Flexible Parameters Research Articles

The propagation of hyper-geometric optical soliton waves in plasma dynamics for the integrable Zhanbota-IIA equation

This research utilizes the new auxiliary equation method to investigate solitary wave patterns in the integrable Zhanbota-IIA equation, a model relevant to phenomena like tidal waves and tsunamis. This method simplifies complex nonlinear-coupled partial differential equations into ordinary differential equation through a traveling wave transformation. Previous studies have not achieved such solutions. The main aim is to enhance comprehension of the integrable Zhanbota-IIA equation behavior under various conditions. Prior to this study, there does not exist any study in which such kinds of solutions are discussed by using the new auxiliary equation method. The new auxiliary equation method is utilized to derive analytical solutions for the underlying model equation. These solutions are expressed in the form of hyperbolic, trigonometric, exponential, and rational functions such as dark, bright, periodic, dark–bright, smooth topological with high peaks, dark-singular, bright singular and periodic singular. The key advantage of this method compared to others lies in its capacity to yield more comprehensive solutions with certain flexible parameters. To illustrate the dynamic structures of these solutions, 3D and 2D graphs are employed with suitable parameter values. This study explores soliton behavior and its telecommunication applications, integrating mathematics, computer science, and physics for technological advancements.

Real-Time Orbit Determination of Micro-Nano Satellite Using Robust Adaptive Filtering.

Low-performing GPS receivers, often used in challenging scenarios such as attitude maneuver and attitude rotation, are frequently encountered for micro-nano satellites. To address these challenges, this paper proposes a modified robust adaptive hierarchical filtering algorithm (named IARKF). This algorithm leverages robust adaptive filtering to dynamically adjust the distribution of innovation vectors and employs a fading memory weighted method to estimate measurement noise in real time, thereby enhancing the filter's adaptability to dynamic environments. A segmented adaptive filtering strategy is introduced, allowing for flexible parameter adjustment in different dynamic scenarios. A micro-nano satellite equipped with a miniaturized dual-frequency GPS receiver is employed to demonstrate precise orbit determination capabilities. On-orbit GPS data from the satellite, collected in two specific scenarios-slow rotation and Earth-pointing stabilization-are analyzed to evaluate the proposed algorithm's ability to cope with weak GPS signals and satellite attitude instability as well as to assess the achievable orbit determination accuracy. The results show that, compared to traditional Extended Kalman Filters (EKF) and other improved filtering algorithms, the IARKF performs better in reducing post-fit residuals and improving orbit prediction accuracy, demonstrating its superior robustness. The three-axes orbit determination internal consistency precision can reach the millimeter level. This work explores a feasible approach for achieving high-performance orbit determination in micro-nano satellites.

Calibration and experiments of discrete element flexible model parameters for kiwifruit stalk

A method combining experimental and simulation optimization was used to calibrate parameters to enhance the accuracy of discrete element model parameters during kiwifruit stem separation. First, physical experiments were conducted to determine the intrinsic and contact parameters of kiwifruit stalk. Second, the mechanical parameters of the kiwifruit stalks were determined using three-point bending and shear tests. On this basis, simulation tests were conducted on kiwifruit stalks by combining the Hertz-Mindlin model with a bonding model, and the optimal combination of bonding parameters was confirmed using the bending strength and maximum shear force. Finally, a discrete element model of the kiwifruit was built with the determined bonding parameters and simulated, and the reliability of the model was verified through mechanical tests. The results showed that the density was 867.5 kg/m3, Poisson's ratio was 0.26, the modulus of elasticity was 3.25 × 108 Pa, the recovery coefficient between the fruit stalks and steel parts was 0.365, and the average values of the static and dynamic friction coefficients between the kiwifruit stalks and steel parts were 0.268 and 0.152, respectively. The kiwifruit stem bonding parameters were normal stiffness per unit area kn=7.201×1011 N/m3, shear stiffness per unit area kt=2.379×1011 N/m3, critical normal stress σmax=5.937×108 Pa, critical shear stress tmax = 2.354×109 Pa, and bonded disc radius Rj=0.164 mm. Compared with the results of the mechanical tests, the relative errors of the bending strength and maximum shear of the discrete element model were 2.13% and 2.84%, respectively. The results showed that the discrete element model improves the simulation of the bending and shearing processes of kiwifruit stalks and is capable of characterizing the physical properties of kiwifruit stalks. The results of this study provide a theoretical foundation for the optimal design of end effectors.

