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Search results for: EXPLAINABLE AI
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Artificial intelligence for biomedical engineering of polysaccharides: A short overview.
PublicationThe advent of computer-aided concepts and cognitive algorithms, along with fuzzy sets and fuzzy logic thoughts, supported the idea of ‘making computers think like people’ (Lotfi A. Zadeh, IEEE Spectrum, 21 (26–32), 1984). Such a school of thought enabled the sophistication of mission-oriented...
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Artificial Intelligence Technologies in Education: Benefits, Challenges and Strategies of Implementation
PublicationSince the education sector is associated with highly dynamic business environments which are controlled and maintained by information systems, recent technological advancements and the increasing pace of adopting artificial intelligence (AI) technologies constitute a need to identify and analyze the issues regarding their implementation in education sector. However, a study of the contemporary literature reveled that relatively...
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Emotions Embodied in the SVC of an Autonomous Driver System
PublicationA concept of embodied intelligence (EI) is considered. None of such implementations can be fully identified with artificial intelligence. Projects that dare to approach AI and EI should be based on both the AI concepts (symbolic and sub-symbolic), in solving real problems of perception and decision-making. Therefore, the EI, in this paper, is understood as a methodology that uses all available resources and algorithms from the...
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Self-Organization in Multi-Agent Systems Based on Examples of Modeling Economic Relationships between Agents
PublicationThe goal of the research was to observe and analyze self-organization patterns in Multi-Agent Systems (MAS) by modeling basic economic relationships between agents forming a closed loop of relations necessary for their survival. The paper describes a worked-out MAS including an example of a production cycle and used economic rules. A special focus is put on behavior rules and decision systems of an individual agent such as: product...
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Spectral Clustering Wikipedia Keyword-Based search Results
PublicationThe paper summarizes our research in the area of unsupervised categorization of Wikipedia articles. As a practical result of our research, we present an application of spectral clustering algorithm used for grouping Wikipedia search results. The main contribution of the paper is a representation method for Wikipedia articles that has been based on combination of words and links and used for categoriation of search results in this...
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Computational Approaches to Modeling Artificial Emotion – An Overview of the Proposed Solutions
PublicationCybernetic approach to modeling artificial emotion through the use of different theories of psychology is considered in this paper, presenting a review of twelve proposed solutions: ActAffAct, FLAME, EMA, ParleE, FearNot!, FAtiMA, WASABI, Cathexis, KARO, MAMID, FCM, and xEmotion. The main motivation for this study is founded on the hypothesis that emotions can play a definite utility role of scheduling variables in the construction...
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Enhancing Facial Palsy Treatment through Artificial Intelligence: From Diagnosis to Recovery Monitoring
PublicationThe objective of this study is to develop and assess a mobile application that leverages artificial intelligence (AI) to support the rehabilitation of individuals with facial nerve paralysis. The application features two primary functionalities: assessing the paralysis severity and facilitating the monitoring of rehabilitation exercises. The AI algorithm employed for this purpose was Google's ML Kit “face-detection”. The classification...
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Modal analysis of railway current collectors using Autodesk Inventor
PublicationThe paper presents the results of modal analysis of railway current collector type 160EC. In the first place, the analysis was carried out analytically for a simplified two lumped mass pantograph model. Then numerical analysis was conducted in the Autodesk Inventor (AI) on the prepared multibody model using the AI modal analysis algorithm, which is based on the finite element method (FEM). Model elements which are most relevant...
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OrphaGPT: An Adapted Large Language Model for Orphan Diseases Classification
PublicationOrphan diseases (OD) represent a category of rare conditions that affect only a relatively small number of individuals. These conditions are often neglected in research due to the challenges posed by their scarcity, making medical advancements difficult. Then, the ever-evolving medical research and diagnosis landscape calls for more attention and innovative approaches to address the complex challenges of rare diseases and OD. Pre-trained...
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How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe
PublicationThis paper uses a sample of over 9 million workers from 22 European countries to study the intertwined relationship between digital technology, cross-border production links and working conditions. We compare the social consequences of technological change exhibited by three types of innovation: computerisation (software), automation (robots) and artificial intelligence (AI). To fully quantify work-related wellbeing, we propose...
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Adding Interpretability to Neural Knowledge DNA
PublicationThis paper proposes a novel approach that adds the interpretability to Neural Knowledge DNA (NK-DNA) via generating a decision tree. The NK-DNA is a promising knowledge representation approach for acquiring, storing, sharing, and reusing knowledge among machines and computing systems. We introduce the decision tree-based generative method for knowledge extraction and representation to make the NK-DNA more explainable. We examine...
