Composition Framework Research Articles

Poetry Fridays: Authorizing Readers in the High-Stakes, Testing-Oriented Classroom

ABSTRACT This article examines the liberatory potential of student-led discussions in an increasingly neoliberal global context. More specifically, it will explore one such poetry-oriented practice as it embodies theories from scholars like Peter Rabinowitz and Michael Smith (as established in Authorizing Readers: Resistance and Respect in the Teaching of Literature, 1998) and Sheridan Blau (The Literature Workshop, 2003). Years after these authors first recommended locating classroom authority in students and the text rather than in the teacher, such practices remain rare; however, as both scholarship and student survey responses show, they are vital tools in cultivating genuine learning, student agency, and collaborative engagement. Although the article concentrates on student engagement with poetry as it exists in relation to the Advanced Placement® (AP) framework for English Literature and Composition, the commentary it provides is also relevant to alternative models such as International Baccalaureate® (I.B.) programs and college preparatory curricula more generally.

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

While digital twins (DTs) have recently gained prominence as a viable option for creating reliable asset representations, many existing frameworks and architectures in the literature involve the integration of different technologies and paradigms, including the Internet of Things (IoTs), data modeling, and machine learning (ML). This complexity requires the orchestration of these different technologies, often resulting in subsystems and composition frameworks that are difficult to seamlessly align. In this paper, we present a scalable compositional framework designed for the development of a DT-based production management system (PMS) with advanced production monitoring capabilities. The conducted approach used to design the compositional framework utilizes the Factory Design and Improvement (FDI) methodology. Furthermore, the validation of our proposed framework is illustrated through a case study conducted in a phosphate screening station within the context of the mining industry.

Composite attention mechanism network for deep contrastive multi-view clustering

Contrastive learning-based deep multi-view clustering methods have become a mainstream solution for unlabeled multi-view data. These methods usually utilize a basic structure that combines autoencoder, contrastive learning, or/and MLP projectors to generate more representative latent representations for the final clustering stage. However, existing deep contrastive multi-view clustering ignores two key points: (i) the latent representations projecting from one or more layers of MLP or new representations directly obtained from autoencoder fail to mine inherent relationship inner-view or cross-views; (ii) more existing frameworks only employ a one or dual-contrastive learning module, i.e., view- or/and category-oriented, which may result in the lack of communication between latent representations and clustering assignments. This paper proposes a new composite attention framework for contrastive multi-view clustering to address the above two challenges. Our method learns latent representations utilizing composite attention structure, i.e., Hierarchical Transformer for each view and Shared Attention for all views, rather than simple MLP. As a result, the learned representations can simultaneously preserve important features inside the view and balance the contributions across views. In addition, we add a new communication loss in our new dual contrastive framework. The common semantics will be brought into clustering assignments by pushing clustering assignments closer to the fused latent representations. Therefore, our method will provide a higher quality of clustering assignments for the segmentation problem of unlabeled multi-view data. The extensive experiments on several real data demonstrate that the proposed method can achieve superior performance over many state-of-the-art clustering algorithms, especially the significant improvement of an average of 10% on datasets Caltech and its subsets according to accuracy.

Detritivores maintain stoichiometric homeostasis, but alter body size and population density in response to altitude induced stoichiometric mismatches

Maintaining a balance between growth needs and available food resources is critical to the development of any organism. Ecological stoichiometry provides a theoretical basis for studying stoichiometric mismatches between organisms and their food resources. Recent studies have shown that detritivore taxa occupying different multidimensional stoichiometric niches (MSNs) exhibit different stoichiometric mismatch patterns. However, changes in stoichiometric mismatch patterns of different functional groups within the same taxon in response to changes in food resources are poorly understood. Here, we investigated changes in the stoichiometric mismatch between litter as major food resource and five functional groups of soil detritivores (millipedes; Diplopoda) for eleven elements along an altitudinal gradient from 800 to 1850 m on Changbai Mountain, Northeast China. We quantified MSNs and multidimensional stoichiometric mismatch patterns, and investigated changes with altitude and relationships with body size and population density. The concentration of chemical elements of litter varied significantly with altitude and this also was true for the trophic stoichiometric mismatch in millipedes. Furthermore, millipede stoichiometry homeostasis resulted in changing stoichiometric mismatches with changing litter element ratios. Element concentrations in litter, specifically N, Ca, P, Na and Cu, impacted the body size and population density of millipedes, with different elements correlating with individual functional groups. The results indicate that consumer-resource stoichiometric mismatches significantly affect detritivore populations, highlighting the predictive power of the multidimensional stoichiometry framework for detritivore community composition in context of environmental change.

