System-level Approach Research Articles

Designing of Potential Polyvalent Vaccine Model for Respiratory Syncytial Virus by System Level Immunoinformatics Approaches.

Background Respiratory syncytial virus (RSV) infection is a public health epidemic, leading to around 3 million hospitalization and about 66,000 deaths each year. It is a life-threatening condition exclusive to children with no effective treatment. Methods In this study, we used system-level and vaccinomics approaches to design a polyvalent vaccine for RSV, which could stimulate the immune components of the host to manage this infection. Our framework involves data accession, antigenicity and subcellular localization analysis, T cell epitope prediction, proteasomal and conservancy evaluation, host-pathogen-protein interactions, pathway studies, and in silico binding affinity analysis. Results We found glycoprotein (G), fusion protein (F), and small hydrophobic protein (SH) of RSV as potential vaccine candidates. Of these proteins (G, F, and SH), we found 9 epitopes for multiple alleles of MHC classes I and II bear significant binding affinity. These potential epitopes were linked to form a polyvalent construct using AAY, GPGPG linkers, and cholera toxin B adjuvant at N-terminal with a 23.9 kDa molecular weight of 224 amino acid residues. The final construct was a stable, immunogenic, and nonallergenic protein containing cleavage sites, TAP transport efficiency, posttranslation shifts, and CTL epitopes. The molecular docking indicated the optimum binding affinity of RSV polyvalent construct with MHC molecules (-12.49 and -10.48 kcal/mol for MHC classes I and II, respectively). This interaction showed that a polyvalent construct could manage and control this disease. Conclusion Our vaccinomics and system-level investigation could be appropriate to trigger the host immune system to prevent RSV infection.

Real-Life Mission Profile-Oriented Lifetime Estimation of a SiC Interleaved Bidirectional HV DC/DC Converter for Electric Vehicle Drivetrains

The rapid growth of battery electric vehicles (BEVs) in the automotive field has led to the need for improving their drivetrain performance, mainly focusing on the extension of the battery operating range. However, the majority of performed technical assessments only consider battery state-of-charge (SoC) and depth of discharge, while neglecting the effects on lifetime and failure probability of power electronic components, more specifically the emerging wide bandgap (WBG)-based technologies. Toward fulfilling this gap, the EV market demands lifetime estimation carried out under real-life mission profile to confirm efficiency and reliable operation of EV power electronics for an extended range meeting the EVs lifetime requirements. In this regard, this study proposes a versatile experimental device-under-test setup to investigate a novel stepwise holistic system-level lifetime estimation approach for BEV drivetrains equipped with SiC interleaved bidirectional HV dc/dc converter (IBC). To this end, three different real-life mission profile use-cases are investigated in this article and they provide systematic stress-based lifetime estimation, statistical analyses, and validations in comparison. The study outcome highlights realistic information related to significant impacts of operation range and battery SoC features on the IBC lifetime from all aspects.

Comparison of System-Level Design Approaches on Different Types of Digitally-Controlled Ring-Oscillator

This paper presents a comparative study between two different implementations of digitally-controlled-oscillators (DCOs), whcih is the DAC-based and the digital controller-based DCO in TSMC 65 nm CMOS technology. This paper focuses on ring-oscillator architectures due to their high stability against PVT. The DAC-based oscillator implements a differential architecture, and the digital controller-based architecture operates in a single-ended signal. The SFDR of the DAC-based DCO is 77.2 dBc and controller-based DCO is 56.8 dBc at 125 MHz offset. The Monte-Carlo simulation gives a deviation of 7.4% and 8.5% for the DAC-based and controller-based DCO, respectively. The phase noise performance of the DAC-based DCO and controller-based DCO is −78.9 dBc/Hz and −81.3 dBc/Hz at 1 MHz offset, respectively. The implementations are given and compared according to their performance based on post-layout simulation results.

Resilience function uncovers the critical transitions in cancer initiation.

