Pengujian Resin Berbasis Lignin Sebagai Bahan Pencegah Serangan Rayap Kayu Kering (Cryptotermes Cynocepbalus Light.)

Kayu karet dan tusam banyak digunakan sebagai bahan mebel. Kelemahan kedua kayu tersebut mudah diserang organisme Perusak kayu. Oleh karena itu perlu dilakukan pencegahan untuk meningkatkan keawetannya. Penelitian ini bertujuan untuk mendapatkan jenis bahan pencegah serangan rayap kayu kering menggunakan resin lignin formaldehida.Dalam penelitian ini resin dibuat dari 3 jenis lignin yang dihidroksimetilasi kemudian dikondensasi dengan larutan NaOH 50% dan formaldehida 37%. Reaksi dilangsungkan pada suhu 70 -80OC selama 1 jam. Nisbah mol lignin: formalin = 1 : 2. Resin tersebut diaplikasikan pada kayu karet dan tusam, masing-masing mewakili kayu daun lebar dan kayu daun jarum yang selanjutnya diuji ketahanannya terhadap serangan rayap kayu kering.Hasil penelitian menunjukkan bahwa resin berbasis lignin formaldehida yang dibuat dari ke-3 jenis lignin efektif dalam mencegah serangan rayap kayu kering pada kayu karet dan tusam dengan tingkat kematian rayap kayu kering antara 62,4 - 100,0% dan mampu meningkatkan kelas ketahanan kayu karet maupun tusam dari kelas IV (tanpa perlakuan) menjadi kelas II

The Paradox of Dynamic Corporate Identity

Dynamic Corporate Identity has brought the new perspective of designing a brand identity. Dynamic Corpo- rate identity is a system that applying the latest technology to create a flexible logo as the result the logo will constantly can change in color, pattern or shape. It is believed as the new way to create a living brand. However the new approach may not suitable for several types of businesses or identities. This research aimed to understand; what improvement that dynamic identity could do to make brand more alive. By collecting qualitative data, and some relevant literature this study has found that there is a paradox in dynamic identity system. Keywords Corporate Identity, Dyanmic Identity, Logo Desig

Penggolongan Performans 25 Jenis Rotan Indonesia Berdasarkan Kerapatan, Kekakuan, Dan Kekuatan

Rotan merupakan salah satu hasil hutan bukan kayu, dan di Indonesia berperan penting sebab memasok 80% kebutuhan bahan baku rotan dunia. Rotan banyak dimanfaatkan antara lain untuk tali, anyaman, tikar, keranjang, perabot rumah tangga, barang kerajinan, dan produk meubelar. Pemanfaatan rotan menjadi produk berguna ditentukan diantaranya oleh kerapatan, dan kekuatan (MOR) dan kekakuan (MOE), di mana semakin tinggi nilai ketiga sifat tersebut, maka semakin baik pula kualitas rotan tersebut. Di Asia Tenggara, termasuk Indonesia, terdapat 2 dari 8 genera rotan yang bernilai ekonomi tinggi, yaitu Calamus dan Daemonorops. Sebagai kaitannya, telah dilakukan pencermatan 25 jenis rotan Indonesia dan kelasifikasinya berdasarkan kerapatan, MOR, dan MOE. Dua puluh lima jenis tersebut didominasi oleh Calamus spp. dan Daemonorops spp. Penelaahan secara menyeluruh berdasarkan kerapatan, MOR, dan MOE, sebanyak 16% dari 25 jenis rotan dapat dikelompokkan sebagai kelas I (sangat baik); 36% sebagai kelas II (baik); 32% sebagai kelas III (sedang); dan 16% sebagai kelas IV (rendah). Penelahan berdasarkan keseluruhan sifat (Kerapatan, MOR, MOE) mengindikasikan 4 jenis rotan yang paling berprospek untuk dimanfaatkan (mulai dari urutan tertinggi) yaitu Korthlsia rigida Bl, Calamus inops Becc.ex Heyne, dan Calamus koordesianus Becc dan Korthalsia echinometra Becc; sedangkan yang paling tidak berprospek adalah Korthalsia zeppelii Burret, Plectocomiopsis geminiflora(Griff) Becc, dan Calamus ornatus Blume dan Daemonorops malanocaetes BL

