Bending and Breaking of Stripes in a Charge-Ordered Manganite

In complex electronic materials, coupling between electrons and the atomic lattice gives rise to remarkable phenomena, including colossal magnetoresistance and metal-insulator transitions. Charge-ordered phases are a prototypical manifestation of charge-lattice coupling, in which the atomic lattice undergoes periodic lattice displacements (PLDs). Here we directly map the picometer scale PLDs at individual atomic columns in the room temperature charge-ordered manganite Bi$_{0.35}$Sr$_{0.18}$Ca$_{0.47}$MnO$_3$ using aberration corrected scanning transmission electron microscopy (STEM). We measure transverse, displacive lattice modulations of the cations, distinct from existing manganite charge-order models. We reveal locally unidirectional striped PLD domains as small as $\sim$5 nm, despite apparent bidirectionality over larger length scales. Further, we observe a direct link between disorder in one lattice modulation, in the form of dislocations and shear deformations, and nascent order in the perpendicular modulation. By examining the defects and symmetries of PLDs near the charge-ordering phase transition, we directly visualize the local competition underpinning spatial heterogeneity in a complex oxide.Comment: Main text: 20 pages, 4 figures. Supplemental Information: 27 pages, 14 figure

Commensurate Stripes and Phase Coherence in Manganites Revealed with Cryogenic Scanning Transmission Electron Microscopy

Incommensurate charge order in hole-doped oxides is intertwined with exotic phenomena such as colossal magnetoresistance, high-temperature superconductivity, and electronic nematicity. Here, we map at atomic resolution the nature of incommensurate order in a manganite using scanning transmission electron microscopy at room temperature and cryogenic temperature ($\sim$ 93K). In diffraction, the ordering wavevector changes upon cooling, a behavior typically associated with incommensurate order. However, using real space measurements, we discover that the underlying ordered state is lattice-commensurate at both temperatures. The cations undergo picometer-scale ($\sim$6-11 pm) transverse displacements, which suggests that charge-lattice coupling is strong and hence favors lattice-locked modulations. We further unearth phase inhomogeneity in the periodic lattice displacements at room temperature, and emergent phase coherence at 93K. Such local phase variations not only govern the long range correlations of the charge-ordered state, but also results in apparent shifts in the ordering wavevector. These atomically-resolved observations underscore the importance of lattice coupling and provide a microscopic explanation for putative "incommensurate" order in hole-doped oxides

Autonomous 3D Urban and Complex Terrain Geometry Generation and Micro-Climate Modelling Using CFD and Deep Learning

Sustainable building design requires a clear understanding and realistic modelling of the complex interaction between climate and built environment to create safe and comfortable outdoor and indoor spaces. This necessitates unprecedented urban climate modelling at high temporal and spatial resolution. The interaction between complex urban geometries and the microclimate is characterized by complex transport mechanisms. The challenge to generate geometric and physics boundary conditions in an automated manner is hindering the progress of computational methods in urban design. Thus, the challenge of modelling realistic and pragmatic numerical urban micro-climate for wind engineering, environmental, and building energy simulation applications should address the complexity of the geometry and the variability of surface types involved in urban exposures. The original contribution to knowledge in this research is the proposed an end-to-end workflow that employs a cutting-edge deep learning model for image segmentation to generate building footprint polygons autonomously and combining those polygons with LiDAR data to generate level of detail three (LOD3) 3D building models to tackle the geometry modelling issue in climate modelling and solar power potential assessment. Urban and topography geometric modelling is a challenging task when undertaking climate model assessment. This paper describes a deep learning technique that is based on U-Net architecture to automate 3D building model generation by combining satellite imagery with LiDAR data. The deep learning model used registered a mean squared error of 0.02. The extracted building polygons were extruded using height information from corresponding LiDAR data. The building roof structures were also modelled from the same point cloud data. The method used has the potential to automate the task of generating urban scale 3D building models and can be used for city-wide applications. The advantage of applying a deep learning model in an image processing task is that it can be applied to a new set of input image data to extract building footprint polygons for autonomous application once it has been trained. In addition, the model can be improved over time with minimum adjustments when an improved quality dataset is available, and the trained parameters can be improved further building on previously learned features. Application examples for pedestrian level wind and solar energy availability assessment as well as modeling wind flow over complex terrain are presented

“Quality teaches you how to use water. It doesn’t provide a water pump”: a qualitative study of context and mechanisms of action in an Ethiopian quality improvement program

Background Quality improvement collaboratives are a common approach to bridging the quality-of-care gap, but little is known about implementation in low-income settings. Implementers rarely consider mechanisms of change or the role of context, which may explain collaboratives’ varied impacts. Methods To understand mechanisms and contextual influences we conducted 55 in-depth interviews with staff from four health centres and two hospitals involved in quality improvement collaboratives in Ethiopia. We also generated control charts for selected indicators to explore any impacts of the collaboratives. Results The cross facility learning sessions increased the prominence and focus on quality, allowed learning from experts and peers and were motivational through public recognition of success or a desire to emulate peers. Within facilities, new structures and processes were created. These were fragile and sometimes alienating to those outside the improvement team. The trusted and respected mentors were important for support, motivation and accountability. Where mentor visits were infrequent or mentors less skilled, team function was impacted. These mechanisms were more prominent, and quality improvement more functional, in facilities with strong leadership and pre-existing good teamwork; as staff had shared goals, an active approach to problems and were more willing and able to be flexible to implement change ideas. Quality improvement structures and processes were more likely to be internally driven and knowledge transferred to other staff in these facilities, which reduced the impact of staff turnover and increased buy-in. In facilities which lacked essential inputs, staff struggled to see how the collaborative could meaningfully improve quality and were less likely to have functioning quality improvement. The unexpected civil unrest in one region strongly disrupted the health system and the collaborative. These contextual issues were fluid, with multiple interactions and linkages. Conclusions The study confirms the need to carefully consider context in the implementation of quality improvement collaboratives. Facilities that implement quality improvement successfully may be those that already have characteristics that foster quality. Quality improvement may be alienating to those outside of the improvement team and implementers should not assume the organic spread or transfer of quality improvement knowledge

