Search

To assess the long-term stability of underground structures, it is crucial to understand the time-dependent behaviors of different rock types. Creep and stress relaxation are typical behaviors of generalized relaxation, which can explain temporal changes in rock stress and strain. In this study, generalized relaxation tests for Class I and Class II rocks were conducted to analyze their time-dependency behavior. A method was proposed for calculating the generalized relaxation modulus (GRM), which may be regarded as an extension of the stress relaxation modulus in linear rheological theory. Experimental results showed that GRM does not depend on α, and its value under uniaxial compression was larger than that under triaxial compression, indicating an obvious confining pressure effect. GRM is inversely proportional to stress level but strongly positively correlated with tangential Young’s modulus. The generalized relaxation compliance (GRC) also was considered, and the GRC/GRM ratio was taken as the local stiffness coefficient of rocks. When the stress reached the yield strength, the local stiffness of the rock decreased before failure. This ratio can predict the long-term strength of rock masses and stability of underground engineering. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the psychometric properties of Cultural Intelligence Scale (CQS), based on item response theory (IRT) using the graded response model (GRM). The study calibration sample included 400, while the study sample included 1000, male and female Saudi participants, aged between 18 and 62 years. IRT‐GRM results supported the quality of the psychometric properties of CQS, and its appropriateness to measure cultural intelligence (CQ) for the majority of individuals. CQS well‐distinguished people at different ability levels along the CQ latent trait, particularly with middle and low abilities. However, CQS full scale and subscales had less accurate measurement precision at high levels of CQ, and some subscales had more precision at low level abilities. CQS items had medium ability to differentiate among subjects, and they provided more information in evaluating individuals with medium CQ. Therefore, CQS might be more suitable for identification and development purposes, where low to med‐levels of CQ are expected. Additional assessment procedures need to be added, for selection or promotion purposes to increase the measurement precision. Confirmatory factor analysis results confirmed the multidimensional construct of CQS with four specific‐related factors at the first level, and an aggregate factor at the second level. This model provided better model fit using IRT‐GRM approach, and it was supported by classical test theory analysis results. Therefore, it is important to rely on subscale scores, besides the total score to interpret CQ for individuals. The study stressed the importance of examining CQS item parameters and information based on the country it is adapted for, to investigate how they interact with country culture; and to take into account ability level, when selecting optimal measures. Practitioner points: The results of confirmatory factor analysis (CFA) and item response theory (IRT) graded response model (GRM) supported the multidimensional construct of Cultural Intelligence Scale (CQS) with four specific‐related factors at the first level, and an aggregate factor at the second level, that was proposed by the CQS theory, compared to other models.IRT‐GRM analysis results in this study indicated that CQS has good psychometric properties and indicated that it appears to be a valid and moderately reliable instrument in detecting Cultural intelligence (CQ). These results were supported by CTT analysis results.IRT‐GRM analysis results showed that CQS well‐distinguished people at different ability levels along the CQ latent trait, particularly with middle and low abilities. However, CQS full scale and subscales had less accurate measurement precision at high levels of CQ, and some subscales had more precision at low level abilities.The study suggested that it is important to examine the CQS model fit, item parameters, information functions for the full scale and subscales based on the country it is adapted for, before considering it. It is important also to rely on the subscale scores to interpret CQ for individuals, and to identify their strengths, rather than relying on the total score alone.The study results suggested that CQS suites better CQ identification and development purposes. For selection or promotion purposes, it is suggested to add additional assessment procedures to increase the measurement precision. [ABSTRACT FROM AUTHOR]

The utilization of sludge from sewage treatment plants, ground granulated blast furnace slag (GGBFS) and recycled fine aggregate (RFA) from demolition of abandoned buildings in the production of geopolymer recycled aggregate mortar (GRM) offers a sustainable solution to reduce Ordinary Portland cement (OPC) application, and to address the growing volume of municipal sludge and construction waste. This work aims to investigate the workability, mechanical performance and microstructure of GGBFS and sewage sludge ash (SSA) based alkali activated GRM. GGBFS and SSA based geopolymer was used to replace 100% of OPC and RFA was employed to substitute various proportions (0%, 15%, 30% and 50%) of natural fine aggregates (NFA). Influences of SSA and RFA content on the consistency, setting time, compressive strength and flexural strength of GRM were investigated. The geopolymerization products were characterized through scanning electron microscopy (SEM), x-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FT-IR) tests. Results show that the consistency value and setting time of GRM decrease when the SSA and RFA content increases. When SSA content is 10% and RFA content is 15% (S10R15 sample), sample's microstructure becomes more compact, displaying robust mechanical properties. And S10R15 sample attained an average 28-day compressive strength of 51.7 MPa and flexural strength of 7.2 MPa. This demonstrates that GRM exhibits satisfactory working performance, mechanical properties. This study is expected to offer more insights into the application of SSA and RFA.

