Toxicity And Surface Modification Of Dendrimers: A Critical Review

: As compared to other nano polymers, dendrimers have novel three dimensional, synthetic hyperbranched, nano-polymeric structures. The characteristic of these supramolecular dendritic structures has a high degree of significant surface as well as core functionality in the transportation of drugs for targeted therapy, specifically in host-guest response, gene transfer therapy and imaging of biological systems. However, there are conflicting shreds of evidence regarding biological safety and dendrimers toxicity due to their positive charge at the surface. It includes cytotoxicity, hemolytic toxicity, haematological toxicity, immunogenicity and in vivo toxicity. Therefore to resolve these problems surface modification of the dendrimer group is one of the methods. From that point, this review involves different strategies which reduce the toxicity and improve the biocompatibility of different types of dendrimers. From that viewpoint, we broaden the structural and safe characteristics of the dendrimers in the biomedical and pharmaceutical fields.

Rich specifications for Ethereum smart contract verification

Smart contracts are programs that execute in blockchains such as Ethereum to manipulate digital assets. Since bugs in smart contracts may lead to substantial financial losses, there is considerable interest in formally proving their correctness. However, the specification and verification of smart contracts faces challenges that rarely arise in other application domains. Smart contracts frequently interact with unverified, potentially adversarial outside code, which substantially weakens the assumptions that formal analyses can (soundly) make. Moreover, the core functionality of smart contracts is to manipulate and transfer resources; describing this functionality concisely requires dedicated specification support. Current reasoning techniques do not fully address these challenges, being restricted in their scope or expressiveness (in particular, in the presence of re-entrant calls), and offering limited means of expressing the resource transfers a contract performs. In this paper, we present a novel specification methodology tailored to the domain of smart contracts. Our specifications and associated reasoning technique are the first to enable: (1) sound and precise reasoning in the presence of unverified code and arbitrary re-entrancy, (2) modular reasoning about collaborating smart contracts, and (3) domain-specific specifications for resources and resource transfers, expressing a contract's behaviour in intuitive and concise ways and excluding typical errors by default. We have implemented our approach in 2vyper, an SMT-based automated verification tool for Ethereum smart contracts written in Vyper, and demonstrated its effectiveness for verifying strong correctness guarantees for real-world contracts.

Mobile apps in retail: Effect of push notification frequency on app user behavior

Push notifications are a core functionality of mobile apps and allow app publishers to interact with existing app users and send promotional content. Since every push notification can also interrupt or annoy app users, the frequency of push notifications is a critical success factor. This study investigates how different frequencies of push notifications affect the behavior of app users of mobile apps in retail. In an experiment with 17,500 app users, five different frequencies are tested over seven weeks, and the effects on real observed app user behavior are analyzed. The results show that as the frequency of the non-personalized push notifications increases, uninstalls increase, and the direct open rate of push notifications decreases. A significant influence on indirect opens cannot be proven. The results provide practitioners with important insights into the potential harm that a too high frequency of push notifications can cause. Furthermore, the results support the importance of relevant content tailored to the respective user.

Mass Tracking in Cellular Networks for the COVID-19 Pandemic Monitoring

The year 2020 was marked by the emergence of the COVID-19 pandemic. After months of uncontrolled spread worldwide, a clear conclusion is that controlling the mobility of the general population can slow down the propagation of the pandemic. Tracking the location of the population enables better use of mobility limitation policies and the prediction of potential hotspots, as well as improved alert services to individuals that may have been exposed to the virus. With mobility in their core functionality and a high degree of penetration of mobile devices within the general population, cellular networks are an invaluable asset for this purpose. This paper shows an overview of the possibilities offered by cellular networks for the massive tacking of the population at different levels. The major privacy concerns are also reviewed and a specific use case is shown, correlating mobility and number of cases in the province of Málaga (Spain).

Before, Between, and After: Enriching Robot Communication Surrounding Collaborative Creative Activities

Research in creative robotics continues to expand across all creative domains, including art, music and language. Creative robots are primarily designed to be task specific, with limited research into the implications of their design outside their core task. In the case of a musical robot, this includes when a human sees and interacts with the robot before and after the performance, as well as in between pieces. These non-musical interaction tasks such as the presence of a robot during musical equipment set up, play a key role in the human perception of the robot however have received only limited attention. In this paper, we describe a new audio system using emotional musical prosody, designed to match the creative process of a musical robot for use before, between and after musical performances. Our generation system relies on the creation of a custom dataset for musical prosody. This system is designed foremost to operate in real time and allow rapid generation and dialogue exchange between human and robot. For this reason, the system combines symbolic deep learning through a Conditional Convolution Variational Auto-encoder, with an emotion-tagged audio sampler. We then compare this to a SOTA text-to-speech system in our robotic platform, Shimon the marimba player.We conducted a between-groups study with 100 participants watching a musician interact for 30 s with Shimon. We were able to increase user ratings for the key creativity metrics; novelty and coherence, while maintaining ratings for expressivity across each implementation. Our results also indicated that by communicating in a form that relates to the robot’s core functionality, we can raise likeability and perceived intelligence, while not altering animacy or anthropomorphism. These findings indicate the variation that can occur in the perception of a robot based on interactions surrounding a performance, such as initial meetings and spaces between pieces, in addition to the core creative algorithms.

