scholarly journals Pengaruh Salinitas dan Limbah Cair Tahu pada Konsentrasi yang Berbeda terhadap Pertumbuhan Mikroalga Botryococcus braunii Kutzing

2021 ◽  
Vol 6 (2) ◽  
pp. 161-166
Author(s):  
Savira Amelia Putri ◽  
Riche Hariyati ◽  
Tri Retnaningsih Soeprobowati
Keyword(s):  
Botryococcus Braunii ◽  
Total Data

Pertumbuhan mikroalga Botryococcus braunii Kutzing dipengaruhi oleh faktor lingkungan berupa salinitas, suhu, pH, oksigen terlarut (DO), intensitas cahaya dan nutrisi pada media kultivasi. Penelitian ini bertujuan untuk mengkaji pengaruh salinitas dan limbah cair tahu terhadap pertumbuhan mikroalga B. braunii. Perlakuan yang dilakukan dalam penelitian ini yaitu konsentrasi limbah cair tahu 10% dengan salinitas 15‰ (L10S15); limbah cair tahu 10% dengan salinitas 20‰ (L10S20); limbah cair tahu 10% dengan salinitas 25‰ (L10S25); limbah cair tahu 20% dengan salinitas 15‰ (L20S15); limbah cair tahu 20% dengan salinitas 20‰ (L20S20); limbah cair tahu 20% dengan salinitas 25‰ (L20S25); limbah cair tahu 30% dengan salinitas 15‰ (L30S15); limbah cair tahu 30% dengan salinitas 20‰ (L30S20); dan limbah cair tahu 30% dengan salinitas 25‰ (L30S25). Pengamatan yang dilakukan meliputi kepadatan sel dan faktor lingkungan berupa salinitas, suhu, pH, oksigen terlarut, serta kadar N dan P total. Data yang diperoleh diolah menggunakan metode analisis sidik ragam (ANOVA) yang dilanjutkan dengan uji Duncan. Hasil penelitian menunjukkan kepadatan sel tertinggi didapatkan pada perlakuan L10S25 dengan rata-rata kepadatan sel 313x104sel/ml. Secara umum, semakin tinggi limbah cair tahu yang diberikan maka kepadatan sel mikroalga akan semakin rendah.

Pengelolaan Data Terintegrasi Berdasarkan Instrumen Akreditasi Perguruan Tinggi 3.0 Menggunakan Zachman Framework

2020 ◽  
Vol 4 (6) ◽  
Author(s):  
Ardhin Primadewi ◽  
Mukhtar Hanafi
Keyword(s):  
Higher Education ◽  
Self Evaluation ◽  
The Core ◽  
Depth Analysis ◽  
Performance Report ◽  
Total Data ◽  
Zachman Framework ◽  
The Government ◽  
Data Gap ◽  
Education Performance

Higher education in Indonesia is regulated by the government with the Higher Education Accreditation (APT). In APT 3.0, Higher Education is required to be able to present performance data in the form of a Higher Education Performance Report (LKPT) as a reference in making a Self-Evaluation Report (LED). However, it is necessary to have an in-depth analysis to determine the gaps in the data required by Higher Education according to the APT 3.0 standard. The process of integrating the samples refer to the Zachman Framework (ZF). The results of this simplification that the data is available in support of APT 3.0 approximately 79% of the total data both inside and outside the core business of Higher Education and is well managed in an integrated database. The remaining 21% of the data that are not available is spread across several information systems, especially SIMMawa, SIMHumas and Cooperation, and SIMAKU. This shows that the change in accreditation standards that have been in effect since April 2019 has created a significant data gap for Higher Education. This research also produced an alternative model of integrated data management that can be used as input for Information System developers in the Higher Education scope.

Pengaruh Senyawa Merkuri Klorida (HgCl2) Terhadap Pertumbuhan dan Kandungan Pigmen Klorofil Mikroalga Botryococcus braunii

2017 ◽  
Vol 4 (2) ◽  
pp. 23
Author(s):  
Grace Simanjuntak ◽  
Desy Mantiri ◽  
Kurniati Kemer
Keyword(s):  
Botryococcus Braunii

