Wyniki wyszukiwania dla: deep l
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The role of water in deep eutectic solvent-base extraction
PublikacjaDeep eutectic solvents (DESs) are currently being used in different sectors, such as electrochemistry, electrodeposition, organic synthesis, nanoparticle preparation, bioactive compound separation, etc. Their use in analytical chemistry has only recently begun to expand. Despite the publication of a sufficient number of DES-based analytical extraction procedures, some details, such as interaction of DESwith the sample and target...
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Solubility advantage of sulfanilamide and sulfacetamide in natural deep eutectic systems: experimental and theoretical investigations
PublikacjaObjective: The aim of this study was to explore the possibility of using natural deep eutectic solvents (NADES) as solvation media for enhancement of solubility of sulfonamides, as well as gaining some thermodynamic characteristics of the analyzed systems. Significance: Low solubility of many active pharmaceutical ingredients is a well-recognized difficulty in pharmaceutical industry, hence the need for different strategies addressing...
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Awaria ściany szczelinowej stanowiącej obudowę wykopu głębokiego
PublikacjaW artykule przedstawiono awarię ściany szczelinowej stanowiącej obudowę wykopu głębokiego. Omówiono warunki geologiczne, hydrogeologiczne i geotechniczne podłoża. Przeprowadzono analizę rozwiązań konstrukcyjnych w kolejnych oszczędnościowych modyfikacjach projektu oraz zrealizowanej wersji. Wykonano obliczenia porównawcze. Wskazano przyczyny wystąpienia awarii. In the paper a failure of diaphragm wall protecting deep excavation...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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Superhydrophobic sponges based on green deep eutectic solvents for spill oil removal from water
PublikacjaThe paper described a new method for crude oil-water separation by means of superhydrophobic melamine sponges impregnated by deep eutectic solvents (MS-DES). Due to the numerous potential of two-component DES formation, simple and quick screening of 156 non-ionic deep eutectic solvents using COSMO-RS (Conductor-like Screening Model for Real Solvents) computational model was used. DES which were characterized by high solubility...
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Concurrent Video Denoising and Deblurring for Dynamic Scenes
PublikacjaDynamic scene video deblurring is a challenging task due to the spatially variant blur inflicted by independently moving objects and camera shakes. Recent deep learning works bypass the ill-posedness of explicitly deriving the blur kernel by learning pixel-to-pixel mappings, which is commonly enhanced by larger region awareness. This is a difficult yet simplified scenario because noise is neglected when it is omnipresent in a wide...
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Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublikacjaIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
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Mobilenet-V2 Enhanced Parkinson's Disease Prediction with Hybrid Data Integration
PublikacjaThis study investigates the role of deep learning models, particularly MobileNet-v2, in Parkinson's Disease (PD) detection through handwriting spiral analysis. Handwriting difficulties often signal early signs of PD, necessitating early detection tools due to potential impacts on patients' work capacities. The study utilizes a three-fold approach, including data augmentation, algorithm development for simulated PD image datasets,...
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Zastosowanie mieszania wgłębnego i iniekcji strumieniowej do wzmocnienia podłoża pod budynkiem basenu.
PublikacjaPrzedstawiono jeden z pierwszych przykładów zastosowania w Europie nowoczesnej technologii wgłębnego mieszania gruntu na mokro (ang. wet Deep Soil Mixing) w celu posadowienia budynku basenu na uwarstwionym podłożu zawierającym grunt organiczny. Technologia DSM, wprowadzona w Polsce przez firmę Keller, polega na mechanicznym mieszaniu in situ gruntu z zaczynem cementowym i pozwala na formowanie w gruncie kolumn z cementogruntu w...
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Deep compaction control of sandy soils
PublikacjaVibroflotation, vibratory compaction, micro-blasting or heavy tamping are typical improvement methods for the cohesionless deposits of high thickness. The complex mechanism of deep soil compaction is related to void ratio decrease with grain rearrangements, lateral stress increase, prestressing effect of certain number of load cycles, water pressure dissipation, aging and other effects. Calibration chamber based interpretation...
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Routing Method for Interplanetary Satellite Communication in IoT Networks Based on IPv6
PublikacjaThe matter of interplanetary network (IPN) connection is a complex and sophisticated topic. Space missions are aimed inter alia at studying the outer planets of our solar system. Data transmission itself, as well as receiving data from satellites located on the borders of the solar system, was only possible thanks to the use of powerful deep space network (DSN) receivers, located in various places on the surface of the Earth. In...
