Concept Store #3: Art, Activism and Recuperation

Concept store is a bi-annual journal, published by Arnolfini, focusing on critical issues of contemporary art and their relationship to wider cultural, social and political contexts. While Concept Store reflects upon ideas explored within Arnolfini's artistic programme as well as future research projects, it is intended to be a critical platform in its own right, operating as a discursive space for commissioned texts, artists' contributions, interviews and other experimental forms. Published under a copyleft licenc

Hubungan Religiusitas Dengan Need for Achievement (N-Ach) Studi Pada Mahasiswa Fakultas Agama Islam Universitas Muhammadiyah Magelang

Penelitian ini bertujuan untuk Untuk mengetahui hubungan religiusitas dengan need for achievement mahasiswa Fakultas Agama Islam UMMagelang. Populasi dalam penelitian ini adalah mahasiswa Fakultas Agama Islam Universitas Muhammmadiyah Magelang yang berjumlah 332 Mahasiswa. Sampel penelitian berjumlah 42 Mahasiswa yang ditentukan dengan teknik Purposive Sampling. Metode pengumpulan data menggunakan angket. Teknik analisis data dalam penelitian ini menggunakan analisis korelasi. Hasil penelitian menunjukkan respon mahasiswa terhadap Religiusitas diperoleh data sebesar 79% atau religiusitas pada mahasiswa dalam kategori baik. Need For Achievement mahasiswa diperoleh data sebesar 71% atau Need for Achivement mahasiswa Fakultas Agama Islam dalam kategori baik. Berdasarkan analisis data secara deskriptif diketahui bahwa tidak ada hubungan antara Religiusitas dengan Need For Achievement (motivasi berprestasi)

Perbedaan Hasil Belajar Matematika Siswa antara yang Mendapatkan Model Pembelajaran Brain Based Learning dengan Numbered Head Together

The research was conducted to distinguish the two models , this is Brain Based Learning ( BBL ) with the Numbered Head Together ( NHT ) to see the extent to which the two models are instrumental in improving the learning outcomes of students learning mathematics . Authors wanted to see if there are differences in mathematics achievement between students who received Brain Based Learning ( BBL ) with Numbered Head Together ( NHT ) ? . The method that I use in this study is experimental research that is giving treatment to two different classes . The population in this study were all students class VII of SMP Negeri 1 Cikajang with a randomly selected sample of the class VII- C and class VII - D . The instrument used to measure student learning outcomes in the form mathematics objective tests , administered before and after the treatment the author gives a treat . From the analysis of the Mann Whitney test , to test initial value Zhitung = 1.72 and Ztabel = 2.24 with a significance level of 5 % ( α = 0.05 ) zhitung which is located in the reception area Ho , Ho is accepted then it means there is no difference initial ability between experimental classes experiment I and experiment II . While the results of Mann Whitney test to post test at significance level of 5 % ( α = 0.05 ) , zhitung = 3.18 using the two test sides of Zhitung value = 3.18 > Ztabel = 2.24 , in other words zhitung rejection of Ho is in the region , in other words Ha accepted . It means that there are differences in mathematics outcomes between students who received learning model with Brain Based Learning (BBL) with Numbered Head Together (NHT)

An antibody raised against a pathogenic serpin variant induces mutant-like behaviour in the wild-type protein.

A monoclonal antibody (mAb) that binds to a transient intermediate may act as a catalyst for the corresponding reaction; here we show this principle can extend on a macro-molecular scale to the induction of mutant-like oligomerisation in a wild-type protein. Using the common, pathogenic Glu342Lys (Z) variant of α1-antitrypsin as antigen - whose native state is susceptible to the formation of a proto-oligomeric intermediate - we have produced a mAb (5E3) that increases the rate of oligomerisation of the wild-type (M) variant. Employing ELISA, gel shift, thermal stability and FRET time-course experiments, we show that mAb5E3 does not bind to the native state of α1-antitrypsin, but recognises a cryptic epitope in the vicinity of the post-helix A loop and strand 4C that is revealed upon transition to the polymerisation intermediate, and which persists in the ensuing oligomer. This epitope is not shared by loop-inserted monomeric conformations. We show the increased amenity to polymerisation by either the pathogenic Glu342Lys mutation or the binding of mAb5E3 occurs without affecting energetic barrier to polymerisation. As mAb5E3 also does not alter the relative stability of the monomer to intermediate, it acts in a manner similar to the Glu342Lys mutation, by facilitating the conformational interchange between these two states

Perbedaan Kemampuan Komunikasi Matematik Siswa antara yang Mendapatkan Model Pembelajaran Jigsaw dan Cooperative Script

This research is done because a lot of students who have difficulty in understanding the concepts of mathematics.based formulation of the problem in this study , ie whether there is a difference between the students' mathematical communication skills are getting instructional model jigsaw premises cooperetive script ? . the study aims to determine differences in mathematical ability of communication between the students who get the Jigsaw cooperative learning model script. This research was conducted using a quasi-experimental. The instrument used to measure the communication skills of mathematics that is shaped in the form of a written test descriptions . Tests administered before researcher provide treatment ( pretest ) and after treatment ( posttest ) , about the same as the pretest posttest questions . Based on data from the pretest and posttest results , both normal distribution and homogeneous so that data processing followed by t-test, thus Ho is accepted . The results of this study indicate that there is no difference between the students' mathematical communication skills that get the Jigsaw cooperative learning model script

Performance Comparison of New Heuristic With Genetic Algorithm in Parallel Flow Line Set Up

A new heuristic has been developed to solve the problem in parallel flow line scheduling. It involves the minimization of the makespan by the optimal allocation of a finite number of jobs to finite number of lines in the first phase and the optimal sequencing of allocated jobs in each line in the second phase. Here new heuristic and genetic algorithm for analyzing the parallel flow line scheduling are discussed and executed on a set of randomly generated problems. The results obtained for the test problems suggest that the developed new heuristic can be used successfully to solve large scale parallel flow line scheduling problems

Enhancing the Reliability of Photovoltaic Systems in Microgrid at Campus Area

This paper assesses the reliability of photovoltaic systems within a microgrid, considering the system's operational mode and monthly data on solar radiation and load demand. The evaluation encompasses various reliability metrics, including microgrid failure rate, interruption duration, system unavailability, EENS, EIR, LOLE, and LOLP, with the objective of minimizing these parameters. The methodologies applied involve the Markov model and artificial intelligence algorithms such as Naive Bayes and Support Vector Machine (SVM). Results indicate that the microgrid exhibits enhanced reliability in an on-grid mode configuration, with a LOLP value of 0.0008. Furthermore, employing machine learning, specifically SVM, for LOLP calculation based on solar radiation yields a more precise value of 0.7245. This study offers valuable insights for policymakers and system designers in determining the optimal configuration for microgrids.This paper assesses the reliability of photovoltaic systems within a microgrid, considering the system's operational mode and monthly data on solar radiation and load demand. The evaluation encompasses various reliability metrics, including microgrid failure rate, interruption duration, system unavailability, EENS, EIR, LOLE, and LOLP, with the objective of minimizing these parameters. The methodologies applied involve the Markov model and artificial intelligence algorithms such as Naive Bayes and Support Vector Machine (SVM). Results indicate that the microgrid exhibits enhanced reliability in an on-grid mode configuration, with a LOLP value of 0.0008. Furthermore, employing machine learning, specifically SVM, for LOLP calculation based on solar radiation yields a more precise value of 0.7245. This study offers valuable insights for policymakers and system designers in determining the optimal configuration for microgrids