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ObjectiveThe oral microbiota is the second largest microbiota in the human body and has a significant impact on human health. Recent evidence suggests that dysbiosis of the oral microbiota may be associated with the development of metabolism-associated fatty liver disease (MAFLD). This review aimed to validate the relationship between oral microbial diversity and the development of MAFLD.MethodsA systematic evaluation was performed based on PRISMA guidelines. Three independent reviewers searched for relevant literature in several databases, including PubMed/Medline, Web of Science, and Scopus, with a search date ranging from the establishment of the databases to June 2024.ResultsA total of 1278 publications were initially screened, including five cross-sectional studies, seven case-control studies, one cohort study, and one retrospective study. These studies included a total of 3335 patients with MAFLD, 254 patients with MASH, and 105 patients with liver cirrhosis. All 14 included studies concluded that there was a correlation or potential correlation between oral microbiota and MAFLD. Seven studies found that the composition of the oral microbiota in MAFLD patients differed from that of healthy controls, and specific oral bacteria may be associated with an increased incidence of MAFLD. At the phylum level, several studies found differences in the abundance of the phyla Firmicutes, Proteobacteria, and Clostridia compared to healthy controls. Additionally, a study on oral fungi found significant differences in the phyla Proteobacteria and in the genus Staphylococcus between patients with MAFLD and healthy controls. At the genus level, Porphyromonas was studied most frequently, with all 8 studies identifying infection with Porphyromonas as a significant risk factor for pathological progression in MAFLD. Furthermore, a dysbiosis in the ratio of Porphyromonas gingivalis./Porphyromonas anomalies may be an important marker of MAFLD progression.ConclusionThere is an important association between the diversity of oral microbiota composition and MAFLD. This finding suggests the importance of oral health assessment and monitoring for the prevention or intervention of MAFLD.

ObjectiveResearch evidence suggests that exercise is a potent therapeutic strategy for non-alcoholic fatty liver disease (NAFLD). Many investigations have delved into the curative potential of diverse exercise regimens on NAFLD. This investigation synthesizes findings from randomized controlled trials via a network meta-analysis to evaluate the efficacy of exercise-based interventions on NAFLD.MethodsWe conducted a search across five electronic databases (Web of Science, EMBASE, PubMed, SCOPUS, and CNKI)to identify randomized controlled trials (RCTs) comparing the effects of different exercise modalities on metabolic profiles and liver functions in patients with NAFLD. The literature search was comprehensive up to 15, December 2023. The selected studies were subjected to a rigorous quality appraisal and risk of bias analysis in accordance with the Cochrane Handbook’s guidelines, version 5.1.0. We employed Stata/MP 17 for the network meta-analysis, presenting effect sizes as standardized mean differences (SMD).ResultsThis study aggregated results from 28 studies, involving a total of 1,606 participants. The network meta-analysis revealed that aerobic exercise was the most effective intervention for improving BMI in patients with NAFLD, demonstrating a significant decrease in BMI (−0.72, 95%CI: −0.98 to −0.46; p < 0.05; Surface Under the Cumulative Ranking (SUCRA) = 79.8%). HIIT was the top intervention for enhancing HDL-C (0.12, 95% CI: 0.04 to 0.20; p < 0.05; SUCRA = 76.1%). Resistance exercise was the most effective for reducing LDL-C (−0.20, 95% CI: −0.33 to −0.06; p < 0.05; SUCRA = 69.7%). Mind-body exercise showed superior effectiveness in improving TC (−0.67, 95% CI: −1.10 to −0.24; p < 0.05; SUCRA = 89.7%), TG = −0.67, 95% CI: −1.10 to −0.24; p < 0.05; SUCRA = 99.6%), AST (−8.07, 95% CI: −12.88 to −3.25; p < 0.05; SUCRA = 76.1%), ALT (−12.56, 95% CI: −17.54 to −7.58; p < 0.05; SUCRA = 99.5%), and GGT (−13.77, 95% CI: −22.00 to −5.54; p < 0.05; SUCRA = 81.8%).ConclusionThis network meta-analysis demonstrates that exercise interventions positively affect various metabolic profiles and liver functions in NAFLD patients. Mind-body exercises are particularly effective, surpassing other exercise forms in improving metabolic profiles and liver functions.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier registration number CRD42024526332.

