Optical Levitation of a Droplet under Linear Increase of Gravitational Acceleration

Optical levitation of a liquid droplet in gas phase was investigated under timedependent change of the gravitational acceleration with specific flight pattern of an airplane. Through multiple trials under linear increase of effective gravitational acceleration, we performed the experiment of ptical trapping of a droplet from 0.3g_0 to 0.9g_0, where g_0 = 9.8 m/s^2. During such change of the effective gravitational acceleration, the trapping position on a droplet with the radius of 14 μm was found to be lowered by ca. 100 μm. The essential feature of the change of the trapping position is reproduced by a theoretical calculation under the framework of ray optics. As far as we know, the present study is the first report on optical levitation under time-dependent gravitational change

Toward the Stable Optical Trapping of a Droplet with Counter Laser Beams under Microgravity

To identify the optimum conditions for the optical trapping of a droplet under microgravity, we theoretically analyzed the efficiency of trapping with counter laser beams. We found that the distance between the two foci is an important parameter for obtaining stable trapping conditions. We also performed an optical trapping experiment with counter laser beams under microgravity. The experimental results correspond well to the theoretical prediction

Higher-continuity s-version of finite element method with B-spline functions

This paper proposes a strategy to solve the problems of the conventional s-version of finite element method (SFEM) fundamentally. Because SFEM can reasonably model an analytical domain by superimposing meshes with different spatial resolutions, it has intrinsic advantages of local high accuracy, low computation time, and simple meshing procedure. However, it has disadvantages such as accuracy of numerical integration and matrix singularity. Although several additional techniques have been proposed to mitigate these limitations, they are computationally expensive or ad-hoc, and detract from its strengths. To solve these issues, we propose a novel strategy called B-spline based SFEM. To improve the accuracy of numerical integration, we employed cubic B-spline basis functions with $C^2$-continuity across element boundaries as the global basis functions. To avoid matrix singularity, we applied different basis functions to different meshes. Specifically, we employed the Lagrange basis functions as local basis functions. The numerical results indicate that using the proposed method, numerical integration can be calculated with sufficient accuracy without any additional techniques used in conventional SFEM. Furthermore, the proposed method avoids matrix singularity and is superior to conventional methods in terms of convergence for solving linear equations. Therefore, the proposed method has the potential to reduce computation time while maintaining a comparable accuracy to conventional SFEM.Comment: 40 pages, 15 figures and 2 table

Managing protected areas in post-apartheid South Africa: A framework for integrating conservation with rural development

The South African National Parks (SANParks) initiated this study in order to provide a policy framework for integrating national parks with the development needs of local people living adjacent its national parks. However, based on the selection of case studies and the changing legal framework in the post-apartheid era, the study extended to cover all state protected areas (PAs). Indeed, the transformation of state agencies following the postapartheid election of April 1994, in part, drove the need for this integration. Given the history of land alienation during apartheid rule, the relationship between land tenure rights, various levels of ownership, and PAs formed the central hypothesis of this study. Hence, case studies with tenure arrangements ranging from weak, through intermediate, to strong ownership, were selected to test the attitudes of beneficiaries towards PAs. To set the study in its widest context, obstacles and challenges surrounding biodiversity loss, the key motive behind conservation efforts, were analysed (Chapter 1). The review concluded that governance in conservation and development initiatives (CDIs) could enhance the accountability of key role players involved, i.e., the state, private sector and local people within the context of institutions (Chapter 2). Based on the South African context, case studies were selected (Chapter 3). The results of this study demonstrated that strong ownership out- performed lesser ownership levels on short-term and medium-term benefits arising from PAs (Chapter 4). Thus, lesser ownership cannot secure biodiversity in PAs in times of pressing social needs. The study limitation is that relatively wealthy individuals of strong ownership were compared to relatively poor individuals of lesser ownership. The influence of conservation agencies on the attitudes of local people to PAs under different provincial contexts and philosophical approaches was somehow important only if it could be sustained (Chapter 5). For lesser ownership, combinations of explanatory variables acting together on medium and long-term benefits co-deterrnined the attitudes of respondents to different benefits arising from PAs (Chapter 6). Of these combinations the most important were: the conservation agency in charge, the age and the ownership of respondents for they acted across medium and long term time frames. In the post-apartheid era, the challenges to transform conservation agencies in order to achieve the developmental imperatives under the 1996 Constitution are fraught with difficulties. Using SANParks as a case study (Chapter 7), it became clear that without good leadership with well-articulated desired outcomes, technocrats could scupper transformation efforts. Given all the challenges, the new legal framework for PAs, rural development, and policy guidelines is outlined (Chapter 8), and thereafter recommendations and conclusions of the study are presented (Chapter 9)

Chemo-Sensitive Running Droplet

Chemical control of the spontaneous motion of a reactive oil droplet moving on a glass substrate under an aqueous phase is reported. Experimental results show that the self-motion of an oil droplet is confined on an acid-treated glass surface. The transient behavior of oil-droplet motion is also observed with a high-speed video camera. A mathematical model that incorporates the effect of the glass surface charge is built based on the experimental observation of oil-droplet motion. A numerical simulation of this mathematical model reproduced the essential features concerning confinement within a certain chemical territory of oil-droplet motion, and also its transient behavior. Our results may shed light on physical aspects of reactive spreading and a chemotaxis in living things.Comment: 17 pages, 10 figure

Optimization of treatment strategy

The purpose of this study was to predict the survival time of patients with malignant glioma after radiotherapy with high accuracy by considering additional clinical factors and optimize the prescription dose and treatment duration for individual patient by using a machine learning model. A total of 35 patients with malignant glioma were included in this study. The candidate features included 12 clinical features and 192 dose–volume histogram (DVH) features. The appropriate input features and parameters of the support vector machine (SVM) were selected using the genetic algorithm based on Akaike’s information criterion, i.e. clinical, DVH, and both clinical and DVH features. The prediction accuracy of the SVM models was evaluated through a leave-one-out cross-validation test with residual error, which was defined as the absolute difference between the actual and predicted survival times after radiotherapy. Moreover, the influences of various values of prescription dose and treatment duration on the predicted survival time were evaluated. The prediction accuracy was significantly improved with the combined use of clinical and DVH features compared with the separate use of both features (P < 0.01, Wilcoxon signed rank test). Mean ± standard deviation of the leave-one-out cross-validation using the combined clinical and DVH features, only clinical features and only DVH features were 104.7 ± 96.5, 144.2 ± 126.1 and 204.5 ± 186.0 days, respectively. The prediction accuracy could be improved with the combination of clinical and DVH features, and our results show the potential to optimize the treatment strategy for individual patients based on a machine learning model