Scoring Procedure Research Articles

Determinants of Efficient Needs Delivery to Farmers of Odisha, India: A Multi-approach Constraint Analysis

Extension and Advisory Service (EAS) providers serve as the primary means of delivering these needs and play a crucial role in improving agricultural output; yet, farmers have challenges related to the effective implementation of these services. This study seeks to identify the primary challenges encountered by farmers in Odisha. Utilizing an exploratory study design with two methodologies, namely Mean Percent Score and Garrett's Ranking procedure, the issues were prioritized. Farmers had challenges with the EAS in three primary domains: social skills, empowerment, and innovation adoption. Poor leadership development training under the Social Skill with a mean garret score with 77.14 ranked 1, the casual approach from EAS towards empowerment issues under empowerment with a mean garret score of 77.07 ranked 2 and finally high investment required for adopting recommended practices ranked third in the Adoption of Innovation with a mean garret score of 76.81. The study proposes targeted solutions to the challenges encountered by farmers in the region via a collaborative approach involving all stakeholders.

Investigating the quality of a high-stakes EFL writing assessment procedure in the Turkish higher education context

Employing G-theory and rater interviews, the study investigated how a high-stakes writing assessment procedure (i.e., a single-task, single-rater, and holistic scoring procedure) impacted the variability and reliability of its scores within the Turkish higher education context. Thirty-two essays written on two different writing tasks (i.e., narrative and opinion) by 16 EFL students studying at a Turkish state university were scored by 10 instructor raters both holistically and analytically. After the raters completed the scoring procedure, semi-structured individual interviews were held with them to gain insight into their views regarding the quality of the current scoring procedure. The G-theory results showed that the reliability coefficients obtained from the current scoring procedure would not be sufficient to draw sound conclusions. The quantitative results were partly supported by the qualitative data. Important implications were discussed to improve the quality of the current high-stakes EFL writing assessment policy.

An improved diagrammatic procedure for interpreting and scoring the Wisconsin Card Sorting Test: An update to Steve Berry’s 1996 edition

The Wisconsin Card Sorting Test (WCST) is a popular neuropsychological test that is complicated to score and interpret. In an attempt to make scoring of the WCST simpler, Berry (The Clinical Neuropsychologist 10, 117–121, 1996) developed a diagrammatic scoring procedure, particularly to aid scoring of perseverative responses. We identified key limitations of Berry’s diagram, including its unnecessary ambiguity and complexity, use of terminology different from that used in the standardized WCST manual, and lack of distinction between perseverative errors and perseverative responses. Our new diagrammatic scoring procedure scores each response one-by-one; we strongly suggest that the diagram is used in conjunction with the 1993 WCST manual. Our new diagrammatic scoring procedure aims to assist novice users in learning how to accurately score the task, prevent scoring errors when using the manual version of the task, and help scorers verify whether other existing computerized versions of the task (apart from the PAR version) conform to the Heaton et al. (1993) scoring method. Our diagrammatic scoring procedure holds promise to be incorporated into any future versions of the WCST manual.

Depth of Hydrogel Spacer Rectal Wall Infiltration Was Not Associated With Rectal Toxicity: Results From a Randomized Prospective Trial

Rectal spacers have gained popularity as a dose-sparing material for prostate cancer radiation therapy (RT). However, the procedure can be associated with unintended rectal wall infiltration (RWI) of the spacer gel. We therefore classified RWI severity as a function of depth and explored its association with rectal toxicity using a data set from prostate cancer patients treated with RT on a prospective randomized clinical trial (RCT). Postimplant T2-weighted magnetic resonance images of 149 subjects randomized to the hydrogel spacer arm of a published multicenter RCT were assessed for the presence and depth of RWI. All implants were assigned a score of 0 (no rectal wall signal changes), 1 (rectal wall edema/signal change), 2 (partial RWI), or 3 (full-thickness RWI); RWI was defined as a score of 2 or 3. Correlations were made between RWI score and physician-reported procedure, acute, and late rectal toxicity. Although 62.4% of implants had no rectal wall signal abnormalities, 24% [scores of 2 (20.1%) and 3 (4.0%)] of procedures exhibited radiographic evidence of RWI. Full-thickness RWI was associated with both a longer length (22.8 ± 7.0 mm, P = .008) and a larger circumferential percentage (35.8% ± 9.2%, P = .045) of rectal infiltration. Although 7 subjects (5%) experienced transient procedure-related rectal toxicities (most commonly perineal/rectal pain), only one had RWI (score of 2, National Cancer Institute's Common Terminology Criteria for Adverse Events grade 1). Consequently, no correlation was observed between procedural rectal toxicity and the presence/extent of RWI (P = .64). Similarly, no difference in acute (P = .64) or late (P = .85) rectal toxicity incidence or grade was detected between RWI categories; none of the 6 men with a RWI score of 3 developed late rectal toxicity by 15 months. Based on data from an RCT, RWI did not contribute to increased rectal toxicity prior and up to 15 months after conventional prostate cancer RT.

