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Abstract Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.

Abstract Amid economic globalisation and the rapid development of advanced technologies in recent years, the world economy has shown an increasing trend of digitalisation, whilst digital trade has become the primary pattern of international trade. Based on differences rooted in socio-political systems, as well as the current precarious geopolitical realities, governments adopt different ideas in accordance with their respective interests in the institutionalisation of digital trade. As the world’s second-largest economy and a major digital power, China’s behaviours and ideological stances attract scholarly attention and states’ concern. Whilst Western countries and scholars have criticised China’s ideas of “government intervention in data regulation” and “cyber sovereignty” applied in its existing approach to digital trade, warning that China’s approach poses a threat to Western powers’ adherence to liberalism in the international digital trade system and the idea of “free data flow” in their approaches to digital trade, there has been insufficient research into how China’s approach to digital trade has evolved over time and which ideas and interests have influenced it. To bridge this gap in the literature, this paper divides the evolution of China’s approach to digital trade over the past three decades (1993–2023) into three phases using a longitudinal approach. This research conducts qualitative content analysis using official documents, white papers, and declarations from official Chinese websites, then adopts the 3I analytical framework to analyse which ideas and interests have influenced China’s approach in each phase and how its approach to digital trade has evolved over time.

BackgroundSolitary fibrous tumor (SFT) is a rare soft tissue tumor originating from mesenchymal cells. Thus far, there have been no reported cases of SFT closely related to the iliac vessels.Case presentationAn elderly woman was found to have had a lower abdominal mass for more than 20 years. The enhanced computerized tomography (CT) showed a progressively enhanced hypervascular mass. The external iliac blood vessels were closely related to the mass, which was misdiagnosed as an ovarian tumor. During laparotomy, the external iliac vein was seen to penetrate the tumor, and the external iliac artery was seen to penetrate the tumor capsule. The retroperitoneal tumor was diagnosed during the operation. The surgical plan of complete tumor resection, severing of the external iliac arteries and veins, and blood vessel replacement was implemented. Pathological immunohistochemistry showed positive results for STAT6 and CD34, confirming the diagnosis of giant retroperitoneal SFT. The risk is classified as high and requires long-term follow-up. There has been no local recurrence or distant metastasis almost 1 year after surgery.ConclusionThe incidence of giant retroperitoneal SFT is rare, and the diagnosis can be confirmed through preoperative imaging examination and pathological examination. If the SFT capsule is intact, there is a chance of surgical resection. For SFTs that are penetrated by the iliac blood vessels, adequate preparation must be made before the surgery is performed. Removing the tumor and the iliac blood vessels at the corresponding site and then replacing it with artificial blood vessels is a feasible method with less risk of bleeding. In this case, imaging showed a progressively enhancing hypervascular mass in the lower abdomen, which was related to blood vessels. Preoperative biopsy and pathological testing can confirm the diagnosis. Neoadjuvant therapy or interventional therapy before surgery can shrink the tumor, making the surgical procedure relatively easy with less risk of bleeding.

There is an increasing demand for data with the development of the world, and various fiber optic multiplexing techniques have become an important research direction to improve transmission capacity. However, the transmitted signals are subject to great interference due to mode coupling and mode dispersion, which require multiple-input multiple-output (MIMO) digital signal processing techniques to restore the quality of the transmitted signals. In this paper, a novel MIMO detector is designed using an adaptive learning recurrent neural network and successfully implemented in a mixed wavelength-division-mode-division-multiplexing (WDM-MDM) optical transmission system, and its performance is compared with that of the forced-zero detector and the minimum-mean-square-error detector. The results show that the introduction of an adaptive machine learning model in MIMO detection for WDM-MDM optical transmission systems can significantly improve the quality of the transmitted signals and achieve better performance than other MIMO detection algorithms while maintaining a faster computational speed and a lower number of parameters.

