Deer impact and plant resistance traits

White-tail deer (Odocoileus virginianus), a generalist herbivore, are widely considered to influence ecological communities, ecosystems and human wellbeing by foraging preferentially on certain plant species. Previous research has shown that high deer density can change the relative abundance of tree species in forest communities. Furthermore, some evidence shows that resistance traits of plants can influence plant photosynthetic ability which is an important factor in an ecosystem. The purpose of this experiment is to test whether plant resistance traits can change within species when they are exposed to high levels of deer herbivores. The experiment, established in 1979, enclosed deer within forest stands at high and low densities. Resistance traits of five dominant woody plant species were sampled from individuals that established during the deer density treatments and are now adults. Plant resistance traits (Leaf mass per area, Leaf dry matter content, C:N ratio, and Wood density) were tested and compared between low and high deer density area by using mixed effect statistical models. Leaf mass per area (LMA), leaf carbon—nitrogen ratio (C:N), and wood density did not respond significantly to increasing deer density. However, leaf dry matter content (L D MC) showed a slight but significant increase in response to high deer density. These results indicate that this plant trait may respond to increasing deer density, resulting in potential impacts on ecosystem functioning

Genetic population structure and microbiome of german cockroaches in urban environments

Pests of human habitats may harbor and disperse pathogens that cause human disease. One such pest is the German cockroach (Blattella germanica), which is known to harbor numerous pathogens, including Klebsiella and Pseudomonas. The aim of this study is to reveal the importance of the German cockroach as a potential vector of human medically important diseases. To do so, this study investigates German cockroach population structure and their associated bacterial microbiome in urban residential environments. Ninety German cockroaches are collected from three residential apartment buildings in three New Jersey cities. Samples are caught by glue traps and stored at -20°C. DNA and RNA are extracted from cockroach samples and sent for Next Generation Sequencing. Single-Nucleotide Polymorphisms (SNPs) are the genetic markers used for the cockroach population structure analysis. Thirty samples of the same extractions are also used for bacterial genetic analysis. Phylogeny, Principal Component Analysis (PCA), and STRUCTURE analysis are used for characterizing the population structure of cockroaches, which reflects the dispersal ability and colonization history of the cockroach populations. Results show that population structure exists among the three buildings/cities and within each building, and indicates limited gene flow among buildings/cities. Within buildings, genetic population structure indicates both dispersal within buildings and multiple colonization events within each building. 16S rRNA is studied for understanding the bacterial microbiome community on cockroaches, and is used to quantify the abundance of bacterial operational taxonomic units (OTUs) found on the cockroaches. Bacterial microbiome diversity and ordination of OTUs are used to characterize the bacterial microbiome among the 30 samples from the same three buildings/cities. The results show a low but significant differentiation of bacterial community among three buildings and within one building. To test whether the genetic distance of German cockroaches within and among the three buildings is correlated with community distance among bacterial communities on the cockroaches, a Mantel test is implemented. The result of this test is negative, which indicates the lack of correlation between cockroach populations and bacterial communities. A laboratory test of the bacterial dispersal ability of German cockroaches is done by infecting cockroaches with fluorescence-marked E. coli. This test shows the strong bacterial dispersal ability of cockroaches. In conclusion, German cockroach structure is shaped by geographic separation, which doesn’t affect the bacterial community found on the same cockroach populations. These results have several important implications for control of cockroach infestations and for control of the spread of human disease. First, cockroaches are able to spread among within buildings and cockroaches also may colonize a building multiple time. This indicates that control efforts should aim to eliminate cockroaches from all apartments within a building to prevent recolonization from within. Residents should be informed of effective methods to prevent reintroduction from external sources. Second, cockroaches harbor several medically important human bacterial pathogens. Care should be taken not to interact with cockroaches to limit human infection. Third, because bacterial communities do not appear to be strongly shaped by cockroaches, researchers should investigate other mechanisms of bacterial dispersal

Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition, after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion's direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification

Assessment of habitat suitability and connectivity across the potential distribution landscape of the sambar (Rusa unicolor) in Southwest China

