INOVASI MODEL MITIGASI BENCANA NON STRUKTURAL BERBASIS KOMUNIKASI, INFORMASI, KOORDINASI DAN  KERJASAMA   (Innovation of Non Structural Disaster Mitigation Model based on Communication, Information, Coordination and Cooperation)

Dian Tamitiadini; Wayan Weda Asmara Dewi; Isma Adila

doi:10.21107/ilkom.v13i1.5216

INOVASI MODEL MITIGASI BENCANA NON STRUKTURAL BERBASIS KOMUNIKASI, INFORMASI, KOORDINASI DAN KERJASAMA (Innovation of Non Structural Disaster Mitigation Model based on Communication, Information, Coordination and Cooperation)

Jurnal Komunikasi ◽

10.21107/ilkom.v13i1.5216 ◽

2019 ◽

Vol 13 (1) ◽

pp. 41-52

Author(s):

Dian Tamitiadini ◽

Wayan Weda Asmara Dewi ◽

Isma Adila

Keyword(s):

Disaster Mitigation ◽

Model Based ◽

Unit Unit

ABSTRAKPenelitian ini mengusulkan bagaimana ilmu komunikasi diterapkan pada Mitigasi Bencana. Terutama, berdasarkan bagaimana Komunitas dan Komunikasi Bersinergi untuk Membuat Mitigasi Bencana Menengah, khususnya dalam Menyelesaikan Masalah Kesehatan setelah Bencana. Hasil dari penelitian ini dapat menjadi proyek percontohan untuk BNBP Indonesia dan Dinas Kesehatan,dalam menentukan sikap pemerintah untuk langkah-langkah selanjutnya dalam melindungi orangorang yang berada di wilayah Rawan terhadap bencana alam di Indonesia. Untuk mencapai tujuan penelitian, jenis penelitian yang digunakan adalah Penelitian Tindakan. Jenis Tindakan Penelitian yang digunakan dalam penelitian ini adalah penelitian tindakan partisipatif. Hasil unit unit pemetaan daerah yang terkena dampak akan menghasilkan tingkat prioritas manajemen pasca bencana Letusan Gunung Agung. Rencana aksi untuk mitigasi bencana akan dibahas dalam media komunikasi yang dibentuk secara organik, baik berdasarkan teknologi komunikasi atau media komunitas lokal, seperti Pasebaya. Program Penyelesaian Kesehatan ini mengacu pada Kerangka Utama Pencegahan Bencana SDG di Lempeng Asia Pasifik. BNPB Nasional juga berupaya untuk menerapkan Kerangka Sendai 2015-2030 tentang Mitigasi Bencana di Asia, khususnya Indonesia yang memiliki Resiko Bencana Tinggi di Asia Tenggara. Negara-negara Mengingat pentingnya program ini, semua daerah rawan bencana di Indonesia harus menerapkan program pengurangan risiko bencana berbasis masyarakat.Kata Kunci : Mitigasi Bencana, Komunikasi Bencana, Komunikasi Kesehatan, Pengurangan Risiko Bencana

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Representation, abstraction, and simple-minded sophisticates

Behavioral and Brain Sciences ◽

10.1017/s0140525x19002942 ◽

2020 ◽

Vol 43 ◽

Author(s):

Peter Dayan

Keyword(s):

Decision Theory ◽

Predictive Coding ◽

Bayesian Decision Theory ◽

Bayesian Decision ◽

Model Based ◽

Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

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Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

Microscopy and Microanalysis ◽

10.1017/s1431927600028968 ◽

2001 ◽

Vol 7 (S2) ◽

pp. 578-579

Author(s):

David W. Knowles ◽

Sophie A. Lelièvre ◽

Carlos Ortiz de Solόrzano ◽

Stephen J. Lockett ◽

Mina J. Bissell ◽

...

Keyword(s):

Image Analysis ◽

Mammary Epithelial Cells ◽

Nuclear Organization ◽

Critical Role ◽

Quantitative Model ◽

Mammary Epithelial ◽

Cell Phenotype ◽

Proliferating Cells ◽

Mitotic Apparatus ◽

Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

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