Understanding how human leukocyte antigen (HLA) polymorphism affects both the susceptibility and severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection will help to identify individuals at higher risk to better manage and prioritize vaccination at the clinical level and explain the differences in epidemic trends in different regions at the epidemiological level. This study compared the frequencies of HLA class I alleles (HLA-A, B) in 214 coronavirus disease 2019 (COVID-19) patients with different disease severity and 35 healthy controls and analyzed the correlations between specific HLA alleles and disease severity and T cell memory. The results showed no significant difference in HLA allele frequencies between COVID-19 patients and healthy controls (P > 0.05). The allele HLA-B*13:02 was significantly correlated with the disease severity of COVID-19 patients (P = 0.006). After adjustment for age and disease severity, the T cell responses of COVID-19 convalescents with the allele HLA-B*40:01 may be lower at six months (P = 0.044) and 12 months (P = 0.069). Moreover, these results may be due to their rare peptide anchors by analyzing the binding peptide motifs of these HLA alleles. The study may be valuable for investigating the potential association of specific HLA alleles with SARS-CoV-2 infection.

Baijiu, one of the world’s six major distilled spirits, has an extremely rich flavor profile, which increases the complexity of its flavor quality evaluation. This study employed an electronic nose (E-nose) and electronic tongue (E-tongue) to detect 42 types of strong-aroma Baijiu. Linear discriminant analysis (LDA) was performed based on the different production origins, alcohol content, and grades. Twelve trained Baijiu evaluators participated in the quantitative descriptive analysis (QDA) of the Baijiu samples. By integrating characteristic values from the intelligent sensory detection data and combining them with the human sensory evaluation results, machine learning was used to establish a multi-submodel-based flavor quality prediction model and classification model for Baijiu. The results showed that different Baijiu samples could be well distinguished, with a prediction model R2 of 0.9994 and classification model accuracy of 100%. This study provides support for the establishment of a flavor quality evaluation system for Baijiu.

Summary: Investigating immune memory to vaccinia virus and pre-existing immunity to mpox virus (MPXV) among the population is crucial for the global response to this ongoing mpox epidemic. Blood was sampled from vaccinees inoculated with vaccinia virus Tiantan (VTT) strain born before 1981 and unvaccinated control subjects born since 1982. After at least 40 years of the inoculation, 60% or 5% VTT vaccinees possess neutralizing antibodies (NAbs) to VTT or MPXV, with at least 50% having T cell memory to VTT protein antigens. Notably, 46.7% vaccinees show pre-existing T cell responses to MPXV. Broad pre-existing CD8+ T cell reactivities to MPXV are detected not only against conserved epitopes but also against variant epitopes between VTT and MPXV. Persistent NAbs and T cell memory to VTT among vaccinees, along with pre-existing T cells to MPXV among both vaccinees and the unvaccinated population, indicate a particular immune barrier to mpox.

BackgroundDisseminated tuberculosis is an uncommon but devastating form of tuberculosis, possibly developing with the immune response of patients. COVID-19 infection may produce an immunosuppressive effect with possible implications for tuberculosis dissemination.Case presentationA 17-year-old female patient with a history of tuberculous pleurisy presented to the hospital with a high fever and life-threatening dyspnea after contracting a COVID-19 infection. Her condition deteriorated rapidly with grand mal epilepsy and acute gastrointestinal bleeding with a grossly depressed CD4 T-cell count, which was indicative of her profoundly immunosuppressed state. After identifying Mycobacterium tuberculosis in her cerebrospinal fluid and a subcutaneous abscess in her left lower back, she was diagnosed with disseminated tuberculosis involving both lungs, the central nervous system, the terminal ileum, the liver, bilateral adnexal tissue, and subcutaneous soft tissue in accordance with the chest and abdominal CT. Empirical treatment was initiated with dexamethasone (5 mg/day) and an anti-tuberculosis regimen of isoniazid, rifampicin, pyrazinamide, amikacin, and meropenem, which was replaced with faropenem after she left the hospital. The therapeutic effect was considered satisfied in the second month of follow-up.ConclusionTo the best of our knowledge, we report the first case report of disseminated tuberculosis after COVID-19 infection. Tuberculosis may disseminate and progress during the COVID-19 pandemic, requiring more significant studies to provide better diagnosis and treatment options for the co-infection.

Tilapia is a freshwater fish group with a sustainable prospect but suffers off-notes appearing during cooking processes. To promote pleasant odorants by thermal cooking processes, tilapia fillets were cooked in different ways (roasting, microwave-heating, boiling and steaming). Their aroma profiles were analysed with special focus on off-notes and umami-enhancing odorants by principal component analysis, and correlated with the heating time, colour, moisture and water activity by partial least squares regression analysis. Results showed that the “green” and “earthy” off-notes were highly correlated with the boiling process (excess of water, short heating time), while most of the umami-enhancing odorants had a high association with the roasting process (low water content, long heating time, better Maillard reaction). This study indicated that roasting is the most adapted cooking process promoting Maillard-derived aromas, umami-enhancing aromas and meanwhile, reducing off-notes. This research helps in understanding the off-note generation in tilapia and promoting desirable umami-enhancing odorants.