Considerable evidence suggests that during the progression of cancer initiation, the state transition from wellness to disease is not necessarily smooth but manifests switch-like nonlinear behaviors, preventing the cancer prediction and early interventional therapy for patients. Understanding the mechanism of such wellness-to-disease transitions is a fundamental and challenging task. Despite the advances in flux theory of nonequilibrium dynamics and 'critical slowing down'-based system resilience theory, a system-level approach still lacks to fully describe this state transition. Here, we present a novel framework (called bioRFR) to quantify such wellness-to-disease transition during cancer initiation through uncovering the biological system's resilience function from gene expression data. We used bioRFR to reconstruct the biologically and dynamically significant resilience functions for cancer initiation processes (e.g. BRCA, LUSC and LUAD). The resilience functions display the similar resilience pattern with hysteresis feature but different numbers of tipping points, which implies that once the cell become cancerous, it is very difficult or even impossible to reverse to the normal state. More importantly, bioRFR can measure the severe degree of cancer patients and identify the personalized key genes that are associated with the individual system's state transition from normal to tumor in resilience perspective, indicating that bioRFR can contribute to personalized medicine and targeted cancer therapy.

Global modes for the reduction of flexible multibody systems

Modeling a flexible multibody system employing the floating frame of reference formulation (FFRF) requires significant computational resources when the flexible components are represented through finite elements. Reducing the complexity of the governing equations of motion through component-level reduced-order models (ROM) can be an effective strategy. Usually, the assumed field of deformation is created considering local modes, such as normal, static, or attachment modes, obtained from a single component. A different approach has been proposed in Cammarata (J. Sound Vibr. 489, 115668, 2020) for planar systems only and involves a reduction based on global flexible modes of the whole mechanism. Through the use of global modes, i.e., obtained from an eigenvalue analysis performed on the linearized dynamic system around a certain configuration, it is possible to obtain a modal basis for the flexible coordinates of the multibody system. Here, the same method is extended to spatial mechanisms to verify its applicability and reliability. It is demonstrated that global modes can be used to create ROM both at the system and component levels. Studies on the complexity of the method reveal this approach can significantly reduce the calculation times and the computational effort compared to the unreduced model. Unlike the planar case, the numerical experiments reveal that the system-level approach based on global modes can suffer from slow convergence speed and low accuracy in results.

"There's a lot of talent in the room but it's only really the medical talent that gets heard": a qualitative exploration of multidisciplinary clinicians' perspectives of optimal nutrition care of patients with head and neck cancer.

The high prevalence of malnutrition in patients with head and neck cancer (HNC) negatively impacts outcomes. The best-available evidence has been published in clinical nutrition guidelines; however, translation into practice has lagged. This project aimed to explore multidisciplinary team (MDT) clinicians' perspectives regarding barriers and enablers to best-practice nutrition care in order to inform the design of a new model of care. Qualitative interviews were conducted with clinicians who were purposively sampled from a major HNC tertiary referral centre in Sydney, Australia. To elicit information regarding barriers and facilitators to change, a semi-structured interview schedule was developed, interviews were transcribed verbatim and analyzed employing an inductive thematic approach. The Consolidated Framework for Implementation Research (CFIR) was used to guide data analysis and interpretation of key themes identified. Nineteen participants (11 supportive care and eight medical clinicians) representing allied health, medical, and nursing disciplines participated. Five key themes were identified: (1) acknowledgement of dietetics expertise and access to resources to deliver nutrition care; (2) proactive versus reactive nutrition care; (3) integrated and coordinated care-"The One Stop Shop"; (4) MDT favours the medical model; and (5) leadership-within disciplines, within the MDT. MDT clinicians expressed similar views regarding delivering optimal nutrition care to this high nutritional risk patient group. However, perspectives differed at times between medical and supportive care clinicians, attributable to perceptions that current service structure favours the medical model. In order to design and deliver an evidence-based model of care, specific strategies will be required to ensure: early and ongoing access to expert nutrition care; nutrition care processes are proactive; integrated and coordinated care; and leadership, both intra- and inter-disciplinary. This novel exploration of MDT clinicians' views provides supporting evidence that multi-component implementation strategies comprising individual, team and system-level approaches will be essential to leverage sustainable change.

