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"Xu, Xiao-Chu"
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ذات الرداء الأحمر، التي تشعر دائما بالفضول تجاه العالم، تريد زيارة جدتها عبر الغابة بمفردها. لكنها لا تستطيع رؤية طريقها، ما هي الصعوبات التي ستواجهها ؟ كيف يمكنها مواجهة الذئب الكبير بمفردها في الغابة ؟ في طريقها، تلتقي بأرنب وقنفذ وظربان. تتعلم استخدام مشاعرها لإدراك العالم، وشجاعتها وحكمتها لإنقاذ نفسها من المخاطر. والمثير للدهشة أن الذئب الكبير في عينيها لطيف جدا، لم يأكل الذئب السيئ الكبير ذات الرداء الأحمر هذه المرة فحسب، بل ساعد أيضا ذو الرداء الأحمر الصغير في الوصول إلى منزل جدته.
Book
Promoting ordering degree of intermetallic fuel cell catalysts by low-melting-point metal doping
Carbon supported intermetallic compound nanoparticles with high activity and stability are promising cathodic catalysts for oxygen reduction reaction in proton-exchange-membrane fuel cells. However, the synthesis of intermetallic catalysts suffers from large diffusion barrier for atom ordering, resulting in low ordering degree and limited performance. We demonstrate a low-melting-point metal doping strategy for the synthesis of highly ordered L1
0
-type M-doped PtCo (M = Ga, Pb, Sb, Cu) intermetallic catalysts. We find that the ordering degree of the M-doped PtCo catalysts increases with the decrease of melting point of M. Theoretic studies reveal that the low-melting-point metal doping can decrease the energy barrier for atom diffusion. The prepared highly ordered Ga-doped PtCo catalyst exhibits a large mass activity of 1.07 A mg
Pt
−1
at 0.9 V in H
2
-O
2
fuel cells and a rated power density of 1.05 W cm
−2
in H
2
-air fuel cells, with a Pt loading of 0.075 mg
Pt
cm
−2
.
The development of highly ordered intermetallic catalyst for oxygen reduction reactions suffers from large diffusion barrier for atom ordering. Here, the authors use a low melting-point metal doping strategy to synthesize a series of highly ordered metal-doped platinum–cobalt alloy fuel cell catalysts.
Journal Article
Development of a nomogram to predict progression-free survival in patients with locally advanced renal cell carcinoma
The study was approved by the Peking University Third Hospital Medical Science Research Ethics Committee. [...]patients who were diagnosed with locally advanced RCC and underwent curative-intent surgery were included in our study cohort. Patient demographic and clinicopathological data were collected, including sex, age, symptoms at presentation, body mass index, medical comorbidities, surgical approach, surgical time, inter-operative blood loss, tumor side, and tumor size, and pathologic data including histologic subtype, nuclear grade, necrosis, sarcomatoid and rheumatoid differentiation, lymphovascular invasion, renal sinus invasion, perirenal fat invasion, urinary collecting system invasion, venous tumor thrombus, lymph node invasion, and adrenal invasion. [...]we established a nomogram that exhibited good discrimination and calibration when used in our study cohort. [...]the C-index of our nomogram was 0.751 to 0.783 and slightly higher than that of the other models, which suggested moderate, but not optimal, predicted accuracy of the model. [...]the potential prognostic factors of locally advanced RCC were extremely complex and could not be thoroughly revealed based on these four simple factors. [...]our nomogram was developed, and internal validation was performed based on data from a single-center cohort.
Journal Article
Controlled synthesis of silver nanoplates and nanoparticles by reducing silver nitrate with hydroxylamine hydrochloride
An easy and effective method of silver nanoplate synthesis technique was created by reducing silver nitrate （AgNO3） with hydroxylamine hydrochloride （NH2OH·HCl） at room temperature. Silver nanoplates of various shapes, including triangular, truncated triangular, hexagonal, and truncated hexagonal, exhibit an average width and thickness of approximately 1 μm and 50 nm, respectively. Silver nanoparticles were acquired by placing polyvinyl pyrrolidone （PVP） in the reaction solution. The produced silver nanoparticles are quasi-spherical in shape and - 100 nm in size. The catalytic activity in the thermal decomposition of ammonium perchlorate （AID） was distinguished by thermogravimetric （TG） analysis and differential scanning calorimetry （DSC）. The outcomes reveal that the addition of silver nanoplates and nanoparticles diminishes the low decomposition temperature of AP by 7 and 14 ℃ and leads to a drop in the high decomposition temperature of AP by 60 and 110 ℃ and a rise in the total DSC heat release by 0.86 and 1.05 kJ.g^-1, respectively.
Journal Article
Knockout of circRNAs by base editing back-splice sites of circularized exons
Many circular RNAs (circRNAs) are produced from back-splicing of exons of precursor mRNAs and are generally co-expressed with cognate linear RNAs. Methods for circRNA-specific knockout are lacking, largely due to sequence overlaps between forms. Here, we use base editors (BEs) for circRNA depletion. By targeting splice sites involved in both back-splicing and canonical splicing, BEs can repress circular and linear RNAs. Targeting sites predominantly for circRNA biogenesis, BEs could efficiently repress the production of circular but not linear RNAs. As hundreds of exons are predominantly back-spliced to produce circRNAs, this provides an efficient method to deplete circRNAs for functional study.
Journal Article
Aircraft 4D Trajectory Prediction in Civil Aviation: A Review
Aircraft four dimensional (4D, including longitude, latitude, altitude and time) trajectory prediction is a key technology for existing automation systems and the basis for future trajectory-based operations. This paper firstly summarizes the background and significance of the trajectory prediction problems and then introduces the definition and basic process of trajectory prediction, including four modules: preparation, prediction, update, and output. In addition, the trajectory prediction methods are summarized into three types: the state estimation model, the Kinetic model, and the machine learning model, and in-depth analysis of various models is carried out. Further, the relevant databases required for the study are introduced, including the aircraft performance database, aircraft monitoring database, and meteorological database. Finally, challenges and future development directions of the current trajectory prediction problem are summarized.
Journal Article
Multi-Aircraft Trajectory Collaborative Prediction Based on Social Long Short-Term Memory Network
Aircraft trajectory prediction is the basis of approach and departure sequencing, conflict detection and resolution and other air traffic management technologies. Accurate trajectory prediction can help increase the airspace capacity and ensure the safe and orderly operation of aircraft. Current research focuses on single aircraft trajectory prediction without considering the interaction between aircraft. Therefore, this paper proposes a model based on the Social Long Short-Term Memory (S-LSTM) network to realize the multi-aircraft trajectory collaborative prediction. This model establishes an LSTM network for each aircraft and a pooling layer to integrate the hidden states of the associated aircraft, which can effectively capture the interaction between them. This paper takes the aircraft trajectories in the Northern California terminal area as the experimental data. The results show that, compared with the mainstream trajectory prediction models, the S-LSTM model in this paper has smaller prediction errors, which proves the superiority of the model’s performance. Additionally, another comparative experiment is conducted on airspace scenes with aircraft interactions, and it is found that S-LSTM has a better prediction effect than LSTM, which proves the effectiveness of the former considering aircraft interaction.
Journal Article