Excellent sodium metal deposition enabled by three-dimensional porous structures with natrophilic Ni-Sn alloy

Na metal has long been an ideal potential anode material for sodium secondary batteries due to its own superiority; however, the Na dendrite problem during cycling makes it face a great obstacle in application. Here, we grow sodiophilic thin film materials with tin and nickel-tin components uniformly on three-dimensional nickel foam (3D-Ni) to obtain a 3D sodiophilic composite framework (namely 3D-NiSn) using a reproducible and mass-produced electrodeposition strategy. The combination of sodiophilic film (NiSn) and 3D porous framework could lower nucleation overpotential of Na and accelerate ions diffusion, hence inducing the uniform deposition and reversible stripping of sodium and inhibiting the growth of Na dendrites, which makes the 3D-NiSn/Na composite anode exhibit good performance compared to 3D-Ni/Na and Na-foil. The symmetrical cells with 3D-NiSn/Na can maintain up to 2500 h at 2 mA cm−2 and 1 mAh cm−2 with a low overpotential of around 30 mV during the whole cycling process. Additionally, the 3D-NiSn/NaǁNa3V2(PO4)3 full cells deliver good cycle stability with a high specific capacity of around 98.1 mAh g−1 at 3C for over 600 cycles. This work provides an idea for constructing low-cost and commercially available Na metal electrodes toward high-performance SIBs.

Association between musculoskeletal pain and exposures to awkward postures during work: a compositional analysis approach.

This study aimed to explore the association between arm elevation and neck/shoulder pain, and trunk forwarding bending and low back pain among home care workers. Home care workers (N = 116) from 11 home care units in Trondheim, Norway, filled in pain assessment and working hours questionnaire, and wore 3 accelerometers for up to 7 consecutive days. Work time was partitioned into upright awkward posture, nonawkward posture, and nonupright time, i.e. sitting. Within a compositional approach framework, posture time compositions were expressed in terms of log-ratio coordinates for statistical analysis and modeling. Poisson generalized linear mixed models were used to analyze the relationship between arm elevation in upright postures and neck/shoulder pain, and between trunk forward bending in upright postures and low back pain, respectively. Isotemporal substitution analysis was used to investigate the association of pain assessment with the reallocation of time spent in the different postures. Time spent in awkward postures was modest, especially for the more extreme angles (60° and 90°). Adjusting for age, gender, and body mass index, our study suggested that the compositions of time spent by home care workers in awkward postures were significantly associated with pain assessment (P < 0.01). Isotemporal substitution analysis showed that reallocating 5 min from upright posture with arms elevated below to above 60° and 90° was associated with a 6.8% and 19.9% increase in the neck/shoulder pain score, respectively. Reallocating 5 min from a forward bending posture while upright below to above 30°, 60°, and 90° was associated with 1.8%, 3.5%, and 4.0% increase in low back pain, respectively. Although the exposure to awkward postures was modest, our results showed an association between increased time spent in awkward postures and an increase in neck/shoulder pain and low back pain in home care workers. As musculoskeletal pain is the leading cause of sickness absence, these findings suggest that home care units could benefit from re-organizing work to avoid excessive arm elevation and trunk forward bending in workers.

A high performance fireproof quasi-solid-state electrolyte enabled by multi-phase synergistic mechanism

Composite quasi-solid electrolytes usually suffer from reduced safety performance due to the presence of liquid plasticizers and an inherently unsafe polymer matrix. Adding inorganic fillers is an effective strategy to improve the safety performance of quasi-solid electrolytes, but excessive content may block ion transport channels, leading to a decrease in electrochemical performance. Therefore, it is proposed to construct a multi-phase synergistic non-flammable composite quasi-solid electrolyte (MS-NCQE) by combining an intrinsically safe porous composite framework with a Li+ conductive polymer through in-situ solidification technique. Thanks to multi-phase synergistic mechanism, a porous composite framework consisting of ceramic powder as well as a non-flammable polymer matrix enables MS-NCQE to exhibit significantly improved safety properties. At the same time, due to the interaction between the third-phase Li+ conductive polymer and ceramic powder, MS-NCQE presents excellent lithium ion transport performance (6.59×10−4 S cm−1 at 25 °C) and dendrite resistance (0.1 mA cm−2; 3000 h). Further, the as-prepared LiFePO4|Li and LiNi0.83Co0.12Mn0.05O2|Li batteries display outstanding cycling performance. In particular, the capacity retention rate of the LiFePO4|Li battery is approximately 98 % after 300 cycles at 0.5 C, and its average Coulombic efficiency is higher than 99.8 %. In addition, the pouch cell can work normally and safely under different abuse conditions. This work provides new insights into the design of composite quasi-solid electrolytes with high safety and excellent electrochemical properties.

