Thermal conductivity and resonant multipole interactions

The influence of multipole interactions on exchanges of rotational energy in molecular collisions was investigated by means of a simple two-state impact parameter approximation. The calculations are restricted to linear molecules and to dipole and quadrupole fields. The effects of such exchanges on the thermal conductivity of gases and of gaseous mixtures was investigated, after correcting the kinetic theory of mixtures to include exchanges between unlike molecules. It was found that dipole-quadrupole and quadrupole-quadrupole interactions may have a significant effect for molecules with low moments of inertia. In particular, quadrupole interactions are important in the hydrogen isotopes, and the calculated corrections for H2 are consistent with recent experimental work by Harris. The theory seems capable of accounting for the anomalies observed in HF + DF and HCl + DCl mixtures in terms of multipolar accidental resonances

Drugs, crime and methadone.

This paper seeks to examine the evidence of causal links between drug -misuse, particularly heroin, and criminal behaviour. While it is generally accepted that such a link*exists, the question is asked whether the treatment of drug misuse has an effect on levels of drug misuse and on criminal activity. The value of methadone treatment as one of several treatment modalities, is examined in this context. The author does not wish to advocate one form of treatment over another but merely to investigate what can be gained from a study of the literature

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx. 2.6 million citizens in Denmark, SARS-CoV-2 PCR tests were performed on subjects suspected for COVID-19 disease; 3944 cases had at least one positive test and were subjected to further analysis. SARS-CoV-2 positive cases from the United Kingdom Biobank was used for external validation. The ML models predicted the risk of death (Receiver Operation Characteristics—Area Under the Curve, ROC-AUC) of 0.906 at diagnosis, 0.818, at hospital admission and 0.721 at Intensive Care Unit (ICU) admission. Similar metrics were achieved for predicted risks of hospital and ICU admission and use of mechanical ventilation. Common risk factors, included age, body mass index and hypertension, although the top risk features shifted towards markers of shock and organ dysfunction in ICU patients. The external validation indicated fair predictive performance for mortality prediction, but suboptimal performance for predicting ICU admission. ML may be used to identify drivers of progression to more severe disease and for prognostication patients in patients with COVID-19. We provide access to an online risk calculator based on these findings