields and charge densities for both polarities. (3) Increasing insulating paper layers elevates electric field strengths. Both electrodes show the similar peak field of about 17 kV/mm with differing paper layers due to higher charge injection from the Al electrode. (4) Utilizing the Schottky effect and field emission principles, the study clarifies charge generation and migration mechanisms. These insights could provide a theoretical foundation for designing and verifying oil-pressboard/paper insulation structures in transformers.

Value-at-risk modeling of naira exchange rates

The naira exchange rate has experienced extreme volatility, and the use of derivatives to control interest rates and currency risks has grown quickly. These developments have made risk management research necessary. To this effect, this paper investigated the optimal volatility model that offers the best VaR forecasts and minimizes expected loss in the Naira exchange rate. The data was collected from FX time and consisted of the Euro to Naira exchange and the daily closing rate of the US dollar to Naira exchange rate from 24/10/2016 to 15/06/2018. These data were estimated using different symmetric and asymmetric GARCH models. The finding shows that there is less volatility in the USD to Naira exchange rate compared to the Euro to Naira exchange rate. The study shows that SPLINE- GJR under skewed student t distribution is the optimal model for the Euro to Naira exchange rate while GARCH is the optimal model for the US dollar to Naira exchange rate. This study suggests that model risk assessments be given careful consideration by regulators, banks, and other stakeholders and integrated into the process of operational and regulatory design.