Structural Features Research Articles

Functionalized graphene oxide-modified sulfonated poly (2,6-dimethyl-1,4-phenylene oxide) based thermal-resistance anti-fouling bi-functional cation exchange membrane for electrodialytic desalination

We report a sustainable strategy for fabricating thermal-resistance anti-fouling cation exchange membrane (CEM), using sulfonated poly (2,6-dimethyl-1,4-phenylene oxide) (SPPO), and phosphorylated graphene oxide (FGO). The GO was phosphorylated, and different CEMs (3.0–7.0 % weight ratio of FGO) were prepared to investigate their electrodialysis (ED) performance. Structural features of SPPO-FGO composite CEMs such as ̴ 21.51 % degree of sulphonation (SPPO), bi-functional (-SO3H, and -PO3H2) nature, and balanced hydrophobic-hydrophilic segments, etc., were attributed for thermal-resistance and anti-fouling membrane nature of the membrane. The presence of FGO in the SPPO polymer matrix significantly improved mechanical, thermal, oxidative stabilities, ionic conductivity (κm), and counter-ion transport number (tm+). Suitable optimized SPPO-FGO/7 % (7.0 % of FGO) showed excellent physicochemical properties (14.1 % water uptake, 3.2 % swelling ratio, and 1.76 m eq./g ion exchange capacity), along with 10.92 × 10−2 S cm−1 conductivity, and 0.95 counter-ion transport number at 30 °C. Improved i-V curves and ED performance at 60 °C, showed relatively low energy consumption (0.72 k W hr/kg of NaCl removed), and high current efficiency (99.0 %) for SPPO-FGO/7 % CEM revealed, its potential candidature for electrodialytic water desalination. Further, CEM also avoids any significant deterioration in ED performance due to the presence of cationic, anionic and zwitterionic foulants.

A Novel Tri-Magnet Levitating Bistable Electromagnetic Energy Harvester with Variable Potential Wells to Promote Snap-Through Behavior

To achieve broadband energy harvesting under weak excitations, this paper comprehensively investigates a novel tri-magnet levitating bistable electromagnetic energy harvester with variable potential wells (BEEH-VP). The bistable nonlinear mechanism is realized using the single-sided bipolarity of the ring magnets. Auxiliary springs are integrated into the ring magnets to dynamically self-adjust the spacing of the ring magnets, causing variable potential wells. The analytical model of BEEH-VP is derived and verified experimentally. The performance of the proposed BEEH-VP is compared with that of the bistable electromagnetic energy harvester with featuring fixed potential wells (BEEH-FP). The comparative results clearly demonstrate that the BEEH-VP exhibits superior capabilities in terms of energy output under weak excitation and possesses a broader frequency bandwidth. Bifurcation analysis for the excitation conditions reveals that the proposed structure features complex dynamic behaviors, such as intra-well, chaotic, harmonic inter-well and subharmonic inter-well vibrations. In comparison to BEEH-FP, BEEH-VP requires lower acceleration to perform the snap-through and has a larger vibration amplitude, facilitating improved output performance.

Volatile acetic acid selective adsorption by biomass-derived activated carbon with humidity-resistance: Tunable implanting and activation approach of activator

The selective adsorption and capture of polar organic acid gas by activated carbon (AC) absorbent could solve the challenge of irritant volatile organic compound discharge. However, volatile acid gas selective adsorption by traditional activated carbon with humidity resistance remains challenged. In this study, we developed an innovative one-step chemical synthesis method using discarded banana peels as a carbon source to create porous carbon materials. The selection of activators including sodamide and potassium hydroxide along with tunable implanting means of activator under different activated temperatures were modulated to optimize the fabrication of activated carbon. The results reveal that the low dosage of NaNH2 activator (NaNH2/carbon precursor = 1) implanted into carbon precursor through one-step ball-milling could contribute an excellent structural properties, and higher activated temperature makes the mesoporous behavior of activated carbon more obvious. Based on various optimization conditions, the optimal sample, BAC900, displays remarkable structural features (SBET = 2302 m2/g, Vtotal = 1.968 cm3 g−1, V>2nm = 1.474 cm3 g−1), achieving exceptional acetic acid adsorption efficiency (24.105 mmol g−1). Comparative analysis under various synthetic conditions revealed a close linear relationship between the structural characteristics (total pore volume) of adsorbent and acetic acid adsorption efficiency. We further explored the role of mesopores in facilitating acetic acid adsorption at relatively high pressures and their contribution to enhancing the hydrophobicity of the adsorbent. Additionally, we employed the Differential Isothermal Heat (DIH) technique to predict adsorption selectivity at varying relative humidity, revealing the higher adsorption heat (57 kJ mol−1) of acetic acid compared to water vapor (36 kJ mol−1). This comprehensive study emphasizes the outstanding adsorption selectivity of adsorbent for acetic acid, even in humid environments. Furthermore, the low adsorption heat of the BAC900 indicates good reversibility and reusability, paving the way for the practical application of biomass-derived functional biochar adsorbents in the environmental management of threatening acid VOCs pollutants.

Plant cathepsin B, a versatile protease.

Plant proteases are essential enzymes that play key roles during crucial phases of plant life. Some proteases are mainly involved in general protein turnover and recycle amino acids for protein synthesis. Other proteases are involved in cell signalling, cleave specific substrates and are key players during important genetically controlled molecular processes. Cathepsin B is a cysteine protease that can do both because of its exopeptidase and endopeptidase activities. Animal cathepsin B has been investigated for many years, and much is known about its mode of action and substrate preferences, but much remains to be discovered about this potent protease in plants. Cathepsin B is involved in plant development, germination, senescence, microspore embryogenesis, pathogen defence and responses to abiotic stress, including programmed cell death. This review discusses the structural features, the activity of the enzyme and the differences between the plant and animal forms. We discuss its maturation and subcellular localisation and provide a detailed overview of the involvement of cathepsin B in important plant life processes. A greater understanding of the cell signalling processes involving cathepsin B is needed for applied discoveries in plant biotechnology.

Cognitive, Structural, and Semantic Features of Professional Neologisms in Modern English

This article describes 180 modern English neologisms with a professional component. Their structural and semantic features reveal how native speakers perceive and conceptualize new words through spiritual and practical activities, thus adjusting their worldview to the changing reality. The research involved the methods of definitional analysis, word formation, semantic assay, and cognitive-discursive interpretation, as well as various standard linguistic and statistical methods. The material was classified according to the type of professional activity. These lexical and semantic groups were united by intralinguistic links based on interrelated and interdependent connotative shades of meaning. Many neologisms demonstrated a metaphorical basis, which served as a tool for creating expressive images. All the neological units were emotive and evaluative. The emotive content conveyed the thoughts and feelings of the speaker, while the evaluative content was associated with the pragmatic function and contained information about the speaker’s attitude to the denotation. Most professional neologisms were gender-neutral. The universal nature of the images behind the neologisms probably testifies to the current mental changes in a society that values gender equality. Interdiscursivity appeared to permeate all lexical and semantic fields of the English neological space. The heterogeneity reflected the complex activity the speaker performs in an attempt to comprehend a complex and multifaceted environment, which, in turn, gives the neological units an anthropocentric character. The relevance of the research is determined by the rapid development of various social spheres, which inevitably affects the modern communication and the linguistic worldview in general.

Relationships between the Photodegradation Reaction Rate and Structural Properties of Polymer Systems.

The development of reusable polymeric materials inspires an attempt to combine renewable biomass with upcycling to form a biorenewable closed system. It has been reported that 2,5-furandicarboxylic acid (FDCA) can be recovered for recycling when incorporated as monomers into photodegradable polymeric systems. Here, we develop a procedure to better understand the photodegradation reactions combining density functional theory (DFT) based time-dependent excited-state molecular dynamics (TDESMD) studies with machine learning-based quantitative structure-activity relationships (QSAR) methodology. This procedure allows for the unveiling of hidden structural features between active orbitals that affect the rate of photodegradation and is coined InfoTDESMD. Findings show that electrotopological features are influential factors affecting the rate of photodegradation in differing environments. Additionally, statistical validations and knowledge-based analysis of descriptors are conducted to further understand the structural features' influence on the rate of photodegradation of polymeric materials.

