How to discriminate wood of CITES-listed tree species from their look-alikes: using an attention mechanism with the ResNet model on an enhanced macroscopic image dataset

IntroductionGlobal illegal trade in timbers is a major cause of the loss of tree species diversity. The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) has been developed to combat the illegal international timber trade. Its implementation relies on accurate wood identification techniques for field screening. However, meeting the demand for timber field screening at the species level using the traditional wood identification method depending on wood anatomy is complicated, time-consuming, and challenging for enforcement officials who did not major in wood science.MethodsThis study constructed a CITES-28 macroscopic image dataset, including 9,437 original images of 279 xylarium wood specimens from 14 CITES-listed commonly traded tree species and 14 look-alike species. We evaluated a suitable wood image preprocessing method and developed a highly effective computer vision classification model, SE-ResNet, on the enhanced image dataset. The model incorporated attention mechanism modules [squeeze-and-excitation networks (SENet)] into a convolutional neural network (ResNet) to identify 28 wood species.ResultsThe results showed that the SE-ResNet model achieved a remarkable 99.65% accuracy. Additionally, image cropping and rotation were proven effective image preprocessing methods for data enhancement. This study also conducted real-world identification using images of new specimens from the timber market to test the model and achieved 82.3% accuracy.ConclusionThis study presents a convolutional neural network model coupled with the SENet module to discriminate CITES-listed species with their look-alikes and investigates a standard guideline for enhancing wood transverse image data, providing a practical computer vision method tool to protect endangered tree species and highlighting its substantial potential for CITES implementation

Clinical feasibility of the therapeutic strategies total neoadjuvant therapy and “watch and wait” in the treatment of rectal cancer patients with recurrence after clinical complete response

PurposeIn recent years, total neoadjuvant therapy (TNT) has emerged as a new therapeutic strategy against advanced rectal cancer (RC). After administration of TNT, some patients show complete clinical response (cCR) to treatment however, disputes about the effects of TNT and the alternative treatment plans in case of recurrence after cCR still exist.MethodsA total of 100 patients were included in this paper. CR and non-CR was observed when these patients were administered with TNT at the First Affiliated Hospital of Dalian Medical University, China from May 2015 to June 2021. These patients received different chemotherapeutic regimens, with close monitoring and watch and wait (W&W) strategy being applied by a multidisciplinary team (MDT). According to treatment results, patients were divided into a cCR group and a non-cCR group; according to the recurrence during W&W, they were divided into a recurrence group and a no-local-recurrence group. This study analyzed the factors that may affect the prognosis, and summarized the surgery and treatment after recurrence.ResultsThe TNT strategy was effective, and 85% of patients achieved local remission. However, W&W did not affect the survival time of CR patients, nor did it cause new distant metastasis due to local recurrence during the observation period (P > 0.05). However, for patients with positive CRM, we do not recommend W&W as the first choice of treatment (P < 0.05).Conclusion(1) Whole-course neoadjuvant therapy was an effective treatment scheme for advanced mid-term rectal cancer. The total local reduction rate of this group of cases was 85.00%, meaning that 25 patients achieved CR. (2) W&W was safe and reliable, and CR patients could receive it as the preferred treatment. (3) CRM was an independent risk factor for local recurrence in CR patients. We do not recommend W&W as the preferred treatment for CR patients with positive CRM

A face recognition algorithm using a fusion method based on Adaboost Bidirectional 2DLDA

A challenge for face recognition is variation, such as due to lighting or facial expression differences. To solve this problem, we fuses bidirectional two-dimensional linear discriminant analysis (2DLDA) feature by adaboost technique and propose a novel recognition method called AB2DLDA in this paper. This method can perform well with small number of samples. In this paper, firstly we analyze complementarity for vertical direction of 2DLDA and horizontal direction of E2DLDA. Then we use adaboost to design a classifier, which improves recognition performance by fusing 2DLDA and E2DLDA. Finally, our method is tested on AR face databases. Experimental results show that our method functions with good recognition accuracy and robustness

Facile Fabrication of Polydopamine-Functionalized Titanium Dioxide Nano/Submicro-Particles on the NiTi Substrate for Highly Efficient Solid-Phase Microextraction of Benzotriazole Ultraviolet Filters from Environmental Water Samples

