Demand or supply? An empirical exploration of the effects of climate change on the macroeconomy

Using an original panel data set for 24 OECD countries over the sample 1990–2019 and a multivariate empirical macroeconomic framework for business cycle analysis, the paper tests the combined macroeconomic effects of climate change, environmental policies and green innovation. Overall, we find evidence of significant macroeconomic effects over the business cycle: physical risks act as negative demand shocks while transition risks act as downward supply movements. The disruptive effects on the economy typical of a disorderly transition are exacerbated for low income, high emission countries with no history of environmental policy or with a high exposure to natural disasters. In general, one size does not fit all and results support the need for a (possibly country-specific) policy mix to counteract climate change with a balance between demand-pull and technology-push policies

A genealogical survey on the main bloodline of the Australian Cattle Dog in Italy

This paper presents the results of genetic variability analyses using genealogical data on the main genetic bloodline of the Australian Cattle Dog in Italy, a line that has had a significant impact on the development of the breed. All the genealogical data on the progeny and ancestors of one of the first stallions introduced in Italy were considered, i.e. Cattlefarm's Comeback Jack born on 1/2/1997 in Finland. Animals from the bloodline born between 1962 and 2019 were considered. A total number of 1722 animals were found to be from the line which represents the entire population (WP), including the basic population (BP) and the reference population (RP) defined as the animals currently living. A total of 982 animals were in the RP, with the oldest living dogs born in 2004. A total of 854 dogs were inbred. The average inbreeding coefficient (F) in the RP was 5.1%, while the average inbreeding of the inbred animals was 5.8%. The F was < 0.10 in 711 dogs (77.3% of inbred), and > 0.20 in only 36 dogs (3.91% of inbred). Fifteen traced generations were highlighted. A maximum average inbreeding value (6.45%) was observed in the dogs with 11 traced generations. This research highlighted the good genetic variability of this Australian Cattle Dog bloodline thanks to the efficient management of the breeders who in the past introduced some stallions from abroad. Currently, the lines in Italy are not sufficiently high to prevent inbreeding in the new matings, which is becoming frequent. It is, therefore, important to continue to import new stallions for reproduction to expand the genetic variability. However, at the same time, the old lines need to be preserved genetically, aptitudinally and morphologically, as they are an important heritage of the breed in Italy

Neurophysiological Vocal Source Modeling for Biomarkers of Disease

Speech is potentially a rich source of biomarkers for detecting and monitoring neuropsychological disorders. Current biomarkers typically comprise acoustic descriptors extracted from behavioral measures of source, filter, prosodic and linguistic cues. In contrast, in this paper, we extract vocal features based on a neurocomputational model of speech production, reflecting latent or internal motor control parameters that may be more sensitive to individual variation under neuropsychological disease. These features, which are constrained by neurophysiology, may be resilient to artifacts and provide an articulatory complement to acoustic features. Our features represent a mapping from a low-dimensional acoustics-based feature space to a high-dimensional space that captures the underlying neural process including articulatory commands and auditory and somatosensory feedback errors. In particular, we demonstrate a neurophysiological vocal source model that generates biomarkers of disease by modeling vocal source control. By using the fundamental frequency contour and a biophysical representation of the vocal source, we infer two neuromuscular time series whose coordination provides vocal features that are applied to depression and Parkinson’s disease as examples. These vocal source coordination features alone, on a single held vowel, outperform or are comparable to other features sets and reflect a significant compression of the feature space.United States. Air Force (Contract No. FA8721-05-C-0002)United States. Air Force (Contract No. FA8702-15- D-0001

Fire Weather Index application in north-western Italy

International audiencePiedmont region is located in North-Western Italy and is surrounded by the alpine chain and by the Appennines. The region is covered by a wide extension of forests, mainly in its mountain areas (the forests cover 36% of the regional territory). Forested areas are interested by wildfire events. In the period 1997?2005 Piedmont was interested by an average 387 forest fires per year, covering an average 1926 ha of forest per year. Meteorological conditions like long periods without precipitation contribute to create favourable conditions to forest fire development, while the fire propagation is made easier by the foehn winds, frequently interesting the region in winter and spring particularly. The meteorological danger index FWI (Fire Weather Index) was developed by Van Wagner (1987) for the Canadian Forestry Service, providing a complete description of the behaviour of the different forest components in response to the changing weather conditions. We applied the FWI to the Piedmont region on warning areas previously defined for fire management purposes. The meteorological data-set is based on the data of the very-dense non-GTS network of weather stations managed by Arpa Piemonte. The thresholds for the definition of a danger scenarios system were defined comparing historical FWI data with fires occurred on a 5 years period. The implementation of a prognostic FWI prediction system is planned for the early 2008, involving the use of good forecasts of weather parameters at the station locations obtained by the Multimodel SuperEnsemble post-processing technique

