Weakly Supervised Video Representation Learning with Unaligned Text for Sequential Videos

Sequential video understanding, as an emerging video understanding task, has driven lots of researchers' attention because of its goal-oriented nature. This paper studies weakly supervised sequential video understanding where the accurate time-stamp level text-video alignment is not provided. We solve this task by borrowing ideas from CLIP. Specifically, we use a transformer to aggregate frame-level features for video representation and use a pre-trained text encoder to encode the texts corresponding to each action and the whole video, respectively. To model the correspondence between text and video, we propose a multiple granularity loss, where the video-paragraph contrastive loss enforces matching between the whole video and the complete script, and a fine-grained frame-sentence contrastive loss enforces the matching between each action and its description. As the frame-sentence correspondence is not available, we propose to use the fact that video actions happen sequentially in the temporal domain to generate pseudo frame-sentence correspondence and supervise the network training with the pseudo labels. Extensive experiments on video sequence verification and text-to-video matching show that our method outperforms baselines by a large margin, which validates the effectiveness of our proposed approach. Code is available at https://github.com/svip-lab/WeakSVRComment: CVPR 2023. Code: https://github.com/svip-lab/WeakSV

Pre-disaster transmission maintenance scheduling considering network topology optimization

Several devastating experiences with extreme natural disasters demonstrate that improving power system resilience is becoming increasingly important. This paper proposes a pre-disaster transmission maintenance scheduling considering network topology optimization to ensure the power system economics before disasters and power system resilience during disasters. The transmission line fragility is distinguished and considered in the proposed optimization model to determine the maintenance scheduling of defective lines that minimizes load shedding during disasters. The proposed model is established as a tri-level optimization problem that is further reformulated to a bi-level problem utilizing duality theory. The column-and-constraint generation (C&CG) algorithm is employed to solve the equivalent robust optimization problem. Finally, the proposed model and its solution algorithm are implemented on the modified IEEE RTS-79 system. The significant cost savings and increased resilience illustrate the effectiveness of the proposed model

Circulating tumor DNA clearance predicts prognosis across treatment regimen in a large real-world longitudinally monitored advanced non-small cell lung cancer cohort

Background: Although growth advantage of certain clones would ultimately translate into a clinically visible disease progression, radiological imaging does not reflect clonal evolution at molecular level. Circulating tumor DNA (ctDNA), validated as a tool for mutation detection in lung cancer, could reflect dynamic molecular changes. We evaluated the utility of ctDNA as a predictive and a prognostic marker in disease monitoring of advanced non-small cell lung cancer (NSCLC) patients.Methods: This is a multicenter prospective cohort study. We performed capture-based ultra-deep sequencing on longitudinal plasma samples utilizing a panel consisting of 168 NSCLC-related genes on 949 advanced NSCLC patients with driver mutations to monitor treatment responses and disease progression. The correlations between ctDNA and progression-free survival (PFS)/overall survival (OS) were performed on 248 patients undergoing various treatments with the minimum of 2 ctDNA tests.Results: The results of this study revealed that higher ctDNA abundance (P=0.012) and mutation count (P=8.5x10(-4)) at baseline are associated with shorter OS. We also found that patients with ctDNA clearance, not just driver mutation clearance, at any point during the course of treatment were associated with longer PFS (P=2.2x10(-1)6, HR 0.28) and OS (P=4.5x10(-6), HR 0.19) regardless of type of treatment and evaluation schedule.Conclusions: This prospective real-world study shows that ctDNA clearance during treatment may serve as predictive and prognostic marker across a wide spectrum of treatment regimens

The transmembrane channel-like 6 (TMC6) in primary sensory neurons involving thermal sensation via modulating M channels

