System Level Research Articles

A quantitative analysis of the security of PoW-based blockchains

AbstractThis study analyzes the security implications of Proof-of-Work blockchains with respect to the stale block rate and the lack of a block verification process. The stale block rate is a crucial security metric that quantifies the proportion of rejected blocks in the blockchain network. The absence of a block verification process represents another critical security concern, as it permits the potential for invalid transactions within the network. In this article, we propose and implement a quantitative and analytical model to capture the primary operations of Proof-of-Work blockchains utilizing the Performance Evaluation Process Algebra. The proposed model can assist blockchain designers, architects, and analysts in achieving the ideal security level for blockchain systems by determining the proper network and consensus settings. We conduct extensive experiments to determine the sensitivity of security to four aspects: the number of active miners and their mining hash rates, the duration between blocks, the latency in block propagation, and the time required for block verification, all of which have been shown to influence the outcomes. We contribute to the findings of the existing research by conducting the first analysis of how the number of miners affects the frequency of stale block results, as well as how the delay in block propagation influences the incentives received by rational miners who choose to avoid the block verification process.

Advanced golden jackal optimization-based fractional-order integral terminal sliding-mode (FO-ITSM) controller for level control of the conical tank system

This article examines a conical tank nonlinear system's level control. A crucial component of facilities like milk processing plants and sugarcane mills is the conical tank. The fluid drains entirely due to the conical shape of the tank. The conical form of the system causes nonlinear dynamics. The conical tank nonlinear system transfer mechanism is not easily accessible, and different operating heights require different transfer mechanisms, making controller design difficult. Developing the Fractional-Order Integral Terminal Sliding-Mode (FO-ITSM) Controller system for Advanced Golden Jackal Optimisation (GJO) based conical tank systems is the main objective of this paper. This is utilised to deliver real-time liquid level management in non-linear conical systems. The dynamics of these models make it possible to identify the conical tank system that produces control signals from liquid samples taken at reference levels with greater accuracy. This system, which is employed on multiple platforms, maintains and controls the liquid level while meeting all design specifications, including time constant, no overshoot, less settling, and rise time. For research simulation work, MATLAB software's FOMCON toolbox is utilised.

Optimal placement of light sensor for improving energy efficiency and visual comfort in smart buildings

The energy consumed by artificial lighting accounts for a significant part of the energy consumption in buildings. Thus, energy consumption can be significantly decreased using optimization techniques, such as the optimum placement of the lighting sensors. In this paper, an optimal placement method of the light sensors is presented to minimize the lighting system's equipment costs and energy consumption and also meet visual comfort under the requirements of the European standard EN12464–1 regarding illuminance-based criteria. In the beginning, based on the illumination measurement grid's mathematical model, the potential location of the sensors is determined. As an average of the dimming levels of the LED lights, the objective function has been introduced. Then, the illuminance and uniformity levels are defined as constraints for the optimization problem. The Battle Royale Optimization (BRO) algorithm is used to solve the optimization problem. Ultimately, based on the results of the BRO algorithm and the calculation of the illuminance deviation, the optimal location of the light sensors is determined. The proposed method is tested in an office room. A fuzzy logic controller is developed to regulate the lighting control system's dimming levels to evaluate the proposed method's performance with other approaches. The comparison results have shown that the proposed method is superior as regards the number of sensors and the optimal sensor position, significant savings in energy consumption of up to 30.8%, and satisfactory visual comfort per the requirements of the European standard EN12464–1.

