Search Results (1,738)

Flexibility is advocated as an effective solution to address the growing need to alleviate grid congestion, necessitating efficient energy management strategies for industrial operations. This paper presents a mixed-integer linear programming (MILP)-based optimization framework for a flexible asset in an industrial setting, aiming to minimize operational costs and enhance energy efficiency. The method integrates dynamic pricing and real-time grid analysis, alongside a state estimation model using Extended Kalman Filtering (EKF) that improves the accuracy of system state predictions. Model Predictive Control (MPC) is employed for real-time adjustments. A real-world case studies from aquaculture industries and industrial power grids in Denmark demonstrates the approach. By leveraging dynamic pricing and grid signals, the system enables adaptive pump scheduling, achieving a 27% reduction in energy costs while maintaining voltage stability within 0.95–1.05 p.u. and ensuring operational safety. These results confirm the effectiveness of grid-aware, flexible control in reducing costs and enhancing stability, supporting the transition toward smarter, sustainable industrial energy systems. Full article

The main objective of this research is to obtain interesting estimates for Jensen’s gap in the integral sense, along with their applications. The convexity of a fifth-order absolute function is used to established proposed estimates of Jensen’s gap. We performed numerical computations to compare our estimates with previous findings. With the use of the primary findings, we are able to obtain improvements of the Hölder inequality and Hermite–Hadamard inequality. Furthermore, the primary results lead to some inequalities for power means and quasi-arithmetic means. We conclude by outlining the information theory applications of our primary inequalities. Full article

The BRAF V595E mutation analysis in canine urothelial carcinomas (UCs) has found its way into routine diagnostics, but no data analysis has been published until now. The present study aimed to estimate the distribution of age, sex, and breed in 8365 canine diagnostic samples submitted for BRAF mutation analysis during 2018–2024. The specimens included 8215 urine samples, 17 cytological, and 133 histopathological specimens, and were submitted in cases of suspected UC, to rule out UC, or for screening purposes. All samples were tested for the BRAF V595E mutation using droplet digital PCR (ddPCR). The data were statistically analysed and logistic regression models (Odds Ratio (OR)) were calculated. Compared to samples from mixed-breed dogs, the specimens from Scottish Terriers (OR: 4.21), Shetland Sheepdogs (OR: 2.65), Beagles (OR: 2.33), Fox Terriers (OR: 1.92), Staffordshire Bull Terriers (OR: 1.86), Magyar Vizslas (OR: 1.77), Chihuahuas (OR: 1.70), and West Highland White Terriers (OR: 1.43) had a significantly increased probability of the presence of BRAF mutation indicating UC. The youngest BRAF-positive dogs of these predisposed breeds (n = 4) were 5 years old. In conclusion, screening tests in predisposed breeds may be recommended from the age of 5 years. Full article

Faecal microbiota transplantation (FMT) is an emerging therapy for gastrointestinal and neurological disorders, acting via the microbiota–gut–brain axis. Altering gut microbial composition may influence cognitive function, but this has not been tested in cognitively healthy adults. This randomised, double-blinded, placebo-controlled pilot trial investigates whether FMT is feasible and improves cognition in adults with irritable bowel syndrome (IBS). Participants receive a single dose of FMT or placebo via rectal retention enema. Cognitive performance is the primary outcome, assessed using the Cambridge Neuropsychological Test Automated Battery (CANTAB). Secondary outcomes include IBS symptom severity and mood. Tertiary outcomes include microbiome composition and plasma biomarkers related to inflammation, short-chain fatty acids, and tryptophan metabolism. Outcomes are assessed at baseline and at one, three, six, and twelve months following treatment. We hypothesise that FMT will lead to greater improvements in cognitive performance than placebo, with benefits extending beyond practice effects, emerging at one month and persisting in the long term. The findings will contribute to evaluating the safety and efficacy of FMT and enhance our understanding of gut–brain interactions. Full article

