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This study aimed to examine authentic models of science assessment in assessing the competence of senior high school students who met the criteria of validity, practicality, and effectiveness. The methodology applied was an evaluation and developmental research. Research was conducted in senior high school in accordance with the needs of the development of authentic Statistical Analysis System (SAS) models. The participants were students of class X senior high school Gowa in South Sulawesi academic year 2020/2021. The instruments comprised (1) SAS model validation sheet; (2) science achievement test; (3) questionnaires; and (4) observation sheet. The findings of the quality authentic science assessment model met the validity and effectiveness criteria for high category learning outcomes with positive student responses. The practicality implications of the SAS model were also very worthy of applied science in teaching science for assessing the competence of senior high school students.

This study offers a comprehensive review of research trends in WASH in Indonesia from 1975 to April 2021. A total of 272 articles related to Sustainable Development Goals 6.1 and 6.2 were analyzed, sourced from the Web of Science and Scopus databases. The analysis found that water-related research (41%) was more prominent than topics related to sanitation (22%) or hygiene (13%). Social aspects (39%) were the most common focus in literature, particularly studies exploring the factors influencing WASH-related behaviors. However, there was a noticeable lack of studies on the implementation of WASH programs or interventions aimed at changing behavior, highlighting a disconnect between research findings and their application in policy and practice. In contrast, topics on hygiene (14%) and WASH financing (6%) were among the least covered. There was also a significant amount of research that combined multiple topics (23%) and themes (15%), reflecting a growing recognition of the need to address WASH challenges from a holistic, multi-faceted perspective. Geographically, most WASH research was centered in central Indonesia, even though WASH issues, such as inadequate services and poor behavior, tend to be more acute in other areas. This study also identifies several research gaps relating to topic selection, thematic focus, and regional coverage that should be addressed in future WASH studies in Indonesia.

Abstract Pistacia lentiscus L. is an aromatic plant containing a significant percentage of essential oil (EO) used in fragrance, pharmaceuticals, cosmetics, and the food industry. The purpose of this work is focused on the optimization of Pistacia lentiscus L. oleo gum resin EO yield extracted by superheated steam extraction (SHSE) by response surface methodology, including extraction parameters of particle size (0. 5 − 1 mm), temperature (140–180 °C) and time (90–150 min). The optimum conditions for Pistacia lentiscus L. EO extracted by SHSE were found to be (particle size: 0.75 mm, time: 120 min and temperature: 160 ℃) which produced the highest EO yield of 5.7%. A regression model was developed, demonstrating a robust quadratic correlation with an R2 value of 0.9991, making it suitable for predictions. Furthermore, the yield of Pistacia lentiscus L. EO extracted by SHSE was compared with the conventional steam and hydro distillation techniques. The study revealed that SHSE yielded higher quantities of EO than other extraction methods. GC-MS analyzed the chemical composition of Pistacia lentiscus L. EO. The predominant compound of Pistacia lentiscus L. EO was determined to be α-pinene, while the other identified compounds include trans-verbenol, verbenol, cis-verbenone, camphene, β-myrcene, d-limonene, cymene, α-myrtenol, α-campholenal, α-copaene, and α-thujene, whose content differed according to different extraction techniques. Overall, superheated steam extraction is an efficient technique for extracting Pistacia lentiscus L. essential oil that enhances EO yield, requiring less time for extraction.

This article reports data from a qualitative study conducted within the elitist English-medium schools in three cities of Pakistan to claim that theory building, and English teaching practices are still modeled on monolingual biases inherent in the orthodox notions of linguistic purism and Anglo-normative traditions of the 1990s. Orthodoxy is manifest in schools' strong emphasis on direct method and communicative language teaching, and essentialist language management where English is enforced as the sole legitimate language of academic and non-academic transactions. Native language use is attached a stigma and viewed as deficiency in the English language. Such Anglo-normative culture invokes guilty conscience in teachers and students as they disapprove native languages even when they know that they can serve as useful meditating tools for effective content transfer. Crucially, amid English gatekeepers' celebratory attitudes toward English as the sole legitimate language, some teachers still demonstrate deviation from the pervasive linguistic norms. Showing reflexivity and agency, these teachers ideologically oppose the official policy. They discursively generate spaces for negotiating and appropriating the official policies, which signifies that language policy can be a complex multi-layered process rather than a linear, discrete, or top-down phenomenon. Teachers' agency is interpreted as 'decolonial performativity'.

