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Despite the popularity of AI-oriented e-commerce live-streaming, the service failures that can result from real-time interaction and instant transactions have not been taken seriously. This study aims to assess the failure of AI-oriented live-streaming e-commerce services and help retailers identify various risks. Based on expectancy disconfirmation theory and a stressor–strain–outcome framework, this study identified a comprehensive framework including information, functional, system, interaction, and aesthetic failures. The structural equation modeling (SEM) method is used to further examine its effect on consumers’ discontinuance behavior. Further research reveals the mediating role of consumer disappointment and emotional exhaustion, as well as the moderating role of the live-streaming platform type. These results shed light on the negative influence of AI-oriented live-streaming e-commerce service failures and contribute to the literature on live-streaming commerce, service failure, and virtual streamers.

BackgroundLarge language models (LLMs) demonstrated advanced performance in processing clinical information. However, commercially available LLMs lack specialized medical knowledge and remain susceptible to generating inaccurate information. Given the need for self-management in diabetes, patients commonly seek information online. We introduce the Retrieval-augmented Information System for Enhancement (RISE) framework and evaluate its performance in enhancing LLMs to provide accurate responses to diabetes-related inquiries. ObjectiveThis study aimed to evaluate the potential of the RISE framework, an information retrieval and augmentation tool, to improve the LLM’s performance to accurately and safely respond to diabetes-related inquiries. MethodsThe RISE, an innovative retrieval augmentation framework, comprises 4 steps: rewriting query, information retrieval, summarization, and execution. Using a set of 43 common diabetes-related questions, we evaluated 3 base LLMs (GPT-4, Anthropic Claude 2, Google Bard) and their RISE-enhanced versions respectively. Assessments were conducted by clinicians for accuracy and comprehensiveness and by patients for understandability. ResultsThe integration of RISE significantly improved the accuracy and comprehensiveness of responses from all 3 base LLMs. On average, the percentage of accurate responses increased by 12% (15/129) with RISE. Specifically, the rates of accurate responses increased by 7% (3/43) for GPT-4, 19% (8/43) for Claude 2, and 9% (4/43) for Google Bard. The framework also enhanced response comprehensiveness, with mean scores improving by 0.44 (SD 0.10). Understandability was also enhanced by 0.19 (SD 0.13) on average. Data collection was conducted from September 30, 2023 to February 5, 2024. ConclusionsThe RISE significantly improves LLMs’ performance in responding to diabetes-related inquiries, enhancing accuracy, comprehensiveness, and understandability. These improvements have crucial implications for RISE’s future role in patient education and chronic illness self-management, which contributes to relieving medical resource pressures and raising public awareness of medical knowledge.

Persistent microbial contamination commonly occurs in the environment. However, the characteristics and associated risks remain largely unknown. The coexistence of virulence factor genes (VFGs) and “last-resort” antibiotic resistance genes (LARGs) on human bacterial pathogens (HBPs) are notorious, creating ecological concerns and health risks. Herein, we explored the pathogenicity and antibiotic resistance levels of LARG-harboring HBPs in agricultural soils. Our findings revealed a high distribution level of VFGs and LARGs in soils (an absolute abundance up to 4.7 × 107 gene copies/g soil) by quantitative PCR (qPCR). Furthermore, most isolated LARG-harboring HBPs exhibited a 100 % lethality rate to Galleria mellonella. LARG-carrying plasmids had a low fitness cost to their host bacteria, implying the high adaptation of these plasmids within the HBPs. Most importantly, multiple LARG and VFG plasmid fusion and core genetic arrangements suggested that these LARG/VFG-linked plasmids endowed the stable and persistent horizontal spread of these genes in and/or cross the species and environments. This study not only unveiled high risk, multisource, compliance and stability aspects of environmentally persistent microbial contamination but also illuminated the importance of linking the phenotype-genotype-niche colonization of environmental microbial contamination within “One Health” framework.

Fermentation broth from fruit and vegetable waste (FFVW) has demonstrated remarkable ability as a soil amendment and in reducing antibiotic resistance genes (ARGs) pollution. However, the potential of FFVW to mitigate other microbial contamination such as human bacterial pathogens (HBPs) and virulence factor genes (VFGs), which are closely associated with human health, remains unknown. In this study, metagenomic analysis revealed that FFVW reduced the HBPs with high-risk of ARGs and VFGs including Klebsiella pneumoniae (reduced by 40.4 %), Mycobacterium tuberculosis (reduced by 21.4 %) and Streptococcus pneumoniae (reduced by 38.7 %). Correspondingly, VFG abundance in soil decreased from 3.40 copies/cell to 2.99 copies/cell. Further analysis illustrated that these was mainly attributed to the inhibition of quorum sensing (QS). FFVW reduced the abundance of QS signals, QS synthesis genes such as rpaI and luxS, as well as receptor genes such as rpfC and fusK, resulting in a decreased in risk of ARGs and VFGs. The pure culture experiment revealed that the expression of genes related to QS, VFGs, ARGs and mobile genetic elements (MGEs) were downregulated in Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli and K. pneumoniae treated by FFVW, consistent with the result of metagenomic analysis. This study suggested an environmentally friendly approach for controlling soil VFGs/ARGs-carrying HBPs, which is crucial for both soil and human health under the framework of “One Health”.

