Schemes for Probabilistic Teleportation of an Unknown Three-Particle Three-Level Entangled State

In this paper, two schemes for teleporting an unknown three-particle three-level entangled state are proposed. In the first scheme, two partial three-particle three-level entangled states are used as the quantum channels, while in the second scheme, three two-particle three-level non-maximally entangled states are employed as quantum channels. It is shown that the teleportation can be successfully realized with certain probability, for both two schemes, if a receiver adopts some appropriate unitary transformations. It is shown also that the successful probabilities of these two schemes are different.     

High-performance potassium poly(heptazine imide) films for photoelectrochemical water splitting

Photoelectrochemical (PEC) water splitting is an appealing approach by which to convert solar energy into hydrogen fuel. Polymeric semiconductors have recently attracted intense interest of many scientists for PEC water splitting. The crystallinity of polymer films is regarded as the main factor that determines the conversion efficiency. Herein, potassium poly(heptazine) imide (K-PHI) films with improved crystallinity were in situ prepared on a conductive substrate as a photoanode for solar-driven water splitting. A remarkable photocurrent density of ca. 0.80 mA cm⁻² was achieved under air mass 1.5 global illumination without the use of any sacrificial agent, a performance that is ca. 20 times higher than that of the photoanode in an amorphous state, and higher than those of other related polymeric photoanodes. The boosted performance can be attributed to improved charge transfer, which has been investigated using steady state and operando approaches. This work elucidates the pivotal importance of the crystallinity of conjugated polymer semiconductors for PEC water splitting and other advanced photocatalytic applications.

Potassium poly(heptazine imide) photoanode is synthesized, and owing to the improved crystallinity, it has presented a remarkable performance for solar-driven water splitting.     

Rapid Identification for the Pterocarpus Bracelet by Three-Step Infrared Spectrum Method

In order to explore a rapid identification method for the anti-counterfeit of commercial high value collections, a three-step infrared spectrum method was used for the pterocarpus collection identification to confirm whether a commercial pterocarpus bracelet (PB) was made from the precious species of Pterocarpus santalinus (P. santalinus). In the first step, undertaken by Fourier transform infrared spectroscopy (FTIR) spectrum, the absorption peaks intensity of PB was slightly higher than that of P. santalinus only at 1594 cm⁻¹, 1205 cm⁻¹, 1155 cm⁻¹ and 836 cm⁻¹. In the next step of second derivative IR spectra (SDIR), the FTIR features of the tested samples were further amplified, and the peaks at 1600 cm⁻¹, 1171 cm⁻¹ and 1152 cm⁻¹ become clearly defined in PB. Finally, by means of two-dimensional correlation infrared (2DIR) spectrum, it revealed that the response of holocellulose to thermal perturbation was stronger in P. santalinus than that in PB mainly at 977 cm⁻¹, 1008 cm⁻¹, 1100 cm⁻¹, 1057 cm⁻¹, 1190 cm⁻¹ and 1214 cm⁻¹, while the aromatic functional groups of PB were much more sensitive to the thermal perturbation than those of P. santalinus mainly at 1456 cm⁻¹, 1467 cm⁻¹, 1518 cm⁻¹, 1558 cm⁻¹, 1576 cm⁻¹ and 1605 cm⁻¹. In addition, fluorescence microscopy was used to verify the effectiveness of the above method for wood identification and the results showed good consistency. This study demonstrated that the three-step IR method could provide a rapid and effective way for the anti-counterfeit of pterocarpus collections.     

EGFAFS: A Novel Feature Selection Algorithm Based on Explosion Gravitation Field Algorithm

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As a result, they are not suitable to be processed by simple methods, such as the filter-based method. In this study, we propose a novel feature selection algorithm based on the Explosion Gravitation Field Algorithm, called EGFAFS. To reduce the dimensions of the feature space to acceptable dimensions, we constructed a recommended feature pool by a series of Random Forests based on the Gini index. Furthermore, by paying more attention to the features in the recommended feature pool, we can find the best subset more efficiently. To verify the performance of EGFAFS for FS, we tested EGFAFS on eight gene expression datasets compared with four heuristic-based FS methods (GA, PSO, SA, and DE) and four other FS methods (Boruta, HSICLasso, DNN-FS, and EGSG). The results show that EGFAFS has better performance for FS on gene expression data in terms of evaluation metrics, having more than the other eight FS algorithms. The genes selected by EGFAGS play an essential role in the differential co-expression network and some biological functions further demonstrate the success of EGFAFS for solving FS problems on gene expression data.     

