Surface expressions of discontinuities, and the estimation of their 3-D orientations using combined LiDAR and optical imaging

The importance of the collection and analysis of data on discontinuities cannot be overemphasized. Problems which include sampling difficulties, risks, limited access to rock faces and exposures, and the delay in data collection has led to a high need for data collection tools and analysis techniques that can overcome these problems. Discontinuities manifest themselves as either traces or as facets. Traces are linear features that intersect with both the discontinuity and the rock cut. Facets are the actual discontinuity surfaces that are exposed in the rock cut. Facets can be natural or induced. Identifying a facet as either natural or induced can sometimes be very difficult and can affect analytical results. The orientation of facets can be estimated from LiDAR point cloud. The orientation of traces can be estimated from optical imaging methods. LiDAR scanning alone cannot measure traces, neither can optical imaging methods measure facets. This is complicated by the fact that both facets and \u27traces\u27 are often present in the same rock cut, making the selection of an appropriate methodology or tool very difficult if not impossible. The set of traces in a rock mass usually belong to a set of facets of the same rock mass. These set of traces and facets can be combined either by the use of stereonets or by the equation of the angle between two lines. This research has provided a simple method by which the orientation of facets can be estimated from LiDAR point cloud. It has also provided a simple method by which the orientation of traces could be estimated from 2-D images. Additionally, this research has provided a reasonable way by which professionals could differentiate between traces, natural, and induced facets. Finally, this research has provided a methodology by which traces from optical images can be combined to facets from point cloud data --Abstract, page iii

Evaluating the Effectiveness of Alternative Extension Methods: Triple-Bag Storage of Cowpeas by Small-Scale Farmers in West Africa

This study examined two questions related to the adoption of triple-bag storage technology for farmers storing cowpeas in West Africa. First the effect of an extension program, focused on village demonstrations, on adoption was considered. Second, the effect of radio messages to augment this extension program was analyzed. The results indicate that adoption was positively affected by the extension program and radio messages do augment the effectiveness.Effective extension methods, cowpeas, hermetic storage, Teaching/Communication/Extension/Profession,

Suspended Sediment Transport Dynamics and Sediment Yields in Relation to Watershed Characteristics, Upper Green River Basin, Kentucky

Sediment delivery is a major problem in the Green River, Kentucky, home of 71 of the state’s 103 known mussel species and 151 fish species. The river also provides water for many of its surrounding counties. This research focuses on how suspended sediment loads, grain size, and sediment concentration during runoff events are related to watershed characteristics. The research characterized suspended sediment loads, grain size, and sediment concentration during runoff events and how they were related to watershed characteristics such as hydro-climatic regime, watershed size, geology and soils, topography and landuse conditions and land cover conditions. The study focused on Brush Creek and Pitman Creek watersheds in the Upper Green River Basin. This research can help in the planning and development of effective environmental strategies by screening out mitigation measures that would not be effective for implementation to minimize sediment load and suspended sediment concentration in the Green River, thereby improving the water quality of the river. Water quality was monitored using data sondes positioned at selected sites in the two watersheds. Water samples were collected during turbidity thresholds of 100 NTU and analyzed for suspended sediment concentrations. Regression models between ‘discharge and stage’ and also between ‘average turbidity and suspended sediment concentration’ were formulated and load estimates were made and compared. Four sets of samples were collected, two at Brush Creek on 11 April (Brush Creek’s event 1) and 3 May (Brush Creek’s event 2) and the other two at Pitman Creek on the 12 February (Pitman Creek’s event 1) and 3 March (Pitman Creek’s event 2) all in the year 2008. The suspended sediment samples collected for all four events were well graded but had relatively more silt than clay and sand. This could be due to the fact that more time and energy was needed to break the bonds in clay minerals or particles and also to the fact that more energy was also needed to transport sand compared to silt. Brush Creek watershed’s particles had smaller grain sizes than Pitman Creek watershed’s particles. All four events showed clockwise hysteresis indicating that most of the sediments from both watersheds during the events were derived from the bed and banks of the channel or area adjacent to the channel. The 11 April event (Brush Creek’s event 1) produced an estimated load of 1.1 x 105 kg and a sediment yield of 5.3 x 102 kg/km2. The 3 May event (Brush Creek’s event 2) produced an estimated load of 3.8 x 104 kg and a sediment yield of 1.8 x 102 kg/km2. Brush Creek watershed’s estimated load for the period compared was 4.9 x 105 kg and a sediment yield of 2.3 x 103 kg/km2 (53 kg/km2/day). The 12 February event (Pitman Creek’s event 1) produced an estimated load of 2.9 x 105 kg and a sediment yield of 8.4 x 102 kg/km2. The 3 March event (Pitman Creek’s event 2) produced an estimated load of 5.7 x 105 kg and a sediment yield of 1.6 x 103 kg/km2. Pitman Creek watershed’s estimated load for the period compared was 1.1 x 106 kg and a sediment yield of 3.1 x 103 kg/km2 (71 kg/km2/day). Pitman Creek watershed’s higher number of stream network per unit area, its high elevation and relief, its high percentage of erodible soil per unit area, its lesser area of protection of erodible soil by its vegetation compared to Brush Creek watershed’s are responsible for its higher sediment load and yield

