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This study aims to map three main benthic habitats (coral, seagrass, and sand) in Kapota Atoll (Wakatobi, Indonesia) using single-beam echosounder (SBES) Simrad EK15. Eight acoustic parameters are used as classification aThis study aims to map three main benthic habitats (coral, seagrass, and sand) in Kapota Atoll (Wakatobi, Indonesia) using a single-beam echosounder (SBES) Simrad EK15. The acoustic data were processed using Sonar5-Pro ​​software. Eight acoustic parameters were used as input for the classification and prediction of benthic habitats, including depth (D), five acoustic parameters of the first echo (BD, BP, AttSv1, DecSv1, and AttDecSv1), and cumulative energy of the second and third echoes (AttDecSv2 and AttDecSv3). The classification and prediction process of benthic habitats uses two machine learning algorithms, Random Forest (RF) and Support Vector Machine (SVM), in XLSTAT Basic+ software. The study results show that 49 combinations of acoustic parameters produce benthic habitat maps that meet the minimum accuracy standards for benthic habitat mapping (≥60%). Using eight acoustic parameters produces a more accurate benthic habitat map than using only two main SBES parameters (DecSv1 and AttDecSv2 parameters or E1 and E2 in the RoxAnn system indicating the roughness and hardness indices). The RF and SVM algorithms produce benthic habitat maps with the highest accuracy of 79.33% and 78.67%, respectively. Each acoustic parameter has a different importance for the classification of benthic habitats, where the order of importance of each acoustic parameter in the overall classification follows the following order: AttDecSv2 > D > DecSv1 > BD > AttDecSv3 > AttSv1 > AttDecSv1 > BP. Overall, using more acoustic parameters can significantly improve the accuracy of benthic habitat mapsinput, including depth (D), five acoustic parameters of the first echo (BD, BP, AttSv1, DecSv1, and AttDecSv1) and cumulative energy of the second and third echoes (AttDecSv2 and AttDecSv3). The classification and prediction process of benthic habitats uses two machine learning algorithms, namely Random Forest (RF) and Support Vector Machine (SVM). The study results show that using eight acoustic parameters produces a more accurate benthic habitat map than using only two main SBES parameters (as in the RoxAnn system: roughness and hardness indices). The RF and SVM algorithms produce benthic habitat maps with the highest accuracy of 79.33% and 78.67%, respectively. Each acoustic parameter has a different importance for the classification of benthic habitats, where five acoustic parameters have the highest importance for the overall classification, namely AttDecSv2, D, DecSv1, BD, and AttDecSv3.

Upwelling adalah proses naiknya massa air laut dari lapisan bawah ke permukaan akibat perbedaan tekanan permukaan. Terjadi proses upwelling akan meningkatkan kesuburan perairan karena massa air di lapisan dalam naik ke permukaan yang kaya nutrisi yang dibutuhkan fitoplankton untuk berkembang. Luas sebaran daerah upwelling (radius deformasi) akan menentukan dampak proses upwelling di perairan. Penelitian ini bertujuan untuk menganalisis proses upwelling dan radius deformasi dari data satelit sensor termal. Data yang digunakan adalah data satelit termal harian dan rata-rata bulanan selama tahun 2014-2018. Data dari buoy Argo digunakan untuk memvalidasi data satelit dan menghitung radius deformasi upwelling. Analisis statistik seperti korelasi, Root Mean Square Error (RMSE), bias, dan standar deviasi digunakan untuk menguji keakuratan perkiraan data Suhu Permukaan Laut (SPL) dari satelit. Data perhitungan radius deformasi dari Argo menunjukkan bahwa pada musim timur terjadi upwelling, SPL berkisaran antara 24-26ºC, normalnya berkisaran antara 27-29ºC. Korelasi antara SPL dari data satelit dan data SPL dari Argo adalah 0,92, nilai RMSE 0,0236, bias 0,017, dan standar deviasi 0,287. Koefisien korelasi antara radius deformasi dari data in situ dan data satelit yang dihitung tinggi (r=0,9) menunjukkan bahwa citra satelit dapat digunakan untuk menentukan radius deformasi.

