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Existing evidence supported that congenital heart defect (CHD) was associated with a combination of environmental and genetic factors. Based on this, this study aimed at assessing the association of maternal folic acid supplementation (FAS), genetic variations in offspring methylenetetrahydrofolate dehydrogenase (MTHFD)1 and MTHFD2 genes, and their interactions with CHD and its subtypes. A hospital-based case–control study, including 620 cases with CHD and 620 healthy children, was conducted. This study showed that the absence of FAS was significantly associated with an increased risk of total CHD and its subtypes, such as atrial septal defect (ASD). FAS during the first and second trimesters was associated with a significantly higher risk of CHD in offspring compared to FAS during the three months prior to conception. The polymorphisms of offspring MTHFD1 and MTHFD2 genes at rs2236222, rs11849530, and rs828858 were significantly associated with the risk of CHD. Additionally, a significantly positive interaction between maternal FAS and genetic variation at rs828858 was observed for the risk of CHD. These findings suggested that pregnant women should carefully consider the timing of FAS, and individuals with higher genetic risk may benefit from targeted folic acid supplementation as a preventive measure against CHD. Full article

This study focuses on the translation of Buddhist scriptures into Chinese, specifically the Faju jing, a Chinese version of the Dhammapada completed in the third century CE. It reveals that the Faju jing is not a straightforward translation but a combination of different sources. The translator, Zhi Qian, faced challenges in integrating multiple translation practices, dealing with diverse original Indian languages, incorporating pre-existing phrases from other translators’ work, and managing divergent opinions within the translation team regarding the translation style. This multi-layered process of translation, involving the participation of multiple translators, also likely occurred in other early translations. These challenges extended beyond mere comprehension of the Indian text, resulting in potential errors and deviations from straightforward translations. It is possible that some mistranslations were a consequence of integrating multiple traditions within the source text, making it difficult for translators to maintain a consistent linguistic framework and leading to errors. Furthermore, this study highlights the remarkable efforts of Chinese translators who collaborated with foreign monks in translation groups. It emphasizes the important role of Chinese translators in integrating diverse translation processes and refining the language to suit Chinese readers. They incorporated earlier translations and modified the language to align with Chinese forms. Overall, this case study sheds light on the complexity of early Chinese Buddhist translations, influenced by the integration of multiple traditions and the localization of the texts. It underscores the significance of Chinese translators in the translation process and their contributions to the development of Chinese Buddhist literature. Full article

In phenylketonuria (PKU), natural protein tolerance is defined as the maximum natural protein intake maintaining a blood phenylalanine (Phe) concentration within a target therapeutic range. Tolerance is affected by several factors, and it may differ throughout a person’s lifespan. Data on lifelong Phe/natural protein tolerance are limited and mostly reported in studies with low subject numbers. This systematic review aimed to investigate how Phe/natural protein tolerance changes from birth to adulthood in well-controlled patients with PKU on a Phe-restricted diet. Five electronic databases were searched for articles published until July 2020. From a total of 1334 results, 37 articles met the eligibility criteria (n = 2464 patients), and 18 were included in the meta-analysis. The mean Phe (mg/day) and natural protein (g/day) intake gradually increased from birth until 6 y (at the age of 6 months, the mean Phe intake was 267 mg/day, and natural protein intake was 5.4 g/day; at the age of 5 y, the mean Phe intake was 377 mg/day, and the natural protein intake was 8.9 g/day). However, an increase in Phe/natural protein tolerance was more apparent at the beginning of late childhood and was >1.5-fold that of the Phe tolerance in early childhood. During the pubertal growth spurt, the mean natural protein/Phe tolerance was approximately three times higher than in the first year of life, reaching a mean Phe intake of 709 mg/day and a mean natural protein intake of 18 g/day. Post adolescence, a pooled analysis could only be performed for natural protein intake. The mean natural protein tolerance reached its highest (32.4 g/day) point at the age of 17 y and remained consistent (31.6 g/day) in adulthood, but limited data were available. The results of the meta-analysis showed that Phe/natural protein tolerance (expressed as mg or g per day) increases with age, particularly at the beginning of puberty, and reaches its highest level at the end of adolescence. This needs to be interpreted with caution as limited data were available in adult patients. There was also a high degree of heterogeneity between studies due to differences in sample size, the severity of PKU, and target therapeutic levels for blood Phe control. Full article

The microwave field is used for drying and disinfecting grains during the pre-sowing seed treatment. The use of a microwave field in these installations leads to an increase in their productivity and a decrease in the energy consumed by them. In grain dryers, where the grain moves in a dense layer without being loosened, one of the challenges in using microwave fields is ensuring sufficient uniformity of the field distribution. In this article, waveguide design options that introduce microwave radiation into the grain layer are discussed. The objective of this study was to use application software to find the optimum type of transmitter from the three options presented. A mathematical simulation of the electromagnetic field distribution was performed with the use of CST Microwave Studio software 2019 in order to evaluate and compare horn-type, rectangular, and semicircular waveguides. The data on the standing wave ratio and radiation efficiency of these types of waveguides have been reported. The specific features of the microwave electromagnetic field distribution and radiation power in the output of these waveguides have been described. The results of mathematical simulations revealed that semicircular waveguides with slot-type radiators are preferable for processing dense grain layers. Full article

The application of mulching film has significantly contributed to improving agricultural output and benefits, but residual film has caused severe impacts on agricultural production and the environment. In order to realize the accurate recycling of agricultural residual film, the detection of residual film is the first problem to be solved. The difference in color and texture between residual film and bare soil is not obvious, and residual film is of various sizes and morphologies. To solve these problems, the paper proposes a method for detecting residual film in agricultural fields that uses the attention mechanism. First, a two-stage pre-training approach with strengthened memory is proposed to enable the model to better understand the residual film features with limited data.Second, a multi-scale feature fusion module with adaptive weights is proposed to enhance the recognition of small targets of residual film by using attention. Finally, an inter-feature cross-attention mechanism that can realize full interaction between shallow and deep feature information to reduce the useless noise extracted from residual film images is designed. The experimental results on a self-made residual film dataset show that the improved model improves precision, recall, and mAP by 5.39%, 2.02%, and 3.95%, respectively, compared with the original model, and it also outperforms other recent detection models. The method provides strong technical support for accurately identifying farmland residual film and has the potential to be applied to mechanical equipment for the recycling of residual film. Full article

Emerging smart devices have gathered increasing popularity within the sports community, presenting a promising avenue for enhancing athletic performance. Among these, the Rise Dynamics Alpha (RD $\alpha$) smart gloves exemplify a system designed to quantify boxing techniques. The objective of this study is to expand upon the existing RD $\alpha$ system by integrating machine-learning models for striking technique and target object classification, subsequently validating the outcomes through empirical analysis. For the implementation, a data-acquisition experiment is conducted based on which the most common supervised ML models are trained: decision tree, random forest, support vector machine, k-nearest neighbor, naive Bayes, perceptron, multi-layer perceptron, and logistic regression. Using model optimization and significance testing, the best-performing classifier, i.e., support vector classifier (SVC), is selected. For an independent evaluation, a final experiment is conducted with participants unknown to the developed models. The accuracy results of the data-acquisition group are 93.03% (striking technique) and 98.26% (target object) and for the independent evaluation group 89.55% (striking technique) and 75.97% (target object). Therefore, it is concluded that the system based on SVC is suitable for target object and technique classification. Full article

Mobile emergency services are better able to meet the needs of frequent public emergencies; however, their data quality problems seriously affect decision-making. In order to reduce the interference of low-quality data and solve the problem of data quality ambiguity, this paper first summarizes the five characteristics of mobile emergency big data. Second, based on the characteristics of mobile emergency big data, four data quality dimensions are defined with reference to existing research and national standards and combined with the measure of medium truth degree to give single-dimension and multi-dimension data quality truth degree measure models. Finally, a subjective-objective, qualitative-quantitative mobile emergency big data quality evaluation method based on the measure of medium truth degree is formed. The validity and practicality of the method are also verified by examples of algorithmic analysis of fire text datasets from Australian mountain fire data and the Chinese Emergency Incident Corpus. The experiments show that the method can realize quantitative mobile emergency big data quality assessment, solve the problem of data quality ambiguity, and reduce the interference of low-quality data, so as to save resources and improve the analysis and decision-making ability. Full article

