System-level Perspective Research Articles

The Multilevel Limb-loss and Preservation Rehabilitation Continuum model (MLPRC): An evidence-based implementation model integrating multiple perspectives to improve outcomes for people facing limb loss.

The patient journey from threatened to actual limb loss, subsequent rehabilitation, and limb preservation through the health system is complicated and prone to delays, attrition, and inequities. A shared multi(socioecological)-level conceptualization of this journey among the multiple stakeholders is the first step for systematically improving limb care through identification of bottlenecks and gaps, contributory factors, and responsive interventions and implementation strategies. To meet this knowledge gap by presenting a novel implementation model, the Multilevel Limb-loss and Preservation Rehabilitation Continuum (MLPRC), that can be used to develop multilevel applications. MLPRC was developed in three overlapping steps: (1) design of the patient journey through the health system (horizontal element), (2) addition of multilevel perspectives along the journey (vertical element), and (3) implementation facilitation by incorporating implementation model constructs (concentric cells element). MLPRC is an implementation model for limb loss and preservation with three concentric cells: inner context cell (horizontal time-ordered patient journey at patient level, based on phases of amputation rehabilitation and patient journey concepts, and corresponding care delivery at provider/organization-level, based on the continuum of care and lower limb loss rehabilitation continuum concepts, on the journey timeline), less influenceable outer context cell (community, system and policy level perspectives), and outermost implementation cell, based on Proctor Model of Implementation Research, that utilizes inner and outer context cells (concept derived from Exploration, Preparation, Implementation, Sustainment framework) information to define responsive metrics, interventions and implementation strategies. Examples of MLPRC use as a blueprint for multilevel applications include patient level (education and navigation instruments), provider level (integrated practice clinic, referral streams), organization level (limb care continuum programs), and community, system, and policy level (interdisciplinary organizational partnerships, data repositories). MLPRC is among the first implementation model to present both a unified picture of the field of limb loss and preservation and a blueprint for multilevel applications.

Towards scalable memristive hardware for spiking neural networks.

Spiking neural networks (SNNs) represent a promising frontier in artificial intelligence (AI), offering event-driven, energy-efficient computation that mimics rich neural dynamics in the brain. However, running large-scale SNNs on mainstream computing hardware faces significant challenges to efficiently emulate these dynamical processes using synchronized and logical chips. Memristor based systems have recently demonstrated great potential for AI acceleration, sparking speculations and explorations of using these emerging devices for SNN tasks. This paper reviews the promises and challenges of memristive devices in SNN implementations, and our discussions are focused on the scaling and integration of neuronal and synaptic devices. We survey recent progress in device and circuit development, discuss possible pathways for chip-level integration, and finally probe into hardware-oriented algorithm designs. This review offers a system-level perspective on implementing scalable memristor based SNN platforms.

Exploring and comparing the knowledge structures, collaborations and key themes of electric vehicle research in the environment domain

Using bibliometric analysis, science mapping, and thematic clustering, this study analyzed the knowledge structure, collaboration network, and key themes in electric vehicle (EV) research in the environment domain (ED) from 2010 to 2022. The analysis reveals rapid growth in knowledge production with continued influence over time. China, the United States, and the United Kingdom led environmental EV research during this period, with cluster analysis revealing associations between international collaboration patterns, geographical attributes, and research performance. Countries with strong qualitative research performance showed corresponding excellence in sustainability indices. Comparative analysis revealed that, among major journals and countries, articles in multidisciplinary journals (AMDJ) demonstrated stronger research performance, while articles in environment-specific journals (AESJ) were characterized by stronger research leadership. Analysis of EV research revealed several core themes, including climate change responses, energy management systems, battery and environmental sustainability, and renewable energy, alongside expanding research on charging infrastructure that parallels EV diffusion Furthermore, AESJ emphasized environmental, economic, and system-level perspectives of EVs, while AMDJ primarily addressed EV value chain development, infrastructure optimization, and challenges associated with technological implementation. This study represents the first thorough analysis of environmental EV research across sub-domains, one which identifies associations between research performance, collaboration, and sustainability measures. This thematic analysis demonstrates the interconnection between environmental themes and EV technological progress, highlighting the effect of environmental concerns on the direction of EV research. These findings provide implications for both scholarly research and policies associated with sustainable transportation development from an environmental perspective.

