Discrimination Parameters Research Articles

Differentiation between high-grade gliomas and solitary brain metastases based on multidiffusion MRI model quantitative analysis.

Differentiating high-grade gliomas (HGGs) from solitary brain metastases (SBMs) using conventional magnetic resonance imaging (MRI) remains challenging due to their similar imaging features. This study aimed to evaluate the diagnostic performance of advanced diffusion models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator magnetic resonance imaging (MAP-MRI), incomparison to traditional techniques like diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) for distinguishing HGGs from SBMs. In total, 17 patients with HGGs and 26 patients with SBMs were prospectively recruited based on the established inclusion and exclusion criteria. Structural MRI sequences and diffusion spectrum imaging (DSI) were utilized to assess quantitative parameter models, including NODDI, MAP-MRI, DWI, DTI, and DKI. Quantitative parameters were measured for both the tumor parenchymal area and the peritumoral edema area. The quantitative parameters of the two patient groups were compared using either the independent Student's t-test or the Mann-Whitney U test. The effectiveness of each model was evaluated using receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Finally, the DeLong test was employed to compare the diagnostic performance of each model through pairwise comparisons of ROC curves. Isotropic volume fraction (Viso) based on NODDI; mean squared displacement (MSD) and the return to plane probabilities (RTPP) based on MAP-MRI; radial diffusivity (RDk) and mean diffusivity (MDk) based on DKI; and axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) based on DTI of the peritumoral edema tumor were significantly different between HGGs and SBMs (p < 0.05). The optimal single discriminant parameters for each model are NODDI_Viso, MAP-MRI_MSD, DKI_MDk, and DTI_AD. Among these, the AUC of Viso (0.809) exceeds that of MSD (0.733), MDk (0.718), and AD (0.779). The combined model, which incorporates DTI_AD, DKI_RD, and NODDI_Viso, demonstrated superior diagnostic performance (0.897). Advanced diffusion MRI quantitative parameters derived from NODDI, such as Viso, have the potential to enhance the differentiation between HGGs and SBMs. The integrated utilization of these models is anticipated to enhance diagnostic accuracy and refine MRI protocols for brain tumor assessment.

Psychometric Properties of the Saudi Version of the Mathematics Confidence Scale using the Modern Test Theory

The aim of the study was to analyze the psychometric properties of the Arabic version of the Math Confidence Rating Scale (MCS), using Item Response Theory (IRT) and Exploratory Factor Analysis (EFA). The participants were (315) from Imam Mouhammad Ibn Saud Islamic University; They are distributed into (92) female and (223) male, selected through a convenience sampling. The EFA models indicated that the one-dimensional structure better represents the data, and the pairs of items were considered locally independent, IRT findings indicate that all items had a very high discrimination parameter and all items had acceptable threshold parameters, And that MCS is more informative for mid-level ability of Math confidence. The MCS in Arabic has adequate psychometric properties to be used as a short measure of Math confidence.

Psychometric properties of Parenting Sense of Competence Scale using item-response theory

Parental competence is one of the essential components of raising ethical and healthy children. The mother's satisfaction with her maternal role significantly influences her cognitive responses and parenting behaviors. Having appropriate instruments to measure maternal satisfaction and identify and solve potential problems after childbirth can substantially contribute to maintaining and improving mother and infant health. This study aimed to evaluate the psychometric properties of the Parenting Sense of Competence (PSOC) Scale in mothers referring to the healthcare centers affiliated with Qazvin University of Medical Sciences. This cross-sectional psychometric study collected data from 254 mothers with 1.5-month-old infants referred to the healthcare centers in Qazvin Province. Data were analyzed using the item response theory (IRT) in SPSS 26 and Stata 17 software. The mean age (±standard deviation) of participants was 30.05 ± 5.7, and the overall Cronbach's alpha for the scale was 0.931. We used the graded response model (GRM) appropriate for Likert-type rating scales to fit the IRT. The discrimination parameter estimates showed that item 5 had a discrimination level <0.65, leading to its exclusion from the final analysis. In addition, the total information index confirmed that the scale was suitable in the trait range of −2.1 to 1.8. Compared with other common models for ordered responses based on general model fit indices, the GRM showed a better fit. The study results recommend applying the IRT models to improve and enhance the quality of questionnaires in various measurement fields.

