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DNA-binding proteins play a vital role in cellular processes. It is an extremely urgent to develop a high-throughput method for efficiently identifying DNA-binding proteins. According to the current research situation, some methods in machine learning and deep learning show excellent computational speed and accuracy, which are worthy of application. In this work, a novel predictor was proposed to predict DNA binding proteins called UMAP-DBP. Firstly, the feature extraction of primary protein sequence was realized based on physicochemical distance transformation, Profile-based auto-cross covariance and General series correlation pseudo amino acid composition. Secondly, uniform manifold approximation and projection (UMAP) and feature importance score methods were used for feature selection; there is a progressive relationship between them. Finally, the Adaboost operation engine with jackknife test were adopted for predicting DNA-binding proteins. For the jackknife test on the BP1075 and BP594, we obtained an overall accuracy of 82.97% and 82.14%, Cohen's kappa (CK) of 0.66 and 0.64, respectively. The results illustrate that a feasible method has been developed for predicting DNA-binding proteins by UMAP and Adaboost. This is the first study in which UMAP has been successfully applied to identify DNA-binding proteins. All the datasets and codes are accessible at https://github.com/Wang-Jinyue/UMAP-DBP. [ABSTRACT FROM AUTHOR]

DNase I hypersensitive sites (DHSs) are highly sensitive active chromatin regions to DNase I enzymes, which provide the basis for the study of gene transcriptional regulation mechanism and play an important role in the analysis of gene expression regulatory elements. The identification of DHSs has contributed to biomedical research and genome analysis. There are already southern blotting technology and high-throughput sequencing technology to identify DHSs, but these experimental methods are often time-consuming and expensive, thus, novel and powerful computational methods are needed to predict DHSs. It is understood that researchers in related fields have proposed many feasible methods for the identification of DNase I hypersensitive sites. However, the accuracy of these methods is not satisfactory, so it is necessary to use more effective methods to predict DHSs. Therefore, on the basis of previous studies, we design a novel predictor called iDHS-DXG. First of all, we choose three sequence-derived feature representation methods to extract features, including kmer, mismatch and the dinucleotide property matrix based on Moran coefficient. Truncated singular value decomposition is selected for reducing the dimensionality of the benchmark dataset, and the optimal dimension is obtained through the test. Then, synthetic minority over-sampling technique is utilized to balance the positive and negative samples. After that, we introduce extreme gradient boosting ensemble classifier to predict DHSs. Compared with the previous research results, the main performance evaluation metrics of our method have been improved after five-fold cross-validation test. DHSs were identified on two human genome datasets with an accuracy of 90.84% and 91.27% respectively. This result shows that our method is a feasible, effective and competitive tool for the analysis of gene regulatory elements. Our research is helpful for biologists and geneticists to study genome analysis and gene regulation mechanism. Meanwhile, it is also of great significance to the development of human disease and drug design. Furthermore, the datasets and codes of iDHS-DXG can be obtained from the website: http://github.com/Xtian-696/iDHS-DXG/. [ABSTRACT FROM AUTHOR]

This paper investigated the roles of hydrogen sulfide (H2S) and hydrogen peroxide (H2O2) and the possible relationship between them in regulating the AsA-GSH cycle in wheat leaves under drought stress (DS). Results showed that DS markedly increased the production of H2S and H2O2, the transcript levels and activities of ascorbate peroxidase (APX), glutathione reductase (GR), monodehydroascorbate reductase (MDHAR), and dehydroascorbate reductase (DHAR); malondialdehyde (MDA) content; and electrolyte leakage (EL). Meanwhile, DS markedly reduced plant height and biomass. Above increases induced by drought stress except MDA content and EL were all suppressed by pretreatments with H2S synthesis inhibitor aminooxyaceticacid (AOA) and H2O2 synthesis inhibitor diphenylene iodonium (DPI). Besides, pretreatments with AOA and DPI further significantly increased MDA content and EL and significantly reduced plant height and biomass under DS. DPI reduced the production of H2O2 and H2S induced by DS. AOA also reduced the production of H2S and H2O2 induced by DS. Pretreatments with NaHS + AOA and H2O2 + DPI reversed above effects of AOA and DPI. Our results suggested that H2S and H2O2 all participated in the up-regulation of AsA-GSH cycle in wheat leaves by DS and possibly affected each other. [ABSTRACT FROM AUTHOR]