Cross-ValidatedFunctional Generalized Partially Linear Single-Functional Index Model

In this paper, we have introduced a functional approach for approximating nonparametric functions and coefficients in the presence of multivariate and functional predictors. By utilizing the Fisher scoring algorithm and the cross-validation technique, we derived the necessary components that allow us to explain scalar responses, including the functional index, the nonlinear regression operator, the single-index component, and the systematic component. This approach effectively addresses the curse of dimensionality and can be applied to the analysis of multivariate and functional random variables in a separable Hilbert space. We employed an iterative Fisher scoring procedure with normalized B-splines to estimate the parameters, and both the theoretical and practical evaluations demonstrated its favorable performance. The results indicate that the nonparametric functions, the coefficients, and the regression operators can be estimated accurately, and our method exhibits strong predictive capabilities when applied to real or simulated data.

The Effect of the Seed of Descurainia Sophia on Functional Constipation in Iranian Women Aged 50-70 Years: A Randomized Controlled Trial

Background: Constipation in older adults is a common issue and is more prevalent in women. The current study aimed to assess the effectiveness of the seed of Descurainia Sophia as an herbal medicine on the severity of constipation in older women. Methods: Total, sixty-four women aged between 50 to 70 participated in the study. The study used a randomized controlled trial to investigate the effectiveness of the seed of Descurainia Sophia on constipation. Data were collected using a constipation assessment scale and analyzed using independent samples t-test and gain score procedure. Results: It was shown that taking a mixture of water and seeds of Descurainia Sophia significantly reduces constipation severity in older women. Conclusion: It was concluded that the seed of Descurainia Sophia is a safe and effective alternative for treating constipation in older women.

Two-Part Mixed Effects Mixture Model for Zero-Inflated Longitudinal Compositional Data

Compositional data (CD) is mostly analyzed using ratios of components and log-ratio transformations to apply known multivariable statistical methods. Therefore, CD where some components equal zero represents a problem. Furthermore, when the data is measured longitudinally, and appear to come from different sub-populations, the analysis becomes highly complex. Our objective is to build a statistical model addressing structural zeros in longitudinal CD and apply it to the analysis of radiation-induced lung damage (RILD) over time. We propose a two-part mixed-effects model extended to the case where the non-zero components of the vector might come from a two-component mixture population. Maximum likelihood estimates for fixed effects and variance components were calculated by an approximate Fisher scoring procedure base on sixth-order Laplace approximation. The expectation-maximization (EM) algorithm estimates the mixture model’s probability. This model was used to analyze the radiation therapy effect on tissue change in one patient with non-small cell lung cancer (NSCLC), utilizing five CT scans over 24 months. Instead of using voxel-level data, voxels were grouped into larger subvolumes called patches. Each patch’s data is a CD vector showing proportions of dense, hazy, or normal tissue. Proposed method performed reasonably for estimation of the fixed effects, and their variability. However, the model produced biased estimates of the nuisance parameters in the model.

Utilizing Aerobic Capacity Data for EDSS Score Estimation in Multiple Sclerosis: A Machine Learning Approach.

