Predicting Age and Gender in Author Profiling: AMulti-Feature Exploration

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,etc.However, the research on RomanUrdu is not up to the mark.Hence, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.

Molecular Profiling of Sugarcane Wine, a Traditional Fermented Beverage (Loungouila) from Madingou

A number of studies reported that traditional fermented beverages possessed pharmaceutical biomolecules involved in biocatalysis for good therapeutic effects on various pathology including tumor, diabetes, inflammation, and obesity. This dimension of understanding is the prerogative of the biomolecular profile found in these fermented foods and beverages. The current work aimed to study the postfermentation molecular profile of the Congolese fermented beverage (Lougwila). The determination of pH, the acidity titratable, the distillation of sugar cane, the determination of total polyphenols and flavonoids and the matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) have been used. As results, the fermenting sugar cane juice at room temperature for a period of seven days, leading to a decrease of the pH value to 4.25 ± 0.10 and increase in titratable acidity and alcohol content of at least 6.421 g/L (w/v) and 7% respectively. The polyphenol concentration of Loungouila increase from 14.9 to 20.5 mg Eq AG/g Ms after 10 days of fermentation. The flavonoid concentration varies from 1.70 to 5.22 mg Eq Cat/g Ms. among 46 isolates of Bacillus species, 55% (25/45) were able to show a very interesting clear zones in terms of cellulolytic activity with the percentage ranging from 37.3% to 83.9%, and 41.3% of amylolytic activity for the percentage ranging from 52.02% to 75%. 65.21% (30/46) of the isolates tested were found to be positive by the caseinolytic test with zones of inhibition ranging in diameter from 1.10 ± 0.09 to 3.25 ± 0.07 cm. In addition to the determination of biomolecule profile, 34.78% (16/46) of Bacillus isolates were able to produce biosurfactants with percentages ranging from 14% to 100%. Proteomic profiling of Loungouila has been investigated by using MALDI-TOF Technique. Short sequences showed 100% identity and were associated with AprE, SubC, amyE, NprE, CelA, lytF, Mut, and ykfC proteins. The National Center for Biotechnology Information (NCBI) allowed to associate short sequences to Bacillus species.

Depth profiling of arsenian pyrite in Carlin-type ores through wet chemistry

Enrichment of As and Au at the overgrowth rims of arsenian pyrite is a distinctive feature of Carlin-type gold ores.Revealing distribution of such key elements in high resolution is of fundamental importance yet often proves challenging.In this study,repeated non-oxidative acid etching of ore samples from Shuiyindong gold deposit was applied to enable elemental depth profiling of goldbearing arsenian pyrite grains.ICP-OES and AAS were used to determine the dissolved Fe,As,and Au concentrations in each of the etching solutions,and XPS was carried out to exam the etched mineral surfaces.In contrast to conventional ion beam etching that may cause substantial sample damage,our acid etching method does not seem to significantly alter the composition and chemical state of the samples.The etched depths directly converted from the measured elemental concentrations can reproducibly reach a very high resolution of~1 nm,and can be conveniently controlled through varying the etching time.While the Fe and As depth profiles consistently reflect the surface oxidation property of arsenian pyrite,the Au profile displaying an obvious upward trend reveals the ore fluid evolution at the late stage of mineralization.Based on our experimental results,we demonstrate that our wet chemistry method is capable of effective depth profiling of gold ore and perhaps other geological samples,with advantages surpassing many instrumental techniques including negligible sample damage,nanoscale resolution as well as isotropic etching.

DMMIC derivatization-assisted liquid chromatography-mass spectrometry method for metabolite profiling of the glutathione anabolic pathway in esophageal cancer tissues and cells

In this work,a new pyrylium derivatization-assisted liquid chromatography-mass spectrometry(LC-MS)method was developed for metabolite profiling of the glutathione anabolic pathway(GAP)in cancer tissues and cells.The pyrylium salt of 6,7-dimethoxy-3-methyl isochromenylium tetrafluoroborate(DMMIC)was used to label the amino group of metabolites,and a reductant of dithiothreitol(DTT)was employed to stabilize the thiol group.By combining DMMIC derivatization with LC-MS,it was feasible to quantify the 13 main metabolites on the GAP in complex biological samples,which had good linearity(R^(2)=0.99810.9999),precision(interday precision of 1.6%e19.0%and intraday precision of 1.4%e19.8%)and accuracy(83.4%-115.7%).Moreover,the recovery assessments in tissues(82.5%e107.3%)and in cells(98.1%e118.9%)with GSH-^(13)C2,^(15)N,and Cys-^(15)N demonstrated the reliability of the method in detecting tissues and cells.Following a methodological evaluation,the method was applied successfully to investigate difference in the GAP between the carcinoma and para-carcinoma tissues of esophageal squamous cell carcinoma(ESCC)and the effect of p-hydroxycinnamaldehyde(CMSP)on the GAP in KYSE150 esophageal cancer cells.The results demonstrate that the developed method provides a promising new tool to elucidate the roles of GAP in physiological and pathological processes,which can contribute to research on drugs and diseases.