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Towards Knowledge Sharing Oriented Adaptive Control
PublikacjaIn this paper, we propose a knowledge sharing oriented approach to enable a robot to reuse other robots' knowledge by adapting itself to the inverse dynamics model of the knowledge-sharing robot. The purpose of this work is to remove the heavy fine-tuning procedure required before using a new robot for a task via reusing other robots' knowledge. We use the Neural Knowledge DNA (NK-DNA) to help robots gain empirical knowledge and...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publikacjaconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Outlier detection method by using deep neural networks
PublikacjaDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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Detailed studies of superconducting properties of Y2Pd1.25Ge2.75
PublikacjaWe report a successful synthesis of a high-purity intermetallic germanide Y2Pd1.25Ge2.75, crystallizing in the disordered variant of the AlB2-type structure. A single-phase sample was obtained via arc-melting by deliberately tuning the composition out of the ideal 2:1:3 ratio. Specific heat, electrical resistivity and magnetization measurements show that the compound is a weakly-coupled (λ e-p = 0.58) type-II superconductor with...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Application of deep eutectic solvents in analytical sample pretreatment (update 2017–2022). Part A: Liquid phase microextraction
PublikacjaSustainable development in all branches of human activity has become an unequivocal necessity in the last two decades, and green chemistry goes hand in hand with it. Various ways have been proposed in analytical chemistry to meet the current requirements of green chemistry. One such approach is the research of new reagents and solvents for analytical purposes. Deep eutectic solvents (DESs) began being investigated and used in analytical...
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Analysis of the Application of Horizontal Directional Drilling
PublikacjaConstruction works are often considered to be very intrusive for the environment. Project designers assume deep excavations, or a complete replacement of the ground within the investment, which sometimes changes the initial conditions drastically. The problem started to appear in places, where the terrain is complicated and the excavation is burdensome. Some of state authorities...
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Towards a modification of a regulatory framework aiming at bunker oil spill prevention from ships - A design aspect of bunker tanks vents location guided by CFD simulations
PublikacjaAlthough accidental bunker oil spills at seaway are relatively rare events, they can be pose real threat to the natural marine environment. One of the reasons for the bunker spill to occur is a design failure; one of the ways it can demonstrate is an improper location or height of vent heads, leading to a bunker oil discharge during heavy rolling, due to sloshing phenomenon. Design of a ship and her systems is guided by various...
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A general approach to study molecular fragmentation and energy redistribution after an ionizing event
PublikacjaWe propose to combine quantum chemical calculations, statistical mechanical methods, and photoionization and particle collision experiments to unravel the redistribution of internal energy of the furan cation and its dissociation pathways. This approach successfully reproduces the relative intensity of the different fragments as a function of the internal energy of the system in photoelectron–photoion coincidence experiments and...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Changes in conditions of acoustic wave propagation in the Gdansk deep as an effect of climate changes in the Baltic Sea region
PublikacjaThe article presents the results from a research project investigating acoustic climate changes in the Gdansk Deep based on data extending from 1902 to 2019. This part of the southern Gotland Basin, is rarely discussed in the scientific literature. The speed of sound in the seawater is a function of temperature, salinity, and depth. In such shallow sea as Baltic Sea, the impact of depth is not substantial. The other two factors...
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Experimental study on the selected aspects of bow thruster generated flow field at ship zero-speed conditions
PublikacjaThe paper presents the results of experimental study on the interaction between the bow thrusters understood as the flow field changes generated by bow tunnel thruster in deep water conditions operated as a single and twin units. The research was limited to zero-speed case for the ship dead in the water. The influence of the hull form and jet spread between the neighbouring thrusters for several combinations of the applied bow...
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Sensors and Sensor’s Fusion in Autonomous Vehicles
PublikacjaAutonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications. New technologies such as multisensory data fusion, big data processing, and deep learning are changing the quality of areas of applications, improving the sensors and systems used. New ideas such as 3D radar, 3D sonar, LiDAR, and others are based on autonomous vehicle revolutionary development. The Special...
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Comparison of the exponential thermal transient parameterization methods with the SMTP method in the unipedicled DIEP flap computer modelling and simulation
PublikacjaThe aim of this paper is to compare the spatial contrast of the image descriptors obtained via three different thermal transient parameterization methods in Active Dynamic Thermography. The thermal constants and amplitude values of the one- and two- exponential parametrization are compared to the Simplified Magnitude-Temporal Parametrization method (SMTP). The comparison is performed using the data obtained by simulating the cold...
