Count Distribution Research Articles

Global species hotspots and COI barcoding cold spots of marine Gastropoda

With the on-going efforts in digitising museum collections, increased participation of citizen scientists, and greater accessibility to research data, accurately determining global patterns of diversity has become more achievable. Here, we used occurrence records from the Global Biodiversity Information Facility, with annotation of authoritative taxonomy, to evaluate the taxonomic richness of marine gastropods and to identify global species hotspots for this group. We also reviewed the availability of genetic resources within hotspots to detect potentially important regions where reference sequences for identifying these organisms are wanting. We find 33,268 unique and valid species under 3291 genera belonging to 380 gastropod families that have been recorded from 1662 to 2023. Globally, only 12.1% of reported species are linked to a COI barcode, whilst 27.1% of the families are represented with complete mitogenomes. Georeferenced records show the wide albeit disparate distribution of observations and species counts. The compiled dataset, published by organisations that are restricted to 55 countries, reveal a seeming lack of local submissions, but nonetheless demonstrates the growing contribution of citizen science platforms. We present 28 marine provinces across the globe as putative gastropod species hotspots and call for further work and stronger involvement, particularly within COI barcoding cold spots, to address the observed genetic reference inequity. Lastly, we highlight the important and relevant role of open and inclusive science to biodiversity monitoring and research.

Biomass burning records of the Shulehe Glacier No. 4 from Qilian Mountains, Northeastern Tibetan Plateau

Biomass burning play a key role in the global carbon cycle by altering the atmospheric composition, and affect regional and global climate. Despite its importance, a very few high-resolution records are available worldwide, especially for recent climate change. This study analyzes levoglucosan, a specific tracer of biomass burning emissions, in a 38-year ice core retrieved from the Shulehe Glacier No. 4, northeastern Tibetan Plateau. The levoglucosan concentration in the Shulehe Glacier No. 4 ice core ranged from 0.1 to 55 ng mL−1, with an average concentration of 8 ± 8 ng mL−1. The concentrations showed a decreasing trend from 2002 to 2018. Meanwhile, regional wildfire activities in Central Asian also exhibited a declining trend during the same period, suggesting the potential correspondence between levoglucosan concentration of the Shulehe Glacier No. 4 ice core and the fire activity of Central Asia. Furthermore, a positive correlation also exists between the levoglucosan concentration of the Shulehe Glacier No. 4 ice core and the wildfire counts in Central Asia from 2002 to 2018. While backward air mass trajectory analysis and fire spots data showed a higher distribution of fire counts in South Asia compared to Central Asia, but the dominance of westerly circulation in the northern TP throughout the year. Therefore, the levoglucosan in the Shulehe Glacier No. 4 provides clear evidence of Central Asian wildfire influence on Tibetan Plateau glaciers through westerlies. This highlights a great importance of ice core data for wildfire history reconstruction in the Tibetan Plateau Glacier regions.

Rural-Urban mild cognitive impairment comparison in West Michigan through EHR.

Mild cognitive impairment (MCI) is a significant public health concern and a potential precursor to Alzheimer's disease (AD). This study leverages electronic health record (EHR) data to explore rural-urban differences in MCI incidence, risk factors, and healthcare navigation in West Michigan. Analysis was conducted on 1,528,464 patients from Corewell Health West, using face-to-face encounters between 1/1/2015 and 7/31/2022. MCI cases were identified using International Classification of Diseases (ICD) codes, focusing on patients aged 45+ without prior MCI, dementia, or AD diagnoses. Incidence rates, cumulative incidences, primary care physicians (PCPs), and neuropsychology referral outcomes were examined across rural and urban areas. Risk factors were evaluated through univariate and multivariate Cox regression analyses. The geographic distribution of patient counts, hospital locations, and neurology department referrals were examined. Among 423,592 patients, a higher MCI incidence rate was observed in urban settings compared to rural settings (3.83 vs. 3.22 per 1,000 person-years). However, sensitivity analysis revealed higher incidence rates in rural areas when including patients who progressed directly to dementia. Urban patients demonstrated higher rates of referrals to and completion of neurological services. While the risk factors for MCI were largely similar across urban and rural populations, urban-specific factors for incident MCI are hearing loss, inflammatory bowel disease, obstructive sleep apnea, insomnia, being African American, and being underweight. Common risk factors include diabetes, intracranial injury, cerebrovascular disease, coronary artery disease, stroke, Parkinson's disease, epilepsy, chronic obstructive pulmonary disease, depression, and increased age. Lower risk was associated with being female, having a higher body mass index, and having a higher diastolic blood pressure. This study highlights rural-urban differences in MCI incidence and access to care, suggesting potential underdiagnosis in rural areas likely due to reduced access to specialists. Future research should explore socioeconomic, environmental, and lifestyle determinants of MCI to refine prevention and management strategies across geographic settings. Leveraged EHRs to explore rural-urban differences in MCI in West Michigan.Revealed a significant underdiagnosis of MCI, especially in rural areas.Observed lower rates of neurological referrals and completions for rural patients.Identified risk factors specific to rural and urban populations.