The detection and classification of foodborne pathogenic bacteria is crucial for food safety monitoring, consequently requiring rapid, accurate and sensitive methods. In this study, the surface-enhanced Raman spectroscopy (SERS) technique coupled with chemometrics methods was used to detect and classify six kinds of foodborne pathogenic bacteria, including Salmonella typhimurium (S. typhimurium), Escherichia coli (E. coli) O157:H7, Staphylococcus aureus (S. aureus), Listeria monocytogenes (L. monocytogenes), Listeria innocua (L. innocua), and Listeria welshimeri (L. welshimeri). First, silver nanoparticles (AgNPs) with different particle sizes were prepared as SERS-enhanced substrates by changing the concentration of sodium citrate, and the volume ratio of silver nanosol to bacterial solution was optimised to obtain the optimal SERS signal. Then, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to classify the SERS spectra of six bacteria at three classification levels (Gram type level, genus level and species level), and appropriate classification models were established. Finally, these models were validated on 540 spectra using linear discriminant analysis (LDA), achieving an average accuracy of 95.65%. Overall, it was concluded that the SERS technique combined with chemometrics methods could achieve the rapid detection and classification identification of foodborne pathogenic bacteria, providing an effective means for food safety monitoring.

PurposeHow cortical functional reorganization occurs after hearing loss in preschool children with congenital sensorineural hearing loss (CSNHL) is poorly understood. Therefore, we used resting-state functional MRI (rs-fMRI) to explore the characteristics of cortical reorganization in these patents.MethodsSixty-three preschool children with CSNHL and 32 healthy controls (HCs) were recruited, and the Categories of Auditory Performance (CAP) scores were determined at the 6-month follow-up after cochlear implantation (CI). First, rs-fMRI data were preprocessed, and amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) were calculated. Second, whole-brain functional connectivity (FC) analysis was performed using bilateral primary auditory cortex as seed points. Finally, Spearman correlation analysis was performed between the differential ALFF, ReHo and FC values and the CAP score.ResultsALFF analysis showed that preschool children with CSNHL had lower ALFF values in the bilateral prefrontal cortex and superior temporal gyrus than HCs, but higher ALFF values in the bilateral thalamus and calcarine gyrus. And correlation analysis showed that some abnormal brain regions were weak negatively correlated with CAP score (p

Patients with substance use disorders (SUDs) often suffer from cognitive dysfunction (CD), affecting their quality of life and daily functioning. Current treatments, including pharmacotherapy and psychotherapy, have limited efficacy and notable side effects. Transcranial direct current stimulation (tDCS), a non-invasive technique that modulates cortical activity, shows promise in improving cognitive function with minimal side effects and low cost, and could potentially serve as a valuable adjunct to existing therapies. This systematic review aims to evaluate the literature on the effectiveness of tDCS for CD in SUD patients to inform clinical practice and future research. Following PRISMA guidelines, the review includes studies that used tDCS for SUD-related CD. The criteria for inclusion encompassed participants aged 18 and older with a diagnosis of SUD, the use of tDCS (either conventional or high-definition), control groups receiving sham stimulation or no intervention, and cognitive outcome measures for substance-related cognitive function using validated tools. Databases searched were Ovid MEDLINE, PubMed, Web of Science, Embase, Scopus, and PsycINFO, with specific keywords. Twenty-two studies met the criteria, suggesting tDCS can improve cognitive functions in SUD patients, though results varied. Effectiveness may depend on the brain area targeted, stimulation parameters, task requirements, and individual differences. tDCS shows potential in treating SUD-related CD, but further research is needed to optimize stimulation protocols and address study variability. Future studies should use functional magnetic resonance imaging to explore the brain mechanisms by which tDCS improves cognitive function in SUDs and focus on larger, long-term trials to confirm efficacy and refine tDCS treatment parameters.