Copyright of Acta Biologica Slovenica is the property of Drustvo Biologov Slovenije and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recently, there have been many abnormal natural phenomena caused by climate change. Anthropogenic factors associated with insufficient water resource management can be another cause. Among natural causes, rainfall intensity and volume often induce flooding. Therefore, accurate rainfall estimation and prediction can prevent and mitigate damage caused by these hazards. Sadly, uncertainties often hinder accurate rainfall forecasting. This study investigates the uncertainty of the Korean rainfall ensemble prediction data and runoff analysis model in order to enhance reliability and improve prediction. The objectives of this study include: (i) evaluating the spatial characteristics and applicability of limited area ensemble prediction system (LENS) data; (ii) understanding uncertainty using parameter correction and generalized likelihood uncertainty estimation (GLUE) and grid-based rainfall-runoff model (GRM); (iii) evaluating models before and after LENS-GRM correction. In this study, data from the Wicheon Basin was used. The informal likelihood (R2, NSE, PBIAS) and formal likelihood (log-normal) were used to evaluate model applicability. The results confirmed that uncertainty of the behavioral model exists using the likelihood threshold when applying the runoff model to rainfall forecasting data. Accordingly, this method is expected to enable more reliable flood prediction by reducing the uncertainties of the rainfall ensemble data and the runoff model when selecting the behavioral model for the user's uncertainty analysis. It also provides a basis for flood prediction studies that apply rainfall and geographical characteristics for rainfall-runoff uncertainty analysis. [ABSTRACT FROM AUTHOR]

When fitting unidimensional item response theory (IRT) models, the population distribution of the latent trait (θ) is often assumed to be normally distributed. However, some psychological theories would suggest a nonnormal θ. For example, some clinical traits (e.g., alcoholism, depression) are believed to follow a positively skewed distribution where the construct is low for most people, medium for some, and high for few. Failure to account for nonnormality may compromise the validity of inferences and conclusions. Although corrections have been developed to account for nonnormality, these methods can be computationally intensive and have not yet been widely adopted. Previous research has recommended implementing nonnormality corrections when θ is not "approximately normal." This research focused on examining how far θ can deviate from normal before the normality assumption becomes untenable. Specifically, our goal was to identify the type(s) and degree(s) of nonnormality that result in unacceptable parameter recovery for the graded response model (GRM) and 2-parameter logistic model (2PLM). [ABSTRACT FROM AUTHOR]

The present study deals with the alternating field (AF) demagnetization of the volcanic rocks and meta-sediments from the North Singhbhum Mobile Belt (NSMB) within a field of 2.5 to 100 mT. All the three rock types encountered were subjected to AF demagnetization and the behavior during demagnetization was noted. As the rocks of the NSMB have variable potential to record remanences, the samples to demagnetize were sorted based on their feasibility to record characteristic remanent magnetization (ChRM). A gradual decrease in the magnetic intensity of the quartzites during AF demagnetization yielded two stable palaeomagnetic vectors recorded in them. Two palaeomagnetic poles are determined from these stable vectors. The palaeomagnetic poles thus obtained from the quartzites lie on a hairpin bend in the Proterozoic apparent polar wandering path (APWP) of the Indian subcontinent. This is significant towards the ~ 1850 Ma initiated Satpura orogeny which developed the regional mesoscopic as well as the magnetic fabrics in the NSMB. Thus, these palaeomagnetic poles are useful in relating the regional tectonics and magneto-tectonics of the NSMB. However, the magnetic intensity of the schists and volcanic rocks continues to decrease with increasing applied AF up to a certain extent, and then again continues to increase, which proves that these samples are affected by the acquisition of gyro remanent magnetization (GRM), which is a magnetic vector component acquired by certain rocks during AF demagnetization of their natural remanent magnetization (NRM). As GRM is an imperfection commonly associated with AF demagnetization of the rocks, the samples with such features are not considered for tectonics-related palaeomagnetic studies in the NSMB. [ABSTRACT FROM AUTHOR]

Item parameter recovery in the compensatory multidimensional graded response model (MGRM) under simple and complex structures with rating-scale item response data was examined. A simulation study investigated factors that influence the precision of item parameter estimation, including sample size, intercorrelation between the dimensions, and test lengths for the MGRM under balanced and unbalanced complex structures, as well as the simple structure. The item responses for the MGRM were generated and analyzed across conditions using the R package mirt. The bias and root mean square error (RMSE) was used to evaluate item parameter recovery. Results suggested that item parameter estimation was more accurate in balanced complex structure conditions than in unbalanced or simple structures, especially when the test length was 40 items, and the sample size was large. Further, the mean bias and RMSE in the recovery of item threshold estimates along the two dimensions for both balanced and unbalanced complex structures were consistent across all conditions.

