Lag Correction Research Articles

Effect of frame rate on image quality in cardiology evaluated using an indirect conversion dynamic flat-panel detector.

To verify the effect of the frame rate on image quality in cardiology, we used an indirect conversion dynamic flat-panel detector (FPD). We quantified the input-output characteristics, and determined the modulation transfer function (MTF) and normalized noise power spectrum (NNPS) of the equipment used in cardiology at 7.5, 10, 15, and 30 frames per second (fps). We also calculated the noise power spectrum for still images and videos at all frame rates and obtained the image lag correction factor r. The input-output characteristics and the MTF agreed even when the frame rate was varied. The NNPS tended to decrease uniformly as a function of frequency at increasing frame rates. The factor r decreased as a function of the frame rate, and its minimum value was 30 fps. Our results suggest that high-frame-rate imaging in cardiology using indirect conversion dynamic FPDs is affected by image lag.

ARDL and VECM Investigation of the Environmental Kuznets Curve Hypothesis in Egypt, India, Mexico, Pakistan, Thailand, and Turkey: Financial Development, Globalization, and Government Expenditure Implications for Sustainable Development

<p class="MsoNormal" style="margin-top: 10pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">The present paper empirically examines the validity of the environmental Kuznets curve (EKC) hypothesis, which posits an inverted U-shaped relationship between CO2 emissions and economic growth, in Egypt, India, Mexico, Pakistan, Thailand, and Turkey for the period 1970-2020. The EKC validity is highly debated due to varying results across countries. This study is significant to addresses this controversy by estimating the EKC's robustness while considering the influence of financial development, globalization, and government expenditure. We employ two cointegration techniques, the autoregressive distributed lag (ARDL) and vector error correction model (VECM), also considering potential structural breaks in the data. Out key findings indicate that the EKC hypothesis is supported in India, Pakistan, and Turkey, with carbon emissions eventually declining after reaching a peak. The hypothesis is not supported in Egypt and Thailand, where emissions rise monotonically with economic growth. In Mexico, the results are mixed, with ARDL suggesting a U-shaped relationship and VECM supporting the EKC. From our empirical analysis of the EKC hypothesis, we derive the following policy implications: 1) countries should adopt comprehensive policy strategies that integrate these goals and fully consider the long-term environmental and societal impacts of their decisions; 2) countries should invest heavily in research and development to accelerate the creation of new technologies that can effectively reduce carbon emissions; and 3) countries must actively raise awareness about the environmental repercussions of economic growth.</span></p>

The Roles of Insurance on Economic Growth in Malaysia: An ARDL Approach

Malaysia’s economic growth has been rising steadily over the years and one of the main contributors is the insurance sector. The literature has recorded mixed findings on the relationship between insurance and economic growth. This paper examines the relationship between the insurance sector and economic growth in Malaysia over an extended period of 1990-2021. This paper uses three proxies for the insurance sector i.e. life insurance premiums, nonlife insurance premiums, and total insurance premiums. The Autoregressive-Distributed Lag (ARDL) and Error Correction Model (ECM) approaches are employed to achieve the objective. While controlling for foreign direct investment, export, and import, this paper found that there is a positive long-run relationship between non-life insurance premiums and economic growth. Conversely, a negative short-run relationship is observed between life insurance premiums and economic growth. The total insurance premium has a negative short-run relationship with economic growth yet is insignificant for the long-run. The non-life insurance sector has a larger contribution compared to life insurance on Malaysia's economic growth as the market depends more on capital formation and investments, particularly in infrastructure, real estate, and capital markets. The insurance sector provides financial expansion in terms of payment for protection which results in an economic boost.

