The distribution of extremal points of Gaussian scalar fields

We consider the signed density of the extremal points of (two-dimensional) scalar fields with a Gaussian distribution. We assign a positive unit charge to the maxima and minima of the function and a negative one to its saddles. At first, we compute the average density for a field in half-space with Dirichlet boundary conditions. Then we calculate the charge-charge correlation function (without boundary). We apply the general results to random waves and random surfaces. Furthermore, we find a generating functional for the two-point function. Its Legendre transform is the integral over the scalar curvature of a 4-dimensional Riemannian manifold.Comment: 22 pages, 8 figures, corrected published versio

X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs

Structured, or tabular, data is the most common format in data science. While deep learning models have proven formidable in learning from unstructured data such as images or speech, they are less accurate than simpler approaches when learning from tabular data. In contrast, modern tree-based Machine Learning (ML) models shine in extracting relevant information from structured data. An essential requirement in data science is to reduce model inference latency in cases where, for example, models are used in a closed loop with simulation to accelerate scientific discovery. However, the hardware acceleration community has mostly focused on deep neural networks and largely ignored other forms of machine learning. Previous work has described the use of an analog content addressable memory (CAM) component for efficiently mapping random forests. In this work, we focus on an overall analog-digital architecture implementing a novel increased precision analog CAM and a programmable network on chip allowing the inference of state-of-the-art tree-based ML models, such as XGBoost and CatBoost. Results evaluated in a single chip at 16nm technology show 119x lower latency at 9740x higher throughput compared with a state-of-the-art GPU, with a 19W peak power consumption

Impact of long-term storage on the quality of selected sugar-based foods stored at different temperatures

The aim of the presented study was to evaluate the microbiological, chemical, physical and organoleptic properties of sugar-based foods (apricot-apple jam, flower meadow honey, sweetened hazelnut cocoa spread) stored at four different temperatures (−18, 5, 23 and 40 °C) for a period of 24 months. In addition, critical combinations of storage temperature and time were determined for maintaining food quality and food safety. Storage of all samples ≤23 °C appeared to be safe from a microbiology perspective, while in the case of storage at 40 °C it was not recommended to exceed a storage period of 6 or 12 months. The pH-values decreased and the dry matter, ammonia, TBARS content increased most intensively during the first 6 months of storage (P < 0.05). The amino acid content of sweetened hazelnut cocoa spread decreased significantly at 40 °C (P < 0.05). With the prolonged storage time, the organoleptic properties of the samples deteriorated. The changes were more intensive when an elevated storage temperature was used (P < 0.05). Moreover, under the above-mentioned conditions a marginal decrease of the total saccharide content in all samples was observed. In addition, the apparent viscosity of the honey and the firmness of the jam increased significantly at elevated temperatures of 40 °C (P < 0.05). © 2022 The Author(s)Univerzita Tomáše Bati ve Zlíně: IGA/FT/2019/006; Ministerstvo Obrany České Republiky, MOČRTomas Bata University in Zlin [IGA/FT/2019/006]; project of long-term strategy of organization development DZRO ROZVOLOG Development of Capabilities and Sustainability of Logistics Support (DZRO ROZVOLOG, 2016-2021) - Ministry of Defence of the Czech Republi

Metodologický prístup Várossovej k výskumu dejín filozofického myslenia

Článok sa zameriava na metodologické úvahy o výskume dejín slovenskej filozofie v období uplatňovania marxisticko-leninskej filozofie s dôrazom na filozofické dielo Eleny Várossovej. Marxisticko-leninská filozofia vytvorila na Slovensku nový kontext, ktorý priniesol nové teoretické a metodologické výzvy pre interpretáciu filozofického myslenia. Várossová odmietla viaceré metodologické princípy, čím vyvolala niekoľko rokov trvajúcu diskusiu. V pozadí tejto debaty bola zásadná diskusia o filozoficko-metodologickom prístupe k interpretácii a hodnoteniu filozofického myslenia. Prvá časť sa zameriava na prístup k dialektickému materializmu ako metóde. V ďalšej časti sa analyzujú metodologické princípy, ktoré sú základom Várossovej výskumu filozofického myslenia, a kritika, ktorá bola vznesená voči jej metodologickým predpokladom. Záverečná časť príspevku podrobne skúma Várossovej metodologický prístup, ktorý chápe dejiny filozofie ako zložitý, rozporuplný proces objavovania kvalít. Várossová sa zaoberá aj vzťahom medzi idealizmom a materializmom, interpretuje ich v kontexte poznania a skúma ich vzťah k objektívnej realite. Várossová pritom kriticky hodnotí marxistické perspektívy a zdôrazňuje potrebu rozšíriť analýzu o psychologické a sociálne aspekty človeka. Elena Várossová - marxizmus - materializmus - idealizmus - dejiny filozofi