Bamboo is composed of thick-walled fibrous tissue and thin-walled parenchymal tissue. To compare the energy consumption of preparing lignocellulose nanofibrils (LCNF) from these bamboo tissues, the crystallinity, sol. viscosity, morphology and mechanical properties of LCNF at different preparation stages were characterized in detail. It required at least nine homogenization cycles for dissociating the fibrous tissue, but only six cycles for the parenchymal tissue. The average diameter of LCNF isolated from fibrous and parenchymal tissues was 45.1 nm and 36.2 nm, respectively. The tensile strength of the LCNF film prepared from parenchymal tissue reached 142.46 MPa, whereas the film from fibrous tissue reached only 122.82 MPa. Additionally, a metal organic framework (MOF) was used to produce MOF-LCNF film with enhanced UV protection and antibacterial properties. The results indicated that the energy consumption for preparing LCNF from parenchymal tissue is significantly lower than that for preparing LCNF from fibrous tissue. This study offers a low-cost and eco-friendly method for preparing LCNF, promoting the precise utilization of different tissues from bamboo based on their unique characteristics.

The World Health Organization (WHO) has identified the use of iron cookware as a potential strategy for alleviating iron deficiency anaemia (IDA) and emphasises the need for action-oriented research in this area. In response to this need, our study systematically investigated the patterns of iron release from various types of cookware under different cooking conditions. Among these, nitrided iron pots (NIPs), the most widely used cookware, were selected for the development of kinetic models to predict iron release efficiently across a range of cooking temperatures and pH levels in food materials. Our results demonstrated that iron release from the pots was significantly influenced by cooking conditions such as the type of cookware, cooking temperatures, cooking times, types of acidic substances, and the pH of the cooking environment. Specifically, higher temperatures, longer cooking times, lower pH levels, and the presence of acetic acid were found to maximise iron release into food. We developed a series of kinetic models—Iron Release-Temperature Models (I, II, and III) and Iron Release-pH Models (IV, V, and VI)—to predict iron release from NIPs. The temperature models are applicable for cooking food with a pH of 5.00–6.00 within a temperature range of 50–100 °C, while the pH models are designed for food with a pH of 3.00–6.00 at boiling temperatures. Validation experiments confirmed the relative accuracy of these models. Additionally, when comparing the predicted iron release with the Recommended Nutrient Intake (RNI) guidelines, the findings support the efficacy of iron pots as a viable method for iron supplementation.

This study investigated the effects of different adhesives, phenol formaldehyde (PF) and melamine urea formaldehyde (MUF), on the mechanical and fire properties of flame-retardant laminated bamboo lumber (LBL). The results demonstrated that the flame-retardant treatment using phosphorus–nitrogen–boron compounds endowed the LBL with excellent flame retardancy and smoke suppression properties, even though the bending strength and bond shear strength were slightly reduced. The PF-glued LBL exhibited superior mechanical and shear properties to the MUF-glued ones, primarily due to its higher processing temperature and deeper adhesive penetration. In addition, the MUF-glued flame-retardant LBL displayed better heat release reduction and smoke suppression properties than the PF-glued LBL, which resulted from the synergistic flame retardancy between the melamine element in MUF and the applied flame retardant. The analysis of the influence of adhesive type on the mechanical and fire properties of flame-retardant LBL holds significant importance for the future design and production of high-performance LBL material.

Plant‐based flow microreactors with natural channel structures, renewable properties, and environmental friendliness have increasingly gained popularity in heterogeneous catalysis. However, firmly immobilizing the catalysts simultaneously with ease and adaptability, maintaining great effectivity and long‐term stability, is still a fundamental challenge. Herein, a highly efficient and ultrastable bamboo‐based catalytic microreactor (CMR) containing mesoporous TiO2 (M‐TiO2)‐encapsulating ultrafine Pd nanoparticles (NPs) is constructed for the continuous‐flow hydrogenation of nitroaromatics. The fabrication of the Pd‐TiO2 catalysts in required bamboo microchannels (Pd‐TiO2/B CMR) mainly involves a two‐step region‐selective synthetic strategy with ultra‐low chemical usage, fast preparation, and low catalyst loading (0.007 wt%). The M‐TiO2 films: 1) provide abundant oxygen vacancies and enough open cavities to facilitate the growth of Pd NPs; 2) improve Pd dispersion and reduce particle size; 3) allow diffusion of reactants, and 4) induce strong metal‐support interactions for enhanced catalytic activity and stability. The optimized Pd‐TiO2/B CMR demonstrates high efficiency (>97%) and excellent stability (1,000 h) for the continuous‐flow hydrogenation of nitroaniline, even under intermittent operation (12 h on/12 h off for five cycles) or in a real aqueous matrix (>200 h), making it a promising candidate for Pd‐catalyzed hydrogenation.

Vehicle scheduling plays a profound role in public transportation. Especially, stochastic vehicle scheduling may lead to more robust schedules. To solve the stochastic vehicle scheduling problem (SVSP), a discrete artificial bee colony algorithm (DABC) is proposed. Due to the discreteness of SVSP, in DABC, a new encoding and decoding scheme with small dimensions is designed, whilst an initialization rule and three neighborhood search schemes (i.e., discrete scheme, heuristic scheme, and learnable scheme) are devised individually. A series of experiments demonstrate that the proposed DABC with any neighborhood search scheme is able to produce better schedules than the benchmark results and DABC with the heuristic scheme performs the best among the three proposed search schemes.