Cutting-edge Bioinformatics strategies for synthesizing Cyclotriazadisulfonamide (CADA) analogs in next-Generation HIV therapies

Cyclotriazadisulfonamide (CADA) is a macrocyclic compound known for its unique mechanism in inhibiting HIV infection by downregulating the CD4 T-cell receptor, a crucial entry point for the virus. Unlike other antiretrovirals, CADA exhibits activity against a wide range of HIV strains, as all HIV variants require CD4 binding for infection. Furthermore, CADA has shown a synergistic effect with clinically approved anti-HIV drugs, offering potential for enhanced therapeutic strategies (Vermeire & Schols, [65]). One proposed mechanism for CADA’s inhibition of the CD4 receptor involves blocking the gates of the Sec61 channel, thereby preventing its translocation. However, CADA suffers from poor solubility and bioavailability. To address this, the study aimed to design CADA analogs with improved binding to the Sec61 channel, enhanced bioavailability, and reduced toxicity. The analogs were designed using SeeSAR, with Avogadro and Meeko used for 3D configuration and pseudoatom placement, respectively. AutoDock Vina version 1.2.4 was employed to predict the binding energies of these analogs. Of the 113 analogs designed, 93 demonstrated a more negative binding energy to the Sec61 channel compared to CADA. Structure-binding energy analyses were done to the top-binding analogs to show favorable structural modifications. Enzyme-ligand interactions were analyzed to elucidate the forces contributing to these binding energies. Additionally, 33 of the 113 analogs were deemed bioavailable using a bioavailability criteria specific for macrocycles. Toxicity predictions using PASS Online and StopTox identified analogs JGL023, JGL024, JGL032, and JGL047 as potential drug candidates. Molecular dynamics simulations using Gromacs-2020.4 revealed that JGL023 and JGL032 exhibited the most favorable binding to the Sec61 channel, as determined by evaluating ligand and residue flexibility, compactness, contact frequency, motion pathways, free energy, and other relevant parameters. Synthetic routes for these four analogs were proposed for future studies. The results of this study offer a new perspective on developing drugs to inhibit HIV entry.

Symmetry and Complexity in Gene Association Networks Using the Generalized Correlation Coefficient

High-dimensional gene expression data cause challenges for traditional statistical tools, particularly when dealing with non-linear relationships and outliers. The present study addresses these challenges by employing a generalized correlation coefficient (GCC) that incorporates a flexibility parameter, allowing it to adapt to varying levels of symmetry and asymmetry in the data distribution. This adaptability is crucial for analyzing gene association networks, where the GCC demonstrates advantages over traditional measures such as Kendall, Pearson, and Spearman coefficients. We introduce two novel adaptations of this metric, enhancing its precision and broadening its applicability in the context of complex gene interactions. By applying the GCC to relevance networks, we show how different levels of the flexibility parameter reveal distinct patterns in gene interactions, capturing both linear and non-linear relationships. The maximum likelihood and Spearman-based estimators of the GCC offer a refined approach for disentangling the complexity of biological networks, with potential implications for precision medicine. Our methodology provides a powerful tool for constructing and interpreting relevance networks in biomedicine, supporting advancements in the understanding of biological interactions and healthcare research.

