Revista Jurídica Digital UANDES
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High-temperature electronic devices enabled by hBN-encapsulated graphene
No full textNumerous applications call for electronics capable of operation at high temperatures where conventional Si-based electrical devices fail. In this work, we show that graphene-based devices are capable of performing in an extended temperature range up to 500 °C without noticeable thermally induced degradation when encapsulated by hexagonal boron nitride (hBN). The performance of these devices near the neutrality point is dominated by thermal excitations at elevated temperatures. Non-linearity pronounced in electric field-mediated resistance of the aligned graphene/hBN allowed us to realize heterodyne signal mixing at temperatures comparable to that of the Venus atmosphere (∼460 °C).</p
Material Encounters:Knotting Cultures in Early Modern Peru and Spain
No full textThis article discusses the early modern nexus between feather-work and textiles with a focus on Spanish Peru. Whilst Peruvian feather-work has been defined as pre-Columbian, this article presents new textual, visual, and material evidence that shows its significance in the material culture of colonial Peru, which serves to initiate a broader debate on the dynamics of cultural encounters in the Ibero-American world. I chart the development of craft cultures beyond the moment of the Spanish conquest of the Americas by discussing Peruvian practices of feather manufacturing in relation to the production and usage of textiles in early modern Spain. This approach, I argue, will enable a reconsideration of the dynamics of the Spanish Empire, whose centres and peripheries were linked through circulating objects that constituted a shared material world. In the particular case of feather-work, this was a world that jointly valued the aesthetics of knots and the intricacy of knotting
Learning from Peers’ Eye Movements in the Absence of Expert Guidance: a Proof of Concept Using Laboratory Stock Trading, Eye Tracking, and Machine Learning
No full textExisting research shows that people can improve their decision skills by learning what experts 23 paid attention to when faced with the same problem. However, in domains like financial 24 education, effective instruction requires frequent, personalized feedback given at the point of 25 decision, which makes it time-consuming for experts to provide and thus prohibitively costly. 26 We address this by demonstrating an automated feedback mechanism that allows amateur 27 decision-makers to learn what information to attend to from one another, rather than from an 28 expert. In the first experiment, eye-movements of N=100 subjects were recorded while they 29 repeatedly performed a standard behavioral finance investment task. Consistent with previous 30 studies, we found that a significant proportion of subjects were affected by decision bias. In the 31 second experiment, a different group of N=100 subjects faced the same task but, after each 32 choice, they received individual, machine-learning-generated feedback on whether their pre-33 decision eye-movements resembled those made by Experiment 1 subjects prior to good 34 decisions. As a result, Experiment 2 subjects learned to analyze information similarly to their 35 successful peers, which in turn reduced their decision bias. Furthermore, subjects with low 36 Cognitive Reflection Test scores gained more from the proposed form of process feedback than 37 from standard behavioral feedback based on decision outcomes
The importance of riparian plant orientation in river flow: implications for flow structures and drag
No full textIn a series of high resolution numerical modelling experiments, we incorporate submerged riparian plants into a Computational Fluid Dynamics (CFD) model used to predict flow structures and drag in river flow. Individual plant point clouds were captured using Terrestrial Laser Scanning (TLS) and geometric characteristics quantified. In the first experiment, flow is modelled around three different plant specimens of the same species (Prunus laurocerasus). In the second experiment, the orientation of another specimen is incrementally rotated to modify the flow-facing structure when foliated and defoliated. Each plant introduces a unique disturbance pattern to the normalised downstream velocity field, resulting in spatially heterogeneous and irregularly shaped velocity profiles. The results question the extent to which generalised velocity profiles can be quantified for morphologically complex plants. Incremental changes in plant orientation introduce gradual changes to the downstream velocity field and cause a substantial range in the quantified drag response. Form drag forces are up to an order of magnitude greater for foliated plants compared to defoliated plants, although the mean drag coefficient for defoliated plants is higher (1.52 defoliated; 1.03 foliated). Variation in the drag coefficients are greatest when the plant is defoliated (up to ~210% variation when defoliated, ~80% when foliated)
Unmet Medical Needs in Pulmonary Neuroendocrine (Carcinoid) Neoplasms
No full textPulmonary carcinoids (PCs) display the common features of all well-differentiated neuroendocrine neoplasms (NEN) and are classified as low- and intermediate-grade malignant tumours (i.e., typical and atypical carcinoid, respectively). There is a paucity of randomised studies dedicated to advanced PCs and management principles are drawn from the larger gastroenteropancreatic NEN experience. There is growing evidence that NEN anatomic subgroups have different biology and different responses to treatment and, therefore, should be investigated as separate entities in clinical trials. In this review, we discuss the existing evidence and limitations of tumour classification, diagnostics and staging, prognostication, and treatment in the setting of PC, with focus on unmet medical needs and directions for the future.</p
Priority of International Law vs. Supremacy of the Russian Constitution:Collision of Fundamental Principles
