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Operando Characterization of Fe in Doped Ni_<i>x</i>(Fe_1–<i>x</i>)O_<i>y</i>H_<i>z</i> Catalysts for Electrochemical Oxygen Evolution

Martini compatible coarse-grained model of polyethylenimine for pulmonary gene delivery

Lipophilicity Modulation of Fluorescent Probes for <i>In Situ</i> Imaging of Cellular Microvesicle Dynamics

Hybrid quantum neural networks show strongly reduced need for free parameters in entity matching

Abstract Modern technology and scientific experiments increasingly generate larger and larger amounts of data. This data is sometimes redundant, incomplete or inaccurate and needs to be cleaned and merged with other data before becoming useful for scientific exploration. Hence, entity matching, i.e. the process of linking data about a given entity gathered from multiple data sets, is a major problem in artificial intelligence with applications in science and industry. Typical methods for entity matching either use specialized algorithms or supervised machine learning. Although the problem has been well studied on classical computers, it is unclear how quantum approaches would tackle these challenges. In this paper, we evaluate quantum machine learning algorithms for entity matching on a hand-crafted data set and compare them to similar classical algorithms. We do this by implementing a neural network with a classical embedding layer and extending it with quantum layers. Our experimental results suggest that our hybrid quantum neural network reaches similar performance as classical approaches while requiring an order of magnitude fewer parameters than its classical counterpart. Furthermore, we also show that a model trained on a quantum simulator is portable and thus transferable to a real quantum computer. From a practical perspective and as long as quantum hardware is a scarce resource, experiments, e.g. addressing performance, can profit from producing good initial configurations for quantum neural networks via a simulator, thus only leaving the fine-tuning to quantum computations.

Atomically Dispersed Co–P Moieties via Direct Thermal Exfoliation for Alkaline Hydrogen Electrosynthesis

Applying the layers of protection analysis (LOPA) method to high containment level biological facilities

Abstract The Layers of Protection Analysis (LOPA) method is a semi-quantitative risk assessment tool that is used to determine the ability of safeguards to protect against unplanned hazardous scenarios. One possible outcome of a LOPA is that existing and proposed safeguards are deemed sufficient to reduce the risk associated with the hazardous scenario to a level that can be deemed as acceptable. Alternatively, the LOPA may also show that the safeguards are insufficient and therefore additional Safety Instrumented Function(s) (SIF) would be required to reduce risk to an acceptable level. In the latter case, the LOPA method will inform the end user as to the reliability requirements of the safety function in question. The LOPA method has been used extensively in the process industries (e.g., oil and gas) as a useful tool to manage and understand risk and to demonstrate if the facility is ‘safe’ to operate, but much less so in the biosafety sector. This paper describes the LOPA method and provides some practical examples of how it may be applied in microbiological high Containment Level (CL) facilities.

EPR Characterization of the BlsE Substrate Radical Offers Insight into the Determinants of Reaction Outcome that Distinguish Radical SAM Dioldehydratases from Dehydrogenases

Assessment of different genotyping markers and algorithms for distinguishing Plasmodium falciparum recrudescence from reinfection in Uganda

Abstract Antimalarial therapeutic efficacy studies are vital for monitoring drug efficacy in malaria-endemic regions. The WHO recommends genotyping polymorphic markers including msp-1 , msp-2 , and glurp for distinguishing recrudescences from reinfections. Recently, WHO proposed replacing glurp with microsatellites (Poly-α, PfPK2, TA1). However, suitable combinations with msp-1 and msp-2 , as well as the performance of different algorithms for classifying recrudescence, have not been systematically assessed. This study investigated various microsatellites alongside msp-1 and msp-2 for molecular correction and compared different genotyping algorithms across three sites in Uganda. Microsatellites 313, Poly-α, and 383 exhibited the highest diversity, while PfPK2 and Poly-α revealed elevated multiplicity of infection (MOI) across all sites. The 3/3 match-counting algorithm classified significantly fewer recrudescences than both the ≥ 2/3 and Bayesian algorithms at probability cutoffs of ≥ 0.7 and ≥ 0.8 ( P  &lt; 0.05). The msp-1 / msp-2 /2490 combination identified more recrudescences using the ≥ 2/3 and 3/3 algorithms in the artemether-lumefantrine (AL) treatment arm, while msp-1 / msp-2 / glurp combination classified more cases of recrudescence using the ≥ 2/3 in the dihydroartemisinin-piperaquine (DP) arm. Microsatellites PfPK2 and Poly-α, potentially sensitive to detecting minority clones, are promising replacements for glurp . Discrepancies in recrudescence classification between match-counting and Bayesian algorithms highlight the need for standardized PCR correction practices.

Electron Microscopy Reveals Inhomogeneous Adsorption of Iodine and Concurrent Defect Formation in a Metal–Organic Framework

The effect of surgical treatment of tubal pregnancy on concurrent intrauterine pregnancy after in vitro fertilization

Superconductor–Insulator Transition Induced by Precise Subtripled Vapor Chemical Gating

Multi-scale non-uniform hierarchical filtering model based on fractal theory

Gasoline particulate filters (GPF) are widely used due to their superior environmental benefits, but its trapping efficiency is affected by many factors. We established a multi-scale non-uniform hierarchical filtering model (MNHF) based on the fractal theory to accurately analyze the dynamic changes of trapping efficiency during GPF operation. The multi-scale characteristics of the filter wall about trap diameter and pore size are presented. Additionally, filter theory and Brownian kinematics are used to precisely predict particle motion. The study focuses on the dynamic change of trapping efficiency of MNHF in different particle size ranges. The results indicate the following: By comparing the numerical simulation results of the model with experimental data, the maximum relative error range is found to be within 0.7%. The MNHF model accurately predicts the change in trapping performance at different times when particles move in the trap. The trapping efficiency of the upper layer of the single-layer trap is higher than that of the lower layer based on the particles’ moving distance in unit time, and the trapping efficiency of the next layer is reduced by up to 29.34% compared to that of the upper layer. Additionally, it provides a more accurate simulation of the trapping efficiency for particles with sizes ranging from 0.01 μm to 0.5 μm under conditions of low wall flow velocity.