In ocean remote sensing, the intensity of light entering the water column decreases exponentially with increasing depth due to scattering and particle absorption in the water column. This process of decreasing light intensity is called attenuation. Attenuation is a limiting factor in detecting objects in the water column and seafloor using remote sensing, which relies on light intensity. The attenuation coefficient (Kd) is an important optical property of seawater as it provides information about water clarity and the level of light attenuation. This study aims to analyze the estimation of the attenuation coefficient values and their variability using in-situ measurements and Sentinel-2 level 2A data in Karang Lebar, Pulau Panggang, and Pulau Air, in the Seribu Islands Regency, North Jakarta. We tested several algorithms to estimate the attenuation coefficient values. The research results show that the in-situ Kd and the estimated model values have a good correlation (r = 0.75-0.86). The distribution of attenuation coefficient values in the shallow waters of the study area ranges from 0.06 to 0.18m-1. The accuracy of estimating shallow water depth at the study sites was best represented by R2 and RMSE values in the range of 0-5m with an attenuation coefficient of 0.06-0.11m-1. Keywords: Diffuse Attenuation Coefficient, Remote Sensing, Sentinel-2 Imagery, Algorithm.

Global sea level rise (SLR) has emerged as a pressing concern because of its impacts, especially increased vulnerability of coastal urban areas flooding. This study addresses the pressing concern of SLR and flood vulnerability in the East Coast of North Sumatra (ECNS) and Medan City. We employ a data-driven approach integrating multicriteria analysis, analytical hierarchy process (AHP)-based weighting, and spatial modeling within a geographic information system framework. The analysis considers crucial factors such as slope, land use, soil type, SLR, and land deformation. The study expands the existing framework by incorporating SLR and land subsidence, acknowledging their significant roles in exacerbating flood vulnerability. Future flood-intensity scenarios are simulated based on SLR projections. Data for spatial analysis primarily originated from multisensor satellite imagery, secondary sources from published literature, and field surveys. We validated the consistency of the variable weightings assigned for vulnerability analysis using a consistency ratio threshold (

Remotely sensed data and habitat model approach were employed to evaluate the present of oceanographic aspect in the Bigeye tuna's potential fishing zone (PFZ) at a profundity of 155 m. Vessel monitoring system was employed to acquire the angling vessels for Bigeye tuna from January through December, 2015-2016. Daily data of sub-surface temperature (Sub_ST), sub-surface chlorophyll-a (Sub_SC), and sub-surface salinity (Sub_SS) were downloaded from INDESO Project website. Vessel monitoring system and environmental data were employed for maximum entropy (maxent) model development. The model predictive achievement was then estimated applying the area under the curve (AUC) value. Maxent model results (AUC>0.745) exhibited its probable to understand the Bigeye tuna's spatial dispersion on the specific sub-surface. In addition, the results also showed Sub_ST (43,1%) was the most affective aspect in the Bigeye tuna dispersion, pursued by Sub_SC (35,2%) and Sub_SS (21,6%).