The Expanded Disability Status Scale (EDSS) is the most popular method to assess disease progression and treatment effectiveness in patients with multiple sclerosis (PwMS). One of the main problems with the EDSS method is that different results can be determined by different physicians for the same patient. In this case, it is necessary to produce autonomous solutions that will increase the reliability of the EDSS, which has a decision-making role. This study proposes a machine learning approach to predict EDSS scores using aerobic capacity data from PwMS. The primary goal is to reduce potential complications resulting from incorrect scoring procedures. Cardiovascular and aerobic capacity parameters of individuals, including aerobic capacity, ventilation, respiratory frequency, heart rate, average oxygen density, load, and energy expenditure, were evaluated. These parameters were given as input to CatBoost, gradient boosting (GBM), extreme gradient boosting (XGBoost), and decision tree (DT) machine learning methods. The most significant EDSS results were determined with the XGBoost algorithm. Mean absolute error, root mean square error, mean square error, mean absolute percent error, and R square values were obtained as 0.26, 0.4, 0.26, 16, and 0.68, respectively. The XGBoost based machine learning technique was shown to be effective in predicting EDSS based on aerobic capacity and cardiovascular data in PwMS.

Unveiling Off-Target Mutations in CRISPR Guide RNAs: Implications for Gene Region Specificity.

The revolutionary CRISPR-Cas9 technology has revolutionized genetic engineering, and it holds immense potential for therapeutic interventions. However, the presence of off-target mutations and mismatch capacity poses significant challenges to its safe and precise implementation. In this study, we explore the implications of off-target effects on critical gene regions, including exons, introns, and intergenic regions. Leveraging a benchmark dataset and using innovative data preprocessing techniques, we have put forth the advantages of categorical encoding over one-hot encoding in training machine learning classifiers. Crucially, we use latent class analysis (LCA) to uncover subclasses within the off-target range, revealing distinct patterns of gene region disruption. Our comprehensive approach not only highlights the critical role of model complexity in CRISPR applications but also offers a transformative off-target scoring procedure based on ML classifiers and LCA. By bridging the gap between traditional target-off scoring and comprehensive model analysis, our study advances the understanding of off-target effects and opens new avenues for precision genome editing in diverse biological contexts. This work represents a crucial step toward ensuring the safety and efficacy of CRISPR-based therapies, underscoring the importance of responsible genetic manipulation for future therapeutic applications.

Potential non-invasive detection of lesions in broiler femur heads: application of the DXA imaging system.

Leg health is a significant economic and welfare concern for the poultry industry. Current methods of detection rely on visual assessment of the legs and gait scores and bone scoring during necropsy for full characterization. Additionally, the current scoring of femurs only examines the external surface of the femoral head. Through the use of the dual-energy X-ray absorptiometry (DXA) imaging system, we show the presence of a necrotic region in the femurs that would otherwise be considered healthy based on the current evaluation procedures. Importantly, these lesions were present in almost 60% (22 of 37) of femurs that scored normal for femoral head necrosis (FHN). Additionally, these femurs showed greater bone mineral content (BMC) relative to weight compared to their counterparts with no lucent lesions (6.95% ± 0.20% vs. 6.26% ± 0.25; p = 0.038). Identification of these lesions presents both a challenge and an opportunity. These subclinical lesions are likely to be missed in routine scoring procedures for FHN and can inadvertently impact the characterization of the disease and genetic selection programs. Furthermore, this imaging system can be used for in vivo, ex vivo, and embryonic (egg) studies and, therefore, constitutes a potential non-invasive method for early detection of bone lesions in chickens and other avian species.

The struggle within dual systems of government: dealing with conflict between traditional leaders and ward councilors in the greater Giyani Municipality in South Africa

IntroductionCurrent frameworks of conflict resolution have shown only partial success, particularly in the context of local municipalities where conflicts persist. There is a pressing need for context-specific framework that address leadership conflicts while fostering peace.MethodsTo address the lack of progress in resolving conflicts, this study identifies major challenges undermining the assimilation and implementation of objectively informed conflict resolution strategies. A purposive sampling method was employed to select 33 respondents from the Greater Giyani Municipality. Data were collected through semistructured interviews and analyzed using statistically established matrix scoring procedures. ATLAS.ti software was utilized for data analysis.ResultsWithout claiming to be exhaustive, this paper highlights examples of externalities that threaten the coexistence of the dual system of governance in South African communities, with a focus on leadership conflict and unsustainable peace. Factors contributing to conflict escalation include capacity constraints, lack of inclusive, bias, divisive decision-making and contested court decisions.DiscussionThe study underscores the importance of addressing these challenges to foster effective conflict resolution. It emphasizes the need for the scientific community to provide critical information necessary for responding effectively to these challenges.ConclusionTo enhance conflict resolution in local municipalities, it is imperative to develop context-specific frameworks that address underlying challenges and promote sustainable peace. This requires concerted efforts from both researchers and practitioners to provide the necessary insights and strategies for resolution.

