Mechanical signatures of microbial biofilms in micropillar-embedded growth chambers

Biofilms are surface-attached communities of microorganisms embedded in an extracellular matrix and are essential for the cycling of organic matter in natural and engineered environments. They are also the leading cause of many infections, for example, those associated with chronic wounds and implanted medical devices. The extracellular matrix is a key biofilm component that determines its architecture and defines its physical properties. Herein, we used growth chambers embedded with micropillars to study the net mechanical forces (differential pressure) exerted during biofilm formation in situ. Pressure from the biofilm is transferred to the micropillars via the extracellular matrix, and reduction of major matrix components decreases the magnitude of micropillar deflections. The spatial arrangement of micropillar deflections caused by pressure differences in the different biofilm strains may potentially be used as mechanical signatures for biofilm characterization. Hence, we submit that micropillar-embedded growth chambers provide insights into the mechanical properties and dynamics of the biofilm and its matrix.Singapore. National Research Foundation (Singapore-MIT Alliance for Research and Technology (SMART)

Impacts of climate change on soybean production under different treatments of field experiments considering the uncertainty of general circulation models

Earth is faced with dramatic changes in the weather systems, which leads to climate change. Climate change affects water resources and crop production. In this study, five and seven general circulation models (GCMs) were respectively collected via the IPCC Fourth and Fifth Assessment Reports. Emission scenarios including B1, A1B, and A2 for AR4 and RCP2.6 and RCP8.5 for AR5 were applied to predict future climate change. The weighting method of mean observed temperature-precipitation (MOTP) was utilized to compute uncertainty related to different climate models. The scenario files made by ΔT and ΔP were applied to the downscaled model of LARS-WG to generate weighted multi-model ensemble means of temperature and precipitation for the period 2020–2039 centered on 2030s. These ensemble means were incorporated into the calibrated AquaCrop model to predict final yield and biomass. In this study, soybean data were applied for four different varieties under three irrigation treatments in field experiments carried out at Karaj Seed and Plant Improvement Institute in two successive years. However, the results of statistical analysis between the model output and observed data for all varieties and irrigation treatments in the calibration year (2010) and validation year (2011) were the same at the 95% confidence level. It is suggested that AquaCrop is a valid model to predict yield and biomass for the study area in the future. Furthermore, comparing future climatic variables to the historical period during the soybean growing season showed enhancement of these variables by the 2030s. The amplitude change of temperature was larger in AR5, whereas the amplitude change of precipitation and CO2 were larger in AR4. The soybean yield and biomass increased for all treatments in the 2030 s with positive correlation with the climatic variables. The maximum temperature represented the most significant correlation with yield and biomass for almost all treatments. Finally, soybeans might achieve an optimal threshold temperature in the future, leading to yield increases in the 2030s

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 201

3-(3-Bromo-4-methoxy­phen­yl)-1,5-diphenyl­pentane-1,5-dione

In the title compound, C24H21BrO3, the central bromo­methoxy­benzene ring forms dihedral angles of 63.6 (1) and 60.3 (1)° with the terminal phenyl rings, while the angle between the two phenyl rings is 25.8 (1)°. The crystal structure is stabilized by weak C—H⋯Br and C—H⋯O hydrogen bonds, and C—H⋯π and π–π stacking [centroid–centroid distance = 3.910 (3) Å] inter­actions

EXACT RUN LENGTH DISTRIBUTION OF THE DOUBLE SAMPLING X CHART WITH ESTIMATED PROCESS PARAMETERS

Since the run length distribution is generally highly skewed, a significant concern about focusing too much on the average run length (ARL) criterion is that we may miss some crucial information about a control chart’s performance. Thus it is important to investigate the entire run length distribution of a control chart for an in-depth understanding before implementing the chart in process monitoring. In this paper, the percentiles of the run length distribution for the double sampling (DS) X chart with estimated process parameters are computed. Knowledge of the percentiles of the run length distribution provides a more comprehensive understanding of the expected behaviour of the run length. This additional information includes the early false alarm, the skewness of the run length distribution, and the median run length (MRL). A comparison of the run length distribution between the optimal ARL-based and MRL-based DS X chart with estimated process parameters is presented in this paper. Examples of applications are given to aid practitioners to select the best design scheme of the DS X chart with estimated process parameters, based on their specific purpose

EXACT RUN LENGTH DISTRIBUTION OF THE DOUBLE SAMPLING X CHART WITH ESTIMATED PROCESS PARAMETERS

Since the run length distribution is generally highly skewed, a significant concern about focusing too much on the average run length (ARL) criterion is that we may miss some crucial information about a control chart’s performance. Thus it is important to investigate the entire run length distribution of a control chart for an in-depth understanding before implementing the chart in process monitoring. In this paper, the percentiles of the run length distribution for the double sampling (DS) X chart with estimated process parameters are computed. Knowledge of the percentiles of the run length distribution provides a more comprehensive understanding of the expected behaviour of the run length. This additional information includes the early false alarm, the skewness of the run length distribution, and the median run length (MRL). A comparison of the run length distribution between the optimal ARL-based and MRL-based DS X chart with estimated process parameters is presented in this paper. Examples of applications are given to aid practitioners to select the best design scheme of the DS X chart with estimated process parameters, based on their specific purpose

Immobilization of Saccharomyces Cerevisiae in Rice Hulls for Ethanol Production

The whole cell immobilization in ethanol fermentation can be done by using natural carriers or through synthetic carriers. All of these methods have the same purpose of retaining high cell concentrations within a certain defined region of space which leads to higher ethanol productivity. Lignocellulosic plant substance represents one of highly potential sources in ethanol production. Some studies have found that cellulosic substances substances can also be used as a natural carrier in cell immobilization by re-circulating pre-culture medium into a reactor. In this experiment, ricehulls without any treatment were used to immobilize Saccharomyces cerevisiae through semi solid state incubation combined with re-circulating pre-culture medium. The scanning electron microscopy (SEM) pictures of the carrier show that the yeast cells are absorbed and embedded to the rice hull pore. In liquid batch fermentation system with an initial sugar concentration of 50 g/L, nearly 100% total sugar was consumed after 48 hours. This resulted in an ethanol yield of 0.32 g ethanol/g glucose, which is 62.7% of the theoretical value. Ethanol productivity of 0.59 g/(L.h) is 2.3 fold higher than that of free cells which is 0.26 g/(L.h). An effort to reuse the immobilized cells in liquid fermentation system showed poor results due to cell desorption in the first batch which led to high sugar concentration inhibitory effect in the second batch fermentation. This might be solved by using semi solid fermentation process in the future work

From Heisenberg matrix mechanics to EBK quantization: theory and first applications

Despite the seminal connection between classical multiply-periodic motion and Heisenberg matrix mechanics and the massive amount of work done on the associated problem of semiclassical (EBK) quantization of bound states, we show that there are, nevertheless, a number of previously unexploited aspects of this relationship that bear on the quantum-classical correspondence. In particular, we emphasize a quantum variational principle that implies the classical variational principle for invariant tori. We also expose the more indirect connection between commutation relations and quantization of action variables. With the help of several standard models with one or two degrees of freedom, we then illustrate how the methods of Heisenberg matrix mechanics described in this paper may be used to obtain quantum solutions with a modest increase in effort compared to semiclassical calculations. We also describe and apply a method for obtaining leading quantum corrections to EBK results. Finally, we suggest several new or modified applications of EBK quantization.Comment: 37 pages including 3 poscript figures, submitted to Phys. Rev.

Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data

Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future