Mechanically-Guided 3D Assembly for Architected Flexible Electronics.

Architected flexible electronic devices with rationally designed 3D geometries have found essential applications in biology, medicine, therapeutics, sensing/imaging, energy, robotics, and daily healthcare. Mechanically-guided 3D assembly methods, exploiting mechanics principles of materials and structures to transform planar electronic devices fabricated using mature semiconductor techniques into 3D architected ones, are promising routes to such architected flexible electronic devices. Here, we comprehensively review mechanically-guided 3D assembly methods for architected flexible electronics. Mainstream methods of mechanically-guided 3D assembly are classified and discussed on the basis of their fundamental deformation modes (i.e., rolling, folding, curving, and buckling). Diverse 3D interconnects and device forms are then summarized, which correspond to the two key components of an architected flexible electronic device. Afterward, structure-induced functionalities are highlighted to provide guidelines for function-driven structural designs of flexible electronics, followed by a collective summary of their resulting applications. Finally, conclusions and outlooks are given, covering routes to achieve extreme deformations and dimensions, inverse design methods, and encapsulation strategies of architected 3D flexible electronics, as well as perspectives on future applications.

A soft microrobot with highly deformable 3D actuators for climbing and transitioning complex surfaces.

The climbing microrobots have attracted growing attention due to their promising applications in exploration and monitoring of complex, unstructured environments. Soft climbing microrobots based on muscle-like actuators could offer excellent flexibility, adaptability, and mechanical robustness. Despite the remarkable progress in this area, the development of soft microrobots capable of climbing on flat/curved surfaces and transitioning between two different surfaces remains elusive, especially in open spaces. In this study, we address these challenges by developing voltage-driven soft small-scale actuators with customized 3D configurations and active stiffness adjusting. Combination of programmed strain distributions in liquid crystal elastomers (LCEs) and buckling-driven 3D assembly, guided by mechanics modeling, allows for voltage-driven, complex 3D-to-3D shape morphing (bending angle > 200°) at millimeter scales (from 1 to 10 mm), which is unachievable previously. These soft actuators enable development of morphable electroadhesive footpads that can conform to different curved surfaces and stiffness-variable smart joints that allow different locomotion gaits in a single microrobot. By integrating such morphable footpads and smart joints with a deformable body, we report a multigait, soft microrobot (length from 6 to 90 mm, and mass from 0.2 to 3 g) capable of climbing on surfaces with diverse shapes (e.g., flat plane, cylinder, wavy surface, wedge-shaped groove, and sphere) and transitioning between two distinct surfaces. We demonstrate that the microrobot could navigate from one surface to another, recording two corresponding ceilings when carrying an integrated microcamera. The developed soft microrobot can also flip over a barrier, survive extreme compression, and climb bamboo and leaf.

Leveraging permutation testing to assess confidence in positive-unlabeled learning applied to high-dimensional biological datasets.

BACKGROUND: Compared to traditional supervised machine learning approaches employing fully labeled samples, positive-unlabeled (PU) learning techniques aim to classify "unlabeled" samples based on a smaller proportion of known positive examples. This more challenging modeling goal reflects many real-world scenarios in which negative examples are not available-posing direct challenges to defining prediction accuracy and robustness. While several studies have evaluated predictions learned from only definitive positive examples, few have investigated whether correct classification of a high proportion of known positives (KP) samples from among unlabeled samples can act as a surrogate to indicate model quality. RESULTS: In this study, we report a novel methodology combining multiple established PU learning-based strategies with permutation testing to evaluate the potential of KP samples to accurately classify unlabeled samples without using "ground truth" positive and negative labels for validation. Multivariate synthetic and real-world high-dimensional benchmark datasets were employed to demonstrate the suitability of the proposed pipeline to provide evidence of model robustness across varied underlying ground truth class label compositions among the unlabeled set and with different proportions of KP examples. Comparisons between model performance with actual and permuted labels could be used to distinguish reliable from unreliable models. CONCLUSIONS: As in fully supervised machine learning, permutation testing offers a means to set a baseline "no-information rate" benchmark in the context of semi-supervised PU learning inference tasks-providing a standard against which model performance can be compared.

