Mathematical Framework for Breathing Chimera States

About two decades ago it was discovered that systems of nonlocally coupled oscillators can exhibit unusual symmetry-breaking patterns composed of coherent and incoherent regions. Since then such patterns, called chimera states, have been the subject of intensive study but mostly in the stationary case when the coarse-grained system dynamics remains unchanged over time. Nonstationary coherence–incoherence patterns, in particular periodically breathing chimera states, were also reported, however not investigated systematically because of their complexity. In this paper we suggest a semi-analytic solution to the above problem providing a mathematical framework for the analysis of breathing chimera states in a ring of nonlocally coupled phase oscillators. Our approach relies on the consideration of an integro-differential equation describing the long-term coarse-grained dynamics of the oscillator system. For this equation we specify a class of solutions relevant to breathing chimera states. We derive a self-consistency equation for these solutions and carry out their stability analysis. We show that our approach correctly predicts macroscopic features of breathing chimera states. Moreover, we point out its potential application to other models which can be studied using the Ott–Antonsen reduction technique.

BOREAL- A fixed-wing unmanned aerial system for the measurement of wind and turbulence in the atmospheric boundary layer

An instrumentation package for wind and turbulence observations in the atmospheric boundary layer on an unmanned aerial vehicle (UAV) called BOREAL has been developed. BOREAL is a fixed wing UAV built by BOREAL company which weighs up to 25kg (5kg of payload) and has a wingspan of 4.2m. With a light payload and optimal weather conditions, it has a flight endurance of nine hours. The instrumental payload was designed in order to measure every parameter required for the computation of the three wind components, at a rate of 100 s−1 which is fast enough to capture turbulence fluctuations: a GPS-IMU platform measures the three components of the groundspeed a well as the attitude angles; the airplane nose has been replaced by a five-hole probe in order to measure the angles of attack and sideslip, according to the so-called radome technique. This probe was calibrated using computational fluid dynamics (CFD) simulations and wind tunnel tests. The remaining instruments are a Pitot tube for static and dynamic pressure measurement, and temperature/humidity sensors in dedicated housings. The optimal airspeed at which the vibrations are significantly reduced to an acceptable level was defined from qualification flights. With appropriate flight patterns, the reliability of the mean wind estimates, through self-consistency and comparison with observations performed at 60m on an instrumented tower could be assessed. Promising first observations of turbulence up to frequencies around 10Hz and corresponding to a spatial resolution to the order of 3m, are hereby presented.

COSMOS2020: A Panchromatic View of the Universe to z ∼ 10 from Two Complementary Catalogs

The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data have been collected in the COSMOS field. This paper describes the collection, processing, and analysis of these new imaging data to produce a new reference photometric redshift catalog. Source detection and multiwavelength photometry are performed for 1.7 million sources across the 2 deg2 of the COSMOS field, ∼966,000 of which are measured with all available broadband data using both traditional aperture photometric methods and a new profile-fitting photometric extraction tool, The Farmer, which we have developed. A detailed comparison of the two resulting photometric catalogs is presented. Photometric redshifts are computed for all sources in each catalog utilizing two independent photometric redshift codes. Finally, a comparison is made between the performance of the photometric methodologies and of the redshift codes to demonstrate an exceptional degree of self-consistency in the resulting photometric redshifts. The i < 21 sources have subpercent photometric redshift accuracy and even the faintest sources at 25 < i < 27 reach a precision of 5%. Finally, these results are discussed in the context of previous, current, and future surveys in the COSMOS field. Compared to COSMOS2015, it reaches the same photometric redshift precision at almost one magnitude deeper. Both photometric catalogs and their photometric redshift solutions and physical parameters will be made available through the usual astronomical archive systems (ESO Phase 3, IPAC-IRSA, and CDS).

βLact-Pred: A Predictor Developed for Identification of Beta-Lactamases Using Statistical Moments and PseAAC via 5-Step Rule

Beta-lactamase (β-lactamase) produced by different bacteria confers resistance against β-lactam-containing drugs. The gene encoding β-lactamase is plasmid-borne and can easily be transferred from one bacterium to another during conjugation. By such transformations, the recipient also acquires resistance against the drugs of the β-lactam family. β-Lactam antibiotics play a vital significance in clinical treatment of disastrous diseases like soft tissue infections, gonorrhoea, skin infections, urinary tract infections, and bronchitis. Herein, we report a prediction classifier named as βLact-Pred for the identification of β-lactamase proteins. The computational model uses the primary amino acid sequence structure as its input. Various metrics are derived from the primary structure to form a feature vector. Experimentally determined data of positive and negative beta-lactamases are collected and transformed into feature vectors. An operating algorithm based on the artificial neural network is used by integrating the position relative features and sequence statistical moments in PseAAC for training the neural networks. The results for the proposed computational model were validated by employing numerous types of approach, i.e., self-consistency testing, jackknife testing, cross-validation, and independent testing. The overall accuracy of the predictor for self-consistency, jackknife testing, cross-validation, and independent testing presents 99.76%, 96.07%, 94.20%, and 91.65%, respectively, for the proposed model. Stupendous experimental results demonstrated that the proposed predictor “βLact-Pred” has surpassed results from the existing methods.

