Спектральные характеристики и перенос энергии Ce-=SUP=-3+-=/SUP=-->Tb-=SUP=-3+-=/SUP=-->Eu-=SUP=-3+-=/SUP=- в соединении LuBO-=SUB=-3-=/SUB=-(Ce, Tb, Eu)

The structure, IR, luminescence, and luminescence excitation spectra of Ce3+, Tb3+, and Eu3+ ions in Lu1−2xCexEuхBO3 and Lu0.91−2xCexTb0.09EuхBO3 solid solutions were studied. The minimum "threshold" distance between Ce3+ and Eu3+ ions was estimated, at which there is no charge transfer between these ions, leading to the quenching of Ce3+ and Eu3+ luminescence. It is shown that in Lu0.91−2xCexTb0.09EuхBO3 compounds, the range of Ce and Eu concentrations of 0.2 – 0.25 at. % is optimal for obtaining the maximum luminous intensity of this compound.

Pelaksanaan Sistem Pemerintahan Presidensial Dengan Multi Partai Di Indonesia

The government system in post-reform Indonesia is a presidential system with many parties. The advantage of this system is that it is more democratic because many parties are considered to accommodate the wishes and interests of people from various backgrounds through political parties, while the weakness is that it is difficult for the ruling party if it is not in the majority. The purpose of this study was to determine the implementation of a presidential system of multi-party governance in post-reform Indonesia. The results of the study are that in a presidential government system with many parties (multi-party system) such as in Indonesia, it will cause problems if no political party wins the election with a majority vote, the President must build a coalition with a number of political parties that have representatives in the House of Representatives (DPR). DPR). Since the holding of the 1999 and 2004 elections, there have been efforts to simplify political parties, by reducing the number of election participants through the electoral threshold and then changing since 2009 to reducing the number of political parties that may sit in parliament by using the minimum threshold requirement (parliamentary threshold). However, this method has not been successful because there are still relatively many political parties sitting in parliament, this is due to the parliamentary threshold that is too small. Ideally, the parliamentary threshold, which was previously 4% in the 2019 election, is raised to 8% in the 2024 election. Thus, a strong, effective and stable presidential government system with only 4 (four) to 6 (six) political parties will be realized.

A novel temporal frequent subgraph based mining algorithm using spark

Generally, big interaction networks keep the interaction records of actors over a certain period. With the rapid increase of these networks users, the demand for frequent subgraph mining on a large database is more and more intense. However, most of the existing studies of frequent subgraphs have not considered the temporal information of the graph. To fill this research gap, this article presents a novel temporal frequent subgraph-based mining algorithm (TFSBMA) using spark. TFSBMA employs frequent subgraph mining with a minimum threshold in a spark environment. The proposed algorithm attempts to analyze the temporal frequent subgraph (TFS) using a Frequent Subgraph Mining Based Using Spark (FSMBUS) method with a minimum support threshold and evaluate its frequency in temporal manner. Furthermore, based on the FSMBUS results, the study also tries to compute TFS using an incremental update strategy. Experimental results show that the proposed algorithm can accurately and efficiently compute all the TFS with corresponding frequencies. In addition, we applied the proposed algorithm on a real-world dataset having artificial time information that confirms the practical usability of the proposed algorithm.

Minimum threshold determination method based on dataset characteristics in association rule mining

Association rule mining is a technique that is widely used in data mining. This technique is used to identify interesting relationships between sets of items in a dataset and predict associative behavior for new data. Before the rule is formed, it must be determined in advance which items will be involved or called the frequent itemset. In this step, a threshold is used to eliminate items excluded in the frequent itemset which is also known as the minimum support. Furthermore, the threshold provides an important role in determining the number of rules generated. However, setting the wrong threshold leads to the failure of the association rule mining to obtain rules. Currently, user determines the minimum support value randomly. This leads to a challenge that becomes worse for a user that is ignorant of the dataset characteristics. It causes a lot of memory and time consumption. This is because the rule formation process is repeated until it finds the desired number of rules. The value of minimum support in the adaptive support model is determined based on the average and total number of items in each transaction, as well as their support values. Furthermore, the proposed method also uses certain criteria as thresholds, therefore, the resulting rules are in accordance with user needs. The minimum support value in the proposed method is obtained from the average utility value divided by the total existing transactions. Experiments were carried out on 8 specific datasets to determine the association rules using different dataset characteristics. The trial of the proposed adaptive support method uses 2 basic algorithms in the association rule, namely Apriori and Fpgrowth. The test is carried out repeatedly to determine the highest and lowest minimum support values. The result showed that 6 out of 8 datasets produced minimum and maximum support values for the apriori and fpgrowth algorithms. This means that the value of the proposed adaptive support has the ability to generate a rule when viewed from the quality as adaptive support produces at a lift ratio value of > 1. The dataset characteristics obtained from the experimental results can be used as a factor to determine the minimum threshold value.

