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263 results for “Forensics”
Figures 32-35 in A key and checklist to the Neotropical forensically important "Little House Flies" (Diptera: Fanniidae)
Figures 32-35. Fannia, male. (32) F. pusio, abdomen, posterior view; (33) F. grandis, dorsal view; (34) F. katios, posterior view; (35) F. obscurinervis, wing, dorsal view. Scale bars: 1 mm.
Figures 36-38 in A key and checklist to the Neotropical forensically important "Little House Flies" (Diptera: Fanniidae)
Figures 36-38. Fannia, male. (36) F. chibcha, hind leg, anterior view; (37) F. yunguensis, hind leg, posterior view; (38) F. pusio, hind leg, anterior view. Scale bars: 1 mm.
Fig. 3 in Bionomy of two flies of sanitary and forensic importance: Peckia (Sarcodexia) lambens (Wiedemann) and Oxysarcodexia amorosa (Schiner) (Diptera, Sarcophagidae)
Fig. 3. Survival curve following the Weibull distribution model. Male [observed (crosses); expected (solid line)] and female [observed (large dots); expected (dotted line)] of Oxysarcodexia amorosa kept under laboratory conditions (27 ± 1 ◦C, 60 ± 10% RH with 12 h of photophase).
Fig. 11 in Comparative morphology and identification key for females of nine Sarcophagidae species (Diptera) with forensic importance in Southern Brazil
Fig. 11. Female terminalia. (A) Oxysarcodexia paulistanensis (sternites 1–4 omitted); (B) Oxysarcodexia riograndensis (sternites 1–4 omitted); (C) Peckia (Pattonella) resona (sternites 1–4 omitted); (D) Peckia (Euboettcheria) florencioi (sternites 1–4 omitted); (E) Peckia (Sarcodexia) lambens (sternites 1–4 omitted); (F) Microcerella halli (sternites 1–4 omitted); (G) Peckia (Pattonella) intermutans (tergite 6 and sternite 1 omitted); (H) Peckia (Euboettcheria) australis; (I) Sarcophaga (Bercaea) africa (sternite 1 omitted). Scales: 1 mm.
Fig. 8 in Comparative morphology and identification key for females of nine Sarcophagidae species (Diptera) with forensic importance in Southern Brazil
Fig. 8. External female morphology of Peckia (Sarcodexia) lambens. (A) Habitus, lateral view; scale: 2 mm; (B) abdomen, dorsal view; scale: 1 mm; (C) abdominal terminal segments, ventral view; scale: 0.5 mm; (D) abdomen, ventral view; scale: 1 mm.
Fig. 3 in Comparative morphology and identification key for females of nine Sarcophagidae species (Diptera) with forensic importance in Southern Brazil
Fig. 3. External female morphology of Oxysarcodexia riograndensis. (A) Habitus, lateral view; scale: 2 mm; (B) abdomen, dorsal view; scale: 1 mm; (C) abdominal terminal segments, ventral view; scale: 0.5 mm; (D) abdomen, ventral view; scale: 1 mm.
Fig. 6 in Comparative morphology and identification key for females of nine Sarcophagidae species (Diptera) with forensic importance in Southern Brazil
Fig. 6. External female morphology of Peckia (Euboettcheria) australis. (A) Habitus, lateral view; scales: 2 mm; (B) abdomen, dorsal view; scale: 2 mm; (C) abdominal terminal segments, ventral view; scale: 0.5 mm; (D) abdomen, ventral view; scale: 1 mm.
Fig. 1 in Comparative morphology and identification key for females of nine Sarcophagidae species (Diptera) with forensic importance in Southern Brazil
Fig. 1. General morphology of female terminalia. (A) Oxysarcodexia paulistanensis (pink = tergite 8; green = cercus; yellow = hypoproct; blue = vaginal plate; dark red = spiracle 6; dark green = spiracle 7. (B) Peckia (Euboettcheria) florencioi (orange = epiproct). (C) Microcerella halli (light yellow = sternite 5; light green = sternite 6; light pink = sternites 7 + 8).
Fig. 2 in Comparative morphology and identification key for females of nine Sarcophagidae species (Diptera) with forensic importance in Southern Brazil
Fig. 2. External female morphology of Oxysarcodexia paulistanensis. (A) Habitus, lateral view; scale: 2 mm; (B) abdomen, dorsal view; scale: 1 mm; (C) abdominal terminal segments, ventral view; scale: 0.5 mm; (D) abdomen, ventral view; scale: 1 mm.
Fig. 1 in Bionomy of two flies of sanitary and forensic importance: Peckia (Sarcodexia) lambens (Wiedemann) and Oxysarcodexia amorosa (Schiner) (Diptera, Sarcophagidae)
Fig. 1. Survival curve following the Weibull distribution model. Male [observed (crosses); expected (solid line)] and female [observed (large dots); expected (dotted line)] of Peckia (Sarcodexia) lambens kept under laboratory conditions (27 ± 1 ◦ C, 60 ± 10% RH with 12 h of photophase).
