Tracking turtles in the past:Zooarchaeological evidence for human-turtle interactions in the ancient Eastern Mediterranean

Turtles are important barometers of human impact on marine biodiversity. Very little, however, is known about the deep history of human-turtle interactions and whether this is reflected in the present-day vulnerability of Mediterranean turtle populations. Here, the authors critically assess the zooarchaeological evidence for the nature and intensity of past human interactions with green, loggerhead turtles and Nile soft-shell turtles in the Eastern Mediterranean. Species and sex identifications, estimates of relative abundance, and size reconstructions at five coastal archaeological sites demonstrate the variety in interactions, from turtle capture to processing, and allow informative comparisons with present-day distributions of these species across the region

On the Optical Activity of Steroidal 5,7-Dienes

Circular dichroism (CD) data are reported of a series of 9,10- stereoisomeric steroidal 5,7-dienes. In general the effects in the longest wavelength transition (270-280 nm) are large (Mm" 10---30) and consignate with respect to the diene helicity rule. The magnitude of the CD appears to vary markedly with the substituent at C-3 and at C-17, and with solvent. In the case of the 9a,10p-H dienes, variation of solvent and temperature can affect even the sign of the Cotton effect. This is explained from a change of geometry of the diene ring: solvation, substitution and temperature can affect the average geometry of the ring including the values of the angle of twist of the diene (ef> (6-7». The relevance of the observed chiroptical data for the theoretical description of the optical activity in the So-+ Sl transition of homoannular cisoid dienes is discussed

Atomic layer deposition of titanium nitride for quantum circuits

Superconducting thin films with high intrinsic kinetic inductance are of great importance for photon detectors, achieving strong coupling in hybrid systems, and protected qubits. We report on the performance of titanium nitride resonators, patterned on thin films (9-110 nm) grown by atomic layer deposition, with sheet inductances of up to 234 pH/square. For films thicker than 14 nm, quality factors measured in the quantum regime range from 0.4 to 1.0 million and are likely limited by dielectric two-level systems. Additionally, we show characteristic impedances up to 28 kOhm, with no significant degradation of the internal quality factor as the impedance increases. These high impedances correspond to an increased single photon coupling strength of 24 times compared to a 50 Ohm resonator, transformative for hybrid quantum systems and quantum sensing.Comment: 10 pages, 8 figures including supplemental material

A Hermetic On-Cryostat Helium Source for Low Temperature Experiments

We describe a helium source cell for use in cryogenic experiments that is hermetically sealed $in$ $situ$ on the cold plate of a cryostat. The source cell is filled with helium gas at room temperature and subsequently sealed using a cold weld crimping tool before the cryostat is closed and cooled down. At low temperature the helium condenses and collects in a connected experimental volume, as monitored via the frequency response of a planar superconducting resonator device sensitive to small amounts of liquid helium. This on-cryostat helium source negates the use of a filling tube between the cryogenic volumes and room temperature, thereby preventing unwanted effects such as such as temperature instabilities that arise from the thermomechanical motion of helium within the system. This helium source can be used in experiments investigating the properties of quantum fluids or to better thermalize quantum devices.Comment: 5 pages, 3 figure

Preserved collagen reveals species identity in archaeological marine turtle bones from Caribbean and Florida sites

Advancements in molecular science are continually improving our knowledge of marine turtle biology and evolution. However, there are still considerable gaps in our understanding, such as past marine turtle distributions, which can benefit from advanced zooarchaeological analyses. Here, we apply collagen fingerprinting to 130 archaeological marine turtle bone samples up to approximately 2500 years old from the Caribbean and Florida's Gulf Coast for faunal identification, finding the vast majority of samples (88%) to contain preserved collagen despite deposition in the tropics. All samples can be identified to species-level with the exception of the Kemp's ridley (Lepidochelys kempii) and olive ridley (L. olivacea) turtles, which can be separated to genus level, having diverged from one another only approximately 5 Ma. Additionally, we identify a single homologous peptide that allows the separation of archaeological green turtle samples, Chelonia spp., into two distinct groups, which potentially signifies a difference in genetic stock. The majority of the archaeological samples are identified as green turtle (Chelonia spp.; 63%), with hawksbill (Eretmochelys imbricata; 17%) and ridley turtles (Lepidochelys spp.; 3%) making up smaller proportions of the assemblage. There were no molecular identifications of the loggerhead turtle (Caretta caretta) in the assemblage despite 9% of the samples being morphologically identified as such, highlighting the difficulties in relying on morphological identifications alone in archaeological remains. Finally, we present the first marine turtle molecular phylogeny using collagen (I) amino acid sequences and find our analyses match recent phylogenies based on nuclear and mitochondrial DNA. Our results highlight the advantage of using collagen fingerprinting to supplement morphological analyses of turtle bones and support the usefulness of this technique for assessing their past distributions across the Caribbean and Florida's Gulf Coast, especially in these tropical environments where DNA preservation may be poor

Machine learning based natural language processing of radiology reports in orthopaedic trauma

OBJECTIVES: To compare different Machine Learning (ML) Natural Language Processing (NLP) methods to classify radiology reports in orthopaedic trauma for the presence of injuries. Assessing NLP performance is a prerequisite for downstream tasks and therefore of importance from a clinical perspective (avoiding missed injuries, quality check, insight in diagnostic yield) as well as from a research perspective (identification of patient cohorts, annotation of radiographs). METHODS: Datasets of Dutch radiology reports of injured extremities (n = 2469, 33% fractures) and chest radiographs (n = 799, 20% pneumothorax) were collected in two different hospitals and labeled by radiologists and trauma surgeons for the presence or absence of injuries. NLP classification was applied and optimized by testing different preprocessing steps and different classifiers (Rule-based, ML, and Bidirectional Encoder Representations from Transformers (BERT)). Performance was assessed by F1-score, AUC, sensitivity, specificity and accuracy. RESULTS: The deep learning based BERT model outperforms all other classification methods which were assessed. The model achieved an F1-score of (95 ± 2)% and accuracy of (96 ± 1)% on a dataset of simple reports (n= 2469), and an F1 of (83 ± 7)% with accuracy (93 ± 2)% on a dataset of complex reports (n= 799). CONCLUSION: BERT NLP outperforms traditional ML and rule-base classifiers when applied to Dutch radiology reports in orthopaedic trauma