Poor Flexibility Research Articles

Flexible highly-sensitive pressure sensor based on rGO/Fe nanowires composites for wearable human health detection

Flexible pressure sensors applied in wearable detection often face challenges, such as low sensitivity, large device size, poor flexibility, and long response time. This study aims to design and develop high-performance pressure-sensitive materials for wearable human detection applications. Using a sensitive layer composite and microstructural design, rGO/Fe nanowires (NWs) composites were proposed as the pressure-sensitive material. This approach yields a compact sensor with high flexibility, good mechanical properties, and excellent sensing performance. Firstly, rGO/Fe NWs composites were prepared by the Hummers method and an in situ reduction technique under a magnetic field. Secondly, the structural design, component construction, and sensing mechanism of the sensors were thoroughly investigated. Finally, the performance of the flexible pressure sensor was tested, and its application in the wearable field was explored. The results demonstrate that the sensor exhibits excellent performance with a good response to both large and small pressures within the range of 0–30 kPa, providing an effective method for wearable human health detection.

Reversible Antireflection Materials Inspired by Cicada Wings for Anticounterfeit and Photovoltaic Cells.

Antireflection (AR) surfaces are essential for the fields of flexible displays, photovoltaic industry, medical endoscope, intelligent windows, etc. Although natural creatures with well-organized micro/nanostructures have provided some coupling design principles for the rapid development of bioinspired AR materials, the mechanical vulnerability, poor flexibility, and nonadjustability have been pointed out as the drawback of these nanostructures. Here, a bioinspired reversible AR film with 4% reflectivity, 90% transmittance, and 9% haze in broadband (400-900 nm) was prepared. The flexible switching of AR performance enhancement and weakening throughout the visible wavelength band has been achieved by controlling the reversible change in the morphology of the interface structure. A variety of patterned film samples can be obtained by simply changing the template, which can be used in intelligent identification fields such as anticounterfeiting. The cycle test and photoelectric test show that the bionic reversible antireflection structure has certain stability and can effectively reduce the loss of photovoltaic cell conversion efficiency caused by mechanical deformation. It has broad application prospects in the fields of anticounterfeiting, intelligent window, flexible display, photoelectric element, and so on.

A Facile Method in Fabricating Flexible Conductive Composites with Large-Size Segregated Structures for Electromagnetic Interference Shielding.

To resist the plastic deformation of polymer particles during hot press molding, high molecular weights, and moduli are required for composites with segregated structures, thus the prepared composites exhibit poor flexibility. Also, larger particle sizes can bring lower percolation thresholds while the ensuing greater deformation destroys the conductive network. Moreover, segregated composites still face preparation complexities. Herein, a facile method for developing flexible composites with large-size segregated structures is proposed. First, silver-coated polydopamine-modified reduced graphene oxide (Ag@PrGO), as conductive fillers, is prepared by electroless plating. Next, polydimethylsiloxane (PDMS)-coated polyolefin elastomer (POE) beads are put into a bag containing the fillers. After a simple shaking, the fillers are adhered to the POE surface as the cohesive property of cured PDMS. Finally, flexible composites with large-size segregated structures are obtained via hot pressing. Benefiting from the 2D structure of the Ag@PrGO and the ability to slip, the conductive networks possess adaptable deformability. The prepared composites exhibit excellent electrical conductivity (203.55 Scm-1) at filler volume fractions of 3.4 vol%. The EMI shielding effectiveness can reach 70dB in the X-band at a thickness of 1.9mm and remains stable after bending and rubbing damage. This work paves the way for constructing large-size segregated structures.

