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[Display omitted] Component selection is crucial for microwave absorbents. Multi-component absorbers are increasingly useful and can be prepared through the rational design and control of various electrical, magnetic, and other auxiliary components. In this paper, Ni 3 Fe/NiFe 2 O 4 nanospheres with two-phase magnetism were designed for use as a multi-component absorber. Specifically, a Ni 3 Fe/ NiFe 2 O 4 @SPC composite with 3D networks was successfully fabricated by hydrothermal method, high-temperature carbonization for activation, and electrostatic self-assembly. The contact interface and coupling effect between the two magnetic components can promote the attenuation of electromagnetic waves. Moreover, the introduction of porous carbon successfully inhibits the easy aggregation of the magnetic particles. Impressively, with a filling load of 10 wt%, the optimal RL of the prepared Ni 3 Fe/NiFe 2 O 4 @SPC composite reaches −60.6 dB, and the effective absorption bandwidth is 5.2 GHz at 2 mm. The combination of two magnetic components and porous carbon in this multiphase microwave-absorbing composite demonstrates a feasible strategy for designing efficient microwave absorbers in the future. [ABSTRACT FROM AUTHOR]

Cavitation is a common phenomenon in nature and has numerous applications. In contrast to a cavitation bubble in a free domain, a cavitation bubble in a thin tube is restricted by the tube wall, which is expected to significantly affect bubble evolution, but its mechanism is still unclear. In this study, the dynamics of a cavitation bubble in a thin circular tube is studied by numerical simulation, focusing on the confinement effects of the tube. The results show that besides affecting the size and lifetime of the bubble, the confinement effects of the tube lead to the generation of counter jets and a ring jet during the contraction process of the bubble, and the curvature of the two counter jets determines the ring jet's peak velocity. When the bubble deviates from the midpoint of the tube in the axial direction, the two sides of the bubble along the axial direction show asymmetric behaviors, which results in the bubble migrating toward the midpoint. The tube diameter, tube length, liquid viscosity, and initial bubble position can significantly influence the degree of confinement effects, which can be characterized by the variations of several key indicators, such as bubble size, lifetime, degree of deformation, counter jet velocity, ring jet velocity, and axial migration of the bubble. [ABSTRACT FROM AUTHOR]

[Display omitted] • In this study, the genome of one perennial Gb cotton accession was assembled leading to identify intraspecific and interspecific SVs associated with the agronomic traits. • Haploblocks in sea-island cotton were associated with agronomic traits improvement and drove the differentiation and adaptation of sea-island cotton. • Our study builds a foundation for the breeding and improvement of sea-island cotton. Sea-island cotton (Gossypium barbadense , Gb) is one of the major sources of high-grade natural fiber. Besides the common annual Gb cotton, perennial Gb cotton is also cultivated, but studies on perennial Gb cotton are rare. We aimed to make a systematic analysis of perennial sea-island cotton and lay a foundation for its utilization in breeding, and try to identify the representative structural variations (SVs) in sea-island cotton, and to reveal the population differentiation and adaptive improvement of sea-island cotton. Through genome assembly of one perennial Gb cotton accession (named Gb_M210936) and comparative genome analysis, variations during Gb cotton domestication were identified by comparing Gb_M210936 with annual Gb accession 3–79 and with wild allotetraploid cotton G. darwinii. Six perennial Gb accessions combining with the resequenced 1,129 cotton accessions were used to conduct population and genetic analysis. Large haplotype blocks (haploblocks), generated from interspecific introgressions and intraspecific inversions, were identified and were used to analyze their effects on population differentiation and agronomic traits of sea-island cotton. One reference genome of perennial sea-island cotton was assembled. Representative SVs in sea-island cotton were identified, and 31 SVs were found to be associated with agronomic traits. Perennial Gb cotton had a closer kinship with the wild-to-landrace continuum Gb cotton from south America where Gb cotton is originally domesticated. Haploblocks were associated with agronomic traits improvement of sea-island cotton, promoted sea-island cotton differentiation into three subgroups, were suffered from breeding selection, and may drive Gb cotton to be adapted to central Asian. Our study made up the lack of perennial Gb cotton genome, and clarified that exotic introgressions improved the traits of sea-island cotton, promoted the population differentiation, and drove sea-island cotton adaptive to central Asia, which will provide new insights for the genetic breeding improvement of sea-island cottons. [ABSTRACT FROM AUTHOR]

In this article, the fully discrete local discontinuous Galerkin (LDG) method is presented for numerically solving a class of nonlocal viscous water wave model, where the BDF2 with the L 1 formula of the time Caputo fractional derivative is applied to deal with the time direction, and the LDG method is developed to approximate the space direction. The stability of the fully discrete LDG scheme is proven, and the a priori error result with O (τ 3 2 + h k + 1 2 ) in L 2 -norm is derived in detail. Finally, numerical examples supporting theoretical error result are provided, and the decay rates under different coefficients are also discussed. [ABSTRACT FROM AUTHOR]

Aims: This study aimed to evaluate the safety, efficacy, and long-term outcomes of endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) for treating colorectal adenomas and tumors. Methods: A systematic literature review was conducted using databases including PubMed, Web of Science, and Embase. Parameters such as number of patients or lesions, histological diagnosis, lesion size, surgery time, en-bloc resection, R0 resection, severe postoperative complications, and local recurrence were extracted and pooled for analysis. Results: A total of 12 retrospective studies involving 1289 patients and 1850 lesions were included in the analysis. EMR was found to have a shorter operation time by 53.6 minutes (95% CI: 51.3, 55.9, P<0.001) and fewer incidences of severe postoperative complications such as perforation and delayed bleeding (OR = 0.40, 95%CI: 0.23, 0.71, P<0.001). On the other hand, ESD had higher rates of en-bloc resection (OR = 0.15, 95%CI: 0.07, 0.30, P<0.001) and R0 resection (OR = 0.32, 95%CI: 0.16, 0.65, P<0.001). Recurrence after EMR was found to be significantly higher than that after ESD surgery (OR = 5.88, 95%CI: 2.15, 16.07, P = 0.037). Conclusions: The study suggests that the choice of surgical method may have a greater impact on recurrence compared to the pathological type, and that ESD may be more suitable for the treatment of malignant lesions despite its higher rates of severe postoperative complications and longer operation time. [ABSTRACT FROM AUTHOR]

Autosomal short tandem repeats (STRs) are crucial in identifying humans. Herein, a developmental validation was performed for a newly generated autosomal STR kit (Microreader™ 36A ID System). The sensitivity of this kit was fine when the input DNA dropped down to 0.02 ng/uL. Mixture analysis showed that when male:female = 200 pg: 5400 pg, full profiles of both individuals could be obtained. When inhibited substances existed, all alleles were acquired up to 2000 μM haematin, 1000 ng/μL humic acid or 250 ng/μL tannic acid. The kit exhibited a high precision level with no more than 0.29 nt standard deviation of allele size, with the accuracy (the difference of allele size between the true allele and ladder allele) no more than 0.4 nt. The total discrimination power of this system in the Chinese Han and Hui population was larger than 1–0.1 × 10−30. For the full-sibling test, the identical-by-state (IBS) score varied from 37 to 46, while it was from 21 to 28 when using the AGCU Express marker 22 STR Kit. This kit can increase the autosomal STR information of a single PCR reaction and is promising in the casework of forensic genetic as well as database construction. [ABSTRACT FROM AUTHOR]

