Redefining the Economical Power of Nations

This paper is (over the formulas) self explaining . The measurement of economies no longer by GDP alone, but by an Index that includes other important factors as well, a So-cial factors relativized GDP. This index cuts out the part of the GDP that is long term fro-zen up by social transfers (using the highly aggregated GINI coefficient). Social factors relativized GDP: GDP – GDP x GINI = K_Index Written differently: (1 – GINI) x GDP = K_Index Inflation indexed Version: (1 – GINI – Inflation) x GDP = K_Index_Infl. Productivity Index: K_Index / Labor Force = K_PROD Inflation indexed Productivity Index: K_Index_Infl. / Labor Force = K_PROD_Infl. Debt-to-K_Index: National debt / K_Index = K_Debt Debt-to-K_Index_Infl: National debt / K_Index_Infl. = K_Debt_Infl

Redefining the Economical Power of Nations: An international macroeconomic model that introduces a future aspect into the GDP

The paper challenges the current common rankings of economies when measured over the GDP, and introduces a set of new Indices based on the factors GDP, Gini Coefficient and Inflation. This Social factors relativized GDP cuts out that part of the GDP, which is structurally long term frozen up by social transfers. Furthermore, the paper introduces an economic model that implements the future aspect into the GDP over the factors of change in capital expenditures and change in private investments. The first part of the pa-per explains the κ_Index models, the factors that were applied, as well as the reasons for the choice. The second part of the paper shows variations of the κ_Index including a few ideal-typical examples. The final part asks some critical questions and concludes the pa-per. Basic social factors relativized GDP: κ _Index = GDP – GDP x Gini is (1 – GINI) x GDP Inflation indexed Version: κ _Index_Infl. = (1 – Gini – Inflation) x GDP Future aspect of GDP With Private Investment variable: κp = (B + B × ΔP) – (B × G) With Private Investment variable and inflation: κip = (B + B × ΔP) - [(B × G)+(B × In)] Productivity Index: κ_PROD = κ_Index / Labor Force = κ_PROD Inflation indexed Productivity Index: κ_PROD_Infl. = κ_Index_Infl. / Labor Force Debt-to- κ _Index κ _Debt = National debt / κ_Index Debt-to- κ _Index_Inflation κ _Debt_Infl. = National debt / κ_Index_Infl

Redefining the Economical Power of Nations: An international macroeconomic model that introduces a future aspect into the GDP

The paper challenges the current common rankings of economies when measured over the GDP, and introduces a set of new Indices based on the factors GDP, Gini Coefficient and Inflation. This Social factors relativized GDP cuts out that part of the GDP, which is structurally long term frozen up by social transfers. Furthermore, the paper introduces an economic model that implements the future aspect into the GDP over the factors of change in capital expenditures and change in private investments. The first part of the pa-per explains the κ_Index models, the factors that were applied, as well as the reasons for the choice. The second part of the paper shows variations of the κ_Index including a few ideal-typical examples. The final part asks some critical questions and concludes the pa-per. Basic social factors relativized GDP: κ _Index = GDP – GDP x Gini is (1 – GINI) x GDP Inflation indexed Version: κ _Index_Infl. = (1 – Gini – Inflation) x GDP Future aspect of GDP With Private Investment variable: κp = (B + B × ΔP) – (B × G) With Private Investment variable and inflation: κip = (B + B × ΔP) - [(B × G)+(B × In)] Productivity Index: κ_PROD = κ_Index / Labor Force = κ_PROD Inflation indexed Productivity Index: κ_PROD_Infl. = κ_Index_Infl. / Labor Force Debt-to- κ _Index κ _Debt = National debt / κ_Index Debt-to- κ _Index_Inflation κ _Debt_Infl. = National debt / κ_Index_Infl

Working Paper: Redefining the Economical Power of Nations

The measurement of economies no longer by GDP alone, but by an Index that includes other important factors as well, a Social factors relativized GDP. Social factors relativized GDP: GDP – GDP x GINI = K_Index Written differently: (1 – GINI) x GDP = K_Index Inflation indexed Version: (1 – GINI – Inflation) x GDP = K_Index_Infl. Productivity Index: K_Index / Labor Force = K_PROD Inflation indexed Productivity Index: K_Index_Infl. / Labor Force = K_PROD_Infl. Debt-to-K_Index: National debt / K_Index = K_Debt Debt-to-K_Index_Infl: National debt / K_Index_Infl. = K_Debt_Infl

Solution Equilibrium Studies on Anticancer Ruthenium(II)–eta6-p-cymene Complexes of 3-Hydroxy-2(1H)-pyridones

Ru-II(eta(6)-p-cymene) complexes of bidentate (0,0) alkoxycarbonylmethyl-3-hydroxy-2(1H)-pyridone ligands exhibit in vitro antitumor activity. We determined the stoichiometry and stability in aqueous solution of two examples by pH-potentiometry, H-1 NMR spectroscopy and UV-vis spectrophotometry and also characterized the proton dissociation processes of the ligands. Formation of mono-ligand complexes with moderate stability was found to predominate in the physiological pH range. Moreover, the chlorido/aqua co-ligand exchange processes of the [Ru-II(eta(6)-p-cymene)(L)(H2O)](+) species were also monitored and 55-65% of the aqua ligand was found to be replaced by chloride in 0.2 M KCl-containing aqueous solutions. Under basic conditions, the complexes decompose to dinuclear tri-hydroxido-bridged [Ru-2(I)(eta(6)-p-cymene)(2)(OH)(3)](+) and metal-free ligand and also a hydroxido species [Ru-II(eta(6)-p-cymene)(L)(OH)] was found. Furthermore, the ligands contain an ester functional group, which may hydrolyze at basic pH, which is however negligible at acidic or neutral pH

Periventricular magnetisation transfer abnormalities in early multiple sclerosis

OBJECTIVE: Recent studies suggested that CSF-mediated factors contribute to periventricular (PV) T2-hyperintense lesion formation in multiple sclerosis (MS) and this in turn correlates with cortical damage. We thus investigated if such PV-changes are observable microstructurally in early-MS and if they correlate with cortical damage. METHODS: We assessed the magnetisation transfer ratio (MTR) in PV normal-appearing white matter (NAWM) and in MS lesions in 44 patients with a clinically isolated syndrome (CIS) suggestive of MS and 73 relapsing-remitting MS (RRMS) patients. Band-wise MTR values were related to cortical mean thickness (CMT) and compared with 49 healthy controls (HCs). For each band, MTR changes were assessed relative to the average MTR values of all HCs. RESULTS: Relative to HCs, PV-MTR was significantly reduced up to 2.63% in CIS and 5.37% in RRMS (p<0.0001). The MTR decreased towards the lateral ventricles with 0.18%/mm in CIS and 0.31%/mm in RRMS patients, relative to HCs. In RRMS, MTR-values adjacent to the ventricle and in PV-lesions correlated positively with CMT and negatively with EDSS. CONCLUSION: PV-MTR gradients are present from the earliest stage of MS, consistent with more pronounced microstructural WM-damage closer to the ventricles. The positive association between reduced CMT and lower MTR in PV-NAWM suggests a common pathophysiologic mechanism. Together, these findings indicate the potential use of multimodal MRI as refined marker for MS-related tissue changes