Distributed large scale systems: a multi-agent RL-MPC architecture

Universidat Politécnica de Cataluya. Programa de Doctorat: Automàtica, Robòtica I Visiò.[EN]: This thesis describes a methodology to deal with the interaction between MPC controllers in a distributed MPC architecture. This approach combines ideas from Distributed Artificial Intelligence (DAI) and Reinforcement Learning (RL) in order to provide a controller interaction based on cooperative agents and learning techniques. The aim of this methodology is to provide a general structure to perform optimal control in networked distributed environments, where multiple dependencies between subsystems are found. Those dependencies or connections often correspond to control variables. In that case, the distributed control has to be consistent in both subsystems. One of the main new concepts of this architecture is the negotiator agent. Negotiator agents interact with MPC agents to determine the optimal value of the shared control variables in a cooperative way using learning techniques (RL). The optimal value of those shared control variables has to accomplish a common goal, probably different from the specific goal of each agent sharing the variable. Two cases of study, in which the proposed architecture is applied and tested are considered, a small water distribution network and the Barcelona water network. The results suggest this approach is a promising strategy when centralized control is not a reasonable choice.[ES]: Esta tesis describe una metodología para hacer frente a la interacción entre controladores MPC en una arquitectura MPC distribuida. Este enfoque combina las ideas de Inteligencia Artificial Distribuida (DIA) y aprendizaje por refuerzo (RL) con el fin de proporcionar una interacción entre controladores basado en agentes de cooperativos y técnicas de aprendizaje. El objetivo de esta metodología es proporcionar una estructura general para llevar a cabo un control óptimo en entornos de redes distribuidas, donde se encuentran varias dependencias entre subsistemas. Esas dependencias o conexiones corresponden a menudo a variables de control. En ese caso, el control distribuido tiene que ser coherente en ambos subsistemas. Uno de los principales conceptos novedosos de esta arquitectura es el agente negociador. Los agentes negociadores actúan junto con agentes MPC para determinar el valor óptimo de las variables de control compartidas de forma cooperativa utilizando técnicas de aprendizaje (RL). El valor óptimo de esas variables compartidas debe lograr un objetivo común, probablemente diferente de los objetivos específicos de cada agente que está compartiendo la variable. Se consideran dos casos de estudio, en el que la arquitectura propuesta se ha aplicado y probado, una pequeña red de distribución de agua y la red de agua de Barcelona. Los resultados sugieren que este enfoque es una estrategia prometedora cuando el control centralizado no es una opción razonable.Peer Reviewe

Supramolecular drug inclusion complex constructed from cucurbit[7]uril and the hepatitis B drug Adefovir

The interaction between cucuribit[7]uril (Q[7]) and Adefovir (ADV) has been studied in aqueous solution by 1H NMR spectroscopy, electronic absorption spectroscopy, Isothermal Titration Calorimetry and mass spectrometry. The results revealed that an inclusion complex was formed via encapsulation of the purine rings of the guest ADV, while the phosphonomethoxyethyl group was prevented from entering the cavity. ITC data revealed that the formation of this 1:1 inclusion complex is mainly driven by favourable enthalpy changes. Studies investigating the release of ADV from the inclusion complex revealed enhanced rates under acidic conditions, although the rates were slower than observed for the free guest under the same conditions. Thermal stability studies indicated that the included form of ADV was more stable that the free form

Amino acid recognition by a fluorescent chemosensor based on cucurbit[8]uril and acridine hydrochloride

A new fluorescent chemosensor comprised of cucurbit[8]uril (Q[8]) and acridine hydrochloride (AC) has been designed and utilized for the recognition of amino acids. The AC was encapsulated by the Q[8] cavity and formed a 1:2 host-guest inclusion complex both in solution (aqueous) and in the solid-state. Whilst free AC is known to be strongly fluorescent, this strong fluorescence was quenched in the inclusion complex Q[8]-AC. This non-fluorescent complex Q[8]-AC was capable of serving as a fluorescence “off-on” probe, and was able to recognize either L-Phe or L-Trp via the competitive interaction between L-Phe or L-Trp. Moreover, the pH responsive nature of the probe allowed for the detection of basic amino acids, namely L-Arg, L-His, or L-Lys). As a result, a fluorescence method for the detection of five amino acids using a single system has been developed

