Control Models
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Molecules ◽  
2021 ◽  
Vol 26 (18) ◽  
pp. 5459
Piotr Szcześniak ◽  
Barbara Grzeszczyk ◽  
Bartłomiej Furman

An efficient method for the synthesis of nojirimycin- and pyrrolidine-based iminosugar derivatives has been developed. The strategy is based on the partial reduction in sugar-derived lactams by Schwartz’s reagent and tandem stereoselective nucleophilic addition of cyanide or a silyl enol ether dictated by Woerpel’s or diffusion control models, which affords amino-modified iminosugars, such as ADMDP or higher nojirimycin derivatives.

Jianqiang Hu ◽  
Jinde Cao

Demand response flexible loads can provide fast regulation and ancillary services as reserve capacity in power systems. This paper proposes a joint optimization dispatch control strategy for source-load system with stochastic renewable power injection and flexible thermostatically controlled loads (TCLs) and plug-in electric vehicles (PEVs). Specifically, the optimization model is characterized by a chance constraint look-ahead programming to maximal the social welfare of both units and load agents. By solving the chance constraint optimization with sample average approximation (SAA) method, the optimal power scheduling for units and TCL/PEV agents can be obtained. Secondly, two demand response control algorithms for TCLs and PEVs are proposed respectively based on the aggregate control models of the load agents. The TCLs are controlled by its temperature setpoints and PEVs are controlled by its charging power such that the DR control objective can be fulfilled. The effectiveness of the proposed dispatch and control algorithm has been demonstrated by the simulation studies on a modified IEEE 39 bus system with a wind farm, a photovoltaic power station, two TCL agents and two PEV agents.

2021 ◽  
Vol 17 (2) ◽  
pp. 129-143
Nadia Hocine

Telework is an important alternative to work that seeks to enhance employees’ safety and well-being while reducing the company costs. Employees can work anytime, any where and under high mobility conditions using new devices. Therefore, the access control of remote exchanges of Enterprise Content Management systems (ECM) have to take into consideration the diversity of users’ devices and context conditions in a telework open network. Different access control models were proposed in the literature to deal with the dynamic nature of users’ context and devices. However, most access control models rely on a centralized management of permissions by an authorization entity which can reduce its performance with the increase of number of users and requests in an open network. Moreover, they often depend on the administrator’s intervention to add new devices’ authorization and to set permissions on resources. In this paper, we suggest a distributed management of access control for telework open networks that focuses on an agent-based access control framework. The framework uses a multi-level rule engine to dynamically generate policies. We conducted a usability test and an experiment to evaluate the security performance of the proposed framework. The result of the experiment shows that the ability to resist deny of service attacks over time increased in the proposed distributed access control management compared with the centralized approach.

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Xin Su ◽  
Maohua Zhong

Efficient and reasonable supply chain management helps enterprises improve their efficiency, reduce costs, shorten cash flow times, and reduce enterprise risks. Risk prevention and control is a safety symbol for supply chains. To explore different influence degrees of multirisk factors and multilinks on enterprises, we propose a supply chain risk prevention and control model based on a fuzzy influence diagram and Hopfield neural network. Using the model that both calculates the risk size and occurrence probability of the supply chain and allows identifying various risk prevention and control levels, the supply chain risk is evaluated both objectively and fairly. We analyzed the theoretical and practical properties of supply chain risk prevention and control models and used it in the H company to illustrate this model.

2021 ◽  
Tanner Y Jacobson ◽  
Kwangsik Nho ◽  
Shannon Risacher ◽  
Sujuan Gao ◽  
Li Shen ◽  

Introduction: Genetic association analysis of key Alzheimer's disease (AD) endophenotypes may provide insight into molecular mechanisms and genetic contributions. Methods: Major AD endophenotypes based on the A/T/N (Amyloid-beta, Tau, and Neurodegeneration) biomarkers and cognitive performance were selected from Alzheimer's Disease Neuroimaging Initiative (ADNI) in up to 1,565 subjects. Genome-wide association analysis of quantitative phenotypes was performed using a main SNP effect and a SNP by Diagnosis interaction (SNPxDX) model to identify stage specific genetic effects. Results: Sixteen novel or replicated loci were identified in the main effect model, with six (SRSF10, MAPT, XKR3, KIAA1671, ZNF826P, and LOC100507506) meeting study significance thresholds with the A/T/N biomarkers. The SNPxDX model identified three study significant genetic loci (BACH2, EP300, PACRG-AS1) associated with a neuroprotective effect in later AD stage endophenotypes. Discussion: An endophenotype approach identified novel genetic associations and new insights into the associations that may otherwise be missed using conventional case-control models.

Seungmoon Song ◽  
Łukasz Kidziński ◽  
Xue Bin Peng ◽  
Carmichael Ong ◽  
Jennifer Hicks ◽  

