Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal

Model-free reinforcement learning has recently been shown to be effective at learning navigation policies from complex image input. However, these algorithms tend to require large amounts of interaction with the environment, which can be prohibitively costly to obtain on robots in the real world. We present an approach for efficiently learning goal-directed navigation policies on a mobile robot, from only a single coverage traversal of recorded data. The navigation agent learns an effective policy over a diverse action space in a large heterogeneous environment consisting of more than 2km of travel, through buildings and outdoor regions that collectively exhibit large variations in visual appearance, self-similarity, and connectivity. We compare pretrained visual encoders that enable precomputation of visual embeddings to achieve a throughput of tens of thousands of transitions per second at training time on a commodity desktop computer, allowing agents to learn from millions of trajectories of experience in a matter of hours. We propose multiple forms of computationally efficient stochastic augmentation to enable the learned policy to generalise beyond these precomputed embeddings, and demonstrate successful deployment of the learned policy on the real robot without fine tuning, despite environmental appearance differences at test time. The dataset and code required to reproduce these results and apply the technique to other datasets and robots is made publicly available at rl-navigation.github.io/deployable

Money laundering through real estate investments – An introduction to the analysis of the phenomenon

Objective: An overview of the basic, practical and theoretical issues related to money laundering, including real estate investment as one of the ways to legalize money from legally sanctioned sources. The aim of the article is also to introduce concepts related to money laundering and issues related to this process that may be the subject of further research.Methodology/research approach: In the study, the author used a classic analysis of the literature, including traditional and internet sources, and a review of legal regulations.Results: Money laundering is one of the common, though undesirable, aspects of economic life. Obtaining funds from illegal sources is associated with difficulty of legalizing them, which means that criminal organizations are constantly looking for ways to make it possible. One of these ways is real estate investment. A preliminary overview of the issues related to the discussed topic allows to get to know the essence of the phenomenon and the problems associated with it from the theoretical and practical side, and also indicates the need for further research and its possible direction.Originality/value: Money laundering is not very often analyzed in the scientific literature, especially in Poland. The analysis of this phenomenon and related concepts can contribute to a more effective fight against it thanks to the understanding of its mechanisms. Like any other economic phenomena, those of a criminal and pathological nature should be investigated, if only because of the selection of institutions and methods to combat them.Cel: Przegląd podstawowych, tak praktycznych, jak i teoretycznych zagadnień związanych z praniem brudnych pieniędzy, z uwzględnieniem inwestycji w nieruchomości jako jednego ze sposobów legalizacji środków pieniężnych pochodzących z prawnie sankcjonowanych źródeł. Celem artykułu jest również przybliżenie pojęć związanych z praniem brudnych pieniędzy i zagadnień z tym procesem związanych, które mogą być przedmiotem dalszych badań.Metodyka/podejście badawcze: W opracowaniu autor posłużył się klasyczną analizą literatury obejmującą źródła tradycyjne i internetowe oraz przeglądem przepisów prawa.Wyniki: Pranie brudnych pieniędzy jest jednym z powszechnie występujących, choć nie-pożądanych, aspektów życia gospodarczego. Zdobycie środków pieniężnych z nielegalnych źródeł wiąże się z trudnością ich legalizacji, a to powoduje, że organizacje przestępcze nieustanne poszukują sposobów, które to umożliwią. Jednym z tych sposobów są inwestycje na rynku nieruchomości. Wstępny przegląd zagadnień dotyczących omawianego tematu pozwala poznać istotę zjawiska i problemy z nim związane od strony teoretycznej jak i praktycznej, a także wskazuje na potrzebę dalszych badań oraz na ich możliwy kierunek.Oryginalność/wartość: Niezbyt często, szczególnie w Polsce, w literaturze naukowej analizowane jest zjawisko prania brudnych pieniędzy. Analiza tego zjawiska i związanych z nim pojęć, może przyczynić się do skuteczniejszej walki z praniem brudnych pieniędzy, dzięki zrozumieniu jego mechanizmów. Jak każde inne zjawiska gospodarcze również te o charakterze kryminalnym i patologicznym powinny być badane, choćby ze względu na dobór instytucji i metod do walki z nimi

Support Vector Machine and Probability Neural Networks in a Device-free Passive Localisation (DfPL) Scenario

