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FIGURE 5. Paracymus aeneus, third instar larva. A in Morphology of the egg-case and larva of Paracymus aeneus (Germar) (Coleoptera: Hydrophilidae)
FIGURE 5. Paracymus aeneus, third instar larva. A, Head, dorsal view; B, anterior margin of head capsule, dorsal view; C, head capsule, dorsal view; D, head capsule, ventral view; E, prosternal sclerite, ventral view; F, meso- and metanotal sclerites, dorsal view; G, dorsal sclerites on first abdominal segment; H, right mesothoracic leg, anterior view; I, spiracular atrium, dorsal view.
FIGURE 4 in Morphology of the egg-case and larva of Paracymus aeneus (Germar) (Coleoptera: Hydrophilidae)
FIGURE 4. Paracymus aeneus, head, second instar larva. A, Anterior margin of head capsule, dorsal view. B–E, Head appendages; B, right antenna, dorsal view; C, mandible, dorsal view; D, right maxilla, dorsal (left) and ventral (right) view; E, labium, dorsal (left), lateral (middle) and ventral (right) view.
FIGURE 3 in Morphology of the egg-case and larva of Paracymus aeneus (Germar) (Coleoptera: Hydrophilidae)
FIGURE 3. Paracymus aeneus, head appendages, first instar larva. A, Right antenna, dorsal view; B, mandible, dorsal view; C, right maxilla, dorsal (left) and ventral (right) view; D, labium, dorsal (left) and ventral (right) view.
A Preliminary Investigation on the Usage of Quantum Approximate Optimization Algorithms for Test Case Selection - Online Appendix
<p>QAOA-TCS - Quantum Regression Test Case Selection <br>This repository contains all the necessary resources to reproduce the results of the QAOA-TCS method. </p> <p>Dataset Files <br>The "datasets" folder contains: <br>- "sir_programs" </p> <p>SIR Programs <br>The "datasets/sir_programs" folder contains, for each SIR program considered by this project, all the files needed to gather statement coverage, execution costs, and past fault coverage information. </p> <p>For example, in the "flex" program folder: <br>- The file "fault-matrix.txt" contains rows representing flex's test cases. Each row has columns representing different versions of the program. Each cell (i,j) contains a binary value (0 or 1) indicating whether the i-th test case detects a fault in the j-th version. This configuration is called the fault matrix and provides historical fault coverage information. <br>- The folder "json_flex" contains a folder for each test case, with files like "flexi.gcov.json" to recover statement coverage and execution costs. These files detail which basic blocks were executed and how many times, enabling the calculation of total statement coverage and execution costs for each test case. </p> <p>Source Code Files </p> <p>DIVGA.m <br>The "MATLAB/DIVGA.m" file contains the pipeline for the DIVGA algorithm. For simplicity, the statement coverage, execution costs, and fault coverage data already gathered by "Notebook.ipynb" are written into text files, which DIVGA.m reads to bypass the actual datasets. </p> <p>DIVGA.m must be reconfigured for each target program. Update parameters like M, N, and gamultiobj routine settings. Ensure H_size in line 104 is less than max{N, M} + 1. Update the denominator in line 53 based on the total number of code lines in the target program. Adjust the result reporting target files as well. </p> <p>Notebook.ipynb <br>This file includes pipelines for dataset analysis, algorithm execution, and empirical comparisons. </p> <p>It has two main sections: </p> <p>1. QAOA-TCS vs SelectQA and Classical Algorithms <br> - Pipelines analyze SIR programs and compare QAOA-TCS, SelectQA, and classical algorithms. Manual configuration is needed when changing the target program, including updating file paths for Pareto fronts and configuring frontiers to build the reference. <br> - Statistical analysis requires populating the variables "algorithm_nondom_sirprogram" with the number of non-dominated solutions found during each of the 10 runs. </p> <p>Results Files <br>The "results" folder contains the outcomes of QAOA-TCS, DIV-GA, Additional Greedy, and SelectQA after experiment execution. These files enable empirical evaluations and comparisons between the methods. </p>
Figure 1 in Two cases of introducing Lipoptena fortisetosa Maa (Diptera: Hippoboscidae) into Europe through different deer species
Figure 1. Lipoptena fortisetosa (form B) female. Dorsal total view (a); ventral total view (b); dorsal view of the head and thorax length combined (c); ventral view of the head and thorax (d). Lipoptena fortisetosa (form B) male, dorsal total view (e); ventral view of abdomen (f); genital sclerite (g). Scale bars: 1 mm.