Model-based pathway enrichment analysis applied to the TGF-beta regulation of autophagy in autism

To differentiate between conditions of health and disease, current pathway enrichment analysis methods detect the differential expression of distinct biological pathways. System-level model-driven approaches, however, are lacking. Here we present a new methodology that uses a dynamic model to suggest a unified subsystem to better differentiate between diseased and healthy conditions. Our methodology includes the following steps: 1) detecting connections between relevant differentially expressed pathways; 2) construction of a unified in silico model, a stochastic Petri net model that links these distinct pathways; 3) model execution to predict subsystem activation; and 4) enrichment analysis of the predicted subsystem. We apply our approach to the TGF-beta regulation of the autophagy system implicated in autism. Our model was constructed manually, based on the literature, to predict, using model simulation, the TGF-beta-to-autophagy active subsystem and downstream gene expression changes associated with TGF-beta, which go beyond the individual findings derived from literature. We evaluated the in silico predicted subsystem and found it to be co-expressed in the normative whole blood human gene expression data. Finally, we show our subsystem’s gene set to be significantly differentially expressed in two independent datasets of blood samples of ASD (autistic spectrum disorders) individuals as opposed to controls. Our study demonstrates that dynamic pathway unification can define a new refined subsystem that can significantly differentiate between disease conditions.

A Dedicated Veno-Venous Extracorporeal Membrane Oxygenation Unit during a Respiratory Pandemic: Lessons Learned from COVID-19 Part I: System Planning and Care Teams

Background: The most critically ill patients with coronavirus disease 2019 (COVID-19) may require advanced support modalities, such as veno-venous extracorporeal membrane oxygenation (VV-ECMO). A systematic, methodical approach to a respiratory pandemic on a state and institutional level is critical. Methods: We conducted retrospective review of our institutional response to the COVID-19 pandemic, focusing on the creation of a dedicated airlock biocontainment unit (BCU) to treat patients with refractory COVID-19 acute respiratory distress syndrome (CARDS). Data were collected through conversations with staff on varying levels in the BCU, those leading the effort to make the BCU and hospital incident command system, email communications regarding logistic changes being implemented, and a review of COVID-19 patient census at our institution from March through June 2020. Results: Over 2100 patients were successfully admitted to system hospitals; 29% of these patients required critical care. The response to this respiratory pandemic augmented intensive care physician staffing, created a 70-member nursing team, and increased the extracorporeal membrane oxygenation (ECMO) capability by nearly 200%. During this time period, 40 COVID-19 patients on VV-ECMO were managed in the BCU. Challenges in an airlock unit included communication, scarcity of resources, double-bunking, and maintaining routine care. Conclusions: Preparing for a surge of critically ill patients during a pandemic can be a daunting task. The implementation of a coordinated, system-level approach can help with the allocation of resources as needed. Focusing on established strengths of hospitals within the system can guide triage based on individual patient needs. The management of ECMO patients is still a specialty care, and a systematic and hospital based approach requiring an ECMO team composed of multiple experienced individuals is paramount during a respiratory viral pandemic.

Pursuing Excellence: Integrating Clinical Learning Environment Staff and Learners Into the Pursuit of Quality, Safety, Equity, and Value

<i>Pursuing Excellence</i>: Integrating Clinical Learning Environment Staff and Learners Into the Pursuit of Quality, Safety, Equity, and Value

Implications of STAMP for Warhead Safety at AWE

STAMP (System-Theoretic Accident Model and Processes) is a relatively new approach to safety assessment methodology and post-accident cause analysis; its prime developer is Nancy Leveson of MIT. STAMP is a holistic system-level approach to overall organizational structure and to technical operations and design. It takes a comprehensive look at all possible organizational and technical system influences that can ultimately affect the safety of technical processes and product designs in whatever scenarios or environments in which they operate or to which they are subjected. Of course, the process can be applied equally to both reliability of performance and security, in addition to safety.

Outcomes of a Specialized Clinic on Rates of Investigation and Treatment of Primary Aldosteronism

Primary aldosteronism (PA) is one of the most common causes of secondary hypertension but remains largely unrecognized and untreated. To understand the outcomes of a specialized clinic on rates of evaluation and treatment of PA in the context of secondary factors. This population-based cohort study was conducted in Alberta, Canada, using linked administrative data between April 1, 2012, and July 31, 2019, on adults identified as having hypertension. We evaluated each step of the diagnostic and care pathway for PA to determine the proportion of people with hypertension who received screening, subtyping, and targeted treatment for PA. Variations in diagnosis and treatment were examined according to individual-level, clinician-level, and system-level characteristics. Of the 1.1 million adults with hypertension, 7941 people (0.7%) were screened for PA. Among those who were screened, 1703 (21.4%) had positive test results consistent with possible PA, and 1005 (59.0%) of these were further investigated to distinguish between unilateral and bilateral forms of PA. Only 731 individuals (42.9%) with a positive screen result received disease-targeted treatment. Geographic zones and clinician specialty were the strongest determinants of screening, subtyping, and treatment of PA, with the highest rates corresponding to the location of the provincial endocrine hypertension program. In this cohort, less than 1% of patients expected to have PA were ever formally diagnosed and treated. These findings suggest that a system-level approach to assist with investigation and treatment of PA may be highly effective in closing care gaps and improving clinical outcomes.