The gamma regression model is widely applied when the response variable is continuous and positively skewed. In the multicollinearity problem, the usual maximum likelihood estimator is inadequate due to its inflated variance. To reduce this effect, well-known ridge and Liu estimators are generally used. In this study, we propose some shrinkage parameters for the new estimator and compared with some best ridge parameters indicated by Amin et al. [Performance of some ridge estimators for the gamma regression model. Stat Pap. 2020;61:997–1026] and two proposed ridge parameters for the GRM specified by Lukman et al. [A new ridge-type estimator for the gamma regression model. Scientifica. 2021;2021:5545356]. A Monte Carlo simulation study and an empirical application are conducted to assess the effectiveness of the proposed and other estimators. Based on the findings of simulation results and applications, we found that one of our proposed estimators performed the best for small dispersion levels. [ABSTRACT FROM AUTHOR]

Damage prevention from the local storms and typhoons in Korea, the development of a rainfall-runoff model reflecting local geological, meteorological and physical characteristics is necessary. The accuracy of the rainfall-runoff model is influenced by the various uncertainty factors that can occur in the modeling processes, including input data, model parameters, modeling simplification, and so on. Thus, the objectives of this study are (1) to estimate runoff for two rainfall events using Grid Rainfall-Runoff Model (GRM); (2) to quantify the uncertainty of the GRM model using the Generalized Likelihood Uncertainty Estimation (GLUE) method, and (3) to assess the uncertainty ranges of the GRM based on different likelihood functions. For this, two rainfall events were implemented to the GRM in the Cheongmicheon watershed, and informal likelihood functions (LNSE, LPBIAS, LRSR, and LLOG) based on the fitness indices (NSE, PBIAS, RSR, and Log-normal) were used for uncertainty analysis and quantification using GLUE method. As a result, the GRM parameters varied according to the different rainfall patterns even in the same watershed. In addition, among the GRM parameters, the CRC (Channel Roughness Coefficient) and CSHC (Correction factor for Soil Hydraulic Conductivity) characteristics are the most sensitive. Moreover, this study showed that the uncertainty range of the GRM model can be changed with the subjective selection of likelihood functions and thresholds. The GRM model is open source and has good accessibility. Especially, this open-source model allows various approaches to disaster prevention plans such as flood forecasting and flood insurance policies. In addition, if the parameter range of GRM is quantified and standardized at domestic watersheds, it is expected that the reliability of the rainfall-runoff simulation can be increased by the reduction of the uncertainty factors. [ABSTRACT FROM AUTHOR]

The implementation of polytomous item response theory (IRT) models such as the graded response model (GRM) and the generalized partial credit model (GPCM) to inform instrument design and validation has been increasing across social and educational contexts where rating scales are usually used. The performance of such models has not been fully investigated and compared across conditions with common survey-specific characteristics such as short test length, small sample size, and data missingness. The purpose of the current simulation study is to inform the literature and guide the implementation of GRM and GPCM under these conditions. For item parameter estimations, results suggest a sample size of at least 300 and/or an instrument length of at least five items for both models. The performance of GPCM is stable across instrument lengths while that of GRM improves notably as the instrument length increases. For person parameters, GRM reveals more accurate estimates when the proportion of missing data is small, whereas GPCM is favored in the presence of a large amount of missingness. Further, it is not recommended to compare GRM and GPCM based on test information. Relative model fit indices (AIC, BIC, LL) might not be powerful when the sample size is less than 300 and the length is less than 5. Synthesis of the patterns of the results, as well as recommendations for the implementation of polytomous IRT models, are presented and discussed.

Abstract Background The Four-Dimensional Symptom Questionnaire (4DSQ) is a self-report questionnaire designed to measure distress, depression, anxiety, and somatization. Prior to computing scale scores from the item scores, the three highest response alternatives (‘Regularly’, ‘Often’, and ‘Very often or constantly present’) are usually collapsed into one category to reduce the influence of extreme responding on item- and scale scores. In this study, we evaluate the usefulness of this transformation for the distress scale based on a variety of criteria. Methods Specifically, by using the Graded Response Model, we investigated the effect of this transformation on model fit, local measurement precision, and various indicators of the scale’s validity to get an indication on whether the current practice of recoding should be advocated or not. In particular, the effect on the convergent- (operationalized by the General Health Questionnaire and the Maastricht Questionnaire), divergent- (operationalized by the Neuroticism scale of the NEO-FFI), and predictive validity (operationalized as obtrusion with daily chores and activities, the Biographical Problem list and the Utrecht Burnout Scale) of the distress scale was investigated. Results Results indicate that recoding leads to (i) better model fit as indicated by lower mean probabilities of exact test statistics assessing item fit, (ii) small (

In genome-wide association studies, ordinal categorical phenotypes are widely used to measure human behaviors, satisfaction, and preferences. However, because of the lack of analysis tools, methods designed for binary or quantitative traits are commonly used inappropriately to analyze categorical phenotypes. To accurately model the dependence of an ordinal categorical phenotype on covariates, we propose an efficient mixed model association test, proportional odds logistic mixed model (POLMM). POLMM is computationally efficient to analyze large datasets with hundreds of thousands of samples, can control type I error rates at a stringent significance level regardless of the phenotypic distribution, and is more powerful than alternative methods. In contrast, the standard linear mixed model approaches cannot control type I error rates for rare variants when the phenotypic distribution is unbalanced, although they performed well when testing common variants. We applied POLMM to 258 ordinal categorical phenotypes on array genotypes and imputed samples from 408,961 individuals in UK Biobank. In total, we identified 5,885 genome-wide significant variants, of which, 424 variants (7.2%) are rare variants with MAF < 0.01. [ABSTRACT FROM AUTHOR]

Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The Four-Dimensional Symptom Questionnaire (4DSQ) is a self-report questionnaire designed to measure distress, depression, anxiety, and somatization. Prior to computing scale scores from the item scores, the three highest response alternatives (‘Regularly’, ‘Often’, and ‘Very often or constantly present’) are usually collapsed into one category to reduce the influence of extreme responding on item- and scale scores. In this study, we evaluate the usefulness of this transformation for the distress scale based on a variety of criteria. Methods: Specifically, by using the Graded Response Model, we investigated the effect of this transformation on model fit, local measurement precision, and various indicators of the scale’s validity to get an indication on whether the current practice of recoding should be advocated or not. In particular, the effect on the convergent- (operationalized by the General Health Questionnaire and the Maastricht Questionnaire), divergent- (operationalized by the Neuroticism scale of the NEO-FFI), and predictive validity (operationalized as obtrusion with daily chores and activities, the Biographical Problem list and the Utrecht Burnout Scale) of the distress scale was investigated. Results: Results indicate that recoding leads to (i) better model fit as indicated by lower mean probabilities of exact test statistics assessing item fit, (ii) small (<.02) losses in the sizes of various validity coefficients, and (iii) a decrease (DIFF (SE’s) = .10–.25) in measurement precision for medium and high levels of distress. Conclusions: For clinical applications and applications in longitudinal research, the current practice of recoding should be avoided because recoding decreases measurement precision for medium and high levels of distress. It would be interesting to see whether this advice also holds for the three other domains of the 4DSQ. [ABSTRACT FROM AUTHOR]

In this article, we proposed some influence diagnostics for the gamma regression model (GRM) and the gamma ridge regression model (GRRM). We assess the impact of influential observations on the GRM and GRRM estimates by extending the work of Pregibon [Logistic regression diagnostics. Ann Stat. 1981;9:705-724] and Walker and Birch [Influence measures in ridge regression. Technometrics. 1988;30:221-227]. Comparison of both models is made and demonstrated with the help of a simulation study and a real data set. We report some momentous results in detecting the influential observations and their effects on the GRM and GRRM estimates. [ABSTRACT FROM AUTHOR]

Stressing events in the early period of life affect neuronal plasticity and cognitive functions in adulthood. A key role in the mechanisms of formation of memory and attention is played by the glutamatergic system. However, there has been virtually no systematic study on the effect of early postnatal stress on the expression of glutamatergic system genes in various regions of the brain in mice. In this study, we used two types of early postnatal stress: prolonged separation of pups from mothers (for 3 hours per day) and shortterm separation (15 minutes per day) during the first 2 weeks of life. We used an object recognition test to evaluate attention and memory to assess cognitive abilities in adults. We found that prolonged maternal separation reduced the ability to recognize a novel object and also disrupted motor and exploratory activities in adult animals, while short-term separation did not affect the studied parameters. We assessed the expression of the major genes of the glutamatergic system (AMPA receptor subunits Gria1, Gria2; NMDA subunits Grin1, Grin2a, and Grin2b; metabotropic receptor subunits Grm1, Grm2, and Grm3; glutamate transporters Vglut2, Eaat2, and Rab4a) in the frontal cortex, hippocampus, and hypothalamus. In the group with prolonged maternal separation, we found a decrease in the expression of Grin2b in the hypothalamus in comparison with the control, which led to a decrease in the mRNA ratio of this subunit to Grin2a mRNA, and possibly to a change in the ratio of these subunits in the NMDA receptor. In spite of the revealed cognitive impairments, we did not find significant changes in the expression of genes in the frontal cortex and hippocampus. Shortterm daily separation from mothers did not lead to changes in cognitive abilities and expression of genes of the glutamatergic system in mice. Thus, our results show that prolonged maternal separation may lead to a redistribution of the receptor subunits in the hypothalamus, which can modify the activity of the HPAA and determine the response to stress in these mice. [ABSTRACT FROM AUTHOR]

Glutamatergic dysregulation is implicated in the neuropathology of bipolar disorder (BD). There is increasing interest in investigating the role of metabotropic glutamate receptors (mGluRs) in BD and as a target for treatment intervention. Bipolar mGluR studies (published January 1992–April 2016) were identified via PubMed, Embase, Web of Science, and Scopus. Full-text screening, data extraction, and quality appraisal were conducted in duplicate, with strict inclusion and exclusion criteria. The initial literature search for mGluRs in BD, including non-bipolar mood disorders and primary psychotic disorders, identified 1544 articles. 61 abstracts were selected for relevance, 16 articles met full inclusion criteria, and three additional articles were found via citations. Despite limited literature, studies demonstrated: single nucleotide polymorphisms (SNPs) associated with BD, including a GRM3 SNP associated with greater likelihood of psychosis (rs6465084), mRNA binding protein Fragile X Mental Retardation Protein associated with altered mGluR1/5 activity in BD populations, and lithium decreasing mGluR5 expression and mGluR-mediated intracellular calcium signaling. Limited research has been performed on the role of mGluRs in BD, but results highlight the importance of ongoing study. Future directions for research of mGluRs in BD include GRM polymorphisms, epigenetic regulation, intracellular proteins, and pharmacologic interactions. [ABSTRACT FROM AUTHOR]