Sanhuang chicken is a popular native breed in China and well-known for delicious flavour. Spices could enhance the chicken meat flavour and work well in preservation. Chinese 5-spice blend (CS) and garam masala (GM) are routinely using spices in China and Pakistan, respectively. The flavour profiles of Sanhuang chicken breast (CB) and its blends with CS and GM were obtained by electronic nose (E-nose), solid-phase microextraction gas chromatography-mass spectrometry (SPME GC-MS) and GC-ion mobility spectrometry (GC-IMS). Principal component analysis (PCA) efficiently discriminated the aroma profiles of three chicken formulations. The GC-chromatographs revealed the significant aroma alterations of chicken breast meat after marination with spices. Aldehydes were the major contributors of chicken aroma, while most of the aromatic hydrocarbons were generated by spices. Almost all chicken key-compounds produced by oxidation reaction were either reduced or eliminated by marination, showing the antioxidation capacity of spices leading to meat preservation. GC-IMS is not only a rapid and comprehensive detection method, but also proved to be more sensitive than GC-MS. The substantial role of both traditional spices in enhancing flavour quality of chicken meat, and their exposure as functional ingredients in Chinese and Pakistan cuisines could lead to the cross-cultural meat trade opportunities.

BackgroundChina is a country with a high burden of tuberculosis (TB). TB outbreaks are frequent in schools. Thus, understanding the transmission patterns is crucial for controlling TB.MethodIn this genomic epidemiological study, the conventional epidemiological survey data combined with whole-genome sequencing was used to assess the genotypic distribution and transmission characteristics of Mycobacterium tuberculosis strains isolated from patients with TB attending schools during 2015 to 2019 in Guangzhou, China.ResultThe TB incidence was mainly concentrated in regular secondary schools and technical and vocational schools. The incidence of drug resistance among the students was 16.30% (22/135). The phylogenetic tree showed that 79.26% (107/135) and 20.74% (28/135) of the strains belonged to lineage 2 (Beijing genotype) and lineage 4 (Euro-American genotype), respectively. Among the 135 isolates, five clusters with genomic distance within 12 single nucleotide polymorphisms were identified; these clusters included 10 strains, accounting for an overall clustering rate of 7.4% (10/135), which showed a much lower transmission index. The distance between the home or school address and the interval time of symptom onset or diagnosis indicated that campus dissemination and community dissemination may be existed both, and community dissemination is the main.Conclusion and recommendationTB cases in Guangzhou schools were mainly disseminated and predominantly originated from community transmission. Accordingly, surveillance needs to be strengthened to stop the spread of TB in schools.

The wide colour gamut displays have improved the viewing experience greatly. However, highly saturated colours may also bring problems such as visual discomfort. In this study, the influence of colour saturation on visual discomfort is investigated. Visual stimuli sequences with different images and saturation levels were presented in subjective and objective experiments. The scores of image quality, visual comfort, and preference were collected in questionnaires. The peak amplitude of heamodynamic response was extracted from fNIRS. The results show that, in the mid saturation level, subjective evaluation on visual discomfort was the lowest and the smallest peak amplitude of heamodynamic response was observed. While the image quality and preference increased as the saturation increased. For wide colour gamut displays, the visual discomfort induced by highly saturated colours should be taken into consideration.

Abstract Since the implementation of the Chinese economic reforms. The habitat quality of coastal has gradually deteriorated with economic development, but the concept of "ecological construction" has slowed the negative trend. For quantitative analysis of the correlation between the Pearl River Delta urban expansion and changes in habitat quality under the influence of the policy, we first analyzed the habitat quality change based on the InVEST model and then measured the impact of construction land expansion on the habitat quality through habitat quality change index (HQCI) and contribution index (CI) indicators. Finally, the correlation between urbanization level and habitat quality was evaluated using geographically weighted regression (GWR) and the Self-organizing feature mapping neural network (SOFM). The results indicated that: (1) during the study period from 2000 to 2020, habitat quality declined due to urban sprawl, indicating a deterioration of ecological structure and function, and the decrease was most significant from 2000 to 2010. (2) The urbanization index had a negative effect on the habitat quality, but the negative effect have improved after 2000, reflecting the positive effect of policies such as "ecological civilization construction" (3) The implementation degree of ecological civilization varies greatly among cities in the study area: Shenzhen, Dongguan, Foshan, and Zhongshan have the best level of green development. These results reflect the positive role of policies in the prevention of damage to habitat quality caused by economic development and provide a reference for the formulation of sustainable urban development policies with spatial differences.

