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Light detection and ranging (LiDAR) offers high-precision, 3D information, and the ability to rapidly acquire data, giving it a significant advantage in timely resource monitoring. Currently, LiDAR is widely utilized in land-cover classification tasks. However, the complexity and uneven distribution of land-cover types in rural and township settings pose additional challenges for fine-scale classification. Although the geometric features of LiDAR can provide valuable insights and have been extensively explored, distinguishing between objects with similar 3D characteristics has considerable room for improvement, particularly in complex scenarios where the introduction of additional attribute information is necessary. To address these challenges, this work proposes the integration of solar-induced chlorophyll fluorescence (SIF) features to assist and optimize LiDAR data for land-cover classification, leveraging the sensitivity of SIF to vegetation physiological characteristics. Moreover, a multi-stage classification strategy is introduced to enhance the utilization of SIF information. The implementation of this approach achieves a maximum classification accuracy of 92.45%, yielding satisfactory results with low computational costs. This outcome validates the feasibility of applying SIF information in land-cover classification. Furthermore, the results obtained through the multi-stage classification strategy demonstrate improvements ranging from 6.65% to 9.12% compared with land-cover classification relying solely on LiDAR, effectively highlighting the optimization role of SIF in enhancing LiDAR-based land-cover classification, particularly in complex rural and township environments. Our approach offers a robust framework for precise and efficient land-cover classification by leveraging the combined strengths of LiDAR and SIF. [ABSTRACT FROM AUTHOR]

Zr:Ho:LiNbO3 crystals with different concentrations of Zr4+ were prepared by Czochralski method. The internal structure changes and the occupancy of doped ions were analyzed by X-ray diffraction (XRD). The effective segregation coefficient was analyzed by inductively coupled plasma atomic emission spectrometer (ICP-AES), and the optical homogeneity was analyzed by birefringence gradient method. The experimental results show that doping does not change the inherent structure of the crystal, the threshold concentration of Zr4+ is 1 mol%, and the occupation of Zr4+ changes before and after the threshold concentration. The effective separation coefficient of Zr4+ and Ho3+ decreases with the increase of ZrO2 concentration. The optical homogeneity of the crystal will increase with the increase of ZrO2 concentration, and the optical homogeneity of the crystal is strongest when the concentration of ZrO2 reaches the maximum (4 mol%). In this study, a series of Zr:Ho:LiNbO3 crystals of different Zr ions doped concentrations were grown using the Czochralski method. The defect structure of different Zr ions concentrations crystals is analyzed using X-ray diffraction mode. The effects of Zr ions concentrations changes on the concentration of doping elements and the segregation coefficient were investigated using ICP. The optical uniformity of Zr:Ho:LiNbO3 crystals with different concentrations of Zr4+ has been analyzed by birefringence gradient method. [ABSTRACT FROM AUTHOR]

Food poisoning caused by eating contaminated food remains a threat to global public health. Making the situation even worse is the aggravated global environmental pollution, which poses a major threat to the safety of agricultural resources. Food adulteration has been rampant owing to negligent national food safety regulations. The speed at which contaminated food is detected and disposed of determines the extent to which consumers' lives are safeguarded and agricultural economic losses are prevented. Micro/nanomotors offer a high-speed mobile loading platform that substantially increases the chemical reaction rates and, accordingly, exhibit great potential as alternatives to conventional detection and degradation techniques. This review summarizes the propulsion modes applicable to micro/nanomotors in food systems and the advantages of using micro/nanomotors, highlighting examples of their potential use in recent years for the detection and removal of food contaminants. Micro/nanomotors are an emerging technology for food applications that is moving toward mass production, simple preparation, and important functions. [ABSTRACT FROM AUTHOR]

Smart electroactive materials that can dynamically regulate stem cell fate without external stimuli have fascinated increasing attention. Meanwhile, noninvasive electrical stimulation has emerged as a less restrictive approach, generating considerable interest in its potential biomedical applications. The intricate interplay between cells and materials within complex microenvironments includes encompassing substrate response, ion exchange, and membrane potential alterations. However, the mechanisms by which smart materials influence stem cells have yet to be fully elucidated. Herein, electrospinning technology is utilized to fabricate bone‐mimicking microenvironments comprising disordered and highly oriented polyvinylidene fluoride (PVDF) nanofibers. The aligned annealed PVDF (AA) and random annealed PVDF (RA) membranes present high fractions of β‐phase. By comparing the osteogenic ability, calcium activity, and F‐actin distribution of bone marrow‐derived mesenchymal stem cells (BMSCs) cultured with these PVDF nanofibers, it is proposed that the stem cells autonomously regulate their differentiation by remodeling the cytoskeleton on the electrospun membranes. Electrical stimulation, more adhesion area, and active calcium influx support the greater osteogenesis of BMSCs on RA than AA. This mechanism can provide a basic theory for the design and preparation of bone tissue engineering scaffolds and contribute to the further study of cells and microenvironments. [ABSTRACT FROM AUTHOR]

With the escalating environmental and health concerns over petroleum‐based plastics, sustainable and biodegradable cellulosic materials are a promising alternative to plastics, yet remain unsatisfied properties such as fragility, inflammability and water sensitivity for practical usage. Herein, we present a novel dual‐network design strategy to address these limitations and fabricate a high‐performance cellulosic composite bioplastic metafilm with the exceptional mechanical toughness (23.5 MJ m−3), flame retardance, and solvent resistance by in situ growth of cyclotriphosphazene‐bridged organosilica network within bacterial cellulose matrix. The phosphorus, nitrogen‐containing organosilica network, verified by the experimental and theoretical results, plays a triple action on significantly enhancing tensile strength, toughness, flame retardance and water resistance of composite bioplastic metafilm. Furthermore, cellulosic bioplastic composite metafilm demonstrates a higher maximum usage temperature (245 °C), lower thermal expansion coefficient (15.19 ppm °C−1), and better solvent resistance than traditional plastics, good biocompatibility and natural biodegradation. Moreover, the composite bioplastic metafilm have a good transparency of average 74 % and a high haze over 80 %, which can serve as an outstanding substrate substitute for commercial polyethylene terephthalate film to address the demand of flexible ITO films. This work paves a creative way to design and manufacture the competitive bioplastic composite to replace daily‐used plastics. [ABSTRACT FROM AUTHOR]

With the escalating environmental and health concerns over petroleum‐based plastics, sustainable and biodegradable cellulosic materials are a promising alternative to plastics, yet remain unsatisfied properties such as fragility, inflammability and water sensitivity for practical usage. Herein, we present a novel dual‐network design strategy to address these limitations and fabricate a high‐performance cellulosic composite bioplastic metafilm with the exceptional mechanical toughness (23.5 MJ m−3), flame retardance, and solvent resistance by in situ growth of cyclotriphosphazene‐bridged organosilica network within bacterial cellulose matrix. The phosphorus, nitrogen‐containing organosilica network, verified by the experimental and theoretical results, plays a triple action on significantly enhancing tensile strength, toughness, flame retardance and water resistance of composite bioplastic metafilm. Furthermore, cellulosic bioplastic composite metafilm demonstrates a higher maximum usage temperature (245 °C), lower thermal expansion coefficient (15.19 ppm °C−1), and better solvent resistance than traditional plastics, good biocompatibility and natural biodegradation. Moreover, the composite bioplastic metafilm have a good transparency of average 74 % and a high haze over 80 %, which can serve as an outstanding substrate substitute for commercial polyethylene terephthalate film to address the demand of flexible ITO films. This work paves a creative way to design and manufacture the competitive bioplastic composite to replace daily‐used plastics. [ABSTRACT FROM AUTHOR]