Hole drilling in basalt-reinforced sustainable composites using abrasive waterjet for construction applications

This study aimed to develop, characterize, and optimize abrasive waterjet (AWJ) machining of sustainable basalt fiber-reinforced polymer composites for construction and industrial applications. Dynamic mechanical analysis, thermogravimetric analysis, and X-ray diffraction revealed enhanced thermal stability, increased decomposition temperatures, and improved crystallinity, correlating with improved tensile strength of developed composites. To address drilling-induced damage that can compromise long-term quality and applicability, AWJ drilling parameters were optimized to minimize damage while enhancing material removal rates. A novel quantification method for entry total surface damage (ETD) was implemented to assess machining defects. Results showed that standoff distance significantly influences ETD and exit delamination, while higher water pressure reduces entry damage. Abrasive flow rate primarily affected the material removal rate. FE-SEM analysis revealed microstructural changes in drilled surfaces, including damage zones and matrix fractures specific to AWJ processing. Multi-objective optimization using Genetic Algorithm is performed to enable flexible parameter selection and informed decision making, balancing machining efficiency and minimal damage.

Home-Based HIFT Altered Quality of Life and Health Related Fitness Parameters in Women

The effects of high intensity functional training (HIFT) on health related components of fitness and quality of life were studied in the gym environment, but there has not been any study on examining the effects of HIFT by using bodyweight exercises at home environment on health related components of fitness and quality of life in women. The goal of this research is to examine the effects of home-based bodyweight HIFT on health related components of physical fitness and quality of life in women. Twenty-one recreationally active female participants (age 26.3 ± 3.7 years) were included in the study. After completing the pretest, participants applied HIFT at home with bodyweight exercises three times a week for a duration of eight weeks. Cardiovascular endurance, muscular strength, muscular endurance, flexibility, body composition and quality of life assessments were carried out in both pretest and posttest applications. Significant differences were observed between the pretest and posttest results of cardiovascular endurance (p=0.042), muscular strength (p<0.001), muscular endurance (p<0.001) and flexibility (p=0.001) parameters. No significant difference was observed between the pretest and posttest results of body composition analysis. Significant improvement (p=0.045) was found on the quality of life scale. Home-based bodyweight HIFT altered quality of life in recreationally active women and enhanced health related components of fitness, which could prevent the increase of health-related risk factors caused by inactivity.

A Fuzzy-Logic-Based Approach for Eliminating Interference Lines in Micro Rain Radar (MRR-2)

This research presents a novel fuzzy-logic-based algorithm aimed at detecting and removing interference lines from Micro Rain Radar (MRR-2) data. Interference lines, which are non-meteorological echoes with unknown origins, can severely obscure meteorological signals. Leveraging an understanding of interference line characteristics, such as temporal continuity, we identified and utilized eight key variables to distinguish interference lines from meteorological signals. These variables include radar moments, Doppler spectrum peaks, and the spatial/temporal continuity of Doppler velocity. The algorithm was developed and validated using data from MRR installations at three sites (Seoul, Suwon, and Incheon) in South Korea, from June to September 2021–2023. While there is a slight tendency to eliminate some weak precipitation, results indicate that the algorithm effectively removes interference lines while preserving the majority of genuine precipitation signals, even in complex scenarios where both interference and precipitation signals are present. The developed software, written in Python 3 and available as open-source, outputs in NetCDF4 format, with customizable parameters for user flexibility. This tool offers a significant contribution to the field, facilitating the accurate interpretation of MRR-2 data contaminated by interference.

Flexible Piezoelectric Nanocolumnar Composite Films as Flat-Panel Loudspeakers: Application and Modeling.

Highly anisotropic piezoelectric composites promise to progress electroacoustic devices as a class by combining the advantages of both piezoceramics and polymers. Fundamentally, piezoelectric loudspeakers employ the converse piezoelectric effect to convert electrical to mechanical energy. Quasi-1-3 piezoceramic/polymer composites enable flat-panel loudspeakers that are tunable in elastic modulus, with opportunities for mechanical flexibility, optical transparency, and large-area coverage. Their processing route enables relatively flexible design parameters, such as the particle loading, polymer-matrix modulus, film thickness, film size, and electrode-material stiffness. Alternative processing routes of electric field (E-field) aligned-piezoelectric composites are demonstrated, including using the relaxor ferroelectric lead magnesium niobate-lead titanate (PMN-PT) to enhance the acoustic performance and photocurable resins to accelerate the materials processing. Material properties critical for dielectrophoresis are characterized, and loudspeakers were fabricated based on the optimal processing conditions. Subsequently, electroacoustic characterization explores the effect of loudspeaker size, substrate stiffness, the microphone distance, the piezoceramic material, and the matrix modulus. Finally, finite-element (FE) modeling of the electromechanical behavior validates the natural frequencies and modes shapes of the loudspeakers via the analytical solution and frequency response to electrical and mechanical excitation. Good correspondence between the predicted electroacoustic performance and experimentally validated model is observed.

