Standard Deviation Coefficient Research Articles

Evaluation of fish meal freshness using a metal-oxide semiconductor electronic nose combined with the long short-term memory feature extraction method.

To improve the classification and regression performance of the total volatile basic nitrogen (TVB-N) and acid value (AV) of different freshness fish meal samples detected by a metal-oxide semiconductor electronic nose (MOS e-nose), 402 original features, 62 manually extracted features, manually extracted and selected features by the RFRFE method, and the features extracted by the long short-term memory (LSTM) network were used as inputs to identify the freshness. The classification performance of the freshness grades and the estimation performance of the TVB-N and AV values of fish meal with different freshness were compared. According to the sensor response curve, preprocessing and feature extraction steps were first applied to the original data. Then, five classification algorithms and four regression algorithms were used for modeling. The results showed that a total of 30 features were extracted using the LSTM network, and the number of extracted features was significantly reduced. In the classification, the highest accuracy rate of 95.4% was obtained using the support vector machine method. In the regression, the least squares support vector regression method obtained the best root mean square error (RMSE). The coefficient of determination (R2), RMSE, and relative standard deviation (RSD) between the predicted value of TVBN and the actual value were 0.963, 11.01, and 7.9%, respectively. The R2, RMSE, and RSD between the predicted value of AV and the actual value were 0.972, 0.170, and 6.05%, respectively. The LSTM feature extraction method provided a new method and reference for feature extraction using an E-nose to identify other animal-derived material samples.

Associations of prenatal blood pressure trajectory and variability with child neurodevelopment at 2 years old

BackgroundThe patterns of blood pressure (BP) change throughout the pregnancy were related to adverse birth outcomes. However, little is known about the long-term effect of BP change patterns on child neurodevelopment. This study aimed to explore the relationship between the BP trajectory and BP variability during pregnancy and early childhood neurodevelopment.MethodA total of 2797 mother-newborn pairs were derived from the Wuhan Healthy Baby Cohort Study. BP was measured during each antenatal visit, and Mental and Psychomotor Development Indexes (MDI and PDI) were assessed using the Bayley Scales of Infant Development (BSID) when the children were 2 years old. Delayed neurodevelopment was defined as scores of PDI or MDI less than − 1SD relative to the mean score of the study population. A group-based multi-trajectory model was adopted to identify multi-trajectories of systolic blood pressure (SBP) and diastolic blood pressure (DBP). Visit-to-visit BP variability was assessed by the coefficient of variation (CV), standard deviation (SD), and average real variability (ARV). Generalized linear models and multivariate logistic regressions were used to assess the associations of BP trajectories and variability with BSID scores and delayed neurodevelopment, respectively.ResultsFive distinct trajectories for SBP and DBP were identified, namely, “Low-increasing,” “Low-stable,” “Moderate-decreasing,” “Moderate-increasing,” and “High-stable” groups. Compared with the “Low-stable” group, the children whose mothers’ BP fell into the other four groups had lower PDI scores, and mothers in the “Low-increasing,” “Moderate-increasing,” and “Moderate-decreasing” groups had 43% (OR: 1.43, 95% CI: 1.01, 2.03), 48% (OR: 1.48, 95% CI: 1.05, 2.08) and 45% (OR:1.45, 95% CI: 1.03, 2.04) higher risk of having offspring with delayed psychomotor neurodevelopment, respectively. High DBP variability was associated with lower BSID scores, and delayed psychomotor neurodevelopment (OR = 1.46, 95% CI: 1.10, 1.92 for DBP-SD; OR = 1.53, 95% CI: 1.16, 2.02 for DBP-CV).ConclusionOur findings suggest that BP change patterns assessed by multi-trajectory and visit-to-visit variability were associated with lower BSID scores and delayed neurodevelopment. Health professionals should be aware of the influence of BP level and its oscillations during pregnancy on the risk of delayed neurodevelopment.

