Statistics sunspots and settlement: Influences on sum of probability curves

Large data sets of radiocarbon dates are becoming a more common feature of archaeological research. The sheer numbers of radiocarbon dates produced, however, raise issues of representation and interpretation. This paper presents a methodology which both reduces the visible impact of dating fluctuations, but also takes into consideration the influence of the underlying radiocarbon calibration curve. By doing so, it may be possible to distinguish between periods of human activity in early medieval Ireland and the statistical tails produced by radiocarbon calibration.

Next generation sequencing-based molecular diagnosis of retinitis pigmentosa: identification of a novel genotype-phenotype correlation and clinical refinements

Retinitis pigmentosa (RP) is a devastating form of retinal degeneration, with significant social and professional consequences. Molecular genetic information is invaluable for an accurate clinical diagnosis of RP due to its high genetic and clinical heterogeneity. Using a gene capture panel that covers 163 of the currently known retinal disease genes, including 48 RP genes, we performed a comprehensive molecular screening in a collection of 123 RP unsettled probands from a wide variety of ethnic backgrounds, including 113 unrelated simplex and 10 autosomal recessive RP (arRP) cases. As a result, 61 mutations were identified in 45 probands, including 38 novel pathogenic alleles. Interestingly, we observed that phenotype and genotype were not in full agreement in 21 probands. Among them, eight probands were clinically reassessed, resulting in refinement of clinical diagnoses for six of these patients. Finally, recessive mutations in CLN3 were identified in five retinal degeneration patients, including four RP probands and one cone-rod dystrophy patient, suggesting that CLN3 is a novel non-syndromic retinal disease gene. Collectively, our results underscore that, due to the high molecular and clinical heterogeneity of RP, comprehensive screening of all retinal disease genes is effective in identifying novel pathogenic mutations and provides an opportunity to discover new genotype-phenotype correlations. Information gained from this genetic screening will directly aid in patient diagnosis, prognosis, and treatment, as well as allowing appropriate family planning and counseling.

Integrating geophysical data and upscaling techniques to support regional groundwater flow modelling: A practical example of the Lagan Valley, Northern Ireland

When studying heterogeneous aquifer systems, especially at regional scale, a degree of generalization is anticipated. This can be due to sparse sampling regimes, complex depositional environments or lack of accessibility to measure the subsurface. This can lead to an inaccurate conceptualization which can be detrimental when applied to groundwater flow models. It is important that numerical models are based on observed and accurate geological information and do not rely on the distribution of artificial aquifer properties. This can still be problematic as data will be modelled at a different scale to which it was collected. It is proposed here that integrating geophysics and upscaling techniques can assist in a more realistic and deterministic groundwater flow model. In this study, the sedimentary aquifer of the Lagan Valley in Northern Ireland is chosen due to intruding sub-vertical dolerite dykes. These dykes are of a lower permeability than the sandstone aquifer. The use of airborne magnetics allows the delineation of heterogeneities, confirmed by field analysis. Permeability measured at the field scale is then upscaled to different levels using a correlation with the geophysical data, creating equivalent parameters that can be directly imported into numerical groundwater flow models. These parameters include directional equivalent permeabilities and anisotropy. Several stages of upscaling are modelled in finite element. Initial modelling is providing promising results, especially at the intermediate scale, suggesting an accurate distribution of aquifer properties. This deterministic based methodology is being expanded to include stochastic methods of obtaining heterogeneity location based on airborne geophysical data. This is through the Direct Sample method of Multiple-Point Statistics (MPS). This method uses the magnetics as a training image to computationally determine a probabilistic occurrence of heterogeneity. There is also a need to apply the method to alternate geological contexts where the heterogeneity is of a higher permeability than the host rock.

Dyslexia in higher education: Implications for maths anxiety, statistics anxiety and psychological well-being

This study examined levels of mathematics and statistics anxiety, as well as general mental health amongst undergraduate students with dyslexia (n = 28) and those without dyslexia (n = 71). Students with dyslexia had higher levels of mathematics anxiety relative to those without dyslexia, while statistics anxiety and general mental health were comparable for both reading ability groups. In terms of coping strategies, undergraduates with dyslexia tended to use planning-based strategies and seek instrumental support more frequently than those without dyslexia. Higher mathematics anxiety was associated with having a dyslexia diagnosis, as well as greater levels of worrying, denial, seeking instrumental support and less use of the positive reinterpretation coping strategy. By contrast, statistics anxiety was not predicted by dyslexia diagnosis, but was instead predicted by overall worrying and the use of denial and emotion focused coping strategies. The results suggest that disability practitioners should be aware that university students with dyslexia are at risk of high mathematics anxiety. Additionally, effective anxiety reduction strategies such as positive reframing and thought challenging would form a useful addition to the support package delivered to many students with dyslexia.

