Relating Production Units and Alignment Units in Translation Activity Data

2010 ◽  
Keyword(s):  
Activity Data

PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE NUMBERED HEADS TOGETHER (NHT) UNTUK MENINGKATKAN HASIL BELAJAR BAHASA INDONESIA SISWA KELAS IVA SD NEGERI 78 PEKANBARU KECAMATAN TENAYAN RAYA

2017 ◽  
Vol 6 (1) ◽  
pp. 32
Author(s):  
Nismarni Nismarni
Keyword(s):  
Cooperative Learning ◽  
Learning Outcomes ◽  
Learning Model ◽  
Instructional Materials ◽  
Test Results ◽  
Activity Data ◽  
Reflection Data ◽  
Teachers And Students ◽  
Bahasa Indonesia ◽  
Daily Test

In the background backs Indonesian learning results obtained by the students is very low because the method of learning that are not relevant. Classroom action research aims to determine the implementation of cooperative learning model Numbered Heads Together (NHT) to improve learning outcomes Indonesian grade IV A SD Negeri 78 Pekanbaru on instructional materials do. The experiment was conducted in two cycles each cycle two meetings and one daily tests. Each cycle stages are: planning, implementation, observation and reflection. Data from the activity of teachers and students in the can from the observation sheet, while, learning outcomes in getting the daily test results. The results showed the activities of teachers and students has increased, in the first cycle of meetings I obtained a score of 33 (68.75%), in the first cycle of meetings II obtained a score of 38 (79.17%), the second cycle of meetings I obtained a score of 40 (83 , 33%), and the second cycle II meeting obtained a score of 44 (91.67%). And in the first cycle of the first meeting of student activity data obtained a score of 27 (56.25%), in the first cycle II meeting increased with the acquisition of a score of 36 (75.00%), and the second cycle first meeting increased to 41 (85.42 %), the second cycle II meeting increased to 45 (93.75%). Learning outcomes of students has increased, this is evidenced by: the preliminary data the number of students who reach KKM amounted to 10 students (28.57%) with an average of learning outcomes at 65.37. Increased in the first cycle by the number of students who completed totaling 26 students (74.28%) with an average of learning outcomes at 76.00. And the second cycle increases with the number of students 32 students (91.42%) with an average of learning outcomes at 86.86. Based on these results it can be concluded that the implementation of cooperative learning model NHT can improve learning outcomes Indonesian grade IV A SD Negeri 78 Pekanbaru. 

Truck Weight Enforcement Measures of Effectiveness: Development and Software Application

1998 ◽  
Vol 1643 (1) ◽  
pp. 152-160 ◽  
Author(s):  
F. R. Hanscom ◽  
M. W. Goelzer
Keyword(s):  
Software Tool ◽  
Field Evaluation ◽  
Seasonal Effects ◽  
Data Sets ◽  
Activity Data ◽  
Software Application ◽  
Enforcement Effort ◽  
Measures Of Effectiveness ◽  
Truck Weight ◽  
Enforcement Activity

A software tool was developed to determine what is accomplished as the result of truck weight enforcement efforts. Traditionally applied measures (e.g., numbers of trucks weighed and citations issued) have simply provided indications of enforcement effort. These previously applied measures failed to provide results in terms of real enforcement objectives, such as deterring overweight trucks and minimizing pavement wear and tear. Consequently the need exists to develop and validate truck weight enforcement measures of effectiveness (MOE). MOEs were developed via a series of analytical procedures. They were subsequently validated in a comprehensive four-state field evaluation. Matched (weigh-in-motion) (WIM) data sets, collected under controlled baseline and enforcement conditions, were analyzed to determine the sensitivity of candidate MOEs to actual enforcement activity. Data collection conditions were controlled in order to avoid contamination from hour-of-day, day-of-week, and seasonal effects. The following MOEs, were validated on the basis of their demonstrated sensitivity to truck weight enforcement objectives and the presence of enforcement activity: (1) severity of overweight violations, (2) proportion of overweight trucks, (3) average equivalent single-axle load (ESAL), (4) excess ESALs, and (5) bridge formula violations. These measures are sensitive to legal load-limit compliance objectives of truck weight enforcement procedures as well as the potential for overweight trucks to produce pavement deterioration. The software User Guide that statistically compares calculated MOEs between observed enforcement conditions is described in this paper. The User Guide also allows users to conduct an automated pavement design life analysis estimating, the theoretical pavement-life effect resulting from the observed enforcement activity.