Preparation of Silica Aerogel/Resin Composites and Their Application in Dental Restorative Materials

As the most advanced aerogel material, silica aerogel has had transformative industrial impacts. However, the use of silica aerogel is currently limited to the field of thermal insulation materials, so it is urgent to expand its application into other fields. In this work, silica aerogel/resin composites were successfully prepared by combining silica aerogel with a resin matrix for dental restoration. The applications of this material in the field of dental restoration, as well as its performance, are discussed in depth. It was demonstrated that, when the ratio of the resin matrix Bis-GMA to TEGDMA was 1:1, and the content of silica aerogel with 50 μm particle size was 12.5%, the composite achieved excellent mechanical properties. The flexural strength of the silica aerogel/resin composite reached 62.9546 MPa, which was more than five times that of the pure resin. Due to the presence of the silica aerogel, the composite also demonstrated outstanding antibacterial capabilities, meeting the demand for antimicrobial properties in dental materials. This work successfully investigated the prospect of using commercially available silica aerogels in dental restorative materials; we provide an easy method for using silica aerogels as dental restorative materials, as well as a reference for their application in the field of biomedical materials.     

基于关联规则和技术功效矩阵的企业技术创新机会发现和辅助决策方法

为助力科技型创新企业准确且快速地从外部捕获创新技术机会, 提出一种企业技术机会发现和辅助决策方法. 首先, 挖掘领域内的技术热点、技术重点和有潜力的技术作为领域技术创新机会. 然后, 通过关联规则分析领域技术机会和企业已有技术之间的相关性, 进一步结合技术掌握度和新颖度, 识别更适合企业的技术创新机会. 最后, 创新性地采用Sen-BERT语言模型和K-means聚类方法构建技术功效矩阵, 辅助企业从功能需求的角度进行技术创新决策. 以电动汽车领域为例验证了该方法的可行性.     

Diode-pumped Nd:LGS intracavity-doubled green laser at 532 nm

It is reported that efficient continuous-wave (CW) green laser generation at 532 nm in a KTP crystal at type-II phase matching direction performed with a diode-pumped Nd:LGS laser. With incident pump power of 18.2 W, output power of 2.68 W at 532 nm has been obtained using a 5 mm-long KTP crystal. The optical conversion efficiency was up to 14.7%. At the output power level of 2.68 W, the output stability is better than 3.5%. The beam quality M ² values were equal to 1.33 and 1.19 in X and Y directions, respectively.     

辉光等离子体辅助化学气相沉积低温合成金刚石薄膜的研究

采用辉光放电等离子体增强化学气相沉积 (GP CVD)技术在低温条件下合成了高品质的亚微米金刚石薄膜 ,并通过对合成过程的实时发射光谱诊断确定了 [CH4 H2 ]系统参与金刚石合成反应的主要荷能粒子。对合成过程的研究表明 :采用这种技术能使电子增强热丝化学气相沉积 (EACVD)合成高品质金刚石薄膜的温度从 85 0℃降至 (340± 5 )℃ ;薄膜低温合成中的主要荷能粒子为CH3 、CH ,CH+ 、H 等 ,其中过饱和原子氢保证了高品质金刚石薄膜的合成 ;根据光诊断和探针测量的结果推断近表面辉光放电可在基片表面形成电偶极层 ,该偶极层是进行超常态反应的必要环境 ,并在低温合成中起重要作用     

消荧光现象与表面谐波产生

消荧光现象是激光与物质表面非线性相互作用的结果，这是一种普遍现象。在表面谐波产生的研究中，它常常被忽略。大量研究表明：表面谐波产生与消荧光现象，有着密切的内在联系。本文以消荧光观点详细讨论了表面谐波产生的机制，提出了表面谐波产生的消荧光模型。新机制可归纳为：（ａ）多光子受激吸收产生消荧光光斑，（ｂ）激光热效应等促进自发辐射转向准受激辐射，（ｃ）伴随荧光消失，部分产生荧光的激光能量转换为产生表面谐波