PNA-Functionalized, Silica Nanowires-Filled Glass Microtube for Ultrasensitive and Label-Free Detection of miRNA-21.

MicroRNAs (miRNAs) are endogenous and noncoding single-stranded RNA molecules with a length of approximately 18-25 nucleotides, which play an undeniable role in early cancer screening. Therefore, it is very important to develop an ultrasensitive and highly specific method for detecting miRNAs. Here, we present a bottom-up assembly approach for modifying glass microtubes with silica nanowires (SiNWs) and develop a label-free sensing platform for miRNA-21 detection. The three-dimensional (3D) networks formed by SiNWs make them abundant and highly accessible sites for binding with peptide nucleic acid (PNA). As a receptor, PNA has no phosphate groups and exhibits an overall electrically neutral state, resulting in a relatively small repulsion between PNA and RNA, which can improve the hybridization efficiency. The SiNWs-filled glass microtube (SiNWs@GMT) sensor enables ultrasensitive, label-free detection of miRNA-21 with a detection limit as low as 1 aM at a detection range of 1 aM-100 nM. Noteworthy, the sensor can still detect miRNA-21 in the range of 102-108 fM in complex solutions containing 1000-fold homologous interference of miRNAs. The high anti-interference performance of the sensor enables it to specifically recognize target miRNA-21 in the presence of other miRNAs and distinguish 1-, 3-mismatch nucleotide sequences. Significantly, the sensor platform is able to detect miRNA-21 in the lysate of breast cancer cell lines (e.g., MCF-7 cells and MDA-MB-231 cells), indicating that it has good potential in the screening of early breast cancers.

Enhanced Intrinsic Self-Healing Performance of Mussel Inspired Coating via In-Situ Cation Capture.

Under damp or aquatic conditions, the corrosion products deposited on micro-cracks/pore sites bring about the failure of intrinsically healable organic coatings. Inspired by mussels, a composite coating of poly (methyl methacrylate-co-butyl acylate-co-dopamine acrylamide)/phenylalanine-functionalized boron nitride (PMBD/BN-Phe) is successfully prepared on the reinforcing steel, which exhibits excellent anti-corrosion and underwater self-healing capabilities. The self-healing property of PMBD is derived from the synergistic effect of hydrogen bonding and metal-ligand coordination bonding, and thereby the continuous generation of corrosion products can be significantly suppressed through in situ capture of cations by the catechol group. Furthermore, the corrosion protection ability can be remarkably improved by the labyrinth effect of BN and the inhibition role of Phe, and the desired interfacial compatibility can be formed by the hydrogen bonds between BN-Phe and PMBD matrix. The corrosion current density (icorr) of PMBD/BN-Phe coating is determined as 7.95 × 10-11 A cm-2. The low-frequency impedance modulus (|Z|f  =  0.0 1 Hz is remained at 3.47 × 109 Ω cm2, indicating an ultra-high self-healing efficiency (≈89.5%). It is anticipated to provide a unique strategy for development of an underwater self-healing coating and robust durability for application in anti-corrosion engineering of marine buildings.

Interphase Engineering Enhanced Electro-chemical Stability of Prelithiated Anode.

Prelithiation is an essential technology to compensate for the initial lithium loss of lithium-ion batteries due to the formation of solid electrolyte interphase (SEI) and irreversible structure change. However, the prelithiated materials/electrodes become more reactive with air and electrolyte resulting in unwanted side reactions and contaminations, which makes it difficult for the practical application of prelithiation technology. To address this problem, herein, interphase engineering through a simple solution treatment after chemical prelithiation is proposed to protect the prelithiated electrode. The used solutions are carefully selected, and the composition and nanostructure of the as-formed artificial SEIs are revealed by cryogenic electron microscopy and X-ray photoelectron spectroscopy. The electrochemical evaluation demonstrates the unique merits of this artificial SEI, especially for the fluorinated interphase, which not only enhances the interfacial ion transport but also increases the tolerance of the prelithiated electrode to the air. The treated graphite electrode shows an initial Coulombic efficiency of 129.4%, a high capacity of 170 mAh g-1 at 3 C, and negligible capacity decay after 200 cycles at 1 C. These findings not only provide a facile, universal, and controllable method to construct an artificial SEI but also enlighten the upgrade of battery fabrication and the alternative use of advanced electrolytes.

