Advancements in AI-driven multilingual comprehension for social robot interactions: An extensive review

In the digital era, human-robot interaction is rapidly expanding, emphasizing the need for social robots to fluently understand and communicate in multiple languages. It is not merely about decoding words but about establishing connections and building trust. However, many current social robots are limited to popular languages, serving in fields like language teaching, healthcare and companionship. This review examines the AI-driven language abilities in social robots, providing a detailed overview of their applications and the challenges faced, from nuanced linguistic understanding to data quality and cultural adaptability. Last, we discuss the future of integrating advanced language models in robots to move beyond basic interactions and towards deeper emotional connections. Through this endeavor, we hope to provide a beacon for researchers, steering them towards a path where linguistic adeptness in robots is seamlessly melded with their capacity for genuine emotional engagement

A fingerprint based crypto-biometric system for secure communication

To ensure the secure transmission of data, cryptography is treated as the most effective solution. Cryptographic key is an important entity in this procedure. In general, randomly generated cryptographic key (of 256 bits) is difficult to remember. However, such a key needs to be stored in a protected place or transported through a shared communication line which, in fact, poses another threat to security. As an alternative, researchers advocate the generation of cryptographic key using the biometric traits of both sender and receiver during the sessions of communication, thus avoiding key storing and at the same time without compromising the strength in security. Nevertheless, the biometric-based cryptographic key generation possesses few concerns such as privacy of biometrics, sharing of biometric data between both communicating users (i.e., sender and receiver), and generating revocable key from irrevocable biometric. This work addresses the above-mentioned concerns. In this work, a framework for secure communication between two users using fingerprint based crypto-biometric system has been proposed. For this, Diffie-Hellman (DH) algorithm is used to generate public keys from private keys of both sender and receiver which are shared and further used to produce a symmetric cryptographic key at both ends. In this approach, revocable key for symmetric cryptography is generated from irrevocable fingerprint. The biometric data is neither stored nor shared which ensures the security of biometric data, and perfect forward secrecy is achieved using session keys. This work also ensures the long-term security of messages communicated between two users. Based on the experimental evaluation over four datasets of FVC2002 and NIST special database, the proposed framework is privacy-preserving and could be utilized onto real access control systems.Comment: 29 single column pages, 8 figure

Mobile Target Detection in Wireless Sensor Networks With Adjustable Sensing Frequency

How to sense and monitor the environment with high quality is an important research subject in the Internet of Things (IOT). This paper deals with the important issue of the balance between the quality of target detection and lifetime in wireless sensor networks. Two target-monitoring schemes are proposed. One scheme is Target Detection with Sensing Frequency K (TDSFK), which distributes the sensing time that currently is only on a portion of the sensing period into the entire sensing period. That is, the sensing frequency increases from 1 to K. The other scheme is Target Detection with Adjustable Sensing Frequency (TDASF), which adjusts the sensing frequency on those nodes that have residual energy. The simulation results show that the TDASF scheme can improve the network lifetime by more than 17.4% and can reduce the weighted detection delay by more than 101.6%

Artificial intelligence techniques for ground fault line selection in power systems: State-of-the-art and research challenges

In modern power systems, efficient ground fault line selection is crucial for maintaining stability and reliability within distribution networks, especially given the increasing demand for energy and integration of renewable energy sources. This systematic review aims to examine various artificial intelligence (AI) techniques employed in ground fault line selection, encompassing artificial neural networks, support vector machines, decision trees, fuzzy logic, genetic algorithms, and other emerging methods. This review separately discusses the application, strengths, limitations, and successful case studies of each technique, providing valuable insights for researchers and professionals in the field. Furthermore, this review investigates challenges faced by current AI approaches, such as data collection, algorithm performance, and real-time requirements. Lastly, the review highlights future trends and potential avenues for further research in the field, focusing on the promising potential of deep learning, big data analytics, and edge computing to further improve ground fault line selection in distribution networks, ultimately enhancing their overall efficiency, resilience, and adaptability to evolving demands

Infection of inbred BALB/c and C57BL/6 and outbred Institute of Cancer Research mice with the emerging H7N9 avian influenza virus

A new avian-origin influenza virus A (H7N9) recently crossed the species barrier and infected humans; therefore, there is an urgent need to establish mammalian animal models for studying the pathogenic mechanism of this strain and the immunological response. In this study, we attempted to develop mouse models of H7N9 infection because mice are traditionally the most convenient models for studying influenza viruses. We showed that the novel A (H7N9) virus isolated from a patient could infect inbred BALB/c and C57BL/6 mice as well as outbred Institute of Cancer Research (ICR) mice. The amount of bodyweight lost showed differences at 7 days post infection (d.p.i.) (BALB/c mice 30%, C57BL/6 and ICR mice approximately 20%), and the lung indexes were increased both at 3 d.p.i. and at 7 d.p.i.. Immunohistochemistry demonstrated the existence of the H7N9 viruses in the lungs of the infected mice, and these findings were verified by quantitative real-time polymerase chain reaction (RT-PCR) and 50% tissue culture infectious dose (TCID50) detection at 3 d.p.i. and 7 d.p.i.. Histopathological changes occurred in the infected lungs, including pulmonary interstitial inflammatory lesions, pulmonary oedema and haemorrhages. Furthermore, because the most clinically severe cases were in elderly patients, we analysed the H7N9 infections in both young and old ICR mice. The old ICR mice showed more severe infections with more bodyweight lost and a higher lung index than the young ICR mice. Compared with the young ICR mice, the old mice showed a delayed clearance of the H7N9 virus and higher inflammation in the lungs. Thus, old ICR mice could partially mimic the more severe illness in elderly patients. </p