Taxation and Consumers’ Spending Patterns in Nigeria: An Autoregressive Distributed Lag and Error Correction Model Approach

This study evaluates the effects of personal income tax and consumption tax on the spending system of consumers in Nigeria. The autoregressive distributed lag (ARDL) model has been employed for the co-integration test. The research additionally employs the Error Correction Model (ECM) to assess the pace at which any divergence from the long run equilibrium can return to normal in the current period. The findings show that Value added tax has an insignificant impact on purchasing power of consumers in both the short and long intervals. However, personal income tax and exchange rate exert substantial positive effect on consumer spending power in the long run but not in the short run. At the 1% level, the ECT coefficient is shown to be significant and unfavourable. This demonstrates a pretty slow convergence rate, with the model pushing itself towards equilibrium by 37% each year. The consequence is that any disequilibrium caused by shocks from the previous year requires 37% adjustment speed to return to long-run equilibrium in the current year. There have been several studies on how consumption tax affects households’ welfare without considering the effects of income tax and ever fluctuating exchange rate alongside these whole scenarios. This study puts all of these issues into consideration and contributes meaningfully to the existing literature that personal income tax is an integral part of the factors that affect households’ spending capacity. The study recommends that proper tax policy to enhance consumers’ spending capacity.

Relative responses of trade in goods and services to currency devaluation: Evidence from Ethiopia

Lack of hard currency is one of the key growth barriers in emerging countries, as imports vastly outstrip exports. In response, governments in these countries usually undertake a variety of policy packages, including the devaluation of the domestic currency. Despite these efforts, there have been no discernible adjustments to foreign balance. This study examines whether the response to devaluation differs significantly between the goods and services trade in Ethiopia. We estimate the long- and short-run elasticities of the disaggregated trade indicators using an autoregressive distributed lag (ARDL) and error correction mechanisms. The empirical results confirm a significant difference between the goods and service sectors in terms of their responses to the devaluation policy in the long and short run. The estimated long-run elasticities of devaluation are only statistically significant for service imports and trade balances with negative signs. The remaining sectors did not show any significant relationships. In addition, we obtain meaningful short-run elasticities for service imports, goods exports, and total exports, all of which have a negative sign. Domestic inflation accounted for a large portion of the short-run import dynamics, output growth, and FDI, which contributed significantly to long-term export performance. The current study reveals that the government should not rely exclusively on the devaluation policy to bridge its external imbalances, and should see alternative and more effective policy mixes to alter the demand and supply sides of foreign trade.

Cointegration Behavior and Diagnostic Stability of Philippine Monetary Policy Implementation During the Period From 1990 to 2022

The observations made in this study were used to evaluate the diagnostic stability of the Philippine Central Bank’s selected monetary policy targets, namely, the Gross Domestic Product and inflation, with money supply, credits, interest rates, and exchange rates, as independent variables, using the autoregressive distributed lag and error correction model analysis. The co-integrating behavior depicted that all p-values of less than the 5% significance level generated different behaviors. However, analysis of the Central Bank’s performance showed that there were no unit roots at all (p > .05) that signified a strong indication of cointegration behavior. The diagnostic stability of the Philippine monetary policy implementation was established over the period from 1990 to 2022. Further, money in circulation caused increases in domestic prices, interest rates, and inflationary pressure, and ultimately affected GDP (ppp). Understanding cointegration behavior is an imperative implication for policy makers to observe and take into consideration.

FOOD IMPORT, FOOD PRICE INFLATION, WAGES AND AGRICULTURAL EMPLOYMENT IN SOUTH AFRICA

Agricultural industry plays a significant role in the South African economy, specifically in creating jobs. However, this sector is facing significant challenges owing to economic and social unrest. Within the application of both Autoregressive Distributed Lag (ARDL) and Error Correction Model (ECM) on time series data from 2010q1 to 2021q4; this paper assessed the effects of food imports, inflation, and real wage on agricultural employment in South Africa. The results from bounds testing indicated that food imports, inflation and real wage stimulate longterm disruptions in agricultural employment. However, short-run results indicated that agricultural employment is only affected by the real wage. Based on these findings, this study suggests a policy that incorporation of both inflation rate and real wages policy to improve employment in the agricultural industry. Additionally, easing the import of food products that are complements to domestic agricultural products should be another strategy to increase the number of people employed in the agricultural industry.

