Infrared and infrared emission spectroscopy of nesquehonite Mg(OH)(HCO3)•2H2O : implications for the formula of nesquehonite

The mineral nesquehonite Mg(OH)(HCO3)•2H2O has been analysed by a combination of infrared (IR) and infrared emission spectroscopy (IES). Both techniques show OH vibrations, both stretching and deformation modes. IES proves the OH units are stable up to 450°C. The strong IR band at 934 cm-1 is evidence for MgOH deformation modes supporting the concept of HCO3- units in the molecular structure. Infrared bands at 1027, 1052 and 1098 cm-1 are attributed to the symmetric stretching modes of HCO3- and CO32- units. Infrared bands at 1419, 1439, 1511, and 1528 cm-1 are assigned to the antisymmetric stretching modes of CO32- and HCO3- units. IES supported by thermoanalytical results defines the thermal stability of nesquehonite IES defines the changes in the molecular structure of nesquehonite with temperature. The results of IR and IES supports the concept that the formula of nesquehonite is better defined as Mg(OH)(HCO3)•2H2O.

Raman spectroscopy of decrespignyite (Y,REE)4Cu(CO3)4Cl(OH)5•2(H2O) and in relation with other halogenated carbonates including bastnasite, hydroxybastnasite, parisite and northupite

Raman spectroscopy complimented with infrared spectroscopy has been used to study the rare earth based mineral decrespignyite (Y,REE)4Cu(CO3)4Cl(OH)5•2(H2O) and compared with the Raman spectra of a series of selected natural halogenated carbonates from different origins including bastnasite, parisite and northupite. The Raman spectrum of decrespignyite displays three bands are at 1056, 1070 and 1088 cm-1 attributed to the CO32- symmetric stretching vibration. The observation of three symmetric stretching vibrations is very unusual. The position of CO32- symmetric stretching vibration varies with mineral composition. Raman bands of decrespignyite show bands at 1391, 1414, 1489 and 1547 cm-1. Raman spectra of bastnasite, parisite and northupite show a single band at 1433, 1420 and 1554 cm-1 assigned to the ν3 (CO3)2- antisymmetric stretching mode. The observation of additional Raman bands for the ν3 modes for some halogenated carbonates is significant in that it shows distortion of the carbonate anion in the mineral structure. Four Raman bands are observed at 791, 815, 837 and 849 cm-1and assigned to the (CO3)2- ν2 bending modes. Raman bands are observed for decrespignyite at 694, 718 and 746 cm-1 and are assigned to the (CO3)2- ν4 bending modes. Raman bands are observed for the carbonate ν4 in phase bending modes at 722 cm-1 for bastnasite, 736 and 684 cm-1 for parisite, 714 cm-1 for northupite. Multiple bands are observed in the OH stretching region for decrespignyite, bastnasite and parisite indicating the presence of water and OH units in the mineral structure.

Miscarriage, preterm delivery, and stillbirth: Large variations in rates within a cohort of Australian women

Objectives We aimed to use simple clinical questions to group women and provide their specific rates of miscarriage, preterm delivery, and stillbirth for reference. Further, our purpose was to describe who has experienced particularly low or high rates of each event. Methods Data were collected as part of the Australian Longitudinal Study on Women's Health, a national prospective cohort. Reproductive histories were obtained from 5806 women aged 31–36 years in 2009, who had self-reported an outcome for one or more pregnancy. Age at first birth, number of live births, smoking status, fertility problems, use of in vitro fertilisation (IVF), education and physical activity were the variables that best separated women into groups for calculating the rates of miscarriage, preterm delivery, and stillbirth. Results Women reported 10,247 live births, 2544 miscarriages, 1113 preterm deliveries, and 113 stillbirths. Miscarriage was correlated with stillbirth (r = 0.09, P<0.001). The calculable rate of miscarriage ranged from 11.3 to 86.5 miscarriages per 100 live births. Women who had high rates of miscarriage typically had fewer live births, were more likely to smoke and were more likely to have tried unsuccessfully to conceive for ≥12 months. The highest proportion of live preterm delivery (32.2%) occurred in women who had one live birth, had tried unsuccessfully to conceive for ≥12 months, had used IVF, and had 12 years education or equivalent. Women aged 14–19.99 years at their first birth and reported low physical activity had 38.9 stillbirths per 1000 live births, compared to the lowest rate at 5.5 per 1000 live births. Conclusion Different groups of women experience vastly different rates of each adverse pregnancy event. We have used simple questions and established reference data that will stratify women into low- and high-rate groups, which may be useful in counselling those who have experienced miscarriage, preterm delivery, or stillbirth, plus women with fertility intent.