Advancing a system-level perspective in stakeholder theory: Insights from the institutional economics of John R. Commons

Stakeholder theory is a growing body of scholarly literature at the crossroads of business ethics and strategic management. This literature encompasses two distinct levels of inquiry, the levels of the firm and of the capitalistic system as a whole. At the firm level, stakeholder theory provides insight into the roots of the firm-level competitive advantage, whereas at the system level, it explores how capitalistic business can act as a social institution serving moral goals. Until now, the firm-level and system-level perspectives in stakeholder theory have not been effectively integrated. Drawing on the classical institutional economics of John Commons, the present paper elaborates the distinction between the firm and system levels of stakeholder collaboration and examines how they are interconnected. Stakeholder collaboration is shown to be shaped by larger institutions, such as habits, customs, public purposes, and prevailing perceptions of reasonableness. Whereas the system-level perspective in stakeholder theory focuses on the evolution of these larger institutions, the firm-level perspective explores how these institutions contribute to the emergence of the firm-level competitive advantage, thereby generating evolutionary forces that adjust the larger institutions.

Embracing Complexity: Developing a Framework for Evaluating a Multi-Faceted Training and Technical Assistance System.

The benefits of training and technical assistance (TTA) have been well documented. There is limited literature that explores how complex systems of TTA are implemented and evaluated particularly in the violence prevention field. The Violence Prevention Practice and Translation Branch (VPPTB) within the Centers for Disease Control and Prevention's (CDC) Division of Violence Prevention funds multiple technical assistance providers who are tasked with building the capacity of program recipients to implement comprehensive approaches to prevent multiple forms of violence. VPPTB designed the Violence Prevention Technical Assistance Center (VPTAC) with the goal of implementing and evaluating comprehensive TTA efforts that integrates the work of multiple TTA providers to build the capacity of recipients to plan, implement, and evaluate violence prevention efforts. The VPTAC evaluation incorporates data from program recipients, TTA providers, and TTA modalities enabling the VPPTB staff to show improvement in technical knowledge, gather examples of enhanced implementation, and facilitate proactive TTA planning. An important step in the process of evaluating VPTAC from a system-level perspective required an expansion beyond evaluating a single TTA event, provider, or engagement. This is essential to understand how a diverse set of TTA activities and partners work together in their efforts to build capacity.

Dynamic impact of transiting weather systems on coastal currents in the northern Gulf of Mexico

Moving weather systems determine the history of wind variations with patterns as the systems transit through the ocean. These weather systems are integrated entities that can provide a system level perspective. A vessel-based survey repeatedly occupying a 30-km transect 12 times in 36 h provided non-aliased measurements of velocity field that showed how the along-shelf transport varied by more than three-fold in response to a transiting high-pressure weather system following an atmospheric cold front. To further illustrate the impact of different weather systems, we analyzed time series data from moored ADCPs, which showed influence on the velocity field from infrequent summertime cold fronts and remote hurricanes moving through the region, one on the west and the other on the east of the study site. Rotary spectrum analysis showed that the flow field rotated mostly clockwise with a smaller but non-negligible counterclockwise component, consistent with near inertial oscillations mixed with weak tidal currents. A theoretical model is presented by a Laplace transform and a general relationship between the velocity field and forcing functions is obtained, which shows that the contributions to the rotary velocity field from various forcing functions are through mathematical convolutions between the forcing functions and the complex frictional-rotary inertial function (CFRIF). These convolutions include an integrated effect of history of the forcing. CFRIF is effectively a frictional rotary filter that favors inertial oscillations. The wind-stress induced velocity field over a few days is computed and it shows significant variations after the passage of a cold front, with a magnitude consistent with observations. The wind-stress induced velocity is a few times greater than the density driven flow during the ship-based observations. The weather systems passing through the region can impact coastal currents causing a great variability over short time scales.

