Chemical composition and larvicidal activity of the essential oil of Pimenta dioica leaves

In this study, we investigated the main constituent, the predominant class and biological activity of the essential oil extracted from the leaves of Pimenta dioica and the pattern of the major constituent against larvae in the third stage of Aedes aegypti. For this reason, we extracted the oil by hydrodistillation, identified its components by gas chromatography coupled with mass spectrometry (GC/MS) and calculated the lethal concentration (LC50) of the larvicidal activity using the Reed-Muench method. The results show that the oil consists mainly of eugenol, in which the phenylpropanoid class predominated and the lethal concentration, LC50, was 38.86 μg mL-1at a confidence level of 2.25 μg mL-1, while the eugenol standard presented LC5079.75 μg mL-1at a confidence level of 2.10 μg mL-1. Given the facts, we conclude that the oil is more active than the standard and that it has the potential to replace chemical larvicides.

PENDEKATAN METODE MARKOWITZ UNTUK OPTIMALISASI PORTOFOLIO DENGAN RISIKO EXPECTED SHORTFALL (ES) PADA SAHAM SYARIAH DILENGKAPI GUI MATLAB

A portfolio is a combination of two or more securities as investment targets for a certain period of time with certain conditions. The Markowitz method is a method that emphasizes efforts to maximize return expectations and can minimize stock risk. One method that can be used to measure risk is Expected Shortfall (ES). ES is an expected measure of risk whose value is above Value-at-Risk (VaR). To make it easier to calculate optimal portfolios with the Markowitz method and risk analysis with ES, an application was made using the Matlab GUI. The data used in this study consisted of three JII stocks including CPIN, CTRA, and BSDE stocks. The results of the portfolio formation with the Markowitz method obtained an optimal portfolio, namely the combination of CPIN = 34.7% and BSDE = 65.3% stocks. At the 95% confidence level, the ES value of 0.206727 is greater than the VaR value (0.15512).

Subjectivity reducing in software version criticality classification with the support of an expert system

In the software version release management process, there is a need, on the part of human specialists, to classify the criticality of each software version. However, the subjectivity of this classification may be present according to the experience acquired by specialists over the years. To reduce subjectivity in the process, an Artificial Intelligence technique called Expert System (ES) can be applied to represent the knowledge of human specialists and use it in problem solving. Thus, the aim of this paper was to reduce the subjectivity in the criticality classification of the software version with the support of the Expert System. To this end, a questionnaire was developed with the objective of obtaining the criticality opinions classified as High, Medium and Low in each specialist's software version to assist in the preparation of the ES production rules. ES generated 17 production rules with a 100% confidence level applied to a production database. The results of the classification carried out by the ES corresponded to the classification carried out by the specialists in the production base, that is, the ES was able to represent their knowledge. Then, another questionnaire was applied to the specialists to verify the perception of satisfaction regarding the use of the ES with a result obtained of 4.8, considered satisfactory. It was concluded, then, that the ES supported the reduction of subjectivity in the classification of the criticality of software version.

On the Suitability of Vibration Acceptance Criteria of Process Pipework

The risk of vibration-induced fatigue in process pipework is usually assessed through vibration measurements. For small-bore pipework, integrity personnel would measure the vibration of the pipework and refer to widely used charts to quantify the risk of vibration-induced fatigue. If the vibration levels are classified as OK, no action is required on behalf of the operators. However, if it is a CONCERN or PROBLEM vibration level, strain measurements are required to adequately quantify the risk through a fatigue life assessment. In this paper, we examine the suitability of a widely used vibration acceptance criteria through finite element models. A total of 4,800 models are used to study the suitability of this vibration acceptance criteria by monitoring both the vibration and dynamic stress. The model comprises a small-bore pipe (2″ SCH 40) that is fitted on a mainline size 5″ SCH 40 using a weldolet; the length of the mainline takes three values resulting in three models. The mainline supporting conditions will be varied using translational and rotational springs. The finite element models will be excited using a point load resembling flow-induced forces (with varying flow velocity and fluid composition). These excitations are obtained from the literature and are based on experimental studies as power spectral density functions. The results show that the studied vibration acceptance criterion is suitable in 99.73% of all the studied models with 68.27% confidence level. For the models with a shorter mainline pipe, the criterial is suitable in 76.5% of the time with 68.27% confidence level.

Determination of the Uncertainties in S-Curve Logistic Fits

Look-up tables and graphs are provided for determining the uncertainties during logistic fits, on the three parameters M, α and to describing an S-curve of the form: S(t) = M/(1+exp(-α(t-t0))).The uncertainties and the associated confidence levels are given as a function of the uncertainty on the data points and the length of the historical period. Correlations between these variables are also examined; they make “what-if” games possible even before doing the fit.The study is based on some 35,000 S-curve fits on simulated data covering a variety of conditions and carried out via a χ2 minimization technique. A rule-of-thumb general result is that, given at least half of the S-curve range and a precision of better than 10% on each historical point, the uncertainty on M will be less than 20% with 90% confidence level.