Heavy ion beam (HIB) is an effective physical mutagen that has been widely used in plant mutational breeding. Systemic knowledge of the effects caused by different HIB doses at developmental and genomic levels will facilitate efficient breeding for crops. Here we examined the effects of HIB systematically. Kitaake rice seeds were irradiated by ten doses of carbon ion beams (CIB, 25 – 300 Gy), which is the most widely used HIB. We initially examined the growth, development and photosynthetic parameters of the M1 population and found that doses exceeding 125 Gy caused significant physiological damages to rice. Subsequently, we analyzed the genomic variations in 179 M2 individuals from six treatments (25 – 150 Gy) via whole-genome sequencing (WGS). The mutation rate peaks at 100 Gy (2.66×10-7/bp). Importantly, we found that mutations shared among different panicles of the same M1 individual are at low ratios, validating the hypothesis that different panicles may be derived from different progenitor cells. Furthermore, we isolated 129 mutants with distinct phenotypic variations, including changes in agronomic traits, from 11,720 M2 plants, accounting for a 1.1% mutation rate. Among them, about 50% possess stable inheritance in M3. WGS data of 11 stable M4 mutants, including three lines with higher yields, reveal their genomic mutational profiles and candidate genes. Our results demonstrate that HIB is an effective tool that facilitates breeding, that the optimal dose range for rice is 67 – 90% median lethal dose (LD50), and that the mutants isolated here can be further used for functional genomic research, genetic analysis, and breeding.

Vehicle routing problem with time windows (VRPTW) is a core combinatorial optimization problem in distribution tasks. The electric vehicle routing problem with time windows under demand uncertainty and weight-related energy consumption is an extension of the VRPTW. Although some researchers have studied either the electric VRPTW with nonlinear energy consumption model or the impact of the uncertain customer demand on the conventional vehicles, the literature on the integration of uncertain demand and energy consumption of electric vehicles is still scarce. However, practically, it is usually not feasible to ignore the uncertainty of customer demand and the weight-related energy consumption of electronic vehicles (EVs) in actual operation. Hence, we propose the robust optimization model based on a route-related uncertain set to tackle this problem. Moreover, adaptive large neighbourhood search heuristic has been developed to solve the problem due to the NP-hard nature of the problem. The effectiveness of the method is verified by experiments, and the influence of uncertain demand and uncertain parameters on the solution is further explored.

With the increasing concern regarding the undesirable environmental and socioeconomic consequences of petrochemicals and limited fossil resources, biomass, bio-based polymers, and other renewable natural resources have increasingly become alternatives for the production of functional materials [...]

The degree of organised alignment of fibre structures, referred to as the degree of orientation, significantly influences the textural properties and consumer acceptance of fibrous foods. To develop a new method to quantitatively characterise the fibre structure of such foods, a laser transmission imaging system is constructed to capture the laser beam spot on a sample, and the resulting image undergoes a series of image processing steps that use computer vision to translate the light and dark variations of the original images into distinct ellipses. The results show that the degree of orientation can be reasonably calculated from the ellipse obtained by fitting the outermost isopixel points. To validate the reliability of the newly developed method, we determine the degree of orientation of typical fibrous foods (extruded beef jerky, pork jerky, chicken jerky, and duck jerky). The ranking of the measured orientation agrees with the results of pseudocolour maps and micrographs, confirming the ability of the method to distinguish different fibrous foods. Furthermore, the relatively small coefficients of variation and the strong positive correlation between the degree of organisation and the degree of orientation confirm the reliability of this newly developed method.

Super-hydrophobic and fire-retardant coatings have been applied to the bamboo surface. However, it remains a significant challenge to develop coating materials that perform multiple functions simultaneously. In this paper, a novel conductive bamboo timber (RGO@AgBT), coated with reduced graphene oxide (RGO) and silver nanoparticles, was fabricated via a hydrothermal process and a silver mirror reaction process. The RGO@AgBT composites had excellent photo-catalytic activity, meanwhile, the removal rate of rhodamine B (RhB), methylene blue (MB), and methyl orange (MO) after 60 min photo-degradation were 77.6 %, 88.8 %, and 78.4 %, respectively, superior to the raw bamboo timber (BT) and the bamboo timber coated with reduced graphene oxide (RGOBT). The RGO@AgBT samples showed excellent antibacterial performance against Escherichia coli and Staphylococcus aureus. Additionally, the RGO@AgBT samples exhibited improved thermal stability and fire-resistant property with a limiting oxygen index of 30.5 %. Finally, the future directions of multifunctional bamboo research and opportunities for electronic industry application are prospected.

With the global pandemic of COVID-19, it has been striking psychological burdens on individuals. Under this background, more and more people get wellbeing by watching live broadcasts. However, the psychological mechanism behind this phenomenon is still a black box. This study finds that when people watch a live broadcast and interact with anchors and other people, an interaction ritual chain is formed, and emotional energy is generated, thus making people experience and understand the meaning of the live interaction ritual chains. Under the effect of the meaning transfer model, people will generate wellbeing. Specifically, the basic meaning of live interaction (emotional meaning and functional meaning) drives people’s generation of wellbeing. The meanings of self-participation, self-display, self-concept, and self-renewal play a role in mediation in enhancing people’s wellbeing with the basic meaning of live broadcast interaction.