A Marginalized Zero-Inflated Negative Binomial Model for Spatial Data: Modeling COVID-19 Deaths in Georgia.

Spatial count data with an abundance of zeros arise commonly in disease mapping studies. Typically, these data are analyzed using zero-inflated models, which comprise a mixture of a point mass at zero and an ordinary count distribution, such as the Poisson or negative binomial. However, due to their mixture representation, conventional zero-inflated models are challenging to explain in practice because the parameter estimates have conditional latent-class interpretations. As an alternative, several authors have proposed marginalized zero-inflated models that simultaneously model the excess zeros and the marginal mean, leading to a parameterization that more closely aligns with ordinary count models. Motivated by a study examining predictors of COVID-19 death rates, we develop a spatiotemporal marginalized zero-inflated negative binomial model that directly models the marginal mean, thus extending marginalized zero-inflated models to the spatial setting. To capture the spatiotemporal heterogeneity in the data, we introduce region-level covariates, smooth temporal effects, and spatially correlated random effects to model both the excess zeros and the marginal mean. For estimation, we adopt a Bayesian approach that combines full-conditional Gibbs sampling and Metropolis-Hastings steps. We investigate features of the model and use the model to identify key predictors of COVID-19 deaths in the US state of Georgia during the 2021 calendaryear.

A comparative analysis of several multivariate zero-inflated and zero-modified models with applications in insurance

. Given that insurance companies often operate across multiple lines of insurance business, where claim frequencies on different lines are often correlated, it often becomes advantageous to employ multivariate count modeling where dependence between lines of business can be included in the modeling. Due to the operation of bonus-malus systems where there is a reward to the insurance policyholder for not claiming, claims data in automobile insurance often exhibits an excess of common zeros, a characteristic known as multivariate zero-inflation. In this article, we propose two approaches to address this feature. The first approach involves utilizing a multivariate zero-inflated model, where we artificially enhance the probability of common zeros based on standard multivariate count distributions. The second approach applies a multivariate zero-modified model, which separately handles the common zeros and the number of claims incurred in each line given that at least one claim occurs. We present several models under these frameworks, along with detailed inference procedures. In the applications section, we conduct a comprehensive comparative analysis of these models using data from an automobile insurance portfolio.

Land Cover Disaggregated Fire Occurrence and Particulate Matter2.5 Relationship in the Mekong Region: A Comprehensive Study

Air pollution has become an increasing concern in the Mekong region due to seasonal vegetative burning triggered by related anthropogenic activities and climate change. While the assumption of a correlation between agriculture burning and air pollution is a common postulation, little evidence exists on the association between fire incidents and air pollution concentrations. The current study explores the relationship between satellite-derived fire occurrence, land surface characteristics, and particulate matter 2.5 (PM2.5) concentrations for the five Lower Mekong countries, namely Cambodia, Laos, Myanmar, Thailand, and Vietnam, in an effort to gain new insights into fire distributions related to air quality. Publicly available daily active fire hotspots from the VIIRS satellite instrument, annual land cover products from the MODIS satellite, and mean monthly ground-level PM2.5 estimates from the V5.GL.04 database were analyzed in two relational assessments; first, the distribution of VIIRS active fire counts and fire radiative power (FRP) temporally and spatially and secondly, the correlations between the monthly VIIRS active fire counts, cumulative monthly FRP and mean monthly PM2.5 estimates per country and land cover type. The results suggest a statistically significant positive correlation between monthly fire counts, cumulative FRP, and PM2.5 estimates for each country, which differ based on land cover. The strongest correlation between monthly fire incidences and PM2.5 estimates was found in the case of Myanmar. For all countries combined, fires detected in forests displayed the highest correlation with monthly PM2.5 estimates. This study demonstrates the use of the VIIRS active fire product and provides important insights into temporal and spatial fire distributions as baseline information for fire prevention and mitigation strategies in the Mekong region.