Crafting an ultrashort workplace incivility scale and determining cutoffs for varied risk levels through item response theory

AbstractWorkplace incivility (WI), characterized by disrespectful or rude behavior in the workplace, is linked to poor mental health and overall well-being. The Workplace Incivility Scale (WIS) is a popular 7-item measure for assessing WI. There is a current need for an ultrashort conceptually clear version of the WIS. In addition, the cutoffs for varied at-risks of WI, requiring intervention, remains unknown. Using data from 426 employees across diverse organizations, we employed item response theory (IRT) to create an ultrashort WIS and establish cutoffs for high, moderate, low, and at-not risk of WI. Confirmatory factor analyses were utilized to validate WIS construct validity. In supporting convergent validity, WIS was correlated with workplace bullying and poor health-related quality of life. All items demonstrated adequate severity threshold parameters with very high discrimination and good reliability parameters except for item WIS7. We successfully developed an ultrashort and valid 3-item WIS, specifically comprising items WIS2–4, and identified cutoffs for varying levels of WI risk. This streamlined measure aims to reduce response burden and foster a healthier organizational culture. In essence, cutoff points streamline the classification process, allowing for quicker and more standardized identification of at-risk employees. This concise, valid, and reliable ultrashort WIS holds potential for use in intervention studies conducted by organizational and occupational health psychologists, ultimately promoting employee well-being and cultivating a positive workplace environment. The current study further advances the existing theoretical framework rooted in the social interactionist perspective by delineating WI as a distinct and independent construct.

An Item Response Theory Analysis of the Psychosis Screening Questionnaire in Ethiopia.

Few psychosis screening instruments have been tested for use in Africa, yet appropriate tools can increase the detection of self-reported psychotic symptoms, improve the detection of psychosis and impact its prognosis. The construct validity and factor structure of Psychosis Screening Questionnaire (PSQ) were tested with confirmatory factor analysis (CFA) and item response theory (IRT) in a sample of 1928 Ethiopian adults without any history of psychosis. We tested a unidimensional model with and without an item on mania. For IRT, unidimensional latent structure one-parameter logistic (1PL) and two-parameter (2PL) logistic models were tested and compared for relative fit using a likelihood-ratio test. The prevalence of lifetime positive screens was 2.8% in an Ethiopian sample of adults from a general medical setting. A unidimensional model demonstrated good fit for the PSQ, (CFI = 0.993, TLI = 0.986 and RMSEA = 0.025). For IRT, a 2PL model was the best fitting one. IRT tests of item difficulty and discrimination parameters showed that paranoia had the highest discrimination and lowest difficulty ( ), likely to be endorsed at low levels of psychotic features. Thought insertion had the highest item difficulty ( ). Overall, the measure captures the psychosis construct at higher levels of the latent trait and may be suited for detecting moderate to severe levels of psychosis. The PSQ is found to have good construct validity in screening for psychosis among Ethiopian adults. Future studies may focus on the diagnostic validity of the PSQ comparing it with a structured clinical interview.