Investigation of Causal Linkages Between Financial Development and Economic Growth: Evidence from Pakistan

Financial development is a driving factor for economic growth and is important in fostering growth. An efficient and effective financial system contributes to economic growth and fosters the performance of other economic measures. This study aims to investigate the influence of financial innovation on economic expansion to understand the correspondence between financial development and economic growth in Pakistan. Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) are used for stationarity. Auto Regressive Distributed Lag (ARDL) and Error Correction Model are employed to analyze the correlation between economic growth and financial development. The finding shows that financial development stimulates economic growth. The research explains that foreign direct investment and personal remittances adversely affect GDP growth. These understandings recommend that although financial development generally promotes, its results can vary extensively and depend on specific context-dependent conditions. Furthermore, applying CUSUM AND CUSUM of square tests to measure model stability convincingly confirms a long-term relation between financial development and economic expansion, disproving the null hypothesis of no co-integration and reinforcing that financial development is essential to domestic economies. Policymakers need to practice these understandings in actionable plans by highlighting financial innovations that advance access to credit and efficiently allocate resources so investment in education and agriculture can maximize economic growth.

Determinants of greenhouse gas emissions by Brazilian agricultural sector.

The agricultural sector is one of the most polluting economic activities, contributing significantly to greenhouse gas (GHGs) emissions. Brazil is one of the largest agricultural producers worldwide and plays a major role in reducing the environmental impact of this sector. Here, we aimed to determine the impact of the agricultural sector, with special attention to production, prices, and trade openness, on the short- and long-term GHGs emissions of Brazilian agriculture. Employing data from 1974 to 2019, we tested the cointegration of variables and compared the determinants of GHG emissions using Autoregressive Distributed Lag (ARDL) and Vector Error Correction Model (VECM) methods. Our results show a long-term equilibrium trend for Brazilian agricultural GHGs emissions, a result that correlates with emerging environmental compliance, and society demands the adoption of sustainable technologies, processes, and policies. In the short run, both cattle herds and Agricultural Added Value to GDP per capita showed an expected positive and significant contribution to GHGs emissions, while agricultural crop area demonstrated an inverse relationship. The trade openness index confirmed that foreign trade plays an important role in reducing GHGs emissions. The price index is not significant in our models. Both the private and public sectors have important roles in sustainable agriculture, especially in increasing system efficiency through the adoption of management and technologies that reduce GHG emissions levels.

The impact of gender equality on economic growth of Pakistan

The present paper examines the impact of gender discrimination in context of education, health and labor force participation rate in Pakistan. The significance of education, health and equal employment opportunities for Pakistani female has been highlighted in this study. The dependent variable is Economic growth (GDP) and three independent variables literacy rate, life expectancy and labor force participation rate are selected as key variables. To analyze the short term as well as long term effects of variables and their speed of adjustment Autoregressive distributed lag (ARDL) and error correction (ECM) models were applied respectively. Moreover the Bounds testing analysis confirmed the existence of a long-term linkage between the variables. ARDl test has been employed to the available data which shows significant impact of literacy rate of female and life expectancy a proxy of health factor on the economic growth of Pakistan during selected twenty years (2003-2023). Labor force participation rate of female shows an insignificant effect on economic growth.

