Otsar ha-shorashim : ... shorshe ha-lashon ha-ʻIvrit ṿe-haʻataḳatam ... me-ʻIvrit le-ʾAshkenazit ume-ʾAshkenazit le-ʻIvrit ... gam ha-shorashim bi-leshon Aramit ... /

Added t.p.: Hebräisch-deutsches and deutsch-hebräisches Wörterbuch über das alte Testament.

Ben Yishai : ...seder ḥeshbon ha-ʻitim...gam bi-leshon Italya : ʻim luaḥ ha-maḥazorim li-teḳufat Shemuʾel...ṿe-luaḥ shanim...581-741.

Mode of access: Internet.

Ḥamishah ḥumshe Torah : ʻim Ḥamesh megilot ṿe-hafṭarot ṿe-gam perush ha-milot...

Mode of access: Internet.

Maḥzor kol ha-shanah : kefi minhag ḳ. ḳ. Iṭaliyani ... . Ṿe-nosaf gam ... Mavo le-maḥzor bene Roma /

Mode of access: Internet.

Michigan Daily Bulletin" scoreboard at Regents Field at 1898 Beloit Gam

[Scoreboard was first used at the October 23 Notre Dame game.]

Grupo de Ajuda Mútua e Qualidade de Vida dos Cuidadores dos Doentes de Alzheimer: um estudo sobre o GAM de Pombal

Perante a falta ou escassez das redes familiares, de amigos e vizinhos, os Grupos de Ajuda Mútua surgem como uma rede social de apoio que proporciona aos doentes de Alzheimer e seus cuidadores a mudança para melhorar a sua qualidades de vida. O objectivo do estudo foi analisar o contributo do Grupo de Ajuda Mútua na melhoria da qualidade de vida dos cuidadores dos doentes de Alzheimer. Utilizou-se uma abordagem essencialmente qualitativa, mas com alguns aspectos quantitativos, para entrevistar nove cuidadores e dois elementos da equipa técnica da Alzheimer Portugal- -Centro. As informações foram analisadas pela Analise de Conteúdo percorrendo dezassete categorias, onze referentes aos cuidadores dos doentes de Alzheimer: conhecimento da associação, conhecimento do GAM, instituições/organismos de apoio, integração no GAM, informação e formação, partilha de experiências e conhecimentos, rotina diária, contributos, necessidades, apoios do GAM e comunicação/ relacionamento com a equipa técnica. Foram ainda analisadas seis categorias referentes à equipa técnica: comunicação com os cuidadores, informação/formação, orientação para a prestação do cuidado, construção da capacidade pessoal e social, necessidades dos cuidadores e estratégias de intervenção. Este estudo permitiu identificar as necessidades dos cuidadores de doentes de Alzheimer e verificar de que modo o GAM possibilita o promoção da qualidade de vida deste cuidadores, que estratégias de intervenção utiliza.

Predicting loss and fragmentation of habitat of the vulnerable subtropical rainforest tree Macadamia integrifolia with models developed from compiled ecological data

Habitat models are widely used in ecology, however there are relatively few studies of rare species, primarily because of a paucity of survey records and lack of robust means of assessing accuracy of modelled spatial predictions. We investigated the potential of compiled ecological data in developing habitat models for Macadamia integrifolia, a vulnerable mid-stratum tree endemic to lowland subtropical rainforests of southeast Queensland, Australia. We compared performance of two binomial models—Classification and Regression Trees (CART) and Generalised Additive Models (GAM)—with Maximum Entropy (MAXENT) models developed from (i) presence records and available absence data and (ii) developed using presence records and background data. The GAM model was the best performer across the range of evaluation measures employed, however all models were assessed as potentially useful for informing in situ conservation of M. integrifolia, A significant loss in the amount of M. integrifolia habitat has occurred (p < 0.05), with only 37% of former habitat (pre-clearing) remaining in 2003. Remnant patches are significantly smaller, have larger edge-to-area ratios and are more isolated from each other compared to pre-clearing configurations (p < 0.05). Whilst the network of suitable habitat patches is still largely intact, there are numerous smaller patches that are more isolated in the contemporary landscape compared with their connectedness before clearing. These results suggest that in situ conservation of M. integrifolia may be best achieved through a landscape approach that considers the relative contribution of small remnant habitat fragments to the species as a whole, as facilitating connectivity among the entire network of habitat patches.

Do drivers respond emotionally and behaviourally differently to an intentionally anger provoking driving situation than to an ambiguous, but potentially provocative, one? Results of a self-report survey.