Abstract Understanding the prevalence of abnormal lung function and its associated factors among patients recovering from COVID-19 is crucial for enhancing post-COVID care strategies. This study primarily aimed to determine the prevalence and types of spirometry abnormalities among post-COVID-19 patients in Malaysia, with a secondary objective of identifying its associated factors. Conducted at the COVID-19 Research Clinic, Faculty of Medicine, University Technology MARA, from March 2021 to December 2022, this study included patients at least three months post-discharge from hospitals following moderate-to-critical COVID-19. Of 408 patients studied, abnormal spirometry was found in 46.8%, with 28.4% exhibiting a restrictive pattern, 17.4% showing preserved ratio impaired spirometry (PRISm), and 1.0% displaying an obstructive pattern. Factors independently associated with abnormal spirometry included consolidation on chest X-ray (OR 8.1, 95% CI 1.75–37.42, p = 0.008), underlying cardiovascular disease (OR 3.5, 95% CI 1.19–10.47, p = 0.023), ground-glass opacity on chest X-ray (OR 2.6, 95% CI 1.52–4.30, p

This study aims to develop of a learning model based on Realistic Mathematics Education (RME) that are valid, practical, and effective to improve mathematical literacy skills and students' mathematical disposition. This study uses a research and development method with modified Plomp model. This research was carried out at SMP Negeri 9 Medan in the odd semester of the 2023/2024 academic year. The instruments in this study were the Mathematical Literacy Ability Test and the Mathematical Disposition Questionnaire. The data analysis technique in this study used descriptive statistical analysis. The results of this research showed that: (1) the RME-based learning model developed met the criteria for validity, practicality and effectiveness of the learning model; (2) increasing students' mathematical literacy skills using the realistic RME-based learning model developed in terms of the N-Gain in trial I of 0.29 with low criteria and in trial II of 0.59 with medium criteria. (3) increasing students' mathematical disposition abilities using the developed RME learning model in terms of the average in trial I and trial II, namely 5.04.

Abstract Background This study was exclusively focused on the documentation and cross-cultural evaluation of ethnomedicinal knowledge (EMK) within the diverse linguistic groups of Kohistan situated between the Himalayan and Hindukush Mountain ranges in the north Pakistan. Methods Data were gathered during the field survey (May 2022 to July 2023) through group conversations, semi-structured interviews, and on-site observation. Venn diagrams were employed to illustrate the comparative assessment of EMK, and different ethnobotanical indices were utilized to examine the data. Results A total of 96 wild medicinal plant species (MPs) belonging to 74 genera and 52 botanical families were documented. The most reported MPs belong to the family Polygonaceae (11 species), followed by Asteraceae (9 species) and Lamiaceae (8 species). The ethnomedicinal uses of Leontopodium himalayanum, Pedicularis oederi, Plocama brevifolia, Polypodium sibiricum, Pteridium esculentum, Sambucus wightiana, Solanum cinereum, Teucrium royleanum, Rhodiola integrifolia, Aconitum chasmanthum were reported for the first time in this region. Among the reported taxa herbaceous species were dominated (72%), followed by trees and shrubs (17% and 10%, respectively). Digestive problems (40 taxa and 114 use reports) and skin disorders (19 taxa and 549 use reports) were the most cited disease categories, whereas M. communis, M. longifolia, Ajuga integrifolia, Ziziphus jujuba, and Clematis grata exhibited the highest percentage fidelity levels. Out of 109 documented medicinal uses, a mere 12 were shared across all linguistic groups, and Bateri emerges as a notable outlier with the highest number of medicinal uses. In addition, a significant homogeneity was noted in the reported botanical taxa (61 species) among different linguistic groups. However, since the last decade biocultural heritage of Kohistan is facing multifaceted risks that need urgent attention. Conclusion Our findings could be valuable addition to the existing stock of ethnomedicinal knowledge and may provide ethnopharmacological basis to novel drug discovery for preexisting and emerging diseases prioritizing detailed phytochemical profiling and the evaluation of bioactive potential.