Integrating Multiple Point Statistics with Aerial Geophysical Data to assist Groundwater Flow Models

The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by low-permeability volcanic dykes in Northern Ireland, UK. The use of two two-dimensional bivariate training images aids in creating spatial probability distributions of heterogeneities of hydrogeological interest, despite relatively ‘noisy’ magnetics data (i.e. including hydrogeologically irrelevant urban noise and regional geologic effects). These distributions are incorporated into a hierarchy system where previously published density function and upscaling methods are applied to derive regional distributions of equivalent hydraulic conductivity tensor K. Several K models, as determined by several stochastic realisations of MPS dyke locations, are computed within groundwater flow models and evaluated by comparing modelled heads with field observations. Results show a significant improvement in model calibration when compared to a simplistic homogeneous and isotropic aquifer model that does not account for the dyke occurrence evidenced by airborne magnetic data. The best model is obtained when normal and reverse polarity dykes are computed separately within MPS simulations and when a probability threshold of 0.7 is applied. The presented stochastic approach also provides improvement when compared to a previously published deterministic anisotropic model based on the unprocessed (i.e. noisy) airborne magnetics. This demonstrates the potential of coupling MPS to airborne geophysical data for regional groundwater modelling.

Correlation of Static Ageing Effects on Automotive Catalysts

This study identifies and analyzes the effect that aging time and temperature have on the CO light-off activity of three-way catalyst samples, aged in a static air (oxidizing) atmosphere. The bench aging time (BAT) equation proposed by the Environmental Protection Agency (EPA), which describes aging as dependent upon time at temperature, was used to calculate a range of oven aging times and temperatures based on a RAT-A engine bench aging cycle.

CO light-off tests carried out on cores aged between 800 and 900 °C have shown that it is the aging temperature that has the greatest effect on catalyst deterioration for static aging testing, with aging time having little effect. These results were in contradiction to the BAT equation, an industry norm for the aging of catalysts. This demonstrates that static aging, whilst showing how temperature affects aging, gives little or no time effects. The results have shown that static aging is not representative of actual aging on a vehicle.

Progressive aging conducted at a temperature of 1000 °C was shown to cause a decrease in catalyst activity as the aging time increased. However, even in these extreme conditions, static aging gave a slower rate of aging with time when compared to engine aging as defined by the BAT equation. Overall, static aging in air has been shown to produce a greater increase in aging due to temperature than predicted by the BAT equation, but less aging due to aging time.

Detecting the work statistics through Ramsey-like interferometry

Out-of-equilibrium statistical mechanics is attracting considerable interest due to the recent advances in the control and manipulations of systems at the quantum level. Recently, an interferometric scheme for the detection of the characteristic function of the work distribution following a time-dependent process has been proposed [L. Mazzola et al., Phys. Rev. Lett. 110 (2013) 230602]. There, it was demonstrated that the work statistics of a quantum system undergoing a process can be reconstructed by effectively mapping the characteristic function of work on the state of an ancillary qubit. Here, we expand that work in two important directions. We first apply the protocol to an interesting specific physical example consisting of a superconducting qubit dispersively coupled to the field of a microwave resonator, thus enlarging the class of situations for which our scheme would be key in the task highlighted above. We then account for the interaction of the system with an additional one (which might embody an environment), and generalize the protocol accordingly.

Quantitative correlation of aflatoxin biomarker with dietary intake of aflatoxin in Tanzanian children

The association between aflatoxin intake from maize-based weaning food and aflatoxin albumin adducts (AF-alb) was investigated in 148 Tanzanian children aged between 12 and 22 months, at 2 visits 6 months apart. At the first visit (storage season) there was a significant correlation at the individual level between AF-alb (geometric mean 43.2 pg/mg albumin) and aflatoxin intake (geometric mean 81.7 ng/kg b.w./d) through maize-based weaning food (r = 0.51, p < 0.01). Overall, this correlation was r = 0.43 (p < 0.01). The AF-alb level in weaning-age children in Tanzania closely reflects aflatoxin intake from maize in weaning food. Exposure levels suggest children may be at risk from aflatoxin associated health effects.

Correlation of phantom-based and log file patient-specific QA with complexity scores for VMAT