3D Genome Reconstruction from Partially Phased Hi-C Data

The 3-dimensional (3D) structure of the genome is of significant importance for many cellular processes. In this paper, we study the problem of reconstructing the 3D structure of chromosomes from Hi-C data of diploid organisms, which poses additional challenges compared to the better-studied haploid setting. With the help of techniques from algebraic geometry, we prove that a small amount of phased data is sufficient to ensure finite identifiability, both for noiseless and noisy data. In the light of these results, we propose a new 3D reconstruction method based on semidefinite programming, paired with numerical algebraic geometry and local optimization. The performance of this method is tested on several simulated datasets under different noise levels and with different amounts of phased data. We also apply it to a real dataset from mouse X chromosomes, and we are then able to recover previously known structural features.

Solvothermal synthesis of bismuth-based halide perovskites: Investigating the influence of alcohol solvents on photocatalytic performance

Our study explores the effect of different solvents on the synthesis of bismuth-based halide perovskite (BHP) crystals with distinct morphologies. BHP crystals were successfully synthesized using various alcohol solvents, including ethanol (EtOH), butanol (BuOH), ethylene glycol (EG), glycerol (GL), and without the use of alcohol solvents. The choice of solvent acted a crucial role in shaping the nucleation and growth of BHP crystals, as it affected key solvent characteristics, including dielectric constant, ion-coordination, and atomic chain length. The resulting BHP crystals exhibited varying geometrical and structural features, which, in turn, significantly impacted their photophysical properties and photocatalytic activity for the degradation of organic pollutants under visible light irradiation. The introduction of EtOH into the synthesis process led to larger crystallite sizes and an increased adsorption of oxygen molecules on BHP, thereby enhancing the separation of photo-excited electrons and holes. Consequently, the photodegradation efficiency of rhodamine B achieved an impressive 99.6% after 30 min of irradiation. The degradation rate of tetracycline hydrochloride over BHP photocalysts followed this order: mesoporous structure with strong agglomeration of particles (EtOH) > irregular agglomerates composed of spherical particles (BuOH) > irregular clusters of sheets (EG) > thick plates (GL) > flower-like agglomerates (without the use of an alcohol solvent). Our evaluation considered changes in morphological characteristics, surface properties, and photon absorption capacities of the BHP crystalline structures. This study provides valuable insights into the role of various alcohol solvents in tailoring the structure and improving the photocatalytic performance of BHP photocatalyst synthesized through the solvothermal route.

LaZn1−xBi2 as a Candidate for Dirac Nodal-Line Intermetallic Systems

The complex theoretical analysis of the density of states, band structures, and Fermi surfaces, based on predictions of the density functional theory methods, unveils the unique electronic properties of the LaZn1−xBi2 system. In this paper, the Zn vacancies (for x=0.5) were modeled using a modified unit cell of lower symmetry than that for a fully stoichiometric one (for x=0). The existence of several Dirac-like features in the electronic band structures was found. Some of them were found to be intimately associated with the nonsymmorphic symmetry of the system, and these were investigated in detail. The calculated Fermi surface shapes, as well as the Fermi velocity values (up to ∼1.2 ×106 m/s), are in good agreement with other analogous square-net Dirac semimetals. The combination of charge-carrier uncompensation, relatively small band splitting, and the tolerance factor for square-net semimetals t≤0.95 for LaZn0.5Bi2, constitutes a very promising indicator of the topological features of this system, warranting further experimental studies.

Message from the Editor-in-Chief

Welcome to the first issue for 2024! The IJHE provides an important platform for the development of theory, the addressing of policy questions, and the dissemination of innovative practice in the field of tertiary education, specifically widening participation and lifelong learning. This first issue features six research articles from the USA, China, Thailand, Greece and Egypt. The articles cover a range of themes including distance learning tools and strategies, features of management structures, and effective teaching and learning processes.

Structural Characterization and Functional Analysis of Mevalonate Kinase from Tribolium castaneum (Red Flour Beetle).

Mevalonate kinase (MevK) is an important enzyme in the mevalonate pathway that catalyzes the phosphorylation of mevalonate into phosphomevalonate and is involved in juvenile hormone biosynthesis. Herein, we present a structure model of MevK from the red flour beetle Tribolium castaneum (TcMevK), which adopts a compact α/β conformation that can be divided into two parts: an N-terminal domain and a C-terminal domain. A narrow, deep cavity accommodating the substrate and cofactor was observed at the junction between the two domains of TcMevK. Computational simulation combined with site-directed mutagenesis and biochemical analyses allowed us to define the binding mode of TcMevK to cofactors and substrates. Moreover, TcMevK showed optimal enzyme activity at pH 8.0 and an optimal temperature of 40 °C for mevalonate as the substrate. The expression profiles and RNA interference of TcMevK indicated its critical role in controlling juvenile hormone biosynthesis, as well as its participation in the production of other terpenoids in T. castaneum. These findings improve our understanding of the structural and biochemical features of insect Mevk and provide a structural basis for the design of MevK inhibitors.

