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Wound infection and poor wound healing are the major challenges of wound treatment. Antibiotic drug treatment is the effective way to inhibit wound infection. It is necessary to achieve sustained release of antibiotics to get a longer treatment for wound infection. The double network hydrogels based on liposome, polyethylene glycol (PEG), α- cyclodextrin ( α-CD) and acrylamide (AM) were developed, in which liposome acts as amoxicillin repository. Because the drug would release from the multiple barriers including two cavities of liposome and α-CD, as well as polyethylene glycol - α- cyclodextrin/acrylamide (PEG-CD/AM) double network, the PEG- α-CD/AM/liposome @amoxicillin double network hydrogels could achieve sustained drug release. The drug release assay showed that the dressing could release amoxicillin continuously until 12 days, than that of 8th day for single-network hydrogel releasing. The antibacterial ratio of the hydrogel could reach above 80%. What’s more, the hydrogels present adjustable mechanical strength by changing the ratio of the components. The swelling ratio proved that the hydrogel had potential ability to absorb wound exudates. The cytotoxicity test of the hydrogels demonstrated excellent biocompatibility. These results indicated that this study can provide a new thought for antibacterial wound dressing and has a broad application prospect.

We exploited a unique porous structure of the nano-covalent triazine polymer (NCTP) containing aggregation-induced emission (AIE) group to achieve controlled release and drug tracking in tumor acidic microenvironment. NCTP was synthesized by the Friedel-Crafts alkylation and the McMurry coupling reaction. It not only had strong doxorubicin (DOX)-loading capacity due to its high specific surface area and large pore volume, but also showed the significant cumulative drug release as a result of the pH response of triazine polymers. NCTP was induced luminescence after mass accumulation near tumor cells. Besides, it had excellent biocompatibility and obvious antineoplastic toxicity. The results demonstrate that NCTP as a utility-type drug carrier provides a new route for designing the multi-functional drug delivery platform.

Bimetallic two-dimensional (2D) metal–organic framework (MOF) materials display excellent electrocatalytic performance due to the synergistic effect between metals and the advantage of the 2D structure. In this work, Cu was introduced into the 2D Co-MOF structure, and a 2D book-like CuCo-MOF structure was fixed on carbon fiber paper (CFP) for direct electrochemical glucose detection and oxygen evolution reaction (OER). The materials showed good electrocatalytic glucose detection performance with a sensitivity as high as 6.861 mA mM−1 cm−2 and a detection limit as low as 0.12 μM. For the OER, when the current density is 10 mA cm−2, the overpotential (η) is 340 mV, and good stability is maintained for about 10 h without current attenuation. This work not only exploits a new 2D MOF structure containing Cu, but also expands the potential of Cu-containing MOF materials in the electrocatalytic OER, making a contribution to the field of energy conversion and biomolecular sensing.

This work demonstrates a double-step method, a simple chemical bath deposition and an in situ polymerization process, to synthesize the stable structure of a composite of Polyaniline/BiVO4/cellulose aerogel (PBC) in wastewater treatment. The poor stability of the carrier catalyst was improved significantly by forming a dense film of polyaniline (PANI) through polymerization on BiVO4/cellulose aerogel (BC). The developed three-dimensional porous structure enhanced photocatalytic stability. For instance, photocatalytic degradation of a dye, methylene blue, reached to 91.67% under the eight times successive irradiation of the visible light. The resulted fine performance could be owed to the strong adsorption of cellulose aerogel, uniform spreading of BiVO4, and the speedy electron separation efficiency of PBC. Moreover, the photocatalytic mechanisms including the role of the free radicals (•OH and •O2−) of the developed PBC were also discussed. The novel structure may present a new insight into the development of the carrier catalyst.

