Miracle-dz/UniFAR-FTUs huggingface dataset:
Semiochemistry of Cerambycid Beetles: Interactions Among Pheromones, Host Plant Volatiles, and Density Dependent Effects

Author(s): Collignon, Robert Maxwell | Advisor(s): Millar, Jocelyn | Abstract: Longhorn beetles (Coleoptera: Cerambycidae) are wood-boring insects that infest trees and woody plants of varying conditions, from healthy to dead. Pheromones have now been identified for a number of cerambycid species, but our understanding of pheromone use in the family is limited. The first section of my research investigated the role of host plant volatiles on attraction to pheromones, and sought to identify new host volatiles that may be attractive or synergistic, particularly for oak-infesting species. My results corroborated previous work demonstrating that conifer volatiles are synergists for some species of conifer-infesting cerambycids; no such effect was found for oak volatiles and oak-infesting species, however. The second portion of this dissertation examined how cerambycids utilize their pheromones, focusing on several species that use male-produced pheromones, which attract both sexes and are often not species-specific compounds. Several possible pheromone partitioning mechanisms were tested, and I found that diel activity periods and pheromone blends have roles in reproductively and/or competitively isolating cerambycid species that use similar or the same pheromone components. Although not directly tested, there is evidence that host plant volatiles may play a role in partitioning and isolation as well. Evidence was also found that males of one species, Phymatodes grandis, may exploit the volatiles emitted by males of another species, Phymatodes obliquus, as a kairomone. Response to increasing release rates of two common pheromone components, 2-methylbutan-1-ol and 3-hydroxyhexan-2-one, was also tested and I found that responses increased with release rates for four of the five test species, even at the highest rates tested (~1,450 μg/h and ~720 μg/h, respectively). However, responses of the fifth species, P. obliquus, did plateau with increasing release rates. I also tested the effect of density of conspecific males on per capita pheromone production. Headspace volatiles of male P. grandis were sampled from individuals, pairs, or groups of three or four beetles held in 500 ml Teflon chambers. Emission rates of their pheromone (R)-2-methylbutan-1-ol were found to decrease with increasing density, suggesting that cerambycids may use optimal density strategies, as has been shown for other coleopteran species that utilize male-produced sex-aggregation pheromones.
Mapping potable reuse survey data using spatial statistics to inform tailored education and outreach

This research describes geospatial analyses of water‐related knowledge and opinion data on potable water reuse collected through a large‐scale public survey of water utility customers in Albuquerque, New Mexico. We identify key geographic areas, or statistically significant “hotspots,” of public distrust in the local water utility provider, public willingness (or lack thereof) to accept potable water reuse, and lack of knowledge or misconceptions about water‐related issues and climate change. By combining public survey data, geographic information system software, and spatial statistics for hotspot analyses, we introduce a tailored outreach method to identify geographic locations for targeted outreach and education on water‐related issues. This new approach to analyzing survey data is a promising dimension of water management, and the method could be important for tackling other resource management issues in additional cities or regions as well.
The Role of Cell-polarity in Development and Disease

From the simplest unicellular organisms to complex metazoans, cell polarity is a widespread characteristic that is essential for almost every aspect of biology. Proper polarization of cells is crucial for the establishment and maintenance of higher order structures such as tissue and organs. Cell polarity refers to the asymmetric distribution of various macromolecules and cellular structures, resulting in polarized architecture and function of the cell. Defects in cell polarity lead to various phenotypes, ranging from aberrant signaling, proliferation, cell adhesion and migration, cell fate determination and pluripotency, as well as embryonic lethality, neoplasia and cancer. Given the various roles for cell polarity in development and disease, the characterization of the components involved in polarity and their mechanisms of function is of great importance. My thesis work has encompassed three major projects, each of which is focused on understanding the role of cell polarity in development and disease. Although genetic screens in invertebrates have led to the identification of a number of cell-polarity proteins, similar systematic approach have not been undertaken in mammalian systems. The goal of my first project was to design and implement a high-throughput screen to systematically knockdown individual genes using siRNA, and then assess cell junction integrity as a measure of cell polarity. Given the importance of cell polarity to signaling pathways, I next sought to determine the mechanism by which cell polarity affects TGFβ and Hippo pathways, two important signaling pathways involved in development and disease. Lastly, by studying the acquisition of
Comparative study of glenoid version and inclination using two-dimensional images from computed tomography and three-dimensional reconstructed bone models