Have They Already Emerged? Mapping the Population of National Interest Organisations in Post-Communist Poland

While political parties provide a key channel for political representation, organised interests can also be an important mechanism. A valid question is whether a system of interest groups is capable of ensuring the representation of a variety of public and private interests. Addressing this conundrum requires data that map the essential traits of organised interest groups in a given country, including their number (density) and types (diversity). This article explores the density and composition of the Polish system of organised interests. The previously unexplored system-level approach delivers insights into the nature of the system and also provides a framework for the subsequent conceptualisation of advocacy and lobbying dynamics.

Rapid Expansion of the Airway Response Team to Meet the Needs of the COVID-19 Pandemic.

ABSTRACTIntroduction:The COVID-19 pandemic has brought unprecedented numbers of patients with acute respiratory distress to medical centers. Hospital systems require rapid adaptation to respond to the increased demand for airway management while ensuring high quality patient care and provider safety. There is limited literature detailing successful system-level approaches to adapt to the surge of COVID-19 patients requiring airway management.Methods:A deliberate system-level approach was used to expand a preexisting airway response service. Through a needs analysis (taking into account both existing resources and anticipated demands), we established priorities and solutions for the airway management challenges encountered during the pandemic.Results:During our COVID-19 surge (March 10, 2020, through May 26, 2020), there were 619 airway consults, and the COVID airway response team (CART) performed 341 intubations. Despite a 4-fold increase in intubations during the surge, there was no increase in cardiac arrests or surgical airways and no documented COVID-19 infections among the CART.Conclusions:Our system-level approach successfully met the sudden escalation in demand in airway management incurred by the COVID-19 surge. The approach that addressed staffing needs prioritized provider protection and enhanced quality and safety monitoring may be adaptable to other institutions.

Beyond targeted searches: the need for system-level approaches to understanding the connection between astrochemistry and the emergence of life

Beyond targeted searches: the need for system-level approaches to understanding the connection between astrochemistry and the emergence of life

Analysis of Dynamic Wireless Power Transfer Systems Based on Behavioral Modeling of Mutual Inductance

This paper proposes a system-level approach suitable to analyze the performance of a dynamic Wireless Power Transfer System (WPTS) for electric vehicles, accounting for the uncertainty in the vehicle trajectory. The key-point of the approach is the use of an analytical behavioral model that relates mutual inductance between the coil pair to their relative positions along the actual vehicle trajectory. The behavioral model is derived from a limited training data set of simulations, by using a multi-objective genetic programming algorithm, and is validated against experimental data, taken from a real dynamic WPTS. This approach avoids the massive use of computationally expensive 3D finite element simulations, that would be required if this analysis were performed by means of look-up tables. This analytical model is here embedded into a system-level circuital model of the entire WPTS, thus allowing a fast and accurate analysis of the sensitivity of the performance as the actual vehicle trajectory deviates from the nominal one. The system-level analysis is eventually performed to assess the sensitivity of the power and efficiency of the WPTS to the vehicle misalignment from the nominal trajectory during the dynamic charging process.

A system level approach to estimate maximum load steps that can be applied on a fuel cell powered marine DC system

This paper presents a system level approach to estimate the maximum load steps on a hydrogen fuel cell powered marine system. In the proposed approach, a model has been developed to predict the system distribution voltage drop due to sudden load changes applied on the system. The estimated voltage drop is used as a metric to determine if a system can sustain the applied load change. Such technique is beneficial for system engineers in the early stage of marine system design and dimensioning. Additionally, the model can be used by a power management system to coordinate starting and stopping of fuel cells for improved system performance. In this work, the proposed approach is validated using a real-time hardware-in-loop simulation platform and it is demonstrated that the proposed approach is accurate within 1.2%.

