Learning Point-Language Hierarchical Alignment for 3D Visual Grounding

This paper presents a novel hierarchical alignment model (HAM) that learns multi-granularity visual and linguistic representations in an end-to-end manner. We extract key points and proposal points to model 3D contexts and instances, and propose point-language alignment with context modulation (PLACM) mechanism, which learns to gradually align word-level and sentence-level linguistic embeddings with visual representations, while the modulation with the visual context captures latent informative relationships. To further capture both global and local relationships, we propose a spatially multi-granular modeling scheme that applies PLACM to both global and local fields. Experimental results demonstrate the superiority of HAM, with visualized results showing that it can dynamically model fine-grained visual and linguistic representations. HAM outperforms existing methods by a significant margin and achieves state-of-the-art performance on two publicly available datasets, and won the championship in ECCV 2022 ScanRefer challenge. Code is available at~\url{https://github.com/PPjmchen/HAM}.Comment: Champion on ECCV 2022 ScanRefer Challeng

PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment

Two-party computation (2PC) is promising to enable privacy-preserving deep learning (DL). However, the 2PC-based privacy-preserving DL implementation comes with high comparison protocol overhead from the non-linear operators. This work presents PASNet, a novel systematic framework that enables low latency, high energy efficiency & accuracy, and security-guaranteed 2PC-DL by integrating the hardware latency of the cryptographic building block into the neural architecture search loss function. We develop a cryptographic hardware scheduler and the corresponding performance model for Field Programmable Gate Arrays (FPGA) as a case study. The experimental results demonstrate that our light-weighted model PASNet-A and heavily-weighted model PASNet-B achieve 63 ms and 228 ms latency on private inference on ImageNet, which are 147 and 40 times faster than the SOTA CryptGPU system, and achieve 70.54% & 78.79% accuracy and more than 1000 times higher energy efficiency.Comment: DAC 2023 accepeted publication, short version was published on AAAI 2023 workshop on DL-Hardware Co-Design for AI Acceleration: RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inferenc

PolyMPCNet: Towards ReLU-free Neural Architecture Search in Two-party Computation Based Private Inference

The rapid growth and deployment of deep learning (DL) has witnessed emerging privacy and security concerns. To mitigate these issues, secure multi-party computation (MPC) has been discussed, to enable the privacy-preserving DL computation. In practice, they often come at very high computation and communication overhead, and potentially prohibit their popularity in large scale systems. Two orthogonal research trends have attracted enormous interests in addressing the energy efficiency in secure deep learning, i.e., overhead reduction of MPC comparison protocol, and hardware acceleration. However, they either achieve a low reduction ratio and suffer from high latency due to limited computation and communication saving, or are power-hungry as existing works mainly focus on general computing platforms such as CPUs and GPUs. In this work, as the first attempt, we develop a systematic framework, PolyMPCNet, of joint overhead reduction of MPC comparison protocol and hardware acceleration, by integrating hardware latency of the cryptographic building block into the DNN loss function to achieve high energy efficiency, accuracy, and security guarantee. Instead of heuristically checking the model sensitivity after a DNN is well-trained (through deleting or dropping some non-polynomial operators), our key design principle is to em enforce exactly what is assumed in the DNN design -- training a DNN that is both hardware efficient and secure, while escaping the local minima and saddle points and maintaining high accuracy. More specifically, we propose a straight through polynomial activation initialization method for cryptographic hardware friendly trainable polynomial activation function to replace the expensive 2P-ReLU operator. We develop a cryptographic hardware scheduler and the corresponding performance model for Field Programmable Gate Arrays (FPGA) platform

