The Inland Empire Nonprofit Sector: A Growing Region Faces the Challenges of Capacity

While many people know the work of individual nonprofits, it can be difficult to understand the sector as a whole. This report connects the dots in the Inland Empire. It is intended to build public awareness about the region's nonprofit sector and provide information to help civic, nonprofit and philanthropic leaders strategize and take action to strengthen it. California's Inland Empire is a geographically vast region with a diverse and growing population. As the size and nature of this two-county region change, the infrastructure of its nonprofit sector is not keeping pace. This report describes the characteristics of the Inland Empire's nonprofit sector, the work it does, the ways it has changed between 2000 and 2005, the challenges it faces today and recommendations for strengthening its future. The Inland Empire's Riverside and San Bernardino counties and their subregions have distinct identities and resources, but they share many issues due to similarities in geography, population growth and the location of nonprofits relative to need. These persistent issues can serve as the basis for concerted action

Total Propagated Uncertainty (TPU) for Hydrographic LiDAR to Aid Objective Comparison to Acoustic Datasets

Previously, when comparing LiDAR datasets to other LiDAR or acoustic datasets, comparisons have always presumed that one control dataset is ultimately correct, with no errors. All error is attributed to the second dataset. Surface and target analysis methods have therefore been somewhat subjective. The use of TPU takes into account the fact that each depth point is an estimate with an associated uncertainty. This paper discusses a method to derive TPU for LiDAR sensors, so that CUBE may be used to perform an objective comparison of LiDAR bathymetry and acoustic datasets.Previamente, cuando se compara la base de datos LIDAR con otras bases de datos LIDAR o acüsticos, las comparaciones siempre presumen que una base de datos de control es finalmente correcta, sin errores. Todo error es atribuido a la segunda base de datos. Los métodos de anâlisis de blancos y superficie han sido por lo tanto en cierta medida subjetivos. El empleo de TPU toma en consideracion el hecho que cada puto de profundidad es una estimaciôn con una incertidumbre asociada. Este articulo discute un método para derivar TPU del sensor LIDAR, de forma taI que CUBE pueda ser empleado para hacer una comparaciôn objetiva delas bases de datos de batimetna LIDAR y acustica.Auparavant, lorsque l'on comparait des ensembles de données LiDAR à d’autres ensembles de données LiDAR ou accoustiques, on présumait qu'un ensemble de données de contrôle était finalement correct, sans aucune erreur. Toute erreur était attribuée au deuxième ensemble de données. Les méthodes d’analyse de surface et d'objectif étaient toutefois quelque peu subjectives. L'utilisation du TPU prend en compte le fait que chaque point de profondeur représente une estimation à laquelle est associée une incertitude. Cet article traite d'une méthode en vue de dériver le TPU pour les capteurs LiDAR, de façon à ce que CUBE puisse être utilisé en vue d’établir une comparaison objective de la bathymétrie LiDAR et des ensembles de données acoustiques

Using Common Academic Indicators to Predict Graduation Rates at CSUN, 2005-2014

The median time to graduation at California State University, Northridge (CSUN) is five years and fewer than fifty percent of first time freshmen graduate in less than eight years. We used data mining and predictive analytics to determine some of the key academic indicators of success at CSUN. The most important indicators that we found were (a) which math course the student was placed in (or took first); (b) student grade point average (GPA) at the end of each of the first two terms in residence; and (c) successful completion of a freshman experience seminar course (UNIV 100). When all three are considered simultaneously, we can correctly identify over two thirds of the students who will drop out without graduating, while misidentifying approximately one-fifth of students who ultimately graduate as at-risk of not graduating

The effectiveness of computer-aided assessment for purposes of a mathematical sciences lecturer

Computer-Aided Assessment (CAA) is becoming an increasingly popular method for assessing students in their mathematics courses in higher education. This article examines six lecturers’ practices of using CAA on their mathematics courses. The interview with these lecturers revealed that the CAA system did provide many benefits that were promised; however, there were some important aims not satisfied by the system, which limited the scope of its effectiveness. Using a model for effective assessment, which draws upon ideas from the assessment literature and cultural-historical activity theory, the lecturer interviews give an insight into what stops this assessment tool from remaining effective. This study shows that the CAA system was reasonably effective to an extent, and lecturers had achieved a relatively stable practice that they were satisfied to maintain; however, there were shortcomings with the existing system that limited the scope of its effectiveness, which led to diverse practices and a desire to change system

Lecturers’ perspectives on the use of a mathematics-based computer-aided assessment system

