Kematian Manusia Sebagai Inspirasi Dalam Seni Grafis

Kematian adalah suatu peristiwa yang paling hebat yang pasti akan terjadi atas diri manusia, melupakan mati atau tidak mengingat mati adalah suatu sikap yang tidak bertanggungjawab dari sudut pandang Islam. Semua manusia akan menemui kematian dalam hidupnya, ini adalah suatu kenyataan yang terjadi pada manusia. Maka persiapan menghadapi kematian menjadi penting dipertimbangkan untuk mendapatkan kebahagiaan dunia dan akhirat. Dalam kesenian, pesan-pesan agama, hubungan antara seni dan religi saling jalin menjalin sepanjang sejarah kehidupan manusia. Seni selalu hadir dalam setiap peradaban Islam, seperti, masjisd Nabawi di Madinah al Munawwarah yang sangat indah, atau penyampaian melalui lukisan “Arasbaque” dan karya seni lainnya. Konsep perwujudan dengan bentuk Tengkorak dan anatomi kerangka tulang manusia sebagai simbol yang dapat mewakili ide tentang kematian manusia, dipadu dengan objek pendukung lain dimaksudkan agar ilustrasi yang ingin dicapai dapat tersampaikan pesan dan makna ke dalam karya seni grafis. Dengan menggunakan teknik cetak saring atau serigrafi dalam visualisasinya dapat mendukung atau menghasilkan perwujudan karya yang maksimal sesuai dengan cita rasa, fantasi pengalaman estetis, dan kemampuan artistik yang diinginkan. Semua yang terjadi dari proses pembuatan karya seni Tugas Akhir ini merupakan respon atau tanggapan penulis terhadap seluruh permasalahan yang penulis alami dan amati atas realita yang terjadi di lingkungan sekitar. Penulis mencoba merefleksikan pengalaman pribadi penulis ke dalam karya-karya tugas akhir ini

Additional file 2: of A quantitative evidence base for population health: applying utilization-based cluster analysis to segment a patient population

Evaluation of the number of clusters. (DOCX 612 kb

Patient-safety-related adult deaths in NHS acute hospital settings: analysis of areas of systemic service failure.

<p>Covers a 17-mo period from 1 June 2010 to 31 October 2012, during which reports of deaths were mandatory.</p

Extracts of free text from patient safety incident reports of death.

<p>Extracts of free text from patient safety incident reports of death.</p

Network of citations.

<p>The network includes 9,423 articles that received or made at least one citation. The visualization of the network was obtained through the network visualization software Gephi^® (Gephi^® Consortium, Compiegne, France). The size of each node <i>i</i> is proportional to its in-degree (i.e., the number of citations received), and the color associated with each node denotes the surgical specialty it belongs to. The network is partitioned into topological communities that are coextensive with surgical specialties (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0183332#pone.0183332.s001" target="_blank">S1 Online Supplement</a>).</p

Scientific production and citations across surgical specialties.

<p>Published and cited articles per surgical specialty (top panel). Cumulative number of published and cited articles: (a) number of published articles over time, (b) number of cited articles over time, (c) number of citations received over time by published articles.</p

Rankings of surgical specialties.

<p>(a) Ranking by citations to seed articles; (b) ranking by fraction of citations to seed articles within one year; (c) ranking by cascade size; (d) ranking by structural depth; (e) ranking by structural width. Rankings were obtained by using the medians (red lines) of the complementary cumulative distribution functions (CCDFs). In case of ties between medians, the 75^th percentiles (dotted blue lines) were used. The bottom of each panel shows results from Mann-Whitney U tests (for citations and size) and Kolmogorov-Smirnov tests (for fraction of citations, depth, and width) of independence between pairs of distributions (green color: p<0.05). For clarity, specialties are reported only as labels to the rows of the square matrix, but are equally listed as labels to the columns from left to right. (f) Sankey diagram representing the ranking of surgical specialties in terms of innovation index. Specialties are listed in the left column, with the top-ranked scoring the highest by innovation index. The height of colored bars is proportional to the number of published articles in the corresponding specialty. Levels of evidence are listed in the right column, with the top-ranked being the final implementation stage. The height of colored bars is proportional to the number of published articles at the corresponding level of evidence across all specialties. The width of the lines connecting a given specialty to a given level of evidence is proportional to the number of articles published by the specialty at that level of evidence. Green lines refer to contributions of specialties to the final stage of implementation.</p

Schematic representation of cascades and real world examples.

<p>Top panels: (a) broadcast-driven diffusion; (b) viral diffusion. In both cases, we calculated the number of citations received by the seed node, the size of the cascade, the structural depth, and the structural width of the cascade. Bottom panels: two real examples of cascades within (c) thyroidectomy and (d) cardiac surgery. For each cascade, we calculated the number of citations to seed article, the cascade size, and structural depth and width. The color of nodes denotes their distances from the seed article (red node). Links between nodes carry the color of the citing node. The size of each node is proportional to the ratio between the node’s second-step citations and first-step citations.</p

Additional file 2: of Indicators of deterioration in young adults with serious mental illness: a systematic review protocol

Full search strategy. (DOCX 45 kb

sj-pdf-1-hpq-10.1177_13591053241246933 – Supplemental material for Patients’ subjective well-being: Determinants and its usage as a metric of healthcare service quality

Supplemental material, sj-pdf-1-hpq-10.1177_13591053241246933 for Patients’ subjective well-being: Determinants and its usage as a metric of healthcare service quality by Henry A Lee, Neo Poon, Paul Dolan, Ara Darzi and Ivo Vlaev in Journal of Health Psychology</p