Index Variables Research Articles

Does Political Instability cause and affect Macroeconomic instability in Pakistan?

This study is intended to examine the cause and effect of political instability on macroeconomic instability in Pakistan over the period of 1993-2023. As the nature of the data is time series therefore stationarity testing is necessary and ADF and PP tests are used for the said purpose. ARDL is employed to tests the required impact and granger causality to get the required objective. Result of the ARDL model reported that Inflation rate and Unemployment rate negatively and significantly influenced Political stability in long-run. Besides this, ECM is applied for short run effect. ECM’s result shows that Unemployment rate, Exchange rate, and Current account balance negatively and significantly influence Political stability in short-run. In the second model, the impact of Political stability variables employed Political stability & absence of terrorism, Voice & accountability, Regulation Quality, and Government Effectiveness on Macroeconomic instability. ARDL model result indicated that Political stability & absence of terrorism, Voice & accountability, and Government effectiveness have negative and significant impact on macroeconomic crisis index. Bound test result shows long-run relationship existence among variables. Besides this, ECM model shows that Political stability & absence of terrorism, Voice & accountability, Regulation Quality, and Government Effectiveness negatively and significantly influence macroeconomic instability. Beside this granger causality test was applied to test causal relationships among variables. The test found that Macroeconomic instability unidirectional granger cause Political stability significantly. Furthermore, Political variables index and Inflation rate show bidirectional causality. Unemployment rate unidirectional causes Political variables index. Similarly, current account balance is unidirectional granger causal political index. On the other hand, only Voice & accountability shows unidirectional causal relationship with Economic variables index.

Bioinformatic analysis constructs an optimal prognostic index for survival-related variables (OPISV) based on whole-genome expression data in Glioblastoma

PurposeUsing clinical information and transcriptomic sequencing data from glioblastoma (GBM) patients in the TCGA database to perform gene-by-gene analysis that is aligned with individual patient characteristics and develop an optimal prognostic index of survival-related variables (OPISV) through iterative machine learning techniques to predict the prognosis of GBM patients. Study designThe TCGA dataset was utilized as the training dataset, while two GEO datasets served as independent validation cohorts. Initially, survival analysis (p < 0.001***), differential gene expression analysis (p < 0.05*), and univariate Cox regression analysis (p < 0.05*) were employed to identify genes that are highly correlated with patient prognosis and exhibit significant differences in survival status. Subsequently, incorporating the non-excludable variable of age, a multivariate Cox regression analysis was performed in a stepwise manner to construct the OPISV. Finally, logistic and LASSO regressions were used to validate the association between the identified genes and patient survival. The OPISV performance is evaluated and its potential mechanisms are explored. ResultsAge, CTSD, PTPRN, PTPRN2, NSUN5, DNAJC30 and SOX21 emerged as the optimal variables through multivariate Cox regression iterations. Further analysis characterized Age, PTPRN and DNAJC30 as independent prognostic risk factors for constructing OPISV, which is validated with external GEO datasets and GEPIA database. In OPISV_high populations, significantly upregulated GABAergic synapse function was exposed. Differential genes identified from gene clustering of the GABAergic synapse pathway and gene module highly correlated with GABAergic synapse in the WGCNA analysis are pointing unequivocally to the glioma progress. ConclusionOPISV is feasible for predicting patient survival, as it may serve as a potential mechanism underlying the involvement of GABAergic synapses in the progression of GBM.

Maturity Level Framework ITIL V3 dalam Mengukur Kepuasan Mahasiswa Terhadap Web Student Universitas Amikom Purwokerto

In this era of globalization, technology increasingly influences education. Students of Amikom University Purwokerto use Web Student to access academic information such as schedules and grades. Although educational technology is developing, challenges in meeting student needs still exist. Evaluation is needed to assess the effectiveness of Web Student, especially in user satisfaction. This study uses ITIL Version 3 in the service operation domain, with a Likert scale-based questionnaire to 60 respondents to measure the maturity level. The results of the maturity level include: event management 2.90, incident management 2.45, problem management 2.13, request fulfillment 2.24, and access management 3.18. Overall, the average index of all questionnaire results variables obtained was 2.58, which is on a scale of 3 out of 5 maturity levels, namely defined.