Sampling environmental acoustic recordings to determine bird species richness

Acoustic sensors can be used to estimate species richness for vocal species such as birds. They can continuously and passively record large volumes of data over extended periods. These data must subsequently be analyzed to detect the presence of vocal species. Automated analysis of acoustic data for large numbers of species is complex and can be subject to high levels of false positive and false negative results. Manual analysis by experienced surveyors can produce accurate results; however the time and effort required to process even small volumes of data can make manual analysis prohibitive. This study examined the use of sampling methods to reduce the cost of analyzing large volumes of acoustic sensor data, while retaining high levels of species detection accuracy. Utilizing five days of manually analyzed acoustic sensor data from four sites, we examined a range of sampling frequencies and methods including random, stratified, and biologically informed. We found that randomly selecting 120 one-minute samples from the three hours immediately following dawn over five days of recordings, detected the highest number of species. On average, this method detected 62% of total species from 120 one-minute samples, compared to 34% of total species detected from traditional area search methods. Our results demonstrate that targeted sampling methods can provide an effective means for analyzing large volumes of acoustic sensor data efficiently and accurately. Development of automated and semi-automated techniques is required to assist in analyzing large volumes of acoustic sensor data. Read More: http://www.esajournals.org/doi/abs/10.1890/12-2088.1

Reliability and validity of query intent assessments

In most intent recognition studies, annotations of query intent are created post hoc by external assessors who are not the searchers themselves. It is important for the field to get a better understanding of the quality of this process as an approximation for determining the searcher's actual intent. Some studies have investigated the reliability of the query intent annotation process by measuring the interassessor agreement. However, these studies did not measure the validity of the judgments, that is, to what extent the annotations match the searcher's actual intent. In this study, we asked both the searchers themselves and external assessors to classify queries using the same intent classification scheme. We show that of the seven dimensions in our intent classification scheme, four can reliably be used for query annotation. Of these four, only the annotations on the topic and spatial sensitivity dimension are valid when compared with the searcher's annotations. The difference between the interassessor agreement and the assessor-searcher agreement was significant on all dimensions, showing that the agreement between external assessors is not a good estimator of the validity of the intent classifications. Therefore, we encourage the research community to consider using query intent classifications by the searchers themselves as test data.

Exercise-induced phosphorylation of the novel Akt substrates AS160 and filamin A in human skeletal muscle

Skeletal muscle contraction stimulates multiple signaling cascades that govern a variety of metabolic and transcriptional events. Akt/protein kinase B regulates metabolism and growth/muscle hypertrophy, but contraction effects on this target and its substrates are varied and may depend on the mode of the contractile stimulus. Accordingly, we determined the effects of endurance or resistance exercise on phosphorylation of Akt and downstream substrates in six trained cyclists who performed a single bout of endurance or resistance exercise separated by ?7 days. Muscle biopsies were taken from the vastus lateralis at rest and immediately after exercise. Akt Ser 473 phosphorylation was increased (1.8-fold; P = 0.011) after endurance but was unchanged after resistance exercise. Conversely, Akt Thr 308 phosphorylation was unaltered after either bout of exercise. Several exercise-responsive phosphoproteins were detected by immunoblot analysis with a phospho-Akt substrate antibody. pp160 and pp300 were identified as AS160 and filamin A, respectively, with increased phosphorylation (2.0- and 4.9-fold, respectively; P < 0.05) after endurance but not resistance exercise. In conclusion, AS160 and filamin A may provide an important link to mediate endurance exercise-induced bioeffects in skeletal muscle.

Tensile properties of Si nanowires with faulted stacking layers

Semiconductor nanowires (NWs) show tremendous applications in micro/nano-electro-mechanical systems. In order to fulfill their promising applications, an understanding of the mechanical properties of NWs becomes increasingly important. Based on the large-scale molecular dynamics simulations, this work investigated the tensile properties of Si NWs with different faulted stacking layers. Different faulted stacking layers were introduced around the centre of the NW by the insertion or removal of certain stacking layers, inducing twins, intrinsic stacking fault, extrinsic stacking fault, and 9R crystal structure. Stress–strain curves obtained from the tensile deformation tests reveal that the presence of faulted stacking layers has induced a considerable decrease to the yield strength while only a minor decrease to Young's modulus. The brittle fracture phenomenon is observed for all tested NWs. In particular, the formation of a monatomic chain is observed for the perfect NW, which exists for a relatively wide strain range. For the defected NW, the monatomic chain appears and lasts shorter. Additionally, all defected NWs show a fracture area near the two ends, in contrast to the perfect NW whose fracture area is adjacent to the middle. This study provides a better understanding of the mechanical properties of Si NWs with the presence of different faulted stacking layers.