Birth outcomes for medically high-risk pregnancies: comparing group to individual prenatal care

Objective(s): Group prenatal care models were initially designed for women with medically low risk pregnancies, and early outcome data focused on these patient populations. Pregnancy outcome data for women with medically high-risk pregnancies participating in group prenatal care is needed to guide clinical practice. This study compares rates of preterm birth, low birthweight, and neonatal intensive care unit admissions among women with medical risk for poor birth outcomes who receive group vs. individual prenatal care. Study Design: This retrospective cohort study uses vital statistics data to compare pregnancy outcomes for women from 21 obstetric practices participating in a statewide expansion project of group prenatal care. The study population for this paper included women with pregestational or gestational hypertension, pregestational or gestational diabetes, and high body mass index (BMI >45). Patients were matched using propensity scoring, and outcomes were compared using logistic regression. Two levels of treatment exposure based on group visit attendance were evaluated for women in group care: any exposure (1 or more groups) or minimum threshold (≥ 5 groups). Results: Participation in group prenatal care at either treatment exposure level was associated with a lower risk of NICU admissions (10.2% group vs 13.8% individual care, OR 0.708, p<0.001). Participating in the minimum threshold of groups (≥5 sessions) was associated with reduced risk of preterm birth (11.4% group vs. 18.4% individual care, OR 0.569, p<0.001) and NICU admissions (8.4% group vs. 15.9% individual care, OR 0.483, p<0.001). No differences in birthweight were observed. Conclusion: This study provides preliminary evidence that women who have or develop common medical conditions during pregnancy are not at greater risk for preterm birth, low birthweight, or NICU admissions if they participate in group prenatal care. Practices who routinely exclude patients with these conditions from group participation should reconsider increasing inclusivity of their groups.

Embracing the Xenophone

By interrogating the borderlands of the discipline of Chinese literature, this article argues that Chinese literary studies should recognize non-Sinitic-language literatures that engage with issues of Chineseness as proper objects of study. Prevailing frameworks in Chinese and Sinophone literary studies range from an implicit aversion to non-Sinitic-language texts to their explicit exclusion. The consequence, however, is that texts that would otherwise be considered works of Chinese literature based on their content and/or combinations of other factors are condemned to a “literary no-man's land.” By removing the minimum threshold of language for consideration in the Chinese literary tradition and permitting texts that otherwise reflect or participate in the production of discourses of Chineseness—which the author theorizes as an embrace of the xenophone—the study of Chinese literature recuperates previously excluded expressions of Chineseness and begins writing a new branch of Chinese literary history. As case in point, the author analyzes the Spanish-language Chinese literature of Chinese Peruvian American writer Siu Kam Wen, specifically, his first collection of short stories, El tramo final (The Final Stretch). From offering new ideas of what it means to be Chinese to rewriting the history of China's red legacies, Siu's work represents a needed intervention in Chinese literary studies that would otherwise be excluded owing to its language of composition.

Active Queue Management in RED Considering Critical Point on Target Queue

The basic philosophy behind RED is to prevent congestion. When the average queue length exceeds the minimum threshold, packets are randomly dropped, or the explicit congestion notification bit is marked. Since network requirements differ significantly, it is not an optimal approach to establish RED parameters with constant value. There is a new algorithm we are proposing called Critical Point on Target Queue (AQM-RED-CPTQ), provide greater congestion management over the network while also preserving the value of RED. To overcome the problem in RED without changing queue weight parameter, we have proposed few models to control the congestion by introducing range parameter with probability and control mechanism which will belong between minimum and maximum threshold. The current queue size is controlled together with average queue size. A new range variable has been introduced to improve the performance of priority queue of existing RED based algorithm which improves the overall performance of networks. For each packet, minimum and maximum threshold has been updated and dropped with probability (Pa) for a special condition. Instead of multiplicative increase and decrease the maximum probability, the scheme uses additive-increase and multiplicative-decrease. Once the AVG queue length is close to the minimum threshold value, our approach automatically sets queue parameter according to queue conditions and handles queuing delay and improve throughput. The simulated results proof that our approaches are better than RED in terms of throughput, end to end delay, packet delivery ratio and goodput.

Comparison of numerical and standard sarnat grading using the NICHD and SIBEN methods

Objective The NICHD and SIBEN assessments are adapted from the Sarnat grade, and used to determine severity of neonatal encephalopathy (NE). We compare NICHD and SIBEN methods, and their ability to define a minimum threshold associated with significant cerebral injury. Study design Between 2016 and 2019, 145 infants with NE (77-mild; 65-moderate; 3-severe) were included. NICHD and SIBEN grade and numerical scores were assigned. Kappa scores described agreement between methods, and ROC curves their ability to predict MR injury. Results Good agreement existed between grading systems (K = 0.86). SIBEN defined more infants as moderate, and less as mild, than NICHD (p < 0.001). Both numerical scores were superior to standard grades in predicting MR injury. Conclusion Despite good agreement between methods, SIBEN defines more infants as moderate NE. Both numerical scores were superior to standard grade, and comparable to each other, in defining a minimum threshold for cerebral injury. Further assessment contrasting their predictive ability for long-term outcome is required.