Time-Lagged Response of Streamflow in the Lower Yellow River to the Water Regulation by Xiaolangdi Reservoir: Implication for Efficient Water Supply

The Lower Yellow River (LYR) is a vital water resource for agriculture, industry, and domestic use in the surrounding areas. Understanding the delayed response of local streamflow response to remote reservoir operations is crucial for effective water management and flood control. In this work, we utilize historical hydrological data and statistical analysis techniques to investigate the time-lagged response of streamflow in the LYR to water regulation by the Xiaolangdi Reservoir. The results demonstrate that there is a time lag of 1.98 days, 2.86 days, and 3.93 days between the record of water regulation at Xiaolangdi Reservoir and the arrival time at Gaocun, Aishan, and Lijin stations, respectively. Time lag correction is proven to be crucial when establishing the relationship between the daily streamflows in the LYR and those at Xiaolangdi station. Further analysis reveals that the travel distance of streamflow is the dominant factor determining the lag time, with a time lag coefficient of 0.57 days per hundred kilometers. It is expected that the findings in this study could offer a fundamental basis for decision-makers in water resource management.

Evidence from the energy-technology-growth nexus: A new study based on technology-minerals based complexity index

The increasing trend in sustainable economic growth over the last few decades has elevated the energy demand, technological innovation, and access to minerals resources are contributing well to economic development. This article investigates the nexus among minerals resource complexity, energy consumption, technology, and economic growth by employing autoregressive distributed lag and vector error correction techniques for Pakistan from 1995 to 2021. Following thorough research, the long-term results show that an important 9.73 points of economic growth result from every 1 % increase in the complexity of natural resources. On the other hand, technology and energy use negatively affect economic growth, causing drops of −0.03 and −12.9 points, respectively. One-way causality was noted between mineral resources' complexity and economic growth. Moreover, a one-sided causality effect was also confirmed between energy use, technology, and economic growth. Additionally, it was predicted that there is a neutral causality between mineral resources and technology. Corresponding to this, technology and energy consumption have a bidirectional causal relationship. These results imply that energy consumption, technological advancements, and mineral resources contribute as major economic growth drivers and can improve environmental quality.

Macroeconomics factor, institutional quality and export performance: Empirical evidence from Pakistan

AbstractA country's institutional quality (INS) influences its export performance (EXP) and plays a vital role in international trade. The purpose of this study is to investigate the short‐run and long‐run relationships among these macroeconomic factors in Pakistan. Annual data from the World Development Indicators and the International Country Risk Guide were used from ‘1989 to 2019’. To investigate the short‐run and long‐run linkage between INS and EXP, the non‐linear auto‐regressive distributed lag and error correction model are used after incorporating structural breaks. Additionally, the macroeconomic explanatory variables used are the exchange rate (ER), human capital (HC), gross domestic product (GDP) and foreign direct investment (FDI). In the long run, INS, HC, GDP and FDI have a significant positive relationship with EXP, whereas the ER has a significant negative relationship. In the short run, INS is significant and positive, whereas HC, GDP and FDI with EXP are modest but significantly positive. To improve export performance in Pakistan, strategic reform of governmental institutions is required.

Carbon nanotube-based multiple source C-arm CT system: feasibility study with prototype system.

To extend the field of view while reducing dimensions of the C-arm, we propose a carbon nanotube (CNT)-based C-arm computed tomography (CT) system with multiple X-ray sources. A prototype system was developed using three CNT X-ray sources, enabling a feasibility study. Geometry calibration and image reconstruction were performed to improve the quality of image acquisition. However, the geometry of the prototype system led to projection truncation for each source and an overlap region of object area covered by each source in the two-dimensional Radon space, necessitating specific corrective measures. We addressed these problems by implementing truncation correction and applying weighting techniques to the overlap region during the image reconstruction phase. Furthermore, to enable image reconstruction with a scan angle less than 360°, we designed a weighting function to solve data redundancy caused by the short scan angle. The accuracy of the geometry calibration method was evaluated via computer simulations. We also quantified the improvements in reconstructed image quality using mean-squared error and structural similarity. Moreover, detector lag correction was applied to address the afterglow observed in the experimental data obtained from the prototype system. Our evaluation of image quality involved comparing reconstructed images obtained with and without incorporating the geometry calibration results and images with and without lag correction. The outcomes of our simulation study and experimental investigation demonstrated the efficacy of our proposed geometry calibration, image reconstruction method, and lag correction in reducing image artifacts.