Knee muscle strength, body composition, and balance performance of youth soccer players

BackgroundMuscle strength and balance abilities have been related to game performance injury prevention. This study aimed to (1) assess knee muscle strength performance based on intra- and inter-limb asymmetries, (2) investigate the relationships between knee muscle strength, body composition, and balance, and (3) analyze the variance in the overall stability index (OSI) explained by knee muscle strength indicators after controlling for age and body composition.MethodsThe sample included 104 young male soccer players (16.0 ± 1.6 years). Body composition, knee muscle strength, and balance ability were assessed. A paired samples t-test was used to examine differences between the preferred leg (PL) and the non-preferred leg (NPL). Pearson correlations and hierarchical multiple regression were conducted to explore the relationships between strength, body composition, and balance.ResultsNo significant inter-limb asymmetries were detected for the knee flexors (KF) and knee extensors (KE) performance. The hamstrings-to-quadriceps ratio does not suggest the existence of intra-limb asymmetries (p = 0.06). Significant and negative correlations were found between KF (r = -0.38, p ≤ 0.01) and KE (r = -0.58, p ≤ 0.01) for the PL. Concerning the NPL, KE also revealed a significant and negative relationship with balance (r = -0.30, p ≤ 0.01). Significant and positive relationships were found between bodyweight, fat-free mass, and balance. After controlling for age and body composition, knee muscle strength could explain between 13% and 30% of the variance observed in the OSI (NPL and PL, respectively).ConclusionsThe results underline knee muscle strength as an important predictor of balance. Thus, training programs targeting knee muscle strength development should be considered during the season periodization by coaches and their staff throughout the players’ developmental stages.

Temporal geometric mapping defines morphoelastic growth model of Type B aortic dissection evolution

The human aorta undergoes complex morphologic changes that mirror the evolution of disease. Finite element analysis (FEA) enables the prediction of aortic pathologic states, but the absence of a biomechanical understanding hinders the applicability of this computational tool. We incorporate geometric information from computed tomography angiography (CTA) imaging scans into FEA to predict a trajectory of future geometries for four aortic disease patients. Through defining a geometric correspondence between two patient scans separated in time, a patient-specific FEA model can recreate the deformation of the aorta between the two time points, showing that pathologic growth drives morphologic heterogeneity. FEA-derived trajectories in a shape-size geometric feature space, which plots the variance of the shape index versus the inverse square root of aortic surface area (δS vs. AT−1), quantitatively demonstrate an increase in δS. This represents a deviation from physiologic shape changes and parallels the true geometric progression of aortic disease patients.

Predicting the Dry Season Habitat Occupancy of African Savannah Elephant Using Vegetation Indices and Modelling Landscape Variability in a Mesic Protected Area

ABSTRACTAfrican savannah elephants (Loxodonta africana) are key ecosystem engineers that migrate over large spatiotemporal scales foraging as they require copious amounts of food and water across habitable landscapes. Therefore a need to understand movement patterns arises in relation to vegetation type and landscape variability, moreso in forage depauparate arid areas such as Gonarezhou National Park (GNP) in Zimbabwe. The objectives of this study were to: (i) assess the performance of vegetation indices in modelling the distribution of African savannah elephants, and (ii) model future landscape variability in Gonarezhou National Park (GNP) in Zimbabwe. Maximum entropy (MaxEnt) algorithm was used to explore the relationship between vegetation indices and distribution of African savannah elephants in the GNP. The Soil Adjusted Vegetation Index (SAVI) performs better relative to other indices in modelling the distribution of African savannah elephants across all habitat types in the GNP. Cellular automata‐Artificial Neural Network (CA‐ANN) showed a significant future decrease (Kruskal Anova; p &lt; 0.05) in landscape suitable to sustain large populations of African savannah elephants in the GNP by the year 2083. Future remote sensing reveals directional insights into the future consequences of current landscape management for African savannah elephant conservation which is a crucial in the sustainability of climate threatened arid protected areas such as the GNP.

