Electrical Activation Studies of Silicon Implanted Alx Gal-x N and Coimplanted GaN

A comprehensive study of the electrical activation of silicon implanted AlxGa1-xN was performed as a function ion dose, anneal temperature, and aluminum mole fraction, Also, GaN coimplanted with silicon and nitrogen was investigated. Room temperature Hall effect measurements were used to determine carrier concentration and mobility. All the samples had a 500 Å encapsulant of AlN, and were implanted at room temperature with 200 keV silicon ions at doses ranging from 1x1013 to 1x1015 /sq cm. The GaN was also implanted with nitrogen under the same conditions in doses of 9x1012 to 9x1014 /sq cm, respectively. The samples were annealed at temperatures ranging from 1200 to 1350 °C for 30 to 120 seconds in a flowing nitrogen environment. The aluminum mole fractions considered were 0.2 and 0.3. The electrical activation efficiency for the Al0.2Ga0.8N annealed at 1350 °C and implanted with 1x1015 /sq cm was almost 90%. While the Al0.3Ga0.7N annealed at 1350 °C and implanted with 1x1015 /sq cm exhibited only about 42% activation. The activation efficiency for all the samples increased with anneal temperature, but decreased with aluminum mole fraction. The mobilities and the carrier concentrations demonstrate an increase with the anneal temperature. Although the Al0.2Ga0.8N exhibited almost perfect activation, the mobility was generally low, only 50 /sq cm/Vxs. The coimplanted GaN showed surprisingly poor results. The highest activation efficiency was only 37% for the sample annealed at 1300 °C and implanted with a dose of 1x1015 silicon ions /sq cm. The mobilities for these samples were high, on average 100 /sq cm/Vxs. The carrier concentration and activation efficiency were found to increase with implanted dose. The mobilities, however, decreased as the anneal temperature increased

Measuring hidden phenotype:Quantifying the shape of barley seeds using the Euler characteristic transform

Shape plays a fundamental role in biology. Traditional phenotypic analysis methods measure some features but fail to measure the information embedded in shape comprehensively. To extract, compare and analyse this information embedded in a robust and concise way, we turn to topological data analysis (TDA), specifically the Euler characteristic transform. TDA measures shape comprehensively using mathematical representations based on algebraic topology features. To study its use, we compute both traditional and topological shape descriptors to quantify the morphology of 3121 barley seeds scanned with X-ray computed tomography (CT) technology at 127 μm resolution. The Euler characteristic transform measures shape by analysing topological features of an object at thresholds across a number of directional axes. A Kruskal-Wallis analysis of the information encoded by the topological signature reveals that the Euler characteristic transform picks up successfully the shape of the crease and bottom of the seeds. Moreover, while traditional shape descriptors can cluster the seeds based on their accession, topological shape descriptors can cluster them further based on their panicle. We then successfully train a support vector machine to classify 28 different accessions of barley based exclusively on the shape of their grains. We observe that combining both traditional and topological descriptors classifies barley seeds better than using just traditional descriptors alone. This improvement suggests that TDA is thus a powerful complement to traditional morphometrics to comprehensively describe a multitude of 'hidden' shape nuances which are otherwise not detected.</p

Creation and confidence: BME students as academic partners…but where were the staff?

This Case Study documents the REACT project 'Creation and Confidence' based at Sheffield Hallam University, which has a larger-than-expected Black Minority and Ethnic (BME) attainment gap; hence, this student group has been constructed as 'hard to reach'. The project team consisted of a range of academic and professional services staff alongside three dedicated student researchers. The project set out to achieve: gaining evidence-based insights into the use of co-design and peer-learning as conduits of confidence-building for and belonging of BME students; developing a scalable approach to building confidence for and fostering belonging of all students; raising awareness of the need to think differently about explanations for BME underachievement. In reality, the team found that staff engagement constituted the biggest barrier, as - no matter how much incontrovertible evidence was presented - other facets of institutional provision were always identified as having priority, which resulted in inertia. This study documents the emotional labour of trying to effect change within a resistant culture. Whilst some of the aims remain unachieved – and, arguably, were always going to be unachievable - there have been some very positive developments and enlightening lessons

The miser in La comedie humaine

iii, 169 leaves ; 29 cm.Contents include: the importance of money in French society of the restoration period, the miser in La Comedie Humaine, Balzac's presentation of the miser, and the character of the miser in Balzac and Galdos

The shape of things to come: Topological Data Analysis and biology, from molecules to organisms

Shape is data and data is shape. Biologists are accustomed to thinking about how the shape of biomolecules, cells, tissues, and organisms arise from the effects of genetics, development, and the environment. Less often do we consider that data itself has shape and structure, or that it is possible to measure the shape of data and analyze it. Here, we review applications of topological data analysis (TDA) to biology in a way accessible to biologists and applied mathematicians alike. TDA uses principles from algebraic topology to comprehensively measure shape in data sets. Using a function that relates the similarity of data points to each other, we can monitor the evolution of topological features—connected components, loops, and voids. This evolution, a topological signature, concisely summarizes large, complex data sets. We first provide a TDA primer for biologists before exploring the use of TDA across biological sub‐disciplines, spanning structural biology, molecular biology, evolution, and development. We end by comparing and contrasting different TDA approaches and the potential for their use in biology. The vision of TDA, that data are shape and shape is data, will be relevant as biology transitions into a data‐driven era where the meaningful interpretation of large data sets is a limiting factor

