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Abstract Wind power is a clean and renewable energy, yet it poses integration challenges to the grid due to its variable nature. Thus, Wind Power Forecasting (WPF) is crucial for its successful integration. However, existing WPF datasets often cover only a limited number of turbines and lack detailed information. To bridge this gap and advance WPF research, we introduce the Spatial Dynamic Wind Power Forecasting dataset (SDWPF). The SDWPF dataset not only provides information on power generation and wind speed but also details the spatial distribution of the wind turbines and dynamic contextual factors specific to each turbine. These factors include weather information and the internal status of each wind turbine, thereby enriching the dataset and improving its applicability for predictive analysis. Further leveraging the potential of SDWPF, we initiated the ACM KDD Cup 2022, a competition distinguished as the foremost annual event in data mining, renowned for presenting cutting-edge challenges and attracting top talent from academia and industry. Our event successfully draws registrations from over 2400 teams around the globe.

Abstract Iron single‐atom catalysts (SACs) have garnered increasing attention as highly efficient catalysts for the oxygen reduction reaction (ORR), yet their performance in practical devices remains suboptimal due to the low density of accessible active sites. Anchoring iron single atoms on 2D support is a promising way to increase the accessible active sites but remains difficult attributing to the high aggregation tendency of iron atoms on the 2D support. Herein, a vacuum vapor deposition strategy is presented to fabricate an iron SAC supported on ultrathin N‐doped carbon nanosheets with densely active sites (FeSAs‐UNCNS). Experimental analyses confirm that the FeSAs‐UNCNS achieves densely accessible active sites (1.11 × 1020 sites g−1) in the configuration of Fe─N4O. Consequently, the half‐wave potential of FeSAs‐UNCNS in 0.1 m KOH reaches a remarkable value of 0.951 V versus RHE. Moreover, when employed as the cathode of various kinds of Zn–air batteries, FeSAs‐UNCNS exhibits boosting performances by achieving a maximum power density of 306 mW cm−2 and long cycle life (>180 h) at room temperature, surpassing both Pt/C and reported SACs. Further investigations reveal that FeSAs‐UNCNS facilitates the mass and charge transfer during catalysis and the atomic configuration favors the desorption of *OH kinetically.

Technology-driven startups often experience fluctuations in business volume and their delivery peak exceeds the conventional functional department’s human resource staffing. Resource allocation is crucial for ensuring timely completion of project deliverables within resource constraints. This study tackles the scheduling challenge under the condition of composite skills, with the goal of efficiently allocating diverse human resources while adhering to constraints such as external labor coordination and skill compatibility. Initially, an integer programming model was formulated to minimize the overall project duration and equalize the workload among employees. Subsequently, an enhanced fast and elitist non-dominated sorting genetic algorithm (NSGA-II) was developed by integrating heuristic-based population initialization and adaptive genetic strategies. A case study was then developed based on the R program of technology-driven company S. The allocation model was solved using both the classic and improved versions of the algorithm. The outcomes indicate that the fitness of the final generation significantly exceeds that of the initial generation, and the refined algorithm outperforms the conventional one in reducing the project duration and enhancing balance, with the potential to reduce project duration by 9% and enhance the balance by 40%. Cluster analysis and statistical methods were applied to extract three pivotal traits of the optimal allocation scheme, providing a scientific reference and decision-making foundation for managerial resource-allocation strategies.

As the ubiquity and complexity of system-on-chip (SoC) designs increase across electronic devices, incorporating security into an SoC design flow poses significant challenges. Existing security solutions are inadequate to effectively verify modern SoC designs due to their limitations in scalability, comprehensiveness, and adaptability. On the other hand, large language models (LLMs) are celebrated for their remarkable success in language understanding, advanced reasoning, and program synthesis tasks. Recognizing an opportunity, our research explores leveraging the emergent capabilities of generative pre-trained transformers (GPTs) to address the existing gaps in SoC security, aiming for a more efficient, scalable, and adaptable methodology. By integrating LLMs into the SoC security verification paradigm, we open a new frontier of possibilities and challenges to ensure the security of increasingly complex SoCs. This paper offers an in-depth analysis of existing works, presents practical case studies, and demonstrates comprehensive experiments. We also present the achievements, prospects, and challenges of employing LLM in different SoC security verification tasks.