Linkage of El Niño-Southern Oscillation to astronomic forcing

Abstract Deciphering the causes of El Niño-Southern Oscillation (ENSO) represents one of the greatest scientific and societal challenges because ENSO impacts people’s safety, food, water, health, and economy. Traditionally, ENSO has been considered a phenomenon that is mostly influenced by the interactions between oceanic and atmospheric processes, i.e. by the internal variability in Earth’s ocean-atmosphere system. However, dendrochronological records of climate indices, ENSO among them, have statistically significant variance at periodicities related to solar activity (sunspots) and lunar precessions. Other studies indicate a modulation by the lunar nodal cycle of ocean’s mixing and its implications on water and air temperatures, steric sea levels, coastal flooding, rain, river discharge and heat transport. Those findings suggest that astronomic forces may influence ENSO. In fact, this study shows that a fit to well-established periodicities from lunar precessions, solar activity and their interactions explains 91% of the variance of an ENSO index smoothed at 5 years, and 67% of a 3 yr filtered ENSO index. Provided that the future Earth’s ocean-atmospheric system remains roughly within historical bounds under a changing climate in the next 2–3 decades, one can venture a projection into the future of 3- and 5 yr smoothed ENSO variability. Such projection is given here and might help in preparations for adaptation and mitigation measures caused by ENSO-related coastal hazards.

Alpha band oscillations in common synaptic input are explanatory of the complexity of isometric knee extensor muscle torque signals.

We investigated whether the strength of oscillations in common synaptic input was explanatory of knee extensor (KE) torque signal complexity during fresh and fatigued submaximal isometric contractions, in adults aged from 18 to 90years. The discharge times of motor units were derived from the vastus lateralis muscle of 60 participants using high-density surface EMG, during 20s isometric KE contractions at 20% of maximal voluntary contraction, performed before and after a fatiguing repeated isometric KE contraction protocol at 60% of maximal voluntary contraction. Within-muscle coherence Z-scores were estimated using frequency-domain coherence analysis, and muscle torque complexity was assessed using multiscale entropy analysis and detrended fluctuation analysis. Alpha band (5-15Hz) coherence was found to predict 23.1% and 31.4% of the variance in the complexity index under 28-scales (CI-28) and detrended fluctuation analysis α complexity metrics, respectively, during the fresh contractions. Delta, alpha and low beta band coherence were significantly increased due to fatigue. Fatigue-related changes in alpha coherence were significantly predictive of the fatigue-related changes in CI-28 and detrended fluctuation analysis α. The fatigue-related increase in sample entropy from scales 11 to 28 of the multiscale entropy analysis curves was significantly predicted by the increase in the alpha band coherence. Age was not a contributory factor to the fatigue-related changes in within-muscle coherence and torque signal complexity. These findings indicate that the strength of alpha band oscillations in common synaptic input can explain, in part, isometric KE torque signal complexity and the fatigue-related changes in torque signal complexity.

Hiddenly degrading performance prognosis based on recursive model incorporating double-layer rolling optimization strategy

An integrated and adaptive prognostic framework is proposed for hiddenly degrading actuator in the closed-loop system. Furthermore, the dual influence of degradation progress and operation time is considered in the established augmented model. It is important to obtain accurate and real-time distribution of degradation information under different degradation progress. Firstly, the expectation and variance of hidden index, unknown operation time parameter and degradation progress parameter are evaluated by designing a double-layer rolling optimization strategy. Then, the uncertainty distribution of degradation model is iteratively derived by employing Bayesian theorem. Finally, the distribution of remaining useful life (RUL) is calculated based on available distribution of degradation model and states. The effectiveness of proposed algorithm is demonstrated by a mold model of continuous casting driven by servo motor.

Genetic association of FTO gene polymorphisms with obesity and its related phenotypes: A case-control study.

FTO gene belongs to the non-heme Fe (II) and 2 oxoglutarate-dependent dioxygenase superfamily. Polymorphisms within the first intron of the FTO gene have been examined across various populations, yielding disparate findings.The present study aimed to determine the impact of two intronic polymorphisms FTO 30685T/G (rs17817449) and -23525T/A (rs9939609) on the risk of obesity in Punjab, India. Genotypic and biochemical analysis were done for 671 unrelated participants (obese=333 and non-obese=338) (age≥18 years). Genotyping of the polymorphisms was done by PCR-RFLP method. However, 50% of the samples were sequenced by Sanger sequencing. Both the FTO variants 30685 (TT vs GG: odds ratio (OR), 2.30; 95% confidence interval (CI), 1.39-3.79) and -23525 (TT vs AA: odds ratio (OR), 2.78; 95% confidence interval (CI), 1.37-5.64) showed substantial risk towards obesity by conferring it 2 times and 3 times, respectively. The analysis by logistic regression showed a significant association for both the variants 30685T/G (rs17817449) and -23525T/A (rs9939609) (OR=2.29; 95%CI: 1.47-3.57) and (OR=5.25; 95% CI: 2.68-10.28) under the recessive genetic model, respectively. The haplotype combination TA (30685; -23525) develops a 4 times risk for obesity (P=0.0001). Among obese, the G allele of 30685T/G and A- allele of -23525T/A showed variance in Body mass index (BMI), waist circumference (WC), waist-to-height ratio(WHtR), systolic blood pressure (SBP), diastolic blood pressure (DBP) and triglyceride(TG). The present investigation indicated that both the FTO 30685T/G (rs17817449) and -23525T/A (rs9939609) polymorphisms have a key impact on an individual's vulnerability to obesity in this population.