Abstract Few comparative studies have assessed metabolic brain changes in cognitive impairment among neurodegenerative disorders, and the posterior cingulate cortex (PCC) is a metabolically active brain region with high involvement in multiple cognitive processes. Therefore, in this study, metabolic abnormalities of the PCC were compared in patients with mild cognitive impairment (MCI) due to Parkinson’s disease (PD) or Alzheimer’s disease (AD), as examined by proton magnetic resonance spectroscopy (1H-MRS). Thirty-eight patients with idiopathic PD, including 20 with mild cognitive impairment (PDMCI) and 18 with normal cognitive function (PDN), 18 patients with probable mild cognitive impairment (ADMCI), and 25 healthy elderly controls (HCs) were recruited and underwent PCC 1H-MRS scans. Compared with HCs, patients with PDMCI exhibited significantly reduced concentrations of N-acetyl aspartate (NAA), total NAA (tNAA), choline (Cho), glutathione (GSH), glutamate + glutamine (Glx) and total creatine (tCr), while ADMCI cases exhibited significantly elevated levels of myo-inositol (Ins) and Ins/tCr ratio, as well as reduced NAA/Ins ratio. No significant metabolic changes were detected in PDN subjects. Compared with ADMCI, reduced NAA, Ins and tCr concentrations were detected in PDMCI. Besides, ROC curve analysis revealed that tCr concentration could differentiate PDMCI from PDN with an AUC of 0.71, and NAA/Ins ratio could differentiate patients with MCI from controls with normal cognitive function with an AUC of 0.74. Patients with PDMCI and ADMCI exhibited distinct PCC metabolic 1H-MRS profiles. The findings suggested cognitively normal PD patients with low NAA and tCr in the PCC might be at risk of preclinical PDMCI, and Ins and/or NAA/MI ratio in the PCC should be reconsidered a possible biomarker of preclinical MCI in clinical practice. So, comparing PCC’s 1H-MRS profiles of cognitive impairment among neurodegenerative illnesses may provide useful information for better defining the disease process and elucidate possible treatment mechanisms.

Abstract Cholesterol metabolism plays a critical role in the progression of hepatocellular carcinoma (HCC), but it is not clear how cholesterol metabolism is regulated. The tubulin beta class I genes (TUBBs) are associated with the prognosis of many different cancers. To confirm the function of TUBBs in HCC, the Kaplan–Meier method and Cox analyses were performed using TCGA and GSE14520 datasets. A higher expression of TUBB2B is an independent prognostic factor for shorter over survival in HCC patients. Deletion of TUBB2B in hepatocytes inhibits proliferation and promotes tumor cell apoptosis, while over-expression of TUBB2B has the opposite function. This result was confirmed in a mouse xenograft tumor model. Mechanistically, TUBB2B induces the expression of CYP27A1, an enzyme responsible for the conversion of cholesterol to 27-hydroxycholesterol, which leads to the up-regulation of cholesterol and the progression of HCC. In addition, TUBB2B regulates CYP27A1 via human hepatocyte nuclear factor 4alpha (HNF4A). These findings indicated that TUBB2B functions as an oncogene in HCC, and plays a role in promoting cell proliferation and anti-apoptosis through targeting HNF4A/CYP27A1/cholesterol.

The large amounts of greenhouse gases, such as carbon dioxide, produced by severe forest fires not only seriously affect the ecosystems in the area where the fires occur but also cause a greenhouse effect that has a profound impact on the natural environment in other parts of the world. Numerical simulations of greenhouse gas transport processes are often affected by uncertainties in the location and timing of the emission sources and local meteorological conditions, and it is difficult to obtain accurate and credible predictions by combining remote sensing satellite data with given meteorological forecasts or reanalyses. To study the regional transport processes and impacts of greenhouse gases produced by sudden large-scale forest fires, this study applies the Lagrangian particle dispersion model Massive-Parallel Trajectory Calculations (MPTRAC) to conduct forward simulations of the CO2 transport process of greenhouse gases emitted from forest fires in the central region of Saskatchewan, Canada, during the period of 17 May to 25 May 2021. The simulation results are validated with the Orbiting Carbon Observatory-2 Goddard Earth Observing System (OCO-2 GEOS) Level 3 daily gridded CO2 product over the study area. In order to leverage the high computational costs of the numerical simulations of the model, we implement the forward simulations on the Tianhe-2 supercomputer platform and the JUWELS HPC system, which greatly improves the computational efficiency through parallel computation and makes near-real-time predictions of atmospheric transport processes feasible.