Sensorless model-based displacement estimator for piezoelectric actuator through a practical three-stage mechanism

Piezoelectric elements (PEMs) are used in a variety of applications. In this paper, we developed a new simple sensorless method for a Piezoelectric Actuator (PEA), which includes piezostack elements and a three-stage amplification mechanism.This research focuses on a piezoelectric actuator that incorporates a three-stage amplification system, where the outcome of one stage serves as the input for the subsequent one. The actuator receives two types of inputs: the voltage applied to the piezoelectric elements and the mechanical load it carries. Its output is defined by the rotation angle observed at the end of the third amplification stage. To indirectly measure the actuator's displacement, a basic external circuit is utilized.The precise movement of these actuators is essential. To circumvent the high costs and limitations associated with highly accurate displacement sensors, there has been a growing interest in sensorless control methods. Certain electrical signals, when measured, can provide an estimation of displacement. However, induced voltage measurements are not effective for piezoelectric stacks. Two more promising measures are the voltage and current of the piezoelectric material.Given that the electrical charge on these actuators closely reflects their displacement with minimal hysteresis across a broad frequency spectrum, it's proposed that displacement can be effectively gauged through current measurements that assess charge.The core contribution of this paper is the introduction and validation, both theoretically and experimentally, of a hybrid algorithm that leverages these two electrical signals to enhance the accuracy of displacement estimates. This was confirmed using a laboratory setup.The primary benefit of this research is the presentation of a straightforward sensorless control algorithm, poised for further exploration within the realm of piezoelectric actuators. The simplicity of both the theoretical model and the sensorless technique facilitates their application across a diverse range of piezoelectric actuators and amplification systems, thereby streamlining the design, modeling, and control strategy development for various actuators.The innovation of this study stems from the application of an uncomplicated sensorless estimation algorithm, coupled with a system-level perspective on piezoelectric actuators. This approach utilizes a simple, adaptable model suitable for a wide array of applications and operational techniques.

Relay-empowered beyond 5G radio access networks with edge computing capabilities

Relevant services envisaged for beyond 5G (B5G) systems, such as extended reality and holographic communications, have extremely demanding user experience requirements with significant computational and communication demands. While edge computing aims to address the computation requirements by offloading the computational tasks to edge servers near the user, the communication will take advantage of the technologies developed for 5G New Radio jointly with an never-before-seen degree of network densification. This paper proposes the use of relays with edge computing capabilities. The approach's potential for B5G are identified, and a system model is defined to characterize both computational and communications viewpoints. Based on this, results are provided to highlight the gains and limitations of the proposed approach from a system-level perspective. Finally, the main challenges for enabling relays with computing capabilities in B5G deployments are discussed.

Transition pathway towards more sustainable waste management practices for end-of-life reverse osmosis membranes: Challenges and opportunities in Brazil

Desalination using reverse osmosis (RO) elements is increasing worldwide. In addition to creating technical alternatives to extend their life-cycle, it is also important to assess how circular economy can be encouraged considering the role of the involved stakeholders. To help address this issue, this work proposed a transition pathway towards more sustainable waste management scenarios. It was built using a three-step methodology whose highlight was to use life-cycle assessment results to classify the level of institutional and sustainable disruption of three disposure options (reuse/chemical conversion/recycling of materials). Once built, a system-level perspective was used to explore potential win, losses, and conflicts from the actors involved in the waste chain. It was seen that the current scenario follows a linear take-make-disposal structure and there is a need to promote actors that will actually perform direct reuse and chemical conversion of the membranes. However, even if these actors are encouraged, they might encounter a resistance of business-as-usual, since there is no legal restriction for landfill disposal. In addition, institutional framework needs to be addressed to avoid direct competition and promote partnership with these and other actors in the waste chain.

