To improve their predictions, election forecasters should look to other disciplines like meteorology

The recent surge in public attention to election predictions has generated much discussion about how to improve forecasting model accuracy. Michael S. Lewis-Beck and Mary Stegmaier argue that advances in weather forecasting hold lessons for election forecasting. First, like weather models, election models should be based on sound theory. Second, more intensive data gathering, especially at the state level with repeated measurements over time, will capture the dynamics of the campaign and ultimately enhance the accuracy of predictions. Third, ensemble forecasting and applying expertise to adjust forecasts are other methods to consider for reducing forecast error

Using citizen forecasts we predict that with 362 electoral votes, Hillary Clinton will be the next president

Who will be the next US President? Some commentators have argued that voter intention polls are flawed because it is difficult to know who will actually turn out to vote. To get around this problem, Andreas Murr, Mary Stegmaier, and Michael S. Lewis-Beck use citizen forecasts, a “who do you think will win” survey question, to predict the election result

Vote expectations versus vote intentions : rival forecasting strategies

Are ordinary citizens better at predicting election results than conventional voter intention polls? We address this question by comparing eight forecasting models for British general elections: one based on voters’ expectations of who will win and seven based on who voters themselves intend to vote for (including “uniform national swing model” and “cube rule” models). The data come from ComRes and Gallup polls as well as the Essex Continuous Monitoring Surveys, 1950 – 2017, yielding 449 months with both expectation and intention polls. The large sample size allows us to compare the models’ prediction accuracy not just in the months prior to the election, but over the years leading up to it. In predicting both the winning party and parties’ seat shares, we find that vote expectations outperform vote intent ions models. Vote expectations thus appear an excellent tool for predicting the winning party and its seat share

Citizen forecasting 2019: a big win for the Conservatives

The recent failures of voter intention polls to predict UK election results has led to public scepticism about the usefulness of polls. Andreas Murr, Mary Stegmaier, and Michael S. Lewis-Beck deploy an alternative approach, which focuses on which party opinion poll respondents expect to win the election (rather than just on their voting intentions). This ‘voter expectations’ model predicts a solid Johnson majority, with the Conservatives gaining 360 seats, and Labour only 190

Decreasing time consumption of microscopy image segmentation through parallel processing on the GPU

The computational performance of graphical processing units (GPUs) has improved significantly. Achieving speedup factors of more than 50x compared to single-threaded CPU execution are not uncommon due to parallel processing. This makes their use for high throughput microscopy image analysis very appealing. Unfortunately, GPU programming is not straightforward and requires a lot of programming skills and effort. Additionally, the attainable speedup factor is hard to predict, since it depends on the type of algorithm, input data and the way in which the algorithm is implemented. In this paper, we identify the characteristic algorithm and data-dependent properties that significantly relate to the achievable GPU speedup. We find that the overall GPU speedup depends on three major factors: (1) the coarse-grained parallelism of the algorithm, (2) the size of the data and (3) the computation/memory transfer ratio. This is illustrated on two types of well-known segmentation methods that are extensively used in microscopy image analysis: SLIC superpixels and high-level geometric active contours. In particular, we find that our used geometric active contour segmentation algorithm is very suitable for parallel processing, resulting in acceleration factors of 50x for 0.1 megapixel images and 100x for 10 megapixel images

Short sequence motifs, overrepresented in mammalian conserved non-coding sequences