The implementation of precise agricultural fields can drive the intelligent development of agricultural production, and high-resolution remote sensing images provide convenience for obtaining precise fields. With the advancement of spatial resolution, the complexity and heterogeneity of land features are accentuated, making it challenging for existing methods to obtain structurally complete fields, especially in regions with blurred edges. Therefore, a multi-task learning network with attention-guided mechanism is introduced for segmenting agricultural fields. To be more specific, the attention-guided fusion module is used to learn complementary information layer by layer, while the multi-task learning scheme considers both edge detection and semantic segmentation task. Based on this, we further segmented the merged fields using broken edges, following the theory of connectivity perception. Finally, we chose three cities in The Netherlands as study areas for experimentation, and evaluated the extracted field regions and edges separately, the results showed that (1) The proposed method achieved the highest accuracy in three cities, with IoU of 91.27%, 93.05% and 89.76%, respectively. (2) The Qua metrics of the processed edges demonstrated improvements of 6%, 6%, and 5%, respectively. This work successfully segmented potential fields with blurred edges, indicating its potential for precision agriculture development. Full article

Satellite imaging mission planning is used to optimize satellites to obtain target images efficiently. Many evolutionary algorithms (EAs) have been proposed for satellite mission planning. EAs typically require evolutionary parameters, such as the crossover and mutation rates. The performance of EAs is considerably affected by parameter setting. However, most parameter configuration methods of the current EAs are artificially set and lack the overall consideration of multiple parameters. Thus, parameter configuration becomes suboptimal and EAs cannot be effectively utilized. To obtain satisfactory optimization results, the EA comp ensates by extending the evolutionary generation or improving the evolutionary strategy, but it significantly increases the computational consumption. In this study, a multi-objective learning evolutionary algorithm (MOLEA) was proposed to solve the optimal configuration problem of multiple evolutionary parameters and used to solve effective imaging satellite task planning for region mapping. In the MOLEA, population state encoding provided comprehensive population information on the configuration of evolutionary parameters. The evolutionary parameters of each generation were configured autonomously through deep reinforcement learning (DRL), enabling each generation of parameters to gain the best evolutionary benefits for future evolution. Furthermore, the HV of the multi-objective evolutionary algorithm (MOEA) was used to guide reinforcement learning. The superiority of the proposed MOLEA was verified by comparing the optimization performance, stability, and running time of the MOLEA with existing multi-objective optimization algorithms by using four satellites to image two regions of Hubei and Congo (K). The experimental results showed that the optimization performance of the MOLEA was significantly improved, and better imaging satellite task planning solutions were obtained. Full article

Personalized mappings become popular among the public with the support of data diversity and device diversity. To develop personalized maps, constructing map symbols through automated ways is beneficial. The formal representation of map symbols (i.e., expressing map symbols by mathematical operators) is fundamental to the automated construction of map symbols. A previous study to evaluate the feasibility of structures of Chinese characters for representing map symbols shows that 77.5% of map symbols can be represented by them, although there are imperfections in some cases. It means that: (1) the other 22.5% of symbols should be formally represented by other mathematical solutions, and (2) those imperfect cases should be made perfect through some modification or refinements. In this study, we solve the representation problems of these two types of map symbols (i.e., the map symbol did not or imperfectly fit the structures of Chinese characters) by employing additional basic operators and proposing some metric and color modifications. To validate these proposed solutions, experiments have been carried out by using eight sets of symbols that are publicly available (e.g., Google Icons). The results indicated that almost all the map symbols can be formally represented with additional operators and metric and color modifications. The percentages of map symbols that did not fit structures of Chinese characters solved by these operators and modifications are 2.4% and 20.1%, respectively. The percentages of map symbols that imperfectly fit them solved by these operators and modifications are 8.7% and 8%, respectively. This work could not only enrich cartographic theory but also prompt the mathematization of map symbol construction. Full article

Leber’s hereditary optic neuropathy (LHON) is a disease that affects the optical nerve, causing visual loss. The diagnosis of LHON is mostly defined by the identification of three pathogenic variants in the mitochondrial DNA. Idebenone is widely used to treat LHON patients, but only some of them are responders to treatment. In our study, we assessed the maximal respiration rate (MRR) and other respiratory parameters in eight fibroblast lines from subjects carrying LHON pathogenic variants. We measured also the effects of idebenone treatment on cell growth and mtDNA amounts. Results showed that LHON fibroblasts had significantly reduced respiratory parameters in untreated conditions, but no significant gain in MRR after idebenone supplementation. No major toxicity toward mitochondrial function and no relevant compensatory effect in terms of mtDNA quantity were found for the treatment at the tested conditions. Our findings confirmed that fibroblasts from subjects harboring LHON pathogenic variants displayed impaired respiration, regardless of the disease penetrance and severity. Testing responsiveness to idebenone treatment in cultured cells did not fully recapitulate in vivo data. The in-depth evaluation of cellular respiration in fibroblasts is a good approach to evaluating novel mtDNA variants associated with LHON but needs further evaluation as a potential biomarker for disease prognosis and treatment responsiveness. Full article