QSAR Analysis of Selected Antimicrobial Structures Belonging to Nitro-derivatives of Heterocyclic Compounds

2020 ◽  
Vol 17 (2) ◽  
pp. 214-225 ◽  
Author(s):  
Piotr Kawczak ◽  
Leszek Bober ◽  
Tomasz Bączek
Keyword(s):  
Antimicrobial Activity ◽  
Heterocyclic Compounds ◽  
Molecular Descriptors ◽  
Microbiological Activity ◽  
Activity Data ◽  
Qsar Analysis ◽  
Qsar Models ◽  
Nitro Derivatives ◽  
Semi Empirical ◽  
Derivatives Of

Background: Nitro-derivatives of heterocyclic compounds were used as active agents against pathogenic microorganisms. A set of 4- and 5-nitroimidazole derivatives exhibiting antimicrobial activity was analyzed with the use of Quantitative Structure-Activity Relationships (QSAR) method. The study included compounds used both in documented treatment and those described as experimental. Objective: The purpose of this study was to demonstrate the common and differentiating characteristics of the above-mentioned chemical compounds alike physicochemically as well as pharmacologically based on the quantum chemical calculations and microbiological activity data. Methods: During the study PCA and MLR analysis were performed, as the types of proposed chemometric approach. The semi-empirical and ab initio level of in silico molecular modeling was performed for calculations of molecular descriptors. Results: QSAR models were proposed based on chosen descriptors. The relationship between the nitro-derivatives structure and microbiological activity data was able to class and describe the antimicrobial activity with the use of statistically significant molecular descriptors. Conclusion: The applied chemometric approaches revealed the influential features of the tested structures responsible for the antimicrobial activity of studied nitro-derivatives.

Evaluation of Chemotherapeutic Activity of the Selected Bases’ Analogues of Nucleic Acids Supported by ab initio Various Quantum Chemical Calculations

2020 ◽  
Vol 16 (2) ◽  
pp. 93-103 ◽  
Author(s):  
Piotr Kawczak ◽  
Leszek Bober ◽  
Tomasz Bączek
Keyword(s):  
Biological Activity ◽  
Nucleic Acids ◽  
Ab Initio ◽  
Quantum Chemical Calculations ◽  
Quantum Chemical ◽  
Structural Parameters ◽  
Principal Component ◽  
Polarizable Continuum Model ◽  
Activity Data ◽  
Qsar Models

Background: Pharmacological and physicochemical classification of bases’ selected analogues of nucleic acids is proposed in the study. Objective: Structural parameters received by the PCM (Polarizable Continuum Model) with several types of calculation methods for the structures in vacuo and in the aquatic environment together with the huge set of extra molecular descriptors obtained by the professional software and literature values of biological activity were used to search the relationships. Methods: Principal Component Analysis (PCA) together with Factor Analysis (FA) and Multiple Linear Regressions (MLR) as the types of the chemometric approach based on semi-empirical ab initio molecular modeling studies were performed. Results: The equations with statistically significant descriptors were proposed to demonstrate both the common and differentiating characteristics of the bases' analogues of nucleic acids based on the quantum chemical calculations and biological activity data. Conclusion: The obtained QSAR models can be used for predicting and explaining the activity of studied molecules.

Kinetic Behaviour of Amylase According to pH: A New Perspective for Starch Hydrolysis Process

2020 ◽  
Vol 16 (2) ◽  
pp. 135-144
Author(s):  
Ravneet K. Grewal ◽  
Baldeep Kaur ◽  
Gagandeep Kaur
Keyword(s):  
Metal Ions ◽  
Competitive Inhibition ◽  
Deae Cellulose ◽  
Kinetic Studies ◽  
Cost Effective ◽  
Starch Hydrolysis ◽  
Divalent Metal Ions ◽  
Activity Data ◽  
Time Saving ◽  
Alkaline Conditions