Background This study was performed to compare glenoid version and inclination measured using two-dimensional (2D) images from computed tomography (CT) scans or three-dimensional (3D) reconstructed bone models. Methods Thirty patients who had undergone conventional CT scans were included. Two orthopedic surgeons measured glenoid version and inclination three times on 2D images from CT scans (2D measurement), and two other orthopedic surgeons performed the same measurements using 3D reconstructed bone models (3D measurement). The 3D-reconstructed bone models were acquired and measured with Mimics and 3-Matics (Materialise). Results Mean glenoid version and inclination in 2D measurements were –1. 705º and 9. 08º, respectively, while those in 3D measurements were 2. 635º and 7. 23º. The intra-observer reliability in 2D measurements was 0.605 and 0.698, respectively, while that in 3D measurements was 0.883 and 0.892. The inter-observer reliability in 2D measurements was 0.456 and 0.374, respectively, while that in 3D measurements was 0.853 and 0.845. Conclusions The difference between 2D and 3D measurements is not due to differences in image data but to the use of different tools. However, more consistent results were obtained in 3D measurement. Therefore, 3D measurement can be a good alternative for measuring glenoid version and inclination.
Pancreatic ductal adenocarcinoma progression is restrained by stromal matrix.

Desmoplasia describes the deposition of extensive extracellular matrix and defines primary pancreatic ductal adenocarcinoma (PDA). The acellular component of this stroma has been implicated in PDA pathogenesis and is being targeted therapeutically in clinical trials. By analyzing the stromal content of PDA samples from numerous annotated PDA data sets and correlating stromal content with both anatomic site and clinical outcome, we found PDA metastases in the liver, the primary cause of mortality to have less stroma, have higher tumor cellularity than primary tumors. Experimentally manipulating stromal matrix with an anti- lysyl oxidase like-2 (anti-LOXL2) antibody in syngeneic orthotopic PDA mouse models significantly decreased matrix content, led to lower tissue stiffness, lower contrast retention on computed tomography, and accelerated tumor growth, resulting in diminished overall survival. These studies suggest an important protective role of stroma in PDA and urge caution in clinically deploying stromal depletion strategies.
Deep learning diffusion fingerprinting to detect brain tumour response to chemotherapy

Artificial neural networks are being widely implemented for a range of different biomedical imaging applications.Convolutional neural networks are by far the most popular type of deep earning architecture,but often require very large datasets for robust training and evaluation We introduce deep learning diffusion fingerprinting (DLDF), which we have used to classifydiffusion-weighted magnetic resonance imaging voxels in a mouse model of glioblastoma (GL261 cell line), both prior to and in response to Temozolomide (TMZ) chemotherapy.We show that, even with limited training, DLDF can automatically segment brain tumours from normal brain, can automatically distinguish between young and older (after 9 days of growth) tumours and that DLDF can detect whether or not a tumour has been treated with chemotherapy.Our results also suggest that DLDF can detect localised changes in the underlying tumour microstructure, which are not evident using conventional measurements of the apparent diffusion coefficient (ADC). Tissue category maps generated by DLDF showed regions containing a mixture of normal brain and tumour cells, and in some cases evidence of tumour invasion across the corpus callosum, which were broadly consistent with histology.In conclusion, DLDF shows the potential for applying deep learning on a pixel-wise level,which reduces the need for vast training datasets and could easily be applied to other multi-dimensional imaging acquisitions Abbreviations ANN artificial neural network CT x-ray computed tomography PET positron emission tomography CNN convolutional neural network HARDI high angular resolution diffusion weighted imaging NODDI neurite orientation dispersion and density imaging VERDICT vascular, extracellular and restricted diffusion for cytometry in tumours DLDF deep learning with diffusion fingerprinting TMZ Temozolomide PFA paraformaldehyde H&E hematoxylin and eosin GFAP glial fibrillary acidic protein
Genetic Variability for Agronomic Traits in SorghumMinicore Collection

Sorghum is a major cereal crop globally with economically important uses such as food, feed, fodder, fuel, and fiber. Crop improvement and precision breeding can be achieved by understanding and utilizing the variability in sorghum germplasm collection. A total of 242 germplasm accessions of sorghum minicore were assessed for the extent of variability, trait associations and genetic diversity. Sorghum minicore collection was evaluated for agronomic traits in two post-rainy seasons at ICRISAT- Patancheru, India. Large variability was observed for agronomic traits and strong associations between the traits studied. The 242 minicore accessions were grouped into six clusters under a hierarchical dendrogram. Genotypes from diverse clusters can be used in crossing programs to combine desirable traits and can be used as donors in breeding programs.
Exploring peer feedback processes and peer feedback meta-dialogues with learners of academic and business English

