As a country surrounded by the ocean, Indonesia is categorized as a country that has marine potential. The fishermen communities’ economy depends on ocean. However, the fishermen communities live below the poverty line and their average income is less than regional minimum wage. In conjunction with the issue, this study seeks to investigate the factors affecting the income of fishermen communities and right decision to fishermen in covering with welfare insurance in Cirebon, Indonesia. The quantitative study is designed using cross-sectional approach. The data collected by applying random sampling with open-ended questions and interview. A total of 100 fishermen’s have participated in this study. The study used some factors in measuring the fishermen community income, namely coastal environment condition, fish catching technology and location, operational capital, climate (season) condition, fishermen’s age, fishermen’s education, and fishing experience. The data are analyzed using the multinomial logistic regression model by assisting the statistical software, i.e., SPSS-23. The results show that coastal environment condition, fish catching technology and location, operational capital, climate (season) condition, fishermen’s age, fishermen’s education, and fishing experience have significant effects on fishermen income. Interestingly, the factor of coastal environment condition and climate (season) condition have significant negative effects on fishermen income. In conclusion, this study identified that two important factors reduced the welfare level of fishermen (via income). Also, in line with that things, the right decision which can provide to support and assist the fishermen community was by providing the welfare insurance. It is purposely to give them the protection from various risks faced by fishermen.

In a decision-making environment related to risk, there are four basic circumstances, namely certainty, risk, uncertainty and conflict. The dynamics of the strategic environment in Southeast Asia cannot be separated from the movement of the development of the Islamic State (IS). The terror threat in Southeast Asia is currently divided into different generations of terror, namely the threat of the Al-Qaeda terror network and the threat of the ISIS terror network. This study aims to analyze and identify the risk value of the development of the Islamic State network in Southeast Asia using the Borda and TOPSIS methods. The Borda method is used to give weight to the criteria related to risk analysis. The TOPSIS method is used to provide a criteria-based risk score. This research is limited to the Southeast Asia region with 4 (four) major countries, namely Indonesia, Malaysia, Thailand, and the Philippines. This research is expected to contribute to control the development of Islamic state networks in the Southeast Asian region. Based on the results of the overall risk analysis, it was found that the Philippines has the highest risk factor value for Islamic State (IS) with a value of 0.550 at level 4 in the High category. Indonesia maintains a risk factor value of 0.307. Thailand has a risk factor value of 0.427. Indonesia and Thailand are at level 3 with the Medium category. Meanwhile, Malaysia has a risk factor value of 0.203 at level 2 in the Low category.

Bidding strategy is an important part of a negotiation strategy in automated multi-issue negotiations. In order to present good offers, which help maximize the agent’s utility, we need to search the outcome space and find appropriate bids. Bid search can become challenging in large outcome spaces with more than ten thousands of possible bids. The traditional search methods such as exhaustive or binary search are not efficient enough to find the right bids in a large space. This is mostly due to the high number of issues, high number of possible values for each issue, and increased time complexity of usual search methods. In this paper, we investigate the potential of using meta-heuristic methods for optimizing bid search in large outcome spaces. We apply some of the most popular meta-heuristic algorithms for bid search in bidding strategy of baseline negotiating agents and evaluate their impacts on negotiation performance in different negotiation domains. The evaluation results obtained through comprehensive experiments show how meta-heuristic algorithms can help improve bid search capability and consequently negotiation performance of the agents on different performance criteria. In addition, we show which search algorithm is most suitable for improving any particular performance criterion.

Indole is a hazardous substance existing in the curl oil, which released to the environment by various industrial activities; thus, decreasing its ratio from nature seems to be essential. In this study, a facial pathway for loading Cu(II) particles on MCM-41 mesoporous material was introduced as an efficient catalyst for indole oxidation. The obtained catalyst was characterized by XRD, FESEM, EDS, TEM and BET/BJH techniques. Based on Taguchi method, indole oxidation via prepared catalyst at mild condition was evaluated. By applying this method, the operating factors including Indole initial concentration (mg/L), pH value and the mass of catalyst (g) were optimized. It was found that pH plays the most crucial role in indole oxidation, on the other word, in alkaline environment; indole oxidation was happened with higher yield.

The regioselectivity of the [3+2] cycloaddition reactions between benzonitrile N-oxide as three-atom component and two series of para-substituted β-nitrostyrene analogues was analysed in the framework of
a Molecular Electron Density Theory. All of the considered processes were found to be initiated by the attack of the most nucleophilic oxygen atom in the benzonitrile N-oxide on the most electrophilic carbon atom (C_α) in the nitroalkenes. This type of interaction favours the formation of 4-nitro-substituted
Δ²-isoxazolines.