Abstract The holy grail of tracking people indoors is being able to locate them when they are not carrying any wireless tracking devices. The aim is to be able to track people just through their physical body interfering with a standard wireless network that would be in most peoples home. The human body contains about 70% water which attenuates the wireless signal reacting as an absorber. The changes in the signal along with prior fingerprinting of a physical location allow identification of a person’s location. This paper is focused on taking the principle of Device-free Passive Localisation (DfPL) and applying it to be able to actually distinguish if there is more than one person in the environment. In order to solve this problem, we tested a Support Vector Machine (SVM) classifier with kernel functions such as Linear, Quadratic, Polynomial, Gaussian Radial Basis Function (RBF) and Multilayer Perceptron (MLP), and a Probabilistic Neural Network (PNN) in order to detect movement based on changes in the wireless signal strength.</jats:p

Uptake of radiolabelled modified fragment of human alfa-fetoptrotein by experimental mammary adenocarcinoma: in vitro and in vivo studies

BACKGROUND: The aim of the study was to examine in vitro and in vivo binding of radiolabelled analogues of P149 peptide by experimental mammary adenocarcinoma with the intention of potential application for diagnosis and internal radiotherapy of tumours. MATERIAL AND METHODS: The 36-amino acid peptide (P149-QY) of 90% homology to 447&#8211;480 peptide fragment of hAFP was synthesised and radiolabelled with iodine-125. The biodistribution of P149-Q[125I]-Y was studied in experimental mammary tumours. For in vitro experiments, extract from mouse mammary tumours were prepared and incubated with radioiodinated P149-QY peptide in the presence of a cross-linking reagent. RESULTS: The gel electrophoresis analysis (SDS-PAGE) showed that radioiodinated P149-QY peptide formed a complex with adenocarcinoma proteins of about 30 kDa. The biodistribution of P149-Q[125I]-Y studied in experimental mammary tumours revealed a higher pharmacokinetic rate in comparison with the whole radioiodinated AFP molecule. A moderate uptake of P149-Q[125I]-Y in the tumour tissue was observed (3.2% ID/g at 30-min p.i.v). However, a faster radioactivity clearance from blood and normal tissues resulted in an increase in the tumour/muscle (T/M) ratio, i.e. from 2.3 to 3.4 after 30 mins and 24 h p.i.v, respectively. CONCLUSIONS: The present study shows that radioiodinated P149-QY peptide reveals some positive features as the AFP receptor radioligand, however, some additional structural modifications of the initial peptide molecule are necessary for full retention of the ligand-receptor interaction of its radiolabelled forms

CLIP-CLOP: CLIP-Guided Collage and Photomontage

The unabated mystique of large-scale neural networks, such as the CLIP dual image-and-text encoder, popularized automatically generated art. Increasingly more sophisticated generators enhanced the artworks' realism and visual appearance, and creative prompt engineering enabled stylistic expression. Guided by an artist-in-the-loop ideal, we design a gradient-based generator to produce collages. It requires the human artist to curate libraries of image patches and to describe (with prompts) the whole image composition, with the option to manually adjust the patches' positions during generation, thereby allowing humans to reclaim some control of the process and achieve greater creative freedom. We explore the aesthetic potentials of high-resolution collages, and provide an open-source Google Colab as an artistic tool.Comment: 5 pages, 7 figures, published at the International Conference on Computational Creativity (ICCC) 2022 as Short Paper: Dem

Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate

International audienceABSTRACT: BACKGROUND: Nitrate, acting as both a nitrogen source and a signaling molecule, controls many aspects of plant development. However, gene networks involved in plant adaptation to fluctuating nitrate environments have not yet been identified. RESULTS: Here we use time-series transcriptome data to decipher gene relationships and consequently to build core regulatory networks involved in Arabidopsis root adaptation to nitrate provision. The experimental approach has been to monitor genome-wide responses to nitrate at 3, 6, 9, 12, 15 and 20 minutes, using Affymetrix ATH1 gene chips. This high-resolution time course analysis demonstrated that the previously known primary nitrate response is actually preceded by a very fast gene expression modulation, involving genes and functions needed to prepare plants to use or reduce nitrate. A state-space model inferred from this microarray time-series data successfully predicts gene behavior in unlearnt conditions. CONCLUSIONS: The experiments and methods allow us to propose a temporal working model for nitrate-driven gene networks. This network model is tested both in silico and experimentally. For example, the over-expression of a predicted gene hub encoding a transcription factor induced early in the cascade indeed leads to the modification of the kinetic nitrate response of sentinel genes such as NIR, NIA2, and NRT1.1, and several other transcription factors. The potential nitrate /hormone connections implicated by this time-series data is also evaluated