Genetically predicted inflammatory proteins and the risk of atrial fibrillation: a bidirectional Mendelian randomization study

PurposeThe causal associations between inflammatory factors and atrial fibrillation (AF) remained unclear. We aimed to investigate whether genetically predicted inflammatory proteins are related to the risk of AF, and vice versa.MethodsA bidirectional two-sample Mendelian randomization study was performed. The genetic variation of 91 inflammatory proteins were derived from genome-wide association study (GWAS) data of European ancestry (n = 14,824). Summary statistics for AF were obtained from a published meta-analysis study (n = 1,030,836) and the FinnGen study (n = 261,395).ResultsGenetically predicted fibroblast growth factor 5 (FGF5) was significantly positively associated with risk of AF [[odds ratio (OR): 1.07; 95% CI: 1.04–1.10; P < 0.01], and CD40l receptor was significantly negatively associated with risk of AF (OR: 0.95; 95% CI: 0.92–0.98; P = 0.02) in the meta-analysis study. In the FinnGen study, similar results were observed in FGF5 (OR: 1.11; 95% CI: 1.06–1.16; P < 0.01) and CD40l receptor (OR: 0.93; 95% CI: 0.89–0.97; P = 0.03) for AF. In the FinnGen study, TNF-beta was significantly positively associated with risk of AF (OR: 1.05; 95% CI: 1.02–1.09; P = 0.03) and leukemia inhibitory factor receptor was significantly negatively associated with risk of AF (OR: 0.86; 95% CI: 0.80–0.91; P = 0.001). The causal effect of AF on inflammatory proteins was not observed.ConclusionOur study suggested that FGF5 and CD40l receptor have a potential causal association with AF, and targeting these factors may help in the treatment of AF

Spatiotemporal DNA methylome dynamics of the developing mouse fetus

Cytosine DNA methylation is essential for mammalian development but understanding of its spatiotemporal distribution in the developing embryo remains limited. Here, as part of the mouse Encyclopedia of DNA Elements (ENCODE) project, we profiled 168 methylomes from 12 mouse tissues or organs at 9 developmental stages from embryogenesis to adulthood. We identified 1,808,810 genomic regions that showed variations in CG methylation by comparing the methylomes of different tissues or organs from different developmental stages. These DNA elements predominantly lose CG methylation during fetal development, whereas the trend is reversed after birth. During late stages of fetal development, non-CG methylation accumulated within the bodies of key developmental transcription factor genes, coinciding with their transcriptional repression. Integration of genome-wide DNA methylation, histone modification and chromatin accessibility data enabled us to predict 461,141 putative developmental tissue-specific enhancers, the human orthologues of which were enriched for disease-associated genetic variants. These spatiotemporal epigenome maps provide a resource for studies of gene regulation during tissue or organ progression, and a starting point for investigating regulatory elements that are involved in human developmental disorders

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

Comparative Study of the Pop Music Industry in China and the United States

The pop music industry has a wide-ranging social influence and serves as an important medium for cultural exchange and international dissemination. This article aims to conduct a comparative study of the pop music industries in China and the United States, with the goal of comparing the differences and variations in pop music development between these two-major economic and cultural powers. Firstly, we compare and analyze the differences and similarities between the two countries in terms of music market size, music consumption patterns, and the value chain of the music industry. Secondly, we explore the challenges and opportunities faced by the pop music industries in China and the United States, aiming to inspire reflections on the development of the pop music industry in both countries. The study reveals that the future direction of China's pop music industry focuses on increasing the number of paying users and integrating pop music with social platforms. On the other hand, the U.S. pop music industry is dedicated to expanding into emerging overseas markets and enhancing its own influence. The future development trends of the pop music industry in China and the United States provide valuable insights for further exploration and promotion of the pop music industry's development

A neural network based computational model to predict the output power of different types of photovoltaic cells - Fig 3

<p>Mono-crystalline (a), multi-crystalline (b) and amorphous crystalline (c) cells compared to experimental data using different numbers of hidden neurons (n = 3, 6, and 9).</p