Kernel Logistic Regression-linear for Leukemia Classification Using High Dimensional Data

Kernel Logistic Regression (KLR) is one of the statistical models that has been proposed for classification in the machine learning and data mining communities, and also one of the effective methodologies in the kernel–machine techniques. Basely, KLR is kernelized version of linear Logistic Regression (LR). Unlike LR, KLR has ability to classify data with non linear boundary and also can accommodate data with very high dimensional and very few instances. In this research, we proposed to study the use of Linear Kernel on KLR in order to increase the accuracy of Leukemia Classification. Leukemia is one of the cancer types that causes mortality in medical diagnosis problem. Improving the accuracy of Leukemia Classification is essential for more effective diagnosis and treatment of Leukemia disease. The Leukemia data sets consists of 7120 (very high dimensional) DNA micro arrays data of 72 (very few instances) patient samples on the state of Leukemia types. In Leukemia classification based upon gene expression, monitoring data using DNA micro array offer hope to achieve an objective and highly accurate classification. It can be demonstrated that the use of Linear Kernel on Kernel Logistic Regression (KLR–Linear) can improve the performance in classifying Leukemia patient samples and also can be shown that KLR–Linear has better accuracy than KLR–Polynomial and Penalized Logistic Regression

Investigation into the regulation and transfer of conjugative transposons of the Tn916-like family

The Tn916-like family of conjugative transposons are broad host range mobile genetic elements and are clinically important as they are one of the major vectors responsible for the spread of antibiotic resistance among bacterial pathogens. This study was designed to investigate the behaviour of the conjugative transposons Tn916 and Tn5397, focusing on the transcriptional regulation and transfer. The proposed regulatory system of Tn916 involves transcriptional attenuation upstream of tet(M) and is regulated by tetracycline. The translation of orf12 is central to this regulatory mechanism as it is the translating ribosome upon orf12 RNA that is hypothesised to destroy, or prevent the formation of the transcriptional terminators. This hypothesis was tested using a Bacillus subtilis construct, with a 2 bp mutation disrupting the start codon of orf12. This construct is expected to result in the transcriptional terminators being permanently formed as the ribosome will no longer translate the orf12 and destroy them. Results indicate a lower transcription of tet(M) and downstream genes which was supported by the slower growth rate of the B. subtilis mutant compared to the wild type upon challenged with tetracycline. When tetracycline is present, a reduced fitness of this mutant was observed compared to the wild type. However, the transfer frequency of the B. subtilis mutant was similar to that of the wild type. The transcription of Tn916 and Tn5397 was investigated by quantifying the expression level using reporter assays, where the Ptet(M) promoter and the open reading frames upstream of tet(M) were cloned upstream of a ß-glucuronidase gene. In the presence of tetracycline, Tn916 wild type construct was upregulated whereas the Tn5397 wild type construct showed a constant expression level. Disruption of the start codon of orf12 (Tn916) and orf26 (Tn5397) has also led to a constant expression level of ß-glucuronidase. The termination efficiency of the Tn916 terminators was estimated using promoter assays and a published algorithm. Results suggest that the large terminator is more efficient [47% (± 18)] than the small terminator [23% (± 15)], which was supported by the algorithm analysis for Tn916. Finally, reciprocal gene transfer of Tn5397 between Clostridium difficile and Enterococcus faecalis was demonstrated. The transfer frequency [± standard deviation (SD)] detected was 8.85 x 10-8 (± 2.14 x 10-7) per recipient. Tn5397 integrates into the genome of E. faecalis at a single site that is within an orf encoding the phosphotransferase (PTS) IIA component. Comparative growth curves showed that the acquisition of Tn5397 has a very small effect on the growth of E. faecalis. This work has extended the current knowledge of the regulation and transfer of conjugative transposons of the Tn916-like family. It has provided a better understanding about the mechanism of transcriptional regulation of these elements

A comprehensive review on methods for solving FACTS optimization problem in power systems.