To date developments of seismic attenuation models of the Earth have lagged those of velocity models. This is partly due to difficulties in isolating waveform perturbations caused by attenuation and velocity heterogeneities and partly due to different theories (e.g., ray theory, finite frequency theory) used in most previous and current studies to approximate sensitivity kernels and invert for the attenuation structure. We present in this paper a new method for computing the 3D waveform Fréchet kernels that account for full physical‐dispersion and dissipation attenuation. For solving the 3D isotropic anelastic wave equation described by the generalized Maxwell body model, we extend our previously proposed full waveform modeling method in Cartesian coordinates to that in spherical coordinates, which can provide stable numerical solutions even in the presence of strong attenuation. Then, we apply the scattering‐integral method for calculating 3D travel time and amplitude sensitivity kernels with respect to velocity and attenuation structures. We demonstrate the accuracy of our forward method and the effectiveness of the implementation of absorbing and free surface boundary conditions through numerical tests. Moreover, by choosing the Northwestern United States region as a realistic example, we verify the accuracy of the computed 3D sensitivity kernels through comparing the waveform measurements with predictions from the kernels. Finally, we discuss the importance of calculating full anelastic sensitivity kernels including both effects of physical dispersion and dissipation, where we specially explore the effect of scattering due to random velocity and attenuation heterogeneities on waveform measurements. Plain Language Summary: Anelasticity is an intrinsic property of the Earth that causes energy reduction of propagating seismic waves. Anelastic structures (including velocities and attenuation) are strongly related to temperature, partial melt, and water contents of the Earth, which provide crucial insight into the plate tectonics and geodynamic processes. To date developments of seismic attenuation models have lagged those of velocity models, because of difficulties in isolating effects of velocity heterogeneities and attenuation on waveform perturbations and large discrepancies in various theoretical methods and the resulting attenuation models. The full waveform inversion (FWI) method is promising to deal with the two difficulties and here we develop a novel anelasitc scattering‐integral‐based FWI method. We verify the effectiveness of our forward method in anelastic modeling even in the presence of strong attenuation, and we testify the accuracy of the computed 3D velocity and attenuation sensitivity kernels using the Northwestern United States region as a realistic example. We also demonstrate the importance of computing full anelastic sensitivity kernels including both effects of physical dispersion and dissipation, where we specially estimate the amount of scattering due to heterogeneous velocity and attenuation perturbations on waveform perturbations in subduction zones. Key Points: We develop a new method for computing 3D sensitivity kernels with full attenuation and verify its accuracy through numerical experimentsWe demonstrate the importance of computing full anelastic sensitivity kernels including both effects of physical dispersion and dissipationScattering due to 30% attenuation heterogeneities alone in subduction zones could contribute up to 9% of observed waveform perturbations [ABSTRACT FROM AUTHOR]

Background: The study aimed to establish a prognostic survival model with 8 pyroptosis-and-cuproptosis-related genes to examine the prognostic effect in patients of hepatocellular carcinoma (HCC). Methods: We downloaded gene expression data and clinical information of HCC patients from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). The clustering analysis and cox regression with LASSO were used for constructing an 8 PCmRNAs survival model. Using TCGA, ICGC and GEO cohort, the overall survival (OS) between high- and low- risk group was determined. We also evaluated independent prognostic indicators using univariate and multivariate analyses. The relatively bioinformatics analysis, including immune cell infiltration, function enrichment and drug sensitivity analyses, was performed as well. The gene expression of 8 PCmRNAs in vitro were validated in several HCC cell lines by qRT-PCR and Western blot. The relationship between GZMA and Fludarabine were further checked by CCK-8 assay. Results: The survival prognostic model was constructed with ATP7A, GLS, CDKN2A, BAK1, CHMP4B, NLRP6, NOD1 and GZMA using data from TCGA cohort. The ICGC and GEO cohort were used for model validation. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. Risk scores had the highest predictable value for survival among Stage, Age, Gender and Grade. Most Immune cells and immune functions were decreased in high-risk group. Besides, function enrichment analyses showed that steroid metabolic process, hormone metabolic process, collagen − containing extracellular matrix, oxidoreductase activity and pyruvate metabolism were enriched. Potential drugs targeted different PCDEGs like Nelarabine, Dexamethasone and Fludarabine were found as well. ATP7A, GLS, CDKN2A, BAK1, CHMP4B, NOD1 were upregulated while NLRP6 and GZMA were downregulated in most HCC cell lines. The potential therapy of Fludarabine was demonstrated when GZMA was low expressed in Huh7 cell line. Conclusion: We constructed a novel 8-gene (ATP7A, GLS, CDKN2A, BAK1, CHMP4B, NLRP6, NOD1 and GZMA) prognostic model and explored potential functional information and microenvironment of HCC, which might be worthy of clinical application. In addition, several potential chemotherapy drugs were screened and Fludarabine might be effective for HCC patients whose GZMA was low expressed. [ABSTRACT FROM AUTHOR]

• Human awareness detection dynamically reacts to high-altitude environment. • Early and late components co-mediate the reaction with exposure duration. • Opposite change of two components as a response to the reduced cognitive resources. • Increased late component and fast reaction resist high-altitude exposure. The psychological effects of long-term exposure to high-altitude environments have attracted great attention. These effects are usually attributed to the diminished cognitive resources due to high-altitude exposure. This study employed electroencephalography (EEG) to investigate the effects of exposure duration on awareness detection tasks. Neither reaction time nor accuracy showed the direct effects of the exposure duration, so did the model indexes obtained from drift diffusion model analysis. However, event-related potentials (ERP) analysis revealed that exposure duration was associated with changes in the visual awareness negativity (VAN) and the late positivity (LP) components, which in turn affected reaction time. Specifically, longer exposure durations were associated with lower VAN and higher LP, resulting in shorter reaction times and greater drift rate. In contrast to previous studies, the reverse relationship between VAN and LP may reflect a compensatory response to the reduced cognitive resources caused by high-altitude exposure. Additionally, increased LP and shorter reaction times with exposure duration may reflect a resistance to the high-altitude environment. We also conducted time–frequency analysis and found that theta power did not vary with exposure duration, suggesting that the reduction in cognitive resources remains stable in these individuals over time. Overall, our study provides new insights into the dynamic effects of high-altitude environments on awareness detection in the presence of reduced cognitive resources. [ABSTRACT FROM AUTHOR]

Photochemical generation is an important pathway for atmospheric sulfate formation. However, the roles of atmospheric co-existing photosensitive dissolved organic matter (DOM) in sulfate formation are still unclear. The experimental results in this work provide evidence that atmospheric photosensitizers produce active intermediates to oxidize S(IV) into S(VI) under illumination. Quenching experiments of eight photosensitive model compounds (PS) demonstrate that their triplet-excited states (3PS*) dominate sulfate formation for the photosensitizing pathway with a contribution of over 90%, and 1O2 plays an important role in sulfate formation. The results using humic acid (HA) and water-soluble organic carbon in vehicle exhaust particles (WSOC) as representatives of atmospheric photosensitizers further verify that triplet-excited DOM (3DOM*) is the main reactive species for sulfate formation, which is consistent with the results of PS. Our findings provide new insights into the photochemical formation pathways of atmospheric sulfate. [ABSTRACT FROM AUTHOR]

[Display omitted] • microRNA expression compared in Cd-tolerant/sensitive barley Zhenong8 vs W6nk2. • First report a novel gene HvNAT2 targeted by miR156g-3p_3 vital in barley Cd tolerance. • HvNAT2 evolved from the Zygnematales in Streptophyte algae and positively regulates Cd tolerance. • Overexpression of HvNAT2 enhances the expression of genes for ROS scavenging and antoxidative enzyme activity. Cadmium (Cd) is one of the most detrimental heavy metal pollutants, seriously affecting crop production and human health. Nucleobase-ascorbic acid transporters (NAT) are widely present in many living organisms including plants, animals and microbes; however, the role of NAT in plant Cd tolerance remains unknown. To identify Cd-induced miRNAs that target HvNAT2 and to determine the role of this gene and its product in Cd tolerance. High-throughput-sequencing was used to identify the miRNA expression profile of barley roots in response to Cd stress. Overexpression (OX) and RNAi lines were then constructed for HvNAT2 and comparative transcriptomic analysis was performed to determine the function of this transporter examining its effects on traits such as Cd uptake/flux and translocation, morphology and antioxidant capacity in relation to Cd tolerance. In addition, phylogenetic analysis was performed to obtain insights into the evolution of HvNAT2. Cd stress-induced genome-wide expression profiles of miRNAs identified a Cd-induced miRNA, miR156g-3p_3, that had HvNAT2 as its target. HvNAT2 was negatively regulated in the high-Cd-accumulating and Cd-tolerant genotype Zhenong8. Evolutionary analysis indicated that orthologues of the plasma membrane localized, HvNAT2 , can be traced back to the sister group of land plants, the streptophyte algae. Overexpression of HvNAT2 increases Cd tolerance with higher tissue Cd accumulation but less oxidative damage in transgenic barley plants. RNAi of HvNAT2 leads to a significant reduction of Cd tolerance. The higher Cd accumulation in roots of the OX3 line was also demonstrated by confocal microscopy and electrophysiology. Transcriptome analysis showed that the enhancement of antioxidant capacity by HvNAT2 was related to stress signaling pathways. Furthermore, oxidative stress tolerance in HvNAT2 -OX plants was regulated by the synthesis of phytochelatins and the glutathione metabolism cycle. Our study reveals a key molecular mechanism of NAT in Cd tolerance in plants that is useful for sustainable agricultural production and management of hazardous this heavy metal for better environment management and ecosystem function. [ABSTRACT FROM AUTHOR]

