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A simple interpolation-based data augmentation method for implicit sentiment identification

Correction: A cytidine deaminase-like protein modulates pyrimidine nucleotide homeostasis in Trypanosoma brucei

Global pneumococcal sequence cluster lineage for invasive pneumococcal isolates in Denmark from summer 2019 to 2023

Low sintering temperature enhancing colossal dielectric permittivity and humidity sensitivity in Ta5+ substituted TiO2 ceramics via high energy ball milling

Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis

Prediction of dust migration and distribution characteristics in open pits at different vehicle speeds

Microstructural damage analysis during drilling in composite laminate with and without smart magneto-elastomer backup

Relationship between telomere length and postoperative delirium: a single center prospective observational pilot study

DSF-YOLO for robust multiscale traffic sign detection under adverse weather conditions

Downward movement of nitrate stimulates losses of soil organic carbon in deeper soil layers

A comprehensive stalagmite investigation distinguishing anthropogenic and natural signals in Madagascar between 1680 and 1860

Abstract Disentangling anthropogenic from natural induced changes is difficult, but crucial to accurately assess the specific environmental impacts of humans’ actions versus climate in the paleoclimate records. Here we combine a new set of proxies, including stable isotopes, element concentrations (mainly Mg, Sr, and U), and detailed mineralogy to better distinguish the impacts of these two factors in the stalagmite records. We studied the period between 1680 and 1860 CE because of the known historical events in Madagascar history (e.g., western colonization and the growth of Malagasy kingdom). This is an ideal period to study given these known events. Our data suggest that redox conditions during alternating wet and dry conditions is revealed by U/Ca covarying with δ18O, but extreme climatic conditions may reverse that relationship. We also found an Mg/Ca increase combined with a decrease in δ13C starting ca. 1820 CE that suggest anthropogenic imprints associated with local burning in Madagascar. This new multiproxy combination, paired with a thorough understanding of Madagascar history over this time allowed us to distinguish anthropogenic versus natural–induced signals in Madagascar stalagmite. This unique and novel pairing of proxies can be used to understand and predict human and natural induced changes in similar settings.

Mid-IR standoff measurement of ageing-related spectroscopic changes in bitumen in the 6 µm (1700 cm−1) region. Part 2: Instrument development and results

Abstract The development and experimental performance of instrumentation to measure ageing-related spectroscopic changes in bitumen is described. Oxidation of bitumen at the surface increases the number of carbonyl (C=O) bonds, and this can be measured in the 6 μm region (1700 cm−1) of the mid-infrared. Standoff measurements of surface reflectivity were performed using 4 discrete wavelengths, 3 for the carbonyl absorption and the fourth as a spectral reference. The standoff height of 20 cm caused problems resulting from the presence of numerous strong absorption lines of atmospheric water in the optical path, which was solved by use of wavelengths centred within available “water windows” and a pathlength-matched reference channel. The instrument was tested using bitumen samples aged artificially using UV exposure. Results illustrating the instrument’s response to bitumen age, along with tolerance to changes in height and tilt, are shown. Measurements made during preliminary field trials on outdoor asphalt are also demonstrated. Part 1 of this paper describes the scientific challenges involved in designing this instrument.

Machine learning analysis of CO2 and methane adsorption in tight reservoir rocks

Abstract Greenhouse gases, particularly CO 2 and CH 4 , are key contributors to climate change and global warming. Consequently, effective management and reduction of these emissions, especially in subsurface storage applications, are crucial. Adsorption presents a promising strategy for mitigating CO 2 and CH 4 emissions in the energy sector, particularly in the storage and utilization of fossil fuel resources, thereby minimizing the environmental impact of their extraction and consumption. In this study, the adsorption behavior of CO 2 and CH 4 in tight reservoirs is examined using experimental data and advanced machine learning (ML) techniques. The dataset incorporates key variables such as temperature, pressure, rock type, total organic carbon (TOC), moisture content, and the CO 2 fraction in the injected gas. Various ML models were employed to predict gas adsorption capacity, with CatBoost and Extra Trees demonstrating high predictive performance. The CatBoost model achieved superior results, with R² values of 0.9989 for CO₂ and 0.9965 for CH₄, along with low RMSE and MAE values, indicating strong stability and accuracy across all metrics. Sensitivity analysis identified pressure as the most influential factor, followed by TOC and CO 2 percentage, while temperature had a restrictive effect on adsorption. Secondary variables, such as rock type and moisture content, also contributed, though to a lesser extent. Graphical analyses further validated the high accuracy of the ML models, particularly CatBoost and Extra Trees. The findings underscore the effectiveness of ML approaches and optimized hyperparameter tuning in enhancing the prediction of gas adsorption capacity, thereby improving the design of gas injection and storage processes. This research provides valuable insights for optimizing gas composition and operational parameters in storage applications, serving as a foundation for future studies in gas sequestration and reservoir engineering.

Efficacy of measuring lysophosphatidylcholine levels in human cerebrospinal fluid to differentiate myelopathy from cauda equina syndrome

Meshless numerical simulation on Frost cracking of rock masses containing random fissures under water-ice phase change

Competitive exclusion approach using an E. coli live vaccine to protect broilers from colonization with ESBL-/ pAmpC- E. coli

Abstract Antimicrobial-resistant bacteria originating from broilers pose an ongoing challenge as they can spread in the environment and food chain. One approach to lower colonization is to administer live bacteria to broilers. A live Escherichia coli (E. coli) vaccine, consisting of a single E. coli strain used as a competitive exclusion (CE) approach, was evaluated to decrease the colonization with ESBL-/pAmpC- producing E. coli. 168 ESBL-/pAmpC- negative Ranger Gold broilers were divided into six groups (3 x n = 46 experimental groups; 3 x n = 10 control groups for quality assurance). The E. coli vaccine was administered on day one through coarse spray or by drinking water on day five. Experimental groups were orally co-colonized with 102 cfu of one ESBL- (ST410, bla CTX−M−15) and one pAmpC- producing E. coli (ST10, bla CMY−2/mcr-1) on day three. Colonization status was monitored throughout the trial and quantified at the end of the study (day 49). A transient reduction in ESBL-producing E. coli colonization (p < 0.001) was observed following coarse spray administration. However, this decrease was not sustained over time. It can be concluded that a single E. coli strain originating from a live vaccine cannot decrease colonization of broilers with ESBL-/pAmpC- E. coli throughout a fattening period.

Optimization of connection patterns between mobile phones and base stations using quantum annealing

Effects of calcined dolomite on the fatigue performance of asphalt concrete affected by water with variable acidity

Cognitive impairment 2 years after mild to severe SARS-CoV-2 infection in a population-based study with matched-comparison groups

Abstract COVID-19 may have long lasting cognitive consequences. Studies with a follow-up longer than 1 year after infection are lacking. This study presents the prevalence of cognitive impairment 2 years after SARS-CoV-2 infection in survivors of the first year of the pandemic and comparison groups matched 1:1 for sex, age, and level of care. Users of the Local Health Unit of Matosinhos (comprising almost all citizens of the municipality) were retrospectively selected according to hospitalization and SARS-CoV-2 infection between March 2020 and February 2021: group #1, hospitalized for COVID-19 (n = 101); group #2, hospitalized, uninfected (n = 87); group #3, non-hospitalized, infected (n = 252); group #4, non-hospitalized, uninfected (n = 258). Between July 2022 and October 2023, all participants completed the Montreal Cognitive Assessment. Those with a score below 1.5 SD of age- and education-specific norms (n = 279) were invited for a comprehensive neuropsychological assessment to identify cognitive impairment. The prevalence of cognitive impairment was higher in group #1 than #2 (19.1% vs. 6.8%; adjusted OR 5.41, 95% CI 1.54, 19.03) and in group #3 than #4 (10.7% vs. 3.2%; adjusted OR 3.27, 95% CI 1.23, 8.67). These results suggest that specific care to timely diagnose and treat cognitive impairment is needed for COVID-19 survivors of the first year of the pandemic.

Enhanced LED light driven photocatalytic degradation of Cefdinir using bismuth titanate nanoparticles

Abstract Photodegradation of antibiotics using visible light represents a promising approach for efficiently removing antibiotic contaminants from water sources. This study investigated bismuth titanate (Bi4Ti3O12) nanoparticles for the photodegradation of Cefdinir (CEF), a third-generation cephalosporin, under visible LED irradiation. Bismuth titanate nanoparticles were synthesized and characterized using transmission electron microscopy (TEM), X-ray diffraction (XRD), and diffuse reflectance spectroscopy (DRS). Factors affecting the degradation protocol were optimized using a central composite design model, and the degradation efficiency was assessed using a validated RP-HPLC method. Results of the experimental design demonstrated that bismuth titanate nanoparticles exhibited high photocatalytic performance (⁓ 98% photodegradation), which was found in an optimum condition of 0.05 g/L of BIT-NP in pH 5 for 50 µg/mL of CEF in 1 h at room temperature. The degradation efficiency depended on the concentration of the nanoparticles, the initial concentration of CEF, and pH. The antimicrobial effect of CEF was assessed before and after the degradation process, and the loss of antibiotic activity was observed after treatment. The findings provide valuable insights into developing innovative photocatalytic materials for the economic remediation of antibiotic-contaminated water sources using eco-friendly LED sources for degradation under visible light for the first time. This would offer a promising solution to mitigate the environmental impact of antibiotic residues.