Philips College

This research aims to evaluate the effectiveness of monetary circulation in Cyprus by applying the Index of the Cycle of Money, derived from the Theory of the Cycle of Money. The analysis focuses exclusively on the Cypriot economy over the period of 2012–2017, a timeframe marked by severe financial stress following a domestic banking crisis. Using national GDP and bank deposits as core inputs, the study computes the country-specific cycle-of-money index and compares it to the global benchmark. The results show that Cyprus consistently exhibits a cycle-of-money index significantly above the global average, indicating a highly efficient internal redistribution and reuse of money. This finding suggests that the Cypriot economic structure possesses strong resilience and recovery capacity, even under adverse monetary and fiscal conditions. The analysis contributes to the comparative literature on monetary circulation by providing a clearly delimited single-country application and by reinforcing the explanatory power of the cycle-of-money framework in crisis contexts.

Economic systems face critical challenges, including widening income inequality, unemployment driven by automation, mounting public debt, and environmental degradation. This study introduces Economocracy as a transformative framework aimed at addressing these systemic issues by integrating democratic principles into economic decision-making to achieve social equity, economic efficiency, and environmental sustainability. The research focuses on two core mechanisms: Economic Productive Resets (EPRs) and Economic Periodic Injections (EPIs). EPRs facilitate proportional redistribution of resources to reduce income disparities, while EPIs target investments to stimulate job creation, mitigate automion-related job displacement, and support sustainable development. The study employs a theoretical and analytical methodology, developing mathematical models to quantify the impact of EPRs and EPIs on key economic indicators, including the Gini coefficient for inequality, unemployment rates, average wages, and job displacement due to automation. Hypothetical scenarios simulate baseline conditions, EPR implementation, and the combined application of EPRs and EPIs. The methodology is threefold: (1) a mathematical–theoretical validation of the Cycle of Money framework, establishing internal consistency; (2) an econometric analysis using global historical data (2000–2023) to evaluate the correlation between GNI per capita, Gini coefficient, and average wages; and (3) scenario simulations and Difference-in-Differences (DiD) estimates to test the systemic impact of implementing EPR/EPI policies on inequality and labor outcomes. The models are further strengthened through tools such as OLS regression, and Impulse results to assess causality and dynamic interactions. Empirical results confirm that EPR/EPI can substantially reduce income inequality and unemployment, while increasing wage levels, findings supported by both the theoretical architecture and data-driven outcomes. Results demonstrate that Economocracy can significantly lower income inequality, reduce unemployment, increase wages, and mitigate automation’s effects on the labor market. These findings highlight Economocracy’s potential as a viable alternative to traditional economic systems, offering a sustainable pathway that harmonizes growth, social justice, and environmental stewardship in the global economy. Economocracy demonstrates potential to reduce debt per capita by increasing the efficiency of public resource allocation and enhancing average income levels. As EPIs stimulate employment and productivity while EPRs moderate inequality, the resulting economic growth expands the tax base and alleviates fiscal pressures. These dynamics lead to lower per capita debt burdens over time. The analysis is situated within the broader discourse of institutional economics to demonstrate that Economocracy is not merely a policy correction but a new economic system akin to democracy in political life.

This method considers the problem of predicting already censored values of the dependent variable in the Tobit model. Assuming normality, it suggests a prediction formula that is equivalent to the classical correction using the inverse Mills ratio (IMR). The main contribution is providing an alternative derivation linking Ordinary Least Squares (OLS) and Maximum Likelihood Estimation (MLE) approaches, providing additional practical implementation insights. An extensive experimental investigation and robustness checks demonstrate the method's performance.

The gut microbiome, which comprises symbiotic bacteria colonizing the human digestive tract, undergoes dynamic changes during the lifespan, as evidenced by the fact that the number of species and the diversity of their composition decrease significantly with age. The aim of this review is to illuminate bilateral neuroimmunological pathways that determine the role of gut microbiome dysbiosis, not only as a cause but also as a byproduct of many neurodegenerative diseases of the CNS, such as Alzheimer's disease (AD) and Parkinson's disease (PD), but also in the frame of several behavioral and psychiatric pathological conditions such as depressive and anxiety disorders, schizophrenia, and autism spectrum disorder (ASD). Dysbiosis, in particular, reveals a model of "deceptive" mimicry of host molecules that might cause abnormal folding ("misfolding") and pathological aggregation of Aβ-peptide, leading to its dispersion through the gut-brain axis, precipitating microglia cell activation. By controlling myelination at the prefrontal cortex (PFC), a crucial area for multifaceted cognitive behavior, forecasting, and decision-making, the gut/microbiome-brain axis influences mood and social behavior, since major depressive disorder is correlated to white matter disturbance in the PFC, due to disregulations in the expression of myelin-related mRNA in this area. The gut microbiome is altered in psychosis compared to healthy controls, while medication with antipsychotics may result in reduced microbial community diversity. The vagus nerve, as a key element of the parasympathetic nervous system, regulating immune responses, may "detect" gut microbiome metabolites and transfer this intestinal information to the CNS, through its afferents, as in a "pseudo-neurotransmission" process. Scientific interest towards microbiome-based therapies increases as psychobiotics (which are strains of probiotics/prebiotics with specific properties to influence the gut-brain axis) appear to be able to exercise a beneficial effect in many CNS disorders. Lifestyle modifications, such as dietary interventions via psychobiotics intake that might enhance the gut microbiome's ability to produce beneficial metabolites that exert therapeutic effects on intestinal permeability, cognitive function, and immunity, may reveal new research pathways and therapeutic directions leading to a radical change of the "epistemology paradigm" as far as prevention and treatment of major neuro-psychiatric disorders is concerned.

The origin of the word “Statistics” is mistakenly sought in the Latin word “Status”. Although the term is indeed etymologically linked to “Status”, it is derived from the Greek noun “Στατός” (statos), meaning standing.