Penelitian ini bertujuan untuk mengetahui pertumbuhan populasi Botryococcus braunii dengan pemberian senyawa merkuri klorida (HgCl2) serta untuk mengetahui konsentrasi pigmen klorofil dari ekstrak pigmen total yang telah diberi senyawa merkuri klorida (HgCl2) terhadap mikroalga Botryococcus braunii. Stok mikroalga yang digunakan diperoleh dari Pusat Penelitian Dan Pengembangan Daya Saing Produk Dan Bioteknologi Kelautan Dan Perikanan, di Jalan KS Tubun- Pertamburan VI, Slipi, Jakarta Pusat. Stok mikroalga yang telah ada dikeluarkan dari cool box (kotak pendingin). Selanjutnya stok tersebut dibuat medium yang telah diisi oleh air laut dan media conway, setelah itu diberi aerator kemudian di kulturisasi di ruang kultur bersuhu 25oC dengan penerangan lampu tabung 40 watt selama 24 jam dan dikontrol. Kulturisasi dan perlakuan senyawa merkuri klorida dilakukan di Laboratorium Biologi Molekur dan Farmasitika Laut Fakultas Perikanan dan Ilmu Kelautan, serta untuk mengetahui panjang gelombang dan kandungan pigmennya menggunakan alat spektrofotometri dilakukan di Laboratorium Farmasi  FMIPA. Berdasarkan hasil penelitian yang telah dilakuan didapatkan senyawa merkuri klorida (HgCl2) dengan konsentrasi 2 ppm mengalami penurunan jumlah sel pada hari kedelapan, jumlah selnya 1,9 sel/ml Botryococcus braunii. Artinya senyawa yang tinggi dapat menurunkan konsentrasi pigmen sehingga menghalangi terjadinya proses fotosinteisis dengan menghambat pembelahan sel.

Ultrasonic Block Compressed Sensing Imaging Reconstruction Algorithm Based on Wavelet Sparse Representation

2020 ◽  
Vol 16 (3) ◽  
pp. 262-272
Author(s):  
Guangzhi Dai ◽  
Zhiyong He ◽  
Hongwei Sun
Keyword(s):  
Compressed Sensing ◽  
Sparse Representation ◽  
Linear Array ◽  
Imaging System ◽  
Ultrasonic Imaging ◽  
Large Data ◽  
Reconstruction Algorithm ◽  
Array Transducer ◽  
Total Data ◽  
Block Compressed Sensing

Background: This study is carried out targeting the problem of slow response time and performance degradation of imaging system caused by large data of medical ultrasonic imaging. In view of the advantages of CS, it is applied to medical ultrasonic imaging to solve the above problems. Objective: Under the condition of satisfying the speed of ultrasound imaging, the quality of imaging can be further improved to provide the basis for accurate medical diagnosis. Methods: According to CS theory and the characteristics of the array ultrasonic imaging system, block compressed sensing ultrasonic imaging algorithm is proposed based on wavelet sparse representation. Results: Three kinds of observation matrices have been designed on the basis of the proposed algorithm, which can be selected to reduce the number of the linear array channels and the complexity of the ultrasonic imaging system to some extent. Conclusion: The corresponding simulation program is designed, and the result shows that this algorithm can greatly reduce the total data amount required by imaging and the number of data channels required for linear array transducer to receive data. The imaging effect has been greatly improved compared with that of the spatial frequency domain sparse algorithm.

Investigating Occupation Wise Perception of Customers Towards Access to Cooperative Banking Services

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Neetu Andotra ◽  
Tarsem Lal
Keyword(s):  
Secondary Data ◽  
Principal Component ◽  
Himachal Pradesh ◽  
Primary Data ◽  
Varimax Rotation ◽  
Banking Services ◽  
Banking Service ◽  
Total Data ◽  
Cooperative Banks ◽  
Secondary Information

The present paper aims at investigating the occupation-wise perception of customers towards access to cooperative banking services. The study is both expressive and evaluative in nature. In order to investigate the perception of customers towards access to cooperative banking services, both primary and secondary data has been collected. The primary data have been collected from 540 customers of cooperative banks operating in three northern states of India i.e J&K, Himachal Pradesh, and Punjab. The technique of factor analysis has been used through SPSS (version 17.00) with Principal Component Analysis along with varimax rotation for summarisation of the total data into minimum factors. Secondary information was collected from published sources i.e books, journals, files, cooperative bulletins, organizational reports, annual drafts of Planning and Statistical Department (Government of J&K, Himachal Pradesh, and Punjab), RBI reports, magazines, and Internet. ANOVA has been applied for data analysis. The results of the study shows that there exits significant means difference between perception of customers towards access to Cooperative banking service.