With the imminent era dominated by high-tech electronic products, the development of high-efficiency electromagnetic wave absorption materials has become a critical task. Rational component regulation and structural design are considered to be effective methods to optimize the electromagnetic wave absorption performance of materials. Herein, we first prepared a Fe-PBA@ PDA@GO precursor via solvothermal method; then, vulcanization was used to develop a FeS 2 /Fe 7 S 8 @C@rGO composite with a core-shell heterostructure, in which core-shell FeS 2 /Fe 7 S 8 @C microspheres were embedded on the wrinkled reduced graphene oxide layer. FeS 2 /Fe 7 S 8 @C@rGO, as a multi-component composite, demonstrates superior impedance matching and can thus capture more electromagnetic waves, while the multiple losses facilitate the dissipation of incident electromagnetic waves. Concretely, FeS 2 /Fe 7 S 8 @C@rGO can display significant attenuation of incident electromagnetic waves through multi-interface polarization, dipole polarization, resonance loss and eddy current loss. Additionally, the three-dimensional hierarchical structure not only improves the conductive loss, but also promotes multiple reflections and scattering. The FeS 2 /Fe 7 S 8 @C@rGO composite exhibits a minimum reflection loss of −62.7 dB and an effective absorption broadband (6.1 GHz) with a filler loading of 20 wt% at 2.2 mm, and the effective absorption bandwidth reaches 7.6 GHz at a layer thickness of 2.5 mm. These results provide a valuable reference for the preparation of high-performance microwave absorbers through composition adjustment and controlled structural design. [Display omitted] [ABSTRACT FROM AUTHOR]

SUMMARY: Structural variations (SVs) are critical factors affecting genome evolution and important traits. However, identification results and functional analyses of SVs in upland cotton are rare. Here, based on the genetic relationships, breeding history and cumulative planting area of upland cotton in China, nine predominant cultivars from the past 60 years (1950s–2010s) were selected for long read sequencing to uncover genic variations and breeding improvement targets for this crop. Based on the ZM24 reference genome, 0.88–1.47 × 104 SVs per cultivar were identified, and an SV set was constructed. SVs affected the expression of a large number of genes during fiber elongation, and a transposable element insertion resulted in the glandless phenotype in upland cotton. Six widespread inversions were identified based on nine draft genomes and high‐throughput chromosome conformation capture data. Multiple haplotype blocks that were always associated with aggregated SVs were demonstrated to play a pivotal role in the agronomic traits of upland cotton and drove its adaptation to the northern planting region. Exotic introgression was the source of these haplotype blocks and increased the genetic diversity of upland cotton. Our results enrich the genome resources of upland cotton, and the identified SVs will promote genetic and breeding research in cotton. Significance Statement: The present study uncovered structural variants in upland cottons, many of which affected gene expression in cotton fibers. A transposable element insertion resulting in the glandless phenotype was identified. Inversions affecting population differentiation and adaptation in upland cotton were identified. Haplotype blocks generated from interspecies introgressions associated with upland cotton agronomic traits, providing new ideas for cotton breeding. [ABSTRACT FROM AUTHOR]

In this paper we establish the modular relation for Maass forms to the effect that the Fourier–Whittaker expansion and the ramified functional equation are equivalent, i.e. the RHB (Riemann–Hecke–Bochner) correspondence. This arises from the new standpoint that Maass' procedure is one of the ways leading to the Fourier–Whittaker expansion similar to the situation that various representations of the modified Bessel function K ν have provided such vast amount of different methods including the Hardy transform and the beta-transform leading to the Fourier-Bessel expansion from opposite directions. Naturally, we may abridge the gap between Hecke Eisenstein series and Epstein zeta-functions and the Chowla–Selberg integral formula and Ramanujan–Guinand formula are immediate corollaries, whose remark is due to the referee. [ABSTRACT FROM AUTHOR]

Exploring the spatial and temporal evolution characteristics of the border land use multifunctionality (LUMF) provides insights for taking advantage of border land use and optimizing border land use policies. Based on the improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) mode, this study identifies and evaluates the LUMFs in the China-Vietnam border area between 2000 and 2018 from the perspectives of agricultural production, social security, ecological service, landscape recreation, and national security. The results show that: 1) The comprehensive land use functions in most counties and cities continued to be improved. 2) The comprehensive land use function exhibits remarkable spatial divergence and aggregation characteristics. The high-value area of the agricultural production function and social security function evolves from the east to the west. In addition, the spatial evolution of ecological service function is complicated, without an obvious spatial divergence and aggregation pattern. The landscape recreation function shows different spatial differentiation characteristics in the early and middle stage, and forms a large cluster in the later stage. Finally, the spatial evolution pattern of the national security function is significant. 3) Designing differentiated border land policies, improving border land use security, and establishing a long-term mechanism for ecological protection and ecological compensation can aid in optimizing the LUMF level in the border area. [ABSTRACT FROM AUTHOR]

A new positive-sense single-stranded RNA (+ssRNA) mycovirus, Verticillium dahliae magoulivirus 1 (VdMoV1), was isolated from two strains (2-19 and XLZ70) of Verticillium dahliae. The complete genome of VdMoV1 is 2303 nucleotides (nt) in length and has a large open reading frame (nt positions from 61 to 1938) encoding an RNA-dependent RNA polymerase (RdRp). A multiple sequence alignment indicated that the central region of the RdRp encoded by VdMoV1 contains eight typical viral RdRp motifs. BLASTp analysis demonstrated that VdMoV1 has the highest sequence identity (86.88%) to Bremia lactucae associated ourmia-like virus 2 (BlaOLV2). Phylogenetic analysis revealed that VdMoV1 is a new member of the genus Magoulivirus. As far as we know, VdMoV1 is the first reported member of the family Botourmiaviridae infecting V. dahliae. [ABSTRACT FROM AUTHOR]

With the advent of the "Information Era", the development of an integrated infrastructure, which involves the integration of traditional transportation infrastructure and informatization development, has become a new impetus for economic growth. Meanwhile, its environmental performance remains uncovered. Using data from 30 Chinese provinces between 2013 and 2020, this study designed an index system and constructed the coupling coordination degree model to assess the development level of integrated infrastructure. The regression model was established to examine the nonlinear effect of the integrated infrastructure on carbon emissions. The influencing mechanism was also discussed through identifying the impacts of integrated infrastructure on the energy intensity, industrial structure, and technological innovation. The evaluation of the evolutionary trend showed that the level of integrated infrastructure continues to improve and displays a feature of "higher highs, lower lows", although the regional disparity was significant. The regression analysis showed that there was an inverted U–shaped relationship between integrated infrastructure and CO2 emissions. It is also found that most provinces were below the turning point. In the mechanism analysis section, we can demonstrate that integrated infrastructure can enhance energy intensity, which might hamper reductions in emissions. However, an integrated infrastructure facilitates the development of tertiary industry, which can lead to lower carbon emissions. Based on the conclusions, some insightful policy implications are provided. [ABSTRACT FROM AUTHOR]

To evaluate the magic angle effect on diffusion tensor imaging (DTI) measurements in rat ligaments and mouse brains. Three rat knee joints and three mouse brains were scanned at 9.4 T using a modified 3D diffusion-weighted spin echo pulse sequence with the isotropic spatial resolution of 45 μm. The b value was 1000 s/mm2 for rat knee and 4000 s/mm2 for mouse brain. DTI model was used to investigate the quantitative metrics at different orientations with respect to the main magnetic field. The collagen fiber structure of the ligament was validated with polarized light microscopy (PLM) imaging. The signal intensity, signal-to-noise ratio (SNR), and DTI metrics in the ligament were strongly dependent on the collagen fiber orientation with respect to the main magnetic field from both simulation and actual MRI scans. The variation of fractional anisotropy (FA) was about ~32%, and the variation of mean diffusivity (MD) was ~11%. These findings were further validated with the numerical simulation at different SNRs (~10.0 to 86.0). Compared to the ligament, the DTI metrics showed little orientation dependence in mouse brains. Magic angle effect plays an important role in DTI measurements in the highly ordered collagen-rich tissues, while MD showed less orientation dependence than FA. [ABSTRACT FROM AUTHOR]

