信息技术对抑郁症心理调适的模式开发创新研究——基于VR沉浸技术的应用

随着科技的不断发展,虚拟现实技术(以下简称VR技术)也在不断的创新,VR技术在当今社会被广泛推崇,多个重要领域都发现了它的重要性,它在未来的发展趋势势必也会只增不减,现已逐渐将此技术应用到医学方面,该文通过高频发生的抑郁心理问题现状,结合SWOT分析方法,通过研究VR技术与抑郁症心理调适交叉结合的创新模式,推动VR技术在异常心理调适与数字化模式上的探索.     

Study on the Ballistic Performance of Multiply Wadded Through-the-thickness Angle-interlock Fabric Reinforced Composites

Applied Composite Materials - The paper presents a study on the ballistic performance of 3D woven wadded through-the-thickness angle-interlock fabrics (TTAI) fabric reinforced composites. Their...     

Influence of selenium growth condition on the photovoltaic conversion efficiency of Sb2Se3 as the solar cell absorption layer

Journal of Materials Science: Materials in Electronics - The influences of the selenium (Se) growth condition on the electronic level structure including deep defects and further on the...     

Characteristic tryptic peptides and gelling properties of porcine skin gelatin affected by thermal action

Thermal action in extraction process had effects on characteristic tryptic peptides identification and gelling properties of porcine gelatin. SDS-PAGE, HPLC-LTQ/Orbitrap high-resolution mass spectrometry, texture analyser and rheometer were used to evaluate collagen depolymerisation degree, characteristic tryptic peptides and gelling properties of gelatins prepared in various thermal actions. Results showed that with increasing temperature and time, depolymerisation degree enlarged, while gel strength, gelling and melting temperature decreased. Mass spectra showed that 47 and 49 common characteristic tryptic peptides were identified in gelatins extracted at 50 °C and 100 °C with various times, respectively. Moreover, 34 common characteristic tryptic peptides were identified in all gelatin samples. Further comparison between this work and our previous investigations yielded 20 common characteristic tryptic peptides, which stably exist in various thermal actions. These common characteristic tryptic peptides may be very helpful for the accurate authentication of porcine gelatin.     

A high-throughput chaotic advection microreactor for preparation of uniform and aggregated barium sulfate nanoparticles

A high-throughput (105.5 g/h) passive four-stage asymmetric oscillating feedback microreactor using chaotic mixing mechanism was developed to prepare aggregated Barium sulfate (BaSO₄) particles of high primary nanoparticle size uniformity. Three-dimensional unsteady simulations showed that chaotic mixing could be induced by three unique secondary flows (i.e., vortex, recirculation, and oscillation), and the fluid oscillation mechanism was examined in detail. Simulations and Villermaux–Dushman experiments indicate that almost complete mixing down to molecular level can be achieved and the prepared BaSO₄ nanoparticles were with narrow primary particle size distribution (PSD) having geometric standard deviation, σ_g, less than 1.43 when the total volumetric flow rate Q_total was larger than 10 ml/min. By selecting Q_total and reactant concentrations, average primary particle size can be controlled from 23 to 109 nm as determined by microscopy. An average size of 26 nm with narrow primary PSD (σ_g = 1.22) could be achieved at Q_total of 160 ml/min.     

纯净美妆产品的设计理念

以消费者、行业专家、各品牌商以及全球各个美妆相关行业对纯净美妆的认识为依据,从配方设计、关键的原料筛选、生产过程、包材选择以及测试评估等方面,对如何实现纯净美妆产品进行了较为详细的阐述,无疑为纯净美妆的标准建立和定义提供很好的参考.     

Spatial–Temporal Fusion Based Path Planning for Source Seeking in Wireless Sensor Network

International Journal of Wireless Information Networks - Source seeking problem has been faced in many fields, especially in search and rescue applications. We proposed a virtual structure-based...     

个性化学习路径推荐综述

近年来，伴随着现代信息技术的迅猛发展，以人工智能为代表的新兴技术在教育领域得到了广泛应用，引发了学习理念和方式的深刻变革.在这种大背景下，在线学习超越了时空的限制，为学习者“随时随地”学习提供了更多的可能性，从而得到了蓬勃发展.然而，在线学习中师生时间、空间分离的特征，导致教师无法及时掌握学生的学习状态，一定程度上制约了在线学习中教学质量的提升.面对多元化的学习需求及海量学习资源，如何迅速完成学习目标、降低学习成本、合理分配学习资源等问题成为限制个人和时代发展的重大问题.然而，传统的“一刀切”的教育模式已经不能满足人们获取知识的需求了，需要一个更高效、更科学的个性化教育模式，以帮助学习者以最小的学习成本最大限度地完成学习目标.基于以上背景，如何自动高效识别学习者特征，高效地组织和分配学习资源，为每一位学习者规划个性化路径，成为面向个体的精准化教育资源匹配机制研究中亟待解决的问题.系统地综述并分析了当前个性化学习路径推荐的研究现状，并从多学科领域的角度分析了对于同一问题的不同研究思路，同时也归纳总结了当前研究中最为主流的核心推荐算法.最后，强调当前研究存在的主要不足之处.