Attentional biases in problem and non-problem gamblers

Background: From a cognitive perspective, attentional biases are deemed as factors responsible in the onset and development of gambling disorder. However, knowledge relating to attentional processes in gambling is scarce and studies to date have reported contrasting results. Moreover, no study has ever examined which component and what type of bias are involved in attentional polarization in gambling. Methods: In the present study, 108 Italian participants, equally divided into problem and non-problem gamblers were administered a modified Posner Task, an attentional paradigm in which – through the manipulation of stimuli presentation time – it is possible to measure both initial orienting and maintenance of attention. In addition to the experimental task, participants completed self-report measures involving (i) craving (Gambling Craving Scale), (ii) depression, anxiety and stress (Depression Anxiety Stress Scale) and (iii) emotional dysregulation (Difficulties in Emotion Regulation Scale). Results: Analyses revealed facilitation in detecting gambling-related stimuli at the encoding level in problem gamblers but not in non-problem gamblers. Compared to non-problem gamblers, problem gamblers also reported higher levels of craving, emotional dysregulation, and negative mood states. Furthermore, all measures correlated with the gambling severity. Limitations: The use of indirect measure of attentional bias could be less accurate compared to direct measures. Conclusions: The facilitation in detecting gambling-related stimuli in problem gamblers and the correlation between subjective craving and facilitation bias suggests that attentional polarization could not be due to a conditioning process but that motivational factors such as craving could induce addicted-related seeking-behaviors

Attentional bias in non-problem gamblers, problem gamblers, and abstinent pathological gamblers: an experimental study

Background Attentional biases have been recognized as factors responsible for the maintenance of gambling problems. To date, no study has ever assessed the attentional biases among problem gamblers that have discontinued gambling (e.g., abstinent gamblers in treatment). Methods The sample consisted of 75 participants comprising three groups: non-problem gamblers, problem gamblers, and abstinent pathological gamblers undergoing treatment. The groups were discriminated using South Oaks Gambling Screen scores, with the exception of the abstinent pathological gamblers that already had a DSM-5 diagnosis for gambling disorder. Participants carried out a modified Posner Task for the assessment of attentional bias for gambling stimuli and completed the Depression Anxiety Stress Scale and the Gambling Craving Scale. Results Abstinent pathological gamblers showed an avoidance bias in the maintenance of attention, whereas problem gamblers exhibited a facilitation in detecting gambling stimuli. No biases were detected in non-problem gamblers. The results also demonstrated that compared to the other groups, abstinent pathological gamblers showed high emotional stress and problem gamblers reported a higher level of craving. Limitations The sample size limits the generalizability of results. Conclusions The present study demonstrated that attentional biases affect the maintenance and the discontinuation of gambling activities, and that the subjective feeling of craving for gambling may facilitate problem gamblers’ attention towards gambling stimuli

Mentalizing failures, emotional dysregulation, and cognitive distortions among adolescent problem gamblers

Over the past decade, several studies have investigated the relationship between cognitive distortions and emotion regulation among adolescent gamblers, demonstrating the exacerbating role of alcohol consumption when co-occurring with gambling problems. An important construct, that to date has been largely neglected, is mentalizing (i.e. the ability to refect on one’s own and others’ mental states). The aim of the present study was (for the frst time) to investigate the relative contribution of mentalization, emotional dysregulation, cognitive distortions, and alcohol consumption among adolescent gamblers. A total of 396 students (69.2% females) aged 14–19 years were recruited from secondary schools in Southern Italy. Assessment measures included the South Oaks Gambling Screen Revised for Adolescents (SOGS-RA), the Refective Functioning Questionnaire (RFQ-8), the Diffculties in Emotion Regulation Scale (DERS), the Gambling Related Cognitions Scale (GRCS), and the Alcohol Use Disorders Identifcation Test (AUDIT). Regression analysis showed that, along with male gender, the best predictors of adolescent gambling were scores on two GRCS subscales (i.e., ‘inability to stop gambling’ and ‘interpretative bias’), the RFQ-8’s ‘uncertainty about mental states’ dimension, and the DERS ‘impulse control difculties’ factor, with the overall model explaining more than one-third of the total variance. The results clearly indicated that, along with gambling-related cognitive distortions, uncertainty about mental states, and difculties remaining in control of one’s behavior when experiencing negative emotions contributed signifcantly to problematic gambling among adolescents