Physical layer network coding (PNC) significantly improves the throughput of the two-way relay channel (TWRC). However, most of current work on PNC just focuses on one pair users, and there are limit work on multi-pair PNC, in which the main bottleneck on system performance is the interference caused by the remaining communicating pairs. In this paper, we consider a scenario where multiple pairs communicate with each other through one relay node. For a purpose of comparison, we present the analytical capacities of the multi-pair version of the existing TWRC schemes in closed forms. Considering more practical issues such as the direction distribution of incident signals, we propose a spatial multi-pair physical layer network coding scheme. The novelty includes: in the multiple access phase, the log likelihood ratio combination scheme is proposed, which is robust in bad communication conditions; in the broadcast phase, two adaptive group broadcasting schemes are proposed, which can efficiently overcome the near interference problem. Simulation results validate the superiority of the proposed algorithms. [ABSTRACT FROM AUTHOR]

This work considers Mamdani fuzzy systems constructed from finite input-output data pairs using the generalized fuzzy sets with contradictory, opposite and medium negation (GFScom). Considering that the information available often consists of a set of finite numerical data pairs, a new table look-up scheme for constructing Mamdani fuzzy systems is presented. The designed fuzzy system is proved to be capable of approximating any real continuous function on a compact set to arbitrary degree of accuracy. We use this fuzzy modeling method for the truck back-upper control problem. The effectiveness of the proposed method is demonstrated by a comparison with the traditional table look-up scheme. [ABSTRACT FROM AUTHOR]

We extend the classical Damour–Ruffini method and discuss Hawking radiation in Kerr–Newman–de Sitter (KNdS) black hole. Under the condition that the total energy, angular momentum and charge of spacetime are conserved, taking the reaction of the radiation of the particle to the spacetime and the relation between the black hole event horizon and the cosmological horizon into consideration, we derive the black hole radiation spectrum. The radiation spectrum is no longer a pure thermal one. It is related to the change of the Bekenstein–Hawking entropy corresponding the black hole event horizon and the cosmological horizon. It is consistent with the underlying unitary theory. [ABSTRACT FROM AUTHOR]

We propose a concept of universal coherent source for quantum key distribution. The weak coherent pulse (WCP) and heralded single photon source (HSPS) are the most common photon sources for state-of-art quantum key distribution (QKD). However, there exists a prominent crossover between the maximal secure distance and the secure key generating rate in short and middle distance if one applies these two sources in a practical decoy state quantum key distribution. It is shown that by combining the heralded pair coherent state (HPCS) photon source and the practical decoy state method together, one can not only strengthen the maximal secure transmission distance, but also improve key generating rate at short and medium distance. Moreover, the advancement in key generating is not confined in the particular protocol utilized and can be easily checked for both BB84 and SARG protocol. Finally, we clearly demonstrate how the HPCS-based decoy method works effectively and feasibly by proposing an efficient HPCS-based "1 signal+2 decoy" state method. [ABSTRACT FROM AUTHOR]

The IEEE 802.11ax standard defined a set of new specifications to improve spectrum efficiency, power efficiency, and reliability of future wireless local area networks (WLANs). Among these specifications, the uplink multi-user multiple-input, multiple-output (MU-MIMO) remedies the uplink shortcomings of existing WLANs and enables high-efficiency uplink transmissions. This paper considers the problem of adaptive modulation and coding (AMC) for uplink MU-single-input, multiple-output (MU-SIMO) in the upcoming WLANs. Our target is to select the appropriate modulation and coding scheme (MCS) for the existing users so as to maximize the throughput and at the same time guarantee that all users can satisfy a frame error constraint. We adopt a deep learning approach to tackle this problem. We propose to let the access point (AP) leverage the estimated channel state information (CSI) of all users along with the estimated noise standard deviation as the input features to a deep convolutional neural network (DCNN) that is trained to perform AMC. Simulation results reveal that the proposed DCNN for the uplink MU-SIMO AMC outperforms rival machine learning techniques such as fully-connected deep neural network (DNN), k-nearest neighbors (KNN), support vector machines (SVM), Gaussian Naive Bayes (GNB), and random forest (RF) in terms of the throughput and the frame error rate (FER). [ABSTRACT FROM AUTHOR]