Habitat suitability assessment is the basis for wildlife conservation management and habitat restoration. It is a useful tool to understand the quality of wildlife habitat and its potential spatial distribution. In order to reveal the habitat suitability and connectivity of sambar (Rusa unicolor) to promote species and biodiversity conservation, this study collected records of sambar (Rusa unicolor) from over 2,000 camera traps in the forests of Southwest China in the past 5 years to assess the overall situation of their habitat. The results of the species distribution model revealed that the suitable habitat area for sambar in the five major mountain ranges (Minshan, Qionglai, Daxiangling, Xiaoxiangling, and Liangshan) in Southwest China is 18,231 km2, accounting for 17.02% of the total area. The most suitable habitat of sambar is primarily distributed in Qionglai, as well as the intersection areas of Daxiangling, Xiaoxiangling, and Minshan. The temperature annual range, temperature seasonality, elevation, and distance to road were important factors affecting the distribution of suitable habitat for sambar. Analysis of landscape pattern shows that there were 273 habitat patches, with a maximum patch area of 9,983 km2, accounting for 54.8% of the total suitable habitat area. However, the segmentation index and separation index of each habitat patch were 0.99 and 106.58, respectively, indicating a relatively high habitat fragmentation in the study area. The results of habitat connectivity analysis showed that the Qionglai mountains have the largest suitable habitat area and the highest connectivity among habitat patches. However, habitat connectivity between the five mountains is very low, suggesting that gene flow among these mountain ranges is probably limited. We therefore recommend strengthening protection of sambar and their habitat, with special attention to the establishment of corridors between the different mountain populations

Numerical Simulation of Dilution in Laser Metal Deposition by Powder Injection

Laser deposition is a method of depositing material by which a powdered material is melted and consolidated by use of a laser in order to coat part of a substrate or fabricate a near-net shape part. The development of an accurate predictive model for laser deposition is extremely complicated due to the multitude of process parameters and materials properties involved. In this work, the metal powder used in the laser cladding/deposition process is injected into the system by using a coaxial nozzle. The interaction of the metallic powder stream and the laser causes melting to occur, which is known as the melt pool. The metal is deposited onto a substrate; moving the substrate allows the melt pool to solidify and thus produces a track of solid metal. In cladding/deposition operations, dilution is often defined as the amount of intermixing of the deposit and substrate. In this process, it is desirable to have minimum dilution but at the same time to have a metallurgical bonding between the substrate and deposit. Therefore, it is very critical to understand and predict the degree of dilution in the process. In this study, a heat transfer and fluid flow model for laser deposition is developed to predict dilution under varying process parameters. The material for both substrates and the powder is Ti-6Al-4V, but 5% of steel powder was added to observe the actual degree of dilution. The laser used is a direct diode laser. Experimental validation of the predicted dilution is also presented

Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition, after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion’s direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification

Genetic and Chemical Engineering of Phages for Controlling Multidrug-Resistant Bacteria

Along with the excessive use of antibiotics, the emergence and spread of multidrug-resistant bacteria has become a public health problem and a great challenge vis-à-vis the control and treatment of bacterial infections. As the natural predators of bacteria, phages have reattracted researchers’ attentions. Phage therapy is regarded as one of the most promising alternative strategies to fight pathogens in the post-antibiotic era. Recently, genetic and chemical engineering methods have been applied in phage modification. Among them, genetic engineering includes the expression of toxin proteins, modification of host recognition receptors, and interference of bacterial phage-resistant pathways. Chemical engineering, meanwhile, involves crosslinking phage coats with antibiotics, antimicrobial peptides, heavy metal ions, and photothermic matters. Those advances greatly expand the host range of phages and increase their bactericidal efficiency, which sheds light on the application of phage therapy in the control of multidrug-resistant pathogens. This review reports on engineered phages through genetic and chemical approaches. Further, we present the obstacles that this novel antimicrobial has incurred

Comparison of a commercial ELISA and indirect hemagglutination assay with the modified agglutination test for detection of Toxoplasma gondii antibodies in giant panda (Ailuropoda melanoleuca)

Toxoplasma gondii is a worldwide-distributed zoonotic protozoan parasite which causes toxoplasmosis and has a significant effect on public health. In the giant panda (Ailuropoda melanoleuca), toxoplasmosis can cause asymptomatic infections, reproductive disorder and even death, which poses a serious threat to the conservation of this rare protected species. Therefore, serological investigation of T. gondii is essential to understanding its risk to giant pandas, however, there are no specific testing kits for giant pandas. Previous research has used MAT as the reference method for screening T. gondii, to investigate this further, this study focused on the agreement comparing of MAT with ELISA and IHA tests for detecting T. gondii antibodies in 100 blood samples from 55 captive giant pandas in Chengdu, China. The results showed 87.0%, 87.0%, 84.0%, samples were sero-positive for T. gondii using ELISA (kits a, b, c), respectively, while MAT and IHA tests were 84.0% and 9.0% sero-positive, respectively. There was no significant difference between MAT and the three ELISA kits and these two methods had substantial agreement (0.61 < қ ≤ 0.80). Meanwhile, there was a significant difference (P < 0.001) between MAT and IHA, and these two methods had only a slight agreement (қ ≤ 0.20). The relative sensitivity of the ELISA (kits a, b, c) were 89.0%, 91.5% and 95.1%, and the specificity were 86.7%, 80.0% and 80.0%, respectively, which showed these three ELISA kits all had great accuracy. It is suggested that MAT is the recommended test method for primary screening T. gondii in giant pandas and then verified by ELISA