Background: The deep learning techniques have been attracted increasing attention on wireless body sensor networks (WBSNs) gait pattern recognition that has a great contribution to monitoring gait change in clinical application. However, in existing studies, there are some challenging issues such as low generalization performance and no potential interpretation for gait variability. It is necessary to search for the advanced deep learning models to resolve these issues. Method: A public WARD database including acceleration and gyroscope data acquired from each subject wearing five sensors was selected, and the gait with different combination of on-body multi-sensors is considered as a WBSNs’ gait pattern. An advanced attention-enhanced hybrid deep learning model of DCNN and LSTM for WBSNs’ gait pattern recognition was proposed. In our proposed technique, the combination model of DCNN with LSTM is firstly to discover the spatial-temporary gait correlation features. And then the attention mechanism is introduced to exploit the more valuable intrinsic nonlinear dynamic correlation gait characteristics associated with gait variability hidden in spatial-temporary gait space obtained. This significantly contributes to enhancing the generalization performance and taking insight on gait variability in a certain anatomical region. Results: The ten gait patterns are randomly selected from WARD database to evaluate the feasibility of our proposed method. Our experiments demonstrated the superior generalization ability of our method to some models such as CNN-LSTM, DCNN-LSTM. Our proposed model could classify ten gait patterns with the highest accuracy and F1-score of 91.48% and 91.46%, respectively. Moreover, we also found that the classification performance of a certain gait pattern was almost same best when the combinations of three or five on-body sensors were employed respectively, suggesting that our method possibly take insight on gait variability in a certain anatomical region. Conclusion: Our proposed technique could feasibly discover the more intrinsic nonlinear dynamic correlation gait characteristics associated with gait variability from on-body multi-sensors gait data, which greatly contributed to best generalization performance and potential clinical interpretation. Our proposed technique would hopefully become a powerful tool of monitoring gait change in clinical application.

A novel antibacterial hydrogel was prepared through the addition of IT to a chitin (CT) and polyvinyl alcohol (PVA) hydrogel, creating a promising material for wound dressings. The addition of nano particles IT endowed the anti-bacterial activity of hydrogel as well as had a positive impact on the mechanical properties of the hydrogels. The structure of the prepared hydrogel dressing was characterized by FTIR, XPS, XRD, SEM and TEM. The composite hydrogel exhibited excellent anti-bacterial activity under the visible light. Cytotoxicity tests (L929 fibroblast cells) showed all samples achieving up to 80% cell viability. Furthermore, compared with conventional dressings, wound healing test revealed that CT/PVA/IT hydrogel could accelerated wound healing in vivo, wound closure rates reached 95.5% after 10 days. This study suggests that the novel hydrogel has considerable potential for applications in wound dressings.

During the photocatalytic production of hydrogen gas, close interface with a catalyst is very important. We designed a noble-metal-free photocatalytic system that is spatially separated to produce hydrogen by high frequency visible light. We used a new type of a catalyst consisting of hollow core-shell CdS@TiO2/Ni2P structures prepared using sacrificial template method. Photocatalytic decomposition of water was tested using this catalyst. Hydrogen production yield using 420 nm light was 14.80 mmol/g after 2.5 h and using Xe lamp with AM1.5G filter was 34.78 mmol/g after 2.5 h. Hollow core shell CdS@TiO2/Ni2P particles were more stable than hollow core shell CdS@TiO2/Pt structures because TiO2 protected CdS from photo-corrosion. Combination of CdS and Ni2P increased absorption range of TiO2 at 720 nm. Holes and electrons produced during the photo-reaction can migrate to the CdS on the inside and to the Ni2P on the outside of the TiO2 protective coating. Such design exposes more surface, thus, increases hydrogen production.

Carbon layer coated black TiO2−x/g-C3N4 nanosheets (C@TiO2−x/CNNS) heterojunction photocatalysts were successfully prepared via a polydopamine dopamine carbonization route for the first time. It was found that the hydrogen evolution rate of C@TiO2−x/CNNS was 417.2 μmol h−1 g−1 under visible light irradiation, which was much higher than that of other prepared photocatalysts in solar water splitting process at the same conditions, and obvious decrease in catalytic activity can be observed after three recycles. The formation of carbon layer on the surface of TiO2−x can effectively protect Ti3+ and oxygen vacancies (Ovs) from oxidation by air and dissolved O2, afterwards much more Ti3+/Ovs are exsited, which can serve as charge carrier traps to inhibit the recombination of light-excited electrons-holes. Therefore, C@TiO2−x/CNNS showed a highly conductivity, rapidly effective electron-hole separation and lower transmission resistance comprehensive consideration of the advantages of carbon layer and hetero-junction, which are of great benefit to the improvement of photocatalytic performance. Hence, a new catalytic tactic namely layer-protection effect was founded and this strategy for boosting hydrogen evolution and protection Ti3+/Ovs may give us some hints on the design of photocatalytic systems.