Advance in grain legumes genetic transformation: The case of GM pea and cowpea

Grain legumes are socio-economically important crops playing a substantial role in providing dietary protein for millions of households in the world. As multipurpose crops, they are used for different purposes such as food and feed. They also fix atmospheric nitrogen contributing to the sustainability of farming system by enriching soil fertility and maintaining the productivity of agricultural land. However, different production factors, such as insect pests and diseases, have limited the productivity of grain legumes both in field and during the storage and are impacting their contribution to nutrition security and poverty reduction. Furthermore, in the current trend of climate change, there is an increasing pressure on plant breeders to develop climate-smart varieties of crops with multiple traits against the different production factors. In order to enhance the economic and social contribution of grain legumes, genetic transformation approaches have been used to develop transgenic lines with new traits such as resistance to insects and diseases as well as tolerance to drought. In this paper, the experience and result of pea and cowpea Agrobacterium-mediated transformation will be presented. Special emphasis will be given to the success and challenges of transgenic insect resistance and its importance in these two important grain legumes. Based on insect bioassay tests, the level of insect resistance in some of the transgenic lines will be presented against that of none transgenic lines. Finally, recommendation will also be discussed for future genetic transformation to develop climate-smart variety of transgenic grain legumes

Sample-ready multiplex qPCR assay for detection of malaria

BACKGROUND: Microscopy and antigen detecting rapid diagnostic tests are the diagnostic tests of choice in management of clinical malaria. However, due to their limitations, the need to utilize more sensitive methods such as real-time PCR (qPCR) is evident as more studies are now utilizing molecular methods in detection of malaria. Some of the challenges that continue to limit the widespread utilization of qPCR include lack of assay standardization, assay variability, risk of contamination, and the need for cold-chain. Lyophilization of molecular assays can overcome some of these limitations and potentially enable widespread qPCR utilization. METHODS: A recently published multiplex malaria qPCR assay was lyophilized by freezing drying into Sample-Ready™ format (MMSR). MMSR assay contained all the required reagents for qPCR including primers and probes, requiring only the addition of water and sample to perform qPCR. The performance of the MMSR assay was compared to the non-freeze dried, “wet” assay. Stability studies were done by maintaining the MMSR assays at four different ambient temperatures of 4°C, room temperature (RT), 37°C and 42°C over a period of 42 days, tested at seven-day intervals. Plasmodium falciparum and Plasmodium vivax DNAs were used for analysis of the MMSR assay either as single or mixed parasites, at two different concentrations. The C(T) values and the standard deviations (SD) were used in the analysis of the assay performance. RESULTS: The limit of detection for the MMSR assay was 0.244 parasites/μL for Plasmodium spp. (PLU) and P. falciparum (FAL) assay targets compared to “wet” assay which was 0.39 and 3.13 parasites/μL for PLU and FAL assay targets, respectively. The MMSR assay performed with high efficiencies similar to those of the “wet” assay and was stable at 37°C for 42 days, with estimated shelf-life of 5 months. When used to analyse field clinical samples, MMSR assay performed with 100% sensitivity and specificity compared to the “wet” assay. CONCLUSION: The MMSR assay has the same robust performance characteristics as the “wet” assay and is highly stable. Availability of MMSR assay allows flexibility and provides an option in choosing assay for malaria diagnostics depending on the application, needs and budget

Podoconiosis and soil-transmitted helminths (STHs): double burden of neglected tropical diseases in Wolaita zone, rural southern Ethiopia

Background Both podoconiosis and soil-transmitted helminth (STH) infections occur among barefoot people in areas of extreme poverty; however, their co-morbidity has not previously been investigated. We explored the overlap of STH infection and podoconiosis in Southern Ethiopia and quantified their separate and combined effects on prevalent anemia and hemoglobin levels in podoconiosis patients and health controls from the same area. Methods and Principal Findings A two-part comparative cross-sectional study was conducted in Wolaita zone, southern Ethiopia. Data were collected from adult patients presenting with clinically confirmed podoconiosis, and unmatched adult neighborhood controls living in the same administrative area. Information on demographic and selected lifestyle factors was collected using interviewer-administered questionnaires. Stool samples were collected and examined qualitatively using the modified formalin-ether sedimentation method. Hemoglobin level was determined using two different methods: hemoglobinometer and automated hematology analyzer. A total of 913 study subjects (677 podoconiosis patients and 236 controls) participated. The prevalence of any STH infection was 47.6% among patients and 33.1% among controls (p<0.001). The prevalence of both hookworm and Trichuris trichiura infections was significantly higher in podoconiosis patients than in controls (AOR 1.74, 95% CI 1.25 to2.42, AOR 6.53, 95% CI 2.34 to 18.22, respectively). Not wearing shoes and being a farmer remained significant independent predictors of infection with any STH. There was a significant interaction between STH infection and podoconiosis on reduction of hemoglobin level (interaction p value = 0.002). Conclusions Prevalence of any STH and hookworm infection was higher among podoconiosis patients than among controls. A significant reduction in hemoglobin level was observed among podoconiosis patients co-infected with hookworm and ‘non-hookworm STH’. Promotion of consistent shoe-wearing practices may have double advantages in controlling both podoconiosis and hookworm infection in the study area