Data underlying research paper "Developing an open data intermediation business model: insights from the case of Esri"
<p><strong>Data underlying research paper “Developing an open data intermediation business model: insights from the case of Esri” </strong></p> <p>by Ashraf Shaharudin, Bastiaan van Loenen, and Marijn Janssen from Delft University of Technology (TU Delft), the Netherlands.</p> <p>This folder contains data underlying the research paper “Developing an open data intermediation business model: insights from the case of Esri”. It consists of:</p> <p>1. De-identified interview transcripts</p> <p>2. Informed consent form template</p> <p><strong>Note about the de-identified interview transcripts:</strong></p> <p>The de-identified interview transcripts should be read in the context of the research on open data ecosystem and the role of Esri as open data intermediaries.</p> <p>The 27 interviews, involving 29 interviewees, were conducted between April 2023 and April 2024 based on the semi-structured approach. We shared the tentative interview questions with the interviewees in advance (for the majority, at least three working days prior). Since they are semi-structured interviews, the ultimate interview questions may differ from the tentative questions.</p> <p>We removed personally identifiable information from the transcripts. Some interviewees may risk being identifiable if their organization is known. Hence, we removed the organization and country information from all transcripts. </p> <p>With verbal communication, some sentences may be less incomprehensible in writing. Thus, we did minimal edits when transcribing to improve the comprehensibility where necessary, but the main objective was to keep the transcripts as close to verbatim as possible. </p> <p><strong>Note about the informed consent form template:</strong></p> <p>We sent the informed consent form to every interviewee in advance and requested that they return it to us before or during the interview. </p> <p>All interviewees whose interview transcripts are recorded in this document give permission for the anonymized transcript of their interview, with personally identifiable information redacted, to be shared in 4TU.ResearchData repository so it can be used for future research and learning.</p> <p><strong>Acknowledgement:</strong></p> <p>This research is part of the 'Towards a Sustainable Open Data ECOsystem' (ODECO) project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955569. The opinions expressed in this document reflect only the author’s view and in no way reflect the European Commission’s opinions. The European Commission is not responsible for any use that may be made of the information it contains.</p>
AnnData object for case study tutorials
<p>This dataset works for the Filter, Plot & Explore tutorial: https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-case_basic-pipeline/tutorial.html</p>
Bridging the gap between total peroxyl radical observations and models by measuring OH reactivity to improve estimates of ozone production: a case study from the 24th Winter Olympics Games-
Open the record for dataset details and reuse information.
Transvenous extraction of double dual-coil implantable cardioverter-defibrillator leads – Case report
<p>Abstract: Implantable cardioverter-defibrillator (ICD) is the standard treatment for prevention of sudden cardiac death (SCD) in high-risk patients. Transvenous lead extraction (TLE) is an integral part of management of patients with ICD, since ICD leads are prone to damage in long-term follow-up. TLE is a procedure with high risk of complications. Major complications include haemothorax , thromboembolic events, vascular laceration, cardiac avulsion, and even death, with pericardial tamponade beeing the most common major complication. We report the clinical case of a 54-year-old male patient with a history of chronically implanted ICD who presented with isolated pocket erosion. Cardiac fluoroscopy revealed one dual-coil ICD lead connected to the pulse generator and another dual-coil ICD lead was noted to be fractured, with the proximal end lead remnant in the ICD pocket. Suspicion of pocket infection was raised, therefore the device and the leads extractions were necessary. Dual-coil implantable cardioverter-defibrillator leads are difficult to extract due to fibrotic scar tissue formed around the leads especially near the coils. Transvenous lead extraction technique was used to remove the dual-coil implantable cardioverter-defibrillator leads, without neither major nor minor complications. As ICD therapy was recommended for secondary prophylaxis, a new ICD was implanted on the contralateral side.</p>
FIGURE 2 in Resolving the "muddle in the middle": The case for Homo bodoensis sp. nov.
