Keys, Wallet, and Pistol: The Seventh Circuit Establishes a Constitutional Right to Carry Firearms Outside of the Home

In 2012, the Seventh Circuit decided Moore v. Madigan, declaring Illinois\u27 ban on concealed carry unconstitutional. With this decision, the court extended the Supreme Court\u27s previous Second Amendment jurisprudence. In 2008, the Supreme Court held in District of Columbia v. Heller that the constitutional right to bear arms includes a right to self-defense in the home; however, the Court did not state whether that right extended to a constitutional right to carry handguns in public. In his Moore opinion, Judge Posner decided that because the Second Amendment is a right to self-defense, citizens must be allowed to exercise that right outside their homes. By couching the right to bear arms in personal protection, the Seventh Circuit provided a logical and succinct argument to extend the right to bear arms outside of the home and into the street. This Note will discuss how the Seventh Circuit reached this monumental decision and the implications the decision has on the right to carry. It will conclude by showing that the Seventh Circuit\u27s opinion is consistent with the Supreme Court\u27s previous Second Amendment rulings

Keys, Wallet, and Pistol: The Seventh Circuit Establishes a Constitutional Right to Carry Firearms Outside of the Home

In 2012, the Seventh Circuit decided Moore v. Madigan, declaring Illinois\u27 ban on concealed carry unconstitutional. With this decision, the court extended the Supreme Court\u27s previous Second Amendment jurisprudence. In 2008, the Supreme Court held in District of Columbia v. Heller that the constitutional right to bear arms includes a right to self-defense in the home; however, the Court did not state whether that right extended to a constitutional right to carry handguns in public. In his Moore opinion, Judge Posner decided that because the Second Amendment is a right to self-defense, citizens must be allowed to exercise that right outside their homes. By couching the right to bear arms in personal protection, the Seventh Circuit provided a logical and succinct argument to extend the right to bear arms outside of the home and into the street. This Note will discuss how the Seventh Circuit reached this monumental decision and the implications the decision has on the right to carry. It will conclude by showing that the Seventh Circuit\u27s opinion is consistent with the Supreme Court\u27s previous Second Amendment rulings

Individuality and stability of the koala (Phascolarctos cinereus) faecal microbiota through time

Gut microbiota studies often rely on a single sample taken per individual, representing a snapshot in time. However, we know that gut microbiota composition in many animals exhibits intra-individual variation over the course of days to months. Such temporal variations can be a confounding factor in studies seeking to compare the gut microbiota of different wild populations, or to assess the impact of medical/veterinary interventions. To date, little is known about the variability of the koala (Phascolarctos cinereus) gut microbiota through time. Here, we characterise the gut microbiota from faecal samples collected at eight timepoints over a month for a captive population of South Australian koalas (n individuals = 7), and monthly over 7 months for a wild population of New South Wales koalas (n individuals = 5). Using 16S rRNA gene sequencing, we found that microbial diversity was stable over the course of days to months. Each koala had a distinct faecal microbiota composition which in the captive koalas was stable across days. The wild koalas showed more variation across months, although each individual still maintained a distinct microbial composition. Per koala, an average of 57 (±16) amplicon sequence variants (ASVs) were detected across all time points; these ASVs accounted for an average of 97% (±1.9%) of the faecal microbial community per koala. The koala faecal microbiota exhibits stability over the course of days to months. Such knowledge will be useful for future studies comparing koala populations and developing microbiota interventions for this regionally endangered marsupial.Raphael Eisenhofer, Kylie L. Brice, Michaela DJ Blyton, Scott E. Bevins, Kellie Leigh, Brajesh K. Singh, Kristofer M. Helgen, Ian Hough, Christopher B. Daniels, Natasha Speight and Ben D. Moor

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

Developing an energy satellite for an MRIO virtual laboratory

Sanitary Engineerin