Unbiased estimation of sampling variance for Simpson's diversity index.

Quantification of measurement uncertainty is crucial for robust scientific inference, yet accurate estimates of this uncertainty remain elusive for ecological measures of diversity. Here, we address this longstanding challenge by deriving a closed-form unbiased estimator for the sampling variance of Simpson's diversity index. In numerical tests the estimator consistently outperforms existing approaches, particularly for applications in which species richness exceeds sample size. We apply the estimator to quantify biodiversity loss in marine ecosystems and to demonstrate ligand-dependent contributions of T-cell-receptor chains to specificity, illustrating its versatility across fields. The novel estimator provides researchers with a reliable method for comparing diversity between samples, essential for quantifying biodiversity trends and making informed conservation decisions.

A Patient-Specific Morphoelastic Growth Model of Aortic Dissection Evolution.

The human aorta undergoes complex morphologic changes that indicate the evolution of disease. Finite element analysis enables the prediction of aortic pathologic states, but the absence of a biomechanical understanding hinders the applicability of this computational tool. We incorporate geometric information from computed tomography angiography (CTA) imaging scans into finite element analysis (FEA) to predict a trajectory of future geometries for four aortic disease patients. Through defining a geometric correspondence between two patient scans separated in time, a patient-specific FEA model can recreate the deformation of the aorta between the two time points, showing pathologic growth drives morphologic heterogeneity. A shape-size geometric feature space plotting the variance of the shape index versus the inverse square root of aortic surface area (δ𝒮 vs. ) quantitatively demonstrates the simulated breakdown in aortic shape. An increase in δ𝒮 closely parallels the true geometric progression of aortic disease patients.

Surgical Extraction of Mandibular Third Molars: Risk Assessment and Predictable Complexity

Objective. The study aims to develop and validate new practical and simple but robust index to determine the complexity level of surgical extraction of mandibular third molars (MTM). Methods. A cross-sectional study with sample of 100 patients referred for management of MTM. Complexity index scores recorded twice at 6 weeks intervals preoperatively by oral and maxillofacial specialist. Prediction of the surgical difficulty and the degree of agreement of different variable indexes were calculated. Results. Out of 100, 78 patients with 139 impacted MTM, 26 were males and 52 were female, with a mean age of 26.40±6.39 years (range, 18-45 years). The prediction of operative difficulty was significant as measured by impaction angulation, distance to ramus, and impaction depth. Most cases were classified as complexity level II (63 [80%]). Although only 3 out of 100 cases (4%) were classified as complexity level III. There was no significant difference in age based on the gender (male: 27.54±7.35 years, female: 25.83±5.86 years; P=0.268). Conclusion. Using MTM complexity index as a preoperative tool to evaluate the surgical difficulty, including different patient-specific variables could facilitate treatment planning, help prevent complications and assess the possibility of referral.

Identification of Novel Loci Precisely Modulating Pre-Harvest Sprouting Resistance and Red Color Components of the Seed Coat in T. aestivum L.