FIGURE 2 Homo bodoensis sp. nov. holotype partial cranium Bodo 1 (Middle Awash, Ethiopia). Frontal (a), left lateral (b), superior (c) inferior (d) views. Scale bar: 5 cm. Source: Original photos Copyright © Jeffrey H. Schwartz
Fault test cases for series compensated transmission line with the capacitor at the middle of the line
<p><strong>Description</strong></p> <p>This data set contains time series data of different simulated fault cases in high voltage series compensated transmission lines. The simulation is done in PSCAD using the Python automation library. The capacitor is located in the middle of the line. The model of the line is given in the attached pdf file. The CT and VT are located at bus S. The distance are counted from bus S. The modelled line is 500 kV and 200 km long. The simulation is run for 1 second with 10 kHz sampling rate. </p> <p>Each file contains 10 data in the following order, </p> <p>Time<br> Voltage phase A<br> Voltage phase B<br> Voltage phase C<br> Current phase A<br> Current phase B<br> Current phase C<br> Voltage across capacitor phase A<br> Voltage across capacitor phase B<br> Voltage across capacitor phase C</p> <p>The variables used to study different test cases are shown below,</p> <p>Fault inception angle (referred to phase A voltage): 0 and 90 degree<br> Source impedance ratio: 0.20 and 0.35<br> Capacitor compensation level: 94 µF(50%), 78 µF(60%), 67 µF(70%)<br> Fault resistance: 0.10, 10, 20 ohm<br> Fault location: 10 km, 30 km, 50, 70 km, 90 km, 95 km, 105 km, 110 km, 130 km, 150 km, 160 km, 170 km, 180 km<br> Fault type: No-fault, AG, BG, CG, ABG, CAG, BCG, ABCG, AB, CA, BC, ABC</p> <p>All these factors lead to 5616 test cases in total. The test cases are organized in four (4) zipped folders each containing 1404 test cases. The PSCAD model file and an example python script that can be used to automate the simulations are also included herewith for anyone interested to replicate the results. </p> <p> </p> <p>The name of the folders contains the information regarding fault inception angle and source impedance ratio for all test cases inside that folder, for example, the folder name <strong>Outputs_0_0.20</strong> can be decoded as,</p> <p>0: Fault inception angle (phase A)<br> 0.20: Source impedance ration</p> <p>The files names inside the folders include information about the other variables used in generating the test case. For example, the name<strong> test_f_10_0_67_0.01</strong> can be interpreted as,</p> <p>test_f: f for forward fault<br> 10: fault location, 10 km<br> 0: Fault type<br> 67: Compensation level<br> 0.01: Fault resistance</p> <p>Fault types are interpreted as in PSCAD.</p> <p>0 = No-Fault,<br> 1 = Phase A to Ground<br> 2 = Phase B to Ground<br> 3 = Phase C to Ground<br> 4 = Phase AB to Ground<br> 5 = Phase AC to Ground<br> 6 = Phase BC to Ground<br> 7 = Phase ABC to Ground<br> 8 = Phase AB<br> 9 = Phase AC<br> 10 = Phase BC<br> 11 = Phase ABC</p> <p>The different line parameters used in the PSCAD model is as below,</p> <p><strong>Conductor</strong></p> <p>Type: Chukar<br> Geometric mean radius: 20.345 mm<br> DC resistance: 0.0318Ω/km<br> Strands: 84<br> Strand radius: 1.8491 mm<br> Relative permeability: 1.0<br> Sag: 12 m<br> Height: 22 m<br> Sub-conductor: 2<br> Sub-conductor spacing: 0.4572 m<br> Ground wire number: 2<br> Radius: 5.5245 mm<br> DC resistance: 2.8645Ω/km<br> Relative permeability: 1.0<br> Sag: 10 m<br> Height: 10 m</p> <p><strong>Impedance</strong></p> <p>Positive sequence 0.018 +j0.339 Ω/km<br> Zero sequence 0.266 +j1.017 Ω/km</p> <p> </p> <p><strong>These simulations were run for assessing time-domain protections. Therefore, the parallel CB protection across the series capacitor is disabled, as one can safely assume even with the highest current levels, the CB will take at least 20 ms to operate. This is higher than the time limits for time-domain protection. </strong></p>
Physical and biological constraints on the capacity for life-history expression of anadromous salmonids: an Eel River, California, case study
Recovery of anadromous salmonid populations is complicated by the fact that these fish have complex life-histories. Habitat valuation and capacity methods need to account for spatiotemporal variability in temperature, geomorphic features, and a species' thermal sensitivity mediated by biological interactions. We examined this interplay in a case study of steelhead trout (<i>Oncorhynchus mykiss</i>) and Chinook Salmon (<i>O. tshawytscha</i>) in California's Eel River watershed. We estimated habitat suitability and fish capacity for each salmonid run and freshwater life stage during average, cool, and warm years in each of the watershed's subbasins, including a high-elevation subbasin upstream of an impassable dam. Our estimates varied depending on whether we accounted for exposure to the Sacramento pikeminnow (<i>Ptychocheilus grandis</i>), an introduced predator/competitor. Our results indicate that the dammed subbasin could provide an important cool-water refuge during warm years and from pikeminnow, potentially improving the productivity and resilience of multiple anadromous salmonid populations. Our approach can be applied in any setting where spatially explicit habitat metrics can be estimated and population specific and life-stage specific habitat criteria can be specified.