Tertiary lymphoid structures (TLSs) play a crucial role in determining prognosis and response to immunotherapy in several solid malignancies. Nevertheless, the effect of TLS-associated gene signature based on The Cancer Genome Atlas (TCGA) cohort in patients with breast cancer (BRCA) remains controversial. Based on TCGA-BRCA dataset (n = 866), 9-gene was identified to construct an TLS signature and further analyzed its prognostic value. Then, we explored the relationship of this TLS signature with molecular subtype, immune microenvironment, tumor mutational burden (TMB). High-TLS signature patients had a better overall survival (OS) than low-TLS signature patients, consistent with the results in the METABRIC cohort. Multivariate analysis revealed that TLS signature remained an independent prognostic indicator for OS. In addition, we established a nomogram with the integration of TLS signature and other independent variables to predict individual risk of death. The comprehensive results showed that patients with high TLS signature benefit from immunotherapy; the signature was also correlated with inhibition of cell proliferation pathways, low TP53 mutation rate, high infiltration of B cells, CD8 + T cells, CD4 + T cells, and M1 macrophages. Therefore, TLS signature is a promising biomarker to distinguish the prognosis and immune microenvironment in BRCA. [ABSTRACT FROM AUTHOR]

α-Gliadins are a major group of gluten proteins in wheat flour that contribute to the end-use properties for food processing and contain major immunogenic epitopes that can cause serious health-related issues including celiac disease (CD). α-Gliadins are also the youngest group of gluten proteins and are encoded by a large gene family. The majority of the gene family members evolved independently in the A, B, and D genomes of different wheat species after their separation from a common ancestral species. To gain insights into the origin and evolution of these complex genes, the genomic regions of the Gli-2 loci encoding α-gliadins were characterized from the tetraploid wild emmer, a progenitor of hexaploid bread wheat that contributed the AABB genomes. Genomic sequences of Gli-2 locus regions for the wild emmer A and B genomes were first reconstructed using the genome sequence scaffolds along with optical genome maps. A total of 24 and 16 α-gliadin genes were identified for the A and B genome regions, respectively. α-Gliadin pseudogene frequencies of 86% for the A genome and 69% for the B genome were primarily caused by C to T substitutions in the highly abundant glutamine codons, resulting in the generation of premature stop codons. Comparison with the homologous regions from the hexaploid wheat cv. Chinese Spring indicated considerable sequence divergence of the two A genomes at the genomic level. In comparison, conserved regions between the two B genomes were identified that included α-gliadin pseudogenes containing shared nested TE insertions. Analyses of the genomic organization and phylogenetic tree reconstruction indicate that although orthologous gene pairs derived from speciation were present, large portions of α-gliadin genes were likely derived from differential gene duplications or deletions after the separation of the homologous wheat genomes ~ 0.5 MYA. The higher number of full-length intact α-gliadin genes in hexaploid wheat than that in wild emmer suggests that human selection through domestication might have an impact on α-gliadin evolution. Our study provides insights into the rapid and dynamic evolution of genomic regions harboring the α-gliadin genes in wheat. [ABSTRACT FROM AUTHOR]

The integrity of cement–salt rock interfaces (CSI) in salt cavern gas storage wells may be damaged during circulating gas injection, production, and long-term gas pressure maintenance. In this study, permeability tests were conducted on cement–salt rock samples under cyclic loading confining pressure at different holding times. The cracks and micro-annuli at the interface were visualised using X-ray computed tomography. The bonding strength of the interface after the permeability test was measured in a triaxial environment. The results showed that with an increase in the number of cycles, the cumulative volumetric strain rate and permeability first decreased rapidly and then tended to stabilise, and the decreasing amplitude was positively correlated with the holding time. When the holding times were 10, 30, and 60 min, the permeability change ratios were 0.844, 0.762, and 0.638, respectively, after one cycle and 0.722, 0.444, and 0.420, respectively, after five cycles. The permeability of CSI is mainly influenced by the holding time. The mechanical properties of the CSI specimens with similar permeabilities showed differences at different holding times. Cyclic loading easily degrades the mechanical properties, which can be improved by extending the holding time. The CSI is the main channel for gas leakage, extending the holding time, and increasing the number of cycles can effectively improve the pore structure of CSI and enhance the cement sheath integrity. This study provides a reference for long-term safe operation of salt cavern gas storage wells. Highlights: Permeability tests and triaxial shear bond strength tests after permeability tests were performed on a cement–salt rock interface. The effects of cyclic loading and holding time on the permeability and mechanical properties of the cement–salt rock interface were investigated. Microcracks' distribution within the cement–salt rock interface under cyclic loads was characterised using computed tomography. [ABSTRACT FROM AUTHOR]

Tertiary lymphoid structures (TLSs) play a crucial role in determining prognosis and response to immunotherapy in several solid malignancies. Nevertheless, the effect of TLS-associated gene signature based on The Cancer Genome Atlas (TCGA) cohort in patients with breast cancer (BRCA) remains controversial. Based on TCGA-BRCA dataset (n = 866), 9-gene was identified to construct an TLS signature and further analyzed its prognostic value. Then, we explored the relationship of this TLS signature with molecular subtype, immune microenvironment, tumor mutational burden (TMB). High-TLS signature patients had a better overall survival (OS) than low-TLS signature patients, consistent with the results in the METABRIC cohort. Multivariate analysis revealed that TLS signature remained an independent prognostic indicator for OS. In addition, we established a nomogram with the integration of TLS signature and other independent variables to predict individual risk of death. The comprehensive results showed that patients with high TLS signature benefit from immunotherapy; the signature was also correlated with inhibition of cell proliferation pathways, low TP53 mutation rate, high infiltration of B cells, CD8 + T cells, CD4 + T cells, and M1 macrophages. Therefore, TLS signature is a promising biomarker to distinguish the prognosis and immune microenvironment in BRCA. [ABSTRACT FROM AUTHOR]

Highlights: A comprehensive summary of the representative promising applications of metal halide perovskite materials, including traditional optoelectronic devices (solar cells, light-emitting diodes, photodetectors, lasers), and cutting-edge technologies in terms of neuromorphic devices (artificial synapses and memristors) and pressure-induced emission. For each application, the fundamentals of the field, the current progress and the remaining challenges are provided, based on the up-to-date works. Nowadays, the soar of photovoltaic performance of perovskite solar cells has set off a fever in the study of metal halide perovskite materials. The excellent optoelectronic properties and defect tolerance feature allow metal halide perovskite to be employed in a wide variety of applications. This article provides a holistic review over the current progress and future prospects of metal halide perovskite materials in representative promising applications, including traditional optoelectronic devices (solar cells, light-emitting diodes, photodetectors, lasers), and cutting-edge technologies in terms of neuromorphic devices (artificial synapses and memristors) and pressure-induced emission. This review highlights the fundamentals, the current progress and the remaining challenges for each application, aiming to provide a comprehensive overview of the development status and a navigation of future research for metal halide perovskite materials and devices. [ABSTRACT FROM AUTHOR]

Human cholesteryl ester transfer protein (CETP) mediates the net transfer of cholesteryl ester mass from atheroprotective high-density lipoproteins to atherogenic low-density lipoproteins by an unknown mechanism. Delineating this mechanism would be an important step toward the rational design of new CETP inhibitors for treating cardiovascular diseases. Using EM, single-particle image processing and molecular dynamics simulation, we discovered that CETP bridges a ternary complex with its N-terminal ?-barrel domain penetrating into high-density lipoproteins and its C-terminal domain interacting with low-density lipoprotein or very-low-density lipoprotein. In our mechanistic model, the CETP lipoprotein-interacting regions, which are highly mobile, form pores that connect to a hydrophobic central cavity, thereby forming a tunnel for transfer of neutral lipids from donor to acceptor lipoproteins. These new insights into CETP transfer provide a molecular basis for analyzing mechanisms for CETP inhibition. [ABSTRACT FROM AUTHOR]