Abstract Background Lung cancer is the most frequently diagnosed carcinoma and the leading cause of cancer-related mortality. Although molecular targeted therapy and immunotherapy have made great progress, the overall survival (OS) is still poor due to a lack of accurate and available prognostic biomarkers. Therefore, in this study we aimed to establish a multiple-gene panel predicting OS for lung adenocarcinoma. Methods We obtained the mRNA expression and clinical data of lung adenocarcinoma (LUAD) from TCGA database for further integrated bioinformatic analysis. Lasso regression and Cox regression were performed to establish a prognosis model based on a multi-gene panel. A nomogram based on this model was constructed. The receiver operating characteristic (ROC) curve and the Kaplan–Meier curve were used to assess the predicted capacity of the model. The prognosis value of the multi-gene panel was further validated in TCGA-LUAD patients with EGFR, KRAS and TP53 mutation and a dataset from GEO. Gene set enrichment analysis (GSEA) was performed to explore potential biological mechanisms of a novel prognostic gene signature. Results A four-gene panel (including DKK1, GNG7, LDHA, MELTF) was established for LUAD prognostic indicator. The ROC curve revealed good predicted performance in both test cohort (AUC = 0.740) and validation cohort (AUC = 0.752). Each patient was calculated a risk score according to the model based on the four-gene panel. The results showed that the risk score was an independent prognostic factor, and the high-risk group had a worse OS compared with the low-risk group. The nomogram based on this model showed good prediction performance. The four-gene panel was still good predictors for OS in LUAD patients with TP53 and KRAS mutations. GSEA revealed that the four genes may be significantly related to the metabolism of genetic material, especially the regulation of cell cycle pathway. Conclusion Our study proposed a novel four-gene panel to predict the OS of LUAD, which may contribute to predicting prognosis accurately and making the clinical decisions of individual therapy for LUAD patients.

Abstract The interactions between the gut microbiome and metabolome play an important role in human health and diseases. Current studies mainly apply statistical correlation analysis between the gut microbiome and all the identified metabolites to explore their relationship. However, it remains challenging to identify the specific metabolic functions of microbes without in vitro culture experiments for validation. Discriminating the microbial metabolites from others (e.g., host, food, or environment) and exploring their metabolic functions and correlations with microbiome specifically may improve the efficiency and accuracy of biomarker discovery. So far, there have been no such bioinformatics tools available. Herein, we developed MetOrigin, an interactive web server that discriminates metabolites originating from the microbiome, performs the origin‐based metabolic pathway enrichment analysis, and integrates the statistical correlations and biological relationships in the database using Sankey network visualization. MetOrigin not only enables the quick identification of microbial metabolites and their metabolic functions but also facilitates the discovery of specific bacterial species that are closely associated with metabolites statistically and biologically. MetOrigin is freely available at http://metorigin.met-bioinformatics.cn/.

Abstract Background CD8+CD28− T suppressor (Ts) cells play critical role in transplant tolerance. Our previous study has generated CD8+CD28− Ts cells in vitro which exert robust allospecific suppressive capacity in vitro. Results CD8+CD28− Ts cells were expanded by stimulating human CD8+ T cells with allogeneic antigen presenting cells in the presence of the common gamma chain cytokines IL-2, IL-7 and IL-15 in vitro, and were further verified in vitro through day 7 to 11 for their persistency of the allospecific suppressive capacity. When CD8+CD28− Ts cells were adoptively transferred into NOG mice, their capacity to inhibit CD4+ T cell proliferation in allospecific manner remained potent on 11 days after their injection. The mechanisms for expansion of CD8+CD28− Ts cells by the common gamma chain cytokines were investigated. These included promoting CD8+CD28− T cells proliferation, converting CD8+CD28+ T cells to CD8+CD28− T cells and decreasing CD8+CD28− T cell death. Furthermore, the expanded CD8+CD28− Ts cells showed upregulation of the co-inhibitory molecule Tim-3 and down-regulation of the cytotoxic molecule granzyme B. Conclusions In summary, these results demonstrated that the in vitro-expanded human CD8+CD28− T cells retained potent allospecific suppressive capacity in vivo and depicted multiple mechanisms for the expansion of Ts cells, which might promote further bench to clinic research.

