University of Crete

About: University of Crete is a education organization based out in Rethymno, Greece. It is known for research contribution in the topics: Population & Galaxy. The organization has 8681 authors who have published 21684 publications receiving 709078 citations. The organization is also known as: Panepistimio Kritis.

Towards effective COVID­19 vaccines: Updates, perspectives and challenges (Review).

Abstract: In the current context of the pandemic triggered by SARS-COV-2, the immunization of the population through vaccination is recognized as a public health priority. In the case of SARS‑COV‑2, the genetic sequencing was done quickly, in one month. Since then, worldwide research has focused on obtaining a vaccine. This has a major economic impact because new technological platforms and advanced genetic engineering procedures are required to obtain a COVID‑19 vaccine. The most difficult scientific challenge for this future vaccine obtained in the laboratory is the proof of clinical safety and efficacy. The biggest challenge of manufacturing is the construction and validation of production platforms capable of making the vaccine on a large scale.

Automatic acoustic detection of birds through deep learning : the first bird audio detection challenge

Abstract: Assessing the presence and abundance of birds is important for monitoring specific species as well as overall ecosystem health. Many birds are most readily detected by their sounds, and thus passive acoustic monitoring is highly appropriate. Yet acoustic monitoring is often held back by practical limitations such as the need for manual configuration, reliance on example sound libraries, low accuracy, low robustness, and limited ability to generalise to novel acoustic conditions. Here we report outcomes from a collaborative data challenge. We present new acoustic monitoring datasets, summarise the machine learning techniques proposed by challenge teams, conduct detailed performance evaluation, and discuss how such approaches to detection can be integrated into remote monitoring projects. Multiple methods were able to attain performance of around 88% AUC (area under the ROC curve), much higher performance than previous general‐purpose methods. With modern machine learning including deep learning, general‐purpose acoustic bird detection can achieve very high retrieval rates in remote monitoring data with no manual recalibration, and no pre‐training of the detector for the target species or the acoustic conditions in the target environment.

Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals

Abstract: In this paper, we strive to answer two questions: What is the current state of 3D hand pose estimation from depth images? And, what are the next challenges that need to be tackled? Following the successful Hands In the Million Challenge (HIM2017), we investigate the top 10 state-of-the-art methods on three tasks: single frame 3D pose estimation, 3D hand tracking, and hand pose estimation during object interaction. We analyze the performance of different CNN structures with regard to hand shape, joint visibility, view point and articulation distributions. Our findings include: (1) isolated 3D hand pose estimation achieves low mean errors (10 mm) in the view point range of [70, 120] degrees, but it is far from being solved for extreme view points; (2) 3D volumetric representations outperform 2D CNNs, better capturing the spatial structure of the depth data; (3) Discriminative methods still generalize poorly to unseen hand shapes; (4) While joint occlusions pose a challenge for most methods, explicit modeling of structure constraints can significantly narrow the gap between errors on visible and occluded joints.

GOODS-Herschel: dust attenuation properties of UV selected high redshift galaxies

Abstract: Context. Dust attenuation in galaxies is poorly known, especially at high redshift. And yet the amount of dust attenuation is a key parameter to deduce accurate star formation rates from ultraviolet (UV) rest-frame measurements. The wavelength dependence of the dust attenuation is also of fundamental importance to interpret the observed spectral energy distributions (SED) and to derive photometric redshifts or physical properties of galaxies. Aims. We want to study dust attenuation at UV wavelengths at high redshift, where the UV is redshifted to the observed visible light wavelength range. In particular, we search for a UV bump and related implications for dust attenuation determinations. Methods. We use photometric data in the Chandra Deep Field South (CDFS), obtained in intermediate and broad band filters by the MUSYC project, to sample the UV rest-frame of 751 galaxies with 0:95 < z < 2:2. When available, infrared (IR) Herschel/PACS ? data from the GOODS-Herschel project, coupled with Spitzer/MIPS measurements, are used to estimate the dust emission and to constrain dust attenuation. The SED of each source is fit using the CIGALE code. The amount of dust attenuation and the characteristics of the dust attenuation curve are obtained as outputs of the SED fitting process, together with other physical parameters linked to the star formation history. Results. The global amount of dust attenuation at UV wavelengths is found to increase with stellar mass and to decrease as UV luminosity increases. A UV bump at 2175 A is securely detected in 20% of the galaxies, and the mean amplitude of the bump for the sample is similar to that observed in the extinction curve of the LMC supershell region. This amplitude is found to be lower in galaxies with very high specific star formation rates, and 90% of the galaxies exhibiting a secure bump are at z < 1:5. The attenuation curve is confirmed to be steeper than that of local starburst galaxies for 20% of the galaxies. The large dispersion found for these two parameters describing the attenuation law is likely to reflect a wide diversity of attenuation laws among galaxies. The relations between dust attenuation, IR-to-UV flux ratio, and the slope of the UV continuum are derived for the mean attenuation curve found for our sample. Deviations from the average trends are found to correlate with the age of the young stellar population and the shape of the attenuation curve. Conclusions.

Skeletal anomalies in reared European fish larvae and juveniles, part 2 : main typologies, occurrences and causative factors

Abstract: The presence of skeletal anomalies in farmed teleost fish is currently a major problem in aquaculture, entailing economical, biological and ethical issues. The common occurrence of skeletal abnormalities in farmed fish and the absence of effective solutions for avoiding their onset or definitely culling out the affected individuals as early as possible from the productive cycle, highlight the need to improve our knowledge on the basic processes regulating fish skeletogenesis and skeletal tissues differentiation, modelling and remodelling. Severe skeletal anomalies may actually occur throughout the entire life cycle of fish, but their development often begins with slight aberrations of the internal elements. Comprehensive investigation efforts conducted on reared larvae and juveniles could provide a great contribution in filling the gap in knowledge, as skeletogenesis and skeletal tissue differentiation occur during these early life stages. The aim of this review is to provide a synthetic but comprehensive picture of the actual knowledge on the ontogeny, typologies and occurrence of skeletal anomalies, and on the proposed causative factors for their onset in larvae and juveniles of European farmed fish. The state-of-art of knowledge of these issues is analysed critically intending to individualize the main gaps of knowledge that require to be filled, in order to optimize the morphological quality of farmed juveniles.