Study of gross alpha (GA) and gross beta (GB) activity in road and surface deposited sediments were performed in various geographical areas in three Russian cities. To perform radiation measurements, new methods were applied which allow dealing with low mass and low volume dust size (2-100μm) samples obtained after the size fractionation procedure. The 2-10 μm fraction size has the highest gross beta activity concentration (GB)– 1.32Bq/g in Nizhny Novgorod (NN) and Rostov-On-Don (RND) while the 50-100 μm fraction size in Ekaterinburg. This is maybe associated with the subsistence of radionuclides that conveyed through natural processes and anthropogenic applications. The highest gross alpha activity concentration (GA) in fraction sizes was found in Rostov-on-Don city within the 50-100 μm– 0.22Bq/g. The fraction size 50-100 μmhas a higher gross alpha activity concentration than 2-10 and 10-50 μmfraction sizes due to natural partitioning of the main minerals constituting the urban surface deposited sediment (USDS). The geochemical processes that occur during the formation and transportation of USDS are reflected in the observed dependencies.Developed experimental methods of radiation measurements allowed to the extent the methodological base of urban geochemical studies.

A remarkable, unquestioned assumption in studies measuring the association between national average Intellectual Quotients (IQ) and Gross Domestic Products (GDP) per capita is that a supposedly immutable genetic factor (IQ) may be correlated with a markedly fluctuant one (the wealth of nations). Using historical GDP per capita data produced by the Maddison project, we find that, over history, the (Pearson productmoment) correlation coefficient (r) between average IQ and GDP per capita is highly variable and ranges from strong negative values to strong positive values. The correlation between national IQ and GDP per capita is thus a snapshot of the world order at some point in time, and historical data allow us to identify several other eras. Moreover, global GDP at any point in time is never difficult to predict in the first place. We show that arbitrary ad-hoc scores based on a country’s continental location present a more significant correlation with contemporary GDP per capita. We conclude this paper by a call to clarify the purpose of IQ studies in Macroeconomics and for the consideration of GDP as a time-series in this line of research.

One of the most important parameters that characterize the traction-coupling properties of a wheeled tractor is its slip. The more tractor's gross traction, the higher its traction-coupling properties. But, this gross traction should not exceed its maximum possible value, which, in turn out, is to be determined by the maximum permissible slip. This article provides the equation to calculate this crucial parameter and establishes the dependencies between the tractor's slip and soil structure coefficient. It was shown that the value basically depends on such soil characteristics as the bulk deformation coefficient and the coefficient of rolling resistance. Calculations showed that for the average value of the soil bulk deformation coefficient at, the average value of rolling resistance coefficient at 0.16, the ratio value of the maximum permissible soil pressure to the tractor wheel rolling radius at the maximum permitted amount slip of the tractor wheels should not exceed 15%. With more slip, the soil structure deteriorates significantly. In this case, its structure coefficient may be less than critical, equal to 0.4.

Atmospheric CO2 concentration, temperature and precipitation escalate and it is critical to investigate the agricultural practices best suited to face such new conditions. An important aspect is soil management, which alters soil organic matter content, nutrients and structure, and thus soil/atmosphere interactions and ultimately production. This in vitro study addresses greenhouse gas (GHG) emissions from two long-term soil management experiments in France. One set of soil columns were managed with either grain legume + cover crops or no grain legumes + bare fallow. The other with either plowed or reduced tillage soils. GHG exchange (CO2, N2O) measurements was conducted under different environmental conditions, before and during growth of barley and eventually with three levels of barley biomass cuts (everything removed, cut halfway, intact). The gas exchange was influenced by time and environmental settings, and to a smaller degree management history, with highly variable emissions of N2O. The environmental treatments induced different patterns of effect depending on the management history of the soils. The gas exchange from soil with grain legume was more responsive to the environmental treatments than the rotation without grain legumes. Depending on the history of tillage, the gas exchange responded likewise differently to the induced environment.