Simplified and Detailed Evaluations of the Uncertainty of the Measurement of Microbiological Contamination of Pharmaceutical Products.

The control of the microbial contamination of pharmaceutical products (PP) is crucial to ensure their safety and efficacy. The validity of the monitoring of such contamination depends on the uncertainty of this quantification. Highly uncertain quantifications due to the variability of determinations or the magnitude of systematic effects affecting microbial growth or other analytical operations make analysis unfit for the intended use. The quantification of the measurement uncertainty expressing the combined effects of all random and systematic effects affecting the analysis allows for a sound decision about quantification adequacy for their intended use. The complexity of the quantification of microbial analysis uncertainty led to the development of simplified ways of performing this evaluation. This work assesses the adequacy of the simplified quantification of the uncertainty of the determination of the microbial contamination of PP by log transforming microbial count and dilution factor of the test sample whose uncertainty is combined in a log scale using the uncertainty propagation law. This assessment is performed by a parallel novel bottom-up and accurate evaluation of microbial analysis uncertainty involving the Monte Carlo method simulation of the Poisson log-normal distribution of counts and of the normally distributed measured volumes involved in the analysis. Systematic effects are assessed and corrected on results to compensate for their impact on the determinations. Poisson regression is used to predict precision affecting determinations on unknown test samples. Simplified and detailed models of the uncertainty of the measurement of the microbial contamination of PP are provided, allowing objective comparisons of several determinations and those with a maximum contamination level. This work concludes that triplicate determinations are required to produce results with adequately low uncertainty and that simplified uncertainty quantification underevaluates or overevaluates the uncertainty from determinations based on low or high colony numbers, respectively. Therefore, detailed uncertainty evaluations are advised for determinations between 50 and 200% of PP's maximum admissible contamination value. User-friendly tools for detailed and simplified evaluations of the uncertainty of the measurement of microbial contamination of PP are provided together with the understanding of when simplifications are adequate.

Nonparametric High-Dimensional Multi-Sample Tests based on Graph Theory

High-dimensional data pose unique challenges for data processing in an era of ever-increasing amounts of data availability. Graph theory can provide a structure of high-dimensional data. We introduce two key properties desirable for graphs in testing homogeneity. Roughly speaking, these properties may be described as: unboundedness of edge counts under the same distribution and boundedness of edge counts under different distributions. It turns out that the minimum spanning tree violates these properties but the shortest Hamiltonian path posses them. Based on the shortest Hamiltonian path, we propose two combinations of edge counts in multiple samples to test for homogeneity. We give the permutation null distributions of proposed statistics when sample sizes go to infinity. The power is analyzed by assuming both sample sizes and dimensionality tend to infinity. Simulations show that our new tests behave very well overall in comparison with various competitors. Real data analysis of tumors and images further convince the value of our proposed tests. Software implementing the test is available in the R package GRelevance. Supplemental materials for this article are available online.

PROFICIENCY AND ACADEMIC PERFORMANCE OF GRADE 7 LEARNERS IN ENGLISH AS A SECOND LANGUAGE

The purpose of this study is to analyze the English as a Second Language (ESL) proficiency and academic performance of Grade 7 students at Monico Rarama National High School in San Pedro, Roxas, Isabela. In this study, a descriptive correlational method was used to examine the relationships between ESL proficiency levels, academic performance, ESL learning activities, and literacy challenges. Data were collected from 81 Grade 7 learners through structured questionnaires. Frequency count and percentage distribution, weighted mean, and Pearson-r correlation were used to analyze the data. Results show that students demonstrated proficiency in listening, speaking, reading, writing, and viewing skills, with varying levels of academic performance. Academic performance was not significantly correlated with diverse ESL learning activities, while it was significantly correlated with proficiency levels across communication skills. Further, the respondents stated that they had trouble completing ESL literacy tasks which served as a challenge among them. Thus, it is recommended intervention programs and personalized approaches should be implemented to address these challenges. Implementing these recommendations can lead to improved learning outcomes and overall proficiency in English among Grade 7 ESL learners. Further, educators, policymakers, and curriculum developers can use the findings to optimize ESL learning strategies and support student success.