This paper presents a comprehensive review of various methods for solution of flexible AC transmission systems (FACTS) optimization problem in power systems. First, it explains the requirements of an ideal solution for FACTS optimization problem, then classifies the methods used by researchers in four main groups as classical methods, technical methods, heuristics and mixed methods, and discusses thoroughly about characteristics, advantages and disadvantages of each group of methods. Finally, according to the pros and cons of these methods, heuristic methods are determined as the most effective group of optimizers and also some hints are offered for future researches on this area

The Tn916/Tn1545 Family of Conjugative Transposon

The conjugative transposon Tn916 was first discovered in the late 1970s and is, together with the related conjugative transposon Tn1545, the paradigm of a large family of related conjugative transposons known as the Tn916/Tn1545 family, which are found in an extremely diverse range of bacteria. With the huge increase in bacterial genomic sequence data available, due to the widespread use of next generation sequencing, more putative conjugative transposons belonging to the Tn916/Tn1545 family are being reported. Many of these are capable of excision, integration and conjugation. Nearly all of the Tn916/Tn1545‑like elements discovered to date encode tetracycline resistance however, increasingly resistance to other antimicrobials is being found. Some of the members of the Tn916/Tn1545 family of elements are composite structures which contain smaller mobile genetic elements which are also capable of transposition. Tn916/Tn1545‑like elements themselves are also found within larger and more complex elements. This review will give an overview of the current knowledge of the Tn916/Tn1545 family of conjugative transposons highlighting recently characterized composite elements carrying additional and novel resistance genes

Prediction of player position for talent identification in association netball: a regression-based approach

Among the challenges in industrial revolutions, 4.0 is managing organizations’ talents, especially to ensure the right person for the position can be selected. This study is set to introduce a predictive approach for talent identification in the sport of netball using individual player qualities in terms of physical fitness, mental capacity, and technical skills. A data mining approach is proposed using three data mining algorithms, which are Decision Tree (DT), Neural Network (NN), and Linear Regressions (LR). All the models are then compared based on the Relative Absolute Error (RAE), Mean Absolute Error (MAE), Relative Square Error (RSE), Root Mean Square Error (RMSE), Coefficient of Determination (R2), and Relative Square Error (RSE). The findings are presented and discussed in light of early talent spotting and selection. Generally, LR has the best performance in terms of MAE and RMSE as it has the lowest values among the three models

Treatment of wastewater using response surface methodology: a brief review

Response surface methodology (RSM) is widely applied to gathering knowledge on the interactions among parameters that require optimization during the treatment of wastewater. It can be used to optimize parameters during the process of treating wastewater, e.g., landfill leachate. The experimental design methods are useful to evaluate the parameters involved in a treatment with the minimum number of experiments. This will reduce the need for reagents and materials for experiments, which finally causes both time and expense to be increased. Anaerobic digestion of wastewater technologies escalated depending on the design configuration of the reactor. Several important parameters are taken into consideration in designing an anaerobic reactor such as operating conditions, seed sludge, wastewater composition and mixing. To construct a highly efficient degradation system, it is necessary to optimize such effective parameters. As a result, the advanced statistical design is used for process characterization, optimization and modelling. In this paper, the fundamentals of RSM and its application in the anaerobic treatment of wastewater was discussed in brief. The various works done in an anaerobic reactor using RSM for prediction and optimization are given

Factors Affecting Current Ratings for Underground and Air Cables

The aim of this paper is to present a parametric study to determine the major factors that influence the calculations of current rating for both air and underground cables. The current carrying capability of the power cables rely largely on the installation conditions and material properties. In this work, the influences on ampacity of conductor size, soil thermal resistivity and ambient soil temperature for underground installations are shown. The influences on the current-carrying capacity of solar heating (time of day effects and intensity of solar radiation), ambient air temperature and cable size for cables air are also presented. IEC and IEEE standards are taken as reference