Increasing the cancer screening of the medically underserved in south florida

Diagnosis and treatment of cancers at advanced stages have contributed to a significantly lower survival rate among individuals of low socioeconomic status compared with those in higher brackets. In an effort to increase the accessibility and acceptability of cancer screening among such individuals in Dade County, Florida, the Cancer Control Division of the Sylvester Comprehensive Cancer Center at the University of Miami School of Medicine initiated a pilot early detection program in 1987. The program initially provided breast cancer screening for women, aged 40 and older, who attended ten community health care centers located in low‐income neighborhoods. With the selection of Miami by the American Cancer Society as one of three sites for conducting a screening demonstration project for the socioeconomically disadvantaged, this program has recently been expanded to include pelvic screening for women, aged 40 and older, and prostate screening for men, aged 65 and older

The shape of aroma: Measuring and modeling citrus oil gland distribution

Societal Impact Statement Citrus are intrinsically connected to human health and culture, preventing human diseases like scurvy and inspiring sacred rituals. Citrus fruits come in a stunning number of different sizes and shapes, ranging from small clementines to oversized pummelos, and fruits display a vast diversity of flavors and aromas. These qualities are key in both traditional and modern medicine and in the production of cleaning and perfume products. By quantifying and modeling overall fruit shape and oil gland distribution, we can gain further insight into citrus development and the impacts of domestication and improvement on multiple characteristics of the fruit. Summary Citrus come in diverse sizes and shapes, and play a key role in world culture and economy. Citrus oil glands in particular contain essential oils which include plant secondary metabolites associated with flavor and aroma. Capturing and analyzing nuanced information behind the citrus fruit shape and its oil gland distribution provide a morphology‐driven path to further our insight into phenotype–genotype interactions. We investigated the shape of citrus fruit of 51 accessions based on 3D X‐ray computed tomography (CT) scan reconstructions. Accessions include members of the three ancestral citrus species as well as related genera, and several interspecific hybrids. We digitally separate and compare the size of fruit endocarp, mesocarp, exocarp, and oil gland tissue. Based on the centers of the oil glands, overall fruit shape is approximated with an ellipsoid. Possible oil gland distributions on this ellipsoid surface are explored using directional statistics. There is a strong allometry along fruit tissues; that is, we observe a strong linear relationship between the logarithmic volume of any pair of major tissues. This suggests that the relative growth of fruit tissues with respect to each other follows a power law. We also observe that on average, glands distance themselves from their nearest neighbor following a square root relationship, which suggests normal diffusion dynamics at play. The observed allometry and square root models point to the existence of biophysical developmental constraints that govern novel relationships between fruit dimensions from both evolutionary and breeding perspectives. Understanding these biophysical interactions prompts an exciting research path on fruit development and breeding

Resource selection by coyotes (Canis latrans) in a longleaf pine ecosystem: effects of anthropogenic fires and landscape features

Prescribed fire is used to restore and maintain fire-dependent forest communities. Because fire affects food and cover resources, fire-mediated resource selection has been documented for many wildlife species. The first step in understanding these interactions is to understand resource selection of the predators in a fire-maintained system. We attached GPS radiocollars to 27 coyotes (Canis latrans Say, 1823) and examined resource selection relative to fire-maintained vegetation types, years-since-fire, anthropogenic features that facilitate prescribed burning, and other landscape features likely to affect coyote resource selection. Coyote home ranges were characterized by more open vegetation types and more recently burned forest (i.e., burned 0 â 1 year prior) than available on the study area. Within their home ranges, coyotes avoided areas close to densely vegetated drainages and paved roads. Coyote selection of more recently burned forest likely was in response to greater prey density or increased ability to detect prey soon after vegetation cover was reduced by fires; similarly, coyotes likely avoided drainages due to decreased hunting efficiency. Coyote resource selection was linked to prescribed fire, suggesting the interaction between fire and coyotes may influence ecosystem function in fire-dependent forests.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

X-Ray CT scans of barley panicles and their individual seeds from the Composite Cross II experiment

Shape plays a fundamental role in biology. Traditional phenotypic analysis methods measure some features but fail to measure the information embedded in shape comprehensively. To extract, compare, and analyze this information embedded in a robust and concise way, we turn to Topological Data Analysis (TDA), specifically the Euler Characteristic Transform. TDA measures shape comprehensively using mathematical representations based on algebraic topology features. To study its use, we compute both traditional and topological shape descriptors to quantify the morphology of 3121 barley seeds scanned with X-ray Computed Tomography (CT) technology at 127 micron resolution. The Euler Characteristic Transform measures shape by analyzing topological features of an object at thresholds across a number of directional axes. A Kruskal-Wallis analysis of the information encoded by the topological signature reveals that the Euler Characteristic Transform picks up successfully the shape of the crease and bottom of the seeds. Moreover, while traditional shape descriptors can cluster the seeds based on their accession, topological shape descriptors can cluster them further based on their panicle. We then successfully train a support vector machine (SVM) to classify 28 different accessions of barley based exclusively on the shape of their grains. We observe that combining both traditional and topological descriptors classifies barley seeds better than using just traditional descriptors alone. This improvement suggests that TDA is thus a powerful complement to traditional morphometrics to comprehensively describe a multitude of "hidden" shape nuances which are otherwise not detected