Optimizing secure multimedia communication in embedded systems a parallel convolutional neural network approach to RIS and D2D resource allocation

With the rapid development of Internet of Things (IoT) services, technologies that leverage multimedia computer communication for information sharing in embedded systems have become a research focus. To address the challenges of low spectral efficiency and poor network flexibility in multimedia computer communications, this paper proposes a resource allocation scheme based on parallel Convolutional Neural Network (CNN). The scheme optimizes the base station beamforming vector and the Reconfigurable Intelligent Surface (RIS) phase shifts to maximize the secure transmission rate for cellular users (CUs), while ensuring normal and secure communication for device-to-device (D2D) users. First, to mitigate interference caused by D2D users reusing CU spectrum resources, the RIS phase shifts and beamforming vectors are optimized to suppress interference and enhance system secrecy rates. Second, to maximize the CU secrecy rate, the paper proposes a parallel CNN-based resource allocation model that considers base station transmission power, RIS reflection coefficients, and D2D communication rate constraints, incorporating multi-scale residual modules in the convolutional layers of the model. Simulation results demonstrate that the proposed CNN-based resource allocation scheme significantly improves the secrecy rate of embedded system communications, ensuring secure multimedia computing, and outperforms traditional methods.

Work-related musculoskeletal disorder and health risk behaviors in market-vendors: a mixed-methods study.

Work-related musculoskeletal disorders (WRMDs) are frequently observed among market vendors, and engaging in health risk behaviors can exacerbate these issues, leading to various health problems. Common health risk behaviors among market vendors include alcohol consumption and insufficient physical activity. However, there is currently a lack of research examining the prevalence of WRMDs and health risk behaviors among market vendors in Bangkok. Furthermore, the emerging trend of drug misuse within this group remains poorly understood. This study aims to explore the prevalence of muscle pain and flexibility issues and assess health risk behaviors, including alcohol consumption, inadequate exercise, and drug misuse, among market vendors. A mixed-method study was undertaken among 213 market vendors in Bangkok. Data collection utilized direct observation techniques, questionnaires, and muscle flexibility tests. Qualitative data were elucidated and showcased through textual descriptions and quotations. Quantitative data were analyzed using descriptive statistics to present numerical and percentage values. Qualitative findings revealed that market vendors often engage in static muscular work and maintain awkward postures due to their job characteristics and workstation setups. Quantitatively, the right arm was the most common pain region (34.7%), followed by the left leg (31.0%), right leg (30.0%), and left arm (28.6%). Additionally, 64.3% of participants showed poor muscle flexibility. The study also found that 35% of market vendors resorted to alcohol and 11.7% to drug misuse to cope with fatigue and prevent adverse symptoms. Moreover, 68.5% of participants reported no regular exercise due to lack of time. The study highlights the prevalence of musculoskeletal issues among market vendors, largely attributed to static muscular work and awkward postures dictated by their job roles and workstation arrangements. The right arm emerged as the most commonly affected area, followed by the left leg, right leg, and left arm, with significant rates of reported pain. The research also points to a notable lack of muscle flexibility in a majority of vendors and a concerning tendency towards alcohol and drug misuse as coping mechanisms for fatigue and symptom management. Furthermore, a significant portion of the vendors do not participate in regular exercise, primarily due to time constraints. These findings can be used to implement health prevention programs within the market vendor group.

Fabrication of a ZIF-8/PVA Membrane on PVDF Fiber by Spray for the Highly Efficient Separation of Oil-in-Water Emulsions.

In human life and production, excessive oily wastewaters containing detergents are produced and discharged, causing severe environmental pollution and water resource problems. A metal-organic framework (MOF)-based membrane is an economical and environmentally friendly tool for emulsion separation but is limited by a complex preparation process and poor flexibility. Herein, we developed a simple method to synthesize a MOF-based mixed-matrix membrane (MMM) by spray and fabricated the membrane on poly(vinylidene fluoride) (PVDF) fibers via postdeposition and in situ growth manners. The prepared ZIF-8/PVA MMMs have uniform distribution of ZIF-8 particles and poly(vinyl alcohol) (PVA) on the PVDF fibers. PVA improved the adhesion between the ZIF-8 particles and between the MOF layer and PVDF fiber, endowing the separation membrane with high flexibility and bendability. The prepared ZIF-8/PVA membrane exhibited hydrophilicity and underwater superoleophobicity, which showed high separation efficiency and considerable water flux for emulsions, emulsion containing dye, and surfactant-stabilized emulsion. In addition, the fabricated ZIF-8/PVA/PVDF fibers exhibited good antifouling property and flexibility and can maintain stable separation efficiency after working several times and even under bending, demonstrating the stability and potentiality of the ZIF-8/PVA/PVDF fibers in practical applications. This work paves a new avenue for the synthesis and application of MOF-based MMMs.

