Positive and psycho-pathological aspects between shame and shamelessness

Interpersonal relationships represent an essential aspect of mental wellbeing and social functioning. If all the symptoms contain a relational meaning, shame represents the relational affect par excellence both in terms of its origin and its purpose. This paper aims to highlight the role of shame as an affect inherent in the rhythmic nature of the encounter with the other, as well as the pathological elements of this aspect in both its conscious and unconscious dimensions. There is a heterogeneous quantitative and qualitative declination of shame, or of the defenses against this affect, among the various pathologies. We consider the fundamental needs of belonging and acceptance and the parallel abandonment anguish from various psychoanalytic and philosophical theoretical perspectives and then analyze the link between their dissatisfaction and the origin of shame. We also touch on the different interpretaions of shame based on eastern and western cultural norms. These hypotheses are closely intertwined with the beliefs of classical psychopathology. The role of the body in the encounter with the other and in the experience of shame is also examined. In particular, we study the role of this affect in schizophrenia, depression, eating disorders, and personality disorders

Offloading personal security applications to a secure and trusted network node

The current device-centric protection model against security threats has serious limitations from the final user perspective, among the other the necessity to keep each device updated with the latest security updates and the necessity to replicate all the security polices across all devices. In our model, the protection is decoupled from the users terminals and it is provided through a Trusted Virtual Domain (TVD) instantiated in future edge routers. Each TVD provides unified and homogeneous security for a single user, irrespective of the terminal employed. This paper shows a first prototype implementing this concept through a network element, called Network Edge Device, capable of running the proposed virtualized architecture and making extensive use of SDN technologies, with the aim at providing a uniform security level for the final user

Lung segmentation and characterization in covid-19 patients for assessing pulmonary thromboembolism: An approach based on deep learning and radiomics

The COVID-19 pandemic is inevitably changing the world in a dramatic way, and the role of computed tomography (CT) scans can be pivotal for the prognosis of COVID-19 patients. Since the start of the pandemic, great care has been given to the relationship between interstitial pneumonia caused by the infection and the onset of thromboembolic phenomena. In this preliminary study, we collected n = 20 CT scans from the Polyclinic of Bari, all from patients positive with COVID-19, nine of which developed pulmonary thromboembolism (PTE). For eight CT scans, we obtained masks of the lesions caused by the infection, annotated by expert radiologists; whereas for the other four CT scans, we obtained masks of the lungs (including both healthy parenchyma and lesions). We developed a deep learning-based segmentation model that utilizes convolutional neural networks (CNNs) in order to accurately segment the lung and lesions. By considering the images from publicly available datasets, we also realized a training set composed of 32 CT scans and a validation set of 10 CT scans. The results obtained from the segmentation task are promising, allowing to reach a Dice coefficient higher than 97%, posing the basis for analysis concerning the assessment of PTE onset. We characterized the segmented region in order to individuate radiomic features that can be useful for the prognosis of PTE. Out of 919 extracted radiomic features, we found that 109 present different distributions according to the Mann–Whitney U test with corrected p-values less than 0.01. Lastly, nine uncorrelated features were retained that can be exploited to realize a prognostic signature

Techniques for Complex Analysis of Contemporary Data

Contemporary data objects are typically complex, semi-structured, or unstructured at all. Besides, objects are also related to form a network. In such a situation, data analysis requires not only the traditional attribute-based access but also access based on similarity as well as data mining operations. Though tools for such operations do exist, they usually specialise in operation and are available for specialized data structures supported by specific computer system environments. In contrary, advance analyses are obtained by application of several elementary access operations which in turn requires expert knowledge in multiple areas. In this paper, we propose a unification platform for various data analytical operators specified as a general-purpose analytical system ADAMiSS. An extensible data-mining and similarity-based set of operators over a common versatile data structure allow the recursive application of heterogeneous operations, thus allowing the definition of complex analytical processes, necessary to solve the contemporary analytical tasks. As a proof-of-concept, we present results that were obtained by our prototype implementation on two real-world data collections: the Twitter Higg's boson and the Kosarak datasets

Arginine 200 of Heparin Cofactor II Promotes Intramolecular Interactions of the Acidic Domain: IMPLICATION FOR THROMBIN INHIBITION

