The uncertainty analysis of the MODIS GPP product in global maize croplands

Gross primary productivity (GPP) is very important in the global carbon cycle. Currently, the newly released estimates of 8-day GPP at 500 m spatial resolution (Collection 6) are provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Science Team for the global land surface via the improved light use efficiency (LUE) model. However, few studies have evaluated its performance. In this study, the MODIS GPP products (GPPMOD) were compared with the observed GPP (GPPEC) values from site-level eddy covariance measurements over seven maize flux sites in different areas around the world. The results indicate that the annual GPPMOD was underestimated by 6%‒58% across sites. Nevertheless, after incorporating the parameters of the calibrated LUE, the measurements of meteorological variables and the reconstructed Fractional Photosynthetic Active Radiation (FPAR) into the GPPMOD algorithm in steps, the accuracies of GPPMOD estimates were improved greatly, albeit to varying degrees. The differences between the GPPMOD and the GPPEC were primarily due to the magnitude of LUE and FPAR. The underestimate of maize cropland LUE was a widespread problem which exerted the largest impact on the GPPMOD algorithm. In American and European sites, the performance of the FPAR exhibited distinct differences in capturing vegetation GPP during the growing season due to the canopy heterogeneity. In addition, at the DE-Kli site, the GPPMOD abruptly produced extreme low values during the growing season because of the contaminated FPAR from a continuous rainy season. After correcting the noise of the FPAR, the accuracy of the GPPMOD was improved by approximately 14%. Therefore, it is crucial to further improve the accuracy of global GPPMOD, especially for the maize crop ecosystem, to maintain food security and better understand global carbon cycle

A review of research on acoustic detection of heat exchanger tube

Leakage in heat exchanger tubes can result in unreliable products and dangerous situations, which could cause great economic losses. Along with fast development of modern acoustic detection technology, using acoustic signals to detect leakage in heat exchange tube has been gradually accepted and considered with great potential by both industrial and research societies. In order to further advance the development of acoustic signal detection technology and investigate better methods for leakage detection in heat exchange tube, in this paper, firstly, we conduct a short overview of the theory of acoustic signal detection on heat exchanger tube, which had already been continuously developed for a few decades by researchers worldwide. Thereafter, we further expound the advantages and limitations of acoustic signal detection technology on heat exchanger tube in four aspects: 1) principles of acoustic signal detection, 2) characteristics of sound wave propagation in heat exchanger tube, 3) methods of leakage detection, and 4) leakage localization in heat exchanger tube

Optimization of Energy Saving and Consumption Reduction of Polysilicon Siemens Method Based on Improved K-means Algorithm

The core technology of polysilicon production by improved Siemens method is still controlled and monopolized by developed countries. Firstly, it is proposed to improve the algorithm instability caused by the random determination of clustering center of K-means algorithm. The initial clustering center is determined by the method of distance to improve the performance of the algorithm, and it is applied to the energy saving and consumption reduction of polysilicon Siemens method. It can be graded from the quality point of view to ensure the quality of supply. Secondly, the convective heat transfer model in Siemens reactor was established, and the total energy consumption of laboratory-scale Siemens reactor predicted by K-means model was compared with the experimental data in the public literature. The relative errors were all within 1%, indicating that the convective heat transfer model established was effective. At the same time, by adding dichlorodihydrosilane to the feed of the traditional process, it is obtained that at 100 kPa, when the molar ratio of dichlorodisilane, trichlorosilane and hydrogen is 1:1:5, the polysilicon yield is increased by 9.6%, the silicon tetrachlorosilane yield is reduced by 8.7%, and the energy consumption is reduced by 35% compared with the traditional process. Finally, combined with the production practice and other factors unchanged, the ratio of mixture flow rate to silicon rod power is taken as the research object, and the furnace times with different feed and power ratio are compared, and the operation results are analyzed and summarized

Establishment of reference intervals of thyroid-related hormones for adults with normal liver function in Zhejiang Province by indirect method

