Elucidation of subfamily segregation and intramolecular coevolution of the olfactomedin-like proteins by comprehensive phylogenetic analysis and gene expression pattern assessment

AbstractThe categorization of genes by structural distinctions relevant to biological characteristics is very important for understanding of gene functions and predicting functional implications of uncharacterized genes. It was absolutely necessary to deploy an effective and efficient strategy to deal with the complexity of the large olfactomedin-like (OLF) gene family sharing sequence similarity but playing diversified roles in many important biological processes, as the simple highest-hit homology analysis gave incomprehensive results and led to inappropriate annotation for some uncharacterized OLF members. In light of evolutionary information that may facilitate the classification of the OLF family and proper association of novel OLF genes with characterized homologs, we performed phylogenetic analysis on all 116 OLF proteins currently available, including two novel members cloned by our group. The OLF family segregated into seven subfamilies and members with similar domain compositions or functional properties all fell into relevant subfamilies. Furthermore, our Northern blot analysis and previous studies revealed that the typical human OLF members in each subfamily exhibited tissue-specific expression patterns, which in turn supported the segregation of the OLF subfamilies with functional divergence. Interestingly, the phylogenetic tree topology for the OLF domains alone was almost identical with that of the full-length tree representing the unique phylogenetic feature of full-length OLF proteins and their particular domain compositions. Moreover, each of the major functional domains of OLF proteins kept the same phylogenetic feature in defining similar topology of the tree. It indicates that the OLF domain and the various domains in flanking non-OLF regions have coevolved and are likely to be functionally interdependent. Expanded by a plausible gene duplication and domain couplings scenario, the OLF family comprises seven evolutionarily and functionally distinct subfamilies, in which each member shares similar structural and functional characteristics including the composition of coevolved and interdependent domains. The phylogenetically classified and preliminarily assessed subfamily framework may greatly facilitate the studying on the OLF proteins. Furthermore, it also demonstrated a feasible and reliable strategy to categorize novel genes and predict the functional implications of uncharacterized proteins based on the comprehensive phylogenetic classification of the subfamilies and their relevance to preliminary functional characteristics

New symmetries for the Ablowitz-Ladik hierarchies

In the letter we give new symmetries for the isospectral and non-isospectral Ablowitz-Ladik hierarchies by means of the zero curvature representations of evolution equations related to the Ablowitz-Ladik spectral problem. Lie algebras constructed by symmetries are further obtained. We also discuss the relations between the recursion operator and isospectral and non-isospectral flows. Our method can be generalized to other systems to construct symmetries for non-isospectral equations.Comment: 11 page

Improved PSO algorithm based on chaos theory and its application to design flood hydrograph

AbstractThe deficiencies of basic particle swarm optimization (bPSO) are its ubiquitous prematurity and its inability to seek the global optimal solution when optimizing complex high-dimensional functions. To overcome such deficiencies, the chaos-PSO (COSPSO) algorithm was established by introducing the chaos optimization mechanism and a global particle stagnation-disturbance strategy into bPSO. In the improved algorithm, chaotic movement was adopted for the particles' initial movement trajectories to replace the former stochastic movement, and the chaos factor was used to guide the particles' path. When the global particles were stagnant, the disturbance strategy was used to keep the particles in motion. Five benchmark optimizations were introduced to test COSPSO, and they proved that COSPSO can remarkably improve efficiency in optimizing complex functions. Finally, a case study of COSPSO in calculating design flood hydrographs demonstrated the applicability of the improved algorithm

AgBiS\u3csub\u3e2\u3c/sub\u3e as a low-cost and eco-friendly all-inorganic photovoltaic material: nanoscale morphology– property relationship†