Thermal integrity profiling of cast-in-situ piles in sand using fiber-optic distributed temperature sensing

Defects in cast-in-situ piles have an adverse impact on load transfer at the pile‒soil interface and pile bearing capacity. In recent years, thermal integrity profiling (TIP) has been developed to measure temperature profiles of cast-in-situ piles, enabling the detection of structural defects or anomalies at the early stage of construction. However, using this integrity testing method to evaluate potential defects in cast-in-situ piles requires a comprehensive understanding of the mechanism of hydration heat transfer from piles to surrounding soils. In this study, small-scale model tests were conducted in laboratory to investigate the performance of TIP in detecting pile integrity. Fiber-optic distributed temperature sensing (DTS) technology was used to monitor detailed temperature variations along model piles in sand. Additionally, sensors were installed in sand to measure water content and matric suction. An interpretation method against available DTS-based thermal profiles was proposed to reveal the potential defective regions. It shows that the temperature difference between normal and defective piles is more obvious in wet sand. In addition, there is a critical zone of water migration in sand due to the water absorption behavior of cement and temperature transfer-induced water migration in the early-age concrete setting. These findings could provide important insight into the improvement of the TIP testing method for field applications.

三维薛定谔方程组的线性Profile分解

为了研究线性薛定谔方程组解Strichartz估计的紧性缺失问题,针对H•^(1)(R^(3))×H•^(1)(R^(3))中的三维线性薛定谔方程组的有界解向量序列,使用解序列的Profile分解方法,构造为解向量子列的(1/√h_(n))U(t-t_(n))/h_(n)^(2),(x-x_(n))/h_(n)类型的Profile分解和.其中,U是线性薛定谔方程组的解向量,在Strichartz范数估计下具有一个很小的余项.首先确定伸缩变换参数序列族,利用傅里叶变换和迭代的思想确定Profile分解族.其次验证了Profile分解和的收敛性,说明了Strichartz范数下余项的收敛性.最后证明了当线性薛定谔方程组的解序列有界时,都可以分解为解向量子列和的形式.

An efficient physics-guided Bayesian framework for predicting ground settlement profile during excavations in clay

Recently,the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly.However,updating the ground settlement profile,which is crucial for determining potential damage to nearby infrastructures,has received limited attention.To address this,this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile.The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly.Furthermore,the model is physically interpretable,which can provide valuable references for construction adjustments.The effectiveness of the proposed method is demonstrated through two field case studies,showing that it can yield satisfactory predictions for the settlement profile.

Neurocognitive Profile of People Living with Human Immunodeficiency Virus Initiating Treatment in Kinshasa in the Dolutegravir Era, Democratic Republic of Congo

Context: Antiretroviral therapies improve the prognosis of NeuroAIDS contrasting with a high frequency of Minor Neurocognitive Disorders (MND) even in aviremic subjects. Objective: The objective of this study is to present the neurological and cognitive profile of People Living with HIV (PLHIV) initiating antiretroviral treatment in Kinshasa in the era of Dolutegravir (DTG). Methods: This is a multicenter, cross-sectional study with a descriptive aim carried out in 16 HIV Outpatient Treatment Centers (OTC) in Kinshasa from October 4, 2021 to February 15, 2022. The International HIV Dementia Scale (IHDS) correlated with the Activities of Daily Living (IADL) scale facilitated the categorization of NeuroCognitive Disorders (NCD) of PLHIV evaluated after carrying out a summary neurological examination. Results: Of the 96 patients recruited, 56.3% were women with a sex ratio of 0.68. The average age was 40.1 ± 12.1 years. The secondary education level was the majority at 64.6%. Malaria (44.8%) and tuberculosis (32.3%) were more common as opportunistic infections. They were alcoholics in (30.2%). Their history was heart disease (15.6%), high blood pressure (18.8%);drug abuse (10.4%). The IHDS score was light in 55.2% of cases. The correlation between IHDS/IADL watches asymptomatic neurocognitive impairments (ANI) in 77.1%, almost all of subjects are found with normal overall functioning (94.8%) and a disturbed neurological examination in 53.1% of cases with a predominance of motor impairments in 79.1%. Conclusion: In view of these results, early and systematic screening of NCD and associated factors remains necessary in our context. .

Multi-circular formation control with reinforced transient profiles for nonholonomic vehicles:A path-following framework

This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the feature of spatial-temporal decoupling is devised for a group of vehicles guided by a virtual leader evolving along an implicit path,which allows for a circumnavigation on multiple circles with an anticipant angular spacing.In addition,notice that it typically imposes a stringent time constraint on time-sensitive enclosing scenarios,hence an improved prescribed performance control(IPPC)using novel tighter behavior boundaries is presented to enhance transient capabilities with an ensured appointed-time convergence free from any overshoots.The significant merits are that coordinated circumnavigation along different circles can be realized via executing geometric and dynamic assignments independently with modified transient profiles.Furthermore,all variables existing in the entire system are analyzed to be convergent.Simulation and experimental results are provided to validate the utility of suggested solution.

Profiles of the Headspace Volatile Organic and Essential Oil Compounds from the Tunisian Cardaria draba (L.) Desv. and Its Leaf and Stem Epidermal Micromorphology

In this work, we investigated aroma volatiles emanated by dry roots, stems, leaves, flowers, and fruits of Cardariadraba (L.) Desv. growing wild in Tunisia and its aerial part essential oils (EOs) composition. A total of 37 volatileorganic compounds (96.7%–98.9%) were identified;4 esters, 4 alcohols, 7 hydrocarbons, 12 aldehydes, 5 ketones,1 lactone, 1 organosulfur compound, 2 organonitrogen compounds, and 1 acid. The hydrocarbons form the maingroup, representing 49.5%–84.6% of the total detected volatiles. The main constituent was 2,2,4,6,6-pentamethylheptane(44.5%–76.2%) reaching the highest relative percentages. Forty-two compounds were determined in thetwo fractions of EOs, representing 98.8% and 97.2% of the total oil composition, respectively. The principal componentswere hexadecanoic acid (34.6%), 6-methyl-5-hepten-2-one (18.3%), decanal (15.0%), 6,10,14-trimethyl-2-pentadecanone (13.2%), and n-pentacosane (13%). Micromorphological details of the leaf and stem epidermisusing light microscopy revealed polygonal cells with sinuous walls in the adaxial and abaxial leaf surfaces andnearly rectangular and long ones with linear and thick walls for the stem epidermis. The stomata complexes wereanisocytic in the leaf epidermis and mainly anisocytic and rarely paracytic in the stem epidermis. Non-glandulartrichomes were unbranched and long with an acute apex or short with a convex apex. The glandular ones wereidentified for the first time in this species. They were short-stalked with a large secretory head. The highest stomatalindex (17.02%) was recorded in the abaxial leaf surface. The identification of headspace volatiles and essentialoil compounds can be used to characterize this species, and the various epidermis micromorphologicalfeatures are very useful for biosystematics taxonomic studies within Brassicaceae.

Radical Hysterectomy in Cervical Cancer: Patients’ Epidemiological and Clinical Profiles and Perioperative Outcome in Two Referral Hospitals in Cameroon

Background: Cervical cancer (CC) is one of the most frequent cancers and the leading cause of death from gynecological cancer in Low and middle income countries, Cameroon inclusive. Surgery is the primary treatment modality when the disease is diagnosed at early stage. Radical hysterectomy in cervical cancer has not been evaluated in recent years in Cameroon. The purpose of this study is thus to evaluate the epidemiological and clinical features and short term outcomes of patients who underwent surgery. Patients and methods: This retrospective study was conducted at the Douala Gynaeco-obstetric and Pediatric Hospital and the Douala General Hospital. Cervical cancer patients who underwent Radical hysterectomy between January 2015 and December 2020 were included. A pre-established data collection tool was used to record socio-demographic, clinical and outcomes information from patients’ files;additional outcome information was obtained from phone calls. Descriptive analysis was done using the SPSS version 26. Bivariate analysis was used to determine associations between disease and patients characteristics and occurrence of adverse postoperative outcome. P value of 0.05 was considered. Results: Sixty one patients were enrolled. Their ages ranged from 33 to 74 years with a mean age of 51.95 ± 10.29 years. Over 85% of women were married, 65.57% were unemployed and 86.88% were multiparous. Only 28% had never done cervical cancer screening. Most patients had stage IB1 to IB2 stage disease (57.1%). Less than 9% underwent radical hysterectomy and 8 of those (13.11%) suffered intraoperative complications. Twenty-five patients (40.98%) presented immediate and short term complications. There was no significant association between the disease or patients’ characteristics and adverse outcomes. Conclusion: Cervical cancer patients are relatively young in our settings and only 9% of them reach the hospital at early stage. Postoperative adverse outcomes rate is higher than that reported in the literature. Sensitization on screening and awareness of early symptoms can reverse the situation.

Metabolic profiles and morphological characteristics of leaf tips among different sweet potato(Ipomoea batatas Lam.)varieties

Sweet potato leaf tips have high nutritional value,and exploring the differences in the metabolic profiles of leaf tips among different sweet potato varieties can provide information to improve their qualities.In this study,a UPLC-Q-Exactive Orbitrap/MS-based untargeted metabolomics method was used to evaluate the metabolites in leaf tips of 32 sweet potato varieties.Three varieties with distinct overall metabolic profiles(A01,A02,and A03),two varieties with distinct profiles of phenolic acids(A20 and A18),and three varieties with distinct profiles of flavonoids(A05,A12,and A16)were identified.In addition,a total of 163 and 29 differentially expressed metabolites correlated with the color and leaf shape of sweet potato leaf tips,respectively,were identified through morphological characterization.Group comparison analysis of the phenotypic traits and a metabolite-phenotypic trait correlation analysis indicated that the color differences of sweet potato leaf tips were markedly associated with flavonoids.Also,the level of polyphenols was correlated with the leaf shape of sweet potato leaf tips,with lobed leaf types having higher levels of polyphenols than the entire leaf types.The findings on the metabolic profiles and differentially expressed metabolites associated with the morphology of sweet potato leaf tips can provide useful information for breeding sweet potato varieties with higher nutritional value.

Experimental study of core MHD behavior and a novel algorithm for rational surface detection based on profile reflectometry in EAST

Microwave reflectometry is a powerful diagnostic that can measure the density profile and localized turbulence with high spatial and temporal resolution and will be used in ITER,so understanding the influence of plasma perturbations on the reflect signal is important.The characteristics of the reflect signal from profile reflectometry,the time-of-flight(TOF)signal associated with the MHD instabilities,are investigated in EAST.Using a 1D full-wave simulation code by the Finite-DifferenceTime-Domain(FDTD)method,it is well validated that the local density flattening could induce the discontinuity of the simulated TOF signal and an obvious change of reflect amplitude.Experimental TOF signals under different types of MHD instabilities(sawtooth,sawtooth precursors and tearing mode)are studied in detail and show agreement with the simulation.Two new improved algorithms for detecting and localizing the radial positions of the low-order rational surface,the cross-correlation and gradient threshold(CGT)method and the 2D convolutional neural network approach(CNN)are presented for the first time.It is concluded that TOF signal analysis from profile reflectometry can provide a straightforward and localized measurement of the plasma perturbation from the edge to the core simultaneously and may be a complement or correction to the q-profile control,which will be beneficial for the advanced tokamak operation.

On the calibration of a shear stress criterion for rock joints to represent the full stress-strain profile

Conventional numerical solutions developed to describe the geomechanical behavior of rock interfaces subjected to differential load emphasize peak and residual shear strengths.The detailed analysis of preand post-peak shear stress-displacement behavior is central to various time-dependent and dynamic rock mechanic problems such as rockbursts and structural instabilities in highly stressed conditions.The complete stress-displacement surface(CSDS)model was developed to describe analytically the pre-and post-peak behavior of rock interfaces under differential loads.Original formulations of the CSDS model required extensive curve-fitting iterations which limited its practical applicability and transparent integration into engineering tools.The present work proposes modifications to the CSDS model aimed at developing a comprehensive and modern calibration protocol to describe the complete shear stressdisplacement behavior of rock interfaces under differential loads.The proposed update to the CSDS model incorporates the concept of mobilized shear strength to enhance the post-peak formulations.Barton’s concepts of joint roughness coefficient(JRC)and joint compressive strength(JCS)are incorporated to facilitate empirical estimations for peak shear stress and normal closure relations.Triaxial/uniaxial compression test and direct shear test results are used to validate the updated model and exemplify the proposed calibration method.The results illustrate that the revised model successfully predicts the post-peak and complete axial stressestrain and shear stressedisplacement curves for rock joints.