Aggressive driving is considered an important road-safety concern for drivers in highly motorised countries. However, understanding of the causes and maintenance factors fundamental to aggressive driving is limited. In keeping with theoretical advances from general aggression research such as the General Aggression Model (GAM), research has begun to examine the emotional and cognitive antecedents of aggressive driving in order to better understand the underlying processes motivating aggressive driving. Early findings in the driving area have suggested that greater levels of aggression are elicited in response to an intentionally aggressive on-road event. In contrast, general aggression research suggests that greater levels of aggression are elicited in response to an ambiguous event. The current study examined emotional and cognitive responses to two hypothetical driving scenarios with differing levels of aggressive intent (intentional versus ambiguous). There was also an interest in whether factors influencing responses were different for hostile aggression (that is, where the action is intended to harm the other) versus instrumental aggression (that is, where the action is motivated by an intention to remove an impediment or attain a goal). Results were that significantly stronger negative emotion and negative attributions, as well as greater levels of threat were reported in response to the scenario which was designed to appear intentional in nature. In addition, participants were more likely to endorse an aggressive behavioural response to a situation that appeared deliberately aggressive than to one where the intention was ambiguous. Analyses to determine if greater levels of negative emotions and cognitions are able to predict aggressive responses provided different patterns of results for instrumental aggression from those for hostile aggression. Specifically, for instrumental aggression, negative emotions and negative attributions were significant predictors for both the intentional and the ambiguous scenarios. In addition, perceived threat was also a significant predictor where the other driver’s intent was clearly aggressive. However, lower rather than higher, levels of perceived threat were associated with greater endorsement of an aggressive response. For hostile aggressive behavioural responses, trait aggression was the strongest predictor for both situations. Overall the results suggest that in the driving context, instrumental aggression is likely to be a much more common response than hostile aggression. Moreover, aggressive responses are more likely in situations where another driver’s behaviour is clearly intentional rather than ambiguous. The results also support the conclusion that there may be different underlying mechanisms motivating an instrumental aggressive response to those motivating a hostile one. In addition, understanding the emotions and cognitions underlying aggressive driving responses may be helpful in predicting and intervening to reduce driving aggression. The finding that drivers appear to regard tailgating as an instrumental response is of concern since this behaviour has the potential to result in crashes.

Assessing the short-term effects of heatwaves on mortality and morbidity in Brisbane, Australia : comparison of case-crossover and time series analyses

Background Heat-related impacts may have greater public health implications as climate change continues. It is important to appropriately characterize the relationship between heatwave and health outcomes. However, it is unclear whether a case-crossover design can be effectively used to assess the event- or episode-related health effects. This study examined the association between exposure to heatwaves and mortality and emergency hospital admissions (EHAs) from non-external causes in Brisbane, Australia, using both case-crossover and time series analyses approaches. Methods Poisson generalised additive model (GAM) and time-stratified case-crossover analyses were used to assess the short-term impact of heatwaves on mortality and EHAs. Heatwaves exhibited a significant impact on mortality and EHAs after adjusting for air pollution, day of the week, and season. Results For time-stratified case-crossover analysis, odds ratios of mortality and EHAs during heatwaves were 1.62 (95% confidence interval (CI): 1.36–1.94) and 1.22 (95% CI: 1.14–1.30) at lag 1, respectively. Time series GAM models gave similar results. Relative risks of mortality and EHAs ranged from 1.72 (95% CI: 1.40–2.11) to 1.81 (95% CI: 1.56–2.10) and from 1.14 (95% CI: 1.06–1.23) to 1.28 (95% CI: 1.21–1.36) at lag 1, respectively. The risk estimates gradually attenuated after the lag of one day for both case-crossover and time series analyses. Conclusions The risk estimates from both case-crossover and time series models were consistent and comparable. This finding may have implications for future research on the assessment of event- or episode-related (e.g., heatwave) health effects.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Investigation into chemistry of new particle formation and growth in subtropical urban environment

The role of different chemical compounds, particularly organics, involved in the new particle formation (NPF) and its consequent growth are not fully understood. Therefore, this study was conducted to investigate the chemistry of aerosol particles during NPF events in an urban subtropical environment. Aerosol chemical composition was measured along with particle number size distribution (PNSD) and several other air quality parameters at five sites across an urban subtropical environment. An Aerodyne compact Time-of-Flight Aerosol Mass Spectrometer (c-TOF-AMS) and a TSI Scanning Mobility Particle Sizer (SMPS) measured aerosol chemical composition and PNSD, respectively. Five NPF events, with growth rates in the range 3.3-4.6 nm, were detected at two sites. The NPF events happened on relatively warmer days with lower humidity and higher solar radiation. Temporal percent fractions of nitrate, sulphate, ammonium and organics were modelled using the Generalised Additive Model (GAM), with a basis of penalised spline. Percent fractions of organics increased after the NPF events, while the mass fraction of ammonium and sulphate decreased. This uncovered the important role of organics in the growth of newly formed particles. Three organic markers, factors f43, f44 and f57, were calculated and the f44 vs f43 trends were compared between nucleation and non-nucleation days. f44 vs f43 followed a different pattern on nucleation days compared to non-nucleation days, whereby f43 decreased for vehicle emission generated particles, while both f44 and f43 decreased for NPF generated particles. It was found for the first time that vehicle generated and newly formed particles cluster in different locations on f44 vs f43 plot and this finding can be used as a tool for source apportionment of measured particles.

Modelling the distribution and relative abundance of feral camels in the Northern Territory using count data

The objectives of this study were to predict the potential distribution, relative abundance and probability of habitat use by feral camels in southern Northern Territory. Aerial survey data were used to model habitat association. The characteristics of ‘used’ (where camels were observed) v. ‘unused’ (pseudo-absence) sites were compared. Habitat association and abundance were modelled using generalised additive model (GAM) methods. The models predicted habitat suitability and the relative abundance of camels in southern Northern Territory. The habitat suitability maps derived in the present study indicate that camels have suitable habitat in most areas of southern Northern Territory. The index of abundance model identified areas of relatively high camel abundance. Identifying preferred habitats and areas of high abundance can help focus control efforts.