A new approach to multiaxial fatigue life prediction: A multi-dimensional multi-scale composite neural network with multi-depth

Many multiaxial fatigue life prediction methods tend to increase additional parameters and model depth as the complexity of the loading path increases. This leads to issues such as poor model robustness, limited flexibility, and single-dimensional approaches. In this study, a multi-dimensional multi-scale composite neural network with multi-depth is proposed to address these challenges and enhance prediction accuracy. Initially, physical and sensitive features serve as input data for the proposed model, to enhance the richness of input features. Subsequently, a multi-dimensional feature extraction module is deployed to extract feature information from the composite data. To process these features, an improved multi-domain query cascaded transformer network (IMQCT) is employed as the feature processing module of the proposed model. The proposed model is verified to have better prediction accuracy and extrapolation capability by using experimental data from nine materials and comparing its performance with six machine learning models.

Phytic acid-based super antifreeze multifunctional conductive hydrogel for human motion monitoring and energy harvesting devices

Conductive hydrogels have broad application prospects in the field of self-powered sensors and energy harvesting devices due to their good electrical conductivity and flexibility. However, at low temperatures, conductive hydrogels are usually frozen, resulting in problems such as poor electrical conductivity and flexibility, which seriously hinder the application of these fields. To address these challenges, phytic acid (PA) was employed as the crosslinker and antifreezing agent in this study. Polyvinyl alcohol (PVA), 2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS), chitosan (CS), and PA were used as raw materials to successfully synthesize PVA/AMPS/CS/PA (PACP) multifunctional conductive hydrogels with outstanding antifreeze and water retention properties (freezing point below −80 °C, 30-day water loss rate of 3.5%). In addition, PACP hydrogels exhibit exceptional electrical conductivity of up to 9.4 S/m, along with antibacterial and biocompatible properties, enabling their utilization as wearable sensors on human skin tissue. Notably, the PACP hydrogel-based triboelectric nanogenerator (PACP-TENG) excels in accurately monitoring human motion and powering small electronic devices, facilitating remote control of small light switches. The resulting open circuit voltage is as high as 314 V at 25 °C and about 110 V at low temperature. Therefore, PACP hydrogels with excellent properties are expected to expand their applications in these fields.

Surgical Treatment Strategies for Severe and Neglected Spinal Deformities in Children and Adolescents without the Use of Radical Three-Column Osteotomies.

Background: Severe spinal deformity manifests as a pronounced deviation from the normal curvature of the spine in the frontal, sagittal, and horizontal planes, where the coronal plane curvature exceeds 90 degrees and may coincide with hyperkyphotic deformity. The most severe deformities exhibit rigidity, with flexibility below 30%. If left untreated or improperly treated, these deformities can result in serious complications associated with progression of the curvature. A combination of surgical techniques is frequently employed to attain optimal outcomes and minimize the risk of complications. The overall medical condition of the patient, their capacity to endure extensive procedures, the expertise of the surgeon, and the resources available all play significant roles in determining the course of management. A systematic and thorough review of the relevant literature was conducted utilizing a variety of electronic databases. The primary objective of this study was to scrutinize the surgical techniques commonly employed in complex spine surgeries for the management of severe scoliosis without resection vertebral body techniques, with higher potential risk of major complications, including permanent neurological deficit. Conclusions: Halo-gravity traction, halo femoral traction, and all techniques for releases of the spine (anterior, posterior, or combine), as well as thoracoplasty, have demonstrated significant effectiveness in managing severe and rigid idiopathic scoliosis. The combination of several of these methods can lead to optimal alignment correction without the need to perform high-risk techniques involving three-column osteotomies. Surgeons must customize the indications based on factors such as available resources, characteristics of the deformity, and the patient's individual profile. Surgical correction of severe scoliosis without vertebral body resection surgeries decreases the potential risks related to neurological and pulmonary complications while providing significant clinical improvement outcomes. The powerful Ponte osteotomy is indicated for severe scoliosis, curves with poor flexibility, for better restoration of hypokyphosis, and decrease of hyperkyphosis. These corrective techniques combined with HGT or temporary internal distraction rods are recommended as viable options for managing individuals with severe rigid spine deformity characteristics. Therefore, they also should be considered and performed by a proficient surgical team. The presence of neuromonitoring is crucial throughout these procedures.