Association between long-term visit-to-visit blood pressure variability and depression among Chinese middle-aged and older adults

ABSTRACT Background Whether there is a longitudinal association between long-term blood pressure variability (BPV) and subsequent depression among Chinese adults remains inconclusive. Methods This study utilized data from a nationwide cohort of the China Health and Retirement Longitudinal Study, which included participants aged > 45 years without prevalent psychiatric or memory-related diseases. The intra-individual coefficient of variation (CV) and standard deviation (SD) across 3 visits from 2011 to 2015 were used to examine the long-term variability in systolic BP (SBP) and diastolic BP (DBP). The depressive symptoms were examined using the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10), and moderate-to-severe depression was defined as CES-D-10 ≥ 15. Results A total of 5,249 participants (mean age: 61.4 ± 8.1 years, 46.5% were men) were included in the current analysis. Individuals in the highest quartile of both BP CV and SD were independently correlated with a higher total CES-D-10 score compared to those in the lowest quartile after multivariable adjustment. 1,070 participants (20.4%) had moderate-to-severe depression during the 3-year follow-up period. Participants in the Q4 of SBP and DBP CV had 1.23-fold higher odds (95% CI: 1.01, 1.49) and 1.20-fold higher odds (95% CI: 1.01, 1.41) of moderate-to-severe depression compared to those in Q1. Subgroup analyses revealed that men with higher BP CVs had a greater risk of severe depressive symptoms (p for SBP CV-by-sex interaction = 0.050, p for SBP CV-by-sex interaction = 0.025). Conclusions Depression was common among Chinese middle-aged and older adults and long-term visit-to-visit BPV was positively associated with depressive symptoms, highlighting the importance of implementing intensive prevention strategies for depression and enhancing blood pressure monitors in China.

Deep-Learning Correction Methods for Weather Research and Forecasting (WRF) Model Precipitation Forecasting: A Case Study over Zhengzhou, China

Systematic biases and coarse resolutions are major limitations of current precipitation datasets. Many studies have been conducted for precipitation bias correction and downscaling. However, it is still challenging for the current approaches to handle the complex features of hourly precipitation, resulting in the incapability of reproducing small-scale features, such as extreme events. In this study, we proposed a deep-learning model called PBT (Population-Based Training)-GRU (Gate Recurrent Unit) based on numerical model NWP gridded forecast data and observation data and employed machine-learning (ML) methods, such as Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Gradient-Boosted Decision Tree (GBDT), to correct the WRF hourly precipitation forecasts. To select the evaluation method, we conducted a sample balance experiment and found that when the proportion of positive and negative samples was 1:1, the Threat Score (TS) and accuracy scores were the highest, while the Probability of Detection (POD) score was slightly lower. The results showed that: (1) the overall errors of the PBT-GRU model were relatively smaller, and its root mean square error (RMSE) was only 1.12 mm, which was reduced by 63.04%, 51.72%, 58.36%, 37.43%, and 26.32% compared to the RMSE of WRF, SVM, KNN, GBDT, and RF, respectively; and (2) according to the Taylor diagram, the standard deviation (σn) and correlation coefficient (r) of PBT-GRU were 1.02 and 0.99, respectively, while the σn and r of RF were 1.12 and 0.98, respectively. Furthermore, the σn and r of the SVM, GBDT, and KNN models were between those of the above models, with values of 1.24 and 0.95, 1.15 and 0.97, and 1.26 and 0.93, respectively. Based on a comprehensive analysis of the TS, accuracy, RMSE, r and σn, the PBT-GRU model performed the best, with a significantly better correction effect than that of the ML methods, resulting in an overall performance ranking of PBT-GRU > RF > GBDT > SVM > KNN. This study provides a hint of the possibility that the proposed PBT-GRU model can outperform model precipitation correction based on a small sample of one-station data. Thus, due to its promising performance and excellent robustness, we recommend adopting the proposed PBT-GRU model for precipitation correction in business applications.

Prediction of gas-solid nozzle performance based on CFD and response surface methodology

In this work, structural parameters and performance prediction of fan nozzles for powder spraying are investigated. Computational Fluid Dynamics (CFD) was used to simulate the working process of the grooved fan nozzle. A Box-Behnken experimental model was developed to analyze the effects of the structural parameters on the nozzle air flow stability and working performance, taking the nozzle structural parameter contraction angle (α), the ratio of outlet to inlet diameter (d/D), the ratio of outlet diameter to length (L2/d), and the half angle of the “V”– shaped groove (β). The air flow stability and working performance of nozzle were evaluated through coefficient of variation (Cv) and standard deviation (SD). Using multiple regression analysis, the prediction model of Cv and SD on the structural parameters is established. It was obtained that: with the increase of the diameter and length of the nozzle outlet, the spray angle of the nozzle decreases. As the “V”– shaped groove angle increases, the powder spray angle decreases. The effects of structural parameters on Cv are d/D, α, β, and L2/d in ascending order, and on SD are d/D, α, β, and L2/d in ascending order. In addition, the influence of the interaction of each structural parameter on Cv and SD was obtained. This study can provide a reference for the design and structural optimization of fan nozzles for powder spraying.