The association between pre-harvest sprouting (PHS) and seed coat color has long been recognized. Red-grained wheats generally exhibit greater PHS resistance compared to white-grained wheat, although variability in PHS resistance exists within red-grained varieties. Here, we conducted a genome-wide association study on a panel consisting of red-grained wheat varieties, aimed at uncovering genes that modulate PHS resistance and red color components of seed coat using digital image processing. Twelve loci associated with PHS traits were identified, nine of which were described for the first time. Genetic loci marked by SNPs AX-95172164 (chromosome 1B) and AX-158544327 (chromosome 7D) explained approximately 25% of germination index variance, highlighting their value for breeding PHS-resistant varieties. The most promising candidate gene for PHS resistance was TraesCS6B02G147900, encoding a protein involved in aleurone layer morphogenesis. Twenty-six SNPs were significantly associated with grain color, independently of the known Tamyb10 gene. Most of them were related to multiple color characteristics. Prioritization of genes within the revealed loci identified TraesCS1D03G0758600 and TraesCS7B03G1296800, involved in the regulation of pigment biosynthesis and in controlling pigment accumulation. In conclusion, our study identifies new loci associated with grain color and germination index, providing insights into the genetic mechanisms underlying these traits.

Propagation characteristics of the Bessel-Gaussian beams in turbulent plasma sheath surrounding the hypersonic aerocraft

To investigate the transmission characteristics of the Bessel-Gaussian beams in a turbulent plasma sheath, the flow field around a hypersonic vehicle is numerically simulated and analyzed according to the Navier-Stokes (N-S) equation and turbulence model. Then, utilizing the characteristics of the thickness of the plasma flow field around the supersonic vehicle at the centimeters level, the double fast Fourier transform (D-FFT) algorithm based on the Fresnel diffraction integral is used for the first time to predict the propagation characteristics of the Bessel-Gaussian beams in the turbulent plasma sheath. The results show that the lower the height and the higher the velocity, the smaller the thickness of the plasma sheath shock layer. The refractive index variance, the wavelength and the waist-radius are essential factors affecting the transmission quality of the Bessel-Gaussian beams. When compared to the Gaussian beams, the Bessel-Gaussian beams have smaller drift and scintillation index, which have the advantage in suppressing turbulence.

Monitoring spatial tree diversity indices using relascope sampling: Estimators, interactions and limitations

With ongoing climate change the monitoring of tree diversity has become very important for avoiding or at least decelerating the loss of biodiversity and for maintaining forest ecosystem resilience. As part of such monitoring, spatial indices of tree diversity which are calculated for individual trees often serve as surrogates for more direct measures of biodiversity. Mainly for its efficiency and ease of application, relascope sampling is a widespread method applied in forest inventory of many countries and thus has often been suggested as a data source for the monitoring of tree diversity. Since the interaction between sampling design and spatial diversity indices is not always clear to data analysts, we reviewed existing estimators and experimentally examined a new one, conducted extensive sampling simulations using different indices and estimators and additionally analysed the data from a large-scale forest inventory in Austria. We found that both forest structure and index algorithm greatly influence the sampling error. The largest source of sampling error was the index variance and contrary to our expectation not so much the bias due to spatial effects. For diversity indices related to distances, it has turned out to be best to apply estimators that include spatial edge correction methods. For all other indices an estimator performed better that included information on both the sample trees and their nearest neighbours, as it much reduced overall index variance. However, if possible the plus-sampling edge correction method should be applied.

Analysis of the Relationship Between Cross Capital Flows and Stock Exchange Index with Machine Learning

This paper investigates forecasting the BIST100 stock index using cross-capital flow analysis. It employs feature engineering and the Orthogonal Matching Pursuit (OMP) model to navigate the intricacies of financial time series prediction. The study meticulously selects features such as lagged values, moving averages, and volatility metrics, normalized to ensure unbiased model impact. The OMP model is carefully optimized to handle the dimensionality of financial data, avoiding overfitting through a sparsity constraint. This approach yields an R-squared score of 0.88, indicating a solid capability to capture index variance. Visual comparisons between actual and predicted values further validate the model's accuracy. The paper highlights the importance of methodological precision in developing models capable of discerning complex patterns, offering valuable insights for investment strategies. Implications of the study show that cross-capital movements and macroeconomic variables are a good fit with ML to predict the Stock Market despite the complexity of financial markets.

The role of physical activity on obstructive sleep apnea severity and hypoxic load, and the mismatch between subjective and objective physical activity assessments.