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Importance of artificial intelligence to support the process of anaerobicdigestion of kitchen waste with bioplastics / Znaczenie sztucznej inteligencji we wspomaganiu procesu beztlenowej fermentacji odpadów kuchennych zawierających bioplastiki
PublicationArtificial intelligence (AI) and machine learning were used to obtain more effective methods for conducting the digestion process and achieving final products. Data acquisition was carried out by an automatic monitoring and anal. research. The knowledge describing the anaerobic digestion process was summarized in the form of rules: IF (premise) THEN (conclusion). The compiled set of rules created a knowledge base of the expert...
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A survey of neural networks usage for intrusion detection systems
PublicationIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
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Elimination of dominated partial schedules in scheduling deteriorating jobs
Publicationw artykule rozważany jest problem szeregowania zadań uwarunkowanych czasowo, w notacji trójpolowej opisywany przez 1 | pi = a + bisi | ?ci. wprowadzona jest koncepcja zdominowanych częściowych harmonogramów oraz przedstawiony jest niewielomianowy algorytm dla problemu, który bazuje na eliminacji zdominowanych częściowych harmonogramów. przedstawione są wyniki eksperymentów obliczeniowych, porównujących zaprezentowany algorytm oraz...
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Mercury concentrations in Antarctic zooplankton with a focus on the krill species, Euphausia superba
PublicationThe Antarctic is the most isolated region in the world; nevertheless, it has not avoided the negative impact of human activity, including the inflow of toxic mercury (Hg). Hg deposited in the Antarctic marine environment can be bioavailable and accumulate in the food web, reaching elevated concentrations in high-trophic-level biota, especially if methylated. Zooplankton, together with
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublicationThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
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AlP compound and P-doping for promotion of electrocatalytic activity of N-doped carbon derived from metal-organic framework
PublicationWater splitting plays a key role in future fuels, where two processes occur - the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER). Nitrogen-doped carbon derived from...
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Current status and future success of renewable energy in Pakistan
PublicationMismatch between energy demand and supply from last two decades has been increasing because of the domination of expensive imported oil in energy mix of Pakistan. To import crude oil Government paid US $ 9 billion in 2008–2009 to meet the energy demands...
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Evaluation of ChatGPT Applicability to Learning Quantum Physics
PublicationChatGPT is an application that uses a large language model. Its purpose is to generate answers to various questions as well as provide information, help solve problems and participate in conversations on a wide range of topics. This application is also widely used by students for the purposes of learning or cheating (e.g., writing essays or programming codes). Therefore, in this contribution, we evaluate the ability of ChatGPT...
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Partial dominated schedules and minimizing the total completion time of deteriorating jobs
PublicationA problem of scheduling deteriorating jobs on a single processor is considered. The processing time of a job is given by a function pi=ai+bisi, where si is the starting time of the job, ai>=0, bi>=0, for i=1,...,n. Jobs are non-preemptive and independent and there are neither ready times nor deadlines. The goal is to minimize the total weighted completion time. We show how to employ the concept of non-dominated schedules to construct...
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Sensitivity of the Baltic Sea level prediction to spatial model resolution
Publicationhe three-dimensional hydrodynamic model of the Baltic Sea (M3D) and...
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Application and modelling of Shape-Memory Alloys for structural vibration control: State-of-the-art review
PublicationOne of the most essential components of structural design for civil engineers is to build a system that is resistant to environmental conditions such as harsh chemical environments, and catastrophic disasters like earthquakes and hurricanes. Under these circumstances and disturbances, conventional building materials such as steel and concrete may demonstrate inadequate performance in the form of corrosion, deterioration, oxidizing,...
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Mercury in suspended matter of the Gulf of Gdańsk: Origin, distribution and transport at the land–sea interface
PublicationThe coastal regions of inland seas are particularly vulnerable to Hg pollution. An important carrier of toxic Hg in the marine environment is suspended matter originating from multiple sources. The present study was conducted in the Gulf...
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Szeregowanie zadań uwarunkowanych czasowo
Publicationw pracy przedstawiono wyniki badań nad problemami szeregowania zadań uwarunkowanych czasowo. dla problemu 1|pi=a+bisi|σci przedstawiono nowe heurystyki, przypadek wielomianowy oraz w pełni wielomianowy schemat. wprowadzono koncepcję eliminacji zdominowanych fragmentów harmonogramu, oraz pokazano jak wykorzysta¢ ją do konstrukcji algorytmu dokładnego dla tego problemu, a także jak przy jej pomocy przyspieszy¢ inne algorytmy. następnie...
