The Influence of Carbon Nitride Nanosheets Doping on the Crystalline Formation of MIL‐88B(Fe) and the Photocatalytic Activities

In this research, bulk graphitic carbon nitride (g‐C₃N₄) is exfoliated and transferred to the carbon nitride nanosheets (CNNSs), which are then coupled with MIL‐88B(Fe) to form the hybrid. From the results of the powder X‐ray diffraction, scanning electronic microscopy and thermogravimetric analysis, it is found that the doping of CNNSs on the surface of MIL‐88(Fe) could maintain the basic structure of MIL‐88B(Fe), and the smaller dimension of CNNSs might influence the crystallization process of metal‐organic frameworks (MOFs) compared to bulk g‐C₃N₄. Besides, the effects of the CNNSs incorporation on photocatalysis are also investigated. Through the photoluminescence spectra, electrochemical measurements, and photocatalytic experiments, the hybrid containing 6% CNNSs is certified to possess the highest catalytic activity to degrade methylene blue and reduce Cr(VI) under visible light. The improvement of the photocatalytic performance can be attributed to the matched energy level which favors the formation of the heterojunctions. Besides, it promotes the charge migration such that the contact between MOFs and CNNSs is more intimate, which can be inferred from the electronic microscopy images. Finally, a possible photocatalytic mechanism is put forward by the relative calculation and the employment of the scavengers to trap the active species.     

Highly uniform ultrasound-sensitive nanospheres produced by a pH-induced micelle-to-vesicle transition for tumor-targeted drug delivery

Although gas-filled microbubbles with high echogenicity are widely applied inclinical ultrasonography, the micron scale particle size impedes their use in the treatment of solid tumors,which are accessible to objects less than several hundred nanometers. We herein propose an unusual approach involving apH-induced core–shell micelle-to-vesicle transition to prepare ultrasound-sensitive polymeric nanospheres (polymersomes in structure) possessing multiple features, including nanosize, monodispersity, and incorporation of a phase-transitional imaging agent into the aqueous lumen. These features are not achievable via the conventional double-emulsion method for polymersome preparation. The nanospheres were constructed based on a novel triblock copolymer with dual pH sensitivity. The liquid-to-gas phase transition of the imaging agent induced by external low-frequency ultrasound may destroy the nanospheres for a rapid drug release, with simultaneous tissue-penetrating drug delivery inside a tumor. These effects may provide new opportunities for the development of an effective cancer therapy with few adverse effects.

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Recent advances in controlled modification of the size and morphology of metal-organic frameworks

Advances in metal-organic frameworks (MOFs) resulted in significant contributions to diverse applications such as carbon capture, gas storage, heat transformation and separation along with emerging applications toward catalysis, medical imaging, drug delivery, and sensing. The unique in situ and ex situ structural features of MOFs can be tailored by conceptual selection of the organic (e.g., ligand) and inorganic (e.g., metal) components. Here, we provide a comprehensive review on the synthesis and characterization of MOFs, particularly with respect to controlling their size and morphology. A better understanding of the specific size and morphological parameters of MOFs will help initiate a new era for their real-world applications. Most importantly, this assessment will help develop novel synthesis methods for MOFs and their hybrid/porous materials counterparts with considerably improved properties in targeted applications.

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基于数字兆欧表自动切换档位的研究与实现

随着电力、电气设备的日益复杂化,对于其安全性能也有了更高的要求,数字兆欧表作为测量绝缘阻值的重要工具,已在工业领域中广泛应用;为了满足测量精度以及兆欧表的可靠性,通过基于S3C2440的嵌入式平台,提出了一种基于数字兆欧表的自动切换档位的实现方案,以达到更加精确的测量;此方案通过判断采集到的电压值选择相应的采样电阻来实现,并结合硬件平台和软件设计,分别介绍了驱动程序和应用程序的编写与测试,并很好地应用到了实际电路中;经测试,能够达到预期的效果,测量精度高,测量误差控制在±2%。     

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

Room-Temperature Magnetic Skyrmions and Large Topological Hall Effect in Chromium Telluride Engineered by Self-Intercalation

