Quadratic cone cutting surfaces for quadratic programs with on–off constraints

We study the convex hull of a set arising as a relaxation of difficult convex mixed integer quadratic programs (MIQP). We characterize the extreme points of the convex hull of the set and the extreme points of its continuous relaxation. We derive four quadratic cutting surfaces that improve the strength of the continuous relaxation. Each of the cutting surfaces is second-order-cone representable. Via a shooting experiment, we provide empirical evidence as to the importance of each inequality type in improving the relaxation. Computational results that employ the new cutting surfaces to strengthen the relaxation for MIQPs arising from portfolio optimization applications are promising.     

A complete characterization of disjunctive conic cuts for mixed integer second order cone optimization

We study the convex hull of the intersection of a disjunctive set defined by parallel hyperplanes and the feasible set of a mixed integer second order cone optimization (MISOCO) problem. We extend our prior work on disjunctive conic cuts (DCCs), which has thus far been restricted to the case in which the intersection of the hyperplanes and the feasible set is bounded. Using a similar technique, we show that one can extend our previous results to the case in which that intersection is unbounded. We provide a complete characterization in closed form of the conic inequalities required to describe the convex hull when the hyperplanes defining the disjunction are parallel.     

基于个体仿真的机场安检系统优化研究

建立了安检流程的网络流模型,模型中包含了不稳定的乘客到达情形、嫌疑乘客以及反馈机制。分析了安检过程中的瓶颈所在,并给出了相应的优化方案,包括整个安检过程的通行规则,A区和B区内部预检节点与普通节点的适当比例等。仿真结果显示,为了充分利用安检资源并兼顾预检乘客的利益,通行规则应采用连通方案。依照统计数据中计算出的各种参数,在A区预检节点和普通节点比例设置为2∶2,B区预检节点和普通节点比例设置为3∶5的情况下,旅客平均等待时间最短,等待时间的标准差也最小,同时高峰期的通行量也相对较优。进一步分析了不同的文化背景及机场情况。对于美国人和瑞士人,通过改变预检乘客的选择概率来满足他们不同的行为偏好。仿真结果说明,预检乘客选择哪类节点进行安检对平均等待时间、等待时间的标准差和高峰期通行量的影响不大。分析了插队情形,插队对平均等待时间和高峰期通行量几乎没有影响,但当插队比例非常大时,旅客等待时间标准差会增加,影响乘客到达的准确性。最后,针对具体情况提出了一些合理的建议,并给出了进一步的研究计划。     

涡旋提取-改进BCR法测定土壤中重金属的化学形态

土壤中重金属的化学形态更能表明其迁移性和生物毒性。传统的重金属化学形态检测方法BCR法由于其提取时间长,影响检测效率。采用涡旋提取对传统BCR法进行方法优化,对土壤中Cu、Zn、Pb、Cd、Ni、Cr等6种重金属元素化学形态进行了实验分析。研究了涡旋转速、涡旋时间以及涡旋提取的方法精密度与准确度。结果表明,当涡旋转速为2500rpm,酸可交换态涡旋10min,可还原态涡旋10min,可氧化态涡旋5min时,涡旋提取效果良好。采用土壤标准物质对方法的适用性进行了验证,6种元素的检出限在0.4?32μg/kg,测定值均在标准值范围内,相对标准偏差在0.3%?5.5%之间。涡旋提取-改进BCR法分析速度快,灵敏度高,能满足同时测定土壤中多种金属元素化学形态的检测要求。     

Improving the Accuracy of Small-Molecule Crystal Structures Solved from Powder X-Ray Diffraction Data by Using External Sources

Structural analysis using powder X-ray diffraction data has overcome many obstacles and nowadays is readily applicable for structural analysis of all types of compounds and materials. Being less straightforward than single crystal diffraction, it requires significant users’ input and consequently, implementation of standardized tools to assess the accuracy of crystal structures. This article discusses potential errors in crystal structure solution and refinement of small-molecule structures obtained from PXRD data. Moreover, it proposes how accuracy of these structures can be improved by using high-quality PXRD data, complementary external analytical techniques, knowledge stored in crystal structure databases, as well as an approach to search the parameter space to avoid local minima in testing different sets of geometry restraints.     

Tunable magnetophoretic method for distinguishing and separating wear debris particles in an Fe-PDMS-based microfluidic chip

Wear debris analysis provides an early warning of mechanical transmission system aging and wear fault diagnosis, which has been widely used in machine health monitoring. The ability to detect and distinguish the ferromagnetic and nonmagnetic debris in oil is becoming an effective way to assess the health status of machinery. In this work, an Fe-poly(dimethylsiloxane) (PDMS)-based magnetophoretic method for the continuous separation of ferromagnetic iron particles by diameter and the isolation of ferromagnetic particles and nonmagnetic particles with similar diameter by type is developed. The particles experience magnetophoretic effects when passing through the vicinity of the Fe-PDMS where the strongest gradient of the magnetic fields exists. By choosing a relatively short distance between the magnet and the sidewall of the horizontal main channel and the length of Fe-PDMS with controlled particles flow rate, the diameter-dependent separation of ferromagnetic iron particles, that is, smaller than 7 µm, in the range of 8–12 µm, and larger than 14 µm, and the isolation of ferromagnetic iron particles and nonmagnetic aluminum particles based on opposite magnetophoretic behaviors by types are demonstrated, providing a potential method for the detection of wear debris particles with a high sensitivity and resolution and the diagnostic of mechanical system.     