ObjectiveThyroid disorders are prevalently diagnosed yet face significant challenges in their accurate identification in China. Predominantly, the reference intervals (RIs) currently in use across Chinese medical facilities derive from company-provided data, lacking stringent scientific validation. This practice underscores the urgent necessity for establishing tailored RIs for thyroid-related hormones, specifically tailored to the coastal area populations. Such refined RIs are imperative for empowering clinicians with the precise tools needed for the accurate diagnosis of both overt and subclinical thyroid conditions.MethodsThis investigation analyzed the medical histories of 6021 euthyroid individuals mainly from East coastal area of China between June 2019 and December 2020. The cohort comprised residents of coastal areas, focusing on extracting insights into the regional specificity of thyroid hormone levels. A thorough examination protocol was implemented, encompassing inquiries into thyroid health history, ultrasound screenings, palpations during thyroid surgery, detections of thyroid antibodies, and reviews of medication histories. Adherence to the CLSI C28-A3 guidelines facilitated the derivation of RIs for thyroid-related hormones, subsequently juxtaposed against those provided by commercial entities.ResultsThe study delineated the following gender- and age-specific RIs for Thyroid-Stimulating Hormone (TSH): for males under 50 years, 0.57-3.37; males over 50 years, 0.51-4.03; females under 50 years, 0.53-3.91; and females over 50 years, 0.63-4.31. Further analysis revealed the RIs for Free Thyroxine (FT4), Free Triiodothyronine (FT3), Total Thyroxine (TT4), and Total Triiodothyronine (TT3) amongst males and females, with notable distinctions observed between the two genders and across age brackets. These findings are in stark contrast to the standardized intervals provided by manufacturers, particularly highlighting differences in TT3 and FT3 levels between genders and a tendency for TSH levels to increase with age.ConclusionThis research successfully establishes refined RIs for thyroid-related hormones within the Chinese coastal area populations, taking into account critical demographic factors such as gender and age. These tailored RIs are anticipated to significantly enhance the diagnostic accuracy for thyroid diseases, addressing the previously noted discrepancies with manufacturer-provided data and underscoring the importance of regionally and demographically adjusted reference intervals in clinical practice

PeP: a Point enhanced Painting method for unified point cloud tasks

Point encoder is of vital importance for point cloud recognition. As the very beginning step of whole model pipeline, adding features from diverse sources and providing stronger feature encoding mechanism would provide better input for downstream modules. In our work, we proposed a novel PeP module to tackle above issue. PeP contains two main parts, a refined point painting method and a LM-based point encoder. Experiments results on the nuScenes and KITTI datasets validate the superior performance of our PeP. The advantages leads to strong performance on both semantic segmentation and object detection, in both lidar and multi-modal settings. Notably, our PeP module is model agnostic and plug-and-play. Our code will be publicly available soon

Randomized vs. Deterministic? Practical Randomized Synchronous BFT in Expected Constant Time

Most practical synchronous Byzantine fault-tolerant (BFT) protocols, such as Sync HotStuff (S&P 2020), follow the convention of partially synchronous BFT and adopt a deterministic design. Indeed, while these protocols achieve O(n) time complexity, they exhibit impressive performance in failure-free scenarios. This paper challenges this conventional wisdom, showing that a randomized paradigm terminating in expected O(1) time may well outperform prior ones even in the failure-free scenarios. Our framework reduces synchronous BFT to a new primitive called multi-valued Byzantine agreement with strong external validity (MBA-SEV). Inspired by the external validity property of multi-valued validated Byzantine agreement (MVBA), the additional validity properties allow us to build a BFT protocol where replicas agree on the hashes of the blocks. Our instantiation of the paradigm, Sonic, achieves O(n) amortized message complexity per block proposal, expected O(1) time, and enables a fast path of only two communication step. Our evaluation results using up to 91 instances on Amazon EC2 show that the peak throughput of Sonic and P-Sonic (a pipelining variant of Sonic) is 2.24x-14.52x and 3.08x-24.25x that of Sync HotStuff, respectively

A novel distance learning for elastic cross-modal audio-visual matching

In this work we propose a novel network formulation for joint representation of cross-modal audio and visual information base on metric learning. We employ a distance learning framework as a training procedure. For this purpose we introduce an elastic matching network (EmNet) and a novel loss function to learn the shared latent space representation of multi-modal information. The elastic matching network is capable of matching given face image (or audio voice clip) from diverse number of audio clips (or face images). We quantitatively and qualitatively evaluate the purposed approach on the standard audio-visual matching evaluation dataset, the overlap of VoxCeleb and VGGFace by both multi-way and binary audio-visual matching tasks. The promising performance comparing to the existing methods verifies the effectiveness of the proposed approach, which yields to a new state-of-the-art for cross-modal audio-visual matching