Multi-Interactive-Modality based Modeling for Myopia Pro-Gression of Adolescent Student

Myopia is a common visual disorder that affects millions of people worldwide and its prevalence has been increasing in recent years. Environmental factors, such as reading time, viewing distance, and ambient lighting, have been identified as potential factors in the development of myopia. In this study, we investigated the relationship between three major factors and myopia in 120 adolescents. By collecting environmental images of the adolescents in the learning state as well as retinal fundus images, we proposed an environmental visual load (EVL) model to extract the potential information in these images. Through experimental data analysis, we found that these three major factors are closely related to the severity of myopia, and that the simultaneous exacerbation of these factors sharply increases the myopia of the eye. Our results suggest that interventions targeting these environmental factors may help prevent and manage myopia.Comment: 9 pages, 5 figure

Analgesic effect and safety of postoperative low-dose ketamine/midazolam combination vis-à-vis dexmedetomidine in non-cardiac surgery

Purpose: To compare the analgesic efficacy and safety of use of postoperative low-dose parenteral ketamine/midazolam combination, and postoperative parenteral dexmedetomidine in major non-cardiac surgeries.Methods: Major non-cardiac surgeries were performed in patients under propofol/morphine anesthesia. After the surgeries, patients received low-dose of ketamine with midazolam (KM cohort, n = 115), dexmedetomidine (DEX cohort, n = 112), or paracetamol infusion (PL cohort, n = 148). When visual analog scale score was > 4 in a resting condition, 3 mg bolus intravenous morphine was administered. Data for total morphine requirements and treatment-emergent adverse effects (within 2 days of postoperative treatment) were collected and analyzed.Results: Thirty-eight patients from KM cohort, 55 patients from DEX cohort, and 109 patients from PL cohort required 3 mg bolus intravenous morphine for postoperative pain management. Patients from KM cohort had nausea, vomiting, blurred vision,  dizziness, and hallucinations, while patients in DEX cohort experienced headache and bradycardia post-surgery. Patients in PL cohort reported drossiness, constipation, urinary retention, and dry mouth.Conclusion: Postoperative low doses of ketamine + midazolam and dexmedetomidine are effective for postoperative pain management, and they produce low adverse effects.&nbsp

Tuning the upconversion photoluminescence lifetimes of NaYF4:Yb3+, Er3+ through lanthanide Gd3+ doping

The multiplexing capacity of conventional fluorescence materials are significantly limited by spectral overlap and background interference, mainly due to their short-lived fluorescence lifetimes. Here, we adopt a novel Gd3+ doping strategy in NaYF4 host materials, realized tuning of upconversion photoluminescence (UCPL) lifetimes at selective emissions. Time-correlated single-photon counting (TCSPC), was applied to measure the photoluminescence lifetimes accurately. We demonstrated the large dynamic range of lifetimes of upconversion nanoparticles with good upconversion quantum yields, mainly owing to the dominance of high efficient energy transfer upconversion mechanism. The exceptional tunable properties of upconversion materials allow great potential for them to be utilized in biotechnology and life sciences

A Spatiotemporal Reallocation Method for Energy Management in Edge Data Centres

Edge data centres (EDCs) have been widely developed in these years to supply delay-sensitive computing services, which impose prohibitive increasing electricity costs for EDC operators. This paper develops a new spatiotemporal reallocation (STR) method for energy management in EDCs. This method uses spare resources, including servers and energy storage systems (ESSs) within EDCs to reduce energy costs based on both spatial and temporal features of spare resources. This solution: 1) reallocates flexible workload between EDCs within one cluster; and 2) coordinates electricity load of data processing, ESSs and distributed energy resources (DERs) within one EDC cluster to gain benefits from flexible electricity tariffs. In addition, this paper the first time develops a Bit-Watt transformation to simplify the STR method and represent the relation between data workload and electricity consumption of EDCs. The case studies justified the developed STR method delivers satisfied costs reduction with robustness. The STR method fully utilized both spatial and temporal features of spare resources in EDCs to gain benefits from 1) the varying electricity tariffs, and 2) maximumly consuming the DER generation

A Spatiotemporal Reallocation Method for Energy Management in Edge Data Centres

Edge data centres (EDCs) have been widely developed in these years to supply delay-sensitive computing services, which impose prohibitive increasing electricity costs for EDC operators. This paper develops a new spatiotemporal reallocation (STR) method for energy management in EDCs. This method uses spare resources, including servers and energy storage systems (ESSs) within EDCs to reduce energy costs based on both spatial and temporal features of spare resources. This solution: 1) reallocates flexible workload between EDCs within one cluster; and 2) coordinates electricity load of data processing, ESSs and distributed energy resources (DERs) within one EDC cluster to gain benefits from flexible electricity tariffs. In addition, this paper the first time develops a Bit-Watt transformation to simplify the STR method and represent the relation between data workload and electricity consumption of EDCs. The case studies justified the developed STR method delivers satisfied costs reduction with robustness. The STR method fully utilized both spatial and temporal features of spare resources in EDCs to gain benefits from 1) the varying electricity tariffs, and 2) maximumly consuming the DER generation