Safflower yellow for injection enhances anti-coagulation of warfarin in rats: implications in pharmacodynamics and pharmacokinetics.

This study investigated whether Safflower Yellow for injection (SYI) would affect the anticoagulation of warfarin in rats.Wistar male rats were divided into six groups randomly and administered with SYI (9 mg/kg, intraperitoneal injection) in single-dose and steady-dose warfarin (0.2 mg/kg, oral gavage), respectively. The pharmacodynamic parameters of PT and APTT were measured by a coagulation analyser. R/S-warfarin concentration was measured by UHPLC-MS/MS, and pharmacokinetic parameters calculated using DAS 2.0 software.The single-dose study demonstrated that SYI, alone or co-administered with warfarin, could significantly increase PT, INR, and APTT values (p < 0.01). R-warfarin Cmax, AUC, and t1/2 values increased by 9.25% (p > 0.05), 25.96% (p < 0.01), and 26.17% (p < 0.01), respectively, whereas the CL/F value reduced by 22.22% (p < 0.01) in the presence of SYI. Meanwhile, S-warfarin Cmax, AUC, and t1/2 values increased by 37.41%, 32.11%, and 31.73% (all p < 0.01), respectively, whereas the CL/F value reduced by 33.33% (p < 0.01). The steady-dose study showed that PT, INR, APTT, and the concentrations of R/S-warfarin increased significantly when SYI was co-administered with warfarin (p < 0.01).SYI can enhance warfarin's anticoagulation intensity and decelerate its metabolism in rats.

Based ATP-gating mechanism for detection of alkaline phosphatase in single-glass micropipettes functionalized by three-dimensional DNA network.

The construction of gating system in artificial channels is a cutting-edge research direction in understanding biological process and application sensing. Here, by mimicking the gating system, we report a device that easily synthesized single-glass micropipettes functionalized by three-dimensional (3D) DNA network, which triggers the gating mechanism for the detection of biomolecules. Based on this strategy, the gating mechanism shows that single-glass micropipette assembled 3D DNA network is in the "OFF" state, and after collapsing in the presence of ATP, they are in the "ON" state, at which point they exhibit asymmetric response times. In the "ON" process of the gating mechanism, the ascorbic acid phosphate (AAP) can be encapsulated by a 3D DNA network and released in the presence of adenosine triphosphate (ATP), which initiates a catalyzed cascade reaction under the influence of alkaline phosphatase (ALP). Ultimately, the detection of ALP can be responded to form the fluorescence signal generated by terephthalic acid that has captured hydroxyl radicals, which has a detection range of 0-250 mU/mL and a limit of detection of 50 mU/mL. This work provides a brand-new way and application direction for research of gating mechanism.

MWIRGas-YOLO: Gas Leakage Detection Based on Mid-Wave Infrared Imaging.

The integration of visual algorithms with infrared imaging technology has become an effective tool for industrial gas leak detection. However, existing research has mostly focused on simple scenarios where a gas plume is clearly visible, with limited studies on detecting gas in complex scenes where target contours are blurred and contrast is low. This paper uses a cooled mid-wave infrared (MWIR) system to provide high sensitivity and fast response imaging and proposes the MWIRGas-YOLO network for detecting gas leaks in mid-wave infrared imaging. This network effectively detects low-contrast gas leakage and segments the gas plume within the scene. In MWIRGas-YOLO, it utilizes the global attention mechanism (GAM) to fully focus on gas plume targets during feature fusion, adds a small target detection layer to enhance information on small-sized targets, and employs transfer learning of similar features from visible light smoke to provide the model with prior knowledge of infrared gas features. Using a cooled mid-wave infrared imager to collect gas leak images, the experimental results show that the proposed algorithm significantly improves the performance over the original model. The segment mean average precision reached 96.1% (mAP50) and 47.6% (mAP50:95), respectively, outperforming the other mainstream algorithms. This can provide an effective reference for research on infrared imaging for gas leak detection.