Evaluating the psychometric properties of ChatGPT-generated questions

Not much is known about how LLM-generated questions compare to gold-standard, traditional formative assessments concerning their difficulty and discrimination parameters, which are valued properties in the psychometric measurement field. We follow a rigorous measurement methodology to compare a set of ChatGPT-generated questions, produced from one lesson summary in a textbook, to existing questions from a published Creative Commons textbook. To do this, we collected and analyzed responses from 207 test respondents who answered questions from both item pools and used a linking methodology to compare IRT properties between the two pools. We find that neither the difficulty nor discrimination parameters of the 15 items in each pool differ statistically significantly, with some evidence that the ChatGPT items were marginally better at differentiating different respondent abilities. The response time also does not differ significantly between the two sources of items. The ChatGPT-generated items showed evidence of unidimensionality and did not affect the unidimensionality of the original set of items when tested together. Finally, through a fine-grained learning objective labeling analysis, we found greater similarity in the learning objective distribution of ChatGPT-generated items and the items from the target OpenStax lesson (0.9666) than between ChatGPT-generated items and adjacent OpenStax lessons (0.6859 for the previous lesson and 0.6153 for the subsequent lesson). These results corroborate our conclusion that generative AI can produce algebra items of similar quality to existing textbook questions that share the same construct or constructs as those questions.

Measurement of bullying in the Progress in International Reading Literacy Study 2021 cohort: Evidence for model misspecification

We evaluated the use of the Rasch model in the scoring and scaling of the context questionnaire scales from the Progress in International Reading Literacy Study 2021 cohort. Focusing on the bullying scale of the Progress in International Reading Literacy Study, we contrasted polytomous item response theory models using free (two-parameter logistic modeling) and fixed (Rasch modeling) discrimination parameters. Our analyses included data from 354,074 students from 63 countries or entities. Across all countries and entities, the Rasch-based model significantly distorted levels of bullying. The rank ordering of countries was consistent between models in 32 of the cases (50.8%), while in other cases there were changes in rank of up to five places. This study provides a robust basis for evidence-based decisions on whether a country is lagging or exceeding the global norm in aberrant behaviors such as bullying.

Revisiting the English Short Measure for Adult Playfulness (SMAP): An Investigation of Reliability, Validity, and Cross-Cultural Comparisons

Adult playfulness describes the personality of the quick initiation and strong intensity of enjoyable experiences coupled with the frequency of engaging in playful behaviors. In addition to examining the reliability and validity of the Short Measure for Adult Playfulness (SMAP), we compared the psychometric properties of the SMAP across (a) 4- and 7-point answer formats; (b) German and English language versions; and (c) gender. The SMAP and criterion validity measures were distributed across three independent samples from Canada (N total = 1,177) and a German sample (N = 660). Results supported a unidimensional solution with strong factor loadings for all items (>.50 across all samples) and high test-retest reliability (r = .67, BF10>100). In item response theory analyses, high discrimination parameters were found across the latent continuum. Although both the four-point and seven-point Likert scale versions showed robust item properties, the seven-point Likert scale version yielded more precise measurement of higher playfulness (θ > 1.50). No significant differential item functioning was located across gender or language. Finally, results supported external construct validity via associations with broad personality traits, humor, and orientations to happiness. The present investigation provides support for the reliability and validity of the English SMAP for concise adult playfulness measurement.

Cross-cultural validation of the Jenkins Sleep Scale in Spanish-speaking countries.

The study aimed to validate the Jenkins Sleep Scale (JSS-4) in six Spanish-Speaking countries. A total of 1726 people participated and were distributed between men (32.4%) and women (67.6%). Confirmatory factor analysis confirmed the unidimensional structure and high reliability of the JSS-4 overall (α = 0.85, ω = 0.81) and within each country. The invariance analysis revealed that JSS-4 exhibited complete invariance across countries, thus establishing a robust foundation for inter-group comparisons. Interestingly, a comparative analysis revealed significant differences in the average levels of sleep difficulties, with particularly high rates in Spain and Chile. Item Response Theory (IRT) showed sufficient discrimination parameters for all items, and a correlation of 0.998 between Confirmatory Factor Analysis (CFA) and IRT highlighted the robustness and reliability of the results obtained. In summary, JSS-4 exhibits strong evidence of validity and consistency in measurement invariance across the six countries.

