Karsa (Finland)

Pregnancy and childbirth are natural processes and changes occur physically and psychologically that women need to adapt. Psychological changes that occur during pregnancy, one of which is anxiety that occurs in the third trimester. Anxiety in pregnancy is associated with increased obstetric complications. One of the obstetric cares performed to reduce anxiety in the labor with relaxation, prenatal yoga. The purpose of this study was determine the effect of the application of relaxing prenatal yoga on the level anxiety of pregnancy women in the thirdh trimester. This research uses qualitative methods with a case study approach. The results of the study of respondents who were given a relaxing prenatal yoga intervention experienced a decrease in anxiety scores. Meanwhile, respondents who were not given the intervention experienced a decrease in anxiety scores but at each meeting different anxiety scores. From the results of the study, it can be concluded that relaxing prenatal yoga can help control the anxiety of pregnant women in the third trimester if routinely done. This study can provide a means of information or additional knowledge about the effect of relaxing prenatal yoga to the anxiety level of pregnant women in the third trimester.

Introduction: The high rates of maternal and neonatal mortality remain a major global health challenge, with non-obstetric complications and hypertensive disorders being the dominant causes of death. Although the Maternal and Child Health (MCH) Handbook is used as a monitoring instrument, incomplete data recording by healthcare providers continues to hinder the early detection of high-risk conditions. Objective: The purpose of this study is to determine the relationship between attitudes, workloads, and work environment to the performance of midwives in filling out the KIA book in the early detection of high-risk pregnant women in the Tarogong Kidul sub-district area in 2024. Method: The research method is quantitative research, with a descriptive analytical method with a Cross Sectional design. The sample of this research is a midwife in the working area of Tarogong Kidul Garut District with a sampling technique using total sampling. The data analysis used used the Chi square statistical test. Results: The study showed that workload and work environment can affect the work performance of midwives with a sig value (p=<0.05) in filling out the KIA book in the early detection of high-risk pregnant women. Conclusion: this study shows that workload and work environment are significantly related to midwife's performance in filling out the KIA book.

This study aims to analyze the long-term impact of stunting in childhood on cognitive development and educational attainment through a meta-analysis approach. Stunting, which is indicated by stunted linear growth due to chronic malnutrition, has long been associated with various negative consequences on health and social aspects. By systematically examining the results of quantitative studies from various countries and socio-economic contexts, this study identified a consistent pattern of association between stunting in early life and decline in cognitive function and academic achievement in adolescence and adulthood. Data were obtained from 25 studies that met the inclusion criteria published in the 2015 to 2024 range, and were analyzed using fixed-effect and randomized effects models with the help of the JASP application. The results of the meta-analysis showed that children who experienced stunting had an effect on cognitive and education with a pooled effect size value (Hedges' g = 1.10 t= 9.103; p < 0.001) with a high effect size category. These findings confirm that stunting not only has an impact on short-term physical conditions, but also has significant consequences for human resource development in the long term. Therefore, comprehensive nutrition and education interventions in early life are essential to break the chain of loss due to stunting.

Critical values ​​in an examination indicate a disorder that requires special and rapid action to improve patient safety. Urea examination is one of the laboratory parameters that functions as an indicator in assessing the level of kidney function. Urea levels are considered critical if the results exceed 100 mg/dl. This study aims to understand how to handle critical values ​​in urea examinations. This study describes a case in the field of clinical chemistry related to critical results obtained from urea examinations. The object of the case study used in this study was a serum sample, with data showing a critical urea level of 185 mg/dl. Based on the confirmation results, this figure is in accordance with the condition of patients who have kidney failure and will undergo hemodialysis therapy. The conclusion of this study shows that handling critical values ​​in urea examinations is carried out by identifying patient identity and ensuring good sample quality. In addition, the sample testing process must be carried out carefully and precisely, control results must be optimal, the reagents used must have the appropriate temperature and not expired, and the equipment must be properly maintained and calibrated. Finally, confirmation and reporting of results must be carried out accurately and on time.

Continuous use of gadgets over a long period of time can emit short waves of high energy which can penetrate the eyes and ultimately cause photochemical damage to retinal cells. Excessive use of gadgets will have a negative impact on teenagers, one of which is a decline in eye health. Asthenopia is a disease experienced by the eye because the eye muscles are forced to work hard, especially when they have to look at close objects for a long time. The aim of this research is to determine the relationship between the duration of gadget use and the incidence of eye fatigue (asthenopia) in teenagers at SMAN 1 Garut. The research method used was a quantitative approach with a cross sectional research design. The population in this study was 1374 students and a sample of 94 respondents was obtained using puposive sampling techniques. Data was collected using a gadget usage duration questionnaire and a Visual Fatigue Index (VFI) questionnaire, then the data was analyzed using the Chi Square test. The results of this study show that there is a significant relationship between the duration of gadget use and the incidence of eye fatigue (asthenopia) with a p-value = 0.000 where p <0.05. So it can be concluded that there is a relationship between the duration of gadget use and the incidence of eye fatigue (asthenopia) in teenagers at SMAN 1 Garut. This research is useful as insight that there are negative impacts from excessive use of gadgets, so it is recommended that teenagers apply time limits on gadget use to prevent an increase in the incidence of asthenopia.