In this study, we develop the adjusted deviance residuals for the gamma regression model (GRM) by following Cordeiro's (2004) method. These adjusted deviance residuals under the GRM are used for influence diagnostics. A comparative analysis has been sorted out between our proposed method of the adjusted deviance residuals and an existing method for influence diagnostics. These results are illustrated by a simulation study and using a real data set. They are presented for different values of dispersion and sample sizes and indicate the significant role of the GRM inferences. [ABSTRACT FROM AUTHOR]

Graphene and related materials (GRMs) are promising candidates for the fabrication of resistive random access memories (RRAMs). Here, this emerging field is analyzed, classified, and evaluated, and the performance of a number of RRAM prototypes using GRMs is summarized. Graphene oxide, amorphous carbon films, transition metal dichalcogenides, hexagonal boron nitride and black phosphorous can be used as resistive switching media, in which the switching can be governed either by the migration of intrinsic species or penetration of metallic ions from adjacent layers. Graphene can be used as an electrode to provide flexibility and transparency, as well as an interface layer between the electrode and dielectric to block atomic diffusion, reduce power consumption, suppress surface effects, limit the number of conductive filaments in the dielectric, and improve device integration. GRM-based RRAMs fit some non-volatile memory technological requirements, such as low operating voltages (<1V) and switching times (<10 ns), but others, like retention >10 years, endurance >109 cycles and power consumption ≈10 pJ per transition still remain a challenge. More technology-oriented studies including reliability and variability analyses may lead to the development of GRMs-based RRAMs with realistic possibilities of commercialization. [ABSTRACT FROM AUTHOR]

Background: Most genome-wide association studies assumed an additive model of inheritance which may result in significant loss of power when there is a strong departure from additivity. The General Regression Model (GRM), which allows performing an assumption-free test for association by testing for both additive effect and deviation from additive effect, may be more appropriate for association tests. Additionally, GRM allows testing the underlying genetic model. We compared the power of GRM association test to additive and other Cochran-Armitage Trend (CAT) tests through simulations and by applying GRM to a large case/control sample, the bipolar Welcome Trust Case Control Cohort data. Simulations were performed on two sets of case/control samples (1000/1000 and 2000/2000), using a large panel of genetic models. Four association tests (GRM and additive, recessive and dominant CAT tests) were applied to all replicates. Results: We showed that GRM power to detect association was similar or greater than the additive CAT test, in particular in case of recessive inheritance, with up to 67% gain in power. GRM analysis of genome-wide bipolar disorder Welcome Trust Consortium data (1998 cases/3004 controls) showed significant association in the 16p12 region (rs420259; P = 3.4E-7) which has not been identified using the additive CAT test. As expected, rs42025 fitted a non-additive (recessive) model. Conclusions: GRM provides increased power compared to the additive CAT test for association studies and is easily applicable. [ABSTRACT FROM AUTHOR]

Copyright of Human Resource Management / Zarzadzanie Zasobami Ludzkimi is the property of Institute of Labour & Social / Instytut Pracy i Spraw Socjalnych and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents an integrated supplier selection and inventory management using grey relationship model (GRM) as well as multi-objective decision making process. The proposed model of this paper first ranks different suppliers based on GRM technique and then determines the optimum level of inventory by considering different objectives. To show the implementation of the proposed model, we use some benchmark data presented by Talluri and Baker [Talluri, S., & Baker, R. C. (2002). A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research, 141(3), 544-558.]. The preliminary results indicate that the proposed model of this paper is capable of handling different criteria for supplier selection.

Penelitian ini bertujuan untuk menghasilkan model tes yang cocok dengan data. Pengembangan item pada penelitian menggunakan pendekatan teori respons butir politomus (TRBP). Subjek ujicoba diambil dari siswa lima SMP kelas VII akhir mewakili peringkat SMP di Kota Yogyakarta sebanyak 1030 siswa. Hasil Model TRBP yang cocok dipilih berdasarkan hasil parametrisasi menggunakan PARSCALE dan deskripsi hubungan fungsional antara respons peserta tes dengan tingkat kemampuannya yang dinyatakan dalam test information curves (TIC). Penelitian ini menghasilkan 16 butir untuk bank soal dengan karakteristik masing-masing butir memiliki nilai daya beda yang tidak rendah (>0,25 skala logit) dan nilai kesulitan butir pada selang -3 sampai +3 skala logit. Berdasarkan informasi yang dihasilkan, kedua macam model penskoran GRM dan GPCM cocok memodelkan penskoran TPPB yang diadministrasikan. GPCM mungkin lebih merefleksikan realitas bagaimana data dihasilkan sehingga dari TIC tampak lebih akurat menaksir kemampuan dibanding GRM. Kata Kunci: tes pengetahuan praktikum biologi, GRM, GPCM ______________________________________________________________ DEVELOPMENT OF A TEST OF BIOLOGY PRACTICUM KNOWLEDGE WITH GRADED RESPONSE AND GENERALIZED PARTIAL CREDIT MODELS Abstract This study aims to generate information to define the polytomous item response models which are more suitable with the data. The items were developed by the polytomous item response theory approach. The tryout participants were 1030 Year VII students selected from five junior high schools in Yogyakarta City. A suitable model was selected based on the result of PARSCALE parameterization and a description of the functional relationship between the testees’ responses and their ability levels indicated by the test information curves (TIC). The study yields 16 items for the item bank in which the discrimination index of each item is > 0.25 logit scale and the difficulty index ranges from -3 to +3 logit scale. The information shows that GRM and GPCM models of are suitable for scoring the administered TBPK. GPCM possibly reflects reality more regarding how the data are yielded so that on the basis of TIC it seems more accurate to estimate students’ ability than GRM. Keywords: a test of biology practicum knowledge (TBPK), GRM, GPCM

