Digesting omni-video along routes for navigation

poster abstractOmni-directional video records complete visual information along a route. Though replaying an omni-video presents reality, it requires significant amount of memory and communication bandwidth. This work extracts distinct views from an omni-video to form a visual digest named route sheet for navigation. We sort scenes at the motion and visibility level and investigate the similarity/redundancy of scenes in the context of a route. We use source data from 3D elevation map or omni-videos for the view selection. By condensing the flow in the video, our algorithm can generate distinct omni-view sequences with visual information as rich as the omni-video for further scene indexing and navigation with GIS data

Arthroscopic reconstruction of shoulder's labrum with extensive tears

AbstractBackgroundWith the continuous development of arthroscopic techniques, the majority of superior labrum anterior-posterior (SLAP) lesions can be treated with minimally invasive endoscopic repair. The aim of this study was to determine the efficacy of arthroscopic capsulolabral reconstruction of SLAP lesions with extensive tears.MethodsEighteen patients with SLAP lesions with extensive tears (median age, 27.50 years) were included in this study. Twelve patients had type-V SLAP lesions, 4 patients had type-VIII SLAP lesions, and 2 patients had deeply located SLAP lesions. The average duration of follow-up was 15.83 months (range, 11–22 months). Outcome measures included shoulder range of motion (ROM), American Shoulder and Elbow Surgeons (ASES) and Constant-Murley scores, and visual analogue scale (VAS) pain score.ResultsAfter arthroscopic surgery, shoulder forward flexion, shoulder external rotation, and external rotation in 90° of abduction were significantly greater than before surgery (169.5° vs. 165.5°, P = 0.001), (90° vs. 63.5°, P < 0.001), and (90° vs. 81.5°, P = 0.004), respectively. Median ASES and Constant-Murley scores after surgery were both 94 as compared to 77.0 and 77.5, respectively, before surgery (both, P < 0.001). The median VAS score decreased to 1.5 after surgery as compared to 6 before surgery (P < 0.001).ConclusionsArthroscopic repair of SLAP lesions with extensive tears can achieve good outcomes

Antenna Response Consistency Driven Self-supervised Learning for WIFI-based Human Activity Recognition

Self-supervised learning (SSL) for WiFi-based human activity recognition (HAR) holds great promise due to its ability to address the challenge of insufficient labeled data. However, directly transplanting SSL algorithms, especially contrastive learning, originally designed for other domains to CSI data, often fails to achieve the expected performance. We attribute this issue to the inappropriate alignment criteria, which disrupt the semantic distance consistency between the feature space and the input space. To address this challenge, we introduce \textbf{A}ntenna \textbf{R}esponse \textbf{C}onsistency (ARC) as a solution to define proper alignment criteria. ARC is designed to retain semantic information from the input space while introducing robustness to real-world noise. Moreover, we substantiate the effectiveness of ARC through a comprehensive set of experiments, demonstrating its capability to enhance the performance of self-supervised learning for WiFi-based HAR by achieving an increase of over 5\% in accuracy in most cases and achieving a best accuracy of 94.97\%

Antenna Response Consistency Driven Self-supervised Learning for WIFI-based Human Activity Recognition

Self-supervised learning (SSL) for WiFi-based human activity recognition (HAR) holds great promise due to its ability to address the challenge of insufficient labeled data. However, directly transplanting SSL algorithms, especially contrastive learning, originally designed for other domains to CSI data, often fails to achieve the expected performance. We attribute this issue to the inappropriate alignment criteria, which disrupt the semantic distance consistency between the feature space and the input space. To address this challenge, we introduce \textbf{A}ntenna \textbf{R}esponse \textbf{C}onsistency (ARC) as a solution to define proper alignment criteria. ARC is designed to retain semantic information from the input space while introducing robustness to real-world noise. Moreover, we substantiate the effectiveness of ARC through a comprehensive set of experiments, demonstrating its capability to enhance the performance of self-supervised learning for WiFi-based HAR by achieving an increase of over 5\% in accuracy in most cases and achieving a best accuracy of 94.97\%

Road Planning for Slums via Deep Reinforcement Learning

Millions of slum dwellers suffer from poor accessibility to urban services due to inadequate road infrastructure within slums, and road planning for slums is critical to the sustainable development of cities. Existing re-blocking or heuristic methods are either time-consuming which cannot generalize to different slums, or yield sub-optimal road plans in terms of accessibility and construction costs. In this paper, we present a deep reinforcement learning based approach to automatically layout roads for slums. We propose a generic graph model to capture the topological structure of a slum, and devise a novel graph neural network to select locations for the planned roads. Through masked policy optimization, our model can generate road plans that connect places in a slum at minimal construction costs. Extensive experiments on real-world slums in different countries verify the effectiveness of our model, which can significantly improve accessibility by 14.3% against existing baseline methods. Further investigations on transferring across different tasks demonstrate that our model can master road planning skills in simple scenarios and adapt them to much more complicated ones, indicating the potential of applying our model in real-world slum upgrading. The code and data are available at https://github.com/tsinghua-fib-lab/road-planning-for-slums.Comment: KDD'2

Spatial distribution and diversity of the heterotrophic flagellates in the Cosmonaut Sea, Antarctic

