Impact of UAV Hardware Options on Bridge Inspection Mission Capabilities

Uncrewed Aerial Vehicles (UAV) constitute a rapidly evolving technology field that is becoming more accessible and capable of supplementing, expanding, and even replacing some traditionally manual bridge inspections. Given the classification of the bridge inspection types as initial, routine, in-depth, damage, special, and fracture critical members, specific UAV mission requirements can be developed, and their suitability for UAV application examined. Results of a review of 23 applications of UAVs in bridge inspections indicate that mission sensor and payload needs dictate the UAV configuration and size, resulting in quadcopter configurations being most suitable for visual camera inspections (43% of visual inspections use quadcopters), and hexa- and octocopter configurations being more suitable for higher payload hyperspectral, multispectral, and Light Detection and Ranging (LiDAR) inspections (13%). In addition, the number of motors and size of the aircraft are the primary drivers in the cost of the vehicle. 75% of vehicles rely on GPS for navigation, and none of them are capable of contact inspections. Factors that limit the use of UAVs in bridge inspections include the UAV endurance, the capability of navigation in GPS deprived environments, the stability in confined spaces in close proximity to structural elements, and the cost. Current research trends in UAV technologies address some of these limitations, such as obstacle detection and avoidance methods, autonomous flight path planning and optimization, and UAV hardware optimization for specific mission requirements

Impact of UAV Hardware Options on Bridge Inspection Mission Capabilities

Uncrewed Aerial Vehicles (UAV) constitute a rapidly evolving technology field that is becoming more accessible and capable of supplementing, expanding, and even replacing some traditionally manual bridge inspections. Given the classification of the bridge inspection types as initial, routine, in-depth, damage, special, and fracture critical members, specific UAV mission requirements can be developed, and their suitability for UAV application examined. Results of a review of 23 applications of UAVs in bridge inspections indicate that mission sensor and payload needs dictate the UAV configuration and size, resulting in quadcopter configurations being most suitable for visual camera inspections (43% of visual inspections use quadcopters), and hexa- and octocopter configurations being more suitable for higher payload hyperspectral, multispectral, and Light Detection and Ranging (LiDAR) inspections (13%). In addition, the number of motors and size of the aircraft are the primary drivers in the cost of the vehicle. 75% of vehicles rely on GPS for navigation, and none of them are capable of contact inspections. Factors that limit the use of UAVs in bridge inspections include the UAV endurance, the capability of navigation in GPS deprived environments, the stability in confined spaces in close proximity to structural elements, and the cost. Current research trends in UAV technologies address some of these limitations, such as obstacle detection and avoidance methods, autonomous flight path planning and optimization, and UAV hardware optimization for specific mission requirements

Changing the face of STEM with stormwater research

Abstract Background The University of Maine Stormwater Management and Research Team (SMART) program began in 2014 with the goal of creating a diverse science-technology-engineering-math (STEM) pathway with community water research. The program engages female and underrepresented minority high school students in locally relevant STEM research. It focuses on creating educational experiences that are active and relevant to students that build confidence, connect knowledge and skills directly to solving problems in local communities, and support student cultural identities. The core tools of the SMART program are resources and relationships: university-designed or commercial water data collection equipment, data loggers and chemistry supplies, on-campus science and engineering training for teacher-mentors and students, and a community mentor network. The program supports an annual summer institute that trains both students and teacher-mentors and academic-year student research projects. SMART groups are formed at local schools or community centers. Activities revolve around engaging students in citizen-science to expand their understanding of the environment, developing community strategies to address the complex problem of stormwater pollution, and using the tools of science, engineering, and technology effectively. In addition, the program supports teachers and students in reaching out to local science and engineering professionals to form a mentor network for student research. Results Over 3 years, 220 students and 25 teachers have been trained in the science and engineering of stormwater, having taken and recorded over 4000 local water measurements (i.e., temperature, conductivity, pH). In all cohorts to date, over 75% of student participants have self-identified as either female or a racial minority. Of approximately 125 currently college-eligible former and current SMART students, more than 41% have been accepted or are enrolled in a secondary STEM degree program. In pre- and post-program surveys, female and underrepresented minority students reported that SMART activities and their relationship with mentors have increased their awareness of how stormwater affects the community and increased their interest in pursuing a STEM career. Conclusion With its focus on problem-solving at the community level, SMART supports students in active, local, and culturally relevant science and engineering experiences that contribute to building their confidence and affirming their decision to pursue post-secondary STEM careers

Organ-, inflammation- and cancer specific transcriptional fingerprints of pancreatic and hepatic stellate cells