Detailed investigations of landslides are essential to understand fundamental landslide mechanisms. Seismic refraction method has been proven as a useful geophysical tool for investigating shallow landslides. The objective of this study is to introduce a new workflow using neural network in analyzing seismic refraction data and to compare the result with some methods; that are general reciprocal method (GRM) and refraction tomography. The GRM is effective when the velocity structure is relatively simple and refractors are gently dipping. Refraction tomography is capable of modeling the complex velocity structures of landslides. Neural network is found to be more potential in application especially in time consuming and complicated numerical methods. Neural network seem to have the ability to establish a relationship between an input and output space for mapping seismic velocity. Therefore, we made a preliminary attempt to evaluate the applicability of neural network to determine velocity and elevation of subsurface synthetic models corresponding to arrival times. The training and testing process of the neural network is successfully accomplished using the synthetic data. Furthermore, we evaluated the neural network using observed data. The result of the evaluation indicates that the neural network can compute velocity and elevation corresponding to arrival times. The similarity of those models shows the success of neural network as a new alternative in seismic refraction data interpretation.

Cerebral atrophy affects the brain and is a common feature of patients with mild cognitive impairment or Alzheimer's diseases. It is evaluated by the radiologist or reader based on patient's history, age and the space between the brain and the skull as indicated by magnetic resonance (MR) images. A total of 70 patients were scanned in the supine and prone positions before three radiologist assessed their atrophy level. This study examined the radiologist's assessment of the cerebral atrophy level using a graded response model of item response theory (IRT). A graded response model (GRM) is fitted to our data and then item-fit and person-fit statistics are evaluated to assess the fitted model. Our analysis found that the cerebral atrophy level is better discriminated by readers in the prone position because all item slopes were greater than 2 at this position, versus the supine position where all the slope parameters were less than 1. However, the thresholds are very similar for the first reader and are quite different for the second and third readers because the scanning position affects readers differently as the category threshold estimates vary considerably between the readers.. [ABSTRACT FROM AUTHOR]

Most runoff analyses using a grid-based distributed model use one parameter group calibrated at the outlet of a watershed, instead of dividing the watershed into subwatersheds. Significant differences between the observed value and the simulation result of the subwatersheds can occur if just one parameter group is used in all subwatersheds that have different hydrological characteristics from each other. Therefore, to improve the simulation results of the subwatersheds within a watershed, a model calibrated at every subwatershed needs to be used to reflect the characteristics of each subwatershed. In this study, different parameter groups were set up for one or two sites using a distributed model, the GRM (Grid based Rainfall-runoff Model), and the evaluations were based on the results of rainfall-runoff analysis, which uses a multi-site calibration (MSC) technique to calibrate the model at the outlet of each site. The Hyangseok watershed in Naeseong River, which is a tributary of Nakdong River in Korea, was chosen as the study area. The watershed was divided into five subwatersheds each with a subwatershed outlet that was applied to the calibration sites . The MSC was applied for five cases. When a site was added for calibration in a watershed, the runoff simulation showed better results than the calibration of only one site at the most downstream area of the watershed. The MSC approach could improve the simulation results on the calibrated sites and even on the non-calibrated sites, and the effect of MSC was improved when the calibrated site was closer to the runoff site. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Aim. In this article, we develop a method, that we call the gameplay review method, for measuring players’ engagement with digital games through players’ interactions with video recordings of their own gameplay.Method. The gameplay review method arose from a microsociological study of the gameplay of eight young adults who each played approximately 20 hours of WORLD OF WARCRAFT over a 3-month period in 2012. Using data from in-depth interviews and audiovisual recordings of one of the eight participants, this article focuses on how the method leveraged participants’ knowledge of their experiences and ties that knowledge to measures of engagement. We outline the method’s four-step process (producing Level I data, analyzing Level I data, producing Level II data, analyzing Level II data) to guide the generation and analysis of rich video data. The method involves focused discussions on selected recorded segments of participants’ gameplay and is a means of connecting game design with both empirical and interpretive data.Results. We show how, as participants progress, they learn about game design features and deepen their understanding of games. We found that participants’ developing perceptions of, and relationships to, design features affect their engagement with digital games.Conclusion. The gameplay review method is significant in its ability to measure engagement by dealing explicitly with empirical and interpretive data. [ABSTRACT FROM AUTHOR]

Background Pharmacological modulation of metabotropic glutamate receptor 5 (mGluR5) is of marked interest as a novel therapeutic mechanism to treat schizophrenia and major depression. However, the status of mGluR5 in the pathophysiology of these disorders remains unknown. Discussion The majority of studies in the schizophrenia post-mortem brain indicate that total mGluR5 expression is unaltered. However, close examination of the literature suggests that these findings are superficial, and in actuality, a number of critical factors have not yet been considered; alterations may be highly dependent on brain region, neuronal population or molecular organisation in specific cellular compartments. A number of genetic knockout studies (mGluR5, Norbin, Homer1 etc.) continue to lend support to a role of mGluR5 in the pathology of schizophrenia, providing impetus to explore the regulation of mGluR5 beyond total mGluR5 protein and mRNA levels. With regards to major depression, preliminary evidence to date shows a reduction in total mGluR5 protein and mRNA levels; however, as in schizophrenia, there are no studies examining mGluR5 function or regulation in the pathological state. A comprehensive understanding of mGluR5 regulation in major depression, particularly in comparison to schizophrenia, is crucial as this has extensive implications for mGluR5 targeting novel therapeutics, especially considering that opposing modulation of mGluR5 is of therapeutic interest for these two disorders. Summary Despite the complexities, examinations of post-mortem human brain provide valuable insights into the pathologies of these inherently human disorders. It is important, especially with regards to the identification of novel therapeutic drug targets, to have an in depth understanding of the pathophysiologies of these disorders. We posit that brain region- and cell type-specific alterations exist in mGluR5 in schizophrenia and depression, with evidence pointing towards altered regulation of this receptor in psychiatric pathology. We consider the implications of these alterations, as well as the distinction between schizophrenia and depression, in the context of novel mGluR5 based therapeutics. [ABSTRACT FROM AUTHOR]

Penelitian ini akan membahas perbedaan tingkat reliabilitas tes prestasi hasil belajar matematika pada tes bentuk uraian dengan model penskoran GPCM dan penskoran GRM. Berdasarkan hasil penelitian menunjukkan ada perbedaan tingkat reliabilitas tes prestasi hasil belajar matematika pada tes bentuk uraian dengan model penskoran GPCM dan penskoran GRM

The violation of the assumption of local independence when applying item response theory (IRT) models has been shown to have a negative impact on all estimates obtained from the given model. Numerous indices and statistics have been proposed to aid analysts in the detection of local dependence (LD). A Monte Carlo study was conducted to evaluate the relative performance of selected LD measures in conditions considered typical of studies collecting psychological assessment data. Both the Jackknife Slope Index and likelihood ratio statistic G2 are available across the two IRT models used and displayed adequate to good performance in most simulation conditions. The use of these indices together is the final recommendation for applied analysts. Future research areas are discussed. [ABSTRACT FROM AUTHOR]

Alpha satellites are tandemly repeated sequences found in all human centromeres. In addition to the functional and structural role within centromere they are also a suitable model for evolutionary studies, because of being subject to concerted evolution. The Global Repeat Map (GRM) algorithm is a convenient computational tool to determine consensus repeat units and their exact size within a given genomic sequence, both of monomeric and higher-order (HOR) type. Using GRM, we identify in Build 37.2 assembly fifteen different alpha satellite HORs, three of them novel, not reported previously. In the next step we compute suprachromosomal family classification and CENP-B box / pJα distributions for these HORs. All human alpha satellite sequences originate from one pra-ancestral alpha satellite monomer. For the first time we perform GRM analysis and compare human and chimpanzee alpha satellite HORs for chromosomes 4 and give an evidence that the human and chimpanzee alpha satellites originate from a common ancestor that predated the human-chimpanzee separation. We also compare the codon-like trinucleotide (CLT) extensions of human and chimpanzee chromosome 4. Our results are consistent with the expectation that the alpha satellite HORs in human and chimpanzee have been created after the human-chimpanzee separation. [ABSTRACT FROM AUTHOR]

Detailed investigations of landslides are essential to understand fundamental landslide mechanisms. Seismic refraction method has been proven as a useful geophysical tool for investigating shallow landslides. The objective of this study is to introduce a new workflow using neural network in analyzing seismic refraction data and to compare the result with some methods; that are general reciprocal method (GRM) and refraction tomography. The GRM is effective when the velocity structure is relatively simple and refractors are gently dipping. Refraction tomography is capable of modeling the complex velocity structures of landslides. Neural network is found to be more potential in application especially in time consuming and complicated numerical methods. Neural network seem to have the ability to establish a relationship between an input and output space for mapping seismic velocity. Therefore, we made a preliminary attempt to evaluate the applicability of neural network to determine velocity and elevation of subsurface synthetic models corresponding to arrival times. The training and testing process of the neural network is successfully accomplished using the synthetic data. Furthermore, we evaluated the neural network using observed data. The result of the evaluation indicates that the neural network can compute velocity and elevation corresponding to arrival times. The similarity of those models shows the success of neural network as a new alternative in seismic refraction data interpretation. [ABSTRACT FROM AUTHOR]