A General Implicit Framework for Fast NeRF Composition and Rendering

A variety of Neural Radiance Fields (NeRF) methods have recently achieved remarkable success in high render speed. However, current accelerating methods are specialized and incompatible with various implicit methods, preventing real-time composition over various types of NeRF works. Because NeRF relies on sampling along rays, it is possible to provide general guidance for acceleration. To that end, we propose a general implicit pipeline for composing NeRF objects quickly. Our method enables the casting of dynamic shadows within or between objects using analytical light sources while allowing multiple NeRF objects to be seamlessly placed and rendered together with any arbitrary rigid transformations. Mainly, our work introduces a new surface representation known as Neural Depth Fields (NeDF) that quickly determines the spatial relationship between objects by allowing direct intersection computation between rays and implicit surfaces. It leverages an intersection neural network to query NeRF for acceleration instead of depending on an explicit spatial structure.Our proposed method is the first to enable both the progressive and interactive composition of NeRF objects. Additionally, it also serves as a previewing plugin for a range of existing NeRF works.

Hierarchical medical image report adversarial generation with hybrid discriminator

Background and objectivesGenerating coherent reports from medical images is an important task for reducing doctors' workload. Unlike traditional image captioning tasks, the task of medical image report generation faces more challenges. Current models for generating reports from medical images often fail to characterize some abnormal findings, and some models generate reports with low quality. In this study, we propose a model to generate high-quality reports from medical images. MethodsIn this paper, we propose a model called Hybrid Discriminator Generative Adversarial Network (HDGAN), which combines Generative Adversarial Network (GAN) with Reinforcement Learning (RL). The HDGAN model consists of a generator, a one-sentence discriminator, and a one-word discriminator. Specifically, the RL reward signals are judged on the one-sentence discriminator and one-word discriminator separately. The one-sentence discriminator can better learn sentence-level structural information, while the one-word discriminator can learn word diversity information effectively. ResultsOur approach performs better on the IU-X-ray and COV-CTR datasets than the baseline models. For the ROUGE metric, our method outperforms the state-of-the-art model by 0.36 on the IU-X-ray, 0.06 on the MIMIC-CXR and 0.156 on the COV-CTR. ConclusionsThe compositional framework we proposed can generate more accurate medical image reports at different levels.

A knowledge interchange broker composition modeling framework for simulating water, energy, and water-energy nexus systems

Understanding the dynamics of complex systems requires developing and combining different kinds of models that can be simulated separately and together. Modeling the interactions as separate models contributes to building flexible hybrid simulation frameworks. In this research, a Discrete Event System Specification–based Interaction Model (DEVS-IM) framework is developed based on the Knowledge Interchange Broker (KIB) approach. This KIB-based RESTful modeling composition framework is shown to enable systematic modeling and simulation of interactions between disparate simulatable models. It supports storing IMs developed for componentized Water Evaluation and Planning System (WEAP) and Low Emissions Analysis Platform (LEAP) tools. It generates the skeleton of DEVS-IMs stored in database for DEVS-Suite simulator. An exemplar model consisting of water, energy, and IMs demonstrates this methodology for developing nexus models of water–energy systems.

A compositional simulation framework for Abstract State Machine models of Discrete Event Systems

Modeling complex system requirements often requires specifying system components in separate models, which can be validated and verified in isolation from each other, and then integrating all components’ behavior in order to validate the operation of the whole system. If models are executable, as for state-based formal specifications, engines to orchestrate the simulation of separate component operational models are extremely useful. This paper presents an approach for the co-simulation, according to predefined orchestration schemas, of state-based models of separate components of a Discrete Event System. More precisely, we exploit the Abstract State Machine (ASM) formal method as state-based formalism, and we ( i ) define a set of operators to compose ASMs that communicate with each other through I/O events, and ( ii ) present an engine to execute the compositional simulation of the ASMs as a whole assembly. As proof of concepts, we use a set of model examples of Discrete Event Systems of increasing complexity to show the application of our approach and to evaluate its effectiveness in co-simulating models of real systems.