Background: Amylases are the most widely used biocatalysts in starch saccharification and detergent industries. However, commercially available amylases have few limitations viz. limited activity at low or high pH and Ca2+ dependency. Objective: The quest for exploiting amylase for diverse applications to improve the industrial processes in terms of efficiency and feasibility led us to investigate the kinetics of amylase in the presence of metal ions as a function of pH. Methods: The crude extract from soil fungal isolate cultures is subjected to salt precipitation, dialysis and DEAE cellulose chromatography followed by amylase extraction and is incubated with divalent metal ions (i.e., Ca2+, Fe2+, Cu2+, and Hg2+); Michaelis-Menton constant (Km), and maximum reaction velocity (Vmax) are calculated by plotting the activity data obtained in the absence and presence of ions, as a function of substrate concentration in Lineweaver-Burk Plot. Results: Kinetic studies reveal that amylase is inhibited un-competitively at 5mM Cu2+ at pH 4.5 and 7.5, but non-competitively at pH 9.5. Non-competitive inhibition of amylase catalyzed starch hydrolysis is observed with 5mM Hg2+ at pH 9.5, which changes to mixed inhibition at pH 4.5 and 7.5. At pH 4.5, Ca2+ induces K- and V-type activation of amylase catalyzed starch hydrolysis; however, the enzyme has V-type activation at 7mM Ca2+ under alkaline conditions. Also, K- and V-type of activation of amylase is observed in the presence of 7mM Fe2+ at pH 4.5 and 9.5. Conclusion: These findings suggest that divalent ions modulation of amylase is pH dependent. Furthermore, a time-saving and cost-effective solution is proposed to overcome the challenges of the existing methodology of starch hydrolysis in starch and detergent industries.

Design, Synthesis and Antitubercular Evaluation of New Benzimidazole Scaffolds

2021 ◽  
Vol 18 (4) ◽  
pp. 375-383
Author(s):  
Smriti Yadav ◽  
Bharath Kumar Inturi ◽  
Shrinidhi B.R ◽  
Pooja H.J ◽  
Neenu Ganesh ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Cell Lines ◽  
Normal Cell ◽  
Acyl Carrier Protein ◽  
Antitubercular Activity ◽  
Resistance Mechanisms ◽  
Docking Studies ◽  
Chemical Library ◽  
Activity Data ◽  
Mycobacterium Tuberculosis H37rv

Background: To overcome one of the resistance mechanisms of Isoniazid (INH), there is a need for an antitubercular agent that can inhibit InhA enzyme by circumventing the formation of INH-NAD+ adduct. Objective: The objective of the study is the development of novel antitubercular agents that target Mycobacterium tuberculosis InhA (Enoyl Acyl Carrier Protein Reductase). Methods: A small-molecule chemical library was used for the identification of the novel InhA inhibitors using primary screening and molecular docking studies followed by the scaffold hopping approach. The designed molecules, 2-(2-(hydroxymethyl)-1H- benzo[d] imidazole-1-yl)- N- substituted acetamides were synthesized by reacting (1H- benzo[d]imidazole -2-yl)methanol with appropriate 2-chloro-N-substituted acetamides / dialkylamino carbonyl chlorides respectively in good yields (42-65%). The antitubercular activity of synthesized compounds was determined by Microplate Alamar Blue Assay (MABA) against Mycobacterium tuberculosis H37Rv strain. The selected compounds were screened for cytotoxicity on normal cell lines. Results: The antitubercular activity data revealed that the 4-chlorophenyl substituted derivative (3b) showed good MIC value at 6.25 μg/mL and, dimethylacetamide substituted derivative (3i) showed MIC at 25 μg/mL among the tested compounds. The substitution of dimethylacetamide (3i) group on the 1st position of benzimidazole has good antitubercular activity (25μg/mL) in comparison to the diethyl acetamide group (3j, 100μg/mL). Conclusion: The antitubercular activity data indicated that the tested compounds exhibited well to moderate inhibition of the H37Rv strains. The compounds (3b) with electronegative substitution on the phenyl moiety exhibited better antitubercular activity than that of the other substitutions. The active compounds have displayed a good safety profile on normal cell lines.

Penerapan Model Pembelajaran Kooperatif Tipe STAD untuk Meningkatkan Hasil Belajar Siswa pada Penentuan Sifat Larutan Asam – Basa dan Derajat Keasaman (Ph) Larutan di Kelas XI IPA SMAN 2 Tanjung Jabung Timur

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Nurasiah Nurasiah
Keyword(s):  
Learning Outcomes ◽  
Learning Process ◽  
Descriptive Analysis ◽  
Observation Data ◽  
Activity Data ◽  
Student Activities ◽  
Average Value ◽  
Base Solution ◽  
Student Questionnaire ◽  
Motivation And Learning