Biophysical and biochemical vegetation parameters are important indicators for quantitatively monitoring vegetation growth status and ecosystem. Compared to hyperspectral data, the emergence of ultraspectral remote sensing technology supports the acquisition of thousands of more narrow bands in near-infrared spectrum. It is helpful to capture more detailed vegetation spectral features, thereby providing more accurate quantitative inversion. However, there are still many unknowns in utilizing ultraspectral sensors for vegetation biochemical and biophysical parameters inversion, particularly in extracting meaningful inversion information from thousands of spectral bands. Here, we discuss the potentiality, efficiency and accuracy of the ultraspectral sensor AisaIBIS in this field. Firstly, we conducted sensitivity analysis based on simulated sensor dataset and the PROSAIL model to determine the vegetation parameters suitable for inversion. Secondly, in order to enhance the inversion efficiency and reduce the effects of multicollinearity in ultraspectral data, we proposed the stepped asymptotic optimization strategy that combined random forest (RF) and Gaussian process regression (GPR-BAT) methods for dimensionality reduction. Lastly, using experimental data, we compared the inversion accuracy between traditional band selection methods and our proposed method, thereby validating the application potential of ultraspectral sensors. The experimental results indicate that leaf area index (LAI), chlorophyll content, and brown pigment are the most sensitive parameters to the spectral information and are suitable for inversion. Based on the stepped asymptotic optimization strategy, we effectively avoid incomplete information extraction caused by high correlation and spectral redundancy, achieving optimal bands covering the entire spectrum of the sensor. The LAI inversion shows a correlation of 0.691 and an RMSE of 1.955 with the original data, outperforming the accuracy of the traditional band selection methods RF and principal component analysis (PCA). Moreover, the inversion time has decreased by approximately 66% after the dimensionality reduction. This study illustrates the application value of monitoring vegetation parameters by ultraspectral sensor. [ABSTRACT FROM AUTHOR]

Background: Bladder cancer (BLCA) is a malignant tumor occurring in bladder mucosa. Metadherin (MTDH) has been implicated in tumor progression; however, its molecular biological mechanisms in BLCA remain unclear. Materials and Methods: Cell functions were tested after BLCA cells were transfected by both short hairpin RNAs and small interfering RNAs to silence MTDH. Furthermore, in-house RNA sequencing (RNA-seq) was performed with T24 cells after the knockdown of MTDH. In addition, MTDH-related pathways were explored. Finally, MTDH mRNA and protein expression levels were examined using multiple detection methods in BLCA tissues. Results: MTDH knockdown could largely inhibit cell proliferation, viability, and migration and induce apoptosis of BLCA cells. In-house RNA-seq showed that MTDH knockdown led to extracellular matrix organization and cell division. The integrated analysis showed that the comprehensive expression of MTDH at the mRNA level was 0.47 and that at the protein level was 0.54, based on 11 platforms, including 1485 BLCA and 180 non-BLCA samples. Conclusions: MTDH promotes the growth of BLCA cells through the pathway of cell division. This study provides new directions and biomarkers for future treatment. [ABSTRACT FROM AUTHOR]

The advancement of ultra-hyperspectral imaging technology, exemplified by the AisaIBIS sensor, has enabled a leap from hyperspectral data (hundreds of bands) to ultra-hyperspectral data (thousands of bands). It provides immense potential for precise ground object recognition within intricate scenes. However, the complexities inherent to features of the ground objects, coupled with the copious redundant information within the ultra-hyperspectral data, pose substantial challenges for accurate object recognition. Therefore, this paper proposed a comprehensive framework to explore the optimal precise classification strategy of ultra-hyperspectral data in complex scenes (12 vegetation and non-vegetation classes). (a) Our investigation delves into the influence of diverse feature subsets and a range of machine learning classifiers on the precision of ground objects recognition. The proposed strategy is up to an overall accuracy of 88.44%, effectively avoiding the curse of dimension, and significantly enhancing the capability to recognize the complex ground objects. (b) Furthermore, based on the simulation of hyperspectral images with different spectral resolutions, we compared the classification results of ultra-hyperspectral data (0.11 nm) and the hyperspectral datasets (10 nm, 5 nm, and 1 nm) by machine learning methods. Compared with the hyperspectral datasets, ultra-hyperspectral data improved the classification accuracy by 5.30–6.38%. This substantiates the pronounced advantages of ultra-hyperspectral data in precision land cover classification. This study provides a valuable reference for the application of ultra-hyperspectral data in recognition of complex ground objects scenes, and urban accurate monitoring. [ABSTRACT FROM AUTHOR]

Highlights: Bioinspired directional moisture-wicking electronic skin (DMWES) was successfully realized by surface energy gradient and push–pull effect via the design of distinct hydrophobic-hydrophilic difference. The DMWES membrane showed excellent comprehensive pressure sensing performance with high sensitivity and good single-electrode triboelectric nanogenerator performance The superior pressure sensing and triboelectric performance enabled the DMWES for all-range healthcare sensing, including accurate pulse monitoring, voice recognition, and gait recognition. Electronic skins can monitor minute physiological signal variations in the human skins and represent the body's state, showing an emerging trend for alternative medical diagnostics and human–machine interfaces. In this study, we designed a bioinspired directional moisture-wicking electronic skin (DMWES) based on the construction of heterogeneous fibrous membranes and the conductive MXene/CNTs electrospraying layer. Unidirectional moisture transfer was successfully realized by surface energy gradient and push–pull effect via the design of distinct hydrophobic-hydrophilic difference, which can spontaneously absorb sweat from the skin. The DMWES membrane showed excellent comprehensive pressure sensing performance, high sensitivity (maximum sensitivity of 548.09 kPa−1), wide linear range, rapid response and recovery time. In addition, the single-electrode triboelectric nanogenerator based on the DMWES can deliver a high areal power density of 21.6 µW m−2 and good cycling stability in high pressure energy harvesting. Moreover, the superior pressure sensing and triboelectric performance enabled the DMWES for all-range healthcare sensing, including accurate pulse monitoring, voice recognition, and gait recognition. This work will help to boost the development of the next-generation breathable electronic skins in the applications of AI, human–machine interaction, and soft robots. [ABSTRACT FROM AUTHOR]

Highly sensitive flexible pressure sensors are extensively investigated for various applications, such as electronic skin, human physiological monitoring, and artificial intelligence. However, traditional fabrication technologies are hard to realize the large‐area and mass production of wearable sensing devices. Current trend of miniaturization, systematization, and multifunction has raised the problems of total energy consumption, frequent charging, and reduced usage time. These issues have hindered the progress of wearable sensing electronics. In the light of nanomaterial design, mass production, and facile manufacturing, electrospun piezoelectric pressure sensors offer the best properties of self‐powering, breathability, stretchability, and flexibility, providing ideal interfacing platforms for smart wearables. Tremendous advances have been achieved recently in the high sensitivity, piezoelectric output, composite optimization, and nano‐/microstructure design of nonwoven nanofiber membranes. Nevertheless, how to fulfill real textile‐level integration in consideration of biocompatibility, integration, wearability, geometrical design, multifunction, and systematization remains a big challenge. Therefore, recent progress of piezoelectric pressure sensors from electrospun nanofibers to their fabrics is comprehensively summarized. Plentiful strategies, structure designs, and underlying mechanisms that boost the piezoelectric properties are discussed. Lastly, the challenges and possible solutions for the future electrospinning‐based pressure sensing systems are proposed. [ABSTRACT FROM AUTHOR]

Lidar can effectively obtain three-dimensional information on ground objects. In recent years, lidar has developed rapidly from single-wavelength to multispectral hyperspectral imaging. The multispectral airborne lidar Optech Titan is the first commercial system that can collect point cloud data on 1550, 1064, and 532 nm channels. This study proposes a method of point cloud segmentation in the preprocessed intensity interpolation process to solve the problem of inaccurate intensity at the boundary during point cloud interpolation. The entire experiment consists of three steps. First, a multispectral lidar point cloud is obtained using point cloud segmentation and intensity interpolation; the spatial dimension advantage of the multispectral point cloud is used to improve the accuracy of spectral information interpolation. Second, point clouds are divided into eight categories by constructing geometric information, spectral reflectance information, and spectral characteristics. Accuracy evaluation and contribution analysis are also conducted through point cloud truth value and classification results. Lastly, the spatial dimension information is enhanced by point cloud drop sampling, the method is used to solve the error caused by airborne scanning and single-tree extraction of urban trees. Classification results showed that point cloud segmentation before intensity interpolation can effectively improve the interpolation and classification accuracies. The total classification accuracy of the data is improved by 3.7%. Compared with the extraction result (377) of single wood without subsampling treatment, the result of the urban tree extraction proved the effectiveness of the proposed method with a subsampling algorithm in improving the accuracy. Accordingly, the problem of over-segmentation is solved, and the final single-wood extraction result (329) is markedly consistent with the real situation of the region. [ABSTRACT FROM AUTHOR]