Evaluation of Rock Fall Hazards using LiDAR Technology

Lidar (light detection and ranging) is a relatively new technology that is being used in many aspects of geology and engineering, including researching the potential for rock falls on highway rock cuts. At Missouri University of Science and Technology, we are developing methods for measuring joint orientations remotely and quantifying the raveling process. Measuring joint orientations remotely along highways is safer, more accurate and can result in larger and more accurate data sets, including measurements from otherwise inaccessible areas. Measuring the nature of rock raveling will provide the data needed to begin the process of modeling the rock raveling process. In both cases, terrestrial lidar scanning is used to generate large point clouds of coordinate triplets representing the surface of the rock cut. Automated algorithms have been developed to organize the lidar data, register successive images without survey control, and removal of vegetation and non-rock artifacts. In the first case, we look for planar elements, identify the plane and calculate the orientations. In the second case, we take a series of scans over time and use sophisticated change detection algorithms to calculate the numbers and volumes of rock that has fallen off the rock face

What's normal? Oligosaccharide concentrations and profiles in milk produced by healthy women vary geographically.

Background: Human milk is a complex fluid comprised of myriad substances, with one of the most abundant substances being a group of complex carbohydrates referred to as human milk oligosaccharides (HMOs). There has been some evidence that HMO profiles differ in populations, but few studies have rigorously explored this variability.Objectives: We tested the hypothesis that HMO profiles differ in diverse populations of healthy women. Next, we examined relations between HMO and maternal anthropometric and reproductive indexes and indirectly examined whether differences were likely related to genetic or environmental variations.Design: In this cross-sectional, observational study, milk was collected from a total of 410 healthy, breastfeeding women in 11 international cohorts and analyzed for HMOs by using high-performance liquid chromatography.Results: There was an effect of the cohort (P 4 times higher in milk collected in Sweden than in milk collected in rural Gambia (mean ± SEM: 473 ± 55 compared with 103 ± 16 nmol/mL, respectively; P < 0.05), and disialyllacto-N-tetraose (DSLNT) concentrations ranged from 216 ± 14 nmol/mL (in Sweden) to 870 ± 68 nmol/mL (in rural Gambia) (P < 0.05). Maternal age, time postpartum, weight, and body mass index were all correlated with several HMOs, and multiple differences in HMOs [e.g., lacto-N-neotetrose and DSLNT] were shown between ethnically similar (and likely genetically similar) populations who were living in different locations, which suggests that the environment may play a role in regulating the synthesis of HMOs.Conclusions: The results of this study support our hypothesis that normal HMO concentrations and profiles vary geographically, even in healthy women. Targeted genomic analyses are required to determine whether these differences are due at least in part to genetic variation. A careful examination of sociocultural, behavioral, and environmental factors is needed to determine their roles in this regard. This study was registered at clinicaltrials.gov as NCT02670278

Comparison of Two Approaches for the Metataxonomic Analysis of the Human Milk Microbiome.

Recent work has demonstrated the existence of large inter-individual and inter-population variability in the microbiota of human milk from healthy women living across variable geographical and socio-cultural settings. However, no studies have evaluated the impact that variable sequencing approaches targeting different 16S rRNA variable regions may have on the human milk microbiota profiling results. This hampers our ability to make meaningful comparisons across studies. In this context, the main purpose of the present study was to re-process and re-sequence the microbiome in a large set of human milk samples (n = 412) collected from healthy women living at diverse international sites (Spain, Sweden, Peru, United States, Ethiopia, Gambia, Ghana and Kenya), by targeting a different 16S rRNA variable region and reaching a larger sequencing depth. Despite some differences between the results obtained from both sequencing approaches were notable (especially regarding alpha and beta diversities and Proteobacteria representation), results indicate that both sequencing approaches revealed a relatively consistent microbiota configurations in the studied cohorts. Our data expand upon the milk microbiota results we previously reported from the INSPIRE cohort and provide, for the first time across globally diverse populations, evidence of the impact that different DNA processing and sequencing approaches have on the microbiota profiles obtained for human milk samples. Overall, our results corroborate some similarities regarding the microbial communities previously reported for the INSPIRE cohort, but some differences were also detected. Understanding the impact of different sequencing approaches on human milk microbiota profiles is essential to enable meaningful comparisons across studies. Clinical Trial Registration: www.clinicaltrials.gov, identifier NCT02670278

