Conservation and efficient utilization of resources: a major indicator of China's economic transformation

After more than 30 years of rapid growth, China's economy is increasingly faced with the bottleneck brought about by resources and environment. To achieve a sustained economic growth, more attention should be paid to the safety of the arable land, fresh water, energy, and other important resources. Great efforts should be made to transform the mode of economic development, adjust the economic structure, deepen reform, and expand opening-up. It is necessary to promote the transformation of the growth means characterized by ineffective utilization of resources and extensive expansion to the one characterized by intensive and efficient utilization of resources as well as quality and efficiency so that the economy and society are really going toward the track of scientific development

Offline and Online Optical Flow Enhancement for Deep Video Compression

Video compression relies heavily on exploiting the temporal redundancy between video frames, which is usually achieved by estimating and using the motion information. The motion information is represented as optical flows in most of the existing deep video compression networks. Indeed, these networks often adopt pre-trained optical flow estimation networks for motion estimation. The optical flows, however, may be less suitable for video compression due to the following two factors. First, the optical flow estimation networks were trained to perform inter-frame prediction as accurately as possible, but the optical flows themselves may cost too many bits to encode. Second, the optical flow estimation networks were trained on synthetic data, and may not generalize well enough to real-world videos. We address the twofold limitations by enhancing the optical flows in two stages: offline and online. In the offline stage, we fine-tune a trained optical flow estimation network with the motion information provided by a traditional (non-deep) video compression scheme, e.g. H.266/VVC, as we believe the motion information of H.266/VVC achieves a better rate-distortion trade-off. In the online stage, we further optimize the latent features of the optical flows with a gradient descent-based algorithm for the video to be compressed, so as to enhance the adaptivity of the optical flows. We conduct experiments on a state-of-the-art deep video compression scheme, DCVC. Experimental results demonstrate that the proposed offline and online enhancement together achieves on average 12.8% bitrate saving on the tested videos, without increasing the model or computational complexity of the decoder side.Comment: 9 pages, 6 figure

MotionChain: Conversational Motion Controllers via Multimodal Prompts

Recent advancements in language models have demonstrated their adeptness in conducting multi-turn dialogues and retaining conversational context. However, this proficiency remains largely unexplored in other multimodal generative models, particularly in human motion models. By integrating multi-turn conversations in controlling continuous virtual human movements, generative human motion models can achieve an intuitive and step-by-step process of human task execution for humanoid robotics, game agents, or other embodied systems. In this work, we present MotionChain, a conversational human motion controller to generate continuous and long-term human motion through multimodal prompts. Specifically, MotionChain consists of multi-modal tokenizers that transform various data types such as text, image, and motion, into discrete tokens, coupled with a Vision-Motion-aware Language model. By leveraging large-scale language, vision-language, and vision-motion data to assist motion-related generation tasks, MotionChain thus comprehends each instruction in multi-turn conversation and generates human motions followed by these prompts. Extensive experiments validate the efficacy of MotionChain, demonstrating state-of-the-art performance in conversational motion generation, as well as more intuitive manners of controlling and interacting with virtual humans.Comment: 14 pages, 4 figure

Identification of human fetal liver miRNAs by a novel method

AbstractMicroRNAs (miRNAs) are short 20–25 nucleotides RNA molecules that have been shown to regulate gene expressions in a variety of eukaryotic systems. miRNAs are widespread in eukaryotes and several hundred of miRNAs have been identified, but still a lot of miRNAs have not been detected in various eukaryotic organisms. However, it is not an easy work to clone miRNAs by traditional methods. Here, we describe the identification of 27 miRNAs from a human fetal liver cDNA library by a novel cloning method. Low molecular weight RNA fraction (⩽200nt) from fetal liver tissue was extracted, and polyadenylated by poly(A) polymerase. A 5′ RNA adaptor was ligated to poly(A)-tailed RNA using T4 RNA ligase. After reverse transcription, the cDNA was amplified by PCR with two adaptor primers. The PCR product with a size about 109bp was recovered and cloned into T vector. After sequencing, database searching, and expression profiling, 5 novel miRNAs were discovered among other 22 known miRNAs in human fetal liver. These finding indicate that a large diverse population of miRNAs may function to regulate gene expression in hepatocyte

Cumulative sum learning curve analysis of tubularized incised plate repair for hypospadias: a study of a single surgeon with a single surgical procedure

