Patterning and manipulating microparticles into a three-dimensional matrix using standing surface acoustic waves

A method based on standing surface acoustic waves (SSAWs) is proposed to pattern and manipulate microparticles into a three-dimensional (3D) matrix inside a microchamber. An optical prism is used to observe the 3D alignment and patterning of the microparticles in the vertical and horizontal planes simultaneously. The acoustic radiation force effectively patterns the microparticles into lines of 3D space or crystal-lattice-like matrix patterns. A microparticle can be positioned precisely at a specified vertical location by balancing the forces of acoustic radiation, drag, buoyancy, and gravity acting on the microparticle. Experiments and finite-element numerical simulations both show that the acoustic radiation force increases gradually from the bottom of the chamber to the top, and microparticles can be moved up or down simply by adjusting the applied SSAW power. Our method has great potential for acoustofluidics applications, building the large-scale structures associated with biological objects and artificial neuron networks

Preparation and characterisation of manganese and iron compounds as potential control-release foliar fertilisers

Nanoscale crystals containing manganese and iron as potential foliar fertilizers have been further investigated with the experience accumulated from previous research on potential zinc foliar fertilizer. Compared to Zn(II), Mn(II) and Fe(II) are easily oxidisable in ambient environment, adding stricter criteria to compound selection to prevent oxidation. Adoption of phosphate buffer saline system and chelate have been proposed as the solution and extensively assessed in this paper. After quick co-precipitation, as-prepared crystals were characterised via XRD, FTIR, SEM, TEM, elemental analysis, and AAS to confirm the compositions and two-dimensional nanoscale morphology and assess the nutrient ion release and aqueous stability. In particular, the available Mn concentration in manganese ammonium phosphate and manganese oxalate suspensions was similar to 10 and similar to 110 mg/L, respectively. In comparison, ferrous ammonium phosphate and ferrous oxalate suspensions contained similar to 10 and similar to 30 mg/L of iron ions, respectively. Therefore, these suspensions can all be used as long-term foliar fertilizers for the correction of Mn and Fe deficiency in plants

Preparation and Foliar Application of Oligochitosan - Nanosilica on the Enhancement of Soybean Seed Yield

Oligochitosan with weight average molecu-lar weight (Mw) of 5000 g/mol was prepared by gamma Co-60 radiation degradation of 4% chitosan solution containing 0.5% H2O2 at 21 kGy. Nanosilica with size of 10 – 30 nm was synthesized by calcination of acid treated rice husk at 700o C for 2 h. The mixture of 2% oligo-chitosan-2% nanosilica was prepared by dispersion of nanosilica in oligochitosan solution. Oligochitosan, nanosilica and their mixture were characterized by gel permeation chromatography (GPC), transmission electr-on microscopy (TEM), X-ray diffraction (XRD), energy dispersive x-ray spectroscopy (EDX), Ultraviolet-visible spectroscopy (UV-Vis), and Furrier transform infrared spectroscopy (FT-IR). Effect of foliar application of oli-gochitosan and oligochitosan-nanosilica on soybean seed yield was conducted in experimental field. Results indi-cated that soybean seed yield increased 10.5 and 17.0% for oligochitosan and oligochitosan-nanosilica, respect-tively for the control. Radiation degraded oligo-chitosan and its mixture with nanosilica can be potentially used for cultivation of soybean with enhanced seed yield

An experimental study of combining evolutionary algorithms with KD-tree to solving dynamic optimisation problems

This paper studies the idea of separating the explored and unexplored regions in the search space to improve change detection and optima tracking. When an optimum is found, a simple sampling technique is used to estimate the basin of attraction of that optimum. This estimated basin is marked as an area already explored. Using a special tree-based data structure named KD-Tree to divide the search space, all explored areas can be separated from unexplored areas. Given such a division, the algorithm can focus more on searching for unexplored areas, spending only minimal resource on monitoring explored areas to detect changes in explored regions. The experiments show that the proposed algorithm has competitive performance, especially when change detection is taken into account in the optimisation process. The new algorithm was proved to have less computational complexity in term of identifying the appropriate sub-population/region for each individual. We also carry out investigations to find out why the algorithm performs well. These investigations reveal a positive impact of using the KD-Tree