Abstract Intrahepatic cholangiocarcinoma (ICC) is the second most common malignancy among primary liver cancers, with an increasing overall incidence and poor prognosis. The intertumoral and intratumoral heterogeneity of ICC makes it difficult to find efficient drug therapies. Therefore, it is essential to identify tumor suppressor genes and oncogenes that induce ICC formation and progression. Here, we performed CRISPR/Cas9-mediated genome-wide screening in a liver-specific Smad4/Pten knockout mouse model (Smad4 co/co ;Pten co/co ;Alb-Cre, abbreviated as SPC), which normally generates ICC after 6 months, and detected that mutations in Trp53, Fbxw7, Inppl1, Tgfbr2, or Cul3 markedly accelerated ICC formation. To illustrate the potential mechanisms, we conducted transcriptome sequencing and found that multiple receptor tyrosine kinases were activated, which mainly upregulated the PI3K pathway to induce cell proliferation. Remarkably, the Cul3 mutation stimulated cancer progression mainly by altering the immune microenvironment, whereas other mutations promoted the cell cycle. Moreover, Fbxw7, Inppl1, Tgfbr2, and Trp53 also affect inflammatory responses, apelin signaling, mitotic spindles, ribosome biogenesis, and nucleocytoplasmic transport pathways, respectively. We further examined FDA-approved drugs for the treatment of liver cancer and performed high-throughput drug screening of the gene-mutant organoids. Different drug responses and promising drug therapies, including chemotherapy and targeted drugs, have been discovered for ICC.

Line structured light (LSL) measurement systems can obtain high accuracy profiles, but the overall clarity relies greatly on the sampling interval of the scanning process. Photometric stereo (PS), on the other hand, is sensitive to tiny features but has poor geometrical accuracy. Cooperative measurement with these two methods is an effective way to ensure precision and clarity results. In this paper, an LSL-PS cooperative measurement system is brought out. The calibration methods used in the LSL and PS measurement system are given. Then, a data fusion algorithm with adaptive weights is proposed, where an error function that contains the 3D point cloud matching error and normal vector error is established. The weights, which are based on the angles of adjacent normal vectors, are also added to the error function. Afterward, the fusion results can be obtained by solving linear equations. From the experimental results, it can be seen that the proposed method has the advantages of both the LSL and PS methods. The 3D reconstruction results have the merits of high accuracy and high clarity.

The extensive use of the parabens triclosan (TCS) and bisphenol A (BPA) has potential adverse effects on human health and aquatic organisms. However, their monitoring information in freshwater lakes is still limited. This study simultaneously summarized the concentrations, spatial distribution characteristics, and correlations of four types of parabens, TCS, and BPA in the surface water and sediment of Baiyang Lake. Finally, the potential risks of target pollutants were evaluated from two aspects: human health risks and ecological risks. The average contaminations of target compounds in surface water and sediment—BPA, TCS, and ∑4 parabens—was 33.1, 26.1, 0.7 ng/L and 24.5, 32.5, 2.5 ng/g, respectively. The total concentration of target compounds at the inlet of the upstream Fu River and Baigouyin River is significantly higher than that near Hunan and the outlet. In addition, Spearman’s correlation analysis showed a significant positive correlation between compounds. The health hazards of target compounds in surface water were all within safe limits. However, the risk quotient results indicate that in some locations in surface water, TCS poses a high risk to algae and a moderate risk to invertebrates and fish, and appropriate attention should be paid to these areas.

Summary: China implemented the first phase of its National Healthy Cities pilot program from 2016-20. Along with related urban health governmental initiatives, the program has helped put health on the agenda of local governments while raising public awareness. Healthy City actions taken at the municipal scale also prepared cities to deal with the COVID-19 pandemic. However, after intermittent trials spanning the past two decades, the Healthy Cities initiative in China has reached a crucial juncture. It risks becoming inconsequential given its overlap with other health promotion efforts, changing public health priorities in response to the pandemic, and the partial adoption of the Healthy Cities approach advanced by the World Health Organization (WHO). We recommend aligning the Healthy Cities initiative in China with strategic national and global level agendas such as Healthy China 2030 and the Sustainable Development Goals (SDGs) by providing an integrative governance framework to facilitate a coherent intersectoral program to systemically improve population health. Achieving this alignment will require leveraging the full spectrum of best practices in Healthy Cities actions and expanding assessment efforts. Funding: Tsinghua-Toyota Joint Research Fund “Healthy city systems for smart cities” program.