Peer feedback has been proposed as a way to boost student feedback literacy and learners’ evaluative judgment. However, the notion of peer feedback and its related processes present numerous challenges for teachers and learners. By adopting the principles of Exploratory Practice with my undergraduates studying academic and business English, I explored why my learners did not seem to view peer feedback as worthwhile, unpacking their attitudes and beliefs in this area of practice using both traditional surveys and the idea of classroom meta-dialogues. I attempted to develop evaluative judgment skills and proactive recipience by tailoring peer feedback processes around oral presentations, a central course component and assessment task for both groups of learners. Survey responses, classroom discussion (the meta-dialogues), observation, and reflection revealed that, overall, my learners were positively predisposed to peer feedback whilst, at the same time, only moderately enthusiastic about the usefulness of the actual peer feedback they received. In a minority of cases, learners resisted peer feedback processes strongly, reflecting the complex interplay of linguistic, cultural and affective factors that represent peer feedback in practice. My learners, at first, struggled to be proactively recipient but helped to identify tensions around tailoring peer feedback. I reflect on the learner resistance encountered and the personal implications for my own teaching. I also suggest ways that language teachers can scaffold proactive recipience and enact tailored peer feedback in a way that is inclusive of both composers’ and recipients’ needs. Finally, I provide a practitioner vantage point on peer feedback, contributing to a diversity of research perspectives in this area.
Remotely Sensed Changes in Vegetation Cover Distribution and Groundwater along the Lower Gila River

Introduced as a soil erosion deterrent, salt cedar has become a menace along riverbeds in the desert southwest. Salt cedar replaces native species, permanently altering the structure, composition, function, and natural processes of the landscape. Remote sensing technologies have the potential to monitor the level of invasion and its impacts on ecosystem services. In this research, we developed a species map by segmenting and classifying various species along a stretch of the Lower Gila River. We calculated metrics from high-resolution multispectral imagery and light detection and ranging (LiDAR) data to identify salt cedar, mesquite, and creosote. Analysts derived training and validation information from drone-acquired orthophotos to achieve an overall accuracy of 94%. It is clear from the results that salt cedar completely dominates the study area with small numbers of mesquite and creosote present. We also show that vegetation has declined in the study area over the last 25 years. We discuss how water usage may be influencing the plant health and biodiversity in the region. An examination of ground well, stream gauge, and Gravity Recovery and Climate Experiment (GRACE) groundwater storage data indicates a decline in water levels near the study area over the last 25 years.
Reconstruction algorithm for 3D Compton scattering imaging with incomplete data

Compton scattering describes the scattering of a photon after its collision with an electron. The recent developments of spectral cameras, able to collect photons in terms of energy, open the way to a new imaging concept: 3D Compton scattering imaging (CSI), which seeks to exploit the scattered radiation as a vector of information while a specimen of interest is illuminated by a monochromatic ionizing source. Focusing on modelling the first-order scattering, image reconstruction from CSI data remains a difficult challenge. In particular, physical constraints (detector and architecture of the scanner) lead to various incompleteness scenario within the data and thus streak artifacts when using filtered backprojection type formulas. This paper addresses the problem of recovering an object under study using CSI data subject to incompleteness and assuming only first-order scattering. The proposed method consists of suitably tuning the multiplicative Kaczmarz algorithm and is implemented and tested for two architectures of the scanner. Furthermore, the modality on CSI considered here presents the advantage of not requiring any rotation of the source or object.
Low-temperature GaAs-based plasmonic photoconductive terahertz detector with Au nano-islands

We have fabricated low-temperature grown GaAs (LT-GaAs)-based plasmonic photoconductive antennas by RF sputtering of Au nanoparticles and have evaluated their terahertz detection properties. Localized surface plasmon resonance enhances the electric fields near the surface and increases the optical absorption of nanoparticles. The resonance frequency depends on the density of electrons, the effective electron mass, and the size and shape of the nanoparticles. Therefore, we tried to develop a high-sensitivity LT-GaAs photoconductive detector (PCD), which is effective over a wide range of wavelengths, by RF sputtering of Au nano-islands with a variety of aspect ratios from 1.2 to 5.1 on the dipole gap region of the PCD. As a result, we succeeded in increasing the sensitivity by 29% and 40% in the amplitude of observed terahertz pulse for 800 nm and 1560 nm femtosecond laser excitations, respectively.
Tecnologia e degradação de pastagens na pecuária no Cerrado brasileiro

A pecuária no Brasil teve papel relevante na formação do espaço rural. Tal processo ocasionou um passivo ambiental, pois se desenvolveu sem considerar os impactos ao meio ambiente, relativos à erosão e compactação dos solos, emissão de gases de efeito estufa (GEE), além do uso intensivo de terra e dos recursos hídricos. Em significativa parcela das propriedades o manejo inadequado resultou em pastagens com níveis de degradação. A literatura aponta a importância da intensificação da tecnologia como forma de garantir pastagens sustentáveis. Esta pesquisa tem por objetivo analisar a relação entre nível tecnológico de produção de bovinos e de degradação de pastagens na Bacia Hidrográfica do Rio Vermelho, em Goiás - Brasil. Esta área é considerada como representativa da pecuária no cerrado brasileiro. Foi utilizada amostra estratificada por compartimentos com 60 estabelecimentos agropecuários. Utilizaram-se as técnicas de análise de correspondência múltipla, análise de cluster e regressão beta para obter o Índice de Degradação de Pastagens (IDP). Verificaram-se associações bivariadas entre o Índice Tecnológico (IT) e as variáveis: renda, relevo e tamanho da propriedade. Foi possível constatar o emprego de maior nível tecnológico nas maiores propriedades e em terrenos mais planos. Também se constatou que o maior nível tecnológico propicia maior remuneração aos gestores. Porém não se observou relação entre a tecnologia empregada nos estabelecimentos e taxa de lotação animal, o que pode comprometer os resultados econômicos e bem-estar animal. Assim, como não foi observada associação entre índice tecnológico e índice de degradação de pastagens, sugerindo ocorrência de degradação de pastagens, mesmo quando do uso de tecnologias na produção de bovinos.
Production of Fe nanoparticles from γ-Fe2O3 by high-pressure hydrogen reduction