Low-carbon economic dispatch strategy for microgrids considering stepwise carbon trading and generalized energy storage

Integrating carbon trading mechanisms with generalized energy storage (GES) fully embodies the principles of green and coordinated development, serving as a crucial means to achieve low-carbon construction of microgrids. This research presents a strategy for optimizing energy allocation within microgrids to minimize carbon emissions and enhance microgrid systems' economic-environmental benefits. The strategy takes into account the use of tiered carbon trading and GES. Based on a typical microgrid system architecture, an economic dispatch model for microgrids is developed, which integrates renewable energy sources such as wind and solar storage, gas turbines, energy storage systems, and flexible resources on the demand side. The model aims to minimize carbon emissions while optimizing the allocation of resources. Subsequently, the model facilitates microgrid carbon emission control by considering the transferable, convertible, and reducible properties of GES. Furthermore, implementing a tiered carbon trading mechanism decreases carbon emissions. Finally, using a real microgrid example from a specific region in China, the results indicate that the proposed method significantly enhances the system's low-carbon level. Notably, compared to scenarios that do not consider GES, the proposed method substantially reduces total costs by 6.62% and decreases carbon emissions by 22.2%. The findings indicate that the suggested dispatch model can substantially decrease carbon emissions while simultaneously improving the economic efficiency of the microgrid system.

Design and Implementation of an Intelligent Ultrasonic System based on 51 Microcontroller

With the rapid development of microelectronics and intelligent technology, microcontroller units (MCUs) are increasingly applied in various fields. This paper proposes the design and implementation of an intelligent ultrasonic system based on a 51 microcontroller, integrating ultrasonic sensors, an LCD display, and a 51 MCU to achieve real-time distance measurement, data display, and intelligent control functions. The system utilizes a CD4069 ultrasonic sensor to transmit and receive ultrasonic waves, measuring the distance between the sensor and an object by calculating the time difference between transmission and reception. The measured distance data is processed and displayed on an LCD screen in real-time. Furthermore, the system features intelligent control capabilities, automatically adjusting and controlling devices based on the measured data, thereby enhancing the system's level of intelligence. The intelligent ultrasonic system based on the 51 microcontroller offers advantages such as low cost, high precision, and strong versatility. It can be widely used in various fields, including intelligent robots, obstacle avoidance systems, and automatic parking systems. The design and implementation of this system not only demonstrate innovative applications of ultrasonic ranging technology but also provide valuable references for the extensive application of microcontroller units in intelligent technology fields.

Comparative Analysis of Drought Effects on the Soil Moisture Level and Penetration Resistance in Conventional and Non-Conventional Tillage Systems in Maize Production

The period of extreme weather anomalies in recent years has challenged farmers, and this has encouraged greater adaptability in farming practices. In the last decade, conventional tillage systems have been complemented by more biologically based cropping systems. The research evaluated the impact of drought on soil physical parameters in maize production by testing different conventional and non-conventional tillage systems to ensure optimal soil physical parameters. In the analysis of the prevailing weather conditions, rainfall values were divided into two parts, the pre-growing season and the growing season. We studied different climatic seasons. In 2021, the soil moisture content in the upper shallow 15 cm soil layer during the sowing period in April in the case of conventional tillage was significantly lower than in reduced tillage, conservation tillage and strip tillage. The most significant difference was measured between conventional and conservation tillage, with a difference of 11.25 v/v%. The 2022 crop year was extremely dry. In June, the highest moisture value in the soil was measured in the case of strip tillage with a value of 21.64 v/v%, which was more than 60% higher than in the case of conventional and conservation tillage. In conventional tillage, a very pronounced compacted layer was observed in the lower part of the ploughed layer. This zone reached a compaction of 6.9 MPa between 28 and 34 cm, which is agronomically harmful. No compacted soil layer was found in the experiment site under conservation tillage. In the severe drought year of 2022, only the strip-till system provided the proper water management conditions for the maize stand.

Functional connectome through the human life span.

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer's disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

Dynamics of the nonlinear optical second- and third-harmonic generation in quantum well due to hydrostatic pressure and temperature

We studied the effects of hydrostatic pressure and temperature on the second- and third-harmonic generation (SHG and THG) in semi-parabolic GaAs/Al0.3Ga0.7As quantum wells. By solving the Schrödinger equation numerically, we can determine the system's sub-band energy levels and wave functions, and then calculate its optical gain. The numerical simulation results show that both temperature and hydrostatic pressure can effectively improve the nonlinear optical performance of the system. Notably, we explore the mechanisms underlying these interactions. These findings suggest a viable approach to adjust the nonlinear optical performance of GaAs/Al0.3Ga0.7As quantum system through the subtle interaction between hydrostatic pressure, temperature and structural parameters.