As a strong oxidizing pollutant, NO2 can cause fire or even explosion. People living in atmosphere containing NO2 for a long time will significantly affects human health. In this work, we developed a Schottky heterojunction sensor modified by g-C3N4 quantum dots (g-C3N4QDs) and rGO deposited on TiO2 nanotubes (TNTs) arrays. This sensor showed high response and extremely fast response/recovery time as well as excellent detection of ppb level of NO2 at room temperature. TNTs were obtained using a one-step anodic oxidation process. TNTs were modified with g-C3N4QDs and rGO using quasi-CVD method and cyclic voltammetry during in situ electrodeposition, respectively. TNTs/g-C3N4QDs/rGO Schottky heterojunction sensor exhibited high sensitivity to 10 ppm of NO2 (response equal to 15982) at room temperature. Below 15 ppb, sensing response also can reach 127. Sensor response was very fast and increased to 15982 in just 2 s when exposed to 10 ppm of NO2 after which it recovers 90% within 1.16 s. This work clarified the influence of abundant oxygen vacancies (VO·) in TNTs and photogenerated electrons on TNTs/g-C3N4QDs/rGO nanostructures as well as their sensing performances. Our experimental details demonstrated that Schottky barrier was established between TNTs and rGO, which was very beneficial for ppb-level NO2 detection at room temperature.

ZnO nanocone arrays (NCAs) decorated with black TiO2 nanoparticles (B-TiO2 NPs) were uniformly anchored on the surface of carbon cloth (CC) directly by a simply electrochemical deposition method. Thus a novel B-TiO2 NPs/ZnO NCAs-CC hierarchical heterostructure was formed. It displayed superior performance and achieved a higher photocurrent over 0.4 mA$cm-2 before the onset of the dark current, attributed to the separation of the photogenerated electron-hole pair. Based on the B-TiO2 NPs/ZnO NCAs-CC heterostructure, the catalyst was fabricated for promoting the separation of charge carriers. Moreover, the introduction of Ti3+ and oxygen vacancies on the surface of TiO2 NPs expanded the absorption band edge and enhanced the electrical conductivity as well as the charge transportation on the catalytic surface. It indicates that the B-TiO2 NPs/ZnO NCAs-CC composite is beneficial to the improvement of the photoelectrochemical (PEC) activity.

A polyacrylic acid (PAA)/gelatin (Gela)/polyvinyl alcohol (PVA) hydrogel was prepared by copolymerization, cooling, and freezing/thawing methods. This triple-network (TN) structure hydrogel displayed superior mechanical properties, low swelling ratio and self-healing properties. The superior mechanical properties are attributed to the triple helix association of Gela and PVA crystallites by reversible hydrogen bonding. The characterization results indicated that the fracture stress and the strain were 808 kPa and 370% respectively, while the compression strength could reach 4443 kPa and the compressive modulus was up to 39 MPa under the deformation of 90%. The hydrogen bonding in PVA contributed to maintain and improve the self-healing ability of hydrogels. Every type of hydrogels exhibited a higher swelling ratio under alkaline conditions, and the swelling ratios of PAA, PAA/PVA and PAA/Gela hydrogels were 27.71, 12.30 and 9.09, respectively. The PAA/Gela/PVA TN hydrogel showed the lowest swelling ratio (6.57) among these hydrogels. These results indicate that the novel TN hydrogels possess good environmental adaptability and have potential applications in the biomedical engineering and sensor field.

In order to effectively improve the accuracy of identifying the gait pattern of wearable sensing data, this paper proposes a new model for deep learning gait mode discrimination that integrates convolutional neural network and long short-term memory neural network, which makes full use of the convolutional neural network to obtain the most local spatial characteristics of data and the long short-term memory neural network to obtain the inherent characteristics of the data, and effectively excavates the hidden high-dimensional, nonlinear, time-space gait characteristics of random wearable sensing timing gait data that are closely related to gait pattern changes, to improve the classification performance of gait mode. The effectiveness of the proposed model in this paper is evaluated using the HAR dataset from University of California UCI database. The experiment results showed that the proposed model in this paper can effectively obtain the time-space gait characteristics embedded in the wearable sensor gait data, and the classification accuracy can reach 91.45%, the precision rate 91.54%, and the recall rate 91.53%, and the classification performance is significantly better than that of the traditional machine learning model, which provides a new solution for accurately identifying the gait mode of wearable sensor data.