A deep dive into burn-mediated ARDS severity assessment: a retrospective study on hematological markers

Acute Respiratory Distress Syndrome (ARDS) is a critical form of Acute Lung Injury (ALI), challenging clinical diagnosis and severity assessment. This study evaluates the potential utility of various hematological markers in burn-mediated ARDS, including Neutrophil-to-Lymphocyte Ratio (NLR), Mean Platelet Volume (MPV), MPV-to-Lymphocyte Ratio (MPVLR), Platelet count, and Platelet Distribution Width (PDW). Employing a retrospective analysis of data collected over 12 years, this study focuses on the relationship between these hematological markers and ARDS diagnosis and severity in hospitalized patients. The study establishes NLR as a reliable systemic inflammation marker associated with ARDS severity. Elevated MPV and MPVLR also emerged as significant markers correlating with adverse outcomes. These findings suggest these economical, routinely measured markers can enhance traditional clinical criteria, offering a more objective approach to ARDS diagnosis and severity assessment. Hematological markers such as NLR, MPV, MPVLR, Platelet count, and PDW could be invaluable in clinical settings for diagnosing and assessing ARDS severity. They offer a cost-effective, accessible means to improve diagnostic accuracy and patient stratification in ARDS. However, further prospective studies are necessary to confirm these findings and investigate their integration with other diagnostic tools in diverse clinical settings.

Asymptotic results for recursive multivariate associated-kernel estimators of the probability density mass function of a data stream

. In this article, our central focus is to investigate the non parametric estimator of the probability density or mass function of a data stream by using the general family of kernels, also called multivariate associated kernels. Being able to estimate categorial, count, discrete, and (semi)continuous distributions, these multivariate associated kernel estimators unify several particular cases. Within this framework, we first introduce a recursive estimator for non classical associated kernels. Under reasonable assumptions, we subsequently exhibit their asymptotic results, such as the local uniform L q -consistency, the pointwise asymptotic normality and finally the strong global consistency. Illustrative examples of associated kernels are revisited.

Prevalence and Characterization of NOTCH2NLC GGC Repeat Expansions in Koreans: From a Hospital Cohort Analysis to a Population-Wide Study.

GGC repeat expansions in the NOTCH2NLC gene are associated with a broad spectrum of progressive neurologic disorders, notably, neuronal intranuclear inclusion disease (NIID). We aimed to investigate the population-wide prevalence and clinical manifestations of NOTCH2NLC-related disorders in Koreans. We conducted a study using 2 different cohorts from the Korean population. Patients with available brain MRI scans from Seoul National University Hospital (SNUH) were thoroughly reviewed, and NIID-suspected patients presenting the zigzag edging signs underwent genetic evaluation for NOTCH2NLC repeats by Cas9-mediated nanopore sequencing. In addition, we analyzed whole-genome sequencing data from 3,887 individuals in the Korea Biobank cohort to estimate the distribution of the repeat counts in Koreans and to identify putative patients with expanded alleles and neurologic phenotypes. In the SNUH cohort, among 90 adult-onset leukoencephalopathy patients with unknown etiologies, we found 20 patients with zigzag edging signs. Except for 2 diagnosed with fragile X-associated tremor/ataxia syndrome and 2 with unavailable samples, all 16 patients (17.8%) were diagnosed with NIID (repeat range: 87-217). By analyzing the Korea Biobank cohort, we estimated the distribution of repeat counts and threshold (>64) for Koreans, identifying 6 potential patients with NIID. Furthermore, long-read sequencing enabled the elucidation of transmission and epigenetic patterns of NOTCH2NLC repeats within a family affected by pediatric-onset NIID. This study presents the population-wide distribution of NOTCH2NLC repeats and the estimated prevalence of NIID in Koreans, providing valuable insights into the association between repeat counts and disease manifestations in diverse neurologic disorders.