3D printing techniques offer an effective method in fabricating complex radially multi-material structures. However, it is challenging for complex and delicate radially multi-material model geometries without supporting structures, such as tissue vessels and tubular graft, among others. In this work, we tackle these challenges by developing a polar digital light processing technique which uses a rod as the printing platform. The 3D model fabrication is accomplished through line projection. The rotation and translation of the rod are synchronized to project and illuminate the photosensitive material volume. By controlling the distance between the rod and the printing window, we achieved the printing of tubular structures with a minimum wall thickness as thin as 50 micrometers. By controlling the width of fine slits at the printing window, we achieved the printing of structures with a minimum feature size of 10 micrometers. Our process accomplished the fabrication of thin-walled tubular graft structure with a thickness of only 100 micrometers and lengths of several centimeters within a timeframe of just 100 s. Additionally, it enables the printing of axial multi-material structures, thereby achieving adjustable mechanical strength. This method is conducive to rapid customization of tubular grafts and the manufacturing of tubular components in fields such as dentistry, aerospace, and more.

Customer relationships are important strategic resources. With a sample of A-share listed firms from 2007 to 2020 in China, this paper examines the recognition and value relevance of customer-related intangible assets. Current accounting standards require an acquirer to recognise identifiable intangible assets acquired in the business combination separately from goodwill. However, stakeholders question the usefulness of the information about customer relationships that are difficult to value reliably. The IASB and IFRIC have discussed a lot about whether to continue to separate customer-related intangible assets from goodwill. We find that firms with more R&D investments are more likely to recognise customer-related intangible assets. We also find that the book value of customer-related intangibles is positively associated with share price, which means recognised customer-related intangibles provide useful information to investors. We report empirical evidence in support of both international and Chinese accounting standards for separate recognition of identifiable intangible assets.

Ammonia has been used on a small scale in other industrial equipment, such as gas turbines, as a carbon-free fuel. However, ammonia fuel suffers disadvantages such as high ignition temperature, low flame velocity and high NOx emissions. Doping with ammonia using a more reactive fuel, such as methane, can solve the above problems. Therefore, under the relevant operating conditions of the gas turbine (T = 723 K, p = 16.5 atm), the effect of ammonia content on the combustion and emission characteristics of laminar premixed methane flames was numerically investigated. This research uses the PREMIX code from ANSYS CHEMKIN-PRO 2020 and Okafor chemical kinetic mechanisms and provides a reference for our subsequent analysis of gas turbine operating conditions. Firstly, the emission data of major pollutants under different ammonia content (XNH3 = 0–1.0) and equivalent ratio (Φ = .6–1.4) were calculated. Then, the laminar premixed flame structure is analyzed under the lean fuel conditions associated with gas turbines (Φ = .6, .8). Finally, the effect of ammonia addition on the chemical reaction path of NO and CO emission was studied. The results show that ammonia/methane mixture fuel is more suitable for combustion at .6 < Φ < .8 under high temperature and pressure. High ammonia content (XNH3 > .6) and low equivalent ratio can reduce NO and CO emissions. The molar fractions of H, O, and OH radicals and flame temperature decreased with the increase in ammonia content. In addition, high temperature and high pressure conditions and ammonia content greatly influence the reaction path of NO and CO production. The increase in pressure resulted in a change in the primary reaction that produced NO. In conclusion, this study guides reducing the emission of NO and CO from lean side of gas turbine plants.

The paper examines the motivation and consequences of Golden Parachute (GP) contracts in the context of TBEA, a Chinese company whose GP payment was 1,000 times executive annual salary and which rescinded its GP provision in 2019. We find that for TBEA, whose ownership is dispersed, anti-takeover was the main motivation for the adoption of GPs, and that managerial power was the key factor in designing GPs with payment of high monetary value. We also find that such GPs may induce higher excess executive compensation, lower shareholder participation, and reduce firm value, and that market reaction to the rescinding of GPs is positive. These results show that emerging capital markets should beware of the negative effect of GPs on firm value.

