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Because violations of information security (ISec) and privacy have become ubiquitous in both personal and work environments, academic attention to ISec and privacy has taken on paramount importance. Consequently, a key focus of ISec research has been discovering ways to motivate individuals to engage in more secure behaviors. Over time, the protection motivation theory (PMT) has become a leading theoretical foundation used in ISec research to help motivate individuals to change their security-related behaviors to protect themselves and their organizations. Our careful review of the foundation for PMT identified four opportunities for improving ISec PMT research. First, extant ISec studies do not use the full nomology of PMT constructs. Second, only one study uses fear-appeal manipulations, even though these are a core element of PMT. Third, virtually no ISec study models or measures fear. Fourth, whereas these studies have made excellent progress in predicting security intentions, none of them have addressed actual security behaviors. This article describes the theoretical foundation of these four opportunities for improvement. We tested the nomology of PMT, including manipulated fear appeals, in two different ISec contexts that model the modern theoretical treatment of PMT more closely than do extant ISec studies. The first data collection was a longitudinal study in the context of data backups. The second study was a short-term cross-sectional study in the context of anti-malware software. Our new model demonstrated better results and stronger fit than the existing models and confirms the efficacy of the four potential improvements we identified.

To make decisions, animals must evaluate candidate choices by accessing memories of relevant experiences. Yet little is known about which experiences are considered or ignored during deliberation, which ultimately governs choice. We propose a normative theory predicting which memories should be accessed at each moment to optimize future decisions. Using nonlocal ‘replay’ of spatial locations in hippocampus as a window into memory access, we simulate a spatial navigation task in which an agent accesses memories of locations sequentially, ordered by utility: how much extra reward would be earned due to better choices. This prioritization balances two desiderata: the need to evaluate imminent choices versus the gain from propagating newly encountered information to preceding locations. Our theory offers a simple explanation for numerous findings about place cells; unifies seemingly disparate proposed functions of replay including planning, learning, and consolidation; and posits a mechanism whose dysfunction may underlie pathologies like rumination and craving.

Recently, ransomware attacks have been among the major threats that target a wide range of Internet and mobile users throughout the world, especially critical cyber physical systems. Due to its unique characteristics, ransomware has attracted the attention of security professionals and researchers toward achieving safer and higher assurance systems that can effectively detect and prevent such attacks. The state-of-the-art crypto ransomware early detection models rely on specific data acquired during the runtime of an attack’s lifecycle. However, the evasive mechanisms that these attacks employ to avoid detection often nullify the solutions that are currently in place. More effort is needed to keep up with an attacks’ momentum to take the current security defenses to the next level. This survey is devoted to exploring and analyzing the state-of-the-art in ransomware attack detection toward facilitating the research community that endeavors to disrupt this very critical and escalating ransomware problem. The focus is on crypto ransomware as the most prevalent, destructive, and challenging variation. The approaches and open issues pertaining to ransomware detection modeling are reviewed to establish recommendations for future research directions and scope.

In this paper, a critical issue related to power management control in autonomous hybrid systems is presented. Specifically, challenges in optimizing the performance of energy sources and backup systems are proposed, especially under conditions of heavy loads or low renewable energy output. The problem lies in the need for an efficient control mechanism that can enhance power availability while protecting and extending the lifespan of the various power sources in the system. Furthermore, it is necessary to adapt the system's operations to variations in climatic conditions for sustained effectiveness. To address the identified problem. It is proposed the use of an intelligent power management control (IPMC) system employing fuzzy logic control (FLC). The IPMC is designed to optimize the performance of energy sources and backup systems. It aims to predict and adjust the system's operating processes based on variations in climatic conditions, providing a dynamic and adaptive control strategy. The integration of FLC is specifically emphasized for its effectiveness in balancing multiple power sources and ensuring a steady and secure operation of the system. The proposed IPMC with FLC offers several advantages over existing strategies. Firstly, it showcases enhanced power availability, particularly under challenging conditions such as heavy loads or low renewable energy output. Secondly, the system protects and extends the lifespan of the power sources, contributing to long-term sustainability. The dynamic adaptation to climatic variations adds a layer of resilience to the system, making it well-suited for diverse geographical and climatic conditions. The use of realistic data and simulations in MATLAB/Simulink, along with real-time findings from the RT-LAB simulator, indicates the reliability and practical applicability of the proposed IPMC strategy. Efficient load supply and preserved batteries further underscore the benefits of the fuzzy logic-based control strategy in achieving a well-balanced and secure system operation.

ABSTRACT This work proposes a 6T1R non‐volatile SRAM (nvSRAM) cell based on resistive memory (RRAM) with a small area overhead and low store power compared to previous designs. It features (1) reusing the transistors in the SRAM cell for accessing the RRAM cell, (2) a voltage‐division (VD)‐based restore process with reduced DC current and (3) a trimmable multi‐cycle (TMC) store process to reduce data backup and recovery errors. We fabricated a 1 kb VD‐6T1R nvSRAM test array with back‐end‐of‐line integrated metal oxide RRAM cells in a 180 nm CMOS process. The reuse of transistors allows the VD‐6T1R cell structure to occupy only 1.14× the area of a standard 6T SRAM cell. The store and restore operations were experimentally verified at the array level. The restore error rates of the fabricated test array can be effectively suppressed using TMC store cycles. The restore errors in the fabricated 1 kb cell array can be eliminated after five cycles.

The recent global warming effect has brought into focus different solutions for combating climate change. The generation of climate-friendly renewable energy alternatives has been vastly improved and commercialized for power generation. As a result of this industrial revolution, solar photovoltaic (PV) systems have drawn much attention as a power generation source for varying applications, including the main utility-grid power supply. There has been tremendous growth in both on- and off-grid solar PV installations in the last few years. This trend is expected to continue over the next few years as government legislation and awareness campaigns increase to encourage a shift toward using renewable energy alternatives. Despite the numerous advantages of solar PV power generation, the highly variable nature of the sun’s irradiance in different seasons of various geopolitical areas/regions can significantly affect the expected energy yield. This variation directly impacts the profitability or economic viability of the system, and cannot be neglected. To overcome this challenge, various procedures have been applied to forecast the generated solar PV energy. This study provides a comprehensive and systematic review of recent advances in solar PV power forecasting techniques with a focus on data-driven procedures. It critically analyzes recent studies on solar PV power forecasting to highlight the strengths and weaknesses of the techniques or models implemented. The clarity provided will form a basis for higher accuracy in future models and applications.

An energy crisis has seen regular power blackouts throughout South America. Andersson Boscán reports from Ecuador where the situation is costing lives in both hospitals and homes

In service-transaction scenarios, blockchain technology is widely used as an effective tool for establishing trust between service providers and consumers. The consensus algorithm is the core technology of blockchain. However, existing consensus algorithms, such as the practical Byzantine fault tolerance (PBFT) algorithm, still suffer from high resource consumption and latency. To solve this problem, in this study, we propose an improved PBFT blockchain consensus algorithm based on quality of service (QoS)-aware trust service evaluation for secure and efficient service transactions. The proposed algorithm, called the QoS-aware trust practical Byzantine fault tolerance (QTPBFT) algorithm, efficiently achieves consensus, significantly reduces resource consumption, and enhances consensus efficiency. QTPBFT incorporates a QoS-aware trust service global evaluation mechanism that implements service reliability ranking by conducting a dynamic evaluation according to the real-time performance of the services. To reduce the traffic of the blockchain, it uses a mechanism that selects nodes with higher values to form a consensus group that votes for consensus according to the global evaluation result of the trust service. A practical protocol is also constructed for the proposed algorithm. The results of extensive simulations and comparison with other schemes verify the efficacy and efficiency of the proposed scheme.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. [...]the Consortium Model (CM) allows institutions to pool resources, expertise, and infrastructure to create shared HPC facilities, enhancing collaboration and cost efficiency but requiring complex governance and security management as seen in the Open Science Grid (OSG) (https://osg-htc.org/). ACE-Uganda operates a hybrid HPC operational model between the CFM, operating as a centralized core facility within Makerere University (an academic institution) and IDI (a research institution); an RCM focusing on health data science and bioinformatics; and a VTCM where HPC systems are tailored to the specific needs of the students, faculty, and researchers. ACE-Uganda’s HPC is cooled by air coolers, two floor-standing Samsung Air Conditioners of 42,000 Btu/h and two wall-mounted Trane Air Conditioners of 18,000 Btu/h each, with a section of the HPC enclosed such that a small area is cooled instead of a large room that is also occupied by systems administrators.

There is no doubt that the transition towards renewable energies is generating many changes on different continents, some with greater impacts than others, but the development that has occurred is recognized and widely accepted. The progress has been significant but it is necessary to analyze the roadmaps that have been proposed so far at the island level so that decision makers have sufficient tools to commit the much-needed economic resources to transform their energy systems into 100% renewable ones. These approaches are not simple and the hard work of the authors who have disseminated their research is recognized. The roadmaps are planned based on the energy potential available in the territories and the future energy demand. Within countries, it is important to increase the economic resources to allocate to investments in environmentally friendly renewable energies. In this review of 100% renewable smart systems on islands, the situation of the American continent, its challenges and its long-term approaches in the different geographical areas facing 2050 are analyzed. This article shows that research into the design of 100% renewable energy systems in scientific articles is fairly new but has gained more and more attention in recent years. In total, 175 articles published since 2002 were identified and analyzed. Many of these articles have a predominant focus on the electricity sector. As a general result, it has been determined that although there has been significant progress towards an orderly energy transition, this has not been consistent with the international agreements signed since the Paris Summit, which is a real challenge in complying with the new commitment of the COP28 of Dubai in tripling the participation of renewables.