Dayak culture offers a wealth of noble values that can positively shape the character of elementary school students. This paper aims to: (1) identify the values of Dayak culture contained in the poem "Philosophy of Huma Betang". (2) Explain the method of introducing these cultural values to elementary school students. (3) Describe the effectiveness of using poetry as a medium of cultural introduction. One of the effective methods to introduce Dayak culture to students is through poetry. This article discusses the poem "Philosophy of Huma Betang" by Misnawati as a medium that conveys cultural values in an interesting and easy-to-understand manner for elementary school students. The importance of this research is based on the need to understand and preserve Dayak cultural values. This research uses a descriptive qualitative approach, by identifying the cultural values contained in the poem. The method of introducing cultural values to elementary school students involves reading with expression, discussion, creative activities, and educational visits. The results of the study show that the use of the poem "Philosophy of Huma Betang" is successful in increasing students' understanding and appreciation of Dayak culture. Students show high interest, they can remember well the values learned, and show improvement in language skills and creativity. Educators also give positive feedback on the effectiveness of this method in learning in elementary school classrooms.

<strong class="journal-contentHeaderColor">Abstract.</strong> Chemical ionization mass spectrometry (CIMS) is widely used in atmospheric chemistry studies. However, due to the complex interactions between reagent ions and target compounds, chemical understanding remains limited and compound identification difficult. In this study, we apply machine learning to a reference dataset of pesticides in two standard solutions to build a model that can provide insights from CIMS analyses in atmospheric science. The CIMS measurements were performed with an orbitrap mass spectrometer coupled to a thermal desorption multi-scheme chemical ionization inlet unit (TD-MION-MS) with both negative and positive ionization modes utilizing Br^-, O₂^-, H₃O⁺ and (CH₃)₂COH⁺ (AceH⁺) as reagent ions. We then trained two machine learning methods on this data: 1) random forest (RF) for classifying if a pesticide can be detected with CIMS, and 2) &nbsp;kernel ridge regression (KRR) for predicting the expected CIMS signals. We compared their performance on five different representations of the molecular structure: the topological fingerprint (TopFP), the molecular access system keys (MACCS), a custom descriptor based on standard molecular properties (RDKitPROP), the Coulomb matrix (CM) and the many-body tensor representation (MBTR). The results indicate that MACCS outperforms the other descriptors. Our best classification model reaches a prediction accuracy of 0.85 &plusmn; 0.02 and a receiver operating characteristic curve area of 0.91 &plusmn; 0.01. Our best regression model reaches an accuracy of 0.44 &plusmn; 0.03 logarithmic units of the signal intensity. Subsequent feature importance analysis of the classifiers reveals that the most important structural fragments are NH and OH for the negative ionization schemes and nitrogen-containing groups for the positive ionization schemes.

Abstract. Chemical ionization mass spectrometry (CIMS) is widely used in atmospheric chemistry studies. However, due to the complex interactions between reagent ions and target compounds, chemical understanding remains limited and compound identification difficult. In this study, we apply machine learning to a reference dataset of pesticides in two standard solutions to build a model that can provide insights from CIMS analyses in atmospheric science. The CIMS measurements were performed with an orbitrap mass spectrometer coupled to a thermal desorption multi-scheme chemical ionization inlet unit (TD-MION-MS) with both negative and positive ionization modes utilizing Br-, O2-, H3O+ and (CH3)2COH+ (AceH+) as reagent ions. We then trained two machine learning methods on this data: 1) random forest (RF) for classifying if a pesticide can be detected with CIMS, and 2) kernel ridge regression (KRR) for predicting the expected CIMS signals. We compared their performance on five different representations of the molecular structure: the topological fingerprint (TopFP), the molecular access system keys (MACCS), a custom descriptor based on standard molecular properties (RDKitPROP), the Coulomb matrix (CM) and the many-body tensor representation (MBTR). The results indicate that MACCS outperforms the other descriptors. Our best classification model reaches a prediction accuracy of 0.85 ± 0.02 and a receiver operating characteristic curve area of 0.91 ± 0.01. Our best regression model reaches an accuracy of 0.44 ± 0.03 logarithmic units of the signal intensity. Subsequent feature importance analysis of the classifiers reveals that the most important structural fragments are NH and OH for the negative ionization schemes and nitrogen-containing groups for the positive ionization schemes.

Rheumatoid Arthritis is an illness that targets the joints, particularly in the limbs, which can cause pain. Pain management can use non-pharmacological management such as cutaneous stimulation, namely with warm ginger compresses. This non-pharmacological management can help relax the body so that it can block pain receptors that will be perceived in the brain. The general objective in the purpose of this study was to ascertain whether ginger compresses could lessen the intensity of elderly rheumatic discomfort at RPSTW Garut, West Java Province in 2023. Pre and posttest designs were used in a quasi-experimental research design..The study population was 75 people with sampling techniques using purposive sampling methods obtained a sample of 14 people. The results indicated that the average severity Assessing the severity of rheumatic pain prior to the application of ginger compress 6.07 with a deviation standard 0.730. While the typical level of pain after Posttest of was 2,79 with a standard deviation of 0.699. Based on the statistical analysis wilcoxon signed rank test obtained a significant impact analyzing the impact of ginger compresses on rheumatoid arthritis pain intensity among older individuals. Researchers suggest that it should be used as gerontic nursing knowledge material, especially complementary therapies and for it is advised to carry out additional studies again using a true experiment design so that the research results are better and the data obtained are more valid