Grey relational analysis for optimization of wear parameters and surface roughness on nano composite coating

The higher wear resistance of Ni based nano composite coatings makes them potential replacement in protecting the substrate materials. The role of surface roughness of the coating along with wear parameters on the specific wear rate, pin temperature, and COF are addressed in the present study. The use of hard nano Al₂O₃ particles found significant role in increasing the resistance to wear for Ni matrix coatings on Al6061 material. The resistance to dislocation offered by these nano Al₂O₃ particles and smear out of debris with plastic deformation indicated abrasive and adhesive nature of wear mechanism in combination. The optimization of wear parameters are carried out by surface response method based grey relation analysis. The normal load applied onto the pin has significant influence on the specific wear rate and temperature rise in the pin. The surface roughness of the coating has also found instrumental in the higher pin temperature and friction coefficient.     

单颗粒光散射显微成像技术在生化医药分析中的应用

等离子体纳米颗粒(PNPs)具有体积小、易表面修饰、生物相容性好、毒性低等优点,在生物传感、生物成像、疾病诊断、肿瘤治疗、材料科学等领域得到了广泛的应用。PNPs的光散射光学性质可以通过调节其大小、组成、形貌和微环境来控制,可用于生化和药物分析。此外,由于单粒子散射显微技术具有高空间分辨率和高灵敏度,借助PNPs具有的独特局域表面等离子体共振(LSPR)特性,可在单颗粒水平进行实时成像。根据PNPs的大小、组成、形态、微环境或耦合变化引起的信号变化,研究人员发展了多种显微成像分析方法,主要分为4种,包括散射光谱的波长位移、单粒子散射强度的变化、高通量RGB分析和计数方法。基于纳米颗粒LSPR散射光谱位移变化的方法准确、灵敏,但需要昂贵的单颗粒散射光谱仪和复杂的操作。基于纳米颗粒散射强度变化的方法简单可行,但易受纳米颗粒粒径和曝光时间等因素的影响。高通量RGB分析方法灵敏度高、成本低,但不适用于颜色变化不明显的单颗粒分析,且重复性差。单粒子计数法灵敏度高,但有时粒子分布不均匀,背景杂质的干扰限制了方法的准确度。因此,这4种定量方法各有优缺点。此外,近年来逐渐发展了一些新的定量方法。例如,研究人员开发了新的时间分辨分析定量方法,并将暗场显微镜与偏振器、滤光片等光学器件相结合以消除背景干扰,以及与电化学、拉曼等仪器相结合以扩大应用范围。此外,为提高分析方法的准确度和灵敏度,暗场显微镜与深度学习、云计算、人工智能等现代计算机科学技术的结合,越来越受到人们的欢迎。基于以上原因,该文重点介绍了单粒子光散射显微镜在生化和药物分析领域的应用,总结了近年来的最新研究进展,讨论了单粒子光散射显微镜在定量分析中的几种主要定量方法,提出了未来的发展趋势,以期为相关研究领域的新人提供一定的学术参考。     

Accessing the spatiotemporal heterogeneities of single nanocatalysts by optically imaging gas nanobubbles

Catalysts that catalyze the generation of products in the gas phase, especially those involved in the hydrogen evolution reaction (HER), hold great promise for ecofriendly and sustainable energy development. In general, gas chromatography is widely used to measure catalytic activity. Unfortunately, it gives an averaged output that washes out the heterogeneities among individuals. To assess the unique catalytic properties at the single nanoparticle level, various methods based on single particle catalysis have been proposed. Over the past fifteen years, tremendous breakthroughs have been achieved, which uncovered hidden spatial and temporal heterogeneities. Although powerful, effectively quantifying the activities of single HER nanocatalysts remains challenging because of the fast diffusion of hydrogen (H₂). In 2017, a novel approach based on a nanobubble indicator was proposed to correlate the kinetics of gas bubble evolution with the catalytic activities of individual nanoentities during the HER process. Since then, a plethora of optical microscopy techniques have been utilized to monitor dynamically evolved nanobubbles and to measure the catalytic activities of single HER catalysts. In this minireview, we summarized state-of-the-art optical microscopy for in operando imaging of dynamic nanobubbles involved in gas-generating reactions while highlighting some important discoveries, including the blinking photocatalytic activity and heterogeneous distribution of active sites. Finally, challenges and future perspectives in this promising field were identified.     

Optimization of Vacuum-Microwave-Assisted Extraction of Natural Polyphenols and Flavonoids from Raw Solid Waste of the Orange Juice Producing Industry at Industrial Scale

Orange pomace (OP) is a solid waste produced in bulk as a byproduct of the orange juice industry and accounts for approximately 50% of the quantity of the fruits processed into juice. In numerous literature references there is information about diverse uses of orange pomace for the production of high-added-value products including production of natural antioxidant and antimicrobial extracts rich in polyphenols and flavonoids which can substitute the hazardous chemical antioxidants/antimicrobials used in agro-food and cosmetics sectors. In this work and for the first time, according to our knowledge, the eco-friendly aqueous vacuum microwave assisted extraction of orange pomace was investigated and optimized at real industrial scale in order to produce aqueous antioxidant/antimicrobial extracts. A Response Surface Optimization methodology with a multipoint historical data experimental design was employed to obtain the optimal values of the process parameters in order to achieve the maximum rates of extraction of OP total polyphenols and/or total flavonoids for economically optimum production at industrial scale. The three factors used for the optimization were: (a) microwave power (b) water to raw pomace ratio and (c) extraction time. Moreover, the effectiveness and statistical soundness of the derived cubic polynomial predictive models were verified by ANOVA.