Background/Objectives: Saliva as a diagnostic medium for COVID-19 requires fewer resources to collect and is more readily adopted across a range of testers. Our study compared an Emergency Use Authorized direct saliva-to-RT-qPCR test against an FDA-authorized nasal swab RT-qPCR assay for participants who reported symptoms of respiratory infection. Methods: We analyzed 737 symptomatic participants who self-selected to test at either a community testing facility or a walk-in clinic due to respiratory symptoms and provided matched saliva and nasal swab samples. Samples were collected between March and September of 2023, both before and after the declared end of the public health emergency. Results: A total of 120 participants tested positive in at least one of the tests. For participants testing in the first 5 days of reported symptoms, the saliva test had a 94.0 positive percent agreement (PPA; 95% C.I. 88.9–99.1%) with the nasal test and a 99.0 negative percent agreement (NPA; 95% C.I. 98.1–99.9%). The viral load decreased beyond day 1 of reported symptoms for saliva testing. Viral load increased up to day 4 for nasal swabs and then decreased. The same number of discordant positive samples (five each) occurred for both tests within 5 days of symptoms onset. Conclusions: In the endemic phase of COVID-19 and for development of new tests, testing methods that are less invasive are more likely to be adopted. The results of saliva-based versus nasal swab PCR measurements relative to days of symptom onset are needed to optimize future testing strategies. Full article

Various SARS-CoV-2 remdesivir resistance-associated substitutions (RAS) have been reported, but a comprehensive comparison of their resistance levels is lacking. We identified novel RAS and performed head-to-head comparisons with known RAS in Vero E6 cells. A remdesivir escape polyclonal virus exhibited a 3.6-fold increase in remdesivir EC₅₀ and mutations throughout the genome, including substitutions in nsp12 (E796D) and nsp14 (A255S). However, in reverse-genetics infectious assays, viruses harboring both these substitutions exhibited only a slight decrease in remdesivir susceptibility (1.3-fold increase in EC₅₀). The nsp12-E796D substitution did not impair viral fitness (Vero E6 cells or Syrian hamsters) and was reported in a remdesivir-treated COVID-19 patient. In replication assays, a subgenomic replicon containing nsp12-E796D+nsp14-A255S led to a 16.1-fold increase in replication under remdesivir treatment. A comparison with known RAS showed that S759A, located in the active site of nsp12, conferred the highest remdesivir resistance (106.1-fold increase in replication). Nsp12-RAS V166A/L, V792I, E796D or C799F, all adjacent to the active site, caused intermediate resistance (2.0- to 11.5-fold), whereas N198S, D484Y, or E802D, located farther from the active site, showed no resistance (≤2.0-fold). In conclusion, our classification system, correlating replication under remdesivir treatment with RAS location in nsp12, shows that most nsp12-RAS cause moderate resistance. Full article

Deep learning models rely heavily on extensive training data, but obtaining sufficient real-world data remains a major challenge in clinical fields. To address this, we explore methods for generating realistic synthetic multivariate fall data to supplement limited real-world samples collected from three fall-related datasets: SmartFallMM, UniMib, and K-Fall. We apply three conventional time-series augmentation techniques, a Diffusion-based generative AI method, and a novel approach that extracts fall segments from public video footage of older adults. A key innovation of our work is the exploration of two distinct approaches: video-based pose estimation to extract fall segments from public footage, and Diffusion models to generate synthetic fall signals. Both methods independently enable the creation of highly realistic and diverse synthetic data tailored to specific sensor placements. To our knowledge, these approaches and especially their application in fall detection represent rarely explored directions in this research area. To assess the quality of the synthetic data, we use quantitative metrics, including the Fréchet Inception Distance (FID), Discriminative Score, Predictive Score, Jensen–Shannon Divergence (JSD), and Kolmogorov–Smirnov (KS) test, and visually inspect temporal patterns for structural realism. We observe that Diffusion-based synthesis produces the most realistic and distributionally aligned fall data. To further evaluate the impact of synthetic data, we train a long short-term memory (LSTM) model offline and test it in real time using the SmartFall App. Incorporating Diffusion-based synthetic data improves the offline F1-score by 7–10% and boosts real-time fall detection performance by 24%, confirming its value in enhancing model robustness and applicability in real-world settings. Full article

Amdoparvoviruses, encompassing the well-characterized Aleutian mink disease viruses (AMDV) as well as less investigated viruses infecting both captive and wild animals, are important carnivoran viruses that are significant pathogens in the mink farming industry. We investigated the molecular epidemiology of amdoparvoviruses among Danish wildlife. Spleen samples from 118 animals of seven carnivoran species were screened with a pan-amdoparvovirus PCR, and the identified viruses were molecularly characterized. In one of five European badgers (Meles meles), we identified an AMDV-3 strain whose ancestors were likely of farmed mink origin. This virus was last reported on a mink farm in 2002, demonstrating how farm-derived viruses have established themselves among wildlife. We also discovered and fully characterized a novel virus found in five of 81 (6.2%) foxes (Vulpes vulpes) and one of five badgers (20.0%), which we named fox and badger amdoparvovirus 1 (FBAV-1). FBAV-1 fulfills the criteria for classification as a novel species and phylogenetically is positioned as an intermediate between the North American and Eurasian amdoparvoviral clades. This study provides baseline data and expands our understanding of amdoparvoviral ecology. Further studies including more animals across diverse geographic areas are warranted to clarify amdoparvovirus epidemiology, spread, cross-species transmission, epidemic potential, and evolutionary paths. Full article

This paper investigates the error performance of cooperative decode-and-forward (DF) multiple-input multiple-output (MIMO) systems employing one-bit analog-to-digital converters (ADCs) over Rayleigh fading channels. In cooperative DF MIMO systems, detection errors at the relay may propagate to the destination, thereby degrading overall detection performance. Although joint maximum likelihood detection can efficiently mitigate error propagation by leveraging probabilistic information from a source-to-relay link, its computational complexity is impractical. To address this issue, an approximate maximum likelihood (AML) detection scheme is introduced, which significantly reduces complexity while maintaining reliable performance. However, its analysis under one-bit ADCs is challenging because of its nonlinearity. The main contributions of this paper are summarized as follows: (1) a tractable upper bound on the pairwise error probability (PEP) of the AML detector is derived using Jensen’s inequality and the Chernoff bound, (2) the asymptotic behavior of the PEP is analyzed to reveal the achievable diversity gain, (3) the analysis shows that full diversity is attained only when symbol pairs in the PEP satisfy a sign-inverted condition and the relay correctly decodes the source symbol, and (4) the simulation results verify the accuracy of the theoretical analysis and demonstrate the effectiveness of the proposed analysis. Full article

Objectives: Non-cystic fibrosis bronchiectasis (BE) is a chronic airway disease with increasing prevalence, reduced quality of life, and increased mortality. Inhaled corticosteroids (ICS) are used in BE despite limited evidence of effect on lung function parameters. ICS may increase the risk of Staphylococcus aureus (S. aureus) infections in patients with BE, but this is unexplored. We examined the association between ICS use prior to BE diagnosis at different doses and the risk of S. aureus isolation in patients with BE. Methods: We conducted a national register-based cohort study including Danish patients with a BE diagnosis code between 2001 and 2018 with a 1-year follow-up time from the date of diagnosis. ICS exposure was categorized based on accumulated prescriptions redeemed 365 days before BE diagnosis and divided into none, low, moderate, or high use based on clinically relevant doses. A cause-specific Cox proportional hazards regression model was used to estimate the risk of S. aureus isolation. A sensitivity analysis, an inverse probability of treatment weighted model (IPTW), was performed. Results: A total of 5093 patients were included in this study. S. aureus was isolated in 156 patients (3.1%). High-dose ICS was associated with an increased risk of S. aureus isolation, HR 3.81 (95% CI 2.51; 5.79). No association for low or moderate use was found, low-dose HR 1.22 (95% CI 0.77; 1.93), and moderate-dose HR 1.24 (95% CI 0.72; 2.16). IPTW analysis yielded similar results. Conclusions: High-dose ICS use in patients with BE was associated with an increased risk of S. aureus isolation. ICS should be used cautiously in patients with BE. Full article

Background: Kidney transplant recipients (KTRs) exhibit a significantly diminished immune response to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) vaccines compared with the general population, primarily due to ongoing immunosuppressive therapy. This study evaluated the immunogenicity of a third SARS-CoV-2 mRNA vaccine dose in KTRs and assessed the association between antibody response and protection against SARS-CoV-2 breakthrough infection. Additionally, the clinical and immunological correlates of post-vaccination SARS-CoV-2 infection were examined. Methods: A prospective cohort of 135 KTRs received a third vaccine dose approximately six months following the second dose. Plasma samples were collected at baseline (pre-vaccination), six months after the second dose, and six weeks following the third dose. Humoral responses were assessed using SARS-CoV-2-specific Immunoglobulin G (IgG) titers and virus neutralization assays against wild-type (WT) and viral strains, including multiple Omicron sub-lineages. Results: After the third vaccine dose, 74% of the KTRs had detectable SARS-CoV-2-specific IgG antibodies, compared with 48% following the second dose. The mean IgG titers increased approximately ten-fold post-booster. Despite this increase, neutralizing activity against the Omicron variants remained significantly lower than that against the WT strain. KTRs who subsequently experienced a SARS-CoV-2 breakthrough infection demonstrated reduced neutralizing antibody activity across all variants tested. Additionally, individuals receiving triple immunosuppressive therapy had a significantly higher risk of SARS-CoV-2 breakthrough infection compared with those on dual or monotherapy. A multivariate machine learning analysis identified age and neutralizing activity against WT, Delta, and Omicron BA.2 as the most robust correlates of SARS-CoV-2 breakthrough infection. Conclusions: A third SARS-CoV-2 mRNA vaccine dose significantly improves SARS-CoV-2-specific IgG levels in KTRs; however, the neutralizing response against Omicron variants remains suboptimal. Diminished neutralizing capacity and intensified immunosuppression are key determinants of SARS-CoV-2 breakthrough infection in this immunocompromised population. Full article

Background: Accurate and rapid diagnosis of drug-resistant tuberculosis is essential for initiating appropriate treatment and preventing the transmission of these strains. This study compares phenotypic and genotypic methods of drug susceptibility testing for Mycobacterium tuberculosis (M. tuberculosis). Methods: Resistance to first-line drugs, as well as resistance to second-line drugs (fluoroquinolones and aminoglycosides), was assessed using the Löwenstein–Jensen medium phenotypic method and the GenoType MTBDRplus genotypic method and analyzed. Results: The phenotypic resistance rate was 84.85% for INH (n = 56), 46.97% for RIF (n = 31), 48.48% for STR (n = 32), and 30.30% for EMB (n = 20). Of the MDR-TB isolates (n = 29), 41.37% were resistant to fluoroquinolones (n = 12) and 31.03% were resistant to both fluoroquinolones and injectable aminoglycosides, being classified as XDR-TB (n = 9). In addition, 22.73% of the MDR-TB isolates were resistant to all four first-line drugs (n = 15). The overall concordance between the line probe assay method and phenotypic testing was 94.74% for RIF and 95.16% for INH. Discordances were identified in three cases for RIF and two cases for INH, where isolates were reported as susceptible by GenoType MTBDRplus, but phenotypically resistant. Conclusions: Genotypic testing using GenoType MTBDRplus provides rapid and accurate results, but some cases of phenotypic resistance are not detected by this method. The results highlight the importance of using combined phenotypic and genotypic methods for accurate diagnosis of MDR-TB, as well as the need to integrate genomic sequencing to improve diagnostic accuracy. Full article