Supplementary material 1 from: Mally R, Ward SF, Trombik J, Buszko J, Medzihorský V, Liebhold AM (2021) Non-native plant drives the spatial dynamics of its herbivores: the case of black locust (Robinia pseudoacacia) in Europe. NeoBiota 69: 155-175. https://doi.org/10.3897/neobiota.69.71949
Table S1. First record locations of Parectopa robiniella, Macrosaccus robiniella and Obolodiplosis robiniae from Europe.
Subspecies and Distribution. S. s. scrofa Linnaeus, 1758 — W Europe, from Denmark, Germany, Poland, and Czech Republic to N Italy and N Iberian Peninsula; possibly also Albania. The taxonomic status of animals in Austria, Switzerland, Slovenia, and Slovakia is unclear but presumably these populations are included in scrofa, as are the populations of Sweden, Finland, and the Baltic states. However, restocking of once depleted populations, for example in Italy, has likely involved the introduction and mixing of this subspecies with other subspecies, such as attila. S. s. affinis Gray, 1847 — S India and Sri Lanka. S. s. algirus Loche, 1867 — Tunisia, Algeria, and Morocco, on the coastal side of the mountains or in the low montane areas. S. s. attila Thomas, 1912 — Hungary, Ukraine, C & S Belarus, Romania, Moldova, and S Russia towards the N flank of the Caucasus, but not including the Transcaucasian countries of Georgia, Armenia, and Azerbaijan. The range possibly extends as far S as the Mesopotamian Delta in Iraq, in which case it would likely include W & SW Iran, and possibly E Turkey and Syria, where it borders with lybicus. Such a range could not be easily reconciled with a statement by Groves that "the difference between pigs from N and S of the Caucasus is quite striking; Transcaucasian boars are certainly not attila." This subspecies may also extend into C Asia and include Kazakhstan, Uzbekistan, and Turkmenistan, but no data exist to support this. S. s. baeticus Thomas, 1912 — originally described from Coto Donana, S Spain, and later merged with meridionalis; also S Portugal. Unless evidence is found that these Italian and Iberian populations are the relics of a much larger formerly contiguous range, this subspecies should be kept as distinct. S. s. coreanus Heude, 1897 — Korean Peninsula. S. s. eristatus Wagner, 1839 — Himalayas S to C India and E to Indochina (N of the Kra Isthmus). S. s. davidi Groves, 1981 — the arid zone from E Iran to Gujarat, including Pakistan and NW India, and perhaps N to Tajikistan. S. s. leucomystax Temminck, 1842 — main Is ofJapan (Honshu, Shikoku, Kyushu, Nakadori, Hiburijima, Tojima, Kushima, and other smaller Is). S. s. lybicus Gray, 1868 — Bulgaria, Greece, Turkey, Syria, Jordan, Israel, Palestine, in the past also in Lybia, and Egypt. The former Yugoslavia was included in its range, which would suggest that now Slovenia, Serbia, Croatia, Bosnia and Herzegovina, Montenegro, and Kosovo are within the range of this subspecies, although the exact boundaries are unclear. Pigs from Albania have been assigned to S. s. scrofa. S. s. majori De Beaux & Festa, 1927 — C & S Italian Peninsula. S. s. menidionalis Forsyth Major, 1882 — Corsica and Sardinia, with the proviso that the two populations are very likely to be introduced or feral. S. s. moupinensis Milne-Edwards, 1871 — China, S to Vietnam and W to Sichuan. S. s. nigripes Blanford, 1875 — the flanks of the Tianshan mountains in Kyrgyzstan and NW China (Xinjiang). An animal photographed in NE Iran (Golestan) looked like this subspecies. S. s. nukiuanus Kuroda, 1924 — Iriomote, Ishigaki, Okinawa, Tokunoshima, Amamioshima, and Kakerome Is in the Ryukyu chain in extreme S Japan, though some of these populations have hybridized with introduced domesticates. S. s. sibiricus Staffe, 1922 — Mongolia and Transbaikal (S & E of Lake Baikal). S. s. tawvanus Swinhoe, 1863 — Taiwan. S. s. ussuricus Heude, 1888 — far E Russia and the Manchurian region (China). Korean populations were previously included in this subspecies, but