Obesity is the primary risk factor for the development of obstructive sleep apnea, and physical inactivity plays an important role. However, most studies have either only evaluated physical activity subjectively or objectively in obstructive sleep apnea. The objectives of this study were: (i) to assess the relationship between obstructive sleep apnea severity (both apnea-hypopnea index and desaturation parameters) and both objectively and subjectively measured physical activity after adjustment for anthropometry and body composition parameters; and (ii) to assess the relationship between objective and subjective physical activity parameters and whether obstructive sleep apnea severity has a modulatory effect on this relationship. Fifty-four subjects (age 47.7 ± 15.0 years, 46% males) were categorized into groups according to obstructive sleep apnea severity: no obstructive sleep apnea; mild obstructive sleep apnea; and moderate-to-severe obstructive sleep apnea. All subjects were evaluated with subjective and objective physical activity, anthropometric and body composition measurements, and 3-night self-applied polysomnography. A one-way ANOVA was used to evaluate the differences between the three obstructive sleep apnea severity groups and multiple linear regression to predict obstructive sleep apnea severity. Differences in subjectively reported sitting time (p ≤ 0.004) were found between participants with moderate-to-severe obstructive sleep apnea, and those with either mild or no obstructive sleep apnea (p = 0.004). Age, body mass index and neck circumference explained 63.3% of the variance in the apnea-hypopnea index, and age, body mass index and visceral adiposity explained 67.8% of the variance in desaturation parameters. The results showed that the person's physical activity does not affect obstructive sleep apnea severity. A weak correlation was found between objective and subjective physical activity measures, which could be relevant for healthcare staff encouraging patients with obstructive sleep apnea to increase their physical activity.

Spatial Fluctuations of Optical Turbulence Strength in a Laboratory Turbulence Simulator

Controlled turbulence simulators in the laboratory have been extensively employed to investigate turbulence effects on light propagation in the atmosphere, driven by some advanced optical engineering such as remote sensing, energy-delivery systems, and free-space optical communication systems. Many studies have achieved rich results on the optical turbulence intensity, scintillation index, and power spectral density characteristics of the light propagation path in the center of a turbulence simulator, but a comprehensive analysis of the optical turbulence characteristics for different spatial locations is still lacking. We simulate turbulence with air as the medium in a classical convective Rayleigh–Bénard turbulence simulator through high-resolution computational fluid dynamics methods, the three-dimensional refractive index distribution is obtained, and the optical properties are analyzed comprehensively. It is found that the hot and cold plumes and the large-scale circulation strongly influence the inhomogeneity of Cn2 in the turbulence tank, making it weak in the middle and strong near the boundary. The refractive index power spectral density at different heights is centrally symmetric, with the slope gradually deviating from the −5/3 scaling power with increasing distance from the central region. Under the log-log plot, the variation of the refractive index variance with height exhibits a three-segmented feature, showing in order: a stable region, a logarithmic profile, and a power-law profile, in the region close to the boundary. These results will contribute to the construction of a suitable turbulence simulator for optical engineering applications.

The effectiveness of acceptance and commitment therapy (ACT) on neurotic perfectionism and internalized self-criticism in neurotic perfectionist girls: A single-case experimental study

Introduction: Neurotic perfectionism has a variety of psychological consequences that should be considered in psychotherapy applications. Aim: The present study aimed to examine the effectiveness of acceptance and commitment therapy (ACT) on neurotic perfectionism and internalized self-criticism in neurotic perfectionist girls. Method: This study was conducted using a single-case quasi-experimental design with, concurrent multiple baseline. The research population consisted of neurotic perfectionist girls visiting counseling centers in Ahvaz in 2022. The participants were a sample of 5 girls selected using purposive sampling with a minimum cut-off score of 145 in the Neurotic Perfectionism Questionnaire (NPQ). The acceptance and commitment therapy (ACT) (Twohig &amp; et al, 2021) was implemented in eleven 90-minute sessions. The participants completed the Neurotic Perfectionism Questionnaire (1994), and the Levels of Self-Criticism Scale (2004). The data were collected in three baseline, intervention, and three-month follow-up phases and analyzed using reliable change index (RCI), recovery percentage, and visual inspection. Results: The analysis of the recovery percentage showed the participants’ neurotic perfectionism 17.67 and internalized self-criticism 19.73 improved in the intervention phase and their neurotic perfectionism 36.25 and internalized self-criticism 49.90 increased in the follow-up phase. Moreover, the reliability change index of both variables in the post-treatment and follow-up phases was significant (P=0.05). Conclusion: Considering the effectiveness of acceptance and commitment therapy in reducing neurotic perfectionism and internalized self-criticism by increasing psychological flexibility, this therapy can be used as an intervention method in neurotic perfectionist girls.