Spinal cord atrophy in a primary progressive multiple sclerosis trial: Improved sample size using GBSI

Background: We aimed to evaluate the implications for clinical trial design of the generalised boundary-shift integral (GBSI) for spinal cord atrophy measurement. / Methods: We included 220 primary-progressive multiple sclerosis patients from a phase 2 clinical trial, with baseline and week-48 3DT1-weighted MRI of the brain and spinal cord (1 × 1 × 1 mm3), acquired separately. We obtained segmentation-based cross-sectional spinal cord area (CSA) at C1-2 (from both brain and spinal cord MRI) and C2-5 levels (from spinal cord MRI) using DeepSeg, and, then, we computed corresponding GBSI. / Results: Depending on the spinal cord segment, we included 67.4–98.1% patients for CSA measurements, and 66.9–84.2% for GBSI. Spinal cord atrophy measurements obtained with GBSI had lower measurement variability, than corresponding CSA. Looking at the image noise floor, the lowest median standard deviation of the MRI signal within the cerebrospinal fluid surrounding the spinal cord was found on brain MRI at the C1-2 level. Spinal cord atrophy derived from brain MRI was related to the corresponding measures from dedicated spinal cord MRI, more strongly for GBSI than CSA. Spinal cord atrophy measurements using GBSI, but not CSA, were associated with upper and lower limb motor progression. / Discussion: Notwithstanding the reduced measurement variability, the clinical correlates, and the possibility of using brain acquisitions, spinal cord atrophy using GBSI should remain a secondary outcome measure in MS studies, until further advancements increase the quality of acquisition and reliability of processing

Reconfigurable Boolean Logic using Magnetic Single-Electron Transistors

We propose a novel hybrid single-electron device for reprogrammable low-power logic operations, the magnetic single-electron transistor (MSET). The device consists of an aluminium single-electron transistors with a GaMnAs magnetic back-gate. Changing between different logic gate functions is realized by reorienting the magnetic moments of the magnetic layer which induce a voltage shift on the Coulomb blockade oscillations of the MSET. We show that we can arbitrarily reprogram the function of the device from an n-type SET for in-plane magnetization of the GaMnAs layer to p-type SET for out-of-plane magnetization orientation. Moreover, we demonstrate a set of reprogrammable Boolean gates and its logical complement at the single device level. Finally, we propose two sets of reconfigurable binary gates using combinations of two MSETs in a pull-down network

Rarity: Discovering rare cell populations from single-cell imaging data

MOTIVATION: Cell type identification plays an important role in the analysis and interpretation of single-cell data and can be carried out via supervised or unsupervised clustering approaches. Supervised methods are best suited where we can list all cell types and their respective marker genes a priori. While unsupervised clustering algorithms look for groups of cells with similar expression properties. This property permits the identification of both known and unknown cell populations, making unsupervised methods suitable for discovery. Success is dependent on the relative strength of the expression signature of each group as well as the number of cells. Rare cell types therefore present a particular challenge that are magnified when they are defined by differentially expressing a small number of genes. RESULTS: Typical unsupervised approaches fail to identify such rare sub-populations, and these cells tend to be absorbed into more prevalent cell types. In order to balance these competing demands, we have developed a novel statistical framework for unsupervised clustering, named Rarity, that enables the discovery process for rare cell types to be more robust, consistent and interpretable. We achieve this by devising a novel clustering method based on a Bayesian latent variable model in which we assign cells to inferred latent binary on/off expression profiles. This lets us achieve increased sensitivity to rare cell populations while also allowing us to control and interpret potential false positive discoveries. We systematically study the challenges associated with rare cell type identification and demonstrate the utility of Rarity on various IMC data sets. AVAILABILITY: Implementation of Rarity together with examples are available from the Github repository (https://github.com/kasparmartens/rarity). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online