유아 놀이중심 교육과정을 반영한 기후·생태계 프로그램 효과성 연구

Objectives The purpose of this study is to investigate the effectiveness of a climate-ecosystem program reflect-ing an early childhood play-based curriculum on early childhood development (nature), environmental con-servation attitudes, ecological literacy, and early childhood playfulness. Methods The study participants are 5-year-old children from a kindergarten in Gyeonggi Province, with 13 in-dividuals in the experimental group and 15 individuals in the control group. SPSS 23.0 was used to determine the mean, standard deviation, and reliability coefficient of the study variables. The homogeneity test was conducted using the pre-test mean scores between groups, and the difference between the experimental and control groups was analyzed using the Mann-Whitney U test based on post-test mean scores. Pre-post differences between the experimental and comparison groups were analyzed using the Wilcoxon signed-rank test. Results The main research results are as follows: First, the simple difference between the pre-test and post-test mean scores of the study variables revealed improvement in the experimental group(from 0.13 to 1.02 points), while the comparison group showed both an increase(from 0.01 to 0.36 points) and a decrease(from -0.26 to -0.03 points). There was no statistically significant difference in pretest mean scores between the experimental and comparison groups, confirming homogeneity. The pre-post difference test of the experimental group showed statistically significant differences in early childhood development (nature) and environmental conservation atti-tudes and subscales (conservation attitude, recycling attitude, environmental pollution prevention attitude), eco-logical literacy and subscales (nature's rights, intention to support, resource protection, ecological sensitivity, eco-logical social environment, ecological development_reverse, nature governance_reverse, ecological crisis indif-ference), and early childhood playfulness and some subscales (physical spontaneity, social spontaneity, sense of humor). On the other hand, there were no statistically significant differences in the cognitive spontaneity and ex-pression of pleasure sub-domains of preschoolers' playfulness. The pre-post difference test for the comparison group found statistical significance only for ecological sensitivity, a sub-scale of ecological literacy, and physical spontaneity, a sub-scale of preschoolers' playfulness. Second, the factors that resulted in statistically significant differences in post-hoc mean scores between the experimental and comparison groups were environmental con-servation attitudes and their sub-scales, recycling attitudes, ecological literacy and its sub-scales, supportive in-tention, ecological sensitivity, nature dominance(reverse), and ecological crisis indifference. Conclusions The results of this study confirm the effectiveness of climate and ecosystem programs through play. As an extension of this study, we aim to propose collaborative activities with the local community through a living lab approach.

Genetic determinants of obesity in adolescent girls

Significant progress in understanding the genetic contribution in obesity and its prevalence at all ages has been achieved since existing methods of treatment and preventive measures aimed at combating obesity are not effective enough.Purpose. To study the prevalence of pathologic single nucleotide polymorphisms rs6265 of the brain neutrophic factor gene BDNF; rs1137101 of the leptin receptor gene LEPR; rs9939609 of the gene, associated with fat mass, FTO; rs4762 and rs699 of angiotensinogen AGT gene; rs1799883 of fatty acid transporter gene FABP2; rs1801282 of PPARG2 gene in obese adolescent girls.Material and methods. 72 teenage girls aged 12–17 years were examined. Group 1 consisted of 36 obese children (standard deviation coefficient SDS BMI ≥ 2.0), group 2 — 36 non-obese children (SDS BMI <1.0). Anthropometric, molecular genetic, and statistical methods were used.Results. In obese adolescent girls, an association was detected with only one gene — PPARG2, a polymorphic locus (Pro/Pro). The prevalence rate of the C allele in group 1 was 80%, in group 2 — 3% (p<0.05). No statistically significant differences in the frequencies of genotypes and alleles of other genes in children with obesity and normal body weight were established.Conclusion. Further large-scale studies, including biochemical and hormonal parameters, are needed to establish the influence of specific polymorphic loci of various genes contributing in obesity and metabolic processes.