This study examined the link between tax revenue components and economic growth in South Africa, utilizing time series data for the period of 22 years. The stationarity of the variables was established using the Phillips-Perron (PP) unit root test, and the existence of long-run and short-run equilibrium conditions was tested using the Autoregressive Distributed Lag (ARDL) model. As a proxy for economic growth, the study used the real GDP growth rate as the dependent variable, with company income tax, personal income tax, taxes on international trade and transactions, taxes on income, profits, and capital gains tax, foreign direct investment, inflation, and gross savings as the independent variables. According to the PP findings, none of the variables are integrated at a higher order than one, i.e. (1). All variables are found to be cointegrated, and all explanatory variables have a long-run link with economic growth. According to the ARDL findings, company income tax, personal income tax, and taxes on international trade and transactions all have a positive long-run and short-run link with economic growth, whereas capital gain tax, foreign direct investment, and gross savings all have a negative long-run and short-run link with economic growth. The long-run coefficient is negatively related to RGDP, while the short-run coefficient revealed a positive link between inflation and economic growth, among other findings. Heteroskedasticity and autocorrelation are not present in our model, according to diagnostic tests. The CUSUM and CUSUMSQ values indicate that the model is structurally sound.

This paper investigates and explores the minor crops production in Pakistan and its association with the agricultural gross domestic product. The agriculture sector of Pakistan has a rich contribution to the economic growth and development. Like major crops; minor crops also have a vital role to boost up the agriculture sector. Time span data was used in this study and it was collected from the Economy Survey of Pakistan annual reports. Augmented Dickey-Fuller (ADF) unit root test and Ordinary Least Square (OLS) method was used to analyze the data and results were interpreted by employing the Johansen co-integration test. Study results reveal that bajra, barely and jowar has a significant impact on the agricultural gross domestic product, while the total cropped area has a negative impact on AGDP. On the basis of the study results, we recommend the policy implications.

In this paper, we study the Parisian time of a reflected Brownian motion with drift on a finite collection of rays. We derive the Laplace transform of the Parisian time using a recursive method, and provide an exact simulation algorithm to sample from the distribution of the Parisian time. The paper is motivated by the settlement delay in the real-time gross settlement (RTGS) system. Both the central bank and the participating banks in the system are concerned about the liquidity risk, and are interested in the first time that the duration of settlement delay exceeds a predefined limit, we reduce this problem to the calculation of the Parisian time. The Parisian time is also crucial in the pricing of Parisian type options; to this end, we will compare our results with the existing literature.

It is important for enterprises to decide their environmental policies after carefully examining their future paths based on the relationship between the environment and the economy. This study focused on Japanese minimum administrative divisions (municipalities) and attempted to quantify the annual environmental efficiency of production activities within each division according to the theory of life-cycle impact assessment (LCIA). This study leverages the assessment theory LIME2, which is an endpoint-type LCIA method developed in 2010 that integrates environmental loads for certain impact categories, such as global warming and land use into a simple indicator by monetary unit. First, annual environmental impact assessments were conducted for all Japanese municipalities based on statistical information that was reliable, verifiable, and comparable. Next, the environmental efficiency of productivity for each division was conceptualized by dividing the gross domestic product by the environmental damage amounts as calculated above. Assessment results for each municipality were placed on a map of Japan in order to visualize the regionality of each indicator. The findings revealed in this study will aid public administrators in their decision-making process with respect to environmental policies.

In most econometrics literature, the Autoregressive Distributed Lag (ARDL) model is often applied in many economic analyses to study short and long run relationships. This is because ARDL model can deal with economic variables that are integrated of different order (I(0), I(1) or combination of both) and also it is robust where there is single long-run relationship between the underlying variables in a simple sample size. This study applied the ARDL model to examine the contributions of commercial Banks to GDP growth in Nigeria. To achieve this, annual data covering 1981 to 2015 for loans and advances, savings, lending rates and GDP of Financial Institutions were collected from CBN bulletin. The ADF test revealed that the variables are I(1) except for lending rate which was of I(0) order. The ARDL(1,1,1,2) model revealed that loans and advances, and lending rates are significantly positively related to GDP in Nigeria but savings was not significant in the model. The model revealed some evidence of short run relationships while the ecm(-1) was -0.6156 (P-value=0.0038<0.05) which means that the rate of the speed of adjustment to equilibrium is 61.56% annually. The estimated model is free from serial correlation, multicollinearity, heteroscedasticity while the model is stable and the residuals are normally distributed. The study recommends that savings and savings culture should be encouraged in Nigeria since economic theory states that savings and investment are related in any economic development.