Using item response theory to identify key symptoms of insomnia in a sample of university students with probable eating disorders

PurposeResearchers have theorized that interactions between appetitive and circadian disruptions result in increased eating disorder (ED) symptoms and insomnia. However, it is unclear how specific insomnia symptoms present among people with EDs and if the latent structure of insomnia in this population is similar to that of people with insomnia disorder.MethodsWe conducted a secondary analysis of data collected on ED and insomnia symptoms using a subset of students (N = 547; 79.52% female) with probable EDs at a large Midwestern American university. Item response theory (IRT) for polytomous items was performed to identify item difficulty, discrimination, and information parameters for the Insomnia Severity Index (ISI). IRT parameters were compared to those established in a 2011 study of people diagnosed with insomnia disorder by Morin and colleagues.ResultsClinically significant insomnia symptoms were common among students with ED pathology and symptom endorsement for each ISI item ranged from 40.77 to 86.65%. ISI items assessing insomnia-related impairment and distress showed better discriminative capacities and had higher item information than items assessing sleep behavior alterations (i.e., difficulties falling asleep, difficulties maintaining sleep, waking too early). Item discrimination was largely similar among the ED sample compared to previous IRT analyses in an insomnia disorder sample.ConclusionInsomnia symptoms are common among university students with probable EDs and similar to those reported by people with insomnia disorder. When considering insomnia assessment, items assessing sleep behaviors alone are likely inadequate to provide information about insomnia severity among people with EDs.Level VEvidence obtained from a cross-sectional descriptive study.

Development of Four-Item Attitudes toward People Living with Dementia Scale for population surveys.

This study developed a short version of a scale measuring attitudes toward people living with dementia, the Four-Item Attitudes toward People Living with Dementia Scale (APDS4), that could be included in a large population survey. We used three datasets from Japan: a web panel survey, a community-based mail survey, and data from a randomised controlled trial on dementia education. The original scale used was the Attitudes toward People Living with Dementia Scale developed by Kim and Kuroda. Test-retest reliability and item response theory analyses were used to reduce the number of items. The reliability, internal consistency, validity, and responsiveness of the short version were evaluated. Six items with low test-retest reliability and four items with low discrimination parameters were removed from the 14-item scale. The APDS4, consisting of four items, had test-retest reliability and internal consistency comparable to those of the original scale. Confirmatory factor analysis indicated that the APDS4 fit a unidimensional model. The validity of the APDS4 was confirmed by significant associations between the APDS4 scores and the original scale scores, knowledge of dementia, helping behaviour intentions toward people living with dementia, helping behaviour experience, attending the Dementia Supporter Training Course, and engagement in healthcare jobs. In a randomised controlled trial dataset, the APDS4 was more responsive to educational interventions than the original scale. The shortened APDS4 was established as a reliable, validated, and responsive scale. This scale can be used efficiently in population surveys to evaluate dementia-friendly initiatives at the community level.

Methods for measuring career readiness of high school students: based on multidimensional item response theory and text mining

In contemporary society, career readiness holds paramount significance for individual life, exerting a direct influence on initial employment, job satisfaction, and the sense of career identity. Framed within multidimensional item response theory and text mining, this study embarks on exploring assessment methodologies for high school students’ career readiness by revising the “Career Readiness Questionnaire – Adolescent Version” and employing text mining techniques. Study One collected 1261 valid data points through cluster sampling. With the aid of Bayesian multivariate item response theory parameter estimation procedures and R language, the career readiness measurement tool was revised, yielding a concise scale that aligns with psychometric requirements. The research findings indicated that the concept of “career readiness” is more suitable for the multidimensional graded response model than for the bifactor model. The dataset’s discrimination parameters fell within the range of [1.59, 3.84], the difficulty parameters fell between [−2.91, 2.24], and the peak values of the maximum information functions fell within [0.24, 2.35]. After six items with the lowest peaks were removed (Items 4, 5, 6, 31, 32, and 33), the remaining 30 items composed the Chinese concise version “Career Readiness Questionnaire – Adolescent Version,” with discrimination parameters ranging from [1.45, 3.38], difficulty parameters between [−3.31, 1.76], and maximum information function peaks within [0.50, 2.64]. Building upon the effective participants from Study One, Study Two matched questionnaire data with textual information, resulting in 1012 valid participants. Leveraging text mining, a machine learning model was constructed to predict high school students’ career readiness based on essay texts. The results of Study 2 prove that the revised lexicon was more accurate in feature extraction. Building upon this, the machine learning model for essay text demonstrated excellent performance in predicting career readiness, with random forest outperforming the other algorithms. This study provides a novel approach for schools and parents to comprehend the state of career readiness among high school students, offering a convenient and effective tool for educational activities related to students’ career development.