Optimization-based Component Sizing Method for Electrified Heavy-Duty Powertrain Concepts

The demand for battery-powered, exhaust emission-free mobile machinery is increasing. However, the high energy requirements of mobile machines result in large, heavy and expensive battery storage systems. Driven by continuously decreasing but still fairly high battery costs battery costs, the efficiency of the drive system is becoming the focus of development activities, even in an industry where robustness, service lifetime, productivity and power density have been the driving factors up to now. Interactions between topology, component sizing, and control strategy require a system-level approach for the development of drive systems. In this paper, a novel optimization-based sizing method for electrified heavy-duty powertrain concepts is presented and applied to subsystems of a wheeled excavator. Scalable component cost and efficiency models are used in a system simulation to calculate objective function values for a multi-objective optimization. The result of the optimization, a trade-off between energy consumption and costs provides the OEM with a decision support in the development process. The modular structure of the approach allows a subsequent extension of the design parameter space as well as the detailing of the models used.

Modeling the immune response to Salmonella during typhoid.

Several facets of the host immune response to Salmonella infection have been studied independently at great depths to understand the progress and pathogenesis of Salmonella infection. The circumstances under which a Salmonella-infected individual succumbs to an active disease, evolves as a persister or clears the infection are not understood in detail. We have adopted a system-level approach to develop a continuous-time mechanistic model. We considered key interactions of the immune system state variables with Salmonella in the mesenteric lymph node to determine the final disease outcome deterministically and exclusively temporally. The model accurately predicts the disease outcomes and immune response trajectories operational during typhoid. The results of the simulation confirm the role of anti-inflammatory (M2) macrophages as a site for persistence and relapsing infection. Global sensitivity analysis highlights the importance of both bacterial and host attributes in influencing the disease outcome. It also illustrates the importance of robust phagocytic and anti-microbial potential of M1 macrophages and dendritic cells (DCs) in controlling the disease. Finally, we propose therapeutic strategies for both antibiotic-sensitive and antibiotic-resistant strains (such as IFN-γ therapy, DC transfer and phagocytic potential stimulation). We also suggest prevention strategies such as improving the humoral response and macrophage carrying capacity, which could complement current vaccination schemes for enhanced efficiency.

Dynamical analysis and effects of law enforcement in a social interaction model

Crime is a rising problem all over the world. Over the years, several researches have been conducted to coin suitable model systems and intervention strategies that would decrease delinquent behavior and promote prosocial development. Being dynamic and complex process, the spread of crime requires a system level approach. In this paper, we formulate and analyze a series of dynamical model systems of the dilation of crime incorporating law enforcement. The population models of social interactions have been constructed based on predator–prey interaction models with Holling type II response function. Two different types of populations (criminal minded and non-criminal minded) have been assumed in the given community/society. According to law policy for crime control, we scrutinize the dynamic behavior of the model system concerning law enforcement on the criminal minded population. Along with analytical expressions for the existence of different equilibrium points and their stability, we have also provided their geometrical interpretations using isocline analysis. The expressions obtained for the existence and stability of equilibrium points have been used to investigate the effects of coefficient of law enforcement and the logistic growth term on the prevalence of crime. It is observed that for a threshold value of law enforcement, a stable limit cycle exists. In particular, a threshold of law enforcement is determined beyond which the associated place/community could be made crime free. A threshold value R0 (similar to basic reproduction number in epidemiology) has also been introduced. It is shown that when R0<1, crime free equilibrium is stable. The elimination and persistence of crime have been discussed via two parameters (law enforcement and half saturation constant) bifurcation diagram. Theoretical results have been supported via numerical simulations followed by discussion and societal impacts of the present study.

Generalised system level approach

Recently, system level approach has been proposed as a novel design tool for large-scale cyber physical systems in the discrete time LTI framework. The main idea of the new paradigm is a shift from constructing and parametrizing the desired optimal controller to the parametrization of the achievable closed loop behaviours (closed loop shape). Then, the controller is synthesised from the system level data in a way that keep the imposed structural constraints intact. In this paper we lift the main idea of the system level parametrization to a general level, that also includes the class of LPV systems. We also provide a general scheme for the realization related to different Möbius transforms which are formulated in terms of the original data and also keep intact the structural information.