A crop-weed simulation model is presented to compare and evaluate Integrated Weed Management (IWM) strategies. Specifically, the model was parameterized for soybean crops in competition with Euphorbia davidii Subils. We used both, weed and crop demographic data surveyed in agronomic fields of the central zone of the Buenos Aires province, Argentina, throughout two crop cycles (2011/2012 and 2013/2014). The proposed model underwent a calibration process and subsequent validation with 70/30 % data split respectively (N=37). Two annual-based and one multiannual-based case studies were simulated to demonstrate the performance of the model. Different IWM strategies were compared under both, operational and tactical planning horizons through the evaluation of different model outcomes (i.e. crop yield, interspecific competition, economic return, and environmental impact). Our case studies results suggest that the inclusion of cultural management practices could reduce weed interspecific competition by 46 to 97 % and weed seed production by 40 to 89%. An increment in both expected crop yield, by 6 to 20%, and annual gross margin, by 44 to 199 US$.ha-1, were obtained in silico for similar levels of environmental impact.

The universal health insurance system in Taiwan was formed with good intentions to help vulnerable groups. However, the possibility of bankrupting the system due to wasted medical resources. In this study, using the medical expenditures of the Taiwanese Government and gross domestic product (GDP) as variables, the wavelet analysis method was used to empirically study the correlations and leading-lagging relationships in quarterly data in the period from 1996 to 2016. In addition, the dependent population of the insured was used as the control variable. This population had no income and had high medical demands. Results: After the dependent population was included as a control variable, there was a period of low-frequency (one to four years short-term) linkage correlation, as well as a period of high-frequency (four to eight years long-term) linkage correlation. In addition, for more than eight years, there was also a high degree of linkage correlation, indicating that the linkage between medical expenditures and GDP occurred over the long term. Moreover, since medical expenditures positively affected GDP, one-way causality was observed. However, after 2008, regardless of whether a long or short term was examined, there was almost no linkage correlation. Before 2008, the medical expenditures of the government were positively correlated with economic growth; i.e., they enhanced economic growth. But, after 2008, this effect had already disappeared. The universal health insurance system has long been denounced as a waste of medical resources, and the waste must be immediately stopped. The government urgently needs to find a new solution.

This paper based on systems - theoretic approach to the definition of a country's GDP as not directly observable characteristic of system state. Leontief dynamic model is generalized to take into account the stimulating effect of consumption on GDP growth. In consumption, apart from final consumption, terms are considered: balance of foreign trade, fictitious investments and hidden costs. The Kalman filter uses Rosstat's gross output (for system output) and final consumption (for system control) data from 1995 to 2015. It is concluded that if in the years 2014, 2015 it was possible to increase consumption by 5% by, say, price cuts or some increase in money supply, then GDP would be greater by about 2.5%. GDP real values in recent years are most likely greater than official values. Fictitious investments and hidden costs are found in the amount of up to third the value of final consumption. The accuracy of one-year forecasts of true GDP by the methodology of this article is approximately 1.5%.

