Global Earth’s gravity field solution with GRACE orbit and range measurements using modified short arc approach

Traditionally, the Earth’s gravity field model is computed from GRACE orbit and range rate measurements, e.g., in a short arc approach where both the position and the velocity vectors are integrated from a force model. In this contribution, we use the GRACE orbit and range measurements to recover the Earth’s gravity field model, thus we only need to integrate the position vectors. We use the range differences between two adjacent epochs to eliminate the range ambiguities. Using GRACE Level-1B RL02 data released by Jet Propulsion laboratory, the gravity field model TJGRACE02O complete to degree and order 90 is developed from 7 years of reduced dynamic orbits covering the period 2004–2010, and the gravity field model TJGRACE02K complete to degree and order 120 is computed from 1 month of kinematic orbits and K-band range data of January. Comparing the degree geoid errors of our new models with recent gravity field models such as the CHAMP-only models EIGEN-CHAMP05S, AIUB-CHAMP03S, ULUX-CHAMP2013S and the GRACE-only models GGM05S, Tongji-GRACE01 as well as a monthly model from the ITG-GRACE2010 time series, and validating these models with GPS-leveling data sets in the USA, we can conclude that the TJGRACE02O model is more accurate than all the CHAMP-only models and TJGRACE02K is comparable in quality to the corresponding GRACE monthly model from ITG-GRACE2010.Department of Land Surveying and Geo-Informatic

Survivin-based recombinant overlapping peptides induce t lymphocyte cytotoxicity and prolong the survival in in vivo melanoma model

Anti-cancer vaccination emerged as a promising and cost-effective immunotherapy, but the lack of immunogenicity has hindered the success of therapeutic vaccine development. To address this issue and improve therapeutic efficacy, this study presents the examination of recombinant overlapping peptides (ROP) based on the tumor-associated antigen, survivin, on in vivo immunogenicity and anti-tumor efficacy using a melanoma C57/BL mouse model. Results show that ROPs induce a remarkable 46.5% cytotoxic activity mediated by activated cytotoxic T lymphocytes, compared to only 3% in wild-type (WT) survivin protein. Additionally, ROPs significantly reduce tumor size by over 500 mm3 and prolong survival rates in mice with zero deaths in the first 17 days and 30% survival at the end of day 23, while no mice immunized with WT survivin protein survive beyond day 20. ROPs combined with anti-4-1BB agonists lead to additional tumor size reduction by 500 mm3 and 70% survival on day 23. These findings underscore the importance of survivin as a trigger for tumor-restricting immunity and provide therapeutic evidence of ROPs' anti-tumor potential, especially when combined with other immunostimulants, such as anti-4-1BB agonists. ROPs and adjuvant immunostimulants represent a potent vaccine strategy for therapeutic purposes, increasing vaccine immunogenicity and improving survival against cancer

Neural Circuits and Some New Factors Involved in Hippocampal Memory

Humans and other primates have memory, and the hippocampus plays a critical role in this process. The neural circuitry is one of the structural foundations for the hippocampus in exerting memory function. To understand the relationship between the hippocampus and memory, we need to understand neural circuits. Past research has identified several classical neural circuits involved in memory. Although there are challenges with the study of hippocampal neural circuits, research on this topic has continued, and some progress has been made. Here, we discuss recent advances in our understanding of hippocampal neural circuit mechanisms and some of the newly discovered factors that affect memory. Substantial progress has been made regarding hippocampal memory circuits and Alzheimer’s disease. However, it is unclear whether these novel findings regarding hippocampal memory circuits hold promise for human memory studies. Additional research on this topic is needed

Species-specific effects of microplastics on juvenile fishes

Microplastics contamination have been extensively reported in aquatic ecosystem and organisms. It is wildly acknowledged that the ingestion, accumulation and elimination of microplastics in fishes are species-specific, which mainly depending on the feeding behavior. This study aimed to investigate the effects of microplastics on the morphology and inflammatory response in intestines of fishes with different feeding types. Largemouth bass (carnivorous fish), grass carp (herbivorous fish) and Jian carp (omnivorous fish) were used as organism model. The contributing concentration and size of microplastics were explored as well as the response time and legacy effect in fishes. Two different sizes of polystyrene microplastics (80 nm and 8 μm) were set at three concentrations. And samples were analyzed at different exposure times and depuration times. Histological analysis indicated that multiple abnormalities in intestines were presented in three species fishes after acute exposure microplastics. The mRNA abundance of immune-related genes in the intestine tissues of fishes were significantly fluctuant. There were differential expressions of genes coping with differential sizes and concentrations of microplastics exposure in different fishes. The reason for the difference effects of microplastics on fishes was still unclear but could be due to the difference in the structure and function of the digestive system. These results provided a theoretical basis to further analysis of the mechanism of fish intestinal pathology caused by microplastics

