Application Effect of Limited Fluid Resuscitation in Emergency Patients with Multiple Trauma Complicated with Shock

This article explores the methods and effects of limited fluid resuscitation in the treatment of hemorrhagic shock caused by multiple trauma, which is common in clinic. 80 patients with multiple trauma complicated with shock were randomly selected from the emergency department of our hospital and divided into the observation group and the control group, with 40 members in each group. Patients in the observation group were treated with limited fluid resuscitation, while those in the control group were treated with aggressive fluid resuscitation. By comparing the therapeutic effects of the two groups, it is concluded that the therapeutic effect of the observation group is significantly better than that of the control group. Therefore, adopting limited fluid resuscitation in the clinical treatment of patients with multiple trauma complicated with shock can realize faster recovery, as well as protect patients’ coagulation function, effectively reducing complications and mortality. Moreover, it can also reduce the injury of trauma perfusion to the body, ensuring the recovery of patients

Understanding Daily Travel Patterns of Subway Users – An Example from the Beijing Subway

The daily travel patterns (DTPs) present short-term and timely characteristics of the users’ travel behaviour, and they are helpful for subway planners to better understand the travel choices and regularity of subway users (SUs) in details. While several well-known subway travel patterns have been detected, such as commuting modes and shopping modes, specific features of many patterns are still confused or omitted. Now, based on the automatic fare collection (AFC) system, a data-mining procedure to recognize DTPs of all SUs has become possible and effective. In this study, DTPs are identified by the station sequences (SSs), which are modelled from smart card transaction data of the AFC system. The data-mining procedure is applied to a large weekly sample from the Beijing Subway to understand DTPs. The results show that more than 93% SUs of the Beijing Subway travel in 7 DTPs, which are remarkably stable in share and distribution. Different DTPs have their own unique characteristics in terms of time distribution, activity duration and repeatability, which provide a wealth of information to calibrate different types of users and characterize their travel patterns.</p

Zero-Shot Aerial Object Detection with Visual Description Regularization

Existing object detection models are mainly trained on large-scale labeled datasets. However, annotating data for novel aerial object classes is expensive since it is time-consuming and may require expert knowledge. Thus, it is desirable to study label-efficient object detection methods on aerial images. In this work, we propose a zero-shot method for aerial object detection named visual Description Regularization, or DescReg. Concretely, we identify the weak semantic-visual correlation of the aerial objects and aim to address the challenge with prior descriptions of their visual appearance. Instead of directly encoding the descriptions into class embedding space which suffers from the representation gap problem, we propose to infuse the prior inter-class visual similarity conveyed in the descriptions into the embedding learning. The infusion process is accomplished with a newly designed similarity-aware triplet loss which incorporates structured regularization on the representation space. We conduct extensive experiments with three challenging aerial object detection datasets, including DIOR, xView, and DOTA. The results demonstrate that DescReg significantly outperforms the state-of-the-art ZSD methods with complex projection designs and generative frameworks, e.g., DescReg outperforms best reported ZSD method on DIOR by 4.5 mAP on unseen classes and 8.1 in HM. We further show the generalizability of DescReg by integrating it into generative ZSD methods as well as varying the detection architecture.Comment: 13 pages, 3 figure

Stacked Intelligent Metasurface Enabled LEO Satellite Communications Relying on Statistical CSI

Low earth orbit (LEO) satellite communication systems have gained increasing attention as a crucial supplement to terrestrial wireless networks due to their extensive coverage area. This letter presents a novel system design for LEO satellite systems by leveraging stacked intelligent metasurface (SIM) technology. Specifically, the lightweight and energy-efficient SIM is mounted on a satellite to achieve multiuser beamforming directly in the electromagnetic wave domain, which substantially reduces the processing delay and computational load of the satellite compared to the traditional digital beamforming scheme. To overcome the challenges of obtaining instantaneous channel state information (CSI) at the transmitter and maximize the system's performance, a joint power allocation and SIM phase shift optimization problem for maximizing the ergodic sum rate is formulated based on statistical CSI, and an alternating optimization (AO) algorithm is customized to solve it efficiently. Additionally, a user grouping method based on channel correlation and an antenna selection algorithm are proposed to further improve the system performance. Simulation results demonstrate the effectiveness of the proposed SIM-based LEO satellite system design and statistical CSI-based AO algorithm.Comment: 14 pages, 4 figures, accepted by IEEE WC

Effects of taurine on male reproduction in rats of different ages

<p>Abstract</p> <p>Background</p> <p>It has been demonstrated that taurine is one of the most abundant free amino acids in the male reproductive system, and can be biosynthesized by male reproductive organs. But the effect of taurine on male reproduction is poorly understood.</p> <p>Methods</p> <p>Taurine and β-alanine (taurine transport inhibitor) were offered in water to male rats of different ages. The effects of taurine on reproductive hormones, testis marker enzymes, antioxidative ability and sperm quality were investigated.</p> <p>Results</p> <p>The levels of T and LH were obviously increased by taurine supplementation in rats of different ages, and the level of E was also significantly elevated in baby rats. The levels of SOD, ACP, SDH and NOS were obviously increased by taurine administration in adult rats, but the levels of AKP, AST, ALT and NO were significantly decreased. The levels of SOD, ACP, LDH, SDH, NOS, NO and GSH were significantly elevated by taurine administration in aged rats, but the levels of AST and ALT were significantly decreased. The motility of spermatozoa was obviously increased by taurine supplement in adult rats. The numbers and motility of spermatozoa, the rate of live spermatozoa were significantly increased by taurine supplement in aged rats.</p> <p>Conclusions</p> <p>The present study demonstrated that a taurine supplement could stimulate the secretion of LH and T, increase the levels of testicular marker enzymes, elevate testicular antioxidation and improve sperm quality. The results imply that taurine plays important roles in male reproduction especially in aged animals.</p

VCL Challenges 2023 at ICCV 2023 Technical Report: Bi-level Adaptation Method for Test-time Adaptive Object Detection

This report outlines our team's participation in VCL Challenges B Continual Test_time Adaptation, focusing on the technical details of our approach. Our primary focus is Testtime Adaptation using bi_level adaptations, encompassing image_level and detector_level adaptations. At the image level, we employ adjustable parameterbased image filters, while at the detector level, we leverage adjustable parameterbased mean teacher modules. Ultimately, through the utilization of these bi_level adaptations, we have achieved a remarkable 38.3% mAP on the target domain of the test set within VCL Challenges B. It is worth noting that the minimal drop in mAP, is mearly 4.2%, and the overall performance is 32.5% mAP

Recessive Social Networking:Preventing Privacy Leakage against Reverse Image Search

This work investigates the image privacy problem in the context of social networking under the threat of reverse image search. We introduce a new concept called recessive social networking. Unlike conventional privacy-preserving social networking, in our setting, the aim is to deceive machine learning algorithms that used in reverse image search, while still enabling unaffected ubiquitous social networking among humans. We, for the first time, ultilize adversarial example technique as a defensive mechanism to protect image privacy against content-based image search algorithms in the context of social networking. Finally, rigorous evaluations are conducted to demonstrate the effectiveness, transferability, and robustness of the proposed countermeasure