Backdooring Neural Code Search

Reusing off-the-shelf code snippets from online repositories is a common practice, which significantly enhances the productivity of software developers. To find desired code snippets, developers resort to code search engines through natural language queries. Neural code search models are hence behind many such engines. These models are based on deep learning and gain substantial attention due to their impressive performance. However, the security aspect of these models is rarely studied. Particularly, an adversary can inject a backdoor in neural code search models, which return buggy or even vulnerable code with security/privacy issues. This may impact the downstream software (e.g., stock trading systems and autonomous driving) and cause financial loss and/or life-threatening incidents. In this paper, we demonstrate such attacks are feasible and can be quite stealthy. By simply modifying one variable/function name, the attacker can make buggy/vulnerable code rank in the top 11%. Our attack BADCODE features a special trigger generation and injection procedure, making the attack more effective and stealthy. The evaluation is conducted on two neural code search models and the results show our attack outperforms baselines by 60%. Our user study demonstrates that our attack is more stealthy than the baseline by two times based on the F1 score

Transcriptome analysis reveals the molecular mechanisms of rubber biosynthesis and laticifer differentiation during rubber seed germination

The molecular mechanisms underlying the initiation of natural rubber synthesis and laticifer differentiation have not been fully elucidated. In this study, we conducted a time-series transcriptome analysis of five rubber tree tissues at four stages of seed germination. A total of 161,199 DEGs were identified between the two groups, including most 16,673 DEGs (A3 vs B3 and A3 vs C3) and lest 1,210 DEGs (C2 vs D2). We found that the maturation of the seed is accompanied by the formation of laticifer cells in cotyledon. Meanwhile, the analysis of hormones related genes expression may provide effective clues for us to promote the differentiation of laticifer cells in seeds by hormones in the future. In this study, hormone-related gene enrichment analyses revealed that IAA, GA, and CTK were activated in laticifer containing tissues. Similarly, GO and GEGG analysis showed that hormone pathways, especially the auxin pathway, are enriched. Gene expression clustering was analyzed using the short time-series expression miner (STEM), and the analysis revealed four distinct trends in the gene expression profiles. Moreover, we enriched transcription factor (TF) enrichment in cotyledon and embryonic axis tissues, and the MYB type exhibited the most significant difference. Furthermore, our findings revealed that genes related to rubber synthesis exhibited tissue-specific expression patterns during seed germination. Notably, key genes associated with rubber biosynthesis, specifically small rubber particle protein (SRPP) and cis-prenyltransferase (CPT), exhibited significant changes in expression in cotyledon and embryonic axis tissues, suggesting synchronous rubber synthesis with seed germination. Our staining results reveled that laticifer cells were exits in the cotyledon before seed imbibition stage. In conclusion, these results lay the foundation for exploring the molecular mechanisms underlying laticifer differentiation and rubber synthesis during seed germination, deepening our understanding of the initiation stages of rubber biosynthesis and laticifer differentiation

ImmFusion: Robust mmWave-RGB Fusion for 3D Human Body Reconstruction in All Weather Conditions

3D human reconstruction from RGB images achieves decent results in good weather conditions but degrades dramatically in rough weather. Complementary, mmWave radars have been employed to reconstruct 3D human joints and meshes in rough weather. However, combining RGB and mmWave signals for robust all-weather 3D human reconstruction is still an open challenge, given the sparse nature of mmWave and the vulnerability of RGB images. In this paper, we present ImmFusion, the first mmWave-RGB fusion solution to reconstruct 3D human bodies in all weather conditions robustly. Specifically, our ImmFusion consists of image and point backbones for token feature extraction and a Transformer module for token fusion. The image and point backbones refine global and local features from original data, and the Fusion Transformer Module aims for effective information fusion of two modalities by dynamically selecting informative tokens. Extensive experiments on a large-scale dataset, mmBody, captured in various environments demonstrate that ImmFusion can efficiently utilize the information of two modalities to achieve a robust 3D human body reconstruction in all weather conditions. In addition, our method's accuracy is significantly superior to that of state-of-the-art Transformer-based LiDAR-camera fusion methods

PyPose v0.6: The Imperative Programming Interface for Robotics

PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has been used in many tasks due to its meticulously designed application programming interface (API) and efficient implementation. From its initial launch in early 2022, PyPose has experienced significant enhancements, incorporating a wide variety of new features into its platform. To satisfy the growing demand for understanding and utilizing the library and reduce the learning curve of new users, we present the fundamental design principle of the imperative programming interface, and showcase the flexible usage of diverse functionalities and modules using an extremely simple Dubins car example. We also demonstrate that the PyPose can be easily used to navigate a real quadruped robot with a few lines of code