Polymer Competitive Solvation Reduced Propylene Carbonate Cointercalation in a Graphitic Anode.

Polymer electrolytes have been studied as an alternative to organic liquid electrolytes but suffer from low ionic conductivity. Propylene carbonate (PC) proves to be an interesting solvent but is incompatible with graphitic anodes due to its cointercalation effect. In this work, adding poly(ethylene oxide) (PEO) into a PC-based electrolyte can alter the solvation structure as well as transform the solution into a polymer electrolyte with high ionic conductivity. By spectroscopic techniques and calculations, we demonstrate that PEO can compete with PC in solvating the Li+ ions, reducing the Li+-PC bond strength, and making it easier for PC to be desolvated. Due to the unique solvation structure, PC-cointercalation-induced graphite exfoliation is inhibited, and the reduction stability of the electrolyte is improved. This work will extend the applications of the PC-based electrolytes, deepen the understandings of the solvation structure, and spur designs of advanced electrolytes.

The influence of almond's water activity and storage temperature on Salmonella survival and thermal resistance.

This study investigated the effects of inoculation method, water activity (aw), packaging method, and storage temperature and duration on the survival of Salmonella on almonds as well as their resistance to subsequent thermal treatments. Whole almond kernels were inoculated with a broth-based or agar-based growth Salmonella cocktail and conditioned to aw of 0.52, 0.43 or 0.27. Inoculated almonds with aw of 0.43 were treated with a previously validated treatment (4 h of dry heat at 73 °C) to determine the potential differences in heat resistance resulted from the two inoculation methods. The inoculation method did not significantly (P > 0.05) impact the thermal resistance of Salmonella. Inoculated almonds at aw of 0.52 and 0.27 were either vacuum packaged in moisture-impermeable mylar bags or non-vacuum packaged in moisture-permeable polyethylene bags before stored at 35, 22, 4, or -18 °C for up to 28 days. At selected storage intervals, almonds were measured for aw, analyzed for Salmonella population level, and subjected to dry heat treatment at 75 °C. Over the month-long storage of almonds, Salmonella populations remained almost unchanged (<0.2 log CFU/g) at 4 °C and -18 °C and declined slightly (<0.8 log CFU/g) at 22 °C and more substantially (1.6-2.0 log CFU/g) at 35 °C regardless of the inoculation method, packaging method, and almond aw. When stored at 35 °C, almonds with initial aw of 0.52 had significantly higher (P < 0.05) Salmonella reductions than those with initial aw of 0.27. Prior storage of almonds vacuum packaged in mylar bags at temperatures between -18 °C and 35 °C for 28 days affected their aw levels but did not significantly (P > 0.05) affect the subsequent thermal resistance of Salmonella at 75 °C regardless of almond aw and storage duration. Salmonella on almonds with higher aw was more sensitive to heat treatment than those with lower aw. To achieve >5 log CFU/g reductions of Salmonella, a dry heat treatment at 75 °C for 4 and 6 h was needed for almonds with initial aw of 0.52 and 0.27, respectively. When applying the dry heating technology for almond decontamination, the processing time needs to be determined based on initial aw of almonds regardless of storage condition or age of almonds within the current design frame.

Antibody attributes that predict the neutralization and effector function of polyclonal responses to SARS-CoV-2.

