iPUNet:Iterative Cross Field Guided Point Cloud Upsampling

Point clouds acquired by 3D scanning devices are often sparse, noisy, and non-uniform, causing a loss of geometric features. To facilitate the usability of point clouds in downstream applications, given such input, we present a learning-based point upsampling method, i.e., iPUNet, which generates dense and uniform points at arbitrary ratios and better captures sharp features. To generate feature-aware points, we introduce cross fields that are aligned to sharp geometric features by self-supervision to guide point generation. Given cross field defined frames, we enable arbitrary ratio upsampling by learning at each input point a local parameterized surface. The learned surface consumes the neighboring points and 2D tangent plane coordinates as input, and maps onto a continuous surface in 3D where arbitrary ratios of output points can be sampled. To solve the non-uniformity of input points, on top of the cross field guided upsampling, we further introduce an iterative strategy that refines the point distribution by moving sparse points onto the desired continuous 3D surface in each iteration. Within only a few iterations, the sparse points are evenly distributed and their corresponding dense samples are more uniform and better capture geometric features. Through extensive evaluations on diverse scans of objects and scenes, we demonstrate that iPUNet is robust to handle noisy and non-uniformly distributed inputs, and outperforms state-of-the-art point cloud upsampling methods

Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area

China’s anthropogenic methane emissions are the largest of any country in the world. A recent study using atmospheric observations suggested that recent policies aimed at reducing emissions of methane due to coal production in China after 2010 had been largely ineffective. Here, based on a longer observational record and an updated modelling approach, we find a statistically significant positive linear trend (0.36 ± 0.04 ( $\pm1\sigma$ ) Tg CH _4 yr ^−2 ) in China’s methane emissions for 2010–2017. This trend was slowing down at a statistically significant rate of -0.1 ± 0.04 Tg CH _4 yr ^−3 . We find that this decrease in growth rate can in part be attributed to a decline in China’s coal production. However, coal mine methane emissions have not declined as rapidly as production, implying that there may be substantial fugitive emissions from abandoned coal mines that have previously been overlooked. We also find that emissions over rice-growing and aquaculture-farming regions show a positive trend (0.13 ± 0.05 Tg CH _4 yr ^−2 for 2010–2017) despite reports of shrinking rice paddy areas, implying potentially significant emissions from new aquaculture activities, which are thought to be primarily located on converted rice paddies

3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge

Teeth localization, segmentation, and labeling from intra-oral 3D scans are essential tasks in modern dentistry to enhance dental diagnostics, treatment planning, and population-based studies on oral health. However, developing automated algorithms for teeth analysis presents significant challenges due to variations in dental anatomy, imaging protocols, and limited availability of publicly accessible data. To address these challenges, the 3DTeethSeg'22 challenge was organized in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2022, with a call for algorithms tackling teeth localization, segmentation, and labeling from intraoral 3D scans. A dataset comprising a total of 1800 scans from 900 patients was prepared, and each tooth was individually annotated by a human-machine hybrid algorithm. A total of 6 algorithms were evaluated on this dataset. In this study, we present the evaluation results of the 3DTeethSeg'22 challenge. The 3DTeethSeg'22 challenge code can be accessed at: https://github.com/abenhamadou/3DTeethSeg22_challengeComment: 29 pages, MICCAI 2022 Singapore, Satellite Event, Challeng

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Validation of Five Gas Analysers for Application in Ammonia Emission Measurements at Livestock Houses According to the VERA Test Protocol

Ammonia emissions are an important issue in livestock production. Many mitigation measures have been proposed in order to reduce the environmental impact of livestock farms, and reliable field measurements are required to evaluate the amount of released or reduced ammonia while applying these measures. Following the guideline of the Verification of Environmental Technologies for Agricultural Production test protocol, five commercially available gas analysers, i.e., INNOVA 1314, Picarro G2103, Rosemount CT5100, Gasmet CX4000, and Axetris LGD F200-A, were validated as alternative methods to the wet-chemistry method (reference method) for measuring ammonia in livestock houses. High correlations ( r > 0.99 ) were found between the analysers and the reference method. The measurement errors of the tested analysers were below 2 ppmv or 10%. Equivalence to the wet-chemistry method was demonstrated for the INNOVA and Rosemount analysers without a recalibration and for the Picarro and Axetris analysers with a recalibration. The Gasmet analyser was seemingly subjected to an interference from carbon-dioxide and, after compensating for the cross-sensitivity, the equivalence to the wet-chemistry method could also be demonstrated. Calibration curves that were based on a certified gas cylinder were inconsistent with that based on wet-chemistry measurements, which suggested that field calibration might be necessary for optimal measurement accuracy