ABSTRACT Arbuscular mycorrhizal fungi (AMF) have been reported to have a wide distribution in terrestrial ecosystems and to play a vital role in ecosystem functioning and symbiosis with Stipa grasses. However, exactly how AMF communities in the rhizosphere change and are distributed along different Stipa population with substituted distribution and their relationships remain unclear. Here, the changes and distribution of the rhizosphere AMF communities and their associations between hosts and the dynamic differences in the glomalin-related soil protein (GRSP) in the rhizosphere soil of seven Stipa species with spatial substitution distribution characteristics in arid and semiarid grasslands were investigated. Along with the substituted distribution of the Stipa populations, the community structures, taxa, species numbers, and alpha diversity index values of AMF in the rhizosphere changed. Some AMF taxa appeared only in certain Stipa species, but there was no obvious AMF taxon turnover. When the Stipa baicalensis population was replaced by the Stipa gobica population, the GRSP tended to decline, whereas the carbon contribution of the GRSP tended to increase. Stipa grandis and Stipa krylovii had a great degree of network modularity of the rhizosphere AMF community and exhibited a simple and unstable network structure, while the networks of Stipa breviflora were complex, compact, and highly stable. Furthermore, with the succession of zonal populations, the plant species, vegetation coverage, and climate gradient facilitated the differentiation of AMF community structures and quantities in the rhizospheres of different Stipa species. These findings present novel insights into ecosystem functioning and dynamics correlated with changing environments. IMPORTANCE This study fills a gap in our understanding of the soil arbuscular mycorrhizal fungal community distribution, community composition changes, and diversity of Stipa species along different Stipa population substitution distributions and of their adaptive relationships; furthermore, the differences in the glomalin-related soil protein (GRSP) contents in the rhizospheres of different Stipa species and GRSP’s contribution to the grassland organic carbon pool were investigated. These findings provide a theoretical basis for the protection and utilization of regional biodiversity resources and sustainable ecosystem development.

To develop monoammonium phosphate (MAP) as a novel acid source for durable intumescent fire retardants (IFR), MAP microcapsules (MCMAPs) containing MAP as the internal core and melamine-formaldehyde (MF) as the external shell were prepared by in situ polymerization in this study. The influences of synthesis conditions (including reaction temperature, polymerization time, and reaction pH value) on the properties of obtained MCMAPs (MAP content, yield, morphologies, and thermal properties) were then investigated systematically. The morphologies, chemical structures, and thermal properties were characterized by optical microscopy, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), Fourier transform infrared (FTIR) spectroscopy, and thermogravimetry analyzer (TGA). The results show that MAP was well encapsulated by MF resin. No microcapsules are obtained at

Advancements in artificial intelligence algorithms and models, along with embedded device support, have resulted in the issue of high energy consumption and poor compatibility when deploying artificial intelligence models and networks on embedded devices becoming solvable. In response to these problems, this paper introduces three aspects of methods and applications for deploying artificial intelligence technologies on embedded devices, including artificial intelligence algorithms and models on resource-constrained hardware, acceleration methods for embedded devices, neural network compression, and current application models of embedded AI. This paper compares relevant literature, highlights the strengths and weaknesses, and concludes with future directions for embedded AI and a summary of the article.

The ABCD rule is a simple framework that physicians, novice dermatologists and non-physicians can use to learn about the features of melanoma in its early curable stage, enhancing thereby the early detection of melanoma. Since the interpretation of the ABCD rule traits is subjective, different solutions have been proposed in literature to tackle such subjectivity and provide objective evaluations to the different traits. This paper reviews the main contributions in literature towards automating asymmetry, border irregularity, color variegation and diameter, where the different methods involved have been highlighted. This survey could serve as an essential reference for researchers interested in automating the ABCD rule.

Cell images, which have been widely used in biomedical research and drug discovery, contain a great deal of valuable information that encodes how cells respond to external stimuli and intentional perturbations. Meanwhile, to discover rarer phenotypes, cell imaging is frequently performed in a high-content manner. Consequently, the manual interpretation of cell images becomes extremely inefficient. Fortunately, with the advancement of deep-learning technologies, an increasing number of deep learning-based algorithms have been developed to automate and streamline this process. In this study, we present an in-depth survey of the three most critical tasks in cell image analysis: segmentation, tracking, and classification. Despite the impressive score, the challenge still remains: most of the algorithms only verify the performance in their customized settings, causing a performance gap between academic research and practical application. Thus, we also review more advanced machine learning technologies, aiming to make deep learning-based methods more useful and eventually promote the application of deep-learning algorithms.

Because thermal infrared sport targets have rich and complex semantic information, there is a high coupling between different types of features. In view of these limitations, we propose a Non-Glodal decoupled Attention, namely,local U-shaped attention decoupling network (LUANets), which aims to decompose the coupling relationship of different sport target features in thermal infrared images and establish effective spatial dependence between them. This method takes the captured multi-scale initial features according to different levels and inputs them into the local decoupling module with U-shaped attention structure to realize the decomposition of semantic details. At the same time, considering the correlation between different targets, in the process of feature decomposition, using prior knowledge as guiding information many times to establish effective spatial dependence. Secondly, we design a two-way cross-aggregation FPN module to cross-aggregate information flows in the front and back directions to achieve feature interaction while further reducing the coupling between different types of features. The evaluation results on data such as TIIs,SportFCs and FLIR show that the LUANets method we proposed has achieved the best detection performance, with mAP of 68.72%,59.51% and 65.29%, respectively.