BACKGROUND: While antibodies can provide significant protection from SARS-CoV-2 infection and disease sequelae, the specific attributes of the humoral response that contribute to immunity are incompletely defined. METHODS: We employ machine learning to relate characteristics of the polyclonal antibody response raised by natural infection to diverse antibody effector functions and neutralization potency with the goal of generating both accurate predictions of each activity based on antibody response profiles as well as insights into antibody mechanisms of action. RESULTS: To this end, antibody-mediated phagocytosis, cytotoxicity, complement deposition, and neutralization were accurately predicted from biophysical antibody profiles in both discovery and validation cohorts. These models identified SARS-CoV-2-specific IgM as a key predictor of neutralization activity whose mechanistic relevance was supported experimentally by depletion. CONCLUSIONS: Validated models of how different aspects of the humoral response relate to antiviral antibody activities suggest desirable attributes to recapitulate by vaccination or other antibody-based interventions.

Lithium titanate nanoplates embedded with graphene quantum dots as electrode materials for high-rate lithium-ion batteries.

Anode materials based on lithium titanate (LTO)/graphene composites are considered as ideal candidates for high-rate lithium-ion batteries (LIBs). Considering the blocking effects of graphene nanosheets in electrodes during ion-transfer processes, construction of LTO/graphene composite structures with enhanced electrical and ionic conductivity via facile and scalable techniques is still challenging for high-rate LIB. In this work, structures of anode materials based on LTO nanoplates embedded with graphene quantum dots (GQDs) are demonstrated for high-rate LIB. The hybrids can be facilely prepared viain situintroduction of GQDs during the process LTO preparation, which enables a uniform dispersion of GQDs within LTO. This method is convenient, rapid, and can be easily scaled-up. The introduction of 0.05 wt.% GQDs can greatly enhance the electrochemical performance of the electrodes. The electrodes with 0.05 wt.% GQDs deliver a specific discharge capacity of 185, 181 and 179 mAh g-1at 5, 10, and 20 C, respectively. The performance enhancement is suggested to be due to the synergistic interactions between LTO and GQDs. The strategy as well as as-designed structures of LTO/GQDs show potentials for application as high-rate anode materials in LIBs application.

Oral health in patients with dementia: A meta-analysis of comparative and observational studies.

OBJECTIVE: Poor oral health is common in dementia, but findings of epidemiological studies have been inconsistent. This meta-analysis examined oral health in patients with dementia diagnosed according to standardized diagnostic criteria. METHODS: Six international databases (PubMed, EMBASE, PsycINFO, Medline, Cochrane Library, and Web of Science) were searched from their commencement date until 8 November 2018. Oral health was measured by the Remaining Teeth (RT) and Decayed, Missing, and Filled Teeth (DMFT) Index. The mean differences (MD) and 95% confidence intervals (CI) of DMFT Index total and component scores were calculated using a random-effect model. RESULTS: Twenty-four studies were included for analyses. The pooled DMFT Index was 23.48 (95% CI: 22.34, 24.62), while the pooled score for each component was 2.38 (95% CI: 1.56, 3.20) in decayed teeth (DT), 18.39 (95% CI: 15.92, 20.87) in missing teeth (MT), 2.29 (95% CI: 0.62, 3.95) in filled teeth (FT), and 11.59 (95% CI: 9.14, 14.05) in RT. Compared to controls, people with dementia had significantly a higher DMFT Index total score (MD = 3.80, 95% CI: 2.21, 5.39, p < 0.00,001), and significantly lower number of RT (MD = -3.15, 95% CI: -4.23, -2.06, p < 0.00,001). Subgroup analyses revealed that higher DMFT Index score was significantly associated with year of survey (>2010), study design (case-control study), percentage of females (≤54.3), and the Mini Mental State Examination score (≤18.2). Higher MT score was significantly associated with study design (cross-sectional study), and lower FT score was significantly associated with year of survey (>2010). CONCLUSIONS: Oral health was significantly poorer in people with dementia compared with controls. Regular screening and effective treatment should be implemented for this population.

Effects of alkalinity on interaction between EPS and hydroxy-aluminum with different speciation in wastewater sludge conditioning with aluminum based inorganic polymer flocculant.

