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Combining domains of different chemical nature within the same hybrid material through the formation of heterojunctions provides the opportunity to exploit the properties of each individual component within the same nano-object; furthermore, new synergistic properties will often arise as a result of unique interface interactions. However, synthetic strategies enabling precise control over the final architecture of multicomponent objects still remain scarce for certain classes of materials. Herein, we report on the formation of Cu/MOx (M = Ce, Zn and Zr) hybrid nanocrystals with a tunable number of interfaces between the two domains. We demonstrate that the organic ligands employed during the synthesis play a key role in regulating the final configuration. Finally, we show that the synthesized nanocrystals serve as materials platforms to investigate the impact of the Cu/metal oxide interfaces in applications by focusing on the electrochemical CO2 reduction reaction as one representative example., We report on the formation of Cu/metal oxide hybrid nanocrystals with a tunable number of interfaces between the two domains. We demonstrate that the organic ligands employed during the synthesis play a key role in regulating the final configuration.

The production of food within cities through urban agriculture can be considered as a nature-based solution and is argued to be an important response to the current COVID-19 pandemic as well as to climate change and other urban challenges. However, current research on urban agriculture is still fragmented, calling for a systematic and integrative assessment of different forms of urban agriculture and the drivers and constraints for their effective realization. In this context, the Special Issue presents conceptual and empirical research articles from around the world on the impact and implementation potential of various types of urban agriculture. The studies of this Special Issue cover a broad range of impact and implementation dimensions, asssessment methods and geographical backgrounds that can support future studies to develop a systemic perspective on urban food production. Deutsche Forschungsgemeinschaft Bundesministerium für Bildung und Forschung Czech Science Foundation

Technology has become an integral part of contemporary society. The current transition from an industrial society to an information society is accompanied by the implementation of new technologies in every part of human activity. Increasing pressure to apply ICT in critical infrastructure resulted in the creation of new vulnerabilities. Traditional safety approaches are ineffective in a considerable number of cases. Therefore, machine learning another evolutionary step that provides robust solutions for extensive and sophisticated systems. The article focuses on cybersecurity research for industrial control systems that are widely used in the field of critical information infrastructure. Moreover, cybernetic protection for industrial control systems is one of the most important security types for a modern state. We present an adaptive solution for defense against cyber-attacks, which also consider the specifics of the industrial control systems environment. Moreover, the experiments are based on four machine learning algorithms (artificial neural network, recurrent neural network LSTM, isolation forest, and algorithm OCSVM). The proposed anomaly detection system utilizes multiple techniques and processes as preprocessing techniques, optimization techniques, and processes required for result interpretation. These procedures allow the creation of an adaptable and robust system that meets the need for industrial control systems. © 2021 The Authors, Ministry of the Interior of the Czech Republic [VI20192022151]; UIUI A.I.Lab at the Faculty of AppliedInformatics, Tomas Bata University in Zlin; project "e-Infra-struktura CZ" (e-INFRA) [LM2018140], LM2018140; Ministerstvo Vnitra České Republiky: VI20192022151

The industrial processes and systems have become more sophisticated and also adopted in diverse areas of human activities. The Industrial Control System (ICS) or Internet of Things (IoT) have become essential for our daily life, and therefore vital for contemporary society. These systems are often included in Critical Information Infrastructure (CII) which is crucial for each state. Consequently, the cyber defense is and will be one of the most important security field for our society. Therefore, we use the novelty detection approach in order to identify anomalies which can be a symptom of the cyber-attack in ICS environment. To achieve the main goal of the article One-Class Support Vector Machine (OCSVM) algorithm was used. Moreover, the anomaly detection algorithm is adjusted via multi-criteria evaluation and classifier fusion.

The detection of cyber-attacks has become a crucial task for highly sophisticated systems like industrial control systems (ICS). These systems are an essential part of critical information infrastructure. Therefore, we can highlight their vital role in contemporary society. The effective and reliable ICS cyber defense is a significant challenge for the cyber security community. Thus, intrusion detection is one of the demanding tasks for the cyber security researchers. In this article, we examine classification problem. The proposed detection system is based on supervised anomaly detection techniques. Moreover, we utilized classifiers algorithms in order to increase intrusion detection capabilities. The fusion of the classifiers is the way how to achieve the predefined goal.

The accelerating development of information and communication technologies have an eminent influence on contemporary society. As a result, we have an opportunity to increase our effectiveness. However, there is a drawback. Contemporary systems becoming much more interconnected and opened. However, it negatively affects cyber security of Supervisory Control and Data Acquisition (SCADA) systems. Therefore, the reliable security system must be applied in order to increase system resilience. The article deals with widely used systems for intrusion detection (IDS). These systems are an indispensable basis for cyber security of every organization. The aim of the article is to evaluate an anomaly detection predictive models based on classification.