based on new evidence, the Korean taxon seems more similar to moupinensis. S. s. vittatus Boie, 1828 — Malay Peninsula, S of the Isthmus of Kra, the offshore islands of Terutai and Langkawi, Sumatra, Riau Archipelago, Java, Bali, and a range of smaller islands around these, including Babi, Bakong, Batam, Bawean, Bengkalis, Bintan, Bulan, Bunguran, Cuyo, Deli, Durian, Enggano, Galang, Jambongan, Karimon (Riau Is), Kundur, Lagong, Laut, Lingga, Lingung, Mapor, Moro Kecil, North Pagai, Nias, Panaitan, Payong, Penang, Pinie, Rupat, Siantan, Siberut, Simeulue, Singkep, Sugi, Sugi Bawa, Telibon, Tinggi, Tuangku, and the Tambelan Is. This species was originally present from the British Is in the extreme W, through Eurasia from S Scandinavia to S Siberia, extending as far E as Korea and Japan, and SE into some of the Sunda Is and Taiwan. In the S the species ranged along the Nile Valley to Khartoum, and N of the Sahara in Africa, more orless following the continental coasts of S, E, and SE Asia. Within this range it was absent only from extremely dry deserts, e.g. the driest regions of Mongolia and in China W of Sichuan; and alpine zones, such as the high altitudes of Pamir and Tien Shan. In recent centuries, the range of S. scrofa has changed dramatically because of hunting and changes in available habitat. The species disappeared from the British Is in the 17" century, from Denmark in the 19" century, and was greatly reduced in range and numbers in the 20" century from areas as distant as Tunisia, Sudan, Germany, and Russia. Following these severe declines, there were some slight population recoveries in Russia, Italy, Spain, and Germany in the mid-20™ century, and natural and assisted range expansions in Denmark and Sweden. The species has also been inadvertently reintroduced in various locations in the Great Britain via escapees of mixed origin from commercial farming enterprises. Ex-S. scrofa stocks also occur as introduced feral populations in various other parts of the world, including Australia, New Zealand, the eastern Malay Archipelago, and in North, Central, and South America. In all of these areas they are now generally recognized as a major pest. in Suidae
Subspecies and Distribution. S. s. scrofa Linnaeus, 1758 — W Europe, from Denmark, Germany, Poland, and Czech Republic to N Italy and N Iberian Peninsula; possibly also Albania. The taxonomic status of animals in Austria, Switzerland, Slovenia, and Slovakia is unclear but presumably these populations are included in scrofa, as are the populations of Sweden, Finland, and the Baltic states. However, restocking of once depleted populations, for example in Italy, has likely involved the introduction and mixing of this subspecies with other subspecies, such as attila. S. s. affinis Gray, 1847 — S India and Sri Lanka. S. s. algirus Loche, 1867 — Tunisia, Algeria, and Morocco, on the coastal side of the mountains or in the low montane areas. S. s. attila Thomas, 1912 — Hungary, Ukraine, C & S Belarus, Romania, Moldova, and S Russia towards the N flank of the Caucasus, but not including the Transcaucasian countries of Georgia, Armenia, and Azerbaijan. The range possibly extends as far S as the Mesopotamian Delta in Iraq, in which case it would likely include W & SW Iran, and possibly E Turkey and Syria, where it borders with lybicus. Such a range could not be easily reconciled with a statement by Groves that "the difference between pigs from N and S of the Caucasus is quite striking; Transcaucasian boars are certainly not attila." This subspecies may also extend into C Asia and include Kazakhstan, Uzbekistan, and Turkmenistan, but no data exist to support this. S. s. baeticus Thomas, 1912 — originally described from Coto Donana, S Spain, and later merged with meridionalis; also S Portugal. Unless evidence is found that these Italian and Iberian populations are the relics of a much larger formerly contiguous range, this subspecies should be kept as