To investigate the seismic performance of a wind turbine that is influenced by both the ice load and the seismic load, the research proposes a numerical approach for simulating the seismic behavior of a wind turbine on a monopile foundation. First, the fluid–solid coupled equation for the water–ice–wind turbine is simplified by assigning reasonable boundary conditions and solving the motion equation, and the seismic motion equation of the wind turbine is developed. Then, on this basis, we propose a simplified 3D numerical model that can simulate the interactions among the wind turbine, water and sea ice. By conducting shaking table tests, the results demonstrate that the established numerical model is effective. Finally, we investigate the effect of the boundary range and ice thickness on the seismic performance of a turbine under near-field and far-field seismic actions. Research results illustrate that ice changes the distribution form of the hydrodynamic pressure. Moreover, the thickness of the ice greatly influences the seismic behavior, while the influence of the ice boundary range is only within a certain range. Additionally, the ice load decreases the energy-dissipating capacity of the wind turbine, so the earthquake resilience of the wind turbine is significantly decreased.

Esophageal squamous cell carcinoma (ESCC) is the sixth leading cause of death due to cancer, indicating that finding new therapeutic targets or approaches for ESCC treatment is imperative. Transient Receptor Potential cation channel subfamily M, member 2 (TRPM2) is a calcium-permeable, nonselective cation channel that responds to reactive oxygen species (ROS), which are found in the tumor microenvironment and are important regulators of tumorigenesis, cell proliferation, apoptosis, and the therapeutic response. Here, we used immunohistochemical analysis of tumor tissue derived from patients with ESCC to find that the TRPM2 channel protein expression level was increased in tumor tissue compared with adjacent normal tissue. Intracellular calcium concentration measurements, western blotting, and ROS and cell viability assays were used with a human ESCC cell line (TE-1 cells) to find that TRPM2 participated in the ROS hydrogen peroxide-induced increase in intracellular calcium. This increased calcium inhibited cell proliferation and enhanced apoptosis. Pretreatment of cells with the anticancer agent 5-fluorouracil (5-FU) significantly increased ROS production, which potentiated TRPM2-mediated calcium signaling, decreased cell proliferation, and increased apoptosis in TE-1 cells, suggesting that the therapeutic effect of 5-FU in ESCC cells may be mediated by the TRPM2 channel-mediated calcium influx. These findings offer a potential treatment target and provide mechanistic insight into the therapeutic effects of 5-FU in patients with ESCC.

The prediction method plays crucial roles in the accurate prediction of rockfall runout range which could improve the protection of endangered residential areas and infrastructure. Recently, the Knearest neighbor (KNN) algorithm, one of many machine learning techniques, showed good performance in pattern classification. Therefore, the aim of this study was to use the K-nearest neighbor (KNN) algorithm to predict the rockfall runout range which is classified into different subintervals according to the distance from the slope toe. First, we proposed the prediction model of the rockfall runout range based on our improved KNN algorithm which could better offer robustness against different choices of the neighborhood size k, and it is the first work of applying our improved KNN algorithm to rockfall runout range prediction. Second, the shaking table tests of rockfall runout models were conducted for simulating the rockfall process, and the influence laws of factors-including types of an earthquake, peak ground acceleration, vibration frequency, slope angle, slope height, and block mass and block shape-on rockfall distance are investigated. Finally, there is a discussion of the performance of our proposed prediction model based on our improved KNN algorithm in the prediction of rockfall runout range. The extensive experimental results for rockfall runout range prediction demonstrate the effectiveness of our proposed prediction model.

An accurate slope prediction model is important for slope reinforcement before the disaster. The k-nearest neighbor (KNN) algorithm, as a simple and effective nonparametric machine learning method, is widely applied in classification recognition. In our study, the k-nearest neighbor (KNN) algorithm is improved to reduce its sample dependence and improve the robustness of the algorithm, and then the prediction model of the slope stability is proposed based on the improved k-nearest neighbor (KNN) algorithm. Extensive experimental results show that our proposed prediction model achieves high prediction performance in this regard. Moreover, a comparison between our proposed prediction model and the finite element method, which is the classical theoretical method of slope stability, was made, which will provide an important approach to predicting the slope stability for slope engineering. Finally, shaking table test of a slope model is conducted to evaluate whether the slope is stable or not, and the experimental results are in good agreement with the prediction results of our proposed prediction model, which further demonstrates its effectiveness.