An improved algorithm based on equivalent sound velocity profile method at large incident angle

With the development of ultra-wide coverage technology,multibeam echo-sounder(MBES)system has put forward higher requirements for localization accuracy and computational efficiency of ray tracing method.The classical equivalent sound speed profile(ESSP)method replaces the measured sound velocity profile(SVP)with a simple constant gradient SVP,reducing the computational workload of beam positioning.However,in deep-sea environment,the depth measurement error of this method rapidly increases from the central beam to the edge beam.By analyzing the positioning error of the ESSP method at edge beam,it is discovered that the positioning error increases monotonically with the incident angle,and the relationship between them could be expressed by polynomial function.Therefore,an error correction algorithm based on polynomial fitting is obtained.The simulation experiment conducted on an inclined seafloor shows that the proposed algorithm exhibits comparable efficiency to the original ESSP method,while significantly improving bathymetry accuracy by nearly eight times in the edge beam.

Current Status of Key Competencies among Medical Students: A Latent Profile Analysis

The purpose of this study was to understand the overall level of key competencies of medical students and explore the potential profile of key competencies, promoting quality education, and improving the quality talent cultivation in medical colleges. A stratified random sampling method selected 734 medical students from four medical colleges in Chongqing Province of China. A general information questionnaire and a key competencies survey questionnaire were used to conduct the survey. The overall score and scores of each dimension of key competencies were analyzed. Latent profile analysis was conducted to classify the key competencies of medical students and compare the distribution differences of demographic variables among different categories. The results showed that 26% of medical students have never heard of the concept of key competencies, and 59% of them are not familiar with the content related to key competencies. The score of key competencies is 3.66 ± 0.60, with the highest score in the dimension of responsibility and the lowest score in the dimension of humanistic accomplishment. The latent profile analysis classified them into three categories: “low key competencies group (14.71%)”, “medium key competencies group (36.79%)”, and “high key competencies group (48.50%)”. The R3STEP regression analysis results showed statistically significant differences in educational level and whether they served as student cadres among different key competencies categories of medical students. This paper discusses three different potential key competencies categories among medical students, and the overall level of key competencies is relatively good. However, medical students lack a comprehensive and systematic understanding of key competencies. Humanistic accomplishment, healthy living, and practical innovation are the three dimensions with lower scores and should be given more attention. Medical colleges should integrate the concept of key competencies into teaching and implement it in medical practice to cultivate more high-quality medical talents for society.

监控广义线性Profile数据的变样本容量动态控制图

对于离散响应变量的profile数据,比如二元的、多项的、次序的和Poisson响应的profile,进行有效的监控越来越受到统计过程控制领域研究人员的关注。这些profile都可看作广义线性模型的特殊情况。本文提出了一种基于加权似然比检验的第二阶段的变样本容量动态控制图用来监控广义线性profile数据。不仅能增强对中小漂移的检测敏感度,还可以提高检测的速度, 降低抽样成本,提高企业统计决策的精确度和可靠度。通过平均运行长度来衡量控制图的性能表现,模拟结果表明,与静态控制图相比,所提出的控制图对于模型参数的变化有很好的监控能力。

lift⁃off制程PEB温度对负性光阻显影后截面Profile的影响

本文研究了lift⁃off(揭开-剥离)制程曝光后烘烤温度(post exposure bake,PEB)对负性光阻显影截面Profile(光刻胶结构)的影响。结果表明:在保留原有PEB盘面加热的方式前提下通过增加PEB盘盖加热功能进行烘烤,通过控制PEB盘面温度可调整光阻关键尺寸(critical dimension,CD)及截面Profile形貌,通过控制PEB盘盖加热可调整截面Profile光阻顶端形貌及强度,可显著改善负性光阻显影后截面Profile难以调整的问题。另外,不同的盘面温度、不同盘盖温度以及不同的显影时间相互配合,可以实现一种负性光阻产生不同截面光刻胶结构效果,可以实现同种光阻lift⁃off制程多样化。

A Corpus-Based Behavioral Profile Study of the Near-Synonyms: Serious, Severe, Grave, Grievous

Using Corpus of Contemporary American English as the source data,this paper carries out a corpus-based behavioral profile study to investigate four near-synonymous adjectives(serious,severe,grave,and grievous),focusing on their register and the types of nouns they each modify.Although sharing core meaning,these adjectives exhibit variations in formality levels and usage patterns.The identification of fine-grained usage differences complements the current inadequacies in describing these adjectives.Furthermore,the study reaffirms the effectiveness of the corpus-based behavioral profile approach in examining synonym differences.