A subset D ⊆ V (G) is said to be a positive influence dominating set of a graph G if every vertex v ∈ V (G) has at least half of its neighbors in D. The positive influence domination number of G, denoted by γ PI (G) , is the cardinality of the smallest positive influence dominating set of G. To find a smallest positive influence dominating set of G is called the positive influence domination problem. In this paper, we first establish some sharp lower bounds on γ PI (G) . Next, we investigate the complexity of the positive influence domination problem and show that the decision version of it is NP-complete even when restricted to bipartite graphs and split graphs. Moreover, we prove that the positive influence domination problem on graphs with maximum degree 3 remains APX-complete. [ABSTRACT FROM AUTHOR]

The study of tractor ergonomics is both an essential part of public health and a very significant part of the scientific community's focus at the moment. It offers a foundation for the layout design of the tractor cab, making it possible to effectively avoid occupational diseases, minimize the number of safety accidents, and enhance the comfort of operation. Devices are categorized as control rod devices, knob-type devices, and steering wheels according to the various modes of operation of the tractor cab. Steering wheels are also included. The ease of handling of a number of different components was ranked according to how well they performed on the fast evaluation approach for the upper limbs. After that, in accordance with the concept that underpins this evaluation approach, the comfortable range of motion of human upper limb joints is evaluated while undergoing a variety of manipulation modalities. In conjunction with the structure of the human body and the characteristics of its movement, a streamlined point-line structure model of the human upper limb is constructed, with the H-point serving as the reference point. The problem of figuring out how to distribute the control components in the best possible way has been solved, and the optimal distribution range diagram of the steering wheel has been obtained. The ideal height for the distribution of control rod devices is around 300-400 millimeters, whereas the ideal height for the distribution of knob-type devices is approximately 200-500 millimeters. In conclusion, the cab design of the KAT2204 tractor is improved upon thanks to the analysis done in this study, which can be found above. The legitimacy of the research conclusion is confirmed by the fact that the RULA value is lower than 2, which is proved by the fact that the design findings are validated by the Creo Manikin module. The ergonomics of the tractor cab were taken into consideration when using this research approach as a reference. [ABSTRACT FROM AUTHOR]

As an important mechanism to maintain cellular homeostasis, autophagy exerts critical functions via degrading misfolded proteins and damaged organelles. Recent years, alternative autophagy, a new type of autophagy has been revealed, which shares similar morphology with canonical autophagy but is independent of Atg5/Atg7. Investigations on different diseases showed the pivotal role of alternative autophagy during their physio-pathological processes, including heart diseases, neurodegenerative diseases, oncogenesis, inflammatory bowel disease (IBD), and bacterial infection. However, the studies are limited and the precise roles and mechanisms of alternative autophagy are far from clear. It is necessary to review current research on alternative autophagy and get some hint in order to provide new insight for further study. Bv7JFPcu7G5EZBu7jDT_sS Video Abstract [ABSTRACT FROM AUTHOR]

• A flexible optimization strategy is introduced to better learn pair-based similarity. • Imposing Weibull distribution-based constraint helps to reduce neighborhood ambiguous. • A maximum mean discrepancy quantization is proposed to minimize information loss. Hashing has been a promising technology for fast nearest neighbor retrieval in large-scale datasets due to the low storage cost and fast retrieval speed. Most existing deep hashing approaches learn compact hash codes through pair-based deep metric learning such as the triplet loss. However, these methods often consider that the intra-class and inter-class similarity make the same contribution, and consequently it is difficult to assign larger weights for informative samples during the training procedure. Furthermore, only imposing relative distance constraint increases the possibility of being clustered with larger average intra-class distance for similar pairs, which is harmful to learning a high separability Hamming space. To tackle the issues, we put forward deep Weibull hashing with maximum mean discrepancy quantization (DWH), which jointly performs neighborhood structure optimization and error-minimizing quantization to learn high-quality hash codes in a unified framework. Specifically, DWH learns the desired neighborhood structure in conjunction with a flexible pair similarity optimization strategy and a Weibull distribution-based constraint between anchors and their neighbors in Hamming space. More importantly, we design a maximum mean discrepancy quantization objective function to preserve the pairwise similarity when performing binary quantization. Besides, a class-level loss is introduced to mine the semantic structural information of images by using supervision information. The encouraging experimental results on various benchmark datasets demonstrate the efficacy of the proposed DWH. [ABSTRACT FROM AUTHOR]

Single‐image dehazing is an important problem because it is a key prerequisite for most high‐level computer vision tasks. Traditional prior‐based methods adopt priors generated from clear images to restrain the atmospheric scattering model and then recover haze‐free images. However, these prior‐based methods always encounter over‐enhancement, such as halos and colour distortion. To solve this problem, many works use a convolutional neural network to retrieve original images. However, without priors as guidance, these learning‐based methods dehaze effectively in synthetic datasets but perform poorly in real scenes. Hence, in this paper, we propose a prior‐guided multiscale network for single‐image dehazing named PGMNet. Specifically, prior‐based methods are adopted to acquire dehazed images of the training dataset in advance and then send these dehazed images to a parameter‐shared encoder to form multiscale features. During the decoding process, these multiscale features are adopted to guide the prior‐guided multiscale network to recover more image details. Moreover, considering that these prior‐based dehazed images usually contain some over‐enhanced regions, a spatial attention guided feature aggregation module and squeeze‐and‐excitation module are adopted to alleviate colour distortion. The proposed PGMNet takes the advantage of prior‐based methods in real haze removal and provides superior performance compared with the state‐of‐the‐art methods on both synthetic and real‐world datasets. [ABSTRACT FROM AUTHOR]

Single image dehazing has become a key prerequisite for most high-level computer vision tasks since haze severely degrades the input images. Traditional prior-based methods dehaze images by some assumptions concluded from haze-free images, which recover high-quality results but always cause some halos or color distortion. Recently, many methods have been using convolutional neural networks to learn the haze-relevant features and then retrieve the original images. These learning-based methods achieve better performance in synthetic scenes but can hardly restore a clear image with discriminative texture when applied to real-world images, mainly because these networks are trained on synthetic datasets. To solve these problems, a self-modulated generative adversarial network for single image dehazing named SMGAN is proposed. The SMGAN inputs prior-dehazed images into a parameter-shared encoder to produce some latent information of these dehazed images. During the hazy image decoding process, the latent information is sent to self-modulated batch normalization layers, which makes the network fit in real haze removal. Moreover, consider that there are some over-enhanced regions in the guidance images, and a refine module is proposed to alleviate the negative information. The proposed SMGAN combines the advantages of prior-based methods and learning-based methods, which provides superior performance compared with the state-of-the-art methods on both synthetic and real-word datasets. [ABSTRACT FROM AUTHOR]

The high-quality reference-grade genome for Gossupium tomentosum can greatly promote the progress in biological research and introgression breeding for the mainly cultivated species, G. hirsutum. Here, we report a high-quality genome assembly for G. tomentosum by integrating PacBio and Hi-C technologies. Comparative genomic analysis revealed a large number of genetic variations. Two re-sequencing-based ultra-dense genetic maps were constructed which comprised 4,047,199 and 6,009,681 SNPs, 4120 and 4599 bins and covering 4126.36 cM and 4966.72 cM in the EMF 2 (F 2 from G. hirsutum × G. tomentosum) and GHF 2 (F 2 from G. hirsutum × G. barbadense). The EMF 2 exhibited lower recombination rate at the whole - genome level as compared with GHF 2. We mapped 22 and 33 QTL associated with crossover frequency and predicted Gh_MRE11 and Gh_FIGL1 as the candidate genes governing crossover in the EMF 2 and GHF 2 , respectively. We identified 13 significant QTL that regulate the floral transition, and revealed that Gh_AGL18 was associated with the floral transition. Therefore, our study provides a valuable genomic resource to support a better understanding of cotton interspecific cross and recombination landscape for genetic improvement and breeding in cotton. • An high-quality reference-grade genome of Gossupium tomentosum. • A high resolution of genetic linkage map of G. hirsutum × G. tomentosum. • QTL associated with crossovers frequency and QTL regulating floral transition in interspecific hybridization. [ABSTRACT FROM AUTHOR]