Accelerated biological aging in COVID-19 patients

Chronological age is a risk factor for SARS-CoV-2 infection and severe COVID-19. Previous findings indicate that epigenetic age could be altered in viral infection. However, the epigenetic aging in COVID-19 has not been well studied. In this study, DNA methylation of the blood samples from 232 healthy individuals and 413 COVID-19 patients is profiled using EPIC methylation array. Epigenetic ages of each individual are determined by applying epigenetic clocks and telomere length estimator to the methylation profile of the individual. Epigenetic age acceleration is calculated and compared between groups. We observe strong correlations between the epigenetic clocks and individual's chronological age (r > 0.8, p < 0.0001). We also find the increasing acceleration of epigenetic aging and telomere attrition in the sequential blood samples from healthy individuals and infected patients developing non-severe and severe COVID-19. In addition, the longitudinal DNA methylation profiling analysis find that the accumulation of epigenetic aging from COVID-19 syndrome could be partly reversed at late clinic phases in some patients. In conclusion, accelerated epigenetic aging is associated with the risk of SARS-CoV-2 infection and developing severe COVID-19. In addition, the accumulation of epigenetic aging from COVID-19 may contribute to the post-COVID-19 syndrome among survivors. Age is a risk factor for SARS-CoV-2 infection and severe disease. Here the authors perform DNA methylation analyses in whole blood from COVID-19 patients using established epigenetic clocks and telomere length estimators, and describing correlations between epigenetic aging and the risk of SARS-CoV-2 infection and severe disease

Research on Factors Affecting the Optimal Exploitation of Natural Gas Resources in China

This paper develops an optimizing model for the long-term exploitation of limited natural gas reserves in China. In addition to describing the life cycle characteristics of natural gas production and introducing the inter-temporal allocation theory, this paper builds the optimal exploitation model of natural gas resources within a gas field in the Ordos Basin as an example to analyze its exploitation scale and how influence factors, such as recovery rate, discount rate and the gas well exhausting cycle, affect the optimal exploration path of this gas field. We determine that an increase in the discount rate stimulates investors to invest more aggressively in natural gas exploitation in the early period due to the lower discounted value, thereby increasing the pace of the exploitation of natural gas and the exhaustion of gas fields. A higher recoverable factor implies more recoverable reserves and greater potential of increasing the output of gas fields. The exhaustion rate of gas wells affects the capability of converting capacity to output. When exhaustion occurs quickly in gas wells, the output will likely increase in the output rising period, and the output will likely decrease at a faster rate in the output reduction period. Price reform affects the economic recoverable reserves of gas fields

Dual-Zone Active Noise Control Algorithm

When active noise control (ANC) is applied to acquire a &lsquo;quiet zone&rsquo;, it may produce an increase in the sound power outside the quiet zone and a change in the primary sound field, which are undesirable in anti-detection and personal audio. To obtain a large noise reduction in the control zone and a small increase of sound power outside the control zone, three wideband ANC algorithms are proposed based on the acoustic contrast control (ACC), least-squares (LS), and least-squares with acoustic contrast control (SFR-ACC) algorithms. With a loudspeaker array as the secondary source, dual-zone ANC with directivity, which realizes noise reduction in one zone without changing the sound power in the other zone, is achieved. Compared with the traditional LS algorithm, the three algorithms proposed in this paper can not only realize that the sound power outside the control zone is increased by less than 1 dB, but also reduce the noise in the control zone by more than 10 dB, which provides a new solution to multi-zone ANC research

Multiple Arginine Residues Are Methylated in Drosophila Mre11 and Required for Survival Following Ionizing Radiation

Mre11 is a key player for DNA double strand break repair. Previous studies have shown that mammalian Mre11 is methylated at multiple arginines in its C-terminal Glycine-Arginine-Rich motif (GAR) by protein arginine methyltransferase PRMT1. Here, we found that the Drosophila Mre11 is methylated at arginines 559, 563, 565, and 569 in the GAR motif by DART1, the Drosophila homolog of PRMT1. Mre11 interacts with DART1 in S2 cells, and this interaction does not require the GAR motif. Arginines methylated Mre11 localizes exclusively in the nucleus as soluble nuclear protein or chromatin-binding protein. To study the in vivo functions of methylation, we generated the single Arg-Ala and all Arginines mutated flies. We found these mutants were sensitive to ionizing radiation. Furthermore, Arg-Ala mutated flies had no irradiation induced G2/M checkpoint defect in wing disc and eye disc. Thus, we provided evidence that arginines in Drosophila Mre11 are methylated by DART1 methytransferase and flies loss of arginine methylation are sensitive to irradiation

