The Effect of Clean and Healthy Lifestyle Education with Poster Media on the Level of Knowledge of Clean and Healthy Lifestyle and the Presence of Mosquito Flies in Geyer Village

Education on Clean and Healthy Living Behavior is considered important as an effort to prevent diseases transmitted through mosquito larvae, especially in areas with low levels of health awareness. The purpose of this study was to analyze the effect of Clean and Healthy Living Behavior education using poster media on the level of community knowledge and the presence of mosquito larvae in Geyer Village. This research method uses a quantitative approach with a pre-test-post-test design. The research location was in Geyer Village. The research was conducted in January-June 2024. The study population included all heads of families in Geyer Village, totaling 2,086 heads of families. The sampling technique was accidental sampling. The sample in this study was 95 family heads. Data collection can be done by using questionnaires in the form of interviews and observations. Data were analyzed using paired t-test, namely Dependent T-Test or Wilcoxon test. The results showed that there was an effect of Clean and Healthy Living Behavior education with poster media on the level of knowledge about Clean and Healthy Living Behavior and the presence of larvae in Geyer Village (p-value=0.000). Education on Clean and Healthy Living Behavior using poster media is effective in increasing community knowledge and reducing the presence of larvae, which in turn can contribute to efforts to prevent mosquito-borne diseases. In addition, education through posters also contributed to a decrease in the presence of larvae in the neighborhood. It is recommended that the Clean and Healthy Living Behavior education program be carried out in a sustainable manner by utilizing various media for optimal impact. Keywords: Hygiene and healthy lifestyle, Knowledge, Mosquito larva

Promoting Equitable and Inclusive Green Job Growth in Southeast Asia

The transition to a green economy offers a bright future for Southeast Asia. It's not only a US$1 trillion market opportunity by 2030 across the region's economies. It's also a pathway to a sustainable future, one that is resilient to the climate crisis, more secure for nations, healthier for residents, and inclusive for all.To guide this radical transformation, we studied employment markets across six countries—Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam—and conducted 80 interviews with employers, researchers, and nongovernmental organisations (NGOs). This report, supported by J.P. Morgan, identifies steps that leaders across sectors— governments, funders, NGOs, investors, and employers—can take to ensure the emerging green economy achieves a "just transition" that leaves no one behind

Short-term Water Level Forecast Using ANN Hybrid Gaussian-Nonlinear Autoregressive Neural Network

The aim of this study is to develop the best forecast model using hybrid Gaussian-Nonlinear Autoregressive Neural Network to forecast the water level with multiple hour ahead for Melaka River.The  development of flood forecast models is crucial and has led to risk control, policy recommendations, a reduction in human life loss, and a reduction in flood-related property destruction. In this research, Artificial Neural Network (ANN) approach was used to forecast flood by modeling and forecasting water level time series . ANN approach was selected due to its high reputation abilities to learn from the time-series data pattern. A total of  2782 data for the period of one month  was used in ANN training, validation, and testing to forecast the flash flood. In this study , Hybrid Gaussian Nonlinear Autoregressive Neural Network (Gaussian-NAR) was used as the ANN approach to forecasting the water level time series. This study's primary focus is to find the most appropriate forecast model to forecast the water level in multiple time steps ahead, which are 1 hour, 3 hours, 5 hours, and 7 hours. The forecast accuracy measures are measured using the Pearson R and R-squared to find the most accurate model for this multiple time-step ahead. The result indicates that with 7 hours forecast ahead, the R squared is 86.7%. The best model in the Gaussian-NAR forecast is a 3-hour water level forecast with the R squared of 99.8 percent and had the best model performance result

ANALISIS PENINGKATAN KUALITAS HIDUP MASYARAKAT DKI JAKARTA MENGGUNAKAN KEBIJAKAN POIN SOSIAL TIONGKOK

Kesejahteraan kualitas hidup dan keamanan sebuah negara adalah suatu indikator kemajuan suatu bangsa. Dengan jumlah penduduk sebanyak 270 juta jiwa, Indonesia dinobatkan sebagai negara dengan populasi tertinggi ke-4 di dunia. Dengan populasi sebanyak ini, maka akan sangat sulit untuk menjaga kualitas hidup warga negara terutama dalam hal keamanan negara Indonesia. Oleh karena itu, penelitian ini bertujuan untuk mengetahui pendapat masyarakat DKI Jakarta apabila sistem kebijakan Poin Sosial Tiongkok diterapkan di DKI Jakarta. Metode yang digunakan dalam penelitian ini adalah metode kuantitatif dengan 880 responden masyarakat DKI Jakarta. Pengujian dilakukan menggunakan Uji t dengan alpha 0,05. Hasil penelitian Thitung (9,452) > Ttabel (1,963) dan Sig (0,001) < Alpha (0,05) menunjukkan hasil positif yang menyatakan bahwa kebijakan Poin Sosial Tiongkok akan berpengaruh meningkatkan kualitas hidup masyarakat DKI Jakarta bila diterapkan di DKI Jakarta

Memory enhancing drugs and Alzheimer’s Disease: Enhancing the self or preventing the loss of it?

In this paper we analyse some ethical and philosophical questions related to the development of memory enhancing drugs (MEDs) and anti-dementia drugs. The world of memory enhancement is coloured by utopian thinking and by the desire for quicker, sharper, and more reliable memories. Dementia is characterized by decline, fragility, vulnerability, a loss of the most important cognitive functions and even a loss of self. While MEDs are being developed for self-improvement, in Alzheimer’s Disease (AD) the self is being lost. Despite this it is precisely those patients with AD and other forms of dementia that provide the subjects for scientific research on memory improvement. Biomedical research in the field of MEDs and anti-dementia drugs appears to provide a strong impetus for rethinking what we mean by ‘memory’, ‘enhancement’, ‘therapy’, and ‘self’. We conclude (1) that the enhancement of memory is still in its infancy, (2) that current MEDs and anti-dementia drugs are at best partially and minimally effective under specific conditions, (3) that ‘memory᾿and ‘enhancement᾿are ambiguous terms, (4) that there is no clear-cut distinction between enhancement and therapy, and (5) that the research into MEDs and anti-dementia drugs encourages a reductionistic view of the human mind and of the self

Short-term water level forecast using ANN hybrid Gaussian-nonlinear autoregressive neural network

The aim of this study is to develop the best forecast model using hybrid Gaussian-Nonlinear Autoregressive Neural Network to forecast the water level with multiple hour ahead for Melaka River. The development of flood forecast models is crucial and has led to risk control, policy recommendations, a reduction in human life loss, and a reduction in flood-related property destruction. In this research, Artificial Neural Network (ANN) approach was used to forecast flood by modeling and forecasting water level time series . ANN approach was selected due to its high reputation abilities to learn from the time-series data pattern. A total of 2782 data for the period of one month was used in ANN training, validation, and testing to forecast the flash flood. In this study , Hybrid Gaussian Nonlinear Autoregressive Neural Network (Gaussian-NAR) was used as the ANN approach to forecasting the water level time series. This study's primary focus is to find the most appropriate forecast model to forecast the water level in multiple time steps ahead, which are 1 hour, 3 hours, 5 hours, and 7 hours. The forecast accuracy measures are measured using the Pearson R and R-squared to find the most accurate model for this multiple time-step ahead. The result indicates that with 7 hours forecast ahead, the R squared is 86.7%. The best model in the Gaussian-NAR forecast is a 3-hour water level forecast with the R squared of 99.8 percent and had the best model performance result

Flood Prediction Using ARIMA Model In Sungai Melaka, Malaysia

The aim of this study is to develop a flood prediction model by analyzing the real-time flood parameters for Pengkalan Rama, Melaka river hereafter known as Sungai Melaka using the Box-Jenkins method. Hourly water levels are predicted to alleviate flood related problems caused by the overflow of Sungai Melaka.. The time series from 7 January 2020 12.00 am until 15 January 2020 8.00 am was used to check the stationarity by using the Augmented Dickey-Fuller (ADF) and differencing method to make a non-stationary time series stationary. The main methods used for model identification with autocorrelation (ACF) function and partial autocorrelation function (PACF) are visual observation of the series. The best ARIMA model was identified by the parameter Akaike Information Information Criterion (AIC) and the Bayesian Information Criterion (BIC). The best ARIMA model for the Pengkalan Rama was ARIMA (2, 1, 2) with the AIC value 1297.5 and BIC value 1304.6. The time series had lead forecast up to 8 hours generated by using the ARIMA (2, 1, 2) model. The accuracy of the model was checked by comparing the original series and forecast series. The result of this research indicated that the ARIMA model is adequate for Sungai Melaka. In conclusion, ARIMA model is an adequate short term forecast of water level with the lead forecast of up to 8 hours. Hence, it is indubitable that the ARIMA model is suitable for river flood

Design of a healthcare ecosystem to improve user experience in pediatric urotherapy

This paper addresses challenges in pediatric urotherapy, focusing on low patient compliance and motivation. Informed by creative sessions with children aged 9-13y, a novel urotherapy ecosystem concept is designed. It includes a smart drinking bottle, context-aware reminder watch, home uroflowmeter, smartphone app, and clinician portal. Interconnected products, embodied interaction, stigma-free design, and a digital training buddy aim to enhance engagement, motivation, and patient experience. This concept showcases the potential of integrating diverse design methodologies in healthcare design

Parental Substance Abuse As an Early Traumatic Event. Preliminary Findings on Neuropsychological and Personality Functioning in Young Drug Addicts Exposed to Drugs Early.

open5noParental substance use is a major risk factor for child development, heightening the risk of drug problems in adolescence and young adulthood, and exposing offspring to several types of traumatic events. First, prenatal drug exposure can be considered a form of trauma itself, with subtle but long-lasting sequelae at the neuro-behavioral level. Second, parents’ addiction often entails a childrearing environment characterized by poor parenting skills, disadvantaged contexts and adverse childhood experiences (ACEs), leading to dysfunctional outcomes. Young adults born from/raised by parents with drug problems and diagnosed with a Substance Used Disorder (SUD) themselves might display a particularly severe condition in terms of cognitive deficits and impaired personality function. This preliminary study aims to investigate the role of early exposure to drugs as a traumatic event, capable of affecting the psychological status of young drug addicts. In particular, it intends to examine the neuropsychological functioning and personality profile of young adults with severe SUDs who were exposed to drugs early in their family context. The research involved three groups, each consisting of 15 young adults (aged 18–24): a group of inpatients diagnosed with SUDs and exposed to drugs early, a comparison group of non-exposed inpatients and a group of non-exposed youth without SUDs. A neuropsychological battery (Esame Neuropsicologico Breve-2), an assessment procedure for personality disorders (Shedler-Westen Assessment Procedure-200) and the Symptom CheckList-90-Revised were administered. According to present preliminary results, young drug addicts exposed to drugs during their developmental age were characterized by elevated rates of neuropsychological impairments, especially at the expense of attentive and executive functions (EF); personality disorders were also common but did not differentiate them from non-exposed youth with SUDs. Alternative multi-focused prevention and intervention programs are needed for children of drug-misusing parents, addressing EF and adopting a trauma-focused approach.openParolin, Micol; Simonelli, Alessandra; Mapelli, Daniela; Sacco, M.; Cristofalo, P.Parolin, Micol; Simonelli, Alessandra; Mapelli, Daniela; Sacco, M.; Cristofalo, P

Development of the HT&Me intervention to support women with breast cancer to adhere to adjuvant endocrine therapy and improve quality of life.

BACKGROUND: Breast cancer is the most common cancer in women worldwide. Approximately 80% of breast cancers are oestrogen receptor positive (ER+). Patients treated surgically are usually recommended adjuvant endocrine therapy (AET) for 5-10 years. AET significantly reduces recurrence, but up to 50% of women do not take it as prescribed. OBJECTIVE: To co-design and develop an intervention to support AET adherence and improve health-related quality-of-life (QoL) in women with breast cancer. METHODS: Design and development of the HT&Me intervention took a person-based approach and was guided by the Medical Research Council framework for complex interventions, based on evidence and underpinned by theory. Literature reviews, behavioural analysis, and extensive key stakeholder involvement informed 'guiding principles' and the intervention logic model. Using co-design principles, a prototype intervention was developed and refined. RESULTS: The blended tailored HT&Me intervention supports women to self-manage their AET. It comprises initial and follow-up consultations with a trained nurse, supported with an animation video, a web-app and ongoing motivational 'nudge' messages. It addresses perceptual (e.g. doubts about necessity, treatment concerns) and practical (e.g. forgetting) barriers to adherence and provides information, support and behaviour change techniques to improve QoL. Iterative patient feedback maximised feasibility, acceptability, and likelihood of maintaining adherence; health professional feedback maximised likelihood of scalability. CONCLUSIONS: HT&Me has been systematically and rigorously developed to promote AET adherence and improve QoL, and is complemented with a logic model documenting hypothesized mechanisms of action. An ongoing feasibility trial will inform a future randomised control trial of effectiveness and cost-effectiveness