Teachers’ Utilization of Digital Tools and Confidence in Technology

The utilization of technology has emerged as a crucial instrument for educators to augment instruction and enrich the educational encounters of learners. This study sought to determine the extent of teachers' utilization of digital tools, their level of confidence in technology, and the significant relationship between the extent of teachers' utilization of digital tools and confidence in technology, among the 101 teachers from the nine (9) schools of Manolo Fortich III District, Division of Bukidnon, chosen through universal sampling. This study utilized two instruments. One was a research-made questionnaire for the teachers’ utilization of digital tools and for the teachers’ confidence in technology was adapted, and modified questionnaire from the study of Heather (2014). Descriptive statistics were used such as mean, standard deviation, and Pearson Product Moment Correlation Coefficient. The study revealed that most of the time teachers utilized Excel/Spreadsheets than video/Capcut. Teachers' confidence level in technology found to be Always Confident. Furthermore, teachers' utilization of digital tools such as PPT/canvas, video/caput and the like, and Excel/spreadsheets has a significant relationship to teachers' confidence in technology. Thus, to enhance video/CapCut usage, teachers need training, support, and collaboration. Schools should provide professional development, technical assistance, and recognition of achievements. These efforts boost confidence in digital tools, improve pupils’ learning, and encourage creative teaching methods in the digital era.

Social Support as a Correlate of Depression and Quality of Life Among Nigerian Older Adults: a Cross-Sectional Study.

Reduced social support has been associated with presence of depression and reduced quality of life among older adults. The relationships may be better understood by exploring the interactions of individual domains among the constructs. This cross-sectional survey involved a consecutive sample of 206 (116 females and 90 males) older adults living in a Southern Nigeria community. The Multidimensional Scale of Perceived Social Support, Geriatric Depression Scale, and World Health Organization Quality of Life-OLD Questionnaire, were used to measure social support, depression, and quality of life respectively. Data was analyzed using frequency counts, percentages, mean, standard deviation, multiple regression and Spearman rank-order correlation coefficient, at 0.05 alpha level. Prevalence rate of depression among participants was 45.5%. Social support was perceived to be low by 37.4% of participants with the lowest mean social support score coming from friends domain. Participants' quality of life was generally fairly good (> 60%) with the lowest scores coming from the intimacy domain. Significant correlations between social support domains and each of quality of life (p < 0.05) and depression were respectively positive and negative; but weakest for the friend and strongest for significant others domains. All quality of life domains were significantly correlated with social support except the death and dying domain. All the domains of social support (family and significant other) were significant predictors of depression except the friend domain. Significant others around individual older adults particularly those with depression ought to be educated on the importance of their roles. Stakeholders including healthcare providers may create and support programmes for improved social networking for the older adults in order to enhance their general wellbeing and quality of life.

Teachers’ commitment and leadership behavior as correlates of academic performance

This study examined the relationship between students’ academic performance, teachers’ commitment, and leadership behavior of school administrators. Teachers’ commitment was measured in two areas–commitment to job and commitment to organization and the leadership behavior of school administrators were evaluated in terms of consideration and initiating structure. Eighty-one teachers, 11 school heads, and 470 students served as respondents. The descriptive survey research technique, correlation analysis, and the following statistical methods were used: frequency, mean, standard deviation, and correlation coefficient. The study revealed that the initiating structure and consideration dimensions of leadership behavior affect teachers’ commitment to job (CTJ) and teacher’s commitment to organization (CTO). The correlation between CTJ and CTO and leadership behavior-initiating structure is positive and with leadership behavior-consideration negative. CTJ and CTO is correlated with the students’ academic performance in math, but not in Science and English. The correlation is negative. Students’ academic performance in all subject areas is negatively correlated with leadership behavior-initiating structure and has no significant relationship with leadership behavior-consideration. The leadership behavior-initiating structure is positively correlated with teachers’ commitment to both job and organization but has negative correlation with students’ academic performance in math, science, and English.