<p>Abstract</p> <p>Background</p> <p>A substantial fraction of non-coding DNA sequences of multicellular eukaryotes is under selective constraint. In particular, ~5% of the human genome consists of conserved non-coding sequences (CNSs). CNSs differ from other genomic sequences in their nucleotide composition and must play important functional roles, which mostly remain obscure.</p> <p>Results</p> <p>We investigated relative abundances of short sequence motifs in all human CNSs present in the human/mouse whole-genome alignments <it>vs</it>. three background sets of sequences: (i) weakly conserved or unconserved non-coding sequences (non-CNSs); (ii) near-promoter sequences (located between nucleotides -500 and -1500, relative to a start of transcription); and (iii) random sequences with the same nucleotide composition as that of CNSs. When compared to non-CNSs and near-promoter sequences, CNSs possess an excess of AT-rich motifs, often containing runs of identical nucleotides. In contrast, when compared to random sequences, CNSs contain an excess of GC-rich motifs which, however, lack CpG dinucleotides. Thus, abundance of short sequence motifs in human CNSs, taken as a whole, is mostly determined by their overall compositional properties and not by overrepresentation of any specific short motifs. These properties are: (i) high AT-content of CNSs, (ii) a tendency, probably due to context-dependent mutation, of A's and T's to clump, (iii) presence of short GC-rich regions, and (iv) avoidance of CpG contexts, due to their hypermutability. Only a small number of short motifs, overrepresented in all human CNSs are similar to binding sites of transcription factors from the FOX family.</p> <p>Conclusion</p> <p>Human CNSs as a whole appear to be too broad a class of sequences to possess strong footprints of any short sequence-specific functions. Such footprints should be studied at the level of functional subclasses of CNSs, such as those which flank genes with a particular pattern of expression. Overall properties of CNSs are affected by patterns in mutation, suggesting that selection which causes their conservation is not always very strong.</p

Charge carrier injection into insulating media: single-particle versus mean-field approach

Self-consistent, mean-field description of charge injection into a dielectric medium is modified to account for discreteness of charge carriers. The improved scheme includes both the Schottky barrier lowering due to the individual image charge and the barrier change due to the field penetration into the injecting electrode that ensures validity of the model at both high and low injection rates including the barrier dominated and the space-charge dominated regimes. Comparison of the theory with experiment on an unipolar ITO/PPV/Au-device is presented.Comment: 32 pages, 9 figures; revised version accepted to PR

The sequential trauma score - a new instrument for the sequential mortality prediction in major trauma*

<p>Abstract</p> <p>Background</p> <p>There are several well established scores for the assessment of the prognosis of major trauma patients that all have in common that they can be calculated at the earliest during intensive care unit stay. We intended to develop a sequential trauma score (STS) that allows prognosis at several early stages based on the information that is available at a particular time.</p> <p>Study design</p> <p>In a retrospective, multicenter study using data derived from the Trauma Registry of the German Trauma Society (2002-2006), we identified the most relevant prognostic factors from the patients basic data (P), prehospital phase (A), early (B1), and late (B2) trauma room phase. Univariate and logistic regression models as well as score quality criteria and the explanatory power have been calculated.</p> <p>Results</p> <p>A total of 2,354 patients with complete data were identified. From the patients basic data (P), logistic regression showed that age was a significant predictor of survival (AUC_{model p}, area under the curve = 0.63). Logistic regression of the prehospital data (A) showed that blood pressure, pulse rate, Glasgow coma scale (GCS), and anisocoria were significant predictors (AUC_{model A}= 0.76; AUC_{model P + A}= 0.82). Logistic regression of the early trauma room phase (B1) showed that peripheral oxygen saturation, GCS, anisocoria, base excess, and thromboplastin time to be significant predictors of survival (AUC_{model B1}= 0.78; AUC_{model P +A + B1}= 0.85). Multivariate analysis of the late trauma room phase (B2) detected cardiac massage, abbreviated injury score (AIS) of the head ≥ 3, the maximum AIS, the need for transfusion or massive blood transfusion, to be the most important predictors (AUCmodel B2 = 0.84; AUCfinal model P + A + B1 + B2 = 0.90). The explanatory power - a tool for the assessment of the relative impact of each segment to mortality - is 25% for P, 7% for A, 17% for B1 and 51% for B2. A spreadsheet for the easy calculation of the sequential trauma score is available at: <url>http://www.sequential-trauma-score.com</url></p> <p>Conclusions</p> <p>This score is the first sequential, dynamic score to provide a prognosis for patients with blunt major trauma at several points in time. With every additional piece of information the precision increases. The medical team has a simple, useful tool to identify patients at high risk and to predict the prognosis of an individual patient with major trauma very early, quickly and precisely.</p