A New Hybrid Improved Arithmetic Optimization Algorithm for Solving Global and Engineering Optimization Problems

The Arithmetic Optimization Algorithm (AOA) is a novel metaheuristic inspired by mathematical arithmetic operators. Due to its simple structure and flexible parameter adjustment, the AOA has been applied to solve various engineering problems. However, the AOA still faces challenges such as poor exploitation ability and a tendency to fall into local optima, especially in complex, high-dimensional problems. In this paper, we propose a Hybrid Improved Arithmetic Optimization Algorithm (HIAOA) to address the issues of susceptibility to local optima in AOAs. First, grey wolf optimization is incorporated into the AOAs, where the group hunting behavior of GWO allows multiple individuals to perform local searches at the same time, enabling the solution to be more finely tuned and avoiding over-concentration in a particular region, which can improve the exploitation capability of the AOA. Second, at the end of each AOA run, the follower mechanism and the Cauchy mutation operation of the Sparrow Search Algorithm are selected with the same probability and perturbed to enhance the ability of the AOA to escape from the local optimum. The overall performance of the improved algorithm is assessed by selecting 23 benchmark functions and using the Wilcoxon rank-sum test. The results of the HIAOA are compared with other intelligent optimization algorithms. Furthermore, the HIAOA can also solve three engineering design problems successfully, demonstrating its competitiveness. According to the experimental results, the HIAOA has better test results than the comparator.

Dynamic control of elastic wave transmission by a digital metalayer

Piezoelectric materials with shunt circuits have aroused much research interest due to flexible parameter adjustment. However, shunted piezoelectric elements are difficult to respond to the dynamic changes in the whole system due to the absence of autonomous control ability, which constrains their practical applications. Here, we propose a digital metalayer to control the wave energy transmission across different materials in real time. This digital metalayer comprises a stack of multiple piezoelectric lead zirconate titanate (PZT) disks connected with shunt capacitance circuits (SCCs). The external digital control system adjusts the effective acoustic impedance of the PZT disks through digital potentiometers and microprogrammed control unit, thereby enabling digital manipulation of wave transmission. Utilization of optimized SCCs further enhances adjustment accuracy, supporting both negative and positive capacitance values. The experiments demonstrate that this digital metalayer exhibits remarkable performance in controlling wave transmission. Moreover, the distinct variations in transmitted amplitudes, precisely controlled by the digital metalayer, are harnessed as binary signals for information transmission. An image of letters is encoded into a series of amplitude-modulated waves by the digital metalayer and clearly transmitted. The proposed digital metalayer shows great promise for applications in intelligent impedance matching and the real-time modulation systems.

Correlations among flexibility, stiffness, strength and muscle ultrasound parameters in older males afflicted with hamstrings tightness

IntroductionAge-induced inflexibility may lead to significant mobility impairments and declines in well-being. However, the relationship between the structural and mechanical properties of soft tissue and joint extensibility remains unclear. This study aimed to investigate the correlation between flexibility, muscle tendon unit (MTU) stiffness, muscle ultrasound characteristics, muscle strength, and hamstring flexibility prediction in older males with hamstring inflexibility. MethodsA hundred retired old males (mean age: 67.2 ± 4.9 years) participated in this investigation. Muscle ultrasound, flexibility, MTU stiffness, and knee flexors strength were measured in a single visit. ResultsThe results revealed a modest correlation between straight leg raise (SLR) and biceps femoris fascicle length (FL) elongation (r = 0.222), MTU stiffness (r = -0.401), and eccentric strength (r = 0.219) (all p < 0.05). MTU stiffness, eccentric strength, and FL elongation collectively explained 24.8% of the variance in SLR prediction, while deep fascia thickness predicted MTU stiffness with a variance of 6.4%. ConclusionIn summary, increased SLR was associated with lower MTU stiffness, lengthened FL, and higher eccentric strength. SLR was primarily predicted by MTU stiffness, with lesser contributions from FL elongation and knee flexor eccentric strength in older males experiencing hamstring tightness.