Key genetic variants associated with variation of milk oligosaccharides from diverse human populations

Human milk oligosaccharides (HMO), the third most abundant component of human milk, are thought to be important contributors to infant health. Studies have provided evidence that geography, stage of lactation, and Lewis and secretor blood groups are associated with HMO profile. However, little is known about how variation across the genome may influence HMO composition among women in various populations. In this study, we performed genome-wide association analyses of 395 women from 8 countries to identify genetic regions associated with 19 different HMO. Our data support FUT2 as the most significantly associated (P < 4.23-9 to P < 4.5-70) gene with seven HMO and provide evidence of balancing selection for FUT2. Although polymorphisms in FUT3 were also associated with variation in lacto-N-fucopentaose II and difucosyllacto-N-tetrose, we found little evidence of selection on FUT3. To our knowledge, this is the first report of the use of genome-wide association analyses on HMO

Variation in Human Milk Composition Is Related to Differences in Milk and Infant Fecal Microbial Communities.

Previously published data from our group and others demonstrate that human milk oligosaccharide (HMOs), as well as milk and infant fecal microbial profiles, vary by geography. However, little is known about the geographical variation of other milk-borne factors, such as lactose and protein, as well as the associations among these factors and microbial community structures in milk and infant feces. Here, we characterized and contrasted concentrations of milk-borne lactose, protein, and HMOs, and examined their associations with milk and infant fecal microbiomes in samples collected in 11 geographically diverse sites. Although geographical site was strongly associated with milk and infant fecal microbiomes, both sample types assorted into a smaller number of community state types based on shared microbial profiles. Similar to HMOs, concentrations of lactose and protein also varied by geography. Concentrations of HMOs, lactose, and protein were associated with differences in the microbial community structures of milk and infant feces and in the abundance of specific taxa. Taken together, these data suggest that the composition of human milk, even when produced by relatively healthy women, differs based on geographical boundaries and that concentrations of HMOs, lactose, and protein in milk are related to variation in milk and infant fecal microbial communities

Corrigendum: What's Normal? Microbiomes in Human Milk and Infant Feces Are Related to Each Other but Vary Geographically: The INSPIRE Study

A correction has been made to the Materials and Methods section, subsection Extraction of DNA fromMilk, paragraph 2, The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated

What's Normal? Microbiomes in Human Milk and Infant Feces Are Related to Each Other but Vary Geographically: The INSPIRE Study

Background: Microbial communities in human milk and those in feces from breastfed infants vary within and across populations. However, few researchers have conducted cross-cultural comparisons between populations, and little is known about whether certain “core” taxa occur normally within or between populations and whether variation in milk microbiome is related to variation in infant fecal microbiome. The purpose of this study was to describe microbiomes of milk produced by relatively healthy women living at diverse international sites and compare these to the fecal microbiomes of their relatively healthy infants. Methods: We analyzed milk (n = 394) and infant feces (n = 377) collected from mother/infant dyads living in 11 international sites (2 each in Ethiopia, The Gambia, and the US; 1 each in Ghana, Kenya, Peru, Spain, and Sweden). The V1-V3 region of the bacterial 16S rRNA gene was sequenced to characterize and compare microbial communities within and among cohorts. Results: Core genera in feces were Streptococcus, Escherichia/Shigella, and Veillonella, and in milk were Streptococcus and Staphylococcus, although substantial variability existed within and across cohorts. For instance, relative abundance of Lactobacillus was highest in feces from rural Ethiopia and The Gambia, and lowest in feces from Peru, Spain, Sweden, and the US; Rhizobium was relatively more abundant in milk produced by women in rural Ethiopia than all other cohorts. Bacterial diversity also varied among cohorts. For example, Shannon diversity was higher in feces from Kenya than Ghana and US-California, and higher in rural Ethiopian than Ghana, Peru, Spain, Sweden, and US-California. There were limited associations between individual genera in milk and feces, but community-level analyses suggest strong, positive associations between the complex communities in these sample types. Conclusions: Our data provide additional evidence of within- and among-population differences in milk and infant fecal bacterial community membership and diversity and support for a relationship between the bacterial communities in milk and those of the recipient infant's feces. Additional research is needed to understand environmental, behavioral, and genetic factors driving this variation and association, as well as its significance for acute and chronic maternal and infant health