Introduction: The transmembrane channel-like (TMC) protein family contains eight members, TMC1–TMC8. Among these members, only TMC1 and TMC2 have been intensively studied. They are expressed in cochlear hair cells and are crucial for auditory sensations. TMC6 and TMC8 contribute to epidermodysplasia verruciformis, and predispose individuals to human papilloma virus. However, the impact of TMC on peripheral sensation pain has not been previously investigated.Methods: RNAscope was employed to detect the distribution of TMC6 mRNA in DRG neurons. Electrophysiological recordings were conducted to investigate the effects of TMC6 on neuronal characteristics and M channel activity. Zn2+ indicators were utilized to detect the zinc concentration in DRG tissues and dissociated neurons. A series of behavioural tests were performed to assess thermal and mechanical sensation in mice under both physiological and pathological conditions.Results and Discussion: We demonstrated that TMC6 is mainly expressed in small and medium dorsal root ganglion (DRG) neurons and is involved in peripheral heat nociception. Deletion of TMC6 in DRG neurons hyperpolarizes the resting membrane potential and inhibits neuronal excitability. Additionally, the function of the M channel is enhanced in TMC6 deletion DRG neurons owing to the increased quantity of free zinc in neurons. Indeed, heat and mechanical hyperalgesia in chronic pain are alleviated in TMC6 knockout mice, particularly in the case of heat hyperalgesia. This suggests that TMC6 in the small and medium DRG neurons may be a potential target for chronic pain treatment

Locally advanced rectal cancer with dMMR/MSI-H may be excused from surgery after neoadjuvant anti-PD-1 monotherapy: a multiple-center, cohort study

ObjectiveExamine patients with locally advanced rectal cancer (LARC) with deficient mismatch repair (dMMR) or microsatellite instability-high (MSI-H) who received neoadjuvant immunotherapy (nIT), and compare the outcomes of those who chose a watch-and-wait (WW) approach after achieving clinical complete response (cCR) or near-cCR with those who underwent surgery and were confirmed as pathological complete response (pCR).MethodsLARC patients with dMMR/MSI-H who received nIT were retrospectively examined. The endpoints were 2-year overall survival (OS), 2-year disease-free survival (DFS), local recurrence (LR), and distant metastasis (DM). The efficacy of programmed cell death protein-1 (PD-1) inhibitor, immune-related adverse events (irAEs), surgery-related adverse events (srAEs), and enterostomy were also recorded.ResultsTwenty patients who received a PD-1 inhibitor as initial nIT were examined. Eighteen patients (90%) achieved complete response (CR) after a median of 7 nIT cycles, including 11 with pCR after surgery (pCR group), and 7 chose a WW strategy after evaluation as cCR or near-cCR (WW group). Both groups had median follow-up times of 25.0 months. Neither group had a case of LR or DM, and the 2-year DFS and OS in each group was 100%. The two groups had similar incidences of irAEs (P=0.627). In the pCR group, however, 2 patients (18.2%) had permanent colostomy, 3 (27.3%) had temporary ileostomy, and 2 (18.2%) had srAEs.ConclusionNeoadjuvant PD-1 blockade had high efficacy and led to a high rate of CR in LARC patients with dMMR/MSI-H. A WW strategy appears to be a safe and reliable option for these patients who achieve cCR or near-cCR after nIT

Nitrification inhibitor chlorate and nitrogen substrates differentially affect comammox Nitrospira in a grassland soil

IntroductionThrough the combined use of two nitrification inhibitors, Dicyandiamide (DCD) and chlorate with nitrogen amendment, this study aimed to investigate the contribution of comammox Nitrospira clade B, ammonia oxidizing bacteria (AOB) and archaea (AOA) to nitrification in a high fertility grassland soil, in a 90-day incubation study.MethodsThe soil was treated with nitrogen (N) at three levels: 0 mg-N kg-1 soil, 50 mg-N kg-1 soil, and 700 mg-N kg-1 soil, with or without the two nitrification inhibitors. The abundance of comammox Nitrospira, AOA, AOB, and nitrite oxidising bacteria (NOB) was measured using qPCR. The comammox Nitrospira community structure was assessed using Illumina sequencing.Results and DiscussionThe results showed that the application of chlorate inhibited the oxidation of both NH4+ and NO2- in all three nitrogen treatments. The application of chlorate significantly reduced the abundance of comammox Nitrospira amoA and nxrB genes across the 90-day experimental period. Chlorate also had a significant effect on the beta diversity (Bray-Curtis dissimilarity) of the comammox Nitrospira clade B community. Whilst AOB grew in response to the N substrate additions and were inhibited by both inhibitors, AOA showed litle or no response to either the N substrate or inhibitor treatments. In contrast, comammox Nitrospira clade B were inhibited by the high ammonium concentrations released from the urine substrates. These results demonstrate the differential and niche responses of the three ammonia oxidising communities to N substrate additions and nitrification inhibitor treatments. Further research is needed to investigate the specificity of the two inhibitors on the different ammonia oxidising communities

Two ultraviolet radiation datasets that cover China

Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes