Facial Video-based Remote Physiological Measurement via Self-supervised Learning

Facial video-based remote physiological measurement aims to estimate remote photoplethysmography (rPPG) signals from human face videos and then measure multiple vital signs (e.g. heart rate, respiration frequency) from rPPG signals. Recent approaches achieve it by training deep neural networks, which normally require abundant facial videos and synchronously recorded photoplethysmography (PPG) signals for supervision. However, the collection of these annotated corpora is not easy in practice. In this paper, we introduce a novel frequency-inspired self-supervised framework that learns to estimate rPPG signals from facial videos without the need of ground truth PPG signals. Given a video sample, we first augment it into multiple positive/negative samples which contain similar/dissimilar signal frequencies to the original one. Specifically, positive samples are generated using spatial augmentation. Negative samples are generated via a learnable frequency augmentation module, which performs non-linear signal frequency transformation on the input without excessively changing its visual appearance. Next, we introduce a local rPPG expert aggregation module to estimate rPPG signals from augmented samples. It encodes complementary pulsation information from different face regions and aggregate them into one rPPG prediction. Finally, we propose a series of frequency-inspired losses, i.e. frequency contrastive loss, frequency ratio consistency loss, and cross-video frequency agreement loss, for the optimization of estimated rPPG signals from multiple augmented video samples and across temporally neighboring video samples. We conduct rPPG-based heart rate, heart rate variability and respiration frequency estimation on four standard benchmarks. The experimental results demonstrate that our method improves the state of the art by a large margin.Comment: IEEE Transactions on Pattern Analysis and Machine Intelligenc

Tightness of exponential metrics for log-correlated Gaussian fields in arbitrary dimension

We prove the tightness of a natural approximation scheme for an analog of the Liouville quantum gravity metric on $\mathbb R^d$ for arbitrary $d\geq 2$. More precisely, let $\{h_n\}_{n\geq 1}$ be a suitable sequence of Gaussian random functions which approximates a log-correlated Gaussian field on $\mathbb R^d$. Consider the family of random metrics on $\mathbb R^d$ obtained by weighting the lengths of paths by $e^{\xi h_n}$, where $\xi > 0$ is a parameter. We prove that if $\xi$ belongs to the subcritical phase (which is defined by the condition that the distance exponent $Q(\xi)$ is greater than $\sqrt{2d}$), then after appropriate re-scaling, these metrics are tight and that every subsequential limit is a metric on $\mathbb R^d$ which induces the Euclidean topology. We include a substantial list of open problems.Comment: 68 pages, 8 figures; version 2 has updated reference

Enhancing Space-time Video Super-resolution via Spatial-temporal Feature Interaction

The target of space-time video super-resolution (STVSR) is to increase both the frame rate (also referred to as the temporal resolution) and the spatial resolution of a given video. Recent approaches solve STVSR with end-to-end deep neural networks. A popular solution is to first increase the frame rate of the video; then perform feature refinement among different frame features; and last increase the spatial resolutions of these features. The temporal correlation among features of different frames is carefully exploited in this process. The spatial correlation among features of different (spatial) resolutions, despite being also very important, is however not emphasized. In this paper, we propose a spatial-temporal feature interaction network to enhance STVSR by exploiting both spatial and temporal correlations among features of different frames and spatial resolutions. Specifically, the spatial-temporal frame interpolation module is introduced to interpolate low- and high-resolution intermediate frame features simultaneously and interactively. The spatial-temporal local and global refinement modules are respectively deployed afterwards to exploit the spatial-temporal correlation among different features for their refinement. Finally, a novel motion consistency loss is employed to enhance the motion continuity among reconstructed frames. We conduct experiments on three standard benchmarks, Vid4, Vimeo-90K and Adobe240, and the results demonstrate that our method improves the state of the art methods by a considerable margin. Our codes will be available at https://github.com/yuezijie/STINet-Space-time-Video-Super-resolution

Impact of subchorionic hematoma on pregnancy outcomes in women with recurrent pregnancy loss

We conducted a retrospective cohort study with the aim of investigating the relationship between subchorionic hematoma (SCH) and pregnancy outcomes in women with recurrent pregnancy loss (RPL). We reviewed all RPL patients who came to the Fourth Hospital of Shijiazhuang from January 2019 to June 2021. Two groups were divided according to the presence or absence of SCH. Live birth rate was considered as the primary outcome. Secondary outcomes included adverse pregnancy outcomes and complications. Univariable and multivariable analyses were conducted. Of 274 RPL women included in the final analysis, 49 (17.9%) had SCH. The occurrence of thrombophilia was significantly higher in SCH group than that in non-SCH group (38.8% vs 24.4%, P=0.041). There were no significant differences between the two groups in live birth rate, adverse pregnancy outcomes and pregnancy complications. Among women with SCH, live birth rate or SCH duration was not associated with continued use of low-dose aspirin (LDA) after the diagnosis of SCH. Our findings suggest that SCH does not reduce live birth rate in RPL women or increase the risk of adverse pregnancy outcomes or pregnancy complications. Continued use of LDA after the detection of a hematoma is unlikely to affect SCH duration or the live birth rate

Role of cystatin C in urogenital malignancy

Urogenital malignancy accounts for one of the major causes of cancer-related deaths globally. Numerous studies have investigated novel molecular markers in the blood circulation, tumor tissue, or urine in order to assist in the clinical identification of tumors at early stages, predict the response of therapeutic strategies, and give accurate prognosis assessment. As an endogenous inhibitor of lysosomal cysteine proteinases, cystatin C plays an integral role in diverse processes. A substantial number of studies have indicated that it may be such a potential promising biomarker. Therefore, this review was intended to provide a detailed overview of the role of cystatin C in urogenital malignancy

Key Information Retrieval to Classify the Unstructured Data Content of Preferential Trade Agreements

With the rapid proliferation of textual data, predicting long texts has emerged as a significant challenge in the domain of natural language processing. Traditional text prediction methods encounter substantial difficulties when grappling with long texts, primarily due to the presence of redundant and irrelevant information, which impedes the model's capacity to capture pivotal insights from the text. To address this issue, we introduce a novel approach to long-text classification and prediction. Initially, we employ embedding techniques to condense the long texts, aiming to diminish the redundancy therein. Subsequently,the Bidirectional Encoder Representations from Transformers (BERT) embedding method is utilized for text classification training. Experimental outcomes indicate that our method realizes considerable performance enhancements in classifying long texts of Preferential Trade Agreements. Furthermore, the condensation of text through embedding methods not only augments prediction accuracy but also substantially reduces computational complexity. Overall, this paper presents a strategy for long-text prediction, offering a valuable reference for researchers and engineers in the natural language processing sphere.Comment: AI4TS Workshop@AAAI 2024 accepted publicatio

Efficient Secure Multiparty Computation for Multidimensional Arithmetics and Its Application in Privacy-Preserving Biometric Identification

Over years of the development of secure multi-party computation (MPC), many sophisticated functionalities have been made pratical and multi-dimensional operations occur more and more frequently in MPC protocols, especially in protocols involving datasets of vector elements, such as privacy-preserving biometric identification and privacy-preserving machine learning. In this paper, we introduce a new kind of correlation, called tensor triples, which is designed to make multi-dimensional MPC protocols more efficient. We will discuss the generation process, the usage, as well as the applications of tensor triples and show that it can accelerate privacy-preserving biometric identification protocols, such as FingerCode, Eigenfaces and FaceNet, by more than 1000 times

Optimizing nitrogen-fertilizer management by using RZWQM2 with consideration of precipitation can enhance nitrogen utilization on the Loess Plateau

Crop yields are related to N fertilizer management, and also depend on local precipitation. Varying precipitation levels with long-term meteorological data have not been considered to optimize nitrogen (N) strategies in previous studies on the Loess Plateau of China. In this study, Root Zone Water Quality Model 2 (RZWQM2) was calibrated and validated using data from multi-year experiments and used to assess and optimize N management strategies for winter wheat cultivation. Results showed that the basal dressing fertilizer with 120 kg N ha-1 together with the topdressing of 67–77 kg N ha-1 was recommended in regions with 443 mm average annual precipitation. For those with 364 mm and 290 mm average annual precipitation, the basal dressing fertilizer with 90 kg N ha-1 together with the topdressing of 67–77 kg N ha-1 and the basal dressing with 90 kg N ha-1 together with the topdressing fertilizer of 13–23 kg N ha-1 were recommended, respectively. Compared with farmers’ practice (i.e., the single basal dressing), although decreasing the total rate by 12–18 kg N ha-1, the optimized N strategies (i.e., the basal fertilizer together with one-time topdressing) can effectively promote grain N uptake, nitrogen harvest index, and agronomic efficiency of N. It also maintained similar grain yield, evapotranspiration, and crop water productivity. The minimum precipitation threshold was around 300 mm, where the topdressing N fertilizer had little influence on grain yield, evapotranspiration, and grain N uptake. Additionally, the largest advantage of optimized N strategies was saving N fertilizer and reducing the environment footprint of wheat production. However, the crop production under the optimized N strategies was more sensitive to the precipitation variation than that under farmers’ practice. Thus, if climate continues to change following historical data, greater harvest fluctuations are expected under optimized N strategies. To cope with the evolving climate change, optimized N strategies should be integrated with other management measures for smallholder farming households on the Loess Plateau

