October 2021

Background: Poor nutrition in pregnancy is a major public health concern. The high intake of saturated fats, carbohydrates and sodas have been related to an increased risk of gestational diabetes mellitus. Therefore, nutritional deficiencies in pregnant women can lead to preterm labor & intra uterine growth retardation. Objective: Reproductive-aged women should adopt a healthy dietary lifestyle, which reduces the risk of adverse birth outcomes and chronic diseases of both mother and newborn. Therefore, the purpose of this study is to assess cultural-dietary behavior of consuming vegetables and fruit with adverse birth outcomes in pregnant ethnic minority women. Method: Literature for this review was conducted using the following online databases such as Pubmed, Google scholar and Science direct; a total of thirty-four articles were included in this study after the inclusion and exclusion criteria. All the findings in this study are based on published information as listed in the references. Result: Several of the reviewed study reported that association between maternal diet and adverse birth outcomes such as preterm birth, stillbirth, low birth weight, neonatal death, congenital anomaly and small for gestational age. Studies showed that the lifestyle intervention group showed higher consumption of vegetables compared to women in the control group. Also, sixty-five percent of ethnic minority women did not meet the maximum score for total vegetables intake. Conclusion: In a nutshell, longitudinal studies are required to assess and explore long-term influences and dietary behaviors for an effective behavioral change intervention study.

The research is a case study at horsemeat shredded business group in Binamu Sub-district Jeneponto Regency. The research aims to find out development strategies of horsemeat shredded business in business and to analyze supporting and inhibiting factors of the business. The research is conducted for three months, April to June 2016. The research population includes one horsemeat shredded business group located in Binamu Sub-district. Sampling in the research is conducted purposively by selecting one horsemeat shredded business group of that employs nine workers in Binamu Sub-district Jeneponto Regency. The research results indicate that factors supporting the horsemeat shredded business to stay exist in its product development consist of raw material availability, having experiences in floss production business, the existence of business brand, good product storability quality, and unique flavor. The inhibiting factors include less effective promotion, less comfortable working condition, unstandardized work arrangements, production tools, and horsemeat shredded that is sometimes veined. Strategies to develop the horsemeat shredded floss business comprise conduct effective and efficient promotion that could be done through SME (small and medium enterprises) exhibitions held by the local government, brochures, advertising on internet media and other social media, put up the product expired date and halallabel from the MUI (the Council of Indonesian Ulama), nutrient composition and suitable for consumption production code from the BPOM, and reducing product price by putting up 10% Discount remark since the average consumers favor discount.

A Linear Wireless Sensor Network (LWSN) is a grouping of sensors arranged in a linear topology with or without junction zones. LWSNs are applied in several areas involving, among others, gas pipelines, road or rail infrastructure, border surveillance infrastructure, waterways, oil, etc. The (LWSN) are subjected to the same constraints as those subjected by the traditional networks (non-linear), energy saving, overload, delays, latency etc. To optimize the energy consumption of the network, among other things, one technique consists in organizing the network into several groups of nodes called clusters. Several algorithms for the construction of clusters have been proposed in the research. The majority of these propositions concern classical networks (non-linear). Recent proposals for clustering algorithms relating exclusively to linear networks have been made in the current research. These last proposals concerned k-redundant networks (number of nodes within transmission range) with a k previously assumed as an assumption (k = 2). On the other hand, these proposals do not take into account the addition, loss and removal of nodes in the sensor network. Therefore, faced with these situations, the clustering algorithms already proposed may be unsuitable. In this article we propose a generalization (extension) of a clustering mechanism for linear wireless sensor networks. The algorithms that we propose in this work will allow the linear sensor network to be able to react to the addition of new nodes as well as to the loss and deletion that the network nodes may experience. The solution that we present also works for all k-redundant networks regardless of the value of k, it is not fixed on a constant value of k as was the case for the solutions previously proposed in current research. The solution was evaluated with the Castalia / Omnet ++ simulator, on a topology with several junction zones. The results obtained showed a complete reconstitution of the clusters with a relatively very fast reaction time, and this as well for the addition of nodes as in the face of the losses and deletions of nodes of the linear wireless sensor network.