Electrolytes for Sodium Ion Batteries: The Current Transition from Liquid to Solid and Hybrid systems.

Sodium-ion batteries (NIBs) have recently garnered significant interest in being employed alongside conventional lithium-ion batteries, particularly in applications where cost and sustainability are particularly relevant. The rapid progress in NIBs will undoubtedly expedite the commercialization process. In this regard, tailoring and designing electrolyte formulation is a top priority, as they profoundly influence the overall electrochemical performance and thermal, mechanical, and dimensional stability. Moreover, electrolytes play a critical role in determining the system's safety level and overall lifespan. This review delves into recent electrolyte advancements from liquid (organic and ionic liquid) to solid and quasi-solid electrolyte (dry, hybrid, and single ion conducting electrolyte) for NIBs, encompassing comprehensive strategies for electrolyte design across various materials, systems and their functional applications. Our objective is to offer strategic direction for the systematic production of safe electrolytes and to investigate the potential applications of these designs in real-world scenarios while thoroughly assessing the current obstacles and forthcoming prospects within this rapidly evolving field. This article is protected by copyright. All rights reserved.

Measuring patient safety: the Agency for Healthcare Research and Qualityís patient safety indicators

There is a lot of interest in patient safety, but there is still little useable national level information on the actual magnitude of patient safety problems that can be used by providers and policy makers to judge performance. The AHRQ Patient Safety Indicators (PSIs) are a set of measures that can be used with hospital inpatient administrative (discharge) data to provide a perspective on patient safety. They screen for problems that patients experience as a result of exposure to the healthcare system and that are likely amenable to prevention by changes at the system or provider level. There is a growing interest in the possible use of the AHRQ PSIs in international settings. The Organization for Economic Cooperation and Development (OECD) maintains an ongoing project on Health Care Quality Indicators (HCQI) and whose goal is to develop a set of quality indicators that can be used to reliably assess quality of care across countries and raise questions about differences in quality of care internationally. Work is ongoing though a partnership between AHRQ and the Italian National Observatory on Health in the Italian Regions to test the AHRQ QIs with the Italian national hospital discharge data set. Preliminary results indicate that many of the operational issues associated with differences in coding schemes and data set structure are surmountable. With additional refinements on their clinical specificity, increased stability in their definitions over time to permit long-term monitoring and country interest within organizations such as the OECD to build on the existing scientific work of these indicators, their to help answer questions about patient safety worldwide will be significantly enhanced.

Triaxial Load Cell for Ergonomic Risk Assessment: A Study Case of Applied Force of Thumb

To assess the ergonomic risk level in work systems involving tasks performed with hands or fingers, it is necessary to know the exerted triaxial forces. To address this need, a prototype of a triaxial load cell based on principles of linear elasticity theory and mechanical problems of torsion, bending and axial load is presented. This work includes an analytical strain model for each instrumented point and its solution regarding the applied force to a triaxial load cell. The proposed load cell was calibrated and validated by performing different static experimental tests. As a case study, the applied force in three directions while the thumb activates a cigarette lighter was measured. Triaxial forces and resultant forces were obtained and compared with the parameter of 10 N established by the ergonomic standards as reference values for pressing down with the thumb, finding that the applied forces in eight tests were 23.73 N, 43.51 N, 12.69 N, 14.50 N 20.35 N, 21.67 N, 39.74 N and 46.02 N, exceeding the reference values and establishing a direct relationship with Quervain syndrome. In conclusion, the developed load cell is a valid and reliable alternative to measure many forces that cannot be obtained with commercial devices, allowing the level of ergonomic risk to be determined with great precision.