The 1D τ-p inversion algorithm is widely employed to generate starting models with most computer programs that implement refraction tomography. However, this algorithm emphasizes the vertical resolution of many layers, and as a result, it frequently fails to detect even large lateral variations in seismic velocities, such as the decreases that are indicative of shear zones. This study presents a case that demonstrates the failure of the 1D τ-p inversion algorithm to define or even detect a major shear zone that is 50 m or ten stations wide. Furthermore, the majority of refraction tomography programs parameterize the seismic velocities within each layer with vertical velocity gradients. By contrast, the 2D generalized reciprocal method (GRM) inversion algorithms emphasize the lateral resolution of individual layers. This study demonstrates the successful detection and definition of the 50-m wide shear zone with the GRM inversion algorithms. The existence of the shear zone is corroborated by a 2D analysis of the head wave amplitudes and by numerous closely spaced orthogonal seismic profiles carried out as part of a later 3D refraction investigation. Furthermore, a 1D analysis of the head wave amplitudes indicates that a reversal in the seismic velocities, rather than vertical velocity gradients, occurs in the weathered layers. While all seismic refraction operations should aim to provide as accurate depth estimates as is practical, the major conclusion reached in this study is that refraction inversion algorithms that emphasize the lateral resolution of individual layers generate more useful results for geotechnical and environmental applications. The advantages of the improved lateral resolution are obtained with 2D profiles in which the structural features can be recognized from the magnitudes of the variations in the seismic velocities. Furthermore, the spatial patterns obtained with 3D investigations facilitate the recognition of structural features that do not display any intrinsic variation or “signature” in seismic velocities. [ABSTRACT FROM AUTHOR]

Abstract: Although the glutamatergic system usually functions in the CNS, expression has been observed in non-neuronal tissues and a subset of cancers. Metabotropic glutamate receptors (mGlus) are highly “druggable” GPCRs and thus a priority for validation as therapeutic targets. We have previously reported that the aberrant expression of mGlu1 is sufficient to induce spontaneous melanoma development in vivo. We isolated and characterized several stable mGlu1-mouse melanocytic clones and demonstrated that these clones are transformed and tumorigenic. We hypothesize that expression of mGlus may not be uncommon in the pathogenesis of tumors other than melanoma, and that activity of an otherwise normal glutamate receptor in an ectopic cellular environment involves signaling pathways which dysregulate cell growth, ultimately leading to tumorigenesis. As most human cancers are of epithelial origin (carcinomas), in this review, the possibility that mGlu1 could function as a complete oncogene and transform epithelial cells is also discussed. [Copyright &y& Elsevier]

Abstract: Fourteen shallow seismic refraction profiles were conducted in Wadi Wardan, northeast Gulf of Suez, Sinai to delineate some of the shallow soil engineering characteristics for construction purposes. Both compressional (P) and shear (S) waves were acquired and interpreted using Generalized Reciprocal Method (GRM) then the resulted velocity-depth model is verified using a Finite Difference (FD) method to improve the final velocity-depth model. A number of engineering parameters such as Concentration Index, Material Index, Density Gradient, and Stress Ratios are calculated. The seismic velocity values, engineering, consolidation, and strength parameters show that the bedrock at northern and southern parts of the study area is characterized by less competent rock quality, while the central part is characterized by more competent rock quality. Hence, the central part is suggested for construction activities. [Copyright &y& Elsevier]

Abstract: This study puts forward a novel method to prepare granular red mud (GRM) and evaluates its potential use to remove cadmium ions from aqueous solutions as a low-cost adsorbent. The properties of the novel adsorbent were examined and then used for cadmium adsorption experiments. Batch experiments were conducted and equilibrium isotherms at different temperatures (20°C, 30°C, 40°C) have been determined and analyzed with a Freundlich model. Kinetics data at initial pH 6.0 and 3.0 were fitted with Pseudo-second-order model and external mass transfer coefficients, effective particle diffusion coefficients were subsequently calculated for cadmium–GRM system at initial pH 6.0. Column breakthrough curves were depicted and the data were analyzed with a Thomas model. The column adsorption was reversal and the regeneration operation was accomplished by pumping 0.1mol/L hydrochloric acid through the adsorbed column. [Copyright &y& Elsevier]

The gyromagnetic properties of CrO2 recording particles have been investigated and compared to those of γ-Fe2O3, which have previously been subject to similar studies. Rotational remanent magnetization (RRM) was determined as a function of rotation speed and of the strength of the magnetizing alternating field (AF). Gyromagnetic remanent magnetization (GRM) acquired by anisotropic samples in a static experiment was measured for various peak AF as a function of the angle between the AF and the axis of anisotropy. The asymmetry of GRM curves obtained with non-saturating fields may be related to the incoherent reversal mode of the particles. While GRM (RRM) of the γ-Fe2O3 particles had the sign expected theoretically, the gyromagnetic remanences obtained for CrO2 in both types of experiments were of opposite signs. Possible reasons for the reversed gyromagnetic effect are discussed. [Copyright &y& Elsevier]

The weight distribution of GRM (generalized Reed-Muller) codes is unknown in general. This article describes and applies some new techniques to the codes over F3. Specifically, we decompose GRM codewords into words from smaller codes and use this decomposition, along with a projective geometry technique, to relate weights occurring in one code with weights occurring in simpler codes. In doing so, we discover a new gap in the weight distribution of many codes. In particular, we show there is no word of weight 3m−2 in GRM3(4, m) for m>6, and for even-order codes over the ternary field, we show that under certain conditions, there is no word of weight d+Δ, where d is the minimum distance and Δ is the largest integer dividing all weights occurring in the code. [ABSTRACT FROM AUTHOR]