Library staff support with Fourth Industrial Revolution's application to provide information resources to remote clients during the COVID-19 library services

PurposeThe Fourth Industrial Revolution (4IR) and the Coronavirus Disease 2019 (COVID-19) have challenged the academic libraries system with a paradigm shift that has never been experienced before. This article highlights how the library staff offered support with the 4IR to the remote during the COVID-19 era; to ensure that the provision of information resources does not halt because of the imposed lockdown COVID-19 regulations. The purpose of this study was to examine the library staff support with 4IR's application to provide information resources to remote clients during the COVID-19 library services.Design/methodology/approachThe study was anchored by the positivism research paradigm and used a quantitative research approach. Microsoft Form was used to design an online questionnaire to collect data from the library staff working in a distance education environment in Gauteng Province of South Africa. The collected data were analyzed using the Statistical Package for the Social Sciences (SPSS).FindingsThe findings discovered that the library staff was keen on job innovation; however, the COVID-19 restrictions were a major cause for the library staff not to provide information resources to remote clients effectively.Research limitations/implicationsThe 4IR has both positive and negative effects on the library staff and the remote clients. To ensure that academic libraries fully embrace the 4IR; it is imperative to examine how the remote clients affected by digital divide can benefit from this revolution since they do not have access to adequate gadgets such as laptops/personal computers/tablets/smartphone/iPods and data for Internet connection.Practical implicationsThis study contributed to the Library and Information Science's (LIS) field by adding value to the knowledge base concerning how the library staff working in academic libraries operating in a distance education environment in Gauteng Province of South Africa offered support to the remote clients during the COVID-19 pandemic that impacted the drastic adoption of the 4IR.Social implicationsStakeholders, library management and policymakers gained insight to revisit the existing library staff support regarding mentoring, coaching training remote clients on how to access and download online information resources. This is inspired by the fact that COVID-19 significantly influenced library services' value for knowledge by facilitating policy changes and aligning with 4IR.Originality/valueThe study greatly influences policymakers and information practitioners to mobilize new methods of library staff support.

Neurologic Music Therapy via Telehealth: A Survey of Clinician Experiences, Trends, and Recommendations During the COVID-19 Pandemic

This cross-sectional survey investigated the transition of Neurologic Music Therapy (NMT) services from in-person (pre-COVID-19) to telehealth (since COVID-19) to (1) determine whether the use of an NMT paradigm contributes to the successful transition of therapy services to telehealth, (2) identify which NMT domains and techniques are transferable from in-person to telehealth, (3) identify whether there are differences in the transition of NMT services across different employment settings, and (4) evaluate the potential benefits and challenges of telehealth NMT. An online survey comprised of 49 closed and open-ended questions was distributed by the Academy of Neurologic Music Therapy to 2,778 NMT affiliates worldwide. The survey sought information on demographics, telehealth perceptions, technology, assessment, clinical practice, safety, and caregiver involvement. Quantitative and qualitative analyses were applied. Eighty-one participants answered the survey and the 69 who completed the survey in its entirety were included in the analysis. Results indicated that the frequency of NMT technique usage had no impact on the overall number of clinical hours retained over telehealth. Correlation analysis revealed an association between more frequent NMT usage and perceived likelihood of using telehealth in the future (i.e., once COVID-19 is no longer a major threat), as well as with fewer group sessions lost over telehealth. All NMT domains transferred to telehealth, although within the sensorimotor domain, fewer therapists implemented rhythmic auditory stimulation for telehealth sessions compared to in-person. Overall, NMTs had fewer hours for telehealth compared to in-person regardless of employment setting. Technological challenges were notable drawbacks, while major benefits included the ability to continue providing NMT when in-person sessions were not possible, increased accessibility for remote clients, and positive outcomes related to increased caregiver involvement. Based on the results, our recommendations for implementing telehealth in Neurologic Music Therapy include integrating telehealth into routine care, mitigating safety concerns, identifying those who could benefit most from remote delivery, involving caregivers, and developing/sharing resources for telehealth NMT.

Information Technology Skills and Competencies for Academic Library Staff

Academic libraries are now enduring a substantial shift, which is influenced by the advancement of information technology (IT) that has drastically changed the operating system of academic libraries. The changes have impacted significantly on the skills and competencies required of library staff. This chapter shed light on the background of modern academic libraries, the IT tools used by various academic libraries (for both remote clients and library staff) around the world to provide and access information resources and/or library and information services (LIS) to meet the information needs of remote clients. IT is becoming a tool in modern academic libraries designed to facilitate library operations to meet the information needs of academic library clients. In light of this, library staff is obliged to be equipped with IT skills and competencies to assist the institution to achieve its objectives by supporting teaching, learning, and research.

FFAU—Framework for Fully Autonomous UAVs

Unmanned Aerial Vehicles (UAVs), although hardly a new technology, have recently gained a prominent role in many industries being widely used not only among enthusiastic consumers, but also in high demanding professional situations, and will have a massive societal impact over the coming years. However, the operation of UAVs is fraught with serious safety risks, such as collisions with dynamic obstacles (birds, other UAVs, or randomly thrown objects). These collision scenarios are complex to analyze in real-time, sometimes being computationally impossible to solve with existing State of the Art (SoA) algorithms, making the use of UAVs an operational hazard and therefore significantly reducing their commercial applicability in urban environments. In this work, a conceptual framework for both stand-alone and swarm (networked) UAVs is introduced, with a focus on the architectural requirements of the collision avoidance subsystem to achieve acceptable levels of safety and reliability. The SoA principles for collision avoidance against stationary objects are reviewed and a novel approach is described, using deep learning techniques to solve the computational intensive problem of real-time collision avoidance with dynamic objects. The proposed framework includes a web-interface allowing the full control of UAVs as remote clients with a supervisor cloud-based platform. The feasibility of the proposed approach was demonstrated through experimental tests using a UAV, developed from scratch using the proposed framework. Test flight results are presented for an autonomous UAV monitored from multiple countries across the world.