Visual-motor integration in children with unilateral cerebral palsy: application of the computer-aided measure of visual-motor integration

BackgroundChildren with unilateral cerebral palsy (UCP) are encouraged to participate in the regular school curriculum. However, even when using the less-affected hand for handwriting, children with UCP still experience handwriting difficulties. Visual-motor integration (VMI) is a predictor of handwriting quality. Investigating VMI in children with UCP is important but still lacking. Conventional paper-based VMI assessments is subjective and use all-or-nothing scoring procedures, which may compromise the fidelity of VMI assessments. Moreover, identifying important shapes that are predictive of VMI performance might benefit clinical decision-making because different geometric shapes represent different developmental stepping stones of VMI. Therefore, a new computer-aided measure of VMI (the CAM-VMI) was developed to investigate VMI performance in children with UCP and to identify shapes important for predicting their VMI performance.MethodsTwenty-eight children with UCP and 28 typically-developing (TD) children were recruited. All participants were instructed to complete the CAM-VMI and Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery-VMI). The test items of the CAM-VMI consisted of nine simple geometric shapes related to writing readiness. Two scores of the CAM-VMI, namely, Error and Effort, were obtained by image registration technique. The performances on the Beery-VMI and the CAM-VMI of children with UCP and TD children were compared by independent t-test. A series of stepwise regression analyses were used to identify shapes important for predicting VMI performance in children with UCP.ResultsSignificant group differences were found in both the CAM-VMI and the Beery-VMI results. Furthermore, Error was identified as a significant aspect for predicting VMI performance in children with UCP. Specifically, the square item was the only significant predictor of VMI performance in children with UCP.ConclusionsThis study was a large-scale study that provided direct evidence of impaired VMI in school-aged children with UCP. Even when using the less-affected hand, children with UCP could not copy the geometric shapes as well as TD children did. The copied products of children with UCP demonstrated poor constructional accuracy and inappropriate alignment. Furthermore, the predictive model suggested that the constructional accuracy of a copied square is an important predictor of VMI performance in children with UCP.

SEMIPARAMETRIC ESTIMATION OF DYNAMIC BINARY CHOICE PANEL DATA MODELS

We propose a new approach to the semiparametric analysis of panel data binary choice models with fixed effects and dynamics (lagged dependent variables). The model under consideration has the same random utility framework as in Honoré and Kyriazidou (2000, Econometrica 68, 839–874). We demonstrate that, with additional serial dependence conditions on the process of deterministic utility and tail restrictions on the error distribution, the (point) identification of the model can proceed in two steps, and requires matching only the value of an index function of explanatory variables over time, rather than the value of each explanatory variable. Our identification method motivates an easily implementable, two-step maximum score (2SMS) procedure – producing estimators whose rates of convergence, in contrast to Honoré and Kyriazidou’s (2000, Econometrica 68, 839–874) methods, are independent of the model dimension. We then analyze the asymptotic properties of the 2SMS procedure and propose bootstrap-based distributional approximations for inference. Evidence from Monte Carlo simulations indicates that our procedure performs satisfactorily in finite samples.

Flood vulnerability assessment trough overlay-scoring data method based on Geographical Information System (GIS) in Giriwoyo, Wonogiri, Indonesia