Effects of acidification on nitrification and associated nitrous oxide emission in estuarine and coastal waters

In the context of an increasing atmospheric carbon dioxide (CO2) level, acidification of estuarine and coastal waters is greatly exacerbated by land-derived nutrient inputs, coastal upwelling, and complex biogeochemical processes. A deeper understanding of how nitrifiers respond to intensifying acidification is thus crucial to predict the response of estuarine and coastal ecosystems and their contribution to global climate change. Here, we show that acidification can significantly decrease nitrification rate but stimulate generation of byproduct nitrous oxide (N2O) in estuarine and coastal waters. By varying CO2 concentration and pH independently, an expected beneficial effect of elevated CO2 on activity of nitrifiers (“CO2-fertilization” effect) is excluded under acidification. Metatranscriptome data further demonstrate that nitrifiers could significantly up-regulate gene expressions associated with intracellular pH homeostasis to cope with acidification stress. This study highlights the molecular underpinnings of acidification effects on nitrification and associated greenhouse gas N2O emission, and helps predict the response and evolution of estuarine and coastal ecosystems under climate change and human activities.publishedVersio

Metatranscriptomics Reveals the Functions and Enzyme Profiles of the Microbial Community in Chinese Nong-Flavor Liquor Starter

Chinese liquor is one of the world's best-known distilled spirits and is the largest spirit category by sales. The unique and traditional solid-state fermentation technology used to produce Chinese liquor has been in continuous use for several thousand years. The diverse and dynamic microbial community in a liquor starter is the main contributor to liquor brewing. However, little is known about the ecological distribution and functional importance of these community members. In this study, metatranscriptomics was used to comprehensively explore the active microbial community members and key transcripts with significant functions in the liquor starter production process. Fungi were found to be the most abundant and active community members. A total of 932 carbohydrate-active enzymes, including highly expressed auxiliary activity family 9 and 10 proteins, were identified at 62°C under aerobic conditions. Some potential thermostable enzymes were identified at 50, 62, and 25°C (mature stage). Increased content and overexpressed key enzymes involved in glycolysis and starch, pyruvate and ethanol metabolism were detected at 50 and 62°C. The key enzymes of the citrate cycle were up-regulated at 62°C, and their abundant derivatives are crucial for flavor generation. Here, the metabolism and functional enzymes of the active microbial communities in NF liquor starter were studied, which could pave the way to initiate improvements in liquor quality and to discover microbes that produce novel enzymes or high-value added products

Rapamycin Nano-Micelle Ophthalmic Solution Reduces Corneal Allograft Rejection by Potentiating Myeloid-Derived Suppressor Cells' Function

Allograft rejection is the major cause of corneal allograft failure. Rapamycin (RAPA) has been reported as an effective and novel immunosuppressive agent for patients undergoing corneal transplantation. However, its high water insolubility and low bioavailability have strongly constrained its clinical application. In this study, we successfully developed a RAPA nano-micelle ophthalmic solution and found that corneal allograft survival in recipients treated with RAPA nano-micelle ophthalmic solution was significantly prolonged for more than 2 months, with less inflammatory infiltration, decreased production of pro-inflammatory factors, and elevated recruitment of myeloid-derived suppressor cells (MDSCs). MDSCs from mice treated with RAPA nano-micelle ophthalmic solution could significantly inhibit the proliferation of CD4+T cells through increased expressions of inducible nitric oxidase (iNOS) and arginase-1 (Arg-1). The activity blockade of Arg-1 and iNOS pharmacologically reversed their immunosuppressive ability. Moreover, the effects of RAPA were antagonized by the administration of anti-Gr-1 antibody or by inhibiting the activity of iNOS pharmacologically. In addition, RAPA nano-micelle also effectively alleviated allograft rejection in high-risk rabbit penetrating keratoplasty (PKP) models with corneal vascularization. Collectively, our results demonstrate that RAPA nano-micelle ophthalmic solution could improve the immunosuppressive activity of MDSCs through elevated expression of Arg-1 and iNOS, which highlights the possible therapeutic applications of RAPA against corneal allograft rejection

Design of reinforced concrete frame structure of exhibition hall

Import 23/08/2017Předmětem bakalářské práce je železobetonová dvoupatrová rámová konstrukce, která má sloužit pro občanskou vybavenost jako výstavní síň. Cílem je navrhnout a posoudit nosné prvky rámové konstrukce, konstrukce schodiště a stropů a založení na základových patkách podle metody mezních stavů, platných norem a konstrukčních zásad. Pro posouzené prvky byly vypracovány výkresy výztuže a stavební výkresy.The subject of Bachelor thesis is two storey reinforced concrete frame structure, which has to serve for civil amenitied as exhibition hall. The aim is to design and assess the support elements of frame structure, the structure of staircase and the ceilings and the foundation on foundation plinths according to the method of limit states, applicable standards and design principles. For assess elements have been created reinforcement drawings and constuction drawings.221 - Katedra konstrukcívýborn