The bacterial communities of the root-zone soil are capable of regulating vital biogeochemical cycles and the succession of plant growth. Stipa as grassland constructive species is restricted by the difference features of east–west humidity and north–south heat, which shows the population substituting distribution. The distribution, turnover, and potential driving factors and ecological significance of the root-zone bacterial community along broad spatial gradients of Stipa taxa transition remain unclear. This paper investigated seven Stipa species root-zone soils based on high-throughput sequencing combined with the measurements of multiple environmental parameters in arid and semi-arid steppe. The communities of soil bacteria in root zone had considerable turnover, and some regular variations in structure along the Stipa taxa transition are largely determined by climatic factors, vegetation coverage, and pH at a regional scale. Bacterial communities had a clear Stipa population specificity, but they were more strongly affected by the main annual precipitation, which resulted in a biogeographical distribution pattern along precipitation gradient, among which Actinobacteria, Acidobacteria, Proteobacteria, and Chloroflexi were the phyla that were most abundant. During the transformation of Stipa taxa from east to west, the trend of diversity shown by bacterial community in the root zone decreased first, and then increased sharply at S. breviflora, which was followed by continuous decreasing toward northwest afterwards. However, the richness and evenness showed an opposite trend, and α diversity had close association with altitude and pH. There would be specific and different bacterial taxa interactions in different Stipa species, in which S. krylovii had the simplest and most stable interaction network with the strongest resistance to the environment and S. breviflora had most complex and erratic. Moreover, the bacterial community was mainly affected by dispersal limitation at a certain period. These results are conducive to the prediction of sustainable ecosystem services and protection of microbial resources in a semi-arid grassland ecosystem.

To overcome various factors that limit crop production and to meet the growing demand for food by the increasing world population. Seed priming technology has been proposed, and it is considered to be a promising strategy for agricultural sciences and food technology. This technology helps to curtail the germination time, increase the seed vigor, improve the seedling establishment, and enhance the stress tolerance, all of which are conducive to improving the crop yield. Meanwhile, it can be used to reduce seed infection for better physiological or phytosanitary quality. Compared to conventional methods, such as the use of water or chemical-based agents, X-rays, gamma rays, electron beams, proton beams, and heavy ion beams have emerged as promising physics strategies for seed priming as they are time-saving, more effective, environmentally friendly, and there is a greater certainty for yield improvement. Ionizing radiation (IR) has certain biological advantages over other seed priming methods since it generates charged ions while penetrating through the target organisms, and it has enough energy to cause biological effects. However, before the wide utilization of ionizing priming methods in agriculture, extensive research is needed to explore their effects on seed priming and to focus on the underlying mechanism of them. Overall, this review aims to highlight the current understanding of ionizing priming methods and their applicability for promoting agroecological resilience and meeting the challenges of food crises nowadays.

Vegetation and soil microorganisms are important components of terrestrial ecosystems and play a crucial role in ecosystem functioning. However, little is known about the synergistic changes in soil microbial community with aboveground plants in grassland degradation and the role of the microbial community in the process of vegetation restoration succession. In this study, we investigated the characteristics of soil microbial communities and diversities in the different levels of grassland degradation using Illumina MiSeq high-throughput sequencing. The dominant bacteria phyla were: Actinobacteriota, 31.61–48.90%; Acidobacteriota, 7.19–21.73%; Chloroflexi, 9.08–19.09%; and Proteobacteria, 11.14–18.03%. While the dominant fungi phyla were: Ascomycota, 46.36–81.58%; Basidiomycota, 5.63–33.18%; and Mortierellomycota, 1.52–37.69%. Through RDA/CCA, the effects of environmental factors on the differences in the soil microbial community between different sites were interpreted. Results showed that the pH was the most critical factor affecting soil microbial communities in seriously degraded grassland; nevertheless, soil microbial communities in non-degraded grassland and less degraded grasslands were mainly affected by the soil moisture content and soil enzyme activities (sucrase activity, alkaline phosphatase activity and catalase activity). We systematically demonstrated the soil microbial communities of different grassland degradation gradients in Mongolia, which provided valuable information for grassland degradation reduction and vegetation restoration succession.

The enormous pressures of energy consumption and the severe pollution produced by non-renewable resources have prompted researchers to develop various environmentally friendly energy-saving materials. Transparent bamboo represents an emerging result of biomass material research that has been identified and studied for its many advantages, including light weight, excellent light transmittance, environmental sustainability, superior mechanical properties, and low thermal conductivity. The present review summarizes methods for preparing transparent bamboo, including delignification and resin impregnation. Next, transparent bamboo performance is quantified in terms of optical, mechanical, and thermal conductivity characteristics and compared with other conventional and emerging synthetic materials. Potential applications of transparent bamboo are then discussed using various functionalizations achieved through doping nanomaterials or modified resins to realize advanced energy-efficient building materials, decorative elements, and optoelectronic devices. Finally, challenges associated with the preparation, performance improvement, and production scaling of transparent bamboo are summarized, suggesting opportunities for the future development of this novel, bio-based, and advanced material.

The timetabling problem (TTP) and vehicle scheduling problem (VSP) are two indispensable problems in public transit planning process. They used to be solved in sequence; hence, optimality of resulting solutions is compromised. To get better results, some integrated approaches emerge to solve the TTP and VSP as an integrated problem. In the existing integrated approaches, the passenger comfort on bus and the uncertainty in the real world are rarely considered. To provide better service for passengers and enhance the robustness of the schedule to be compiled, we study the integrated optimization of TTP and VSP with uncertainty. In this paper, a novel multiobjective optimization approach with the objectives of minimizing the passenger travel cost, the vehicle scheduling cost, and the incompatible trip-link cost is proposed. Meanwhile, a multiobjective hybrid algorithm, which is a combination of the self-adjust genetic algorithm (SGA), large neighborhood search (LNS) algorithm, and Pareto separation operator (PSO), is applied to solve the integrated optimization problem. The experimental results show that the approach outperforms existing approaches in terms of service level and robustness.