The Sub-District of Giriwoyo, located on the southern edge of Wonogiri District, is classified as an agricultural land. This subdistrict is located in the Keduang sub-watershed. This geographical condition makes this subdistrict extremely vulnerable to flooding. This research seeks to determine the distribution of flood-prone areas and categorize the level of flood vulnerability in the Wonogiri Regency, with Giriwoyo as a research site. Quantitative descriptive research employs a scoring procedure based on environmental conditions-related scoring parameters. These variables include slope, soil type, rainfall, altitude, land use, and buffers for river flow. The measured parameters are then layered in a geographic information system (GIS) application to generate a flood vulnerability map. The data analysis procedure employed a descriptive approach. The results indicate that the dispersed, areas of Giriwoyo are classified into 4 vulnerability catogeries such as not vulnerable, vulnerable enough, vulnerable and very vulnerable. Areas with vulnerable categories are scattered throughout the giriwoyo area which is dominated by rice fields and settlements with a flat slope. The very vulnerable area dominates the western part of the giriwoyo which has a lower elevation and flat slope. The parts of giriwoyo that are not prone to flooding are in Selomarto, Tukulrejo, and Girikikis.

An incremental method-based machine learning approach for max–min knapsack with multiple scenarios

In this paper, the max–min knapsack problem with multiple scenarios is addressed using an incremental method-based machine learning approach. The method is structured around three key phases: a learning phase, an exploitation phase, and an exploration phase. During the learning phase, the algorithm initiates by generating a sequential set of initial elite solutions through a Q-table scoring procedure. Moving on to the exploitation phase, the goal is to improve the quality of the current solution through an intensification-based tabu search, emphasizing iterative solution optimization. The exploration phase introduces controlled randomness to diversify exploration, revealing promising sub-spaces and facilitating the discovery of new solutions. This iterative process results in a series of new elite solutions, some of which are combined to highlight the method’s efficiency. To maintain diversity, a new fusion operator is introduced, where couples related to elite solutions are combined, forming an incremental subset of elite solutions capable of exploring new solution subspaces. The proposed method is evaluated using benchmark instances from the literature, and its results are compared to those provided by recently published algorithms. The computational analysis underscores the algorithm’s competitiveness in producing high-quality solutions, often surpassing previously published methods with superior solution bounds.

Performance Analysis of Driving Ability (P-Drive): Investigating Construct Validity and Concordance of Australasian Data.

On-road assessment is optimal for determining medical fitness-to-drive but unreliable if determined by global pass/fail decisions alone. Occupational therapists need standardized, psychometrically sound on-road scoring procedures. Performance Analysis of Driving Ability (P-Drive) is a promising on-road test developed in Sweden, but it has not been standardized for Australasia. We investigated the psychometric properties and concordance with an on-road decision of data gathered with the Australasian version of P-Drive. P-Drive was administered to older and cognitively impaired drivers (N = 134) aged 18 to 91 years (mean age 68) who were referred to 10 driving clinics in Australia and New Zealand to determine driving performance. Rasch analysis provided evidence for construct validity and concordance of the data gathered. An optimal cut-off score of 85 was set, yielding evidence of good sensitivity at 88% and specificity at 88%. The Australasian version of P-Drive produces valid and reliable data regarding on-road driving performance.

Assessing risk factors associated with breakthrough early post-traumatic seizures in patients receiving phenytoin prophylaxis.

Post-traumatic seizure (PTS) is a well-known complication of traumatic brain injury (TBI). The objective of this study was to identify risk factors associated with breakthrough early PTS in TBI patients receiving phenytoin prophylaxis. This was a single-centered retrospective study including adult patients admitted to the intensive care unit (ICU), had a TBI, and started on phenytoin for seizure prophylaxis within 24 h of admission. The primary outcome was the incidence and factors associated with early PTS, defined as a confirmed seizure on a continuous electroencephalogram within 7 days of TBI. Secondary outcomes included the association between early post-traumatic seizures and ICU length of stay, hospital length of stay, and in-hospital mortality. A total of 105 patients were included in the final analysis. Patients with early PTS were older (65 vs. 48 years old, p = 0.01), had a higher Marshall score (5 vs. 2, p = 0.01), were more likely to have a Marshall score > 2 (73 vs. 37%, p = 0.01), and had more neurosurgeries for hematoma evacuation (57 vs. 19%, p = 0.01). In patients with early PTS, 57% had a level at the time of seizure, and of those, 87.5% had a therapeutic level (>10 mcg/mL). Patients with early PTS had a longer ICU length of stay (14.7 vs. 5.9 days, p = 0.04) and a greater proportion of hospital mortality (21 vs. 2%, p = 0.02). Patients with higher age, Marshall score, and neurosurgical procedures for hematoma evacuation had higher incidences of breakthrough early PTS despite the use of phenytoin prophylaxis. The majority of patients with early PTS had therapeutic phenytoin levels at the time of seizure when a level was available; however, approximately half (43%) did not have a level.

