A Simple Model Unifies Space, Matter and Light

An alternative model is proposed to derive several of Einstein’s basic relativity equations, which would make relativity theory easier to comprehend and more intuitive. Despite the radical nature of the hypothesis, the findings are consistent with many predictions of relativity theory and shed light on the fundamental aspects of various relativity concepts. The model unifies Space, Matter, and Light, all of which are of the same nature. The building block is a mass-unit composed of size and motion. The invariant space-time interval and the corresponding space-mass interval are derived and explained. Only when there is “external force”, the Einstein’s energy-momentum equation becomes applicable. The “no external force” scenario leads to the generation of a new energy-momentum equation that explains the nature of gravity and perhaps even dark matter. Modified Minkowski space-time and space-mass diagrams clearly depict time dilation, length contraction, the mass-momentum-energy relationship, and other relativity phenomena.

高性能超韧聚乳酸共混物的研究进展

聚乳酸(PLA)具有优异的可生物降解性、生物相容性及力学强度和加工性能,被认为是最具有工业化应用前景的绿色生物基高分子材料。但聚乳酸材料性脆、结晶速率慢和耐热温度低等缺点限制了其发展与应用。近些年,通过在聚乳酸中添加功能性反应单体、与韧性高分子进行反应共混以及与弹性体、橡胶实现原位动态硫化等不同方式对聚乳酸进行改性,研制了一系列高性能超韧聚乳酸共混物。由于聚乳酸在共混过程中的原位反应增容可以大幅度地提高聚乳酸共混组分间的界面相容性,并通过有效控制聚乳酸共混物组成与形态结构,制备出性能优异的超韧聚乳酸共混物。

基于多维球体信息融合的航空发动机故障分类研究

针对航空发动机各类故障表征参数存在耦合且故障类别不易区分的问题,引入多维几何球体距离信息融合的方法,旨在解决航空发动机多故障模式分类的问题。基于发动机自适应模型生成对应的性能参数和测量参数组成故障样本,利用样本的先验状态作为类别标签。同时去掉异常故障样本,并将每一类故障数据看成是一个多维几何球体,利用带动态邻域的自适应粒子群算法确定最优的几何球体的中心以及半径,得到的球体能更好地区分不同的故障类别。同时融合多个几何球体距离的信息,克服了以往仅仅依据样本点与故障类别中心的距离进行分类的弊端。将该方法应用到某航空发动机故障分类中。结果表明,故障分类精度达到96.67%,且计算时间比其他故障分类方法短。