LO-Net: Deep Real-time Lidar Odometry

We present a novel deep convolutional network pipeline, LO-Net, for real-time lidar odometry estimation. Unlike most existing lidar odometry (LO) estimations that go through individually designed feature selection, feature matching, and pose estimation pipeline, LO-Net can be trained in an end-to-end manner. With a new mask-weighted geometric constraint loss, LO-Net can effectively learn feature representation for LO estimation, and can implicitly exploit the sequential dependencies and dynamics in the data. We also design a scan-to-map module, which uses the geometric and semantic information learned in LO-Net, to improve the estimation accuracy. Experiments on benchmark datasets demonstrate that LO-Net outperforms existing learning based approaches and has similar accuracy with the state-of-the-art geometry-based approach, LOAM

Evaluating GPT's Programming Capability through CodeWars' Katas

In the burgeoning field of artificial intelligence (AI), understanding the capabilities and limitations of programming-oriented models is crucial. This paper presents a novel evaluation of the programming proficiency of Generative Pretrained Transformer (GPT) models, specifically GPT-3.5 and GPT-4, against coding problems of varying difficulty levels drawn from Codewars. The experiments reveal a distinct boundary at the 3kyu level, beyond which these GPT models struggle to provide solutions. These findings led to the proposal of a measure for coding problem complexity that incorporates both problem difficulty and the time required for solution. The research emphasizes the need for validation and creative thinking capabilities in AI models to better emulate human problem-solving techniques. Future work aims to refine this proposed complexity measure, enhance AI models with these suggested capabilities, and develop an objective measure for programming problem difficulty. The results of this research offer invaluable insights for improving AI programming capabilities and advancing the frontier of AI problem-solving abilities.Comment: 9 page

Air pollution and timing of childbirth: a retrospective survey analysis based on birth registration data of Chinese newborns

ObjectivesCurrently, there is a lack of research on whether people will take action to avoid the harm of air pollution and the heterogeneous behavior of different groups. The goal of this paper is to examine the effects of air pollution on the resulting differential effects on newborns and the timing of pregnancy.MethodsBased on a survey of newborns in a total of 32 hospitals in 12 cities across China in 2011, and after matching with city-level air pollution data, a multiple regression statistical method is then used to examine how the pollution level in a certain period is related to the number of conceptions in that certain period, after controlling for region and season fixed effects.ResultsWe first demonstrate that exposure to air pollution during pregnancy is associated with a significant increase in adverse birth outcomes. Most importantly, the empirical results show that the number of conceptions decreased significantly during periods of severe air pollution.ConclusionEvidence suggests that air pollution may be causing some families to delay conception to reduce the possible adverse impact on neonatal outcomes. This helps us to understand the social cost of air pollution more, and then make more accurate environmental policies

Modeling User Viewing Flow using Large Language Models for Article Recommendation

This paper proposes the User Viewing Flow Modeling (SINGLE) method for the article recommendation task, which models the user constant preference and instant interest from user-clicked articles. Specifically, we employ a user constant viewing flow modeling method to summarize the user's general interest to recommend articles. We utilize Large Language Models (LLMs) to capture constant user preferences from previously clicked articles, such as skills and positions. Then we design the user instant viewing flow modeling method to build interactions between user-clicked article history and candidate articles. It attentively reads the representations of user-clicked articles and aims to learn the user's different interest views to match the candidate article. Our experimental results on the Alibaba Technology Association (ATA) website show the advantage of SINGLE, which achieves 2.4% improvements over previous baseline models in the online A/B test. Our further analyses illustrate that SINGLE has the ability to build a more tailored recommendation system by mimicking different article viewing behaviors of users and recommending more appropriate and diverse articles to match user interests.Comment: 8 pages

Acetaldehyde released by Lactobacillus plantarum enhances accumulation of pyranoanthocyanins in wine during malolactic fermentation

This study investigated the evolution of acetaldehyde and pyranoanthocyanins in wine during malolactic fermentation, and further evaluated the correlation between acetaldehyde and pyranoanthocyanins. Cabernet Gernischt wine after alcoholic fermentation was inoculated with four lactic acid bacteria strains. Malolactic fermentation kinetics and wine characteristics were compared. Results showed these strains exhibited different kinetics on wine malolactic fermentation. Wine with Lactobacillus plantarum had lower reducing sugar, total acid, and yellowness. Lactobacillus plantarum elevated the level of acetaldehyde in wine model medium and wine during malolactic fermentation. Malolactic fermentation using Lactobacillus plantarum significantly increased the concentration of pyranoanthocyanins, whereas O. oeni strain reduced the level of pyranoanthocyanins in wine. Polymerized anthocyanins percentage in wine was significantly enhanced after fermentation with Lactobacillus plantarum. Principal component analysis indicated that the characteristics of these strains inoculated wines after malolactic fermentation were segregated. The findings from this study could provide useful information on the wine color improvement through malolactic fermentation with suitable lactic acid bacteria strains

Involvement of MicroRNAs in Probiotics-Induced Reduction of the Cecal Inflammation by Salmonella Typhimurium

The microRNAs (miRNAs) have been shown to play important roles in the development of the immune system and in regulation of host inflammation responses. Probiotics can effectively alleviate the inflammation caused by Salmonella in chickens. However, whether and how miRNAs are involved in modulation of the inflammation response in the gut of chickens have not been reported. In this study, the impact of a probiotics, Lactobacillus plantarum Z01 (LPZ01), was investigated on the cecal miRNAs and cytokine secretions in Salmonella Typhimurium (S. Typhimurium)-infected chickens at the age of 3 days. Newly hatched chicks were assigned to four groups (1): NC (basal diet) (2): S (basal diet + S. Typhimurium challenged) (3): SP (basal diet + S. Typhimurium challenged + LPZ01) (4): P (basal diet + LPZ01). In comparison with the S group, chicks in the SP group reduced the number of S. Typhimurium and had lower levels of interferon-γ and lipopolysaccharide-induced tumor necrosis factor alpha factor (LITAF) in ceca post challenge. Expression of 14 miRNAs was significantly affected by the presence of S. Typhimurium and/or lactobacillus. Five differential expression miRNAs (gga-miR-215-5p, gga-miR-3525, gga-miR-193a-5p, gga-miR-122-5p, and gga-miR-375) were randomly selected for confirmation by the RT-PCR. Predicted target genes of differentially expressed miRNAs were enriched in regulation of cAMP-dependent protein kinase activity, stress-activated MAPK cascade, immune system development and regulation of immune system process as well as in immune related pathways such as MAPK and Wnt signaling pathways. The relationship between changes of miRNAs and changes of cytokines was explored. Finally, 119 novel miRNAs were identified in 36 libraries totally. Identification of novel miRNAs significantly expanded the repertoire of chicken miRNAs and provided the basis for understanding the function of miRNAs in the host. Our results suggest that the probiotics reduce the inflammation of the S. Typhimurium infection in neonatal broiler chicks, at least partially, through regulation of miRNAs expression

Highly Efficient Visible Light Catalysts Driven by Ti3+-V-O-2Ti(4+)-N3- Defect Clusters

Local defect structures play significant roles on material properties, but they are seriously neglected in the design, synthesis, and development of highly efficient TiO2‐based visible light catalysts (VLCs). Here, we take anatase TiO2 nanocrystals that contain (Ti3+, N3−) ions and have the complicated chemical formula of (urn:x-wiley:2199692X:media:cnma201800400:cnma201800400-math-0001 )(urn:x-wiley:2199692X:media:cnma201800400:cnma201800400-math-0002 □z) as an example, and point out that the formation of Ti3+‐VO‐2Ti4+‐N3− local defect clusters is a key missing step for significantly enhancing VLC properties of host TiO2 nanocrystals. Experimental and theoretical investigations also demonstrate the emergent behaviors of these intentionally introduced defect clusters for developing highly efficient VLCs. This research thus not only provides highly efficient visible light catalysts for various practical applications but also addresses the significance of local defect structures on modifying material properties.Q. Sun, D. Cortie, T. J. Frankcome, N. Cox and Y. Liu acknowledge the supports of the Australian Research Council in the form of Discovery Projects and the ARC Future Fellowships program. S. Zhang and W. Shi thank the support from CAS (1A1111KYSB20180017, XDB17030000)

Tetramethylpyrazine attenuates spinal cord ischemic injury due to aortic cross-clamping in rabbits

BACKGROUND: Lower limb paralysis occurs in 11% of patients after surgical procedure of thoracic or thoracoabdominal aneurysms and is an unpredictable and distressful complication. The aim of this study was to investigate the effects of tetramethylpyrazine (TMP), an intravenous drug made from traditional Chinese herbs, on the neurologic outcome and hisotpathology after transient spinal cord ischemia in rabbits. METHODS: Forty-five male New Zealand white rabbits were anesthetized with isoflurane and spinal cord ischemia was induced for 20 min by infrarenal aortic occlusion. Animals were randomly allocated to one of five groups (n = 8 each). Group C received no pharmacologic intervention. Group P received intravenous infusion of 30 mg·kg(-1) TMP within 30 min before aortic occlusion. Group T(1), Group T(2) and Group T(3) received intravenous infusion of 15, 30 and 60 mg·kg(-1) TMP respectively within 30 min after reperfusion. In the sham group (n = 5), the animals underwent the same procedures as the control group except infrarental aortic unocclusion. Neurologic status was scored by using the Tarlov criteria (in which 4 is normal and 0 is paraplegia) at 4 h, 8 h, 12 h, 24 h, and 48 h after reperfusion. All animals were sacrificed at 48 h after reperfusion and the spinal cords (L(5)) were removed immediately for histopathologic study. RESULTS: All animals in the control group became paraplegic. Neurologic status and histopathology (48 h) in the Groups P, T(2) and T(3) were significantly better than those in the control group (P < 0.05). There was a strong correlation between the final neurologic scores and the number of normal neurons in the anterior spinal cord (r = 0.776, P < 0.01). CONCLUSION: Tetramethylpyrazine significantly reduces neurologic injury related to spinal cord ischemia and reperfusion after aortic occlusion within a certain range of dose