Blockchain for social memory institutions: Functional value and possibilities

De-centralized storage and the closely-coupled related constancy of loaded data, immunity against hacker attacks, transaction history recording and complete transparency make the blockchain technology attractive not only for developing cryptocurrencies and economic transactions. The author reviews the world experience in applying the technology to various activities of social memory institutions and, in particular, individual programs based on the blockchain. The technology enables to provide control and insurance for pieces of art, to ensure copyright, to prevent illegal copying, to store digital copies and ori- ginal works created in the digital environment, to integrate resources using the key functionality of distributed databases. The possibilities and prospects for Russia are evaluated; the need for regulative foundation to define core functionality and legal liability of blockchain processes is emphasized. The possibility for using the technology for building the single knowledge space as the integrative model of digital museum, archival and library resources is analyzed.

Towards trustworthy blockchains: normative reflections on blockchain-enabled virtual institutions

This paper proposes a novel way to understand trust in blockchain technology by analogy with trust placed in institutions. In support of the analysis, a detailed investigation of institutional trust is provided, which is then used as the basis for understanding the nature and ethical limits of blockchain trust. Two interrelated arguments are presented. First, given blockchains’ capacity for being institution-like entities by inviting expectations similar to those invited by traditional institutions, blockchain trust is argued to be best conceptualized as a specialized form of trust in institutions. Keeping only the core functionality and certain normative ideas of institutions, this technology broadens our understanding of trust by removing the need for third parties while retaining the value of trust for the trustor. Second, the paper argues that blockchains’ decentralized nature and the implications and effects of this decentralization on trust issues are double-edged. With the erasure of central points, the systems simultaneously crowd out the pivotal role played by traditional institutions and a cadre of representatives in meeting their assigned obligations and securing the functional systems’ trustworthy performances. As such, blockchain is positioned as a technology containing both disruptive features that can be embedded with meaningful normative values and inherent ethical limits that pose a direct challenge to the actual trustworthiness of blockchain implementations. Such limits are proposed to be ameliorated by facilitating a shift of responsibility to the groups of people directly associated with the engendering of trust in the blockchain context.

Cascading dominates large-scale disruptions in transport over complex networks

The core functionality of many socio-technical systems, such as supply chains, (inter)national trade and human mobility, concern transport over large geographically-spread complex networks. The dynamical intertwining of many heterogeneous operational elements, agents and locations are oft-cited generic factors to make these systems prone to large-scale disruptions: initially localised perturbations amplify and spread over the network, leading to a complete standstill of transport. Our level of understanding of such phenomena, let alone the ability to anticipate or predict their evolution in time, remains rudimentary. We approach the problem with a prime example: railways. Analysing spreading of train delays on the network by building a physical model, supported by data, reveals that the emergence of large-scale disruptions rests on the dynamic interdependencies among multiple ‘layers’ of operational elements (resources and services). The interdependencies provide pathways for the so-called delay cascading mechanism, which gets activated when, constrained by local unavailability of on-time resources, already-delayed ones are used to operate new services. Cascading locally amplifies delays, which in turn get transported over the network to give rise to new constraints elsewhere. This mechanism is a rich addition to some well-understood ones in, e.g., epidemiological spreading, or the spreading of rumours and opinions over (contact) networks, and stimulates rethinking spreading dynamics on complex networks. Having these concepts built into the model provides it with the ability to predict the evolution of large-scale disruptions in the railways up to 30-60 minutes up front. For transport systems, our work suggests that possible alleviation of constraints as well as a modular operational approach would arrest cascading, and therefore be effective measures against large-scale disruptions.

COMPARATIVE ANALYSIS OF POPULAR PLATFORMS FOR LEARNING MANAGEMENT SYSTEMS

В настоящий момент система онлайн-образования принимает новые масштабы. Потребность в платформе, в которой будет гармонично сочетаться современный функционал и простота пользования, всё больше и больше увеличивается. Использование новейших технических разработок позволяет создавать электронные платформы для организации качественного онлайн-обучения. Представлен обзор платформ, а именно: «Moodle», «iSpring Learn» и «Google Calssroom». Рассматриваемые сервисы имеют большую целевую аудиторию и высокий спрос в сфере онлайн-образования. С помощью них можно осуществлять как очное, так и заочное обучение, хранение информации курса, тестов и лекций, а также производить контроль за прохождением обучения и вести отчётность. Были рассмотрены преимущества и недостатки каждого сервиса. Сравнение платформ производится по ряду характеристик, а именно: удобство интерфейса, мобильность системы (развертывание системы без привлечения специалистов), наличие встроенного редактора курса, наличие видеоконференции, доступность основного функционала, наличие дополнительного функционала, поддержка различного рода файловых расширений, гибкость системы, наличие мобильных приложений, денежные затраты при использовании платформы. Эти аспекты выступают основными при выборе платформы, так как они являются ключевыми при использовании сервисов онлайн-обучения At the moment, the online education system is taking on new dimensions. The need for a platform that will harmoniously combine modern functionality and ease of use is increasing. Creating electronic platforms using the latest technical developments allows you to organize high-quality online education. This article provides an overview of the platforms, namely: "Moodle", "iSpring Learn" and "Google Calssroom". These services have a large target audience and high demand in the field of online education. They can be used for both full-time and part-time training, storing course information, tests, and lectures, as well as monitoring training progress and maintaining reports. We considered the advantages and disadvantages of each service. We compare the platforms by a number of characteristics, namely: usability, mobility of the system (deployment system without the involvement of specialists), the presence of the built-in editor of the course, the availability of video conferencing, the availability of core functionality, additional functionality, support of various kinds of file extensions, the flexibility of the system, the availability of mobile applications, costs when using the platform. These aspects are the main ones when choosing a platform, as they are key when using online learning services

Apprentice for Event Generator Tuning

APPRENTICE is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and likelihood evaluation. Apprentice also introduces algorithms to automate the selection of observable weights to minimize the effect of mis-modeling in the event generators. We illustrate our improvements for the task of MC-generator tuning and limit setting.