We give several further norm inequalities for sums of bounded linear operators on a complex Hilbert space. These inequalities refine and generalize earlier inequalities. Among other applications, it is shown that for A ∈ B (H) and r ∈ [ 0 , 1 ] , w (A) ≤ 1 2 ‖ A ‖ + 1 2 ‖ | A | r | A ⁎ | r ‖ 1 2 ‖ | A | 1 − r | A ⁎ | 1 − r ‖ 1 2 , which refines a result of Kittaneh (2003) [5]. Here, w (⋅) and ‖ ⋅ ‖ denote the numerical radius and the usual operator norm, respectively. [ABSTRACT FROM AUTHOR]

Somatic variants act as critical players during cancer occurrence and development. Thus, an accurate and robust method to identify them is the foundation of cutting-edge cancer genome research. However, due to low accessibility and high individual-/sample-specificity of the somatic variants in tumor samples, the detection is, to date, still crammed with challenges, particularly when lacking paired normal samples as control. To solve this burning issue, we developed a tumor-only somatic and germline variant identification method (TSomVar) using the random forest algorithm established on sample-specific variant datasets derived from genotype imputation, reads-mapping level annotation and functional annotation. We trained TSomVar by using genomic variant datasets of three major cancer types: colorectal cancer, hepatocellular carcinoma and skin cutaneous melanoma. Compared with existing tumor-only somatic variant identification tools, TSomVar shows excellent performances in somatic variant detection with higher accuracy and better capability of recalling for test datasets from colorectal cancer and skin cutaneous melanoma. In addition, TSomVar is equipped with the competence of accurately identifying germline variants in tumor samples. Taken together, TSomVar will undoubtedly facilitate and revolutionize somatic variant explorations in cancer research. [ABSTRACT FROM AUTHOR]

There is an urgent need for a code which is consistent, efficient, and easy to remember to process the diverse and large data generated in planning, construction, and management of construction and building. Grid selection, coding rules, spatial position information identification, transmission and big data processing about building are stipulated by an encoding method, Beidou grid position coding. This paper proposes a construction building space identification position coding technology to code the construction building that is based on the coding rules of the Beidou grid position code and its good scalability in the field of building spatial identification position coding. The coding is unique, consistent, efficient and easy to remember. The coding rules and its application are introduced in the paper including coding index, code generation, and the corresponding query algorithm. This paper also describes how to verify the corresponding algorithm through engineering experiments. [ABSTRACT FROM AUTHOR]

The energy harvested by an ocean wave energy converter (WEC) can be enhanced by a well-designed wave-by-wave control strategy. One of such superior control methods is model predictive control (MPC), which is a nonlinear constrained optimization control strategy. A limitation of the classical MPC algorithm is its requirement of an accurate WEC dynamic model for real-time implementation. This article overcomes this challenge by proposing a data-driven MPC scheme for wave energy converters. The data-based WEC model is developed by a Gaussian process (encompassing mean predictions and symmetric uncertainties) for a more accurate description of nonlinear and unmodeled system dynamics. A cross-entropy solver for data-driven MPC is employed for rapid, high-performance results, which samples trajectories from Gaussian distributions based on the concept of the symmetry principle. The proposed strategy is verified numerically by simulations which demonstrate its superior performance over a classical complex-conjugate controller. [ABSTRACT FROM AUTHOR]

In this study, hydrophobic sodium alginate/anthocyanin/cellulose nanocrystal indicator films were fabricated by incorporating nanosilica (NS) as a waterproofing layer. The concentrations and formation methods (spraying (S), coating (C), and impregnation (I)) of the NS layer (denoted as NSS, NSC, NSI, respectively) were optimized. The results indicated that the optimum concentration of the NS layer was 5 % at a water contact angle (WCA) 110.5°. Further, Fourier transform infrared spectra showed the presence of Si O Si and Si CH 3 groups in the NSS, NSC, and NSI films, and X-ray diffraction spectra indicated that original structures of these films were disordered. Moreover, the surface morphology, mechanical properties, and light transmission were affected by the NS layer, and the optimal layer was found to be NSI. After 10 days of storage at 100 % humidity, the NSI film exhibited low water vapor adsorption (37.22 g) and permeability (0.1484 g/m·s·Pa·10−11) and a high WCA (110.2°). In addition, the NSI film exhibited a visible color shift with an increasing pH of the buffer solution. A monitoring test of fish freshness showed that the NSI film displayed a distinctive color change corresponding to fish spoilage during 14 days of storage. This indicates that NSI has high potential in indicator film applications. [ABSTRACT FROM AUTHOR]

Lead‐based halide perovskite nanomaterials with excellent optical properties have aroused great attention in the fields of solar cells, light‐emitting diodes, lasing, X‐ray imaging, etc. However, the toxicity of lead prompts researchers to develop alternatives to cut down the usage of lead. Herein, all‐inorganic manganese‐based perovskite derivatives, CsMnCl3 nanocrystals (NCs), with uniform size and morphology have been synthesized successfully via a modified hot‐injection method. These NCs have a direct bandgap of 4.08 eV and a broadband emission centered at 660 nm. Through introducing modicum lead (1%) into the CsMnCl3 NCs, the photoluminescence intensity greatly improves, and the quantum yield (PLQY) increases from 0.7% to 21%. Furthermore, the CsMnCl3:1%Pb NCs feature high‐efficiency of X‐ray absorption and radioluminescence, which make these NCs promising candidates for X‐ray imaging. [ABSTRACT FROM AUTHOR]

Designing wound dressing materials with hemocompatibility, suitable mechanical properties, outstanding hemostatic effects and anti-inflammatory activity is of great practical significance for wound management. Herein, a hemostatic hydrogel loaded with Lycium barbarum L. polysaccharide (LBP)-functionalized ultrathin MMT nanosheets (L-MMT NSs) was fabricated for efficient hemostasis and wound healing. Loading the L-MMT NSs into polyvinyl alcohol (PVA), the obtained P-L-MMT hydrogel exhibited a 3D porous structure with good swelling properties, cytocompatibility, hemocompatibility, and anti-inflammatory activity. Importantly, in vivo investigations demonstrated that the P-L-MMT hydrogel exerts outstanding hemostasis activity in the hemorrhaging mouse liver model and reduces tissue damage caused by inflammation to shorten wound healing time. Altogether, the convenient exfoliation and functionalization of bulk MMT using LBPs make this inexpensive and rising nanostructure more attractive in the application of nanomedicine. Moreover, due to the synergy between hemostasis and anti-inflammation, this newly developed multifunctional P-L-MMT hydrogel represents a promising material in biomedical fields. [Display omitted] • LBPs functionalized ultrathin MMT nanosheets were efficiently obtained via liquid exfoliation. • The L-MMT-loaded PVA hydrogel shows 3D porous structure with good swelling property. • P-L-MMT hydrogel exhibited excellent hemostatic and anti-inflammatory activity. • The healing of inflammation-induced tissue damage in wound was facilitated. [ABSTRACT FROM AUTHOR]