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The sensors-based artificial intelligence Train Control and Monitoring System (TCMS) for managing the railway transport fleet
PublicationRailways deliver a safe and sustainable form of transport and are typically pointed as one the safest form of transportation. Nevertheless, train accidents still happen, and when they happen, the consequences concern serious fatalities and injuries. Since every case is unique, the most frequent causes of train accidents are mechanical derailments, failures, as well as human errors and ignorance. In order to mitigate the risks posed...
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Przegląd metod szybkiego prototypowania algorytmów uczenia maszynowego w FPGA
PublicationW artykule opisano możliwe do wykorzystania otwarte narzędzia wspomagające szybkie prototypowanie algorytmów uczenia maszynowego (ML) i sztucznej inteligencji (AI) przy użyciu współczesnych platform FPGA. Przedstawiono przykład szybkiej ścieżki przy realizacji toru wideo wraz z implementacją przykładowego algorytmu prze-twarzania w trybie na żywo.
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Distributed Operation of CHP and Hybrid PV Using Consensus Protocol
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Civil liability for artificial intelligence products versus the sustainable development of CEECs: which institutions matter?
PublicationThe aim of this paper is to conduct a meta-analysis of the EU and CEECs civil liability institutions in order to find out if they are ready for the Artificial Intelligence (AI) race. Particular focus is placed on ascertaining whether civil liability institutions such as the Product Liability Directive (EU) or civil codes (CEECs) will protect consumers and entrepreneurs, as well as ensure undistorted competition. In line with the...
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Spectrum-based modal parameters identification with Particle Swarm Optimization
PublicationThe paper presents the new method of the natural frequencies and damping identification based on the Artificial Intelligence (AI) Particle Swarm Optimization (PSO) algorithm. The identification is performed in the frequency domain. The algorithm performs two PSO-based steps and introduces some modifications in order to achieve quick convergence and low estimation error of the identified parameters’ values for multi-mode systems....
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Metaheurystyki w szeregowaniu zadań uwarunkowanych czasowo
Publicationw artykule tym zbadano zastosowanie algorytmów metaheurystycznych w problemach szeregowania zadań uwarunkowanych czasowo. porównano wyniki algorytmu genetycznego, ewolucji różnicowej oraz symulowanego wyżarzania, z reprezentacjami rozwiązania: permutacyjną, opartą o priorytety reguł i kodowaniem przedziałowym, osiągnięte w rozwiązywaniu np-trudnego problemu 1 | pi = ai + bisi | sum wici. gdzie to możliwe, wyniki porównano z rozwiązaniami...
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AUTOMATED NEGOTIATIONS OVER COLLABORATION PROTOCOL AGREEMENTS
PublicationThe dissertation focuses on the augmentation of proactive document - agents with built-in intelligence to recognize execution context provided by devices visited during a business process, and to reach collaboration agreement despite conflicting requirements. The proposed solution, based on intelligent bargaining using neural networks to improve simple multi-issue negotiation between the document and thedevice, requires practically...
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Edu Inspiracje WZiE: Sztuczna inteligencja w edukacji. Czy strach ma wielkie oczy?
PublicationNa dzień dzisiejszy bardzo trudno jest odróżnić treści pisane przez człowieka od tych generowanych przez AI, a najsmutniejsze jest to, że wszyscy, którzy używają pożyczonej inteligencji w nadmiarze, pozbawiają się okazji do uczenia i rozwoju. W rezultacie życie staje się łatwiejsze, ale mądrości jakby ubywa. W artykule dokonano krytycznego przeglądu narzędzi i algorytmów opartych o sztuczną inteligencję wspierający procesy edukacyjne.
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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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The carbohydrate glycosylphosphatidylinositol anchor chain under mechanical stress
PublicationCarbohydrates have quite complicated micro heterogenic structure which may undergo different structural transitions. Due to their extreme flexibility it is very difficult to investigate such structural changes experimentally. In these studies we want to predict what structural and conformational changes are possible in the carbohydrate
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Sztuczna inteligencja w onkologii - nowe narzędzia do diagnostyki i medycyny spersonalizowanej
Publicationstatnie dekady doprowadziły do rozwoju zaawansowanych technologii badawczych, cechujących się wysoką przepustowością. Zmienia to oblicze medycyny, doprowadzając do generowania ogromnej ilości danych. Z każdym kolejnym rokiem przybywa pacjentów onkologicznych, a zebrane informacje o pacjentach przekraczają możliwości lekarzy i naukowców w zakresie samodzielnej analizy tzw. big data. Właśnie dlatego świat nauki coraz częściej zwraca...
