Born in Poland in 1931, Henryk Miroslaw Wisniewski, obtained MD at the Medical School in Gdansk (1955), where he continued his neuropathological research awarded with Ph. D. in 1960. During 1961-1962 a worked as a Visiting Scientist at NIH (Institute of Neurology and Communicative Diseases and Stroke). In Medical School in Warsaw he was promoted to Docent degree (an associate professor). In 1966 he emigrated with his family to New York, where he was a Research Associate and Professor at Albert Einstein College of Medicine (1966-1975) Subsequently he became a Director of the State Institute for Basic Research in Developmental Disabilities Staten Island. In New York he remained till his early death at the age of 68. Prof. Wisniewski advanced pathological research concerning the development of dementia, including Alzheimer disease. His investigations proved that presentile dementia (Alzheimer disease) is almost identical with senile dementia. That is why he is called the pioneer of modern Alzheimers research. The comments about his scientific contribution were generously published in scientific journals and daily press. The New York Times cited Dr Mony de Leon Prof. of Psychiatry statement reflecting so well Prof. Wisniewski's achievements "He taught us what the lesions for Alzheimers looked like, what they were made of and how they worked".
This study utilises the R programming language for statistical data analysis to understand Tourism dynamics in Poland. It focuses on methods for data visualisation, multivariate statistics, and hypothesis testing. To investigate the expenditure behavior of tourist, spending patterns, correlations, and associations among variables were analysed in the dataset. The results revealed a significant relationship between accommodation type and the purpose of trip, showing that the purpose of a trip impacts the selection of accommodation. A strong correlation was observed between organizer expenditure and private expenditure, indicating that individual spending are more when the spending on organizing the trip are higher. However, no significant difference was observed in total expenditure across different accommodation types and purpose of the trip revealing that travelers tend to spend similar amounts regardless of their reason for travel or choice of accommodation. Although significant relationships were observed among certain variables, ANOVA could not be applied because the dataset was not able to hold on the normality assumption. In future, the dataset can be explored further to find
We apply the political stress index as introduced by Goldstone (1991) and implemented by Turchin (2013), to the case study of Poland. The approach quantifies political and social unrest as a single quantity based on a multitude of economic and demographic variables. The present-day data allow us to directly apply index without the need of simulating the elite component, as was done previously. Neither model version shows appreciable unrest levels for the present, while the simulated model applied to partial historical data yields the index in remarkable agreement with the fall of communism in Poland. We next analyze the model's sensitive dependence on its parameters (the hallmark of chaos), which limits its utility and application to other countries. The original equations cannot, by construction, describe the elite fraction for longer time-periods; and we propose a modification to remedy this problem. The model still holds some predictive power, but we argue that some components should be reinterpreted if one wants to keep its dynamical equations.
Emerging carbon capture and storage (CCS) markets face critical challenges in developing systematic methodologies to assess geological CO2 storage potential under conditions of limited data availability, evolving regulatory frameworks, and nascent infrastructure development. This study establishes an assessment framework designed for lower-maturity CCS regions, using Poland as a representative case study to demonstrate methodology application and validate framework effectiveness. The framework integrates geological characterization, storage capacity assessment, regulatory analysis, and socio-economic evaluation through a structured approach adaptable to diverse global contexts. Poland's coal-reliant economy exemplifies the decarbonization challenges facing emerging CCS regions while meeting European Union climate mandates. The country's geological setting offers substantial sequestration opportunities across three major sedimentary regions. Through multidisciplinary analysis synthesizing scattered geological data, policy developments, CCUS value chain, and stakeholder perspectives, we systematically evaluate CO2 storage potential. Onshore saline aquifers and depleted hydrocarbon fi
Analyses of near-surface air temperature T in Poland for 1781-2016 and in Tbilisi (Georgia) for 1881-2016 have been carried out. We show that the centenary warming effect in Poland and in Tbilisi has almost the same peculiarities. An average centenary warming effect deltaT = (1.08+/-0.29) C is observed in Poland and in Tbilisi for 1881-2016. A warming effect is larger in winter season (deltaT = ~1.15 C) than in other seasons (average warming effect for these seasons deltaT = ~0.95 C). We show that a centenary warming is mainly related to the change of solar activity (estimated by sunspot numbers (SSN) and total solar irradiance (TSI)); particularly, a time interval about ~70 years (1890-1960), when a correlation coefficients between 11 years smoothed SSN and T, and TSI and T are high, r = 0.66+/-0.07 and r = 0.73+/-0.07 for Poland and r = 0.82+/-0.05 and r = 0.90+/-0.05 for Tbilisi, respectively; in this period solar activity contributes decisively in the global warming. We show that a global warming effect equals zero based on the temperature T data in Poland for period 1781-1880, when human activities were relatively less than in 1881-2016. We recognize a few feeble ~20+/-3 years
We examine the gender gap in income in Poland in relation to parenthood status, employing the placebo event history method adapted to low-resolution data (Polish Generations and Gender Survey). Our analysis reveals anticipatory behavior in both women and men who expect to become parents. We observe a decrease of approximately 20 percent in mothers' income post-birth. In contrast, the income of fathers surpasses that of non-fathers both pre- and post-birth, suggesting that the fatherhood child premium may be primarily driven by selection. We note an increase (decrease) in hours worked for fathers (mothers). Finally, we compare the gender gaps in income and wages between women and men in the sample with those in a counterfactual scenario where the entire population is childless. Our findings indicate no statistically significant gender gaps in the counterfactual scenario, leading us to conclude that parenthood drives the gender gaps in income and wages in Poland.
