PointOBB: Learning Oriented Object Detection via Single Point Supervision

Single point-supervised object detection is gaining attention due to its cost-effectiveness. However, existing approaches focus on generating horizontal bounding boxes (HBBs) while ignoring oriented bounding boxes (OBBs) commonly used for objects in aerial images. This paper proposes PointOBB, the first single Point-based OBB generation method, for oriented object detection. PointOBB operates through the collaborative utilization of three distinctive views: an original view, a resized view, and a rotated/flipped (rot/flp) view. Upon the original view, we leverage the resized and rot/flp views to build a scale augmentation module and an angle acquisition module, respectively. In the former module, a Scale-Sensitive Consistency (SSC) loss is designed to enhance the deep network's ability to perceive the object scale. For accurate object angle predictions, the latter module incorporates self-supervised learning to predict angles, which is associated with a scale-guided Dense-to-Sparse (DS) matching strategy for aggregating dense angles corresponding to sparse objects. The resized and rot/flp views are switched using a progressive multi-view switching strategy during training to achieve coupled optimization of scale and angle. Experimental results on the DIOR-R and DOTA-v1.0 datasets demonstrate that PointOBB achieves promising performance, and significantly outperforms potential point-supervised baselines.Comment: 11 pages,5 figures, 6 tables. Code: https://github.com/Luo-Z13/pointob

H2RBox-v2: Boosting HBox-supervised Oriented Object Detection via Symmetric Learning

With the increasing demand for oriented object detection e.g. in autonomous driving and remote sensing, the oriented annotation has become a labor-intensive work. To make full use of existing horizontally annotated datasets and reduce the annotation cost, a weakly-supervised detector H2RBox for learning the rotated box (RBox) from the horizontal box (HBox) has been proposed and received great attention. This paper presents a new version, H2RBox-v2, to further bridge the gap between HBox-supervised and RBox-supervised oriented object detection. While exploiting axisymmetry via flipping and rotating consistencies is available through our theoretical analysis, H2RBox-v2, using a weakly-supervised branch similar to H2RBox, is embedded with a novel self-supervised branch that learns orientations from the symmetry inherent in the image of objects. Complemented by modules to cope with peripheral issues, e.g. angular periodicity, a stable and effective solution is achieved. To our knowledge, H2RBox-v2 is the first symmetry-supervised paradigm for oriented object detection. Compared to H2RBox, our method is less susceptible to low annotation quality and insufficient training data, which in such cases is expected to give a competitive performance much closer to fully-supervised oriented object detectors. Specifically, the performance comparison between H2RBox-v2 and Rotated FCOS on DOTA-v1.0/1.5/2.0 is 72.31%/64.76%/50.33% vs. 72.44%/64.53%/51.77%, 89.66% vs. 88.99% on HRSC, and 42.27% vs. 41.25% on FAIR1M.Comment: 13 pages, 4 figures, 7 tables, the source code is available at https://github.com/open-mmlab/mmrotat

Warming-induced permafrost thaw exacerbates tundra soil carbon decomposition mediated by microbial community.

BACKGROUND:It is well-known that global warming has effects on high-latitude tundra underlain with permafrost. This leads to a severe concern that decomposition of soil organic carbon (SOC) previously stored in this region, which accounts for about 50% of the world's SOC storage, will cause positive feedback that accelerates climate warming. We have previously shown that short-term warming (1.5 years) stimulates rapid, microbe-mediated decomposition of tundra soil carbon without affecting the composition of the soil microbial community (based on the depth of 42684 sequence reads of 16S rRNA gene amplicons per 3 g of soil sample). RESULTS:We show that longer-term (5 years) experimental winter warming at the same site altered microbial communities (p < 0.040). Thaw depth correlated the strongest with community assembly and interaction networks, implying that warming-accelerated tundra thaw fundamentally restructured the microbial communities. Both carbon decomposition and methanogenesis genes increased in relative abundance under warming, and their functional structures strongly correlated (R2 > 0.725, p < 0.001) with ecosystem respiration or CH4 flux. CONCLUSIONS:Our results demonstrate that microbial responses associated with carbon cycling could lead to positive feedbacks that accelerate SOC decomposition in tundra regions, which is alarming because SOC loss is unlikely to subside owing to changes in microbial community composition. Video Abstract

Effects of frozen soil on soil temperature, spring infiltration, and runoff: results from the PILPS 2(d) experiment at Valdai, Russia

Permission to place copies of these works on this server has been provided by the American Meteorological Society (AMS). The AMS does not guarantee that the copies provided here are accurate copies of the published work. © Copyright 2003 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/AMS) or from the AMS at 617-227-2425 or [email protected] Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated. It was found that when soil-water freezing is explicitly included in a model, it improves the simulation of soil temperature and its variability at seasonal and interannual scales. Although change of thermal conductivity of the soil also affects soil temperature simulation, this effect is rather weak. The impact of frozen soil on soil moisture is inconclusive in this experiment due to the particular climate at Valdai, where the top 1 m of soil is very close to saturation during winter and the range for soil moisture changes at the time of snowmelt is very limited. The results also imply that inclusion of explicit snow processes in the models would contribute to substantially improved simulations. More sophisticated snow models based on snow physics tend to produce better snow simulations, especially of snow ablation. Hysteresis of snow-cover fraction as a function of snow depth is observed at the catchment but not in any of the models

Effects of Frozen Soil on Soil Temperature, Spring Infiltration, and Runoff: Results from the PILPS 2(d) Experiment at Valdai, Russia

The Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated. It was found that when soil-water freezing is explicitly included in a model, it improves the simulation of soil temperature and its variability at seasonal and interannual scales. Although change of thermal conductivity of the soil also affects soil temperature simulation, this effect is rather weak. The impact of frozen soil on soil moisture is inconclusive in this experiment due to the particular climate at Valdai, where the top 1 m of soil is very close to saturation during winter and the range for soil moisture changes at the time of snowmelt is very limited. The results also imply that inclusion of explicit snow processes in the models would contribute to substantially improved simulations. More sophisticated snow models based on snow physics tend to produce better snow simulations, especially of snow ablation. Hysteresis of snow-cover fraction as a function of snow depth is observed at the catchment but not in any of the models

The representation of snow in land surface schemes: results from PILPS 2(d)

Permission to place copies of these works on this server has been provided by the American Meteorological Society (AMS). The AMS does not guarantee that the copies provided here are accurate copies of the published work. © Copyright 2001 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/AMS) or from the AMS at 617-227-2425 or [email protected] land surface schemes (LSSs) performed simulations forced by 18 yr of observed meteorological data from a grassland catchment at Valdai, Russia, as part of the Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS) Phase 2(d). In this paper the authors examine the simulation of snow. In comparison with observations, the models are able to capture the broad features of the snow regime on both an intra- and interannual basis. However, weaknesses in the simulations exist, and early season ablation events are a significant source of model scatter. Over the 18-yr simulation, systematic differences between the models’ snow simulations are evident and reveal specific aspects of snow model parameterization and design as being responsible. Vapor exchange at the snow surface varies widely among the models, ranging from a large net loss to a small net source for the snow season. Snow albedo, fractional snow cover, and their interplay have a large effect on energy available for ablation, with differences among models most evident at low snow depths. The incorporation of the snowpack within an LSS structure affects the method by which snow accesses, as well as utilizes, available energy for ablation. The sensitivity of some models to longwave radiation, the dominant winter radiative flux, is partly due to a stability-induced feedback and the differing abilities of models to exchange turbulent energy with the atmosphere. Results presented in this paper suggest where weaknesses in macroscale snow modeling lie and where both theoretical and observational work should be focused to address these weaknesses

Association between dietary folate intake and bone mineral density in a diverse population: a cross-sectional study

Abstract Background Osteoporosis is a major public health problem, yet the association between dietary folate intake and bone health has been rarely studied. This study aimed to investigate the relationship between dietary folate intake and bone mineral density (BMD) in the general population of the USA. Methods Utilizing data from the National Health and Nutrition Examination Survey, dietary folate intake was gauged through 24-h dietary recall and BMD was determined via dual-energy X-ray absorptiometry. Multivariate linear regression models and generalized additive models were employed for correlation analysis. Results The study incorporated 9839 participants (48.88% males, aged 20–85 years, mean age: 47.62 ± 16.22). The average dietary folate intake stood at 401.1 ± 207.9 μg/day. And the average total femur, femoral neck, trochanter, intertrochanter, and lumbar BMD were 0.98 ± 0.16 g/cm2, 0.84 ± 0.15 g/cm2, 0.73 ± 0.13 g/cm2, 1.16 ± 0.19 g/cm2, and 1.03 ± 0.15 g/cm2, respectively. The higher quartiles of dietary folate intake directly correlated with increased total femoral, femoral neck, intertrochanteric, and lumbar BMD (P for trend = 0.003, 0.016, < 0.001, and 0.033, respectively). A consistent positive association between folate intake and BMD across age groups was observed, with significant findings for individuals over 80 years and non-Hispanic whites. Physical activity level and serum 25-hydroxyvitamin D levels influenced the association, with an optimal daily folate intake of 528–569 µg recommended for postmenopausal women. Conclusion In summary, our study reveals a significant positive association between dietary folate intake and BMD, across different age groups and particularly among individuals over 80 years old. Non-Hispanic whites benefit the most from increased folate intake. Physical activity level and serum 25-hydroxyvitamin D levels interact with this association. Screening and early intervention for osteoporosis may be essential for individuals with low dietary folate intake

Provenance-based Indexing Support in Micro-blog Platforms

Recently, lots of micro-blog message sharing applications have emerged on the web. Users can publish short messages freely and get notified by the subscriptions instantly. Prominent examples include Twitter, Facebook&apos;s statuses, and Sina Weibo in China. The Micro-blog platform becomes a useful service for real time information creation and propagation. However, these messages&apos; short length and dynamic characters have posed great challenges for effective content understanding. Additionally, the noise and fragments make it difficult to discover the temporal propagation trail to explore development of micro-blog messages. In this paper, we propose a provenance model to capture connections between micro-blog messages. Provenance refers to data origin identification and transformation logging, demonstrating of great value in recent database and workflow systems. To cope with the real time micro-message deluge, we utilize a novel message grouping approach to encode and maintain the provenance information. Furthermore, we adopt a summary index and several adaptive pruning strategies to implement efficient provenance updating. Based on the index, our provenance solution can support rich query retrieval and intuitive message tracking for effective message organization. Experiments conducted on a real dataset verify the effectiveness and efficiency of our approach.Computer Science, Theory &amp; MethodsEngineering, Electrical &amp; ElectronicCPCI-S(ISTP)

The complete chloroplast genome sequence of Dendrobium densiflorum and its phylogenetic implications

Dendrobium is one of the largest genera in Orchidaceae with approximately 1500 species. Many of them have been used as Traditional Chinese Medicine (TCM) for hundreds of years. Here, the first complete chloroplast genome sequence of D. densiflorum was reported and characterized. The complete cpDNA of D. densiflorum is a circular molecule of 153,122 bp, which contains 76 protein-coding genes, 30 tRNA genes, and four rRNA genes. Our phylogenetic analysis indicated that the newly sequenced cpDNA of D. densiflorum could be used for the phylogenetic study of Dendrobium species