Due to the advantages of simple construction, easy application and good environmental suitability, handheld structured-light measurement systems have broad application prospects in 3D measurements. Here, a monocular-vision-guided line-structured-light measurement system is developed, and the posture of the handheld device can be obtained via a specifically designed target attached to it. No more marker points need to be adhered onto the object under inspection. The key for the system calibration is to obtain the coordinate transformation matrix from the sensor to the featured target coordinate system. The mathematical model of the system is first established. Then, an improved multi-view calibration method is proposed, where a selection process for the image pairs is conducted for accuracy improvement. With this method, the maximum relative error of the measured stair heights can be reduced from 0.48% to 0.16%. The measurement results for the specific parts further verified the effectiveness of the proposed system and the calibration method.

ObjectivesLimosilactobacillus reuteri FN041 is a potential probiotic bacterium isolated from breast milk in traditional farming and pastoral areas of China. The purpose of this study was to investigate the optimal intervention mode and potential mechanism of FN041 to prevent atopic dermatitis (AD) in mice.MethodsIn intervention mode I, FN041 was supplemented to dams during the late trimester and lactation and pups after weaning; in intervention mode II, FN041 was supplemented after pups were weaned. AD was induced in pups with MC903 plus ovalbumin on the ear after weaning.ResultsThe effect of intervention mode I in preventing AD was significantly better than that of intervention mode II. Compared with the model group, the inflammatory response of the pup’s ears, the proportion of spleen regulatory T cells and the plasma IgE were significantly decreased in mice in intervention mode I. Furthermore, the intestinal mucosal barrier was enhanced, and the Shannon index of the ileal microbiota was significantly increased. The microbiota structure deviated from the AD controls and shifted toward the healthy controls according to the PCoA of unweighted UniFrac. The relative abundances of Limosilactobacillus, Faecalibacterium, Bifidobacterium, and Akkermansia in the ileum were significantly increased compared to the AD group. Based on RNA-seq analysis of pups’ Peyer’s patches (PPs), FN041 inhibits autoimmune pathways such as asthma and systemic lupus erythematosus and activates retinol metabolism and PPAR signaling pathways to reduce inflammatory responses. Intervention mode II also significantly reduced AD severity score, but the reduction was approximately 67% of that of intervention mode I. This may be related to its ineffective remodeling of the ileal microbiota.ConclusionPrenatal and postnatal administration of FN041 is an effective way to prevent AD in offspring, and its mechanism is related to remodeling of ileal microbiota and PPs immune response.

Diabetic nephropathy is a serious complication of diabetes. Hyperoside has been widely reported to ameliorate diabetes-associated disease. The current study is designed to explore the mechanism of hyperoside in diabetic nephropathy. In the present study, high glucose was used to treat podocytes. Diabetic nephropathy mice models were established by high-fat feeding followed by multiple low dose injections of streptozocin. Western blot analysis was conducted for detection of extracellular matrix accumulation, inflammatory response and cell apoptosis. We found out that hyperoside improved high glucose-induced cell injury. Additionally, hyperoside prevented mice with diabetic nephropathy from diabetic symptoms and renal dysfunction. Mechanistically, hyperoside inhibited the mRNA and protein expression of APC. MiR-499–5p was found to be an upstream negative mediator of APC, and hyperoside induced the upregulation of miR-499–5p. MiR-499–5p bound with the 3’ untranslated region of APC to inhibit its expression. Finally, rescue assays revealed that the suppressive effects of miR-499–5p overexpression on renal dysfunction were rescued by upregulation of APC in mice with diabetic nephropathy. In conclusion, these findings indicated that hyperoside ameliorates diabetic nephropathy via targeting the miR-499–5p/APC axis, suggesting that hyperoside may offer a potential tactic for diabetic nephropathy treatment.

Line structured light sensor has been applied in various three dimensional (3D) measurement scenes with the advantages of non-contact, low cost and high speed. Its accuracy, which is directly determined by the calibration method, needs to be further improved to fulfill the measuring tasks of precision parts. Here, we proposed a numerical method that can eliminate the errors of the model based methods through two strategies. One is the establishment of the numerical mapping relationship between stripe pixel coordinates and their world coordinates through piecewise cubic interpolation. Corner points of a checkerboard target are used to obtain sufficient interpolating nodes. This target can be manually aligned with the laser plane and the alignment error would be eliminated via the point projection. The other is the data-driven laser plane optimization. The data set of reference interval distance is computed based on the invariance of cross ratio. The optimization model is to minimize the root mean squared error of measured interval distances by adjusting the laser plane coefficients. After the optimization, a higher numerical mapping relationship can be achieved. It bypasses the camera and the distortion models and reaches a calibration error of only 0.005mm. The comparison studies and the measurement of the steps further validate the proposed method.