A new polydopamine-functionalized titanium dioxide nano/submicro-particles (PDA@TiO2NPs) coating was successfully constructed on the surface of NiTi substrate as a solid-phase microextraction (SPME) fiber. To obtain a stable and uniform PDA@TiO2NPs coating, the NiTi fiber was hydrothermally treated for in situ growth of titanium/nickel oxide composite nanosheets (TiNiOCNSs). Subsequently, the titanium dioxide nano/submicro-particles (TiO2NPs) were electrophoretically deposited on the TiNiOCNSs coating. Finally, the polydopamine (PDA) coating was modified on the TiO2NPs coating by self-polymerization of dopamine (DA). Scanning electron microscopy (SEM) of the new PDA@TiO2NPs@TiNiOCNSs@NiTi fiber showed a popcornlike nanostructure with a larger surface area and more adsorption sites. Benefitting from the abundant hydrogen bonding, rich π-electron system, and strong hydrophobicity, the functionalized PDA@TiO2NPs@TiNiOCNSs@NiTi fiber illustrated excellent extraction capability for benzotriazole ultraviolet filters (BUvFs) among typical aromatic compounds coupled to HPLC with UV detection. The main SPME conditions such as extraction and desorption time, extraction temperature, stirring rate, and ionic strength were examined and optimized one by one. Under the optimum conditions, the calibration curves presented good linearity for BUvFs in the ranges from 0.01 µg·L−1 to 300 µg·L−1, and the correlation coefficients (r) were above 0.9990. The limits of detection (LODs, S/N = 3) were between 0.005 µg·L−1 and 0.043 µg·L−1. RSD repeatability of intraday and interday for one fiber was less than 5.3% and 6.9%, respectively. Moreover enrichment factors (EFs) ranged from 63 to 218. The recommended method can completely extract and detect trace BUvFs in different environmental water samples. Furthermore, the new fiber shows good stability and high strength

Network Structure and Properties of Lithium Aluminosilicate Glass

Based on lithium aluminosilicate glass, the composition of glass was optimized by replacing SiO2 with B2O3, and the influence of glass composition on structure and performance was studied. With the increase in B2O3 concentrations from 0 to 6.5 mol%, Al2O3 always existed in the form of four-coordinated [AlO4] in the network structure, and B2O3 mainly entered the network in the form of four-coordinated [BO4]. The content of Si-O-Si linkages (Q4(0Al)) was always dominant. The incorporation of boron oxide improved the overall degree of polymerization and connectivity of the lithium aluminosilicate glass network structure. An increase in the degree of network polymerization led to a decrease in the thermal expansion coefficient of the glass and an increase in Vickers hardness and density. The durability of the glass in hydrofluoric acid and NaOH and KOH solutions was enhanced overall

Chromosome-Level Genome Assembly and Transcriptome Comparison Analysis of Cephalopholis sonnerati and Its Related Grouper Species

The tomato hind, Cephalopholis sonnerati, is a bottom-dwelling coral reef fish, which is widely distributed in the Indo-Pacific and Red Sea. C. sonnerati also features complex social structures and behaviour mechanisms. Here, we present a high-quality, chromosome-level genome assembly for C. sonnerati that was derived using PacBio sequencing and Hi-C technologies. A 1043.66 Mb genome with an N50 length of 2.49 Mb was assembled, produced containing 795 contigs assembled into 24 chromosomes. Overall, 97.2% of the complete BUSCOs were identified in the genome. A total of 26,130 protein-coding genes were predicted, of which 94.26% were functionally annotated. Evolutionary analysis revealed that C. sonnerati diverged from its common ancestor with E. lanceolatus and E. akaara approximately 41.7 million years ago. In addition, comparative genome analyses indicated that the expanded gene families were highly enriched in the sensory system. Finally, we found the tissue-specific expression of 8108 genes. We found that these tissue-specific genes were highly enriched in the brain. In brief, the high-quality, chromosome-level reference genome will provide a valuable genome resource for studies of the genetic conservation, resistance breeding, and evolution of C. sonnerati

An SNP-Based Genetic Map and QTL Mapping for Growth Traits in the Red-Spotted Grouper (Epinephelus akaara)

The red-spotted grouper (Epinephelus akaara) is one of the most commercially important aquatic species in China. However, its seedstock has low larval survival rates, and its stability is confronted with the danger of overexploitation. In this study, a high-density genetic map was constructed using 3435 single nucleotide polymorphisms (SNPs) from 142 first generation (F1) full-sib offspring and two parents of a red-spotted grouper population. The total genetic length of the map was 2300.12 cM with an average intermarker distance of 0.67 cM. Seventeen genome-wide significant quantitative trait loci (QTLs) for growth-related traits were detected on 24 linkage groups, including 5 QTLs for full length, 7 QTLs for body length, and 5 QTLs for body weight. The contribution values of explained phenotypic variance ranged from 10.7% to 12.9%. Moreover, 13 potential candidate genes for growth-related traits were identified. Collectively, these findings will be useful for conducting marker-assisted selection of the red-spotted grouper in future studies