Machine Learning Pipeline for Exoplanet Classification

Planet identification has typically been a tasked performed exclusively by teams of astronomers and astrophysicists using methods and tools accessible only to those with years of academic education and training. NASA’s Exoplanet Exploration program has introduced modern satellites capable of capturing a vast array of data regarding celestial objects of interest to assist with researching these objects. The availability of satellite data has opened up the task of planet identification to individuals capable of writing and interpreting machine learning models. In this study, several classification models and datasets are utilized to assign a probability of an observation being an exoplanet. A Random Forest Classifier was selected as the optimum machine learning model to classify objects of interest in the Cumulative Kepler Object of Information table. The Random Forest Classifier obtained a cross-validated accuracy score of 98%. 968 candidate observations have a greater than 95% probability of being an exoplanet. Finally, the Random Forest Classifier was made publicly accessible by an application programming interface (API) and an Azure Container Instance web service in the Microsoft Azure cloud

Restoring freshwater habitat mosaics to promote resilience of vulnerable salmon populations

Phenotypic diversity and abundance drive salmon resilience in the face of increasing environmental variability. But what happens when human activities fundamentally alter the habitat complexity that drives this diversity? And how can we restore habitats to recover both diversity and abundance to support salmon persistence in a warming climate? Here, we looked at the impact of a large watershed restoration effort on the abundance and climate resilience of the three remaining core natural spring-run Chinook Salmon populations in the California Central Valley (Butte, Mill, and Deer Creek). Butte Creek fish, which have floodplain access, had higher overall productivity and faster juvenile growth compared with Mill and Deer Creek populations, and the proportion of floodplain inundation was positively correlated with Butte Creek adult abundance two years later. While Butte Creek exhibited significant increases in abundance post-restoration (~2000%), it generally exhibited lower phenotypic diversity and only a marginal increase in population stability after restoration based on the coefficient of variation (CV). In particular, Butte Creek salmon tended to exhibit larger drops in escapement following dry years (e.g., return years 2010, 2017) compared with Mill and Deer Creek populations, presumably due to limited inundation of its downstream floodplain. The late-migrating juvenile strategy (i.e., yearling), which disproportionately supported Mill and Deer Creek populations during droughts, was uncommon among Butte Creek adults (averaging 60% of returns for Mill and Deer Creek vs. 0.3% for Butte Creek). Increased spring-run stock complex stability was found, post-restoration, when combining the three spring-run populations (i.e., lower aggregate CV). However, among-river pairwise correlations also suggested increased synchronization in population abundances post-restoration, potentially due to increasing frequency and severity of extreme climatic events (e.g., droughts and ocean warming). This study underscores the importance of restoring a connected mosaic of aquatic habitats across modified landscapes, such as cold water refugia and floodplains, to preserve multiple (across-population) life history pathways for increasing salmon stock complex stability and abundance. These landscape-scale process-based habitat restoration efforts are likely to be crucial for the successful long-term recovery of vulnerable species in a rapidly changing climate.publishedVersio