Investigate Discriminative AutoEncoder in Few-shot Learning-based Anomaly Detection

Discriminative AutoEncoder (DisAE) plays a crucial role in enhancing the adaptability and gener- alization of few-shot learning methods (DisAEFL) for detecting rare anomalies. DisAE captures meta- knowledge from multiple known tasks, facilitating rapid adaptation in DisAEFL. Key factors like the discriminative parameter (a) and normal proportion (pn) significantly impact DisAEFL performance. However, their influence on the DisAE manifold and DisAEFL’s efficacy in rare cyberattack detection remain understudied in cybersecurity. This study presents an investigative approach to probe DisAE’s influence on DisAEFL’s performance in addressing rare, unseen cyberattacks, aiming to gain insight into the DisAE manifold and outline future research directions. Through intensive analysis, we focus on parameters a and pn, detailing how to examine them to observe DisAE’s effects on DisAEFL. Two main experiments are conducted to investigate their influences. Experimental results on the NSL-KDD dataset reveal a strong correlation between these parameters and both the DisAE manifold and DisAEFL performance. These findings suggest strategies for more efficiently constructing the DisAE manifold to enhance DisAEFL’s adaptability and generalization. Overall, this study contributes to advancing anomaly detection methodologies in cybersecurity by shedding light on the interplay between DisAE, DisAEFL, and crucial parameters.

Development and validation of the MultiScent-20 digital odour identification test using item response theory

Although validated and reliable psychophysical tests of olfactory function are available, an easy-to-use and feasible test has yet to be developed. This study aimed to design a digital odour identification test, evaluate its validity, assess its reliability, establish a normative curve, and explore the impact of demographic factors. The odour identification test was presented with the Multiscent-20, a hand-held, tablet-like digital scent device that features an integrated odour digital delivery system. The identification performance on the 20 odours was assessed using item response theory (IRT). The normative curve was established by administering the test to a large sample of participants (n = 1299). The mean identification score was 17.5 (SD = 2.1). The two-parameter logistic IRT model provided the best fit, revealing variation in item discrimination and difficulty parameters. Educational attainment influenced performance, with primary education associated with lower scores. Additionally, sex was not found to be associated with performance. This study provides initial evidence supporting the validity and reliability of use of the Multiscent-20 as a digital odour identification test. The test’s automation and portability enable the standardized delivery of olfactory stimuli and efficient automatic recording and scoring of responses.

Enhancing Intraoperative Tissue Identification: Investigating a Smart Electrosurgical Knife's Functionality During Electrosurgery.

Detecting the cancerous growth margin and achieving a negative margin is one of the challenges that surgeons face during cancer procedures. A smart electrosurgical knife with integrated optical fibers has been designed previously to enable real-time use of diffuse reflectance spectroscopy for intraoperative margin assessment. In this paper, the thermal effect of the electrosurgical knife on tissue sensing is investigated. Porcine tissues and phantoms were used to investigate the performance of the smart electrosurgical knife after electrosurgery. The fat-to-water content ratio (F/W-ratio) served as the discriminative parameter for distinguishing tissues and tissue mimicking phantoms with varying fat content. The F/W-ratio of tissues and phantoms was measured with the smart electrosurgical knife before and after 14 minutes of electrosurgery. Additionally, a layered porcine tissue and phantom were sliced and measured from top to bottom with the smart electrosurgical knife. Mapping the thermal activity of the electrosurgical knife's electrode during animal tissue electrosurgery revealed temperatures exceeding 400 °C. Electrosurgery for 14 minutes had no impact on the device's accurate detection of the F/W-ratio. The smart electrosurgical knife enables real-time tissue detection and predicts the fat content of the next layer from 4 mm ahead. The design of the smart electrosurgical knife outlined in this paper demonstrates its potential utility for tissue detection during electrosurgery. In the future, the smart electrosurgical knife could be a valuable intraoperative margin assessment tool, aiding surgeons in detecting tumor borders and achieving negative margins.