TASKS, SYSTEM, METHODS OF CRIMINALISTICS, RELATIONSHIP WITH LEGAL AND OTHER SCIENCES. FORENSIC IDENTIFICATION AND DIAGNOSIS
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Data from: Broad-scale genetic diversity of Cannabis for forensic applications
Cannabis (hemp and marijuana) is an iconic yet controversial crop. On the one hand, it represents a growing market for pharmaceutical and agricultural sectors. On the other hand, plants synthesizing the psychoactive THC produce the most widespread illicit drug in the world. Yet, the difficulty to reliably distinguish between Cannabis varieties based on morphological or biochemical criteria impedes the development of promising industrial programs and hinders the fight against narcotrafficking. Genetics offers an appropriate alternative to characterize drug vs. non-drug Cannabis. However, forensic applications require rapid and affordable genotyping of informative and reliable molecular markers for which a broad-scale reference database, representing both intra- and inter-variety variation, is available. Here we provide such a resource for Cannabis, by genotyping 13 microsatellite loci (STRs) in 1 324 samples selected specifically for fibre (24 hemp varieties) and drug (15 marijuana varieties) production. We showed that these loci are sufficient to capture most of the genome-wide diversity patterns recently revealed by NGS data. We recovered strong genetic structure between marijuana and hemp and demonstrated that anonymous samples can be confidently assigned to either plant types. Fibres appear genetically homogeneous whereas drugs show low (often clonal) diversity within varieties, but very high genetic differentiation between them, likely resulting from breeding practices. Based on an additional test dataset including samples from 41 local police seizures, we showed that the genetic signature of marijuana cultivars could be used to trace crime scene evidence. To date, our study provides the most comprehensive genetic resource for Cannabis forensics worldwide.
Figure 1 from: Sonet G, Jordaens K, Braet Y, Bourguignon L, Dupont E, Backeljau T, de Meyer M, Desmyter S (2013) Utility of GenBank and the Barcode of Life Data Systems (BOLD) for the identification of forensically important Diptera from Belgium and France. ZooKeys 365: 307-328. https://doi.org/10.3897/zookeys.365.6027
Figure 1 - Best matches obtained for each species using five different search procedures:Barcode fragment (642–658 bp) submitted to GenBank (1) and the public records of BOLD (2); barcode fragment submitted to the species level records of BOLD, including early-released sequences (3); barcode fragment and keyword "barcode" submitted to GenBank (4) and longer COI fragment (1412–1534 bp) submitted to GenBank (5). Numbers of haplotypes used as queries are between parentheses. Longer COI fragments were obtained for all species except for Protophormia terraenovae.
Figure 2 from: Verscheure S, Backeljau T, Desmyter S (2013) Reviewing population studies for forensic purposes: Dog mitochondrial DNA. ZooKeys 365: 381-411. https://doi.org/10.3897/zookeys.365.5859
Figure 2 - Impact of including maternally related dogs in population samples of 200 versus 1000 dogs on the estimation of the frequencies of rare haplotypes.
Figure 1 from: Verscheure S, Backeljau T, Desmyter S (2013) Reviewing population studies for forensic purposes: Dog mitochondrial DNA. ZooKeys 365: 381-411. https://doi.org/10.3897/zookeys.365.5859
Figure 1 - Position of the control region and its subregions within the Kim et al. (1998) reference dog mitochondrial genome.
Figure 2 from: Yusseff-Vanegas S, Agnarsson I (2016) Molecular phylogeny of the forensically important genus Cochliomyia (Diptera: Calliphoridae). ZooKeys 609: 107-120. https://doi.org/10.3897/zookeys.609.8638
Figure 2 - Variability in feeding habits, habitat preference and morphology within Cochliomyia. *Cochliomyia aldrichi has been reported in the Florida Keys Islands. **We refer to temperatures around 10–15 °C. ● Carrion feeder; ▴ primary facultative parasite; ■ secondary facultative parasite; ★ obligate parasite.
Figure 1 from: Yusseff-Vanegas S, Agnarsson I (2016) Molecular phylogeny of the forensically important genus Cochliomyia (Diptera: Calliphoridae). ZooKeys 609: 107-120. https://doi.org/10.3897/zookeys.609.8638
Figure 1 - Phylogenetic relationship within Cochliomyia (ingroup) based on partitioned Bayesian analysis of the combined gene (COI, EF-1α, 28S rRNA and ITS2) data set. Branch support values: normal fond, Bayesian posterior probability; bold-italic font, maximum likelihood percentage bootstrap. Each color represents different species.