Rapid industrialization and urbanization accelerate land use and land cover change, resulting in problems of stability and health with ecosystem services losses. It remains unclear and needs to be detailed discussed what spatial–temporal characteristics of the production-living-ecological spaces (PLES) would be in a rapidly developing bay area under a certain development goal. A novel future land use simulation model integrated with a dual environment evaluation system consisting of the evaluation of resources and environmental carrying capacity and territorial spatial development suitability was conducted to predict the PLES in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in a multi-scenario view; and then we figured out the spatial–temporal changes of the PLES in the GBA during 2015–2035. Results suggest: 1) Using the DEE to determine conversion probability estimation helps to simulate and predict land use changes with high accuracy. Under the CUA scenario, the PLES account for 21.76%, 14.60% and 63.64%, respectively. The production space in Shenzhen, Hong Kong and Dongguan is dispersed, while the living space in Dongguan is clustered. The patch boundary of ecological space in Zhaoqing, Huizhou and Jiangmen would become more complex. 2) The change of the PLES in the GBA is mainly manifested by the processes of production and ecological space transferring to living space even under CUA scenario, which mainly occurs on the edge of the existing living space, especially in Zhaoqing, Conghua District of Guangzhou, Longmen County and Boluo County of Huizhou. 3) With potential conflicts between production space and ecological space, more attention should be paid to reducing the occupation of basic farmland in ecological restoration in the GBA. The future PLES in the GBA would be characterized by the conflict between the living and non-living spaces and that between productive and ecological spaces. The predicted PLES under CUA scenario may provide a spatial reference for policy-making in the future territorial spatial development and construction of ecological security patterns in the GBA.

Cultivation conditions may greatly affect fruit quality, especially in the accumulation of functional metabolites. Blackcurrant fruits (Ribes nigrum L.) have high ascorbic acid (AsA) concentrations. The purpose of the current study was to investigate the influence of different shading treatments (full sunlight, and 40% and 60% sunlight) on the fruits’ maturity, and on the levels of fruit firmness, soluble solid, AsA, and enzyme activity involved in AsA biosynthesis and recycling in two blackcurrant (Ribes nigrum) cultivars, ‘Heifeng’ and ‘Adelinia’. Shading conditions of 40% and 60% sunlight delayed fruit ripening and increased fruit firmness in both ‘Adelinia’ and ‘Heifeng’. Soluble solids in ‘Adelinia’ were markedly reduced by shading compared with ‘Heifeng’. Compared with full sunlight, the AsA content was significantly decreased in the ripe fruits under the 40% and 60% shading treatments. Additionally, the AsA content was decreased during the fruit development process under the 60% shading treatment, which was associated with the reduced activity of the enzymes monodehydroascorbate reductase (MDHAR), dehydroascorbate reductase (DHAR), glutathione oxidoreductase (GR), ascorbate peroxidase (APX), and L-galactose dehydrogenase (GalDH) involved in the biosynthesis and recycling pathway of AsA. The correlation analysis results showed that the activity of MDHAR, DHAR, GR, APX, and GalDH was significantly positively correlated with AsA concentrations during the 60% shading treatment in ‘Adelinia’ and ‘Heifeng’ fruits, suggesting that AsA biosynthesis and recycling were affected and the two cultivars have similar mechanisms to deal with shading. Our results not only provide a better understanding of the regulation mechanism of AsA accumulation under shading, but also provide a theoretical basis for taking effective cultivation measures aimed at the improvement of AsA levels in blackcurrant fruits.

With the continuous miniaturization of conventional integrated circuits, obstacles such as excessive cost, increased resistance to electronic motion, and increased energy consumption are gradually slowing down the development of electrical computing and constraining the application of deep learning. Optical neuromorphic computing presents various opportunities and challenges compared with the realm of electronics. Algorithms running on optical hardware have the potential to meet the growing computational demands of deep learning and artificial intelligence. Here, we review the development of optical neural networks and compare various research proposals. We focus on fiber-based neural networks. Finally, we describe some new research directions and challenges.