No full textThe combination of constitutional clauses providing for direct effect and supremacy of international law over domestic legislation and clauses according the supreme legal force to the Constitution makes Russia an excellent case study on the ‘duel for supremacy’ between international law and national fundamental principles. Despite a very high status accorded to international human rights norms in the legal system in general, recently, in the process of ‘gaining back sovereignty’, the Russian Constitutional Court confirmed the supremacy of the Russian Constitution over conflicting judgments of international human rights courts and tribunals. This chapter draws on three cases of ‘exceptionally unreconcilable’ incompatibility between international norms interpreted by ECtHR and ‘fundamental basics of the constitutional order’ promoted by the Russian Constitutional Court to illustrate the growing conflict between two of the foundational principles of Russian constitutional law: the principle of priority of international law above domestic legislation and the principle of ‘supreme legal force’ of the Constitution across the whole territory of the state
4D Seismic History Matching Incorporating Unsupervised Learning
No full textThis work focuses on the history matching of reservoirs by coupling 4D seismic data with machine learning techniques. An integrated scheme for the reconstruction of petro-physical properties with a modified Ensemble Smoother with Multiple Data Assimilation (ES-MDA) in a synthetic reservoir is proposed. In this work the permeability field is parametrised with the unsupervised learning algorithm, K-SVD, (signifying the Kmeans with Singular Value Decomposition); in conjunction with the Orthogonal Matching Pursuit (OMP) and also, the seismic attributes in particular acoustic impedance are parametrised with the Discrete Cosine Transform (DCT). The aim of doing all these is to alleviate the ill-possednes of the inversion of historical production data using ES-MDA, by making the optimisation problem less ill-posed. Time-lapse seismic data represents changes in the rock elastic properties caused by reservoir depletion when the water front evolves during the production of the field. The initial realisations are generated using the Multiple-Point Statistics (MPS) algorithm. 200 realisations of static reservoir parameters, which are the permeability fields, are generated based on the well data. The changes of the dynamic parameters, pressure and saturation, and the simulated pressure-production data are generated using a three-phase flow simulator to obtain an ensemble of simulated states. The simulated impedance maps associated with the simulate states for one particular time step, are calculated using the given petro-elastic model. The simulated changes in seismic attribute, in particular impedance maps, and the well production data, give rise to an ensemble of simulated measurements. The true or reference measurements are the seismic attributes and the historical production data, in particular real impedance maps, computed from a prior elastic full-waveform inversion scheme. The DCT algorithm parametrises this seismic attribute by selecting the leading cosine basis of these properties. The K-SVD learned dictionary enforces prior structural information on the permeability field during the ES-MDA inversion step. The updated state vector contains the corrected static and dynamic states of the reservoir after a single iteration of the ES-MDA.We conclude that with these sparse representations on the petro physical properties and the seismic attributes, we obtain better production data matches to the true production data and quantify the propagating water front better with a method absent of these parametrisation techniques.<br/
The development and first validation of a Patient Reported Experience Measure in Chronic Obstructive Pulmonary Disease:PREM-C9
No full textWhat is the key question Living with COPD impacts greatly on a person’s everyday life; including experience of living with COPD and as a recipient of healthcare. No currently available instrument captures this experience. What is the bottom line We have developed and validated a COPD Patient Reported Experience Measure (PREM-C9). A simple and easy to use 9-item unidimensional measure designed to quantify the experience of people living with COPD. Why read on? The article describes the development and validation of the PREM-C9 which will enable measurement of patient experience and help to benchmark across services and tailor healthcare services
Sharpening Up Your Spectra: Broadband Homonuclear Decoupling in HSQC by Real-time Pure Shift Acquisition
No full textStructure elucidation using NMR spectroscopy has become a vital part of the toolkit of modern synthetic chemistry. Characterisation of final products, quality control of production, analysis of complex mixtures in synthetic method development, and structure elucidation of isolated natural products are examples where NMR spectroscopy is a part of daily routine. The two factors that usually limit the applicability of NMR are resolution and sensitivity. The experimental method described in this account, real-time pure shift acquisition, yields heteronuclear correlation spectra such as HSQC that offer significant improvements in both resolution and sensitivity, at negligible cost to the analyst. The advantages that real-time pure shift acquisition enjoys over conventional experiments are discussed, and illustrated with selected examples including carbohydrate and alkaloid mixtures. Advanced data acquisition and processing techniques that reduce experiment time and are easily combined with pure shift NMR methods are also described
Citizen Social Science for More Integrative and Effective Climate Action: A Science-Policy Perspective
No full textGovernments are struggling to limit global temperatures below the 2◦C Paris target with existing climate change policy approaches. This is because conventional climate policies have been predominantly (inter)nationally top-down, which limits citizen agency in driving policy change and influencing citizen behavior. Here we propose elevating Citizen Social Science (CSS) to a new level across governments as an advanced collaborative approach of accelerating climate action and policies that moves beyond conventional citizen science and participatory approaches. Moving beyond the traditional science-policy model of the democratization of science in enablingmore inclusive climate policy change, we present examples of how CSS can potentially transform citizen behavior and enable citizens to become key agents in driving climate policy change. We also discuss the barriers that could impede the implementation of CSS and offer solutions to these. In doing this, we articulate the implications of increased citizen action through CSS in moving forward the broader normative and political program of transdisciplinary and co-productive climate change research and policy