Efficient refinements on YOLOv3 for real-time detection and assessment of diabetic foot Wagner grades

Currently, the screening of Wagner grades of diabetic feet (DF) still relies on professional podiatrists. However, in less-developed countries, podiatrists are scarce, which led to the majority of undiagnosed patients. In this study, we proposed the real-time detection and location method for Wagner grades of DF based on refinements on YOLOv3. We collected 2,688 data samples and implemented several methods, such as a visual coherent image mixup, label smoothing, and training scheduler revamping, based on the ablation study. The experimental results suggested that the refinements on YOLOv3 achieved an accuracy of 91.95% and the inference speed of a single picture reaches 31ms with the NVIDIA Tesla V100. To test the performance of the model on a smartphone, we deployed the refinements on YOLOv3 models on an Android 9 system smartphone. This work has the potential to lead to a paradigm shift for clinical treatment of the DF in the future, to provide an effective healthcare solution for DF tissue analysis and healing status.Comment: 11 pages with 11 figure

An optimized short-arc approach: methodology and application to develop refined time series of Tongji-Grace2018 GRACE monthly solutions

Abstract Considering the unstable inversion of ill-conditioned intermediate matrix required in each integral arc in the short-arc approach presented in Chen et al. (2015), an optimized short-arc method via stabilizing the inversion is proposed. To account for frequency-dependent noise in observations, a noise whitening technique is implemented in the optimized short-arc approach. Our study shows the optimized short-arc method is able to stabilize the inversion and eventually prolong the arc length to 6 hours. In addition, the noise whitening method is able to mitigate the impacts of low-frequency noise in observations. Using the optimized short-arc approach, a refined time series of GRACE monthly models called Tongji-Grace2018 has been developed. The analyses allow us to derive the following conclusions: (a) during the analyses over the river basins (i.e. Amazon, Mississippi, Irrawaddy and Taz) and Greenland, the correlation coefficients of mass changes between Tongji-Grace2018 and others (i.e. CSR RL06, GFZ RL06 and JPL RL06 Mascon) are all over 92 and the corresponding amplitudes are comparable; (b) the signals of Tongji-Grace2018 agree well with those of CSR RL06, GFZ RL06, ITSG-Grace2018 and JPL RL06 Mascon, while Tongji-Grace2018 and ITSG-Grace2018 are less noisy than CSR RL06 and GFZ RL06; (c) clearer global mass change trend and less striping noise over oceans can be observed in Tongji-Grace2018 even only using decorrelation filtering; and (d) for the tests over Sahara, over 36 and 19 of noise reductions are achieved by Tongji-Grace2018 relative to CSR RL06 in the cases of using decorrelation filtering and combined filtering, respectively

Computer-Aided Diagnosis Evaluation of the Correlation Between Magnetic Resonance Imaging With Molecular Subtypes in Breast Cancer

BackgroundThere is a demand for additional alternative methods that can allow the differentiation of the breast tumor into molecular subtypes precisely and conveniently.PurposeThe present study aimed to determine suitable optimal classifiers and investigate the general applicability of computer-aided diagnosis (CAD) to associate between the breast cancer molecular subtype and the extracted MR imaging features.MethodsWe analyzed a total of 264 patients (mean age: 47.9 ± 9.7 years; range: 19–81 years) with 264 masses (mean size: 28.6 ± 15.86 mm; range: 5–91 mm) using a Unet model and Gradient Tree Boosting for segmentation and classification.ResultsThe tumors were segmented clearly by the Unet model automatically. All the extracted features which including the shape features,the texture features of the tumors and the clinical features were input into the classifiers for classification, and the results showed that the GTB classifier is superior to other classifiers, which achieved F1-Score 0.72, AUC 0.81 and score 0.71. Analyzed the different features combinations, we founded that the texture features associated with the clinical features are the optimal features to different the breast cancer subtypes.ConclusionCAD is feasible to differentiate the breast cancer subtypes, automatical segmentation were feasible by Unet model and the extracted texture features from breast MR imaging with the clinical features can be used to help differentiating the molecular subtype. Moreover, in the clinical features, BPE and age characteristics have the best potential for subtype