Non-coal mine safety supervision mode based on risk monitoring and early warning

At present, non-coal mine safety supervision mainly includes safety management inspection and on-site safety supervision inspection. They rely on safety information management platform and on-site inspection by safety inspectors respectively. There are problems of low supervision efficiency, delayed information acquisition, and it is difficult to realize dynamic and comprehensive supervision. In view of the above problems, this paper puts forward a non-coal mine safety supervision mode based on risk monitoring and early warning, considering the characteristics of non-coal mines, such as large number, scattered, poor, small, and the differences in risks and informatization management and control of different types of non-coal mines. Based on the risk monitoring and early warning system of non-coal mine, the risk monitoring index data in five aspects of personnel, environment, equipment and facilities, management and monitoring topics are extracted. The single risk early warning analysis and comprehensive risk alarm analysis are carried out in two ways of risk point and risk surface respectively. The graded push of single risk early warning and the graded control of comprehensive risk alarm can be realized. The monitoring data and special topics of various types of non-coal mines are sorted out. The trigger and disposal mechanism of single risk graded early warning is introduced. This study focuses on the construction process of the model for comprehensive risk research and judgment and graded supervision. Based on the risk monitoring data of non-coal mines, the risk monitoring index system is established. The entropy weight method is adopted to give weight to the risk monitoring index, and the scoring standard is formulated to score the risk index of non-coal mines. Based on the index weight and score, the comprehensive risk level of mining enterprises is determined. The non-coal mine safety supervision mode based on risk monitoring and early warning realizes the graded supervision and inspection of non-coal mines by supervision departments under different supervision periods and ranges. The mode optimizes the allocation of supervision and inspection resources, and improves the efficiency of supervision and inspection

Speciation analysis of 129I in seawater using coprecipitationand accelerator mass spectrometry and its applications

Speciation analysis of long-lived 129I in seawater can provide useful information on the source of water masses. This paper presents an improved method for speciation analysis of 129I based on coprecipitation of iodide as AgI with Ag2SO3 and AgCl. By adding a small amount of 127I carrier, the separation efficiency of iodine species and the accuracy and precision of 129I measurement are remarkably improved. 129I species in depth profiles of seawater from the Antarctic were analyzed for investigation of water circulation in the Antarctic

The efficacy of mouthwashes on oral microorganisms and gingivitis in patients undergoing orthodontic treatment: a systematic review and meta-analysis

Abstract Background Mouthwashes were convenient adjuncts to mechanical cleaning procedures. This review aimed to evaluate the efficacy of mouthwashes on oral microorganisms and gingivitis in orthodontic patients. Methods By April 16, 2022, multiple databases and grey literature were searched based on the PICOS strategy. Randomized controlled trials in orthodontic patients evaluating the efficacy of mouthwashes with at least one microbial parameter and/or plaque- and/or gingival inflammation-related index were included. Relevant data were extracted, and the risk of bias was evaluated using Cochrane's tool. Individual mean and standard deviation of the outcomes in mouthwashes and placebos/blank controls were pooled to estimate the weighted mean differences (WMDs) and 95% confidence intervals (95%CIs). Sensitivity analysis, and certainty of evidence were evaluated. Results Of 1684 articles, 32 studies satisfied the eligibility criteria, and nine were included for meta-analysis. Missing outcome data was the primary source of bias. Compared to blank controls, the short-term application of fluoride mouthwashes significantly reduced the colony counts of Mutans streptococci (MS), while the long-term application may not be effective. Compared to placebos or blank controls, Chlorhexidine mouthwashes significantly reduced the colony counts of multiple microorganisms in the short-term. Compared to placebos or blank controls, herbal mouthwashes showed the inhibitory effect of MS in the short-term, with some results lacking statistical significance. After meta-analysis, significant lower plaque- and gingival inflammation-related indexes were observed in the Chlorhexidine mouthwashes groups [Gingival Index: WMD = -0.45, 95%CI = -0.70 to -0.20 (placebos as control); WMD = -0.54, 95%CI = -0.96 to -0.13 (blank controls); Plaque Index: WMD = -0.70, 95%CI = -1.12 to -0.27 (blank controls)]. Significant lower gingival inflammation-related indexes were observed in the herbal mouthwashes groups [Gingival Index: WMD = -0.20, 95%CI = -0.32 to -0.09 (blank controls)]. Conclusions The short-term application of fluoride mouthwashes may reduce the colony counts of cariogenic bacteria, but the long-term effect is not evident. Chlorhexidine may reduce the colony counts of multiple microorganisms in the short-term. Short-term application Chlorhexidine and herbal mouthwashes may effectively reduce plaque- and gingival inflammation-related indexes. However, the risk of bias, inconsistency, and imprecision in the included studies may reduce the certainty of the evidence