Essential proteins are a vital part of the survival of organisms and cells. Identification of essential proteins lays a solid foundation for understanding protein functions and discovering drug targets. The traditional biological experiments are expensive and time-consuming. Recently, many computational methods have been proposed. However, some noises in the protein-protein interaction (PPI) networks affect the efficiency of essential protein prediction. It is necessary to construct a credible PPI network by using other useful biological information to reduce the effects of these noises. In this article, we proposed a model, Ess-NEXG, to identify essential proteins, which integrates biological information, including orthologous information, subcellular localization information, RNA-Seq information, and PPI network. In our model, first, we constructed a credible weighted PPI network by using different types of biological information. Second, we extracted the topological features of proteins in the constructed weighted PPI network by using the node2vec technique. Last, we used eXtreme Gradient Boosting (XGBoost) to predict essential proteins by using the topological features of proteins. The extensive results show that our model has better performance than other computational methods. [ABSTRACT FROM AUTHOR]

The structure of the sunflower head can be used to realize broadband applications in optics. However, this 2D structure, with a ring-shaped reciprocal space, only has a normalized Fourier coefficient peak around 0.033, which leads to a relatively low conversion efficiency and may restrict its applications. We tried to maintain its broadband features while with larger Fourier coefficients by structure dimension reduction. We obtained an aperiodic 1D structure from a 2D Vogel sunflower spiral array by a cut-and-projection method. Workable reciprocal vector bands were found with this 1D structure in the vicinity of a pre-set central wavelength λ0 = 1.4 µm, and its peak Fourier coefficients can be 5–7 times as large as the original 2D structure. With this, we investigated broadband quasi-phase matching (QPM) second harmonic generation (SHG) in samples with different reversed ratios D. To illustrate in more detail, three samples were closely examined with D = 0.4, 0.5, and 0.6. Bandwidths of these three samples for first-order QPM SHG are 90, 70, and 30 nm, respectively, with a fundamental wave in the vicinity of λ0 = 1.4 µm. The exact SHG solution of coupled-wave equations was used in the evaluation of conversion efficiencies. Calculations showed broadband high conversion efficiency. [ABSTRACT FROM AUTHOR]

Summary: Multi‐omics approach was adopted to investigate the modulation of bacterial microbiota and metabolome as well as their interactions in whole crop corn ensiling systems by inoculating homofermentative Lactobacillus plantarum or heterofermentative Lactobacillus buchneri. Inoculations of the two different inoculants resulted in substantial differences in microbial community and metabolic composition as well as their dynamics in ensiled corn. Inoculants also altered the correlations of microbiota in different manners, and various keystone species were identified in corn silages with different treatments. Many metabolites with biofunctional activities like bacteriostatic, antioxidant, central nervous system inhibitory and anti‐inflammatory were found in the present silage. A constitutive difference in microbiota dynamics was found for several pathways, which were upregulated by specific taxa in middle stage of fermentation, and widespread associations between metabolites with biofunctions and the species of lactic acid bacteria dominated in silage were observed. Multiple microbial and metabolic structures and dynamics were correlated and affected the fermentation process of the corn ensiling systems. Results of the current study improve our understanding of the complicated biological process underlying silage fermentation and provide a framework to re‐evaluate silages with biofunctions, which may contribute to target‐based regulation methods to produce functional silage for animal production. [ABSTRACT FROM AUTHOR]

With the ever-increasing growth of massive high-dimensional data, deep learning to hash technology has been widely used for approximate nearest neighbor search on large-scale datasets, due to its remarkable efficiency and retrieval performance. In this paper, we propose a novel supervised deep hashing method, named Multi-granularity Feature Learning Hashing (MFLH), to learn compact binary descriptors. Specifically, we design an end-to-end trainable network to jointly learn feature representations and hash codes, in which a global stream and a local stream are responsible for learning feature representations with different granularities, and a hashing stream is devoted to encoding multi-granularity features into binary codes. In the local stream, a Cyclic Shift Mechanism (CSM) strategy is developed to assist mining more discriminative local fine information. In the meantime, an approximate sign activation function, which can be used for continuous optimization, is introduced to reduce quantization error. Furthermore, an improved variant of the triplet loss is presented to enhance the representation of pair-wise similarity for hash codes. Extensive experiments demonstrate that our proposed method significantly outperforms state-of-the-art hashing methods on the benchmark datasets, thereby verifying the effectiveness of our approach. Source code is provided for reproducibility. [ABSTRACT FROM AUTHOR]

Transcription activator-like effectors (TALEs) are virulence factors of Xanthomonas that induce the expression of host susceptibility (S) genes by specifically binding to effector binding elements (EBEs) in their promoter regions. The DNA binding specificity of TALEs is dictated by their tandem repeat regions, which are highly variable between different TALEs. Mutation of the EBEs of S genes is being utilized as a key strategy to generate resistant crops against TALE-dependent pathogens. However, TALE adaptations through rearrangement of their repeat regions is a potential obstacle for successful implementation of this strategy. We investigated the consequences of TALE adaptations in the citrus pathogen Xanthomonas citri subsp. citri (Xcc), in which PthA4 is the TALE required for pathogenicity, whereas CsLOB1 is the corresponding susceptibility gene, on host resistance. Seven TALEs, containing two-to-nine mismatching-repeats to the EBEPthA4 that were unable to induce CsLOB1 expression, were introduced into Xcc pthA4:Tn5 and adaptation was simulated by repeated inoculations into and isolations from sweet orange for a duration of 30 cycles. While initially all strains failed to promote disease, symptoms started to appear between 9–28 passages in four TALEs, which originally harbored two-to-five mismatches. Sequence analysis of adapted TALEs identified deletions and mutations within the TALE repeat regions which enhanced putative affinity to the CsLOB1 promoter. Sequence analyses suggest that TALEs adaptations result from recombinations between repeats of the TALEs. Reintroduction of these adapted TALEs into Xcc pthA4:Tn5 restored the ability to induce the expression of CsLOB1, promote disease symptoms and colonize host plants. TALEs harboring seven-to-nine mismatches were unable to adapt to overcome the incompatible interaction. Our study experimentally documented TALE adaptations to incompatible EBE and provided strategic guidance for generation of disease resistant crops against TALE-dependent pathogens. Author summary: Mutation of the EBEs of susceptibility (S) genes via genome editing and utilization of naturally occurring EBE variants have been used to generate disease resistant plants. However, TALE adaptations may lead to resistance loss, limiting the long-term efficacy of the strategy. We utilized an experimental evolution approach to test TALEs adaptations in the Xanthomonas citri-citrus pathosystem using designer TALEs that cannot recognize the EBE of host targets. We identified adaptive TALE mutations and deletions that occurred during less than 30 cycles of repeated infections, which reconstituted the virulence on the host. Adaptive variants originated from TALEs that harbored a small number of mismatches (≤5) to the EBE, whereas designer TALEs that harbored larger number of mismatches (≥7) to the EBE failed to adapt in the duration of this study. Our study experimentally demonstrates adaptive rearrangements of TALEs during host adaptation and suggests that the potential durability in the resistance of modified crops should be a significant factor to be considered prior to their introduction into the field. [ABSTRACT FROM AUTHOR]