NUMERICAL INVESTIGATION OF A OMNIDIRECTIONAL BENDING ACTUATOR FOR CLIMBING ANALYSIS

With its good flexibility and adaptability to the environment, soft robot has been attached great importance by the majority of researchers in recent years, and is widely used in rehabilitation treatment, flexible grasping and other fields. However, the existing actuators have disadvantages such as single deformation mode, poor flexibility and insufficient environmental adaptability. The reason is that the actuator structure is too simple to meet the complex application scenarios. In this paper, an omnidirectional bending multi-segment soft actuator is proposed, and the parameter analysis and dynamic analysis models are given. Meanwhile, the prestressed modal analysis of the proposed model is carried out to better characterize the dynamic behavior. A numerical study of a climbing motion verifies the novelty and validity of the proposed structure.

Au – MoS2 nanoflowers sensors on interdigitated electrode for monitoring human respiration

Abstract Respiratory humidity sensors are essential for monitoring breath conditions in a variety of applications such as respiratory disease diagnosis, sleep apnea screening, and personalized medicine. With the increasing prevalence of respiratory diseases, such as asthma, chronic obstructive pulmonary disease (COPD), and sleep apnea, they have become essential tools for healthcare professionals, researchers and individuals. However, existing humidity sensors often suffer from poor sensitivity, slow response, and limited flexibility. In this paper, we report a novel Au – MoS2 respiratory humidity sensor that exhibits high resistivity, fast response, and excellent flexibility. The sensor is fabricated by drop casting a thin layer of Au decorated MoS2 on copper interdigitated electrodes (fabricated using copper clad PCB). The increase in the intensity of the peak was observed in Au – MoS2 hybrids in comparison to MoS2 analyzed using micro–Raman Spectroscopy. Using scanning electron microscopy (SEM), the morphology of MoS2 was observed, confirming its flower like structure. The Au nanoparticles were detected on the edges of MoS2, confirmed by transmission electron microscope (TEM).
The interfacial electronic interaction suggests that there is the formation of Schottky barrier between Au and MoS2 as confirmed by X–Ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS). The improved electronic interaction results in better sensing properties. The high dielectric constant and excellent surface-to-volume ratio of the MoS2 layer make it extremely sensitive to humidity; the Au nanoparticles offer good electrical conductivity and mechanical flexibility in its place. The study tested a respiratory sensor in a simulated environment, finding it more responsive to breathing and quick to return to rest. This suggests potential for the Au-MoS2 sensor in tracking breath states due to its sensitivity and adaptability, promising applications across various fields.

Multi-scale control and action recognition based human-robot collaboration framework facing new generation intelligent manufacturing

Facing the new generation intelligent manufacturing, traditional manufacturing models are transitioning towards large-scale customized productions, improving the efficiency and flexibility of complex manufacturing processes. This is crucial for enhancing the stability and core competitiveness of the manufacturing industry, and human-robot collaboration systems are an important means to achieve this goal. At present, mainstream manufacturing human-robot collaboration systems are modeled for specific scenarios and actions, with poor scalability and flexibility, making it difficult to flexibly handle actions beyond the set. Therefore, this article proposes a new human-robot collaboration framework based on action recognition and multi-scale control, designs 27 basic gesture actions for motion control, and constructs a robot control instruction library containing 70 different semantics based on these actions. By integrating static gesture recognition, dynamic action process recognition, and You-Only-Look-Once V5 object recognition and positioning technology, accurate recognition of various control actions has been achieved. The recognition accuracy of 27 types of static control actions has reached 100%, and the dynamic action recognition accuracy of the gearbox assembly process based on lightweight MF-AE-NNOBJ has reached 90%. This provides new ideas for simplifying the complexity of human-robot collaboration problems, improving system accuracy, efficiency, and stability.

