420 research outputs found

    EEOC and Arellano v. Hamilton Sundstrand Corporation

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    EVALUASI PERUBAHAN KADAR AIR, TEKSTUR, DAN RASA SAGU LEMPENG DALAM BERBAGAI KEMASAN PLASTIK SELAMA PENYIMPANAN

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    The objectives of the research were to determine kinds of suitable plastic packaging to keep five sago lempeng formulations, and to examine the changes of sago lempeng characteristics during storage. Three kinds of plastics used were Polyvinyl chloride (PVC), Polyethylene (PE) and Polypropylene (PP). The five sago lempeng formulations were (1) 100% of sago starch (control); (2) 70% of sago starch and 30% of coconut (F1); (3) 70 % of sago starch, 10% of wheat flour, 10% of soybean flour and 10% of skim milk (F2); (4) 70% of sago starch, 10% of wheat flour, 10% of skim milk, and 10 % of coconut (F3); and (5) 70% of sago starch, 10 % of soybean flour, 10 % of skim milk, and 10 % of coconut (F4). Results of the study revealed that PE plastic was better in preventing sago lempeng to absorb water dan oxygen, compared to PVC and PP. In addition, the use of PE plastic was able to maintain flavor dan self life of sago lempeng during storage for a period of 16-32 weeks. During the storage, texture of the sago lempeng was the first physical properties changed, with the fastest change occurred in F2. This was because the addition of hydrophilic soy bean flour and hygroscopic skim milk that made the products was easier to absorb water. Keywords: sago lempeng formulation, plastic packaging, and sago characteristic

    An Efficient, Green Chemical Synthesis of the Malaria\ud Drug, Piperaquine

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    To provide a robust, efficient synthesis of the malaria drug piperaquine for potential use in resource-poor settings. We used in-process analytical technologies (IPAT; HPLC) and a program of experiments to develop a synthesis of piperaquine that avoids the presence of a toxic impurity in the API and is optimized for overall yield and operational simplicity. A green-chemical synthesis of piperaquine is described that proceeds in 92 – 93 % overall yield. The chemistry is robust and provides very pure piperaquine tetraphosphate salt (> 99.5 %). The overall process utilizes modest amounts (about 8 kg/kg) of 2-propanol and ethyl acetate as the only organic materials not incorporated into the API; roughly 60 % of this waste can be recycled into the production process. This process also completely avoids the formation of a toxic impurity commonly seen in piperaquine that is otherwise difficult to remove. An efficient synthesis of piperaquine is described that may be useful for application in resource-poor settings as a means of expanding access to and reducing the cost of ACTs

    Non‐Invasive Assessment of the Embryo Viability via the Analysis of the Culture Media

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    Infertility in recent years is a growing public health issue throughout the developed world. Assisted reproductive techniques, especially in vitro fertilization, have the potential to partially overcome the low natural reproductive ratio. Nowadays, single embryo transfer gains grounds in clinical practice, urging the development of more reliable methods for selecting the best embryo. In the traditional clinical practice, embryos are selected for transfer based on morphological evaluation. In vitro culturing of embryos also provides a very important material for further non‐invasive evaluation by means of examining a biomarker in the spent culture medium (SEC). Current measure methods concentrate on the metabolomic activity of the developing embryos none compounds. These studies are mainly utilizing the tools of modern analytics and proteomics. In a paper published by Montskó et al. in 2015, the alpha‐1 chain of the human haptoglobin molecule was described as a quantitative biomarker of embryo viability. In a series of retrospective, blind experiments achieved more than 50% success rate. This chapter summarizes the currently available metabolomic and proteomic approaches as the non‐invasive molecular assessment of embryo viability

    Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

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    This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches

    Chemical and Organoleptic Characteristics of Cocoa Powder from Fermented and Unfermented Cocoa Beans from Masni District and Sidey in Manokwari Regency

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    beverage industry, such as chocolate drinks and ingredients for cakes, puddings, and ice cream. The fermentation process of cocoa beans is one of the determining factors for the quality of cocoa powder products produced. This is because during the fermentation process, physical, chemical, and organoleptic characteristics are formed, which become the standard for high-quality cocoa powder products. One of the factors that influences the success of the cocoa bean fermentation process is the fermentation time. The right fermentation time is expected to produce high-quality cocoa beans with a distinctive chocolate flavor, according to consumer preferences. The aim of this study was to determine the chemical, and organoleptic characteristics of cocoa powder from cocoa beans originating from Masni District and Sidey District with different fermentation times. The study consisted of six treatments: cocoa beans processed by the community (BKT), cocoa beans without fermentation (BKTF), cocoa beans fermented for 3 days (BK3), 4 days (BK4), 5 days (BK5), and 6 days (BK6). The differences between the treatments of unfermented cocoa beans and the fermentation time affect the physicochemical and organoleptic characteristics of the resulting cocoa powder. The fermentation process tends to improve the color of cocoa powder from dark brown to a lighter shade of brown, increase the moisture content, decrease the fat content, and significantly influence the organoleptic characteristics. Fermenting cocoa beans for 5 days results in cocoa powder with the best physical, chemical, and organoleptic characteristics. The organoleptic test of cocoa powder from cocoa beans fermented 5 days (BK5) show a slightly light brown to brown color, a strong to very strong cocoa powder flavor, a taste from less bitter to moderately bitter, and acidity levels from less acidic to moderately acidic

    A Mixed Binary Linear Programming Model for Optimal Energy Management of Smart Buildings

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    Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs charge and discharge processes and also those of BESS, in which the binary decision variables represent the charging and discharging of EVs/BESS in each period. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis are considered. The results point to a 65% reduction in peak load consumption supplied by an external power grid and a 28.4% reduction in electricity consumption costs.This research was funded by FEDER Funds through COMPETE program and from National Fundsthrough FCT under the project UID/EEA/00760/2019 and BENEFICE – PTDC/EEI-EEE/29070/2017.info:eu-repo/semantics/publishedVersio
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