Corporate credit risk prediction under stochastic volatility and jumps

This paper examines the impact of allowing for stochastic volatility and jumps (SVJ) in a structural model on corporate credit risk prediction. The results from a simulation study verify the better performance of the SVJ model compared with the commonly used Merton model, and three sources are provided to explain the superiority. The empirical analysis on two real samples further ascertains the importance of recognizing the stochastic volatility and jumps by showing that the SVJ model decreases bias in spread prediction from the Merton model, and better explains the time variation in actual CDS spreads. The improvements are found particularly apparent in small firms or when the market is turbulent such as the recent financial crisis.

Frequency-motivated observer design for the prediction of parametric roll resonance control applications in marine systems

This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

Natural ventilation heuristics in high-rise residential buildings : evaluation and prediction

Complex behaviour of air flow in the buildings makes it difficult to predict. Consequently, architects use common strategies for designing buildings with adequate natural ventilation. However, each climate needs specific strategies and there are not many heuristics for subtropical climate in literature. Furthermore, most of these common strategies are based on low-rise buildings and their performance for high-rise buildings might be different due to the increase of the wind speed with increase in the height. This study uses Computational Fluid Dynamics (CFD) to evaluate these rules of thumb for natural ventilation for multi-residential buildings in subtropical climate. Four design proposals for multi-residential towers with natural ventilation which were produced in intensive two days charrette were evaluated using CFD. The results show that all the buildings reach acceptable level of wind speed in living areas and poor amount of air flow in sleeping areas.

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

A continent-wide study reveals clear relationships between regional abiotic conditions and post-dispersal seed predation

Aim Large-scale patterns linking energy availability, biological productivity and diversity form a central focus of ecology. Despite evidence that the activity and abundance of animals may be limited by climatic variables associated with regional biological productivity (e.g. mean annual precipitation and annual actual evapotranspiration), it is unclear whether plant–granivore interactions are themselves influenced by these climatic factors across broad spatial extents. We evaluated whether climatic conditions that are known to alter the abundance and activity of granivorous animals also affect rates of seed removal. Location Eleven sites across temperate North America. Methods We used a common protocol to assess the removal of the same seed species (Avena sativa) over a 2-day period. Model selection via the Akaike information criterion was used to determine a set of candidate binomial generalized linear mixed models that evaluated the relationship between local climatic data and post-dispersal seed predation. Results Annual actual evapotranspiration was the single best predictor of the proportion of seeds removed. Annual actual evapotranspiration and mean annual precipitation were both positively related to mean seed removal and were included in four and three of the top five models, respectively. Annual temperature range was also positively related to seed removal and was an explanatory variable in three of the top four models. Main conclusions Our work provides the first evidence that energy and precipitation, which are known to affect consumer abundance and activity, also translate to strong, predictable patterns of seed predation across a continent. More generally, these findings suggest that future changes in temperature and precipitation could have widespread consequences for plant species composition in grasslands, through impacts on plant recruitment.