This study presented various types of soliton solutions for the nonlinear integrable Kairat-X equation by utilizing the improved F-expansion technique with symbolic computational software Mathematica. Explored results for the nonlinear integrable Kairat-X equation are interesting, novel, and more general with different physical structures of solitary waves and solitons, such as kink wave, mixed dark–bright, peakon, anti-kink wave, bright, anti-kink dark, periodic, and dark solitons. With numerical simulations, the secured soliton solutions visualized in two-dimensional, three-dimensional, and contour graphs represent the physical phenomena of the demonstrated results. The explored soliton solutions will be helpful to comprehend interesting physical structures in fiber optics, nonlinear optics, ferromagnetic dynamics, and many other scientific fields. The extracted soliton structure sheds light that the enhanced technique is effective, powerful, concise, and reliable. We can also investigate the soliton results of other nonlinear integrable partial and fractional equations.

According to the world health organization (WHO), stroke stands as a significant contributor to mortality and adult disability, causing motor function impairment, paralysis, and intense back pain. In aiding stroke patients' mobility recovery, physiotherapists employ diverse therapeutic techniques. This research introduces an automated method for identifying distinct therapeutic exercises performed by stroke patients during their rehabilitation process. For detecting rehabilitation exercises, leveraging pre-trained neural networks like GoogLeNet, InceptionV3, ResNet-101, DenseNet-201, Xception, InceptionResNetV2, and DarkNet-53, all potent models trained on extensive datasets. The proposed models were trained on a dataset of 2250 diverse RGB images to classify eight rehabilitation exercises: Elbow Extension, Knee Flexion, Neck Exercise, Planter Flexion of Foot, Trunk Extension, Trunk Flexion, Wrist Extension, and Wrist Flexion. The resulting average validation accuracies are as follows: InceptionV3 (97.4%), Xception (97.3%), ResNet101 (97.3%), DarkNet53 (96.7%), GoogLeNet (95.9%), DenseNet201 (94.3%), and InceptionResNetV2 (93.4%). Fuzzy EDAS is then employed to rank the models. This ranking suggests that the inception-v3 model has high rank for most of the classes and is highly recommended for physiotherapy exercises classification.

Numerous harmful phenolic contaminants are discharged into water that pose a serious threat to environment where two of the most important purification methodologies for the mitigation of phenolic contaminants are adsorption and photocatalysis. Besides cost, each process has drawbacks in terms of productivity, environmental impact, sludge creation, and the development of harmful by-products. To overcome these limitations, the modeling and optimization of water treatment methods is required. Artificial Intelligence (AI) is employed for the interpretation of treatment-based processes due to powerful learning, simplicity, high estimation accuracy, effectiveness, and improvement of process efficiency where artificial neural networks (ANNs) are most frequently employed for predicting and analyzing the efficiency of processes applied for the mitigation of these phenolic contaminants from water. ANNs are superior to conventional linear regression models because the latter are incapable of dealing with non-linear systems. ANNs can also reduce the operational cost of treating phenol-contaminated water. A correlation coefficient of >0.99 can be achieved using ANN with enhanced phenol mitigation percentage accuracy generally ranging from 80 % to 99.99 %. Using ANN optimization, the maximum phenol mitigation efficiencies achieved were 99.99 % for phenol, 99.93 % for bisphenol A, 99.6 % for nonylphenol, 97.1 % for 2-nitrophenol, 96.6 % for 4-chlorophenol and 90 % for 2,6-dichlorophenol. In numerous ANN models, Levenberg-Marquardt backpropagation algorithm for training was employed using MATLAB software. This study overviews their employment and application for optimization and modeling of removal processes and explicitly discusses the important input and output parameters necessary for better performance of the system. The comparison of ANNs with other AI techniques revealed that ANNs have better predictability for mitigation of most of the phenolic contaminants. Furthermore, several challenges and future prospects have also been discussed.

This work investigates the dynamics of solitary waves in a thin-film ferroelectric material model, an essential component of optical systems. The study recognizes the limitations of the inverse scattering transform in solving the Cauchy problem for this conformable thin-film ferroelectric material model and applies a new Kudryashov approach and Bernoulli’s equation technique to ordinary differential equations. We apply these methods to the present model and obtain closed form analytical solutions. A variety of traveling wave and soliton solutions are constructed, including kink, bell, bright, and dark soliton solutions. It is acknowledged that the nonlinear evolution equation can be transformed into an ordinary differential equation by applying traveling wave transformations. Suitable physical parameters are chosen to create 2D, 3D, and contour plots that graphically depict the graphical dispersion of obtained fractional soliton solutions. The impact of the conformable fractional parameter is further demonstrated by the graphical representation of solitons propagation. Furthermore, the study develops the Hamiltonian function of the dynamical system to discuss the system’s total energy in terms of momentum and position. While a chaos analysis describes chaotic, quasi-periodic, and periodic behaviors, a sensitivity analysis demonstrates how responsive the model is to various initial conditions. Due to their dual-purpose nature as nonlinear ferroelectric and dielectric materials, thin ferroelectric films are widely used in modern electrical devices.

Background & objectives: Biological approaches for vector mosquito control such as sterile insect technique (SIT) requires sterilization of male mosquitoes through specific radiation doses for sterility induction in males. Under the SIT program, the males used must be compatible with the wild males in vigor, flight and selection of mate. Much of this potential is determined by the diet provided in the larval stages and optimizing the irradiation doses that cause complete sterility but have very minimal effect on the lives of irradiated males. The current study is designed to evaluate gamma radiation doses for inducing sterility in male Aedes aegypti mosquitoes with a genomic background from Pakistan (Swat district) and to assess the effects of radiation exposure on the competency of irradiated males and other life traits of irradiated mosquitoes. Methods: Sterilization of 17-hour-old male pupae (groups of 50 pupa/cup in three replicates) of the Ae. aegypti Swat strain was conducted using radiation doses of 30, 60, 70, 90, and 105 gray (Gy) from (Co60) at the Nuclear Institute for Food and Agriculture (NIFA) in Peshawar, Pakistan. Post-irradiated pupae were released in adult cages. Virgin females of the same cohort were released (1:1) to mate with the irradiated males. Mortality, longevity, mating competitiveness of males, and female fecundity were recorded. Results: An average of 71 eggs per female was recorded in control with 86% hatch rate. Individual females mated with a 60 Gy treated males produced 60 ± 0.6 eggs per female with 17% hatch rate, and those mated with 70 Gy males produced 42 ± 0.01 eggs with a nil hatch rate, whereas females mated with males treated with ≥70 Gy doses did not reproduce to next generation. Females in groups of 50 mated with 60, 70 Gy treated males (equal pairs), produced 369±1.3 and 98±0.01 eggs with 15% and zero hatch rate. Significant dose dependent reduction in longevity was observed for >30 Gy doses. The matting competence of irradiated males was about half that of un-irradiated males. Interpretation & conclusion: Aedes aegypti with a Pakistani genomic background treated with a ≥70 Gy dose of gamma radiation induced complete sterility in males and provided the first-step foundation for SIT application in Pakistan. Further extensive studies are required to optimize the SIT techniques so that fully sterile males with very minor quality changes can be produced on large scales for field trials.

Background Gastroschisis is the most common abdominal congenital defect worldwide. While the mortality rate is 5–10% in developed countries, the rate escalates in developing countries due to less access to surgical care, and studies on the condition are scarce. Gastroschisis mortality and morbidity rates in Indonesia are unknown or unclear; little is also known about influencing factors that reveal epidemiological characteristics. Objective To identify the rate and factors associated with gastroschisis mortality in Indonesia. Methods A retrospective cohort study was conducted at Dr. Cipto Mangunkusumo Hospital, which included neonates with gastroschisis who underwent defect closure surgery from January 2015 to September 2020. We explored possible influencing risk factors, including gestational age, birth weight, number of surgeries, age at closure, and presence of gastroschisis complications. Bivariate analysis was done using Chi-square or Fisher’s test. Results Of 49 neonates with gastroschisis, 42 were included in the study. Seven neonates were excluded due to incomplete medical records. The mortality rate of gastroschisis based on our data was 69%. The age at closure (

Smelting atau peleburan adalah proses mengekstraksi bijih logam murni dari dalam tanah. Dengan kata lain, ini adalah proses pemisahan logam murni dari bijih yang mengandungnya. Untuk mengekstraksi logam, bijih dipanaskan hingga suhu tinggi (di atas titik lelehnya). Untuk proses ini digunakan smelter yang dalam prosesnya akan menghasilkan limbah cair dan limbah padat (sludge). Sludge tersebut biasanya digunakan sebagai penutup lubang bekas tambang. Sludge digunakan sebagai material dasar pembentuk paving block untuk mengurangi limbah dan peningkatan nilai ekonomis. Pada penelitian ini sludge atau lumpur digunakan sebagai pengganti pasir pada produksi paving block. Kadar sludge yang digunakan adalah 10%, 25% dan 50% menggantikan volume pasir, paving block tanpa sludge sebagai benda uji kontrol. Untuk mengetahui mutu paving block yang dihasilkan dilakukan pengujian kuat tekan dan penyerapan. Hasil penelitian menunjukkan bahwa paving block dengan kadar 10% menghasilkan paving block mutu B, pada kadar 25% dan 50% menghasilkan paving block mutu C.

Abstract The quasi-Poisson regression model is used for count data and is preferred over the Poisson regression model in the case of over-dispersed count data. The quasi-likelihood estimator is used to estimate the regression coefficients of the quasi-Poisson regression model. The quasi-likelihood estimator gives sub-optimal estimates if regressors are highly correlated—multicollinearity issue. Biased estimation methods are often used to overcome the multicollinearity issue in the regression model. In this study, we explore the ridge estimator for the quasi-Poisson regression model to mitigate the multicollinearity issue. Furthermore, we propose various ridge parameter estimators for this model. We derive the theoretical properties of the ridge estimator and compare its performance with the quasi-likelihood estimator in terms of matrix and scalar mean squared error. We further compared the proposed estimator numerically through a Monte Carlo simulation study and a real-life application. We found that both the simulation and application results show the superiority of the ridge estimator, particularly with the best ridge parameter estimator, over the quasi-likelihood estimator in the presence of multicollinearity issue.

Women of childbearing age are a group that plays an important role in the agricultural sector not only in Indonesia but also in other agricultural countries around the world. The types of agricultural activities undertaken by WUS are sometimes the same as those of men, even those that allow contact with pesticides. Women of childbearing age in Pagaralam are at risk of experiencing health effects such as anemia, due to their exposure to Organophosphates. It is necessary to conduct research aimed at analyzing the determinants of pesticide exposure to the haemoglobin level in WUS as a basis for recommendations for efforts to prevent and overcome the effects of pesticide exposure. The design of this study was observational with a cross sectional study approach. The study population was women of childbearing age who were exposed to pesticides in the South Dempo District of Pagaralam, with a sample size of 120 WUS. Sampling using cluster sampling technique. Data collection was carried out through interviews using a questionnaire, observation using a checklist, measurement of body weight using a weight scale, height using a microtoise, and Hb levels using the Easy Touch GCHB tool. Data analysis of the results of the study was carried out univariately, and bivariate using the Chi- Square.The results of bivariate analysis of variables show that were significant with the haemoglobin level in women of childbearing age in South Dempo District were tenure, long time laundry spraying and length of time preparing pesticide. While variables that are not associated with haemoglobin levels are length of spraying, length of time mixed, frequency of spraying, and use of PPE. It is recommended that women of childbearing age reduce the length of time washing clothes spraying and the length of time preparing pesticides through good time management. Keywords : Haemoglobin level, pesticide exposure, woman of childbearing age

Depletion of oil and gas resources is a major concern for researchers and the global community. Researchers are trying to develop a way to overcome these issues using the Fischer–Tropsch synthesis (FTS) process. The FTS reaction converts a mixture of hydrogen and carbon monoxide gases into a liquid fuel. The reactions are performed in the reactor and in the presence of a catalyst. A series of catalysts, such as iron, cobalt, nickel, and ruthenium, have been used for the FTS process. In iron-based catalysts, the Fe5C phase is the active phase that produces C5+ hydrocarbons. At higher conversion rates, the presence of water in the products is a problem for cobalt catalysts because it can trigger catalyst deactivation mechanisms. Ni-based catalysts play key roles as base catalysts, promoters, and photothermal catalysts in FTS reactions to produce different useful hydrocarbons. Ruthenium catalysts offer not only high activity but also selectivity toward long-chain hydrocarbons. Moreover, depending on the Ru particle size and interaction with the oxide support, the catalyst properties can be tuned to enhance the catalytic activity during FTS. The detailed reaction pathways based on catalyst properties are explained in this article. This review article describes the issues and challenges associated with catalysts used for the FTS process.

Low back pain (LBP) is a prevalent spinal issue, affecting eight out of ten individuals. Notably, lumbar intervertebral disc (IVD) abnormalities frequently contribute to LBP. To diagnose LBP, Magnetic Resonance Imaging (MRI) is crucial for obtaining detailed spinal images. This paper employs deep learning (DL) to detect and locate lumbar IVD in sagittal MR images. It further classifies lumbar IVDs as healthy or herniated, utilizing both novel convolutional neural network (CNN) and conventional CNN models. The dataset utilized comprises MR images from 32 patients, with 10 exhibiting healthy discs and the remaining 22 posing a mix of healthy and herniated discs, totaling 160 lumbar discs, incorporating 112 healthy and 48 herniated discs. In this study, ResNet-50 architecture in the Novel Lumbar IVD detection (NLID) model served as the feature extractor to segment the five lumbar IVDs from MR images. The features extracted from ResNet-50 were input into YOLOv2 for the identification of the region of interest (ROI). The findings indicate that optimal performance was achieved at the 22nd Rectified Linear Unit (ReLU) activation layer, boasting a remarkable 99.59% average precision, 97.22% F1-score, 94.59% precision, and a perfect 100% recall. This commendable performance consistently held above the 85% threshold until the 22nd ReLU activation layer. Regarding imbalanced dataset classification, AlexNet emerged as the frontrunner among other pre-trained networks, boasting the highest test accuracy of 90.63%, and an impressive F1 score of 88.77%. Meanwhile, the Novel Lumbar IVD Classification (NLIC) model achieved superior results with 93.75% test accuracy, and 92.27% F1-score. In the setting of the balanced dataset, NLIC achieved 96.88% test accuracy, and 96.46% F1-score with fewer epochs compared to AlexNet, affirming the robustness of the novel trained-from-scratch network. These findings distinctly underscore the effectiveness of CNNs in both medical image segmentation and classification.

This research was motivated by the low level of mathematical literacy skills and student independence at school. The focus of the problems studied in this research includes 1) Students' mathematical literacy abilities; 2) Student learning independence; 3) Realistic Mathematics Learning Process; 4) Increasing students' mathematical literacy skills and learning independence in the experimental class and control class; 5) The influence of PMR on students' literacy skills and learning independence in the experimental class. The research method used is quasi-experimental, pretest posttest type. The research population included all fifth-grade students at SDN 29 Pardomuan. The treatment given to the experimental class was Building Space learning using a Realistic Mathematical Approach model. Data analysis was carried out using quantitative analysis. The results of data calculations through statistical tests obtained 1) There is a positive (unidirectional) influence between the Educational Learning Model on Mathematical Literacy Ability with the Sig. Educational Learning Model value (0.000) < 0.05 and the calculated t value (3.838) > t table (1.995); 2) There is a positive (unidirectional) influence between the Educational Learning Model on Student Learning Independence and the Sig. Educational Learning Model (0.000) < 0.05 and calculated t value (4.487) > t table (1.995); 3) There is a positive (unidirectional) influence between the Educational Learning Model on Mathematical Literacy Ability and the Sig value. Educational Learning Model (0.000) < 0.05 and calculated t value (3.838) > t table (1.995); 4) There is a positive (unidirectional) influence between the Educational Learning Model on Student Learning Independence with the Sig. Educational Learning Model value (0.000) < 0.05 and the calculated t value (4.487) > t table (1.995).

Environmental problems as a world issue require the importance of preparing citizens to have the ability to prevent environmental problems. This research aims to present a study of pedagogical approaches and citizenship education learning schemes in strengthening the integration of ecological citizenship into education as an effort to provide a foundation for citizenship education to develop ecological citizenship in schools. This research uses a comprehensive literature review research method, involving analysis and synthesis of findings from various literature to gain an understanding of the ecological citizenship education learning scheme. The research results show that the pedagogical landscape of ecological citizenship education can be packaged in learning approaches (1) place-based learning; (2) problem-based learning; (3) environmental justice pedagogy; (4) ecological citizenship education; (5) action competency learning; (6) learning to serve; (7) participatory action research; (8) socio-scientific inquiry-based learning (SSIBL). the pedagogical approach to ecological citizenship education includes six (6) stages: (1) inquiry; (2) planning action; (3) critical and active involvement; (4) community participation and networking on a scale (local, national, global), (5) maintaining environmental and social change, and (6) evaluation and reflection.

Female farmers of childbearing age are at risk of adverse health effects due to pesticide exposure in agricultural activities. The use of Personal Protective Equipment (PPE) that does not meet the required standards is one of the factors that causes high pesticide exposure in female farmers of childbearing age. Therefore, the objective of this research was to analyze the factors associated with PPE use behavior among female farmers of childbearing age in South Dempo District of Pagar Alam. This research was a quantitative analytic with a cross-sectional approach. The population of this study was all farmers of childbearing age in the South Dempo District Pagar Alam. A sample of 116 respondents was selected through simple random sampling. Data collection was conducted through interviews using a questionnaire. Data processing was carried out with the stages of editing, coding, entry, and cleaning. Bivariate analysis employed the chi-square test, while multivariate employed the multiple logistic regression. The results of the bivariate analysis showed that there were significant associations between the variables and PPE use behavior: education level, income level, knowledge, attitude, and PPE availability (p-value0,05). The multivariate analysis showed that the most dominant variable determining PPE use behavior was PPE availability. The study concluded that PPE availability was the most determining factor in the PPE use behavior among female farmers of childbearing age.

The family Aphididae (Hemiptera) represents one of the most diverse groups of sap-sucking insect pests referred to as aphids or plant-lice, with 366 species reported in Pakistan, associated with wide array of agricultural and horticultural crops, including fruit and forest trees, weeds, grasses, shrubs, and vines. This work aims to provide an updated checklist of aphids and their associated host plants documented across various regions of Pakistan. The checklist consolidates information from various published literature sources, including annotated checklists, regional distribution data, and host plant records from Pakistan. In this study, we present an annotated checklist of 366 aphid species, belonging to 134 genera and 11 subfamilies, associated with a total of 359 host plant species stretched over 84 families in Pakistan.