Extracellular polymeric substances (EPS) form a stable gel-like structure to combine with water molecules through steric hindrance, making the mechanical dewatering of wastewater sludge considerably difficult. Coagulation/flocculation has been widely applied in improving the sludge dewatering performance, while sludge properties (organic fraction and solution chemistry conditions) are highly changeable and have important effects on sludge flocculation process. In this work, the alkalinity effects on sludge conditioning with hydroxy-aluminum were comprehensively investigated, and the interaction mechanisms between EPS and hydroxy-aluminum with different speciation were unraveled. The results showed that the effectiveness of hydroxy-aluminum conditioning gradually deteriorated with increase in alkalinity. Meanwhile, the polymeric hydroxy-aluminum (Al13) and highly polymerized hydroxy-aluminum (Al30) were hydrolysed and converted into amorphous aluminum hydroxide (Al(OH)3), which changed the flocculation mechanism from charge neutralization and complexing adsorption to hydrogen bond interaction. Additionally, both Al13 and Al30 showed higher binding capacity for proteins and polysaccharides in EPS than monomeric aluminum and Al(OH)3. Al13 and Al30 coagulation changed the secondary structure of proteins in EPS, which caused a gelation reaction to increase molecular hydrophobicity of proteins and consequently sludge dewaterability. This study provided a guidance for optimizing the hydroxy-aluminum flocculation conditioning of sludge with high solution alkalinity.

Flexible room-temperature formaldehyde sensors based on rGO film and rGo/MoS2 hybrid film.

Gas sensors based on reduced graphene oxide (rGO) films and rGO/MoS2 hybrid films were fabricated on polyethylene naphthalate substrates by a simple self-assembly method, which yielded flexible devices for detection of formaldehyde (HCHO) at room temperature. The sensing test results indicated that the rGO and rGO/MoS2 sensors were highly sensitive and fully recoverable to a ppm-level of HCHO. The bending and fatigue test results revealed that the sensors were also mechanically robust, durable and effective for long-term use. The rGO/MoS2 sensors showed higher sensitivities than rGO sensors, which was attributed to the enhanced HCHO adsorption and electron transfer mediated by MoS2. Furthermore, two kinds of MoS2 nanosheets were prepared by either hydrothermal synthesis or chemical exfoliation and were compared for their detection of HCHO, which revealed that the hydrothermally produced MoS2 nanosheets with rich defects led to enhanced sensitivity of the rGO/MoS2 sensors. Moreover, these fabricated flexible sensors can be applied for the HCHO detection in food packaging.

Effect of Amino Silicone Oil-Phosphorylation Hybrid Modification on the Properties of Microcellulose Fibers.

Microcellulose materials are increasingly considered multifunctional candidates for emerging energy applications. Microcellulose fibers (MCF) are a kind of bio-based reinforcement in composites, and their hydrophilic character hinders their wide application in industry. Thus, in the present work, MCF was hybrid-modified by amino silicone oil-phosphorylated to fabricate hydrophobic, thermal stability, and flame-retardant microcellulose fibers for potential application in vehicle engineering. The results showed that the amino silicone oil-phosphorylated (ASOP) hybrid modification could transform the surface property of microcellulose from hydrophilic to hydrophobic and improve the compatibility between MCF and resin matrix. Meanwhile, the ASOP treatment led to the formation of an amino silicone oil film layer on the surface of the microcellulose, which improved the thermal stability of the MCF. Furthermore, the ASOP hybrid modification microcellulose fibers paper (100% microcellulose fibers paper) was transformed from flammable to flame-retardant and showed self-extinguishing behavior after burning under flame for 2 s. The flame-retardant mechanism was attributed to the formation of the char layer in the condensed phase and the production of non-combustible gases in the gaseous phase.

Silica Nanowires-Filled Glass Microporous Sensor for the Ultrasensitive Detection of Deoxyribonucleic Acid.