Room-temperature magnetic skyrmion materials exhibiting robust topological Hall effect (THE) are crucial for novel nano-spintronic devices. However, such skyrmion-hosting materials are rare in nature. In this study, a self-intercalated transition metal dichalcogenide Cr_1+xTe₂ with a layered crystal structure that hosts room-temperature skyrmions and exhibits large THE is reported. By tuning the self-intercalate concentration, a monotonic control of Curie temperature from 169 to 333 K and a magnetic anisotropy transition from out-of-plane to the in-plane configuration are achieved. Based on the intercalation engineering, room-temperature skyrmions are successfully created in Cr_1.53Te₂ with a Curie temperature of 295 K and a relatively weak perpendicular magnetic anisotropy. Remarkably, a skyrmion-induced topological Hall resistivity as large as ≈106 nΩ cm is observed at 290 K. Moreover, a sign reversal of THE is also found at low temperatures, which can be ascribed to other topological spin textures having an opposite topological charge to that of the skyrmions. Therefore, chromium telluride can be a new paradigm of the skyrmion material family with promising prospects for future device applications.     

基于人工神经网络预测柴油机油台架试验结果

根据ＣＤ级柴油机的模拟实验与台架试验的基础数据,用人工神经网络的反向传播（ＢＰ）方法,对两者的关系进行了研究,给出了人工神经网络的学习速率为０．２,动量因子为０．９,对人工神经网络的拓扑结构也进行了研究,得到了合适的５－７－２拓扑结构及各节点间的权重系数。探讨了用模拟实验数据预测台架试验结果的可能性,通过检验,证明了用人工神经网络方法建立的模型能准确预报柴油机油的台架试验结果。     

动态优化调度走向实用的策略与段落全局优化

本文在总结动态优化调度在实际系统中应用经验的基础上,提出了动态优化调度走向实用的策略及以段落一局优化算动态化调度的方法,该策略可以较地贯彻电力系统运行“安全,优质,经济”的原则,段落全局优化方法则可以一次性处理各种负荷紧段落,包括单调升降段落及以往方法只有通过反向导引才能够处理的陡升连续等类的段落,具有计算时间短,节省内存等特点,为动态优化调度在电力系统中的进一步实用化打下了坚实的基础。     

An efficient microfluidic sorter: implementation of double meandering micro striplines for magnetic particles switching

The ability to trap, manipulate, and separate magnetic beads has become one of the key requirements in realizing an integrated magnetic lab-on-chip biosensing system. In this article, we present the design and fabrication of an integrated magneto-fluidic device for sorting magnetic particles with a sorting efficiency of up to 95%. The actuation and manipulation of magnetic beads are realized using microfabricated square meandering current-carrying micro striplines. The current is alternated between two neighboring micro striplines to switch the magnetic beads to either one of the two outlets. We performed a series of parametric study to investigate the effect of applied current, flow rate, and switching frequency on the sorting efficiency. Experimental results reveal that the sorting efficiency is proportional to the square of current applied to the stripline, and decreases with increasing buffer flow rate and switching frequency. Such phenomena agree well with our theoretical analysis and simulation result. The fastest switching rate, which is limited by the microchannel geometry and bead velocity, is 2 Hz.     

Localization of an unmanned ground vehicle based on hybrid 3D registration of 360 degree range data and DSM

A computer vision technique to identify the location of an outdoor unmanned ground vehicle (UGV) is presented. The proposed technique is based on hybrid 3D registration of 360 degree laser range data to a digital surface model (DSM). Range frames obtained from 48 laser detectors are aligned with the reference coordinate system of the DSM. Three novel approaches are proposed for accurate and fast 3D registration of range data and the DSM. First, a two-step hybrid 3D registration technique is proposed. A pair-wise registration step of two consecutive range frames is followed by a refinement step using a layered DSM. Second, a fast projection-based pair-wise registration is proposed by employing rasterized 360 degree range frames. Third, a high elevation DSM is divided into several elevation layers and correspondence search is done near the vehicle’s current elevation. This reduces the number of matching outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. Error analysis on five outdoor paths is presented with respect to ground truth.