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The theory governing the strong nuclear force—quantum chromodynamics—predicts that at sufficiently high energy densities, hadronic nuclear matter undergoes a deconfinement transition to a new phase of quarks and gluons 1 . Although this has been observed in ultrarelativistic heavy-ion collisions 2 , 3 , it is currently an open question whether quark matter exists inside neutron stars 4 . By combining astrophysical observations and theoretical ab initio calculations in a model-independent way, we find that the inferred properties of matter in the cores of neutron stars with mass corresponding to 1.4 solar masses ( M ⊙ ) are compatible with nuclear model calculations. However, the matter in the interior of maximally massive stable neutron stars exhibits characteristics of the deconfined phase, which we interpret as evidence for the presence of quark-matter cores. For the heaviest reliably observed neutron stars 5 , 6 with mass M  ≈ 2 M ⊙ , the presence of quark matter is found to be linked to the behaviour of the speed of sound c s in strongly interacting matter. If the conformal bound c s 2 ≤ 1 / 3 (ref. 7 ) is not strongly violated, massive neutron stars are predicted to have sizable quark-matter cores. This finding has important implications for the phenomenology of neutron stars and affects the dynamics of neutron star mergers with at least one sufficiently massive participant. The cores of neutron stars could be made of hadronic matter or quark matter. By combining first-principles calculations with observational data, evidence for the presence of quark matter in neutron star cores is found.

The book provides a review of concepts and methodologies developed and adopted for quantitative imaging-guided radiation dosimetry calculations in targeted radionuclide. It also provides an overview of model design of anthropomorphic computational models and software packages developed for Monte Carlo-based dosimetry calculations.

This textbook covers a basis of mathematical algorithm in artificial intelligence and clinical adaptation and contribution of AI in radiotherapy. More experienced practitioners and researchers and members of medical physics communities, such as AAPM, ASTRO, and ESTRO, would find this book extremely useful.

The efficiency of the synthesis of renewable fuels and feedstocks from electrical sources is limited, at present, by the sluggish water oxidation reaction. Single-atom catalysts (SACs) with a controllable coordination environment and exceptional atom utilization efficiency open new paradigms toward designing high-performance water oxidation catalysts. Here, using operando X-ray absorption spectroscopy measurements with calculations of spectra and electrochemical activity, we demonstrate that the origin of water oxidation activity of IrNiFe SACs is the presence of highly oxidized Ir single atom (Ir5.3+) in the NiFe oxyhydroxide under operating conditions. We show that the optimal water oxidation catalyst could be achieved by systematically increasing the oxidation state and modulating the coordination environment of the Ir active sites anchored atop the NiFe oxyhydroxide layers. Based on the proposed mechanism, we have successfully anchored Ir single-atom sites on NiFe oxyhydroxides (Ir0.1/Ni₉Fe SAC) via a unique in situ cryogenic–photochemical reduction method that delivers an overpotential of 183 mV at 10 mA · cm−2 and retains its performance following 100 h of operation in 1 M KOH electrolyte, outperforming the reported catalysts and the commercial IrO₂ catalysts. These findings open the avenue toward an atomic-level understanding of the oxygen evolution of catalytic centers under in operando conditions.

This paper explores the application of the Word2Vec model in document compliance detection, and evaluates the performance of Word2Vec in calculating compliance similarity between documents by comparing it with the traditional text analysis method TFIDF, the topic modeling method LDA, and the advanced deep learning model BERT. During the research, we collected and preprocessed a large amount of archival data from multiple sources, generated document vectors using Word2Vec, TFIDF, LDA, and BERT, and comprehensively evaluated the models through indicators such as cosine similarity, precision, recall, F1 score, and AUC. The experimental results show that the Word2Vec model performs well in capturing the semantic similarity of documents, especially when distinguishing between compliant and non-compliant document pairs. Specifically, on the legal document dataset, Word2Vec achieved an F1 score of 0.84, which is 12% higher than TFIDF. In addition, the AUC of Word2Vec on the internal audit report dataset reached 0.92, which is 5 percentage points higher than LDA. However, compared with BERT, Word2Vec is slightly inferior in processing complex semantics and technical terms; for example, in the financial report dataset, BERT's F1 score is 0.78, while Word2Vec is 0.75, a gap of 3%. Word2Vec has obvious advantages in efficiency and simplicity, and is suitable for application scenarios that require fast deployment and low computing resources. At the same time, its performance in specific fields also proves its effectiveness as a compliance detection tool. 翻译搜索复制

A new fluorescent sensor for detecting Fe[sup.3+] was developed based on chemical modification of the quinoline group. Titration experiments showed that the sensor exhibits high selectivity and sensitivity toward Fe[sup.3+], even in complex systems. The recognition mechanism was verified through theoretical calculations, demonstrating that the sensor can perform qualitative and quantitative analysis on Fe[sup.3+]. The cell imaging and zebrafish imaging experiments further prove the potential application of the sensor in the field of bioluminescence imaging.