Pushing the Limits of the Cosmic Origin Spectrograph (COS) with an Optimized Background Correction

Observations utilizing the ultraviolet capabilities of the Cosmic Origin Spectrograph (COS) onboard the Hubble Space Telescope are of unique value to the astronomy community. Spectroscopy down to 900 Å with COS has enabled new science areas. However, contrary to the situation at longer wavelengths, these observations are limited by detector background noise. The background correction currently applied by the standard calibration pipeline (CalCOS) is not optimized for faint targets, limiting the scientific value of low signal-to-noise ratio (S/N) observations. In this work we investigate a possible dependence of the variations of the dark rate in both segments of the COS far-ultraviolet detector on time, detector high voltage (HV), and solar activity. Through our analysis we identified a number of detector states (on a configuration basis, e.g., HV and segment) characterizing the spatial distribution of dark counts, and created superdarks to be used in an optimized two-dimensional (2D) background correction. We have developed and tested Another COS Dark Correction (ACDC), a dedicated pipeline to perform a 2D background correction based on statistical methods, producing background-corrected and flux-calibrated spectra. While our testing of ACDC showed an average improvement in S/N values of ∼10%, in a few cases the improvements in S/N reached 60% across the whole wavelength range of individual segments.

Implementation of Evacuation Management Plan of a Rural Barangay in Surigao Del Norte, Philippines

This descriptive quantitative study evaluated the extent of evacuation management plan implementation as experienced by the residents of Brgy. Poblacion, San Francisco, Surigao del Norte. The respondents were 123 residents and were selected through convenient sampling. The data gathered were analyzed and treated using the following descriptive statistical tools: frequency count and percentage distribution, mean and standard deviation, and analysis of variance (ANOVA). Results showed that the camp coordination and management plan was moderately implemented. This suggests that while the plan is being implemented to some extent, there is room for improvement to ensure a more effective and robust evacuation process in the future. In addition, the findings showed a significant degree of difference in the perceived implementation extent of the evacuation phase with respect to the respondents’ years of residency, indicating that length of stay may impact residents’ knowledge, familiarity with the area, and ability to contribute to the community’s resilience during evacuations. Finally, it was recommended that implementing the recommended strategies, actions and proposed enhancement plan can have a transformative impact on the barangay’s camp coordination and management plan.

Knowledge, Attitudes, and Beliefs of Paulinian College Students about Diabetes

The main purpose of the study was to evaluate the degree of knowledge, attitudes, and beliefs of Paulinian college students on diabetes for appropriate plans and interventions. The participants were 218 Paulinian college students at St. Paul University Surigao during the academic year 2022-2023. The study employed a quantitative descriptive research design involving the use of a researcher-made survey questionnaire that underwent validation and pilot testing. The data gathered were analyzed and treated by using the following descriptive statistical tools: frequency count and percentage distribution, mean and standard deviation, analysis of variance (ANOVA), and Shapiro-Wilk test. Results showed that the college students had a significant degree of difference in the level of respondent’s attitudes and beliefs on Diabetes based on behavior formation and belief generation when grouped according to age, sex, and socio-economic status. Students had significant differences in their attitudes and beliefs when grouped as to their knowledge as there was found to be a correlation between attitudes and beliefs. Generally, the findings showed that there is a significant degree of difference in the level of respondent’s knowledge, attitudes, and beliefs. It was recommended to provide an action plan as a health education strategy according to their knowledge about Diabetes for a continuum favorable attitude of students and change their beliefs on a more scientific approach and analyze deeply the misconceptions regarding the disease.

Adherence to Hypertension Management Practices Based on International Society of Hypertension (ISH) Guidelines among Hypertensive Patients

Hypertension is a significant global health concern with profound cardiovascular implications. The researchers used a quantitative research design employing a descriptive research survey approach and the instrument used to seek information was a researcher-made questionnaire for assessing demographic characteristics, adherence to hypertension management such as medication adherence, lifestyle changes, and blood pressure control. These tools were used in data analysis frequency count and percentage distribution, mean and standard deviation, and lastly analysis of variance (ANOVA). This abstract presents a study conducted in Brgy. Washington, Surigao City, focusing on adherence to hypertension management guidelines by the International Society of Hypertension (ISH). Respondents generally showed high adherence to hypertension management, primarily taking medicine, with moderate adherence to monitoring blood pressure, physical activity, and diet, influenced by demographic factors. The study found no significant difference in medication adherence or adherence to a balanced diet among hypertensive individuals in Brgy. Washington, but did show differences based on age, occupation, income, and years of hypertension, emphasizing the need for community-based initiatives.

Estimating mutation rates under heterogeneous stress responses.