Solar cells made of low-cost solution-processed all-inorganic materials are a promising alternative to conventional solar cells made of high-temperature processed inorganic materials, especially because many high-temperature processed inorganic materials contain toxic element(s) such as lead or cadmium (e.g., CsPbI3 perovskite, PbS, CdTe and CdS(Se)). AgBiS2 nanocrystals, consisting of earth-abundant elements but without lead and cadmium, have already emerged as a promising candidate in highperformance solar cells. However, the nanoscale morphology–optoelectronic property relationship for AgBiS2 nanocrystals is still largely unknown. Herein, we investigate the electronic properties of various AgBiS2 nanocrystals by using first-principles computation. We show that the optoelectronic properties of bulk AgBiS2 are highly dependent on the M–S–M–S– (M: Ag or Bi) orderings. Moreover, because Ag–S– Ag–S– and Bi–S–Bi–S– in AgBiS2 bulk crystals contribute respectively to the valence band maximum and conduction band minimum, these unique chemical orderings actually benefit easy separation of mobile electrons and holes for photovoltaic application. More importantly, we find that AgBiS2 nanocrystals (NCs) can exhibit markedly different optoelectronic properties, depending on their stoichiometry. NCs with minor off-stoichiometry give rise to mid-gap states, whereas NCs with substantial off-stoichiometry give rise to many deep defect states in the band gap, and some NCs even show metallic-like electronic behavior. We also find that the deep-defect states can be removed through ligand passivation with optimal coverage. The new insights into the nanoscale morphology– optoelectronic property relationship offer a rational design strategy to engineer the band alignment of AgBiS2 NC layers while addressing some known challenging issues inherent in all-inorganic photovoltaic materials

Fully integrated InGaAs/InP single-photon detector module with gigahertz sine wave gating

InGaAs/InP single-photon avalanche diodes (SPADs) working in the regime of GHz clock rates are crucial components for the high-speed quantum key distribution (QKD). We have developed for the first time a compact, stable and user-friendly tabletop InGaAs/InP single-photon detector system operating at a 1.25 GHz gate rate that fully integrates functions for controlling and optimizing SPAD performance. We characterize the key parameters of the detector system and test the long-term stability of the system for continuous operation of 75 hours. The detector system can substantially enhance QKD performance and our present work paves the way for practical high-speed QKD applications.Comment: 11 pages, 6 figures. Accepted for publication in Review of Scientific Instrument

Optimal dynamic pricing for smart grid having mixed customers with and without smart meters

This paper investigates an optimal day-ahead dynamic pricing problem in an electricity market with one electricity retailer and multiple customers. The main objective of this paper is to support the retailer to make the best day-ahead dynamic pricing decision, which maximizes its profit under the realistic assumption that mixed types of customers coexist in the electricity market where some customers have installed smart meters with the embedded home energy management system in their home whereas other customers have not installed smart meters. To this end, we propose a hybrid demand modelling framework which firstly uses an optimal energy management algorithm with bill minimization to model the behavior of customers with smart meters and secondly use a data-driven demand modelling method to model the behavior of customers without smart meters. Such a hybrid demand model can not only schedule usages of home appliances to the interests of customers with smart meters but also be used to understand electricity usage behaviors of customers without smart meters. Based on the established hybrid demand model for all customers, a profit maximization algorithm is developed to achieve optimal prices for the retailer under relevant market constraints. Under the condition of no growth of the revenue (i.e. no increase of total bill from all customers), simulation results indicate our optimization algorithm can improve the profit for around 5% on average

Experimental Test of Tracking the King Problem

In quantum theory, the retrodiction problem is not as clear as its classical counterpart because of the uncertainty principle of quantum mechanics. In classical physics, the measurement outcomes of the present state can be used directly for predicting the future events and inferring the past events which is known as retrodiction. However, as a probabilistic theory, quantum-mechanical retrodiction is a nontrivial problem that has been investigated for a long time, of which the Mean King Problem is one of the most extensively studied issues. Here, we present the first experimental test of a variant of the Mean King Problem, which has a more stringent regulation and is termed "Tracking the King". We demonstrate that Alice, by harnessing the shared entanglement and controlled-not gate, can successfully retrodict the choice of King's measurement without knowing any measurement outcome. Our results also provide a counterintuitive quantum communication to deliver information hidden in the choice of measurement.Comment: 16 pages, 5 figures, 2 table

Corneal optical density: Structural basis, measurements, influencing factors, and roles in refractive surgery

The cornea is the main refractive medium of the human eye, and its clarity is critical to visual acuity. Corneal optical density (COD) is an important index to describe corneal transparency. Intact corneal epithelial and endothelial cells, regular arrangement of collagen fibers in the stroma, and normal substance metabolism are all integral for the cornea to maintain its transparency. In the last two decades, the Pentacam Scheimpflug imaging system has emerged as a breakthrough for the measurement of COD (also called corneal densitometry). It has been found that a wide variety of factors such as age, refractive status, and corneal diseases can affect COD. Different corneal refractive surgery methods also change COD in different corneal regions and layers and affect visual acuity following the surgery. Thus, COD has gradually become a significant indicator to evaluate corneal health, one on which the attention of clinicians has been increasingly focused