Broadband Near-Infrared Light Excitation Generates Long-Lived Near-Infrared Luminescence in Gallates.

Persistent luminescence describes the phenomenon whereby luminescence remains after the stoppage of excitation. Recently, upconversion persistent luminescence (UCPL) phosphors that can be directly charged by near-infrared (NIR) light have gained considerable attention due to their promising applications ranging from photonics to biomedicine. However, current lanthanide-based UCPL phosphors show small absorption cross sections and low upconversion charging efficiency. The development of UCPL phosphors faces challenges due to the lack of flexible upconversion charging pathways and poor design flexibility. Herein, we discovered a lattice defect-mediated broadband photon upconversion process and the accompanying NIR-to-NIR UCPL in Cr-doped zinc gallate nanoparticles. The zinc gallate nanoparticles can be directly activated by broadband NIR light in the 700-1000 nm range to produce persistent luminescence at about 700 nm, which is also readily enhanced by rationally tailoring the lattice defects in the phosphors. This proposed UCPL phosphor achieved a signal-to-background ratio of over 200 in bioimaging by efficiently avoiding interference from autofluorescence and light scattering. Our work reported a lattice defect-mediated photon upconversion phenomenon, which significantly expands the horizons for the flexible design of UCPL phosphors toward broad applications ranging from bioimaging to photocatalysis.

Percolation network and piezoresistive properties of ultraductile cementitious monitoring coating with A-POSS modified carbon-based nanoconductors

Conventional cement-based sensors are large and often embedded in cast-in-place concrete structures, resulting in poor flexibility, low sensing accuracy, and inability to be replaced after damage. This paper reports a promising health monitoring technology, namely the composite coated sensor (sensing skin) prepared by anionic waterborne polyurethane (WPU)-modified cement, in which N-(2-aminoethyl)-3-amino propyl trime thoxy silane (NAEAPTMS) silsesquioxane modified ettringite (A-POSS) acts as a core modifier. The results showed that a continuous interpenetration polymer network was formed between the WPU and the cement, which greatly improved the crack resistance and balanced the polarisation reaction field. The agglomerated GO-CNT particles self-dispersed into micron/nanometer-sized particles under the co-precipitation of Ca2+/Al3+ and the semi-cage-like POSS structure formed by NAEAPTMS, using AFt as the supporting skeleton. The toughness and bond strength of the sensing skins were improved in the presence of A-POSS and, in particular, the maximum deflection angle exceeded 110°. Meanwhile, the electrical resistivity was reduced by more than 2 orders of magnitude. The effective conductivity inside and outside the interface can be precisely delineated when GO-CNT was perfectly arranged inside WPU-CEMENT. The agreement between the theoretical and experimental results of effective conductivity indicates that the sensing skin had a percolation network with imperfect and tunnel-assisted interfaces. The synergistic effect of WPU and A-POSS gave the sensing skin excellent performance of high sensitivity (80 times larger than strain gauges), low relaxation time (50 ms), and monitoring stability.