• DEM and Monte Carlo ray tracing are applied to ellipsoidal particle beds. • Impact of particle shape and packing on radiation heat transfer is explored. • Orientation/direction, shielding, and indirect radiation are key factors on RDF. • Oblate particle has the highest radiation absorption capacity. The calculation of radiative heat transfer between particles in particle-based solar systems presents significant challenges in terms of computational cost and accuracy. This study addresses these challenges by employing the discrete element method to generate random particle packings and the Monte Carlo ray tracing method to investigate the influence of particle shape and volume fraction (ϕ) on interparticle radiation transfer and the absorption of incident radiation. The results reveal that, at low volume fractions, the shape and orientation of ellipsoidal particles have a pronounced impact on direct radiative transfer. Oblate particles exhibit the highest average radiation distribution factor (RDF), and the dispersion of RDF data is more prominent for oblate and elongated prolate particles compared to spheres. As ϕ increases to 0.35, the contribution of indirect transfer from neighboring particles becomes significant for oblate particles, resulting in a reduction in the dispersion of RDF data. Furthermore, when ϕ reaches 0.55, the decisive factor in determining RDF becomes the shielding effect of particles positioned between the emitting and receiving particles. The average RDF tends to converge among particles of different shapes, although oblate and elongated prolate particles still exhibit considerably larger RDF dispersion compared to spherical and near-spherical particles. Additionally, the effective absorptivity of the particle bed for incident radiation decreases as the aspect ratio of particles increases at all volume fractions. Moreover, the transmitted fraction demonstrates an exponential relationship with the depth, and beds composed of spherical particles exhibit better radiation transmittance compared to beds containing non-spherical particles. [ABSTRACT FROM AUTHOR]

[Display omitted] • The TiO 2 @MXene/P, N-containing polyimine nanocomposite (TMPNP) is designed. • TMPNP exhibits good contact fire warning and flame position monitoring performance. • The light-powered self-healing and flame retardant properties are achieved. • The TMPNP@Cotton based on IoT technology provides wireless fire warning function. Scalable early fire warning sensors that integrate passive flame-retardant strategies and active fire alarm sensing are highly requirable in diverse areas. However, the single-mode fire response and performance degradation or even malfunction under mechanical damages remain key challenges for current early fire warning sensors. Herein, a self-healable and flame retardant TiO 2 @MXene/P, N-containing polyimine nanocomposite (TMPNP) is designed as repeatable dual-mode fire warning sensors. On the one hand, the TMPNP exhibits a high temperature coefficient of resistance of −2.21 %/℃, which endows nanocomposite with an extraordinarily sensitive non-contacting fire warning performance; on the other hand, the TMPNP demonstrates outstanding fire contact warning features of responsive time being less than 1 s and repeatable alarming response, as well as excellent flame-retardant functionality of LOI reaching up to 32.0 %. Moreover, the TMPNP can be effectively recovered after 30 cutting-and-healing cycles with a healing efficiency of 89.3 % via dynamic imine bonds. Particularly, its flame retardancy and fire warning properties in contact/non-contact mode are well maintained after self-healing. These merits support the scalable assembly TMPNP onto cotton textile to develop a wireless household fire early warning sensor linked to the Internet of Things, contributing to construct fire-safety smart buildings. This work provides a scalable strategy for preparing healable sensitive fire warning sensors, opening up a new opportunity for the practical application of eliminating indoor fire hazards. [ABSTRACT FROM AUTHOR]

Gentiana straminea Maxim. exhibits various biological activities. However, the purification and functions of polysaccharides in Gentiana straminea Maxim. have never been reported. Herein, by proposing a flexible 3D graphene-based decoloration column (3DD column), Gentiana straminea Maxim. polysaccharide (GMP) was high-throughput obtained and its anti-inflammatory activity was investigated. Benefiting from the large macroporous network of 3D NH 2 -graphene oxide hydrogel with selective adsorption towards pigments, the 3DD column exhibits high decoloration ratio (96.41%). In addition, the 3DD column provides superior practical functionality as compared to the traditional approaches, which are time-consuming and need toxic solvents, and exhibiting widespread-application for the purification of polysaccharide from other common plant species. More importantly, the decolored GMP as a natural product has promising anti-inflammatory activity on RAW264.7 cells without negative impact on cell viability. Overall, this work reveals a new functional polysaccharides and provides a flexible approach for polysaccharide decoloration, exhibiting a promising prospect for natural polysaccharides in practical application of pharmaceutical. [Display omitted] • A high-throughput 3D graphene-based decoloration column is proposed. • 3DD column is nondestructive as regards the GMP. • Compared with traditional methods, 3DD column has superior practical functionality. • GMP exhibits excellent anti-inflammatory activity. [ABSTRACT FROM AUTHOR]

Person re-identification with natural language description is a process of retrieving the corresponding person's image from an image dataset according to a text description of the person. The key challenge in this cross-modal task is to extract visual and text features and construct loss functions to achieve cross-modal matching between text and image. Firstly, we designed a two-branch network framework for person re-identification with natural language description. In this framework we include the following: a Bi-directional Long Short-Term Memory (Bi-LSTM) network is used to extract text features and a truncated attention mechanism is proposed to select the principal component of the text features; a MobileNet is used to extract image features. Secondly, we proposed a Cascade Loss Function (CLF), which includes cross-modal matching loss and single modal classification loss, both with relative entropy function, to fully exploit the identity-level information. The experimental results on the CUHK-PEDES dataset demonstrate that our method achieves better results in Top-5 and Top-10 than other current 10 state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Genotype imputation is a statistical method for estimating missing genotypes from a denser haplotype reference panel. Existing methods usually performed well on common variants, but they may not be ideal for low-frequency and rare variants. Previous studies showed that the population similarity between study and reference panels is one of the key factors influencing the imputation accuracy. Here, we developed an imputation reference panel reconstruction method (RefRGim) using convolutional neural networks (CNNs), which can generate a study-specified reference panel for each input data based on the genetic similarity of individuals from current study and references. The CNNs were pretrained with single nucleotide polymorphism data from the 1000 Genomes Project. Our evaluations showed that genotype imputation with RefRGim can achieve higher accuracies than original reference panel, especially for low-frequency and rare variants. RefRGim will serve as an efficient reference panel reconstruction method for genotype imputation. RefRGim is freely available via GitHub: https://github.com/shishuo16/RefRGim [ABSTRACT FROM AUTHOR]

Accompaniment production is one of the most important elements in music work, and chord arrangement is the key link of accompaniment production, which usually requires more musical talent and profound music theory knowledge to be competent. In this article, the machine learning model is used to replace manual accompaniment chords' arrangement, and an automatic computer means is provided to complete and assist accompaniment chords' arrangement. Also, through music feature extraction, automatic chord label construction, and model construction and training, the whole system finally has the ability of automatic accompaniment chord arrangement for the main melody. Based on the research of automatic chord label construction method and the characteristics of MIDI data format, a chord analysis method based on interval difference is proposed to construct chord labels of the whole track and realize the construction of automatic chord labels. In this study, the hidden Markov model is constructed according to the chord types, in which the input features are the improved theme PCP features proposed in this paper, and the input labels are the label data set constructed by the automated method proposed in this paper. After the training is completed, the PCP features of the theme to be predicted and improved are input to generate the accompaniment chords of the final arrangement. Through PCP features and template-matching model, the system designed in this paper improves the matching accuracy of the generated chords compared with that generated by the traditional method. [ABSTRACT FROM AUTHOR]

The last article titled "Building Space Coding Based on Beidou Grid Position Code" proposes a construction building space identification position coding technology to code the construction building that is based on the coding rules of the Beidou grid position code and its good scalability in the field of building spatial identification position coding. The second article titled "A General Matrix Factorization Framework for Recommender Systems in Multi-access Edge Computing Network" integrates the multi-access edge computing network into recommender systems to take fully advantage of base stations and user terminals. B Editorial: b With the rapid development of social economy, human needs have gradually risen from basic survival needs to the pursuit of quality of life, so more and more emerging technologies have emerged. [Extracted from the article]