Plasma-activated solution has attracted more attention in the food industry due to no chemical residue and good bacteriostatic properties. This study aimed to evaluate the effects of plasma-activated hydrogen peroxide solution (PAH) on the morphophysiology of Staphylococcus aureus biofilms. PAH was prepared using dielectric-barrier-discharge plasma and incubated with S. aureus biofilms for 0–40 min. Changes in biofilm morphophysiology were evaluated with laser scanning confocal microscopy, electron microscopic images, reactive oxygen species (ROS) content, metabolic capacity, and 1% agarose gel. Results indicated that the population of S. aureus in the biofilms was reduced by 4.04-log after incubation with PAH for 30 min. The thickness and metabolic capacity of biofilms were decreased, the ROS content and DNA fragments of bacteria increased after PAH treatments. Data suggested that PAH treatments significantly destroyed the morphophysiology of S. aureus (ATCC 6538) biofilms and could be considered as a valuable anti-biofilm technology to reduce foodborne pathogens on food and/or in food facilities.

This study aimed to investigate effects of plasma-activated solution (PAS) on the cell biology of Staphylococcus aureus and qualities of fresh lettuce leaves. PAS was prepared by dielectric barrier discharge plasma and incubated with S. aureus for 10–30 min or with lettuces for 10 min. Effects on cell biology were evaluated with microscopic images, cell integrity, and chemical modification of cellular components. Effects on lettuce quality were estimated with the viable microbial counts, color, contents of vitamin C and chlorophyll, and surface integrity. PAS reduced S. aureus population by 4.95-log and resulted in increased cell membrane leakage. It also resulted in increased contents of reactive oxygen species in cells, C=O bonds in peptidoglycan, and 8-hydroxydeoxyguanosine content in cellular DNA, and reduced ratios of unsaturated/saturated fatty acids in the cell membrane. PAS treatment reduced bacterial load on fresh lettuce and had no negative effects on the quality. Data suggest that PAS can be used for the disinfection of ready-to-eat fresh vegetables.

The hybrid excitation synchronous motor (HESM), which aim at combining the advantages of permanent magnet motor and wound excitation motor, have the characteristics of low-speed high-torque hill climbing and wide speed range. Firstly, a new kind of HESM is presented in the paper, and its structure and mathematical model are illustrated. Then, based on a space voltage vector control, a novel flux-weakening method for speed adjustment in the high speed region is presented. The unique feature of the proposed control method is that the HESM driving system keeps the q-axis back-EMF components invariable during the flux-weakening operation process. Moreover, a copper loss minimization algorithm is adopted to reduce the copper loss of the HESM in the high speed region. Lastly, the proposed method is validated by the simulation and the experimental results.

Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS) algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP) TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.

A study was conducted to determine the effect of dielectric barrier discharge non-thermal plasma (DBD-NTP) on Salmonella typhimurium and Staphylococcus aureus populations on solid surfaces and in liquid suspensions. Our results showed that inactivation kinetics of S. typhimurium and S. aureus by DBD-NTP treatments can be well predicted with mathematical models. The survival curves of both S. typhimurium and S. aureus showed a log-linear phase followed by tailing behaviors on solid surfaces, and shoulder behaviors followed by a log-linear phase in liquid suspensions. The D values (decimal reduction time) for S. typhimurium and S. aureus in suspension were higher than those on solid surfaces (p < 0.05). Additionally, the maxima of sublethal injury values under low NaCl concentration and neutral pH condition were higher than those under high NaCl and low pH condition. In addition, mathematical modeling was evaluated to predict the final inactivation result for potential industrial applications. This study indicates that different microbial supporting matrices significantly influence the inactivation effect of DBD-NTP; it also provides useful information for future applications of NTP in enhancing food shelf life and safety.

This paper presents an effective local image feature region descriptor, called CLDTP descriptor (Compact Local Directional Texture Pattern), and its application in image matching and object recognition. The CLDTP descriptor encodes the directional and contrast information in a local region, so it contains the gradient orientation information and the gradient magnitude information. As the dimension of the CLDTP histogram is much lower than the dimension of the LDTP histogram, the CLDTP descriptor has higher computational efficiency and it is suitable for image matching. Extensive experiments have validated the effectiveness of the designed CLDTP descriptor.