Stakeholder perspectives of mental healthcare services in Bangladesh, its challenges and opportunities: a qualitative study.

This study explores Bangladesh's mental health services from an individual- and system-level perspective and provides insights and recommendations for strengthening it's mental health system. We conducted 13 in-depth interviews and 2 focus group discussions. Thirty-one participants were recruited using a combination of purposive and snowball sampling methods. All interviews and group discussions were audio-recorded and transcribed, and key findings were translated from Bengali to English. Data were coded manually and analysed using a thematic and narrative analysis approach. Stakeholders perceived scarcity of service availability at the peripheral level, shortage of professionals, weak referral systems, lack of policy implementation and regulatory mechanisms were significant challenges to the mental health system in Bangladesh. At the population level, low levels of mental health literacy, high societal stigma, and treatment costs were barriers to accessing mental healthcare. Key recommendations included increasing the number of mental health workers and capacity building, strengthening regulatory mechanisms to enhance the quality of care within the health systems, and raising awareness about mental health. Introducing measures that relate to tackling stigma, mental health literacy as well as building the capacity of the health workforce and governance systems will help ensure universal mental health coverage.

Optimizing the Placement and Beamforming of RIS in Cellular Networks: A System-Level Modeling Perspective

Optimizing the Placement and Beamforming of RIS in Cellular Networks: A System-Level Modeling Perspective

Limitations and Opportunities in PHM for Offshore Wind Farms: A Socio-Technical-Ecological System Perspective

The burgeoning importance of offshore wind farms (OWFs) in the transition to sustainable energy systems underscores the need for effective Prognostics and Health Management (PHM) strategies. While the current PHM framework demonstrates its prowess in enhancing the reliability and operational efficiency of OWFs, this paper contends that its potential remains largely untapped due to certain inherent limitations. This study casts a comprehensive spotlight on the limitations and untapped opportunities within the PHM framework for OWFs from a Socio-Technical-Ecological Systems (SETS) perspective.
 The limitations, as identified, are threefold. First, the existing framework exhibits an over-reliance on technical factors, thus prioritizing maximization of Remaining Useful Life and cost minimization. This emphasis disregards crucial Non-Technological Factors (such as community impacts, stakeholder engagement, Human and Organization Factors (HOFs)) and uncertainty arising from them, which can exert significant influences on OWF’s health and performance. Second, the PHM approach often adopts a component-centric view, with focus on dominant degradation modes, thus undermining the intricate interdependencies among diverse components and failure modes. This lack of a System Level Perspective (SLP) and Multi-Modal Degradation (MMD) hampers a comprehensive understanding of how component degradation cascades through the entire system. Third, the current framework largely ignores the ecological considerations, despite compelling evidence that the current monitoring, assessment, and maintenance activities has significant ecological consequences.
 By addressing the identified limitations and leveraging the opportunities together with AI, the PHM framework for OWFs can evolve into a more comprehensive, inclusive, and resilient approach. The proposed paradigm shift resonates deeply with the contemporary drive towards sustainability, not only in terms of technical efficacy but also in terms of social acceptance and ecological compatibility.

Optimization Approaches for Cost and Lifetime Improvements of Lithium-Ion Batteries in Electric Vehicle Powertrains

With the increasing adoption of electric vehicles (EVs), optimizing lithium-ion battery capacity is critical for overall powertrain performance. Recent studies have optimized battery capacity in isolation without considering interactions with other powertrain components. Furthermore, even when the battery is considered within the full powertrain, most works have only modeled the electrical behavior without examining thermal or ageing dynamics. However, this fails to capture systemic impacts on overall performance. This study takes a holistic approach to investigate the effects of battery capacity optimization on convergence of the full EV powertrain. A battery multiphysics model was developed in MATLAB/Simulink, incorporating experimental data on electrical, thermal, and ageing dynamics and interactions with other components. The model was evaluated using real-world WLTP and Artemis driving cycles to simulate realistic conditions lacking in prior works. The findings reveal significant impacts of battery optimization on total powertrain performance unaccounted for in previous isolated studies. By adopting a system-level perspective and realistic driving cycles, this work provides enhanced understanding of interdependent trade-offs to inform integrated EV design.