Bamboo timber (BT) is a kind of natural porous material, and usually bamboo cracking and deformation are caused by the change of humidity in the environment. Inspired by the natural structure of the shell, a multilayer structure was designed to fabricate a kind of graphene/silica composite coating on the BT surface. The multilayer bamboo composite (FAS-RGO@SiO2BT) was prepared by using the self-assembly process of nanospherical silica on graphene followed by hydrophobic modification. A possible formation mechanism of FAS-RGO@SiO2BT was discussed by X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray analysis, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy. The FAS-RGO@SiO2BT has excellent hydrophobic properties for tea, orange juice, milk, coffee, blue ink, red wine, and green juice. Also, the FAS-RGO@ SiO2BT has an obvious hydrophobic effect on any of the various solutions with a pH of 1 to 14. In addition, after a 90-day immersion test, the water absorption rate of FAS-RGO@ SiO2BT is 9.7% and the thickness swelling rate is 0.5%. The wettability and dimensional stability of the FAS-RGO@SiO2BT are significantly improved compared to those of BT.

Skin lesion border irregularity, which represents the B feature in the ABCD rule, is considered one of the most significant factors in melanoma diagnosis. Since signs that clinicians rely on in melanoma diagnosis involve subjective judgment including visual signs such as border irregularity, this deems it necessary to develop an objective approach to finding border irregularity. Increased research in neural networks has been carried out in recent years mainly driven by the advances of deep learning. Artificial neural networks (ANNs) or multilayer perceptrons have been shown to perform well in supervised learning tasks. However, such networks usually don't incorporate information pertaining the ambiguity of the inputs when training the network, which in turn could affect how the weights are being updated in the learning process and eventually degrading the performance of the network when applied on test data. In this paper, we propose a fuzzy multilayer perceptron (F-MLP) that takes the ambiguity of the inputs into consideration and subsequently reduces the effects of ambiguous inputs on the learning process. A new optimization function, the fuzzy gradient descent, has been proposed to reflect those changes. Moreover, a type-II fuzzy sigmoid activation function has also been proposed which enables finding the range of performance the fuzzy neural network is able to attain. The fuzzy neural network was used to predict the skin lesion border irregularity, where the lesion was firstly segmented from the skin, the lesion border extracted, border irregularity measured using a proposed measure vector, and using the extracted border irregularity measures to train the neural network. The proposed approach outperformed most of the state-of-the-art classification methods in general and its standard neural network counterpart in particular. However, the proposed fuzzy neural network was more time-consuming when training the network.

Skin lesion border irregularity is considered an important clinical feature for the early diagnosis of melanoma, representing the B feature in the ABCD rule. In this article we propose an automated approach for skin lesion border irregularity detection. The approach involves extracting the skin lesion from the image, detecting the skin lesion border, measuring the border irregularity, training a Convolutional Neural Network and Gaussian naive Bayes ensemble, to the automatic detection of border irregularity, which results in an objective decision on whether the skin lesion border is considered regular or irregular. The approach achieves outstanding results, obtaining an accuracy, sensitivity, specificity, and F-score of 93.6%, 100%, 92.5% and 96.1%, respectively.

Asymmetry, color variegation and diameter are considered strong indicators of malignant melanoma. The subjectivity inherent in the first two features and the fact that 10% of melanomas tend to be missed in the early diagnosis due to having a diameter less than 6mm, deem it necessary to develop an objective computer vision system to evaluate these criteria and aid in the early detection of melanoma which could eventually lead to a higher 5-year survival rate. This paper proposes an approach for evaluating the three criteria objectively, whereby we develop a measure to find asymmetry with the aid of a decision tree which we train on the extracted asymmetry measures and then use to predict the asymmetry of new skin lesion images. A range of colors that demonstrate the suspicious colors for the color variegation feature have been derived, and Feret's diameter has been utilized to find the diameter of the skin lesion. The decision tree is 80% accurate in determining the asymmetry of skin lesions, and the number of suspicious colors and diameter values are objectively identified.

Moisture content and shrinkage strain are essential parameters during the wood drying process. The accurate detection of these parameters has very important significance for controlling the drying process and minimizing drying defects. The presented study describes an electrochemical method to determine wood moisture content and shrinkage strain during drying, and the accuracy of this method is also evaluated. According to the results, the electrical resistance of the samples increased with the decrease in wood moisture content. As the moisture content changed from 42% to 12%, the resistance increased from 1.0 × 107 Ω to 1.2 × 108 Ω. A polynomial fitting curve was fitted with a determination coefficient of 0.937 to describe the relationship between moisture content and electrical resistance. In addition, both the shrinkage strain and resistance change rate increased with the decrease in wood moisture content, especially for the moisture content range of 23% to 8%, where the shrinkage strain and resistance change rate increased by 4% and 30%, respectively. The shrinkage strain increased exponentially with the increase in the resistance change rate; thereby, an exponential regression equation was proposed with a determination coefficient of 0.985, expressing the correlation between the two. This demonstrates the feasibility of the electrochemical method for measuring wood moisture content and shrinkage strain.

Soil salinity is a widespread and important abiotic factor impeding rice production by adversely affecting seed germination, seedling growth, and plant productivity. In this study, the rice cultivar TH899 was treated with 200 Gy of heavy-ion beam irradiation, and 89 mutant lines with stable phenotypes were selected using the pedigree method based on continuous assessment over six years. The seed germination performance of these mutants was tested under different saline–alkaline concentrations. Five highly tolerant lines were further evaluated in a series of experiments at the seedling stage and in the field. During the seedling stage, the reduction of seedling length, root length, fresh weight, and dry weight were dramatically lower in these five mutants than those in TH899 under saline–alkali stress. The K+/Na+ ratio was higher in these five mutants than in TH899. In the field experiment, the grain yield of mutant lines was higher than that of TH899. In addition, the grain yield of mutant line M89 was higher than that of the local cultivar in actual production. These mutant lines are expected to increase grain yield in soda saline–alkaline regions in northeast China.