All-inorganic cesium lead halide perovskites have been emerging as the promising semiconductor materials for next-generation optoelectronics. However, the fundamental question of how the environmental atmosphere affects their photophysical properties, which is closely related to the practical applications, remains elusive. Here, we report the dynamic switching between radiative exciton recombination and non-radiative carrier trapping in CsPbBr3 by controlling the atmospheric conditions. Specifically, we show that the photoluminescence (PL) intensity from the CsPbBr3 crystals can be boosted by ~ 60 times by changing the surrounding from vacuum to air. Based on the comprehensive optical characterization, near-ambient pressure X-ray photoelectron spectroscopy (NAP-XPS) as well as density functional theory (DFT) calculations, we unravel that the physisorption of oxygen molecules, which repairs the trap states by passivating the PL-quenching bromine vacancies, is accountable for the enhanced PL in air. These results are helpful for better understanding the optical properties of all-inorganic perovskites. Perovskite-based optoelectronics are expected to become an important component of devices such as solar cells and light-emitting diodes. However, how they are affected by environmental conditions is still not fully understood. The authors investigate the mechanisms, which occur for inorganic perovskites when in contact with ambient atmosphere and how this could potentially impact upon device performance. [ABSTRACT FROM AUTHOR]

For a nonperiodic system, a bamboo SiGe nanowire with axially degraded components, it is impossible to obtain its phonon dispersion relations through lattice dynamic or the first principle calculation. Therefore, we present a simple and available method to solve this problem. At first, the SiGe nanowire with axially degraded component is divided into several sections according to its component distribution like bamboos' sections formed in the growth process. For each section with a given x value, we constructed a pseudo-cell to calculate its phonon dispersion relations. Thermal conductances of junctions and of each section are then calculated by the phonon mismatch model and the phonon transmission probability with diffusive and ballistic portions. The dependences of thermal conductivity on the length of each section and the gradient of degraded component between sections are presented. We studied thermal conductivity dependence on temperature, length and diameter of the SiGe nanowire with axially degraded component. And we found κ ~ l , in which the exponent 0.8 is ascribed to the competition between phonons ballistic and diffusive transport. Furthermore, thermal conductivities along axial (100), (110), and (111) directions are discussed in detail. The method provides a simple and available tool to study thermal conductivity of a non-period system, such as a quasiperiodic superlattice or a nanowire with axially degraded component. [ABSTRACT FROM AUTHOR]

Coarse root biomass (CRB) is an important store of carbon (C) and forest residue for renewable energy, but is often overlooked due to the lack of a simple and effective way to estimate its magnitude. In this study, we developed allometric equations for three functional groups using data from 133 tree samples, with a diameter at breast height (DBH) ranging from 2.6 to 52.0 cm. The functional groups included evergreen coniferous ( Pinus massoniana), deciduous broad-leaved ( Alniphyllum fortunei, Choerospondias axillaris, Liquidambar formosana and Quercus fabri) and evergreen broad-leaved ( Castanopsis carlesii, Cyclobalanopsis glauca, Litsea coreana and Schima superba) species. Allometric equations that related CRB to plot inventory data (e.g. DBH or tree height (H)) and their combinations significantly fitted ( P < 0.0001) for the functional groups and all tree species. The equations using DBH or DBH-H as predictor variables were the best fit ( R ≥ 0.90) and produced good predictions with little bias (less than 21%) for local sites and at regional scales. Allometric equations related to easily obtained remote sensing data (i.e. crown width (CW) and H) were also significantly fitted ( P < 0.0001, R ≥ 0.76), and predictions were close to the observed CRB, despite a high bias (larger than 98.0%). In conclusion, the use of these equations to estimate CRB is essential to the harvest process and helps to formulate new policies for managing the feedstock supply to bioenergy production in subtropical forests. [ABSTRACT FROM AUTHOR]

