Holomorphic extension of smooth CR-mappings between real-analytic and real-algebraic CR-manifolds

We establish results on holomorphic extension of CR-mappings of class $C^\infty$ between a real-analytic CR-submanifold of \C^N and a real-algebraic CR-submanifold of \C^{N'}

Quantitative Intensity Harmonization of Dopamine Transporter SPECT Images Using Gamma Mixture Models

PURPOSE: Differences in site, device, and/or settings may cause large variations in the intensity profile of dopamine transporter (DAT) single-photon emission computed tomography (SPECT) images. However, the current standard to evaluate these images, the striatal binding ratio (SBR), does not efficiently account for this heterogeneity and the assessment can be unequivalent across distinct acquisition pipelines. In this work, we present a voxel-based automated approach to intensity normalize such type of data that improves on cross-session interpretation. PROCEDURES: The normalization method consists of a reparametrization of the voxel values based on the cumulative density function (CDF) of a Gamma distribution modeling the specific region intensity. The harmonization ability was tested in 1342 SPECT images from the PPMI repository, acquired with 7 distinct gamma camera models and at 24 different sites. We compared the striatal quantification across distinct cameras for raw intensities, SBR values, and after applying the Gamma CDF (GDCF) harmonization. As a proof-of-concept, we evaluated the impact of GCDF normalization in a classification task between controls and Parkinson disease patients. RESULTS: Raw striatal intensities and SBR values presented significant differences across distinct camera models. We demonstrate that GCDF normalization efficiently alleviated these differences in striatal quantification and with values constrained to a fixed interval [0, 1]. Also, our method allowed a fully automated image assessment that provided maximal classification ability, given by an area under the curve (AUC) of AUC = 0.94 when used mean regional variables and AUC = 0.98 when used voxel-based variables. CONCLUSION: The GCDF normalization method is useful to standardize the intensity of DAT SPECT images in an automated fashion and enables the development of unbiased algorithms using multicenter datasets. This method may constitute a key pre-processing step in the analysis of this type of images.Instituto de Salud Carlos III FI14/00497 MV15/00034Fondo Europeo de Desarrollo Regional FI14/00497 MV15/00034ISCIII-FEDER PI16/01575Wellcome Trust UK Strategic Award 098369/Z/12/ZNetherland Organization for Scientific Research NWO-Vidi 864-12-00

Editorial: Special Issue on Recent Advances in Computer and Communication Networks Technology

Dramatic improvements in networking technologies over the past couple of decades have yielded substantial increase in computer and communication capabilities. A number of new networking technologies such as middleware, wireless mesh networks anWiMAX, global IPv6, new generation multimedia, and modern network security started taking off. To date, some of these development efforts have mainly focused on protocol standardization, product development, and network operations besides being research targets. We believe that the accumulated experience in new networking practices now provide interesting research opportunities, not only for the broader network research community, but also for those who have been involved in these advancement developments

Packet-Switching Network with Symmetrical Topology and Method of Routing Packets

A mesh network for routing a plurality of data segments therethrough, each of the data segments containing address information. The network includes: a first, second, and third switch element each having a respective external input for routing data segments into the network and a respective external output for routing data segments out of the network; a bi-directional coupling between each of the switch elements; and a first controller for interrogating the address information of each of the data segments inbound into the first switch element. The exit pathway for any inbound data segment received by a switch element is selected according to the address information of that data segment, and if a contention exists for the exit pathway, further according to a priority designator of that data segment. The first external output, if free and if the first switch element is the outbound destination for that data segment, will be selected as the exit pathway, otherwise one of said bi-directional couplings in communication with the first switch element will be selected as the exit pathway. Also, an associated method and computer executable program code on a computer readable storage medium for routing a plurality of data segments through a mesh network

EDCOPA : Enhancing DCOPA Protocol by Exploring New Criteria for Improved Clustering

The Internet of Things (IoT) has significantly expanded the connectivity of smart devices, emphasizing the crucial importance of clustering for optimizing device energy, particularly in data communication. The DCOPA protocol is presented as a distributed clustering protocol for data communication in IoT based on Wireless Sensor Networks (WSN). The DCOPA protocol uses competition among network nodes, based on the multicriteria aggregation approach. Residual energy and Distance from a Base Station (DistBS) criteria are used to elect Cluster-Heads (CHs). DCOPA operates in two distinct phases: a Setup phase dedicated to CH designation and a Steady-state phase that includes specific periods for normal nodes and CHs. In this article, we propose an enhancement to the DCOPA protocol called EDCOPA, in which we focus on integrating two additional parameters that can influence and optimize the selection of CHs for increased energy efficiency and a better network lifetime. This improvement preserves the distributed and multicriteria aspects of the protocol. The number of times a given node has assumed the role of CH, as well as the energy consumed in the previous round, have been incorporated into the objective function. Simulation results demonstrate that this integration has significantly improved the network’s lifetime and the energy consumption of both nodes and the entire network. "© {Mir, et al. | ACM} {2024}. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in {Proceedings of the 7th International Conference on Future Networks and Distributed Systems (ICFNDS '23)}, http://dx.doi.org/10.1145/3644713.36448}.

The Limitations of Equivalent Linear Site Response Analysis Considering Soil Nonlinearity Properties

Seismic site effect has been a major issue in the field of earthquake engineering due to the large local amplification of the seismic motion. This paper presents the importance of an appropriate soil behavior model to simulate earthquake site response and gives a critical overview of the field of site response analysis. Some of the well known site response analysis methods are summarized and discussed. The objective of this paper is to investigate the influences of nonlinearity on the site response analysis by means of a more precise numerical model. In this respect, site responses of four different types of one layered soil deposit, based on various shear wave velocities, with the assumption of linear and rigid base bedrock, were analyzed by using the equivalent linear and fully nonlinear approaches. Nonlinear analyses’ results were compared with those of the linear method and the similarities and differences are discussed. As a result, it is concluded that, in the case of nonlinearity of soil under strong ground motions, 1-D equivalent linear modeling overestimates the amplification patterns in terms of absolute amplification level, and cannot correctly account for resonant frequencies and hysteric soil behavior. Hence more practical and appropriate numerical techniques for ground response analysis should be surveyed