An Investigation into the Relationship between Transformational Leadership Style and Organizational Commitment in a College of Administration and Economics: An Empirical Research

The current research aims to demonstrate the relationship and impact between transformational leadership and its dimensions (Idealized Influence Behaviour, Idealized Influence Attributed, Intellectual Stimulation, Inspiring Motivation, and Individual Consideration) on organizational commitment and its dimensions (continuous organizational commitment, emotional organizational commitment, and normative organizational commitment) at the College of Administration and Economics. Descriptive-analytical approach used to achieve the core object of the research. The research adopted the questionnaire as the core tool for this purpose. A research sample included various administrative levels (director, chief inspector, supervisor, and assistant supervisor). The questionnaire distributed randomly, and 70 valid questionnaires collected for statistical analysis. The research adapted a set of statistical methods such as arithmetic mean, coefficient of variation, standard deviation, and simple regression coefficient by the statistical program (SPSS V26) to analyze data and test hypotheses. The research reached a set of essential results, the most important of which was that transformational leadership is the main factor for building an organization's culture to achieve growth and success and motivate individuals. Paper type: Research paper

Measurement method for live chicken shank length based on improved ResNet and fused multi-source information

Phenotypic parameters are crucial reference indicators in poultry breeding. However, the chickens shank length is still manually measured, which is time-consuming and labor-intensive. Additionally, the measurement results are difficult to unify due to the subjective factors of different individuals. To address this issue, this paper proposed a method for live chicken shank length measurement (SLM). It enriches chicken shank feature by fusing visible images and infrared images. The fusion images are then input into a deep regression model based on the improved ResNet. The measurement model used ResNet as its backbone and introduces Squeeze-and-Excitation (SE) blocks and a Spatial Pyramid Pooling (SPP) block, resulting in more precise and stable shank length measurements. The average coefficient of variation, average floating error, average standard deviation and Pearson correlation coefficient for shank length measurements using the fusion images are 0.21 %, 0.49 %, 0.181 mm and 0.996, respectively, compared with using single visible or infrared image, the accuracy and stability are obviously improved. That indicated combining deep learning model and fusion information, the SLM proposed in this paper can achieve a more precise, reliable and standardized measurement of live chicken shank length.

Chemical fingerprinting and multicomponent quantitative analysis for quality control of Cinnamomum tamala collected from Western Himalaya by HPLC-DAD

Cinnamomum tamala, commonly known as “Indian bay leaf” or “Tejpat”, is an economically important plant widely used in medicine, food and cosmetic industries. Growing demand for its leaf and bark in the herbal trade and non-availability of quality materials lead to large-scale species admixture and adulteration in the global market. The present study aims at developing a validated HPLC-DAD (High-performance liquid chromatography coupled with diode array detection) method and multiple markers-based chemical fingerprints for quality evaluation of C. tamala leaf extracts. Five bioactive compounds, viz., coumarin, cinnamyl alcohol, cinnamic acid, cinnamaldehyde and cinnamyl acetate, were identified and quantified in 28 samples collected from the western Himalayan region of India. The chromatographic separation was achieved on Shimadzu Shimpak C18 column (dimension 250 × 4.6 mm, pore size 5 μm) with a gradient elution of mobile phase using acetonitrile and 0.1 percent phosphate buffer and the chromatograms were obtained at a wavelength of 265 nm. The method validation was done by analyzing the linearity, LOD, LOQ, precision, stability, repeatability and recovery rates of standard compounds for quantitative analysis. The values of coefficient of correlation (R2) were found to be close to 1 for linearity and similarity analysis; and standard deviation was less than 3 percent in case of precision, stability, repeatability and recovery rates. The content of target compounds such as coumarin, cinnamyl alcohol, cinnamic acid, cinnamaldehyde and cinnamyl acetate varied in the range of 0–1.09, 0–0.05, 0.07–0.51, 0.39–1.27 and 0–0.27 percent, respectively. In the chemical fingerprint of C. tamala leaves, a total of 13 peaks were assigned as common peaks. The results of the study indicated that the HPLC method now developed combining chemical fingerprint with quantification of analytes could serve as a useful tool for quality evaluation of herbal raw materials of C. tamala and a valuable reference for further study.