distinct. S. s. coreanus Heude, 1897 — Korean Peninsula. S. s. eristatus Wagner, 1839 — Himalayas S to C India and E to Indochina (N of the Kra Isthmus). S. s. davidi Groves, 1981 — the arid zone from E Iran to Gujarat, including Pakistan and NW India, and perhaps N to Tajikistan. S. s. leucomystax Temminck, 1842 — main Is ofJapan (Honshu, Shikoku, Kyushu, Nakadori, Hiburijima, Tojima, Kushima, and other smaller Is). S. s. lybicus Gray, 1868 — Bulgaria, Greece, Turkey, Syria, Jordan, Israel, Palestine, in the past also in Lybia, and Egypt. The former Yugoslavia was included in its range, which would suggest that now Slovenia, Serbia, Croatia, Bosnia and Herzegovina, Montenegro, and Kosovo are within the range of this subspecies, although the exact boundaries are unclear. Pigs from Albania have been assigned to S. s. scrofa. S. s. majori De Beaux & Festa, 1927 — C & S Italian Peninsula. S. s. menidionalis Forsyth Major, 1882 — Corsica and Sardinia, with the proviso that the two populations are very likely to be introduced or feral. S. s. moupinensis Milne-Edwards, 1871 — China, S to Vietnam and W to Sichuan. S. s. nigripes Blanford, 1875 — the flanks of the Tianshan mountains in Kyrgyzstan and NW China (Xinjiang). An animal photographed in NE Iran (Golestan) looked like this subspecies. S. s. nukiuanus Kuroda, 1924 — Iriomote, Ishigaki, Okinawa, Tokunoshima, Amamioshima, and Kakerome Is in the Ryukyu chain in extreme S Japan, though some of these populations have hybridized with introduced domesticates. S. s. sibiricus Staffe, 1922 — Mongolia and Transbaikal (S & E of Lake Baikal). S. s. tawvanus Swinhoe, 1863 — Taiwan. S. s. ussuricus Heude, 1888 — far E Russia and the Manchurian region (China). Korean populations were previously included in this subspecies, but based on new evidence, the Korean taxon seems more similar to moupinensis. S. s. vittatus Boie, 1828 — Malay Peninsula, S of the Isthmus of Kra, the offshore islands of Terutai and Langkawi, Sumatra, Riau Archipelago, Java, Bali, and a range of smaller islands around these, including Babi, Bakong, Batam, Bawean, Bengkalis, Bintan, Bulan, Bunguran, Cuyo, Deli, Durian, Enggano, Galang, Jambongan, Karimon (Riau Is), Kundur, Lagong, Laut, Lingga, Lingung, Mapor, Moro Kecil, North Pagai, Nias, Panaitan, Payong, Penang, Pinie, Rupat, Siantan, Siberut, Simeulue, Singkep, Sugi, Sugi Bawa, Telibon, Tinggi, Tuangku, and the Tambelan Is. This species was originally present from the British Is in the extreme W, through Eurasia from S Scandinavia to S Siberia, extending as far E as Korea and Japan, and SE into some of the Sunda Is and Taiwan. In the S the species ranged along the Nile Valley to Khartoum, and N of the Sahara in Africa, more orless following the continental coasts of S, E, and SE Asia. Within this range it was absent only from extremely dry deserts, e.g. the driest regions of Mongolia and in China W of Sichuan; and alpine zones, such as the high altitudes of Pamir and Tien Shan. In recent centuries, the range of S. scrofa has changed dramatically because of hunting and changes in available habitat. The species disappeared from the British Is in the 17" century, from Denmark in the 19" century, and was greatly reduced in range and numbers in the 20" century from areas as distant as Tunisia, Sudan, Germany, and Russia. Following these severe declines, there were some slight population recoveries in Russia, Italy, Spain, and Germany in the mid-20™ century, and natural and assisted range expansions in Denmark and Sweden. The species has also been inadvertently reintroduced in various locations in the Great Britain via escapees of mixed origin from commercial farming enterprises. Ex-S. scrofa stocks also occur as introduced feral populations in various other parts of the world, including Australia, New Zealand, the eastern Malay Archipelago, and in North, Central, and South America. In all of these areas they are now generally recognized as a major pest.
