Pyrite-type ruthenium disulfide with tunable disorder and defects enables ultra-efficient overall water splitting

The exploration of efficient electrocatalysts for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is significant for water splitting associated with the storage of clean and renewable energy. Here, we report a simple and scalable low-temperature sulfuration method to achieve simultaneous modulation of disorder and defects in pyrite-type RuS2 nanoparticles to dramatically enhance the HER and OER catalytic activity. The disordered structure can increase the electrochemically active surface area, while defect engineering can effectively regulate the electronic structure and thus improve the intrinsic activity, as revealed by combined experimental and theoretical density functional theory (DFT) investigations. Through controllable disorder and defect engineering, the optimized RuS2-500 catalyst (with a sulfuration temperature of 500 °C) supported on a glassy carbon electrode exhibits ultra-efficient bifunctional electrocatalytic activity with η-10 = 78 mV for the HER and η10 = 282 mV for the OER, superior to various Ru-based and pyrite-type catalysts. Remarkably, when used as both the anode and the cathode in an alkaline water electrolyzer, RuS2-500 delivers 10 mA cm-2 at an ultralow cell voltage of 1.527 V with long-term stability, outperforming the benchmark Pt/C//RuO2 couple and most state-of-the-art overall-water-splitting electrocatalysts ever reported. This work thus provides a new and facile way for improving the catalytic activity through a synergistic modulation strategy

Intelligent medical case based e-learning system

Educational theory has purported the notion that student-centric modes of learning are more effective in enhancing student engagement and by extension, learning outcomes. However, the translation of this theoretical pedagogy of learning into an applied model for medical training has been fraught with difficulty due to the structural complexity of creating a classroom environment that enables students to exercise full autonomy. In this paper, we propose an intelligent computational e-learning platform for case-based learning (CBL) in Medicine that enriches and enhances the learning experiences of medical students by exposing them to simulated real-world clinical contexts. We argue that computational systems in Medicine should not merely provide a passive outlay of information, but instead promote active engagement through an immersive learning experience. This is achieved through a digital platform that renders a virtual patient simulation, which allows students to assess, diagnose, treat and test patients as they would in the real-world

Positioning variation modeling for aircraft panels assembly based on elastic deformation theory

Dimensional variation in aircraft panel assembly is one of the most critical issues that affects the aerodynamic performance of aircraft, due to elastic deformation of parts during the positioning and clamping process. This paper proposes an assembly deformation prediction model and a variation propagation model to predict the assembly variation of aircraft panels, and derives consecutive 3-D deformation expressions which explicitly describe the nonlinear behavior of physical interaction occurring in compliant components assembly. An assembly deformation prediction model is derived from equations of statics of elastic beam to calculate the elastic deformation of panel component resulted from positioning error and clamping force. A variation propagation model is used to describe the relationship between local variations and overall assembly variations. Assembly variations of aircraft panels due to positioning error are obtained by solving differential equations of statics and operating spatial transformations of the coordinate. The calculated results show a good prediction of variation in the experiment. The proposed method provides a better understanding of the panel assembly process and creates an analytical foundation for further work on variation control and tolerance optimization

On the stability of high-speed milling with spindle speed variation

Spindle speed variation is a well-known technique to suppress regenerative machine tool vibrations, but it is usually considered to be effective only for low spindle speeds. In this paper, the effect of spindle speed variation is analyzed in the high-speed domain for spindle speeds corresponding to the first flip (period doubling) and to the first Hopf lobes. The optimal amplitudes and frequencies of the speed modulations are computed using the semidiscre- tization method. It is shown that period doubling chatter can effectively be suppressed by spindle speed variation, although, the technique is not effective for the quasiperiodic chatter above the Hopf lobe. The results are verified by cutting tests. Some special cases are also discussed where the practical behavior of the system differs from the predicted one in some ways. For these cases, it is pointed out that the concept of stability is understood on the scale of the principal period of the system—that is, the speed modulation period for variable spindle speed machining and the tooth passing period for constant spindle speed machining

Mitochondrial DNA Copy Number Is Associated with Breast Cancer Risk

Mitochondrial DNA (mtDNA) copy number in peripheral blood is associated with increased risk of several cancers. However, data from prospective studies on mtDNA copy number and breast cancer risk are lacking. We evaluated the association between mtDNA copy number in peripheral blood and breast cancer risk in a nested case-control study of 183 breast cancer cases with pre-diagnostic blood samples and 529 individually matched controls among participants of the Singapore Chinese Health Study. The mtDNA copy number was measured using real time PCR. Conditional logistic regression analyses showed that there was an overall positive association between mtDNA copy number and breast cancer risk (Ptrend = 0.01). The elevated risk for higher mtDNA copy numbers was primarily seen for women with <3 years between blood draw and cancer diagnosis; ORs (95% CIs) for 2nd, 3rd, 4th, and 5th quintile of mtDNA copy number were 1.52 (0.61, 3.82), 2.52 (1.03, 6.12), 3.12 (1.31, 7.43), and 3.06 (1.25, 7.47), respectively, compared with the 1st quintile (Ptrend = 0.004). There was no association between mtDNA copy number and breast cancer risk among women who donated a blood sample ≥3 years before breast cancer diagnosis (Ptrend = 0.41). This study supports a prospective association between increased mtDNA copy number and breast cancer risk that is dependent on the time interval between blood collection and breast cancer diagnosis. Future studies are warranted to confirm these findings and to elucidate the biological role of mtDNA copy number in breast cancer risk. © 2013 Thyagarajan et al