Making residential green space exposure evaluation more accurate: A composite assessment framework that integrates objective and subjective indicators

Traditional satellite or land use-derived indicators for assessing residential green space (RGS) exposure have limitations in predicting health benefits, owing to the individual differences in the absorption of ‘real’ green exposure. This study developed a novel framework, Greenspace Exposure Composite Indices (GCIs), that modifies objective RGS metrics by including residents’ subjective factors. First, three RGS objective indicators were established based on 3D point clouds: the overall green exposure index(GEI), floor-level green exposure index(FGEI), and activity-site green exposure index(AGEI). The individual factors (i.e. perception, emotion, and behaviour towards RGS) are then weighted to these objective indicators to obtain modified GCIs through the Brunswikian lens model. We also used this novel framework to examine the effects of the RGS indicators on environmental satisfaction based on a case study including 1594 participants in Nanjing, China. The Random Forest Model was used to examine the associations between GCIs and environmental satisfaction, and the results showed that GCIs had a higher explanatory degree of environmental satisfaction than traditional objective ones. Our findings demonstrated that incorporating subjective indicators to optimise objective RGS indicators could offer advantages in predicting environmental satisfaction. This framework is also applicable for predicting the potential effects of RGS exposure on other health-related outcomes.

Simvastatin-loaded 3D aerogel scaffolds promote bone regeneration.

It is imperative to design a suitable material for bone regeneration that emulates the microstructure and compositional framework of natural bone while mitigating the shortcomings of current repair materials. The aim of the study is to synthesize a 3D aerogel scaffold composed of PLCL/gelatin electro-spun nanofiber loaded with Simvastatin and investigate its biocompatibility as well as its performance in cell proliferation and ossification differentiation. PLCL/gelatin nanofibers were fabricated in coaxial electrospinning with simvastatin added. Fibers were fragmented, pipetted into molds, frozen, and dried. The morphology of fibers and contact angles in 4 groups of PLCL, PLCL@S, 3D-PLCL, and 3D-PLCL@S was observed and compared. MC3T3-E1 cells were planted at the four materials to observe cell growth status, and ALP and ARS tests were conducted to compare the ossification of cells. TEM scanning showed the coaxial fiber of the inner PLCL and outer gelatin. The mean diameter of the PLCL/gelatin fibers is 561 ± 95nm and 631 ± 103nm after the drug loading. SEM showed the fibers in the 3D-PLCL@S group were more curled and loose with more space interlaced. The contact angle in this group was 27.1°, the smallest one. Drug release test demonstrated that simvastatin concentration in the 3D-PLCL@S could remain at a relatively high level compared to the control group. The cell proliferation test showed that MC3T3-EI cells could embed into the scaffold deeply and exhibit higher viability in the 3D-PLCL@S group than other groups. The ossification tests of ALP and ARS also inferred that the 3D-PLCL@S scaffold could offer a better osteogenic differentiation matrix. The PLCL/gelatin aerogel scaffold, when loaded with Simvastatin, demonstrates a more pronounced potential in enhancing osteoblast proliferation and osteogenic differentiation. We hypothesize that this scaffold could serve as a promising material for addressing bone defects.

A Composite Index for Tracking the Evolution towards Energy Transition at Urban Scale: The Turin Case Study

Cities play a pivotal role in achieving worldwide carbon neutrality due to their significant contribution to global energy consumption and carbon emissions. Therefore, planning effective strategies and guiding evidence-based policymaking at the city scale becomes even more crucial. Composite indices serve as a valuable tool for monitoring urban energy transition trends. This paper aims to present a novel approach, robust and flexible even under conditions of data scarcity, for tracking the energy transition trend of a city by means of a composite index (UETI). The Turin case study is introduced to test the applicability of the proposed approach. Additionally, to demonstrate the robustness of the composite index framework, the paper includes the findings of correlation and sensitivity analyses. This study reveals a significant improvement in Turin’s environmental and energy domains, while the socio-economic domain shows more modest improvement. Furthermore, the study highlights the need to address the shortage of urban data to enhance the accuracy and reliability of metric-based frameworks and to extend the assessment to a larger sample of cities.