Assessing Substance Use Disorder Symptoms with a Checklist among Primary Care Patients with Opioid Use Disorder and/or Long-Term Opioid Treatment: An Observational Study.

Primary care (PC) offers an opportunity to treat opioid use disorders (OUD). The Substance Use Symptom Checklist ("Checklist") can assess DSM-5 substance use disorder (SUD) symptoms in PC. To test the psychometric properties of the Checklist among PC patients with OUD or long-term opioid therapy (LTOT) in Kaiser Permanente Washington (KPWA). Observational study using item response theory (IRT) and differential itemfunctioning (DIF) analyses of measurement consistency across age, sex, race and ethnicity, and receipt of treatment. Electronic health records (EHR) data were extracted for all adult PC patients visiting KPWA 3/1/15-8/30/2020 who had ≥ 1 Checklist documented and indication of either (a) clinically-recognized OUD (i.e., documented OUD diagnosis and/or OUD medication treatment) or (b) LTOT in the year prior to the checklist. The Checklist includes 11 items reflecting DSM-5 criteria for SUD. We described the prevalence of 2 SUD symptoms reported on the Checklist (consistent with mild-severe DSM-5 SUD). Analyses were conducted in the overall sample and in two subsamples (clinically-recognized OUD and LTOT only). Among 2007 eligible patients, 39.9% endorsed ≥ 2 SUD symptoms (74.3% in the clinically-recognized OUD subsample and 13.1% in LTOT subsample). IRT indicated that a unidimensional model for the 11 checklist items had excellent fit (comparative fit index = 0.998) with high item-level discrimination parameters for the overall sample and both subsamples. DIF across age, race and ethnicity, and treatment was observed for one item each, but had minimal impact on expected number of criteria (0-11) patients endorse. The Substance Use Symptom Checklist measured SUD symptoms consistent with DSM-5 conceptualization (scaled, unidimensional) in patients with clinically-recognized OUD and LTOT and had similar measurement properties across demographic subgroups. The Checklist may support symptom assessment in patients with OUD and diagnosis in patients with LTOT.

Racism in obstetric care: a psychometric study of the Gendered Racial Microaggressions Scale among Global Majority birthing people in obstetric contexts

In the United States, maternal health inequities disproportionately affect Global Majority (e.g., Asian, Black, and Hispanic) populations. Despite a substantial body of research underscoring the influence of racism on these inequities, little research has examined how experiences of gendered racial microaggressions during pregnancy and birth impact racially and ethnically diverse Global Majority pregnant and birthing people in obstetric hospital settings. We evaluated the psychometric properties of an adapted version of Lewis & Neville’s Gendered Racial Microaggressions Scale, using data collected from 417 Global Majority birthing people. Findings from our study indicate that our adapted GRMS is a valid tool for assessing the experiences of gendered racial microaggressions in hospital-based obstetric care settings among Global Majority pregnant and birthing people whose preferred languages are English or Spanish. Item Response Theory (IRT) analysis demonstrated high construct validity of the adapted GRMS scale (Root Mean Square Error of Approximation = 0.1089 (95% CI 0.0921, 0.1263), Comparative Fit Index = 0.977, Standardized Root Mean Square Residual = 0.075, log-likelihood c2 = -85.6, df = 8). IRT analyses demonstrated that the unidimensional model was preferred to the bi-dimensional model as it was more interpretable, had lower AIC and BIC, and all items had large discrimination parameters onto a single factor (all discrimination parameters > 3.0). Given that we found similar response profiles among Black and Hispanic respondents, our Differential Item Functioning analyses support validity among Black, Hispanic, and Spanish-speaking birthing people. Inter-item correlations demonstrated adequate scale reliability, α = 0.97, and empirical reliability = 0.67. Pearsons correlations was used to assess the criterion validity of our adapted scale. Our scale’s total score was significantly and positively related to postpartum depression and anxiety. Researchers and practitioners should seek to address instances of gendered racial microaggressions in obstetric settings, as they are manifestations of systemic and interpersonal racism, and impact postpartum health.

