Micro- and nanoscale systems have provided means to detect biological targets, such as DNA, proteins, and human cells, at ultrahigh sensitivity. However, these devices suffer from noise in the raw data, which continues to be significant as newer and devices that are more sensitive produce an increasing amount of data that needs to be analyzed. An important dimension that is often discounted in these systems is the ability to quickly process the measured data for an instant feedback. Realizing and developing algorithms for the accurate detection and classification of biological targets in realtime is vital. Toward this end, we describe a supervised machine-learning approach that records single cell events (pulses), computes useful pulse features, and classifies the future patterns into their respective types, such as cancerous/non-cancerous cells based on the training data. The approach detects cells with an accuracy of 70% from the raw data followed by an accurate classification when larger training sets are employed. The parallel implementation of the algorithm on graphics processing unit (GPU) demonstrates a speedup of three to four folds as compared to a serial implementation on an Intel Core i7 processor. This incredibly efficient GPU system is an effort to streamline the analysis of pulse data in an academic setting. This paper presents for the first time ever, a non-commercial technique using a GPU system for realtime analysis, paired with biological cluster targeting analysis.

This study was conducted at Malalayang Dua waters (Sub-district Malalayang Dua, Manado City). The aim of study is: To know and to inform the coral of Favites abdita. The other aim was to describe the distribution of  Favites abdita. This research also will contribute for the management effort of coral reef in Malalayang Dua area, and also as information and literature in doing research at the same place in the future. Data collection was done by using simple random method with 1x1 meter quadrant. Every coral found was wrote at data sheet. The pictures of those coral was taken by using underwater camera. The highest percentage cover of  hard coral was found in station 3 (1.46%), while the lowest was wrote at station first (0.13%). The distributions patterns of hard coral were found in each stations are Clumped. There is no significant difference in number of colony, percentage cover and diameter for the three depths. Keyword : Distribution coral, Favites abdita Abstrak Penelitian ini dilaksanakan di pantai Kelurahan Malalayang Dua Kecamatan Malalayang Kota Manado. Penelitian ini dilakukan untuk mengetahui dan menginformasikan serta bagaimana mengkaji distribusi karang batu F. abdita. Manfaat penelitian yaitu Memberikan kontribusi bagi upaya pengelolaan terumbu karang di wilayah Pantai Malalayang Dua dan Sebagai bahan informasi dan pustaka serta acuan dalam melakukan penelitian pada tempat yang sama di waktu yang akan datang. Pengambilan data dilakukan dengan menggunakan metode acak sederhana dengan mengunakan kuadran. Pada lokasi penelitian, ditentukan tiga titik pengambilan data, yaitu stasiun 1 stasiun 2 dan stasiun 3. Pada setiap stasiun diletakkan transek berukuran 10x10 meter sebanyak 30 kali ulangan mengunakan kuadran 1x1 meter dengan jarak setiap stasiun 100 meter. Setiap karang yang ditemukan dalam kuadran dicatat pada data sheet dan mengambil gambar dengan camera underwater. Persentase tutupan karang batu tertinggi diperoleh pada stasiun 3 yaitu sebesar 1,46 % dan tutupan terendah pada stasiun 1 yaitu 0,13 %. Pola distribusi karang batu pada ketiga stasiun masing (mengelompok). Pada ketiga kedalaman ini tidak terdapat perbedaan yang nyata antara jumlah koloni, persentase tutupan dan panjang diameter.

channels have been shown to be localized to the intercalated disks along with Cx43 channels. Recent evidence of reciprocity in the co-localized expression of Kir2.1 and Nav1.5 channels in cardiac myocytes suggest that ionic currents due to these two channels are in some way calibrated to each other. In isolated cells, the fast sodium current is much larger than IK1 resulting in a large depolarization reserve. Using simulations of chains of cardiac cells, we show that the depolarization reserve for conducting action potentials is significantly smaller than in isolated cells. We also studied the changes in the depolarization reserve with variations in gap junction channel density and explored the conditions under which propagation slowed or failed. These insights will allow a better understanding of the effects of Na channel blockers as well as regional differences in action potential conduction in the heart.