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Zastosowanie modułu symulacji dynamicznej programu CAD w analizie układu napędowego elektronarzędzia
PublicationW referacie przedstawiono analizę mechanicznego układu przeniesienia napędu elektronarzędzia (wyrzynarki elektrycznej) przy zastosowaniu Modułu Symulacji Dynamicznej (MSD) programu Autodesk Inventor (AI). Opracowano modele 3D poszczególnych części elektronarzędzia i połączono je przy zachowaniu tzw. kinematyki odwrotnej. Przeprowadzono analizę wpływu poszczególnych węzłów kinetycznych na przebieg momentu na wale silnika elektrycznego....
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Possible uses of crisis situation aiding system in virtual world simulation
PublicationMany of the real world crisis situations like spreading fire, hostile units attack, flood, and etc. are commonly used in computer games where a simulation of extensive virtual world is crucial. This paper presents some ideas for possible uses of existing crisis situation aiding system in such environments. Moreover, it shows how this kind of system can be taught during subsequent games with a large number of players. As an example...
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Collaborative Data Acquisition and Learning Support
PublicationWith the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly annotated and informative data samples. In this paper, we propose a crowdsourcing based approach for data acquisition and tagging with support for Active Learning where the system acts as an...
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From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublicationFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
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Intelligence Augmentation and Amplification: Approaches, Tools, and Case Studies
PublicationMost experts agree that truly intelligent artificial system is yet to be developed. The main issue that still remains a challenge is imposing trust and explainability into such systems. However, is full replication of human intelligence really desirable key aim in intelligence related technology and research? This is where the concept of augmented intelligence comes into play. It is an alternative conceptualization of artificial...
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Algorithmic Human Resources Management
PublicationThe rapid evolution of Digital Human Resources Management has introduced a transformative era where algorithms play a pivotal role in reshaping the landscape of workforce management. This transformation is encapsulated in the concepts of algorithmic management and algorithmic Human Resource Management (HRM). The integration of advanced analytics, predictive and prescriptive analytics and the power of Artificial Intelligence (AI)...
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Smart Knowledge Engineering for Cognitive Systems: A Brief Overview
PublicationCognition in computer sciences refers to the ability of a system to learn at scale, reason with purpose, and naturally interact with humans and other smart systems, such as humans do. To enhance intelligence, as well as to introduce cognitive functions into machines, recent studies have brought humans into the loop, turning the system into a human–AI hybrid. To effectively integrate and manipulate hybrid knowledge, suitable technologies...
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The influence of image masks definition onsegmentation results of histopathological imagesusing convolutional neural network
PublicationAbstract—In the era of collecting large amounts of tissue materials, assisting the work of histopathologists with various electronic and information IT tools is an undeniable fact. The traditional interaction between a human pathologist and the glass slide is changing to interaction between an AI pathologist with a whole slide images. One of the important tasks is the segmentation of objects (e.g. cells) in such images. In this...
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CMGNet: Context-aware middle-layer guidance network for salient object detection
PublicationSalient object detection (SOD) is a critical task in computer vision that involves accurately identifying and segmenting visually significant objects in an image. To address the challenges of gridding issues and feature...
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Multi-objective optimization of water quality, pumps operation, and storage sizing of water distribution systems
PublicationA multi-objective methodology utilizing the Strength Pareto Evolutionary Algorithm (SPEA2) linked to EPANET for trading-off pumping costs, water quality, and tanks sizing of water distribution systems is developed and demonstrated. The model integrates variable speed pumps for modeling the pumps operation, two water quality objectives (one based on chlorine disinfectant concentrations and one on water age), and tanks sizing cost...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Kazimierz Market Place. Akwarela 38x56cm
PublicationL'acquerello in Alessandria, la mostra internazionale patrocinata dal Comune e dalle Provincia di Alessandria, dalla Regione Piemonte e dal Comune di Vignale e organizzata dall'Associazione italiana acquerellisti. L'esposizione, circa 150 acquerelli dei socie Aia e di artisti provenienti da Australia, Belgio, Brasile Polonia e Spagna per presentare le principali tecniche dell'acquerelli e le diverse concezioni artistiche e stilistiche...
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Enhanced degradation of glucocorticoids, a potential COVID-19 remedy, by co-fermentation of waste activated sludge and animal manure: The role of manure type and degradation mechanism
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