The synthesis of a sustainable material through carbon nitride (C3N4) chemically grafted on waste-derived carbon including carbonizing coals (PM), melamine-urea-formaldehyde resins (MUF-C-1100), and luffa cylindrical sponges (SG), respectively, and its application as sulfur cathode in lithium-sulfur (Li-S) batteries were demonstrated.  https://www.selleckchem.com/products/pembrolizumab.html  The Li-S cell assembled by the sulfur (S) cathode with component from C3N4grafted coal-derived carbon (PM-CN) possesses a specific capacity of 1269.8 mA h g-1at 0.05 C. At 1 C, the initial specific capacity of PM cathode is only 380.0 mA h g-1, comparable to the PM-CN5 cathode of 681.9 mA h g-1, and PM-CN10 cathode of 580.7 mA h g-1, respectively. And, PM-CN 5 cathode presents the capacity retention of 75.9% with a coulomb efficiency (C.E.) of 97.3% after 200 cycles. The MUF-CN cathode gives a specific capacity of 1335.6 mA h g-1at 0.05 C, and the capacity retention of 66.7% with a C. E. of 93.6% after 300 cycles at 0.5 C. The SG-CN cathode had a specific capacity of 953.9 mA h g-1at 0.05 C, and capacity retention of 95.1% with a C. E. of 98.2% after 125 cycles at 1 C. The remarkable improved performances were mainly ascribed to the sustainable materials as S host with micro-meso pore and C3N4structure providing the strong affinity N sites to lithium polysulfides (LiPSs). This work provides an attractive approach for the preparation of sustainable materials by rational design of grafting C3N4to waste-derived carbons with functions as S cathode materials for high-performance Li-S batteries.The Most Likely Path formalism (MLP) is widely established as the most statistically precise method for proton path reconstruction in proton computed tomography (pCT). However, while this method accounts for small-angle Multiple Coulomb Scattering (MCS) and energy loss, inelastic nuclear interactions play an influential role in a significant number of proton paths. By applying cuts based on energy and direction, tracks influenced by nuclear interactions are largely discarded from the MLP analysis. In this work we propose a new method to estimate the proton paths based on a Deep Neural Network (DNN). Through this approach, estimates of proton paths equivalent to MLP predictions have been achieved in the case where only MCS occurs, together with an increased accuracy when nuclear interactions are present. Moreover, our tests indicate that the DNN algorithm can be considerably faster than the MLP algorithm.Objective.For patients with disorders of consciousness (DOC), such as vegetative state (VS) and minimally conscious state (MCS), communication is challenging. Currently, the communication methods of DOC patients are limited to behavioral responses. However, DOC patients cannot provide sufficient behavioral responses due to motor impairments and limited attention. In this study, we proposed a hybrid asynchronous brain-computer interface (BCI) system that provides a new communication channel for DOC patients.Approach.Seven DOC patients (3 VS and 4 MCS) and eleven healthy subjects participated in our experiment. Each subject was instructed to focus on the square with the Chinese words 'Yes' and 'No'. Then, the BCI system determined the target square with both P300 and steady-state visual evoked potential (SSVEP) detections. For the healthy group, we tested the performance of the hybrid system and the single-modality BCI system.Main results.All healthy subjects achieved significant accuracy (range from 72% to 100%) in both the hybrid system and the single-modality system. The hybrid asynchronous BCI system outperformed the P300-only and SSVEP-only systems. Furthermore, we employed the asynchronous approach to dynamically collect the EEG signals. Compared with the synchronous system, there was a 21% reduction in the average required rounds and a reduction of 105 s in the online experiment time. This asynchronous system was applied to detect the 'yes/no' communication function of seven DOC patients, and the results showed that three of the patients (3 MCS) showed significant accuracies (67 ± 3%) in the online experiment, and their Coma Recovery Scale-Revised (CRS-R) scores were also improved compared with the scores before the experiment. This result demonstrated that 3 of 7 patients were able to communicate using our hybrid asynchronous BCI system.Significance.This hybrid asynchronous BCI system represents a useful auxiliary bedside tool for simple communication with DOC patients.Different from conventional insulating or semiconducting boron nitride,metallicBN has received increasing attention in recent years as its intrinsic metallicity grants it great potential for broad applications. In this study, by assembling the experimentally synthesized pentagonal B2N3units, we have proposed the first pentagon-based three-dimensional (3D) metallic boron nitride, labeled penta-B4N7.First-principles calculations together with molecular dynamics simulations and convex hull diagram show that penta-B4N7is not only thermally, dynamically and mechanically stable, but also three dimensionally metallic. A detailed analysis of its electronic structure reveals that the intrinsic metallicity comes from the delocalized electrons in the partially occupied antibonding N-Nπorbitals. Equally important, the energy density of penta-B4N7is found to be 4.07 kJ g-1, which is the highest among that of all the 3D boron nitrides reported so far.Water pollution which is a global environmental problem has attracted great concern, and functional carbon nanomaterials are widely used in water treatment. Here, to optimize the removal performance of both the oil/organic matter and dye molecules, we fabricated a kind of porous and hydrophobic core-shell sponges by growing graphene on three-dimensional (3D) stacked copper nanowires. The interconnected pores among the 1D nanocore-shells construct the porous channels within the sponge, and the multilayered graphene shells equip the sponge with a water contact angle over 120oeven under acidic and alkaline environments, which enables fast and efficient cleanup of oil on or under the water. The core-shell sponge could absorb oil or organic solvents with different densities 40 to 90 times to its own weight, and its oil-sorption capacity is much larger than the other porous materials like activated carbon and loofah. On the other side, the adsorption behaviour of the core-shell sponge to dyes, another common water pollutant, was also measured including methyl orange (MO), malachite green (MG) and so on.