Community wide interventions for increasing physical activity

Background Multi-strategic community wide interventions for physical activity are increasingly popular but their ability to achieve population level improvements is unknown. Objectives To evaluate the effects of community wide, multi-strategic interventions upon population levels of physical activity. Search methods We searched the Cochrane Public Health Group Segment of the Cochrane Register of Studies,The Cochrane Library, MEDLINE, MEDLINE in Process, EMBASE, CINAHL, LILACS, PsycINFO, ASSIA, the British Nursing Index, Chinese CNKI databases, EPPI Centre (DoPHER, TRoPHI), ERIC, HMIC, Sociological Abstracts, SPORTDiscus, Transport Database and Web of Science (Science Citation Index, Social Sciences Citation Index, Conference Proceedings Citation Index). We also scanned websites of the EU Platform on Diet, Physical Activity and Health; Health-Evidence.org; the International Union for Health Promotion and Education; the NIHR Coordinating Centre for Health Technology (NCCHTA); the US Centre for Disease Control and Prevention (CDC) and NICE and SIGN guidelines. Reference lists of all relevant systematic reviews, guidelines and primary studies were searched and we contacted experts in the field. The searches were updated to 16 January 2014, unrestricted by language or publication status. Selection criteria Cluster randomised controlled trials, randomised controlled trials, quasi-experimental designs which used a control population for comparison, interrupted time-series studies, and prospective controlled cohort studies were included. Only studies with a minimum six-month follow up from the start of the intervention to measurement of outcomes were included. Community wide interventions had to comprise at least two broad strategies aimed at physical activity for the whole population. Studies which randomised individuals from the same community were excluded. Data collection and analysis At least two review authors independently extracted the data and assessed the risk of bias. Each study was assessed for the setting, the number of included components and their intensity. The primary outcome measures were grouped according to whether they were dichotomous (per cent physically active, per cent physically active during leisure time, and per cent physically inactive) or continuous (leisure time physical activity time (time spent)), walking (time spent), energy expenditure (as metabolic equivalents or METS)). For dichotomous measures we calculated the unadjusted and adjusted risk difference, and the unadjusted and adjusted relative risk. For continuous measures we calculated percentage change from baseline, unadjusted and adjusted. Main results After the selection process had been completed, 33 studies were included. A total of 267 communities were included in the review (populations between 500 and 1.9 million). Of the included studies, 25 were set in high income countries and eight were in low income countries. The interventions varied by the number of strategies included and their intensity. Almost all of the interventions included a component of building partnerships with local governments or non-governmental organisations (NGOs) (29 studies). None of the studies provided results by socio-economic disadvantage or other markers of equity. However, of those included studies undertaken in high income countries, 14 studies were described as being provided to deprived, disadvantaged or low socio-economic communities. Nineteen studies were identified as having a high risk of bias, 10 studies were unclear, and four studies had a low risk of bias. Selection bias was a major concern with these studies, with only five studies using randomisation to allocate communities. Four studies were judged as being at low risk of selection bias although 19 studies were considered to have an unclear risk of bias. Twelve studies had a high risk of detection bias, 13 an unclear risk and four a low risk of bias. Generally, the better designed studies showed no improvement in the primary outcome measure of physical activity at a population level. All four of the newly included, and judged to be at low risk of bias, studies (conducted in Japan, United Kingdom and USA) used randomisation to allocate the intervention to the communities. Three studies used a cluster randomised design and one study used a stepped wedge design. The approach to measuring the primary outcome of physical activity was better in these four studies than in many of the earlier studies. One study obtained objective population representative measurements of physical activity by accelerometers, while the remaining three low-risk studies used validated self-reported measures. The study using accelerometry, conducted in low income, high crime communities of USA, emphasised social marketing, partnership with police and environmental improvements. No change in the seven-day average daily minutes of moderate to vigorous physical activity was observed during the two years of operation. Some program level effect was observed with more people walking in the intervention community, however this result was not evident in the whole community. Similarly, the two studies conducted in the United Kingdom (one in rural villages and the other in urban London; both using communication, partnership and environmental strategies) found no improvement in the mean levels of energy expenditure per person per week, measured from one to four years from baseline. None of the three low risk studies reporting a dichotomous outcome of physical activity found improvements associated with the intervention. Overall, there was a noticeable absence of reporting of benefit in physical activity for community wide interventions in the included studies. However, as a group, the interventions undertaken in China appeared to have the greatest possibility of success with high participation rates reported. Reporting bias was evident with two studies failing to report physical activity measured at follow up. No adverse events were reported.The data pertaining to cost and sustainability of the interventions were limited and varied. Authors' conclusions Although numerous studies have been undertaken, there is a noticeable inconsistency of the findings in the available studies and this is confounded by serious methodological issues within the included studies. The body of evidence in this review does not support the hypothesis that the multi-component community wide interventions studied effectively increased physical activity for the population, although some studies with environmental components observed more people walking. Plain language summary Community wide interventions for increasing physical activity Not having enough physical activity leads to poorer health. Regular physical activity can reduce the risk of chronic disease and improve one's health and wellbeing. The lack of physical activity is a common and in some cases a growing health problem. To address this, 33 studies have used improvement activities directed at communities, using more than one approach in a single program. When we first looked at the available research in 2011 we observed that there was a lack of good studies which could show whether this approach was beneficial or not. Some studies claimed that community wide programs improved physical activities and other studies did not. In this update we found four new studies that were of good quality; however none of these four studies increased physical activity levels for the population. Some studies reported program level effects such as observing more people walking, however the population level of physical activity had not increased. This review found that community wide interventions are very difficult to undertake, and it appears that they usually fail to provide a measurable benefit in physical activity for a population. It is apparent that many of the interventions failed to reach a substantial portion of the community, and we speculate that some single strategies included in the combination may lack individual effectiveness. Laički sažetak Intervencije u zajednici za povećanje tjelesne aktivnosti Nedostatna tjelesna aktivnost povezana je s lošijim zdravljem.Redovita tjelesna aktivnost može umanjiti rizik od kroničnih bolesti te poboljšati zdravlje i kvalitetu života pojedinca.Manjak tjelesne aktivnosti čest je problem, a učestalost tog problema se povećava.Cochrane sustavni pregled je analizirao 33 studije koje su istražile programe za povećanje tjelesne aktivnosti u zajednici, u kojima se koristilo više od jednog pristupa.Kad su prvi put pregledani dokazi iz istraživanja koja su bila dostupna 2011. godine, utvrđeno je da nema dovoljno dobrih studija koje bi mogle pokazati je li takav pristup koristan ili ne.Primjerice, neke studije tvrde da programi za povećanje tjelesne aktivnosti u zajednici poboljšavaju tjelesnu aktivnost pojedinaca u zajednici, a druge studije tvrde suprotno.U ovom obnovljenom sustavnom pregledu pronađene su 4 nove studije koje su bile visoke kvalitete, ail nijedna od tih studija nije pokazala da je istraživana intervencija dovela do povećanja tjelesne aktivnosti u zajednici.Neke su studije opisale učinak na način da je opisano da je uočeno da više ljudi u zajednici hoda, međutim, ukupna razina tjelesne aktivnosti u promatranoj populaciji nije se povećala.Ovaj sustavni pregled je utvrdio da je intervencije za povećanje tjelesne aktivnosti u zajednici teško provesti i čini se da one obično ne uspijevaju u svojoj namjeri da na mjerljiv način povećaju tjelesnu aktivnost u populaciji.Čini se da mnoge intervencije nisu uspjele doseći veći broj stanovnika u zajednici pa se može smatrati da neke od strategija uključene u analizirane kombinacije nisu zasebno učinkovite.

