Draft Genome Sequence of Botrytis cinerea BcDW1, Inoculum for Noble Rot of Grape Berries.

Botrytized wines are produced from grape berries infected by Botrytis cinerea under specific environmental conditions. Here, we report the draft genome sequence of B. cinerea BcDW1, a strain isolated from Sémillon grapes in Napa Valley in 1992 that is used with the intent to induce noble rot for botrytized wine production

System and method for providing structured tours of hypertext files

A system and method for providing structured tours of hypertext files. A server controls the presentation of hypertext files to a user. Accompanying information to the hypertext files in the form of an automated tour guide is presented and synchronized with the hypertext files by the tour server. A user may depart from the structured tour to explore linked files for a predetermined period of time, and may effect the content and order of the tour by indicating preferences at predetermined points along the tour. More than one user may take a tour, and the users on a tour may communicate with each other. Items may be purchased on a tour, and the user may send postcards based upon visited hypertext files to other users.Published versio

Estimating Population Parameters using the Structured Serial Coalescent with Bayesian MCMC Inference when some Demes are Hidden

Using the structured serial coalescent with Bayesian MCMC and serial samples, we estimate population size when some demes are not sampled or are hidden, ie ghost demes. It is found that even with the presence of a ghost deme, accurate inference was possible if the parameters are estimated with the true model. However with an incorrect model, estimates were biased and can be positively misleading. We extend these results to the case where there are sequences from the ghost at the last time sample. This case can arise in HIV patients, when some tissue samples and viral sequences only become available after death. When some sequences from the ghost deme are available at the last sampling time, estimation bias is reduced and accurate estimation of parameters associated with the ghost deme is possible despite sampling bias. Migration rates for this case are also shown to be good estimates when migration values are low

Crisis Intervention Team Training and the Protection Motivation Theory

The problem addressed in this phenomenological study was the lack of documentation that supported the lived experiences of crisis intervention team (CIT)-trained police officers related to their field encounters with persons with mental illnesses. The purpose of the study was to explore the lived experiences of officers among CIT-trained police officers to address the problem. The protection motivation theory was aligned closest with the teachings of CIT training as described by the study participants’ lived experiences. Participants provided the study’s collected data, which was composed of completed questionnaires and transcribed interviews. The empirical theoretical framework method of analysis used was a combination of inductive coding and theme analysis that established the results of this study. Key findings of the study identified a significant amount of frustration expressed in the lived experiences of the CIT-trained police officers. Frustration was experienced by officers who applied the protection motivation theory to ensure the well-being of persons experiencing a mental crisis. There was considerable pushback from the public mental health facilities, which added to the frustration experienced by CIT-trained police officers who attempted to navigate treatment with the limited resources available to help persons in mental crisis. The positive social change produced from this study included recommendations to police leadership and mental health advocates to encourage certain CIT-training-related practices that directly impact CIT field encounters with persons in mental crises. Specialized training may promote improved departmental outcomes such as sustainability of gains for those in crises and enable police officer accountability and reliability

Microelectronics Process Engineering at San Jose State University: A Manufacturing-Oriented Interdisciplinary Degree Program

San Jose State University\u27s new interdisciplinary curriculum in Microelectronics Process Engineering is described. This baccalaureate program emphasizes hands-on thin-film fabrication experience, manufacturing methods such as statistical process control, and fundamentals of materials science and semiconductor device physics. Each course of the core laboratory sequence integrates fabrication knowledge with process engineering and manufacturing methods. The curriculum development process relies on clearly defined and detailed program and course learning objectives. We also briefly discuss our strategy of making process engineering experiences accessible for all engineering students through both Lab Module and Statistics Module series

Automatic Recognition of Light Microscope Pollen Images

This paper is a progress report on a project aimed at the realization of a low-cost, automatic, trainable system "AutoStage" for recognition and counting of pollen. Previous work on image feature selection and classification has been extended by design and integration of an XY stage to allow slides to be scanned, an auto focus system, and segmentation software. The results of a series of classification tests are reported, and verified by comparison with classification performance by expert palynologists. A number of technical issues are addressed, including pollen slide preparation and slide sampling protocols

Surrogate-Based SmallSat Architecture Design Leveraging Integrated Parametric Mission Models

The modern space mission landscape requires consideration of many trade variables to meet growing cost and performance constraints. In the defense sector, threats continue to proliferate, driving the need for multi-layered constellations that are robust to myriad potential conflicts. In the civil sector, stakeholders seek science data with ever increasing timeliness, coverage, and resolution to monitor the pulse of Earth\u27s changing environment. Across the commercial arena, companies compete to deliver the best space products and services, bringing cutting edge business opportunities into the realm of possibility for the first time. Now more than ever, all three sectors demand optimal mission performance at low cost. For years academic methods have existed to address such challenges through complex system-of-systems analyses. However, widespread practical application of these methods to multi-satellite mission design remains uncommon. It is in the best interest of industry to evaluate, adopt, deploy, and standardize these methods as they have the capability to deliver unbiased, quick-turn constellation assessments, improving responsiveness to customer investigations of next-generation space missions of all types. Such capabilities lay the groundwork for rapid discovery of highly capable, low cost, future space architectures. This paper presents an approach to identify promising smallsat architectures through integration of parameterized engineering and cost estimation models. This approach simultaneously explores design drivers at multiple levels of mission architecture including payload, bus, orbit, and launch vehicle by employing proven statistical, data science, and machine learning techniques. When deployed at the early stages of constellation development, this analysis approach delivers two main benefits: It informs stakeholders of mission performance and cost sensitivity to a variety of design variables, leading to better decision making earlier in the acquisition timeline; and it uncovers promising regions of large design spaces to be examined further by teams of experts, increasing the efficiency of engineering design cycles