Chinese subtropical forests contain a diversity of tree species and exhibit a high carbon (C) sequestration capacity, but biomass and C stock assessments in subtropical secondary forests remain uncertain because of a limited availability of allometric equations and an uncertain applicability of existing allometric equations that have not been tested for these forests. We developed allometric equations for important coniferous ( Pinus massoniana), deciduous broadleaved ( Alniphyllum fortunei, Choerospondias axillaris, Liquidambar formosana) and evergreen broadleaved ( Cyclobalanopsis glauca, Litsea rotundifolia, Schima superba) species. A total of 70 trees (10 trees for each species) with diameters at breast height ( D) ranging from 2.6 to 50.9 cm were destructively harvested and dissected into tree components (stem, branch, leaf and coarse root). Species-specific equations using D alone as the predictor variable fitted the data well ( p < 0.0053 and R > 0.72) for each tree component. Including height ( H) in the form of D H only improved the regression fit for A. fortunei and L. rotundifolia. The relationships of branch, leaf and root biomass against D varied among tree species. General equations for functional groups and all species combined showed comparable bias for stem, aboveground and total tree biomass to species-specific equations. We recommend the general equations of multiple species to estimate forest biomass at regional scales and also to estimate stem, aboveground and total tree biomass for each species when species-specific allometric equations are not available at a given site. For branch, leaf and root biomass, species-specific equations are preferred, even though this requires biomass data for additional tree species. [ABSTRACT FROM AUTHOR]

Combining Landau diamagnetism and differential magnetic susceptibility to an electromagnetic wave, we theoretically predict a graphene-sheet periodic structure, which exhibits a left-handed property to an electromagnetic wave in the infrared region by modulating external fields. Our new mechanism, unlike the usual mechanism, does not use resonant behavior and is thus able to synthesize broadband left-handed metamaterial. [ABSTRACT FROM AUTHOR]

Connecting genome-wide association study (GWAS) to biological mechanisms underlying complex traits is a major challenge. Mastitis resistance and milk production are complex traits of economic importance in the dairy sector and are associated with intra-mammary infection (IMI). Here, we integrated IMI-relevant RNA-Seq data from Holstein cattle and sequence-based GWAS data from three dairy cattle breeds (i.e., Holstein, Nordic red cattle, and Jersey) to explore the genetic basis of mastitis resistance and milk production using post-GWAS analyses and a genomic feature linear mixed model. At 24 h post-IMI, genes responsive to IMI in the mammary gland were preferentially enriched for genetic variants associated with mastitis resistance rather than milk production. Response genes in the liver were mainly enriched for variants associated with mastitis resistance at an early time point (3 h) post-IMI, whereas responsive genes at later stages were enriched for associated variants with milk production. The up- and down-regulated genes were enriched for associated variants with mastitis resistance and milk production, respectively. The patterns were consistent across breeds, indicating that different breeds shared similarities in the genetic basis of these traits. Our approaches provide a framework for integrating multiple layers of data to understand the genetic architecture underlying complex traits. [ABSTRACT FROM AUTHOR]

The adsorption of glycine, glutamic acid, histidine and phenylalanine on single-layer graphdiyne/ graphene is investigated by ab initio calculations. The results show that for each amino acid molecule, the adsorption energy on graphdiyne is larger than the adsorption energy on graphene and dispersion interactions predominate in the adsorption. Molecular dynamics simulations reveal that at room temperature the amino acid molecules keep migrating and rotating on graphdiyne surface and induce fluctuation in graphdiyne bandgap. Additionally, the photon absorption spectra of graphdiyne-amino-acid systems are investigated. We uncover that the presence of amino acid molecules makes the photon absorption peaks of graphdiyne significantly depressed and shifted. Finally, quantum electronic transport properties of graphdiyne-amino-acid systems are compared with the transport properties of pure graphdiyne. We reveal that the amino acid molecules induce distinct changes in the electronic conductivity of graphdiyne. The results in this paper reveal that graphdiyne is a promising two-dimensional material for sensitively detecting amino acids and may potentially be used in biosensors. [ABSTRACT FROM AUTHOR]