Dataset Literature Review Digital Forensic AND Methods
<p>Data yang saya upload adalah data yang mana diambil dari lens.org dengan memasukkan keyword/kata kunci “Digital Forensic” “Methods” pada Scholarly Works lalu akan muncul banyak jumlah Scholarly Works yang kemudian sesuai instruksi saya filter sebanyak 3 kali.<br> Yang pertama, saya filter pada bagian Document Type = Journal Articel, selanjutnya yang kedua filter Years = 2012-2022, dan yang ketiga adalah pada bagian Subject,Subject Matter = Law.<br> Yang mana disetiap melakukan filter saya mengekspor data dalam 2 bentuk yaitu, Csv dan BibTex sekaligus menyimpan gambar Analysis Data yang tertera.</p>
Dataset Literature Review Digital Forensic AND Methods
<p>Data ini diambil dari website lens.org dengan memasukkan keyword/kata kunci “Digital Forensic” “Methods” pada Sholarly Works yang kemudian difilter sebanyak 3 kali. yang pertama di filter pada bagian Document Type yaitu pada “Journal Articel”. kedua, di filter pada Years yang mana data rate 10 tahun sebelumnya yaitu mulai tahun 2012 sampai dengan tahun 2022. dan yang terakhir di filter pada bagian Subject, Subject Matter “Law”. Pada setiap tahapan mulai awal hingga akhir semua data tersebut di export dengan format CSV dan BIBTEX. Kemudian semua data yang udah terkumpul akan digunakan untuk membuat penelitian sesuai dengan Literature Review dengan kata kunci Digital Forensic AND Methods.</p>
The Digital Forensics 2023 dataset - DF2023
<p>For a detailed description of the DF2023 dataset, please refer to:<strong> </strong></p> <pre><code> @inproceedings{Fischinger2023DFNet, title={DF2023: The Digital Forensics 2023 Dataset for Image Forgery Detection}, author={David Fischinger and Martin Boyer}, journal={The 25th Irish Machine Vision and Image Processing conference. (IMVIP)}, year={2023} } </code></pre> <p>DF2023 is a dataset for image forgery detection and localization. The training and validation datasets contain 1,000,000/5,000 manipulated images (and the ground truth masks).</p> <p>The DF2023 training dataset comprises:</p> <ul> <li>100K forged images produced by removal (inpainting) operations</li> <li>200K images produced by enhancement modifications</li> <li>300K copy-move manipulated images and</li> <li>400K spliced images</li> </ul> <p> </p> <p><strong>=== Naming convention === </strong></p> <p>The naming convention of DF2023 encodes information about the applied manipulations. Each image name has the following form:</p> <p><strong>COCO_DF_0123456789_NNNNNNNN.{EXT}</strong> (e.g. <em>COCO_DF_E000G40117_00200620.jpg</em>)</p> <p>After the identifier of the image data source ("<em>COCO</em>") and the self-reference to the Digital Forensics ("<em>DF</em>") dataset, there are 10 digits as placeholders for the manipulation. Position <em>0</em> defines the manipulation types copy-move, splicing, removal, enhancement ([C,S,R,E]). The following digits 1-9 represent donor patch manipulations. For positions [1,2,7,8] (resample, flip, noise and brightness), a binary value indicates if this manipulation was applied to the donor image patch. Position 3 (rotate) indicates by the values 0-3 if the rotation was executed by 0, 90, 180 or 270 degrees. Position 4 defines if <em>BoxBlur </em>(B) or <em>GaussianBlur </em>(G) was used. Position 5 specifies the blurring radius. A value of 0 indicates that no blurring was executed. Position 6 indicates which of the Python-PIL contrast filters <em>EDGE ENHANCE</em>, <em>EDGE ENHANCE MORE</em>, <em>SHARPEN</em>, <em>UnsharpMask</em> or <em>ImageEnhance </em>(values 1-5) was applied. If none of them was applied, this value is set to 0. Finally, position 9 is set to the JPEG compression factor modulo 10, a value of 0 indicates that no JPEG compression was applied. The 8 characters <em>NNNNNNNN</em> in the image name template stand for a running number of the images.</p> <p> </p> <p><strong>=== Terms of Use / Licence ===</strong></p> <p>The DF2023 dataset is based on the MS COCO dataset. Therefore, rules for using the images form MS COCO apply also for DF2023:</p> <blockquote> <p>Images</p> <p>The COCO Consortium does not own the copyright of the images. Use of the images must abide by the <a href="https://www.flickr.com/creativecommons/">Flickr Terms of Use</a>. The users of the images accept full responsibility for the use of the dataset, including but not limited to the use of any copies of copyrighted images that they may create from the dataset.</p> </blockquote>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.