Increasing temperatures associated with climate change will lead to (periodic) temperature-induced reductions in food intake in human and other mammal populations. Human adults, however, are both tolerant and resilient to periodic nutritional deficits, and the associated health effects should be limited. Intermittent nutritional deficits may also cause growth restriction in developing foetuses and young children, which potentially affects their food intake in later life. Therefore, temperature-induced hypophagia can be hypothesised to manifest as later compensatory responses with multiple concomitant (or extended) lags of varying temporal dimensions. We examined the relationship between calorie intake and ambient outdoor temperatures for a time series covering past decades (FAO data for 1961–2013) in 80 countries to determine if humans alter their food intake in response to elevated temperatures. We included eleven different temporal “windows of exposure” of varying lag. These windows considered current and recent exposure, just as lagged effects allowed for a consideration of past effects on mothers, their children, and childhood exposure. It was hypothesised that one of these could provide a basis for predicting future changes in human calorie intake in response to climate change. Our analyses showed no apparent association with temperatures in ten of the eleven hypotheses/models. The remaining hypothesis suggests that current calorie intake is linked to decadal mean temperatures with a lag of approximately three decades, pointing to an impact on mothers and their (developing) children. The impact of an increase in mean temperature varies with temperature amplitudes, and negative impacts are only found in countries with low temperature amplitudes (warmer countries), albeit the impact on calorie intake caused by a 2–3 °C change in temperatures or temperature amplitudes is generally modest. However, in considering calorie intake, we only address quantities of food (with unspecified quality), which insufficiently reflect the full range of nutritional challenges associated with increasing temperatures. Understanding climate-driven changes in human food intake requires global interdisciplinary collaboration across public health, environmental science, and policy. Full article

Droughts are predicted to intensify with climate change, posing a serious threat to global crop production. Increasing drought tolerance in plants requires an understanding of the underlying mechanisms. This study measured the physiological, phytohormonal and transcriptomic responses to drought in two apple rootstocks to identify drought ‘biomarkers’ and investigated whether the application of acibenzolar-S-methyl (ASM) to the roots could enhance drought tolerance. Two potted-plant trials were conducted on dwarfing (M9) and semi-dwarfing (CG202) apple rootstocks. In both trials, the response patterns in the roots and leaves were compared between irrigated and non-irrigated plants over a 14-day period. In trial 2, ASM was applied 14 days before and immediately before withdrawing irrigation. Drought induced significant decreases in transpiration, photosynthesis and stomatal conductance in both trials. This was accompanied by the accumulation of abscisic acid (ABA) metabolites and the upregulation of ABA pathway transcripts (CYP707A1/A2 and NCED3), a decrease in 12-oxophytodienoic acid (cis-OPDA) and the downregulation of ABA receptor genes (PYL4). The responses to drought were greater in the roots than the leaves, broadly similar across both rootstocks, but differed in strength and timing between the rootstocks. The application of ASM to the roots did not significantly affect the responsiveness to drought in either rootstock. The identified phytohormonal and transcriptomic biomarkers require further validation across a broader range of genotypes. Full article

Bregman divergences form a class of distance-like comparison functions which plays fundamental roles in optimization, statistics, and information theory. One important property of Bregman divergences is that they generate agreement between two useful formulations of information content (in the sense of variability or non-uniformity) in weighted collections of vectors. The first of these is the Jensen gap information, which measures the difference between the mean value of a strictly convex function evaluated on a weighted set of vectors and the value of that function evaluated at the centroid of that collection. The second of these is the divergence information, which measures the mean divergence of the vectors in the collection from their centroid. In this brief note, we prove that the agreement between Jensen gap and divergence informations in fact characterizes the class of Bregman divergences; they are the only divergences that generate this agreement for arbitrary weighted sets of data vectors. Full article