TRANSFORMATIONAL LEADERSHIP, TRAITS, AND COMPETENCIES OF NURSING STUDENTS IN THE COMMUNITY HEALTH NURSING

The transformational leadership attributes and leadership traits of nursing students are essential components in their competency development in Community Health Nursing. The study explored the level of transformational leadership and leadership traits of nursing students in relation to their level of competency in Community Health Nursing. The study employed a descriptive-correlational research design. 175 Level Two Bachelor of Science in Nursing (BSN) students were chosen as respondents through purposive sampling. The researcher utilized Mean, Standard Deviation, Frequency, Percentage, and Pearson Product Moment Correlation Coefficient in the data analysis. Results revealed that the nursing students possessed high transformational leadership attributes and skills, leadership traits, and have a fair competency in their Community Health Nursing clinical exposure. Among the six constructs of transformational leadership, only delegation showed a highly influential relationship with competency. Meanwhile, no leadership trait manifested to correlate with nursing students’ competency at present. The study implies that nursing students with high transformational leadership attributes and high leadership traits will be future successful nurse leaders. Moreover, delegation skill is the key to becoming a competent leader and thus it is important to be introduced to nursing students even at their entry into the baccalaureate nursing education. This study also suggests that nursing educators ensure that they provide high-quality undergraduate nursing education, as this is vital in developing transformational leadership skills and improving leadership traits needed to produce competent nursing graduates who are well-equipped to work in the community setting.

Teachers’ Resilience and Self-Efficacy

Teachers’ resilience and self-efficacy play an important role in effectively handling educational challenges and its impact to student outcomes. This study sought to determine the teachers’ resilience level, the level of self-efficacy, and the relationship between teachers’ resilience level and self-efficacy among the three (3) Junior High Schools of South District, Division of Cagayan de Oro City of SY 2023-2024. A total of one hundred forty-eight (148) respondents through stratified sampling method. The study utilized a descriptive correlational research method and used both adopted questionnaire (Unda, 2022) and modified questionnaire (Pacamo, 2021) to gather the necessary data. Mean, Standard Deviation, and Pearson Product Moment Correlation Coefficient (r) were employed to ascertain the significant relationship between teachers’ resilience and self-efficacy. Results revealed that teachers’ resilience level was Very High while their self-efficacy level was Very Good. A moderate positive relationship exists between teachers’ resilience and self-efficacy. High level of resilience is fundamental for teachers to demonstrate effectiveness and self-efficacy. Hence, developing the factors in teachers’ resilience with focus on personal characteristics is recommended.

Estimation of traditional numerical characteristics of lognormal distribution laws of a one-dimensional random variable in conditions of large volume statistical data

The efficiency of estimating the numerical characteristics of a family of the lognormal distribution law of a onedimensional random variable under conditions of large volumes of statistical data is considered. To circumvent the problem of large samples, methods of discretization the range of values of a random variable based on the formulas of Sturges, Brooks-Carruthers, Heinhold-Gaede and the formula proposed by the authors of this article are used. Data arrays have been generated that make it possible to evaluate the numerical characteristics of the laws of distribution of random variables, taking into account their discrete values. Based on the transformed data arrays, estimates of the mathematical expectation, standard deviation, skewness and kurtosis coefficients were calculated. Estimates of the numerical characteristics of the considered distribution laws under the conditions of a continuous and discrete random variable are compared for different volumes of initial statistical data. The effectiveness of methods for estimating the numerical characteristics of the family of the lognormal distribution law based on the initial statistical data and on the results of transformations of these data using known discretization formulas has been established. The reliability of the comparison of the effectiveness indicators of the studied methods was confirmed by using the Kolmogorov-Smirnov criterion. It is shown that the discretization formula proposed by the authors of this article is better and more effective compared to traditional methods.

Pupils’ Study Habits and Academic Performance

Reading, taking notes, and holding study sessions are all examples of routine, habitual study behaviors that pupils engage in to fulfill the learning objective. This study was conducted to the two hundred-five (n=205) grade 6 pupils at Malitbog 1 District, Division of Bukidnon, School Year 2022-2023. It attempted to answer the level of pupils’ study habits and academic performance and determine the significant relationship between the study habits and academic performance. The study utilized the descriptive-correlational research design with documentary analysis and used an adapted and modified questionnaire to gather the necessary data to answer the specific questions of the study. Purposive sampling was employed to determine the respondents. Mean, Standard Deviation, Frequency, Percentage and Pearson Product Moment Correlation Coefficient or Pearson r were used as statistical tools. Results revealed that pupils’ overall level of study habits was high while their overall academic performance was at very satisfactory level. Significant correlation was registered between pupils’ study habits and their academic performance. Thus, teachers, parents and stakeholders may collaborate with each other to create and conduct activities that will continue to enhance and improve the pupils study habits to improve their academic performance.