DNA carries genetic information and can serve as an important biomarker for the early diagnosis and assessment of the disease prognosis. Here, we propose a bottom-up assembly method for a silica nanowire-filled glass microporous (SiNWs@GMP) sensor and develop a universal sensing platform for the ultrasensitive and specific detection of DNA. The three-dimensional network structure formed by SiNWs provides them with highly abundant and accessible binding sites, allowing for the immobilization of a large amount of capture probe DNA, thereby enabling more target DNA to hybridize with the capture probe DNA to improve detection performance. Therefore, the SiNWs@GMP sensor achieves ultrasensitive detection of target DNA. In the detection range of 1 aM to 100 fM, there is a good linear relationship between the decrease rate of current signal and the concentration of target DNA, and the detection limit is as low as 1 aM. The developed SiNWs@GMP sensor can distinguish target DNA sequences that are 1-, 3-, and 5-mismatched, and specifically recognize target DNA from complex mixed solution. Furthermore, based on this excellent selectivity and specificity, we validate the universality of this sensing strategy by detecting DNA (H1N1 and H5N1) sequences associated with the avian influenza virus. By replacing the types of nucleic acid aptamers, it is expected to achieve a wide range and low detection limit sensitive detection of various biological molecules. The results indicate that the developed universal sensing platform has ultrahigh sensitivity, excellent selectivity, stability, and acceptable reproducibility, demonstrating its potential application in DNA bioanalysis.

A data-mining study on the prediction of head injury in traffic accidents among vulnerable road users with varying body sizes and head anatomical characteristics.

Body sizes and head anatomical characteristics play the major role in the head injuries sustained by vulnerable road users (VRU) in traffic accidents. In this study, in order to study the influence mechanism of body sizes and head anatomical characteristics on head injury, we used age, gender, height, and Body Mass Index (BMI) as characteristic parameters to develop the personalized human body multi-rigid body (MB) models and head finite element (FE) models. Next, using simulation calculations, we developed the VRU head injury dataset based on the personalized models. In the dataset, the dependent variables were the degree of head injury and the brain tissue von Mises value, while the independent variables were height, BMI, age, gender, traffic participation status, and vehicle speed. The statistical results of the dataset show that the von Mises value of VRU brain tissue during collision ranges from 4.4 kPa to 46.9 kPa at speeds between 20 and 60 km/h. The effects of anatomical characteristics on head injury include: the risk of a more serious head injury of VRU rises with age; VRU with higher BMIs has less head injury in collision accidents; height has very erratic and nonlinear impacts on the von Mises values of the VRU's brain tissue; and the severity of head injury is not significantly influenced by VRU's gender. Furthermore, we developed the classification prediction models of head injury degree and the regression prediction models of head injury response parameter by applying eight different data mining algorithms to this dataset. The classification prediction models have the best accuracy of 0.89 and the best R2 value of 0.85 for the regression prediction models.

Crown-Ether Crystal Channel Membranes with Subnanometer Pores for Selective Na+ Transport.

Emulating biological sodium ion channels to achieve high selectivity and rapid Na+ transport is important for water desalination, energy conversion, and separation processes. However, the development of artificial ion channels, especially multichannels, to achieve high ion selectivity, remains a challenge. In this work, we demonstrate the fabrication of ion channel membranes utilizing crown-ether crystals (DA18C6-nitrate crystals), which feature extremely consistent subnanometer pores. The polyethylene terephthalate (PET) membranes were initially subjected to amination, followed by the in situ growth of DA18C6-nitrate crystals to establish ordered multichannels aimed at facilitating selective Na+ conductance. These channels allow rapid Na+ transport while inhibiting the migration of other ions (K+ and Ca2+). The Na+ transport rate was 2.15 mol m-2 h-1, resulting in the Na+/K+ and Na+/Ca2+ selectivity ratios of 6.53 and 12.56, respectively. Due to the immobilization of the crown-ether ring, when the size of the transmembrane ion exceeded that of the crown-ether ring's cavity, the ions had to undergo a dehydration process to pass through the channel. This resulted in the ions encountering a higher energy barrier upon entering the channel, making it more difficult for them to permeate. However, the size of Na+ was compatible with the cavity of the crown-ether ring and was able to displace the hydrated layer effectively, facilitating selective Na+ translocation. In summary, this research offers a promising approach for the future development of functionalized ion channels and efficient membrane materials tailored for high-performance Na+ separation.