Karyomorphological analyses and chromatin characterization by banding techniques in Euphorbia characias L. and E. wulfenii Hoppe (= E. veneta Willd.) (Euphorbiaceae)

Abstract Karyomorphological analysis of Euphorbia characias L. using Giemsa and fluorescent techniques revealed a characteristic C-banding pattern. Intraspecific variation in C-banding pattern was observed within of chromosomal complements of some populations of this species. Using fluorochrome Chromomycin A3 (CMA), E. characias exhibit trait patterns of CMA+ bands in intercalary and telomeric regions. Many bands correspond to Giemsa C-band. After the double staining with chromomycin A3/DAPI numerous chromosomes have showed a distribution of rich pattern in basic G-C (CMA+/DAPI-). The present studies indicate that to determine this characteristic C-banding pattern has intervened a deep restructuring of the karyotype. The karyotypes of E. characias and E. wulfenii were indistinguishable with very similar karyomorphologies and banding patterns, and these data suggest that both entities might be geographical biotypes

Heterochromatin distribution in selected taxa of the 42-chromosomes Orchis s. l. (Orchidaceae)

In six 42-chromosomes taxa belonging to genus Orchis s. l. heterochromatin location and distribution and staining properties were analysed by means of C-banding and of the fluorochromes 4'-6-diamino-2-phenylindole-2HCl (DAPI) and Hoechst 33258. Most species could be distinguished on the basis of heterochromatin amounts and distribution. In the species O. mascula and O. provincialis most DAPI-positive sites did not co-localize with C-bands. DAPI revealed bright fluorescence at telomeric or subtelomeric regions of numerous chromosomes of O. mascula and particularly large/bright blocks at the telomeres of O. provincialis. In O. x penzigiana (Orchis mascula ssp. ichnusae x O. provincialis) overall heterochromatin distribution followed that of the parental species. In Neotinea group all DAPI positive bands co-localize with C-bands, but have different distribution in the taxa analysed. Present and literature data indicate a high level of plasticity of heterochromatin organization in Orchis s. l., and suggest evolutionary pathways in agreement with recent molecular data

The role of pollinator attracting scent in the sexually deceptive orchids Ophrys chestermanii, O. normanii and O. tenthredinifera

Sexual deception of male bees is one of the most remarkable mechanisms of pollination (Ackermann 1986, Proctor & al. 1996). Flowers of the orchid genus Ophrys mimic females of their pollinator species, usually bees and wasps, to attract males, which try to copulate with the flowers. During this so-called “pseudocopulation” the male removes the pollinia and transfers them to another flower to ensure pollination. Apart from visual and tactile cues, floral scent was shown to be most important for eliciting mating behaviour in males (Kullenberg 1961, Schiestl & al. 1999, Ayasse & al. 2003). Pollination in Ophrys is highly specific and usually each Ophrys species attracts only one pollinator species (Paulus & Gack 1990). The high degree of specialization provides the means of reproductive isolation between the intercrossable Ophrys-species (Ehrendorfer 1980). The complex odour-bouquets released by the flowers are species-specific and often consist of more than 100 different chemical compounds (Borg-Karlson & al. 1985, Ayasse 2006). Speciation in Ophrys-orchids may be brought about by changes in the pollinator attracting floral scent. The attraction of a new pollinator may act as a pre-zygotic isolation barrier (Stebbins 1970, Paulus & Gack 1990, Soliva & al. 2001). We investigated three sympatrically occuring Ophrys-species on Sardinia. O. chestermanii and O. normanii are endemic and are both pollinated by males of the bumblebee B. vestalis. O. tenthredinifera is pollinated by Eucera nigrilabris. There are different opinions concerning the taxonomic status of O. normanii. It has been described as an actual hybrid between O. chestermanii and O. tenthredinifera (Wood 1983). Paulus & Gack (1995) suggested that it is an own species, that either has developed from a hybrid between O. chestermanii and O. normanii or that has evolved by radiation from O. tenthredinifera. By conducting behavioural-tests with B. vestalis males, performing gas chromatographic analyses and electrophysiological studies we wanted to identify pollinator attracting scent and to clarify the taxonomic status of O. normanii.Sexualtäuschorchideen der Gattung Ophrys (Orchidaceae) imitieren die Weibchen ihrer Bestäuber in Duft, Form und Farbe. Insektenmännchen versuchen mit dem Labellum der Blüte zu kopulieren und transportieren den Pollen von Blüte zu Blüte, wodurch die Orchidee bestäubt wird. In dieser Arbeit untersuchten wir die Bestäuber anlockenden Duftstoffe der beiden endemisch auf Sardinien vorkommenden Arten O. normanii und O. chestermanii, die beide von Bombus vestalis Männchen (Hymenoptera: Apidae) bestäubt werden und von O. tenthredinifera, die Eucera nigrilabris (Hymenoptera: Apidae) zur Bestäubung anlockt. O. normanii wurde von Wood (1983) als Primärhybride beschrieben. Nach Paulus und Gack (1995) handelt es sich um eine hybridogene Art oder um eine Art die durch Abspaltung von O. tenthredinifera entstanden ist. Das Ziel der Untersuchungen war die Identifizierung Männchen-anlockender Verbindungen. Die Attraktivität der drei Arten für B. vestalis Männchen sollte Hinweise auf den Artstatus von O. normanii geben. In Biotests mit B. vestalis-Männchen lösten Blütenextrakte von O. normanii und O. chestermanii ebenso wie B. vestalis-Weibchen Kopulationsverhalten der Männchen aus, nicht jedoch Extrakte von O. tenthredinifera. Folglich handelt es sich bei O. normanii nicht um einen aktuellen Hybriden zwischen O. chestermanii und O. tenthredinifera. Ein Vergleich der GC-EAD-aktiven Duftbouquets mittels Diskriminanzanalyse ergab große Ähnlichkeiten zwischen O. normanii und O. chestermanii für die Substanzklassen der Ester, Alkohole und Fettsäuren, die daher vermutlich eine Schlüsselfunktion bei der Bestäuberanlockung haben