A comprehensive study on the kinetics and isotherms of D2/H2 adsorptive separation using pure and composite Cu-BDC-NH2 MOFs at 77 K

Pure and composite Cu-Amino-terephthalate MOF has been produced by ultrasound wave to evaluate the adsorption capacity and adsorptive separation of D2 and H2 at 77 K up to 1000 mbar. The frameworks are characterized by XRD, SEM, FTIR, ICP, BET, and EDX analysis. Separation studies were performed using idealized adsorption solution theory (IAST) and direct measurements. Isotherm studies showed the data had good agreement with the Langmuir model and the adsorption capacity of deuterium was greater than hydrogen in all samples. Linear Driving Force (LDF) model was applied to investigate the effective diffusion coefficients of deuterium and hydrogen in the frameworks. The LDF model showed hydrogen molecules diffused faster than deuterium molecules in all frameworks. In the adsorption enthalpy studies, there was a slight difference between deuterium and hydrogen adsorption energy. In this regard, Cu-BDC-NH2@rGO showed a higher adsorption enthalpy difference compared to Cu-BDC-NH2. Finally, the D2/H2 selectivity of the composite framework was greater than the pure one. Regarding this matter, the Cu-BDC-NH2@rGO MOF showed a maximum selectivity factor of about 2.2 at 77 K and 1000 mbar based on the IAST model.

Enhancing supercapacitor performance with biomass-derived activated carbon interlinked CoS2 embedded graphitic carbon nitride

This work investigates the improved electrochemical performance of CoS2 on composites CoS2/AC and CoS2/AC/g-C3N4 that are prepared via hydrothermal method and the production of activated carbon is of bio-derived configuration. The structural, vibrational modes, and functional groups of the as synthesized nanostructures are confirmed through X-ray Diffraction (XRD), Raman, and FTIR analyses. The specific surface area of CoS2/AC and CoS2/AC/g-C3N4 is 54.3 m2g−1, and 41.3 m2g−1, respectively. X-ray Photoelectron Spectroscopy (XPS) reveals the charge state of Co2+ and high charge transfer between Co and C in CoS2/AC/g-C3N4 compared to CoS2/AC. Nanoprobe Projection X-ray microscopy (PXM) discloses distorted octahedral coordination of Co2+ and site-dependent charge transfer by Co in CoS2/AC in comparison with CoS2/AC/g-C3N4. Further, the CoS2/AC electrode demonstrates a high specific capacity of 984 Fg−1 in the three-electrode system. The high-performance CoS2/AC electrode produced a high-power density of 2042.21 W Kg−1 and an energy density of 28.36 Whkg−1 in an aqueous electrolyte. The integration of CoS2 nanoparticles into the CoS2/AC and CoS2/AC/g-C3N4 composite framework significantly contributes to the improvement of specific capacity and excellent cycle stability up to 5000 cycles. This improvement could be influenced by several factors, such as reduced ion transport distances, strengthened interfacial interactions, high surface area, distortion of octahedral coordination of Co2+, and spatial-dependent charge transfer by Co in CoS2/AC. The distinct characteristics in specific capacity and cycling stability is attributed to the incorporation of CoS2 nanoparticles within the CoS2/AC and CoS2/AC/g-C3N4 composites that cause the short transport distance of the ions, enhanced interfacial interaction, and further provide better structural stability of the CoS2/AC and CoS2/AC/g-C3N4 composite network.

Design of multifunctional interfaces on ceramic solid electrolytes for high-performance lithium-air batteries

High-energy-density lithium (Li)–air cells have been considered a promising energy-storage system, but the liquid electrolyte-related safety and side-reaction problems seriously hinder their development. To address these above issues, solid-state Li–air batteries have been widely developed. However, many commonly-used solid electrolytes generally face huge interface impedance in Li–air cells and also show poor stability towards ambient air/Li electrodes. Herein, we fabricate a differentiating surface-regulated ceramic-based composite electrolyte (DSCCE) by constructing disparately LiI-containing polymethyl methacrylate (PMMA) coating and Poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) layer on both sides of Li1.5Al0.5Ge1.5(PO4)3 (LAGP). The cathode-friendly LiI/PMMA layer displays excellent stability towards O2− and also greatly reduces the decomposition voltage of discharge products in Li–air system. Additionally, the anode-friendly PVDF-HFP coating shows low-resistance properties towards anodes. Moreover, Li dendrite/passivation derived from liquid electrolyte-induced side reactions and air/I-attacking can be obviously suppressed by the uniform and compact composite framework. As a result, the DSCCE-based Li–air batteries possess high capacity/low voltage polarization (11,836 mA h g−1/1.45 V under 500 mA g−1), good rate performance (capacity ratio under 1000 mA g−1/250 mA g−1 is 68.2%) and long-term stable cell operation (∼300 cycles at 750 mA g−1 with 750 mAh g−1) in ambient air.