Objectives:Lactobacillus reuteri Fn041 (Fn041) is a probiotic isolated from immunoglobulin A coated microbiota in the human breast milk of Gannan in China with a low incidence of hypercholesterolemia. This study aims to explore the role and mechanism of Fn041 in preventing hypercholesterolemia caused by a high-fat diet in mice.MethodsC57BL/6N mice were fed a low-fat diet or a high-fat diet and gavage with Fn041 and Lactobacillus rhamnosus GG (LGG) for 8 weeks.ResultsBoth Fn041 and LGG prevented the occurrence of hypercholesterolemia, liver and testicular fat accumulation. In addition, a high-fat diet causes intestinal dysbiosis and mucosal barrier damage, which is associated with hypercholesterolemia. Fn041 prevented the high-fat diet-induced reduction in alpha diversity of intestinal microbiota and intestinal mucosal barrier damage. Fn041 treatment significantly increased fecal total cholesterol and total bile acids.ConclusionsFn041 prevented hypercholesterolemia by enhancing cholesterol excretion and mucosal barrier function.

The Lauraceae is a family of the order Laurales, with 2500–3000 species comprising 50 genera, mainly distributed in tropical and subtropical evergreen broad-leaved forests. Up to two decades ago, the systematic classification of the Lauraceae was based on floral morphology, but molecular phylogenetic approaches have made tremendous advances in elucidating tribe- and genus-level relationships within the family in recent decades. Our review focused on the phylogeny and systematics of Sassafras, a genus of three species with highly disjunct distributions in eastern North America and East Asia, whose tribe affiliation within the Lauraceae has long been controversial. By synthesizing information on the floral biology and molecular phylogeny of Sassafras, this review aimed to explore the position of Sassafras within the Lauraceae, and to provide suggestions and implications for future phylogenetic studies. Our synthesis highlighted Sassafras as a transitional type between Cinnamomeae and Laureae with a closer genetic relationship with Cinnamomeae, as revealed by molecular phylogenetic evidence, while it shares many similar characteristics with Laureae in morphology. We therefore discovered that several molecular and morphological methods should be concurrently considered to illuminate the phylogeny and systematics of Sassafras in Lauraceae.

Sassafras tzumu (Hemsl.) Hemsl., as an Arctic Tertiary relict woody species, is an ecologically and economically important deciduous tree endemic to southern China. Nonetheless, the genetic resources and backgrounds of S. tzumu are still lacking and remain largely unclear. Here, we predicted 16,215 candidate polymorphic nuclear microsatellite (nSSR) loci from the assembled nucleus databases of six geographic-distant individuals of S. tzumu via CandiSSR. Among these nSSRs, the di- (75.53%) and tri-nucleotide (19.75%) repeats were the most abundant, and 27 new polymorphic SSRs were developed and characterized in 136 individuals from six natural populations of S. tzumu. The majority of the above 27 SSRs (24 loci, 88.89%) presented moderate polymorphism (mean PIC = 0.356), and the transferability of these markers in other Sassafras species was high (85.19%). A moderately low level of genetic diversity and a high variation (FST = 0.286) of six wild populations of S. tzumu were illuminated by 16 selected polymorphic nSSRs, with the average expected heterozygosity (HE) of 0.430 at the species level and HE ranging from 0.195 to 0.387 at the population level. Meanwhile, a bottleneck effect was shown in two populations. Consistent with the results of the principal coordinate analysis (PCoA) and phylogenetic trees, structure analysis optimally divided these six S. tzumu populations into two clusters, and the further strong population subdivision appeared from K = 2 to K = 5, which corresponded to two evolutionarily significant units (ESUs). Moreover, the significant correlation between genetic and geographic distance was tested by the Mantel test (r = 0.742, p = 0.006), clarifying the effect about isolation by distance (IBD), which could be possibly explained by the low gene flow (Nm = 0.625), a relatively high degree of inbreeding (FIS = 0.166), a relatively large distribution, and mountainous barriers. Above all, our research not only enlarged the useful genetic resources for future studies of population genetics, molecular breeding, and germplasm management of S. tzumu and its siblings but also contributed to proposing scientific conservation strategies and schemes for the better preservation of S. tzumu and other Sassafras (Lauraceae) species.