PurposeTo ascertain the quantity of instances by which a single surgeon achieves competency and proficiency in using tubularized incised plate (TIP) technique for the repair of distal and mid-shaft hypospadias using the cumulative sum (CUSUM) analysis.MethodsWe retrospectively evaluated patients with distal and mid-shaft hypospadias who were treated by a single surgeon between 2015 and 2021, using a single primary TIP technique with a de-epithelialized Byars flap. Data including type of hypospadias, age at surgery, curvature, operation time (OT), length of the reconstructed urethra, and postoperative outcomes were collected and assessed. CUSUM was used to assess the trends in OT and complication rate (CR) in order to generate the learning curve. The evolution of OT and CR can be divided into three phases: learning, competence, and proficiency.ResultsCUSUM identified three phases in the learning curves of all TIP repairs. The median OT decreased from 135 min [interquartile range (IQR) = 125–155] to 92 min (IQR = 80–100) (P < 0.001), CR decreased from 28 (28%) to 8 (5.3%) (P < 0.001), and reoperations decreased from 15 (15.2%) to 4 (2.6%) (P < 0.001). According to the CUSUM learning curve, technical competency plateaued after the 99th case, and both OT and CR entered a significantly declining proficiency phase after the 231st case. Further, when the neourethral length exceeded the total average, total complications, urethrocutaneous fistula, and reoperations increased (P = 0.013, P = 0.006, and P = 0.028, respectively).ConclusionsOur study suggests that surgeons performing TIP repair may reach technical competency and achieve proficiency after operating on 99,231 cases, respectively. Moreover, the longer the neourethral length, the higher is the CR

SpeechLM: Enhanced Speech Pre-Training with Unpaired Textual Data

How to boost speech pre-training with textual data is an unsolved problem due to the fact that speech and text are very different modalities with distinct characteristics. In this paper, we propose a cross-modal Speech and Language Model (SpeechLM) to explicitly align speech and text pre-training with a pre-defined unified discrete representation. Specifically, we introduce two alternative discrete tokenizers to bridge the speech and text modalities, including phoneme-unit and hidden-unit tokenizers, which can be trained using a small amount of paired speech-text data. Based on the trained tokenizers, we convert the unlabeled speech and text data into tokens of phoneme units or hidden units. The pre-training objective is designed to unify the speech and the text into the same discrete semantic space with a unified Transformer network. Leveraging only 10K text sentences, our SpeechLM gets a 16\% relative WER reduction over the best base model performance (from 6.8 to 5.7) on the public LibriSpeech ASR benchmark. Moreover, SpeechLM with fewer parameters even outperforms previous SOTA models on CoVoST-2 speech translation tasks. We also evaluate our SpeechLM on various spoken language processing tasks under the universal representation evaluation framework SUPERB, demonstrating significant improvements on content-related tasks. Our code and models are available at https://aka.ms/SpeechLM.Comment: 14 page

Comparison of curative effect between OBS assisted by 3D printing and PFNA in the treatment of AO/OTA type 31-A3 femoral intertrochanteric fractures in elderly patients

ObjectiveTo compare and analyze the Ortho-Bridge System (OBS) clinical efficacy assisted by 3D printing and proximal femoral nail anti-rotation (PFNA) of AO/OTA type 31-A3 femoral intertrochanteric fractures in elderly patients.MethodsA retrospective analysis of 25 elderly patients diagnosed with AO/OTA type 31-A3 femoral intertrochanteric fracture was conducted from January 2020 to August 2022 at Yan’an Hospital, affiliated to Kunming Medical University. The patients were divided into 10 patients in the OBS group and 15 in the PFNA group according to different surgical methods. The OBS group reconstructed the bone models and designed the guide plate by computer before the operation, imported the data of the guide plate and bone models into a stereolithography apparatus (SLA) 3D printer, and printed them using photosensitive resin, thus obtaining the physical object, then simulating the operation and finally applying the guide plate to assist OBS to complete the operation; the PFNA group was treated by proximal femoral nail anti-rotation. The operation time, the intraoperative blood loss, Harris hip score (HHS), Oxford Hip Score (OHS), and complications were compared between the two groups.ResultsThe operation time and the intraoperative blood loss in the PFNA group were less than that in the OBS group, and there was a significant difference between the two groups (P < 0.05). The HHS during the 6th month using OBS was statistically higher than PFNA (P < 0.05), however, there were no significant differences in OHS during the 6th month between the OBS group and PFNA group (P > 0.05). The HHS and OHS during the 12th month in the OBS group were statistically better than in the PFNA group (P < 0.05).ConclusionThe OBS assisted by 3D printing and PFNA are effective measures for treating intertrochanteric fractures. Prior to making any decisions regarding internal fixation, it is crucial to evaluate the distinct circumstances of each patient thoroughly