Although tumour budding is an adverse prognostic factor for many cancer types, the molecular mechanisms governing this phenomenon are incompletely understood. Therefore, understanding the molecular basis of tumour budding may provide new therapeutic and diagnostic options. We employ digital image analysis to demonstrate that the number of tumour buds in cytokeratin-stained sections correlates with patients having lymph node metastases at diagnosis. The tumour bud count was also a predictor of overall survival, independent of TNM stage. Tumour buds and paired central tumour areas were subsequently collected from oral squamous cell carcinoma ( OSCC) specimens, using laser capture microdissection, and examined with RNA sequencing and miRNA-qPCR arrays. Compared with cells from the central parts of the tumours, budding cells exhibited a particular gene expression signature, comprising factors involved in epithelial-mesenchymal transition ( EMT) and activated TGFβ signalling. Transcription factors ZEB1 and PRRX1 were up-regulated concomitantly with the decreased expression of mesenchymal-epithelial ( MET) transcription factors (eg OVOL1) in addition to Krüppel-like factors and Grainyhead-like factors. Moreover, miR-200 family members were down-regulated in budding tumour cells. We used immunohistochemistry to validate five markers of the EMT/ MET process in 199 OSCC tumours, as well as in situ hybridization in 20 OSCC samples. Given the strong relationship between tumour budding and the development of lymph node metastases and an adverse prognosis, therapeutics based on inhibiting the activation of TGFβ signalling may prove useful in the treatment of OSCC. Copyright © 2015 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Pemetaan lahan yang potensial untuk budidaya perikanan dilakukan melalui pemetaan topografi dan tutupan lahan dari citra satelit serta survei lapang di perairan pantai Timur Belitung. Peta Topografi estimasi dari citra satelit mempunyai pola yang sama dengan hasil pengukuran terestris dimana ketinggian lahan semakin meningkat mulai dari garis pantai menuju daratan. Data hasil pengukuran topografi secara terestris lebih tinggi dari data topografi estimasi dari data satelit. Tipe pasut di perairan pantai Belitung timur adalah tipe tunggal. Data pasut ini digunakan menjadi acuan untuk pengukuran topografi secara terestris. Peta tutupan lahan hasil intrepretasi dari citra satelit diklasifikasikan menjadi kelas: hutan primer, hutan sekunder, belukar, rawa/air, lahan terbuka, permukiman dan galian tambang. Berdasarkan peta topografi, peta tutupan lahan dan data pasang surut maka lahan di wilayah kajian pesisir pantai Timur Belitung potensial dikembangkan untuk budidaya perikanan seluas 9.000 ha. ABSTRACT Mapping potential land for aquaculture was done through topography, and land cover mapping derived satellite imagery and field survey in the east coast of Belitung. Topographic data derived satellite, and terrestrial measurement shows that topographic patterns increase as we move from the coastal line to inland. Topographic data from the terrestrial measurement was higher than satellite estimations. The type of tide in the east coast Belitung’s is the diurnal type. Within this research, tidal data was used as a reference terrestrial topographic measurement. Land coverage maps from satellite images were classified into primary and secondary forests, grove forests, marsh/water lands, open land, inhabited land, and mining areas. According to topographic, land cover map, and tide pattern it can be confirmed that the eastern coastal area of Belitung has the potential to be developed into an aquaculture fishery area of 9,000 ha.

Pemetaan zona geomorfologi terumbu karang di Pulau Tunda ini belum pernah dilakukan khususnya menggunakan klasifikasi citra berbasis objek. Hasil pemetaan ini dapat digunakan sebagai dasar informasi perencanaan dan pengembangan suatu kawasan menuju pemanfaatan yang optimal seperti contoh pemanfaatan sebagai kawasan ekowisata bahari. Penelitian ini bertujuan untuk memetakan zona geomorfologi terumbu karang Pulau Tunda denganmenggunakan klasifikasi berbasis objek. Bahan analisis menggunakan citra multispektral Worldview-2 dengan akuisisi data tanggal 25 Agustus 2013 dan profil batimetri. Klasifikasi memakai algoritma segmentasi multiresolusi. Klasifikasi dibagi kedalam 2 level klasifikasi. Parameter klasifikasi level 1 menggunakan scale sebesar 200, shape 0.6 dan compactness 0.4. Segmentasi level 2 menggunakan scale 30, shape 0.6 dan compactness 0.4. Klasifikasi segmentasi objek ini mampu menghasilkan peta dengan tingkat akurasi yang tinggi pada setiap level. Akurasi klasifikasi level 1 adalah sebesar 97% dan level 2 sebesar 91%.

Tumpahan minyak di Laut Timor yang terjadi pada tahun 2009 telah menyebarkan minyak seluas 10.842.81 km2.Tumpahan minyak ini berhasil dideteksi oleh satelit Moderate Resolution Imaging Spectroradiometer (MODIS). Tujuan dari penelitian ini adalah membandingkan hasil deteksi tumpahan minyak dari beberapa algoritma dengan citra menggunakan citra MODIS dan melihat perbedaan visual yang dihasilkan. Algoritma yang digunakan adalah Oil Spill Index, Fluorescence Index, Principal Component Analysis (PCA), Normalized Difference Vegetation Index (NDVI). Visualisasi tumpahan minyak yang terlihat pada citra MODIS dengan algoritma oil spill indeks dan fluorescence index lebih cerah dibandingkan dengan badan air disekitarnya dan juga memiliki nilai piksel lebih tinggi, sedangkan visualisasi minyak menggunakan algoritma PCA dan NDVI lebih gelap dibandingkan dengan badan air disekitarnya dan juga memiliki nilai piksel yang lebih rendah. Hasil uji akurasi yang dilakukan terhadap algoritma oil splill index, fluorescence index, PCA, NDVI berturut-turut sebagai berikut 41%, 46%, 41%, dan 60%