miEAA 2.0: integrating multi-species microRNA enrichment analysis and workflow management systems

Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs. Here, we present miEAA 2.0, supporting miRNA input from ten frequently investigated organisms. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miRBase miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualizations such as heatmaps and running sum curves with background distributions. We demonstrate the new features with case studies for human kidney cancer, a biomarker study on Parkinson’s disease from the PPMI cohort, and a mouse model for breast cancer. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.

miEAA 2.0: Integrating multi-species microRNA enrichment analysis and workflow management systems

Gene set enrichment analysis has become one of the most frequently used applications in molecular biology research. Originally developed for gene sets, the same statistical principles are now available for all omics types. In 2016, we published the miRNA enrichment analysis and annotation tool (miEAA) for human precursor and mature miRNAs.Here, we present miEAA 2.0, supporting miRNA input from Homo sapiens, Mus musculus, and Rattus norvegicus. To facilitate inclusion of miEAA in workflow systems, we implemented an Application Programming Interface (API). Users can perform miRNA set enrichment analysis using either the web-interface, a dedicated Python package, or custom remote clients. Moreover, the number of category sets was raised by an order of magnitude. We implemented novel categories like annotation confidence level or localisation in biological compartments. In combination with the miR-Base miRNA-version and miRNA-to-precursor converters, miEAA supports research settings where older releases of miRBase are in use. The web server also offers novel comprehensive visualisations such as heatmaps and running sum curves with background distributions. Lastly, additional methods to correct for multiple hypothesis testing were implemented. We demonstrate the new features using case studies for human kidney cancer and mouse samples. The tool is freely accessible at: https://www.ccb.uni-saarland.de/mieaa2.

Weather Prediction using Multiple IoT Based Wireless Sensors

Environmental monitoring has become extremely important due to recent changes in the climate. It is important for ensuring a safe and wealthy life of both humans and artifacts. This field is based on remote sensing and wireless sensor networks for gathering data about the environment. Recent advancements, for example, the vision of the Internet of Things (IoT), the distributed computing model, and digital physical frameworks support the transmission and management of huge amounts of data relating to the trends determined in environmental parameters. In this context, the paper presents three different IoT-based wireless sensors for weather prediction and environmental monitoring: one employing User Datagram Protocol (UDP)-based Wi-Fi communication, second communicating through Wi-Fi and Hypertext Transfer Protocol (HTTP), and a third one using Bluetooth communication. The system consists of three different wireless sensor nodes based on Node-MCU Wi-Fi module or Arduino microcontroller that is connected to the internet, and a firebase cloud server, which provides information storage and delivery to remote clients. In addition, to view the result output in an effective and user friendly manner, MIT App Inventor is used to develop applications for Android phones using a web browser and either an associated phone or the on-screen phone person. The system conducts a lookup table which contains the value of temperature, humidity, real time rain, and a level of carbon monoxide (CO) and are used to predict the current environmental conditions.

A Bit More Than a Bit Is More Than a Bit Better

We study both the practical and theoretical efficiency of private information retrieval (PIR) protocols in a model wherein several untrusted servers work to obliviously service remote clients’ requests for data and yet no pair of servers colludes in a bid to violate said obliviousness. In exchange for such a strong security assumption, we obtain new PIR protocols exhibiting remarkable efficiency with respect to every cost metric—download, upload, computation, and round complexity—typically considered in the PIR literature. The new constructions extend a multiserver PIR protocol of Shah, Rashmi, and Ramchandran (ISIT 2014), which exhibits a remarkable property of its own: to fetch a b-bit record from a collection of r such records, the client need only download b + 1 bits total. We find that allowing “a bit more” download (and optionally introducing computational assumptions) yields a family of protocols offering very attractive trade-offs. In addition to Shah et al.’s protocol, this family includes as special cases (2-server instances of) the seminal protocol of Chor, Goldreich, Kushilevitz, and Sudan (FOCS 1995) and the recent DPF-based protocol of Boyle, Gilboa, and Ishai (CCS 2016). An implicit “folklore” axiom that dogmatically permeates the research literature on multiserver PIR posits that the latter protocols are the “most efficient” protocols possible in the perfectly and computationally private settings, respectively. Yet our findings soundly refute this supposed axiom: These special cases are (by far) the least performant representatives of our family, with essentially all other parameter settings yielding instances that are significantly faster.

Measurement applications in Industry 4.0: the case of an IoT–oriented platform for remote programming of automatic test equipment

<p><span lang="EN-GB">A laboratory regarded as a site that collects IoT devices, and which allows remote clients to use them as an automatic test equipment (ATE) through a controller acting as service provider, is proposed herein. To assure efficiency and responsiveness, the controller is programmed as a multithreading system that takes advantage of multicore processors. The controller includes a server application that supports communication with clients by means of a TCP/IP protocol. It uses GPIB bus functionalities to control the instruments of the local ATE. It allows several clients to connect and interact with the specific resources of the laboratory. Thanks to the availability of identical sets of resources and to the underlying multithreading philosophy, client requests are processed in tandem rather than according to a classical queuing approach.</span></p><p><span lang="EN-GB"><br /></span></p>