How Workplace Social Capital Affects Turnover Intention: The Mediating Role of Job Satisfaction and Burnout

Committed social workers are significant to organizational performance and service quality; therefore, it is crucial to explore the contributing factors of turnover intention to enhance social workers’ commitment. To reduce social workers’ turnover intention, this study used the first national survey data (N = 5620) of social workers in China to find out the relationship between workplace social capital and turnover intention in public service and explore possible solutions. This study treated workplace social capital as a comprehensive measure that captured employees’ overall perceptions of their interpersonal relations in the public sector. It covered the impact of many other organizational factors on turnover intention, such as job embeddedness, social networks, social relations, communication, and organizational fairness. The results confirmed that workplace social capital had a significant negative impact on employees’ turnover intention. Workplace social capital could be a better predictor of employees’ turnover intention than a single organizational factor or a combination of several factors. These findings not only deepened the theoretical understanding of social capital within the organization and brought insight into how workplace social capital affected employees’ turnover but also promoted a formation of a holistic organizational perspective from the fragmented organizational factors. Results also showed that job burnout and job satisfaction mediated the relation between workplace social capital and turnover intention. Public service agencies should endeavor to foster an organizational climate of cooperation and trust, encourage teamwork and altruistic behaviors among coworkers to reduce emotional exhaustion, and strengthen the professional identity and professional value of social work

A Theoretical Study of Phase Equilibria of Pt Doped Calcium Titanate

Previous Experiments reported that precious-metal Pt is able to migrate between perovskite CaTiO_3 surface and bulk with change of the external redox conditions. This novel process can efficiently suppress the agglomeration of precious-metal particles, and maintain the high performance of the so-called " intelligent catalysts" for a long period. However, the study of the interactions between precious-metal and CaTiO_3 substrate is rather limited. The first-principles calculations combined with cluster expansion and Monte Carlo methods were employed to construct the PtO_x-CaO-TiO_x pseudo-ternary phase diagrams to explore the properties of Pt-doped CaTiO_3system. The first-principles phase diagrams show that Pt can be doped in CaTiO_3 and occupy the Ti-site at various concentrations, and the thermodynamic phase diagrams indicate that the doped CaTi, -xPtxO_3 structures evolve to solid solutions at ambient temperatures. More importantly, Pt tends to dissolve into CaTiO_3substrate under oxidizing conditions while precipitating from the perovskite matrix and exist as metallic particles under reducing conditions,which is consistent with the concept of intelligent catalyst". Furthermore,the investigations of the phase diagram indicate the existence of some other oxides and metal alloys in the catalyst system at various conditions. The results might inform the experiments and be helpful for preparing highly efficient catalysts for elimination of harmful exhaust gas

Does a Distributed Practice Strategy for Multiple Choice Questions Help Novices Learn Programming?

Learning how to program is becoming essential in many disciplines. However, programming cannot be easily learned, especially by non-engineering students. It is challenging to conduct engineering education for non-engineering majored students. Therefore, it is important to teach non-engineering students to learn with efficient learning strategies. To discover an efficient learning strategy, we had 64 students practice programming with a simple learning management system and tracked all of their practice behaviors on multiple choice questions. The learning management system assigned one multiple choice question per day, but let students themselves decide their own practice frequencies. Students could also make unsynchronized communications by commenting on the questions. By analyzing their behavior patterns and other performance indicators, this paper compared the effect of two different practice strategies for multiple choice questions: distributed practice and massed practice. Our analysis found that students who adopted distributed practice significantly outperformed those who adopted massed practice on final exams (p=0.031). We further explored the possible reasons that led to this significant difference. Students who adopted distributed practice strategy tended to make higher percentage of first submission correctness, be more cautious while correcting errors, and be more constructive in posting question-related comments