Palmitic acid (PA)-induced myocardial injury is considered a critical contributor to the development of obesity and type 2 diabetes mellitus (T2DM)-related cardiomyopathy. However, the underlying mechanism has not been fully understood. Here, we demonstrated that PA induced the cell death of H9c2 cardiomyoblasts in a dose- and time-dependent manner, while different ferroptosis inhibitors significantly abrogated the cell death of H9c2 cardiomyoblasts and primary neonatal rat cardiomyocytes exposed to PA. Mechanistically, PA decreased the protein expression levels of both heat shock factor 1 (HSF1) and glutathione peroxidase 4 (GPX4) in a dose- and time-dependent manner, which were restored by different ferroptosis inhibitors. Overexpression of HSF1 not only alleviated PA-induced cell death and lipid peroxidation but also improved disturbed iron homeostasis by regulating the transcription of iron metabolism-related genes (e.g., Fth1 , Tfrc , Slc40a1). Additionally, PA-blocked GPX4 protein expression was evidently restored by HSF1 overexpression. Inhibition of endoplasmic reticulum (ER) stress rather than autophagy contributed to HSF1-mediated GPX4 expression. Moreover, GPX4 overexpression protected against PA-induced ferroptosis, whereas knockdown of GPX4 reversed the anti-ferroptotic effect of HSF1. Consistent with the in vitro findings, PA-challenged Hsf 1−/− mice exhibited more serious ferroptosis, increased Slc40a1 and Fth1 mRNA expression, decreased GPX4 and TFRC expression and enhanced ER stress in the heart compared with Hsf 1+/+ mice. Altogether, HSF1 may function as a key defender against PA-induced ferroptosis in cardiomyocytes by maintaining cellular iron homeostasis and GPX4 expression. Unlabelled Image • Ferroptosis is involved in PA-induced cell death in cardiomyocytes. • HSF1 protects cardiomyocytes against PA-induced ferroptosis. • GPX4 is required for the anti-ferroptotic function of HSF1 in PA-induced cardiomyocyte death. • ER stress activation contributes to HSF1-mediated GPX4 expression in PA-challenged cardiomyocytes. [ABSTRACT FROM AUTHOR]

Wang et al. first studied hierarchical quantum information splitting of an arbitrary single-qubit state via the χ state as the entangled channel. There exists a hierarchy among the three receivers as far as the power to recover the teleported state is concerned. But the scheme is considered in ideal environment. In this paper, we reinvestigate the scheme in amplitude-damping and phase-damping noises. The fidelity and average fidelity are adopted to quantify the effect of noise. It is found that they are both dependent on the coefficients of the teleported state and the noise parameter. Moreover, we put forward a novel deterministic scheme to realize hierarchical controlled remote preparation of an arbitrary single-qubit state. Comparing with the previous scheme via the χ state, the sender does not need to perform information dividing due to the subtly constructed measurement basis. We also consider the proposed scheme under noisy environment. [ABSTRACT FROM AUTHOR]

Summary: Climate‐driven phenological change across local spatial gradients leads to leaf shape variation. At higher elevations, leaves of broadleaf species tend to become narrower, but the underlying molecular mechanism is largely unknown.In this study, a series of morphometric analyses and biochemical assays, combined with functional identification in apple, were performed.We show that the decrease in apple leaf width with increasing altitude is controlled by a basic/helix–loop–helix transcription factor (bHLH TF), MdbHLH3. The MdbHLH3‐overexpressing lines have a lower transcript abundance of MdPIN1 encoding an auxin efflux carrier but a higher transcript abundance of MdGH3‐2 encoding a putative auxin amido conjugate synthase, resulting in a lower free auxin concentration; feeding the transgenic leaves with exogenous auxin partially restores leaf width. MdbHLH3 transcriptionally suppresses and activates MdPIN1 and MdGH3‐2, respectively, by specifically binding to their promoters. This alters auxin homeostasis and transport, consequently leading to changes in leaf shape.These findings suggest that the bHLH TF MdbHLH3 directly modulates auxin signaling in controlling leaf shape in response to local spatial gradients in apple. [ABSTRACT FROM AUTHOR]

Although person re-identification (ReID) has been intensively studied over the past few years, the shortage of annotated training data stands as an obstacle for further performance improvement. To address this issue, many data augmentation methods have been successfully applied to person ReID, such as random scaling, flipping and cropping, which mainly operate on a single image, whilst overlooking the relationship between images. Recently, generative adversarial networks (GANs) have been widely used for data augmentation and smoothly migrated to person ReID. However, the cost of training GAN is expensive and the performance improvement is often limited. Moreover, all these methods focus on augmenting samples for existing IDs. This paper proposes a simple yet effective data augmentation strategy based on self-supervised learning to handle these problems, which consists of the offline ID augmentation that can generate new categories and the online instance augmentation. These two components are integrated i nto a unified framework for boosting the ReID performance. Furthermore, a novel Siamese-like network is developed for ReID in conjunction with the proposed data augmentation method. Extensive experiments on three benchmark datasets demonstrate that the proposed approach outperforms the state-of-the-art by a clear margin, which verifies the robustness and the effectiveness of our method. Code will be released at: https://github.com/flychen321/data_aug_reid. [ABSTRACT FROM AUTHOR]

Advanced microanalytical techniques such as high-resolution transmission electron microscopy (HRTEM), atom probe tomography (APT), and synchrotron-based scanning transmission X-ray microscopy (STXM) enable one to characterize the structure and chemical and isotopic compositions of natural materials down towards the atomic scale. Dual focused ion beam-scanning electron microscopy (FIB-SEM) is a powerful tool for site-specific sample preparation and subsequent analysis by TEM, APT, and STXM to the highest energy and spatial resolutions. FIB-SEM also works as a stand-alone technique for three-dimensional (3D) tomography. In this review, we will outline the principles and challenges when using FIB-SEM for the advanced characterization of natural materials in the Earth and Planetary Sciences. More specifically, we aim to highlight the state-of-the-art applications of FIB-SEM using examples including (a) traditional FIB ultrathin sample preparation of small particles in the study of space weathering of lunar soil grains, (b) migration of Pb isotopes in zircons by FIB-based APT, (c) coordinated synchrotron-based STXM characterization of extraterrestrial organic material in carbonaceous chondrite, and finally (d) FIB-based 3D tomography of oil shale pores by slice and view methods. Dual beam FIB-SEM is a powerful analytical platform, the scope of which, for technological development and adaptation, is vast and exciting in the field of Earth and Planetary Sciences. For example, dual beam FIB-SEM will be a vital technique for the characterization of fine-grained asteroid and lunar samples returned to the Earth in the near future. [ABSTRACT FROM AUTHOR]

The diamondback moth (Plutella xylostella, DBM) is an important pest of cruciferous vegetables. The use of chlorantraniliprole has been essential in the management of the DBM. However, in many countries and areas, DBM has become highly resistant to chlorantraniliprole. Three different DBM strains, susceptible (S), chlorantraniliprole-selected (Rc), and field-collected (Rb) resistant strains/populations were studied for the role of phenoloxidase in resistance development to the insecticide. By assaying the activity of phenoloxidase (PO) in the three different DBM strains, the results showed that the PO activity in the Rc strain was increased significantly compared with the S strain. The synergistic effects of quercetin showed that the resistant ratio (RR) of the QRc larvae to chlorantraniliprole was decreased from 423.95 to 316.42-fold compared with the Rc larvae. Further studies demonstrated that the transcriptional and translational expression levels of PxPPO1 (P. xylostella prophenoloxidase-1 gene) and PxPPO2 (P. xylostella prophenoloxidase-2 gene) were increased to varying degrees compared with the S strain, such as the transcriptional expression levels of PxPPO2 were 24.02-fold that of the S strain. The responses of phenoloxidase were significantly different in chlorantraniliprole-resistant DBM. [ABSTRACT FROM AUTHOR]

Recent work shows that incorporating tag information to recommender systems is promising for improving the recommendation accuracy in social systems. However, existing approaches suffer from less reasonable assignment of tag weights when constructing the user profiles and item characteristics in real-world scenarios, resulting in decreased accuracy in making recommendations. The above issue is specifically summarized into two aspects: 1) the weight of a target item is mainly determined by number of one certain type of tags, and 2) users place equal focus on the same tag for different items. To tackle these problems, we propose a novel model named TNAM, a T ag-aware N eural A ttention M odel, which accurately captures users' special attention to tags of items. In the proposed model, we design a tag-based neural attention network by extracting potential tag information to overcome the difficulty of assigning tag weights for personalized users. We combine user-item interactions with tag information to map sparse data to dense vectors in higher-order space. In this way, TNAM acquires more interrelations between users and items to make recommendations more accurate. Extensive experiments of our model on three publicly implicit feedback datasets reveal significant improvements on the metrics of HR and NDCG in Top-N recommendation tasks over several state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