Past and Present of Social Inequality: Analysing Structure and Future Trends

The purpose of the article is to highlight the peculiarities of fundamental and applied forms of social inequality in the context of cultural and historical experience and prospects of civilisational development. Social differentiation has a diverse character, which forms the diversity of parameters of this socio-cultural phenomenon. The purpose of scientific research is to unify social indicators that activate and determine the level of inequality in society. Social processes are marked by contradictions in the worldview and mental understanding, so the issue of inequality is regulated by clear and understandable theoretical, methodological, legal, and socio-cultural guidelines. The research methodology is focused on the scientific and sociological methodological cluster. A sociological study based on content analysis, monitoring, and expert opinions allows us to determine the structure and manifestations of social inequality. Long-term sociological observations and in-depth analytical descriptions form the constants of the fundamental nature of social inequality. The results of the study emphasise the need to correlate the fundamental understanding of social inequality and the applied manifestation of this phenomenon in the socio-cultural space. In today's dynamic world, traditional and sustainable interpretations of inequality are hardly accepted, since the current principles of social development involve rapid permanent changes that determine the parameters of social inequality almost online. Under such conditions, society needs new flexible parameters that will determine the quantitative and qualitative parameters of social inequality. Thus, social inequality is an integral element of cultural and historical experience, having formed the fundamental dimensions of this phenomenon, while its prospects require regulation by society to avoid and mitigate the negative impact of social inequality in the form of injustice, discrimination, chauvinism, etc. Promising areas of research on the problem of social inequality include focusing on the dynamics of the social structure, which fundamentally changes the fundamental and targeted understanding of social inequality, leading to inadequate assessments of threats associated with the direct manifestation of social inequality in society.

Predictive modeling of flexible EHD pumps using Kolmogorov–Arnold Networks

We present a novel approach to predicting the pressure and flow rate of flexible electrohydrodynamic pumps using the Kolmogorov–Arnold Network. Inspired by the Kolmogorov–Arnold representation theorem, KAN replaces fixed activation functions with learnable spline-based activation functions, enabling it to approximate complex nonlinear functions more effectively than traditional models like Multi-Layer Perceptron and Random Forest. We evaluated KAN on a dataset of flexible EHD pump parameters and compared its performance against RF, and MLP models. KAN achieved superior predictive accuracy, with Mean Squared Errors of 12.186 and 0.012 for pressure and flow rate predictions, respectively. The symbolic formulas extracted from KAN provided insights into the nonlinear relationships between input parameters and pump performance. These findings demonstrate that KAN offers exceptional accuracy and interpretability, making it a promising alternative for predictive modeling in electrohydrodynamic pumping.

Quantifying the operational flexibility and invocation costs of urban regional integrated energy systems for participation in demand response programs

As a typical aggregation platform, the regional integrated energy system (RIES) is required to pre-submit its flexibility for each time period when participating in demand response. However, existing studies fail to quantify the flexibility parameters necessary for RIES pre-reporting. Therefore, this paper introduces a flexibility quantification framework tailored for RIES engagement in demand response. The core principle of the framework is grounded in the RIES day-ahead dispatch model considering virtual energy storage, which transforms the flexibility quantification problem into dispatch optimization problems under baseline scenarios and flexibility invocation scenarios. In the flexibility invocation scenario, a control term is incorporated into the objective function to steer the system towards fulfilling flexibility requirements in the most economical strategy. The deviation of power and operating costs in both scenarios defines the system's flexibility and flexibility invocation cost, respectively. This framework holds broad applicability across various aggregation platforms and can measure flexibility across different time scales by adjusting the control interval of the day-ahead dispatch optimization model. Finally, the framework is validated through case studies, revealing the impact characteristics of system type and capacity on flexibility, and analyzing the sensitivity of flexibility to various uncertainty parameters.