Validation of five gas analysers for application in ammonia emission measurements at livestock houses according to the VERA test protocol

Ammonia emissions are an important issue in livestock production. Many mitigation measures have been proposed in order to reduce the environmental impact of livestock farms, and reliable field measurements are required to evaluate the amount of released or reduced ammonia while applying these measures. Following the guideline of the Verification of Environmental Technologies for Agricultural Production test protocol, five commercially available gas analysers, i.e., INNOVA 1314, Picarro G2103, Rosemount CT5100, Gasmet CX4000, and Axetris LGD F200-A, were validated as alternative methods to the wet-chemistry method (reference method) for measuring ammonia in livestock houses. High correlations (r>0.99) were found between the analysers and the reference method. The measurement errors of the tested analysers were below 2 ppm(v)or 10%. Equivalence to the wet-chemistry method was demonstrated for the INNOVA and Rosemount analysers without a recalibration and for the Picarro and Axetris analysers with a recalibration. The Gasmet analyser was seemingly subjected to an interference from carbon-dioxide and, after compensating for the cross-sensitivity, the equivalence to the wet-chemistry method could also be demonstrated. Calibration curves that were based on a certified gas cylinder were inconsistent with that based on wet-chemistry measurements, which suggested that field calibration might be necessary for optimal measurement accuracy

Rational size and stability analysis of horizontal isolated pillars in deep mining from caving to filling method

For mining using the caving and filling methods in metal mines, determining a suitable size for the isolated pillars—the connecting part of the extension from shallow to deep—is crucial for ensuring safety and efficiency. Considering actual cases involving deep caving and cut-and-fill mining in the Chifeng Hongling lead-zinc mine in Inner Mongolia, China, the reserved thickness range of the horizontal isolation layer is obtained via theoretical analysis. On this basis, the pre-processing software HyperMesh is used to build a high-precision hexahedral grid model of the mining area, and the three-dimensional geological model of the mining area is imported into the finite-difference software FLAC3D. The stress field, displacement field, and plastic area evolution law of pillars (horizontally isolated pillars and adjacent rib pillars) in the stope of the ninth middle section after excavation are analyzed via numerical simulation inversion of the selected scheme of horizontal isolated pillars. The numerical simulation results show that the scheme employed to retain the upper horizontal isolated pillars in the ninth middle section involves reserving thicknesses of 8 m and 32 m at average ore body thicknesses of 15 m and 35 m, respectively. These results can provide theoretical guidance and a basis for safe and efficient mining of deep metal mines

Evaluation of a cost-effective ammonia monitoring system for continuous real-time concentration measurements in a fattening pig barn

Ammonia (NH3) emission is one of the major environmental issues in livestock farming. Gas measurements are required to study the emission process, to establish emission factors, and to assess the efficiency of emission reduction techniques. However, the current methods for acquiring reference measurements of NH3 are either high in cost or labor intensive. In this study, a cost-effective ammonia monitoring system (AMS) was constructed from a commercially-available gas analyzing module based on tunable diode laser absorption (TDLA) spectroscopy. To cope with the negative measurement biases caused by differing inlet pressures, a set of correction equations was formulated. Field validation of the AMS on NH3 measurement was conducted in a fattening pig barn, where the system was compared to a Fourier-transform infrared (FTIR) spectroscopy analyzer. Under two test conditions in a fattening pig barn, the absolute error of the AMS measurements with respect to the average obtained values between the AMS and the FTIR was respectively 0.66 and 0.08 ppm(v), corresponding to 5.9% and 0.5% relative error. Potential sources of the measurement uncertainties in both the AMS and FTIR were discussed. The test results demonstrated that the AMS was capable of performing high-quality measurement with sub-ppm accuracy, making it a promising cost-effective tool for establishing NH3 emission factors and studying NH3 emission processes in pig houses