Self-Consistency Congruence and Smartphone Addiction in Adolescents: The Mediating Role of Subjective Well-Being and the Moderating Role of Gender

Adolescent smartphone addiction has increasingly attracted the attention of scholars because of the widespread use of internet technology in educational environments. In addition, previous studies have found that there is a complex relationship between smartphone addiction and self-consistency congruence, and subjective well-being. This research was conducted to examine whether subjective well-being would mediate the relation between self-consistency congruence and adolescent smartphone addiction, and whether gender would moderate the mediating process. A total of 1,011 Chinese adolescents completed self-report questionnaires measuring self-consistency congruence, subjective well-being, and smartphone addiction. Self-consistency congruence was shown to be a significant predictor of smartphone addiction. Furthermore, subjective well-being partially mediated the association between self-consistency congruence and adolescent smartphone addiction. Gender could moderate the mediating process; as compared with boys, girls’ self-consistency congruence and subjective well-being are more easily mediated. We envision the findings as being helpful in guiding scholars who are developing interventions to minimize smartphone addiction and its disrupting effects in adolescents.

Importance of charge self-consistency in first-principles description of strongly correlated systems

First-principles approaches have been successful in solving many-body Hamiltonians for real materials to an extent when correlations are weak or moderate. As the electronic correlations become stronger often embedding methods based on first-principles approaches are used to better treat the correlations by solving a suitably chosen many-body Hamiltonian with a higher level theory. The success of such embedding theories, often referred to as second-principles, is commonly measured by the quality of self-energy Σ which is either a function of energy or momentum or both. However, Σ should, in principle, also modify the electronic eigenfunctions and thus change the real space charge distribution. While such practices are not prevalent, some works that use embedding techniques do take into account these effects. In such cases, choice of partitioning, of the parameters defining the correlated Hamiltonian, of double-counting corrections, and the adequacy of low-level Hamiltonian hosting the correlated subspace hinder a systematic and unambiguous understanding of such effects. Further, for a large variety of correlated systems, strong correlations are largely confined to the charge sector. Then an adequate nonlocal low-order theory is important, and the high-order local correlations embedding contributes become redundant. Here we study the impact of charge self-consistency within two example cases, TiSe2 and CrBr3, and show how real space charge re-distribution due to correlation effects taken into account within a first-principles Green’s function-based many-body perturbative approach is key in driving qualitative changes to the final electronic structure of these materials.

Quantum Spectral Curve for AdS3/CFT2: a proposal

We conjecture the Quantum Spectral Curve equations for string theory on AdS3× S3× T4 with RR charge and its CFT2 dual. We show that in the large-length regime, under additional mild assumptions, the QSC reproduces the Asymptotic Bethe Ansatz equations for the massive sector of the theory, including the exact dressing phases found in the literature. The structure of the QSC shares many similarities with the previously known AdS5 and AdS4 cases, but contains a critical new feature — the branch cuts are no longer quadratic. Nevertheless, we show that much of the QSC analysis can be suitably generalised producing a self-consistent system of equations. While further tests are necessary, particularly outside the massive sector, the simplicity and self-consistency of our construction suggests the completeness of the QSC.

Relationship Analysis among Apparel Brand Image, Self-Congruity, and Consumers’ Purchase Intention

Brand image has been a crucial clue to making subjective judgment for consumers to determine the brand, which is critical to making a purchase decision. The influence mechanism from apparel brand images on consumers’ purchase intention was explored for theoretical and positive analysis based on the self-congruity theory. This research first constructed a hypothetical model of apparel brand images influencing consumers’ purchase intention with self-congruity and perceived quality as mediators, in which a questionnaire was designed and conducted to test the theoretical model. The research shows that apparel brand image and perceived quality can significantly influence consumers’ purchase intention. The consumer purchase intention is directly related to clothing brand image provided self-consistency and perceived quality play an intermediary with the regulatory effect of self-motivation and brand familiarity. A positive attitude toward apparel brand image will stimulate consumers to build cognitive clues and associations between the consumers and the brand and strengthen cognitive consistency with the apparel brand’s spirit. The research results are beneficial to textile fashion and clothing enterprises to improve brand building and marketing.