Gadolinium: A DFT exploration of structural, electronic, and magnetic features in bulk and film configurations for enhanced magnetocaloric understanding

Gadolinium stands as the favored choice among magnetic refrigerant materials for numerous active magnetic regenerator (AMR) prototypes due to its remarkable ability to exhibit a substantial change in magnetic entropy. This unique characteristic arises from its status as one of the elemental ferromagnets with a high Curie temperature, closely aligning with room temperature conditions, and undergoing a second-order magnetic phase transition. In this comprehensive study, we employ density functional theory (DFT) calculations to explore the structural, electronic, and magnetic properties of both Gadolinium bulk and film configurations. Our primary objective is to gain a deeper understanding of the intricate physics underlying the intriguing magnetocaloric features observed in Gadolinium. This investigation provides valuable insights into the potential applications and the broader implications of Gadolinium in the realm of magnetic refrigeration technology.

Down-conversion luminescence nanocomposites based on nitrogen-doped carbon quantum dots@bioplastic for applications in optical displays, LEDs and UVC tubes

Carbon quantum dots (CQDs)-based composites as luminous down-conversion materials are becoming more popular due to several advantages such as steady fluorescence, ease of functionalization, tailoring of emission in the visible range, and so on. We report an inexpensive and environmentally sustainable synthesis of fluorescent nitrogen doped-CQDs produced from Cissus quadrangularis, a low-cost plant precursor with therapeutic value. The morphological, structural, and physicochemical features of the material were carefully investigated. Under UV stimulation (365 nm), almost spherical shaped N-CQDs with an average diameter of 5.1 nm were discovered to generate yellow-green fluorescence, have excellent photostability, and strong water solubility, with a quantum yield of up to 5 %. Furthermore, as a solid-phase dispersion matrix for CQDs, ecologically friendly and biodegradable bioplastic is appealing. The down-conversion of solid-state fluorescence of LEDs and UVC tubes was demonstrated by creating a nanocomposite by inserting N-CQDs into the solid matrix of a wheat starch-based bioplastic. Furthermore, employing constructed quantum dot-based optical displays, down-converted LEDs, and UVC tubes, the impacts of varied CQD concentrations and pH sensitivity were examined.

Kinome-Wide Virtual Screening by Multi-Task Deep Learning.

Deep learning is a machine learning technique to model high-level abstractions in data by utilizing a graph composed of multiple processing layers that experience various linear and non-linear transformations. This technique has been shown to perform well for applications in drug discovery, utilizing structural features of small molecules to predict activity. Here, we report a large-scale study to predict the activity of small molecules across the human kinome-a major family of drug targets, particularly in anti-cancer agents. While small-molecule kinase inhibitors exhibit impressive clinical efficacy in several different diseases, resistance often arises through adaptive kinome reprogramming or subpopulation diversity. Polypharmacology and combination therapies offer potential therapeutic strategies for patients with resistant diseases. Their development would benefit from a more comprehensive and dense knowledge of small-molecule inhibition across the human kinome. Leveraging over 650,000 bioactivity annotations for more than 300,000 small molecules, we evaluated multiple machine learning methods to predict the small-molecule inhibition of 342 kinases across the human kinome. Our results demonstrated that multi-task deep neural networks outperformed classical single-task methods, offering the potential for conducting large-scale virtual screening, predicting activity profiles, and bridging the gaps in the available data.

A Perinatal Social Nutrition Approach to Improve Breastfeeding in a Culturally Diverse Group of Low-Income Women.