The regulatory mechanism of lincomycin biosynthesis remains largely unknown, although lincomycin and its derivatives have been of great application in pharmaceutical industry. As a global regulator, BldD is widespread in Streptomyces , and functions as an on-off switch to regulate the transition from morphological differentiation to secondary metabolism, inspiring us to explore scarcely regulatory realm of lincomycin biosynthesis. In this work, deletion of bldD gene (SLCG_1664) in Streptomyces lincolnensis blocked the sporulation and nearly abolished lincomycin production, while the morphological phenotype and lincomycin production were restored when introducing a functional bldD gene into the Δ bldD mutant. S. lincolnensis BldD (BldD SL) was validated to bind to upstream regions of lincomycin biosynthetic structural genes lmbA , lmbC-lmbD , lmbE , lmbV-lmbW , resistant genes lmrA , lmrB , lmrC , and regulatory gene lmbU. Disruption of bldD significantly decreased the transcription of genes in lincomycin biosynthetic cluster, thus resulting in the sharply loss of lincomycin production. These findings indicate that BldD SL , similar to Saccharopolyspora erythraea BldD (BldD SE), directly regulates the biosynthesis of lincomycin. What's more, we discovered that BldD SE could bind to upstream regions of lmbA , lmbV - lmbW , lmrA and lmrC. Corresponding to this, S. lincolnensis BldD can bind to upstream region of eryAI - eryBIV , revealing an interactional regulation of the two BldDs. In summary, our data indicated that the developmental regulator BldD played a vital role in directly regulating the biosynthesis of lincomycin, and expanded the knowledge on lincomycin biosynthetic regulation in S. lincolnensis. • BldD SL affects morphological differentiation and cell growth of S. lincolnensis. • BldD SL positively regulates lincomycin production. • BldD SL directly regulates lincomycin biosynthesis by binding to most gene promoters in lincomycin biosynthesis cluster. • BldD SL presents functional inter-regulation with BldD SE from S. erythraea. [ABSTRACT FROM AUTHOR]

Methods have been developed to allow quantitative connectivity of the whole fixed mouse brain by means of magnetic resonance imaging (MRI). We have translated what we have learned in clinical imaging to the very special domain of the mouse brain. Diffusion tensor imaging (DTI) of perfusion fixed specimens can now be performed with spatial resolution of 45 μm3, that is, voxels that are 21,000 times smaller than the human connectome protocol. Specimen preparation has been optimized through an active staining protocol using a Gd chelate. Compressed sensing has been integrated into high performance reconstruction and post processing pipelines allowing acquisition of a whole mouse brain connectome in <12 hr. The methods have been validated against retroviral tracer studies. False positive tracts, which are especially problematic in clinical studies, have been reduced substantially to ~28%. The methods have been streamlined to provide high‐fidelity, whole mouse brain connectomes as a routine study. The data package provides holistic insight into the mouse brain with anatomic definition at the meso‐scale, quantitative volumes of subfields, scalar DTI metrics, and quantitative tractography. [ABSTRACT FROM AUTHOR]

Zero-shot sketch-based image retrieval (ZS-SBIR) has attracted increasing attention in computer vision, with the aim of searching the natural images that match a given sketch under the setting of zero-shot learning. In this paper, we propose a novel ZS-SBIR method based on the specifically developed domain-aware dual attention (DADA) module and similarity loss, which utilizes prior knowledge more fully than previous work. The DADA module emphasizes the importance of different channels and spaces according to the prior knowledge of whether the input is a sketch or a natural image. To preserve more prior knowledge from the models pre-trained on ImageNet, a similarity loss function is designed to supervise inter-class similarity. Furthermore, the center loss is introduced into our model, which can bridge the representation gap between the sketch domain and the natural image domain. We perform experiments on the TU-Berlin extended dataset and the Sketchy extended dataset, and the corresponding results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Hashing has received broad attention in large-scale image retrieval due to its appealing efficiency in computation and storage. Particularly, with the drawn of deep learning, much efforts have been directed towards using deep neural networks to learn feature representations and hash codes simultaneously, and the developed deep hashing methods have shown superior performance over conventional hashing methods. In this paper, we propose Deep Attention Sampling Hashing (DASH), a novel deep hashing method that yields high-quality hash codes to enable efficient image retrieval. Specifically, we employ two sub-networks in DASH, i.e., a master branch and a part branch, to capture global structure features and discriminative feature representations, respectively. Furthermore, we develop an Attention Sampler Module (ASM), which consists of an Object Region Extraction (ORE) block and an Informative Patch Generation (IPG) block, to yield richer informative image patches. The ORE block provides a well-designed multi-scale attentional fusion mechanism to highlight and extract the significant regions of images, and the IPG block employs a direction-specific shift mechanism to generate desired image patches with discriminative details. Both blocks could be seamlessly integrated into various convolutional neural network (CNN) architectures. Subsequently, we conduct knowledge distillation optimization to transfer the details learned by the part branch into the master branch to guide hash code learning. In addition, we design a Weibull quantization loss to minimize the information loss caused by binary quantization. The experimental results on three benchmark datasets demonstrate the effectiveness of the proposed DASH with respect to different evaluation metrics. [ABSTRACT FROM AUTHOR]

• The shorter access time was more explained by the lower threshold. • The heart rate predicted the access time and threshold at high altitudes. • The cardiac deceleration-acceleration pattern was slightly various at high-altitudes. Many studies have indicated a strong relationship between cardiac and brain activities, both of which are sensitive to high-altitude exposure. This study combined a consciousness access task and electrocardiograms (ECG) to uncover conscious awareness in response to high-altitude exposure and its relation to cardiac activity. When compared with the low-altitude groups, the behavioral results showed that the high-altitude participants shortened the time of access to visual awareness of grating orientation, which was accompanied by a faster heart rate, excluding the influence of pre-stimulus heart rate, extent of cardiac deceleration after presenting the stimulus, and task difficulty. Although there were post-stimulation cardiac deceleration and post-response acceleration at both high and low altitudes, a slight increase in heart rate after stimulation at high altitudes may indicate that participants at high altitudes could quickly readjust their attention to the target stimulus. More importantly, the drift diffusion model (DDM) was used to fit the access time distribution of all participants. These results suggest that shorter time at high altitudes might be due to the lower threshold, suggesting that less evidence in high-altitude participants was required to access visual consciousness. The participants' heart rates also negatively predicted the threshold through a hierarchical drift diffusion modeling (HDDM) regression. These findings imply that individuals with higher heart rates at high altitudes have a greater cognitive burden. [ABSTRACT FROM AUTHOR]

Clonorchis sinensis (C. sinensis) is a fish-borne trematode that inhabits the bile duct of mammals including humans, cats, dogs, rats, and so on. In the complex life cycle of C. sinensis , the worm develops successively in two intermediate hosts in fresh water and one definitive host. What's more, it undergoes eight developmental stages with a distinct morphology. Clonorchiasis, caused by C. sinensis infection, is an important food-borne parasitic disease and one of the most common zoonoses. C. sinensis infection could result in hyperplasia of the bile duct epithelium, obstructive jaundice, gall-stones, cholecystitis and cholangitis, even liver cirrhosis and cholangiocarcinoma. Thus, clonorchiasis is a serious public health problem in endemic areas. Integrated strategies should be adopted in the prevention and control of clonorchiasis due to the epidemiological characteristics. The recent advances in high-throughput technologies have made available the profiling of multiple layers of a biological system, genomics, transcriptomics, proteomics, and metabolomics. These data can help us to get more information about the development, physiology, metabolism, and reproduction of the parasite as well as pathogenesis and parasite-host interactions in clonorchiasis. In the present study, we summarized recent progresses in omics studies on C. sinensis providing insights into the studies and future directions on treating and preventing C. sinensis associated diseases. • Slight differences in the genome of Clonorchis sinensis from different regions. • Differential expression of genes in various stages and tissues of Clonorchis sinensis is required for survival. • The tegument and excretory-secretory products of Clonorchis sinensis play a crucial part in the interaction with the host. • Some metabolites of the host can be used as diagnostic indicators of Clonorchis sinensis infection. [ABSTRACT FROM AUTHOR]