Evaluation Methods for Gamification Use Case to SPI - Database
<p>This document presents the dataset of the definition of evaluation methods, detailed in the work "Reporting the Application of a Gamification Evaluation Framework to Solve Software Process Improvement Problems"</p>
Clinical and histopathological features of 81 cases of canine apocrine gland carcinoma of the anal sac
<p>Canine apocrine gland anal sac adenocarcinoma (AGASAC) is a malignant tumour with variable clinical progression. The objective of this study was to use robust multivariate models, based on models employed in human medical oncology, to establish clinical and histopathological risk factors of poor survival. Clinical data and imaging of 81 cases with AGASAC were reviewed. Tissue was available for histological review and immunohistochemistry in 49 cases. Tumour and lymph node size were determined using the response evaluation criteria in solid tumours system (RECIST). Modelling revealed tumour size over 2 cm, lymph node size grouped in three tiers by the two thresholds 1.6 cm and 5 cm, surgical management, and radiotherapy were independent clinical variables associated with survival, irrespective of tumour stage. Tumour size over 1.3 cm and presence of distant metastasis were independent clinical variables associated with first progression free interval. The presence of the histopathological variables of tumour necrosis, a solid histological pattern, and vascular invasion in the primary tumour were independent risk factors of poor survival. Based upon these independent risk factors, scoring algorithms to predict survival in AGASAC patients are presented.</p>
FIGURES 5–18. O in Otostigmus (Otostigmus) xizangensis n. sp., from China and a case of sexual dimorphism in the subgenus Otostigmus (Otostigmus) Porat, 1876 (Chilopoda, Scolopendromorpha, Scolopendridae)
FIGURES 5–18. O. (O.) xizangensis n. sp., Holotype (figs 5, 6, 8, 10–13); Paratype (Ar.-MHU-SoBM1705250502, figs 7, 9, 14, 15; the dissected female, Ar.-MHU-SoBM1705250515, fig. 16; the dissected male, Ar.-MHU-SoBM1705250516, figs 17–18) 5: Head and tergite 1, dorsal view; 6–7: Cephalic plate, dorsal view; 8–9: Forcipular segment, ventral view; 10–11: Legbearing segments 13–17, dorsal and ventral views; 12–15: Ultimate leg-bearing segment and ultimate legs, dorsal and ventral views; 16–17: Ultimate leg-bearing segment and ultimate legs, ventral view; 18: Three pairs of testes. Scale bar (6, 8, 9, 12): 1 mm, scale bars (5, 7, 10, 11, 13–18): 2 mm. Abbreviations: (bs)—basal suture of tooth-plate, (gp)—glabrous basal portion of antennal article 3, (pt)—process of trochanteroprefemur (tp)—tooth-plate, (md)—median depression, (mk)—tergal median keel, (S17)—sternite 17, (us)— ultimate sternite, (cp)—coxopleural process.
Continuous and proactive software architecture evaluation: An IoT case -- Dataset generated from iFogSim
<p>There will always be a trade-off between using the simulators and physical IoT devices in experimentation and data generation. This is due to the high cost of the actual deployment of IoT devices as compared to simulators. However, some companies, such as Amazon, IBM, and Intel, are motivating the need for having IoT simulation instrumenting what-if test scenarios, typically used during the architecture analysis and refinement stages to evaluate the response and sensitivity of the architecture to these tests. </p> <p>Additionally, many researchers are currently looking for an IoT dataset that provides QoS for IoT architectures. This work provides a dataset well-tested for the most important quality attributes when evaluating IoT architectures.</p> <p>In particular, this work used iFogSim to generate QoS of various IoT architectures in the form of Response Time, Energy consumption, and network usage. After that, MOA framework was used to generate the Forecast QoS values using different time series forecasting algorithms.</p>
MIROC4-ACTM CO2 Inversion flux (2001-2020; case s050_ux4_gc3t)
<p>Details in :</p> <p>Chandra, N., Patra, P. K., Niwa, Y., Ito, A., Iida, Y., Goto, D., Morimoto, S., Kondo, M., Takigawa, M., Hajima, T., and Watanabe, M.: Estimated regional CO<sub>2</sub> flux and uncertainty based on an ensemble of atmospheric CO<sub>2</sub> inversions, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2021-1039, in review, 2021.</p>
Table S2: In Anorexia as a new type of adverse reaction caused by the COVID-19 vaccination: a case study applying detailed personal care records
<p><strong>Table S2</strong> Representative continuous care and vital data since April 2019 admission to August 2021 exit by participant death, and May to June data interrupting 2 June of COVID-19 vaccine injection were described in detail. 5 pre-injection disorder datasets were also included.</p>
ScienceDex guides
Understand access before you commit
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.