Urban stormwater runoff from a medium-density residential development in southeast Queensland has been monitored in the field since November 2013. A treatment train installed on the site includes rainwater tanks collecting roofwater, 200-micron mesh baskets installed in grated gully pits and two 850 mm high media filtration cartridges installed in an underground 4 m³ vault. A monitoring protocol developed by research partners, Queensland University of Technology (QUT), guided the monitoring process over a 4.5-year period. Heavy metals were included in the list of analytes during the monitoring period as the catchment is within 1 km of the environmentally-sensitive Moreton Bay, Queensland. Removal efficiencies observed at this site for the regulated pollutants; total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN) for the pit baskets were 61%, 28% and 45% respectively. The cartridge filters removed 78% TSS, 59% TP, 42% TN, 40% total copper and 51% total zinc. As the measured influent concentrations to the cartridge filters were low when compared to industry guidelines, the dataset was merged with international field results for TSS (n=39) and TP (n=32) but truncated within anticipated guideline levels. The combined dataset for the media filter demonstrates performance at 89% TSS, 66% TP and 42% TN. The total gross pollutant generation rate from the medium-density residential catchment was observed to be 0.24 m³/Ha/year, with a corresponding air-dried mass of 142.5 kg/Ha/year. Less than 2% of the gross pollutant mass was anthropogenic. The findings of this research suggest that the treatment train, and in particular the media filter, holds promise for the removal of total copper and total zinc, in addition to TSS, TP and TN, from urban stormwater runoff. Based on a maximum, low risk trigger TN concentration of 1.5 mg/L, the field test data from 4.5 years of operation and standard maintenance, suggests a 5.5-year replacement interval for the media filters.

Student mobility is one of the most important indicators to reflect institutional internationalization in a sustainable higher education system. While student mobility issues have been addressed persistently, the phenomenon is rarely discussed in association with higher education expansion. Since higher education sustainable development has received much scholarly attention, monitoring student mobility flows to adjust international strategies is necessary. This study explored practical approaches to detect student mobility flows in the process of higher education expansion. Targeting Taiwan’s higher education system as an example, we addressed the topic of system expansion and the core issues of student mobility. Target series data were collected from 1950 to 2021, including higher education enrollment, gross enrollment ratio (GER), and number of inbound and outbound students. The data were transformed with index formats, for example enrollment increasing ratio (IR) and net flow ratio. The cross-correlation function (CCF) and autoregressive integrated moving average (ARIMA) were used to determine the correlations of the series data and their future trends. The findings suggested that the effect of system expansion, with GER and IR, might influence the mobility ratios significantly in the process of higher education expansion. This study confirmed that the time series approaches work well in detecting the phenomena of higher education expansion and their effects on student mobility flows in the future.

The present reality of the Nigerian economy is the fact that inflation has remained unabated in spite of all exchange rate measures that have been adopted by the monetary authority. This calls for investigation into the extent to which exchange rate impact on inflation in Nigeria. The research paper examined the impact of exchange rate depreciation on inflation in Nigeria for the period 1981–2017, using Auto Regressive Distributed Lag (ARDL) Bounds Test Cointegration Procedure. The research shows that inflation rate in Nigeria is highly susceptible to lagged inflation rate, exchange rate, lagged exchange rate, lagged broad money, and lagged gross domestic product at 5% level of significance. A long run relationship was also found to exist between inflation rate, gross domestic product and general government expenditure, indicating that the model has a self-adjusting mechanism for correcting any deviation of the variables from equilibrium. Therefore, this study concludes that exchange rate is an important tool to manage inflation in the country; thus, this paper recommends that policies that have direct influence on inflation as well as exchange rate policies that would checkmate inflation movement in the country, should be used by the Central Bank of Nigeria. Also, monetary growth and import management policies should be put in place to encourage domestic production of export commodities, which are currently short-supplied. In addition, policy makers should not rely on this instrument totally to control inflation, but should use it as a complement to other macro-economic policies.

In the present study, a hybrid optimizing algorithm has been proposed using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for Artificial Neural Network (ANN) to improve the estimation of electricity demand of the state of Tamil Nadu in India. The GA-PSO model optimizes the coefficients of factors of gross state domestic product (GSDP), per capita demand, income and consumer price index (CPI) that affect the electricity demand. Based on historical data of 25 years from 1991 till 2015 , the simulation results of GA-PSO models are having greater accuracy and reliability than single optimization methods based on either PSO or GA. The forecasting results of ANN-GA-PSO are better than models based on single optimization such as ANN-BP, ANN-GA, ANN-PSO models. Further the paper also forecasts the electricity demand of Tamil Nadu based on two scenarios. First scenario is the "as-it-is" scenario , the second scenario is based on milestones set for achieving goals of "Vision 2023" document for the state. The present research also explores the causality between the economic growth and electricity demand in case of Tamil Nadu. The research indicates that the direct causality exists between GSDP and the electricity demand of the state.