Alima, Perinatal Social Nutrition Centre, is an established community organization that adopts a perinatal social nutrition approach to provide multidimensional support to women living in vulnerable conditions, particularly those with a precarious migratory status. This study aims to (a) determine which maternal characteristics, pregnancy-related variables, and structural features of the Alima intervention are associated with breastfeeding; and (b) examine whether the association between attending breastfeeding workshops and breastfeeding characteristics differ according to maternal factors. The Alima digital database was used to analyze data from women who received the perinatal intervention between 2013 and 2020. Infant feeding data was retrieved at two weeks postpartum (T0, n=2925), two months postpartum (T2, n=1475), and four months postpartum (T4, n=890). Logistic regressions were used to estimate the odds of overall and exclusive breastfeeding depending on sociodemographic characteristics, pregnancy-related variables, and features of the intervention. The prevalence of overall and exclusive breastfeeding was, respectively, 96.1% and 60.7% at T0; 93.0% and 58.5% at T2; 83.0% and 48.4% at T4. Higher education, previous breastfeeding experience, and recent immigration were associated with a higher likelihood of breastfeeding at each time point. Breastfeeding workshop attendance was associated with a greater likelihood of overall and exclusive breastfeeding at T2 and T4, with a stronger effect among women aged 35 or less, those with lower education, and those with excessive gestational weight gain. In conclusion, the Alima intervention is associated with positive breastfeeding outcomes, especially among vulnerable women living with precarious migratory status in Canada.

3D Aligned Nanofiber Scaffold Fabrication with Trench-Guided Electrospinning for Cardiac Tissue Engineering.

Constructing three-dimensional (3D) aligned nanofiber scaffolds is significant for the development of cardiac tissue engineering, which is promising in the field of drug discovery and disease mechanism study. However, the current nanofiber scaffold preparation strategy, which mainly includes manual assembly and hybrid 3D printing, faces the challenge of integrated fabrication of morphology-controllable nanofibers due to its cross-scale structural feature. In this research, a trench-guided electrospinning (ES) strategy was proposed to directly fabricate 3D aligned nanofiber scaffolds with alternative ES and a direct ink writing (DIW) process. The electric field effect of DIW poly(dimethylsiloxane) (PDMS) side walls on guiding whipping ES nanofibers was investigated to construct trench design rules. It was found that the width/height ratio of trenches greatly affected the nanofiber alignment, and the trench width/height ratio of 1.5 provided the nanofiber alignment degree over 60%. As a proof of principle, 3D nanofiber scaffolds with controllable porosity (60-80%) and alignment (30-60%) were fabricated. The effect of the scaffolds was verified by culturing human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), which resulted in the uniform 3D distribution of aligned hiPSC-CMs with ∼1000 μm thickness. Therefore, this printing strategy shows great potential for the efficient engineered tissue construction.

Corporate interest groups and their implications for global food governance: mapping and analysing the global corporate influence network of the transnational ultra-processed food industry.

A major challenge to transforming food systems to promote human health and sustainable development is the global rise in the manufacture and consumption of ultra-processed foods (UPFs). A key driver of this dietary transition is the globalization of UPF corporations, and their organized corporate political activity (CPA) intended to counter opposition and block government regulation. UPF industry CPA and the corporate interest groups who lobby on their behalf have been well described at the national level, however, at the global level, this network has not been systematically characterized. This study aims to map, analyse, and describe this network, and discuss the implications for global food policy action on UPFs, global food governance (GFG), and food systems transformation. We conducted a network analysis of the declared interest group memberships of the world's leading UPF corporations, extracted from web sources, company reports, and relevant academic and grey literature. Data on the characteristics of these interest groups were further extracted for analysis, including year founded, level, type, and headquarter location. We identified 268 interest groups affiliated with the UPF industry. The UPF manufacturers Nestlé (n = 171), The Coca-Cola Company (n = 147), Unilever (n = 142), PepsiCo (n = 138), and Danone (n = 113) had the greatest number of memberships, indicating strong centrality in coordinating the network. We found that this network operates at all levels, yet key actors now predominantly coordinate globally through multistakeholder channels in GFG. The most common interest group types were sustainability/corporate social responsibility/multistakeholder initiatives, followed by branding and advertising, and food manufacturing and retail. Most corporate interest groups are headquartered where they can access powerful government and GFG decision-makers, nearly one-third in Washington DC and Brussels, and the rest in capital cities of major national markets for UPFs. The UPF industry, and especially its leading corporations, coordinate a global network of interest groups spanning multiple levels, jurisdictions, and governance spaces. This represents a major structural feature of global food and health governance systems, which arguably poses major challenges for actions to attenuate the harms of UPFs, and to realising of healthy and sustainable food systems.