The motivation for this study was to reduce physics workload relating to patient- specific quality assurance (QA). VMAT plan delivery accuracy was determined from analysis of pre- and on-treatment trajectory log files and phantom-based ionization chamber array measurements. The correlation in this combination of measurements for patient-specific QA was investigated. The relationship between delivery errors and plan complexity was investigated as a potential method to further reduce patient-specific QA workload. Thirty VMAT plans from three treatment sites - prostate only, prostate and pelvic node (PPN), and head and neck (H&amp;N) - were retrospectively analyzed in this work. The 2D fluence delivery reconstructed from pretreatment and on-treatment trajectory log files was compared with the planned fluence using gamma analysis. Pretreatment dose delivery verification was also car- ried out using gamma analysis of ionization chamber array measurements compared with calculated doses. Pearson correlations were used to explore any relationship between trajectory log file (pretreatment and on-treatment) and ionization chamber array gamma results (pretreatment). Plan complexity was assessed using the MU/ arc and the modulation complexity score (MCS), with Pearson correlations used to examine any relationships between complexity metrics and plan delivery accu- racy. Trajectory log files were also used to further explore the accuracy of MLC and gantry positions. Pretreatment 1%/1 mm gamma passing rates for trajectory log file analysis were 99.1% (98.7%-99.2%), 99.3% (99.1%-99.5%), and 98.4% (97.3%-98.8%) (median (IQR)) for prostate, PPN, and H&amp;N, respectively, and were significantly correlated to on-treatment trajectory log file gamma results (R = 0.989, p &lt; 0.001). Pretreatment ionization chamber array (2%/2 mm) gamma results were also significantly correlated with on-treatment trajectory log file gamma results (R = 0.623, p &lt; 0.001). Furthermore, all gamma results displayed a significant correlation with MCS (R &gt; 0.57, p &lt; 0.001), but not with MU/arc. Average MLC position and gantry angle errors were 0.001 ± 0.002 mm and 0.025° ± 0.008° over all treatment sites and were not found to affect delivery accuracy. However, vari- ability in MLC speed was found to be directly related to MLC position accuracy. The accuracy of VMAT plan delivery assessed using pretreatment trajectory log file fluence delivery and ionization chamber array measurements were strongly correlated with on-treatment trajectory log file fluence delivery. The strong corre- lation between trajectory log file and phantom-based gamma results demonstrates potential to reduce our current patient-specific QA. Additionally, insight into MLC and gantry position accuracy through trajectory log file analysis and the strong cor- relation between gamma analysis results and the MCS could also provide further methodologies to both optimize the VMAT planning and QA process. 

Process efficiency in polymer extrusion: Correlation between the energy demand and melt thermal stability

Thermal stability is of major importance in polymer extrusion, where product quality is dependent upon the level of melt homogeneity achieved by the extruder screw. Extrusion is an energy intensive process and optimisation of process energy usage while maintaining melt stability is necessary in order to produce good quality product at low unit cost. Optimisation of process energy usage is timely as world energy prices have increased rapidly over the last few years. In the first part of this study, a general discussion was made on the efficiency of an extruder. Then, an attempt was made to explore correlations between melt thermal stability and energy demand in polymer extrusion under different process settings and screw geometries. A commodity grade of polystyrene was extruded using a highly instrumented single screw extruder, equipped with energy consumption and melt temperature field measurement. Moreover, the melt viscosity of the experimental material was observed by using an off-line rheometer. Results showed that specific energy demand of the extruder (i.e. energy for processing of unit mass of polymer) decreased with increasing throughput whilst fluctuation in energy demand also reduced. However, the relationship between melt temperature and extruder throughput was found to be complex, with temperature varying with radial position across the melt flow. Moreover, the melt thermal stability deteriorated as throughput was increased, meaning that a greater efficiency was achieved at the detriment of melt consistency. Extruder screw design also had a significant effect on the relationship between energy consumption and melt consistency. Overall, the relationship between the process energy demand and thermal stability seemed to be negatively correlated and also it was shown to be highly complex in nature. Moreover, the level of process understanding achieved here can help to inform selection of equipment and setting of operating conditions to optimise both energy and thermal efficiencies in parallel. 

Lack of in vitro-in vivo correlation for a UC781-releasing vaginal ring in macaques

This study describes the preclinical development of a matrix-type silicone elastomer vaginal ring device designed to provide controlled release of UC781, a non-nucleoside re- verse transcriptase inhibitor. Testing of both human- and macaque-sized rings in a sink condition in vitro release model demonstrated continuous UC781 release in quantities consid- ered sufficient to maintain vaginal fluid concentrations at levels 82–860-fold higher than the in vitro IC50 (2.0 to 10.4 nM) and therefore potentially protect against mucosal trans- mission of HIV. The 100-mg UC781 rings were well tolerated in pig-tailed macaques, did not induce local inflammation as determined by cytokine analysis and maintained median con- centrations in vaginal fluids of UC781 in the range of 0.27 to 5.18 mM during the course of the 28-day study. Analysis of residual UC781 content in rings after completion of both the in vitro release and macaque pharmacokinetic studies revealed that 57 and 5 mg of UC781 was released, respectively. The pharmacokinetic analysis of a 100-mg UC781 vaginal ring in pig-tailed macaques showed poor in vivo–in vitro correlation, attributed to the very poor solubility of UC781 in vaginal fluid and resulting in a dissolution-controlled drug release mecha- nism rather than the expected diffusion-controlled mechanism.