Nanoparticle-cell interactions begin with the cellular uptake of the nanoparticles, a process that eventually determines their cellular fate. In the present work, we show that the morphological features of nanodiamonds (NDs) affect both the anchoring and internalization stages of their endocytosis. While a prickly ND (with sharp edges/corners) has no trouble of anchoring onto the plasma membrane, it suffers from difficult internalization afterwards. In comparison, the internalization of a round ND (obtained by selective etching of the prickly ND) is not limited by its lower anchoring amount and presents a much higher endocytosis amount. Molecular dynamics simulation and continuum modelling results suggest that the observed difference in the anchoring of round and prickly NDs likely results from the reduced contact surface area with the cell membrane of the former, while the energy penalty associated with membrane curvature generation, which is lower for a round ND, may explain its higher probability of the subsequent internalization.

The recent evolution of cyber-attacks creates eminent pressure on information and communication systems. The increasing number of cyber-attacks and their sophistication have resulted in needs of the new type of cyber defense. The anomaly detection in relation to intrusion detection system (IDS) in connection with standard cyber defense technologies may be the answer to contemporary development in cyber security. Moreover, unsupervised anomaly detection based on K-means algorithm is broadly examined by a considerable number of researchers. Therefore, the algorithm is a solid selection in relation to intrusion detection system. However, one of the problems is to determine a proper number of cluster for the K-means. Nonetheless, there are methods to determine the optimal number of clusters. The aim of the article is to determine the number of clusters in relation to Supervisory Control and Data Acquisition system.

This article deals with influence of long term mechanical and temperature stress on whisker growth. The experiments were conducted on three different surfaces. FR4 substrate was having copper, gold and HAL surface finish. Copper and gold surface finish was provided with thin layer of solder. Altogether, three solders (Sn63%Pb37%, Sn99%Cu1% and Sn97%Cu3%) were used. The samples were exposed to long term stress. The aging lasted 6500 hours and the temperature was either laboratory for the first batch or elevated (50 °C) for the second batch. The whisker growth was not observed on samples where the solder alloy was deposited in a thick layer, not even after exposure to elevated temperature or bolt induced compressive stress. The highest amount of tin whiskers was observed on a sample with copper surface finish and solder with high tin content, specifically Sn99%Cu1% solder. The presence of lead in the solder hindered the whisker growth. The length of the whiskers varied from tens to hundreds of micrometers. The whisker observation and measurement was conducted using Olympus SZX8 microscope.[1]

Increased interconnectivity, interoperability and complexity of communication in Supervisory Control and Data Acquisition (further only SCADA) systems, resulted in increasing efficiency of industrial processes. However, the recently isolated SCADA systems are considered as the targets of considerable number of cyber-attacks. Because of this, the SCADA cyber-security is under constant pressure. In this article we examine suitability of current state signature based Intrusion Detection System (further only IDS) in SCADA systems. Therefore, we deeply evaluate the Snort and the Quickdraw rules based on signatures in order to specify their relations to SCADA cyber security. We report the results of the study comprising more than two hundred rules. © Springer International Publishing Switzerland 2016.

International audience; Alumino-silicate coatings and structures formed from alumino-silicate and amorphous chalcogenide submicrometer layers were prepared by pulsed laser deposition. Fabricated thin films were characterized in terms of their structure, morphology, topography, chemical composition, optical properties, and basic anticorrosive functionality. Prepared coatings are amorphous, smooth, without micrometer-sized droplets, with chemical composition close to parent targets. Spectral dependencies of refractive indices and extinction coefficients were derived from variable angle spectroscopic ellipsometry data. Amorphous chalcogenide/alumino-silicate structures present large refractive index differences of individual layers (Δn ~ 1.2 at 1550 nm) which could be useful for optical systems working at infrared telecommunication band wavelengths. Basic anticorrosion data of alumino-silicate layers show promising anticorrosion behavior.

The combination of porous reticular frameworks and nanocrystals (NCs) offers a rich playground to design materials with functionalities, which are beneficial for a large variety of applications. Achieving compositional and structural tunability of these hybrid platforms is not trivial, and new approaches driven by the understanding of their formation mechanism are needed. Here, we present a synthetic route to encapsulate NCs of various sizes, shapes, and compositions in the microporous imine-linked covalent organic framework (COF) LZU1. The tunable NC@LZU1 core-shell hybrids are synthesized by combining colloidal chemistry and homogeneous microwave-assisted syntheses, an approach that allows tailoring of the shell thickness while ensuring COF crystallinity in the presence of the NCs. The uniform morphologies of these new composite materials along with their colloidal nature enable insights into their formation mechanism. Having learned that the COFs heterogeneously nucleate on the NC seeds, we further expand the synthetic approach by developing a step-by-step encapsulation strategy. Here, we gain control over the spatial distribution of various NCs within multilayered NC@LZU1@Nc@LZU1 core-shell-core-shell hybrids and also form yolk-shell nanostructures. The synthetic route is general and applicable to a broad variety of NCs (with catalytic, magnetic, or optical properties), thus revealing a new way to impart functionalities to COFs.