As a potential technology in weak signal detection (WSD), the chaos theory benefits from its characteristics of the sensitivity to the initial condition and the immunity to the Additive White Gaussian Noise (AWGN). Traditional methods based on chaos theory perform well on single non-variable-frequency signal detection (SNVFSD), which is a common situation in texture flaw detection while it is a rare scenario in the communication field. In this paper, we give a comprehensive analysis of the chaos-based approach for weak signal frequency detection. To better understand the advantages and limitations of the chaos theory, we present the research results for several typical communication scenarios. Specifically, we proposed several chaos-based approaches to get a satisfying performance in the following situations: single variable-frequency signal detection (SVFSD), multiple non-variable-frequency signals detection (MNVFSD), multiple variable-frequency signals detection (MVFSD). To enhance the generalization performance to real application, the critical state's characteristics, Lyapunov Exponents (LE) and Melnikov method are analyzed to employed in these proposed chaos-based approaches. By theoretical analysis and numerical simulations, we study the performance of chaos-based detection systems in terms of SVFSD, MNVFSD, MVFSD. Our results show that these proposed schemes can obtain a satisfying performance in terms of accuracy and robustness, and the extensive simulations demonstrate their effectiveness. [ABSTRACT FROM AUTHOR]

Ovarian cancer is the most lethal gynecological cancer, most patients relapse within 12–24 months, and eventually die, especially platinum-resistant patients. Gene therapy has been one of the most potential methods for tumor treatment. Bone marrow mesenchymal stem cells (BMSCs) have been used for systemic delivery of therapeutic genes to solid tumors. Sodium iodide symporter (NIS) is an intrinsic membrane glycoprotein and can concentrate 131I, which is important for radionuclide therapy and nuclear medicine imaging in recent years. However, the rapid iodine efflux has become a bottleneck for NIS-mediated radionuclide gene therapy. Our previous studies found that the early growth response-1 (Egr1) promoter containing CC(A/T)6GG (CArG) elements had an 131I radiation-positive feedback effect on the NIS gene. Other research showed the synthesized Egr1 promoter containing four CArG elements, E4, was nearly three times as sensitive as the Egr1 promoter. In our study, BMSC-E4-NIS was engineered to express NIS under the control of E4 promoter using lentivirial vectors. After BMSC-E4-NIS implantation, no tumors were seen in BALB/c nude mice and BMSC-E4-NIS did not promote the growth of SKOV3 tumor. BMSCs migrated toward ovarian cancer samples in chemotaxis assays and to ovarian tumors in mice. Using micro-single-photon emission computed tomography/computed tomography (SPECT/CT) imaging, we found that E4 promoter produced a notable increase in 125I uptake after 131I irradiation, the radionuclide uptake is almost three and six times more than Egr1 and cytomegalovirus (CMV) promoters. These studies confirmed the feasibility of using BMSCs as carriers for lentivirus-mediated E4-NIS gene therapy for ovarian cancer. Further research on BMSC-E4-NIS gene therapy for ovarian cancer in vivo will also be carried on, and if successful, this might provide a new adjuvant therapeutical option for platinum-resistant ovarian cancer patients and provide a new method for dynamic evaluation of curative effect. [ABSTRACT FROM AUTHOR]

Graphdiyne (GDY) exhibits great application potential. However, large-yield and scalable exfoliation of few-layered GDY nanosheets (GDYNSs) remains a huge challenge. Here, we reported a liquid-phase, facile and efficient hydrothermal exfoliation approach to produce mono- or few-layered GDYNSs, which can achieve 82 wt% of high actual yield and 5 mg/ml concentration. The GYDNSs were then dispersed in mineral oil (MO) to act as heat transfer nano fluids for the first time. Typically, at a fraction of 1.0 vol %, the nano-oils showed significantly enhanced thermal conductivity ((K eff / K 0)-1) %, up to ∼122%. The low filler fraction and high thermal conductivity enhancement for this GYDNSs/MO nano-oil demonstrates several thermal transfer applications of heavy equipment. Our work provides reasonable insight into the exfoliation and thermal-fluid applications of GDYNSs. [Display omitted] • Ultrathin graphdiyne nanosheets (GDYNSs) are synthesized by hydrothermal method. • The GDYNSs oil-based nanofluids are prepared for the first time. • The nanofluids with an enhanced thermal conductivity ((k eff / k 0)-1) % of ∼122%. [ABSTRACT FROM AUTHOR]

At present, unmanned aerial vehicles (UAVs) have been widely used in communication systems, and the fifth-generation wireless system (5G) has further promoted the vigorous development of them. The trajectory planning of UAV is an important factor that affects the timeliness and completion of missions, especially in scenarios such as emergency communications and post-disaster rescue. In this paper, we consider an emergency communication network where a UAV aims to achieve complete coverage of potential underlaying device-to-device (D2D) users. Trajectory planning issues are grouped into clustering and supplementary phases for optimization. Aiming at trajectory length and sum throughput, two trajectory planning algorithms based on K-means are proposed, respectively. In addition, in order to balance sum throughput with trajectory length, we present a joint evaluation index. Then relying on this index, a third trajectory optimization algorithm is further proposed. Simulation results show the validity of the proposed algorithms which have advantages over the well-known benchmark scheme in terms of trajectory length and sum throughput. [ABSTRACT FROM AUTHOR]

Background: Congenital heart disease is a leading cause of death in newborns and infants. The feasibility of fetal cardiac surgery is linked to extracorporeal circulation (ECC); therefore, cardioplegic solutions need to be effective and long-lasting.Methods: Eighteen pregnant sheep were divided into an ECC-only group, St. Thomas' Hospital cardioplegic solution (STH1) group (STH group), and HTK preservation solution (Custodiol®) group (HTK group). Markers of myocardial injury including troponin I (cTnI), troponin T (cTnT) and creatine kinase myocardial band (CKMB) were measured at specific time points (T1: pre-ECC, T2: 30 min of ECC, T3: 60 min of ECC, T4: 60 min post-ECC, T5: 120 min post-ECC). Myocardial tissue was removed from the fetal sheep at T5, and apoptosis was detected by TUNEL staining.Results: Changes in the serum cTnI, cTnT and CKMB concentrations were not significantly different among the three groups before and during the ECC(T1,T2,T3). At 60 min after ECC shutdown(T4), cTnI and cTnT concentrations were significantly higher in the STH group than before the start of ECC. The concentration of cTnI was higher in the STH group than in the HTK and ECC-only groups. The concentration of cTnT was higher in the STH group than in the ECC-only group. At 120 min after ECC shutdown(T5), cTnI and cTnT concentrations were significantly higher in the ECC and HTK groups than before the start of ECC, and CKMB concentration was significantly higher in STH and HTK groups. The concentrations of cTnT, cTnI and CKMB was higher in the STH group than in the HTK and ECC-only groups. The number of TUNEL-positive cells in the HTK and STH groups was higher than in the ECC-only group. The number of TUNEL-positive cells in the STH group was higher than in the HTK group. There was no statistically significant difference among the groups in the heart rate and mean arterial pressure after ECC.Conclusion: The HTK preservation solution was significantly better than STH1 in reducing the release of cardiomyocyte injury markers and the number of apoptotic cells in fetal sheep ECC. Fetal sheep receiving ECC-only had an advantage in all indicators, which suggests ECC-only fetal heart surgery is feasible. [ABSTRACT FROM AUTHOR]

Multispectral lidar has become a promising technology with the rise in capability of 3-D spectral imaging. However, the precise acquisition of spectral information is interfered by measurement geometry, namely, incidence angle and detection distance. These issues may cause discrepancy within the spectral information, thus limiting the classification capabilities of multispectral lidar. To fill this gap, a hue–saturation–intensity (HSI) color space-based method for multispectral lidar classification is proposed in this study. The proposed scheme does not require radiometric calibration, as the HSI color space is robust to spectral intensity variations within a single target. In this method, spectral data are transformed from red–green–blue (RGB) color space to HSI color space. The three components of the HSI color space are inputted for the classification. Then, a reference target-based radiometric calibration is conducted for comparison. The complex indoor scene and the random forest classifier are used for the validation. The classification results of using raw RGB data, raw HSI data, calibrated RGB data, and calibrated HSI data are compared. Results show that the raw HSI data outperform the raw RGB data in terms of classification accuracy. In particular, the raw HSI data can correct the classification error caused by the measurement geometry more effectively than the calibrated RGB data. The improvement resulting from using the HSI color space is demonstrated by both the three-wavelength multispectral lidar and the 32-channel multispectral lidar. That indicates that HSI color space is a promising tool for enhancing the classification capability of multispectral lidar. [ABSTRACT FROM AUTHOR]