Heparin cofactor II (HCII) is presumed to be a physiological inhibitor of the serine proteinase thrombin. The reaction between HCII and thrombin is quite unique, because it involves an unusual HCII-reactive site loop sequence of Leu444-Ser445, requires the presence of glycosaminoglycans for optimal activity and involves a protein-protein interaction besides the reactive site loop-active site interaction characteristic of serine proteinase inhibitor-serine proteinase pairs. Two mutations at a unique HCII residue, Arg200 --> Ala or Glu, were generated by site-directed mutagenesis. The mutations did not alter either HCII binding to heparin-Sepharose or HCII inhibition of thrombin in the presence of heparin or dermatan sulfate, suggesting that Arg200 is not part of the glycosaminoglycan binding site of HCII. In the absence of glycosaminoglycan, there was a significant increase in alpha-thrombin inhibition by the Arg200 mutants as compared with wild type recombinant HCII (wt-rHCII), whereas inhibition rates with chymotrypsin were identical. Inhibition of gammaT-thrombin, which lacks anion-binding exosite 1 ((ABE-1), the region of alpha-thrombin that interacts with the acidic domain of HCII), was significantly reduced compared with alpha-thrombin, but the reduction was more dramatic for the Arg200-rHCII mutants. Hirugen, which binds to ABE-1 of alpha-thrombin, also diminished inhibition of alpha-thrombin by the Arg200-rHCII mutants to nearly wt-rHCII levels. Both Arg200-rHCII mutants had significantly increased ka values as compared with wt-rHCII, whereas the kd rates were unchanged. Collectively, these results suggest that the improved inhibitory activity of the Arg200-rHCII mutants is mediated by enhanced interactions between the acidic domain and ABE-1, resulting in an increased HCII-thrombin association rate

Safety Considerations and Proposed Workflow for Laboratory-Scale Chemical Synthesis by Ball Milling

Chemical reactions that take place in a ball mill and in the absence of a bulk reaction solvent present different safety profiles to stirred solution reactions. Herein, we present and describe steps that a researcher may take to better ensure that they have considered some of the hazards and measures that emerge and minimize the risk to themselves and their colleagues

Massive transcriptome sequencing of human spinal cord tissues provides new insights into motor neuron degeneration in als

ALS is a devastating and debilitating human disease characterized by the progressive death of upper and lower motor neurons. Although much effort has been made to elucidate molecular determinants underlying the onset and progression of the disorder, the causes of ALS remain largely unknown. In the present work, we have deeply sequenced whole transcriptome from spinal cord ventral horns of post-mortem ALS human donors affected by the sporadic form of the disease (which comprises ∼90% of the cases but which is less investigated than the inherited form of the disease). We observe 1160 deregulated genes including 18 miRNAs and show that down regulated genes are mainly of neuronal derivation while up regulated genes have glial origin and tend to be involved in neuroinflammation or cell death. Remarkably, we find strong deregulation of SNAP25 and STX1B at both mRNA and protein levels suggesting impaired synaptic function through SNAP25 reduction as a possible cause of calcium elevation and glutamate excitotoxicity. We also note aberrant alternative splicing but not disrupted RNA editing

Photon-mediated long range coupling of two Andreev level qubits

In a superconducting weak link, the supercurrent is carried by Andreev bound states (ABSs) formed by the phase-coherent reflection of electrons and their time-reversed partners. A single, highly transmissive ABS can serve as an ideal, compact two-level system, due to a potentially large energy difference to the next ABS. While the coherent manipulation of such Andreev levels qubits (ALQs) has been demonstrated, a long-range coupling between two ALQs, necessary for advanced qubit architectures, has not been achieved, yet. Here, we demonstrate a coherent remote coupling between two ALQs, mediated by a microwave photon in a novel superconducting microwave cavity coupler. The latter hosts two modes with different coupling rates to an external port. This allows us to perform fast readout of each qubit using the strongly coupled mode, while the weakly coupled mode is utilized to mediate the coupling between the qubits. When both qubits are tuned into resonance with the latter mode, we find excitation spectra with avoided-crossings, in very good agreement with the Tavis-Cummings model. Based on this model, we identify highly entangled two-qubit states for which the entanglement is mediated over a distance of six millimeters. This work establishes ALQs as compact and scalable solid-state qubits.Comment: 13 pages, 7 figure