In this work, the reduction of iron oxide γ-Fe2O3 nanoparticles by hydrogen at high pressures is studied. Increasing the hydrogen pressure enables reduction of γ-Fe2O3 to α-Fe at significantly lower temperatures. At low pressures, a temperature of 390 °C is necessary whereas at 530 bar complete reduction can be realized at temperatures as low as 210 °C. This leads to significant improvement in the final particle morphology, maintaining high surface-to-volume ratio of the nanoparticles with an average size of 47 ± 5 nm which is close to that of the precursor γ-Fe2O3. Neck formation, coalescence and growth during reduction can be significantly suppressed. Investigations of magnetic properties show that saturation magnetization of the reduced α-Fe nanoparticles decreases with particle size from 209 A m2 kg−1 at 390 °C reduction temperature to 204 A m2 kg−1 at 210 °C. Coercivity for the fine iron particles reaches 0.076 T which exceeds the theoretical anisotropy field. This is attributed to nano-scale surface effects.
Developing an Empathy Spectrum for Games

Games often encourage players to feel empathy for characters or scenarios by design. However, the term ‘empathy’ is often misunderstood and used in a variety of contexts as a substitute for feelings of sympathy, pity and compassion. This article defines a distinction between these similar terms and uses their definitions to describe how players emotionally engage with a game. This helps define an empathy spectrum, ranging from pity to compassion, that can be used to subjectively classify different games. To show the spectrum in use, the article discusses a variety of video games that can be placed at the spectrum’s key points, before discussing how games might reach the spectrum’s furthest point: compassion. The research hopes that modelling these abstract psychological concepts on this spectrum can help game designers, players and scholars better understand the range of emotional responses present in games.
Particle Swarm Optimization Based Parameter Identification Applied to a Target Tracker Robot with Flexible Joint

This paper focuses on parameter identification of a target tracker robot possessing flexible joints using particle swarm optimization (PSO) algorithm. Since, belt and pulley mechanisms are known as flexible joints in robotic systems, their elastic behavior affecting a tracker robot is investigated in this work. First, dynamic equations governing the robot behavior are extracted taking into account the effects of considered flexible joints. Thus, a flexible joint is modeled by a non-linear spring and damper system connecting the motor to the link. It is found that the governing dynamic equations include some unknown parameters, which must be identified in order to design the robot system. Consequently, a PSO-based identification scheme is proposed to achieve the unknown variables based on the experimental data of the open-loop system. Lastly, for validating the proposed identification scheme, the obtained results are compared to the experimental measurements as well as the results of another similar work in which the robot is modeled with rigid joints. The consequences reveal that the mathematical model of the robot with flexible joint can describe the elastic behavior of the tracker robot. Thus, a better agreement between the simulation and experimental data are found in comparison with outcomes of the robot model with rigid joints.
Approaches to quantify optical coherence tomography angiography metrics

Optical coherence tomography (OCT) has revolutionized the field of ophthalmology in the last three decades. As an OCT extension, OCT angiography (OCTA) utilizes a fast OCT system to detect motion contrast in ocular tissue and provides a three-dimensional representation of the ocular vasculature in a non-invasive, dye-free manner. The first OCT machine equipped with OCTA function was approved by U.S. Food and Drug Administration in 2016 and now it is widely applied in clinics. To date, numerous methods have been developed to aid OCTA interpretation and quantification. In this review, we focused on the workflow of OCTA-based interpretation, beginning from the generation of the OCTA images using signal decorrelation, which we divided into intensity-based, phase-based and phasor-based methods. We further discussed methods used to address image artifacts that are commonly observed in clinical settings, to the algorithms for image enhancement, binarization, and OCTA metrics extraction. We believe a better grasp of these technical aspects of OCTA will enhance the understanding of the technology and its potential application in disease diagnosis and management. Moreover, future studies will also explore the use of ocular OCTA as a window to link ocular vasculature to the function of other organs such as the kidney and brain.