This study investigates the waterproof layer formed by beeswax (BW) to improve the hydrophobicity of sodium alginate/black soybean seed coat anthocyanin/cellulose nanocrystal indicator films. The concentrations of BW and the fabrication method of the waterproof layer, including spraying, coating (CO), and soaking, were optimized. The results showed that the optimal concentration of BW in the waterproof layer was 5% owing to its high water contact angle of 111.5°. Different methods of fabricating waterproof layers with BW led to the formation of particles of different sizes on the microscopic film surface. Hydrophobic films with a waterproof layer of BW-CO had high transmittance and pH sensitivity, ensuring the basic properties of indicator films. Meanwhile, they exhibited excellent water barrier properties based on the water contact angle, water vapor adsorption, water vapor permeability, water content and water solubility. In particular, these films remained highly hydrophobic after 10 days of storage at 100% humidity, with a water contact angle of 108.3°. The findings indicated that hydrophobic sodium alginate/black soybean seed coat anthocyanin/cellulose nanocrystal indicator films were prepared using BW, which improved their potential application in intelligent food packaging. [Display omitted] • Achieve hydrophobic modification of hydrophilic sodium alginate indicator films. • Waterproof layer coated with beeswax (BW-CO) provides hydrophobicity. • BW-CO layer with high transparency had no negative effect on pH sensitivity of film. • BW-CO layer had excellent water barrier properties. • Strong hydrophobicity of BW-CO layers were maintained for 10 days. [ABSTRACT FROM AUTHOR]

• CT-based adipose distribution pattern has great predictive value for HCC prognosis. • Comprehensive analysis of diverse adipose depots affirmed VSR's prognostic value. • VSR exhibited consistency and no publication bias across relevant studies. The present meta-analysis aimed at identifying potential prognostic indicators associated with adipose distribution patterns for predicting the survival outcomes of patients diagnosed with hepatocellular carcinoma (HCC). A systematic retrieve was performed to identify studies investigating the association of adipose distribution patterns and the prognosis of HCC from the inception of PubMed, Embase, Cochrane Library, and Web of Science databases to May 25, 2023. The Newcastle–Ottawa scale was applied to assess the quality of included studies. The hazard ratios (HRs) and 95 % confidence intervals (CIs) of adipose distribution parameters of visceral, subcutaneous, and intermuscular adipose tissue were extracted. Univariate and multivariable meta-analyses were performed by Stata 12.0 to evaluate the relationship between these factors and overall survival (OS) and recurrence-free survival (RFS). A total of 31 studies, comprising 7021 patients, including 2456 patients with HCV and 1466 patients with HBV were included. The pooled results indicated that only high visceral to subcutaneous adipose area ratio (VSR) (univariate analysis of OS: HR = 1.42, 95 % CI = 1.28–1.58, P < 0.001; multivariate analysis of OS: HR = 1.45, 95 % CI = 1.27–1.65, P < 0.001; univariate analysis of RFS: HR = 1.30, 95 % CI = 1.08–1.56, P = 0.006; multivariate analysis of RFS: HR = 1.36, 95 % CI = 1.10–1.67, P = 0.004) was both related to worse OS and RFS, with no significant heterogeneity observed. Pretreatment VSR, as the sole parameter among adipose distribution-related factors exhibiting independent and stable associations with OS and RFS in patients with HCC, may hold promise as a potential prognostic factor for HCC. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc network (VANET) is expected one of promising network forms for intelligent transportation system which supports road safety applications, in-vehicle entertainment and arriving automatic driving. Establishing and maintaining stable connections in VANETs are challenging on account of the high mobility of vehicles, dynamic vehicle topology, and time-varying vehicle density. Clustering can provide scalability and reliability for VANETs by grouping vehicles with hierarchical structures. However, keeping cluster stable became a hard nut to crack due to high vehicle speed and unpredictable driving pattern. Recent rapid development of artificial intelligence (AI) provided an innovative solution for this situation. In this paper, a Naive Bayes Classifier based driving habit prediction scheme for stable clustering is proposed, briefly named NBP. According to driving speed and overtaking decisions, vehicles are classified into two alignments with different driving habit. Specifically, Naive Bayes classifier perform driving habit prediction through several relative independent factors, such as relative velocity, vehicle type, number of lanes traveled. The cluster head candidates will be chosen from alignment with mild driving pattern which will benefit for stable clusters. Combined with clustering design, the proposed method has been proven effective for stable clustering in VANET based on the real data of highways in California. [ABSTRACT FROM AUTHOR]

This article focuses on the problem of scheduling the optimal paths of multiple mobile elements (e.g. robots, vehicles, etc.) to minimize the travel distance and balance the energy consumption and the data gathering latency in wireless sensor networks for smart cities. To partition the network for the multiple mobile elements and compute the trajectories of the multiple mobile elements, we utilize the sensor's communication range and construct a multiple mobile elements scheduling problem. A heuristic mobile data gathering approach is proposed to solve this problem, which includes the following three steps. The sensor nodes are preliminarily partitioned into four levels, and then the clusterheads are further partitioned, and the traveling tour is scheduled for each cluster. After the first two steps, all the sensor nodes are partitioned reasonably for the multiple mobile elements. In the last step, the traveling tour is scheduled for each cluster, and the meeting point of each clusterhead is determined. We compare the proposed heuristic mobile data gathering with the existing approaches. The results indicate that the travel distance and the data gathering latency are reduced significantly, which further validates that the communication range is beneficial to minimize the travel distance. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LUAD), the main subtype of non-small cell lung cancer, is known to be regulated by various microRNAs (miRs/miRNAs); however, the role of miR-198-5p in LUAD has not been clarified. In the present study, the clinical value of miR-198-5p in LUAD and its potential molecular mechanism was evaluated. miR-198-5p expression was examined by reverse transcription-quantitative PCR (RT-qPCR) in 101 paired LUAD and adjacent normal lung tissues. Subsequently, the miR-198-5p expression level was determined from microarray data from the Gene Expression Omnibus, ArrayExpress and by meta-analyses. Furthermore, the target mRNAs of miR-198-5p from 12 miRNA-mRNA predictive tools were intersected with The Cancer Genome Atlas (TCGA)-based differentially expressed genes. In addition, Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to determine the possible mechanism of miR-198-5p in LUAD. The Search Tool for the Retrieval of Interacting Genes/Proteins database was employed to construct a protein-protein interaction network among the potential target genes of miR-198-5p. The results showed that miR-198-5p expression was lower in LUAD tissues than in adjacent non-cancerous lung tissues (4.469±2.495 vs. 5.301±2.502; P=0.015). Meta-analyses, including the data from the present study and online microarray data, also verified the downregulation of miR-198-5p in 584 cases of LUAD. The expression of miR-198-5p was associated with the age, blood vessel invasion, Tumor-Node-Metastasis stage, and lymph node metastasis of patients with LUAD and served as an independent prognostic factor for survival. The hub genes of miR-198-5p were upregulated in LUAD, according to TCGA and The Human Protein Atlas. For the KEGG pathway analysis, the most enriched KEGG pathway was the p53 signaling pathway (P=1.42×10−6). These findings indicated that the downregulation of miR-198-5p may play a pivotal role in the development of LUAD by targeting various signaling pathways. [ABSTRACT FROM AUTHOR]