Decryption of sequence, structure, and functional features of SINE repeat elements in SINEUP non-coding RNA-mediated post-transcriptional gene regulation

RNA structure folding largely influences RNA regulation by providing flexibility and functional diversity. In silico and in vitro analyses are limited in their ability to capture the intricate relationships between dynamic RNA structure and RNA functional diversity present in the cell. Here, we investigate sequence, structure and functional features of mouse and human SINE-transcribed retrotransposons embedded in SINEUPs long non-coding RNAs, which positively regulate target gene expression post-transcriptionally. In-cell secondary structure probing reveals that functional SINEs-derived RNAs contain conserved short structure motifs essential for SINEUP-induced translation enhancement. We show that SINE RNA structure dynamically changes between the nucleus and cytoplasm and is associated with compartment-specific binding to RBP and related functions. Moreover, RNA–RNA interaction analysis shows that the SINE-derived RNAs interact directly with ribosomal RNAs, suggesting a mechanism of translation regulation. We further predict the architecture of 18 SINE RNAs in three dimensions guided by experimental secondary structure data. Overall, we demonstrate that the conservation of short key features involved in interactions with RBPs and ribosomal RNA drives the convergent function of evolutionarily distant SINE-transcribed RNAs.

Development of efficient and economic Bi2O3/BN/Co3O4 composite photocatalyst: Degradation mechanism, pathway and toxicity study of norfloxacin

The production of cheap, efficient, and stable photocatalysts for degrading antibiotic contaminants remains challenging. Herein, Bi2O3/boron nitride (BN)/Co3O4 ternary composites were synthesized using the impregnation method. The morphological characteristics, structural features, and photochemical properties of the prepared photocatalysts were investigated via X-ray diffraction, Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy, high-resolution transmission electron microscopy, and ultraviolet–visible (Vis) diffuse reflectance spectrum techniques. BN was used as a charge transfer bridge in the ternary composites, which afforded a heterojunction between the two semiconductors. The formation of the heterojunction substantially enhanced the charge separation and improved the photocatalyst performance. The degradation activity of the Bi2O3/BN/Co3O4 ternary composites against norfloxacin (NOR) under Vis light irradiation was investigated. The degradation rate of NOR using 5-wt% Bi2O3/BN/Co3O4 reached 98% in 180 min, indicating excellent photocatalytic performance. The ternary composites also exhibited high photostability with a degradation efficiency of 88.4% after five cycles. Hydroxyl radicals (•OH), superoxide radicals (•O2−), and holes (h+) played a synergistic role in the photocatalytic reaction, where h+ and •O2− were more important than •OH. Consequently, seven intermediates and major photocatalytic degradation pathways were identified. Toxicity experiments showed that the toxicity of the degradation solution to Chlorella pyrenoidosa decreased. Finally, the ecotoxicity of NOR and its intermediates were analyzed using the Toxicity Estimation Software Tool, with most intermediates exhibiting low toxicity.

Multi-granularity Cross Transformer Network for person re-identification

Person re-identification (Re-ID) aims to retrieve the same person in the gallery. Transformers have been introduced to the Re-ID task due to their excellent ability to model long-range dependency. However, due to the properties of the global attention mechanism, they are less effective in capturing the discriminative local semantics of pedestrians compared to convolutional operations. To address this issue, we present a Multi-granularity Cross Transformer Network (MCTN) that progressively learns salient features of different local structures in a global context. Specifically, we first utilize a Multi-granularity Convolutional Layer (MCL) to investigate salient pedestrian features at various granularities. On this basis, we propose a Pyramidal Cross Transformer learning layer (PCT), which contains a pyramidal division of pedestrian image feature maps, differentiated feature extraction of different parts of pedestrians, and cross attention to exploring the local–global relationship of the feature map. It allows effective mining of local information in the global structure from a coarse-to-fine perspective. Furthermore, to enhance the interaction between low-level detailed features and high-level semantic features, a Hierarchical Aggregation Strategy (HAS) is introduced to fuse features learned by cross attention learning at different stages. Pedestrian features learned in shallow layers will serve as global priors for semantics learning in deep layers. We evaluate our method on four large-scale Re-ID datasets, and the experimental results reveal that the proposed method outperforms the state-of-the-art methods.