Wound infection and poor wound healing are the major challenges of wound treatment. Antibiotic drug treatment is the effective way to inhibit wound infection. It is necessary to achieve sustained release of antibiotics to get a longer treatment for wound infection. The double network hydrogels based on liposome, polyethylene glycol (PEG)

A novel multichannel dilated convolution neural network for improving the accuracy of human activity recognition is proposed. The proposed model utilizes the multichannel convolution structure with multiple kernels of various sizes to extract multiscale features of high-dimensional data of human activity during convolution operation and not to consider the use of the pooling layers that are used in the traditional convolution with dilated convolution. Its advantage is that the dilated convolution can first capture intrinsical sequence information by expanding the field of convolution kernel without increasing the parameter amount of the model. And then, the multichannel structure can be employed to extract multiscale gait features by forming multiple convolution paths. The open human activity recognition dataset is used to evaluate the effectiveness of our proposed model. The experimental results showed that our model achieves an accuracy of 95.49%, with the time to identify a single sample being approximately 0.34 ms on a low-end machine. These results demonstrate that our model is an efficient real-time HAR model, which can gain the representative features from sensor signals at low computation and is hopeful for the effective tool in practical applications.

All kinds of commercially available wound dressings are clinically used as fleshly obstacles and therapeutic materials in opposition to microbial incursion. Few researches focused on effective-bleeding and anti-bacteria at the same time. In order to better solve this problem, two hydrogels were synthetized in this study. One is phosphate buffer solution-activated dopamine-modified-γ-poly glutamic acid (PBS-PD) hydrogel, the other one is cirsium setosum extracts-activated dopamine-modified-γ-poly glutamic acid (CSE-PD) hydrogel. The two hydrogels are prepared by applying an enzyme-catalyzed crosslinking means in the presence of horseradish peroxidase (HRP) and hydrogen peroxide (H2O2). The chemical structures were characterized through 1H-NMR and FT-IR. In conclusion, both PBS-PD and CSE-PD hydrogels exhibit superior tissue adhesion properties, and remarkable anti-infection quality. In addition, these two hydrogels manifest prominent hemostatic efficiency. The bio adhesion performance can achieve 30 kPa, meanwhile the CSE-PD hydrogels show good germicidal properties, and the antibacterial rate can reach 98%. The hydrogels could reduce blood loss without any obvious side effect, and present a new prospect in the field of hemostasis rapidly.

Herein, we exploit the unique structure, high surface area and porous structure of covalent triazine polymers (CTP) for efficient and targeted drug delivery. We have designed and synthesized a nano-covalent triazine polymer (NCTP) by using Friedel–Crafts reactions and utilized it as a drug carrier for controlled release. The salient features of as-prepared NCTP include excellent dispersibility in physiologic solution and structural stability. Furthermore, we have achieved excellent loading of doxorubicin (DOX), an anticancer drug, onto the NCTP by utilizing the π–π interactions and hydrophobic nature. The toxicity of as-prepared NCTP was assessed by CaSki and HeLa cells, and high efficacy in vitro against both types of cells has been demonstrated.