Therapeutic anti-inflammatory immune potentials of some seaweeds extracts on chemically induced liver injury in mice

Abstract Carbon tetrachloride (CCl4) is a well-known hepatotoxin. This work aimed to assess the therapeutic anti-inflammatory immune potentials of the seaweeds Padina pavonia and Jania rubens extracts on carbon tetrachloride (CCL4)-caused liver damage in mice. Our experimentation included two testing regimens: pre-treatment and post-treatment of P. pavonia and J. rubens extracts in CCL4/mice. Pre-treatment and post-treatment of P. pavonia and J. rubens extracts in CCL4/mice increased WBCs count and lymphocytes relative numbers and reduced the neutrophils and monocytes relative numbers. Pre-treatment and post-treatment of CCL4/mice with P. pavonia and J. rubens extracts significantly reduced the release amounts of pro-inflammatory cytokines TNF-α and IL-6 and significantly inhibited the increased CRP level. Furthermore, pre-treatment and post-treatment of CCL4/mice with P. pavonia and J. rubens extracts recovered the activities of GSH, and significantly decreased MDA level. CCL4/mice pre-treated and post-treated with P. pavonia and J. rubens extracts decreased alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels. Pre- and post-treatment of CCL4/mice with the P. pavonia and J. rubens extracts ameliorated the liver damages caused by CCl4 and significantly inhibited the necrotic area, indicating hepatic cell death and decreased periportal hepatic degeneration, fibrosis, and inflammation.

Systematic Fluorination Is a Powerful Design Strategy toward Fluid Molecular Ferroelectrics

Cross-ViT based benign and malignant classification of pulmonary nodules

The benign and malignant discrimination of pulmonary nodules plays a very important role in diagnosing the extent of lung cancer lesions. There are many methods using Convolutional neural network (CNN) for benign and malignant classification of pulmonary nodules, but traditional CNN models focus more on the local features of pulmonary nodules and lack the extraction of global features of pulmonary nodules. To solve this problem, a Cross fusion attention ViT (Cross-ViT) network that fuses local features extracted by CNN and global features extracted by Transformer is proposed. The network first extracts different features independently through two branches and then performs feature fusion through the Cross fusion attention module. Cross-ViT can effectively capture and process both local and global information of lung nodules, which improves the accuracy of classifying the benign and malignant nature of pulmonary nodules. Experimental validation was performed on the LUNA16 dataset, and the accuracy, precision, recall and F1 score reached 91.04%, 91.42%, 92.45% and 91.92%, respectively, and the accuracy, precision, recall and F1 score with SENet as CNN branch reached 92.43%, 94.27%, 91.68% and 92.96%, respectively. The results show that the accuracy, precision, recall and F1 score of the proposed method are 0.3%, 0.11%, 4.52% and 3.03% higher than those of the average optimal method, respectively, and the performance of Cross-ViT network for benign and malignant classification is better than most classification methods.

Enhanced methanol electro-oxidation activity of CuO nanoparticles derived from the thermal decomposition of a CuII salophen type coordination compound

Synthesis, Structure, and Redox Reactivity of Ni Complexes Bearing a Redox and Acid–Base Non-innocent Ligand with Ni^II, Ni^III, and Ni^IV Formal Oxidation States

Use of screens, books and adults’ interactions on toddler’s language and motor skills: A cross-cultural study among 19 Latin American countries from different SES

Children’s screen use is ubiquitous, with toddlers in particular demonstrating increases after the pandemic and negative associations with cognitive abilities. Thus, the objective of this cross-cultural study was to broaden and deepen existing results by describing Latin American toddlers’ screen use and its association with parental reports of language skills, developmental milestones, and sociodemographic variables. A sample of 1878 toddlers from 12 to 48 months (M.age = 27.55, SD = 9.68, male = 933, low-SES = 945) from 19 different Latin American countries was evaluated. Parent-report measures of children’s use of screens, SES, language, and developmental milestones were administered virtually or face-to-face. Results indicated that infants’ screen exposure times were longer than recommended, with TV and smartphone being the most frequent screen media among them. Also, most of the screen time was shared with an adult. These results were consistent across parent-reported SES and nationality. In addition, negative and significant associations were generally found between screen time and language skills, which were in turn positively associated with shared reading times. The frequency of shared screen use with adults demonstrated positive correlations with language skills, after controlling for sociodemographic variables. Lastly, entertainment and educational content was associated with higher levels of language skills compared to music. In conclusion, this study demonstrates the importance of promoting responsible and accompanied use of screens with age-appropriate content during the first years of life across different contexts.

Author Correction: Variability of marine heatwaves’ characteristics and assessment of their potential drivers in the Baltic Sea over the last 42 years

Synergistic Enhancement of Ferroptosis via Mitochondrial Accumulation and Photodynamic-Controlled Release of an Organogold(I) Cluster Prodrug