Moral injury in post-9/11 combat-experienced military veterans: A qualitative thematic analysis.

War zone exposure is associated with enduring negative mental health effects and poorer responses to treatment, in part because this type of trauma can entail crises of conscience or moral injury. Although a great deal of attention has been paid to posttraumatic stress disorder and fear-based physiological aspects of trauma and suffering, comparatively less attention has been given to the morally injurious dimension of trauma. Robust themes of moral injury were identified in interviews with 26 post-9/11 military veterans. Thematic analysis identified 12 themes that were subsumed under four categories reflecting changes, shifts, or ruptures in worldview, meaning making, identity, and relationships. Moral injury is a unique and challenging clinical construct with impacts on the individual as well as at every level of the social ecological system. Recommendations are offered for addressing moral injury in a military population; implications for community public health are noted. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mixed (regular and chaotic) dynamics under the channeling of the high energy positrons in [100] direction of the silicon crystal and Podolskiy-Narimanov distribution

The character of motion (regular or chaotic) on the quantum level manifests itself in the statistics of the set of the system's energy levels. The completely regular case generates the sequence of the levels with exponential (Poisson) level spacing distribution; the completely chaotic one — with Wigner distribution. The most interesting case is the co-existence of the regular and chaotic motion domains in the phase space of the system under consideration. The assumption of independent generation of two level sequencies by one chaotic domain and by all regular domains leads to Berry-Robnik distribution. However, the presence of the chaotic motion domain in the phase space affects the levels produced by the regular domains via the so-called chaos-assisted tunneling (CAT) that leads to Podolskiy-Narimanov distribution of the level spacings. This distribution needs the mean amplitude of the tunnel transition and the relative contribution of the regular domains to the mean level density as the parameters. Using their estimations for the transverse motion of the high energy positrons channeling near [100] direction in the silicon crystal we found that Podolskiy-Narimanov distribution demonstrates the best agreement with the level spacing distribution.

Identifying and Responding to Lead in Drinking Water in a University Setting.

Lead is an established neurotoxicant, and it has known associations with adverse neurodevelopmental and reproductive outcomes. Exposure to lead at any level is unsafe, and the United States (US) has enacted various federal and state legislations to regulate lead levels in drinking water in K-12 schools and childcare facilities; however, no regulations exist for higher education settings. Upon the discovery of lead in drinking water fixtures in the University of North Carolina at Chapel Hill (UNC-CH) campus, a cross-campus water testing network and sampling plan was developed and deployed. The campaign was based on the US Environmental Protection Agency's (EPA) 3Ts (Training, Testing, and Taking Action) guidance. The seven-month campaign involved 5954 tests on 3825 drinking water fixtures across 265 buildings. A total of 502 (8.43%) tests showed lead above the limit of detection (1 part per billion, ppb), which represented 422 (11.03%) fixtures. Fewer than 1.5% of the tests were above the EPA action level for public water systems (15 ppb). In conclusion, systematic testing of all the fixtures across campus was required to identify localized contamination, and each entity in the cross-campus network undertook necessary roles to generate a successful testing campaign. UNC-CH established preventative measures to test drinking water fixtures every three years, which provide a framework for other higher education institutions in responding to lead contamination.

Occurrence of microplastics and metals in European seabass produced in different aquaculture systems: Implications for human exposure, risk, and food safety