Understanding the groups of care transition strategies used by U.S. hospitals: An application of factor analytic and latent class methods

BACKGROUND: After activation of the Hospital Readmission Reduction Program (HRRP) in 2012, hospitals nationwide experimented broadly with the implementation of Transitional Care (TC) strategies to reduce hospital readmissions. Although numerous evidence-based TC models exist, they are often adapted to local contexts, rendering large-scale evaluation difficult. Little systematic evidence exists about prevailing implementation patterns of TC strategies among hospitals, nor which strategies in which combinations are most effective at improving patient outcomes. We aimed to identify and define combinations of TC strategies, or groups of transitional care activities, implemented among a large and diverse cohort of U.S. hospitals, with the ultimate goal of evaluating their comparative effectiveness. METHODS: We collected implementation data for 13 TC strategies through a nationwide, web-based survey of representatives from short-term acute-care and critical access hospitals (N = 370) and obtained Medicare claims data for patients discharged from participating hospitals. TC strategies were grouped separately through factor analysis and latent class analysis. RESULTS: We observed 348 variations in how hospitals implemented 13 TC strategies, highlighting the diversity of hospitals\u27 TC strategy implementation. Factor analysis resulted in five overlapping groups of TC strategies, including those characterized by 1) medication reconciliation, 2) shared decision making, 3) identifying high risk patients, 4) care plan, and 5) cross-setting information exchange. We determined that the groups suggested by factor analysis results provided a more logical grouping. Further, groups of TC strategies based on factor analysis performed better than the ones based on latent class analysis in detecting differences in 30-day readmission trends. CONCLUSIONS: U.S. hospitals uniquely combine TC strategies in ways that require further evaluation. Factor analysis provides a logical method for grouping such strategies for comparative effectiveness analysis when the groups are dependent. Our findings provide hospitals and health systems 1) information about what groups of TC strategies are commonly being implemented by hospitals, 2) strengths associated with the factor analysis approach for classifying these groups, and ultimately, 3) information upon which comparative effectiveness trials can be designed. Our results further reveal promising targets for comparative effectiveness analyses, including groups incorporating cross-setting information exchange

Acoustofluidic closed-loop control of microparticles and cells using standing surface acoustic waves

Precise, automatic and reliable position control of micro-objects such as single particles, biological cells or bio-organisms is critical for applications in biotechnology and tissue engineering. However, conventional acoustofluidic techniques generally lack reliability and automation capability thus are often incapable of building an efficient and automated system where the biological cells need to be precisely manipulated in three dimensions (3D). To overcome these limitations, we developed an acoustofluidic closed-loop control system which is combined with computer vision techniques and standing surface acoustic waves (SSAWs) to implement selective, automatic and precise position control of an object, such as a single cell or microparticle in a microfluidic chamber. Position of the object is in situ extracted from living images that are captured from a video camera. By utilizing the closed-loop control strategy, the object is precisely moved to the desired location in 3D patterns or along designed trajectories by manipulating the phase angle and power signal of the SSAWs. Controlling of breast cancer cells has been conducted to verify the principle and biocompatibility of the control system. This system could be employed to build an automatic system for cell analysis, cell isolation, self-assembling of materials into complex microstructures, or lab-on-chip and organ-on-chip applications

Improving Evidence-Based Grouping of Transitional Care Strategies in Hospital Implementation Using Statistical Tools and Expert Review