Results of the QUENCH-20 experiment with BWR test bundle [in press]

The experiment QUENCH-20 with BWR geometry simulation bundle was successfully conducted at KIT on 9th October 2019 in the framework of the international SAFEST project. The test bundle mock-up represented one quarter of a BWR fuel assembly with 24 electrically heated fuel rod simulators and two B4C control blades. The rod simulators were filled with Kr to an inner pressure of 5.5 bar. The pre-oxidation stage in a flowing gas mixture of steam and argon (each 3 g/s) and system pressure of 2 bar lasted 4 hours at the peak cladding temperature of 1250 K. The Zry-4 corner rod, withdrawn at the end of this stage, showed the maximal oxidation at elevations between 930 and 1020 mm with signs of breakaway. During the transient stage, the bundle was heated to a maximum temperature of 2000 K. The coolability of the bundle was decreased by its squeezing due to the shroud ductile deformation caused by an overpressure outside the shroud. The cladding radial strain and failures due to inner overpressure (about 4 bar) were observed at temperature about 1700 K and lasted about 200 s. During the period of rod failures also the first absorber melt relocation accompanied by shroud failure were registered. The interaction of B4C with the steel blade and the ZIRLO channel box were observed at elevations 650…950 mm with the formation of eutectic melt. The typical components of this melt are (Fe, Cr) borides and ZrB2 precipitated in steel or in Zr-steel eutectic melt. Massive absorber melt relocation was observed 50 s before the end of transition stage. Small fragments of the absorber melt moved down to the elevation of 50 mm. The melting point of Inconel spacer grids at 500 and 1050 mm was also reached at the end of the transition stage. The Inconel melt from the elevation 1050 mm relocated downwards through hot bundle regions to the Inconel grid spacer at 550 mm and later (during the escalation caused by quench) to 450 mm. This melt penetrated also under the damaged cladding oxide layer and formed molten eutectic mixtures between elevations 450 and 550 mm. The test was terminated by quench water injection with a flow rate of 50 g/s from the bundle bottom. Fast temperature escalation from 2000 to 2300 K during 20 s was observed due to the strongly exothermic oxidation reactions. As result, the metal part (prior β-Zr) of the claddings between 550 and 950 mm was melted, partially released into space between rods and partially relocated in the gap between pellet and outer oxide layer to 450 mm. In this case, the positive role of the oxide layer should be noted, which does not allow the melt to completely escape into the inter-rod space. It is thereby limiting the possibility of interactions of a large amount of melt with steam, which could significantly increase the exothermic oxidation processes and the escalation of temperatures. The distribution of the oxidation rate within each bundle cross section is very inhomogeneous: whereas the average outer ZrO2 layer thickness for the central rod (#1) at the elevation of 750 mm is 465 µm, the same parameter for the peripheral rod #24 is only 108 µm. The average oxidation rate of the inner cladding surface (due to interaction with steam and with ZrO2 pellets) is about 20% in comparison to the outer cladding oxidation. The bundle elevations 850 and 750 mm are mostly oxidized with average cladding ECR 33%. The oxidation of the melt relocated inside the rods was observed at elevations 550…950 mm. The mass spectrometer measured release of CO (12.6 g), CO2 (9.7 g) and CH4 (0.4 g) during the reflood as products of absorber oxidation; the corresponding B4C reacted mass was 41 g or 4.6% of the total B4C inventory. It is significantly lower than in the PWR bundle tests QUENCH-07 and QUENCH-09 containing central absorber rod with B4C pellets inserted into a thin stainless steel cladding and Zry-4 guide tubes (20% and 50% reacted B4C correspondingly). Hydrogen production during the reflood amounted to 32 g during the reflood (57.4 g during the whole test) including 10 g from B4C oxidation