Microplastics (MPs) are emerging contaminants of increasing concern as they may cause adverse effects and carry other contaminants, which may potentially compromise human health. Despite occurring in aquatic ecosystems worldwide, the knowledge about MP presence in different aquaculture systems and their potential impact on seafood products is still limited. This study aimed to determine the levels of MPs in water, feed, and European seabass (Dicentrarchus labrax) from three relevant aquaculture systems and estimate human exposure to MPs and metals through seabass consumption. The recirculating aquaculture system (RAS) had the highest MP occurrence in water and feed. MP levels in seabass followed the aquaculture system's levels in water and feed, with RAS-farmed fish presenting the highest MP load, both in the fish gastrointestinal tract (GIT) and muscle, followed by pond-, and cage-farmed fish. MPs' characteristics across aquaculture systems and fish samples remained consistent, with the predominant recovered particles falling within the MP size range. The particles were visually characterized and chemically identified by micro-Fourier Transform Infrared Spectroscopy (μFTIR). Most of these particles were fibres composed of man-made cellulose and PET. MP levels in GIT were significantly higher than in muscle for pond- and RAS-farmed fish, MPs' bioconcentration factors >1 indicated bioconcentration in farmed seabass. Metal concentrations in fish muscle were below permissible limits, posing low intake risks for consumers according to the available health-based guidance values and estimated dietary scenarios.

PowerScout: Security-Oriented Power Delivery Network Modeling for Side-Channel Vulnerability Analysis

The growing complexity of modern electronic systems leads to the design of more sophisticated power delivery networks (PDNs). Similar to other system-level shared hardware resources, the on-board PDN unintentionally introduces side channels across design layers and voltage domains which are not explicitly specified in the functional specification. Recent works have demonstrated that the exploitation of the side channel can compromise the system security such as information leakage and fault injection. In this work, we systematically investigate the PDN-based side channel as well as potential countermeasures. To facilitate this goal, we develop PowerScout, a security-oriented PDN simulation framework that unifies the modeling of different PDN-based side-channel attacks. PowerScout performs a fast nodal analysis of complex PDNs at the system level to quantitatively evaluate the severity of side-channel vulnerabilities. With the support of PowerScout, for the first time, we validate PDN side-channel attacks in the literature via simulation. Furthermore, we are able to quantitatively measure the security impact of PDN parameters and configurations. For example, towards information leakage, removing near-chip capacitors can increase intra-chip information leakage by a maximum of 23.23 dB at mid-frequency range and inter-chip leakage by an average of 31.68 dB at mid- and high-frequency range. Similarly, the optimal toggling frequency and duty cycle are derived to achieve fault injection attacks with higher success rate and more precise control. In addition, the vulnerabilities are evaluated when hiding-based countermeasures are implemented. Based on the evaluation, we can understand the optimal defense configuration and explore the trade-off between information leakage mitigation and power supply stability.

Digital Twin-Based Cyber-Attack Detection Framework for Cyber-Physical Manufacturing Systems

Smart manufacturing (SM) systems utilize run-time data to improve productivity via intelligent decision-making and analysis mechanisms on both machine and system levels. The increased adoption of cyber-physical systems in SM leads to the comprehensive framework of cyber-physical manufacturing systems (CPMS) where data-enabled decision-making mechanisms are coupled with cyber-physical resources on the plant floor. Due to their cyber-physical nature, CPMS are susceptible to cyber-attacks that may cause harm to the manufacturing system, products, or even the human workers involved in this context. Therefore, detecting cyber-attacks efficiently and timely is a crucial step toward implementing and securing high-performance CPMS in practice. This paper addresses two key challenges to CPMS cyber-attack detection. The first challenge is distinguishing expected anomalies in the system from cyber-attacks. The second challenge is the identification of cyber-attacks during the transient response of CPMS due to closed-loop controllers. Digital twin (DT) technology emerges as a promising solution for providing additional insights into the physical process (twin) by leveraging run-time data, models, and analytics. In this work, we propose a DT framework for detecting cyber-attacks in CPMS during controlled transient behavior as well as expected anomalies of the physical process. We present a DT framework and provide details on structuring the architecture to support cyber-attack detection. Additionally, we present an experimental case study on off-the-shelf 3D printers to detect cyber-attacks utilizing the proposed DT framework to illustrate the effectiveness of our proposed approach. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This work is motivated by developing a general-purpose and extensible digital twin-enabled cyber-attack detection framework for manufacturing systems. Existing works in the field consider specialized attack scenarios and models that may not be extensible in practical manufacturing scenarios. We utilize digital twin (DT) technology as a key enabler to develop a systematic and extensible framework where we identify the abnormality of a resource and detect if the abnormality is due to an attack or an expected anomaly. We provide several remarks on how our proposed framework can extend existing industrial control systems (ICS) and can accommodate further extensions. The presented DTs utilize data-driven machine learning models, physics-based models, and subject matter expert knowledge to perform detection and differentiation tasks in the context of expected anomalies and model-based controllers that control the manufacturing process between multiple setpoints. We utilize a model predictive controller on an off-the-shelf 3D printer to run the process, and stage anomalies and cyber-attacks that are successfully detected by the proposed framework.