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Neural network model of ship magnetic signature for different measurement depths
PublikacjaThis paper presents the development of a model of a corvette-type ship’s magnetic signature using an artificial neural network (ANN). The capabilities of ANNs to learn complex relationships between the vessel’s characteristics and the magnetic field at different depths are proposed as an alternative to a multi-dipole model. A training dataset, consisting of signatures prepared in finite element method (FEM) environment Simulia...
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Grade of service determination methodology in IP networks with SIP protocol
PublikacjaAlthough Grade of Service is very important in VoIP providers evaluation, We wasn't able to find any paper regarding the topic of measuring GoS variables for IP networks utilizing SIP, which are defined like for PSTN/ISDN/GSM networks (post-selection delay, answering delay, release delay, or probability of end-to-end blocking). Due to the lack of research in this field, it was necessary to start from defining measures and cover...
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Non-invasive blood glucose monitoring with Raman spectroscopy: prospects for device miniaturization
PublikacjaThe number of patients with diabetes has reached over 350 million, and still continues to increase. The need for regular blood glucose monitoring sparks the interest in the development of modern detection technologies. One of those methods, which allows for noninvasive measurements, is Raman spectroscopy. The ability of infrared light to penetrate deep into tissues allows for obtaining measurements through the skin without its...
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Comparison of the Ability of Neural Network Model and Humans to Detect a Cloned Voice
PublikacjaThe vulnerability of the speaker identity verification system to attacks using voice cloning was examined. The research project assumed creating a model for verifying the speaker’s identity based on voice biometrics and then testing its resistance to potential attacks using voice cloning. The Deep Speaker Neural Speaker Embedding System was trained, and the Real-Time Voice Cloning system was employed based on the SV2TTS, Tacotron,...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublikacjaRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Ultrasound-assisted deep eutectic solvent-based liquid–liquid microextraction for simultaneous determination of Ni (II) and Zn (II) in food samples
PublikacjaA new approach was developed for the simultaneous pre-concentration and determination of Ni (II) and Zn (II) in food samples. This method is based on ultrasound-assisted liquid–liquid micro extraction using hydrophobic deep eutectic solvent (DES) and 1,10-phenanthroline as chelating agent. The effect of several parameters, such as pH, selection and volume of DES, amount of chelating agent, time of sonication and centrifugation,...
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Application of deep eutectic solvents in bioanalysis
PublikacjaThe application of deep eutectic solvents (DESs) is sharply surging as a green alternative to conventional solvents due to their unique properties in terms of simplicity of preparation, designability and low cost. A great deal of attention has been paid to the application of these green solvents in analytical chemistry in recent years, and a lot of interesting work has been reported. This review summarizes the most relevant applications...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublikacjaA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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Latest Insights on Novel Deep Eutectic Solvents (DES) for Sustainable Extraction of Phenolic Compounds from Natural Sources
PublikacjaPhenolic compounds have long been of great importance in the pharmaceutical, food, and cosmetic industries. Unfortunately, conventional extraction procedures have a high cost and are time consuming, and the solvents used can represent a safety risk for operators, consumers, and the environment. Deep eutectic solvents (DESs) are green alternatives for extraction processes, given their low or non-toxicity, biodegradability, and reusability....
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Deep learning for recommending subscription-limited documents
PublikacjaDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Efficient Extraction of Fermentation Inhibitors by Means of Green Hydrophobic Deep Eutectic Solvents
PublikacjaThe methods for hydrogen yield efficiency improvements, the gaseous stream purification in gaseous biofuels generation, and the biomass pretreatment are considered as the main trends in research devoted to gaseous biofuel production. The environmental aspect related to the liquid stream purification arises. Moreover, the management of post-fermentation broth with the application of various biorefining techniques gains importance....
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublikacjaThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention
PublikacjaThis paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native (L2) English speech: attention-based feature extraction and data augmentation based on Neural Text-To-Speech (TTS). In a classical approach, audio features are usually extracted from fixed regions of speech such as the syllable nucleus. We propose an attention-based deep learning model that automatically de...
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Is Germany a Hub of ‘Factory Europe’ for CEE Countries?
PublikacjaThe goal of the paper is to decompose gross exports and imports to/from Germany for seven selected economies in Central and Eastern Europe (CEE): the Czech Republic, Estonia, Hungary, Lithuania, Latvia, Poland and Slovakia for 2000 and 2014, in order to identify the role of Germany in absorbing, reflecting and redirecting CEE trade. The authors use a gross trade decomposition proposed by Bonin and Mancini (2017), which is the extended...