A Tiny Transformer for Low-Power Arrhythmia Classification on Microcontrollers

Wearable systems for the continuous and real-time monitoring of cardiovascular diseases are becoming widespread and valuable assets in diagnosis and therapy. A promising approach for real-time analysis of the electrocardiographic (ECG) signal and the detection of heart conditions, such as arrhythmia, is represented by the transformer machine learning model. Transformers are powerful models for the classification of time series, although efficient implementation in the wearable domain raises significant design challenges, to combine adequate accuracy and a suitable complexity. In this work, we present a tiny transformer model for the analysis of the ECG signal, requiring only 6k parameters and reaching 98.97% accuracy in the recognition of the 5 most common arrhythmia classes from the MIT-BIH Arrhythmia database, assessed considering 8-bit integer inference as required for efficient execution on low-power microcontroller-based devices. We explored an augmentation-based training approach for improving the robustness against electrode motion artifacts noise, resulting in a worst-case post-deployment performance assessment of 98.36% accuracy. Suitability for wearable monitoring solutions is finally demonstrated through efficient deployment on the parallel ultra-low-power GAP9 processor, where inference execution requires 4.28ms and 0.09mJ

Advances in chromosomal studies in Neottieae (Orchidaceae): constitutive heterochromatin, chromosomal rearrangements and speciation.

Abstract — In this work, we describe a karyomorphological study on three taxa of the tribe Neottieae (Orchidaceae). Epipactis aspromontana and E. schubertiorum are characterized by a chromosome complement of 2n = 2× = 38. Significant differences in heterochromatin distribution were found between them. Similarities in the karyotype structure and C-banding of E. schubertiorum and E. helleborine group have been observed. A specimen of E. aspromontana showed a triploid chromosome number. The meiosis are characterized by univalent, bivalent and trivalent forms and in some somatic metaphase cells has been possible to observe a series of aneuploid numbers with 46, 47, 48, 49, 50, 51, 52 and 53 chromosomes. The largest differences can be emphasized between the Epipactis species and Neottia nidusavis, mainly in the the karyomorphology and heterochromatin distributions. In Neottia nidusavis the evolution process seems to be determined by reversing Robertsonian mutations

Adaptive cognitive sensor nodes for the internet of medical things

The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical trials and healthcare procedures. It relies on novel, very accurate and compact sensing devices, network and communication infrastructures, opening previously unmatched possibilities of implementing data collection and continuous patient monitoring. Nevertheless, to fully exploit the potential of IoMT, some steps forward are needed. First, the edge-computing paradigm must be added to the picture. A certain level of near-sensor processing has to be enabled, to improve the scalability, portability, reliability and responsiveness of the IoMT nodes. Second, novel, increasingly accurate data analysis algorithms, such as those based on artificial intelligence and deep learning, must be exploited. To reach these objectives, designers, and programmers of IoMT nodes, have to face challenging optimization tasks, in order to execute fairly complex computing processes on low-power wearable and portable processing systems, with tight power and battery lifetime budgets. In this thesis, the implementation on resource-constrained computing platforms of a cognitive data analysis algorithm based on a convolutional neural network was explored. The treatment of cardiovascular disease and fitness tracking were chosen as use cases within the IoMT context to validate our approach. To minimize power consumption, an adaptivity layer has been added, the latter dynamically manages the hardware and software configuration of the device to adapt it at runtime to the required operating mode. The experimental results show that adapting the node setup to the workload at runtime can save up to 60% power consumption. The optimized and quantized neural network reaches an accuracy value higher than 97% for arrhythmia disorders detection and more than 97% for detecting some specific physical exercises on a wobble board

Runtime Adaptive IoMT Node on Multi-Core Processor Platform

The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical trials and healthcare procedures. Thanks to innovative technologies, latest-generation communication networks, and state-of-the-art portable devices, IoTM opens up new scenarios for data collection and continuous patient monitoring. Two very important aspects should be considered to make the most of this paradigm. For the first aspect, moving the processing task from the cloud to the edge leads to several advantages, such as responsiveness, portability, scalability, and reliability of the sensor node. For the second aspect, in order to increase the accuracy of the system, state-of-the-art cognitive algorithms based on artificial intelligence and deep learning must be integrated. Sensory nodes often need to be battery powered and need to remain active for a long time without a different power source. Therefore, one of the challenges to be addressed during the design and development of IoMT devices concerns energy optimization. Our work proposes an implementation of cognitive data analysis based on deep learning techniques on resource-constrained computing platform. To handle power efficiency, we introduced a component called Adaptive runtime Manager (ADAM). This component takes care of reconfiguring the hardware and software of the device dynamically during the execution, in order to better adapt it to the workload and the required operating mode. To test the high computational load on a multi-core system, the Orlando prototype board by STMicroelectronics, cognitive analysis of Electrocardiogram (ECG) traces have been adopted, considering single-channel and six-channel simultaneous cases. Experimental results show that by managing the sensory node configuration at runtime, energy savings of at least 15% can be achieved