In this article we use the methods of functional data analysis to analyze the number of positive tests, deaths, convalescents, hospitalized and intensive care people during second and third wave of the COVID-19 pandemic in Poland. For this purpose firstly we convert the data to smooth functions. Then we use principal component analysis and multiple function-on-function linear regression model to analyze waves of COVID-19 pandemic in Polish voivodeships.
Poland is currently undergoing substantial transformation in its energy sector, and gaining public support is pivotal for the success of its energy policies. We conducted a study with 338 Polish participants to investigate societal attitudes towards various energy sources, including nuclear energy and renewables. Applying a novel network approach, we identified a multitude of factors influencing energy acceptance. Political ideology is the central factor in shaping public acceptance, however we also found that environmental attitudes, risk perception, safety concerns, and economic variables play substantial roles. Considering the long-term commitment associated with nuclear energy and its role in Poland's energy transformation, our findings provide a foundation for improving energy policy in Poland. Our research underscores the importance of policies that resonate with the diverse values, beliefs, and preferences of the population. While the risk-risk trade-off and technology-focused strategies are effective to a degree, we advocate for a more comprehensive approach. The framing strategy, which tailors messages to distinct societal values, shows particular promise.
Throughout the coronavirus disease 2019 (COVID-19) pandemic, decision makers have relied on forecasting models to determine and implement non-pharmaceutical interventions (NPI). In building the forecasting models, continuously updated datasets from various stakeholders including developers, analysts, and testers are required to provide precise predictions. Here we report the design of a scalable pipeline which serves as a data synchronization to support inter-country top-down spatiotemporal observations and forecasting models of COVID-19, named the where2test, for Germany, Czechia and Poland. We have built an operational data store (ODS) using PostgreSQL to continuously consolidate datasets from multiple data sources, perform collaborative work, facilitate high performance data analysis, and trace changes. The ODS has been built not only to store the COVID-19 data from Germany, Czechia, and Poland but also other areas. Employing the dimensional fact model, a schema of metadata is capable of synchronizing the various structures of data from those regions, and is scalable to the entire world. Next, the ODS is populated using batch Extract, Transfer, and Load (ETL) jobs. The SQL queri
Poland-Scheraga models were introduced to describe the DNA denaturation transition. We give a rigorous and refined discussion of a family of these models. We derive possible scaling functions in the neighborhood of the phase transition point and review common examples. We introduce a self-avoiding Poland-Scheraga model displaying a first order phase transition in two and three dimensions. We also discuss exactly solvable directed examples. This complements recent suggestions as to how the Poland-Scheraga class might be extended in order to display a first order transition, which is observed experimentally.
The Poland-Scheraga model describes the denaturation transition of two complementary - in particular, equally long - strands of DNA, and it has enjoyed a remarkable success both for quantitative modeling purposes and at a more theoretical level. The solvable character of the homogeneous version of the model is one of features to which its success is due. In the bio-physical literature a generalization of the model, allowing different length and non complementarity of the strands, has been considered and the solvable character extends to this substantial generalization. We present a mathematical analysis of the homogeneous generalized Poland-Scheraga model. Our approach is based on the fact that such a model is a homogeneous pinning model based on a bivariate renewal process, much like the basic Poland-Scheraga model is a pinning model based on a univariate, i.e. standard, renewal. We present a complete analysis of the free energy singularities, which include the localization-delocalization critical point and (in general) other critical points that have been only partially captured in the physical literature. We obtain also precise estimates on the path properties of the model.
We propose a novel methodology for estimating the epidemiological parameters of a modified SIRD model (acronym of Susceptible, Infected, Recovered and Deceased individuals) and perform a short-term forecast of SARS-CoV-2 virus spread. We mainly focus on forecasting number of deceased. The procedure was tested on reported data for Poland. For some short-time intervals we performed numerical test investigating stability of parameter estimates in the proposed approach. Numerical experiments confirm the effectiveness of short-term forecasts (up to 2 weeks) and stability of the method. To improve their performance (i.e. computation time) GPU architecture was used in computations.
The origins of the series of European Cosmic-Ray Symposia are briefly described. The first meeting in the series, on Hadronic Interactions and Extensive Air Showers, held in Lodz, Poland in 1968, was attended by the author: some memories are recounted.