Wide area control of SVCs for first swing stabilisation and damping in longitudinal systems

A non-linear Kalman filter based control strategy for SVCs located in major load groups is presented. This focusses on the limitation and damping of inter-area modes. It does this through treating local modes as noise and uses a tunable nonlinear control algorithm to improve both first swing stability and system damping. Simulation on a four machine system shows that the Kalman filer can successfully lock on to a desired inter-area mode and obtain a 31% improvement in critical clearing time as well as improved damping.

The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

Facile dearomatisation of porphyrins using palladium-catalysed hydrazination: the 5,15-diiminoporphodimethenes and their redox products

The synthesis, electronic absorption and 1H NMR spectra of a suite of novel porphyrinoids derived from meso-bromoporphyrins by palladium-catalysed aminations using ethyl and tert-butylcarbazates are reported. Instead of the expected carbazate-substituted porphyrins, a facile oxidative dearomatisation of the porphyrin ring occurs in high yield, especially for the nickel(II) complexes, resulting in high yields of 5,15-diiminoporphodimethenes (DIPDs). The analogous zinc(II) and free base DIPDs were also characterised, the former by X-ray crystallography. The oxidation and reduction reactions of DIPDs and their precursor carbazate porphyrins were studied. Density Functional Theory (DFT) was used to calculate the optimised geometries and frontier molecular orbitals of DIPD Ni8c and bis(azocarboxylate) 19c, and Time Dependent DFT calculations allowed the prediction of electronic absorption spectra, whose characteristics corresponded well with those of the observed solution spectra. In the latter case, the calculated low-energy absorptions were unlike those of a typical porphyrin, due to the near-degeneracy of the highest filled frontier orbitals, and the wide energy separation between the unfilled orbitals. This feature was present in the observed spectrum.