New series of mononuclear octahedral Ru(III) complexes of general formula [RuL^1-3Cl]Cl₂ (1-3) where L = dianion of Schiff bases namely: 2,2'-(((1E,1'E)-thiophene-2,5-diylbis(methaneylylidene))bis(azaneylylidene))diphenol (H₂L¹), 2,2'-(((1E,1'E)-thiophene-2,5-diylbis(methaneylylidene))bis(azaneylylidene))dibenzenethiol (H2L2) and 2,2'-(((1E,1'E)-thiophene-2,5-diylbis(methaneylyli-dene))bis(azaneylyli-dene))-dibenzoic acid (H₂L³), respectively are synthesized and characterized by different physico-chemical techniques. The results of interaction of complexes with CT-DNA supported that, the Ru (III) complexes bind to DNA via an intercalative mode. The interaction has also been investigated by gel electrophoresis. Interestingly, it was found that all Ru(III) complexes cleave super coiled (SC) pUC19 plasmid DNA efficiently in the absence of an external agent. Further, the antiproliferative activity of the complexes on Human Cervical Cancer Cells (HeLa) and Human Breast Cancer Cells (MCF-7) were evaluated by MTT assay, which revealed that, all the complexes showed more intense inhibition against HeLa and MCF-7 cell lines, particularly Ru(III) complex (3) attenuated the strongest proliferation, allowing its use as chemotherapeutic agent for cancer treatment.

Patient Bed Assignment (PBA) consists of assigning patients to hospital beds according to specific requirements such as patient diagnosis, equipment requirements, age and gender policies, among others. We worked in conjunction with the Hospital Universitario San Ignacio (HUSI) with the goal of designing an application to support decision-making during the bed assignment process. We introduced a mathematical model for the PBA. We used Analytic Hierarchy Process (AHP) to determine the weights attributed to each part of the objective function. Due to the long execution time required, we used a Greedy Algorithm and Tabu Search (TS) to optimize the match between the patient’s requirements and the characteristics of the assigned bed. To test the algorithms, we created 15 test instances of various sizes. The results showed that the gap between the value of the objective function resulting from using the Greedy/TS in comparison with the optimal solution is on average 6.2%. Also, the TS takes 84% less time than the MILP for medium and large instances. We collected data from real life instances and compared the actual method with the designed metaheuristic. On average, the value of the objective function resulting from using the proposed Greedy/Tabu algorithm is 8.6% higher.

A new series of 4-amino-4H-1,2,4-triazole derivatives, 3a-f and 5a-f were synthesized by using various aryl aldehydes and ketones. FT-IR, ¹H NMR, ¹³C NMR and mass spectral studies were characteristic of the synthesized compounds. These new compounds were screened in male wistar rats and compared with the standard drug for their anticonvulsant activity against maximal electroshock seizure (MES) model. Compounds 3b and 5d of this sequence were found to be the most active. The same compound did not demonstrate neurotoxicity at the administered maximum dose (100 mg / kg) and these compounds showed good protection compared to other compounds.

Machine vision systems are among the novel tools proven to be useful in different applications, among which monitoring and controlling manufacturing processes is one of the most important ones. However, due to the complexity resulted from high-dimensional image data and their inherent correlations, the acquisition of traditional statistical process control tools seems inapplicable. To overcome the shortcomings of the traditional methods in this regard, a statistical model is proposed in this paper which utilizes the concepts of both the PCA-based T2 control chart and the classification methods to develop a tool capable of controlling an image-based process. By defining the warning zones, collected data taken from an image-based process are classified into more than the two classes related to in-control and out-of-control processes. This helps practitioners to define rules to make it easier to realize when the process is getting out of control. Through simulation, the accuracy performance and the speed of four different types of classifiers including linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), kth nearest neighbors (KNN), and support vector machine (SVM) are assessed in different scenarios, based on which the functionality of the proposed approach is evaluated in in-control and out-of-control conditions.

A synthesis of 2-amino-4-(R)-7,7-dimethyl-5-oxo-5,6,7,8-tetrahydro-4H-chromene-3-carbonitrile derivatives (4a-l) in single flasks containing aromatic aldehydes (1a-l), malononitrile (2), and dimedone (3) by using green catalyst, extract of orange without solvent under ultrasound irradiations and reflux condition. Synthesis of 2-amino-4-(R)-7,7-dimethyl-5-oxo-5,6,7,8-tetrahydro-4H-chromene-3-carbonitrile derivatives (4a-l) show potent in-vitro anti-inflammatory activity. All synthesized compounds were characterized by FTIR, ¹H NMR, ¹³C NMR and mass spectroscopic data & elemental analysis.