Circular economy, environmental quality and tourism receipts in Europe: A time series data analysis.

The study examines how progress towards a circular economy (CE), patents related to recycling and secondary raw materials as a proxy for innovation, affect tourism receipts. The study uses Autoregressive Distributed Lag (ARDL) and Error Correction Method (ECM) to analyse time series data from EU countries from 2000 to 2020. Our estimates show that there exist long-run and short-run equilibrium relationships. In sum, evidence shows that promoting circular innovative practices, including recycling and using secondary raw materials in tourist destinations, could improve environmental quality and positively impact tourism receipts. The study concludes with policy and practical suggestions for circular economy innovation towards green tourism, destination management, and sustainable tourism.

The Role of Industrialization on Employment and Economic Growth in South Africa

Nowadays economic performance and people's well-being are driven by various factors linked to technological improvement and industrialization. South Africa is one of the countries that adopted technology and innovation to improve its economic performance and employment conditions. However, the country is still facing a growing unemployment rate and sluggish economic growth. The current study investigated the role of industrialization in heightening employment and economic growth. The autoregressive distributed lag (ARDL) and error correction model (ECM) approaches were applied to time series data from 1998 to 2019. Empirical findings indicated that industrialisation has a significant impact on South African economic growth and employment opportunities. While automotive, food and beverage, chemical and metal industries positively affect economic growth; employment growth is fuelled by high production in food and beverage, chemical, automotive and metal industries. Nonetheless, high production in clothing and chemical industries have adverse effects on economic and employment growth respectively. In the short run, employment behaviour is determined by the production of metal, food and beverages industries while changes in economic growth are driven by production in the automotive and metal industries. Grounded on findings, South African policymakers should consider pro-industrialization strategies, especially in those industries whose production is highly demanded such as metal, food and beverages. These industries enhance trade and the latter improve economic growth and create employment.

Stokvel saving and banking sector liquidity in South Africa: cointegration and short-run dynamics

Stokvel is a term used in South Africa to denote an informal saving club. A large population of South Africa are members of one stokvel or the other. A large amount of stokvel savings go unaccounted for in the banking sector resulting in distortions in the flow of funds in the banking sector. Thus, the objective of this paper was to establish the presence of a long-run relationship and causality between stokvel savings, money supply, gross domestic product growth rate and banking sector liquidity in South Africa. Applying the Autoregressive Distributed Lag (ARDL) and Error Correction Model (ECM) techniques on quarterly time series data for the period from 1987Q3 to 2020Q1, the study reveals that in the long run, stokvel savings and money supply were found to have a negative relationship with banking sector liquidity albeit insignificant, however, gross domestic product growth rate exhibited a negative and statistically significant relationship at 1%. The coefficient of the error correction model (ECM(-1)) was, as expected, negative and statistically significant thus providing evidence of a short-run relationship. This study concludes that informal savings must be included in the formal banking services to harness the cash that is held by the informal sector and thus improve banking sector liquidity while minimizing the prevalence of financial disintermediation.

Anomalous heating rate effect in GdAl3(BO3)4:Dy3+ under beta radiation stimulation: Analysis of dose response and kinetic parameters