Chasing the conversation:Autistic experiences of speech perception

Background and aims: Humans communicate primarily through spoken language and speech perception is a core function of the human auditory system. Among the autistic community, atypical sensory reactivity and social communication difficulties are pervasive, yet the research literature lacks in-depth self-report data on speech perception in this population. The present study aimed to elicit detailed first-person accounts of autistic individuals’ abilities and difficulties perceiving the spoken word. Methods: Semi-structured interviews were conducted with nine autistic adults. The interview schedule addressed interviewees’ experiences of speech perception, factors influencing those experiences, and responses to those experiences. Resulting interview transcripts underwent thematic analysis. The six-person study team included two autistic researchers, to reduce risk of neurotypical ‘overshadowing’ of autistic voices. Results: Most interviewees reported pronounced difficulties perceiving speech in the presence of competing sounds. They emphasised that such listening difficulties are distinct from social difficulties, though the two can add and interact. Difficulties were of several varieties, ranging from powerful auditory distraction to drowning out of voices by continuous sounds. Contributing factors encompassed not only features of the soundscape but also non-acoustic factors such as multisensory processing and social cognition. Participants also identified compounding factors, such as lack of understanding of listening difficulties. Impacts were diverse and sometimes disabling, affecting socialising, emotions, fatigue, career, and self-image. A wide array of coping mechanisms was described. Conclusions: The first in-depth qualitative investigation of autistic speech-perception experiences has revealed diverse and widespread listening difficulties. These can combine with other internal, interpersonal, and societal factors to induce profound impacts. Lack of understanding of such listening difficulties – by the self, by communication partners, by institutions, and especially by clinicians – appears to be a crucial exacerbating factor. Many autistic adults have developed coping strategies to lessen speech-perception difficulties or mitigate their effects, and these are generally self-taught due to lack of clinical support. Implications: There is a need for carefully designed, adequately powered confirmatory research to verify, quantify, and disentangle the various forms of listening difficulty, preferably using large samples to explore heterogeneity. More immediate benefit might be obtained through development of self-help and clinical guidance materials, and by raising awareness of autistic listening experiences and needs, among the autistic community, communication partners, institutions, and clinicians

Covalent enzyme coupling on cellulose acetate membranes for glucose sensor development

International audienceMethods for immobilizing glucose oxidase (GOx) on cellulose acetate (CA) membranes are compared. The optimal method involves covalent coupling of bovine serum albumin (BSA) to CA membrane and a subsequent reaction of the membrane with GOx, which has previously been activated with an excess of p-benzoquinone. This coupling procedure is fairly reproducible and allows the preparation of thin membranes (5-20 µm) showing high surface activities (1-3 U/cm2) which are stable over a period of 1-3 months. Electrochemical and radiolabeling experiments show that enzyme inactivation as a result of immobilization is negligible. A good correlation between surface activity of membranes and their GOx load is observed

Cigarette smoke and lipopolysaccharide induce a proliferative airway smooth muscle phenotype

Background: A major feature of chronic obstructive pulmonary disease (COPD) is airway remodelling, which includes an increased airway smooth muscle (ASM) mass. The mechanisms underlying ASM remodelling in COPD are currently unknown. We hypothesized that cigarette smoke (CS) and/or lipopolysaccharide (LPS), a major constituent of CS, organic dust and gram-negative bacteria, that may be involved in recurrent airway infections and exacerbations in COPD patients, would induce phenotype changes of ASM. Methods: To this aim, using cultured bovine tracheal smooth muscle (BTSM) cells and tissue, we investigated the direct effects of CS extract (CSE) and LPS on ASM proliferation and contractility. Results: Both CSE and LPS induced a profound and concentration-dependent increase in DNA synthesis in BTSM cells. CSE and LPS also induced a significant increase in BTSM cell number, which was associated with increased cyclin D1 expression and dependent on activation of ERK 1/2 and p38 MAP kinase. Consistent with a shift to a more proliferative phenotype, prolonged treatment of BTSM strips with CSE or LPS significantly decreased maximal methacholine- and KCl-induced contraction. Conclusions: Direct exposure of ASM to CSE or LPS causes the induction of a proliferative, hypocontractile ASM phenotype, which may be involved in airway remodelling in COPD

CSR and related terms in SME owner-managers' mental models in six European countries: national context matters

As a contribution to the emerging field of corporate social responsibility (CSR) cognition, this article reports on the findings of an exploratory study that compares SME owner–managers’ mental models with regard to CSR and related concepts across six European countries (Belgium, Italy, Norway, France, UK, Spain). Utilising Repertory Grid Technique, we found that the SME owner–managers’ mental models show a few commonalities as well as a number of differences across the different country samples. We interpret those differences by linking individual cognition to macro-environmental variables, such as language, national traditions and dissemination mechanisms. The results of our exploratory study show that nationality matters but that classifications of countries as found in the comparative capitalism literature do not exactly mirror national differences in CSR cognition and that these classifications need further differentiation. The findings from our study raise questions on the universality of cognition of academic management concepts and warn that promotion of responsible business practice should not rely on the use of unmediated US American management terminology

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability