‘The Rest is Silence’:Psychogeography, Soundscape and Nostalgia in Pat Collins’ Silence

Guy Debord defines the term psychogeography as 'the study of the precise laws and specific effects of the geographical environment, consciously organised or not, on the emotions and behaviour of individuals' (Debord 1955: 23). Similar to the belief of psychogeographers that the geography of an environment has a psychological effect on the human mind, proponents of acoustic ecology such as R. Murray Schafer hold that humans are affected by the sound of the environment in which they find themselves. Further to this, they examine the extent to which soundscapes can be shaped by human behaviour. Recently a body of Irish films has emerged that directly engages with the Irish soundscape and landscape on a psychogeographical level. Rather than using landscape as a physical space for the locus of action, these representations of the Irish landscape allow for an engagement with the aesthetic effects of the geographical landscape as a reflection of the psychological states of the protagonists. Bearing this in mind, this article examines how Silence (Collins 2012) arguably demonstrates the most overt and conscious incursion into this area to date. It specifically interrogates how the filmic representation of the psychogeography and soundscape of the Irish rural landscape can serve to express emotion, alienation and nostalgia, thus confronting both the Irish landscape and the weight of its associated history

CAM-related changes in chloroplastic metabolism of Mesembryanthemum crystallinum L.

Crassulacean acid metabolism (CAM) is an intriguing metabolic strategy to maintain photosynthesis under conditions of closed stomata. A shift from C3 photosynthesis to CAM in Mesembryanthemum crystallinum plants was induced by high salinity (0.4 M NaCl). In CAM-performing plants, the quantum efficiencies of photosystem II and I were observed to undergo distinct diurnal fluctuations that were characterized by a strong decline at the onset of the day, midday recovery, and an evening drop. The temporal recovery of both photosystems’ efficiency at midday was associated with a more rapid induction of the electron transport rate at PSII. This recovery of the photosynthetic apparatus at midday was observed to be accompanied by extreme swelling of thylakoids. Despite these fluctuations, a persistent effect of CAM was the acceptor side limitation of PSI during the day, which was accompanied by a strongly decreased level of Rubisco protein. Diurnal changes in the efficiency of photosystems were parallel to corresponding changes in the levels of mRNAs for proteins of PSII and PSI reaction centers and for rbcL, reaching a maximum in CAM plants at midday. This might reflect a high demand for new protein synthesis at this time of the day. Hybridization of run-on transcripts with specific probes for plastid genes of M. crystallinum revealed that the changes in plastidic mRNA levels were regulated at the level of transcription

Dipeptidyl peptidase-1 inhibition in patients hospitalised with COVID-19: a multicentre, double-blind, randomised, parallel-group, placebo-controlled trial

Background Neutrophil serine proteases are involved in the pathogenesis of COVID-19 and increased serine protease activity has been reported in severe and fatal infection. We investigated whether brensocatib, an inhibitor of dipeptidyl peptidase-1 (DPP-1; an enzyme responsible for the activation of neutrophil serine proteases), would improve outcomes in patients hospitalised with COVID-19. Methods In a multicentre, double-blind, randomised, parallel-group, placebo-controlled trial, across 14 hospitals in the UK, patients aged 16 years and older who were hospitalised with COVID-19 and had at least one risk factor for severe disease were randomly assigned 1:1, within 96 h of hospital admission, to once-daily brensocatib 25 mg or placebo orally for 28 days. Patients were randomly assigned via a central web-based randomisation system (TruST). Randomisation was stratified by site and age (65 years or ≥65 years), and within each stratum, blocks were of random sizes of two, four, or six patients. Participants in both groups continued to receive other therapies required to manage their condition. Participants, study staff, and investigators were masked to the study assignment. The primary outcome was the 7-point WHO ordinal scale for clinical status at day 29 after random assignment. The intention-to-treat population included all patients who were randomly assigned and met the enrolment criteria. The safety population included all participants who received at least one dose of study medication. This study was registered with the ISRCTN registry, ISRCTN30564012. Findings Between June 5, 2020, and Jan 25, 2021, 406 patients were randomly assigned to brensocatib or placebo; 192 (47·3%) to the brensocatib group and 214 (52·7%) to the placebo group. Two participants were excluded after being randomly assigned in the brensocatib group (214 patients included in the placebo group and 190 included in the brensocatib group in the intention-to-treat population). Primary outcome data was unavailable for six patients (three in the brensocatib group and three in the placebo group). Patients in the brensocatib group had worse clinical status at day 29 after being randomly assigned than those in the placebo group (adjusted odds ratio 0·72 [95% CI 0·57–0·92]). Prespecified subgroup analyses of the primary outcome supported the primary results. 185 participants reported at least one adverse event; 99 (46%) in the placebo group and 86 (45%) in the brensocatib group. The most common adverse events were gastrointestinal disorders and infections. One death in the placebo group was judged as possibly related to study drug. Interpretation Brensocatib treatment did not improve clinical status at day 29 in patients hospitalised with COVID-19. Funding Sponsored by the University of Dundee and supported through an Investigator Initiated Research award from Insmed, Bridgewater, NJ; STOP-COVID19 trial

Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs

Monitoring water quality in reservoirs is essential for the maintenance of aquatic ecosystems and socioeconomic services. In this scenario, the observation of abrupt elevations of physicochemical parameters, such as turbidity and other indicators, can signal anomalies associated with the occurrence of critical events, requiring operational actions and planning to mitigate negative environmental impacts on water resources. This work aims to integrate Machine Learning methods specialized in anomaly detection with data obtained from remote sensing images to identify with high turbidity events in the surface water of the Três Marias Hydroelectric Reservoir. Four distinct threshold-based scenarios were evaluated, in which the overall performance, based on F1-score, showed decreasing trends as the thresholds became more restrictive. In general, the anomaly identification maps generated through the models ratified the applicability of the methods in the diagnosis of surface water in reservoirs in distinct hydrological contexts (dry and wet), effectively identifying locations with anomalous turbidity values