Penelitian ini bertujuan untuk mempelajari variasi spasial dan temporal konsentrasi klorofil-a dan suhu permukaan laut serta hubungannya dengan hasil tangkapan ikan pelagis di Laut Jawa. Hasil penelitian menunjukkan dalam tahun 2006-2010 terjadi kenaikan suhu permukan laut sebesar 1°C dimana suhu permukan laut rata-rata bulanan berkisar antara 27,9°C ­– 31,4°C. Suhu permukaan laut relatif lebih tinggi pada saat musim peralihan dibandingkan dengan musim barat dan musim timur. Konsentrasi klorofil-a pada wilayah penelitian berkisar antara 0,22 mg/m³- 1,15 mg/m³. Nilai konsentrasi klorofil-a setiap bulannya berfluktuasi mengikuti musim angin yang sedang berlangsung. Nilai maksimum konsentrasi klorofil-a terjadi pada musim Barat dan nilai minimumnya terjadi pada musim peralihan 2. Ikan layang, banyar dan tembang memiliki respon yang negatif terhadap suhu permukaan laut terutama pada musim timur. Sedangkan untuk ikan lemuru dan ikan tembang menunjukkan tidak adanya hubungan langsung antara suhu permukaan laut dengan nilai CPUE hasil tangkapan. Ikan lemuru dan ikan tembang menunjukkan adanya respon positif terhadap naiknya konsentrasi klorofil-a, sedangkan untuk ikan layang, banyar dan tongkol kenaikan nilai konsentrasi klorofil tidak berdampak langsung pada naiknya nilai CPUE ketiga jenis ikan ini

Mangrove is one of the most important objects in wetland ecosystems. Mangrove research has been done, one of them is using remote sensing technology. This study aims to assess accuracy of object based image analysis (OBIA) approach on both Support Vector Machine (SVM) and Decision Tree classification methods to classify mangrove and estimate mangrove area in the field study. We selected Kawasan Konservasi Laut Daerah (KKLD) Gili Sulat as a research site. This research used Sentinel-2B satellite imagery. We took field data using stratified random sampling and the amount of the data we collected were 121 points. The classification analysis result with object based showed that SVM had an overall accuracy of 95 % (kappa = 0.86) and Decision Tree classification had an overall accuracy of 93 % (kappa = 0.82). It is caused SVM can reduce the error of classification than Decision Tree. Estimation result based on assessment showed that mangrove using SVM had 634.62 Ha while using Decision Tree had 590.47 Ha

Upwelling musiman pada umumnya terjadi di sepanjang selatan jawa hingga barat Sumatera. Penelitian ini bertujuan untuk mengestimasi intensitas upwelling dari data SPL dan konsentrasi klorofil-a dari sensor satelit. Data SPL dan Klorofil-a yang digunakan adalah data satelit Aqua-MODIS level-3 dan data angin dari satelit Quikscat pada bulan Juli 2002 sampai Juni 2011. Indeks upwelling diperoleh dengan formula Coastal Upwelling Index (CUIx). Analisis statistik digunakan untuk melihat hubungan antara SPL dan klorofil dengan CUIx. Hasil penelitian menunjukan bahwa secara temporal upwelling terjadi pada musim timur, dengan kisaran SPL 25.10 – 27.30 °C dan konsentrasi klorofil-a 0.30 – 0.67 mg m-3. Namun pada tahun 2006 terjadi anomali intensitas upwelling yang ditandai dengan SPL yang turun mencapai 24.98 °C (Selatan Jawa) dan 25.97 °C (Barat Sumatera), konsentrasi klorofil-a meningkat 1.33 mg m-3 (Barat Sumatera) dan 3.71 mg m-3 (Selatan Jawa). Hasil analisis menunjukkan bahwa SPL memiliki hubungan yang sangat kuat dengan CUIx di Barat Sumatra (r=0.84). Sementara di perairan selatan Jawa, kedua parameter (SPL dan klorofil-a) menunjukkan hubungan yang sangat kuat dengan CUIx (r=0.86 yang untuk SPL dan r = 0.81 untuk klorofil-a).

Seagrass has an important role in coastal areas, so it’s sustainability need to be maintained. One effort to preserve it is sustainable manner management of segrass based on the spatial data using remote sensing techniques. The aim of this study was to map seagrass ecosystems and to determining the accuracy level from classification results that obtained by the WorldView-2 images. This study was conducted in Karang Bongkok and Kotok Islands in August 2014 and March 2015. The satellite images data used on this study was WorldView-2 satellite images at the acquisition date of October 5, 2013. The method used to conduct image processing data is Depth Invariant Index (DII) using Support Vector Machine (SVM) classification. The result shows that seagrass mapping in Karang Bongkok and Kotok Islands using DII transformation has 19.5112 ha areas with 72% accuracy on Karang Bongkok Island and 2.5704 ha areas with of 83% accuracy on Kotok Island. Key words: Seagrass mapping, DII, SVM, Karang Bongkok, Kotok Island.

Accurate and up-to-date information of marine resources is needed for optimum resource utilization. If the required information cannot be obtained with traditional field surveys, remote sensing as a tool for providing fast, efficient, and accurate information is used to detect the changes. The study aims to use remote sensing data for assessing distribustion and condition of marine resources in Nias water's before and after tsunami. Marine resources pararameter derived remote sensing data are sea surface temperature (SST), suspended solid matter, chlorphyll-a concentration, coral reef and mangrove distributions. Mapping and differences in coral reef and mangrove distribution were evaluated using two scans of Landsat image in 1989 and 2005. Sea surface temperature was derived from NOAA-AVHRR data, and chlorophyll-a concentration was derived from SeaWiFS data. The study showed that there were no significant changes of coral reef and mangrove distribution, SST, chlorophyll-a concentration after and before tsunami. Spectral analysis of SST and chlorophyll-a showed that the variability of the parameters was affected by monsoon system and global climate change, namely El Nino Southern Oscillation and Indian Ocean Dipole

Abstract Background BRCA2 germ-line mutations predispose to breast and ovarian cancer. Mutations are widespread and unclassified splice variants are frequently encountered. We describe the parental origin and functional characterization of a novel de novo BRCA2 splice site mutation found in a patient exhibiting a ductal carcinoma at the age of 40. Methods Variations were identified by denaturing high performance liquid chromatography (dHPLC) and sequencing of the BRCA1 and BRCA2 genes. The effect of the mutation on splicing was examined by exon trapping in COS-7 cells and by RT-PCR on RNA isolated from whole blood. The paternity was determined by single nucleotide polymorphism (SNP) microarray analysis. Parental origin of the de novo mutation was determined by establishing mutation-SNP haplotypes by variant specific PCR, while de novo and mosaic status was investigated by sequencing of DNA from leucocytes and carcinoma tissue. Results A novel BRCA2 variant in the splice donor site of exon 21 (nucleotide 8982+1 G→A/c.8754+1 G→A) was identified. Exon trapping showed that the mutation activates a cryptic splice site 46 base pairs 3' of exon 21, resulting in the inclusion of a premature stop codon and synthesis of a truncated BRCA2 protein. The aberrant splicing was verified by RT-PCR analysis on RNA isolated from whole blood of the affected patient. The mutation was not found in any of the patient's parents or in the mother's carcinoma, showing it is a de novo mutation. Variant specific PCR indicates that the mutation arose in the male germ-line. Conclusion We conclude that the novel BRCA2 splice variant is a de novo mutation introduced in the male spermatozoa that can be classified as a disease causing mutation.