The uniform distribution of silver nanoparticles on the surfaces of diamond-wire sawn multicrystalline silicon (mc-Si) is critical for the texturing of mc-Si by the Ag metal-assisted chemical etching method (Ag-MACE). In this study, an additive containing alkylphenol polyoxyethylene is developed to improve the Ag-MACE process. It enables an even deposition of the silver nanoparticles over the surface of the silicon wafer, so that the entire wafer surface can be uniformly textured with nanostructures. The experimental results show that the additive improves the appearance and performance of solar cells, including their reflectivity, efficiency, internal quantum efficiency and external quantum efficiency. Mass-produced mc-Si solar cells textured using Ag-MACE with this additive have achieved a maximum efficiency of 19.51%, compared with an efficiency of 19.16% for cells fabricated without the additive. Keywords: Multicrystalline silicon, Solar cell, Diamond wire saw, Metal-assisted chemical etching, Uniform textures, Additive

Optical neural networks (ONNs) are getting more and more attention due to their advantages such as high-speed and low power consumption. However, in a non-ideal environment, the noise and low-bits control may heavily lead to a decrease in the accuracy of ONNs. Since there is AD/DA conversion in a simulated neural network, it needs to be quantified in the model. In this paper, we propose a quantitative method to adapt ONN to a non-ideal environment with fixed-point transmission, based on the new chip structure we designed previously. An MNIST hand-written data set was used to test and simulate the model we established. The experimental results showed that the quantization-noise model we established has a good performance, for which the accuracy was up to about 96%. Compared with the electrical method, the proposed quantization method can effectively solve the non-ideal ONN problem.

Solar-driven electrochromic smart windows with energy-storage ability are promising for energy-saving buildings. In this work, a flexible photoelectrochromic device (PECD) was designed for this purpose. The PECD is composed of two flexible transparent conductive layers, a photocatalytic layer, an electrochromic material layer, and a transparent electrolyte layer. The photocatalytic layer is a dye-sensitized TiO2 thick film and the electrochromic layer is a WO3 thin film, which also possesses a supercapacitive property. Under illumination, dye-sensitized TiO2 thick film realizes photo-drive electrochromism that the WO3 changes from colorless to blue with large optical modulation. Meanwhile, the PECD has an electrochemical supercapacitance showing an energy storage property of 21 mF·cm−2 (114.9 F·g−1 vs the mass of WO3), stable mechanical performance and long cycle performance. The PECD can effectively adjust the transmittance of visible and near-infrared light without any external power supply, realizing zero energy consumption, and can convert solar energy into electrical energy for storage.

In recent years, with the expansion of information, artificial intelligence technology has been developed and used in various fields. Among them, optical neural network provides a new type of special neural network accelerator chip solution, which has the advantages of high speed, high bandwidth, and low power consumption. In this paper, we construct an optical neural network based on Mach-Zehnder interferometer. The experimental results on the image classification of MNIST handwritten digitals show that the optical neural network has high accuracy, fast convergence and good scalability. [ABSTRACT FROM AUTHOR]

As one of Tibet's most vital traffic safety devices, guide signs are usually Tibetan-Chinese bilingual. Therefore, drivers need effective recognition of Tibetan-Chinese bilingual traffic signs for safe driving. This study aims to determine two design parameters of the Tibetan-Chinese bilingual guide signs: Tibetan character height (hT) and aspect (height to width) ratio. Two highway facilities were selected for the simulation experiment: a general highway intersection and a high-grade highway exit ramp. To incorporate drivers' visual recognition characteristics, 20 Tibetan drivers and 20 Han drivers were invited to wear head-mounted eye trackers for a dynamic driving simulation experiment of visual identification of guide signs. Four layout designs were used to analyze Tibetan and Han drivers' visual recognition characteristics. The regression model for hT was first developed based on the visibility theory of guide signs. Then, the character-height design values for the Tibetan-Chinese bilingual guide signs were established for different speed limits. The results of this study should help to optimize the design of traffic signs in Tibet and improve highway traffic safety. [ABSTRACT FROM AUTHOR]