Owing to the inferior dispersibility of boron nitride nanosheets (BNNSs) and weak interfacial interaction with the matrix, the performance of BNNS‐based composites is usually far below theoretically predicted values. Here, binary multiscale BNNSs (LDH‐BNNSs) fillers are synthesized through in situ growth of layered double hydroxide (LDH) on the BNNSs' surfaces. LDH‐BNNSs with a multiple mosaic interface show superior dispersion of nanosheets in matrix and extraordinary filler‐matrix bonding. Density functional theory simulations reveal the stable dispersion mechanism of LDH‐BNNSs. Moreover, the bio‐based poly(ethylene furandicarboxylate) composites with 0.2 wt% LDH‐BNNSs loading exhibit simultaneous improvements in tensile strength (≈140 MPa), Young's modulus (≈6.5 GPa), toughness (≈2.0 MJ m−3), and gas barrier properties. Regulation of the interfacial structures of binary multiscale BNNSs significantly increases the filler utilization of the nanosheets, leading to extraordinary stress transfer efficiency and a physical shielding effect. Therefore, this simple, efficient, and novel strategy has promised in enhancing composite performance, and it provides a novel way to develop strong, tough, and high‐barrier bio‐based polyester composites. [ABSTRACT FROM AUTHOR]

In order to alleviate the energy shortage problem and realize green communication, we propose a multiple unmanned aerial vehicles (UAV) enabled energy harvesting (EH) system based on time division multiple address (TDMA) and frequency division multiple address (FDMA). Taking energy efficiency as an objective, we jointly optimize the time allocation scheme and power control in multi-UAV EH network. Before solving the optimization problem, node assignment scheme which determines the connection relationship between nodes and each UAV needs to be obtained first. In TDMA mode, we obtain the node assignment scheme and the trajectory of UAVs based on genetic algorithm. In FDMA mode, the node assignment scheme is obtained based on K-means clustering algorithm, and the hover points’ coordinates of UAV are optimized according to the result of node assignment. We design a time and power joint optimization algorithm (TPJOA) based on Lagrange duality method and discuss three possible cases of the optimal solutions. Simulation results show that our TPJOA method performs better than the water-filling algorithm in energy efficiency. [ABSTRACT FROM AUTHOR]

Microgrids may suffer from full blackouts when confronted with unexpected disruptions due to man‐made faults or natural disasters. How to quickly restore the power supply of microgrids by making use of local distributed energy resources (DERs) is therefore a practical issue to help microgrids ride through full blackouts. Accordingly, this study proposes a novel black start strategy for microgrids to determine the restoration sequence and optimally allocate the DERs after full blackouts. In particular, the uncertainty of power output of renewable energy sources is considered using a data‐driven chance‐constrained approach when renewable energy sources are integrated. The proposed approach only utilises historical data and does not need any prior knowledge about the true probability distribution of the uncertainty. In addition, affine‐based techniques and sample‐dependent band functions are developed to convert the chance‐constrained problem into a tractable mixed‐integer linear programming problem. Finally, numerical experiments based on two microgrid test systems are performed to validate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The mechanically strong chitin films were fabricated via a simple and green pathway. • Both the σ b and ε b of the films were improved greatly by chemical crosslinking with epichlorohydrin. • The chitin films exhibited good optical transparency. • The chitin films had good biocompatibility and breathable property. Abstract Chitin is the second abundant polysaccharide after cellulose, and has been demonstrated to possess various applications in the fields of the biomaterials, water treatment, etc. Here, mechanically strong chitin films were successfully fabricated from chitin solution in NaOH/urea aqueous system with cooling by chemical crosslinking with epichlorohydrin (ECH). The results indicated that tensile strength and elongation at break of the chitin film prepared by using the weight ratio of ECH to chitin solution of 6:100 enhanced significantly to achieve 139 MPa and 43%, respectively, showing highly strong strength and elongation. The cell assay results confirmed that the chitin films were non-toxicity. Water vapor transmittance rate testing indicated that the chitin films had better breathable properties than commercial product. The robust chitin films with high transmittance, biocompatibility and breathability have great potentials in the wide applications such as biomedical, food packaging, wound healing, garments fields, etc. [ABSTRACT FROM AUTHOR]

Purpose: Autophagy is a major catabolic system by which eukaryotic cells undergo self-degradation of damaged, defective, or unwanted intracellular components. An abnormal autophagic level is implicated in the pathogenesis of multiple diseases, including cancers. The aim of this study is to explore the prognostic value of autophagy in bladder cancer (BC), which is a major cause of cancer-related death globally. Patients and methods: First, 27 differentially expressed autophagy-related genes (ARGs) were identified in BC patients based on The Cancer Genome Atlas (TCGA) database. Functional enrichment analyses hinted that autophagy may act in a tumor-suppressive role in the initiation of BC. Then, the Cox proportional hazard regression model were employed to identify three key prognostic ARGs (JUN, MYC, and ITGA3), which were related with overall survival (OS) significantly in BC. The three genes represented important clinical significance and prognostic value in BC. Then a prognostic index (PI) was constructed. Results: The PI was constructed based on the three genes, and significantly stratified BC patients into high- and low-risk groups in terms of OS (HR=1.610, 95% CI=1.200–2.160, P=0.002). PI remained as an independent prognostic factor in multivariate analyses (HR=2.355, 95% CI=1.483–3.739, P<0.001). When integrated with clinical characteristics of age and stage, an autophagy-clinical prognostic index (ACPI) was finally validated, which had improved performance in predicting OS of BC patients (HR=2.669, 95% CI=1.986–3.587, P<0.001). The ACPI was confirmed in datasets of GSE13507 (HR=7.389, 95% CI=3.645–14.980, P<0.001) and GSE31684 (HR=1.665, 95% CI=0.872–3.179, P=0.122). Conclusion: This study provides a potential prognostic signature for predicting prognosis of BC patients and molecular insights of autophagy in BC. [ABSTRACT FROM AUTHOR]

Highlights • Five wavelengths were selected for leaf chlorophyll and water content estimation. • The consistency of the wavelengths was tested by different PROSPECT versions. • The performance of the selected wavelengths tested with three experimental datasets. Abstract The estimation of leaf biochemical constituents is of high interest for the physiological and ecological applications of remote sensing. The multispectral lidar (MSL) system emerges as a promising active remote sensing technology with the ability to acquire both three-dimensional and spectral characteristics of targets. The detection wavelengths of the MSL system can be geared toward the specific application purposes. Therefore, it's important to conduct the wavelength selection work to maximize the potential of the MSL system in vegetation monitoring. Traditional strategies of wavelength selection attempt to establish an empirical relationship between large quantities of observed reflectance and foliar biochemical constituents. By contrast, this study proposed to select wavelengths through the radiative transfer model PROSPECT. A five-wavelength combination was established to estimate leaf chlorophyll and water contents: 680, 716, 1104, 1882 and 1920 nm. The consistency of the wavelengths selected were tested by running different versions of PROSPECT model. Model inversion using simulated and experimental datasets showed that the selected wavelengths have the ability to retrieve leaf chlorophyll and water contents accurately. Overall, this study demonstrated the potential of the MSL system in vegetation monitoring and can serve as a guide in the design of new MSL systems for the application community. [ABSTRACT FROM AUTHOR]