With the increasing emphasis on sustainable development, bamboo is receiving an increasing attention as a kind of forest resource. But bamboo is readily discoloured by mould fungi, which greatly limits the applications of bamboo. In this research, ZnO nanoparticles were successfully fabricated on the surface of bamboo timber by a simple low-temperature wet chemical method. The morphology, chemical structure, and crystalline structure of the samples were characterized by using scanning electron microscopy (SEM), atomic force microscopy (AFM), Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and energy dispersive spectroscopy (EDS). XRD studies confirmed that the as-prepared ZnO nanoparticles were wurtzite. The microstructure and hydroxyl groups in the bamboo timber surface at the wet state provided cavities and affinity for the creation and the immobilization of ZnO nanoparticles on the bamboo timber surface through electrostatic and hydrogen bonding interactions. Moreover, the mould-resistance of ZnO coated bamboo timber was also in focus on the present study. The results indicated that bamboo timber treated with ZnO had a better resistance against Aspergillus niger V. Tiegh (A. niger) and Penicillium citrinum Thom (P. citrinum), but poor against Trichoderma viride Pers. ex Fr (T. viride). Keywords: Bamboo timber, ZnO nanoparticles, Wet chemical method, Surface, Mould-resistance

The process parameters significantly influence the preparation and final properties of outdoor wood mats-based engineering composite (OWMEC). During outdoor use, wood composites are susceptible to destruction by rot fungi. Herein, the role of process parameters such as density and resin content on OWMEC resistance to fungal decay was investigated. The poplar OWMEC samples were exposed to white-rot fungus Trametes versicolor and brown-rot fungus Gloeophyllum trabeum for a period of 12 weeks. The chemical composition, crystallinity, and morphology were evaluated to investigate the effect of process parameters on the chemical composition and microstructure of the decayed OWMEC. With an increase in the density and resin content, the mass loss of the decayed OWMEC decreased. The highest antifungal effect against T. versicolor (12.34% mass loss) and G. trabeum (19.43% mass loss) were observed at a density of 1.15 g/m3 and resin content of 13%. As results of the chemical composition and microstructure measurements, the resistance of OWMEC against T. versicolor and G. trabeum fungi was improved remarkably by increasing the density and resin content. The results of this study will provide a technical basis to improve the decay resistance of OWMEC in outdoor environments.

A round-the-clock photocatalyst with energy-storage ability has piqued the interest of researchers for removing microbial contaminants from indoor environments. This work presents a moderate round-the-clock method for inhibiting the growth of fungus spores on bamboo materials using Ag-modified TiO2 thin films. Photoactivated antifungal coating with catalytic memory activity was assembled on a hydrophilic bamboo by first anchoring anatase TiO2 thin films (TB) via hydrogen bonding and then decorating them with Ag nanoparticles (ATB) via electrostatic interactions. Antifungal test results show that the Ag/TiO2 composite films grown on the bamboo surface produced a synergistic antifungal mechanism under both light and dark conditions. Interestingly, post-illumination catalytic memory was observed for ATB, as demonstrated by the inhibition of Aspergillus niger (A. niger) spores, in the dark after visible light was removed, which could be attributed to the transfer of photoexcited electrons from TiO2 to Ag, their trapping on Ag under visible-light illumination, and their release in the dark after visible light was removed. The mechanism study revealed that the immobilized Ag nanoparticles served the role of “killing two birds with one stone”: increasing visible-light absorption through surface plasmon resonance, preventing photogenerated electron–hole recombination by trapping electrons, and contributing to the generation of ●O2−and ●OH. This discovery creates a pathway for the continuous removal of indoor air pollutants such as volatile organic compounds, bacteria, and fungus in the day and night time.

Abstract Increasing attention has been paid to the relationship between biodiversity and ecosystem functioning (BEF) because of the rapid increase in species loss. However, over the past 20 years, most BEF studies only focused on the effect of species diversity on one or a few ecosystem functions, and only a few studies focused on ecosystem multifunctionality (i.e., the simultaneous provision of several ecosystem functions). Grassland ecosystems have important economic, environmental, and esthetic value; thus, this study focused on the heterogeneous microcommunities in grasslands under three management modes. The multifunctionality index (M‐index) was assessed at community and microcommunity scales, and the relationship between species diversity and multifunctionality was investigated. The communities were found to be respectively composed of one, three, and six microcommunities in grazing, clipping, and enclosure management, based on a two‐way indicator species analysis (TWINSPAN) and detrended correspondence analysis (DCA) for community structure. Biodiversity and soil indicators showed an apparent degradation of the grazing community, which had the worst M‐index. Clipping and enclosure communities showed no significant difference in biodiversity indices, soil variables, and M‐index; however, these indices were clearly different among microcommunities. Therefore, the microcommunity scale may be suitable to investigate the relationship between vegetation and multifunctionality in seminatural grassland ecosystems. Dominant species richness had more explanatory power for ecosystem multifunctionality than subdominant species richness, rare species richness, and the number of all species. Therefore, it is important to distinguish the role and rank of different species in the species richness–multifunctionality model; otherwise, the model might include redundant and unclear information. Communities with more codominant species whose distribution is also even might have better multifunctionality.

