Can Blockchain Really Remove All Intermediaries? A Multiple-Case Study in Different Industries

Blockchain is a disruptive and innovative technology. How will the blockchain technology disrupt different fields? Blockchain technology has disrupted the existing processes and will improve the efficiency of many operations. With improved efficiency, will blockchain remove all intermediaries in the chains? Further, will all positions of the intermediaries agree to be replaced by blockchain? Many intermediaries have demonstrated their liberal attitudes toward embracing blockchain technology. What are the intended purposes behind the ambition of the intermediaries? The research is still in progress and will adopt a multiple-case study and summarize the research intentions into a cross analysis table. The table will briefly show the role of users and indicate whether intermediaries are necessary in the ecosystems or they transfer into new roles and create new business models after deploying the blockchain technology

Effects of crossed states on photoluminescence excitation spectroscopy of InAs quantum dots

In this report, the influence of the intrinsic transitions between bound-to-delocalized states (crossed states or quasicontinuous density of electron-hole states) on photoluminescence excitation (PLE) spectra of InAs quantum dots (QDs) was investigated. The InAs QDs were different in size, shape, and number of bound states. Results from the PLE spectroscopy at low temperature and under a high magnetic field (up to 14 T) were compared. Our findings show that the profile of the PLE resonances associated with the bound transitions disintegrated and broadened. This was attributed to the coupling of the localized QD excited states to the crossed states and scattering of longitudinal acoustical (LA) phonons. The degree of spectral linewidth broadening was larger for the excited state in smaller QDs because of the higher crossed joint density of states and scattering rate

From antiferromagnetism to d-wave superconductivity in the 2D t-J model

We have found that the two dimensional t-J model, for the physical parameter range J/t = 0.4 reproduces the main experimental qualitative features of High-Tc copper oxide superconductors: d-wave superconducting correlations are strongly enhanced upon small doping and clear evidence of off diagonal long range order is found at the optimal doping \delta ~ 0.15. On the other hand antiferromagnetic long range order, clearly present at zero hole doping, is suppressed at small hole density with clear absence of antiferromagnetism at \delta >~ 0.1.Comment: 4 pages, 5 figure

Measurement of Cosmic-ray Muon-induced Spallation Neutrons in the Aberdeen Tunnel Underground Laboratory

AbstractMuon-induced neutrons are one of the major backgrounds to various underground experiments, such as dark matter searches, low-energy neutrino oscillation experiments and neutrino-less double beta-decay experiments. Previous experiments on the underground production rate of muon-induced neutrons were mostly carried out either at shallow sites or at very deep sites. The Aberdeen Tunnel experiment aims to measure the neutron production rate at a moderate depth of 611 meters water equivalent. Our apparatus comprises of six layers of plastic-scintillator hodoscopes for tracking the incident cosmic-ray muons, and 760 L of gadolinium-doped liquid-scintillator for both neutron production and detection targets. In this paper, we describe the design and the performance of the apparatus. The preliminary result on the measurement of neutron production rate is also presented

Active Galactic Nuclei at the Crossroads of Astrophysics

Over the last five decades, AGN studies have produced a number of spectacular examples of synergies and multifaceted approaches in astrophysics. The field of AGN research now spans the entire spectral range and covers more than twelve orders of magnitude in the spatial and temporal domains. The next generation of astrophysical facilities will open up new possibilities for AGN studies, especially in the areas of high-resolution and high-fidelity imaging and spectroscopy of nuclear regions in the X-ray, optical, and radio bands. These studies will address in detail a number of critical issues in AGN research such as processes in the immediate vicinity of supermassive black holes, physical conditions of broad-line and narrow-line regions, formation and evolution of accretion disks and relativistic outflows, and the connection between nuclear activity and galaxy evolution.Comment: 16 pages, 5 figures; review contribution; "Exploring the Cosmic Frontier: Astrophysical Instruments for the 21st Century", ESO Astrophysical Symposia Serie

Software quality management improvement through mentoring: an exploratory study from GSD projects

Proceeding of: OTM 2011 Workshops: Confederated InternationalWorkshops and Posters: EI2N+NSF ICE, ICSP+INBAST, ISDE, ORM, OTMA, SWWS+MONET+SeDeS, and VADER 2011, Hersonissos, Crete, Greece, October 17-21, 2011Software Quality Management (SQM) is a set of processes and procedures designed to assure the quality of software artifacts along with their development process. In an environment in which software development is evolving to a globalization, SQM is seen as one of its challenges. Global Software Development is a way to develop software across nations, continents, cultures and time zones. The aim of this paper is to detect if mentoring, one of the lead personnel development tools, can improve SQM of projects developed under GSD. The results obtained in the study reveal that the influence of mentoring on SQM is just temperate

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

A Web-Based Agent Framework for Collaborative Design-Build Communication

The Internet connects the globe as a whole and at the same time pushes the competition increasing dramatically. Multidiscipline and distributed collaborative design-build in architecture, engineering and construction (A/E/C) companies can gain foster competitive advantage, improved designs, and more effective management of construction facilities. However collaboration can often fail, since it involves different professions who often hold different goals and also one-off organizations also build obstacles to collaboration. This paper presents a web-based agent framework to support communication, to facilitate shared understanding amongst the participants and to inspire teamwork. This paper proposes a multi-agent social interaction framework as the communication model of design-build projects. The conceptual framework emp hasizes process-centric learning and the creation of group agreements within design-build collaborative activities, which help facilitate conflict migration. In addition, based upon web agent technology, this communication framework providing an intelligence distribution opportunity for the for the A/C/E industry to introduce a new and innovative paradigm of collaborative design