The antibiotic residues and pathogenic resistance against the drug are very common in poultry due to usage of antibiotics in their feed. It is the need of the time to use natural feed additives as effective alternatives instead of synthetic antibiotic. The aim of this study was to investigate the immune response of Nigella sativa and Curcuma longa in broilers under biological stress against Pasteurella multocida. The total 100, one-day old chicks were divided into 5 groups. The Groups 1 and 2 were served as control negative and control positive. Both control groups were receiving simple diet without any natural feed additives but infection was given in Group 2 at day 28 with the dose of 5.14×107 CFU by IV. Groups 3A & 3B were offered 2% seed powder of Nigella sativa, Groups 4A & 4B were offered Curcuma longa 1% in powdered form and Group 5A & 5B were offered both Curcuma longa 1% & Nigella sativa 2% in feed from day 1 and groups 3B, 4B and 5B were challenged with Pasteurella multocida. The Haemagglutination inhibition titter against Newcastle Disease Virus (NDV), feed conversion ratio, mortality, gross and histopathology were studied. The results of this study revealed that haemagglutination inhibition titers against NDV were highly significant (P< 0.05) in treated groups, highest titers (3A 6.8, 3B 6.4 and 5A 7.2) were obtained from treated Group. The feed conversion ratio (FCR) of Nigella sativa + Curcuma longa treated Groups (5A 1.57 and 3A 1.76) were higher as compared to other non-treated groups. The gross and histopathological changes were much severe in control positive, but less changes were seen in treated groups. Therefore, we recommend that natural feed additives; black cumin (Nigella sativa) and turmeric (Curcuma longa) act as immune enhancer in broilers against Pasteurella multocida.

We introduce a class of logarithmic wave equation. We study the global existence of week solution for this class of equation. We deal with the initial boundary value problem of this class. Using the Galerkin method and the Gross logarithmic Sobolev inequality we establish the main theorem of existence of week solution for this class of equation arising from Q-Ball Dynamic in particular.

Ensuring equal access to affordable higher education for women and men has become a crucial target of UNESCO’s SDG4-Education 2030. Currently, about one-third of the world's college-age population participates in higher education, while the gender disparity persists in various systems. This study employed GDP per capita, gross enrollment ratio (GER), and the gender parity index (GPI) to demonstrate how the education systems have expanded resulting in the transformation of gender parity. We selected Japan, Korea, Taiwan, and the UK as research targets using a cross-correlation function and trend analysis to detect concurrent relationships and future trends with GDP per capita, GER, and GPI. The findings suggest Japan, Korea, and the UK continue to show gender disparity and need to respond to this issue in their policy intervention for SDG4-Education 2030. The results reveal a potential problem in the UK when GPI growth might become unlimited with females dominated. This study suggests the higher education expansion phenomenon and gender diversity in mass and universal systems can be detected by the trend analysis with GDP per capita, GER, and GPI in different settings. The design of the study provides an example to explore the gender diversity patterns in higher education systems for sustainable development.

The study uses annual time series data from the South Africa Reverse Bank (SARB) from 1980 to 2020 to examine the effectiveness of fiscal policy on economic growth in South Africa. The Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests, as well as the Johansen Co-integration test, Granger causality test, and Vector Auto-Regression (VAR) method, were used in the study. Real GDP per capita (RGDP) is used as proxy of economic growth and gross fixed capital formation (GFCF), government expenditure (GEXP) and government deficit (GOVD) as the proxies of fiscal policy. The ADF test results show that all variables are stationary at the first difference, with the exception of GFCF and GEXP, which are stationary at I(0), whereas the PP test results show that all variables are stationary at I(1), with the exception of GEXP, which is stationary at I(0). At Maximum Eigenvalue, the four variables are not cointegrated. The findings of the Granger causality test demonstrated a unidirectional causation from GOVD to RGDP, as well as a bidirectional causality from RGDP to GFCF and GEXP. Error Correction Model Estimated using VAR shows that GFCF, GEXP have positive effect on RGDP whereas GOVD has a negative effect on RGDP in the short run. The findings also presented that the VAR's residuals are homoscedastic, which means they are normally distributed and have no serial correlation.

