Wapiennik Breccia Member (Pieniny Klippen Belt, Poland) - is it really Jurassic?

The main goal of this study was to verify the age of the Wapiennik Breccia Member (Birkenmajer 1977) from the Pieniny Klippen Belt, so far described as Callovian-Oxfordian on base on its stratigraphical position (Birkenmajer 1977). The age of the breccia in the Wapiennik quarry in Szaflary, near Nowy Targ (Poland), has been constrained by means of microfacies and foraminifera analyses. The breccia includes two subsets of conglomerates, differing in clasts composition, but incorporated into the red, limestone matrix. The age of the matrix could be confined to the Middle Albian-the lowermost Cenomanian time, thus questioning Jurassic age of the breccia

Podstawowe fakty o orbitach transformacji Kaprekara

Presented paper, above all, completes two other papers, made previously by the authors and cited in References, concerning the orbits of the Kaprekar’s transformations. In the current paper many detailed facts for five initial Kaprekar’s transformations (from T2 to T6) are described. There are introduced some new concepts and there is shown how important is the observation of numerical results giving the motivation for theoretical discussion on the Kaprekar’s transformations. Moreover, the paper includes the interesting and original results concerning the fixed points and the 2-element orbits of the Kaprekar’s transformations. All these results encourage to continue the discussion. The paper contains also quite large survey section devoted to the generalizations and modifications of the Kaprekar’s transformations. Furthermore, some pieces of information from OEIS by N.J.A. Sloane connected with the orbits of the Kaprekar’s transformations are presented here.Prezentowany artykuł uzupełnia dwie inne prace autorów, cytowane w dołączonej tu literaturze, dotyczące orbit transformacji Kaprekara. W pracy przedstawiono wiele szczegółowych faktów dla pierwszych pięciu transformacji Kaprekara (od T2 do T6). Wprowadzono nowe pojęcia i pokazano, jak istotna jest analiza wyników numerycznych jako motywacja do dyskusji teoretycznej transformacji Kaprekara. Ponadto w artykule zamieszczono interesujące i oryginalne wyniki dotyczące punktów stałych i 2-elementowych orbit transformacji Kaprekara. Wszystkie te wyniki wręcz zachęcają do dalszej dyskusji. Artykuł zawiera również obszerny rozdział dotyczący uogólnień i modyfikacji transformacji Kaprekara. Wreszcie mamy tu zamieszczoną garść informacji z OEIS, ufundowanej przez N.J.A. Sloane’a, związanych z orbitami transformacji Kaprekara

Reluctant Experts

Two duties arising under Rule 45 and related provisions of the Federal Rules of Civil Procedures, including the duty of a scientific or technical expert not retained by a party to testify to an opinion on a disputed scientific or technical issue, are discussed

Data analytics for simplifying thermal efficiency planning in cities.

More than 44% of building energy consumption in the USA is used for space heating and cooling, and this accounts for 20% of national CO2emissions. This prompts the need to identify among the 130 million households in the USA those with the greatest energy-saving potential and the associated costs of the path to reach that goal. Whereas current solutions address this problem by analysing each building in detail, we herein reduce the dimensionality of the problem by simplifying the calculations of energy losses in buildings. We present a novel inference method that can be used via a ranking algorithm that allows us to estimate the potential energy saving for heating purposes. To that end, we only need consumption from records of gas bills integrated with a building's footprint. The method entails a statistical screening of the intricate interplay between weather, infrastructural and residents' choice variables to determine building gas consumption and potential savings at a city scale. We derive a general statistical pattern of consumption in an urban settlement, reducing it to a set of the most influential buildings' parameters that operate locally. By way of example, the implications are explored using records of a set of (N= 6200) buildings in Cambridge, MA, USA, which indicate that retrofitting only 16% of buildings entails a 40% reduction in gas consumption of the whole building stock. We find that the inferred heat loss rate of buildings exhibits a power-law data distribution akin to Zipf's law, which provides a means to map an optimum path for gas savings per retrofit at a city scale. These findings have implications for improving the thermal efficiency of cities' building stock, as outlined by current policy efforts seeking to reduce home heating and cooling energy consumption and lower associated greenhouse gas emissions

Data analytics for simplifying thermal efficiency planning in cities.

More than 44% of building energy consumption in the USA is used for space heating and cooling, and this accounts for 20% of national CO2emissions. This prompts the need to identify among the 130 million households in the USA those with the greatest energy-saving potential and the associated costs of the path to reach that goal. Whereas current solutions address this problem by analysing each building in detail, we herein reduce the dimensionality of the problem by simplifying the calculations of energy losses in buildings. We present a novel inference method that can be used via a ranking algorithm that allows us to estimate the potential energy saving for heating purposes. To that end, we only need consumption from records of gas bills integrated with a building's footprint. The method entails a statistical screening of the intricate interplay between weather, infrastructural and residents' choice variables to determine building gas consumption and potential savings at a city scale. We derive a general statistical pattern of consumption in an urban settlement, reducing it to a set of the most influential buildings' parameters that operate locally. By way of example, the implications are explored using records of a set of (N= 6200) buildings in Cambridge, MA, USA, which indicate that retrofitting only 16% of buildings entails a 40% reduction in gas consumption of the whole building stock. We find that the inferred heat loss rate of buildings exhibits a power-law data distribution akin to Zipf's law, which provides a means to map an optimum path for gas savings per retrofit at a city scale. These findings have implications for improving the thermal efficiency of cities' building stock, as outlined by current policy efforts seeking to reduce home heating and cooling energy consumption and lower associated greenhouse gas emissions