Classroom Management and Teaching Competencies of Elementary Teachers

Teachers are the most essential persons for the teaching and learning processes to take place in schools. Specifically, this study sought to determine the level of the teachers in classroom management in terms of behavior reduction, classroom instruction, proactive classroom, and rules and procedures; find out the level of the teachers in teaching competencies in terms of communication and interpersonal skills, organization and planning, facilitation and engagement, and flexibility and adaptability; and determine the significant relationship between classroom management and teaching competencies. The respondents were one hundred fifty (150) elementary teachers in eighteen (12) schools within the Talisayan district. This study used two adapted research instruments and data were gathered using descriptive-correlational research methods. The statistical tools utilized in this study were the Weighted Mean and Standard Deviation and Pearson Product Moment Coefficient Correlation the relationship between the Teachers’ Classroom Management and Teaching Competencies. The results showed that teachers at all times practiced managing classroom management effectively with the aid of their teaching competencies at a very high level. Teachers’ classroom management has positively correlated to teachers’ teaching competencies. The relationship of classroom management and teaching competencies cannot be denied. Therefore, it must be given due importance and attention for better teacher performance as well as pupils performance.

Teachers’ Occupational Stress and Coping Mechanisms

Teachers often experience high levels of stress in their work, but they are equipped with effective coping mechanisms to navigate through it. This study aimed to explore the relationship between teachers' occupational stress and coping mechanisms in public elementary settings. It sought to assess occupational stress based on working, living, and subjectrelated conditions while also evaluating teachers' emotion-focused and problem-focused coping mechanisms. Additionally, it aimed to establish significant relationships between occupational stress and these coping mechanisms. A descriptive correlational involving 145 public elementary teachers in Opol-West District, Misamis Oriental, utilized universal sampling. The study utilized an adapted and modified instrument from Cayao and Arenga (2021) and achieved a reliable Cronbach alpha of 0.855 to validate the survey questionnaire. Statistical tools, including mean, standard deviation, and Pearson correlation coefficients, were employed to analyze the data. Results showed that teachers feel some stress in their living conditions, but report challenges bring extreme stress. They also have moderate stress from subject-related conditions. It was concluded that teachers wanting to grow professionally can occasionally add stress to their overall work pressure. It was recommended that, implement strategies for teachers by coming up with better ways to submit reports.

Analysis of the quality of tunnel roof topography by automatic cutting control under the coupling of multiple factors.

The automatic cutting of coal and rock surface morphology modeling based on the actual geological environment of coal mine underground excavation and mining is of great significance for improving the surface quality of coal and rock after cutting and enhancing the safety and stability of advanced support. To this end, using the principle of coordinate transformation, the kinematic trajectory of the cutting head of the tunneling machine is established, and the contour morphology of the cutting head under variable cutting technology is obtained. Then, based on the regenerative vibration theory of the cutting head, a dynamic model of the cutting head coal wall is established, and the coordinate relationship of the cutting head in the tunnel coordinate system under vibration induction is analyzed. Based on fractal theory and Z-MAP method, a simulation method for the surface morphology of coal and rock after cutting is proposed, which is driven by the cutting trajectory Under the coupling effect of cutting vibration induction and random fragmentation of coal and rock, simulation of the surface morphology of comprehensive excavation tunnels was conducted, and relevant experiments were conducted to verify the results. A 1:3 similarity experimental model of EBZ160 tunneling machine was used to build a cutting head coal and rock system cutting experimental platform for comparative experiments of cutting morphology. Furthermore, statistical methods were used to compare and evaluate the simulated roof with the actual roof. The results show that the relative errors between the maximum range of peaks and valleys, the peak skewness coefficient of height standard deviation, and the kurtosis coefficient of the actual roof are 1.3%, 24.5%, 16%, and 2.9%, respectively. Overall, this indicates that the surface morphology distribution characteristics of the simulated roof and the actual roof are similar, verifying the effectiveness of the modeling and simulation method proposed in this paper, and providing theoretical support for the design and optimization of advanced support in the future.