AbstractModeling human motor control and predicting how humans will move in novel environments is a grand scientific challenge. Researchers in the fields of biomechanics and motor control have proposed and evaluated motor control models via neuromechanical simulations, which produce physically correct motions of a musculoskeletal model. Typically, researchers have developed control models that encode physiologically plausible motor control hypotheses and compared the resulting simulation behaviors to measurable human motion data. While such plausible control models were able to simulate and explain many basic locomotion behaviors (e.g. walking, running, and climbing stairs), modeling higher layer controls (e.g. processing environment cues, planning long-term motion strategies, and coordinating basic motor skills to navigate in dynamic and complex environments) remains a challenge. Recent advances in deep reinforcement learning lay a foundation for modeling these complex control processes and controlling a diverse repertoire of human movement; however, reinforcement learning has been rarely applied in neuromechanical simulation to model human control. In this paper, we review the current state of neuromechanical simulations, along with the fundamentals of reinforcement learning, as it applies to human locomotion. We also present a scientific competition and accompanying software platform, which we have organized to accelerate the use of reinforcement learning in neuromechanical simulations. This “Learn to Move” competition was an official competition at the NeurIPS conference from 2017 to 2019 and attracted over 1300 teams from around the world. Top teams adapted state-of-the-art deep reinforcement learning techniques and produced motions, such as quick turning and walk-to-stand transitions, that have not been demonstrated before in neuromechanical simulations without utilizing reference motion data. We close with a discussion of future opportunities at the intersection of human movement simulation and reinforcement learning and our plans to extend the Learn to Move competition to further facilitate interdisciplinary collaboration in modeling human motor control for biomechanics and rehabilitation research

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Shila Monazam Ebrahimpour ◽  
Fariborz Rahimnia ◽  
Alireza Pooya ◽  
Morteza Pakdaman

PurposeWorkforce planning must answer how many workforces, in which positions, and talents, and when each organization is needed. To find the requirements workforce, organizations need to know the organizational position and talents pools. Clarifying the number of workforces required in each pool requires attention to workforce flows, including hiring, promotion, degradation, horizontal movement, and exiting the organization. It is a dynamic issue and must be addressed over several periods over a specific duration, which adds to the complexity. According to the talent management presented in this research, all the above complex questions are answered by applying the optimal control (OC) model according to talent management presented in this research.Design/methodology/approachThis research presents a dynamic model by using a linear-quadratic optimal control model, which was solved by Pontryagin's maximum principle, to achieve an optimal number of workforce requirements for each of the positions of nursing services manager, supervisor, head nurses and nurses in the health sector according to the required talents in each position.FindingsThe results have shown that the target value of workforce numbers has been achieved in the planning period, and the validation test and sensitivity analysis justified the model by reaching the workforce planning targets.Originality/valueThis study provides a dynamic model for achieving quantitative workforce planning targets; the model presented in this manuscript has included an important qualitative factor, namely workforce talents. According to the authors' review, there is no comprehensive research devoted to workforce planning through optimal control models by attention to workforces skills.

Actuators ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 184
Peng Hang ◽  
Xinbo Chen

In this paper, the related studies of chassis configurations and control systems for four-wheel independent drive/steering electric vehicles (4WID-4WIS EV) are reviewed and discussed. Firstly, some prototypes and integrated X-by-wire modules of 4WID-4WIS EV are introduced, and the chassis configuration of 4WID-4WIS EV is analyzed. Then, common control models of 4WID-4WIS EV, i.e., the dynamic model, kinematic model, and path tracking model, are summarized. Furthermore, the control frameworks, strategies, and algorithms of 4WID-4WIS EV are introduced and discussed, including the handling of stability control, rollover prevention control, path tracking control and active fault-tolerate control. Finally, with a view towards autonomous driving, some challenges, and perspectives for 4WID-4WIS EV are discussed.

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Kesavan Meganathan ◽  
Ramachandran Prakasam ◽  
Dustin Baldridge ◽  
Paul Gontarz ◽  
Bo Zhang ◽  

Abstract Background Copy number variants (CNVs) linked to genes involved in nervous system development or function are often associated with neuropsychiatric disease. While CNVs involving deletions generally cause severe and highly penetrant patient phenotypes, CNVs leading to duplications tend instead to exhibit widely variable and less penetrant phenotypic expressivity among affected individuals. CNVs located on chromosome 15q13.3 affecting the alpha-7 nicotinic acetylcholine receptor subunit (CHRNA7) gene contribute to multiple neuropsychiatric disorders with highly variable penetrance. However, the basis of such differential penetrance remains uncharacterized. Here, we generated induced pluripotent stem cell (iPSC) models from first-degree relatives with a 15q13.3 duplication and analyzed their cellular phenotypes to uncover a basis for the dissimilar phenotypic expressivity. Results The first-degree relatives studied included a boy with autism and emotional dysregulation (the affected proband-AP) and his clinically unaffected mother (UM), with comparison to unrelated control models lacking this duplication. Potential contributors to neuropsychiatric impairment were modeled in iPSC-derived cortical excitatory and inhibitory neurons. The AP-derived model uniquely exhibited disruptions of cellular physiology and neurodevelopment not observed in either the UM or unrelated controls. These included enhanced neural progenitor proliferation but impaired neuronal differentiation, maturation, and migration, and increased endoplasmic reticulum (ER) stress. Both the neuronal migration deficit and elevated ER stress could be selectively rescued by different pharmacologic agents. Neuronal gene expression was also dysregulated in the AP, including reduced expression of genes related to behavior, psychological disorders, neuritogenesis, neuronal migration, and Wnt, axonal guidance, and GABA receptor signaling. The UM model instead exhibited upregulated expression of genes in many of these same pathways, suggesting that molecular compensation could have contributed to the lack of neurodevelopmental phenotypes in this model. However, both AP- and UM-derived neurons exhibited shared alterations of neuronal function, including increased action potential firing and elevated cholinergic activity, consistent with increased homomeric CHRNA7 channel activity. Conclusions These data define both diagnosis-associated cellular phenotypes and shared functional anomalies related to CHRNA7 duplication that may contribute to variable phenotypic penetrance in individuals with 15q13.3 duplication. The capacity for pharmacological agents to rescue some neurodevelopmental anomalies associated with diagnosis suggests avenues for intervention for carriers of this duplication and other CNVs that cause related disorders.

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