We study the μ-μ45-T phase diagram of the 2+1-dimensional Gross-Neveu model, where μ denotes the ordinary chemical potential, μ45 the chiral chemical potential and T the temperature. We use the mean-field approximation and two different lattice regularizations with naive chiral fermions. An inhomogeneous phase at finite lattice spacing is found for one of the two regularizations. Our results suggest that there is no inhomogeneous phase in the continuum limit. We show that a chiral chemical potential is equivalent to an isospin chemical potential. Thus, all results presented in this work can also be interpreted in the context of isospin imbalance.

Low-cost miniature hyperspectral and thermal cameras onboard lightweight unmanned aerial vehicles (UAV) bring new opportunities for monitoring land surface variables at unprecedented fine spatial resolution with acceptable accuracy. This research applies hyperspectral and thermal imagery from a drone to quantify upland rice growth and water use efficiency (WUE) after biochar application in a Costa Rican dry region. The field flights were conducted over two experimental groups with bamboo biochar and sugarcane biochar amendments and one control group without biochar application. Rice canopy biophysical variables were estimated by inversion of a canopy radiative transfer model on hyperspectral reflectance. Variations in gross primary production (GPP) and WUE across treatments were estimated from the normalized difference vegetation index (NDVI), canopy chlorophyll content (CCC), and evapotranspiration. We found that GPP was increased by 41.9±3.4 % when using bamboo biochar and 17.5±3.4 % when using sugarcane biochar, which was probably due to higher soil moisture in the biochar-amended plots and led to significantly higher WUE by 40.8±3.5 % in bamboo biochar and 13.4±3.5 % in sugarcane biochar. This study demonstrated the use of hyperspectral and thermal imagery from drone to provide indicators for quantifying biochar effects on tropical dry cropland by integrating with ground point samples and physical models.

Kluyveromyces marxianus (K. marxianus) is a newly emerging industrially relevant yeast. It is known to possess a highly efficient Non-Homologous End Joining (NHEJ) pathway that promotes random integration of non-homologous DNA fragments into its genome. The nature of the integration events was traditionally analyzed by Southern blot hybridization. However, the precise DNA sequence at the insertion sites were not fully explored. We transformed a PCR product of the Saccharomyces cerevisiae URA3 gene (ScURA3) into an uracil auxotroph K. marxianus wildtype strain and picked 24 stable Ura+ transformants for sequencing analysis. We took advantage of rapid advances in DNA sequencing technologies and developed a method using a combination of Illumina MiSeq and Oxford Nanopore sequencing. This approach enables us to uncover the Gross Chromosomal Rearrangements (GCRs) that are associated with the ScURA3 random integration. Moreover, it will shine a light on understanding DNA repair mechanisms in Eukaryotes, which could potentially provide insights for cancer research.

The present reality about the Nigerian economy calls for investment and development in the non-oil sector. This becomes necessary as a result of fall in the oil price in the global market. This paper examined the Bayesian Vector Autoregression (BVAR) modeling and forecasting of the dynamic interrelationship between Economic growth and revenue from the oil and non-oil sectors in Nigeria. To achieve this, annual data on Gross Domestic Product (GDP), revenue from oil and non-oil sectors were collected from Central Bank of Nigeria (CBN) bulletin, the sample from 1981 to 2008 was used for analysis, while sample from 2009 to 2014 was used for model validation. Six (6) versions of Sims-Zha BVAR models were compared for out-of-sample forecast, the result revealed the superiority of the BVAR6 model over the other BVAR models. Lastly, evidence from the decomposition forecast errors revealed that revenue of oil sector contributed 7.69% to GDP while revenue from non-oil sector contributed 0.12% to GDP in Nigeria. This paper therefore recommended that the present government should encourage investment that is geared toward development in the non-oil sector, of which it has the capacity to improve the Economic growth of the Nigerian economy.