Nowadays, it is possible to collect precise data describing movements of public transport. Specifically, for each bus (or tram) geoposition data can be regularly collected. This includes data for all buses in Warsaw, Poland. Moreover, this data can be downloaded and analyzed. In this context, one of the simplest questions is: can a model be build to represent behavior of busses, and predict their delays. This work provides initial results of our attempt to answer this question.
African Swine Fever (ASF) is viral infection which causes acute disease in domestic pigs and wild boar. Although the virus does not cause disease in humans, the impact it has on the economy, especially through trade and farming, is substantial. Recent rapid propagation of the (ASF) from East to West of Europe encouraged us to prepare risk assessment for Poland. The early growth estimation can be easily done by matching incidence trajectory to the exponential function, resulting in the approximation of the force of infection. With these calculations the basic reproduction rate of the epidemic, the effective outbreaks detection and elimination times could be estimated. In regression mode, 380 Polish counties (poviats) have been analysed, where 18 (located in Northeast Poland) have been affected (until August 2017) for spatial propagation (risk assessment for future). Mathematical model has been applied by taking into account: swine amount significance, disease vectors (wild boards) significance. We use pseudogravitational models of short and longrange interactions referring to the socio-migratory behavior of wild boars and the pork production chain significance. Spatial modeling in a
In this article we address the question of how to measure the size and characteristics of the platform economy. We propose a~different, to sample surveys, approach based on smartphone data, which are passively collected through programmatic systems as part of online marketing. In particular, in our study we focus on two types of services: food delivery (Bolt Courier, Takeaway, Glover, Wolt and transport services (Bolt Driver, Free Now, iTaxi and Uber). Our results show that the platform economy in Poland is growing. In particular, with respect to food delivery and transportation services performed by means of applications, we observed a growing trend between January 2018 and December 2020. Taking into account the demographic structure of apps users, our results confirm findings from past studies: the majority of platform workers are young men but the age structure of app users is different for each of the two categories of services. Another surprising finding is that foreigners do not account for the majority of gig workers in Poland. When the number of platform workers is compared with corresponding working populations, the estimated share of active app users accounts for about 0.
Dwarf spheroidal galaxies (dSphs) are excellent targets for indirect dark matter (DM) searches using gamma-ray telescopes because they are thought to have high DM content and a low astrophysical background. The sensitivity of these searches is improved by combining the observations of dSphs made by different gamma-ray telescopes. We present the results of a combined search by the most sensitive currently operating gamma-ray telescopes, namely: the satellite-borne Fermi-LAT telescope; the ground-based imaging atmospheric Cherenkov telescope arrays H.E.S.S., MAGIC, and VERITAS; and the HAWC water Cherenkov detector. Individual datasets were analyzed using a common statistical approach. Results were subsequently combined via a global joint likelihood analysis. We obtain constraints on the velocity-weighted cross section $\langle σ\mathit{v} \rangle$ for DM self-annihilation as a function of the DM particle mass. This five-instrument combination allows the derivation of up to 2-3 times more constraining upper limits on $\langle σ\mathit{v} \rangle$ than the individual results over a wide mass range spanning from 5 GeV to 100 TeV. Depending on the DM content modeling, the 95% confidence
Contact tracing and quarantine are well established non-pharmaceutical epidemic control tools. The paper aims to clarify the impact of these measures in COVID-19 epidemic. A new deterministic model is introduced (SEIRQ: susceptible, exposed, infectious, removed, quarantined) with Q compartment capturing individuals and releasing them with delay. We obtain a simple rule defining the reproduction number $\mathcal{R}$ in terms of quarantine parameters, ratio of diagnosed cases and transmission parameters. The model is applied to the epidemic in Poland in March - April 2020, when social distancing measures were in place. We investigate 3 scenarios corresponding to different ratios of diagnosed cases. Our results show that depending on the scenario contact tracing could have prevented from 50\% to over 90\% of cases. The effects of quarantine are limited by fraction of undiagnosed cases. Taking into account the transmission intensity in Poland prior to introduction of social restrictions it is unlikely that the control of the epidemic could be achieved without any social distancing measures.
In this study we consider relations between companies in Poland taking into account common branches they belong to. It is clear that companies belonging to the same branch compete for similar customers, so the market induces correlations between them. On the other hand two branches can be related by companies acting in both of them. To remove weak, accidental links we shall use a concept of threshold filtering for weighted networks where a link weight corresponds to a number of existing connections (common companies or branches) between a pair of nodes.
The Black Death is regarded as a turning point in late medieval European history. Recent studies have shown that even regions that have so far been perceived in the literature as not or only marginally affected by the epidemic, suffered from its profound demographic and economic consequences. The scale and geographical range of the plague in Central Europe, the Kingdom of Poland included remains, however, a matter of dispute and from the beginning scholar's views on this matter have been divided. What is particularly important, the outbreak of the plague in Western Europe coincided with the reign of Casimir of the Piast dynasty, the only ruler of Poland to receive the nickname the Great, who is associated with the modernization and extraordinary development of his kingdom which was entering the golden age of its history.