Communicating Uncertainty in National Security Intelligence: Expert and Non-expert Interpretations of and Preferences for Verbal and Numeric Formats

Organizations in several domains including national security intelligence communicate judgments under uncertainty using verbal probabilities (e.g., likely) instead of numeric probabilities (e.g., 75% chance), despite research indicating that the former have variable meanings across individuals. In the intelligence domain, uncertainty is also communicated using terms such as low, moderate, or high to describe the analyst’s confidence level. However, little research has examined how intelligence professionals interpret these terms and whether they prefer them to numeric uncertainty quantifiers. In two experiments (N = 481 and 624, respectively), uncertainty communication preferences of expert (n = 41 intelligence analysts inExperiment 1) and non-expert intelligence consumers were elicited. We examined which format participants judged to be more informative and simpler to process. We further tested whether participants treated probability and confidence as independent constructs and whether participants provided coherent numeric probability translations of verbal probabilities. Results showed that whereas most non-experts favored the numeric format, experts were about equally split, and most participants in both samples regarded the numeric format as more informative.Experts and non-experts consistently conflated probability and confidence. For instance, confidence intervals inferred from verbal confidence terms had a greater effect on the location of the estimate than the width of the estimate, contrary to normative expectation. Approximately ¼ of experts and over ½ of non-experts provided incoherent numeric probability translations of best estimates and lower and upper bounds when elicitations were spaced by intervening tasks.

KARAKTERISTIK ORGANOLEPTIK DAN PROKSIMAT MIE BASAH DENGAN PENAMBAHAN TEPUNG TERIPANG PASIR (Holothuria scabra)

ABSTRACTThe purpose of this study was to determine the effect of the addition of sea cucumber flour on the organoleptic and proximate characteristics of wet noodles. This study consisted of four treatments, namely without the addition of sand sea cucumber flour (T0), the addition of 5% sea cucumber flour (T1), the addition of 10% sea cucumber flour (T2), and the addition of 15% sea cucumber flour (T3). The analyzed parameters were organoleptic and physicochemical values. This study used a completely randomized design (CRD). Data were analyzed using Analysis of Variance (ANOVA) and continued with Duncan's Multiple Range Test (DMRT) at a 95% confidence level. The results show that the effect of adding sand sea cucumber flour had a very significant effect on organoleptic assessment in T1 treatment (95% wheat flour: 5% sea cucumber flour) with preference scores of color, aroma, taste, and texture reached 4.03 (like), 4.06 (like), 3.91 (like), and 4.06 (like). Proximate analysis of the best treatment shows that it contained 50.12% water, 1.18% ash, 0.20% fat, 7.23% protein, and 41.75% carbohydrate. The results show that the product met the standard of SNI 01-2987-1992 for ash, fat, and protein contents. Keywords: Sea Cucumber, Wet NoodlesABSTRAKTujuan penelitian ini untuk menentukan pengaruh penambahan tepung teripang pasir terhadap karakteristik organoleptik dan proksimat mie basah. Penelitian ini terdiri dari empat perlakuan yaitu tanpa penambahan tepung teripang pasir (T0), penambahan tepung teripang pasir 5% (T1), penambahan tepung teripang pasir 10% (T2), dan penambahan tepung teripang pasir 15% (T3), lalu dianalisis terhadap nilai organoleptik dan fisikokimia. Penelitian ini menggunakan Rancangan Acak Lengkap (RAL). Data di analisis menggunakan Analysis of Varian (ANOVA) dan dilanjutkan dengan uji Duncan’s Multiple Range Test (DMRT) pada taraf kepercayaan 95%. Hasil penelitian menunjukkan bahwa pengaruh penambahan tepung teripang pasir berpengaruh sangat nyata terhadap penilaian organoleptik pada perlakuan T1 (tepung terigu 95% : tepung teripang pasir 5%) sebesar warna 4.03 (suka), aroma 4.06 (suka), rasa 3.91 (suka), dan tekstur 4.06 (suka). Analisis proksimat perlakuan terbaik diperoleh nilai kadar air 50.12%, kadar abu 1.18%, kadar lemak 0.20%, kadar protein 7.23% dan kadar karbohidrat 41.75%. Berdasarkan hasil penelitian nilai kadar abu, kadar lemak, dan kadar protein telah memenuhi SNI 01-2987-1992.Kata kunci: Teripang Pasir, Mie Basah

Critical Thinking and the Socratic Method

This chapter starts by answering the question, “What is critical thinking?” As it turns out, not everyone agrees on what critical thinking is. Nevertheless, researchers agree that critical thinking allows many people to reason together for solutions to complex problems. Also, in this chapter, the authors look at how computing capabilities enhance Socratic problem solving. A computer-based Socratic problem-solving system can keep problem solvers on track, document the outcome of a problem-solving session, and share those results with participants and a larger audience. In addition, Socrates DigitalTM can also help problem solvers combine evidence about their quality of reasoning for individual problem-solving steps and the overall confidence level for the solution.

Conclusions, Implications, and Viewpoints

This chapter shows how users can use Socrates DigitalTM to analyze information, identify assumptions, and apply concepts to determine conclusions. After the user determines the conclusions, the next step for users is to predict the implications of those conclusions. Predicting the implications is followed by a step where the user summarizes the conclusions and implications into a viewpoint. Afterward, the user evaluates this viewpoint, and Socrates DigitalTM presents the opportunity to create another viewpoint. After the user decides there is no more evidence to gather, Socrates DigitalTM will calculate a score that provides a confidence level in the current viewpoint for the user.