Computer-aided assessment (CAA) has been used at a university with one of the largest mathematics and engineering undergraduate cohorts in the UK for more than ten years. Lecturers teaching mathematics to first year students were asked about their current use of CAA in a questionnaire and in interviews. This article presents the issues that these lecturers faced as they made use of this assessment tool. Lecturers explained how they attempted to overcome these issues. The findings show that while the lecturers were happy to use the CAA system because it is efficient and timesaving, there were concerns that it might not always be beneficial for students. The bases for lecturers’ concerns were that some students developed tendencies to depend on the feedback to complete assessments and to develop procedural, context-dependent strategies for solving problems

A definition for effective assessment and implications on computer-aided assessment practice

For a decade, computer-aided assessment (CAA) has been used extensively with first-year mathematics and engineering undergraduates studying mathematics modules at the institution under investigation. This project sought to evaluate the effectiveness of CAA. Using assessment literature and activity theory to frame the study, this paper explores the aims of assessment and what it means for assessment to be “effective”: it proposes a definition for effective assessment and discusses whether CAA can be considered effective assessment by this definition

Vision-Based Safety System for Barrierless Human-Robot Collaboration

Human safety has always been the main priority when working near an industrial robot. With the rise of Human-Robot Collaborative environments, physical barriers to avoiding collisions have been disappearing, increasing the risk of accidents and the need for solutions that ensure a safe Human-Robot Collaboration. This paper proposes a safety system that implements Speed and Separation Monitoring (SSM) type of operation. For this, safety zones are defined in the robot's workspace following current standards for industrial collaborative robots. A deep learning-based computer vision system detects, tracks, and estimates the 3D position of operators close to the robot. The robot control system receives the operator's 3D position and generates 3D representations of them in a simulation environment. Depending on the zone where the closest operator was detected, the robot stops or changes its operating speed. Three different operation modes in which the human and robot interact are presented. Results show that the vision-based system can correctly detect and classify in which safety zone an operator is located and that the different proposed operation modes ensure that the robot's reaction and stop time are within the required time limits to guarantee safety.Comment: Accepted for publication at the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS

ULTRA-SCALE DOWN STUDIES OF HUMAN CELL BIOPROCESSING FOR A PROSTATE CANCER VACCINE THERAPY - THE IMPACT OF CAPILLARY SHEAR

The scale-up and manufacturing of therapies based on intact whole cells presents a major challenge for development scientists and engineers due to the stress-reactive nature of these cells. The administrated cells may be characterized in terms of their membrane integrity and their surface markers and eventually their biopotency. The challenge is to process the cells at various scales and in a way which maintains these cell properties. Also during formulation the presence of cytokines produced by cells prior to their inactivation is a critical factor. This poster presents an approach to allow the rapid characterization of human cell lines in terms of their resistance to hydrodynamic stress. An ultra scale-down method has been developed which allows investigation with small quantities of cells commonly available at the early discovery stage. The study describes controlled flow through a capillary device where cells are exposed to several defined hydrodynamic stresses. A Design of Experiments approach was used to understand the combined effect of many process parameters such as flow rate, length of capillary and number of passes. This was followed by an additional set of detailed ultra scale-down experiments where other critical quality attributes like cell size, surface phenotype, biopotency and cytokine release were measured. Computational fluid dynamics was used to describe the capillary entry region which allows the cells to be characterized in terms of a critical stress below which there is no significant damage to cell integrity or surface phenotype. A UK Technology Strategy Board funded program in collaboration with LGC, Nottingham Trent University and originally with Onyvax Ltd

Assessing the Gene Content of the Megagenome: Sugar Pine (Pinus lambertiana).

Sugar pine (Pinus lambertiana Douglas) is within the subgenus Strobus with an estimated genome size of 31 Gbp. Transcriptomic resources are of particular interest in conifers due to the challenges presented in their megagenomes for gene identification. In this study, we present the first comprehensive survey of the P. lambertiana transcriptome through deep sequencing of a variety of tissue types to generate more than 2.5 billion short reads. Third generation, long reads generated through PacBio Iso-Seq have been included for the first time in conifers to combat the challenges associated with de novo transcriptome assembly. A technology comparison is provided here to contribute to the otherwise scarce comparisons of second and third generation transcriptome sequencing approaches in plant species. In addition, the transcriptome reference was essential for gene model identification and quality assessment in the parallel project responsible for sequencing and assembly of the entire genome. In this study, the transcriptomic data were also used to address questions surrounding lineage-specific Dicer-like proteins in conifers. These proteins play a role in the control of transposable element proliferation and the related genome expansion in conifers