Abstract Background Tissue fibrosis is an integral component of chronic inflammatory (liver and pancreas) diseases and pancreatic cancer. Activated pancreatic- (PSC) and hepatic- (HSC) stellate cells play a key role in fibrogenesis. To identify organ- and disease-specific stellate cell transcriptional fingerprints, we employed genome-wide transcriptional analysis of primary human PSC and HSC isolated from patients with chronic inflammation or cancer. Methods Stellate cells were isolated from patients with pancreatic ductal adenocarcinoma (n = 5), chronic pancreatitis (n = 6), liver cirrhosis (n = 5) and liver metastasis of pancreatic ductal adenocarcinoma (n = 6). Genome-wide transcriptional profiles of stellate cells were generated using our 51K human cDNA microarray platform. The identified organ- and disease specific genes were validated by quantitative RT-PCR, immunoblot, ELISA, immunocytochemistry and immunohistochemistry. Results Expression profiling identified 160 organ- and 89 disease- specific stellate cell transcripts. Collagen type 11a1 (COL11A1) was discovered as a novel PSC specific marker with up to 65-fold higher expression levels in PSC compared to HSC (p CCL2 and the cell adhesion molecule VCAM1 were confined to HSC. PBX1 expression levels tend to be increased in inflammatory- vs. tumor- stellate cells. Intriguingly, tyrosine kinase JAK2 and a member of cell contact-mediated communication CELSR3 were found to be selectively up-regulated in tumor stellate cells. Conclusions We identified and validated HSC and PSC specific markers. Moreover, novel target genes of tumor- and inflammation associated stellate cells were discovered. Our data may be instrumental in developing new tailored organ- or disease-specific targeted therapies and stellate cell biomarkers.</p

Organ-, inflammation- and cancer specific transcriptional fingerprints of pancreatic and hepatic stellate cells

BACKGROUND: Tissue fibrosis is an integral component of chronic inflammatory (liver and pancreas) diseases and pancreatic cancer. Activated pancreatic- (PSC) and hepatic- (HSC) stellate cells play a key role in fibrogenesis. To identify organ- and disease-specific stellate cell transcriptional fingerprints, we employed genome-wide transcriptional analysis of primary human PSC and HSC isolated from patients with chronic inflammation or cancer. METHODS: Stellate cells were isolated from patients with pancreatic ductal adenocarcinoma (n = 5), chronic pancreatitis (n = 6), liver cirrhosis (n = 5) and liver metastasis of pancreatic ductal adenocarcinoma (n = 6). Genome-wide transcriptional profiles of stellate cells were generated using our 51K human cDNA microarray platform. The identified organ- and disease specific genes were validated by quantitative RT-PCR, immunoblot, ELISA, immunocytochemistry and immunohistochemistry. RESULTS: Expression profiling identified 160 organ- and 89 disease- specific stellate cell transcripts. Collagen type 11a1 (COL11A1) was discovered as a novel PSC specific marker with up to 65-fold higher expression levels in PSC compared to HSC (p < 0.0001). Likewise, the expression of the cytokine CCL2 and the cell adhesion molecule VCAM1 were confined to HSC. PBX1 expression levels tend to be increased in inflammatory- vs. tumor- stellate cells. Intriguingly, tyrosine kinase JAK2 and a member of cell contact-mediated communication CELSR3 were found to be selectively up-regulated in tumor stellate cells. CONCLUSIONS: We identified and validated HSC and PSC specific markers. Moreover, novel target genes of tumor- and inflammation associated stellate cells were discovered. Our data may be instrumental in developing new tailored organ- or disease-specific targeted therapies and stellate cell biomarkers

Cellular dissociation grading based on the parameters tumor budding and cell nest size in pretherapeutic biopsy specimens allows for prognostic patient stratification in esophageal squamous cell carcinoma independent from clinical staging.

Initial treatment planning in esophageal squamous cell carcinoma mainly relies on clinical staging. Recently, a highly prognostic grading system based on the cellular dissociation parameters Tumor Budding and Cell Nest Size has been proposed for resected esophageal squamous cell carcinoma. To probe for the transferability and relevance of this established novel grading system in the pretreatment setting, we evaluated Tumor Budding/Cell Nest Size in pretherapeutic biopsies of either primarily resected (cohort 1, n=80) or neoadjuvantly treated (cohort 2, n=75) esophageal squamous cell carcinoma. Grading data were correlated with clinicopathologic and survival parameters. High Tumor Budding Activity and small Cell Nest Size in pretherapeutic biopsies were strongly associated with shortened overall survival, disease-free survival, and disease-specific survival in both cohorts. A modified histopathologic grading system incorporating both factors termed Cellular Dissociation Grade showed excellent prognostic demarcation between well (G1), moderately (G2), and poorly differentiated (G3) carcinomas in both scenarios (overall survival: cohort 1: P&lt;0.001; cohort 2: P=0.009) and was predictive for a high pathologic tumor stage and the presence of nodal metastases in primarily resected patients. Multivariate analyses revealed the Cellular Dissociation Grade to be a predictor of poor outcome in the pretherapeutic setting independent of clinical stage (overall survival, disease-free survival, and disease-specific survival: P&lt;0.001). Hazard ratio for disease-free survival was 3.19 for G2 and 5.66 for G3 carcinomas compared with G1 neoplasms. Our data not only prove the transferability of histopathologic grading based on Tumor Budding/Cell Nest Size to biopsy specimens in esophageal squamous cell carcinoma, but also demonstrate that the Cellular Dissociation Grade is a strong outcome predictor in this entity even in the pretreatment scenario. Therefore, we believe that this novel type of grading has the ability to serve as a powerful histology-based pretherapeutic biomarker, that might supplement clinical staging for choosing the most suitable therapy decision