Purpose. Group B Streptococcus (GBS) is one of the major pathogens in severe materno-neonatal infections. We aimed to describe the clinical and molecular characteristics of GBS isolates causing infections in 45 maternal and 50 neonatal subjects, collected from eight healthcare centres in mainland China over the period 2010– 2017. Methodology. The phenotypic and genotypic features of the GBS isolates, including capsular polysaccharide (cps) serotypes, pilus island (PI) genes and antibiotic resistance profiles and genes, were characterized by both conventional and molecular methods. The clonal relationship between these strains was investigated using multilocus sequence typing (MLST). Results. Of the 95 isolates, the predominant serotypes were III (51, 53.7 %), V (13, 13.7 %) and Ib (13, 13.7 %). All GBS strains carried at least one pilus island, with 32.6 % carrying PI-2b and 67.4 % PI-2a, singly or in combination. The most frequently-detected pilus island pattern was the combination of PI-1 and PI-2a, accounting for 56.8 % (54 isolates), followed by PI-1 combined with PI-2b (28, 29.5 %), PI-2a (10, 10.5 %) and PI-2b (3, 3.2 %). The strains were classified into 17 individual sequence types, and further clustered into six clonal complexes (CCs). A high prevalence of CC17/PI-1 and PI-2b (17, 34.0 %) was detected in 50 GBS isolates causing neonatal infections. No strain was resistant to penicillin, ampicillin, ceftriaxone or vancomycin, whereas 78.9, 76.8 and 81.5 % were resistant to erythromycin, clindamycin and tetracycline, respectively. Conclusion. Our study highlights the high genotypic diversity of GBS strains causing materno-neonatal infections, and the CC17/PI-1 and PI-2b sublineages should be noted in neonatal infections.

A novel type of large reticulation, three-dimensional structure of a coal–water slurry dispersant was designed and synthesized, which was mainly used to test the Xinjiang Zhundong coal with abundant reserves and poor slurrying performance. The same types of three dispersants (TIA-1, TIA-2, and TIA-3) were made by adjusting the amount of tannic acid (TA). Commercial NDF dispersant is used for comparison. TA molecules were linked into reticulation by a linker (1,6-dibromohexane) and then modified with 2-acrylanmido-2-methylpropanesulfonic acid and itaconic acid on this reticulated structure. The structure of TIA was confirmed by Fourier transform infrared spectroscopy and 1H nuclear magnetic resonance. The rheology and stability indicated that the optimal amount of this dispersant was 0.1 wt %, and its pulping concentration was increased to 59 wt %. The dispersants of TIA-1, TIA-2, and TIA-3 comparative tests demonstrated that TIA-1 exhibited excellent stability and rheology, reducing the dosage of the disp...

We fabricated pH and light dual-responsive adsorption materials which could induce the transition of surface wettability between hydrophobicity and hydrophilicity by using ATRP. The structure and morphology of adsorption materials were confirmed by ATR-FTIR, XPS, TGA and SEM. It showed that the modified cellulose (CE)-based foam was hydrophobic, which can adsorb a range of oils and organic solvents in water under pH = 7.0 or visible light irradiation (λ > 500 nm). Meanwhile, the wettability of robust CE-based foam can convert hydrophobicity into hydrophilicity and underwater oleophobicity under pH = 3.0 or UV irradiation (λ = 365 nm), giving rise to release oils and organic solvents. Most important of all, the adsorption and desorption processes of the modified CE-based foam could be switched by external stimuli. Furthermore, the modified CE-based foam was not damaged and still retained original performance after reversible cycle repeated for many times with variation of surface wettability. In short, it indicates that CE-based foam materials with switchable surface wettability are new responsive absorbent materials and have owned potential application in the treatment of oil recovery.

In this study, a highly efficient and eco-friendly porous cellulose-based aerogel was synthesized by grafting polyethyleneimine onto quaternized cellulose (PQC) to remove the anionic dye Congo Red (CR). The prepared aerogel had a good flexibility and formability. The adsorbents were characterized by scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy and elemental analysis. The results showed that there were many amino groups on CE/PQC aerogel and the structure was porous, which increased the adsorption capacity. The effects of initial concentration, adsorbent dose, contact time, temperature, and pH on the dye sorption were all investigated. The adsorption mechanism was also explored, including adsorption kinetics, adsorption isotherms and thermodynamic studies of adsorption. The results showed that the adsorption kinetics and isotherms fitted the pseudo-second-order kinetic model and Langmuir isotherm, respectively. The Langmuir isotherm revealed that the maximum theoretical adsorption capacity of the aerogels for CR was 518.403 mg g−1. The thermodynamic parameters including Gibbs free energy change (ΔG0), enthalpy change (ΔH0) and entropy change (ΔS0), showed the adsorption process was exothermic and spontaneous. These results imply that this new absorbent can be universally and effectively used for the removal of dyes from industrial textile wastewater.