BACKGROUND: As health systems transition to value-based care, improving transitional care (TC) remains a priority. Hospitals implementing evidence-based TC models often adapt them to local contexts. However, limited research has evaluated which groups of TC strategies, or transitional care activities, commonly implemented by hospitals correspond with improved patient outcomes. In order to identify TC strategy groups for evaluation, we applied a data-driven approach informed by literature review and expert opinion. METHODS: Based on a review of evidence-based TC models and the literature, focus groups with patients and family caregivers identifying what matters most to them during care transitions, and expert review, the Project ACHIEVE team identified 22 TC strategies to evaluate. Patient exposure to TC strategies was measured through a hospital survey (N = 42) and prospective survey of patients discharged from those hospitals (N = 8080). To define groups of TC strategies for evaluation, we performed a multistep process including: using ACHIEVE\u27S prior retrospective analysis; performing exploratory factor analysis, latent class analysis, and finite mixture model analysis on hospital and patient survey data; and confirming results through expert review. Machine learning (e.g., random forest) was performed using patient claims data to explore the predictive influence of individual strategies, strategy groups, and key covariates on 30-day hospital readmissions. RESULTS: The methodological approach identified five groups of TC strategies that were commonly delivered as a bundle by hospitals: 1) Patient Communication and Care Management, 2) Hospital-Based Trust, Plain Language, and Coordination, 3) Home-Based Trust, Plain language, and Coordination, 4) Patient/Family Caregiver Assessment and Information Exchange Among Providers, and 5) Assessment and Teach Back. Each TC strategy group comprises three to six, non-mutually exclusive TC strategies (i.e., some strategies are in multiple TC strategy groups). Results from random forest analyses revealed that TC strategies patients reported receiving were more important in predicting readmissions than TC strategies that hospitals reported delivering, and that other key co-variates, such as patient comorbidities, were the most important variables. CONCLUSION: Sophisticated statistical tools can help identify underlying patterns of hospitals\u27 TC efforts. Using such tools, this study identified five groups of TC strategies that have potential to improve patient outcomes

PomBase – the scientific resource for fission yeast

The fission yeast Schizosaccharomyces pombe has become well established as a model species for studying conserved cell-level biological processes, especially the mechanics and regulation of cell division. PomBase integrates the S. pombe genome sequence with traditional genetic, molecular and cell biological experimental data as well as the growing body of large datasets generated by emerging high-throughput methods. This chapter provides insight into the curation philosophy and data organization at PomBase, and provides a guide to using PomBase for infrequent visitors and anyone considering exploring S. pombe in their research

A <i>Herschel</i> and BIMA study of the sequential star formation near the W 48A H II region

We present the results of Herschel HOBYS (Herschel imaging survey of OB Young Stellar objects) photometric mapping combined with Berkeley Illinois Maryland Association (BIMA) observations and additional archival data, and perform an in-depth study of the evolutionary phases of the star-forming clumps in W 48A and their surroundings. Age estimates for the compact sources were derived from bolometric luminosities and envelope masses, which were obtained from the dust continuum emission, and agree within an order of magnitude with age estimates from molecular line and radio data. The clumps in W 48A are linearly aligned by age (east-old to west-young): we find a ultra-compact (UC) H II region, a young stellar object (YSO) with class II methanol maser emission, a YSO with a massive outflow and finally the NH2D prestellar cores from Pillai et al. This remarkable positioning reflects the (star) formation history of the region. We find that it is unlikely that the star formation in the W 48A molecular cloud was triggered by the UC H II region and discuss the Aquila supershell expansion as a major influence on the evolution of W 48A. We conclude that the combination of Herschel continuum data with interferometric molecular line and radio continuum data is important to derive trustworthy age estimates and interpret the origin of large-scale structures through kinematic information

Model-independent search for CP violation in D0→K−K+π−π+ and D0→π−π+π+π− decays

A search for CP violation in the phase-space structures of D0 and View the MathML source decays to the final states K−K+π−π+ and π−π+π+π− is presented. The search is carried out with a data set corresponding to an integrated luminosity of 1.0 fb−1 collected in 2011 by the LHCb experiment in pp collisions at a centre-of-mass energy of 7 TeV. For the K−K+π−π+ final state, the four-body phase space is divided into 32 bins, each bin with approximately 1800 decays. The p-value under the hypothesis of no CP violation is 9.1%, and in no bin is a CP asymmetry greater than 6.5% observed. The phase space of the π−π+π+π− final state is partitioned into 128 bins, each bin with approximately 2500 decays. The p-value under the hypothesis of no CP violation is 41%, and in no bin is a CP asymmetry greater than 5.5% observed. All results are consistent with the hypothesis of no CP violation at the current sensitivity