Development of the Vietnamese Rape Myths Acceptance Scales: A Web-Based Survey of Young Adults.

Rape myths-false but widely held beliefs that serve to deny and justify sexual aggression-present a major barrier to reporting and prevention of sexual violence in Vietnam and globally. Based on a parent study aimed at reducing sexual violence at two universities in Hanoi, we developed and assessed a contextualized measure of rape myths among young people in Vietnam. Items from previously validated rape myth acceptance (RMA) scales and data from qualitative research informed the development of 50 items, which were administered to Vietnamese 18-24-year-olds (n = 2,756 total, n = 1,798 cisgender women) via an anonymous link in February 2021. We used factor analysis to explore and test factor structure and multi-group factor analysis to assess measurement equivalence across gender. We calculated item-level discrimination and difficulty parameters and visualized information curves using item response theory analysis, informing the development of a short form. Four hypothesized subconstructs identified in the qualitative data emerged as factors: (1) "He didn't mean to"; (2) "She asked for it"; (3) "It wasn't really rape"; and (4) "Rape is a deviant event." A fifth factor, "She didn't protect herself," included four items from formative data. Confirming formative findings and prior literature, cisgender women had lower RMA than cisgender men, particularly on items related to victim-blaming. The Vietnamese Rape Myths Acceptance Scales were internally consistent and equivalent between cisgender men and women, capturing elements specific to the Vietnamese context and providing a tool for campus climate surveys and evaluations of sexual violence prevention programs.

Waveform simulation for scintillation characteristics of NaI(Tl) crystal

The lowering of the energy threshold in the NaI detector is crucial not only for comprehensive validation of DAMA/LIBRA but also for exploring new possibilities in the search for low-mass dark matter and observing coherent elastic scattering between neutrino and nucleus. Alongside hardware enhancements, extensive efforts have focused on refining event selection to discern noise, achieved through parameter development and the application of machine learning. Acquiring pure, unbiased datasets is crucial in this endeavor, for which a waveform simulation was developed. The simulation data were compared with the experimental data using several pulse shape discrimination parameters to test its performance in describing the experimental data. Additionally, we present the outcomes of multi-variable machine learning trained with simulation data as a scintillation signal sample. The distributions of outcomes for experimental and simulation data show a good agreement. As an application of the waveform simulation, we validate the trigger efficiency alongside estimations derived from the minimally biased measurement data.

Effects of hydroxyl radical oxidation on the stability and biochemical functions of rex rabbit meat

Reactive oxygen species (ROS)-generating system in muscle food is an important factor as it greatly influences shelf life and quality of meat. In this study, whole muscle homogenate was used as the research object, and the Fenton reaction system as an inducer was established for analyzing the effect of oxidation on Chuanbai Rex and Hyla rabbits meat. The homogenates were exposed to varying concentrations of hydrogen peroxide (H2O2, 0, 2, 4, 6, 8, and 10 mmol/L), the level of lipid oxidation of both breeds increased with the increased H2O2 concentration, while Hyla rabbits was higher. Oxidation and molecular aggregation of myofibrillar protein (MP) was observed in both breeds, including formation of carbonyl compounds, depleted sulphydryl, and increased hydrophobicity while fluorescence decreased. After oxidation, the loss of amino acids was higher in Hyla (16%) than in Rex rabbits (11%). Cys content was identified as the most discriminant parameter capable of elucidating the variations between the two breeds under this oxidation system.