Validation of Graphoanalysis by “Global” or “Holistic” Method

1977 ◽  
Vol 44 (2) ◽  
pp. 403-410 ◽  
Author(s):  
James C. Crumbaugh ◽  
Emilie Stockholm
Keyword(s):  
Personality Assessment ◽  
Statistical Study ◽  
Handwriting Analysis ◽  
Expressive Movement ◽  
Projective Techniques ◽  
Matching Technique ◽  
Total Data ◽  
Holistic Method

Graphoanalysis is the most systematically developed and best researched of all methods of handwriting analysis (generically called graphology). This is a projective expressive movement that is neither better nor more poorly validated than most projective techniques as a means of personality assessment, which is inadequate because their subjectivity makes statistical study difficult. With all projective techniques “sign” or trait validation has been minimal, and the best validation has come from “global” or “holistic” methods. The present study presents a paradigm for the latter type of approach to handwriting analysis, using a matching technique with probabilities of 1/5, wherein five subjects were matched by people who knew them to one of five blind Graphoanalyses of the subjects' writing. This design is herein replicated five times, with total data significantly different from chance expectation ( p < .001), supporting the hypothesis that it is possible to evaluate personality through analysis of handwriting.

scholarly journals Metabolic response of Botryococcus braunii to high bicarbonate dosages and other conditions: analysis of photosynthetic performance, productivity, and lipidomic profile

2021 ◽  
Author(s):  
Néstor David Giraldo ◽  
Sandra Marcela Correa ◽  
Andrés Arbeláez ◽  
Felix L. Figueroa ◽  
Rigoberto Ríos-Estepa ◽  
...  
Keyword(s):  
Nutrient Limitation ◽  
Metabolic Response ◽  
Neutral Lipids ◽  
Biomass Productivity ◽  
Botryococcus Braunii ◽  
Photosynthetic Performance ◽  
Lipid Productivity ◽  
Cellular Growth ◽  
Adaptive Responses ◽  
Nitrogen And Phosphorus

AbstractIn this study the metabolic responses of Botryococcus braunii were analyzed upon different inorganic carbon dosages and nutrient limitation conditions in terms of lipid and biomass productivity, as well as photosynthetic performance. The nutritional schemes evaluated included different levels of sodium bicarbonate and nitrogen and phosphorus starvation, which were contrasted against standard cultures fed with CO2. Bicarbonate was found to be an advantageous carbon source since high dosages caused a significant increase in biomass and lipid productivity, in addition to an enhanced photosynthetic quantum yield and neutral lipids abundance. This contrasts to the commonly used approach of microalgae nutrient limitation, which leads to high lipid accumulation at the expense of impaired cellular growth, causing a decline in overall lipid productivity. The lipidome analysis served to hypothesize about the influence of the nutritional context on B. braunii structural and storage lipid metabolism, besides the adaptive responses exhibited by cells that underwent nutrient stress.

scholarly journals Large-scale screening of natural genetic resource in the hydrocarbon-producing microalga Botrycoccus braunii identified novel fast-growing strains

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Koji Kawamura ◽  
Suzune Nishikawa ◽  
Kotaro Hirano ◽  
Ardianor Ardianor ◽  
Rudy Agung Nugroho ◽  
...  
Keyword(s):  
Large Scale ◽  
Biomass Productivity ◽  
Botryococcus Braunii ◽  
Algal Biofuel ◽  
Fast Growing ◽  
Wild Strains ◽  
Glass Tubes ◽  
The Tropics ◽  
Large Scale Screening ◽  
Hydrocarbon Productivity

AbstractAlgal biofuel research aims to make a renewable, carbon–neutral biofuel by using oil-producing microalgae. The freshwater microalga Botryococcus braunii has received much attention due to its ability to accumulate large amounts of petroleum-like hydrocarbons but suffers from slow growth. We performed a large-scale screening of fast-growing strains with 180 strains isolated from 22 ponds located in a wide geographic range from the tropics to cool-temperate. A fast-growing strain, Showa, which recorded the highest productivities of algal hydrocarbons to date, was used as a benchmark. The initial screening was performed by monitoring optical densities in glass tubes and identified 9 wild strains with faster or equivalent growth rates to Showa. The biomass-based assessments showed that biomass and hydrocarbon productivities of these strains were 12–37% and 11–88% higher than that of Showa, respectively. One strain, OIT-678 established a new record of the fastest growth rate in the race B strains with a doubling time of 1.2 days. The OIT-678 had 36% higher biomass productivity, 34% higher hydrocarbon productivity, and 20% higher biomass density than Showa at the same cultivation conditions, suggesting the potential of the new strain to break the record for the highest productivities of hydrocarbons.

scholarly journals Association between CYP3A5 Polymorphism and Statin-Induced Adverse Events: A Systemic Review and Meta-Analysis

2021 ◽  
Vol 11 (7) ◽  
pp. 677
Author(s):  
Jeong Yee ◽  
Hamin Kim ◽  
Yunhee Heo ◽  
Ha-Young Yoon ◽  
Gonjin Song ◽  
...  
Keyword(s):  
Adverse Events ◽  
Web Of Science ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Systemic Review ◽  
Event Risk ◽  
Total Data ◽  
Lipophilic Statin ◽  
The Relationship ◽  
Review Manager

Purpose: Cytochrome P450 (CYP) is involved in the metabolism of statins; CYP3A5 is the main enzyme responsible for lipophilic statin metabolism. However, the evidence of the association between CYP3A5*3 polymorphism and the risk of statin-induced adverse events remains unclear. Therefore, this study aimed to perform a systematic review and meta-analysis to investigate the relationship between the CYP3A5*3 polymorphism and the risk of statin-induced adverse events. Methods: The PubMed, Web of Science, and EMBASE databases were searched for qualified studies published until August 2020. Observational studies that included the association between statin-induced adverse events and the CYP3A5*3 polymorphism were reviewed. The odds ratios (ORs) and 95% confidence intervals (CIs) were evaluated to assess the strength of the relationship. The Mantel–Haenszel method was used to provide the pooled ORs. Heterogeneity was estimated with I2 statistics and publication bias was determined by Begg’s and Egger’s test of the funnel plot. Data analysis was performed using Review Manager (version 5.4) and R Studio (version 3.6). Results: In total, data from 8 studies involving 1614 patients were included in this meta-analysis. The CYP3A5*3 polymorphism was found to be associated with the risk of statin-induced adverse events (*3/*3 vs. *1/*1 + *1/*3: OR = 1.40, 95% CI = 1.08–1.82). For myopathy, the pooled OR was 1.30 (95% CI: 0.96–1.75). The subgroup analysis of statin-induced myopathy revealed a trend, which did not achieve statistical significance. Conclusions: This meta-analysis demonstrated that the CYP3A5*3 polymorphism affected statin-induced adverse event risk. Therefore, CYP3A5 genotyping may be useful to predict statin toxicity.

scholarly journals Comparison of predicted psychological distress among workers between artificial intelligence and psychiatrists: a cross-sectional study in Tsukuba Science City, Japan

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e046265
Author(s):  
Shotaro Doki ◽  
Shinichiro Sasahara ◽  
Daisuke Hori ◽  
Yuichi Oi ◽  
Tsukasa Takahashi ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Psychological Distress ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Explanatory Variables ◽  
The Neural Network ◽  
Significant Difference ◽  
Total Data

ObjectivesPsychological distress is a worldwide problem and a serious problem that needs to be addressed in the field of occupational health. This study aimed to use artificial intelligence (AI) to predict psychological distress among workers using sociodemographic, lifestyle and sleep factors, not subjective information such as mood and emotion, and to examine the performance of the AI models through a comparison with psychiatrists.DesignCross-sectional study.SettingWe conducted a survey on psychological distress and living conditions among workers. An AI model for predicting psychological distress was created and then the results were compared in terms of accuracy with predictions made by psychiatrists.ParticipantsAn AI model of the neural network and six psychiatrists.Primary outcomeThe accuracies of the AI model and psychiatrists for predicting psychological distress.MethodsIn total, data from 7251 workers were analysed to predict moderate and severe psychological distress. An AI model of the neural network was created and accuracy, sensitivity and specificity were calculated. Six psychiatrists used the same data as the AI model to predict psychological distress and conduct a comparison with the AI model.ResultsThe accuracies of the AI model and psychiatrists for predicting moderate psychological distress were 65.2% and 64.4%, respectively, showing no significant difference. The accuracies of the AI model and psychiatrists for predicting severe psychological distress were 89.9% and 85.5%, respectively, indicating that the AI model had significantly higher accuracy.ConclusionsA machine learning model was successfully developed to screen workers with depressed mood. The explanatory variables used for the predictions did not directly ask about mood. Therefore, this newly developed model appears to be able to predict psychological distress among workers easily, regardless of their subjective views.

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