The effect of polylactic acid-based blend films modified with various biodegradable polymers on the preservation of strawberries

Polylactic acid (PLA) has garnered much attention in the field of fruit and vegetable packaging. Despite its poor flexibility and water resistance, PLA film faces challenges in being used for strawberry storage and freshness preservation due to its inability to maintain flavor quality. In this study, a series of PLA-based modified films was produced by melt blending and extrusion cast processing with PLA as the main component, along with flexible biodegradable polyesters or polycarbonate as the secondary component. First, five different biodegradable polymers were used to investigate the effect of the flexibility and barrier properties of different dispersed phases on the morphology, mechanical properties, and water vapor barrier of PLA-based blend films. Next, the impact on the freshness of strawberries was assessed through examination of fruit color and weight, as well as the levels of O2 and CO2 in the packaging bags. The results showed that the size of the dispersed phase and interfacial bonding with PLA were the key factors determining the mechanical and barrier properties of the blend films. The PLA-polycaprolactone (PCL) blend showed the best compatibility among them, with PCL having the smallest dispersion size (D=0.58 µm), higher toughness than the other four PLA blends, and greater enhancement of PLA. Additionally, it exhibited a similar rate of quality loss in strawberry preservation compared to commercial PE. As a result, the color and luster were more completely preserved. The results of this study may help the future development of degradable plastics, to reduce environmental pollution.

Bioinspired carbon black deposited polyimide fabric for sustainable water energy harvesting

Water is the source of life and the largest energy carrier on Earth. Various excellent hydrovoltaic technologies have been proposed, but still suffer from issues such as intermittent output, material limitations, and poor flexibility. Here, we proposed a method for fabrication of a hydrovoltaic generator using the flexible polyimide fabric. Carbon black was deposited on the polyimide fabric surface using a simple method of candle flame burning. On the basis of water transport in the fabric and charge separation induced by negatively charged carbon black channels, sustainable hydrovoltaic power generation was achieved by the generator. A single carbon deposited polyimide fabric (CBP) could generate a continuous voltage output of nearly 260 mV by dripping a water drop on one side. Multiple CBP devices were connected in series and parallel to increase output power, which could be applied for the power and energy storage of small electronic devices. This work may provide a convenient strategy for fabricating sustainable flexible hydrovoltaic generators and offer insights for the development of clean power sources.

Development of High Performance Thermoelectric Polymers via Doping or Dedoping Engineering.

It is of great significance to develop high-performance thermoelectric (TE) materials, because they can be used to harvest waste heat into electricity and there is abundant waste heat on earth. The conventional TE materials are inorganic semimetals or semiconductors like Bi2Te3 and its derivatives. However, they have problems of high cost, scarce/toxic elements, high thermal conductivity, and poor mechanical flexibility. Organic TE materials emerged as the next-generation TE materials because of their merits including solution processability, low cost, abundant element, low intrinsic thermal conductivity, and high mechanical flexibility. Organic TE materials are mainly conducting polymers because of their high conductivity. Both the conductivity and Seebeck coefficient depend on the doping level, and they are interdependent. Hence, the TE properties of polymers can be improved through doping/dedoping engineering. There are three types of doping forms, oxidative (or reductive) doping, protonic acid doping, and charge transfer doping. Accordingly, they can be dedoped by different approaches. In this article, we review the methods to dope and dedope p-type and n-type TE polymers and the combination of doping and dedoping to optimize their TE properties. Secondary doping is also covered, since it can significantly enhance the conductivity of some TE polymers.

Design of Human–Computer Interaction Gesture Recognition System Based on a Flexible Biosensor