The effect of multiplayer dynamic difficulty adjustment on the player experience of video games

Multiplayer Dynamic Difficulty Adjustment (mDDA) is a method of reducing the difference in player performance and subsequent challenge in competitive multiplayer video games. As a balance of between player skill and challenge experienced is necessary for optimal player experience, this experimental study investigates the effects of mDDA and awareness of its presence on player performance and experience using subjective and biometric measures. Early analysis indicates that mDDA normalizes performance and challenge as expected, but awareness of its presence can reduce its effectiveness.

Investigating online recognition for blood donor retention : an experiential donor value approach

Recognising that charitable behaviour can be motivated by public recognition and emotional satisfaction, not-for-profit organisations have developed strategies that leverage self-interest over altruism by facilitating individuals to donate conspicuously. Initially developed as novel marketing programs to increase donation income, such conspicuous tokens of recognition are being recognised as important value propositions to nurture donor relationships. Despite this, there is little empirical evidence that identifies when donations can be increased through conspicuous recognition. Furthermore, social media’s growing popularity for self-expression, as well as the increasing use of technology in donor relationship management strategies, makes an examination of virtual conspicuous tokens of recognition in relation to what value donors seek particularly insightful. Therefore, this research examined the impact of experiential donor value and virtual conspicuous tokens of recognition on blood donor intentions. Using online survey data from 186 Australian blood donors, results show that in fact emotional value is a stronger predictor of intentions to donate blood than altruistic value, while social value is the strongest predictor of intentions if provided with recognition. Clear linkages between dimensions of donor value (altruistic, emotional and social) and conspicuous donation behaviour (CDB) were identified. The findings provide valuable insights into the use of conspicuous donation tokens of recognition on social media, and contribute to our understanding into the under-researched areas of donor value and CDB.

Polymer-mediated synthesis of γ-Fe2O3 nano-particles

Nano-particles of γ-Fe2O3 were synthesized by reacting polyethylene oxide–FeCl3 complex with NH4OH. These were characterized by X-ray diffraction (XRD), scanning electron miscroscopy (SEM), selected area electron diffraction (SAED) and transmision electron microscopy (TEM). The average particle size was found to be 10 nm, as determined from the line broadening of the main XRD peak. The crystalline phase was a spinel-type tetragonal structure, which was confirmed from the electron diffraction pattern. The zero field cooled magnetization of samples with varying γ-Fe2O3 content as a function of temperature was measured using a vibrating sample magnetometer. The magnetization curves show a peak at low temperature (15 K) corresponding to the blocking temperature TB. The value of TB was found to decrease with decreasing particle size. The magnetization measurements with respect to field at 5 and 170 K confirmed the transition from superparamagnetic to spin-glass state at TB, as evidenced from the remanence and hysteresis. These results can be explained on the basis of Néel's theory of superparamagnetism as applied to nano-particles.

Fine-grained plant classification using convolutional neural networks for feature extraction

We present an overview of the QUT plant classification system submitted to LifeCLEF 2014. This system uses generic features extracted from a convolutional neural network previously used to perform general object classification. We examine the effectiveness of these features to perform plant classification when used in combination with an extremely randomised forest. Using this system, with minimal tuning, we obtained relatively good results with a score of 0:249 on the test set of LifeCLEF 2014.

Deriving word association networks from text corpora

This article presents and evaluates a model to automatically derive word association networks from text corpora. Two aspects were evaluated: To what degree can corpus-based word association networks (CANs) approximate human word association networks with respect to (1) their ability to quantitatively predict word associations and (2) their structural network characteristics. Word association networks are the basis of the human mental lexicon. However, extracting such networks from human subjects is laborious, time consuming and thus necessarily limited in relation to the breadth of human vocabulary. Automatic derivation of word associations from text corpora would address these limitations. In both evaluations corpus-based processing provided vector representations for words. These representations were then employed to derive CANs using two measures: (1) the well known cosine metric, which is a symmetric measure, and (2) a new asymmetric measure computed from orthogonal vector projections. For both evaluations, the full set of 4068 free association networks (FANs) from the University of South Florida word association norms were used as baseline human data. Two corpus based models were benchmarked for comparison: a latent topic model and latent semantic analysis (LSA). We observed that CANs constructed using the asymmetric measure were slightly less effective than the topic model in quantitatively predicting free associates, and slightly better than LSA. The structural networks analysis revealed that CANs do approximate the FANs to an encouraging degree.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.