The purpose of this study was to improve students' motivation and learning outcomes of students of class XI IPA SMAN 2 Tanjung Jabung Timur. The classroom action research was conducted in the second semester of the academic year 2013-2014 in period of January until March, as much as four times the meetings which were divided into two cycles. Each cycle was performed twice meetings and one evaluation. The subjects of the study were the  students of class XI IPA 1. To measure students' motivation and learning outcome used student’s activity data during the learning process with guidance observation data, questionnaire data and achievement test data. Then these data were analysed using descriptive analysis method. In the first cycle shows the percentage of student activities, at the first meeting and the second meeting of 45, 71% and 74, 28%. While in the second cycle, the first meeting and the second meeting of 88, 57% and 94, 28%. The Increasing of learning outcomes in the first cycle was shown learning mastery of 59, 38% with an average value of 70, 17. Whereas in second cycle was shown learning mastery of 87,50% with an  average value of 82,76. In addition, the student’s responses are positive towards learning process by implementation of cooperative learning (model STAD) in determination of acid-base solution properties and acidity of solution using natural indicators. It is based on student questionnaire answers which feel happy or satisfied (agree) was 86, 89%. Keywords: Learning outcomes, Learning activities, STAD model, Natural indicators, Learning mastery

Neurochemistry of L-Glutamate Transport in the CNS: A Review of Thirty Years of Progress

2001 ◽  
Vol 66 (9) ◽  
pp. 1315-1340 ◽  
Author(s):  
Vladimir J. Balcar ◽  
Akiko Takamoto ◽  
Yukio Yoneda
Keyword(s):  
Molecular Biology ◽  
Glutamate Transport ◽  
Mammalian Brain ◽  
Activity Data ◽  
System A ◽  
Recent Developments ◽  
The Central Nervous System ◽  
Health And Disease ◽  
Disease Analysis

The review highlights the landmark studies leading from the discovery and initial characterization of the Na+-dependent "high affinity" uptake in the mammalian brain to the cloning of individual transporters and the subsequent expansion of the field into the realm of molecular biology. When the data and hypotheses from 1970's are confronted with the recent developments in the field, we can conclude that the suggestions made nearly thirty years ago were essentially correct: the uptake, mediated by an active transport into neurons and glial cells, serves to control the extracellular concentrations of L-glutamate and prevents the neurotoxicity. The modern techniques of molecular biology may have provided additional data on the nature and location of the transporters but the classical neurochemical approach, using structural analogues of glutamate designed as specific inhibitors or substrates for glutamate transport, has been crucial for the investigations of particular roles that glutamate transport might play in health and disease. Analysis of recent structure/activity data presented in this review has yielded a novel insight into the pharmacological characteristics of L-glutamate transport, suggesting existence of additional heterogeneity in the system, beyond that so far discovered by molecular genetics. More compounds that specifically interact with individual glutamate transporters are urgently needed for more detailed investigations of neurochemical characteristics of glutamatergic transport and its integration into the glutamatergic synapses in the central nervous system. A review with 162 references.

scholarly journals Deep Convolutional Neural Network with RNNs for Complex Activity Recognition Using Wrist-Worn Wearable Sensor Data

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1685
Author(s):  
Sakorn Mekruksavanich ◽  
Anuchit Jitpattanakul
Keyword(s):  
Neural Networks ◽  
Activity Recognition ◽  
Human Activities ◽  
Recognition Performance ◽  
Confusion Matrix ◽  
Experimental Studies ◽  
Industrial Applications ◽  
Sensor Data ◽  
Complex Activity ◽  
Activity Data

Sensor-based human activity recognition (S-HAR) has become an important and high-impact topic of research within human-centered computing. In the last decade, successful applications of S-HAR have been presented through fruitful academic research and industrial applications, including for healthcare monitoring, smart home controlling, and daily sport tracking. However, the growing requirements of many current applications for recognizing complex human activities (CHA) have begun to attract the attention of the HAR research field when compared with simple human activities (SHA). S-HAR has shown that deep learning (DL), a type of machine learning based on complicated artificial neural networks, has a significant degree of recognition efficiency. Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are two different types of DL methods that have been successfully applied to the S-HAR challenge in recent years. In this paper, we focused on four RNN-based DL models (LSTMs, BiLSTMs, GRUs, and BiGRUs) that performed complex activity recognition tasks. The efficiency of four hybrid DL models that combine convolutional layers with the efficient RNN-based models was also studied. Experimental studies on the UTwente dataset demonstrated that the suggested hybrid RNN-based models achieved a high level of recognition performance along with a variety of performance indicators, including accuracy, F1-score, and confusion matrix. The experimental results show that the hybrid DL model called CNN-BiGRU outperformed the other DL models with a high accuracy of 98.89% when using only complex activity data. Moreover, the CNN-BiGRU model also achieved the highest recognition performance in other scenarios (99.44% by using only simple activity data and 98.78% with a combination of simple and complex activities).

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