Comparative Analysis of the Core Values among Different Groups of Chinese People

Values are principles that guide people’s behavior. Values are formed by life experiences influenced by one’s family, school, culture, and society. Some values are universal and others are culturally distinct. This project intends to examine if people change their values as they go through different stages of life, especially for students who grew up in China and come to American universities for education. Do they keep their values intact or do their values change? If their values change, in what areas do those changes occur and to what degree do they occur? This project studies the values held by Chinese students in China, Chinese students studying in the United States, and students of Chinese origin

EDA: Explicit Text-Decoupling and Dense Alignment for 3D Visual Grounding

3D visual grounding aims to find the object within point clouds mentioned by free-form natural language descriptions with rich semantic cues. However, existing methods either extract the sentence-level features coupling all words or focus more on object names, which would lose the word-level information or neglect other attributes. To alleviate these issues, we present EDA that Explicitly Decouples the textual attributes in a sentence and conducts Dense Alignment between such fine-grained language and point cloud objects. Specifically, we first propose a text decoupling module to produce textual features for every semantic component. Then, we design two losses to supervise the dense matching between two modalities: position alignment loss and semantic alignment loss. On top of that, we further introduce a new visual grounding task, locating objects without object names, which can thoroughly evaluate the model's dense alignment capacity. Through experiments, we achieve state-of-the-art performance on two widely-adopted 3D visual grounding datasets, ScanRefer and SR3D/NR3D, and obtain absolute leadership on our newly-proposed task. The source code will be available at https://github.com/yanmin-wu/EDA.Comment: 16 pages with 5 pages of supplementary materia

Implicit Neural Representation for Cooperative Low-light Image Enhancement

The following three factors restrict the application of existing low-light image enhancement methods: unpredictable brightness degradation and noise, inherent gap between metric-favorable and visual-friendly versions, and the limited paired training data. To address these limitations, we propose an implicit Neural Representation method for Cooperative low-light image enhancement, dubbed NeRCo. It robustly recovers perceptual-friendly results in an unsupervised manner. Concretely, NeRCo unifies the diverse degradation factors of real-world scenes with a controllable fitting function, leading to better robustness. In addition, for the output results, we introduce semantic-orientated supervision with priors from the pre-trained vision-language model. Instead of merely following reference images, it encourages results to meet subjective expectations, finding more visual-friendly solutions. Further, to ease the reliance on paired data and reduce solution space, we develop a dual-closed-loop constrained enhancement module. It is trained cooperatively with other affiliated modules in a self-supervised manner. Finally, extensive experiments demonstrate the robustness and superior effectiveness of our proposed NeRCo. Our code is available at https://github.com/Ysz2022/NeRCo

4-Amino-13-(1-naphth­yl)-[2,2]paracyclo­phane

The title compound [systematic name: 12-amino-42-(1-naphth­yl)-1,4(1,4)-dibenzenacyclo­hexa­phane], C26H23N, was synthesized from 4-amino-13-bromo-[2,2]paracyclo­phane and 1-naphthalene­boronic acid in the presence of 1,4-dioxane. It is a new cyclo­phane-derived compound which can be regarded as a prospective ligand for asymmetric synthesis and catalysis. The benzene rings of the paracyclo­phane units are very slightly deformed from planarity as shallow boats

Melatonin protects against ovarian damage by inhibiting autophagy in granulosa cells in rats

Objectives: This study sought to further verify the protective mechanism of Melatonin (MT) against ovarian damage through animal model experiments and to lay a theoretical and experimental foundation for exploring new approaches for ovarian damage treatment. Method: The wet weight and ovarian index of rat ovaries were weighted, and the morphology of ovarian tissues and the number of follicles in the pathological sections of collected ovarian tissues were recorded. And the serum sex hormone levels, the key proteins of the autophagy pathway (PI3K, AKT, mTOR, LC3II, LC3I, and Agt5) in rat ovarian tissues, as well as the viability and mortality of ovarian granulosa cells in each group were measured by ELISA, western blotting, CCK8 kit and LDH kit, respectively. Results: The results showed that MT increased ovarian weight and improved the ovarian index in ovarian damage rats. Also, MT could improve autophagy-induced ovarian tissue injury, increase the number of primordial follicles, primary follicles, and sinus follicles, and decrease the number of atretic follicles. Furthermore, MT upregulated serum AMH, INH-B, and E2 levels downregulated serum FSH and LH levels in ovarian damage rats and activated the PI3K/AKT/mTOR signaling pathway. Besides, MT inhibited autophagic apoptosis of ovarian granulosa cells and repressed the expression of key proteins in the autophagic pathway and reduced the expression levels of Agt5 and LC3II/I. Conclusions: MT inhibits granulosa cell autophagy by activating the PI3K/Akt/mTOR signaling pathway, thereby exerting a protective effect against ovarian damage

EAO-SLAM: Monocular Semi-Dense Object SLAM Based on Ensemble Data Association

Object-level data association and pose estimation play a fundamental role in semantic SLAM, which remain unsolved due to the lack of robust and accurate algorithms. In this work, we propose an ensemble data associate strategy for integrating the parametric and nonparametric statistic tests. By exploiting the nature of different statistics, our method can effectively aggregate the information of different measurements, and thus significantly improve the robustness and accuracy of data association. We then present an accurate object pose estimation framework, in which an outliers-robust centroid and scale estimation algorithm and an object pose initialization algorithm are developed to help improve the optimality of pose estimation results. Furthermore, we build a SLAM system that can generate semi-dense or lightweight object-oriented maps with a monocular camera. Extensive experiments are conducted on three publicly available datasets and a real scenario. The results show that our approach significantly outperforms state-of-the-art techniques in accuracy and robustness. The source code is available on: https://github.com/yanmin-wu/EAO-SLAM.Comment: Accepted to IROS 2020. Project Page: https://yanmin-wu.github.io/project/eaoslam/; Code: https://github.com/yanmin-wu/EAO-SLA

Measurement and interpretation of electrocardiographic QT intervals in murine hearts.

Alterations in ECG QT intervals correlate with the risk of potentially fatal arrhythmias, for which transgenic murine hearts are becoming increasingly useful experimental models. However, QT intervals are poorly defined in murine ECGs. As a consequence, several different techniques have been used to measure murine QT intervals. The present work develops a consistent measure of the murine QT interval that correlates with changes in the duration of ventricular myocyte action potentials (APs). Volume-conducted ECGs were compared with simultaneously recorded APs, obtained using floating intracellular microelectrodes in Langendorff-perfused mouse hearts. QT intervals were measured from the onset of the QRS complex. The interval, Q-APR90, measured to the time at 90% AP recovery, was compared with two measures of the QT interval. QT1 was measured to the recovery of the ECG trace to the isoelectric baseline for entirely positive T-waves or to the trough of any negative T-wave undershoot. QT2-used extensively in previous studies-was measured to the return of any ECG trough to the isoelectric baseline. QT1, but not QT2, closely correlated with changes in Q-APR90. These findings were confirmed over a range of pacing rates, in low K(+) concentration solutions, and in Scn5a+/ΔKPQ hearts used to model human long QT syndrome. Application of this method in whole anesthetized mice similarly demonstrated a prolonged corrected QT (QTc) in Scn5a+/ΔKPQ hearts. We therefore describe a robust method for the determination of QT and QTc intervals that correlate with the duration of ventricular myocyte APs in murine hearts.This is the final published version. It has been published by the American Physiological Society in the American Journal of Physiology Heart and Circulatory Physiology here: http://ajpheart.physiology.org/content/306/11/H1553

An Object SLAM Framework for Association, Mapping, and High-Level Tasks

Object SLAM is considered increasingly significant for robot high-level perception and decision-making. Existing studies fall short in terms of data association, object representation, and semantic mapping and frequently rely on additional assumptions, limiting their performance. In this paper, we present a comprehensive object SLAM framework that focuses on object-based perception and object-oriented robot tasks. First, we propose an ensemble data association approach for associating objects in complicated conditions by incorporating parametric and nonparametric statistic testing. In addition, we suggest an outlier-robust centroid and scale estimation algorithm for modeling objects based on the iForest and line alignment. Then a lightweight and object-oriented map is represented by estimated general object models. Taking into consideration the semantic invariance of objects, we convert the object map to a topological map to provide semantic descriptors to enable multi-map matching. Finally, we suggest an object-driven active exploration strategy to achieve autonomous mapping in the grasping scenario. A range of public datasets and real-world results in mapping, augmented reality, scene matching, relocalization, and robotic manipulation have been used to evaluate the proposed object SLAM framework for its efficient performance.Comment: Accepted by IEEE Transactions on Robotics(T-RO

Renal primitive neuroectodermal tumor: A rare case with a good prognosis

BackgroundRenal primitive neuroectodermal tumor (rPNET) has the characteristics of a difficult preoperative diagnosis, a high degree of malignancy, easy early metastasis or postoperative recurrence, a poor prognosis, and so on. However, rPNET that has no metastasis before surgery can have a good survival prognosis only after radical surgical resection.MethodsWe report the case of a 14-year-old male patient with a renal tumor who underwent open radical left nephrectomy without radiotherapy or chemotherapy before or after surgery, as confirmed by postoperative pathological results. The prognosis was followed up by a regular review of the chest and whole abdomen on CT, hematuria analysis, renal function, and electrolytes according to the guidelines for renal cancer.ResultsPostoperative pathological results confirmed rPNET; no adjuvant radiotherapy or chemotherapy were performed after surgery; no tumor recurrence or metastasis were observed during the follow-up of nearly 5 years.ConclusionsDespite the high degree of rPNET malignancy, patients without metastases before surgery can still obtain a good survival prognosis through timely radical surgery

RESEARCH ON DATA MANAGEMENT MODEL OF NATIONAL DEFENSE MOBILIZATION POTENTIAL BASED ON GEO-SPATIAL FRAMEWORK

At present, the national defense mobilization potential data is mainly unstructured data composed of text, images, report forms, lacking space attribute and location information. Therefore, a large study of national defense mobilization potential database has focused on data collection, reporting and information system construction, etc. To solve national defense mobilization potential data application problems in the construction of informatization, taking advantage of the characteristics of geographical spatial framework, this paper discusses national defense mobilization potential data management model based on geographical spatial framework