This study presents a comprehensive investigation into the thermoluminescence (TL) properties of Dy3+-activated gadolinium aluminate garnet (Dy3+:GdAl3(BO3)4 or Dy3+-GAB) phosphor materials. The research aims to unravel the intricate interplay among heating rate, radiation dose, and TL glow curve responses to optimize dosimetry applications. The TL response of the material is scrutinized across diverse heating rates (HR) and dose levels, while accounting for temperature lag correction. Concentration quenching effects are explored through Dy3+ concentrations spanning from 0.5 to 7 wt%, revealing the optimal doping concentration to be 3 wt%. The study underscores the critical role of choosing an appropriate band-pass filter, revealing the effectiveness of the “IRSL-TL wideband blue” filter's in capturing TL signals. Furthermore, the study examines kinetic parameter estimated using different approaches and shedding light on how heating rate and radiation dose affect activation energy values. Intriguingly, the study observes an anomalous heating rate effect, resulting in elevated TL peak intensities at higher HR. This effect is attributed to non-radiative transitions and the semi-localized transition model. The reusability of Dy3+-doped GAB is also examined, confirming its consistency and reproducibility across multiple uses. This study significantly contributes to the advancement of TL dosimetry methodologies and enhances our understanding of luminescent material behaviours. We utilized both the Tm-Tstop technique in conjunction with the Initial Rise (IR) method and Computerized Glow Curve Deconvolution (CGCD) techniques, revealing the presence of seven overlapping glow peaks alongside the main ones. Both methods appear to provide excellent agreement in terms of activation energy values, ranging from 0.70 to 1.50 eV for each peak. Furthermore, the findings strongly indicate the effective utilization of TL signals in radiation dosimetry applications.

International Trade in Muslim-Majority Countries and Volatility of The Dollar Exchange Rate

The study was to examine the relationship between the volatility of the dollar exchange rate on international trade variables, namely exports and imports, in 3 Muslim-majority countries. This study analyzes the possibility that the volatility of the dollar exchange rate can hamper the economy of a country. The method used is the Autoregressive Distributed Lag and Error Correction Model (ARDL-ECM) to analyze the short-term and long-term relationship between the volatility of the dollar exchange rate against international trade in Indonesia, Pakistan, and Turkey. And to see the causality relationship between variables, the Granger-Causality method is used. The data used are monthly data for the period January 2006 to December 2021. From this research, it can be seen that in the long term there is no relationship between exchange rate volatility and export performance except in Turkey. Meanwhile, there is a relationship between exchange rate volatility and import performance in Pakistan and Turkey. In the short term in the export dependent model, Turkey is the country that takes the longest to respond to shocks to international trade, while in the import dependent model, Indonesia takes the longest to respond to shocks and Pakistan is the fastest country.

A quantitative CBCT pipeline based on 2D antiscatter grid and grid-based scatter sampling for image-guided radiation therapy.

Quantitative accuracy is critical for expanding the role of cone beam CT (CBCT) imaging from target localization to quantitative treatment monitoring and plan adaptations in radiation therapy. Despite advances in CBCT image quality improvement methods, quantitative accuracy gap between CBCT and multi-detector CT (MDCT) remains. In this work, a physics-driven approach was investigated that combined robust scatter rejection, raw data correction and iterative image reconstruction to further improve CBCT image quality and quantitative accuracy, referred to as quantitative CBCT (qCBCT). QCBCT approach includes tungsten 2D antiscatter grid hardware, residual scatter correction with grid-based scatter sampling, image lag, and beam hardening correction for offset detector geometry linac-mounted CBCT. Images were reconstructed with iterative image reconstruction to reduce image noise. qCBCT was evaluated using a variety of phantoms to investigate the effect of object size and its composition on image quality, and image quality was benchmarked against clinical CBCT and gold standard MDCT images used for treatment planning. QCBCT provided statistically significant improvement in CT number accuracy and reduced image artifacts when compared to clinical CBCT images. When compared to gold standard MDCT, mean HU errors in qCBCT and clinical CBCT were 17±9 and 38±29 HU, respectively. Magnitude of phantom size dependent HU variations were comparable between MDCT and qCBCT images. With iterative reconstruction, contrast-to-noise ratio improved by 25% when compared to clinical CBCT protocols. Combination of novel scatter suppression techniques and other data correction methods in qCBCT provided CT number accuracy comparable to gold standard MDCT used for treatment planning. This approach may potentially improve CBCT's promise in fulfilling the tasks that demand high quantitative accuracy, such as online dose calculations and treatment response assessment, in image guided radiation therapy.