• Conjugate heat transfer of a film-cooled leading edge model is investigated. • Two jet impingement designs: the normal jet and the tangential jet are studied. • The estimated Biot number in this study is about 1.3 to 1.7. This paper investigates the overall effectiveness of film-cooled leading edge model with normal and tangential impinging jets. The leading edge has three rows of cylindrical film cooling holes, located at the stagnation line (0°) and ± 40° measured from the stagnation line. Film cooling holes are at an inclined angle of 25° relatives to the surface. The normal jet has one row of normal jet impinging holes and the tangential jet has two rows of tangential jet impinging holes. Mainstream Reynolds number based on the leading edge cylinder external diameter is about 100,000, and the mainstream turbulence intensity is about 7%. Three blowing ratios of 0.77, 1.54, and 2.31 are considered. Pressure sensitive paint technique is applied to measure the adiabatic effectiveness with the density ratio of 0.97. Liquid crystal technique is used to obtain the overall effectiveness with the density ratio of 0.94. Numerical simulations using realizable k-ɛ (RKE) turbulence model with enhanced wall treatment were applied to calculate the adiabatic effectiveness and overall effectiveness. Compared with experiments, numerical simulations overpredict overall effectiveness about 20% to 30% between the 0° row and the 40° row, and the difference between simulations and experiments is about 10% to 20% after the 40° row. The results provide baseline information for turbine blade leading edge film cooling design and heat transfer analysis. [ABSTRACT FROM AUTHOR]

• Internal heat transfer of film-cooled leading edge is investigated. • Two jet impinging designs: the normal jet and the tangential jet are studied. • Mainstream flow influence decreases with increasing jet Reynolds number. • CFD simulations show a good agreement with experimental data. This paper investigates internal heat transfer of film-cooled leading edge with mainstream flow. The semi-cylindrical leading edge model receives coolant through impinging jets located at the neighborhood rectangular channel. The leading edge has three rows of cylindrical film cooling holes: row 1 located along the stagnation line (0°) and rows 2 and 3 at ±40° measured from the stagnation line. All film cooling holes are at an inclined angle of 25° relatives to the surface. There are two impinging jet designs in this study: the normal jet and the tangential jet. The normal jet has one row of normal jet impinging holes. After jets impinging on the inner wall of the semi-cylinder stagnation line, coolant spreads out through film cooling holes. The tangential jet has two rows of tangential jet impinging holes. Swirl flow is generated when jets enter the semi-cylinder from two sides of the semi-cylinder. Mainstream Reynolds number is about 100,000 based on the outside diameter of the leading edge cylinder, and the mainstream turbulence intensity is about 7%. Leading edge detailed internal heat transfer distributions are measured by using transient liquid crystal method. Three different coolant jet Reynolds numbers are tested (Re j = 5000, 10,000 and 15,000), corresponding to averaged blowing ratios about 0.77, 1.54, and 2.31. The experimental results provide useful information for the jet impingement cooling design, especially the leading edge region is under the conditions of mainstream flow and external film extraction. CFD simulations are performed to present the velocity field and compare the heat transfer results with experimental data. [ABSTRACT FROM AUTHOR]

Summary: Recombination breaks up ancestral linkage disequilibrium, creates combinations of alleles, affects the efficiency of natural selection, and plays a major role in crop domestication and improvement. However, there is little knowledge regarding the variation in the population‐scaled recombination rate in cotton. We constructed recombination maps and characterized the difference in the genomic landscape of the population‐scaled recombination rate between Gossypium hirsutum and G. arboreum and sub‐genomes based on the 381 sequenced G. hirsutum and 215 G. arboreum accessions. Comparative genomics identified large structural variations and syntenic genes in the recombination regions, suggesting that recombination was related to structural variation and occurred preferentially in the distal chromosomal regions. Correlation analysis indicated that recombination was only slightly affected by geographical distribution and breeding period. A genome‐wide association study (GWAS) was performed with 15 agronomic traits using 267 cotton accessions and identified 163 quantitative trait loci (QTL) and an important candidate gene (Ghir_COL2) for early maturity traits. Comparative analysis of recombination and a GWAS revealed that the QTL of fibre quality traits tended to be more common in high‐recombination regions than were those of yield and early maturity traits. These results provide insights into the population‐scaled recombination landscape, suggesting that recombination contributed to the domestication and improvement of cotton, which provides a useful reference for studying recombination in other species. Significance Statement: There is little knowledge regarding the population‐scaled recombination rate variation in cotton. Genome‐wide fine‐scaled recombination maps were constructed and characterized the population‐scaled recombination rate in Gossypium hirsutum and G. arboreum in the present study; and GWAS revealed that agronomic trait QTL tended to be co‐located in high‐recombination regions, which revealed that recombination contributed to the domestication and genetic improvement of cotton. [ABSTRACT FROM AUTHOR]

Accurate and robust source location is fundamental in seismology. Previously, we proposed a new full waveform location method using waves scattered by topography near the source, and we demonstrated its potential in obtaining accurate source location using synthetic data. In the work presented here, we validate this method with observed seismic data from the 1993 Non‐Proliferation Experiment, a chemical explosion with a precisely known location in a region with moderate topography at the Nevada Test Site. We select the first arrivals (Pn/Pg) and their immediate codas to determine the source location and compare our solution with the known location. We use a collocated‐grid finite‐difference method to calculate the strain Green's tensor in a grid‐search volume containing the source and obtain three‐component synthetic waveforms at 12 broadband seismic stations at regional distances using source‐receiver reciprocity. We assess the solution using a least squares misfit between the observed and synthetic waveforms. When scattered coda waves are incorporated, the best solution is within a few hundreds of meters of the exact source location, and the estimated uncertainty of the solution is reduced compared to the waveform‐based solution using only the P waves. The solution is robust to the choice of the frequency content and to the addition of random velocity heterogeneity. We conclude that the full waveform source location method is effective for real seismic data, though more validation tests like this one are needed to further understand its efficacy for source‐station geometry, roughness of topography, signal quality, and other factors. Key Points: We explore the power and limitation of a new full‐waveform location method incorporating scattering by topography with real seismic dataThis location method uses scattering waves to achieve accurate absolute source locations with robust determinations of the source depthThe solution is robust with overlapping finite frequency bands and unmodeled random velocity heterogeneities [ABSTRACT FROM AUTHOR]

Genome sequencing is commonly used in research laboratories right now thanks to the rise of high-throughput sequencing with higher speed and output-to-cost ratios. Here, we summarized the application of genomics in different aspects of plant bacterial pathosystems. Genomics has been used in studying the mechanisms of plant-bacteria interactions, and host specificity. It also helps with taxonomy, study of non-cultured bacteria, identification of causal agent, single cell sequencing, population genetics, and meta-transcriptomic. Overall, genomics has significantly improved our understanding of plant-microbe interaction. [ABSTRACT FROM AUTHOR]

Advanced biophysical models like neurite orientation dispersion and density imaging (NODDI) have been developed to estimate the microstructural complexity of voxels enriched in dendrites and axons for both in vivo and ex vivo studies. NODDI metrics derived from high spatial and angular resolution diffusion MRI using the fixed mouse brain as a reference template have not yet been reported due in part to the extremely long scan time required. In this study, we modified the three-dimensional diffusion-weighted spin-echo pulse sequence for multi-shell and undersampling acquisition to reduce the scan time. This allowed us to acquire several exhaustive datasets that would otherwise not be attainable. NODDI metrics were derived from a complex 8-shell diffusion (1000–8000 s/mm2) dataset with 384 diffusion gradient-encoding directions at 50 µm isotropic resolution. These provided a foundation for exploration of tradeoffs among acquisition parameters. A three-shell acquisition strategy covering low, medium, and high b values with at least angular resolution of 64 is essential for ex vivo NODDI experiments. The good agreement between neurite density index (NDI) and the orientation dispersion index (ODI) with the subsequent histochemical analysis of myelin and neuronal density highlights that NODDI could provide new insight into the microstructure of the brain. Furthermore, we found that NDI is sensitive to microstructural variations in the corpus callosum using a well-established demyelination cuprizone model. The study lays the ground work for developing protocols for routine use of high-resolution NODDI method in characterizing brain microstructure in mouse models. [ABSTRACT FROM AUTHOR]