The continuous development of high-speed Internet technology has made the application of robots increasingly widespread. Current robots and human–computer interaction systems mostly use rigid materials, such as metals and semiconductors, which have limitations in terms of deformability and flexibility. In addition, the biocompatibility and user comfort of these materials are also an issue. Therefore, research into new flexible biosensors is essential to improve the flexibility, comfort, and interactivity of these systems. This research will select polymer hydrogel as the electrode material of the sensor and polydimethylsiloxane as the base material of the sensor to design a resistance flexible biosensor to solve the poor flexibility. The research will use a template-matching method to verify the feasibility of gesture recognition of the flexible sensor. The remote control system of the robot finger is designed by a proportional-integral differential controller tuned by aradial basis function neural network. The feasibility of the research system is verified by simulation and scene experiments. The flexible sensor studied and prepared had a sensitivity of 0.7269, a tensile limit of 300%, and a thickness of 0.16 mm, showing good sensitivity and stability. The recognition accuracy of the sensor designed in the study was 92.8%, which was 8.1% higher than that of the data glove. Compared with traditional proportional-integral derivative (PID) controllers, the improved controller system error was within 10 to 3 rad, which had better adaptability and stability. Key information includes the design method of the flexible biosensor, its high sensitivity and stability under multiple stretches, and the proposal and validation of a new RBFNN–PID control model. These results showed that using this new sensor and control model significantly improved the control accuracy of mechanical fingers and the effect of gesture recognition. These results have important implications for the development of more advanced human–computer interaction systems. They not only improve the performance and reliability of the system, but also improve the user's interactive experience. These technologies are particularly promising in the fields of prosthetics for disabled people, advanced game controllers, and remotely controlled robots operating in hazardous environments. The research results are expected to lead to the development of advanced prosthetics, augmented reality devices, advanced game controllers, and automated robots. The main contribution of the research is to design a resistive flexible biosensor, which improves the traditional sensor's poor flexibility and large size and improves the sensor's ability to sense small changes. Future research may focus on further improving the sensor's long-term stability and performance under a variety of environmental conditions. In addition, commercializing these technologies and making them universal is also an important direction for the future.

Hierarchical Coordinated Predictive Control of Multiagent Systems for Process Industries

Focusing on the requirements for efficient and accurate control in large-scale process industries with integrated “distributed-decentralized” characteristics, a novel hierarchical coordinated predictive control strategy for process industries is proposed with a multiagent system as the computational paradigm. This approach comprehensively considers the overall state of the system, the interactions of control actions among agents, the constraints of processes and energy consumption to solve the problems of poor flexibility of agent decision-making in the narrow consensus strategy and strong interaction of parts of the system. The proposed hierarchical control strategy requires each agent to perform three tasks at each time step. First, each agent iteratively obtains a consistent basis for closed-loop prediction in a distributed way. Then, each agent independently proposes a control scheme and determines its own priority by playing games based on the economic performance of the scheme. Next, each agent calculates its own optimal dynamic predictive control sequence in order of priority based on the system’s dynamic process model. Finally, by considering the temperature-control process of heating an alumina ceramic block in a high-power microwave reactor with six microwave sources, the effectiveness of the proposed hierarchical coordinated predictive control strategy is verified under different communication topologies by comparing it with the centralized model predictive control strategy.

No Evidence for Cross-Sectional or Longitudinal Associations between Cognitive Flexibility Performances and Nutritional Status in a Cohort of Inpatients with Anorexia Nervosa.

According to the Cognitive-Interpersonal model of anorexia nervosa (AN), the combined influence of cognitive and socio-emotional difficulties would constitute vulnerability and maintaining factors. Poor cognitive flexibility is one of the endophenotypic candidates (i.e., a trait marker) of the disorder, but few studies have examined its association with illness symptom variations, notably weight status. The study aimed to evaluate the relationships between cognitive flexibility performances and nutritional status indices (BMI; body composition) at different times of the disorder. Cross-sectional and longitudinal associations between cognitive flexibility (TAP 2.1) and nutritional status indices, along with anxious and depressive (HAD) and eating disorder (EDE-Q) symptomatology were investigated using univariate and multivariate analyses in a cohort of AN inpatients evaluated at hospital admission (N = 167) and discharge (N = 94). We found no or negligible associations between nutritional status and HAD or EDE-Q scores or cognitive flexibility performances, either cross-sectionally or longitudinally. Cognitive performances did not significantly differ between the AN subtypes. In agreement with the Cognitive-Interpersonal model of AN, cognitive flexibility is independent of nutritional status, as well as the AN subtype. It is also independent of the levels of anxious, depressive, or ED symptomatology. A new therapeutic approach targeting cognitive flexibility and intolerance to change could benefit severely emaciated people with AN, regardless of disease subtype and level of dysphoria.