H2 norm based parameter optimization of multiple tuned mass dampers for resonance suppression

Flexible dynamic behavior of ultra-precision motion stage significantly deteriorates control performance. To tackle this problem, this paper presents an [Formula: see text] norm based parameter optimization of multiple Tuned Mass Dampers (TMDs) for resonance suppression applied on linear flexible structures, assuming all parameters of multiple TMDs are independent, and considering locations of TMDs as variables. Linear flexible structures with multiple TMDs are modeled as a closed-loop control system through modeling in steps. Genetic algorithm is implemented employing [Formula: see text] norm as the optimization criterion. The effectiveness of the optimization is numerically verified on a free-free thin plate. The effects of uncertainties in TMDs parameters, linear flexible structure parameters, and TMDs failure on the vibration suppression effect are studied. The proposed modeling and optimization methods are promising for application to various flexible structures with provided modal frequencies and mode shape matrix.

Relationship Between Endothelial Function, Vital Parameters, and Cognitive Performance in Community Dwellers with Subjective Cognitive Decline: An Observational Study with Six Months Follow Up.

With advancing age, cognitive decline is frequently associated with endothelial dysfunction, but data on vascular performance prior to the onset of mild cognitive impairment (MCI) is scarce. To investigate the relationship between endothelial function, vital parameters and cognitive performance in older adults with subjective cognitive decline (SCD). Forty-five volunteers aged 65 years and older with SCD underwent comprehensive geriatric assessment-based prognosis evaluation by means of the Multidimensional Prognostic Index (MPI), full neuropsychological examination and peripheral arterial tonometry measurement by means of EndoPAT™2000 to evaluate endothelial flexibility and vital parameters. Six months after initial evaluation, participants were contacted by phone and a telephone-administered version of the MPI (TELE-MPI) was conducted. Fifteen study participants scored below the cutoff score of 26 on the Montreal Cognitive Assessment, suggesting MCI (26.56±2.23). Nominal significant correlations were found between heart rate (HR) and trail making test (TMT) A (β= -0.49, p = 0.03), between heart rate variability (HRV) and TMT B (β= 0.78, p = 0.041), between power of low-frequency band (LF) HRV and Mini Nutritional Assessment-Short Form (β= 0.007, p = 0.037) as well as between augmentation index (AI) and CogState Detection Test (β= 0.002, p = 0.034). HR, HRV, and AI, but not endothelial flexibility are associated with cognitive performance in SCD and suspected MCI patients and may serve as clinical biomarkers in the early diagnosis of neurodegenerative disorders with advancing age.

Ultrasound normalized cumulative residual entropy imaging: Theory, methodology, and application

Background and Objective:Ultrasound information entropy imaging is an emerging quantitative ultrasound technique for characterizing local tissue scatterer concentrations and arrangements. However, the commonly used ultrasound Shannon entropy imaging based on histogram-derived discrete probability estimation suffers from the drawbacks of histogram settings dependence and unknown estimator performance. In this paper, we introduced the information-theoretic cumulative residual entropy (CRE) defined in a continuous distribution of cumulative distribution functions as a new entropy measure of ultrasound backscatter envelope uncertainty or complexity, and proposed ultrasound CRE imaging for tissue characterization. Methods:We theoretically analyzed the CRE for Rayleigh and Nakagami distributions and proposed a normalized CRE for characterizing scatterer distribution patterns. We proposed a method based on an empirical cumulative distribution function estimator and a trapezoidal numerical integration for estimating the normalized CRE from ultrasound backscatter envelope signals. We presented an ultrasound normalized CRE imaging scheme based on the normalized CRE estimator and the parallel computation technique. We also conducted theoretical analysis of the differential entropy which is an extension of the Shannon entropy to a continuous distribution, and introduced a method for ultrasound differential entropy estimation and imaging. Monte-Carlo simulation experiments were performed to evaluate the estimation accuracy of the normalized CRE and differential entropy estimators. Phantom simulation and clinical experiments were conducted to evaluate the performance of the proposed normalized CRE imaging in characterizing scatterer concentrations and hepatic steatosis (n = 204), respectively. Results:The theoretical normalized CRE for the Rayleigh distribution was π/4, corresponding to the case where there were ≥10 randomly distributed scatterers within the resolution cell of an ultrasound transducer. The theoretical normalized CRE for the Nakagami distribution decreased as the Nakagami parameter m increased, corresponding to that the ultrasound backscattered statistics varied from pre-Rayleigh to Rayleigh and to post-Rayleigh distributions. Monte-Carlo simulation experiments showed that the proposed normalized CRE and differential entropy estimators can produce a satisfying estimation accuracy even when the size of the test samples is small. Phantom simulation experiments showed that the proposed normalized CRE and differential entropy imaging can characterize scatterer concentrations. Clinical experiments showed that the proposed ultrasound normalized CRE imaging is capable to quantitatively characterize hepatic steatosis, outperforming ultrasound differential entropy imaging and being comparable to ultrasound Shannon entropy and Nakagami imaging. Conclusion:This study sheds light on the theory and methodology of ultrasound normalized CRE. The proposed ultrasound normalized CRE can serve as a new, flexible quantitative ultrasound envelope statistics parameter. The proposed ultrasound normalized CRE imaging may find applications in quantified characterization of biological tissues. Our code will be made available publicly at https://github.com/zhouzhuhuang.

Enhancement of cooling process of hot blocks mounted inside a horizontal channel using flexible baffles — Alternative arrangement

In this paper, two heated blocks and three flexible baffles that are alternately placed on the upper and bottom sides of a rectangular channel are used to replicate the transient heat and air movement. The novelty of this research is the use of flexible baffles to destruct the thermal boundary layer with maintaining little pressure drop, and thus reducing the required pumping capacity. The finite thickness blocks are subject to a constant heat flux, while the baffles are very thin and deforms depending on the strength of the flow of coolant (air). Finite element method with arbitrary Lagrangian–Eulerian approach is used for solving such deforming domain problem. The problem is inspected transiently by varying the dimensionless time (τ=0.0 to 10) and two salient parameters which are Reynolds number Re=10−500, and baffle elasticity parameter E=105−108. Results show that the flexibility feature of the baffles contributes not only in directing the coolant towards the hot blocks, but also contributes in reducing the skin friction and pressure drop through the channel. At Re=150, the skin friction and pressure drop of the flexible baffles are 13.2% and 16.5%, respectively lesser than the rigid baffles. The improvement of Nusselt number with flexibility parameter is marginal and within a limited low Reynolds number, where the maximal improvement is about 3.4% at Re=150.

Glial scarring around intra-cortical MEA implants with flexible and free microwires inserted using biodegradable PLGA needles.

Introduction: Many invasive and noninvasive neurotechnologies are being developed to help treat neurological pathologies and disorders. Making a brain implant safe, stable, and efficient in the long run is one of the requirements to conform with neuroethics and overcome limitations for numerous promising neural treatments. A main limitation is low biocompatibility, characterized by the damage implants create in brain tissue and their low adhesion to it. This damage is partly linked to friction over time due to the mechanical mismatch between the soft brain tissue and the more rigid wires. Methods: Here, we performed a short biocompatibility assessment of bio-inspired intra-cortical implants named "Neurosnooper" made of a microelectrode array consisting of a thin, flexible polymer-metal-polymer stack with microwires that mimic axons. Implants were assembled into poly-lactic-glycolic acid (PLGA) biodegradable needles for their intra-cortical implantation. Results and Discussion: The study of glial scars around implants, at 7days and 2months post-implantation, revealed a good adhesion between the brain tissue and implant wires and a low glial scar thickness. The lowest corresponds to electrode wires with a section size of 8μm × 10μm, compared to implants with the 8μm × 50μm electrode wire section size, and a straight shape appears to be better than a zigzag. Therefore, in addition to flexibility, size and shape parameters are important when designing electrode wires for the next generation of clinical intra-cortical implants.