Identifying Robust Milk Production Systems

The European dairy industry faces an increasingly uncertain world. There is uncertainty about subsidy payment levels and compliance conditions, global competition, price variability, consumer demand, carbon footprints, water quality, biodiversity, landscapes, animal welfare, food safety, etc. The future is uncertain because it cannot be reliably predicted; therefore the industry must adopt production systems that will be financially robust over a wide range of possible circumstances. Adding to the uncertainty is a lack of consensus regarding the specific characteristics of these sustainable production systems. In this interdisciplinary research project we developed a profit maximizing whole-farm model and employ it to identify robust milk production systems for Northern Ireland under varying market, policy and farm family conditions. The milk production systems incorporated into the model involve variations in date of calving, quantity of concentrate fed, and nature of forage utilized. The model also incorporates a disaggregated specification of time use within farm households and links intra-household resource allocation to the process of agricultural technology adoption. This work illustrates how profit maximizing whole-farm models can play a decision support role in helping farmers, agricultural researchers, agribusiness advisers and agricultural policy makers to identify economically sustainable agricultural production systems.Production Economics,

Differentiable Grey-box Modelling of Phaser Effects using Frame-based Spectral Processing

Machine learning approaches to modelling analog audio effects have seen intensive investigation in recent years, particularly in the context of non-linear time-invariant effects such as guitar amplifiers. For modulation effects such as phasers, however, new challenges emerge due to the presence of the low-frequency oscillator which controls the slowly time-varying nature of the effect. Existing approaches have either required foreknowledge of this control signal, or have been non-causal in implementation. This work presents a differentiable digital signal processing approach to modelling phaser effects in which the underlying control signal and time-varying spectral response of the effect are jointly learned. The proposed model processes audio in short frames to implement a time-varying filter in the frequency domain, with a transfer function based on typical analog phaser circuit topology. We show that the model can be trained to emulate an analog reference device, while retaining interpretable and adjustable parameters. The frame duration is an important hyper-parameter of the proposed model, so an investigation was carried out into its effect on model accuracy. The optimal frame length depends on both the rate and transient decay-time of the target effect, but the frame length can be altered at inference time without a significant change in accuracy.Comment: Accepted for publication in Proc. DAFx23, Copenhagen, Denmark, September 202

Open source clinical science for emerging infections

International audienc

Global outbreak research: harmony not hegemony

No abstract available

Functional impact of global rare copy number variation in autism spectrum disorders

The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviors1. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability (ID)2. While ASDs are known to be highly heritable (~90%)3, the underlying genetic determinants are still largely unknown. Here, we analyzed the genome-wide characteristics of rare (<1% frequency) copy number variation (CNV) in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic CNVs (1.19 fold, P= 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P= 3.4×10−4). Among the CNVs, there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes like SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene-sets involved in cellular proliferation, projection and motility, and GTPase/Ras signaling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways

Procalcitonin Is Not a Reliable Biomarker of Bacterial Coinfection in People With Coronavirus Disease 2019 Undergoing Microbiological Investigation at the Time of Hospital Admission

Abstract Admission procalcitonin measurements and microbiology results were available for 1040 hospitalized adults with coronavirus disease 2019 (from 48 902 included in the International Severe Acute Respiratory and Emerging Infections Consortium World Health Organization Clinical Characterisation Protocol UK study). Although procalcitonin was higher in bacterial coinfection, this was neither clinically significant (median [IQR], 0.33 [0.11–1.70] ng/mL vs 0.24 [0.10–0.90] ng/mL) nor diagnostically useful (area under the receiver operating characteristic curve, 0.56 [95% confidence interval, .51–.60]).</jats:p

Implementation of corticosteroids in treating COVID-19 in the ISARIC WHO Clinical Characterisation Protocol UK:prospective observational cohort study

BACKGROUND: Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. METHODS: We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. FINDINGS: Between June 17, 2020, and April 14, 2021, 47 795 (75·2%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86·6%] of 12 909 vs 36 415 [72·4%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0·79 [95% CI 0·70–0·89], p=0·0001, for 70–79 years; 0·52 [0·46–0·58], p80 years), independent of patient demographics and illness severity. 84 (54·2%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27·5% in the week before June 16, 2020, to 75–80% in January, 2021. INTERPRETATION: Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant women. This could reflect appropriate clinical decision making, but the possibility of inequitable access to life-saving care should be considered. FUNDING: UK National Institute for Health Research and UK Medical Research Council