Aiming at the characteristics of underwater pure orientation target tracking, an adaptive box length Kullback-Leibler Distance (KLD) Particle Filter (PF) algorithm is proposed based on traditional adaptive KLD PF algorithm. When performing underwater pure orientation target tracking, the traditional adaptive KLD sampling may have a problem that the filtering accuracy is reduced or even invalid due to the fixed length of the KLD box. In the algorithm proposed in this paper, the length of the KLD box can be automatically adjusted according to the current particle distribution range, which can well solve the problem of precision degradation caused by the fixed KLD box length of the traditional adaptive KLD algorithm. The effectiveness of the adaptive box length KLD PF algorithm is verified by comparison with the traditional KLD PF algorithm in simulation. In this simulation, the adaptive box length KLD PF algorithm can effectively adapt to the changing environment of underwater tracking and has good tracking performance.

Air quality in China has gradually been improving in recent years; however, the Beijing-Tianjin-Hebei (BTH) region continues to be the most polluted area in China, with the worst air quality index. BTH and its surrounding areas experience high agglomeration of heavy-polluting manufacturers that generate electric power, process petroleum and coal, and carry out smelting and pressing of ferrous metals, raw chemical materials, chemical products, and non-metallic mineral products. This study presents evidence of the air pollution impacts of industrial agglomeration using the Ellison-Glaeser index, Herfindahl-Hirschman index, and spatial autocorrelation analysis. This was based on data from 73,353 enterprises in "2+26" atmospheric pollution transmission channel cities in BTH and its surrounding areas (herein referred to as BTH "2+26" cities). The results showed that Beijing, Yangquan, Puyang, Kaifeng, Taiyuan, and Jinan had the highest Ellison-Glaeser index among the BTH "2+26" cities; this represents the highest enterprise agglomeration. Beijing, Langfang, Tianjin, Baoding, and Tangshan also showed a low Herfindahl-Hirschman index of pollutant emissions, which have a relatively high degree of industrial agglomeration in BTH "2+26" cities. There was an inverted U-shaped relationship between enterprise agglomeration and air quality in the BTH "2+26" cities. This means that air quality improved with increased industrial agglomeration up to a certain level; beyond this point, the air quality begins to deteriorate with a decrease in industrial agglomeration.

Phoebe minutiflora H. W. Li, is a member of the Lauraceae family, while its generic relationship has been long-term controversial. The complete chloroplast (cp) genome of P. minutiflora was first reported in this paper. The cp genome was 152,654 bp in length with four typical quadripartite structures, which was consisted of a large single-copy (LSC) region of 93,697 bp, a small single-copy (SSC) region of 18,809 bp, and two inverted repeats (IRs) of 20,074 bp. In addition, there were a total of 112 unique genes, including 79 protein-coding genes, 29 tRNA genes, and four rRNA genes. The phylogenetic analysis indicated that P. minutiflora should be placed into Machilus.

Premise Pteroceltis tatarinowii (Ulmaceae), the only species of the genus Pteroceltis, is an endangered tree in China. Here, novel expressed sequence tag–simple sequence repeat (EST‐SSR) markers were developed to illuminate its genetic diversity for conservation and assisted breeding. Methods and Results Based on Illumina transcriptome data from P. tatarinowii, a total of 70 EST‐SSR markers were initially designed and tested. Forty‐eight of 70 loci (68.6%) were successfully amplified, of which 20 were polymorphic. The number of alleles per locus ranged from two to six, and the levels of observed and expected heterozygosity ranged from 0.018 to 0.781 and from 0.023 to 0.702, respectively. Additionally, cross‐amplification was successful for 17 loci in two related species, Ulmus gaussenii and U. chenmoui. Conclusions These new EST‐SSR markers are valuable transcriptomic resources for P. tatarinowii and will facilitate population genetics and molecular breeding of this species and its relatives in Ulmaceae.

This paper aims to evaluate the cost of environmental degradation by adopting the conventional environmental economic methodology in China from 2004 to 2017 and summarize the change in both the causes and costs of China’s environmental degradation. Results from this study revealed the following: i. The environmental degradation cost in China increased from 511 billion yuan to 1,892 billion yuan from 2004 to 2017, and its share in the GDP decreased from 3.05% to 2.23%; ii. The environmental degradation cost growth rate was lower than the GDP growth rate. The environmental degradation cost growth rate decreased sharply, by dropping from 10% in 2014 to 2% in 2017. The environmental benefits of industrial transformation have emerged; iii. The provinces of Shandong, Hebei, Jiangsu, Henan, and Guangdong had the highest environmental degradation costs. The annual average growth rate of the environmental degradation costs in Jiangsu, Guangdong, and Zhejiang were lower than their growth rate of the GDP respectively; iv. Consideration of environmental degradation cost in decision-making could contribute to the high-quality development of China.

In order to realize rapid extraction of the center coordinates for row billet end faces when labeled by multi-strand billet end face labeling robot, a research program is proposed that the image coordinates in billet end face image are extracted and then the center point's coordinates of the billets end face image are calculated. Firstly, an improved SUSAN corner detection algorithm is proposed to solve the corner leak detection problem caused by the distance between the adjacent billet image edge being too small and the billet image corner angle being the arc angle. Then, the image plane coordinates of corners point are extracted, and the number of the billets end faces image in each enclosed area is calculated. Finally, a method for extracting the coordinates of slant billet end faces is provided, and the center point image plane coordinates of each billet end face are calculated, respectively. The robot labeling experiment of each billet end face in a row billet is carried out, and experimental results indicate that the horizontal and vertical labeling position error ranges of each billet end face are -0.625~0.850 mm and -0.550~0.875 mm, respectively, meeting the enterprises' allowed center coordinates position error value 1 mm of the billet end face fully. The visual methods mentioned in this paper are feasible in both theoretical and practical applications, and it not only provides an accurate labeling position for the continuous blank end labeling robot, but also provides a reliable method for extracting the center coordinates of rectangular image elements, and has some application value.

Line structured light sensor (LSLS) is composed of a laser line projector and a camera. The profile data of the measured object can be obtained by analyzing the perturbed stripe images captured by the camera. The sensors have the advantages of simple construction, low cost, non-contact, high efficiency and flexible application. Thus, they have gained extensive application prospects in research and industry. The measuring technique by use of the LSLSs is reviewed in four aspects as quality control of stripe images and center extraction, sensor calibration, collaborative measurement via multiple sensors, and the integration of the sensor with motion axes. The current problems in the research and the application of this measuring technique are summarized, and the future research trends can be concluded as further improving the measuring accuracy, enhancing the sensor adaptability, and developing the structured light sensor based intelligent measuring system.

Celtis sinensis Pers. is a popular garden landscape tree in riparian areas and a valuable resistant tree in many extreme environments. Here, we determined the first complete chloroplast genome of C. sinensis using high-throughput sequencing technology. Our results showed the chloroplast genome of C.sinensis was 159,092 bp long and displayed a typical quadripartite structure consisting of a pair of inverted repeats with a length of 26,895 bp and separating by two single-copy regions (LSC, 86,085 bp and SSC, 19,217 bp). Besides, the chloroplast genome of C. sinensis totally contained 131 genes, including 87 protein coding genes, 36 transfer RNAs and eight ribosomal RNAs. Additionally, a maximum likelihood phylogenetic analysis based on the 19 chloroplast genomes demonstrated the monophyly of Cannabaceae and C. sinensis formed a sister clade to Celtis biondii.

Abstract The unfavorable I–V characteristics of perovskite solar cells (PSCs), such as the I–V hysteresis phenomena, have been one major obstacle for their future practical application. However, corresponding analysis based on traditional theories have shown non-negligible flaws and failed for satisfactory explanation. To present a novel mechanism, here we utilize for the first time the memristive property of the perovskite material to analyze the I–V characteristics of PSCs. The obtained joint physical model and the deduced equation may help solving the long-existent mysteries of the I–V characteristics of PSCs. On the basis of our analysis and memristor theory, we also propose an original device optimization strategy for PSCs, which may help further increase their performance to the limit.

Lauraceae is a large family of woody plants with high ecological and economic value. The tribal and generic division and phylogenetic relationship of Lauraceae have long been controversial. Based on morphological and molecular evidence, phylogenetic relationships within the Cinnamomeae, Laureae and Perseeae tribes, also called ‘the Core Lauraceae’, have arisen particular attention. In this review, we comprehensively collated the literatures on the phylogeny of Lauraceae published in recent years and summarized progress made in molecular systematic researches employing gene fragments, chloroplast genomes and DNA barcodings analyses. We clarified the phylogenetic relationships and main controversies of ‘the Core Lauraceae’, the systemic position of fuzzy genera (Neocinnamomum, Caryodaphnopsis and Cassytha) and the development of chloroplast genome and DNA barcodes. We further suggested and proposed the whole genome analysis and different inflorescence types would be possible to provide more information for further research on phylogenetic relationships and taxonomy of Lauraceae.

A line structured light sensor (LSLS) is generally constituted of a laser line projector and a camera. With the advantages of simple construction, non-contact, and high measuring speed, it is of great perspective in 3D measurement. For traditional LSLSs, the camera exposure time is usually fixed while the surface properties can be varied for different measurement tasks. This would lead to under/over exposure of the stripe images or even failure of the measurement. To avoid these undesired situations, an adaptive control method was proposed to modulate the average stripe width (ASW) within a favorite range. The ASW is first computed based on the back propagation neural network (BPNN), which can reach a high accuracy result and reduce the runtime dramatically. Then, the approximate linear relationship between the ASW and the exposure time was demonstrated via a series of experiments. Thus, a linear iteration procedure was proposed to compute the optimal camera exposure time. When the optimized exposure time is real-time adjusted, stripe images with the favorite ASW can be obtained during the whole scanning process. The smoothness of the stripe center lines and the surface integrity can be improved. A small proportion of the invalid stripe images further proves the effectiveness of the control method.

It is a difficult task to analyze the coupling characteristics of rotating machinery fault signals under the influence of complex and nonlinear interference signals. This difficulty is due to the strong noise background of rotating machinery fault feature extraction and weaknesses, such as modal mixing problems, in the existing Ensemble Empirical Mode Decomposition (EEMD) time⁻frequency analysis methods. To quantitatively study the nonlinear synchronous coupling characteristics and information transfer characteristics of rotating machinery fault signals between different frequency scales under the influence of complex and nonlinear interference signals, a new nonlinear signal processing method—the harmonic assisted multivariate empirical mode decomposition method (HA-MEMD)—is proposed in this paper. By adding additional high-frequency harmonic-assisted channels and reducing them, the decomposing precision of the Intrinsic Mode Function (IMF) can be effectively improved, and the phenomenon of mode aliasing can be mitigated. Analysis results of the simulated signals prove the effectiveness of this method. By combining HA-MEMD with the transfer entropy algorithm and introducing signal processing of the rotating machinery, a fault detection method of rotating machinery based on high-frequency harmonic-assisted multivariate empirical mode decomposition-transfer entropy (HA-MEMD-TE) was established. The main features of the mechanical transmission system were extracted by the high-frequency harmonic-assisted multivariate empirical mode decomposition method, and the signal, after noise reduction, was used for the transfer entropy calculation. The evaluation index of the rotating machinery state based on HA-MEMD-TE was established to quantitatively describe the degree of nonlinear coupling between signals to effectively evaluate and diagnose the operating state of the mechanical system. By adding noise to different signal-to-noise ratios, the fault detection ability of HA-MEMD-TE method in the background of strong noise is investigated, which proves that the method has strong reliability and robustness. In this paper, transfer entropy is applied to the fault diagnosis field of rotating machinery, which provides a new effective method for early fault diagnosis and performance degradation-state recognition of rotating machinery, and leads to relevant research conclusions.

Laser stripe center extraction is a key step for the profile measurement of line structured light sensors (LSLS). To accurately obtain the center coordinates at sub-pixel level, an improved gray-gravity method (IGGM) was proposed. Firstly, the center points of the stripe were computed using the gray-gravity method (GGM) for all columns of the image. By fitting these points using the moving least squares algorithm, the tangential vector, the normal vector and the radius of curvature can be robustly obtained. One rectangular region could be defined around each of the center points. Its two sides that are parallel to the tangential vector could alter their lengths according to the radius of the curvature. After that, the coordinate for each center point was recalculated within the rectangular region and in the direction of the normal vector. The center uncertainty was also analyzed based on the Monte Carlo method. The obtained experimental results indicate that the IGGM is suitable for both the smooth stripes and the ones with sharp corners. The high accuracy center points can be obtained at a relatively low computation cost. The measured results of the stairs and the screw surface further demonstrate the effectiveness of the method.