Learner Assessment and Program Evaluation: Supporting Precision Education.

Precision education (PE) systematically leverages data and advanced analytics to inform educational interventions that, in turn, promote meaningful learner outcomes. PE does this by incorporating analytic results back into the education continuum through continuous feedback cycles. These data-informed sequences of planning, learning, assessing, and adjusting foster competence and adaptive expertise. PE cycles occur at individual (micro), program (meso), or system (macro) levels. This article focuses on program- and system-level PE.Data for PE come from a multitude of sources, including learner assessment and program evaluation. The authors describe the link between these data and the vital role evaluation plays in providing evidence of educational effectiveness. By including prior program evaluation research supporting this claim, the authors illustrate the link between training programs and patient outcomes. They also describe existing national reports providing feedback to programs and institutions, as well as 2 emerging, multiorganization program- and system-level PE efforts. The challenges encountered by those implementing PE and the continuing need to advance this work illuminate the necessity for increased cross-disciplinary collaborations and a national cross-organizational data-sharing effort.Finally, the authors propose practical approaches for funding a national initiative in PE as well as potential models for advancing the field of PE. Lessons learned from successes by others illustrate the promise of these recommendations.

Systems level analysis of time and stimuli specific signaling through PKA.

It is well known that eukaryotic cells create gradients of cAMP across space and time to regulate the cAMP dependent protein kinase (PKA) and, in turn, growth and metabolism. However, it is unclear how PKA responds to different concentrations of cAMP. Here, to address this question, we examine PKA signaling in Saccharomyces cerevisiae in different conditions, timepoints, and concentrations of the chemical inhibitor 1-NM-PP1, using phosphoproteomics. These experiments show that there are numerous proteins that are only phosphorylated when cAMP and PKA activity are at/near their maximum level, while other proteins are phosphorylated even when cAMP levels and PKA activity are low. The data also show that PKA drives cells into distinct growth states by acting on proteins with different thresholds for phosphorylation in different conditions. Analysis of the sequences surrounding the 118 PKA-dependent phosphosites suggests that the phosphorylation thresholds are set, at least in part, by the affinity of PKA for each site.

Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing.

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique for investigating biological heterogeneity at the single-cell level in human systems and model organisms. Recent advances in scRNA-seq have enabled the pooling of cells from multiple samples into single libraries, thereby increasing sample throughput while reducing technical batch effects, library preparation time, and the overall cost. However, a comparative analysis of scRNA-seq methods with and without sample multiplexing is lacking. In this study, we benchmarked methods from two representative platforms: Parse Biosciences (Parse; with sample multiplexing) and 10x Genomics (10x; without sample multiplexing). By using peripheral blood mononuclear cells (PBMCs) obtained from two healthy individuals, we demonstrate that demultiplexed scRNA-seq data obtained from Parse showed similar cell type frequencies compared to 10x data where samples were not multiplexed. Despite relatively lower cell capture affecting library preparation, Parse can detect rare cell types (e.g., plasmablasts and dendritic cells) which is likely due to its relatively higher sensitivity in gene detection. Moreover, a comparative analysis of transcript quantification between the two platforms revealed platform-specific distributions of gene length and GC content. These results offer guidance for researchers in designing high-throughput scRNA-seq studies.