The aim of this study is to empirically examine the link between foreign direct investment (FDI) and domestic investment (DI) in South Africa over the period of 41 years (1975-2016). Accurately, it attempts to determine whether FDI crowds in or crowds out DI in South Africa. DI is sub-divided into private domestic investment (credit to domestic private sector) and public corporation investment (state owned enterprises). We used the Autoregressive Distributed Lag-Error Correction Model (ARDL-ECM) technique to ascertain long run and short run effects concurrently after establishing that the variables were stationary (using the PP test). The results of the unit root test shows that all variables are integrated of order zero I(0) or integrated of order one I(1), indicating that the series of variables are stationary in the level or first difference form. The findings revealed that variables are cointegrated in the long run. The ARDL model found a negative link between FDI and domestic investment. The result implies that FDI crowds out domestic investment. Moreover, the long run estimate revealed that domestic investment is crowded in by government investment expenditure (GINV). Other findings uncovered that, GDP crowds out private domestic investment while crowding in public corporation investment. Moreover, the long run estimate revealed that domestic investment is crowded in by gross domestic savings (SAV). On the other hand, the real exchange rate (EXCR) crowds out private domestic investment while crowding in public corporation investment. Trade openness (TRA) crowds out domestic investment. Additionally, the short run estimate uncovered that private domestic investment is crowded out by FDI, EXCR, and TRA whereas GINV, GDP and SAV is crowding in private domestic investment. Other findings discovered that, in the short run, public corporation investment is crowded out by FDI, GDP, EXCR and TRA, while GINV and SAV crowd in public corporation investment. The CUSUM confirms that the models are structurally firmness.

Objective: In this pilot study, we described the gross motor development of infants aged 4 to 24 months with congenital heart disease (CHD) and assessed through a systematic develop­mental screening programme, with individualised motor interventions. Methods: Thirty infants who had cardiac repair underwent gross motor evaluations using the AIMS at 4 months, and the Bayley-III at 12 and 24 months. Results: Based on AIMS, 80% of 4-month-old infants had a delay in gross motor development and required physical therapy. Gross motor abilities significantly improved by 24 months. Infants who benefited from regular physiotherapy tended to show better improvement in motor scores. Conclusion: Our study highlights the importance of early motor screening in infants with CHD and suggests a potential benefit of early physical therapy in those at-risk. Further research is needed to assess the effectiveness of systematic developmental screening and individualized inter­vention programmes at identifying at risk patients, and their impact on developmental outcomes.

Evidence-based medicine (EBM) is in crisis, in part due to bad methods, which are understood as misuse of statistics that is considered correct in itself. This article exposes two related common misconceptions in statistics, the effect size (ES) based on correlation (CBES) and a misconception of contingency tables (MCT). CBES is a fallacy based on misunderstanding of correlation and ES and confusion with 2 × 2 tables, which makes no distinction between gross crosstabs (GCTs) and contingency tables (CTs). This leads to misapplication of Pearson’s Phi, designed for CTs, to GCTs and confusion of the resulting gross Pearson Phi, or mean-square effect half-size, with the implied Pearson mean square contingency coefficient. Generalizing this binary fallacy to continuous data and the correlation in general (Pearson’s r) resulted in flawed equations directly expressing ES in terms of the correlation coefficient, which is impossible without including covariance, so these equations and the whole CBES concept are fundamentally wrong. MCT is a series of related misconceptions due to confusion with 2 × 2 tables and misapplication of related statistics. The misconceptions are threatening because most of the findings from contingency tables, including CBES-based meta-analyses, can be misleading. Problems arising from these fallacies are discussed and the necessary changes to the corpus of statistics are proposed resolving the problem of correlation and ES in paired binary data. Since exposing these fallacies casts doubt on the reliability of the statistical foundations of EBM in general, we urgently need to revise them.