An Electro-Photonic System for Accelerating Deep Neural Networks

The number of parameters in deep neural networks (DNNs) is scaling at about 5× the rate of Moore’s Law. To sustain this growth, photonic computing is a promising avenue, as it enables higher throughput in dominant general matrix-matrix multiplication (GEMM) operations in DNNs than their electrical counterpart. However, purely photonic systems face several challenges including lack of photonic memory and accumulation of noise. In this article, we present an electro-photonic accelerator, ADEPT, which leverages a photonic computing unit for performing GEMM operations, a vectorized digital electronic application-specific integrated circuits for performing non-GEMM operations, and SRAM arrays for storing DNN parameters and activations. In contrast to prior works in photonic DNN accelerators, we adopt a system-level perspective and show that the gains while large are tempered relative to prior expectations. Our goal is to encourage architects to explore photonic technology in a more pragmatic way considering the system as a whole to understand its general applicability in accelerating today’s DNNs. Our evaluation shows that ADEPT can provide, on average, 5.73× higher throughput per watt compared to the traditional systolic arrays in a full-system, and at least 6.8× and 2.5× better throughput per watt, compared to state-of-the-art electronic and photonic accelerators, respectively.

Transcriptome Analyses Reveal the Mechanism of Changes in the Sugar Constituents of Jujube Fruits under Saline–Alkali Stress

Saline–alkali stress is an important environmental factor affecting the growth and development of plants. Plants affected by saline–alkali stress can mitigate the damage by regulating the content of osmoregulatory substances such as soluble sugars. Elucidating the regulatory mechanism of the changes in sugar fractions in jujube fruits under saline–alkali stress is crucial for the development of the jujube fruit industry in saline areas. In this study, we investigated the effects of saline–alkali stress on the development and sugar contents of jujube fruits by subjecting jujube trees to low- and high-saline–alkali stress treatments. The result showed that low saline–alkali stress increased the content of each sugar component and total sugar, whereas high saline–alkali stress suppressed their contents. In the early developmental stage, the fruit mainly accumulated fructose and glucose, whereas in the late stage, it accumulated mainly sucrose. We screened various genes, namely trehalose 6-phosphate phosphatase gene (LOC107418410), α-amylase gene (LOC107428855), α-glucosidase gene (LOC107418468), sucrose synthase gene (LOC107416188), and β-amylase gene (LOC107430415, LOC107406235), all of which were highly correlated with sucrose content in saline–alkali stress, indicating that the starch and sucrose metabolic pathways of jujube fruit are the key pathways regulating sugar accumulation in response to saline–alkali stress. To summarize, this study provides a system-level perspective on the dynamic transcriptional regulation of jujube fruits under saline–alkali stress. Additionally, the study preliminarily screened key differentially expressed genes that affect sugar accumulation in response to saline–alkali stress, providing a theoretical basis for the scientific regulation of jujube fruit quality.

Understanding factors affecting the integration of geriatric nurse practitioners into health systems.