Exposure to environmental stressors, including certain antibiotics, induces stress responses in bacteria. Some of these responses increase mutagenesis and thus potentially accelerate resistance evolution. Many studies report increased mutation rates under stress, often using the standard experimental approach of fluctuation assays. However, single-cell studies have revealed that many stress responses are heterogeneously expressed in bacterial populations, which existing estimation methods have not yet addressed. We develop a population dynamic model that considers heterogeneous stress responses (subpopulations of cells with the response off or on) that impact both mutation rate and cell division rate, inspired by the DNA-damage response in Escherichia coli (SOS response). We derive the mutant count distribution arising in fluctuation assays under this model and then implement maximum likelihood estimation of the mutation-rate increase specifically associated with the expression of the stress response. Using simulated mutant count data, we show that our inference method allows for accurate and precise estimation of the mutation-rate increase, provided that this increase is sufficiently large and the induction of the response also reduces the division rate. Moreover, we find that in many cases, either heterogeneity in stress responses or mutant fitness costs could explain similar patterns in fluctuation assay data, suggesting that separate experiments would be required to identify the true underlying process. In cases where stress responses and mutation rates are heterogeneous, current methods still correctly infer the effective increase in population mean mutation rate, but we provide a novel method to infer distinct stress-induced mutation rates, which could be important for parameterising evolutionary models.

CONTEXTUAL CORRELATES OF A SUSTAINABLE SCHOOL ENVIRONMENT IN ROXAS, ISABELA, PHILIPPINES

The study investigates the contextual correlates of sustainable practices at Anao-Kiling Elementary School, emphasizing human values as dominant factors in environmental stewardship. Specifically, this study aims to assess the level of environmental awareness, identify environmental issues, explore practiced behaviors, and examine challenges faced by students. Using a descriptive-normative research design, data was collected from 36 Grade 6 pupils through structured questionnaires. Frequency count and percentage distribution, weighted mean, Pearson-r correlation, and Chi-Square test were used to analyze the data. Results show that most respondents had access to smartphones, indicating a certain level of economic stability. Environmental care programs were implemented in many schools, and pollution and overpopulation were considered moderately serious issues. Both technology-based and non-technology-based activities showed a slightly aware level of environmental awareness. The findings also revealed that the respondents demonstrated practiced behaviors and exhibited human values like respect and honesty. Challenges faced included miscommunication about waste segregation policies and a lack of enthusiasm for clean-up activities. The statistical analysis indicated no significant correlation between environmental issues and human values, nor between environmental awareness and confronting environmental problems. Moreover, socioeconomic factors do not relate to the level of environmental care practices. To foster sustainable behaviors among students, regardless of socioeconomic status, it is essential to integrate environmental values and practices into school curricula. It is recommended that schools prioritize environmental education and enhance communication regarding waste segregation policies to promote a culture of environmental stewardship.

Extent of Teachers’ Utilization of Pedagogical Approaches

Pedagogical approaches refer to the various methods and strategies that educators use to facilitate learning and teaching. With the educational trends and development, the researchers conduct this study to assess the extent of utilization of pedagogical strategies – inquiry-based, integrative, collaborative, constructivist and reflective. This is conducted to the grade school teachers of St. Paul University Surigao where total population sampling was applied. A modified survey questionnaire was used to assess the extent of utilization of pedagogical strategies and the data gathered were analyzed using frequency count and percentage distribution, mean and standard deviation, and analysis of variance. It was found that the teachers highly utilized the pedagogical approaches. In addition, the respondents’ age, sex, highest educational attainment, length of service and subject/s taught do not influence their utilization of pedagogical approaches. Thus, it is recommended for the teachers to continue utilize the pedagogical approaches to ensure effective teaching-learning engagement.

Pupils’ Number Knowledge Readiness

Preparing students for school involves equipping them with the necessary skills to learn and excel, such as through play, communication, focus, and social interaction. Ensuring children have a solid foundation in basic number skills before delving into more advanced mathematical concepts is crucial for their academic development. This study focused on evaluating the readiness of Grade 1 students at St. Paul University Surigao in terms of their number knowledge. This involved 24 Grade 1 students and utilized a pretest-post-test design, using a School Readiness Test (SRT) to assess their number knowledge readiness. Data analysis included frequency count and percentage distributions, and paired t-test. The results indicated a significant improvement in the students' number knowledge readiness following the teaching and learning activities, suggesting that these interventions were effective. Furthermore, the study found that factors such as sex and previous school attended did not influence the students' readiness in number knowledge. It is recommended that the school continues implementing activities that enhance students' performance in this area.