As predators of bacteria and viruses and as food sources for microzooplankton, heterotrophic flagellates (HFs) play an important role in the marine micro-food web. Based on the global climate change’s impact on marine ecosystems, particularly sea ice melting, we analyzed the community composition and diversity of heterotrophic flagellates, focusing on the Antarctic Cosmonaut Sea. During the 36th China Antarctic research expedition (2019-2020), we collected seawater samples, subsequently analyzing HFs through IlluminaMiSeq2000 sequencing to assess community composition and diversity. Notable variations in HFs abundance were observed between the western and eastern sectors of the Cosmonaut Sea, with a distinct concentration at a 100-meter water depth. Different zones exhibited diverse indicators and dominants taxa influenced by local ocean currents. Both the northern Antarctic Peninsula and the western Cosmonaut Sea, where the Weddell Eddy and Antarctic Land Slope Current intersect, showcased marine stramenopiles as dominant HFs species. Our findings offer insights into dominant taxa, spatial distribution patterns among heterotrophic flagellates, correlations between taxa distribution and environmental factors, and the exploration of potential indicator taxa

Higher adjuvant radioactive iodine therapy dosage helps intermediate-risk papillary thyroid carcinoma patients achieve better therapeutic effect

ObjectiveThis retrospective study aims to evaluate the therapeutic effect of varying dosages of adjuvant radioactive iodine (RAI) therapy on intermediate-risk papillary thyroid carcinoma (PTC) patients.MethodsThis retrospective study involved a total of 427 intermediate-risk PTC patients, out of which 202 received a 3.7GBq dosage of RAI, and 225 received a 5.55GBq dosage. The evaluation involved assessing the therapeutic outcomes, number of treatment cycles, and successful remnant ablation rates in both dose groups, six months post-adjuvant RAI therapy. Univariate and multivariate logistic regression analyses were employed to identify factors linked with excellent response (ER). Following this, prognostic nomograms were constructed to provide a visual representation of the prediction models. Calibration curves, the concordance index (C-index), and the receiver operating characteristic (ROC) curve were employed to evaluate the predictive performance of these nomograms. The Hosmer-Lemeshow test was applied to assess the models’ goodness-of-fit. Additionally, the clinical utility of the prognostic nomograms was appraised through decision curve analysis (DCA)ResultsThe high-dose (HD) group exhibited significantly higher proportions of ER, single treatment cycles, and successful remnant ablation rates (p&lt;0.05). Being male, receiving a 3.7GBq dose, having an N1b stage, an sTg level ≥10ng/ml, or an sTg/TSH ratio ≥0.11 were independent risk factors for Non-ER. Two prognostic nomograms, “sTg Nomogram” and “sTg/TSH Nomogram”, were established. The ranking of factors contributing to ER, in descending order, included the sTg or sTg/TSH ratio, N stage, therapy dosage, sex, and soft tissue invasion. The “sTg/TSH Nomogram” demonstrated a higher C-index compared to the “sTg Nomogram”. The calibration curves indicated excellent calibration for both nomograms. DCA demonstrated that the net benefit of the “sTg/TSH Nomogram” was higher than that of the “sTg Nomogram”.ConclusionHigher initial RAI therapy doses can improve therapeutic efficacy for intermediate-risk PTC patients. The developed nomograms, particularly the “sTg/TSH Nomogram”, could assist clinicians in optimal therapeutic decision-making

The various substrates of Usnea aurantiaco-atra and its algal sources in the Fildes Peninsula, Antarctica

The lichen species Usnea aurantiaco-atra (Jacq.) Bory is the most dominant vegetation on the Fildes Peninsula, Antarctica. Most individuals grow on rocks, and some are found with mosses. During the 27th and 28th Chinese National Antarctic Research expeditions of the Great Wall Station, U. aurantiaco-atra was observed growing on the lichen thallus of Umbilicaria antarctica Frey & I.M. Lamb, or on wood, which indicated that Usnea aurantiaco-atra could grow on various substrates. The diversities of the symbionts in U. aurantiaco-atra collected in the Fildes Peninsula were investigated using ITS rDNA sequences. The results showed that the sequences from mycobionts of U. aurantiaco-atra growing on various substrates did not exhibit significant differences. All photobionts in this lichen species were the green algae Trebouxia jamesii (Hildreth & Ahmadjian) Gärtner. The identical sequences from the photobionts of both Umbilicaria antarctica and Usnea aurantiaco-atra indicated there was an algae pool in this area and different mycobionts could obtain their algal partners from this pool. The variety of substrates for U. aurantiaco-atra suggested its photobiont could be obtained from a mature lichen thallus by vegetative propagation; from other lichen thalli (e.g. Umbilicaria antarctica); or from the surroundings. This study will promote understanding of the distribution of photobionts and the process of lichenization

A highly sensitive and selective antioxidant probe based on a bi-modally functionalized conjugated polyelectrolyte

A new water-soluble anionic conjugated polyelectrolyte with a nitroxide radical covalently linked to the sulfonated poly(phenylene ethynylene) backbone (PPE-SO(3)) is reported. This radical-functionalized PPE-SO(3) (RF-PPE-SO(3)) demonstrates fluorescence and electron spin resonance (ESR) bimodal signaling function and shows sensitive and selective response to antioxidants.Ministry of Science and Technology of China[2011CB910403]; National Natural Science Foundation of China[20835005, 20975086, J1030415