A novel eco-friendly porous adsorbent of cellulose (CE)/chitosan (CS) aerogel was prepared through sol-gel process and freeze-drying to remove Congo Red (CR). A series of aerogels were prepared by adjusting the mass ratios of CE and CS. Composite aerogels were characterized by Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). SEM images showed that it was possible to change the structure of the aerogel by adjusting the amount of chitosan. The effects of dosage of chitosan, initial pH, temperature, adsorbent dosage, contact time, and initial dye concentration on adsorption capacities for CR were studied in detail. Batch adsorption studies showed that aerogel exhibited maximum removal efficiency to CR at a composite ratio of 1:3 and dosage of 2.5 g/l. CE/CS aerogel had excellent adsorption capacities for CR at a pH range of 3-11, which indicated stability of the aerogel in both acidic and alkaline conditions. CR adsorption on the composite aerogel fitted pseudo-second-order kinetics and Langmuir isotherm. The Langmuir isotherm model revealed that the maximum theoretical adsorption capacity of this material for CR was 381.7 mg/g at pH 7.0 at 303 K for 24 h. The adsorption mechanism included electrostatic and chemical interactions. The results indicated that the adsorption capacity of CE/CS aerogels was higher than the other chitosan composites adsorbents.

Metal-free triple conducting polymers were designed as 3D layered independent unit structure. The as-prepared PDA@CNNS-PANI@CC showed an enhanced photocatalytic activity by the photo-degradation of Rhodamine B (RhB) under visible light. Moreover the recyclable PDA@CNNS-PANI@CC photocatalyst retain ∼78.57% of the activity after 3-cycle reuse, which shows higher stability than others. Compared with the traditional powder photocatalyst, the novel structure has a perfect recyclability and it is beneficial to save the cost and further approach the industrialization of photocatalytic degradation of organic pollutants.

In this work, a CoPi-decorated type II heterojunction composed of one-dimensional (1D) ZnO nanorod arrays (NRAs) coated with two-dimensional (2D) carbon nitride (g-C3N4) was successfully prepared and used as photoanode. CoPi has been speculated to be a mixture of amorphous compound and two cobalt-based compounds: Co3(PO3)6·14H2O and Co(H2PO2)2·6H2O. The advanced bi-functional CoPi acts like a shelter, effectively inhibiting the photocorrosion of CNNS/ZnO NRAs and providing a faster hole transfer channel. Synergistic effects at the interface of the heterojunction efficiently improve the separation of charge carriers from photoexcited g-C3N4 nanosheets to the ZnO nanorods. Photocurrent density is also greatly enhanced by loading CoPi on CNNS/ZnO NRAs heterojunction. The maximum photocurrent density (2.45 mA cm-2 at 1.23 V vs. RHE) generated from CoPi(10)-CNNS(600)/ZnO nanorods is about 10.2 times greater than that of pristine ZnO nanorods (0.24 mA cm-2 at 1.23 V vs. RHE) and 2.5 times higher than that of CNNS(800)/ZnO (0.95 mA cm-2 at 1.23 V vs. RHE). The further increase of photoelectrocatalytic performance may be attributed to CoPi relieving the charge accumulation at the semiconductor/electrolyte, which decreases the electron-hole recombination rate.

In this study, we prepared a novel triple-network (TN) structure hydrogel composed of polyacrylic acid (PAA), agar and polyvinyl alcohol (PVA). The obtained TN hydrogel has a superior mechanical property as well as self-healing property feature. In the TN hydrogel system, PAA-Fe3+ polymer mainly providing hydrogel self-healing properties by the ionic coordinates between COO− and Fe3+ as the first network, while, agar and PVA polymers gel mainly providing hydrogel high mechanical properties as the second and third network. The structure of TN the hydrogel can be controlled by adjusting the content of Fe3+ and composition in the three polymers. When 1.5 wt% Fe3+ in the TN hydrogels, the PAA/Agar/PVA TN hydrogels possess high mechanical strength, the fracture strain and fracture stress were 497% and 450 kPa, respectively, and the compression strength reached up to 1337 kPa under the compression deformation of 80%. Besides, the TN hydrogels exhibited excellent self-healing ability, when healed 72% at tensile stress and 84% at tensile strain after 24 h without adding any solvent or additive. The research offers a novel design strategy to improve mechanical strength and self-healing ability of hydrogels by controlling the compositions and interactions in the three networks.