Праздник русской березки: советское инсценирование концепта тринитаризма

This paper is focused on the means of transforming Trinity Sunday and attempts to “reinvent” this festival into the Russian Birch festival. In late 50s of the 20th century in a burst of the anticlerical campaign, the Soviet festival committees were concerned with creating new secular rituals, and anti-religious analogues of festivals, which would be able to get rid of ingrained “popular Orthodoxy”. The modes of performing the meaningful core of Trinity Sunday are a subject of this research, and theatrical and methodological scenario-based experience in holding the Russian Birch festival is an object. This research is based on numerous methodological guidelines, scenarios, reviews, and transcripts of relevant committees, which made it possible to shed light on complicated processes of generating a new festival. This paper represents the way, in which heroic and plot and compositional framework of original Trinity Sunday was being substituted. This research results in the following: in spite of the anticlerical position being declared, which had constituted the basis for the substitution of Trinity Sunday for the Russian Birch festival, in fact, the newly “invented” festival duplicated the basic functions and elements of the trinitarian concept and was within the framework of Trinity Sunday in terms of archetype. Moreover, the association with commemoration of the dead appropriate to Trinity was reflected in a cult of a heroic death of a soldier of the Soviet Army and updating of other cultural agendas.

A layered multifunctional framework based on polyacrylonitrile and MOF derivatives for stable lithium metal anode

Composite Li metal anodes based on three-dimensional (3D) porous frameworks have been considered as an effective material for achieving stable Li metal batteries with high energy density. However, uneven Li deposition behavior still occurs at the top of 3D frameworks owing to the local accumulation of Li ions. To promote uniform Li deposition without top dendrite growth, herein, a layered multifunctional framework based on oxidation-treated polyacrylonitrile (OPAN) and metal-organic framework (MOF) derivatives was proposed for rationally regulating the distribution of Li ions flux, nucleation sites, and electrical conductivity. Profiting from these merits, the OPAN/carbon nano fiber-MOF (CMOF) composite framework demonstrated a reversible Li plating/stripping behavior for 500 cycles with a stable Coulombic efficiency of around 99.0% at the current density of 2 mA/cm2. Besides, such a Li composite anode exhibited a superior cycle lifespan of over 1300 h under a low polarized voltage of 18 mV in symmetrical cells. When the Li composite anode was paired with LiFePO4 (LFP) cathode, the obtained full cell exhibited a stable cycling over 500 cycles. Moreover, the COMSOL Multiphysics simulation was conducted to reveal the effects on homogeneous Li ions distribution derived from the above-mentioned OPAN/CMOF framework and electrical insulation/conduction design. These electrochemical and simulated results shed light on the difficulties of designing stable and safe Li metal anode via optimizing the 3D frameworks.

A New Method Used to Enhance the SPAIR Image of the Spine MRI.

Magnetic resonance imaging (MRI) is a handy diagnostic tool for orthopedic disorders, particularly spinal and joint diseases. The lumbar intervertebral disc is visible in the T1 and T2 weight sequences of the spine MRI, which aids in diagnosing lumbar disc herniation, lumbar spine tuberculosis, lumbar spine tumors, and other conditions. The lumbar intervertebral disc cannot be seen accurately in the Spectral Attenuated Inversion Recovery (SPAIR) due to weaknesses in the fat and frequency offset parameters, which is not conducive to developing the intelligence diagnosis model of medical image. In order to solve this problem, we propose a composite framework, which is first to use the contrast limited adaptive histogram equalization (CLAHE) method to enhance the SPAIR image contrast of the spine MRI and then use the non-local means method to remove the noise of the image to ensure that the image contrast is uniform without losing details. We employ the Information Entropy (IE), Peak signal-to-noise ratio (PSNR), and feature similarity index measure (FSIM) to quantify image quality after enhancement by the composite framework. The outcomes of the experiments' output images and quantitative data indicate that our composite framework is better than others.