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Visual Content Learning in a Cognitive Vision Platform for Hazard Control (CVP-HC)
PublikacjaThis work is part of an effort for the development of a Cognitive Vision Platform for Hazard Control (CVP-HC) for applications in industrial workplaces, adaptable to a wide range of environments. The paper focuses on hazards resulted from the nonuse of personal protective equipment (PPE). Given the results of previous analysis of supervised techniques for the problem of classification of a few PPE (boots, hard hats, and gloves...
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The Influence of the Cuboid Float’s Parameters on the Stability of a Floating Building
PublikacjaUsually, the concept of sufficient stability of a floating structure is connected with the capacity to keep a small heel angle despite the moment of heeling. The variable responsible for these characteristics is the initial metacentric height, which is the relation between the hydrostatic features of the pontoon and the mass properties of the entire object. This article answers the questions of how heavy the floating system should...
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Changes in conditions of acoustic wave propagation in the Gdansk deep as an effect of climate changes in the Baltic Sea region
PublikacjaThe article presents the results from a research project investigating acoustic climate changes in the Gdansk Deepbased on data extending from 1902 to 2019. This part of the southern Gotland Basin, is rarely discussed in thescientific literature.The speed of sound in the seawater is a function of temperature, salinity, and depth. In such shallow sea asBaltic Sea, the impact of depth is not substantial....
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Monitoring of absorptive model biogas purification process using sensor matrices and gas chromatography
PublikacjaThis study examined the process of purifying model biogas using a new type of absorbent based on a Deep Eutectic Solvent (DES) and a commercially available absorbent (Genosorb) to remove acetone, toluene, and cyclohexane. The main aim of the research was to control the purification efficiency using gas chromatography (GC) and an alternative method based on sensor matrices (SM). As a result of comparing the multidimensional SM signals...
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Surfactants application in sample preparation techniques: Insights, trends, and perspectives
PublikacjaSince the implementation of Green Chemistry into analytical practice, significant efforts have been made to improve the sustainability of chemical analysis. These include reducing the use of hazardous chemicals and solvents, minimizing waste, and improving energy efficiency. Surfactants can be applied in chemical analysis as an environmentally friendly alternative to conventional solvents and chemicals. The use of surfactants can...
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Hybrid DUMBRA: an efficient QoS routing algorithm for networks with DiffServ architecture
PublikacjaDynamic routing is very important issue of current packet networks. It may support the QoS and help utilize available network resources. Unfortunately current routing mechanisms are not sufficient to fully support QoS. Although many research has been done in this area no generic QoS routing algorithm has been proposed that could be used across all network structures. Existing QoS routing algorithms are either dedicated to limited...
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Dynamic soil improvement by hybrid technologies
PublikacjaHybrid method of subsoil improvement for road embankment foundation is described. This method is composed of two wellknown methods: dynamic replacement (DR) and microblasting (DDC) one (Deep Dynamic Compaction). The method was used for both the strengthening of the fully saturated organic subsoil as well as for acceleration of the consolidation of the organic layers. The practice ensures the expected results. A proper example on...
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Syntheses and structures of the first terminal phosphanylphosphido complex of hafnium [cp2hf(cl){η1-(me3si)p-p(net2)2}] and the firstzirconocene-phosphanylphosphinidene dimer [cp2zr{μ2-p-p(net2)2}2zrcp2]
PublikacjaReactions of (Et2N)2P-P(SiMe3)Li with [Cp2MCl2] (M= Zr, Hf) in toluene or pentane yield the related terminal phosphanylphosphido complexes [Cp2M(Cl){η1-(Me3Si)P-P(NEt2)2}]. The solid statestructure of [Cp2Hf(Cl){η1-(Me3Si)P-P(NEt2)2}] was established by single crystal X-ray diffraction. The reaction of (Et2N)2P-P(SiMe3)Li with [Cp2ZrCl2] in THF or DME solutions leads to the formationof deep red crystals of the first neutral diamagnetic...
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Molecularly imprinted polymers based on deep eutectic solvents as a greenest materials for selective extraction of emerging contaminants from complex samples
PublikacjaSome of the reagents applied in the synthesis of molecularly imprinted polymers (MIPs) may impact on health and the environment. Thus, a new generation of promising green chemicals are nowadays introduced and investigated, including deep eutectic solvents (DESs). DESs seems to be a reasonable choice as they are characterized as non-toxic, low cost, easy to prepare and biodegradable chemicals. This review presents the information...
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Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?
PublikacjaIn this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...