Bamboo-plastic composites (BPCs) as new biomass-plastic composites have recently attracted much attention. However, weak mechanical performance and high moisture absorption as well as low thermal stability greatly limit their industrial applications. In this context, different amounts of halloysite nanotubes (HNTs) were used as a natural reinforcing filler for BPCs. It was found that the thermal stability of BPCs increased with increasing HNT contents. The mechanical strength of BPCs was improved with the increase in HNT loading up to 4 wt% and then worsened, while the impact strengths were slightly reduced. Low HNT content (below 4 wt%) also improved the dynamic thermomechanical properties and reduced the water absorption of the BPCs. Morphological studies confirmed the improved interfacial compatibility of the BPC matrix with 4 wt% HNT loading, and high-concentration HNT loading (above 6 wt%) resulted in easy agglomeration. The results highlight that HNTs could be a feasible candidate as nanoreinforcements for the development of high-performance BPCs.

The purpose of this study is to evaluate the influence of media treatments on color changes, dimensional stability, and cracking behavior of bamboo scrimber, which has many applications in construction. The bamboo scrimber specimens comprised bamboo bundles with a low molecular weight phenol formaldehyde resin which were manufactured via a cold-in and cold-out hot-pressing process. Small clear specimens were sampled and treated under ten different conditions: water immersion at 25°C, 63°C, and 100°C; oil immersion at 100°C and 150°C; air drying at 63°C, 100°C, and 150°C; and infrared drying at 100°C and 150°C. Then, tests were conducted to determine the color changes, dimensional stability, and cracking behavior of the bamboo scrimbers. The results showed that the bamboo scrimber specimens became darker after all treatment conditions, especially the oil treatments and infrared drying. The color of the oil-treated bamboo scrimbers was found to be more homogenous than the others. The dimensional stability of the bamboo scrimbers was more or less influenced by the water treatments, air drying, and infrared drying, and the oil-treated bamboo scrimbers were relatively stable. Moreover, during the 4-hour treatments, cracks were found in the bamboo scrimbers after air drying at 150°C or infrared drying at 100°C or 150°C.

Bamboo is susceptible to mould and attack by fungi because of its high content of starch and sugar. To make bamboo-based outdoor materials, a new type of bamboo timber with improved mould resistance and antibacterial activity, coated with reduced graphene oxide and nanocrystal ZnO (abbreviated as RGO@ZnOBT), was fabricated by a two-step dip-dry and hydrothermal process. A possible synthesis mechanism for RGO@ZnOBT was investigated by X-ray diffraction, scanning electron microscopy, transmission electron microscope, energy-dispersal X-ray analysis, X-ray photoelectron spectroscopy and Fourier-transform infrared spectroscopy. According to the China standard test method, the Aspergillus niger mould resistance of RGO@ZnOBT is grade 2, whereas the Trichoderma viride and Penicillium citrinum mould resistance of RGO@ZnOBT is grade 0, both of which are better than the grade 4 of original bamboo timber. The Escherichia coli resistance test showed that the antibacterial circle of RGO@ZnOBT is 3 mm, which is significantly higher than that of original bamboo timber (0 mm). The antibacterial activity of treated bamboo is significantly improved compared with that of untreated bamboo.

We developed a novel green approach for the in situ fabrication of Ag NPs in mesoporous TiO2 films via the bamboo self-sacrificing reduction of Ag(NH3)2+ ions, which can inhibit fungal growth on the bamboo surface. Mesoporous anatase TiO2 (MT) films were first synthesized on bamboo via a hydrothermal method. Then, Ag NPs with a 5.3 nm mean diameter were incorporated into the pore channels of optimal MT/bamboo (MTB) samples at room temperature without the addition of reducing agents, such that the Ag NPs were almost entirely embedded into the MT films. Our analysis indicated that the solubilized lignin from bamboo, which is rich in oxygen-containing functional groups, serves as a green reductant for reducing the Ag(NH3)2+ ions to Ag NPs. Antifungal experiments with Trichoderma viride under dark conditions highlighted that the antifungal activity of the Ag/MT/bamboo samples were greater than those of naked bamboo, MTB, and Ag/bamboo, suggesting that these hybrid nanomaterials produce a synergistic antifungal effect that is unrelated to photoactivity. The inhibition of Penicillium citrinum effectively followed a similar trend. This newly developed bamboo protection method may provide a sustainable, eco-friendly, and efficient method for enhancing the antifungal characteristics of traditional bamboo, having the potential to prolong the service life of bamboo materials, particularly under dark conditions.

We assessed the impact of species composition and stand structure on the spatial variation of forest carbon density using data collected from a 4-ha plot in a subtropical forest in southern China. We found that 1) forest biomass carbon density significantly differed among communities, reflecting a significant effect of community structure and species composition on carbon accumulation; 2) soil organic carbon density increased whereas stand biomass carbon density decreased across communities, indicating that different mechanisms might account for the accumulation of stand biomass carbon and soil organic carbon in the subtropical forest; and 3) a small number of tree individuals of the medium- and large-diameter class contributed predominantly to biomass carbon accumulation in the community, whereas a large number of seedlings and saplings were responsible for a small proportion of the total forest carbon stock. These findings demonstrate that both biomass carbon and soil carbon density in the subtropical forest are sensitive to species composition and community structure, and that heterogeneity in species composition and stand structure should be taken into account to ensure accurate forest carbon accounting.