МОДЕЛИРОВАНИЕ ВЕРОЯТНОСТИ БАНКРОТСТВА КОМПАНИЙ СТРОИТЕЛЬНОЙ ОТРАСЛИ

Due to the unstable economic situation, companies are facing financial difficulties, so their assessment of the likelihood of bankruptcy in the short term is more than relevant. This article reflects the main results of building a model for predicting the probability of bankruptcy of companies in the construction industry: companies, developers. The model was built using a statistical method – logistic regression. The sample of the study included operating construction companies that operate on the territory of the Russian Federation and bankrupt companies. Initially, the study sample consisted of 132 companies, data on which were collected using the Russian reference and information system SPARK. The total sample of the study was divided into training and test in the ratio of 80% and 20%, respectively. The endogenous variable was a binary one, and the exogenous variables were 10 financial indicators selected by experts based on a literature review. As a result, the following factors turned out to be significant: solvency ratio; coverage ratio; asset turnover ratio. According to the results of the study, the accuracy of predicting bankrupt companies of the author's model is 76,2%, and nonbankrupt 83,3%. The overall predictive power of the logit model is 78%. The obtained model for predicting the probability of bankruptcy of companies in the construction industry, firms that operate in the wholesale and retail trade in building materials and goods for repairs, can be introduced into their scoring system for assessing the reliability of counterparties in order to conduct a more accurate scoring procedure and minimize financial risks.

The ANALYSIS OF THE SPONTANEITY SPEECH IN SPEAKING ASSESSMENT AT INSTITUTION OF FOREIGN LANGUAGE DEVELOPMENT AL-YASINI PASURUAN

Speaking is more than just creating and constructing sentences correctly and with proper grammar, but the ability to speak has a broad scope, such as in the fields of mechanics, functions, pragmatics, communication, and social interaction. To find out the students' ability, the teacher gives them a test. As an assessment, the teacher conducts a speaking test to find out how well students speak and their progress in learning. The speaking test is a procedure to measure students' speaking ability in which students are required to speak aloud, conveying their ideas, and then students are graded based on their speech. This research was conducted at LPBA Al-Yasini where the researchers focused on the scoring procedure for the spontaneity speech in assessing the students’ speaking skill. This research was descriptive-qualitative method. The result of the research was there are several aspect that used by LPBA to assess spontaneity speech, which are fluency, grammar, vocabulary, comprehension, pronunciation they are then divided into three categories, which are body language, delivery and content.

The Acquisition of Black Language by Spanish-Speaking Preschoolers: A Community-Based Sociolinguistic Approach to Language Assessment.

The purpose of this case series was to demonstrate a community-based sociolinguistic approach to language sample analysis (LSA) for the evaluation of Spanish-English bilingual preschoolers acquiring Black language (BL). As part of a comprehensive bilingual speech-language evaluation, we examined sociolinguistic variables in the context of the children's English language samples. Specific emphasis is placed on sociolinguistic information to account for all language(s) and dialect(s) in each child's environment, BL feature patterns, and appropriate scoring procedures for characterizing language use. This case series includes four monolingual English-speaking and four bilingual Spanish-English-speaking 4-year-olds in a linguistically diverse preschool program. Play samples were collected from each child and coded for morphosyntactic features across three categories: BL, Spanish-Influenced English, and shared. Measures derived from the language samples include percent grammatical utterances, mean length of utterance in words, and number of different words. The children's language is characterized within a community-based sociolinguistic approach that combines three culturally responsive methods for assessment found in the speech-language pathology literature in addition to a novel sociolinguistic questionnaire. We explain how conducting LSA using a community-based sociolinguistic approach yields diagnostically relevant information that is pertinent to conducting a comprehensive and accurate evaluation of preschoolers in linguistically diverse settings without the use of standardized assessments. A community-based sociolinguistic approach to LSA is a useful procedure for mitigating misdiagnosis in preschoolers reared in linguistically diverse environments.