Land use and land cover (LULC) changes are of vital significance in fields such as environmental impact assessment and natural disaster monitoring. This study, through an analysis of 1432 papers over the past decade employing quantitative, qualitative, bibliometric analysis, and knowledge graph techniques, aims to assess the evolution and current landscape of deep learning (DL) in LULC. The focus areas are: (1) trend analysis of the number and annual citations of published articles, (2) identification of leading institutions, countries/regions, and publication sources, (3) exploration of scientific collaborations among major institutions and countries/regions, and (4) examination of key research themes and their development trends. From 2013 to 2023 there was a substantial surge in the application of DL in LULC, with China standing out as the principal contributor. Notably, international cooperation, particularly between China and the USA, saw a significant increase. Furthermore, the study elucidates the challenges concerning sample data and models in the application of DL to LULC, providing insights that could guide future research directions to accelerate progress in this domain. Full article

Tuberculosis remains one of the major health problems worldwide. Besides the lungs, tuberculosis affects other organs, including bones and joints. In the case of bone tuberculosis, current treatment protocols include necrectomy in combination with conventional anti-tuberculosis therapy, followed by reconstruction of the resulting bone defects. In this study, we compared autografting and implantation with a biodegradable composite scaffold for bone-defect regeneration in a tuberculosis rabbit model. Porous three-dimensional composite materials were prepared by 3D printing and consisted of poly(ε-caprolactone) filled with nanocrystalline cellulose modified with poly(glutamic acid). In addition, rabbit mesenchymal stem cells were adhered to the surface of the composite scaffolds. The developed tuberculosis model was verified by immunological subcutaneous test, real-time polymerase chain reaction, biochemical markers and histomorphological study. Infected animals were randomly divided into three groups, representing the infection control and two experimental groups subjected to necrectomy, anti-tuberculosis treatment, and plastic surgery using autografts or 3D-composite scaffolds. The lifetime observation of the experimental animals and analysis of various biochemical markers at different time periods allowed the comparison of the state of the animals between the groups. Micro-computed tomography and histomorphological analysis enabled the evaluation of osteogenesis, inflammation and cellular changes between the groups, respectively. Full article

The use of equipment such as dental handpieces and ultrasonic tips in the dental environment has potentially heightened the generation and spread of aerosols, which are dispersant particles contaminated by etiological factors. Although numerous types of personal protective equipment have been used to lower contact with contaminants, they generally do not exhibit excellent removal rates and user-friendliness in tandem. To solve this problem, we developed a prototype of an air-barrier device that forms an air curtain as well as performs suction and evaluated the effect of this newly developed device through a simulation study and experiments. The air-barrier device derived the improved design for reducing bioaerosols through the simulation results. The experiments also demonstrated that air-barrier devices are effective in reducing bioaerosols generated at a distance in a dental environment. In conclusion, this study demonstrates that air-barrier devices in dental environments can play an effective role in reducing contaminating particles. Full article

Blockchain technology is very useful. This paper considers the application of blockchain technology to smart contracts, green certification, and market information disclosure, and introduces the carbon trading market price as a parameter to solve the dynamic incentive problem of the government for port enterprises to reduce emissions under the carbon trading policy. Based on the state change of port carbon emission reduction, this paper uses principal–agent theory to construct the dynamic incentive contract model of government without blockchain, with blockchain, and when carbon trading is considered under blockchain, respectively, and uses the optimal control method to solve and analyze the model. This paper finds that only when the opportunity cost of port enterprises is greater than a certain critical point and the fixed cost of blockchain is less than a certain critical point, the implementation of blockchain will help improve government efficiency. However, only when the critical value of carbon emission reduction of port enterprises and the unit operating cost of blockchain are small, the government should start the carbon trading market under blockchain technology. Through numerical simulation, this paper also finds that it is usually beneficial for the government to regulate and appropriately increase the carbon trading market price. Full article