Geriatric nurse practitioners (NPs) are introduced into health systems to alleviate provider shortages and improve care for older adults. To achieve these goals, geriatric NPs must be integrated into the health system such that they can efficaciously practice. Internationally, little is known about factors affecting the integration of NPs. Such evidence would improve policymaking and the impact of geriatric NPs on care. In Israel, geriatric NPs were recently introduced. Their ongoing integration is an exemplar for other countries. To identify factors affecting the integration of geriatric NPs in Israel and discuss application of these factors in international policy and research. The Consolidated Framework for Implementation Research guided this qualitative descriptive study. A semistructured interview guide was used to collect data from four professional groups (geriatric NPs, physicians, administrators, and policymakers), which, together, provide a system-level perspective. Factors were identified using deductive content analysis and designated as facilitators, barriers, neutral, or mixed effects. There were 58 participants across the four professional groups. Twenty-eight factors were identified, including patient needs and leadership engagement (facilitators), available information (barrier), culture (mixed), and evidence strength (neutral). Perspectives on several factors differed by the professional group's role in integrating NPs (e.g., costs ). The barriers highlight lacking interprofessional support from a priori policymaking and communication breakdowns. Policies should reflect priorities of administrators, clinicians, and policymakers. These factors may inform policymaking in other countries but would be most effective if based on country-specific research. This implementation science approach may inform future studies.

System-level creep-fatigue reliability evaluation by engineering damage mechanics incorporating cumulative damage-damage threshold interference

Reliability assessment for structural system is of great significance in ensuring system safety, providing a scientific guidance for life management. In this work, a creep-fatigue reliability modeling method is developed for system-level perspective on the basis of cumulative damage-damage threshold interference. Probabilistic damage accumulations to given loading cycles are associated with the creep-fatigue models considering multi-source uncertainties and the damage threshold is regarded as a random variable. Particularly, a numerical procedure is proposed for practical application in engineering by combining the Monte Carlo simulation with Gaussian process regression-based surrogate model. Furthermore, a low-pressure turbine disk under creep-fatigue loading condition is taken as an instance to evaluate its reliability considering multiple weakness sites. Results show that the proposed method is better than the independent treatment because it is capable of avoiding the overly-conservative reliability estimation. In addition, the influence of damage summation rules and damage threshold on reliability is quantitatively analyzed in terms of the developed method. The effect of random parameters in structural system on computational efficiency of the proposed numerical procedure is investigated.

Multilayer network analysis for measuring the inter-connectedness between the oil market and G20 stock markets

We constructed a multilayer information spillover network containing a return spillover layer, a volatility spillover layer, and an extreme risk spillover layer to explore the system risk in the oil and G20 stock markets during 2006–2022. This paper explores the topology of the static and dynamic multilayer networks from both system-level and market-level perspectives. We find that: (i) At the system-level, the structure of layers is significantly different from each other, and risk is transmitted mainly in the volatility spillover layer. In times of crisis, the spillover effect between layers increases. In addition, multilayer networks are more sensitive to risk identification and can identify risks earlier. (ii) At the market-level, developed markets tend to have high connectivity and act as risk-emitter in spillover networks. Developing markets tend to be risk-receivers. Markets with a homogeneous economic structure are more likely to receive shocks and change from risk-receiving to risk-emitting markets. Multilayer information spillover networks provide comprehensive information on financial linkages between national stock markets, which helps regulators and investors to prevent system risks better and allocate assets appropriately.

Wireless Information and Power Transfer: A Bottom-Up Multi-Layer Design Framework

The efficiency of wireless information and power transfer (WIPT) systems requires an essential reevaluation and rethinking of the entire transceiver chain, which is characterized by a bottom-up multi-layer design approach. In this article, we introduce and describe the key design layers: “Mathematical modeling,” associated with the investigation of mathematical models for the wireless power transfer process, “Information-theoretic limits,” which refers to the fundamental limits of the WIPT channel, “Link design,” corresponding to signal processing techniques that make WIPT feasible, “System-level perspective,” which studies the developed WIPT techniques from a macroscopic system-level point-of-view, and “Experimental studies,” that refers to real-world implementation of WIPT systems. These layers are well-connected and their interplay is imperative for the effective design of WIPT systems. Specific case studies are discussed, which demonstrates the interdisciplinary nature of the aforementioned multi-layer design framework.

Federated Learning for Activity Recognition: A System Level Perspective

Federated Learning for Activity Recognition: A System Level Perspective