Abstract Through the calculation of the matrix element of the singlet axial-current operator between the vacuum and a pair of gluons in dimensional regularization with an anti-commuting γ 5 defined in a Kreimer-scheme variant, we find that additional renormalization counter-terms proportional to the Chern-Simons current operator are needed starting from O $$ \\mathcal{O} $$ ( α s 2 $$ {\\alpha}_s^2 $$ ) in QCD. This is in contrast to the well-known purely multiplicative renormalization of the singlet axial-current operator defined with a non-anticommuting γ 5. Consequently, without introducing compensation terms in the form of additional renormalization, the Adler-Bell-Jackiw anomaly equation does not hold automatically in the bare form in this kind of schemes. We determine the corresponding (gauge-dependent) coefficient to O $$ \\mathcal{O} $$ ( α s 3 $$ {\\alpha}_s^3 $$ ) in QCD, using a variant of the original Kreimer prescription which is implemented in our computation in terms of the standard cyclic trace together with a constructively-defined γ 5. Owing to the factorized form of these divergences, intimately related to the axial anomaly, we further performed a check, using concrete examples, that with γ 5 treated in this way, the axial-current operator needs no more additional renormalization in dimensional regularization but only for non-anomalous amplitudes in a perturbatively renormalizable theory. To be complete, we provide a few additional ingredients needed for a proposed extension of the algorithmic procedure formulated in the above analysis to potential applications to a renormalizable anomaly-free chiral gauge theory, i.e. the electroweak theory.

Purpose. Development of a technology for optimal formula determination of the IOL required optical power, based on the artificial intelligence (AI) and the individual clinical characteristics of the patient’s eye. Material and methods. A retrospective analysis of 1337 uncomplicated phacoemulsification with implantation of a monofocal IOL RAO100C (Rayner) was performed. For artificial intelligence training and models testing, a database was created containing 1080 clinical cases (1080 eyes); the process of filling the database was fully automated. The accuracy criterion for IOL prediction was the range of spheroequivalent (SE) values in the postoperative period <|0.5|. Results. A retrospective analysis showed that in uncomplicated cataract surgery, the accuracy of the target refraction achievement is high and does not go beyond ±0.5 D. 16 artificial intelligence models were developed and tested, of which 4 were selected based on accuracy metrics – 1 model for each formula (Barrett, Haigis, Holladay 2, HofferQ). The best models turned out to be DecisionTreeClassifier. Validation of AI models was carried out by comparing the choice of IOL diopter between the AI and an expert. All models showed an advantage over the expert. A software interface for this service was developed and implemented. Conclusion. A selective database has been created for training and testing artificial intelligence models that determine IOL optical power. A system has been developed to help a doctor make a decision to determine the required IOL optical power based on artificial intelligence, depending on the individual clinical characteristics of the patient’s eye. The high efficiency of the developed technology has been proven on a test model (90–95%). The program interface was developed and implemented. Key words: IOL calculation, artificial intelligence

The subject of this paper is the technology (the 'how') of constructing machine-learning interatomic potentials, rather than science (the 'what' and 'why') of atomistic simulations using machine-learning potentials. Namely, we illustrate how to construct moment tensor potentials using active learning as implemented in the MLIP package, focusing on the efficient ways to automatically sample configurations for the training set, how expanding the training set changes the error of predictions, how to set up ab initio calculations in a cost-effective manner, etc. The MLIP package (short for Machine-Learning Interatomic Potentials) is available at https://mlip.skoltech.ru/download/.

The latest discovery of ferromagnetism in atomically thin films of semiconductors Cr2Ge2Te6 and CrI3 has unleashed numerous opportunities for fundamental physics of magnetism in two-dimensional (2D) limit and also for technological applications based on 2D magnetic materials. To exploit these 2D magnetic materials, however, the mechanisms that control their physical properties should be thoroughly understood. In this paper, we present a comprehensive theoretical study of the magnetic, electronic, optical and magneto-optical (MO) properties of multilayers (monolayer (ML), bilayer (BL) and trilayer) as well as bulk CrI3, based on the density functional theory with the generalized gradient approximation plus on-site Coulomb repulsion scheme. Interestingly, all the structures except the BL, are found to be single-spin ferromagnetic semiconductors. They all have a large out-of-plane magnetic anisotropy energy (MAE) of ∼0.5 meV/Cr, in contrast to the significantly thickness-dependent MAE in multilayers of Cr2Ge2Te6. These large MAEs suppress transverse spin fluctuations and thus stabilize long-range magnetic orders at finite temperatures down to the ML limit. They also exhibit strong MO effects with their Kerr and Faraday rotation angles being comparable to that of best-known bulk MO materials. The shape and position of the main features in the optical and MO spectra are found to be nearly thickness-independent although the magnitude of Kerr rotation angles increases monotonically with the film thickness. Magnetic transition temperatures estimated based on calculated exchange coupling parameters, calculated optical conductivity spectra, MO Kerr and Faraday rotation angles agree quite well with available experimental data. The calculated MAE as well as optical and MO properties are analyzed in terms of the calculated orbital-decomposed densities of states, band state symmetries and dipole selection rules. Our findings of large out-of-plane MAEs and strong MO effects in these single-spin ferromagnetic semiconducting CrI3 ultrathin films suggest that they will find valuable applications in semiconductor MO and spintronic nanodevices.