Bone-marrow mesenchymal stem cells (BMSCs) have been used for systemic delivery of therapeutic genes to solid tumors. However, the optimal treatment time post-BMSC implantation and the assessment of the long-term fate of therapeutic BMSCs post-tumor treatment are critical if such promising therapies are to be translated into clinical practice. An efficient BMSC-based therapeutic strategy has been developed that simultaneously allows killing of tumor cells, inhibiting of tumor angiogenesis, and assessment and eradication of implanted BMSCs after treatment of glioblastoma. BMSCs were engineered to co-express the angiogenesis inhibitor kringle 5 (K5) of human plasminogen, under the control of the cytomegalovirus promoter (CMV) and the human sodium–iodide symporter (NIS), involved in uptake of radioisotopes, under the control of early growth response factor 1 (Egr1), a radiation-activated promoter. A significant decrease in tumor growth and tumor angiogenesis and a subsequent increase in survival were observed when mice bearing glioblastoma were treated with 188Re post-therapeutic intravenous BMSC implantation. Furthermore, the systemic administration of 188Re post-tumor treatment selectively eliminated therapeutic BMSCs expressing NIS, which was monitored in real time by 125I micro single photon emission computed tomography/computed tomography imaging. Meanwhile, the Egr1 promoter induced a 188Re radiation positive feedback effect absorbed by NIS. After intravenous BMSC implantation, BMSCs levels in the tumor and lung both peaked on day 10 and decreased to the lowest levels on days 24 and 17, respectively. These findings suggest that day 17 post-BMSC implantation could be an optimal time for 188Re treatment. These results provide a new adjuvant therapy mediated by BMSCs for glioblastoma treatment. [ABSTRACT FROM AUTHOR]

Summary: In the modeling of hydrocarbon thermal cracking processes, complicated reaction networks of multicomponent reactants make kinetic parameter predictions very challenging. To solve this problem, the additivity method and Evans‐Polanyi equation were proposed for the prediction of kinetic factors. As the calculation of kinetic parameters using quantum chemical theory was used for higher accuracy, new additivity methods at the quantum theory level were developed for the prediction of thermodynamic kinetic parameters. At the same time, a reaction class transition state theory RC‐TST, analogous to the Evans‐Polanyi equation, was proposed by considering quantum factors for kinetic constant evaluation. Quantum calculation methods promoted mechanistic studies of electronic effects to accurately reveal the kinetic constant rules with different structural factors. Under these circumstances, kinetic parameter predictions by different quantum chemical computation methods were firstly introduced and reviewed. Meanwhile, development of the new additivity method and RC‐TST theory at the quantum chemistry level were summarized, and the new outlook on electronic effects with an appropriate quantum chemical computational method into the new additivity method was conducted to develop more perspicuous and accuracy in a simplified method for the calculation of complicated thermal cracking reaction. [ABSTRACT FROM AUTHOR]

Zinc oxide–Graphitic carbon nitride (ZnO@g-C 3 N 4) composite membranes were prepared via in-situ growing ZnO crystals in the g-C 3 N 4 membrane. In this composite membrane, ZnO crystals were embedded in loose surface layers of g-C 3 N 4 membrane, which can repair some non-selective defects and improve the dye retention performance. In addition, the hetero-structures formed between ZnO and g-C 3 N 4 nanosheets promoted the separation of photogenerated electron-holes in g-C 3 N 4 layer, and improving the photocatalytic and anti-fouling performance of ZnO@g-C 3 N 4 composite membranes. Herein, the prepared composite membranes showed excellent dye removal performance and self-cleaning property in dynamic recirculation filtration systems under visible light irradiation. The optimized sample (CNZ-0.15 g) showed MB removal efficiency of 94.4% and water flux of 336.8 L.m−2.bar−1.h−1. The outcome of this research would suggest the application of graphitic nitride nanomaterials for developing highly efficient photocatalytic membranes. [Display omitted] • The ZnO@g-C 3 N 4 photocatalytic membranes were designed and fabricated. • The introduced ZnO particles repaired the defects in the pristine g-C 3 N 4 membrane. • The hetero-structure promoted the electron-hole separation in composite membranes. • The composite membranes showed efficient dye removal under continuous operation conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] It is difficult to infer causality from high-dimension metagenomic data due to interference from numerous confounders. By imitating the twin studies in genetic research, we develop a straightforward method—virtual twins (VTwins)—to eliminate the confounder effects by transforming the original cohort into a paired cohort of "Twin" samples with distinct phenotypes but matched taxonomic profiles. The results show that VTwins outperforms the conventional approach in the sensitivity of identifying causative features and only requires a 10-fold reduced sample size for recalling disease-associated microbes or pathways, as tested by simulated and empirical data. Benchmark test with other 16 kinds of software further validates the power and applicability of VTwins for handling high-dimension compositional datasets and mining causalities in metagenomic research. In conclusion, VTwins is straightforward and effective in handling high-diversity, high-dimension compositional data, promising applications in mining causalities for metagenomic and potentially other omics data. VTwins is open access and available at https://github.com/mengqingren/VTwins. [ABSTRACT FROM AUTHOR]

Chlorophyll (Chl) is an important indicator of photosynthetic capacity and stress of vegetation. Remote sensing provides fast and nondestructive methods for estimating leaf Chl content based on its optical characteristics in visible and near-infrared spectrum. Multispectral lidar (MSL) systems have been developed to combine spectral and spatial detection abilities. Statistical relationships of plant biochemical constituents can be established through MSL measurements. However, empirical models cannot be readily extended to independent datasets. Simultaneously, the few spectral bands of MSL limit the use of a physical model. Hence, the development of hyperspectral lidar (HSL) systems offers a wider range of spectrum. This study investigated the possibility of adopting an HSL system with 32 channels covering 539–910 nm to estimate foliar Chl through a physical model. This study aimed to (1) Determine whether reflectance at the 32 channels is sufficient to retrieve Chl content through PROSPECT model inversion and (2) Considering the difference between passively and actively measured reflectance, investigate whether HSL measurements can be applied into PROSPECT model inversion for leaf biochemical constituents. Three kinds of datasets were used: a synthetic dataset simulated by running the PROSPECT model in forward mode, a public dataset ANGERS taking the channels of the HSL system, and an experimental dataset of paddy rice measured by the HSL system. Results showed HSL measurements can be directly used to retrieve leaf Chl content through PROSPECT-4 model inversion ( R 2  = 0.55). These measurements also exhibit higher accuracy than that of support vector regression (threefold cross validation; 100 repetitions: median R 2  = 0.47). This validation work provides basis in the determination of vegetation physiological status directly from HSL measurements through model inversion with the PROSPECT model. [ABSTRACT FROM AUTHOR]

Texture features of the salient patches are closely related to the facial expression recognition on face images. To obtain these features, we applied the Gabor wavelets to extract the relevant values on the whole-face and important regions such as the eyes, nose, and mouth of the face, and assigned different weights to them with respect to their different recognition effectiveness. Since the LBP operator is largely dependent on the center pixel and is easily to be affected by the lighting conditions, an Around Center Instable Local Binary Pattern (ACI-LBP) operator is applied in this research. The technique takes consideration of the relationship between the center point and the adjacent points, thus extends the representations of the fetures in the local region and is more robust to noise and illumination. To get the ACI-LBP, the LBP value is calculated first, then the Near Local Binary Pattern (N-LBP) value is calculated based on the distance between each pixel point and its neighborhood points in clockwise direction. The inconsistent values of LBP and N-LBP in corresponding positions are calculated in terms of their absolute values. In addition, a multi-scale histogram statistics method is adopted in the ACI-LBP extraction. Finally, the two parts features, Gabor and ACI-LBP, are merged as an integrated feature vector to classify and recognize the facial expression. Experimental results based on the JAFFE and CK facial databases show that the method can effectively improve the recognition accuracy of the facial expression recognition. [ABSTRACT FROM AUTHOR]

Maleae consists of economically and ecologically important plants. However, there are considerable disputes on generic circumscription due to the lack of a reliable phylogeny at generic level. In this study, molecular phylogeny of 35 generally accepted genera in Maleae is established using 15 chloroplast regions. Gillenia is the most basal clade of Maleae, followed by Kageneckia + Lindleya, Vauquelinia, and a typical radiation clade, the core Maleae, suggesting that the proposal of four subtribes is reasonable. In the core Maleae including 31 genera, chloroplast gene data support that the four Malus-related genera should better be merged into one genus and the six Sorbus-related genera would be classified into two genera, whereas all Photinia-related genera should be accepted as distinct genera. Although the phylogenetic relationships among the genera in Maleae are much clearer than before, it is still premature to make a formal taxonomic treatment for these genera. [ABSTRACT FROM AUTHOR]