Reverse atrial remodeling in heart failure with recovered ejection fraction

Background Heart failure with recovered ejection fraction (HFrecEF) has been a newly recognized entity since 2020. However, the concept has primarily focused on left ventricular ejection fraction improvement, with less focus on the recovery of the left atrium. In this study, we investigated changes in left atrial (LA) echocardiographic indices in HFrecEF. Methods and Results An inpatient cohort with heart failure with reduced ejection fraction (HFrEF) was identified retrospectively and followed up prospectively in a single tertiary hospital. The enrolled patients were classified into HFrecEF and persistent HFrEF groups. Alternations in LA parameters by echocardiography were calculated. The primary outcome was a composite of cardiovascular death or heart failure rehospitalization. A total of 699 patients were included (HFrecEF: n=228; persistent HFrEF: n=471). Compared with persistent HFrEF, the HFrecEF group had greater reductions in LA diameter, LA transverse diameter, LA superior–inferior diameter, LA volume, and LA volume index but not in LA sphericity index. Cox regression analysis showed that the HFrecEF group experienced lower risks of prespecified end points than the persistent HFrEF group after adjusting for confounders. Additionally, 136 (59.6%) and 62 (13.0%) patients showed LA reverse remodeling (LARR) for the HFrecEF and persistent HFrEF groups, respectively. Among the HFrecEF subgroup, patients with LARR had better prognosis compared with those without LARR. Multivariate logistic analysis demonstrated that age and coronary heart disease were 2 independent negative predictors for LARR. Conclusions In HFrecEF, both left ventricular systolic function and LA structure remodeling were improved. Patients with HFrecEF with LARR had improved clinical outcomes, indicating that the evaluation of LA size provides a useful biomarker for risk stratification of heart failure

Efficacy of guideline-directed medical treatment in heart failure with mildly reduced ejection fraction.

Heart failure with mildly reduced ejection fraction (HFmrEF) has received increasing attention following the publication of the latest ESC guidelines in 2021. However, it remains unclear whether patients with HFmrEF could benefit from guideline-directed medical treatment (GDMT), referring the combination of ACEI/ARB/ARNI, β-blockers, and MRAs, which are recommended for those with reduced ejection fraction. This study explored the efficacy of GDMT in HFmrEF patients. This was a retrospective cohort study of HFmrEF patients admitted to The First Affiliated Hospital of Dalian Medical University between 1 September 2015 and 30 November 2019. Propensity score matching (1:2) between patients receiving triple-drug therapy (TT) and non-triple therapy (NTT) based on age and sex was performed. The primary outcome was all cause death, cardiac death, rehospitalization from any cause, and rehospitalization due to worsening heart failure. Of the 906 patients enrolled in the matched cohort (TT group, n = 302; NTT group, N = 604), 653 (72.08%) were male, and mean age was 61.1 ± 11.92. Survival analysis suggested that TT group experienced a significantly lower incidence of prespecified primary endpoints than NTT group. Multivariable Cox regression showed that TT group had a lower risk of all-cause mortality (HR 0.656, 95% CI 0.447-0.961, P = 0.030), cardiac death (HR 0.599, 95% CI 0.380-0.946, P = 0.028), any-cause rehospitalization (HR 0.687, 95% CI 0.541-0.872, P = 0.002), and heart failure rehospitalization (HR 0.732, 95% CI 0.565-0.948, P = 0.018). In patients with HFmrEF, combined use of neurohormonal antagonists produces remarkable effects in reducing the occurrence of the primary outcome of rehospitalization and death. Thus, the treatment of HFmrEF should be categorized as HFrEF due to the similar benefit of neurohormonal blocking therapy in HFrEF and HFmrEF. [Abstract copyright: © 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.