A self-cleaning micro-fluidic chip biospired by the filtering system of manta rays.

Size-based particle filtration has become indispensable in numerous biomedical and environmental applications. In this study, bioinspired by the filter-feeding mechanism (lobe filtration) of manta rays, we designed a U-shaped biomimetic gill rake filter that combined lobe filtration and Dean flow to filter monodisperse suspensions, bi-disperse suspensions and yeast cells. Compared with other equipment using the inertial focusing technology, our equipment can perform high-throughput (up to 8 mL min-1) and high-efficiency filtration of particles (maximum filtration efficiencies of 96.08% and 97.14% for 10 and 15 µm monodisperse suspensions at the optimum flow rate of 6 mL min-1). The complex velocity field of the micro-fluidic flow within the filter is numerically simulated, and in combination with experiments, a threshold for the flow rate is identified. When the inlet flow rate exceeds the threshold value, the efficiency of particle filtration is increased rapidly. Afterwards, by analysing the filtration mechanism, we develop three novel filtration processes. The equilibrium positions of the particles and yeast cells in the main channel are close to the outer wall at high flow rate, which diminishes the likelihood of particles and yeast cells entering the side channel. This configuration establishes a self-cleaning mechanism, ensuring prolonged and efficient operation of the filter with high-throughput processing. Furthermore, the influence of the filter lobe angle and channel width on the filtration efficiency and outlet flow rate ratio are explored, and an optimisation plan is prepared.

The motion of micro-swimmers over a cavity in a micro-channel.

This article combines the lattice Boltzmann method (LBM) with the squirmer model to investigate the motion of micro-swimmers in a channel-cavity system. The study analyses various influential factors, including the value of the squirmer-type factor (ß), the swimming Reynolds number (Rep), the size of the cavity, initial position and particle size on the movement of micro-swimmers within the channel-cavity system. We simultaneously studied three types of squirmer models, Puller (ß > 0), Pusher (ß < 0), and Neutral (ß = 0) swimmers. The findings reveal that the motion of micro-swimmers is determined by the value of ß and Rep, which can be classified into six distinct motion modes. For Puller and Pusher, when the ß value is constant, an increase in Rep will lead to transition in the motion mode. Moreover, the appropriate depth of cavity within the channel-cavity system plays a crucial role in capturing and separating Neutral swimmers. This study, for the first time, explores the effect of complex channel-cavity systems on the behaviour of micro-swimmers and highlights their separation and capture ability. These findings offer novel insights for the design and enhancement of micro-channel structures in achieving efficient separation and capture of micro-swimmers.

Analysis of the Energy Loss and Performance Characteristics in a Centrifugal Pump Based on Sinusoidal Tubercle Volute Tongue.

The energy loss inside a centrifugal pump has a significant effect on its performance characteristics. Based on the structural characteristics of the humpback pectoral fin, a new tongue was designed to improve the performance of the centrifugal pump. The influence of three sinusoidal tubercle volute tongues (STVT) and one original volute tongue (OVT) on energy dissipation using the enstrophy analysis method was investigated. To accomplish this, the pressure fluctuations and performances of four centrifugal pumps were analyzed. The results indicate that enstrophy is primarily distributed at the impeller outlet and near the tongue. The total enstrophy of the profiles of STVT was smaller than that of the profiles of OVT. This difference was more obvious near the tongue. The reductions in the total enstrophy of the pumps were 8% (STVT-1), 8.2% (STVT-2), and 9% (STVT-3). The pressure fluctuations of the STVT profiles also decreased to different degrees. The average pressure fluctuations at the monitoring points decreased by 20.6% (STVT-1), 21.7% (STVT-2), and 23.3% (STVT-3). The performances of the bionic retrofit pumps increased by 1.5% (STVT-1), 2% (STVT-2), and 2.45% (STVT-3) under the design flow rate. This study guides the structural optimization of pumps.

Prediction of Newtonian Droplet Breaking Time from a Capillary at Low Weber Numbers.

Droplet formation and growth processes have numerous scientific and industrial applications. Experimental and numerical studies on the formation, growth, and breaking of droplet are carried out in present work. The numerical results are in good agreement with the experiment. This work focused on the effect of different Weber numbers (We) on the droplet breaking time. The results show when We < 0.05, the length and volume of the droplet increase, and the breaking time decreases rapidly. The resultant force acting on the main droplet suddenly drops around the critical breaking time. The difference rate between the time t n (when the resultant force is zero) and the breaking time t b is less than 8.49%. For the dimensional analysis of the numerical results, a prediction formula of breaking time on the Weber number is modeled as aWe b + c for We < 0.5.

Probing age-related changes in cardio-respiratory dynamics by multimodal coupling assessment.

Quantifying respiratory sinus arrhythmia (RSA) can provide an index of parasympathetic function. Fourier spectral analysis, the most widely used approach, estimates the power of the heart rate variability in the frequency band of breathing. However, it neglects the time-varying characteristics of the transitions as well as the nonlinear properties of the cardio-respiratory coupling. Here, we propose a novel approach based on Hilbert-Huang transform, called the multimodal coupling analysis (MMCA) method, to assess cardio-respiratory dynamics by examining the instantaneous nonlinear phase interactions between two interconnected signals (i.e., heart rate and respiration) and compare with the counterparts derived from the wavelet-based method. We used an online database. The corresponding RSA components of the 90-min ECG and respiratory signals of 20 young and 20 elderly healthy subjects were extracted and quantified. A cycle-based analysis and a synchro-squeezed wavelet transform were also introduced to assess the amplitude or phase changes of each respiratory cycle. Our results demonstrated that the diminished mean and standard deviation of the derived dynamical RSA activities can better discriminate between elderly and young subjects. Moreover, the degree of nonlinearity of the cycle-by-cycle RSA waveform derived from the differences between the instantaneous frequency and the mean frequency of each respiratory cycle was significantly decreased in the elderly subjects by the MMCA method. The MMCA method in combination with the cycle-based analysis can potentially be a useful tool to depict the aging changes of the parasympathetic function as well as the waveform nonlinearity of RSA compared to the Fourier-based high-frequency power and the wavelet-based method.

Hydrostable and Nitryl/Methyl-Functionalized Metal-Organic Framework for Drug Delivery and Highly Selective CO2 Adsorption.

By using a strategy of introducing hydrophobic groups to the linkers, a hydrostable MOF was constructed based on 5-nitroisophthalate and 2,2'-dimethyl-4,4'-bipyridine coligands, revealing a 3D dia topology structure with a 1D channel parallel to the c axis. TGA, PXRD, and water vapor sorption results show high thermal and water stability for the framework. The framework is very porous and possesses not only high busulfan payloads with an encapsulation efficiency up to 21.5% (17.2 wt %) but also very high CO2 selective capture compared with that of other small gases (i.e., CH4, N2, O2, CO, and H2) at 298 K based on molecular simulations due to the pore surface being populated by methyl and nitryl groups. Furthermore, in vitro MTT assays were conducted on four different cells lines with increasing concentrations of the framework, and the results showed that the framework was nontoxic (cell viability >80%) in spite of the concentrations up to 500 µg/mL.

Correlations between the signal complexity of cerebral and cardiac electrical activity: a multiscale entropy analysis.

The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1-58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11-20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6-20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration.

Empirical mode decomposition based detrended sample entropy in electroencephalography for Alzheimer's disease.

Quantitative electroencephalographs (qEEG) provide a potential method to objectively quantify the cortical activations in Alzheimer's disease (AD), but they are too insensitive to probe the alteration of EEG in the early AD. The sample entropy (SaEn) attempts to quantify the complex information embedded in EEG non-linearly, which fits in that EEG originates from non-linear interactions. However, a technical issue which has been ignored by most researchers is that the signal should be stationary. In order to resolve the non-stationarity of SaEn in EEG to improve the sensitivity, an empirical mode decomposition (EMD) was applied for detrending in this study. Twenty-seven AD patients (9M/18F; mean age 74.0±1.5 years) were included. Their initial Minimal Mental Status Examination was 19.3±0.7. They received the first resting-awake 30-mine EEG before the therapy. Five of them received a follow-up examination within 6 months after the therapy. The 30-s EEG data without artifacts were selected and analyzed with a new proposed method, "EMD-based detrended-SaEn" to attenuate the influence of intrinsic non-stationarity. The correlation factors in 27 AD patients showed a moderate correlation (0.361-0.523, p<0.05) between MMSE and EMD-based detrended SaEn in Fp1, Fp2, F4 and T3. There was a high correlation (Correlation coefficient=0.975, p<0.05) between the changes of MMSE and the changes of EMD-based detrended-SaEn in F7 in 5 follow-up patients. The dynamic complexity of EEG fluctuations is degraded by pathological degeneration, and EMD-based detrended SaEn provides an objective, non-invasive and non-expensive tool for evaluating and following AD patients.